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samchon/typia

# Typia  [](https://github.com/samchon/typia/blob/master/LICENSE) [](https://www.npmjs.com/package/typia) [](https://www.npmjs.com/package/typia) [](https://github.com/samchon/typia/actions?query=workflow%3Abuild) [](https://typia.io/docs/) ```typescript // RUNTIME VALIDATORS export function is<T>(input: unknown): input is T; // returns boolean export function assert<T>(input: unknown): T; // throws TypeGuardError export function assertGuard<T>(input: unknown): asserts input is T; export function validate<T>(input: unknown): IValidation<T>; // detailed // JSON FUNCTIONS export namespace json { export function application<T>(): IJsonApplication; // JSON schema export function assertParse<T>(input: string): T; // type safe parser export function assertStringify<T>(input: T): string; // safe and faster } // PROTOCOL BUFFER export namespace protobuf { export function message<T>(): string; // Protocol Buffer message export function assertDecode<T>(buffer: Uint8Array): T; // safe decoder export function assertEncode<T>(input: T): Uint8Array; // safe encoder } // RANDOM GENERATOR export function random<T>(g?: Partial<IRandomGenerator>): T; ``` Typia is a transformer library supporting below features: - Super-fast Runtime Validators - Enhanced JSON functions - Protocol Buffer encoder and decoder - Random data generator > [!NOTE] > > - **Only one line** required, with pure TypeScript type > - Runtime validator is **20,000x faster** than `class-validator` > - JSON serialization is **200x faster** than `class-transformer` ## Sponsors Thanks for your support. Your donation encourages `typia` development. [](https://opencollective.com/typia) ## Playground You can experience how typia works by [playground website](https://typia.io/playground): - 💻 https://typia.io/playground ## Guide Documents Check out the document in the [website](https://typia.io/docs/): ### 🏠 Home - [Introduction](https://typia.io/docs/) - [Setup](https://typia.io/docs/setup/) - [Pure TypeScript](https://typia.io/docs/pure/) ### 📖 Features - Runtime Validators - [`assert()` function](https://typia.io/docs/validators/assert/) - [`is()` function](https://typia.io/docs/validators/is/) - [`validate()` function](https://typia.io/docs/validators/validate/) - [Functional Module](https://typia.io/docs/validators/functional) - [Special Tags](https://typia.io/docs/validators/tags/) - Enhanced JSON - [JSON Schema](https://typia.io/docs/json/schema) - [`stringify()` functions](https://typia.io/docs/json/stringify/) - [`parse()` functions](https://typia.io/docs/json/parse/) - Protocol Buffer - [Message Schema](https://typia.io/docs/protobuf/message) - [`decode()` functions](https://typia.io/docs/protobuf/decode/) - [`encode()` functions](https://typia.io/docs/protobuf/encode/) - [Random Generator](https://typia.io/docs/random/) - [Miscellaneous](https://typia.io/docs/misc/) ### 🔗 Appendix - [API Documents](https://typia.io/api) - Utillization Cases - [NestJS](https://typia.io/docs/utilization/nestjs/) - [Prisma](https://typia.io/docs/utilization/prisma/) - [tRPC](https://typia.io/docs/utilization/trpc/) - [⇲ Benchmark Result](https://github.com/samchon/typia/tree/master/benchmark/results/11th%20Gen%20Intel(R)%20Core(TM)%20i5-1135G7%20%40%202.40GHz) - [⇲ `dev.to` Articles](https://dev.to/samchon/series/22474)

Super-fast/easy runtime validations and serializations through transformation

json,stringify,typescript,fast,ajv,checker,generator,runtime,transform,validator

breezy-weather/breezy-weather

<div align="center"> <br /> <img src="app/src/main/res/mipmap-xxxhdpi/ic_launcher_round.webp" alt="Logo" /> </div> <h1 align="center">Breezy Weather</h1> <br /> <div align="center"> <img alt="API 21+" src="https://img.shields.io/badge/Api%2021+-50f270?logo=android&logoColor=black&style=for-the-badge"/> <img alt="Kotlin" src="https://img.shields.io/badge/Kotlin-a503fc?logo=kotlin&logoColor=white&style=for-the-badge"/> <img alt="Jetpack Compose" src="https://img.shields.io/static/v1?style=for-the-badge&message=Jetpack+Compose&color=4285F4&logo=Jetpack+Compose&logoColor=FFFFFF&label="/> <img alt="Material You" src="https://custom-icon-badges.demolab.com/badge/material%20you-lightblue?style=for-the-badge&logoColor=333&logo=material-you"/> <br /> <img src="https://img.shields.io/github/license/breezy-weather/breezy-weather?style=for-the-badge" alt="License LGPL-3.0" /> <img src="https://img.shields.io/github/languages/code-size/breezy-weather/breezy-weather?style=for-the-badge" alt="GitHub code size in bytes" /> <br /><br /> <a href="https://github.com/breezy-weather/breezy-weather/releases/latest"> <img src="https://img.shields.io/github/v/release/breezy-weather/breezy-weather?color=purple&include_prereleases&logo=github&style=for-the-badge" alt="Download from GitHub" /> </a> <a href="https://apt.izzysoft.de/fdroid/index/apk/org.breezyweather/"> <img src="https://img.shields.io/endpoint?url=https://apt.izzysoft.de/fdroid/api/v1/shield/org.breezyweather?color=purple&include_prereleases&logo=FDROID&style=for-the-badge" alt="Download from IzzyOnDroid repo" /> </a> <a href="https://f-droid.org/packages/org.breezyweather/"> <img src="https://img.shields.io/f-droid/v/org.breezyweather?color=purple&include_prereleases&logo=FDROID&style=for-the-badge" alt="Download from F-Droid default repo" /> </a> </div> <h4 align="center">Breezy Weather is a weather app with a strong focus on design, with a simple, clean UX, smooth animations, and Material Design all over, plus lots of customizability.</h4> <div align="center"> # Download <a href="https://github.com/breezy-weather/breezy-weather/releases"> <img src="https://user-images.githubusercontent.com/69304392/148696068-0cfea65d-b18f-4685-82b5-329a330b1c0d.png" alt="Get it on GitHub" align="center" height="80" /></a> <a href="https://github.com/breezy-weather/breezy-weather/blob/main/INSTALL.md#obtainium"> <img src="https://github.com/ImranR98/Obtainium/blob/main/assets/graphics/badge_obtainium.png" alt="Get it on Obtainium" align="center" height="54" /> </a> <a href="https://github.com/breezy-weather/breezy-weather/blob/main/INSTALL.md#f-droid-client"> <img src="https://f-droid.org/badge/get-it-on.png" alt="Get it on F-Droid" align="center" height="80" /></a> </div> <div align="center"> <a href="https://github.com/breezy-weather/breezy-weather/blob/main/INSTALL.md"><strong>All installation methods</strong></a> </div> <hr /> <div align="center"> <img src="docs/FullHomepageScreenshot.png" alt="" style="width: 300px" /> </div> # Features - Weather data - Daily and hourly forecasts up to 16 days - Temperature - Air quality - Wind - UV index - Precipitation - Feels like temperature - Hourly forecasts - Humidity / Dew point - Pressure - Cloud cover - Visibility - Precipitation in the next hour - Air quality - Pollen & Mold - Ephemeris (Sun & Moon) - Severe weather and precipitation alerts - Real-time weather conditions - Temperature - Feels like - Wind - UV index - Humidity - Dew point - Atmospheric pressure - Visibility - Cloud cover - Ceiling - <details><summary>Multiple weather sources (<a href="docs/SOURCES.md">comparison</a>)</summary> - Open-Meteo - AccuWeather - MET Norway - Pirate Weather (no API key provided) - HERE (no API key provided) - Météo France - Danmarks Meteorologiske Institut (DMI) - Mixed China sources - National Weather Service (NWS) - Bright Sky (DWD) - Environment and Climate Change Canada - Central Weather Administration (CMA), Taiwan - Israel Meteorological Service (IMS) - SMHI - MET Éireann - World Meteorological Organization (WMO) Severe Weather - Recosanté - ATMO AuRA </details> - Large selection of home screen widgets for at-a-glance information - Live wallpaper - Custom icon packs - [Geometric Weather icon packs](https://github.com/breezy-weather/breezy-weather-icon-packs/blob/main/README.md) - Chronus Weather icon packs - Automatic dark mode - Looking for radar? [Check out this document](docs/RADAR.md) - <details><summary>Free and Open Source</summary> - No proprietary blobs/dependencies (versions 5.0.0-alpha and later) - Releases generated by GitHub actions, guaranteeing it matches the source code - Fully works with Open-Meteo (FOSS source) </details> - <details><summary>Privacy-friendly</summary> - No personal data collected by the app ([link to app privacy policy](https://github.com/breezy-weather/breezy-weather/blob/main/PRIVACY.md)) - Multiple sources are available, with links to their privacy policies for transparency - Current location is optional and not added by default - If using current location, an IP location service can be used instead of GPS to send less accurate coordinates to weather source - No trackers/automatic crash reporters </details> # Help * [Frequently Asked Questions / Help](HELP.md) * [Homepage explanations](docs/HOMEPAGE.md) * [Weather sources comparison](docs/SOURCES.md) # Contribute Pull requests are welcome. You can have a look at [issues opened to contributions](https://github.com/breezy-weather/breezy-weather/issues?q=is%3Aissue+is%3Aopen+label%3A%22Open+to+contributions%22). For other changes, please open an issue first to discuss what you would like to change. * [Contribution guide (includes a guide to create a new weather source)](CONTRIBUTE.md) ## Features currently being worked on by a contributor - [#14](https://github.com/breezy-weather/breezy-weather/issues/14), [#252](https://github.com/breezy-weather/breezy-weather/issues/252) - New 24-hour fitting charts ## Features lacking an active contributor - [#10](https://github.com/breezy-weather/breezy-weather/issues/10) - “Add location” page needs a new design, in the spirit of Google Maps where you can select location points on the map, or search manually - No mockup done yet - [#937](https://github.com/breezy-weather/breezy-weather/issues/937) - Widget overhaul (prerequisite for any new widget improvement) - Some mockups were done but no one is working on it anymore ## Features that will not be implemented - Paid-only sources, too limited free-tier, or free-tier that requires privacy-invasive information (credit card info, phone number, etc) - Adding `standard` flavor or non-free sources to the F-Droid default repo: please use the `standard` flavor from a different store/source instead - Changes to the [background updates process](docs/UPDATES.md), including but not limited: options for refreshing less than every 30 minutes, every time you open the app, every time you tap on widget, every time you unlock your phone - “Circular sky” interface: please set a fixed background per location instead - Publish to Google Play Store: please [check alternatives](INSTALL.md) - Allow different flavors to be installed in parallel - Implement features that are no longer available in latest Android versions - Backport features/fixes from latest Android versions to older Android versions - Donations: if you have extra money to spare, consider [donating to Open-Meteo](https://github.com/sponsors/open-meteo) to support infrastructure costs and future developments (we currently lack a libre and gratis worldwide alternative for the following features: [Reverse geocoding](https://github.com/open-meteo/geocoding-api/issues/6), [Alerts](https://github.com/open-meteo/open-meteo/issues/351), [Normals](https://github.com/open-meteo/open-meteo/issues/361)) # Translations Translation is done externally [on Weblate](https://hosted.weblate.org/projects/breezy-weather/breezy-weather-android/#information). Please read carefully project instructions if you want to help. [](https://hosted.weblate.org/projects/breezy-weather/breezy-weather-android/#information) English (and regional variants) and French translations are maintained by repo maintainers, but they are open to proofreading/improvements. You will need to make a pull request, as we didn’t find a way to make these languages in suggestion-only mode in Weblate (let us know if you find anything). # Contact us * If you’d like to report a bug or suggest a new feature, GitHub discussions or issues are best for organization. * We’ve also created a Matrix/Element space with a number of different channels for more general discussion: [`#breezy-weather-space:matrix.org`](https://matrix.to/#/#breezy-weather-space:matrix.org). * If you are not comfortable writing a GitHub discussion/issue in English, you can ask on the channel if someone can help you in your language. * We also have a dedicated help channel in French: [`#breezy-weather-francais:matrix.org`](https://matrix.to/#/#breezy-weather-francais:matrix.org) * If you’d prefer a direct channel link instead of a space link, here’s the main Breezy Weather Matrix channel: [`#breezy-weather:matrix.org`](https://matrix.to/#/#breezy-weather:matrix.org) # License * [GNU Lesser General Public License v3.0](/LICENSE) * This License does not grant any rights in the trademarks, service marks, or logos of any Contributor. * Misrepresentation of the origin of that material is prohibited, and modified versions of such material must be marked in reasonable ways as different from the original version. When creating a fork, remember to: - Respect the project’s LICENSE - Avoid confusion with Breezy Weather app: - Change the app name - Change the app icon - Avoid installation conflicts: - Change the `applicationId` in [`build.gradle.kts`](https://github.com/breezy-weather/breezy-weather/blob/main/app/build.gradle.kts#L19)

A Material Design Weather Application

SteamDeckHomebrew/decky-loader

<h1 align="center"> <a name="logo" href="https://deckbrew.xyz/"><img src="https://deckbrew.xyz/static/icon-45ca1f5aea376a9ad37e92db906f283e.png" alt="Deckbrew logo" width="200"></a> <br> Decky Loader <br> <a name="download button" href="https://github.com/SteamDeckHomebrew/decky-installer/releases/latest/download/decky_installer.desktop"><img src="./docs/images/download_button.svg" alt="Download decky" width="350px" style="padding-top: 15px;"></a> </h1> <p align="center"> <a href="https://github.com/SteamDeckHomebrew/decky-loader/releases"><img src="https://img.shields.io/github/downloads/SteamDeckHomebrew/decky-loader/total" /></a> <a href="https://github.com/SteamDeckHomebrew/decky-loader/stargazers"><img src="https://img.shields.io/github/stars/SteamDeckHomebrew/decky-loader" /></a> <a href="https://github.com/SteamDeckHomebrew/decky-loader/commits/main"><img src="https://img.shields.io/github/last-commit/SteamDeckHomebrew/decky-loader.svg" /></a> <a href="https://weblate.werwolv.net/engage/decky/"><img src="https://weblate.werwolv.net/widgets/decky/-/decky/svg-badge.svg" alt="Translation status" /></a> <a href="https://github.com/SteamDeckHomebrew/decky-loader/blob/main/LICENSE"><img src="https://img.shields.io/github/license/SteamDeckHomebrew/decky-loader" /></a> <a href="https://deckbrew.xyz/discord"><img src="https://img.shields.io/discord/960281551428522045?color=%235865F2&label=discord" /></a> <br> <br> <img src="https://media.discordapp.net/attachments/966017112244125756/1012466063893610506/main.jpg" alt="Decky screenshot" width="80%"> </p> ## 📖 About Decky Loader is a homebrew plugin launcher for the Steam Deck. It can be used to [stylize your menus](https://github.com/suchmememanyskill/SDH-CssLoader), [change system sounds](https://github.com/EMERALD0874/SDH-AudioLoader), [adjust your screen saturation](https://github.com/libvibrant/vibrantDeck), [change additional system settings](https://github.com/NGnius/PowerTools), and [more](https://plugins.deckbrew.xyz/). For more information about Decky Loader as well as documentation and development tools, please visit [our wiki](https://deckbrew.xyz). ### 🎨 Features 🧹 Clean injecting and loading of multiple plugins. 🔒 Stays installed between system updates and reboots. 🔗 Allows two-way communication between plugins and the loader. 🐍 Supports Python functions run from TypeScript React. 🌐 Allows plugins to make fetch calls that bypass CORS completely. ### 🤔 Common Issues - Syncthing may use port 8080 on Steam Deck, which Decky Loader needs to function. If you are using Syncthing as a service, please change its port to something else. - 8384 is the recommended port for Syncthing. - If you are using any software that uses port 1337 or 8080, please change its port to something else or uninstall it. - Sometimes Decky will disappear on SteamOS updates. This can easily be fixed by just re-running the installer and installing the stable branch again. If this doesn't work, try installing the prerelease instead. If that doesn't work, then [check the existing issues](https://github.com/SteamDeckHomebrew/decky-loader/issues) and if there isn't one then you can [file a new issue](https://github.com/SteamDeckHomebrew/decky-loader/issues/new?assignees=&labels=bug&template=bug_report.yml&title=%5BBUG%5D+%3Ctitle%3E). ## 💾 Installation - This installation can be done without an admin/sudo password set. 1. Prepare a mouse and keyboard if possible. - Keyboards and mice can be connected to the Steam Deck via USB-C or Bluetooth. - Many Bluetooth keyboard and mouse apps are available for iOS and Android. (KDE connect is preinstalled on the steam deck) - The Steam Link app is available on [Windows](https://media.steampowered.com/steamlink/windows/latest/SteamLink.zip), [macOS](https://apps.apple.com/us/app/steam-link/id1246969117), and [Linux](https://flathub.org/apps/details/com.valvesoftware.SteamLink). It works well as a remote desktop substitute. - If you have no other options, use the right trackpad as a mouse and press <img src="./docs/images/light/steam.svg#gh-dark-mode-only" height=16><img src="./docs/images/dark/steam.svg#gh-light-mode-only" height=16>+<img src="./docs/images/light/x.svg#gh-dark-mode-only" height=16><img src="./docs/images/dark/x.svg#gh-light-mode-only" height=16> to open the on-screen keyboard as needed. 1. Press the <img src="./docs/images/light/steam.svg#gh-dark-mode-only" height=16><img src="./docs/images/dark/steam.svg#gh-light-mode-only" height=16> button and open the Power menu. 1. Select "Switch to Desktop". 1. Navigate to this Github page on a browser of your choice. 1. Download the [installer file](https://github.com/SteamDeckHomebrew/decky-installer/releases/latest/download/decky_installer.desktop). (If using firefox, it will be named `decky_installer.desktop.download`. Rename it to `decky_installer.desktop` before running it) 1. Drag the file onto your desktop and double click it to run it. 1. Either type your admin password or allow Decky to temporarily set your admin password to `Decky!` (this password will be removed after the installer finishes) 1. Choose the version of Decky Loader you want to install. - **Latest Release** Intended for most users. This is the latest stable version of Decky Loader. - **Latest Pre-Release** Intended for plugin developers. Pre-releases are unlikely to be fully stable but contain the latest changes. For more information on plugin development, please consult [the wiki page](https://wiki.deckbrew.xyz/en/loader-dev/development). 1. Open the Return to Gaming Mode shortcut on your desktop. - There is also a fast install for those who can use Konsole. Run `curl -L https://github.com/SteamDeckHomebrew/decky-installer/releases/latest/download/install_release.sh | sh` and type your password when prompted. ### 👋 Uninstallation We are sorry to see you go! If you are considering uninstalling because you are having issues, please consider [opening an issue](https://github.com/SteamDeckHomebrew/decky-loader/issues) or [joining our Discord](https://deckbrew.xyz/discord) so we can help you and other users. 1. Press the <img src="./docs/images/light/steam.svg#gh-dark-mode-only" height=16><img src="./docs/images/dark/steam.svg#gh-light-mode-only" height=16> button and open the Power menu. 1. Select "Switch to Desktop". 1. Run the installer file again, and select `uninstall decky loader`. - There is also a fast uninstall for those who can use Konsole. Run `curl -L https://github.com/SteamDeckHomebrew/decky-installer/releases/latest/download/uninstall.sh | sh` and type your password when prompted. ## 🚀 Getting Started Now that you have Decky Loader installed, you can start using plugins. Each plugin is maintained by a different developer and has its own uses, but most follow a general structure outlined below. ### 📦 Plugins 1. Press the <img src="./docs/images/light/qam.svg#gh-dark-mode-only" height=16><img src="./docs/images/dark/qam.svg#gh-light-mode-only" height=16> button and navigate to the <img src="./docs/images/light/plug.svg#gh-dark-mode-only" height=16><img src="./docs/images/dark/plug.svg#gh-light-mode-only" height=16> icon. This is the Decky menu used for interacting with plugins and the loader itself. 1. Select the <img src="./docs/images/light/store.svg#gh-dark-mode-only" height=16><img src="./docs/images/dark/store.svg#gh-light-mode-only" height=16> icon to open the Plugins Browser. This is where you can find and install plugins. - You can also install from URL in the Settings menu. We do not recommend installing plugins from untrusted sources. 1. To install a plugin, select the "Install" button on the plugin you want. You can also select a version from a dropdown menu, but this is not recommended. 1. To update, uninstall, and reload plugins, navigate to the Decky menu and select the <img src="./docs/images/light/gear.svg#gh-dark-mode-only" height=16><img src="./docs/images/dark/gear.svg#gh-light-mode-only" height=16> icon. - Keep in mind that uninstalling a plugin will only remove its plugin files, not any other files it may have created. ### 🛠️ Plugin Development There is no complete plugin development documentation yet. However a good starting point is the [plugin template repository](https://github.com/SteamDeckHomebrew/decky-plugin-template). Consider [joining our Discord](https://deckbrew.xyz/discord) if you have any questions. ### 🤝 Contributing Please consult [the wiki page regarding development](https://wiki.deckbrew.xyz/en/loader-dev/development) for more information on installing development versions of Decky Loader. You can also install the Steam Deck UI on a Windows or Linux computer for testing by following [this YouTube guide](https://youtu.be/1IAbZte8e7E?t=112). 1. Clone the repository using the latest commit to main before starting your PR. 1. In your clone of the repository, run these commands. ```bash cd frontend pnpm i pnpm run build ``` 1. If you are modifying the UI, these commands will need to be run before deploying the changes to your Steam Deck. 1. Use the VS Code tasks or `deck.sh` script to deploy your changes to your Steam Deck to test them. 1. You will be testing your changes with the Python script version. You will need to build, deploy, and reload each time. ⚠️ If you are recieving build errors due to an out of date library, you should run this command inside of your repository. ```bash pnpm update decky-frontend-lib --latest ``` Source control and deploying plugins are left to each respective contributor for the cloned repos in order to keep dependencies up to date. ## 📜 Credits The original idea for the plugin loader concept is based on the work of [marios8543's Steam Deck UI Inject project](https://github.com/marios8543/steamdeck-ui-inject).

A plugin loader for the Steam Deck.

steam,steamdeck,plugins,steamos,python

MrGlockenspiel/activate-linux

# activate-linux [](https://www.gnu.org/licenses/gpl-3.0) The "Activate Windows" watermark ported to Linux with cairo in C "Science isn't about WHY. It's about WHY NOT. Why is so much of our science dangerous? Why not marry safe science if you love it so much. In fact, why not invent a special safety door that won't hit you on the butt on the way out, because you are fired." — Cave Johnson (Portal 2) > Read [ARGS.md](ARGS.md) for information about command line arguments. ## Building Note that the executable's name depends on the target platform. You can use `make install` to install and `make uninstall` to remove it. ### Xmake I've been experimenting with using [Xmake](https://xmake.io/#/) for building instead of make, you can test this by installing it and running ```console xmake ``` Please leave feedback to improve this if you want ### *nix: ```console make ``` ### Windows (using [MSYS2](https://msys2.org)): Replace `gcc` with `clang`, if you want. But then don't forget to start proper shortcut `MSYS2 CLANG64`. ```console pacman -S --noconfirm git make pkgconf pactoys pacboy -S --noconfirm gcc:p git clone https://github.com/MrGlockenspiel/activate-linux cd activate-linux export backends=gdi make ``` ## Linux ### Dependencies This project depends on: - [`libcairo2-dev`](https://cairographics.org) - [`libxi-dev`](https://gitlab.freedesktop.org/xorg/lib/libxi) - [`libx11-dev`](https://gitlab.freedesktop.org/xorg/lib/libx11) - `x11proto-core-dev` - [`x11proto-dev`](https://gitlab.freedesktop.org/xorg/proto/x11proto) - [`libxt-dev`](https://gitlab.freedesktop.org/xorg/lib/libxt) - [`libxext-dev`](https://gitlab.freedesktop.org/xorg/lib/libxext) - [`libxfixes-dev`](https://gitlab.freedesktop.org/xorg/lib/libxfixes) - [`libxinerama-dev`](https://gitlab.freedesktop.org/xorg/lib/libxinerama) - [`libxrandr-dev`](https://gitlab.freedesktop.org/xorg/lib/libxrandr) - [`libwayland-dev`](https://gitlab.freedesktop.org/wayland/wayland) - [`wayland-protocols`](https://gitlab.freedesktop.org/wayland/wayland-protocols) Optional dependencies: - [`libconfig-dev`](https://hyperrealm.github.io/libconfig) Those packages may be installed (in Debian-based distros) like this: ```console sudo apt install libconfig-dev libcairo2-dev libxi-dev libx11-dev x11proto-core-dev x11proto-dev \ libxt-dev libxext-dev libxfixes-dev libxinerama-dev libxrandr-dev libwayland-dev wayland-protocols ``` ### Installing #### Ubuntu @eddelbuettel runs a PPA with activate linux in it, so it can be installed with: ```console sudo add-apt-repository ppa:edd/misc sudo apt update sudo apt install activate-linux ``` #### Arch Linux This project is in the AUR under [activate-linux-git](https://aur.archlinux.org/packages/activate-linux-git). Install/uninstall it using your favorite AUR helper. #### Nix (NixOS) This repository is a flake. Run it using `nix run "github:MrGlockenspiel/activate-linux"`. #### Gentoo @Plexvola maintains an ebuild for activate-linux and can be installed with the following ```console eselect repository enable vaacus emerge --sync vaacus emerge -av activate-linux ``` #### openSUSE / SLE The package is built for various releases on [OBS](https://build.opensuse.org/package/show/home:tschmitz:activate-linux/activate-linux). Installation instructions for your specific distribution are available here: **[https://software.opensuse.org/download.html?project=home%3Atschmitz%3Aactivate-linux&package=activate-linux](https://software.opensuse.org/download.html?project=home%3Atschmitz%3Aactivate-linux&package=activate-linux)** Here are the Tumbleweed instructions: ```console zypper addrepo https://download.opensuse.org/repositories/home:tschmitz:activate-linux/openSUSE_Tumbleweed/home:tschmitz:activate-linux.repo zypper refresh zypper install activate-linux ``` #### Fedora The package is built for various releases on [OBS](https://build.opensuse.org/package/show/home:tschmitz:activate-linux/activate-linux). Installation instructions for your specific distribution are available here: **[https://software.opensuse.org/download.html?project=home%3Atschmitz%3Aactivate-linux&package=activate-linux](https://software.opensuse.org/download.html?project=home%3Atschmitz%3Aactivate-linux&package=activate-linux)** Here are the Fedora Rawhide instructions: ```console dnf config-manager --add-repo https://download.opensuse.org/repositories/home:tschmitz:activate-linux/Fedora_Rawhide/home:tschmitz:activate-linux.repo dnf install activate-linux ``` ## Windows ### Scoop You can install it on the [Extras](https://github.com/ScoopInstaller/Extras) bucket: ```powershell scoop bucket add extras # Ensure bucket is added first scoop install activate-linux ``` ## MacOS (Horrific) ### Dependencies Use MacPorts to install the following, then build normally. - `xorg-server` - `cairo` - `xorg-libXinerama` Alternatively, you can use [this](https://github.com/Lakr233/ActivateMac) project instead because it actually works properly. ## Example: 

The "Activate Windows" watermark ported to Linux

jassics/security-study-plan

 A Practical Study Plan to become a successful cybersecurity engineer based on roles like Pentest, AppSec, Cloud Security, DevSecOps, and so on with free/paid resources, tools, and concepts to excel. **It will cover but not limited to:** **_Done_** 1. [Common Skills for Security Study Plan](common-skills-study-plan.md) 2. [AWS Security Study Plan](aws-security-study-plan.md) 3. [GCP Security Study Plan](gcp-security-study-plan.md) 4. [Web Penetration Testing Study Plan](web-pentest-study-plan.md) 5. [Application Security Testing Plan](application-security-study-plan.md) 6. [API Security Study Plan](api-security-study-plan.md) **_ToDo_** 1. [Azure Security Study Plan](azure-security-study-plan.md) 2. [DevSecOps Study Plan](devsecops-study-plan.md) - _In Progress_ 3. [Docker Security Study Plan](docker-security-study-plan.md) 4. [Kubernetes Security Study Plan](kubernetes-security-study-plan.md) 5. [Network Security Study Plan](network-security-study-plan.md) 6. [Cryptography Study Plan](cryptography-study-plan.md) 7. [Threat Modeling Study Plan](threat-modeling-study-plan.md) 8. [Software Supply Chain Security Study Plan](software-supply-chain-security-study-plan.md) 9. [Secure Code Review Study Plan](secure-code-review-study-plan.md) 10. [Secure Software Development Lifecycle Study Plan](secure-software-development-lifecycle-study-plan.md) 11. [Security Architecture Study Plan](security-architecture-study-plan.md) I got the idea of creating this repo after seeing [coding-interview-security](https://github.com/jwasham/coding-interview-university) as it echoes the journey that I went through to get into the full-time security role. >I created this study plan to help people who are looking for guidance and help to plan and prepare for a job-specific skill set. If you study 3-4 hours per day for the next 6 months, you can clear high rewarding jobs provided you do lots of hands-on and go through each necessary topic/concept more than thrice and you are from a tech background. This worked in my case. > >Please note that some topics would be common for any listed security roles. Check [common-skills-study-plan](common-skills-study-plan.md) > >I will try my level best to add study references from the beginners' perspective but will have even advanced level coverage too. > >All the best for your security journey! ## What is it? This is to give a study plan to prepare for a specific role. It is of course multiple months of hard work and dedication which need a proper roadmap. Hence, this repo would be a point source for all your study plans. **Prerequisites:** - Ready to devote time daily - from a tech background, it can take a little more time but still possible to make a career in cybersecurity. - Never give up attitude - Hacker Mindset - Ready to explore on your own **Please note** that there are many job titles under each of these study plans, but I am keeping a generic study plan so that you can tick out whichever you already know. This way you would know how much you know and how much you still need to learn to grow up the ladder. Check out the YouTube video on ["Cybersecurity Roadmap for Beginners"](https://www.youtube.com/watch?v=-qklv1WXdmo) and ["How to make a career in Cybersecurity"](https://www.youtube.com/watch?v=TPoI1vwcdxo&list=PLRTsCutScZnzN66sG_X9GyJFt-kkKoksi&index=5). Then, you will have a better idea of why to use it and how to use this study plan for your preparation. ## Why use it? If you want to work as a security engineer, these are the skills/topics/concepts you need to know and learn thoroughly.. When I started learning security concepts, everything was new to me, and I wasted lots of time on Google searches, YouTube videos, articles, etc. to figure out what was required and what was not. I am still learning as cybersecurity is evolving, so we must. My target is to keep this repo up to date, of course with the help of wonderful learners like you. It takes time to be confident in some skills, treat it as a long plan. It may take months or sometimes a year too, but keep yourself motivated and don't stop learning. However, If you are familiar with a lot of topics already it will take less time for you. ## How to use it? Everything below is like an outline, and you can tick out the items that you have already covered or know in order from top to bottom. I'm using [GitHub's special markdown flavor](https://guides.github.com/features/mastering-markdown/#GitHub-flavored-markdown), including task lists to track progress. As a Cybersecurity professional, I would [recommend you to learn git](https://www.udemy.com/course/git-basics-for-everyone) and clone this repo for your learning purposes. ## Update your resume Before updating or creating a resume for a job, please check: 1. What job title you are trying for? 2. Do you fall in that experience range? 3. Check what skills it is looking for. 4. Check for job location or is it remote(work from home/anywhere)? Now, prepare the resume based on the above info and your skill sets. Try to be honest here. See, if you can finish your resume in 1-2 pages. Check the 1-page resume below links: 1. [One page resume template from zety.com](https://zety.com/blog/one-page-resume-templates) 2. [Easy Resume](https://www.easyresume.io/) 3. [Various Security Resume sample from qwikresume.com](https://www.qwikresume.com/resume-samples/security-engineer/) 4. [How To Write a Security Engineer Resume (With Example)](https://www.indeed.com/career-advice/resumes-cover-letters/security-engineer-resume) 5. [Network Security Engineer Sample](https://enhancv.com/resume-examples/network-security-engineer/) 6. [Cloud Security Engineer Resume](https://www.hireitpeople.com/resume-database/68-network-and-systems-administrators-resumes/138883-cloud-security-engineer-resume) 7. [AWS Security Engineer Resume](https://www.livecareer.com/resume-search/r/aws-solutions-architect-cloud-security-engineer-dfe9b3bd87d04311bcb32119da547271) 8. [Lead DevSecOps Resume Example](https://www.livecareer.com/resume-search/r/lead-devsecops-engineer-53a226a3bebc4987af0dea7ce0c6740b) 9. [Sr. DevSecOps Engineer Resume Example](https://www.livecareer.com/resume-search/r/sr-devsecops-engineer-81ad059140cf43fda69e77d614d65685) 10. [Penetration Tester Consultant Resume Sample](https://www.livecareer.com/resume-search/r/penetration-tester-consultant-25926a15cbac482883f8d00d26da0d86) ## Finding the right job You might see hundreds of job openings, some may be from your dream company. But, once you closely look it doesn't match with your skills. It seems the job title was a little misleading and more of a generic description. Security researchers or security analysts are just a few examples. So, finetune and narrow down the job search with the below websites but not limited to: 1. Which job title you are targeting? 2. What skills do you have vs what skills JD requires? 3. Years of experience (range) is matching? Now search or subscribe to below job portal below: 1. Linkedin. Yes, nowadays it's job alert setting does a better job in finding the right job for you. 2. Naukri.com (Mostly in Asian countries) 3. indeed.com 4. monster.com 5. instahyre.com 6. cutshort.io 7. [Null Jobs Community](https://jobs.null.community/) 8. [Cybersecurity Jobs](https://www.cybersecurityjobs.com/) 9. [Interactive way to find jobs, skills, salary, etc.](https://www.cyberseek.org/pathway.html) ## Interview Preparation You can start preparing for the job interview once you have solid knowledge as per the checklist for the given role(s). There are a few common security questions that you should have a look at: 1. [Cybersecurity Interview Questions and Answers - Youtube](https://www.youtube.com/watch?v=q5pQ_YtJWpA) 2. [Cybersecurity Questions and Answers by Springboard](https://www.springboard.com/blog/cybersecurity/25-cybersecurity-job-interview-questions-and-answers/) 3. [Cybersecurity Questions and Answers form indeed](https://in.indeed.com/career-advice/interviewing/cyber-security-interview-questions) 4. [100+ Q&A for Cybersecurity domain from guru99](https://www.guru99.com/cyber-security-interview-questions.html) ### Common Interview Questions * How do you keep updated yourself in the security domain? * What would you do typically on the first day of your job? * What personal achievement are you most proud of? * What was your last tough vulnerability that you found? * Why should we hire you? * What did you learn in the last 6 months and how was it relevant to your career/project? * Where do you see after 5 years of working with this organization? You can check [some common answers from here](https://ayedot.com/119/MiniBlog/General-Interview-Questions-and-their-Answers-for-Tech-Jobs) ## Let's contribute and grow this repo together **Want to contribute? Please [fork the repo](https://github.com/jassics/security-study-plan/fork) and [send PR for review](https://github.com/jassics/security-study-plan/pulls)**

Complete Practical Study Plan to become a successful cybersecurity engineer based on roles like Pentest, AppSec, Cloud Security, DevSecOps and so on...

aws-security,study-guide,study-plan,appsec,appsec-tutorials,azure-security,devsecops-university,gcp-security,pentesting,application-security

Atri-Labs/atrilabs-engine

# Atri framework ### Seamless no-code and code in one tool <div align="center"> <a href="https://github.com/Atri-Labs/atrilabs-engine/issues" target="_blank"><img src="https://img.shields.io/github/issues/Atri-Labs/atrilabs-engine?color=FEF08A" alt="Open issues"></a> <a href="https://github.com/Atri-Labs/atrilabs-engine/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22" target="_blank"><img src="https://img.shields.io/github/issues/Atri-Labs/atrilabs-engine/good%20first%20issue?color=FEF08A" alt="Good first issues"></a> <a href="https://github.com/Atri-Labs/atrilabs-engine/discussions" target="_blank"><img src="https://img.shields.io/github/discussions/Atri-Labs/atrilabs-engine?color=DB2777" alt="Discussions"></a> </br> <a href="https://pepy.tech/badge/atri" target="_blank"><img src="https://pepy.tech/badge/atri" alt="Downloads"></a>  <a href="https://www.youtube.com/channel/UC1uR2Q5x_8olWS_Y4PdK1Bw"> <img src="https://img.shields.io/youtube/channel/views/UC1uR2Q5x_8olWS_Y4PdK1Bw?label=YouTube&style=social" alt="Watch on YouTube"> </a> <a href="https://www.ycombinator.com/companies/atri-labs"><img src="https://img.shields.io/website?color=%23f26522&down_message=Y%20Combinator&label=Backed&logo=ycombinator&style=flat-square&up_message=Y%20Combinator&url=https%3A%2F%2Fwww.ycombinator.com"></a> <h3 align="center"> <a href="https://atrilabs.com">Website</a> <span> | </span> <a href="https://docs.atrilabs.com/next/highlights">Docs</a> <span> | </span> <a href="https://join.slack.com/t/atricommunity/shared_invite/zt-1otyguhy8-P4OQQRWFWcMUsKk7yp0FHQ">Community Slack</a> <span> | </span> <a href="https://www.youtube.com/channel/UC1uR2Q5x_8olWS_Y4PdK1Bw">YouTube</a> <span> | </span> <a href="https://www.linkedin.com/company/atri-labs">LinkedIn</a> <span> | </span> <a href="https://twitter.com/atrilabs">Twitter</a> </h3> </div> ---------------------------------------- > **📈 Trending as the #1 TypeScript repository in GitHub!** [Source](readme-assets/top_ts_repo.png) > **🎉 Ranked as a top 10 TypeScript repository in GitHub in Nov and Dec.** [Source](https://user-images.githubusercontent.com/102641692/204081761-06d0f525-004e-4cb9-8c1c-4c7bc0271b10.png) > **🔥 Listed as a "Hot JS Tool" for the week of Nov 6.** [Source](https://jstools.substack.com/p/hot-js-tools-45-612-november-2022) Web framework that helps developers in creating drag-and-drop zones for no-code development in their applications [](https://twitter.com/intent/tweet?text=Check%20out%20this%20new%20full-stack%20web%20development%20framework:%20&url=https://github.com/Atri-Labs/atrilabs-engine&via=atrilabs&hashtags=webframework,fullstack,react,python) - Frontend development: Use our powerful visual builder to create frontend or write React code - Deployment support: Use our CLI to deploy at your platform of choice such as AWS, GitHub Pages, etc. or Atri cloud ## Watch the 1 min introduction video to Atri framework 👇 <div align="center"> [](https://www.youtube.com/watch?v=mdPZUab2IlQ&t=52s) </div> If you like our project, please support us by giving us **a star ⭐!** ## What can I build using this framework? Atri is a general purpose framework that can be used to build everything from e-commerce websites to internal apps. <div align="center"> [](https://www.youtube.com/watch?v=mdPZUab2IlQ&t=52s) </div> ### Apps built using Atri [Venture Copilot](https://www.venturecopilot.app/) The static instances of the web apps created using Atri have been deployed at the below URLs: [Restaurant website](https://atri-apps.github.io/restaurant_website) | [Sportswear website](https://github.com/Atri-Apps/travel_website) | [Personal website](https://github.com/Atri-Apps/portfolio-templates) | [Ecommerce app](https://atri-apps.github.io/full_stack_ecommerce_website) | [Personal blog](https://atri-apps.github.io/personal_blog/) | [Data app](https://atri-apps.github.io/review_tabular_data) | [Custom background (ML) app](https://atri-apps.github.io/custom_background/) Find more examples at Atri-Apps (https://github.com/orgs/Atri-Apps/repositories). ## How is Atri framework different from other web development frameworks? 1. Atri framework is not just limited to the JavaScript world. You can use this framework with many languages such as Python, NodeJS (upcoming), etc. 2. Atri framework comes with a suite of productivity tools such as visual editor, asset management tools, etc. that significantly reduce development time from months to hours. 3. Using Atri framework, developers do not need to write and document REST APIs. Instead, they rely upon the object model which acts as a single source of truth. This also has other benefits as well such as reducing compliance breaches. Thus, Atri framework is extending the definition of full-stack to include non web developers in the development and maintenance of an app. ## Getting Started Please follow the [docs here](https://docs.atrilabs.com/next/highlights). ## How to contribute? Thanks for your interest in contributing to the Atri framework. 💖 You can contribute in any or all of the following ways: - [ask a question](https://github.com/Atri-Labs/atrilabs-engine/discussions) - [submit a bug report](https://github.com/Atri-Labs/atrilabs-engine/issues/new/choose) - [request a new feature](https://github.com/Atri-Labs/atrilabs-engine/issues/new/choose) - [suggest ways to improve the developer experience of an existing feature](https://github.com/Atri-Labs/atrilabs-engine/issues/new/choose) - [submit a documentation report](https://github.com/Atri-Labs/atrilabs-engine/issues/new/choose) - [propose an Atri app](https://github.com/Atri-Labs/atrilabs-engine/issues/new/choose) - [create an Atri App](https://github.com/orgs/Atri-Apps/repositories) and share it with the [community](https://github.com/Atri-Labs/atrilabs-engine/discussions/categories/show-and-tell) - contribute to the Atri framework: You can get started with ["good first issues"](https://github.com/Atri-Labs/atrilabs-engine/issues?q=is%3Aissue+is%3Aopen+label%3A%22good+first+issue%22) which are suitable for newcomers. Please refer to our [contributing guidelines](CONTRIBUTING.md) for details. Besides, please make sure you adhere to the [code of conduct](CODE_OF_CONDUCT.md). If you make any contribution to our project (code or no-code; check the [vast list of contribution types](https://allcontributors.org/docs/en/emoji-key)), you will be featured in the table below 👇 ## Contributors 🎉 <!-- ALL-CONTRIBUTORS-BADGE:START - Do not remove or modify this section --> [](#contributors-) <!-- ALL-CONTRIBUTORS-BADGE:END --> We are grateful to these wonderful people who contributed to Atri framework. 🙏 ([emoji key](https://allcontributors.org/docs/en/emoji-key)): <!-- ALL-CONTRIBUTORS-LIST:START - Do not remove or modify this section --> <!-- prettier-ignore-start --> <!-- markdownlint-disable --> <table> <tbody> <tr> <td align="center"><a href="https://github.com/cruxcode"><img src="https://avatars.githubusercontent.com/u/30747788?v=4?s=100" width="100px;" alt="Shyam Swaroop"/><br />_{<b>Shyam Swaroop</b>}</a><br /><a href="https://github.com/Atri-Labs/atrilabs-engine/commits?author=cruxcode" title="Code">💻</a> <a href="https://github.com/Atri-Labs/atrilabs-engine/commits?author=cruxcode" title="Documentation">📖</a> <a href="#infra-cruxcode" title="Infrastructure (Hosting, Build-Tools, etc)">🚇</a> <a href="#projectManagement-cruxcode" title="Project Management">📆</a> <a href="#maintenance-cruxcode" title="Maintenance">🚧</a> <a href="#mentoring-cruxcode" title="Mentoring">🧑‍🏫</a> <a href="https://github.com/Atri-Labs/atrilabs-engine/pulls?q=is%3Apr+reviewed-by%3Acruxcode" title="Reviewed Pull Requests">👀</a> <a href="https://github.com/Atri-Labs/atrilabs-engine/commits?author=cruxcode" title="Tests">⚠️</a> <a href="#video-cruxcode" title="Videos">📹</a></td> <td align="center"><a href="https://www.linkedin.com/in/darshitac/"><img src="https://avatars.githubusercontent.com/u/102641692?v=4?s=100" width="100px;" alt="Darshita Chaturvedi"/><br />_{<b>Darshita Chaturvedi</b>}</a><br /><a href="https://github.com/Atri-Labs/atrilabs-engine/commits?author=darshitac11" title="Code">💻</a> <a href="#infra-darshitac11" title="Infrastructure (Hosting, Build-Tools, etc)">🚇</a> <a href="#maintenance-darshitac11" title="Maintenance">🚧</a> <a href="#mentoring-darshitac11" title="Mentoring">🧑‍🏫</a> <a href="#projectManagement-darshitac11" title="Project Management">📆</a> <a href="https://github.com/Atri-Labs/atrilabs-engine/pulls?q=is%3Apr+reviewed-by%3Adarshitac11" title="Reviewed Pull Requests">👀</a> <a href="https://github.com/Atri-Labs/atrilabs-engine/commits?author=darshitac11" title="Tests">⚠️</a></td> <td align="center"><a href="https://github.com/adityaxpique"><img src="https://avatars.githubusercontent.com/u/56078748?v=4?s=100" width="100px;" alt="Aditya Kumar Singh"/><br />_{<b>Aditya Kumar Singh</b>}</a><br /><a href="https://github.com/Atri-Labs/atrilabs-engine/commits?author=adityaxpique" title="Code">💻</a> <a href="#maintenance-adityaxpique" title="Maintenance">🚧</a> <a href="#mentoring-adityaxpique" title="Mentoring">🧑‍🏫</a></td> <td align="center"><a href="https://www.melvindavis.me/"><img src="https://avatars.githubusercontent.com/u/7814072?v=4?s=100" width="100px;" alt="Melvin Davis"/><br />_{<b>Melvin Davis</b>}</a><br /><a href="https://github.com/Atri-Labs/atrilabs-engine/commits?author=melvinodsa" title="Code">💻</a></td> <td align="center"><a href="https://github.com/jonathanalvares9009"><img src="https://avatars.githubusercontent.com/u/74007627?v=4?s=100" width="100px;" alt="Jonathan Elroy Alvares"/><br />_{<b>Jonathan Elroy Alvares</b>}</a><br /><a href="https://github.com/Atri-Labs/atrilabs-engine/commits?author=jonathanalvares9009" title="Code">💻</a></td> <td align="center"><a href="https://github.com/Supratim30"><img src="https://avatars.githubusercontent.com/u/49454292?v=4?s=100" width="100px;" alt="Supratim Majumder"/><br />_{<b>Supratim Majumder</b>}</a><br /><a href="https://github.com/Atri-Labs/atrilabs-engine/commits?author=Supratim30" title="Code">💻</a></td> <td align="center"><a href="https://github.com/MuminAhmadKhan"><img src="https://avatars.githubusercontent.com/u/63766734?v=4?s=100" width="100px;" alt="MuminAhmadKhan"/><br />_{<b>MuminAhmadKhan</b>}</a><br /><a href="https://github.com/Atri-Labs/atrilabs-engine/commits?author=MuminAhmadKhan" title="Code">💻</a></td> </tr> <tr> <td align="center"><a href="https://github.com/Rishabh2012329"><img src="https://avatars.githubusercontent.com/u/57484495?v=4?s=100" width="100px;" alt="Rishabh Baid"/><br />_{<b>Rishabh Baid</b>}</a><br /><a href="https://github.com/Atri-Labs/atrilabs-engine/commits?author=Rishabh2012329" title="Code">💻</a></td> <td align="center"><a href="https://github.com/Shivam8452"><img src="https://avatars.githubusercontent.com/u/97235825?v=4?s=100" width="100px;" alt="Shivam8452"/><br />_{<b>Shivam8452</b>}</a><br /><a href="https://github.com/Atri-Labs/atrilabs-engine/commits?author=Shivam8452" title="Code">💻</a></td> <td align="center"><a href="https://lucidmach.vercel.app/"><img src="https://avatars.githubusercontent.com/u/39376102?v=4?s=100" width="100px;" alt="Nukala Suraj"/><br />_{<b>Nukala Suraj</b>}</a><br /><a href="https://github.com/Atri-Labs/atrilabs-engine/commits?author=LucidMach" title="Code">💻</a></td> <td align="center"><a href="https://github.com/SurajPhulara"><img src="https://avatars.githubusercontent.com/u/73554410?v=4?s=100" width="100px;" alt="SURAJ PHULARA"/><br />_{<b>SURAJ PHULARA</b>}</a><br /><a href="https://github.com/Atri-Labs/atrilabs-engine/commits?author=SurajPhulara" title="Code">💻</a></td> <td align="center"><a href="https://github.com/harishfalco"><img src="https://avatars.githubusercontent.com/u/62054469?v=4?s=100" width="100px;" alt="harishfalco"/><br />_{<b>harishfalco</b>}</a><br /><a href="https://github.com/Atri-Labs/atrilabs-engine/commits?author=harishfalco" title="Code">💻</a></td> <td align="center"><a href="https://github.com/Tej-git-212"><img src="https://avatars.githubusercontent.com/u/69730029?v=4?s=100" width="100px;" alt="Tejaswini AVSV"/><br />_{<b>Tejaswini AVSV</b>}</a><br /><a href="https://github.com/Atri-Labs/atrilabs-engine/commits?author=Tej-git-212" title="Code">💻</a></td> <td align="center"><a href="https://github.com/ayushi0809"><img src="https://avatars.githubusercontent.com/u/42436449?v=4?s=100" width="100px;" alt="ayushi0809"/><br />_{<b>ayushi0809</b>}</a><br /><a href="#userTesting-ayushi0809" title="User Testing">📓</a></td> </tr> <tr> <td align="center"><a href="https://github.com/Potato-29"><img src="https://avatars.githubusercontent.com/u/53327808?v=4?s=100" width="100px;" alt="Prayas Ahir"/><br />_{<b>Prayas Ahir</b>}</a><br /><a href="#userTesting-Potato-29" title="User Testing">📓</a></td> <td align="center"><a href="https://github.com/corners2wall"><img src="https://avatars.githubusercontent.com/u/110557519?v=4?s=100" width="100px;" alt="Artem"/><br />_<b>Artem</b></a><br /><a href="#research-corners2wall" title="Research">🔬</a></td> <td align="center"><a href="https://github.com/RamAIbot"><img src="https://avatars.githubusercontent.com/u/54279782?v=4?s=100" width="100px;" alt="Ramachandran SS"/><br />_{<b>Ramachandran SS</b>}</a><br /><a href="#userTesting-RamAIbot" title="User Testing">📓</a></td> <td align="center"><a href="https://github.com/RohitKakade"><img src="https://avatars.githubusercontent.com/u/89378775?v=4?s=100" width="100px;" alt="RohitKakade"/><br />_{<b>RohitKakade</b>}</a><br /><a href="#userTesting-RohitKakade" title="User Testing">📓</a></td> <td align="center"><a href="https://github.com/JadhavSankalp7"><img src="https://avatars.githubusercontent.com/u/68782251?v=4?s=100" width="100px;" alt="JadhavSankalp7"/><br />_{<b>JadhavSankalp7</b>}</a><br /><a href="#userTesting-JadhavSankalp7" title="User Testing">📓</a> <a href="https://github.com/Atri-Labs/atrilabs-engine/commits?author=JadhavSankalp7" title="Code">💻</a></td> <td align="center"><a href="https://github.com/harikishantk"><img src="https://avatars.githubusercontent.com/u/58771359?v=4?s=100" width="100px;" alt="Harikishan TK"/><br />_{<b>Harikishan TK</b>}</a><br /><a href="#userTesting-harikishantk" title="User Testing">📓</a></td> <td align="center"><a href="https://github.com/Sayak-singha"><img src="https://avatars.githubusercontent.com/u/69098567?v=4?s=100" width="100px;" alt="Sayak Singha"/><br />_{<b>Sayak Singha</b>}</a><br /><a href="#userTesting-Sayak-singha" title="User Testing">📓</a></td> </tr> <tr> <td align="center"><a href="https://github.com/PansaraPriyanshi"><img src="https://avatars.githubusercontent.com/u/72371836?v=4?s=100" width="100px;" alt="PansaraPriyanshi"/><br />_{<b>PansaraPriyanshi</b>}</a><br /><a href="#userTesting-PansaraPriyanshi" title="User Testing">📓</a></td> <td align="center"><a href="https://github.com/shashtag"><img src="https://avatars.githubusercontent.com/u/54642876?v=4?s=100" width="100px;" alt="Shashwat Gupta"/><br />_{<b>Shashwat Gupta</b>}</a><br /><a href="#userTesting-shashtag" title="User Testing">📓</a></td> <td align="center"><a href="https://aman10.web.app/"><img src="https://avatars.githubusercontent.com/u/76661001?v=4?s=100" width="100px;" alt="Aman Kr. Poddar"/><br />_{<b>Aman Kr. Poddar</b>}</a><br /><a href="#userTesting-Am10aN16" title="User Testing">📓</a></td> <td align="center"><a href="https://github.com/Mahe9041"><img src="https://avatars.githubusercontent.com/u/84344925?v=4?s=100" width="100px;" alt="Mahe9041"/><br />_{<b>Mahe9041</b>}</a><br /><a href="#userTesting-Mahe9041" title="User Testing">📓</a></td> <td align="center"><a href="https://github.com/sahilsuman933"><img src="https://avatars.githubusercontent.com/u/34382211?v=4?s=100" width="100px;" alt="Sahil Suman"/><br />_{<b>Sahil Suman</b>}</a><br /><a href="#userTesting-sahilsuman933" title="User Testing">📓</a></td> <td align="center"><a href="https://github.com/vamsirevada"><img src="https://avatars.githubusercontent.com/u/38239734?v=4?s=100" width="100px;" alt="Vamsi Revada"/><br />_{<b>Vamsi Revada</b>}</a><br /><a href="#userTesting-vamsirevada" title="User Testing">📓</a></td> <td align="center"><a href="https://www.linkedin.com/in/ayush-kumar-shukla/"><img src="https://avatars.githubusercontent.com/u/68881799?v=4?s=100" width="100px;" alt="Ayush Kumar Shukla"/><br />_{<b>Ayush Kumar Shukla</b>}</a><br /><a href="#userTesting-Ayush-k-Shukla" title="User Testing">📓</a></td> </tr> <tr> <td align="center"><a href="https://github.com/Nikhil-Singh-Parmar"><img src="https://avatars.githubusercontent.com/u/72020334?v=4?s=100" width="100px;" alt="Nikhil Singh Parmar"/><br />_{<b>Nikhil Singh Parmar</b>}</a><br /><a href="#userTesting-Nikhil-Singh-Parmar" title="User Testing">📓</a></td> <td align="center"><a href="https://github.com/aryans1319"><img src="https://avatars.githubusercontent.com/u/72180855?v=4?s=100" width="100px;" alt="Aryan Shaw"/><br />_{<b>Aryan Shaw</b>}</a><br /><a href="#userTesting-aryans1319" title="User Testing">📓</a></td> <td align="center"><a href="https://sanjayz.netlify.app/"><img src="https://avatars.githubusercontent.com/u/102804548?v=4?s=100" width="100px;" alt="Sanjay"/><br />_{<b>Sanjay</b>}</a><br /><a href="https://github.com/Atri-Labs/atrilabs-engine/issues?q=author%3Asanjayk0508" title="Bug reports">🐛</a></td> <td align="center"><a href="https://www.linkedin.com/in/anurag-singh-a428a61ab/"><img src="https://avatars.githubusercontent.com/u/63997049?v=4?s=100" width="100px;" alt="Anurag Singh"/><br />_{<b>Anurag Singh</b>}</a><br /><a href="https://github.com/Atri-Labs/atrilabs-engine/issues?q=author%3Aanuragc10" title="Bug reports">🐛</a></td> <td align="center"><a href="https://github.com/sanskarg348"><img src="https://avatars.githubusercontent.com/u/56079398?v=4?s=100" width="100px;" alt="sanskar gupta"/><br />_{<b>sanskar gupta</b>}</a><br /><a href="https://github.com/Atri-Labs/atrilabs-engine/issues?q=author%3Asanskarg348" title="Bug reports">🐛</a> <a href="https://github.com/Atri-Labs/atrilabs-engine/commits?author=sanskarg348" title="Documentation">📖</a> <a href="https://github.com/Atri-Labs/atrilabs-engine/commits?author=sanskarg348" title="Code">💻</a> <a href="#example-sanskarg348" title="Examples">💡</a> <a href="#promotion-sanskarg348" title="Promotion">📣</a> <a href="#video-sanskarg348" title="Videos">📹</a></td> <td align="center"><a href="https://github.com/devsachin007"><img src="https://avatars.githubusercontent.com/u/79436926?v=4?s=100" width="100px;" alt="Sachin Sharma"/><br />_{<b>Sachin Sharma</b>}</a><br /><a href="#question-devsachin007" title="Answering Questions">💬</a></td> <td align="center"><a href="https://github.com/Suryapp8"><img src="https://avatars.githubusercontent.com/u/113302256?v=4?s=100" width="100px;" alt="Surya Pandey"/><br />_{<b>Surya Pandey</b>}</a><br /><a href="#question-Suryapp8" title="Answering Questions">💬</a></td> </tr> <tr> <td align="center"><a href="https://github.com/ipriyanshi1708"><img src="https://avatars.githubusercontent.com/u/92941945?v=4?s=100" width="100px;" alt="Priyanshi Agarwal"/><br />_{<b>Priyanshi Agarwal</b>}</a><br /><a href="#question-ipriyanshi1708" title="Answering Questions">💬</a></td> <td align="center"><a href="http://aashutosh-kr.github.io"><img src="https://avatars.githubusercontent.com/u/95764284?v=4?s=100" width="100px;" alt="Aashutosh Kumar"/><br />_{<b>Aashutosh Kumar</b>}</a><br /><a href="#question-Aashutosh-kr" title="Answering Questions">💬</a></td> <td align="center"><a href="https://github.com/prativh24"><img src="https://avatars.githubusercontent.com/u/71186265?v=4?s=100" width="100px;" alt="Prativh Gupta"/><br />_{<b>Prativh Gupta</b>}</a><br /><a href="#question-prativh24" title="Answering Questions">💬</a></td> <td align="center"><a href="https://github.com/geetanjalikandpal21"><img src="https://avatars.githubusercontent.com/u/79351146?v=4?s=100" width="100px;" alt="Geetanjali Kandpal"/><br />_{<b>Geetanjali Kandpal</b>}</a><br /><a href="#question-geetanjalikandpal21" title="Answering Questions">💬</a></td> <td align="center"><a href="https://github.com/DivyanshSingh786"><img src="https://avatars.githubusercontent.com/u/93871896?v=4?s=100" width="100px;" alt="Divyansh Singh"/><br />_{<b>Divyansh Singh</b>}</a><br /><a href="#question-DivyanshSingh786" title="Answering Questions">💬</a></td> <td align="center"><a href="https://github.com/wereign"><img src="https://avatars.githubusercontent.com/u/101888489?v=4?s=100" width="100px;" alt="Virenn Jay"/><br />_{<b>Virenn Jay</b>}</a><br /><a href="https://github.com/Atri-Labs/atrilabs-engine/issues?q=author%3Awereign" title="Bug reports">🐛</a></td> <td align="center"><a href="https://github.com/rohinirai010"><img src="https://avatars.githubusercontent.com/u/96288899?v=4?s=100" width="100px;" alt="ROHINI RAI"/><br />_{<b>ROHINI RAI</b>}</a><br /><a href="#userTesting-rohinirai010" title="User Testing">📓</a></td> </tr> <tr> <td align="center"><a href="https://github.com/zapkirin"><img src="https://avatars.githubusercontent.com/u/112710485?v=4?s=100" width="100px;" alt="zapkirin"/><br />_{<b>zapkirin</b>}</a><br /><a href="https://github.com/Atri-Labs/atrilabs-engine/commits?author=zapkirin" title="Documentation">📖</a> <a href="#question-zapkirin" title="Answering Questions">💬</a></td> <td align="center"><a href="https://github.com/Vitika9"><img src="https://avatars.githubusercontent.com/u/79760854?v=4?s=100" width="100px;" alt="Vitika Soni"/><br />_{<b>Vitika Soni</b>}</a><br /><a href="https://github.com/Atri-Labs/atrilabs-engine/issues?q=author%3AVitika9" title="Bug reports">🐛</a></td> <td align="center"><a href="https://www.codechef.com/users/dumbledog"><img src="https://avatars.githubusercontent.com/u/63693789?v=4?s=100" width="100px;" alt="Vivek T."/><br />_{<b>Vivek T.</b>}</a><br /><a href="https://github.com/Atri-Labs/atrilabs-engine/commits?author=VivekThazhathattil" title="Code">💻</a></td> <td align="center"><a href="https://github.com/grishamg"><img src="https://avatars.githubusercontent.com/u/90051331?v=4?s=100" width="100px;" alt="Grisham Garg"/><br />_{<b>Grisham Garg</b>}</a><br /><a href="https://github.com/Atri-Labs/atrilabs-engine/issues?q=author%3Agrishamg" title="Bug reports">🐛</a></td> <td align="center"><a href="https://github.com/Ankittripa"><img src="https://avatars.githubusercontent.com/u/95485610?v=4?s=100" width="100px;" alt="Ankittripa"/><br />_{<b>Ankittripa</b>}</a><br /><a href="#ideas-Ankittripa" title="Ideas, Planning, & Feedback">🤔</a> <a href="#mentoring-Ankittripa" title="Mentoring">🧑‍🏫</a> <a href="https://github.com/Atri-Labs/atrilabs-engine/issues?q=author%3AAnkittripa" title="Bug reports">🐛</a> <a href="#question-Ankittripa" title="Answering Questions">💬</a></td> <td align="center"><a href="http://www.codeholic.epizy.com"><img src="https://avatars.githubusercontent.com/u/68885196?v=4?s=100" width="100px;" alt="sahil kandpal"/><br />_{<b>sahil kandpal</b>}</a><br /><a href="https://github.com/Atri-Labs/atrilabs-engine/issues?q=author%3Asahilkandpal" title="Bug reports">🐛</a></td> <td align="center"><a href="https://github.com/khalid2203"><img src="https://avatars.githubusercontent.com/u/100707364?v=4?s=100" width="100px;" alt="Khalid Saifullah"/><br />_{<b>Khalid Saifullah</b>}</a><br /><a href="https://github.com/Atri-Labs/atrilabs-engine/issues?q=author%3Akhalid2203" title="Bug reports">🐛</a></td> </tr> <tr> <td align="center"><a href="https://github.com/ahmed733"><img src="https://avatars.githubusercontent.com/u/58221987?v=4?s=100" width="100px;" alt="ahmed733"/><br />_{<b>ahmed733</b>}</a><br /><a href="https://github.com/Atri-Labs/atrilabs-engine/issues?q=author%3Aahmed733" title="Bug reports">🐛</a></td> <td align="center"><a href="https://leetcode.com/awdhesh_kumar/"><img src="https://avatars.githubusercontent.com/u/100534409?v=4?s=100" width="100px;" alt="Awdhesh Kumar"/><br />_{<b>Awdhesh Kumar</b>}</a><br /><a href="https://github.com/Atri-Labs/atrilabs-engine/issues?q=author%3Aawdhesh-kumar27" title="Bug reports">🐛</a></td> <td align="center"><a href="https://github.com/Jitulteron7"><img src="https://avatars.githubusercontent.com/u/58761652?v=4?s=100" width="100px;" alt="Jitul Teron"/><br />_{<b>Jitul Teron</b>}</a><br /><a href="https://github.com/Atri-Labs/atrilabs-engine/commits?author=Jitulteron7" title="Code">💻</a></td> <td align="center"><a href="https://www.youtube.com/channel/UCw4WQJ6A38AnUTQKhxwITSw"><img src="https://avatars.githubusercontent.com/u/16379731?v=4?s=100" width="100px;" alt="Anuj Singla"/><br />_{<b>Anuj Singla</b>}</a><br /><a href="https://github.com/Atri-Labs/atrilabs-engine/commits?author=anujsingla" title="Code">💻</a></td> <td align="center"><a href="https://github.com/anujsi"><img src="https://avatars.githubusercontent.com/u/30435233?v=4?s=100" width="100px;" alt="Anuj Singla"/><br />_{<b>Anuj Singla</b>}</a><br /><a href="https://github.com/Atri-Labs/atrilabs-engine/commits?author=anujsi" title="Code">💻</a></td> <td align="center"><a href="https://github.com/mhered"><img src="https://avatars.githubusercontent.com/u/75589082?v=4?s=100" width="100px;" alt="Manuel Heredia"/><br />_{<b>Manuel Heredia</b>}</a><br /><a href="https://github.com/Atri-Labs/atrilabs-engine/commits?author=mhered" title="Code">💻</a></td> <td align="center"><a href="https://nishant2209.github.io/Portfolio/"><img src="https://avatars.githubusercontent.com/u/71169457?v=4?s=100" width="100px;" alt="Nishant Kumar Singh "/><br />_{<b>Nishant Kumar Singh </b>}</a><br /><a href="#mentoring-Nishant2209" title="Mentoring">🧑‍🏫</a> <a href="#question-Nishant2209" title="Answering Questions">💬</a></td> </tr> <tr> <td align="center"><a href="https://sarfraz-alam.netlify.app/"><img src="https://avatars.githubusercontent.com/u/73013838?v=4?s=100" width="100px;" alt="MOHAMMAD SARFRAZ ALAM"/><br />_{<b>MOHAMMAD SARFRAZ ALAM</b>}</a><br /><a href="https://github.com/Atri-Labs/atrilabs-engine/issues?q=author%3ASarfraz-droid" title="Bug reports">🐛</a></td> </tr> </tbody> </table> <!-- markdownlint-restore --> <!-- prettier-ignore-end --> <!-- ALL-CONTRIBUTORS-LIST:END --> <!-- prettier-ignore-start --> <!-- markdownlint-disable --> <!-- markdownlint-restore --> <!-- prettier-ignore-end --> <!-- ALL-CONTRIBUTORS-LIST:END --> This project follows the [all-contributors](https://allcontributors.org/) specification. [Contributions of all types](https://allcontributors.org/docs/en/emoji-key) are welcome!

🧘‍♂️ Open-source no-code & code web app builder

fastapi,javascript,python3,reactjs,webframeworks

ggandor/leap.nvim

<img align="left" width="150" height="85" src="../media/kangaroo.png?raw=true"> # leap.nvim Leap is a general-purpose motion plugin for Neovim, building and improving primarily on [vim-sneak](https://github.com/justinmk/vim-sneak), with the ultimate goal of establishing a new standard interface for moving around in the visible area in Vim-like modal editors. It allows you to reach any target in a very fast, uniform way, and minimizes the required focus level while executing a jump.  ### How to use it (TL;DR) Leap's default motions allow you to jump to any position in the visible editor area by entering a 2-character search pattern, and then potentially a label character to pick your target from multiple matches, in a manner similar to Sneak. The main novel idea in Leap is that **you get a preview of the target labels** - Leap shows you which key you will need to press before you actually need to do that. - Initiate the search in the forward (`s`) or backward (`S`) direction, or in the other windows (`gs`). (Note: you can use a single key for the current window or even the whole tab page, if you are okay with the trade-offs.) - Start typing a 2-character pattern (`{char1}{char2}`). - After typing the first character, you see "labels" appearing next to some of the `{char1}{?}` pairs. You cannot _use_ the labels yet. - Enter `{char2}`. If the pair was not labeled, then voilà, you're already there. You can safely ignore the remaining labels, and continue editing - those are guaranteed non-conflicting letters, disappearing on the next keypress. - Else: type the label character. If there are more matches than available labels, you can switch between groups, using `<space>` and `<tab>`. Labels in the immediate next group are already visible, but highlighted differently than the active ones. Character pairs give you full coverage of the screen: - `s{char}<space>` jumps to a character before the end of the line. - `s<space><space>` jumps to any EOL position, including empty lines. At any stage, `<enter>` consistently jumps to the next available target (`<tab>` steps back): - `s<enter>...` repeats the previous search. - `s{char}<enter>...` can be used as a multiline substitute for `fFtT` motions. ### Why is this method cool? It is ridiculously fast: not counting the trigger key, leaping to literally anywhere on the screen rarely takes more than 3 keystrokes in total, that can be typed in one go. Often 2 is enough. At the same time, it reduces mental effort to almost zero: - You _don't have to weigh alternatives_: a single universal motion type can be used in all non-trivial situations. - You _don't have to compose in your head_: one command achieves one logical movement. - You _don't have to be aware of the context_: the eyes can keep focusing on the target the whole time. - You _don't have to make decisions on the fly_: the sequence you should enter is determined from the very beginning. - You _don't have to pause in the middle_: if typing at a moderate speed, at each step you already know what the immediate next keypress should be, and your mind can process the rest in the background. ## Getting started ### Status The plugin is not 100% stable yet, but don't let that stop you - the usage basics are extremely unlikely to change. To follow breaking changes, subscribe to the corresponding [issue](https://github.com/ggandor/leap.nvim/issues/18). ### Requirements * Neovim >= 0.7.0 stable, or latest nightly ### Dependencies * [repeat.vim](https://github.com/tpope/vim-repeat), for dot-repeats (`.`) to work ### Installation Use your preferred method or plugin manager. No extra steps needed besides defining keybindings - to use the default ones, put the following into your config (overrides `s`, `S` and `gs` in all modes): `require('leap').create_default_mappings()` (init.lua) `lua require('leap').create_default_mappings()` (init.vim) <details> <summary>Alternative key mappings</summary> Calling `require('leap').create_default_mappings()` is equivalent to: ```lua vim.keymap.set({'n', 'x', 'o'}, 's', '<Plug>(leap-forward)') vim.keymap.set({'n', 'x', 'o'}, 'S', '<Plug>(leap-backward)') vim.keymap.set({'n', 'x', 'o'}, 'gs', '<Plug>(leap-from-window)') ``` A suggested alternative arrangement (bidirectional `s` for Normal mode): ```lua vim.keymap.set('n', 's', '<Plug>(leap)') vim.keymap.set('n', 'S', '<Plug>(leap-from-window)') vim.keymap.set({'x', 'o'}, 's', '<Plug>(leap-forward)') vim.keymap.set({'x', 'o'}, 'S', '<Plug>(leap-backward)') ``` Mapping to `<Plug>(leap)` is not recommended for Visual mode, as autojumping in a random direction might be too disorienting with the selection highlight on, and neither for Operator-pending mode, as dot-repeat cannot be used if the search is non-directional. Note that compared to using separate keys for the two directions, you will get twice as many targets and thus half as many autojumps on average, but not needing to press the Shift key for backward motions might compensate for that. Another caveat is that you cannot traverse through the matches (`:h leap-traversal`), although invoking repeat right away (`:h leap-repeat`) can substitute for that. `<Plug>(leap)` sorts matches by euclidean distance from the cursor, with the exception that the current line, and on the current line, forward direction is prioritized. That is, you can always be sure that the targets right in front of you will be the first ones. See `:h leap-custom-mappings` for more. </details> <details> <summary>Suggested additional tweaks</summary> ```lua -- Define equivalence classes for brackets and quotes, in addition to -- the default whitespace group. require('leap').opts.equivalence_classes = { ' \t\r\n', '([{', ')]}', '\'"`' } -- Override some old defaults - use backspace instead of tab (see issue #165). require('leap').opts.special_keys.prev_target = '<backspace>' require('leap').opts.special_keys.prev_group = '<backspace>' -- Use the traversal keys to repeat the previous motion without explicitly -- invoking Leap. require('leap.user').set_repeat_keys('<enter>', '<backspace>') ``` </details> <details> <summary>Workaround for the duplicate cursor bug when autojumping</summary> For Neovim versions < 0.10 (https://github.com/neovim/neovim/issues/20793): ```lua -- Hide the (real) cursor when leaping, and restore it afterwards. vim.api.nvim_create_autocmd('User', { pattern = 'LeapEnter', callback = function() vim.cmd.hi('Cursor', 'blend=100') vim.opt.guicursor:append { 'a:Cursor/lCursor' } end, } ) vim.api.nvim_create_autocmd('User', { pattern = 'LeapLeave', callback = function() vim.cmd.hi('Cursor', 'blend=0') vim.opt.guicursor:remove { 'a:Cursor/lCursor' } end, } ) ``` Caveat: If you experience any problems after using the above snippet, check [#70](https://github.com/ggandor/leap.nvim/issues/70#issuecomment-1521177534) and [#143](https://github.com/ggandor/leap.nvim/pull/143) to tweak it. </details> <details> <summary>Lazy loading</summary> ...is all the rage now, but doing it via your plugin manager is unnecessary, as Leap lazy loads itself. Using the `keys` feature of lazy.nvim might even cause [problems](https://github.com/ggandor/leap.nvim/issues/191). </details> ### Next steps Help files are not exactly page-turners, but I suggest at least skimming [`:help leap`](doc/leap.txt), even if you don't have a specific question yet (if nothing else: `:h leap-usage`, `:h leap-config`, `:h leap-events`). While Leap has deeply thought-through, opinionated defaults, its small(ish) but comprehensive API makes it pretty flexible. ## Design considerations in detail ### The ideal Premise: jumping from point A to B on the screen should not be some [exciting puzzle](https://www.vimgolf.com/), for which you should train yourself; it should be a non-issue. An ideal keyboard-driven interface would impose almost no more cognitive burden than using a mouse, without the constant context-switching required by the latter. That is, **you do not want to think about** - **the command**: we need one fundamental targeting method that can bring you anywhere: a "jetpack on the back", instead of "airline routes" (↔ [EasyMotion](https://github.com/easymotion/vim-easymotion) and its derivatives) - **the context**: it should be enough to look at the target, and nothing else (↔ vanilla Vim motion combinations using relative line numbers and/or repeats) - **the steps**: the motion should be atomic (↔ Vim motion combos), and ideally you should be able to type the whole sequence in one go, on more or less autopilot (↔ any kind of "just-in-time" labeling method; note that the "search command on steroids" approach by [Pounce](https://github.com/rlane/pounce.nvim) and [Flash](https://github.com/folke/flash.nvim), where the labels appear at an unknown time by design, makes this last goal impossible) All the while using **as few keystrokes as possible**, and getting distracted by **as little incidental visual noise as possible**. ### How do we measure up? It is obviously impossible to achieve all of the above at the same time, without some trade-offs at least; but in our opinion Leap comes pretty close, occupying a sweet spot in the design space. (The worst remaining offender might be visual noise.) The **one-step shift between perception and action** is the big idea that cuts the Gordian knot: a fixed pattern length combined with ahead-of-time labeling can eliminate the surprise factor from the search-based method (which is the only viable approach - see "jetpack" above). Fortunately, a 2-character pattern \- the shortest one with which we can play this trick - is also long enough to sufficiently narrow down the matches in the vast majority of cases. Fixed pattern length also makes **(safe) automatic jump to the first target** possible. You cannot improve on jumping directly, just like how `f` and `t` works, not having to read a label at all, and not having to accept the match with `<enter>` either. However, we can do this in a smart way: if there are many targets (more than 15-20), we stay put, so we can use a bigger, "unsafe" label set - getting the best of both worlds. The non-determinism we're introducing is less of an issue here, since the outcome is known in advance. In sum, compared to other methods based on labeling targets, Leap's approach is unique in that it * offers a smoother experience, by (somewhat) eliminating the pause before typing the label * feels natural to use for both distant _and_ close targets ### Auxiliary principles <details> <summary>Optimize for the common case</summary> A good example is using strictly one-character labels and switching between groups, which can become awkward beyond, say, 200 targets, but makes a whole bunch of edge cases and UI problems nonexistent. </details> <details> <summary>Sharpen the saw</summary> Build on Vim's native features, aim for synergy, and don't reinvent the wheel (dot-repeat (`.`), inclusive/exclusive toggle (`v`), [keymap](https://neovim.io/doc/user/mbyte.html#mbyte-keymap) support, autocommands via `User` events, `<Plug>` keys, etc.). (http://vimcasts.org/blog/2012/08/on-sharpening-the-saw/) </details> <details> <summary>Mechanisms instead of policies</summary> Complement the small and opinionated core by [extension points](#extending-leap), keeping the plugin flexible and future-proof. </details> ## FAQ ### Bugs <details> <summary>Workaround for the duplicate cursor bug when autojumping</summary> For Neovim versions < 0.10 (https://github.com/neovim/neovim/issues/20793): ```lua -- Hide the (real) cursor when leaping, and restore it afterwards. vim.api.nvim_create_autocmd('User', { pattern = 'LeapEnter', callback = function() vim.cmd.hi('Cursor', 'blend=100') vim.opt.guicursor:append { 'a:Cursor/lCursor' } end, } ) vim.api.nvim_create_autocmd('User', { pattern = 'LeapLeave', callback = function() vim.cmd.hi('Cursor', 'blend=0') vim.opt.guicursor:remove { 'a:Cursor/lCursor' } end, } ) ``` Caveat: If you experience any problems after using the above snippet, check [#70](https://github.com/ggandor/leap.nvim/issues/70#issuecomment-1521177534) and [#143](https://github.com/ggandor/leap.nvim/pull/143) to tweak it. </details> ### Defaults <details> <summary>Why remap `s`/`S`?</summary> Common operations should use the fewest keystrokes and the most comfortable keys, so it makes sense to take those over by Leap, especially given that both native commands have synonyms: Normal mode - `s` = `cl` (or `xi`) - `S` = `cc` Visual mode - `s` = `c` - `S` = `Vc`, or `c` if already in linewise mode If you are not convinced, just head to `:h leap-custom-mappings`. </details> ### Features <details> <summary>Search in all windows</summary> ```lua vim.keymap.set('n', 's', function () require('leap').leap { target_windows = require('leap.user').get_focusable_windows() } end) ``` The additional trade-off here is that if you have multiple windows open on the tab page, then you will almost never get an autojump, except if all targets are in the same window (it would be too disorienting if the cursor could suddenly jump in/to a different window than your goal, right before selecting the target, not to mention that we don't want to change the state of a window we're not targeting). </details> <details> <summary>Smart case sensitivity, wildcard characters (one-way aliases)</summary> Ahead-of-time labeling, unfortunately, makes them impossible, by design: for a potential match in phase one, we might need to show two different labels (corresponding to two different futures) at the same time. ([1](https://github.com/ggandor/leap.nvim/issues/28), [2](https://github.com/ggandor/leap.nvim/issues/89#issuecomment-1368885497), [3](https://github.com/ggandor/leap.nvim/issues/155#issuecomment-1556124351)) </details> <details> <summary>Arbitrary remote actions instead of jumping</summary> Basic template: ```lua local function remote_action () require('leap').leap { target_windows = require('leap.user').get_focusable_windows(), action = function (target) local winid = target.wininfo.winid local lnum, col = unpack(target.pos) -- 1/1-based indexing! -- ... do something at the given position ... end, } end ``` See [Extending Leap](#extending-leap) for more. </details> <details> <summary>Other supernatural powers besides clairvoyance?</summary> You might be interested in [telekinesis](https://github.com/ggandor/leap-spooky.nvim). </details> ### Configuration <details> <summary>Disable auto-jumping to the first match</summary> ```lua require('leap').opts.safe_labels = {} ``` </details> <details> <summary>Greying out the search area</summary> ```lua -- Or just set to grey directly, e.g. { fg = '#777777' }, -- if Comment is saturated. vim.api.nvim_set_hl(0, 'LeapBackdrop', { link = 'Comment' }) ``` </details> <details> <summary>Hiding secondary labels</summary> You can hide the letters, and show emtpy boxes by tweaking the `LeapLabelSecondary` highlight group (that way you keep a visual indication that the target is labeled): ```lua vim.api.nvim_create_autocmd('ColorScheme', { callback = function () local bg = vim.api.nvim_get_hl(0, {name = 'LeapLabelSecondary'}).bg vim.api.nvim_set_hl(0, 'LeapLabelSecondary',{ fg = bg, bg = bg, }) end }) ``` </details> <details> <summary>Lightspeed-style highlighting</summary> ```lua -- The below settings make Leap's highlighting closer to what you've been -- used to in Lightspeed. vim.api.nvim_set_hl(0, 'LeapBackdrop', { link = 'Comment' }) -- or some grey vim.api.nvim_set_hl(0, 'LeapMatch', { -- For light themes, set to 'black' or similar. fg = 'white', bold = true, nocombine = true, }) -- Lightspeed colors -- primary labels: bg = "#f02077" (light theme) or "#ff2f87" (dark theme) -- secondary labels: bg = "#399d9f" (light theme) or "#99ddff" (dark theme) -- shortcuts: bg = "#f00077", fg = "white" -- You might want to use either the primary label or the shortcut colors -- for Leap primary labels, depending on your taste. vim.api.nvim_set_hl(0, 'LeapLabelPrimary', { fg = 'red', bold = true, nocombine = true, }) vim.api.nvim_set_hl(0, 'LeapLabelSecondary', { fg = 'blue', bold = true, nocombine = true, }) -- Try it without this setting first, you might find you don't even miss it. require('leap').opts.highlight_unlabeled_phase_one_targets = true ``` </details> <details> <summary>Working with non-English text</summary> If a [`language-mapping`](https://neovim.io/doc/user/map.html#language-mapping) ([`'keymap'`](https://neovim.io/doc/user/options.html#'keymap')) is active, Leap waits for keymapped sequences as needed and searches for the keymapped result as expected. Also check out `opts.equivalence_classes`, that lets you group certain characters together as aliases, e.g.: ```lua { ' \t\r\n', 'aäàáâãā', 'dḍ', 'eëéèêē', 'gǧğ', 'hḥḫ', 'iïīíìîı', 'nñ', 'oō', 'sṣšß', 'tṭ', 'uúûüűū', 'zẓ' } ``` </details> ### Miscellaneous <details> <summary>Was the name inspired by Jef Raskin's Leap?</summary> To paraphrase Steve Jobs about their logo and Turing's poison apple, I wish it were, but it is a coincidence. "Leap" is just another synonym for "jump", that happens to rhyme with Sneak. That said, in some respects you can indeed think of leap.nvim as a spiritual successor to Raskin's work, and thus the name as a little tribute to the great pioneer of interface design, even though embracing the modal paradigm is a fundamental difference in our approach. </details> ## Extending Leap There are lots of ways you can extend the plugin and bend it to your will - see `:h leap.leap()` and `:h leap-events`. Besides tweaking the basic parameters (search scope, jump offset, etc.) of the function, you can: * give it a custom **action** to perform, instead of jumping * feed it with custom **targets**, aquired by arbitrary means, and only use it as labeler/selector * customize the behavior on a per-call basis via **autocommands** Some practical examples: <details> <summary>Linewise motions</summary> ```lua local function get_line_starts(winid, skip_range) local wininfo = vim.fn.getwininfo(winid)[1] local cur_line = vim.fn.line('.') -- Skip lines close to the cursor. local skip_range = skip_range or 2 -- Get targets. local targets = {} local lnum = wininfo.topline while lnum <= wininfo.botline do local fold_end = vim.fn.foldclosedend(lnum) -- Skip folded ranges. if fold_end ~= -1 then lnum = fold_end + 1 else if (lnum < cur_line - skip_range) or (lnum > cur_line + skip_range) then table.insert(targets, { pos = { lnum, 1 } }) end lnum = lnum + 1 end end -- Sort them by vertical screen distance from cursor. local cur_screen_row = vim.fn.screenpos(winid, cur_line, 1)['row'] local function screen_rows_from_cur(t) local t_screen_row = vim.fn.screenpos(winid, t.pos[1], t.pos[2])['row'] return math.abs(cur_screen_row - t_screen_row) end table.sort(targets, function (t1, t2) return screen_rows_from_cur(t1) < screen_rows_from_cur(t2) end) if #targets >= 1 then return targets end end -- You can pass an argument to specify a range to be skipped -- before/after the cursor (default is +/-2). function leap_line_start(skip_range) local winid = vim.api.nvim_get_current_win() require('leap').leap { target_windows = { winid }, targets = get_line_starts(winid, skip_range), } end -- For maximum comfort, force linewise selection in the mappings: vim.keymap.set('x', '|', function () -- Only force V if not already in it (otherwise it would exit Visual mode). if vim.fn.mode(1) ~= 'V' then vim.cmd('normal! V') end leap_line_start() end) vim.keymap.set('o', '|', "V<cmd>lua leap_line_start()<cr>") ``` </details> <details> <summary>Select Tree-sitter nodes</summary> Not as sophisticated as flash.nvim's implementation, but totally usable, in 50 lines: ```lua local api = vim.api local ts = vim.treesitter local function get_ts_nodes() if not pcall(ts.get_parser) then return end local wininfo = vim.fn.getwininfo(api.nvim_get_current_win())[1] -- Get current node, and then its parent nodes recursively. local cur_node = ts.get_node() if not cur_node then return end local nodes = { cur_node } local parent = cur_node:parent() while parent do table.insert(nodes, parent) parent = parent:parent() end -- Create Leap targets from TS nodes. local targets = {} local startline, startcol for _, node in ipairs(nodes) do startline, startcol, endline, endcol = node:range() -- (0,0) local startpos = { startline + 1, startcol + 1 } local endpos = { endline + 1, endcol + 1 } -- Add both ends of the node. if startline + 1 >= wininfo.topline then table.insert(targets, { pos = startpos, altpos = endpos }) end if endline + 1 <= wininfo.botline then table.insert(targets, { pos = endpos, altpos = startpos }) end end if #targets >= 1 then return targets end end local function select_node_range(target) local mode = api.nvim_get_mode().mode -- Force going back to Normal from Visual mode. if not mode:match('no?') then vim.cmd('normal! ' .. mode) end vim.fn.cursor(unpack(target.pos)) local v = mode:match('V') and 'V' or mode:match('') and '' or 'v' vim.cmd('normal! ' .. v) vim.fn.cursor(unpack(target.altpos)) end local function leap_ts() require('leap').leap { target_windows = { api.nvim_get_current_win() }, targets = get_ts_nodes, action = select_node_range, } end vim.keymap.set({'x', 'o'}, '\\', leap_ts) ``` </details> <details> <summary>Shortcuts to Telescope results</summary> ```lua -- NOTE: If you try to use this before entering any input, an error is thrown. -- (Help would be appreciated, if someone knows a fix.) local function get_targets (buf) local pick = require('telescope.actions.state').get_current_picker(buf) local scroller = require('telescope.pickers.scroller') local wininfo = vim.fn.getwininfo(pick.results_win)[1] local top = math.max( scroller.top(pick.sorting_strategy, pick.max_results, pick.manager:num_results()), wininfo.topline - 1 ) local bottom = wininfo.botline - 2 -- skip the current row local targets = {} for lnum = bottom, top, -1 do -- start labeling from the closest (bottom) row table.insert(targets, { wininfo = wininfo, pos = { lnum + 1, 1 }, pick = pick, }) end return targets end local function pick_with_leap (buf) require('leap').leap { targets = function () return get_targets(buf) end, action = function (target) target.pick:set_selection(target.pos[1] - 1) require('telescope.actions').select_default(buf) end, } end require('telescope').setup { defaults = { mappings = { i = { ['<a-p>'] = pick_with_leap }, } } } ``` </details> <details> <summary>Remote text objects</summary> See [leap-spooky.nvim](https://github.com/ggandor/leap-spooky.nvim). </details> <details> <summary>Enhanced f/t motions</summary> See [flit.nvim](https://github.com/ggandor/flit.nvim). </details>

Neovim's answer to the mouse 🦘

neovim,neovim-plugin,nvim,nvim-plugin,fennel,vim,motion

Tencent/tmagic-editor

# TMagic TMagic 可视化搭建平台。 * 💪 Vue 3.0 Composition API * 🔥 Written in TypeScript # 文档 文档请移步 https://tencent.github.io/tmagic-editor/docs/index.html 目前文档仍在逐步完善中，如有疑问欢迎给我们提 issue。 # Playground 体验 https://tencent.github.io/tmagic-editor/playground/index.html ## 环境准备 node.js >= 18 pnpm >= 9 先安装 pnpm ```bash $ npm install -g pnpm ``` 然后安装依赖 ```bash $ pnpm bootstrap ``` ## 运行项目 执行命令 ```bash $ pnpm playground ``` 最后在浏览器中打开 http://localhost:8098/tmagic-editor/playground/ 即可得到一个魔方编辑器示例项目 ## magic-admin 已迁移至 https://github.com/vft-magic/tmagic-admin ## 项目介绍 在本项目中，我们核心内容，是包含在 `packages/editor` 中的编辑器，以及 `runtime` 和 `packages/ui` 提供的各个前端框架相关的 runtime 和 ui。 - `packages` 目录中提供的内容，我们都以 npm 包形式输出，开发者可以通过安装对应的包来使用。 - `runtime` 是我们提供的编辑器活动页和编辑器模拟器运行的页面项目示例。可以直接使用，也可以参考并自行实现。 - `playground` 是一个简单的编辑器项目示例。即使用了 `packages` 和 `runtime` 内容的集成项目。开发者可以参考 playground，使用魔方提供的能力实现一个满足业务方需求的编辑器。 ### 编辑器 通过安装和使用 @tmagic/editor，可以快速搭建起一个魔方编辑器。 <img src="https://image.video.qpic.cn/oa_88b7d-32_509802977_1635842258505918" alt="魔方demo图"> ### 页面渲染 runtime 是魔方提供的页面渲染环境。通过加载在编辑器中产出的 DSL，即可得到魔方编辑器希望拥有的最终产物，一个活动页面。我们提供了 vue2/vue3/react 几个版本的 runtime。 通过魔方编辑器和 runtime 渲染，以及通过自定义的复杂组件开发，可以在魔方项目上，搭建出复杂而精美的页面。 <img src="https://image.video.qpic.cn/oa_7cf5e6-5_466783002_1637935497991411" width="375"> ### 表单渲染 魔方的表单配置项，使用了我们开发的基于 element-ui 的 @tmagic/form，@tmagic/form 也可以在其他地方单独使用。支持渲染 JS Schema 提供的表单描述。 <img src="https://image.video.qpic.cn/oa_28dbde-2_1333081854_1637935825410557" > ### 使用 playground 的示例项目，就是为开发者提供的基础应用示例。开发者可以基于此或者参考自行实现，搭建一个基于魔方的可视化搭建平台。 tmagic-editor主要定位是搭建生成移动端H5页面，如果有搭建PC端低代码平台的需求，可以了解一下腾讯出品的另外一个低代码平台：[无极低代码平台](https://wujicode.cn?from=tmagic)。 ### 参与贡献 如果你有好的意见或建议，欢迎给我们提 Issues 或 Pull Requests，为提升魔方可视化编辑器开发体验贡献力量。<br>详见：[CONTRIBUTING.md](./CONTRIBUTING.md) ## 贡献者 <a href="https://github.com/Tencent/tmagic-editor/graphs/contributors"> <img src="https://contrib.rocks/image?repo=Tencent/tmagic-editor" /> </a> ### 欢迎入群交流 <img src="https://vfiles.gtimg.cn/vupload/20220412/b85d331649748582992.jpg" width=375>

pufferffish/wireproxy

# wireproxy [](./LICENSE) [](https://github.com/octeep/wireproxy/actions) [](https://pkg.go.dev/github.com/octeep/wireproxy) A wireguard client that exposes itself as a socks5/http proxy or tunnels. # What is this `wireproxy` is a completely userspace application that connects to a wireguard peer, and exposes a socks5/http proxy or tunnels on the machine. This can be useful if you need to connect to certain sites via a wireguard peer, but can't be bothered to setup a new network interface for whatever reasons. # Why you might want this - You simply want to use wireguard as a way to proxy some traffic. - You don't want root permission just to change wireguard settings. Currently, I'm running wireproxy connected to a wireguard server in another country, and configured my browser to use wireproxy for certain sites. It's pretty useful since wireproxy is completely isolated from my network interfaces, and I don't need root to configure anything. Users who want something similar but for Amnezia VPN can use [this fork](https://github.com/juev/wireproxy/tree/feature/amnezia-go) of wireproxy by [@juev](https://github.com/juev). # Feature - TCP static routing for client and server - SOCKS5/HTTP proxy (currently only CONNECT is supported) # TODO - UDP Support in SOCKS5 - UDP static routing # Usage ``` ./wireproxy -c [path to config] ``` ``` usage: wireproxy [-h|--help] [-c|--config "<value>"] [-s|--silent] [-d|--daemon] [-i|--info "<value>"] [-v|--version] [-n|--configtest] Userspace wireguard client for proxying Arguments: -h --help Print help information -c --config Path of configuration file -s --silent Silent mode -d --daemon Make wireproxy run in background -i --info Specify the address and port for exposing health status -v --version Print version -n --configtest Configtest mode. Only check the configuration file for validity. ``` # Build instruction ``` git clone https://github.com/octeep/wireproxy cd wireproxy make ``` # Use with VPN Instructions for using wireproxy with Firefox container tabs and auto-start on MacOS can be found [here](/UseWithVPN.md). # Sample config file ``` # The [Interface] and [Peer] configurations follow the same semantics and meaning # of a wg-quick configuration. To understand what these fields mean, please refer to: # https://wiki.archlinux.org/title/WireGuard#Persistent_configuration # https://www.wireguard.com/#simple-network-interface [Interface] Address = 10.200.200.2/32 # The subnet should be /32 and /128 for IPv4 and v6 respectively # MTU = 1420 (optional) PrivateKey = uCTIK+56CPyCvwJxmU5dBfuyJvPuSXAq1FzHdnIxe1Q= DNS = 10.200.200.1 [Peer] PublicKey = QP+A67Z2UBrMgvNIdHv8gPel5URWNLS4B3ZQ2hQIZlg= # PresharedKey = UItQuvLsyh50ucXHfjF0bbR4IIpVBd74lwKc8uIPXXs= (optional) Endpoint = my.ddns.example.com:51820 # PersistentKeepalive = 25 (optional) # TCPClientTunnel is a tunnel listening on your machine, # and it forwards any TCP traffic received to the specified target via wireguard. # Flow: # <an app on your LAN> --> localhost:25565 --(wireguard)--> play.cubecraft.net:25565 [TCPClientTunnel] BindAddress = 127.0.0.1:25565 Target = play.cubecraft.net:25565 # TCPServerTunnel is a tunnel listening on wireguard, # and it forwards any TCP traffic received to the specified target via local network. # Flow: # <an app on your wireguard network> --(wireguard)--> 172.16.31.2:3422 --> localhost:25545 [TCPServerTunnel] ListenPort = 3422 Target = localhost:25545 # STDIOTunnel is a tunnel connecting the standard input and output of the wireproxy # process to the specified TCP target via wireguard. # This is especially useful to use wireproxy as a ProxyCommand parameter in openssh # For example: # ssh -o ProxyCommand='wireproxy -c myconfig.conf' ssh.myserver.net # Flow: # Piped command -->(wireguard)--> ssh.myserver.net:22 [STDIOTunnel] Target = ssh.myserver.net:22 # Socks5 creates a socks5 proxy on your LAN, and all traffic would be routed via wireguard. [Socks5] BindAddress = 127.0.0.1:25344 # Socks5 authentication parameters, specifying username and password enables # proxy authentication. #Username = ... # Avoid using spaces in the password field #Password = ... # http creates a http proxy on your LAN, and all traffic would be routed via wireguard. [http] BindAddress = 127.0.0.1:25345 # HTTP authentication parameters, specifying username and password enables # proxy authentication. #Username = ... # Avoid using spaces in the password field #Password = ... ``` Alternatively, if you already have a wireguard config, you can import it in the wireproxy config file like this: ``` WGConfig = <path to the wireguard config> # Same semantics as above [TCPClientTunnel] ... [TCPServerTunnel] ... [Socks5] ... ``` Having multiple peers is also supported. `AllowedIPs` would need to be specified such that wireproxy would know which peer to forward to. ``` [Interface] Address = 10.254.254.40/32 PrivateKey = XXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXXX= [Peer] Endpoint = 192.168.0.204:51820 PublicKey = YYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYY= AllowedIPs = 10.254.254.100/32 PersistentKeepalive = 25 [Peer] PublicKey = ZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZZ= AllowedIPs = 10.254.254.1/32, fdee:1337:c000:d00d::1/128 Endpoint = 172.16.0.185:44044 PersistentKeepalive = 25 [TCPServerTunnel] ListenPort = 5000 Target = service-one.servicenet:5000 [TCPServerTunnel] ListenPort = 5001 Target = service-two.servicenet:5001 [TCPServerTunnel] ListenPort = 5080 Target = service-three.servicenet:80 ``` Wireproxy can also allow peers to connect to it: ``` [Interface] ListenPort = 5400 ... [Peer] PublicKey = YYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYYY= AllowedIPs = 10.254.254.100/32 # Note there is no Endpoint defined here. ``` # Health endpoint Wireproxy supports exposing a health endpoint for monitoring purposes. The argument `--info/-i` specifies an address and port (e.g. `localhost:9080`), which exposes a HTTP server that provides health status metric of the server. Currently two endpoints are implemented: `/metrics`: Exposes information of the wireguard daemon, this provides the same information you would get with `wg show`. [This](https://www.wireguard.com/xplatform/#example-dialog) shows an example of what the response would look like. `/readyz`: This responds with a json which shows the last time a pong is received from an IP specified with `CheckAlive`. When `CheckAlive` is set, a ping is sent out to addresses in `CheckAlive` per `CheckAliveInterval` seconds (defaults to 5) via wireguard. If a pong has not been received from one of the addresses within the last `CheckAliveInterval` seconds (+2 seconds for some leeway to account for latency), then it would respond with a 503, otherwise a 200. For example: ``` [Interface] PrivateKey = censored Address = 10.2.0.2/32 DNS = 10.2.0.1 CheckAlive = 1.1.1.1, 3.3.3.3 CheckAliveInterval = 3 [Peer] PublicKey = censored AllowedIPs = 0.0.0.0/0 Endpoint = 149.34.244.174:51820 [Socks5] BindAddress = 127.0.0.1:25344 ``` `/readyz` would respond with ``` < HTTP/1.1 503 Service Unavailable < Date: Thu, 11 Apr 2024 00:54:59 GMT < Content-Length: 35 < Content-Type: text/plain; charset=utf-8 < {"1.1.1.1":1712796899,"3.3.3.3":0} ``` And for: ``` [Interface] PrivateKey = censored Address = 10.2.0.2/32 DNS = 10.2.0.1 CheckAlive = 1.1.1.1 ``` `/readyz` would respond with ``` < HTTP/1.1 200 OK < Date: Thu, 11 Apr 2024 00:56:21 GMT < Content-Length: 23 < Content-Type: text/plain; charset=utf-8 < {"1.1.1.1":1712796979} ``` If nothing is set for `CheckAlive`, an empty JSON object with 200 will be the response. The peer which the ICMP ping packet is routed to depends on the `AllowedIPs` set for each peers. # Stargazers over time [](https://starchart.cc/octeep/wireproxy)

Wireguard client that exposes itself as a socks5 proxy

wireguard,socks5,proxy,network,socks5-proxy,wireguard-tunnel,vpn,golang

subframe7536/maple-font

<br> <p align="center"> <img src="./img/head.svg" height="230" alt="logo"> </p> <h1 align="center"> Maple Font </h1> <p align="center"> Open source monospace & nerd font with round corner and ligatures. </p> <p align="center"> <a href="https://github.com/subframe7536/Maple-font/releases"> <img src="https://img.shields.io/github/v/release/subframe7536/Maple-font?display_name=tag" alt="release version"> </a> </p> <p align="center"> <a href="#install">install</a> | <a href="https://github.com/users/subframe7536/projects/1">what's next</a> | English | <a href="./README_CN.md">中文</a> </p> ## Preparing for [V7](https://github.com/subframe7536/maple-font/tree/variable), try the new variable font at [latest release](https://github.com/subframe7536/maple-font/releases) ## Features Inspired by [Source Code Pro](https://github.com/adobe-fonts/source-code-pro), [Fira Code Retina](https://github.com/tonsky/FiraCode), [Sarasa Mono SC Nerd](https://github.com/laishulu/Sarasa-Mono-SC-Nerd) and so on, but: - 🎨 **New shape** - such as `@ # $ % &` and new shape of italic style - 🤙🏻 **More ligatures** - such as `.., ..., /*, /**` - 📦 **Small size** - leave only contains latin, standard set of accents, table control characters and few symbols - 🦾 **Better rendering effect** - redesigned it according to Fira Code Retina's spacing and glyph | v4 | v5 | | :----------------------------------------------------: | :-----------------------------------------------------: | | <img src="./img/sizechange.gif" height="200" alt="v4"> | <img src="./img/sizechange1.gif" height="200" alt="v5"> | | `+` and `=` are not centered at some font-size | `+` and `=` are always centered | - 🗒 **More readable** - cursive style, better glyph shape, lower the height of capital letters and numbers, reduce or modify kerning and center operators `+ - * = ^ ~ < >` - 🛠️ **More configable** - enable or disable font features as you want, just make your own font - ✨ See it in [screenshots](#screenshots) ## Install | Platform | Command | | :--------- | :-------------------------------------------------------------------------- | | macOS | `brew install --cask font-maple` | | Arch Linux | `paru -S ttf-maple` | | Others | Download in [releases](https://github.com/subframe7536/Maple-font/releases) | ## Notice Because I don't have a Mac OS machine, this is the greatest adaption I can do with Mac OS currently, but I can't test whether it works. My ability is not enough to solve other problems on Mac OS. I will record the problem and try to solve it, and **PR welcome!** `Maple Mono NF` now maybe can't be recognized as Mono, and I try my best but it doesn't work orz ## Overview <p align="center"> <img src="./img/base.png" /><br> <img src="./img/ligature.png" /><br> <img src="./img/ligature.gif"/><br> multiply ways to get TODO tag<br> ps: in Jetbrains' product, [todo) can't be properly rendered, so please use todo))<br> </p> <p align="center"> <img src="./img/option.png"/><br> <h3 align="center">font features are different in font features are different in V7, see in <a href="https://github.com/subframe7536/maple-font/tree/variable?tab=readme-ov-file#features">docs</h3><br/> compatibility & usage: in <a href="https://github.com/tonsky/FiraCode#editor-compatibility-list" target="_blank">FiraCode README</a> </p> ## Screenshots code theme: [vscode-theme-maple](https://github.com/subframe7536/vscode-theme-maple) generate by: [VSCodeSnap](https://github.com/luisllamasbinaburo/VSCodeSnap) <details> <summary><b>Cli (click to expand!)</b></summary>  </details> <details> <summary><b>React</b></summary>  </details> <details> <summary><b>Vue</b></summary>  </details> <details> <summary><b>Java</b></summary>  </details> <details> <summary><b>Go</b></summary> <p align="center"> <img src="img/code_sample/go.webp" width="540px"/> </p> </details> <details> <summary><b>Python</b></summary>  </details> <details> <summary><b>Rust</b></summary>  </details> ## Build your own font see [doc](./source/README.md) ## Donate If this was helpful to you, please feel free to buy me a coffee <a href="https://www.buymeacoffee.com/subframe753"><img src="https://img.buymeacoffee.com/button-api/?text=Buy me a coffee&emoji=&slug=subframe753&button_colour=5F7FFF&font_colour=ffffff&font_family=Lato&outline_colour=000000&coffee_colour=FFDD00" /></a>  ## License SIL Open Font License 1.1

[testing V7] Maple Mono: Open source monospace font with round corner, ligatures and Nerd-Font for IDE and command line. 带连字和控制台图标的圆角等宽字体，中英文宽度完美2:1

font,monospace-font,ligatures,programming-ligatures,coding-font,programming-font,monospace,typeface

webstudio-is/webstudio

<img width="1512" alt="builder-screenshot" src="https://github.com/webstudio-is/.github/blob/main/assets/builder-screenshot.png?raw=true"> <br /><br /> <section align="center"> Webstudio is an Open Source Visual Development Platform for developers, designers, and cross-functional teams. You own the data, components, and infrastructure. You can use the hosted version or roll out your own. </section> <br /><br /> ## Learning Resources - [Blog](https://webstudio.is/blog) - [Documentation](https://docs.webstudio.is/) - [Brand and Product Design](https://docs.webstudio.is/contributing/contributing-for-designers) - [Contributing Guide for Devs](https://docs.webstudio.is/contributing/contributing-for-developers) - [Github Discussions](https://github.com/webstudio-is/webstudio-community/discussions) - [Wishlist](https://github.com/webstudio-is/webstudio-community/discussions/categories/wishlist) - [Builder Issues Tracker](https://github.com/webstudio-is/webstudio/issues) - [Roadmap](https://github.com/orgs/webstudio-is/projects/11) ## Social Media - [Twitter](https://twitter.com/getwebstudio) - [Youtube](https://www.youtube.com/@getwebstudio) - [Discord](https://discord.gg/UNdyrDkq5r) ## Thanks <a href="https://www.lost-pixel.com/"><img src="https://user-images.githubusercontent.com/29632358/168112844-77e76a0d-b96f-4bc8-b753-cd39f4afd428.png" width="50" height="50" alt="Lost Pixel" /></a> Thanks to [Lost Pixel](https://www.lost-pixel.com/) for providing the visual testing platform that helps us review UI changes and catch visual regressions.

Open Source alternative to Webflow, check out our CMS launch https://webstudio.is/cms

Qovery/Replibyte

<p align="center"> <img src="assets/RepliByte%20Logo.png" alt="replibyte logo"/> </p> <h3 align="center">Seed Your Development Database With Real Data ⚡️</h3> <p align="center">Replibyte is a blazingly fast tool to seed your databases with your production data while keeping sensitive data safe 🔥</p> <p align="center"> <a href="https://opensource.org/licenses/MIT"> <img alt="MIT License" src="https://img.shields.io/badge/License-MIT-yellow.svg"> </a> <img src="https://img.shields.io/badge/stability-stable-green.svg?style=flat-square" alt="stable badge"> <img src="https://img.shields.io/badge/stability-stable-green.svg?style=flat-square" alt="stable badge"> <img src="https://github.com/Qovery/replibyte/actions/workflows/build-and-test.yml/badge.svg?style=flat-square" alt="Build and Tests"> <a href="https://discord.qovery.com"> <img alt="Discord" src="https://img.shields.io/discord/688766934917185556?label=discord&style=flat-square"> </a> </p> <p align="center"> <a href="https://runacap.com/ross-index/q3-2022/" target="_blank" rel="noopener"> <img style="width: 260px; height: 56px" src="https://runacap.com/wp-content/uploads/2022/10/ROSS_badge_black_Q3_2022.svg" alt="ROSS Index - Fastest Growing Open-Source Startups in Q3 2022 | Runa Capital" width="260" height="56" /> </a> </p> ## Prerequisites - MacOSX / Linux / Windows - Nothing more! Replibyte is stateless and does not require anything special. ## Usage Create a dump ```shell replibyte -c conf.yaml dump create ``` List all dumps ```shell replibyte -c conf.yaml dump list type name size when compressed encrypted PostgreSQL dump-1647706359405 154MB Yesterday at 03:00 am true true PostgreSQL dump-1647731334517 152MB 2 days ago at 03:00 am true true PostgreSQL dump-1647734369306 149MB 3 days ago at 03:00 am true true ``` Restore the latest dump in a local container ```shell replibyte -c conf.yaml dump restore local -v latest -i postgres -p 5432 ``` Restore the latest dump in a remote database ```shell replibyte -c conf.yaml dump restore remote -v latest ``` ## Features - [x] Support data dump and restore for PostgreSQL, MySQL and MongoDB - [x] Analyze your data schema 🔎 - [x] Replace sensitive data with fake data - [x] Works on large database (> 10GB) - [x] Database Subsetting: Scale down a production database to a more reasonable size 🔥 - [x] Start a local database with the production data in a single command 🔥 - [x] On-the-fly data (de)compression (Zlib) - [x] On-the-fly data de/encryption (AES-256) - [x] Fully stateless (no server, no daemon) and lightweight binary 🍃 - [x] Use [custom transformers](examples/wasm) Here are the features we plan to support - [ ] Auto-detect and version database schema change - [ ] Auto-detect sensitive fields - [ ] Auto-clean backed up data ## Getting Started 1. [How Replibyte works](https://www.replibyte.com/docs/how-replibyte-works) 2. Initial setup: 1. [Install](https://www.replibyte.com/docs/getting-started/installation) 2. [Configure](https://www.replibyte.com/docs/getting-started/configuration) 3. Step-by-step guides: 1. [Create a dump](https://www.replibyte.com/docs/guides/create-a-dump) 2. [Restore a dump](https://www.replibyte.com/docs/guides/restore-a-dump) 3. [Subset a dump](https://www.replibyte.com/docs/guides/subset-a-dump) 4. [Delete a dump](https://www.replibyte.com/docs/guides/delete-a-dump) 5. Deploy Replibyte 1. [Container](https://www.replibyte.com/docs/guides/deploy-replibyte/container) 2. [Qovery](https://www.replibyte.com/docs/guides/deploy-replibyte/qovery) ## Demo [](https://www.youtube.com/watch?v=IKeLnZvECQw) ## Contributing Check [here](https://www.replibyte.com/docs/contributing). ## Thanks Thanks to all people sharing their ideas to make Replibyte better. We do appreciate it. I would also thank [AirByte](https://airbyte.com/), a great product and a trustworthy source of inspiration for this project. --- Replibyte is initiated and maintained by [Qovery](https://www.qovery.com?ref=replibyte-readme).

Seed your development database with real data ⚡️

database,cloud,cloudnative,rust,rust-lang,postgresql,s3,backup,aws,postgres

blacklanternsecurity/bbot

[](https://github.com/blacklanternsecurity/bbot) # BEE·bot ### A Recursive Internet Scanner for Hackers. [](https://www.python.org) [](https://github.com/blacklanternsecurity/bbot/blob/dev/LICENSE) [](https://forum.defcon.org/node/246338) [](https://pepy.tech/project/bbot) [](https://github.com/psf/black) [](https://github.com/blacklanternsecurity/bbot/actions?query=workflow%3A"tests") [](https://codecov.io/gh/blacklanternsecurity/bbot) [](https://discord.com/invite/PZqkgxu5SA) BBOT (Bighuge BLS OSINT Tool) is a recursive internet scanner inspired by [Spiderfoot](https://github.com/smicallef/spiderfoot), but designed to be faster, more reliable, and friendlier to pentesters, bug bounty hunters, and developers. Special features include: - Support for Multiple Targets - Web Screenshots - Suite of Offensive Web Modules - AI-powered Subdomain Mutations - Native Output to Neo4j (and more) - Python API + Developer [Documentation](https://www.blacklanternsecurity.com/bbot/) https://github.com/blacklanternsecurity/bbot/assets/20261699/742df3fe-5d1f-4aea-83f6-f990657bf695 _A BBOT scan in real-time - visualization with [VivaGraphJS](https://github.com/blacklanternsecurity/bbot-vivagraphjs)_ ## Quick Start Guide Below are some short help sections to get you up and running. <details> <summary><b>Installation ( Pip )</b></summary> Note: BBOT's [PyPi package](https://pypi.org/project/bbot/) requires Linux and Python 3.9+. ```bash # stable version pipx install bbot # bleeding edge (dev branch) pipx install --pip-args '\--pre' bbot bbot --help ``` </details> <details> <summary><b>Installation ( Docker )</b></summary> [Docker images](https://hub.docker.com/r/blacklanternsecurity/bbot) are provided, along with helper script `bbot-docker.sh` to persist your scan data. ```bash # bleeding edge (dev) docker run -it blacklanternsecurity/bbot --help # stable docker run -it blacklanternsecurity/bbot:stable --help # helper script git clone https://github.com/blacklanternsecurity/bbot && cd bbot ./bbot-docker.sh --help ``` </details> <details> <summary><b>Example Usage</b></summary> ## Example Commands Scan output, logs, etc. are saved to `~/.bbot`. For more detailed examples and explanations, see [Scanning](https://www.blacklanternsecurity.com/bbot/scanning). <!-- BBOT EXAMPLE COMMANDS --> **Subdomains:** ```bash # Perform a full subdomain enumeration on evilcorp.com bbot -t evilcorp.com -f subdomain-enum ``` **Subdomains (passive only):** ```bash # Perform a passive-only subdomain enumeration on evilcorp.com bbot -t evilcorp.com -f subdomain-enum -rf passive ``` **Subdomains + port scan + web screenshots:** ```bash # Port-scan every subdomain, screenshot every webpage, output to current directory bbot -t evilcorp.com -f subdomain-enum -m nmap gowitness -n my_scan -o . ``` **Subdomains + basic web scan:** ```bash # A basic web scan includes wappalyzer, robots.txt, and other non-intrusive web modules bbot -t evilcorp.com -f subdomain-enum web-basic ``` **Web spider:** ```bash # Crawl www.evilcorp.com up to a max depth of 2, automatically extracting emails, secrets, etc. bbot -t www.evilcorp.com -m httpx robots badsecrets secretsdb -c web_spider_distance=2 web_spider_depth=2 ``` **Everything everywhere all at once:** ```bash # Subdomains, emails, cloud buckets, port scan, basic web, web screenshots, nuclei bbot -t evilcorp.com -f subdomain-enum email-enum cloud-enum web-basic -m nmap gowitness nuclei --allow-deadly ``` <!-- END BBOT EXAMPLE COMMANDS --> ## Targets BBOT accepts an unlimited number of targets via `-t`. You can specify targets either directly on the command line or in files (or both!): ```bash bbot -t evilcorp.com evilcorp.org 1.2.3.0/24 -f subdomain-enum ``` Targets can be any of the following: - `DNS_NAME` (`evilcorp.com`) - `IP_ADDRESS` (`1.2.3.4`) - `IP_RANGE` (`1.2.3.0/24`) - `OPEN_TCP_PORT` (`192.168.0.1:80`) - `URL` (`https://www.evilcorp.com`) For more information, see [Targets](https://www.blacklanternsecurity.com/bbot/scanning/#targets-t). To learn how BBOT handles scope, see [Scope](https://www.blacklanternsecurity.com/bbot/scanning/#scope). ## API Keys Similar to Amass or Subfinder, BBOT supports API keys for various third-party services such as SecurityTrails, etc. The standard way to do this is to enter your API keys in **`~/.config/bbot/secrets.yml`**: ```yaml modules: shodan_dns: api_key: 4f41243847da693a4f356c0486114bc6 c99: api_key: 21a270d5f59c9b05813a72bb41707266 virustotal: api_key: dd5f0eee2e4a99b71a939bded450b246 securitytrails: api_key: d9a05c3fd9a514497713c54b4455d0b0 ``` If you like, you can also specify them on the command line: ```bash bbot -c modules.virustotal.api_key=dd5f0eee2e4a99b71a939bded450b246 ``` For details, see [Configuration](https://www.blacklanternsecurity.com/bbot/scanning/configuration/) ## BBOT as a Python Library BBOT exposes a Python API that allows it to be used for all kinds of fun and nefarious purposes, like a [Discord Bot](https://www.blacklanternsecurity.com/bbot/dev/#bbot-python-library-advanced-usage#discord-bot-example) that responds to the `/scan` command.  **Synchronous** ```python from bbot.scanner import Scanner # any number of targets can be specified scan = Scanner("example.com", "scanme.nmap.org", modules=["nmap", "sslcert"]) for event in scan.start(): print(event.json()) ``` **Asynchronous** ```python from bbot.scanner import Scanner async def main(): scan = Scanner("example.com", "scanme.nmap.org", modules=["nmap", "sslcert"]) async for event in scan.async_start(): print(event.json()) import asyncio asyncio.run(main()) ``` </details> <details> <summary><b>Documentation - Table of Contents</b></summary> <!-- BBOT DOCS TOC --> - **User Manual** - **Basics** - [Getting Started](https://www.blacklanternsecurity.com/bbot/) - [How it Works](https://www.blacklanternsecurity.com/bbot/how_it_works) - [Comparison to Other Tools](https://www.blacklanternsecurity.com/bbot/comparison) - **Scanning** - [Scanning Overview](https://www.blacklanternsecurity.com/bbot/scanning/) - [Events](https://www.blacklanternsecurity.com/bbot/scanning/events) - [Output](https://www.blacklanternsecurity.com/bbot/scanning/output) - [Tips and Tricks](https://www.blacklanternsecurity.com/bbot/scanning/tips_and_tricks) - [Advanced Usage](https://www.blacklanternsecurity.com/bbot/scanning/advanced) - [Configuration](https://www.blacklanternsecurity.com/bbot/scanning/configuration) - **Modules** - [List of Modules](https://www.blacklanternsecurity.com/bbot/modules/list_of_modules) - [Nuclei](https://www.blacklanternsecurity.com/bbot/modules/nuclei) - **Misc** - [Release History](https://www.blacklanternsecurity.com/bbot/release_history) - [Troubleshooting](https://www.blacklanternsecurity.com/bbot/troubleshooting) - **Developer Manual** - [How to Write a Module](https://www.blacklanternsecurity.com/bbot/contribution) - [Development Overview](https://www.blacklanternsecurity.com/bbot/dev/) - [Scanner](https://www.blacklanternsecurity.com/bbot/dev/scanner) - [Event](https://www.blacklanternsecurity.com/bbot/dev/event) - [Target](https://www.blacklanternsecurity.com/bbot/dev/target) - [BaseModule](https://www.blacklanternsecurity.com/bbot/dev/basemodule) - **Helpers** - [Overview](https://www.blacklanternsecurity.com/bbot/dev/helpers/) - [Command](https://www.blacklanternsecurity.com/bbot/dev/helpers/command) - [DNS](https://www.blacklanternsecurity.com/bbot/dev/helpers/dns) - [Interactsh](https://www.blacklanternsecurity.com/bbot/dev/helpers/interactsh) - [Miscellaneous](https://www.blacklanternsecurity.com/bbot/dev/helpers/misc) - [Web](https://www.blacklanternsecurity.com/bbot/dev/helpers/web) - [Word Cloud](https://www.blacklanternsecurity.com/bbot/dev/helpers/wordcloud) <!-- END BBOT DOCS TOC --> </details> <details> <summary><b>Contribution</b></summary> BBOT is constantly being improved by the community. Every day it grows more powerful! We welcome contributions. Not just code, but ideas too! If you have an idea for a new feature, please let us know in [Discussions](https://github.com/blacklanternsecurity/bbot/discussions). If you want to get your hands dirty, see [Contribution](https://www.blacklanternsecurity.com/bbot/contribution/). There you can find setup instructions and a simple tutorial on how to write a BBOT module. We also have extensive [Developer Documentation](https://www.blacklanternsecurity.com/bbot/dev/). Thanks to these amazing people for contributing to BBOT! :heart: <p align="center"> <a href="https://github.com/blacklanternsecurity/bbot/graphs/contributors"> <img src="https://contrib.rocks/image?repo=blacklanternsecurity/bbot&max=500"> </a> </p> Special thanks to the following people who made BBOT possible: - @TheTechromancer for creating [BBOT](https://github.com/blacklanternsecurity/bbot) - @liquidsec for his extensive work on BBOT's web hacking features, including [badsecrets](https://github.com/blacklanternsecurity/badsecrets) - Steve Micallef (@smicallef) for creating Spiderfoot - @kerrymilan for his Neo4j and Ansible expertise - @aconite33 and @amiremami for their ruthless testing - Aleksei Kornev (@alekseiko) for allowing us ownership of the bbot Pypi repository <3 </details> ## Comparison to Other Tools BBOT consistently finds 20-50% more subdomains than other tools. The bigger the domain, the bigger the difference. To learn how this is possible, see [How It Works](https://www.blacklanternsecurity.com/bbot/how_it_works/).  ## BBOT Modules By Flag For a full list of modules, including the data types consumed and emitted by each one, see [List of Modules](https://www.blacklanternsecurity.com/bbot/modules/list_of_modules/). <!-- BBOT MODULE FLAGS --> | Flag | # Modules | Description | Modules | |------------------|-------------|----------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | safe | 82 | Non-intrusive, safe to run | affiliates, aggregate, ajaxpro, anubisdb, asn, azure_realm, azure_tenant, baddns, baddns_zone, badsecrets, bevigil, binaryedge, bucket_amazon, bucket_azure, bucket_digitalocean, bucket_file_enum, bucket_firebase, bucket_google, builtwith, c99, censys, certspotter, chaos, code_repository, columbus, credshed, crobat, crt, dehashed, digitorus, dnscommonsrv, dnsdumpster, docker_pull, dockerhub, emailformat, filedownload, fingerprintx, fullhunt, git, git_clone, github_codesearch, github_org, github_workflows, gitlab, gowitness, hackertarget, httpx, hunt, hunterio, iis_shortnames, internetdb, ip2location, ipstack, leakix, myssl, newsletters, ntlm, oauth, otx, passivetotal, pgp, postman, rapiddns, riddler, robots, secretsdb, securitytrails, shodan_dns, sitedossier, skymem, social, sslcert, subdomaincenter, sublist3r, threatminer, trufflehog, urlscan, viewdns, virustotal, wappalyzer, wayback, zoomeye | | passive | 62 | Never connects to target systems | affiliates, aggregate, anubisdb, asn, azure_realm, azure_tenant, bevigil, binaryedge, bucket_file_enum, builtwith, c99, censys, certspotter, chaos, code_repository, columbus, credshed, crobat, crt, dehashed, digitorus, dnscommonsrv, dnsdumpster, docker_pull, dockerhub, emailformat, excavate, fullhunt, git_clone, github_codesearch, github_org, github_workflows, hackertarget, hunterio, internetdb, ip2location, ipneighbor, ipstack, leakix, massdns, myssl, otx, passivetotal, pgp, postman, rapiddns, riddler, securitytrails, shodan_dns, sitedossier, skymem, social, speculate, subdomaincenter, sublist3r, threatminer, trufflehog, urlscan, viewdns, virustotal, wayback, zoomeye | | subdomain-enum | 45 | Enumerates subdomains | anubisdb, asn, azure_realm, azure_tenant, baddns_zone, bevigil, binaryedge, builtwith, c99, censys, certspotter, chaos, columbus, crt, digitorus, dnscommonsrv, dnsdumpster, fullhunt, github_codesearch, github_org, hackertarget, httpx, hunterio, internetdb, ipneighbor, leakix, massdns, myssl, oauth, otx, passivetotal, postman, rapiddns, riddler, securitytrails, shodan_dns, sitedossier, sslcert, subdomaincenter, subdomains, threatminer, urlscan, virustotal, wayback, zoomeye | | active | 42 | Makes active connections to target systems | ajaxpro, baddns, baddns_zone, badsecrets, bucket_amazon, bucket_azure, bucket_digitalocean, bucket_firebase, bucket_google, bypass403, dastardly, dotnetnuke, ffuf, ffuf_shortnames, filedownload, fingerprintx, generic_ssrf, git, gitlab, gowitness, host_header, httpx, hunt, iis_shortnames, masscan, newsletters, nmap, ntlm, nuclei, oauth, paramminer_cookies, paramminer_getparams, paramminer_headers, robots, secretsdb, smuggler, sslcert, telerik, url_manipulation, vhost, wafw00f, wappalyzer | | web-thorough | 29 | More advanced web scanning functionality | ajaxpro, azure_realm, badsecrets, bucket_amazon, bucket_azure, bucket_digitalocean, bucket_firebase, bucket_google, bypass403, dastardly, dotnetnuke, ffuf_shortnames, filedownload, generic_ssrf, git, host_header, httpx, hunt, iis_shortnames, nmap, ntlm, oauth, robots, secretsdb, smuggler, sslcert, telerik, url_manipulation, wappalyzer | | aggressive | 20 | Generates a large amount of network traffic | bypass403, dastardly, dotnetnuke, ffuf, ffuf_shortnames, generic_ssrf, host_header, ipneighbor, masscan, massdns, nmap, nuclei, paramminer_cookies, paramminer_getparams, paramminer_headers, smuggler, telerik, url_manipulation, vhost, wafw00f | | web-basic | 17 | Basic, non-intrusive web scan functionality | azure_realm, baddns, badsecrets, bucket_amazon, bucket_azure, bucket_firebase, bucket_google, filedownload, git, httpx, iis_shortnames, ntlm, oauth, robots, secretsdb, sslcert, wappalyzer | | cloud-enum | 12 | Enumerates cloud resources | azure_realm, azure_tenant, baddns, baddns_zone, bucket_amazon, bucket_azure, bucket_digitalocean, bucket_file_enum, bucket_firebase, bucket_google, httpx, oauth | | slow | 10 | May take a long time to complete | bucket_digitalocean, dastardly, docker_pull, fingerprintx, git_clone, paramminer_cookies, paramminer_getparams, paramminer_headers, smuggler, vhost | | affiliates | 8 | Discovers affiliated hostnames/domains | affiliates, azure_realm, azure_tenant, builtwith, oauth, sslcert, viewdns, zoomeye | | email-enum | 7 | Enumerates email addresses | dehashed, emailformat, emails, hunterio, pgp, skymem, sslcert | | deadly | 4 | Highly aggressive | dastardly, ffuf, nuclei, vhost | | portscan | 3 | Discovers open ports | internetdb, masscan, nmap | | web-paramminer | 3 | Discovers HTTP parameters through brute-force | paramminer_cookies, paramminer_getparams, paramminer_headers | | baddns | 2 | Runs all modules from the DNS auditing tool BadDNS | baddns, baddns_zone | | iis-shortnames | 2 | Scans for IIS Shortname vulnerability | ffuf_shortnames, iis_shortnames | | report | 2 | Generates a report at the end of the scan | affiliates, asn | | social-enum | 2 | Enumerates social media | httpx, social | | repo-enum | 1 | Enumerates code repositories | code_repository | | service-enum | 1 | Identifies protocols running on open ports | fingerprintx | | subdomain-hijack | 1 | Detects hijackable subdomains | baddns | | web-screenshots | 1 | Takes screenshots of web pages | gowitness | <!-- END BBOT MODULE FLAGS --> ## BBOT Output Modules BBOT can save its data to TXT, CSV, JSON, and tons of other destinations including [Neo4j](https://www.blacklanternsecurity.com/bbot/scanning/output/#neo4j), [Splunk](https://www.blacklanternsecurity.com/bbot/scanning/output/#splunk), and [Discord](https://www.blacklanternsecurity.com/bbot/scanning/output/#discord-slack-teams). For instructions on how to use these, see [Output Modules](https://www.blacklanternsecurity.com/bbot/scanning/output). <!-- BBOT OUTPUT MODULES --> | Module | Type | Needs API Key | Description | Flags | Consumed Events | Produced Events | |-----------------|--------|-----------------|-----------------------------------------------------------------------------------------|----------------|--------------------------------------------------------------------------------------------------|---------------------------| | asset_inventory | output | No | Merge hosts, open ports, technologies, findings, etc. into a single asset inventory CSV | | DNS_NAME, FINDING, HTTP_RESPONSE, IP_ADDRESS, OPEN_TCP_PORT, TECHNOLOGY, URL, VULNERABILITY, WAF | IP_ADDRESS, OPEN_TCP_PORT | | csv | output | No | Output to CSV | | * | | | discord | output | No | Message a Discord channel when certain events are encountered | | * | | | emails | output | No | Output any email addresses found belonging to the target domain | email-enum | EMAIL_ADDRESS | | | http | output | No | Send every event to a custom URL via a web request | | * | | | human | output | No | Output to text | | * | | | json | output | No | Output to Newline-Delimited JSON (NDJSON) | | * | | | neo4j | output | No | Output to Neo4j | | * | | | python | output | No | Output via Python API | | * | | | slack | output | No | Message a Slack channel when certain events are encountered | | * | | | splunk | output | No | Send every event to a splunk instance through HTTP Event Collector | | * | | | subdomains | output | No | Output only resolved, in-scope subdomains | subdomain-enum | DNS_NAME, DNS_NAME_UNRESOLVED | | | teams | output | No | Message a Teams channel when certain events are encountered | | * | | | web_report | output | No | Create a markdown report with web assets | | FINDING, TECHNOLOGY, URL, VHOST, VULNERABILITY | | | websocket | output | No | Output to websockets | | * | | <!-- END BBOT OUTPUT MODULES -->

A recursive internet scanner for hackers.

hacking,neo4j,osint,osint-framework,python,subdomain-enumeration,automation,recon,command-line-tool,cli

GreptimeTeam/greptimedb

<p align="center"> <picture> <source media="(prefers-color-scheme: light)" srcset="https://cdn.jsdelivr.net/gh/GreptimeTeam/greptimedb@main/docs/logo-text-padding.png"> <source media="(prefers-color-scheme: dark)" srcset="https://cdn.jsdelivr.net/gh/GreptimeTeam/greptimedb@main/docs/logo-text-padding-dark.png"> <img alt="GreptimeDB Logo" src="https://cdn.jsdelivr.net/gh/GreptimeTeam/greptimedb@main/docs/logo-text-padding.png" width="400px"> </picture> </p> <h1 align="center">Cloud-scale, Fast and Efficient Time Series Database</h1> <div align="center"> <h3 align="center"> <a href="https://greptime.com/product/cloud">GreptimeCloud</a> | <a href="https://docs.greptime.com/">User guide</a> | <a href="https://greptimedb.rs/">API Docs</a> | <a href="https://github.com/GreptimeTeam/greptimedb/issues/3412">Roadmap 2024</a> </h4> <a href="https://github.com/GreptimeTeam/greptimedb/releases/latest"> <img src="https://img.shields.io/github/v/release/GreptimeTeam/greptimedb.svg" alt="Version"/> </a> <a href="https://github.com/GreptimeTeam/greptimedb/releases/latest"> <img src="https://img.shields.io/github/release-date/GreptimeTeam/greptimedb.svg" alt="Releases"/> </a> <a href="https://hub.docker.com/r/greptime/greptimedb/"> <img src="https://img.shields.io/docker/pulls/greptime/greptimedb.svg" alt="Docker Pulls"/> </a> <a href="https://github.com/GreptimeTeam/greptimedb/actions/workflows/develop.yml"> <img src="https://github.com/GreptimeTeam/greptimedb/actions/workflows/develop.yml/badge.svg" alt="GitHub Actions"/> </a> <a href="https://codecov.io/gh/GrepTimeTeam/greptimedb"> <img src="https://codecov.io/gh/GrepTimeTeam/greptimedb/branch/main/graph/badge.svg?token=FITFDI3J3C" alt="Codecov"/> </a> <a href="https://github.com/greptimeTeam/greptimedb/blob/main/LICENSE"> <img src="https://img.shields.io/github/license/greptimeTeam/greptimedb" alt="License"/> </a> <br/> <a href="https://greptime.com/slack"> <img src="https://img.shields.io/badge/slack-GreptimeDB-0abd59?logo=slack&style=for-the-badge" alt="Slack"/> </a> <a href="https://twitter.com/greptime"> <img src="https://img.shields.io/badge/twitter-follow_us-1d9bf0.svg?style=for-the-badge" alt="Twitter"/> </a> <a href="https://www.linkedin.com/company/greptime/"> <img src="https://img.shields.io/badge/linkedin-connect_with_us-0a66c2.svg?style=for-the-badge" alt="LinkedIn"/> </a> </div> ## Introduction **GreptimeDB** is an open-source time-series database focusing on efficiency, scalability, and analytical capabilities. Designed to work on infrastructure of the cloud era, GreptimeDB benefits users with its elasticity and commodity storage, offering a fast and cost-effective **alternative to InfluxDB** and a **long-term storage for Prometheus**. ## Why GreptimeDB Our core developers have been building time-series data platforms for years. Based on our best-practices, GreptimeDB is born to give you: * **Easy horizontal scaling** Seamless scalability from a standalone binary at edge to a robust, highly available distributed cluster in cloud, with a transparent experience for both developers and administrators. * **Analyzing time-series data** Query your time-series data with SQL and PromQL. Use Python scripts to facilitate complex analytical tasks. * **Cloud-native distributed database** Fully open-source distributed cluster architecture that harnesses the power of cloud-native elastic computing resources. * **Performance and Cost-effective** Flexible indexing capabilities and distributed, parallel-processing query engine, tackling high cardinality issues down. Optimized columnar layout for handling time-series data; compacted, compressed, and stored on various storage backends, particularly cloud object storage with 50x cost efficiency. * **Compatible with InfluxDB, Prometheus and more protocols** Widely adopted database protocols and APIs, including MySQL, PostgreSQL, and Prometheus Remote Storage, etc. [Read more](https://docs.greptime.com/user-guide/clients/overview). ## Try GreptimeDB ### 1. [GreptimePlay](https://greptime.com/playground) Try out the features of GreptimeDB right from your browser. ### 2. [GreptimeCloud](https://console.greptime.cloud/) Start instantly with a free cluster. ### 3. Docker Image To install GreptimeDB locally, the recommended way is via Docker: ```shell docker pull greptime/greptimedb ``` Start a GreptimeDB container with: ```shell docker run --rm --name greptime --net=host greptime/greptimedb standalone start ``` Read more about [Installation](https://docs.greptime.com/getting-started/installation/overview) on docs. ## Getting Started * [Quickstart](https://docs.greptime.com/getting-started/quick-start/overview) * [Write Data](https://docs.greptime.com/user-guide/clients/overview) * [Query Data](https://docs.greptime.com/user-guide/query-data/overview) * [Operations](https://docs.greptime.com/user-guide/operations/overview) ## Build Check the prerequisite: * [Rust toolchain](https://www.rust-lang.org/tools/install) (nightly) * [Protobuf compiler](https://grpc.io/docs/protoc-installation/) (>= 3.15) * Python toolchain (optional): Required only if built with PyO3 backend. More detail for compiling with PyO3 can be found in its [documentation](https://pyo3.rs/v0.18.1/building_and_distribution#configuring-the-python-version). Build GreptimeDB binary: ```shell make ``` Run a standalone server: ```shell cargo run -- standalone start ``` ## Extension ### Dashboard - [The dashboard UI for GreptimeDB](https://github.com/GreptimeTeam/dashboard) ### SDK - [GreptimeDB Go Ingester](https://github.com/GreptimeTeam/greptimedb-ingester-go) - [GreptimeDB Java Ingester](https://github.com/GreptimeTeam/greptimedb-ingester-java) - [GreptimeDB C++ Ingester](https://github.com/GreptimeTeam/greptimedb-ingester-cpp) - [GreptimeDB Erlang Ingester](https://github.com/GreptimeTeam/greptimedb-ingester-erl) - [GreptimeDB Rust Ingester](https://github.com/GreptimeTeam/greptimedb-ingester-rust) - [GreptimeDB JavaScript Ingester](https://github.com/GreptimeTeam/greptimedb-ingester-js) ### Grafana Dashboard Our official Grafana dashboard is available at [grafana](grafana/README.md) directory. ## Project Status The current version has not yet reached General Availability version standards. In line with our Greptime 2024 Roadmap, we plan to achieve a production-level version with the update to v1.0 in August. [[Join Force]](https://github.com/GreptimeTeam/greptimedb/issues/3412) ## Community Our core team is thrilled to see you participate in any ways you like. When you are stuck, try to ask for help by filling an issue with a detailed description of what you were trying to do and what went wrong. If you have any questions or if you would like to get involved in our community, please check out: - GreptimeDB Community on [Slack](https://greptime.com/slack) - GreptimeDB [GitHub Discussions forum](https://github.com/GreptimeTeam/greptimedb/discussions) - Greptime official [website](https://greptime.com) In addition, you may: - View our official [Blog](https://greptime.com/blogs/) - Connect us with [Linkedin](https://www.linkedin.com/company/greptime/) - Follow us on [Twitter](https://twitter.com/greptime) ## License GreptimeDB uses the [Apache License 2.0](https://apache.org/licenses/LICENSE-2.0.txt) to strike a balance between open contributions and allowing you to use the software however you want. ## Contributing Please refer to [contribution guidelines](CONTRIBUTING.md) and [internal concepts docs](https://docs.greptime.com/contributor-guide/overview.html) for more information. ## Acknowledgement - GreptimeDB uses [Apache Arrow™](https://arrow.apache.org/) as the memory model and [Apache Parquet™](https://parquet.apache.org/) as the persistent file format. - GreptimeDB's query engine is powered by [Apache Arrow DataFusion™](https://arrow.apache.org/datafusion/). - [Apache OpenDAL™](https://opendal.apache.org) gives GreptimeDB a very general and elegant data access abstraction layer. - GreptimeDB's meta service is based on [etcd](https://etcd.io/). - GreptimeDB uses [RustPython](https://github.com/RustPython/RustPython) for experimental embedded python scripting.

