ytzi/the-stack-dedup-python-filtered · Datasets at Hugging Face

fff3557fd7e005babefb16e3b6b117ef8a3354ec

918

py

Python

file_automation.py

FlightDev/YSPA

5226712ebf305e7a3c686c43c996517a617f748b

[ "MIT" ]

null

file_automation.py

FlightDev/YSPA

5226712ebf305e7a3c686c43c996517a617f748b

[ "MIT" ]

null

file_automation.py

FlightDev/YSPA

5226712ebf305e7a3c686c43c996517a617f748b

[ "MIT" ]

null

import os import glob from astropy.io import fits #/home/student/Desktop/Images/iTelescope/20180716-California-T24-GOOD # Yo Neal. When you use this program, you have to change a few things between iTelescope and LFOP # FIRST, remember to change the file path or you'll be a dummy. Also for LFOP -13 and -12 while # for iTelescope it should be -9 and -8. Hopefully you know what to do with those numbers... #/home/student/Desktop/Images/LFOP dir = '20180726-LFOP-GOOD' path = '/home/student/Desktop/Images/LFOP/' + dir + '/' dict = {} date = "" for filename in os.listdir(path): if filename.endswith(".fit"): file = path + str(filename) image = fits.open(file) s = image[0].header.get("DATE-OBS") date = s[:len(s) - 13] dict.update({s[len(s) - 12:]: filename}) for key, value in sorted(dict.items()): print value + "\t\t" + str(key) print date print len(dict)

32.785714

99

0.667756

fff3dd07c2f6cdec73bcd25788a20c7594c2652d

959

py

Python

streamlit/main.py

prakhar134/clean-or-messy

0b9080363c48ca9cff0449875dfcbd169ef64321

[ "MIT" ]

13

2020-10-08T13:52:21.000Z

2022-03-11T07:02:35.000Z

streamlit/main.py

architsharmaa/clean-or-messy

b40028cb4c4c8bbefb91a4b016096953b445c146

[ "MIT" ]

null

streamlit/main.py

architsharmaa/clean-or-messy

b40028cb4c4c8bbefb91a4b016096953b445c146

[ "MIT" ]

9

2020-10-08T12:02:50.000Z

2022-01-25T23:38:46.000Z

from fastai.vision.all import * from PIL import Image import streamlit as st import numpy as np from io import BytesIO from .config import imgWidth, imgHeight st.title("CleanvsMessy") st.markdown(''' ## Upload the image''',True) st.set_option('deprecation.showfileUploaderEncoding', False) file = st.file_uploader(" ") model = load_learner('model/model_v0.pkl') st.markdown(''' ## Preview of the Image''',True) if file != None: st.image(file, width = imgWidth, height = imgHeight) if file != None: result = upload(file) st.write("Is Image Clean? "+result["is_image_clean"]) st.write("Confidence "+str(result["predictedVal"]))

30.935484

65

0.683003

fff46233cd9fc6a4821a3755e7bb2b8fd09e058e

1,030

py

Python

read_trials.py

Volkarl/P10-ExoskeletonTransferLearning

311daf3791c65838ff9c496eeb6526b096b41d4c

[ "MIT" ]

null

read_trials.py

Volkarl/P10-ExoskeletonTransferLearning

311daf3791c65838ff9c496eeb6526b096b41d4c

[ "MIT" ]

2

2020-11-13T18:39:27.000Z

2021-08-25T15:59:36.000Z

read_trials.py

Volkarl/P10-ExoskeletonTransferLearning

311daf3791c65838ff9c496eeb6526b096b41d4c

[ "MIT" ]

null

import pickle import matplotlib.pyplot as plt import pandas as pd trials = pickle.load(open("trials.p", "rb")) print("Set breakpoint here") #for item in trials.trials: # args = item["vals"] # res = item["result"]["loss"] #itemtuples = [(item["misc"]["vals"]["dilation_group"], item["misc"]["vals"]["use_ref_points"], item["result"]["loss"]) for item in trials.trials] #(dil, ref, loss) = zip(*itemtuples) #plt.figure() #plt.plot(dil, 'ro') #plt.title('Use_dilation (1 is true, 0 is false)') #plt.plot(loss) #plt.plot(pd.DataFrame(loss).ewm(span=1).mean()) #plt.title('MAE') #plt.plot(ref, 'g^') #plt.legend() #plt.show() print("Set breakpoint here") print("PRINT BEST TRIALS") myitems = [(trial["result"]["loss"], str(trial["misc"]["vals"])) for trial in trials.trials if trial["result"]["status"] == "ok"] myitems.sort(key=lambda tup: tup[0]) for item in myitems[:10]: print("--------------------------\n") print(item) print("\n\n") # If you want to print training times use attemptid["book_time"]

24.52381

146

0.635922

fff5f55a4eee57bae636a577f32adbde97ba453e

3,151

py

Python

e3/provisioning/AtlassianAwsSecurity.py

sguillory6/e3

1505e6ea389157b9645155b9da13d6d316235f1a

[ "Apache-2.0" ]

null

e3/provisioning/AtlassianAwsSecurity.py

sguillory6/e3

1505e6ea389157b9645155b9da13d6d316235f1a

[ "Apache-2.0" ]

null

e3/provisioning/AtlassianAwsSecurity.py

sguillory6/e3

1505e6ea389157b9645155b9da13d6d316235f1a

[ "Apache-2.0" ]

null

import logging import logging.config import os import subprocess from datetime import datetime, timedelta from botocore.credentials import CredentialProvider, RefreshableCredentials from dateutil.tz import tzlocal from common.E3 import e3

39.886076

114

0.614408

fff5fae09ca4ba6758cfde4e7471355a0e7af098

3,506

py

Python

RecRoomAnimatedProfilePicture.py

zigzatuzoo/Rec-Room-Animated-Profile-Picture

b8eeabf478613f47d3bdb9195ad2f5051e7aaaad

[ "Apache-2.0" ]

4

2021-08-17T01:13:03.000Z

2022-03-19T04:03:01.000Z

RecRoomAnimatedProfilePicture.py

zigzatuzoo/Rec-Room-Animated-Profile-Picture

b8eeabf478613f47d3bdb9195ad2f5051e7aaaad

[ "Apache-2.0" ]

null

RecRoomAnimatedProfilePicture.py

zigzatuzoo/Rec-Room-Animated-Profile-Picture

b8eeabf478613f47d3bdb9195ad2f5051e7aaaad

[ "Apache-2.0" ]

null

''' Stuff you need to update for this to work ''' 'Enter your username here' user = '' 'Enter your password here' passwd = '' image1 = '2d83af05944d49c69fa9565fb238a91b.jpg' image2 = '49b2788b672e4088a25eb0a9eff35c17.jpg' image3 = '355c2c7e87f0489bb5f0308cdec108f6.jpg' " ^ You need to change EACH of these to whatever you want the 3 pics to be (Currently set to a waving red zigzag)" ''' Stuff that will change how the program works ''' speed = 0.2 "^ As you can probably guess, this changes how long the PFP stays on each image" import time try: import requests except: print('''You do not have the requests library installed, you need to install it via the following command: pip install requests Thank you!''') try: import recnetlogin as rnl except: print('''You do not have the RecNetLogin package installed, you need to install it via the following command: python -m pip install git+https://github.com/Jegarde/RecNet-Login.git#egg=recnetlogin Thank you!''') ''' Just Initializing some values ''' login = rnl.login_to_recnet(username=user,password=passwd) x = 0 BToken = '' ''' Making the strings into the format read by the rec.net image api ''' imageName1 = 'imageName=' + image1 imageName2 = 'imageName=' + image2 imageName3 = 'imageName=' + image3 ''' Initial token request ''' BToken = login.access_token print(BToken) ''' The loop program that actually makes the picure move ''' while 1 == 1: ''' The HTTP header for changing your In-Game pfp ''' Headers = {'sec-ch-ua':'";Not A Brand";v="99", "Chromium";v="88"', 'Accept' : '*/*', 'sec-ch-ua-mobile' : '?0', 'Authorization' : BToken, 'Content-Type' : 'application/x-www-form-urlencoded; charset=UTF-8', 'Origin' : 'https://rec.net', 'Sec-Fetch-Site' : 'same-site', 'Sec-Fetch-Mode' : 'cors', 'Sec-Fetch-Dest' : 'empty', 'Referer' : 'https://rec.net/', 'Accept-Encoding' : 'gzip, deflate', 'Accept-Language' : 'en-US,en;q=0.9', } ''' The easy way to edit what pfp plays after what ''' ''' In this default format, it will show image 1 first, then image 2, then image 3, then image 2 again and will LOOP this. The x value in the function calls is to make the counter function, if you don't add it to your function calls or you delete them, THE COUNTER WILL NOT WORK. ''' x = x + 1 i1() x = x + 1 i2() x = x + 1 i3() x = x + 1 i2() ''' Requests a new auth token when that one is no longer valid ''' r = requests.put('https://accounts.rec.net/account/me/profileImage', headers = Headers) if r.status_code == 401: print('Invalid Token') login = rnl.login_to_recnet(username=user,password=passwd) BToken = login.access_token print(BToken)

35.77551

287

0.634341

fff7d77cd5951c966e8c3d645997399fd6e953c2

14,121

py

Python

rcommander/src/rcommander/graph_view.py

rummanwaqar/rcommander-core

7106d5868db76c47dea6ad11118a54351a8bd390

[ "BSD-3-Clause" ]

4

2015-04-08T09:57:43.000Z

2021-08-12T01:44:37.000Z

rcommander/src/rcommander/graph_view.py

jhu-lcsr-forks/rcommander-core

1a0350e9b93687eff6a4407f72b5250be5f56919

[ "BSD-3-Clause" ]

1

2015-03-12T09:10:27.000Z

rcommander/src/rcommander/graph_view.py

jhu-lcsr-forks/rcommander-core

1a0350e9b93687eff6a4407f72b5250be5f56919

[ "BSD-3-Clause" ]

3

2015-03-12T10:59:17.000Z

2021-06-21T02:13:57.000Z

#import roslib; roslib.load_manifest('rcommander_core') import graph.style as gs import graph import graph.layout as gl import tool_utils as tu import graph_model as gm import numpy as np import time import copy

39.116343

146

0.578217

fff91c879216ac70a7559f58214c7d1b3892a9ea

3,264

py

Python

django_input_collection/api/restframework/collection.py

pivotal-energy-solutions/django-input-collection

cc2ce3e0a7104ba9c524eaba5706da94ddb04a5f

[ "Apache-2.0" ]

null

django_input_collection/api/restframework/collection.py

pivotal-energy-solutions/django-input-collection

cc2ce3e0a7104ba9c524eaba5706da94ddb04a5f

[ "Apache-2.0" ]

4

2019-08-25T15:47:24.000Z

2022-03-24T19:35:09.000Z

django_input_collection/api/restframework/collection.py

pivotal-energy-solutions/django-input-collection

cc2ce3e0a7104ba9c524eaba5706da94ddb04a5f

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- from django.urls import reverse from rest_framework.response import Response from rest_framework import status from ...collection import BaseAPICollector, BaseAPISpecification from ... import models from . import serializers

38.857143

99

0.662377

fffc90bcd5aabe8c07f5b2517e1c835715addf0e

770

py

Python

DFS/depth_first_search.py

Quanta-Algorithm-Design/graphs

3a5b6362bf60a1e2fb06d2fadab46e72124d637d

[ "MIT" ]

null

DFS/depth_first_search.py

Quanta-Algorithm-Design/graphs

3a5b6362bf60a1e2fb06d2fadab46e72124d637d

[ "MIT" ]

null

DFS/depth_first_search.py

Quanta-Algorithm-Design/graphs

3a5b6362bf60a1e2fb06d2fadab46e72124d637d

[ "MIT" ]

1

2020-10-05T06:46:13.000Z

#!/usr/bin/env python3 """ This module defines functions for depth-first-search in a graph with a given adjacency list """ def dfs_visit(node_list, adj_list, root_node, parent): """ Takes the graph node list, its adj list, and a node s, and visits all the nodes reachable from s recursively. """ for node in adj_list[root_node]: if node not in parent: parent[node] = root_node dfs_visit(node_list, adj_list, node, parent) def dfs(node_list, adj_list): """ Iterate over possible root_nodes to explore the whole graph """ parent = {} for root_node in node_list: if root_node not in parent: parent[root_node] = None dfs_visit(node_list, adj_list, root_node, parent)

29.615385

91

0.654545

ffff1e4cd8bc9bad42ca402b2c639f4b45a16abe

791

py

Python

pirates/quest/QuestHolderBase.py

itsyaboyrocket/pirates

6ca1e7d571c670b0d976f65e608235707b5737e3

[ "BSD-3-Clause" ]

3

2021-02-25T06:38:13.000Z

2022-03-22T07:00:15.000Z

pirates/quest/QuestHolderBase.py

itsyaboyrocket/pirates

6ca1e7d571c670b0d976f65e608235707b5737e3

[ "BSD-3-Clause" ]

null

pirates/quest/QuestHolderBase.py

itsyaboyrocket/pirates

6ca1e7d571c670b0d976f65e608235707b5737e3

[ "BSD-3-Clause" ]

1

2021-02-25T06:38:17.000Z

# uncompyle6 version 3.2.0 # Python bytecode 2.4 (62061) # Decompiled from: Python 2.7.14 (v2.7.14:84471935ed, Sep 16 2017, 20:19:30) [MSC v.1500 32 bit (Intel)] # Embedded file name: pirates.quest.QuestHolderBase

30.423077

104

0.694058

0803020bd1e3c35bd9b149aea49e7ac12f9623a3

933

py

Python

setup.py

yihong0618/-nbnhhsh-cli

3c8241dbc772b4b693e06b350c4351e75572596a

[ "Apache-2.0" ]

33

2021-07-09T05:40:00.000Z

2022-02-07T12:49:34.000Z

setup.py

yihong0618/-nbnhhsh-cli

3c8241dbc772b4b693e06b350c4351e75572596a

[ "Apache-2.0" ]

1

2021-07-09T05:37:02.000Z

setup.py

yihong0618/-nbnhhsh-cli

3c8241dbc772b4b693e06b350c4351e75572596a

[ "Apache-2.0" ]

2

2021-07-10T10:25:08.000Z

2021-07-11T03:16:38.000Z

from setuptools import setup, find_packages VERSION = "0.1.1" setup( name="hhsh", version=VERSION, description=" cli", long_description=" cli", keywords="python hhsh cli terminal", author="itorr,yihong0618", author_email="zouzou0208@gmail.com", url="https://github.com/yihong0618/hhsh", packages=find_packages(), include_package_data=True, zip_safe=True, install_requires=["requests", "rich"], classifiers=[ "Development Status :: 4 - Beta", "Environment :: Console", "Intended Audience :: Developers", "Operating System :: OS Independent", "Programming Language :: Python :: 3.6", "Programming Language :: Python :: 3.7", "Programming Language :: Python :: 3.8", "Topic :: Software Development :: Libraries", ], entry_points={ "console_scripts": ["hhsh = hhsh.hhsh:main"], }, )

29.15625

53

0.621651

08058658e2bf102d2ac28a2a02f1701e1eb02d65

937

py

Python

container/base/src/cache.py

hmrc/devops-tooling-build

03d62df3a45d5dcce306cd6cad6c95a24a4b34ab

[ "Apache-2.0" ]

1

2021-11-10T16:09:43.000Z

container/base/src/cache.py

hmrc/devops-tooling-build

03d62df3a45d5dcce306cd6cad6c95a24a4b34ab

[ "Apache-2.0" ]

6

2021-07-02T14:15:25.000Z

2022-02-03T12:57:36.000Z

container/base/src/cache.py

hmrc/devops-tooling-build

03d62df3a45d5dcce306cd6cad6c95a24a4b34ab

[ "Apache-2.0" ]

null

import datetime import hashlib import os import pathlib from typing import Optional import yaml

25.324324

78

0.649947

08075a784b23b26531f0e2fcf4a1653e8cbbe078

1,118

py

Python

tests/test_blender.py

dumpmemory/lassl

dfe56f09cc2ade6c777ad8561b24f23d83a34188

[ "Apache-2.0" ]

null

tests/test_blender.py

dumpmemory/lassl

dfe56f09cc2ade6c777ad8561b24f23d83a34188

[ "Apache-2.0" ]

null

tests/test_blender.py

dumpmemory/lassl

dfe56f09cc2ade6c777ad8561b24f23d83a34188

[ "Apache-2.0" ]

null

from collections import Counter import pytest from datasets import load_dataset from lassl.blender import DatasetBlender

30.216216

82

0.620751

080796109f90dd5533115b48ae3a4657f5fb4224

4,542

py

Python

wisps/data_analysis/path_parser.py

caganze/WISPS

81b91f8b49c7345ab68b7c4eb480716985e8905c

[ "MIT" ]

null

wisps/data_analysis/path_parser.py

caganze/WISPS

81b91f8b49c7345ab68b7c4eb480716985e8905c

[ "MIT" ]

7

2021-02-02T21:51:56.000Z

2022-01-13T00:57:45.000Z

wisps/data_analysis/path_parser.py

caganze/wisps

6572201f94a6af6d1c0a306f2f447215d4330bd7

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ After the introduction of version 6.2, all wisp data and hst-3d are now on MAST 3D-HST has not added any new data nor changed their directory structure, but that's not the case for WISP Aim: parse new directories to make them compatible with v5.0 """ import os import glob from ..utils import memoize_func REMOTE_FOLDER=os.environ['WISP_SURVEY_DATA']

34.409091

170

0.647952

08092e15e7923e75bbc9274300846c3ee3fbd2d9

158

py

Python

tests/utils/TestTransaction.py

Shaid3r/reservations

43e17ae88eed74593879f9f8c5a9bed7252888f7

[ "MIT" ]

null

tests/utils/TestTransaction.py

Shaid3r/reservations

43e17ae88eed74593879f9f8c5a9bed7252888f7

[ "MIT" ]

null

tests/utils/TestTransaction.py

Shaid3r/reservations

43e17ae88eed74593879f9f8c5a9bed7252888f7

[ "MIT" ]

null

import storage import pytest

15.8

33

0.683544

080b1f9b578c418d65d4a8c4119d27d86ab70fa5

2,451

py

Python

aldryn_redirects/migrations/0003_auto_20171206_1150.py

compoundpartners/aldryn-redirects

ed1b1e90a7774a4bead771e158e30d5846e64e60

[ "BSD-3-Clause" ]

1

2020-05-14T06:41:50.000Z

aldryn_redirects/migrations/0003_auto_20171206_1150.py

compoundpartners/aldryn-redirects

ed1b1e90a7774a4bead771e158e30d5846e64e60

[ "BSD-3-Clause" ]

11

2016-01-11T11:42:58.000Z

2018-11-05T16:13:27.000Z

aldryn_redirects/migrations/0003_auto_20171206_1150.py

compoundpartners/aldryn-redirects

ed1b1e90a7774a4bead771e158e30d5846e64e60

[ "BSD-3-Clause" ]

6

2016-11-22T04:53:37.000Z

2018-11-15T13:56:39.000Z

# -*- coding: utf-8 -*- # Generated by Django 1.11.8 on 2017-12-06 13:50 from __future__ import unicode_literals import aldryn_redirects.validators from django.db import migrations, models import django.db.models.deletion

50.020408

268

0.651571

0811b7481588bc53cfde102ac50bffe1f9e0e41c

161

py

Python

velocity/constants.py

aisthesis/mfstockmkt

d442ec4cb3b379f6984397926b4466420236c032

[ "MIT" ]

null

velocity/constants.py

aisthesis/mfstockmkt

d442ec4cb3b379f6984397926b4466420236c032

[ "MIT" ]

1

2015-12-27T17:37:54.000Z

2015-12-31T05:06:06.000Z

velocity/constants.py

aisthesis/mfstockmkt

d442ec4cb3b379f6984397926b4466420236c032

[ "MIT" ]

