Datasets:

---

lparkourer10

/

starcoder-python5b

like 0

793f577ac11bbbc7e376229ad4cc942f0f7a2e50

py

Python

hypebot/data/league/client_vars.py

jellzilla/hypebot

d85158cf5d966d24c3c2ca5789530864c9fe2662

2018-04-06T18:15:38.000Z

2021-05-20T13:44:15.000Z

hypebot/data/league/client_vars.py

jellzilla/hypebot

d85158cf5d966d24c3c2ca5789530864c9fe2662

2018-04-06T16:04:50.000Z

2022-01-06T02:54:38.000Z

hypebot/data/league/client_vars.py

jellzilla/hypebot

d85158cf5d966d24c3c2ca5789530864c9fe2662

2018-04-06T00:28:37.000Z

2021-10-15T11:29:44.000Z

# coding=utf-8 # Copyright 2018 The Hypebot Authors. 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. """Collection of League client variable values. Some of Rito's API methods return description strings that have variables. Unfortunately, Rito habitually does not make variable values accessible through the API. Instead, the substitution table lives in the League client and we chose to copy them here. """ from __future__ import unicode_literals REFORGED_RUNE_VARS = { 'SummonAery': { '@DamageBase@': '15', '@DamageMax@': '40', '@DamageAPRatio.-1@': '0.1', '@DamageADRatio.-1@': '0.15', '@ShieldBase@': '30', '@ShieldMax@': '80', '@ShieldRatio.-1@': '0.25', '@ShieldRatioAD.-1@': '0.4', }, 'ArcaneComet': { '@DamageBase@': '30', '@DamageMax@': '100', '@APRatio.-1@': '0.2', '@ADRatio.-1@': '0.35', '@RechargeTime@': '20', '@RechargeTimeMin@': '8', '@PercentRefund*100@': '20', '@AoEPercentRefund*100@': '10', '@DotPercentRefund*100@': '5', }, 'PhaseRush': { '@Window@': '3', '@HasteBase*100@': '15', '@HasteMax*100@': '40', '@SlowResist*100@': '75', '@Duration@': '3', '@Cooldown@': '15', }, # TODO: Fill in the rest of these. }

793f57bf6fc445f89665b60c9f14cb65b839ed5c

py

Python

mypy_boto3_builder/parsers/docstring_parser/type_value.py

ahonnecke/mypy_boto3_builder

38b002d62ceae5488a6d963aadec9157d3c807da

mypy_boto3_builder/parsers/docstring_parser/type_value.py

ahonnecke/mypy_boto3_builder

38b002d62ceae5488a6d963aadec9157d3c807da

mypy_boto3_builder/parsers/docstring_parser/type_value.py

ahonnecke/mypy_boto3_builder

38b002d62ceae5488a6d963aadec9157d3c807da

""" Structure for parsed as dict request or response syntax values. """ from typing import Any, Dict, List, Optional from mypy_boto3_builder.import_helpers.import_string import ImportString from mypy_boto3_builder.logger import get_logger from mypy_boto3_builder.service_name import ServiceName from mypy_boto3_builder.type_annotations.external_import import ExternalImport from mypy_boto3_builder.type_annotations.fake_annotation import FakeAnnotation from mypy_boto3_builder.type_annotations.type import Type from mypy_boto3_builder.type_annotations.type_annotation import TypeAnnotation from mypy_boto3_builder.type_annotations.type_literal import TypeLiteral from mypy_boto3_builder.type_annotations.type_subscript import TypeSubscript from mypy_boto3_builder.type_annotations.type_typed_dict import TypeTypedDict from mypy_boto3_builder.type_maps.shape_type_map import get_shape_type_stub from mypy_boto3_builder.type_maps.syntax_type_map import SYNTAX_TYPE_MAP class TypeValue: """ Structure for parsed as dict request or response syntax values. """ def __init__(self, service_name: ServiceName, prefix: str, value: Dict[str, Any]) -> None: self.service_name = service_name self.logger = get_logger() self.prefix = prefix self.raw: Dict[str, Any] = value self.dict_items: Optional[List[Dict[str, Any]]] = value.get("dict_items") if value.get("empty_dict"): self.dict_items = [] self.set_items: Optional[List[Any]] = value.get("set_items") self.list_items: Optional[List[Any]] = value.get("list_items") if value.get("empty_list"): self.list_items = [] self.func_call: Optional[Dict[str, Any]] = value.get("func_call") self.union_items: List[Any] = [] if value.get("union_first_item"): self.union_items.append(value["union_first_item"]) self.union_items.extend(value["union_rest_items"]) self.literal_items: List[Any] = [] if value.get("literal_first_item"): self.literal_items.append(value["literal_first_item"]) self.literal_items.extend(value["literal_rest_items"]) self.value: Optional[str] = value.get("value") def is_dict(self) -> bool: """ Whether value is Dict. """ return self.dict_items is not None def is_list(self) -> bool: """ Whether value is List. """ return self.list_items is not None def is_literal(self) -> bool: """ Whether value is Literal. """ return bool(self.literal_items) def is_set(self) -> bool: """ Whether value is Set. """ return bool(self.set_items) def is_union(self) -> bool: """ Whether value is Union. """ return bool(self.union_items) def is_func_call(self) -> bool: """ Whether value is Callable. """ return bool(self.func_call) def is_plain(self) -> bool: """ Whether value is not None. """ return self.value is not None def _get_type_dict(self) -> FakeAnnotation: if not self.dict_items: return Type.DictStrAny first_key = self.dict_items[0]["key"] if first_key in SYNTAX_TYPE_MAP: result = TypeSubscript(Type.Dict) result.add_child(SYNTAX_TYPE_MAP[first_key]) result.add_child( TypeValue(self.service_name, self.prefix, self.dict_items[0]["value"]).get_type() ) return result typed_dict_name = f"{self.prefix}TypeDef" shape_type_stub = get_shape_type_stub(self.service_name, typed_dict_name) if shape_type_stub: return shape_type_stub typed_dict = TypeTypedDict(typed_dict_name) for item in self.dict_items: key_name = self._parse_constant(item["key"]) prefix = f"{self.prefix}{key_name}" typed_dict.add_attribute( key_name, TypeValue(self.service_name, prefix, item["value"]).get_type(), required=False, ) return typed_dict def _get_type_list(self) -> TypeSubscript: if not self.list_items: return TypeSubscript(Type.List, [Type.Any]) result = TypeSubscript(Type.List) for item_index, item in enumerate(self.list_items): prefix = f"{self.prefix}{item_index if item_index else ''}" result.add_child(TypeValue(self.service_name, prefix, item).get_type()) return result def _get_type_union(self) -> FakeAnnotation: if not self.union_items: return Type.Any result = TypeSubscript(Type.Union) for item_index, item in enumerate(self.union_items): prefix = f"{self.prefix}{item_index if item_index else ''}" result.add_child(TypeValue(self.service_name, prefix, item).get_type()) if all(i is result.children[0] for i in result.children): return result.children[0] return result def _get_type_set(self) -> TypeAnnotation: if not self.set_items: return Type.Any plain_values = [i["value"] for i in self.set_items] if plain_values == ["'... recursive ...'"]: return Type.Any self.logger.warning(f"Unknown set: {self.raw}, fallback to Any") return Type.Any def _get_type_func_call(self) -> FakeAnnotation: if not self.func_call: raise ValueError(f"Value is not a func call: {self.raw}") if self.func_call["name"] == "datetime": return ExternalImport(ImportString("datetime"), "datetime") if self.func_call["name"] == "StreamingBody": return ExternalImport(ImportString("botocore", "response"), "StreamingBody") if self.func_call["name"] == "EventStream": return ExternalImport(ImportString("botocore", "eventstream"), "EventStream") self.logger.warning(f"Unknown function: {self.raw}, fallback to Any") return Type.Any def _get_type_plain(self) -> FakeAnnotation: if not self.value or isinstance(self.value, dict): raise ValueError(f"Value is not plain: {self.raw}") if self.value in SYNTAX_TYPE_MAP: return SYNTAX_TYPE_MAP[self.value] if self.value.startswith("'"): return Type.str self.logger.warning(f"Unknown plain value: {self.raw}, fallback to Any") return Type.Any def is_literal_item(self) -> bool: """ Whether value is Literal item. """ if self.value is None: return False return self.value.startswith("'") def _get_type_literal(self) -> FakeAnnotation: if not self.literal_items: raise ValueError(f"Value is not literal: {self.raw}") items = [TypeValue(self.service_name, self.prefix, i) for i in self.literal_items] if all(i.is_literal_item() for i in items): item_constants = [self._parse_constant(i.value or "") for i in items] return TypeLiteral(f"{self.prefix}Type", item_constants) item_types = [i.get_type() for i in items] if all([i is item_types[0] for i in item_types]): return item_types[0] return TypeSubscript(Type.Union, item_types) @staticmethod def _parse_constant(value: str) -> Any: if value.startswith("'"): return value.replace("'", "") if value.isdigit(): return int(value) raise ValueError(f"Invalid constant: {value}") def get_type(self) -> FakeAnnotation: """ Get value type. """ if self.is_list(): return self._get_type_list() if self.is_dict(): return self._get_type_dict() if self.is_set(): return self._get_type_set() if self.is_func_call(): return self._get_type_func_call() if self.is_union(): return self._get_type_union() if self.is_literal(): return self._get_type_literal() if self.is_plain(): return self._get_type_plain() raise ValueError(f"Unknown value: {self.raw}")

793f58be9da27b680ff8fd87f827a7e47f61d389

py

Python

ctpbee/json/pollen.py

yutiansut/ctpbee

02ceb3d4456a54b1b4f8066a2662c4b8fac1027f

ctpbee/json/pollen.py

yutiansut/ctpbee

02ceb3d4456a54b1b4f8066a2662c4b8fac1027f

ctpbee/json/pollen.py

yutiansut/ctpbee

02ceb3d4456a54b1b4f8066a2662c4b8fac1027f

2019-11-21T03:38:14.000Z

2022-02-14T08:09:11.000Z

import json from collections import defaultdict class ProxyPollen(object): """ +-------------------+---------------+--------------------+ | Python | JSON |Pollen(Can change | +===================+===============+====================+ | dict | object |cls:Data,Request | +-------------------+---------------+--------------------+ | list, tuple,set | array | | +-------------------+---------------+--------------------+ | str | string | Enum | +-------------------+---------------+--------------------+ | int, float | number | | +-------------------+---------------+--------------------+ | True | true | | +-------------------+---------------+--------------------+ | False | false | | +-------------------+---------------+--------------------+ | None | null | | +-------------------+---------------+--------------------+ |Datetime | str(Datetime) | Datetime | +-------------------+---------------+--------------------+ """ """ str_can_to:用于筛选str转python类型时的tag类,存在str_tags default_tags:所有tag实例 str_tags: "" enum_store:自定义Enum仓库 data_class_store:自定义Data类仓库[BaseDataClass,BaseRequestClass] data_base_class: BaseData request_base_class: BaseRequest """ str_can_to = ['enum', 'datetime'] default_tags = dict() str_tags = dict() enum_store = dict() data_class_store = defaultdict(set) data_base_class = None request_base_class = None def __init__(self, tags: list = None, enums: list = None, data_class=None, request_class=None): if tags: self.labeling(tags) if enums: self.add_enum(enums) if data_class: self.add_data_class(data_class) if request_class: self.add_request_class(request_class) self._init_class_store() def _init_class_store(self): # 初始化 data_class_store data = data_class + request_class for cls in data: cls_name = cls.__name__ attribute = set() for c in cls.__dict__['__annotations__']: if c.startswith("__") or c.startswith("create"): continue attribute.add(c) self.data_class_store[cls] = attribute def labeling(self, tags: list): """ 添加tag类 :param tags: :return: """ if not isinstance(tags, list): raise TypeError("[^^]tags must list") for t in tags: self.default_tags[t.tag] = t(self) if t.tag in self.str_can_to: self.str_tags[t.tag] = t(self) def add_enum(self, enums: list): """ 添加自定义Enum类属性值 :param enums: :return: """ if not isinstance(enums, list): raise TypeError("[^^]enums must list") for e in enums: for _, v in e.__members__.items(): self.enum_store[v.value] = v def add_data_class(self, data_class: list): """ {cls_name:{attr1,attr2},} 模糊获取类变量属性 :param data_class: :return: """ if not isinstance(data_class, list): raise TypeError("[^^]data_class must list") self.data_base_class = data_class[0].__bases__ def add_request_class(self, request_class: list): """ {cls_name:{attr1,attr2},} 模糊获取类变量属性 :param request_class: :return: """ if not isinstance(request_class, list): raise TypeError("[^^]request_class must list") self.request_base_class = request_class[0].__bases__ def update_data_class_store(self, data): """ 在dumps时将类实例的全部属性覆盖模糊获取的属性,提高精确性 :param data: Dataclass或RequestClass实例 :return: """ cls_name = data.__class__.__name__ for c in list(self.data_class_store.keys()): if c.__name__ == cls_name: self.data_class_store[c] = set(data._to_dict().keys()) @classmethod def find_tag(cls, value): """ :param value: :return: """ for t in cls.default_tags.values(): if t.check(value): return t @classmethod def loads(cls, json_data): """ to python :param value: :return: """ if isinstance(json_data, str): json_data = json.loads(json_data) tag = cls.find_tag(json_data) if tag: return tag.to_pollen(json_data) @classmethod def dumps(cls, value): """ to json :param value: :return: """ tag = cls.find_tag(value) if tag: return json.dumps(tag.to_json(value), ensure_ascii=False) from .tag import tags from ctpbee.constant import enums, data_class, request_class Pollen = ProxyPollen(tags=tags, enums=enums, data_class=data_class, request_class=request_class)

793f5a0c237e6621305c613c3fe49be6382c6e0a

py

Python

ansible/modules/windows/win_command.py

EnjoyLifeFund/macHighSierra-py36-pkgs

5668b5785296b314ea1321057420bcd077dba9ea

2022-01-25T22:52:58.000Z

2022-01-25T22:52:58.000Z

ansible/modules/windows/win_command.py

EnjoyLifeFund/Debian_py36_packages

1985d4c73fabd5f08f54b922e73a9306e09c77a5

ansible/modules/windows/win_command.py

EnjoyLifeFund/Debian_py36_packages

1985d4c73fabd5f08f54b922e73a9306e09c77a5

#!/usr/bin/python # -*- coding: utf-8 -*- # (c) 2016, Ansible, inc # # This file is part of Ansible # # Ansible is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # Ansible is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with Ansible. If not, see <http://www.gnu.org/licenses/>. # ANSIBLE_METADATA = {'metadata_version': '1.1', 'status': ['preview'], 'supported_by': 'core'} DOCUMENTATION = r''' --- module: win_command short_description: Executes a command on a remote Windows node version_added: 2.2 description: - The C(win_command) module takes the command name followed by a list of space-delimited arguments. - The given command will be executed on all selected nodes. It will not be processed through the shell, so variables like C($env:HOME) and operations like C("<"), C(">"), C("|"), and C(";") will not work (use the M(win_shell) module if you need these features). - For non-Windows targets, use the M(command) module instead. options: free_form: description: - the C(win_command) module takes a free form command to run. There is no parameter actually named 'free form'. See the examples! required: true creates: description: - a path or path filter pattern; when the referenced path exists on the target host, the task will be skipped. removes: description: - a path or path filter pattern; when the referenced path B(does not) exist on the target host, the task will be skipped. chdir: description: - set the specified path as the current working directory before executing a command notes: - If you want to run a command through a shell (say you are using C(<), C(>), C(|), etc), you actually want the M(win_shell) module instead. The C(win_command) module is much more secure as it's not affected by the user's environment. - C(creates), C(removes), and C(chdir) can be specified after the command. For instance, if you only want to run a command if a certain file does not exist, use this. - For non-Windows targets, use the M(command) module instead. author: - Matt Davis ''' EXAMPLES = r''' - name: Save the result of 'whoami' in 'whoami_out' win_command: whoami register: whoami_out - name: Run command that only runs if folder exists and runs from a specific folder win_command: wbadmin -backupTarget:C:\backup\ args: chdir: C:\somedir\ creates: C:\backup\ ''' RETURN = r''' msg: description: changed returned: always type: boolean sample: True start: description: The command execution start time returned: always type: string sample: '2016-02-25 09:18:26.429568' end: description: The command execution end time returned: always type: string sample: '2016-02-25 09:18:26.755339' delta: description: The command execution delta time returned: always type: string sample: '0:00:00.325771' stdout: description: The command standard output returned: always type: string sample: 'Clustering node rabbit@slave1 with rabbit@master ...' stderr: description: The command standard error returned: always type: string sample: 'ls: cannot access foo: No such file or directory' cmd: description: The command executed by the task returned: always type: string sample: 'rabbitmqctl join_cluster rabbit@master' rc: description: The command return code (0 means success) returned: always type: int sample: 0 stdout_lines: description: The command standard output split in lines returned: always type: list sample: [u'Clustering node rabbit@slave1 with rabbit@master ...'] '''

793f5a42d0e99ced330446a62cb47cb9233fa4e8

py

Python

couscous/__main__.py

sthagen/improved-couscous

797807f5c4a834f60c8a7d61b7477df46cd775aa

2021-03-07T11:08:57.000Z

2021-03-07T11:08:57.000Z

couscous/__main__.py

sthagen/improved-couscous

797807f5c4a834f60c8a7d61b7477df46cd775aa

2021-03-02T21:14:54.000Z

2021-03-02T22:00:30.000Z

couscous/__main__.py

sthagen/improved-couscous

797807f5c4a834f60c8a7d61b7477df46cd775aa

# -*- coding: utf-8 -*- # pylint: disable=expression-not-assigned,line-too-long import sys from couscous.cli import main if __name__ == "__main__": sys.exit(main(sys.argv[1:])) # pragma: no cover

793f5dddd22364d937f649667f226d2f0741584b

py

Python

Commands/Log.py

Heufneutje/PyMoronBot

055abf0e685f3d2fc02863517952dc7fad9050f3

Commands/Log.py

Heufneutje/PyMoronBot

055abf0e685f3d2fc02863517952dc7fad9050f3

Commands/Log.py

Heufneutje/PyMoronBot

055abf0e685f3d2fc02863517952dc7fad9050f3

# -*- coding: utf-8 -*- """ Created on May 11, 2014 @author: Tyranic-Moron """ import datetime import codecs import os from moronbot import cmdArgs from IRCMessage import IRCMessage from IRCResponse import IRCResponse, ResponseType from CommandInterface import CommandInterface import GlobalVars logFuncs = { 'PRIVMSG': lambda m: u'<{0}> {1}'.format(m.User.Name, m.MessageString), 'ACTION': lambda m: u'*{0} {1}*'.format(m.User.Name, m.MessageString), 'NOTICE': lambda m: u'[{0}] {1}'.format(m.User.Name, m.MessageString), 'JOIN': lambda m: u' >> {0} ({1}@{2}) joined {3}'.format(m.User.Name, m.User.User, m.User.Hostmask, m.ReplyTo), 'NICK': lambda m: u'{0} is now known as {1}'.format(m.User.Name, m.MessageString), 'PART': lambda m: u' << {0} ({1}@{2}) left {3}{4}'.format(m.User.Name, m.User.User, m.User.Hostmask, m.ReplyTo, m.MessageString), 'QUIT': lambda m: u' << {0} ({1}@{2}) quit{3}'.format(m.User.Name, m.User.User, m.User.Hostmask, m.MessageString), 'KICK': lambda m: u'!<< {0} was kicked by {1}{2}'.format(m.Kickee, m.User.Name, m.MessageString), 'TOPIC': lambda m: u'# {0} set the topic to: {1}'.format(m.User.Name, m.MessageString), 'MODE': lambda m: u'# {0} sets mode: {1}{2} {3}'.format(m.User.Name, m.ModeOperator, m.Modes, ' '.join(m.ModeArgs)) } def log(text, target): now = datetime.datetime.utcnow() time = now.strftime("[%H:%M]") data = u'{0} {1}'.format(time, text) print target, data fileName = "{0}{1}.txt".format(target, now.strftime("-%Y%m%d")) fileDirs = os.path.join(GlobalVars.logPath, cmdArgs.server) if not os.path.exists(fileDirs): os.makedirs(fileDirs) filePath = os.path.join(fileDirs, fileName) with codecs.open(filePath, 'a+', 'utf-8') as f: f.write(data + '\n') class Log(CommandInterface): triggers = []#['log'] help = "Logs {} messages.".format("/".join(logFuncs.keys()))#"log (-n / yyyy-mm-dd) - " \ #"without parameters, links to today's log. " \ #"-n links to the log n days ago. " \ #"yyyy-mm-dd links to the log for the specified date" priority = -1 def shouldExecute(self, message): """ @type message: IRCMessage """ return True def execute(self, message): """ @type message: IRCMessage """ if message.Type in logFuncs: logString = logFuncs[message.Type](message) log(logString, message.ReplyTo) if message.Type in self.acceptedTypes and message.Command in self.triggers: # log linking things super(Log, self).execute(message)

793f5ee56f7cde94fdcef03ecde62c6dc2ac36c7

py

Python

test/vanilla/Expected/AcceptanceTests/BodyComplex/bodycomplex/models/_auto_rest_complex_test_service_enums.py

fearthecowboy/autorest.python

a251e361218598b55b0621db2275aafcb7158a5c

test/vanilla/Expected/AcceptanceTests/BodyComplex/bodycomplex/models/_auto_rest_complex_test_service_enums.py

fearthecowboy/autorest.python

a251e361218598b55b0621db2275aafcb7158a5c

test/vanilla/Expected/AcceptanceTests/BodyComplex/bodycomplex/models/_auto_rest_complex_test_service_enums.py

fearthecowboy/autorest.python

a251e361218598b55b0621db2275aafcb7158a5c

# coding=utf-8 # -------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for # license information. # # Code generated by Microsoft (R) AutoRest Code Generator. # Changes may cause incorrect behavior and will be lost if the code is # regenerated. # -------------------------------------------------------------------------- from enum import Enum class CMYKColors(str, Enum): cyan = "cyan" magenta = "Magenta" yellow = "YELLOW" blac_k = "blacK" class GoblinSharkColor(str, Enum): pink = "pink" gray = "gray" brown = "brown" class MyKind(str, Enum): kind1 = "Kind1"