An open-source, cloud-native, distributed time-series database with PromQL/SQL/Python supported. Available on GreptimeCloud.

cloud-native,database,distributed,rust,timeseries,sql,time-series,analytics,metrics,tsdb

tauri-apps/awesome-tauri

<!--lint disable awesome-heading awesome-toc awesome-github double-link --> <div align="center"> <h1>Awesome Tauri</h1> A curated collection of the best stuff from the Tauri ecosystem and community. <br /> [](https://awesome.re) </div> ## Table of Contents - [Getting Started](#getting-started) - [Guides](#guides) - [Tutorials](#tutorials) - [Templates](#templates) - [Development](#development) - [Plugins](#plugins) - [Integrations](#integrations) - [Articles](#articles) - [Applications](#applications) - [Audio & Video](#audio--video) - [ChatGPT clients](#chatgpt-clients) - [Data](#data) - [Developer tools](#developer-tools) - [Email & Feeds](#email--feeds) - [File management](#file-management) - [Finance](#finance) - [Gaming](#gaming) - [Information](#information) - [Learning](#learning) - [Networking](#networking) - [Office & Writing](#office--writing) - [Productivity](#productivity) - [Search](#search) - [Security](#security) - [Social media](#social-media) - [Utilities](#utilities) ## Getting Started ### Guides - [Introduction](https://tauri.app/about/intro/) ![officially maintained] - Official introduction to Tauri. - [Getting Started](https://tauri.app/v1/guides/getting-started/prerequisites/) ![officially maintained] - Official getting started with Tauri docs. - [create-tauri-app](https://github.com/tauri-apps/create-tauri-app) ![officially maintained] - Rapidly scaffold your Tauri app. ### Tutorials - [Create Tauri App with React](https://www.youtube.com/watch?v=zawhqLA7N9Y&ab_channel=chrisbiscardi) - Chris Biscardi shows how easy it is to wire up a Rust crate with a JS module and communicate between them. - [Publish to Apple's App Store](https://thinkgo.io/post/2023/02/publish_tauri_to_apples_app_store/) - Details all the steps needed to publish your Mac app to the app store. Includes a sample bash script. - [Tauri & ReactJS - Creating Modern Desktop Apps](https://youtube.com/playlist?list=PLmWYh0f8jKSjt9VC5sq2T3mFETasG2p2L) - Creating a modern desktop application with Tauri. ### Templates - [angular-tauri](https://github.com/maximegris/angular-tauri) - Angular with Typescript, SASS, and Hot Reload. - [tauri-angular-template](https://github.com/charlesxsh/tauri-angular-boilerplate) - Angular template - [tauri-astro-template](https://github.com/HuakunShen/tauri-astro-template) - Astro template - [tauri-bishop-template](https://github.com/RoseBlume/Bishop-Tauri-Template) - Minimized vanilla template designed for highschool students - [tauri-clojurescript-template](https://github.com/rome-user/tauri-clojurescript-template) - Minimal ClojureScript template with Shadow CLJS and React. - [tauri-deno-starter](https://github.com/marc2332/tauri-deno-starter) - React template using esbuild with Deno. - [tauri-leptos-template](https://gitlab.com/cristofa/tauri-leptos-template) - Leptos template - [tauri-nextjs-template](https://github.com/kvnxiao/tauri-nextjs-template) - Next.js (SSG) template, with TailwindCSS, opinionated linting, and GitHub Actions preconfigured. - [tauri-nuxt-template](https://github.com/HuakunShen/tauri-nuxt-template) - Nuxt3 template. - [tauri-preact-rsbuild-template](https://github.com/Alfredoes234/tauri-preact-rsbuild-template) - Preact template that uses rsbuild, rather than vite. - [tauri-react-mantine-vite-template](https://github.com/elibroftw/modern-desktop-app-template) - React Mantine template featuring custom titlebar for Windows, auto publish action, auto update, and more. - [tauri-react-parcel-template](https://github.com/henrhie/tauri-react-parcel-template) - React template with Parcel as build tool, TypeScript and hot module replacement. - [tauri-rescript-template](https://github.com/JonasKruckenberg/tauri-rescript-template) - Tauri, ReScript, and React template. - [tauri-solid-ts-tailwind-vite-template](https://github.com/AR10Dev/tauri-solid-ts-tailwind-vite) - SolidJS Template preconfigured to use Vite, TypeScript, Tailwind CSS, ESLint and Prettier. - [tauri-svelte-template](https://github.com/probablykasper/tauri-svelte-template) - Svelte template with cross-platform GitHub action builds, Vite, TypeScript, Svelte Preprocess, hot module replacement, ESLint and Prettier. - [tauri-sveltekit-template](https://github.com/deid84/tauri-sveltekit-admin-template) - SvelteKit Admin template with cross-platform GitHub action builds, Vite, TypeScript, Svelte Preprocess, hot module replacement, ESLint and Prettier. - [tauri-sycamore-template](https://github.com/JonasKruckenberg/tauri-sycamore-template) - Tauri and Sycamore template. - [tauri-vue-template](https://github.com/Uninen/tauri-vue-template) - Vue template with TypeScript, Vite + HMR, Vitest, Tailwind CSS, ESLint, and GitHub Actions. - [tauri-vue-template-2](https://github.com/skymen/tauri-vue-template) - Another vue template with Javascript, Vite, Pinia, Vue Router and Github Actions. - [tauri-yew-example](https://bitbucket.org/ftegtmeyer/tauri-yew-stopwatch/) - Simple stopwatch with Yew using commands and Tauri events. ## Development ### Plugins - [tauri-plugin-authenticator](https://github.com/tauri-apps/tauri-plugin-authenticator) ![officially maintained] - Interface with hardware security keys. - [tauri-plugin-log](https://github.com/tauri-apps/tauri-plugin-log) ![officially maintained] - Configurable logging. - [tauri-plugin-sql](https://github.com/tauri-apps/tauri-plugin-sql) ![officially maintained] - Interface with SQL databases. - [tauri-plugin-store](https://github.com/tauri-apps/tauri-plugin-store) ![officially maintained] - Persistent key value storage. - [tauri-plugin-stronghold](https://github.com/tauri-apps/tauri-plugin-stronghold) ![officially maintained] - Encrypted, secure, p2p database. - [tauri-plugin-window-state](https://github.com/tauri-apps/tauri-plugin-window-state) ![officially maintained] - Persist window sizes and positions. - [window-vibrancy](https://github.com/tauri-apps/window-vibrancy) ![officially maintained] - Make your windows vibrant. - [window-shadows](https://github.com/tauri-apps/window-shadows) ![officially maintained] - Add native shadows to your windows. - [tauri-plugin-positioner](https://github.com/JonasKruckenberg/tauri-plugin-positioner) - Move windows to common locations. - [tauri-plugin-graphql](https://github.com/JonasKruckenberg/tauri-plugin-graphql) - Type-safe IPC for Tauri using GraphQL. - [sentry-tauri](https://github.com/timfish/sentry-tauri) - Capture JavaScript errors, Rust panics and native crash minidumps to Sentry. - [tauri-plugin-aptabase](https://github.com/aptabase/tauri-plugin-aptabase) - Privacy-first and minimalist analytics for desktop and mobile apps. - [tauri-plugin-clipboard](https://github.com/CrossCopy/tauri-plugin-clipboard) - Clipboard plugin for reading/writing clipboard text/image, and monitoring clipboard update. - [taurpc](https://github.com/MatsDK/TauRPC) - Typesafe IPC wrapper for Tauri commands and events. - [tauri-plugin-context-menu](https://github.com/c2r0b/tauri-plugin-context-menu) - Native context menu. - [tauri-plugin-network](https://github.com/HuakunShen/tauri-plugin-network) - Tools for reading network information and scanning network. - [tauri-plugin-serialport](https://github.com/deid84/tauri-plugin-serialport) - Cross-compatible serialport communication tool. - [tauri-plugin-system-info](https://github.com/HuakunShen/tauri-plugin-system-info) - Detailed system information. - [tauri-plugin-theme](https://github.com/wyhaya/tauri-plugin-theme) - Dynamically change Tauri App theme. - [tauri-awesome-rpc](https://github.com/ahkohd/tauri-awesome-rpc) - Custom invoke system that leverages WebSocket. - [tauri-nspanel](https://github.com/ahkohd/tauri-nspanel) - Convert a window to panel. - [tauri-plugin-nosleep](https://github.com/pevers/tauri-plugin-nosleep/) - Block the power save functionality in the OS. ### Integrations - [Astrodon](https://github.com/astrodon/astrodon) - Make Tauri desktop apps with Deno. - [Tauri Specta](https://github.com/oscartbeaumont/tauri-specta) - Completely typesafe Tauri commands. - [axios-tauri-adapter](https://git.kaki87.net/KaKi87/axios-tauri-adapter) - `axios` adapter for the `@tauri-apps/api/http` module. - [axios-tauri-api-adapter](https://github.com/persiliao/axios-tauri-api-adapter) - Makes it easy to use Axios in Tauri, `axios` adapter for the `@tauri-apps/api/http` module. - [ngx-tauri](https://codeberg.org/crapsilon/ngx-tauri) - Small lib to wrap around functions from tauri modules, to integrate easier with Angular. - [svelte-tauri-filedrop](https://github.com/probablykasper/svelte-tauri-filedrop) - File drop handling component for Svelte. - [tauri-macos-menubar-app-example](https://github.com/ahkohd/tauri-macos-menubar-app-example) - Example macOS Menubar app project. - [tauri-macos-spotlight-example](https://github.com/ahkohd/tauri-macos-spotlight-example) - Example macOS Spotlight app project. - [tauri-update-cloudflare](https://github.com/KilleenCode/tauri-update-cloudflare) - One-click deploy a Tauri Update Server to Cloudflare. - [tauri-update-server](https://git.kaki87.net/KaKi87/tauri-update-server) - Automatically interface the Tauri updater with git repository releases. - [vite-plugin-tauri](https://github.com/amrbashir/vite-plugin-tauri) - Integrate Tauri in a Vite project to build cross-platform apps. ### Articles - [Getting Started Using Tauri Mobile](https://medium.com/p/6f90de5b098) ![paid] - Ed Rutherford outlines how to create a mobile app with Tauri. - [How to use local SQLite database with Tauri and Rust](https://blog.moonguard.dev/how-to-use-local-sqlite-database-with-tauri) - Guide to setup and use SQLite database with Tauri and Rust. - [Managing State in Desktop Applications with Rust and Tauri](https://blog.moonguard.dev/manage-state-with-tauri) - How to share and manage any kind of state globally in Tauri apps. - [Setting up Actix Web in a Tauri App](https://blog.moonguard.dev/setting-up-actix-in-tauri) - How to setup a HTTP server with Tauri and Actix Web. - [Tauri's async process](https://rfdonnelly.github.io/posts/tauri-async-rust-process/) - Rob Donnelly dives deep into Async with Tauri. ## Applications ### Audio & Video - [Cider](https://cider.sh) ![closed source] - 3rd Party Client for Apple Music, Complete with Audio Lab. - [Curses](https://github.com/mmpneo/curses) - Speech-to-Text and Text-to-Speech captions for OBS, VRChat, Twitch chat and more. - [Douyin Downloader](https://github.com/lzdyes/douyin-downloader) - Cross-platform douyin video downloader. - [Feiyu Player](https://github.com/idootop/feiyu-player) - Cross-platform online video player where beauty meets functionality. - [Hypetrigger](https://hypetrigger.io/) ![closed source] - Detect highlight clips in video with FFMPEG + Tensorflow on the GPU. - [Jellyfin Vue](https://github.com/jellyfin/jellyfin-vue) - GUI client for a Jellyfin server based on Vue.js and Tauri. - [mediarepo](https://github.com/Trivernis/mediarepo) - Tag-based media management application. - [Mr Tagger](https://github.com/probablykasper/mr-tagger) - Music file tagging app. - [Lofi Engine](https://github.com/meel-hd/lofi-engine) - Generate Lo-Fi music on the go and locally. - [Watson.ai](https://github.com/LatentDream/watson.ai) - Easily record and extract the most important information from your meetings. - [XGetter](https://github.com/xgetter-team/xgetter) ![closed source]- Cross-platform GUI to download videos and audio from Youtube, Facebook, X(Twitter), Instagram, Tiktok and more. - [yt-dlp GUI](https://github.com/gaeljacquin/yt-dlp-gui) - Cross-platform GUI client for the `yt-dlp` command-line audio/video downloader. ### ChatGPT clients - [chatbox](https://github.com/Bin-Huang/chatbox) - Cross-platform desktop application for ChatGPT API (OpenAI API), also a prompt debugging and management tool. - [ChatGPT](https://github.com/lencx/ChatGPT) - Cross-platform ChatGPT desktop application. - [ChatGPT App](https://github.com/Poordeveloper/chatgpt-app) - Cross-platform ChatGPT App and more. - [ChatGPT-Desktop](https://github.com/Synaptrix/ChatGPT-Desktop) - Cross-platform productivity ChatGPT assistant launcher. - [Orion](https://github.com/taecontrol/orion) - Cross-platform app that lets you create multiple AI assistants with specific goals powered with ChatGPT. - [QuickGPT](https://github.com/dubisdev/quickgpt) - Lightweight AI assistant for Windows. - [Yack](https://github.com/rajatkulkarni95/yack) - Spotlight like app for interfacing with GPT APIs ### Data - [BS Redis Desktop Client](https://github.com/fuyoo/bs-redis-desktop-client) - The Best Surprise Redis Desktop Client. - [Dataflare](https://dataflare.app) ![closed source] ![paid] - Simple and elegant database manager. - [Duckling](https://github.com/l1xnan/duckling) - Lightweight and fast viewer for csv/parquet files and databases such as DuckDB, SQLite, PostgreSQL, MySQL, Clickhouse, etc. - [Mason](https://mason.app) ![closed source] - Seamlessly query, visualize and share data with your team. - [Noir](https://noirdb.dev) - Keyboard-driven database management client. - [pgMagic🪄](https://pgmagic.app/?ref=awesometauri) ![closed source] ![paid] - GUI client to talk to Postgres in SQL or with natural language. ### Developer tools - [AHQ Store](https://github.com/ahqsoftwares/tauri-ahq-store) - Publish, Update and Install apps to the Windows-specific AHQ Store. - [AppCenter Companion](https://github.com/zenoxs/tauri-appcenter-companion) - Regroup, build and track your `VS App Center` apps. - [AppHub](https://github.com/francesco-gaglione/AppHub) - Streamlines .appImage package installation, management, and uninstallation through an intuitive Linux desktop interface. - [Aptakube](https://aptakube.com/) ![closed source] - Multi-cluster Kubernetes UI. - [claws](https://clawsapp.com/) ![closed source] - Visual interface for the AWS CLI. - [CrabNebula DevTools](https://crabnebula.dev/devtools) - Visual tool for understanding your app. Optimize the development process with easy debugging and profiling. - [CrabNebula DevTools Premium](https://crabnebula.dev/devtools) ![closed source] ![paid] - Optimize the development process with easy debugging and profiling. Debug the Rust portion of your app with the same comfort as JavaScript! - [DevBox](https://www.dev-box.app/) ![closed source] - Many useful tools for developers, like generators, viewers, converters, etc. - [DevClean](https://github.com/HuakunShen/devclean) - Clean up development environment with ease. - [DevTools-X](https://github.com/fosslife/devtools-x) - Collection of 30+ cross platform development utilities. - [Dropcode](https://github.com/egoist/dropcode) - Simple and lightweight code snippet manager. - [Echoo](https://github.com/zsmatrix62/echoo-app) - Offline/Online utilities for developers on MacOS & Windows. - [GitButler](https://gitbutler.com) - GitButler is a new Source Code Management system. - [GitLight](https://github.com/colinlienard/gitlight) - GitHub & GitLab notifications on your desktop. - [JET Pilot](https://www.jet-pilot.app) - Kubernetes desktop client that focuses on less clutter, speed and good looks. - [Hoppscotch](https://hoppscotch.com/download) ![closed source] - Trusted by millions of developers to build, test and share APIs. - [Keadex Mina](https://github.com/keadex/keadex) - Open Source, serverless IDE to easily code and organize at a scale C4 model diagrams. - [KFtray](https://github.com/hcavarsan/kftray) - A tray application that manages port forwarding in Kubernetes. - [Soda](https://github.com/Web3-Builders-Alliance/soda) - Generate source code from an IDL. - [Pake](https://github.com/tw93/Pake) - Turn any webpage into a desktop app with Rust with ease. - [Rivet](https://github.com/Ironclad/rivet) - Visual programming environment for creating AI features and agents. - [TableX](https://tablex-tan.vercel.app/) - Table viewer for modern developers - [Tauri Mobile Test](https://github.com/dedSyn4ps3/tauri-mobile-test) - Create and build cross-platform mobile applications. - [Testfully](https://testfully.io/) ![closed source] ![paid] - Offline API Client & Testing tool. - [verbcode](https://verbcode.staaph.com/) ![closed source] - Simplify your localization journey. - [Yaak](https://yaak.app) ![closed source] - Interact with REST and GraphQL APIs. ### Email & Feeds - [Alduin](https://alduin.stouder.io/) - Alduin is a free and open source RSS, Atom and JSON feed reader that allows you to keep track of your favorite websites. - [Aleph](https://github.com/chezhe/aleph) - Aleph is an RSS reader & podcast client. - [BULKUS](https://github.com/KM8Oz/BULKUS) - Email validation software. - [Lettura](https://github.com/zhanglun/lettura) - Open-source feed reader for macOS. - [mdsilo Desktop](https://github.com/mdSilo/mdSilo-app) - Feed reader and knowledge base. ### File management - [enassi](https://github.com/enassi/enassi) - Encryption assistant that encrypts and stores your notes and files. - [EzUp](https://github.com/HuakunShen/ezup) - File and Image uploader. Designed for blog writing and note taking. - [Orange](https://github.com/naaive/orange) - Cross-platform file search engine that can quickly locate files or folders based on keywords. - [Payload](https://payload.app/) ![closed source] - Drag & drop file transfers over local networks. - [Spacedrive](https://github.com/spacedriveapp/spacedrive) - A file explorer from the future. - [SquirrelDisk](https://github.com/adileo/squirreldisk) - Beautiful cross-platform disk usage analysis tool. - [Time Machine Inspector](https://github.com/probablykasper/time-machine-inspector) - Find out what's taking up your Time Machine backup space. - [Xplorer](https://github.com/kimlimjustin/xplorer) - Customizable, modern and cross-platform File Explorer. ### Finance - [Compotes](https://github.com/Orbitale/Compotes) - Local bank account operations storage to vizualize them as graphs and customize them with rules and tags for better filtering. - [CryptoBal](https://github.com/Rabbit-Company/CryptoBal-Desktop) - Desktop application for monitoring your crypto assets. - [Ghorbu Wallet](https://github.com/matthias-wright/ghorbu-wallet) - Cross-platform desktop HD wallet for Bitcoin. - [nym-wallet](https://github.com/nymtech/nym/tree/develop/nym-wallet) - The Nym desktop wallet enables you to use the Nym network and take advantage of its key capabilities. - [UsTaxes](https://github.com/ustaxes/ustaxes) - Free, private, open-source US tax filings. ### Gaming - [9Launcher](https://github.com/wearrrrr/9Launcher) - Modern Cross-platform launcher for Touhou Project Games. - [BestCraft](https://github.com/Tnze/ffxiv-best-craft) - Crafting simulator with solver algorithms for Final Fantasy XIV(FF14). - [BetterFleet](https://github.com/zelytra/BetterFleet) - Help players of Sea of Thieves create an alliance server. - [clear](https://clear.adithya.zip) - Clean and minimalist video game library manager and launcher. - [CubeShuffle](https://github.com/philipborg/CubeShuffle) - Card game shuffling utility. - [En Croissant](https://github.com/franciscoBSalgueiro/en-croissant) - Chess database and game analysis app. - [FishLauncher](https://github.com/fishfight/FishLauncher) - Cross-platform launcher for `Fish Fight`. - [OpenGOAL](https://github.com/open-goal/launcher) - Cross-platform installer, mod-manager and launcher for `OpenGOAL`; the reverse engineered PC ports of the Jak and Daxter series. - [OyasumiVR](https://github.com/Raphiiko/OyasumiVR) - Software that helps you sleep in virtual reality, for use with SteamVR, VRChat, and more. - [Resolute](https://github.com/Gawdl3y/Resolute) - User-friendly, cross-platform mod manager for the game Resonite. - [Steam Art Manager](https://github.com/Tormak9970/Steam-Art-Manager) - Tool for customizing the art of your Steam games. - [Teyvat Guide](https://github.com/BTMuli/TeyvatGuide) - Game Tool for Genshin Impact player. ### Information - [Seismic](https://github.com/breadthe/seismic) - Taskbar app for USGS earthquake tracking. - [Stockman](https://github.com/awkj/stockman) - Display stock info on mac menubar. - [Watchcoin](https://github.com/lifecoder1988/tauri-watch-coin) - Display cypto price on OS menubar without a window. ### Learning - [Manjaro Starter](https://github.com/oguzkaganeren/manjaro-starter) - Documentation and support app for new Manjaro users. - [Piano Trainer](https://github.com/ZaneH/piano-trainer) - Practice piano chords, scales, and more using your MIDI keyboard. - [Solars](https://github.com/hiltontj/solars) - Visualize the planets of our solar system. - [Syre](https://github.com/syre-data/syre) - Scientific data assistant. - [Rosary](https://github.com/Roseblume/Rosary) - Study Christianity. ### Networking - [Clash Verge Rev](https://github.com/clash-verge-rev/clash-verge-rev) - Continuation of Clash Verge, a rule-based proxy. - [CyberAPI](https://github.com/vicanso/cyberapi) - API tool client for developer. - [Jexpe](https://github.com/jexpe-apps/jexpe) - Cross-platform, open source SSH and SFTP client that makes connecting to your remote servers easy. - [Mail-Dev](https://github.com/samirdjelal/mail-dev) - Cross-platform, local SMTP server for email testing/debugging. - [Nhex](https://github.com/nhexirc/nhex) - Next-generation IRC client inspired by HexChat. - [RustDesk](https://github.com/rustdesk/rustdesk-server) - Self-hosted server for RustDesk, an open source remote desktop. - [RustDuck](https://github.com/thewh1teagle/RustDuck) - Cross platform dynamic DNS updater for duckdns.org. - [T-Shell](https://github.com/TheBlindM/T-Shell) - An open-source SSH, SFTP intelligent command line terminal application. - [TunnlTo](https://github.com/TunnlTo/desktop-app) - Windows WireGuard VPN client built for split tunneling. - [UpVPN](https://github.com/upvpn/upvpn-app) - WireGuard VPN client for Linux, macOS, and Windows. - [Watcher](https://github.com/windht/watcher) - API manager built for a easier use to manage and collaborate. - [Wirefish](https://github.com/stefanodevenuto/wirefish) - Cross-platform packet sniffer and analyzer. ### Office & Writing - [Bidirectional](https://github.com/samirdjelal/bidirectional) - Write Arabic text in apps that don't support bidirectional text. - [Blank](https://github.com/FPurchess/blank) - Minimalistic, opinionated markdown editor made for writing. - [Ensō](https://enso.sonnet.io) ![closed source] - Write now, edit later. Ensō is a writing tool that helps you enter a state of flow. - [Handwriting keyboard](https://github.com/BigIskander/Handwriting-keyboard-for-Linux-tesseract) - Handwriting keyboard for Linux X11 desktop environment. - [JournalV](https://github.com/ahmedkapro/journalv) - Journaling app for your days and dreams. - [MarkFlowy](https://github.com/drl990114/MarkFlowy) - Modern markdown editor application with built-in ChatGPT extension. - [MDX Editor](https://github.com/maqi1520/mdx-editor/tree/tauri-app) - Versatile WeChat typesetting editor and cross-platform Markdown note-taking software. - [Noor](https://noor.to/) ![closed source] - Chat app for high-performance teams. Designed for uninterrupted deep work and rapid collaboration. - [Notedown](https://github.com/ruralad/notedown) - Minimal, local-first cross-platform note taking app. - [Parchment](https://github.com/tywil04/parchment) - Simple local-only cross-platform text editor with basic markdown support. - [Semanmeter](https://yibiao.fun/) ![closed source] - OCR and document conversion software. - [Ubiquity](https://github.com/opensourcecheemsburgers/ubiquity) - Cross-platform markdown editor; built with Yew, Tailwind, and DaisyUI. ### Productivity - [Banban](https://github.com/HubertK05/banban) - Kanban board with tags, categories and markdown support. - [BuildLog](https://github.com/rajatkulkarni95/buildlog) - Menu bar for keeping track of Vercel Deployments. - [Dalgona](https://github.com/GHGHGHKO/dalgona) - GIF meme finder app for Windows and macOS. - [GitBar](https://github.com/mikaelkristiansson/gitbar) - System tray app for GitHub reviews. - [Gitification](https://github.com/Gitification-App/gitification) - Menu bar app for managing Github notifications. - [Google Task Desktop Client](https://github.com/codad5/google-task-tauri) - Google Task Desktop Client - [Jarvis](https://jarvis.huakun.tech/) - Cross-platform, extensible app launcher. Alternative to Alfred and Raycast. - [Kanri](https://github.com/trobonox/kanri) - Cross-platform, offline-first Kanban board app with a focus on simplicity and user experience. - [Kianalol](https://github.com/zxh3/kianalol) - Spotlight-like efficiency tool for swift website access. - [Link Saas](https://github.com/linksaas/desktop) - Efficiency tools for software development teams. - [MacroGraph](https://github.com/Brendonovich/macrograph) - Visual programming for content creators. - [Obliqoro](https://github.com/mrjackwills/obliqoro) - Oblique Strategies meets Pomodoro. - [Pomodoro](https://github.com/g07cha/pomodoro) - Time management tool based on Pomodoro technique. - [Remind Me Again](https://github.com/probablykasper/remind-me-again) - Toggleable reminders app for Mac, Linux and Windows. - [TimeChunks](https://danielulrich.com/en/timechunks/) ![closed source] - Time tracking for freelancers without timers and HH:MM:SS inputs. - [WindowPet](https://github.com/SeakMengs/WindowPet) - Overlay app that lets you have adorable companions such as pets and anime characters on your screen. - [Zawee](https://zawee.net) ![closed source] - Experience the synergy of Kanban boards, note-taking, file sharing, and more, seamlessly integrated into one powerful application. ### Search - [Harana](https://github.com/harana/search) - Search your desktop and 300+ cloud apps, instantly. - [Spyglass](https://github.com/a5huynh/spyglass) - Personal search engine that indexes your files/folders, cloud accounts, and whatever interests you on the internet. ### Security - [Authme](https://github.com/Levminer/authme) - Two-factor (2FA) authentication app for desktop. - [Calciumdibromid](https://codeberg.org/Calciumdibromid/CaBr2) - Generate "experiment wise safety sheets" in compliance to European law. - [Gluhny](https://github.com/angeldollface/gluhny) A graphical interface to validate IMEI numbers. - [OneKeePass](https://github.com/OneKeePass/desktop) - Secure, modern, cross-platform and KeePass compatible password manager. - [Padloc](https://github.com/padloc/padloc) - Modern, open source password manager for individuals and teams. - [Raspirus](https://github.com/Raspirus/Raspirus) - User- and resources-friendly signatures-based malware scanner. - [Secops](https://github.com/kunalsin9h/secops) - Ubuntu Operating System security made easy. - [Tauthy](https://github.com/pwltr/tauthy) - Cross-platform TOTP authentication client. - [Truthy](https://github.com/fosslife/truthy/) - Modern cross-platform 2FA manager with tons of features and a beautiful UI. ### Social media - [Dorion](https://github.com/SpikeHD/Dorion) - Light weight third-party Discord client with support for plugins and themes. - [Identia](https://github.com/iohzrd/identia) - Decentralized social media on IPFS. - [Kadium](https://github.com/probablykasper/kadium) - App for staying on top of YouTube channel uploads. - [Scraper Instagram GUI Desktop](https://git.kaki87.net/KaKi87/scraper-instagram-gui-desktop) - Alternative Instagram front-end for desktop. ### Utilities - [AgeTimer](https://github.com/dhextras/age-timer-tauri) - Desktop utility that counts your age in real-time. - [Auto Wallpaper](https://github.com/auto-wallpaper/auto-wallpaper) - Automatically generates 4K wallpapers based on user's location, weather, and time of day or any custom prompts. - [bewCloud Desktop Sync](https://github.com/bewcloud/bewcloud-desktop) - Desktop sync app for bewCloud, a simpler alternative to Nextcloud and ownCloud. - [TypeView - KeyStroke Visualizer](https://github.com/dunkbing/typeview) - Visualizes keys pressed on the screen and simulates the sound of mechanical keyboard. - [Browsernaut](https://github.com/billyjacoby/browsernaut) - Browser picker for macOS. - [Clipboard Record](https://github.com/lesterhnu/clipboard) - Record Clipboard Content. - [Clippy](https://github.com/0-don/clippy) - Modern & Fast Clipboard Manager. - [Fancy Screen Recorder](https://fancyapps.com/freebies/) ![closed source] - Record entire screen or a selected area, trim and save as a GIF or video. - [Flying Carpet](https://github.com/spieglt/flyingcarpet) - File transfer between Android, iOS, Linux, macOS, and Windows over auto-configured hotspot. - [Imagefly](https://www.imagefly.dev/?ref=awesometauri) ![closed source] - Powerful offline image processing toolkit for Windows, Linux and macOS - [Jane Reader](https://janereader.com) ![closed source] - Modern and distraction-free epub reader. - [KittyCAD](https://github.com/KittyCAD/modeling-app) - Modern 3D mechanical/hardware design. Build 3D models with both code and WYSIWYG editors. - [KoS - Key on Screen](https://github.com/dubisdev/key-on-screen) - Show in your screen the keys you are pressing. - [Lanaya](https://github.com/ChurchTao/Lanaya) - Easy to use, cross-platform clipboard management. - [Linka!](https://github.com/linka-app/linka) - AI powered, easy to use, cross-platform bookmark management tool. - [MBTiles Viewer](https://github.com/Akylas/mbview-rs) - MBTiles Viewer and Inspector. - [Metronome](https://github.com/ZaneH/metronome) - Visual metronome for Windows, Linux and macOS. - [Mobslide](https://github.com/thewh1teagle/mobslide) - Turn your smartphone into presentation remote controller. - [Overlayed](https://overlayed.dev) - Voice chat overlay for Discord. - [Pavo](https://github.com/zhanglun/pavo) - Cross-platform desktop wallpaper application. - [Peekaboo](https://github.com/angeldollface/peekaboo) A graphical interface to display images. - [Pointless](https://github.com/kkoomen/pointless) - Endless drawing canvas. - [Pot](https://github.com/pot-app/pot-desktop) - Cross-platform Translation Software. - [Rounded Corners](https://github.com/RoundedCorners/Application) - Rounded Corners app for Windows. - [RunMath](https://github.com/dubisdev/runmath) - Keyboard-first calculator for Windows. - [SensiMouse](https://github.com/Nicify/sensi-mouse) - Easily change macOS system-wide mouse sensitivity and acceleration settings. - [Stable Diffusion Buddy](https://github.com/breadthe/sd-buddy) - Desktop UI companion for the self-hosted Mac version of Stable Diffusion. - [Stacks](https://github.com/cablehead/stacks) - Modern and capable clipboard manager for macOS. Seeking Linux and Windows contributions. - [Tauview](https://github.com/sprout2000/tauview) - Minimalist image viewer for macOS and Linux based on Leaflet.js. - [ToeRings](https://github.com/acarl005/toerings) - Conky Seamod inspired system monitor app. - [Toolcat](https://toolcat.app) ![closed source] - All-in-one toolkit for developers and creators. - [TrguiNG](https://github.com/openscopeproject/TrguiNG) - Remote GUI for Transmission torrent daemon. - [Verve](https://github.com/ParthJadhav/verve) - Launcher for accessing and opening applications, files and documents. - [Vibe](https://thewh1teagle.github.io/vibe) - Transcribe audio or video in every language on every platform. - [Wallpaper changer](https://github.com/zeet2020/wallpaper-changer-tauri) - Simple wallpaper changer app. - [Zap](https://usezap.sh/?ref=awesometauri) ![closed source] - macOS spotlight-like dock that makes navigating apps convenient. [officially maintained]: https://img.shields.io/badge/official-FFC131?&logo=tauri&logoColor=black [closed source]: https://img.shields.io/badge/closed%20source-FFC131?&logoColor=black [paid]: https://img.shields.io/badge/paid-FFC131?&logoColor=black

🚀 Awesome Tauri Apps, Plugins and Resources

awesome,awesome-list,tauri

liyupi/mianshiya-public

# 面试鸭   <!-- ALL-CONTRIBUTORS-BADGE:START - Do not remove or modify this section --> [](#contributors-) <!-- ALL-CONTRIBUTORS-BADGE:END --> > 一个干净免费的面试刷题网站！ > > React + 云开发 / Node.js 全栈项目，包含网站前台 + 管理员后台的完整前后端代码。 地址：[https://www.mianshiya.com](https://mianshiya.com) 视频介绍：[欢迎点赞、收藏、投币三连](https://www.bilibili.com/video/BV1hu411U7Cc/) 为什么开源？[看视频了解](https://www.bilibili.com/video/BV1LZ4y1B7Q1/)  如果你是 - 求职者 👨：高效刷题、把握高频考点，快速分享面经，顺利通过面试 - 面试官 🧓🏻：快速选题、一键生成试卷，把控面试考点，高效招纳人才 - 学生 👨‍🎓：了解面试考察重点，明确学习方向，积累小题库，稳步提升 - 老师 👩‍🏫：了解企业招聘需求，改进教学方向，帮助更多学生走进大厂 ## 项目背景 如今面试越来越卷了，每场面试必考八股文，所以不得不背诵面试题。 但网上的面试题过于分散、很多面经也是只有问题没有题解，就导致我们需要一个个去搜索、或者关注这号那号去领取别人整理好的面试题，很麻烦。 因此，我做了【面试鸭】，一个专注面试刷题的网站。有了它，大家可以直接一站式在线刷题看题解，告别搜索和求人，大大提高复习效率。希望它能帮助大家拿到理想的 offer。 ## 优势 - 干净：界面简洁，纯净无广 - 免费：永久免费，可赚激励 - 全面：海量题目，上百方向 - 共建：全民编辑，共同完善 - 崭新：持续更新，拥抱变化 - 效率：灵活选题，高效刷题 - ~~多端适配（算个毛的优势）~~ ## 项目定位 **专注** 面试刷题，本就是鸭鸭最大的不同！  ## 功能 🌟 亮点功能 🧪 试验功能 🚀 未来计划（画饼） - 题目 - 浏览题目 - 折叠解析 - 🌟 多维度筛选题目（难度、标签、题型） - 🌟 多维度排序题目（热度、收藏数、频率） - 🌟 题目推荐 - 🌟 题目遇见次数 - 🌟 共同编辑解析 - 精选题目 - 上传题目 - 搜索题目 - 热门搜索 - 搜索历史 - 收藏题目 - 🧪 语音读题 - 🚀 选题练习 - 🚀 分析报告 - 举报 - 标签 - 🌟 关注标签 - 搜索标签 - 🚀 标签树 - 回答 - 🌟 回答题目 - 精选回答 - 点赞回答 - 回复 - 试卷 - 🌟 试题篮 - 🌟 一键组卷 - 🌟 下载试卷 - 查看 / 隐藏解析 - 试卷可见范围（公开 / 私有） - 🧪 语音读卷 - 🚀 试卷打分 - 用户 - 设置个人信息 - 积分 - 🌟 收藏夹 - 题目管理 - 回答管理 - 试卷管理 - 消息中心 - 个人主页 - 其他 - 排行榜 ## 项目展示 多维度题目检索和排序：  题目浏览：  试卷浏览：  快速组卷：  ## 技术栈 > 可先观看：[面试鸭技术分享视频](https://www.bilibili.com/video/BV1sa41117zV/) ### 前端 - 开发框架：React、Umi - 脚手架：Ant Design Pro - 组件库：Ant Design、Ant Design Components - 语法扩展：TypeScript、Less - 打包工具：Webpack - 代码规范：ESLint、StyleLint、Prettier ### 后端 - 主语言：JavaScript（Node.js / 腾讯云云开发） - 开发框架：Express（Express Session） - 数据库：MongoDB - 中间件：Redis、Elasticsearch - 对象存储：腾讯云云存储 / 腾讯云 COS ### 部署 - web 服务：Nginx - Docker 容器、微信云托管 - CDN 加速 ## 整体架构 > 仅供参考  ## 快速上手 ### 前端 环境要求：Node.js >= 14 安装依赖： ```bash yarn ``` 启动： ```bash yarn start ``` 部署： ```bash yarn build ``` 执行命令后会得到 dist 目录，可以放到自己的 web 服务器指定的路径；也可以使用 Docker 容器部署，将 dist、Dockerfile、docker 目录（文件）一起打包即可。 ### Node.js 后端 > 代码均在 server 目录中 请阅读 [参考文档](./server/README.md) ### 云函数后端 > 代码均在 cloudfunctions 目录中 请阅读 [参考文档](./cloudfunctions/README.md) ## 🍊 进一步学习 如果想进一步了解项目的完整制作过程、系统设计、数据库设计、经验感悟等，欢迎加入鱼皮的 [编程知识星球](https://dogyupi.com) ，在星球内会直播带大家玩转这个项目。 ## 欢迎贡献 项目需要大家的支持，期待更多小伙伴的贡献，你可以： - [上传优质题目](https://www.mianshiya.com/addQuestion/) - [分享试卷或面经](https://www.mianshiya.com/addPaper/) - 回答题目或优化题目解析 - 提建议或 Bug：[反馈平台](https://support.qq.com/products/370820) ## Contributors ✨ Thanks goes to these wonderful people ([emoji key](https://allcontributors.org/docs/en/emoji-key)): <!-- ALL-CONTRIBUTORS-LIST:START - Do not remove or modify this section --> <!-- prettier-ignore-start --> <!-- markdownlint-disable --> <table> <tr> <td align="center"><a href="https://www.code-nav.cn"><img src="https://avatars.githubusercontent.com/u/26037703?v=4?s=100" width="100px;" alt=""/><br />_{<b>程序员鱼皮</b>}</a><br /><a href="#infra-liyupi" title="Infrastructure (Hosting, Build-Tools, etc)">🚇</a> <a href="https://github.com/liyupi/mianshiya/commits?author=liyupi" title="Tests">⚠️</a> <a href="https://github.com/liyupi/mianshiya/commits?author=liyupi" title="Code">💻</a></td> <td align="center"><a href="http://blog.code520.com.cn"><img src="https://avatars.githubusercontent.com/u/73232691?v=4?s=100" width="100px;" alt=""/><br />_{<b>周靖</b>}</a><br /><a href="#content-jokereven" title="Content">🖋</a> <a href="https://github.com/liyupi/mianshiya/commits?author=jokereven" title="Tests">⚠️</a></td> <td align="center"><a href="https://github.com/taiyang"><img src="https://avatars.githubusercontent.com/u/11793873?v=4?s=100" width="100px;" alt=""/><br />_<b>Tai</b></a><br /><a href="#content-taiyang" title="Content">🖋</a> <a href="https://github.com/liyupi/mianshiya/commits?author=taiyang" title="Tests">⚠️</a> <a href="https://github.com/liyupi/mianshiya/pulls?q=is%3Apr+reviewed-by%3Ataiyang" title="Reviewed Pull Requests">👀</a></td> <td align="center"><a href="https://github.com/Luo-0518"><img src="https://avatars.githubusercontent.com/u/92662475?v=4?s=100" width="100px;" alt=""/><br />_{<b>Luo-0518</b>}</a><br /><a href="#content-Luo-0518" title="Content">🖋</a> <a href="https://github.com/liyupi/mianshiya/commits?author=Luo-0518" title="Tests">⚠️</a></td> </tr> </table> <!-- markdownlint-restore --> <!-- prettier-ignore-end --> <!-- ALL-CONTRIBUTORS-LIST:END --> This project follows the [all-contributors](https://github.com/all-contributors/all-contributors) specification. Contributions of any kind welcome!

干净免费的面试刷题网站，帮助大家拿到满意的 offer！💎 React 前端 + Node 后端 + 云开发全栈项目 by 程序员鱼皮

java,python,javascript,algorithm,golang,backend,frontend,cpp,interview,programmer

LSPosed/LSPosed.github.io

# LSPosed Official Website ## LSPosed Download here: <https://github.com/LSPosed/LSPosed/releases> ## Xposed Module Repository Go to here: <https://modules.lsposed.org> ## Shamiko Download here: <https://github.com/LSPosed/LSPosed.github.io/releases>

openmlsys/openmlsys-zh

# 机器学习系统：设计和实现 本开源项目试图给读者讲解现代机器学习系统的设计原理和实现经验。 🔥 **书籍网页版：** [机器学习系统：设计和实现](https://openmlsys.github.io/) 🔥 **书籍PDF：** 将在勘误后，2022年中发布。 ## 发布 - 27/06/2022: OpenMLSys社区发布通俗易懂的高性能AI算子开发教程，助力学生和工程师60分钟理解算子性能优化的关键知识点。相应的[技术博客](https://zhuanlan.zhihu.com/p/531498210)和[复现代码](https://github.com/openmlsys/openmlsys-cuda)都已免费公开。感谢@[Jie Ren](https://github.com/JieRen98) 和 @[Wenteng Liang](https://github.com/Went-Liang) 的贡献！🔥 - 17/03/2022: 本书处于勘误阶段。如发现文字和图片错误，可创建Issue并@[章节编辑](info/editors.md)。我们非常欢迎社区提交PR直接勘误。 ## 适用读者 本书的常见读者包括： - **学生：** 随着大量机器学习课程在大学中的普及，学生已经开始掌握大量机器学习的基础理论和神经网络的实现。然而，需要训练出可以实际应用的机器学习模型，需要对现代机器学习系统有充分的认识。 - **科研人员：** 研发新型的机器学习模型不仅仅需要会使用基础的机器学习系统接口。同时，新型的模型需要给系统提供新的自定义算子（Custom Operators），又或者是会利用高级的分布式执行算子来实现大模型的开发。这一系列需求都需要对底层系统具有充分认识。 - **开发人员：** 大量的数据和AI驱动的公司都部署了机器学习基础设施。这一设施的核心就是机器学习系统。因此了解机器学习系统有助于开发人员对于系统性能调优，以定位问题，并且根据业务需求对机器学习系统进行深度定制。 ## 内容介绍 现代机器学习框架具有复杂的内部架构和繁多的外部相关组件。在本书中，我们将对其细致拆分，深入解读： 基础： - **编程接口：** 为了支持海量应用，机器学习框架的编程接口设计具有大量的设计哲学，在易用性和性能之间取得平衡。本书将讲述编程接口的演进，机器学习工作流，定义深度学习模型，以及用C/C++进行框架开发。 - **计算图：** 机器学习框架需要支持自动微分，硬件加速器，多编程前端等。实现这些支持的核心技术是：计算图（Computational Graph）。本书将讲述计算图的基本构成，生成方法和调度策略。 性能进阶： - **编译器前端：** 机器学习框架需要利用编译器前端技术对计算图进行功能拓展和性能优化。本书将讲述常见的前端技术，包括类型推导，中间表示（Intermediate Representation），自动微分等。 - **编译器后端和运行时：** 机器学习框架的一个核心目标是：如何充分利用异构硬件。这其中会涉及编译器后端技术，以及将计算图算子（Operator）调度到硬件上的运行时（Runtime）。本书将讲述计算图优化，算子选择，内存分配和计算调度与执行。 - **硬件加速器：** 机器学习框架的基本运行单元是算子，而算子的实现必须充分利用硬件加速器（GPU和Ascend）的特性。本书将会讲述硬件加速器的基本构成原理和常见的高性能编程接口。 - **数据处理框架：** 机器学习框架会集成高性能框架来进行数据预处理。本书将会讲述这一类数据处理框架在设计中需要达到的多个目标：易用性，高效性，保序性，分布式等。 - **模型部署：** 在模型完成训练后，用户需要将模型部署到终端设备（如云服务器，移动终端和无人车）。这其中涉及到的模型转换，模型压缩，模型推理和安全保护等知识也会在本书中讨论。 - **分布式训练：** 机器学习模型的训练需要消耗大量资源。越来越多的机器学习框架因此原生支持分布式训练。在本书中我们将会讨论常见的分布式训练方法（包括数据并行，模型并行和流水线并行），以及实现这些方法的系统架构（包括集合通讯和参数服务器）。 功能拓展： - **深度学习推荐系统：** 推荐系统是目前机器学习应用最成功的领域之一。本书将会概括推荐系统的运作原理，详细描述大规模工业场景下的推荐系统架构设计。 - **联邦学习系统：** 随着数据保护法规和隐私保护的崛起，联邦学习正成为日益重要的研究领域。本书将会介绍联邦学习的常用方法以及相关系统实现。 - **强化学习系统：** 强化学习是走向通用人工智能的关键技术。本书将会介绍目前常见的强化学习系统（包括单智能体和多智能体等）。 - **可解释性AI系统：** 随着机器学习在安全攸关（Safety-critical）领域的应用，机器学习系统越来越需要对决策给出充分解释。本书将会讨论可解释AI系统的常用方法和落地实践经验。 - **机器人系统：** 机器人（无人车，无人机，家用机器人等）作为机器学习技术重要的应用领域，在最近数年得到了广泛应用。在实践中，机器人系统在实时性，安全性，鲁棒性等方面都有极高要求，这要求开发者具有算法和系统的双重思维，从而解决实际问题。本书中我们将结合最新研究成果和机器人系统实践经验讲解该类系统的设计原则和实现细节。 我们在持续拓展拓展本书的内容，如元学习系统，自动并行，深度学习集群调度，绿色AI系统，图学习系统等。我们也非常欢迎社区对于新内容提出建议，贡献章节。 ## 构建指南 请参考[构建指南](info/info.md)来了解如何构建本书的网页版本和PDF版本。 ## 写作指南 我们欢迎大家来一起贡献和更新本书的内容。常见的贡献方式是提交PR来更新和添加Markdown文件。写作的风格和图片要求请参考[风格指南](info/style.md)。同时，机器学习领域涉及到大量的中英文翻译，相关的翻译要求请参考[术语指南](info/terminology.md)。

《Machine Learning Systems: Design and Implementation》- Chinese Version

machine-learning,software-architecture,textbook,computer-systems

pk910/PoWFaucet

# PoWFaucet <img src="https://faucets.pk910.de/images/logo-cat-small.png" height="90px" /> [](https://github.com/pk910/PoWFaucet/releases/latest) [](https://codecov.io/gh/pk910/PoWFaucet) Modularized faucet for EVM chains with different protection methods (Captcha, Mining, IP, Mainnet Balance, Gitcoin Passport and more) # Why Faucets for ETH Testnets are spammed by bots. This faucet tries to reduce the efficiency of these automated requests by various protection methods. This faucet is mostly known for its proof-of-work based protection, which is currently the best and most reliable way to distribute funds on a network that got low on fund reserves. For clarification: This faucet does NOT generate new coins with the "mining" process. It's just one of the protection methods the faucet uses to prevent anyone from requesting big amount of funds and draining the faucet wallet. If you want to run your own instance you need to transfer the funds you want to distribute to the faucet wallet yourself! For a more detailed description, take a look into the [Project Wiki](https://github.com/pk910/PoWFaucet/wiki) # Instances <table> <thead> <tr> <th>Testnet</th> <th>Link</th> <th></th> </tr> </thead> <tbody> <tr> <td><a href="https://github.com/eth-clients/sepolia">Sepolia Testnet</a></td> <td><a href="https://sepolia-faucet.pk910.de">https://sepolia-faucet.pk910.de</a></td> <td> <a href="#"><img alt="Faucet Version" src="https://img.shields.io/endpoint?url=https%3A%2F%2Ffaucets.pk910.de%2Fbadges%2Fversion.php%3Ffaucet%3Dsepolia-faucet" /></a> <a href="https://stats.uptimerobot.com/lW1jltO2k0/794659718"><img alt="Uptime Robot ratio (30 days)" src="https://img.shields.io/uptimerobot/ratio/m794659718-c8c94ebdcae5283c5df1a5ad" /></a> <a href="https://sepolia.etherscan.io/address/0x6Cc9397c3B38739daCbfaA68EaD5F5D77Ba5F455"><img alt="Faucet Balance" src="https://img.shields.io/endpoint?url=https%3A%2F%2Ffaucets.pk910.de%2Fbadges%2Fbalance.php%3Ffaucet%3Dsepolia-faucet" /></a> </td> </tr> <tr> <td><a href="https://github.com/eth-clients/holesky">Holešovice Testnet</a></td> <td><a href="https://holesky-faucet.pk910.de">https://holesky-faucet.pk910.de</a></td> <td> <a href="#"><img alt="Faucet Version" src="https://img.shields.io/endpoint?url=https%3A%2F%2Ffaucets.pk910.de%2Fbadges%2Fversion.php%3Ffaucet%3Dholesky-faucet" /></a> <a href="https://stats.uptimerobot.com/lW1jltO2k0/795198747"><img alt="Uptime Robot ratio (30 days)" src="https://img.shields.io/uptimerobot/ratio/m795198747-dbc5794093556ee744ed909a" /></a> <a href="https://holesky.etherscan.io/address/0x6Cc9397c3B38739daCbfaA68EaD5F5D77Ba5F455"><img alt="Faucet Balance" src="https://img.shields.io/endpoint?url=https%3A%2F%2Ffaucets.pk910.de%2Fbadges%2Fbalance.php%3Ffaucet%3Dholesky-faucet" /></a> </td> </tr> <tr> <td><a href="https://github.com/ephemery-testnet/ephemery-resources">Ephemery Testnet</a></td> <td><a href="https://ephemery-faucet.pk910.de">https://ephemery-faucet.pk910.de</a></td> <td> <a href="#"><img alt="Faucet Version" src="https://img.shields.io/endpoint?url=https%3A%2F%2Ffaucets.pk910.de%2Fbadges%2Fversion.php%3Ffaucet%3Dephemery-faucet" /></a> <a href="https://stats.uptimerobot.com/lW1jltO2k0/794659832"><img alt="Uptime Robot ratio (30 days)" src="https://img.shields.io/uptimerobot/ratio/m794659832-bc531ed47aa35b919d3f8d98" /></a> <a href="https://explorer.ephemery.dev/address/0x6Cc9397c3B38739daCbfaA68EaD5F5D77Ba5F455"><img alt="Faucet Balance" src="https://img.shields.io/endpoint?url=https%3A%2F%2Ffaucets.pk910.de%2Fbadges%2Fbalance.php%3Ffaucet%3Dephemery-faucet" /></a> </td> </tr> </tbody> </table> # Run Yourself Read the [Faucet Operator Wiki](https://github.com/pk910/PoWFaucet/wiki/Operator-Wiki) to see the installation and configuration instructions. You can also find some demo instances with different module combinations here: [Demo Instances](https://github.com/pk910/PoWFaucet/blob/master/docs/demo/README.md) # Bugs & Features Please feel free to report bugs and add new features via PRs if you like. # Thanks To This faucet contains parts of code from the following projects: [pow-captcha](https://git.sequentialread.com/forest/pow-captcha) - faucet-wasm build script [FaucETH](https://github.com/komputing/FaucETH) - faucet page design # License [](https://www.gnu.org/licenses/agpl-3.0)

Modularized faucet for EVM chains with different protection methods (Captcha, Mining, IP, Mainnet Balance, Gitcoin Passport and more)

ethereum,faucet,testnet,testnet-faucet,web3,sybil-resistance

Evavic44/portfolio-ideas

 <div> <img align="right" src="https://user-images.githubusercontent.com/62628408/203671459-3c139f1e-31fa-43af-80b2-e3a14ce7e646.svg" width="60px"> <h1 align="center">Portfolio Ideas</h1> <p>A curation of awesome portfolio ideas for developers and designers to draw inspirations when they decide to create their own. Want to add yours or someone else's, feel free to raise a PR to add them. Inspired by <a href="https://github.com/GorvGoyl/Clone-Wars">clone Wars</a>, <a href="https://hashnode.com/post/30-web-developer-portfolios-to-inspire-you-cknfx6wdg069kxws1bjjv8mhw">30 web developer ideas to inspire you</a> and my personal struggles :).</p> </div> Read about how this project started: <a href="https://eke.hashnode.dev/portfolio-ideas-an-open-source-repository-for-inspiration">Portfolio Ideas - An open-source repository for inspiration</a> ## Contribute <!-- ALL-CONTRIBUTORS-BADGE:START - Do not remove or modify this section --> [](#contributors) <!-- ALL-CONTRIBUTORS-BADGE:END --> <div>Want to add a portfolio to this list? read the <a href="https://github.com/Evavic44/portfolio-ideas/blob/main/CONTRIBUTING.md">guidelines</a> on how to do that.</div> <br> <!-- === ⭐ PORTFOLIO LINE START ⭐ === --> | Author | Screenshot | Live URL | Repo | Tech Stack | | -------------------------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | ------------------------------------------------------------------------------------------------------------- | ---------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------- | | Victor Eke |  | [victoreke.com](https://victoreke.com) | [GitHub](https://github.com/evavic44/victoreke.com) | Nextjs, Sanity, Tailwind CSS, TypeScript, Umami, Vercel | | Kent C. Dodds |  | [kentcdodds.com](https://kentcdodds.com) | [GitHub](https://github.com/kentcdodds/kentcdodds.com) | React, TypeScript, Remix, Prisma, Redis, Postgres, CSS | | Brittany Chiang |  | [v4.brittanychiang.com](https://v4.brittanychiang.com/) | [GitHub](https://github.com/bchiang7/v4) | React, Gatsby, Styled-components | | Braydon Coyer |  | [braydoncoyer.dev](https://braydoncoyer.dev/) | [GitHub](https://github.com/braydoncoyer/braydoncoyer.dev) | React, TypeScript, NextJS, Tailwindcss, Notion API, Supabase | | Tania Rascia |  | [taniarascia.com](https://taniarascia.com) | [GitHub](https://github.com/taniarascia/taniarascia.com) | React, Gatsby, CSS, Netlify, NodeJS | | Jemima Abu |  | [jemimaabu.com](https://jemimaabu.com) | [GitHub](https://github.com/jemimaabu/portfolio) | HTML, CSS, JavaScript. | | Rekhchand Sahu |  | [rekhchandsahu.com](https://rekhchandsahu.com) | None | React, Gatsby, Preact, GSAP | | Olaolu Olawuyi |  | [olaolu.dev](https://olaolu.dev) | [GitHub](https://github.com/whizkydee/olaolu.dev) | VueJS, JavaScript, HTML, styled-components, Sass | | Thang Huu Vu |  | [thvu.dev](https://www.thvu.dev/) | [GitHub](https://github.com/ThangHuuVu/thvu-blog) | React, NextJS, NodeJS, TypeScript, GraphQL, Tailwindcss | | George Francis |  | [georgefrancis.dev](https://georgefrancis.dev) | None | GSAP, Netlify, HTML, CSS, JavaScript | | Aditya Vikram |  | [people.umass.edu/avsingh](https://people.umass.edu/avsingh) | [GitHub](https://github.com/AVS1508/My-Alternate-Portfolio-Website) | HTML, CSS, JavaScript | | Adeola Adeoti |  | [adeolaadeoti.xyz](https://www.adeolaadeoti.xyz) | [GitHub](https://github.com/adeolaadeoti/adeolaadeoti-v2) | TypeScript, GSAP, NodeJS, NextJS, SCSS | | Dejan Markovic |  | [dejan.works](https://www.dejan.works) | None | HTML, CSS, JavaScript, Jquery | | Jack Jeznach |  | [jacekjeznach.com/](https://jacekjeznach.com) | None | jQuery, PHP, GSAP, MySQL | | Max Böck |  | [mxb.dev](https://mxb.dev) | [GitHub](https://github.com/maxboeck/mxb) | Eleventy, SCSS, Nunjucks | | David Darnes |  | [darn.es](https://darn.es) | None | Netlify, Jekyll, ETC | | Schulz Daniel |  | [iamschulz.com](https://iamschulz.com) | [GitHub](https://github.com/iamschulz/iamschulz-hugo) | Hugo, Shell, JavaScript | | Rafael Conde |  | [rafa.design](https://rafa.design) | [GitHub](https://github.com/rafaelconde/rafaelconde) | Nunjucks, JavaScript, CSS | | Bruno Simon |  | [bruno-simon.com](https://bruno-simon.com) | [Github](https://github.com/brunosimon/folio-2019) | GSAP, ThreeJS, JavaScript, ETC | | Oluwadare Oluwaseyi |  | [seyi.dev](https://www.seyi.dev) | [GitHub](https://github.com/oluwadareseyi/folio-v2) | HTML, SCSS, JavaScript, GSAP | | Jason Lengstorf |  | [jason.energy](https://www.jason.energy) | [GitHub](https://github.com/jlengstorf/jason.energy) | JavaScript, TypeScript, Nunjucks, CSS | | Deidre Driscoll |  | [deidredriscoll.com](https://deidredriscoll.com) | None | HTML, JavaScript, CSS, GSAP | | Chris Porter |  | [madebyporter.com](https://madebyporter.com) | [GitHub](https://github.com/madebyporter/madebyporter) | HTML, Slim, Ruby, SCSS, Shell, JavaScript, CSS | | Louis Hoebregts |  | [mamboleoo.be](https://www.mamboleoo.be) | None | PHP, Parcel | | Adrien Gervaix |  | [adriengervaix.com](https://adriengervaix.com) | None | HTML, CSS, JavaScript | | Aaron Shapiro |  | [aaron.mn](https://www.aaron.mn) | [GitHub](https://github.com/aarshap/aaron.mn) | React, Gatsby, Styled Components, Netlify | | Peter Tait |  | [petertait.com](https://petertait.com) | [GitHub](https://github.com/petertait/petertait.com) | React, Webpack, Radium, Netlify | | Rick Waalders |  | [rickwaalders.com](https://www.rickwaalders.com) | None | NextJS, React, NodeJS, GSAP, Webpack | | Community Pro |  | [cpro-portfolio-html](https://cpro-portfolio-html.netlify.app) | [Github](https://github.com/CommunityPro/portfolio-html) | HTML, CSS, JavaScript | | Ahmed Zougari |  | [ahmedzougari.com](https://ahmedzougari.com) | [GitHub](https://github.com/zougari47/portfolio-template) | HTML, SASS, Bootstrap, JavaScript, Vite | | Raj Savaliya |  | [rajsavaliya.com](https://www.rajsavaliya.com/) | [GitHub](https://github.com/SRX9/portfoliosrx9) | NextJS, React, TypeScript, Tailwind CSS | | Israel Mitolu |  | [israelmitolu.netlify.app](https://israelmitolu.netlify.app) | [GitHub](https://github.com/israelmitolu/premier-portfolio) | HTML, SASS, Javascript, GSAP | | Saikat Roy |  | [saikatroy.netlify.app](https://saikatroy.netlify.app/) | [GitHub](https://github.com/njmsaikat/portfolio) | HTML, CSS, Bootstrap, JavaScript, jQuery | | Anand Baraik |  | [anandbaraik.github.io](https://anandbaraik.github.io) | [GitHub](https://github.com/anandbaraik/anandbaraik.github.io) | HTML, CSS, React.js | | Nirban Chakraborty |  | [nirban-chakraborty.netlify.app](https://nirban-chakraborty.netlify.app/) | [GitHub](https://github.com/nirban256/personal_website) | ReactJs, JavaScript, SASS, HTML | | Benaiah Alumona |  | [benrobo.vercel.app](https://benrobo.vercel.app) | [GitHub](https://github.com/benrobo/portfolio-v3) | Reactjs, TailwindCss, Next.js, Emailjs, BaayMax | | Md Nayeem Hossain |  | [nayeemdev.github.io/](https://nayeemdev.github.io/) | [GitHub](https://github.com/nayeemdev/nayeemdev.github.io) | HTML, CSS, Bootstrap, Javascript, jQuery | | Sachin Chaurasiya |  | [sachinchaurasiya.dev](https://sachinchaurasiya.dev) | None | HTML, CSS, JavaScript, ReactJs, Material UI | | Anish De |  | [anishde.dev](https://anishde.dev) | [GitHub](https://github.com/AnishDe12020/portfolio) | Next.js, TypeScript, Tailwind CSS, Content Layer | | Shourya Shikhar Ghosh |  | [shourya.vercel.app](https://shourya.vercel.app) | [GitHub](https://github.com/danger-ahead/flutter_dev_folio) | Flutter | | Omar Sherif Ali ~OSA |  | [osa-portfolio.vercel.app](https://osa-portfolio.vercel.app/) | [GitHub](https://github.com/omar-sherif9992) | ReactJs, JavaScript, CSS, HTML | | Robby Leonardi |  | [rleonardi.com/](http://www.rleonardi.com) | None | NextJS, React, NodeJS, GSAP, Webpack | | Serdar Gökhan |  | [serdargokhan.dev](https://serdargokhan.dev) | [GitHub](https://github.com/serdargokhan/portfolio-website-v1) | NextJS, TypeScript, TailwindCSS | | Jeferson Brito |  | [jefersonsilva.me/](https://www.jefersonsilva.me/) | [GitHub](https://github.com/jeferson-sb/portfolio) | Vue 3.0, Vite | | Trịnh Minh Nhật |  | [trinhminhnhat.com](https://trinhminhnhat.com) | None | React, Tailwindcss | | Yunus Ertürk |  | [yunuserturk.com](https://yunuserturk.com) | None | HTML, CSS, React, NextJS, | | Phong Nguyen |  | [napthedev.com](https://napthedev.com) | [Github](https://github.com/napthedev/portfolio-next) | Nextjs, Tailwind, Framer-motion, Locomotive-scroll | | Ismael López |  | [ismaellopez.dev](https://ismaellopez.dev) | None | Svelte, JavaScript, CSS, HTML, Netlify CMS | | Micah Lindley |  | [micahlindley.com](https://micahlindley.com) | [GitHub](https://github.com/micahlt/micahlt.github.io) | Vue 3, Vite | | Tri Dang |  | [tri-dang.github.io](https://tri-dang.github.io/about) | [GitHub](https://github.com/tri-dang/tri-dang.github.io) | Ruby, Jekyll, Markdown | | Reza Ghasemzadeh |  | [rezaghz.com](https://rezaghz.com) | None | HTML, CSS, Bootstrap,Javascript, Blade | | Ariful Alam |  | [arifszn.github.io/gitprofile](https://arifszn.github.io/gitprofile) | [GitHub](https://github.com/arifszn/gitprofile) | React, Vite, Tailwind CSS | | Dale Larroder |  | [dalelarroder.com](https://dalelarroder.com) | [GitHub](https://github.com/dlarroder/dalelarroder) | NextJS, Preact, TypeScript, Tailwind, MDX | | Williams Samuel |  | [williamssam.netlify.app](https://williamssam.netlify.app/) | [GitHub](https://github.com/williamssam/My-Portfolio) | HTML, CSS, Javascript | | Guillaume Gouessan |  | [guillaumegouessan.com](https://guillaumegouessan.com/) | [GitHub](https://github.com/superguigui/guillaumegouessan.com) | GSAP, ThreeJS, JavaScript | | Patrick Heng |  | [patrickheng.com](https://patrickheng.com/) | None | Nuxt.js, GSAP, ThreeJS | | Andrew Baisden |  | [andrewbaisden.com](https://andrewbaisden.com) | [GitHub](https://github.com/andrewbaisden/andrew-baisden-portfolio-2022) | HTML, CSS, TypeScript, ReactJS | | Aziz Rahman |  | [azizstark.com](https://azizstark.com) | [Github](https://github.com/AzizStark/AzizStark/tree/portfolio-v2) | React, Gatsby, Styled-Components, SCSS, AnimeJS | | Leonel Ngoya |  | [lndev.me](https://lndev.me) | [GitHub](https://github.com/ln-dev7) | HTML, CSS, JavaScript | | Jimmy Soussan |  | [cozy-codeur.fr](https://www.cozy-codeur.fr) | [Github](https://github.com/jilink/personal-portfolio) | React, Gatsby, Chakra UI, Framer Motion | | Segun Ajibola |  | [segunajibola.com](https://www.segunajibola.com) | [Github](https://github.com/segunajibola/portfolio) | HTML, CSS, TailwindCSS, React, SwiperJS | | Hisami Kurita |  | [hsmkrt1996.com](https://hsmkrt1996.com/) | [Github](https://github.com/hisamikurita/hisamikurita-portfoliosite) | Vue.js, Nuxt.js, SCSS, ThreeJS, GSAP, ASSCROLL, imagesLoaded | | Dennis Snellenberg |  | [dennissnellenberg.com](https://dennissnellenberg.com/) | None | GSAP. JQuery, PHP, VueJS | | Isaac Fayemi |  | [fayemi.design](https://www.fayemi.design/) | None | Vanilla JS, pug, Prismic CMS, SCSS, ThreeJS, GSAP | | Bhavin Virani |  | [bhavinn.xyz](https://bhavinn.xyz) | [Github](https://github.com/bhavinvirani/Protfolio) | HTML, CSS, JS, React.js, Github API | | Patrick Scott |  | [pscott.io](https://pscott.io) | None | React.js, Heroku and Github Pages | | Lazar Nikolov |  | [nikolovlazar.com](https://nikolovlazar.com) | [Github](https://github.com/nikolovlazar/nikolovlazar.com) | Next.js, Chakra UI, MDX, Prisma, PlanetScale | | Reuben Rapose |  | [reubence.com](https://reubence.com) | [GitHub](https://github.com/reubence/reubence) | HTML, TailwindCSS, React, Javascript, Next.JS, MDX, Mailchimp Newsletter, Gisqus Comments, etc. | | M. Shahanwaz |  | [mshahanwaz.me](https://mshahanwaz.me) | [GitHub](https://github.com/mshahanwaz/portfolio-v4) | HTML, CSS, JavaScript, React, Next.js, Nodemailer | | Lee Robinson |  | [leerob.io](https://leerob.io/) | [GitHub](https://github.com/leerob/leerob.io) | Next.js, PlanetScale, Prisma, Vercel, Sanity, Tailwind CSS | | Parth Desai |  | [musing.vercel.app](https://musing.vercel.app/) | [GitHub](https://github.com/pycoder2000/blog) | TailwindCSS, React, Javascript, Next.JS, MDX, Mailchimp Newsletter, Gisqus Comments | | Victor Ikechukwu |  | [iamvictor.tech](https://iamvictor.tech) | None | Next.js, Tailwind CSS, React Rough Notation, Vivus, Netlify | | Usman Sabuwala |  | [usman-s.me](https://www.usman-s.me) | [GitHub](https://github.com/max-programming/usman-s.me) | NextJS, Chakra UI, Framer Motion | | Zacky Aduoli |  | [lookupzach.netlify.app](https://lookupzach.netlify.app) | None | ReactJS, Material UI, SCSS, Styled Components | | Payton Pierce |  | [paytonpierce.dev](https://paytonpierce.dev) | [GitHub](https://github.com/paytonjewell/paytonpierce.dev) | ReactJS, Material UI | | Jacob Valdez |  | [jacobfv.github.io](https://jacobfv.github.io) | [GitHub](https://github.com/JacobFV/jacobfv.github.io) | HTML, Jekyll | | Jasmeet Singh |  | [jasmeetsinghbhatia.github.io/resume](https://jasmeetsinghbhatia.github.io/resume) | [GitHub](https://github.com/jasmeetsinghbhatia/resume) | HTML, CSS, JavaScript | | Walter Teng |  | [walterteng.com](https://walterteng.com/) | [GitHub](https://github.com/davzoku/personal-website-v1) | React, Typescript, Gatsby, Netlify | | Jahidul Islam |  | [XahidEx.com](https://xahidex.com/) | None | Typescript, NextJs, TailwindCSS, Prisma, Contentlayer, React | | Greg Sithole |  | [gregsithole.com](https://gregsithole.com) | [GitHub](https://github.com/GregSithole/gregsithole-react-portfolio) | HTML, CSS, React.js | | Rohit Saini |  | [rohit-saini](https://portfolio-45b9b.web.app/) | None | ReactJs, CSS, GSAP, Framer Motion | | Oscar Barajas |  | [gndx.io](https://gndx.io) | [GitHub](https://github.com/gndx/gndx.io) | HTML, TailwindCSS | | Phillip Cabrera |  | [Portfolio](https://pcabreram-portfolio.netlify.app/) | [GitHub](https://github.com/pcabreram1234/portfolio) | HTML, CSS, JavaScript, Webpack, ReactJs | | Nahuel Carrizo |  | [Portfolio](https://nahuel61920.github.io/portafolio-Nahuel/) | [GitHub](https://github.com/Nahuel61920/portafolio-Nahuel) | HTML, CSS, JavaScript, React, Webpack, Github Pages | | Alfaizkhan Pathan |  | [Portfolio](https://alfaizkhan.github.io) | [GitHub](https://github.com/Alfaizkhan/alfaizkhan.github.io) | Flutter, Dart, Github Pages | | Jatin Kamboj |  | [jatinkamboj.me](https://jatinkamboj.me/) | None | HTML, CSS, JavaScript, GreenSock | | Leonid Meleshin |  | [leon0399.ru](https://leon0399.ru/) | [GitHub](https://github.com/leon0399/leon0399.ru) | ReactJS, Tailwind, CSS, Vercel | | Brayden |  | [braydentw.io](https://braydentw.io/) | [GitHub](https://github.com/BraydenTW/braydentw.io) | React, NextJS, TailwindCSS | | Ben |  | [nuro.dev](https://nuro.dev/) | [GitHub](https://github.com/NuroDev/nuro.dev) | React, NextJS, TailwindCSS | | Matthias Kretschmann |  | [matthiaskretschmann.com](https://matthiaskretschmann.com/) | [GitHub](https://github.com/kremalicious/portfolio) | React, Gatsby | | Hamish Williams |  | [hamishw.com](https://hamishw.com/) | [GitHub](https://github.com/HamishMW/portfolio) | React, ThreeJS, NextJS | | Çağlar Turalı |  | [turali.js.org](https://turali.js.org/) | [GitHub](https://github.com/caglarturali/caglarturali.github.io) | React, TypeScript | | Pyae Sone |  | [pyaesonepsn.github.io](https://pyaesonepsn.github.io/portfolio-project/) | [GitHub](https://github.com/pyaesonepsn/portfolio-project) | HTML, CSS, JavaScript | | Efren Martinez |  | [efrencodes.com](https://efrencodes.com) | [GitHub](https://github.com/efrencodes/efrencodes.ts) | NextJS, TypeScript, TailwindCSS | | Eliaz LR |  | [portfolio2.eliaz-lr.dev](https://portfolio2.eliaz-lr.dev/) | [GitHub](https://github.com/Eliaz-LR/Personal-website-v2) | Vue 3, Vite, TailwindCSS | | Hikmet C. Kufteoglu |  | [hicaku.com](https://hicaku.com) | [GitHub](https://github.com/spencehiko/portfolio) | Vue 3, Pinia, TypeScript | | Ara Oladipo |  | [araoladipo.tech](https://araoladipo.tech/) | [GitHub](https://github.com/Ara-O/Portfolio-Website) | HTML, CSS, Javascript, Vue.js, Spline3D | | Anthony Fu |  | [antfu.me](https://antfu.me/) | [GitHub](https://github.com/antfu/antfu.me) | VueJS, Markdown, TypeScript, CSS, HTML | | Timothy Lin |  | [timlrx.com](https://timlrx.com) | [GitHub](https://github.com/timlrx/timlrx.com) | NextJS, MDX, TailwindCSS, JavaScript, SASS | | Ngô Phú Thịnh |  | [thinhcorner.com](https://thinhcorner.com) | [GitHub](https://github.com/Th1nhNg0/th1nhng0.vercel.app) | NextJS, TailwindCSS, TypeScript, CSS | | Josiah B. Etuk |  | [jobenetuk.dev](https://jobenetuk.dev/) | None | Vanilla JS, Node JS, Prismic CMS, SASS, GSAP | | Stef Ivanov |  | [stefivanov.com](https://stefivanov.com) | None | WordPress, Yoast SEO, MailChimp, PWA, Google Analytics, Sumo. | | Erika Senft Miller |  | [erikasenftmiller.com](https://www.erikasenftmiller.com/) | None | Contentful, GSAP, LazySizes, PWA, Google Analytics. | | Ruben Kuipers |  | [rubenkuipers.design](https://rubenkuipers.design/) | None | Vue.js, Nuxt.js, Tailwind CSS, scrollreveal, Google Tag Manager, Google Analytics | | Maggie Appleton |  | [maggieappleton.com](https://maggieappleton.com/) | [Github](https://github.com/MaggieAppleton/maggieappleton.com-V2) | React, Next.js, MDX, Algolia Search, Reach UI, Tippy.js, Framer Motion, styled-components, Lodash | | Moe Dayraki |  | [moe.dayrakiarts.com](https://moe.dayrakiarts.com) | [Github](https://github.com/moedayraki/moedayraki.github.io) | Vue 3, Vite, Cypress, Tailwindcss, Typescript, Pinia, Primevue, magic.css, VueUse | | Truong Phan |  | [techika.com](https://techika.com) | [Github](https://github.com/infantiablue) | Vue 3, Vite, VuePress, Tailwindcss, Tailwind, Lighthouse | | Wasim Baig |  | [wasimbaig.com](https://wasimbaig.com) | [GitHub](https://github.com/simbaig/portfolio-nextjs) | Next JS, Tailwind CSS, Framer-Motion | | Mike Bifulco |  | [mikebifulco.com](https://mikebifulco.com) | [GitHub](https://github.com/mbifulco/blog) | NextJS, React, SCSS, MDX, Vercel | | Shodipo Ayomide |  | [shodipoayomide.com](https://shodipoayomide.com/) | [GitHub](https://github.com/Developerayo/shodipoayomide.com) | Gatsby, React, SCSS, Bootstrap, Jquery | | Damian Watracz |  | [watracz.com](https://watracz.com/) | None | HTML, CSS, JavaScript, Swiper | | Franklin Ohaegbulam |  | [frankiefab.com](https://frankiefab.com) | [GitHub](https://github.com/frankiefab100/frankiefab.tech) | HTML, CSS, JavaScript | | Samuel Akinosho |  | [samuelakinosho.com](https://www.samuelakinosho.com/) | None | Webflow, Jquery | | Rutik Wankhade |  | [rutikwankhade.dev](https://rutikwankhade.dev/) | None | NextJs, React, NodeJS, TailwindCSS | | Adenekan Wonderful |  | [codewonders.dev](https://www.codewonders.dev/) | None | React, NextJS, Styled-components | | Olamide Sholanke |  | [olamide.dev](https://www.olamide.dev/) | None | Vue, NuxtJS | | Daniel Ezekiel |  | [danielezekiel.me](https://danielezekiel.me/) | [GitHub](https://github.com/Daniel-Ezekiel/Portfolio-Website) | HTML, CSS, JavaScript | | Julia Johnson |  | [juliacodes.com](https://www.juliacodes.com/) | [GitHub](https://github.com/juliacodes/JuliaCodesGatsby) | React, Styled-components | | Rida F'kih |  | [rida.dev](https://www.rida.dev/) | [GitHub](https://github.com/ridafkih/portfolio) | React, NextJS | | Anand Baraik |  | [anandbaraik-folio.netlify.app](https://anandbaraik-folio.netlify.app/) | [GitHub](https://github.com/anandbaraik/anandfolio) | HTML, CSS. | | Abhishek Jha |  | [abhishekjha.me](https://www.abhishekjha.me) | None | HTML, CSS, JavaScript, Ruby on Rails, GSAP | | Olamide Adeyi |  | [olamideadeyi.com](https://www.olamideadeyi.com) | None | Vue, NuxtJS, GSAP | | Greg Ives |  | [gregives.co.uk](https://www.gregives.co.uk) | [GitHub](https://github.com/gregives/gregives.co.uk) | Vue, NuxtJS, SASS, Netlify | | Collins Enebeli |  | [kadet.dev](https://kadet.dev/) | [GitHub](https://github.com/kadetXx/kadet.dev) | React, Gatsby | | Cole_Solomon |  | [colesolomon.me](https://colesolomon.me/) | [GitHub](https://github.com/codecole/colesolomonme) | HTML, CSS, SASS, JavaScript, GSAP, W3js, PHP | | Adewale Adeyemi |  | [adex.onrender.com](https://adex.onrender.com/) | [GitHub](https://github.com/dev-adewale/portfolio) | Gridsome, GraphQL, Tailwind. | | Harsh Singh |  | [harshsingh.xyz](https://harshsingh.xyz/) | [GitHub](https://github.com/harshhhdev/harshhhdev.github.io) | NextJS, TailwindCSS, TypeScript, Prisma | | Wallace Nascimento |  | [portfolio-srnascimento40.vercel.app](https://portfolio-srnascimento40.vercel.app/) | [GitHub](https://github.com/SrNascimento40/portfolio) | NextJS, ReactJS, TypeScript, Styled-Components | | Idris Olubisi |  | [idrisolubisi.com](https://idrisolubisi.com) | [GitHub](https://github.com/Olanetsoft/idrisolubisi.com) | ReactJs, GatsbyJs, TypedJs, Styled Component | | Aycan Öğüt |  | [aycan.dev](https://www.aycan.dev) | [Github](https://github.com/aycanogut/aycan.dev) | React, Next, TypeScript, Mantine | | Manish Kumar |  | [manishk.dev](https://manishk.dev) | [Github](https://github.com/manishprivet/portfolio) | React, Next, TypeScript, ParticleJS, Firebase, Vercel | | Andrea Toffanello |  | [andreatoffanello.com](https://andreatoffanello.com) | None | VueJS, ThreeJS, GSAP, Blender | | Chandraprakash Darji |  | [chandraprakash.vercel.app](https://chandraprakash.vercel.app/) | [Github](https://github.com/Chandraprakash-Darji/personal) | Nextjs, Typescript, Tailwindcss, Vercel | | Khaled Mohamed |  | [John Doe](https://portfolio-john2.netlify.app/) | None | HTML5, SCSS, Bootstrap5, JavaScript, SwipperJS, Netlify | | Michael Kolesidis |  | [michaelkolesidis.com](https://michaelkolesidis.com/) | [GitHub](https://github.com/michaelkolesidis/michaelkolesidis.com) | TypeScript, p5.js, Sass, Vite | | Piyush Goyani |  | [piyushgoyani.thesourcepedia.org](https://piyushgoyani.thesourcepedia.org) | None | VueJS, Gridsome, TailwindCSS, Firebase | | Vanessa Santana |  | [nessajs.com.br](https://www.nessajs.com.br/) | [GitHub](https://github.com/vanessa-dev/nessa.js) | HTML, CSS, JavaScript and PHP | | Mahmoud Elkariouny |  | [clear-sleet.surge.sh](https://clear-sleet.surge.sh/) | [GitHub](https://github.com/mahmoudessam820/my_portfolio) | HTML, CSS, JavaScript | | Antonio Ayola |  | [antonioayola.netlify.app](antonioayola.netlify.app) | [GitHub](https://github.com/Tono2007/Portafolio) | React, HTML, CSS, Modules CSS, JavaScript, PWA | | Ajo Alex |  | [devpenzil.dev](https://devpenzil.dev/) | [GitHub](https://github.com/devpenzil/devpenzil.dev) | NextJS, Tailwind, GraphCMS | | Erys Mozo |  | [erysmozo.vercel.app](https://erysmozo.vercel.app/) | [GitHub](https://github.com/ErysCode7/Web-Portfolio) | React, SASS, Vite, AOS | | Peace Jinadu-Paul |  | [pjpportfolio.netlify.app](https://pjpportfolio.netlify.app/) | [GitHub](https://github.com/Pappyjay23/my-portfolio-1) | React, HTML, CSS, Javascript, Framer Motion, Netlify | | Hari Prasad |  | [hariprasd.me](https://hariprasd.me) | [GitHub](https://github.com/hariprasd) | React, Tailwind CSS | | Danilo Batson |  | [batson-portfolio.vercel.app/](https://batson-portfolio.vercel.app/) | [GitHub](https://github.com/danilobatson/batson-portfolio) | TypeScript, JavaScript, Python, React, React Native, Vue, Express, Node, MongoDB, Next JS | | Soumyadeep Das Bhowmick |  | [soumyadeeposd.github.io](https://soumyadeeposd.github.io/Tensor-Block/) | [GitHub](https://github.com/SoumyadeepOSD/Tensor-Block) | HTML, CSS, JavaScript | | Byunggeun Cho |  | [bbangjo.kr](https://bbangjo.kr) | [GitHub](https://github.com/bbangjooo/buffalo) | HTML, CSS, JavaScript, TypeScript, Threejs, Blender | | James Warner |  | [jmswrnr.com](https://jmswrnr.com/) | None | NextJS, Sanity, CSS, Preact, NodeJS, ThreeJS | | Maxime Heckel |  | [maximeheckel.com](https://maximeheckel.com/) | [GitHub](https://github.com/MaximeHeckel/blog.maximeheckel.com) | NextJS, TypeScript, Stiches/CSS, MDX | | Twan Mulder |  | [twanmulder.com](https://www.twanmulder.com/) | [GitHub](https://github.com/twanmulder/portfolio) | React, TailwindCSS, Stripe, Netlify | | Rishi Mohan |  | [rishimohan.me](https://rishimohan.me) | [GitHub](https://github.com/rishimohan/rishimohan.me) | Next.js, TailwindCSS, Framer Motion | | Nikhil Rajput |  | [nixrajput.nixlab.co.in](https://nixrajput.nixlab.co.in/) | [GitHub](https://github.com/nixrajput/portfolio-nextjs) | Next.js, SCSS, Node.js | | Raphaël Chelly |  | [raphaelchelly.com/](https://www.raphaelchelly.com) | [GitHub](https://github.com/raphaelchelly/raph_www) | Next.js, TailwindCSS, Vercel | | Damian Demasi |  | [damiandemasi.com](https://www.damiandemasi.com/) | [GitHub](https://github.com/Colo-Codes/portfolio-v2) | ReactJS, TailwindCSS, DaisyUI | | Ifedili Onyegbu |  | [ifedili.com](https://www.ifedili.com) | [GitHub](https://github.com/saucecodee/ifedili.com) | Angular, TypeScript, SASS | | Daniel Cranney |  | [danielcranney.com/](https://www.danielcranney.com/) | [GitHub](https://github.com/danielcranney/portfolio) | NextJS, TailwindCSS, Vercel | | Abdellatif Laghjaj |  | [abdellatif-laghjaj.ml/](https://www.abdellatif-laghjaj.ml/) | None | VueJS, Lottilefiles, Verel, CSS | | Adham Dannaway |  | [adhamdannaway.com](https://www.adhamdannaway.com/) | None | Wordpress, PHP, jQuery, MySQL | | Khaled Mohamed |  | [James Oliver](https://james-oliver-portfolio.netlify.app/) | None | HTML5, CSS3, SCSS, Bootstrap5, TypeScript, SwipperJS, Fontello, PurgeCSS, Netlify | | Glayson Visgueira |  | [glaysonvisgueira.vercel.app](https://glaysonvisgueira.vercel.app/) | [GitHub](https://github.com/Glaysonvisgueira/glaysonvisgueira_next-js) | NextJS, Styled-components, NodeJS, Vercel, Animate.css, Lottiefiles | | Chai Phonbopit |  | [devahoy.com](https://devahoy.com/) | None | NextJS, Preact, Tailwind CSS, NodeJS | | Aravind Balla |  | [aravindballa.com](https://aravindballa.com) | [GitHub](https://github.com/aravindballa/website) | NextJS, TypeScript, Tailwind CSS, Vercel | | Khaled Mohamed |  | [Thomas David](https://thomas-david-portfolio.netlify.app/) | None | React JS, Tailwind CSS, AOS, SwipperJS, React Scroll, React Icons, React Laze Load Image, PostCSS, Netlify | | Tanishka Yadav |  | [tanishka-yadav.netlify.app](https://tanishka-yadav.netlify.app/) | [Github](https://github.com/Tanishka-dev/Portfolio-Reactjs) | ReactJS, Javascript, SASS, Framer Motion | | David Obodo |  | [davidobodo.com](https://www.davidobodo.com/) | None | NextJS, Typescript, SASS, GSAP, Jest, Sendgrid, Google Analytics | | Manuel David Gomez |  | [manueldavgomez.com](https://manueldavgomez.github.io/manueldavidgomez/) | [Github](https://github.com/ManuelDavGomez/manueldavidgomez) | ReactJs, Javascript, Css, Bootstrap, Bootstrap Icons, React-Animate-On-Scroll, React-Scroll, Vite, TsParticles | | Olasunkanmi Balogun |  | [kanmibalogun.vercel.app](https://kanmibalogun.vercel.app/) | [Github](https://github.com/SiR-PENt/folio-me) | NextJS, JavaScript, Tailwind, Framer-motion, vanilla CSS | | Priyankar Pal |  | [itspp.vercel.app](https://itspp.vercel.app) | [GitHub](https://github.com/priyankarpal/Priyankar) | HTML & SCSS | | Marieflor Bawanan |  | [marieflor.dev](https://marieflor.dev) | [GitHub](https://github.com/mariebawanan/marieflor.dev) | NextJS, TypeScript, TailwindCSS & GSAP | | Delba Oliviera |  | [delba.dev](https://delba.dev/) | [GitHub](https://github.com/delbaoliveira/website) | Next.js, MDX, Tailwind, Prisma, Typescript | | Vivek Patel |  | [vivek9patel.github.io](https://vivek9patel.github.io/) | [GitHub](https://github.com/vivek9patel/vivek9patel.github.io) | NextJS, Tailwind CSS, GitHub Pages | | Sarah Dayan |  | [sarahdayan.dev](https://www.sarahdayan.dev/) | None | NextJS, Tailwind CSS, NodeJS, Vercel | | Theodorus Clarence |  | [theodorusclarence.com](https://theodorusclarence.com/) | [Github](https://github.com/theodorusclarence/theodorusclarence.com) | NextJS, TypeScript, Tailwind CSS, MDX Bundler, Prisma | | Arafat Islam |  | [portfolio-khaki-iota-89.vercel.app](https://portfolio-khaki-iota-89.vercel.app/) | [Github](https://github.com/arafat4693/portfolio) | NextJS, TypeScript, GraphQL, Tailwind CSS | | Siddharth Verma |  | [iamdev.netlify.app/home.html](https://iamdev.netlify.app/home.html) | None | Tailwind, Javascript, React, html/CSS | | Abo Ghanbari |  | [aboghanbari.com](https://www.aboghanbari.com/) | None | Gatsby, Emotion, GSAP, Preact | | PATRICK T.LO |  | [pleaseleaveon.com](https://pleaseleaveon.com/) | None | HTML5, CSS, JavaScript, jQuery | | Aliyah Adefolake |  | [aliyahadefolake.com](https://www.aliyahadefolake.com/) | None | ReactJS, Gatsby, SASS, GSAP, Contentful | | Travis Fischer |  | [transitivebullsh.it](https://transitivebullsh.it/) | [Github](https://github.com/transitive-bullshit/nextjs-notion-starter-kit) | NextJS, TypeScript, Notion API, Vercel | | Lynn Fisher |  | [lynnandtonic.com](https://lynnandtonic.com/) | [Github](https://github.com/lynnandtonic/lynnandtonic.com) | HTML5, CSS, JavaScript, SVG, Netlify, GoatCounter, HSTS, Open Graph | | Danny Garcia |  | [danny-garcia.com](https://danny-garcia.com/) | [Github](https://github.com/dannygarcia/dannygarcia.github.com) | HTML5, CSS, JavaScript, TypeScript, GLSL, Netlify | | Robin Payot |  | [robinpayot.com](http://www.robinpayot.com/) | None | HTML5, CSS, JavaScript, GSAP, Howler.js, Hammer.js, three.js, WebGL, PWA, Open Graph, Apache | | Jesse Zhou |  | [jesse-zhou.com](https://jesse-zhou.com/) | [Github](https://github.com/enderh3art/Ramen-Shop) | HTML5, CSS, JavaScript, GLSL, Howler.js, GSAP, Three.js, Node.js, Vercel | | Rauno Freiberg |  | [rauno.me](https://rauno.me/) | None | NextJS, NodeJS, Stiches, Vercel | | Anurag Hazra |  | [anuraghazra.dev](https://anuraghazra.dev/) | [GitHub](https://github.com/anuraghazra/anuraghazra.github.io) | React, Gatsby, Styled-components, Cypress, Jest, TravisCI | | Hardik Gohil |  | [hardikgohilhlr.tech](https://hardikgohilhlr.tech/) | None | Next.js, TypeScript, Firebase, SCSS | | Jonathan Toon |  | [jonathontoon.com](https://jonathontoon.com/) | [Github](https://github.com/jonathontoon/jonathontoon.com) | Gulp, EsBuild, postCSS, Nunjuck | | Rafael Derolez |  | [derolez.dev](https://derolez.dev/) | None | NextJS, Sanity, ChakraUI, Emotion | | Chris Williams |  | [astro-theme-cactus.netlify.app](https://astro-theme-cactus.netlify.app/) | [Github](https://github.com/chrismwilliams/astro-theme-cactus) | Astro, Typescript, Tailwind CSS, MDX | | Ben Holmes |  | [bholmes.dev](https://bholmes.dev/) | [Github](https://github.com/bholmesdev/bholmesdev) | Gatsby, Javascript, SCSS, Pug | | Yasio |  | [yasio.dev](https://yasio.dev/) | [Github](https://github.com/YasiOnFire) | Nuxt.js, Node.js, core-js, Vue.js, VideoJS, Firebase, HSTS, Open Graph, HTTP/3, Webpack, PWA | | Alec Babala |  | [alecbabala.com](https://www.alecbabala.com/) | None | Next.js, Node.js, core-js, React, HSTS, Open Graph, Webpack, MobX, GSAP, Contentful | | Gavin Nelson |  | [nelson.co](https://nelson.co/) | [Github](https://github.com/gavinmn/nelson.co) | NextJS, Tailwind CSS, Vercel, MDX | | Yinka Adedire |  | [yinka.codes](https://www.yinka.codes/) | [Github](https://github.com/yinkakun/yinkakun-portfolio) | Gatsby, ReactJS, Styled-Components | | Abdullah Abdulfatah |  | [draq.tech](https://www.draq.tech/) | None | NextJS, Typescript, ChakraUI | | Samuel Imolorhe |  | [xkoji.dev](https://www.xkoji.dev/) | [Github](https://github.com/imolorhe/xkoji-code) | Gatsby, GSAP, JavaScript, Netlify | | Abu Said |  | [abusaid.netlify.app](https://abusaid.netlify.app/) | [GitHub](https://github.com/said7388/developer-portfolio) | Next.js, Tailwind CSS, Email.JS | | Quiet Node |  | [quiet-node.dev](https://quiet-node.dev) | [GitHub](https://github.com/quiet-node/portfolio-v2) | TypeScript, ReactJS, ViteJS, TailwindCSS, Motion Framer | | Daniel Wisky |  | [danielwisky.com.br](https://danielwisky.com.br/) | [GitHub](https://github.com/danielwisky/danielwisky.github.io) | HTML, CSS, JavaScript | | JJ Kasper |  | [jjsweb.site](https://jjsweb.site/) | [Github](https://github.com/ijjk/jjsweb.site) | NextJS, Vercel, CSS | | Cassidy Williams |  | [cassidoo.co](https://cassidoo.co/) | None | HTML, CSS, JavaScript | | Jahir Fiquitiva |  | [jahir.dev](https://jahir.dev/) | [Github](https://github.com/jahirfiquitiva/jahir.dev) | Next.js, Tailwind CSS, MDX, contentlayer, PlanetScale, Vercel, TypeScript | | Stefan Topalovic |  | [stefantopalovicdev.vercel.app](https://stefantopalovicdev.vercel.app/) | None | ReactJS, SCSS, Vercel | | Abdullah Moiz |  | [mrmoiz.vercel.app](https://mrmoiz.vercel.app/) | None | Next Js ,Tailwind css, Vercel | | Victor Williams |  | [victorwilliams.me](https://www.victorwilliams.me/) | [Github](https://github.com/victorcodess/folio-v1) | React, Next.js, TypeScript, TailwindCSS, Framer Motion, GSAP, Vercel | | Modupe Akanni |  | [modupe-akanni.vercel.app](https://modupe-akanni.vercel.app/) | [Github](https://github.com/Goketech/next-p) | React, Next.js, Styled Components, Vercel | | Anuoluwapo Abolarin |  | [anuoluwapo.xyz](https://anuoluwapo.xyz/) | [Github](https://github.com/Anu-oluwapo/portfolio-v2) | VueJS, SCSS, GSAP, Vite | | Andrew Branch |  | [blog.andrewbran.ch](https://blog.andrewbran.ch/) | [Github](https://github.com/andrewbranch/blog) | Gatsby, TypeScript, Emotion, Netlify | | Max Böck |  | [mxb.dev](https://mxb.dev/) | [Github](https://github.com/maxboeck/mxb) | Eleventy, SCSS, Nunjucks | | Shahriar Shafin |  | [shahriarshafin.github.io](https://shahriarshafin.github.io/) | [Github](https://github.com/shahriarshafin/myportfolio) | React, Next.js, Tailwind CSS | | Mukul Chugh |  | [mukulchugh.com](https://mukulchugh.com/) | None | React, Next.js, Styled Components, Netlify | | Vijay Verma |  | [vjy.me](https://vjy.me/) | None | NextJS, Styled Components, Vercel | | Jhey Tompkins |  | [jhey.dev](https://jhey.dev/) | [Github](https://github.com/jh3y/jhey.dev) | Sanity, Astro, Tailwind CSS, Netlify | | David Heckhoff |  | [david-hckh.com/](https://david-hckh.com/) | None | HTML, CSS, JavaScript, ThreeJS, GSAP, PWA, Howler.js | | Ashish |  | [asrvd.me](https://asrvd.me/) | [Github](https://github.com/asrvd/asrvd.me) | Next.js, tRPC, Tailwind CSS, TypeScript, NextAuth.js, Prisma | | Robb Owen |  | [robbowen.digital](https://robbowen.digital/) | None | HTML, CSS, JavaScript, Netlify | | Josh Comeau |  | [joshwcomeau.com](https://www.joshwcomeau.com/) | None | NextJS, Styled Components, MDX, MongoDB, Framer Motion, React Spring, Vercel | | Charles Bruyerre |  | [itssharl.ee](https://itssharl.ee/) | None | NextJS, ThreeJS, PWA, Vercel | | Patrick David |  | [bepatrickdavid.com](https://bepatrickdavid.com/) | None | HTML, CSS, JavaScript, jQuery, Plesk, ThreeJS, GSAP, PWA | | Seán Halpin |  | [seanhalpin.xyz](https://www.seanhalpin.xyz/) | None | Svelte, SvelteKit, Vite, PWA, Node.js | | Cyd Stumpel |  | [cydstumpel.nl](https://cydstumpel.nl/) | None | WordPress, PHP, ThreeJS, MySQL, GSAP, Lenis | | Tamal Sen |  | [tamalsen.dev](https://tamalsen.dev/) | None | WordPress, Elementor, PHP, MySQL, Anime.js | | Aristide Benoist |  | [aristidebenoist.com](https://aristidebenoist.com/) | None | PHP, JavaScript, WebGL, AWS | | Abhishek Jha |  | [abhishekjha.me](https://abhishekjha.me/) | None | HTML, CSS, JavaScript, GSAP, Varnish, Locomotive Scroll, Github Pages | | Robin Mastromarino |  | [robinmastromarino.com](http://robinmastromarino.com/) | None | HTML, CSS, JavaScript, WebGL, GSAP, Google Analytics | | Lanre Adelowo |  | [lanre.wtf](https://lanre.wtf/) | None | NextJS, CSS Modules, GSAP, Vercel, Hugo | | Prince Muhammad |  | [princemuhammad.pro](https://princemuhammad.pro) | None | JavaScript, React.js, Next.js, TailwindCSS | | Victor Adeniji |  | [codevickk.com](https://codevickk.com/) | None | Nuxt.js, Vue.js, GSAP, Netlify, Lenis | | Kaung Myat Kyaw |  | [barry121.com](https://barry121.vercel.app/) | [Github](https://github.com/Rhaegar121/Portfolio) | ReactJS, ThreeJS, TailwindCSS | | Eliaz LR |  | [eliaz-lr.dev](https://eliaz-lr.dev/) | [Github](https://github.com/Eliaz-LR/portfolio-v3) | Astro, TailwindCSS, Vue, DaisyUI | | Danny Johnson |  | [mrdannyjohnson.co.uk](https://www.mrdannyjohnson.co.uk/) | None | Astro, Vue, Sanity, Tailwind CSS | | Wahid Ali |  | [https://www.wahidali.dev](https://www.wahidali.dev/) | [Github](https://github.com/Aliwahid17/portfolio) | Svelte, Tailwind CSS, TypeScript, Vercel | | Deepanshu Mehra |  | [deeshu2002.github.io/folio](https://deeshu2002.github.io/folio) | [Github](https://github.com/deeshu2002/folio) | HTML, CSS, TypeScript, Vite, PWA | | Brian Lovin |  | [brianlovin.com](https://brianlovin.com/) | [Github](https://github.com/brianlovin/briOS) | NextJS, TypeScript, Tailwind CSS, Prisma, Planetscale | | Pritish Samal |  | [pritishsamal.com](https://pritishsamal.com/) | [Github](https://github.com/CIPHERTron/portfolio-v2) | Next.js, TypeScript, Emotion, Chakra UI | | Sandeep Kumar |  | [eternalfrustation.github.io](https://eternalfrustation.github.io/) | [Github](https://github.com/eternalfrustation/eternalfrustation.github.io) | HTML, CSS, JavaScript | | Mike Liu |  | [mikeliuu.com](https://mikeliuu.com) | [Github](https://github.com/mikeliuu/mikeliuu.com) | NextJS, TypeScript, Tailwind CSS, HTML, CSS, Vercel | | Bryan Smith |  | [multikitty.onrender.com](https://multikitty.onrender.com) | [Github](https://github.com/multikitty/multikitty.github.io) | HTML, CSS, JavaScript | | Goodness Urama |  | [goodie.work](https://www.goodie.work/) | [Github](https://github.com/GoodyBoy301/goodie.work) | Pug, SCSS, Javascript ThreeJS, GSAP, Vercel | | Zai Santillan |  | [plskz-me.vercel.app](https://plskz-me.vercel.app/) | [Github](https://github.com/plskz/plskz.me) | NextJS, TypeScript, Tailwind CSS, DaisyUI | | Ashutosh Hathidara |  | [ashutoshhathidara.com](https://ashutoshhathidara.com/#/) | [Github](https://github.com/ashutosh1919/masterPortfolio) | HTML5, CSS3, React, NextJS | | Syed Moshin |  | [opensource-portfolio.netlify.app](https://opensource-portfolio.netlify.app/) | [Github](https://github.com/devsyedmohsin/portfolio-template) | HTML5, CSS3, JavaScript | | David Angulo |  | [davidangulo.xyz](https://www.davidangulo.xyz/) | [Github](https://github.com/dcangulo/davidangulo.xyz) | HTML, Jekyl, Ruby, Bootstrap | | George Christeas |  | [chr-ge.com](https://chr-ge.com/) | [Github](https://github.com/chr-ge/chr-ge.com) | Next.js, Typescript, ChakraUI, Vercel | | Julien Thême |  | [julien-theme.dev](https://julien-theme.dev/) | [Github](https://github.com/ZIRTR0X/PersonalWebsite) | Angular, TailwindCSS, ThreeJs | | Shubh Porwal |  | [shubhporwal.me](https://www.shubhporwal.me/) | [Github](https://github.com/shubh73/devfolio) | NextJS, ReactJS, Tailwind CSS, GSAP | | Ross Moody |  | [rossmoody.com](https://rossmoody.com/) | [Github](https://github.com/rossmoody/rossmoody.com) | Next.js, Chakra UI, TypeScript, MDX, Netlify | | Rémy Beumier |  | [remybeumier.be](https://remybeumier.be/) | [Github](https://github.com/beumsk/beumsk.github.io) | Next.js, Sass, MDX, AOS | | Anirban Das |  | [anirbandas.in](https://www.anirbandas.in/) | [Github](https://github.com/anirban12d/portfolio-2023) | Qwik, React, Tailwind CSS | | Rafael Santana |  | [rafaelsantana.dev](https://www.rafaelsantana.dev/) | [Github](https://github.com/rafalmeida73/portfolio) | Next.js, Material UI, TypeScript | | Apoorv Maurya |  | [LivePortfolio](https://apoorv.onrender.com) | [Github](https://github.com/apoorvmaurya/portfolio) | HTML, CSS, JavaScript, | | Sumonta Saha Mridul |  | [sumonta056.github.io](https://sumonta056.github.io/) | [Github](https://github.com/Sumonta056/sumonta056.github.io) | HTML5, CSS3, JavaScript | | Daniel Coyula |  | [portfolio.dctech.dev](https://portfolio.dctech.dev/) | None | Flutter | | Shaan Alam |  | [shaanalam.vercel.app](https://shaanalam.vercel.app) | [GitHub](https://github.com/shaan-alam/shaanalam) | NextJS, Tailwind, TypeScript & Hygraph | | Gregory Koberger |  | [gkoberger.com](https://gkoberger.com/) | None | VueJS, GSAP, NodeJS, Express | | Monica Powell |  | [aboutmonica.com](https://aboutmonica.com/) | None | Gatsby, Emotion, Netlify | | Ismoilbek Ilxomov |  | [ismail.uz](https://ismail.uz/) | None | NextJS, TailwindCSS, Netlify | | Kehinde Omopariola |  | [pariola.dev](https://www.pariola.dev) | [Github](https://github.com/Pariola-droid/pariola-v2.2.0) | NextJS, Typescript, SASS, Motion One | | Shivam Gupta |  | [the-shivam-gupta.github.io](https://the-shivam-gupta.github.io/) | [Github](https://github.com/the-shivam-gupta/the-shivam-gupta.github.io) | HTML, CSS, JS | | Mateus Felipe Gonçalves |  | [mateusf.com](https://mateusf.com) | [Github](https://github.com/mateusfg7/mateusf.com) | Next.js, Typescript, Tailwindcss, Giscus, Contentlayer & MDX | | Anubhav Sigdel |  | [anubhavsigdel.vercel.app](https://anubhavsigdel.vercel.app/) | [GitHub](https://github.com/asigdel29/portfolio) | HTML, CSS, JS | | Krish Depani |  | [krish-depani.vercel.app](https://krish-depani.vercel.app/) | [GitHub](https://github.com/Krish-Depani/Portfolio-Website) | HTML & CSS | | Bona Brian Siagian |  | [bonabrian.com](https://bonabrian.com) | [GitHub](https://github.com/bonabrian/bonabrian.com) | Typescript, NextJs, TailwindCSS, Prisma, Contentlayer | | SofiDev |  | [itssofi.dev](https://itssofi.dev/) | [GitHub](https://github.com/SofiDevO/sofidev-portfolio-astro) | Astro, CSS, Javascript, React | | Sadee |  | [codewithsadee.github.io/vcard-personal-portfolio](https://codewithsadee.github.io/vcard-personal-portfolio/) | [Github](https://github.com/codewithsadee/vcard-personal-portfolio) | HTML, CSS, JavaScript | | Emmanuel Nsikan-david |  | [nsikandavid.dev](https://nsikandavid.dev) | None | ReactJS, CSS | | Cruip |  | [preview.cruip.com](https://preview.cruip.com/devspace/) | None | Alpine.JS, Tailwind CSS, Chartjs | | Dev Khandelwal |  | [slyro.vercel.app](https://slyro.vercel.app/) | [GitHub](https://github.com/khandelwaldev/dev) | Next.JS, Tailwind CSS, MDX | | Skifli |  | [skifli.github.io](https://skifli.github.io/) | [GitHub](https://github.com/skifli/skifli.github.io) | HTML, CSS, JavaScript | | Eva Decker |  | [evadecker.com](https://evadecker.com) | [GitHub](https://github.com/evadecker/evadecker.com) | Astro, React, TypeScript, Framer Motion | | Guglielmo Cerri |  | [guglielmocerri.github.io](https://guglielmocerri.github.io) | [GitHub](https://github.com/GuglielmoCerri/GuglielmoCerri.github.io) | HTML, CSS, JavaScript, reCAPTCHA | | Wisnu Wicaksono |  | [wiscaksono.com](https://wiscaksono.com/) | [GitHub](https://github.com/wiscaksono/wiscaksono-site) | Nextjs, Tailwind CSS, MDX, Next Auth | | Emmanuel Alabi |  | [emmanuelalabi.vercel.app](https://emmanuelalabi.vercel.app/) | None | HTML, TailwindCSS | | Zaher Al Majed |  | [zaher.design](https://zaher.design/) | None | React, TypeScript, NextJS, TailwindCSS | | Shivani Yadav |  | [shivaniyadav.online](https://shivaniyadav.online) | [GitHub](https://github.com/ShivaniYadav07/Portfolio) | React, TypeScript, ParticleJS, Hostinger, SCSS | | Matthias Kretschmann |  | [matthiaskretschmann.com](https://matthiaskretschmann.com/) | [GitHub](https://github.com/kremalicious/portfolio) | NextJS, TypeScript, CSS Modules, Vercel | | Le Vinh Khang |  | [levinhkhang.org](https://levinhkhang.org/) | [GitHub](https://github.com/levinhkhangzz/personal-website) | NextJS, TailwindCSS, React | | Ali Imam |  | [aliimam.in](https://www.aliimam.in/) | [GitHub](https://github.com/aliimam-in/aliimam) | NextJS, TailwindCSS, React, Lenis | | Ahmed Amer |  | [tammura.com](https://tammura.com/) | None | NextJS, TailwindCSS, Vercel, Cloudflare | | Alpay Celik |  | [alpaycelik.dev](https://alpaycelik.dev/) | [GitHub](https://github.com/AlpayC/portfolio_site) | NextJS, TailwindCSS, Typescript, Framer Motion, Swiper, Vercel, NodeMailer | | Hanaia Youcef |  | [poysa213.me](https://poysa213.me/) | [GitHub](https://github.com/poysa213/portfolio) | Typescript, NextJS, TailwindCSS, Framer Motion | | Jaber Said |  | [jaberdev.com](https://jaberdev.com) | [GitHub](https://github.com/Jaber-Saed/3d-protfoluo) | React JS, Tailwind CSS, Three JS | | Xiaohan Zou |  | [portfolio.zxh.io](https://portfolio.zxh.io) | [GitHub](https://github.com/Renovamen/playground-macos) | React JS, Zustand, UnoCSS, Typescript, Vite | | Manh Hung Dao |  | [age-of-23.vercel](https://age-of-23.vercel.app/) | [GitHub](https://github.com/mahhung12/AgeOf23) | Nextjs, MDX, Tailwind CSS, TypeScript, JavaScript | | CuB3y0nd |  | [cubeyond.net](https://cubeyond.net) | [GitHub](https://github.com/CuB3y0nd/cubeyond.net) | Nextjs, MDX, Tailwind CSS, TypeScript | | Baraa Alshaer |  | [alshaer.vercel.app](https://alshaer.vercel.app/) | [GitHub](https://github.com/balshaer/alshaer) | React JS, Typescript, Shadcn ui , Tailwind CSS | | Sameera Sandakelum |  | [sameerasw.com](https://sameerasw.com/) | [GitHub](https://github.com/sameerasw/sameerasw.com) | HTML, CSS, Javascript, Netlify | | Jam Moonbami |  | [moonbamiofficial.vercel.app](https://moonbamiofficial.vercel.app) | [GitHub](https://github.com/MoonbamiOfficial/dev-portfolio) | Next.js, Node.js, React, Tailwind CSS, MongoDB, Vercel | | Asharib Ali |  | [cv.asharib.xyz](https://cv.asharib.xyz/) | [GitHub](https://github.com/AsharibAli/cv) | Next.js, React, Typescript, Shadcn/ui, Tailwind CSS, Vercel | | MAHG |  | [mahg.me](https://mahg.me) | [GitHub](https://github.com/mahg0899/mahgv2) | NextJS, React, Typescript, TailwindCSS, Vercel | | Sunidhi Singh |  | [sunidhi-singh.netlify.app](https://sunidhi-singh.netlify.app/) | [GitHub](https://github.com/sunidhi014) | HTML, CSS, JavaScript | | Dhairya Majmudar |  | [https://dhaiyra-majmudar.netlify.app](https://dhaiyra-majmudar.netlify.app) | [Github](https://github.com/DhairyaMajmudar/Personal-Portfolio) | React, Tailwind , Material UI | | Jay Bhavsar |  | [https://jay.is-savvy.dev](https://jay.is-savvy.dev) | [Github](https://github.com/jbhv12/portfolio) | Vue, Gridsome, Tailwind CSS | | Siyana Zdravkova |  | [professionalportfolio](https://bluebutterflies.github.io/professionalportfolio/) | [Github](https://github.com/BlueButterflies/professionalportfolio) | Javascript, JSON, React JS, Bootstrap, Tachyons, animate.css, Tspracticles | | Anshul Gora |  | [anshulwork.netlify.app](https://anshulwork.netlify.app/) | None | ReactJs, Bootstrap, Vanilla CSS, Javascript | | Dogan Merden |  | [doganmerden.vercel.app](https://doganmerden.vercel.app/) | None | Next.js, TypeScript, Tailwind CSS, AuthJs, next-intl, Daisy UI, framer-motion | | Ibrahim Sadik Tamim |  | [tam11a.dev](https://tam11a.dev) | [GitHub](https://github.com/tam11a/tam11a.dev) | NextJS, TypeScript, TailwindCSS, Framer, GSAP | | Dipesh Murmu |  | [portfolio.itsmedipesh.xyz](https://portfolio.itsmedipesh.xyz/) | None | Laravel PHP, Tailwind, JavaScript, CSS | | Akshay kumar |  | [akshaytalanki19.com](https://akshaytalanki.netlify.app/) | [GitHub](https://github.com/akshaytalanki19/portfolio) | Html, CSS, JavaScript | | Pieter-Jan Scheir |  | [pieterjanscheir.com](https://www.pieterjanscheir.com/) | None | React/Next.js, Typescript, Tailwindcss, Vercel, Lucide | | Huy Nguyen |  | [huyng.xyz](https://www.huyng.xyz/) | None | React.js, TailwindCSS, GSAP, Lenis | | Anshul Soni |  | [anshulsoni.in](https://www.anshulsoni.in/) | [GitHub](https://github.com/anshulsoni2010/portfolio-website) | HTML, CSS, JavaScript, Other Libraries | | David Simoes |  | [davesimoesportfolio.netlify.app](https://davesimoesportfolio.netlify.app/) | [GitHub](https://github.com/DaveSimoes/Developer.Portfolio) | HTML, CSS, JavaScript | | Saahil Dutta |  | [saahild.com](https://saahild.com/) | [GitHub](https://github.com/NeonGamerBot-QK/saahild.com) | Reactjs | | Moshood Sanusi |  | [olawale.dev](https://www.olawale.dev/) | None | ReactJS, TailwindCSS, GSAP | | MD Affan Asghar |  | [affancoder.github.io/Portfolio_Website](https://affancoder.github.io/Portfolio_Website/) | [GitHub](https://github.com/affancoder/Portfolio_Website) | HTML, CSS, JavaScript | | DEBAJYOTI GHOSH |  | [convolexa-2503.web.app](https://convolexa-2503.web.app/) | None | React JS | | Muhammad Naeem Tahir |  | [muhammadnaeemtahir.github.io](https://muhammadnaeemtahir.github.io/) | [GitHub](https://github.com/muhammadnaeemtahir/muhammadnaeemtahir.github.io) | HTML, CSS, JavaScript, Bootstrap | | Aravind Ashokan |  | [aravind.xyz](https://aravind.xyz) | [GitHub](https://github.com/code-lover636/aravindashokan) | ReactJS, CSS(SASS), Framer Motion, SwiperJS, EmailJS | | Moinak Majumdar |  | [moinak05.portfolio](https://moinak05.vercel.app/) | [GitHub](https://github.com/Moinak-Majumdar/portfolio) | Next.js, TypeScript, Framer Motion, TailwindCss | | Saleh Salehizadeh |  | [SirSaleh.github.io](https://sirsaleh.github.io/Portfolio/) | [GitHub](https://github.com/SirSaleh/Portfolio) | Nextjs, Tailwind CSS, TypeScript | | Vijay Kumar Reddy Talakola |  | [talakolavijay.vercel.app](https://talakolavijay.vercel.app/) | [GitHub](https://github.com/VijayKumarReddyTalakola/MyPortFolio) | Reactjs, Tailwind CSS, AOS | | Nisarg Kavi |  | [nisargkavi.in](https://www.nisargkavi.in/) | None | Nextjs, Tailwind CSS, Framer Motion, AnimeJS | | Malik Naik |  | [maliknaik.me](https://www.maliknaik.me/) | None | HTML, CSS, Bootstrap, and JavaScript | | Kshitij Gehlot |  | [KDGehlot2003.github.io](https://kdgehlot2003.github.io/Portfolio/) | [GitHub](https://github.com/KDGehlot2003/Portfolio) | HTML, CSS, Bootstrap, and JavaScript | | Johnson Takashi |  | [johnson-takashi-blockchain.web.app](https://johnson-takashi-blockchain.web.app/) | [GitHub](https://github.com/John-T45/John-T45.github.io) | HTML, CSS, Bootstrap, and JavaScript | <!-- === ⭐ PORTFOLIO LINE END ⭐ === --> ## Suggestions Do you have any portfolio you want to see added but you can't add it yourself? Just mention it in this [issue](https://github.com/Evavic44/portfolio-ideas/issues/104) and it will be picked up by the community. You can also raise a PR to add any of the portfolios suggested here as well. ## Sponsor As you build your portfolio we hope you get that job or achieve what you want with it. Don't forget to star this project if you find it helpful. If you like this project and want to give back, consider buying me a coffee. I'll appreciate every cup. ☕ <a href="https://buymeacoffee.com/victoreke"> <img width="170px" alt="bmc-button" src="https://user-images.githubusercontent.com/62628408/163418953-1d32bf9c-317b-44ca-b773-44e36140fc9d.png"> </a> ## Contributors Thanks goes to these wonderful people. ([emoji key](https://allcontributors.org/docs/en/emoji-key)): <!-- ALL-CONTRIBUTORS-BADGE:START - Do not remove or modify this section --> <!-- ALL-CONTRIBUTORS-LIST:START - Do not remove or modify this section --> <!-- prettier-ignore-start --> <!-- markdownlint-disable --> <table> <tbody> <tr> <td align="center" valign="top" width="14.28%"><a href="http://victoreke.com"><img src="https://avatars.githubusercontent.com/u/62628408?v=4?s=100" width="100px;" alt="Victor Eke "/><br />_{<b>Victor Eke </b>}</a><br /><a href="#maintenance-Evavic44" title="Maintenance">🚧</a> <a href="https://github.com/Evavic44/portfolio-ideas/commits?author=Evavic44" title="Code">💻</a> <a href="https://github.com/Evavic44/portfolio-ideas/commits?author=Evavic44" title="Documentation">📖</a> <a href="https://github.com/Evavic44/portfolio-ideas/issues?q=author%3AEvavic44" title="Bug reports">🐛</a></td> <td align="center" valign="top" width="14.28%"><a href="https://israelmitolu.netlify.app"><img src="https://avatars.githubusercontent.com/u/53873209?v=4?s=100" width="100px;" alt="Israel Mitolu"/><br />_{<b>Israel Mitolu</b>}</a><br /><a href="https://github.com/Evavic44/portfolio-ideas/commits?author=israelmitolu" title="Code">💻</a> <a href="https://github.com/Evavic44/portfolio-ideas/commits?author=israelmitolu" title="Documentation">📖</a></td> <td align="center" valign="top" width="14.28%"><a href="https://piyushgoyani.thesourcepedia.org"><img src="https://avatars.githubusercontent.com/u/18528418?v=4?s=100" width="100px;" alt="Piyush Goyani"/><br />_{<b>Piyush Goyani</b>}</a><br /><a href="https://github.com/Evavic44/portfolio-ideas/commits?author=piyush-multiplexer" title="Code">💻</a> <a href="https://github.com/Evavic44/portfolio-ideas/commits?author=piyush-multiplexer" title="Documentation">📖</a></td> <td align="center" valign="top" width="14.28%"><a href="http://frankiefab.com"><img src="https://avatars.githubusercontent.com/u/46662771?v=4?s=100" width="100px;" alt="Franklin Ohaegbulam"/><br />_{<b>Franklin Ohaegbulam</b>}</a><br /><a href="https://github.com/Evavic44/portfolio-ideas/commits?author=frankiefab100" title="Code">💻</a> <a href="https://github.com/Evavic44/portfolio-ideas/commits?author=frankiefab100" title="Documentation">📖</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/vimode"><img src="https://avatars.githubusercontent.com/u/39148877?v=4?s=100" width="100px;" alt="vimode"/><br />_{<b>vimode</b>}</a><br /><a href="https://github.com/Evavic44/portfolio-ideas/commits?author=vimode" title="Code">💻</a> <a href="https://github.com/Evavic44/portfolio-ideas/commits?author=vimode" title="Documentation">📖</a></td> </tr> </tbody> </table> <!-- markdownlint-restore --> <!-- prettier-ignore-end --> <!-- ALL-CONTRIBUTORS-LIST:END --> This project follows the [all-contributors](https://github.com/all-contributors/all-contributors) specification. Contributions of any kind welcome!

A curation of awesome portfolio website ideas for developers and designers to draw inspiration from. Raise a pull request to add more. 💜

designers,developer-portfolio,ideas,portfolio,portfolio-website,devfolio,portfolio-ideas,inspiration,resume,personal-website

superfly/litefs

LiteFS    ====== LiteFS is a FUSE-based file system for replicating SQLite databases across a cluster of machines. It works as a passthrough file system that intercepts writes to SQLite databases in order to detect transaction boundaries and record changes on a per-transaction level in [LTX files](https://github.com/superfly/ltx). This project is actively maintained but is currently in a beta state. Please report any bugs as an issue on the GitHub repository. You can find a [Getting Started guide](https://fly.io/docs/litefs/getting-started/) on [LiteFS' documentation site](https://fly.io/docs/litefs/). Please see the [ARCHITECTURE.md](/docs/ARCHITECTURE.md) design document for details about how LiteFS works. ## SQLite TCL Test Suite It's a goal of LiteFS to pass the SQLite TCL test suite, however, this is currently a work in progress. LiteFS doesn't have database deletion implemented yet so that causes many tests to fail during teardown. To run a test from the suite against LiteFS, you can use the `Dockerfile.test` to run it in isolation. First build the Dockerfile: ```sh docker build -t litefs-test -f Dockerfile.test . ``` Then run it with the filename of the test you want to run. In this case, we are running `select1.test`: ```sh docker run --device /dev/fuse --cap-add SYS_ADMIN -it litefs-test select1.test ``` ## Contributing LiteFS contributions work a little different than most GitHub projects. If you have a small bug fix or typo fix, please PR directly to this repository. If you would like to contribute a feature, please follow these steps: 1. Discuss the feature in an issue on this GitHub repository. 2. Create a pull request to **your fork** of the repository. 3. Post a link to your pull request in the issue for consideration. This project has a roadmap and features are added and tested in a certain order. Additionally, it's likely that code style, implementation details, and test coverage will need to be tweaked so it's easier to for me to grab your implementation as a starting point when implementing a feature.

FUSE-based file system for replicating SQLite databases across a cluster of machines

sqlite

synercys/annotated_latex_equations

The file "eqn_annotate.tex" is the main latex file. This repository provides four examples of annotated equations: 1. [example_prob.tex] A simple one inside the equation construct, in a double column format 2. [example_prob2.tex] A more complex one, but this time inside the figure construct in a double column format 3. [example_laplace.tex] Inside the wrapfigure construct but for a single column format 4. [example_overlay.tex] More complicated examples, side-by-side using the minipage construct in a single column format The folder, "example_output_figs" includes figures that show the outputs of the above four cases. Note: the main latex file, "eqn_annotate.tex" includes many latex packages and some definitions that are required. To build all the examples into a single file, type: > make OR > pdflatex (or xelatex) eqn_annotate The output PDF file (containing all the examples) is named: eqn_annotate.pdf **Update**: There is now a [Latex package](https://github.com/st--/annotate-equations) that makes it easier to create annotated equations! Check it out. They have even [created a demo file that uses the same examples as mine](https://github.com/st--/annotate-equations/blob/main/examples/sibin_demo.tex). Link to the [CTAN package](https://ctan.org/pkg/annotate-equations) page. # Examples # * [example_prob.tex] A simple one inside the equation construct, in a double column format  * [example_prob2.tex] A more complex one, but this time inside the figure construct in a double column format  * [example_laplace.tex] Inside the wrapfigure construct but for a single column format  * [example_overlay.tex] More complicated examples, side-by-side using the minipage construct in a single column format 

Examples of how to create colorful, annotated equations in Latex using Tikz.

cloudnative-pg/cloudnative-pg

[](https://landscape.cncf.io/?item=app-definition-and-development--database--cloudnativepg) [][latest-release] [][license] [![Documentation][documentation-badge]][documentation] [][stackoverflow] # Welcome to the CloudNativePG project! **CloudNativePG** is a comprehensive open source platform designed to seamlessly manage [PostgreSQL](https://www.postgresql.org/) databases within Kubernetes environments, covering the entire operational lifecycle from initial deployment to ongoing maintenance. The main component is the CloudNativePG operator. CloudNativePG was originally built and sponsored by [EDB](https://www.enterprisedb.com). ## Table of content - [Code of conduct](CODE_OF_CONDUCT.md) - [Governance policies](https://github.com/cloudnative-pg/governance/blob/main/GOVERNANCE.md) - [Contributing](CONTRIBUTING.md) - [Adopters](ADOPTERS.md) - [License](LICENSE) ## Getting Started The best way to get started is with the ["Quickstart"](docs/src/quickstart.md) section in the documentation. ## Scope The goal of CloudNativePG is to increase the adoption of PostgreSQL, one of the most loved DBMS in traditional VM and bare metal environments, inside Kubernetes, thus making the database an integral part of the development process and GitOps CI/CD automated pipelines. ### In scope CloudNativePG has been designed by Postgres experts with Kubernetes administrators in mind. Put simply, it leverages Kubernetes by extending its controller and by defining, in a programmatic way, all the actions that a good DBA would normally do when managing a highly available PostgreSQL database cluster. Since the inception, our philosophy has been to adopt a Kubernetes native approach to PostgreSQL cluster management, making incremental decisions that would answer the fundamental question: "What would a Kubernetes user expect from a Postgres operator?". The most important decision we made is to have the status of a PostgreSQL cluster directly available in the `Cluster` resource, so to inspect it through the Kubernetes API. We've fully embraced the operator pattern and eventual consistency, two of the core principles upon which Kubernetes is built for managing complex applications. As a result, the operator is responsible for managing the status of the `Cluster` resource, keeping it up to date with the information that each PostgreSQL instance manager regularly reports back through the API server. Changes to the cluster status might trigger, for example, actions like: * a PostgreSQL failover where, after an unexpected failure of a cluster's primary instance, the operator itself elects the new primary, updates the status, and directly coordinates the operation through the reconciliation loop, by relying on the instance managers * scaling up or down the number of read-only replicas, based on a positive or negative variation in the number of desired instances in the cluster, so that the operator creates or removes the required resources to run PostgreSQL, such as persistent volumes, persistent volume claims, pods, secrets, config maps, and then coordinates cloning and streaming replication tasks * updates of the endpoints of the PostgreSQL services that applications rely on to interact with the database, as Kubernetes represents the single source of truth and authority * updates of container images in a rolling fashion, following a change in the image name, by first updating the pods where replicas are running, and then the primary, issuing a switchover first The latter example is based on another pillar of CloudNativePG: immutable application containers - as explained in the [blog article "Why EDB Chose Immutable Application Containers"](https://www.enterprisedb.com/blog/why-edb-chose-immutable-application-containers). The above list can be extended. However, the gist is that CloudNativePG exclusively relies on the Kubernetes API server and the instance manager to coordinate the complex operations that need to take place in a business continuity PostgreSQL cluster, without requiring any assistance from an intermediate management tool responsible for high availability and failover management like similar open source operators. CloudNativePG also manages additional resources to help the `Cluster` resource manage PostgreSQL - currently `Backup`, `ClusterImageCatalog`, `ImageCatalog`, `Pooler`, and `ScheduledBackup`. Fully embracing Kubernetes means adopting a hands-off approach during temporary failures of the Kubernetes API server. In such instances, the operator refrains from taking action, deferring decisions until the API server is operational again. Meanwhile, Postgres instances persist, maintaining operations based on the latest known state of the cluster. ### Out of scope CloudNativePG is exclusively focused on the PostgreSQL database management system maintained by the PostgreSQL Global Development Group (PGDG). We are not currently considering adding to CloudNativePG extensions or capabilities that are included in forks of the PostgreSQL database management system, unless in the form of extensible or pluggable frameworks. CloudNativePG doesn't intend to pursue database independence (e.g. control a MariaDB cluster). ## Communications - [Slack Channel](https://join.slack.com/t/cloudnativepg/shared_invite/zt-2ij5hagfo-B04EQ9DUlGFzD6GEHDqE0g) - [Github Discussions](https://github.com/cloudnative-pg/cloudnative-pg/discussions) - [Twitter](https://twitter.com/CloudNativePg) ## Resources - [Roadmap](https://github.com/orgs/cloudnative-pg/projects/1) - [Website](https://cloudnative-pg.io) - [FAQ](docs/src/faq.md) - [Blog](https://cloudnative-pg.io/blog/) ## Adopters A list of publicly known users of the CloudNativePG operator is in [ADOPTERS.md](ADOPTERS.md). Help us grow our community and CloudNativePG by adding yourself and your organization to this list! ### CloudNativePG at KubeCon - March 21 2024, KubeCon Europe 2024 in Paris: ["Scaling Heights: Mastering Postgres Database Vertical Scalability with Kubernetes Storage Magic"](https://kccnceu2024.sched.com/event/1YeM4/scaling-heights-mastering-postgres-database-vertical-scalability-with-kubernetes-storage-magic-gabriele-bartolini-edb-gari-singh-google) (Gari Singh, Google & Gabriele Bartolini, EDB) - March 19 2024, Data on Kubernetes Day at KubeCon Europe 2024 in Paris: ["From Zero to Hero: Scaling Postgres in Kubernetes Using the Power of CloudNativePG"](https://colocatedeventseu2024.sched.com/event/1YFha/from-zero-to-hero-scaling-postgres-in-kubernetes-using-the-power-of-cloudnativepg-gabriele-bartolini-edb) (Gabriele Bartolini, EDB) - 7 November 2023, KubeCon North America 2023 in Chicago: ["Disaster Recovery with Very Large Postgres Databases (in Kubernetes)"](https://kccncna2023.sched.com/event/1R2ml/disaster-recovery-with-very-large-postgres-databases-gabriele-bartolini-edb-michelle-au-google) (Michelle Au, Google & Gabriele Bartolini, EDB) - 27 October 2022, KubeCon North America 2022 in Detroit: ["Data On Kubernetes, Deploying And Running PostgreSQL And Patterns For Databases In a Kubernetes Cluster"](https://kccncna2022.sched.com/event/182GB/data-on-kubernetes-deploying-and-running-postgresql-and-patterns-for-databases-in-a-kubernetes-cluster-chris-milsted-ondat-gabriele-bartolini-edb) (Chris Milsted, Ondat & Gabriele Bartolini, EDB) ### Useful links - [Data on Kubernetes (DoK) Community](https://dok.community/) - ["How to migrate your PostgreSQL database in Kubernetes with ~0 downtime from anywhere" by Gabriele Bartolini](https://gabrielebartolini.it/articles/2024/03/cloudnativepg-recipe-5-how-to-migrate-your-postgresql-database-in-kubernetes-with-~0-downtime-from-anywhere/) (March 2024) - ["Maximizing Microservice Databases with Kubernetes, Postgres, and CloudNativePG" by Gabriele Bartolini](https://gabrielebartolini.it/articles/2024/02/maximizing-microservice-databases-with-kubernetes-postgres-and-cloudnativepg/) (February 2024) - ["Recommended Architectures for PostgreSQL in Kubernetes" by Gabriele Bartolini](https://www.cncf.io/blog/2023/09/29/recommended-architectures-for-postgresql-in-kubernetes/) (September 2023) - ["The Current State of Major PostgreSQL Upgrades with CloudNativePG" by Gabriele Bartolini](https://www.enterprisedb.com/blog/current-state-major-postgresql-upgrades-cloudnativepg-kubernetes) (August 2023) - ["The Rise of the Kubernetes Native Database" by Jeff Carpenter](https://thenewstack.io/the-rise-of-the-kubernetes-native-database/) (December 2022) - ["Why Run Postgres in Kubernetes?" by Gabriele Bartolini](https://cloudnativenow.com/kubecon-cnc-eu-2022/why-run-postgres-in-kubernetes/) (May 2022) - ["Shift-Left Security: The Path To PostgreSQL On Kubernetes" by Gabriele Bartolini](https://www.tfir.io/shift-left-security-the-path-to-postgresql-on-kubernetes/) (April 2021) - ["Local Persistent Volumes and PostgreSQL usage in Kubernetes" by Gabriele Bartolini](https://www.2ndquadrant.com/en/blog/local-persistent-volumes-and-postgresql-usage-in-kubernetes/) (June 2020) ## Star History [](https://star-history.com/#cloudnative-pg/cloudnative-pg&Date) ## Trademarks *[Postgres, PostgreSQL and the Slonik Logo](https://www.postgresql.org/about/policies/trademarks/) are trademarks or registered trademarks of the PostgreSQL Community Association of Canada, and used with their permission.* [stackoverflow]: https://stackoverflow.com/questions/tagged/cloudnative-pg [latest-release]: https://github.com/cloudnative-pg/cloudnative-pg/releases/latest [documentation]: https://cloudnative-pg.io/documentation/current/ [license]: https://github.com/cloudnative-pg/cloudnative-pg?tab=Apache-2.0-1-ov-file#readme [documentation-badge]: https://img.shields.io/badge/Documentation-white?logo=data%3Aimage%2Fpng%3Bbase64%2CiVBORw0KGgoAAAANSUhEUgAAACAAAAAgCAYAAABzenr0AAAGN0lEQVR4nJRXXWwcVxU%2B8%2F%2BzP%2BPZtR2v7dqy07jUJUALNaiK6lZyUVVKWgGKaIv8QCMekBAVQlQICcEzVZFQVYFKQhASEBHlISJPCRJEshTFChgrIYHEiYMh69jetffHM7Mzc%2B9Bs7vjnTs7yZpZWbt37s%2F5zne%2Bc861CD0eXRkbHc3NfjeffvxNAGEAgULD2756v35%2B3qe1Nc4fnQVEXlA2LnOcXlCF8S%2B6vvVgq%2FL3M65X3e51PvfQCU4WJgZe%2B8GQ8fS7AKgjBB8KEHwjDXZSjkf0CREAaXM2eI9c65siqWxWl360Xl74ANHz%2Fy8AitxnTBfmz%2BhyYS4wGhwObQCIHSA0AigOMBzvOsXzd4pnjyL6NMmWEH8hi2b28Og3%2FqRJA0ewfQy0v1vGO2NovwPo%2FEU%2FwVgSU1PI%2BSu79v3lJAB8HM%2BTI%2FO%2FUUXzM4xHIe0xI4DdRqOAwnF%2F38ePPyzaDIDh%2FMxcWh462m08aojuGY97C0nrAEHg9BlF0fmeAPr0J15vbaKsp0BZQzEDEAlP9B209UIIVXUta%2FQEQHwxgxFjTc%2BRskAwrgVWmHtg22vMPJwLDqGUNJIAMHVAkGu3WdpZz6NAkgSXpINSycluV28er1a3rJ4M3F2%2F9AtCvXKycRrTQttrjINjxxxIL9jevxdaDHU%2FTBr6pL5ruzuLZubgUQBOY2hPij3GBUe7tBCMBRE2KrXVSz0BBI%2FtPVgtV%2F%2FxkZ5WSjI%2F%2BFIXC3sHJwgT4yFqrZFFTSlVrp3sGYLwcfxSmXCbS00j2Ms4K7qkOsFx6qdTuiHtG4AimfmM8NyvOvR2G48qXtZ2fsfrN7%2BqpcRyUp0glKiimDm4TwAcHBp%2B9WeA4ki0GMWNR9OVF8BZvn7xtI%2FF09H8jzLEgz6yLwCDuelnFXHkTZZOytCOEdqDOtGwsm%2BNj00fXt%2B6%2Bj4vcA7bwNrZwENmXwAKuZnvsNRThs5ozMPfPiHyoDF7xiduHcXb70A8dRFheHjiySQATBZk0nl9MHPkBEWUoEtYjyrPFNwGzfdlD37Zdu98KCv%2BMmD2BYpUCvcST39e0%2BS1Wr249FAAg7mPzWrS5NstEbE0xrsiA6QN1PfRFLnhr%2BspxVJTlY8Mw1DqNXeyCQFREEXz9cHB0QOev73QaNhOF4B%2B45PHFHFgDhJTqjuubJFqX1KQco7NTTuW8kq95k2G4eLEGzM7lfItnjNeTKcOfV%2FT8hOuV77A9IK0XjgMpCO0ZiuV3L%2F6njCFAOmucGB3OII5XgCXEJTDdZLElVbu3Vz0fWexvL30k0B6ggBACOmIUBAEUKX0dDTvW7RCYcdZPq6n%2FSsQnUO2RuyBRgQ9Rc5mMvJ6CNIj1nXfd9qWAsCkaZzJAk1L8UjVqY737dSjfCGrPHWqXL32Q0mB%2F2BXnke00WaEYv2aTzAbnuV5pcWkDGAAGJmhSafh6hjr%2BW2SVYHrP7bb%2BOdPW%2FUgflGlTM2gaK%2Ft7tp6%2BN6yixdN89DcIwGktIFPABfNbwoQqQWEUnDJzg1g0jDeK5p7Kp7nensXFI7uyAr%2FLyM7fYLnpa6LYScE8vDnot5hrKlslm%2BfE3nVxJgO4o3KcYu%2FF8XM8yFQ27n%2F65Te%2FzKl3Jhpjj6TCIDneRD5%2FItxr1vdkALw7p1qfeWPpjHxMtsXaPxu6FLc%2BrnbSB1r7fcrlr36nqwMzQfnplJDryQCGOh%2FbLjhcM%2FEvQ4Pdund9xRV5m1LfTXaF%2BK9gsLGB9nsgddcz8thM%2FarPzYM8%2FFazf9sMFaU%2Fi%2FwvNANwEhPvUGR8ozn7d%2BiDKXixtKpbHp81nV9E7puRy31ixKUbOe%2Fv3Ud891ghhDrL5Z975eaOvV%2BCNRp0Gfz%2BcJjDABdTwlpdfKbId0t5XYAcHz5D5ZVtWUp9%2Flog2L7PgVJqZx0HOE5Cqghemv1%2Bt%2FeGBmZ%2BdB2yNN72UEpnzXG32YADA186i3bIpPxMhuKrFK%2Fd77JUnbkKbYvRJlC8DzKSZK76Lq1he2dKy%2BZuSfesSz5a2xHDbLJ%2BJaqdv5H4EUY%2BzbG2m9HgN7mg81bfw4W1uu7AjvHaqDhqF%2FZ3Fq5XFy%2FcESSDsx5fvZ7wLEsNfXk%2BjlVHfpSCOB%2FAQAA%2F%2F8zd8orZc2N9AAAAABJRU5ErkJggg%3D%3D

CloudNativePG is a comprehensive platform designed to seamlessly manage PostgreSQL databases within Kubernetes environments, covering the entire operational lifecycle from initial deployment to ongoing maintenance

postgres,postgresql,kubernetes,k8s,database,sql,operator,database-management,high-availability,self-healing

DGP-Studio/Snap.Hutao

 胡桃工具箱是一款以 MIT 协议开源的原神工具箱，专为现代化 Windows 平台设计，旨在改善桌面端玩家的游戏体验。通过将既有的官方资源与开发团队设计的全新功能相结合，提供了一套完整且实用的工具集，且无需依赖任何移动设备。它不对游戏客户端进行任何破坏性修改以确保工具箱的安全性 Snap Hutao is an open-source Genshin Impact toolkit under MIT license, designed for modern Windows platform to improve the gaming experience for desktop players. By combining existing official resources with new features designed by the development team, it provides a complete and useful set of tools without the need to rely on mobile devices. Snap Hutao does not take any destructive modification to the game client to ensure the security of the toolkit. ## 安装 / Installation  [](https://github.com/DGP-Studio/Snap.Hutao/releases/latest) []() --- 你可以按照[快速开始](https://hut.ao/zh/quick-start.html)文档中提供的流程安装并设置 Snap Hutao。 You can follow the instructions in the [Quick Start](https://hut.ao/en/quick-start.html) document to install and set up Snap Hutao. ## 本地化翻译 / Localization [].data.translationProgress&url=https%3A%2F%2Fbadges.awesome-crowdin.com%2Fstats-15670597-565845.json)](https://crowdin.com/project/snap-hutao) [].data.translationProgress&url=https%3A%2F%2Fbadges.awesome-crowdin.com%2Fstats-15670597-565845.json)](https://crowdin.com/project/snap-hutao) [].data.translationProgress&url=https%3A%2F%2Fbadges.awesome-crowdin.com%2Fstats-15670597-565845.json)](https://crowdin.com/project/snap-hutao) [].data.translationProgress&url=https%3A%2F%2Fbadges.awesome-crowdin.com%2Fstats-15670597-565845.json)](https://crowdin.com/project/snap-hutao) [].data.translationProgress&url=https%3A%2F%2Fbadges.awesome-crowdin.com%2Fstats-15670597-565845.json)](https://crowdin.com/project/snap-hutao) [].data.translationProgress&url=https%3A%2F%2Fbadges.awesome-crowdin.com%2Fstats-15670597-565845.json)](https://crowdin.com/project/snap-hutao) [].data.translationProgress&url=https%3A%2F%2Fbadges.awesome-crowdin.com%2Fstats-15670597-565845.json)](https://crowdin.com/project/snap-hutao) [].data.translationProgress&url=https%3A%2F%2Fbadges.awesome-crowdin.com%2Fstats-15670597-565845.json)](https://crowdin.com/project/snap-hutao) [].data.translationProgress&url=https%3A%2F%2Fbadges.awesome-crowdin.com%2Fstats-15670597-565845.json)](https://crowdin.com/project/snap-hutao) Snap Hutao 使用 [Crowdin](https://translate.hut.ao/) 作为客户端文本翻译平台，在该平台上你可以为你熟悉的语言提交翻译文本。我们感谢每一个为 Snap Hutao 做出贡献的社区成员，并且欢迎更多的朋友能参与到这个项目中。 Snap Hutao uses [Crowdin](https://translate.hut.ao/) as a client text translation platform where you can submit translated text for languages you are familiar with. We are grateful to every community member who has contributed to Snap Hutao and welcome more friends to participate in this project. ## 社区 / Community [](https://discord.gg/CcH5XtDtvR) [](https://qm.qq.com/q/WJKykrY9W) ## 贡献 / Contribute * [向我们提交 PR / Make Pull Requests](https://hut.ao/development/contribute.html) * [为我们更新文档 / Enhance our Document](https://github.com/DGP-Studio/Snap.Hutao.Docs) ## 特别感谢 / Special Thanks * [HolographicHat](https://github.com/HolographicHat) * [UIGF organization](https://uigf.org) ### 特定的原神项目 / Specific Genshin-related Projects * [Scighost/Starward](https://github.com/Scighost/Starward) ### 使用的技术栈 / Tech Stack * [CommunityToolkit/dotnet](https://github.com/CommunityToolkit/dotnet) * [CommunityToolkit/Labs-Windows](https://github.com/CommunityToolkit/Labs-Windows) * [CommunityToolkit/Windows](https://github.com/CommunityToolkit/Windows) * [dotnet/efcore](https://github.com/dotnet/efcore) * [dotnet/runtime](https://github.com/dotnet/runtime) * [DotNetAnalyzers/StyleCopAnalyzers](https://github.com/DotNetAnalyzers/StyleCopAnalyzers) * [microsoft/vs-validation](https://github.com/microsoft/vs-validation) * [microsoft/WindowsAppSDK](https://github.com/microsoft/WindowsAppSDK) * [microsoft/microsoft-ui-xaml](https://github.com/microsoft/microsoft-ui-xaml) * [quartznet/quartznet](https://github.com/quartznet/quartznet) ### 支撑项目 / Supporter Project * [Snap.Hutao.Server](https://github.com/DGP-Studio/Snap.Hutao.Server) * [Snap.Metadata](https://github.com/DGP-Studio/Snap.Metadata) ## 赞助商 / Sponsorship Snap Hutao is currently using sponsored software from the following service providers. | [](https://www.netlify.com/) | [](https://crowdin.com/) | [](https://gitlab.cn/) | | :----------------------------------------------------------: | :----------------------------------------------------------: | :----------------------------------------------------------: | | [](https://about.signpath.io) | [](https://1password.com/) | [](https://www.digitalocean.com) | | [](https://hi.ducalis.io/) | [](https://www.jetbrains.com/opensource/) | | - Netlify provides document and home page hosting service for Snap Hutao - Crowdin provides its SaaS platform to help Snap Hutao's localization - Jihu GitLab (极狐) provides Git repository and CI/CD SaaS service for Snap Hutao in China - Free code signing provided by [SignPath.io](https://signpath.io/), certificate by [SignPath Foundation](https://signpath.org/) - 1Password provides Snap Hutao development team with their amazing password management software - DigitalOcean provides reliable cloud database for Snap Hutao database backup - [Ducalis.io](https://hi.ducalis.io/) provides Snap Hutao project with a complete decision-making toolkit for project management - Jetbrains provides powerful IDE for Snap Hutao infrastructure services coding ## 开发 / Development  [](https://star-history.com/#DGP-Studio/Snap.Hutao&Date)

实用的开源多功能原神工具箱 🧰 / Multifunctional Open-source Genshin Impact Toolkit 🧰

genshin-impact,yuanshen,genshin,hoyoverse,hutao,mihoyo,dotnet,windows,snap-hutao,winui3

huggingface/deep-rl-class

# [The Hugging Face Deep Reinforcement Learning Course 🤗 (v2.0)](https://huggingface.co/deep-rl-course/unit0/introduction) <img src="https://huggingface.co/datasets/huggingface-deep-rl-course/course-images/resolve/main/en/unit0/thumbnail.jpg" alt="Thumbnail"/> If you like the course, don't hesitate to **⭐ star this repository. This helps us 🤗**. This repository contains the Deep Reinforcement Learning Course mdx files and notebooks. **The website is here**: https://huggingface.co/deep-rl-course/unit0/introduction?fw=pt - The syllabus 📚: https://simoninithomas.github.io/deep-rl-course - The course 📚: https://huggingface.co/deep-rl-course/unit0/introduction?fw=pt - **Sign up here** ➡️➡️➡️ http://eepurl.com/ic5ZUD ## Citing the project To cite this repository in publications: ```bibtex @misc{deep-rl-course, author = {Simonini, Thomas and Sanseviero, Omar}, title = {The Hugging Face Deep Reinforcement Learning Class}, year = {2023}, publisher = {GitHub}, journal = {GitHub repository}, howpublished = {\url{https://github.com/huggingface/deep-rl-class}}, } ```

This repo contains the syllabus of the Hugging Face Deep Reinforcement Learning Course.

deep-reinforcement-learning,reinforcement-learning,reinforcement-learning-excercises,deep-learning

multiprocessio/dsq

# Not under active development While development may continue in the future with a different architecture, for the moment you should probably instead use [DuckDB](https://github.com/duckdb/duckdb), [ClickHouse-local](https://clickhouse.com/docs/en/operations/utilities/clickhouse-local), or [GlareDB (based on DataFusion)](https://github.com/GlareDB/glaredb). These are built on stronger analytics foundations than projects like dsq based on SQLite. For example, column-oriented storage and vectorized execution, let alone JIT-compiled expression evaluation, are possible with these other projects. [More here](https://twitter.com/eatonphil/status/1708130091425784146). # Commandline tool for running SQL queries against JSON, CSV, Excel, Parquet, and more Since Github doesn't provide a great way for you to learn about new releases and features, don't just star the repo, join the [mailing list](https://docs.google.com/forms/d/e/1FAIpQLSfYF3AZivacRrQWanC-skd0iI23ermwPd17T_64Xc4etoL_Tw/viewform). - [About](#about) - [Install](#install) - [macOS Homebrew](#macos-homebrew) - [Binaries on macOS, Linux, WSL](#binaries-on-macos-linux-wsl) - [Binaries on Windows (not WSL)](#binaries-on-windows-not-wsl) - [Build and install from source](#build-and-install-from-source) - [Usage](#usage) - [Pretty print](#pretty-print) - [Piping data to dsq](#piping-data-to-dsq) - [Multiple files and joins](#multiple-files-and-joins) - [SQL query from file](#sql-query-from-file) - [Transforming data to JSON without querying](#transforming-data-to-json-without-querying) - [Array of objects nested within an object](#array-of-objects-nested-within-an-object) - [Multiple Excel sheets](#multiple-excel-sheets) - [Limitation: nested arrays](#limitation-nested-arrays) - [Nested object values](#nested-object-values) - [Caveat: PowerShell, CMD.exe](#caveat-powershell-cmdexe) - [Nested objects explained](#nested-objects-explained) - [Limitation: whole object retrieval](#limitation-whole-object-retrieval) - [Nested arrays](#nested-arrays) - [JSON operators](#json-operators) - [REGEXP](#regexp) - [Standard Library](#standard-library) - [Output column order](#output-column-order) - [Dumping inferred schema](#dumping-inferred-schema) - [Caching](#caching) - [Interactive REPL](#interactive-repl) - [Converting numbers in CSV and TSV files](#converting-numbers-in-csv-and-tsv-files) - [Supported Data Types](#supported-data-types) - [Engine](#engine) - [Comparisons](#comparisons) - [Benchmark](#benchmark) - [Notes](#notes) - [Third-party integrations](#third-party-integrations) - [Community](#community) - [How can I help?](#how-can-i-help) - [License](#license) ## About This is a CLI companion to [DataStation](https://github.com/multiprocessio/datastation) (a GUI) for running SQL queries against data files. So if you want the GUI version of this, check out DataStation. ## Install Binaries for amd64 (x86_64) are provided for each release. ### macOS Homebrew `dsq` is available on macOS Homebrew: ```bash $ brew install dsq ``` ### Binaries on macOS, Linux, WSL On macOS, Linux, and WSL you can run the following: ```bash $ VERSION="v0.23.0" $ FILE="dsq-$(uname -s | awk '{ print tolower($0) }')-x64-$VERSION.zip" $ curl -LO "https://github.com/multiprocessio/dsq/releases/download/$VERSION/$FILE" $ unzip $FILE $ sudo mv ./dsq /usr/local/bin/dsq ``` Or install manually from the [releases page](https://github.com/multiprocessio/dsq/releases), unzip and add `dsq` to your `$PATH`. ### Binaries on Windows (not WSL) Download the [latest Windows release](https://github.com/multiprocessio/dsq/releases), unzip it, and add `dsq` to your `$PATH`. ### Build and install from source If you are on another platform or architecture or want to grab the latest release, you can do so with Go 1.18+: ```bash $ go install github.com/multiprocessio/dsq@latest ``` `dsq` will likely work on other platforms that Go is ported to such as AARCH64 and OpenBSD, but tests and builds are only run against x86_64 Windows/Linux/macOS. ## Usage You can either pipe data to `dsq` or you can pass a file name to it. NOTE: piping data doesn't work on Windows. If you are passing a file, it must have the usual extension for its content type. For example: ```bash $ dsq testdata.json "SELECT * FROM {} WHERE x > 10" ``` Or: ```bash $ dsq testdata.ndjson "SELECT name, AVG(time) FROM {} GROUP BY name ORDER BY AVG(time) DESC" ``` ### Pretty print By default `dsq` prints ugly JSON. This is the most efficient mode. ```bash $ dsq testdata/userdata.parquet 'select count(*) from {}' [{"count(*)":1000} ] ``` If you want prettier JSON you can pipe `dsq` to `jq`. ```bash $ dsq testdata/userdata.parquet 'select count(*) from {}' | jq [ { "count(*)": 1000 } ] ``` Or you can enable pretty printing with `-p` or `--pretty` in `dsq` which will display your results in an ASCII table. ```bash $ dsq --pretty testdata/userdata.parquet 'select count(*) from {}' +----------+ | count(*) | +----------+ | 1000 | +----------+ ``` ### Piping data to dsq When piping data to `dsq` you need to set the `-s` flag and specify the file extension or MIME type. For example: ```bash $ cat testdata.csv | dsq -s csv "SELECT * FROM {} LIMIT 1" ``` Or: ```bash $ cat testdata.parquet | dsq -s parquet "SELECT COUNT(1) FROM {}" ``` ### Multiple files and joins You can pass multiple files to DSQ. As long as they are supported data files in a valid format, you can run SQL against all files as tables. Each table can be accessed by the string `{N}` where `N` is the 0-based index of the file in the list of files passed on the commandline. For example this joins two datasets of differing origin types (CSV and JSON). ```bash $ dsq testdata/join/users.csv testdata/join/ages.json \ "select {0}.name, {1}.age from {0} join {1} on {0}.id = {1}.id" [{"age":88,"name":"Ted"}, {"age":56,"name":"Marjory"}, {"age":33,"name":"Micah"}] ``` You can also give file-table-names aliases since `dsq` uses standard SQL: ```bash $ dsq testdata/join/users.csv testdata/join/ages.json \ "select u.name, a.age from {0} u join {1} a on u.id = a.id" [{"age":88,"name":"Ted"}, {"age":56,"name":"Marjory"}, {"age":33,"name":"Micah"}] ``` ### SQL query from file As your query becomes more complex, it might be useful to store it in a file rather than specify it on the command line. To do so replace the query argument with `--file` or `-f` and the path to the file. ```bash $ dsq data1.csv data2.csv -f query.sql ``` ### Transforming data to JSON without querying As a shorthand for `dsq testdata.csv "SELECT * FROM {}"` to convert supported file types to JSON you can skip the query and the converted JSON will be dumped to stdout. For example: ```bash $ dsq testdata.csv [{...some csv data...},{...some csv data...},...] ``` ### Array of objects nested within an object DataStation and `dsq`'s SQL integration operates on an array of objects. If your array of objects happens to be at the top-level, you don't need to do anything. But if your array data is nested within an object you can add a "path" parameter to the table reference. For example if you have this data: ```bash $ cat api-results.json { "data": { "data": [ {"id": 1, "name": "Corah"}, {"id": 3, "name": "Minh"} ] }, "total": 2 } ``` You need to tell `dsq` that the path to the array data is `"data.data"`: ```bash $ dsq --pretty api-results.json 'SELECT * FROM {0, "data.data"} ORDER BY id DESC' +----+-------+ | id | name | +----+-------+ | 3 | Minh | | 1 | Corah | +----+-------+ ``` You can also use the shorthand `{"path"}` or `{'path'}` if you only have one table: ```bash $ dsq --pretty api-results.json 'SELECT * FROM {"data.data"} ORDER BY id DESC' +----+-------+ | id | name | +----+-------+ | 3 | Minh | | 1 | Corah | +----+-------+ ``` You can use either single or double quotes for the path. #### Multiple Excel sheets Excel files with multiple sheets are stored as an object with key being the sheet name and value being the sheet data as an array of objects. If you have an Excel file with two sheets called `Sheet1` and `Sheet2` you can run `dsq` on the second sheet by specifying the sheet name as the path: ```bash $ dsq data.xlsx 'SELECT COUNT(1) FROM {"Sheet2"}' ``` #### Limitation: nested arrays You cannot specify a path through an array, only objects. ### Nested object values It's easiest to show an example. Let's say you have the following JSON file called `user_addresses.json`: ```bash $ cat user_addresses.json [ {"name": "Agarrah", "location": {"city": "Toronto", "address": { "number": 1002 }}}, {"name": "Minoara", "location": {"city": "Mexico City", "address": { "number": 19 }}}, {"name": "Fontoon", "location": {"city": "New London", "address": { "number": 12 }}} ] ``` You can query the nested fields like so: ```sql $ dsq user_addresses.json 'SELECT name, "location.city" FROM {}' ``` And if you need to disambiguate the table: ```sql $ dsq user_addresses.json 'SELECT name, {}."location.city" FROM {}' ``` #### Caveat: PowerShell, CMD.exe On PowerShell and CMD.exe you must escape inner double quotes with backslashes: ```powershell > dsq user_addresses.json 'select name, \"location.city\" from {}' [{"location.city":"Toronto","name":"Agarrah"}, {"location.city":"Mexico City","name":"Minoara"}, {"location.city":"New London","name":"Fontoon"}] ``` #### Nested objects explained Nested objects are collapsed and their new column name becomes the JSON path to the value connected by `.`. Actual dots in the path must be escaped with a backslash. Since `.` is a special character in SQL you must quote the whole new column name. #### Limitation: whole object retrieval You cannot query whole objects, you must ask for a specific path that results in a scalar value. For example in the `user_addresses.json` example above you CANNOT do this: ```sql $ dsq user_addresses.json 'SELECT name, {}."location" FROM {}' ``` Because `location` is not a scalar value. It is an object. ### Nested arrays Nested arrays are converted to a JSON string when stored in SQLite. Since SQLite supports querying JSON strings you can access that data as structured data even though it is a string. So if you have data like this in `fields.json`: ```json [ {"field1": [1]}, {"field1": [2]}, ] ``` You can request the entire field: ``` $ dsq fields.json "SELECT field1 FROM {}" | jq [ { "field1": "[1]" }, { "field1": "[2]", } ] ``` #### JSON operators You can get the first value in the array using SQL JSON operators. ``` $ dsq fields.json "SELECT field1->0 FROM {}" | jq [ { "field1->0": "1" }, { "field1->0": "2" } ] ``` ### REGEXP Since DataStation and `dsq` are built on SQLite, you can filter using `x REGEXP 'y'` where `x` is some column or value and `y` is a REGEXP string. SQLite doesn't pick a regexp implementation. DataStation and `dsq` use Go's regexp implementation which is more limited than PCRE2 because Go support for PCRE2 is not yet very mature. ```sql $ dsq user_addresses.json "SELECT * FROM {} WHERE name REGEXP 'A.*'" [{"location.address.number":1002,"location.city":"Toronto","name":"Agarrah"}] ``` ### Standard Library dsq registers [go-sqlite3-stdlib](https://github.com/multiprocessio/go-sqlite3-stdlib) so you get access to numerous statistics, url, math, string, and regexp functions that aren't part of the SQLite base. View that project docs for all available extended functions. ### Output column order When emitting JSON (i.e. without the `--pretty` flag) keys within an object are unordered. If order is important to you you can filter with `jq`: `dsq x.csv 'SELECT a, b FROM {}' | jq --sort-keys`. With the `--pretty` flag, column order is purely alphabetical. It is not possible at the moment for the order to depend on the SQL query order. ### Dumping inferred schema For any supported file you can dump the inferred schema rather than dumping the data or running a SQL query. Set the `--schema` flag to do this. The inferred schema is very simple, only JSON types are supported. If the underlying format (like Parquet) supports finer-grained data types (like int64) this will not show up in the inferred schema. It will show up just as `number`. For example: ``` $ dsq testdata/avro/test_data.avro --schema --pretty Array of Object of birthdate of string cc of Varied of Object of long of number or Unknown comments of string country of string email of string first_name of string gender of string id of number ip_address of string last_name of string registration_dttm of string salary of Varied of Object of double of number or Unknown title of string ``` You can print this as a structured JSON string by omitting the `--pretty` flag when setting the `--schema` flag. ### Caching Sometimes you want to do some exploration on a dataset that isn't changing frequently. By turning on the `--cache` or `-C` flag DataStation will store the imported data on disk and not delete it when the run is over. With caching on, DataStation calculates a SHA1 sum of all the files you specified. If the sum ever changes then it will reimport all the files. Otherwise when you run additional queries with the cache flag on it will reuse that existing database and not reimport the files. Since without caching on DataStation uses an in-memory database, the initial query with caching on may take slightly longer than with caching off. Subsequent queries will be substantially faster though (for large datasets). For example, in the first run with caching on this query might take 30s: ``` $ dsq some-large-file.json --cache 'SELECT COUNT(1) FROM {}' ``` But when you run another query it might only take 1s. ``` $ dsq some-large-file.json --cache 'SELECT SUM(age) FROM {}' ``` Not because we cache any result but because we cache importing the file into SQLite. So even if you change the query, as long as the file doesn't change, the cache is effective. To make this permanent you can export `DSQ_CACHE=true` in your environment. ### Interactive REPL Use the `-i` or `--interactive` flag to enter an interactive REPL where you can run multiple SQL queries. ``` $ dsq some-large-file.json -i dsq> SELECT COUNT(1) FROM {}; +----------+ | COUNT(1) | +----------+ | 1000 | +----------+ (1 row) dsq> SELECT * FROM {} WHERE NAME = 'Kevin'; (0 rows) ``` ### Converting numbers in CSV and TSV files CSV and TSV files do not allow to specify the type of the individual values contained in them. All values are treated as strings by default. This can lead to unexpected results in queries. Consider the following example: ``` $ cat scores.csv name,score Fritz,90 Rainer,95.2 Fountainer,100 $ dsq scores.csv "SELECT * FROM {} ORDER BY score" [{"name":"Fountainer","score":"100"}, {"name":"Fritz","score":"90"}, {"name":"Rainer","score":"95.2"}] ``` Note how the `score` column contains numerical values only. Still, sorting by that column yields unexpected results because the values are treated as strings, and sorted lexically. (You can tell that the individual scores were imported as strings because they're quoted in the JSON result.) Use the `-n` or `--convert-numbers` flag to auto-detect and convert numerical values (integers and floats) in imported files: ``` $ dsq ~/scores.csv --convert-numbers "SELECT * FROM {} ORDER BY score" [{"name":"Fritz","score":90}, {"name":"Rainer","score":95.2}, {"name":"Fountainer","score":100}] ``` Note how the scores are imported as numbers now and how the records in the result set are sorted by their numerical value. Also note that the individual scores are no longer quoted in the JSON result. To make this permanent you can export `DSQ_CONVERT_NUMBERS=true` in your environment. Turning this on disables some optimizations. ## Supported Data Types | Name | File Extension(s) | Mime Type | Notes | | |------------------------|-------------------|--------------------------------------------------|-------------------------------------------------------------------------------------------------------------------------------------------------|---| | CSV | `csv` | `text/csv` | | | | TSV | `tsv`, `tab` | `text/tab-separated-values` | | | | JSON | `json` | `application/json` | Must be an array of objects or a [path to an array of objects](https://github.com/multiprocessio/dsq#array-of-objects-nested-within-an-object). | | | Newline-delimited JSON | `ndjson`, `jsonl` | `application/jsonlines` | | | | Concatenated JSON | `cjson` | `application/jsonconcat` | | | | ORC | `orc` | `orc` | | | | Parquet | `parquet` | `parquet` | | | | Avro | `avro` | `application/avro` | | | | YAML | `yaml`, `yml` | `application/yaml` | | | | Excel | `xlsx`, `xls` | `application/vnd.ms-excel` | If you have multiple sheets, you must [specify a sheet path](https://github.com/multiprocessio/dsq#multiple-excel-sheets). | | | ODS | `ods` | `application/vnd.oasis.opendocument.spreadsheet` | If you have multiple sheets, you must [specify a sheet path](https://github.com/multiprocessio/dsq#multiple-excel-sheets). | | | Apache Error Logs | NA | `text/apache2error` | Currently only works if being piped in. | | | Apache Access Logs | NA | `text/apache2access` | Currently only works if being piped in. | | | Nginx Access Logs | NA | `text/nginxaccess` | Currently only works if being piped in. | | | LogFmt Logs | `logfmt` | `text/logfmt` | | | ## Engine Under the hood dsq uses [DataStation](https://github.com/multiprocessio/datastation) as a library and under that hood DataStation uses SQLite to power these kinds of SQL queries on arbitrary (structured) data. ## Comparisons | Name | Link | Caching | Engine | Supported File Types | Binary Size | |-|---|-|-|------------------------------------------------------------------------|-| | dsq | Here | Yes | SQLite | CSV, TSV, a few variations of JSON, Parquet, Excel, ODS (OpenOffice Calc), ORC, Avro, YAML, Logs | 49M | | q | http://harelba.github.io/q/ | Yes | SQLite | CSV, TSV | 82M | | textql | https://github.com/dinedal/textql | No | SQLite | CSV, TSV | 7.3M | | octoql | https://github.com/cube2222/octosql | No | Custom engine | JSON, CSV, Excel, Parquet | 18M | | csvq | https://github.com/mithrandie/csvq | No | Custom engine | CSV | 15M | | sqlite-utils | https://github.com/simonw/sqlite-utils | No | SQLite | CSV, TSV | N/A, Not a single binary | | trdsql | https://github.com/noborus/trdsql | No | SQLite, MySQL or PostgreSQL | Few variations of JSON, TSV, LTSV, TBLN, CSV | 14M | | spysql | https://github.com/dcmoura/spyql | No | Custom engine | CSV, JSON, TEXT | N/A, Not a single binary | | duckdb | https://github.com/duckdb/duckdb | ? | Custom engine | CSV, Parquet | 35M | Not included: * clickhouse-local: fastest of anything listed here but so gigantic (over 2GB) that it can't reasonably be considered a good tool for any environment * sqlite3: requires multiple commands to ingest CSV, not great for one-liners * datafusion-cli: very fast (slower only than clickhouse-local) but requires multiple commands to ingest CSV, so not great for one-liners ## Benchmark This benchmark was run June 19, 2022. It is run on a [dedicated bare metal instance on OVH](https://us.ovhcloud.com/bare-metal/rise/rise-1/) with: * 64 GB DDR4 ECC 2,133 MHz * 2x450 GB SSD NVMe in Soft RAID * Intel Xeon E3-1230v6 - 4c/8t - 3.5 GHz/3.9 GHz It runs a `SELECT passenger_count, COUNT(*), AVG(total_amount) FROM taxi.csv GROUP BY passenger_count` query against the well-known NYC Yellow Taxi Trip Dataset. Specifically, the CSV file from April 2021 is used. It's a 200MB CSV file with ~2 million rows, 18 columns, and mostly numerical values. The script is [here](./scripts/benchmark.sh). It is an adaptation of the [benchmark that the octosql devs run](https://github.com/cube2222/octosql#Benchmarks). | Program | Version | Mean [s] | Min [s] | Max [s] | Relative | |:----------|:--------------------|---------------:|--------:|--------:|-------------:| | dsq | 0.20.1 (caching on) | 1.151 ± 0.010 | 1.131 | 1.159 | 1.00 | | duckdb | 0.3.4 | 1.723 ± 0.023 | 1.708 | 1.757 | 1.50 ± 0.02 | | octosql | 0.7.3 | 2.005 ± 0.008 | 1.991 | 2.015 | 1.74 ± 0.02 | | q | 3.1.6 (caching on) | 2.028 ± 0.010 | 2.021 | 2.055 | 1.76 ± 0.02 | | sqlite3 * | 3.36.0 | 4.204 ± 0.018 | 4.177 | 4.229 | 3.64 ± 0.04 | | trdsql | 0.10.0 | 12.972 ± 0.225 | 12.554 | 13.392 | 11.27 ± 0.22 | | dsq | 0.20.1 (default) | 15.030 ± 0.086 | 14.895 | 15.149 | 13.06 ± 0.13 | | textql | fca00ec | 19.148 ± 0.183 | 18.865 | 19.500 | 16.63 ± 0.21 | | spyql | 0.6.0 | 16.985 ± 0.105 | 16.854 | 17.161 | 14.75 ± 0.16 | | q | 3.1.6 (default) | 24.061 ± 0.095 | 23.954 | 24.220 | 20.90 ± 0.20 | \* While dsq and q are built on top of sqlite3 there is not a builtin way in sqlite3 to cache ingested files without a bit of scripting Not included: * clickhouse-local: faster than any of these but over 2GB so not a reasonable general-purpose CLI * datafusion-cli: slower only than clickhouse-local but requires multiple commands to ingest CSV, can't do one-liners * sqlite-utils: takes minutes to finish ### Notes OctoSQL, duckdb, and SpyQL implement their own SQL engines. dsq, q, trdsql, and textql copy data into SQLite and depend on the SQLite engine for query execution. Tools that implement their own SQL engines can do better on 1) ingestion and 2) queries that act on a subset of data (such as limited columns or limited rows). These tools implement ad-hoc subsets of SQL that may be missing or differ from your favorite syntax. On the other hand, tools that depend on SQLite have the benefit of providing a well-tested and well-documented SQL engine. DuckDB is exceptional since there is a dedicated company behind it. dsq also comes with numerous [useful functions](https://github.com/multiprocessio/go-sqlite3-stdlib) (e.g. best-effort date parsing, URL parsing/extraction, statistics functions, etc.) on top of [SQLite builtins](https://www.sqlite.org/lang_corefunc.html). ## Third-party integrations * [ob-dsq](https://github.com/fritzgrabo/ob-dsq) ## Community [Join us at #dsq on the Multiprocess Discord](https://discord.gg/9BRhAMhDa5). ## How can I help? Download dsq and use it! Report bugs on [Discord](https://discord.gg/f2wQBc4bXX). If you're a developer with some Go experience looking to hack on open source, check out [GOOD_FIRST_PROJECTS.md](https://github.com/multiprocessio/datastation/blob/main/GOOD_FIRST_PROJECTS.md) in the DataStation repo. ## License This software is licensed under an Apache 2.0 license.