1

2020-05-02T08:25:35.000Z

14.636364

45

0.652174

0811dfdcb7e741d544fe728950a10ae174c04263

3,284

py

Python

fileForRepair/src/parking.py

ChangSeonKim/5G_UWC_project

0504a1b1ed30787f30e18a178897978de55660ef

[ "Apache-2.0" ]

null

fileForRepair/src/parking.py

ChangSeonKim/5G_UWC_project

0504a1b1ed30787f30e18a178897978de55660ef

[ "Apache-2.0" ]

null

fileForRepair/src/parking.py

ChangSeonKim/5G_UWC_project

0504a1b1ed30787f30e18a178897978de55660ef

[ "Apache-2.0" ]

null

#! /usr/bin/env python3 import rospy from geometry_msgs.msg import Twist from sensor_msgs.msg import LaserScan import numpy as np import math from std_msgs.msg import String if __name__ =='__main__': rospy.init_node('parking') pub = rospy.Publisher('/cmd_vel',Twist, queue_size=10) rospy.Subscriber('/scan',LaserScan, queue_size = 1, callback = callback) rospy.Subscriber('helloworld03', String, callback=stop) rospy.spin() pass

29.061947

76

0.546894

08138545899e44b68cb9f2c6902d9d5be0b380f7

2,622

py

Python

opennsa/provreg.py

jmacauley/opennsa

853c0fc8e065e74815cbc3f769939f64ac6aadeb

[ "BSD-3-Clause" ]

null

opennsa/provreg.py

jmacauley/opennsa

853c0fc8e065e74815cbc3f769939f64ac6aadeb

[ "BSD-3-Clause" ]

null

opennsa/provreg.py

jmacauley/opennsa

853c0fc8e065e74815cbc3f769939f64ac6aadeb

[ "BSD-3-Clause" ]

null

""" Registry for tracking providers dynamically in OpenNSA. Keeping track of providers in a dynamical way in an NSI implementation is a huge pain in the ass. This is a combination of things, such as seperate identities and endpoints, callbacks, and the combination of local providers. The class ProviderRegistry tries to keep it a bit sane. """ from twisted.python import log from opennsa import error LOG_SYSTEM = 'providerregistry'

34.051948

108

0.672006

081559dc3ab661ae3a1df9c2d52bc8d2ba1f2ae4

997

py

Python

tests/test_task_tracker.py

jmchilton/shedclient-beta

50041b488652f8bf40555b0c1ef001290f1c3f6a

[ "CC-BY-3.0" ]

2

2015-12-21T02:18:54.000Z

2016-09-08T13:56:36.000Z

tests/test_task_tracker.py

jmchilton/shedclient-beta

50041b488652f8bf40555b0c1ef001290f1c3f6a

[ "CC-BY-3.0" ]

1

2015-12-21T19:26:21.000Z

tests/test_task_tracker.py

jmchilton/shedclient-beta

50041b488652f8bf40555b0c1ef001290f1c3f6a

[ "CC-BY-3.0" ]

null

from test_utils import TempDirectoryContext from shedclient import task_tracker

33.233333

76

0.657974

081691097da1b52252fbbf22f08b3e7856a39982

5,825

py

Python

gonder_rc.py

TarikCinar/python-sesli-asistan

1a29a8d3081b67ff352cf03f7b01ac01b7118deb

[ "MIT" ]

1

2021-05-28T17:27:50.000Z

gonder_rc.py

TarikCinar/python-sesli-asistan

1a29a8d3081b67ff352cf03f7b01ac01b7118deb

[ "MIT" ]

null

gonder_rc.py

TarikCinar/python-sesli-asistan

1a29a8d3081b67ff352cf03f7b01ac01b7118deb

[ "MIT" ]

null

# -*- coding: utf-8 -*- # Resource object code # # Created by: The Resource Compiler for PyQt5 (Qt v5.13.0) # # WARNING! All changes made in this file will be lost! from PyQt5 import QtCore qt_resource_data = b"\ \x00\x00\x04\x1a\ \x00\ \x01\x08\x3e\x78\x9c\xed\x9c\x4d\x6e\xd3\x50\x14\x85\x1d\x65\x10\ \x66\x61\xc4\x2c\x75\x87\xdd\x85\x59\x4a\x77\x92\xcc\xd2\x59\x97\ \xc2\x12\x40\x62\x01\x2c\xa1\x48\xb4\x62\x58\x86\x0c\x10\xc1\x76\ \x52\xc7\x3e\x21\x8e\xe3\xdf\x77\xdf\xfb\xbe\xea\x22\x1d\x17\x61\ \xc7\xe7\xbe\x73\x18\x54\x8d\xa2\x59\xfa\xb5\xd9\x44\xe9\x9f\xb7\ \xd1\xdd\xbb\x59\xf4\x21\x8a\xa2\xbb\x74\xd2\x4b\xd9\xc5\xfc\x7a\ \x4e\xfa\x3d\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\ \x00\x00\x08\x97\x97\xed\x6a\xf3\xfc\xb0\x7a\x7a\xde\xae\xee\x9f\ \x1e\xe3\xf7\x53\x3f\x0f\x8c\x4b\xe6\xff\xcb\xc3\xcd\x2e\x9f\xed\ \xea\xf5\x79\x7b\xf3\xf8\x73\x1b\xdf\x4e\xfd\x5c\x30\x0e\x15\xff\ \x4b\x93\xee\xc1\xa7\x1f\xdb\xf8\xe3\xd4\xcf\x07\xc3\x72\xce\xff\ \x62\x0f\xe8\x06\xaf\xb9\xe4\x3f\xdd\xe0\x37\x8d\xfd\xa7\x1b\xbc\ \xa4\x8d\xff\x74\x83\x3f\x74\xf1\x9f\x6e\xb0\x4f\x2f\xfe\xd3\x0d\ 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\x1a\x8e\xd1\x6e\xe8\x0a\xd9\x71\x3a\x3e\x75\x43\x17\x42\xcf\x0e\ \xdf\xbb\xa1\x2b\xc1\x64\x47\xa0\xdd\xd0\x05\x5f\xb3\x83\x6e\xe8\ \x07\xeb\xd9\x41\x37\x0c\x87\xa9\xec\xa0\x1b\x46\xc7\xd5\xec\xa0\ \x1b\xc6\x01\xff\xfd\x86\xfc\xf7\x1f\x57\xcf\x70\xe3\xb3\xce\xff\ \xff\x6a\x31\x75\x86\xc9\xf8\x56\x58\x3f\xc3\x8d\x27\xd0\x8c\xf7\ \xf5\x0c\x37\x3e\xeb\x01\x64\x7c\x30\x67\xf8\x1a\xdf\x3d\xca\xf8\ \xd0\xcf\x70\xe3\x31\x9c\xf1\x9c\xe1\xf6\x63\x21\xe3\x39\xc3\x03\ \xf8\xee\x68\xc6\xf3\xf3\x9f\x03\x8e\x81\x8c\xe7\xe7\xbf\xfb\x1f\ \x0b\x19\xff\x06\xfe\xf7\xe8\xbb\xa3\x19\x5f\x07\xfe\x77\x1c\x03\ \x19\x5f\x07\xfe\xb7\x1b\x4b\x19\x5f\x07\xfe\x5f\xe9\xbb\xc1\x8c\ \xaf\x03\xff\x1b\x8c\xf1\x8c\xaf\x03\xff\xcf\x8f\x2f\x19\x5f\x07\ \xfe\xff\xc7\x77\xcf\x32\xbe\x0e\xfc\x3f\x8c\xc7\x19\x5f\x47\xe8\ \xfe\x87\x90\xf1\x75\x84\xea\x7f\x48\x19\x5f\x47\x50\xfe\x07\x9a\ \xf1\x75\x84\xe0\x7f\xe8\x19\x5f\x87\xcf\xfe\x93\xf1\x97\xf1\xce\ \x7f\x32\xfe\x2a\x7c\xf1\x9f\x8c\x6f\x87\x75\xff\xc9\xf8\x6e\x98\ \xf4\x9f\x8c\xef\x0d\x4b\xfe\x93\xf1\xfd\x63\xc1\x7f\x32\x7e\x38\ \x9c\xf5\x9f\x8c\x1f\x05\xd7\xfc\x27\xe3\xc7\xc5\x15\xff\xc9\xf8\ \x69\x98\xd4\x7f\x32\x7e\x72\xa6\xf0\x9f\x8c\x77\x87\x31\xfd\x27\ \xe3\xdd\x63\x70\xff\xc9\x78\xa7\x19\xca\x7f\x32\xde\x06\x7d\xfb\ \x4f\xc6\xdb\xa2\x17\xff\xc9\x78\xb3\x74\xf1\x9f\x8c\xb7\x4f\x1b\ \xff\xc9\x78\x7f\x68\xec\x3f\x19\xef\x25\x97\xfc\x27\xe3\xfd\xe6\ \x9c\xff\x64\x7c\x18\x54\xfc\x27\xe3\x83\x23\xff\xfd\x5e\x64\x3c\ \x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x00\x80\ \x73\xec\x42\xe7\xab\xe8\x2f\xaa\x13\xd1\x0b\xd1\x33\xd1\xd1\x5a\ \xf4\x52\xf4\x5c\x74\xa4\x3a\x16\xbd\x10\x3d\x13\x1d\x25\xa2\x97\ \xa2\xe7\xa2\xcb\x8f\x98\xeb\x58\xf4\x42\x74\xa4\x3a\x11\xbd\x14\ \x3d\x13\x7d\xbc\xe3\x41\xc7\xa2\xe7\xa2\x23\xd5\x89\xe8\x85\xe8\ \x99\xe8\xb7\x3b\x16\x7a\x29\x7a\x2e\x3a\x52\x1d\x8b\x5e\x88\x9e\ \x89\xde\x3f\x62\x49\xe7\x77\xfc\x7b\xd4\xfb\x3b\x96\x2e\xec\x1f\ \xf1\x8f\xdc\xf1\x78\xe1\xed\x33\xfe\xae\x3e\xe2\xf1\x42\x61\xc3\ \xaf\xca\x67\x2c\x2e\x94\x36\xe5\x7b\xf9\xa5\x14\x17\xe2\xb3\x5a\ \xfe\xbe\xfc\x7b\x72\x3f\x79\x1e\x79\x5e\xf9\x3c\xf2\x79\xe5\x7d\ \xe8\xfb\xd2\xf7\x59\xd2\xf2\xbe\xd5\x0f\xf5\x2b\x16\xbd\xab\x6a\ \xdd\x07\xdd\x97\x75\x55\xeb\xbe\xe9\x3e\x26\xa2\x77\x55\xad\xfb\ \x1e\x8b\x5e\x57\xb5\x9e\x27\x3d\x6f\x89\xe8\x5d\x55\xeb\x79\x8e\ \x45\xaf\xab\x5a\xf3\x42\xf3\x24\xa9\x6a\xcd\x23\xcd\xab\x58\xf4\ \xae\xaa\x35\x0f\x35\x2f\xd7\x55\xad\x79\xab\x79\x9c\x88\xae\xca\ \x93\xbc\x0f\x9c\x7f\x31\x73\xbc\x32\ " qt_resource_name = b"\ \x00\x09\ \x0c\x78\x54\x88\ \x00\x6e\ \x00\x65\x00\x77\x00\x50\x00\x72\x00\x65\x00\x66\x00\x69\x00\x78\ \x00\x0a\ \x0a\xc8\x83\x1f\ \x00\x67\ \x00\x6f\x00\x6e\x00\x64\x00\x65\x00\x72\x00\x2e\x00\x69\x00\x63\x00\x6f\ " qt_resource_struct_v1 = b"\ \x00\x00\x00\x00\x00\x02\x00\x00\x00\x01\x00\x00\x00\x01\ \x00\x00\x00\x00\x00\x02\x00\x00\x00\x01\x00\x00\x00\x02\ \x00\x00\x00\x18\x00\x01\x00\x00\x00\x01\x00\x00\x00\x00\ " qt_resource_struct_v2 = b"\ \x00\x00\x00\x00\x00\x02\x00\x00\x00\x01\x00\x00\x00\x01\ \x00\x00\x00\x00\x00\x00\x00\x00\ \x00\x00\x00\x00\x00\x02\x00\x00\x00\x01\x00\x00\x00\x02\ \x00\x00\x00\x00\x00\x00\x00\x00\ \x00\x00\x00\x18\x00\x01\x00\x00\x00\x01\x00\x00\x00\x00\ \x00\x00\x01\x6e\xda\x88\xff\x59\ " qt_version = [int(v) for v in QtCore.qVersion().split('.')] if qt_version < [5, 8, 0]: rcc_version = 1 qt_resource_struct = qt_resource_struct_v1 else: rcc_version = 2 qt_resource_struct = qt_resource_struct_v2 qInitResources()

47.357724

103

0.72721

081745d5d369bb388f32e0870139795f7243852c

213

py

Python

tuples-and-sets/3_unique_names.py

Minkov/python-advanced-2020-01

f2ee26f1325d943529673457a1cbba5657ae5905

[ "MIT" ]

5

2020-01-16T18:17:08.000Z

2020-04-12T06:42:47.000Z

tuples-and-sets/3_unique_names.py

Minkov/python-advanced-2020-01

f2ee26f1325d943529673457a1cbba5657ae5905

[ "MIT" ]

null

tuples-and-sets/3_unique_names.py

Minkov/python-advanced-2020-01

f2ee26f1325d943529673457a1cbba5657ae5905

[ "MIT" ]

null

n = int(input()) # names = {input() for _ in range(n)} names = [] for _ in range(n): names.append(input()) unique_names = list(set(names)) [print(name) for name in sorted(unique_names, key=names.index)]

15.214286

42

0.643192

081c3a4e5b548789411fc11be988031444e552dd

233

py

Python

dialogue/tensorflow/task/common/common.py

ishine/nlp-dialogue

d47c1438cb5c45c2c2aebfb82fea92bef4c3d65c

[ "Apache-2.0" ]

478

2020-10-28T01:30:30.000Z

2022-03-30T06:34:07.000Z

paper-code/tensorflow_src/models/task/common/common.py

HengYongChao/nlp-paper

fcf985e3c9bfd6944d07c4c36afbaee3384d040d

[ "Apache-2.0" ]

1

2021-08-29T11:55:09.000Z

2021-11-04T09:25:19.000Z

paper-code/tensorflow_src/models/task/common/common.py

HengYongChao/nlp-paper

fcf985e3c9bfd6944d07c4c36afbaee3384d040d

[ "Apache-2.0" ]

89

2021-01-05T06:11:55.000Z

2022-03-24T12:51:57.000Z

from optparse import OptionParser

19.416667

39

0.622318

081da69448bb7e8d65c5e3d690d670101f274a22

587

py

Python

posts/migrations/0003_auto_20200522_0446.py

NotBlizzard/lark

b348f8d2b532ce20581030397cbba7f6565d1c56

[ "MIT" ]

2

2020-12-10T06:13:36.000Z

2021-01-15T09:32:41.000Z

posts/migrations/0003_auto_20200522_0446.py

NotBlizzard/lark

b348f8d2b532ce20581030397cbba7f6565d1c56

[ "MIT" ]

7

2021-03-10T21:21:55.000Z

2021-09-22T19:20:03.000Z

posts/migrations/0003_auto_20200522_0446.py

NotBlizzard/lark

b348f8d2b532ce20581030397cbba7f6565d1c56

[ "MIT" ]

null

# Generated by Django 3.0.6 on 2020-05-22 04:46 from django.db import migrations, models

23.48

63

0.574106

081ea6e893da219c4f8a085a91c4473a4ef03166

191

py

Python

tasking/utils/models.py

cmanallen/tasking

0a613357148afdb4b55078c58429ec45bb60a436

[ "MIT" ]

null

tasking/utils/models.py

cmanallen/tasking

0a613357148afdb4b55078c58429ec45bb60a436

[ "MIT" ]

null

tasking/utils/models.py

cmanallen/tasking

0a613357148afdb4b55078c58429ec45bb60a436

[ "MIT" ]

null

from django.db import models

21.222222

50

0.78534

08212ae6445b938c3145af03c666f1c2c0d5163b

439

py

Python

{{cookiecutter.project_slug}}/{{cookiecutter.project_slug}}/conftest.py

SirTelemak/cookiecutter-python-template

d7d8c4493250654a4ee3badb36c4c4da1ccb8d3d

[ "MIT" ]

2

2020-06-04T19:17:13.000Z

2020-06-05T08:05:16.000Z

{{cookiecutter.project_slug}}/{{cookiecutter.project_slug}}/conftest.py

SirTelemak/cookiecutter-python-template

d7d8c4493250654a4ee3badb36c4c4da1ccb8d3d

[ "MIT" ]

1

2020-08-06T15:01:47.000Z

{{cookiecutter.project_slug}}/{{cookiecutter.project_slug}}/conftest.py

SirTelemak/cookiecutter-python-template

d7d8c4493250654a4ee3badb36c4c4da1ccb8d3d

[ "MIT" ]

2

2020-06-15T19:26:33.000Z

2020-11-20T20:24:03.000Z

import logging import pytest from loguru import logger

21.95

84

0.708428

08217e660e94837e28763173bb72fbc25fe9ee5e

216

py

Python

locale/pot/api/plotting/_autosummary/pyvista-Plotter-enable_lightkit-1.py

tkoyama010/pyvista-doc-translations

23bb813387b7f8bfe17e86c2244d5dd2243990db

[ "MIT" ]

4

2020-08-07T08:19:19.000Z

2020-12-04T09:51:11.000Z

locale/pot/api/plotting/_autosummary/pyvista-Plotter-enable_lightkit-1.py

tkoyama010/pyvista-doc-translations

23bb813387b7f8bfe17e86c2244d5dd2243990db

[ "MIT" ]

19

2020-08-06T00:24:30.000Z

2022-03-30T19:22:24.000Z

locale/pot/api/plotting/_autosummary/pyvista-Plotter-enable_lightkit-1.py

tkoyama010/pyvista-doc-translations

23bb813387b7f8bfe17e86c2244d5dd2243990db

[ "MIT" ]

1

2021-03-09T07:50:40.000Z

# Create a plotter without any lights and then enable the # default light kit. # import pyvista pl = pyvista.Plotter(lighting=None) pl.enable_lightkit() actor = pl.add_mesh(pyvista.Cube(), show_edges=True) pl.show()

24

57

0.763889

0822f1091f07394bee07ab3fa63b7142aa217e7c

1,353

py

Python

sphinx/environment/managers/__init__.py

rweickelt/sphinx

1a4c41a7691e8f78d42e2db221192962c53b27df

[ "BSD-2-Clause" ]

null

sphinx/environment/managers/__init__.py

rweickelt/sphinx

1a4c41a7691e8f78d42e2db221192962c53b27df

[ "BSD-2-Clause" ]

null

sphinx/environment/managers/__init__.py

rweickelt/sphinx

1a4c41a7691e8f78d42e2db221192962c53b27df

[ "BSD-2-Clause" ]

null

# -*- coding: utf-8 -*- """ sphinx.environment.managers ~~~~~~~~~~~~~~~~~~~~~~~~~~~ Manager components for sphinx.environment. :copyright: Copyright 2007-2016 by the Sphinx team, see AUTHORS. :license: BSD, see LICENSE for details. """ if False: # For type annotation from typing import Any # NOQA from docutils import nodes # NOQA from sphinx.environment import BuildEnvironment # NOQA

26.529412

68

0.604582

0822f39156313d04e61ff6ddaaed66e14edc3a38

3,692

py

Python

scripts/convert_queries.py

galuscakova/podcasts

967cc04e2b0f7cf963a189ac5270cfa69f81a540

[ "BSD-4-Clause-UC" ]

null

scripts/convert_queries.py

galuscakova/podcasts

967cc04e2b0f7cf963a189ac5270cfa69f81a540

[ "BSD-4-Clause-UC" ]

null

scripts/convert_queries.py

galuscakova/podcasts

967cc04e2b0f7cf963a189ac5270cfa69f81a540

[ "BSD-4-Clause-UC" ]