793f5f4d80b6062d18b2c3630e41d33e2a9a5abf

py

Python

cogs/general/meta.py

Mystic-Alchemy/Vale.py

b4cc964d34672444c65e2801a15f37d774c5e6e3

2018-10-13T17:58:58.000Z

2018-10-13T17:58:58.000Z

cogs/general/meta.py

Mystic-Alchemy/Vale.py

b4cc964d34672444c65e2801a15f37d774c5e6e3

cogs/general/meta.py

Mystic-Alchemy/Vale.py

b4cc964d34672444c65e2801a15f37d774c5e6e3

import inspect import os import platform import re import discord import psutil from discord.ext import commands from utils.colors import random_color from utils.converter import BotCommand from utils.paginator import Paginator # Thanks, Milky VERSION_HEADER_PATTERN = re.compile(r'^## (\d+\.\d+\.\d+) - (\d{4}-\d{2}-\d{2}|Unreleased)$') CHANGE_TYPE_PATTERN = re.compile(r'^### (Added|Changed|Deprecated|Removed|Fixed|Security)$') def _is_bulleted(line): return line.startswith(('* ', '- ')) def _changelog_versions(lines): version = change_type = release_date = None changes = {} for line in lines: line = line.strip() if not line: continue match = VERSION_HEADER_PATTERN.match(line) if match: if version: yield version, {'release_date': release_date, 'changes': changes.copy()} version = match[1] release_date = match[2] changes.clear() continue match = CHANGE_TYPE_PATTERN.match(line) if match: change_type = match[1] continue if _is_bulleted(line): changes.setdefault(change_type, []).append(line) else: changes[change_type][-1] += ' ' + line.lstrip() yield version, {'release_date': release_date, 'changes': changes.copy()} def _load_changes(): with open('CHANGELOG.md') as f: return dict(_changelog_versions(f.readlines())) _CHANGELOG = _load_changes() def _format_line(line): if _is_bulleted(line): return '\u2022 ' + line[2:] return line def _format_changelog_without_embed(version): changes = _CHANGELOG[version] nl_join = '\n'.join change_lines = '\n\n'.join( f'{type_}\n{nl_join(map(_format_line, lines))}' for type_, lines in changes['changes'].items() ) return f'Version {version} \u2014 {changes["release_date"]}\n\n{change_lines}' def _format_changelog_with_embed(version, url): changes = _CHANGELOG[version] nl_join = '\n'.join change_lines = '\n\n'.join( f'**__{type_}__**\n{nl_join(map(_format_line, lines))}' for type_, lines in changes['changes'].items() ) embed = discord.Embed(description=change_lines) name = f'Version {version} \u2014 {changes["release_date"]}' embed.set_author(name=name, url=url) return embed class Meta: """Primary a class that provides some meta information about the bot.""" def __init__(self, bot): self.bot = bot @property def emojis(self): return self.bot.bot_emojis @staticmethod async def _get_commits(repo): cmd = r'git show -s HEAD~5..HEAD --format="[{}](https://github.com/' + repo + '/commit/%H) %s (%cr)"' # 10 commits if os.name == 'posix': cmd = cmd.format(r'\`%h\`') else: cmd = cmd.format(r'`%h`') try: revision = os.popen(cmd).read().strip() except OSError: revision = 'Couldn\'t fetch commits. Either a memory error or a non-existant repository was provided.' return revision @staticmethod def _get_os_information(cpu, memory): return inspect.cleandoc(f""" **System information:** ```yaml :Architecture: -{platform.architecture()[0]}- :System: -{platform.system()}- :Node: -{platform.node()}- :Release: -{platform.release()}- :Version: -{platform.version()}- :Machine: -{platform.version()}- :Processor: -{platform.processor()}- :CPU usage: -{cpu}- :Memory usage: -{memory}- ``` """) @commands.command(name='about') async def _about(self, ctx): """Get some cool information about the bot.""" pages = [] process = self.bot.process cpu = process.cpu_percent() / psutil.cpu_count() memory = process.memory_info().rss / float(2 ** 20) latency = round(self.bot.latency * 1000, 2) shards = len(self.bot.shards) version = '.'.join(map(str, ctx.bot.version_info[:3])) changelog = ( f'**{self.emojis.get("announcements")} Recent updates:**\n\n' f'```css\n{_format_changelog_without_embed(version)}```' ) commits = await self._get_commits('itsVale/Vale.py') system = self._get_os_information(cpu, memory) python = platform.python_version() postgres = '.'.join(map(str, ctx.db.get_server_version()[:3])) pages = [ ( f'[`Source Code`]({self.bot.source})\n' f'[`Invite me with minimal perms`]({self.bot.minimal_invite_url})\n' f'[`Invite me with full perms (Required for certain commands to work)`]({self.bot.invite_url})\n\n' f'[__**Need help with something? Check out the support server!**__]({self.bot.support_server})' ), ( f'{self.emojis.get("version")} Version: **{version}**\n' f'{self.emojis.get("status")} Online for: **{self.bot.uptime}**\n' f'{self.emojis.get("signal")} Latency: **{latency} ms**\n' f'{self.emojis.get("server")} Guilds: **{self.bot.guild_count}**\n' f'{self.emojis.get("cpu")} CPU usage: **{cpu:.2f}%**\n' f'{self.emojis.get("memory")} RAM usage: **{memory:.2f} Mb**\n' f'{self.emojis.get("shard")} Shards: **{shards}**\n' f'{self.emojis.get("python")} Python version: **{python}**\n' f'{self.emojis.get("discordpy")} discord.py version: **{discord.__version__}**\n' f'{self.emojis.get("postgres")} PostgreSQL version: **{postgres}**\n' ), system, f'**\N{WRITING HAND} Latest commits:**\n\n' + commits, changelog ] paginator = Paginator(ctx, pages, per_page=1, title=f'{self.emojis.get("statistics")} Stats for Vale.py') await paginator.interact() @commands.command(name='source', aliases=['skid', 'steal']) async def _source(self, ctx, *, command: BotCommand = None): """Displays the source code for a command. If the source code has too many lines, it will send a GitHub URL instead. """ if not command: return await ctx.send(self.bot.source) paginator = commands.Paginator(prefix='```py') source = command.callback.__code__ lines, firstlineno = inspect.getsourcelines(command.callback) if len(lines) < 20: for line in lines: paginator.add_line(line.rstrip().replace('`', '\u200b')) for page in paginator.pages: await ctx.send(page) return lastline = firstlineno + len(lines) - 1 location = os.path.relpath(source.co_filename).replace('\\', '/') url = f'<{self.bot.source}/tree/master/{location}#L{firstlineno}-L{lastline}>' await ctx.send(url) @commands.command(name='stats') async def _stats(self, ctx): """Shows some usage statistics about this bot.""" content = ( f'__**Usage statistics:**__\n', f'Commands invoked in total: **{self.bot.command_counter.get("total")}**', f'Commands invoked in this guild: **{self.bot.command_counter.get(str(ctx.guild.id))}**', f'Commands invoked in DMs: **{self.bot.command_counter.get("in DMs")}**\n', f'And here are the commands, which were invoked successfully in total: **{self.bot.command_counter.get("succeeded")}**\n', f'*Only applies to the period from since the bot was restarted for the last time until now.*', ) if ctx.bot_has_embed_links(): await ctx.send(embed=discord.Embed(description='\n'.join(content), color=random_color())) else: await ctx.send('\n'.join(content)) def setup(bot): bot.add_cog(Meta(bot))

793f6099d8f51f4388d61ad66f58ee21180eb185

py

Python

venv/lib/python3.6/site-packages/xero_python/payrollau/models/deduction_type_calculation_type.py

6enno/FarmXero

881b1e6648e927631b276e66a4c5287e4de2cbc1

venv/lib/python3.6/site-packages/xero_python/payrollau/models/deduction_type_calculation_type.py

6enno/FarmXero

881b1e6648e927631b276e66a4c5287e4de2cbc1

venv/lib/python3.6/site-packages/xero_python/payrollau/models/deduction_type_calculation_type.py

6enno/FarmXero

881b1e6648e927631b276e66a4c5287e4de2cbc1

# coding: utf-8 """ Xero Payroll AU This is the Xero Payroll API for orgs in Australia region. # noqa: E501 Contact: api@xero.com Generated by: https://openapi-generator.tech """ import re # noqa: F401 from enum import Enum class DeductionTypeCalculationType(Enum): """NOTE: This class is auto generated by OpenAPI Generator. Ref: https://openapi-generator.tech Do not edit the class manually. allowed enum values """ FIXEDAMOUNT = "FIXEDAMOUNT" PRETAX = "PRETAX" POSTTAX = "POSTTAX"

793f60e8206d42961b695a224825f440d0855852

py

Python

grp_modules/util/log/base/util.py

JGU-VC/activation-pattern-analysis

14da42ad541ee4faf35d360a6e871fd44decd33d

grp_modules/util/log/base/util.py

JGU-VC/activation-pattern-analysis

14da42ad541ee4faf35d360a6e871fd44decd33d

grp_modules/util/log/base/util.py

JGU-VC/activation-pattern-analysis

14da42ad541ee4faf35d360a6e871fd44decd33d

import datetime from os.path import basename from html import escape import git from colored import fg, attr def datestr_sort(): return datetime.datetime.now().strftime('%y%m%d-%H%M%S') def datestr(): return datetime.datetime.now().strftime('%Y-%m-%d %H:%M:%S') def get_git_revisions(): # check repo for SHA and diffs repo = git.Repo(search_parent_directories=True) name = basename(repo.working_dir) sha = [repo.head.object.hexsha] diffs = [repo.git.diff('HEAD')] modules = [name] # check also submodules for SHAs and diffs if len(repo.submodules) > 0: modules += [s.name for s in repo.submodules] sha += [s.hexsha for s in repo.submodules] diffs += [s.module().git.diff('HEAD') for s in repo.submodules] return modules, sha, diffs def training_header(state): gpu = ("gpu" + str(state.all["gpu"][0]) if len(state.all["gpu"]) == 1 else "multigpu(%s)" % ",".join(str(g) for g in state.all["gpu"])) if "gpu" in state.all else "cpu" s = [" ", "Experiment", state["tag"], "on", gpu, " "] seed_mode = "seed: %s " % state["seed"] if "seed" in state and state["seed"] >= 0 else "random mode" bar = "—" * len(" ".join(s)) # pylint: disable=blacklisted-name s[1] = s[1] s[2] = fg('red') + attr('bold') + s[2] + attr('reset') s[3] = attr('dim') + s[3] + attr('reset') s[4] = fg('red') + attr('bold') + s[4] + attr('reset') print() print(" ╭" + bar + "╮") print(" │" + " ".join(s) + "│", attr('dim') + seed_mode + attr('reset')) print(" ╰" + bar + "╯") if "record" in state and state["record"]: print(fg('red') + " Recording Log-Calls" + attr('reset')) def html_summary(state, event): html_repostate = "<ul style='list-style: circle'>" + ("".join("<li style='margin:0 3em;'>%s:%s:<code>%s</code></li>" % (name, "clean" if len(diff) == 0 else "<b>diverged</b>", sha[:7]) for (name, diff, sha) in state["repository_state"])) + "</ul>" html_loaded_modules = "<ul style='list-style: circle'>" + ("".join("<li style='margin:0 3em;'>%s</li>" % s for s in state["loaded_modules"])) + "</ul>" html_env = "<ul style='list-style: circle'>" + ("".join("<li style='margin:0 3em;'>%s: <code>%s</code></li>" % (name, ver) for (name, ver) in [("python", state["python"]), ("pytorch", state["pytorch"])])) + "</ul>" html_prepend = """ <h1>Experiment on %s</h1> <h1 style="font-size:120%%; margin-top: -0.25em;">%s</h1> <b>Repository Status:</b></br> %s </br></br> <b>CLI-Call:</b></br> <code><pre>%s</pre></code> </br></br> <b>Loaded Modules:</b></br> %s </br></br> <b>Environment:</b></br> %s </br></br> """ % (state["date"], state["tag"], html_repostate, state["cli_overwrites"], html_loaded_modules, html_env) html_diffs = "\n".join(""" <h1>Repository Diffs</h1> <b><b>%s</b>:</b></br> <code><pre>%s</pre></code> </br></br> """ % (module, escape(diff)) for module, diff, sha in state["repository_state"]) html_settings = html_prepend + "".join(event.settings_html()) return html_settings, html_diffs def plot_every(state, steps): return steps and state["main.current_batch"] % steps == 0

793f619a7e8698942f2ce687ceec9b46d4464fe6

py

Python

openbot.py

n0tpetya/discordbot

dfbcc50b5c37fb2acaefe566bd93fc9980e214dc

openbot.py

n0tpetya/discordbot

dfbcc50b5c37fb2acaefe566bd93fc9980e214dc

2021-02-21T13:10:23.000Z

2021-02-21T13:10:23.000Z

openbot.py

n0tpetya/discordbot

dfbcc50b5c37fb2acaefe566bd93fc9980e214dc

2021-06-03T13:49:22.000Z

2021-06-03T13:49:22.000Z

import asyncio import random import discord from discord import Member, Guild, User from discord import Profile from datetime import datetime client = discord.Client(intents=discord.Intents.all()) antworten = ['Ja', 'Nein', 'Wahrscheinlich', 'Unwahrscheinlich', 'Vielleicht', 'Sehr wahrscheinlich', 'Sehr unwarscheinlich'] beleidigungen = [] uhrzeit = datetime.now().strftime('%H:%M') status = ['Drinking coffee☕️', 'Eating something🧁', 'Playing Minecraft🎮', 'Playing CS:GO🎮', 'Playing GTA V🎮', 'Playing Rocket League🎮', 'Vibing🎷', 'Doing work👨🏼‍🔧', 'Meeting friends👨‍👨‍👦', 'Listening to music🎧', 'On the phone📞', 'Writing with friends📱', 'On a party🎭', 'Going out👫'] def is_not_pinned(cmess): return not cmess.pinned @client.event # Start async def on_ready(): print('Eingeloggt als {}'.format(client.user.name)) # Startup succes MSG print(uhrzeit) client.loop.create_task(status_task()) async def status_task(): # Schleife die Status des Bots ändert while True: await client.change_presence(activity=discord.Game('Status 1'), status=discord.Status.online) await asyncio.sleep(5) await client.change_presence(activity=discord.Game('Status 2'), status=discord.Status.online) await asyncio.sleep(5) await client.change_presence(activity=discord.Game('{}'.format(random.choice(status))), status=discord.Status.online) await asyncio.sleep(5) @client.event # Befehle async def on_message(message): if message.author.bot: return # Hilfe-Liste if message.content.startswith(".help"): embedhelp = discord.Embed(title='Bot-Commands', description='', color=0x04ff00) embedhelp.add_field(name='.help', value='Zeigt dir diese Liste an', inline=False) embedhelp.add_field(name='!oracle <Frage>', value='Gibt dir die Antwort auf deine Frage', inline=False) embedhelp.add_field(name='!uinfo <User>', value='Zeigt Informationen über einen Nutzer', inline=False) embedhelp.add_field(name='!forum', value='Zeigt dir den Link zur Webseite', inline=False) embedhelp.add_field(name='!youtube', value='Zeigt dir den Link zu unserem YouTube Channel', inline=False) embedhelp.add_field(name='!support', value='Zeigt dir Support Möglichkeiten an', inline=False) embedhelp.add_field(name='!ticket', value='Du kannst damit bei Problemen ein Ticket erstellen und mit den Admins in Kontakt treten.') embedhelp.add_field(name='Bot erstellt von', value='Game-Forum.net | Deine Gaming Community!') embedhelp.set_footer(text='Text') await message.channel.send(embed=embedhelp) # Nutzerinfos if message.content.startswith('!uinfo'): args = message.content.split(' ') if len(args) == 2: member: Member = discord.utils.find(lambda m: args[1] in m.name, message.guild.members) if member: embed = discord.Embed(title='Userinfo für {}'.format(member.name), description='Informationen über: {}'.format(member.mention), color=0x04ff00) embed.add_field(name='Server beigetreten', value=member.joined_at.strftime('%d. %m. %Y um %H:%M:%S Uhr'), inline=True) embed.add_field(name='Discord beigetreten', value=member.created_at.strftime('%d. %m. %Y um %H:%M:%S Uhr'), inline=True) rollen = '' for role in member.roles: if not role.is_default(): rollen += '{} \r\n'.format(role.mention) if rollen: embed.add_field(name='Rollen: ', value=rollen, inline=True) embed.add_field(name='Bewertung', value=('Gebe gerne eine Bewertung zu {} ab!'.format(member.mention)), inline=False) embed.set_thumbnail(url=member.avatar_url) embed.set_footer(text='Text') react = await message.channel.send(embed=embed) await react.add_reaction('👍') await react.add_reaction('👎') else: await message.channel.send("Der Nutzer muss auf dem Discord sein!") else: await message.channel.send("Bitte gib einen Nutzernamen an!") # Links if message.content.startswith('!forum'): embed2 = discord.Embed(title='Forum-Adresse', description='Link', color=0xfffb00) embed2.set_footer(text='Game-Forum.net Discord Bot') await message.channel.send(embed=embed2) # Support if message.content.startswith('!support'): embed3 = discord.Embed(title='Support Möglichkeiten', description='Möglichkeiten um Support zu erhalten', color=0xfffb00) embed3.add_field(name='Forum Support', value='Text', inline=True) embed3.set_thumbnail(url='https://game-forum.net/wp-content/uploads/discord/support.png') embed3.set_footer(text='Text') await message.channel.send(embed=embed3) # Team-join-leave-changename # Join if message.content.startswith('!jointeam') and message.author.permissions_in(message.channel).send_tts_messages: args = message.content.split(' ') if len(args) >= 3: member: Member = discord.utils.find(lambda m: args[1] in m.name, message.guild.members) teammsg1 = ' '.join(args[2:]) await message.channel.purge(limit=1, check=is_not_pinned) embedjoin = discord.Embed(title='Team-Beitritt/Promotion', description='Jemand ist dem Team beigetreten oder wurde befördert!', color=0x22ff00) embedjoin.add_field(name='Änderung', value='**{}**'.format(teammsg1), inline=False) embedjoin.set_thumbnail(url=member.avatar_url) embedjoin.set_footer(text='Text') await message.channel.send(embed=embedjoin) # Leave if message.content.startswith('!leaveteam') and message.author.permissions_in(message.channel).send_tts_messages: args = message.content.split(' ') if len(args) >= 3: member: Member = discord.utils.find(lambda m: args[1] in m.name, message.guild.members) teammsg2 = ' '.join(args[2:]) await message.channel.purge(limit=1, check=is_not_pinned) embedleave = discord.Embed(title='Team-Leave/Degradierung', description='Jemand hat das Team verlassen oder wurde degradiert!', color=0xff0000) embedleave.add_field(name='Änderung', value='**{}**'.format(teammsg2), inline=False) embedleave.set_thumbnail(url=member.avatar_url) embedleave.set_footer(text='Text') await message.channel.send(embed=embedleave) # NameChange if message.content.startswith('!nameteam') and message.author.permissions_in(message.channel).send_tts_messages: args = message.content.split(' ') if len(args) >= 3: member: Member = discord.utils.find(lambda m: args[1] in m.name, message.guild.members) teammsg3 = ' '.join(args[2:]) await message.channel.purge(limit=1, check=is_not_pinned) embedchange = discord.Embed(title='Namensänderung', description='Jemand hat seinen Namen geändert.', color=0xfbff00) embedchange.add_field(name='Änderung', value='**{}**'.format(teammsg3), inline=False) embedchange.set_thumbnail(url=member.avatar_url) embedchange.set_footer(text='Text') await message.channel.send(embed=embedchange) # Geburtstag if message.content.startswith('!birthday') and message.author.permissions_in(message.channel).send_tts_messages: args = message.content.split(' ') if len(args) >= 2: teammsg4 = ' '.join(args[1:]) await message.channel.purge(limit=1, check=is_not_pinned) embedbday = discord.Embed(title='Geburtstag', description='Jemand feiert heute seinen Geburtstag! Gratuliere ihm!', color=0x00ffdd) embedbday.add_field(name='Informationen', value='**{}**'.format(teammsg4), inline=False) embedbday.set_thumbnail(url='https://game-forum.net/wp-content/uploads/discord/birthday.png') embedbday.set_footer(text='Text') await message.channel.send(embed=embedbday) # Clearcommand if message.content.startswith('!clear'): if message.author.permissions_in(message.channel).manage_messages: args = message.content.split(' ') if len(args) == 2: if args[1].isdigit(): count = int(args[1]) + 1 deleted = await message.channel.purge(limit=count, check=is_not_pinned) embed4 = discord.Embed(title='Nachrichten gelöscht!', description='Gelöschte Nachrichten (Angepinnte ausgeschlossen)', color=0xff0000) embed4.add_field(name='Anzahl gelöschter Nachrichten', value='{}'.format(len(deleted) - 1)) embed4.set_footer(text='Text') await message.channel.send(embed=embed4) await asyncio.sleep(3) await message.channel.purge(limit=1, check=is_not_pinned) else: await message.channel.send('Bitte gib eine gültige Zahl ein!') else: await message.channel.send('Bitte gib eine gültige Zahl ein!') else: await message.channel.send('Du hast keine Berechtigung dazu!') # Orakel if message.content.startswith('!oracle'): args = message.content.split(' ') if len(args) >= 2: frage = ' '.join(args[1:]) embed5 = discord.Embed(title='Deine Frage an das Orakel', description='Die Antwort auf deine Frage (Ist vielleicht etwas schwammig aber besser als nix ._.)', color=0xff0000) if message.content.endswith('?'): embed5.add_field(name='Frage', value='**{}**'.format(frage)) else: embed5.add_field(name='Frage', value='**{}**'.format(frage) + '?') embed5.add_field(name='Meine Antwort', value='{}'.format(random.choice(antworten))) embed5.set_thumbnail(url='https://game-forum.net/wp-content/uploads/discord/support.png') embed5.set_footer(text='Text') await message.channel.send(embed=embed5) else: await message.channel.send("Bitte gib eine Frage an!") # YouTube-Link if message.content.startswith('!youtube'): embedyoutube = discord.Embed(title='YouTube Kanal', description='Link zum YouTube Kanal', color=0xff0000) embedyoutube.add_field(name='Link', value='Link') embedyoutube.set_footer(text=Text') await message.channel.send(embed=embedyoutube) # Ban-System if message.content.startswith('!ban') and message.author.guild_permissions.ban_members: args = message.content.split(' ') if len(args) >= 2: banreason = ' '.join(args[2:]) member: Member = discord.utils.find(lambda m: args[1] in m.name, message.guild.members) if member: embed7 = discord.Embed(title='Benutzer gebannt', description='Ein Benutzer wurde gebannt', color=0xff0000) embed7.add_field(name='Name des Benutzers', value='**{}**'.format(member.name)) embed7.add_field(name='Grund', value='{}'.format(banreason)) embed7.set_footer(text='Text') await message.channel.send(embed=embed7) embedbandm = discord.Embed(title='Du wurdest gebannt!', description='Du wurdest vom Discord gebannt!', color=0xff0000) embedbandm.add_field(name='Grund', value='{}'.format(banreason)) embedbandm.set_footer(text='Text') try: if not member.bot: if not member.dm_channel: await member.create_dm() await member.dm_channel.send(embed=embedbandm) except discord.errors.Forbidden: print('Es konnte keine Bannachricht an {0} gesendet werden.'.format(member.name)) if member.bot: print('Der User ist ein Bot.') await member.ban() else: await message.channel.send(f'Kein user mit dem Namen {args[1]} gefunden.') else: await message.channel.send('Bitte gib einen Namen an!') if message.content.startswith('!unban') and message.author.guild_permissions.ban_members: args = message.content.split(' ') unbanreason = ' '.join(args[2:]) if len(args) >= 2: user: User = discord.utils.find(lambda m: args[1] in m.user.name, await message.guild.bans()).user if user: await message.guild.unban(user) embed8 = discord.Embed(title='Benutzer entbannt', description='Ein Benutzer wurde entbannt', color=0x04ff00) embed8.add_field(name='Name des Benutzers', value='**{}**'.format(user.name)) embed8.add_field(name='Grund', value='{}'.format(unbanreason)) embed8.set_footer(text='Game-Forum Discord Bot') await message.channel.send(embed=embed8) embedunbandm = discord.Embed(title='Du wurdest entbannt!', description='Du wurdest vom Discord entbannt!', color=0x04ff00) embedunbandm.add_field(name='Grund', value='{}'.format(unbanreason)) embedunbandm.set_footer(text='Du kannst dem Discord nun wieder beitreten!') try: if not user.bot: if not user.dm_channel: await user.create_dm() await user.dm_channel.send(embed=embedunbandm) except discord.errors.Forbidden: print('Es konnte keine Unbannachricht an {0} gesendet werden.'.format(member.name)) if user.bot: print('Der User ist ein Bot.') else: await message.channel.send(f'Kein user mit dem Namen {args[1]} gefunden.') else: await message.channel.send('Bitte gib einen Namen an!') #News-Command if message.content.startswith('!news') and message.author.permissions_in(message.channel).send_tts_messages: args = message.content.split(' ') if len(args) >= 3: titel = '{}'.format(args[1]) news = ' ' .join(args[2:]) embednews = discord.Embed(title='Eine neue News ist erschienen!', description='', color=0x04ff00) embednews.add_field(name='{}'.format(titel), value='{}'.format(news), inline=False) embednews.set_footer(text="Text") await message.channel.purge(limit=1, check=is_not_pinned) await message.channel.send(embed = embednews) if message.content.startswith('!kick') and message.author.guild_permissions.kick_members: args = message.content.split(' ') kickreason = ' '.join(args[2:]) if len(args) >= 2: member: Member = discord.utils.find(lambda m: args[1] in m.name, message.guild.members) if member: embed9 = discord.Embed(title='Benutzer gekickt', description='Ein Benutzer wurde gekickt', color=0xfffb00) embed9.add_field(name='Name des Benutzers', value='**{}**'.format(member.name)) embed9.add_field(name='Grund', value='{}'.format(kickreason)) embed9.set_footer(text='Game-Forum Discord Bot') embedkickdm = discord.Embed(title='Du wurdest gekickt!', description='Du wurdest vom Discord gekickt!', color=0xfffb00) embedkickdm.add_field(name='Name des Benutzers', value='**{}**'.format(member.name)) embedkickdm.add_field(name='Grund', value='{}'.format(kickreason)) embedkickdm.set_footer(text='Du kannst dem Discord weiterhin beitreten!') await message.channel.send(embed=embed9) try: if not member.bot: if not member.dm_channel: await member.create_dm() await member.dm_channel.send(embed=embedkickdm) except discord.errors.Forbidden: print('Es konnte keine Kicknachricht an {0} gesendet werden.'.format(member.name)) if member.bot: print('Der user ist ein Bot.') await member.kick() else: await message.channel.send(f'Kein User mit dem Namen {args[1]} gefunden.') else: await message.channel.send('Bitte gib einen Namen an!') if message.content.startswith('!warn') and message.author.guild_permissions.manage_nicknames: args = message.content.split(' ') warnreason = ' '.join(args[2:]) if len(args) >= 2: member: Member = discord.utils.find(lambda m: args[1] in m.name, message.guild.members) if member: embedwarn = discord.Embed(title='Benutzer verwarnt', description='Ein Benutzer wurde verwarnt', color=0xfffb00) embedwarn.add_field(name='Name des Benutzers', value='**{}**'.format(member.name)) embedwarn.add_field(name='Grund', value='{}'.format(warnreason)) embedwarn.set_footer(text='Game-Forum Discord Bot') embedwarndm = discord.Embed(title='Du wurdest verwarnt', description='Du wurdest am Discord verwarnt!', color=0xfffb00) embedwarndm.add_field(name='Name des Benutzers', value='**{}**'.format(member.name)) embedwarndm.add_field(name='Grund', value='{}'.format(warnreason)) embedwarndm.set_footer(text='Du kannst dem Discord weiterhin beitreten!') await message.channel.send(embed=embedwarn) try: if not member.bot: if not member.dm_channel: await member.create_dm() await member.dm_channel.send(embed=embedwarndm) except discord.errors.Forbidden: print('Es konnte keine Warnnachricht an {0} gesendet werden.'.format(member.name)) if member.bot: print('Der User ist ein Bot.') else: await message.channel.send(f'Kein user mit dem Namen {args[1]} gefunden.') else: await message.channel.send('Bitte gib einen Namen an!') @client.event # Beitritt des Servers async def on_member_join(member): # Willkommennachricht und Rollenvergabe für User mitgliedrolle = discord.utils.get(member.guild.roles, name='User') botrolle = discord.utils.get(member.guild.roles, name='BOT') willkommenschannel_id = # Channel ID willkommenschannel = client.get_channel(willkommenschannel_id) await willkommenschannel.send('Hey **{}**, willkommen auf dem Server!'.format(member.mention)) embed = discord.Embed(title='Willkommen {} auf dem Game-Forun.net Discord Server! 👍 😀'.format(member.name), description='Wir heißen dich herzlich Willkommen', color=0x04ff00) embed.set_thumbnail(url=member.avatar_url) await willkommenschannel.send(embed=embed) if not member.bot: await member.add_roles(mitgliedrolle) embed = discord.Embed(title='Hey **{}**, willkommen auf dem Discord Server!'.format(member.name), description='Wir heißen dich herzlich willkommen und wünsche dir eine angenehme Zeit auf dem Server.', color=0x04ff00) try: if not member.dm_channel: await member.create_dm() await member.dm_channel.send(embed=embed) except discord.errors.Forbidden: print('Ich konnte keine persönliche Willkommennachricht an **{}** senden'.format(member.name)) if member.bot: await member.add_roles(botrolle) client.run('Bot Token')