Commandline tool for running SQL queries against JSON, CSV, Excel, Parquet, and more.

golang,csv,json,tsv,excel,openoffice-calc,parquet,sql,cli

microsoft/Microsoft-3D-Movie-Maker

# Microsoft 3D Movie Maker Released in 1995, this is the original source code to the Microsoft 3D Movie Maker project, now released under the [MIT license](LICENSE) as open source.  ## Building instructions This project is unlikely to build successfully under modern hardware/software, but you can get started with compilation and get partial completed binaries. Here's what will get you going. Thanks to Mac Sample for their work on getting this far! - Make sure this repo is checked out to a folder with a short name, ideally right on the root of a drive (i.e. C:\3d). - You will need Visual C++ 2.0's dev tools (located under MSVC20\BIN on its installer disk) on your path. Modern compilers dislike some of the pre C++98 conventions. - From the root of this repo, run ```setvars.bat``` you can change the values in this script to change what your build will target. - Locate and place font files (see [FONTS.md](FONTS.md)) - Run nmake and you'll begin building 3d Movie Maker. ## Contributing The source files in this repo are for historical reference and will be kept static, and this repository will be archived. Feel free to fork this repo and experiment. ## Code cleanup This code was restored from the Microsoft corporate archives and cleared for release. - Developer names and aliases were removed, with the exception of current employees who worked on the original release who consented to keeping their names in place - The archive consisted of several CDs, some of which were for alternate builds or products, and have been excluded - The code does not build with today's engineering tools, and is released as-is. ## Trademarks This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft trademarks or logos is subject to and must follow [Microsoft's Trademark & Brand Guidelines](https://www.microsoft.com/en-us/legal/intellectualproperty/trademarks/usage/general). Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship. Any use of third-party trademarks or logos are subject to those third-party's policies. This repo includes a build from 1995 of BRender from Argonaut software. Approval to open source BRender as MIT was given in an email from Jez San, former CEO of Argonaut. Other versions of BRender exist at https://github.com/foone/BRender-v1.3.2 and https://github.com/foone/BRender-1997 Thanks to Jez and the whole BRender team for their hard work on this amazing engine. A full historical list of BRender contributors is available at https://github.com/foone/BRender-v1.3.2/blob/main/README.md This repo does NOT include the SoftImage SDK "./DKIT" from 1992. Jez also offered this interesting BRender anecdote in an email: ``` When Sam Littlewood designed BRender, he didn’t write the code. And then document it. The way most things were built at the time. First, he wrote the manual. The full documentation That served as the spec. Then the coding started. ```

This is the source code for the original Microsoft 3D Movie Maker released in 1995. This is not supported software.

getaurora/download

## 极光（aurora)3.X版下载 - <a href="https://files.7ecnologia.com/aurora_v3.0.8-arm64.apk"> Android 下载连接1</a> - <a href="https://files.jsa1004.com/aurora_v3.0.8-arm64.apk"> Android 下载连接2</a> - <a href="http://121.10.141.102:8888/new.apk"> Android 下载连接3</a> - <a href="https://121.10.141.102:8889/new.apk"> Android 下载连接5</a> - <a href="https://files.7ecnologia.com/Aurora_3.0.6_x86_zh-CN.msi"> Windows 下载连接1</a> - <a href="https://files.jsa1004.com/Aurora_3.0.6_x86_zh-CN.msi"> Windows 下载连接2</a> - <a href="http://121.10.141.102:8888/new.msi"> Windows 下载连接6</a> - <a href="https://121.10.141.102:8889/new.msi"> Windows 下载连接5</a> - <a href="https://m.jsa1004.com/Aurora_3.0.6_x64.dmg"> Mac OS 下载链接1</a> - <a href="https://files.7ecnologia.com/Aurora_3.0.6_x64.dmg"> Mac OS 下载链接2</a> ## 极光 (aurora）稳定版本下载 Stable version of aurora - <a href="https://a.jsa1004.com/aurora-v3.0.7S-update1.apk"> Android aurora-v3.0.7S-update1.apk 下载链接1</a> - <a href="https://files.7ecnologia.com/aurora-v3.0.7S-update1.apk"> Android aurora-v3.0.7S-update1.apk 下载链接2</a> - <a href="https://a.jsa1004.com/aurora-v3.0.7S-release.apk"> Android aurora-v3.0.7S-release.apk 下载链接1</a> - <a href="https://files.7ecnologia.com/aurora-v3.0.7S-release.apk"> Android aurora-v3.0.7S-release.apk 下载链接2</a> - <a href="https://w.jsa1004.com/aurora-v3.0.5s-release.exe"> Windows aurora-v3.0.5s-release.exe 下载链接1</a> - <a href="https://files.7ecnologia.com/aurora-v3.0.5s-release.exe"> Windows aurora-v3.0.5s-release.exe 下载链接2</a> - <a href="https://m.jsa1004.com/aurora-v3.0.3s-release.pkg"> Mac OS aurora-v3.0.3s-release.pkg 下载链接1</a> - <a href="https://files.7ecnologia.com/aurora-v3.0.3s-release.pkg"> Mac OS aurora-v3.0.3s-release.pkg 下载链接2</a> ## 如果您需要进一步的帮助和账户相关事宜，您可以在工作时间内，即: ## a) 周一至周五上午10:00-下午7:00 ## b) 周六中午12:00-晚上9:00 ## （周日与公共假期除外），通过我们的线上反馈系统与我们的客服进行聊天。 ## 备注：请务必收藏本页面，方便日后下载新版本（本页面为官方唯一防封下载发布页）Remarks: Please be sure to bookmark this page so that you can download new versions in the future (this page is the only official anti-blocking download release page)

极光官方版本下载页 翻墙 代理 科学上网 外网 加速器 梯子 路由

cirruslabs/tart

<img src="https://github.com/cirruslabs/tart/raw/main/Resources/TartSocial.png"/> *Tart* is a virtualization toolset to build, run and manage macOS and Linux virtual machines (VMs) on Apple Silicon. Built by CI engineers for your automation needs. Here are some highlights of Tart: * Tart uses Apple's own `Virtualization.Framework` for [near-native performance](https://browser.geekbench.com/v5/cpu/compare/20382844?baseline=20382722). * Push/Pull virtual machines from any OCI-compatible container registry. * Use Tart Packer Plugin to automate VM creation. * Easily integrates with any CI system. Tart powers [Cirrus Runners](https://cirrus-runners.app/) service — a drop-in replacement for the standard GitHub-hosted runners, offering 2-3 times better performance for a fraction of the price. <p align="center"> <a href="https://cirrus-runners.app/?utm_source=github&utm_medium=referral" target=_blank> <img src="https://github.com/cirruslabs/tart/raw/main/Resources/CirrusRunnersForGHA.png" height="65"/> </a> </p> Many companies are using Tart in their internal setups. Here are a few of them: <p align="center"> <a href="https://atlassian.com/" target=_blank> <img src="https://github.com/cirruslabs/tart/raw/main/Resources/Users/Atlassian.png" height="65"/> </a> <a href="https://krisp.ai/" target=_blank> <img src="https://github.com/cirruslabs/tart/raw/main/Resources/Users/Krisp.png" height="65"/> </a> <a href="https://mullvad.net/" target=_blank> <img src="https://github.com/cirruslabs/tart/raw/main/Resources/Users/Mullvad.png" height="65"/> </a> <a href="https://shape.dk/" target=_blank> <img src="https://github.com/cirruslabs/tart/raw/main/Resources/Users/shape.png" height="65"/> </a> <a href="https://suran.com/" target=_blank> <img src="https://github.com/cirruslabs/tart/raw/main/Resources/Users/Suran.png" height="65"/> </a> <a href="https://symflower.com/" target=_blank> <img src="https://github.com/cirruslabs/tart/raw/main/Resources/Users/Symflower.png" height="65"/> </a> <a href="https://transloadit.com/" target=_blank> <img src="https://github.com/cirruslabs/tart/raw/main/Resources/Users/Transloadit.png" height="65"/> </a> <a href="https://uphold.com/" target=_blank> <img src="https://github.com/cirruslabs/tart/raw/main/Resources/Users/Uphold.png" height="65"/> </a> <a href="https://www.pitsdatarecovery.net/" target=_blank> <img src="https://github.com/cirruslabs/tart/raw/main/Resources/Users/PITSGlobalDataRecoveryServices.png" height="65"/> </a> <a href="https://ahrefs.com/" target=_blank> <img src="https://github.com/cirruslabs/tart/raw/main/Resources/Users/ahrefs.png" height="65"/> </a> </p> **Note:** If your company or project is using Tart please consider [adding yourself to the list above](/Resources/Users/HowToAddYourself.md). <p align="center"> <a href="https://aws.amazon.com/marketplace/pp/prodview-qczco34wlkdws?utm_source=github&utm_medium=referral" target=_blank> <img src="https://github.com/cirruslabs/tart/raw/main/Resources/AWSMarkeplaceLogo.png" height="90"/> </a> </p> ## Usage Try running a Tart VM on your Apple Silicon device running macOS 13.0 (Ventura) or later (will download a 25 GB image): ```bash brew install cirruslabs/cli/tart tart clone ghcr.io/cirruslabs/macos-sonoma-base:latest sonoma-base tart run sonoma-base ``` Please check the [official documentation](https://tart.run) for more information and/or feel free to use [discussions](https://github.com/cirruslabs/tart/discussions) for remaining questions.

macOS and Linux VMs on Apple Silicon to use in CI and other automations

automation,macos,tart,virtualization,virtualization-framework,apple-silicon,ci

Giskard-AI/giskard

<p align="center"> <img alt="giskardlogo" src="https://raw.githubusercontent.com/giskard-ai/giskard/main/readme/giskard_logo.png#gh-light-mode-only"> <img alt="giskardlogo" src="https://raw.githubusercontent.com/giskard-ai/giskard/main/readme/giskard_logo_green.png#gh-dark-mode-only"> </p> <h1 align="center" weight='300' >The Evaluation & Testing framework for LLMs & ML models</h1> <h3 align="center" weight='300' >Control risks of performance, bias and security issues in AI models</h3> <div align="center"> [](https://github.com/Giskard-AI/giskard/releases) [](https://github.com/Giskard-AI/giskard/blob/main/LICENSE) [](https://github.com/Giskard-AI/giskard/actions/workflows/build-python.yml?query=branch%3Amain) [](https://sonarcloud.io/summary/new_code?id=giskard) [](https://gisk.ar/discord) <a rel="me" href="https://fosstodon.org/@Giskard"></a> </div> <h3 align="center"> <a href="https://docs.giskard.ai/en/stable/getting_started/index.html"><b>Docs</b></a> &bull; <a href="https://www.giskard.ai/knowledge-categories/news/?utm_source=github&utm_medium=github&utm_campaign=github_readme&utm_id=readmeblog"><b>Blog</b></a> &bull; <a href="https://www.giskard.ai/?utm_source=github&utm_medium=github&utm_campaign=github_readme&utm_id=readmeblog"><b>Website</b></a> &bull; <a href="https://gisk.ar/discord"><b>Discord</b></a> </h3> <br /> ## Install Giskard 🐢 Install the latest version of Giskard from PyPi using pip: ```sh pip install "giskard[llm]" -U ``` We officially support Python 3.9, 3.10 and 3.11. ## Try in Colab 📙 [Open Colab notebook](https://colab.research.google.com/github/giskard-ai/giskard/blob/main/docs/getting_started/quickstart/quickstart_llm.ipynb) ______________________________________________________________________ Giskard is an open-source Python library that **automatically detects performance, bias & security issues in AI applications**. The library covers LLM-based applications such as RAG agents, all the way to traditional ML models for tabular data. ## Scan: Automatically assess your LLM-based agents for performance, bias & security issues ⤵️ Issues detected include: - Hallucinations - Harmful content generation - Prompt injection - Robustness issues - Sensitive information disclosure - Stereotypes & discrimination - many more... <p align="center"> <img src="https://raw.githubusercontent.com/giskard-ai/giskard/main/readme/scan_updates.gif" alt="Scan Example" width="800"> </p> ## RAG Evaluation Toolkit (RAGET): Automatically generate evaluation datasets & evaluate RAG application answers ⤵️ If you're testing a RAG application, you can get an even more in-depth assessment using **RAGET**, Giskard's RAG Evaluation Toolkit. - **RAGET** can generate automatically a list of `question`, `reference_answer` and `reference_context` from the knowledge base of the RAG. You can then use this generated test set to evaluate your RAG agent. - **RAGET** computes scores *for each component of the RAG agent*. The scores are computed by aggregating the correctness of the agent’s answers on different question types. - Here is the list of components evaluated with **RAGET**: - `Generator`: the LLM used inside the RAG to generate the answers - `Retriever`: fetch relevant documents from the knowledge base according to a user query - `Rewriter`: rewrite the user query to make it more relevant to the knowledge base or to account for chat history - `Router`: filter the query of the user based on his intentions - `Knowledge Base`: the set of documents given to the RAG to generate the answers <p align="center"> <img src="https://raw.githubusercontent.com/giskard-ai/giskard/main/readme/RAGET_updated.gif" alt="Test Suite Example" width="800"> </p> Giskard works with any model, in any environment and integrates seamlessly with your favorite tools ⤵️ <br/> <p align="center"> <img width='600' src="https://raw.githubusercontent.com/giskard-ai/giskard/main/readme/tools_updated.png"> </p> <br/> # Contents - 🤸‍♀️ **[Quickstart](#quickstart)** - **1**. 🏗️ [Build a LLM agent](#build-a-llm-agent) - **2**. 🔎 [Scan your model for issues](#scan-your-model-for-issues) - **3**. 🪄 [Automatically generate an evaluation dataset for your RAG applications](#automatically-generate-an-evaluation-dataset-for-your-rag-applications) - 👋 **[Community](#community)** <h1 id="quickstart">🤸‍♀️ Quickstart</h1> <h2 id="build-a-llm-agent">1. 🏗️ Build a LLM agent</h2> Let's build an agent that answers questions about climate change, based on the 2023 Climate Change Synthesis Report by the IPCC. Before starting let's install the required libraries: ```sh pip install langchain tiktoken "pypdf<=3.17.0" ``` ```python from langchain import OpenAI, FAISS, PromptTemplate from langchain.embeddings import OpenAIEmbeddings from langchain.document_loaders import PyPDFLoader from langchain.chains import RetrievalQA from langchain.text_splitter import RecursiveCharacterTextSplitter # Prepare vector store (FAISS) with IPPC report text_splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=100, add_start_index=True) loader = PyPDFLoader("https://www.ipcc.ch/report/ar6/syr/downloads/report/IPCC_AR6_SYR_LongerReport.pdf") db = FAISS.from_documents(loader.load_and_split(text_splitter), OpenAIEmbeddings()) # Prepare QA chain PROMPT_TEMPLATE = """You are the Climate Assistant, a helpful AI assistant made by Giskard. Your task is to answer common questions on climate change. You will be given a question and relevant excerpts from the IPCC Climate Change Synthesis Report (2023). Please provide short and clear answers based on the provided context. Be polite and helpful. Context: {context} Question: {question} Your answer: """ llm = OpenAI(model="gpt-3.5-turbo-instruct", temperature=0) prompt = PromptTemplate(template=PROMPT_TEMPLATE, input_variables=["question", "context"]) climate_qa_chain = RetrievalQA.from_llm(llm=llm, retriever=db.as_retriever(), prompt=prompt) ``` <h2 id="scan-your-model-for-issues">2. 🔎 Scan your model for issues</h2> Next, wrap your agent to prepare it for Giskard's scan: ```python import giskard import pandas as pd def model_predict(df: pd.DataFrame): """Wraps the LLM call in a simple Python function. The function takes a pandas.DataFrame containing the input variables needed by your model, and must return a list of the outputs (one for each row). """ return [climate_qa_chain.run({"query": question}) for question in df["question"]] # Don’t forget to fill the `name` and `description`: they are used by Giskard # to generate domain-specific tests. giskard_model = giskard.Model( model=model_predict, model_type="text_generation", name="Climate Change Question Answering", description="This model answers any question about climate change based on IPCC reports", feature_names=["question"], ) ``` ✨✨✨Then run Giskard's magical scan✨✨✨ ```python scan_results = giskard.scan(giskard_model) ``` Once the scan completes, you can display the results directly in your notebook: ```python display(scan_results) # Or save it to a file scan_results.to_html("scan_results.html") ``` *If you're facing issues, check out our [docs](https://docs.giskard.ai/en/stable/open_source/scan/scan_llm/index.html) for more information.* <h2 id="automatically-generate-an-evaluation-dataset-for-your-rag-applications">3. 🪄 Automatically generate an evaluation dataset for your RAG applications</h2> If the scan found issues in your model, you can automatically extract an evaluation dataset based on the issues found: ```python test_suite = scan_results.generate_test_suite("My first test suite") ``` By default, RAGET automatically generates 6 different question types (these can be selected if needed, see advanced question generation). The total number of questions is divided equally between each question type. To make the question generation more relevant and accurate, you can also provide a description of your agent. ```python from giskard.rag import generate_testset, KnowledgeBase # Load your data and initialize the KnowledgeBase df = pd.read_csv("path/to/your/knowledge_base.csv") knowledge_base = KnowledgeBase.from_pandas(df, columns=["column_1", "column_2"]) # Generate a testset with 10 questions & answers for each question types (this will take a while) testset = generate_testset( knowledge_base, num_questions=60, language='en', # optional, we'll auto detect if not provided agent_description="A customer support chatbot for company X", # helps generating better questions ) ``` Depending on how many questions you generate, this can take a while. Once you’re done, you can save this generated test set for future use: ```python # Save the generated testset testset.save("my_testset.jsonl") ``` You can easily load it back ```python from giskard.rag import QATestset loaded_testset = QATestset.load("my_testset.jsonl") # Convert it to a pandas dataframe df = loaded_testset.to_pandas() ``` Here’s an example of a generated question: | question | reference_context | reference_answer | metadata | |----------------------------------------|----------------------------------------------------------------------------------------------------------------------------------------------------------------------|--------------------------------------------------------------|-------------------------------------------------------| | For which countries can I track my shipping? | Document 1: We offer free shipping on all orders over $50. For orders below $50, we charge a flat rate of $5.99. We offer shipping services to customers residing in all 50 states of the US, in addition to providing delivery options to Canada and Mexico. Document 2: Once your purchase has been successfully confirmed and shipped, you will receive a confirmation email containing your tracking number. You can simply click on the link provided in the email or visit our website’s order tracking page. | We ship to all 50 states in the US, as well as to Canada and Mexico. We offer tracking for all our shippings. | `{"question_type": "simple", "seed_document_id": 1, "topic": "Shipping policy"}` | Each row of the test set contains 5 columns: - `question`: the generated question - `reference_context`: the context that can be used to answer the question - `reference_answer`: the answer to the question (generated with GPT-4) - `conversation_history`: not shown in the table above, contain the history of the conversation with the agent as a list, only relevant for conversational question, otherwise it contains an empty list. - `metadata`: a dictionary with various metadata about the question, this includes the question_type, seed_document_id the id of the document used to generate the question and the topic of the question <h1 id="community">👋 Community</h1> We welcome contributions from the AI community! Read this [guide](./CONTRIBUTING.md) to get started, and join our thriving community on [Discord](https://gisk.ar/discord). 🌟 [Leave us a star](https://github.com/Giskard-AI/giskard), it helps the project to get discovered by others and keeps us motivated to build awesome open-source tools! 🌟 ❤️ If you find our work useful, please consider [sponsoring us](https://github.com/sponsors/Giskard-AI) on GitHub. With a monthly sponsoring, you can get a sponsor badge, display your company in this readme, and get your bug reports prioritized. We also offer one-time sponsoring if you want us to get involved in a consulting project, run a workshop, or give a talk at your company.

🐢 Open-Source Evaluation & Testing for LLMs and ML models

mlops,ml-validation,ml-testing,ai-testing,ai-safety,ml-safety,llmops,ethical-artificial-intelligence,responsible-ai,fairness-ai

VonHeikemen/lsp-zero.nvim

# LSP Zero Collection of functions that will help you setup Neovim's LSP client, so you can get IDE-like features with minimum effort. Out of the box it will help you integrate [nvim-cmp](https://github.com/hrsh7th/nvim-cmp) (an autocompletion plugin) and [nvim-lspconfig](https://github.com/neovim/nvim-lspconfig) (a collection of configurations for various language servers). So a minimal config can look like this. ```lua require('lsp-zero') require('lspconfig').intelephense.setup({}) ``` With this code when `intelephense` (a language server for PHP) is active you'll get all the features Neovim offers by default plus autocompletion. [See demo in asciinema](https://asciinema.org/a/648850). ## How to get started If you are new to Neovim and you don't have a configuration file (`init.lua`) follow this [step by step tutorial](https://lsp-zero.netlify.app/v3.x/tutorial.html). If you know how to configure Neovim go to the [Getting started](https://lsp-zero.netlify.app/v3.x/getting-started.html) page in the documentation. Also consider `nvim-lspconfig` works fine without lsp-zero. And you can setup `nvim-cmp` by yourself. I wrote a blog post that shows how to do it: [You might not need lsp-zero](https://lsp-zero.netlify.app/v3.x/blog/you-might-not-need-lsp-zero.html). ## Documentation You can browse the documentation at [lsp-zero.netlify.app/v3.x](https://lsp-zero.netlify.app/v3.x/introduction.html) * [Installation and basic usage](https://lsp-zero.netlify.app/v3.x/getting-started.html) * [LSP configuration](https://lsp-zero.netlify.app/v3.x/language-server-configuration.html) * [Autocompletion](https://lsp-zero.netlify.app/v3.x/autocomplete.html) * [Frequent Questions](https://lsp-zero.netlify.app/v3.x/faq.html) <details> <summary>Expand: More Documentation Links </summary> * Integrations * [Integrate with mason.nvim](https://lsp-zero.netlify.app/v3.x/guide/integrate-with-mason-nvim.html) * [Enable folds with nvim-ufo](https://lsp-zero.netlify.app/v3.x/guide/quick-recipes.html#enable-folds-with-nvim-ufo) * [Setup copilot.lua + nvim-cmp](https://lsp-zero.netlify.app/v3.x/guide/setup-copilot-lua-plus-nvim-cmp.html) * [Setup with nvim-jdtls](https://lsp-zero.netlify.app/v3.x/guide/setup-with-nvim-jdtls.html) * [Setup lsp-inlayhints.nvim](https://lsp-zero.netlify.app/v3.x/guide/quick-recipes.html#enable-inlay-hints-with-lsp-inlayhints-nvim) * [Setup with nvim-navic](https://lsp-zero.netlify.app/v3.x/guide/quick-recipes.html#setup-with-nvim-navic) * [Setup with rustaceanvim](https://lsp-zero.netlify.app/v3.x/guide/quick-recipes.html#setup-with-rustaceanvim) * [Setup with flutter-tools](https://lsp-zero.netlify.app/v3.x/guide/quick-recipes.html#setup-with-flutter-tools) * [Setup with nvim-metals](https://lsp-zero.netlify.app/v3.x/guide/quick-recipes.html#setup-with-nvim-metals) * [Setup with haskell-tools](https://lsp-zero.netlify.app/v3.x/guide/quick-recipes.html#setup-with-haskell-tools) * Guides * [What to do when the language server doesn't start?](https://lsp-zero.netlify.app/v3.x/guide/what-to-do-when-lsp-doesnt-start.html) * [Lazy loading with lazy.nvim](https://lsp-zero.netlify.app/v3.x/guide/lazy-loading-with-lazy-nvim.html) * [lua_ls for Neovim](https://lsp-zero.netlify.app/v3.x/guide/neovim-lua-ls.html) * [Configure Volar 2.0 (with typescript support)](https://lsp-zero.netlify.app/v3.x/guide/configure-volar-v2.html) * [Migrate from v2.x to v3.x](https://lsp-zero.netlify.app/v3.x/guide/migrate-from-v2-branch.html) * [Migrate from v1.x to v3.x](https://lsp-zero.netlify.app/v3.x/guide/migrate-from-v1-branch.html) * API * [Commands](https://lsp-zero.netlify.app/v3.x/reference/commands.html) * [Variables](https://lsp-zero.netlify.app/v3.x/reference/variables.html) * [Lua API](https://lsp-zero.netlify.app/v3.x/guide/what-to-do-when-lsp-doesnt-start.html) * Blog posts * [You might not need lsp-zero](https://lsp-zero.netlify.app/v3.x/blog/you-might-not-need-lsp-zero.html) * [lsp-zero under the hood](https://lsp-zero.netlify.app/v3.x/blog/under-the-hood.html) * [require lsp-zero](https://lsp-zero.netlify.app/v3.x/blog/what-require-lsp-zero-does.html) * [ThePrimeagen 0 to LSP config](https://lsp-zero.netlify.app/v3.x/blog/theprimeagens-config-from-2022.html) </details> ## If you need any help Feel free to open a new [discussion](https://github.com/VonHeikemen/lsp-zero.nvim/discussions) in this repository. Or join the chat [#lsp-zero-nvim:matrix.org](https://matrix.to/#/#lsp-zero-nvim:matrix.org). If you have problems with a language server read this guide: [What to do when the language server doesn't start?](https://lsp-zero.netlify.app/v3.x/guide/what-to-do-when-lsp-doesnt-start.html) If you want to migrate from a previous version to the `v3.x` branch, follow one of these guides: * [Migrate from v2.x to v3.x](https://lsp-zero.netlify.app/v3.x/guide/migrate-from-v2-branch.html) * [Migrate from v1.x to v3.x](https://lsp-zero.netlify.app/v3.x/guide/migrate-from-v1-branch.html) ### When asking for help for a specific language One thing you should know when asking for help online: asking the question "how to configure [random language] with lsp-zero?" is not going to give you the results you want. You probably want to ask "how to configure the language server for [random language] using [nvim-lspconfig](https://github.com/neovim/nvim-lspconfig)?" That will give you better results because `nvim-lspconfig` is the plugin that configures the language servers. ## Quickstart (for the impatient) If you are not that impatient, I recommend reading the [Getting started](https://lsp-zero.netlify.app/v3.x/getting-started.html) page. But for those of you that just want to copy/paste, here are some templates you can use. * [Lua template configuration](https://lsp-zero.netlify.app/v3.x/template/lua-config.html) * [Vimscript template configuration](https://lsp-zero.netlify.app/v3.x/template/vimscript-config.html) * [ThePrimeagen's "0 to LSP" config updated](https://lsp-zero.netlify.app/v3.x/blog/theprimeagens-config-from-2022.html) ## Support If you find this tool useful and want to support my efforts, [buy me a coffee ☕](https://www.buymeacoffee.com/vonheikemen). [](https://www.buymeacoffee.com/vonheikemen)

A starting point to setup some lsp related features in neovim.

neovim,nvim,lsp,language-server-protocol

cinit/QAuxiliary

<div align="center"> <h1> QAuxiliary </h1> [](https://github.com/cinit/QAuxiliary/releases/latest) [](https://github.com/cinit/QAuxiliary/actions/workflows/push_ci.yml) [](https://t.me/QAuxiliary) [](https://t.me/QAuxiliary_CI) [](https://t.me/QAuxiliaryChat) </div> --- QAuxiliary 是一个基于 QNotified 的开源 Xposed 模块 ## 使用方法 激活本模块后，在 QQ 或者 TIM 自带设置中点击 QAuxiliary 即可进入设置页面 - Android >= 7.0 - QQ >= 8.2.0, TIM >= 2.2.0, QQLite >= 4.0, QQ HD >= 5.9.3 ## 一切开发旨在学习，请勿用于非法用途 - 本项目保证永久开源，欢迎提交 PR，但是请不要提交用于非法用途的功能。 - 如果某功能被大量运用于非法用途或严重侵害插件使用者权益，那么该功能将会被移除。 - 本模块完全免费开源，没有任何收费，请勿二次贩卖。 - 鉴于项目的特殊性，开发团队可能在任何时间**停止更新**或**删除项目** ### 许可证 - [EULA](https://github.com/qwq233/License/blob/master/v2/LICENSE.md) ``` 版权所有©2022 gao_cai_sheng <qwq233@qwq2333.top, qwq2333.top> 允许在遵守 CC BY-NC-SA 4.0 协议的同时，复制和分发此协议文档的逐字记录副本， 且允许对其进行更改，但必须保留其版权信息与原作者。如果您提出申请特殊权限，协议 作者可在其口头或书面授予任何人任何但不包括以盈利为目的的使用本协议的权利。 请务必仔细阅读和理解通用许可协议书中规定的所有权利和限制。在使用前，您需要仔细 阅读并决定接受或不接受本协议的条款。除非或直至您接受本协议的条款，否则本作品及 其相关副本、相关程序代码或相关资源不得在您的任何终端上下载、安装或使用。 您一旦下载、使用本作品及其相关副本、相关程序代码或相关资源，即表示您同意接受本 协议各项条款的约束。如您不同意本协议中的条款，您则应当立即删除本作品、附属资源 及其相关源代码。 本作品权利只许可使用，而不出售。 ``` ## 发行渠道说明 <details> QAuxiliary 采用滚动更新方式发布新版本，我们总是推荐用户使用最新版 QAuxiliary，无论您的 QQ 或者 TIM 客户端是哪个版本。 QAuxiliary 将为分 `CI` 和 `推荐的CI` 两个版本 - `CI` 版本为 commit 后自动触发更新，可能包含外围文档或 CI 流程更新，不会编写任何更新文档或说明， 具体更新内容可在[GitHub](https://github.com/cinit/QAuxiliary/commits/master) 自行查看，本更新由开源的流程自动编译发布，可能包含严重的功能及行为异常。 - `推荐的CI` 版本为重大功能变更或长期积累更新，发布频率由开发组决定，包含上次`CI` 版至今的所有功能更新及 Bug 修复，但可能不包括尚未稳定或正在开发中的功能； `推荐的CI` 版本是被挑选出的推荐用户更新的 `CI` 版本 (如：添加功能或者修复重要 Bug) 开发组不限制用户选择自己需要的版本，同时也不为任何版本产生的任何后果承担任何责任 （详情请见[QAuxiliary EULA](https://github.com/cinit/QAuxiliary/blob/master/app/src/main/assets/eula.md)）， 但希望各位用户各取所需，根据自己的能力范围选择适合自己的版本。 - QAuxiliary 的版本号组成为`major.minor.bugfix.rev.commit` - 其中 major 为 主版本号，minor 为 次版本号，bugfix 为修正版本号； - 所有版本更新的`rev`为 commit 计数，`commit` 位都会是触发此次更新的 commit 的 hash 的前 7 位。 1. [](https://t.me/QAuxiliary) 将只发布 `推荐的CI` 版更新。 2. [](https://t.me/QAuxiliary_CI) 发布 `CI` 版更新。 3. [](https://github.com/cinit/QAuxiliary/releases/latest) 将只发布 `推荐的CI` 版更新。 4. [](https://github.com/Xposed-Modules-Repo/io.github.qauxv/releases/) 将只发布 `推荐的CI` 版更新。 5. 为什么没有上架 Google Play? 因为 Google Play 不允许 app 具有运行时动态加载外部代码的行为。 而本模块为了能够在运行期动态继承宿主的类（类名被混淆，运行时才能确定），使用了 [byte-buddy](https://github.com/raphw/byte-buddy) 库用于在运行时动态生成代码并使用 InMemoryDexClassLoader 实现 dex 不落地加载，这是 Google Play 不允许的行为。 </details> ## 不会支持的功能 - 抢红包及其他金钱相关功能 - 修改聊天记录等可能被恶意利用的功能 - 群发消息 ## 编译 1. 安装 git, ccache(可选), cmake, SDK 和 NDK, 版本参考 [Version.kt](build-logic/convention/src/main/kotlin/Version.kt); 注意: 编译脚本会自动寻找 ccache 并使用，而 Windows 平台下 msys2 的 ccache 存在问题会卡在 sync 阶段， 建议 Windows 用户使用从 ccache 官网下载的 ccache 而不是 msys2 的 ccache; 另外你也可以选择不使用 ccache (如果你已经安装了 ccache 但不想使用，可以修改 [build.gradle.kts](app/build.gradle.kts) 中的 `ccacheExecutablePath` 为 `null`) 2. 将本仓库 clone 至本地：`git clone --recursive https://github.com/cinit/QAuxiliary`; 3. 使用 Gradle 编译安装包: `./gradlew :app:assembleDebug` 或者 `./gradlew :app:synthesizeDistReleaseApksCI`; --- ## 赞助 - 由于项目的特殊性，我们不接受任何形式的捐赠，但是我们希望有更多的人能够参与本项目的开发 - 如果您有兴趣参与本项目的开发，您可以参考[贡献指南](.github/CONTRIBUTING.md) ## [通用许可协议](https://github.com/qwq233/License/blob/master/v2/LICENSE.md)

QNotified phoenix - To make OICQ great again

qq,tim,xposed,xposed-module,oicq,qnotified

ip-scanner/cloudflare

# cloudflare

Librum-Reader/Librum

# Librum Librum is an application designed to make reading <b>enjoyable</b> and <b>straightforward</b> for everyone. It's not **just** an e-book reader. With Librum, you can manage your own online library and access it from any device anytime, anywhere. It has features like note-taking, AI tooling, and highlighting, while offering customization to make it as personal as you want! Librum also provides free access to over 70,000 books and personal reading statistics while being free and completely open source. ___ Join us on [Discord](https://discord.gg/hSX64qsFHc) # Preview Setup and manage your own online library  <br> A simple and modern interface  <br> Add your books to collections, tag them, and sort them in any way you want  <br> Customize Librum to make it personal to you  <br> # Where can I get Librum? Simply go to https://librumreader.com to download Librum. If you want to build Librum from source, follow the instructions [here](#build-guide). <br> # Contact For questions, you can reach us under: help@librumreader.com <br> For business related contact, reach out to us here: contact@librumreader.com <br> # Donations Donations make it possible for us to cover our server costs and allow us to make investments into new areas of development. <br> If you would like to support us, check out: https://librumreader.com/contribute/donate or become a Github sponsor! <br> <br> As a team of opensource developers we rely on donations to continue working on projects like Librum. Your help is greatly appreciated. <br> # Translations Librum is currently available in: - English - German - Russian - Ukrainian - Indonesian - Italian - Korean - Portuguese - Mandarin If you want to translate Librum to another language, follow the steps below: - Download [this file](https://github.com/Librum-Reader/Librum/blob/dev/develop/src/presentation/translations/librum_en.ts) - Rename the file to contain your language's suffix, e.g. "librum_ru.ts" for Russian or "librum_de.ts" for German - Download the translation software (Qt Linguist) either for Windows from [here](https://github.com/thurask/Qt-Linguist) or using the [Qt Installer](https://www.qt.io/download-open-source) - Now start Qt Linguist, open the downloaded file, set the target language to the language you want to translate to and start translating. (Check out [this guide](https://youtu.be/xNIz78IPBu0?t=347) for a quick overview of Qt Linguist) Once you are done, create a pull request or open up an issue with your new translation file!<br> If you run into any problems, need guidance or have questions, feel free to reach out to us at: contact@librumreader.com <br> Notes: - Make sure that your translations are approximately the same length as the original text - Please carefully check for spelling mistakes (including punctuation and capitalization) <br> # Documentation For documentation go to [Librum's GitHub-wiki](https://github.com/Librum-Reader/Librum/wiki) <br> # Contributing If you'd like to contribute, check out: https://librumreader.com/contribute <br> <br> If you are interested in contributing, feel free to contact us on either:<br> 1. Discord (m_david#0631) 2. Email (contact@librumreader.com) <br> We are following a pull request workflow where every contribution is sent as a pull request and merged into the dev/develop branch for testing. <br> Please make sure to run clang format, keep to the conventions used throughout the application and ensure that all tests pass, before submitting any pull request. <br> <br> # Self-hosting To self-host Librum you need to run [Librum-Server](https://github.com/Librum-Reader/Librum-Server) locally (instructions can be found [here](https://github.com/Librum-Reader/Librum-Server#self-hosting)) and tell the client to use your self-hosted server by: - (Linux) Editing ~/.config/Librum-Reader/Librum.conf and setting `selfHosted=true` and `serverHost` to your server's url (e.g. `serverHost=https://127.0.0.1:5001`) - (Windows) Opening the registry editor (Press `Win + R` and search for `regedit`), navigating to `HKEY_CURRENT_USER\Software\Librum-Reader\Librum` and setting `selfHosted=true` and `serverHost` to your server's url Make sure to run the application before following the steps above, to generate the required files. <br> # Details ### Supported platforms Part of Librum's aim is to work on **any** platform. No matter where you are or which device you use, you can always continue your book with Librum, as it is <b>cross platform</b>.<br> We support: - Windows - GNU/Linux - MacOS - IOS (Coming Soon) - Android (Coming Soon) <br> ### Supported formats Librum is the best choice for all kinds of books, since Librum supports <b>all</b> major book formats<br> including: - PDF - EPUB - CBZ (Comic books) - FB2 - TIFF - Mobi - XPS - Images And many more! <br> ### Features Librum's objective is to make your reading more <b>productive</b>; to that end, we provide you with a variety of features that you can access via a <b>simple</b> and <b>straightforward</b> interface.<br> These features include: - A modern e-reader - A personalized and customizable online library - Book meta-data editing - A free in-app bookstore with more than 70,000 books - Book syncing across all of your devices - Highlighting - Bookmarking - Text search - Unlimited customization - Fine-grained organization through Librum's folder system - Note-taking (Coming Soon) - TTS (Coming Soon) - Personalized reading statistics (Coming Soon) Want a new feature? Feel free to leave a feature request ticket! <br><br> # Build Guide Follow this guide to build Librum from source. <br> ## For GNU/Linux ### Prerequisites - cmake (https://cmake.org/download) - make (http://ftp.gnu.org/gnu/make) - g++ (https://gcc.gnu.org) - python3-venv (on ubuntu use `sudo apt install python3-venv`) - Qt 6.5 (https://www.qt.io/download-open-source) ### Installation The installation is straight forward, just follow the steps below: <br> 1. Clone the repository. ```sh git clone https://github.com/Librum-Reader/Librum.git --recursive ``` 2. Step into the cloned project folder. ```sh cd Librum ``` 3. Create the build folder and step into it. ```sh mkdir build-Release cd build-Release ``` 4. Run cmake. ```sh cmake -DCMAKE_INSTALL_PREFIX=/usr -DCMAKE_BUILD_TYPE=Release -DBUILD_TESTS=Off -DCMAKE_PREFIX_PATH=<path/to/Qt> .. ``` Set `CMAKE_PREFIX_PATH` to your Qt installation path. Installing Qt via the online installer usually installs it to `/home/<name>/Qt/<version>/gcc_64` 6. Build the project ```sh cmake --build . -j $(nproc) ``` 7. Install Librum ```sh cmake --install . ``` <br> ### Troubleshooting Here are solutions to some common errors. If your error is not listed here, please open an issue. <br> - Error: `Failed to find required Qt component "Quick".`<br> - Solution: Install the libGL mesa dev package, on ubuntu its `sudo apt install libgl1-mesa-dev` and on fedora its `sudo dnf install mesa-libGL-devel`. - Error: `Could not load the qt platform plugin "xcb" even though it was found` - Solution: Install the libxcb-cursor-dev, on ubuntu its `sudo apt install libxcb-cursor-dev` <br> ## For Windows ### Prerequisites - cmake (https://cmake.org/download) - Visual Studio <b>19</b> (https://visualstudio.microsoft.com/de/vs/older-downloads) - Python (https://www.python.org/downloads) - Qt 6.5 (https://www.qt.io/download-open-source) ### Installation To build Librum on windows, run the following commands in the Powershell: <br> 1. Clone the repository. ```sh git clone https://github.com/Librum-Reader/Librum.git --recursive ``` 2. Step into the cloned project folder. ```sh cd Librum ``` 3. Create the build folder and step into it. ```sh mkdir build cd build ``` 4. Run cmake. ```sh cmake -DBUILD_TESTS=Off -DCMAKE_PREFIX_PATH=<path/to/qt> .. ``` Set `CMAKE_PREFIX_PATH` to your Qt installation path. Installing Qt via the online installer usually installs it to `<Drive>\\Qt\\<version>\\msvc2019_64` 6. Build the project ```sh cmake --build . --config Release ``` 7. Run the app ```sh ./librum ``` ### Additional Info Here are some things to keep in mind during the build process. <br> - Make sure to add cmake and the Qt binaries to the `PATH` environment variable - You need Visual Studio 2019, newer versions will **not** work - For the Qt installation, you **only** need to choose "MSVC 2019 64-bit", you can untick everything else to reduce the download size <br> ## For MacOS ### Prerequisites - cmake (https://cmake.org/download) - make (http://ftp.gnu.org/gnu/make) - g++ (https://gcc.gnu.org) - python3 (https://www.python.org/downloads) - Qt 6.5 (https://www.qt.io/download-open-source) ### Installation The installation is straight forward, just follow the steps below: <br> 1. Clone the repository. ```sh git clone https://github.com/Librum-Reader/Librum.git --recursive ``` 2. Step into the cloned project folder. ```sh cd Librum ``` 3. Create the build folder and step into it. ```sh mkdir build-Release cd build-Release ``` 4. Run cmake. ```sh cmake -DCMAKE_INSTALL_PREFIX=/usr/local -DCMAKE_BUILD_TYPE=Release -DBUILD_TESTS=Off -DCMAKE_PREFIX_PATH=<path/to/Qt> .. ``` Set `CMAKE_PREFIX_PATH` to your Qt installation path. Installing Qt via the online installer usually installs it to `/Users/<name>/Qt/<version>/macos` 6. Build the project ```sh cmake --build . -j $(nproc) ``` 7. Install Librum ```sh cmake --install ``` Note: Make sure to add `/usr/local/lib` to your DYLIB path, for MacOS to find the installed libraries by exporting `DYLD_LIBRARY_PATH=$DYLD_LIBRARY_PATH:/usr/local/lib`. <br>

The Librum client application

cmake,cpp,qml,qt,ebook-reader,ebooks,library-management,reader,linux,qt6

open-duelyst/duelyst

# OpenDuelyst  This is the source code for Duelyst, a digital collectible card game and turn-based strategy hybrid developed by Counterplay Games and released in 2016. ## Running the Game Locally If you'd like to run the game locally or contribute to OpenDuelyst, check out our [Documentation](docs/README.md), especially the [Roadmap](docs/ROADMAP.md) and [Contributor Guide](docs/CONTRIBUTING.md). You can also join the OpenDuelyst developer Discord server [here](https://discord.gg/HhUWfZ9cxe). This Discord server is focused on the development of OpenDuelyst, and has channels for frontend, backend, and infrastructure discussions, but it is open for anyone to join. ## Downloading the Desktop Clients Desktop clients for Windows, Mac, and Linux can be downloaded on the [Releases](https://github.com/open-duelyst/duelyst/releases) page. They can be used against your local environment. ## Playing on Android or iOS We have basic support for playing on mobile web currently. To hide the status/navigation bar in Chrome or Safari, open the game and select "Add to Home Screen". When you open the game from the home screen, the status bar will be hidden. ## Filing Issues and Reporting Bugs If you encounter a bug and would like to report it, first check the [Open Issues](https://github.com/open-duelyst/duelyst/issues/) to see if the bug has already been reported. If not, feel free to create a new issue with the `bug` label. If you would like to request a technical feature or enhancement to the code, you can create a new issue with the `enhancement` label. Since OpenDuelyst is currently focused on recreating the game as it last existed in v1.96.17, please avoid creating feature requests related to balance changes. ## Localization The game currently includes English and German localization. If you'd like to contribute translations for another language, take a look at the `app/localization/locales` directory. You can copy the `en` folder and start updating strings for the new language, then submit a Pull Request with your contribution. There are about 4,500 localized strings, so this can also be done a little bit at a time. Once the translations are in, we can help get the language included in the game. ## License OpenDuelyst is licensed under the Creative Commons Zero v1.0 Universal license. You can see a copy of the license [here](LICENSE).

Duelyst is a digital collectible card game and turn-based strategy hybrid, developed by Counterplay Games.

sofn-xyz/mailing

packages/cli/README.md

Build, test, send emails with React

PeiQi0/PeiQi-WIKI-Book

 ## 0x01 关于文库 PeiQi文库是一个面对网络安全从业者的知识库，涉及漏洞研究，代码审计，CTF夺旗，红蓝对抗等多个安全方向，用于解决安全信息不聚合，安全资料不易找的难题。帮助网络安全从业者共同构建安全的互联网，快速验证并及时修复相关漏洞，为甲方等提出安全建设意见。  ## 0x02 使用须知 & 关注公众号 由于传播、利用此文所提供的信息而造成的任何直接或者间接的后果及损失，均由使用者本人负责，文章作者不为此承担任何责任。文库内容中部分攻防技巧等只允许在目标授权的情况下进行使用，大部分文章来自各大安全社区，个人博客，如有侵权请立即联系公众号进行删除。若不同意以上警告信息请立即退出使用  ## 0x03 快速搭建 Yarn源码搭建 (个人二次扩展，需要编译环境) ```sh git clone https://github.com/PeiQi0/PeiQi-WIKI-Book.git cd PeiQi-WIKI-Book yarn add vuepress-theme-antdocs -d yarn install yarn run dev ``` Html源码搭建 (无需编译环境，使用编译好的Html文件直接部署) ```sh git clone https://github.com/PeiQi0/PeiQi-WIKI-Book.git (Github,国外较快) git clone https://gitee.com/peiqi0/PeiQi-WIKI-Book.git (Gitee,国内较快) cd PeiQi-WIKI-Book/docs/.vuepress/dist mv * 你的服务器Web目录 ``` Docker搭建 (只需要Dokcer环境，快速搭建在各个环境中，定时同步Gitee自动更新) ```sh docker search peiqipeiqi docker pull peiqipeiqi/peiqi_wiki:220420 docker run -t -d -p 65534:80 --name "PeiQi_Wiki" peiqipeiqi/peiqi_wiki:220420 User/Pass: peiqi:peiqi (手动更新:进入Docker执行命令，/usr/share/nginx/html/synchronous.sh) ```  ## 0x04 关于开源 我认为开源才是最好的交流方式，所以文库的文章，代码都是公开可以任意下载的。希望能帮助到不管是一线红队，还是刚入门的安全小白，让大家都有一个可以公开交流，查找资料的地方。在文库开放后，我几乎将所有的闲暇时间都用在了文库的搭建上。现在的文库与之前的Gitbook版本相比，无论是阅读感受还是用户交互，都得到了更大的提升，希望大家可以通过提出建设性意见或者赞助项目来给予我更多更新的动力～  ## 0x05 文库动态 & 建议反馈 & 友情链接   

面向网络安全从业者的知识文库🍃

cve,1day,0day,vuln,redteam,peiqi-wiki

metalbear-co/mirrord

<div align="center">  </div> [](https://discord.gg/metalbear)   [](https://twitter.com/metalbearco) [mirrord lets developers run local processes in the context of their Kubernetes environment](https://mirrord.dev/). It’s meant to provide the benefits of running your service on a cloud environment (e.g. staging) without actually going through the hassle of deploying it there, and without disrupting the environment by deploying untested code. It comes as a Visual Studio Code extension, an IntelliJ plugin and a CLI tool. You can read more about it [here](https://mirrord.dev/docs/overview/introduction/). # Contents - [Contents](#contents) - [Getting Started](#getting-started) - [VS Code Extension](#vs-code-extension) - [Installation](#installation) - [How To Use](#how-to-use) - [IntelliJ Plugin](#intellij-plugin) - [Installation](#installation-1) - [How To Use](#how-to-use-1) - [CLI Tool](#cli-tool) - [Installation](#installation-2) - [How To Use](#how-to-use-2) - [How It Works](#how-it-works) - [Additional capabilities](#additional-capabilities) - [FAQ](#faq) - [Contributing](#contributing) - [Help and Community](#help-and-community) - [Code of Conduct](#code-of-conduct) - [License](#license) --- ## Getting Started - [VS Code Extension](#vs-code-extension) - [IntelliJ Plugin](#intellij-plugin) - [CLI Tool](#cli-tool) > mirrord uses your machine's default kubeconfig for access to the Kubernetes API. --- ## VS Code Extension ### Installation Get the extension [here](https://marketplace.visualstudio.com/items?itemName=MetalBear.mirrord). ### How To Use - Click "Enable mirrord" on the status bar - Start debugging your project - Choose pod to impersonate - The debugged process will be plugged into the selected pod by mirrord <p align="center"> <img src="./images/vscode.gif"> </p> --- ## IntelliJ Plugin ### Installation Get the plugin [here](https://plugins.jetbrains.com/plugin/19772-mirrord). ### How To Use - Click the mirrord icon in the Navigation Toolbar - Start debugging your project - Choose a namespace and pod to impersonate - The debugged process will be plugged into the selected pod by mirrord <p align="center"> <img src="./intellij-ext/src/main/resources/META-INF/usage.gif"> </p> --- ## CLI Tool ### Installation You can use either ```sh brew install metalbear-co/mirrord/mirrord ``` or ```sh curl -fsSL https://raw.githubusercontent.com/metalbear-co/mirrord/main/scripts/install.sh | bash ``` - Windows isn't currently supported (you can use WSL) ### How To Use ```sh mirrord exec <process command> --target <target-path> ``` e.g. ```sh mirrord exec node app.js --target pod/my-pod ``` --- ## How It Works When you select a pod to impersonate, mirrord launches a pod on the same node as the pod you selected. The new pod is then used to connect your local process and the impersonated pod: it mirrors incoming traffic from the pod to your process, routes outgoing traffic from your process through the pod, and does the same for file reads, file writes, and environment variables. You can read more about it [here](https://mirrord.dev/docs/overview/introduction/). ### Additional capabilities Container run inside the pod launched by mirrord requires additional [Linux capabilities](https://man7.org/linux/man-pages/man7/capabilities.7.html): - `CAP_NET_ADMIN` and `CAP_NET_RAW` - for modifying routing tables - `CAP_SYS_PTRACE` - for reading target pod environment - `CAP_SYS_ADMIN` - for joining target pod network namespace However, you can disable any subset of those in the [configuration](https://mirrord.dev/docs/reference/configuration/). This will possibly limit mirrord functionalities or even make it unusable in some setups. ```bash MIRRORD_AGENT_DISABLED_CAPABILITIES=CAP_NET_RAW,CAP_SYS_PTRACE mirrord exec node app.js --target pod/my-pod ``` <p align="center"> <img src="./images/how_it_works.svg" alt="How It Works"/> </p> ## FAQ Our FAQ is available [here](https://mirrord.dev/docs/faq/general/). If you have a question that's not on there, feel free to ask in our [Discussions](https://github.com/metalbear-co/mirrord/discussions) or on [Discord](https://discord.gg/metalbear). ## Contributing Contributions are very welcome. Start by checking out our [open issues](https://github.com/metalbear-co/mirrord/issues), and by going through our [contributing guide](CONTRIBUTING.md). We're available on [Discord](https://discord.gg/metalbear) for any questions. ## Help and Community Join our [Discord Server](https://discord.gg/metalbear) for questions, support and fun. ## Code of Conduct We take our community seriously and we are dedicated to providing a safe and welcoming environment for everyone. Please take a few minutes to review our [Code of Conduct](./CODE_OF_CONDUCT.md). ## License [MIT](./LICENSE)

Connect your local process and your cloud environment, and run local code in cloud conditions.

cloud,kubernetes,debug,traffic,api,sniffer,ide,vscode,vscode-extension,cli

alibaba/fastjson2

[](https://github.com/alibaba/fastjson2/actions/workflows/ci.yaml) [](https://codecov.io/gh/alibaba/fastjson2/branch/main) [](https://search.maven.org/artifact/com.alibaba.fastjson2/fastjson2) [](https://github.com/alibaba/fastjson2/releases) [](https://openjdk.java.net/) [](https://www.apache.org/licenses/LICENSE-2.0.html) [](https://gitpod.io/#https://github.com/alibaba/fastjson2) [](https://oss.sonatype.org/content/repositories/snapshots/com/alibaba/fastjson2/) [](https://github.com/alibaba/fastjson2/stargazers) [](https://github.com/alibaba/fastjson2/fork) [](https://github.com/alibaba/fastjson2/network/dependents) [](https://github.com/alibaba/fastjson2/graphs/contributors) ##### [📖 English Documentation](README_EN.md) | 📖 中文文档 ##### 本项目的Issues会被同步沉淀至[阿里云开发者社区](https://developer.aliyun.com/ask/) # FASTJSON v2 `FASTJSON 2`是一个性能极致并且简单易用的Java JSON库。 - `FASTJSON 2`是`FASTJSON`项目的重要升级，和FASTJSON 1相比，性能有非常大的提升，解决了autoType功能因为兼容和白名单的安全性问题。 - 性能极致，性能远超过其他流行JSON库，包括jackson/gson/org.json，性能数据: [https://github.com/alibaba/fastjson2/wiki/fastjson_benchmark](https://github.com/alibaba/fastjson2/wiki/fastjson_benchmark) - 支持JDK新特性，包括`JDK 11`/`JDK 17`，针对`compact string`优化，支持Record，支持`GraalVM Native-Image` - 完善的[`JSONPath`](https://alibaba.github.io/fastjson2/jsonpath_cn)支持，支持[SQL:2016](https://en.wikipedia.org/wiki/SQL:2016)的JSONPath语法 - 支持`Android 8+`，客户端和服务器一套API - 支持`Kotlin` [https://alibaba.github.io/fastjson2/kotlin_cn](https://alibaba.github.io/fastjson2/kotlin_cn) - 支持`JSON Schema` [https://alibaba.github.io/fastjson2/json_schema_cn](https://alibaba.github.io/fastjson2/json_schema_cn) - 新增加支持二进制格式JSONB [https://alibaba.github.io/fastjson2/jsonb_format_cn](https://alibaba.github.io/fastjson2/jsonb_format_cn)  # 1. 使用准备 ## 1.1 添加依赖 在`fastjson v2`中，`groupId`和`1.x`不一样，是`com.alibaba.fastjson2`： `Maven`: ```xml <dependency> <groupId>com.alibaba.fastjson2</groupId> <artifactId>fastjson2</artifactId> <version>2.0.51</version> </dependency> ``` `Gradle`: ```groovy dependencies { implementation 'com.alibaba.fastjson2:fastjson2:2.0.51' } ``` 可以在 [maven.org](https://search.maven.org/artifact/com.alibaba.fastjson2/fastjson2) 查看最新可用的版本。 ## 1.2 其他模块 ### `Fastjson v1`兼容模块 如果原来使用`fastjson 1.2.x`版本，可以使用兼容包，兼容包不能保证100%兼容，请仔细测试验证，发现问题请及时反馈。 `Maven`: ```xml <dependency> <groupId>com.alibaba</groupId> <artifactId>fastjson</artifactId> <version>2.0.51</version> </dependency> ``` `Gradle`: ```groovy dependencies { implementation 'com.alibaba:fastjson:2.0.51' } ``` ### `Fastjson Kotlin`集成模块 如果项目使用`Kotlin`，可以使用`fastjson-kotlin`模块，使用方式上采用`kotlin`的特性。 * `Maven`: ```xml <dependency> <groupId>com.alibaba.fastjson2</groupId> <artifactId>fastjson2-kotlin</artifactId> <version>2.0.51</version> </dependency> ``` 酌情添加标准库(kotlin-stdlib)、反射库(kotlin-reflect)， 其中若使用数据类(data class)、通过构造函数传入参数则添加反射库。 ```xml <dependency> <groupId>org.jetbrains.kotlin</groupId> <artifactId>kotlin-stdlib</artifactId> <version>${kotlin-version}</version> </dependency> <dependency> <groupId>org.jetbrains.kotlin</groupId> <artifactId>kotlin-reflect</artifactId> <version>${kotlin-version}</version> </dependency> ``` * `Kotlin Gradle`: ```kotlin dependencies { implementation("com.alibaba.fastjson2:fastjson2-kotlin:2.0.51") } ``` ```kotlin dependencies { implementation("org.jetbrains.kotlin:kotlin-stdlib:$kotlin_version") implementation("org.jetbrains.kotlin:kotlin-reflect:$kotlin_version") } ``` ### `Fastjson Extension`扩展模块 如果项目使用`SpringFramework`等框架，可以使用`fastjson-extension`模块，使用方式参考 [SpringFramework Support](docs/spring_support_cn.md)。 `Maven`: ```xml <dependency> <groupId>com.alibaba.fastjson2</groupId> <artifactId>fastjson2-extension-spring5</artifactId> <version>2.0.51</version> </dependency> ``` ```xml <dependency> <groupId>com.alibaba.fastjson2</groupId> <artifactId>fastjson2-extension-spring6</artifactId> <version>2.0.51</version> </dependency> ``` `Gradle`: ```groovy dependencies { implementation 'com.alibaba.fastjson2:fastjson2-extension-spring5:2.0.51' } ``` ```groovy dependencies { implementation 'com.alibaba.fastjson2:fastjson2-extension-spring6:2.0.51' } ``` # 2. 简单使用 在`fastjson v2`中，`package`和`1.x`不一样，是`com.alibaba.fastjson2`。如果你之前用的是`fastjson1`，大多数情况直接更包名就即可。 ### 2.1 将`JSON`解析为`JSONObject` `Java`: ```java String text = "..."; JSONObject data = JSON.parseObject(text); byte[] bytes = ...; JSONObject data = JSON.parseObject(bytes); ``` `Kotlin`: ```kotlin import com.alibaba.fastjson2.* val text = ... // String val data = text.parseObject() val bytes = ... // ByteArray val data = bytes.parseObject() // JSONObject ``` ### 2.2 将`JSON`解析为`JSONArray` `Java`: ```java String text = "..."; JSONArray data = JSON.parseArray(text); ``` `Kotlin`: ```kotlin import com.alibaba.fastjson2.* val text = ... // String val data = text.parseArray() // JSONArray ``` ### 2.3 将`JSON`解析为`Java`对象 `Java`: ```java String text = "..."; User data = JSON.parseObject(text, User.class); ``` `Kotlin`: ```kotlin import com.alibaba.fastjson2.* val text = ... // String val data = text.to<User>() // User val data = text.parseObject<User>() // User ``` ### 2.4 将`Java`对象序列化为`JSON` `Java`: ```java Object data = "..."; String text = JSON.toJSONString(data); byte[] text = JSON.toJSONBytes(data); ``` `Kotlin`: ```kotlin import com.alibaba.fastjson2.* val data = ... // Any val text = text.toJSONString() // String val bytes = text.toJSONByteArray() // ByteArray ``` ### 2.5 使用`JSONObject`、`JSONArray` #### 2.5.1 获取简单属性 ```java String text = "{\"id\": 2,\"name\": \"fastjson2\"}"; JSONObject obj = JSON.parseObject(text); int id = obj.getIntValue("id"); String name = obj.getString("name"); ``` ```java String text = "[2, \"fastjson2\"]"; JSONArray array = JSON.parseArray(text); int id = array.getIntValue(0); String name = array.getString(1); ``` #### 2.5.2 读取`JavaBean` `Java`: ```java JSONArray array = ... JSONObject obj = ... User user = array.getObject(0, User.class); User user = obj.getObject("key", User.class); ``` `Kotlin`: ```kotlin val array = ... // JSONArray val obj = ... // JSONObject val user = array.to<User>(0) val user = obj.to<User>("key") ``` #### 2.5.3 转为`JavaBean` `Java`: ```java JSONArray array = ... JSONObject obj = ... User user = obj.toJavaObject(User.class); List<User> users = array.toJavaList(User.class); ``` `Kotlin`: ```kotlin val array = ... // JSONArray val obj = ... // JSONObject val user = obj.to<User>() // User val users = array.toList<User>() // List<User> ``` ### 2.6 将`JavaBean`对象序列化为`JSON` `Java`: ```java class User { public int id; public String name; } User user = new User(); user.id = 2; user.name = "FastJson2"; String text = JSON.toJSONString(user); byte[] bytes = JSON.toJSONBytes(user); ``` `Kotlin`: ```kotlin class User( var id: Int, var name: String ) val user = User() user.id = 2 user.name = "FastJson2" val text = user.toJSONString() // String val bytes = user.toJSONByteArray() // ByteArray ``` 序列化结果: ```json { "id" : 2, "name" : "FastJson2" } ``` # 3. 进阶使用 ### 3.1 使用`JSONB` #### 3.1.1 将`JavaBean`对象序列化`JSONB` ```java User user = ...; byte[] bytes = JSONB.toBytes(user); byte[] bytes = JSONB.toBytes(user, JSONWriter.Feature.BeanToArray); ``` #### 3.1.2 将`JSONB`数据解析为`JavaBean` ```java byte[] bytes = ... User user = JSONB.parseObject(bytes, User.class); User user = JSONB.parseObject(bytes, User.class, JSONReader.Feature.SupportBeanArrayMapping); ``` ### 3.2 使用`JSONPath` #### 3.2.1 使用`JSONPath`读取部分数据 ```java String text = ...; JSONPath path = JSONPath.of("$.id"); // 缓存起来重复使用能提升性能 JSONReader parser = JSONReader.of(text); Object result = path.extract(parser); ``` #### 3.2.2 使用`JSONPath`读取部分`byte[]`的数据 ```java byte[] bytes = ...; JSONPath path = JSONPath.of("$.id"); // 缓存起来重复使用能提升性能 JSONReader parser = JSONReader.of(bytes); Object result = path.extract(parser); ``` #### 3.2.3 使用`JSONPath`读取部分`byte[]`的数据 ```java byte[] bytes = ...; JSONPath path = JSONPath.of("$.id"); // 缓存起来重复使用能提升性能 JSONReader parser = JSONReader.ofJSONB(bytes); // 注意这里使用ofJSONB方法 Object result = path.extract(parser); ``` ## Star History [](https://star-history.com/#alibaba/fastjson2)

🚄 FASTJSON2 is a Java JSON library with excellent performance.

json,fastjson,json-parser,jsonb,java-json,json-serialization,json-path,high-performance,fastjson2,android

dromara/dynamic-tp

<p align="center"> <img alt="logo" src="resources/img/logo.png" width="50%"> </p> <p align="center"> <strong>基于配置中心的轻量级动态线程池，内置监控告警功能，集成常用中间件线程池管理，可通过SPI自定义扩展实现</strong> </p> <p align="center"> <a href="https://gitee.com/dromara/dynamic-tp"><img src="https://gitee.com/dromara/dynamic-tp/badge/star.svg"></a> <a href="https://gitee.com/dromara/dynamic-tp/members"><img src="https://gitee.com/dromara/dynamic-tp/badge/fork.svg"></a> <a href="https://github.com/dromara/dynamic-tp"><img src="https://img.shields.io/github/stars/dromara/dynamic-tp?style=flat-square&logo=github"></a> <a href="https://github.com/dromara/dynamic-tp/network/members"><img src="https://img.shields.io/github/forks/dromara/dynamic-tp?style=flat-square&logo=GitHub"></a> <a href="https://github.com/dromara/dynamic-tp/blob/master/LICENSE"><img src="https://img.shields.io/github/license/dromara/dynamic-tp.svg?style=flat-square"></a> <a target="_blank" href="/resources/img/contact.jpg"><img src='resources/img/wechat.jpg' alt='备注加群'></a> </p> <p align="center"> 官网： <a href="https://dynamictp.cn">https://dynamictp.cn</a> 🔥 </p> --- ## 使用痛点 使用线程池 ThreadPoolExecutor 过程中你是否有以下痛点呢？ > 1. 代码中创建了一个 ThreadPoolExecutor，但是不知道那几个核心参数设置多少比较合适 > > 2. 凭经验设置参数值，上线后发现需要调整，改代码重新发布服务，非常麻烦 > > 3. 线程池相对开发人员来说是个黑盒，运行情况不能及时感知到，直到出现问题 如果有以上痛点，动态可监控线程池框架（**DynamicTp**）或许能帮助到你。 如果看过 ThreadPoolExecutor 的源码，大概可以知道它对核心参数基本都有提供 set / get 方法以及一些扩展方法，可以在运行时动态修改、获取相应的值，这些方法有： ```java public void setCorePoolSize(int corePoolSize); public void setMaximumPoolSize(int maximumPoolSize); public void setKeepAliveTime(long time, TimeUnit unit); public void setThreadFactory(ThreadFactory threadFactory); public void setRejectedExecutionHandler(RejectedExecutionHandler handler); public void allowCoreThreadTimeOut(boolean value); public int getCorePoolSize(); public int getMaximumPoolSize(); public long getKeepAliveTime(TimeUnit unit); public BlockingQueue<Runnable> getQueue(); public RejectedExecutionHandler getRejectedExecutionHandler(); public boolean allowsCoreThreadTimeOut(); protected void beforeExecute(Thread t, Runnable r); protected void afterExecute(Runnable r, Throwable t); ``` 现在大多数的互联网项目都会采用微服务化部署，有一套自己的服务治理体系，微服务组件中的分布式配置中心 扮演的就是动态修改配置，实时生效的角色。 那么我们是否可以结合配置中心来做运行时线程池参数的动态调整呢？ 答案是肯定的，而且配置中心相对都是高可用的，使用它也不用过于担心配置推送失败这类问题，而且也能减少研发动态线程池组件本身的难度和接入的工作量。 **综上，可以总结出以下的背景** - **广泛性**：在 Java 开发中，想要提高系统性能，线程池已经是一个 90% 以上开发人员都会选择使用的基础工具 - **不确定性**：项目中可能存在很多线程池，既有 IO 密集型的，也有 CPU 密集型的，但线程池的核心参数并不好确定，需要有套机制在运行过程中动态去调整参数 - **无感知性**：线程池运行过程中的各项指标一般感知不到，需要有套监控报警机制在事前、事中就能让开发人员感知到线程池的运行状况，及时处理 - **高可用性**：配置变更需要及时推送到客户端，需要有高可用的配置管理推送服务，配置中心是现在大多数互联网系统都会使用的组件，与之结合可以极大提高系统可用性 --- ## 功能特性 基于以上背景分析，我们对线程池 ThreadPoolExecutor 做一些扩展增强，主要实现以下目标 > 1. 实现对运行中线程池参数的动态修改，实时生效 > > 2. 实时监控线程池的运行状态，触发设置的报警策略时报警，报警信息推送办公平台 > > 3. 定时采集线程池指标数据，配合像 Grafana 这种可视化监控平台做大盘监控 > > 4. 集成常用三方中间件内部线程池管理 **经过多个版本的迭代，目前最新版本 v1.1.7 具有以下特性** ✅ - **代码零侵入**：我们改变了线程池以往的使用姿势，所有配置均放在配置中心，服务启动时会从配置中心拉取配置生成线程池对象放到 Spring 容器中，使用时直接从 Spring 容器中获取，对业务代码零侵入 - **通知告警**：提供多种通知告警维度（配置变更通知、活性报警、队列容量阈值报警、拒绝触发报警、任务执行或等待超时报警），触发配置阈值实时推送告警信息，已支持企微、钉钉、飞书、邮件、云之家报警，同时提供 SPI 接口可自定义扩展实现 - **运行监控**：定时采集线程池指标数据（20 多种指标，包含线程池维度、队列维度、任务维度、tps、tp99等），支持通过 MicroMeter、JsonLog 两种方式，也可以通过 SpringBoot Endpoint 端点实时获取最新指标数据，同时提供 SPI 接口可自定义扩展实现 - **任务增强**：提供任务包装功能（比 Spring 线程池任务包装更强大），实现 TaskWrapper 接口即可，如 MdcTaskWrapper、TtlTaskWrapper、SwTraceTaskWrapper、OpenTelemetryWrapper，可以支持线程池上下文信息传递 - **多配置中心支持**：支持多种主流配置中心，包括 Nacos、Apollo、Zookeeper、Consul、Etcd、Polaris、ServiceComb，同时也提供 SPI 接口可自定义扩展实现 - **中间件线程池管理**：集成管理常用第三方组件的线程池，已集成 Tomcat、Jetty、Undertow、Dubbo、RocketMq、Hystrix、Grpc、Motan、Okhttp3、Brpc、Tars、SofaRpc、RabbitMq 等组件的线程池管理（调参、监控报警） - **轻量简单**：使用起来极其简单，引入相应依赖，接入只需简单 4 步就可完成，顺利 3 分钟搞定，相当丝滑 - **多模式**：提供了增强线程池 DtpExecutor，IO 密集型场景使用的线程池 EagerDtpExecutor，调度线程池 ScheduledDtpExecutor，有序线程池 OrderedDtpExecutor，可以根据业务场景选择合适的线程池 - **兼容性**：JUC 普通线程池和 Spring 中的 ThreadPoolTaskExecutor 也可以被框架管理，@Bean 定义时加 @DynamicTp 注解即可 - **可靠性**：依靠 Spring 生命周期管理，可以做到优雅关闭线程池，在 Spring 容器关闭前尽可能多的处理队列中的任务 - **高可扩展**：框架核心功能都提供 SPI 接口供用户自定义个性化实现（配置中心、配置文件解析、通知告警、监控数据采集、任务包装等等） - **线上大规模应用**：参考[美团线程池实践](https://tech.meituan.com/2020/04/02/java-pooling-pratice-in-meituan.html)，美团内部已经有该理论成熟的应用经验 --- ## 架构设计 **框架功能大体可以分为以下几个模块** > 1. 配置变更监听模块 > > 2. 线程池管理模块 > > 3. 监控模块 > > 4. 通知告警模块 > > 5. 三方组件线程池管理模块  详细查看官网文档，[架构设计](https://dynamictp.cn/guide/introduction/architecture.html) --- ## 接入步骤 > 1. 引入相应配置中心的依赖，具体见官网文档 > > 2. 配置中心配置线程池实例，配置文件见官网文档 > > 3. 启动类加 @EnableDynamicTp 注解 > > 4. 使用 @Resource 或 @Autowired 进行依赖注入，或通过 DtpRegistry.getExecutor("name") 获取 > > 5. 通过以上 4 步就可以使用了，是不是感觉超级简单呀 更详细使用示例请参考 `example` 工程及[官网文档](https://dynamictp.cn/guide/use/quick-start.html) --- ## 通知报警 - 触发报警阈值会推送相应报警消息（活性、容量、拒绝、任务等待超时、任务执行超时），且会高亮显示相应字段 <img src="resources/img/alarm.jpg" alt="告警" width="50%" /> - 配置变更会推送通知消息，且会高亮变更的字段 <img src="resources/img/notice.jpg" alt="变更通知" width="50%" /> 更多见官网文档，[通知报警](https://dynamictp.cn/guide/notice/alarm.html) --- ## 监控    目前框架提供了四种监控数据采集方式，通过 collectorTypes 属性配置监控指标采集类型，默认 Micrometer > 1. Logging：线程池指标数据会以 Json 格式输出到指定的日志文件里 > > 2. Internal_logging：线程池指标数据会以 Json 格式输出到项目日志文件里 > > 3. Micrometer：采用监控门面，通过引入相关 Micrometer 依赖采集到相应的存储平台里（如 Prometheus，InfluxDb...） > > 4. Endpoint：暴露 Endpoint 端点，可以通过 http 方式实时获取指标数据 更多见官网文档，[监控](https://dynamictp.cn/guide/monitor/collect_types.html) --- ## Star History [](https://star-history.com/#dromara/dynamic-tp&Date) --- ## 知识星球  --- ## 联系我 看到这儿，**请给项目一个 star**，你的支持是我们前进的动力！ 使用过程中有任何问题，或者对项目有什么想法或者建议，可以加入社群，跟 1000+ 群友一起交流讨论。 微信群已满 200 人，可以关注微信公众号，加我个人微信拉群（备注：dynamic-tp）。  为了项目更好的发展，请在此进行登记，[使用登记](https://dynamictp.cn/guide/other/users.html) --- ## 友情链接 - [HertzBeat](https://github.com/dromara/hertzbeat) : 易用友好的实时监控告警系统，无需Agent，强大自定义监控能力. --- ## 特别赞助 **JNPF低代码开发平台** <a href="https://www.jnpfsoft.com/?from=dynamic-tp"><img src="/resources/img/jnpfsoft.png"></a> --- ## 鸣谢 感谢 JetBrains 对开源项目的支持 <a href="https://jb.gg/OpenSourceSupport"> <img src="https://user-images.githubusercontent.com/8643542/160519107-199319dc-e1cf-4079-94b7-01b6b8d23aa6.png" align="left" height="150" width="150" alt="JetBrains"> </a>

🔥🔥🔥轻量级动态线程池，内置监控告警功能，集成三方中间件线程池管理，基于主流配置中心（已支持Nacos、Apollo，Zookeeper、Consul、Etcd，可通过SPI自定义实现）。Lightweight dynamic threadpool, with monitoring and alarming functions, base on popular config centers (already support Nacos、Apollo、Zookeeper、Consul, can be customized through SPI).

java,dynamic-threadpool,spring,nacos,apollo,micrometer,consul,springcloud,threadpool,threadpoolexecutor

warp-tech/warpgate

<br/> <p align="center"> <img src="warpgate-web/public/assets/logo.svg" width="100" /> </p> <br/> <p align="center"> <a href="https://github.com/warp-tech/warpgate/releases/latest"><img alt="GitHub All Releases" src="https://img.shields.io/github/downloads/warp-tech/warpgate/total.svg?label=DOWNLOADS&logo=github&style=for-the-badge"></a> &nbsp; <a href="https://nightly.link/warp-tech/warpgate/workflows/build/main"><img src="https://shields.io/badge/-Nightly%20Builds-orange?logo=hackthebox&logoColor=fff&style=for-the-badge"/></a> &nbsp; <a href="https://twitter.com/eugeeeeny"><img alt="Twitter" src="https://shields.io/badge/Subscribe-News-blue?logo=twitter&style=for-the-badge&color=blue"></a> </p> <p align="center"> <a href="https://ko-fi.com/J3J8KWTF"> <img src="https://cdn.ko-fi.com/cdn/kofi3.png?v=2" width="150"> </a> </p> --- Warpgate is a smart SSH, HTTPS and MySQL bastion host for Linux that doesn't need special client apps. * Set it up in your DMZ, add user accounts and easily assign them to specific hosts and URLs within the network. * Warpgate will record every session for you to view (live) and replay later through a built-in admin web UI. * Not a jump host - forwards your connections straight to the target instead. * Native 2FA and SSO support (TOTP & OpenID Connect) * Single binary with no dependencies. * Written in 100% safe Rust.  ## Getting started & downloads * See the [Getting started](https://github.com/warp-tech/warpgate/wiki/Getting-started) wiki page (or [Getting started on Docker](https://github.com/warp-tech/warpgate/wiki/Getting-started-on-Docker)). * [Release / beta binaries](https://github.com/warp-tech/warpgate/releases) * [Nightly builds](https://nightly.link/warp-tech/warpgate/workflows/build/main) <center> <img width="783" alt="image" src="https://user-images.githubusercontent.com/161476/162640762-a91a2816-48c0-44d9-8b03-5b1e2cb42d51.png"> </center> <table> <tr> <td> <img width="500" alt="image" src="https://user-images.githubusercontent.com/161476/177408495-80268a91-1a21-43bf-b171-2a563a322f5f.png"> </td> <td> <img width="500" alt="image" src="https://user-images.githubusercontent.com/161476/177410749-cf029df7-223e-4c9c-827a-bb96dbe0a7c8.png"> </td> </tr> </table> ## Project Status The project is currently in **alpha** stage and is gathering community feedback. See the [official roadmap](https://github.com/orgs/warp-tech/projects/1/views/2) for the upcoming features. In particular, we're working on: * Requesting admin approvals for sessions * Support for tunneling PostgreSQL connections, * and much more. ## How it works Warpgate is a service that you deploy on the bastion/DMZ host, which will accept SSH, HTTPS and MySQL connections and provide an (optional) web admin UI. Run `warpgate setup` to interactively generate a config file, including port bindings. See [Getting started](https://github.com/warp-tech/warpgate/wiki/Getting-started) for details. It receives connections with specifically formatted credentials, authenticates the user locally, connects to the target itself, and then connects both parties together while (optionally) recording the session. When connecting through HTTPS, Warpgate presents a selection of available targets, and will then proxy all traffic in a session to the selected target. You can switch between targets at any time. You manage the target and user lists and assign them to each other through the admin UI, and the session history is stored in an SQLite database (default: in `/var/lib/warpgate`). You can also use the admin web interface to view the live session list, review session recordings, logs and more. ## Contributing / building from source * You'll need Rust, NodeJS and Yarn * Clone the repo * [Just](https://github.com/casey/just) is used to run tasks - install it: `cargo install just` * Install the admin UI deps: `just yarn` * Build the frontend: `just yarn build` * Build Warpgate: `cargo build` (optionally `--release`) The binary is in `target/{debug|release}`. ### Tech stack * Rust 🦀 * HTTP: `poem-web` * Database: SQLite via `sea-orm` + `sqlx` * SSH: `russh` * Typescript * Svelte * Bootstrap ### Backend API * Warpgate admin and user facing APIs use autogenerated OpenAPI schemas and SDKs. To update the SDKs after changing the query/response structures, run `just openapi-all`. ## Contributors ✨ Thanks goes to these wonderful people ([emoji key](https://allcontributors.org/docs/en/emoji-key)): <!-- ALL-CONTRIBUTORS-LIST:START - Do not remove or modify this section --> <!-- prettier-ignore-start --> <!-- markdownlint-disable --> <table> <tbody> <tr> <td align="center" valign="top" width="14.28%"><a href="https://github.com/Eugeny"><img src="https://avatars.githubusercontent.com/u/161476?v=4?s=100" width="100px;" alt="Eugeny"/><br />_{<b>Eugeny</b>}</a><br /><a href="https://github.com/Eugeny/warpgate/commits?author=Eugeny" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://the-empire.systems/"><img src="https://avatars.githubusercontent.com/u/18178614?v=4?s=100" width="100px;" alt="Spencer Heywood"/><br />_{<b>Spencer Heywood</b>}</a><br /><a href="https://github.com/Eugeny/warpgate/commits?author=heywoodlh" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/apiening"><img src="https://avatars.githubusercontent.com/u/2064875?v=4?s=100" width="100px;" alt="Andreas Piening"/><br />_{<b>Andreas Piening</b>}</a><br /><a href="https://github.com/Eugeny/warpgate/commits?author=apiening" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/Gurkengewuerz"><img src="https://avatars.githubusercontent.com/u/10966337?v=4?s=100" width="100px;" alt="Niklas"/><br />_{<b>Niklas</b>}</a><br /><a href="https://github.com/Eugeny/warpgate/commits?author=Gurkengewuerz" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/notnooblord"><img src="https://avatars.githubusercontent.com/u/11678665?v=4?s=100" width="100px;" alt="Nooblord"/><br />_{<b>Nooblord</b>}</a><br /><a href="https://github.com/Eugeny/warpgate/commits?author=notnooblord" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://shea.nz/"><img src="https://avatars.githubusercontent.com/u/51303984?v=4?s=100" width="100px;" alt="Shea Smith"/><br />_{<b>Shea Smith</b>}</a><br /><a href="https://github.com/Eugeny/warpgate/commits?author=SheaSmith" title="Code">💻</a></td> </tr> </tbody> </table> <!-- markdownlint-restore --> <!-- prettier-ignore-end --> <!-- ALL-CONTRIBUTORS-LIST:END --> This project follows the [all-contributors](https://github.com/all-contributors/all-contributors) specification. Contributions of any kind welcome!

Smart SSH, HTTPS and MySQL bastion that requires no additional client-side software

bastion,bastion-host,infrastructure,ssh,ssh-server,proxy,rust,https,https-proxy,mysql

ydb-platform/ydb

<img width="64" src="ydb/docs/_assets/logo.svg" /><br/> [](https://github.com/ydb-platform/ydb/blob/main/LICENSE) [](https://github.com/ydb-platform/ydb/releases) [](https://discord.gg/R5MvZTESWc) ## YDB [Website](https://ydb.tech) | [Documentation](https://ydb.tech/docs/en/) | [Official Repository](https://github.com/ydb-platform/ydb) | [Blog](https://blog-redirect.ydb.tech) | [YouTube](https://www.youtube.com/c/YDBPlatform) | [Discord](https://discord.gg/R5MvZTESWc) | [Telegram](https://t.me/ydb_en) | [LinkedIn](https://www.linkedin.com/company/ydb-platform) | [X](https://x.com/YDBPlatform) YDB is an open source Distributed SQL Database that combines high availability and scalability with strict consistency and ACID transactions. [](https://youtu.be/bxZRUtMAlFI) ## Main YDB Advantages YDB was designed from scratch to respond to the growing demand for scalable interactive web services. Scalability, strict consistency, and effective cross-row transactions were a must for such an OLTP-like workload. YDB was built by people with strong backgrounds in databases and distributed systems who have experience developing a NoSQL database and the MapReduce system for one of the largest search engines in the world. Basic YDB features: - Both row-oriented and column-oriented [tables](https://ydb.tech/docs/en/concepts/datamodel/table) for transactional and analytical workloads. Also, [persistent queues (topics)](https://ydb.tech/docs/en/concepts/topic) for moving data around. - Fault-tolerant configuration that survives disk, node, rack, or even datacenter outages. - Automatic disaster recovery with minimum latency disruptions for applications. - Independent horizontal scalability of storage and compute layers. - ACID transactions across multiple nodes and tables with strict consistency. - Rich [SQL dialect (YQL)](https://ydb.tech/docs/en/yql/reference/) for data manipulation and schema definition. - [PostgreSQL-compatible mode](https://ydb.tech/docs/en/postgresql/intro) for table operations and [Kafka-compatible mode](https://ydb.tech/docs/en/reference/kafka-api/) for topics. - YDB clusters can be deployed with [Ansible](https://ydb.tech/docs/en/devops/ansible/), [Kubernetes](https://ydb.tech/docs/en/devops/kubernetes/), or [manually](https://ydb.tech/docs/en/devops/manual/). ### Fault-tolerant Configurations YDB can be deployed in three availability zones (datacenters). A cluster remains available for both reads and writes during a complete outage of a single zone. Availability zones and regions are covered in more detail [in documentation](https://ydb.tech/en/docs/concepts/databases#regions-az). ### Horizontal Scalability Unlike traditional relational databases, YDB [scales out](https://en.wikipedia.org/wiki/Scalability#Horizontal_or_scale_out), providing developers with the capability to simply extend clusters with computation or storage resources to handle increasing load. YDB has disaggregated storage and compute layers, which allow you to scale storage and compute resources independently. Current production installations have over 10000 nodes, store petabytes of data, and handle millions of distributed transactions per second. ### Automatic Disaster Recovery YDB's built-in automatic recovery support allows it to seamlessly survive hardware failures. After unpredictable disk, node, rack, or even datacenter failure, YDB remains fully available for reads and writes and automatically restores required data redundancy. ### Multitenant and Serverless Database YDB supports multitenant and serverless setups. A user can run a YDB cluster and create several databases that share one pool of storage and have different compute nodes. Alternatively, a user can run several serverless databases that share one pool of compute resources to utilize them effectively. ## Supported Platforms ### Minimal system requirements YDB runs on x86 64-bit platforms with at least 8 GB of RAM. ### Operating Systems In most production environments, YDB runs on 64-bit x86 machines working under Ubuntu Linux. For development purposes, it is regularly tested that YDB can be compiled and run under the latest versions of MacOS and Microsoft Windows. ## Getting Started If you want to experiment with YDB, start with the [Quick Start guide](https://ydb.tech/docs/en/quickstart). It will yield a single-node cluster suitable for functional testing, app development, and similar tasks. Suppose you want to jump into more serious scenarios like testing YDB fault tolerance, running performance benchmarks, or even running production or preproduction workloads. In that case, you'll need a full-fledged multi-node YDB cluster that can be deployed with either [Ansible](https://ydb.tech/docs/en/devops/ansible/initial-deployment) for bare metal or virtual machines or [Kubernetes](https://ydb.tech/docs/en/devops/kubernetes/initial-deployment) for containers. ## How to Build from Source Code Instructions on how to build YDB server (ydbd) and client (ydb) binaries are provided in [BUILD.md](BUILD.md). Also, see documentation on [Ya Make build system](https://ydb.tech/docs/en/contributor/build-ya). ## How to Contribute We are glad to welcome new contributors! The [contributor's guide](CONTRIBUTING.md) provides more details on how to get started as a contributor. There's also a separate section of [YDB documentation for contributors](https://ydb.tech/docs/en/contributor/), mostly with more technical content. ## Success Stories Visit YDB [website](https://ydb.tech/) for the latest success stories and user scenarios.

YDB is an open source Distributed SQL Database that combines high availability and scalability with strong consistency and ACID transactions

database,distributed,sql,dbms,cloud-native,cpp,distributed-database,distributed-sql,distributed-sql-database

hemansnation/God-Level-AI

# god level AI A collection of scientific methods, processes, algorithms, and systems to build stories & models. An in-depth learning resource for humans. Build Your Strong Machine Learning Gen AI MLOps Portfolio/Personal Brand🚀 <img src="https://github.com/hemansnation/Data-Science-ML-Full-Stack/blob/master/images/components.png" height='300px' width='300px' /> ### The‌ ‌Roadmap‌ Duration:‌ ‌(11 ‌Months)‌ ‌and many more hours for practice and project building. ### Phase 1 1. [Python‌ ‌Programming‌ ‌and‌ ‌Logic‌ ‌Building‌](#1--python-programming-and-logic-building) 2. [Data‌ ‌Structure‌ ‌&‌ ‌Algorithms‌](#2--data-structure--algorithms) 3. [Git & GitHub](#15--git--github) ### Phase 2 It contains 7 Modules 1. [Mathematics of Machine Learning‌](#3) 2. [Machine‌ ‌Learning‌ Concepts](#4--statistics) 3. [Data Processing X Machine Learning](#5--machine-learning) 4. [Models]() - [Natural‌ ‌Language‌ ‌Processing‌](#7--natural-language-processing) - [Computer‌ ‌Vision‌‌](#8--computer-vision) - [GenerativeAI](#6--mlops) 5. [ML Operations](#6--mlops) 6. [ML System Design](#6--mlops) 7. [ML Interview and Projects](#6--mlops) ### Phase 3 13. [Data‌ ‌Visualization‌ ‌with‌ ‌Tableau‌](#9--data-visualization-with-tableau) 14. [Structure‌d ‌Query‌ ‌Language‌ ‌(SQL)‌](#10--structured-query-language-sql) 15. [Data Engineering](#11--data-engineering) 16. [Data System Design](#12--data-system-design) 17. [Five‌ ‌Major‌ Capstone ‌Projects‌](#13--five-major-projects-and-git) 18. [Interview Preparations](#14--interview-preperation) 20. [Personal Branding and portfolio](#16--personal-profile--portfolio) ### [Resources](#resources) - [Dataset Collection]() ### Technology‌ ‌Stack‌ - Python‌ - Data‌ ‌Structures‌ - NumPy‌ - Pandas‌ - Matplotlib‌ - Seaborn‌ - Scikit-Learn‌ - Statsmodels‌ - Natural‌ ‌Language‌ ‌Toolkit‌ ‌(‌ ‌NLTK‌ ‌)‌ - PyTorch‌ - OpenCV‌ - Tableau‌ - Structure‌ ‌Query‌ ‌Language‌ ‌(‌ ‌SQL‌ ‌)‌ - PySpark‌ - Azure‌ ‌Fundamentals‌ - Azure‌ ‌Data‌ ‌Factory‌ - Databricks‌ - 5‌ ‌Major‌ ‌Projects‌ - Git‌ ‌and‌ ‌GitHub‌ ‌ # 1 | Python Programming and Logic Building I will prefer Python Programming Language. Python is the best for starting your programming journey. Here is the roadmap of python for logic building. - Python basics, Variables, Operators, Conditional Statements - List and Strings - While Loop, Nested Loops, Loop Else - For Loop, Break, and Continue statements - Functions, Return Statement, Recursion - Dictionary, Tuple, Set - File Handling, Exception Handling - Object-Oriented Programming - Modules and Packages <a href="https://github.com/hemansnation/Python-Roadmap-2022">In-Depth Roadmap of Python</a> # 2 | Data Structure & Algorithms #### Data Structures - Stack - Queue - Linked List - Tree - Graph #### Algorithms - List - Searching - Swapping and Sorting - Recursion - Hashing - Strings Dynamic Programming Fundamentals # 3 | Git and GitHub #### Part 1 - [YouTube Tutorial Part 1](https://www.youtube.com/watch?v=Q_ps0aqNvHc) - Understanding Git - Commands and How to commit your first code? - How to use GitHub? - How to work with a team? - How to make your first open-source contribution? #### Part 2 - [YouTube Tutorial Part 2](https://www.youtube.com/watch?v=IusjTe7dVXQ) - How to create your stunning GitHub profile? - How to build your own viral repository? - Building a personal landing page for your Portfolio for FREE - How to grow followers on GitHub? - How to work with a team? - issues, milestones, and projects [Git Notes and Resources on Notion](https://god-level-python.notion.site/Git-GitHub-Course-Make-Recruiters-reach-You-Build-your-stunning-profile-First-open-source-cont-439867a44e724488a590436a164f8dff?pvs=4) Python supports n-dimensional arrays with Numpy. For data in 2-dimensions, Pandas is the best library for analysis. You can use other tools but tools have drag-and-drop features and have limitations. Pandas can be customized as per the need as we can code depending upon the real-life problem. ### Numpy - Vectors, Matrix - Operations on Matrix - Mean, Variance, and Standard Deviation - Reshaping Arrays - Transpose and Determinant of Matrix - Diagonal Operations, Trace - Add, Subtract, Multiply, Dot, and Cross Product. ### Pandas - Series and DataFrames - Slicing, Rows, and Columns - Operations on DataFrame - Different ways to create DataFrame - Read, Write Operations with CSV files - Handling Missing values, replace values, and Regular Expression - GroupBy and Concatenation ### Matplotlib - Graph Basics - Format Strings in Plots - Label Parameters, Legend - Bar Chart, Pie Chart, Histogram, Scatter Plot # 4 | Statistics ### Descriptive Statistics - Measure of Frequency and Central Tendency - Measure of Dispersion - Probability Distribution - Gaussian Normal Distribution - Skewness and Kurtosis - Regression Analysis - Continuous and Discrete Functions - Goodness of Fit - Normality Test - ANOVA - Homoscedasticity - Linear and Non-Linear Relationship with Regression ### Inferential Statistics - t-Test - z-Test - Hypothesis Testing - Type I and Type II errors - t-Test and its types - One way ANOVA - Two way ANOVA - Chi-Square Test - Implementation of continuous and categorical data # 5 | Machine Learning The best way to master machine learning algorithms is to work with the Scikit-Learn framework. Scikit-Learn contains predefined algorithms and you can work with them just by generating the object of the class. These are the algorithm you must know including the types of Supervised and Unsupervised Machine Learning: - Linear Regression - Logistic Regression - Decision Tree - Gradient Descent - Random Forest - Ridge and Lasso Regression - Naive Bayes - Support Vector Machine - KMeans Clustering ### Other Concepts and Topics for ML - Measuring Accuracy - Bias-Variance Trade-off - Applying Regularization - Elastic Net Regression - Predictive Analytics - Exploratory Data Analysis # 6 | MLOps You can master any one of the cloud services provider from AWS, GCP and Azure. You can switch easily once you understand one of them. We will focus on AWS - Amazon Web Services first - Deploy ML models using Flask - Amazon Lex - Natural Language Understanding - AWS Polly - Voice Analysis - Amazon Transcribe - Speech to Text - Amazon Textract - Extract Text - Amazon Rekognition - Image Applications - Amazon SageMaker - Building and deploying models - Working with Deep Learning on AWS # 7 | Natural Language Processing If you are interested in working with Text, you should do some of the work an NLP Engineer do and understand the working of Language models. - Sentiment analysis - POS Tagging, Parsing, - Text preprocessing - Stemming and Lemmatization - Sentiment classification using Naive Bayes - TF-IDF, N-gram, - Machine Translation, BLEU Score - Text Generation, Summarization, ROUGE Score - Language Modeling, Perplexity - Building a text classifier - Identifying the gender # 8 | Computer Vision To work on image and video analytics we can master computer vision. To work on computer vision we have to understand images. - PyTorch Tensors - Understanding Pretrained models like AlexNet, ImageNet, ResNet. - Neural Networks - Building a perceptron - Building a single layer neural network - Building a deep neural network - Recurrent neural network for sequential data analysis ### Convolutional Neural Networks - Understanding the ConvNet topology - Convolution layers - Pooling layers - Image Content Analysis - Operating on images using OpenCV-Python - Detecting edges - Histogram equalization - Detecting corners - Detecting SIFT feature points # 9 | Data Visualization with Tableau How to use it Visual Perception - What is it, How it works, Why Tableau - Connecting to Data - Building charts - Calculations - Dashboards - Sharing our work - Advanced Charts, Calculated Fields, Calculated Aggregations - Conditional Calculation, Parameterized Calculation # 10 | Structured Query Language (SQL) - Fundamental to SQL syntax and Installation - Creating Tables, Modifiers - Inserting and Retrieving Data, SELECT INSERT UPDATE DELETE - Aggregating Data using Functions, Filtering and RegEX - Subqueries, retrieve data based on conditions, grouping of Data. - Practice Questions - JOINs - Advanced SQL concepts such as transactions, views, stored procedures, and functions. - Database Design principles, normalization, and ER diagrams. - Practice, Practice, Practice: Practice writing SQL queries on real-world datasets, and work on projects to apply your knowledge. # 11 | Data Engineering ### BigData - What is BigData? - How is BigData applied within Business? ### PySpark - Resilient Distributed Datasets - Schema - Lambda Expressions - Transformations - Actions ### Data Modeling - Duplicate Data - Descriptive Analysis on Data - Visualizations - ML lib - ML Packages - Pipelines ### Streaming - Packaging Spark Applications # 12 | Data System Design ### What is system design? - IP and OSI Model - Domain Name System (DNS) - Load Balancing - Clustering - Caching - Availability, Scalability, Storage ### Databases and DBMS - SQL databases - NoSQL databases - SQL vs NoSQL databases - Database Replication - Indexes - Normalization and Denormalization - CAP theorem ### System Design Interview - URL Shortener - Whatsapp, Twitter, Netflix, Uber # 13 | Five Major Projects and Git We follow project-based learning and we will work on all the projects in parallel. # 14 | Interview Preperation # 16 | Personal Profile & Portfolio # Resources ### Datasets 1️⃣ [Awesome Public Datasets](https://github.com/awesomedata/awesome-public-datasets) This list of a topic-centric public data sources in high quality. 2️⃣[NLP Datasets](https://github.com/niderhoff/nlp-datasets) Alphabetical list of free/public domain datasets with text data for use in NLP. 3️⃣[Awesome Dataset Tools](https://github.com/jsbroks/awesome-dataset-tools) A curated list of awesome dataset tools. 4️⃣[Awesome time series database](https://github.com/xephonhq/awesome-time-series-database) A curated list of time series databases. 5️⃣[Awesome-Cybersecurity-Datasets](https://github.com/shramos/Awesome-Cybersecurity-Datasets) A curated list of amazingly awesome Cybersecurity datasets. 6️⃣[Awesome Robotics Datasets](https://github.com/mint-lab/awesome-robotics-datasets) Robotics Dataset Collections. # Research Starting Point ### Machine Learning 1. [Introduction to Statistical Learning](https://www.ime.unicamp.br/~dias/Intoduction%20to%20Statistical%20Learning.pdf) 2. ### Deep Learning ### Reinforcement Learning # Projects [Here is the list of project ideas](https://github.com/hemansnation/God-Level-Data-Science-ML-Full-Stack/tree/master/projects) # Data Science ML Full Stack -> [Notion Template](https://god-level-python.notion.site/Data-Science-ML-Full-Stack-Roadmap-05e6c16389c845d1a438ed4cff2b9952) ### Join the WhatsApp Community Group https://chat.whatsapp.com/BSUPbYhzzM1BcJplcTTIxb # Socials ### Join Telegram for Data Science ML AI Resources: https://t.me/+sREuRiFssMo4YWJl ### Connect with me on these platforms: LinkedIn: https://www.linkedin.com/in/hemansnation/ YouTube: https://www.youtube.com/@Himanshu-Ramchandani Twitter: https://twitter.com/hemansnation GitHub: https://github.com/hemansnation Instagram: https://www.instagram.com/masterdexter.ai/ ### AI Jobs LinkedIn Group: https://www.linkedin.com/groups/12540639/ ### Medium Blog: https://medium.com/@hemansnation ### Notes on Data, Product, and AI - Newsletter: https://www.linkedin.com/build-relation/newsletter-follow?entityUrn=7014799989251956736 ### Any Query? Email Me Here: connect@himanshuramchandani.co

A collection of scientific methods, processes, algorithms, and systems to build stories & models.

python,datastructures,numpy,pandas,matplotlib,scikit-learn,machine-learning,deep-learning,pytorch,data-science

BewlyBewly/BewlyBewly

# BewlyBewly English | [官话 - 简体中文](README-cmn_CN.md) | [官話 - 正體中文](README-cmn_TW.md) | [廣東話](README-jyut.md) <p align="center" style="margin-bottom: 0px !important;"> <img width="100" alt="BewlyBewly icon" src="https://user-images.githubusercontent.com/33394391/160250512-410b71fc-7f25-4caf-b850-429227ff082a.png"><br/> </p> <h1 align="center" style="margin-top: 0px;">BewlyBewly</h1> <p align="center">Just make a few small changes to your Bilibili homepage.</p> <!--   --> ## 👋 Introduction BewlyBewly is a browser extension for BiliBili that aims to enhance the user experience by redesigning the BiliBili UI. The design is inspired by YouTube, Vision OS, and iOS, resulting in a more visually appealing and user-friendly interface. This project uses the [vitesse-webext](https://github.com/antfu/vitesse-webext) template for development. Without this template, it may not be possible to develop this project. ## 🔨 Build (Firefox) Please make sure you have [Node.js](https://nodejs.org/) and [pnpm](https://pnpm.io/) installed locally, and it is recommended to use [Visual Studio Code](https://code.visualstudio.com/) for development. 1. To build the extension, run ```bash # Install dependencies pnpm install pnpm build-firefox ``` 2. Load the generated `extension-firefox/` folder in the browser, The extension will then take effect on [www.bilibili.com](https://www.bilibili.com). [Chrome & Edge](/docs/CONTRIBUTING.md#building-chrome-or-edge) ## ⬇️ Installation ### Online Installation > [!Caution] > Even in the Edge browser, we strongly recommend you install it in the Chrome web store. > In terms of review speed, the Chrome web store is faster than Edge Add-ons. > > Additionally, the Chrome Web Store version of BewlyBewly will address and fix critical bugs more quickly. - Chrome: <https://chromewebstore.google.com/detail/bewlybewly/bbbiejemhfihiooipfcjmjmbfdmobobp> - Edge: <https://chromewebstore.google.com/detail/bewlybewly/bbbiejemhfihiooipfcjmjmbfdmobobp> - Firefox: <https://addons.mozilla.org/en-US/firefox/addon/bewlybewly/> #### To Firefox users > [!WARNING] > When using the Firefox browser, remember to enable all permissions shown in the picture below for normal use of BewlyBewly <br/> <img width="655" alt="enable all bewlybewly permissions on firefox" src="https://github.com/hakadao/BewlyBewly/assets/33394391/9566aed8-040a-4435-a2ec-c61117f8e429"> ### Local Installation [CI](https://github.com/hakadao/BewlyBewly/actions): Automatically build with the latest code [Releases](https://github.com/hakadao/BewlyBewly/releases): Stable version #### Edge & Chrome (RECOMMENDED) > Ensure you installed [extension.zip](https://github.com/hakadao/BewlyBewly/releases) . Opening the `edge://extensions` page in the Edge or `chrome://extensions` page in Chrome, simply drag and drop the downloaded `extension.zip` file into the browser to complete the installation. <details> <summary> Another installation method for Edge & Chrome </summary> #### Edge > Ensure you installed [extension.zip](https://github.com/hakadao/BewlyBewly/releases) and decompress this file. 1. Type in `edge://extensions/` in the address bar and press Enter 2. Turn on `Developer mode` then press `Load Unpacked` <br/> <img width="655" alt="image" src="https://user-images.githubusercontent.com/33394391/232246901-e3544c16-bde2-480d-b770-ca5242793963.png"> 3. Load the decompressed extension folder in your browser #### Chrome > > Ensure you installed [extension.zip](https://github.com/hakadao/BewlyBewly/releases) and decompress this file. 1. Type in `chrome://extensions/` in the address bar and press Enter 2. Turn on `Developer mode` then press `Load Unpacked` <br/> <img width="655" alt="Snipaste_2022-03-27_18-17-04" src="https://user-images.githubusercontent.com/33394391/160276882-13da0484-92c1-47dd-add8-7655c5c2bf1c.png"> 3. Load the decompressed extension folder in your browser </details> ## 🤝 Contribution See [CONTRIBUTION.md](docs/CONTRIBUTING.md) ### Contributors  ## ❤️ Credits - [vitesse-webext](https://github.com/antfu/vitesse-webext) - The template used for this project - [UserScripts/bilibiliHome](https://github.com/indefined/UserScripts/tree/master/bilibiliHome), [bilibili-app-recommend](https://github.com/magicdawn/bilibili-app-recommend) - Reference source for obtaining the access key - [Bilibili-Evolved](https://github.com/the1812/Bilibili-Evolved) - Partial implementation of functionalities - [bilibili-API-collect](https://github.com/SocialSisterYi/bilibili-API-collect)

Improve your Bilibili homepage by redesigning it, adding more features, and personalizing it to match your preferences. (English | 简体中文 | 正體中文 | 廣東話)

bilibili,chrome-extension,browser-extension,dark-mode,dark-theme

keploy/keploy

<p align="center"> <img align="center" src="https://docs.keploy.io/img/keploy-logo-dark.svg?s=200&v=4" height="40%" width="40%" alt="keploy logo"/> </p> <h3 align="center"> <b> ⚡️ API tests faster than unit tests, from user traffic ⚡️ </b> </h3 > <p align="center"> 🌟 The must-have tool for developers in the AI-Gen era 🌟 </p> --- <h4 align="center"> <a href="https://twitter.com/Keploy_io"> <img src="https://img.shields.io/badge/follow-%40keployio-1DA1F2?logo=twitter&style=social" alt="Keploy Twitter" /> </a> <a href="https://github.com/Keploy/Keploy/issues"> <img src="https://img.shields.io/github/stars/keploy/keploy?color=%23EAC54F&logo=github&label=Help us reach 4k stars! Now at:" alt="Help us reach 4k stars!" /> </a> <a href="https://landscape.cncf.io/?item=app-definition-and-development--continuous-integration-delivery--keploy"> <img src="https://img.shields.io/badge/CNCF%20Landscape-5699C6?logo=cncf&style=social" alt="Keploy CNCF Landscape" /> </a> [](https://join.slack.com/t/keploy/shared_invite/zt-2dno1yetd-Ec3el~tTwHYIHgGI0jPe7A) [](https://www.linkedin.com/company/keploy/) [](https://www.youtube.com/channel/UC6OTg7F4o0WkmNtSoob34lg) [](https://twitter.com/Keployio) </h4> [Keploy](https://keploy.io) is **developer-centric** API testing tool that creates **tests along with built-in-mocks**, faster than unit tests. Keploy not only records API calls, but also records database calls and replays them during testing, making it **easy to use, powerful, and extensible**. <img src="https://raw.githubusercontent.com/keploy/docs/main/static/gif/record-tc.gif" width="60%" alt="Convert API calls to test cases"/> > 🐰 **Fun fact:** Keploy uses itself for testing! Check out our swanky coverage badge: [](https://coveralls.io/github/keploy/keploy?branch=main&kill_cache=1) &nbsp; ## 🚨 Here for [Unit Test Generator](README-UnitGen.md) (ut-gen)? Keploy's new launched world's first unit test generator(ut-gen) implementation of [Meta LLM research paper](https://arxiv.org/pdf/2402.09171), it understands code semantics and generates meaningful unit tests, aiming to: - **Automate unit test generation (UTG)**: Quickly generate comprehensive unit tests and reduce the redundant manual effort. - **Improve edge cases**: Extend and improve the scope of tests to cover more complex scenarios that are often missed manually. - **Boost test coverage**: As codebase grows, ensuring exhaustive coverage should become feasible. ### 📜 Follow [Unit Test Generator README](README-UnitGen.md)! ✅ ## 📘 Documentation! Become a Keploy pro with **[Keploy Documentation](https://keploy.io/docs/)**. <img src="https://raw.githubusercontent.com/keploy/docs/main/static/gif/record-replay.gif" width="100%" alt="Record Replay Testing"/> # 🚀 Quick Installation (API test generator) Integrate Keploy by installing the agent locally. No code-changes required. ```shell curl --silent -O -L https://keploy.io/install.sh && source install.sh ``` ## 🎬 Recording Testcases Start your app wit Keploy to convert API calls as Tests and Mocks/Stubs. ```zsh keploy record -c "CMD_TO_RUN_APP" ``` For example, if you're using a simple Python app the `CMD_TO_RUN_APP` would resemble to `python main.py`, for Golang `go run main.go`, for java `java -jar xyz.jar`, for node `npm start`.. ```zsh keploy record -c "python main.py" ``` ## 🧪 Running Tests Shut down the databases, redis, kafka or any other services your application uses. Keploy doesn't need those during test. ```zsh keploy test -c "CMD_TO_RUN_APP" --delay 10 ``` ## ✅ Test Coverage Integration To integrate with your unit-testing library and see combine test coverage, follow this [test-coverage guide](https://keploy.io/docs/server/sdk-installation/go/). > #### **If You Had Fun:** Please leave a 🌟 star on this repo! It's free, and you'll bring a smile. 😄 👏 ## 🤔 Questions? Reach out to us. We're here to help! [](https://join.slack.com/t/keploy/shared_invite/zt-2dno1yetd-Ec3el~tTwHYIHgGI0jPe7A) [](https://www.linkedin.com/company/keploy/) [](https://www.youtube.com/channel/UC6OTg7F4o0WkmNtSoob34lg) [](https://twitter.com/Keployio) ## 🌐 Language Support From Go's gopher 🐹 to Python's snake 🐍, we support:       ## 🫰 Keploy Adopters 🧡 So you and your organisation are using Keploy? That’s great. Please add yourselves to [**this list,**](https://github.com/orgs/keploy/discussions/1765) and we'll send you goodies! 💖 We are happy and proud to have you all as part of our community! 💖 ## 🎩 How's the Magic Happen? Keploy proxy captures and replays **ALL** (CRUD operations, including non-idempotent APIs) of your app's network interactions. Take a journey to **[How Keploy Works?](https://keploy.io/docs/keploy-explained/how-keploy-works/)** to discover the tricks behind the curtain! Here are Keploy's core features: 🛠 - ♻️ **Combined Test Coverage:** Merge your Keploy Tests with your fave testing libraries(JUnit, go-test, py-test, jest) to see a combined test coverage. - 🤖 **EBPF Instrumentation:** Keploy uses EBPF like a secret sauce to make integration code-less, language-agnostic, and oh-so-lightweight. - 🌐 **CI/CD Integration:** Run tests with mocks anywhere you like—locally on the CLI, in your CI pipeline (Jenkins, Github Actions..) , or even across a Kubernetes cluster. - 📽️ **Record-Replay Complex Flows:** Keploy can record and replay complex, distributed API flows as mocks and stubs. It's like having a time machine for your tests—saving you tons of time! - 🎭 **Multi-Purpose Mocks:** You can also use keploy Mocks, as server Tests! ## 👨🏻‍💻 Let's Build Together! 👩🏻‍💻 Whether you're a newbie coder or a wizard 🧙‍♀️, your perspective is golden. Take a peek at our: 📜 [Contribution Guidelines](https://github.com/keploy/keploy/blob/main/CONTRIBUTING.md) ❤️ [Code of Conduct](https://github.com/keploy/keploy/blob/main/CODE_OF_CONDUCT.md) ## 🐲 Current Limitations! - **Unit Testing:** While Keploy is designed to run alongside unit testing frameworks (Go test, JUnit..) and can add to the overall code coverage, it still generates integration tests. - **Production Lands**: Keploy is currently focused on generating tests for developers. These tests can be captured from any environment, but we have not tested it on high volume production environments. This would need robust deduplication to avoid too many redundant tests being captured. We do have ideas on building a robust deduplication system [#27](https://github.com/keploy/keploy/issues/27) ## ✨ Resources! 🤔 [FAQs](https://keploy.io/docs/keploy-explained/faq/) 🕵️‍️ [Why Keploy](https://keploy.io/docs/keploy-explained/why-keploy/) ⚙️ [Installation Guide](https://keploy.io/docs/application-development/) 📖 [Contribution Guide](https://keploy.io/docs/keploy-explained/contribution-guide/)

Test generation for Developers. Generate tests and stubs for your application that actually work!

testing,test-automation,golang,productivity,api,api-testing,unit-testing,unit-testing-framework,go,testing-tools

NVIDIA/warp

[](https://badge.fury.io/py/warp-lang)  [](https://pepy.tech/project/warp-lang) [](https://codecov.io/github/NVIDIA/warp)  [](https://discord.com/invite/nvidiaomniverse) # NVIDIA Warp Warp is a Python framework for writing high-performance simulation and graphics code. Warp takes regular Python functions and JIT compiles them to efficient kernel code that can run on the CPU or GPU. Warp is designed for spatial computing and comes with a rich set of primitives that make it easy to write programs for physics simulation, perception, robotics, and geometry processing. In addition, Warp kernels are differentiable and can be used as part of machine-learning pipelines with frameworks such as PyTorch and JAX. Please refer to the project [Documentation](https://nvidia.github.io/warp/) for API and language reference and [CHANGELOG.md](./CHANGELOG.md) for release history. <div align="center"> <img src="https://github.com/NVIDIA/warp/raw/main/docs/img/header.jpg"> <p><i>A selection of physical simulations computed with Warp</i></p> </div> ## Installing Python version 3.9 or newer is recommended. Warp can run on x86-64 and ARMv8 CPUs on Windows, Linux, and macOS. GPU support requires a CUDA-capable NVIDIA GPU and driver (minimum GeForce GTX 9xx). The easiest way to install Warp is from [PyPI](https://pypi.org/project/warp-lang/): pip install warp-lang You can also use `pip install warp-lang[extras]` to install additional dependencies for running examples and USD-related features. The binaries hosted on PyPI are currently built with the CUDA 11.8 runtime. We provide binaries built with the CUDA 12.5 runtime on the [GitHub Releases](https://github.com/NVIDIA/warp/releases) page. Copy the URL of the appropriate wheel file (`warp-lang-{ver}+cu12-py3-none-{platform}.whl`) and pass it to the `pip install` command, e.g. pip install https://github.com/NVIDIA/warp/releases/download/v1.2.0/warp_lang-1.2.0+cu12-py3-none-manylinux2014_x86_64.whl The `--force-reinstall` option may need to be used to overwrite a previous installation. ## Getting Started An example first program that computes the lengths of random 3D vectors is given below: ```python import warp as wp import numpy as np num_points = 1024 @wp.kernel def length(points: wp.array(dtype=wp.vec3), lengths: wp.array(dtype=float)): # thread index tid = wp.tid() # compute distance of each point from origin lengths[tid] = wp.length(points[tid]) # allocate an array of 3d points points = wp.array(np.random.rand(num_points, 3), dtype=wp.vec3) lengths = wp.zeros(num_points, dtype=float) # launch kernel wp.launch(kernel=length, dim=len(points), inputs=[points, lengths]) print(lengths) ``` ## Running Examples The [warp/examples](./warp/examples/) directory contains a number of scripts categorized under different subdirectories that show how to implement different simulation methods using the Warp API. Most examples will generate USD files containing time-sampled animations (stored in the current working directory). Before running examples, users should ensure that the ``usd-core``, ``matplotlib``, and ``pyglet`` packages are installed using: pip install usd-core matplotlib pyglet Examples can be run from the command-line as follows: python -m warp.examples.<example_subdir>.<example> To browse the example source code, you can open the directory where the files are located like this: python -m warp.examples.browse Most examples can be run on either the CPU or a CUDA-capable device, but a handful require a CUDA-capable device. These are marked at the top of the example script. USD files can be viewed or rendered inside [NVIDIA Omniverse](https://developer.nvidia.com/omniverse), Pixar's UsdView, and Blender. Note that Preview in macOS is not recommended as it has limited support for time-sampled animations. Built-in unit tests can be run from the command-line as follows: python -m warp.tests ### examples/core <table> <tbody> <tr> <td><a href="https://github.com/NVIDIA/warp/tree/main/warp/examples/core/example_dem.py"><img src="https://github.com/NVIDIA/warp/raw/main/docs/img/examples/core_dem.png"></a></td> <td><a href="https://github.com/NVIDIA/warp/tree/main/warp/examples/core/example_fluid.py"><img src="https://github.com/NVIDIA/warp/raw/main/docs/img/examples/core_fluid.png"></a></td> <td><a href="https://github.com/NVIDIA/warp/tree/main/warp/examples/core/example_graph_capture.py"><img src="https://github.com/NVIDIA/warp/raw/main/docs/img/examples/core_graph_capture.png"></a></td> <td><a href="https://github.com/NVIDIA/warp/tree/main/warp/examples/core/example_marching_cubes.py"><img src="https://github.com/NVIDIA/warp/raw/main/docs/img/examples/core_marching_cubes.png"></a></td> </tr> <tr> <td align="center">dem</td> <td align="center">fluid</td> <td align="center">graph capture</td> <td align="center">marching cubes</td> </tr> <tr> <td><a href="https://github.com/NVIDIA/warp/tree/main/warp/examples/core/example_mesh.py"><img src="https://github.com/NVIDIA/warp/raw/main/docs/img/examples/core_mesh.png"></a></td> <td><a href="https://github.com/NVIDIA/warp/tree/main/warp/examples/core/example_nvdb.py"><img src="https://github.com/NVIDIA/warp/raw/main/docs/img/examples/core_nvdb.png"></a></td> <td><a href="https://github.com/NVIDIA/warp/tree/main/warp/examples/core/example_raycast.py"><img src="https://github.com/NVIDIA/warp/raw/main/docs/img/examples/core_raycast.png"></a></td> <td><a href="https://github.com/NVIDIA/warp/tree/main/warp/examples/core/example_raymarch.py"><img src="https://github.com/NVIDIA/warp/raw/main/docs/img/examples/core_raymarch.png"></a></td> </tr> <tr> <td align="center">mesh</td> <td align="center">nvdb</td> <td align="center">raycast</td> <td align="center">raymarch</td> </tr> <tr> <td><a href="https://github.com/NVIDIA/warp/tree/main/warp/examples/core/example_sph.py"><img src="https://github.com/NVIDIA/warp/raw/main/docs/img/examples/core_sph.png"></a></td> <td><a href="https://github.com/NVIDIA/warp/tree/main/warp/examples/core/example_torch.py"><img src="https://github.com/NVIDIA/warp/raw/main/docs/img/examples/core_torch.png"></a></td> <td><a href="https://github.com/NVIDIA/warp/tree/main/warp/examples/core/example_wave.py"><img src="https://github.com/NVIDIA/warp/raw/main/docs/img/examples/core_wave.png"></a></td> <td></td> </tr> <tr> <td align="center">sph</td> <td align="center">torch</td> <td align="center">wave</td> <td align="center"></td> </tr> </tbody> </table> ### examples/fem <table> <tbody> <tr> <td><a href="https://github.com/NVIDIA/warp/tree/main/warp/examples/fem/example_apic_fluid.py"><img src="https://github.com/NVIDIA/warp/raw/main/docs/img/examples/fem_apic_fluid.png"></a></td> <td><a href="https://github.com/NVIDIA/warp/tree/main/warp/examples/fem/example_convection_diffusion.py"><img src="https://github.com/NVIDIA/warp/raw/main/docs/img/examples/fem_convection_diffusion.png"></a></td> <td><a href="https://github.com/NVIDIA/warp/tree/main/warp/examples/fem/example_diffusion_3d.py"><img src="https://github.com/NVIDIA/warp/raw/main/docs/img/examples/fem_diffusion_3d.png"></a></td> <td><a href="https://github.com/NVIDIA/warp/tree/main/warp/examples/fem/example_diffusion.py"><img src="https://github.com/NVIDIA/warp/raw/main/docs/img/examples/fem_diffusion.png"></a></td> </tr> <tr> <td align="center">apic fluid</td> <td align="center">convection diffusion</td> <td align="center">diffusion 3d</td> <td align="center">diffusion</td> </tr> <tr> <td><a href="https://github.com/NVIDIA/warp/tree/main/warp/examples/fem/example_mixed_elasticity.py"><img src="https://github.com/NVIDIA/warp/raw/main/docs/img/examples/fem_mixed_elasticity.png"></a></td> <td><a href="https://github.com/NVIDIA/warp/tree/main/warp/examples/fem/example_navier_stokes.py"><img src="https://github.com/NVIDIA/warp/raw/main/docs/img/examples/fem_navier_stokes.png"></a></td> <td><a href="https://github.com/NVIDIA/warp/tree/main/warp/examples/fem/example_stokes_transfer.py"><img src="https://github.com/NVIDIA/warp/raw/main/docs/img/examples/fem_stokes_transfer.png"></a></td> <td><a href="https://github.com/NVIDIA/warp/tree/main/warp/examples/fem/example_stokes.py"><img src="https://github.com/NVIDIA/warp/raw/main/docs/img/examples/fem_stokes.png"></a></td> </tr> <tr> <td align="center">mixed elasticity</td> <td align="center">navier stokes</td> <td align="center">stokes transfer</td> <td align="center">stokes</td> </tr> </tbody> </table> ### examples/optim <table> <tbody> <tr> <td><a href="https://github.com/NVIDIA/warp/tree/main/warp/examples/optim/example_bounce.py"><img src="https://github.com/NVIDIA/warp/raw/main/docs/img/examples/optim_bounce.png"></a></td> <td><a href="https://github.com/NVIDIA/warp/tree/main/warp/examples/optim/example_cloth_throw.py"><img src="https://github.com/NVIDIA/warp/raw/main/docs/img/examples/optim_cloth_throw.png"></a></td> <td><a href="https://github.com/NVIDIA/warp/tree/main/warp/examples/optim/example_diffray.py"><img src="https://github.com/NVIDIA/warp/raw/main/docs/img/examples/optim_diffray.png"></a></td> <td><a href="https://github.com/NVIDIA/warp/tree/main/warp/examples/optim/example_drone.py"><img src="https://github.com/NVIDIA/warp/raw/main/docs/img/examples/optim_drone.png"></a></td> </tr> <tr> <td align="center">bounce</td> <td align="center">cloth throw</td> <td align="center">diffray</td> <td align="center">drone</td> </tr> <tr> <td><a href="https://github.com/NVIDIA/warp/tree/main/warp/examples/optim/example_inverse_kinematics.py"><img src="https://github.com/NVIDIA/warp/raw/main/docs/img/examples/optim_inverse_kinematics.png"></a></td> <td><a href="https://github.com/NVIDIA/warp/tree/main/warp/examples/optim/example_spring_cage.py"><img src="https://github.com/NVIDIA/warp/raw/main/docs/img/examples/optim_spring_cage.png"></a></td> <td><a href="https://github.com/NVIDIA/warp/tree/main/warp/examples/optim/example_trajectory.py"><img src="https://github.com/NVIDIA/warp/raw/main/docs/img/examples/optim_trajectory.png"></a></td> <td><a href="https://github.com/NVIDIA/warp/tree/main/warp/examples/optim/example_walker.py"><img src="https://github.com/NVIDIA/warp/raw/main/docs/img/examples/optim_walker.png"></a></td> </tr> <tr> <td align="center">inverse kinematics</td> <td align="center">spring cage</td> <td align="center">trajectory</td> <td align="center">walker</td> </tr> </tbody> </table> ### examples/sim <table> <tbody> <tr> <td><a href="https://github.com/NVIDIA/warp/tree/main/warp/examples/sim/example_cartpole.py"><img src="https://github.com/NVIDIA/warp/raw/main/docs/img/examples/sim_cartpole.png"></a></td> <td><a href="https://github.com/NVIDIA/warp/tree/main/warp/examples/sim/example_cloth.py"><img src="https://github.com/NVIDIA/warp/raw/main/docs/img/examples/sim_cloth.png"></a></td> <td><a href="https://github.com/NVIDIA/warp/tree/main/warp/examples/sim/example_granular.py"><img src="https://github.com/NVIDIA/warp/raw/main/docs/img/examples/sim_granular.png"></a></td> <td><a href="https://github.com/NVIDIA/warp/tree/main/warp/examples/sim/example_granular_collision_sdf.py"><img src="https://github.com/NVIDIA/warp/raw/main/docs/img/examples/sim_granular_collision_sdf.png"></a></td> </tr> <tr> <td align="center">cartpole</td> <td align="center">cloth</td> <td align="center">granular</td> <td align="center">granular collision sdf</td> </tr> <tr> <td><a href="https://github.com/NVIDIA/warp/tree/main/warp/examples/sim/example_jacobian_ik.py"><img src="https://github.com/NVIDIA/warp/raw/main/docs/img/examples/sim_jacobian_ik.png"></a></td> <td><a href="https://github.com/NVIDIA/warp/tree/main/warp/examples/sim/example_quadruped.py"><img src="https://github.com/NVIDIA/warp/raw/main/docs/img/examples/sim_quadruped.png"></a></td> <td><a href="https://github.com/NVIDIA/warp/tree/main/warp/examples/sim/example_rigid_chain.py"><img src="https://github.com/NVIDIA/warp/raw/main/docs/img/examples/sim_rigid_chain.png"></a></td> <td><a href="https://github.com/NVIDIA/warp/tree/main/warp/examples/sim/example_rigid_contact.py"><img src="https://github.com/NVIDIA/warp/raw/main/docs/img/examples/sim_rigid_contact.png"></a></td> </tr> <tr> <td align="center">jacobian ik</td> <td align="center">quadruped</td> <td align="center">rigid chain</td> <td align="center">rigid contact</td> </tr> <tr> <td><a href="https://github.com/NVIDIA/warp/tree/main/warp/examples/sim/example_rigid_force.py"><img src="https://github.com/NVIDIA/warp/raw/main/docs/img/examples/sim_rigid_force.png"></a></td> <td><a href="https://github.com/NVIDIA/warp/tree/main/warp/examples/sim/example_rigid_gyroscopic.py"><img src="https://github.com/NVIDIA/warp/raw/main/docs/img/examples/sim_rigid_gyroscopic.png"></a></td> <td><a href="https://github.com/NVIDIA/warp/tree/main/warp/examples/sim/example_rigid_soft_contact.py"><img src="https://github.com/NVIDIA/warp/raw/main/docs/img/examples/sim_rigid_soft_contact.png"></a></td> <td><a href="https://github.com/NVIDIA/warp/tree/main/warp/examples/sim/example_soft_body.py"><img src="https://github.com/NVIDIA/warp/raw/main/docs/img/examples/sim_soft_body.png"></a></td> </tr> <tr> <td align="center">rigid force</td> <td align="center">rigid gyroscopic</td> <td align="center">rigid soft contact</td> <td align="center">soft body</td> </tr> </tbody> </table> ## Building For developers who want to build the library themselves, the following tools are required: * Microsoft Visual Studio 2019 upwards (Windows) * GCC 9.4 upwards (Linux) * CUDA Toolkit 11.5 or higher * [Git LFS](https://git-lfs.github.com/) installed After cloning the repository, users should run: python build_lib.py This will generate the `warp.dll` / `warp.so` core library respectively. It will search for the CUDA Toolkit in the default install directory. This path can be overridden by setting the `CUDA_PATH` environment variable. Alternatively, the path to the CUDA Toolkit can be passed to the build command as `--cuda_path="..."`. After building, the Warp package should be installed using: pip install -e . This ensures that subsequent modifications to the library will be reflected in the Python package. ## Learn More Please see the following resources for additional background on Warp: * [Product Page](https://developer.nvidia.com/warp-python) * [GTC 2022 Presentation](https://www.nvidia.com/en-us/on-demand/session/gtcspring22-s41599) * [GTC 2021 Presentation](https://www.nvidia.com/en-us/on-demand/session/gtcspring21-s31838) * [SIGGRAPH Asia 2021 Differentiable Simulation Course](https://dl.acm.org/doi/abs/10.1145/3476117.3483433) * [GTC 2024 Presentation](https://www.nvidia.com/en-us/on-demand/session/gtc24-s63345/) The underlying technology in Warp has been used in a number of research projects at NVIDIA including the following publications: * Accelerated Policy Learning with Parallel Differentiable Simulation - Xu, J., Makoviychuk, V., Narang, Y., Ramos, F., Matusik, W., Garg, A., & Macklin, M. [(2022)](https://short-horizon-actor-critic.github.io) * DiSECt: Differentiable Simulator for Robotic Cutting - Heiden, E., Macklin, M., Narang, Y., Fox, D., Garg, A., & Ramos, F [(2021)](https://github.com/NVlabs/DiSECt) * gradSim: Differentiable Simulation for System Identification and Visuomotor Control - Murthy, J. Krishna, Miles Macklin, Florian Golemo, Vikram Voleti, Linda Petrini, Martin Weiss, Breandan Considine et al. [(2021)](https://gradsim.github.io) ## Frequently Asked Questions See the [FAQ](https://nvidia.github.io/warp/faq.html) in the Warp documentation. ## Support Problems, questions, and feature requests can be opened on [GitHub Issues](https://github.com/NVIDIA/warp/issues). The Warp team also monitors the **#warp** channel on the public [Omniverse Discord](https://discord.com/invite/nvidiaomniverse) server, come chat to us! ## Versioning Versions take the format X.Y.Z, similar to [Python itself](https://devguide.python.org/developer-workflow/development-cycle/#devcycle): * Increments in X are reserved for major reworks of the project causing disruptive incompatibility (or reaching the 1.0 milestone). * Increments in Y are for regular releases with a new set of features. * Increments in Z are for bug fixes. In principle there are no new features. Can be omitted if 0 or not relevant. This is similar to [Semantic Versioning](https://semver.org/) but less strict around backward compatibility. Like with Python, some breaking changes can be present between minor versions if well documented and gradually introduced. Note that prior to 0.11.0 this schema was not strictly adhered to. ## License Warp is provided under the NVIDIA Software License, please see [LICENSE.md](./LICENSE.md) for full license text. ## Contributing Contributions and pull requests from the community are welcome and are taken under the terms described in the **9. Feedback** section of the [license](LICENSE.md). [CONTRIBUTING.md](./CONTRIBUTING.md) provides additional information on how to open a pull request for Warp. ## Citing If you use Warp in your research please use the following citation: ```bibtex @misc{warp2022, title= {Warp: A High-performance Python Framework for GPU Simulation and Graphics}, author = {Miles Macklin}, month = {March}, year = {2022}, note= {NVIDIA GPU Technology Conference (GTC)}, howpublished = {\url{https://github.com/nvidia/warp}} } ```

A Python framework for high performance GPU simulation and graphics

lwthiker/curl-impersonate

# curl-impersonate     [](https://github.com/lwthiker/curl-impersonate/actions/workflows/build-and-test-make.yml) [](https://github.com/lwthiker/curl-impersonate/actions/workflows/build-and-test-docker.yml) A special build of [curl](https://github.com/curl/curl) that can impersonate the four major browsers: Chrome, Edge, Safari & Firefox. curl-impersonate is able to perform TLS and HTTP handshakes that are identical to that of a real browser. curl-impersonate can be used either as a command line tool, similar to the regular curl, or as a library that can be integrated instead of the regular libcurl. See [Usage](#Basic-usage) below. ## Why? When you use an HTTP client with a TLS website, it first performs a TLS handshake. The first message of that handshake is called Client Hello. The Client Hello message that most HTTP clients and libraries produce differs drastically from that of a real browser. If the server uses HTTP/2, then in addition to the TLS handshake there is also an HTTP/2 handshake where various settings are exchanged. The settings that most HTTP clients and libraries use differ as well from those of any real browsers. For these reasons, some web services use the TLS and HTTP handshakes to fingerprint which client is accessing them, and then present different content for different clients. These methods are known as [TLS fingerprinting](https://lwthiker.com/networks/2022/06/17/tls-fingerprinting.html) and [HTTP/2 fingerprinting](https://lwthiker.com/networks/2022/06/17/http2-fingerprinting.html) respectively. Their widespread use has led to the web becoming less open, less private and much more restrictive towards specific web clients With the modified curl in this repository, the TLS and HTTP handshakes look *exactly* like those of a real browser. ## How? To make this work, `curl` was patched significantly to resemble a browser. Specifically, The modifications that were needed to make this work: * Compiling curl with nss, the TLS library that Firefox uses, instead of OpenSSL. For the Chrome version, compiling with BoringSSL, Google's TLS library. * Modifying the way curl configures various TLS extensions and SSL options. * Adding support for new TLS extensions. * Changing the settings that curl uses for its HTTP/2 connections. * Running curl with some non-default flags, for example `--ciphers`, `--curves` and some `-H` headers. The resulting curl looks, from a network perspective, identical to a real browser. Read the full technical description in the blog posts: [part a](https://lwthiker.com/reversing/2022/02/17/curl-impersonate-firefox.html), [part b](https://lwthiker.com/reversing/2022/02/20/impersonating-chrome-too.html). ## Supported browsers The following browsers can be impersonated. | Browser | Version | Build | OS | Target name | Wrapper script | | --- | --- | --- | --- | --- | --- | |  | 99 | 99.0.4844.51 | Windows 10 | `chrome99` | [curl_chrome99](chrome/curl_chrome99) | |  | 100 | 100.0.4896.75 | Windows 10 | `chrome100` | [curl_chrome100](chrome/curl_chrome100) | |  | 101 | 101.0.4951.67 | Windows 10 | `chrome101` | [curl_chrome101](chrome/curl_chrome101) | |  | 104 | 104.0.5112.81 | Windows 10 | `chrome104` | [curl_chrome104](chrome/curl_chrome104) | |  | 107 | 107.0.5304.107 | Windows 10 | `chrome107` | [curl_chrome107](chrome/curl_chrome107) | |  | 110 | 110.0.5481.177 | Windows 10 | `chrome110` | [curl_chrome110](chrome/curl_chrome110) | |  | 116 | 116.0.5845.180 | Windows 10 | `chrome116` | [curl_chrome116](chrome/curl_chrome116) | |  | 99 | 99.0.4844.73 | Android 12 | `chrome99_android` | [curl_chrome99_android](chrome/curl_chrome99_android) | |  | 99 | 99.0.1150.30 | Windows 10 | `edge99` | [curl_edge99](chrome/curl_edge99) | |  | 101 | 101.0.1210.47 | Windows 10 | `edge101` | [curl_edge101](chrome/curl_edge101) | |  | 91 ESR | 91.6.0esr | Windows 10 | `ff91esr` | [curl_ff91esr](firefox/curl_ff91esr) | |  | 95 | 95.0.2 | Windows 10 | `ff95` | [curl_ff95](firefox/curl_ff95) | |  | 98 | 98.0 | Windows 10 | `ff98` | [curl_ff98](firefox/curl_ff98) | |  | 100 | 100.0 | Windows 10 | `ff100` | [curl_ff100](firefox/curl_ff100) | |  | 102 | 102.0 | Windows 10 | `ff102` | [curl_ff102](firefox/curl_ff102) | |  | 109 | 109.0 | Windows 10 | `ff109` | [curl_ff109](firefox/curl_ff109) | |  | 117 | 117.0.1 | Windows 10 | `ff117` | [curl_ff117](firefox/curl_ff117) | |  | 15.3 | 16612.4.9.1.8 | MacOS Big Sur | `safari15_3` | [curl_safari15_3](chrome/curl_safari15_3) | |  | 15.5 | 17613.2.7.1.8 | MacOS Monterey | `safari15_5` | [curl_safari15_5](chrome/curl_safari15_5) | This list is also available in the [browsers.json](browsers.json) file. ## Basic usage For each supported browser there is a wrapper script that launches `curl-impersonate` with all the needed headers and flags. For example: ``` curl_chrome116 https://www.wikipedia.org ``` You can add command line flags and they will be passed on to curl. However, some flags change curl's TLS signature which may cause it to be detected. Please note that the wrapper scripts use a default set of HTTP headers. If you want to change these headers, you may want to modify the wrapper scripts to fit your own purpose. See [Advanced usage](#Advanced-usage) for more options, including using `libcurl-impersonate` as a library. ## Documentation More documentation is available in the [docs/](docs/README.md) directory. ## Installation There are two versions of `curl-impersonate` for technical reasons. The **chrome** version is used to impersonate Chrome, Edge and Safari. The **firefox** version is used to impersonate Firefox. ### Pre-compiled binaries Pre-compiled binaries for Linux and macOS (Intel) are available at the [GitHub releases](https://github.com/lwthiker/curl-impersonate/releases) page. Before you use them you need to install nss (Firefox's TLS library) and CA certificates: * Ubuntu - `sudo apt install libnss3 nss-plugin-pem ca-certificates` * Red Hat/Fedora/CentOS - `yum install nss nss-pem ca-certificates` * Archlinux - `pacman -S nss ca-certificates` * macOS - `brew install nss ca-certificates` Also ensure you have zlib installed on your system. zlib is almost always present, but on some minimal systems it might be missing. The pre-compiled binaries contain libcurl-impersonate and a statically compiled curl-impersonate for ease of use. The pre-compiled Linux binaries are built for Ubuntu systems. On other distributions if you have errors with certificate verification you may have to tell curl where to find the CA certificates. For example: ``` curl_chrome116 https://www.wikipedia.org --cacert /etc/ssl/certs/ca-bundle.crt ``` Also make sure to read [Notes on Dependencies](#notes-on-dependencies). ### Building from source See [INSTALL.md](INSTALL.md). ### Docker images Docker images based on Alpine Linux and Debian with `curl-impersonate` compiled and ready to use are available on [Docker Hub](https://hub.docker.com/r/lwthiker/curl-impersonate). The images contain the binary and all the wrapper scripts. Use like the following: ```bash # Firefox version, Alpine Linux docker pull lwthiker/curl-impersonate:0.6-ff docker run --rm lwthiker/curl-impersonate:0.6-ff curl_ff109 https://www.wikipedia.org # Chrome version, Alpine Linux docker pull lwthiker/curl-impersonate:0.6-chrome docker run --rm lwthiker/curl-impersonate:0.6-chrome curl_chrome110 https://www.wikipedia.org ``` ### Distro packages AUR packages are available to Archlinux users: * Pre-compiled package: [curl-impersonate-bin](https://aur.archlinux.org/packages/curl-impersonate-bin), [libcurl-impersonate-bin](https://aur.archlinux.org/packages/libcurl-impersonate-bin). * Build from source code: [curl-impersonate-chrome](https://aur.archlinux.org/packages/curl-impersonate-chrome), [curl-impersonate-firefox](https://aur.archlinux.org/packages/curl-impersonate-firefox). Unofficial Homebrew receipts for Mac (Chrome only) are available [here](https://github.com/shakacode/homebrew-brew/blob/main/Formula/curl-impersonate.rb): ``` brew tap shakacode/brew brew install curl-impersonate ``` ## Advanced usage ### libcurl-impersonate `libcurl-impersonate.so` is libcurl compiled with the same changes as the command line `curl-impersonate`. It has an additional API function: ```c CURLcode curl_easy_impersonate(struct Curl_easy *data, const char *target, int default_headers); ``` You can call it with the target names, e.g. `chrome116`, and it will internally set all the options and headers that are otherwise set by the wrapper scripts. If `default_headers` is set to 0, the built-in list of HTTP headers will not be set, and the user is expected to provide them instead using the regular [`CURLOPT_HTTPHEADER`](https://curl.se/libcurl/c/CURLOPT_HTTPHEADER.html) libcurl option. Calling the above function sets the following libcurl options: * `CURLOPT_HTTP_VERSION` * `CURLOPT_SSLVERSION`, `CURLOPT_SSL_CIPHER_LIST`, `CURLOPT_SSL_EC_CURVES`, `CURLOPT_SSL_ENABLE_NPN`, `CURLOPT_SSL_ENABLE_ALPN` * `CURLOPT_HTTPBASEHEADER`, if `default_headers` is non-zero (this is a non-standard HTTP option created for this project). * `CURLOPT_HTTP2_PSEUDO_HEADERS_ORDER`, `CURLOPT_HTTP2_NO_SERVER_PUSH` (non-standard HTTP/2 options created for this project). * `CURLOPT_SSL_ENABLE_ALPS`, `CURLOPT_SSL_SIG_HASH_ALGS`, `CURLOPT_SSL_CERT_COMPRESSION`, `CURLOPT_SSL_ENABLE_TICKET` (non-standard TLS options created for this project). * `CURLOPT_SSL_PERMUTE_EXTENSIONS` (non-standard TLS options created for this project). Note that if you call `curl_easy_setopt()` later with one of the above it will override the options set by `curl_easy_impersonate()`. ### Using CURL_IMPERSONATE env var If your application uses `libcurl` already, you can replace the existing library at runtime with `LD_PRELOAD` (Linux only). You can then set the `CURL_IMPERSONATE` env var. For example: ```bash LD_PRELOAD=/path/to/libcurl-impersonate.so CURL_IMPERSONATE=chrome116 my_app ``` The `CURL_IMPERSONATE` env var has two effects: * `curl_easy_impersonate()` is called automatically for any new curl handle created by `curl_easy_init()`. * `curl_easy_impersonate()` is called automatically after any `curl_easy_reset()` call. This means that all the options needed for impersonation will be automatically set for any curl handle. If you need precise control over the HTTP headers, set `CURL_IMPERSONATE_HEADERS=no` to disable the built-in list of HTTP headers, then set them yourself with `curl_easy_setopt()`. For example: ```bash LD_PRELOAD=/path/to/libcurl-impersonate.so CURL_IMPERSONATE=chrome116 CURL_IMPERSONATE_HEADERS=no my_app ``` Note that the `LD_PRELOAD` method will NOT WORK for `curl` itself because the curl tool overrides the TLS settings. Use the wrapper scripts instead. ### Notes on dependencies If you intend to copy the self-compiled artifacts to another system, or use the [Pre-compiled binaries](#pre-compiled-binaries) provided by the project, make sure that all the additional dependencies are met on the target system as well. In particular, see the [note about the Firefox version](INSTALL.md#a-note-about-the-firefox-version). ## Contents This repository contains two main folders: * [chrome](chrome) - Scripts and patches for building the Chrome version of `curl-impersonate`. * [firefox](firefox) - Scripts and patches for building the Firefox version of `curl-impersonate`. The layout is similar for both. For example, the Firefox directory contains: * [Dockerfile](firefox/Dockerfile) - Used to build `curl-impersonate` with all dependencies. * [curl_ff91esr](firefox/curl_ff91esr), [curl_ff95](firefox/curl_ff95), [curl_ff98](firefox/curl_ff98) - Wrapper scripts that launch `curl-impersonate` with the correct flags. * [curl-impersonate.patch](firefox/patches/curl-impersonate.patch) - The main patch that makes curl use the same TLS extensions as Firefox. Also makes curl compile statically with libnghttp2 and libnss. Other files of interest: * [tests/signatures](tests/signatures) - YAML database of known browser signatures that can be impersonated. ## Contributing If you'd like to help, please check out the [open issues](https://github.com/lwthiker/curl-impersonate/issues). You can open a pull request with your changes. This repository contains the build process for `curl-impersonate`. The actual patches to `curl` are maintained in a [separate repository](https://github.com/lwthiker/curl) forked from the upstream curl. The changes are maintained in the [impersonate-firefox](https://github.com/lwthiker/curl/tree/impersonate-firefox) and [impersonate-chrome](https://github.com/lwthiker/curl/tree/impersonate-chrome) branches. ## Sponsors Sponsors help keep this project open and maintained. If you wish to become a sponsor, please contact me directly at: lwt at lwthiker dot com. <a href="https://serpapi.com/"> <img src="https://i.imgur.com/CBOSxrm.png" alt="Logo" width="165px" height="65px"> </a>

curl-impersonate: A special build of curl that can impersonate Chrome & Firefox

https,curl,ssl,tls,security

rxyhn/yoru

夜 - Yoru | Aesthetic and Beautiful Awesome Environment :first_quarter_moon:

dotfiles,awesomewm,widgets,rofi,rice,setup,unixporn,linux,unix,windowmanager

Threekiii/Awesome-Redteam

# Awesome-Redteam **【免责声明】本项目所涉及的技术、思路和工具仅供学习，任何人不得将其用于非法用途和盈利，不得将其用于非授权渗透测试，否则后果自行承担，与本项目无关。使用本项目前请先阅读 [法律法规](https://github.com/Threekiii/Awesome-Laws)。** ## _Roadmap_  ## 目录 _Contents_ - [目录 _Contents_](#%E7%9B%AE%E5%BD%95-contents) - [项目导航 _Project Navigation_](#%E9%A1%B9%E7%9B%AE%E5%AF%BC%E8%88%AA-project-navigation) - [速查文档 _CheatSheets_](#%E9%80%9F%E6%9F%A5%E6%96%87%E6%A1%A3-cheatsheets) - [一些代码 _Scripts_](#%E4%B8%80%E4%BA%9B%E4%BB%A3%E7%A0%81-scripts) - [攻防知识 _Tips_](#%E6%94%BB%E9%98%B2%E7%9F%A5%E8%AF%86-tips) - [开源导航 _Open-Source Navigation_](#%E5%BC%80%E6%BA%90%E5%AF%BC%E8%88%AA-open-source-navigation) - [编解码/加解密 _Cryptography_](#%E7%BC%96%E8%A7%A3%E7%A0%81%E5%8A%A0%E8%A7%A3%E5%AF%86-cryptography) - [威胁情报 _Threat Intelligence_](#%E5%A8%81%E8%83%81%E6%83%85%E6%8A%A5-threat-intelligence) - [网络空间测绘 _Cyberspace Search Engine_](#%E7%BD%91%E7%BB%9C%E7%A9%BA%E9%97%B4%E6%B5%8B%E7%BB%98-cyberspace-search-engine) - [开源情报 _Open-Source Intelligence_](#%E5%BC%80%E6%BA%90%E6%83%85%E6%8A%A5-open-source-intelligence) - [攻防相关 _Offensive Security_](#%E6%94%BB%E9%98%B2%E7%9B%B8%E5%85%B3-offensive-security) - [漏洞相关 _Vulnerabilities_](#%E6%BC%8F%E6%B4%9E%E7%9B%B8%E5%85%B3-vulnerabilities) - [社区/知识库 _Open-Source Resources_](#%E7%A4%BE%E5%8C%BA%E7%9F%A5%E8%AF%86%E5%BA%93-open-source-resources) - [工具集 _Open-Source Toolkit_](#%E5%B7%A5%E5%85%B7%E9%9B%86-open-source-toolkit) - [信息收集 _Reconnaissance_](#%E4%BF%A1%E6%81%AF%E6%94%B6%E9%9B%86-reconnaissance) - [综合工具 _Nice Tools_](#%E7%BB%BC%E5%90%88%E5%B7%A5%E5%85%B7-nice-tools) - [IP/域名/子域名 _IP/Domain/Subdomain_](#ip%E5%9F%9F%E5%90%8D%E5%AD%90%E5%9F%9F%E5%90%8D-ipdomainsubdomain) - [指纹识别 _Fingerprint_](#%E6%8C%87%E7%BA%B9%E8%AF%86%E5%88%AB-fingerprint) - [扫描/爆破 _Brute Force_](#%E6%89%AB%E6%8F%8F%E7%88%86%E7%A0%B4-brute-force) - [扫描/爆破工具 _Brute Force Tools_](#%E6%89%AB%E6%8F%8F%E7%88%86%E7%A0%B4%E5%B7%A5%E5%85%B7-brute-force-tools) - [扫描/爆破字典 _Brute Force Dictionaries_](#%E6%89%AB%E6%8F%8F%E7%88%86%E7%A0%B4%E5%AD%97%E5%85%B8-brute-force-dictionaries) - [字典生成 _Generate a Custom Dictionary_](#%E5%AD%97%E5%85%B8%E7%94%9F%E6%88%90-generate-a-custom-dictionary) - [默认口令查询 _Default Credentials_](#%E9%BB%98%E8%AE%A4%E5%8F%A3%E4%BB%A4%E6%9F%A5%E8%AF%A2-default-credentials) - [社会工程学 _Social Engineering_](#%E7%A4%BE%E4%BC%9A%E5%B7%A5%E7%A8%8B%E5%AD%A6-social%C2%A0engineering) - [凭据泄露 _Leaked Credentials_](#%E5%87%AD%E6%8D%AE%E6%B3%84%E9%9C%B2-leaked-credentials) - [邮箱 _Email_](#%E9%82%AE%E7%AE%B1-email) - [短信 _SMS_](#%E7%9F%AD%E4%BF%A1-sms) - [钓鱼 _Phishing_](#%E9%92%93%E9%B1%BC-phishing) - [移动端 _Mobile_](#%E7%A7%BB%E5%8A%A8%E7%AB%AF-mobile) - [漏洞研究 _Vulnerability Research_](#%E6%BC%8F%E6%B4%9E%E7%A0%94%E7%A9%B6-vulnerability-research) - [漏洞复现 _Reproduce_](#%E6%BC%8F%E6%B4%9E%E5%A4%8D%E7%8E%B0-reproduce) - [PoC _Proof of Concept_](#poc-proof-of-concept) - [漏洞利用 _Exploits_](#%E6%BC%8F%E6%B4%9E%E5%88%A9%E7%94%A8-exploits) - [综合工具 _Nice Tools_](#%E7%BB%BC%E5%90%88%E5%B7%A5%E5%85%B7-nice-tools) - [反序列化 _Deserialization_](#%E5%8F%8D%E5%BA%8F%E5%88%97%E5%8C%96-deserialization) - [代码审计 _Code Audit_](#%E4%BB%A3%E7%A0%81%E5%AE%A1%E8%AE%A1-code-audit) - [数据库 _Database_](#%E6%95%B0%E6%8D%AE%E5%BA%93-database) - [信息泄露 _Information Disclosure_](#%E4%BF%A1%E6%81%AF%E6%B3%84%E9%9C%B2-information-disclosure) - [_CMS/OA_](#cmsoa) - [中间件/应用层 _Middleware/Application_](#%E4%B8%AD%E9%97%B4%E4%BB%B6%E5%BA%94%E7%94%A8%E5%B1%82-middlewareapplication) - [渗透测试 _Penertation Testing_](#%E6%B8%97%E9%80%8F%E6%B5%8B%E8%AF%95-penertation-testing) - [综合工具 _Nice Tools_](#%E7%BB%BC%E5%90%88%E5%B7%A5%E5%85%B7-nice-tools) - [_Web_](#web) - [_DNSLog_](#dnslog) - [_Payload and Bypass_](#payload-and-bypass) - [内网渗透 _Red Teaming_](#%E5%86%85%E7%BD%91%E6%B8%97%E9%80%8F-red-teaming) - [凭证获取 _Credential Access_](#%E5%87%AD%E8%AF%81%E8%8E%B7%E5%8F%96-credential-access) - [后渗透 _Post Exploitation_](#%E5%90%8E%E6%B8%97%E9%80%8F-post-exploitation) - [权限提升 _Privilege Escalation_](#%E6%9D%83%E9%99%90%E6%8F%90%E5%8D%87-privilege-escalation) - [权限维持 _Persistence_](#%E6%9D%83%E9%99%90%E7%BB%B4%E6%8C%81-persistence) - [免杀项目 _Defense Evasion_](#%E5%85%8D%E6%9D%80%E9%A1%B9%E7%9B%AE-defense-evasion) - [内网穿透 _Proxy_](#%E5%86%85%E7%BD%91%E7%A9%BF%E9%80%8F-proxy) - [辅助工具 _Auxiliary Tools_](#%E8%BE%85%E5%8A%A9%E5%B7%A5%E5%85%B7-auxiliary-tools) - [域渗透 _Active Directory / Kerberos_](#%E5%9F%9F%E6%B8%97%E9%80%8F-active-directory--kerberos) - [开源资源 _Resources_](#%E5%BC%80%E6%BA%90%E8%B5%84%E6%BA%90-resources) - [域内信息收集 Collection and Discovery](#%E5%9F%9F%E5%86%85%E4%BF%A1%E6%81%AF%E6%94%B6%E9%9B%86-collection-and-discovery) - [域内已知漏洞 _Known Vulnerabilities_](#%E5%9F%9F%E5%86%85%E5%B7%B2%E7%9F%A5%E6%BC%8F%E6%B4%9E-known-vulnerabilities) - [域内渗透方式 Methodology](#%E5%9F%9F%E5%86%85%E6%B8%97%E9%80%8F%E6%96%B9%E5%BC%8F-methodology) - [ADCS _Active Directory Certificate Services_](#adcs-active-directory-certificate-services) - [安全防护 _Defensive Security_](#%E5%AE%89%E5%85%A8%E9%98%B2%E6%8A%A4-defensive-security) - [内存马查杀 _Memshell Dectect_](#%E5%86%85%E5%AD%98%E9%A9%AC%E6%9F%A5%E6%9D%80-memshell-dectect) - [Webshell查杀 _Webshell Dectect_](#webshell%E6%9F%A5%E6%9D%80-webshell-dectect) - [攻击研判 _Blue Teaming_](#%E6%94%BB%E5%87%BB%E7%A0%94%E5%88%A4-blue-teaming) - [基线加固 _Enforcement_](#%E5%9F%BA%E7%BA%BF%E5%8A%A0%E5%9B%BA-enforcement) - [勒索病毒 _Ransomware_](#%E5%8B%92%E7%B4%A2%E7%97%85%E6%AF%92-ransomware) - [开源蜜罐 _Open-Source Honeypot_](#%E5%BC%80%E6%BA%90%E8%9C%9C%E7%BD%90-open-source-honeypot) - [云安全 _Cloud Security_](#%E4%BA%91%E5%AE%89%E5%85%A8-cloud-security) - [开源资源 _Resources_](#%E5%BC%80%E6%BA%90%E8%B5%84%E6%BA%90-resources) - [云安全矩阵 _Cloud Matrices_](#%E4%BA%91%E5%AE%89%E5%85%A8%E7%9F%A9%E9%98%B5-cloud-matrices) - [_AK/SK_](#aksk) - [_Docker_](#docker) - [_Kubernetes_](#kubernetes) - [移动端安全 _Mobile Security_](#%E7%A7%BB%E5%8A%A8%E7%AB%AF%E5%AE%89%E5%85%A8-mobile-security) - [小程序 _Mini Program_](#%E5%B0%8F%E7%A8%8B%E5%BA%8F-mini-program) - [_APK_](#apk) - [_SessionKey_](#sessionkey) - [逆向工程 _Reverse engineering_](#%E9%80%86%E5%90%91%E5%B7%A5%E7%A8%8B-reverse-engineering) - [提高生产力的辅助工具](#%E6%8F%90%E9%AB%98%E7%94%9F%E4%BA%A7%E5%8A%9B%E7%9A%84%E8%BE%85%E5%8A%A9%E5%B7%A5%E5%85%B7) - [_Shell_](#shell) - [_Chrome Extensions_](#chrome-extensions) - [_Infrastructure_](#infrastructure) - [提高生产力的使用姿势](#%E6%8F%90%E9%AB%98%E7%94%9F%E4%BA%A7%E5%8A%9B%E7%9A%84%E4%BD%BF%E7%94%A8%E5%A7%BF%E5%8A%BF) - [如何通过.bat使用alias](#%E5%A6%82%E4%BD%95%E9%80%9A%E8%BF%87bat%E4%BD%BF%E7%94%A8alias) - [如何通过.bat激活conda并运行py](#%E5%A6%82%E4%BD%95%E9%80%9A%E8%BF%87bat%E6%BF%80%E6%B4%BBconda%E5%B9%B6%E8%BF%90%E8%A1%8Cpy) - [如何配合tabby实现高效操作](#%E5%A6%82%E4%BD%95%E9%85%8D%E5%90%88tabby%E5%AE%9E%E7%8E%B0%E9%AB%98%E6%95%88%E6%93%8D%E4%BD%9C) - [如何解决cmd中文乱码](#%E5%A6%82%E4%BD%95%E8%A7%A3%E5%86%B3cmd%E4%B8%AD%E6%96%87%E4%B9%B1%E7%A0%81) ## 项目导航 _Project Navigation_ ### 速查文档 _CheatSheets_ 戳这里 [Click Here](https://github.com/Threekiii/Awesome-Redteam/blob/master/cheatsheets/) ``` DefaultCreds-Cheat-Sheet.csv Huawei-iBMC-DefaultCreds.csv Huawei-Product-Cheat-Sheet.csv WeakPassword-Cheat-Sheet.csv 安全厂商及官网链接速查.txt ``` ### 一些代码 _Scripts_ 戳这里 [Click Here](https://github.com/Threekiii/Awesome-Redteam/blob/master/scripts/) ``` ShellcodeWrapper: Shellcode加密 AntivirusScanner: 杀软进程检测脚本 runtime-exec-payloads.html: java.lang.Runtime.exec() Payloads生成 Ascii2Char: ASCII码和字符互相转换脚本 修改webshell文件名密码 Weakpass_Generator: 在线弱密码生成工具 汉化版 Godzilla_Decryptor: 哥斯拉流量解密 Behinder4_Key_Bruteforce: 冰蝎4密钥爆破 Flask_Session_Decryptor: Flask session注入解密 ``` ### 攻防知识 _Tips_ 戳这里 [Click Here](https://github.com/Threekiii/Awesome-Redteam/blob/master/tips/) ``` 信息收集-敏感信息收集 内网渗透-免杀 内网渗透-隐藏 内网渗透-Pentesting AD Mindmap 安全架构-网络攻击与防御图谱 平台搭建-DNS Log 流量分析-CobaltStrike 流量分析-Webshell 社会工程学-钓鱼邮件主题汇总 逆向分析-微信小程序反编译 ``` ## 开源导航 _Open-Source Navigation_ ### 编解码/加解密 _Cryptography_ - Online: - http://www.ip33.com/ - https://evilcos.me/lab/xssee/ - http://www.metools.info/ - https://www.107000.com/ - https://github.com/wangyiwy/oktools - http://www.hiencode.com/ - http://www.atoolbox.net/ - https://www.sojson.com/ - https://the-x.cn/ - Offline: - https://github.com/Ciphey/Ciphey - https://github.com/gchq/CyberChef - http://1o1o.xyz/bo_ctfcode.html - https://github.com/guyoung/CaptfEncoder - MD5: - https://www.cmd5.org/ - https://www.somd5.com/ - https://www.onlinehashcrack.com/ - https://crackstation.net/ - https://crack.sh/ - https://passwordrecovery.io/ - https://md5decrypt.net/en/Sha256/ - https://hashes.com/en/decrypt/hash - RSA: - https://www.ssleye.com/ssltool/ - https://www.lddgo.net/en/encrypt/rsa work with .pem - Encode/Decode: - GB2312: http://code.mcdvisa.com/ - Unicode: https://www.compart.com/en/unicode/ - UUencode: http://web.chacuo.net/charsetuuencode - Escape/Unescape: https://tool.chinaz.com/tools/escape.aspx - HTML 实体编码: https://zh.rakko.tools/tools/21/ - Regular Expressions: - https://regex101.com/ - https://github.com/VincentSit/ChinaMobilePhoneNumberRegex - https://github.com/any86/any-rule ### 威胁情报 _Threat Intelligence_ - Virustotal: https://www.virustotal.com/ - 腾讯哈勃分析系统: https://habo.qq.com/tool/index - 微步在线威胁情报: https://x.threatbook.com/ - 奇安信威胁情报: https://ti.qianxin.com/ - 360 威胁情报: https://ti.360.net/ - 网络安全威胁信息共享平台: https://share.anva.org.cn/web/publicity/listPhishing - 安恒威胁情报: https://ti.dbappsecurity.com.cn/ - 火线安全平台: https://www.huoxian.cn - 知道创宇黑客新闻流: https://hackernews.cc/ - Hacking8 安全信息流: https://i.hacking8.com/ - SecWiki 安全信息流: https://www.sec-wiki.com/ ### 网络空间测绘 _Cyberspace Search Engine_ - Fofa: https://fofa.info/ - Shodan: https://www.shodan.io/ - ZoomEye: https://www.zoomeye.org/ - 鹰图: https://hunter.qianxin.com/ - 谛听: https://www.ditecting.com/ - Quake: https://quake.360.cn/quake/ - Censys: https://search.censys.io/ - Netlas: https://app.netlas.io/domains/ - Wayback Machine: 网页历史缓存 https://web.archive.org/ - VisualPing: 网页变动监测 https://visualping.io/ - Dark Web Exposure: https://www.immuniweb.com/darkweb/ - SG TCP/IP 端口数据库: https://www.speedguide.net/ports.php - Google Hacking Database: - https://www.exploit-db.com/google-hacking-database - https://github.com/cipher387/Dorks-collections-list - https://cxsecurity.com/dorks/ - Google Hacking Online: - https://dorks.faisalahmed.me/ - https://pentest-tools.com/information-gathering/google-hacking - http://advangle.com/ - https://0iq.me/gip/ - Google Hacking Cli: - https://github.com/obheda12/GitDorker - https://github.com/six2dez/dorks_hunter - Github Dork: - https://github.com/search/advanced - https://github.com/obheda12/GitDorker - https://github.com/damit5/gitdorks_go ### 开源情报 _Open-Source Intelligence_ - OSINT Resource List: https://start.me/p/rx6Qj8/nixintel-s-osint-resource-list - OSINT Framework: https://osintframework.com/ - OSINT Handbook: https://i-intelligence.eu/uploads/public-documents/OSINT_Handbook_2020.pdf - Public APIs: - https://www.postman.com/explore/ - https://rapidapi.com/ - Discover secret API keys: https://serene-agnesi-57a014.netlify.app/ - Source code Search Engine: - https://publicwww.com/ - https://searchcode.com/ ### 攻防相关 _Offensive Security_ - Red Teaming and Offensive Security: - https://www.ired.team/ - https://www.thehacker.recipes/ - https://ppn.snovvcrash.rocks/ - https://book.hacktricks.xyz/ - https://blog.harmj0y.net/ - https://hausec.com/domain-penetration-testing/ - https://dirkjanm.io/ - https://casvancooten.com/ - https://evasions.checkpoint.com/ - https://redteam.guide/docs/definitions - https://github.com/HadessCS/Red-team-Interview-Questions - Blue Teaming and Defensive Security: - https://github.com/Purp1eW0lf/Blue-Team-Notes - OPSEC: - https://github.com/WesleyWong420/OPSEC-Tradecraft ### 漏洞相关 _Vulnerabilities_ - 国内信息披露平台: - 国家信息安全漏洞库: https://www.cnnvd.org.cn/ - 国家互联网应急中心: https://www.cert.org.cn/ - 360 网络安全响应中心: https://cert.360.cn/ - 知道创宇漏洞库: https://www.seebug.org/ - 长亭漏洞库: https://stack.chaitin.com/vuldb/ - 阿里云漏洞库: https://avd.aliyun.com/high-risk/list - PeiQi 漏洞库: https://peiqi.wgpsec.org/ - 国外信息披露平台: - https://www.hackerone.com/ - https://cve.mitre.org/ - https://nvd.nist.gov/ - https://www.rapid7.com/db/ - https://packetstormsecurity.com/files/tags/exploit - https://github.com/trickest/cve - Exploits 搜索引擎: - https://sploitus.com/ - https://www.exploit-db.com/ kali 中可以配合命令 `searchsploit <keywords>` 使用 ### 社区/知识库 _Open-Source Resources_ - 先知社区: https://xz.aliyun.com/ - Infocon: https://infocon.org/ - ffffffff0x 团队安全知识框架: https://github.com/ffffffff0x/1earn - 狼组公开知识库: https://wiki.wgpsec.org/ - Mitre ATT&CK: - matrices: https://attack.mitre.org/matrices/enterprise - techniques: http://attack.mitre.org/techniques/enterprise/ - Hacking articles: https://www.hackingarticles.in/ - PostSwigger blog: https://portswigger.net/blog - InGuardians Labs blog: https://www.inguardians.com/ - Pentest Workflow: https://pentest.mxhx.org/ - Pentest cheatsheet: https://pentestbook.six2dez.com/ - Programming/Toolkit/Command/OS/Shortcuts Cheatsheets: - https://cheatsheets.zip/ - https://learnxinyminutes.com/ ### 工具集 _Open-Source Toolkit_ - Nice Tools: - https://forum.ywhack.com/bountytips.php?tools - https://github.com/knownsec/404StarLink - https://pentest-tools.com/ - Beautifier： - http://web.chacuo.net/formatsh - https://beautifier.io/ - http://jsnice.org/ - Reverse Shell Generator: - https://www.revshells.com/ - https://forum.ywhack.com/reverse-shell/ - https://tex2e.github.io/reverse-shell-generator/index.html - https://github.com/0dayCTF/reverse-shell-generator - File Download Generator: - https://github.com/r0eXpeR/File-Download-Generator - Shorten URLs: https://a.f8x.io/ ## 信息收集 _Reconnaissance_ ### 综合工具 _Nice Tools_ - AlliN: https://github.com/P1-Team/AlliN - fscan: https://github.com/shadow1ng/fscan - TscanPlus: https://github.com/TideSec/TscanPlus - kscan: https://github.com/lcvvvv/kscan - Kunyu: https://github.com/knownsec/Kunyu - OneForAll: https://github.com/shmilylty/OneForAll - ShuiZe: https://github.com/0x727/ShuiZe_0x727 - FofaX: https://github.com/xiecat/fofax - Fofa Viewer: https://github.com/wgpsec/fofa_viewer - ENScan_GO: https://github.com/wgpsec/ENScan_GO - Amass: https://github.com/owasp-amass/amass ### IP/域名/子域名 _IP/Domain/Subdomain_ - IP 信息收集: - https://www.ipuu.net/ - https://site.ip138.com/ - https://myip.ms/ - https://ipwhois.cnnic.net.cn - 多个地点 Ping 服务器: - https://ping.chinaz.com/ - https://www.host-tracker.com/ - https://www.webpagetest.org/ - https://dnscheck.pingdom.com/ - IP 反查域名: - https://site.ip138.com/ - https://x.threatbook.cn/ - https://www.virustotal.com/ - Whois 信息收集: - https://whois.chinaz.com/ - https://whois.aliyun.com/ - https://who.is/ - https://www.whoxy.com/ - DNS 信息收集: - https://hackertarget.com/find-dns-host-records - https://dnsdumpster.com - https://dnsdb.io/zh-cn - https://centralops.net/co/ - https://viewdns.info/ - https://dnsdumpster.com/ - https://rapiddns.io/ - ASN 信息收集: - https://wq.apnic.net/ - https://bgp.he.net/ - https://bgpview.io/ - TLS 证书查询: - https://censys.io - https://crt.sh ### 指纹识别 _Fingerprint_ - Fingerprint Collection: - https://github.com/r0eXpeR/fingerprint - Fingerprint Reconnaissance: - https://github.com/EASY233/Finger - https://github.com/EdgeSecurityTeam/EHole - https://github.com/0x727/ObserverWard - https://github.com/TideSec/TideFinger_Go - https://github.com/zhzyker/dismap - https://www.webshell.cc/4697.html - http://www.yunsee.cn/ online - Waf Checks: - https://github.com/stamparm/identYwaf - https://github.com/EnableSecurity/wafw00f - https://github.com/MISP/misp-warninglists ### 扫描/爆破 _Brute Force_ #### 扫描/爆破工具 _Brute Force Tools_ - Port: - https://github.com/antirez/hping - Subdomain: - https://github.com/projectdiscovery/subfinder - https://github.com/knownsec/ksubdomain - Web: - https://github.com/pingc0y/URLFinder - https://github.com/s0md3v/Arjun - https://github.com/OJ/gobuster - https://github.com/jaeles-project/gospider - https://github.com/xmendez/wfuzz - Directory: - https://github.com/maurosoria/dirsearch - https://github.com/H4ckForJob/dirmap - https://github.com/ffuf/ffuf - Password: - https://github.com/vanhauser-thc/thc-hydra - https://github.com/openwall/john - https://github.com/hashcat/hashcat - https://github.com/galkan/crowbar supports sshkey and openvpn - https://github.com/evilsocket/legba/ - Json web token (JWT): - https://jwt.io/ - https://github.com/ticarpi/jwt_tool - https://github.com/brendan-rius/c-jwt-cracker - https://github.com/wallarm/jwt-secrets/blob/master/jwt.secrets.list #### 扫描/爆破字典 _Brute Force Dictionaries_ - Wordlists for all: - https://github.com/danielmiessler/SecLists 46.4k star - https://github.com/SexyBeast233/SecDictionary + ffuf - https://github.com/insightglacier/Dictionary-Of-Pentesting - https://github.com/TheKingOfDuck/fuzzDicts - https://github.com/gh0stkey/Web-Fuzzing-Box - https://github.com/a3vilc0de/PentesterSpecialDict - https://github.com/Bo0oM/fuzz.txt - https://github.com/assetnote/wordlists - Web fuzz wordlists: - https://github.com/lutfumertceylan/top25-parameter - Others (not frequently used): - https://github.com/danielmiessler/SecLists/tree/master/Discovery/Web-Content - https://github.com/assetnote/commonspeak2-wordlists/tree/master/wordswithext - https://github.com/random-robbie/bruteforce-lists - https://github.com/google/fuzzing/tree/master/dictionaries - https://github.com/six2dez/OneListForAll #### 字典生成 _Generate a Custom Dictionary_ - Online: - Generate wordlists: https://weakpass.com/generate - Generate subdomains and wordlists: https://weakpass.com/generate/domains - 汉字转拼音: https://www.aies.cn/pinyin.htm - 密码猜解: https://www.hacked.com.cn/pass.html - Private Deployment: - Generate wordlists(offline): https://github.com/zzzteph/weakpass - Generate subdomains and wordlists(offline): https://github.com/zzzteph/probable_subdomains - Offline: - pydictor: 一个强大实用的黑客暴力破解字典建立工具 https://github.com/LandGrey/pydictor/ - crunch: - Kali/Linux: https://sourceforge.net/projects/crunch-wordlist - Windows: https://github.com/shadwork/Windows-Crunch #### 默认口令查询 _Default Credentials_ - Default Credentials Cheat Sheet: 3468 个默认密码 https://github.com/ihebski/DefaultCreds-cheat-sheet - datarecovery: 在线默认口令查询 https://datarecovery.com/rd/default-passwords/ - cirt.net: 在线默认口令查询 https://cirt.net/passwords - 在线路由器密码查询: - https://www.routerpasswords.com/ - https://portforward.com/router-password/ - https://www.cleancss.com/router-default/ - https://www.toolmao.com/baiduapp/routerpwd/ - https://datarecovery.com/rd/default-passwords/ ### 社会工程学 _Social Engineering_ #### 凭据泄露 _Leaked Credentials_ - https://have-ibeenpwned.com/ - https://breachdirectory.org/ #### 邮箱 _Email_ - Temporary Email: - http://24mail.chacuo.net/ - https://www.guerrillamail.com/ - https://rootsh.com/ - Snov.io: https://app.snov.io - Phonebook: also works on subdomains and urls https://phonebook.cz - Skymem: https://www.skymem.info - Hunter: https://hunter.io - email-format: https://www.email-format.com/i/search/ - 搜邮箱: https://souyouxiang.com/find-contact/ - theHarvester: also works on subdomains https://github.com/laramies/theHarvester - Verify emails: https://tools.emailhippo.com/ - Accounts registered by email: https://emailrep.io/ #### 短信 _SMS_ - SMS Online: - https://www.supercloudsms.com/en/ - https://getfreesmsnumber.com/ - https://www.zusms.com/ - https://yunduanxin.net/ - https://www.free-sms-receive.com/ - https://receive-sms.cc/#google_vignette - https://bestsms.xyz/ - https://smscodeonline.com/ #### 钓鱼 _Phishing_ - gophish: 钓鱼邮件 https://github.com/gophish/gophish - SpoofWeb: 一键部署 https 钓鱼网站 https://github.com/5icorgi/SpoofWeb ### 移动端 _Mobile_ - 小蓝本: https://www.xiaolanben.com/ - 七麦数据: https://www.qimai.cn/ ## 漏洞研究 _Vulnerability Research_ ### 漏洞复现 _Reproduce_ - Basic: - Sqli-labs: https://github.com/Audi-1/sqli-labs - Upload-labs: https://github.com/c0ny1/upload-labs - Xss-labs: https://github.com/do0dl3/xss-labs - DVWA: https://github.com/digininja/DVWA - WebGoat: https://github.com/WebGoat/WebGoat - Comprehensive: - Vulhub: https://vulhub.org/ - ichunqiu: https://yunjing.ichunqiu.com/ - HackTheBox: https://www.hackthebox.com/ - OWASP Top10: https://owasp.org/www-project-juice-shop/ - Vulstudy: 17 platform based on docker https://github.com/c0ny1/vulstudy - Vulfocus: https://github.com/fofapro/vulfocus - IoT: - IoT-vulhub: https://github.com/firmianay/IoT-vulhub - Cloud: - Metarget: https://github.com/Metarget/metarget - Attack Defense: https://attackdefense.pentesteracademy.com/listing?labtype=cloud-services&subtype=cloud-services-amazon-s3 - AWSGoat: https://github.com/ine-labs/AWSGoat - TerraformGoat: https://github.com/HXSecurity/TerraformGoat - Kubernetes Goat: https://github.com/madhuakula/kubernetes-goat - CloudGoat: https://github.com/RhinoSecurityLabs/cloudgoat - Others: - FastJsonParty: https://github.com/lemono0/FastJsonParty ### PoC _Proof of Concept_ > Be careful Malware，POC 库最新的 CVE 可能存在投毒风险。 - PoC 库: - https://github.com/wy876/POC - https://github.com/DawnFlame/POChouse - https://github.com/coffeehb/Some-PoC-oR-ExP - https://github.com/luck-ying/Library-POC - https://github.com/Mr-xn/Penetration_Testing_POC - https://github.com/nomi-sec/PoC-in-GitHub - https://github.com/helloexp/0day - PoC 编写: - https://poc.xray.cool/ online - https://github.com/zeoxisca/gamma-gui offline ## 漏洞利用 _Exploits_ ### 综合工具 _Nice Tools_ - https://github.com/chaitin/xpoc - https://github.com/chaitin/xray - https://github.com/zhzyker/vulmap - https://github.com/zan8in/afrog - https://github.com/ExpLangcn/NucleiTP ### 反序列化 _Deserialization_ - Java: - https://github.com/frohoff/ysoserial - https://github.com/mbechler/marshalsec - https://github.com/qi4L/JYso - https://github.com/welk1n/JNDI-Injection-Exploit - https://github.com/WhiteHSBG/JNDIExploit - https://github.com/rebeyond/JNDInjector - https://github.com/A-D-Team/attackRmi - php: - https://github.com/ambionics/phpggc - Mysql jdbc: - https://github.com/4ra1n/mysql-fake-server - https://github.com/dushixiang/evil-mysql-server - https://github.com/fnmsd/MySQL_Fake_Server ### 代码审计 _Code Audit_ - tabby: https://github.com/wh1t3p1g/tabby ### 数据库 _Database_ - Redis GUI Client: - https://github.com/cinience/RedisStudio - https://github.com/qishibo/AnotherRedisDesktopManager - Redis RCE: - https://github.com/n0b0dyCN/redis-rogue-server - https://github.com/Ridter/redis-rce - https://github.com/yuyan-sec/RedisEXP - https://github.com/r35tart/RedisWriteFile - MDUT: Multiple Database Utilization Tools https://github.com/SafeGroceryStore/MDUT - odat: Oracle RCE https://github.com/quentinhardy/odat ### 信息泄露 _Information Disclosure_ - GitHack: .git 泄露利用脚本 https://github.com/lijiejie/GitHack python3 有时无法恢复.git 目录，推荐 python2 版本 - GitHack: .git 泄露利用脚本 https://github.com/BugScanTeam/GitHack python2 - dvcs-ripper: .svn、.hg、.cvs 泄露利用脚本 https://github.com/kost/dvcs-ripper - ds_store_exp: .DS_Store 文件泄漏利用脚本 https://github.com/lijiejie/ds_store_exp - Hawkeye: GitHub 泄露监控系统 https://github.com/0xbug/Hawkeye ### _CMS/OA_ - 通达 OA: https://github.com/Fu5r0dah/TongdaScan_go - MYExploit: https://github.com/achuna33/MYExploit - Apt_t00ls: https://github.com/White-hua/Apt_t00ls - OA-EXPTOOL: https://github.com/LittleBear4/OA-EXPTOOL - I-Wanna-Get-All: https://github.com/R4gd0ll/I-Wanna-Get-All ### 中间件/应用层 _Middleware/Application_ - Confluence: - ConfluenceMemshell: https://github.com/Lotus6/ConfluenceMemshell - CVE-2022-26134 Memshell: https://github.com/BeichenDream/CVE-2022-26134-Godzilla-MEMSHELL - CVE-2023-22527 Memshell: https://github.com/Boogipop/CVE-2023-22527-Godzilla-MEMSHELL - Druid: - DruidCrack: Druid 密文解密工具 https://github.com/rabbitmask/DruidCrack - druid_sessions: Druid sessions 利用工具 https://github.com/yuyan-sec/druid_sessions - Fastjson: - fastjson-exp: https://github.com/amaz1ngday/fastjson-exp - GitLab: - CVE-2021-22205: https://github.com/Al1ex/CVE-2021-22205/ - Nacos: - NacosRce: Nacos Hessian 反序列化 https://github.com/c0olw/NacosRce/ - nacosleak: 获取 nacos 中配置文件信息 https://github.com/a1phaboy/nacosleak - nacosScan: jwt 硬编码、api 未授权添加用户、配置读取 https://github.com/Whoopsunix/nacosScan - NacosExploitGUI: https://github.com/charonlight/NacosExploitGUI - Nps: - nps-auth-bypass: nps 认证绕过利用工具 https://github.com/carr0t2/nps-auth-bypass - Java: - jdwp-shellifier: python2 https://github.com/IOActive/jdwp-shellifier - jdwp-shellifier: https://github.com/Lz1y/jdwp-shellifier - Shiro: - Shiro rememberMe 在线解密: https://vulsee.com/tools/shiroDe/shiroDecrypt.html - shiro_attack: https://github.com/j1anFen/shiro_attack - shiro_rce_tool: https://github.com/wyzxxz/shiro_rce_tool - ShiroExploit: https://github.com/feihong-cs/ShiroExploit-Deprecated - ShiroExp: https://github.com/safe6Sec/ShiroExp - shiro_key: shiro key 收集 目前 1k+ https://github.com/yanm1e/shiro_key - Struts: - Struts2VulsTools: https://github.com/shack2/Struts2VulsTools - Spring: - SpringBoot-Scan: https://github.com/AabyssZG/SpringBoot-Scan - Spring_All_Reachable: CVE-2022-22947/CVE-2022-22963 https://github.com/savior-only/Spring_All_Reachable - SpringBootVulExploit: https://github.com/LandGrey/SpringBootVulExploit - Spring-cloud-function-SpEL-RCE: CVE-2022-22963 https://github.com/mamba-2021/EXP-POC/tree/main/Spring-cloud-function-SpEL-RCE - swagger-exp: Swagger REST API 信息泄露利用工具 https://github.com/lijiejie/swagger-exp - jasypt decrypt: https://www.devglan.com/online-tools/jasypt-online-encryption-decryption - Heapdump: - heapdump_tool: heapdump 敏感信息查询工具 https://github.com/wyzxxz/heapdump_tool - Memory Analyzer: HeapDump 分析工具 https://eclipse.dev/mat/previousReleases.php - JDumpSpider: HeapDump 敏感信息提取工具 https://github.com/whwlsfb/JDumpSpider - Tomcat: - CVE-2020-1938: https://github.com/YDHCUI/CNVD-2020-10487-Tomcat-Ajp-lfi - ClassHound: https://github.com/LandGrey/ClassHound - Thinkphp: - ThinkphpGUI: https://github.com/Lotus6/ThinkphpGUI - thinkphp_gui_tools: https://github.com/bewhale/thinkphp_gui_tools - Weblogic: - WeblogicTool: https://github.com/KimJun1010/WeblogicTool - WeblogicScan: https://github.com/dr0op/WeblogicScan - WeblogicScan: https://github.com/rabbitmask/WeblogicScan - weblogicScanner: https://github.com/0xn0ne/weblogicScanner - weblogic-framework: https://github.com/sv3nbeast/weblogic-framework - CVE-2020-14882: https://github.com/zhzyker/exphub/blob/master/weblogic/cve-2020-14882_rce.py - WebSocket: - wscat: https://github.com/websockets/wscat - vCenter: - VcenterKiller: 针对 Vcenter 的综合利用工具 https://github.com/Schira4396/VcenterKiller - VcenterKit: Vcenter 综合渗透利用工具包 https://github.com/W01fh4cker/VcenterKit - Zookeeper: - ZooInspector: ZooKeeper 客户端监控软件 https://issues.apache.org/jira/secure/attachment/12436620/ZooInspector.zip - apache-zookeeper: zkCli.sh 客户端命令连接 https://archive.apache.org/dist/zookeeper/zookeeper-3.5.6/ ## 渗透测试 _Penertation Testing_ ### 综合工具 _Nice Tools_ - Yakit: https://github.com/yaklang/yakit - Burpsuite: https://portswigger.net/burp - Burpsuite Extensions: - HaE: 高亮标记与信息提取辅助型插件 https://github.com/gh0stkey/HaE - Log4j2Scan: Log4j 主动扫描插件 https://github.com/whwlsfb/Log4j2Scan - RouteVulScan: 检测脆弱路径插件 https://github.com/F6JO/RouteVulScan - BurpCrypto: 硬编码快乐渗透插件 https://github.com/whwlsfb/BurpCrypto ### _Web_ - XSS: - XSS Chop: https://xsschop.chaitin.cn/demo/ - XSS/CSRF 编码转换: https://evilcos.me/lab/xssor/ - HTML5 Security Cheatsheet: XSS 攻击向量学习/参考 https://html5sec.org/ - Local File Inclusion: - https://github.com/hansmach1ne/lfimap - https://github.com/mzfr/liffy ### _DNSLog_ - Online: - http://ceye.io/ - http://dnslog.cn/ - https://dig.pm/ - Alphalog: dns/http/rmi/ldap https://github.com/AlphabugX/Alphalog - DNS rebinding: https://lock.cmpxchg8b.com/rebinder.html - DNSLog-GO: 自建私有平台 https://github.com/lanyi1998/DNSlog-GO ### _Payload and Bypass_ - Bypass HTTP 40X errors: - https://github.com/yunemse48/403bypasser - https://github.com/lobuhi/byp4xx - https://github.com/Dheerajmadhukar/4-ZERO-3 - https://github.com/devploit/nomore403 - PayloadsAllTheThings: https://github.com/swisskyrepo/PayloadsAllTheThings - java.lang.Runtime.exec() Payload: https://payloads.net/Runtime.exec/ - PHP Generic Gadget Chains: PHP 反序列化 Payload https://github.com/ambionics/phpggc - PHPFuck: https://github.com/splitline/PHPFuck - JSFuck: http://www.jsfuck.com/ - JavaScript Deobfuscator and Unpacker: https://lelinhtinh.github.io/de4js/ - Gopherus: SSRF 生成 gopher 链接 https://github.com/tarunkant/Gopherus python2 - CVE-2021-44228-PoC-log4j-bypass-words: https://github.com/Puliczek/CVE-2021-44228-PoC-log4j-bypass-words ## 内网渗透 _Red Teaming_ ### 凭证获取 _Credential Access_ - Credential Dumping: - LaZagne: https://github.com/AlessandroZ/LaZagne - WirelessKeyView: https://www.nirsoft.net/utils/wireless_key.html - Windows credential manager: https://www.nirsoft.net/utils/credentials_file_view.html - Pillager: https://github.com/qwqdanchun/Pillager/ - searchall: https://github.com/Naturehi666/searchall - Local Enumeration: - HackBrowserData: https://github.com/moonD4rk/HackBrowserData - BrowserGhost: https://github.com/QAX-A-Team/BrowserGhost - chrome: http://www.nirsoft.net/utils/chromepass.html - firefox: https://github.com/unode/firefox_decrypt - foxmail: https://securityxploded.com/foxmail-password-decryptor.php - mobaxterm: https://github.com/HyperSine/how-does-MobaXterm-encrypt-password - navicat: https://github.com/Zhuoyuan1/navicat_password_decrypt - navicat: https://github.com/HyperSine/how-does-navicat-encrypt-password - sunflower: https://github.com/wafinfo/Sunflower_get_Password - securreCRT: https://github.com/depau/shcrt - xshell: - https://github.com/HyperSine/how-does-Xmanager-encrypt-password version<7.0 - https://github.com/RowTeam/SharpDecryptPwd decrypt locally - https://github.com/JDArmy/SharpXDecrypt - Cracking: - NetNTLMv1: https://ntlmv1.com/ online ### 后渗透 _Post Exploitation_ - NICE TOOLS: - https://github.com/rapid7/metasploit-framework - https://github.com/byt3bl33d3r/CrackMapExec - https://github.com/fortra/impacket - https://github.com/XiaoliChan/wmiexec-Pro - https://docs.microsoft.com/en-us/sysinternals/downloads/pstools - https://github.com/GhostPack/Rubeus - https://github.com/Kevin-Robertson/Powermad - https://github.com/PowerShellMafia/PowerSploit - https://github.com/k8gege/Ladon - netspy: 快速探测内网可达网段 https://github.com/shmilylty/netspy - LOLBAS: Windows 二进制文件库 https://github.com/LOLBAS-Project/LOLBAS - GTFOBins: Unix 二进制文件库 https://gtfobins.github.io/ - Responder: - https://github.com/lgandx/Responder - https://github.com/lgandx/Responder-Windows ### 权限提升 _Privilege Escalation_ - Linux Local Enumeration: - https://github.com/carlospolop/privilege-escalation-awesome-scripts-suite - https://github.com/mostaphabahadou/postenum - https://github.com/rebootuser/LinEnum - https://github.com/carlospolop/PEASS-ng/releases/latest/download/linpeas.sh - https://github.com/DominicBreuker/pspy - Windows Local Enumeration: - https://github.com/S3cur3Th1sSh1t/WinPwn - https://github.com/carlospolop/PEASS-ng/blob/master/winPEAS/winPEASbat/winPEAS.bat - https://github.com/S3cur3Th1sSh1t/PowerSharpPack - https://github.com/Flangvik/SharpCollection - https://github.com/PowerShellMafia/PowerSploit/blob/dev/Recon/PowerView.ps1 - https://github.com/dafthack/DomainPasswordSpray - https://github.com/dafthack/MailSniper - Windows Exploits: - https://github.com/AonCyberLabs/Windows-Exploit-Suggester - https://github.com/SecWiki/windows-kernel-exploits - https://github.com/Al1ex/WindowsElevation - https://i.hacking8.com/tiquan/ online - https://github.com/BeichenDream/BadPotato/ - https://github.com/giuliano108/SeBackupPrivilege - https://github.com/gtworek/PSBits/blob/master/Misc/EnableSeBackupPrivilege.ps1 - Linux Exploits: - https://github.com/The-Z-Labs/linux-exploit-suggester - https://github.com/InteliSecureLabs/Linux_Exploit_Suggester - Database Exploits: - https://github.com/Hel10-Web/Databasetools ### 权限维持 _Persistence_ - Webshell Collection: - https://github.com/tennc/webshell - https://github.com/novysodope/RMI_Inj_MemShell - https://github.com/ce-automne/TomcatMemShell - https://github.com/veo/wsMemShell - Webshell Management: - https://github.com/rebeyond/Behinder - https://github.com/BeichenDream/Godzilla - https://github.com/shack2/skyscorpion - Webshell Bypass: - https://github.com/AabyssZG/WebShell-Bypass-Guide - http://bypass.tidesec.com/web/ - https://github.com/cseroad/Webshell_Generate - Reverse Shell Management: - https://github.com/WangYihang/Platypus - https://github.com/calebstewart/pwncat python 3.9+ ### 免杀项目 _Defense Evasion_ - bypassAV: 免杀 shellcode 加载器 过火绒不过 360 https://github.com/pureqh/bypassAV - GolangBypassAV: https://github.com/safe6Sec/GolangBypassAV - BypassAntiVirus: 远控免杀系列文章及配套工具 https://github.com/TideSec/BypassAntiVirus - AV_Evasion_Tool: 掩日 - 适用于红队的综合免杀工具 https://github.com/1y0n/AV_Evasion_Tool - shellcodeloader: Windows 平台的 shellcode 免杀加载器 https://github.com/knownsec/shellcodeloader - 杀软比对 1: tasklist/systeminfo https://www.shentoushi.top/av/av.php - 杀软比对 2: tasklist /svc && ps -aux https://tasklist.ffffffff0x.com/ ### 内网穿透 _Proxy_ - frp: https://github.com/fatedier/frp - frpModify: https://github.com/uknowsec/frpModify - Stowaway: https://github.com/ph4ntonn/Stowaway - Neo-reGeorg: https://github.com/L-codes/Neo-reGeorg - nps: https://github.com/ehang-io/nps - reGeorg: https://github.com/sensepost/reGeorg - rakshasa: https://github.com/Mob2003/rakshasa - Viper: platform with webui https://github.com/FunnyWolf/Viper - Proxifier: tools for windows https://www.proxifier.com/ - Proxychains: tools for kali https://github.com/haad/proxychains - iodine: dns tunnel https://github.com/yarrick/iodine - dnscat2: dns tunnel https://github.com/iagox86/dnscat2 - DNS-Shell: dns tunnel https://github.com/sensepost/DNS-Shell - icmpsh: icmp tunnel https://github.com/bdamele/icmpsh ### 端口转发 _Port Forwarding_ - tcptunnel: https://github.com/vakuum/tcptunnel intranet → dmz → attacker ### 辅助工具 _Auxiliary Tools_ - Cobaltstrike Extensions: - Awesome CobaltStrike: CobaltStrike 知识库 https://github.com/zer0yu/Awesome-CobaltStrike - Erebus: 后渗透测试插件 https://github.com/DeEpinGh0st/Erebus - LSTAR: 综合后渗透插件 https://github.com/lintstar/LSTAR - ElevateKit: 提权插件 https://github.com/rsmudge/ElevateKit - C2ReverseProxy: 不出网上线 https://github.com/Daybr4ak/C2ReverseProxy - pystinger: 不出网上线 https://github.com/FunnyWolf/pystinger - OPSEC Tools: - Privacy.sexy: Scripts for Windows/macOS/Linux 痕迹清理 https://privacy.sexy/ ## 域渗透 _Active Directory / Kerberos_ ### 开源资源 _Resources_ - AD attack&defense mindmaps: https://orange-cyberdefense.github.io/ocd-mindmaps/img/pentest_ad_dark_2023_02.svg - Game of active directory: https://github.com/Orange-Cyberdefense/GOAD - Windows/AD cheatsheet: https://wadcoms.github.io/ ### 域内信息收集 Collection and Discovery - BloodHound: - https://github.com/SpecterOps/BloodHound - https://github.com/dirkjanm/BloodHound.py - https://github.com/BloodHoundAD/SharpHound - https://github.com/CompassSecurity/BloodHoundQueries - https://github.com/lzzbb/Adinfo - https://github.com/wh0amitz/SharpADWS via Active Directory Web Services (ADWS) protocol - https://github.com/FalconForceTeam/SOAPHound via Active Directory Web Services (ADWS) protocol - https://github.com/shmilylty/SharpHostInfo ### 域内已知漏洞 _Known Vulnerabilities_ - noPac: CVE-2021-42278 / CVE-2021-42287 https://github.com/Ridter/noPac - Zerologon CVE-2020-1472: - https://github.com/SecuraBV/CVE-2020-1472/blob/master/zerologon_tester.py - https://github.com/XiaoliChan/zerologon-Shot - https://github.com/dirkjanm/CVE-2020-1472 - https://github.com/Potato-py/Potato/tree/03c3551e4770db440b27b0a48fc02b0a38a1cf04/exp/cve/CVE-2020-1472 reset password - https://github.com/risksense/zerologon reset password - Exchange ProxyLogon & ProxyShell: - https://github.com/dirkjanm/privexchange/ - https://github.com/Jumbo-WJB/PTH_Exchange - https://github.com/hausec/ProxyLogon - Printnightmare CVE-2021-34527 / CVE-2021-1675: - https://github.com/cube0x0/CVE-2021-1675 - https://github.com/nemo-wq/PrintNightmare-CVE-2021-34527 - https://github.com/calebstewart/CVE-2021-1675 ### 域内渗透方式 Methodology - kerbrute: https://github.com/ropnop/kerbrute - DCSync: https://github.com/n00py/DCSync - Coerce & NTLM relay: - PetitPotam: https://github.com/topotam/PetitPotam - PrinterBug: https://github.com/leechristensen/SpoolSample - DFSCoerce: https://github.com/Wh04m1001/DFSCoerce - ShadowCoerce: https://github.com/ShutdownRepo/ShadowCoerce - PrivExchange: https://github.com/dirkjanm/privexchange/ - Coercer: https://github.com/p0dalirius/Coercer ### ADCS _Active Directory Certificate Services_ - Active Directory Certificate Services(AD CS) enumeration and abuse: - Certify: https://github.com/GhostPack/Certify - Certipy: https://github.com/ly4k/Certipy - certi: https://github.com/zer1t0/certi - PKINITtools: https://github.com/dirkjanm/PKINITtools - ADCSPwn: https://github.com/bats3c/ADCSPwn - PassTheCert: https://github.com/AlmondOffSec/PassTheCert ## 安全防护 _Defensive Security_ ### 内存马查杀 _Memshell Dectect_ - Java 内存马查杀: - https://github.com/LandGrey/copagent - https://github.com/c0ny1/java-memshell-scanner - Aspx 内存马查杀: https://github.com/yzddmr6/ASP.NET-Memshell-Scanner ### Webshell 查杀 _Webshell Dectect_ - Webshell Chop: https://webshellchop.chaitin.cn/demo/ - WebShell 查杀: - https://n.shellpub.com/ - http://www.shellpub.com ### 攻击研判 _Blue Teaming_ - CobaltStrike 流量解密脚本: https://github.com/5ime/CS_Decrypt - BlueTeamTools: 综合工具 https://github.com/abc123info/BlueTeamTools - IP Logger: 使用生成的短网址获取访问者 IP 地址 https://iplogger.org/ ### 基线加固 _Enforcement_ - https://github.com/AV1080p/Benchmarks - https://github.com/xiaoyunjie/Shell_Script - https://github.com/grayddq/GScan - https://github.com/ppabc/security_check - https://github.com/T0xst/linux ### 勒索病毒 _Ransomware_ - 搜索引擎: - 360: http://lesuobingdu.360.cn - 腾讯: https://guanjia.qq.com/pr/ls - 启明星辰: https://lesuo.venuseye.com.cn - 奇安信: https://lesuobingdu.qianxin.com - 深信服: https://edr.sangfor.com.cn/#/information/ransom_search - 解密工具: - 腾讯: https://habo.qq.com/tool - 金山毒霸: http://www.duba.net/dbt/wannacry.html - 瑞星: http://it.rising.com.cn/fanglesuo/index.html - 卡巴斯基: https://noransom.kaspersky.com/ - https://www.nomoreransom.org/zh/index.html - https://id-ransomware.malwarehunterteam.com - https://www.avast.com/ransomware-decryption-tools - https://www.emsisoft.com/en/ransomware-decryption/ - Decryption-Tools: 勒索病毒解密工具收集项目 https://github.com/jiansiting/Decryption-Tools ### 开源蜜罐 _Open-Source Honeypot_ - awesome-honeypots: 开源蜜罐列表 https://github.com/paralax/awesome-honeypots - HFish: 一款安全、简单可信赖的跨平台蜜罐软件，允许商业和个人用户免费使用 https://github.com/hacklcx/HFish - conpot: ICS（工业控制系统）蜜罐 https://github.com/mushorg/conpot - MysqlHoneypot: MySQL 蜜罐 获取 wechat ID https://github.com/qigpig/MysqlHoneypot - Ehoney: https://github.com/seccome/Ehoney ## 云安全 _Cloud Security_ ### 开源资源 _Resources_ - TeamsSix 云安全资源: https://github.com/teamssix/awesome-cloud-security - 云安全知识文库: https://wiki.teamssix.com/ - lzCloudSecurity: 云安全攻防入门 - Github: https://github.com/EvilAnne/lzCloudSecurity - Gitbook: https://lzcloudsecurity.gitbook.io/yun-an-quan-gong-fang-ru-men/ - Awesome-CloudSec-Labs: 云原生安全 https://github.com/iknowjason/Awesome-CloudSec-Labs - 阿里云 OpenAPI: https://next.api.aliyun.com/api/ - 云原生全景图: https://landscape.cncf.io/ - 云服务漏洞库: https://www.cloudvulndb.org/ ### 云安全矩阵 _Cloud Matrices_ - ATT&CK Cloud Matrix: https://attack.mitre.org/matrices/enterprise/cloud/ - 火线安全 - 云服务攻防矩阵: https://cloudsec.huoxian.cn/ - 腾讯云鼎实验室 - 云安全攻防矩阵: https://cloudsec.tencent.com/home/ ### _AK/SK_ - CF: 云环境利用框架 https://wiki.teamssix.com/cf/ - aksk_tool: 三大云厂商 +ucloud、AWS、京东云、七牛云 https://github.com/wyzxxz/aksk_tool - cloudTools: 云资产管理工具，三大云厂商 +ucloud https://github.com/dark-kingA/cloudTools - kodo-browser: 七牛云对象存储官方客户端 https://github.com/qiniu/kodo-browser - XstorBrowser: 天翼云对象存储官方客户端 https://www.ctyun.cn/document/10306929/10132519 - oss-browser: 阿里云 OSS 官方客户端 https://github.com/aliyun/oss-browser - cosbrowser: 腾讯云 COS 官方客户端 https://github.com/TencentCloud/cosbrowser - cloudSec: 云平台 AK/SK-WEB 利用工具，三大云厂商（阿里云接管 k8s）、AWS、七牛云 https://github.com/libaibaia/cloudSec - aliyun-accesskey-Tools: 阿里云 GUI https://github.com/mrknow001/aliyun-accesskey-Tools - alicloud-tools: 阿里云 命令行 https://github.com/iiiusky/alicloud-tools - 行云管家: 云存储图形化管理平台 https://yun.cloudbility.com/ ### _Docker_ - CDK: 容器渗透 https://github.com/cdk-team/CDK - veinmind-tools: 容器安全工具集 https://github.com/chaitin/veinmind-tools - Awesome Container Escape: 容器逃逸 https://github.com/brant-ruan/awesome-container-escape - etcdctl: https://github.com/etcd-io/etcd ### _Kubernetes_ - KubeHound: 识别 Kubernetes 集群攻击路径 https://github.com/DataDog/KubeHound - kubectl: https://kubernetes.io/docs/tasks/tools/ ## 移动端安全 _Mobile Security_ ### 小程序 _Mini Program_ - ~~[wxappUnpacker: 小程序解包 https://github.com/xuedingmiaojun/wxappUnpacker]~~ - CrackMinApp: 反编译微信小程序 https://github.com/Cherrison/CrackMinApp - API-Explorer: 公众号/小程序/企业微信 ak/sk https://github.com/mrknow001/API-Explorer ### _APK_ - AppInfoScanner: 移动端信息收集 https://github.com/kelvinBen/AppInfoScanner - Apktool: Android apk 逆向 https://github.com/iBotPeaches/Apktool ### _SessionKey_ - wx_sessionkey_decrypt: wechat SessionKey 加解密 https://github.com/mrknow001/wx_sessionkey_decrypt - BurpAppletPentester: SessionKey 解密插件 https://github.com/mrknow001/BurpAppletPentester ## 逆向工程 _Reverse engineering_ - NICE TOOLS: - OpenArk: Anti-Rootkit 工具集 https://github.com/BlackINT3/OpenArk - 逆向分析工具集: https://pythonarsenal.com/ - ELF/EXE: - IDA: https://hex-rays.com/ida-pro/ - x64DBG: https://x64dbg.com/ - Ollydbg: https://www.ollydbg.de/ - ExeinfoPE: https://github.com/ExeinfoASL/ASL - PEiD: https://www.aldeid.com/wiki/PEiD - UPX: https://github.com/upx/upx - Java: - jadx: https://github.com/skylot/jadx - JEB: https://www.pnfsoftware.com/ - GDA: https://github.com/charles2gan/GDA-android-reversing-Tool - Python: - Py2exe: Python 打包工具 https://www.py2exe.org/ - PyInstaller: Python 打包工具 https://github.com/pyinstaller/pyinstaller - unpy2exe: py2exe 打包程序中提取 .pyc https://github.com/matiasb/unpy2exe - pyinstxtractor: pyInstaller 打包程序中提取 .pyc https://github.com/extremecoders-re/pyinstxtractor - uncompyle6: 字节码文件（.pyc）反编译为源代码（.py） https://github.com/rocky/python-uncompyle6/ - Rust: - https://github.com/cha5126568/rust-reversing-helper - Go: - golang_loader_assist: https://github.com/strazzere/golang_loader_assist - IDAGolangHelper: https://github.com/sibears/IDAGolangHelper - .NET: - dotPeek: https://www.jetbrains.com/zh-cn/decompiler/ - dnSpy: https://github.com/dnSpy/dnSpy ## 提高生产力的辅助工具 ### _Shell_ - oh my zsh: 命令行工具集 https://github.com/ohmyzsh/ohmyzsh - clink: cmd.exe 加强版补全、历史记录和行编辑 https://github.com/chrisant996/clink - tabby: 高度可配置终端 https://github.com/Eugeny/tabby - anew: 命令行工具 文件合并去重 https://github.com/tomnomnom/anew - The art of command line: 快速掌握命令行 https://github.com/jlevy/the-art-of-command-line - Linux 命令行提示工具: - https://github.com/jaywcjlove/linux-command online 版 - https://github.com/chenjiandongx/pls golang 版 - https://github.com/chenjiandongx/how python 版 - Explain Shell: Shell 命令解析 https://explainshell.com/ - ripgrep: 大文本快速检索 https://github.com/BurntSushi/ripgrep ### _Chrome Extensions_ - Proxy SwitchyOmega: 快速切换代理 https://github.com/FelisCatus/SwitchyOmega - serp-analyzer: 识别域名/IP 信息 https://leadscloud.github.io/serp-analyzer/ - FindSomething: 在网页的源代码或 js 中寻找有用信息 https://github.com/ResidualLaugh/FindSomething - Hack Bar: 渗透神器 No.1 https://github.com/0140454/hackbar - Wappalyzer: 识别网站技术/框架/语言 https://www.wappalyzer.com/ - EditThisCookie: 修改 Cookie https://www.editthiscookie.com/ - Disable JavaScript: 禁用 JavaScript 绕过弹窗 https://github.com/dpacassi/disable-javascript - Heimdallr: 被动监听的谷歌插件，用于高危指纹识别、蜜罐特征告警和拦截、机器特征对抗 https://github.com/Ghr07h/Heimdallr - anti-honeypot: 蜜罐识别 https://github.com/cnrstar/anti-honeypot - immersive-translate: 翻译插件 https://github.com/immersive-translate/immersive-translate/ - relingo: 翻译插件 https://cn.relingo.net/en/ - json-formatter: Json 格式化插件 https://github.com/callumlocke/json-formatter - markdown-viewer: 在浏览器查看 markdown 文档 https://github.com/simov/markdown-viewer ### _Infrastructure_ - f8x: 红/蓝队环境自动化部署工具 https://github.com/ffffffff0x/f8x - cloudreve: 私有云盘部署 https://github.com/cloudreve/Cloudreve - updog: uploading and downloading via HTTP/S 文件传输 https://github.com/sc0tfree/updog ## 提高生产力的使用姿势 ### 如何通过.bat 使用 alias - 创建 alias.bat，实现查看 md 文档、运行 exe 程序、激活 conda 环境等功能。文件内容示例: ``` @echo off : : Tips @DOSKEY httpcode=type "D: \HackTools\Tips\http_status_code.md" : : Software @DOSKEY ida64=activate base$t"D: \Software\CTFTools\Cracking\IDA_7.7\ida64.exe" : : Tools @DOSKEY fscan=cd /d D: \Software\HackTools\fscan$tactivate security$tdir ``` - 注册表打开 `计算机\HKEY_CURRENT_USER\Software\Microsoft\Command Processor`。 - 创建字符串值 `autorun`，赋值为 alias.bat 所在位置，例如 `D: \Software\alias.bat`。 - 双击 alias.bat 运行，重启 cmd。 ### 如何通过.bat 激活 conda 并运行 py - run.bat ``` call D: \YOUR_PATH\Anaconda\Scripts\activate.bat D: \YOUR_PATH\Anaconda\ call conda activate YOUR_ENV cd D: \YOUR_WORKDIR python YOUR_PYTHON_FILE.py pause ``` ### 如何配合 tabby 实现高效操作 - 安装 tabby: https://github.com/Eugeny/tabby - 可以通过 tabby 实现自定义 shell 配置，包括但不限于: - vps ssh/ftp/sftp - 自动补全命令（clink） - 快速打开工作区 - 存储输出日志 - ...  ### 如何解决 cmd 中文乱码 - 注册表打开 `计算机\HKEY_LOCAL_MACHINE\SOFTWARE\Microsoft\Command Processor`。 - 创建字符串值 `autorun`，赋值为 `chcp 65001`。

一个攻防知识仓库 Red Teaming and Offensive Security

command-and-control,execution,exploit,initial-access,lateral-movement,privilege-escalation,reconnaissance,red-teaming

cilium/tetragon

<a href="https://tetragon.io"> <picture> <source media="(prefers-color-scheme: light)" srcset="docs/assets/icons/logo.svg" width="400"> <img src="docs/assets/icons/logo-dark.svg" width="400"> </picture> </a> [](https://opensource.org/licenses/Apache-2.0) [](https://opensource.org/license/bsd-2-clause/) [](https://opensource.org/license/gpl-2-0/) --- Cilium’s new [Tetragon](https://tetragon.io) component enables powerful real-time, eBPF-based Security Observability and Runtime Enforcement. Tetragon detects and is able to react to security-significant events, such as - Process execution events - System call activity - I/O activity including network & file access When used in a Kubernetes environment, Tetragon is Kubernetes-aware - that is, it understands Kubernetes identities such as namespaces, pods and so on - so that security event detection can be configured in relation to individual workloads. [](https://tetragon.io/docs/overview/) See more about [how Tetragon is using eBPF](https://tetragon.io/docs/overview#functionality-overview). ## Getting started Refer to the [official documentation of Tetragon](https://tetragon.io/docs/). To get started with Tetragon, take a look at the [getting started guides](https://tetragon.io/docs/getting-started/) to: - [Try Tetragon on Kubernetes](https://tetragon.io/docs/getting-started/install-k8s/) - [Try Tetragon on Linux](https://tetragon.io/docs/getting-started/install-docker/) - [Deploy Tetragon](https://tetragon.io/docs/installation/) - [Install the Tetra CLI](https://tetragon.io/docs/installation/tetra-cli/) Tetragon is able to observe critical hooks in the kernel through its sensors and generates events enriched with Linux and Kubernetes metadata: 1. **Process lifecycle**: generating `process_exec` and `process_exit` events by default, enabling full process lifecycle observability. Learn more about these events on the [process lifecycle use case page](https://tetragon.io/docs/use-cases/process-lifecycle/). 1. **Generic tracing**: generating `process_kprobe`, `process_tracepoint` and `process_uprobe` events for more advanced and custom use cases. Learn more about these events on the [TracingPolicy concept page](https://tetragon.io/docs/concepts/tracing-policy/) and discover [multiple use cases](https://tetragon.io/docs/use-cases/) like: - [🌏 network observability](https://tetragon.io/docs/use-cases/network-observability/) - [📂 filename access](https://tetragon.io/docs/use-cases/filename-access/) - [🔑 credentials monitoring](https://tetragon.io/docs/use-cases/linux-process-credentials/) - [🔓 privileged execution](https://tetragon.io/docs/use-cases/process-lifecycle/privileged-execution/) See further resources: - [Conference Talks, Books, Blog Posts, and Labs](https://tetragon.io/docs/resources/) - [Frequently Asked Question](https://tetragon.io/docs/installation/faq/) - [References](https://tetragon.io/docs/reference/) ## Join the community Join the Tetragon [💬 Slack channel](https://cilium.herokuapp.com/) and the [📅 Community Call](https://isogo.to/tetragon-meeting-notes) to chat with developers, maintainers, and other users. This is a good first stop to ask questions and share your experiences. ## How to Contribute For getting started with local development, you can refer to the [Contribution Guide](https://tetragon.io/docs/contribution-guide/). If you plan to submit a PR, please ["sign-off"](https://tetragon.io/docs/contribution-guide/developer-certificate-of-origin/) your commits.

eBPF-based Security Observability and Runtime Enforcement

bpf,ebpf,kernel,kubernetes,security

helmfile/helmfile

<!-- markdownlint-configure-file { "MD013": { "code_blocks": false, "tables": false }, "MD033": false, "MD041": false } --> <div align="center" markdown="1"> # Helmfile [](https://github.com/helmfile/helmfile/actions/workflows/ci.yaml?query=branch%3Amain) [](https://github.com/helmfile/helmfile/pkgs/container/helmfile) [](https://goreportcard.com/report/github.com/helmfile/helmfile) [](https://slack.sweetops.com) [](https://helmfile.readthedocs.io/en/latest/) Deploy Kubernetes Helm Charts <br /> </div> English | [简体中文](./README-zh_CN.md) ## About Helmfile is a declarative spec for deploying helm charts. It lets you... * Keep a directory of chart value files and maintain changes in version control. * Apply CI/CD to configuration changes. * Periodically sync to avoid skew in environments. To avoid upgrades for each iteration of `helm`, the `helmfile` executable delegates to `helm` - as a result, `helm` must be installed. ## Highlights **Declarative**: Write, version-control, apply the desired state file for visibility and reproducibility. **Modules**: Modularize common patterns of your infrastructure, distribute it via Git, S3, etc. to be reused across the entire company (See [#648](https://github.com/roboll/helmfile/pull/648)) **Versatility**: Manage your cluster consisting of charts, [kustomizations](https://github.com/kubernetes-sigs/kustomize), and directories of Kubernetes resources, turning everything to Helm releases (See [#673](https://github.com/roboll/helmfile/pull/673)) **Patch**: JSON/Strategic-Merge Patch Kubernetes resources before `helm-install`ing, without forking upstream charts (See [#673](https://github.com/roboll/helmfile/pull/673)) ## Status May 2024 Update - We are inviting Helmfile v1 rc testers! Please see the v1 proposal [here](docs/proposals/towards-1.0.md) and the latest rc release in the [releases](/release) page. Please file feature requests in [Discussions](/discussions) and bugs in [Issues](/issues). March 2022 Update - The helmfile project has been moved to [helmfile/helmfile](https://github.com/helmfile/helmfile) from the former home `roboll/helmfile`. Please see roboll/helmfile#1824 for more information. ## Installation **1: Binary Installation** download one of [releases](https://github.com/helmfile/helmfile/releases) **2: Package Manager** * Archlinux: install via `pacman -S helmfile` * openSUSE: install via `zypper in helmfile` assuming you are on Tumbleweed; if you are on Leap you must add the [kubic](https://download.opensuse.org/repositories/devel:/kubic/) repo for your distribution version once before that command, e.g. `zypper ar https://download.opensuse.org/repositories/devel:/kubic/openSUSE_Leap_\$releasever kubic` * Windows (using [scoop](https://scoop.sh/)): `scoop install helmfile` * macOS (using [homebrew](https://brew.sh/)): `brew install helmfile` **3: Container** For more details, see [run as a container](https://helmfile.readthedocs.io/en/latest/#running-as-a-container) > Make sure to run `helmfile init` once after installation. Helmfile uses the [helm-diff](https://github.com/databus23/helm-diff) plugin. ## Getting Started Let's start with a simple `helmfile` and gradually improve it to fit your use-case! Suppose the `helmfile.yaml` representing the desired state of your helm releases looks like: ```yaml repositories: - name: prometheus-community url: https://prometheus-community.github.io/helm-charts releases: - name: prom-norbac-ubuntu namespace: prometheus chart: prometheus-community/prometheus set: - name: rbac.create value: false ``` Sync your Kubernetes cluster state to the desired one by running: ```console helmfile apply ``` Congratulations! You now have your first Prometheus deployment running inside your cluster. Iterate on the `helmfile.yaml` by referencing: * [Configuration](https://helmfile.readthedocs.io/en/latest/#configuration) * [CLI reference](https://helmfile.readthedocs.io/en/latest/#cli-reference) * [Helmfile Best Practices Guide](https://helmfile.readthedocs.io/en/latest/writing-helmfile/) ## Docs Please read [complete documentation](https://helmfile.readthedocs.io/) ## Contributing Welcome to contribute together to make helmfile better: [contributing doc](https://helmfile.readthedocs.io/en/latest/contributing/) ## Attribution We use: * [semtag](https://github.com/pnikosis/semtag) for automated semver tagging. I greatly appreciate the author(pnikosis)'s effort on creating it and their kindness to share it! ## Users Helmfile has been used by many users in production: * [gitlab.com](https://gitlab.com) * [reddit.com](https://reddit.com) * [Jenkins](https://jenkins.io) * ... For more users, please see: [Users](https://helmfile.readthedocs.io/en/latest/users/) ## License [MIT](https://github.com/helmfile/helmfile/blob/main/LICENSE) ## Star History [](https://star-history.com/#helmfile/helmfile&Date)

Declaratively deploy your Kubernetes manifests, Kustomize configs, and Charts as Helm releases. Generate all-in-one manifests for use with ArgoCD.

kubernetes,helm,kustomize

facebook/buck2

<div class="title-block" style="text-align: center;" align="center"> # Buck2: fast multi-language build system ![Version] ![License] [![Build Status]][CI] [Version]: https://img.shields.io/badge/release-unstable,%20"Developer%20Edition"-orange.svg [License]: https://img.shields.io/badge/license-MIT%20OR%20Apache--2.0-blueviolet.svg [Build Status]: https://github.com/facebook/buck2/actions/workflows/build-and-test.yml/badge.svg [CI]: https://github.com/facebook/buck2/actions/workflows/build-and-test.yml <strong> <a href="https://buck2.build">Homepage</a>&nbsp;&nbsp;&bull;&nbsp;&nbsp;<a href="https://buck2.build/docs/getting_started/">Getting Started</a>&nbsp;&nbsp;&bull;&nbsp;&nbsp;<a href="./CONTRIBUTING.md">Contributing</a> </strong> --- </div> Buck2 is a fast, hermetic, multi-language build system, and a direct successor to the original [Buck build system](https://buck.build) ("Buck1") &mdash; both designed by Meta. But what do those words really mean for a build system &mdash; and why might they interest you? "But why Buck2?" you might ask, when so many build systems already exist? - **Fast**. It doesn't matter whether a single build command takes 60 seconds to complete, or 0.1 seconds: when you have to build things, Buck2 doesn't waste time &mdash; it calculates the critical path and gets out of the way, with minimal overhead. It's not just the core design, but also careful attention to detail that makes Buck2 so snappy. Buck2 is up to 2x faster than Buck1 _in practice_[^perf-note]. So you spend more time iterating, and less time waiting. - **Hermetic**. When using Remote Execution[^hermetic-re-only], Buck2 becomes _hermetic_: it is required for a build rule to correctly declare all of its inputs; if they aren't specified correctly (e.g. a `.c` file needs a `.h` file that isn't correctly specified), the build will fail. This enforced correctness helps avoids entire classes of errors that most build systems allow, and helps ensure builds work everywhere for all users. And Buck2 correctly tracks dependencies with far better accuracy than Buck1, in more languages, across more scenarios. That means "it compiles on my machine" can become a thing of the past. - **Multi-language**. Many teams have to deal with multiple programming languages that have complex inter-dependencies, and struggle to express that. Most people settle with `make` and tie together `dune` to `pip` and `cargo`. But then how do you run test suites, code coverage, or query code databases? Buck2 is designed to support multiple languages from the start, with abstractions for interoperation. And because it's completely scriptable, and _users_ can implement language support &mdash; it's incredibly flexible. Now your Python library can depend on an OCaml library, and your OCaml library can depend on a Rust crate &mdash; and with a single build tool, you have a consistent UX to build and test and integrate all of these components. [^perf-note]: This number comes from internal usage of Buck1 versus Buck2 at Meta. Please note that _appropriate_ comparisons with systems like Bazel have yet to be performed; Buck1 is the baseline because it's simply what existed and what had to be replaced. Please benchmark Buck2 against your favorite tools and let us know how it goes! [^hermetic-re-only]: Buck2 currently does not sandbox _local-only_ build steps; in contrast, Buck2 using Remote Execution is _always_ hermetic by design. The vast majority of build rules are remote compatible, as well. Despite that, we hope to lift this restriction in the (hopefully short-term) future so that local-only builds are hermetic as well. If you're familiar with systems like Buck1, [Bazel](https://bazel.build/), or [Pants](https://www.pantsbuild.org/) &mdash; then Buck2 will feel warm and cozy, and these ideas will be familiar. But then why create Buck2 if those already exist? Because that isn't all &mdash; the page _["Why Buck2?"](https://buck2.build/docs/why/)_ on our website goes into more detail on several other important design critera that separate Buck2 from the rest of the pack, including: - Support for ultra-large repositories, through filesystem virtualization and watching for changes to the filesystem. - Totally language-agnostic core executable, with a small API &mdash; even C/C++ support is written as a library. You can write everything from scratch, if you wanted. - "Buck Extension Language" (BXL) can be used for self-introspection of the build system, allowing automation tools to inspect and run actions in the build graph. This allows you to more cleanly support features that need graph introspection, like LSPs or compilation databases. - Support for distributed compilation, using the same Remote Execution API that is supported by Bazel. Existing solutions like BuildBarn, BuildBuddy, EngFlow, and NativeLink all work today. - An efficient, robust, and sound design &mdash; inspired by modern theory of build systems and incremental computation. - And more! If these headline features make you interested &mdash; check out the [Getting Started](https://buck2.build/docs/getting_started/) guide! ## 🚧🚧🚧 **Warning** 🚧🚧🚧 &mdash; rough terrain lies ahead Buck2 was released recently and currently **does not have a stable release tag at this time**. Pre-release tags/binaries, and stable tags/binaries, will come at later dates. Despite that, it is used extensively inside of Meta on vast amounts of code every day, and [buck2-prelude](/prelude/) is the same code used internally for all these builds, as well. Meta just uses the latest committed `HEAD` version of Buck2 at all times. Your mileage may vary &mdash; but at the moment, tracking `HEAD` is ideal for submitting bug reports and catching regressions. The short of this is that you should consider this project and its code to be battle-tested and working, but outside consumers will encounter quite a lot of rough edges right now &mdash; several features are missing or in progress, some toolchains from Buck1 are missing, and you'll probably have to fiddle with things more than necessary to get it nice and polished. Please provide feedback by submitting [issues and questions!](https://github.com/facebook/buck2/issues) ## Installing Buck2 You can get started by downloading the [latest buck2 binary](https://github.com/facebook/buck2/releases/tag/latest) for your platform. The `latest` tag always refers to a recent commit; it is updated on every single push to the GitHub repository, so it will always be a recent version. You can also compile Buck2 from source, if a binary isn't immediately available for your use; check out the [HACKING.md](./HACKING.md) file for information. ## Terminology conventions Frequently used terms and their definitions can be found on the [glossary page](https://buck2.build/docs/concepts/glossary/). ## License Buck2 is licensed under both the MIT license and Apache-2.0 license; the exact terms can be found in the [LICENSE-MIT](LICENSE-MIT) and [LICENSE-APACHE](LICENSE-APACHE) files, respectively.

Build system, successor to Buck

SebLague/Geographical-Adventures

# Geographical Adventures A little work-in-progress geography game about delivering packages to different countries around the world. </br> Made in the Unity game engine. You can try playing the game in its current state [here.](https://sebastian.itch.io/geographical-adventures)   # Development Videos [Episode 01: I Tried Creating a Game Using Real-World Geographic Data](https://youtu.be/sLqXFF8mlEU) </br> [Episode 02: Trying to Improve My Geography Game with More Real-World Data](https://youtu.be/UXD97l7ZT0w) </br> [Episode 03: Polishing and Releasing My Little Geography Game](https://www.youtube.com/watch?v=pNp4ug5F6To)

alura/techguide

# TechGuide.sh [](./LICENSE) O TechGuide.sh é uma iniciativa da Alura para mapear as necessidades mais comuns em cada profissional de tecnologia, direcionando tanto alunos e alunas quanto a própria escola com novos cursos, conteúdos, podcasts e artigos. A gente se inspirou no também opensource http://roadmap.sh, porém usando a abordagem do profissional em T, abrindo mais possibilidades de caminhos e ordenação. Também queremos ter mais descritivos explicando o porquê de aprender cada um daqueles itens (cards) e fechar mais o escopo de cada um. <p align="center"> <img src="https://user-images.githubusercontent.com/13791385/190915091-0ef3f4ad-18bf-4b96-a2ca-0decf5d535ea.png" /> </p> # FAQ/Perguntas Frequentes ## O que é o profissional em T? > **R:** é um profissional que, além da sua especialidade, também tem um certo conhecimento em outras áreas que podem facilitar seu próprio trabalho ou o trabalho em equipe. No site do Dev em T da Alura há bastante a respeito, além de artigos e podcasts: https://alura.com.br/dev-em-t ## Posso gerar meu próprio guia usando esse repositório? > **R:** Sim! Só pedimos que você faça um link para https://techguide.sh 😁 e respeite a licença de uso. Futuramente o site suportará carregar YAMLs de pessoas, empresas e até de outras escolas (esboço da ideia nessa issue: https://github.com/alura/techguide/issues/13) ## Posso sugerir novas carreiras? > **R:** Sim! Use o mecanismo de contribuição do Github. Nesse momento estamos focados em corrigir erros e melhorar as carreiras existentes. > [Por enquanto você pode criar o seu próprio! basta seguir esse tutorial](./docs/br/criando-seu-guide.md) # About the Project/Sobre o Projeto ## Contributing/Contribuir ### O que devo ter em mente antes de abrir um PullRequest? - Esse é um projeto opensource feito pela Alura para a comunidade e contribuições são bem vindas. - Para aumentar a chance de a sua contribuição ser aprovada, escolha um título legal, simples e explicativo para os itens, e siga a formatação correta dos arquivos. - Nesse momento não estamos buscando carreiras novas. Queremos refinar as que já temos. - Mais interessante seria ajudar com o código e projeto em si - 🇧🇷: Quer contribuir com o projeto? [Confira o passo a passo](./CONTRIBUTING.md) ### Próximos Passos? - [X] Exportar o T para você poder trilhar seu caminho e contar suas histórias - [ ] Exportar o T em formato de roteiro de estudos - [ ] Suporte completo em Inglês ## History/Histórico - 🇧🇷: Da uma olhada na aba [Releases](https://github.com/alura/techguide/releases) pra acompanhar as alterações feitas no projeto. ## License/Licença do Projeto - [MIT](./LICENSE) ## Agradecimentos > Aos contribuidores Mário Souto, Fabrício Carraro, Carol Santos, Mateus Henrique, Guilherme Couto, Juliana Amoasei, Mônica Bock, Guilherme Lima, André Bessa, Rodrigo Dias, Vinícius Dias, Rodrigo Caneppele, Fernanda Erahardt, Milena Alves.

TechGuide main repository with the code that guides your tech career!

hacktoberfest

MLNLP-World/Paper-Writing-Tips

<p align="center"> <h1 align="center"> <img src="./pics/icon/ai.png" width="30" /> Paper Writing Tips</h1> </p> <p align="center"> <a href="https://img.shields.io/badge/version-v0.1.0-blue"> <img alt="version" src="https://img.shields.io/badge/version-v0.1.0-blue?color=FF8000?color=009922" /> </a> <a > <img alt="Status-building" src="https://img.shields.io/badge/Status-building-blue" /> </a> <a > <img alt="PRs-Welcome" src="https://img.shields.io/badge/PRs-Welcome-red" /> </a> <a href="https://github.com/MLNLP-World/Paper_Writing_Tips/stargazers"> <img alt="stars" src="https://img.shields.io/github/stars/MLNLP-World/Paper_Writing_Tips" /> </a> <a href="https://github.com/MLNLP-World/Paper_Writing_Tips/network/members"> <img alt="FORK" src="https://img.shields.io/github/forks/MLNLP-World/Paper_Writing_Tips?color=FF8000" /> </a> <a href="https://github.com/MLNLP-World/Paper_Writing_Tips/issues"> <img alt="Issues" src="https://img.shields.io/github/issues/MLNLP-World/Paper_Writing_Tips?color=0088ff"/> </a> <br /> </p> <div align="center"> <p align="center"> <a href="#项目动机">项目动机</a>/ <a href="#写前必看">写前必看</a>/ <a href="#%E7%BB%88%E7%A8%BF%E5%BF%85%E6%9F%A5%E6%8A%95%E7%A8%BF%E5%89%8D%E4%B8%80%E5%91%A8%E4%B8%80%E5%A4%A9">终稿必查</a>/ <a href="#百家之言">百家之言</a>/ <a href="#组织者列表">组织者列表</a>/ <a href="#贡献者列表">贡献者列表</a> </p> </div> ## <img src="./pics/icon/motivation.png" width="25" />项目动机 很多初学者同学在投稿的时候经常会出现一些共有的小错误，为了节省大家的时间和帮助大家能够尽快的定位一些小的问题。本项目总结了我们在自己投稿过程中的经验和一些身边老师同学的投稿经验，希望能对大家有所帮助，由于我们的水平有限，如有疏漏，还望谅解。谢谢大家。 >本项目的特色： > >1. **写前必看**：包含一些常见的错误，每个错误均配有例子，可以在动手写论文之前快速浏览。 >2. **终稿必查**：包含一些例子，方便快速定位是否自己的论文有错误。 >3. **百家之言**：整理了一些网络上公开的写作资源（并不完全，欢迎补充），方便大家系统学习。 ### 免责声明 本项目列举的所有技巧**仅供参考**，并不保证正确。本文主要关注于顶会论文，论文写作以实际需求为准。熟悉写作技巧可能会使写作没有明显的失误，而优秀的论文需要不断打磨。 所有内容仅仅来自于笔者的个人经验、互联网数据、笔者团队日常科研工作中的相关积累，以及笔者团队身边各位大佬的言传身教。有任何问题，欢迎提交 Issue 或 PR。另本项目所用徽章来自互联网，如侵犯了您的图片版权请联系我们删除，谢谢。 ### 欢迎贡献 Paper Writing Tips目前是一个正在进行的中项目，如有疏漏在所难免，欢迎任何的PR及issue讨论。 ### 解释 下文中，标注"Attention"的内容，是目前组织者认为有（较为）明显争议的建议条目。 ## <img src="./pics/icon/intro.png" width="25" />写前必看 ### 公式符号 #### 1. 标量符号用小写拉丁字母表示 * 要点: 为避免混淆字母 l 和数字 1 ，字母 l 可用 \ell 替代。  #### 2. 有结构的值使用 \boldsymbol（Attention） * 要点: 有结构的值例如句子序列、树、图等 （下图仅展示为句子序列情况）  #### 3. \boldsymbol 的集合可用 \mathcal （Attention）  #### 4. 向量值小写加粗，矩阵大写加粗 * 要点: 拉丁字母用\mathbf，希腊字母用\boldsymbol。  #### 5. 数域、期望等使用\mathbb  #### 6. 保持元素与集合的符号对应  #### 7. 写作风格要正式，避免缩写 * `don't` 拆开写成 `do not`s * 所有格 `'s` 尽量转化为 `of`  #### 8. 拉丁文惯用语 - `e.g.,` 表示 `for example,` - `i.e.,` 表示 `that is,` - `et al.` 表示 `and others of the same kind,` - `etc.` 表示 `and others,`，不用于列举人 - `et al.` 或 `etc.` 在句末时，不用再添加额外的句号  #### 9. 英文引号 键位如图所示，使用 `` 和 '' 分别表示左右引号，而不是其他符号或任何中文引号。  #### 10. 不间断空格 "~" 使用 `~` 表示不间断空格，不间断空格不会导致意外的换行，例如： ```latex Figure~\ref{} shows the model performance. Table~\ref{} shows dataset details. We use BERT~\cite{bert} model. Section~\ref{} concludes this paper. ```  #### 11. URL 链接 使用 `\url{}` 命令，需要导入包： ```latex \usepackage{hyperref} ```  #### 12. 引号只表示所谓，不表示引用（Attention） 引用的表述考虑使用斜体 `\textit{}` 而不是引号。  #### 13. 非单个字母的变量名 公式中的 `softmax`，`proj`，`enc` 等超过一个字母的变量或符号，使用正文字体，即使用 `\textrm` 或 `\textit` 命令。  #### 14. 使用函数命令 许多函数和符号有现成的命令，例如：`\arg{}`，`\max{}`，`\sin{}`，`\tanh{}`，`\inf`， `\det{}`， `\exp{}`.  #### 15. 公式中的括号，应通过\left，\right进行标记  - 如 \left(\right), \left{\right}, \left<\right>, \left|\right|等。 - 括号中的分割通过\middle实现。 - Latex代码如下： ```Latex \begin{gather} \bold{s} = \left(\sum_{i=0}^{N-1}{\alpha_{i} \bold{h}_i}\right) + \bold{h}_N\\ \bold{s} = (\sum_{i=0}^{N-1}{\alpha_{i} \bold{h}_i}) + \bold{h}_N \\ \end{gather} \begin{gather} \left\{ x \middle| x\ne\frac{1}{2}\right\} \\ \{ x | x\ne\frac{1}{2}\} \end{gather} ``` #### 16. 使用 align 表示一组公式，等号对齐  - 使用 align 表示一组公式，等号对齐。 - Latex代码如下： ```Latex \begin{gather} E = m c^2 \\ C = B \log_2\left(1+\frac{S}{N}\right) \end{gather} \begin{align} E &= m c^2 \\ C &= B \log_2\left(1+\frac{S}{N}\right) \end{align} ``` #### 17. 只对refer的公式中加编号（Attention）  - 推荐：只对refer的公式加编号，\nonumber去编号。 - Latex代码如下： ```Latex \begin{equation} E = m c^2 \end{equation} \begin{equation} E = m c^2 \nonumber \end{equation} ``` ### 表格图片 #### 18. 使用Booktabs绘制更好看的表格  - 绘制表格时，使用 \usepackage{booktabs}，从而借助 \toprule, \bottomrule, \midrule, \cmidrule 命令，画出好看的分隔线。 - Latex代码如下： ```Latex % Example of a table with booktabs from https://nhigham.com/2019/11/19/better-latex-tables-with-booktabs/. % First version of table. \begin{table}[htbp] \centering \begin{tabular}{|l|c|c|c|c|c|l|} \hline & \multicolumn{3}{c|}{E} & \multicolumn{3}{c|}{F}\\ \hline & $mv$ & Rel.~err & Time & $mv$ & Rel.~err & Time \\\hline A & 11034 & 1.3e-7 & 3.9 & 15846 & 2.7e-11 & 5.6 \\ B & 21952 & 1.3e-7 & 6.2 & 31516 & 2.7e-11 & 8.8 \\ C & 15883 & 5.2e-8 & 7.1 & 32023 & 1.1e-11 & 1.4 \\ D & 11180 & 8.0e-9 & 4.3 & 17348 & 1.5e-11 & 6.6 \\ \hline \end{tabular} \caption{Without booktabs.} \label{tab:without-booktabs} \end{table} % Second version of table, with booktabs. \begin{table}[htbp] \centering \begin{tabular}{lcccccl}\toprule & \multicolumn{3}{c}{E} & \multicolumn{3}{c}{F} \\\cmidrule(lr){2-4}\cmidrule(lr){5-7} & $mv$ & Rel.~err & Time & $mv$ & Rel.~err & Time\\\midrule A & 11034 & 1.3e-7 & 3.9 & 15846 & 2.7e-11 & 5.6 \\ B & 21952 & 1.3e-7 & 6.2 & 31516 & 2.7e-11 & 8.8 \\ C & 15883 & 5.2e-8 & 7.1 & 32023 & 1.1e-11 & 1.4\\ D & 11180 & 8.0e-9 & 4.3 & 17348 & 1.5e-11 & 6.6 \\\bottomrule \end{tabular} \caption{With booktabs.} \label{tab:with-booktabs} \end{table} ``` #### 19. 章节、表格、图片的引用 - 章节、表格、图片使用\label{...}定义后，通过\ref{...}自动引用跳转。 - 对子图或子表的引用可以使用Figure~\ref{fig:figure}(a)来表示。 #### 20. 不要把图表中的Caption在正文中复述  - 说明（Caption）是用来写“这个表格是什么”的。 - 正文是用来写“这个表格说明了什么”的。 #### 21. “三线表”建议：尽量不要画竖线（Attention）  #### 22. 表格大小调整 - 用 \centering 居中；用\small，\scriptsize，\footnotesize，\tiny 调整字号 - 用\setlength{\tabcolsep}{8pt} 调整列间距 - 用 p{2cm} 固定列宽 - 用\multirow，\multicolumn 合并单元格  #### 23. 矢量图：图像应使用矢量图（如PDF格式） - 使用Adobe illustrator、OmniGraffle等软件绘制后存为矢量图 - 使用Matplotlib绘制后存储: plt.savefig('draw.pdf') - 在LaTeX中使用pgfplots直接绘制  #### 24. 图片字体大小介于正文字体与caption之间 - 建议图中字体大小保持一致  #### 25. 论文中图片中文字说明字号应和正文文字大小相当 - 图片中文字字号大小不宜太大  #### 26. 图表设计应适用于黑白打印 - 对黑白打印友好：不要以颜色作为指代图示中线条的唯一特征，可使用实线/虚线 ，亮/暗，不同线形等。  #### 27. 图片风格保持简洁美观 - 不要使用过多的颜色种类，避免过亮的颜色 - 使用简洁的图示，尽量少用文字描述（例子除外） - 同样功能模块使用统一格式 - 箭头走向应趋于同一个方向  ### 选词用词 #### 28. 注意连词符的词性 * 一般连词符中，最后一个词是名词的，连起来是形容词词性；  * 最后一个词是动词的，连起来是动词词性。  #### 29. 词性易错点 * **First**, Secondly，均为副词 * training， **test**，validation，均为名词  #### 30. 缩写符合使用习惯 * 符合习惯，与提出者尽量一致CNN，LSTM，FEVER，ConceptNet，SQuAD，BiDAF，FEVER score，Wikipedia。 * 初次出现时，全称在前，缩写在后；或缩写在前，用于注释的citation在后。graph attention network (GAT)，pre-trained language model (PLM)；BERT~\citep{BERT}。 * 领域名、任务名、指标等一般不需要大写，如 natural language processing, question answering, accuracy, macro-F1 score.  #### 31. 注意单复数 * 尤其是不规则单复数变化、不可数名词。  #### 32. a/an 跟着元音音素走  #### 33. the的使用 * 注意：一般不会独立出现（不用冠词）可数名词单数，要么加the特指，要么加复数泛指。  #### 34. 时态：以一般现在时为主（Attention）  #### 35. 避免绝对化表述。 - 使用straightforward替换obvious - 使用generally、usually、often替换always - 使用rare替换never - 使用alleviate、relieve替换avoid、eliminate  #### 36. 避免一些模糊的表述，比如：meaning, semantic, better等。  以better举例，也就是当表示一个事物更好时，不能仅仅说它更好，需要给出相应的解释与理由 ### 句子表述 #### 37. 避免过多使用代词：it，they等，模型名缩写也不长，并且更清楚。  #### 38. 避免过多贴标签，比如在谈论效果好时。 提出的方法到底改善了哪里，是什么导致的这个结果？  #### 39. 一句话说一件事。尽量使用简单句，少使用长的复合句。  #### 40. 观察/发现？假设？方法？效果？不要混着说。  ### 段落布局 #### 41. 一行字数未超过1/4时，建议删除或者增加字数。（Attention） - 可选：可以尝试在该段话的最后，添加`\looseness=-1`，有时可以在不删除最后一行的情况下，将最后一行的个别单词“挤上去”。  ### 参考文献 #### 42. 参考文献引用需要排查是否在句子中做成分 * 要点：引用使用\citep{}，作为插入语；或\citet{}，作为句子主要成分如主语、宾语等。  #### 43. 尽量引用发表的版本而非arXiv版本。 * 会显得正规一些  #### 44. 引用条目的格式尽量前后一致 * 如会议名缩写、是否包含会议时间地点等是否所有的参考文献格式保持了一致  ## <img src="./pics/icon/resource.png" width="25" />终稿必查——投稿前一周，一天 ### 关于科技英语书写习惯 #### 1. 可参考拼写检查软件，检查文本是否有语病或不符习惯的表达。 * 例如 [grammarly](https://app.grammarly.com), [writefull](https://www.writefull.com/). #### 2. 不要使用 didn't can't don't isn't aren't 之类的缩写形式 任何时候都不要用撇号缩写。对于所有格，完全不要用，非要表达类似意思，用of短语。对于引号，要尽力避免。 #### 3. 使用缩写（如模型名、定义等），需在使用的最初始位置定义。 #### 4. 模型名字大小写保持一致，如BERT，ELECTRA，避免Bert，Electra，electra混合使用。 #### 5. 例句、例子考虑用斜体 #### 6. \begin\item改成正常段落可以使页面更紧凑（然后在每段前手工加打黑点$\bullet$），浪费过多空间有被怀疑灌水之嫌 #### 7. 脚注的写法：一般情况下，脚注可以写在“脚注相关的地方后第一个非左标点符号（如左引号、左括号）”后面。\footnote命令和它前面的标点符号之间没有空格。 #### 8. A和an的区别在于发音：an LSTM cell, an F/H/L/M/N/S/X, a U. #### 9. 文章各级标题的大小写风格统一，例如短语首字母大写或单词首字母大写 #### 10. 使用babel实现单词按音标音节换行（hyphenation patterns）的效果，即`\usepackage[english]{babel}` ### 关于图片： #### 11. 图片内部的字体应统一且跟正文文字大小一致。 #### 12. 整张图片两侧尽量不要有空白，保持紧凑。 #### 13. 图片通常在每一页的最上方或中间，而不是最下方。 #### 14. 同类型模块颜色尽可能保持一个色系，每类单元用同一个颜色填充或作为边框。 #### 15. 同样色系，如果某个模块颜色更深更亮 ，代表这个模块更为重要。如果不是想表达更为重要，更为核心，请在各个模块之间保持均衡颜色分配，比如灰度值尽量一致。 #### 16. 不得使用过多的颜色种类，颜色最好不要高于六种。 #### 17. 图片使用矢量图。 #### 18. figure本意是提供比文字更直观、更明了简洁的表达的，应尽可能动用合理的绘画元素，而不是大量用文字标记。figure元素、规范用最小集合、最统一、一致的设置完成，一般不会难看。 #### 19. 细节到线型、配色：第一，保持统一（低描述复杂性），第二，用一个意思、类别的图形元素该用近似、一样的线形、配色（认知直观性）。 #### 20. 箭头方向尽量保持同向，避免出现来回折转。流程图中避免出现孤立组件（无任何来源或去向箭头标识）。 ### 关于引用： #### 21. 引用标记的选取： * 引用在文字外（parent），使用 \cite。 * 引用在文字内（within text） * ACL/NAACL/EMNLP模板使用\citet{...}； * COLING模板使用\newcite{...}； * AAAI/IJCAI模板使用\citeauthor{...} \shortcite{...}； * IEEE模版：\citeauthor{...}~(\citeyear{...}) 效果：(Zhang et al. 2020) vs. Zhang et al. (2020) #### 22. 如果篇幅较紧张，可以在引用中使用会议期刊名称的缩写。 * 可以参考工具 [SimBiber](https://github.com/MLNLP-World/SimBiber) #### 23. bib管理注意保持会议/期刊名称全称和缩写一致性，检查年份、卷号、页码等，不要完全依赖 scholar 提供的信息（可能存在缺失或格式混乱）。 * 可以参考工具 [Rebiber](https://github.com/yuchenlin/rebiber) #### 24. 章节、表格、图片使用\label定义后，可通过\ref自动引用跳转。 #### 25. 引用和正文之间留有一个空格，而不是紧邻正文字母。 #### 26. 不要重复引用同一论文的不同版本，例如 arXiv和正式会议论文。 ### 关于公式： #### 27. 公式为句子的一部分。因此可在公式内部（尤其是多行）加入逗号和句号。 #### 28. 对于公式后面的文字，若与公式组成完成的句子，则首字母不需要大写，并紧接在公式后面；若另起新的句子或段落，则在公式结束符\end后换行，并句子首字母大写，开启新的句子。 ### 投稿前注意事项： #### 29. 检查文章的匿名性，不能包含个人与机构信息。 #### 30. 检查是否超页（最后时刻慎重勿随意改图表大小） #### 31. 检查标题和摘要与投稿系统填写框内的信息是否对应。 #### 32. 检查提交的数据与代码，不能包含个人与机构信息，尤其 code 里面一些 hard coded 的模型或数据路径等需要处理掉，另外需要注意隐藏文件夹（如 .git） #### 33. Overleaf 在部分会议投稿前可能访问缓慢，请注意LaTex备份 #### 34. 论文的历史版本可以用时间编号，避免提交的不是最终版本 #### 35. 截稿前一天最好提前交一个版本的论文以及附录，防止截稿时服务器崩溃 #### 36. 交稿后仍需要关注会议官网和注册邮箱，以及时收到可能存在的会议截稿日期延后的消息。 ## <img src="./pics/icon/catalogue.png" width="25" />百家之言 ● [清华大学刘洋老师的CWMT-2014报告：机器翻译学术论⽂文写作⽅方法和技巧](http://nlp.csai.tsinghua.edu.cn/~ly/talks/cwmt14_tut.pdf) ● [复旦大学邱锡鹏老师的CCL-2018报告：如何端到端地写科研论文？](https://xpqiu.github.io/slides/20181019-PaperWriting.pdf) ● [清华大学刘知远老师：如何写一篇合格的NLP论文 ](https://zhuanlan.zhihu.com/p/58752815) ● [中国人民大学赵鑫老师：如何以初学者的身份写好一篇国际学术论文](https://zhuanlan.zhihu.com/p/136005095) ● [哈尔滨工业大学车万翔老师：如何做一个精彩的学术报告](http://www.cips-cl.org/static/CCL2019/downloads/stuPPT/01.pdf) ● [香港中文大学（深圳）陈冠英老师整理的写作建议](https://github.com/guanyingc/latex_paper_writing_tips) || [& Rebuttal Template ](https://github.com/guanyingc/cv_rebuttal_template) ● [哥伦比亚大学 Henning Schulzrinne 老师：Tips and Resources for Writing Computer Science Papers](http://www.cs.columbia.edu/~hgs/etc/writing.html) ● [哈佛大学 Whitesides 老师：从写提纲的角度切入讲解如何撰写学术论文](https://onlinelibrary.wiley.com/doi/pdf/10.1002/adma.200400767) ● [卡耐基梅隆大学 Graham Neubig 老师：How to Read/Write an International Conference Paper](http://www.phontron.com/slides/neubig15paperwriting.pdf) & [Paper style guide](http://phontron.com/paper-guide.php) ● [MSR研究员Simon Peyton Jones老师：How to Write a Great Research Paper](http://research.microsoft.com/en-us/um/people/simonpj/papers/giving-a-talk/writing-a-paper-slides.pdf) ● [MSRA研究员王晋东：用LaTex写论文经验分享](https://mp.weixin.qq.com/s/XshMg6Qb8ArLNA75ImQIWQ) ● [支付宝研究员王益老师：“学好语文，才能写好代码”（很多观点对写论文同样适用）](https://zhuanlan.zhihu.com/p/157243326) ● [哈尔滨工业大学刘一佳博士的NLPCC-2018报告：论文写作的易读性原则](http://yjliu.net/cv/res/2018-08-19-nlpcc-sws.compressed.pdf) ● [上海交通大学张倬胜博士整理的写作建议](https://github.com/cooelf/PaperWritingTips) ● [TTIC石昊悦博士：如何优雅地（用TeX）写AI论文](https://zhuanlan.zhihu.com/p/103519006) ● [夕小瑶的卖萌屋：11 个好用的科研工具推荐！工作效率提升 max！](https://mp.weixin.qq.com/s/YaPYZvd12Xxgz1Y1L9Rzuw) ● [夕小瑶的卖萌屋：吐血整理：论文写作中注意这些细节，能显著提升成稿质量](https://mp.weixin.qq.com/s/1ykqoLWjy3WhczAvb_eOoQ) ● [Deepmind Chris Dyer 等老师：关于NLP论文中公式的建议](http://karlstratos.com/teaching/cs445fall20/short-guide-typesetting.pdf) ● [Google Brain的Bo Chang老师的LaTeX Tips](https://bochang.me/blog/posts/latex/) ● [如何让摘要吸引人？Nature论文摘要模板值得收藏](https://zhuanlan.zhihu.com/p/158574876) ● [一个Notation的重要参考](https://www.deeplearningbook.org/contents/notation.html) ● [synercys/annotated_latex_equations：Examples of how to create colorful, annotated equations in Latex using Tikz.](https://github.com/synercys/annotated_latex_equations) ● [acmi-lab/cmu-10717-the-art-of-the-paper: Official repository for CMU Machine Learning Department&#39;s 10717: &#34;The Art of the Paper&#34;. (github.com)](https://github.com/acmi-lab/cmu-10717-the-art-of-the-paper) ● [acl-org/aclpubcheck: Tools for checking ACL paper submissions](https://github.com/acl-org/aclpubcheck) ● [dspinellis/latex-advice: Advice for writing LaTeX documents](https://github.com/dspinellis/latex-advice) ● [Graham Neubig：How to Read/Write an International Conference Paper](http://www.phontron.com/slides/neubig15paperwriting.pdf) ● [Karl Whelan：Writing Tips for PhD Theses](https://www.karlwhelan.com/Teaching/PhD/phd-writing-talk.pdf) ● [Karl Whelan：Tips for Preparing and Publishing Research Papers](https://www.karlwhelan.com/Teaching/isne_talk_sep07.pdf) ## <img src="./pics/icon/organizer.png" width="25" />组织者列表 感谢以下同学对本项目进行组织与指导 <a href="https://github.com/Erutan-pku"> <img src="pics/profile/Erutan-pku.png" width="80" > </a> <a href="https://github.com/cooelf"> <img src="pics/profile/Zhousheng Zhang.png" width="80" ></a> <a href="https://github.com/SivilTaram"> <img src="pics/profile/Qian.png" width="80" ></a> <a href="https://github.com/liucongg"> <img src="pics/profile/logCong.png" width="80" > </a> <a href="https://github.com/yhshu"> <img src="pics/profile/yiheng.png" width="80" > </a> <a href="https://github.com/LooperXX"> <img src="pics/profile/Xiao Xu.png" width="80" > </a> <a href="https://github.com/kokolerk"> <img src="pics/profile/jiaqi.png" width="80" > </a> <a href="https://github.com/yizhen20133868"> <img src="pics/profile/Libo Qin.png" width="80" > </a> ## <img src="./pics/icon/heart.png" width="25" />贡献者列表 感谢以下同学对本项目的支持与贡献 <a href="https://github.com/Erutan-pku"> <img src="pics/profile/Erutan-pku.png" width="80" /></a> <a href="https://github.com/cooelf"> <img src="pics/profile/Zhousheng Zhang.png" width="80" /></a> <a href="https://github.com/SivilTaram"> <img src="pics/profile/Qian.png" width="80" /></a> <a href="https://github.com/liucongg"> <img src="pics/profile/logCong.png" width="80" /></a> <a href="https://github.com/yhshu"> <img src="pics/profile/yiheng.png" width="80" /></a> <a href="https://github.com/LooperXX"> <img src="pics/profile/Xiao Xu.png" width="80" /></a> <a href="https://github.com/kokolerk"> <img src="pics/profile/jiaqi.png" width="80" /></a> <a href="https://github.com/yizhen20133868"> <img src="pics/profile/Libo Qin.png" width="80" /></a> <a href="https://github.com/HMJiangGatech"> <img src="pics/profile/HaomingJiang.png" width="80" /></a> <a href="https://github.com/jiaruonan"> <img src="pics/profile/JiaRuonan.png" width="80" /></a> <a href="https://github.com/Yutong-Zhou-cv"> <img src="pics/profile/YutongZhou.png" width="80" /></a> <a href="https://github.com/wangcongrobot"> <img src="pics/profile/CongWang.png" width="80" /></a> <a href="https://github.com/bright2013"> <img src="pics/profile/bright2013.png" width="80" /></a>

MLNLP社区用来帮助大家避免论文投稿小错误的整理仓库。 Paper Writing Tips

mlnlp

tensorchord/Awesome-LLMOps

# Awesome LLMOps <a href="https://discord.gg/KqswhpVgdU"><img alt="discord invitation link" src="https://dcbadge.vercel.app/api/server/KqswhpVgdU?style=flat"></a> <a href="https://awesome.re"><img src="https://awesome.re/badge-flat2.svg"></a> An awesome & curated list of the best LLMOps tools for developers. ## Contribute Contributions are most welcome, please adhere to the [contribution guidelines](contributing.md). ## Table of Contents - [Table of Contents](#table-of-contents) - [Model](#model) - [Large Language Model](#large-language-model) - [CV Foundation Model](#cv-foundation-model) - [Audio Foundation Model](#audio-foundation-model) - [Serving](#serving) - [Large Model Serving](#large-model-serving) - [Frameworks/Servers for Serving](#frameworksservers-for-serving) - [Observability](#observability) - [Security](#security) - [LLMOps](#llmops) - [Search](#search) - [Vector search](#vector-search) - [Code AI](#code-ai) - [Training](#training) - [IDEs and Workspaces](#ides-and-workspaces) - [Foundation Model Fine Tuning](#foundation-model-fine-tuning) - [Frameworks for Training](#frameworks-for-training) - [Experiment Tracking](#experiment-tracking) - [Visualization](#visualization) - [Model Editing](#model-editing) - [Data](#data) - [Data Management](#data-management) - [Data Storage](#data-storage) - [Data Tracking](#data-tracking) - [Feature Engineering](#feature-engineering) - [Data/Feature enrichment](#datafeature-enrichment) - [Large Scale Deployment](#large-scale-deployment) - [ML Platforms](#ml-platforms) - [Workflow](#workflow) - [Scheduling](#scheduling) - [Model Management](#model-management) - [Performance](#performance) - [ML Compiler](#ml-compiler) - [Profiling](#profiling) - [AutoML](#automl) - [Optimizations](#optimizations) - [Federated ML](#federated-ml) - [Awesome Lists](#awesome-lists) <!-- Created by https://github.com/ekalinin/github-markdown-toc --> ## Model ### Large Language Model | Project | Details | Repository | |---|---|---| | [Alpaca](https://github.com/tatsu-lab/stanford_alpaca) | Code and documentation to train Stanford's Alpaca models, and generate the data. |  | | [BELLE](https://github.com/LianjiaTech/BELLE) | A 7B Large Language Model fine-tune by 34B Chinese Character Corpus, based on LLaMA and Alpaca. |  | | [Bloom](https://github.com/bigscience-workshop/model_card) | BigScience Large Open-science Open-access Multilingual Language Model |  | | [dolly](https://github.com/databrickslabs/dolly) | Databricks’ Dolly, a large language model trained on the Databricks Machine Learning Platform |  | | [Falcon 40B](https://huggingface.co/tiiuae/falcon-40b-instruct) | Falcon-40B-Instruct is a 40B parameters causal decoder-only model built by TII based on Falcon-40B and finetuned on a mixture of Baize. It is made available under the Apache 2.0 license. | | | [FastChat (Vicuna)](https://github.com/lm-sys/FastChat) | An open platform for training, serving, and evaluating large language models. Release repo for Vicuna and FastChat-T5. |  | | [Gemma](https://www.kaggle.com/models/google/gemma) | Gemma is a family of lightweight, open models built from the research and technology that Google used to create the Gemini models.| | | [GLM-6B (ChatGLM)](https://github.com/THUDM/ChatGLM-6B) | An Open Bilingual Pre-Trained Model, quantization of ChatGLM-130B, can run on consumer-level GPUs. |  | | [ChatGLM2-6B](https://github.com/THUDM/ChatGLM2-6B) | ChatGLM2-6B is the second-generation version of the open-source bilingual (Chinese-English) chat model [ChatGLM-6B](https://github.com/THUDM/ChatGLM-6B). |  | | [GLM-130B (ChatGLM)](https://github.com/THUDM/GLM-130B) | An Open Bilingual Pre-Trained Model (ICLR 2023) |  | | [GPT-NeoX](https://github.com/EleutherAI/gpt-neox) | An implementation of model parallel autoregressive transformers on GPUs, based on the DeepSpeed library. |  | | [Luotuo](https://github.com/LC1332/Luotuo-Chinese-LLM) | A Chinese LLM, Based on LLaMA and fine tune by Stanford Alpaca, Alpaca LoRA, Japanese-Alpaca-LoRA. |  | | [Mixtral-8x7B-v0.1](https://huggingface.co/mistralai/Mixtral-8x7B-v0.1) | The Mixtral-8x7B Large Language Model (LLM) is a pretrained generative Sparse Mixture of Experts. | | | [StableLM](https://github.com/Stability-AI/StableLM) | StableLM: Stability AI Language Models |  | **[⬆ back to ToC](#table-of-contents)** ### CV Foundation Model | Project | Details | Repository | |---|---|---| | [disco-diffusion](https://github.com/alembics/disco-diffusion) | A frankensteinian amalgamation of notebooks, models and techniques for the generation of AI Art and Animations. |  | | [midjourney](https://www.midjourney.com/home/) | Midjourney is an independent research lab exploring new mediums of thought and expanding the imaginative powers of the human species. | | | [segment-anything (SAM)](https://github.com/facebookresearch/segment-anything) | produces high quality object masks from input prompts such as points or boxes, and it can be used to generate masks for all objects in an image. |  | | [stable-diffusion](https://github.com/CompVis/stable-diffusion) | A latent text-to-image diffusion model |  | | [stable-diffusion v2](https://github.com/Stability-AI/stablediffusion) | High-Resolution Image Synthesis with Latent Diffusion Models |  | **[⬆ back to ToC](#table-of-contents)** ### Audio Foundation Model | Project | Details | Repository | |---|---|---| | [bark](https://github.com/suno-ai/bark) | Bark is a transformer-based text-to-audio model created by Suno. Bark can generate highly realistic, multilingual speech as well as other audio - including music, background noise and simple sound effects. |  | | [whisper](https://github.com/openai/whisper) | Robust Speech Recognition via Large-Scale Weak Supervision |  | ## Serving ### Large Model Serving | Project | Details | Repository | |---|---|---| | [Alpaca-LoRA-Serve](https://github.com/deep-diver/Alpaca-LoRA-Serve) | Alpaca-LoRA as Chatbot service |  | | [CTranslate2](https://github.com/OpenNMT/CTranslate2) | fast inference engine for Transformer models in C++ |  | | [Clip-as-a-service](https://github.com/jina-ai/clip-as-service) | serving the OpenAI CLIP model |  | | [DeepSpeed-MII](https://github.com/microsoft/DeepSpeed-MII) | MII makes low-latency and high-throughput inference possible, powered by DeepSpeed. |  | | [Faster Whisper](https://github.com/guillaumekln/faster-whisper) | fast inference engine for whisper in C++ using CTranslate2. |  | | [FlexGen](https://github.com/FMInference/FlexGen) | Running large language models on a single GPU for throughput-oriented scenarios. |  | | [Flowise](https://github.com/FlowiseAI/Flowise) | Drag & drop UI to build your customized LLM flow using LangchainJS. |  | | [llama.cpp](https://github.com/ggerganov/llama.cpp) | Port of Facebook's LLaMA model in C/C++ |  | | [Infinity](https://github.com/michaelfeil/infinity) | Rest API server for serving text-embeddings |  | | [Modelz-LLM](https://github.com/tensorchord/modelz-llm) | OpenAI compatible API for LLMs and embeddings (LLaMA, Vicuna, ChatGLM and many others) |  | | [Ollama](https://github.com/jmorganca/ollama) | Serve Llama 2 and other large language models locally from command line or through a browser interface. |  | | [TensorRT-LLM](https://github.com/NVIDIA/TensorRT-LLM) | Inference engine for TensorRT on Nvidia GPUs |  | | [text-generation-inference](https://github.com/huggingface/text-generation-inference) | Large Language Model Text Generation Inference |  | | [text-embeddings-inference](https://github.com/huggingface/text-embeddings-inference) | Inference for text-embedding models |  | | [vllm](https://github.com/vllm-project/vllm) | A high-throughput and memory-efficient inference and serving engine for LLMs. |  | | [whisper.cpp](https://github.com/ggerganov/whisper.cpp) | Port of OpenAI's Whisper model in C/C++ |  | | [x-stable-diffusion](https://github.com/stochasticai/x-stable-diffusion) | Real-time inference for Stable Diffusion - 0.88s latency. Covers AITemplate, nvFuser, TensorRT, FlashAttention. |  | **[⬆ back to ToC](#table-of-contents)** ### Frameworks/Servers for Serving | Project | Details | Repository | |---|---|---| | [BentoML](https://github.com/bentoml/BentoML) | The Unified Model Serving Framework |  | | [Jina](https://github.com/jina-ai/jina) | Build multimodal AI services via cloud native technologies · Model Serving · Generative AI · Neural Search · Cloud Native |  | | [Mosec](https://github.com/mosecorg/mosec) | A machine learning model serving framework with dynamic batching and pipelined stages, provides an easy-to-use Python interface. |  | | [TFServing](https://github.com/tensorflow/serving) | A flexible, high-performance serving system for machine learning models. |  | | [Torchserve](https://github.com/pytorch/serve) | Serve, optimize and scale PyTorch models in production |  | | [Triton Server (TRTIS)](https://github.com/triton-inference-server/server) | The Triton Inference Server provides an optimized cloud and edge inferencing solution. |  | | [langchain-serve](https://github.com/jina-ai/langchain-serve) | Serverless LLM apps on Production with Jina AI Cloud |  | | [lanarky](https://github.com/ajndkr/lanarky) | FastAPI framework to build production-grade LLM applications |  | | [ray-llm](https://github.com/ray-project/ray-llm) | LLMs on Ray - RayLLM |  | | [Xinference](https://github.com/xorbitsai/inference) | Replace OpenAI GPT with another LLM in your app by changing a single line of code. Xinference gives you the freedom to use any LLM you need. With Xinference, you're empowered to run inference with any open-source language models, speech recognition models, and multimodal models, whether in the cloud, on-premises, or even on your laptop. |  | **[⬆ back to ToC](#table-of-contents)** ## Security ### Frameworks for LLM security | Project | Details | Repository | |---|---|---| | [Plexiglass](https://github.com/kortex-labs/plexiglass) | A Python Machine Learning Pentesting Toolbox for Adversarial Attacks. Works with LLMs, DNNs, and other machine learning algorithms. |  | **[⬆ back to ToC](#table-of-contents)** ### Observability | Project | Details | Repository | |---|---|---| | [Azure OpenAI Logger](https://github.com/aavetis/azure-openai-logger) | "Batteries included" logging solution for your Azure OpenAI instance. |  | | [Deepchecks](https://github.com/deepchecks/deepchecks) | Tests for Continuous Validation of ML Models & Data. Deepchecks is a Python package for comprehensively validating your machine learning models and data with minimal effort. |  | | [Evidently](https://github.com/evidentlyai/evidently) | Evaluate and monitor ML models from validation to production. |  | | [Fiddler AI](https://github.com/fiddler-labs/fiddler-auditor) | Evaluate, monitor, analyze, and improve machine learning and generative models from pre-production to production. Ship more ML and LLMs into production, and monitor ML and LLM metrics like hallucination, PII, and toxicity. |  | | [Giskard](https://github.com/Giskard-AI/giskard) | Testing framework dedicated to ML models, from tabular to LLMs. Detect risks of biases, performance issues and errors in 4 lines of code. |  | | [Great Expectations](https://github.com/great-expectations/great_expectations) | Always know what to expect from your data. |  | | [whylogs](https://github.com/whylabs/whylogs) | The open standard for data logging |  | **[⬆ back to ToC](#table-of-contents)** ## LLMOps | Project | Details | Repository | |---|---|---| | [agenta](https://github.com/Agenta-AI/agenta) | The LLMOps platform to build robust LLM apps. Easily experiment and evaluate different prompts, models, and workflows to build robust apps. |  | | [AI studio](https://github.com/missingstudio/ai) | A Reliable Open Source AI studio to build core infrastructure stack for your LLM Applications. It allows you to gain visibility, make your application reliable, and prepare it for production with features such as caching, rate limiting, exponential retry, model fallback, and more. |  | | [Arize-Phoenix](https://github.com/Arize-ai/phoenix) | ML observability for LLMs, vision, language, and tabular models. |  | | [BudgetML](https://github.com/ebhy/budgetml) | Deploy a ML inference service on a budget in less than 10 lines of code. |  | | [CometLLM](https://github.com/comet-ml/comet-llm) | The 100% opensource LLMOps platform to log, manage, and visualize your LLM prompts and chains. Track prompt templates, prompt variables, prompt duration, token usage, and other metadata. Score prompt outputs and visualize chat history all within a single UI. |  | | [deeplake](https://github.com/activeloopai/deeplake) | Stream large multimodal datasets to achieve near 100% GPU utilization. Query, visualize, & version control data. Access data w/o the need to recompute the embeddings for the model finetuning. |  | | [Dify](https://github.com/langgenius/dify) | Open-source framework aims to enable developers (and even non-developers) to quickly build useful applications based on large language models, ensuring they are visual, operable, and improvable. |  | | [Dstack](https://github.com/dstackai/dstack) | Cost-effective LLM development in any cloud (AWS, GCP, Azure, Lambda, etc). |  | | [Embedchain](https://github.com/embedchain/embedchain) | Framework to create ChatGPT like bots over your dataset. |  | | [Fiddler AI](https://www.fiddler.ai/llmops) | Evaluate, monitor, analyze, and improve MLOps and LLMOps from pre-production to production. | | | [Glide](https://github.com/EinStack/glide) | Cloud-Native LLM Routing Engine. Improve LLM app resilience and speed. |  | | [GPTCache](https://github.com/zilliztech/GPTCache) | Creating semantic cache to store responses from LLM queries. |  | | [Haystack](https://github.com/deepset-ai/haystack) | Quickly compose applications with LLM Agents, semantic search, question-answering and more. |  | | [Izlo](https://getizlo.com/) | Prompt management tools for teams. Store, improve, test, and deploy your prompts in one unified workspace. | | | [Keywords AI](https://keywordsai.co/) | A unified DevOps platform for AI software. Keywords AI makes it easy for developers to build LLM applications. | | | [langchain](https://github.com/hwchase17/langchain) | Building applications with LLMs through composability |  | | [LangFlow](https://github.com/logspace-ai/langflow) | An effortless way to experiment and prototype LangChain flows with drag-and-drop components and a chat interface. |  | | [Langfuse](https://github.com/langfuse/langfuse) | Open Source LLM Engineering Platform: Traces, evals, prompt management and metrics to debug and improve your LLM application. |  | | [LangKit](https://github.com/whylabs/langkit) | Out-of-the-box LLM telemetry collection library that extracts features and profiles prompts, responses and metadata about how your LLM is performing over time to find problems at scale. |  | | [LiteLLM 🚅](https://github.com/BerriAI/litellm/) | A simple & light 100 line package to **standardize LLM API calls** across OpenAI, Azure, Cohere, Anthropic, Replicate API Endpoints |  | | [Literal AI](https://literalai.com/) | Multi-modal LLM observability and evaluation platform. Create prompt templates, deploy prompts versions, debug LLM runs, create datasets, run evaluations, monitor LLM metrics and collect human feedback. | | | [LlamaIndex](https://github.com/jerryjliu/llama_index) | Provides a central interface to connect your LLMs with external data. |  | | [LLMApp](https://github.com/pathwaycom/llm-app) | LLM App is a Python library that helps you build real-time LLM-enabled data pipelines with few lines of code. |  | | [LLMFlows](https://github.com/stoyan-stoyanov/llmflows) | LLMFlows is a framework for building simple, explicit, and transparent LLM applications such as chatbots, question-answering systems, and agents. |  | | [LLMonitor](https://github.com/llmonitor/llmonitor) | Observability and monitoring for AI apps and agents. Debug agents with powerful tracing and logging. Usage analytics and dive deep into the history of your requests. Developer friendly modules with plug-and-play integration into LangChain. |  | | [magentic](https://github.com/jackmpcollins/magentic) | Seamlessly integrate LLMs as Python functions. Use type annotations to specify structured output. Mix LLM queries and function calling with regular Python code to create complex LLM-powered functionality. |  | | [Manag.ai](https://www.manag.ai) | Your all-in-one prompt management and observability platform. Craft, track, and perfect your LLM prompts with ease. | | | [Mirascope](https://github.com/Mirascope/mirascope) | Intuitive convenience tooling for lightning-fast, efficient development and ensuring quality in LLM-based applications |  | | [OpenLIT](https://github.com/openlit/openlit) | OpenLIT is an OpenTelemetry-native GenAI and LLM Application Observability tool and provides OpenTelmetry Auto-instrumentation for monitoring LLMs, VectorDBs and Frameworks. It provides valuable insights into token & cost usage, user interaction, and performance related metrics. |  | | [Parea AI](https://www.parea.ai/) | Platform and SDK for AI Engineers providing tools for LLM evaluation, observability, and a version-controlled enhanced prompt playground. |  | | [Pezzo 🕹️](https://github.com/pezzolabs/pezzo) | Pezzo is the open-source LLMOps platform built for developers and teams. In just two lines of code, you can seamlessly troubleshoot your AI operations, collaborate and manage your prompts in one place, and instantly deploy changes to any environment. |  | | [PromptHub](https://www.prompthub.us) | Full stack prompt management tool designed to be usable by technical and non-technical team members. Test, version, collaborate, deploy, and monitor, all from one place. | | | [promptfoo](https://github.com/typpo/promptfoo) | Open-source tool for testing & evaluating prompt quality. Create test cases, automatically check output quality and catch regressions, and reduce evaluation cost. |  | | [Prompteams](https://www.prompteams.com) | Prompt management system. Version, test, collaborate, and retrieve prompts through real-time APIs. Have GitHub style with repos, branches, and commits (and commit history). | | | [prompttools](https://github.com/hegelai/prompttools) | Open-source tools for testing and experimenting with prompts. The core idea is to enable developers to evaluate prompts using familiar interfaces like code and notebooks. In just a few lines of codes, you can test your prompts and parameters across different models (whether you are using OpenAI, Anthropic, or LLaMA models). You can even evaluate the retrieval accuracy of vector databases. |  | | [TreeScale](https://treescale.com) | All In One Dev Platform For LLM Apps. Deploy LLM-enhanced APIs seamlessly using tools for prompt optimization, semantic querying, version management, statistical evaluation, and performance tracking. As a part of the developer friendly API implementation TreeScale offers Elastic LLM product, which makes a unified API Endpoint for all major LLM providers and open source models. | | | [TrueFoundry](https://www.truefoundry.com/) | Deploy LLMOps tools like Vector DBs, Embedding server etc on your own Kubernetes (EKS,AKS,GKE,On-prem) Infra including deploying, Fine-tuning, tracking Prompts and serving Open Source LLM Models with full Data Security and Optimal GPU Management. Train and Launch your LLM Application at Production scale with best Software Engineering practices. | | | [ReliableGPT 💪](https://github.com/BerriAI/reliableGPT/) | Handle OpenAI Errors (overloaded OpenAI servers, rotated keys, or context window errors) for your production LLM Applications. |  | | [Portkey](https://portkey.ai/) | Control Panel with an observability suite & an AI gateway — to ship fast, reliable, and cost-efficient apps. | | | [Vellum](https://www.vellum.ai/) | An AI product development platform to experiment with, evaluate, and deploy advanced LLM apps. | | | [Weights & Biases (Prompts)](https://docs.wandb.ai/guides/prompts) | A suite of LLMOps tools within the developer-first W&B MLOps platform. Utilize W&B Prompts for visualizing and inspecting LLM execution flow, tracking inputs and outputs, viewing intermediate results, securely managing prompts and LLM chain configurations. | | | [Wordware](https://www.wordware.ai) | A web-hosted IDE where non-technical domain experts work with AI Engineers to build task-specific AI agents. It approaches prompting as a new programming language rather than low/no-code blocks. | | | [xTuring](https://github.com/stochasticai/xturing) | Build and control your personal LLMs with fast and efficient fine-tuning. |  | | [ZenML](https://github.com/zenml-io/zenml) | Open-source framework for orchestrating, experimenting and deploying production-grade ML solutions, with built-in `langchain` & `llama_index` integrations. |  | **[⬆ back to ToC](#table-of-contents)** ## Search ### Vector search | Project | Details | Repository | |---|---|---| | [AquilaDB](https://github.com/Aquila-Network/AquilaDB) | An easy to use Neural Search Engine. Index latent vectors along with JSON metadata and do efficient k-NN search. |  | | [Awadb](https://github.com/awa-ai/awadb) | AI Native database for embedding vectors |  | | [Chroma](https://github.com/chroma-core/chroma) | the open source embedding database |  | | [Infinity](https://github.com/infiniflow/infinity) | The AI-native database built for LLM applications, providing incredibly fast vector and full-text search |  | | [Lancedb](https://github.com/lancedb/lancedb) | Developer-friendly, serverless vector database for AI applications. Easily add long-term memory to your LLM apps! |  | | [Marqo](https://github.com/marqo-ai/marqo) | Tensor search for humans. |  | | [Milvus](https://github.com/milvus-io/milvus) | Vector database for scalable similarity search and AI applications. |  | | [Pinecone](https://www.pinecone.io/) | The Pinecone vector database makes it easy to build high-performance vector search applications. Developer-friendly, fully managed, and easily scalable without infrastructure hassles. | | | [pgvector](https://github.com/pgvector/pgvector) | Open-source vector similarity search for Postgres. |  | | [pgvecto.rs](https://github.com/tensorchord/pgvecto.rs) | Vector database plugin for Postgres, written in Rust, specifically designed for LLM. |  | | [Qdrant](https://github.com/qdrant/qdrant) | Vector Search Engine and Database for the next generation of AI applications. Also available in the cloud |  | | [txtai](https://github.com/neuml/txtai) | Build AI-powered semantic search applications |  | | [Vald](https://github.com/vdaas/vald) | A Highly Scalable Distributed Vector Search Engine |  | | [Vearch](https://github.com/vearch/vearch) | A distributed system for embedding-based vector retrieval |  | | [VectorDB](https://github.com/jina-ai/vectordb) | A Python vector database you just need - no more, no less. |  | | [Vellum](https://www.vellum.ai/products/retrieval) | A managed service for ingesting documents and performing hybrid semantic/keyword search across them. Comes with out-of-box support for OCR, text chunking, embedding model experimentation, metadata filtering, and production-grade APIs. | | | [Weaviate](https://github.com/semi-technologies/weaviate) | Weaviate is an open source vector search engine that stores both objects and vectors, allowing for combining vector search with structured filtering with the fault-tolerance and scalability of a cloud-native database, all accessible through GraphQL, REST, and various language clients. |  | **[⬆ back to ToC](#table-of-contents)** ## Code AI | Project | Details | Repository | |---|---|---| | [CodeGeeX](https://github.com/THUDM/CodeGeeX) | CodeGeeX: An Open Multilingual Code Generation Model (KDD 2023) |  | | [CodeGen](https://github.com/salesforce/CodeGen) | CodeGen is an open-source model for program synthesis. Trained on TPU-v4. Competitive with OpenAI Codex. |  | | [CodeT5](https://github.com/salesforce/CodeT5) | Open Code LLMs for Code Understanding and Generation. |  | | [Continue](https://github.com/continuedev/continue) | ⏩ the open-source autopilot for software development—bring the power of ChatGPT to VS Code |  | | [fauxpilot](https://github.com/fauxpilot/fauxpilot) | An open-source alternative to GitHub Copilot server |  | | [tabby](https://github.com/TabbyML/tabby) | Self-hosted AI coding assistant. An opensource / on-prem alternative to GitHub Copilot. |  | ## Training ### IDEs and Workspaces | Project | Details | Repository | |---|---|---| | [code server](https://github.com/coder/code-server) | Run VS Code on any machine anywhere and access it in the browser. |  | | [conda](https://github.com/conda/conda) | OS-agnostic, system-level binary package manager and ecosystem. |  | | [Docker](https://github.com/moby/moby) | Moby is an open-source project created by Docker to enable and accelerate software containerization. |  | | [envd](https://github.com/tensorchord/envd) | 🏕️ Reproducible development environment for AI/ML. |  | | [Jupyter Notebooks](https://github.com/jupyter/notebook) | The Jupyter notebook is a web-based notebook environment for interactive computing. |  | | [Kurtosis](https://github.com/kurtosis-tech/kurtosis) | A build, packaging, and run system for ephemeral multi-container environments. |  | | [Wordware](https://www.wordware.ai) | A web-hosted IDE where non-technical domain experts work with AI Engineers to build task-specific AI agents. It approaches prompting as a new programming language rather than low/no-code blocks. | | **[⬆ back to ToC](#table-of-contents)** ### Foundation Model Fine Tuning | Project | Details | Repository | |----------------------------------------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|---| | [alpaca-lora](https://github.com/tloen/alpaca-lora) | Instruct-tune LLaMA on consumer hardware |  | | [finetuning-scheduler](https://github.com/speediedan/finetuning-scheduler) | A PyTorch Lightning extension that accelerates and enhances foundation model experimentation with flexible fine-tuning schedules. |  | | [Flyflow](https://github.com/flyflow-devs) | Open source, high performance fine tuning as a service for GPT4 quality models with 5x lower latency and 3x lower cost |  | | [LMFlow](https://github.com/OptimalScale/LMFlow) | An Extensible Toolkit for Finetuning and Inference of Large Foundation Models |  | | [Lora](https://github.com/cloneofsimo/lora) | Using Low-rank adaptation to quickly fine-tune diffusion models. |  | | [peft](https://github.com/huggingface/peft) | State-of-the-art Parameter-Efficient Fine-Tuning. |  | | [p-tuning-v2](https://github.com/THUDM/P-tuning-v2) | An optimized prompt tuning strategy achieving comparable performance to fine-tuning on small/medium-sized models and sequence tagging challenges. [(ACL 2022)](https://arxiv.org/abs/2110.07602) |  | | [QLoRA](https://github.com/artidoro/qlora) | Efficient finetuning approach that reduces memory usage enough to finetune a 65B parameter model on a single 48GB GPU while preserving full 16-bit finetuning task performance. |  | | [TRL](https://github.com/huggingface/trl) | Train transformer language models with reinforcement learning. |  | **[⬆ back to ToC](#table-of-contents)** ### Frameworks for Training | Project | Details | Repository | |---|---|---| | [Accelerate](https://github.com/huggingface/accelerate) | 🚀 A simple way to train and use PyTorch models with multi-GPU, TPU, mixed-precision. |  | | [Apache MXNet](https://github.com/apache/mxnet) | Lightweight, Portable, Flexible Distributed/Mobile Deep Learning with Dynamic, Mutation-aware Dataflow Dep Scheduler. |  | | [axolotl](https://github.com/OpenAccess-AI-Collective/axolotl) | A tool designed to streamline the fine-tuning of various AI models, offering support for multiple configurations and architectures. |  | | [Caffe](https://github.com/BVLC/caffe) | A fast open framework for deep learning. |  | | [ColossalAI](https://github.com/hpcaitech/ColossalAI) | An integrated large-scale model training system with efficient parallelization techniques. |  | | [DeepSpeed](https://github.com/microsoft/DeepSpeed) | DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective. |  | | [Horovod](https://github.com/horovod/horovod) | Distributed training framework for TensorFlow, Keras, PyTorch, and Apache MXNet. |  | | [Jax](https://github.com/google/jax) | Autograd and XLA for high-performance machine learning research. |  | | [Kedro](https://github.com/kedro-org/kedro) | Kedro is an open-source Python framework for creating reproducible, maintainable and modular data science code. |  | | [Keras](https://github.com/keras-team/keras) | Keras is a deep learning API written in Python, running on top of the machine learning platform TensorFlow. |  | | [LightGBM](https://github.com/microsoft/LightGBM) | A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks. |  | | [MegEngine](https://github.com/MegEngine/MegEngine) | MegEngine is a fast, scalable and easy-to-use deep learning framework, with auto-differentiation. |  | | [metric-learn](https://github.com/scikit-learn-contrib/metric-learn) | Metric Learning Algorithms in Python. |  | | [MindSpore](https://github.com/mindspore-ai/mindspore) | MindSpore is a new open source deep learning training/inference framework that could be used for mobile, edge and cloud scenarios. |  | | [Oneflow](https://github.com/Oneflow-Inc/oneflow) | OneFlow is a performance-centered and open-source deep learning framework. |  | | [PaddlePaddle](https://github.com/PaddlePaddle/Paddle) | Machine Learning Framework from Industrial Practice. |  | | [PyTorch](https://github.com/pytorch/pytorch) | Tensors and Dynamic neural networks in Python with strong GPU acceleration. |  | | [PyTorch Lightning](https://github.com/lightning-AI/lightning) | Deep learning framework to train, deploy, and ship AI products Lightning fast. |  | | [XGBoost](https://github.com/dmlc/xgboost) | Scalable, Portable and Distributed Gradient Boosting (GBDT, GBRT or GBM) Library. |  | | [scikit-learn](https://github.com/scikit-learn/scikit-learn) | Machine Learning in Python. |  | | [TensorFlow](https://github.com/tensorflow/tensorflow) | An Open Source Machine Learning Framework for Everyone. |  | | [VectorFlow](https://github.com/Netflix/vectorflow) | A minimalist neural network library optimized for sparse data and single machine environments. |  | **[⬆ back to ToC](#table-of-contents)** ### Experiment Tracking | Project | Details | Repository | |---|---|---| | [Aim](https://github.com/aimhubio/aim) | an easy-to-use and performant open-source experiment tracker. |  | | [ClearML](https://github.com/allegroai/clearml) | Auto-Magical CI/CD to streamline your ML workflow. Experiment Manager, MLOps and Data-Management |  | | [Comet](https://github.com/comet-ml/comet-examples) | Comet is an MLOps platform that offers experiment tracking, model production management, a model registry, and full data lineage from training straight through to production. Comet plays nicely with all your favorite tools, so you don't have to change your existing workflow. Check out CometLLM for all your prompt engineering needs! |  | | [Guild AI](https://github.com/guildai/guildai) | Experiment tracking, ML developer tools. |  | | [MLRun](https://github.com/mlrun/mlrun) | Machine Learning automation and tracking. |  | | [Kedro-Viz](https://github.com/kedro-org/kedro-viz) | Kedro-Viz is an interactive development tool for building data science pipelines with Kedro. Kedro-Viz also allows users to view and compare different runs in the Kedro project. |  | | [LabNotebook](https://github.com/henripal/labnotebook) | LabNotebook is a tool that allows you to flexibly monitor, record, save, and query all your machine learning experiments. |  | | [Sacred](https://github.com/IDSIA/sacred) | Sacred is a tool to help you configure, organize, log and reproduce experiments. |  | | [Weights & Biases](https://github.com/wandb/wandb) | A developer first, lightweight, user-friendly experiment tracking and visualization tool for machine learning projects, streamlining collaboration and simplifying MLOps. W&B excels at tracking LLM-powered applications, featuring W&B Prompts for LLM execution flow visualization, input and output monitoring, and secure management of prompts and LLM chain configurations. |  | **[⬆ back to ToC](#table-of-contents)** ### Visualization | Project | Details | Repository | |---|---|---| | [Fiddler AI](https://github.com/fiddler-labs) | Rich dashboards, reports, and UMAP to perform root cause analysis, pinpoint problem areas, like correctness, safety, and privacy issues, and improve LLM outcomes. | | | [Maniford](https://github.com/uber/manifold) | A model-agnostic visual debugging tool for machine learning. |  | | [netron](https://github.com/lutzroeder/netron) | Visualizer for neural network, deep learning, and machine learning models. |  | | [OpenOps](https://github.com/ThePlugJumbo/openops) | Bring multiple data streams into one dashboard. |  | | [TensorBoard](https://github.com/tensorflow/tensorboard) | TensorFlow's Visualization Toolkit. |  | | [TensorSpace](https://github.com/tensorspace-team/tensorspace) | Neural network 3D visualization framework, build interactive and intuitive model in browsers, support pre-trained deep learning models from TensorFlow, Keras, TensorFlow.js. |  | | [dtreeviz](https://github.com/parrt/dtreeviz) | A python library for decision tree visualization and model interpretation. |  | | [Zetane Viewer](https://github.com/zetane/viewer) | ML models and internal tensors 3D visualizer. |  | | [Zeno](https://github.com/zeno-ml/zeno) | AI evaluation platform for interactively exploring data and model outputs. |  | ### Model Editing | Project | Details | Repository | |---|---|---| | [FastEdit](https://github.com/hiyouga/FastEdit) | FastEdit aims to assist developers with injecting fresh and customized knowledge into large language models efficiently using one single command. |  | **[⬆ back to ToC](#table-of-contents)** ## Data ### Data Management | Project | Details | Repository | |---|---|---| | [ArtiVC](https://github.com/InfuseAI/ArtiVC) | A version control system to manage large files. Lake is a dataset format with a simple API for creating, storing, and collaborating on AI datasets of any size. |  | | [Dolt](https://github.com/dolthub/dolt) | Git for Data. |  | | [DVC](https://github.com/iterative/dvc) | Data Version Control - Git for Data & Models - ML Experiments Management. |  | | [Delta-Lake](https://github.com/delta-io/delta) | Storage layer that brings scalable, ACID transactions to Apache Spark and other engines. |  | | [Pachyderm](https://github.com/pachyderm/pachyderm) | Pachyderm is a version control system for data. |  | | [Quilt](https://github.com/quiltdata/quilt) | A self-organizing data hub for S3. |  | **[⬆ back to ToC](#table-of-contents)** ### Data Storage | Project | Details | Repository | |---|---|---| | [JuiceFS](https://github.com/juicedata/juicefs) | A distributed POSIX file system built on top of Redis and S3. |  | | [LakeFS](https://github.com/treeverse/lakeFS) | Git-like capabilities for your object storage. |  | | [Lance](https://github.com/eto-ai/lance) | Modern columnar data format for ML implemented in Rust. |  | **[⬆ back to ToC](#table-of-contents)** ### Data Tracking | Project | Details | Repository | |---|---|---| | [Piperider](https://github.com/InfuseAI/piperider) | A CLI tool that allows you to build data profiles and write assertion tests for easily evaluating and tracking your data's reliability over time. |  | | [LUX](https://github.com/lux-org/lux) | A Python library that facilitates fast and easy data exploration by automating the visualization and data analysis process. |  | **[⬆ back to ToC](#table-of-contents)** ### Feature Engineering | Project | Details | Repository | |---|---|---| | [Featureform](https://github.com/featureform/featureform) | The Virtual Feature Store. Turn your existing data infrastructure into a feature store. |  | | [FeatureTools](https://github.com/Featuretools/featuretools) | An open source python framework for automated feature engineering |  | **[⬆ back to ToC](#table-of-contents)** ### Data/Feature enrichment | Project | Details | Repository | |---|---|---| | [Upgini](https://github.com/upgini/upgini) | Free automated data & feature enrichment library for machine learning: automatically searches through thousands of ready-to-use features from public and community shared data sources and enriches your training dataset with only the accuracy improving features |  | | [Feast](https://github.com/feast-dev/feast) | An open source feature store for machine learning. |  | **[⬆ back to ToC](#table-of-contents)** ## Large Scale Deployment ### ML Platforms | Project | Details | Repository | |---|---|---| | [Comet](https://github.com/comet-ml/comet-examples) | Comet is an MLOps platform that offers experiment tracking, model production management, a model registry, and full data lineage from training straight through to production. Comet plays nicely with all your favorite tools, so you don't have to change your existing workflow. Check out CometLLM for all your prompt engineering needs! |  | | [ClearML](https://github.com/allegroai/clearml) | Auto-Magical CI/CD to streamline your ML workflow. Experiment Manager, MLOps and Data-Management. |  | | [Hopsworks](https://github.com/logicalclocks/hopsworks) | Hopsworks is a MLOps platform for training and operating large and small ML systems, including fine-tuning and serving LLMs. Hopsworks includes both a feature store and vector database for RAG. |  | | [OpenLLM](https://github.com/bentoml/OpenLLM) | An open platform for operating large language models (LLMs) in production. Fine-tune, serve, deploy, and monitor any LLMs with ease. |  | | [MLflow](https://github.com/mlflow/mlflow) | Open source platform for the machine learning lifecycle. |  | | [MLRun](https://github.com/mlrun/mlrun) | An open MLOps platform for quickly building and managing continuous ML applications across their lifecycle. |  | | [ModelFox](https://github.com/modelfoxdotdev/modelfox) | ModelFox is a platform for managing and deploying machine learning models. |  | | [Kserve](https://github.com/kserve/kserve) | Standardized Serverless ML Inference Platform on Kubernetes |  | | [Kubeflow](https://github.com/kubeflow/kubeflow) | Machine Learning Toolkit for Kubernetes. |  | | [PAI](https://github.com/microsoft/pai) | Resource scheduling and cluster management for AI. |  | | [Polyaxon](https://github.com/polyaxon/polyaxon) | Machine Learning Management & Orchestration Platform. |  | | [Primehub](https://github.com/InfuseAI/primehub) | An effortless infrastructure for machine learning built on the top of Kubernetes. |  | | [OpenModelZ](https://github.com/tensorchord/openmodelz) | One-click machine learning deployment (LLM, text-to-image and so on) at scale on any cluster (GCP, AWS, Lambda labs, your home lab, or even a single machine). |  | | [Seldon-core](https://github.com/SeldonIO/seldon-core) | An MLOps framework to package, deploy, monitor and manage thousands of production machine learning models |  | | [Starwhale](https://github.com/star-whale/starwhale) | An MLOps/LLMOps platform for model building, evaluation, and fine-tuning. |  | | [TrueFoundry](https://truefoundry.com/llmops) | A PaaS to deploy, Fine-tune and serve LLM Models on a company’s own Infrastructure with Data Security and Optimal GPU and Cost Management. Launch your LLM Application at Production scale with best DevSecOps practices. | | | [Weights & Biases](https://github.com/wandb/wandb) | A lightweight and flexible platform for machine learning experiment tracking, dataset versioning, and model management, enhancing collaboration and streamlining MLOps workflows. W&B excels at tracking LLM-powered applications, featuring W&B Prompts for LLM execution flow visualization, input and output monitoring, and secure management of prompts and LLM chain configurations. |  | **[⬆ back to ToC](#table-of-contents)** ### Workflow | Project | Details | Repository | |---|---|---| | [Airflow](https://airflow.apache.org/) | A platform to programmatically author, schedule and monitor workflows. |  | | [aqueduct](https://github.com/aqueducthq/aqueduct) | An Open-Source Platform for Production Data Science |  | | [Argo Workflows](https://github.com/argoproj/argo-workflows) | Workflow engine for Kubernetes. |  | | [Flyte](https://github.com/flyteorg/flyte) | Kubernetes-native workflow automation platform for complex, mission-critical data and ML processes at scale. |  | | [Hamilton](https://github.com/dagworks-inc/hamilton) | A lightweight framework to represent ML/language model pipelines as a series of python functions. |  | | [Kubeflow Pipelines](https://github.com/kubeflow/pipelines) | Machine Learning Pipelines for Kubeflow. |  | | [LangFlow](https://github.com/logspace-ai/langflow) | An effortless way to experiment and prototype LangChain flows with drag-and-drop components and a chat interface. |  | | [Metaflow](https://github.com/Netflix/metaflow) | Build and manage real-life data science projects with ease! |  | | [Ploomber](https://github.com/ploomber/ploomber) | The fastest way to build data pipelines. Develop iteratively, deploy anywhere. |  | | [Prefect](https://github.com/PrefectHQ/prefect) | The easiest way to automate your data. |  | | [VDP](https://github.com/instill-ai/vdp) | An open-source unstructured data ETL tool to streamline the end-to-end unstructured data processing pipeline. |  | | [ZenML](https://github.com/zenml-io/zenml) | MLOps framework to create reproducible pipelines. |  | **[⬆ back to ToC](#table-of-contents)** ### Scheduling | Project | Details | Repository | |---|---|---| | [Kueue](https://github.com/kubernetes-sigs/kueue) | Kubernetes-native Job Queueing. |  | | [PAI](https://github.com/microsoft/pai) | Resource scheduling and cluster management for AI (Open-sourced by Microsoft). |  | | [Slurm](https://github.com/SchedMD/slurm) | A Highly Scalable Workload Manager. |  | | [Volcano](https://github.com/volcano-sh/volcano) | A Cloud Native Batch System (Project under CNCF). |  | | [Yunikorn](https://github.com/apache/yunikorn-core) | Light-weight, universal resource scheduler for container orchestrator systems. |  | **[⬆ back to ToC](#table-of-contents)** ### Model Management | Project | Details | Repository | |---|---|---| | [Comet](https://github.com/comet-ml/comet-examples) | Comet is an MLOps platform that offers Model Production Management, a Model Registry, and full model lineage from training straight through to production. Use Comet for model reproducibility, model debugging, model versioning, model visibility, model auditing, model governance, and model monitoring. |  | | [dvc](https://github.com/iterative/dvc) | ML Experiments Management - Data Version Control - Git for Data & Models |  | | [ModelDB](https://github.com/VertaAI/modeldb) | Open Source ML Model Versioning, Metadata, and Experiment Management |  | | [MLEM](https://github.com/iterative/mlem) | A tool to package, serve, and deploy any ML model on any platform. |  | | [ormb](https://github.com/kleveross/ormb) | Docker for Your ML/DL Models Based on OCI Artifacts |  | **[⬆ back to ToC](#table-of-contents)** ## Performance ### ML Compiler | Project | Details | Repository | |---|---|---| | [ONNX-MLIR](https://github.com/onnx/onnx-mlir) | Compiler technology to transform a valid Open Neural Network Exchange (ONNX) graph into code that implements the graph with minimum runtime support. |  | | [TVM](https://github.com/apache/tvm) | Open deep learning compiler stack for cpu, gpu and specialized accelerators |  | **[⬆ back to ToC](#table-of-contents)** ### Profiling | Project | Details | Repository | |---|---|---| | [octoml-profile](https://github.com/octoml/octoml-profile) | octoml-profile is a python library and cloud service designed to provide the simplest experience for assessing and optimizing the performance of PyTorch models on cloud hardware with state-of-the-art ML acceleration technology. |  | | [scalene](https://github.com/plasma-umass/scalene) | a high-performance, high-precision CPU, GPU, and memory profiler for Python |  | **[⬆ back to ToC](#table-of-contents)** ## AutoML | Project | Details | Repository | |---|---|---| | [Archai](https://github.com/microsoft/archai) | a platform for Neural Network Search (NAS) that allows you to generate efficient deep networks for your applications. |  | | [autoai](https://github.com/blobcity/autoai) | A framework to find the best performing AI/ML model for any AI problem. |  | | [AutoGL](https://github.com/THUMNLab/AutoGL) | An autoML framework & toolkit for machine learning on graphs |  | | [AutoGluon](https://github.com/awslabs/autogluon) | AutoML for Image, Text, and Tabular Data. |  | | [automl-gs](https://github.com/minimaxir/automl-gs) | Provide an input CSV and a target field to predict, generate a model + code to run it. |  | | [autokeras](https://github.com/keras-team/autokeras) | AutoML library for deep learning. |  | | [Auto-PyTorch](https://github.com/automl/Auto-PyTorch) | Automatic architecture search and hyperparameter optimization for PyTorch. |  | | [auto-sklearn](https://github.com/automl/auto-sklearn) | an automated machine learning toolkit and a drop-in replacement for a scikit-learn estimator. |  | | [Dragonfly](https://github.com/dragonfly/dragonfly) | An open source python library for scalable Bayesian optimisation. |  | | [Determined](https://github.com/determined-ai/determined) | scalable deep learning training platform with integrated hyperparameter tuning support; includes Hyperband, PBT, and other search methods. |  | | [DEvol (DeepEvolution)](https://github.com/joeddav/devol) | a basic proof of concept for genetic architecture search in Keras. |  | | [EvalML](https://github.com/alteryx/evalml) | An open source python library for AutoML. |  | | [FEDOT](https://github.com/nccr-itmo/FEDOT) | AutoML framework for the design of composite pipelines. |  | | [FLAML](https://github.com/microsoft/FLAML) | Fast and lightweight AutoML ([paper](https://www.microsoft.com/en-us/research/publication/flaml-a-fast-and-lightweight-automl-library/)). |  | | [Goptuna](https://github.com/c-bata/goptuna) | A hyperparameter optimization framework, inspired by Optuna. |  | | [HpBandSter](https://github.com/automl/HpBandSter) | a framework for distributed hyperparameter optimization. |  | | [HPOlib2](https://github.com/automl/HPOlib2) | a library for hyperparameter optimization and black box optimization benchmarks. |  | | [Hyperband](https://github.com/zygmuntz/hyperband) | open source code for tuning hyperparams with Hyperband. |  | | [Hypernets](https://github.com/DataCanvasIO/Hypernets) | A General Automated Machine Learning Framework. |  | | [Hyperopt](https://github.com/hyperopt/hyperopt) | Distributed Asynchronous Hyperparameter Optimization in Python. |  | | [hyperunity](https://github.com/gdikov/hypertunity) | A toolset for black-box hyperparameter optimisation. |  | | [Intelli](https://github.com/intelligentnode/Intelli) | A framework to connect a flow of ML models by applying graph theory. |  | | [Katib](https://github.com/kubeflow/katib) | Katib is a Kubernetes-native project for automated machine learning (AutoML). |  | | [Keras Tuner](https://github.com/keras-team/keras-tuner) | Hyperparameter tuning for humans. |  | | [learn2learn](https://github.com/learnables/learn2learn) | PyTorch Meta-learning Framework for Researchers. |  | | [Ludwig](https://github.com/uber/ludwig) | a toolbox built on top of TensorFlow that allows to train and test deep learning models without the need to write code. |  | | [MOE](https://github.com/Yelp/MOE) | a global, black box optimization engine for real world metric optimization by Yelp. |  | | [Model Search](https://github.com/google/model_search) | a framework that implements AutoML algorithms for model architecture search at scale. |  | | [NASGym](https://github.com/gomerudo/nas-env) | a proof-of-concept OpenAI Gym environment for Neural Architecture Search (NAS). |  | | [NNI](https://github.com/Microsoft/nni) | An open source AutoML toolkit for automate machine learning lifecycle, including feature engineering, neural architecture search, model compression and hyper-parameter tuning. |  | | [Optuna](https://github.com/optuna/optuna) | A hyperparameter optimization framework. |  | | [Pycaret](https://github.com/pycaret/pycaret) | An open-source, low-code machine learning library in Python that automates machine learning workflows. |  | | [Ray Tune](github.com/ray-project/ray) | Scalable Hyperparameter Tuning. |  | | [REMBO](https://github.com/ziyuw/rembo) | Bayesian optimization in high-dimensions via random embedding. |  | | [RoBO](https://github.com/automl/RoBO) | a Robust Bayesian Optimization framework. |  | | [scikit-optimize(skopt)](https://github.com/scikit-optimize/scikit-optimize) | Sequential model-based optimization with a `scipy.optimize` interface. |  | | [Spearmint](https://github.com/HIPS/Spearmint) | a software package to perform Bayesian optimization. |  | | [TPOT](http://automl.info/tpot/) | one of the very first AutoML methods and open-source software packages. |  | | [Torchmeta](https://github.com/tristandeleu/pytorch-meta) | A Meta-Learning library for PyTorch. |  | | [Vegas](https://github.com/huawei-noah/vega) | an AutoML algorithm tool chain by Huawei Noah's Arb Lab. |  | **[⬆ back to ToC](#table-of-contents)** ## Optimizations | Project | Details | Repository | |---|---|---| | [FeatherCNN](https://github.com/Tencent/FeatherCNN) | FeatherCNN is a high performance inference engine for convolutional neural networks. |  | | [Forward](https://github.com/Tencent/Forward) | A library for high performance deep learning inference on NVIDIA GPUs. |  | | [NCNN](https://github.com/Tencent/ncnn) | ncnn is a high-performance neural network inference framework optimized for the mobile platform. |  | | [PocketFlow](https://github.com/Tencent/PocketFlow) | use AutoML to do model compression. |  | | [TensorFlow Model Optimization](https://github.com/tensorflow/model-optimization) | A suite of tools that users, both novice and advanced, can use to optimize machine learning models for deployment and execution. |  | | [TNN](https://github.com/Tencent/TNN) | A uniform deep learning inference framework for mobile, desktop and server. |  | **[⬆ back to ToC](#table-of-contents)** ## Federated ML | Project | Details | Repository | |---|---|---| | [EasyFL](https://github.com/EasyFL-AI/EasyFL) | An Easy-to-use Federated Learning Platform |  | | [FATE](https://github.com/FederatedAI/FATE) | An Industrial Grade Federated Learning Framework |  | | [FedML](https://github.com/FedML-AI/FedML) | The federated learning and analytics library enabling secure and collaborative machine learning on decentralized data anywhere at any scale. Supporting large-scale cross-silo federated learning, cross-device federated learning on smartphones/IoTs, and research simulation. |  | | [Flower](https://github.com/adap/flower) | A Friendly Federated Learning Framework |  | | [Harmonia](https://github.com/ailabstw/harmonia) | Harmonia is an open-source project aiming at developing systems/infrastructures and libraries to ease the adoption of federated learning (abbreviated to FL) for researches and production usage. |  | | [TensorFlow Federated](https://github.com/tensorflow/federated) | A framework for implementing federated learning |  | **[⬆ back to ToC](#table-of-contents)** ## Awesome Lists | Project | Details | Repository | |---|---|---| | [Awesome Argo](https://github.com/terrytangyuan/awesome-argo) | A curated list of awesome projects and resources related to Argo |  | | [Awesome AutoDL](https://github.com/D-X-Y/Awesome-AutoDL) | Automated Deep Learning: Neural Architecture Search Is Not the End (a curated list of AutoDL resources and an in-depth analysis) |  | | [Awesome AutoML](https://github.com/windmaple/awesome-AutoML) | Curating a list of AutoML-related research, tools, projects and other resources |  | | [Awesome AutoML Papers](https://github.com/hibayesian/awesome-automl-papers) | A curated list of automated machine learning papers, articles, tutorials, slides and projects |  | | [Awesome-Code-LLM](https://github.com/huybery/Awesome-Code-LLM) | 👨‍💻 An awesome and curated list of best code-LLM for research. |  | | [Awesome Federated Learning Systems](https://github.com/AmberLJC/FLsystem-paper/blob/main/README.md) | A curated list of Federated Learning Systems related academic papers, articles, tutorials, slides and projects. |  | | [Awesome Federated Learning](https://github.com/chaoyanghe/Awesome-Federated-Learning) | A curated list of federated learning publications, re-organized from Arxiv (mostly) |  | | [awesome-federated-learning](https://github.com/weimingwill/awesome-federated-learning)acc | All materials you need for Federated Learning: blogs, videos, papers, and softwares, etc. |  | | [Awesome Open MLOps](https://github.com/fuzzylabs/awesome-open-mlops) | This is the Fuzzy Labs guide to the universe of free and open source MLOps tools. |  | | [Awesome Production Machine Learning](https://github.com/EthicalML/awesome-production-machine-learning) | A curated list of awesome open source libraries to deploy, monitor, version and scale your machine learning |  | | [Awesome Tensor Compilers](https://github.com/merrymercy/awesome-tensor-compilers) | A list of awesome compiler projects and papers for tensor computation and deep learning. |  | | [kelvins/awesome-mlops](https://github.com/kelvins/awesome-mlops) | A curated list of awesome MLOps tools. |  | | [visenger/awesome-mlops](https://github.com/visenger/awesome-mlops) | Machine Learning Operations - An awesome list of references for MLOps |  | | [currentslab/awesome-vector-search](https://github.com/currentslab/awesome-vector-search) | A curated list of awesome vector search framework/engine, library, cloud service and research papers to vector similarity search. |  | | [pleisto/flappy](https://github.com/pleisto/flappy) | Production-Ready LLM Agent SDK for Every Developer |  | **[⬆ back to ToC](#table-of-contents)**

An awesome & curated list of best LLMOps tools for developers

awesome-list,mlops,ai-development-tools,llmops

riti2409/Resources-for-preparation-Of-Placements

# Resources-for-preparation-Of-Placements (Lecture video links) **Programming Language Used : C** - [Programming in C](https://www.youtube.com/playlist?list=PLu0W_9lII9aiXlHcLx-mDH1Qul38wD3aR) - [DS-ALGO](https://www.youtube.com/playlist?list=PLu0W_9lII9ahIappRPN0MCAgtOu3lQjQi) - [Analysis of Algorithms](https://www.youtube.com/playlist?list=PLDN4rrl48XKpZkf03iYFl-O29szjTrs_O) <hr> **Programming Language Used : C++** - [Programming in C++](https://www.youtube.com/playlist?list=PLu0W_9lII9agpFUAlPFe_VNSlXW5uE0YL) - [ARRAYS](https://www.youtube.com/playlist?list=PLDdcY4olLQk3zG-972eMoDJHLIz3FiGA6) - [STRING](https://www.youtube.com/playlist?list=PLDdcY4olLQk0A0o2U0fOUjmO2v3X6GOxX) - [BINARY SEARCH](https://www.youtube.com/playlist?list=PL_z_8CaSLPWeYfhtuKHj-9MpYb6XQJ_f2) - [Dynamic Programming](https://whimsical.com/dp-sheet-by-love-babbar-EELKgSMWg51ypLyfn9mTjr) - [Aditya Verma](https://www.youtube.com/playlist?list=PL_z_8CaSLPWekqhdCPmFohncHwz8TY2Go) - [TakeuForward](https://www.youtube.com/playlist?list=PLgUwDviBIf0qUlt5H_kiKYaNSqJ81PMMY) - [STACK](https://www.youtube.com/playlist?list=PL_z_8CaSLPWdeOezg68SKkeLN4-T_jNHd) - [HEAP](https://www.youtube.com/playlist?list=PL_z_8CaSLPWdtY9W22VjnPxG30CXNZpI9) - [SLIDING WINDOW](https://www.youtube.com/playlist?list=PL_z_8CaSLPWeM8BDJmIYDaoQ5zuwyxnfj) - [RECURSION , BACKTRACKING](https://www.youtube.com/playlist?list=PLgUwDviBIf0rGlzIn_7rsaR2FQ5e6ZOL9) - [TREES](https://www.youtube.com/playlist?list=PLgUwDviBIf0q8Hkd7bK2Bpryj2xVJk8Vk) - [GRAPHS](https://www.youtube.com/playlist?list=PLgUwDviBIf0rGEWe64KWas0Nryn7SCRWw) - [LINKEDLIST](https://www.youtube.com/playlist?list=PLKZaSt2df1gz775Mz-2gLpY9sld5wH8We) - [TRIE](https://www.youtube.com/playlist?list=PLgUwDviBIf0pcIDCZnxhv0LkHf5KzG9zp) - [SEGMENT TREE](https://www.youtube.com/watch?v=SzLf8DvwIxI&ab_channel=CodeBuddyOfficial) - [STL](https://www.youtube.com/playlist?list=PLhUBmaJES_g-41r_z-kMGWqQ4Iz-z7Oyo) - [HASHING](https://youtube.com/playlist?list=PLzjZaW71kMwQ-D3oxCEDHAvYu8VC1XOsS) - [COMPETITIVE PROGRAMMING](https://www.youtube.com/playlist?list=PLauivoElc3ggagradg8MfOZreCMmXMmJ-) - [CodeWithTwins](https://www.youtube.com/playlist?list=PL2ZC2yNuZ0DWaXlMWSOaR61nAFWDqgQ0Z) <hr> **Programming Language Used : JAVA** - [Programming in JAVA](https://www.youtube.com/playlist?list=PLu0W_9lII9agS67Uits0UnJyrYiXhDS6q) - Data Structure and Algorithams - [Kunal Kushwaha](https://www.youtube.com/playlist?list=PL9gnSGHSqcnr_DxHsP7AW9ftq0AtAyYqJ) - [Pepcoding](https://www.youtube.com/c/Pepcoding) - [Durga Sir](https://youtube.com/playlist?list=PLd3UqWTnYXOmx_J1774ukG_rvrpyWczm0) - [Anuj Bhaiya](https://www.youtube.com/playlist?list=PLUcsbZa0qzu3yNzzAxgvSgRobdUUJvz7p) <hr> **Programming Language Used : Python** - [Programming in Python](https://www.youtube.com/playlist?list=PLu0W_9lII9agICnT8t4iYVSZ3eykIAOME) - [DSA in Python](https://youtu.be/pkYVOmU3MgA) - [DS-ALGO](https://www.youtube.com/playlist?list=PLzgPDYo_3xukPJdH6hVQ6Iic7KiJuoA-l) - [Tech With Tim](https://www.youtube.com/c/TechWithTim) - [Python Engineer](https://www.youtube.com/c/PythonEngineer) <hr> **Placement Series** - [C++](https://www.youtube.com/playlist?list=PLDzeHZWIZsTryvtXdMr6rPh4IDexB5NIA) - [JAVA](https://www.youtube.com/playlist?list=PL9gnSGHSqcnr_DxHsP7AW9ftq0AtAyYqJ) - [JAVA](https://www.pepcoding.com/resources/) - [PYTHON](https://www.youtube.com/playlist?list=PLqcJACtjWm_Xk_9rMh4lQLOfW2E6SAxsF) <hr> **Computer Science Fundamentals** - [DataBase and Management System (DBMS)](https://www.youtube.com/playlist?list=PLxCzCOWd7aiFAN6I8CuViBuCdJgiOkT2Y) - [Operating System (OS)](https://www.youtube.com/playlist?list=PLxCzCOWd7aiGz9donHRrE9I3Mwn6XdP8p) - [Computer Networks (CN)](https://www.youtube.com/playlist?list=PLxCzCOWd7aiGFBD2-2joCpWOLUrDLvVV_) - Object Oriented Programming System (OOPS) - [Java](https://www.youtube.com/watch?v=bSrm9RXwBaI&ab_channel=ApnaCollege) - [C++](https://www.youtube.com/watch?v=wN0x9eZLix4&ab_channel=freeCodeCamp.org) - [Python](https://www.youtube.com/watch?v=qiSCMNBIP2g&ab_channel=Telusko) - [Theory Of Computation (THOC)](https://www.youtube.com/playlist?list=PLBlnK6fEyqRgp46KUv4ZY69yXmpwKOIev) - [Software Engineering (SE)](https://www.youtube.com/playlist?list=PLxCzCOWd7aiEed7SKZBnC6ypFDWYLRvB2) <hr> **Designing** - SYSTEM DESIGN - [Gaurav Sen](https://www.youtube.com/playlist?list=PLMCXHnjXnTnvo6alSjVkgxV-VH6EPyvoX) - [SudoCode](https://www.youtube.com/playlist?list=PLTCrU9sGyburBw9wNOHebv9SjlE4Elv5a) - [Whatsapp System Desgin](https://www.youtube.com/watch?v=LsH-t75P544) - [Instagram Design](https://www.youtube.com/watch?v=QmX2NPkJTKg) - [TikTok Architechture Design](https://www.youtube.com/watch?v=07BVxmVFDGY) - [Tinder System Design](https://www.youtube.com/watch?v=tndzLznxq40) - [System Design of Amazon, Flipkart like E-commerce](https://www.youtube.com/watch?v=2BWr0fsDSs0) - [Mock Low Level Design Interview](https://www.youtube.com/watch?v=J-4UQ_WpMtc) - [High Level Design vs Low Level Design](https://www.youtube.com/watch?v=H703ErIrby8) - [low Level Design of a Fitness App](https://www.youtube.com/watch?v=7-A5NgGrJqY) - [Mock Low Level Design Interview](https://www.youtube.com/watch?v=cqxowa0JbpI) - LOW LEVEL DESIGN - [Soumyajit bhattacharya](https://www.youtube.com/playlist?list=PL12BCqE-Lp650Cg6FZW7SoZwN8Rw1WJI7) - [Sandeep Kaul](https://www.codekarle.com/) - [Crack the System DesigN Interview](https://tianpan.co/notes/2016-02-13-crack-the-system-design-interview) - [System Design Interview — Alex Xu](https://www.amazon.com/System-Design-Interview-Insiders-Guide-ebook/dp/B08B3FWYBX/) - [Designing Data Intensive Applications](https://www.amazon.com/Designing-Data-Intensive-Applications-Reliable-Maintainable-ebook/dp/B06XPJML5D/) - [System Design Interview](https://github.com/checkcheckzz/system-design-interview) - [System Design](https://github.com/shashank88/system_design) - [Services Engineering](https://github.com/mmcgrana/services-engineering) - [Engineering Blogs](https://github.com/kilimchoi/engineering-blogs) - [LLD Coding](https://lldcoding.com) <hr> **Git and Github** - [Git and GitHub for Poets](https://www.youtube.com/playlist?list=PLRqwX-V7Uu6ZF9C0YMKuns9sLDzK6zoiV) <hr> **Projects** - [WEB DEVELOPMENT](https://www.youtube.com/playlist?list=PLu0W_9lII9agiCUZYRsvtGTXdxkzPyItg) - [DATA SCIENCE](https://www.youtube.com/playlist?list=PLu0W_9lII9agK8pojo23OHiNz3Jm6VQCH) - [MACHINE LEARNING](https://www.youtube.com/playlist?list=PLu0W_9lII9ai6fAMHp-acBmJONT7Y4BSG) **ADD- ONS** - [leetcode-patterns](https://github.com/seanprashad/leetcode-patterns) - [Coding-Interview-Patterns](https://github.com/ShrutiSharma01/Grokking-the-Coding-Interview-Patterns) - [Bootcamp-Java](https://github.com/kunal-kushwaha/DSA-Bootcamp-Java) - [Data science intern course](https://www.youtube.com/playlist?list=PL7zl8TDRnbul57eQ-8R5r9h1028aLoQXT) - [Spring Boot](https://www.youtube.com/watch?v=35EQXmHKZYs&ab_channel=Telusko) - [Unity Game Development](https://www.youtube.com/watch?v=j48LtUkZRjU&list=PLPV2KyIb3jR53Jce9hP7G5xC4O9AgnOuL) You can add more in this list . Lets help the community !