1

2021-05-27T07:44:51.000Z

import getopt import sys import os import re import string import xml.etree.ElementTree as ET input_filename = "" expansion_filename = "" output_type = "combine" exclude = set(string.punctuation) options, remainder = getopt.getopt(sys.argv[1:], 'i:e:t:', ['inputfile=', 'expansionfile=', 'type=']) for opt, arg in options: if opt in ('-i', '--inputfile'): input_filename = arg if (not os.path.exists(input_filename)): sys.exit("Error: Inputfile does not exists") if opt in ('-e', '--expansionfile'): expansion_filename = arg if (not os.path.exists(expansion_filename)): sys.exit("Error: Expansion file does not exists") if opt in ('-t', '--type'): output_type = arg expansion_terms = [] if (expansion_filename != ""): with open(expansion_filename) as expandfile: expansion_terms = expandfile.readlines() xml_root = ET.parse(input_filename) print("<parameters>") order = 0 for topic in xml_root.findall('.//topic'): num = topic.find('num').text query = topic.find('query').text description = topic.find('description').text query = query.replace('-', ' ') query = query.replace('\n', ' ') description = description.replace('-', ' ') description = description.replace('\n', ' ') query = query.translate(str.maketrans('', '', string.punctuation)) description = description.translate(str.maketrans('', '', string.punctuation)) print("<query>") print("<number>" + str(num) + "</number>") expansion = "" if ( expansion_filename != ""): line_expansion_term = expansion_terms[order] line_expansion_term = line_expansion_term.replace("[", "") line_expansion_term = line_expansion_term.replace("]", "") line_expansion_term = line_expansion_term.replace('"', "") line_expansion_term = line_expansion_term.replace('\n',"") line_expansion_terms = line_expansion_term.split(',') expansion = " " max_expansion_terms = 10 for i in range (min(max_expansion_terms, len(line_expansion_terms))): if (':' in line_expansion_terms[i]): term,score = line_expansion_terms[i].split(':') score = score.replace("\n", "") if (output_type == "weights"): expansion = expansion + str(score) + " #combine(" + term + ") " else: expansion = expansion + term expansion = expansion + " " if (output_type == "combine"): print("<text>#combine(" + query + " " + expansion + description + ")</text>") if (output_type == "weights"): print("<text>#weight( 1.0 #combine(" + query + ") " + expansion + " 0.5 #combine(" + description + "))</text>") if (output_type == "terms"): print("<text>" + query + " " + expansion + description + "</text>") if (output_type == "sdm"): query_sdm = get_sdm_query(query) description_sdm = get_sdm_query(description) print("<text>#weight(" + query_sdm + " " + description_sdm + ")</text>") print("</query>") order += 1 print("</parameters>")

34.830189

119

0.600488

08235f7faf3865296eebd91470431d320d7b228e

370

py

Python

createGlobalMap.py

abhi20sc/autoClim

b131a19e935e8ba7778a2c73107a183df37e92da

[ "MIT" ]

2

2021-07-28T05:58:20.000Z

2021-08-16T18:27:27.000Z

createGlobalMap.py

abhi20sc/autoClim

b131a19e935e8ba7778a2c73107a183df37e92da

[ "MIT" ]

null

createGlobalMap.py

abhi20sc/autoClim

b131a19e935e8ba7778a2c73107a183df37e92da

[ "MIT" ]

3

2021-08-05T15:21:05.000Z

2021-10-04T03:42:16.000Z

import cartopy.crs as ccrs import cartopy.feature as cf from matplotlib import pyplot as plt from matplotlib import image as img

30.833333

64

0.767568

0823b5eeb8c1036e06aae43d61945a3ec0226291

2,124

py

Python

tests/decloud_unittest.py

CNES/decloud

6b06ae98bfe68821b4ebd0e7ba06723809cb9b42

[ "Apache-2.0" ]

8

2022-02-25T13:15:07.000Z

2022-03-20T18:29:49.000Z

tests/decloud_unittest.py

CNES/decloud

6b06ae98bfe68821b4ebd0e7ba06723809cb9b42

[ "Apache-2.0" ]

1

2022-02-25T13:21:33.000Z

tests/decloud_unittest.py

CNES/decloud

6b06ae98bfe68821b4ebd0e7ba06723809cb9b42

[ "Apache-2.0" ]

1

2022-03-31T23:43:12.000Z

#!/usr/bin/env python3 # -*- coding: utf-8 -*- import os import subprocess import unittest import filecmp import gdal import otbApplication as otb from abc import ABC from decloud.core.system import get_env_var, pathify, basename

38.618182

107

0.672787

08248ac0b1e2686f247d443d0208fc7018480282

1,327

py

Python

test/test_merge.py

tawiesn/sclblonnx

0cf73112db5df13009cd2ddb5d49744689096209

[ "MIT" ]

null

test/test_merge.py

tawiesn/sclblonnx

0cf73112db5df13009cd2ddb5d49744689096209

[ "MIT" ]

null

test/test_merge.py

tawiesn/sclblonnx

0cf73112db5df13009cd2ddb5d49744689096209

[ "MIT" ]

null

from sclblonnx import add_output, add_input, add_node, node, empty_graph, add_constant, display, merge, run import numpy as np

34.025641

107

0.605124

08248cc60a1189c226093e9c782fd70e1acdd43e

2,609

py

Python

src/cameraCalibrator.py

mdaros2016/CarND-Advanced-Lane-Lines

b27d57f1c6730f302f18fb6b8cbbfcb9361d57bf

[ "MIT" ]

null

src/cameraCalibrator.py

mdaros2016/CarND-Advanced-Lane-Lines

b27d57f1c6730f302f18fb6b8cbbfcb9361d57bf

[ "MIT" ]

null

src/cameraCalibrator.py

mdaros2016/CarND-Advanced-Lane-Lines

b27d57f1c6730f302f18fb6b8cbbfcb9361d57bf

[ "MIT" ]

null

import glob import cv2 import numpy as np

38.367647

143

0.63166

0827c8ec658edf16eba00017e1a771b5d2f84def

591

py

Python

nicos_ess/dream/setups/beam_monitor.py

jkrueger1/nicos

5f4ce66c312dedd78995f9d91e8a6e3c891b262b

[ "CC-BY-3.0", "Apache-2.0", "CC-BY-4.0" ]

12

2019-11-06T15:40:36.000Z

2022-01-01T16:23:00.000Z

nicos_ess/dream/setups/beam_monitor.py

jkrueger1/nicos

5f4ce66c312dedd78995f9d91e8a6e3c891b262b

[ "CC-BY-3.0", "Apache-2.0", "CC-BY-4.0" ]

91

2020-08-18T09:20:26.000Z

2022-02-01T11:07:14.000Z

nicos_ess/dream/setups/beam_monitor.py

jkrueger1/nicos

5f4ce66c312dedd78995f9d91e8a6e3c891b262b

[ "CC-BY-3.0", "Apache-2.0", "CC-BY-4.0" ]

6

2020-01-11T10:52:30.000Z

2022-02-25T12:35:23.000Z

description = 'Instrument shutter' prefix = "IOC" devices = dict( beam_monitor_1=device( 'nicos_ess.devices.epics.motor.EpicsMotor', description="Beam monitor continuous position feedback", motorpv=f'{prefix}:m8', abslimits=(-10, 10), unit='mm', speed=5., ), beam_monitor_switch=device( 'nicos.devices.generic.Switcher', description="Toggles between in and out of the beam", moveable="beam_monitor_1", mapping={ 'IN': 0, 'OUT': 5, }, precision=0.01, ) )

24.625

64

0.566836

0829534c63fae0dfb66814593c9605ce70347325

28,509

py

Python

biosteam/_system.py

tylerhuntington222/biosteam

234959180a3210d95e39a012454f455723c92686

[ "MIT" ]

null

biosteam/_system.py

tylerhuntington222/biosteam

234959180a3210d95e39a012454f455723c92686

[ "MIT" ]

null

biosteam/_system.py

tylerhuntington222/biosteam

234959180a3210d95e39a012454f455723c92686

[ "MIT" ]

null

# -*- coding: utf-8 -*- # BioSTEAM: The Biorefinery Simulation and Techno-Economic Analysis Modules # Copyright (C) 2020, Yoel Cortes-Pena <yoelcortes@gmail.com> # # This module is under the UIUC open-source license. See # github.com/BioSTEAMDevelopmentGroup/biosteam/blob/master/LICENSE.txt # for license details. """ """ import flexsolve as flx from .digraph import (digraph_from_units_and_streams, minimal_digraph, surface_digraph, finalize_digraph) from thermosteam import Stream from thermosteam.utils import registered from .exceptions import try_method_with_object_stamp from ._network import Network from ._facility import Facility from ._unit import Unit from .report import save_report from .exceptions import InfeasibleRegion from .utils import colors, strtuple import biosteam as bst __all__ = ('System',) # %% Functions for taking care of numerical specifications within a system path # %% Debugging and exception handling def _evaluate(self, command=None): """ Evaluate a command and request user input for next command. If no command, return. This function is used for debugging a System object. """ # Done evaluating if no command, exit debugger if 'exit' if command is None: Next = colors.next('Next: ') + f'{repr(self)}\n' info = colors.info("Enter to continue or type to evaluate:\n") command = input(Next + info + ">>> ") if command == 'exit': raise KeyboardInterrupt() if command: # Build locals dictionary for evaluating command F = bst.main_flowsheet lcs = {self.ID: self, 'bst': bst, **F.system.__dict__, **F.stream.__dict__, **F.unit.__dict__, **F.flowsheet.__dict__ } try: out = eval(command, {}, lcs) except Exception as err: # Print exception and ask to raise error or continue evaluating err = colors.exception(f'{type(err).__name__}:') + f' {str(err)}\n\n' info = colors.info(f"Enter to raise error or type to evaluate:\n") command = input(err + info + ">>> ") if command == '': raise err _evaluate(self, command) else: # If successful, continue evaluating if out is None: pass elif (not hasattr(out, '_ipython_display_') or isinstance(out, type)): print(out) else: out._ipython_display_() command = input(">>> ") _evaluate(self, command) def _method_debug(self, func): """Method decorator for debugging system.""" wrapper.__name__ = func.__name__ wrapper.__doc__ = func.__doc__ wrapper._original = func return wrapper def _notify_run_wrapper(self, func): """Decorate a System run method to notify you after each loop""" wrapper.__name__ = func.__name__ wrapper.__doc__ = func.__doc__ wrapper._original = func return wrapper # %% Process flow from biosteam import _flowsheet as flowsheet_module

35.725564

128

0.582377

082bb5b00799a75a854f5404ce105bcaeac6c3e7

1,005

py

Python

modules/AI/research/findContour.py

killax-d/Counter-Coins-API

97acede70e26b23f96883bb14e2bf6ace3759174

[ "MIT" ]

null

modules/AI/research/findContour.py

killax-d/Counter-Coins-API

97acede70e26b23f96883bb14e2bf6ace3759174

[ "MIT" ]

null

modules/AI/research/findContour.py

killax-d/Counter-Coins-API

97acede70e26b23f96883bb14e2bf6ace3759174

[ "MIT" ]

null

import cv2 import numpy as np image = cv2.imread('original.png') gray = cv2.cvtColor(image.copy(), cv2.COLOR_BGR2GRAY) gray = cv2.equalizeHist(gray) blur = cv2.GaussianBlur(gray, (19, 19), 0) # Application d'un seuil pour obtenir une image binaire thresh = cv2.adaptiveThreshold(blur, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY_INV, 11, 1) kernel = np.ones((3, 3), np.uint8) # Application d'rosion et d'ouverture pour supprimer les contours de petites pices closing = cv2.morphologyEx(thresh, cv2.MORPH_CLOSE, kernel, iterations=1) contours, hierarchy = cv2.findContours(closing.copy(), cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE) for contour in contours: area = cv2.contourArea(contour) if area < 10000 or area > 50000: continue print(area) if len(contour) < 5: continue try: ellipse = cv2.fitEllipse(contour) cv2.ellipse(image, ellipse, (0,255,0), 2) except: pass # ecriture de l'image cv2.imwrite('result.png', image)

30.454545

103

0.711443

083461c10e66e08e6e0c8ad2d8f84b46b0b09e65

8,413

py

Python

python/src/ties/cli/test/ties_convert_tests.py

Noblis/ties-lib

e7c6165ebcd80e11b792fd4bcddf6ce634da0c60

[ "ECL-2.0", "Apache-2.0" ]

1

2020-04-10T19:02:27.000Z

python/src/ties/cli/test/ties_convert_tests.py

Noblis/ties-lib

e7c6165ebcd80e11b792fd4bcddf6ce634da0c60

[ "ECL-2.0", "Apache-2.0" ]

null

python/src/ties/cli/test/ties_convert_tests.py

Noblis/ties-lib

e7c6165ebcd80e11b792fd4bcddf6ce634da0c60

[ "ECL-2.0", "Apache-2.0" ]

null

################################################################################ # Copyright 2019 Noblis, Inc # # # # 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. # ################################################################################ import json import os import unittest from stat import S_IRUSR from tempfile import mkstemp from unittest import TestCase from ties.cli.ties_convert import main from ties.util.testing import cli_test short_usage = """\ usage: ties-convert [-h] [--classification-level SECURITY_TAG] [--output-file OUTPUT_FILE | --in-place] [--version] EXPORT_PATH""" long_usage = """\ {} Converts TIES export.json files from older versions of the schema (0.1.8, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8) to the current version (0.9). positional arguments: EXPORT_PATH the path to the TIES JSON file or - to read from stdin optional arguments: -h, --help show this help message and exit --classification-level SECURITY_TAG, -c SECURITY_TAG the classification level of the TIES JSON, required for TIES JSON from pre-0.3 versions of the schema --output-file OUTPUT_FILE, -f OUTPUT_FILE the output file path for the converted TIES JSON --in-place, -i modifies the input file in-place, overwriting it with the converted JSON data --version prints version information """.format(short_usage) test_input = """\ { "version": "0.1.8", "objectItem": [ { "sha256Hash": "aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa", "md5Hash": "aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa" } ] }""" test_output = """\ { "version": "0.9", "securityTag": "UNCLASSIFIED", "objectItems": [ { "objectId": "aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa", "sha256Hash": "aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa", "md5Hash": "aaaaaaaaaaaaaaaaaaaaaaaaaaaaaaaa", "authorityInformation": { "securityTag": "UNCLASSIFIED" } } ] }""" if __name__ == '__main__': unittest.main()

36.578261

111

0.562463

0834a96e609f196a4e397fc0d0398ea157ccd7e5

2,316

py

Python

Edge Detection.py

paulmtree/Lung-Segmentation-Project

2cffe09ce6a4818200d88b9e4e87155feb594366

[ "MIT" ]

14

2020-11-10T16:47:54.000Z

2022-03-15T12:17:29.000Z

Edge Detection.py

paulmtree/Lung-Segmentation-Project

2cffe09ce6a4818200d88b9e4e87155feb594366

[ "MIT" ]

3

2020-11-21T09:49:15.000Z

2021-05-30T23:58:30.000Z

Edge Detection.py

paulmtree/Lung-Segmentation-Project

2cffe09ce6a4818200d88b9e4e87155feb594366

[ "MIT" ]

3

2021-11-04T18:08:53.000Z

2022-01-13T03:22:26.000Z

from PIL import Image, ImageFilter import numpy as np import glob from numpy import array import matplotlib.pyplot as plt from skimage import morphology import scipy.ndimage """ datapath = "jpg_images/" img0 = Image.open("jpg_images/maskedimage" + str(0) + ".jpg") counter = 0 img1 = [] for f in glob.glob('/Users/paulmccabe/Desktop/jpg images/*.jpg'): path = "jpg_images/maskedimage" + str(counter) + ".jpg" img0 = Image.open(path).convert('L') img1.append(array(img0)) counter += 1 print("Counter: " + str(counter)) imgs_to_process_orig = np.stack([s for s in img1]) """ id = 2 imgs = np.load("/Users/paulmccabe/Desktop/Segmentation Project/" + "justmask_%d.npy" % (id)) counter = 0 print("Saving as jpg Images...") for img in imgs: scipy.misc.imsave('/Users/paulmccabe/Desktop/Segmentation Project' + '/jpg mask images/justmask{}.jpg'.format(counter), img) counter += 1 counter = 0 #print("Re-Importing jpg Images...") #for f in glob.glob('/Users/paulmccabe/Desktop/Segmentation Project/jpg mask images/*.jpg'): # path = "jpg_images/maskedimage" + str(counter) + ".jpg" # img0 = Image.open(path).convert('L') # img1.append(array(img0)) # counter += 1 imgs[imgs == 1] = 255 list = [] for img in imgs: PIL_img = Image.fromarray(img.astype('uint8')) PIL_edge = PIL_img.filter(ImageFilter.FIND_EDGES) np_img = array(PIL_edge) dilation = morphology.dilation(np_img, np.ones([4,4])) list.append(dilation) imgs_after_processing = np.stack([s for s in list]) np.save("/Users/paulmccabe/Desktop/Segmentation Project" + "/justedge_%d.npy" % (id), imgs_after_processing[:284]) #sample_stack(np_img)

35.090909

128

0.658895

08354cb83dbefe75aa87b426bfa4c3e544572c47

2,191

py

Python

benchmark.py

Umass-ITS/Open3D-PointNet2-Semantic3D

0254926f62cbca695aa1e76a18fec0863be5e455

[ "MIT" ]

330

2019-04-10T21:31:24.000Z

2021-07-26T06:16:17.000Z

benchmark.py

largeword/Open3D-PointNet2-Semantic3D

3a9751dc724877933fc883320100796cef23489d

[ "MIT" ]

44

2019-04-10T15:28:36.000Z

2021-06-22T17:39:05.000Z

benchmark.py

largeword/Open3D-PointNet2-Semantic3D

3a9751dc724877933fc883320100796cef23489d

[ "MIT" ]

78

2019-04-08T09:39:29.000Z

2021-06-08T02:39:14.000Z

import json import numpy as np import tensorflow as tf import time from predict import Predictor if __name__ == "__main__": checkpoint = "logs/semantic_backup_full_submit_dec_10/best_model_epoch_275.ckpt" hyper_params = json.loads(open("semantic.json").read()) predictor = Predictor( checkpoint_path=checkpoint, num_classes=9, hyper_params=hyper_params ) batch_size = 64 # Init data points_with_colors = np.random.randn(batch_size, hyper_params["num_point"], 6) # Warm up pd_labels = predictor.predict(points_with_colors) # Benchmark s = time.time() profiler = tf.profiler.Profiler(predictor.sess.graph) run_options = tf.RunOptions(trace_level=tf.RunOptions.FULL_TRACE) run_metadata = tf.RunMetadata() _ = predictor.predict( points_with_colors, run_options=run_options, run_metadata=run_metadata ) profiler.add_step(0, run_metadata) batch_time = time.time() - s sample_time = batch_time / batch_size print( "Batch size: {}, batch_time: {}, sample_time: {}".format( batch_size, batch_time, sample_time ) ) option_builder = tf.profiler.ProfileOptionBuilder opts = ( option_builder(option_builder.time_and_memory()) .with_step(-1) # with -1, should compute the average of all registered steps. .with_file_output("tf-profile.txt") .select(["micros", "bytes", "occurrence"]) .order_by("micros") .build() ) # Profiling info about ops are saved in 'test-%s.txt' % FLAGS.out profiler.profile_operations(options=opts) for batch_size in [2 ** n for n in range(8)]: # Init data points_with_colors = np.random.randn(batch_size, hyper_params["num_point"], 6) # Warm up pd_labels = predictor.predict(points_with_colors) # Benchmark s = time.time() _ = predictor.predict(points_with_colors) batch_time = time.time() - s sample_time = batch_time / batch_size print( "Batch size: {}, batch_time: {}, sample_time: {}".format( batch_size, batch_time, sample_time ) )

30.013699

86

0.652214

0836babd9f72c506519d713c961b9257fd759c19

447

py

Python

tests/my_select_group.py

oldjun/PyMyORM

ac49910f21d3f3d3d4b3d75a0f998526963f0a2a

[ "MIT" ]