793f63c0920df0d21bc494c2459c68d0f82d1bb4

py

Python

tests/test_read_and_write_state.py

Sage-Bionetworks/SynapseBucketMover

9f9607e6646543832a1d708dd5747dc58a2ead97

2018-09-19T18:05:25.000Z

2018-09-19T18:05:25.000Z

tests/test_read_and_write_state.py

Sage-Bionetworks/SynapseBucketMover

9f9607e6646543832a1d708dd5747dc58a2ead97

2018-10-08T16:48:31.000Z

2018-10-08T17:12:16.000Z

tests/test_read_and_write_state.py

Sage-Bionetworks/SynapseBucketMover

9f9607e6646543832a1d708dd5747dc58a2ead97

2018-10-08T15:47:23.000Z

2018-10-08T15:47:23.000Z

''' Created on Aug 30, 2018 @author: bhoff ''' import unittest import tempfile import os import SynapseBucketMover from nose.tools import assert_raises, assert_equal, assert_is_none, assert_is_not_none, assert_in, assert_false, assert_true class Test(unittest.TestCase): def setUp(self): self.dir = tempfile.TemporaryDirectory() def tearDown(self): if self.dir is not None: os.remove(os.path.join(self.dir.name, "state.txt")) def testPersistence(self): state=SynapseBucketMover.readState(self.dir.name) assert_equal(0, state['filesProcessedCount']) assert_equal([], state['treePageMarker']) state['filesProcessedCount']=100 state['treePageMarker']=[{'parentId':'syn123','nextPageToken':'abc'},{'parentId':'syn456','nextPageToken':'def'}] SynapseBucketMover.writeState(self.dir.name, state) readState = SynapseBucketMover.readState(self.dir.name) assert_equal(state, readState) if __name__ == "__main__": #import sys;sys.argv = ['', 'Test.testPersistence'] unittest.main()

793f64242c01581e4b4912c34c42f3bb4d6bd7dd

py

Python

tests/test_bme280.py

Naohiro2g/bme280

ce3ff06e73965a14060f456a1cd6ede440bd7a22

tests/test_bme280.py

Naohiro2g/bme280

ce3ff06e73965a14060f456a1cd6ede440bd7a22

tests/test_bme280.py

Naohiro2g/bme280

ce3ff06e73965a14060f456a1cd6ede440bd7a22

# -*- coding: utf-8 -*- # Copyright (c) 2018 Richard Hull # See LICENSE.rst for details. try: from unittest.mock import Mock, MagicMock except ImportError: from mock import Mock, MagicMock # noqa: F401 import bme280 smbus = Mock(unsafe=True) def setup_function(function): smbus.reset_mock() def test_load_calibration_params(): smbus.read_word_data = MagicMock(side_effect=list(range(400))) smbus.read_byte_data = MagicMock(side_effect=list(range(400))) calibration_params = bme280.load_calibration_params(bus=smbus, address=0x77) assert calibration_params == { 'dig_H1': 0, 'dig_H2': 12, 'dig_H3': 1, 'dig_H4': 35, 'dig_H5': 64, 'dig_H6': 5, 'dig_P1': 3, 'dig_P2': 4, 'dig_P3': 5, 'dig_P4': 6, 'dig_P5': 7, 'dig_P6': 8, 'dig_P7': 9, 'dig_P8': 10, 'dig_P9': 11, 'dig_T1': 0, 'dig_T2': 1, 'dig_T3': 2 } def test_sample_with_params(): compensation_params = bme280.params() compensation_params.dig_H1 = 0 compensation_params.dig_H2 = 1 compensation_params.dig_H3 = 4 compensation_params.dig_H4 = 3 compensation_params.dig_H5 = 5 compensation_params.dig_H6 = 6 compensation_params.dig_P1 = 10 compensation_params.dig_P2 = 11 compensation_params.dig_P3 = 12 compensation_params.dig_P4 = 13 compensation_params.dig_P5 = 14 compensation_params.dig_P6 = 15 compensation_params.dig_P7 = 16 compensation_params.dig_P8 = 17 compensation_params.dig_P9 = 18 compensation_params.dig_T1 = 20 compensation_params.dig_T2 = 21 compensation_params.dig_T3 = 22 smbus.write_byte_data = MagicMock() smbus.read_i2c_block_data = MagicMock(return_value=list(range(8))) data = bme280.sample(bus=smbus, address=0x76, compensation_params=compensation_params) assert data.pressure == 8801790.518824806 assert data.temperature == 0.0030482932925224304 assert data.humidity == 0.02082886288568924 def test_sample_without_params(): smbus.write_byte_data = MagicMock() smbus.read_word_data = MagicMock(side_effect=list(range(400))) smbus.read_byte_data = MagicMock(side_effect=list(range(400))) smbus.read_i2c_block_data = MagicMock(return_value=list(range(8))) data = bme280.sample(bus=smbus, address=0x76) print(data) assert data.pressure == 37118275.30149117 assert data.temperature == 0.0001507163979113102 assert data.humidity == 0.0 def test_uncompensated_readings_repr(): block = [1, 1, 2, 3, 5, 8, 13, 21] reading = bme280.uncompensated_readings(block) assert repr(reading) == "uncompensated_reading(temp=0x00003050, pressure=0x00001010, humidity=0x00000D15, block=01:01:02:03:05:08:0D:15)" def test_compensated_readings_repr(): compensation_params = bme280.params() compensation_params.dig_H1 = 0 compensation_params.dig_H2 = 1 compensation_params.dig_H3 = 4 compensation_params.dig_H4 = 3 compensation_params.dig_H5 = 5 compensation_params.dig_H6 = 6 compensation_params.dig_P1 = 10 compensation_params.dig_P2 = 11 compensation_params.dig_P3 = 12 compensation_params.dig_P4 = 13 compensation_params.dig_P5 = 14 compensation_params.dig_P6 = 15 compensation_params.dig_P7 = 16 compensation_params.dig_P8 = 17 compensation_params.dig_P9 = 18 compensation_params.dig_T1 = 20 compensation_params.dig_T2 = 21 compensation_params.dig_T3 = 22 block = [1, 1, 2, 3, 5, 8, 13, 21] raw = bme280.uncompensated_readings(block) reading = bme280.compensated_readings(raw, compensation_params) reading.id = "55fea298-5a5d-4873-a46d-b631c8748100" reading.timestamp = "2018-03-18 19:26:14.206233" assert repr(reading) == "compensated_reading(id=55fea298-5a5d-4873-a46d-b631c8748100, timestamp=2018-03-18 19:26:14.206233, temp=0.003 °C, pressure=8758647.58 hPa, humidity=0.05 % rH)"

793f648338972a3a26c70954d344778edb5ec78a

py

Python

src/bot/main.py

MycroftKang/mulgyeol-mkbot

77bcfc5c93e02dbc983d2e6a137ddf835d450c29

src/bot/main.py

MycroftKang/mulgyeol-mkbot

77bcfc5c93e02dbc983d2e6a137ddf835d450c29

src/bot/main.py

MycroftKang/mulgyeol-mkbot

77bcfc5c93e02dbc983d2e6a137ddf835d450c29

import asyncio import logging import sys from discord_host import create_bot sys.path.append("..\\lib") import msvcrt import os import traceback from mgylabs.db.database import run_migrations from mgylabs.db.paths import DB_URL, SCRIPT_DIR from mgylabs.services.telemetry_service import TelemetryReporter from mgylabs.utils.version import VERSION from core.controllers.ipc_controller import IPCController os.chdir(os.path.dirname(os.path.abspath(__file__))) log = logging.getLogger(__name__) def instance_already_running(): if VERSION.is_canary(): lock_name = "mkbot_can.lock" else: lock_name = "mkbot.lock" fd = os.open(f"{os.getenv('TEMP')}\\{lock_name}", os.O_WRONLY | os.O_CREAT) try: msvcrt.locking(fd, msvcrt.LK_NBLCK, 1) already_running = False except IOError: already_running = True return already_running async def dry_run(): errorlevel = await create_bot(True) return errorlevel def main(): if instance_already_running(): print("MKBotCore is already running.") sys.exit(0) run_migrations(SCRIPT_DIR, DB_URL) if "--dry-run" in sys.argv: errorlevel = asyncio.run(dry_run()) if errorlevel == 0: print("Test Passed") else: print("Test Failed") sys.exit(errorlevel) if "--port" in sys.argv: try: loc = sys.argv.index("--port") PORT = int(sys.argv[loc + 1]) except Exception: PORT = 8979 else: PORT = 8979 ipc_controller = IPCController(PORT) ipc_controller.run() if __name__ == "__main__": error = 0 try: TelemetryReporter.start() main() except SystemExit as e: error = e.code except Exception as e: TelemetryReporter.Exception(e) traceback.print_exc() error = 1 finally: TelemetryReporter.terminate() sys.exit(error)

793f648ec29ee752316e0fd3aa1702566bec1c78

py

Python

soft_sort/sinkhorn.py

deepneuralmachine/google-research

d2ce2cf0f5c004f8d78bfeddf6e88e88f4840231

2018-10-04T19:48:53.000Z

2022-03-31T21:27:42.000Z

soft_sort/sinkhorn.py

deepneuralmachine/google-research

d2ce2cf0f5c004f8d78bfeddf6e88e88f4840231

2018-11-10T06:16:13.000Z

2022-03-31T10:42:34.000Z

soft_sort/sinkhorn.py

deepneuralmachine/google-research

d2ce2cf0f5c004f8d78bfeddf6e88e88f4840231

2018-10-12T06:31:02.000Z

2022-03-31T13:59:28.000Z

# coding=utf-8 # Copyright 2021 The Google Research Authors. # # 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. # Lint as: python3 """A Sinkhorn implementation for 1D Optimal Transport. Sinkhorn algorithm was introduced in 1967 by R. Sinkhorn in the article "Diagonal equivalence to matrices with prescribed row and column sums." in The American Mathematical Monthly. It is an iterative algorithm that turns an input matrix (here the kernel matrix corresponding to transportation costs) into a matrix with prescribed (a, b) (row, colums) sum marginals by multiplying it on the left an right by two diagonal matrices. """ from typing import Tuple import gin import tensorflow.compat.v2 as tf def center(cost, f, g): if f.shape.rank == 2: return cost - f[:, :, tf.newaxis] - g[:, tf.newaxis, :] elif f.shape.rank == 3: return cost[:, :, :, tf.newaxis] - ( f[:, :, tf.newaxis, :] + g[:, tf.newaxis, :, :]) def softmin(cost, f, g, eps, axis): return -eps * tf.reduce_logsumexp(-center(cost, f, g) / eps, axis=axis) def error(cost, f, g, eps, b): b_target = tf.math.reduce_sum(transport(cost, f, g, eps), axis=1) return tf.reduce_max((tf.abs(b_target - b) / b)[:]) def transport(cost, f, g, eps): return tf.math.exp(-center(cost, f, g) / eps) def cost_fn(x, y, power): """A transport cost in the form |x-y|^p and its derivative.""" # Check if data is 1D. if x.shape.rank == 2 and y.shape.rank == 2: # If that is the case, it is convenient to use pairwise difference matrix. xy_difference = x[:, :, tf.newaxis] - y[:, tf.newaxis, :] if power == 1.0: cost = tf.math.abs(xy_difference) derivative = tf.math.sign(xy_difference) elif power == 2.0: cost = xy_difference**2.0 derivative = 2.0 * xy_difference else: abs_diff = tf.math.abs(xy_difference) cost = abs_diff**power derivative = power * tf.math.sign(xy_difference) * abs_diff**(power - 1.0) return cost, derivative # Otherwise data is high dimensional, in form [batch,n,d]. L2 distance used. elif x.shape.rank == 3 and y.shape.rank == 3: x2 = tf.reduce_sum(x**2, axis=2) y2 = tf.reduce_sum(y**2, axis=2) cost = (x2[:, :, tf.newaxis] + y2[:, tf.newaxis, :] - tf.matmul(x, y, transpose_b=True))**(power / 2) derivative = None return cost, derivative @gin.configurable def sinkhorn_iterations(x, y, a, b, power = 2.0, epsilon = 1e-3, epsilon_0 = 1e-1, epsilon_decay = 0.95, threshold = 1e-2, inner_num_iter = 5, max_iterations = 2000): """Runs the Sinkhorn's algorithm from (x, a) to (y, b). Args: x: Tensor<float>[batch, n, d]: the input point clouds. y: Tensor<float>[batch, m, d]: the target point clouds. a: Tensor<float>[batch, n, q]: weights of each input point across batch. Note that q possible variants can be considered (for parallelism). Sums along axis 1 must match that of b to converge. b: Tensor<float>[batch, m, q]: weights of each input point across batch. As with a, q possible variants of weights can be considered. power: (float) the power of the distance for the cost function. epsilon: (float) the level of entropic regularization wanted. epsilon_0: (float) the initial level of entropic regularization. epsilon_decay: (float) a multiplicative factor applied at each iteration until reaching the epsilon value. threshold: (float) the relative threshold on the Sinkhorn error to stop the Sinkhorn iterations. inner_num_iter: (int32) the Sinkhorn error is not recomputed at each iteration but every inner_num_iter instead to avoid computational overhead. max_iterations: (int32) the maximum number of Sinkhorn iterations. Returns: A 5-tuple containing: the values of the conjugate variables f and g, the final value of the entropic parameter epsilon, the cost matrix and the number of iterations. """ max_outer_iterations = max_iterations // inner_num_iter loga = tf.math.log(a) logb = tf.math.log(b) cost, d_cost = cost_fn(x, y, power) def body_fn(f, g, eps, num_iter): for _ in range(inner_num_iter): g = eps * logb + softmin(cost, f, g, eps, axis=1) + g f = eps * loga + softmin(cost, f, g, eps, axis=2) + f eps = tf.math.maximum(eps * epsilon_decay, epsilon) return [f, g, eps, num_iter + inner_num_iter] def cond_fn(f, g, eps, num_iter): return tf.math.reduce_all([ tf.math.less(num_iter, max_iterations), tf.math.reduce_any([ tf.math.greater(eps, epsilon), tf.math.greater(error(cost, f, g, eps, b), threshold) ]) ]) f, g, eps, iterations = tf.while_loop( cond_fn, body_fn, [ tf.zeros_like(loga), tf.zeros_like(logb), tf.cast(epsilon_0, dtype=x.dtype), tf.constant(0, dtype=tf.int32) ], parallel_iterations=1, maximum_iterations=max_outer_iterations + 1) return f, g, eps, cost, d_cost, iterations def transport_implicit_gradients(derivative_cost, transport_matrix, eps, b, d_p): """Application of the transpose of the Jacobians dP/dx and dP/db. This is applied to a perturbation of the size of the transport matrix. Required to back-propagate through Sinkhorn's output. Args: derivative_cost: the derivative of the cost function. transport_matrix: the obtained transport matrix tensor. eps: the value of the entropic regualarization parameter. b: the target weights. d_p: the perturbation of the transport matrix. Returns: A list of two tensor that correspond to the application of the transpose of dP/dx and dP/db on dP. """ batch_size = tf.shape(b)[0] m = tf.shape(b)[1] invmargin1 = tf.math.reciprocal(tf.reduce_sum(transport_matrix, axis=2)) m1 = invmargin1[:, 1:, tf.newaxis] * transport_matrix[:, 1:, :] m1 = tf.concat([tf.zeros([tf.shape(m1)[0], 1, tf.shape(m1)[2]]), m1], axis=1) invmargin2 = tf.math.reciprocal(tf.reduce_sum(transport_matrix, axis=1)) m2 = invmargin2[:, :, tf.newaxis] * tf.transpose(transport_matrix, [0, 2, 1]) eye_m = tf.eye(m, batch_shape=[batch_size]) schur = eye_m - tf.linalg.matmul(m2, m1) def jac_b_p_transpose(d_p): """Transposed of the jacobian of the transport w.r.t the target weights.""" d_p_p = d_p * transport_matrix u_f = tf.reduce_sum(d_p_p, axis=2) / eps u_g = tf.reduce_sum(d_p_p, axis=1) / eps m1_tranpose_u_f = tf.linalg.matvec(m1, u_f, transpose_a=True) to_invert = tf.concat( [m1_tranpose_u_f[:, :, tf.newaxis], u_g[:, :, tf.newaxis]], axis=2) inverses = tf.linalg.solve(tf.transpose(schur, [0, 2, 1]), to_invert) inv_m1_tranpose_u_f, inv_u_g = inverses[:, :, 0], inverses[:, :, 1] jac_2 = -inv_m1_tranpose_u_f + inv_u_g return eps * jac_2 / b def jac_x_p_transpose(d_p): """Transposed of the jacobian of the transport w.r.t the inputs.""" d_p_p = d_p * transport_matrix c_x = -tf.reduce_sum(derivative_cost * d_p_p, axis=2) / eps u_f = tf.math.reduce_sum(d_p_p, axis=2) / eps u_g = tf.math.reduce_sum(d_p_p, axis=1) / eps m1_tranpose_u_f = tf.linalg.matvec(m1, u_f, transpose_a=True) to_invert = tf.concat( [m1_tranpose_u_f[:, :, tf.newaxis], u_g[:, :, tf.newaxis]], axis=2) inverses = tf.linalg.solve(tf.transpose(schur, [0, 2, 1]), to_invert) inv_m1_tranpose_u_f, inv_u_g = inverses[:, :, 0], inverses[:, :, 1] jac_1 = u_f + tf.linalg.matvec( m2, inv_m1_tranpose_u_f - inv_u_g, transpose_a=True) jac_2 = -inv_m1_tranpose_u_f + inv_u_g jac_1 = jac_1 * tf.reduce_sum(m1 * derivative_cost, axis=2) jac_2 = tf.linalg.matvec( tf.transpose(m2, [0, 2, 1]) * derivative_cost, jac_2) return c_x + jac_1 + jac_2 return [jac_x_p_transpose(d_p), jac_b_p_transpose(d_p)] def autodiff_sinkhorn(x, y, a, b, **kwargs): """A Sinkhorn function that returns the transportation matrix. This function back-propagates through the computational graph defined by the Sinkhorn iterations. Args: x: [N, n, d] the input batch of points clouds y: [N, m, d] the target batch points clouds. a: [N, n, q] q probability weight vectors for the input point cloud. The sum of all elements of b along axis 1 must match that of a. b: [N, m, q] q probability weight vectors for the target point cloud. The sum of all elements of b along axis 1 must match that of a. **kwargs: additional parameters passed to the sinkhorn algorithm. See sinkhorn_iterations for more details. Returns: A tf.Tensor representing the optimal transport matrix and the regularized OT cost. """ f, g, eps, cost, _, _ = sinkhorn_iterations(x, y, a, b, **kwargs) return transport(cost, f, g, eps) def implicit_sinkhorn(x, y, a, b, **kwargs): """A Sinkhorn function using the implicit function theorem. That is to say differentiating optimality confiditions to recover Jacobians. Args: x: the input batch of 1D points clouds y: the target batch 1D points clouds. a: the intput weight of each point in the input point cloud. The sum of all elements of b must match that of a to converge. b: the target weight of each point in the target point cloud. The sum of all elements of b must match that of a to converge. **kwargs: additional parameters passed to the sinkhorn algorithm. See sinkhorn_iterations for more details. Returns: A tf.Tensor representing the optimal transport matrix. """ @tf.custom_gradient def _aux(x, b): """Auxiliary closure to compute custom gradient over x and b.""" x = tf.stop_gradient(x) b = tf.stop_gradient(b) f, g, eps, cost, d_cost, _ = sinkhorn_iterations(x, y, a, b, **kwargs) # This centering is crucial to ensure Jacobian is invertible. # This centering is also assumed in the computation of the # transpose-Jacobians themselves. to_remove = f[:, 0] f = f - to_remove[:, tf.newaxis] g = g + to_remove[:, tf.newaxis] forward = transport(cost, f, g, eps) def grad(d_p): return transport_implicit_gradients(d_cost, forward, eps, b, d_p) return forward, grad return _aux(x, b) @gin.configurable def sinkhorn(x, y, a, b, implicit = True, **kwargs): """A Sinkhorn function that returns the transportation matrix. This function back-propagates through the computational graph defined by the Sinkhorn iterations. Args: x: the input batch of points clouds y: the target batch points clouds. a: the intput weight of each point in the input point cloud. The sum of all elements of b must match that of a to converge. b: the target weight of each point in the target point cloud. The sum of all elements of b must match that of a to converge. implicit: whether to run the autodiff version of the backprop or the implicit computation of the gradient. The implicit version is more efficient in terms of both speed and memory, but might be less stable numerically. It requires high-accuracy in the computation of the optimal transport itself. **kwargs: additional parameters passed to the sinkhorn algorithm. See sinkhorn_iterations for more details. Returns: A tf.Tensor representing the optimal transport matrix. """ if implicit: if x.shape.rank == 2: return implicit_sinkhorn(x, y, a, b, **kwargs) else: raise ValueError('`Implicit` not yet implemented for multivariate data') return autodiff_sinkhorn(x, y, a, b, **kwargs) def sinkhorn_divergence(x, y, a, b, only_x_varies = False, **kwargs): """A simple implementation of the Sinkhorn divergence. This function back-propagates through the computational graph defined by the Sinkhorn iterations. Args: x: [N,n,d] the input batch of multivariate (dimension d) points clouds y: [N,m,d] the input batch of multivariate (dimension d) points clouds a: [N,n] probability weights per batch b: [N,n] probability weights per batch only_x_varies: <bool> if only x varies, that flag should be set to True, in order to avoid computing the divergence between y and itself. **kwargs: additional parameters passed to the sinkhorn algorithm. See sinkhorn_iterations for more details. Returns: A tf.Tensor representing the optimal transport matrix. """ f_xy, g_xy = sinkhorn_iterations(x, y, a, b, **kwargs)[:2] f_xx, g_xx = sinkhorn_iterations(x, x, a, a, **kwargs)[:2] if only_x_varies: return tf.reduce_sum((f_xy - 0.5 * f_xx - 0.5 * g_xx) * a + g_xy * b, axis=1) else: f_yy, g_yy = sinkhorn_iterations(y, y, b, b, **kwargs)[:2] return (tf.reduce_sum((f_xy - 0.5 * f_xx - 0.5 * g_xx) * a, axis=1) + tf.reduce_sum((g_xy - 0.5 * f_yy - 0.5 * g_yy) * b, axis=1))