Lecture video links for preparation of Placements

arrays-and-strings,linkedlist,heap,dsa-algorithm,dsa,graph,c

piitaya/lovelace-mushroom

# 🍄 Mushroom [![hacs][hacs-badge]][hacs-url] [![release][release-badge]][release-url] ![downloads][downloads-badge] ![build][build-badge] <a href="https://www.buymeacoffee.com/piitaya" target="_blank"><img src="https://www.buymeacoffee.com/assets/img/custom_images/white_img.png" alt="Buy Me A Coffee" style="height: auto !important;width: auto !important;" ></a>  ## What is mushroom ? Mushroom is a collection of cards for [Home Assistant][home-assistant] Dashboard UI. Mushroom mission is to propose easy to use components to build your [Home Assistant][home-assistant] dashboard. ### Features - 🛠 Editor for **all cards** and and **all options** (no need to edit `yaml`) - 😍 Icon picker - 🖌 Color picker - 🚀 0 dependencies : no need to install another card. - 🌈 Based on Material UI colors - 🌓 Light and dark theme support - 🎨 Optional theme customization - 🌎 Internationalization The goal of Mushroom is not to provide custom card for deep customization. You can use the excellent [UI Lovelace Minimalist][ui-lovelace-minimalist] and [Button card][button-card] plugins for this. ## Installation ### HACS Mushroom is available in [HACS][hacs] (Home Assistant Community Store). 1. Install HACS if you don't have it already 2. Open HACS in Home Assistant 3. Go to "Frontend" section 4. Click button with "+" icon 5. Search for "Mushroom" ### Manual 1. Download `mushroom.js` file from the [latest release][release-url]. 2. Put `mushroom.js` file into your `config/www` folder. 3. Add reference to `mushroom.js` in Dashboard. There's two way to do that: - **Using UI:** _Settings_ → _Dashboards_ → _More Options icon_ → _Resources_ → _Add Resource_ → Set _Url_ as `/local/mushroom.js` → Set _Resource type_ as `JavaScript Module`. **Note:** If you do not see the Resources menu, you will need to enable _Advanced Mode_ in your _User Profile_ - **Using YAML:** Add following code to `lovelace` section. ```yaml resources: - url: /local/mushroom.js type: module ``` ## Usage All the Mushroom cards can be configured using Dashboard UI editor. 1. In Dashboard UI, click 3 dots in top right corner. 2. Click _Edit Dashboard_. 3. Click Plus button to add a new card. 4. Find one of the _Custom: Mushroom_ card in the list. ### Cards Different cards are available for differents entities : - 🚨 [Alarm card](docs/cards/alarm-control-panel.md) - 🪟 [Cover card](docs/cards/cover.md) - 🪄 [Entity card](docs/cards/entity.md) - 💨 [Fan card](docs/cards/fan.md) - 💡 [Light card](docs/cards/light.md) - 🙋 [Person card](docs/cards/person.md) - 🛠 [Template card](docs/cards/template.md) - 🔔 [Chips card](docs/cards/chips.md) - ✏️ [Title card](docs/cards/title.md) - 📦 [Update card](docs/cards/update.md) - 🧹 [Vacuum card](docs/cards/vacuum.md) - 📺 [Media card](docs/cards/media-player.md) - 🔒 [Lock card](docs/cards/lock.md) - 💧 [Humidifier card](docs/cards/humidifier.md) - 🌡 [Climate card](docs/cards/climate.md) - 📑 [Select card](docs/cards/select.md) - 🔢 [Number card](docs/cards/number.md) ### Theme customization Mushroom works without theme but you can add a theme for better experience by installing the [Mushroom Themes](https://github.com/piitaya/lovelace-mushroom-themes). If you want more information about themes, check out the official [Home Assistant documentation about themes][home-assitant-theme-docs]. ## Development server ### Home assistant demo You can run a demo instance of Home Assistant with docker by running: ```sh npm run start:hass ``` Once it's done, go to Home Assistant instance [http://localhost:8123](http://localhost:8123) and start configuration. #### Windows Users If you are on Windows, either run the above command in Powershell, or use the below if using Command Prompt: ```sh npm run start:hass-cmd ``` ### Development In another terminal, install dependencies and run development server: ```sh npm install npm start ``` Server will start on port `4000`. ### Build You can build the `mushroom.js` file in `dist` folder by running the build command. ```sh npm run build ``` ### Maintainer steps to add a new language 1. To be compatible with Home Assistant, language tags have to follow [BCP 47](https://www.rfc-editor.org/info/bcp47). A list of most language tags can be found here: [IANA subtag registry](http://www.iana.org/assignments/language-subtag-registry/language-subtag-registry). Examples: `fr`, `fr-CA`, `zh-Hans`. 2. Create a new file `{language_code}.json` with your language code in the [translation folder](https://github.com/piitaya/lovelace-mushroom/tree/main/src/translations). Examples: `fr.json`. 3. Import your file into the [`localize.ts file`](https://github.com/piitaya/lovelace-mushroom/blob/main/src/localize.ts) and add your language in the `languages` record. 4. Don't forget to test locally with the development server by choosing the language with the Home Assistant UI in your profile. ## Troubleshooting ### I don't see the last changes 1. Check that your Home Assistant version is the latest. Some new Mushroom features can only be visible for the latest Home Assistant version. 2. Check that you have the latest Mushroom version 3. Clear your cache : - delete mushroom resources (https://my.home-assistant.io/redirect/lovelace_resources/) - uninstall Mushroom from HACS - reinstall Mushroom from HACS ### My card mod configuration doesn't work. Help about card mod configuration is not provided in this repository. More info in the [state of card mod support](https://github.com/piitaya/lovelace-mushroom/issues/1366). ## Credits The design is inspired by [7ahang’s work][7ahang] on Behance and [Ui Lovelace Minimalist][ui-lovelace-minimalist]. <!-- Badges --> [hacs-url]: https://github.com/hacs/integration [hacs-badge]: https://img.shields.io/badge/hacs-default-orange.svg?style=flat-square [release-badge]: https://img.shields.io/github/v/release/piitaya/lovelace-mushroom?style=flat-square [downloads-badge]: https://img.shields.io/github/downloads/piitaya/lovelace-mushroom/total?style=flat-square [build-badge]: https://img.shields.io/github/actions/workflow/status/piitaya/lovelace-mushroom/build.yml?branch=main&style=flat-square <!-- References --> [home-assistant]: https://www.home-assistant.io/ [home-assitant-theme-docs]: https://www.home-assistant.io/integrations/frontend/#defining-themes [hacs]: https://hacs.xyz [ui-lovelace-minimalist]: https://ui-lovelace-minimalist.github.io/UI/ [button-card]: https://github.com/custom-cards/button-card [7ahang]: https://www.behance.net/gallery/88433905/Redesign-Smart-Home [release-url]: https://github.com/piitaya/lovelace-mushroom/releases

Build a beautiful Home Assistant dashboard easily

card,home-assistant,lovelace,mushroom,hacs,hacktoberfest

VueTubeApp/VueTube

A simple FOSS video streaming client aimed to recreate ALL features from their respective apps (and more)

android,ios,vue,vuetube,watch,youtube-video,contributions-welcome,help-wanted,hacktoberfest

Icalingua-plus-plus/Icalingua-plus-plus

# Icalingua++ Icalingua++ 是 Icalingua 的分叉，为已经删除的 Icalingua 提供有限的更新，同时欢迎社区提交PR。 Icalingua 这个名字是日语中「光」和拉丁语中「语言」的组合。 本项目希望为 Linux 打造一个会话前端框架，通过实现 Adapter 后端接口来适配各种聊天平台。目前已经拥有基于 [oicq](https://github.com/takayama-lily/oicq) 的分叉 [oicq-icalingua-plus-plus](https://github.com/Icalingua-plus-plus/oicq-icalingua-plus-plus) 以及 Icalingua 自有协议的后端。 [](https://github.com/trekhleb/state-of-the-art-shitcode) [](https://github.com/Icalingua-plus-plus/Icalingua-plus-plus/blob/develop/LICENSE) [](https://discord.gg/gKnU7BARzv) [](https://t.me/Icalinguapp) [](https://t.me/Icalinguapp_Updates) [](https://github.com/Icalingua-plus-plus/Icalingua-plus-plus/releases/latest) [](https://aur.archlinux.org/packages/icalingua++/) （感谢社区提供的 AUR Package） #### 分支状态 ##### develop [](https://github.com/Icalingua-plus-plus/Icalingua-plus-plus/actions/workflows/main.yml) [](https://github.com/takayama-lily/oicq) [](https://electronjs.org) ### 头部签名 API 可用于解决无法登录/无法发送消息的问题 **不要随意使用无法信任的 API**，因为这可能导致**消息内容的泄露** ### 常用启动参数 - 禁用硬件加速: `--dha` - 启动时隐藏主界面: `--hide` 或 `-h` - 指定配置: `--config xxx.yaml` 或 `-c xxx.yaml` - 自定义数据目录: `--user-data-dir=`$path-you-want ### 默认数据目录 | 操作系统 | 路径 | |---------|-----------------------| | Linux | `~/.config/icalingua` | | Windows | `%AppData%\icalingua` | | macOS | `~/Library/Application Support/icalingua`| ### 自定义脚本、样式、主题、插件相关 #### 自定义脚本 客户端默认会加载数据目录下的 `addon.js`，但是默认不会创建这个文件。 #### 自定义样式 客户端默认会加载数据目录下的 `style.css`，但是默认不会创建这个文件。 #### 自定义主题 此类主题为**颜色主题**，仅能修改各处的颜色表现，若需修改样式请使用**自定义样式**。 客户端默认会加载数据目录下的 `themes` 目录的所有 JSON 文件，以文件名作为主题的名字，JSON 内容可以参考客户端源码中的[默认主题文件](icalingua/src/renderer/components/vac-mod/themes/index.js)。 默认会采用 **白色 (light)** 作为基础主题，可以在 **bashTheme** 字段中指定 **light** 或者 **dark**。 ##### 参考例子（一个基于黑色主题的透明主题） themes/transparent-dark.json ``` { "baseTheme": "dark", "general": { "backgroundInput": "#20222364" }, "header": { "background": "#181a1b48" }, "footer": { "background": "#13141569", "backgroundReply": "#1b1c1c84", "backgroundTagActive": "#2b2c2c80" }, "content": { "background": "#2c2e3064" }, "message": { "background": "#22242a78", "backgroundMe": "#1f7e8064", "backgroundImage": "#dddddd40" }, "panel": { "background": "#34343484", "itemBg": "#22242a84", "itemBgHover": "#1e1e2584", "sideBar": "#41383684", "headerBg": "#181a1b1c" } } ``` style.css 配置（壁纸 background-image 自定） ``` .el-main { background-image: url(""); background-size: cover; background-repeat: no-repeat; } .vac-container-scroll { margin-top: 64px; } .el-badge__content--info { background-color: #6771856e; } .vac-box-footer input { background: #ccc6; } .el-dialog { background: #526a6bc7; } .vac-card-window a { color: #a3b8cb; } .vac-box-footer>div { backdrop-filter: blur(5px); } ``` #### 自定义插件 须在选项中勾选**启用插件**，bridge 则在配置文件中**设置 `custom` 为 `true`**。 插件为名为 custom 的目录，非 bridge 的插件存放在数据目录中，bridge 的插件目录与 data 目录同级存放。 [参考插件](https://github.com/Icalingua-plus-plus/Icalingua-plus-plus/tree/develop/icalingua-bridge-oicq/custom.example)，**此插件需使用 tsc 编译成 JavaScript 后才能使用！** 插件需使用 JavaScript 编写，且只有在接收到消息时才会调用插件导出的 `onMessage` 方法，data 与 bot 参数的使用方法请参考 [OICQ v1 的 wiki](https://github.com/takayama-lily/oicq/wiki)。若需监听其他事件可使用 `bot.on()`，理论上可以兼容使用修改后的 OICQ v1 API 的机器人框架并增加更完善的插件系统。 ### 统计 [](https://github.com/Icalingua-plus-plus/Icalingua-plus-plus/stargazers) ### License [](https://www.gnu.org/licenses/agpl-3.0.txt) ### 免责声明 本开源项目仅用于学习和交流会话前端框架实现，一切开发旨在学习，请勿用于非法用途。本项目使用 AGPL-3.0 许可，完全免费开源，不收取任何费用。请勿将本项目用于商业用途。**因使用本项目调用不同 Adapter 后端接口（如 oicq）产生的一切问题与后果由使用者自行承担，项目开发者不承担任何责任。** 本项目基于 AGPL 发行。修改、再发行和运行服务需要遵守 AGPL 许可证，源码需要和服务一起提供。

A client for QQ and more. :electron:

dair-ai/ML-Notebooks

# 🐙 Machine Learning Notebooks This repo contains machine learning notebooks for different tasks and applications. The notebooks are meant to be minimal, easily reusable, and extendable. You are free to use them for educational and research purposes. This repo supports Codespaces! - Spin up a new instance by clicking on the green `"<> Code"` button followed by the `"Configure and create codespace"` option. Make sure to select the dev container config provided with this repo. This setups an environment with all the dependencies installed and ready to go. - Once the codespace is fully running, you can install all the libraries you will need to run the notebooks under the `/notebooks` folder. Open up a terminal and simply run `conda create --name myenv --file spec-file.txt` to install all the Python libraries including PyTorch. - Activate your environment `conda activate myenv`. *You might need to run `conda init zsh` or whatever shell you are using... and then close + reopen terminal.* - Finally you can try out if everything is working by opening a notebook such as `/notebooks/bow.ipynb`. --- ## Getting Started <table class="tg"> <tr> <th class="tg-yw4l"><b>Name</b></th> <th class="tg-yw4l"><b>Description</b></th> <th class="tg-yw4l"><b>Notebook</b></th> </tr> <tr> <td class="tg-yw4l">Introduction to Computational Graphs</td> <td class="tg-yw4l">A basic tutorial to learn about computational graphs</td> <td class="tg-yw4l"><a href="https://colab.research.google.com/drive/1eG1AF36Wa0EaANandAhrsbC3j04487SH?usp=sharing"> <img src="https://colab.research.google.com/assets/colab-badge.svg" width = '' > </a></td> </tr> <tr> <td class="tg-yw4l">PyTorch Hello World!</td> <td class="tg-yw4l">Build a simple neural network and train it</td> <td class="tg-yw4l"><a href="https://colab.research.google.com/drive/1ac0K9_aa46c77XEeYtaMAfSOfmH1Bl9L?usp=sharing"> <img src="https://colab.research.google.com/assets/colab-badge.svg" width = '' > </a></td> </tr> <tr> <td class="tg-yw4l">A Gentle Introduction to PyTorch</td> <td class="tg-yw4l">A detailed explanation introducing PyTorch concepts</td> <td class="tg-yw4l"><a href="https://colab.research.google.com/drive/1K7Ks1ERaS-w4rzW_ukeBag8mYRZME1es?usp=sharing"> <img src="https://colab.research.google.com/assets/colab-badge.svg" width = '' > </a></td> </tr> <tr> <td class="tg-yw4l">Counterfactual Explanations</td> <td class="tg-yw4l">A basic tutorial to learn about counterfactual explanations for explainable AI</td> <td class="tg-yw4l"><a href="https://colab.research.google.com/drive/1mTSRjqki3VsH9MVPfNtJ5nJxcCHvL8B6?usp=sharing"> <img src="https://colab.research.google.com/assets/colab-badge.svg" width = '' > </a></td> </tr> <tr> <td class="tg-yw4l">Linear Regression from Scratch</td> <td class="tg-yw4l">An implementation of linear regression from scratch using stochastic gradient descent</td> <td class="tg-yw4l"><a href="https://colab.research.google.com/drive/1br0hM79ORTVNXUpVgkV5t4o4AigGxfwk?usp=sharing"> <img src="https://colab.research.google.com/assets/colab-badge.svg" width = '' > </a></td> </tr> <tr> <td class="tg-yw4l">Logistic Regression from Scratch</td> <td class="tg-yw4l">An implementation of logistic regression from scratch</td> <td class="tg-yw4l"><a href="https://colab.research.google.com/drive/1iBoJ0kngkOthy7SgVaVQA1aHEROt5mra?usp=sharing"> <img src="https://colab.research.google.com/assets/colab-badge.svg" width = '' > </a></td> </tr> <tr> <td class="tg-yw4l">Concise Logistic Regression</td> <td class="tg-yw4l">Concise implementation of logistic regression model for binary image classification.</td> <td class="tg-yw4l"><a href="https://colab.research.google.com/drive/14hnFJvHDq9w7FGb8P6pd6-I7F3djTRG9?usp=sharing"> <img src="https://colab.research.google.com/assets/colab-badge.svg" width = '' > </a></td> </tr> <tr> <td class="tg-yw4l">First Neural Network - Image Classifier</td> <td class="tg-yw4l">Build a minimal image classifier using MNIST</td> <td class="tg-yw4l"><a href="https://colab.research.google.com/drive/1i94k-n97Z5r1KWV9Vly9IiKnYxf3Tfvu?usp=sharing"> <img src="https://colab.research.google.com/assets/colab-badge.svg" width = '' > </a></td> </tr> <tr> <td class="tg-yw4l">Neural Network from Scratch</td> <td class="tg-yw4l">An implementation of simple neural network from scratch</td> <td class="tg-yw4l"><a href="https://colab.research.google.com/drive/1YBcEZMUHhJUiwOIwQbqwmAAGrRznpP_E?usp=sharing"> <img src="https://colab.research.google.com/assets/colab-badge.svg" width = '' > </a></td> </tr> <tr> <td class="tg-yw4l">Introduction to GNNs</td> <td class="tg-yw4l">Introduction to Graph Neural Networks. Applies basic GCN to Cora dataset for node classification.</td> <td class="tg-yw4l"><a href="https://colab.research.google.com/drive/1d0jLDwgNBtjBVQOFe8lO_1WrqTVeVZx9?usp=sharing"> <img src="https://colab.research.google.com/assets/colab-badge.svg" width = '' > </a></td> </tr> </table> ## NLP <table class="tg"> <tr> <th class="tg-yw4l"><b>Name</b></th> <th class="tg-yw4l"><b>Description</b></th> <th class="tg-yw4l"><b>Notebook</b></th> </tr> <tr> <td class="tg-yw4l">Bag of Words Text Classifier</td> <td class="tg-yw4l">Build a simple bag of words text classifier.</td> <td class="tg-yw4l"><a href="https://colab.research.google.com/drive/19suDts9MNIhx0TeGO26_BIY2Xc0n6DBC?usp=sharing"> <img src="https://colab.research.google.com/assets/colab-badge.svg" width = '' > </a></td> </tr> <tr> <td class="tg-yw4l">Continuous Bag of Words (CBOW) Text Classifier</td> <td class="tg-yw4l">Build a continuous bag of words text classifier.</td> <td class="tg-yw4l"><a href="https://colab.research.google.com/drive/1lqS67-mbCspIKzx6y9wn7CuP96utWzP2?usp=sharing"> <img src="https://colab.research.google.com/assets/colab-badge.svg" width = '' > </a></td> </tr> <tr> <td class="tg-yw4l">Deep Continuous Bag of Words (Deep CBOW) Text Classifier</td> <td class="tg-yw4l">Build a deep continuous bag of words text classifier.</td> <td class="tg-yw4l"><a href="https://colab.research.google.com/drive/18yz-qvMQYIYZt1BLihSJrKQZXh8zjH8x?usp=sharing"> <img src="https://colab.research.google.com/assets/colab-badge.svg" width = '' > </a></td> </tr> <tr> <td class="tg-yw4l">Text Data Augmentation</td> <td class="tg-yw4l">An introduction to the most commonly used data augmentation techniques for text and their implementation</td> <td class="tg-yw4l"><a href="https://colab.research.google.com/drive/1kyLaRevVf7VVy9BxJBJaL_ET4wyKSi-S?usp=sharing"> <img src="https://colab.research.google.com/assets/colab-badge.svg" width = '' > </a></td> </tr> <tr> <td class="tg-yw4l">Emotion Classification with Fine-tuned BERT</td> <td class="tg-yw4l">Emotion classification using fine-tuned BERT model</td> <td class="tg-yw4l"><a href="https://colab.research.google.com/drive/1nwCE6b9PXIKhv2hvbqf1oZKIGkXMTi1X?usp=sharing"> <img src="https://colab.research.google.com/assets/colab-badge.svg" width = '' > </a></td> </tr> </table> ## Transformers <table class="tg"> <tr> <th class="tg-yw4l"><b>Name</b></th> <th class="tg-yw4l"><b>Description</b></th> <th class="tg-yw4l"><b>Notebook</b></th> </tr> <tr> <td class="tg-yw4l">Text Classification using Transformer</td> <td class="tg-yw4l">An implementation of Attention Mechanism and Positional Embeddings on a text classification task</td> <td class="tg-yw4l"><a href="https://colab.research.google.com/drive/1Jc-_kcO3xYHDMFYSsIcUimcc38_WFlyh?usp=sharing"> <img src="https://colab.research.google.com/assets/colab-badge.svg" width = '' > </a><br> <a href="https://www.kaggle.com/code/ritvik1909/text-classification-attention" target="_blank"><img align="left" alt="Kaggle" title="Open in Kaggle" src="https://kaggle.com/static/images/open-in-kaggle.svg"></a></td> </tr> <tr> <td class="tg-yw4l">Neural Machine Translation using Transformer</td> <td class="tg-yw4l">An implementation of Transformer to translate human readable dates in any format to YYYY-MM-DD format.</td> <td class="tg-yw4l"><a href="https://colab.research.google.com/drive/1Y6JhWMmgU52MU9vyrOnHf6iK760Qx35h?usp=sharing"> <img src="https://colab.research.google.com/assets/colab-badge.svg" width = '' > </a><br> <a href="https://www.kaggle.com/code/ritvik1909/neural-machine-translation-attention" target="_blank"><img align="left" alt="Kaggle" title="Open in Kaggle" src="https://kaggle.com/static/images/open-in-kaggle.svg"></a></td> </tr> <tr> <td class="tg-yw4l">Feature Tokenizer Transformer</td> <td class="tg-yw4l">An implementation of Feature Tokenizer Transformer on a classification task</td> <td class="tg-yw4l"><a href="https://colab.research.google.com/drive/1tdPifaZCTVpjzCh1FOyGPywMEfrbBZLh?usp=sharing"> <img src="https://colab.research.google.com/assets/colab-badge.svg" width = '' > </a><br> <a href="https://www.kaggle.com/code/ritvik1909/feature-tokenizer-transformer/" target="_blank"><img align="left" alt="Kaggle" title="Open in Kaggle" src="https://kaggle.com/static/images/open-in-kaggle.svg"></a></td> </tr> <tr> <td class="tg-yw4l">Named Entity Recognition using Transformer</td> <td class="tg-yw4l">An implementation of Transformer to perform token classification and identify species in PubMed abstracts</td> <td class="tg-yw4l"><a href="https://colab.research.google.com/drive/12AdzQuOvFMrhlVI92dfaVpttkgBcgWcf?usp=sharing"> <img src="https://colab.research.google.com/assets/colab-badge.svg" width = '' > </a><br> <a href="https://www.kaggle.com/code/ritvik1909/named-entity-recognition-attention" target="_blank"><img align="left" alt="Kaggle" title="Open in Kaggle" src="https://kaggle.com/static/images/open-in-kaggle.svg"></a></td> </tr> <tr> <td class="tg-yw4l">Extractive Question Answering using Transformer</td> <td class="tg-yw4l">An implementation of Transformer to perform extractive question answering</td> <td class="tg-yw4l"><a href="https://colab.research.google.com/drive/1Eq3PkrItGTZMTww-wlzume2j4nkQYsdP?usp=sharing"> <img src="https://colab.research.google.com/assets/colab-badge.svg" width = '' > </a><br> <a href="https://www.kaggle.com/code/ritvik1909/question-answering-attention/" target="_blank"><img align="left" alt="Kaggle" title="Open in Kaggle" src="https://kaggle.com/static/images/open-in-kaggle.svg"></a></td> </tr> </table> ## Computer Vision <table class="tg"> <tr> <th class="tg-yw4l"><b>Name</b></th> <th class="tg-yw4l"><b>Description</b></th> <th class="tg-yw4l"><b>Notebook</b></th> </tr> <tr> <td class="tg-yw4l">Siamese Network</td> <td class="tg-yw4l">An implementation of Siamese Network for finding Image Similarity</td> <td class="tg-yw4l"><a href="https://colab.research.google.com/drive/1sn7BDKVvi8-Ng37gvfyNw8OCf8kZY91o?usp=sharing"> <img src="https://colab.research.google.com/assets/colab-badge.svg" width = '' > </a><br> <a href="https://kaggle.com/code/ritvik1909/siamese-network" target="_blank"><img align="left" alt="Kaggle" title="Open in Kaggle" src="https://kaggle.com/static/images/open-in-kaggle.svg"></a></td> </tr> <tr> <td class="tg-yw4l">Variational Auto Encoder</td> <td class="tg-yw4l">An implementation of Variational Auto Encoder to generate Augmentations for MNIST Handwritten Digits</td> <td class="tg-yw4l"><a href="https://colab.research.google.com/drive/13na-qaRSMwD2jplXjg_oapPDmVozIzLL?usp=sharing"> <img src="https://colab.research.google.com/assets/colab-badge.svg" width = '' > </a><br> <a href="https://www.kaggle.com/code/ritvik1909/variational-auto-encoder" target="_blank"><img align="left" alt="Kaggle" title="Open in Kaggle" src="https://kaggle.com/static/images/open-in-kaggle.svg"></a></td> </tr> <tr> <td class="tg-yw4l">Object Detection using Sliding Window and Image Pyramid</td> <td class="tg-yw4l">A basic object detection implementation using sliding window and image pyramid on top of an image classifier</td> <td class="tg-yw4l"><a href="https://colab.research.google.com/drive/1CiLN6g7puBheHq-tfk4YB4X-Lgypur8M?usp=sharing"> <img src="https://colab.research.google.com/assets/colab-badge.svg" width = '' > </a><br> <a href="https://www.kaggle.com/code/ritvik1909/object-detection-sliding-window" target="_blank"><img align="left" alt="Kaggle" title="Open in Kaggle" src="https://kaggle.com/static/images/open-in-kaggle.svg"></a></td> </tr> <tr> <td class="tg-yw4l">Object Detection using Selective Search</td> <td class="tg-yw4l">A basic object detection implementation using selective search on top of an image classifier</td> <td class="tg-yw4l"><a href="https://colab.research.google.com/drive/1C7Zo5JRMrcETMxn-8jRuszrEXXjRbN37?usp=sharing"> <img src="https://colab.research.google.com/assets/colab-badge.svg" width = '' > </a><br> <a href="https://www.kaggle.com/code/ritvik1909/object-detection-selective-search" target="_blank"><img align="left" alt="Kaggle" title="Open in Kaggle" src="https://kaggle.com/static/images/open-in-kaggle.svg"></a></td> </tr> </table> ## Generative Adversarial Network <table class="tg"> <tr> <th class="tg-yw4l"><b>Name</b></th> <th class="tg-yw4l"><b>Description</b></th> <th class="tg-yw4l"><b>Notebook</b></th> </tr> <tr> <td class="tg-yw4l">Deep Convolutional GAN</td> <td class="tg-yw4l">An Implementation of Deep Convolutional GAN to generate MNIST digits</td> <td class="tg-yw4l"><a href="https://colab.research.google.com/drive/1ss9FCHvI0ZAuS1PJL6RxlgEhM_glZR6S?usp=sharing"> <img src="https://colab.research.google.com/assets/colab-badge.svg" width = '' > </a><br> <a href="https://www.kaggle.com/code/ritvik1909/deep-convolutional-gan/" target="_blank"><img align="left" alt="Kaggle" title="Open in Kaggle" src="https://kaggle.com/static/images/open-in-kaggle.svg"></a></td> </tr> <tr> <td class="tg-yw4l">Wasserstein GAN with Gradient Penalty</td> <td class="tg-yw4l">An Implementation of Wasserstein GAN with Gradient Penalty to generate MNIST digits</td> <td class="tg-yw4l"><a href="https://colab.research.google.com/drive/1x7aDlxkv3PYev2AsmZRl8pII2zsY_DVs?usp=sharing"> <img src="https://colab.research.google.com/assets/colab-badge.svg" width = '' > </a><br> <a href="https://www.kaggle.com/code/ritvik1909/wasserstein-gan-with-gradient-penalty/" target="_blank"><img align="left" alt="Kaggle" title="Open in Kaggle" src="https://kaggle.com/static/images/open-in-kaggle.svg"></a></td> </tr> <tr> <td class="tg-yw4l">Conditional GAN</td> <td class="tg-yw4l">An Implementation of Conditional GAN to generate MNIST digits</td> <td class="tg-yw4l"><a href="https://colab.research.google.com/drive/1Z74CpEu76e6A62gxKXIJ8u8xyVjF21_k?usp=sharing"> <img src="https://colab.research.google.com/assets/colab-badge.svg" width = '' > </a><br> <a href="https://www.kaggle.com/code/ritvik1909/conditional-gan/" target="_blank"><img align="left" alt="Kaggle" title="Open in Kaggle" src="https://kaggle.com/static/images/open-in-kaggle.svg"></a></td> </tr> </table> ## Parameter Efficient Fine-tuning <table class="tg"> <tr> <th class="tg-yw4l"><b>Name</b></th> <th class="tg-yw4l"><b>Description</b></th> <th class="tg-yw4l"><b>Notebook</b></th> </tr> <tr> <td class="tg-yw4l">LoRA BERT</td> <td class="tg-yw4l">An Implementation of BERT Finetuning using LoRA</td> <td class="tg-yw4l"> <a href="https://www.kaggle.com/code/ritvik1909/lora-bert/" target="_blank"><img align="left" alt="Kaggle" title="Open in Kaggle" src="https://kaggle.com/static/images/open-in-kaggle.svg"></a></td> </tr> <tr> <td class="tg-yw4l">LoRA BERT NER</td> <td class="tg-yw4l">An Implementation of BERT Finetuning using LoRA for token classification task</td> <td class="tg-yw4l"> <a href="https://www.kaggle.com/code/ritvik1909/lora-bert-ner/" target="_blank"><img align="left" alt="Kaggle" title="Open in Kaggle" src="https://kaggle.com/static/images/open-in-kaggle.svg"></a></td> </tr> <tr> <td class="tg-yw4l">LoRA T5</td> <td class="tg-yw4l">An Implementation of T5 Finetuning using LoRA</td> <td class="tg-yw4l"> <a href="https://www.kaggle.com/code/ritvik1909/lora-t5/" target="_blank"><img align="left" alt="Kaggle" title="Open in Kaggle" src="https://kaggle.com/static/images/open-in-kaggle.svg"></a></td> </tr> <tr> <td class="tg-yw4l">LoRA TinyLlama 1.1B</td> <td class="tg-yw4l">An Implementation of TinyLlama 1.1B Finetuning using LoRA</td> <td class="tg-yw4l"> <a href="https://www.kaggle.com/code/ritvik1909/lora-tinyllama-1-1b/" target="_blank"><img align="left" alt="Kaggle" title="Open in Kaggle" src="https://kaggle.com/static/images/open-in-kaggle.svg"></a></td> </tr> <tr> <td class="tg-yw4l">QLoRA TinyLlama 1.1B</td> <td class="tg-yw4l">An Implementation of TinyLlama 1.1B Finetuning using QLoRA</td> <td class="tg-yw4l"> <a href="https://www.kaggle.com/code/ritvik1909/qlora-tinyllama-1-1b/" target="_blank"><img align="left" alt="Kaggle" title="Open in Kaggle" src="https://kaggle.com/static/images/open-in-kaggle.svg"></a></td> </tr> <tr> <td class="tg-yw4l">QLoRA Mistral 7B</td> <td class="tg-yw4l">An Implementation of Mistral 7B Finetuning using QLoRA</td> <td class="tg-yw4l"> <a href="https://www.kaggle.com/code/ritvik1909/qlora-mistral-7b/" target="_blank"><img align="left" alt="Kaggle" title="Open in Kaggle" src="https://kaggle.com/static/images/open-in-kaggle.svg"></a></td> </tr> </table> --- If you find any bugs or have any questions regarding these notebooks, please open an issue. We will address it as soon as we can. Reach out on [Twitter](https://twitter.com/omarsar0) if you have any questions. Please cite the following if you use the code examples in your research: ``` @misc{saravia2022ml, title={ML Notebooks}, author={Saravia, Elvis and Rastogi, Ritvik}, journal={https://github.com/dair-ai/ML-Notebooks}, year={2022} } ```

:fire: Machine Learning Notebooks

deep-learning,machine-learning,python,pytorch,ai

niuhuan/jasmine

Jasmine Comic ============= A comic browser，support Android / iOS / MacOS / Windows / Linux. 1. This APP has restricted content 2. Please know local laws before using these codes 3. The owner of the repo will not release these codes and its assets to the community outside github ## Screenshot #### Browser  #### Reader  ## Features - [x] Comics - [x] Comic categories - [x] Comic reader - [x] Comic search - [x] Comic favours - [x] Histories - [x] Cache comic - [ ] Games - [x] Community - [x] List comments - [x] Send comments - [x] User - [x] Login / Register - [x] Devices adaptation - [x] Android's high frequency screen ## Technical architecture Flutter: high-performance UI Rust: High performance service  ## Please follow the rules - These codes can only be learned and used, and are prohibited for commercial use - Do not send Assets to anyone

A comic browser，support Android / iOS / MacOS / Windows / Linux.

comic,acg,ios,flutter,pica,picacg,cosplay,hentai,rust,jmcomic

microsoft/devicescript

# DeviceScript **TypeScript for Tiny IoT Devices.** DeviceScript brings a TypeScript developer experience to low-resource microcontroller-based devices. DeviceScript is compiled to a custom VM bytecode, which can run in very constrained environments. - [Read the documentation](https://microsoft.github.io/devicescript) > Experimental Project from Microsoft Research - Join the <a href="https://github.com/microsoft/devicescript/discussions">discussions</a> to provide feedback. https://user-images.githubusercontent.com/4175913/228997575-122d6ad0-f37e-4d4e-ab79-3d8f680ed99d.mp4 ## Contributing Contributions are welcome! See [contributing page](https://microsoft.github.io/devicescript/contributing). <a href="https://github.com/microsoft/devicescript/graphs/contributors"> <img src="https://contrib.rocks/image?repo=microsoft/devicescript" /> </a> ## Trademarks This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft trademarks or logos is subject to and must follow [Microsoft's Trademark & Brand Guidelines](https://www.microsoft.com/en-us/legal/intellectualproperty/trademarks/usage/general). Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship. Any use of third-party trademarks or logos are subject to those third-party's policies.

TypeScript for Tiny IoT Devices (ESP32, RP2040, ...)

embedded,iot,jacdac,esp32,rp2040,typescript,devicescript

christianversloot/machine-learning-articles

# Machine learning articles I wrote these articles about machine learning in the peroid between May 2019 and February 2022. As I'm no longer maintaining MachineCurve.com, I've moved them here so that they remain available for the public. Enjoy! [](https://star-history.com/#christianversloot/machine-learning-articles&Date)

🧠💬 Articles I wrote about machine learning, archived from MachineCurve.com.

machine-learning,deep-learning,neural-networks,tensorflow,pytorch,scikit-learn,convolutional-neural-networks,gan,gans,transformers

palxiao/poster-design

**[在线体验网站](https://design.palxp.cn/)** | **[在线文档](https://xp.palxp.cn/)** | [常见问题](https://xp.palxp.cn/#/articles/1689323321667) | [性能压测](https://juejin.cn/post/7348288810722869300) --- ## 迅排设计 一款漂亮易用且功能强大的创意图片编辑器，对标稿定设计、创客贴、Canva 等商业产品。 适用于多种场景：海报图片生成、电商分享图、文章长图、视频/公众号封面等，无需下载软件即可轻松实现云端编辑、迅速完成图文排版。 [](https://design.palxp.cn/) ### 特点 - 丝滑的页面操作体验，丰富的交互细节，基础功能完善 - 采用服务端生成图片，确保多端出图统一性，支持各种 HTML5 特性 - 简易 AI 抠图工具，上传图片一键去除背景 - 技术栈：Vue3 、Vite5 、Pinia 、ElementPlus - 图片生成：Puppeteer、Express ### 支持功能 - 导入 PSD 文件解析成模板、在线导出图片下载。 - 元素拖拽、组合、缩放、层级调整、对齐等操作。 - 图片素材插入、替换、裁剪，图片容器等功能。 - SVG 素材颜色、透明度编辑，文字花字组合。 - 支持图层管理、多画板管理、自适应画布。 - 吸附对齐、辅助引导线、标尺功能。 - 键盘快捷键、右键菜单快捷操作，复制删除等常用操作。 - 风格二维码编辑，支持单色、渐变、自定义 logo 等。 - 颜色调色板，原生级取色器颜色吸管（Chrome）。 ## 快速开始 ``` git clone https://github.com/palxiao/poster-design.git cd poster-design npm run prepared npm run dev cd screreenshot npm run dev ```  访问 http://127.0.0.1:5173/ 查看网页。点此查看[更多说明文档](https://xp.palxp.cn/#/articles/1689319644311)。 ### 图片生成服务 代码位于根目录 [/screenshot](https://github.com/palxiao/poster-design/tree/main/screenshot)，接口API文档点此查看：[接口 API 文档](https://xp.palxp.cn/apidoc/screenshot.html)。 ### 服务端 后端需要自己开发，目前本项目演示 Demo 中的后端接口参考：[接口 API 文档](https://xp.palxp.cn/apidoc/index.html)。 ### 其它 一些问题修改与记录[点击这里查看](https://xp.palxp.cn/#/articles/1689319986889?id=%e8%bf%ad%e4%bb%a3%e8%ae%a1%e5%88%92)，项目持续迭代中，还有很多不足，可以将你遇到的问题在 Issues 中提出，或者提交 Pull Request 帮助完善。 ### 交流群 关注公众号：品味前端，回复 “加群” 获取二维码，更新公告不错过。 <img style="width: 380px;" src="https://xp.palxp.cn/images/2024-3-1-1709306365949.png" /> ### 感谢 项目还使用或参考了一些优秀开源项目，包括但不限于： - [moveable](https://github.com/daybrush/moveable): 提供了画布中选择、拖动缩放等能力 - [html2canvas](https://github.com/niklasvh/html2canvas): 前端生图的一种快捷方案 - [qr-code-styling](https://qr-code-styling.com/): 风格化二维码 - [rembg](https://github.com/danielgatis/rembg): 图片抠图，使用 u2net 预训练模型 开源不易，最后别忘了给本项目点个 **Star** ~ [](https://star-history.com/#palxiao/poster-design&Date) ### `Star` 感谢所有支持本项目的朋友 :heart: [](https://github.com/palxiao/poster-design/stargazers) ### `Fork` 这些小伙伴都在使用迅排设计 :heart: [](https://github.com/palxiao/poster-design/network/members) ### 友情赞助商 | Dooring低代码 | DrawOn桌案 | | --- | --- | | <a href="https://dooring.vip/"> <img style="height: 90px" src="https://github.com/palxiao/poster-design/assets/21021314/2240801f-8484-4fd2-8505-8205daa6d53c" /></a> | <a href="https://www.drawon.cn?useSource=hb1"> <img style="height: 120px" src="https://github.com/palxiao/poster-design/assets/21021314/258bb6ec-4e1e-4c86-b45c-22946213f209" /></a> | ### `Contributions` <a href="https://github.com/palxiao/poster-design/graphs/contributors"> <img src="https://contrib.rocks/image?repo=palxiao/poster-design" /> </a> ### `LICENSE` 本项目完全免费，可在保留 [MIT 开源许可证](https://github.com/palxiao/poster-design/blob/main/LICENSE) 的前提下使用。

一款漂亮且功能强大的在线海报设计器，图片编辑器，仿稿定设计，适用于多种场景：海报生成、电商产品图、文章长图、视频/公众号封面等。A beautiful online image designer, suitable for various scenarios like generate posters, making design easier!

image,nodejs,poster,puppeteer,vue3,canvas,moveable,design

louisfb01/best_AI_papers_2022

# 2022: A Year Full of Amazing AI papers- A Review 🚀 ## A curated list of the latest breakthroughs in AI by release date with a clear video explanation, link to a more in-depth article, and code. While the world is still recovering, research hasn't slowed its frenetic pace, especially in the field of artificial intelligence. More, many important aspects were highlighted this year, like the ethical aspects, important biases, governance, transparency and much more. Artificial intelligence and our understanding of the human brain and its link to AI are constantly evolving, showing promising applications improving our life's quality in the near future. Still, we ought to be careful with which technology we choose to apply. >"Science cannot tell us what we ought to do, only what we can do."<br/>- Jean-Paul Sartre, Being and Nothingness Here's curated list of the latest breakthroughs in AI and Data Science by release date with a clear video explanation, link to a more in-depth article, and code (if applicable). Enjoy the read! **The complete reference to each paper is listed at the end of this repository.** *Star this repository to stay up to date and stay tuned for next year!* ⭐️ Maintainer: [louisfb01](https://github.com/louisfb01), also active on [YouTube](https://www.youtube.com/@whatsai) and as a [Podcaster](https://open.spotify.com/show/4rKRJXaXlClkDyInjHkxq3) if you want to see/hear more about AI! [](https://twitter.com/Whats_AI) Subscribe to my [newsletter](https://louisbouchard.substack.com/) - The latest updates in AI explained every week. *Feel free to [message me](https://www.louisbouchard.ai/contact/) any interesting paper I may have missed to add to this repository.* *Tag me on **Twitter** [@Whats_AI](https://twitter.com/Whats_AI) or **LinkedIn** [@Louis (What's AI) Bouchard](https://www.linkedin.com/in/whats-ai/) if you share the list!* And come chat with us in our [Learn AI Together Discord community](https://www.louisbouchard.ai/learn-ai-together/)! 👀 **If you'd like to support my work**, you can check to [Sponsor](https://github.com/sponsors/louisfb01) this repository or support me on [Patreon](https://www.patreon.com/whatsai). ### Watch a complete 2022 rewind in 8 minutes [<img src="https://imgur.com/MGt3APx.png" width="512"/>](https://youtu.be/tYRTzWHOQio) ---- ## The Full List - [Resolution-robust Large Mask Inpainting with Fourier Convolutions [1]](#1) - [Stitch it in Time: GAN-Based Facial Editing of Real Videos [2]](#2) - [NeROIC: Neural Rendering of Objects from Online Image Collections [3]](#3) - [SpeechPainter: Text-conditioned Speech Inpainting [4]](#4) - [Towards real-world blind face restoration with generative facial prior [5]](#5) - [4D-Net for Learned Multi-Modal Alignment [6]](#6) - [Instant Neural Graphics Primitives with a Multiresolution Hash Encoding [7]](#7) - [Hierarchical Text-Conditional Image Generation with CLIP Latents [8]](#8) - [MyStyle: A Personalized Generative Prior [9]](#9) - [OPT: Open Pre-trained Transformer Language Models [10]](#10) - [BlobGAN: Spatially Disentangled Scene Representations [11]](#11) - [A Generalist Agent [12]](#12) - [Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding [13]](#13) - [Dalle mini [14]](#14) - [No Language Left Behind: Scaling Human-Centered Machine Translation [15]](#15) - [Dual-Shutter Optical Vibration Sensing [16]](#16) - [Make-a-scene: Scene-based text-to-image generation with human priors [17]](#17) - [BANMo: Building Animatable 3D Neural Models from Many Casual Videos [18]](#18) - [High-resolution image synthesis with latent diffusion models [19]](#19) - [Panoptic Scene Graph Generation [20]](#20) - [An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion [21]](#21) - [Expanding Language-Image Pretrained Models for General Video Recognition [22]](#22) - [MAKE-A-VIDEO: TEXT-TO-VIDEO GENERATION WITHOUT TEXT-VIDEO DATA [23]](#23) - [Robust Speech Recognition via Large-Scale Weak Supervision [24]](#24) - [DreamFusion: Text-to-3D using 2D Diffusion [25]](#25) - [Imagic: Text-Based Real Image Editing with Diffusion Models [26]](#26) - [eDiffi: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers [27]](#27) - [InfiniteNature-Zero: Learning Perpetual View Generation of Natural Scenes from Single Images [28]](#28) - [Galactica: A Large Language Model for Science [29]](#29) - [Real-time Neural Radiance Talking Portrait Synthesis via Audio-spatial Decomposition [30]](#30) - [ChatGPT: Optimizing Language Models for Dialogue [31]](#31) - [Production-Ready Face Re-Aging for Visual Effects [32]](#32) - [Paper references](#references) --- ## Resolution-robust Large Mask Inpainting with Fourier Convolutions [1]<a name="1"></a> You’ve most certainly experienced this situation once: You take a great picture with your friend, and someone is photobombing behind you, ruining your future Instagram post. Well, that’s no longer an issue. Either it is a person or a trashcan you forgot to remove before taking your selfie that’s ruining your picture. This AI will just automatically remove the undesired object or person in the image and save your post. It’s just like a professional photoshop designer in your pocket, and with a simple click! This task of removing part of an image and replacing it with what should appear behind has been tackled by many AI researchers for a long time. It is called image inpainting, and it’s extremely challenging... * Short Video Explanation:<br/> [<img src="https://imgur.com/d5ClyqP.png" width="512"/>](https://youtu.be/Ia79AvGzveQ) * Short read: [This AI Removes Unwanted Objects From your Images!](https://www.louisbouchard.ai/lama/) * Paper: [Resolution-robust Large Mask Inpainting with Fourier Convolutions](https://arxiv.org/pdf/2109.07161.pdf) * [Code](https://github.com/saic-mdal/lama) * [Colab Demo](https://colab.research.google.com/github/saic-mdal/lama/blob/master/colab/LaMa_inpainting.ipynb) * [Product using LaMa](https://cleanup.pictures/) ## Stitch it in Time: GAN-Based Facial Editing of Real Videos [2]<a name="2"></a> You've most certainly seen movies like the recent Captain Marvel or Gemini Man where Samuel L Jackson and Will Smith appeared to look like they were much younger. This requires hundreds if not thousands of hours of work from professionals manually editing the scenes he appeared in. Instead, you could use a simple AI and do it within a few minutes. Indeed, many techniques allow you to add smiles, make you look younger or older, all automatically using AI-based algorithms. It is called AI-based face manipulations in videos and here's the current state-of-the-art in 2022! * Short Video Explanation:<br/> [<img src="https://imgur.com/lvgMjzS.png" width="512"/>](https://youtu.be/mqItu9XoUgk) * Short read: [AI Facial Editing of Real Videos ! Stitch it in Time Explained](https://www.louisbouchard.ai/stitch-it-in-time/) * Paper: [Stitch it in Time: GAN-Based Facial Editing of Real Videos](https://arxiv.org/abs/2201.08361) * [Code](https://github.com/rotemtzaban/STIT) ## NeROIC: Neural Rendering of Objects from Online Image Collections [3]<a name="3"></a> Neural Rendering. Neural Rendering is the ability to generate a photorealistic model in space just like this one, from pictures of the object, person, or scene of interest. In this case, you’d have a handful of pictures of this sculpture and ask the machine to understand what the object in these pictures should look like in space. You are basically asking a machine to understand physics and shapes out of images. This is quite easy for us since we only know the real world and depths, but it’s a whole other challenge for a machine that only sees pixels. It’s great that the generated model looks accurate with realistic shapes, but what about how it blends in the new scene? And what if the lighting conditions vary in the pictures taken and the generated model looks different depending on the angle you look at it? This would automatically seem weird and unrealistic to us. These are the challenges Snapchat and the University of Southern California attacked in this new research. * Short Video Explanation:<br/> [<img src="https://imgur.com/xTpuwcN.png" width="512"/>](https://youtu.be/88Pl9zD1Z78) * Short read: [Create Realistic 3D Renderings with AI !](https://www.louisbouchard.ai/neroic/) * Paper: [NeROIC: Neural Rendering of Objects from Online Image Collections](https://arxiv.org/pdf/2201.02533.pdf) * [Code](https://github.com/snap-research/NeROIC) ## SpeechPainter: Text-conditioned Speech Inpainting [4]<a name="4"></a> We’ve seen image inpainting, which aims to remove an undesirable object from a picture. The machine learning-based techniques do not simply remove the objects, but they also understand the picture and fill the missing parts of the image with what the background should look like. The recent advancements are incredible, just like the results, and this inpainting task can be quite useful for many applications like advertisements or improving your future Instagram post. We also covered an even more challenging task: video inpainting, where the same process is applied to videos to remove objects or people. The challenge with videos comes with staying consistent from frame to frame without any buggy artifacts. But now, what happens if we correctly remove a person from a movie and the sound is still there, unchanged? Well, we may hear a ghost and ruin all our work. This is where a task I never covered on my channel comes in: speech inpainting. You heard it right, researchers from Google just published a paper aiming at inpainting speech, and, as we will see, the results are quite impressive. Okay, we might rather hear than see the results, but you get the point. It can correct your grammar, pronunciation or even remove background noise. All things I definitely need to keep working on, or… simply use their new model… Listen to the examples in my video! * Short Video Explanation:<br/> [<img src="https://imgur.com/JyQ41Qv.png" width="512"/>](https://youtu.be/zIIc4bRf5Hg) * Short read: [Speech Inpainting with AI !](https://www.louisbouchard.ai/speech-inpainting-with-ai/) * Paper: [SpeechPainter: Text-conditioned Speech Inpainting](https://arxiv.org/pdf/2202.07273.pdf) * [Listen to more examples](https://google-research.github.io/seanet/speechpainter/examples/) ## Towards real-world blind face restoration with generative facial prior [5]<a name="5"></a> Do you also have old pictures of yourself or close ones that didn’t age well or that you, or your parents, took before we could produce high-quality images? I do, and I felt like those memories were damaged forever. Boy, was I wrong! This new and completely free AI model can fix most of your old pictures in a split second. It works well even with very low or high-quality inputs, which is typically quite the challenge. This week’s paper called Towards Real-World Blind Face Restoration with Generative Facial Prior tackles the photo restoration task with outstanding results. What’s even cooler is that you can try it yourself and in your preferred way. They have open-sourced their code, created a demo and online applications for you to try right now. If the results you’ve seen above aren’t convincing enough, just watch the video and let me know what you think in the comments, I know it will blow your mind! * Short Video Explanation:<br/> [<img src="https://imgur.com/DxxFRLI.png" width="512"/>](https://youtu.be/nLDVtzcSeqM) * Short read: [Impressive photo restoration by AI !](https://www.louisbouchard.ai/gfp-gan/) * Paper: [Towards real-world blind face restoration with generative facial prior](https://arxiv.org/pdf/2101.04061.pdf) * [Code](https://github.com/TencentARC/GFPGAN) * [Colab Demo](https://colab.research.google.com/drive/1sVsoBd9AjckIXThgtZhGrHRfFI6UUYOo) * [Online app](https://huggingface.co/spaces/akhaliq/GFPGAN) ## 4D-Net for Learned Multi-Modal Alignment [6]<a name="6"></a> How do autonomous vehicles see? You’ve probably heard of LiDAR sensors or other weird cameras they are using. But how do they work, how can they see the world, and what do they see exactly compared to us? Understanding how they work is essential if we want to put them on the road, primarily if you work in the government or build the next regulations. But also as a client of these services. We previously covered how Tesla autopilot sees and works, but they are different from conventional autonomous vehicles. Tesla only uses cameras to understand the world, while most of them, like Waymo, use regular cameras and 3D LiDAR sensors. These LiDAR sensors are pretty simple to understand: they won’t produce images like regular cameras but 3D point clouds. LiDAR cameras measure the distance between objects, calculating the pulse laser’s traveling time that they project to the object. Still, how can we efficiently combine this information and have the vehicle understand it? And what does the vehicle end up seeing? Only points everywhere? Is it enough for driving on our roads? We will look into this with a new research paper by Waymo and Google Research... * Short Video Explanation:<br/> [<img src="https://imgur.com/AxGLy7p.png" width="512"/>](https://youtu.be/0nJMnw1Ldks) * Short read: [Combine Lidar and Cameras for 3D object detection - Waymo](https://www.louisbouchard.ai/waymo-lidar/) * Paper: [4D-Net for Learned Multi-Modal Alignment](https://openaccess.thecvf.com/content/ICCV2021/papers/Piergiovanni_4D-Net_for_Learned_Multi-Modal_Alignment_ICCV_2021_paper.pdf) ## Instant Neural Graphics Primitives with a Multiresolution Hash Encoding [7]<a name="7"></a> As if taking a picture wasn’t a challenging enough technological prowess, we are now doing the opposite: modeling the world from pictures. I’ve covered amazing AI-based models that could take images and turn them into high-quality scenes. A challenging task that consists of taking a few images in the 2-dimensional picture world to create how the object or person would look in the real world. Take a few pictures and instantly have a realistic model to insert into your product. How cool is that?! The results have dramatically improved upon the first model I covered in 2020, called NeRF. And this improvement isn’t only about the quality of the results. NVIDIA made it even better. Not only that the quality is comparable, if not better, but it is more than 1'000 times faster with less than two years of research. * Short Video Explanation:<br/> [<img src="https://imgur.com/8PilczV.png" width="512"/>](https://youtu.be/UHQZBQOVAIU) * Short read: [NVIDIA Turns Photos into 3D Scenes in Milliseconds](https://www.louisbouchard.ai/nvidia-photos-into-3d-scenes/) * Paper: [Instant Neural Graphics Primitives with a Multiresolution Hash Encoding](https://nvlabs.github.io/instant-ngp/assets/mueller2022instant.pdf) * [Code](https://github.com/NVlabs/instant-ngp) ## Hierarchical Text-Conditional Image Generation with CLIP Latents [8]<a name="8"></a> Last year I shared DALL·E, an amazing model by OpenAI capable of generating images from a text input with incredible results. Now is time for his big brother, DALL·E 2. And you won’t believe the progress in a single year! DALL·E 2 is not only better at generating photorealistic images from text. The results are four times the resolution! As if it wasn’t already impressive enough, the recent model learned a new skill; image inpainting. DALL·E could generate images from text inputs. DALL·E 2 can do it better, but it doesn’t stop there. It can also edit those images and make them look even better! Or simply add a feature you want like some flamingos in the background. Sounds interesting? Learn more in the video or read more below! * Short Video Explanation:<br/> [<img src="https://imgur.com/xZlfsJO.png" width="512"/>](https://youtu.be/rdGVbPI42sA) * Short read: [OpenAI's new model DALL·E 2 is amazing!](https://www.louisbouchard.ai/openais-new-model-dall-e-2-is-amazing/) * Paper: [Hierarchical Text-Conditional Image Generation with CLIP Latents](https://cdn.openai.com/papers/dall-e-2.pdf) ## MyStyle: A Personalized Generative Prior [9]<a name="9"></a> This new model by Google Research and Tel-Aviv University is incredible. You can see it as a very, very powerful deepfake that can do anything. Take a hundred pictures of any person and you have its persona encoded to fix, edit or create any realistic picture you want. This is both amazing and scary if you ask me, especially when you look at the results. Watch the video to see more results and understand how the model works! * Short Video Explanation:<br/> [<img src="https://imgur.com/FAhVBzM.png" width="512"/>](https://youtu.be/BNWAEvFfFvQ) * Short read: [Your Personal Photoshop Expert with AI!](https://www.louisbouchard.ai/mystyle/) * Paper: [MyStyle: A Personalized Generative Prior](https://arxiv.org/abs/2203.17272) * [Code (coming soon)](https://mystyle-personalized-prior.github.io/) > Check out [the What's AI podcast](https://open.spotify.com/show/4rKRJXaXlClkDyInjHkxq3) for more AI content in the form of interviews with experts in the field! An invited AI expert and I will cover specific topics, sub-fields, and roles related to AI to teach and share knowledge from the people who worked hard to gather it. ## OPT: Open Pre-trained Transformer Language Models [10]<a name="10"></a> We’ve all heard about GPT-3 and have somewhat of a clear idea of its capabilities. You’ve most certainly seen some applications born strictly due to this model, some of which I covered in a previous video about the model. GPT-3 is a model developed by OpenAI that you can access through a paid API but have no access to the model itself. What makes GPT-3 so strong is both its architecture and size. It has 175 billion parameters. Twice the amount of neurons we have in our brains! This immense network was pretty much trained on the whole internet to understand how we write, exchange, and understand text. This week, Meta has taken a big step forward for the community. They just released a model that is just as powerful, if not more and has completely open-sourced it. * Short Video Explanation:<br/> [<img src="https://imgur.com/ZBHHYaQ.png" width="512"/>](https://youtu.be/Ejg0OunCi9U) * Short read: [Meta's new model OPT is GPT-3's closest competitor! (and is open source)](https://www.louisbouchard.ai/opt-meta/) * Paper: [OPT: Open Pre-trained Transformer Language Models](https://arxiv.org/pdf/2205.01068.pdf) * [Code](https://github.com/facebookresearch/metaseq) ## BlobGAN: Spatially Disentangled Scene Representations [11]<a name="11"></a> BlobGAN allows for unreal manipulation of images, made super easily controlling simple blobs. All these small blobs represent an object, and you can move them around or make them bigger, smaller, or even remove them, and it will have the same effect on the object it represents in the image. This is so cool! As the authors shared in their results, you can even create novel images by duplicating blobs, creating unseen images in the dataset [like a room with two ceiling fans](https://youtu.be/mnEzjpiA_4E)! Correct me if I’m wrong, but I believe it is one of, if not the first, paper to make the modification of images as simple as moving blobs around and allowing for edits that were unseen in the training dataset.  And you can actually play with this one compared to some companies we all know! They shared their code publicly and a Colab Demo you can try right away. Even more exciting is how BlobGAN works. Learn more in the video! * Short Video Explanation:<br/> [<img src="https://imgur.com/9ouN5ta.png" width="512"/>](https://youtu.be/mnEzjpiA_4E) * Short read: [This is a BIG step for GANs! BlobGAN Explained](https://www.louisbouchard.ai/blobgan/) * Paper: [BlobGAN: Spatially Disentangled Scene Representations](https://dave.ml/blobgan/) * [Code](https://github.com/dave-epstein/blobgan) * [Colab Demo](https://colab.research.google.com/drive/1clvh28Yds5CvKsYYENGLS3iIIrlZK4xO?usp=sharing#scrollTo=0QuVIyVplOKu) ## A Generalist Agent [12]<a name="12"></a> Gato from DeepMind was just published! It is a single transformer that can play Atari games, caption images, chat with people, control a real robotic arm, and more! Indeed, it is trained once and uses the same weights to achieve all those tasks. And as per Deepmind, this is not only a transformer but also an agent. This is what happens when you mix Transformers with progress on multi-task reinforcement learning agents. Gato is a multi-modal agent. Meaning that it can create captions for images or answer questions as a chatbot. You’d say that GPT-3 can already do that, but Gato can do more… The multi-modality comes from the fact that Gato can also play Atari games at the human level or even do real-world tasks like controlling robotic arms to move objects precisely. It understands words, images, and even physics... * Short Video Explanation:<br/> [<img src="https://imgur.com/rr9VUXn.png" width="512"/>](https://youtu.be/xZKSWNv6Esc) * Short read: [Deepmind's new model Gato is amazing!](https://www.louisbouchard.ai/deepmind-gato/) * Paper: [A Generalist Agent](https://storage.googleapis.com/deepmind-media/A%20Generalist%20Agent/Generalist%20Agent.pdf) ## Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding [13]<a name="13"></a> If you thought Dall-e 2 had great results, wait until you see what this new model from Google Brain can do. Dalle-e is amazing but often lacks realism, and this is what the team attacked with this new model called Imagen. They share a lot of results on their project page as well as a benchmark, which they introduced for comparing text-to-image models, where they clearly outperform Dall-E 2, and previous image generation approaches. Learn more in the video... * Short Video Explanation:<br/> [<img src="https://imgur.com/IpwaSvZ.png" width="512"/>](https://youtu.be/qhtYPhPWCsI) * Short read: [Google Brain's Answer to Dalle-e 2: Imagen](https://www.louisbouchard.ai/google-brain-imagen/) * Paper: [Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding](https://imagen.research.google/paper.pdf) * [Project page with results](https://imagen.research.google/) [](https://twitter.com/Whats_AI) ## DALL·E Mini [14]<a name="14"></a> Dalle mini is amazing — and YOU can use it! I'm sure you've seen pictures like those in your Twitter feed in the past few days. If you wondered what they were, they are images generated by an AI called DALL·E mini. If you've never seen those, you need to watch this video because you are missing out. If you wonder how this is possible, well, you are on the perfect video and will know the answer in less than five minutes. Dalle mini is a free, open-source AI that produces amazing images from text inputs. * Short Video Explanation:<br/> [<img src="https://imgur.com/Ux4ItPo.png" width="512"/>](https://youtu.be/qOxde_JV0vI) * Short read: [How does dalle-mini work?](https://www.louisbouchard.ai/dalle-mini/) * [Code](https://github.com/borisdayma/dalle-mini) * [Huggingface official demo](https://huggingface.co/spaces/dalle-mini/dalle-mini) ## No Language Left Behind: Scaling Human-Centered Machine Translation [15]<a name="15"></a> Meta AI’s most recent model, called “No Language Left Behind” does exactly that: translates across 200 different languages with state-of-the-art quality. A single model can handle 200 languages. How incredible is that? We find it difficult to have great results strictly in English while Meta is tackling 200 different languages with the same model, and some of the most complicated and less represented ones that even google translate struggles with... * Short Video Explanation:<br/> [<img src="https://imgur.com/OHV5bTU.png" width="512"/>](https://youtu.be/2G4NeG17Eis) * Short read: [No Language Left Behind](https://www.louisbouchard.ai/no-language-left-behind/) * [Code](https://github.com/facebookresearch/fairseq/tree/nllb) * Paper: [No Language Left Behind](https://ai.facebook.com/research/no-language-left-behind/) ## Dual-Shutter Optical Vibration Sensing [16]<a name="16"></a> They reconstruct sound using cameras and a laser beam on any vibrating surface, allowing them to isolate music instruments, focus on a specific speaker, remove ambient noises, and many more amazing applications. * Short Video Explanation:<br/> [<img src="https://imgur.com/kkS7tGw.png" width="512"/>](https://youtu.be/n1M8ZVspJcs) * Short read: [CVPR 2022 Best Paper Honorable Mention: Dual-Shutter Optical Vibration Sensing](https://www.louisbouchard.ai/cvpr-2022-best-paper/) * [Project page](https://imaging.cs.cmu.edu/vibration/) * Paper: [Dual-Shutter Optical Vibration Sensing](https://www.marksheinin.com/_files/ugd/a41a28_7d370603fafd419da387de85d8ecb5b4.pdf?index=true) ## Make-a-scene: Scene-based text-to-image generation with human priors [17]<a name="17"></a> Make-A-Scene is not “just another Dalle”. The goal of this new model isn’t to allow users to generate random images following text prompt as dalle does — which is really cool — but restricts the user control on the generations. Instead, Meta wanted to push creative expression forward, merging this text-to-image trend with previous sketch-to-image models, leading to “Make-A-Scene”: a fantastic blend between text and sketch-conditioned image generation. * Short Video Explanation:<br/> [<img src="https://imgur.com/bivyUmD.png" width="512"/>](https://youtu.be/K3bZXXjW788) * Short read: [Produce Amazing Artworks with Text and Sketches!](https://www.louisbouchard.ai/make-a-scene/) * Paper: [Make-a-scene: Scene-based text-to-image generation with human priors](https://arxiv.org/pdf/2203.13131.pdf) ## BANMo: Building Animatable 3D Neural Models from Many Casual Videos [18]<a name="18"></a> Create deformable 3D models from pictures with BANMo! * Short Video Explanation:<br/> [<img src="https://imgur.com/ulRCcMS.png" width="512"/>](https://youtu.be/jDTy-liFoCQ) * Short read: [Build Animatable 3D Models with AI](https://www.louisbouchard.ai/banmo/) * Paper: [BANMo: Building Animatable 3D Neural Models from Many Casual Videos](https://banmo-www.github.io/banmo-cvpr.pdf) * [Code](https://github.com/facebookresearch/banmo) ## High-resolution image synthesis with latent diffusion models [19]<a name="19"></a> What do all recent super powerful image models like DALLE, Imagen, or Midjourney have in common? Other than their high computing costs, huge training time, and shared hype, they are all based on the same mechanism: diffusion. Diffusion models recently achieved state-of-the-art results for most image tasks including text-to-image with DALLE but many other image generation-related tasks too, like image inpainting, style transfer or image super-resolution. * Short Video Explanation:<br/> [<img src="https://imgur.com/PanqNAf.png" width="512"/>](https://youtu.be/RGBNdD3Wn-g) * Short read: [Latent Diffusion Models: The Architecture behind Stable Diffusion](https://www.louisbouchard.ai/latent-diffusion-models/) * Paper: [High-resolution image synthesis with latent diffusion models](https://arxiv.org/pdf/2112.10752.pdf) * [Code](https://github.com/CompVis/latent-diffusion) 👀 **If you'd like to support my work**, you can check to [Sponsor](https://github.com/sponsors/louisfb01) this repository or support me on [Patreon](https://www.patreon.com/whatsai). ## Panoptic Scene Graph Generation [20]<a name="20"></a> Panoptic scene graph generation, or PSG, is a new problem task aiming to generate a more comprehensive graph representation of an image or scene based on panoptic segmentation rather than bounding boxes. It can be used to understand images and generate sentences describing what's happening. This may be the most challenging task for an AI! Learn more below... * Short Video Explanation:<br/> [<img src="https://imgur.com/QRQnydw.png" width="512"/>](https://youtu.be/cSsE_H_0Cr8) * Short read: [One of the Most Challenging Tasks for AI](https://www.louisbouchard.ai/psg/) * Paper: [Panoptic Scene Graph Generation](https://arxiv.org/abs/2207.11247) * [Code](https://github.com/Jingkang50/OpenPSG) * [Dataset](https://psgdataset.org/) ## An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion [21]<a name="21"></a> Text-to-Image models like DALLE or stable diffusion are really cool and allow us to generate fantastic pictures with a simple text input. But would it be even cooler to give them a picture of you and ask it to turn it into a painting? Imagine being able to send any picture of an object, person, or even your cat, and ask the model to transform it into another style like turning yourself into a cyborg of into your preferred artistic style or adding it to a new scene. Basically, how cool would it be to have a version of DALLE we can use to photoshop our pictures instead of having random generations? Having a personalized DALLE, while making it much more simple to control the generation as “an image is worth a thousand words”. It would be like having a DALLE model that is just as personalized and addictive as the TikTok algorithm. Well, this is what researchers from Tel Aviv University and NVIDIA worked on. They developed an approach for conditioning text-to-image models, like stable diffusion I covered last week, with a few images to represent any object or concept through the words you will send along your images. Transforming the object of your input images into whatever you want! * Short Video Explanation:<br/> [<img src="https://imgur.com/tpwcGVK.png" width="512"/>](https://youtu.be/f3oXa7_SYek) * Short read: [Guiding Stable Diffusion with your Images](https://www.louisbouchard.ai/imageworthoneword/) * Paper: [An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion](https://arxiv.org/pdf/2208.01618v1.pdf) * [Code](https://github.com/rinongal/textual_inversion) ## Expanding Language-Image Pretrained Models for General Video Recognition [22]<a name="22"></a> We’ve seen AI generate text, then generate images and most recently even generate short videos, even though they still need work. The results are incredible when you think that no one is actually involved in the creation process of these pieces and it only has to be trained once to then be used by thousands of people like stable diffusion is. Still, do these models really understand what they are doing? Do they know what the picture or video they just produced really represents? What does such a model understand when it sees such a picture or, even more complex, a video? * Short Video Explanation:<br/> [<img src="https://imgur.com/65Vz6if.png" width="512"/>](https://youtu.be/seb4lmVPEe8) * Short read: [General Video Recognition with AI](https://www.louisbouchard.ai/general-video-recognition/) * Paper: [Expanding Language-Image Pretrained Models for General Video Recognition](https://arxiv.org/abs/2208.02816) * [Code](https://github.com/microsoft/VideoX/tree/master/X-CLIP) ## MAKE-A-VIDEO: TEXT-TO-VIDEO GENERATION WITHOUT TEXT-VIDEO DATA [23]<a name="23"></a> Meta AI’s new model make-a-video is out and in a single sentence: it generates videos from text. It’s not only able to generate videos, but it’s also the new state-of-the-art method, producing higher quality and more coherent videos than ever before! * Short Video Explanation:<br/> [<img src="https://imgur.com/ZAv9FBH.png" width="512"/>](https://youtu.be/MWwESVyHWto) * Short read: [Make-a-video: The AI Film Maker!](https://www.louisbouchard.ai/make-a-video/) * Paper: [MAKE-A-VIDEO: TEXT-TO-VIDEO GENERATION WITHOUT TEXT-VIDEO DATA](https://makeavideo.studio/Make-A-Video.pdf) * [Code](https://github.com/lucidrains/make-a-video-pytorch) ## Robust Speech Recognition via Large-Scale Weak Supervision [24]<a name="24"></a> Have you ever dreamed of a good transcription tool that would accurately understand what you say and write it down? Not like the automatic YouTube translation tools… I mean, they are good but far from perfect. Just try it out and turn the feature on for the video, and you’ll see what I’m talking about. Luckily, OpenAI just released and open-sourced a pretty powerful AI model just for that: Whisper. It understands stuff I can’t even comprehend, not being a native English speaker (listen in the video) and it works for language translation too! * Short Video Explanation:<br/> [<img src="https://imgur.com/mPbvHfl.png" width="512"/>](https://youtu.be/uFOkMme19Zs) * Short read: [OpenAI's Most Recent Model: Whisper (explained)](https://www.louisbouchard.ai/whisper/) * Paper: [Robust Speech Recognition via Large-Scale Weak Supervision](https://cdn.openai.com/papers/whisper.pdf) * [Code](https://github.com/openai/whisper) ## DreamFusion: Text-to-3D using 2D Diffusion [25]<a name="25"></a> We’ve seen models able to take a sentence and generate images. Then, other approaches to manipulate the generated images by learning specific concepts like an object or particular style. Last week Meta published the Make-A-Video model that I covered, which allows you to generate a short video also from a text sentence. The results aren’t perfect yet, but the progress we’ve made in the field since last year is just incredible. This week we make another step forward. Here’s DreamFusion, a new Google Research model that can understand a sentence enough to generate a 3D model of it. You can see this as a DALLE or Stable Diffusion but in 3D. * Short Video Explanation:<br/> [<img src="https://imgur.com/kgvlHXu.png" width="512"/>](https://youtu.be/epuU0VRIcjE) * Short read: [3D Models from Text! DreamFusion Explained](https://www.louisbouchard.ai/dreamfusion/) * Paper: [DreamFusion: Text-to-3D using 2D Diffusion](https://arxiv.org/abs/2209.14988) ## Imagic: Text-Based Real Image Editing with Diffusion Models [26]<a name="26"></a> If you think the recent image generation models like DALLE or Stable Diffusion are cool, you just won’t believe how incredible this one is. "This one" is Imagic. Imagic takes such a diffusion-based model able to take text and generate images out of it and adapts the model to edit the images. You can generate an image and then teach the model to edit it any way you want. * Short Video Explanation:<br/> [<img src="https://imgur.com/rws0FYl.png" width="512"/>](https://youtu.be/gbpPQ5kVJhM) * Short read: [AI Image Editing from Text! Imagic Explained](https://www.louisbouchard.ai/imagic/) * Paper: [Imagic: Text-Based Real Image Editing with Diffusion Models](https://arxiv.org/abs/2210.09276) * [Stable Diffusion implementation](https://github.com/justinpinkney/stable-diffusion/blob/main/notebooks/imagic.ipynb) ## eDiffi: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers [27]<a name="27"></a> eDiffi, NVIDIA's most recent model, generates better-looking and more accurate images than all previous approaches like DALLE 2 or Stable Diffusion. eDiffi better understands the text you send and is more customizable, adding a feature we saw in a previous paper from NVIDIA: the painter tool. * Short Video Explanation:<br/> [<img src="https://imgur.com/e0g0rNe.png" width="512"/>](https://youtu.be/grwp-ht_ixo) * Short read: [eDiffi explained: New SOTA Image Synthesis model!](https://www.louisbouchard.ai/ediffi/) * Paper: [eDiffi: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers](https://arxiv.org/abs/2211.01324) 👀 **If you'd like to support my work**, you can check to [Sponsor](https://github.com/sponsors/louisfb01) this repository or support me on [Patreon](https://www.patreon.com/whatsai). ## InfiniteNature-Zero: Learning Perpetual View Generation of Natural Scenes from Single Images [28]<a name="28"></a> Generate infinite new frames as if you would be flying into your image! * Short Video Explanation:<br/> [<img src="https://imgur.com/hza3mLh.png" width="512"/>](https://youtu.be/FQzGhukV-l0) * Short read: [InfiniteNature-Zero: Fly Into Your Pictures With AI!](https://www.louisbouchard.ai/infinitenature-zero/) * Paper: [InfiniteNature-Zero: Learning Perpetual View Generation of Natural Scenes from Single Images](https://infinite-nature-zero.github.io/static/pdfs/InfiniteNatureZero.pdf) * [Code](https://github.com/google-research/google-research/tree/master/infinite_nature_zero) ## Galactica: A Large Language Model for Science [29]<a name="29"></a> Galactica is a large language model with a size comparable to GPT-3, but specialized on scientific knowledge. The model can write whitepapers, reviews, Wikipedia pages, and code. It knows how to cite and how to write equations. It’s kind of a big deal for AI and science. * Short Video Explanation:<br/> [<img src="https://imgur.com/HVEKpOY.png" width="512"/>](https://youtu.be/2GfxkCWWzLU) * Short read: [Galactica: What is it and What Happened?](https://www.louisbouchard.ai/galactica/) * Paper: [Galactica: A Large Language Model for Science](https://galactica.org/static/paper.pdf) ## Real-time Neural Radiance Talking Portrait Synthesis via Audio-spatial Decomposition [30]<a name="30"></a> From a single video, they can synthesize the person talking for pretty much any word or sentence in real time with better quality. You can animate a talking head following any audio track in real-time. * Short Video Explanation:<br/> [<img src="https://imgur.com/Sk6fDKu.png" width="512"/>](https://youtu.be/JUqnLN6Q4B0) * Short read: [From Audio to Talking Heads in Real-Time with AI! RAD-NeRF explained](https://www.louisbouchard.ai/rad-nerf/) * Paper: [Real-time Neural Radiance Talking Portrait Synthesis via Audio-spatial Decomposition](https://arxiv.org/abs/2211.12368) ## ChatGPT: Optimizing Language Models for Dialogue [31]<a name="31"></a> ChatGPT has taken over Twitter and pretty much the whole internet, thanks to its power and the meme potential it provides. We all know how being able to generate memes is the best way to conquer the internet, and so it worked. Since you’ve seen numerous examples, you might already know that ChatGPT is an AI recently released to the public by OpenAI, that you can chat with. It is also called a chatbot, meaning you can interact with it conversationally, imitatting a one-on-one human discussion. What you might not know is what it is and how it works... Watch the video or read the article or blog post below to learn more! * Short Video Explanation:<br/> [<img src="https://imgur.com/RpH5S2f.png" width="512"/>](https://youtu.be/AsFgn8vU-tQ) * Short read: [What is ChatGPT?](https://www.louisbouchard.ai/chatgpt/) * Blog Post: [ChatGPT: Optimizing Language Models for Dialogue](https://openai.com/blog/chatgpt/) ## Production-Ready Face Re-Aging for Visual Effects [32]<a name="32"></a> Whether it be for fun in a Snapchat filter, for a movie, or even to remove a few wrinkles, we all have a utility in mind for being able to change our age in a picture. This is usually done by skilled artists using Photoshop or a similar tool to edit your pictures. Worst, in a video, they have to do this kind of manual editing for every frame! Just imagine the amount of work needed for that. Well, here’s a solution and a new problem to this situation... 👇 * Short Video Explanation:<br/> [<img src="https://imgur.com/QOo0O5N.png" width="512"/>](https://youtu.be/WC03N0NFfwk) * Short read: [Automatic Re-Aging with AI! Disney’s FRAN Model Explained](https://www.louisbouchard.ai/disney-re-age/) * Blog Post: [Production-Ready Face Re-Aging for Visual Effects](https://studios.disneyresearch.com/2022/11/30/production-ready-face-re-aging-for-visual-effects/) --- >If you would like to read more papers and have a broader view, here is another great repository for you covering 2021: [2021: A Year Full of Amazing AI papers- A Review](https://github.com/louisfb01/best_AI_papers_2021) and feel free to subscribe to my weekly [newsletter](https://louisbouchard.substack.com/) and stay up-to-date with new publications in AI for 2022! *Tag me on **Twitter** [@Whats_AI](https://twitter.com/Whats_AI) or **LinkedIn** [@Louis (What's AI) Bouchard](https://www.linkedin.com/in/whats-ai/) if you share the list!* --- ## Paper references<a name="references"></a> [1] Suvorov, R., Logacheva, E., Mashikhin, A., Remizova, A., Ashukha, A., Silvestrov, A., Kong, N., Goka, H., Park, K. and Lempitsky, V., 2022. Resolution-robust Large Mask Inpainting with Fourier Convolutions. In Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision (pp. 2149–2159)., https://arxiv.org/pdf/2109.07161.pdf [2] Tzaban, R., Mokady, R., Gal, R., Bermano, A.H. and Cohen-Or, D., 2022. Stitch it in Time: GAN-Based Facial Editing of Real Videos. https://arxiv.org/abs/2201.08361 [3] Kuang, Z., Olszewski, K., Chai, M., Huang, Z., Achlioptas, P. and Tulyakov, S., 2022. NeROIC: Neural Rendering of Objects from Online Image Collections. https://arxiv.org/pdf/2201.02533.pdf [4] Borsos, Z., Sharifi, M. and Tagliasacchi, M., 2022. SpeechPainter: Text-conditioned Speech Inpainting. https://arxiv.org/pdf/2202.07273.pdf [5] Wang, X., Li, Y., Zhang, H. and Shan, Y., 2021. Towards real-world blind face restoration with generative facial prior. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 9168–9178), https://arxiv.org/pdf/2101.04061.pdf [6] Piergiovanni, A.J., Casser, V., Ryoo, M.S. and Angelova, A., 2021. 4d-net for learned multi-modal alignment. In Proceedings of the IEEE/CVF International Conference on Computer Vision (pp. 15435–15445), https://openaccess.thecvf.com/content/ICCV2021/papers/Piergiovanni_4D-Net_for_Learned_Multi-Modal_Alignment_ICCV_2021_paper.pdf. [7] Thomas Muller, Alex Evans, Christoph Schied and Alexander Keller, 2022, "Instant Neural Graphics Primitives with a Multiresolution Hash Encoding", https://nvlabs.github.io/instant-ngp/assets/mueller2022instant.pdf [8] A. Ramesh et al., 2022, "Hierarchical Text-Conditional Image Generation with CLIP Latents", https://cdn.openai.com/papers/dall-e-2.pdf [9] Nitzan, Y., Aberman, K., He, Q., Liba, O., Yarom, M., Gandelsman, Y., Mosseri, I., Pritch, Y. and Cohen-Or, D., 2022. MyStyle: A Personalized Generative Prior. arXiv preprint arXiv:2203.17272. [10] Zhang, Susan et al. “OPT: Open Pre-trained Transformer Language Models.” https://arxiv.org/abs/2205.01068 [11] Epstein, D., Park, T., Zhang, R., Shechtman, E. and Efros, A.A., 2022. BlobGAN: Spatially Disentangled Scene Representations. arXiv preprint arXiv:2205.02837. [12] Reed S. et al., 2022, Deemind: Gato - A generalist agent, https://storage.googleapis.com/deepmind-media/A%20Generalist%20Agent/Generalist%20Agent.pdf [13] Saharia et al., 2022, Google Brain, Photorealistic Text-to-Image Diffusion Models with Deep Language Understanding, https://gweb-research-imagen.appspot.com/paper.pdf [14] Dayma, et al., 2021, DALL·E Mini, doi:10.5281/zenodo.5146400 [15] NLLB Team et al., 2022, No Language Left Behind: Scaling Human-Centered Machine Translation [16] Sheinin, Mark and Chan, Dorian and O’Toole, Matthew and Narasimhan, Srinivasa G., 2022, Dual-Shutter Optical Vibration Sensing, Proc. IEEE CVPR. [17] Gafni, O., Polyak, A., Ashual, O., Sheynin, S., Parikh, D. and Taigman, Y., 2022. Make-a-scene: Scene-based text-to-image generation with human priors. https://arxiv.org/pdf/2203.13131.pdf [18] Yang, G., Vo, M., Neverova, N., Ramanan, D., Vedaldi, A. and Joo, H., 2022. Banmo: Building animatable 3d neural models from many casual videos. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 2863-2873). [19] Rombach, R., Blattmann, A., Lorenz, D., Esser, P. and Ommer, B., 2022. High-resolution image synthesis with latent diffusion models. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 10684–10695), https://arxiv.org/pdf/2112.10752.pdf [20] Yang, J., Ang, Y.Z., Guo, Z., Zhou, K., Zhang, W. and Liu, Z., 2022. Panoptic Scene Graph Generation. arXiv preprint arXiv:2207.11247. [21] Gal, R., Alaluf, Y., Atzmon, Y., Patashnik, O., Bermano, A.H., Chechik, G. and Cohen-Or, D., 2022. An Image is Worth One Word: Personalizing Text-to-Image Generation using Textual Inversion. [22] Ni, B., Peng, H., Chen, M., Zhang, S., Meng, G., Fu, J., Xiang, S. and Ling, H., 2022. Expanding Language-Image Pretrained Models for General Video Recognition. arXiv preprint arXiv:2208.02816. [23] Singer et al. (Meta AI), 2022, “MAKE-A-VIDEO: TEXT-TO-VIDEO GENERATION WITHOUT TEXT-VIDEO DATA”, https://makeavideo.studio/Make-A-Video.pdf [24] Radford, A., Kim, J.W., Xu, T., Brockman, G., McLeavey, C. and Sutskever, I., Robust Speech Recognition via Large-Scale Weak Supervision. [25] Poole, B., Jain, A., Barron, J.T. and Mildenhall, B., 2022. DreamFusion: Text-to-3D using 2D Diffusion. arXiv preprint arXiv:2209.14988. [26] Kawar, B., Zada, S., Lang, O., Tov, O., Chang, H., Dekel, T., Mosseri, I. and Irani, M., 2022. Imagic: Text-Based Real Image Editing with Diffusion Models. arXiv preprint arXiv:2210.09276. [27] Balaji, Y. et al., 2022, eDiffi: Text-to-Image Diffusion Models with an Ensemble of Expert Denoisers, https://arxiv.org/abs/2211.01324 [28] Li, Z., Wang, Q., Snavely, N. and Kanazawa, A., 2022. InfiniteNature-Zero: Learning Perpetual View Generation of Natural Scenes from Single Images. In European Conference on Computer Vision (pp. 515–534). Springer, Cham, https://arxiv.org/abs/2207.11148 [29] Taylor et al., 2022: Galactica: A Large Language Model for Science, https://galactica.org/ [30] Tang, J., Wang, K., Zhou, H., Chen, X., He, D., Hu, T., Liu, J., Zeng, G. and Wang, J., 2022. Real-time Neural Radiance Talking Portrait Synthesis via Audio-spatial Decomposition. arXiv preprint arXiv:2211.12368. [31] OpenAI, 2022: ChatGPT: Optimizing Language Models for Dialogue, https://openai.com/blog/chatgpt/ [32] Loss et al., DisneyResearch, 2022: FRAN, https://studios.disneyresearch.com/2022/11/30/production-ready-face-re-aging-for-visual-effects/

A curated list of the latest breakthroughs in AI (in 2022) by release date with a clear video explanation, link to a more in-depth article, and code.

python,computer-vision,computer-science,deep-learning,machine-learning,artificial-intelligence,ai,paper,technology,innovation

paperswithbacktest/awesome-systematic-trading

<div align="center"> <img src="static/images/awesome-systematic-trading.jpeg" height=200 alt=""/> <h1>Awesome Systematic Trading</h1> </div> <div align=center><img src="https://awesome.re/badge.svg" /></div> [希望阅读中文版？点我](./README_zh.md) We are collecting a list of resources papers, softwares, books, articles for finding, developing, and running systematic trading (quantitative trading) strategies. <!-- omit in toc --> ### What will you find here? - [97 libraries and packages](#libraries-and-packages) for research and live trading - [696 strategies](#strategies) described by institutionals and academics - [55 books](#books) for beginners and professionals - [23 videos](#videos) and interviews - And also some [blogs](#blogs) and [courses](#courses) <div align="center" style="margin-bottom: 50px; margin-top: 50px;"> <div style="border: 2px solid #007bff; border-radius: 10px; padding: 20px; margin-bottom: 20px;"> <h2>📈 Interested in trading strategies implemented in Python?</h2> <p>Visit our comprehensive collection at <a href="https://paperswithbacktest.com" target="_blank">paperswithbacktest.com</a> for exclusive content!</p> </div> </div> <details> <summary>Click here to see the full table of content</summary> - [Libraries and packages](#libraries-and-packages) - [Backtesting and Live Trading](#backtesting-and-live-trading) - [General - Event Driven Frameworks](#general---event-driven-frameworks) - [General - Vector Based Frameworks](#general---vector-based-frameworks) - [Cryptocurrencies](#cryptocurrencies) - [Trading bots](#trading-bots) - [Analytics](#analytics) - [Indicators](#indicators) - [Metrics computation](#metrics-computation) - [Optimization](#optimization) - [Pricing](#pricing) - [Risk](#risk) - [Broker APIs](#broker-apis) - [Data Sources](#data-sources) - [General](#general) - [Cryptocurrencies](#cryptocurrencies-1) - [Data Science](#data-science) - [Databases](#databases) - [Graph Computation](#graph-computation) - [Machine Learning](#machine-learning) - [TimeSeries Analysis](#timeseries-analysis) - [Visualization](#visualization) - [Strategies](#strategies) - [Bonds, commodities, currencies, equities](#bonds-commodities-currencies-equities) - [Bonds, commodities, equities, REITs](#bonds-commodities-equities-reits) - [Bonds, equities](#bonds-equities) - [Bonds, equities, REITs](#bonds-equities-reits) - [Commodities](#commodities) - [Cryptos](#cryptos) - [Currencies](#currencies) - [Equities](#equities) - [Books](#books) - [Beginner](#beginner) - [Biography](#biography) - [Coding](#coding) - [Crypto](#crypto) - [General](#general-1) - [High Frequency Trading](#high-frequency-trading) - [Machine Learning](#machine-learning-1) - [Videos](#videos) - [Blogs](#blogs) - [Courses](#courses) </details> <!-- omit in toc --> > ### How can I help? > You can help by submitting an issue with suggestions and by sharing on Twitter: > > [](https://twitter.com/intent/tweet?text=A%20free%20and%20comprehensive%20list%20of%20papers%2C%20libraries%2C%20books%2C%20blogs%2C%20tutorials%20for%20quantitative%20traders.&url=https://github.com/edarchimbaud/awesome-systematic-trading) # Libraries and packages *List of **97 libraries and packages** implementing trading bots, backtesters, indicators, pricers, etc. Each library is categorized by its programming language and ordered by descending populatrity (number of stars).* ## Backtesting and Live Trading ### General - Event Driven Frameworks | Repository | Description | Stars | Made with | |------------|-------------|-------|-----------| | [vnpy](https://github.com/vnpy/vnpy) | Python-based open source quantitative trading system development framework, officially released in January 2015, has grown step by step into a full-featured quantitative trading platform |  |  | | [zipline](https://github.com/quantopian/zipline) | Zipline is a Pythonic algorithmic trading library. It is an event-driven system for backtesting. |  |  | | [backtrader](https://github.com/mementum/backtrader) | Event driven Python Backtesting library for trading strategies |  |  | | [QUANTAXIS](https://github.com/QUANTAXIS/QUANTAXIS) | QUANTAXIS 支持任务调度 分布式部署的 股票/期货/期权/港股/虚拟货币 数据/回测/模拟/交易/可视化/多账户 纯本地量化解决方案 |  |  | | [QuantConnect](https://github.com/QuantConnect/Lean) | Lean Algorithmic Trading Engine by QuantConnect (Python, C#) |  |  | | [Rqalpha](https://github.com/ricequant/rqalpha) | A extendable, replaceable Python algorithmic backtest && trading framework supporting multiple securities |  |  | | [finmarketpy](https://github.com/cuemacro/finmarketpy) | Python library for backtesting trading strategies & analyzing financial markets (formerly pythalesians) |  |  | | [backtesting.py](https://github.com/kernc/backtesting.py) | Backtesting.py is a Python framework for inferring viability of trading strategies on historical (past) data. Improved upon the vision of Backtrader, and by all means surpassingly comparable to other accessible alternatives, Backtesting.py is lightweight, fast, user-friendly, intuitive, interactive, intelligent and, hopefully, future-proof. |  |  | | [zvt](https://github.com/zvtvz/zvt) | Modular quant framework |  |  | | [WonderTrader](https://github.com/wondertrader/wondertrader) | WonderTrader——量化研发交易一站式框架 |  |  | | [nautilus_trader](https://github.com/nautechsystems/nautilus_trader) | A high-performance algorithmic trading platform and event-driven backtester |  |  | | [PandoraTrader](https://github.com/pegasusTrader/PandoraTrader) | High-frequency quantitative trading platform based on c++ development, supporting multiple trading APIs and cross-platform |  |  | | [HFTBacktest](https://github.com/nkaz001/hftbacktest) | Highly precise backtest on HFT data in Python+Numba |  |  | | [aat](https://github.com/AsyncAlgoTrading/aat) | An asynchronous, event-driven framework for writing algorithmic trading strategies in python with optional acceleration in C++. It is designed to be modular and extensible, with support for a wide variety of instruments and strategies, live trading across (and between) multiple exchanges. |  |  | | [sdoosa-algo-trade-python](https://github.com/sreenivasdoosa/sdoosa-algo-trade-python) | This project is mainly for newbies into algo trading who are interested in learning to code their own trading algo using python interpreter. |  |  | | [lumibot](https://github.com/Lumiwealth/lumibot) | A very simple yet useful backtesting and sample based live trading framework (a bit slow to run...) |  |  | | [quanttrader](https://github.com/letianzj/quanttrader) | Backtest and live trading in Python. Event based. Similar to backtesting.py. |  |  | | [gobacktest](https://github.com/gobacktest/gobacktest) | A Go implementation of event-driven backtesting framework |  |  | | [FlashFunk](https://github.com/HFQR/FlashFunk) | High Performance Runtime in Rust |  |  | ### General - Vector Based Frameworks | Repository | Description | Stars | Made with | |------------|-------------|-------|-----------| | [vectorbt](https://github.com/polakowo/vectorbt) | vectorbt takes a novel approach to backtesting: it operates entirely on pandas and NumPy objects, and is accelerated by Numba to analyze any data at speed and scale. This allows for testing of many thousands of strategies in seconds. |  |  | | [pysystemtrade](https://github.com/robcarver17/pysystemtrade) | Systematic Trading in python from book Systematic Trading by Rob Carver |  |  | | [bt](https://github.com/pmorissette/bt) | Flexible backtesting for Python based on Algo and Strategy Tree |  |  | ### Cryptocurrencies | Repository | Description | Stars | Made with | |------------|-------------|-------|-----------| | [Freqtrade](https://github.com/freqtrade/freqtrade) | Freqtrade is a free and open source crypto trading bot written in Python. It is designed to support all major exchanges and be controlled via Telegram. It contains backtesting, plotting and money management tools as well as strategy optimization by machine learning. |  |  | | [Jesse](https://github.com/jesse-ai/jesse) | Jesse is an advanced crypto trading framework which aims to simplify researching and defining trading strategies. |  |  | | [OctoBot](https://github.com/Drakkar-Software/OctoBot) | Cryptocurrency trading bot for TA, arbitrage and social trading with an advanced web interface |  |  | | [Kelp](https://github.com/stellar/kelp) | Kelp is a free and open-source trading bot for the Stellar DEX and 100+ centralized exchanges |  |  | | [openlimits](https://github.com/nash-io/openlimits) | A Rust high performance cryptocurrency trading API with support for multiple exchanges and language wrappers. |  |  | | [bTrader](https://github.com/gabriel-milan/btrader) | Triangle arbitrage trading bot for Binance |  |  | | [crypto-crawler-rs](https://github.com/crypto-crawler/crypto-crawler-rs) | Crawl orderbook and trade messages from crypto exchanges |  |  | | [Hummingbot](https://github.com/CoinAlpha/hummingbot) | A client for crypto market making |  |  | | [cryptotrader-core](https://github.com/monomadic/cryptotrader-core) | Simple to use Crypto Exchange REST API client in rust. |  |  | ## Trading bots *Trading bots and alpha models. Some of them are old and not maintained.* | Repository | Description | Stars | Made with | |------------|-------------|-------|-----------| | [Blackbird](https://github.com/butor/blackbird) | Blackbird Bitcoin Arbitrage: a long/short market-neutral strategy |  |  | | [bitcoin-arbitrage](https://github.com/maxme/bitcoin-arbitrage) | Bitcoin arbitrage - opportunity detector |  |  | | [ThetaGang](https://github.com/brndnmtthws/thetagang) | ThetaGang is an IBKR bot for collecting money |  |  | | [czsc](https://github.com/waditu/czsc) | 缠中说禅技术分析工具；缠论；股票；期货；Quant；量化交易 |  |  | | [R2 Bitcoin Arbitrager](https://github.com/bitrinjani/r2) | R2 Bitcoin Arbitrager is an automatic arbitrage trading system powered by Node.js + TypeScript |  |  | | [analyzingalpha](https://github.com/leosmigel/analyzingalpha) | Implementation of simple strategies |  |  | | [PyTrendFollow](https://github.com/chrism2671/PyTrendFollow) | PyTrendFollow - systematic futures trading using trend following |  |  | ## Analytics ### Indicators *Libraries of indicators to predict future price movements.* | Repository | Description | Stars | Made with | |------------|-------------|-------|-----------| | [ta-lib](https://github.com/mrjbq7/ta-lib) | Perform technical analysis of financial market data |  |  | | [go-tart](https://github.com/iamjinlei/go-tart) | A Go implementation of the [ta-lib]((https://github.com/mrjbq7/ta-lib) with streaming update support |  |  | | [pandas-ta](https://github.com/twopirllc/pandas-ta) | Pandas Technical Analysis (Pandas TA) is an easy to use library that leverages the Pandas package with more than 130 Indicators and Utility functions and more than 60 TA Lib Candlestick Patterns |  |  | | [finta](https://github.com/peerchemist/finta) | Common financial technical indicators implemented in Pandas |  |  | | [ta-rust](https://github.com/greyblake/ta-rs) | Technical analysis library for Rust language |  |  | ### Metrics computation *Librairies of financial metrics.* | Repository | Description | Stars | Made with | |------------|-------------|-------|-----------| | [quantstats](https://github.com/ranaroussi/quantstats) | Portfolio analytics for quants, written in Python |  |  | | [ffn](https://github.com/pmorissette/ffn) | A financial function library for Python |  |  | ### Optimization | Repository | Description | Stars | Made with | |------------|-------------|-------|-----------| | [PyPortfolioOpt](https://github.com/robertmartin8/PyPortfolioOpt) | Financial portfolio optimizations in python, including classical efficient frontier, Black-Litterman, Hierarchical Risk Parity |  |  | | [Riskfolio-Lib](https://github.com/dcajasn/Riskfolio-Lib) | Portfolio Optimization and Quantitative Strategic Asset Allocation in Python |  |  | | [empyrial](https://github.com/ssantoshp/Empyrial) | Empyrial is a Python-based open-source quantitative investment library dedicated to financial institutions and retail investors, officially released in March 2021 |  |  | | [Deepdow](https://github.com/jankrepl/deepdow) | Python package connecting portfolio optimization and deep learning. Its goal is to facilitate research of networks that perform weight allocation in one forward pass. |  |  | | [spectre](https://github.com/Heerozh/spectre) | Portfolio Optimization and Quantitative Strategic Asset Allocation in Python |  |  | ### Pricing | Repository | Description | Stars | Made with | |------------|-------------|-------|-----------| | [tf-quant-finance](https://github.com/google/tf-quant-finance) | High-performance TensorFlow library for quantitative finance from Google |  |  | | [FinancePy](https://github.com/domokane/FinancePy) | A Python Finance Library that focuses on the pricing and risk-management of Financial Derivatives, including fixed-income, equity, FX and credit derivatives |  |  | | [PyQL](https://github.com/enthought/pyql) | Python wrapper of the famous pricing library QuantLib |  |  | ### Risk | Repository | Description | Stars | Made with | |------------|-------------|-------|-----------| | [pyfolio](https://github.com/quantopian/pyfolio) | Portfolio and risk analytics in Python |  |  | ## Broker APIs | Repository | Description | Stars | Made with | |------------|-------------|-------|-----------| | [ccxt](https://github.com/ccxt/ccxt) | A JavaScript / Python / PHP cryptocurrency trading API with support for more than 100 bitcoin/altcoin exchanges |  |  | | [Ib_insync](https://github.com/erdewit/ib_insync) | Python sync/async framework for Interactive Brokers. |  |  | | [Coinnect](https://github.com/hugues31/coinnect) | Coinnect is a Rust library aiming to provide a complete access to main crypto currencies exchanges via REST API. |  |  | | [PENDAX](https://github.com/CompendiumFi/PENDAX-SDK) | Javascript SDK for Trading, Data, and Websockets for FTX, FTXUS, OKX, Bybit, & More. |  |  | ## Data Sources ### General | Repository | Description | Stars | Made with | |------------|-------------|-------|-----------| | [OpenBB Terminal](https://github.com/OpenBB-finance/OpenBBTerminal) | Investment Research for Everyone, Anywhere. |  |  | | [TuShare](https://github.com/waditu/tushare) | TuShare is a utility for crawling historical data of China stocks |  |  | | [yfinance](https://github.com/ranaroussi/yfinance) | yfinance offers a threaded and Pythonic way to download market data from Yahoo!Ⓡ finance. |  |  | | [AkShare](https://github.com/akfamily/akshare) | AKShare is an elegant and simple financial data interface library for Python, built for human beings! |  |  | | [pandas-datareader](https://github.com/pydata/pandas-datareader) | Up to date remote data access for pandas, works for multiple versions of pandas. |  |  | | [Quandl](https://github.com/quandl/quandl-python) | Get millions of financial and economic dataset from hundreds of publishers via a single free API. |  |  | | [findatapy](https://github.com/cuemacro/findatapy) | findatapy creates an easy to use Python API to download market data from many sources including Quandl, Bloomberg, Yahoo, Google etc. using a unified high level interface. |  |  | | [Investpy](https://github.com/alvarobartt/investpy) | Financial Data Extraction from Investing.com with Python |  |  | | [Fundamental Analysis Data](https://github.com/JerBouma/FundamentalAnalysis) | Fully-fledged Fundamental Analysis package capable of collecting 20 years of Company Profiles, Financial Statements, Ratios and Stock Data of 20.000+ companies. |  |  | | [Wallstreet](https://github.com/mcdallas/wallstreet) | Wallstreet: Real time Stock and Option tools |  |  | ### Cryptocurrencies | Repository | Description | Stars | Made with | |------------|-------------|-------|-----------| | [Cryptofeed](https://github.com/bmoscon/cryptofeed) | Cryptocurrency Exchange Websocket Data Feed Handler with Asyncio |  |  | | [Gekko-Datasets](https://github.com/xFFFFF/Gekko-Datasets) | Gekko trading bot dataset dumps. Download and use history files in SQLite format. |  |  | | [CryptoInscriber](https://github.com/Optixal/CryptoInscriber) | A live crypto currency historical trade data blotter. Download live historical trade data from any crypto exchange. |  |  | | [Crypto Lake](https://github.com/crypto-lake/lake-api) | High frequency order book & trade data for crypto |  |  | ## Data Science | Repository | Description | Stars | Made with | |------------|-------------|-------|-----------| | [TensorFlow](https://github.com/tensorflow/tensorflow) | Fundamental algorithms for scientific computing in Python |  |  | | [Pytorch](https://github.com/pytorch/pytorch) | Tensors and Dynamic neural networks in Python with strong GPU acceleration |  |  | | [Keras](https://github.com/keras-team/keras) | The most user friendly Deep Learning for humans in Python |  |  | | [Scikit-learn](https://github.com/scikit-learn/scikit-learn) | Machine learning in Python |  |  | | [Pandas](https://github.com/pandas-dev/pandas) | Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more |  |  | | [Numpy](https://github.com/numpy/numpy) | The fundamental package for scientific computing with Python |  |  | | [Scipy](https://github.com/scipy/scipy) | Fundamental algorithms for scientific computing in Python |  |  | | [PyMC](https://github.com/pymc-devs/pymc) | Probabilistic Programming in Python: Bayesian Modeling and Probabilistic Machine Learning with Aesara |  |  | | [Cvxpy](https://github.com/cvxpy/cvxpy) | A Python-embedded modeling language for convex optimization problems. |  |  | ## Databases | Repository | Description | Stars | Made with | |------------|-------------|-------|-----------| | [Marketstore](https://github.com/alpacahq/marketstore) | DataFrame Server for Financial Timeseries Data |  |  | | [Tectonicdb](https://github.com/0b01/tectonicdb) | Tectonicdb is a fast, highly compressed standalone database and streaming protocol for order book ticks. |  |  | | [ArcticDB (Man Group)](https://github.com/man-group/arcticdb) | High performance datastore for time series and tick data |  |  | ## Graph Computation | Repository | Description | Stars | Made with | |------------|-------------|-------|-----------| | [Ray](https://github.com/ray-project/ray) | An open source framework that provides a simple, universal API for building distributed applications. |  |  | | [Dask](https://github.com/dask/dask) | Parallel computing with task scheduling in Python with a Pandas like API |  |  | | [Incremental (JaneStreet)](https://github.com/janestreet/incremental) | Incremental is a library that gives you a way of building complex computations that can update efficiently in response to their inputs changing, inspired by the work of Umut Acar et. al. on self-adjusting computations. Incremental can be useful in a number of applications |  |  | | [Man MDF](https://github.com/man-group/mdf) | Data-flow programming toolkit for Python |  |  | | [GraphKit](https://github.com/yahoo/graphkit) | A lightweight Python module for creating and running ordered graphs of computations. |  |  | | [Tributary](https://github.com/timkpaine/tributary) | Streaming reactive and dataflow graphs in Python |  |  | ## Machine Learning | Repository | Description | Stars | Made with | |------------|-------------|-------|-----------| | [QLib (Microsoft)](https://github.com/microsoft/qlib) | Qlib is an AI-oriented quantitative investment platform, which aims to realize the potential, empower the research, and create the value of AI technologies in quantitative investment. With Qlib, you can easily try your ideas to create better Quant investment strategies. An increasing number of SOTA Quant research works/papers are released in Qlib. |  |  | | [FinRL](https://github.com/AI4Finance-Foundation/FinRL) | FinRL is the first open-source framework to demonstrate the great potential of applying deep reinforcement learning in quantitative finance. |  |  | | [MlFinLab (Hudson & Thames)](https://github.com/hudson-and-thames/mlfinlab) | MlFinLab helps portfolio managers and traders who want to leverage the power of machine learning by providing reproducible, interpretable, and easy to use tools. |  |  | | [TradingGym](https://github.com/Yvictor/TradingGym) | Trading and Backtesting environment for training reinforcement learning agent or simple rule base algo. |  |  | | [Stock Trading Bot using Deep Q-Learning](https://github.com/pskrunner14/trading-bot) | Stock Trading Bot using Deep Q-Learning |  |  | ## TimeSeries Analysis | Repository | Description | Stars | Made with | |------------|-------------|-------|-----------| | [Facebook Prophet](https://github.com/facebook/prophet) | Tool for producing high quality forecasts for time series data that has multiple seasonality with linear or non-linear growth. |  |  | | [statsmodels](https://github.com/statsmodels/statsmodels) | Python module that allows users to explore data, estimate statistical models, and perform statistical tests. |  |  | | [tsfresh](https://github.com/blue-yonder/tsfresh) | Automatic extraction of relevant features from time series. |  |  | | [pmdarima](https://github.com/alkaline-ml/pmdarima) | A statistical library designed to fill the void in Python's time series analysis capabilities, including the equivalent of R's auto.arima function. |  |  | ## Visualization | Repository | Description | Stars | Made with | |------------|-------------|-------|-----------| | [D-Tale (Man Group)](https://github.com/man-group/dtale) | D-Tale is the combination of a Flask back-end and a React front-end to bring you an easy way to view & analyze Pandas data structures. |  |  | | [mplfinance](https://github.com/matplotlib/mplfinance) | Financial Markets Data Visualization using Matplotlib |  |  | | [btplotting](https://github.com/happydasch/btplotting) | btplotting provides plotting for backtests, optimization results and live data from backtrader. |  |  | # Strategies *List of **696 academic papers** describing original systematic trading strategies. Each strategy is categorized by its asset class and ordered by descending Sharpe ratio.* 👉 Strategies are now hosted [here](https://paperswithbacktest.com): - [Bonds strategies (7)](https://paperswithbacktest.com/bonds) - [Commodities strategies (50)](https://paperswithbacktest.com/commodities) - [Cryptocurrencies strategies (12)](https://paperswithbacktest.com/cryptocurrencies) - [Currencies strategies (67)](https://paperswithbacktest.com/currencies) - [Equities strategies (471)](https://paperswithbacktest.com/equities) - [Options strategies (8)](https://paperswithbacktest.com/options) - [Bonds / Commodities / Currencies / Equities strategies (22)](https://paperswithbacktest.com/bonds-commodities-currencies-equities) - [Bonds / Commodities / Equities strategies (6)](https://paperswithbacktest.com/bonds-commodities-equities) - [Bonds / Commodities / Equities / REITs strategies (6)](https://paperswithbacktest.com/bonds-commodities-equities-reits) - [Bonds / Equities strategies (13)](https://paperswithbacktest.com/bonds-equities) - [Bonds / Equities / REITs strategies (6)](https://paperswithbacktest.com/bonds-equities-reits) - [Commodities / Equities strategies (3)](https://paperswithbacktest.com/commodities-equities) - [Equities / Options strategies (24)](https://paperswithbacktest.com/equities-options) - [Equities / REITs strategies (1)](https://paperswithbacktest.com/equities-reits) Previous list of strategies: ## Bonds, commodities, currencies, equities | Title | Sharpe Ratio | Volatility | Rebalancing | Implementation | Source | |-------------|--------------|------------|-------------|----------------|--------| | Time Series Momentum Effect | `0.576` | `20.5%` | `Monthly` | [QuantConnect](./static/strategies/time-series-momentum-effect.py) | [Paper](https://pages.stern.nyu.edu/~lpederse/papers/TimeSeriesMomentum.pdf) | | Short Term Reversal with Futures | `-0.05` | `12.3%` | `Weekly` | [QuantConnect](./static/strategies/asset-class-momentum-rotational-system.py) | [Paper](https://ideas.repec.org/a/eee/jbfina/v28y2004i6p1337-1361.html) | ## Bonds, commodities, equities, REITs | Title | Sharpe Ratio | Volatility | Rebalancing | Implementation | Source | |--------------|--------------|------------|-------------|----------------|--------| | Asset Class Trend-Following | `0.502` | `10.4%` | `Monthly` | [QuantConnect](./static/strategies/asset-class-trend-following.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=962461) | | Momentum Asset Allocation Strategy | `0.321` | `11%` | `Monthly` | [QuantConnect](./static/strategies/asset-class-trend-following.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1585517) | ## Bonds, equities | Title | Sharpe Ratio | Volatility | Rebalancing | Implementation | Source | |--------------|--------------|------------|-------------|----------------|--------| | Paired Switching | `0.691` | `9.5%` | `Quarterly` | [QuantConnect](./static/strategies/paired-switching.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1917044) | | FED Model | `0.369` | `14.3%` | `Monthly` | [QuantConnect](./static/strategies/fed-model.py) | [Paper](https://www.researchgate.net/publication/228267011_The_FED_Model_and_Expected_Asset_Returns) | ## Bonds, equities, REITs | Title | Sharpe Ratio | Volatility | Rebalancing | Implementation | Source | |--------------|--------------|------------|-------------|----------------|--------| | Value and Momentum Factors across Asset Classes | `0.155` | `9.8%` | `Monthly` | [QuantConnect](./static/strategies/value-and-momentum-factors-across-asset-classes.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1079975) | ## Commodities | Title | Sharpe Ratio | Volatility | Rebalancing | Implementation | Source | |--------------|--------------|------------|-------------|----------------|--------| | Skewness Effect in Commodities | `0.482` | `17.7%` | `Monthly` | [QuantConnect](./static/strategies/skewness-effect-in-commodities.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2671165) | | Return Asymmetry Effect in Commodity Futures | `0.239` | `13.4%` | `Monthly` | [QuantConnect](./static/strategies/return-asymmetry-effect-in-commodity-futures.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3918896) | | Momentum Effect in Commodities | `0.14` | `20.3%` | `Monthly` | [QuantConnect](./static/strategies/momentum-effect-in-commodities.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=702281) | | Term Structure Effect in Commodities | `0.128` | `23.1%` | `Monthly` | [QuantConnect](./static/strategies/term-structure-effect-in-commodities.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1127213) | | Trading WTI/BRENT Spread | `-0.199` | `11.6%` | `Daily` | [QuantConnect](./static/strategies/trading-wti-brent-spread.py) | [Paper](https://link.springer.com/article/10.1057/jdhf.2009.24) | ## Cryptos | Title | Sharpe Ratio | Volatility | Rebalancing | Implementation | Source | |--------------|--------------|------------|-------------|----------------|--------| | Overnight Seasonality in Bitcoin | `0.892` | `20.8%` | `Intraday` | [QuantConnect](./static/strategies/intraday-seasonality-in-bitcoin.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4081000) | | Rebalancing Premium in Cryptocurrencies | `0.698` | `27.5%` | `Daily` | [QuantConnect](./static/strategies/rebalancing-premium-in-cryptocurrencies.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3982120) | ## Currencies | Title | Sharpe Ratio | Volatility | Rebalancing | Implementation | Source | |--------------|--------------|------------|-------------|----------------|--------| | FX Carry Trade | `0.254` | `7.8%` | `Monthly` | [QuantConnect](./static/strategies/fx-carry-trade.py) | [Paper](http://globalmarkets.db.com/new/docs/dbCurrencyReturns_March2009.pdf) | | Dollar Carry Trade | `0.113` | `5.8%` | `Monthly` | [QuantConnect](./static/strategies/dollar-carry-trade.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1541230) | | Currency Momentum Factor | `-0.01` | `6.7%` | `Monthly` | [QuantConnect](./static/strategies/currency-momentum-factor.py) | [Paper](http://globalmarkets.db.com/new/docs/dbCurrencyReturns_March2009.pdf) | | Currency Value Factor – PPP Strategy | `-0.103` | `5%` | `Quarterly` | [QuantConnect](./static/strategies/currency-value-factor-ppp-strategy.py) | [Paper](http://globalmarkets.db.com/new/docs/dbCurrencyReturns_March2009.pdf) | ## Equities | Title | Sharpe Ratio | Volatility | Rebalancing | Implementation | Source | |--------------|--------------|------------|-------------|----------------|--------| | Asset Growth Effect | `0.835` | `10.2%` | `Yearly` | [QuantConnect](./static/strategies/asset-growth-effect.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1335524) | | Short Term Reversal Effect in Stocks | `0.816` | `21.4%` | `Weekly` | [QuantConnect](./static/strategies/short-term-reversal-in-stocks.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1605049) | | Reversal During Earnings-Announcements | `0.785` | `25.7%` | `Daily` | [QuantConnect](./static/strategies/reversal-during-earnings-announcements.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2275982) | | Size Factor – Small Capitalization Stocks Premium | `0.747` | `11.1%` | `Yearly` | [QuantConnect](./static/strategies/small-capitalization-stocks-premium-anomaly.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3177539) | | Low Volatility Factor Effect in Stocks | `0.717` | `11.5%` | `Monthly` | [QuantConnect](./static/strategies/low-volatility-factor-effect-in-stocks.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=980865) | | How to Use Lexical Density of Company Filings | `0.688` | `10.4%` | `Monthly` | [QuantConnect](./static/strategies/how-to-use-lexical-density-of-company-filings.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3921091) | | Volatility Risk Premium Effect | `0.637` | `13.2%` | `Monthly` | [QuantConnect](./static/strategies/volatility-risk-premium-effect.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=189840) | | Pairs Trading with Stocks | `0.634` | `8.5%` | `Daily` | [QuantConnect](./static/strategies/pairs-trading-with-stocks.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=141615) | | Crude Oil Predicts Equity Returns | `0.599` | `11.5%` | `Monthly` | [QuantConnect](./static/strategies/crude-oil-predicts-equity-returns.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=460500) | | Betting Against Beta Factor in Stocks | `0.594` | `18.9%` | `Monthly` | [QuantConnect](./static/strategies/betting-against-beta-factor-in-stocks.py) | [Paper](https://pages.stern.nyu.edu/~lpederse/papers/BettingAgainstBeta.pdf) | | Trend-following Effect in Stocks | `0.569` | `15.2%` | `Daily` | [QuantConnect](./static/strategies/trend-following-effect-in-stocks.py) | [Paper](https://www.cis.upenn.edu/~mkearns/finread/trend.pdf) | | ESG Factor Momentum Strategy | `0.559` | `21.8%` | `Monthly` | [QuantConnect](./static/strategies/esg-factor-momentum-strategy.py) | [Paper](https://www.semanticscholar.org/paper/Can-ESG-Add-Alpha-An-Analysis-of-ESG-Tilt-and-Nagy-Kassam/64f77da4f8ce5906a73ffe4e9eec7c49c0960acc) | | Value (Book-to-Market) Factor | `0.526` | `11.9%` | `Monthly` | [QuantConnect](./static/strategies/value-book-to-market-factor.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2595747) | | Soccer Clubs’ Stocks Arbitrage | `0.515` | `14.2%` | `Daily` | [QuantConnect](./static/strategies/soccer-clubs-stocks-arbitrage.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1343685) | | Synthetic Lending Rates Predict Subsequent Market Return | `0.494` | `13.7%` | `Daily` | [QuantConnect](./static/strategies/synthetic-lending-rates-predict-subsequent-market-return.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3976307) | | Option-Expiration Week Effect | `0.452` | `5%` | `Weekly` | [QuantConnect](./static/strategies/option-expiration-week-effect.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1571786) | | Dispersion Trading | `0.432` | `8.1%` | `Monthly` | [QuantConnect](./static/strategies/dispersion-trading.py) | [Paper](https://www.academia.edu/16327015/EQUILIBRIUM_INDEX_AND_SINGLE_STOCK_VOLATILITY_RISK_PREMIA) | | Momentum in Mutual Fund Returns | `0.414` | `13.6%` | `Quarterly` | [QuantConnect](./static/strategies/momentum-in-mutual-fund-returns.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1462408) | | Sector Momentum – Rotational System | `0.401` | `14.1%` | `Monthly` | [QuantConnect](./static/strategies/sector-momentum-rotational-system.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1585517) | | Combining Smart Factors Momentum and Market Portfolio | `0.388` | `8.2%` | `Monthly` | [QuantConnect](./static/strategies/combining-smart-factors-momentum-and-market-portfolio.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3745517) | | Momentum and Reversal Combined with Volatility Effect in Stocks | `0.375` | `17%` | `Monthly` | [QuantConnect](./static/strategies/momentum-and-reversal-combined-with-volatility-effect-in-stocks.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1679464) | | Market Sentiment and an Overnight Anomaly | `0.369` | `3.6%` | `Daily` | [QuantConnect](./static/strategies/market-sentiment-and-an-overnight-anomaly.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3829582) | | January Barometer | `0.365` | `7.4%` | `Monthly` | [QuantConnect](./static/strategies/january-barometer.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1436516) | | R&D Expenditures and Stock Returns | `0.354` | `8.1%` | `Yearly` | [QuantConnect](./static/strategies/rd-expenditures-and-stock-returns.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=227564) | | Value Factor – CAPE Effect within Countries | `0.351` | `20.2%` | `Yearly` | [QuantConnect](./static/strategies/value-factor-effect-within-countries.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2129474) | | 12 Month Cycle in Cross-Section of Stocks Returns | `0.34` | `43.7%` | `Monthly` | [QuantConnect](./static/strategies/12-month-cycle-in-cross-section-of-stocks-returns.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=687022) | | Turn of the Month in Equity Indexes | `0.305` | `7.2%` | `Daily` | [QuantConnect](./static/strategies/turn-of-the-month-in-equity-indexes.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=917884) | | Payday Anomaly | `0.269` | `3.8%` | `Daily` | [QuantConnect](./static/strategies/payday-anomaly.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3257064) | | Pairs Trading with Country ETFs | `0.257` | `5.7%` | `Daily` | [QuantConnect](./static/strategies/pairs-trading-with-country-etfs.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1958546) | | Residual Momentum Factor | `0.24` | `9.7%` | `Monthly` | [QuantConnect](./static/strategies/residual-momentum-factor.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2319861) | | Earnings Announcement Premium | `0.192` | `3.7%` | `Monthly` | [QuantConnect](./static/strategies/earnings-announcement-premium.py) | [Paper](https://www.nber.org/system/files/working_papers/w13090/w13090.pdf) | | ROA Effect within Stocks | `0.155` | `8.7%` | `Monthly` | [QuantConnect](./static/strategies/roa-effect-within-stocks.py) | [Paper](https://static1.squarespace.com/static/5e6033a4ea02d801f37e15bb/t/5f61583e88f43b7d5b7196b5/1600215105801/Chen_Zhang_JF.pdf) | | 52-Weeks High Effect in Stocks | `0.153` | `19%` | `Monthly` | [QuantConnect](./static/strategies/52-weeks-high-effect-in-stocks.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1787378) | | Combining Fundamental FSCORE and Equity Short-Term Reversals | `0.153` | `17.6%` | `Monthly` | [QuantConnect](./static/strategies/combining-fundamental-fscore-and-equity-short-term-reversals.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3097420) | | Betting Against Beta Factor in International Equities | `0.142` | `9.1%` | `Monthly` | [QuantConnect](./static/strategies/betting-against-beta-factor-in-country-equity-indexes.py) | [Paper](https://pages.stern.nyu.edu/~lpederse/papers/BettingAgainstBeta.pdf) | | Consistent Momentum Strategy | `0.128` | `28.8%` | `6 Months` | [QuantConnect](./static/strategies/consistent-momentum-strategy.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2652592) | | Short Interest Effect – Long-Short Version | `0.079` | `6.6%` | `Monthly` | [QuantConnect](./static/strategies/short-interest-effect-long-short-version.py) | [Paper](https://www.semanticscholar.org/paper/Why-Do-Short-Interest-Levels-Predict-Stock-Returns-Boehmer-Erturk/06418ef437dc7156229532a97d0f8392373eb297?p2df) | | Momentum Factor Combined with Asset Growth Effect | `0.058` | `25.1%` | `Monthly` | [QuantConnect](./static/strategies/momentum-factor-combined-with-asset-growth-effect.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1684767) | | Momentum Factor Effect in Stocks | `-0.008` | `21.8%` | `Monthly` | [QuantConnect](./static/strategies/momentum-factor-effect-in-stocks.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2435323) | | Momentum Factor and Style Rotation Effect | `-0.056` | `10%` | `Monthly` | [QuantConnect](./static/strategies/momentum-factor-and-style-rotation-effect.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=1276815) | | Earnings Announcements Combined with Stock Repurchases | `-0.16` | `0.1%` | `Daily` | [QuantConnect](./static/strategies/earnings-announcements-combined-with-stock-repurchases.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2589966) | | Earnings Quality Factor | `-0.18` | `28.7%` | `Yearly` | [QuantConnect](./static/strategies/earnings-quality-factor.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2179247) | | Accrual Anomaly | `-0.272` | `13.7%` | `Yearly` | [QuantConnect](./static/strategies/accrual-anomaly.py) | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=546108) | | ESG, Price Momentum and Stochastic Optimization | `N/A` | `N/A` | `Monthly` | | [Paper](https://quantpedia.com/strategies/esg-price-momentum-and-stochastic-optimization/) | | The Positive Similarity of Company Filings and Stock Returns | `N/A` | `N/A` | `Monthly` | | [Paper](https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3690461) | # Books A comprehensive list of **55 books** for quantitative traders. ## Beginner | Title | Reviews | Rating | |----------|---------|--------| | [A Beginner’s Guide to the Stock Market: Everything You Need to Start Making Money Today - Matthew R. Kratter](https://amzn.to/3QN2VdU) |  |  | | [How to Day Trade for a Living: A Beginner’s Guide to Trading Tools and Tactics, Money Management, Discipline and Trading Psychology - Andrew Aziz](https://amzn.to/3bmehFv) |  |  | | [The Little Book of Common Sense Investing: The Only Way to Guarantee Your Fair Share of Stock Market Returns - John C. Bogle](https://amzn.to/3A4mgkR) |  |  | | [Investing QuickStart Guide: The Simplified Beginner’s Guide to Successfully Navigating the Stock Market, Growing Your Wealth & Creating a Secure Financial Future - Ted D. Snow](https://amzn.to/3A5aRkX) |  |  | | [Day Trading QuickStart Guide: The Simplified Beginner’s Guide to Winning Trade Plans, Conquering the Markets, and Becoming a Successful Day Trader - Troy Noonan](https://amzn.to/3HPZijw) |  |  | | [Introduction To Algo Trading: How Retail Traders Can Successfully Compete With Professional Traders - Kevin J Davey](https://amzn.to/39Tf7JC) |  |  | | [Algorithmic Trading and DMA: An introduction to direct access trading strategies - Barry Johnson](https://amzn.to/3xYb0UN) |  |  | ## Biography | Title | Reviews | Rating | |----------|---------|--------| | [My Life as a Quant: Reflections on Physics and Finance - Emanuel Derman](https://amzn.to/3A8KudR) |  |  | | [How I Became a Quant: Insights from 25 of Wall Street’s Elite: - Barry Schachter](https://amzn.to/3Alf8kz) |  |  | ## Coding | Title | Reviews | Rating | |----------|---------|--------| | [Python for Finance: Mastering Data-Driven Finance - Yves Hilpisch](https://amzn.to/3NhkTlP) |  |  | | [Trading Evolved: Anyone can Build Killer Trading Strategies in Python - Andreas F. Clenow](https://amzn.to/3A0jcGB) |  |  | | [Python for Algorithmic Trading: From Idea to Cloud Deployment - Yves Hilpisch](https://amzn.to/3bpkd0C) |  |  | | [Algorithmic Trading with Python: Quantitative Methods and Strategy Development - Chris Conlan](https://amzn.to/3u3cxYo) |  |  | | [Learn Algorithmic Trading: Build and deploy algorithmic trading systems and strategies using Python and advanced data analysis - Sebastien Donadio](https://amzn.to/3NqNghA) |  |  | ## Crypto | Title | Reviews | Rating | |----------|---------|--------| | [The Bitcoin Standard: The Decentralized Alternative to Central Banking - Saifedean Ammous](https://amzn.to/3QMJgec) |  |  | | [Bitcoin Billionaires: A True Story of Genius, Betrayal, and Redemption - Ben Mezrich](https://amzn.to/39SkdWt) |  |  | | [Mastering Bitcoin: Programming the Open Blockchain - Andreas M. Antonopoulos](https://amzn.to/3NniZ3p) |  |  | | [Why Buy Bitcoin: Investing Today in the Money of Tomorrow - Andy Edstrom](https://amzn.to/3OMcKqZ) |  |  | ## General | Title | Reviews | Rating | |----------|---------|--------| | [The Intelligent Investor: The Definitive Book on Value Investing - Benjamin Graham, Jason Zweig](https://www.amazon.fr/gp/product/0060555661/ref=as_li_qf_asin_il_tl?ie=UTF8&tag=darchimbaud-21&creative=6746&linkCode=as2&creativeASIN=0060555661&linkId=aba73910e4e3873b6cc8364487662bd6) |  |  | | [How I Invest My Money: Finance experts reveal how they save, spend, and invest - Joshua Brown, Brian Portnoy](https://amzn.to/3A4rsoU) |  |  | | [Naked Forex: High-Probability Techniques for Trading Without Indicators - Alex Nekritin](https://amzn.to/3NkrAUj) |  |  | | [The Four Pillars of Investing: Lessons for Building a Winning Portfolio - William J. Bernstein](https://www.amazon.fr/gp/product/B0041842TW/ref=as_li_qf_asin_il_tl?ie=UTF8&tag=darchimbaud-21&creative=6746&linkCode=as2&creativeASIN=B0041842TW&linkId=d9bc2fec4f3faa41ca4f24aed3c72122) |  |  | | [Option Volatility and Pricing: Advanced Trading Strategies and Techniques, 2nd Edition - Sheldon Natenberg](https://amzn.to/3btOxXL) |  |  | | [The Art and Science of Technical Analysis: Market Structure, Price Action, and Trading Strategies - Adam Grimes](https://www.amazon.fr/gp/product/1118115120/ref=as_li_qf_asin_il_tl?ie=UTF8&tag=darchimbaud-21&creative=6746&linkCode=as2&creativeASIN=1118115120&linkId=d5dc1f0e6727b2663d2186a110a31ad0) |  |  | | [The New Trading for a Living: Psychology, Discipline, Trading Tools and Systems, Risk Control, Trade Management (Wiley Trading) - Alexander Elder](https://www.amazon.fr/gp/product/1118467450/ref=as_li_qf_asin_il_tl?ie=UTF8&tag=darchimbaud-21&creative=6746&linkCode=as2&creativeASIN=1118467450&linkId=67ee502653bc52a5240ced9fc88eb76d) |  |  | | [Building Winning Algorithmic Trading Systems: A Trader’s Journey From Data Mining to Monte Carlo Simulation to Live Trading (Wiley Trading) - Kevin J Davey](https://amzn.to/39QnsxA) |  |  | | [Systematic Trading: A unique new method for designing trading and investing systems - Robert Carver](https://www.amazon.fr/gp/product/0857194453/ref=as_li_qf_asin_il_tl?ie=UTF8&tag=darchimbaud-21&creative=6746&linkCode=as2&creativeASIN=0857194453&linkId=32d8bffc32c01041cde066bacab76c04) |  |  | | [Quantitative Momentum: A Practitioner’s Guide to Building a Momentum-Based Stock Selection System (Wiley Finance) - Wesley R. Gray, Jack R. Vogel](https://www.amazon.fr/gp/product/111923719X/ref=as_li_qf_asin_il_tl?ie=UTF8&tag=darchimbaud-21&creative=6746&linkCode=as2&creativeASIN=111923719X&linkId=b825cb65462a4a9254af3b7dc5328131) |  |  | | [Algorithmic Trading: Winning Strategies and Their Rationale - Ernest P. Chan](https://amzn.to/3xWi8kd) |  |  | | [Leveraged Trading: A professional approach to trading FX, stocks on margin, CFDs, spread bets and futures for all traders - Robert Carver](https://amzn.to/3Nhl6p7) |  |  | | [Trading Systems: A New Approach to System Development and Portfolio Optimisation - Emilio Tomasini, Urban Jaekle](https://www.amazon.fr/gp/product/1905641796/ref=as_li_qf_asin_il_tl?ie=UTF8&tag=darchimbaud-21&creative=6746&linkCode=as2&creativeASIN=1905641796&linkId=61e6634242c497498338f73641ce0a80) |  |  | | [Trading and Exchanges: Market Microstructure for Practitioners - Larry Harris](https://www.amazon.fr/gp/product/0195144708/ref=as_li_qf_asin_il_tl?ie=UTF8&tag=darchimbaud-21&creative=6746&linkCode=as2&creativeASIN=0195144708&linkId=e47e596fc0696cbd624726cce05b4500) |  |  | | [Trading Systems 2nd edition: A new approach to system development and portfolio optimisation - Emilio Tomasini, Urban Jaekle](https://www.amazon.fr/gp/product/085719755X/ref=as_li_qf_asin_il_tl?ie=UTF8&tag=darchimbaud-21&creative=6746&linkCode=as2&creativeASIN=085719755X&linkId=97aa558484a8dc2bf57a5296e7f38cad) |  |  | | [Machine Trading: Deploying Computer Algorithms to Conquer the Markets - Ernest P. Chan](https://amzn.to/3OIBe4o) |  |  | | [Quantitative Equity Portfolio Management: An Active Approach to Portfolio Construction and Management (McGraw-Hill Library of Investment and Finance) - Ludwig B Chincarini, Daehwan Kim](https://amzn.to/3yl9u0c) |  |  | | [Active Portfolio Management: A Quantitative Approach for Producing Superior Returns and Controlling Risk - Richard Grinold, Ronald Kahn](https://amzn.to/3xMKaic) |  |  | | [Quantitative Technical Analysis: An integrated approach to trading system development and trading management - Dr Howard B Bandy](https://www.amazon.fr/gp/product/0979183855/ref=as_li_qf_asin_il_tl?ie=UTF8&tag=darchimbaud-21&creative=6746&linkCode=as2&creativeASIN=0979183855&linkId=8ef7bda69477bdccf90f5ac02ee495b0) |  |  | | [Advances in Active Portfolio Management: New Developments in Quantitative Investing - Richard Grinold, Ronald Kahn](https://amzn.to/3xUTK2z) |  |  | | [Professional Automated Trading: Theory and Practice - Eugene A. Durenard](https://amzn.to/3yhfOpw) |  |  | | [Algorithmic Trading and Quantitative Strategies (Chapman and Hall/CRC Financial Mathematics Series) - Raja Velu, Maxence Hardy, Daniel Nehren](https://amzn.to/3xUTQXZ) |  |  | | [Quantitative Trading: Algorithms, Analytics, Data, Models, Optimization - Xin Guo, Tze Leung Lai, Howard Shek, Samuel Po-Shing Wong](https://www.amazon.fr/gp/product/0367871815/ref=as_li_qf_asin_il_tl?ie=UTF8&tag=darchimbaud-21&creative=6746&linkCode=as2&creativeASIN=0367871815&linkId=3f2ba1cbc0e1fe02e255da740423b2fb) |  |  | ## High Frequency Trading | Title | Reviews | Rating | |----------|---------|--------| | [Inside the Black Box: A Simple Guide to Quantitative and High Frequency Trading - Rishi K. Narang](https://www.amazon.fr/gp/product/1118362411/ref=as_li_qf_asin_il_tl?ie=UTF8&tag=darchimbaud-21&creative=6746&linkCode=as2&creativeASIN=1118362411&linkId=35e02d4e636350366531a5033597a541) |  |  | | [Algorithmic and High-Frequency Trading (Mathematics, Finance and Risk) - Álvaro Cartea, Sebastian Jaimungal, José Penalva](https://www.amazon.fr/gp/product/1107091144/ref=as_li_qf_asin_il_tl?ie=UTF8&tag=darchimbaud-21&creative=6746&linkCode=as2&creativeASIN=1107091144&linkId=64e3ceb66482d8db6827830964b85613) |  |  | | [The Problem of HFT – Collected Writings on High Frequency Trading & Stock Market Structure Reform - Haim Bodek](https://www.amazon.fr/gp/product/1481978357/ref=as_li_qf_asin_il_tl?ie=UTF8&tag=darchimbaud-21&creative=6746&linkCode=as2&creativeASIN=1481978357&linkId=2f3acf998de645990b681e2ac9f0217c) |  |  | | [An Introduction to High-Frequency Finance - Ramazan Gençay, Michel Dacorogna, Ulrich A. Muller, Olivier Pictet, Richard Olsen](https://www.amazon.fr/gp/product/0122796713/ref=as_li_qf_asin_il_tl?ie=UTF8&tag=darchimbaud-21&creative=6746&linkCode=as2&creativeASIN=0122796713&linkId=7e6c098026204f399e45d7fbb803dcca) |  |  | | [Market Microstructure in Practice - Charles-Albert Lehalle, Sophie Laruelle](https://www.amazon.fr/Market-Microstructure-Practice-Sophie-Laruelle/dp/9813231122) |  |  | | [The Financial Mathematics of Market Liquidity - Olivier Gueant](https://www.amazon.com/Financial-Mathematics-Market-Liquidity-Execution/dp/1498725473) |  |  | | [High-Frequency Trading - Maureen O’Hara, David Easley, Marcos M López de Prado](https://www.amazon.fr/gp/product/178272009X/ref=as_li_qf_asin_il_tl?ie=UTF8&tag=darchimbaud-21&creative=6746&linkCode=as2&creativeASIN=178272009X&linkId=082f861ff6bbe4cca4ef7ccbe620a2c4) |  |  | ## Machine Learning | Title | Reviews | Rating | |----------|---------|--------| | [Dark Pools: The rise of A.I. trading machines and the looming threat to Wall Street - Scott Patterson](https://www.amazon.fr/gp/product/0307887189/ref=as_li_qf_asin_il_tl?ie=UTF8&tag=darchimbaud-21&creative=6746&linkCode=as2&creativeASIN=0307887189&linkId=2572cae24ed7de0b279580312daf0f03) |  |  | | [Advances in Financial Machine Learning - Marcos Lopez de Prado](https://www.amazon.fr/gp/product/1119482089/ref=as_li_qf_asin_il_tl?ie=UTF8&tag=darchimbaud-21&creative=6746&linkCode=as2&creativeASIN=1119482089&linkId=7eff4d3f3d9f2d00d05032f726386e53) |  |  | | [Machine Learning for Algorithmic Trading: Predictive models to extract signals from market and alternative data for systematic trading strategies with Python, 2nd Edition - Stefan Jansen](https://www.amazon.fr/gp/product/1839217715/ref=as_li_qf_asin_il_tl?ie=UTF8&tag=darchimbaud-21&creative=6746&linkCode=as2&creativeASIN=1839217715&linkId=80e3e93e1b6027596858ed0f1fbf10c2) |  |  | | [Machine Learning for Asset Managers (Elements in Quantitative Finance) - Marcos M López de Prado](https://www.amazon.fr/gp/product/1108792898/ref=as_li_qf_asin_il_tl?ie=UTF8&tag=darchimbaud-21&creative=6746&linkCode=as2&creativeASIN=1108792898&linkId=8eb7e3c369d38b36df8dfecf05a622db) |  |  | | [Machine Learning in Finance: From Theory to Practice - Matthew F. Dixon, Igor Halperin, Paul Bilokon](https://www.amazon.fr/gp/product/3030410676/ref=as_li_qf_asin_il_tl?ie=UTF8&tag=darchimbaud-21&creative=6746&linkCode=as2&creativeASIN=3030410676&linkId=5f5f1df6be62ae96ef7a0c536c3ecdb4) |  |  | | [Artificial Intelligence in Finance: A Python-Based Guide - Yves Hilpisch](https://www.amazon.fr/gp/product/1492055433/ref=as_li_qf_asin_il_tl?ie=UTF8&tag=darchimbaud-21&creative=6746&linkCode=as2&creativeASIN=1492055433&linkId=7c20249be4d35badb127d6a5423fc495) |  |  | | [Algorithmic Trading Methods: Applications Using Advanced Statistics, Optimization, and Machine Learning Techniques - Robert Kissell](https://www.amazon.fr/gp/product/0128156309/ref=as_li_qf_asin_il_tl?ie=UTF8&tag=darchimbaud-21&creative=6746&linkCode=as2&creativeASIN=0128156309&linkId=0a197c0b547a0ee63ccd19389bb42edd) |  |  | # Videos | Title | Likes | |--------------------------------------------------------------------|-------| | [Krish Naik - Machine learning tutorials and their Application in Stock Prediction](https://www.youtube.com/watch?v=H6du_pfuznE) |  | | [QuantInsti Youtube - webinars about Machine Learning for trading](https://www.youtube.com/user/quantinsti/search?query=machine+learning) |  | | [Siraj Raval - Videos about stock market prediction using Deep Learning](https://www.youtube.com/channel/UCWN3xxRkmTPmbKwht9FuE5A/search?query=trading) |  | | [Quantopian - Webinars about Machine Learning for trading](https://www.youtube.com/channel/UC606MUq45P3zFLa4VGKbxsg/search?query=machine+learning) |  | | [Sentdex - Machine Learning for Forex and Stock analysis and algorithmic trading](https://www.youtube.com/watch?v=v_L9jR8P-54&list=PLQVvvaa0QuDe6ZBtkCNWNUbdaBo2vA4RO) |  | | [QuantNews - Machine Learning for Algorithmic Trading 3 part series](https://www.youtube.com/playlist?list=PLHJACfjILJ-91qkw5YC83S6COKGscctzz) |  | | [Sentdex - Python programming for Finance (a few videos including Machine Learning)](https://www.youtube.com/watch?v=Z-5wNWgRJpk&index=9&list=PLQVvvaa0QuDcOdF96TBtRtuQksErCEBYZ) |  | | [Chat with Traders EP042 - Machine learning for algorithmic trading with Bert Mouler](https://www.youtube.com/watch?v=i8FNO8r7PaE) |  | | [Tucker Balch - Applying Deep Reinforcement Learning to Trading](https://www.youtube.com/watch?v=Pka0DC_P17k) |  | | [Ernie Chan - Machine Learning for Quantitative Trading Webinar](https://www.youtube.com/watch?v=72aEDjwGMr8&t=1023s) |  | | [Chat with Traders EP147 - Detective work leading to viable trading strategies with Tom Starke](https://www.youtube.com/watch?v=JjXw9Mda7eY) |  | | [Chat with Traders EP142 - Algo trader using automation to bypass human flaws with Bert Mouler](https://www.youtube.com/watch?v=ofL66mh6Tw0) |  | | [Master Thesis presentation, Uni of Essex - Analyzing the Limit Order Book, A Deep Learning Approach](https://www.youtube.com/watch?v=qxSh2VFmRGw) |  | | [Howard Bandy - Machine Learning Trading System Development Webinar](https://www.youtube.com/watch?v=v729evhMpYk&t=1s) |  | | [Chat With Traders EP131 - Trading strategies, powered by machine learning with Morgan Slade](https://www.youtube.com/watch?v=EbWbeYu8zwg) |  | | [Chat with Traders Quantopian 5 - Good Uses of Machine Learning in Finance with Max Margenot](https://www.youtube.com/watch?v=Zj5sXWv9SDM) |  | | [Hitoshi Harada, CTO at Alpaca - Deep Learning in Finance Talk](https://www.youtube.com/watch?v=FoQKCeDuPiY) |  | | [Better System Trader EP028 - David Aronson shares research into indicators that identify Bull and Bear markets.](https://www.youtube.com/watch?v=Q4rV0Y9NokI) |  | | [Prediction Machines - Deep Learning with Python in Finance Talk](https://www.youtube.com/watch?v=xvm-M-R2fZY) |  | | [Better System Trader EP064 - Cryptocurrencies and Machine Learning with Bert Mouler](https://www.youtube.com/watch?v=YgRTd4nLJoU) |  | | [Better System Trader EP023 - Portfolio manager Michael Himmel talks AI and machine learning in trading](https://www.youtube.com/watch?v=9tZjeyhfG0g) |  | | [Better System Trader EP082 - Machine Learning With Kris Longmore](https://www.youtube.com/watch?v=0syNgsd635M) |  | # Blogs | Title | |--------------------------------------------------------------------| | [AAA Quants, Tom Starke Blog](http://aaaquants.com/category/blog/) | | [AI & Systematic Trading](https://blog.paperswithbacktest.com/) | | [Blackarbs blog](http://www.blackarbs.com/blog/) | | [Hardikp, Hardik Patel blog](https://www.hardikp.com/) | | [Max Dama on Automated Trading](https://bit.ly/3wVZbh9) | | [Medallion.Club on Systematic Trading (FR)](https://medallion.club/trading-algorithmique-quantitatif-systematique/) | | [Proof Engineering: The Algorithmic Trading Platform](https://bit.ly/3lX7zYN) | | [Quantsportal, Jacques Joubert's Blog](http://www.quantsportal.com/blog-page/) | | [Quantstart - Machine Learning for Trading articles](https://www.quantstart.com/articles) | | [RobotWealth, Kris Longmore Blog](https://robotwealth.com/blog/) | # Courses | Title | |--------------------------------------------------------------------| | [AI in Finance](https://cfte.education/) | | [AI & Systematic Trading](https://paperswithbacktest.com/) | | [Algorithmic Trading for Cryptocurrencies in Python](https://github.com/tudorelu/tudorials/tree/master/trading) | | [Coursera, NYU - Guided Tour of Machine Learning in Finance](https://www.coursera.org/learn/guided-tour-machine-learning-finance) | | [Coursera, NYU - Fundamentals of Machine Learning in Finance](https://www.coursera.org/learn/fundamentals-machine-learning-in-finance) | | [Coursera, NYU - Reinforcement Learning in Finance](https://www.coursera.org/learn/reinforcement-learning-in-finance) | | [Coursera, NYU - Overview of Advanced Methods for Reinforcement Learning in Finance](https://www.coursera.org/learn/advanced-methods-reinforcement-learning-finance) | | [Hudson and Thames Quantitative Research](https://github.com/hudson-and-thames) | | [NYU: Overview of Advanced Methods of Reinforcement Learning in Finance](https://www.coursera.org/learn/advanced-methods-reinforcement-learning-finance/home/welcome) | | [Udacity: Artificial Intelligence for Trading](https://www.udacity.com/course/ai-for-trading--nd880) | | [Udacity, Georgia Tech - Machine Learning for Trading](https://www.udacity.com/course/machine-learning-for-trading--ud501) |

A curated list of awesome libraries, packages, strategies, books, blogs, tutorials for systematic trading.

finance,awesome,book,paper,trading-bot,algotrading,quant,awesome-list,trading-strategies,trading-algorithms

superstreamlabs/memphis

<p align="center"> Please pay attention that Memphis.dev is no longer supported officially by the Superstream team (formerly Memphis.dev) and was released to the public. <p align="center"> <a href="">[](https://memphis.dev)</a> <p align="center"> <a href="https://memphis.dev/discord"><img src="https://img.shields.io/discord/963333392844328961?color=6557ff&label=discord" alt="Discord"></a> <a href="https://github.com/memphisdev/memphis/issues?q=is%3Aissue+is%3Aclosed"><img src="https://img.shields.io/github/issues-closed/memphisdev/memphis?color=6557ff"></a> <img src="https://img.shields.io/npm/dw/memphis-dev?color=ffc633&label=installations"> <a href="https://github.com/memphisdev/memphis/blob/master/CODE_OF_CONDUCT.md"><img src="https://img.shields.io/badge/Code%20of%20Conduct-v1.0-ff69b4.svg?color=ffc633" alt="Code Of Conduct"></a> <img alt="GitHub release (latest by date)" src="https://img.shields.io/github/v/release/memphisdev/memphis?color=61dfc6"> <img src="https://img.shields.io/github/last-commit/memphisdev/memphis?color=61dfc6&label=last%20commit"> </p> <div align="center"> <h4> **[Memphis.dev](https://memphis.dev)** Is The First Data Streaming Platform Designed For Backend Developers<br> To Build Event-driven And Real-time Features Faster Than Ever.<br> </h4> </div> ##  About Before Memphis came along, handling ingestion and processing of events on a large scale took months to adopt and was a capability reserved for the top 20% of mega-companies. Now, Memphis opens the door for the other 80% to unleash their event and data streaming superpowers quickly, easily, and with great cost-effectiveness. ## 🚀 Getting Started [Tutorials](https://docs.memphis.dev/memphis/getting-started/tutorials) | [Videos](https://www.youtube.com/playlist?list=PL_7iYjqhtXpWpZT2U0zDYo2eGOoGmg2mm)<br> #### ☸ Kubernetes ```shell helm repo add memphis https://k8s.memphis.dev/charts/ --force-update && \ helm install my-memphis memphis/memphis --create-namespace --namespace memphis ``` #### 🐳 Docker Compose ```shell curl -s https://memphisdev.github.io/memphis-docker/docker-compose.yml -o docker-compose.yml && \ docker compose -f docker-compose.yml -p memphis up ``` <div align="center"> <img style="width: 50%" src="https://github.com/memphisdev/memphis/assets/70286779/38c7cee0-964e-40bd-ab3c-0ea5aeefc513" /> </div> ## ✨ Key Features [v1.4.4](https://docs.memphis.dev/memphis/release-notes/releases/v1.4.4-latest)  Production-ready message broker in under 3 minutes<br>  Easy-to-use UI, CLI, and SDKs<br>  Data-level observability<br>  Dead-Letter Queue with automatic message retransmit<br>  Schemaverse - Embedded schema management for produced data (Protobuf/JSON/GraphQL/Avro)<br>  Functions for real-time processing<br>  Graph visualization<br>  Storage tiering<br>  SDKs: Node.JS, Go, Python, Typescript, NestJS, REST, .NET, Kotlin<br>  Kubernetes-native<br>  Community driven<br> <table> <tr> <th> <a href="https://docs.memphis.dev">End-to-end Observability</a> </th> <th> <a href="https://docs.memphis.dev">"Feel" your producers, consumers, and records</a> </th> </tr> <tr> <td width="50%"> <a href="https://docs.memphis.dev"> <img src="https://github.com/memphisdev/memphis/assets/70286779/5763319d-1c06-4478-b0ee-582f37acf2b8" /> </a> </td> <td width="50%"> <a href="https://docs.memphis.dev"> <img width="1512" alt="Screenshot 2023-09-29 at 10 17 01" src="https://github.com/memphisdev/memphis/assets/70286779/1fd5358d-adb8-4aa5-9b19-9640bdfd2417"> </a> </td> </tr> <tr> <th> <a href="https://docs.memphis.dev">Quickly analyze system health using a graph overview</a> </th> <th> <a href="https://docs.memphis.dev">Never lose a message with automatic dead-letter</a> </th> </tr> <tr> <td width="50%"> <a href="https://docs.memphis.dev"> <img src="https://github.com/memphisdev/memphis/assets/70286779/1be9768b-b658-4bb3-89bd-ee814a8813b9" /> </a> </td> <td width="50%"> <a href="https://docs.memphis.dev"> <img width="1512" alt="Screenshot 2023-09-29 at 10 17 12" src="https://github.com/memphisdev/memphis/assets/70286779/2d6638d8-d1f1-4aba-8e36-7b7a57e76f16"> </a> </td> </tr> <tr> <th> <a href="https://docs.memphis.dev/memphis/memphis-broker/concepts/storage-and-redundancy">Save up 96% storage costs with Storage tiering</a> </th> <th> <a href="https://docs.memphis.dev/memphis/memphis-schemaverse/schemaverse-schema-management">Increase data quality with schemas</a> </th> </tr> <tr> <td width="50%"> <a href="https://docs.memphis.dev"> <img width="1512" alt="Screenshot 2023-09-29 at 10 17 58" src="https://github.com/memphisdev/memphis/assets/70286779/beeaec9f-c8a5-4f6a-b520-a810eb68aa13"> </a> </td> <td width="50%"> <a href="https://docs.memphis.dev"> <img width="1512" alt="Screenshot 2023-09-29 at 10 16 40" src="https://github.com/memphisdev/memphis/assets/70286779/7c62977a-2d83-4c54-b233-084958be1411"> </a> </td> </tr> </table> ## Public case studies - [Dstny - Building the next-gen in-house communication using Memphis.dev](https://memphis.dev/blog/how-dstny-building-the-future-of-in-house-communication-using-memphis-dev/) - [Gastromatic - Synchronizing data using Memphis.dev](https://medium.com/gastromatic/synchronizing-data-using-memphis-dev-a-case-study-2e6e9a7b5512) - [KELA - Real-time cyber threats identification](https://memphis.dev/blog/how-kela-is-using-memphis-dev-for-real-time-cyber-threats-identification/) - [Handling millions of discord messages](https://memphis.dev/blog/how-cactusfire-handles-millions-of-daily-discord-messages-using-memphis-dev/) ## Network diagram <a href="https://docs.memphis.dev/memphis/memphis/architecture"> <p align="center"> <img height="500" alt="memphis.dev Architecture" src="https://user-images.githubusercontent.com/70286779/229371674-35a5e4cc-d3f5-413e-982d-d1081b18d82a.jpeg"> </p> </a> ## SDKs supported features Feature | Go | Python | JS | .NET | Java | Rust ------------- | ------------- | ------------- | ------------- | ------------- | ------------- | ------------- Connection | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: Disconnection | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: Create a station | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :x: | :white_check_mark: Destroy a station | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :x: | :white_check_mark: Retention | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :x: | :white_check_mark: Retention values | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :x: | :white_check_mark: Storage types | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :x: | :white_check_mark: Create a new schema | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :x: | :x: Enforce a schema Protobuf | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :x: | :x: Enforce a schema Json | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :x: | :construction: (WIP) Enforce a schema GraphQL | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :x: | :x: Enforce a schema Avro | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :x: | :x: Detach a schema | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :x: | :x: Produce | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: Add headers | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :x: | :white_check_mark: Async produce | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :x: | :white_check_mark: Message ID | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | ? | :white_check_mark: Destroy a producer | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | Partial | :white_check_mark: Consume | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: Context to message handler | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :x: | Not Applicable Ack a message | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: Nack a Message | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :x: | :x: Send a message to dead-letter | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :x: | :x: Get message time sent | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :x: | :x: Fetch | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :x: Message delay | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :x: | :white_check_mark: Get Headers | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :x: | :white_check_mark: Get message sequence number | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: Destroying a Consumer | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :x: | :white_check_mark: Check if broker is connected | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: Consumer prefetch | :white_check_mark: | :white_check_mark: | :x: | :white_check_mark: | :x: | :white_check_mark: Schema deserialization | :white_check_mark: | :white_check_mark: | :white_check_mark: | :white_check_mark: | :x: | :x: ## 👉 Use-cases - Async task management - Real-time streaming pipelines - Data ingestion - Cloud Messaging - Services (microservices, service mesh) - Event/Data Streaming (observability, analytics, ML/AI) - Queuing - N:N communication patterns - Ingest Grafana Loki logs at scale ## Support 🙋‍♂️🤝 ### Have any questions ❓ We welcome you to our discord server with your questions, doubts and feedback. <a href="https://memphis.dev/discord"><img src="https://amplication.com/images/discord_banner_purple.svg"/></a> ### Create a bug 🐞 report If you see an error message or run into an issue, please [create bug report](https://github.com/memphisdev/memphis/issues/new?assignees=&labels=type%3A%20bug&template=bug_report.md&title=). This effort is valued and it will help all Memphis{dev} users. ### Submit a feature 💡 request If you have an idea, or you think that we're missing a capability that would make development easier and more robust, please [Submit feature request](https://github.com/memphisdev/memphis/issues/new?assignees=&labels=type%3A%20feature%20request). If an issue❗with similar feature request already exists, don't forget to leave a "+1". If you add some more information such as your thoughts and vision about the feature, your comments will be embraced warmly :) ## Contributing Memphis.dev is an open-source project.<br> We are committed to a fully transparent development process and appreciate highly any contributions.<br> Whether you are helping us fix bugs, proposing new features, improving our documentation or spreading the word - we would love to have you as part of the Memphis.dev community. Please refer to our [Contribution Guidelines](./CONTRIBUTING.md) and [Code of Conduct](./CODE_OF_CONDUCT.md). ## Contributors ✨ Thanks goes to these wonderful people ❤:<br><br> <a href = "https://github.com/memphisdev/memphis/graphs/contributors"> <img src = "https://contrib.rocks/image?repo=memphisdev/memphis"/> </a> ## License 📃 Memphis is open-sourced and operates under the "Memphis Business Source License 1.0" license Built out of Apache 2.0, the main difference between the licenses is: "You may make use of the Licensed Work (i) only as part of your own product or service, provided it is not a message broker or a message queue product or service; and (ii) provided that you do not use, provide, distribute, or make available the Licensed Work as a Service. A “Service” is a commercial offering, product, hosted, or managed service, that allows third parties (other than your own employees and contractors acting on your behalf) to access and/or use the Licensed Work or a substantial set of the features or functionality of the Licensed Work to third parties as a software-as-a-service, platform-as-a-service, infrastructure-as-a-service or other similar services that compete with Licensor products or services." Please check out [License](./LICENSE) to read the full text.