1

2021-12-01T23:47:24.000Z

tests/my_select_group.py

oldjun/PyMyORM

ac49910f21d3f3d3d4b3d75a0f998526963f0a2a

[ "MIT" ]

null

tests/my_select_group.py

oldjun/PyMyORM

ac49910f21d3f3d3d4b3d75a0f998526963f0a2a

[ "MIT" ]

2

2022-01-03T15:03:37.000Z

2022-02-16T09:00:58.000Z

from pymyorm.database import Database from config import db from models.user import User if __name__ == '__main__': Database.connect(**db) # # case 1 # all = User.find().select('count(*) as count', 'money').group('money').order('count asc').all() # for one in all: # print(one) all = User.find().select('gender', 'count(*) as count', 'avg(money) as avg').group('gender').all() for one in all: print(one)

27.9375

102

0.615213

083725212ef9f198c79212406fcc54599eb1abb4

2,783

py

Python

framework/codejam/extract/cyclomatic_complexity.py

neizod/coding-analysis

cc086bcf204e570032d11b12a46ac819cfe93f2b

[ "MIT" ]

1

2015-05-22T05:01:53.000Z

framework/codejam/extract/cyclomatic_complexity.py

neizod/coding-analysis

cc086bcf204e570032d11b12a46ac819cfe93f2b

[ "MIT" ]

null

framework/codejam/extract/cyclomatic_complexity.py

neizod/coding-analysis

cc086bcf204e570032d11b12a46ac819cfe93f2b

[ "MIT" ]

null

import os import json import logging from framework._utils import FunctionHook

42.815385

75

0.606899

08384f79281339a1e0387a70c9f20061ae7f5d42

64

py

Python

tests/basic/numeric.py

MoonStarCZW/py2rb

89b247717d33d780fbf143e1583bfe9252984da4

[ "MIT" ]

null

tests/basic/numeric.py

MoonStarCZW/py2rb

89b247717d33d780fbf143e1583bfe9252984da4

[ "MIT" ]

null

tests/basic/numeric.py

MoonStarCZW/py2rb

89b247717d33d780fbf143e1583bfe9252984da4

[ "MIT" ]

null

print(int(2.0)) print(float(2)) print(abs(-2.0)) print(abs(-2))

12.8

16

0.625

083ac0bbfaedec44e83a000de5fcb0cfa49ed48e

310

py

Python

tests/symmetry/test_point_group.py

kijanac/Materia

b49af518c8eff7d3a8c6caff39783e3daf80a7a0

[ "MIT" ]

null

tests/symmetry/test_point_group.py

kijanac/Materia

b49af518c8eff7d3a8c6caff39783e3daf80a7a0

[ "MIT" ]

null

tests/symmetry/test_point_group.py

kijanac/Materia

b49af518c8eff7d3a8c6caff39783e3daf80a7a0

[ "MIT" ]

null

# import materia as mtr # import numpy as np # def test_point_group_C1(): # ctable = mtr.symmetry.C1().cayley_table() # assert (ctable == np.array([[0]])).all() # def test_point_group_Ci(): # ctable = mtr.symmetry.Ci().cayley_table() # assert (ctable == np.array([[0, 1], [1, 0]])).all()

20.666667

57

0.606452

083e03b527a87a9ebea41c58c4a9944e76e7007f

1,948

py

Python

extrator/test/test_pipeline.py

MinisterioPublicoRJ/robotj

946e9547eea6f548609f7ccfaf1c6a13fffece65

[ "MIT" ]

3

2018-03-13T12:17:13.000Z

2021-04-18T19:55:04.000Z

extrator/test/test_pipeline.py

MinisterioPublicoRJ/robotj

946e9547eea6f548609f7ccfaf1c6a13fffece65

[ "MIT" ]

1

2018-06-19T13:09:10.000Z

extrator/test/test_pipeline.py

MinisterioPublicoRJ/robotj

946e9547eea6f548609f7ccfaf1c6a13fffece65

[ "MIT" ]

1

2021-04-18T19:55:09.000Z

from unittest.mock import patch, MagicMock from unittest import TestCase from ..crawler.pipeliner import pipeline from ..settings import URL_PROCESSO

38.96

76

0.661704

083f30db4f011f2e287409fe5ae43ef0e966b47a

3,943

py

Python

tests/test_step.py

arup-group/mc

50b8faa8b9d40dece88e0a27f911edd427ebc064

[ "MIT" ]

null

tests/test_step.py

arup-group/mc

50b8faa8b9d40dece88e0a27f911edd427ebc064

[ "MIT" ]

12

2021-12-14T15:10:43.000Z

2022-03-31T13:39:25.000Z

tests/test_step.py

arup-group/mc

50b8faa8b9d40dece88e0a27f911edd427ebc064

[ "MIT" ]

null

from pathlib import Path import pytest from copy import deepcopy import os from mc.base import BaseConfig from mc import step

39.43

103

0.672331

0840e1f2cca91c8f40fea1035d91f9ed0ea2c8f1

15,552

py

Python

lambda_functions.py

intirix/serverless-secrets-manager

2c89b2c497f7078c38885125dfa79db944a214db

[ "Apache-2.0" ]

2

2018-05-23T06:04:13.000Z

2020-11-04T23:16:09.000Z

lambda_functions.py

intirix/serverless-secrets-manager

2c89b2c497f7078c38885125dfa79db944a214db

[ "Apache-2.0" ]

null

lambda_functions.py

intirix/serverless-secrets-manager

2c89b2c497f7078c38885125dfa79db944a214db

[ "Apache-2.0" ]

null

#!/usr/bin/python import system import db import client import server import logging import json import base64 import os from aws_xray_sdk.core import patch_all if "AWS_REGION" in os.environ: patch_all() _singleton = None FORMAT = "%(asctime)-15s %(message)s" logging.basicConfig(format=FORMAT)

29.622857

84

0.600244

08418a8370fcf775a2fd7e29466ecc715efe0e4f

2,575

py

Python

tests/utils_test.py

asrashley/dash-live

1ffbc57896e4e46855a42af6ef79a1865ebfce55

[ "Apache-2.0" ]

2

2019-11-02T06:26:29.000Z

2020-05-15T16:54:20.000Z

tests/utils_test.py

asrashley/dash-live

1ffbc57896e4e46855a42af6ef79a1865ebfce55

[ "Apache-2.0" ]

1

2020-01-20T17:20:54.000Z

2020-01-21T08:38:30.000Z

tests/utils_test.py

asrashley/dash-live

1ffbc57896e4e46855a42af6ef79a1865ebfce55

[ "Apache-2.0" ]

null

try: import cStringIO as StringIO except ImportError: import StringIO import datetime import os import sys import unittest _src = os.path.join(os.path.dirname(__file__),"..", "src") if not _src in sys.path: sys.path.append(_src) import utils if __name__ == "__main__": unittest.main()

35.763889

97

0.597282

08432f03ae4911f91726c50919d96811876b71c7

9,364

py

Python

midv500/download_dataset.py

fcakyon/midv500-to-coco

2f1cd74e0bb8da2301a96e3fb0cd9f17005ed08c

[ "MIT" ]

39

2020-05-15T17:34:32.000Z

2022-03-25T08:22:47.000Z

midv500/download_dataset.py

fcakyon/midv500-to-coco

2f1cd74e0bb8da2301a96e3fb0cd9f17005ed08c

[ "MIT" ]

1

2020-08-04T09:04:06.000Z

2020-08-19T12:50:15.000Z

midv500/download_dataset.py

fcakyon/midv500-to-coco

2f1cd74e0bb8da2301a96e3fb0cd9f17005ed08c

[ "MIT" ]

6

2020-04-23T19:40:16.000Z

2021-12-19T17:52:42.000Z

import os import argparse from midv500.utils import download, unzip midv500_links = [ "ftp://smartengines.com/midv-500/dataset/01_alb_id.zip", "ftp://smartengines.com/midv-500/dataset/02_aut_drvlic_new.zip", "ftp://smartengines.com/midv-500/dataset/03_aut_id_old.zip", "ftp://smartengines.com/midv-500/dataset/04_aut_id.zip", "ftp://smartengines.com/midv-500/dataset/05_aze_passport.zip", "ftp://smartengines.com/midv-500/dataset/06_bra_passport.zip", "ftp://smartengines.com/midv-500/dataset/07_chl_id.zip", "ftp://smartengines.com/midv-500/dataset/08_chn_homereturn.zip", "ftp://smartengines.com/midv-500/dataset/09_chn_id.zip", "ftp://smartengines.com/midv-500/dataset/10_cze_id.zip", "ftp://smartengines.com/midv-500/dataset/11_cze_passport.zip", "ftp://smartengines.com/midv-500/dataset/12_deu_drvlic_new.zip", "ftp://smartengines.com/midv-500/dataset/13_deu_drvlic_old.zip", "ftp://smartengines.com/midv-500/dataset/14_deu_id_new.zip", "ftp://smartengines.com/midv-500/dataset/15_deu_id_old.zip", "ftp://smartengines.com/midv-500/dataset/16_deu_passport_new.zip", "ftp://smartengines.com/midv-500/dataset/17_deu_passport_old.zip", "ftp://smartengines.com/midv-500/dataset/18_dza_passport.zip", "ftp://smartengines.com/midv-500/dataset/19_esp_drvlic.zip", "ftp://smartengines.com/midv-500/dataset/20_esp_id_new.zip", "ftp://smartengines.com/midv-500/dataset/21_esp_id_old.zip", "ftp://smartengines.com/midv-500/dataset/22_est_id.zip", "ftp://smartengines.com/midv-500/dataset/23_fin_drvlic.zip", "ftp://smartengines.com/midv-500/dataset/24_fin_id.zip", "ftp://smartengines.com/midv-500/dataset/25_grc_passport.zip", "ftp://smartengines.com/midv-500/dataset/26_hrv_drvlic.zip", "ftp://smartengines.com/midv-500/dataset/27_hrv_passport.zip", "ftp://smartengines.com/midv-500/dataset/28_hun_passport.zip", "ftp://smartengines.com/midv-500/dataset/29_irn_drvlic.zip", "ftp://smartengines.com/midv-500/dataset/30_ita_drvlic.zip", "ftp://smartengines.com/midv-500/dataset/31_jpn_drvlic.zip", "ftp://smartengines.com/midv-500/dataset/32_lva_passport.zip", "ftp://smartengines.com/midv-500/dataset/33_mac_id.zip", "ftp://smartengines.com/midv-500/dataset/34_mda_passport.zip", "ftp://smartengines.com/midv-500/dataset/35_nor_drvlic.zip", "ftp://smartengines.com/midv-500/dataset/36_pol_drvlic.zip", "ftp://smartengines.com/midv-500/dataset/37_prt_id.zip", "ftp://smartengines.com/midv-500/dataset/38_rou_drvlic.zip", "ftp://smartengines.com/midv-500/dataset/39_rus_internalpassport.zip", "ftp://smartengines.com/midv-500/dataset/40_srb_id.zip", "ftp://smartengines.com/midv-500/dataset/41_srb_passport.zip", "ftp://smartengines.com/midv-500/dataset/42_svk_id.zip", "ftp://smartengines.com/midv-500/dataset/43_tur_id.zip", "ftp://smartengines.com/midv-500/dataset/44_ukr_id.zip", "ftp://smartengines.com/midv-500/dataset/45_ukr_passport.zip", "ftp://smartengines.com/midv-500/dataset/46_ury_passport.zip", "ftp://smartengines.com/midv-500/dataset/47_usa_bordercrossing.zip", "ftp://smartengines.com/midv-500/dataset/48_usa_passportcard.zip", "ftp://smartengines.com/midv-500/dataset/49_usa_ssn82.zip", "ftp://smartengines.com/midv-500/dataset/50_xpo_id.zip", ] midv2019_links = [ "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/01_alb_id.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/02_aut_drvlic_new.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/03_aut_id_old.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/04_aut_id.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/05_aze_passport.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/06_bra_passport.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/07_chl_id.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/08_chn_homereturn.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/09_chn_id.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/10_cze_id.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/11_cze_passport.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/12_deu_drvlic_new.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/13_deu_drvlic_old.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/14_deu_id_new.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/15_deu_id_old.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/16_deu_passport_new.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/17_deu_passport_old.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/18_dza_passport.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/19_esp_drvlic.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/20_esp_id_new.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/21_esp_id_old.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/22_est_id.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/23_fin_drvlic.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/24_fin_id.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/25_grc_passport.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/26_hrv_drvlic.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/27_hrv_passport.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/28_hun_passport.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/29_irn_drvlic.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/30_ita_drvlic.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/31_jpn_drvlic.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/32_lva_passport.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/33_mac_id.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/34_mda_passport.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/35_nor_drvlic.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/36_pol_drvlic.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/37_prt_id.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/38_rou_drvlic.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/39_rus_internalpassport.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/40_srb_id.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/41_srb_passport.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/42_svk_id.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/43_tur_id.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/44_ukr_id.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/45_ukr_passport.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/46_ury_passport.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/47_usa_bordercrossing.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/48_usa_passportcard.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/49_usa_ssn82.zip", "ftp://smartengines.com/midv-500/extra/midv-2019/dataset/50_xpo_id.zip", ] def download_dataset(download_dir: str, dataset_name: str = "midv500"): """ This script downloads the MIDV-500 dataset with extra files and unzips the folders. dataset_name: str "midv500": https://doi.org/10.18287/2412-6179-2019-43-5-818-824 "midv2019": https://doi.org/10.1117/12.2558438 "all": midv500 + midv2019 """ if dataset_name == "midv500": links_set = { "midv500": midv500_links, } elif dataset_name == "midv2019": links_set = { "midv2019": midv2019_links, } elif dataset_name == "all": links_set = { "midv500": midv500_links, "midv2019": midv2019_links, } else: Exception('Invalid dataset_name, try one of "midv500", "midv2019" or "all".') for k, v in links_set.items(): dst = os.path.join(download_dir, k) for link in v: print("--------------------------------------------------------------") # download zip file link = link.replace("\\", "/") # for windows filename = link.split("/")[-1] print("\nDownloading:", filename) download(link, dst) print("Downloaded:", filename) # unzip zip file print("Unzipping:", filename) zip_path = os.path.join(dst, filename) unzip(zip_path, dst) print("Unzipped:", filename.replace(".zip", "")) # remove zip file os.remove(zip_path) if __name__ == "__main__": # construct the argument parser ap = argparse.ArgumentParser() # add the arguments to the parser ap.add_argument( "download_dir", default="data/", help="Directory for MIDV-500 dataset to be downloaded.", ) args = vars(ap.parse_args()) # download dataset download_dataset(args["download_dir"])

54.127168

90

0.705788

0845053b64f5370f1498b8e4729e90a827f0c839

6,329

py

Python

erpnext_taxjar/api.py

DigiThinkIT/erpnext_taxjar

5313dbdd931745e9655d3f5fd53c830abb0d7ee7

[ "MIT" ]

null

erpnext_taxjar/api.py

DigiThinkIT/erpnext_taxjar

5313dbdd931745e9655d3f5fd53c830abb0d7ee7

[ "MIT" ]

8

2017-07-01T11:13:14.000Z

2020-11-19T13:26:29.000Z

erpnext_taxjar/api.py

DigiThinkIT/erpnext_taxjar

5313dbdd931745e9655d3f5fd53c830abb0d7ee7

[ "MIT" ]

13

2017-06-30T15:47:00.000Z

2022-02-22T16:24:41.000Z

import traceback import pycountry import taxjar import frappe from erpnext import get_default_company from frappe import _ from frappe.contacts.doctype.address.address import get_company_address TAX_ACCOUNT_HEAD = frappe.db.get_single_value("TaxJar Settings", "tax_account_head") SHIP_ACCOUNT_HEAD = frappe.db.get_single_value("TaxJar Settings", "shipping_account_head")

26.931915

133

0.746721

08453ede8c646dbf40688a3665092cf3d4f4e359

3,543

py

Python

tests/lib_test.py

grundrauschen/center-points

5a12f68ac012a0a2bf52d8a8381d0272e309ac18

[ "MIT" ]

null

tests/lib_test.py

grundrauschen/center-points

5a12f68ac012a0a2bf52d8a8381d0272e309ac18

[ "MIT" ]

2

2015-06-03T10:57:13.000Z

2015-09-15T12:43:22.000Z

tests/lib_test.py

fu-berlin-swp-2014/center-points

0fa523314a3168d4d229b6f61d0d05d314a8b35a

[ "MIT" ]

null

import unittest import numpy as np import numpy.testing as nptest import centerpoints.lib as lib

36.90625

76

0.519616

084547589496d6e3bddafc72879279f994ed30e1

711

py

Python

genome-experimentation/cleaning-genome-data.py

shivamsyal/summer21

68cdcae1524e720066e57baa190f15477b69515a

[ "MIT" ]

null

genome-experimentation/cleaning-genome-data.py

shivamsyal/summer21

68cdcae1524e720066e57baa190f15477b69515a

[ "MIT" ]

null

genome-experimentation/cleaning-genome-data.py

shivamsyal/summer21

68cdcae1524e720066e57baa190f15477b69515a

[ "MIT" ]

2

2022-01-10T18:16:18.000Z

2022-03-20T01:17:28.000Z

# test comment import os filename = input("File to format: ") os.system("gunzip "+filename) n = int(input("What number genome is this? ")) os.system("mv "+filename[:-3]+" genome"+str(n)+".fna") original = "genome"+str(n)+".fna" copy = "genome"+str(n)+"_copy.fna" filtered = "genome"+str(n)+"_filtered.fna" rem = ['>'] with open(original) as old, open(copy,'w') as new: for line in old: if not any(bad in line for bad in rem): new.write(line) with open(copy) as f, open(filtered,'a') as f2: f2.write("".join(line.strip() for line in f)) with open(filtered, 'r+') as inp: y = inp.read().upper() inp.truncate(0) with open(filtered, 'a') as out: out.write(y) os.remove(copy)

30.913043

54

0.624473

084592c05031adcf4e22889393a72a2880d58eb8

758

py

Python

villas/controller/components/managers/generic.py

VILLASframework/VILLAScontroller

e672439797f209afdd5bc62078f7d49c60269aa4

[ "Apache-2.0" ]

null

villas/controller/components/managers/generic.py

VILLASframework/VILLAScontroller

e672439797f209afdd5bc62078f7d49c60269aa4

[ "Apache-2.0" ]

null

villas/controller/components/managers/generic.py

VILLASframework/VILLAScontroller

e672439797f209afdd5bc62078f7d49c60269aa4

[ "Apache-2.0" ]

null

from villas.controller.components.manager import Manager from villas.controller.component import Component

28.074074

76

0.62533

0845d2588d5c55abf24f9ab405009bd284d758d8

833

py

Python

tests/test_composition.py

gregorynicholas/proto-pigeon

65a5d961e7a8506f3a968b21aaf68f625fd13190

[ "Apache-2.0" ]

null

tests/test_composition.py

gregorynicholas/proto-pigeon

65a5d961e7a8506f3a968b21aaf68f625fd13190

[ "Apache-2.0" ]

null

tests/test_composition.py

gregorynicholas/proto-pigeon

65a5d961e7a8506f3a968b21aaf68f625fd13190

[ "Apache-2.0" ]

null

from protorpc.messages import Message, IntegerField, StringField import protopigeon def test(): ComposedMessage = protopigeon.compose(MessageOne, MessageTwo) assert hasattr(ComposedMessage, 'one') assert hasattr(ComposedMessage, 'two') assert hasattr(ComposedMessage, 'three') assert hasattr(ComposedMessage, 'four') # Make sure these fields weren't modified assert MessageOne.one.number == 1 assert MessageOne.two.number == 2 assert MessageTwo.three.number == 1 assert MessageTwo.four.number == 2 instance = ComposedMessage( one=1, two=2, three='three', four='four') assert instance