793f658a971badf281adaa1a799ebc15d9327324

py

Python

ebirdtaiwan/dash_apps/TaipeiCompetition.py

even311379/EbirdTaiwan2020

2c1aa4d7346b5ade909d45f7c245fa4988394124

ebirdtaiwan/dash_apps/TaipeiCompetition.py

even311379/EbirdTaiwan2020

2c1aa4d7346b5ade909d45f7c245fa4988394124

ebirdtaiwan/dash_apps/TaipeiCompetition.py

even311379/EbirdTaiwan2020

2c1aa4d7346b5ade909d45f7c245fa4988394124

import dash import dash_core_components as dcc import dash_html_components as html from dash.dependencies import Input, Output, State from django_plotly_dash import DjangoDash import dash_bootstrap_components as dbc import plotly.graph_objs as go import random import json import pandas as pd import numpy as np import datetime from fall.models import SignupData, Survey, SurveyObs import plotly.express as px import re import eb_passwords from collections import Counter DEMO_MODE = True app = DjangoDash( 'ThreeTeams', add_bootstrap_links=True, ) # replaces dash.Dash # prevent setup complex map twice def empty_map(): fig = go.Figure(go.Scattermapbox(lat=['38.91427',],lon=['-77.02827',])) fig.update_layout( mapbox=dict( center=dict(lat=23.973793,lon=120.979703), zoom=8, style='white-bg') ) return fig def draw_area_map(): with open('../helper_files/TaiwanCounties_simple.geojson') as f: geoj = json.load(f) data = pd.DataFrame() NorthTaiwan_geo = [] for f in geoj['features']: if f['properties']['COUNTYNAME'] in ['新北市', '臺北市']: NorthTaiwan_geo.append(f) geoj['features'] = NorthTaiwan_geo RN = [] for k in range(len(geoj['features'])): temp = geoj['features'][k]['properties']['COUNTYNAME']+geoj['features'][k]['properties']['TOWNNAME'] geoj['features'][k]['id'] = temp RN.append(temp) # and insert id to df data['Name'] = RN ''' prepare the map data, the team color with most checklist in each town ''' if datetime.date.today() < datetime.date(2020, 10, 1): for t in ['彩鷸隊', '家燕隊', '大冠鷲隊']: data[t] = np.random.randint(5, 40, len(data)) else: temp_town = [] for t in ['彩鷸隊', '家燕隊', '大冠鷲隊']: temp_town.append(Survey.objects.filter(team=t, is_valid=True).values_list('county',flat=True)) if not temp_town[0] and not temp_town[1] and not temp_town[2]: return empty_map() for t in ['彩鷸隊', '家燕隊', '大冠鷲隊']: towns = Survey.objects.filter(team=t, is_valid=True).values_list('county',flat=True) county_counts = Counter(towns) nc = [0] * len(RN) for k in county_counts: nc[RN.index(k)] = county_counts[k] data[t] = nc winner = data[['彩鷸隊', '家燕隊', '大冠鷲隊']].idxmax(axis=1).tolist() # handles when the score are all the same BL = (data['彩鷸隊']==data['家燕隊']) & (data['家燕隊']==data['大冠鷲隊']) & (data['彩鷸隊']==data['大冠鷲隊']) for i, b in enumerate(BL): if b: winner[i] = '平手' data['winner'] = winner # data['winner'] = [random.choice(['A','B','C','E']) for i in range(len(data))] # t = [random.choice(['123','456','789','555']) for i in range(len(data))] area_map = px.choropleth_mapbox(data, geojson=geoj, color="winner", locations="Name",center={"lat": 24.9839, "lon":121.65}, mapbox_style="carto-positron", zoom=10, hover_data=['彩鷸隊', '家燕隊', '大冠鷲隊'], color_discrete_map={'彩鷸隊':'#2E92D3', '家燕隊':'#EF8018', '大冠鷲隊':'#FFF101','平手':'rgba(255,255,255,0.3)'}, ) area_map.update_traces( hovertemplate=''' <b>%{location}</b><br> 上傳清單數<br><br> 彩鷸隊: %{customdata[0]}<br> 家燕隊: %{customdata[1]}<br> 大冠鷲隊: %{customdata[2]}<extra></extra> ''', hoverlabel=dict(font=dict(size=16)), # showlegend=False, marker=dict(line=dict(width=1,color='#000')), ) area_map.update_layout( mapbox = dict( accesstoken=eb_passwords.map_box_api_key, ), margin={"r":0,"t":0,"l":0,"b":0}, legend=dict( title='上傳清單數比較', yanchor="top", y=0.99, xanchor="left", x=0.01, bgcolor='rgba(0,0,0,0)'), # this is a severe bug, dragmode = False should just remove drag, but its not working for me... ) return area_map dashboard_content = html.Div(dbc.Row([ dbc.Col([ html.Div([ html.Div(html.Img(src='/static/img/fall/farmbird.png', className='px-3'),className='team_card_col'), html.Div([ html.Div([html.Div('隊員人數：'), html.Div('',className='ml-auto', id='team1_n_people')], className='d-flex w-75 pb-2'), html.Div([html.Div('總上傳清單數：'),html.Div('',className='ml-auto', id='team1_n_list')], className='d-flex w-75 pb-2'), html.Div([html.Div('總上傳鳥種數:'),html.Div('',className='ml-auto', id='team1_n_species')], className='d-flex w-75 pb-2'), html.Div([html.Div('總上傳鳥隻數：'),html.Div('',className='ml-auto', id='team1_n_count')], className='d-flex w-75'), ], className='team_card_col') ],className='single_team_card'), html.Div([ html.Div(html.Img(src='/static/img/fall/citybird.png', className='px-3'),className='team_card_col'), html.Div([ html.Div([html.Div('隊員人數：'), html.Div('',className='ml-auto', id='team2_n_people')], className='d-flex w-75 pb-2'), html.Div([html.Div('總上傳清單數：'),html.Div('',className='ml-auto', id='team2_n_list')], className='d-flex w-75 pb-2'), html.Div([html.Div('總上傳鳥種數:'),html.Div('',className='ml-auto', id='team2_n_species')], className='d-flex w-75 pb-2'), html.Div([html.Div('總上傳鳥隻數：'),html.Div('',className='ml-auto', id='team2_n_count')], className='d-flex w-75'), ], className='team_card_col') ],className='single_team_card'), html.Div([ html.Div(html.Img(src='/static/img/fall/forestbird.png', className='px-3'),className='team_card_col'), html.Div([ html.Div([html.Div('隊員人數：'), html.Div('',className='ml-auto', id='team3_n_people')], className='d-flex w-75 pb-2'), html.Div([html.Div('總上傳清單數：'),html.Div('',className='ml-auto', id='team3_n_list')], className='d-flex w-75 pb-2'), html.Div([html.Div('總上傳鳥種數:'),html.Div('',className='ml-auto', id='team3_n_species')], className='d-flex w-75 pb-2'), html.Div([html.Div('總上傳鳥隻數：'),html.Div('',className='ml-auto', id='team3_n_count')], className='d-flex w-75'), ], className='team_card_col') ],className='single_team_card'), ], md=4), dbc.Col( dcc.Graph(figure = empty_map(),id='area_map', className='prgression_map', config=dict(displayModeBar=False)), className='' , md=8) ])) app.layout = html.Div([ html.Div(dashboard_content,className='dashboard_container'), dcc.Location(id='url'), html.Div('',id='empty',style={'display':'none'}) ] ) app.clientside_callback( """ function(path) { console.log(path) return path+',' + String(window.innerWidth) + ',' + String(window.innerHeight); } """, Output('empty', 'children'), [Input('url', 'pathname')] ) @app.callback( [Output('team1_n_people', 'children'), Output('team1_n_list', 'children'), Output('team1_n_species', 'children'), Output('team1_n_count', 'children'), Output('team2_n_people', 'children'), Output('team2_n_list', 'children'), Output('team2_n_species', 'children'), Output('team2_n_count', 'children'), Output('team3_n_people', 'children'), Output('team3_n_list', 'children'), Output('team3_n_species', 'children'), Output('team3_n_count', 'children'), Output('area_map','figure')], [Input('empty','children'),], ) def reload_refresh(helper_string): t1np = len(SignupData.objects.filter(team='彩鷸隊')) t2np = len(SignupData.objects.filter(team='家燕隊')) t3np = len(SignupData.objects.filter(team='大冠鷲隊')) if datetime.date.today() < datetime.date(2020,10,1): t1nl = 63 t1ns = 43 t1nc = 1204 t2nl = 53 t2ns = 51 t2nc = 1652 t3nl = 70 t3ns = 38 t3nc = 1301 else: t1nl = len(Survey.objects.filter(team='彩鷸隊', is_valid=True)) t1_rns = SurveyObs.objects.filter(survey__team = '彩鷸隊', survey__is_valid=True).values_list('species_name', flat=True) t1ns = len(set([re.sub(r' ?\(.*?\)','',s) for s in t1_rns])) t1nc = sum(SurveyObs.objects.filter(survey__team = '彩鷸隊', survey__is_valid=True).values_list('amount', flat=True)) t2nl = len(Survey.objects.filter(team='家燕隊', is_valid=True)) t2_rns = SurveyObs.objects.filter(survey__team = '家燕隊', survey__is_valid=True).values_list('species_name', flat=True) t2ns = len(set([re.sub(r' ?\(.*?\)','',s) for s in t2_rns])) t2nc = sum(SurveyObs.objects.filter(survey__team = '家燕隊', survey__is_valid=True).values_list('amount', flat=True)) t3nl = len(Survey.objects.filter(team='大冠鷲隊', is_valid=True)) t3_rns = SurveyObs.objects.filter(survey__team = '大冠鷲隊', survey__is_valid=True).values_list('species_name', flat=True) t3ns = len(set([re.sub(r' ?\(.*?\)','',s) for s in t3_rns])) t3nc = sum(SurveyObs.objects.filter(survey__team = '大冠鷲隊', survey__is_valid=True).values_list('amount', flat=True)) return t1np, t1nl, t1ns, t1nc, t2np, t2nl, t2ns, t2nc, t3np, t3nl, t3ns, t3nc, draw_area_map()

793f65a7de5440917b3f9e1d1480c8aebb966844

py

Python

supervisor/resolution/validate.py

peddamat/home-assistant-supervisor-test

5da55772bcb2db3c6d8432cbc08e2ac9fbf480c4

2021-09-22T00:15:17.000Z

2021-09-22T00:15:17.000Z

supervisor/resolution/validate.py

peddamat/home-assistant-supervisor-test

5da55772bcb2db3c6d8432cbc08e2ac9fbf480c4

2021-07-22T06:14:22.000Z

2022-03-31T06:16:16.000Z

supervisor/resolution/validate.py

peddamat/home-assistant-supervisor-test

5da55772bcb2db3c6d8432cbc08e2ac9fbf480c4

2021-09-22T00:13:58.000Z

2021-09-22T15:06:27.000Z

"""Validate resolution configuration schema.""" from pathlib import Path from typing import List import voluptuous as vol from ..const import ATTR_CHECKS, ATTR_ENABLED def get_valid_modules(folder) -> List[str]: """Validate check name.""" module_files = Path(__file__).parent.joinpath(folder) if not module_files.exists(): raise vol.Invalid(f"Module folder '{folder}' not found!") return [ module.stem for module in module_files.glob("*.py") if module.name not in ("base.py", "__init__.py") ] SCHEMA_CHECK_CONFIG = vol.Schema( { vol.Required(ATTR_ENABLED, default=True): bool, }, extra=vol.REMOVE_EXTRA, ) SCHEMA_CHECKS_CONFIG = vol.Schema( { vol.Required(check, default=SCHEMA_CHECK_CONFIG({})): SCHEMA_CHECK_CONFIG for check in get_valid_modules("checks") }, extra=vol.REMOVE_EXTRA, ) SCHEMA_RESOLUTION_CONFIG = vol.Schema( { vol.Required( ATTR_CHECKS, default=SCHEMA_CHECKS_CONFIG({}) ): SCHEMA_CHECKS_CONFIG, }, extra=vol.REMOVE_EXTRA, )

793f66281a5b6b93bd58388bd8810165bff33d87

py

Python

regexlib/2021-5-15/python_re2_test_file/regexlib_8347.py

yetingli/ReDoS-Benchmarks

f5b5094d835649e957bf3fec6b8bd4f6efdb35fc

2022-01-24T14:43:23.000Z

2022-01-24T14:43:23.000Z

regexlib/2021-5-15/python_re2_test_file/regexlib_8347.py

yetingli/ReDoS-Benchmarks

f5b5094d835649e957bf3fec6b8bd4f6efdb35fc

regexlib/2021-5-15/python_re2_test_file/regexlib_8347.py

yetingli/ReDoS-Benchmarks

f5b5094d835649e957bf3fec6b8bd4f6efdb35fc

# 8347 # (?i)(?s)<a[^>]+?href="?(?<url>[^"]+)"?>(?<innerHtml>.+?)</a\s*> # POLYNOMIAL # nums:5 # POLYNOMIAL AttackString:""+"is<a"*5000+"@1 _SLQ_2" import re2 as re from time import perf_counter regex = """(?i)(?s)<a[^>]+?href="?(?<url>[^"]+)"?>(?<innerHtml>.+?)</a\s*>""" REGEX = re.compile(regex) for i in range(0, 150000): ATTACK = "" + "is<a" * i * 10000 + "@1 _SLQ_2" LEN = len(ATTACK) BEGIN = perf_counter() m = REGEX.search(ATTACK) # m = REGEX.match(ATTACK) DURATION = perf_counter() - BEGIN print(f"{i *10000}: took {DURATION} seconds!")

793f66d0f2bbc6ea08da45e55aaf36870e67a256

py

Python

otcextensions/sdk/dws/v1/flavor.py

zsoltn/python-otcextensions

4c0fa22f095ebd5f9636ae72acbae5048096822c

otcextensions/sdk/dws/v1/flavor.py

zsoltn/python-otcextensions

4c0fa22f095ebd5f9636ae72acbae5048096822c

otcextensions/sdk/dws/v1/flavor.py

zsoltn/python-otcextensions

4c0fa22f095ebd5f9636ae72acbae5048096822c

# 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. from openstack import exceptions from openstack import resource class FlavorSpec(resource.Resource): #: type of the value mtype = resource.Body('type') #: type of the value mvalue = resource.Body('value') #: unit of the value munit = resource.Body('unit') def __str__(self): return self.mtype class Flavor(resource.Resource): base_path = '/node_types' resources_key = 'node_types' allow_list = True # Properties #: Spec name. *Type: str* spec_name = resource.Body('spec_name') #: detail. *Type: str* detail = resource.Body('detail', type=list, list_type=FlavorSpec)

793f66dce80ceff06f76e9cda0246ed1d93b4b27

py

Python

pyTD/market/__init__.py

kevmartian/pyTD

ea8f374a0c9eddf5a46233f5946e68a67c181009

2018-10-25T06:03:56.000Z

2021-06-14T03:53:01.000Z

pyTD/market/__init__.py

td-ameritrade/pyTD

28099664c8a3b6b7e60f62f5e5c120f01e3530af

2018-11-11T19:34:25.000Z

2021-01-16T03:39:45.000Z

pyTD/market/__init__.py

td-ameritrade/pyTD

28099664c8a3b6b7e60f62f5e5c120f01e3530af

2019-03-12T04:16:40.000Z

2021-04-15T20:26:04.000Z

# MIT License # Copyright (c) 2018 Addison Lynch # 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 pyTD.instruments.base import Instruments from pyTD.market.hours import MarketHours from pyTD.market.quotes import Quotes from pyTD.market.movers import Movers from pyTD.market.options import Options from pyTD.market.price_history import PriceHistory def get_fundamentals(*args, **kwargs): """ Retrieve fundamental data for a diven symbol or CUSIP ID Parameters ---------- symbol: str A CUSIP ID, symbol, regular expression, or snippet (depends on the value of the "projection" variable) output_format: str, default "pandas", optional Desired output format. "pandas" or "json" """ kwargs.update({"projection": "fundamental"}) return Instruments(*args, **kwargs).execute() def get_quotes(*args, **kwargs): """ Function for retrieving quotes from the Get Quotes endpoint. Parameters ---------- symbols : str, array-like object (list, tuple, Series), or DataFrame Single stock symbol (ticker), array-like object of symbols or DataFrame with index containing up to 100 stock symbols. output_format: str, default 'pandas', optional Desired output format (json or DataFrame) kwargs: additional request parameters (see _TDBase class) """ return Quotes(*args, **kwargs).execute() def get_market_hours(*args, **kwargs): """ Function to retrieve market hours for a given market from the Market Hours endpoint Parameters ---------- market: str, default EQUITY, optional The market to retrieve operating hours for date : string or DateTime object, (defaults to today's date) Operating date, timestamp. Parses many different kind of date representations (e.g., 'JAN-01-2015', '1/1/15', 'Jan, 1, 1980') output_format: str, default 'pandas', optional Desired output format (json or DataFrame) kwargs: additional request parameters (see _TDBase class) """ return MarketHours(*args, **kwargs).execute() def get_movers(*args, **kwargs): """ Function for retrieving market moveers from the Movers endpoint Parameters ---------- index: str The index symbol to get movers from direction: str, default up, optional Return up or down movers change: str, default percent, optional Return movers by percent change or value change output_format: str, default 'pandas', optional Desired output format (json or DataFrame) kwargs: additional request parameters (see _TDBase class) """ return Movers(*args, **kwargs).execute() def get_option_chains(*args, **kwargs): """ Function to retrieve option chains for a given symbol from the Option Chains endpoint Parameters ---------- contractType: str, default ALL, optional Desired contract type (CALL, PUT, ALL) strikeCount: int, optional Number of strikes to return above and below the at-the-money price includeQuotes: bool, default False, optional Include quotes for options in the option chain strategy: str, default None, optional Passing a value returns a strategy chain (SINGLE or ANALYTICAL) interval: int, optional Strike interval for spread strategy chains strike: float, optional Filter options that only have a certain strike price range: str, optional Returns options for a given range (ITM, OTM, etc.) fromDate: str or datetime.datetime object, optional Only return options after this date toDate: str or datetime.datetime object, optional Only return options before this date volatility: float, optional Volatility to use in calculations (for analytical strategy chains) underlyingPrice: float, optional Underlying price to use in calculations (for analytical strategy chains) interestRate: float, optional Interest rate to use in calculations (for analytical strategy chains) daysToExpiration: int, optional Days to expiration to use in calulations (for analytical strategy chains) expMonth: str, optional Expiration month (format JAN, FEB, etc.) to use in calculations (for analytical strategy chains), default ALL optionType: str, optional Type of contracts to return (S: standard, NS: nonstandard, ALL: all contracts) output_format: str, optional, default 'pandas' Desired output format api: pyTD.api.api object, optional A pyTD api object. If not passed, API requestor defaults to pyTD.api.default_api kwargs: additional request parameters (see _TDBase class) """ return Options(*args, **kwargs).execute() def get_price_history(*args, **kwargs): """ Function to retrieve price history for a given symbol over a given period Parameters ---------- symbols : string, array-like object (list, tuple, Series), or DataFrame Desired symbols for retrieval periodType: str, default DAY, optional The type of period to show period: int, optional The number of periods to show frequencyType: str, optional The type of frequency with which a new candle is formed frequency: int, optional The number of frequencyType to includ with each candle startDate : string or DateTime object, optional Starting date, timestamp. Parses many different kind of date representations (e.g., 'JAN-01-2015', '1/1/15', 'Jan, 1, 1980') endDate : string or DateTime object, optional Ending date, timestamp. Parses many different kind of date representations (e.g., 'JAN-01-2015', '1/1/15', 'Jan, 1, 1980') extended: str or bool, default 'True'/True, optional True to return extended hours data, False for regular hours only output_format: str, default 'pandas', optional Desired output format (json or DataFrame) """ return PriceHistory(*args, **kwargs).execute() # def get_history_intraday(symbols, start, end, interval='1m', extended=True, # output_format='pandas'): # """ # Function to retrieve intraday price history for a given symbol # Parameters # ---------- # symbols : string, array-like object (list, tuple, Series), or DataFrame # Desired symbols for retrieval # startDate : string or DateTime object, optional # Starting date, timestamp. Parses many different kind of date # representations (e.g., 'JAN-01-2015', '1/1/15', 'Jan, 1, 1980') # endDate : string or DateTime object, optional # Ending date, timestamp. Parses many different kind of date # representations (e.g., 'JAN-01-2015', '1/1/15', 'Jan, 1, 1980') # interval: string, default '1m', optional # Desired interval (1m, 5m, 15m, 30m, 60m) # needExtendedHoursData: str or bool, default 'True'/True, optional # True to return extended hours data, False for regular hours only # output_format: str, default 'pandas', optional # Desired output format (json or DataFrame) # """ # result = PriceHistory(symbols, start_date=start, end_date=end, # extended=extended, # output_format=output_format).execute() # if interval == '1m': # return result # elif interval == '5m': # sample = result.index.floor('5T').drop_duplicates() # return result.reindex(sample, method='ffill') # elif interval == '15m': # sample = result.index.floor('15T').drop_duplicates() # return result.reindex(sample, method='ffill') # elif interval == '30m': # sample = result.index.floor('30T').drop_duplicates() # return result.reindex(sample, method='ffill') # elif interval == '60m': # sample = result.index.floor('60T').drop_duplicates() # return result.reindex(sample, method='ffill') # else: # raise ValueError("Interval must be 1m, 5m, 15m, 30m, or 60m.") # def get_history_daily(symbols, start, end, output_format='pandas'): # return PriceHistory(symbols, start_date=start, end_date=end, # frequency_type='daily', # output_format=output_format).execute()