Memphis.dev is a highly scalable and effortless data streaming platform

data,data-stream-processing,data-streaming,kubernetes,messaging-queue,data-engineering,data-pipeline,golang,enrichment,message-broker

fujiapple852/trippy

[](https://github.com/fujiapple852/trippy/actions/workflows/ci.yml) [](https://crates.io/crates/trippy/0.10.0) [](https://repology.org/project/trippy/versions) [](http://github.com/fujiapple852/trippy) [](https://trippy.zulipchat.com/) [](https://matrix.to/#/#trippy-dev:matrix.org) # Trippy Trippy combines the functionality of traceroute and ping and is designed to assist with the analysis of networking issues. <img src="https://raw.githubusercontent.com/fujiapple852/trippy/master/assets/0.8.0/trippy.gif" alt="trippy"/> ## Navigation <!-- TOC --> * [Trippy](#trippy) * [Features](#features) * [Versions](#versions) * [Distributions](#distributions) * [Privileges](#privileges) * [Usage Examples](#usage-examples) * [Command Reference](#command-reference) * [Theme Reference](#theme-reference) * [Column Reference](#column-reference) * [Key Bindings Reference](#key-bindings-reference) * [Configuration Reference](#configuration-reference) * [Frequently Asked Questions](#frequently-asked-questions) * [Acknowledgements](#acknowledgements) * [License](#license) <!-- TOC --> ## Features - Trace using multiple protocols: - `ICMP`, `UDP` & `TCP` - `IPv4` & `IPv6` - Customizable tracing options: - packet size & payload pattern - start and maximum time-to-live (TTL) - minimum and maximum round duration - round end grace period & maximum number of unknown hops - source & destination port (`TCP` & `UDP`) - source address and source interface - `TOS` (aka `DSCP + ECN`) - Support for `classic`, `paris` and `dublin` [Equal Cost Multi-path Routing](https://en.wikipedia.org/wiki/Equal-cost_multi-path_routing) strategies ([tracking issue](https://github.com/fujiapple852/trippy/issues/274)) - RFC4884 [ICMP Multi-Part Messages](https://datatracker.ietf.org/doc/html/rfc4884) - Generic Extension Objects - MPLS Label Stacks - Unprivileged mode - Tui interface: - Trace multiple targets simultaneously from a single instance of Trippy - Per hop stats (sent, received, loss%, last, avg, best, worst, stddev, jitter & status) - Per hop round-trip-time (RTT) history and frequency distributing charts - Interactive chart of RTT for all hops in a trace with zooming capability - Interactive GeoIp world map - Isolate and filter by individual tracing flows - Customizable color theme & key bindings - Customizable column order and visibility - Configuration via both command line arguments and a configuration file - Show multiple hosts per hop with ability to cap display to N hosts and show frequency % - Show hop details and navigate hosts within each hop - Freeze/unfreeze the Tui, reset the stats, flush the cache, preserve screen on exit - Responsive UI with adjustable refresh rate - Hop privacy - DNS: - Use system, external (Google `8.8.8.8` or Cloudflare `1.1.1.1`) or custom resolver - Lazy reverse DNS queries - Lookup [autonomous system](https://en.wikipedia.org/wiki/Autonomous_system_(Internet)) number (ASN) and name - GeoIp: - Lookup and display GeoIp information from local [MaxMind](https://www.maxmind.com) and [IPinfo](https://ipinfo.io) `mmdb` files - Generate tracing reports: - `json`, `csv` & tabular (pretty-printed and markdown) - Tracing `flows` report - Graphviz `dot` charts - configurable reporting cycles - Runs on multiple platform (macOS, Linux, Windows, NetBSD, FreeBSD, OpenBSD) - Capabilities aware application (Linux only) ## Versions The following table lists ths versions of Trippy that are available and links to the corresponding release note and documentation: | Version | Release Date | Status | Release Note | Documentation | |------------|--------------|-------------|--------------------------------------------------------------------|------------------------------------------------------------| | 0.11.0-dev | n/a | Development | n/a | [docs](https://github.com/fujiapple852/trippy/tree/master) | | 0.10.0 | 2024-03-31 | Current | [note](https://github.com/fujiapple852/trippy/releases/tag/0.10.0) | [docs](https://github.com/fujiapple852/trippy/tree/0.10.0) | | 0.9.0 | 2023-11-30 | Previous | [note](https://github.com/fujiapple852/trippy/releases/tag/0.9.0) | [docs](https://github.com/fujiapple852/trippy/tree/0.9.0) | | 0.8.0 | 2023-05-15 | Deprecated | [note](https://github.com/fujiapple852/trippy/releases/tag/0.8.0) | [docs](https://github.com/fujiapple852/trippy/tree/0.8.0) | | 0.7.0 | 2023-03-25 | Deprecated | [note](https://github.com/fujiapple852/trippy/releases/tag/0.7.0) | [docs](https://github.com/fujiapple852/trippy/tree/0.7.0) | | 0.6.0 | 2022-08-19 | Deprecated | [note](https://github.com/fujiapple852/trippy/releases/tag/0.6.0) | [docs](https://github.com/fujiapple852/trippy/tree/0.6.0) | > [!NOTE] > Only the _latest patch versions_ of both the _current_ and _previous_ releases of Trippy are supported. ## Distributions [](https://repology.org/project/trippy/versions) ### Cargo [](https://crates.io/crates/trippy/0.10.0) ```shell cargo install trippy --locked ``` ### PPA (Ubuntu) [](https://launchpad.net/~fujiapple/+archive/ubuntu/trippy/+packages) ```shell sudo add-apt-repository ppa:fujiapple/trippy sudo apt update && apt install trippy ``` ### Snap (Linux) [](https://snapcraft.io/trippy) ```shell snap install trippy ``` ### Homebrew (macOS) [](https://formulae.brew.sh/formula/trippy) ```shell brew install trippy ``` ### WinGet (Windows) [](https://github.com/microsoft/winget-pkgs/tree/master/manifests/f/FujiApple/Trippy/0.10.0) ```shell winget install trippy ``` ### Scoop (Windows) [](https://github.com/ScoopInstaller/Main/blob/master/bucket/trippy.json) ```shell scoop install trippy ``` ### NetBSD [](https://pkgsrc.se/net/trippy) ```shell pkgin install trippy ``` ### FreeBSD [](https://www.freshports.org/net/trippy/) ```shell pkg install trippy ``` ### OpenBSD [](https://openports.pl/path/net/trippy) ```shell pkg_add trippy ``` ### Pacman (Arch Linux) [](https://archlinux.org/packages/extra/x86_64/trippy) ```shell pacman -S trippy ``` ### Nix [](https://github.com/NixOS/nixpkgs/blob/master/pkgs/tools/networking/trippy/default.nix) ```shell nix-env -iA trippy ``` ### Docker [](https://hub.docker.com/r/fujiapple/trippy/) ```shell docker run -it fujiapple/trippy ``` ### Binary Asset Download | OS | Arch | Env | Current | Previous | |---------|-----------|--------------|-------------------------------------------------------------------------------------------------------------------------------|----------------------------------------------------------------------------------------------------------------------------| | Linux | `x86_64` | `gnu` | [0.10.0](https://github.com/fujiapple852/trippy/releases/download/0.10.0/trippy-0.10.0-x86_64-unknown-linux-gnu.tar.gz) | [0.9.0](https://github.com/fujiapple852/trippy/releases/download/0.9.0/trippy-0.9.0-x86_64-unknown-linux-gnu.tar.gz) | | Linux | `x86_64` | `musl` | [0.10.0](https://github.com/fujiapple852/trippy/releases/download/0.10.0/trippy-0.10.0-x86_64-unknown-linux-musl.tar.gz) | [0.9.0](https://github.com/fujiapple852/trippy/releases/download/0.9.0/trippy-0.9.0-x86_64-unknown-linux-musl.tar.gz) | | Linux | `aarch64` | `gnu` | [0.10.0](https://github.com/fujiapple852/trippy/releases/download/0.10.0/trippy-0.10.0-aarch64-unknown-linux-gnu.tar.gz) | [0.9.0](https://github.com/fujiapple852/trippy/releases/download/0.9.0/trippy-0.9.0-aarch64-unknown-linux-gnu.tar.gz) | | Linux | `aarch64` | `musl` | [0.10.0](https://github.com/fujiapple852/trippy/releases/download/0.10.0/trippy-0.10.0-aarch64-unknown-linux-musl.tar.gz) | [0.9.0](https://github.com/fujiapple852/trippy/releases/download/0.9.0/trippy-0.9.0-aarch64-unknown-linux-musl.tar.gz) | | Linux | `arm7` | `gnueabihf` | [0.10.0](https://github.com/fujiapple852/trippy/releases/download/0.10.0/trippy-0.10.0-armv7-unknown-linux-gnueabihf.tar.gz) | [0.9.0](https://github.com/fujiapple852/trippy/releases/download/0.9.0/trippy-0.9.0-armv7-unknown-linux-gnueabihf.tar.gz) | | Linux | `arm7` | `musleabi` | [0.10.0](https://github.com/fujiapple852/trippy/releases/download/0.10.0/trippy-0.10.0-armv7-unknown-linux-musleabi.tar.gz) | [0.9.0](https://github.com/fujiapple852/trippy/releases/download/0.9.0/trippy-0.9.0-armv7-unknown-linux-musleabi.tar.gz) | | Linux | `arm7` | `musleabihf` | [0.10.0](https://github.com/fujiapple852/trippy/releases/download/0.10.0/trippy-0.10.0-armv7-unknown-linux-musleabihf.tar.gz) | [0.9.0](https://github.com/fujiapple852/trippy/releases/download/0.9.0/trippy-0.9.0-armv7-unknown-linux-musleabihf.tar.gz) | | macOS | `x86_64` | `darwin` | [0.10.0](https://github.com/fujiapple852/trippy/releases/download/0.10.0/trippy-0.10.0-x86_64-apple-darwin.tar.gz) | [0.9.0](https://github.com/fujiapple852/trippy/releases/download/0.9.0/trippy-0.9.0-x86_64-apple-darwin.tar.gz) | | macOS | `aarch64` | `darwin` | [0.10.0](https://github.com/fujiapple852/trippy/releases/download/0.10.0/trippy-0.10.0-aarch64-apple-darwin.tar.gz) | [0.9.0](https://github.com/fujiapple852/trippy/releases/download/0.9.0/trippy-0.9.0-aarch64-apple-darwin.tar.gz) | | Windows | `x86_64` | `msvc` | [0.10.0](https://github.com/fujiapple852/trippy/releases/download/0.10.0/trippy-0.10.0-x86_64-pc-windows-msvc.zip) | [0.9.0](https://github.com/fujiapple852/trippy/releases/download/0.9.0/trippy-0.9.0-x86_64-pc-windows-msvc.zip) | | Windows | `x86_64` | `gnu` | [0.10.0](https://github.com/fujiapple852/trippy/releases/download/0.10.0/trippy-0.10.0-x86_64-pc-windows-gnu.zip) | [0.9.0](https://github.com/fujiapple852/trippy/releases/download/0.9.0/trippy-0.9.0-x86_64-pc-windows-gnu.zip) | | Windows | `aarch64` | `msvc` | [0.10.0](https://github.com/fujiapple852/trippy/releases/download/0.10.0/trippy-0.10.0-aarch64-pc-windows-msvc.zip) | [0.9.0](https://github.com/fujiapple852/trippy/releases/download/0.9.0/trippy-0.9.0-aarch64-pc-windows-msvc.zip) | | FreeBSD | `x86_64` | n/a | [0.10.0](https://github.com/fujiapple852/trippy/releases/download/0.10.0/trippy-0.10.0-x86_64-unknown-freebsd.tar.gz) | [0.9.0](https://github.com/fujiapple852/trippy/releases/download/0.9.0/trippy-0.9.0-x86_64-unknown-freebsd.tar.gz) | | NetBSD | `x86_64` | n/a | [0.10.0](https://github.com/fujiapple852/trippy/releases/download/0.10.0/trippy-0.10.0-x86_64-unknown-netbsd.tar.gz) | [0.9.0](https://github.com/fujiapple852/trippy/releases/download/0.9.0/trippy-0.9.0-x86_64-unknown-netbsd.tar.gz) | | RPM | `x86_64` | `gnu` | [0.10.0](https://github.com/fujiapple852/trippy/releases/download/0.10.0/trippy-0.10.0-x86_64.rpm) | [0.9.0](https://github.com/fujiapple852/trippy/releases/download/0.9.0/trippy-0.9.0-x86_64.rpm) | | Debian | `x86_64` | `gnu` | [0.10.0](https://github.com/fujiapple852/trippy/releases/download/0.10.0/trippy_x86_64-unknown-linux-gnu_0.10.0_amd64.deb) | [0.9.0](https://github.com/fujiapple852/trippy/releases/download/0.9.0/trippy_x86_64-unknown-linux-gnu_0.9.0_amd64.deb) | | Debian | `x86_64` | `musl` | [0.10.0](https://github.com/fujiapple852/trippy/releases/download/0.10.0/trippy_x86_64-unknown-linux-musl_0.10.0_amd64.deb) | [0.9.0](https://github.com/fujiapple852/trippy/releases/download/0.9.0/trippy_x86_64-unknown-linux-musl_0.9.0_amd64.deb) | ## Privileges Trippy normally requires elevated privileges due to the use of raw sockets. Enabling the required privileges for your platform can be achieved in several ways, as outlined below. Trippy can also be used without elevated privileged on certain platforms, with some limitations. ### Unix 1: Run as `root` user via `sudo`: ```shell sudo trip example.com ``` 2: `chown` `trip` as the `root` user and set the `setuid` bit: ```shell sudo chown root $(which trip) && sudo chmod +s $(which trip) ``` 3: [Linux only] Set the `CAP_NET_RAW` capability: ```shell sudo setcap CAP_NET_RAW+p $(which trip) ``` > [!NOTE] > Trippy is a capability aware application and will add `CAP_NET_RAW` to the effective set if it is present in the > allowed set. Trippy will drop all capabilities after creating the raw sockets. ### Windows Trippy must be run with Administrator privileges on Windows. ### Unprivileged mode Trippy allows running in an unprivileged mode for all tracing modes (`ICMP`, `UDP` and `TCP`) on platforms which support that feature. > [!NOTE] > Unprivileged mode is currently only supported on macOS. Linux support is possible and may be added in the future. > Unprivileged mode is not supported on NetBSD, FreeBSD or Windows as these platforms do not support > the `IPPROTO_ICMP` socket type. See [#101](https://github.com/fujiapple852/trippy/issues/101) for further information. The unprivileged mode can be enabled by adding the `--unprivileged` (`-u`) command line flag or by adding the `unprivileged` entry in the `trippy` section of the [configuration file](#configuration-reference): ```toml [trippy] unprivileged = true ``` > [!NOTE] > The `paris` and `dublin` `ECMP` strategies are not supported in unprivileged mode as these require > manipulating the `UDP` and `IP` and headers which in turn requires the use of a raw socket. ## Usage Examples Basic usage with default parameters: ```shell trip example.com ``` Trace without requiring elevated privileges (supported platforms only, see [privileges](#privileges)): ```shell trip example.com --unprivileged ``` Trace using the `udp` (or `tcp` or `icmp`) protocol (also aliases `--icmp`, `--udp` & `--tcp`): ```shell trip example.com -p udp ``` Trace to multiple targets simultaneously (`icmp` protocol only, see [#72](https://github.com/fujiapple852/trippy/issues/72)): ```shell trip example.com google.com crates.io ``` Trace with a minimum round time of `250ms` and a grace period of `50ms`: ```shell trip example.com -i 250ms -g 50ms ``` Trace with a custom first and maximum `time-to-live`: ```shell trip example.com --first-ttl 2 --max-ttl 10 ``` Use custom destination port `443` for `tcp` tracing: ```shell trip example.com -p tcp -P 443 ``` Use custom source port `5000` for `udp` tracing: ```shell trip example.com -p udp -S 5000 ``` Use the `dublin` (or `paris`) ECMP routing strategy for `udp` with fixed source and destination ports: ```shell trip example.com -p udp -R dublin -S 5000 -P 3500 ``` Trace with a custom source address: ```shell trip example.com -p tcp -A 127.0.0.1 ``` Trace with a source address determined by the IPv4 address for interface `en0`: ```shell trip example.com -p tcp -I en0 ``` Trace using `IPv6`: ```shell trip example.com -6 ``` Trace using `ipv4-then-ipv6` fallback (or `ipv6-then-ipv4` or `ipv4` or `ipv6`): ```shell trip example.com --addr-family ipv4-then-ipv6 ``` Generate a `json` (or `csv`, `pretty`, `markdown`) tracing report with 5 rounds of data: ```shell trip example.com -m json -C 5 ``` Generate a [Graphviz](https://graphviz.org) `DOT` file report of all tracing flows for a TCP trace after 5 rounds: ```shell trip example.com --tcp -m dot -C 5 ``` Generate a textual report of all tracing flows for a UDP trace after 5 rounds: ```shell trip example.com --udp -m flows -C 5 ``` Perform DNS queries using the `google` DNS resolver (or `cloudflare`, `system`, `resolv`): ```shell trip example.com -r google ``` Lookup AS information for all discovered IP addresses (not yet available for the `system` resolver, see [#66](https://github.com/fujiapple852/trippy/issues/66)): ```shell trip example.com -r google -z ``` Lookup and display `short` (or `long` or `location` or `off`) GeoIp information from a `mmdb` file: ```shell trip example.com --geoip-mmdb-file GeoLite2-City.mmdb --tui-geoip-mode short ``` Parse `icmp` extensions: ```shell trip example.com -e ``` Hide the IP address, hostname and GeoIp for the first two hops: ```shell trip example.com --tui-privacy-max-ttl 2 ``` Customize Tui columns (see [Column Reference](#column-reference)): ```shell trip example.com --tui-custom-columns holsravbwdt ``` Customize the color theme: ```shell trip example.com --tui-theme-colors bg-color=blue,text-color=ffff00 ``` List all Tui items that can have a custom color theme: ```shell trip --print-tui-theme-items ``` Customize the key bindings: ```shell trip example.com --tui-key-bindings previous-hop=k,next-hop=j,quit=shift-q ``` List all Tui commands that can have a custom key binding: ```shell trip --print-tui-binding-commands ``` Specify the location of the Trippy config file: ```shell trip example.com --config-file /path/to/trippy.toml ``` Generate a template configuration file: ```shell trip --print-config-template > trippy.toml ``` Generate `bash` shell completions (or `fish`, `powershell`, `zsh`, `elvish`): ```shell trip --generate bash ``` Generate `ROFF` man page: ```shell trip --generate-man ``` Run in `silent` tracing mode and output `compact` trace logging with `full` span events: ```shell trip example.com -m silent -v --log-format compact --log-span-events full ``` ## Command Reference > [!NOTE] > Trippy command line arguments may be given in any order and my occur both before and after the targets. ```text A network diagnostic tool Usage: trip [OPTIONS] [TARGETS]... Arguments: [TARGETS]... A space delimited list of hostnames and IPs to trace Options: -c, --config-file <CONFIG_FILE> Config file -m, --mode <MODE> Output mode [default: tui] Possible values: - tui: Display interactive TUI - stream: Display a continuous stream of tracing data - pretty: Generate a pretty text table report for N cycles - markdown: Generate a Markdown text table report for N cycles - csv: Generate a CSV report for N cycles - json: Generate a JSON report for N cycles - dot: Generate a Graphviz DOT file for N cycles - flows: Display all flows for N cycles - silent: Do not generate any tracing output for N cycles -u, --unprivileged Trace without requiring elevated privileges on supported platforms [default: false] -p, --protocol <PROTOCOL> Tracing protocol [default: icmp] Possible values: - icmp: Internet Control Message Protocol - udp: User Datagram Protocol - tcp: Transmission Control Protocol --udp Trace using the UDP protocol --tcp Trace using the TCP protocol --icmp Trace using the ICMP protocol -F, --addr-family <ADDR_FAMILY> The address family [default: Ipv4thenIpv6] Possible values: - ipv4: Ipv4 only - ipv6: Ipv6 only - ipv6-then-ipv4: Ipv6 with a fallback to Ipv4 - ipv4-then-ipv6: Ipv4 with a fallback to Ipv6 -4, --ipv4 Use IPv4 only -6, --ipv6 Use IPv6 only -P, --target-port <TARGET_PORT> The target port (TCP & UDP only) [default: 80] -S, --source-port <SOURCE_PORT> The source port (TCP & UDP only) [default: auto] -A, --source-address <SOURCE_ADDRESS> The source IP address [default: auto] -I, --interface <INTERFACE> The network interface [default: auto] -i, --min-round-duration <MIN_ROUND_DURATION> The minimum duration of every round [default: 1s] -T, --max-round-duration <MAX_ROUND_DURATION> The maximum duration of every round [default: 1s] -g, --grace-duration <GRACE_DURATION> The period of time to wait for additional ICMP responses after the target has responded [default: 100ms] --initial-sequence <INITIAL_SEQUENCE> The initial sequence number [default: 33000] -R, --multipath-strategy <MULTIPATH_STRATEGY> The Equal-cost Multi-Path routing strategy (UDP only) [default: classic] Possible values: - classic: The src or dest port is used to store the sequence number - paris: The UDP `checksum` field is used to store the sequence number - dublin: The IP `identifier` field is used to store the sequence number -U, --max-inflight <MAX_INFLIGHT> The maximum number of in-flight ICMP echo requests [default: 24] -f, --first-ttl <FIRST_TTL> The TTL to start from [default: 1] -t, --max-ttl <MAX_TTL> The maximum number of TTL hops [default: 64] --packet-size <PACKET_SIZE> The size of IP packet to send (IP header + ICMP header + payload) [default: 84] --payload-pattern <PAYLOAD_PATTERN> The repeating pattern in the payload of the ICMP packet [default: 0] -Q, --tos <TOS> The TOS (i.e. DSCP+ECN) IP header value (TCP and UDP only) [default: 0] -e, --icmp-extensions Parse ICMP extensions --read-timeout <READ_TIMEOUT> The socket read timeout [default: 10ms] -r, --dns-resolve-method <DNS_RESOLVE_METHOD> How to perform DNS queries [default: system] Possible values: - system: Resolve using the OS resolver - resolv: Resolve using the `/etc/resolv.conf` DNS configuration - google: Resolve using the Google `8.8.8.8` DNS service - cloudflare: Resolve using the Cloudflare `1.1.1.1` DNS service -y, --dns-resolve-all Trace to all IPs resolved from DNS lookup [default: false] --dns-timeout <DNS_TIMEOUT> The maximum time to wait to perform DNS queries [default: 5s] -z, --dns-lookup-as-info Lookup autonomous system (AS) information during DNS queries [default: false] -s, --max-samples <MAX_SAMPLES> The maximum number of samples to record per hop [default: 256] --max-flows <MAX_FLOWS> The maximum number of flows to record [default: 64] -a, --tui-address-mode <TUI_ADDRESS_MODE> How to render addresses [default: host] Possible values: - ip: Show IP address only - host: Show reverse-lookup DNS hostname only - both: Show both IP address and reverse-lookup DNS hostname --tui-as-mode <TUI_AS_MODE> How to render AS information [default: asn] Possible values: - asn: Show the ASN - prefix: Display the AS prefix - country-code: Display the country code - registry: Display the registry name - allocated: Display the allocated date - name: Display the AS name --tui-custom-columns <TUI_CUSTOM_COLUMNS> Custom columns to be displayed in the TUI hops table [default: holsravbwdt] --tui-icmp-extension-mode <TUI_ICMP_EXTENSION_MODE> How to render ICMP extensions [default: off] Possible values: - off: Do not show `icmp` extensions - mpls: Show MPLS label(s) only - full: Show full `icmp` extension data for all known extensions - all: Show full `icmp` extension data for all classes --tui-geoip-mode <TUI_GEOIP_MODE> How to render GeoIp information [default: short] Possible values: - off: Do not display GeoIp data - short: Show short format - long: Show long format - location: Show latitude and Longitude format -M, --tui-max-addrs <TUI_MAX_ADDRS> The maximum number of addresses to show per hop [default: auto] --tui-preserve-screen Preserve the screen on exit [default: false] --tui-refresh-rate <TUI_REFRESH_RATE> The Tui refresh rate [default: 100ms] --tui-privacy-max-ttl <TUI_PRIVACY_MAX_TTL> The maximum ttl of hops which will be masked for privacy [default: 0] --tui-theme-colors <TUI_THEME_COLORS> The TUI theme colors [item=color,item=color,..] --print-tui-theme-items Print all TUI theme items and exit --tui-key-bindings <TUI_KEY_BINDINGS> The TUI key bindings [command=key,command=key,..] --print-tui-binding-commands Print all TUI commands that can be bound and exit -C, --report-cycles <REPORT_CYCLES> The number of report cycles to run [default: 10] -G, --geoip-mmdb-file <GEOIP_MMDB_FILE> The supported MaxMind or IPinfo GeoIp mmdb file --generate <GENERATE> Generate shell completion [possible values: bash, elvish, fish, powershell, zsh] --generate-man Generate ROFF man page --print-config-template Print a template toml config file and exit --log-format <LOG_FORMAT> The debug log format [default: pretty] Possible values: - compact: Display log data in a compact format - pretty: Display log data in a pretty format - json: Display log data in a json format - chrome: Display log data in Chrome trace format --log-filter <LOG_FILTER> The debug log filter [default: trippy=debug] --log-span-events <LOG_SPAN_EVENTS> The debug log format [default: off] Possible values: - off: Do not display event spans - active: Display enter and exit event spans - full: Display all event spans -v, --verbose Enable verbose debug logging -h, --help Print help (see a summary with '-h') -V, --version Print version ``` ## Theme Reference The following table lists the default Tui color theme. These can be overridden with the `--tui-theme-colors` command line option or in the `theme-colors` section of the configuration file. | Item | Description | Default | |--------------------------------------|-----------------------------------------------------------|--------------| | `bg-color` | The default background color | `Black` | | `border-color` | The default color of borders | `Gray` | | `text-color` | The default color of text | `Gray` | | `tab-text-color` | The color of the text in traces tabs | `Green` | | `hops-table-header-bg-color` | The background color of the hops table header | `White` | | `hops-table-header-text-color` | The color of text in the hops table header | `Black` | | `hops-table-row-active-text-color` | The color of text of active rows in the hops table | `Gray` | | `hops-table-row-inactive-text-color` | The color of text of inactive rows in the hops table | `DarkGray` | | `hops-chart-selected-color` | The color of the selected series in the hops chart | `Green` | | `hops-chart-unselected-color` | The color of the unselected series in the hops chart | `Gray` | | `hops-chart-axis-color` | The color of the axis in the hops chart | `DarkGray` | | `frequency-chart-bar-color` | The color of bars in the frequency chart | `Green` | | `frequency-chart-text-color` | The color of text in the bars of the frequency chart | `Gray` | | `flows-chart-bar-selected-color` | The color of the selected flow bar in the flows chart | `Green` | | `flows-chart-bar-unselected-color` | The color of the unselected flow bar in the flows chart | `DarkGray` | | `flows-chart-text-current-color` | The color of the current flow text in the flows chart | `LightGreen` | | `flows-chart-text-non-current-color` | The color of the non-current flow text in the flows chart | `White` | | `samples-chart-color` | The color of the samples chart | `Yellow` | | `help-dialog-bg-color` | The background color of the help dialog | `Blue` | | `help-dialog-text-color` | The color of the text in the help dialog | `Gray` | | `settings-dialog-bg-color` | The background color of the settings dialog | `blue` | | `settings-tab-text-color` | The color of the text in settings dialog tabs | `green` | | `settings-table-header-text-color` | The color of text in the settings table header | `black` | | `settings-table-header-bg-color` | The background color of the settings table header | `white` | | `settings-table-row-text-color` | The color of text of rows in the settings table | `gray` | | `map-world-color` | The color of the map world diagram | `white` | | `map-radius-color` | The color of the map accuracy radius circle | `yellow` | | `map-selected-color` | The color of the map selected item box | `green` | | `map-info-panel-border-color` | The color of border of the map info panel | `gray` | | `map-info-panel-bg-color` | The background color of the map info panel | `black` | | `map-info-panel-text-color` | The color of text in the map info panel | `gray` | The supported [ANSI colors](https://en.wikipedia.org/wiki/ANSI_escape_code#Colors) are: - `Black`, `Red`, `Green`, `Yellow`, `Blue`, `Magenta`, `Cyan`, `Gray`, `DarkGray`, `LightRed`, `LightGreen`, `LightYellow`, `LightBlue`, `LightMagenta`, `LightCyan`, `White` In addition, CSS [named colors](https://developer.mozilla.org/en-US/docs/Web/CSS/named-color) (i.e. SkyBlue) and raw hex values (i.e. ffffff) may be used but note that these are only supported on some platforms and terminals and may not render correctly elsewhere. Color names are case-insensitive and may contain dashes. ## Key Bindings Reference The following table lists the default Tui command key bindings. These can be overridden with the `--tui-key-bindings` command line option or in the `bindings` section of the configuration file. | Command | Description | Default | |------------------------|-------------------------------------------------|----------| | `toggle-help` | Toggle help | `h` | | `toggle-help-alt` | Toggle help (alternative binding) | `?` | | `toggle-settings` | Toggle settings | `s` | | `next-hop` | Select next hop | `down` | | `previous-hop` | Select previous hop | `up` | | `next-trace` | Select next trace | `right` | | `previous-trace` | Select previous trace | `left` | | `next-hop-address` | Select next hop address | `.` | | `previous-hop-address` | Select previous hop address | `,` | | `address-mode-ip` | Show IP address only | `i` | | `address-mode-host` | Show hostname only | `n` | | `address-mode-both` | Show both IP address and hostname | `b` | | `toggle-freeze` | Toggle freezing the display | `ctrl+f` | | `toggle-chart` | Toggle the chart | `c` | | `toggle-map` | Toggle the GeoIp map | `m` | | `toggle-flows` | Toggle the flows | `f` | | `toggle-privacy` | Toggle the hop privacy | `p` | | `expand-hosts` | Expand the hosts shown per hop | `]` | | `expand-hosts-max` | Expand the hosts shown per hop to the maximum | `}` | | `contract-hosts` | Contract the hosts shown per hop | `[` | | `contract-hosts-min` | Contract the hosts shown per hop to the minimum | `{` | | `chart-zoom-in` | Zoom in the chart | `=` | | `chart-zoom-out` | Zoom out the chart | `-` | | `clear-trace-data` | Clear all trace data | `ctrl+r` | | `clear-dns-cache` | Flush the DNS cache | `ctrl+k` | | `clear-selection` | Clear the current selection | `esc` | | `toggle-as-info` | Toggle AS info display | `z` | | `toggle-hop-details` | Toggle hop details | `d` | | `quit` | Quit the application | `q` | The supported modifiers are: `shift`, `ctrl`, `alt`, `super`, `hyper` & `meta`. Multiple modifiers may be specified, for example `ctrl+shift+b`. ## Column Reference The below table lists the columns that are available for display in the Tui. These can be overridden with the `--tui-custom-columns` command line option or in the `tui-custom-columns` attribute in the `tui` section of the configuration file. | Column | Code | Description | |---------|------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------| | `#` | `h` | The time-to-live (TTL) for the hop | | `Host` | `o` | The hostname(s) and IP address(s) for the host(s) for the hop<br/>May include AS info, GeoIp and ICMP extensions<br/>Shows full hop details in hop detail navigation mode | | `Loss%` | `l` | The packet loss % for the hop | | `Snd` | `s` | The number of probes sent for the hop | | `Recv` | `r` | The number of probe responses received for the hop | | `Last` | `a` | The round-trip-time (RTT) of the last probe for the hop | | `Avg` | `v` | The average RTT of all probes for the hop | | `Best` | `b` | The best RTT of all probes for the hop | | `Wrst` | `w` | The worst RTT of all probes for the hop | | `StDev` | `d` | The standard deviation of all probes for the hop | | `Sts` | `t` | The status for the hop:<br/>- 🟢 Healthy hop<br/>- 🔵 Non-target hop with packet loss (does not necessarily indicate a problem)<br/>- 🟤 Non-target hop is unresponsive (does not necessarily indicate a problem) <br/>- 🟡 Target hop with packet loss (likely indicates a problem)<br/>- 🔴 Target hop is unresponsive (likely indicates a problem) | | `Jttr` | `j` | The round-trip-time (RTT) difference between consecutive rounds for the hop | | `Javg` | `g` | The average jitter of all probes for the hop | | `Jmax` | `x` | The maximum jitter of all probes for the hop | | `Jint` | `u` | The smoothed jitter value of all probes for the hop | | `Seq` | `Q` | The sequence number for the last probe for the hop | | `Sprt` | `S` | The source port for the last probe for the hop | | `Dprt` | `P` | The destination port for the last probe for the hop | | `Type` | `T` | The icmp packet type for the last probe for the hop:<br/>- TE: TimeExceeded<br/>- ER: EchoReply<br/>- DU: DestinationUnreachable<br/>- NA: NotApplicable | | `Code` | `C` | The icmp packet code for the last probe for the hop | The default columns are `holsravbwdt`. > [!NOTE] > The columns will be shown in the order specified in the configuration. ## Configuration Reference Trippy can be configured with via command line arguments or an optional configuration file. If a given configuration item is specified in both the configuration file and via a command line argument then the latter will take precedence. The configuration file location may be provided to Trippy via the `-c` (`--config-file`) argument. If not provided, Trippy will attempt to locate a `trippy.toml` or `.trippy.toml` configuration file in one of the following locations: - The current directory - The user home directory - the XDG config directory (Unix only): `$XDG_CONFIG_HOME` or `~/.config` - the Windows data directory (Windows only): `%APPDATA%` An annotated template configuration file is available for [0.9.0](https://github.com/fujiapple852/trippy/blob/0.9.0/trippy-config-sample.toml) and [0.10.0](https://github.com/fujiapple852/trippy/blob/0.10.0/trippy-config-sample.toml). Trippy (version `0.9.0` or later) can generate a template configuration file: ```shell trip --print-config-template > trippy.toml ``` ## Frequently Asked Questions ### Why does Trippy show "Awaiting data..."? > [!IMPORTANT] > If you are using Windows you _must_ [configure](#how-do-i-allow-incoming-icmp-traffic-in-the-windows-defender-firewall) > the Windows Defender firewall to allow incoming ICMP traffic When Trippy shows “Awaiting data...” it means that it has received zero responses for the probes sent in a trace. This indicates that either probes are not being sent or, more typically, responses are not being received. Check that local and network firewalls allow ICMP traffic and that the system `traceroute` (or `tracert.exe` on Windows) works as expected. Note that on Windows, even if `tracert.exe` works as expected, you _must_ [configure](#how-do-i-allow-incoming-icmp-traffic-in-the-windows-defender-firewall) the Windows Defender firewall to allow incoming ICMP traffic. For deeper diagnostics you can run tools such as https://www.wireshark.org and https://www.tcpdump.org to verify that icmp requests and responses are being send and received. <a name="windows-defender"></a> ### How do I allow incoming ICMP traffic in the Windows Defender firewall? The Windows Defender firewall rule can be created using PowerShell: ```shell New-NetFirewallRule -DisplayName "ICMP Trippy Allow" -Name ICMP_TRIPPY_ALLOW -Protocol ICMPv4 -Action Allow ``` The rule can be enabled and disabled as follows: ```shell Enable-NetFirewallRule ICMP_TRIPPY_ALLOW Disable-NetFirewallRule ICMP_TRIPPY_ALLOW ``` The Windows Defender firewall rule may also be configured manually, see [here](https://github.com/fujiapple852/trippy/issues/578#issuecomment-1565149826) for a step-by-step guide. ## Acknowledgements Trippy is made possible by [ratatui](https://github.com/ratatui-org/ratatui) ( formerly [tui-rs](https://github.com/fdehau/tui-rs)), [crossterm](https://github.com/crossterm-rs/crossterm) as well as [several](https://github.com/fujiapple852/trippy/blob/master/Cargo.toml) foundational Rust libraries. Trippy draws heavily from [mtr](https://github.com/traviscross/mtr) and also incorporates ideas from both [libparistraceroute](https://github.com/libparistraceroute/libparistraceroute) & [Dublin Traceroute](https://github.com/insomniacslk/dublin-traceroute). The Trippy networking code is inspired by [pnet](https://github.com/libpnet/libpnet) and some elements of that codebase are incorporated in Trippy. The [AS](https://en.wikipedia.org/wiki/Autonomous_system_(Internet)) data is retrieved from the [IP to ASN Mapping Service](https://team-cymru.com/community-services/ip-asn-mapping/#dns) provided by [Team Cymru](https://team-cymru.com). The [trippy.cli.rs](https://trippy.cli.rs) CNAME hosting is provided by [cli.rs](https://cli.rs). The Trippy chat room is sponsored by [Zulip](https://zulip.com). ## License This project is distributed under the terms of the Apache License (Version 2.0). Unless you explicitly state otherwise, any contribution intentionally submitted for inclusion in time by you, as defined in the Apache-2.0 license, shall be licensed as above, without any additional terms or conditions. See [LICENSE](LICENSE) for details. Copyright 2022 [Trippy Contributors](https://github.com/fujiapple852/trippy/graphs/contributors)

A network diagnostic tool

cli,mtr,network,ping,rust,tool,traceroute,tui,tui-rs,icmp

actuallymentor/battery

# Battery charge limiter for Apple Silicon Macbook devices <img width="300px" align="right" src="./screenshots/tray.png"/>This tool makes it possible to keep a chronically plugged in Apple Silicon Macbook at `80%` battery, since that will prolong the longevity of the battery. It is free and open-source and will remain that way. > Want to know if this tool does anything or is just a placebo? Read [this excellent article](https://batteryuniversity.com/article/bu-808-how-to-prolong-lithium-based-batteries). TL;DR: keep your battery cool, keep it at 80% when plugged in, and discharge it as shallowly as feasible. ### Requirements This is an app for Apple Silicon Macs. It will not work on Intel macs. Do you have an older Mac? Consider the free version of the [Al Dente](https://apphousekitchen.com/) software package. It is a good alternative and has a premium version with many more features. ### Installation - Option 1: install through brew with `brew install battery` - Option 2: [You can download the latest app dmg version here](https://github.com/actuallymentor/battery/releases/). - Option 3: command-line only installation (see section below) The first time you open the app, it will ask for your administator password so it can install the needed components. Please note that the app: - Discharges your battery until it reaches 80%, **even when plugged in** - Disables charging when your battery is above 80% charged - Enabled charging when your battery is under 80% charged - Keeps the limit engaged even after rebooting - Keeps the limit engaged even after closing the tray app - Also automatically installs the `battery` command line tool. If you want a custom charging percentage, the CLI is the only way to do that. Do you have questions, comments, or feature requests? [Open an issue here](https://github.com/actuallymentor/battery/issues) or [Tweet at me](https://twitter.com/actuallymentor). --- ## 🖥 Command-line version > If you don't know what a "command line" is, ignore this section. You don't need it. The GUI app uses a command line tool under the hood. Installing the GUI automatically installs the CLI as well. You can also separately install the CLI. The CLI is used for managing the battery charging status for Apple Silicon Macbooks. Can be used to enable/disable the Macbook from charging the battery when plugged into power. ### Installation One-line installation: ```bash curl -s https://raw.githubusercontent.com/actuallymentor/battery/main/setup.sh | bash ``` This will: 1. Download the precompiled `smc` tool in this repo (built from the [hholtmann/smcFanControl](https://github.com/hholtmann/smcFanControl.git) repository) 2. Install `smc` to `/usr/local/bin` 3. Install `battery` to `/usr/local/bin` ### Usage Example usage: ```shell # This will enable charging when your battery dips under 80, and disable it when it exceeds 80 battery maintain 80 ``` After running a command like `battery charging off` you can verify the change visually by looking at the battery icon:  After running `battery charging on` you will see it change to this:  For help, run `battery` without parameters: ``` Battery CLI utility v1.0.1 Usage: battery status output battery SMC status, % and time remaining battery maintain LEVEL[1-100,stop] reboot-persistent battery level maintenance: turn off charging above, and on below a certain value eg: battery maintain 80 eg: battery maintain stop battery charging SETTING[on/off] manually set the battery to (not) charge eg: battery charging on battery adapter SETTING[on/off] manually set the adapter to (not) charge even when plugged in eg: battery adapter off battery charge LEVEL[1-100] charge the battery to a certain percentage, and disable charging when that percentage is reached eg: battery charge 90 battery discharge LEVEL[1-100] block power input from the adapter until battery falls to this level eg: battery discharge 90 battery visudo ensure you don't need to call battery with sudo This is already used in the setup script, so you should't need it. battery update update the battery utility to the latest version battery reinstall reinstall the battery utility to the latest version (reruns the installation script) battery uninstall enable charging, remove the smc tool, and the battery script ``` ## FAQ & Troubleshooting ### Why does this exist? I was looking at the Al Dente software package for battery limiting, but I found the [license too limiting](https://github.com/davidwernhart/AlDente/discussions/558) for a poweruser like myself. I would actually have preferred using Al Dente, but decided to create a command-line utility to replace it as a side-project on holiday. A colleague mentioned they would like a GUI, so I spend a few evenings setting up an Electron app. And voila, here we are. ### "It's not working" If you used one of the earlier versions of the `battery` utility, you may run into [path/permission issues](https://github.com/actuallymentor/battery/issues/8). This is not your fault but mine. To fix it: ``` sudo rm -rf ~/.battery binfolder=/usr/local/bin sudo rm -v "$binfolder/smc" "$binfolder/battery" ``` Then reopen the app and things should work. If not, [open an issue](https://github.com/actuallymentor/battery/issues/new/choose) and I'll try to help you fix it. ### A note to Little Snitch users This tool calls a number of urls, blocking all of them will only break auto-updates. 1. `unidentifiedanalytics.web.app` is a self-made app that tracks app installations, I use it to see if enough people use the app to justify spending time on it. It tracks only how many unique ip addresses open the app. 1. `icanhazip.com` is used to see if there is an internet connection 1. `github.com` is used both as a liveness check and as the source of updates for the underlying command-line utility 1. `electronjs.org` hosts the update server for the GUI All urls are called over `https` and so not leak data. Unidentified Analytics keeps track of unique ip addresses that open the app, but nothing else. ### What distinguishes this project from Optimized Charging? Optimized Charging, a feature that is built into MacOS, aims to ensure the longevity and health of your battery. It does so by "delaying charging the battery past 80% when it predicts that you’ll be plugged in for an extended period of time, and aims to charge the battery before you unplug," as explained in [Apple's user guide](https://support.apple.com/en-ca/guide/mac-help/mchlfc3b7879/mac#:~:text=Optimized%20Battery%20Charging%3A%20To%20reduce,the%20battery%20before%20you%20unplug.). Additionally, Optimized Charging uses machine learning to decide when the battery should be held at 80%, and when it should become fully charged. If your Mac is not plugged in on a regular schedule, optimized charging will not work as intended. This app is a similar alternative to Optimized Charging, giving the user control over when it is activated, what percentage the battery should be held at, and more. ### How do I support this project? Do you know how to code? Open a pull-request for a feature with the label [help wanted (PR welcome)](https://github.com/actuallymentor/battery/labels/help%20wanted%20%28PR%20welcome%29). Do you have an awesome feature idea? [Add a feature request](https://github.com/actuallymentor/battery/issues/new/choose) Do you just want to keep me motivated to update the app? [Tweet at me](https://twitter.com/actuallymentor)

CLI for managing the battery charging status for M1 Macs

ngneat/falso

<p align="center"> <img width="20%" height="20%" src="logo.png"> </p> > All the Fake Data for All Your Real Needs 🙂 Create massive amounts of fake data in the browser and NodeJS. Tree Shakeable & Fully Typed. <hr /> <p align="center"> [](https://github.com/ngneat/falso/actions/workflows/ci.yml) []() []() [](CODE_OF_CONDUCT.md) [](https://github.com/semantic-release/semantic-release) [](https://github.com/prettier/prettier) </p> ✅ &nbsp;203 Functions ✅ &nbsp;Tree Shakable ✅ &nbsp;Fully Typed ✅ &nbsp;Factory Functions ✅ &nbsp;Entity Functions ✅ &nbsp;Single and Array Result 🤓 Learn about it on the [docs site](https://ngneat.github.io/falso/) <br> ## Sponsoring ngneat [Sponsorships](https://github.com/sponsors/ngneat) aid in the continued development and maintenance of ngneat libraries. Consider asking your company to sponsor ngneat as its core to their business and application development. ### Gold Sponsors Elevate your support by becoming a Gold Sponsor and have your logo prominently featured on our README in the top 5 repositories. ### Silver Sponsors Boost your backing by becoming a Gold Sponsor and enjoy the spotlight with your logo prominently showcased in the top 3 repositories on our README. ### Bronze Sponsors <a href="https://houseofangular.io" target="_blank"> <img src="https://github.com/ngrx/platform/blob/main/projects/ngrx.io/src/assets/images/sponsors/house-of-angular.png" width="50px" height="50px" alt="House of Angular" /> </a> Become a bronze sponsor and get your logo on our README on GitHub. ## StackBlitz [](https://stackblitz.com/edit/typescript-pj5epp?file=index.ts) ## Installation ``` npm i @ngneat/falso yarn add @ngneat/falso ``` ### Usage ```ts import { randEmail, randFullName } from '@ngneat/falso'; const user = { email: randEmail(), name: randFullName() }; const emails = randEmail({ length: 10 }); ``` You can specify the length of elements you want to generate. Below is an example of generating 10 emails with length equal or smaller than 20 characters. ```ts const emails = randEmail({ length: 10, maxCharCount: 20 }); ``` ### Setting a Randomness Seed You can set your own seed if you want consistent results: ```ts import { rand, seed } from '@ngneat/falso'; seed('some-constant-seed'); // Always returns 2 rand([1, 2, 3, 4, 5]); // Reset random seed seed(); ``` ## Contribute - Go over the steps in [this](https://github.com/firstcontributions/first-contributions) guide - Add a new falso  - Use `npm run c` and choose the right answers <div>Icons made by <a href="https://www.freepik.com" title="Freepik">Freepik</a> from <a href="https://www.flaticon.com/" title="Flaticon">www.flaticon.com</a></div>

All the Fake Data for All Your Real Needs 🙂

fake,data,mock,mockdata,fakedata,random

Threekiii/Awesome-POC

# Awesome-POC ##### **【免责声明】本项目所涉及的技术、思路和工具仅供学习，任何人不得将其用于非法用途和盈利，不得将其用于非授权渗透测试，否则后果自行承担，与本项目无关。使用本项目前请先阅读 [法律法规](https://github.com/Threekiii/Awesome-Laws)。** ## 0x01 项目导航 - CHECKLIST * Nacos 漏洞 Checklist * SmartBi 漏洞 Checklist * 安全设备漏洞 Checklist - CMS漏洞 * 74cms v4.2.1 v4.2.129 后台getshell漏洞 * 74cms v5.0.1 后台跨站请求伪造漏洞 CVE-2019-11374 * Anchor CMS 0.12.7 跨站请求伪造 CVE-2020-23342 * AspCMS commentList.asp SQL注入漏洞 * BloofoxCMS 0.5.2.1 存储型XSS * BSPHP index.php 未授权访问 信息泄露漏洞 * CMS Made Simple (CMSMS) 前台SQL注入漏洞 CVE-2019-9053 * CMS Made Simple (CMSMS) 前台代码执行漏洞 CVE-2021-26120 * CmsEasy crossall_act.php SQL注入漏洞 * CmsEasy language_admin.php 后台命令执行漏洞 * CmsEasy update_admin.php 后台任意文件上传漏洞 * CxCMS Resource.ashx 任意文件读取漏洞 * DedeCMS 5.7 file_manage_control.php 文件包含 RCE CVE-2023-2928 * DedeCMS 5.7SP2 代码执行漏洞 CVE-2019-8933 * DedeCMS 5.8.1 common.func.php 远程命令执行漏洞 * Discuz 3.4 最新版后台getshell * Discuz 7.x6.x 全局变量防御绕过导致代码执行 * Discuz!X ≤3.4 任意文件删除漏洞 * Discuz!X 3.4 admincp_setting.php 后台SQL注入漏洞 * Discuz!X3.4 后台修改UCenter配置getshell漏洞 * DocCMS keyword SQL注入漏洞 * Drupal 7.32 “Drupalgeddon” SQL注入漏洞 CVE-2014-3704 * Drupal Core 8 PECL YAML 反序列化任意代码执行漏洞 CVE-2017-6920 * Drupal Drupalgeddon 2 远程代码执行漏洞 CVE-2018-7600 * Drupal XSS漏洞 CVE-2019-6341 * Drupal 远程代码执行漏洞 CVE-2018-7602 * Drupal 远程代码执行漏洞 CVE-2019-6339 * ECShop 2.x3.x SQL注入任意代码执行漏洞 * ECShop 4.x collection_list SQL注入 * emlog widgets.php 后台SQL注入漏洞 * ezEIP 4.1.0 信息泄露漏洞 * Fuel CMS 1.4.1 远程代码执行漏洞 * Joomla 3.4.5 反序列化漏洞 CVE-2015-8562 * Joomla 3.7.0 SQL注入漏洞 CVE-2017-8917) * Joomla application 权限绕过漏洞 CVE-2023-23752 * Joomla 目录遍历及远程代码执行漏洞 CVE-2021-23132 * JunAms内容管理系统文件上传漏洞 CNVD-2020-24741 * Ke361 AuthManagerController.class.php 后台SQL注入漏洞 * Ke361 DistrictController.class.php 后台SQL注入漏洞 CNVD-2021-25002 * Ke361 GoodsController.class.php SSRF漏洞 * Ke361 MenuController.class.php 后台SQL注入漏洞 CNVD-2021-25002 * Ke361 TopicController.class.php SQL注入漏洞 CNVD-2017-04380 * Liferay Portal CE 反序列化命令执行漏洞 CVE-2020-7961 * OKLite 1.2.25 后台插件安装 任意文件上传 * OKLite 1.2.25 后台模块导入 任意文件上传 CVE-2019-16131 * OKLite 1.2.25 后台风格模块 任意文件删除 CVE-2019-16132 * OneBlog 开源博客管理系统 远程命令执行漏洞 * OpenSNS Application ShareController.class.php 远程命令执行漏洞 * OpenSNS AuthorizeController.class.php 后台远程命令执行漏洞 * OpenSNS ChinaCityController.class.php SQL注入漏洞 * OpenSNS CurlModel.class.php SSRF漏洞 * OpenSNS ThemeController.class.php 后台任意文件上传漏洞 * OpenSNS ThemeController.class.php 后台任意文件下载漏洞 * Pb-CMS Shiro默认密钥 远程命令执行漏洞 * PbootCMS domain SQL注入漏洞 * PbootCMS ext_price SQL注入漏洞 * PbootCMS search SQL注入漏洞 * PbootCMS V3.1.2 正则绕过 RCE 漏洞 * PigCMS action_flashUpload 任意文件上传漏洞 * ShopXO download 任意文件读取漏洞 CNVD-2021-15822 * Tiki Wiki CMS Groupware 认证绕过漏洞 CVE-2020-15906 * TypesetterCMS 后台任意文件上传 * UCMS 文件上传漏洞 CVE-2020-25483 * WeiPHP3.0 session_id 任意文件上传漏洞 * WeiPHP5.0 bind_follow SQL注入漏洞 * WeiPHP5.0 download_imgage 前台文件任意读取 CNVD-2020-68596 * WeiPHP5.0 任意用户Cookie伪造 CNVD-2021-09693 * WordPress 3DPrint Lite 3dprint-lite-functions.php 任意文件上传漏洞 * Wordpress 4.6 任意命令执行漏洞 PwnScriptum * WordPress All-in-One Video Gallery video.php 任意文件读取漏洞 CVE-2022-2633 * WordPress Duplicator duplicator.php 任意文件读取漏洞 CVE-2020-11738 * WordPress Elementor Page Builder Plus 身份验证绕过 CVE-2021-24175 * WordPress File Manager＜6.9 RCE CVE-2020-25213 * WordPress Redux Framework class-redux-helpers.php 敏感信息泄漏漏洞 CVE-2021-38314 * WordPress Simple File List ee-downloader.php 任意文件读取漏洞 CVE-2022-1119 * WordPress SuperForms 4.9 任意文件上传到远程代码执行 * WordPress WP_Query SQL 注入漏洞 CVE-2022-21661 * YzmCMS Version 小于V5.8正式版 后台采集模块 SSRF漏洞 * ZZZCMS parserSearch 远程命令执行漏洞 * 华宜互联 硬编码超级管理员漏洞 * 原创先锋 后台管理平台 未授权访问漏洞 * 发货100 M_id SQL注入漏洞 CNVD-2021-30193 * 快排CMS Socket.php 日志信息泄露漏洞 * 快排CMS 后台XSS漏洞 * 快排CMS 后台任意文件上传漏洞 * 极致CMS 1.81 后台存储型XSS * 极致CMS alipay_return_pay SQL注入漏洞 * 极致CMS 后台文件编辑插件 任意文件上传 * 狮子鱼CMS ApiController.class.php SQL注入漏洞 * 狮子鱼CMS ApigoodController.class.php SQL注入漏洞 * 狮子鱼CMS image_upload.php 任意文件上传 * 狮子鱼CMS wxapp.php 任意文件上传漏洞 * 禅道 11.6 api-getModel-api-getMethod-filePath 任意文件读取漏洞 * 禅道 11.6 api-getModel-api-sql-sql 后台SQL注入漏洞 * 禅道 11.6 api-getModel-editor-save-filePath 任意文件写入漏洞 * 禅道 12.4.2 CSRF漏洞 CNVD-2020-68552 * 禅道 12.4.2 后台任意文件上传漏洞 CNVD-C-2020-121325 * 禅道 V16.5 SQL 注入 CNVD-2022-42853 * 禅道 项目管理系统远程命令执行漏洞 CNVD-2023-02709 * 齐博CMS V7 job.php 任意文件读取漏洞 - OA产品漏洞 * O2OA invoke 后台远程命令执行漏洞 CNVD-2020-18740 * O2OA open 后台任意文件读取漏洞 * 一米OA getfile.jsp 任意文件读取漏洞 * 万户OA DocumentEdit.jsp SQL注入漏洞 * 万户OA download_ftp.jsp 任意文件下载漏洞 * 万户OA download_old.jsp 任意文件下载漏洞 * 万户OA downloadhttp.jsp 任意文件下载漏洞 * 万户OA DownloadServlet 任意文件读取漏洞 * 万户OA fileUpload.controller 任意文件上传漏洞 * 万户OA OfficeServer.jsp 任意文件上传漏洞 * 万户OA showResult.action 后台SQL注入漏洞 * 万户OA smartUpload.jsp 任意文件上传漏洞 * 万户OA TeleConferenceService XXE注入漏洞 * 信呼OA beifenAction.php 后台目录遍历漏洞 * 信呼OA qcloudCosAction.php 任意文件上传漏洞 * 华天动力OA 8000版 workFlowService SQL注入漏洞 * 启莱OA CloseMsg.aspx SQL注入漏洞 * 启莱OA messageurl.aspx SQL注入漏洞 * 启莱OA treelist.aspx SQL注入漏洞 * 帆软报表 2012 SSRF漏洞 * 帆软报表 2012 信息泄露漏洞 * 帆软报表 channel 远程命令执行漏洞 * 帆软报表 V8 任意文件读取漏洞 CNVD-2018-04757 * 帆软报表 V9 任意文件覆盖文件上传 * 新点OA ExcelExport 敏感信息泄露漏洞 * 智明 SmartOA EmailDownload.ashx 任意文件下载漏洞 * 极限OA video_file.php 任意文件读取漏洞 * 泛微OA DBconfigReader.jsp 数据库配置信息泄漏漏洞 * 泛微OA E-Bridge saveYZJFile 任意文件读取漏洞 * 泛微OA E-Cology BshServlet 远程代码执行漏洞 CNVD-2019-32204 * 泛微OA E-Cology getSqlData SQL注入漏洞 * 泛微OA E-Cology HrmCareerApplyPerView.jsp SQL注入漏洞 * 泛微OA E-Cology jqueryFileTree.jsp 目录遍历漏洞 * 泛微OA E-cology KtreeUploadAction 任意文件上传 * 泛微OA E-Cology LoginSSO.jsp SQL注入漏洞 CNVD-2021-33202 * 泛微OA E-Cology ofsLogin.jsp 前台任意用户登录漏洞 * 泛微OA E-Cology users.data 敏感信息泄漏 * 泛微OA E-Cology VerifyQuickLogin.jsp 任意管理员登录漏洞 * 泛微OA E-cology WorkflowServiceXml RCE * 泛微OA E-Office group_xml.php SQL注入漏洞 * 泛微OA E-Office mysql_config.ini 数据库信息泄漏漏洞 * 泛微OA E-Office OfficeServer.php 任意文件上传漏洞 * 泛微OA E-Office officeserver.php 任意文件读取漏洞 * 泛微OA E-Office UploadFile.php 任意文件上传漏洞 CNVD-2021-49104 * 泛微OA E-Office uploadify 任意文件上传漏洞 * 泛微OA E-Office UserSelect 未授权访问漏洞 * 泛微OA E-Weaver SignatureDownLoad 任意文件读取漏洞 * 泛微OA getdata.jsp SQL注入漏洞 * 泛微OA ln.FileDownload 任意文件读取漏洞 * 泛微OA sysinterfacecodeEdit.jsp 任意文件上传漏洞 * 泛微OA uploadOperation.jsp 任意文件上传 * 泛微OA v9 E-Cology browser.jsp SQL注入漏洞 * 泛微OA weaver.common.Ctrl 任意文件上传漏洞 * 泛微OA WorkflowCenterTreeData SQL注入漏洞 * 用友 ERP-NC NCFindWeb 目录遍历漏洞 * 用友 FE协作办公平台 templateOfTaohong_manager.jsp 目录遍历漏洞 * 用友 GRP-U8 Proxy SQL注入 CNNVD-201610-923 * 用友 GRP-U8 UploadFileData 任意文件上传漏洞 * 用友 NC bsh.servlet.BshServlet 远程命令执行漏洞 * 用友 NC Cloud jsinvoke 任意文件上传漏洞 * 用友 NC Cloud 远程代码执行漏洞 CNVD-C-2023-76801 * 用友 NC FileReceiveServlet 反序列化RCE漏洞 * 用友 NC NCFindWeb 任意文件读取漏洞 * 用友 NC XbrlPersistenceServlet反序列化 * 用友 NCCloud FS文件管理SQL注入 * 用友 U8 cloud upload.jsp 任意文件上传漏洞 * 用友 U8 CRM客户关系管理系统 getemaildata.php 任意文件上传漏洞 * 用友 U8 CRM客户关系管理系统 getemaildata.php 任意文件读取漏洞 * 用友 U8 OA getSessionList.jsp 敏感信息泄漏漏洞 * 用友 U8 OA test.jsp SQL注入漏洞 * 用友 移动管理系统 uploadApk.do 任意文件上传漏洞 * 用友时空 KSOA V9.0 文件上传漏洞 * 红帆OA ioFileExport.aspx 任意文件读取漏洞 * 致翔OA msglog.aspx SQL注入漏洞 * 致远 OA 未授权短信验证码绕过重置密码漏洞 * 致远OA A6 config.jsp 敏感信息泄漏漏洞 * 致远OA A6 createMysql.jsp 数据库敏感信息泄露 * 致远OA A6 DownExcelBeanServlet 用户敏感信息泄露 * 致远OA A6 initDataAssess.jsp 用户敏感信息泄露 * 致远OA A6 setextno.jsp SQL注入漏洞 * 致远OA A6 test.jsp SQL注入漏洞 * 致远OA A8 htmlofficeservlet 任意文件上传漏洞 * 致远OA A8 status.jsp 信息泄露漏洞 * 致远OA ajax.do 任意文件上传 CNVD-2021-01627 * 致远OA getSessionList.jsp Session泄漏漏洞 * 致远OA M1Server userTokenService 远程命令执行漏洞 * 致远OA webmail.do 任意文件下载 CNVD-2020-62422 * 致远OA wpsAssistServlet 任意文件上传漏洞 * 致远OA 帆软组件 ReportServer 目录遍历漏洞 * 蓝凌EIS 智慧协同平台 api.aspx 任意文件上传漏洞 * 蓝凌OA admin.do JNDI远程命令执行 * 蓝凌OA custom.jsp 任意文件读取漏洞 * 蓝凌OA kmImeetingRes.do 后台SQL注入漏洞 CNVD-2021-01363 * 蓝凌OA sysSearchMain.do 远程命令执行漏洞 * 蓝凌OA treexml.tmpl 远程命令执行漏洞 * 通达OA v11.2 upload.php 后台任意文件上传漏洞 * 通达OA v11.5 login_code.php 任意用户登录 * 通达OA v11.5 logincheck_code.php 登陆绕过漏洞 * 通达OA v11.5 swfupload_new.php SQL注入漏洞 * 通达OA v11.6 print.php 任意文件删除&RCE * 通达OA v11.6 report_bi.func.php SQL注入漏洞 * 通达OA v11.7 auth_mobi.php 在线用户登录漏洞 * 通达OA v11.7 delete_cascade.php 后台SQL注入 * 通达OA v11.8 api.ali.php 任意文件上传漏洞 * 通达OA v11.8 getway.php 远程文件包含漏洞 * 通达OA v11.8 update.php 后台文件包含XSS漏洞 * 通达OA v11.8 update.php 后台文件包含命令执行漏洞 * 通达OA v11.9 getdata 任意命令执行漏洞 * 通达OA v11.9 upsharestatus 后台SQL注入漏洞 * 通达OA v2014 get_contactlist.php 敏感信息泄漏漏洞 * 通达OA v2017 action_upload.php 任意文件上传漏洞 * 通达OA v2017 video_file.php 任意文件下载漏洞 * 通达OA 部分漏洞信息整合 * 金和OA C6 DossierBaseInfoView.aspx 后台越权信息泄露漏洞 * 金和OA C6 download.jsp 任意文件读取漏洞 * 金和OA C6 OpenFile.aspx 后台越权敏感文件遍历漏洞 * 金蝶OA Apusic应用服务器(中间件) server_file 目录遍历漏洞 * 金蝶OA EAS系统 uploadLogo.action 任意文件上传漏洞 * 金蝶OA server_file 目录遍历漏洞 * 金蝶OA 云星空 CommonFileServer 任意文件读取漏洞 * 金蝶OA 云星空 ScpSupRegHandler 任意文件上传漏洞 - Web应用漏洞 * 1039家校通 万能密码绕过 CNVD-2020-31494 * 1039家校通 后台任意文件上传漏洞 * 1Panel loadfile 后台文件读取漏洞 * 360天擎 gettablessize 数据库信息泄露漏洞 * 360天擎 rptsvcsyncpoint 前台SQL注入 * Active UC index.action 远程命令执行漏洞 * Adminer ElasticSearch 和 ClickHouse 错误页面SSRF漏洞 CVE-2021-21311 * Adminer 远程文件读取 CVE-2021-43008 * Adminer-SSRF漏洞 CVE-2021-21311 * Adobe ColdFusion upload.cfm 任意文件上传漏洞 CVE-2018-15961 * Adobe ColdFusion 远程代码执行漏洞 CVE-2021-21087 * Afterlogic Aurora & WebMail Pro 任意文件读取 CVE-2021-26294 * Afterlogic Aurora & WebMail Pro 文件上传漏洞 CVE-2021-26293 * AJ-Report 认证绕过与远程代码执行漏洞 CNVD-2024-15077 * Alibaba AnyProxy fetchBody 任意文件读取漏洞 * Alibaba Canal config 云密钥信息泄露漏洞 * Alibaba otter manager分布式数据库同步系统信息泄漏 CNVD-2021-16592 * Apache Airflow Celery 消息中间件命令执行 CVE-2020-11981 * Apache Airflow 示例DAG中的命令注入 CVE-2020-11978 * Apache Airflow 远程代码执行漏洞 CVE-2022-40127 * Apache Airflow 默认密钥导致的权限绕过 CVE-2020-17526 * Apache Superset SECRET_KEY 未授权访问漏洞 CVE-2023-27524 * Apache Unomi 远程表达式代码执行漏洞 CVE-2020-13942 * Apache Zeppelin 未授权任意命令执行漏洞 * Appspace jsonprequest SSRF漏洞 CVE-2021-27670 * Aria2 任意文件写入漏洞 * Atlassian Bitbucket archive 远程命令执行漏洞 CVE-2022-36804 * Atlassian Bitbucket Data Center 远程代码执行漏洞 CVE-2022-26133 * Atlassian Bitbucket 登录绕过漏洞 * Atlassian Confluence doenterpagevariables.action 远程命令执行漏洞 CVE-2021-26084 * Atlassian Confluence OGNL表达式注入代码执行漏洞 CVE-2021-26084 * Atlassian Confluence OGNL表达式注入命令执行漏洞 CVE-2022-26134 * Atlassian Confluence OGNL表达式注入命令执行漏洞 CVE-2023-22527 * Atlassian Confluence preview SSTI模版注入漏洞 CVE-2019-3396 * Atlassian Confluence server-info.action 属性覆盖导致权限绕过漏洞 CVE-2023-22515 * Atlassian Confluence 敏感信息泄露 CVE-2021-26085 * Atlassian Confluence 路径穿越与命令执行漏洞 CVE-2019-3396 * Atlassian Jira cfx 任意文件读取漏洞 CVE-2021-26086 * Atlassian Jira com.atlassian.jira 敏感信息泄漏 CVE-2019-8442 * Atlassian Jira groupuserpicker 用户信息枚举漏洞 CVE-2019-8449 * Atlassian Jira makeRequest SSRF漏洞 CVE-2019-8451 * Atlassian Jira Mobile Plugin SSRF漏洞 CVE-2022-26135 * Atlassian Jira Server 及 Data Center 信息泄露漏洞 CVE-2020-14179 * Atlassian Jira ViewUserHover.jspa 用户信息泄露漏洞 CVE-2020-14181 * Atlassian Jira 敏感信息泄露 CVE-2021-26086 * Atlassian Jira 模板注入漏洞 CVE-2019-11581 * Atlassian Questions For Confluence 身份认证绕过漏洞 CVE-2022-26138 * AVCON6 系统管理平台 download.action 任意文件下载漏洞 * AVCON6 系统管理平台 org_execl_download.action 任意文件下载漏洞 * Cacti SQL 注入漏洞 CVE-2020-14295 * Cacti 前台命令注入漏洞 CVE-2022-46169 * Casbin get-users 账号密码泄漏漏洞 * Casdoor static 任意文件读取漏洞 * Celery 4.0 Redis未授权访问+Pickle反序列化利用 * Cerebro request SSRF漏洞 * Citrix XenMobile 任意文件读取 CVE-2020-8209 * CloudPanel makefile 任意文件上传漏洞 CVE-2023-35885 * CMA客诉管理系统 upFile.ashx 任意文件上传漏洞 * Coremail 路径遍历与文件上传漏洞 * Coremail 配置信息泄露漏洞 * Crawlab file 任意文件读取漏洞 * Crawlab users 任意用户添加漏洞 * Dapr Dashboard configurations 未授权访问漏洞 CVE-2022-38817 * Dogtag PKI XML实体注入漏洞 CVE-2022-2414 * Dolibarr edit.php 远程命令执行漏洞 CVE-2022-40871 * E-message 越权访问漏洞 * EasyImage down.php 任意文件读取漏洞 * EasyImage manager.php 后台任意文件上传漏洞 * EduSoho 教培系统 app_dev.php 任意读取漏洞 * eGroupWare spellchecker.php 远程命令执行漏洞 * Evolucare Ecsimaging download_stats_dicom.php 任意文件读取漏洞 * Evolucare Ecsimaging new_movie.php 远程命令执行漏洞 * F5 BIG-IP iControl REST身份认证绕过漏洞 CVE-2022-1388 * F5 BIG-IP 远程代码执行漏洞 CVE-2020-5902 * F5 BIG-IP 远程代码执行漏洞 CVE-2021-22986 * FFmpeg 任意文件读取漏洞SSRF漏洞 CVE-2016-1897+CVE-2016-1898 * Fhem FileLog_logWrapper 任意文件读取漏洞 CVE-2020-19360 * Franklin Fueling Systems tsaupload.cgi 任意文件读取漏洞 CVE-2021-46417 * Gerapy clone 后台远程命令执行漏洞 CVE-2021-32849 * Gerapy parse 后台远程命令执行漏洞 * Gerapy read 后台任意文件读取漏洞 * GhostScript 沙箱绕过（命令执行）漏洞 CVE-2018-16509 * GhostScript 沙箱绕过（命令执行）漏洞 CVE-2018-19475 * GhostScript 沙箱绕过（命令执行）漏洞 CVE-2019-6116 * Gitea 1.4.0 目录穿越导致命令执行漏洞 * GitLab Graphql邮箱信息泄露漏洞 CVE-2020-26413 * GitLab SSRF漏洞 CVE-2021-22214 * GitLab 任意文件读取导致RCE CVE-2020-10977 * GitLab 任意文件读取漏洞 CVE-2016-9086 * GitLab 远程命令执行漏洞 CVE-2021-22205 * Gitlist 0.6.0 远程命令执行漏洞 CVE-2018-1000533 * GlassFish 任意文件读取漏洞 * GLPI htmLawedTest.php 远程命令执行漏洞 CVE-2022-35914 * Go-fastdfs GetClientIp 未授权访问漏洞 * Go-fastdfs upload 任意文件上传漏洞 CVE-2023-1800 * Gogs 任意用户登录漏洞 CVE-2018-18925 * Grafana mysql 后台任意文件读取漏洞 CVE-2019-19499 * Grafana plugins 任意文件读取漏洞 CVE-2021-43798 * Grafana管理后台SSRF * H3C IMC dynamiccontent.properties.xhtm 远程命令执行 * Harbor 公开镜像仓库未授权访问 CVE-2022-46463 * Harbor 未授权创建管理员漏洞 CVE-2019-16097 * HTTPoxy CGI 漏洞 CVE-2016-5385 * Hue 后台编辑器命令执行漏洞 * IBOS 数据库模块 后台任意文件上传漏洞 * ICEFlow VPN 信息泄露漏洞 * IceWarp WebClient basic 远程命令执行漏洞 * ImageMagick PDF密码位置命令注入漏洞 CVE-2020-29599 * ImageMagick 命令执行漏洞 CVE-2016–3714 * ImageMagick任意文件读取漏洞 CVE-2022-44268 * imo 云办公室 corpfile.php 远程命令执行漏洞 * imo 云办公室 get_file.php 远程命令执行漏洞 * imo 云办公室 Imo_DownLoadUI.php 任意文件下载漏洞 * JD-FreeFuck 后台命令执行漏洞 * Jeecg jeecgFormDemoController JNDI 代码执行漏洞 CVE-2023-49442 * Jeecg Boot SSTI CVE 2023 4450 * JeecgBoot 企业级低代码平台 qurestSql SQL注入漏洞 CVE-2023-1454 * Jellyfin RemoteImageController.cs SSRF漏洞 CVE-2021-29490 * Jellyfin 任意文件读取漏洞 CVE-2021-21402 * Jetbrains TeamCity 认证绕过导致远程命令执行漏洞 CVE-2023-42793 * JimuReport FreeMarker 服务端模板注入命令执行 CVE-2023-4450 * JumpServer 未授权接口 远程命令执行漏洞 * JumpServer 远程代码执行漏洞 CVE-2024-29201&CVE-2024-29202 * Jupyter Notebook 未授权访问远程命令执行漏洞 * Kibana 原型链污染导致任意代码执行漏洞 CVE-2019-7609 * Kibana 本地文件包含漏洞 CVE-2018-17246 * kkFileView getCorsFile 任意文件读取漏洞 CVE-2021-43734 * kkFileView ZipSlip 远程命令执行漏洞 * Konga 普通用户越权获取管理员权限漏洞 * KubeOperator kubeconfig 未授权访问漏洞 CVE-2023-22480 * KubePi JwtSigKey 登陆绕过漏洞 CVE-2023-22463 * KubePi LoginLogsSearch 未授权访问漏洞 CVE-2023-22478 * Lanproxy 目录遍历漏洞 CVE-2021-3019 * LimeSurvey LimeSurveyFileManager.php 后台任意文件读取漏洞 CVE-2020-11455 * LiveBOS ShowImage.do 任意文件读取漏洞 * Magento 2.2 SQL注入漏洞 * MessageSolution 邮件归档系统EEA 信息泄露漏洞 CNVD-2021-10543 * Metabase geojson 任意文件读取漏洞 CVE-2021-41277 * Metabase 未授权 JDBC 远程代码执行漏洞 CVE-2023-38646 * Metabase任意文件读取漏洞 CVE-2021-41277 * MeterSphere customMethod 远程命令执行漏洞 * Metersphere file 任意文件读取漏洞 CVE-2023-25573 * MeterSphere v1.15.4 认证用户SQL注入漏洞 CVE-2021-45788 * MeterSphere 插件接口未授权访问及远程代码执行 * MinIO 集群模式信息泄露漏洞 CVE-2023-28432 * MKdocs 任意文件读取漏洞 CVE-2021-40978 * MLflow get-artifact 任意文件读取漏洞 CVE-2023-1177 * Mojarra JSF ViewState 反序列化漏洞 * mongo-express 远程代码执行漏洞 CVE-2019-10758 * Nexus Repository Manager 3 extdirect 远程命令执行漏洞 CVE-2019-7238 * Nexus Repository Manager 3 extdirect 远程命令执行漏洞 CVE-2020-10204 * Nexus Repository Manager 3 group 远程命令执行漏洞 CVE-2020-10199 * Nexus Repository Manager 3 未授权目录穿越漏洞 CVE-2024-4956 * Nexus Repository Manger change-password 低权限修改管理员密码漏洞 CVE-2020-11444 * nginxWebUI cmdOver 后台命令执行漏洞 * nginxWebUI runCmd 远程命令执行漏洞 * node-postgres 代码执行漏洞 CVE-2017-16082 * Node-RED ui_base 任意文件读取漏洞 * NPS auth_key 未授权访问漏洞 * ntopng权限绕过漏洞 CVE-2021-28073 * OfficeWeb365 SaveDraw 任意文件上传漏洞 * OneBlog 小于v2.2.1 远程命令执行漏洞 * PDF.js 任意 JavaScript 代码执行 CVE-2024-4367 * pgAdmin ≤ 6.16 无授权远程命令执行漏洞 CVE-2022-4223 * pgAdmin ≤ 7.6 后台远程命令执行漏洞 CVE-2023-5002 * phpMyAdmin后台SQL注入 CVE-2020-26935 * PHPStudy 后台管理页面 one click RCE * PowerJob list 信息泄漏漏洞 CVE-2023-29923 * Richmail 企业邮箱 noCookiesMail 登陆绕过漏洞 * Riskscanner list SQL注入漏洞 * Rocket Chat MongoDB 注入漏洞 CVE-2021-22911 * Roxy-Wi options.py 远程命令执行漏洞 CVE-2022-31137 * Scrapyd 未授权访问漏洞 * Seo-Panel 4.8.0 反射型XSS漏洞 CVE-2021-3002 * ShopXO 任意文件读取漏洞 CNVD-2021-15822 * ShowDoc AdminUpdateController.class.php 任意文件上传漏洞 CVE-2021-36440 * ShowDoc PageController.class.php 任意文件上传漏洞 * ShowDoc 前台任意文件上传 CNVD-2020-26585 * ShowDoc 前台文件上传漏洞 * Smartbi RMIServlet 登陆绕过漏洞 * Smartbi 远程命令执行漏洞 * SolarView Compact 命令注入漏洞 CVE-2022-40881 * SonarQube search_projects 项目信息泄露漏洞 * SonarQube values 信息泄露漏洞 CVE-2020-27986 * SpiderFlow save 远程命令执行漏洞 * TamronOS IPTV系统 ping 任意命令执行漏洞 * TamronOS IPTV系统 submit 任意用户创建漏洞 * TerraMaster TOS createRaid 远程命令执行漏洞 CVE-2022-24989 * TerraMaster TOS exportUser.php 远程命令执行 * TerraMaster TOS makecvs.php 远程命令执行漏洞 CVE-2020-28188 * Terra Master TOS RCE CVE 2020 28188 * TerraMaster TOS 任意账号密码修改漏洞 CVE-2020-28186 * TerraMaster TOS 信息泄漏漏洞 CVE-2022-24990 * TerraMaster TOS 后台任意文件读取漏洞 CVE-2020-28187 * TerraMaster TOS 用户枚举漏洞 CVE-2020-28185 * Webgrind fileviewer.phtml 任意文件读取漏洞 CVE-2018-12909 * Webmin password_change.cgi 远程命令执行漏洞 CVE-2019-15107 * Webmin rpc.cgi 后台远程命令执行漏洞 CVE-2019-15642 * Webmin update.cgi 后台远程命令执行漏洞 CVE-2022-0824 * Webmin 多个高危漏洞 CVE-2021-31760~62 * Webmin 远程命令执行漏洞 CVE-2019-15107 * WiseGiga NAS down_data.php 任意文件下载漏洞 * WiseGiga NAS group.php 远程命令执行漏洞 * WSO2 fileupload 任意文件上传漏洞 CVE-2022-29464 * WSO2 proxy SSRF漏洞 WSO2-2019-0598 * XXL-JOB executor 未授权访问漏洞 * XXL-JOB 任务调度中心 后台任意命令执行漏洞 * YApi NoSQL注入导致远程命令执行漏洞 * YApi 接口管理平台 后台命令执行漏洞 * 七牛云 logkit log_path 任意文件读取漏洞 * 中新金盾信息安全管理系统 默认超级管理员密码漏洞 * 久其财务报表 download.jsp 任意文件读取漏洞 * 云时空 社会化商业ERP系统 Shiro框架 远程命令执行漏洞 * 云时空 社会化商业ERP系统 validateLoginName SQL注入漏洞 * 亿赛通 电子文档安全管理系统 dataimport 远程命令执行漏洞 * 亿赛通 电子文档安全管理系统 UploadFileFromClientServiceForClient 任意文件上传漏洞 * 亿邮电子邮件系统 moni_detail.do 远程命令执行漏洞 * 任我行 CRM SmsDataList SQL注入漏洞 * 任我行 管家婆 订货易在线商城 SelectImage.aspx 任意文件上传漏洞 * 企望制造 ERP comboxstore.action 远程命令执行漏洞 * 众望网络 微议管理系统 后台updatefile.html 任意文件上传漏洞 * 会捷通云视讯 fileDownload 任意文件读取漏洞 * 会捷通云视讯 list 目录文件泄露漏洞 * 会捷通云视讯 登录绕过漏洞 * 吉拉科技 LVS精益价值管理系统 Business 目录遍历漏洞 * 向日葵 check 远程命令执行漏洞 CNVD-2022-10270 * 员工管理系统 Employee Management System 1.0 身份验证绕过 * 和信创天云桌面系统 远程命令执行 RCE漏洞 * 图创软件 图书馆站群管理系统 任意文件读取漏洞 * 天融信 DLP 未授权访问漏洞 * 天融信 TopApp-LB enable_tool_debug.php 远程命令执行漏洞 * 天融信 TopApp-LB SQL注入漏洞 * 天融信 TopApp-LB 命令执行漏洞 * 天融信 TopApp-LB系统 任意登陆 * 孚盟云 AjaxMethod.ashx SQL注入漏洞 * 安天 高级可持续威胁安全检测系统 越权访问漏洞 * 安徽阳光心健 心理测量平台 目录遍历漏洞 CNVD-2021-01929 * 安美数字 酒店宽带运营系统 server_ping.php 远程命令执行漏洞 * 宏景 HCM codesettree SQL注入漏洞 CNVD-2023-0874 * 宝塔 phpmyadmin未授权访问漏洞 * 广联达 Linkworks GetIMDictionary SQL注入漏洞 * 广联达 Linkworks msgbroadcastuploadfile.aspx 后台文件上传漏洞 * 思迪数据 Home 登录绕过漏洞 * 拓尔思 TRS testCommandExecutor.jsp 远程命令执行漏洞 * 新开普 前置服务管理平台 service.action 远程命令执行漏洞 * 昆石网络 VOS3000虚拟运营支撑系统 %c0%ae%c0%ae 任意文件读取漏洞 * 明源云 ERP系统 接口管家 ApiUpdate.ashx 任意文件上传漏洞 * 智慧校园管理系统 前台任意文件上传漏洞 * 极通EWEBS casmain.xgi 任意文件读取漏洞 * 极通EWEBS testweb.php 敏感信息泄露漏洞 * 杭州法源软件 公证实务教学软件 SQL注入漏洞 * 杭州法源软件 法律知识数据库系统 后台XSS漏洞 * 汇文 图书馆书目检索系统 config.properties 信息泄漏漏洞 * 汉得SRM tomcat.jsp 登陆绕过漏洞 * 汉王人脸考勤管理系统 Check SQL注入漏洞 * 浪潮ClusterEngineV4.0 sysShell 任意命令执行漏洞 * 浪潮ClusterEngineV4.0 任意用户登录漏洞 * 浪潮ClusterEngineV4.0 远程命令执行漏洞 CVE-2020-21224 * 深信服 DC数据中心管理系统 sangforindex XML实体注入漏洞 * 深信服 EDR c.php 远程命令执行漏洞 CNVD-2020-46552 * 深信服 EDR 后台任意用户登陆漏洞 * 深信服 SG上网优化管理系统 catjs.php 任意文件读取漏洞 * 深信服 SSL VPN 客户端远程文件下载 * 深信服 应用交付报表系统 download.php 任意文件读取漏洞 * 深信服 应用交付管理系统 login 远程命令执行漏洞 * 深信服 应用交付管理系统 sys_user.conf 账号密码泄漏漏洞 * 深信服 日志中心 c.php 远程命令执行漏洞 * 深信服 行为感知系统 c.php 远程命令执行漏洞 * 瑞友 应用虚拟化系统 GetBSAppUrl SQL注入漏洞 * 瑞友天翼应用虚拟化系统 AgentBoard.XGI 远程代码执行漏洞 * 用友 畅捷通 T+ 前台远程命令执行漏洞 QVD-2023-13615 * 用友 畅捷通T+ DownloadProxy.aspx 任意文件读取漏洞 * 用友 畅捷通T+ GetStoreWarehouseByStore 远程命令执行漏洞 * 用友 畅捷通T+ RecoverPassword.aspx 管理员密码修改漏洞 * 用友 畅捷通T+ Upload.aspx 任意文件上传漏洞 * 用友 畅捷通远程通 GNRemote.dll SQL注入漏洞 * 畅捷CRM get_usedspace.php SQL注入漏洞 * 畅捷CRM 后台附件任意文件上传漏洞 * 科达 MTS转码服务器 任意文件读取漏洞 * 科达 网络键盘控制台 任意文件读取漏洞 * 科迈 RAS系统 硬编码管理员漏洞 * 紫光档案管理系统 editPass.html SQL注入漏洞 CNVD-2021-41638 * 紫光档案管理系统 upload.html 后台文件上传漏洞 * 绿盟 BAS日志数据安全性分析系统 accountmanage 未授权访问漏洞 * 绿盟 UTS综合威胁探针 信息泄露登陆绕过漏洞 * 网御星云 web防护系统 信息泄露漏洞 * 若依管理系统 Druid未授权访问 * 若依管理系统 后台任意文件读取 CNVD-2021-01931 * 蓝海卓越计费管理系统 debug.php 远程命令执行漏洞 * 蓝海卓越计费管理系统 download.php 任意文件读取漏洞 * 辰信领创 辰信景云终端安全管理系统 login SQL注入漏洞 * 金山 V8 V9 终端安全系统 文件上传漏洞 * 金山 V8 终端安全系统 downfile.php 任意文件读取漏洞 * 金山 V8 终端安全系统 get_file_content.php 任意文件读取漏洞 * 金山 V8 终端安全系统 pdf_maker.php 命令执行漏洞 * 金盘 微信管理平台 getsysteminfo 未授权访问漏洞 * 金笛 短信中间件Web版 log 后台任意文件下载漏洞 CNVD-2021-57336 * 金蝶 K3Cloud BinaryFormatter 反序列化漏洞 * 银澎云计算 好视通视频会议系统 任意文件下载 CNVD-2020-62437 * 银达汇智 智慧综合管理平台 FileDownLoad.aspx 任意文件读取漏洞 * 银达汇智 智慧综合管理平台 FileUp.aspx 任意文件上传漏洞 * 锐起云 resetPwd 登陆绕过漏洞 * 锐起云 xiazai 任意文件读取漏洞 * 阿尔法科技 虚拟仿真实验室 未授权访问漏洞 * 零视科技 H5S视频平台 GetUserInfo 信息泄漏漏洞 CNVD-2020-67113 * 霆智科技 VA虚拟应用平台 任意文件读取漏洞 * 章管家 Druid未授权访问漏洞 * 飞企互联 FE业务协作平台 ShowImageServlet 任意文件读取漏洞 * 飞视美 视频会议系统 Struts2 远程命令执行漏洞 * 魅课 OM视频会议系统 proxy.php 文件包含漏洞 * 默安 幻阵蜜罐未授权访问 RCE * 龙璟科技 电池能量BEMS downloads 任意文件下载漏洞 - 中间件漏洞 * ACME Mini_httpd 任意文件读取漏洞 CVE-2018-18778 * Adobe ColdFusion XML 反序列化命令执行漏洞 CVE-2023-29300 * Adobe ColdFusion 反序列化漏洞 CVE-2017-3066 * Adobe ColdFusion 文件读取漏洞 CVE-2010-2861 * Adobe ColdFusion 本地文件包含漏洞 CVE-2023-26360 * Apache ActiveMQ Console 控制台默认弱口令 * Apache ActiveMQ Jolokia 后台远程代码执行漏洞 CVE-2022-41678 * Apache ActiveMQ OpenWire 协议反序列化命令执行漏洞 CVE-2023-46604 * Apache ActiveMQ 任意文件写入漏洞 CVE-2016-3088 * Apache ActiveMQ 信息泄漏漏洞 CVE-2017-15709 * Apache ActiveMQ 反序列化漏洞 CVE-2015-5254 * Apache ActiveMQ 远程代码执行漏洞 CVE-2023-46604 * Apache Axis 远程代码执行漏洞 CVE-2019-0227 * Apache Cocoon XML注入 CVE-2020-11991 * Apache HTTP Server 2.4.48 mod_proxy SSRF漏洞 CVE-2021-40438 * Apache HTTP Server 2.4.49 路径穿越漏洞 CVE-2021-41773 * Apache HTTP Server 2.4.50 路径穿越漏洞 CVE-2021-42013 * Apache HTTPd 多后缀解析漏洞 * Apache HTTPd 换行解析漏洞 CVE-2017-15715 * Apache HTTPd 路径穿越漏洞 CVE-2021-41773 * Apache HTTPd 路径穿越漏洞 CVE-2021-42013 * Apache Kafka Clients LDAP注入漏洞 CVE-2023-25194 * Apache Kylin config 未授权配置泄露 CVE-2020-13937 * Apache Kylin CubeService.java 命令注入漏洞 CVE-2020-1956 * Apache Kylin DiagnosisController.java 命令注入漏洞 CVE-2020-13925 * Apache Log4j Server 反序列化命令执行漏洞 CVE-2017-5645 * Apache Log4j2 lookup JNDI 注入漏洞 CVE-2021-44228 * Apache Mod_jk 访问控制权限绕过 CVE-2018-11759 * Apache NiFi Api 远程代码执行 RCE * Apache RocketMQ RCE 漏洞 CVE-2023-33246 * Apache RocketMQ 远程代码执行漏洞 CVE-2023-37582 * Apache RocketMQ 远程命令执行漏洞 CVE-2023-33246 * Apache ShenYu dashboardUser 账号密码泄漏漏洞 CVE-2021-37580 * Apache Shiro 1.2.4 反序列化漏洞 CVE-2016-4437 * Apache Shiro 1.6.0 身份认证绕过漏洞 CVE-2020-13933 * Apache Shiro 认证绕过漏洞 CVE-2010-3863 * Apache Shiro 认证绕过漏洞 CVE-2020-1957 * Apache SkyWalking 7.0.0 graphql SQL注入漏洞 CVE-2020-9483 * Apache Skywalking 8.3.0 graphql SQL注入漏洞 * Apache Solr JMX服务 RCE CVE-2019-12409 * Apache Solr Log4j 组件 远程命令执行漏洞 * Apache Solr RCE 未授权上传漏洞 CVE-2020-13957 * Apache Solr RCE 远程命令执行漏洞 CVE-2017-12629 * Apache Solr RemoteStreaming 文件读取与SSRF漏洞 * Apache Solr Replication Handler SSRF CVE 2021 27905 * Apache Solr stream.url 任意文件读取漏洞 * Apache Solr Velocity 注入远程命令执行漏洞 CVE-2019-17558 * Apache Solr XML 实体注入漏洞 CVE-2017-12629 * Apache Solr 代码执行漏洞 CNVD-2023-27598 * Apache Solr 远程命令执行漏洞 CVE-2017-12629 * Apache Solr 远程命令执行漏洞 CVE-2019-0193 * Apache Solr 远程执行漏洞 CVE-2019-0193 * Apache SSI 远程命令执行漏洞 * Apache Tomcat AJP 文件包含漏洞 CVE-2020-1938 * Apache Tomcat PUT方法任意写文件漏洞 CVE-2017-12615 * Apache Tomcat RCE Via JSP Upload Bypass * Apache Tomcat WebSocket 拒绝服务漏洞 CVE-2020-13935 * Apache Tomcat 信息泄露漏洞 CVE-2021-24122 * Apache Tomcat 远程代码执行漏洞 CVE-2017-12615 * Apache Tomcat8 弱口令+后台getshell漏洞 * Apache Velocity 远程代码执行 CVE-2020-13936 * Apache ZooKeeper 未授权访问漏洞 CVE-2014-085 * Apereo CAS 4.1 反序列化命令执行漏洞 * AppWeb认证绕过漏洞 CVE-2018-8715 * Consul Docker images 空密码登录漏洞 CVE-2020-29564 * Consul Service API远程命令执行漏洞 * GeoServer OGC Filter SQL注入漏洞 CVE-2023-25157 * GoAhead Server 环境变量注入 CVE-2021-42342 * GoAhead Server 远程命令执行漏洞 CVE-2017-17562 * GoCD plugin 任意文件读取漏洞 CVE-2021-43287 * JBoss 4.x JBossMQ JMS 反序列化漏洞 CVE-2017-7504 * JBoss 5.x6.x 反序列化漏洞 CVE-2017-12149 * JBoss JMXInvokerServlet 反序列化漏洞 CVE-2015-7501 * Jenkins checkScript 远程命令执行漏洞 CVE-2018-1000861 * Jenkins CLI 接口任意文件读取漏洞 CVE-2024-23897 * Jenkins script 未授权远程命令执行漏洞 * Jenkins XStream 反序列化漏洞 CVE-2016-0792 * Jenkins 远程代码执行漏洞 CVE-2015-8103 * Jenkins 远程代码执行漏洞 CVE-2019-1003000 * Jenkins 远程命令执行漏洞 CVE-2018-1000861 * Jenkins-CI 远程代码执行漏洞 CVE-2017-1000353 * Jetty WEB-INF 敏感信息泄露漏洞 CVE-2021-28164 * Jetty WEB-INF 敏感信息泄露漏洞 CVE-2021-34429 * Jetty 通用 Servlets 组件 ConcatServlet 信息泄露漏洞 CVE-2021-28169 * Jmeter RMI 反序列化命令执行漏洞 CVE-2018-1297 * muhttpd 任意文件读取漏洞 CVE-2022-31793 * Nginx 文件名逻辑漏洞 CVE-2013-4547 * Nginx 解析漏洞 * Nginx 配置错误漏洞 * Nginx越界读取缓存漏洞 CVE-2017-7529 * Node.js 目录穿越漏洞 CVE-2017-14849 * Openfire管理后台认证绕过漏洞 CVE-2023-32315 * OpenSMTPD 远程命令执行漏洞 CVE-2020-7247 * OpenSSH 命令注入漏洞 CVE-2020-15778 * OpenSSH 用户名枚举漏洞 CVE-2018-15473 * OpenSSL 心脏出血漏洞 CVE-2014-0160 * OpenSSL 心脏滴血漏洞 CVE-2014-0160 * PayaraMicro microprofile-config.properties 信息泄漏漏洞 CVE-2021-41381 * QEMU 虚拟机逃逸漏洞 CVE-2020-14364 * Rsync 未授权访问漏洞 * Ruby NetFTP 模块命令注入漏洞 CVE-2017-17405 * Ruby On Rails 路径穿越与任意文件读取漏洞 CVE-2019-5418 * Ruby On Rails 路径穿越漏洞 CVE-2018-3760 * SaltStack Minion 命令注入漏洞 CVE-2021-31607 * SaltStack 任意文件读写漏洞 CVE-2020-11652 * SaltStack 命令注入漏洞 CVE-2020-16846 * Saltstack 未授权RCE漏洞 CVE-2021-25281~25283 * SaltStack 未授权访问命令执行漏洞 CVE-2020-16846 25592 * SaltStack 水平权限绕过漏洞 CVE-2020-11651 * Saltstack 远程命令执行漏洞 CVE-2020-11651 11652 * Struts2 S2-001 远程代码执行漏洞 * Struts2 S2-005 远程代码执行漏洞 * Struts2 S2-007 远程代码执行漏洞 * Struts2 S2-008 远程代码执行漏洞 * Struts2 S2-009 远程代码执行漏洞 * Struts2 S2-012 远程代码执行漏洞 * Struts2 S2-013 远程代码执行漏洞 * Struts2 S2-015 远程代码执行漏洞 * Struts2 S2-016 远程代码执行漏洞 CVE-2013-2251 * Struts2 S2-032 远程代码执行漏洞 CVE-2016-3081 * Struts2 S2-045 远程代码执行漏洞 CVE-2017-5638 * Struts2 S2-046 远程代码执行漏洞 CVE-2017-5638 * Struts2 S2-048 远程代码执行漏洞 * Struts2 S2-052 远程代码执行漏洞 CVE-2017-9805 * Struts2 S2-053 远程代码执行漏洞 * Struts2 S2-057 远程代码执行漏洞 CVE-2018-11776 * Struts2 S2-059 远程代码执行漏洞 CVE-2019-0230 * Struts2 S2-061 远程代码执行漏洞 CVE-2020-17530 * Struts2 S2-062 远程代码执行漏洞 CVE-2021-31805 * Supervisord 远程命令执行漏洞 CVE-2017-11610 * Tomcat PUT方法任意写文件漏洞 CVE-2017-12615 * Tomcat8 弱口令+后台getshell漏洞 * uWSGI PHP目录穿越漏洞 CVE-2018-7490 * uWSGI 未授权访问漏洞 * V2board 1.6.1 提权漏洞 * VMware Spring Security 身份认证绕过漏洞 CVE-2022-22978 * VMware View Planner 未授权RCE CVE-2021-21978 * VMware vRealize Operations Manager SSRF漏洞 CVE-2021-21975 * VMware Workspace ONE Access SSTI漏洞 CVE-2022-22954 * VoIPmonitor 远程命令执行漏洞 CVE-2021-30461 * Wazuh Manager 代码执行漏洞 CVE-2021-26814 * Weblogic 10.3.6 wls-wsat XMLDecoder 反序列化漏洞 CVE-2017-10271 * Weblogic LDAP 远程代码执行漏洞 CVE-2021-2109 * WebLogic Local File Inclusion 本地文件包含漏洞 CVE-2022-21371 * Weblogic Server远程代码执行漏洞 CVE-2020-14756 * WebLogic T3 反序列化漏洞 CVE-2016-3510 * Weblogic uddiexplorer SSRF漏洞 CVE-2014-4210 * Weblogic WLS Core Components 反序列化命令执行漏洞 CVE-2018-2628 * Weblogic XMLDecoder 反序列化远程代码执行漏洞 CVE-2019-2725 * Weblogic XMLDecoder 远程代码执行漏洞 CVE-2017-10271 * Weblogic 二次反序列化漏洞 CVE-2021-2394 * Weblogic 任意文件上传漏洞 CVE-2018-2894 * Weblogic 弱口令+前台任意文件读取 * Weblogic 未授权远程代码执行漏洞 CVE-2023-21839 * Weblogic 管理控制台未授权远程命令执行漏洞 CVE-2020-14882+CVE-2020-14883 * Zabbix latest.php SQL注入漏洞 CVE-2016-10134 * Zabbix SAML身份绕过漏洞 CVE-2022-23131 * Zabbix Server trapper命令注入漏洞 CVE-2017-2824 * Zabbix Server trapper命令注入漏洞 CVE-2020-11800 - 云安全漏洞 * Docker daemon api 未授权访问漏洞 RCE * K8s API Server未授权命令执行 * K8s etcd未授权访问 * MinIO SSRF 漏洞 CVE-2021-21287 * Nacos secret.key 默认密钥 未授权访问漏洞 * Nacos 未授权访问漏洞 * Nacos 认证绕过漏洞 CVE-2021-29441 * Nacos 集群 Raft 反序列化漏洞 CNVD-2023-45001 * VMware vCenter Server 任意文件上传漏洞 CVE-2021-22005 * VMware vCenter Server 任意文件读取漏洞 * VMware vCenter Server 服务器端请求伪造漏洞 CVE-2021-21973 * VMware vCenter Server 远程代码执行漏洞 CVE-2021-21972 - 其他漏洞 * DNS域传送漏洞 * Foxit PDF Reader 及 Editor 任意代码执行漏洞 CVE-2023-27363 * Git for Visual Studio远程执行代码漏洞 CVE-2021-21300 * Git-LFS 远程命令执行漏洞 CVE-2020-27955 * GIT-SHELL 沙盒绕过 CVE-2017-8386 * librsvg XInclude 文件包含漏洞 CVE-2023-38633 * Libssh 服务端权限认证绕过漏洞 CVE-2018-10933 * Microsoft Exchange Server 远程执行代码漏洞 CVE-2020-17083 * Microsoft Exchange SSRF漏洞 CVE-2021-26885 * Microsoft Exchange 信息泄露漏洞 CVE-2020-17143 * Microsoft Exchange 远程命令执行 CVE-2021-27065 26857 26858 * Microsoft Outlook 权限提升漏洞 CVE-2023-23397 * Microsoft Word 远程代码执行漏洞 CVE-2023-21716 * NVIDIA GPU显示驱动程序 信息泄露 CVE-2021-1056 * Samba 远程命令执行漏洞 CVE-2017-7494 * Ueditor 编辑器漏洞总结 * Windows Chrome 远程命令执行漏洞 * 微信客户端 远程命令执行漏洞 * 腾讯 企业微信 agentinfo 信息泄漏漏洞 - 开发框架漏洞 * Apache Commons Configuration 远程命令执行漏洞 CVE-2022-33980 * Apache Commons Text 远程代码执行漏洞 CVE-2022-42889 * Apache Dubbo Java反序列化漏洞 CVE-2019-17564 * Apache Flink 小于1.9.1远程代码执行 CVE-2020-17518 * Apache Flink 目录遍历漏洞 CVE-2020-17519 * Apache OF Biz RMI Bypass RCE CVE 2021 29200 * Apache OFBiz RMI反序列化漏洞 CVE-2021-26295 * Apache OFBiz 反序列化 CVE-2021-30128 * Apache OfBiz 反序列化命令执行漏洞 CVE-2020-9496 * Apache OfBiz 反序列化命令执行漏洞 CVE-2023-49070 * Apache OfBiz 服务器端模板注入 SSTI * Apache OFBiz 目录遍历致代码执行漏洞 CVE-2024-36104 * Apache OfBiz 远程代码执行 RCE * Apache OfBiz 鉴权绕过导致命令执行 CVE-2023-51467 * Apache Spark create 未授权访问漏洞 * Apache Spark doAs 远程命令执行漏洞 CVE-2022-33891 * Apache Spark unTarUsingTar 命令注入漏洞 SPARK-38631 * Django 2.0.8 任意URL跳转漏洞 CVE-2018-14574 * Django debug page XSS漏洞 CVE-2017-12794 * Django GIS SQL注入漏洞 CVE-2020-9402 * Django JSONField HStoreField SQL注入漏洞 CVE-2019-14234 * Django QuerySet.order_by() SQL注入漏洞 CVE-2021-35042 * Django Trunc(kind) and Extract(lookup_name) SQL注入漏洞 CVE-2022-34265 * FastAdmin 远程代码执行漏洞 * Fastjson 1.2.24 反序列化导致任意命令执行漏洞 * Fastjson 1.2.47 远程命令执行漏洞 * Fastjson 远程代码执行漏洞 CVE-2022-25845 * Flask Jinja2 服务端模板注入漏洞 * Jackson Databind SSRF RCE CVE 2020 36179 36182 * Jackson-databind 反序列化漏洞 CVE-2017-7525+CVE-2017-17485 * Jackson-databind远程代码执行 CVE-2019-12384 * jQuery XSS漏洞 CVE-2020-11022 11023 * Laravel .env 配置文件泄露 CVE-2017-16894 * Laravel Filemanager插件 download 任意文件读取漏洞 CVE-2022-40734 * Laravel Ignition 2.5.1 代码执行漏洞 CVE-2021-3129 * Laravel 小于 8.4.2 Debug模式 _ignition 远程代码执行漏洞 CVE-2021-3129 * MotionEye 视频监控组件 list 信息泄漏洞 CVE-2022-25568 * PHPUnit eval-stdin.php 远程命令执行漏洞 CVE-2017-9841 * Rails Accept 任意文件读取漏洞 CVE-2019-5418 * Rails sprockets 任意文件读取漏洞 CVE-2018-3760 * Spring Boot 目录遍历 CVE-2021-21234 * Spring Cloud Config 目录遍历漏洞 CVE-2019-3799 * Spring Cloud Function SPEL 远程命令执行漏洞 * Spring Cloud Function SpEL表达式命令注入 CVE-2022-22963 * Spring Cloud Gateway Actuator API SpEL表达式注入命令执行 CVE-2022-22947 * Spring Data Binding与JDK 9+导致的远程代码执行漏洞 CVE-2022-22965 * Spring Data Commons 远程命令执行漏洞 CVE-2018-1273 * Spring Data Rest 远程命令执行漏洞 CVE-2017-8046 * Spring Framework 安全绕过漏洞 CVE-2023-20860 * Spring Messaging 远程命令执行漏洞 CVE-2018-1270 * Spring Security OAuth2 远程命令执行漏洞 CVE-2016-4977 * Spring WebFlow 远程代码执行漏洞 CVE-2017-4971 * ThinkPHP 2.x 任意代码执行漏洞 * ThinkPHP 命令执行漏洞 CNVD-2022-86535 * ThinkPHP 多语言本地文件包含漏洞 * ThinkPHP5 5.0.22 5.1.29 远程代码执行漏洞 * ThinkPHP5 5.0.23 远程代码执行漏洞 * ThinkPHP5 SQL注入漏洞 && 敏感信息泄露 * XStream SSRF 反序列化漏洞 CVE-2020-26258 * XStream 任意文件删除 反序列化漏洞 CVE-2020-26259 * XStream 反序列化命令执行漏洞 CVE-2021-21351 * XStream 反序列化命令执行漏洞 CVE-2021-29505 - 开发语言漏洞 * Java RMI Registry 反序列化漏洞(=jdk8u111) * Java RMI Registry 反序列化漏洞(jdk8u232_b09) * JDWP 调试接口 RCE 漏洞 * PHP 8.1.0-dev 开发版本 zerodium 后门漏洞 * PHP CGI Windows 平台远程代码执行漏洞 CVE-2024-4577 * PHP imap 远程命令执行漏洞 CVE-2018-19518 * PHP XDebug 远程调试模式导致代码执行 * PHP 利用 GNU C Iconv 将文件读取提升至 RCE CVE-2024-2961 * PHP 利用 phpinfo 包含临时文件 getshell * PHP 环境 XML外部实体注入漏洞（XXE） * PHP-FPM Fastcgi 未授权访问漏洞 * PHP-FPM 远程代码执行漏洞 CVE-2019-11043 * Python PIL 远程命令执行漏洞 CVE-2017-8291 * Python PIL 远程命令执行漏洞 CVE-2018-16509 * Python pip install RCE 漏洞 CVE-2013-1629 * Python unpickle 造成任意命令执行漏洞 - 操作系统漏洞 * Linux DirtyPipe 权限提升漏洞 CVE-2022-0847 * Linux eBPF 权限提升漏洞 CVE-2022-23222 * Linux kernel 权限提升漏洞 CVE-2021-3493 * Linux openvswitch 权限提升漏洞 CVE-2022-2639 * Linux Polkit 权限提升漏洞 CVE-2021-4034 * Linux sudo 权限提升漏洞 CVE-2021-3156 * Linux sudo 权限提升漏洞 CVE-2023-22809 * Shellshock 破壳漏洞 CVE-2014-6271 * Windows CryptoAPI 欺骗漏洞 CVE-2020-0601 * Windows SMB 远程代码执行漏洞 CVE-2020-0796 * Windows Win32k 内核提权漏洞 CVE-2022-21882 * Windows Win32k 本地提权漏洞 CVE-2021-1732 * Windows 远程桌面服务漏洞 CVE-2019-0708 - 数据库漏洞 * Apache CouchDB epmd 远程命令执行漏洞 CVE-2022-24706 * Apache CouchDB 任意命令执行漏洞 CVE-2017-12636 * Apache CouchDB 分布式协议代码执行 CVE-2022-24706 * Apache CouchDB 垂直权限绕过漏洞 CVE-2017-12635 * Apache Druid LoadData 任意文件读取漏洞 CVE-2021-36749 * Apache Druid 代码执行漏洞 CVE-2021-25646 * Apache Druid 远程代码执行漏洞 CVE-2021-25646 * Apache Druid 远程代码执行漏洞 CVE-2021-26919 * Apache Druid 远程代码执行漏洞 QVD-2023-9629 * ClickHouse API 数据库接口未授权访问漏洞 * ElasticSearch Groovy 沙盒绕过 & 代码执行漏洞 CVE-2015-1427 * Elasticsearch 未授权访问 * ElasticSearch 目录穿越漏洞 CVE-2015-3337 * H2 Database Console 未授权访问 * Hadoop YARN ResourceManager 未授权访问 * InfluxDB JWT 认证绕过漏洞 CVE-2019-20933 * InfluxDB 未授权访问漏洞 * MySQL UDF 提权漏洞 * MySQL 身份认证绕过漏洞 CVE-2012-2122 * Neo4j Shell Server 反序列化漏洞 CVE-2021-34371 * OpenTSDB 命令注入漏洞 CVE-2020-35476 * OpenTSDB 命令注入漏洞 CVE-2023-25826 * PostgreSQL 提权漏洞 CVE-2018-1058 * PostgreSQL 高权限命令执行漏洞 CVE-2019-9193 * Redis 4.x5.x 未授权访问漏洞 * Redis Lua 沙盒绕过命令执行 CVE-2022-0543 * Redis 小于5.0.5 主从复制 RCE - 网络设备漏洞 * ACTI 视频监控 images 任意文件读取漏洞 * Amcrest IP Camera Web Sha1Account1 账号密码泄漏漏洞 CVE-2017-8229 * Apache APISIX Dashboard API权限绕过导致RCE CVE-2021-45232 * Apache APISIX 默认密钥漏洞 CVE-2020-13945 * Arcadyan固件 cgi_i_filter.js 配置信息泄漏漏洞 CVE-2021-20092 * Arcadyan固件 image 路径遍历漏洞 CVE-2021-20090 * AVEVA InTouch安全网关 AccessAnywhere 任意文件读取漏洞 CVE-2022-23854 * C-Lodop打印机任意文件读取漏洞 * Cisco ASA设备 任意文件读取漏洞 CVE-2020-3452 * Cisco ASA设备任意文件删除漏洞 CVE-2020-3187 * Cisco HyperFlex HX storfs-asup 远程命令执行漏洞 CVE-2021-1497 * Cisco HyperFlex HX upload 任意文件上传漏洞 CVE-2021-1499 * Citrix NetScaler ADC & Gateway 信息泄露漏洞 CVE-2023-4966 * Citrix 远程命令执行漏洞 CVE-2019-19781 * Crestron aj.html 账号密码泄漏漏洞 CVE-2022-23178 * D-Link AC管理系统 默认账号密码 * D-Link DAP-2020 webproc 任意文件读取漏洞 CVE-2021-27250 * D-Link DAR-8000 importhtml.php 远程命令执行漏洞 * D-Link DCS系列监控 账号密码信息泄露漏洞 CVE-2020-25078 * D-Link DIR-645 getcfg.php 账号密码泄露漏洞 CVE-2019-17506 * D-Link DIR-802 命令注入漏洞 CVE-2021-29379 * D-Link DIR-841 命令注入漏洞 CVE-2021-28143 * D-Link DIR-846 命令注入漏洞 CVE-2020-27600 * D-Link DSL-28881A FTP配置错误 CVE-2020-24578 * D-Link DSL-28881A 信息泄露 CVE-2020-24577 * D-Link DSL-28881A 未授权访问 CVE-2020-24579 * D-Link DSL-28881A 远程命令执行 CVE-2020-24581 * D-Link DSR-250N 万能密码漏洞 * D-Link ShareCenter DNS-320 system_mgr.cgi 远程命令执行漏洞 * DD-WRT UPNP缓冲区溢出漏洞 CVE-2021-27137 * DrayTek企业网络设备 远程命令执行 CVE-2020-8515 * DVR 登录绕过漏洞 CVE-2018-9995 * Finetree 5MP 摄像机 user_pop.php 任意用户添加漏洞 CNVD-2021-42372 * FLIR-AX8 download.php 任意文件下载 * FLIR-AX8 res.php 后台命令执行漏洞 * Fortinet FortiOS admin 远程命令执行漏洞 CVE-2022-40684 * H3C SecParh堡垒机 data_provider.php 远程命令执行漏洞 * H3C SecParh堡垒机 get_detail_view.php 任意用户登录漏洞 * H3C SecPath下一代防火墙 任意文件下载漏洞 * H3C 企业路由器（ER、ERG2、GR系列）任意用户登录漏洞 * HIKVISION DSIDSIPC 等设备 远程命令执行漏洞 CVE-2021-36260 * HIKVISION iVMS-8700综合安防管理平台 download 任意文件下载漏洞 * HIKVISION iVMS-8700综合安防管理平台 upload.action 任意文件上传漏洞 * HIKVISION 流媒体管理服务器 user.xml 账号密码泄漏漏洞 * HIKVISION 流媒体管理服务器 后台任意文件读取漏洞 CNVD-2021-14544 * HIKVISION 视频编码设备接入网关 $DATA 任意文件读取 * HIKVISION 视频编码设备接入网关 showFile.php 任意文件下载漏洞 * HIKVISION 综合安防管理平台 applyCT Fastjson远程命令执行漏洞 * HIKVISION 综合安防管理平台 env 信息泄漏漏洞 * HIKVISION 综合安防管理平台 files 任意文件上传漏洞 * HIKVISION 综合安防管理平台 report 任意文件上传漏洞 * HIKVISION 联网网关 downdb.php 任意文件读取漏洞 * Huawei DG8045 deviceinfo 信息泄漏漏洞 * Huawei HG659 lib 任意文件读取漏洞 * iKuai 后台任意文件读取漏洞 * iKuai 流控路由 SQL注入漏洞 * Intelbras Wireless 未授权与密码泄露 CVE-2021-3017 * JCG JHR-N835R 后台命令执行漏洞 * JumpServer 远程命令执行漏洞 * JumpServer 随机数种子泄露导致账户劫持漏洞 CVE-2023-42820 * KEDACOM 数字系统接入网关 任意文件读取漏洞 * KONE 通力电梯管理系统 app_show_log_lines.php 任意文件读取漏洞 * Kyan 网络监控设备 hosts 账号密码泄露漏洞 * Kyan 网络监控设备 license.php 远程命令执行漏洞 * Kyan 网络监控设备 module.php 远程命令执行漏洞 * Kyan 网络监控设备 run.php 远程命令执行漏洞 * Kyan 网络监控设备 time.php 远程命令执行漏洞 * MagicFlow 防火墙网关 main.xp 任意文件读取漏洞 * Milesight Router httpd.log 信息泄漏漏洞 CVE-2023-4714 * Milesight VPN server.js 任意文件读取漏洞 * MSA 互联网管理网关 msa 任意文件下载漏洞 * NetMizer 日志管理系统 cmd.php 远程命令执行漏洞 * NetMizer 日志管理系统 data 目录遍历漏洞 * NetMizer 日志管理系统 登录绕过漏洞 * Panabit iXCache date_config 后台命令执行漏洞 * Panabit Panalog sy_addmount.php 远程命令执行漏洞 * rConfig ajaxArchiveFiles.php 后台远程命令执行漏洞 * rConfig ajaxEditTemplate.php 后台远程命令执行漏洞 * rConfig useradmin.inc.php 信息泄露漏洞 * rConfig userprocess.php 任意用户创建漏洞 * Sapido 多款路由器 远程命令执行漏洞 * Selea OCR-ANPR摄像机 get_file.php 任意文件读取漏洞 * Selea OCR-ANPR摄像机 SeleaCamera 任意文件读取漏洞 * SonicWall SSL-VPN 远程命令执行漏洞 * Teleport堡垒机 do-login 任意用户登录漏洞 * Teleport堡垒机 get-file 后台任意文件读取漏洞 * Tenda 11N无线路由器 Cookie 越权访问漏洞 * Tenda W15E企业级路由器 RouterCfm.cfg 配置文件泄漏漏洞 * TG8 防火墙 RCE及密码泄漏漏洞 * TOTOLink 多个设备 download.cgi 远程命令执行漏洞 CVE-2022-25084 * TP-Link AC1750 预认证远程代码执行漏洞 CVE-2021-27246 * TP-Link SR20 远程命令执行 * TP-Link TL-WR841N 远程代码执行漏洞 CVE-2020-35576 * TVT数码科技 NVMS-1000 路径遍历漏洞 * Wayos AC集中管理系统默认弱口令 CNVD-2021-00876 * Wayos 防火墙 后台命令执行漏洞 * Wayos 防火墙 账号密码泄露漏洞 * XAMPP phpinfo.php 信息泄漏漏洞 * ZeroShell 3.9.0 远程命令执行漏洞 CVE-2019-12725 * Zyxel NBG2105 身份验证绕过 CVE-2021-3297 * Zyxel 硬编码后门账户漏洞 CVE-2020-29583 * 三星 WLAN AP WEA453e路由器 远程命令执行漏洞 * 三汇SMG 网关管理软件 down.php 任意文件读取漏洞 * 中国移动 禹路由 ExportSettings.sh 敏感信息泄露漏洞 CNVD-2020-67110 * 中国移动 禹路由 simple-index.asp 越权访问漏洞 CNVD-2020-55983 * 中科网威 NPFW防火墙 CommandsPolling.php 任意文件读取漏洞 * 中科网威 下一代防火墙控制系统 download.php 任意文件读取漏洞 * 中科网威 下一代防火墙控制系统 账号密码泄露漏洞 * 中远麒麟 iAudit堡垒机 get_luser_by_sshport.php 远程命令执行漏洞 * 佑友防火墙 后台命令执行漏洞 * 信诺瑞得 WiseGrid慧敏应用交付网关 sysadmin_action.php 后台命令执行漏洞 * 华夏创新 LotWan广域网优化系统 check_instance_state.php 远程命令执行漏洞 * 华夏创新 LotWan广域网优化系统 static_arp_del.php SQL注入漏洞 * 华夏创新 LotWan广域网优化系统 static_arp.php 远程命令执行漏洞 * 华硕 GT-AC2900 身份验证绕过 CVE-2021-32030 * 博华网龙防火墙 cmd.php 远程命令执行漏洞 * 博华网龙防火墙 users.xml 未授权访问 * 启明星辰 4A统一安全管控平台 getMaster.do 信息泄漏漏洞 * 启明星辰 天清汉马USG防火墙 逻辑缺陷漏洞 CNVD-2021-12793 * 启明星辰 天清汉马USG防火墙 默认口令漏洞 * 大华 ICC智能物联综合管理平台 readPic 任意文件读取漏洞 * 大华 城市安防监控系统平台管理 attachment_downloadByUrlAtt.action 任意文件下载漏洞 * 大华 智慧园区综合管理平台 getFaceCapture SQL注入漏洞 * 大华 智慧园区综合管理平台 user_getUserInfoByUserName.action 账号密码泄漏漏洞 * 大华 智慧园区综合管理平台 user_save.action 任意文件上传漏洞 * 大华 智慧园区综合管理平台 video 任意文件上传漏洞 * 奇安信 网康 NS-ASG安全网关 cert_download.php 任意文件读取漏洞 * 奇安信 网康 下一代防火墙 router 远程命令执行漏洞 * 安恒 明御WEB应用防火墙 report.php 任意用户登录漏洞 * 安恒 明御安全网关 aaa_portal_auth_local_submit 远程命令执行漏洞 * 安恒 明御安全网关 命令执行 任意文件读取漏洞 * 安恒 明御运维审计与风险控制系统 xmlrpc.sock 任意用户添加漏洞 * 宏电 H8922 Telnet后门漏洞 CVE-2021-28149 * 宏电 H8922 后台任意文件读取漏洞 CVE-2021-28152 * 宏电 H8922 后台命令执行漏洞 CVE-2021-28150 * 宏电 H8922 后台管理员信息泄露漏洞 CVE-2021-28151 * 小米 路由器 c_upload 远程命令执行漏洞 CVE-2019-18370 * 小米 路由器 extdisks 任意文件读取漏洞 CVE-2019-18371 * 思福迪 运维安全管理系统 test_qrcode_b 远程命令执行漏洞 * 思福迪堡垒机 任意用户登录漏洞 * 悦泰节能 智能数据网关 resources 任意文件读取漏洞 * 惠尔顿 e地通 config.xml 信息泄漏漏洞 * 才茂通信 网关 formping 远程命令执行漏洞 * 朗视 TG400 GSM 网关目录遍历 CVE-2021-27328 * 浙江宇视科技 网络视频录像机 ISC LogReport.php 远程命令执行漏洞 * 深信服 NGAF下一代防火墙 loadfile.php 任意文件读取漏洞 * 深信服 NGAF下一代防火墙 login.cgi 远程命令执行漏洞 * 烽火 HG6245D info.asp 信息泄露漏洞 * 电信 中兴ZXHN F450A网关 默认管理员账号密码漏洞 * 电信 天翼网关F460 web_shell_cmd.gch 远程命令执行漏洞 * 电信 网关配置管理系统 login.php SQL注入漏洞 * 百为通达 智能流控路由器 open 远程命令执行漏洞 * 百卓 Patflow showuser.php 后台SQL注入漏洞 * 百卓 Smart importhtml.php 远程命令执行漏洞 * 皓峰防火墙 setdomain.php 越权访问漏洞 * 碧海威 L7多款产品 后台命令执行漏洞 * 磊科 NI360路由器 认证绕过漏洞 * 绿盟 NF下一代防火墙 任意文件上传漏洞 * 绿盟 SAS堡垒机 Exec 远程命令执行漏洞 * 绿盟 SAS堡垒机 GetFile 任意文件读取漏洞 * 绿盟 SAS堡垒机 local_user.php 任意用户登录漏洞 * 网康 NS-ASG安全网关 cert_download.php 任意文件读取漏洞 * 网康 NS-ASG安全网关 index.php 远程命令执行漏洞 * 网康 下一代防火墙 HeartBeat.php 远程命令执行漏洞 * 网康 下一代防火墙 router 远程命令执行漏洞 * 网御 ACM上网行为管理系统 bottomframe.cgi SQL注入漏洞 * 网御 Leadsec ACM管理平台 importhtml.php 远程命令执行漏洞 * 网神 SecGate 3600 防火墙 obj_app_upfile 任意文件上传漏洞 * 网神 SecIPS 3600 debug_info_export 任意文件下载漏洞 * 网神 下一代极速防火墙 pki_file_download 任意文件读取漏洞 * 联软安界 UniSDP 软件定义边界系统 commondRetSt 命令执行漏洞 * 腾达 路由器 AC11 堆栈缓冲区溢出 CVE-2021-31758 * 腾达 路由器 D151D31未经身份验证的配置下载 * 蜂网互联 企业级路由器v4.31 密码泄露漏洞 CVE-2019-16313 * 西迪特 Wi-Fi Web管理 Cookie 越权访问漏洞 * 西迪特 Wi-Fi Web管理 jumpto.php 后台命令执行漏洞 * 迈普 ISG1000安全网关 任意文件下载漏洞 * 金山 VGM防毒墙 downFile.php 任意文件读取漏洞 * 锐捷 BCR商业无线云网关 后台命令执行漏洞 * 锐捷 EG易网关 branch_passw.php 远程命令执行 * 锐捷 EG易网关 cli.php 远程命令执行漏洞 * 锐捷 EG易网关 download.php 任意文件读取漏洞 * 锐捷 EG易网关 phpinfo.view.php 信息泄露漏洞 * 锐捷 EG易网关 管理员账号密码泄露漏洞 * 锐捷 ISG 账号密码泄露漏洞 * 锐捷 NBR 1300G路由器 越权CLI命令执行漏洞 * 锐捷 NBR 路由器 fileupload.php 任意文件上传漏洞 * 锐捷 NBR路由器 远程命令执行漏洞 CNVD-2021-09650 * 锐捷 RG-UAC 账号密码信息泄露 CNVD-2021-14536 * 锐捷 Smartweb管理系统 密码信息泄露漏洞 CNVD-2021-17369 * 锐捷 SSL VPN 越权访问漏洞 * 锐捷 云课堂主机 pool 目录遍历漏洞 * 锐捷 校园网自助服务系统 login_judge.jsf 任意文件读取漏洞 * 飞鱼星 企业级智能上网行为管理系统 权限绕过信息泄露漏洞 * 飞鱼星 家用智能路由 cookie.cgi 权限绕过 * 齐治堡垒机 gui_detail_view.php 任意用户登录漏洞 ## 0x02 声明 本项目收集漏洞均源于互联网： - Peiqi：https://github.com/PeiQi0/PeiQi-WIKI-Book - Vulhub：https://github.com/vulhub/vulhub ## 0x03 更新日志 - 2023.04.01 重构目录，合并 [Vulhub-Reproduce](https://github.com/Threekiii/Vulhub-Reproduce) 与本仓库 - 2022.12.05 图片本地化