23.138889

65

0.686675

0846011f39bb03a7af3bf569426365af42543fe1

1,503

py

Python

udacity-program_self_driving_car_engineer_v2.0/module02-computer vision/exercise02-data acquisiton and visualization/visualization.py

linksdl/futuretec-project-self_driving_cars_projects

38e8f14543132ec86a8bada8d708eefaef23fee8

[ "MIT" ]

null

udacity-program_self_driving_car_engineer_v2.0/module02-computer vision/exercise02-data acquisiton and visualization/visualization.py

linksdl/futuretec-project-self_driving_cars_projects

38e8f14543132ec86a8bada8d708eefaef23fee8

[ "MIT" ]

null

udacity-program_self_driving_car_engineer_v2.0/module02-computer vision/exercise02-data acquisiton and visualization/visualization.py

linksdl/futuretec-project-self_driving_cars_projects

38e8f14543132ec86a8bada8d708eefaef23fee8

[ "MIT" ]

null

""" # !/usr/bin/env python # -*- coding: utf-8 -*- @Time : 2022/2/23 19:35 @Author : shengdl999links@gmail.com @ProjectName : udacity-program_self_driving_car_engineer_v1.0_source.0 @File : visualization.py """ import glob import os.path import matplotlib.pyplot as plt from matplotlib.patches import Rectangle from PIL import Image from utils import get_data def viz(ground_truth): """ create a grid visualization of images with color coded bboxes args: - ground_truth [list[dict]]: ground truth data """ # IMPLEMENT THIS FUNCTION paths = glob.glob('../data/images/*') gt_dic = {} # mapping to access data faster for gt in ground_truth: gt_dic[gt['filename']] = gt # color mapping of classes color_map = {1: [1, 0, 0], 2: [0, 1, 0], 4: [0, 0, 1]} f, ax = plt.subplots(4, 5, figsize=(20, 10)) for i in range(20): x = i % 4 y = i % 5 filename = os.path.basename(paths[i]) img = Image.open(paths[i]) ax[x, y].imshow(img) bboxes = gt_dic[filename]['boxes'] classes = gt_dic[filename]['classes'] for cl, bb in zip(classes, bboxes): y1, x1, y2, x2 = bb rec = Rectangle((x1, y1), x2 - x1, y2 - y1, facecolor='none', edgecolor=color_map[cl]) ax[x, y].add_patch(rec) ax[x, y].axis('off') plt.tight_layout() plt.show() if __name__ == "__main__": ground_truth, _ = get_data() viz(ground_truth)

25.05

98

0.594145

084746dfc5f458e9131b1743d5567db36da8ab9c

898

py

Python

setup.py

georgenicolaou/python-fakeports

24eecf879e0d2d2a100be06952fb3677019457e2

[ "MIT" ]

3

2020-02-03T08:25:10.000Z

2021-09-29T15:59:01.000Z

setup.py

georgenicolaou/python-fakeports

24eecf879e0d2d2a100be06952fb3677019457e2

[ "MIT" ]

2

2021-01-18T19:27:44.000Z

setup.py

georgenicolaou/python-fakeports

24eecf879e0d2d2a100be06952fb3677019457e2

[ "MIT" ]

null

from setuptools import setup long_description = 'TODO' # with open("README.md", "r") as rfd: # long_description = rfd.read() REQUIREMENTS = [r.strip() for r in open("requirements.txt").readlines()] setup( name='python-fakeports', version="0.1", packages=['python_fakeports'], url='', license='GPL', author='George Nicolaou', author_email='george@silensec.com', description='Python clone of portspoof', long_description=long_description, install_requires=REQUIREMENTS, data_files=[ ('/etc/fakeports/', ['fakeports.yml.sample']), ('/usr/local/bin/', ['bin/fakeports.tac']) ], scripts=['bin/fakeportsctl', 'bin/fakeportsd'], platforms='any', classifiers = [line.strip() for line in '''\ Development Status :: 4 - Beta Intended Audience :: System Administrators Operating System :: POSIX :: Linux '''] )

28.967742

72

0.644766

08483d8175b8bd82d7534d3c981f5d1467884db2

195

py

Python

darzalib/Incoming/__init__.py

swrlly/Midnight

b4375002761a13a09a6c3085e9b34384b28227ba

[ "MIT" ]

2

2021-11-18T13:38:52.000Z

2021-11-19T04:15:24.000Z

darzalib/Incoming/__init__.py

swrlly/Midnight

b4375002761a13a09a6c3085e9b34384b28227ba

[ "MIT" ]

null

darzalib/Incoming/__init__.py

swrlly/Midnight

b4375002761a13a09a6c3085e9b34384b28227ba

[ "MIT" ]

null

from .BiomeDisplay import BiomeDisplay from .Chats import Chats from .PlayEffect import PlayEffect from .Reconnect import Reconnect from .SwapAck import SwapAck from .UseItemAck import UseItemAck

32.5

38

0.851282

08486cbf36ba6ba189128910a8b98a815a664466

938

py

Python

python/17_letter_combinations_of_a_phone_number.py

dchapp/blind75

aaa409cf2db4ef6d0f86177f4217eceeb391caa8

[ "MIT" ]

null

python/17_letter_combinations_of_a_phone_number.py

dchapp/blind75

aaa409cf2db4ef6d0f86177f4217eceeb391caa8

[ "MIT" ]

null

python/17_letter_combinations_of_a_phone_number.py

dchapp/blind75

aaa409cf2db4ef6d0f86177f4217eceeb391caa8

[ "MIT" ]

null

num_to_letters = { '2': ['a', 'b', 'c'], '3': ['d', 'e', 'f'], '4': ['g', 'h', 'i'], '5': ['j', 'k', 'l'], '6': ['m', 'n', 'o'], '7': ['p', 'q', 'r', 's'], '8': ['t', 'u', 'v'], '9': ['w', 'x', 'y', 'z'], }

28.424242

65

0.410448

084d1fd01b6f648a85848dd0310b96b0d8966a0e

651

py

Python

yotta/options/registry.py

microbit-foundation/yotta

82d854b43d391abb5a006b05e7beffe7d0d6ffbf

[ "Apache-2.0" ]

176

2015-01-02T07:31:59.000Z

2022-03-21T12:40:02.000Z

yotta/options/registry.py

microbit-foundation/yotta

82d854b43d391abb5a006b05e7beffe7d0d6ffbf

[ "Apache-2.0" ]

549

2015-01-05T16:19:54.000Z

2021-01-15T13:46:42.000Z

yotta/options/registry.py

microbit-foundation/yotta

82d854b43d391abb5a006b05e7beffe7d0d6ffbf

[ "Apache-2.0" ]

84

2015-01-10T21:01:00.000Z

2022-03-24T16:04:42.000Z

27.125

70

0.680492

084edafd90972abf12ce9cf828ac494b0afdd467

4,453

py

Python

src/pybraingym/environment.py

anetczuk/pybraingym

4f930021d7802e88c75a1a0aed135dd4de66cc1b

[ "MIT" ]

null

src/pybraingym/environment.py

anetczuk/pybraingym

4f930021d7802e88c75a1a0aed135dd4de66cc1b

[ "MIT" ]

null

src/pybraingym/environment.py

anetczuk/pybraingym

4f930021d7802e88c75a1a0aed135dd4de66cc1b

[ "MIT" ]

null

# MIT License # # Copyright (c) 2019 Arkadiusz Netczuk <dev.arnet@gmail.com> # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in all # copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE # SOFTWARE. # from pybrain.rl.environments.environment import Environment from gym.spaces.discrete import Discrete def action(self, actionValue): """Transform action value received from PyBrain and pass result to OpenAi Gym.""" return actionValue def reward(self, rewardValue): """Transform reward value received from OpenAi Gym and pass result to PyBrain.""" return rewardValue

32.50365

104

0.651246

084eddbd29309d0a8c29e8b0baeae41ed4f83c9f

7,420

py

Python

logicscen.py

exposit/pythia-oracle

60e4e806c9ed1627f2649822ab1901d28933daac

[ "MIT" ]

32

2016-08-27T01:31:42.000Z

2022-03-21T08:59:28.000Z

logicscen.py

exposit/pythia-oracle

60e4e806c9ed1627f2649822ab1901d28933daac

[ "MIT" ]

3

2016-08-27T00:51:47.000Z

2019-08-26T13:23:04.000Z

logicscen.py

exposit/pythia-oracle

60e4e806c9ed1627f2649822ab1901d28933daac

[ "MIT" ]

10

2016-08-28T14:14:41.000Z

2021-03-18T03:24:22.000Z

#!/usr/bin/env python #-*- coding: utf-8 -*- #--------------------------------------------------------------------------------------------------- # --> Logic to handle scenarios #--------------------------------------------------------------------------------------------------- import imports from imports import * import config import logic from logic import *

27.279412

119

0.508491

0850f9781ec228546bf41eccc932a22fd036e4a8

7,980

py

Python

datyy/views/projects.py

VladimirSiv/datyy

4f3b54557850212ca3ce4c0d16cd56eb9989d7c4

[ "MIT" ]

null

datyy/views/projects.py

VladimirSiv/datyy

4f3b54557850212ca3ce4c0d16cd56eb9989d7c4

[ "MIT" ]

null

datyy/views/projects.py

VladimirSiv/datyy

4f3b54557850212ca3ce4c0d16cd56eb9989d7c4

[ "MIT" ]

null

import dash import dash_html_components as html import dash_bootstrap_components as dbc import numpy as np from server import app from dash.dependencies import Input, Output, State from dash.exceptions import PreventUpdate from components.cards import simple_info_card from components.dropdowns import dropdown_single from components.cards import project_info_card from components.tables import simple_table from components.gantts import simple_gantt_graph from logic.dropdowns import dropdown_single_logic from logic.tables import generate_project_tasks_data from logic.pie_charts import sunburst_chart_logic from logic.gantts import simple_gantt_logic layout = html.Div( children=[ html.Div(id="project-temp", style={"display": "none"}), dbc.Row( className="main-row", children=[ dbc.Col( dropdown_single( id_="project-select", placeholder="Select Project", text="Project:", ), width=3, ), ], ), dbc.Row( className="main-row", children=[ dbc.Col( simple_info_card( id_="project-card-planning", title="Planning", ) ), dbc.Col( simple_info_card( id_="project-card-design", title="Design", ) ), dbc.Col( simple_info_card( id_="project-card-development", title="Development", ) ), dbc.Col( simple_info_card( id_="project-card-testing", title="Testing", ) ), dbc.Col( simple_info_card( id_="project-card-cost", title="Cost", ) ), dbc.Col( simple_info_card( id_="project-card-duration", title="Duration", ) ), ], ), dbc.Row( className="main-row", children=[ dbc.Col( project_info_card( id_="budget-graph", title="Budget spending", subcomponents={ "project-budget": "Budget", "project-remaining": "Remaining", "project-currently": "Currently", }, ), width=6, ), dbc.Col( simple_table( id_="project-tasks-table", title="Overdue tasks", columns=[ "Overdue (days)", "Task", "Deadline", "Employee", ], ), width=6, ), ], ), html.Div( className="main-row", children=[html.H4("Milestones", className="title-bold")] ), dbc.Row( className="main-row", children=[dbc.Col(simple_gantt_graph(id_="project-gantt-graph"))], ), ] )

28.098592

90

0.52193

08540bf2ac8cadc1cf3900bd14a8f79f2ba8831e

146

py

Python

week-02/appendA.py

norbertbodo91/pythonExercises

9cd773c5d6ce3280d19a84ef12b8fd478ff09613

[ "MIT" ]

null

week-02/appendA.py

norbertbodo91/pythonExercises

9cd773c5d6ce3280d19a84ef12b8fd478ff09613

[ "MIT" ]

null

week-02/appendA.py

norbertbodo91/pythonExercises

9cd773c5d6ce3280d19a84ef12b8fd478ff09613

[ "MIT" ]

null

print(appendA(toAppend = raw_input("Enter a word to add an A letter: ")))

24.333333

73

0.684932

085550c02672da4291f033dfdf10337c089c2aa8

16,119

py

Python

multiacctcf.py

DonMills/multiacct-CF-orchestrate

4acce3c984c1801ff66cf9d210e3a0d1a6f9246b

[ "MIT" ]

11

2017-07-19T07:05:44.000Z

2022-02-07T19:35:51.000Z

multiacctcf.py

DonMills/multiacct-CF-orchestrate

4acce3c984c1801ff66cf9d210e3a0d1a6f9246b

[ "MIT" ]

null

multiacctcf.py

DonMills/multiacct-CF-orchestrate

4acce3c984c1801ff66cf9d210e3a0d1a6f9246b

[ "MIT" ]

2

2017-07-19T15:01:52.000Z

2022-02-07T19:35:53.000Z

#!/usr/bin/python from __future__ import print_function import threading import boto3 import botocore import argparse from time import ctime ############### # Some Global Vars ############## lock = threading.Lock() awsaccts = [{'acct': 'acct1ID', 'name': 'master', 'cffile': 'location of cloudformation file in S3'}, {'acct': 'acct2ID', 'name': 'dev', 'cffile': 'location of cloudformation file in S3'}, {'acct': 'acct3ID', 'name': 'staging', 'cffile': 'location of cloudformation file in S3'}, {'acct': 'acct4ID', 'name': 'test', 'cffile': 'location of cloudformation file in S3'}, {'acct': 'acct5ID', 'name': 'QA', 'cffile': 'location of cloudformation file in S3'}] ################################### # This results dict is prepopulated with the info for the master vpc in a region. It will be overwritten # if the master cloudform is run ################################### results = { 'master': { 'CIDRblock': '172.0.1.0/22', 'RTBint': [ 'rtb-xxxxxxxx', 'rtb-xxxxxxxx'], 'VPCID': 'vpc-xxxxxxxx'}} threads = [] ####################### # The function that does CloudFormation and peering requests ####################### if __name__ == '__main__': main()

39.70197

179

0.470749

085769a397608c592ac48390d3b4d6b67aae08eb

882

py

Python

NIM/tests/woa_test.py

buctlab/source-seeking-multi-robot-team-simulator

a68c214b9bd19006a94c0adc832681bbaf0d6dc8

[ "Apache-2.0" ]

null

NIM/tests/woa_test.py

buctlab/source-seeking-multi-robot-team-simulator

a68c214b9bd19006a94c0adc832681bbaf0d6dc8

[ "Apache-2.0" ]

null

NIM/tests/woa_test.py

buctlab/source-seeking-multi-robot-team-simulator

a68c214b9bd19006a94c0adc832681bbaf0d6dc8

[ "Apache-2.0" ]

null

import os from Config import Config from NIM.algorithms import WhaleOptimizationAlgorithm from NIM.algorithms.algorithm import logger if __name__ == '__main__': with open(Config.default_saved_scene_path, 'r') as f: data = f.read() m2d = eval(data) seed = 5 woa = WhaleOptimizationAlgorithm(m2d, Config.rasterized_cell_size, func=Config.func, iterations=Config.iterations, debug=True, population=Config.number_of_robots, robot_size=Config.size, seed=seed, k=Config.leakage_sources) best_sol, best_val = woa.run() logger.info("best sol:{sol}, best val:{val}".format(sol=best_sol, val=best_val)) func_name = type(woa.func).__name__ woa.iter_swarm_pos.to_csv( os.path.join(Config.project_root, "data/csv_file/woa_MultiSourceFunction_" + str(seed) + ".csv"))

36.75

119

0.675737

085893c679735b22d323d01a1e71583ba759cc3a

6,242

py

Python

src/COVIDZejunDatagraphs.py

luisflores0330/ista131final

168ac6afe666e945ae717387b50420804b33c4f3

[ "Apache-2.0" ]

null

src/COVIDZejunDatagraphs.py

luisflores0330/ista131final

168ac6afe666e945ae717387b50420804b33c4f3

[ "Apache-2.0" ]

null

src/COVIDZejunDatagraphs.py

luisflores0330/ista131final

168ac6afe666e945ae717387b50420804b33c4f3

[ "Apache-2.0" ]

4

2021-12-07T21:44:31.000Z

2021-12-07T23:20:04.000Z

''' File: COVIDZejunDatagraphs.py Author: Zejun Li Purpose: This file contains 12 different functions to make 5 different graphs about the COVID 19 in Idaho ''' import pandas as pd, numpy as np, matplotlib.pyplot as plt import matplotlib.dates as mdates import datetime import datetime as dt def get_df(): ''' This function is to get the dataframe from the csv file : data_table_for_daily_death_trends__idaho.csv ''' fname = "data_table_for_daily_death_trends__idaho.csv" df = pd.read_csv(fname,sep=',', skiprows = 2, engine='python') del df["State"] df["Dates"] = np.nan df['Dates'] = df['Date'].apply(date_convert) del df["Date"] return df def get_date_lst(): '''This function is to get all of the dates from the Dates column ''' df = get_df() lst_dates = [] for i in df['Dates']: lst_dates.append(i) return lst_dates def fig1(): '''This function is to make a line graph with x axis of Dates and y axis of Current Hospitalized COVID-19 Patients. ''' df = get_df() lst_dates = get_date_lst() x = [dt.datetime.strptime(d,'%m/%d/%Y').date() for d in lst_dates] plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%m/%d/%Y')) plt.gca().xaxis.set_major_locator(mdates.DayLocator(interval=50)) plt.plot(x,df['Current Hospitalized COVID-19 Patients']) plt.gcf().autofmt_xdate() plt.xlabel("Dates") plt.ylabel("Current Hospitalized COVID-19 Patients") plt.suptitle('Figure 1', fontsize=16) def fig2(): '''This function is to make a bar chart with x axis of Dates and y axis of New Deaths ''' df = get_df() lst_dates = get_date_lst() plt.figure(figsize=(10,10)) plt.style.use('ggplot') lst_dates = [] for i in df['Dates']: lst_dates.append(i) x = [dt.datetime.strptime(d,'%m/%d/%Y').date() for d in lst_dates] lst = [] for i in df['New Deaths']: lst.append(i) x_pos = [i for i, _ in enumerate(x)] plt.bar(x,lst,width=0.8, color='darkviolet') plt.xlabel("Dates") plt.ylabel("New Deaths") plt.suptitle('Figure 2', fontsize=16) def fig3(): '''This function is to make a scatter plot with x axis of Dates and y axis of 7-Day Moving Avg ''' df = get_df() plt.figure(figsize=(16,10), dpi= 80) lst_dates = get_date_lst() lst = [] for i in df["7-Day Moving Avg"]: lst.append(i) int_lst = [] for i in range(len(lst_dates)): int_lst.append(i) x = np.array(lst_dates) y = np.array(lst) x1 = np.array(int_lst) m, b = np.polyfit(x1, y, 1) plt.plot(x, m*x1 + b) plt.scatter(x, y) plt.gca().xaxis.set_major_locator(mdates.DayLocator(interval=50)) plt.xlabel("Dates") plt.ylabel("7-Day Moving Avg") plt.gca().invert_xaxis() plt.suptitle('Figure 3', fontsize=16) main() def csv(file): ''' This function is to get two dataframes from the csv file; df: data_table_for_daily_case_trends__idaho1.csv; df2:data_table_for_daily_death_trends__idaho2.csv ''' df = pd.read_csv(file, sep = ",", skiprows = 2) df2 = pd.read_csv("data_table_for_daily_death_trends__idaho2.csv", sep = "," , skiprows = 2) df["New Deaths"] = df2["New Deaths"] df["Doses Per Day"] = 0 df["Dates"] = df["Date"].replace({"Jan":"01", "Feb":"02","Mar":"03","Apr":"04","May":"05","Jun":"06","Jul":"07","Aug":"08","Sep":"09","Oct":"10","Nov":"11","Dec":"12"}, regex = True) df["Total Doses Administered"] = df["Total Doses Administered"].fillna(0) for i in range(1, len(df["Total Doses Administered"])-1): a = pd.to_numeric(df["Total Doses Administered"]) df.loc[i-1,"Doses Per Day"] = abs((int(a.iloc[i-1]) - int(a.iloc[i]))) a.append(df["Doses Per Day"]) df.drop(labels = [0], axis = 0) df.drop([0, 1, 2], axis = 0,inplace = True) del df["7-Day Moving Avg"] del df["State"] return df def clean_dose(): '''This function is to delete the dates that don't have dose ''' df = csv("data_table_for_daily_case_trends__idaho1.csv") for i in range(626,670): df = df.drop(index=i) return df def fig4(): '''This function is to make a line graph with x axis of Dates and y axis of New cases ''' df = csv("data_table_for_daily_case_trends__idaho1.csv") x = [dt.datetime.strptime(d,'%m %d %Y').date() for d in df["Dates"]] plt.gca().xaxis.set_major_formatter(mdates.DateFormatter('%m %d %Y')) plt.gca().xaxis.set_major_locator(mdates.DayLocator(interval=50)) plt.plot(x,df['New Cases']) plt.gcf().autofmt_xdate() plt.xlabel("Dates") plt.ylabel("New Cases") plt.suptitle('Figure 4', fontsize=16) ''' def fig5(): df = csv("data_table_for_daily_case_trends__idaho1.csv") plt.figure(figsize=(10,10)) plt.style.use('ggplot') lst_dates = [] for i in df['Dates']: lst_dates.append(i) x = [dt.datetime.strptime(d,'%m %d %Y').date() for d in df["Dates"]] lst = [] for i in df['New Deaths']: lst.append(i) x_pos = [i for i, _ in enumerate(x)] plt.bar(x,lst,width=0.8, color='black') plt.xlabel("Dates") plt.ylabel("New Deaths") plt.suptitle('Figure 5', fontsize=16) ''' def fig5(): '''This function is to make a bar chart with x axis of Dates and y axis of Doses Per Day ''' df = clean_dose() plt.figure(figsize=(16,10), dpi= 80) lst = [] for i in df["Doses Per Day"]: lst.append(i) x = np.array(df["Dates"]) y = np.array(lst) plt.gca().xaxis.set_major_locator(mdates.DayLocator(interval=50)) plt.bar(x,lst,width=0.8, color='navy') plt.xlabel("Dates") plt.ylabel("Doses Per Day") plt.gca().invert_xaxis() plt.suptitle('Figure 5', fontsize=16) main2()