793f66e0db6132f4f891ae834a6bd6e9ceec3e59

py

Python

sample.py

Doctorado-ML/mufs

a0f172ac13870043494050ad988a279369043e1b

2021-11-25T12:29:28.000Z

2022-03-09T21:50:09.000Z

sample.py

Doctorado-ML/mfs

a0f172ac13870043494050ad988a279369043e1b

2021-10-05T09:25:12.000Z

2022-03-10T11:50:58.000Z

sample.py

Doctorado-ML/mufs

a0f172ac13870043494050ad988a279369043e1b

import warnings import time from mufs import MUFS from mufs.Metrics import Metrics from stree import Stree import numpy as np from scipy.io import arff mufsc = MUFS(discrete=False) filename = "conn-bench-sonar-mines-rocks.arff" data, meta = arff.loadarff(filename) train = np.array([data[i] for i in meta]) X = train.T X = X[:, :-1].astype("float64") y = data["clase"] m, n = X.shape print("* Differential entropy in X") for i in range(n): print(i, Metrics.differential_entropy(X[:, i], k=10)) print("* Information Gain") print("- Continuous features") print(Metrics.information_gain_cont(X, y)) for i in range(n): print(i, Metrics.information_gain_cont(X[:, i], y)) # Classification warnings.filterwarnings("ignore") print("CFS") now = time.time() cfs_f = mufsc.cfs(X, y).get_results() time_cfs = time.time() - now print(cfs_f, "items: ", len(cfs_f), f"time: {time_cfs:.3f} seconds") print("FCBF") now = time.time() fcbf_f = mufsc.fcbf(X, y, 0.07).get_results() time_fcbf = time.time() - now print(fcbf_f, "items: ", len(fcbf_f), f"time: {time_fcbf:.3f} seconds") now = time.time() print("IWSS") iwss_f = mufsc.iwss(X, y, 0.5).get_results() time_iwss = time.time() - now print(iwss_f, "items: ", len(iwss_f), f"time: {time_iwss:.3f} seconds") print("X.shape=", X.shape) clf = Stree(random_state=0) print("Accuracy whole dataset", clf.fit(X, y).score(X, y)) clf = Stree(random_state=0) print("Accuracy cfs", clf.fit(X[:, cfs_f], y).score(X[:, cfs_f], y)) clf = Stree(random_state=0) print("Accuracy fcfb", clf.fit(X[:, fcbf_f], y).score(X[:, fcbf_f], y)) clf = Stree(random_state=0) print("Accuracy iwss", clf.fit(X[:, iwss_f], y).score(X[:, iwss_f], y))

793f6750e1d8e7a8b07b706c585b75014363c484

py

Python

testing/test_run_facpro.py

hmedal/speu2

7b4a4507e098154161f072465507aa425f56d2b9

testing/test_run_facpro.py

hmedal/speu2

7b4a4507e098154161f072465507aa425f56d2b9

testing/test_run_facpro.py

hmedal/speu2

7b4a4507e098154161f072465507aa425f56d2b9

import argparse import os from examples.facility_protection.params import generate_probs_and_scens_files from modeling import speu import json import unittest class Test_FacPro(unittest.TestCase): def test_run_deterministic_equivalent(self): os.chdir('../examples/facility_protection') print "cwd", os.getcwd() debug = True expr_file = "expr_scripts_for_paper/baseExperimentParameters.json" params_dict = json.loads(open(expr_file).read()) num_facs = params_dict["num_facs"] num_cap_levels = params_dict["num_states"] num_allocation_levels = params_dict["num_allocation_levels"] scens_file = 'params/fac_pro_scens_' + generate_probs_and_scens_files.get_params_string_scens(num_facs, num_cap_levels) + '.json' probs_file = 'params/fac_pro_probs_and_costs_' + generate_probs_and_scens_files.get_params_string_probs( num_allocation_levels, num_cap_levels) + '.json' model = speu.create_model_object(True, expr_file, scens_file, probs_file, debug) model.solve() def test_run_saa(self): os.chdir('../examples/facility_protection') print "cwd", os.getcwd() debug = True expr_file = "expr_scripts_for_paper/baseExperimentParameters.json" params_dict = json.loads(open(expr_file).read()) num_facs = params_dict["num_facs"] num_cap_levels = params_dict["num_states"] num_allocation_levels = params_dict["num_allocation_levels"] scens_file = 'params/fac_pro_scens_saa_' + generate_probs_and_scens_files.get_params_string_scens(num_facs, num_cap_levels) + '.json' probs_file = 'params/fac_pro_probs_and_costs_' + generate_probs_and_scens_files.get_params_string_probs( num_allocation_levels, num_cap_levels) + '.json' model = speu.create_model_object(True, expr_file, scens_file, probs_file, debug) model.solve()

793f68fcc9d3b832358b91523c2780e370f8683a

py

Python

zappa/utilities.py

wangsha/Zappa

cfd311b084b38ca8c51f4381f1c96e23f0add307

zappa/utilities.py

wangsha/Zappa

cfd311b084b38ca8c51f4381f1c96e23f0add307

zappa/utilities.py

wangsha/Zappa

cfd311b084b38ca8c51f4381f1c96e23f0add307

import botocore import calendar import datetime import durationpy import fnmatch import io import json import logging import os import re import shutil import stat import sys from past.builtins import basestring from urllib.parse import urlparse LOG = logging.getLogger(__name__) ## # Settings / Packaging ## def copytree(src, dst, metadata=True, symlinks=False, ignore=None): """ This is a contributed re-implementation of 'copytree' that should work with the exact same behavior on multiple platforms. When `metadata` is False, file metadata such as permissions and modification times are not copied. """ def copy_file(src, dst, item): s = os.path.join(src, item) d = os.path.join(dst, item) if symlinks and os.path.islink(s): # pragma: no cover if os.path.lexists(d): os.remove(d) os.symlink(os.readlink(s), d) if metadata: try: st = os.lstat(s) mode = stat.S_IMODE(st.st_mode) os.lchmod(d, mode) except: pass # lchmod not available elif os.path.isdir(s): copytree(s, d, metadata, symlinks, ignore) else: shutil.copy2(s, d) if metadata else shutil.copy(s, d) try: lst = os.listdir(src) if not os.path.exists(dst): os.makedirs(dst) if metadata: shutil.copystat(src, dst) except NotADirectoryError: # egg-link files copy_file(os.path.dirname(src), os.path.dirname(dst), os.path.basename(src)) return if ignore: excl = ignore(src, lst) lst = [x for x in lst if x not in excl] for item in lst: copy_file(src, dst, item) def parse_s3_url(url): """ Parses S3 URL. Returns bucket (domain) and file (full path). """ bucket = '' path = '' if url: result = urlparse(url) bucket = result.netloc path = result.path.strip('/') return bucket, path def human_size(num, suffix='B'): """ Convert bytes length to a human-readable version """ for unit in ('', 'Ki', 'Mi', 'Gi', 'Ti', 'Pi', 'Ei', 'Zi'): if abs(num) < 1024.0: return "{0:3.1f}{1!s}{2!s}".format(num, unit, suffix) num /= 1024.0 return "{0:.1f}{1!s}{2!s}".format(num, 'Yi', suffix) def string_to_timestamp(timestring): """ Accepts a str, returns an int timestamp. """ ts = None # Uses an extended version of Go's duration string. try: delta = durationpy.from_str(timestring); past = datetime.datetime.utcnow() - delta ts = calendar.timegm(past.timetuple()) return ts except Exception as e: pass if ts: return ts # else: # print("Unable to parse timestring.") return 0 ## # `init` related ## def detect_django_settings(): """ Automatically try to discover Django settings files, return them as relative module paths. """ matches = [] for root, dirnames, filenames in os.walk(os.getcwd()): for filename in fnmatch.filter(filenames, '*settings.py'): full = os.path.join(root, filename) if 'site-packages' in full: continue full = os.path.join(root, filename) package_path = full.replace(os.getcwd(), '') package_module = package_path.replace(os.sep, '.').split('.', 1)[1].replace('.py', '') matches.append(package_module) return matches def detect_flask_apps(): """ Automatically try to discover Flask apps files, return them as relative module paths. """ matches = [] for root, dirnames, filenames in os.walk(os.getcwd()): for filename in fnmatch.filter(filenames, '*.py'): full = os.path.join(root, filename) if 'site-packages' in full: continue full = os.path.join(root, filename) with io.open(full, 'r', encoding='utf-8') as f: lines = f.readlines() for line in lines: app = None # Kind of janky.. if '= Flask(' in line: app = line.split('= Flask(')[0].strip() if '=Flask(' in line: app = line.split('=Flask(')[0].strip() if not app: continue package_path = full.replace(os.getcwd(), '') package_module = package_path.replace(os.sep, '.').split('.', 1)[1].replace('.py', '') app_module = package_module + '.' + app matches.append(app_module) return matches def get_venv_from_python_version(): return 'python{}.{}'.format(*sys.version_info) def get_runtime_from_python_version(): """ """ if sys.version_info[0] < 3: raise ValueError("Python 2.x is no longer supported.") else: if sys.version_info[1] <= 6: return 'python3.6' elif sys.version_info[1] <= 7: return 'python3.7' elif sys.version_info[1] <= 8: return 'python3.8' else: return "python3.9" ## # Async Tasks ## def get_topic_name(lambda_name): """ Topic name generation """ return '%s-zappa-async' % lambda_name ## # Event sources / Kappa ## def get_event_source(event_source, lambda_arn, target_function, boto_session, dry=False): """ Given an event_source dictionary item, a session and a lambda_arn, hack into Kappa's Gibson, create out an object we can call to schedule this event, and return the event source. """ import kappa.function import kappa.restapi import kappa.event_source.base import kappa.event_source.dynamodb_stream import kappa.event_source.kinesis import kappa.event_source.s3 import kappa.event_source.sns import kappa.event_source.cloudwatch import kappa.policy import kappa.role import kappa.awsclient class PseudoContext: def __init__(self): return class PseudoFunction: def __init__(self): return # Mostly adapted from kappa - will probably be replaced by kappa support class SqsEventSource(kappa.event_source.base.EventSource): def __init__(self, context, config): super().__init__(context, config) self._lambda = kappa.awsclient.create_client( 'lambda', context.session) def _get_uuid(self, function): uuid = None response = self._lambda.call( 'list_event_source_mappings', FunctionName=function.name, EventSourceArn=self.arn) LOG.debug(response) if len(response['EventSourceMappings']) > 0: uuid = response['EventSourceMappings'][0]['UUID'] return uuid def add(self, function): try: response = self._lambda.call( 'create_event_source_mapping', FunctionName=function.name, EventSourceArn=self.arn, BatchSize=self.batch_size, Enabled=self.enabled ) LOG.debug(response) except Exception: LOG.exception('Unable to add event source') def enable(self, function): self._config['enabled'] = True try: response = self._lambda.call( 'update_event_source_mapping', UUID=self._get_uuid(function), Enabled=self.enabled ) LOG.debug(response) except Exception: LOG.exception('Unable to enable event source') def disable(self, function): self._config['enabled'] = False try: response = self._lambda.call( 'update_event_source_mapping', FunctionName=function.name, Enabled=self.enabled ) LOG.debug(response) except Exception: LOG.exception('Unable to disable event source') def update(self, function): response = None uuid = self._get_uuid(function) if uuid: try: response = self._lambda.call( 'update_event_source_mapping', BatchSize=self.batch_size, Enabled=self.enabled, FunctionName=function.arn) LOG.debug(response) except Exception: LOG.exception('Unable to update event source') def remove(self, function): response = None uuid = self._get_uuid(function) if uuid: response = self._lambda.call( 'delete_event_source_mapping', UUID=uuid) LOG.debug(response) return response def status(self, function): response = None LOG.debug('getting status for event source %s', self.arn) uuid = self._get_uuid(function) if uuid: try: response = self._lambda.call( 'get_event_source_mapping', UUID=self._get_uuid(function)) LOG.debug(response) except botocore.exceptions.ClientError: LOG.debug('event source %s does not exist', self.arn) response = None else: LOG.debug('No UUID for event source %s', self.arn) return response class ExtendedSnsEventSource(kappa.event_source.sns.SNSEventSource): @property def filters(self): return self._config.get('filters') def add_filters(self, function): try: subscription = self.exists(function) if subscription: response = self._sns.call( 'set_subscription_attributes', SubscriptionArn=subscription['SubscriptionArn'], AttributeName='FilterPolicy', AttributeValue=json.dumps(self.filters) ) kappa.event_source.sns.LOG.debug(response) except Exception: kappa.event_source.sns.LOG.exception('Unable to add filters for SNS topic %s', self.arn) def add(self, function): super().add(function) if self.filters: self.add_filters(function) event_source_map = { 'dynamodb': kappa.event_source.dynamodb_stream.DynamoDBStreamEventSource, 'kinesis': kappa.event_source.kinesis.KinesisEventSource, 's3': kappa.event_source.s3.S3EventSource, 'sns': ExtendedSnsEventSource, 'sqs': SqsEventSource, 'events': kappa.event_source.cloudwatch.CloudWatchEventSource } arn = event_source['arn'] _, _, svc, _ = arn.split(':', 3) event_source_func = event_source_map.get(svc, None) if not event_source_func: raise ValueError('Unknown event source: {0}'.format(arn)) def autoreturn(self, function_name): return function_name event_source_func._make_notification_id = autoreturn ctx = PseudoContext() ctx.session = boto_session funk = PseudoFunction() funk.name = lambda_arn # Kappa 0.6.0 requires this nasty hacking, # hopefully we can remove at least some of this soon. # Kappa 0.7.0 introduces a whole host over other changes we don't # really want, so we're stuck here for a little while. # Related: https://github.com/Miserlou/Zappa/issues/684 # https://github.com/Miserlou/Zappa/issues/688 # https://github.com/Miserlou/Zappa/commit/3216f7e5149e76921ecdf9451167846b95616313 if svc == 's3': split_arn = lambda_arn.split(':') arn_front = ':'.join(split_arn[:-1]) arn_back = split_arn[-1] ctx.environment = arn_back funk.arn = arn_front funk.name = ':'.join([arn_back, target_function]) else: funk.arn = lambda_arn funk._context = ctx event_source_obj = event_source_func(ctx, event_source) return event_source_obj, ctx, funk def add_event_source(event_source, lambda_arn, target_function, boto_session, dry=False): """ Given an event_source dictionary, create the object and add the event source. """ event_source_obj, ctx, funk = get_event_source(event_source, lambda_arn, target_function, boto_session, dry=False) # TODO: Detect changes in config and refine exists algorithm if not dry: if not event_source_obj.status(funk): event_source_obj.add(funk) return 'successful' if event_source_obj.status(funk) else 'failed' else: return 'exists' return 'dryrun' def remove_event_source(event_source, lambda_arn, target_function, boto_session, dry=False): """ Given an event_source dictionary, create the object and remove the event source. """ event_source_obj, ctx, funk = get_event_source(event_source, lambda_arn, target_function, boto_session, dry=False) # This is slightly dirty, but necessary for using Kappa this way. funk.arn = lambda_arn if not dry: rule_response = event_source_obj.remove(funk) return rule_response else: return event_source_obj def get_event_source_status(event_source, lambda_arn, target_function, boto_session, dry=False): """ Given an event_source dictionary, create the object and get the event source status. """ event_source_obj, ctx, funk = get_event_source(event_source, lambda_arn, target_function, boto_session, dry=False) return event_source_obj.status(funk) ## # Analytics / Surveillance / Nagging ## def check_new_version_available(this_version): """ Checks if a newer version of Zappa is available. Returns True is updateable, else False. """ import requests pypi_url = 'https://pypi.org/pypi/Zappa/json' resp = requests.get(pypi_url, timeout=1.5) top_version = resp.json()['info']['version'] return this_version != top_version class InvalidAwsLambdaName(Exception): """Exception: proposed AWS Lambda name is invalid""" pass def validate_name(name, maxlen=80): """Validate name for AWS Lambda function. name: actual name (without `arn:aws:lambda:...:` prefix and without `:$LATEST`, alias or version suffix. maxlen: max allowed length for name without prefix and suffix. The value 80 was calculated from prefix with longest known region name and assuming that no alias or version would be longer than `$LATEST`. Based on AWS Lambda spec http://docs.aws.amazon.com/lambda/latest/dg/API_CreateFunction.html Return: the name Raise: InvalidAwsLambdaName, if the name is invalid. """ if not isinstance(name, basestring): msg = "Name must be of type string" raise InvalidAwsLambdaName(msg) if len(name) > maxlen: msg = "Name is longer than {maxlen} characters." raise InvalidAwsLambdaName(msg.format(maxlen=maxlen)) if len(name) == 0: msg = "Name must not be empty string." raise InvalidAwsLambdaName(msg) if not re.match("^[a-zA-Z0-9-_]+$", name): msg = "Name can only contain characters from a-z, A-Z, 0-9, _ and -" raise InvalidAwsLambdaName(msg) return name def contains_python_files_or_subdirs(folder): """ Checks (recursively) if the directory contains .py or .pyc files """ for root, dirs, files in os.walk(folder): if [filename for filename in files if filename.endswith('.py') or filename.endswith('.pyc')]: return True for d in dirs: for _, subdirs, subfiles in os.walk(d): if [filename for filename in subfiles if filename.endswith('.py') or filename.endswith('.pyc')]: return True return False def conflicts_with_a_neighbouring_module(directory_path): """ Checks if a directory lies in the same directory as a .py file with the same name. """ parent_dir_path, current_dir_name = os.path.split(os.path.normpath(directory_path)) neighbours = os.listdir(parent_dir_path) conflicting_neighbour_filename = current_dir_name+'.py' return conflicting_neighbour_filename in neighbours # https://github.com/Miserlou/Zappa/issues/1188 def titlecase_keys(d): """ Takes a dict with keys of type str and returns a new dict with all keys titlecased. """ return {k.title(): v for k, v in d.items()} # https://github.com/Miserlou/Zappa/issues/1688 def is_valid_bucket_name(name): """ Checks if an S3 bucket name is valid according to https://docs.aws.amazon.com/AmazonS3/latest/dev/BucketRestrictions.html#bucketnamingrules """ # Bucket names must be at least 3 and no more than 63 characters long. if (len(name) < 3 or len(name) > 63): return False # Bucket names must not contain uppercase characters or underscores. if (any(x.isupper() for x in name)): return False if "_" in name: return False # Bucket names must start with a lowercase letter or number. if not (name[0].islower() or name[0].isdigit()): return False # Bucket names must be a series of one or more labels. Adjacent labels are separated by a single period (.). for label in name.split("."): # Each label must start and end with a lowercase letter or a number. if len(label) < 1: return False if not (label[0].islower() or label[0].isdigit()): return False if not (label[-1].islower() or label[-1].isdigit()): return False # Bucket names must not be formatted as an IP address (for example, 192.168.5.4). looks_like_IP = True for label in name.split("."): if not label.isdigit(): looks_like_IP = False break if looks_like_IP: return False return True def merge_headers(event): """ Merge the values of headers and multiValueHeaders into a single dict. Opens up support for multivalue headers via API Gateway and ALB. See: https://github.com/Miserlou/Zappa/pull/1756 """ headers = event.get('headers') or {} multi_headers = (event.get('multiValueHeaders') or {}).copy() for h in set(headers.keys()): if h not in multi_headers: multi_headers[h] = [headers[h]] for h in multi_headers.keys(): multi_headers[h] = ', '.join(multi_headers[h]) return multi_headers

793f6926ab932618a83e95c40989d4b314413217

py

Python

backend/home/migrations/0001_load_initial_data.py

crowdbotics-apps/musix-32595

cdc9560eb55a71d6b2d8291892fe478b63b30c80

backend/home/migrations/0001_load_initial_data.py

crowdbotics-apps/musix-32595

cdc9560eb55a71d6b2d8291892fe478b63b30c80

backend/home/migrations/0001_load_initial_data.py

crowdbotics-apps/musix-32595

cdc9560eb55a71d6b2d8291892fe478b63b30c80

from django.db import migrations def create_site(apps, schema_editor): Site = apps.get_model("sites", "Site") custom_domain = "musix-32595.botics.co" site_params = { "name": "Musix", } if custom_domain: site_params["domain"] = custom_domain Site.objects.update_or_create(defaults=site_params, id=1) class Migration(migrations.Migration): dependencies = [ ("sites", "0002_alter_domain_unique"), ] operations = [ migrations.RunPython(create_site), ]