一个漏洞POC知识库 目前数量 1000+

poc

Fallenbagel/jellyseerr

<p align="center"> <img src="./public/logo_full.svg" alt="Jellyseerr" style="margin: 20px 0;"> </p> <p align="center"> <img src="https://github.com/Fallenbagel/jellyseerr/actions/workflows/release.yml/badge.svg" alt="Jellyseerr Release" /> <img src="https://github.com/Fallenbagel/jellyseerr/actions/workflows/ci.yml/badge.svg" alt="Jellyseerr CI"> </p> <p align="center"> <a href="https://discord.gg/ckbvBtDJgC"><img src="https://img.shields.io/discord/952656177924300932" alt="Discord"></a> <a href="https://hub.docker.com/r/fallenbagel/jellyseerr"><img src="https://img.shields.io/docker/pulls/fallenbagel/jellyseerr" alt="Docker pulls"></a> <a href="http://jellyseerr.borgcube.de/engage/jellyseerr/"><img src="http://jellyseerr.borgcube.de/widget/jellyseerr/jellyseerr-frontend/svg-badge.svg" alt="Translation status" /></a> <a href="https://github.com/fallenbagel/jellyseerr/blob/develop/LICENSE"><img alt="GitHub" src="https://img.shields.io/github/license/fallenbagel/jellyseerr"></a> <!-- ALL-CONTRIBUTORS-BADGE:START - Do not remove or modify this section --> <a href="#contributors-"><img alt="All Contributors" src="https://img.shields.io/badge/all_contributors-40-orange.svg"/></a> <!-- ALL-CONTRIBUTORS-BADGE:END --> **Jellyseerr** is a free and open source software application for managing requests for your media library. It is a fork of [Overseerr](https://github.com/sct/overseerr) built to bring support for [Jellyfin](https://github.com/jellyfin/jellyfin) & [Emby](https://github.com/MediaBrowser/Emby) media servers! _The original Overseerr team have been busy and Jellyfin/Emby support aren't on their roadmap, so we started this project as we wanted to bring the Overseerr experience to the Jellyfin/Emby Community!_ ## Current Features <!-- --> - Full Jellyfin/Emby/Plex integration including authentication with user import & management - Supports Movies, Shows and Mixed Libraries - Ability to change email addresses for smtp purposes - Easy integration with your existing services. Currently, Jellyseerr supports Sonarr and Radarr. More to come! - Jellyfin/Emby/Plex library scan, to keep track of the titles which are already available. - Customizable request system, which allows users to request individual seasons or movies in a friendly, easy-to-use interface. - Incredibly simple request management UI. Don't dig through the app to simply approve recent requests! - Granular permission system. - Support for various notification agents. - Mobile-friendly design, for when you need to approve requests on the go! (Upcoming Features include: Multiple Server Instances, and much more!) With more features on the way! Check out our [issue tracker](https://github.com/fallenbagel/jellyseerr/issues) to see the features which have already been requested. ## Getting Started ### Launching Jellyseerr using Docker (Recommended) Check out our docker hub for instructions on how to install and run Jellyseerr: https://hub.docker.com/r/fallenbagel/jellyseerr ### Building from source (ADVANCED): #### Windows Pre-requisites: - Nodejs [v20](https://nodejs.org/en/download) - Pnpm [v9](https://pnpm.io/installation) - Download/git clone the source code from the github (Either develop branch or main for stable) ```cmd npm i -g win-node-env set CYPRESS_INSTALL_BINARY=0 pnpm install --frozen-lockfile pnpm add typeorm@0.13.11 pnpm run build pnpm start ``` (You can use task scheduler to run a bat script with `@echo off` and `pnpm start` to run jellyseerr in the background) (You can also use nssm to run jellyseerr as a service, see [nssm](https://nssm.cc/usage) for more information) _To set env variables such as `JELLYFIN_TYPE=emby` create a file called `.env` in the root directory of jellyseerr_ #### Linux **Pre-requisites:** - Nodejs [v20](https://nodejs.org/en/download) - Pnpm [v9](https://pnpm.io/installation) - Git **Steps:** 1. Assuming you want the root folder for the jellyseerr source code to be cloned to `/opt` ```bash cd /opt ``` 2. Then execute the following commands to clone and checkout to the stable version ```bash git clone https://github.com/Fallenbagel/jellyseerr.git && cd jellyseerr git checkout main ``` 3. Then install the dependencies and build the dist ```bash CYPRESS_INSTALL_BINARY=0 pnpm install --frozen-lockfile pnpm build ``` 4. Now you can start jellyseerr using `pnpm start` and opening http://localhost:5055 in your browser. 5. If you want to run jellyseerr as a _Systemd-service:_ - assuming jellyseerr was cloned to `/opt/` - first create the environment file at `/etc/jellyseerr/jellyseerr.conf` Environment file: ``` # Jellyseerr's default port is 5055, if you want to use both, change this. # specify on which port to listen PORT=5055 # specify on which interface to listen, by default jellyseerr listens on all interfaces #HOST=127.0.0.1 # Uncomment if your media server is emby instead of jellyfin. # JELLYFIN_TYPE=emby ``` - Then run the command `which node` to find your node path (assuming it's at `/usr/bin/node`) - Then create the service file using `sudo systemctl edit jellyseerr.service` or creating and editing a file at `/etc/systemd/system/jellyseerr.service` Service file contents: ``` [Unit] Description=Jellyseerr Service Wants=network-online.target After=network-online.target [Service] EnvironmentFile=/etc/jellyseerr/jellyseerr.conf Environment=NODE_ENV=production Type=exec Restart=on-failure WorkingDirectory=/opt/jellyseerr ExecStart=/usr/bin/node dist/index.js [Install] WantedBy=multi-user.target ``` ### Packages: Archlinux: [AUR](https://aur.archlinux.org/packages/jellyseerr) Nixpkg: [Nixpkg](https://search.nixos.org/packages?channel=unstable&show=jellyseerr) ~Snap: [Snap](https://snapcraft.io/jellyseerr)~(Deprecated) ## Preview <img src="./public/preview.jpg"> ## Support - You can get support on [Discord](https://discord.gg/ckbvBtDJgC). - You can ask questions in the Help category of our [GitHub Discussions](https://github.com/fallenbagel/jellyseerr/discussions). - Bug reports and feature requests can be submitted via [GitHub Issues](https://github.com/fallenbagel/jellyseerr/issues). ## API Documentation You can access the API documentation from your local Jellyseerr install at http://localhost:5055/api-docs ## Community You can ask questions, share ideas, and more in [GitHub Discussions](https://github.com/fallenbagel/jellyseerr/discussions). If you would like to chat with other members of our growing community, [join the Jellyseerr Discord server](https://discord.gg/ckbvBtDJgC)! Our [Code of Conduct](https://github.com/fallenbagel/jellyseerr/blob/develop/CODE_OF_CONDUCT.md) applies to all Jellyseerr community channels. ## Contributing You can help improve Jellyseerr too! Check out our [Contribution Guide](https://github.com/fallenbagel/jellyseerr/blob/develop/CONTRIBUTING.md) to get started. ## Contributors ✨ Thanks goes to these wonderful people from Overseerr ([emoji key](https://allcontributors.org/docs/en/emoji-key)) and all those that contributed directly to Jellyseerr: ### Jellyseerr Contributors ✨ <!-- ALL-CONTRIBUTORS-LIST:START - Do not remove or modify this section --> <!-- prettier-ignore-start --> <!-- markdownlint-disable --> <table> <tbody> <tr> <td align="center" valign="top" width="14.28%"><a href="https://github.com/Fallenbagel"><img src="https://avatars.githubusercontent.com/u/98979876?v=4?s=100" width="100px;" alt="Fallenbagel"/><br />_{<b>Fallenbagel</b>}</a><br /><a href="https://github.com/Fallenbagel/jellyseerr/commits?author=Fallenbagel" title="Code">💻</a> <a href="#maintenance-Fallenbagel" title="Maintenance">🚧</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/seanzhang98"><img src="https://avatars.githubusercontent.com/u/34902361?v=4?s=100" width="100px;" alt="Sean"/><br />_<b>Sean</b></a><br /><a href="#translation-seanzhang98" title="Translation">🌍</a> <a href="https://github.com/Fallenbagel/jellyseerr/commits?author=seanzhang98" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/notfakie"><img src="https://avatars.githubusercontent.com/u/103784113?v=4?s=100" width="100px;" alt="notfakie"/><br />_{<b>notfakie</b>}</a><br /><a href="https://github.com/Fallenbagel/jellyseerr/commits?author=notfakie" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/Jumail"><img src="https://avatars.githubusercontent.com/u/7672055?v=4?s=100" width="100px;" alt="Mohamed Jumail"/><br />_{<b>Mohamed Jumail</b>}</a><br /><a href="https://github.com/Fallenbagel/jellyseerr/pulls?q=is%3Apr+reviewed-by%3AJumail" title="Reviewed Pull Requests">👀</a></td> <td align="center" valign="top" width="14.28%"><a href="https://www.heywhale.com"><img src="https://avatars.githubusercontent.com/u/4048787?v=4?s=100" width="100px;" alt="Shilong Jiang"/><br />_{<b>Shilong Jiang</b>}</a><br /><a href="https://github.com/Fallenbagel/jellyseerr/commits?author=jsl9208" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://jinas.me"><img src="https://avatars.githubusercontent.com/u/28459081?v=4?s=100" width="100px;" alt="Boring Dragon"/><br />_{<b>Boring Dragon</b>}</a><br /><a href="https://github.com/Fallenbagel/jellyseerr/commits?author=boring-dragon" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/sambartik"><img src="https://avatars.githubusercontent.com/u/63553146?v=4?s=100" width="100px;" alt="Samuel Bartík"/><br />_{<b>Samuel Bartík</b>}</a><br /><a href="https://github.com/Fallenbagel/jellyseerr/commits?author=sambartik" title="Code">💻</a></td> </tr> <tr> <td align="center" valign="top" width="14.28%"><a href="https://github.com/CyferShepard"><img src="https://avatars.githubusercontent.com/u/24864904?v=4?s=100" width="100px;" alt="Thegan Govender"/><br />_{<b>Thegan Govender</b>}</a><br /><a href="https://github.com/Fallenbagel/jellyseerr/commits?author=CyferShepard" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/jab416171"><img src="https://avatars.githubusercontent.com/u/345752?v=4?s=100" width="100px;" alt="jab416171"/><br />_{<b>jab416171</b>}</a><br /><a href="https://github.com/Fallenbagel/jellyseerr/commits?author=jab416171" title="Documentation">📖</a></td> <td align="center" valign="top" width="14.28%"><a href="https://nvds.be"><img src="https://avatars.githubusercontent.com/u/5257222?v=4?s=100" width="100px;" alt="Nicolai Van der Storm"/><br />_{<b>Nicolai Van der Storm</b>}</a><br /><a href="https://github.com/Fallenbagel/jellyseerr/commits?author=NicolaiVdS" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/Smexhy"><img src="https://avatars.githubusercontent.com/u/4880625?v=4?s=100" width="100px;" alt="Smexhy"/><br />_{<b>Smexhy</b>}</a><br /><a href="#translation-Smexhy" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="https://dd06-dev.fr"><img src="https://avatars.githubusercontent.com/u/58089504?v=4?s=100" width="100px;" alt="dd060606"/><br />_{<b>dd060606</b>}</a><br /><a href="https://github.com/Fallenbagel/jellyseerr/commits?author=dd060606" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://qwer.tz"><img src="https://avatars.githubusercontent.com/u/71837281?v=4?s=100" width="100px;" alt="Daniel"/><br />_{<b>Daniel</b>}</a><br /><a href="https://github.com/Fallenbagel/jellyseerr/commits?author=darmiel" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/undone37"><img src="https://avatars.githubusercontent.com/u/10513808?v=4?s=100" width="100px;" alt="undone37"/><br />_{<b>undone37</b>}</a><br /><a href="#translation-undone37" title="Translation">🌍</a></td> </tr> <tr> <td align="center" valign="top" width="14.28%"><a href="https://github.com/CheChu10"><img src="https://avatars.githubusercontent.com/u/32913133?v=4?s=100" width="100px;" alt="Chechu García"/><br />_{<b>Chechu García</b>}</a><br /><a href="#translation-CheChu10" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/DimitriDR"><img src="https://avatars.githubusercontent.com/u/56969769?v=4?s=100" width="100px;" alt="Dimitri"/><br />_{<b>Dimitri</b>}</a><br /><a href="#translation-DimitriDR" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/andrey4korop"><img src="https://avatars.githubusercontent.com/u/24610708?v=4?s=100" width="100px;" alt="andrey4korop"/><br />_{<b>andrey4korop</b>}</a><br /><a href="https://github.com/Fallenbagel/jellyseerr/commits?author=andrey4korop" title="Code">💻</a> <a href="#translation-andrey4korop" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="https://geoffrey-coulaud.fr"><img src="https://avatars.githubusercontent.com/u/20744730?v=4?s=100" width="100px;" alt="Geoffrey Coulaud"/><br />_{<b>Geoffrey Coulaud</b>}</a><br /><a href="#translation-GeoffreyCoulaud" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/Pikachu920"><img src="https://avatars.githubusercontent.com/u/28607612?v=4?s=100" width="100px;" alt="Pikachu920"/><br />_{<b>Pikachu920</b>}</a><br /><a href="https://github.com/Fallenbagel/jellyseerr/commits?author=Pikachu920" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/yalagin"><img src="https://avatars.githubusercontent.com/u/12879142?v=4?s=100" width="100px;" alt="Maxim Yalagin"/><br />_{<b>Maxim Yalagin</b>}</a><br /><a href="https://github.com/Fallenbagel/jellyseerr/commits?author=yalagin" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/jeaboswell"><img src="https://avatars.githubusercontent.com/u/11653068?v=4?s=100" width="100px;" alt="Jesse Boswell"/><br />_{<b>Jesse Boswell</b>}</a><br /><a href="https://github.com/Fallenbagel/jellyseerr/commits?author=jeaboswell" title="Code">💻</a></td> </tr> <tr> <td align="center" valign="top" width="14.28%"><a href="https://github.com/d-fendrich"><img src="https://avatars.githubusercontent.com/u/27904138?v=4?s=100" width="100px;" alt="d-fendrich"/><br />_{<b>d-fendrich</b>}</a><br /><a href="#translation-d-fendrich" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/davidfdezalcoba"><img src="https://avatars.githubusercontent.com/u/15996018?v=4?s=100" width="100px;" alt="David Fernández Alcoba"/><br />_{<b>David Fernández Alcoba</b>}</a><br /><a href="https://github.com/Fallenbagel/jellyseerr/commits?author=davidfdezalcoba" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/Gauvino"><img src="https://avatars.githubusercontent.com/u/68083474?v=4?s=100" width="100px;" alt="Gauvino"/><br />_{<b>Gauvino</b>}</a><br /><a href="#translation-Gauvino" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/EthanArmbrust"><img src="https://avatars.githubusercontent.com/u/22754714?v=4?s=100" width="100px;" alt="EthanArmbrust"/><br />_{<b>EthanArmbrust</b>}</a><br /><a href="https://github.com/Fallenbagel/jellyseerr/commits?author=EthanArmbrust" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="http://www.piribisoft.com"><img src="https://avatars.githubusercontent.com/u/854646?v=4?s=100" width="100px;" alt="Eduardo"/><br />_{<b>Eduardo</b>}</a><br /><a href="https://github.com/Fallenbagel/jellyseerr/commits?author=SirMartin" title="Documentation">📖</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/RickLuiken"><img src="https://avatars.githubusercontent.com/u/34110371?v=4?s=100" width="100px;" alt="RickLuiken"/><br />_{<b>RickLuiken</b>}</a><br /><a href="https://github.com/Fallenbagel/jellyseerr/commits?author=RickLuiken" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/Br33ce"><img src="https://avatars.githubusercontent.com/u/124933490?v=4?s=100" width="100px;" alt="Br33ce"/><br />_{<b>Br33ce</b>}</a><br /><a href="#translation-Br33ce" title="Translation">🌍</a></td> </tr> <tr> <td align="center" valign="top" width="14.28%"><a href="https://athfan.com"><img src="https://avatars.githubusercontent.com/u/13810742?v=4?s=100" width="100px;" alt="Athfan Khaleel"/><br />_{<b>Athfan Khaleel</b>}</a><br /><a href="https://github.com/Fallenbagel/jellyseerr/commits?author=athphane" title="Documentation">📖</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/mdll23"><img src="https://avatars.githubusercontent.com/u/142844478?v=4?s=100" width="100px;" alt="Michael Dallinger"/><br />_{<b>Michael Dallinger</b>}</a><br /><a href="#translation-mdll23" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/xeruf"><img src="https://avatars.githubusercontent.com/u/13354331?v=4?s=100" width="100px;" alt="Janek"/><br />_<b>Janek</b></a><br /><a href="https://github.com/Fallenbagel/jellyseerr/commits?author=xeruf" title="Documentation">📖</a></td> <td align="center" valign="top" width="14.28%"><a href="https://aleksasiriski.dev"><img src="https://avatars.githubusercontent.com/u/31509435?v=4?s=100" width="100px;" alt="Aleksa Siriški"/><br />_{<b>Aleksa Siriški</b>}</a><br /><a href="#infra-aleksasiriski" title="Infrastructure (Hosting, Build-Tools, etc)">🚇</a></td> <td align="center" valign="top" width="14.28%"><a href="http://danishhumair.com"><img src="https://avatars.githubusercontent.com/u/121830048?v=4?s=100" width="100px;" alt="Danish Humair"/><br />_{<b>Danish Humair</b>}</a><br /><a href="https://github.com/Fallenbagel/jellyseerr/commits?author=Danish-H" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://arm0.red"><img src="https://avatars.githubusercontent.com/u/16858514?v=4?s=100" width="100px;" alt="Stephen Harris"/><br />_{<b>Stephen Harris</b>}</a><br /><a href="https://github.com/Fallenbagel/jellyseerr/commits?author=trackmastersteve" title="Documentation">📖</a></td> <td align="center" valign="top" width="14.28%"><a href="https://www.boniface.me"><img src="https://avatars.githubusercontent.com/u/4031396?v=4?s=100" width="100px;" alt="Joshua M. Boniface"/><br />_{<b>Joshua M. Boniface</b>}</a><br /><a href="https://github.com/Fallenbagel/jellyseerr/commits?author=joshuaboniface" title="Code">💻</a></td> </tr> <tr> <td align="center" valign="top" width="14.28%"><a href="https://gauthierth.fr/"><img src="https://avatars.githubusercontent.com/u/37781713?v=4?s=100" width="100px;" alt="Gauthier"/><br />_{<b>Gauthier</b>}</a><br /><a href="https://github.com/Fallenbagel/jellyseerr/commits?author=gauthier-th" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/Kara-Zor-El"><img src="https://avatars.githubusercontent.com/u/69772087?v=4?s=100" width="100px;" alt="Kara"/><br />_<b>Kara</b></a><br /><a href="#infra-Kara-Zor-El" title="Infrastructure (Hosting, Build-Tools, etc)">🚇</a></td> <td align="center" valign="top" width="14.28%"><a href="https://joaquinolivero.com"><img src="https://avatars.githubusercontent.com/u/66050823?v=4?s=100" width="100px;" alt="Joaquin Olivero"/><br />_{<b>Joaquin Olivero</b>}</a><br /><a href="https://github.com/Fallenbagel/jellyseerr/commits?author=JoaquinOlivero" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/Bretterteig"><img src="https://avatars.githubusercontent.com/u/47298401?v=4?s=100" width="100px;" alt="Julian Behr"/><br />_{<b>Julian Behr</b>}</a><br /><a href="#translation-Bretterteig" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/ThowZzy"><img src="https://avatars.githubusercontent.com/u/61882536?v=4?s=100" width="100px;" alt="ThowZzy"/><br />_{<b>ThowZzy</b>}</a><br /><a href="https://github.com/Fallenbagel/jellyseerr/commits?author=ThowZzy" title="Code">💻</a></td> </tr> </tbody> </table> <!-- markdownlint-restore --> <!-- prettier-ignore-end --> <!-- ALL-CONTRIBUTORS-LIST:END --> ### Overseerr Contributors ✨ <table> <tbody> <tr> <td align="center" valign="top" width="14.28%"><a href="https://sct.dev"><img src="https://avatars1.githubusercontent.com/u/234213?v=4?s=100" width="100px;" alt="sct"/><br />_<b>sct</b></a><br /><a href="https://github.com/sct/overseerr/commits?author=sct" title="Code">💻</a> <a href="#design-sct" title="Design">🎨</a> <a href="#ideas-sct" title="Ideas, Planning, & Feedback">🤔</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/azoitos"><img src="https://avatars2.githubusercontent.com/u/26529049?v=4?s=100" width="100px;" alt="Alex Zoitos"/><br />_{<b>Alex Zoitos</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=azoitos" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/OwsleyJr"><img src="https://avatars3.githubusercontent.com/u/8635678?v=4?s=100" width="100px;" alt="Brandon Cohen"/><br />_{<b>Brandon Cohen</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=OwsleyJr" title="Code">💻</a> <a href="https://github.com/sct/overseerr/commits?author=OwsleyJr" title="Documentation">📖</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/Ahreluth"><img src="https://avatars2.githubusercontent.com/u/75682440?v=4?s=100" width="100px;" alt="Ahreluth"/><br />_{<b>Ahreluth</b>}</a><br /><a href="#translation-Ahreluth" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/KovalevArtem"><img src="https://avatars0.githubusercontent.com/u/36500228?v=4?s=100" width="100px;" alt="KovalevArtem"/><br />_{<b>KovalevArtem</b>}</a><br /><a href="#translation-KovalevArtem" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/GiyomuWeb"><img src="https://avatars0.githubusercontent.com/u/62489209?v=4?s=100" width="100px;" alt="GiyomuWeb"/><br />_{<b>GiyomuWeb</b>}</a><br /><a href="#translation-GiyomuWeb" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/angrycuban13"><img src="https://avatars3.githubusercontent.com/u/39564898?v=4?s=100" width="100px;" alt="Angry Cuban"/><br />_{<b>Angry Cuban</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=angrycuban13" title="Documentation">📖</a></td> </tr> <tr> <td align="center" valign="top" width="14.28%"><a href="https://github.com/jvennik"><img src="https://avatars3.githubusercontent.com/u/6672637?v=4?s=100" width="100px;" alt="jvennik"/><br />_{<b>jvennik</b>}</a><br /><a href="#translation-jvennik" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/darknessgp"><img src="https://avatars0.githubusercontent.com/u/1521243?v=4?s=100" width="100px;" alt="darknessgp"/><br />_{<b>darknessgp</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=darknessgp" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/saltydk"><img src="https://avatars1.githubusercontent.com/u/6587950?v=4?s=100" width="100px;" alt="salty"/><br />_<b>salty</b></a><br /><a href="#infra-saltydk" title="Infrastructure (Hosting, Build-Tools, etc)">🚇</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/Shutruk"><img src="https://avatars2.githubusercontent.com/u/9198633?v=4?s=100" width="100px;" alt="Shutruk"/><br />_{<b>Shutruk</b>}</a><br /><a href="#translation-Shutruk" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/krystiancharubin"><img src="https://avatars2.githubusercontent.com/u/17775600?v=4?s=100" width="100px;" alt="Krystian Charubin"/><br />_{<b>Krystian Charubin</b>}</a><br /><a href="#design-krystiancharubin" title="Design">🎨</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/kieron"><img src="https://avatars2.githubusercontent.com/u/8655212?v=4?s=100" width="100px;" alt="Kieron Boswell"/><br />_{<b>Kieron Boswell</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=kieron" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/samwiseg0"><img src="https://avatars1.githubusercontent.com/u/2241731?v=4?s=100" width="100px;" alt="samwiseg0"/><br />_{<b>samwiseg0</b>}</a><br /><a href="#question-samwiseg0" title="Answering Questions">💬</a> <a href="#infra-samwiseg0" title="Infrastructure (Hosting, Build-Tools, etc)">🚇</a></td> </tr> <tr> <td align="center" valign="top" width="14.28%"><a href="https://github.com/ecelebi29"><img src="https://avatars2.githubusercontent.com/u/8337120?v=4?s=100" width="100px;" alt="ecelebi29"/><br />_{<b>ecelebi29</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=ecelebi29" title="Code">💻</a> <a href="https://github.com/sct/overseerr/commits?author=ecelebi29" title="Documentation">📖</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/mmozeiko"><img src="https://avatars3.githubusercontent.com/u/1665010?v=4?s=100" width="100px;" alt="Mārtiņš Možeiko"/><br />_{<b>Mārtiņš Možeiko</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=mmozeiko" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/mazzetta86"><img src="https://avatars2.githubusercontent.com/u/45591560?v=4?s=100" width="100px;" alt="mazzetta86"/><br />_{<b>mazzetta86</b>}</a><br /><a href="#translation-mazzetta86" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/Panzer1119"><img src="https://avatars1.githubusercontent.com/u/23016343?v=4?s=100" width="100px;" alt="Paul Hagedorn"/><br />_{<b>Paul Hagedorn</b>}</a><br /><a href="#translation-Panzer1119" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/Shagon94"><img src="https://avatars3.githubusercontent.com/u/9140783?v=4?s=100" width="100px;" alt="Shagon94"/><br />_{<b>Shagon94</b>}</a><br /><a href="#translation-Shagon94" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/sebstrgg"><img src="https://avatars3.githubusercontent.com/u/27026694?v=4?s=100" width="100px;" alt="sebstrgg"/><br />_{<b>sebstrgg</b>}</a><br /><a href="#translation-sebstrgg" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/danshilm"><img src="https://avatars2.githubusercontent.com/u/20923978?v=4?s=100" width="100px;" alt="Danshil Mungur"/><br />_{<b>Danshil Mungur</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=danshilm" title="Code">💻</a> <a href="https://github.com/sct/overseerr/commits?author=danshilm" title="Documentation">📖</a></td> </tr> <tr> <td align="center" valign="top" width="14.28%"><a href="https://github.com/doob187"><img src="https://avatars1.githubusercontent.com/u/60312740?v=4?s=100" width="100px;" alt="doob187"/><br />_{<b>doob187</b>}</a><br /><a href="#infra-doob187" title="Infrastructure (Hosting, Build-Tools, etc)">🚇</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/johnpyp"><img src="https://avatars2.githubusercontent.com/u/20625636?v=4?s=100" width="100px;" alt="johnpyp"/><br />_{<b>johnpyp</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=johnpyp" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/ankarhem"><img src="https://avatars1.githubusercontent.com/u/14110063?v=4?s=100" width="100px;" alt="Jakob Ankarhem"/><br />_{<b>Jakob Ankarhem</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=ankarhem" title="Documentation">📖</a> <a href="https://github.com/sct/overseerr/commits?author=ankarhem" title="Code">💻</a> <a href="#translation-ankarhem" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/jayesh100"><img src="https://avatars1.githubusercontent.com/u/8022175?v=4?s=100" width="100px;" alt="Jayesh"/><br />_{<b>Jayesh</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=jayesh100" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/flying-sausages"><img src="https://avatars1.githubusercontent.com/u/23618693?v=4?s=100" width="100px;" alt="flying-sausages"/><br />_{<b>flying-sausages</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=flying-sausages" title="Documentation">📖</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/hirenshah"><img src="https://avatars2.githubusercontent.com/u/418112?v=4?s=100" width="100px;" alt="hirenshah"/><br />_{<b>hirenshah</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=hirenshah" title="Documentation">📖</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/TheCatLady"><img src="https://avatars0.githubusercontent.com/u/52870424?v=4?s=100" width="100px;" alt="TheCatLady"/><br />_{<b>TheCatLady</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=TheCatLady" title="Code">💻</a> <a href="#translation-TheCatLady" title="Translation">🌍</a> <a href="https://github.com/sct/overseerr/commits?author=TheCatLady" title="Documentation">📖</a></td> </tr> <tr> <td align="center" valign="top" width="14.28%"><a href="https://github.com/chriscpritchard"><img src="https://avatars1.githubusercontent.com/u/1839074?v=4?s=100" width="100px;" alt="Chris Pritchard"/><br />_{<b>Chris Pritchard</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=chriscpritchard" title="Code">💻</a> <a href="https://github.com/sct/overseerr/commits?author=chriscpritchard" title="Documentation">📖</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/Tamberlox"><img src="https://avatars3.githubusercontent.com/u/56069014?v=4?s=100" width="100px;" alt="Tamberlox"/><br />_{<b>Tamberlox</b>}</a><br /><a href="#translation-Tamberlox" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="https://hmnd.io"><img src="https://avatars.githubusercontent.com/u/12853597?v=4?s=100" width="100px;" alt="David"/><br />_<b>David</b></a><br /><a href="https://github.com/sct/overseerr/commits?author=hmnd" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://www.douglas-parker.com"><img src="https://avatars.githubusercontent.com/u/18235822?v=4?s=100" width="100px;" alt="Douglas Parker"/><br />_{<b>Douglas Parker</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=douglasparker" title="Documentation">📖</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/dancarter"><img src="https://avatars.githubusercontent.com/u/4387516?v=4?s=100" width="100px;" alt="Daniel Carter"/><br />_{<b>Daniel Carter</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=dancarter" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://nuro.dev"><img src="https://avatars.githubusercontent.com/u/4991309?v=4?s=100" width="100px;" alt="nuro"/><br />_<b>nuro</b></a><br /><a href="https://github.com/sct/overseerr/commits?author=NuroDev" title="Documentation">📖</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/onedr0p"><img src="https://avatars.githubusercontent.com/u/213795?v=4?s=100" width="100px;" alt="ᗪєνιη ᗷυнʟ"/><br />_{<b>ᗪєνιη ᗷυнʟ</b>}</a><br /><a href="#infra-onedr0p" title="Infrastructure (Hosting, Build-Tools, etc)">🚇</a></td> </tr> <tr> <td align="center" valign="top" width="14.28%"><a href="https://github.com/JonnyWong16"><img src="https://avatars.githubusercontent.com/u/9099342?v=4?s=100" width="100px;" alt="JonnyWong16"/><br />_{<b>JonnyWong16</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=JonnyWong16" title="Documentation">📖</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/Roxedus"><img src="https://avatars.githubusercontent.com/u/7110194?v=4?s=100" width="100px;" alt="Roxedus"/><br />_{<b>Roxedus</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=Roxedus" title="Documentation">📖</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/WoisWoi"><img src="https://avatars.githubusercontent.com/u/75491231?v=4?s=100" width="100px;" alt="WoisWoi"/><br />_{<b>WoisWoi</b>}</a><br /><a href="#translation-WoisWoi" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/HubDuck"><img src="https://avatars.githubusercontent.com/u/77843475?v=4?s=100" width="100px;" alt="HubDuck"/><br />_{<b>HubDuck</b>}</a><br /><a href="#translation-HubDuck" title="Translation">🌍</a> <a href="https://github.com/sct/overseerr/commits?author=HubDuck" title="Documentation">📖</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/costaht"><img src="https://avatars.githubusercontent.com/u/50637431?v=4?s=100" width="100px;" alt="costaht"/><br />_{<b>costaht</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=costaht" title="Documentation">📖</a> <a href="#translation-costaht" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/Shjosan"><img src="https://avatars.githubusercontent.com/u/20847626?v=4?s=100" width="100px;" alt="Shjosan"/><br />_{<b>Shjosan</b>}</a><br /><a href="#translation-Shjosan" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/kobaubarr"><img src="https://avatars.githubusercontent.com/u/28481522?v=4?s=100" width="100px;" alt="kobaubarr"/><br />_{<b>kobaubarr</b>}</a><br /><a href="#translation-kobaubarr" title="Translation">🌍</a></td> </tr> <tr> <td align="center" valign="top" width="14.28%"><a href="https://github.com/notorius28"><img src="https://avatars.githubusercontent.com/u/1621513?v=4?s=100" width="100px;" alt="Ricardo González"/><br />_{<b>Ricardo González</b>}</a><br /><a href="#translation-notorius28" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="http://torkili.uz"><img src="https://avatars.githubusercontent.com/u/460764?v=4?s=100" width="100px;" alt="Torkil"/><br />_{<b>Torkil</b>}</a><br /><a href="#translation-Torkiliuz" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="https://www.jagandeepbrar.io"><img src="https://avatars.githubusercontent.com/u/3048295?v=4?s=100" width="100px;" alt="Jagandeep Brar"/><br />_{<b>Jagandeep Brar</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=JagandeepBrar" title="Documentation">📖</a></td> <td align="center" valign="top" width="14.28%"><a href="http://dtalens.com"><img src="https://avatars.githubusercontent.com/u/6631832?v=4?s=100" width="100px;" alt="dtalens"/><br />_{<b>dtalens</b>}</a><br /><a href="#translation-dtalens" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/acortelyou"><img src="https://avatars.githubusercontent.com/u/1689668?v=4?s=100" width="100px;" alt="Alex Cortelyou"/><br />_{<b>Alex Cortelyou</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=acortelyou" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://nz.linkedin.com/in/jonocairns"><img src="https://avatars.githubusercontent.com/u/182836?v=4?s=100" width="100px;" alt="Jono Cairns"/><br />_{<b>Jono Cairns</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=jonocairns" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://scias.net/"><img src="https://avatars.githubusercontent.com/u/439655?v=4?s=100" width="100px;" alt="DJScias"/><br />_{<b>DJScias</b>}</a><br /><a href="#translation-DJScias" title="Translation">🌍</a></td> </tr> <tr> <td align="center" valign="top" width="14.28%"><a href="https://github.com/Dabu-dot"><img src="https://avatars.githubusercontent.com/u/52525576?v=4?s=100" width="100px;" alt="Dabu-dot"/><br />_{<b>Dabu-dot</b>}</a><br /><a href="#translation-Dabu-dot" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/Jabster28"><img src="https://avatars.githubusercontent.com/u/29015942?v=4?s=100" width="100px;" alt="Jabster28"/><br />_{<b>Jabster28</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=Jabster28" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/littlerooster"><img src="https://avatars.githubusercontent.com/u/83890654?v=4?s=100" width="100px;" alt="littlerooster"/><br />_{<b>littlerooster</b>}</a><br /><a href="#translation-littlerooster" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/dphildebrandt"><img src="https://avatars.githubusercontent.com/u/154459?v=4?s=100" width="100px;" alt="Dustin Hildebrandt"/><br />_{<b>Dustin Hildebrandt</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=dphildebrandt" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/Generator"><img src="https://avatars.githubusercontent.com/u/44146?v=4?s=100" width="100px;" alt="Bruno Guerreiro"/><br />_{<b>Bruno Guerreiro</b>}</a><br /><a href="#translation-Generator" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/iceHtwoO"><img src="https://avatars.githubusercontent.com/u/27020492?v=4?s=100" width="100px;" alt="Alexander Neuhäuser"/><br />_{<b>Alexander Neuhäuser</b>}</a><br /><a href="#translation-iceHtwoO" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="http://www.unext.co.jp"><img src="https://avatars.githubusercontent.com/u/37431541?v=4?s=100" width="100px;" alt="Livio"/><br />_<b>Livio</b></a><br /><a href="#design-liviokanone" title="Design">🎨</a></td> </tr> <tr> <td align="center" valign="top" width="14.28%"><a href="https://github.com/tangentThought"><img src="https://avatars.githubusercontent.com/u/25516090?v=4?s=100" width="100px;" alt="tangentThought"/><br />_{<b>tangentThought</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=tangentThought" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/nicospz"><img src="https://avatars.githubusercontent.com/u/31373060?v=4?s=100" width="100px;" alt="Nicolás Espinoza"/><br />_{<b>Nicolás Espinoza</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=nicospz" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/sootylunatic"><img src="https://avatars.githubusercontent.com/u/36486087?v=4?s=100" width="100px;" alt="sootylunatic"/><br />_{<b>sootylunatic</b>}</a><br /><a href="#translation-sootylunatic" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/JoKerIsCraZy"><img src="https://avatars.githubusercontent.com/u/47474211?v=4?s=100" width="100px;" alt="JoKerIsCraZy"/><br />_{<b>JoKerIsCraZy</b>}</a><br /><a href="#translation-JoKerIsCraZy" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="https://daddie.dev"><img src="https://avatars.githubusercontent.com/u/33762262?v=4?s=100" width="100px;" alt="Daddie0"/><br />_{<b>Daddie0</b>}</a><br /><a href="#translation-GoByeBye" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="http://ungaro.me"><img src="https://avatars.githubusercontent.com/u/43807696?v=4?s=100" width="100px;" alt="Simone"/><br />_{<b>Simone</b>}</a><br /><a href="#translation-Simoneu01" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/adan89lion"><img src="https://avatars.githubusercontent.com/u/6585644?v=4?s=100" width="100px;" alt="Seohyun Joo"/><br />_{<b>Seohyun Joo</b>}</a><br /><a href="#translation-adan89lion" title="Translation">🌍</a></td> </tr> <tr> <td align="center" valign="top" width="14.28%"><a href="https://github.com/ty4ko"><img src="https://avatars.githubusercontent.com/u/21213535?v=4?s=100" width="100px;" alt="Sergey"/><br />_{<b>Sergey</b>}</a><br /><a href="#translation-ty4ko" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/skafte1990"><img src="https://avatars.githubusercontent.com/u/31465453?v=4?s=100" width="100px;" alt="Shaaft"/><br />_{<b>Shaaft</b>}</a><br /><a href="#translation-skafte1990" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/sr093906"><img src="https://avatars.githubusercontent.com/u/8369201?v=4?s=100" width="100px;" alt="sr093906"/><br />_{<b>sr093906</b>}</a><br /><a href="#translation-sr093906" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/Nackophilz"><img src="https://avatars.githubusercontent.com/u/61667226?v=4?s=100" width="100px;" alt="Nackophilz"/><br />_{<b>Nackophilz</b>}</a><br /><a href="#translation-Nackophilz" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/schambers"><img src="https://avatars.githubusercontent.com/u/31563?v=4?s=100" width="100px;" alt="Sean Chambers"/><br />_{<b>Sean Chambers</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=schambers" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/deniscerri"><img src="https://avatars.githubusercontent.com/u/64997243?v=4?s=100" width="100px;" alt="deniscerri"/><br />_{<b>deniscerri</b>}</a><br /><a href="#translation-deniscerri" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/tomgacz"><img src="https://avatars.githubusercontent.com/u/14138209?v=4?s=100" width="100px;" alt="tomgacz"/><br />_{<b>tomgacz</b>}</a><br /><a href="#translation-tomgacz" title="Translation">🌍</a></td> </tr> <tr> <td align="center" valign="top" width="14.28%"><a href="https://github.com/Andersborrits"><img src="https://avatars.githubusercontent.com/u/29452218?v=4?s=100" width="100px;" alt="Andersborrits"/><br />_{<b>Andersborrits</b>}</a><br /><a href="#translation-Andersborrits" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="http://maxentrouault.fr"><img src="https://avatars.githubusercontent.com/u/67283154?v=4?s=100" width="100px;" alt="Maxent"/><br />_{<b>Maxent</b>}</a><br /><a href="#translation-Maxentr" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/sambartik"><img src="https://avatars.githubusercontent.com/u/63553146?v=4?s=100" width="100px;" alt="Samuel Bartík"/><br />_{<b>Samuel Bartík</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=sambartik" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/frank-cywong"><img src="https://avatars.githubusercontent.com/u/90653148?v=4?s=100" width="100px;" alt="Chun Yeung Wong"/><br />_{<b>Chun Yeung Wong</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=frank-cywong" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/TheMeanCanEHdian"><img src="https://avatars.githubusercontent.com/u/16025103?v=4?s=100" width="100px;" alt="TheMeanCanEHdian"/><br />_{<b>TheMeanCanEHdian</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=TheMeanCanEHdian" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/Gylesie"><img src="https://avatars.githubusercontent.com/u/86306812?v=4?s=100" width="100px;" alt="Gylesie"/><br />_{<b>Gylesie</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=Gylesie" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/Fhd-pro"><img src="https://avatars.githubusercontent.com/u/82862079?v=4?s=100" width="100px;" alt="Fhd-pro"/><br />_{<b>Fhd-pro</b>}</a><br /><a href="#translation-Fhd-pro" title="Translation">🌍</a></td> </tr> <tr> <td align="center" valign="top" width="14.28%"><a href="https://github.com/PovilasID"><img src="https://avatars.githubusercontent.com/u/396243?v=4?s=100" width="100px;" alt="PovilasID"/><br />_{<b>PovilasID</b>}</a><br /><a href="#translation-PovilasID" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/byakurau"><img src="https://avatars.githubusercontent.com/u/1811683?v=4?s=100" width="100px;" alt="byakurau"/><br />_{<b>byakurau</b>}</a><br /><a href="#translation-byakurau" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/miknii"><img src="https://avatars.githubusercontent.com/u/109232569?v=4?s=100" width="100px;" alt="miknii"/><br />_{<b>miknii</b>}</a><br /><a href="#translation-miknii" title="Translation">🌍</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/Eclipseop"><img src="https://avatars.githubusercontent.com/u/5846213?v=4?s=100" width="100px;" alt="Mackenzie"/><br />_{<b>Mackenzie</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=Eclipseop" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/s0up4200"><img src="https://avatars.githubusercontent.com/u/18177310?v=4?s=100" width="100px;" alt="soup"/><br />_<b>soup</b></a><br /><a href="https://github.com/sct/overseerr/commits?author=s0up4200" title="Documentation">📖</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/ceptonit"><img src="https://avatars.githubusercontent.com/u/12678743?v=4?s=100" width="100px;" alt="ceptonit"/><br />_{<b>ceptonit</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=ceptonit" title="Documentation">📖</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/aedelbro"><img src="https://avatars.githubusercontent.com/u/36162221?v=4?s=100" width="100px;" alt="aedelbro"/><br />_{<b>aedelbro</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=aedelbro" title="Code">💻</a></td> </tr> <tr> <td align="center" valign="top" width="14.28%"><a href="http://twitter.com/lunks/"><img src="https://avatars.githubusercontent.com/u/91118?v=4?s=100" width="100px;" alt="Pedro Nascimento"/><br />_{<b>Pedro Nascimento</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=lunks" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://voke.dev"><img src="https://avatars.githubusercontent.com/u/1899334?v=4?s=100" width="100px;" alt="Owen Voke"/><br />_{<b>Owen Voke</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=owenvoke" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/Nimelrian"><img src="https://avatars.githubusercontent.com/u/8960836?v=4?s=100" width="100px;" alt="Sebastian K"/><br />_{<b>Sebastian K</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=Nimelrian" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/jariz"><img src="https://avatars.githubusercontent.com/u/1415847?v=4?s=100" width="100px;" alt="jariz"/><br />_<b>jariz</b></a><br /><a href="https://github.com/sct/overseerr/commits?author=jariz" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://arouillard.fr"><img src="https://avatars.githubusercontent.com/u/13947260?v=4?s=100" width="100px;" alt="Alex"/><br />_<b>Alex</b></a><br /><a href="https://github.com/sct/overseerr/commits?author=Alexays" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/Zebebles"><img src="https://avatars.githubusercontent.com/u/11425451?v=4?s=100" width="100px;" alt="Zeb Muller"/><br />_{<b>Zeb Muller</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=Zebebles" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="http://smoores.dev"><img src="https://avatars.githubusercontent.com/u/5354254?v=4?s=100" width="100px;" alt="Shane Friedman"/><br />_{<b>Shane Friedman</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=SMores" title="Code">💻</a></td> </tr> <tr> <td align="center" valign="top" width="14.28%"><a href="https://izaacj.me"><img src="https://avatars.githubusercontent.com/u/711323?v=4?s=100" width="100px;" alt="Izaac Brånn"/><br />_{<b>Izaac Brånn</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=IzaacJ" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/SalmanTariq"><img src="https://avatars.githubusercontent.com/u/13284494?v=4?s=100" width="100px;" alt="Salman Tariq"/><br />_{<b>Salman Tariq</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=SalmanTariq" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/andrew-kennedy"><img src="https://avatars.githubusercontent.com/u/2387159?v=4?s=100" width="100px;" alt="Andrew Kennedy"/><br />_{<b>Andrew Kennedy</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=andrew-kennedy" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/Fallenbagel"><img src="https://avatars.githubusercontent.com/u/98979876?v=4?s=100" width="100px;" alt="Fallenbagel"/><br />_{<b>Fallenbagel</b>}</a><br /><a href="https://github.com/Fallenbagel/jellyseerr/commits?author=Fallenbagel" title="Jellyseerr">🪼⌨️</a> <a href="https://github.com/sct/overseerr/commits?author=Fallenbagel" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="http://aidoge.xyz"><img src="https://avatars.githubusercontent.com/u/9427639?v=4?s=100" width="100px;" alt="Anton K. (ai Doge)"/><br />_{<b>Anton K. (ai Doge)</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=scorp200" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://marcofaggian.com"><img src="https://avatars.githubusercontent.com/u/19221001?v=4?s=100" width="100px;" alt="Marco Faggian"/><br />_{<b>Marco Faggian</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=marcofaggian" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="http://nemchik.com/"><img src="https://avatars.githubusercontent.com/u/725456?v=4?s=100" width="100px;" alt="Eric Nemchik"/><br />_{<b>Eric Nemchik</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=nemchik" title="Code">💻</a></td> </tr> <tr> <td align="center" valign="top" width="14.28%"><a href="https://github.com/RemiRigal"><img src="https://avatars.githubusercontent.com/u/19256051?v=4?s=100" width="100px;" alt="RemiRigal"/><br />_{<b>RemiRigal</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=RemiRigal" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="http://josephrisk.com"><img src="https://avatars.githubusercontent.com/u/18372584?v=4?s=100" width="100px;" alt="Joseph Risk"/><br />_{<b>Joseph Risk</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=j0srisk" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/Loetwiek"><img src="https://avatars.githubusercontent.com/u/79059734?v=4?s=100" width="100px;" alt="Loetwiek"/><br />_{<b>Loetwiek</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=Loetwiek" title="Code">💻</a></td> <td align="center" valign="top" width="14.28%"><a href="https://github.com/Fuochi"><img src="https://avatars.githubusercontent.com/u/4720478?v=4?s=100" width="100px;" alt="Fuochi"/><br />_{<b>Fuochi</b>}</a><br /><a href="https://github.com/sct/overseerr/commits?author=Fuochi" title="Documentation">📖</a></td> </tr> </tbody> </table>

Fork of overseerr for jellyfin support

docker,emby,jellyfin,movie,notifications,nzb,plex,radarr,sonarr,tv

histoire-dev/histoire

<p align="center"> <img src="./logo.svg" alt="Histoire logo" width="256px" height="256px"> </p> <br> # Histoire > Fast and beautiful interactive component playgrounds [](https://github.com/histoire-dev/histoire/actions/workflows/test.yml) [](https://github.com/histoire-dev/histoire/actions/workflows/test-vue3.yml) [](https://github.com/histoire-dev/histoire/actions/workflows/test-svelte4.yml) [](https://github.com/histoire-dev/histoire/actions/workflows/test-nuxt3.yml) [Read the Documentation](https://histoire.dev) | [Discord server](https://discord.gg/KpCnT72rJk) | [Discussions board](https://github.com/histoire-dev/histoire/discussions) ⚡️ Lightning fast development and instant HMR thanks to [Vite](http://vitejs.dev) 👓 Build and visually test your components in isolation 📚 Document your components with stories and variants 📝 Generate source code examples automatically 🎨 Beautiful and customizable interface  ## Contributing See [Contributing Guide](https://github.com/Akryum/histoire/blob/main/CONTRIBUTING.md) to learn more about the repository and how you can contribute. ## Sponsors Become a sponsor! - [Guillaume Chau](https://github.com/sponsors/Akryum) - [Hugo Attal](https://github.com/sponsors/hugoattal) We are very grateful to all our sponsors for their support: ### [Guillaume Chau](https://github.com/sponsors/Akryum) <p align="center"> <a href="https://guillaume-chau.info/sponsors/" target="_blank"> <img src='https://akryum.netlify.app/sponsors.svg'/> </a> </p> ## License MIT

⚡ Fast and beautiful interactive component playgrounds, powered by Vite

javascript,story,sveltejs,vitejs,vuejs

WhiskeySockets/Baileys

# Baileys - Typescript/Javascript WhatsApp Web API ### Important Note This library was originally a project for **CS-2362 at Ashoka University** and is in no way affiliated with or endorsed by WhatsApp. Use at your own discretion. Do not spam people with this. We discourage any stalkerware, bulk or automated messaging usage. #### Liability and License Notice Baileys and its maintainers cannot be held liable for misuse of this application, as stated in the [MIT license](https://github.com/WhiskeySockets/Baileys/blob/master/LICENSE). The maintainers of Baileys do not in any way condone the use of this application in practices that violate the Terms of Service of WhatsApp. The maintainers of this application call upon the personal responsibility of its users to use this application in a fair way, as it is intended to be used. ## Baileys does not require Selenium or any other browser to be interface with WhatsApp Web, it does so directly using a **WebSocket**. Not running Selenium or Chromimum saves you like **half a gig** of ram :/ Baileys supports interacting with the multi-device & web versions of WhatsApp. Thank you to [@pokearaujo](https://github.com/pokearaujo/multidevice) for writing his observations on the workings of WhatsApp Multi-Device. Also, thank you to [@Sigalor](https://github.com/sigalor/whatsapp-web-reveng) for writing his observations on the workings of WhatsApp Web and thanks to [@Rhymen](https://github.com/Rhymen/go-whatsapp/) for the __go__ implementation. ## Please Read The original repository had to be removed by the original author - we now continue development in this repository here. This is the only official repository and is maintained by the community. **Join the Discord [here](https://discord.gg/WeJM5FP9GG)** ## Example Do check out & run [example.ts](Example/example.ts) to see an example usage of the library. The script covers most common use cases. To run the example script, download or clone the repo and then type the following in a terminal: 1. ``` cd path/to/Baileys ``` 2. ``` yarn ``` 3. ``` yarn example ``` ## Install Use the stable version: ``` yarn add @whiskeysockets/baileys ``` Use the edge version (no guarantee of stability, but latest fixes + features) ``` yarn add github:WhiskeySockets/Baileys ``` Then import your code using: ``` ts import makeWASocket from '@whiskeysockets/baileys' ``` ## Unit Tests TODO ## Connecting multi device (recommended) WhatsApp provides a multi-device API that allows Baileys to be authenticated as a second WhatsApp client by scanning a QR code with WhatsApp on your phone. ``` ts import makeWASocket, { DisconnectReason } from '@whiskeysockets/baileys' import { Boom } from '@hapi/boom' async function connectToWhatsApp () { const sock = makeWASocket({ // can provide additional config here printQRInTerminal: true }) sock.ev.on('connection.update', (update) => { const { connection, lastDisconnect } = update if(connection === 'close') { const shouldReconnect = (lastDisconnect.error as Boom)?.output?.statusCode !== DisconnectReason.loggedOut console.log('connection closed due to ', lastDisconnect.error, ', reconnecting ', shouldReconnect) // reconnect if not logged out if(shouldReconnect) { connectToWhatsApp() } } else if(connection === 'open') { console.log('opened connection') } }) sock.ev.on('messages.upsert', m => { console.log(JSON.stringify(m, undefined, 2)) console.log('replying to', m.messages[0].key.remoteJid) await sock.sendMessage(m.messages[0].key.remoteJid!, { text: 'Hello there!' }) }) } // run in main file connectToWhatsApp() ``` If the connection is successful, you will see a QR code printed on your terminal screen, scan it with WhatsApp on your phone and you'll be logged in! **Note:** install `qrcode-terminal` using `yarn add qrcode-terminal` to auto-print the QR to the terminal. **Note:** the code to support the legacy version of WA Web (pre multi-device) has been removed in v5. Only the standard multi-device connection is now supported. This is done as WA seems to have completely dropped support for the legacy version. ## Connecting native mobile api Baileys also supports the native mobile API, which allows users to authenticate as a standalone WhatsApp client using their phone number. Run the [example](Example/example.ts) file with ``--mobile`` cli flag to use the native mobile API. ## Configuring the Connection You can configure the connection by passing a `SocketConfig` object. The entire `SocketConfig` structure is mentioned here with default values: ``` ts type SocketConfig = { /** the WS url to connect to WA */ waWebSocketUrl: string | URL /** Fails the connection if the socket times out in this interval */ connectTimeoutMs: number /** Default timeout for queries, undefined for no timeout */ defaultQueryTimeoutMs: number | undefined /** ping-pong interval for WS connection */ keepAliveIntervalMs: number /** proxy agent */ agent?: Agent /** pino logger */ logger: Logger /** version to connect with */ version: WAVersion /** override browser config */ browser: WABrowserDescription /** agent used for fetch requests -- uploading/downloading media */ fetchAgent?: Agent /** should the QR be printed in the terminal */ printQRInTerminal: boolean /** should events be emitted for actions done by this socket connection */ emitOwnEvents: boolean /** provide a cache to store media, so does not have to be re-uploaded */ mediaCache?: NodeCache /** custom upload hosts to upload media to */ customUploadHosts: MediaConnInfo['hosts'] /** time to wait between sending new retry requests */ retryRequestDelayMs: number /** max msg retry count */ maxMsgRetryCount: number /** time to wait for the generation of the next QR in ms */ qrTimeout?: number; /** provide an auth state object to maintain the auth state */ auth: AuthenticationState /** manage history processing with this control; by default will sync up everything */ shouldSyncHistoryMessage: (msg: proto.Message.IHistorySyncNotification) => boolean /** transaction capability options for SignalKeyStore */ transactionOpts: TransactionCapabilityOptions /** provide a cache to store a user's device list */ userDevicesCache?: NodeCache /** marks the client as online whenever the socket successfully connects */ markOnlineOnConnect: boolean /** * map to store the retry counts for failed messages; * used to determine whether to retry a message or not */ msgRetryCounterMap?: MessageRetryMap /** width for link preview images */ linkPreviewImageThumbnailWidth: number /** Should Baileys ask the phone for full history, will be received async */ syncFullHistory: boolean /** Should baileys fire init queries automatically, default true */ fireInitQueries: boolean /** * generate a high quality link preview, * entails uploading the jpegThumbnail to WA * */ generateHighQualityLinkPreview: boolean /** options for axios */ options: AxiosRequestConfig<any> /** * fetch a message from your store * implement this so that messages failed to send (solves the "this message can take a while" issue) can be retried * */ getMessage: (key: proto.IMessageKey) => Promise<proto.IMessage | undefined> } ``` ### Emulating the Desktop app instead of the web 1. Baileys, by default, emulates a chrome web session 2. If you'd like to emulate a desktop connection (and receive more message history), add this to your Socket config: ``` ts const conn = makeWASocket({ ...otherOpts, // can use Windows, Ubuntu here too browser: Browsers.macOS('Desktop'), syncFullHistory: true }) ``` ## Saving & Restoring Sessions You obviously don't want to keep scanning the QR code every time you want to connect. So, you can load the credentials to log back in: ``` ts import makeWASocket, { BufferJSON, useMultiFileAuthState } from '@whiskeysockets/baileys' import * as fs from 'fs' // utility function to help save the auth state in a single folder // this function serves as a good guide to help write auth & key states for SQL/no-SQL databases, which I would recommend in any production grade system const { state, saveCreds } = await useMultiFileAuthState('auth_info_baileys') // will use the given state to connect // so if valid credentials are available -- it'll connect without QR const conn = makeWASocket({ auth: state }) // this will be called as soon as the credentials are updated conn.ev.on ('creds.update', saveCreds) ``` **Note:** When a message is received/sent, due to signal sessions needing updating, the auth keys (`authState.keys`) will update. Whenever that happens, you must save the updated keys (`authState.keys.set()` is called). Not doing so will prevent your messages from reaching the recipient & cause other unexpected consequences. The `useMultiFileAuthState` function automatically takes care of that, but for any other serious implementation -- you will need to be very careful with the key state management. ## Listening to Connection Updates Baileys now fires the `connection.update` event to let you know something has updated in the connection. This data has the following structure: ``` ts type ConnectionState = { /** connection is now open, connecting or closed */ connection: WAConnectionState /** the error that caused the connection to close */ lastDisconnect?: { error: Error date: Date } /** is this a new login */ isNewLogin?: boolean /** the current QR code */ qr?: string /** has the device received all pending notifications while it was offline */ receivedPendingNotifications?: boolean } ``` **Note:** this also offers any updates to the QR ## Handling Events Baileys uses the EventEmitter syntax for events. They're all nicely typed up, so you shouldn't have any issues with an Intellisense editor like VS Code. The events are typed as mentioned here: ``` ts export type BaileysEventMap = { /** connection state has been updated -- WS closed, opened, connecting etc. */ 'connection.update': Partial<ConnectionState> /** credentials updated -- some metadata, keys or something */ 'creds.update': Partial<AuthenticationCreds> /** history sync, everything is reverse chronologically sorted */ 'messaging-history.set': { chats: Chat[] contacts: Contact[] messages: WAMessage[] isLatest: boolean } /** upsert chats */ 'chats.upsert': Chat[] /** update the given chats */ 'chats.update': Partial<Chat>[] /** delete chats with given ID */ 'chats.delete': string[] 'labels.association': LabelAssociation 'labels.edit': Label /** presence of contact in a chat updated */ 'presence.update': { id: string, presences: { [participant: string]: PresenceData } } 'contacts.upsert': Contact[] 'contacts.update': Partial<Contact>[] 'messages.delete': { keys: WAMessageKey[] } | { jid: string, all: true } 'messages.update': WAMessageUpdate[] 'messages.media-update': { key: WAMessageKey, media?: { ciphertext: Uint8Array, iv: Uint8Array }, error?: Boom }[] /** * add/update the given messages. If they were received while the connection was online, * the update will have type: "notify" * */ 'messages.upsert': { messages: WAMessage[], type: MessageUpsertType } /** message was reacted to. If reaction was removed -- then "reaction.text" will be falsey */ 'messages.reaction': { key: WAMessageKey, reaction: proto.IReaction }[] 'message-receipt.update': MessageUserReceiptUpdate[] 'groups.upsert': GroupMetadata[] 'groups.update': Partial<GroupMetadata>[] /** apply an action to participants in a group */ 'group-participants.update': { id: string, participants: string[], action: ParticipantAction } 'blocklist.set': { blocklist: string[] } 'blocklist.update': { blocklist: string[], type: 'add' | 'remove' } /** Receive an update on a call, including when the call was received, rejected, accepted */ 'call': WACallEvent[] } ``` You can listen to these events like this: ``` ts const sock = makeWASocket() sock.ev.on('messages.upsert', ({ messages }) => { console.log('got messages', messages) }) ``` ## Implementing a Data Store Baileys does not come with a defacto storage for chats, contacts, or messages. However, a simple in-memory implementation has been provided. The store listens for chat updates, new messages, message updates, etc., to always have an up-to-date version of the data. It can be used as follows: ``` ts import makeWASocket, { makeInMemoryStore } from '@whiskeysockets/baileys' // the store maintains the data of the WA connection in memory // can be written out to a file & read from it const store = makeInMemoryStore({ }) // can be read from a file store.readFromFile('./baileys_store.json') // saves the state to a file every 10s setInterval(() => { store.writeToFile('./baileys_store.json') }, 10_000) const sock = makeWASocket({ }) // will listen from this socket // the store can listen from a new socket once the current socket outlives its lifetime store.bind(sock.ev) sock.ev.on('chats.set', () => { // can use "store.chats" however you want, even after the socket dies out // "chats" => a KeyedDB instance console.log('got chats', store.chats.all()) }) sock.ev.on('contacts.set', () => { console.log('got contacts', Object.values(store.contacts)) }) ``` The store also provides some simple functions such as `loadMessages` that utilize the store to speed up data retrieval. **Note:** I highly recommend building your own data store especially for MD connections, as storing someone's entire chat history in memory is a terrible waste of RAM. ## Sending Messages **Send all types of messages with a single function:** ### Non-Media Messages ``` ts import { MessageType, MessageOptions, Mimetype } from '@whiskeysockets/baileys' const id = 'abcd@s.whatsapp.net' // the WhatsApp ID // send a simple text! const sentMsg = await sock.sendMessage(id, { text: 'oh hello there' }) // send a reply messagge const sentMsg = await sock.sendMessage(id, { text: 'oh hello there' }, { quoted: message }) // send a mentions message const sentMsg = await sock.sendMessage(id, { text: '@12345678901', mentions: ['12345678901@s.whatsapp.net'] }) // send a location! const sentMsg = await sock.sendMessage( id, { location: { degreesLatitude: 24.121231, degreesLongitude: 55.1121221 } } ) // send a contact! const vcard = 'BEGIN:VCARD\n' // metadata of the contact card + 'VERSION:3.0\n' + 'FN:Jeff Singh\n' // full name + 'ORG:Ashoka Uni;\n' // the organization of the contact + 'TEL;type=CELL;type=VOICE;waid=911234567890:+91 12345 67890\n' // WhatsApp ID + phone number + 'END:VCARD' const sentMsg = await sock.sendMessage( id, { contacts: { displayName: 'Jeff', contacts: [{ vcard }] } } ) const reactionMessage = { react: { text: "💖", // use an empty string to remove the reaction key: message.key } } const sendMsg = await sock.sendMessage(id, reactionMessage) ``` ### Sending messages with link previews 1. By default, WA MD does not have link generation when sent from the web 2. Baileys has a function to generate the content for these link previews 3. To enable this function's usage, add `link-preview-js` as a dependency to your project with `yarn add link-preview-js` 4. Send a link: ``` ts // send a link const sentMsg = await sock.sendMessage(id, { text: 'Hi, this was sent using https://github.com/adiwajshing/baileys' }) ``` ### Media Messages Sending media (video, stickers, images) is easier & more efficient than ever. - You can specify a buffer, a local url or even a remote url. - When specifying a media url, Baileys never loads the entire buffer into memory; it even encrypts the media as a readable stream. ``` ts import { MessageType, MessageOptions, Mimetype } from '@whiskeysockets/baileys' // Sending gifs await sock.sendMessage( id, { video: fs.readFileSync("Media/ma_gif.mp4"), caption: "hello!", gifPlayback: true } ) await sock.sendMessage( id, { video: "./Media/ma_gif.mp4", caption: "hello!", gifPlayback: true, ptv: false // if set to true, will send as a `video note` } ) // send an audio file await sock.sendMessage( id, { audio: { url: "./Media/audio.mp3" }, mimetype: 'audio/mp4' } { url: "Media/audio.mp3" }, // can send mp3, mp4, & ogg ) ``` ### Notes - `id` is the WhatsApp ID of the person or group you're sending the message to. - It must be in the format ```[country code][phone number]@s.whatsapp.net``` - Example for people: ```+19999999999@s.whatsapp.net```. - For groups, it must be in the format ``` 123456789-123345@g.us ```. - For broadcast lists, it's `[timestamp of creation]@broadcast`. - For stories, the ID is `status@broadcast`. - For media messages, the thumbnail can be generated automatically for images & stickers provided you add `jimp` or `sharp` as a dependency in your project using `yarn add jimp` or `yarn add sharp`. Thumbnails for videos can also be generated automatically, though, you need to have `ffmpeg` installed on your system. - **MiscGenerationOptions**: some extra info about the message. It can have the following __optional__ values: ``` ts const info: MessageOptions = { quoted: quotedMessage, // the message you want to quote contextInfo: { forwardingScore: 2, isForwarded: true }, // some random context info (can show a forwarded message with this too) timestamp: Date(), // optional, if you want to manually set the timestamp of the message caption: "hello there!", // (for media messages) the caption to send with the media (cannot be sent with stickers though) jpegThumbnail: "23GD#4/==", /* (for location & media messages) has to be a base 64 encoded JPEG if you want to send a custom thumb, or set to null if you don't want to send a thumbnail. Do not enter this field if you want to automatically generate a thumb */ mimetype: Mimetype.pdf, /* (for media messages) specify the type of media (optional for all media types except documents), import {Mimetype} from '@whiskeysockets/baileys' */ fileName: 'somefile.pdf', // (for media messages) file name for the media /* will send audio messages as voice notes, if set to true */ ptt: true, /** Should it send as a disappearing messages. * By default 'chat' -- which follows the setting of the chat */ ephemeralExpiration: WA_DEFAULT_EPHEMERAL } ``` ## Forwarding Messages ``` ts const msg = getMessageFromStore('455@s.whatsapp.net', 'HSJHJWH7323HSJSJ') // implement this on your end await sock.sendMessage('1234@s.whatsapp.net', { forward: msg }) // WA forward the message! ``` ## Reading Messages A set of message keys must be explicitly marked read now. In multi-device, you cannot mark an entire "chat" read as it were with Baileys Web. This means you have to keep track of unread messages. ``` ts const key = { remoteJid: '1234-123@g.us', id: 'AHASHH123123AHGA', // id of the message you want to read participant: '912121232@s.whatsapp.net' // the ID of the user that sent the message (undefined for individual chats) } // pass to readMessages function // can pass multiple keys to read multiple messages as well await sock.readMessages([key]) ``` The message ID is the unique identifier of the message that you are marking as read. On a `WAMessage`, the `messageID` can be accessed using ```messageID = message.key.id```. ## Update Presence ``` ts await sock.sendPresenceUpdate('available', id) ``` This lets the person/group with ``` id ``` know whether you're online, offline, typing etc. ``` presence ``` can be one of the following: ``` ts type WAPresence = 'unavailable' | 'available' | 'composing' | 'recording' | 'paused' ``` The presence expires after about 10 seconds. **Note:** In the multi-device version of WhatsApp -- if a desktop client is active, WA doesn't send push notifications to the device. If you would like to receive said notifications -- mark your Baileys client offline using `sock.sendPresenceUpdate('unavailable')` ## Downloading Media Messages If you want to save the media you received ``` ts import { writeFile } from 'fs/promises' import { downloadMediaMessage } from '@whiskeysockets/baileys' sock.ev.on('messages.upsert', async ({ messages }) => { const m = messages[0] if (!m.message) return // if there is no text or media message const messageType = Object.keys (m.message)[0]// get what type of message it is -- text, image, video // if the message is an image if (messageType === 'imageMessage') { // download the message const buffer = await downloadMediaMessage( m, 'buffer', { }, { logger, // pass this so that baileys can request a reupload of media // that has been deleted reuploadRequest: sock.updateMediaMessage } ) // save to file await writeFile('./my-download.jpeg', buffer) } } ``` **Note:** WhatsApp automatically removes old media from their servers. For the device to access said media -- a re-upload is required by another device that has it. This can be accomplished using: ``` ts const updatedMediaMsg = await sock.updateMediaMessage(msg) ``` ## Deleting Messages ``` ts const jid = '1234@s.whatsapp.net' // can also be a group const response = await sock.sendMessage(jid, { text: 'hello!' }) // send a message // sends a message to delete the given message // this deletes the message for everyone await sock.sendMessage(jid, { delete: response.key }) ``` **Note:** deleting for oneself is supported via `chatModify` (next section) ## Updating Messages ``` ts const jid = '1234@s.whatsapp.net' await sock.sendMessage(jid, { text: 'updated text goes here', edit: response.key, }); ``` ## Modifying Chats WA uses an encrypted form of communication to send chat/app updates. This has been implemented mostly and you can send the following updates: - Archive a chat ``` ts const lastMsgInChat = await getLastMessageInChat('123456@s.whatsapp.net') // implement this on your end await sock.chatModify({ archive: true, lastMessages: [lastMsgInChat] }, '123456@s.whatsapp.net') ``` - Mute/unmute a chat ``` ts // mute for 8 hours await sock.chatModify({ mute: 8*60*60*1000 }, '123456@s.whatsapp.net', []) // unmute await sock.chatModify({ mute: null }, '123456@s.whatsapp.net', []) ``` - Mark a chat read/unread ``` ts const lastMsgInChat = await getLastMessageInChat('123456@s.whatsapp.net') // implement this on your end // mark it unread await sock.chatModify({ markRead: false, lastMessages: [lastMsgInChat] }, '123456@s.whatsapp.net') ``` - Delete a message for me ``` ts await sock.chatModify( { clear: { messages: [{ id: 'ATWYHDNNWU81732J', fromMe: true, timestamp: "1654823909" }] } }, '123456@s.whatsapp.net', [] ) ``` - Delete a chat ``` ts const lastMsgInChat = await getLastMessageInChat('123456@s.whatsapp.net') // implement this on your end await sock.chatModify({ delete: true, lastMessages: [{ key: lastMsgInChat.key, messageTimestamp: lastMsgInChat.messageTimestamp }] }, '123456@s.whatsapp.net') ``` - Pin/unpin a chat ``` ts await sock.chatModify({ pin: true // or `false` to unpin }, '123456@s.whatsapp.net') ``` - Star/unstar a message ``` ts await sock.chatModify({ star: { messages: [{ id: 'messageID', fromMe: true // or `false` }], star: true // - true: Star Message; false: Unstar Message }},'123456@s.whatsapp.net'); ``` **Note:** if you mess up one of your updates, WA can log you out of all your devices and you'll have to log in again. ## Disappearing Messages ``` ts const jid = '1234@s.whatsapp.net' // can also be a group // turn on disappearing messages await sock.sendMessage( jid, // this is 1 week in seconds -- how long you want messages to appear for { disappearingMessagesInChat: WA_DEFAULT_EPHEMERAL } ) // will send as a disappearing message await sock.sendMessage(jid, { text: 'hello' }, { ephemeralExpiration: WA_DEFAULT_EPHEMERAL }) // turn off disappearing messages await sock.sendMessage( jid, { disappearingMessagesInChat: false } ) ``` ## Misc - To check if a given ID is on WhatsApp ``` ts const id = '123456' const [result] = await sock.onWhatsApp(id) if (result.exists) console.log (`${id} exists on WhatsApp, as jid: ${result.jid}`) ``` - To query chat history on a group or with someone TODO, if possible - To get the status of some person ``` ts const status = await sock.fetchStatus("xyz@s.whatsapp.net") console.log("status: " + status) ``` - To change your profile status ``` ts const status = 'Hello World!' await sock.updateProfileStatus(status) ``` - To change your profile name ``` ts const name = 'My name' await sock.updateProfileName(name) ``` - To get the display picture of some person/group ``` ts // for low res picture const ppUrl = await sock.profilePictureUrl("xyz@g.us") console.log("download profile picture from: " + ppUrl) // for high res picture const ppUrl = await sock.profilePictureUrl("xyz@g.us", 'image') ``` - To change your display picture or a group's ``` ts const jid = '111234567890-1594482450@g.us' // can be your own too await sock.updateProfilePicture(jid, { url: './new-profile-picture.jpeg' }) ``` - To remove your display picture or a group's ``` ts const jid = '111234567890-1594482450@g.us' // can be your own too await sock.removeProfilePicture(jid) ``` - To get someone's presence (if they're typing or online) ``` ts // the presence update is fetched and called here sock.ev.on('presence.update', json => console.log(json)) // request updates for a chat await sock.presenceSubscribe("xyz@s.whatsapp.net") ``` - To block or unblock user ``` ts await sock.updateBlockStatus("xyz@s.whatsapp.net", "block") // Block user await sock.updateBlockStatus("xyz@s.whatsapp.net", "unblock") // Unblock user ``` - To get a business profile, such as description or category ```ts const profile = await sock.getBusinessProfile("xyz@s.whatsapp.net") console.log("business description: " + profile.description + ", category: " + profile.category) ``` Of course, replace ``` xyz ``` with an actual ID. ## Groups - To create a group ``` ts // title & participants const group = await sock.groupCreate("My Fab Group", ["1234@s.whatsapp.net", "4564@s.whatsapp.net"]) console.log ("created group with id: " + group.gid) sock.sendMessage(group.id, { text: 'hello there' }) // say hello to everyone on the group ``` - To add/remove people to a group or demote/promote people ``` ts // id & people to add to the group (will throw error if it fails) const response = await sock.groupParticipantsUpdate( "abcd-xyz@g.us", ["abcd@s.whatsapp.net", "efgh@s.whatsapp.net"], "add" // replace this parameter with "remove", "demote" or "promote" ) ``` - To change the group's subject ``` ts await sock.groupUpdateSubject("abcd-xyz@g.us", "New Subject!") ``` - To change the group's description ``` ts await sock.groupUpdateDescription("abcd-xyz@g.us", "New Description!") ``` - To change group settings ``` ts // only allow admins to send messages await sock.groupSettingUpdate("abcd-xyz@g.us", 'announcement') // allow everyone to send messages await sock.groupSettingUpdate("abcd-xyz@g.us", 'not_announcement') // allow everyone to modify the group's settings -- like display picture etc. await sock.groupSettingUpdate("abcd-xyz@g.us", 'unlocked') // only allow admins to modify the group's settings await sock.groupSettingUpdate("abcd-xyz@g.us", 'locked') ``` - To leave a group ``` ts await sock.groupLeave("abcd-xyz@g.us") // (will throw error if it fails) ``` - To get the invite code for a group ``` ts const code = await sock.groupInviteCode("abcd-xyz@g.us") console.log("group code: " + code) ``` - To revoke the invite code in a group ```ts const code = await sock.groupRevokeInvite("abcd-xyz@g.us") console.log("New group code: " + code) ``` - To query the metadata of a group ``` ts const metadata = await sock.groupMetadata("abcd-xyz@g.us") console.log(metadata.id + ", title: " + metadata.subject + ", description: " + metadata.desc) ``` - To join the group using the invitation code ``` ts const response = await sock.groupAcceptInvite("xxx") console.log("joined to: " + response) ``` Of course, replace ``` xxx ``` with invitation code. - To get group info by invite code ```ts const response = await sock.groupGetInviteInfo("xxx") console.log("group information: " + response) ``` - To join the group using groupInviteMessage ``` ts const response = await sock.groupAcceptInviteV4("abcd@s.whatsapp.net", groupInviteMessage) console.log("joined to: " + response) ``` Of course, replace ``` xxx ``` with invitation code. - To get list request join ``` ts const response = await sock.groupRequestParticipantsList("abcd-xyz@g.us") console.log(response) ``` - To approve/reject request join ``` ts const response = await sock.groupRequestParticipantsUpdate( "abcd-xyz@g.us", // id group, ["abcd@s.whatsapp.net", "efgh@s.whatsapp.net"], "approve" // replace this parameter with "reject" ) console.log(response) ``` ## Privacy - To get the privacy settings ``` ts const privacySettings = await sock.fetchPrivacySettings(true) console.log("privacy settings: " + privacySettings) ``` - To update the LastSeen privacy ``` ts const value = 'all' // 'contacts' | 'contact_blacklist' | 'none' await sock.updateLastSeenPrivacy(value) ``` - To update the Online privacy ``` ts const value = 'all' // 'match_last_seen' await sock.updateOnlinePrivacy(value) ``` - To update the Profile Picture privacy ``` ts const value = 'all' // 'contacts' | 'contact_blacklist' | 'none' await sock.updateProfilePicturePrivacy(value) ``` - To update the Status privacy ``` ts const value = 'all' // 'contacts' | 'contact_blacklist' | 'none' await sock.updateStatusPrivacy(value) ``` - To update the Read Receipts privacy ``` ts const value = 'all' // 'none' await sock.updateReadReceiptsPrivacy(value) ``` - To update the Groups Add privacy ``` ts const value = 'all' // 'contacts' | 'contact_blacklist' | 'none' await sock.updateGroupsAddPrivacy(value) ``` - To update the Default Disappearing Mode ``` ts const duration = 86400 // 604800 | 7776000 | 0 await sock.updateDefaultDisappearingMode(duration) ``` ## Broadcast Lists & Stories Messages can be sent to broadcasts & stories. you need to add the following message options in sendMessage, like this: ```ts sock.sendMessage(jid, {image: {url: url}, caption: caption}, {backgroundColor : backgroundColor, font : font, statusJidList: statusJidList, broadcast : true}) ``` - the message body can be a extendedTextMessage or imageMessage or videoMessage or voiceMessage - You can add backgroundColor and other options in the message options - broadcast: true enables broadcast mode - statusJidList: a list of people that you can get which you need to provide, which are the people who will get this status message. - You can send messages to broadcast lists the same way you send messages to groups & individual chats. - Right now, WA Web does not support creating broadcast lists, but you can still delete them. - Broadcast IDs are in the format `12345678@broadcast` - To query a broadcast list's recipients & name: ``` ts const bList = await sock.getBroadcastListInfo("1234@broadcast") console.log (`list name: ${bList.name}, recps: ${bList.recipients}`) ``` ## Writing Custom Functionality Baileys is written with custom functionality in mind. Instead of forking the project & re-writing the internals, you can simply write your own extensions. First, enable the logging of unhandled messages from WhatsApp by setting: ``` ts const sock = makeWASocket({ logger: P({ level: 'debug' }), }) ``` This will enable you to see all sorts of messages WhatsApp sends in the console. Some examples: 1. Functionality to track the battery percentage of your phone. You enable logging and you'll see a message about your battery pop up in the console: ```{"level":10,"fromMe":false,"frame":{"tag":"ib","attrs":{"from":"@s.whatsapp.net"},"content":[{"tag":"edge_routing","attrs":{},"content":[{"tag":"routing_info","attrs":{},"content":{"type":"Buffer","data":[8,2,8,5]}}]}]},"msg":"communication"} ``` The "frame" is what the message received is, it has three components: - `tag` -- what this frame is about (eg. message will have "message") - `attrs` -- a string key-value pair with some metadata (contains ID of the message usually) - `content` -- the actual data (eg. a message node will have the actual message content in it) - read more about this format [here](/src/WABinary/readme.md) You can register a callback for an event using the following: ``` ts // for any message with tag 'edge_routing' sock.ws.on(`CB:edge_routing`, (node: BinaryNode) => { }) // for any message with tag 'edge_routing' and id attribute = abcd sock.ws.on(`CB:edge_routing,id:abcd`, (node: BinaryNode) => { }) // for any message with tag 'edge_routing', id attribute = abcd & first content node routing_info sock.ws.on(`CB:edge_routing,id:abcd,routing_info`, (node: BinaryNode) => { }) ``` Also, this repo is now licenced under GPL 3 since it uses [libsignal-node](https://git.questbook.io/backend/service-coderunner/-/merge_requests/1)

Lightweight full-featured typescript/javascript WhatsApp Web API

fundamentalvision/BEVFormer

<div align="center"> # BEVFormer: a Cutting-edge Baseline for Camera-based Detection </div> https://user-images.githubusercontent.com/27915819/161392594-fc0082f7-5c37-4919-830a-2dd423c1d025.mp4 > **BEVFormer: Learning Bird's-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformers**, ECCV 2022 > - [Paper in arXiv](http://arxiv.org/abs/2203.17270) | [Paper in Chinese](https://drive.google.com/file/d/1dKnD6gUHhBXZ8gT733cIU_A7dHEEzNTP/view?usp=sharing) | [OpenDriveLab](https://opendrivelab.com/) > - [Slides in English](https://docs.google.com/presentation/d/1fTjuSKpj_-KRjUACr8o5TbKetAXlWrmpaorVvfCTZUA/edit?usp=sharing) | [Occupancy and BEV Perception Talk Slides](https://docs.google.com/presentation/d/1U7wVi2_zJxM-EMqLVqC4zJ12ItUgS7ZcsXp7zQ1fkvc/edit?usp=sharing) > - [Blog in Chinese](https://www.zhihu.com/question/521842610/answer/2431585901) | [Video Talk](https://www.bilibili.com/video/BV12t4y1t7Lq?share_source=copy_web) and [Slides](https://docs.google.com/presentation/d/1NNeikhDPkgT14G1D_Ih7K3wbSN0DkvhO9wlAMx3CIcM/edit?usp=sharing) (in Chinese) > - [BEV Perception Survey](https://arxiv.org/abs/2209.05324) (Accepted by PAMI) | [Github repo](https://github.com/OpenDriveLab/BEVPerception-Survey-Recipe) # News - [2022/6/16]: We added two BEVformer configurations, which require less GPU memory than the base version. Please pull this repo to obtain the latest codes. - [2022/6/13]: We release an initial version of BEVFormer. It achieves a baseline result of **51.7%** NDS on nuScenes. - [2022/5/23]: 🚀🚀Built on top of BEVFormer, **BEVFormer++**, gathering up all best practices in recent SOTAs and our unique modification, ranks **1st** on [Waymo Open Datast 3D Camera-Only Detection Challenge](https://waymo.com/open/challenges/2022/3d-camera-only-detection/). We will present BEVFormer++ on CVPR 2022 Autonomous Driving [Workshop](https://cvpr2022.wad.vision/). - [2022/3/10]: 🚀BEVFormer achieve the SOTA on [nuScenes Detection Task](https://nuscenes.org/object-detection?externalData=all&mapData=all&modalities=Camera) with **56.9% NDS** (camera-only)! </br> # Abstract In this work, the authors present a new framework termed BEVFormer, which learns unified BEV representations with spatiotemporal transformers to support multiple autonomous driving perception tasks. In a nutshell, BEVFormer exploits both spatial and temporal information by interacting with spatial and temporal space through predefined grid-shaped BEV queries. To aggregate spatial information, the authors design a spatial cross-attention that each BEV query extracts the spatial features from the regions of interest across camera views. For temporal information, the authors propose a temporal self-attention to recurrently fuse the history BEV information. The proposed approach achieves the new state-of-the-art **56.9\%** in terms of NDS metric on the nuScenes test set, which is **9.0** points higher than previous best arts and on par with the performance of LiDAR-based baselines. # Methods  # Getting Started - [Installation](docs/install.md) - [Prepare Dataset](docs/prepare_dataset.md) - [Run and Eval](docs/getting_started.md) # Model Zoo | Backbone | Method | Lr Schd | NDS| mAP|memroy | Config | Download | | :---: | :---: | :---: | :---: | :---:|:---:| :---: | :---: | | R50 | BEVFormer-tiny_fp16 | 24ep | 35.9|25.7 | - |[config](projects/configs/bevformer_fp16/bevformer_tiny_fp16.py) |[model](https://github.com/zhiqi-li/storage/releases/download/v1.0/bevformer_tiny_fp16_epoch_24.pth)/[log](https://github.com/zhiqi-li/storage/releases/download/v1.0/bevformer_tiny_fp16_epoch_24.log) | | R50 | BEVFormer-tiny | 24ep | 35.4|25.2 | 6500M |[config](projects/configs/bevformer/bevformer_tiny.py) |[model](https://github.com/zhiqi-li/storage/releases/download/v1.0/bevformer_tiny_epoch_24.pth)/[log](https://github.com/zhiqi-li/storage/releases/download/v1.0/bevformer_tiny_epoch_24.log) | | [R101-DCN](https://github.com/zhiqi-li/storage/releases/download/v1.0/r101_dcn_fcos3d_pretrain.pth) | BEVFormer-small | 24ep | 47.9|37.0 | 10500M |[config](projects/configs/bevformer/bevformer_small.py) |[model](https://github.com/zhiqi-li/storage/releases/download/v1.0/bevformer_small_epoch_24.pth)/[log](https://github.com/zhiqi-li/storage/releases/download/v1.0/bevformer_small_epoch_24.log) | | [R101-DCN](https://github.com/zhiqi-li/storage/releases/download/v1.0/r101_dcn_fcos3d_pretrain.pth) | BEVFormer-base | 24ep | 51.7|41.6 |28500M |[config](projects/configs/bevformer/bevformer_base.py) | [model](https://github.com/zhiqi-li/storage/releases/download/v1.0/bevformer_r101_dcn_24ep.pth)/[log](https://github.com/zhiqi-li/storage/releases/download/v1.0/bevformer_r101_dcn_24ep.log) | | [R50](https://drive.google.com/file/d/1JTVcrFcOFdPp7rtZ6K__SfF0Np15vXL7/view?usp=sharing) | BEVformerV2-t1-base | 24ep | 42.6 | 35.1 | 23952M |[config](projects/configs/bevformerv2/bevformerv2-r50-t1-base-24ep.py) | [model/log](https://drive.google.com/drive/folders/1nts_1XxAagCEN_Ub7W2f-507SiDdVS_u?usp=sharing) | | [R50](https://drive.google.com/file/d/1JTVcrFcOFdPp7rtZ6K__SfF0Np15vXL7/view?usp=sharing) | BEVformerV2-t1-base | 48ep | 43.9 | 35.9 | 23952M |[config](projects/configs/bevformerv2/bevformerv2-r50-t1-base-48ep.py) | [model/log](https://drive.google.com/drive/folders/1nts_1XxAagCEN_Ub7W2f-507SiDdVS_u?usp=sharing) | | [R50](https://drive.google.com/file/d/1JTVcrFcOFdPp7rtZ6K__SfF0Np15vXL7/view?usp=sharing) | BEVformerV2-t1 | 24ep | 45.3 | 38.1 | 37579M |[config](projects/configs/bevformerv2/bevformerv2-r50-t1-24ep.py) | [model/log](https://drive.google.com/drive/folders/1uVzQCJq6gYbRLhBde09yzEBeU5l1hAxk?usp=sharing) | | [R50](https://drive.google.com/file/d/1JTVcrFcOFdPp7rtZ6K__SfF0Np15vXL7/view?usp=sharing) | BEVformerV2-t1 | 48ep | 46.5 | 39.5 | 37579M |[config](projects/configs/bevformerv2/bevformerv2-r50-t1-48ep.py) | [model/log](https://drive.google.com/drive/folders/1uVzQCJq6gYbRLhBde09yzEBeU5l1hAxk?usp=sharing) | | [R50](https://drive.google.com/file/d/1JTVcrFcOFdPp7rtZ6K__SfF0Np15vXL7/view?usp=sharing) | BEVformerV2-t2 | 24ep | 51.8 | 42.0 | 38954M |[config](projects/configs/bevformerv2/bevformerv2-r50-t2-24ep.py) | [model/log](https://drive.google.com/drive/folders/1bSyuFWxfJSIidGV7bC8jx2NR7idRN9-s?usp=sharing) | | [R50](https://drive.google.com/file/d/1JTVcrFcOFdPp7rtZ6K__SfF0Np15vXL7/view?usp=sharing) | BEVformerV2-t2 | 48ep | 52.6 | 43.1 | 38954M |[config](projects/configs/bevformerv2/bevformerv2-r50-t2-48ep.py) | [model/log](https://drive.google.com/drive/folders/1bSyuFWxfJSIidGV7bC8jx2NR7idRN9-s?usp=sharing) | | [R50](https://drive.google.com/file/d/1JTVcrFcOFdPp7rtZ6K__SfF0Np15vXL7/view?usp=sharing) | BEVformerV2-t8 | 24ep | 55.3 | 46.0 | 40392M |[config](projects/configs/bevformerv2/bevformerv2-r50-t8-24ep.py) | [model/log](https://drive.google.com/drive/folders/1Ml_usx5BNx43CFH1Di2OTazuzSyAlBto?usp=sharing) | The Baidu Driver Link for (BEVFormerV2 model and log)[https://pan.baidu.com/s/1ynzlAt1DQbH8NkqmisatTw?pwd=fdcv] is here. # Catalog - [ ] BEVFormerV2 HyperQuery - [ ] BEVFormerV2 Optimization, including memory, speed, inference. - [x] BEVFormerV2 Release - [ ] BEV Segmentation checkpoints - [ ] BEV Segmentation code - [x] 3D Detection checkpoints - [x] 3D Detection code - [x] Initialization # Bibtex If this work is helpful for your research, please consider citing the following BibTeX entry. ``` @article{li2022bevformer, title={BEVFormer: Learning Bird’s-Eye-View Representation from Multi-Camera Images via Spatiotemporal Transformers}, author={Li, Zhiqi and Wang, Wenhai and Li, Hongyang and Xie, Enze and Sima, Chonghao and Lu, Tong and Qiao, Yu and Dai, Jifeng} journal={arXiv preprint arXiv:2203.17270}, year={2022} } @article{Yang2022BEVFormerVA, title={BEVFormer v2: Adapting Modern Image Backbones to Bird's-Eye-View Recognition via Perspective Supervision}, author={Chenyu Yang and Yuntao Chen and Haofei Tian and Chenxin Tao and Xizhou Zhu and Zhaoxiang Zhang and Gao Huang and Hongyang Li and Y. Qiao and Lewei Lu and Jie Zhou and Jifeng Dai}, journal={ArXiv}, year={2022}, } ``` # Acknowledgement Many thanks to these excellent open source projects: - [dd3d](https://github.com/TRI-ML/dd3d) - [detr3d](https://github.com/WangYueFt/detr3d) - [mmdet3d](https://github.com/open-mmlab/mmdetection3d) ### &#8627; Stargazers [](https://github.com/fundamentalvision/BEVFormer/stargazers) ### &#8627; Forkers [](https://github.com/fundamentalvision/BEVFormer/network/members)

[ECCV 2022] This is the official implementation of BEVFormer, a camera-only framework for autonomous driving perception, e.g., 3D object detection and semantic map segmentation.

deep-learning,autonomous-driving,computer-vision,object-detection

devcontainers/spec

# Development Containers This repository is for the Development Container Specification. You can check out the spec on our website https://containers.dev/ too. A development container allows you to use a container as a full-featured development environment. It can be used to run an application, to separate tools, libraries, or runtimes needed for working with a codebase, and to aid in continuous integration and testing. The Development Container Specification seeks to find ways to enrich existing formats with common development specific settings, tools, and configuration while still providing a simplified, un-orchestrated single container option – so that they can be used as coding environments or for continuous integration and testing.  The first format in the specification, `devcontainer.json`, was born out of necessity. It is a structured JSON with Comments (jsonc) metadata format that tools can use to store any needed configuration required to develop inside of local or cloud-based containerized coding. We envision that this same structured data can be embedded in images and other formats – all while retaining a common object model for consistent processing. For example, some of this same metadata can be added to a `devcontainer.metadata` image label to tie settings directly to a container image. Beyond repeatable setup, these same development containers provide consistency to avoid environment specific problems across developers and centralized build and test automation services. You can use the [open-source CLI reference implementation](https://github.com/devcontainers/cli) either directly or integrated into product experiences to use the structured metadata to deliver these benefits. It currently supports integrating with Docker Compose and a simplified, un-orchestrated single container option – so that they can be used as coding environments or for continuous integration and testing. A GitHub Action and an Azure DevOps Task are available in [devcontainers/ci](https://github.com/devcontainers/ci) for running a repository's dev container in continuous integration (CI) builds. This allows you to reuse the same setup that you are using for local development to also build and test your code in CI. ### Spec content You may review the specification in the [docs/specs folder](https://github.com/devcontainers/spec/tree/main/docs/specs) of this repo. You may also review active proposals in the [proposals folder](https://github.com/devcontainers/spec/tree/main/proposals). Images used in this repo will be contained in the [images folder](/images). The icon for the [dev container GitHub org](https://github.com/devcontainers) is from the [Fluent icon library](https://github.com/microsoft/fluentui-system-icons/blob/master/assets/Cube/SVG/ic_fluent_cube_32_filled.svg). ## Contributing and Feedback If you are interested in contributing, please check out the [How to Contribute](contributing.md) document, open an issue, or [join our community Slack channel](https://aka.ms/dev-container-community). Please report issues in the following repositories: - Spec-maintained Features and Templates: [devcontainers/features](https://github.com/devcontainers/features), [devcontainers/templates](https://github.com/devcontainers/templates) - CLI reference implementation and non-spec related feature requests: [devcontainers/cli](https://github.com/devcontainers/cli) - GitHub Action and Azure DevOps Task: [devcontainers/ci](https://github.com/devcontainers/ci) # License License for this repository: Copyright © Microsoft Corporation All rights reserved.<br /> Creative Commons Attribution 4.0 License (International): https://creativecommons.org/licenses/by/4.0/legalcode

Development Containers: Use a container as a full-featured development environment.

containers,devcontainers

bitnami/containers

<p align="center"> <img width="400px" height=auto src="https://bitnami.com/downloads/logos/bitnami-by-vmware.png" /> </p> <p align="center"> <a href="https://twitter.com/bitnami"><img src="https://badgen.net/badge/twitter/@bitnami/1DA1F2?icon&label" /></a> <a href="https://github.com/bitnami/containers"><img src="https://badgen.net/github/stars/bitnami/containers?icon=github" /></a> <a href="https://github.com/bitnami/containers"><img src="https://badgen.net/github/forks/bitnami/containers?icon=github" /></a> <a href="https://github.com/bitnami/containers/actions/workflows/ci-pipeline.yml"><img src="https://github.com/bitnami/containers/actions/workflows/ci-pipeline.yml/badge.svg" /></a> </p> # The Bitnami Containers Library Popular applications, provided by [Bitnami](https://bitnami.com), containerized and ready to launch. ## Why use Bitnami Images? * Bitnami closely tracks upstream source changes and promptly publishes new versions of this image using our automated systems. * With Bitnami images the latest bug fixes and features are available as soon as possible. * Bitnami containers, virtual machines, and cloud images use the same components and configuration approach - making it easy to switch between formats based on your project needs. * All our images are based on [**minideb**](https://github.com/bitnami/minideb) -a minimalist Debian-based container image that gives you a small base container image and the familiarity of a leading Linux distribution- or **scratch** -an explicitly empty image-. * All Bitnami images available in Docker Hub are signed with [Notation](https://notaryproject.dev/). [Check this post](https://blog.bitnami.com/2024/03/bitnami-packaged-containers-and-helm.html) to know how to verify the integrity of the images. * Bitnami container images are released regularly with the latest distribution packages available. Looking to use our applications in production? Try [VMware Tanzu Application Catalog](https://bitnami.com/enterprise), the enterprise edition of Bitnami Application Catalog. ## Get an image The recommended way to get any of the Bitnami Images is to pull the prebuilt image from the [Docker Hub Registry](https://hub.docker.com/r/bitnami/). ```console docker pull bitnami/APP ``` To use a specific version, you can pull a versioned tag. ```console docker pull bitnami/APP:[TAG] ``` If you wish, you can also build the image yourself by cloning the repository, changing to the directory containing the Dockerfile, and executing the `docker build` command. ```console git clone https://github.com/bitnami/containers.git cd bitnami/APP/VERSION/OPERATING-SYSTEM docker build -t bitnami/APP . ``` > Remember to replace the `APP`, `VERSION`, and `OPERATING-SYSTEM` placeholders in the example command above with the correct values. ## Run the application using Docker Compose The main folder of each application contains a functional `docker-compose.yml` file. Run the application using it as shown below: ```console curl -sSL https://raw.githubusercontent.com/bitnami/containers/main/bitnami/APP/docker-compose.yml > docker-compose.yml docker-compose up -d ``` > Remember to replace the `APP` placeholder in the example command above with the correct value. ## Vulnerability scan in Bitnami container images As part of the release process, the Bitnami container images are analyzed for vulnerabilities. At this moment, we are using two different tools: * [Trivy](https://github.com/aquasecurity/trivy) * [Grype](https://github.com/anchore/grype) This scanning process is triggered via a GH action for every PR affecting the source code of the containers, regardless of its nature or origin. ## Retention policy Deprecated assets will be retained in the container registry ([Bitnami DockerHub org](https://hub.docker.com/u/bitnami)) without changes for, at least, 6 months after the deprecation. After that period, all the images will be moved to a new _"archived"_ repository. For instance, once deprecated an asset named _foo_ whose container repository was `bitnami/foo`, all the images will be moved to `bitnami/foo-archived` where they will remain indefinitely. Special images, like `bitnami/bitnami-shell` or `bitnami/sealed-secrets`, which are extensively used in Helm charts, will have an extended coexistence period of 1 year. ## Contributing We'd love for you to contribute to those container images. You can request new features by creating an [issue](https://github.com/bitnami/containers/issues/new/choose), or submit a [pull request](https://github.com/bitnami/containers/pulls) with your contribution. ## License Copyright &copy; 2024 Broadcom. The term "Broadcom" refers to Broadcom Inc. and/or its subsidiaries. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at <http://www.apache.org/licenses/LICENSE-2.0> Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

Bitnami container images

bitnami,containers,docker,non-root,docker-image,vmware

Moataz-Elmesmary/Data-Science-Roadmap

<img align="center" width="730" height="720" src="https://github.com/Moataz-Elmesmary/Data-Science-Roadmap/assets/92026137/95f2d5a6-990b-46cf-90c1-098059a9c706"> <h2>&emsp;&emsp;&emsp;&emsp; DATA SCIENCE ROADMAP :pirate_flag: 2024 </h2> ### Data Science Roadmap for anyone interested in how to break into the field! <h4><i>This repository is intended to provide a free Self-Learning Roadmap to learn the field of Data Science. I provide some of the best free resources.</i></h4><br> &emsp;&emsp;[Our Previous Roadmap](https://github.com/Seif-Mohamed1/DataScience-Squad) ♥️<br> &emsp;&emsp; :warning: <b>*Before we start,*</b> :warning: #### If you Dont know What`s Data Science or Projects Life Cycle (starting from Business Understanding to Deployment) or Which Programming Language you should go for or Job Descriptions or the required Soft & Hard Skills needed for this field or Data Science Applications or the Most Common Mistakes, then<br> ### :pushpin:**[This Video](https://www.youtube.com/watch?v=5zRvq7CG6Zw&t=5s) is for you (Highly Recommended :heavy_check_mark:)** <h2>Data Science vs Data Analytics vs Data Engineering - What's the Difference?</h2><br>  <h4><i>These terms are wrongly used interchangeably among people. There are distinct differences:</i></h4> | :small_orange_diamond: **Data Science** | :small_orange_diamond: **Data Analytics** | :small_orange_diamond: **Data Engineering** | | ------------- | --------------------- | -------------------- | |<h5>Is a multidisciplinary field that focuses on looking at raw and structured data sets and providing potential actionable insights. The field of Data Science looks at ensuring we are asking the right questions as opposed to finding exact answers. Data Scientist require skillsets that are centered on Computer Science, Mathematics, and Statistics. Data Scientist use several unique techniques to analyze data such as machine learning, trends, linear regressions, and predictive modeling. The tools Data Scientist use to apply these techniques include Python and R. </h5>|<h5> Focuses on looking at existing data sets and creating solutions to capture data, process data, and finally organize data to draw actionable insights. This field looks at finding general process, business, and engineering improvements we can make based on questions we don't know the answers to. Data Analytics require skillsets that are centered on Statistics, Mathematics, and high level understanding of Computer Science. It involves data cleaning, data visualization, and simple modeling. Common Data Analytic tools used include Microsoft Power Bi, Tableau, and SQL. </h5>|<h5> Focuses on creating the correct infrastructure and tools required to support the business. Data Engineers look at what are the optimal ways to store and extract data and involves writing scripts and building data warehouses. Data Engineering require skillsets that are centered on Software Engineering, Computer Science and high level Data Science. The tools Data Engineers utilize are mainly Python, Java, Scala, Hadoop, and Spark. </h5>| # Prepare your workspace <details><summary> <h3>Tip :one: : Pick one and stick to it. (:file_folder:Click)</h3> </summary> <br> [Anaconda](https://www.anaconda.com/products/distribution): It’s a tool kit that fulfills all your necessities in writing and running code. From Powershell prompt to Jupyter Notebook and PyCharm, even R Studio (if interested to try R)  [Atom](https://atom.io/packages/ide-python): A more advanced Python interface, highly recommended by experts. <br /> [Google Colab](https://colab.research.google.com/notebooks/intro.ipynb): It’s like a Jupyter Notebook but in the cloud. You don’t need to install anything locally. All the important libraries are already installed. For example NumPy, Pandas, Matplotlib, and Sci-kit Learn <br /> [PyCharm](https://www.jetbrains.com/): PyCharm is another excellent IDE that enables you to integrate with libraries such as NumPy and Matplotlib, allowing you to work with array viewers and interactive plots. <br /> [Thonny](https://thonny.org/): Thonny is an IDE for teaching and learning programming. Thonny is equipped with a debugger, and supports code completion, and highlights syntax errors.</details> Most learning platforms have integrated code exercises where you don’t need to install anything locally. But to learn it right, you should have an IDE installed on your local machine. Suggestions will be a marketplace with many options and few improvements from one platform to another. ### Tip :two: : Focus on one course at least. ### Tip :three: : Don’t chase certifications. ### Tip :four: : Don’t rush for ML without having a good background in programming & maths. ## This track is divided into 3 phases :arrow_down: : #### &emsp; 1. Beginner: you get a basic understanding of data analysis, tools and techniques. #### &emsp; 2. Intermediate: dive deeper in more complex topics of ML, Math and data engineering. #### &emsp; 3. Advanced: where we learn more advanced Math, DL and Deployment. :bell: For Data Camp courses, github student pack gives 3 free months. Google how to get it.<br> <i>if you already used it, do not hesitate to contact us to have an account with free access.:hibiscus:</i> ## Legend * :video_camera: Video Content * :closed_book: Online Article Content / Book ### 💡 Roadmap Explanation ▶️ [Youtube Video](https://youtu.be/HbIPJuvzRLk) :movie_camera:<img src="https://media.giphy.com/media/mBYkXvLxkHZFmqBHIC/giphy.gif" width=50px height=40px> *** ## 🔰 Beginner 🔰 [Algorithms Book](https://github.com/cjbt/Free-Algorithm-Books/blob/master/book/Grokking%20Algorithms%20-%20An%20illustrated%20guide%20for%20programmers%20and%20other%20curious%20people.pdf) <i>Every piece of code could be called an algorithm, but this book covers the more interesting bits.</i><br> [Specializations (data structures-algorithms)](https://www.coursera.org/specializations/data-structures-algorithms) **1. Descriptive Statistics** <img src="https://raw.githubusercontent.com/mrankitgupta/66DaysOfData/c8c040f1c85d921db317152567f331354446286a/statistics-21.svg" alt="Statistics" width="25" height="25"/> <br> &emsp;&emsp;&emsp;📹 [Intro to descriptive statistics](https://www.udacity.com/course/intro-to-descriptive-statistics--ud827) | Same Course [on YouTube](https://www.youtube.com/playlist?list=PLAwxTw4SYaPn22DmaF6x8JtG4TeWOJk_1)<br> &emsp;&emsp;&emsp;📹 [Statistics Fundamentals - StatQuest - Youtube](https://www.youtube.com/playlist?list=PLblh5JKOoLUK0FLuzwntyYI10UQFUhsY9)<br> &emsp;&emsp;&emsp;📕 [Online statistics education](http://onlinestatbook.com/Online_Statistics_Education.pdf)<br> &emsp;&emsp;&emsp;📕 Intro to descriptive statistics [Article1](https://medium.com/m/global-identity?redirectUrl=https%3A%2F%2Ftowardsdatascience.com%2Fdescriptive-statistics-f2beeaf7a8df) & [Article2](https://medium.com/m/global-identity?redirectUrl=https%3A%2F%2Ftowardsdatascience.com%2Fintro-to-descriptive-statistics-252e9c464ac9)<br> &emsp;&emsp;&emsp;📹 [Arabic Course](https://www.youtube.com/watch?v=d5jh5mmwcKI&list=PLY99ZSsxRyJiu6kb4WRRpeEFqK1pAr-EO)<br> &emsp;&emsp;&emsp;📹 [Intro to Inferential Statistics](https://www.udacity.com/course/intro-to-inferential-statistics--ud201)++<br> &emsp;&emsp;&emsp;📕 [Practical Statistics for Data Scientists](https://github.com/Moataz-Elmesmary/Data-Science-Roadmap/blob/main/Books/Practical%20Statistics%20for%20Data%20Scientists.pdf)<br> **2. Probability**<br> &emsp;&emsp;&emsp;📹 [Khan Academy](https://www.khanacademy.org/math/statistics-probability/probability-library)<br> &emsp;&emsp;&emsp;📹 [Arabic Course](https://www.youtube.com/playlist?list=PL158D091D26F47358)<br> &emsp;&emsp;&emsp;📕 [Introduction to Probability](https://drive.google.com/file/d/15Y0oFNHQRls1qvQNvO3DFLJVhIZvUjTD/view?usp=sharing)<br> **3. Programming Languages**<br> &emsp;🔹*R* - *good tool for visualization and statistical analysis.*<br> &emsp;&emsp;&emsp;📹 [Introduction to R (Datacamp)](https://www.datacamp.com/courses/free-introduction-to-r)<br> &emsp;&emsp;&emsp;📹 [Data Science Specialization - coursera](https://www.coursera.org/specializations/jhu-data-science)<br> &emsp;&emsp;&emsp;📕 [An Introduction to R](https://cran.r-project.org/doc/manuals/R-intro.pdf)<br> &emsp;&emsp;&emsp;📕 [R for Data Science](https://r4ds.had.co.nz/)<br> &emsp;🔹*Python*:100: <br> &emsp;&emsp;&emsp;📹 [Introduction to Python Programming](https://www.udacity.com/course/introduction-to-python--ud1110)<br> &emsp;&emsp;&emsp;📹 [OOP](https://learn.datacamp.com/courses/object-oriented-programming-in-python)<br> &emsp;&emsp;&emsp;📹 Arabic - [Hassouna](https://www.youtube.com/watch?v=MxYLqE3Ils8&list=PLHIfW1KZRIfnM9y0sQRwjVz2-IwvnEJep) | [Elzero](https://www.youtube.com/watch?v=mvZHDpCHphk&list=PLDoPjvoNmBAyE_gei5d18qkfIe-Z8mocs)<br> &emsp;&emsp;&emsp;📹 [Python Full Course - FreeCodeCamp on YouTube](https://www.youtube.com/watch?v=rfscVS0vtbw)<br> &emsp;&emsp;&emsp;📕 [Intro to Python for CS and Data Science](https://drive.google.com/file/d/1rXkYFjw1iKbXCra_B4Ykm0AMRgo6v93w/view?fbclid=IwAR2lg9omGaAsG3g1ZhHQHja8_uxkZ7QddnOUSxfoceRXShU1V_bl4V63xCQ)<br> &emsp;&emsp;&emsp;[more in OOP](https://www.futurelearn.com/courses/object-oriented-principles)<br> **4. Pandas**<br> &emsp;&emsp;&emsp;📹 [Corey Schafer-Youtube](https://www.youtube.com/watch?v=ZyhVh-qRZPA&list=PL-osiE80TeTsWmV9i9c58mdDCSskIFdDS)<br> &emsp;&emsp;&emsp;📕 [Kaggle](https://www.kaggle.com/learn/pandas)<br> &emsp;&emsp;&emsp;📕 [Docs](https://pandas.pydata.org/pandas-docs/version/0.15/tutorials.html)<br> &emsp;&emsp;&emsp;📹 [Data School-Youtube](https://www.youtube.com/watch?v=yzIMircGU5I&list=PL5-da3qGB5ICCsgW1MxlZ0Hq8LL5U3u9y&index=1)<br> &emsp;&emsp;&emsp;📹 [Arabic Course](https://www.youtube.com/watch?v=3ISW655DemU&list=PLvLvlVqNQGHCb2_ygmr1DQOMOv0yXp84F)<br> &emsp;&emsp;&emsp;📹 PandasAI🐼[1](https://www.youtube.com/watch?v=BtmMNZLxbuI) - [2](https://www.youtube.com/watch?v=5w6eZaoDVVk) *Enhances the capabilities of Pandas by integrating Generative AI functionalities into it.* <br> **5. Numpy**<br> &emsp;&emsp;&emsp;📕 [Kaggle](https://www.kaggle.com/legendadnan/numpy-tutorial-for-beginners-data-science) &emsp;<img src="https://raw.githubusercontent.com/mrankitgupta/mrankitgupta/2a582d085b324cff4917325112229027309ecae3/Numpy-logo.svg" alt="numpy" width="25" height="20"/><br> &emsp;&emsp;&emsp;📹 [Arabic Course](https://www.youtube.com/watch?v=5-5CrLmf2vk&list=PLIA_seGogbkGDYq-dnVCsELEIq_7HK7Ca)<br> &emsp;&emsp;&emsp;📕 [Tutorial](http://cs231n.github.io/python-numpy-tutorial/)<br> &emsp;&emsp;&emsp;📕 [Docs](https://numpy.org/doc/1.18/user/quickstart.html)<br> **6. Scipy**<br> &emsp;&emsp;&emsp;📕 [Tutorial](https://cs231n.github.io/python-numpy-tutorial/#scipy)<br> &emsp;&emsp;&emsp;📕 [Docs](https://docs.scipy.org/doc/scipy/reference/tutorial/general.html)<br> **7. Data Cleaning**: One of the **MOST** important skills that you need to master to become a good data scientist, you need to practice on many datasets to master it.<br> &emsp;&emsp;&emsp;[Read this](https://towardsdatascience.com/the-ultimate-guide-to-data-cleaning-3969843991d4)<br> &emsp;&emsp;&emsp;📹 [Course 1](https://www.datacamp.com/courses/cleaning-data-in-python)<br> &emsp;&emsp;&emsp;📕 [Notebook1](https://www.kaggle.com/bandiatindra/telecom-churn-prediction)<br/> &emsp;&emsp;&emsp;📕 [Notebook2](https://drive.google.com/drive/folders/1OQAEQ8rC4j6oBP7AyDU4bKpPr8sSStJI?fbclid=IwAR2dSrbyoZLM-Wm57yEYy8L8PmpPV9hqXdkNf-pURJC5C5xCz7UJB4YpJ7M)<br/> &emsp;&emsp;&emsp;📕 [Notebook3](https://www.kaggle.com/ashishg21/data-cleaning-and-some-analysis-shoe-prices)<br> &emsp;&emsp;&emsp;📕 [Kaggle Data cleaning](https://www.kaggle.com/learn/data-cleaning)<br> **8. Data Visualization** :bar_chart: <br> &emsp;&emsp;&emsp;📹 [Introduction to Data Visualization with Matplotlib](https://app.datacamp.com/learn/courses/introduction-to-data-visualization-with-matplotlib?fbclid=IwAR1OrJSdZ2LVD_c1o3d-_1I7Nhq8OZ3pzTu4010E_XWEmMc0KYsTosz8CIU) or<br> &emsp;&emsp;&emsp;📹 [ Corey Schafer - Playlist on Youtube](https://www.youtube.com/watch?v=UO98lJQ3QGI&list=PL-osiE80TeTvipOqomVEeZ1HRrcEvtZB_) or<br> &emsp;&emsp;&emsp;📹 [sentdex - Playlist on YouTube](https://www.youtube.com/watch?v=q7Bo_J8x_dw&list=PLQVvvaa0QuDfefDfXb9Yf0la1fPDKluPF)<br> &emsp;&emsp;&emsp;📕 [Kaggle to Data Visualization with Seaborn](https://www.kaggle.com/learn/data-visualization)<br> &emsp;&emsp;&emsp;📹 [Playlist-Youtube](https://www.youtube.com/watch?v=z7ZINBk8EUk&list=PL998lXKj66MpNd0_XkEXwzTGPxY2jYM2d)<br> &emsp;&emsp;&emsp;📹 [Course1: Intro to Data Visualization with Seaborn](https://learn.datacamp.com/courses/introduction-to-data-visualization-with-seaborn)<br> &emsp;&emsp;&emsp;📹 [Course2: Intermediate Data Visualization with Seaborn ](https://learn.datacamp.com/courses/intermediate-data-visualization-with-seaborn)<br> &emsp;&emsp;&emsp;📹 [Course3: Understanding and Visualizing with Python](https://www.coursera.org/learn/understanding-visualization-data)<br> **9. EDA** Note: it's already mentioned in the above probability course <br> &emsp;&emsp;&emsp;📹 [DataCamp-EDA in Python](https://learn.datacamp.com/courses/exploratory-data-analysis-in-python) <br> &emsp;&emsp;&emsp;📹 [IBM-EDA for Machine Learning](https://www.coursera.org/learn/ibm-exploratory-data-analysis-for-machine-learning) <br> **10. Dashboards**<br> &emsp;*Power BI*<br> &emsp;&emsp;&emsp;📹 [Power BI - Youtube (Alex)](https://youtube.com/playlist?list=PLUaB-1hjhk8HqnmK0gQhfmIdCbxwoAoys&si=pR4VSrR1P2O-AaBJ)<br> &emsp;&emsp;&emsp;📹 [Power BI training](https://powerbi.microsoft.com/en-us/learning/)<br> &emsp;&emsp;&emsp;📹 [Arabic - Youtube (Zanoon)](https://www.youtube.com/watch?v=P_Nr0FMyn9w&list=PL69umUTzySPGWMxnmhX9SV5PIEbdnHv63&index=1)<br> &emsp;&emsp;&emsp;📹 [Arabic - Youtube](https://www.youtube.com/watch?v=ykvAWKML9Gk&list=PLof3yw6ZFPFhV75Ptf-5Q88bgUtLOBvOw)<br> &emsp;*Tableau* <img src="https://raw.githubusercontent.com/mrankitgupta/mrankitgupta/a768d6bf0a001f03327578ae12f8867e4056cbaf/tableau-software.svg" alt="tableau" width="20" height="20"/><br> &emsp;&emsp;&emsp;📕 [Tutorial](https://www.datacamp.com/community/tutorials/data-visualisation-tableau)<br> &emsp;&emsp;&emsp;📹 [docs](https://www.tableau.com/learn/training/20201)<br> &emsp;&emsp;&emsp;📹 [course - datacamp](https://learn.datacamp.com/courses/introduction-to-tableau)<br> &emsp;&emsp;&emsp;📹 [Simplilearn - Youtube](https://learn.datacamp.com/courses/introduction-to-tableau)<br> **11. SQL and DB**<br> &emsp;&emsp;&emsp;📹 SQL for Data Analysis ([Udacity](https://www.udacity.com/course/sql-for-data-analysis--ud198)-notes[*l📋l*](https://github.com/julianjohannesen/Udacity-SQL-Notes/tree/main) or [simplilearn](https://www.simplilearn.com/free-online-course-to-learn-sql-basics-skillup))<br> &emsp;&emsp;&emsp;📹 [Intro to SQL](https://learn.datacamp.com/courses/introduction-to-sql) **or** [IBM (SQL for Data Science)](https://www.coursera.org/learn/sql-data-science)<br> &emsp;&emsp;&emsp;📹 [Intro to Relational Databases in SQL](https://learn.datacamp.com/courses/introduction-to-relational-databases-in-sql)<br> &emsp;&emsp;&emsp;📹 [Arabic Course](https://www.youtube.com/watch?v=B7evUQGmN6M&list=PLfM2wZNebA2zROxUcAbGxNrpVZncsF3oD)<br> &emsp;&emsp;&emsp;📹 [Arabic -ITI by Eng.Ramy](https://www.youtube.com/watch?v=QJHy89zMvj8&list=PLYpJKvLDuJhgMzOXRwUJ2_ZlVt3zSh8PA&index=1) *Advanced* - [[Course Materials]](https://drive.google.com/drive/folders/1P_uUWl6pBPC3MFrqR_ovoJQNCZhi9rAS?fbclid=IwAR1EyxPR3pLXABIcK2bkgh4_HYNSowb01Kij8OiHFh_x5maiqsiwvJNHvXg)<br> &emsp;&emsp;&emsp;📹 [365 Data Science - SQL](https://mega.nz/folder/wswGEIhb#tsqUggTZyfy5HyRWUkV9sg/folder/R1AxXCxB)<br> &emsp;&emsp;&emsp;📝 Practice [HackerRank](https://www.hackerrank.com/domains/sql) & [DataLemur](https://datalemur.com/) **12. Python Regular Expression**<br> &emsp;&emsp;&emsp;📕 [Tutorial](https://www.datacamp.com/community/tutorials/python-regular-expression-tutorial)<br> **13. Time Series Analysis**<br> &emsp;&emsp;&emsp;📹 [Track - DataCamp](https://learn.datacamp.com/skill-tracks/time-series-with-python)<br> &emsp;&emsp;&emsp;📹 [Course - Coursera](https://www.coursera.org/learn/practical-time-series-analysis)<br> &emsp;&emsp;&emsp;📕 [Book](https://www.oreilly.com/library/view/practical-time-series/9781492041641/?fbclid=IwAR20cq7hAdWf6voOd61u-pNzZCHvB0rZhT_BUoGTAXxPBhhi82p8BhxLEsI)<br> &emsp;&emsp;&emsp;📕 [fbprohet](https://facebook.github.io/prophet/docs/quick_start.html)<br> &emsp;&emsp;&emsp;📹 Arabic Source [Video1](https://www.youtube.com/watch?v=TvhaHPq6xLU&list=TLPQMjYwNzIwMjEPGXX6392WJA&index=1) & [Video2](https://www.youtube.com/watch?v=mipF7mRVpk0&list=TLPQMjYwNzIwMjEPGXX6392WJA&index=2)<br> <h4><i>At The end of Beginner phase apply all what you've learned on a project.</i></h4> *** ## 🔰 Intermediate 🔰 **1. Math for ML**: consists of Linear Algebra, Calculus and PCA. <br> 📹 [Mathematics for Machine Learning and Data Science - Andrew Ng](https://www.coursera.org/specializations/mathematics-for-machine-learning-and-data-science?irclickid=zzy33K1O0xyNUAmxqWUjDwedUkAUtSWUJXKyTY0&irgwc=1&utm_medium=partners&utm_source=impact&utm_campaign=3117765&utm_content=b2c#courses)<br> 📹 [Specialization](https://www.coursera.org/specializations/mathematics-machine-learning)<br> 📹 [Mathematics for Machine Learning - Most of the needed basics](https://www.youtube.com/watch?v=vLJcduC4lBM&list=PLcQCwsZDEzFmlSc6levE3UV9rZ8yY-D_7)<br><br> :small_blue_diamond:Linear Algebra<br> &emsp;&emsp;&emsp;📹 [Khan Academy - Linear Algebra](https://www.khanacademy.org/math/linear-algebra)<br> &emsp;&emsp;&emsp;📹 [Mathematics for Machine Learning: Linear Algebra](https://www.coursera.org/learn/linear-algebra-machine-learning)<br> &emsp;&emsp;&emsp;📹 [3Blue1Brown - Essence of Linear Algebra](https://www.3blue1brown.com/topics/linear-algebra)<br> :small_blue_diamond:Calculus<br> &emsp;&emsp;&emsp;📹 [Multivariate Calculus - Coursera](https://www.coursera.org/learn/multivariate-calculus-machine-learning?fbclid=IwAR243aoz0jxs4iUn539pnjSQliXtr7Y5QAsvgeRTietZT_tkyoRU3b6Sq1o)<br> &emsp;&emsp;&emsp;📹 [Essence of calculus - Youtube](https://www.youtube.com/playlist?list=PLZHQObOWTQDMsr9K-rj53DwVRMYO3t5Yr)<br> :small_blue_diamond:PCA<br> &emsp;&emsp;&emsp;📹 [PCA - Coursera](https://www.coursera.org/learn/pca-machine-learning)<br> **2. Machine Learning**<br> &emsp;&emsp;&emsp;📹 [Coursera - Old Course by Andrew Ng (Octave/Matlab)](https://www.coursera.org/learn/machine-learning)<br> &emsp;&emsp;&emsp;📹 [Coursera Andrew`s new ML Specialization (Python)](https://www.coursera.org/specializations/machine-learning-introduction?_hsenc=p2ANqtz-_R9x3Nm07uCw6YAw9VpCpdjRdfaUFyxdOcvgDljRt7j_NXiahN1plnI_Ob9jn0jSNipuE_Y08llrfPSt_1P7EBvj4LuImpBTKG3bsR6Z9bzjzBoRY&_hsmi=216611333&action=enroll&utm_campaign=mls-launch-2022&utm_content=216613012&utm_medium=email&utm_source=hs_email#courses)<br> &emsp;&emsp;&emsp;📹 [Machine Learning - StatQuest - YouTube](https://www.youtube.com/playlist?list=PLblh5JKOoLUICTaGLRoHQDuF_7q2GfuJF)<br> &emsp;&emsp;&emsp;📹 [Machine Learning Stanford Full Course on YouTube by Andrew](https://www.youtube.com/watch?v=PPLop4L2eGk&list=PLLssT5z_DsK-h9vYZkQkYNWcItqhlRJLN)<br> &emsp;&emsp;&emsp;📹 [CS480/680 Intro to Machine Learning - Spring 2019 - University of Waterloo](https://www.youtube.com/playlist?list=PLdAoL1zKcqTW-uzoSVBNEecKHsnug_M0k)<br> &emsp;&emsp;&emsp;📹 [SYDE 522 – Machine Intelligence (Winter 2018, University of Waterloo)](https://www.youtube.com/playlist?list=PL4upCU5bnihwCX93Gv6AQnKmVMwx4AZoT)<br> &emsp;&emsp;&emsp;📹 [Machine Learning for Engineers 2022](https://apmonitor.com/pds/) / ([YouTube](https://www.youtube.com/watch?v=Gh5rbBLh4JY&list=PLLBUgWXdTBDg1K1bu60lHypSzSP-WSBmx))<br> &emsp;&emsp;&emsp;📹 [Introduction to Machine Learning Course - Udacity](https://www.udacity.com/course/intro-to-machine-learning--ud120)<br> &emsp;&emsp;&emsp;📹 [Hesham Asem - Arabic content](https://www.youtube.com/c/HeshamAsem/playlists)<br> &emsp;&emsp;&emsp;📹 [IBM ML with Python](https://www.coursera.org/learn/machine-learning-with-python)<br> &emsp;&emsp;&emsp;📹 [Machine Learning From Scratch - YouTube (Python Engineer)](https://www.youtube.com/watch?v=ngLyX54e1LU&list=PLqnslRFeH2Upcrywf-u2etjdxxkL8nl7E)<br> &emsp;&emsp;&emsp;📕 Hands On ML ([1st](https://drive.google.com/file/d/1uro1p6SlYolSkF0fbFKau0pOQ9ENZqny/view?usp=sharing) & [2nd](https://drive.google.com/file/d/1rS95FTNfiVG4WjGnPjd73GqrmEKey4N1/view?usp=sharing) & [3rd](https://drive.google.com/file/d/11VeqPJw8s9SC9Ru7IVeQhiTyV_9TliOE/view?usp=sharing)) Editions | Code: [](https://github.com/ageron/handson-ml?fbclid=IwAR3s31KlwkLKyrEwuEd4UMOcvHN1Q9Z2LLGzPg5vP4UKSwjriHxU0uO405c)<br> &emsp;&emsp;&emsp;📹 [ML Algorithms in Practice](https://www.coursera.org/specializations/machine-learning-algorithms-real-world?utm_medium=email&utm_source=marketing&utm_campaign=A39CcMUuEempyReieZALEQ)<br> &emsp;&emsp;&emsp;📹 [ML scientist](https://learn.datacamp.com/career-tracks/machine-learning-scientist-with-python?version=1)<br> &emsp;&emsp;&emsp;📹 [Project](https://www.coursera.org/learn/applied-data-science-capstone)<br> **3. Web Scraping/APIs**<br> &emsp;&emsp;&emsp;📹 [course](https://learn.datacamp.com/courses/web-scraping-with-python)<br> &emsp;&emsp;&emsp;📕 [intro2](https://www.dataquest.io/blog/web-scraping-tutorial-python/)<br> &emsp;&emsp;&emsp;📕 [Tutorial](https://realpython.com/beautiful-soup-web-scraper-python/)<br> &emsp;&emsp;&emsp;📕 [Book for both topics](https://b-ok.africa/book/3515980/5d50aa)<br> APIs <br> &emsp;&emsp;&emsp;📕 [Tutorial](https://www.dataquest.io/blog/python-api-tutorial/)<br> &emsp;&emsp;&emsp;📕 [Article](https://medium.com/m/global-identity?redirectUrl=https%3A%2F%2Ftowardsdatascience.com%2Fhow-to-pull-data-from-an-api-using-python-requests-edcc8d6441b1)<br> &emsp;&emsp;&emsp;📕 [Tutorial](https://rapidapi.com/blog/how-to-use-an-api-with-python/)<br> **4. Stats.**<br> &emsp;&emsp;&emsp;📕 [This stats - Book](https://greenteapress.com/thinkstats/thinkstats.pdf)<br> &emsp;&emsp;&emsp;📕 [Think Bayes - Book](https://www.greenteapress.com/thinkbayes/thinkbayes.pdf)<br> **5. Advanced SQL**<br> &emsp;&emsp;&emsp;📹 [Joining Data in SQL - DataCamp](https://learn.datacamp.com/courses/joining-data-in-postgresql)<br> &emsp;&emsp;&emsp;📹 [Intermediate SQL - DataCamp](https://learn.datacamp.com/courses/joining-data-in-postgresql)<br> &emsp;&emsp;&emsp;📹 [More advanced SQL](https://www.coursera.org/lecture/data-driven-astronomy/more-advanced-sql-GDmo5)<br> **7. Feature Engineering**<br> &emsp;&emsp;&emsp;📕 [Tutorial](https://www.kaggle.com/learn/feature-engineering)<br> &emsp;&emsp;&emsp;📕 [Article](https://www.medium.com/m/global-identity?redirectUrl=https%3A%2F%2Ftowardsdatascience.com%2Ffeature-engineering-for-machine-learning-3a5e293a5114)<br> &emsp;&emsp;&emsp;📕 [Book](https://drive.google.com/file/d/1BkJYO0tqMYptTWUDQ7X0vd2aygohHRm8/view?usp=sharing)<br> **8. interpet Shapley-based explanations of ML models.**<br/> &emsp;&emsp;&emsp;📕 [SHAP](https://shap.readthedocs.io/en/latest/)<br/> &emsp;&emsp;&emsp;📕 [Kaggle ML explainability](https://www.kaggle.com/learn/machine-learning-explainability)<br/> <h4><i>After finishing this level apply to 2 or 3 good sized projects.</i></h4> <i>Read this book, please</i> :open_book: [Introduction to Statistical Learning with Applications in R](https://github.com/Moataz-Elmesmary/Data-Science-Roadmap/blob/main/Introduction%20to%20Statistical%20Learning%20with%20Applications%20in%20R.pdf) بقولك اقرأه<img src="https://c.tenor.com/SOVMSXmWB1kAAAAi/tony-star-jumping.gif" width="35"><br> *** ## 🔰 Advanced 🔰 **1. Deep Learning** <br> &emsp;&emsp;&emsp;📹 [Deep Learning Fundamentals](https://www.youtube.com/playlist?list=PLZbbT5o_s2xq7LwI2y8_QtvuXZedL6tQU)<br> &emsp;&emsp;&emsp;📹 [Introduction to Deep Learning - MIT](http://introtodeeplearning.com/?fbclid=IwAR35rIygYlCn84DV7mlHvdvs4sMUm2D6RLYVwFpp2nT2t1Zj1GGy3QAWQvQ)<br> &emsp;&emsp;&emsp;📹 [Specialization](https://www.coursera.org/specializations/deep-learning)<br> &emsp;&emsp;&emsp;📕 [Dive into Deep Learning (En)](https://d2l.ai/d2l-en.pdf?fbclid=IwAR0sVdA8VFYpNZCpYZHgo_kl_HYrjcjDfjEka26D8xRWAhbhh6mmSNIXg3U) | (Ar) version :arrow_right:[Part1](https://drive.google.com/file/d/1SrmT_r8dNK42IqyS0gwXtbLCZbk5G8eu/view?fbclid=IwAR1Xcf8PNKkPJMg0uHRE1QyIW4_BMxISIdoB8pPaepw38njhaIf04MYM218) & [Part2](https://drive.google.com/file/d/1UqEu0amRfAvJD0L1HosIn3UJi0FkNemU/view?fbclid=IwAR1og8pkWr1gT3jdUwqikCZVrOCpyrm0x6ZRL63Kitwhki35pazHdo_ScJI) <br> &emsp;&emsp;&emsp;📹 [Deep Learning UC Berkely](https://www.youtube.com/playlist?list=PLZSO_6-bSqHQHBCoGaObUljoXAyyqhpFW)<br> &emsp;&emsp;&emsp;📕 [github of Dive into DL](https://github.com/d2l-ai/d2l-en?fbclid=IwAR0QN35b-NHHWq_zKISA1cbI063aRqqoKqR_0e3cpnT5h58GkcNbCIJs3iw)<br> &emsp;&emsp;&emsp;📹 [Stanford Lecture - Convolutional Neural Networks for Visual Recognition](https://www.youtube.com/watch?v=vT1JzLTH4G4&list=PL3FW7Lu3i5JvHM8ljYj-zLfQRF3EO8sYv)<br> &emsp;&emsp;&emsp;📹 [University of Waterloo - ML / DL](https://www.youtube.com/playlist?list=PLdAoL1zKcqTW-uzoSVBNEecKHsnug_M0k)<br> &emsp;&emsp;&emsp;📕 [Deep Learning for coders with fastai & PyTorch](https://dl.ebooksworld.ir/books/Deep.Learning.for.Coders.with.fastai.and.PyTorch.Howard.Gugger.OReilly.9781492045526.EBooksWorld.ir.pdf)<br> **2. Tensorflow**<br> &emsp;&emsp;&emsp;📹 [Specialization](https://www.coursera.org/specializations/tensorflow-in-practice)<br> &emsp;&emsp;&emsp;📹 [Youtube](https://www.youtube.com/playlist?list=PLZbbT5o_s2xrwRnXk_yCPtnqqo4_u2YGL)<br> &emsp;&emsp;&emsp; [fast.ai's Deep Learning Courses](https://www.fast.ai/)<br> ###### <i>TensorFlow beats PyTorch in visualization capabilities and deploying trained models. Go for PyTorch if you want flexibility, debugging capabilities, and short training duration.</i> **3. PyTorch**<br> &emsp;&emsp;&emsp;📹 [PyTorch (UC Berkeley - Youtube) - Lec3 (The 5 parts)](https://m.youtube.com/watch?v=AOypIa_8RXg&list=PL_iWQOsE6TfXxKgI1GgyV1B_Xa0DxE5eH&index=11)<br> &emsp;&emsp;&emsp;📹 [PyTorch - Dr. Data Science - Youtube](https://www.youtube.com/watch?v=vVQs4h6HUvA&list=PLLeO8f6PhlKb_FAC7qxOBtxT9-8EPDAqk)<br> &emsp;&emsp;&emsp;📹 [Pytorch Tutorial - Aladdin - Youtube](https://www.youtube.com/watch?v=2S1dgHpqCdk&list=PLhhyoLH6IjfxeoooqP9rhU3HJIAVAJ3Vz)<br> &emsp;&emsp;&emsp;📹 [PyTorch Course (2022) - Youtube](https://www.youtube.com/watch?v=v43SlgBcZ5Y&list=PLkdGijFCNuVk9fO1IMfdV1Igob0FUHhkB)<br> &emsp;&emsp;&emsp;📕 [Deep Learning With Pytorch](https://drive.google.com/file/d/1-KG_ufeg7zw2iLgG5RrJSFpyonLwulgF/view?usp=sharing)<br> &emsp;&emsp;&emsp;📕 [Machine Learning with PyTorch and Scikit-Learn -2022](https://dl.ebooksworld.ir/books/Machine.Learning.with.PyTorch.and.Scikit-Learn.Sebastian.Raschka.Packt.9781801819312.EBooksWorld.ir.pdf)<br> **4. Advanced Data Science**<br> &emsp;&emsp;&emsp;📹 [Advanced Data Science with IBM Specialization](https://www.coursera.org/specializations/advanced-data-science-ibm) *Includes Apache Spark*<br> &emsp;☠️*Advanced ML Topics🧠 | Lecs (YouTube)* <br> &emsp;&emsp;&emsp;📹 [Stanford CS330: Deep Multi-Task and Meta Learning I Autumn 2022](https://www.youtube.com/playlist?list=PLoROMvodv4rNjRoawgt72BBNwL2V7doGI) - [Materials](https://cs330.stanford.edu/)<br> &emsp;&emsp;&emsp;📹 [18.409 Algorithmic Aspects of Machine Learning Spring 2015 - MIT](https://www.youtube.com/playlist?list=PLB3sDpSRdrOvI1hYXNsa6Lety7K8FhPpx)<br> &emsp;☠️*ML based Computer Vision | Lecs (YouTube)* <br> &emsp;&emsp;&emsp;📹 [CS 198-126: Modern Computer Vision Fall 2022 (UC Berkeley)](https://www.youtube.com/playlist?list=PLzWRmD0Vi2KVsrCqA4VnztE4t71KnTnP5)<br> &emsp;&emsp;&emsp;📹 [NOC:Deep Learning For Visual Computing - IIT Kharagpur](https://nptel.ac.in/courses/108105103)<br> &emsp;&emsp;&emsp;📹 [Deep Learning for Computer Vision - Michigan](https://www.youtube.com/playlist?list=PL5-TkQAfAZFbzxjBHtzdVCWE0Zbhomg7r)<br> **5. NLP** <br> &emsp;&emsp;&emsp;📹 [Specialization - Coursera](https://www.coursera.org/specializations/natural-language-processing)<br> &emsp;&emsp;&emsp;📹 [Arabic - Ahmed El Sallab](https://www.youtube.com/playlist?list=PLxmZ0b-n395VxzEUL8-Dy257zSqYZe4yU)<br> &emsp;&emsp;&emsp;📹 [Stanford CS224N Lectures - Winter 2021- YouTube](https://www.youtube.com/playlist?app=desktop&list=PLoROMvodv4rMFqRtEuo6SGjY4XbRIVRd4&si=k91y-bepIiPjHMrj&fbclid=IwAR2h6KcYboHCjG9YBIEB08srgYSesqZ5UHXr0ni8yxOqrxNV3-_TGxq0Csg)<br> &emsp;&emsp;&emsp;📹 [Stanford XCS224U Lectures - Spring 2021- YouTube](https://www.youtube.com/playlist?app=desktop&list=PLoROMvodv4rMFqRtEuo6SGjY4XbRIVRd4&si=k91y-bepIiPjHMrj&fbclid=IwAR2h6KcYboHCjG9YBIEB08srgYSesqZ5UHXr0ni8yxOqrxNV3-_TGxq0Csg)<br> &emsp;&emsp;&emsp;📹 [Introduction to Natural Language Processing in Python](https://www.datacamp.com/courses/natural-language-processing-fundamentals-in-python)<br> &emsp;🔸*LLMS [What`s Large Language Model](https://www.snowflake.com/guides/what-large-language-model-and-what-can-llms-do-data-science)?* <br> &emsp;&emsp;&emsp;📹 [Generative AI for Everyone (Andrew Nj) - Coursera](https://www.coursera.org/learn/generative-ai-for-everyone?utm_campaign=genai4e-launch&utm_medium=institutions&utm_source=deeplearning-ai#modules)🆕<br> &emsp;&emsp;&emsp;📹 [Generative AI with LLMs](https://www.deeplearning.ai/courses/generative-ai-with-llms/)<br> &emsp;&emsp;&emsp;📹 [LLM Foundations](https://fullstackdeeplearning.com/llm-bootcamp/spring-2023/llm-foundations/)<br> &emsp;&emsp;&emsp;📹 How ChatGPTs / Transformers work?[1](https://www.youtube.com/watch?v=bQ5BoolX9Ag) - [2](https://jalammar.github.io/how-gpt3-works-visualizations-animations/) - [3](https://jalammar.github.io/illustrated-transformer/) *overview & Maths behind*<br> &emsp;&emsp;&emsp;📹 [Prompt Engineering](https://fullstackdeeplearning.com/llm-bootcamp/spring-2023/prompt-engineering/) | ([Ar](https://www.youtube.com/watch?v=A-sNuzZgY8g&list=PLvLvlVqNQGHDNUshQJBWWCIRGgC0PN7VL)) *If you want to get the most out of LLMs*<br> &emsp;&emsp;&emsp;📹 [LLMOps](https://fullstackdeeplearning.com/llm-bootcamp/spring-2023/llmops/) *A Lec going through the entire LLM pipeline*<br> **6. Inferential Statistics** <br> &emsp;&emsp;&emsp;📹 [Specialization, 2nd & 3rd courses](https://www.coursera.org/specializations/statistics-with-python)<br> &emsp;&emsp;&emsp;📹 [course](https://www.coursera.org/learn/statistical-inferences)<br> **7. Bayesian Statistics**<br> &emsp;&emsp;&emsp;📹 [1 - From Concept to Data Analysis](https://www.coursera.org/learn/bayesian-statistics)<br> &emsp;&emsp;&emsp;📹 [2 - Techniques and Models](https://www.coursera.org/learn/mcmc-bayesian-statistics)<br> &emsp;&emsp;&emsp;📹 [3 - Mixture Models](https://www.coursera.org/learn/mixture-models)<br> **8. Model Deployment** <br> &emsp;&emsp;&emsp;📕 [Flask tutorial](https://towardsdatascience.com/deploying-a-deep-learning-model-using-flask-3ec166ef59fb)<br> &emsp;&emsp;&emsp;📹 [TensorFlow: Data and Deployment Specialization](https://www.coursera.org/specializations/tensorflow-data-and-deployment)<br> &emsp;&emsp;&emsp;📹 [Deploy Models with TensorFlow Serving and Flask](https://www.coursera.org/projects/deploy-models-tensorflow-serving-flask)<br> &emsp;&emsp;&emsp;📹 [How to Deploy a Machine Learning Model to Google Cloud - Daniel Bourke](https://www.youtube.com/watch?v=fw6NMQrYc6w)<br> &emsp;&emsp;&emsp;if you`re interested in more deployment methods, search for (_FastAPI - Heroku - chitra_)<br> **9. MLOps** : is a combination of Model Deployment, Model Serving, Model Monitoring, and Model Maintenance. &emsp;&emsp;&emsp;🔗 [MLOps-zoomcamp](https://github.com/DataTalksClub/mlops-zoomcamp)<br> &emsp;&emsp;&emsp;🔗 [MLOps-guide](https://github.com/Nyandwi/machine_learning_complete/blob/main/010_mlops/1_mlops_guide.md)<br> &emsp;&emsp;&emsp;📕 [Practical MLOps](https://drive.google.com/file/d/17RhXQ2ix6rFMaas3HI7bnM_GL8lS7u3f/view?usp=sharing)<br> **10. Probabilistic Graphical Models** &emsp;&emsp;&emsp;📹 [Specialization - Coursera](https://www.coursera.org/specializations/probabilistic-graphical-models)<br> &emsp;&emsp;&emsp;📹 [Spring 2016, University of Utah - YouTube](https://www.youtube.com/playlist?list=PLbuogVdPnkCpvxdF-Gy3gwaBObx7AnQut)<br> <p align="center"> <img src="https://i.imgur.com/dBaSKWF.gif" height="20" width="100%"> :star2: <i>Read these books, they will be beneficial to you.</i><br> &emsp; :open_book: [Bayesian Reasoning and Machine Learning](https://drive.google.com/file/d/18fh0orqSNAaIyhLkVwh9cGuWBywCBbuw/view?usp=sharing)<br> &emsp; :open_book: [The Elements of Statistical Learning](https://drive.google.com/file/d/1ePRkuB9Zm5Fkw-1-VG8prQXfj8pI6dWX/view?usp=sharing)<br> &emsp; :open_book: [Pattern Recognition and Machine Learning - Bishop](https://drive.google.com/file/d/1QkQj_azL6O7qUzshB8lPzueYWj0TRwEu/view?usp=sharing) (Advanced)<br> ##### &emsp;&emsp; <i> Recommended by [Eng.Mohamed Hammad](https://www.linkedin.com/posts/mohamed-hammad-a720a622_%D9%83%D8%AA%D8%A7%D8%A8-%D9%83%D9%84-%D9%85%D8%B1%D9%87-%D8%A7%D8%AD%D8%AA%D8%A7%D8%AC%D9%87-%D9%88%D8%A7%D8%B1%D8%AC%D8%B9%D9%84%D9%87-%D8%A7%D8%A8%D9%82%D9%8A-%D8%B9%D8%A7%D9%88%D8%B2-%D9%83%D9%84-%D8%A7%D9%84%D9%84%D9%8A-activity-7080526619525693441-nNn0?utm_source=share&utm_medium=member_desktop).</i> <img src="https://media.giphy.com/media/mBYkXvLxkHZFmqBHIC/giphy.gif" width=50px height=40px> *** <img align="right" width="309" height="250" src="https://github.com/Moataz-Elmesmary/Data-Science-Roadmap/assets/92026137/60cd8545-7720-499a-8e08-6d6dda50ee62"> <h3> 📌PROJECTS ⏬</h3><br> &emsp;&emsp;&emsp;🎥[Deena Gergis - End to end Project](https://www.youtube.com/playlist?list=PLatl6hdtJ0RnbkReSAuel6PeCPO155FpG)<br> &emsp;&emsp;&emsp;🎥[Machine Learning Projects - Youtube](https://www.youtube.com/watch?v=fiz1ORTBGpY&list=PLfFghEzKVmjvuSA67LszN1dZ-Dd_pkus6)<br> &emsp;&emsp;&emsp;💻[Top 10 Data Science Projects for Beginners](https://www.kdnuggets.com/2021/06/top-10-data-science-projects-beginners.html)<br> &emsp;&emsp;&emsp;💻[12 Data Science Projects for Beginners and Experts](https://builtin.com/data-science/data-science-projects)<br> &emsp;&emsp;&emsp;💻[Data Science Projects & Ideas](https://nevonprojects.com/data-science-projects-solutions/)<br> &emsp;&emsp;&emsp;💻[Top 310+ Machine Learning Projects for 2023](https://data-flair.training/blogs/machine-learning-project-ideas/)<br> &emsp;&emsp;&emsp;💻[10 End-to-End Guided Data Science Projects](https://pub.towardsai.net/10-end-to-end-guided-data-science-projects-to-build-your-portfolio-b7b9047fe6c9)<br> &emsp;&emsp;&emsp;🎥[Real-World ML Tutorial w/ Scikit Learn](https://www.youtube.com/watch?v=M9Itm95JzL0)<br> &emsp;&emsp;&emsp;💻[Python Codes in Data Science](https://github.com/RubensZimbres/Repo-2017/)<br> &emsp;&emsp;&emsp;🎥[End To End ML Project With Dockers,Github Actions And Deployment](https://www.youtube.com/watch?v=MJ1vWb1rGwM)<br> &emsp;&emsp;&emsp;💻[12 free Data Science projects to practice Python and Pandas (resolve interactive online)](https://www.datawars.io/articles/12-free-data-science-projects-to-practice-python-and-pandas)<br> *** <h3>📌 Common Tools ⤵️</h3><br> <img align="right" width="158" height="85" src="https://github.com/Moataz-Elmesmary/Data-Science-Roadmap/assets/92026137/38a970a5-e723-4831-bc35-153c228beebf"> English | Arabic | Book --- | --- | --- :movie_camera: [Git - Udacity](https://www.udacity.com/course/version-control-with-git--ud123) | :movie_camera: [شخبط وانت مطمن ](https://www.youtube.com/watch?v=Q6G-J54vgKc)🚀 | :closed_book: [Pro Git](https://git-scm.com/book/en/v2) 📖 [w3schools](https://www.w3schools.com/git/) | :movie_camera: [almadrasa](https://almdrasa.com/tracks/programming-foundations/courses/git-github/) &emsp; | :movie_camera: [Elzero](https://www.youtube.com/playlist?list=PLDoPjvoNmBAw4eOj58MZPakHjaO3frVMF) *** ### :pushpin: **More Books :atom::atom: [:pushpin: Check This!](https://drive.google.com/drive/folders/1iW7IPrVUqsHumgXUMH_rgeBLpJjRDCmJ?usp=sharing)** <br> <img align="right" width="309" height="250" src="https://github.com/Moataz-Elmesmary/Data-Science-Roadmap/assets/92026137/b41c09b2-47c4-4ee3-b932-eb14b1c243bf"> &emsp;&emsp;📕 [:fire: <b>12</b> Free Important Books :fire:](https://github.com/Moataz-Elmesmary/Data-Science-Roadmap/tree/main/Books)<br> &emsp;&emsp;📕 [Mathematics for Machine Learning ](https://mml-book.github.io/)<br> &emsp;&emsp;📕 [An Introduction to Statistical Learning](https://www.statlearning.com/)<br> &emsp;&emsp;📕 [Understanding ML: From Theory to Algorithms ](https://www.cs.huji.ac.il/~shais/UnderstandingMachineLearning/understanding-machine-learning-theory-algorithms.pdf)<br> &emsp;&emsp;📕 [Probabilistic Machine Learning: An Introduction](https://probml.github.io/pml-book/book1.html)<br> &emsp;&emsp;📕 [storytelling with data](https://drive.google.com/file/d/1OQu6ZWImGnHbuI_WJOLPdSvKWCABSWMH/view?usp=sharing) ✔️Important data visualization guide.<br> *** <details> <summary> <h3> :pushpin: <b>Collection of the best Cheat sheets</b></h3></summary> 1. [Importing Data](https://lnkd.in/e3jnyTEi) 2. Pandas &emsp;&emsp; - [(1)](https://lnkd.in/eiXuBbWh_) &emsp;&emsp; - [(2)](https://lnkd.in/e8PKwQQQ) &emsp;&emsp; - [(3)](https://lnkd.in/ewQfqe8q) 3. [Matplotlib](https://lnkd.in/ejxbW8ak) 4. [Seaborn](https://lnkd.in/ejhxUp2K) 5. [Probability](https://lnkd.in/e4Jxx6xP) 6. [Supervised Learning](https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/cheatsheet-supervised-learning.pdf) 7. [Unsupervised Learning](https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/cheatsheet-unsupervised-learning.pdf) 8. [Deep Learning](https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/cheatsheet-deep-learning.pdf) 9. [Machine Learning Tips and Tricks](https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/cheatsheet-machine-learning-tips-and-tricks.pdf) 10. [Probabilities and Statistics](https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/refresher-probabilities-statistics.pdf) 11. [Comprehensive Stanford Master Cheat Sheet](https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/super-cheatsheet-machine-learning.pdf) 12. [Linear Algebra and Calculus](https://github.com/afshinea/stanford-cs-229-machine-learning/blob/master/en/refresher-algebra-calculus.pdf) 13. [Data Science Cheat Sheet](https://s3.amazonaws.com/assets.datacamp.com/blog_assets/PythonForDataScience.pdf) 14. [Keras Cheat Sheet](https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Keras_Cheat_Sheet_Python.pdf) 15. [Deep Learning with Keras Cheat Sheet](https://github.com/rstudio/cheatsheets/raw/master/keras.pdf) 16. [Visual Guide to Neural Network Infrastructures](http://www.asimovinstitute.org/wp-content/uploads/2016/09/neuralnetworks.png) 17. [Skicit-Learn Python Cheat Sheet](https://s3.amazonaws.com/assets.datacamp.com/blog_assets/Scikit_Learn_Cheat_Sheet_Python.pdf) 18. [Scikit-learn Cheat Sheet: Choosing the Right Estimator](https://scikit-learn.org/stable/tutorial/machine_learning_map/) 19. [Tensorflow Cheat Sheet](https://github.com/kailashahirwar/cheatsheets-ai/blob/master/PDFs/Tensorflow.pdf) 20. [Machine Learning Test Cheat Sheet](https://www.cheatography.com/lulu-0012/cheat-sheets/test-ml/pdf/) 21. [Machine Learning Cheat Sheets (Recommended Guide)](https://drive.google.com/file/d/1rQRJvWk5s9rUCesri0apxutbF4eDHR69/view?usp=sharing) *راجع المواضيع اللي في الشيت دي يا عزيزي وشوف اللي ناقصك* </details> *** ### The best way to practice is to take part in competitions. <img src="https://media.tenor.com/0ENB5HuTH0gAAAAi/trophy-beker.gif" width="30px" height="30px"><img src="https://media.tenor.com/0ENB5HuTH0gAAAAi/trophy-beker.gif" width="30px" height="30px"> <br> **Competitions will make you even more proficient in Data Science.**<br> When we talk about top data science competitions, [**Kaggle**](https://www.kaggle.com/) is one of the most popular platforms for data science. Kaggle has a lot of competitions where you can participate according to your knowledge level.<br> **You can also check these platforms for data science competitions-**<br> - [Driven Data](https://www.drivendata.org/competitions/)<br> - [Codalab](https://competitions.codalab.org/)<br> - [Iron Viz](https://www.tableau.com/community/iron-viz)<br> - [Topcoder](https://www.topcoder.com/challenges)<br> - [CrowdANALYTIX Community](https://www.crowdanalytix.com/community)<br> - [Bitgrit](https://bitgrit.net/)<br> *** <b> 📓 Data Science Interview Questions: </b> :arrow_forward: &emsp; - [(1)](https://github.com/youssefHosni/Data-Science-Interview-Questions) &emsp;- [(2)](https://github.com/alexeygrigorev/data-science-interviews) &emsp;- [(3)](https://github.com/rbhatia46/Data-Science-Interview-Resources) &emsp;- [(4)](https://github.com/iamtodor/data-science-interview-questions-and-answers) &emsp;- [(5)](https://github.com/milaan9/DataScience_Interview_Questions) &emsp;- [(6) Arabic Podcast](https://www.youtube.com/watch?v=YjloQOreudk):headphones:<br> &emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;&emsp;- [(7) 30 days of interview preparation](https://github.com/Moataz-Elmesmary/Data-Science-Roadmap/blob/main/30%20days%20of%20interview%20preparation.pdf):book: *** <img align="right" width="190" height="145" src="https://github.com/Moataz-Elmesmary/Data-Science-Roadmap/assets/92026137/251a2659-c71e-4051-b431-2e93f8ce4187"> <details><summary>🎧<b>Data Science Podcasts: 🎙️</b><br> <i>The Best Way to Stay Up-to-Date on the Latest Data Science Trends and Developments</i><img src="https://github.com/TheDudeThatCode/TheDudeThatCode/blob/master/Assets/Rocket.gif" width="29px"></summary> <br> Podcasts | About | Produced by -- | --------------------------- | -- [Data Science at Home](https://datascienceathome.com/)|A podcast that provides practical advice and tutorials on data science topics.|Greg Linhardt, a data scientist and machine learning engineer at Google AI [Data Stories](https://datastori.es/)|An interview-driven podcast that tells the stories of data scientists and how they're using their skills to make a difference in the world.| Kirill Eremenko, a data scientist and machine learning engineer at Netflix [O'Reilly Data Show](https://www.oreilly.com/radar/topics/oreilly-data-show-podcast/)|A podcast that covers a wide range of data science topics, from machine learning to artificial intelligence to big data.|Ben Lorica, the Chief Data Scientist at O'Reilly [Learning Machines 101](https://www.learningmachines101.com/) |Mathematics, statistics, and algorithms that power the machine learning systems that we rely on every day.|Richard Golden, a machine learning engineer and researcher at Google AI [Data Engineering Podcast](https://www.dataengineeringpodcast.com/) |Tools, techniques, and difficulties associated with the discipline of data engineering. Databases, workflows, automation, and data manipulation.|Tobias Macey, a data engineer at Netflix [Data Science Mixer](https://community.alteryx.com/t5/Data-Science-Mixer/bg-p/mixer) |A great resource for anyone who wants to learn more about data science and the latest trends in the field. It is also a great way to get inspired by the work of other data scientists and machine learning engineers.|Alteryx, a data science and analytics software company [Chai Time Data Science Show](https://www.youtube.com/playlist?list=PLLvvXm0q8zUbiNdoIazGzlENMXvZ9bd3x) |Interviews top data scientists, practitioners, and researchers from around the world.|Sanyam Bhutani, a data scientist and machine learning engineer at Google AI. [Becoming a Data Scientist](https://www.becomingadatascientist.com/category/podcast/)|Podcast that interviews data scientists about their journey to becoming a data scientist.|Renee Teate, a data scientist and machine learning engineer at Google AI. [AI Today Podcast](https://www.aidatatoday.com/aitoday/)|Explores the latest trends and developments in artificial intelligence.|Ron Schmelzer and Kathleen Walch [Gradient Dissent](https://wandb.ai/fully-connected/podcast)|A weekly podcast that explores the latest research in machine learning and artificial intelligence.|Chris Olah, a machine learning engineer at Google AI [Data Skeptic](https://dataskeptic.com/)|A podcast that challenges the conventional wisdom in data science and asks tough questions about the ethics and implications of data-driven decision making.|Kyle Polich, a data scientist and machine learning engineer [Linear Digressions](https://lineardigressions.com/)|A podcast that covers a wide range of data science topics, from the technical to the theoretical.|Ben Recht and Noah Smith, two machine learning researchers at the University of California, Berkeley [The Data Engineering Show](https://www.dataengineeringshow.com/)|For data engineering and BI practitioners to go beyond theory, and learn from the biggest influencers in tech about their practical day to day data challenges.|Eldad Farkash and Benjamin Wagner, who are both data engineering experts with experience at companies like Firebolt and Sisense [DataTalks.Club](https://podcasters.spotify.com/pod/show/datatalksclub)|A weekly online community of data enthusiasts and practitioners that learn from each other and share their knowledge and experiences through meetups, workshops, and a podcast.|A rotating cast of data experts [Datacast](https://jameskle.com/writes/category/Datacast)|Top data scientists and practitioners in the data and AI infrastructure space.|James Le, who is a data infrastructure expert with experience at companies like Google and Netflix [How to Get an Analytics Job Podcast](https://www.youtube.com/playlist?list=PLBvzkZLydYX0D28bbnfRCV6M4zMQrhXsd)|A great resource for anyone who is interested in a career in analytics. The guests share their insights and advice on how to get started in analytics and how to succeed in an analytics career.|John David Ariansen, an analytics agency owner and career coach [The Analytics Power Hour](https://analyticshour.io/)|Five awesome people, an occasional guest, and drinks all around tackling the hottest data and analytics topics of the day.|Tim Wilson, Michael Helbling, Josh Crowhurst, and Val Kroll. They are all analytics experts from different companies </details> <br> <details><summary>&emsp;&emsp;&emsp; :eyes: Arabic Podcasts??</summary> ###### &emsp;&emsp;&emsp;&emsp; :trollface:شايفك ياللي زهقان في المواصلات &emsp;&emsp;&emsp;📻[Arabic Data Podcast](https://www.youtube.com/@arabic_data_podcast) | [Spotify](https://open.spotify.com/show/6xo79RT4NP73wQA39TgAq1) by Eng. Kareem Abdelsalam<br> &emsp;&emsp;&emsp;📻[lإلي البيانات وما بعدها](https://www.youtube.com/watch?v=3znPvz6P2oM&list=PL9yAM5pvSfU5EdppOCf-YvttRsabeAmbN) by Eng. Youssef Hosni<br> &emsp;&emsp;&emsp;📻[Garage Education](https://www.youtube.com/@GarageEducation/playlists) by Eng. Mostafa Alaa<br> &emsp;&emsp;&emsp;📻[Data Science بالعربي](https://www.boomplay.com/podcasts/29169)<br> </details> *** :pushpin: **Data Analysis Recommendations.**<br> <img align="right" width="150" height="150" src="https://github.com/Moataz-Elmesmary/Data-Science-Roadmap/assets/92026137/653458d5-74a4-4f75-a676-6cb714395656"> Books (📕 [The Data Analysis Workshop](https://drive.google.com/file/d/1BjKsffA2SCY0jY8OIIzgQgM0ZS7E9v_v/view?fbclid=IwAR2_GBlrX7VYoo8WCRO9R2qqrYEqtytoGrObxy1QHWcQ7sRaFjRLb0GmuxM) & 📕 [Head First Data Analysis](https://drive.google.com/file/d/1HXHkwrgsSJLYSeB6I0wPUXIGGnm2-HQ6/view?fbclid=IwAR27M-dlPN6o0YuZg3bXH6_DP9L2fBhkKDEkChvO4SPG-SXfkxrzuoGP5RM))<br> [FWD - (The 3 Levels)](https://egfwd.com/?fbclid=IwAR1phYmHHgi0L4E9nOPZcSfAdHWsDs9EvBh3dJgO6gXN4B1A-nV8vspGggs)<br> [Google Data Analytics Professional Certificate](https://www.coursera.org/professional-certificates/google-data-analytics)<br> [IBM Data Analyst Professional Certificate](https://www.coursera.org/professional-certificates/ibm-data-analyst?fbclid=IwAR1IajEEe2yydVWRt3hbj4qLioXP6oR-fdbw8f1kHAVpAXSA4Z8Eww1Y-fs)<br> [Google Advanced Data Analytics Professional Certificate :new:](https://www.coursera.org/professional-certificates/google-advanced-data-analytics?irclickid=zzy33K1O0xyNUAmxqWUjDwedUkAQlBwwJ21EwA0&irgwc=1&utm_medium=partners&utm_source=impact&utm_campaign=2624140&utm_content=b2c)<br> [Alex The Analyst - YouTube📺](https://www.youtube.com/@AlexTheAnalyst/playlists)<br> *Note: A good knowledge & projects in just [Excel](https://www.coursera.org/learn/excel-basics-data-analysis-ibm), SQL & Power BI / Tableau can bring you great opportunities*.<br> &emsp;&emsp;-<img src="https://raw.githubusercontent.com/mrankitgupta/66DaysOfData/60139fb461ef56a19afd68ea4094f6069f27ce49/icons8-microsoft-excel%20(1).svg" alt="excel" width="25" height="25"/> Excel More Resources: ([Arabic 1📹](https://www.youtube.com/watch?v=9Z5MPeyuLhg&t=397s) - [Arabic 2📹](https://www.youtube.com/watch?v=uRs8_EJqTFo&list=PLXlHqMRg9lAYiiutr-Ou0J1uU20T-5a4-&pp=iAQB) - [Books :page_facing_up: and cheat sheets for revising](https://drive.google.com/drive/folders/1CAUKDb5jv1pMez1WO74ogkpX44UMW_ky))<br> <p align="center"> <img src="https://i.imgur.com/dBaSKWF.gif" height="20" width="100%"> :pushpin: **[Data Engineering](https://youtu.be/qWru-b6m030) Recommendations.**<br> Books (📕 [Fundamentals of Data Engineering](https://drive.google.com/file/d/1CbQFN0Lw8o6v4KlF64LsCyaooMccT45T/view?usp=sharing) & 📕 [Designing Data-Intensive Applications](https://drive.google.com/file/d/1CrzA--WWNcxxQwLqzg1yPfiI3FaEo49z/view?usp=sharing))<br> <img align="right" width="150" height="150" src="https://github.com/Moataz-Elmesmary/Data-Science-Roadmap/assets/92026137/aafc7a10-a8a1-4204-a9f4-9b8cefccf718"> Arabic Podcast, [Starting a Career in Data Engineering.](https://www.youtube.com/watch?v=OtaBhXjrbX4)<br> For Arab, I recommend 2 YouTube Channels: ([Garage Education](https://www.youtube.com/@GarageEducation) & [Big Data بالعربي](https://www.youtube.com/playlist?list=PLrooD4hY1QqAK5pbBpcthLuMa-cXnXJLE))<br> [Roadmap 1](https://github.com/OmarEhab007/Data_Engineering_Mentorship) - *(Recommended)*<br> [Roadmap 2](https://www.educba.com/data-engineer-roadmap/)<br> [Roadmap 3](https://github.com/datastacktv/data-engineer-roadmap)<br> [IBM Data Engineering Professional Certificate](https://www.coursera.org/professional-certificates/ibm-data-engineer)<br> *Note: A good knowledge & projects in SQL, Python, Apache [Spark](https://www.udacity.com/course/learn-spark-at-udacity--ud2002)/Hadoop, Data Modeling and [[Data Warehouse](https://www.coursera.org/learn/dwdesign) - {Arabic-[Starting from the 7th video](https://www.youtube.com/playlist?list=PLxNoJq6k39G_m6DYjpz-V92DkaQEiXxkF)} can bring you great opportunities. Start with them then go for the other tools,concepts and cloud platforms*.<br> *** <details><summary>:file_folder: <b>CV / Resumes :memo: </b> &emsp; <img src="https://media.giphy.com/media/WUlplcMpOCEmTGBtBW/giphy.gif" width="75"> <a href="https://git.io/typing-svg"> <img src="https://readme-typing-svg.herokuapp.com/?lines=فاكرني+هسيبك+تهبده+؟؟&size=17"> </summary> - [Common mistakes by Yehia Arafa Mostafa](https://www.facebook.com/yehia.arafa.mostafa/posts/110086229517000)<br> - [CV Tips by Omar Yasser](https://medium.com/@oyaraouf/cv-tips-5faaec55ec07)<br> - [This Is What A GOOD Resume Should Look Like by careercup](https://www.careercup.com/resume)<br> - After you have made your beta-version resume, check those [reviews from Mostafa Nageeb](https://www.facebook.com/story.php?story_fbid=2928705840553931&id=445112032246670)<br> - [After Graduation by Yasser Alaa](https://www.linkedin.com/feed/update/urn:li:activity:6964595411839799296/)<br> - [How to make Data Science Resume](https://enhancv.com/resume-examples/data-scientist/)<br> - [Data Science Resume Guide](https://www.beamjobs.com/resumes/data-science-resume-example-guide)<br> - Resume/CV building for Data Jobs (Arabic)<br> &emsp;&emsp;📹[Video 1](https://www.youtube.com/watch?v=R0hsJiNxdDE)<br> &emsp;&emsp;📹[Video 2](https://www.youtube.com/watch?v=CrTO0hrC-zQ) </details> *** :pushpin: [<b><i>Data & AI Companies in Egypt</i></b>](https://trello.com/b/u4HH9Anu/data-ai-jobs-in-egypt) &emsp; - &emsp; [<i>AI/ML Driven Companies In Egypt</i>](https://github.com/harryadel/AI-ML-Driven-Companies-In-Egypt) *** <h2>Contact Me :iphone:</h2> <br> <a href="https://www.facebook.com/MoatazElmesmary/" title="Facebook"><img src="https://img.shields.io/badge/Facebook-%234267B2?style=flat&logo=Facebook&logoColor=white"/></a> <a href="https://twitter.com/MoatazElmesmary" title="twitter"><img src="https://img.shields.io/twitter/url?label=twitter&style=social&url=https%3A%2F%2Fimg.shields.io%2Ftwitter%2F%3Flabel%3Dtwitter%26style%3Dsocial"/></a> <a href="https://www.linkedin.com/in/MoatazElmesmary/" title="LinkedIn"><img src="https://img.shields.io/badge/LinkedIn-%230177B5?style=flat&logo=linkedin&logoColor=white"/></a><h1 align="center"> [](https://git.io/typing-svg)</h1>

Data Science Roadmap from A to Z

data-analysis,data-engineering,data-science,data-visualization,deep-learning,machine-learning,mathematics,probability,python,sql

zan8in/afrog

<p align="center"> <a href="http://afrog.net"><img src="images/afrog-logo.svg" width="60px" alt="afrog"></a> </p> <!-- </a> <h1 align="center">afrog</h1> --> <h4 align="center">A Security Tool for Bug Bounty, Pentest and Red Teaming</h4> <p align="center"> <img src="https://img.shields.io/github/go-mod/go-version/zan8in/afrog?filename=go.mod"> <a href="https://github.com/zan8in/afrog/releases"><img src="https://img.shields.io/github/downloads/zan8in/afrog/total"> <a href="https://github.com/zan8in/afrog/graphs/contributors"><img src="https://img.shields.io/github/contributors-anon/zan8in/afrog"> <a href="https://github.com/zan8in/afrog/releases/"><img src="https://img.shields.io/github/release/zan8in/afrog"> <a href="https://github.com/zan8in/afrog/issues"><img src="https://img.shields.io/github/issues-raw/zan8in/afrog"> <a href="https://github.com/zan8in/afrog/discussions"><img src="https://img.shields.io/github/discussions/zan8in/afrog"> </p> <p align="center" dir="auto"> <a href="https://github.com/zan8in/afrog/releases">Download</a> • <a href="https://github.com/zan8in/afrog/wiki">Wiki</a> • <a href="https://github.com/zan8in/afrog/blob/main/afrog-helper-function.md">Helper Function</a> </p> ## PoC Contributors <div><table frame=void> <tr> <td align="center"> <img src="https://images.weserv.nl/?url=raw.githubusercontent.com/zan8in/afrog/main/images/contributors/1.png&mask=circle&w=60&h=60" alt="Typora-Logo" /> <br> <a href="https://blog.csdn.net/U_U520">_不动明王</a> </td> <td align="center"> <img src="https://images.weserv.nl/?url=raw.githubusercontent.com/zan8in/afrog/main/images/contributors/2.png&mask=circle&w=60&h=60" alt="Typora-Logo" /> <br> <a href="https://www.linuxlz.com/">_雪山</a> </td> <td align="center"> <img src="https://images.weserv.nl/?url=raw.githubusercontent.com/zan8in/afrog/main/images/contributors/3.png&mask=circle&w=60&h=60" alt="Typora-Logo" /> <br> <a href="https://github.com/White-hua">_White-hua</a> </td> <td align="center"> <img src="https://images.weserv.nl/?url=raw.githubusercontent.com/zan8in/afrog/main/images/contributors/5.png&mask=circle&w=60&h=60" alt="Typora-Logo" /> <br> <a href="javascript:void(0)">₁₂₃₄₅₆</a> </td> <td align="center"> <img src="https://images.weserv.nl/?url=raw.githubusercontent.com/zan8in/afrog/main/images/contributors/6.png&mask=circle&w=60&h=60" alt="Typora-Logo" /> <br> <a href="https://github.com/ifofor">_ifofor</a> </td> <td align="center"> <img src="https://images.weserv.nl/?url=raw.githubusercontent.com/zan8in/afrog/main/images/contributors/7.png&mask=circle&w=60&h=60" alt="Typora-Logo" /> <br> <a href="https://github.com/SkinAir">_Air</a> </td> <td align="center"> <img src="https://images.weserv.nl/?url=raw.githubusercontent.com/zan8in/afrog/main/images/contributors/8.png&mask=circle&w=60&h=60" alt="Typora-Logo" /> <br> <a href="https://github.com/zhizhuoshuma">_执着</a> </td> <td align="center"> <img src="https://images.weserv.nl/?url=raw.githubusercontent.com/zan8in/afrog/main/images/contributors/4.png&mask=circle&w=60&h=60" alt="Typora-Logo" /> <br> <a href="https://github.com/purple-WL">_purple-WL</a> </td> <td align="center"> <img src="https://images.weserv.nl/?url=raw.githubusercontent.com/zan8in/afrog/main/images/contributors/9.png&mask=circle&w=60&h=60" alt="Typora-Logo" /> <br> <a href="javascript:void(0);">_throat</a> </td> </tr> <tr> <td align="center"> <img src="https://images.weserv.nl/?url=raw.githubusercontent.com/zan8in/afrog/main/images/contributors/10.png&mask=circle&w=60&h=60" alt="Typora-Logo" /> <br> <a href="http://secx.store:4000/archives/">_Secx</a> </td> <td align="center"> <img src="https://images.weserv.nl/?url=raw.githubusercontent.com/zan8in/afrog/main/images/contributors/11.png&mask=circle&w=60&h=60" alt="Typora-Logo" /> <br> <a href="https://github.com/yueyu0740">_冰河</a> </td> <td align="center"> <img src="https://images.weserv.nl/?url=raw.githubusercontent.com/zan8in/afrog/main/images/contributors/12.png&mask=circle&w=60&h=60" alt="Typora-Logo" /> <br> <a href="javascript:void(0);">_Sheen</a> </td> <td align="center"> <img src="https://images.weserv.nl/?url=raw.githubusercontent.com/zan8in/afrog/main/images/contributors/13.png&mask=circle&w=60&h=60" alt="Typora-Logo" /> <br> <a href="javascript:void(0);">_a16</a> </td> <td align="center"> <img src="https://images.weserv.nl/?url=raw.githubusercontent.com/zan8in/afrog/main/images/contributors/14.png&mask=circle&w=60&h=60" alt="Typora-Logo" /> <br> <a href="javascript:void(0);">_A1</a> </td> <td align="center"> <img src="https://images.weserv.nl/?url=raw.githubusercontent.com/zan8in/afrog/main/images/contributors/15.png&mask=circle&w=60&h=60" alt="Typora-Logo" /> <br> <a href="https://github.com/rainbow2972">_rainbow2972</a> </td> <td align="center"> <img src="https://images.weserv.nl/?url=raw.githubusercontent.com/zan8in/afrog/main/images/contributors/16.png&mask=circle&w=60&h=60" alt="Typora-Logo" /> <br> <a href="https://github.com/wuha0926">_wuha0926</a> </td> <td align="center"> <img src="https://images.weserv.nl/?url=raw.githubusercontent.com/zan8in/afrog/main/images/contributors/17.png&mask=circle&w=60&h=60" alt="Typora-Logo" /> <br> <a href="javascript:void(0);">_茄子</a> </td> <td align="center"> <img src="https://images.weserv.nl/?url=raw.githubusercontent.com/zan8in/afrog/main/images/contributors/18.png&mask=circle&w=60&h=60" alt="Typora-Logo" /> <br> <a href="javascript:void(0);">_{lei_sec}</a> </td> </tr> <tr> <td align="center"> <img src="https://images.weserv.nl/?url=raw.githubusercontent.com/zan8in/afrog/main/images/contributors/19.png&mask=circle&w=60&h=60" alt="Typora-Logo" /> <br> <a href="https://github.com/G-H-Z">_G-H-Z</a> </td> <td align="center"> <img 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src="https://images.weserv.nl/?url=raw.githubusercontent.com/zan8in/afrog/main/images/contributors/32.jpg&mask=circle&w=60&h=60" alt="Typora-Logo" /> <br> <a href="javascript:void(0);">_{江湖人称魏...}</a> </td> <td align="center"> <img src="https://images.weserv.nl/?url=raw.githubusercontent.com/zan8in/afrog/main/images/contributors/33.jpg&mask=circle&w=60&h=60" alt="Typora-Logo" /> <br> <a href="javascript:void(0);">_若兮风</a> </td> <td align="center"> <img src="https://images.weserv.nl/?url=raw.githubusercontent.com/zan8in/afrog/main/images/contributors/34.png&mask=circle&w=60&h=60" alt="Typora-Logo" /> <br> <a href="javascript:void(0);">_-sudo</a> </td> <td align="center"> <img src="https://images.weserv.nl/?url=raw.githubusercontent.com/zan8in/afrog/main/images/contributors/35.jpg&mask=circle&w=60&h=60" alt="Typora-Logo" /> <br> <a href="https://github.com/Cuerz">_Cuerz</a> </td> <td align="center"> <img src="https://images.weserv.nl/?url=raw.githubusercontent.com/zan8in/afrog/main/images/contributors/36.jpg&mask=circle&w=60&h=60" alt="Typora-Logo" /> <br> <a href="javascript:void(0);">_laohuan12138</a> </td> </tr> <tr> <td align="center"> <img src="https://images.weserv.nl/?url=raw.githubusercontent.com/zan8in/afrog/main/images/contributors/37.jpg&mask=circle&w=60&h=60" alt="Typora-Logo" /> <br> <a href="https://github.com/exp0l0zzz">_exp0l0zzz</a> </td> <td align="center"> <img src="https://images.weserv.nl/?url=raw.githubusercontent.com/zan8in/afrog/main/images/contributors/38.jpg&mask=circle&w=60&h=60" alt="Typora-Logo" /> <br> <a href="https://github.com/1derian">_1derian</a> </td> <td align="center"> <img src="https://images.weserv.nl/?url=raw.githubusercontent.com/zan8in/afrog/main/images/contributors/39.jpg&mask=circle&w=60&h=60" alt="Typora-Logo" /> <br> <a href="https://github.com/CMDB-M">_CMDB-M</a> </td> <td align="center"> <img src="https://images.weserv.nl/?url=raw.githubusercontent.com/zan8in/afrog/main/images/contributors/40.jpg&mask=circle&w=60&h=60" alt="Typora-Logo" /> <br> <a href="javascript:(0);">_li1u</a> </td> <td align="center"> <img src="https://images.weserv.nl/?url=raw.githubusercontent.com/zan8in/afrog/main/images/contributors/41.png&mask=circle&w=60&h=60" alt="Typora-Logo" /> <br> <a href="https://github.com/s0nd9r">_oxsonder</a> </td> <td align="center"> <img src="https://images.weserv.nl/?url=raw.githubusercontent.com/zan8in/afrog/main/images/contributors/42.jpg&mask=circle&w=60&h=60" alt="Typora-Logo" /> <br> <a href="javascript:void(0);">_Zhiliao</a> </td> <td align="center"> <img src="https://images.weserv.nl/?url=raw.githubusercontent.com/zan8in/afrog/main/images/contributors/43.jpg&mask=circle&w=60&h=60" alt="Typora-Logo" /> <br> <a href="javascript:void(0);">_段</a> </td> <td align="center"> <img src="https://images.weserv.nl/?url=raw.githubusercontent.com/zan8in/afrog/main/images/contributors/44.jpg&mask=circle&w=60&h=60" alt="Typora-Logo" /> <br> <a href="https://github.com/HuiTaiL6">_HuiTaiL</a> </td> <td align="center"> <img src="https://images.weserv.nl/?url=raw.githubusercontent.com/zan8in/afrog/main/images/contributors/45.png&mask=circle&w=60&h=60" alt="Typora-Logo" /> <br> <a href="https://github.com/Miracles666">_Miracles666</a> </td> </td> <tr> <td align="center"> <img src="https://images.weserv.nl/?url=raw.githubusercontent.com/zan8in/afrog/main/images/contributors/46.jpg&mask=circle&w=60&h=60" alt="Typora-Logo" /> <br> <a href="javascript:void(0);">_Observer</a> </td> <td align="center"> <img src="https://images.weserv.nl/?url=raw.githubusercontent.com/zan8in/afrog/main/images/contributors/47.jpg&mask=circle&w=60&h=60" alt="Typora-Logo" /> <br> <a href="javascript:void(0);">_黑熊</a> </td> <td align="center"> <img src="https://images.weserv.nl/?url=raw.githubusercontent.com/zan8in/afrog/main/images/contributors/48.jpg&mask=circle&w=60&h=60" alt="Typora-Logo" /> <br> <a href="javascript:void(0);">_TryA9ain</a> </td> <td align="center"> <img src="https://images.weserv.nl/?url=raw.githubusercontent.com/zan8in/afrog/main/images/contributors/49.jpg&mask=circle&w=60&h=60" alt="Typora-Logo" /> <br> <a href="https://github.com/fgz00">_fgz00</a> </td> <td align="center"> <img src="https://images.weserv.nl/?url=raw.githubusercontent.com/zan8in/afrog/main/images/contributors/50.jpg&mask=circle&w=60&h=60" alt="Typora-Logo" /> <br> <a href="https://github.com/Y3y1ng">_Y3y1ng</a> </td> <td align="center"> <img src="https://images.weserv.nl/?url=raw.githubusercontent.com/zan8in/afrog/main/images/contributors/51.png&mask=circle&w=60&h=60" alt="Typora-Logo" /> <br> <a href="javascript:void(0);">_二大爷</a> </td> <td align="center"> <img src="https://images.weserv.nl/?url=raw.githubusercontent.com/zan8in/afrog/main/images/contributors/52.png&mask=circle&w=60&h=60" alt="Typora-Logo" /> <br> <a href="https://github.com/wanswu">_Wans</a> </td> <td align="center"> <img src="https://images.weserv.nl/?url=raw.githubusercontent.com/zan8in/afrog/main/images/contributors/53.jpg&mask=circle&w=60&h=60" alt="Typora-Logo" /> <br> <a href="https://github.com/hbdxmz">_{海边的小米粥}</a> </td> <td align="center"> <img src="https://images.weserv.nl/?url=raw.githubusercontent.com/zan8in/afrog/main/images/contributors/54.jpg&mask=circle&w=60&h=60" alt="Typora-Logo" /> <br> <a href="javascript:void(0);">_Wen</a> </td> </tr> </table></div> ## What is afrog afrog is a high-performance vulnerability scanner that is fast and stable. It supports user-defined PoC and comes with several built-in types, such as CVE, CNVD, default passwords, information disclosure, fingerprint identification, unauthorized access, arbitrary file reading, and command execution. With afrog, network security professionals can quickly validate and remediate vulnerabilities, which helps to enhance their security defense capabilities. ## Features * [x] Open source * [x] Fast, stable, with low false positives * [x] Detailed HTML vulnerability reports * [x] Customizable and stably updatable PoCs * [x] Active community exchange group ## Installation ### Prerequisites - [Go](https://go.dev/) version 1.19 or higher. you can install it with: **Binary** ```sh $ https://github.com/zan8in/afrog/releases/latest ``` **Github** ```sh $ git clone https://github.com/zan8in/afrog.git $ cd afrog $ go build cmd/afrog/main.go $ ./afrog -h ``` **Go** ```sh $ go install -v github.com/zan8in/afrog/v3/cmd/afrog@latest ``` ## Running afrog By default, afrog scans all built-in PoCs, and if it finds any vulnerabilities, it automatically creates an HTML report with the date of the scan as the filename. ```sh afrog -t https://example.com ``` **Warning occurs when running afrog** If you see an error message saying: ``` [ERR] ceye reverse service not set: /home/afrog/.config/afrog/afrog-config.yaml ``` it means you need to modify the [configuration file](#configuration-file). To execute a custom PoC directory, you can use the following command: ```sh afrog -t https://example.com -P mypocs/ ``` Use the command `-s keyword` to perform a fuzzy search on all PoCs and scan the search results. Multiple keywords can be used, separated by commas. For example: `-s weblogic,jboss`. ```sh afrog -t https://example.com -s weblogic,jboss ``` Use the command `-S keyword` to scan vulnerabilities based on their severity level. Severity levels include: `info`, `low`, `medium`, `high`, and `critical`. For example, to only scan high and critical vulnerabilities, use the command `-S high,critical`. ```sh afrog -t https://example.com -S high,critical ``` You can scan multiple URLs at the same time as well. ```sh afrog -T urls.txt ``` ## -web Command The `-web` command allows for persistently storing vulnerabilities scanned by afrog into an SQLite3 database. Accessing http://x.x.x.x:16868 via a browser provides access to the vulnerability report webpage, where users can conduct simple keyword searches and filter results by vulnerability severity. ```shell afrog -web ``` <img src="https://github.com/zan8in/afrog/blob/main/images/webcommand.png" > ## Configuration file The first time you start afrog, it will automatically create a configuration file called `afrog-config.yaml`, which will be saved in the current user directory under `$HOME/.config/afrog/afrog-config.yaml`. Here is an example config file: ```yaml reverse: ceye: api-key: "xxxxxxxxxxxxxxxxxxxxxxxxxxxxxx" domain: "xxxxxx.cey2e.io" dnslogcn: domain: dnslog.cn alphalog: domain: dnslogxx.sh api_url: "http://dnslogxx.sh/" xray: x_token: "xraytest" domain: dnslogxx.sh api_url: "http://x.x.0.x:8777" revsuit: token: "xx" dns_domain: "log.xx.com" http_url: "http://x.x.x.x/log/" api_url: "http://x.x.x.x/helplog" ``` `reverse` is a reverse connection platform used to verify command execution vulnerabilities that cannot be echoed back. Currently, only ceye can be used for verification. ### Ceye Configuration To obtain ceye, follow these steps: - Go to the [ceye.io](http://ceye.io/) website and register an account. - Log in and go to the personal settings page. - Copy the `domain` and `api-key` and correctly configure them in the `afrog-config.yaml` file. ### Dnslogcn No configuration required, but unstable [dnslog.cn](http://dnslog.cn/) ### Alphalog Need to build services [alphalog](https://github.com/AlphabugX/Alphalog) ### Xray Need to build services [xray](https://docs.xray.cool/tools/xray/advanced/reverse) ### Revsuit Need to build services [Revsuit](https://github.com/Li4n0/revsuit)、 [Tutorial](https://mp.weixin.qq.com/s/hGwcMz8sh7BImBjI3wHqnQ) ## Json Output (For developers) ### Json Optional command: `-json` `-j`, Save the scan results to a JSON file. The JSON file includes the following contents by default: `target`, `fulltarget`, `id`, and `info`. The info field includes the following sub-fields: `name`, `author`, `severity`, `description`, and `reference`. If you want to save both `request` and `response` contents, please use the [-json-all](#jsonall) command parameter. ```sh afrog -t https://example.com -json result.json afrog -t https://example.com -j result.json ``` ### Warning The content of the JSON file is updated in real time. However, there is an important note to keep in mind: before the scan is completed, if developers want to parse the file content, they need to add a '`]`' symbol to the end of the file by themselves, otherwise it will cause parsing errors. Of course, if you wait for the scan to complete before parsing the file, this issue will not occur. ### JsonAll Optional command: `-json-all` `-ja`, The only difference between the `-json-all` and `-json` commands is that `-json-all` writes all vulnerability results, including `request` and `response`, to a JSON file. ```sh afrog -t https://example.com -json-all result.json afrog -t https://example.com -ja result.json ``` ## Screenshot  <!--  --> ## As Library ### Simple Example Scan the website `http://example.com` ```golang package main import ( "fmt" "github.com/zan8in/afrog" ) func main() { if err := afrog.NewScanner([]string{"http://example.com"}, afrog.Scanner{}); err != nil { fmt.Println(err.Error()) } } ``` More examples: - [Basic scanner](examples/basic_scan/main.go) - [Read URL batch scan from file](examples/batch_scan/main.go) ## Discussion group To join the afrog communication group on WeChat, please first add the afrog personal account and mark it as **afrog**. Then, you will be added to the group by the administrator. <img src="https://github.com/zan8in/afrog/blob/main/images/discussion.jpg" width="33%" /> ## 404Starlink <img src="https://github.com/knownsec/404StarLink-Project/raw/master/logo.png" width="30%"> afrog has joined [404Starlink](https://github.com/knownsec/404StarLink) ## Disclaimer This tool is intended only for **legally authorized** enterprise security construction purposes. If you want to test the functionality of this tool, you should build a target environment by yourself. To prevent malicious use, all PoCs included in this project are theoretical assessments of vulnerabilities. The tool does not exploit vulnerabilities, launch real attacks or exploits on targets. When using this tool for vulnerability scanning, it is important to ensure that your behavior complies with local laws and regulations, and that you have obtained sufficient authorization. **Do not scan unauthorized targets**. If you engage in any illegal behavior while using this tool, you will be solely responsible for any corresponding consequences, and we will not bear any legal or joint responsibility. Before installing and using this tool, please **read each clause carefully and thoroughly**. Restrictions, disclaimers, or other clauses that may significantly affect your rights and interests may be highlighted in bold or underlined to draw your attention. Unless you have fully read, fully understood, and agreed to all the terms of this agreement, do not install or use this tool. Your use of the tool or your acceptance of this agreement in any other express or implied manner will be deemed as your acknowledgment and agreement to be bound by this agreement.