33.026455

187

0.603172

0858b5bc59305248e9f97a28c217e52f4157d9b4

1,118

py

Python

tests/test_pipeline_disk_deduplication.py

kingking888/skyscraper

d710202f9581c3791d2cf7ee3ae33e950e46c0b7

[ "MIT" ]

1

2021-03-21T07:25:43.000Z

tests/test_pipeline_disk_deduplication.py

kingking888/skyscraper

d710202f9581c3791d2cf7ee3ae33e950e46c0b7

[ "MIT" ]

null

tests/test_pipeline_disk_deduplication.py

kingking888/skyscraper

d710202f9581c3791d2cf7ee3ae33e950e46c0b7

[ "MIT" ]

1

2021-04-24T11:38:18.000Z

import pytest import json import datetime from scrapy.spiders import Spider import scrapy.exceptions from skyscraper.items import BasicItem from scrapy.exceptions import DropItem from skyscraper.pipelines.filesystem import DiskDeduplicationPipeline

24.304348

74

0.686047

08597f4873dfad388e0eb75f921c519b7373d12a

180

py

Python

windscribe/__init__.py

Dayzpd/Python-Windscribe

eaaca7b39286434ec8588c967076f0b5b9961d91

[ "MIT" ]

9

2020-09-17T19:42:18.000Z

2022-01-04T07:14:37.000Z

windscribe/__init__.py

Dayzpd/Python-Windscribe

eaaca7b39286434ec8588c967076f0b5b9961d91

[ "MIT" ]

4

2020-10-28T16:22:54.000Z

2022-01-04T07:13:18.000Z

windscribe/__init__.py

Dayzpd/Python-Windscribe

eaaca7b39286434ec8588c967076f0b5b9961d91

[ "MIT" ]

4

2020-12-11T11:13:27.000Z

2022-01-16T02:40:55.000Z

__all__ = [ 'account', 'connect', 'locations', 'login', 'logout', ] from .windscribe import ( account, connect, locations, login, logout, )

12

25

0.527778

085a588c3443a2133c8229f5612a92a5ee522cad

335

py

Python

src/videos/migrations/0009_rename_updated_timestamp_video_updated.py

imsubhamsingh/vibeon

5ea67bb8dae0a0c28d36f81374eb4f046d842cf5

[ "Apache-2.0" ]

null

src/videos/migrations/0009_rename_updated_timestamp_video_updated.py

imsubhamsingh/vibeon

5ea67bb8dae0a0c28d36f81374eb4f046d842cf5

[ "Apache-2.0" ]

2

2021-07-19T18:41:46.000Z

2022-02-10T11:43:07.000Z

src/videos/migrations/0009_rename_updated_timestamp_video_updated.py

imsubhamsingh/vibeon

5ea67bb8dae0a0c28d36f81374eb4f046d842cf5

[ "Apache-2.0" ]

null

# Generated by Django 3.2 on 2021-04-20 19:34 from django.db import migrations

22.333333

80

0.674627

085b597e5e9aaf7c138a4db4c8f8739331aa2a66

2,342

py

Python

SVM/SVM_Regression/Sklearn_SVM_Regression.py

Jojoxiao/Machine-Learning-for-Beginner-by-Python3

71b91c9cba5803bd78d4d31be6dabb1d3989e968

[ "MIT" ]

397

2018-05-28T02:07:32.000Z

2022-03-30T09:53:37.000Z

SVM/SVM_Regression/Sklearn_SVM_Regression.py

976634681/Machine-Learning-for-Beginner-by-Python3

d9effcbb1b390dc608a0f4c0a28f0ad03892047a

[ "MIT" ]

4

2019-01-14T16:41:02.000Z

2021-03-11T13:23:06.000Z

SVM/SVM_Regression/Sklearn_SVM_Regression.py

976634681/Machine-Learning-for-Beginner-by-Python3

d9effcbb1b390dc608a0f4c0a28f0ad03892047a

[ "MIT" ]

235

2018-06-28T05:31:40.000Z

2022-03-11T03:20:07.000Z

# -*- codingutf-8 -*- # &Author AnFany # Sklearn """ """ # PM2.5 import SVM_Regression_Data as rdata # from sklearn import svm import numpy as np import matplotlib.pyplot as plt from pylab import mpl mpl.rcParams['font.sans-serif'] = ['FangSong'] # mpl.rcParams['axes.unicode_minus'] = False # """ """ # # ''' linear, poly, rbf, sigmoid ''' # # '''''' if __name__ == "__main__": datasvr = rdata.model_data realtr, outtri, realpre, poupre = result(datasvr, he='rbf') huitu(realtr, outtri, c=['b', 'k'], sign='', cudu=1.5) huitu(realpre, poupre, c=['b', 'k'], sign='', cudu=1.5)

22.519231

101

0.557643

085b8a0758f970cf513eb9555d20e921de2dbc2f

1,655

py

Python

tests/test_history.py

dfroger/conda

c0f99ff46b217d081501e66f4dcd7bcdb5d9c6aa

[ "BSD-3-Clause" ]

null

tests/test_history.py

dfroger/conda

c0f99ff46b217d081501e66f4dcd7bcdb5d9c6aa

[ "BSD-3-Clause" ]

null

tests/test_history.py

dfroger/conda

c0f99ff46b217d081501e66f4dcd7bcdb5d9c6aa

[ "BSD-3-Clause" ]

null

from os.path import dirname import unittest from .decorators import skip_if_no_mock from .helpers import mock from conda import history

31.826923

73

0.590937

085dd2a204aa1776b398919049eef21372b1d7e4

107

py

Python

src/zojax/catalog/tests/__init__.py

Zojax/zojax.catalog

1be9ef2cd4516d6c1dcfe7da52c4d438852e7ea6

[ "ZPL-2.1" ]

null

src/zojax/catalog/tests/__init__.py

Zojax/zojax.catalog

1be9ef2cd4516d6c1dcfe7da52c4d438852e7ea6

[ "ZPL-2.1" ]

null

src/zojax/catalog/tests/__init__.py

Zojax/zojax.catalog

1be9ef2cd4516d6c1dcfe7da52c4d438852e7ea6

[ "ZPL-2.1" ]

null

# This file is necessary to make this directory a package. from zojax.catalog.catalog import queryCatalog

26.75

58

0.813084

085e0152d8a979274c20816965dae9f9c36f8c65

6,066

py

Python

src/bpp/views/raporty/ranking_autorow.py

iplweb/django-bpp

85f183a99d8d5027ae4772efac1e4a9f21675849

[ "BSD-3-Clause" ]

1

2017-04-27T19:50:02.000Z

src/bpp/views/raporty/ranking_autorow.py

mpasternak/django-bpp

434338821d5ad1aaee598f6327151aba0af66f5e

[ "BSD-3-Clause" ]

41

2019-11-07T00:07:02.000Z

2022-02-27T22:09:39.000Z

src/bpp/views/raporty/ranking_autorow.py

iplweb/bpp

f027415cc3faf1ca79082bf7bacd4be35b1a6fdf

[ "BSD-3-Clause" ]

null

# -*- encoding: utf-8 -*- import itertools try: from django.core.urlresolvers import reverse except ImportError: from django.urls import reverse from django.db.models.aggregates import Sum from django.template.defaultfilters import safe from django.utils.functional import cached_property from django_tables2 import Column from django_tables2.export.views import ExportMixin from django_tables2.tables import Table from django_tables2.views import SingleTableView from bpp.models import Autor, Sumy, OpcjaWyswietlaniaField, Uczelnia from bpp.models.struktura import Wydzial def get_dostepne_wydzialy(self): return Wydzial.objects.filter(zezwalaj_na_ranking_autorow=True) def get_wydzialy(self): base_query = self.get_dostepne_wydzialy() wydzialy = self.request.GET.getlist("wydzialy[]") if wydzialy: try: wydzialy = base_query.filter(pk__in=[int(x) for x in wydzialy]) return wydzialy except (TypeError, ValueError): pass return base_query def get_context_data(self, **kwargs): context = super(SingleTableView, self).get_context_data(**kwargs) context["od_roku"] = self.kwargs["od_roku"] context["do_roku"] = self.kwargs["do_roku"] jeden_rok = False if self.kwargs["od_roku"] == self.kwargs["do_roku"]: context["rok"] = self.kwargs["od_roku"] jeden_rok = True wydzialy = self.get_wydzialy() context["wydzialy"] = wydzialy if jeden_rok: context["table_title"] = "Ranking autorw za rok %s" % context["rok"] else: context["table_title"] = "Ranking autorw za lata %s - %s" % ( context["od_roku"], context["do_roku"], ) context["tab_subtitle"] = "" if len(wydzialy) != len(self.get_dostepne_wydzialy()): context["table_subtitle"] = ", ".join([x.nazwa for x in wydzialy]) return context def get_table_kwargs(self): uczelnia = Uczelnia.objects.all().first() pokazuj = uczelnia.pokazuj_liczbe_cytowan_w_rankingu if pokazuj == OpcjaWyswietlaniaField.POKAZUJ_NIGDY or ( pokazuj == OpcjaWyswietlaniaField.POKAZUJ_ZALOGOWANYM and self.request.user.is_anonymous ): return {"exclude": ("liczba_cytowan_sum",)} return {}

32.612903

88

0.616716

f22aabe1afa4a1593594ef47c8110872cb757c3c

16,701

py

Python

client-lib/pypi/nsrr/nsrr.py

nsrr/nsrr-cloud

a1e33bc3ba3220600e8b1973882d2ed76a7277c6

[ "MIT" ]

null

client-lib/pypi/nsrr/nsrr.py

nsrr/nsrr-cloud

a1e33bc3ba3220600e8b1973882d2ed76a7277c6

[ "MIT" ]

null

client-lib/pypi/nsrr/nsrr.py

nsrr/nsrr-cloud

a1e33bc3ba3220600e8b1973882d2ed76a7277c6

[ "MIT" ]

null

#!/usr/bin/python3 import requests from requests.structures import CaseInsensitiveDict import json import getpass from pathlib import Path import hashlib import pandas as pd import gzip from multiprocessing import Process # Global variables #API_SERVER='https://dev-cloud.sleepdata.org/api/v1' API_SERVER='https://cloud.sleepdata.org/api/v1' #API_SERVER='http://localhost:9002/api/v1' procs=[] all_decompress_edfz=[]

42.496183

163

0.598946

f22b087ab319568e891a7406ef151ad2f4d6b818

509

py

Python

assignment2.py

talsperre/random-walk

5c810f571c9de28926850e1ad70ff4c29df9c0f4

[ "MIT" ]

null

assignment2.py

talsperre/random-walk

5c810f571c9de28926850e1ad70ff4c29df9c0f4

[ "MIT" ]

null

assignment2.py

talsperre/random-walk

5c810f571c9de28926850e1ad70ff4c29df9c0f4

[ "MIT" ]

null

import numpy as np N = 100 R = 10000 R_range = range(R) size = (N, 3) C = np.zeros((N, 3)) k = 1 print ("100") print ("STEP: ", k) for i in range(N): print ("He ", C[i, 0], " ", C[i, 1], " ", C[i, 2]) k += 1 for j in range(R): A = np.random.uniform(-1, 1, size) B = np.sum(np.multiply(A, A), axis=1) B = np.sqrt(B) B = B.reshape(N, 1) Norm_A = A / B C += Norm_A if j % 10 == 0: print ("100") print ("STEP: ", k) for i in range(N): print ("He ", C[i, 0], " ", C[i, 1], " ", C[i, 2]) k += 1

18.851852

53

0.489194

f22fac0a3ced91e4e4e5768a9d363783d0f24bd3

1,462

py

Python

parallel/images_common.py

minrk/ipython-cse17

16a9059c7054a8bd4977a3cb8b09c100ea779069

[ "BSD-3-Clause" ]

3

2017-03-02T07:11:37.000Z

2017-03-03T06:13:32.000Z

parallel/images_common.py

minrk/ipython-cse17

16a9059c7054a8bd4977a3cb8b09c100ea779069

[ "BSD-3-Clause" ]

null

parallel/images_common.py

minrk/ipython-cse17

16a9059c7054a8bd4977a3cb8b09c100ea779069

[ "BSD-3-Clause" ]

null

import os import matplotlib.pyplot as plt from skimage.io import imread def plot_corners(img, corners, show=True): """Display the image and plot all contours found""" plt.imshow(img, cmap='gray') plt.plot(corners[:,1], corners[:,0], 'r+', markeredgewidth=1.5, markersize=8) # Plot corners plt.axis('image') plt.xticks([]) plt.yticks([]) if show: plt.show() def find_corners(path, min_distance=5): """Find corners in an image at path Returns the image and the corner lists. """ from skimage.feature import corner_harris, corner_peaks img = imread(path, flatten=True) corners = corner_peaks(corner_harris(img), min_distance=min_distance) return img, corners def get_corners_image(path): """Given a path, return a PNG of the image with contour lines Calls both find_contours and plot_contours """ from IPython.core.pylabtools import print_figure img, corners = find_corners(path) plot_corners(img, corners, show=False) fig = plt.gcf() pngdata = print_figure(fig) plt.close(fig) return pngdata def get_pictures(pictures_dir): """Return a list of picture files found in pictures_dir""" pictures = [] for directory, subdirs, files in os.walk(pictures_dir): for fname in files: if fname.lower().endswith(('.jpg', '.png')): pictures.append(os.path.join(directory, fname)) return pictures

29.24

96

0.666211

f23153ff9da39e77238d222d2874c0c47b3effe7

1,765

py

Python

tests/test_copies.py

mschmidtkorth/shallow-backup

6629fed7d5a3a13eb068c7ef0168cfa8ffbd3bbf

[ "MIT" ]

1

2021-07-25T19:26:47.000Z

tests/test_copies.py

mschmidtkorth/shallow-backup

6629fed7d5a3a13eb068c7ef0168cfa8ffbd3bbf

[ "MIT" ]

null

tests/test_copies.py

mschmidtkorth/shallow-backup

6629fed7d5a3a13eb068c7ef0168cfa8ffbd3bbf

[ "MIT" ]

null

import os import sys import pytest import shutil from .test_utils import setup_env_vars, unset_env_vars, BACKUP_DEST_DIR, FAKE_HOME_DIR, DIRS sys.path.insert(0, "../shallow_backup") from shallow_backup.utils import copy_dir_if_valid TEST_TEXT_FILE = os.path.join(FAKE_HOME_DIR, 'test-file.txt')

32.090909

94

0.65779

f2320f768e412bebfaa5c2e31eeb4a3c480eacaf

1,395

py

Python

loan/killeragent.py

Casper-Smet/LOAN

3aabf80cf4314bcba33779329fc6e4971b85e742

[ "MIT" ]

null

loan/killeragent.py

Casper-Smet/LOAN

3aabf80cf4314bcba33779329fc6e4971b85e742

[ "MIT" ]

null

loan/killeragent.py

Casper-Smet/LOAN

3aabf80cf4314bcba33779329fc6e4971b85e742

[ "MIT" ]

null

from collections import namedtuple import networkx as nx from mesa import Agent, Model

34.875

128

0.658065

f23235dddab2a9fffc993f7fe1be533663c51d2b

290

py

Python

src/calc.py

ceIery/epic7-speed-calculator

2f91e57117e2b6873772e6a703e47241570ab75f

[ "MIT" ]

null

src/calc.py

ceIery/epic7-speed-calculator

2f91e57117e2b6873772e6a703e47241570ab75f

[ "MIT" ]

null

src/calc.py

ceIery/epic7-speed-calculator

2f91e57117e2b6873772e6a703e47241570ab75f

[ "MIT" ]

null

""" Given a base speed value and a list of percentages, calculates the speed value for each percentage """

24.166667

78

0.662069

f2330e7134a6c2ae1cacee5b851dbdfec9f5f1d4

11,762

py

Python

src/magi/actions/base.py

personalrobotics/magipy

6f86d6938168f580f667cfc093cf7e9f218e2853

[ "BSD-3-Clause" ]

null

src/magi/actions/base.py

personalrobotics/magipy

6f86d6938168f580f667cfc093cf7e9f218e2853

[ "BSD-3-Clause" ]

1

2018-01-06T00:24:06.000Z

src/magi/actions/base.py

personalrobotics/magipy

6f86d6938168f580f667cfc093cf7e9f218e2853

[ "BSD-3-Clause" ]

null

"""Base classes, context managers, and exceptions for MAGI actions.""" from abc import ABCMeta, abstractmethod import logging from openravepy import KinBody, Robot LOGGER = logging.getLogger(__name__) LOGGER.setLevel(logging.INFO) class ExecutableSolution(object): """Abstract base class for executing post-processed solutions.""" __metaclass__ = ABCMeta def __init__(self, solution): """ @param solution: Solution that generated this ExecutableSolution """ self.solution = solution self.precondition = solution.precondition self.postcondition = solution.postcondition def to_key(obj): """ Return a tuple that uniquely identifies an object in an Environment. The output of this function can be passed to from_key to find the equivalent object in, potentially, a different OpenRAVE environment. @param obj: object in an OpenRAVE environment @return tuple that uniquely identifies the object """ if obj is None: return None elif isinstance(obj, (KinBody, Robot)): key = obj.GetName(), elif isinstance(obj, (KinBody.Joint, KinBody.Link)): key = obj.GetParent().GetName(), obj.GetName() elif isinstance(obj, Robot.Manipulator): key = obj.GetRobot().GetName(), obj.GetName() else: raise TypeError('Unknown type "{!s}".'.format(type(obj))) return (type(obj), ) + key def from_key(env, key): """ Return the object identified by the input key in an Environment. The input of this function is constructed by the to_key function. @param env: an OpenRAVE environment @param key: tuple that uniquely identifies the object @return object in the input OpenRAVE environment """ if key is None: return None obj_type = key[0] if issubclass(obj_type, (KinBody, Robot)): return env.GetKinBody(key[1]) elif issubclass(obj_type, KinBody.Joint): return env.GetKinBody(key[1]).GetJoint(key[2]) elif issubclass(obj_type, KinBody.Link): return env.GetKinBody(key[1]).GetLink(key[2]) elif issubclass(obj_type, Robot.Manipulator): return env.GetRobot(key[1]).GetManipulator(key[2]) else: raise TypeError('Unknown type "{!s}".'.format(obj_type))