793f6a082529dac1d28f051a27b8b492d78f2bbc

py

Python

tests/zoomus/components/test_base.py

dolohow/zoomus

8498a26af48c2f09957464848d2e8fbf0a034d08

2020-04-13T17:12:13.000Z

2022-03-30T05:55:30.000Z

tests/zoomus/components/test_base.py

dolohow/zoomus

8498a26af48c2f09957464848d2e8fbf0a034d08

2020-04-14T07:37:03.000Z

2022-03-29T02:13:43.000Z

tests/zoomus/components/test_base.py

dolohow/zoomus

8498a26af48c2f09957464848d2e8fbf0a034d08

2020-04-14T09:24:19.000Z

2022-03-24T18:33:48.000Z

import unittest from zoomus import components, util import responses def suite(): """Define all the tests of the module.""" suite = unittest.TestSuite() suite.addTest(unittest.makeSuite(BaseComponentTestCase)) return suite class BaseComponentTestCase(unittest.TestCase): @responses.activate def test_post_request_includes_config_details_in_data_when_no_data(self): component = components.base.BaseComponent( base_uri="http://www.foo.com", config={ "api_key": "KEY", "api_secret": "SECRET", "version": util.API_VERSION_1, }, ) responses.add( responses.POST, "http://www.foo.com/foo?api_key=KEY&api_secret=SECRET" ) component.post_request("foo") @responses.activate def test_post_request_includes_config_details_in_data_when_there_is_data(self): component = components.base.BaseComponent( base_uri="http://www.foo.com", config={ "api_key": "KEY", "api_secret": "SECRET", "version": util.API_VERSION_1, }, ) responses.add( responses.POST, "http://www.foo.com/foo?foo=bar&api_key=KEY&api_secret=SECRET", ) component.post_request("foo", params={"foo": "bar"}) @responses.activate def test_v2_post_request_passes_jwt_token(self): component = components.base.BaseComponent( base_uri="http://www.foo.com", config={ "api_key": "KEY", "api_secret": "SECRET", "version": util.API_VERSION_2, "token": 42, }, ) responses.add( responses.POST, "http://www.foo.com/foo", headers={"Authorization": "Bearer 42"}, ) component.post_request("foo") if __name__ == "__main__": unittest.main()

793f6dc2bd40a24722fa5575d45f50f23bf233c7

py

Python

django/core/serializers/__init__.py

ni-ning/django

2e7ba6057cfc82a15a22b6021cd60cf307152e2d

2015-01-01T00:05:13.000Z

2022-03-31T20:37:54.000Z

django/core/serializers/__init__.py

ni-ning/django

2e7ba6057cfc82a15a22b6021cd60cf307152e2d

2015-01-01T00:12:05.000Z

2022-03-31T19:53:11.000Z

django/core/serializers/__init__.py

mustafa0x/django

d7394cfa13a4d1a02356e3a83e10ec100fbb9948

2015-01-01T02:04:52.000Z

2022-03-31T19:42:46.000Z

""" Interfaces for serializing Django objects. Usage:: from django.core import serializers json = serializers.serialize("json", some_queryset) objects = list(serializers.deserialize("json", json)) To add your own serializers, use the SERIALIZATION_MODULES setting:: SERIALIZATION_MODULES = { "csv": "path.to.csv.serializer", "txt": "path.to.txt.serializer", } """ import importlib from django.apps import apps from django.conf import settings from django.core.serializers.base import SerializerDoesNotExist # Built-in serializers BUILTIN_SERIALIZERS = { "xml": "django.core.serializers.xml_serializer", "python": "django.core.serializers.python", "json": "django.core.serializers.json", "yaml": "django.core.serializers.pyyaml", "jsonl": "django.core.serializers.jsonl", } _serializers = {} class BadSerializer: """ Stub serializer to hold exception raised during registration This allows the serializer registration to cache serializers and if there is an error raised in the process of creating a serializer it will be raised and passed along to the caller when the serializer is used. """ internal_use_only = False def __init__(self, exception): self.exception = exception def __call__(self, *args, **kwargs): raise self.exception def register_serializer(format, serializer_module, serializers=None): """Register a new serializer. ``serializer_module`` should be the fully qualified module name for the serializer. If ``serializers`` is provided, the registration will be added to the provided dictionary. If ``serializers`` is not provided, the registration will be made directly into the global register of serializers. Adding serializers directly is not a thread-safe operation. """ if serializers is None and not _serializers: _load_serializers() try: module = importlib.import_module(serializer_module) except ImportError as exc: bad_serializer = BadSerializer(exc) module = type('BadSerializerModule', (), { 'Deserializer': bad_serializer, 'Serializer': bad_serializer, }) if serializers is None: _serializers[format] = module else: serializers[format] = module def unregister_serializer(format): "Unregister a given serializer. This is not a thread-safe operation." if not _serializers: _load_serializers() if format not in _serializers: raise SerializerDoesNotExist(format) del _serializers[format] def get_serializer(format): if not _serializers: _load_serializers() if format not in _serializers: raise SerializerDoesNotExist(format) return _serializers[format].Serializer def get_serializer_formats(): if not _serializers: _load_serializers() return list(_serializers) def get_public_serializer_formats(): if not _serializers: _load_serializers() return [k for k, v in _serializers.items() if not v.Serializer.internal_use_only] def get_deserializer(format): if not _serializers: _load_serializers() if format not in _serializers: raise SerializerDoesNotExist(format) return _serializers[format].Deserializer def serialize(format, queryset, **options): """ Serialize a queryset (or any iterator that returns database objects) using a certain serializer. """ s = get_serializer(format)() s.serialize(queryset, **options) return s.getvalue() def deserialize(format, stream_or_string, **options): """ Deserialize a stream or a string. Return an iterator that yields ``(obj, m2m_relation_dict)``, where ``obj`` is an instantiated -- but *unsaved* -- object, and ``m2m_relation_dict`` is a dictionary of ``{m2m_field_name : list_of_related_objects}``. """ d = get_deserializer(format) return d(stream_or_string, **options) def _load_serializers(): """ Register built-in and settings-defined serializers. This is done lazily so that user code has a chance to (e.g.) set up custom settings without needing to be careful of import order. """ global _serializers serializers = {} for format in BUILTIN_SERIALIZERS: register_serializer(format, BUILTIN_SERIALIZERS[format], serializers) if hasattr(settings, "SERIALIZATION_MODULES"): for format in settings.SERIALIZATION_MODULES: register_serializer(format, settings.SERIALIZATION_MODULES[format], serializers) _serializers = serializers def sort_dependencies(app_list, allow_cycles=False): """Sort a list of (app_config, models) pairs into a single list of models. The single list of models is sorted so that any model with a natural key is serialized before a normal model, and any model with a natural key dependency has it's dependencies serialized first. If allow_cycles is True, return the best-effort ordering that will respect most of dependencies but ignore some of them to break the cycles. """ # Process the list of models, and get the list of dependencies model_dependencies = [] models = set() for app_config, model_list in app_list: if model_list is None: model_list = app_config.get_models() for model in model_list: models.add(model) # Add any explicitly defined dependencies if hasattr(model, 'natural_key'): deps = getattr(model.natural_key, 'dependencies', []) if deps: deps = [apps.get_model(dep) for dep in deps] else: deps = [] # Now add a dependency for any FK relation with a model that # defines a natural key for field in model._meta.fields: if field.remote_field: rel_model = field.remote_field.model if hasattr(rel_model, 'natural_key') and rel_model != model: deps.append(rel_model) # Also add a dependency for any simple M2M relation with a model # that defines a natural key. M2M relations with explicit through # models don't count as dependencies. for field in model._meta.many_to_many: if field.remote_field.through._meta.auto_created: rel_model = field.remote_field.model if hasattr(rel_model, 'natural_key') and rel_model != model: deps.append(rel_model) model_dependencies.append((model, deps)) model_dependencies.reverse() # Now sort the models to ensure that dependencies are met. This # is done by repeatedly iterating over the input list of models. # If all the dependencies of a given model are in the final list, # that model is promoted to the end of the final list. This process # continues until the input list is empty, or we do a full iteration # over the input models without promoting a model to the final list. # If we do a full iteration without a promotion, that means there are # circular dependencies in the list. model_list = [] while model_dependencies: skipped = [] changed = False while model_dependencies: model, deps = model_dependencies.pop() # If all of the models in the dependency list are either already # on the final model list, or not on the original serialization list, # then we've found another model with all it's dependencies satisfied. if all(d not in models or d in model_list for d in deps): model_list.append(model) changed = True else: skipped.append((model, deps)) if not changed: if allow_cycles: # If cycles are allowed, add the last skipped model and ignore # its dependencies. This could be improved by some graph # analysis to ignore as few dependencies as possible. model, _ = skipped.pop() model_list.append(model) else: raise RuntimeError( "Can't resolve dependencies for %s in serialized app list." % ', '.join( model._meta.label for model, deps in sorted(skipped, key=lambda obj: obj[0].__name__) ), ) model_dependencies = skipped return model_list

793f6f6ef7d0f017038221bb09f6f5e9b134b970

py

Python

Metrics/tse_plots.py

Ginfung/FSSE

c54510b78dfceec76c74893e8514ed5177b504e5

2018-08-07T13:54:57.000Z

2020-02-24T11:46:05.000Z

Metrics/tse_plots.py

Ginfung/FSSE

c54510b78dfceec76c74893e8514ed5177b504e5

2019-01-15T23:22:19.000Z

2019-01-15T23:22:19.000Z

Metrics/tse_plots.py

Ginfung/FSSE

c54510b78dfceec76c74893e8514ed5177b504e5

2019-01-09T15:50:47.000Z

2019-01-09T15:50:47.000Z

from __future__ import division import matplotlib.pyplot as plt from matplotlib.ticker import ScalarFormatter import pickle from scipy.stats import ttest_ind from numpy import median import scipy import numpy import debug class FixedOrderFormatter(ScalarFormatter): """Formats axis ticks using scientific notation with a constant order of magnitude""" def __init__(self, order_of_mag=0, useOffset=True, useMathText=False): self._order_of_mag = order_of_mag ScalarFormatter.__init__(self, useOffset=useOffset, useMathText=useMathText) def _set_orderOfMagnitude(self, range): """Over-riding this to avoid having orderOfMagnitude reset elsewhere""" self.orderOfMagnitude = self._order_of_mag y_titles = ['Generational Distance\n(lower is better)', 'Generated Spread\n(lower is better)', 'Pareto Front Size\n(higher is better)', 'Hypervolume\n(higher is better)'] def bound(x): q25, q75 = numpy.percentile(x, [25, 75]) iqr = q75 - q25 m = median(x) return m - 1.5 * iqr, m + 1.5 * iqr def plot(model, t_i, yround=4, lessIsBetter=True, ax=None): """ :param model: :param t_i: 0-gd, 1-gs, 2-pfs, 3-hv :return: """ plt.setp(ax.spines.values(), linewidth=0.5) with open('../Experiments/tse_rs/all.stat', 'r') as f: data = pickle.load(f) data = data[model] ground = data['ground'][t_i] sway = data['sway'][t_i] moea = data['moea'][t_i] sanity = data['sanity'][t_i] if t_i == 2: sanity = sway # useless data = [sanity, ground, sway, moea] if t_i == 2: data = data[1:] # fig = plt.figure(1, figsize=(3.5, 2.3)) # ax = plt.subplot(12, 4, panelId) ax.get_xaxis().tick_bottom() ax.get_yaxis().tick_left() ax.spines['right'].set_visible(False) ax.spines['top'].set_visible(False) ax.set_xlim([0.1, 1.8]) x_ticks = [0.5, 0.95, 1.4, 1.85] if t_i == 2: x_ticks = x_ticks[:-1] box = ax.boxplot(data, patch_artist=True, widths=0.3, positions=x_ticks, showfliers=False) miny = min(bound(ground)[0], bound(sway)[0], bound(moea)[0], bound(sanity)[0]) if miny < 0: miny = 0 maxy = max(bound(ground)[1], bound(sway)[1], bound(moea)[1], bound(sanity)[1]) miny *= 0.8 maxy *= 1.2 ax.set_ylim([miny, maxy]) miny = round(miny, yround) maxy = round(maxy, yround) y_ticks = [miny, # miny + (maxy - miny) * 0.44, miny + (maxy - miny) * 0.45, maxy * 0.90] y_ticks = [round(i, yround) for i in y_ticks] ax.set_yticks(y_ticks) ax.tick_params(labelsize=6) ax.tick_params( axis='x', # changes apply to the x-axis which='major', # both major and minor ticks are affected bottom='off', # ticks along the bottom edge are off top='off', # ticks along the top edge are off right='off', labelbottom='off') # labels along the bottom edge are off red = ['red', '#FFE6E6'] green = ['green', '#76E959'] orange = ['orange', '#FFE5CC'] colors = ['black'] fcolors = ['#B2B2B2'] les = min(len(ground), len(moea)) p = scipy.stats.wilcoxon(ground[:les], moea[:les])[1] if p < 0.005 and (abs(median(ground) - median(moea)) < median(moea) * 0.1): colors.append(orange[0]) fcolors.append(orange[1]) elif (lessIsBetter and median(ground) - median(moea) < median(moea) * 0.2) or ( (not lessIsBetter) and median(ground) - median(moea) > -median(moea) * 0.2): colors.append(green[0]) fcolors.append(green[1]) else: colors.append(red[0]) fcolors.append(red[1]) les = min(len(sway), len(moea)) p = scipy.stats.wilcoxon(sway[:les], moea[:les])[1] # pdb.set_trace() if p < 0.005 and (abs(median(sway) - median(moea)) < median(moea) * 0.1): colors.append(orange[0]) fcolors.append(orange[1]) elif (lessIsBetter and median(sway) - median(moea) < median(moea) * 0.1) or ( (not lessIsBetter) and median(sway) - median(moea) > -median(moea) * 0.1): colors.append(green[0]) fcolors.append(green[1]) else: colors.append(red[0]) fcolors.append(red[1]) colors.append(orange[0]) fcolors.append(orange[1]) if t_i == 2: colors = colors[1:] fcolors = fcolors[1:] for ml, b, col, fcol in zip(box['medians'], box['boxes'], colors, fcolors): b.set_color(col) b.set_linewidth(0.5) b.set(facecolor=fcol) ml.set_color(col) # median ml.set_linewidth(0.5) # ax.yaxis.set_major_formatter(FixedOrderFormatter(-2)) ax.get_yaxis().get_major_formatter().set_useOffset(True) if model == 'osp': ax.set_title(y_titles[t_i], style='italic', fontsize=6) if t_i == 0: ax.set_ylabel(model, fontsize=6) if model == 'linux': ax.tick_params(labelbottom='on') if t_i == 2: ax.set_xticks(x_ticks) ax.set_xticklabels(('GT', 'SWAY', 'MOEA'), fontsize=6, rotation=50) else: ax.set_xticks(x_ticks) ax.set_xticklabels(['RAND', 'GT', 'SWAY', 'MOEA'], fontsize=6, rotation=50) if __name__ == '__main__': tPlot, axes = plt.subplots(nrows=12, ncols=4, figsize=(6, 7)) for i, m in enumerate( ['osp', 'osp2', 'ground', 'flight', 'p3a', 'p3b', 'p3c', 'webportal', 'eshop', 'fiasco', 'freebsd', 'linux']): print(m) plot(m, 0, 4, True, axes[i][0]) plot(m, 1, 2, True, axes[i][1]) plot(m, 2, 0, False, axes[i][2]) plot(m, 3, 2, False, axes[i][3]) plt.tight_layout() plt.subplots_adjust(wspace=0.4, hspace=0.4) plt.show() # using python tool. save as XXX.pdf

793f71acf283560e97f7437849f9242ab095b86d

py

Python

src/add-control-workflow/graph.py

kfnxu/superset-playground

d11271ddb799e74a2a2f5a9e90f1159c46faf3b6

2019-05-30T21:49:14.000Z

2019-05-30T21:49:14.000Z

src/add-control-workflow/graph.py

kfnxu/superset-playground

d11271ddb799e74a2a2f5a9e90f1159c46faf3b6

src/add-control-workflow/graph.py

kfnxu/superset-playground

d11271ddb799e74a2a2f5a9e90f1159c46faf3b6

import simplejson as json from superset import app ##pip install neo4jrestclient from neo4jrestclient.client import GraphDatabase config = app.config class BaseGraph(object): def __init__(self): host = config.get("GRAPHDB_HOST") #"" user = config.get("GRAPHDB_USER") #"" pw = config.get("GRAPHDB_PW") #"" self.db = GraphDatabase(host, username=user, password=pw) def get_search_categories_graph_db(self, in_vis_type="line", in_vis_id="1", in_vis_container_id="1"): vis_id = str(1) if int(in_vis_id) > 0: vis_id = in_vis_id vis_container_id = str(1) if int(in_vis_container_id) > 0: vis_container_id = in_vis_container_id q = 'match(a:VisContainer) - [r:has] - (p) where a.tid=' + str(vis_id) + ' ' q += 'return p.tid as ID, p.tname as NAME, p.tcat as CATEGORY order by toInteger(p.tid) ' q += 'union MATCH (a:SearchCategory ) WHERE a.tcat in ["measure", "cause", "risk", "location", "age_select", "sex", "unit", "vistype", "viscontainer", "model_group", "year_group"] RETURN a.tid AS ID, a.tname AS NAME, a.tcat as CATEGORY order by toInteger(a.tid), a.tname' print('get_search_categories_graph_db vis_id, vis_container_id, q', in_vis_id, in_vis_container_id, q) results = self.db.query(q, returns=(str, unicode, str)) ### how to use dataset #for r in results: # print("(%s)-[%s]-[%s]" % (r[0], r[1], r[2])) return results def get_search_setting_graph_db(self, in_vis_type="line", in_vis_id="1", in_vis_container_id="1"): print("get_search_setting_graph_db in_vis_type, in_vis_id, in_vis_container_id", in_vis_type, in_vis_id, in_vis_container_id) vis_id = str(1) if int(in_vis_id) > 0: vis_id = in_vis_id vis_container_id = str(1) if int(in_vis_container_id) > 0: vis_container_id = in_vis_container_id #q = 'match (a:dataResult {tname:"forecasting"}) - [:contains] -> (f:VisSection {tname:"FBD Compare"}) - [:contains] -> (g:VisControlRow) - [:contains] -> (h:VisControl) return a.tname, f.tname, g.tname, h.tname order by f.tname, g.pos union match ( a:dataResult {tname:"forecasting"}) - [:typeOf] -> (b:Visualization {tid:' + str(vis_id) + '}) - [r2:typeOf] -> (c:VisContainer {tid:' + str(vis_container_id) + '} ) - [:contains] -> (d:VisView {tname:"simpleFlowView"}) -[:contains] -> (e:VisControlPanel) -[:contains] -> (f:VisSection) - [:contains] -> (g:VisControlRow) - [:contains] -> (h:VisControl) return a.tname,f.tname, g.tname, h.tname order by toInteger(f.pos), toInteger(g.pos)' q = 'match (a:dataResult {tname:"forecasting"}) - [:contains] -> (f:VisSection {tname:"FBD Compare"}) - [:contains] -> (g:VisControlRow) - [:contains] -> (h:VisControl) return a.tname, f.tname, g.tname, h.tname order by f.tname, g.pos union match (s:SearchCategory {tcat: "charttype", tname:"' + str(in_vis_type) + '"} ) - [r:has] - (f:VisSection) with f match ( a:dataResult {tname:"forecasting"}) - [:typeOf] -> (b:Visualization {tid:' + str(vis_id) + '}) - [r2:typeOf] -> (c:VisContainer {tid:' + str(vis_container_id) + '} ) - [:contains] -> (d:VisView {tname:"simpleFlowView"}) -[:contains] -> (e:VisControlPanel) -[:contains] -> (f) - [:contains] -> (g:VisControlRow) - [:contains] -> (h:VisControl) return a.tname, f.tname, g.tname, h.tname order by g.pos'; results = self.db.query(q, returns=(str, str, str, str)) print("get_search_setting_graph_db results q", q, results) return results

793f71fcc7664ff6a566a093060e8a22c4203041

py

Python

tempest/scenario/midokura/test_network_basic_multitenant.py

midokura/tempest

b0ec1d280f057d5d9c2eda081bcbda7e381ecb3b

tempest/scenario/midokura/test_network_basic_multitenant.py

midokura/tempest

b0ec1d280f057d5d9c2eda081bcbda7e381ecb3b

tempest/scenario/midokura/test_network_basic_multitenant.py

midokura/tempest

b0ec1d280f057d5d9c2eda081bcbda7e381ecb3b

# 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 re import os import pprint from tempest import config from tempest.openstack.common import log as logging from tempest.scenario.midokura.midotools import helper from tempest.scenario.midokura import manager from tempest import test CONF = config.CONF LOG = logging.getLogger(__name__) # path should be described in tempest.conf SCPATH = "/network_scenarios/" class TestNetworkBasicMultitenants(manager.AdvancedNetworkScenarioTest): """ Description: Overlapping IP in different tenants Scenario: VMs with overlapping ip address in different tenants should not interfare each other Prerequisites: - 2 tenants - 1 network for each tenant - 1 subnet with same CIDR for each tenant Steps: This testing requires that an option "allow_overlapping_ips = True " is configured in neutron.conf file 1. launch VMs with overlapping IP 2. make sure they are not interfered 3. curl http://169.254.169.254/latest/meta-data-instance-id and make sure it correctly identifies the VM Expected result: should succeed """ def setUp(self): super(TestNetworkBasicMultitenants, self).setUp() self.scenarios = self.setup_topology( os.path.abspath( '{0}scenario_basic_multitenant.yaml'.format(SCPATH))) def _route_and_ip_test(self, ssh_client, remote_ip): LOG.info("Trying to get the list of ips") try: net_info = ssh_client.get_ip_list() LOG.debug(net_info) pattern = re.compile( '[0-9]{1,3}\.[0-9]{1,3}\.[0-9]{1,3}\.[0-9]{1,3}') _list = pattern.findall(net_info) LOG.debug(_list) self.assertIn(remote_ip, _list) route_out = ssh_client.exec_command("sudo /sbin/route -n") self._check_default_gateway(route_out, remote_ip) LOG.info(route_out) except Exception as inst: LOG.info(inst) raise def _check_metadata(self, ssh_client, server): meta_out = ssh_client.exec_command( "curl http://169.254.169.254/latest/meta-data/instance-id") meta_instid = meta_out.split('-')[1] server_instid = server['OS-EXT-SRV-ATTR:instance_name'].split('-')[1] LOG.debug("metadata instance-id: " + meta_instid) LOG.debug("server instance-id: " + server_instid) self.assertTrue(meta_instid == server_instid) def _check_default_gateway(self, route_out, internal_ip): try: rtable = helper.Routetable.build_route_table(route_out) LOG.debug(rtable) self.assertTrue(any([r.is_default_route() for r in rtable])) except Exception as inst: LOG.info(inst.args) raise @test.attr(type='smoke') @test.services('compute', 'network') def test_network_basic_multitenant(self): for creds_and_scenario in self.scenarios: self._multitenant_test(creds_and_scenario) LOG.info("test finished, tearing down now ....") def _multitenant_test(self, creds_and_scenario): # the access_point server should be the last one in the list creds = creds_and_scenario['credentials'] self.set_context(creds) servers_and_keys = creds_and_scenario['servers_and_keys'] ap_details = servers_and_keys[-1] networks = ap_details['server']['addresses'] hops = [(ap_details['FIP'].floating_ip_address, ap_details['keypair']['private_key'])] for element in servers_and_keys[:-1]: server = element['server'] name = server['addresses'].keys()[0] LOG.debug("Server dict\n:" + pprint.pformat(server)) if any(i in networks.keys() for i in server['addresses'].keys()): remote_ip = server['addresses'][name][0]['addr'] privatekey = element['keypair']['private_key'] hops.append((remote_ip, privatekey)) ssh_client = self.setup_tunnel(hops) self._route_and_ip_test(ssh_client, hops[-1][0]) self._check_metadata(ssh_client, server)