A Security Tool for Bug Bounty, Pentest and Red Teaming.

vulnerability-scanner,poc,penetration-testing,afrog,vulnerability-scanning-tools,bug-bounty,pentest,red-teaming

adrianhajdin/project_syncfusion_dashboard

# Build and Deploy a React Admin Dashboard App With Theming, Tables, Charts, Calendar, Kanban and More  ### [🌟 Become a top 1% Next.js 13 developer in only one course](https://jsmastery.pro/next13) ### [🚀 Land your dream programming job in 6 months](https://jsmastery.pro/masterclass) ## Introduction This is a code repository for the corresponding video tutorial. If you want to get a finished, highly customizable Material UI version of a similar dashboard, check out [Flexy React Material Dashboard](https://www.wrappixel.com/templates/flexy-react-material-dashboard-admin/?ref=257&campaign=Flexy). ## Launch your development career with project-based coaching - https://www.jsmastery.pro

This is a code repository for the corresponding YouTube video. In this tutorial we are going to build and deploy a an admin dashboard app using React.js and Syncfusion

react,reactjs,syncfusion,syncfusion-ej2

Textualize/rich-cli

# Rich-CLI Rich-CLI is a command line toolbox for fancy output in the terminal, built with [Rich](https://github.com/Textualize/rich). Use the `rich` command to highlight a variety of file types in the terminal, with specialized rendering for Markdown and JSON files. Additionally you can markup and format text from the command line.  ## Installation There are a few options for installing Rich-CLI. ### Windows / Linux You can install Rich-CLI with [pipx](https://pypa.github.io/pipx/). ``` pipx install rich-cli ``` ### MacOS You can install Rich-CLI with [Homebrew](https://brew.sh/). ``` brew install rich ``` ### Universal Rich-CLI may be installed as a Python package, either using `pip`: ``` python -m pip install rich-cli ``` Or using `conda` or `mamba`: ``` mamba install -c conda-forge rich-cli ``` ## Rich command Once installed you should have the `rich` command in your path. Run the following to see usage / help: ``` rich --help ``` ## Syntax highlighting To syntax highlight a file enter `rich` followed by a path. Many file formats are supported. ``` rich loop.py ```  Add the `--line-number` or `-n` switch to enable line numbers. Add `--guides` or `-g` to enable indentation guides. ``` rich loop.py -n -g ```  You can specify a [theme](https://pygments.org/styles/) with `--theme`. ``` rich loop.py --theme dracula ``` You can set the default theme via the `RICH_THEME` environment variable. So the following is equivalent to the above command: ``` RICH_THEME=dracula rich loop.py ```  By default, `rich` will wrap lines if they don't fit within the available width. You can disable this behavior with `--no-wrap`. `Rich` will try to deduce the format of the via from the filename. If you want to override the auto-detected _lexer_ you can explicitly set it with the `--lexer` or `-x` switch. ## Markdown You can request markdown rendering by adding the `--markdown` switch or `-m`. If the file ends with `.md` markdown will be auto-detected. ``` rich README.md ```  If your terminal supports hyperlinks, you can add `--hyperlinks` or `-y` which will output hyperlinks rather than full URLs. ``` rich README.md --hyperlinks ``` ## Jupyter notebook You can request Jupyter notebook rendering by adding the `--ipynb` switch. If the file ends with `.ipynb` Jupyter notebook will be auto-detected. ``` rich notebook.ipynb ``` All options that apply to syntax highlighting can be applied to code cells, and all options that apply to Markdown can be applied to Markdown cells. ## JSON You can request JSON pretty formatting and highlighting with the `--json` or `-j` switches. If the file ends with `.json` then JSON will be auto-detected. ``` rich cats.json ```  ## CSV Rich can display the contents of a CSV (or TSV) as a table. If the file ends with `.csv` or `.tsv` then CSV will be auto-detected. ``` rich deniro.csv ```  ### Rules You can render a horizontal rule with `--rule` or `-u`. Specify a rule style with `--rule-style`. Set the character(s) to render the line with `--rule-char`. ``` rich "Hello [b]World[/b]!" --rule rich "Hello [b]World[/b]!" --rule --rule-style "red" rich "Hello [b]World[/b]!" --rule --rule-style "red" --rule-char "=" ```  ## Pager Add `--pager` to display the content with a built in pager application. Scroll the pager with cursor keys, page up/down, home, end. Alternatively use the scrollbar which will be visible to the right of the terminal. Or use the vi navigation (j, k, ctrl_d, ctrl-u). ``` rich __main__.py -n -g --theme monokai --pager ```  ## Network The `rich` command can read files from the internet you give it a URL starting with `http://` or `https://`. ``` rich https://raw.githubusercontent.com/Textualize/rich-cli/main/README.md --markdown ```  ## Exporting In addition to rendering to the console, `rich` can write an HTML file. This works with any command. Add `--export-html` or `-o` followed by the output path. ``` rich README.md -o readme.html ``` After running this command you should find a "readme.html" in your current working directory. ## Rich Printing If you add the `--print` or `--p` option then Rich will treat the first argument as [console markup](https://rich.readthedocs.io/en/latest/markup.html) which allows you to insert styles with a markup similar in design to bbcode. ``` rich "Hello, [bold magenta]World[/]!" --print ```  ### Soft wrapping Rich will word wrap your text by default by inserting newlines where appropriate. If you don't want this behavior you can enable _soft_ wrapping with `--soft`. ## Reading from Stdin Where `rich` accepts a path, you can enter `-` which reads the content from stdin. You may want this if you are piping output from another process. Note that when rich isn't writing directly to the terminal it will disable ansi color codes, so you may want to add `--force-terminal` or `-F` to tell `rich` you want to keep ansi codes in the output. ``` cat README.md | rich - --markdown --force-terminal ``` ## General Options There are a number of additional switches you may add to modify the content rendered to the terminal. These options are universal and apply to all of the above features. ### Style You can set a style to apply to the output with `--style` or `-s`. The styles are specified with [this syntax](https://rich.readthedocs.io/en/latest/style.html). ``` rich "Hello, [b]World[/b]!" --print --style "on blue" ```  ### Alignment You can align output to the left, center, or right with the `--left`, `--center`, or `--right` options, or their single letter counterparts: `-l`, `-c`, or `-r`. ``` rich "Hello [b]World[/b]!" --print --center ```  ### Width You can set the width of the output with `--width` or `-w` and the desired width. Note that the default behavior is to wrap text. ``` rich "I must not fear. Fear is the mind-killer. Fear is the little-death that brings total obliteration." -p -w 40 ```  ### Text Justify You can set how `rich` will justify text with `--text-left`, `--text-right`, `--text-center`, and `--text-full`; or the single letter equivalents: `-L`, `-R`, `-C`, and `-F`. The difference between `--left` and `--text-left` may not be obvious unless you specify the width of the output. The `--left`, `--center`, and `--right` options will center the block of text within the terminal dimensions. Whereas, the `--text-left`, `--text-center`, and `--text-right` options define how text is rendered _within_ that block. In the following examples, we specify a width of 40 (`-w 40`) which is center aligned with the `-c` switch. Note how the `-R`, `-C` and `-F` apply the text justification within the 40 character block: ``` rich "I must not fear. Fear is the mind-killer. Fear is the little-death that brings total obliteration." -p -w 40 -c -L rich "I must not fear. Fear is the mind-killer. Fear is the little-death that brings total obliteration." -p -w 40 -c -R rich "I must not fear. Fear is the mind-killer. Fear is the little-death that brings total obliteration." -p -w 40 -c -C rich "I must not fear. Fear is the mind-killer. Fear is the little-death that brings total obliteration." -p -w 40 -c -F ``` ### Padding You can apply _padding_ around the output with `--padding` or `-d`. ``` rich "Hello [b]World[/b]!" -p -c --padding 3 --style "on blue" ```  ### Panel You can draw a _panel_ around content with `--panel` or `-a`, which takes one of a number of [styles](https://rich.readthedocs.io/en/latest/appendix/box.html). ``` rich "Hello, [b]World[/b]!" -p -a heavy ``` 

Rich-cli is a command line toolbox for fancy output in the terminal

rich,terminal,terminal-colors,syntax-highlighting,markdown

HarbourMasters/Shipwright

  ## Website Official Website: https://www.shipofharkinian.com/ ## Discord Official Discord: https://discord.com/invite/shipofharkinian If you're having any trouble after reading through this `README`, feel free ask for help in the Support text channels. Please keep in mind that we do not condone piracy. # Quick Start The Ship does not include any copyrighted assets. You are required to provide a supported copy of the game. ### 1. Verify your ROM dump You can verify you have dumped a supported copy of the game by using the compatibility checker at https://ship.equipment/. If you'd prefer to manually validate your ROM dump, you can cross-reference its `sha1` hash with the hashes [here](docs/supportedHashes.json). ### 2. Download The Ship of Harkinian from [Releases](https://github.com/HarbourMasters/Shipwright/releases) ### 3. Launch the Game! #### Windows * Extract the zip * Launch `soh.exe` #### Linux * Place your supported copy of the game in the same folder as the appimage. * Execute `soh.appimage`. You may have to `chmod +x` the appimage via terminal. #### macOS * Run `soh.app`. When prompted, select your supported copy of the game. * You should see a notification saying `Processing OTR`, then, once the process is complete, you should get a notification saying `OTR Successfully Generated`, then the game should start. #### Nintendo Switch * Run one of the PC releases to generate an `oot.otr` and/or `oot-mq.otr` file. After launching the game on PC, you will be able to find these files in the same directory as `soh.exe` or `soh.appimage`. On macOS, these files can be found in `/Users/<username>/Library/Application Support/com.shipofharkinian.soh/` * Copy the files to your sd card ``` sdcard └── switch └── soh ├── oot-mq.otr ├── oot.otr ├── soh.nro └── soh.otr ``` * Launch via Atmosphere's `Game+R` launcher method. ### 4. Play! Congratulations, you are now sailing with the Ship of Harkinian! Have fun! # Configuration ### Default keyboard configuration | N64 | A | B | Z | Start | Analog stick | C buttons | D-Pad | | - | - | - | - | - | - | - | - | | Keyboard | X | C | Z | Space | WASD | Arrow keys | TFGH | ### Other shortcuts | Keys | Action | | - | - | | F1 | Toggle menubar | | F5 | Save state | | F6 | Change state | | F7 | Load state | | F9 | Toggle Text-to-Speech (Windows and Mac only) | | F11 | Fullscreen | | Tab | Toggle Alternate assets | | Ctrl+R | Reset | ### Graphics Backends Currently, there are three rendering APIs supported: DirectX11 (Windows), OpenGL (all platforms), and Metal (MacOS). You can change which API to use in the `Settings` menu of the menubar, which requires a restart. If you're having an issue with crashing, you can change the API in the `shipofharkinian.json` file by finding the line `gfxbackend:""` and changing the value to `sdl` for OpenGL. DirectX 11 is the default on Windows. # Custom Assets Custom assets are packed in `.otr` files. To use custom assets, place them in the `mods` folder. If you're interested in creating and/or packing your own custom asset `.otr` files, check out the following tools: * [**retro - OTR generator**](https://github.com/HarbourMasters64/retro) * [**fast64 - Blender plugin**](https://github.com/HarbourMasters/fast64) # Development ### Building If you want to manually compile SoH, please consult the [building instructions](docs/BUILDING.md). ### Playtesting If you want to playtest a continuous integration build, you can find them at the links below. Keep in mind that these are for playtesting only, and you will likely encounter bugs and possibly crashes. * [Windows](https://nightly.link/HarbourMasters/Shipwright/workflows/generate-builds/develop/soh-windows.zip) * [macOS](https://nightly.link/HarbourMasters/Shipwright/workflows/generate-builds/develop/soh-mac.zip) * [Linux](https://nightly.link/HarbourMasters/Shipwright/workflows/generate-builds/develop/soh-linux.zip) <a href="https://github.com/Kenix3/libultraship/"> <picture> <source media="(prefers-color-scheme: dark)" srcset="./docs/poweredbylus.darkmode.png"> <img alt="Powered by libultraship" src="./docs/poweredbylus.lightmode.png"> </picture> </a>

apache/opendal

# Apache OpenDAL™: *Access Data Freely* [](mailto:dev@opendal.apache.org) [](https://opendal.apache.org/discord) OpenDAL offers a unified data access layer, empowering users to seamlessly and efficiently retrieve data from diverse storage services. Our goal is to deliver a comprehensive solution for any languages, methods, integrations, and services. <img src="https://opendal.apache.org/img/architectural.png" alt="OpenDAL Architectural" width="61.8%" /> ## For *ANY* languages | Name | Release | Docs | |-------------------|--------------------------------------------------|-----------------------------------------------------------------------------------| | [Rust Core] | [![Rust Core Image]][Rust Core Link] | [![Docs Release]][Rust Core Release Docs] [![Docs Dev]][Rust Core Dev Docs] | | [C Binding] | - | [![Docs Dev]][C Binding Dev Docs] | | [Cpp Binding] | - | [![Docs Dev]][Cpp Binding Dev Docs] | | [Dotnet Binding] | - | - | | [Go Binding] | - | - | | [Haskell Binding] | - | - | | [Java Binding] | [![Java Binding Image]][Java Binding Link] | [![Docs Release]][Java Binding Release Docs] [![Docs Dev]][Java Binding Dev Docs] | | [Lua Binding] | - | - | | [Node.js Binding] | [![Node.js Binding Image]][Node.js Binding Link] | [![Docs Dev]][Node.js Binding Dev Docs] | | [Ocaml Binding] | - | - | | [PHP Binding] | - | - | | [Python Binding] | [![Python Binding Image]][Python Binding Link] | [![Docs Dev]][Python Binding Dev Docs] | | [Ruby Binding] | - | - | | [Swift Binding] | - | - | | [Zig Binding] | - | - | [Docs Release]: https://img.shields.io/badge/docs-release-blue [Docs Dev]: https://img.shields.io/badge/docs-dev-blue [Rust Core]: core/README.md [Rust Core Image]: https://img.shields.io/crates/v/opendal.svg [Rust Core Link]: https://crates.io/crates/opendal [Rust Core Release Docs]: https://docs.rs/opendal [Rust Core Dev Docs]: https://opendal.apache.org/docs/rust/opendal/ [C Binding]: bindings/c/README.md [C Binding Dev Docs]: https://opendal.apache.org/docs/c/ [Cpp Binding]: bindings/cpp/README.md [Cpp Binding Dev Docs]: https://opendal.apache.org/docs/cpp/ [Dotnet Binding]: bindings/dotnet/README.md [Go Binding]: bindings/go/README.md [Haskell Binding]: bindings/haskell/README.md [Java Binding]: bindings/java/README.md [Java Binding Image]: https://img.shields.io/maven-central/v/org.apache.opendal/opendal-java [Java Binding Link]: https://central.sonatype.com/artifact/org.apache.opendal/opendal-java [Java Binding Release Docs]: https://javadoc.io/doc/org.apache.opendal/opendal-java [Java Binding Dev Docs]: https://opendal.apache.org/docs/java/ [Lua Binding]: bindings/lua/README.md [Node.js Binding]: bindings/nodejs/README.md [Node.js Binding Image]: https://img.shields.io/npm/v/opendal [Node.js Binding Link]: https://www.npmjs.com/package/opendal [Node.js Binding Dev Docs]: https://opendal.apache.org/docs/nodejs/ [Ocaml Binding]: bindings/ocaml/README.md [PHP Binding]: bindings/php/README.md [Python Binding]: bindings/python/README.md [Python Binding Image]: https://img.shields.io/pypi/v/opendal [Python Binding Link]: https://pypi.org/project/opendal/ [Python Binding Dev Docs]: https://opendal.apache.org/docs/python/ [Ruby Binding]: bindings/ruby/README.md [Swift Binding]: bindings/swift/README.md [Zig Binding]: bindings/zig/README.md ## For *ANY* methods | Name | Description | Release | |-------|--------------------------------------------------------------------|---------------------------| | [oay] | Access data via API Gateway | [![oay image]][oay crate] | | [oli] | Access data via Command Line (alternative to s3cmd, s3cli, azcopy) | [![oli image]][oli crate] | | [ofs] | Access data via POSIX file system API (alternative to s3fs) | [![ofs image]][ofs crate] | [oay]: bin/oay/README.md [oay image]: https://img.shields.io/crates/v/oay.svg [oay crate]: https://crates.io/crates/oay [oli]: bin/oli/README.md [oli image]: https://img.shields.io/crates/v/oli.svg [oli crate]: https://crates.io/crates/oli [ofs]: bin/ofs/README.md [ofs image]: https://img.shields.io/crates/v/ofs.svg [ofs crate]: https://crates.io/crates/ofs ## For *ANY* integrations | Name | Description | Release | Docs | |------------------------|------------------------------------------------------|---------------------------------------------|-----------------------------------------------------------------------------------| | [dav-server-opendalfs] | a [dav-server-rs] implementation using opendal. | [![dav-server image]][dav-server crate] | [![Docs Release]][dav-server release docs] [![Docs Dev]][dav-server dev docs] | | [object_store_opendal] | an [object_store] implementation using opendal. | [![object_store image]][object_store crate] | [![Docs Release]][object_store release docs] [![Docs Dev]][object_store dev docs] | | [fuse3_opendal] | Access data via integrations to [fuse3] | - | - | | [virtiofs_opendal] | Access data via integrations to [vhost-user-backend] | - | - | | [unftp-sbe-opendal] | an [unftp] storage backend implementation using opendal. | - | - | [dav-server-opendalfs]: integrations/dav-server/README.md [dav-server-rs]: https://github.com/messense/dav-server-rs [dav-server image]: https://img.shields.io/crates/v/dav-server-opendalfs.svg [dav-server crate]: https://crates.io/crates/dav-server-opendalfs [dav-server release docs]: https://docs.rs/dav-server-opendalfs/ [dav-server dev docs]: https://opendal.apache.org/docs/dav-server-opendalfs/dav_server_opendalfs/ [object_store_opendal]: integrations/object_store/README.md [object_store]: https://docs.rs/object_store [object_store image]: https://img.shields.io/crates/v/object_store_opendal.svg [object_store crate]: https://crates.io/crates/object_store_opendal [object_store release docs]: https://docs.rs/object_store_opendal/ [object_store dev docs]: https://opendal.apache.org/docs/object-store-opendal/object_store_opendal/ [fuse3_opendal]: integrations/fuse3/README.md [fuse3]: https://docs.rs/fuse3 [virtiofs_opendal]: integrations/virtiofs/README.md [vhost-user-backend]: https://docs.rs/vhost-user-backend [unftp-sbe-opendal]: integrations/unftp-sbe/README.md [unftp]: https://crates.io/crates/unftp ## For *ANY* services | Type | Services | |--------------------------------|------------------------------------------------------------------------------------------------------------------------------------------| | Standard Storage Protocols | ftp http [sftp] [webdav] | | Object Storage Services | [azblob] [cos] [gcs] [obs] [oss] [s3] <br> [b2] [openstack_swift] [upyun] [vercel_blob] | | File Storage Services | fs [alluxio] [azdls] [azfile] [chainsafe] [compfs] <br> [dbfs] [gridfs] [hdfs] [hdfs_native] [ipfs] [webhdfs] | | Consumer Cloud Storage Service | [aliyun_drive] [gdrive] [onedrive] [dropbox] [icloud] [koofr] <br> [pcloud] [seafile] [yandex_disk] | | Key-Value Storage Services | [cacache] [cloudflare_kv] [dashmap] memory [etcd] <br> [foundationdb] [persy] [redis] [rocksdb] [sled] <br> [redb] [tikv] [atomicserver] | | Database Storage Services | [d1] [mongodb] [mysql] [postgresql] [sqlite] [surrealdb] | | Cache Storage Services | [ghac] [memcached] [mini_moka] [moka] [vercel_artifacts] | | Git Based Storage Services | [huggingface] | [sftp]: https://datatracker.ietf.org/doc/html/draft-ietf-secsh-filexfer-02 [webdav]: https://datatracker.ietf.org/doc/html/rfc4918 [azblob]: https://azure.microsoft.com/en-us/services/storage/blobs/ [cos]: https://www.tencentcloud.com/products/cos [gcs]: https://cloud.google.com/storage [obs]: https://www.huaweicloud.com/intl/en-us/product/obs.html [oss]: https://www.aliyun.com/product/oss [s3]: https://aws.amazon.com/s3/ [b2]: https://www.backblaze.com/ [openstack_swift]: https://docs.openstack.org/swift/latest/ [upyun]: https://www.upyun.com/ [vercel_blob]: https://vercel.com/docs/storage/vercel-blob [alluxio]: https://docs.alluxio.io/os/user/stable/en/api/REST-API.html [azdls]: https://azure.microsoft.com/en-us/products/storage/data-lake-storage/ [azfile]: https://learn.microsoft.com/en-us/rest/api/storageservices/file-service-rest-api [chainsafe]: https://storage.chainsafe.io/ [compfs]: https://github.com/compio-rs/compio/ [dbfs]: https://docs.databricks.com/en/dbfs/index.html [gridfs]: https://www.mongodb.com/docs/manual/core/gridfs/ [hdfs]: https://hadoop.apache.org/docs/r3.3.4/hadoop-project-dist/hadoop-hdfs/HdfsDesign.html [hdfs_native]: https://github.com/Kimahriman/hdfs-native [ipfs]: https://ipfs.tech/ [webhdfs]: https://hadoop.apache.org/docs/stable/hadoop-project-dist/hadoop-hdfs/WebHDFS.html [aliyun_drive]: https://www.aliyundrive.com/ [gdrive]: https://www.google.com/drive/ [onedrive]: https://www.microsoft.com/en-us/microsoft-365/onedrive/online-cloud-storage [dropbox]: https://www.dropbox.com/ [icloud]: https://www.icloud.com/iclouddrive [koofr]: https://koofr.eu/ [pcloud]: https://www.pcloud.com/ [seafile]: https://www.seafile.com/ [yandex_disk]: https://360.yandex.com/disk/ [cacache]: https://crates.io/crates/cacache [cloudflare_kv]: https://developers.cloudflare.com/kv/ [dashmap]: https://github.com/xacrimon/dashmap [etcd]: https://etcd.io/ [foundationdb]: https://www.foundationdb.org/ [persy]: https://crates.io/crates/persy [redis]: https://redis.io/ [rocksdb]: http://rocksdb.org/ [sled]: https://crates.io/crates/sled [redb]: https://crates.io/crates/redb [tikv]: https://tikv.org/ [atomicserver]: https://github.com/atomicdata-dev/atomic-server [d1]: https://developers.cloudflare.com/d1/ [mongodb]: https://www.mongodb.com/ [mysql]: https://www.mysql.com/ [postgresql]: https://www.postgresql.org/ [sqlite]: https://www.sqlite.org/ [surrealdb]: https://surrealdb.com/ [ghac]: https://docs.github.com/en/actions/using-workflows/caching-dependencies-to-speed-up-workflows [memcached]: https://memcached.org/ [mini_moka]: https://github.com/moka-rs/mini-moka [moka]: https://github.com/moka-rs/moka [vercel_artifacts]: https://vercel.com/docs/concepts/monorepos/remote-caching [huggingface]: https://huggingface.co/ ## Examples The examples are available at [here](./examples/). ## Documentation The documentation is available at <https://opendal.apache.org>. ## Contribute OpenDAL is an active open-source project. We are always open to people who want to use it or contribute to it. Here are some ways to go. - Start with [Contributing Guide](CONTRIBUTING.md). - Submit [Issues](https://github.com/apache/opendal/issues/new) for bug report or feature requests. - Discuss at [dev mailing list](mailto:dev@opendal.apache.org) ([subscribe](mailto:dev-subscribe@opendal.apache.org?subject=(send%20this%20email%20to%20subscribe)) / [unsubscribe](mailto:dev-unsubscribe@opendal.apache.org?subject=(send%20this%20email%20to%20unsubscribe)) / [archives](https://lists.apache.org/list.html?dev@opendal.apache.org)) - Asking questions in the [Discussions](https://github.com/apache/opendal/discussions/new?category=q-a). - Talk to community directly at [Discord](https://opendal.apache.org/discord). ## Who is using OpenDAL? ### Rust Core - [apache/iceberg-rust](https://github.com/apache/iceberg-rust/): Native Rust implementation of [Apache Iceberg](https://iceberg.apache.org/), the open table format for analytic datasets. - [Databend](https://github.com/datafuselabs/databend/): A modern Elasticity and Performance cloud data warehouse. - [deepeth/mars](https://github.com/deepeth/mars): The powerful analysis platform to explore and visualize data from blockchain. - [GreptimeDB](https://github.com/GreptimeTeam/greptimedb): An open-source, cloud-native, distributed time-series database. - [mozilla/sccache](https://github.com/mozilla/sccache/): `sccache` is [`ccache`](https://github.com/ccache/ccache) with cloud storage - [OctoBase](https://github.com/toeverything/OctoBase): the open-source database behind [AFFiNE](https://github.com/toeverything/affine), local-first, yet collaborative. - [ParadeDB](https://github.com/paradedb/paradedb): Postgres for Search and Analytics - fast full-text search and analytics in Postgres and over cloud storage. Built as an extension. - [Pants](https://github.com/pantsbuild/pants): A fast, scalable, user-friendly build system for codebases of all sizes. - [QuestDB](https://github.com/questdb/questdb): An open-source time-series database for high throughput ingestion and fast SQL queries with operational simplicity. - [RisingWave](https://github.com/risingwavelabs/risingwave): A Distributed SQL Database for Stream Processing - [Vector](https://github.com/vectordotdev/vector): A high-performance observability data pipeline. ### C Binding - [Milvus](https://github.com/milvus-io/milvus): A cloud-native vector database, storage for next generation AI applications ### Java Binding - [QuestDB](https://github.com/questdb/questdb): An open-source time-series database for high throughput ingestion and fast SQL queries with operational simplicity. ## Branding The first and most prominent mentions must use the full form: **Apache OpenDAL™** of the name for any individual usage (webpage, handout, slides, etc.) Depending on the context and writing style, you should use the full form of the name sufficiently often to ensure that readers clearly understand the association of both the OpenDAL project and the OpenDAL software product to the ASF as the parent organization. For more details, see the [Apache Product Name Usage Guide](https://www.apache.org/foundation/marks/guide). ## License and Trademarks Licensed under the Apache License, Version 2.0: http://www.apache.org/licenses/LICENSE-2.0 Apache OpenDAL, OpenDAL, and Apache are either registered trademarks or trademarks of the Apache Software Foundation.

Apache OpenDAL: access data freely.

storage,s3,rust,azblob,gcs,redis,hacktoberfest

datafold/data-diff

### ⚠️ As of May 17, 2024, Datafold is no longer actively supporting or developing open source data-diff. We’re grateful to everyone who made contributions along the way. Please see [our blog post](https://www.datafold.com/blog/sunsetting-open-source-data-diff) for additional context on this decision. --- # data-diff: Compare datasets fast, within or across SQL databases ## Contributors <a href="https://github.com/datafold/data-diff/graphs/contributors"> <img src="https://contributors-img.web.app/image?repo=datafold/data-diff" /> </a> ## License This project is licensed under the terms of the [MIT License](https://github.com/datafold/data-diff/blob/master/LICENSE).

Compare tables within or across databases

database,mysql,postgresql,snowflake,rdbms,trino,data-engineering,data-quality,data-science,data-quality-monitoring

srush/Tensor-Puzzles

# Tensor Puzzles - by [Sasha Rush](http://rush-nlp.com) - [srush_nlp](https://twitter.com/srush_nlp) (with Marcos Treviso) When learning a tensor programming language like PyTorch or Numpy it is tempting to rely on the standard library (or more honestly StackOverflow) to find a magic function for everything. But in practice, the tensor language is extremely expressive, and you can do most things from first principles and clever use of broadcasting. This is a collection of 21 tensor puzzles. Like chess puzzles these are not meant to simulate the complexity of a real program, but to practice in a simplified environment. Each puzzle asks you to reimplement one function in the NumPy standard library without magic. I recommend running in Colab. Click here and copy the notebook to get start. [](https://colab.research.google.com/github/srush/Tensor-Puzzles/blob/main/Tensor%20Puzzlers.ipynb) If you are interested, there is also a youtube walkthrough of the puzzles [](https://youtu.be/Hafo7hIl8MU) ```python !pip install -qqq torchtyping hypothesis pytest git+https://github.com/danoneata/chalk@srush-patch-1 !wget -q https://github.com/srush/Tensor-Puzzles/raw/main/lib.py ``` ```python from lib import draw_examples, make_test, run_test import torch import numpy as np from torchtyping import TensorType as TT tensor = torch.tensor ``` ## Rules 1. These puzzles are about *broadcasting*. Know this rule.  2. Each puzzle needs to be solved in 1 line (<80 columns) of code. 3. You are allowed @, arithmetic, comparison, `shape`, any indexing (e.g. `a[:j], a[:, None], a[arange(10)]`), and previous puzzle functions. 4. You are *not allowed* anything else. No `view`, `sum`, `take`, `squeeze`, `tensor`. 5. You can start with these two functions: ```python def arange(i: int): "Use this function to replace a for-loop." return torch.tensor(range(i)) draw_examples("arange", [{"" : arange(i)} for i in [5, 3, 9]]) ```  ```python # Example of broadcasting. examples = [(arange(4), arange(5)[:, None]) , (arange(3)[:, None], arange(2))] draw_examples("broadcast", [{"a": a, "b":b, "ret": a + b} for a, b in examples]) ```  ```python def where(q, a, b): "Use this function to replace an if-statement." return (q * a) + (~q) * b # In diagrams, orange is positive/True, where is zero/False, and blue is negative. examples = [(tensor([False]), tensor([10]), tensor([0])), (tensor([False, True]), tensor([1, 1]), tensor([-10, 0])), (tensor([False, True]), tensor([1]), tensor([-10, 0])), (tensor([[False, True], [True, False]]), tensor([1]), tensor([-10, 0])), (tensor([[False, True], [True, False]]), tensor([[0], [10]]), tensor([-10, 0])), ] draw_examples("where", [{"q": q, "a":a, "b":b, "ret": where(q, a, b)} for q, a, b in examples]) ```  ## Puzzle 1 - ones Compute [ones](https://numpy.org/doc/stable/reference/generated/numpy.ones.html) - the vector of all ones. ```python def ones_spec(out): for i in range(len(out)): out[i] = 1 def ones(i: int) -> TT["i"]: raise NotImplementedError test_ones = make_test("one", ones, ones_spec, add_sizes=["i"]) ```  ```python # run_test(test_ones) ``` ## Puzzle 2 - sum Compute [sum](https://numpy.org/doc/stable/reference/generated/numpy.sum.html) - the sum of a vector. ```python def sum_spec(a, out): out[0] = 0 for i in range(len(a)): out[0] += a[i] def sum(a: TT["i"]) -> TT[1]: raise NotImplementedError test_sum = make_test("sum", sum, sum_spec) ```  ```python # run_test(test_sum) ``` ## Puzzle 3 - outer Compute [outer](https://numpy.org/doc/stable/reference/generated/numpy.outer.html) - the outer product of two vectors. ```python def outer_spec(a, b, out): for i in range(len(out)): for j in range(len(out[0])): out[i][j] = a[i] * b[j] def outer(a: TT["i"], b: TT["j"]) -> TT["i", "j"]: raise NotImplementedError test_outer = make_test("outer", outer, outer_spec) ```  ```python # run_test(test_outer) ``` ## Puzzle 4 - diag Compute [diag](https://numpy.org/doc/stable/reference/generated/numpy.diag.html) - the diagonal vector of a square matrix. ```python def diag_spec(a, out): for i in range(len(a)): out[i] = a[i][i] def diag(a: TT["i", "i"]) -> TT["i"]: raise NotImplementedError test_diag = make_test("diag", diag, diag_spec) ```  ```python # run_test(test_diag) ``` ## Puzzle 5 - eye Compute [eye](https://numpy.org/doc/stable/reference/generated/numpy.eye.html) - the identity matrix. ```python def eye_spec(out): for i in range(len(out)): out[i][i] = 1 def eye(j: int) -> TT["j", "j"]: raise NotImplementedError test_eye = make_test("eye", eye, eye_spec, add_sizes=["j"]) ```  ```python # run_test(test_eye) ``` ## Puzzle 6 - triu Compute [triu](https://numpy.org/doc/stable/reference/generated/numpy.triu.html) - the upper triangular matrix. ```python def triu_spec(out): for i in range(len(out)): for j in range(len(out)): if i <= j: out[i][j] = 1 else: out[i][j] = 0 def triu(j: int) -> TT["j", "j"]: raise NotImplementedError test_triu = make_test("triu", triu, triu_spec, add_sizes=["j"]) ```  ```python # run_test(test_triu) ``` ## Puzzle 7 - cumsum Compute [cumsum](https://numpy.org/doc/stable/reference/generated/numpy.cumsum.html) - the cumulative sum. ```python def cumsum_spec(a, out): total = 0 for i in range(len(out)): out[i] = total + a[i] total += a[i] def cumsum(a: TT["i"]) -> TT["i"]: raise NotImplementedError test_cumsum = make_test("cumsum", cumsum, cumsum_spec) ```  ```python # run_test(test_cumsum) ``` ## Puzzle 8 - diff Compute [diff](https://numpy.org/doc/stable/reference/generated/numpy.diff.html) - the running difference. ```python def diff_spec(a, out): out[0] = a[0] for i in range(1, len(out)): out[i] = a[i] - a[i - 1] def diff(a: TT["i"], i: int) -> TT["i"]: raise NotImplementedError test_diff = make_test("diff", diff, diff_spec, add_sizes=["i"]) ```  ```python # run_test(test_diff) ``` ## Puzzle 9 - vstack Compute [vstack](https://numpy.org/doc/stable/reference/generated/numpy.vstack.html) - the matrix of two vectors ```python def vstack_spec(a, b, out): for i in range(len(out[0])): out[0][i] = a[i] out[1][i] = b[i] def vstack(a: TT["i"], b: TT["i"]) -> TT[2, "i"]: raise NotImplementedError test_vstack = make_test("vstack", vstack, vstack_spec) ```  ```python # run_test(test_vstack) ``` ## Puzzle 10 - roll Compute [roll](https://numpy.org/doc/stable/reference/generated/numpy.roll.html) - the vector shifted 1 circular position. ```python def roll_spec(a, out): for i in range(len(out)): if i + 1 < len(out): out[i] = a[i + 1] else: out[i] = a[i + 1 - len(out)] def roll(a: TT["i"], i: int) -> TT["i"]: raise NotImplementedError test_roll = make_test("roll", roll, roll_spec, add_sizes=["i"]) ```  ```python # run_test(test_roll) ``` ## Puzzle 11 - flip Compute [flip](https://numpy.org/doc/stable/reference/generated/numpy.flip.html) - the reversed vector ```python def flip_spec(a, out): for i in range(len(out)): out[i] = a[len(out) - i - 1] def flip(a: TT["i"], i: int) -> TT["i"]: raise NotImplementedError test_flip = make_test("flip", flip, flip_spec, add_sizes=["i"]) ```  ```python # run_test(test_flip) ``` ## Puzzle 12 - compress Compute [compress](https://numpy.org/doc/stable/reference/generated/numpy.compress.html) - keep only masked entries (left-aligned). ```python def compress_spec(g, v, out): j = 0 for i in range(len(g)): if g[i]: out[j] = v[i] j += 1 def compress(g: TT["i", bool], v: TT["i"], i:int) -> TT["i"]: raise NotImplementedError test_compress = make_test("compress", compress, compress_spec, add_sizes=["i"]) ```  ```python # run_test(test_compress) ``` ## Puzzle 13 - pad_to Compute pad_to - eliminate or add 0s to change size of vector. ```python def pad_to_spec(a, out): for i in range(min(len(out), len(a))): out[i] = a[i] def pad_to(a: TT["i"], i: int, j: int) -> TT["j"]: raise NotImplementedError test_pad_to = make_test("pad_to", pad_to, pad_to_spec, add_sizes=["i", "j"]) ```  ```python # run_test(test_pad_to) ``` ## Puzzle 14 - sequence_mask Compute [sequence_mask](https://www.tensorflow.org/api_docs/python/tf/sequence_mask) - pad out to length per batch. ```python def sequence_mask_spec(values, length, out): for i in range(len(out)): for j in range(len(out[0])): if j < length[i]: out[i][j] = values[i][j] else: out[i][j] = 0 def sequence_mask(values: TT["i", "j"], length: TT["i", int]) -> TT["i", "j"]: raise NotImplementedError def constraint_set_length(d): d["length"] = d["length"] % d["values"].shape[1] return d test_sequence = make_test("sequence_mask", sequence_mask, sequence_mask_spec, constraint=constraint_set_length ) ```  ```python # run_test(test_sequence) ``` ## Puzzle 15 - bincount Compute [bincount](https://numpy.org/doc/stable/reference/generated/numpy.bincount.html) - count number of times an entry was seen. ```python def bincount_spec(a, out): for i in range(len(a)): out[a[i]] += 1 def bincount(a: TT["i"], j: int) -> TT["j"]: raise NotImplementedError def constraint_set_max(d): d["a"] = d["a"] % d["return"].shape[0] return d test_bincount = make_test("bincount", bincount, bincount_spec, add_sizes=["j"], constraint=constraint_set_max ) ```  ```python # run_test(test_bincount) ``` ## Puzzle 16 - scatter_add Compute [scatter_add](https://pytorch-scatter.readthedocs.io/en/1.3.0/functions/add.html) - add together values that link to the same location. ```python def scatter_add_spec(values, link, out): for j in range(len(values)): out[link[j]] += values[j] def scatter_add(values: TT["i"], link: TT["i"], j: int) -> TT["j"]: raise NotImplementedError def constraint_set_max(d): d["link"] = d["link"] % d["return"].shape[0] return d test_scatter_add = make_test("scatter_add", scatter_add, scatter_add_spec, add_sizes=["j"], constraint=constraint_set_max ) ```  ```python # run_test(test_scatter_add) ``` ## Puzzle 17 - flatten Compute [flatten](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.flatten.html) ```python def flatten_spec(a, out): k = 0 for i in range(len(a)): for j in range(len(a[0])): out[k] = a[i][j] k += 1 def flatten(a: TT["i", "j"], i:int, j:int) -> TT["i * j"]: raise NotImplementedError test_flatten = make_test("flatten", flatten, flatten_spec, add_sizes=["i", "j"]) ```  ```python # run_test(test_flatten) ``` ## Puzzle 18 - linspace Compute [linspace](https://numpy.org/doc/stable/reference/generated/numpy.linspace.html) ```python def linspace_spec(i, j, out): for k in range(len(out)): out[k] = float(i + (j - i) * k / max(1, len(out) - 1)) def linspace(i: TT[1], j: TT[1], n: int) -> TT["n", float]: raise NotImplementedError test_linspace = make_test("linspace", linspace, linspace_spec, add_sizes=["n"]) ```  ```python # run_test(test_linspace) ``` ## Puzzle 19 - heaviside Compute [heaviside](https://numpy.org/doc/stable/reference/generated/numpy.heaviside.html) ```python def heaviside_spec(a, b, out): for k in range(len(out)): if a[k] == 0: out[k] = b[k] else: out[k] = int(a[k] > 0) def heaviside(a: TT["i"], b: TT["i"]) -> TT["i"]: raise NotImplementedError test_heaviside = make_test("heaviside", heaviside, heaviside_spec) ```  ```python # run_test(test_heaviside) ``` ## Puzzle 20 - repeat (1d) Compute [repeat](https://pytorch.org/docs/stable/generated/torch.Tensor.repeat.html) ```python def repeat_spec(a, d, out): for i in range(d[0]): for k in range(len(a)): out[i][k] = a[k] def constraint_set(d): d["d"][0] = d["return"].shape[0] return d def repeat(a: TT["i"], d: TT[1]) -> TT["d", "i"]: raise NotImplementedError test_repeat = make_test("repeat", repeat, repeat_spec, constraint=constraint_set) ```  ## Puzzle 21 - bucketize Compute [bucketize](https://pytorch.org/docs/stable/generated/torch.bucketize.html) ```python def bucketize_spec(v, boundaries, out): for i, val in enumerate(v): out[i] = 0 for j in range(len(boundaries)-1): if val >= boundaries[j]: out[i] = j + 1 if val >= boundaries[-1]: out[i] = len(boundaries) def constraint_set(d): d["boundaries"] = np.abs(d["boundaries"]).cumsum() return d def bucketize(v: TT["i"], boundaries: TT["j"]) -> TT["i"]: raise NotImplementedError test_bucketize = make_test("bucketize", bucketize, bucketize_spec, constraint=constraint_set) ```  ## Speed Run Mode! What is the smallest you can make each of these? ```python import inspect fns = (ones, sum, outer, diag, eye, triu, cumsum, diff, vstack, roll, flip, compress, pad_to, sequence_mask, bincount, scatter_add) for fn in fns: lines = [l for l in inspect.getsource(fn).split("\n") if not l.strip().startswith("#")] if len(lines) > 3: print(fn.__name__, len(lines[2]), "(more than 1 line)") else: print(fn.__name__, len(lines[1])) ``` ones 29 sum 29 outer 29 diag 29 eye 29 triu 29 cumsum 29 diff 29 vstack 29 roll 29 flip 29 compress 29 pad_to 29 sequence_mask 29 bincount 29 scatter_add 29

Solve puzzles. Improve your pytorch.

machine-learning,puzzle,torch

apple/swift-async-algorithms

# swift-async-algorithms **Swift Async Algorithms** is an open-source package of asynchronous sequence and advanced algorithms that involve concurrency, along with their related types. This package has three main goals: - First-class integration with `async/await` - Provide a home for time-based algorithms - Be cross-platform and open source ## Motivation AsyncAlgorithms is a package for algorithms that work with *values over time*. That includes those primarily about *time*, like `debounce` and `throttle`, but also algorithms about *order* like `combineLatest` and `merge`. Operations that work with multiple inputs (like `zip` does on `Sequence`) can be surprisingly complex to implement, with subtle behaviors and many edge cases to consider. A shared package can get these details correct, with extensive testing and documentation, for the benefit of all Swift apps. The foundation for AsyncAlgorithms was included in Swift 5.5 from [AsyncSequence](https://github.com/apple/swift-evolution/blob/main/proposals/0298-asyncsequence.md). Swift 5.5 also brings the ability to use a natural `for/in` loop with `await` to process the values in an `AsyncSequence` and `Sequence`-equivalent API like `map` and `filter`. Structured concurrency allows us to write code where intermediate state is simply a local variable, `try` can be used directly on functions that `throw`, and generally treat the logic for asynchronous code similar to that of synchronous code. This package is the home for these APIs. Development and API design take place on [GitHub](https://github.com/apple/swift-async-algorithms) and the [Swift Forums](https://forums.swift.org/c/related-projects/swift-async-algorithms). ## Contents #### Combining asynchronous sequences - [`chain(_:...)`](https://github.com/apple/swift-async-algorithms/blob/main/Sources/AsyncAlgorithms/AsyncAlgorithms.docc/Guides/Chain.md): Concatenates two or more asynchronous sequences with the same element type. - [`combineLatest(_:...)`](https://github.com/apple/swift-async-algorithms/blob/main/Sources/AsyncAlgorithms/AsyncAlgorithms.docc/Guides/CombineLatest.md): Combines two or more asynchronous sequences into an asynchronous sequence producing a tuple of elements from those base asynchronous sequences that updates when any of the base sequences produce a value. - [`merge(_:...)`](https://github.com/apple/swift-async-algorithms/blob/main/Sources/AsyncAlgorithms/AsyncAlgorithms.docc/Guides/Merge.md): Merges two or more asynchronous sequence into a single asynchronous sequence producing the elements of all of the underlying asynchronous sequences. - [`zip(_:...)`](https://github.com/apple/swift-async-algorithms/blob/main/Sources/AsyncAlgorithms/AsyncAlgorithms.docc/Guides/Zip.md): Creates an asynchronous sequence of pairs built out of underlying asynchronous sequences. - [`joined(separator:)`](https://github.com/apple/swift-async-algorithms/blob/main/Sources/AsyncAlgorithms/AsyncAlgorithms.docc/Guides/Joined.md): Concatenated elements of an asynchronous sequence of asynchronous sequences, inserting the given separator between each element. #### Creating asynchronous sequences - [`async`](https://github.com/apple/swift-async-algorithms/blob/main/Sources/AsyncAlgorithms/AsyncAlgorithms.docc/Guides/Lazy.md): Create an asynchronous sequence composed from a synchronous sequence. - [`AsyncChannel`](https://github.com/apple/swift-async-algorithms/blob/main/Sources/AsyncAlgorithms/AsyncAlgorithms.docc/Guides/Channel.md): An asynchronous sequence with back pressure sending semantics. - [`AsyncThrowingChannel`](https://github.com/apple/swift-async-algorithms/blob/main/Sources/AsyncAlgorithms/AsyncAlgorithms.docc/Guides/Channel.md): An asynchronous sequence with back pressure sending semantics that can emit failures. #### Performance optimized asynchronous iterators - [`AsyncBufferedByteIterator`](https://github.com/apple/swift-async-algorithms/blob/main/Sources/AsyncAlgorithms/AsyncAlgorithms.docc/Guides/BufferedBytes.md): A highly efficient iterator useful for iterating byte sequences derived from asynchronous read functions. #### Other useful asynchronous sequences - [`adjacentPairs()`](https://github.com/apple/swift-async-algorithms/blob/main/Sources/AsyncAlgorithms/AsyncAlgorithms.docc/Guides/AdjacentPairs.md): Collects tuples of adjacent elements. - [`chunks(...)` and `chunked(...)`](https://github.com/apple/swift-async-algorithms/blob/main/Sources/AsyncAlgorithms/AsyncAlgorithms.docc/Guides/Chunked.md): Collect values into chunks. - [`compacted()`](https://github.com/apple/swift-async-algorithms/blob/main/Sources/AsyncAlgorithms/AsyncAlgorithms.docc/Guides/Compacted.md): Remove nil values from an asynchronous sequence. - [`removeDuplicates()`](https://github.com/apple/swift-async-algorithms/blob/main/Sources/AsyncAlgorithms/AsyncAlgorithms.docc/Guides/RemoveDuplicates.md): Remove sequentially adjacent duplicate values. - [`interspersed(with:)`](https://github.com/apple/swift-async-algorithms/blob/main/Sources/AsyncAlgorithms/AsyncAlgorithms.docc/Guides/Intersperse.md): Place a value between every two elements of an asynchronous sequence. #### Asynchronous Sequences that transact in time - [`debounce(for:tolerance:clock:)`](https://github.com/apple/swift-async-algorithms/blob/main/Sources/AsyncAlgorithms/AsyncAlgorithms.docc/Guides/Debounce.md): Emit values after a quiescence period has been reached. - [`throttle(for:clock:reducing:)`](https://github.com/apple/swift-async-algorithms/blob/main/Sources/AsyncAlgorithms/AsyncAlgorithms.docc/Guides/Throttle.md): Ensure a minimum interval has elapsed between events. - [`AsyncTimerSequence`](https://github.com/apple/swift-async-algorithms/blob/main/Sources/AsyncAlgorithms/AsyncAlgorithms.docc/Guides/Timer.md): Emit the value of now at a given interval repeatedly. #### Obtaining all values from an asynchronous sequence - [`RangeReplaceableCollection.init(_:)`](https://github.com/apple/swift-async-algorithms/blob/main/Sources/AsyncAlgorithms/AsyncAlgorithms.docc/Guides/Collections.md): Creates a new instance of a collection containing the elements of an asynchronous sequence. - [`Dictionary.init(uniqueKeysWithValues:)`](https://github.com/apple/swift-async-algorithms/blob/main/Sources/AsyncAlgorithms/AsyncAlgorithms.docc/Guides/Collections.md): Creates a new dictionary from the key-value pairs in the given asynchronous sequence. - [`Dictionary.init(_:uniquingKeysWith:)`](https://github.com/apple/swift-async-algorithms/blob/main/Sources/AsyncAlgorithms/AsyncAlgorithms.docc/Guides/Collections.md): Creates a new dictionary from the key-value pairs in the given asynchronous sequence, using a combining closure to determine the value for any duplicate keys. - [`Dictionary.init(grouping:by:)`](https://github.com/apple/swift-async-algorithms/blob/main/Sources/AsyncAlgorithms/AsyncAlgorithms.docc/Guides/Collections.md): Creates a new dictionary whose keys are the groupings returned by the given closure and whose values are arrays of the elements that returned each key. - [`SetAlgebra.init(_:)`](https://github.com/apple/swift-async-algorithms/blob/main/Sources/AsyncAlgorithms/AsyncAlgorithms.docc/Guides/Collections.md): Creates a new set from an asynchronous sequence of items. #### Effects Each algorithm has specific behavioral effects. For throwing effects these can either be if the sequence throws, does not throw, or rethrows errors. Sendability effects in some asynchronous sequences are conditional whereas others require the composed parts to all be sendable to satisfy a requirement of `Sendable`. The effects are [listed here](https://github.com/apple/swift-async-algorithms/blob/main/Sources/AsyncAlgorithms/AsyncAlgorithms.docc/Guides/Effects.md). ## Adding Swift Async Algorithms as a Dependency To use the `AsyncAlgorithms` library in a SwiftPM project, add the following line to the dependencies in your `Package.swift` file: ```swift .package(url: "https://github.com/apple/swift-async-algorithms", from: "1.0.0"), ``` Include `"AsyncAlgorithms"` as a dependency for your executable target: ```swift .target(name: "<target>", dependencies: [ .product(name: "AsyncAlgorithms", package: "swift-async-algorithms"), ]), ``` Finally, add `import AsyncAlgorithms` to your source code. ## Getting Started ⚠️ Please note that this package requires Xcode 14 on macOS hosts. Previous versions of Xcode do not contain the required Swift version. ### Building/Testing Using Xcode on macOS 1. In the `swift-async-algorithms` directory run `swift build` or `swift test` accordingly ### Building/Testing on Linux 1. Download the most recent development toolchain for your Linux distribution 2. Decompress the archive to a path in which the `swift` executable is in the binary search path environment variable (`$PATH`) 3. In the `swift-async-algorithms` directory run `swift build` or `swift test` accordingly ## Source Stability The Swift Async Algorithms package has a goal of being source stable as soon as possible; version numbers will follow [Semantic Versioning](https://semver.org/). Source breaking changes to public API can only land in a new major version. The public API of version 1.0 of the `swift-async-algorithms` package will consist of non-underscored declarations that are marked `public` in the `AsyncAlgorithms` module. Interfaces that aren't part of the public API may continue to change in any release, including patch releases. Future minor versions of the package may introduce changes to these rules as needed. We'd like this package to quickly embrace Swift language and toolchain improvements that are relevant to its mandate. Accordingly, from time to time, we expect that new versions of this package will require clients to upgrade to a more recent Swift toolchain release. Requiring a new Swift release will only require a minor version bump.

Async Algorithms for Swift

swift

alex8088/electron-vite

<p align="center"> <img src="https://alex8088.github.io/assets/electron-vite.svg" width="150px" height="150px"> </p> <div align="center"> <h1>electron-vite</h1> </div> <p align="center">Next generation Electron build tooling based on Vite</p> <p align="center"> <img src="https://img.shields.io/npm/v/electron-vite?color=6988e6&label=version"> <img src="https://img.shields.io/github/license/alex8088/electron-vite?color=blue" alt="license" /> </p> <p align="center"> <a href="https://electron-vite.org">Documentation</a> | <a href="https://electron-vite.org/guide">Getting Started</a> | <a href="https://github.com/alex8088/quick-start/tree/master/packages/create-electron">create-electron</a> </p> <p align="center"> <a href="https://cn.electron-vite.org">中文文档</a> </p> <br /> <br /> ## Features - ⚡️ [Vite](https://vitejs.dev) powered and use the same way. - 🛠 Pre-configured for Electron, don't worry about configuration. - 💡 Optimize asset handling (Node.js addons, WebAssembly, Worker Thread, etc). - 🚀 Fast HMR for renderer processes. - 🔥 Hot reloading for main process and preload scripts. - 🔌 Easy to debug in IDEs like VSCode or WebStorm. - 🔒 Compile to v8 bytecode to protect source code. - 🏷️ Support for TypeScript decorators. - 📦 Out-of-the-box support for TypeScript, Vue, React, Svelte, SolidJS and more. ## Usage ### Install ```sh npm i electron-vite -D ``` ### Development & Build In a project where `electron-vite` is installed, you can use `electron-vite` binary directly with `npx electron-vite` or add the npm scripts to your `package.json` file like this: ```json { "scripts": { "start": "electron-vite preview", "dev": "electron-vite dev", "prebuild": "electron-vite build" } } ``` ### Configuration When running `electron-vite` from the command line, electron-vite will automatically try to resolve a config file named `electron.vite.config.js` inside project root. The most basic config file looks like this: ```js // electron.vite.config.js export default { main: { // vite config options }, preload: { // vite config options }, renderer: { // vite config options } } ``` ### Getting Started Clone the [electron-vite-boilerplate](https://github.com/alex8088/electron-vite-boilerplate) or use the [create-electron](https://github.com/alex8088/quick-start/tree/master/packages/create-electron) tool to scaffold your project. ```bash npm create @quick-start/electron ``` Currently supported template presets include: | JavaScript | TypeScript | | :--------------------------------------------------------------------------------------------------------: | :--------------------------------------------------------------------------------------------------------------: | | [vanilla](https://github.com/alex8088/quick-start/tree/master/packages/create-electron/playground/vanilla) | [vanilla-ts](https://github.com/alex8088/quick-start/tree/master/packages/create-electron/playground/vanilla-ts) | | [vue](https://github.com/alex8088/quick-start/tree/master/packages/create-electron/playground/vue) | [vue-ts](https://github.com/alex8088/quick-start/tree/master/packages/create-electron/playground/vue-ts) | | [react](https://github.com/alex8088/quick-start/tree/master/packages/create-electron/playground/react) | [react-ts](https://github.com/alex8088/quick-start/tree/master/packages/create-electron/playground/react-ts) | | [svelte](https://github.com/alex8088/quick-start/tree/master/packages/create-electron/playground/svelte) | [svelte-ts](https://github.com/alex8088/quick-start/tree/master/packages/create-electron/playground/svelte-ts) | | [solid](https://github.com/alex8088/quick-start/tree/master/packages/create-electron/playground/solid) | [solid-ts](https://github.com/alex8088/quick-start/tree/master/packages/create-electron/playground/solid-ts) | ## Contribution See [Contributing Guide](CONTRIBUTING.md). ## License [MIT](./LICENSE) © alex.wei

Next generation Electron build tooling based on Vite 新一代 Electron 开发构建工具，支持源代码保护

electron,source-code-protection,vite,hmr,hot-reloading,node-worker,typescript-decorator,bytecode

arthurspk/guiadofrontend

<p align="center"> <a href="https://github.com/arthurspk/guiadofrontend"> <img src="./images/guia.png" alt="Guia do Desenvolvedor Front-end" width="160" height="160"> </a> <h1 align="center">Guia do Desenvolvedor Front-end</h1> </p> ## :dart: O guia para alavancar a sua carreira Abaixo você encontrará conteúdos para te guiar e ajudar a se torna um desenvolvedor front-end, caso você já atue como front-end confere o repositório para descobrir novas ferramentas para o seu dia-a-dia, os caminhos que você pode tomar e as tecnologias para incorporar na sua stack para se tornar um profissional atualizado e diferenciado em front-end, faça bom uso do guia e bons estudos! _{<strong>Segue nas redes sociais para acompanhar mais conteúdo: </strong> <br> [<img src = "https://img.shields.io/badge/GitHub-100000?style=for-the-badge&logo=github&logoColor=white">](https://github.com/arthurspk) [<img src = "https://img.shields.io/badge/Facebook-1877F2?style=for-the-badge&logo=facebook&logoColor=white">](https://www.facebook.com/seixasqlc/) [<img src="https://img.shields.io/badge/linkedin-%230077B5.svg?&style=for-the-badge&logo=linkedin&logoColor=white" />](https://www.linkedin.com/in/arthurspk/) [<img src = "https://img.shields.io/badge/Twitter-1DA1F2?style=for-the-badge&logo=twitter&logoColor=white">](https://twitter.com/manotoquinho) [](https://discord.gg/NbMQUPjHz7) [<img src = "https://img.shields.io/badge/instagram-%23E4405F.svg?&style=for-the-badge&logo=instagram&logoColor=white">](https://www.instagram.com/guiadevbrasil/) [](https://www.youtube.com/channel/UCzmXzz_VR0Li8-YOvWN_t3g)} ## 💌 Doações > Olá! Se você está lendo isso, é porque provavelmente já conhece o meu repositório no GitHub, que oferece conteúdo gratuito para ajudar desenvolvedores a aprimorarem suas habilidades. E se você está aqui, talvez esteja considerando contribuir com uma doação para apoiar a continuação do projeto. - [Clique aqui para realizar realizar uma doação! 💓](https://beacons.ai/doacoesguiadev) > Se você quiser contribuir, existem várias opções disponíveis, incluindo PayPal, PagSeguro, Mercado Pago, Buy Me A Coffe, Pic Pay e Pix. Qualquer doação, por menor que seja, é extremamente bem-vinda e será usada com responsabilidade e transparência. Obrigado por considerar apoiar meu projeto! Juntos, podemos continuar a compartilhar conhecimento e ajudar a criar uma comunidade de desenvolvedores mais forte e colaborativa. ## :closed_book: E-Book > Este repositório é um projeto gratuito para a comunidade de desenvolvedores. Você pode me ajudar comprando o e-book "e-Front" se estiver interessado em aprender ou melhorar suas habilidades de desenvolvimento front-end. O e-book é completo e cobre tecnologias essenciais como HTML, CSS, JavaScript, React, TypeScript e mais. O valor é simbólico e sua compra me ajuda a produzir e fornecer mais conteúdo gratuito para a comunidade. Adquira agora e comece sua jornada no desenvolvimento front-end. - eFront - Estudando Desenvolvimento Front-end do Zero. [Clique aqui para comprar](https://hotm.art/cSMObU) ## 📛 Direitos autorais > Esse projeto tomou como referência para ser feito os roadmaps feito pelo projeto [roadmap.sh](https://roadmap.sh/roadmaps) você pode conferir todo o projeto original feito pelos autores principais pelos links abaixo, desde já agradecendo a todos eles por fornecer esse conteúdo que serviu de extrema importância e de base para a criação deste repositório. - [Roadmap.sh](https://roadmap.sh/roadmaps) - Site do roadmap.sh onde você encontrará diversos roadmaps em inglês. - [Repositório Oficial do Projeto](https://github.com/kamranahmedse/developer-roadmap/blob/master/license) - Repositório oficial do projeto em inglês. ## :warning: Nossa proposta > A proposta deste guia é dar uma ideia sobre o atual panorama e guiá-lo se você estiver confuso sobre qual o próximo aprendizado, não influenciar você a seguir os 'hypes' e 'trendys' do momento. Acreditamos que com um <b>maior conhecimento das diferentes estruturas e soluções disponíveis poderá escolher a ferramenta que melhor se aplica às suas demandas.</b> E lembre-se, 'hypes' e 'trendys' nem sempre são as melhores opções. ## :beginner: Para quem está começando agora > Não se assuste com a quantidade de conteúdo apresentados neste guia. Mesmo o foco sendo para profissionais já consolidados que desejam se manter atualizados, acredito que quem está começando pode usá-lo não como um objetivo, mas como um apoio para os estudos. <b>Neste momento, dê enfoque no que te dá produtividade e o restante marque como <i>Ver depois</i></b>. Ao passo que seu conhecimento se torna mais amplo, a tendência é este guia fazer mais sentido e fácil de ser assimilado. Bons estudos e entre em contato sempre que quiser! :punch: ## 🚨 Colabore - Abra Pull Requests com atualizações - Discuta ideias em Issues - Compartilhe o repositório com a sua comunidade - Mande feedbacks no [LinkedIn](https://www.linkedin.com/in/arthurspk/) ## 🌍 Tradução > Se você deseja acompanhar esse repositório em outro idioma que não seja o Português Brasileiro, você pode optar pelas escolhas de idiomas abaixo, você também pode colaborar com a tradução para outros idiomas e a correções de possíveis erros ortográficos, a comunidade agradece. <img src = "https://i.imgur.com/lpP9V2p.png" alt="Guia Extenso de Programação" width="16" height="15">・<b>English — </b> [Click Here](https://github.com/arthurspk/guiadevbrasil)<br> <img src = "https://i.imgur.com/GprSvJe.png" alt="Guia Extenso de Programação" width="16" height="15">・<b>Spanish — </b> [Click Here](https://github.com/arthurspk/guiadevbrasil)<br> <img src = "https://i.imgur.com/4DX1q8l.png" alt="Guia Extenso de Programação" width="16" height="15">・<b>Chinese — </b> [Click Here](https://github.com/arthurspk/guiadevbrasil)<br> <img src = "https://i.imgur.com/6MnAOMg.png" alt="Guia Extenso de Programação" width="16" height="15">・<b>Hindi — </b> [Click Here](https://github.com/arthurspk/guiadevbrasil)<br> <img src = "https://i.imgur.com/8t4zBFd.png" alt="Guia Extenso de Programação" width="16" height="15">・<b>Arabic — </b> [Click Here](https://github.com/arthurspk/guiadevbrasil)<br> <img src = "https://i.imgur.com/iOdzTmD.png" alt="Guia Extenso de Programação" width="16" height="15">・<b>French — </b> [Click Here](https://github.com/arthurspk/guiadevbrasil)<br> <img src = "https://i.imgur.com/PILSgAO.png" alt="Guia Extenso de Programação" width="16" height="15">・<b>Italian — </b> [Click Here](https://github.com/arthurspk/guiadevbrasil)<br> <img src = "https://i.imgur.com/0lZOSiy.png" alt="Guia Extenso de Programação" width="16" height="15">・<b>Korean — </b> [Click Here](https://github.com/arthurspk/guiadevbrasil)<br> <img src = "https://i.imgur.com/3S5pFlQ.png" alt="Guia Extenso de Programação" width="16" height="15">・<b>Russian — </b> [Click Here](https://github.com/arthurspk/guiadevbrasil)<br> <img src = "https://i.imgur.com/i6DQjZa.png" alt="Guia Extenso de Programação" width="16" height="15">・<b>German — </b> [Click Here](https://github.com/arthurspk/guiadevbrasil)<br> <img src = "https://i.imgur.com/wWRZMNK.png" alt="Guia Extenso de Programação" width="16" height="15">・<b>Japanese — </b> [Click Here](https://github.com/arthurspk/guiadevbrasil)<br> ## 🗺️ Frontend Roadmap  ## ◾ HTTP > O Hypertext Transfer Protocol, sigla HTTP é um protocolo de comunicação utilizado para sistemas de informação de hipermídia, distribuídos e colaborativos. Ele é a base para a comunicação de dados da World Wide Web. - [MDN - HTTP](https://developer.mozilla.org/pt-BR/docs/Web/HTTP) - O MDN Web Docs é o website oficial de Mozilla para desenvolvimento de padrões web ## ◾ HTML > HTML (Linguagem de Marcação de HiperTexto) é o bloco de construção mais básico da web. Define o significado e a estrutura do conteúdo da web. Outras tecnologias além do HTML geralmente são usadas para descrever a aparência/apresentação (CSS) ou a funcionalidade/comportamento (JavaScript) de uma página da web, sendo assim HTML é uma linguagem essência para você que quer se tornar desenvolvedor front-end. - [MDN - HTML](https://developer.mozilla.org/pt-BR/docs/Web/HTML) - O MDN Web Docs é o website oficial de Mozilla para desenvolvimento de padrões web - [Cursos de HTML](https://github.com/arthurspk/guiadevbrasil#-cursos-de-html-e-css) - Cursos de HTML do repositório geral do Guia Dev Brasil ## ◾ CSS > CSS (Cascading Style Sheets) é um mecanismo para adicionar estilo a um documento web. O código CSS pode ser aplicado diretamente nas tags ou ficar contido dentro das tags <style>. Também é possível, em vez de colocar a formatação dentro do documento, criar um link para um arquivo CSS que contém os estilos. - [MDN - CSS](https://developer.mozilla.org/pt-BR/docs/Web/CSS) - O MDN Web Docs é o website oficial de Mozilla para desenvolvimento de padrões web - [Cursos de CSS](https://github.com/arthurspk/guiadevbrasil#-cursos-de-html-e-css) - Cursos de CSS do repositório geral do Guia Dev Brasil ## ◾ JavaScript > JavaScript é uma linguagem de programação interpretada estruturada, de script em alto nível com tipagem dinâmica fraca e multiparadigma. Juntamente com HTML e CSS, o JavaScript é uma das três principais tecnologias da World Wide Web. - [MDN - JavaScript](https://developer.mozilla.org/pt-BR/docs/Web/CSS) - O MDN Web Docs é o website oficial de Mozilla para desenvolvimento de padrões web - [Cursos de JavaScript](https://github.com/arthurspk/guiadevbrasil#-cursos-de-javascript) - Cursos de JavaScript do repositório geral do Guia Dev Brasil ## ◾ Frameworks > Framework é um conjunto de códigos prontos que podem ser usados no desenvolvimento de aplicativos e sites. O objetivo dessa ferramenta é aplicar funcionalidades, comandos e estruturas já prontas para garantir qualidade no desenvolvimento de um projeto, cada linguagem possi diversos frameworks que podem ser utilizado para te ajudar em umafuncionalidade específica, por configuração, durante a programação de uma aplicação. - [Frameworks para HTML](https://www.webfx.com/blog/web-design/html5-frameworks/) - 10 frameworks responsivos para ser utilizado no HTML5 - [Frameworks para CSS](https://rockcontent.com/br/talent-blog/frameworks-css/) - 14 frameworks que podem ser utilizados no seu CSS - [Frameworks no front-end](https://mundodevops.com/blog/framework-front-end/) - Frameworks mais utilizados no front-end - [Frameworks e bibliotecas JavaScript](https://blog.geekhunter.com.br/frameworks-javascript-e-bibliotecas-java/#:~:text=Um%20framework%20JavaScript%20%C3%A9%20uma,ficar%20reescrevendo%20linhas%20de%20c%C3%B3digo.) - Frameworks e bibliotecas para ser utilizadas no JavaScript ## ◾ APIs > O conceito de API nada mais é do que uma forma de comunicação entre sistemas. Elas permitem a integração entre dois sistemas, em que um deles fornece informações e serviços que podem ser utilizados pelo outro, sem a necessidade de o sistema que consome a API conhecer detalhes de implementação do software, as APIs permitem que o usuário final utilize um aplicativo, software ou até uma simples planilha, consultando, alterando e armazenando dados de diversos sistemas, sem que o usuário precise acessá-los diretamente. - [MDN - APIs](https://developer.mozilla.org/pt-BR/docs/Web/API) - O MDN Web Docs é o website oficial de Mozilla para desenvolvimento de padrões web - [APIs Públicas](https://github.com/public-apis/public-apis) - Uma lista coletiva de APIs gratuitas para uso em software e desenvolvimento web ## 📚 Recomendação de livros - [Clean Code - Código Limpo](https://g.co/kgs/62wx9t) - [Refactoring - Refatoração](https://g.co/kgs/Hf2eY3) - [Clean Archtecture - Arquitertura Limpa](https://g.co/kgs/Hf2eY3) - [O programador pragmático](https://g.co/kgs/5nbqB3) ## 🛠️ Ferramentas > ◾ Sites para desenvolvedor front-end - [Text Pop 3D](https://textpop3d.web.app/) - Cria efeitos de texto 3D - [Shape Dividers](https://shapedividers.com) - Gera divisores de formas verticais, responsivos, e animados facilmente com este gerador de divisores de formas SVG - [Couleur](https://couleur.io) - Uma ferramenta de cores simples para ajudá-lo a encontrar uma boa paleta de cores para seu projeto da web) - [Baseline CSS Filters](https://baseline.is/tools/css-photo-filters/) - 36 Belos filtros de fotos, com edição simples e CSS para copiar) - [UI Deck](https://uideck.com) - Modelo de página de destino HTML gratuitos e premium, temas de bootstrap, modelos de React, modelos de Tailwind, modelos de site HTML, e kits de interface de usúario) - [Naevner](https://naevner.com) - Descrição de cores em linguagem natural, gerador de códigos em cores hexadecimais) > ◾ Templates HTML gratuitos - [Bootstrap Made](https://bootstrapmade.com/) - Temas HTML5 + CSS3 gratuitos - [W3 Layouts](https://w3layouts.com) - Temas HTML5 + CSS3 gratuitos - [One Page Love](https://onepagelove.com) - Temas HTML5 + CSS3 gratuitos - [ThemeWagon Freebies](https://themewagon.com/theme_tag/free/) - Temas HTML5 + CSS3 gratuitos > ◾ Sites para aprender ou treinar CSS - [CSS Grid Garden](http://cssgridgarden.com/) - Ferramenta online para estudos de Grid (CSS) - [Flukeout](http://flukeout.github.io/) - Aplicação online para aprender CSS de forma prática - [Flex Box Froggy](https://flexboxfroggy.com/) - Desafio de Programação Front-end focados na propriedade flex box. IDE integrada. - [Flexbox Defense](http://www.flexboxdefense.com/) - Aprenda flexbox com um game - [100 Dias de CSS](https://100dayscss.com) - 100 Desafios de CSS - [CSS Battle](https://cssbattle.dev/) - Batalhas temporárias de CSS. IDE integrada - [CSS Tricks](https://css-tricks.com/guides/) - Site para treinar - [CSS Hell](https://csshell.dev/) - Coleção de erros comuns de CSS e como corrigi-los > ◾ Geradores de CSS - [Neumorphism](https://neumorphism.io/) - Tendência aplicação border-radius - [Fancy Border-Radius](https://9elements.github.io/fancy-border-radius/) - Gerador de formas com border-radius no CSS - [WAIT! Animate](https://waitanimate.wstone.io) - Gerador de animações de CSS - [Best CSS Button Generator](https://www.bestcssbuttongenerator.com) - Gerador de butões do CSS - [HTML CSS JS Generator](https://html-css-js.com/css/generator/) - Gerador de HTML/CSS/JS - [BennettFeely](https://bennettfeely.com/clippy/) - Criador de clip-path > ◾ Ferramentas de desenvolvimento - [Internxt](https://internxt.com/) - Internxt Drive é um armazenamento de arquivos de conhecimento zero serviço baseado na melhor privacidade e segurança da classe - [Motion](https://motion.dev/) - Uma nova biblioteca de animação, construída na API Web Animations para o menor tamanho de arquivo e o desempenho mais rápido. - [Hokusai](https://hokusai.app/) - Conteúdo sobre NFT's - [Hidden Tools](https://hiddentools.dev) - Ampla coleção de ferramentas feitas pela comunidade disponiveís para uso - [Dev Hints](https://devhints.io) - Coleção de cheatsheets - [Bundlephobia](https://bundlephobia.com) - Descubra o custo de adicionar um pacote npm ao seu pacote - [Refactoring Guru](https://refactoring.guru/pt-br/design-patterns) - Padrões de projetos "Design patterns" - [DevDocs](https://devdocs.io/) - DevDocs combina várias documentações de API em uma interface rápida, organizada e pesquisável. - [HTML Validator](https://www.freeformatter.com/html-validator.html) - Validação de arquivo HTML - [HTML 5 Test](https://html5test.com/index.html) - Testa arquivos HTML5 - [Image Slide Maker](https://imageslidermaker.com/v2) - Ferramenta de geração gratuita do Image Slider Maker - [.NET Fiddle](https://dotnetfiddle.net/) - Codifique e compartilhe projetos C# online - [1PageRank](http://www.1pagerank.com/) - Rankeie seu site nos mecanismos de buscas e aprenda com a concorrência - [Any API](https://any-api.com/) - Diretório gratuito com APIs públicas - [Autoprefixer CSS](http://autoprefixer.github.io/) - Transpile código CSS atual para código CSS com maior cobertura de navegadores antigos - [Browser diet](https://browserdiet.com/pt/) - Guia de performance para desenvolvimento web - [Can I email...](https://www.caniemail.com/) - Descubra o que do HTML e CSS pode ser usado em estruturas de e-mail - [Can I use...](https://caniuse.com/) - Descubra se você pode usar determinadas tecnologias web - [CloudFlare](https://www.cloudflare.com/pt-br/) - CDN grátis - [CMDER](https://cmder.net/) - Linha de comando simples, consegue rodar comands bash e Shell, alternativa ao Hyper - [CodePen](https://codepen.io/) - Rede social de desenvolvedores front-end - [CodeSandbox](https://codesandbox.io/) - Caixa de área para desenvolvedores web - [Connection Strings](https://www.connectionstrings.com/) - Site com strings de conexão para diversas plataformas - [CSS Formatter](https://www.cleancss.com/css-beautify/) - Retire a minificação e formate o código CSS - [CSS Minifier](https://cssminifier.com/) - Conversor de código CSS para CSS minificado - [CSS W3.org](https://jigsaw.w3.org/css-validator/) - Validar CSS - [Debuggex: Online visual regex tester. JavaScript, Python, and PCRE](https://www.debuggex.com) - Construa e teste expressões regulares - [docsify](https://docsify.js.org/#/) - Crie docs incríveis de projetos - [EasyForms](https://easyforms.vercel.app/) - API open source que permite criação formulários de contato com HTML puro - [Editor.md](https://pandao.github.io/editor.md/en.html) - Editor Markdown online e open source - [ES6console](https://es6console.com/) - Compilador de JS para Ecmascript - [Firebase](https://firebase.google.com/?hl=pt-BR) - Desenvolva aplicativos mobile e web incríveis este serviço da Google - [Firefox Developer Edition](https://www.mozilla.org/pt-BR/firefox/developer/) - Navegador web para desenvolvedores web - [Full Page Screen Capture](https://chrome.google.com/webstore/detail/full-page-screen-capture/fdpohaocaechififmbbbbbknoalclacl?hl=pt-BR) - Capture páginas inteiras com uma extensão para Chrome - [generatedata](http://www.generatedata.com/) - Gerador de dados para testes - [Git Command Explorer](https://gitexplorer.com/) - Encontre os comandos certos que você precisa sem vasculhar a web - [GitHub Gist](https://gist.github.com/) - Faça pequenas anotações e pequenos códigos no GitHub Gist - [Google Transparency Report](https://transparencyreport.google.com/safe-browsing/search) - Verificar segurança de um site - [Grader](https://website.grader.com/) - Avaliação de site - [How to Center in CSS](http://howtocenterincss.com/) - Gerador de código para divs ou textos que necessitam de centralização - [Hyper](https://hyper.is/) - Linha de comando simples, útil e gratuito - [Joomla](https://www.joomla.org/) - CMS gratuita - [JS Bin](https://jsbin.com/) - Codifique e compartilhe projetos HTML, CSS e JS - [JSCompress](https://jscompress.com/) - Conversor de código JS para JS minificado - [JSON Editor Online](https://jsoneditoronline.org/) - Ferramenta para visualizar e editar arquivos JSON - [JSFiddle](https://jsfiddle.net/) - Codifique projetos JS online - [JSONLint](https://jsonlint.com/) - Ferramenta para validar seu JSON - [JSON Generator](https://app.json-generator.com/) - Ferramenta para gerar JSON com base em template - [KeyCDN Tools](https://tools.keycdn.com/) - Faça uma análise das suas aplicações web - [Liveweave](https://liveweave.com/) - Codifique projetos HTML, CSS e JS - [Lorem Ipsum](https://br.lipsum.com/) - Gerador de texto fictício - [Mapbox](https://www.mapbox.com/) - Mapas e localização para desenvolvedores - [Memcached](https://memcached.org/) - Melhore o desempenho de seu website com cache - [Mockaroo](https://www.mockaroo.com/) - Gerador de dados para testes - [Mussum Ipsum](https://mussumipsum.com/) - Gerador de texto fictício - [NPM HTTP-Server](https://www.npmjs.com/package/http-server) - Rode um servidor local com um pacote npm - [Password Generator](https://danieldeev.github.io/password-generator/) - Um gerador de senhas simples com foco na segurança - [Online C Compiler](https://www.onlinegdb.com/online_c_compiler) - Ferramenta para compilar C online - [React Dev Tools](https://chrome.google.com/webstore/detail/react-developer-tools/fmkadmapgofadopljbjfkapdkoienihi) - Ferramenta para debug do ReactJS - [React Hook Form](https://react-hook-form.com/) - Valide seus formulários de projetos que utilizam React ou React Native - [RelaX](http://dbis-uibk.github.io/relax/index.htm) - Crie expressões algébricas relacionais de consultas - [Responsive](http://www.codeorama.com/responsive/) - Teste a responsividade do seu site - [Shields.io](https://shields.io/) - Gerador de badges para markdown - [SSL Server Test](https://www.ssllabs.com/ssltest/) - Testar SSL de sites - [StreamYard](https://streamyard.com/) - O StreamYard é um estúdio de transmissões ao vivo no seu navegador - [Swagger](https://swagger.io/) - Ferramenta para projetar, construir, documentar e usar serviços da Web RESTful - [Tabela ASCII](https://web.fe.up.pt/~ee96100/projecto/Tabela%20ascii.htm) - Tabela completa com caracteres ASCII - [Telegram](https://telegram.org/) - Mensageiro criptografado - [TinyJPG](https://tinyjpg.com/) - Comprima imagem do formato JPG - [TinyPNG](https://tinypng.com/) - Comprima imagem do formato PNG - [Creately](https://creately.com/) - Crie e altere lindos diagramas em tempo real com a sua equipe - [Carbon](https://carbon.now.sh/) - Crie Snippets de codigo clean e bonitos - [DbDiagram](https://dbdiagram.io/home) - Crie elegrantes diagramas de banco de dados e gere script ddl - [SqlDesigner](https://ondras.zarovi.cz/sql/demo/) - Crie Diagramas de banco de dados de maneira rapida e gere script ddl - [W3.org](https://validator.w3.org/) - Validar HTML - [WakaTime](https://wakatime.com/) - Gerencie seu tempo de desenvolvimento - [Web Developer](https://chrome.google.com/webstore/detail/web-developer/bfbameneiokkgbdmiekhjnmfkcnldhhm?hl=pt-BR) - Extensão para Chrome com multi-funções - [Web.dev](https://web.dev/) - Testar website (criado pela Google) - [WebPageTest](https://www.webpagetest.org/) - Testar perfomance de site - [Wedsites](https://wedsites.com/) - Liste suas atividades e acompanhe seu progresso - [WordPress](https://wordpress.org/) - Criação de blogs - [XML Sitemaps](https://www.xml-sitemaps.com/) - Criador de sitemaps.xml - [Minimamente](https://www.minimamente.com/project/magic/) - Efeitos para utilizar no CSS - [Hamburgers](https://jonsuh.com/hamburgers/) - Menu de hamburgers para utilizar em CSS - [Hover Effects](https://ianlunn.github.io/Hover/) - Hover effects para utilizar no CSS > ◾ Design front-end - [Adobe XD](https://www.adobe.com/br/products/xd.html) - Software de design para projetos - [Awwwards](https://www.awwwards.com) - Inspiração para interfaces e templates com o que há de mais novo em questão de design de interfaces - [Bootstrap](https://www.getbootstrap.com/) - Framework CSS - [BuildBootstrap](https://buildbootstrap.com/) - Crie layout responsivo para o framework Bootstrap na versão 3 e 4 - [Bulma CSS](https://bulma.io/) - Estrutura CSS gratuita baseada no Flexbox - [Canva](https://www.canva.com/) - Ferramenta de design online - [Chart.js](https://www.chartjs.org/) - Biblioteca JavaScript de criação de gráficos - [Colors and Fonts](https://www.colorsandfonts.com/) - Apresenta paletas de cores e tipografia - [Coolors](https://coolors.co/) - Palhetas de cores e monte a sua própria - [Colors lol](https://colors.lol) - Repositório de paletas de cores - [Cruip](https://cruip.com/) - Recursos de templates - [CSS Effects Snippets](https://emilkowalski.github.io/css-effects-snippets/) - Animações CSS prontas para usar - [CSS Layout](https://csslayout.io/) - Layouts e padrões populares feitos com CSS - [CSS Reference](https://cssreference.io/) - Guia visual para CSS com referencias de uso - [CSS Tricks](https://css-tricks.com/) - Blog com vários tutoriais frontend - [DevSamples](https://www.devsamples.com/) - Exemplos de códigos fáceis de usar para HTML, CSS e JavaScript - [Excalidraw](https://excalidraw.com) - Desenhe diagramas como se tivessem sido feitos a mão - [Fancy Border-Radius](https://9elements.github.io/fancy-border-radius/) - Gerador de formas com border-radius no CSS - [Figma](https://www.figma.com/) - Desenhe projetos online de apps, softwares e websites - [Flatui Color Picker](http://www.flatuicolorpicker.com/) - Paleta de cores interativa de forma harmonizar o front - [Font Flipper](https://fontflipper.com/) - Ferramenta para testar fontes - [FontPair](https://fontpair.co/) - Ferramenta para combinações de fontes - [FontSpark](https://fontspark.app/) - Gera fontes aleatórias de uma lista de fontes famosas usadas na web - [Foundation](https://foundation.zurb.com/) - Framework responsivo - [Framer](https://www.framer.com/) - Ferramenta de criação de interfaces interativas - [FreeFrontEnd](https://freefrontend.com/) - Exemplos de códigos, tutoriais e artigos de HTML, CSS, Javascript (Angular, JQuery, React, Vue) - [Gravit Designer](https://www.designer.io) - Ferramenta de design online com suporte a ilustração vetorial - [Grid Layoutit](https://grid.layoutit.com/) - Gerador de grid para código CSS - [HTML DOM](https://htmldom.dev/) - Gerenciar o DOM HTML com JavaScript vanilla - [Interfacer](https://interfacer.xyz/) - Recursos para criação de interfaces - [Interfaces.pro](https://interfaces.pro/) - Inspiração para interfaces - [Invision](https://www.invisionapp.com/) - Software de design para projetos - [Lottie](https://lottiefiles.com/) - Animações em after effects via json - [Luna](https://github.com/OfficialMarinho/luna) - Framework CSS brasileiro - [Material-UI](https://material-ui.com/) - Um framework de interface de usuário para React - [Mockup](https://mockup.io/about/) - Visualize e colabore no design de aplicativos para dispositivos móveis - [Nes.css](https://nostalgic-css.github.io/NES.css/) - Framework CSS estilo NES - [Neumorphism](https://neumorphism.io/) - Tendência aplicação border-radius - [Normalize CSS](https://necolas.github.io/normalize.css/) - Normaliza estruturas entre navegadores - [Pixilart](https://www.pixilart.com/draw) - Desenhe pixel arts online - [Pixlr](https://pixlr.com/br/) - Conjunto de ferramentas e utilitários de edição de imagem baseado em nuvem - [PSD-To-CSS-Shadow](http://psd-to-css-shadows.com/) - Gera o script para uma sombra (box-shadow & text-shadow) no CSS baseado nas configurações de sombra no Photoshop - [Pure.css](https://purecss.io/) - Framework CSS responsivo - [Remove.bg](https://www.remove.bg/) - Remove fundos de imagens automaticamente - [Sketch](https://www.sketch.com/) - Desenvolvimento de layouts em alta qualidade - [Squoosh.app](https://squoosh.app/) - Compressor de imagens e comparador, via navegador - [SweetAlert2](https://sweetalert2.github.io/) - Biblioteca JavaScript de alertas responsivos e customizáveis - [Tailwind CSS](https://tailwindcss.com/) - Framework de estilo CSS - [UI Gradients](https://uigradients.com/) - UI gradientes para utilizar - [Vectorizer](https://www.vectorizer.io/) - Converta imagens como PNGs, BMPs e JPEGs em gráficos vetoriais ​​(SVG, EPS, DXF) - [Whimsical](https://whimsical.com/) - Flowchart, Wireframe, Sticky Notes e Mind Map - [X-Icon Editor](http://www.xiconeditor.com/) - Gerador de favicon com alta resolução a partir de imagens > ◾ Desafios - [Ace Front End](https://www.acefrontend.com/) - Desafios de programação Front-end. Resultados via texto. IDE integrada - [AdventoOfCode](https://adventofcode.com/) - Desafios de programação por temporada. Sem IDE integrada. Validação manual feita pelo usuário - [App Ideas](https://github.com/florinpop17/app-ideas) - Compilado de desafios para você testar seus conhecimentos e aumentar seu portfólio - [CodePen Challenges](https://codepen.io/challenges) - Desafios de Programação Front-end. IDE integrada - [Codier](https://codier.io/challenge) - Desafios de Programação Front-end, análise dos resultados feita pela comunidade. IDE integrada - [CSS Battle](https://cssbattle.dev/) - Batalhas temporárias de CSS. IDE integrada - [DevChallenge](https://www.devchallenge.com.br/) - Site com desafios de front-end, back-end e mobile - [Flex Box Defense](http://www.flexboxdefense.com/) - Desafio de Programação Front-end focados na propriedade flex box. IDE integrada. - [Flex Box Froggy](https://flexboxfroggy.com/) - Desafio de Programação Front-end focados na propriedade flex box. IDE integrada. - [Front End Challanged Club](https://piccalil.li/category/front-end-challenges-club) - Bogs com desafios de programação front-end - [Frontend Challengens](https://github.com/felipefialho/frontend-challenges) - Repositório no GitHub com vários desafios solicitados reais solicitados por empresas - [Frontend Mentor](https://www.frontendmentor.io/) - Desafios de Programação Front-end, análise dos resultados feita pela comunidade, sem IDE integrada - [Code Well](https://codewell.cc/) - Treine suas habilidade de HTML e CSS com alguns templates > ◾ Bibliotecas para JavaScript - [Lax.js](https://github.com/alexfoxy/lax.js) - [Swiper](https://swiperjs.com/) - [WOW](https://wowjs.uk/) - [Animate](https://animate.style/) - [ApexCharts](https://apexcharts.com/) - [Particles.js](https://vincentgarreau.com/particles.js/) - [ScrollMagic](https://scrollmagic.io/) > ◾ Ferramentas para hospedar seu site - [Github Pages](https://pages.github.com/) - Hospedado diretamente de seu repositório GitHub. Basta editar, enviar e suas alterações entrarão em vigor - [Award Space](https://www.awardspace.com/) - Hospedagem gratuita na web + um subdomínio gratuito, PHP, MySQL, instalador de aplicativo, envio de e-mail e sem anúncios - [Byet](https://byet.host/) - Hospedagem Gratuita e Serviços de Hospedagem Premium. - [Infinity Free](https://infinityfree.net/) - Free Unlimited Web Hosting - [1FreeHosting](http://www.1freehosting.com/) - Hospedagem de sites grátis com 100GB de largura de banda - [Amazon Web Services](https://aws.amazon.com/pt/) - Serviço de aluguel de servidores e outros serviços - [BlueHost](https://www.bluehost.com/) - Empresa americana de hospedagem de sites - [DigitalOcean](https://www.digitalocean.com/) - Aluguel de servidores dedicados e compartilhados - [DreamHost](https://www.dreamhost.com/) - Hospedagem de sites de alta disponibilidade - [Embratel](https://www.embratel.com.br/cloud/hospedagem-de-sites) - Hospedagem de sites nacional - [GoDaddy](https://br.godaddy.com/hosting/web-hosting) - Hospedagem de sites internacional - [GoDaddy](https://br.godaddy.com/) - Empresa de aluguel de servidores compartilhados, dedicados e registro de domínio - [Google Cloud](https://cloud.google.com/solutions/smb/web-hosting/) - Serviço de aluguel de servidores da Google - [Heroku](https://www.heroku.com/) - Hospedagem de sites grátis com suporte à NodeJS, Java, Ruby, PHP, Python, Go, Scala e Clojure - [HostGator](https://www.hostgator.com/) - Hospedagem compartilhada e dedicada para sites e serviços - [Hostinger](https://www.hostinger.com.br/) - Hospedagem de sites - [Hostoo](https://hostoo.io/) - Hospedagem de sites em cloud computing dedicado - [iPage](https://www.ipage.com/) - Hospedagem de sites gringa com descontos para anúncios - [KingHost](https://king.host/) - Hospedagem compartilhada e dedicada para sites e serviços de marketing por e-mail - [Netlify](https://www.netlify.com/) - Hospedagem para sites estáticos que combina implantação global, integração contínua e HTTPS automático - [One.com](https://www.one.com/pt-BR/) - Serviços gerais digitais (incluindo hospedagem de sites) - [Surge](https://surge.sh/) - Hospedagem gratuita para páginas estáticas - [Umbler](https://www.umbler.com/br) - Hospedagem compartilhada, cloud computing sob taxação de uso - [Vercel](https://vercel.com/) - Hospedagem grátis de sites estáticos e serveless > ◾ Sites para inspirar o seu desenvolvimento - [Product Hunt](https://www.producthunt.com/) - [Namify](https://namify.tech/?ref=producthunt) - [Dribbble](https://dribbble.com/) - [Pinterest](https://br.pinterest.com/) - [Deviant Art](https://www.deviantart.com/) - [Lapa](https://www.lapa.ninja/) - [Hyper Pixel](https://hyperpixel.io/) - [One Page Love](https://onepagelove.com/) - [One Page Love Avatars](https://onepagelove.com/boring-avatars) - [Land Book](https://land-book.com/) - [Awwwards](https://www.awwwards.com) - [Best Folios](https://www.bestfolios.com/home) - [Sitesee](https://sitesee.co/) - [Httpster](https://httpster.net/2021/jun/) - [Builders Club](https://builders-club.com/) - [CSS Nectar](https://cssnectar.com/) - [Collect UI](https://collectui.com) - [Best Web Site](https://bestwebsite.gallery) > ◾ Banco de imagens gratuitas - [500px](https://500px.com/creativecommons) - Banco de imagens gratuitas - [Burst](https://pt.shopify.com/burst) - Plataforma de imagens do serviço de ecommerce Shopify - [Cupcake](http://cupcake.nilssonlee.se/) - Imagens gratuitas para uso comercial - [Banco De Imagens Com Diversidade](https://github.com/JulianaHelena5/BancoDeImagensComDiversidade) - Banco de imagens com pessoas diversas - [DrawKIT](https://www.drawkit.io/) - Ilustrações para qualquer um usar - [FlatIcon](https://www.flaticon.com) - Banco de ícones vetoriais - [Flickr](https://flickr.com/) - Rede social de fotógrafos - [FreeImages](https://pt.freeimages.com/) - Banco de imagens gratuitas - [FreePik Stories](https://stories.freepik.com/) - Banco de ilustrações gratuitas - [Freerange](https://freerangestock.com/index.php) - Banco de imagens gratuitas - [Glaze](https://www.glazestock.com) - Banco de ilustrações, sem direitos autorais - [Gratisography](https://gratisography.com/) - Banco de imagens gratuitas - [Humaaans](https://www.humaaans.com/) - Ilustrações de humanóides - [Icons8](https://icons8.com.br/) - Ícones em diversos estilos - [Imgur](https://imgur.com/) - Plataforma com milhões de imagens - [IraDesign](https://iradesign.io/illustrations) - Ilustrações editáveis de cores e objetos - [Life of Pix](https://www.lifeofpix.com/) - Banco de imagens gratuitas - [Little Visuals](https://littlevisuals.co/) - Banco de imagens gratuitas - [Lorempixel](http://lorempixel.com/) - Banco de imagens para uso como template - [Lukas Zadam](https://lukaszadam.com/illustrations) - Ilustrações SVG em diferentes tamanhos e estilos - [ManyPixels](https://www.manypixels.co/gallery/) - Galeria de ilustrações com direito a edição de cores - [Morguefile](https://morguefile.com/) - Banco de imagens gratuitas - [Nappy](https://www.nappy.co) - Banco de imagens gratuitas (atribuição recomendada) - [Nos.twnsnd](https://nos.twnsnd.co/) - Arquivo público de fotos antigas - [OpenMoji](https://openmoji.org/) - Banco de emojis para uso - [Pexels](https://www.pexels.com/) - Banco de imagens gratuitas - [PhotoPin](http://photopin.com/) - Banco de imagens gratuitas no estilo criativo - [Picjumbo](https://picjumbo.com/) - Banco de imagens gratuitas - [Picsum](https://picsum.photos/) - Banco de imagens para uso como template - [Pixabay](http://www.pixabay.com) - Banco de imagens gratuitas (não requer atribuição) - [Public domain archive](https://www.publicdomainarchive.com/) - Banco de imagens gratuitas - [RemixIcon](https://remixicon.com/) - Banco de Ícones para uso gratuito - [StockSnap](https://stocksnap.io/) - Banco de imagens gratuitas (não requer atribuição) - [unDraw](https://undraw.co/) - Ilustrações livres para usar - [Unsplash](https://unsplash.com/) - Banco de imagens gratuitas - [Visual Hunt](https://visualhunt.com/) - Banco de imagens gratuitas - [Wikimedia Commons](https://commons.wikimedia.org/wiki/Main_Page) - Banco de imagens mundial > ◾ Sites para baixar e encontrar fontes - [Adobe Fonts](https://fonts.adobe.com/) - [Google fonts](https://fonts.google.com/) - [Dafont](https://www.dafont.com/pt/) - [NetFontes](https://www.netfontes.com.br/) - [Urbanfonts](https://www.urbanfonts.com/pt/) - [Befonts](https://befonts.com/) - [Fonts space](https://www.fontspace.com/) - [1001 fonts](https://www.1001fonts.com/) - [Abstract fonts](https://www.abstractfonts.com/) - [Fontget](https://www.fontget.com/) - [Material Design Icons](https://materialdesignicons.com/) > ◾ Sites de paletas de cores - [Paletton](https://paletton.com/) - [Adobe Color](https://color.adobe.com/pt/create/color-wheel/) - [Color Hunt](https://colorhunt.co/) - [Happy Hues](https://www.happyhues.co/) - [Coolors](https://coolors.co/) - [Gradient Hunt](https://gradienthunt.com/) - [Flat UI Colors](https://flatuicolors.com/) - [Grabient](https://www.grabient.com/) - [Pigment](https://pigment.shapefactory.co/) - [WebGradient](https://webgradients.com/) - [Color.lol](https://colors.lol/) ◾ Lista de ilustrações - [DrawKIT](https://www.drawkit.io/) - [Humaaans](https://www.humaaans.com/) - [Open Doodle](https://www.opendoodles.com/) - [Storyset](https://storyset.com/) - [unDraw](https://undraw.co/) - [404 Illustrations (by kapwing)](https://www.kapwing.com/404-illustrations/) - [404 Illustrations](https://error404.fun/) - [Ouch](https://icons8.com.br/illustrations/) - [Delesing](https://delesign.com/free-designs/graphics/) - [Pixeltru](https://www.pixeltrue.com/free-illustrations/) - [Iconscout](https://iconscout.com/) > ◾ Site de icones - [DrawKIT](https://www.drawkit/free-icons/) - [Eva Icons](https://akveo.github.io/eva-icons/#/) - [Feather Icons](https://feathericons.com/) - [Font Awesome](https://fontawesome.com) - [Heroicons](https://heroicons.dev/) - [Iconsvg](https://iconsvg.xyz/) - [Icons8 Line Awesome](https://icons8.com/line-awesome/) - [Icons8](https://icons8.com.br/) - [Shape](https://shape.so/) - [Flaticon](https://www.flaticon.com/br/) - [Bootstrap icons](https://icons.getbootstrap.com/) - [devicon](https://devicon.dev/) > ◾ Extensões para o seu navegador - [File Icons for GitHub and GitLab](https://chrome.google.com/webstore/detail/file-icons-for-github-and/ficfmibkjjnpogdcfhfokmihanoldbfe) - [GoFullPage](https://chrome.google.com/webstore/detail/gofullpage-full-page-scre/fdpohaocaechififmbbbbbknoalclacl) - [Web Developer](https://chrome.google.com/webstore/detail/web-developer/bfbameneiokkgbdmiekhjnmfkcnldhhm?hl=pt-BR) - [React Developer Tools](https://chrome.google.com/webstore/detail/react-developer-tools/fmkadmapgofadopljbjfkapdkoienihi) - [Window Resizer](https://chrome.google.com/webstore/detail/window-resizer/kkelicaakdanhinjdeammmilcgefonfh?hl=pt-BR) - [Vue Devtools](https://chrome.google.com/webstore/detail/vuejs-devtools/nhdogjmejiglipccpnnnanhbledajbpd?hl=pt-BR) - [Dark Reader](https://chrome.google.com/webstore/detail/dark-reader/eimadpbcbfnmbkopoojfekhnkhdbieeh?hl=pt-BR)

Nesse guia você encontrará tudo para se torna um desenvolvedor front-end, dessa maneira, encontrará mapas mentais, cursos, trilhas e outras ferramentas para poder praticar o conhecimento adquirido.

css,javascript,html,css3,frontend,front-end-development,javascript-library,javascript-framework,javascript-applications,html5

lens-protocol/core

``` @@@@@@@@@ @@@@@@@@@@@@@@@@@@@@@ @@@@@@@@@@@@@@@@@@@@@@@@@@@@ @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ @@@@@@@@@@@ @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ @@@@@@@@@@@ @@@@@@@@@@@@@@@@@@@@@ @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ @@@@@@@@@@@@@@@@@@@@@@ @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ @@@@@@@@@@@@@@@@@@@@@@@@@@@@ @@@@@@@@@@@@@@ @@@@@@@@@@@@@@@@@@@@@@@@@@@@@ @@@@@@@@@@@@@@@@@@@@@@@@@ @@@@@@@ @@@@@@@@@ @@@@@@ @@@@@@@@@@@@@@@@@@@@@@@@@ @@@@@@@@@@@@@@@@@@@@@@ @@ @@@@@@@@ @@@@@@ @ @@@@@@@@ @@@@@@@@@@@@@@@@@@@@@@ @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ @@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@ ``` # Lens Protocol The Lens Protocol is a decentralized, non-custodial social graph. Lens implements unique, on-chain social interaction mechanisms analogous to commonly understood Web2 social media interactions, but significantly expanded with unique functionality that empower communities to form and participants to own their own social graph. ## Setup ### 1. Clone the Repository ``` git clone git@github.com:lens-protocol/core.git ``` ### 2. Install Foundry Follow the instructions from [their repository](https://book.getfoundry.sh/getting-started/installation) or just do: ``` curl -L https://foundry.paradigm.xyz | bash ``` ``` foundryup ``` ### 3. Install dependencies in submodules You can do it either with forge: ``` forge install ``` or directly with git: ``` git submodule update --init --recursive ``` ### 4. Create Your `.env` File Copy the `.env.example` file into `.env` and fill the necessary fields: ``` MNEMONIC= POLYGON_RPC_URL= MUMBAI_RPC_URL= KOVAN_RPC_URL= ROPSTEN_RPC_URL= MAINNET_RPC_URL= BLOCK_EXPLORER_KEY= TENDERLY_PROJECT= TENDERLY_USERNAME= TENDERLY_FORK_ID= TENDERLY_HEAD_ID= # Forking setup (uncomment to test using a fork) # TESTING_FORK=mainnet # TESTING_FORK_CURRENT_VERSION=1 # TESTING_FORK_BLOCK=45504400 ``` If you just want to test locally without a fork, then you can skip this step. ### 5. Build You can compile the project using: ``` forge build ``` You may notice a warning about some files exceeding code size. To avoid the warning, you can compile Via IR but it will take more time: ``` forge build --via-ir ``` ### 6. Test You can run unit tests using: ``` forge test ``` To run the tests on a fork you need to fill the `.env` file from the step above, and uncomment the `TESTING_FORK` variables. ### 7. Coverage You can run coverage using: ``` forge coverage ```

The Lens Protocol

s0md3v/Smap

<h1 align="center"> <br> <a href="https://github.com/s0md3v/smap"><img src="/static/smap-logo.png" alt="Smap logo"></a> </h1> <h4 align="center">passive Nmap like scanner built with shodan.io</h4> <p align="center"> <a href="https://github.com/s0md3v/Smap/releases"> <img src="https://img.shields.io/github/release/s0md3v/Smap.svg?label=version"> </a> <a href="https://github.com/s0md3v/Smap/releases"> <img src="https://img.shields.io/github/downloads/s0md3v/Smap/total"> </a> <a href="https://github.com/s0md3v/SMap/issues?q=is%3Aissue+is%3Aclosed"> <img src="https://img.shields.io/github/issues-closed-raw/s0md3v/Smap?color=dark-green&label=issues%20fixed"> </a> <a href="https://travis-ci.com/s0md3v/Smap"> <img src="https://img.shields.io/travis/com/s0md3v/Smap.svg?color=dark-green&label=tests"> </a> </p> <p align="center"><img src="/static/smap-demo.png" alt="Smap demo"></p> --- Smap is a port scanner built with shodan.io's free API. It takes same command line arguments as Nmap and produces the same output which makes it a drop-in replacament for Nmap. ## Features - Scans 200 hosts per second - Doesn't require any account/api key - Vulnerability detection - Supports all nmap's output formats - Service and version fingerprinting - Makes no contact to the targets ## Installation ### Binaries You can download a pre-built binary from [here](https://github.com/s0md3v/Smap/releases) and use it right away. ### Manual `go install -v github.com/s0md3v/smap/cmd/smap@latest` Confused or something not working? For more detailed instructions, [click here](https://github.com/s0md3v/Smap/wiki/FAQ#how-do-i-install-smap) ### AUR pacakge Smap is available on AUR as [smap-git](https://aur.archlinux.org/packages/smap-git) (builds from source) and [smap-bin](https://aur.archlinux.org/packages/smap-bin) (pre-built binary). ### Homebrew/Mac Smap is also avaible on [Homebrew](https://formulae.brew.sh/formula/smap). ``` brew update brew install smap ``` ## Usage Smap takes the same arguments as Nmap but options other than `-p`, `-h`, `-o*`, `-iL` are ignored. If you are unfamiliar with Nmap, here's how to use Smap. ### Specifying targets ``` smap 127.0.0.1 127.0.0.2 ``` You can also use a list of targets, seperated by newlines. ``` smap -iL targets.txt ``` **Supported formats** ``` 1.1.1.1 // IPv4 address example.com // hostname 178.23.56.0/8 // CIDR ``` ### Output Smap supports 6 output formats which can be used with the `-o* ` as follows ``` smap example.com -oX output.xml ``` If you want to print the output to terminal, use hyphen (`-`) as filename. **Supported formats** ``` oX // nmap's xml format oG // nmap's greppable format oN // nmap's default format oA // output in all 3 formats above at once oP // IP:PORT pairs seperated by newlines oS // custom smap format oJ // json ``` > Note: Since Nmap doesn't scan/display vulnerabilities and tags, that data is not available in nmap's formats. Use `-oS` to view that info. ### Specifying ports Smap scans these [1237 ports](https://gist.githubusercontent.com/s0md3v/3e953e8e15afebc1879a2245e74fc90f/raw/1e20288e9bef43b60f7306b6f7e23044dabd9b8c/shodan_ports.txt) by default. If you want to display results for certain ports, use the `-p` option. ``` smap -p21-30,80,443 -iL targets.txt ``` ## Considerations Since Smap simply fetches existent port data from shodan.io, it is super fast but there's more to it. You should use Smap if: #### You want - vulnerability detection - a super fast port scanner - results for most common ports (top 1237) - no connections to be made to the targets #### You are okay with - not being able to scan IPv6 addresses - results being up to 7 days old - a few false negatives

a drop-in replacement for Nmap powered by shodan.io

port-scanner,nmap,scanner,scanning,port-scanning,nmap-alternative,network-security,network-scanner

mrd0x/BITB

# BITB Browser templates for Browser In The Browser (BITB) attack. More information: https://mrd0x.com/browser-in-the-browser-phishing-attack/ # Usage Each folder has a `index.html` file which has 4 variables that must be modified: * **XX-TITLE-XX** - The title that shows up for the page (e.g. Sign in to your account now) * **XX-DOMAIN-NAME-XX** - Domain name you're masquerading as. (e.g. gmail.com) * **XX-DOMAIN-PATH-XX** - Domain path (e.g. /auth/google/login) * **XX-PHISHING-LINK-XX** - Phishing link which will be embedded into the iFrame (e.g. https://example.com) Furthermore, if you're using a Windows template you should update the `logo.svg` which is the icon of the website you're masquerading as. The default logo is Microsoft. # Windows-DarkMode-Delay The Windows-DarkMode-Delay folder makes use of jQuery's fadeIn() function to add a slight delay to the pop-up window as it appears. This is only one way of making the Window appear in a delayed fashion, there's various other ways to do the same. # Demo  # Detecting Color Preference To get the most out of this you should determine the OS from the user agent and the color preference and display the appropriate template. To find out if you should use dark or light templates check out: https://stackoverflow.com/questions/50840168/how-to-detect-if-the-os-is-in-dark-mode-in-browsers # Detecting BITB ## Dragging the Window One way of detecting BITB is by attempting to drag the window to the edge of the browser. If the window cannot escape the browser then it's not a real window. ## Browser Extension @odacavo released a great browser extension that can detect and warn users about embedded iframes. It's available here: https://github.com/odacavo/enhanced-iframe-protection All credits go to @odacavo. # Disclaimer Usage of these templates for attacking targets without prior consent is illegal. It's the end user's responsibility to obey all applicable laws. The developer is not responsible for any misuse of these templates.

Browser In The Browser (BITB) Templates

wgpsec/ENScan_GO

<p align="center"> <a href="https://github.com/wgpsec/ENScan_GO"> <img src="README/logo.png" alt="Logo" width="80" height="80"> </a> <h3 align="center">ENScan Go</h3> <p align="center"> 剑指HW/SRC，解决在HW/SRC场景下遇到的各种针对国内企业信息收集难题 <br /> <br /> <a href="https://github.com/wgpsec/ENScan_GO/stargazers"><img alt="GitHub stars" src="https://img.shields.io/github/stars/wgpsec/ENScan_GO"/></a> <a href="https://github.com/wgpsec/ENScan_GO/releases"><img alt="GitHub releases" src="https://img.shields.io/github/release/wgpsec/ENScan_GO"/></a> <a href="https://github.com/wgpsec/ENScan_GO/blob/main/LICENSE"><img alt="License" src="https://img.shields.io/badge/License-Apache%202.0-blue.svg"/></a> <a href="https://github.com/wgpsec/ENScan_GO/releases"><img alt="Downloads" src="https://img.shields.io/github/downloads/wgpsec/ENScan_GO/total?color=brightgreen"/></a> <a href="https://goreportcard.com/report/github.com/wgpsec/ENScan_GO"><img alt="Go Report Card" src="https://goreportcard.com/badge/github.com/wgpsec/ENScan_GO"/></a> <a href="https://twitter.com/wgpsec"><img alt="Twitter" src="https://img.shields.io/twitter/follow/wgpsec?label=Followers&style=social" /></a> <br> <br> <a href="https://github.com/wgpsec/ENScan_GO/discussions"><strong>探索更多Tricks »</strong></a> <br/> <br /> <a href="https://github.com/wgpsec/ENScan_GO/releases">下载程序</a> · <a href="https://github.com/wgpsec/ENScan_GO/issues">反馈Bug</a> · <a href="https://github.com/wgpsec/ENScan_GO/discussions">提交需求</a> </p> **使用程序可能导致⌈账号被封⌋，程序仅用于信息收集用途，禁止商用以及用于非法用途** **若该程序影响或侵犯到您的合法权益，请与我们联系** admin#wgpsec.org(#替换为@) ## 功能列表  - 使用支持以下API，并支持合并数据导出 - 爱企查 (未登陆信息带*) - 天眼查 - 阿拉丁 （数据反馈比较老旧暂时下线） - 酷安市场 - 七麦数据 - 查询信息 - ICP备案 - APP - 微博 - 微信公众号 - 控股公司 - 供应商 - 客户信息 - 小程序 - 控股X的公司的以上所有信息 - ... - 通过APK市场收集使用信息 ## 使用指南 ### 第一次使用 前往[RELEASE](https://github.com/wgpsec/ENScan_GO/releases)下载编译好的文件使用 初次使用时需要使用 -v 命令生成配置文件信息 ``` ./enscan -v ``` **遇到问题请加上参数 --debug 提issue** 如果查询不出来目标网站信息，可以都挂上BURP代理进行查询 **自行编译请使用 go 编译命令，或使用编译脚本 build.sh** ### 登陆配置 **AQC** 出现安全验证请勿结束进程，请使用带cookie的浏览器过验证即可继续 请注意获取COOKIE域名，默认查询为aiqicha.baidu.com，请勿使用 aiqicha.com Cookie信息请勿直接 `document.cookie`，可能因为http-only 选项无法复制全导致登陆失败  **TYC tycid** 配置COOKIE后配置tycid  ### 快速使用 **默认公司信息** (网站备案, 微博, 微信公众号, app) ``` ./enscan -n 小米 ``` **对外投资占股100%的公司 获取孙公司（深度2）** ``` ./enscan -n 小米 -invest 100 -deep 2 ``` **组合筛选** 大于51%控股公司、供应商、分支机构，只要ICP备案信息，并且批量获取邮箱信息 ``` ./enscan -n 小米 -field icp --hold --supplier --branch --email ``` **使用不同渠道** 使用天眼查数据源（或可设定为 all 组合多个数据源） ``` ./enscan -n 小米 -type tyc ``` 使用多数据源一起收集（暂不支持多渠道+筛选） ``` ./enscan -n 小米 -type aqc,tyc ``` ### 选项说明 #### **field 获取字段** 使用参数 `field`指定需要查询的信息，可指定多参数一起查询，方便快速收集 ``` -n 小米 -field icp,app ``` 支持以下参数 - `icp` 网站备案信息 - `weibo` 微博 - `wechat` 微信公众号 - `app` 应用信息 - `job` 招聘信息 - `wx_app` 微信小程序 - `copyright` 软件著作权 - `supplier` 供应商信息（通过招标书确定） #### **type 获取字段** 使用参数 `type`可以指定需要API数据源 ``` -n 小米 -type tyc ``` - `aqc` 爱企查 - `tyc` 天眼查 - `all` 全部查询 - `aldzs` 阿拉丁 （仅小程序） - `coolapk` 酷安市场 （仅APP） - `qimai` 七麦数据（仅APP） - `chinaz` 站长之家（仅ICP备案） #### 完整参数 | 参数 | 样例 | 说明 | | ----------------- | -------------- | -------------------------------------- | | -n | 小米 | 关键词 | | -i | 29453261288626 | 公司PID（自动识别类型） | | -f | file.txt | 批量查询，文本按行分隔（可选PID模式） | | -type | aqc | API类型 | | -o | | 结果输出的文件夹位置(可选) | | -is-merge | | 合并导出 | | -invest | | 投资比例 | | -field | icp | 获取字段信息 | | -deep | 1 | 递归搜索n层公司 | | -hold | | 是否查询控股公司 | | -supplier | | 是否查询供应商信息 | | -branch | | 查询分支机构（分公司）信息 | | -is-branch | | 深度查询分支机构信息（数量巨大） | | -api | | 是否API模式 | | -debug | | 是否显示debug详细信息 | | -is-show | | 是否展示信息输出 | | -is-group | | 查询关键词为集团 | | -is-pid | | 批量查询文件是否为公司PID | | -delay | | 每个请求延迟（S）-1为随机延迟1-5S | | -proxy | | 设置代理 | | -timeout | | 每个请求默认1（分钟）超时 | | -no-merge | | 批量查询【取消】合并导出 | | -v | | 版本信息 | ### API模式 **api调用效果（前端开发中）** 可使用 https://enscan.wgpsec.org/api/info 体验 (因被滥用下线)     #### API说明 获取信息将实时查询展示，可与其他工具进行API联动 **获取信息** ``` GET /api/info?search=小米&invest=100&branch=true ``` | 参数 | 参数 | 说明 | | ------ | -------------------- | -------------------------- | | name | 文本 | 完整公司名称（二选一） | | type | 文本，与命令参数一致 | 数据源 | | field | 文本，与命令参数一致 | 筛选指定信息 | | depth | 数字 | 爬取几层公司 如 2 为孙公司 | | invest | 数字 | 筛选投资比例 | | holds | true | 筛选控股公司 | | supplier | true | 筛选供应商信息 | | branch | true | 筛选分支信息 | | output | true | 为true导出excel表格 | #### 启动部署 **golang 版本依赖** ``` go >= 1.22.1 ``` **API模式** 启动API模式将在配置端口监听，并启动api服务，可通过api服务进行调用读取数据 ``` ./enscan --api ``` ## 交流&反馈 关注公众号 `WgpSec狼组安全团队` 回复`加群`一起交流~  [](https://starchart.cc/wgpsec/ENScan_GO) ## 404星链计划 <img src="https://github.com/knownsec/404StarLink/raw/master/Images/logo.png" width="30%"> ENScanGo 现已加入 [404星链计划](https://github.com/knownsec/404StarLink) ## JetBrains OS licenses ``ENScanGo`` had been being developed with `GoLand` IDE under the **free JetBrains Open Source license(s)** granted by JetBrains s.r.o., hence I would like to express my thanks here. <a href="https://www.jetbrains.com/?from=wgpsec" target="_blank"><img src="https://raw.githubusercontent.com/wgpsec/.github/master/jetbrains/jetbrains-variant-4.png" width="256" align="middle"/></a>

一款基于各大企业信息API的工具，解决在遇到的各种针对国内企业信息收集难题。一键收集控股公司ICP备案、APP、小程序、微信公众号等信息聚合导出。

redteam,app,icp,redteam-tools

Linen-dev/linen.dev

[](https://linen.dev/invite/linen) <a href="https://linen.dev/#gh-light-mode-only"> <img alt="linen-dev" src="https://static.main.linendev.com/logos/linen-black-logo.svg#gh-light-mode-only" width="108"> </a> <a href="https://linen.dev/#gh-dark-mode-only"> <img alt="linen-dev" src="https://static.main.linendev.com/logos/linen-white-logo.svg#gh-dark-mode-only" width="108"> </a> Make Slack and Discord communities Google-searchable Linen syncs your Slack and Discord threads to an SEO friendly website that allows your community to discover you through search engines and reduces the number of repeat questions. Retain your community knowledge and improve your SEO ### Core Features: **Search engine friendly** Linen syncs all your threads in your public channels and threads to linen.dev/s/your_slack_workspace_name. This makes your Slack/Discord contents available for your community members without requiring a login. **Generate organic content for your website and domain** The paid edition puts Linen behind your subdomain where you can generate organic SEO friendly content that is relevant for your domain. You will get a 301 redirect from our subdomain to yours to give all the SEO benefits. You also will be able to customize your Linen page with your custom logo and branding. **Scale your community and reduce support burden** Slack/Discord communities are great for chatting and engaging but over time they become overwhelming. As a community grows so does the number of repeat questions. As previously a former open source maintainer I wanted to minimize the number of repeat questions and encourage the community to search. **A better experience for your community** Linen is a great way to make your community content more discoverable. No longer do you need to login to your Slack/Discord workspace to view your community's content. You can link specific conversations in github issues without requiring a sign in to get the context of the issue. **Community Privacy** Linen only syncs conversations in the public channels. We only pull the display name and profile picture from Slack/Discord and we do not store community member's email or private information. Upon request we will delete any community member's information and messages within 14 days. Finally we have the options of anonymizing your community member's display name with a fake randomly generated string like `many-ancient-parrot`, `adventurous-billowy-kangaroo`, and `benedict-cumberbatch`. ### How to contribute [Contributing](./CONTRIBUTING.md) #### Developers Docs [Getting Started](./docs/getting-started.md)

Lightweight Google-searchable Slack alternative for Communities

chat,collaboration,discord,slack,typescript

reloadware/reloadium

Hot Reloading and Profiling for Python

hot-reload,hot-reloading,python,python3,edit-and-continue,django,flask,pandas,chatgpt,ai

actualbudget/actual-server

This is the main project to run [Actual](https://github.com/actualbudget/actual), a local-first personal finance tool. It comes with the latest version of Actual, and a server to persist changes and make data available across all devices. ### Getting Started Actual is a local-first personal finance tool. It is 100% free and open-source, written in NodeJS, it has a synchronization element so that all your changes can move between devices without any heavy lifting. If you are interested in contributing, or want to know how development works, see our [contributing](https://actualbudget.org/docs/contributing/) document we would love to have you. Want to say thanks? Click the ⭐ at the top of the page. ### Documentation We have a wide range of documentation on how to use Actual. This is all available in our [Community Documentation](https://actualbudget.org/docs/), including topics on [installing](https://actualbudget.org/docs/install/), [Budgeting](https://actualbudget.org/docs/budgeting/), [Account Management](https://actualbudget.org/docs/accounts/), [Tips & Tricks](https://actualbudget.org/docs/getting-started/tips-tricks) and some documentation for developers. ### Feature Requests Current feature requests can be seen [here](https://github.com/actualbudget/actual/issues?q=is%3Aissue+label%3A%22needs+votes%22+sort%3Areactions-%2B1-desc). Vote for your favorite requests by reacting 👍 to the top comment of the request. To add new feature requests, open a new Issue of the "Feature Request" type.

Actual's server

google-research/frame-interpolation

# FILM: Frame Interpolation for Large Motion ### [Website](https://film-net.github.io/) | [Paper](https://arxiv.org/pdf/2202.04901.pdf) | [Google AI Blog](https://ai.googleblog.com/2022/10/large-motion-frame-interpolation.html) | [Tensorflow Hub Colab](https://www.tensorflow.org/hub/tutorials/tf_hub_film_example) | [YouTube](https://www.youtube.com/watch?v=OAD-BieIjH4) <br> The official Tensorflow 2 implementation of our high quality frame interpolation neural network. We present a unified single-network approach that doesn't use additional pre-trained networks, like optical flow or depth, and yet achieve state-of-the-art results. We use a multi-scale feature extractor that shares the same convolution weights across the scales. Our model is trainable from frame triplets alone. <br> [FILM: Frame Interpolation for Large Motion](https://arxiv.org/abs/2202.04901) <br /> [Fitsum Reda](https://fitsumreda.github.io/)¹, [Janne Kontkanen](https://scholar.google.com/citations?user=MnXc4JQAAAAJ&hl=en)¹, [Eric Tabellion](http://www.tabellion.org/et/)¹, [Deqing Sun](https://deqings.github.io/)¹, [Caroline Pantofaru](https://scholar.google.com/citations?user=vKAKE1gAAAAJ&hl=en)¹, [Brian Curless](https://homes.cs.washington.edu/~curless/)^1,2<br /> ¹Google Research, ²University of Washington<br /> In ECCV 2022.  FILM transforms near-duplicate photos into a slow motion footage that look like it is shot with a video camera. ## Web Demo Integrated into [Hugging Face Spaces 🤗](https://huggingface.co/spaces) using [Gradio](https://github.com/gradio-app/gradio). Try out the Web Demo: [](https://huggingface.co/spaces/johngoad/frame-interpolation) Try the interpolation model with the replicate web demo at [](https://replicate.com/google-research/frame-interpolation) Try FILM to interpolate between two or more images with the PyTTI-Tools at [](https://colab.sandbox.google.com/github/pytti-tools/frame-interpolation/blob/main/PyTTI_Tools_FiLM-colab.ipynb#scrollTo=-7TD7YZJbsy_) An alternative Colab for running FILM on arbitrarily more input images, not just on two images, [](https://colab.research.google.com/drive/1NuaPPSvUhYafymUf2mEkvhnEtpD5oihs) ## Change Log * **Nov 28, 2022**: Upgrade `eval.interpolator_cli` for **high resolution frame interpolation**. `--block_height` and `--block_width` determine the total number of patches (`block_height*block_width`) to subdivide the input images. By default, both arguments are set to 1, and so no subdivision will be done. * **Mar 12, 2022**: Support for Windows, see [WINDOWS_INSTALLATION.md](https://github.com/google-research/frame-interpolation/blob/main/WINDOWS_INSTALLATION.md). * **Mar 09, 2022**: Support for **high resolution frame interpolation**. Set `--block_height` and `--block_width` in `eval.interpolator_test` to extract patches from the inputs, and reconstruct the interpolated frame from the iteratively interpolated patches. ## Installation * Get Frame Interpolation source codes ``` git clone https://github.com/google-research/frame-interpolation cd frame-interpolation ``` * Optionally, pull the recommended Docker base image ``` docker pull gcr.io/deeplearning-platform-release/tf2-gpu.2-6:latest ``` * If you do not use Docker, set up your NVIDIA GPU environment with: * [Anaconda Python 3.9](https://www.anaconda.com/products/individual) * [CUDA Toolkit 11.2.1](https://developer.nvidia.com/cuda-11.2.1-download-archive) * [cuDNN 8.1.0](https://developer.nvidia.com/rdp/cudnn-download) * Install frame interpolation dependencies ``` pip3 install -r requirements.txt sudo apt-get install -y ffmpeg ``` ### See [WINDOWS_INSTALLATION](https://github.com/google-research/frame-interpolation/blob/main/WINDOWS_INSTALLATION.md) for Windows Support ## Pre-trained Models * Create a directory where you can keep large files. Ideally, not in this directory. ``` mkdir -p <pretrained_models> ``` * Download pre-trained TF2 Saved Models from [google drive](https://drive.google.com/drive/folders/1q8110-qp225asX3DQvZnfLfJPkCHmDpy?usp=sharing) and put into `<pretrained_models>`. The downloaded folder should have the following structure: ``` <pretrained_models>/ ├── film_net/ │ ├── L1/ │ ├── Style/ │ ├── VGG/ ├── vgg/ │ ├── imagenet-vgg-verydeep-19.mat ``` ## Running the Codes The following instructions run the interpolator on the photos provided in 'frame-interpolation/photos'. ### One mid-frame interpolation To generate an intermediate photo from the input near-duplicate photos, simply run: ``` python3 -m eval.interpolator_test \ --frame1 photos/one.png \ --frame2 photos/two.png \ --model_path <pretrained_models>/film_net/Style/saved_model \ --output_frame photos/output_middle.png ``` This will produce the sub-frame at `t=0.5` and save as 'photos/output_middle.png'. ### Many in-between frames interpolation It takes in a set of directories identified by a glob (--pattern). Each directory is expected to contain at least two input frames, with each contiguous frame pair treated as an input to generate in-between frames. Frames should be named such that when sorted (naturally) with `natsort`, their desired order is unchanged. ``` python3 -m eval.interpolator_cli \ --pattern "photos" \ --model_path <pretrained_models>/film_net/Style/saved_model \ --times_to_interpolate 6 \ --output_video ``` You will find the interpolated frames (including the input frames) in 'photos/interpolated_frames/', and the interpolated video at 'photos/interpolated.mp4'. The number of frames is determined by `--times_to_interpolate`, which controls the number of times the frame interpolator is invoked. When the number of frames in a directory is `num_frames`, the number of output frames will be `(2^times_to_interpolate+1)*(num_frames-1)`. ## Datasets We use [Vimeo-90K](http://data.csail.mit.edu/tofu/dataset/vimeo_triplet.zip) as our main training dataset. For quantitative evaluations, we rely on commonly used benchmark datasets, specifically: * [Vimeo-90K](http://data.csail.mit.edu/tofu/testset/vimeo_interp_test.zip) * [Middlebury-Other](https://vision.middlebury.edu/flow/data) * [UCF101](https://people.cs.umass.edu/~hzjiang/projects/superslomo/UCF101_results.zip) * [Xiph](https://github.com/sniklaus/softmax-splatting/blob/master/benchmark.py) ### Creating a TFRecord The training and benchmark evaluation scripts expect the frame triplets in the [TFRecord](https://www.tensorflow.org/tutorials/load_data/tfrecord) storage format. <br /> We have included scripts that encode the relevant frame triplets into a [tf.train.Example](https://www.tensorflow.org/api_docs/python/tf/train/Example) data format, and export to a TFRecord file. <br /> You can use the commands `python3 -m datasets.create_<dataset_name>_tfrecord --help` for more information. For example, run the command below to create a TFRecord for the Middlebury-other dataset. Download the [images](https://vision.middlebury.edu/flow/data) and point `--input_dir` to the unzipped folder path. ``` python3 -m datasets.create_middlebury_tfrecord \ --input_dir=<root folder of middlebury-other> \ --output_tfrecord_filepath=<output tfrecord filepath> \ --num_shards=3 ``` The above command will output a TFRecord file with 3 shards as `<output tfrecord filepath>@3`. ## Training Below are our training gin configuration files for the different loss function: ``` training/ ├── config/ │ ├── film_net-L1.gin │ ├── film_net-VGG.gin │ ├── film_net-Style.gin ``` To launch a training, simply pass the configuration filepath to the desired experiment. <br /> By default, it uses all visible GPUs for training. To debug or train on a CPU, append `--mode cpu`. ``` python3 -m training.train \ --gin_config training/config/<config filename>.gin \ --base_folder <base folder for all training runs> \ --label <descriptive label for the run> ``` * When training finishes, the folder structure will look like this: ``` <base_folder>/ ├── <label>/ │ ├── config.gin │ ├── eval/ │ ├── train/ │ ├── saved_model/ ``` ### Build a SavedModel Optionally, to build a [SavedModel](https://www.tensorflow.org/guide/saved_model) format from a trained checkpoints folder, you can use this command: ``` python3 -m training.build_saved_model_cli \ --base_folder <base folder of training sessions> \ --label <the name of the run> ``` * By default, a SavedModel is created when the training loop ends, and it will be saved at `<base_folder>/<label>/saved_model`. ## Evaluation on Benchmarks Below, we provided the evaluation gin configuration files for the benchmarks we have considered: ``` eval/ ├── config/ │ ├── middlebury.gin │ ├── ucf101.gin │ ├── vimeo_90K.gin │ ├── xiph_2K.gin │ ├── xiph_4K.gin ``` To run an evaluation, simply pass the configuration file of the desired evaluation dataset. <br /> If a GPU is visible, it runs on it. ``` python3 -m eval.eval_cli \ --gin_config eval/config/<eval_dataset>.gin \ --model_path <pretrained_models>/film_net/L1/saved_model ``` The above command will produce the PSNR and SSIM scores presented in the paper. ## Citation If you find this implementation useful in your works, please acknowledge it appropriately by citing: ``` @inproceedings{reda2022film, title = {FILM: Frame Interpolation for Large Motion}, author = {Fitsum Reda and Janne Kontkanen and Eric Tabellion and Deqing Sun and Caroline Pantofaru and Brian Curless}, booktitle = {European Conference on Computer Vision (ECCV)}, year = {2022} } ``` ``` @misc{film-tf, title = {Tensorflow 2 Implementation of "FILM: Frame Interpolation for Large Motion"}, author = {Fitsum Reda and Janne Kontkanen and Eric Tabellion and Deqing Sun and Caroline Pantofaru and Brian Curless}, year = {2022}, publisher = {GitHub}, journal = {GitHub repository}, howpublished = {\url{https://github.com/google-research/frame-interpolation}} } ``` ## Acknowledgments We would like to thank Richard Tucker, Jason Lai and David Minnen. We would also like to thank Jamie Aspinall for the imagery included in this repository. ## Coding style * 2 spaces for indentation * 80 character line length * PEP8 formatting ## Disclaimer This is not an officially supported Google product.

FILM: Frame Interpolation for Large Motion, In ECCV 2022.

optical-flow,splatting,video,forward-warp,frame-interpolation

mantinedev/ui.mantine.dev

# Mantine UI [Mantine UI](https://ui.mantine.dev/) is a set of more than 120 responsive components built with [Mantine](https://mantine.dev/). All components support dark/light color scheme and Mantine theme customizations. Mantine UI is free for everyone. ## Contributing Mantine UI is an open source project with MIT license – you can browse source code and use components in your applications without any limitations. Although the project is open source, **we do not accept any contributions to the codebase of Mantine UI (unless maintainers asked you to send a PR).** You can contribute to the [Mantine library](https://github.com/mantinedev/mantine) codebase instead. ## License MIT

Mantine UI website and components

react,ui,components

tylearymf/UniHacker

# UniHacker [English Doc](https://github.com/tylearymf/UniHacker/blob/main/README_EN.md) [](https://github.com/tylearymf/UniHacker/releases/latest) [](https://github.com/tylearymf/UniHacker/blob/main/LICENSE) [](https://github.com/tylearymf/UniHacker/releases/latest) [](https://github.com/tylearymf/UniHacker/releases)    <!--[](https://github.com/tylearymf/UniHacker/issues) [](https://github.com/tylearymf/UniHacker/issues?q=is%3Aissue+is%3Aclosed)--> **支持破解所有国际版本的Unity和UnityHub。** **自从 Unity2022.2.0 及以上版本重构了License逻辑，目前无法破解。问题跳转：[#78](https://github.com/tylearymf/UniHacker/issues/78)** 下载地址 1. Unity国际版 官方下载地址（需要配置代理，代理没配置好可能会下载的国内版） * https://unity3d.com/get-unity/download/archive 2. UnityHub国际版 官方下载地址（需要配置代理，代理没配置好可能会下载的国内版） * https://unity.com/download#how-get-started 3. Unity国际版 UnityHub国际版 第三方下载地址（不需要配置代理，基本上下载的都是国际版） * https://github.com/AlianBlank/download.unity.com 4. UnityHub直链下载地址（需要配置代理，代理没配置好可能会下载的国内版） * Windows：https://public-cdn.cloud.unity3d.com/hub/prod/UnityHubSetup.exe * Mac：https://public-cdn.cloud.unity3d.com/hub/prod/UnityHubSetup.dmg * Linux：https://docs.unity3d.com/hub/manual/InstallHub.html#install-hub-linux **使用教程** * 在软件上选择你要破解的 Unity.exe 后，点击破解即可使用，这时已经可以双击Unity.exe打开工程了。如果提示不支持请提交 issue * 如果还需要配合Unity Hub，那么也在软件上选择 Unity Hub.exe，点击破解，即可搭配Unity Hub一起使用 * 注意：**只破解 Unity Hub.exe 是无法打开工程的，因为破解 Unity.exe 才是主要的** **Unity Hub登录教程** 1. 将UnityHub的语言改成English，走后面的流程会自动打开 unity.com，如果还是打开的 unity.cn，那么再走这个步骤：删除本地缓存目录 * Windows：%AppData%/UnityHub（C:\Users\你的用户名\AppData\Roaming\UnityHub） 2. 在[Proxifier](https://www.proxifier.com/)的规则设置中将UnityHub加入代理，需要配合梯子，具体网络搜索，这里不细说 3. 打开UnityHub，点击Sign In，会跳转到 https://api.unity.com/v1/oauth2/...，注意这里是 .com是正确的，如果是 .cn的说明你的第一步或者第二步操作有问题 4. 注册个Unity国外账号（用邮箱注册就可以了，不需要手机号），然后登录好后会自动跳转会UnityHub，如果没反应，可以退出UnityHub再点击登录 注意事项 * 上面的地址下载时需要 **全程代理**，不然可能会出现时重定向为国内地址，具体在软件分析时会提示为 **国内特供版** 。 * **国内特供版的是不支持破解的**。 ## Docker [unihacker-docker](https://github.com/tylearymf/unihacker-docker) ## Windows 系统 ### 支持破解的Unity版本 | 2023.x | 2022.2 | 2022.1 | 2021.x | 2020.x | 2019.x | | :----: | :----: | :----------------: | :----------------: | :----------------: | :----------------: | | :x: | :x: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | | 2018.x | 2017.x | 5.x | 4.x | | | | :----------------: | :----------------: | :----------------: | :----------------: | ---- | ---- | | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | | | ### 支持破解的Unity Hub版本 | 3.x | 2.x | | | | | | :----------------: | :----------------: | :--: | ---- | ---- | ---- | | :heavy_check_mark: | :heavy_check_mark: | | | | | ## Mac 系统 ### 支持破解的Unity版本 | 2023.x | 2022.2 | 2022.1 | 2021.x | 2020.x | 2019.x | | :----: | :----: | :----------------: | :----------------: | :----------------: | :----------------: | | :x: | :x: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | | 2018.x | 2017.x | 5.x | 4.x | | | | :----------------: | :----------------: | :----------------: | :----------------: | ---- | ---- | | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | | | ### 支持破解的Unity Hub版本 | 3.x | 2.x | | | | | | :----------------: | :----------------: | :--: | ---- | ---- | ---- | | :heavy_check_mark: | :heavy_check_mark: | | | | | ## Linux 系统 ### 支持破解的Unity版本 | 2023.x | 2022.2 | 2022.1 | 2021.x | 2020.x | 2019.x | | :----: | :----: | :----------------: | :----------------: | :----------------: | :----------------: | | :x: | :x: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | :heavy_check_mark: | | 2018.x | 2017.x | | | | | | :----------------: | :----------------: | ---- | ---- | ---- | ---- | | :heavy_check_mark: | :heavy_check_mark: | | | | | ### 支持破解的Unity Hub版本 | 3.x | 2.x | | | | | | :----------------: | :----------------: | :--: | ---- | ---- | ---- | | :heavy_check_mark: | :heavy_check_mark: | | | | | ## 免责声明 本软件的任何使用仅用于非营利性的教育和测试目的。 ## 鸣谢 > [asar](https://github.com/Jiiks/asar.net) > > [unity-patch](https://github.com/aevitas/unity-patch) > > [Avalonia](https://github.com/AvaloniaUI/Avalonia)

Patch all versions of Unity3D and UnityHub for Windows, MacOS, Linux and Docker.

crack,patch,unity,unity-hub,unity3d,unityhub,unitytool,docker

dragoonDorise/EmuDeck

# EmuDeck [](https://gitpod.io/from-referrer/) <img src="https://www.emudeck.com/img/hero.png"> EmuDeck is a collection of scripts that allows you to autoconfigure your Steam Deck or any other Linux Distro, it creates your roms directory structure and downloads all of the needed Emulators for you along with the best configurations for each of them. EmuDeck works great with [Steam Rom Manager](https://github.com/SteamGridDB/steam-rom-manager) or with [EmulationStation DE](https://es-de.org) ## How to use EmuDeck? We recomend you take a look at our extensive Wiki, you'll find guides, videos and all sorts of content about the project: [EmuDeck Wiki](https://emudeck.github.io/how-to-install-emudeck/steamos/) ## Developers, developers, developers. If you wanna help us improve EmuDeck we are open to accept your PR! Just keep in mind this simple guide: - Think that EmuDeck is for everybody, tech savvy and is specially directed to regular users that are new to Emulation, so everything has to be properly explained. - Things using sudo are a big no no, there are exceptions but always try to find a way of prevent using sudo. - Every Emulator needs to have a SRM profile and follow the AmberElec hotkey mapping. - Always do your PR to the dev branch. ## Submitting a PR Request for a Steam ROM Manager Parser If you would like to submit a PR request for a Steam ROM Manager parser, use the following format: ### The Basics - Spell out console names - no acronyms - For example, `PSP` should be spelled out as `PlayStation Portable` - Respect original capitalization and spacing - A few examples: - `RetroArch` uses a capital `R` and capital `A` - The `Nintendo Game Boy` uses a capital `N`, `G`, and `B` with spaces between each word - The `PlayStation Portable` uses a capital `P` and `S` in `PlayStation` as do the other `PlayStation` handhelds and consoles ### Parser Structure - `configTitle`: - `COMPANYNAME SYSTEMNAME - EMULATORNAME RETROARCHCORENAME` - If the standalone emulator name is identical to the RetroArch core name, add `(Standalone)` behind the `EMULATORNAME` - A few examples: - Config Title: `"configTitle": "Amiga - RetroArch PUAE",` - Config Title: `"configTitle": "Nintendo Game Boy Color - mGBA (Standalone)",` - Config Title: `"configTitle": "Sony PlayStation 2 - PCSX2",` - `steamCategory`: - **Note:** Non-Default Parsers refer to when a system has multiple emulation choices (through alternative emulators or RetroArch cores). Only one of these parsers is enabled by default and any alternative choices are disabled by default. - Default Parsers: - `COMPANYNAME CONSOLENAME` - Non-Default Parsers: - Standalone: `COMPANYNAME CONSOLENAME - EMULATORNAME` - RetroArch Core: `COMPANYNAME CONSOLENAME - RETROARCHCORENAME` - If the RetroArch core's name is identical to the Standalone emulator name, add `RetroArch` in front of the `RETROARCHCORENAME` - If the standalone emulator name is identical to the RetroArch core name, add `(Standalone)` behind the `EMULATORNAME` - A few examples: - Default Parsers: - Mupen64Plus Next (RetroArch core for Nintendo 64) - Steam Category Name: `"steamCategory": ""${Nintendo 64}",` - DuckStation (PSX Emulator) - Steam Category Name: `"steamCategory": "${Sony PlayStation}",` - Non-Default Parsers: - Rosalie's Mupen GUI (N64 Emulator) - Steam Category Name: `"steamCategory": "${Nintendo 64 - Rosalie's Mupen GUI}",` - Beetle PSX HW (RetroArch core for PSX) - Steam Category Name: `"steamCategory": "${Sony PlayStation - Beetle PSX HW}",` ### Parser Filename `companyname_systemname-emulatorname-retroarchcore.json` If it is a RetroArch core, replace `emulatorname` with `ra`. - A few examples: - `nintendo_wii-dolphin.json` - `nintendo_64-rmg.json` - `nintendo_gba-ra-mgba.json` - `sega_saturn-ra-mednafen.json` ## Credits ### Configurations * bbilford83 * Tweaked and fine-tuned the Model 2 Emulator and Supermodel for EmuDeck on SteamOS * Warped Polygon * Created the wonderful controls for the Model 2 Emulator and Supermodel * [Model 2 Emulator](https://forums.launchbox-app.com/files/file/3926-sega-model-2-emulator-everything-pre-configured-inc-controls-for-pc-controller-mouse-light-guns-test-menus-configured-analogue-inputs-calibrated-free-play-all-games-in-english-2-player-mouse-support-no-screen-flash/) * [Supermodel](https://forums.launchbox-app.com/files/file/3857-sega-model-3-supermodel-git-everything-pre-configured-inc-controls-for-pc-controller-mouse-light-guns-test-menus-configured-free-play-all-games-in-english-2-player-mouse-support-audio-adjusted-layout-imagesthe-whole-9-yards/) ### Contributors * AngelofWoe * doctorjei * DragoonDoorise * DylanTackoor * exp111 * EXtremeExploit * frostymm * Godsbane * GloriousEggroll * JesseTG * Kardbord * KingIzzymon * rawdatafeel * Rosalie241 * SilentException * WedgeSparda * WingOfAGriffin

Emulator configurator for Steam Deck