32.672222

85

0.655841

f233b62fa43bf27f7df361b2d0940e083df21551

6,471

py

Python

src/core/python/core/io/od.py

railtoolkit/OpenLinTim

27eba8b6038946ce162e9f7bbc0bd23045029d51

[ "MIT" ]

null

src/core/python/core/io/od.py

railtoolkit/OpenLinTim

27eba8b6038946ce162e9f7bbc0bd23045029d51

[ "MIT" ]

null

src/core/python/core/io/od.py

railtoolkit/OpenLinTim

27eba8b6038946ce162e9f7bbc0bd23045029d51

[ "MIT" ]

null

from typing import List from core.exceptions.input_exceptions import (InputFormatException, InputTypeInconsistencyException) from core.model.graph import Graph from core.model.impl.fullOD import FullOD from core.model.impl.mapOD import MapOD from core.model.infrastructure import InfrastructureNode from core.model.od import OD, ODPair from core.io.csv import CsvReader, CsvWriter from core.model.ptn import Stop, Link from core.util.config import Config, default_config

44.020408

126

0.626642

f23575bb8b4e289c914a5be32dd736b94767c391

4,395

py

Python

kriging/_kriging.py

ERSSLE/ordinary_kriging

f983081e4f12b0bae03bd042a6f451c65dcb2759

[ "MIT" ]

3

2020-09-08T16:55:44.000Z

2021-12-04T15:35:07.000Z

kriging/_kriging.py

ERSSLE/ordinary_kriging

f983081e4f12b0bae03bd042a6f451c65dcb2759

[ "MIT" ]

null

kriging/_kriging.py

ERSSLE/ordinary_kriging

f983081e4f12b0bae03bd042a6f451c65dcb2759

[ "MIT" ]

2

2021-08-25T09:35:50.000Z

2021-12-07T08:19:11.000Z

# encoding: utf-8 """ Ordinary Kriging interpolation is a linear estimation of regionalized variables. It assumes that the data change into a normal distribution, and considers that the expected value of regionalized variable Z is unknown. The interpolation process is similar to the weighted sliding average, and the weight value is determined by spatial data analysis. """ import numpy as np from shapely.geometry import Polygon,Point,shape from shapely.geometry.multipolygon import MultiPolygon from shapely.prepared import prep def shape_shadow(xgrid,ygrid,mapdata): """ Mask processing. Parameters ---------- xgrid: grid coordinates of longitude. ygrid: grid coordinates of latitude. mapdata: array of map data. Return ------ np.ndarray: An array of Boolean types. """ newshp = Polygon() for shap in mapdata: newshp = newshp.union(shape({'type':'Polygon','coordinates':[shap]})) points = [] for xi,yi in zip(xgrid.ravel(),ygrid.ravel()): points.append(Point([xi,yi])) prep_newshp = prep(newshp) mask = [] for p in points: mask.append(bool(prep_newshp.contains(p)-1)) mask = np.array(mask).reshape(xgrid.shape) return mask def interpolate(xy,z,extension=1.2,point_counts=(100,100)): """ Interpolate through the Kriging class, and return the grid points of the longitude and latitude interpolation results Parameters ---------- xy: The latitude and longitude coordinates of a spatial data point. z: The latitude and longitude coordinates of a spatial data point. extension: The interpolating region is expanded to cover a wider area. point_counts: How many data points to interpolate, default is 100 * 100. """ kri = Kriging() kri.fit(xy,z) x_max,x_min,y_max,y_min = xy[:,0].max(),xy[:,0].min(),xy[:,1].max(),xy[:,1].min() p = (extension - 1.0)/2 x_s = x_min - (x_max-x_min)*p x_e = x_max + (x_max-x_min)*p y_s = y_min - (y_max-y_min)*p y_e = y_max + (y_max-y_min)*p xls = np.linspace(x_s,x_e,point_counts[0]) yls = np.linspace(y_s,y_e,point_counts[1]) xgrid,ygrid = np.meshgrid(xls,yls) xgridls,ygridls = xgrid.ravel(),ygrid.ravel() if len(xgridls) > 100000: # Consider memory limit loop handling. zgridls = np.array([]) for s,e in zip(np.arange(0,len(xgridls),100000)[:-1],np.arange(0,len(xgridls),100000)[1:]): zgridls = np.concatenate([zgridls,kri.predict(np.c_[xgridls[s:e],ygridls[s:e]])]) if e < len(xgridls): zgridls = np.concatenate([zgridls,kri.predict(np.c_[xgridls[e:],ygridls[e:]])]) else: zgridls = kri.predict(np.c_[xgridls,ygridls]) zgrid = zgridls.reshape(xgrid.shape) return xgrid,ygrid,zgrid

35.731707

100

0.597952

f236ea30d7814e6e5f7e36351bc7667f7fad4f04

125

py

Python

steam/utils/__init__.py

ivicel/steamkit-python

0a3f250e432cf890965db5e7245841aa512bca22

[ "Apache-2.0" ]

5

2018-11-16T08:59:41.000Z

2021-04-03T05:32:18.000Z

steam/utils/__init__.py

ivicel/steamkit-python

0a3f250e432cf890965db5e7245841aa512bca22

[ "Apache-2.0" ]

null

steam/utils/__init__.py

ivicel/steamkit-python

0a3f250e432cf890965db5e7245841aa512bca22

[ "Apache-2.0" ]

null

from .util import clear_proto_mask, is_proto_msg, add_proto_mask __all__ = [clear_proto_mask, is_proto_msg, add_proto_mask]

31.25

64

0.84

f2377bda1f457053d6b4f86097a8d1ba0041422b

260

py

Python

src/arm/src/iksolverservicetester.py

Busboombot/ros_idx6dof

63b3a49393ab2c619b6b56c634cd440ab9b464ef

[ "MIT" ]

1

2020-03-15T15:30:43.000Z

src/arm/src/iksolverservicetester.py

Busboombot/ros_idx6dof

63b3a49393ab2c619b6b56c634cd440ab9b464ef

[ "MIT" ]

null

src/arm/src/iksolverservicetester.py

Busboombot/ros_idx6dof

63b3a49393ab2c619b6b56c634cd440ab9b464ef

[ "MIT" ]

null

#!/usr/bin/python import rospy from arm.srv import IKService, IKServiceResponse rospy.init_node("asdf", anonymous=True) rospy.wait_for_service('IKService') srv = rospy.ServiceProxy('IKService', IKService) resp = srv([5, 16, 8, 0, 0, 0], None) print resp

17.333333

48

0.734615

f23806bdb5c4b2e6ddeae98b2f41f0141fe5c5b9

1,410

py

Python

crypto-scrapers/scrapers/spiders/coin_market_cap.py

chnsh/crypto-index-fund

6c4122b868372ba99aba4f703e85d8ee12af07de

[ "MIT" ]

14

2018-05-27T19:34:59.000Z

2022-02-09T12:02:38.000Z

crypto-scrapers/scrapers/spiders/coin_market_cap.py

chnsh/crypto-index-fund

6c4122b868372ba99aba4f703e85d8ee12af07de

[ "MIT" ]

4

2018-05-28T02:44:07.000Z

2022-03-02T14:55:20.000Z

crypto-scrapers/scrapers/spiders/coin_market_cap.py

chnsh/crypto-index-fund

6c4122b868372ba99aba4f703e85d8ee12af07de

[ "MIT" ]

1

2022-03-07T05:26:47.000Z

from datetime import datetime from locale import * import scrapy from injector import Injector from scrapers.items import CoinMarketCapItem from scrapers.utils import UrlListGenerator setlocale(LC_NUMERIC, '')

33.571429

76

0.565248

f23af2303a08de830f84db88bf6e00cef4e25589

4,361

py

Python

crawler/cli.py

NicolasLM/crawler

15ed6441fef3b68bfadc970f597271191fe66cf8

[ "MIT" ]

null

crawler/cli.py

NicolasLM/crawler

15ed6441fef3b68bfadc970f597271191fe66cf8

[ "MIT" ]

null

crawler/cli.py

NicolasLM/crawler

15ed6441fef3b68bfadc970f597271191fe66cf8

[ "MIT" ]

null

from collections import OrderedDict from urllib.parse import urlparse import click import rethinkdb as r import redis import crawler.conf as conf # cli does not need to be thread-safe conn = r.connect(host=conf.RethinkDBConf.HOST, db=conf.RethinkDBConf.DB) domains = r.table('domains') def top(kind, count, data): top = OrderedDict(sorted(data.items(), key=lambda t: -t[1])) i = 1 click.secho('Top {} {}'.format(count, kind), bold=True) for value, occurences in top.items(): if not value: continue click.echo('{:>15} {}'.format(value, occurences)) i += 1 if i > count: break

33.806202

79

0.64022

f23b010b735f63cc59ac899de4d7a1e041082294

9,667

py

Python

run.py

keyunluo/Pytorch-DDP

ff91affdd2c4cebe1719e9a46f118405c308fd1f

[ "Apache-2.0" ]

null

run.py

keyunluo/Pytorch-DDP

ff91affdd2c4cebe1719e9a46f118405c308fd1f

[ "Apache-2.0" ]

null

run.py

keyunluo/Pytorch-DDP

ff91affdd2c4cebe1719e9a46f118405c308fd1f

[ "Apache-2.0" ]

null

# -8*- coding: utf-8 -*- import torch import torch.nn as nn import torch.optim as optim import torch.multiprocessing as mp import torch.backends.cudnn as cudnn from torch.utils.data import DataLoader, Dataset from torch.nn.parallel import DistributedDataParallel from torch.utils.data.distributed import DistributedSampler import argparse, random, time, os import numpy as np def parameter_parser(): parser = argparse.ArgumentParser(description="Run Model") parser.add_argument("--seq_len", type=int, default=512, help="max sequence length") parser.add_argument("--ip", type=str, default="localhost", help="ip address") parser.add_argument("--port", type=str, default=str(random.randint(20000, 30000)), help="port num") parser.add_argument("--cuda_devices", type=int, nargs='+', default=list(range(torch.cuda.device_count())), help="cuda devices") parser.add_argument("--mode", type=str, choices=["train", "eval"], help="train or eval") parser.add_argument("--num_worker", type=int, default=8, help="number of data loader worker") parser.add_argument("--batch_size", type=int, default=32, help="batch size") parser.add_argument("--epoch", type=int, default=5, help="num epoch") parser.add_argument("--max_norm", type=int, default=30, help="max norm value") return parser.parse_args() def set_manual_seed(seed): np.random.seed(seed) torch.manual_seed(seed) random.seed(seed) cudnn.benchmark = False cudnn.deterministic = True def dist_init(ip, rank, local_rank, world_size, port): """ initialize data distributed """ host_addr_full = 'tcp://' + ip + ':' + str(port) torch.distributed.init_process_group("nccl", init_method=host_addr_full, rank=rank, world_size=world_size) torch.cuda.set_device(local_rank) assert torch.distributed.is_initialized() def init_weights(module): if isinstance(module, nn.Linear): nn.init.xavier_uniform_(module.weight.data) nn.init.constant_(module.bias.data, 0.0) elif isinstance(module, nn.LSTM): nn.init.xavier_uniform_(module.weight_ih_l0.data) nn.init.orthogonal_(module.weight_hh_l0.data) nn.init.constant_(module.bias_ih_l0.data, 0.0) nn.init.constant_(module.bias_hh_l0.data, 0.0) hidden_size = module.bias_hh_l0.data.shape[0] // 4 module.bias_hh_l0.data[hidden_size:(2*hidden_size)] = 1.0 if module.bidirectional: nn.init.xavier_uniform_(module.weight_ih_l0_reverse.data) nn.init.orthogonal_(module.weight_hh_l0_reverse.data) nn.init.constant_(module.bias_ih_l0_reverse.data, 0.0) nn.init.constant_(module.bias_hh_l0_reverse.data, 0.0) module.bias_hh_l0_reverse.data[hidden_size:( 2*hidden_size)] = 1.0 if __name__ == '__main__': args = parameter_parser() if args.mode == "train": trainer()

39.618852

150

0.602359

f23c95d3f1d786e4a9f7ff9ea7ec7de8d8f85605

373

py

Python

newsletter/urls.py

vallka/djellifique

fb84fba6be413f9d38276d89ae84aeaff761218f

[ "MIT" ]

null

newsletter/urls.py

vallka/djellifique

fb84fba6be413f9d38276d89ae84aeaff761218f

[ "MIT" ]

null

newsletter/urls.py

vallka/djellifique

fb84fba6be413f9d38276d89ae84aeaff761218f

[ "MIT" ]

null

from django.urls import path from .views import * app_name = 'newsletter' urlpatterns = [ path('pixel/', my_image, name='pixel'), path('click/<str:uuid>/', click_redirect, name='click'), path('notification/', notification, name='notification'), path('sendtest/<str:slug>', sendtest, name='sendtest'), path('stats/<str:slug>', stats, name='stats'), ]

26.642857

61

0.659517

f23e9e3046350977154c8ce79c350de302fd2dce

197

py

Python

04_While/Step03/gamjapark.py

StudyForCoding/BEAKJOON

84e1c5e463255e919ccf6b6a782978c205420dbf

[ "MIT" ]

null

04_While/Step03/gamjapark.py

StudyForCoding/BEAKJOON

84e1c5e463255e919ccf6b6a782978c205420dbf

[ "MIT" ]

3

2020-11-04T05:38:53.000Z

2021-03-02T02:15:19.000Z

04_While/Step03/gamjapark.py

StudyForCoding/BEAKJOON

84e1c5e463255e919ccf6b6a782978c205420dbf

[ "MIT" ]

null

n = int(input()) temp_n = n k=0 while True: a = int(temp_n / 10) b = temp_n % 10 c = (a + b) % 10 new = b*10 + c k += 1 if new == n: break temp_n = new print(k)

14.071429

24

0.446701

f23ec17cf55792ab6ef9150b36b5c3e6f5471fbb

6,491

py

Python

vesc_driver/src/mathdir/cubic_spline_planner.py

Taek-16/vesc_study

c4f8e56a2530b17622ca73e9eba57830a1b51ad9

[ "Apache-2.0" ]

1

2021-02-13T10:48:13.000Z

vesc_driver/src/mathdir/cubic_spline_planner.py

Taek-16/vesc_study

c4f8e56a2530b17622ca73e9eba57830a1b51ad9

[ "Apache-2.0" ]

null

vesc_driver/src/mathdir/cubic_spline_planner.py

Taek-16/vesc_study

c4f8e56a2530b17622ca73e9eba57830a1b51ad9

[ "Apache-2.0" ]

null

#!/usr/bin/env python """ cubic spline planner Author: Atsushi Sakai """ import math import numpy as np import bisect from scipy.spatial import distance def calc_spline_course(x, y, ds=0.1): sp = Spline2D(x, y) s = list(np.arange(0, sp.s[-1], ds)) rx, ry, ryaw, rk, rdk = [], [], [], [], [] for i_s in s: ix, iy = sp.calc_position(i_s) rx.append(ix) ry.append(iy) ryaw.append(sp.calc_yaw(i_s)) rk.append(sp.calc_curvature(i_s)) rdk.append(sp.calc_d_curvature(i_s)) return rx, ry, ryaw, rk, rdk, s def main(): print("Spline 2D test") import matplotlib.pyplot as plt import numpy as np manhae1 = np.load(file='/home/menguiin/catkin_ws/src/macaron_2/path/K-CITY-garage-1m.npy') x = manhae1[0:manhae1.shape[0]-1, 0] y = manhae1[0:manhae1.shape[0]-1, 1] rx, ry, ryaw, rk, rdk, s = calc_spline_course(x, y) s = np.array(s) flg, ax = plt.subplots(1) plt.plot(range(-s.shape[0],s.shape[0],2),s, "s", label="s-value") plt.grid(True) plt.axis("equal") plt.xlabel("index") plt.ylabel("sval") plt.legend() flg, ax = plt.subplots(1) plt.plot(x, y, "xb", label="input") plt.plot(rx, ry, "-r", label="spline") plt.grid(True) plt.axis("equal") plt.xlabel("x[m]") plt.ylabel("y[m]") plt.legend() flg, ax = plt.subplots(1) plt.plot(s, [math.degrees(iyaw) for iyaw in ryaw], "or", label="yaw") plt.grid(True) plt.legend() plt.xlabel("line length[m]") plt.ylabel("yaw angle[deg]") flg, ax = plt.subplots(1) plt.plot(s, rk, "-r", label="curvature") plt.grid(True) plt.legend() plt.xlabel("line length[m]") plt.ylabel("curvature [1/m]") plt.show() if __name__ == '__main__': main()

24.130112

131

0.475582

f23ec9a0fbd46e6d9b5f8659349c47ab52aec354

333

py

Python

bbtest/steps/appliance_steps.py

jancajthaml-openbank/e2e

a2ef84b6564022e95de76438fc795e2ef927aa2b

[ "Apache-2.0" ]

null

bbtest/steps/appliance_steps.py

jancajthaml-openbank/e2e

a2ef84b6564022e95de76438fc795e2ef927aa2b

[ "Apache-2.0" ]

30

2018-03-18T05:58:32.000Z

2022-01-19T23:21:31.000Z

bbtest/steps/appliance_steps.py

jancajthaml-openbank/e2e

a2ef84b6564022e95de76438fc795e2ef927aa2b

[ "Apache-2.0" ]

null

#!/usr/bin/env python3 # -*- coding: utf-8 -*- from behave import * from helpers.eventually import eventually

23.785714

82

0.744745

f23fb929e898694417f38446747b98726264f0e7

1,211

py

Python

irkshop/urls.py

Beomi/irkshop

c109a62216cb6550add64fbf402883debc5011d1

[ "Apache-2.0" ]

19

2016-11-06T10:28:14.000Z

2020-11-01T02:04:51.000Z

irkshop/urls.py

Beomi/irkshop

c109a62216cb6550add64fbf402883debc5011d1

[ "Apache-2.0" ]

17

2016-10-19T11:58:48.000Z

2022-01-13T00:32:34.000Z

irkshop/urls.py

Beomi/irkshop

c109a62216cb6550add64fbf402883debc5011d1

[ "Apache-2.0" ]

4

2016-11-06T10:54:26.000Z

2019-08-31T16:08:56.000Z

from django.conf.urls import url, include from django.contrib import admin from django.contrib.auth.views import login, logout from django.conf import settings from django.views.static import serve from django.views.generic import TemplateView urlpatterns = [ url(r'^admin/', admin.site.urls), url(r'^accounts/login/$', login, {'template_name': 'login_page/login.html'}, name='login'), url(r'^accounts/logout/$', logout, name='logout'), url('', include('social_django.urls', namespace='social')), # . url(r'^ckeditor/', include('ckeditor_uploader.urls')), url(r'^ht/', include('health_check.urls')), url(r'^paypal/', include('paypal.standard.ipn.urls')), url(r'^shop/', include('goods.urls', namespace='shop')), url(r'^$', TemplateView.as_view(template_name='index.html')), ] if settings.DEBUG: import debug_toolbar from django.conf.urls.static import static urlpatterns += [ url(r'^__debug__/', include(debug_toolbar.urls)), url(r'^uploads/(?P<path>.*)$', serve, {'document_root': settings.MEDIA_ROOT}), ] + static(settings.STATIC_URL, document_root=settings.STATIC_ROOT)