793f722cbe2ad5113256020b067861f53010b5a5

py

Python

tests/test_discovery/discovery.py

smok-serwis/bunia

61f032c990f2be8cf9ed5182e847309dd30af91b

tests/test_discovery/discovery.py

smok-serwis/bunia

61f032c990f2be8cf9ed5182e847309dd30af91b

2016-12-21T10:04:38.000Z

2017-01-10T19:11:00.000Z

tests/test_discovery/discovery.py

smok-serwis/bunia

61f032c990f2be8cf9ed5182e847309dd30af91b

# coding=UTF-8 from __future__ import absolute_import, division, print_function from bunia.api import Command class Cmd1(Command): NAME = 'cmd1' class Cmd2(Command): NAME = 'cmd2' COMMAND = Cmd1

793f725b5c1c8eb657e2755fe1c1ac92281512bc

py

Python

base/views.py

AlexWanyoike/Djangoweekone

4dc5c8de2b35fb33e82224cb3edf0d0607b063c7

base/views.py

AlexWanyoike/Djangoweekone

4dc5c8de2b35fb33e82224cb3edf0d0607b063c7

base/views.py

AlexWanyoike/Djangoweekone

4dc5c8de2b35fb33e82224cb3edf0d0607b063c7

#from datetime import db from django.shortcuts import render , redirect from django.http import HttpResponse , request , Http404 from .models import Category , Photo , Location # Create your views here. def base(request): location = request.GET.get('location') if location == None: photo = Photo.objects.all() else: photo = Photo.objects.filter(location__name=location) locations = Location.objects.all() category = request.GET.get('category') if category == None: photo = Photo.objects.all() else: photo = Photo.objects.filter(category__name=category) categories = Category.objects.all() context = {'categories': categories, 'photo': photo , 'locations': locations} return render(request, 'base/base.html', context) def viewphoto(request, pk): photo = Photo.objects.get(id=pk) return render(request, 'base/photo.html', {'photo':photo}) def create(request): categories = Category.objects.all() locations = Location.objects.all() context = {'categories': categories, 'locations': locations} return render(request , 'base/base.html', context)

793f73208441488579b78fe93c475f2d0892d083

py

Python

selfdrive/car/chrysler/interface.py

archlyga/openpilot-1

8ea26c5888d71400cc4a33752bb7cfdcea662edb

2019-07-13T18:34:23.000Z

2019-10-11T00:23:58.000Z

selfdrive/car/chrysler/interface.py

archlyga/openpilot-1

8ea26c5888d71400cc4a33752bb7cfdcea662edb

selfdrive/car/chrysler/interface.py

archlyga/openpilot-1

8ea26c5888d71400cc4a33752bb7cfdcea662edb

2019-07-14T13:58:10.000Z

2020-03-18T02:58:19.000Z

#!/usr/bin/env python from common.realtime import sec_since_boot from cereal import car from selfdrive.config import Conversions as CV from selfdrive.controls.lib.drive_helpers import EventTypes as ET, create_event from selfdrive.controls.lib.vehicle_model import VehicleModel from selfdrive.car.chrysler.carstate import CarState, get_can_parser, get_camera_parser from selfdrive.car.chrysler.values import ECU, check_ecu_msgs, CAR from selfdrive.car import STD_CARGO_KG, scale_rot_inertia, scale_tire_stiffness class CarInterface(object): def __init__(self, CP, CarController): self.CP = CP self.VM = VehicleModel(CP) self.frame = 0 self.gas_pressed_prev = False self.brake_pressed_prev = False self.cruise_enabled_prev = False self.low_speed_alert = False # *** init the major players *** self.CS = CarState(CP) self.cp = get_can_parser(CP) self.cp_cam = get_camera_parser(CP) self.CC = None if CarController is not None: self.CC = CarController(self.cp.dbc_name, CP.carFingerprint, CP.enableCamera) @staticmethod def compute_gb(accel, speed): return float(accel) / 3.0 @staticmethod def calc_accel_override(a_ego, a_target, v_ego, v_target): return 1.0 @staticmethod def get_params(candidate, fingerprint, vin=""): ret = car.CarParams.new_message() ret.carName = "chrysler" ret.carFingerprint = candidate ret.carVin = vin ret.safetyModel = car.CarParams.SafetyModel.chrysler # pedal ret.enableCruise = True # Speed conversion: 20, 45 mph ret.wheelbase = 3.089 # in meters for Pacifica Hybrid 2017 ret.steerRatio = 16.2 # Pacifica Hybrid 2017 ret.mass = 2858. + STD_CARGO_KG # kg curb weight Pacifica Hybrid 2017 ret.lateralTuning.pid.kpBP, ret.lateralTuning.pid.kiBP = [[9., 20.], [9., 20.]] ret.lateralTuning.pid.kpV, ret.lateralTuning.pid.kiV = [[0.15,0.30], [0.03,0.05]] ret.lateralTuning.pid.kf = 0.00006 # full torque for 10 deg at 80mph means 0.00007818594 ret.steerActuatorDelay = 0.1 ret.steerRateCost = 0.7 if candidate in (CAR.JEEP_CHEROKEE, CAR.JEEP_CHEROKEE_2019): ret.wheelbase = 2.91 # in meters ret.steerRatio = 12.7 ret.steerActuatorDelay = 0.2 # in seconds ret.centerToFront = ret.wheelbase * 0.44 ret.minSteerSpeed = 3.8 # m/s ret.minEnableSpeed = -1. # enable is done by stock ACC, so ignore this if candidate in (CAR.PACIFICA_2019_HYBRID, CAR.JEEP_CHEROKEE_2019): ret.minSteerSpeed = 17.5 # m/s 17 on the way up, 13 on the way down once engaged. # TODO allow 2019 cars to steer down to 13 m/s if already engaged. # TODO: get actual value, for now starting with reasonable value for # civic and scaling by mass and wheelbase ret.rotationalInertia = scale_rot_inertia(ret.mass, ret.wheelbase) # TODO: start from empirically derived lateral slip stiffness for the civic and scale by # mass and CG position, so all cars will have approximately similar dyn behaviors ret.tireStiffnessFront, ret.tireStiffnessRear = scale_tire_stiffness(ret.mass, ret.wheelbase, ret.centerToFront) # no rear steering, at least on the listed cars above ret.steerRatioRear = 0. # steer, gas, brake limitations VS speed ret.steerMaxBP = [16. * CV.KPH_TO_MS, 45. * CV.KPH_TO_MS] # breakpoints at 1 and 40 kph ret.steerMaxV = [1., 1.] # 2/3rd torque allowed above 45 kph ret.gasMaxBP = [0.] ret.gasMaxV = [0.5] ret.brakeMaxBP = [5., 20.] ret.brakeMaxV = [1., 0.8] ret.enableCamera = not check_ecu_msgs(fingerprint, ECU.CAM) print("ECU Camera Simulated: {0}".format(ret.enableCamera)) ret.openpilotLongitudinalControl = False ret.steerLimitAlert = True ret.stoppingControl = False ret.startAccel = 0.0 ret.longitudinalTuning.deadzoneBP = [0., 9.] ret.longitudinalTuning.deadzoneV = [0., .15] ret.longitudinalTuning.kpBP = [0., 5., 35.] ret.longitudinalTuning.kpV = [3.6, 2.4, 1.5] ret.longitudinalTuning.kiBP = [0., 35.] ret.longitudinalTuning.kiV = [0.54, 0.36] return ret # returns a car.CarState def update(self, c): # ******************* do can recv ******************* canMonoTimes = [] can_rcv_valid, _ = self.cp.update(int(sec_since_boot() * 1e9), True) cam_rcv_valid, _ = self.cp_cam.update(int(sec_since_boot() * 1e9), False) self.CS.update(self.cp, self.cp_cam) # create message ret = car.CarState.new_message() ret.canValid = can_rcv_valid and cam_rcv_valid and self.cp.can_valid and self.cp_cam.can_valid # speeds ret.vEgo = self.CS.v_ego ret.vEgoRaw = self.CS.v_ego_raw ret.aEgo = self.CS.a_ego ret.yawRate = self.VM.yaw_rate(self.CS.angle_steers * CV.DEG_TO_RAD, self.CS.v_ego) ret.standstill = self.CS.standstill ret.wheelSpeeds.fl = self.CS.v_wheel_fl ret.wheelSpeeds.fr = self.CS.v_wheel_fr ret.wheelSpeeds.rl = self.CS.v_wheel_rl ret.wheelSpeeds.rr = self.CS.v_wheel_rr # gear shifter ret.gearShifter = self.CS.gear_shifter # gas pedal ret.gas = self.CS.car_gas ret.gasPressed = self.CS.pedal_gas > 0 # brake pedal ret.brake = self.CS.user_brake ret.brakePressed = self.CS.brake_pressed ret.brakeLights = self.CS.brake_lights # steering wheel ret.steeringAngle = self.CS.angle_steers ret.steeringRate = self.CS.angle_steers_rate ret.steeringTorque = self.CS.steer_torque_driver ret.steeringPressed = self.CS.steer_override # cruise state ret.cruiseState.enabled = self.CS.pcm_acc_status # same as main_on ret.cruiseState.speed = self.CS.v_cruise_pcm * CV.KPH_TO_MS ret.cruiseState.available = self.CS.main_on ret.cruiseState.speedOffset = 0. # ignore standstill in hybrid rav4, since pcm allows to restart without # receiving any special command ret.cruiseState.standstill = False # TODO: button presses buttonEvents = [] if self.CS.left_blinker_on != self.CS.prev_left_blinker_on: be = car.CarState.ButtonEvent.new_message() be.type = 'leftBlinker' be.pressed = self.CS.left_blinker_on != 0 buttonEvents.append(be) if self.CS.right_blinker_on != self.CS.prev_right_blinker_on: be = car.CarState.ButtonEvent.new_message() be.type = 'rightBlinker' be.pressed = self.CS.right_blinker_on != 0 buttonEvents.append(be) ret.buttonEvents = buttonEvents ret.leftBlinker = bool(self.CS.left_blinker_on) ret.rightBlinker = bool(self.CS.right_blinker_on) ret.doorOpen = not self.CS.door_all_closed ret.seatbeltUnlatched = not self.CS.seatbelt self.low_speed_alert = (ret.vEgo < self.CP.minSteerSpeed) ret.genericToggle = self.CS.generic_toggle #ret.lkasCounter = self.CS.lkas_counter #ret.lkasCarModel = self.CS.lkas_car_model # events events = [] if not (ret.gearShifter in ('drive', 'low')): events.append(create_event('wrongGear', [ET.NO_ENTRY, ET.SOFT_DISABLE])) if ret.doorOpen: events.append(create_event('doorOpen', [ET.NO_ENTRY, ET.SOFT_DISABLE])) if ret.seatbeltUnlatched: events.append(create_event('seatbeltNotLatched', [ET.NO_ENTRY, ET.SOFT_DISABLE])) if self.CS.esp_disabled: events.append(create_event('espDisabled', [ET.NO_ENTRY, ET.SOFT_DISABLE])) if not self.CS.main_on: events.append(create_event('wrongCarMode', [ET.NO_ENTRY, ET.USER_DISABLE])) if ret.gearShifter == 'reverse': events.append(create_event('reverseGear', [ET.NO_ENTRY, ET.IMMEDIATE_DISABLE])) if self.CS.steer_error: events.append(create_event('steerUnavailable', [ET.NO_ENTRY, ET.IMMEDIATE_DISABLE, ET.PERMANENT])) if ret.cruiseState.enabled and not self.cruise_enabled_prev: events.append(create_event('pcmEnable', [ET.ENABLE])) elif not ret.cruiseState.enabled: events.append(create_event('pcmDisable', [ET.USER_DISABLE])) # disable on gas pedal and speed isn't zero. Gas pedal is used to resume ACC # from a 3+ second stop. if (ret.gasPressed and (not self.gas_pressed_prev) and ret.vEgo > 2.0): events.append(create_event('pedalPressed', [ET.NO_ENTRY, ET.USER_DISABLE])) if self.low_speed_alert: events.append(create_event('belowSteerSpeed', [ET.WARNING])) ret.events = events ret.canMonoTimes = canMonoTimes self.gas_pressed_prev = ret.gasPressed self.brake_pressed_prev = ret.brakePressed self.cruise_enabled_prev = ret.cruiseState.enabled return ret.as_reader() # pass in a car.CarControl # to be called @ 100hz def apply(self, c): if (self.CS.frame == -1): return [] # if we haven't seen a frame 220, then do not update. self.frame = self.CS.frame can_sends = self.CC.update(c.enabled, self.CS, self.frame, c.actuators, c.cruiseControl.cancel, c.hudControl.visualAlert, c.hudControl.audibleAlert) return can_sends