41.758621

101

0.663088

f240eb401196f0b66c32fe422e4a7253f5e5528f

1,469

py

Python

mojave_setup/fonts.py

RuchirChawdhry/macOS-Mojave-Setup

5e61fe8c20abc42e63fcbd1c7e310aab8cc02a1c

[ "MIT" ]

null

mojave_setup/fonts.py

RuchirChawdhry/macOS-Mojave-Setup

5e61fe8c20abc42e63fcbd1c7e310aab8cc02a1c

[ "MIT" ]

null

mojave_setup/fonts.py

RuchirChawdhry/macOS-Mojave-Setup

5e61fe8c20abc42e63fcbd1c7e310aab8cc02a1c

[ "MIT" ]

null

#!/usr/bin/env python3 # -*- coding: utf-8 -*- import subprocess as sp

22.953125

80

0.479238

f2414f0188cf0460b22148b0732eea50d4b58390

5,142

py

Python

plag/urls.py

neetu6860/plagiarism-detection-software

7f05210aafdccf33a2bc732a40348eff43f46fba

[ "MIT" ]

19

2018-09-03T09:10:20.000Z

2021-12-24T13:52:18.000Z

plag/urls.py

neetu6860/plagiarism-detection-software

7f05210aafdccf33a2bc732a40348eff43f46fba

[ "MIT" ]

3

2019-10-31T18:42:38.000Z

2021-06-10T21:37:23.000Z

plag/urls.py

neetu6860/plagiarism-detection-software

7f05210aafdccf33a2bc732a40348eff43f46fba

[ "MIT" ]

16

2018-06-06T15:04:59.000Z

2022-03-29T04:53:07.000Z

from django.conf.urls import patterns, url from django.contrib import admin from django.contrib.auth.decorators import login_required from django.views.generic import TemplateView admin.autodiscover() from plag import views, const urlpatterns = patterns('', url(r'^$', views.IndexView.as_view(), name='index'), url(r'^index-trial/$', views.IndexTrialView.as_view(), name='index_trial'), url(r'^download/(?P<prot_res_id>\d+)$', views.download_file, name='download'), url(r'^products/$', TemplateView.as_view(template_name='plag/static/products.html'), name='products'), url(r'^features-screenshots/$', TemplateView.as_view(template_name='plag/static/features_and_screenshots.html'), name='features'), url(r'^url-protection/$', TemplateView.as_view(template_name='plag/static/url_protection.html'), name='url_prot'), url(r'^document-protection/$', TemplateView.as_view(template_name='plag/static/doc_protection.html'), name='doc_prot'), url(r'^pricing/$', TemplateView.as_view(template_name='plag/static/pricing.html'), name='pricing'), url(r'^risks-of-plagiarism/$', TemplateView.as_view(template_name='plag/static/risks_of_plagiarism.html'), name='risks_plag'), url(r'^about-us/$', TemplateView.as_view(template_name='plag/static/about.html'), name='about'), url(r'^our-customers/$', TemplateView.as_view(template_name='plag/static/our_customers.html'), name='our_customers'), url(r'^contact-us/$', TemplateView.as_view(template_name='plag/static/contact_us.html'), name='contact'), url(r'^order/$', views.OrderView.as_view(), name='order'), url(r'^ajax/username-check/$', views.username_unique, name='ajax_username_unique'), url(r'^account/$', views.account, name='account'), url(r'^account/profile/$', login_required(views.ProfileView.as_view()), name='profile'), url(r'^account/invoice/(?P<pk>\d+)$', views.invoice, name='invoice'), url(r'^account/invoice/pay/(?P<pk>\d+)$', views.pay_invoice, name='pay_invoice'), url(r'^account/invoice/subscribe/(?P<pk>\d+)$', views.subscribe_invoice, name='subscribe_invoice'), url(r'^ipn-endpoint/$', views.ipn, name='ipn'), url(r'^account/recent-scans/$', views.recent_scans, name='recent_scans_default'), url(r'^account/recent-scans/(?P<num_days>\d+)$', views.recent_scans, name='recent_scans'), url(r'^account/recent-scans/(?P<num_days>\d+)/(?P<hide_zero>hide-zero)$', views.recent_scans, name='recent_scans_hide_zero'), url(r'^account/scan-history/$', views.scan_history, name='scan_history'), url(r'^account/scan-history/(?P<hide_zero>hide-zero)$', views.scan_history, name='scan_history_hide_zero'), url(r'^ajax/plag-results/$', views.plagiarism_results, name='ajax_plag_results_default'), url(r'^ajax/plag-results/(?P<scan_id>\d+)$', views.plagiarism_results, name='plag_results'), url(r'^ajax/sitemap/$', views.sitemap_to_urls, name='ajax_urls'), url(r'^account/protected-resources/$', login_required(views.ProtectedResources.as_view()), name='protected_resources'), url(r'^sitemap/$', TemplateView.as_view(template_name='plag/static/sitemap.html'), name='sitemap'), url(r'^terms-of-service/$', TemplateView.as_view(template_name='plag/static/terms_of_service.html'), name='terms_of_service'), url(r'^privacy-policy/$', TemplateView.as_view(template_name='plag/static/privacy_policy.html'), name='privacy_policy'), # TODO Remove url(r'^data-cleanse/$', views.data_cleanse, name='data_cleanse'), url(r'^copyright/$', TemplateView.as_view(template_name='plag/static/copyright.html'), name='copyright'), url(r'^login/$', 'django.contrib.auth.views.login', {'template_name': 'plag/static/login_error.html'}), url(r'^logout/$', 'django.contrib.auth.views.logout', {'next_page': 'index'}, name='logout'), )

57.775281

119

0.532283

f242795159bdd7a9675c51d4615c5d8382e738be

2,419

py

Python

coinut.py

DanHenry4/AutoCoinut

f7c79f19a9193bc7c1193712088ca836b030f523

[ "MIT" ]

4

2016-05-08T02:15:50.000Z

2020-07-01T08:16:45.000Z

coinut.py

DanHenry4/AutoCoinut

f7c79f19a9193bc7c1193712088ca836b030f523

[ "MIT" ]

null

coinut.py

DanHenry4/AutoCoinut

f7c79f19a9193bc7c1193712088ca836b030f523

[ "MIT" ]

null

import hmac import hashlib import json import uuid import httplib2 COINUT_URL = 'https://coinut.com/api/'

27.488636

76

0.574618

f2430c615c25842a6a15c7289e5e98e1e77f49ce

1,817

py

Python

src/neighborly/core/residence.py

ShiJbey/neighborly

5af1e3211f1ef0e25803790850e7cd3d3a49be69

[ "MIT" ]

null

src/neighborly/core/residence.py

ShiJbey/neighborly

5af1e3211f1ef0e25803790850e7cd3d3a49be69

[ "MIT" ]

null

src/neighborly/core/residence.py

ShiJbey/neighborly

5af1e3211f1ef0e25803790850e7cd3d3a49be69

[ "MIT" ]

null

from typing import Any, Dict from ordered_set import OrderedSet from neighborly.core.ecs import Component from neighborly.core.engine import AbstractFactory, ComponentDefinition

32.446429

85

0.63071

f2439cb603c2e5bb9b0700a3b097f6415267d55a

15,518

py

Python

tests/SBHRun_Environment.py

SD2E/synbiohub_adapter

492f9ef1054b17d790654310b895bb7ad155808e

[ "MIT" ]

1

2019-10-08T20:31:16.000Z

tests/SBHRun_Environment.py

SD2E/synbiohub_adapter

492f9ef1054b17d790654310b895bb7ad155808e

[ "MIT" ]

84

2018-03-06T16:02:30.000Z

2020-09-01T18:17:54.000Z

tests/SBHRun_Environment.py

SD2E/synbiohub_adapter

492f9ef1054b17d790654310b895bb7ad155808e

[ "MIT" ]

1

2019-02-06T17:17:54.000Z

import threading import time import pandas as pd import numpy as np import matplotlib.cm as cm import matplotlib.pyplot as plt import os import fnmatch import random import re import getpass import sys from rdflib import Graph from synbiohub_adapter.SynBioHubUtil import * from sbol import * """ This class will perform unit testing to query information from SynBioHub's instances. Installation Requirement(s): - This test environment requires two third party packages to display plot: 1. pip install pandas 2. python -mpip install -U matplotlib To run this python file, enter in the following command from the synbiohub_adapter directory: python -m tests.SBHRun_Environment author(s) :Tramy Nguyen """ def get_uniqueID(idPrefix): """Generates a unique id """ t = time.ctime() uid = '_'.join([idPrefix, t]) return re.sub(r'[: ]', '_', uid) def create_sbolDocs(numDocs, idPrefix, sbolFile): """Returns a list of SBOL Documents numDocs: An integer value to indicate how many SBOL documents this method should create idPrefix: A unique id prefix to set each SBOL document sbolFile: the SBOL file to create an SBOL document from """ sbolDoc_List = [] sbolTriples = [] u_counter = 0 for i in range(0, numDocs): uid = get_uniqueID(idPrefix + "_d" + str(i)) trip_obj = SBOLTriple(sbolFile, uid) sbolTriples.append(trip_obj) sbolDoc_List.append(trip_obj.sbolDoc()) print("created doc%s" % i) return sbolDoc_List, sbolTriples def get_randomFile(sbolFiles): """Returns the full path of a randomly selected SBOL file found in the given directory dirLocation: The directory to select a random SBOL file from """ selectedFile = random.choice(sbolFiles) return selectedFile def get_sbolList(dirLocation): """Returns a list of xml file found in the given directory """ for root, dir, files in os.walk(dirLocation): sbolFiles = [os.path.abspath(os.path.join(root, fileName)) for fileName in files] return sbolFiles def push_sbh(sbolDoc, sbh_connector): """Returns the time (seconds) it takes to make a push to a new Collection on SynBioHub sbh_connector: An instance of pySBOL's PartShop needed to perform login for pushing and pulling data to and from SynBioHub sbolURI: The URI of the SynBioHub collection or the specific part to be fetched """ start = time.clock() result = sbh_connector.submit(sbolDoc) end = time.clock() print(result) if result != 'Successfully uploaded': sys.exit() return end - start def pull_sbh(sbh_connector, sbolURI): """Returns the time (seconds) it takes to make a pull from an existing SynBioHub Collection sbh_connector: An instance of pySBOL's PartShop needed to perform login for pushing and pulling data to and from SynBioHub sbolURI: The URI of the SynBioHub collection or the specific part to be fetched """ sbolDoc = Document() setHomespace("https://bbn.com") start = time.clock() sbh_connector.pull(sbolURI, sbolDoc) end = time.clock() if sbolDoc is None: print("Found nothing and caused no error.") else: experimentalData_tl = [] for tl in sbolDoc: if topLevel.type == 'http://sd2e.org#ExperimentalData': experimentalData_tl.append(topLevel) if len(experimentalData_tl) != 74: print("Found the wrong SynBioHub Part with this uri: %s" % sbolURI) return end - start if __name__ == '__main__': server_name = "https://synbiohub.bbn.com" print("Logging into: " + server_name) sbh_connector = PartShop(server_name) sbh_user = input('Enter Username: ') sbh_connector.login(sbh_user, getpass.getpass(prompt='Enter SynBioHub Password: ', stream=sys.stderr)) # Config.setOption("verbose", True) # sbolFiles = get_sbolList("./examples/workingFiles") sbolFiles = ["./examples/c_trips40000.xml"] iterations = 1 sbolDoc_size = 1 br_speed(sbh_connector, sbolDoc_size, sbolFiles) # br_triples(sbh_connector, iterations, sbolFiles) # iterations, set_size=10, t_growthRate=5, sbolDoc_size=100 # TODO: MAKE SURE TO CHANGE COLOR OF BAR GRAPH TO MAKE IT LOOK COOL... # br_setThread(sbh_connector, 3, 5, 3, 50, sbolFiles)

33.661605

110

0.660974

f245528c941762eda827c561627c5aa634c97c9f

2,842

py

Python

setup.py

Unidata/drilsdown

55aca7168fb390f31c36729605401564e9b82c56

[ "MIT" ]

3

2018-05-25T00:19:12.000Z

2021-01-08T15:54:36.000Z

setup.py

suvarchal/drilsdown

e82f58396f640fef847353caf1bd4b2bf016c7a6

[ "MIT" ]

11

2017-10-31T20:15:24.000Z

2019-12-16T21:01:55.000Z

setup.py

suvarchal/drilsdown

e82f58396f640fef847353caf1bd4b2bf016c7a6

[ "MIT" ]

10

2018-02-08T22:23:28.000Z

2019-09-29T23:25:19.000Z

import os from six import iteritems from setuptools import setup from setuptools.command.develop import develop from setuptools.command.install import install import subprocess PACKAGE_NAME = 'drilsdown' SOURCES = { 'ipython_IDV': 'projects/ipython_IDV', 'idv_teleport': 'projects/IDV_teleport', 'ramadda_publish': 'projects/RAMADDA_publish', } VERSION = '2.4.91' def install_drilsdown_projects(sources, develop=False): """ Use pip to install all drilsdown projects. """ print("installing all drilsdown projects in {} mode".format( "development" if develop else "normal")) wd = os.getcwd() for k, v in iteritems(sources): try: os.chdir(os.path.join(wd, v)) if develop: subprocess.check_call(['pip', 'install', '-e', '.']) # could be pip3 on certain platforms else: subprocess.check_call(['pip', 'install', '.']) # could be pip3 on certain platforms except Exception as e: print("Oops, something went wrong installing", k) print(e) finally: os.chdir(wd) setup( name=PACKAGE_NAME, version=VERSION, author="Drilsdown team", author_email="drilsdown@unidata.ucar.edu", description="A collection of tools for jupyter notebooks", long_description_content_type='text/markdown', long_description=open('README.md').read(), url="https://github.com/Unidata/drilsdown", license="MIT", classifiers=[ 'Programming Language :: Python :: 2.7', 'Programming Language :: Python :: 3.4', 'Programming Language :: Python :: 3.5', 'Programming Language :: Python :: 3.6', ], install_requires=[ 'future', 'six', 'requests', 'ipython', 'ipywidgets>=7.1.0rc', 'jupyter-client', # 'ipython_IDV>=' + VERSION + "'", # cannot be source and a dependency?? 'ipython-IDV', # from pypi 'ramadda_publish', #from pypi 'idv_teleport', #from pypi ], cmdclass={ #'install': InstallCmd, # do not overwrite for now to make # pip install and python setup.py install do same. # note in class pip might be called pip3 on certain platforms 'develop': DevelopCmd, }, extras_require={ 'addons': ['numpy','netcdf4','xarray','metpy'], 'visual': ['pyviz','geoviews'], } )

32.295455

105

0.60943

f24567e433386b2908e8d4a58f10fb0b2a6b3b98

2,129

py

Python

ejercicios/Ejercicio6.py

Xavitheforce/Ejercicios_Iteracion

e840439e1277b5946592128d5c771d895c2fac2c

[ "Apache-2.0" ]

null

ejercicios/Ejercicio6.py

Xavitheforce/Ejercicios_Iteracion

e840439e1277b5946592128d5c771d895c2fac2c

[ "Apache-2.0" ]

null

ejercicios/Ejercicio6.py

Xavitheforce/Ejercicios_Iteracion

e840439e1277b5946592128d5c771d895c2fac2c

[ "Apache-2.0" ]

null

from datetime import datetime

39.425926

184

0.622828

f2470b57f1baf4a7e69d418b396753a2d81c5b04

752

py

Python

authentik/sources/saml/migrations/0011_auto_20210324_0736.py

BeryJu/passbook

350f0d836580f4411524614f361a76c4f27b8a2d

[ "MIT" ]

15

2020-01-05T09:09:57.000Z

2020-11-28T05:27:39.000Z

authentik/sources/saml/migrations/0011_auto_20210324_0736.py

BeryJu/passbook

350f0d836580f4411524614f361a76c4f27b8a2d

[ "MIT" ]

302

2020-01-21T08:03:59.000Z

2020-12-04T05:04:57.000Z

authentik/sources/saml/migrations/0011_auto_20210324_0736.py

BeryJu/passbook

350f0d836580f4411524614f361a76c4f27b8a2d

[ "MIT" ]

3

2020-03-04T08:21:59.000Z

2020-08-01T20:37:18.000Z

# Generated by Django 3.1.7 on 2021-03-24 07:36 import django.db.models.deletion from django.db import migrations, models

28.923077

78

0.62633

f248957a375715c7681a4295ca66a47a10ee7ea3

6,891

py

Python

tempest/tests/common/test_service_clients.py

xavpaice/tempest

958bd694df27511e0346d799876fe49331b8145c

[ "Apache-2.0" ]

null

tempest/tests/common/test_service_clients.py

xavpaice/tempest

958bd694df27511e0346d799876fe49331b8145c

[ "Apache-2.0" ]

null

tempest/tests/common/test_service_clients.py

xavpaice/tempest

958bd694df27511e0346d799876fe49331b8145c

[ "Apache-2.0" ]

null

# Copyright 2015 NEC Corporation. All rights reserved. # # 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. import mock import random import six from tempest.services.baremetal.v1.json import baremetal_client from tempest.services.data_processing.v1_1 import data_processing_client from tempest.services.database.json import flavors_client as db_flavor_client from tempest.services.database.json import versions_client as db_version_client from tempest.services.identity.v2.json import identity_client as \ identity_v2_identity_client from tempest.services.identity.v3.json import credentials_client from tempest.services.identity.v3.json import endpoints_client from tempest.services.identity.v3.json import identity_client as \ identity_v3_identity_client from tempest.services.identity.v3.json import policies_client from tempest.services.identity.v3.json import regions_client from tempest.services.identity.v3.json import services_client from tempest.services.image.v1.json import images_client from tempest.services.image.v2.json import images_client as images_v2_client from tempest.services.messaging.json import messaging_client from tempest.services.network.json import network_client from tempest.services.object_storage import account_client from tempest.services.object_storage import container_client from tempest.services.object_storage import object_client from tempest.services.orchestration.json import orchestration_client from tempest.services.telemetry.json import alarming_client from tempest.services.telemetry.json import telemetry_client from tempest.services.volume.v1.json.admin import hosts_client \ as volume_hosts_client from tempest.services.volume.v1.json.admin import quotas_client \ as volume_quotas_client from tempest.services.volume.v1.json.admin import services_client \ as volume_services_client from tempest.services.volume.v1.json.admin import types_client \ as volume_types_client from tempest.services.volume.v1.json import availability_zone_client \ as volume_az_client from tempest.services.volume.v1.json import backups_client from tempest.services.volume.v1.json import extensions_client \ as volume_extensions_client from tempest.services.volume.v1.json import qos_client from tempest.services.volume.v1.json import snapshots_client from tempest.services.volume.v1.json import volumes_client from tempest.services.volume.v2.json.admin import hosts_client \ as volume_v2_hosts_client from tempest.services.volume.v2.json.admin import quotas_client \ as volume_v2_quotas_client from tempest.services.volume.v2.json.admin import services_client \ as volume_v2_services_client from tempest.services.volume.v2.json.admin import types_client \ as volume_v2_types_client from tempest.services.volume.v2.json import availability_zone_client \ as volume_v2_az_client from tempest.services.volume.v2.json import backups_client \ as volume_v2_backups_client from tempest.services.volume.v2.json import extensions_client \ as volume_v2_extensions_client from tempest.services.volume.v2.json import qos_client as volume_v2_qos_client from tempest.services.volume.v2.json import snapshots_client \ as volume_v2_snapshots_client from tempest.services.volume.v2.json import volumes_client as \ volume_v2_volumes_client from tempest.tests import base

47.524138

79

0.753882

f2490fc27568d943c3ececc3e75fce355b5da3ff

3,497

py

Python

advent/days/day17/day.py

RuedigerLudwig/advent2021

ce069d485bb34b4752ec4e89f195f7cc8cf084cc

[ "Unlicense" ]

null

advent/days/day17/day.py

RuedigerLudwig/advent2021

ce069d485bb34b4752ec4e89f195f7cc8cf084cc

[ "Unlicense" ]

null

advent/days/day17/day.py

RuedigerLudwig/advent2021

ce069d485bb34b4752ec4e89f195f7cc8cf084cc

[ "Unlicense" ]

null

from __future__ import annotations from itertools import product from typing import Iterator day_num = 17 Range = tuple[int, int] XStepRange = tuple[int, int | None] YStepRange = tuple[int, int] Pos = tuple[int, int]

31.223214

82

0.501859