793f73281580c9963d319d5f269149cacdd0dbb8

py

Python

tests/features/test_audio.py

kili-technology/datasets

131effc87760d0277145edbfd2fc878b9333419c

tests/features/test_audio.py

kili-technology/datasets

131effc87760d0277145edbfd2fc878b9333419c

tests/features/test_audio.py

kili-technology/datasets

131effc87760d0277145edbfd2fc878b9333419c

import os import sys import tarfile from ctypes.util import find_library from importlib.util import find_spec import pyarrow as pa import pytest from datasets import Dataset, concatenate_datasets, load_dataset from datasets.features import Audio, Features, Sequence, Value # pytestmark = pytest.mark.audio require_sndfile = pytest.mark.skipif( # In Windows and OS X, soundfile installs sndfile (sys.platform != "linux" and find_spec("soundfile") is None) # In Linux, soundfile throws RuntimeError if sndfile not installed with distribution package manager or (sys.platform == "linux" and find_library("sndfile") is None), reason="Test requires 'sndfile': `pip install soundfile`; " "Linux requires sndfile installed with distribution package manager, e.g.: `sudo apt-get install libsndfile1`", ) require_sox = pytest.mark.skipif( find_library("sox") is None, reason="Test requires 'sox'; only available in non-Windows, e.g.: `sudo apt-get install sox`", ) require_torchaudio = pytest.mark.skipif(find_spec("torchaudio") is None, reason="Test requires 'torchaudio'") @pytest.fixture() def tar_wav_path(shared_datadir, tmp_path_factory): audio_path = str(shared_datadir / "test_audio_44100.wav") path = tmp_path_factory.mktemp("data") / "audio_data.wav.tar" with tarfile.TarFile(path, "w") as f: f.add(audio_path, arcname=os.path.basename(audio_path)) return path @pytest.fixture() def tar_mp3_path(shared_datadir, tmp_path_factory): audio_path = str(shared_datadir / "test_audio_44100.mp3") path = tmp_path_factory.mktemp("data") / "audio_data.mp3.tar" with tarfile.TarFile(path, "w") as f: f.add(audio_path, arcname=os.path.basename(audio_path)) return path def iter_archive(archive_path): with tarfile.open(archive_path) as tar: for tarinfo in tar: file_path = tarinfo.name file_obj = tar.extractfile(tarinfo) yield file_path, file_obj def test_audio_instantiation(): audio = Audio() assert audio.sampling_rate is None assert audio.mono is True assert audio.id is None assert audio.dtype == "dict" assert audio.pa_type == pa.struct({"bytes": pa.binary(), "path": pa.string()}) assert audio._type == "Audio" def test_audio_feature_type_to_arrow(): features = Features({"audio": Audio()}) assert features.arrow_schema == pa.schema({"audio": Audio().pa_type}) features = Features({"struct_containing_an_audio": {"audio": Audio()}}) assert features.arrow_schema == pa.schema({"struct_containing_an_audio": pa.struct({"audio": Audio().pa_type})}) features = Features({"sequence_of_audios": Sequence(Audio())}) assert features.arrow_schema == pa.schema({"sequence_of_audios": pa.list_(Audio().pa_type)}) @pytest.mark.parametrize( "build_example", [ lambda audio_path: audio_path, lambda audio_path: {"path": audio_path}, lambda audio_path: {"path": audio_path, "bytes": None}, lambda audio_path: {"path": audio_path, "bytes": open(audio_path, "rb").read()}, lambda audio_path: {"path": None, "bytes": open(audio_path, "rb").read()}, lambda audio_path: {"bytes": open(audio_path, "rb").read()}, ], ) def test_audio_feature_encode_example(shared_datadir, build_example): audio_path = str(shared_datadir / "test_audio_44100.wav") audio = Audio() encoded_example = audio.encode_example(build_example(audio_path)) assert isinstance(encoded_example, dict) assert encoded_example.keys() == {"bytes", "path"} assert encoded_example["bytes"] is not None or encoded_example["path"] is not None decoded_example = audio.decode_example(encoded_example) assert decoded_example.keys() == {"path", "array", "sampling_rate"} @require_sndfile def test_audio_decode_example(shared_datadir): audio_path = str(shared_datadir / "test_audio_44100.wav") audio = Audio() decoded_example = audio.decode_example(audio.encode_example(audio_path)) assert decoded_example.keys() == {"path", "array", "sampling_rate"} assert decoded_example["path"] == audio_path assert decoded_example["array"].shape == (202311,) assert decoded_example["sampling_rate"] == 44100 @require_sndfile def test_audio_resampling(shared_datadir): audio_path = str(shared_datadir / "test_audio_44100.wav") audio = Audio(sampling_rate=16000) decoded_example = audio.decode_example(audio.encode_example(audio_path)) assert decoded_example.keys() == {"path", "array", "sampling_rate"} assert decoded_example["path"] == audio_path assert decoded_example["array"].shape == (73401,) assert decoded_example["sampling_rate"] == 16000 @require_sox @require_torchaudio def test_audio_decode_example_mp3(shared_datadir): audio_path = str(shared_datadir / "test_audio_44100.mp3") audio = Audio() decoded_example = audio.decode_example(audio.encode_example(audio_path)) assert decoded_example.keys() == {"path", "array", "sampling_rate"} assert decoded_example["path"] == audio_path assert decoded_example["array"].shape == (109440,) assert decoded_example["sampling_rate"] == 44100 @require_sndfile def test_dataset_with_audio_feature(shared_datadir): audio_path = str(shared_datadir / "test_audio_44100.wav") data = {"audio": [audio_path]} features = Features({"audio": Audio()}) dset = Dataset.from_dict(data, features=features) item = dset[0] assert item.keys() == {"audio"} assert item["audio"].keys() == {"path", "array", "sampling_rate"} assert item["audio"]["path"] == audio_path assert item["audio"]["array"].shape == (202311,) assert item["audio"]["sampling_rate"] == 44100 batch = dset[:1] assert batch.keys() == {"audio"} assert len(batch["audio"]) == 1 assert batch["audio"][0].keys() == {"path", "array", "sampling_rate"} assert batch["audio"][0]["path"] == audio_path assert batch["audio"][0]["array"].shape == (202311,) assert batch["audio"][0]["sampling_rate"] == 44100 column = dset["audio"] assert len(column) == 1 assert column[0].keys() == {"path", "array", "sampling_rate"} assert column[0]["path"] == audio_path assert column[0]["array"].shape == (202311,) assert column[0]["sampling_rate"] == 44100 @require_sndfile def test_dataset_with_audio_feature_tar_wav(tar_wav_path): audio_filename = "test_audio_44100.wav" data = {"audio": []} for file_path, file_obj in iter_archive(tar_wav_path): data["audio"].append({"path": file_path, "bytes": file_obj.read()}) break features = Features({"audio": Audio()}) dset = Dataset.from_dict(data, features=features) item = dset[0] assert item.keys() == {"audio"} assert item["audio"].keys() == {"path", "array", "sampling_rate"} assert item["audio"]["path"] == audio_filename assert item["audio"]["array"].shape == (202311,) assert item["audio"]["sampling_rate"] == 44100 batch = dset[:1] assert batch.keys() == {"audio"} assert len(batch["audio"]) == 1 assert batch["audio"][0].keys() == {"path", "array", "sampling_rate"} assert batch["audio"][0]["path"] == audio_filename assert batch["audio"][0]["array"].shape == (202311,) assert batch["audio"][0]["sampling_rate"] == 44100 column = dset["audio"] assert len(column) == 1 assert column[0].keys() == {"path", "array", "sampling_rate"} assert column[0]["path"] == audio_filename assert column[0]["array"].shape == (202311,) assert column[0]["sampling_rate"] == 44100 @require_sox @require_torchaudio def test_dataset_with_audio_feature_tar_mp3(tar_mp3_path): audio_filename = "test_audio_44100.mp3" data = {"audio": []} for file_path, file_obj in iter_archive(tar_mp3_path): data["audio"].append({"path": file_path, "bytes": file_obj.read()}) break features = Features({"audio": Audio()}) dset = Dataset.from_dict(data, features=features) item = dset[0] assert item.keys() == {"audio"} assert item["audio"].keys() == {"path", "array", "sampling_rate"} assert item["audio"]["path"] == audio_filename assert item["audio"]["array"].shape == (109440,) assert item["audio"]["sampling_rate"] == 44100 batch = dset[:1] assert batch.keys() == {"audio"} assert len(batch["audio"]) == 1 assert batch["audio"][0].keys() == {"path", "array", "sampling_rate"} assert batch["audio"][0]["path"] == audio_filename assert batch["audio"][0]["array"].shape == (109440,) assert batch["audio"][0]["sampling_rate"] == 44100 column = dset["audio"] assert len(column) == 1 assert column[0].keys() == {"path", "array", "sampling_rate"} assert column[0]["path"] == audio_filename assert column[0]["array"].shape == (109440,) assert column[0]["sampling_rate"] == 44100 @require_sndfile def test_resampling_at_loading_dataset_with_audio_feature(shared_datadir): audio_path = str(shared_datadir / "test_audio_44100.wav") data = {"audio": [audio_path]} features = Features({"audio": Audio(sampling_rate=16000)}) dset = Dataset.from_dict(data, features=features) item = dset[0] assert item.keys() == {"audio"} assert item["audio"].keys() == {"path", "array", "sampling_rate"} assert item["audio"]["path"] == audio_path assert item["audio"]["array"].shape == (73401,) assert item["audio"]["sampling_rate"] == 16000 batch = dset[:1] assert batch.keys() == {"audio"} assert len(batch["audio"]) == 1 assert batch["audio"][0].keys() == {"path", "array", "sampling_rate"} assert batch["audio"][0]["path"] == audio_path assert batch["audio"][0]["array"].shape == (73401,) assert batch["audio"][0]["sampling_rate"] == 16000 column = dset["audio"] assert len(column) == 1 assert column[0].keys() == {"path", "array", "sampling_rate"} assert column[0]["path"] == audio_path assert column[0]["array"].shape == (73401,) assert column[0]["sampling_rate"] == 16000 @require_sox @require_sndfile def test_resampling_at_loading_dataset_with_audio_feature_mp3(shared_datadir): audio_path = str(shared_datadir / "test_audio_44100.mp3") data = {"audio": [audio_path]} features = Features({"audio": Audio(sampling_rate=16000)}) dset = Dataset.from_dict(data, features=features) item = dset[0] assert item.keys() == {"audio"} assert item["audio"].keys() == {"path", "array", "sampling_rate"} assert item["audio"]["path"] == audio_path assert item["audio"]["array"].shape == (39707,) assert item["audio"]["sampling_rate"] == 16000 batch = dset[:1] assert batch.keys() == {"audio"} assert len(batch["audio"]) == 1 assert batch["audio"][0].keys() == {"path", "array", "sampling_rate"} assert batch["audio"][0]["path"] == audio_path assert batch["audio"][0]["array"].shape == (39707,) assert batch["audio"][0]["sampling_rate"] == 16000 column = dset["audio"] assert len(column) == 1 assert column[0].keys() == {"path", "array", "sampling_rate"} assert column[0]["path"] == audio_path assert column[0]["array"].shape == (39707,) assert column[0]["sampling_rate"] == 16000 @require_sndfile def test_resampling_after_loading_dataset_with_audio_feature(shared_datadir): audio_path = str(shared_datadir / "test_audio_44100.wav") data = {"audio": [audio_path]} features = Features({"audio": Audio()}) dset = Dataset.from_dict(data, features=features) item = dset[0] assert item["audio"]["sampling_rate"] == 44100 dset = dset.cast_column("audio", Audio(sampling_rate=16000)) item = dset[0] assert item.keys() == {"audio"} assert item["audio"].keys() == {"path", "array", "sampling_rate"} assert item["audio"]["path"] == audio_path assert item["audio"]["array"].shape == (73401,) assert item["audio"]["sampling_rate"] == 16000 batch = dset[:1] assert batch.keys() == {"audio"} assert len(batch["audio"]) == 1 assert batch["audio"][0].keys() == {"path", "array", "sampling_rate"} assert batch["audio"][0]["path"] == audio_path assert batch["audio"][0]["array"].shape == (73401,) assert batch["audio"][0]["sampling_rate"] == 16000 column = dset["audio"] assert len(column) == 1 assert column[0].keys() == {"path", "array", "sampling_rate"} assert column[0]["path"] == audio_path assert column[0]["array"].shape == (73401,) assert column[0]["sampling_rate"] == 16000 @require_sox @require_sndfile def test_resampling_after_loading_dataset_with_audio_feature_mp3(shared_datadir): audio_path = str(shared_datadir / "test_audio_44100.mp3") data = {"audio": [audio_path]} features = Features({"audio": Audio()}) dset = Dataset.from_dict(data, features=features) item = dset[0] assert item["audio"]["sampling_rate"] == 44100 dset = dset.cast_column("audio", Audio(sampling_rate=16000)) item = dset[0] assert item.keys() == {"audio"} assert item["audio"].keys() == {"path", "array", "sampling_rate"} assert item["audio"]["path"] == audio_path assert item["audio"]["array"].shape == (39707,) assert item["audio"]["sampling_rate"] == 16000 batch = dset[:1] assert batch.keys() == {"audio"} assert len(batch["audio"]) == 1 assert batch["audio"][0].keys() == {"path", "array", "sampling_rate"} assert batch["audio"][0]["path"] == audio_path assert batch["audio"][0]["array"].shape == (39707,) assert batch["audio"][0]["sampling_rate"] == 16000 column = dset["audio"] assert len(column) == 1 assert column[0].keys() == {"path", "array", "sampling_rate"} assert column[0]["path"] == audio_path assert column[0]["array"].shape == (39707,) assert column[0]["sampling_rate"] == 16000 @pytest.mark.parametrize( "build_data", [ lambda audio_path: {"audio": [audio_path]}, lambda audio_path: {"audio": [{"path": audio_path}]}, lambda audio_path: {"audio": [{"path": audio_path, "bytes": None}]}, lambda audio_path: {"audio": [{"path": audio_path, "bytes": open(audio_path, "rb").read()}]}, lambda audio_path: {"audio": [{"path": None, "bytes": open(audio_path, "rb").read()}]}, lambda audio_path: {"audio": [{"bytes": open(audio_path, "rb").read()}]}, ], ) def test_dataset_cast_to_audio_features(shared_datadir, build_data): audio_path = str(shared_datadir / "test_audio_44100.wav") data = build_data(audio_path) dset = Dataset.from_dict(data) item = dset.cast(Features({"audio": Audio()}))[0] assert item.keys() == {"audio"} assert item["audio"].keys() == {"path", "array", "sampling_rate"} item = dset.cast_column("audio", Audio())[0] assert item.keys() == {"audio"} assert item["audio"].keys() == {"path", "array", "sampling_rate"} def test_dataset_concatenate_audio_features(shared_datadir): # we use a different data structure between 1 and 2 to make sure they are compatible with each other audio_path = str(shared_datadir / "test_audio_44100.wav") data1 = {"audio": [audio_path]} dset1 = Dataset.from_dict(data1, features=Features({"audio": Audio()})) data2 = {"audio": [{"bytes": open(audio_path, "rb").read()}]} dset2 = Dataset.from_dict(data2, features=Features({"audio": Audio()})) concatenated_dataset = concatenate_datasets([dset1, dset2]) assert len(concatenated_dataset) == len(dset1) + len(dset2) assert concatenated_dataset[0]["audio"]["array"].shape == dset1[0]["audio"]["array"].shape assert concatenated_dataset[1]["audio"]["array"].shape == dset2[0]["audio"]["array"].shape def test_dataset_concatenate_nested_audio_features(shared_datadir): # we use a different data structure between 1 and 2 to make sure they are compatible with each other audio_path = str(shared_datadir / "test_audio_44100.wav") features = Features({"list_of_structs_of_audios": [{"audio": Audio()}]}) data1 = {"list_of_structs_of_audios": [[{"audio": audio_path}]]} dset1 = Dataset.from_dict(data1, features=features) data2 = {"list_of_structs_of_audios": [[{"audio": {"bytes": open(audio_path, "rb").read()}}]]} dset2 = Dataset.from_dict(data2, features=features) concatenated_dataset = concatenate_datasets([dset1, dset2]) assert len(concatenated_dataset) == len(dset1) + len(dset2) assert ( concatenated_dataset[0]["list_of_structs_of_audios"][0]["audio"]["array"].shape == dset1[0]["list_of_structs_of_audios"][0]["audio"]["array"].shape ) assert ( concatenated_dataset[1]["list_of_structs_of_audios"][0]["audio"]["array"].shape == dset2[0]["list_of_structs_of_audios"][0]["audio"]["array"].shape ) @require_sndfile def test_dataset_with_audio_feature_map_is_not_decoded(shared_datadir): audio_path = str(shared_datadir / "test_audio_44100.wav") data = {"audio": [audio_path], "text": ["Hello"]} features = Features({"audio": Audio(), "text": Value("string")}) dset = Dataset.from_dict(data, features=features) expected_audio = features.encode_batch(data)["audio"][0] for item in dset: assert item.keys() == {"audio", "text"} assert item == {"audio": expected_audio, "text": "Hello"} def process_text(example): example["text"] = example["text"] + " World!" return example processed_dset = dset.map(process_text) for item in processed_dset: assert item.keys() == {"audio", "text"} assert item == {"audio": expected_audio, "text": "Hello World!"} @require_sndfile def test_dataset_with_audio_feature_map_is_decoded(shared_datadir): audio_path = str(shared_datadir / "test_audio_44100.wav") data = {"audio": [audio_path], "text": ["Hello"]} features = Features({"audio": Audio(), "text": Value("string")}) dset = Dataset.from_dict(data, features=features) def process_audio_sampling_rate_by_example(example): example["double_sampling_rate"] = 2 * example["audio"]["sampling_rate"] return example decoded_dset = dset.map(process_audio_sampling_rate_by_example) for item in decoded_dset: assert item.keys() == {"audio", "text", "double_sampling_rate"} assert item["double_sampling_rate"] == 88200 def process_audio_sampling_rate_by_batch(batch): double_sampling_rates = [] for audio in batch["audio"]: double_sampling_rates.append(2 * audio["sampling_rate"]) batch["double_sampling_rate"] = double_sampling_rates return batch decoded_dset = dset.map(process_audio_sampling_rate_by_batch, batched=True) for item in decoded_dset: assert item.keys() == {"audio", "text", "double_sampling_rate"} assert item["double_sampling_rate"] == 88200 @require_sndfile def test_formatted_dataset_with_audio_feature(shared_datadir): audio_path = str(shared_datadir / "test_audio_44100.wav") data = {"audio": [audio_path, audio_path]} features = Features({"audio": Audio()}) dset = Dataset.from_dict(data, features=features) with dset.formatted_as("numpy"): item = dset[0] assert item.keys() == {"audio"} assert item["audio"].keys() == {"path", "array", "sampling_rate"} assert item["audio"]["path"] == audio_path assert item["audio"]["array"].shape == (202311,) assert item["audio"]["sampling_rate"] == 44100 batch = dset[:1] assert batch.keys() == {"audio"} assert len(batch["audio"]) == 1 assert batch["audio"][0].keys() == {"path", "array", "sampling_rate"} assert batch["audio"][0]["path"] == audio_path assert batch["audio"][0]["array"].shape == (202311,) assert batch["audio"][0]["sampling_rate"] == 44100 column = dset["audio"] assert len(column) == 2 assert column[0].keys() == {"path", "array", "sampling_rate"} assert column[0]["path"] == audio_path assert column[0]["array"].shape == (202311,) assert column[0]["sampling_rate"] == 44100 with dset.formatted_as("pandas"): item = dset[0] assert item.shape == (1, 1) assert item.columns == ["audio"] assert item["audio"][0].keys() == {"path", "array", "sampling_rate"} assert item["audio"][0]["path"] == audio_path assert item["audio"][0]["array"].shape == (202311,) assert item["audio"][0]["sampling_rate"] == 44100 batch = dset[:1] assert batch.shape == (1, 1) assert batch.columns == ["audio"] assert batch["audio"][0].keys() == {"path", "array", "sampling_rate"} assert batch["audio"][0]["path"] == audio_path assert batch["audio"][0]["array"].shape == (202311,) assert batch["audio"][0]["sampling_rate"] == 44100 column = dset["audio"] assert len(column) == 2 assert column[0].keys() == {"path", "array", "sampling_rate"} assert column[0]["path"] == audio_path assert column[0]["array"].shape == (202311,) assert column[0]["sampling_rate"] == 44100 @pytest.fixture def jsonl_audio_dataset_path(shared_datadir, tmp_path_factory): import json audio_path = str(shared_datadir / "test_audio_44100.wav") data = [{"audio": audio_path, "text": "Hello world!"}] path = str(tmp_path_factory.mktemp("data") / "audio_dataset.jsonl") with open(path, "w") as f: for item in data: f.write(json.dumps(item) + "\n") return path @require_sndfile @pytest.mark.parametrize("streaming", [False, True]) def test_load_dataset_with_audio_feature(streaming, jsonl_audio_dataset_path, shared_datadir): audio_path = str(shared_datadir / "test_audio_44100.wav") data_files = jsonl_audio_dataset_path features = Features({"audio": Audio(), "text": Value("string")}) dset = load_dataset("json", split="train", data_files=data_files, features=features, streaming=streaming) item = dset[0] if not streaming else next(iter(dset)) assert item.keys() == {"audio", "text"} assert item["audio"].keys() == {"path", "array", "sampling_rate"} assert item["audio"]["path"] == audio_path assert item["audio"]["array"].shape == (202311,) assert item["audio"]["sampling_rate"] == 44100 @require_sndfile def test_dataset_with_audio_feature_loaded_from_cache(): # load first time ds = load_dataset("patrickvonplaten/librispeech_asr_dummy", "clean") # load from cache ds = load_dataset("patrickvonplaten/librispeech_asr_dummy", "clean", split="validation") assert isinstance(ds, Dataset)

793f73d13224d0401c605168ff9405dff0d2357e

py

Python

my_wallet/stocks/migrations/0006_remove_prices_price.py

Bounty1993/my-wallet

c14f8efaa1c3b90f9d5b0a6c5b5aabb26ed541fa

my_wallet/stocks/migrations/0006_remove_prices_price.py

Bounty1993/my-wallet

c14f8efaa1c3b90f9d5b0a6c5b5aabb26ed541fa

2020-06-05T19:52:06.000Z

2022-03-11T23:40:19.000Z

my_wallet/stocks/migrations/0006_remove_prices_price.py

Bounty1993/my-wallet

c14f8efaa1c3b90f9d5b0a6c5b5aabb26ed541fa

# Generated by Django 2.1.5 on 2019-03-11 20:47 from django.db import migrations class Migration(migrations.Migration): dependencies = [ ('stocks', '0005_auto_20190310_1528'), ] operations = [ migrations.RemoveField( model_name='prices', name='price', ), ]

793f745d49be68581ba8f2b75b6de9b845342220

py

Python

examples/uploadVideo.py

partizan007/Instagram-API

3435dc6855e1cccf2c85a41839d15ca930563b21

2016-05-18T19:20:32.000Z

2022-02-12T10:30:50.000Z

examples/uploadVideo.py

partizan007/Instagram-API

3435dc6855e1cccf2c85a41839d15ca930563b21

2016-08-07T17:32:37.000Z

2022-01-13T00:25:31.000Z

examples/uploadVideo.py

partizan007/Instagram-API

3435dc6855e1cccf2c85a41839d15ca930563b21

2016-07-07T14:18:38.000Z

2021-03-28T12:48:26.000Z

import InstagramAPI # /////// CONFIG /////// username = '' password = '' debug = False video = '' # path to the video caption = '' # caption # ////////////////////// i = InstagramAPI.Instagram(username, password, debug) try: i.login() except Exception as e: e.message exit() try: i.uploadVideo(video, caption) except Exception as e: print e.message

793f748a50a0998295123fa9f0f2c4dbf2555762

py

Python

instaapp/urls.py

habibahassan/Instagram

3cc076b54e460f76e602b693abb2f8af91983add

instaapp/urls.py

habibahassan/Instagram

3cc076b54e460f76e602b693abb2f8af91983add

2020-03-09T05:34:02.000Z

2021-09-08T01:51:12.000Z

instaapp/urls.py

habibahassan/Instagram

3cc076b54e460f76e602b693abb2f8af91983add

from django.urls import path,re_path from . import views from django.conf import settings from django.conf.urls.static import static urlpatterns = [ path('',views.home,name='home'), path('profile/',views.profile,name='profile'), path('profile/update/',views.update_profile,name='update_profile'), path('no profile/(\d+)',views.no_profile), path('search/', views.search_results, name='search_results'), path('new/image/',views.new_image,name="new_image"), re_path('comment/(\d+)', views.comment, name='comment'), re_path('comment/like/(\d+)',views.like_pic,name="like"), path('image/update/',views.update_image,name='update_image'), path('profile/follow/', views.follow, name='follow'), path('^$', views.usersignup, name='register_user'), ] if settings.DEBUG: urlpatterns+= static(settings.MEDIA_URL, document_root = settings.MEDIA_ROOT)

793f7524551d797584ba86555b7fc04de36da5c5

py

Python

ntvv/python/cimConverter/__init__.py

Muxelmann/voltage-assessment

b90e3ca829fe25845a698cb86c67c213f8befe7a

2020-01-17T12:40:26.000Z

2021-03-09T07:15:50.000Z

ntvv/python/cimConverter/__init__.py

Muxelmann/voltage-assessment

b90e3ca829fe25845a698cb86c67c213f8befe7a

ntvv/python/cimConverter/__init__.py

Muxelmann/voltage-assessment

b90e3ca829fe25845a698cb86c67c213f8befe7a

from . import logger from .CIMClass import CIMClass

793f75e8d343f7da3d72f87b577cf55f2aae51e4

py

Python

mamba/setup.py

wulmer/mamba

5961d76afdd8b0f070bf0f2da396ef25289c965c

2019-03-25T15:38:35.000Z

2020-06-19T05:51:38.000Z

mamba/setup.py

wulmer/mamba

5961d76afdd8b0f070bf0f2da396ef25289c965c

2019-03-25T15:25:38.000Z

2020-06-18T09:34:54.000Z

mamba/setup.py

wulmer/mamba

5961d76afdd8b0f070bf0f2da396ef25289c965c

2019-03-25T15:05:18.000Z

2020-06-17T14:14:11.000Z

# Copyright (c) 2019, QuantStack and Mamba Contributors # # Distributed under the terms of the BSD 3-Clause License. # # The full license is in the file LICENSE, distributed with this software. # -*- coding: utf-8 -*- import os import sys from setuptools import setup here = os.path.dirname(os.path.abspath(__file__)) version_ns = {} with open(os.path.join(here, "mamba", "_version.py")) as f: exec(f.read(), {}, version_ns) __version__ = version_ns["__version__"] data_files = [ ("etc/profile.d", ["mamba/shell_templates/mamba.sh"]), ] if sys.platform == "win32": data_files.append( ("condabin", ["mamba/shell_templates/mamba.bat"]), ) data_files.append( ("Library/bin", ["mamba/shell_templates/win_redirect/mamba.bat"]), ) setup( name="mamba", version=__version__, author="Wolf Vollprecht", author_email="wolf.vollprecht@quantstack.net", url="https://github.com/mamba-org/mamba", description="A fast, libsolv based solver and installer for conda packages.", packages=["mamba"], entry_points={"console_scripts": ["mamba = mamba.mamba:main"]}, long_description="A (hopefully faster) reimplementation of the slow bits of conda.", install_requires=["conda", "libmambapy"], extras_require={"test": ["pytest", "pytest-lazy-fixture"]}, data_files=data_files, include_package_data=True, zip_safe=False, )

793f761104202aa91ce4d78e0aa3774112e69970

py

Python

sdk/authorization/azure-mgmt-authorization/azure/mgmt/authorization/v2021_03_01_preview/operations/_access_review_instances_assigned_for_my_approval_operations.py

rsdoherty/azure-sdk-for-python

6bba5326677468e6660845a703686327178bb7b1

2015-01-09T10:19:32.000Z

2022-03-31T14:50:33.000Z

sdk/authorization/azure-mgmt-authorization/azure/mgmt/authorization/v2021_03_01_preview/operations/_access_review_instances_assigned_for_my_approval_operations.py

rsdoherty/azure-sdk-for-python

6bba5326677468e6660845a703686327178bb7b1

2015-01-05T15:57:17.000Z

2022-03-31T23:50:25.000Z

sdk/authorization/azure-mgmt-authorization/azure/mgmt/authorization/v2021_03_01_preview/operations/_access_review_instances_assigned_for_my_approval_operations.py

rsdoherty/azure-sdk-for-python

6bba5326677468e6660845a703686327178bb7b1

2015-01-19T05:05:41.000Z

2022-03-31T19:36:44.000Z

# coding=utf-8 # -------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for license information. # Code generated by Microsoft (R) AutoRest Code Generator. # Changes may cause incorrect behavior and will be lost if the code is regenerated. # -------------------------------------------------------------------------- from typing import TYPE_CHECKING import warnings from azure.core.exceptions import ClientAuthenticationError, HttpResponseError, ResourceExistsError, ResourceNotFoundError, map_error from azure.core.paging import ItemPaged from azure.core.pipeline import PipelineResponse from azure.core.pipeline.transport import HttpRequest, HttpResponse from azure.mgmt.core.exceptions import ARMErrorFormat from .. import models as _models if TYPE_CHECKING: # pylint: disable=unused-import,ungrouped-imports from typing import Any, Callable, Dict, Generic, Iterable, Optional, TypeVar T = TypeVar('T') ClsType = Optional[Callable[[PipelineResponse[HttpRequest, HttpResponse], T, Dict[str, Any]], Any]] class AccessReviewInstancesAssignedForMyApprovalOperations(object): """AccessReviewInstancesAssignedForMyApprovalOperations operations. You should not instantiate this class directly. Instead, you should create a Client instance that instantiates it for you and attaches it as an attribute. :ivar models: Alias to model classes used in this operation group. :type models: ~azure.mgmt.authorization.v2021_03_01_preview.models :param client: Client for service requests. :param config: Configuration of service client. :param serializer: An object model serializer. :param deserializer: An object model deserializer. """ models = _models def __init__(self, client, config, serializer, deserializer): self._client = client self._serialize = serializer self._deserialize = deserializer self._config = config def list( self, schedule_definition_id, # type: str filter=None, # type: Optional[str] **kwargs # type: Any ): # type: (...) -> Iterable["_models.AccessReviewInstanceListResult"] """Get access review instances assigned for my approval. :param schedule_definition_id: The id of the access review schedule definition. :type schedule_definition_id: str :param filter: The filter to apply on the operation. Other than standard filters, one custom filter option is supported : 'assignedToMeToReview()'. When one specified $filter=assignedToMeToReview(), only items that are assigned to the calling user to review are returned. :type filter: str :keyword callable cls: A custom type or function that will be passed the direct response :return: An iterator like instance of either AccessReviewInstanceListResult or the result of cls(response) :rtype: ~azure.core.paging.ItemPaged[~azure.mgmt.authorization.v2021_03_01_preview.models.AccessReviewInstanceListResult] :raises: ~azure.core.exceptions.HttpResponseError """ cls = kwargs.pop('cls', None) # type: ClsType["_models.AccessReviewInstanceListResult"] error_map = { 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError } error_map.update(kwargs.pop('error_map', {})) api_version = "2021-03-01-preview" accept = "application/json" def prepare_request(next_link=None): # Construct headers header_parameters = {} # type: Dict[str, Any] header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') if not next_link: # Construct URL url = self.list.metadata['url'] # type: ignore path_format_arguments = { 'scheduleDefinitionId': self._serialize.url("schedule_definition_id", schedule_definition_id, 'str'), } url = self._client.format_url(url, **path_format_arguments) # Construct parameters query_parameters = {} # type: Dict[str, Any] query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') if filter is not None: query_parameters['$filter'] = self._serialize.query("filter", filter, 'str', skip_quote=True) request = self._client.get(url, query_parameters, header_parameters) else: url = next_link query_parameters = {} # type: Dict[str, Any] request = self._client.get(url, query_parameters, header_parameters) return request def extract_data(pipeline_response): deserialized = self._deserialize('AccessReviewInstanceListResult', pipeline_response) list_of_elem = deserialized.value if cls: list_of_elem = cls(list_of_elem) return deserialized.next_link or None, iter(list_of_elem) def get_next(next_link=None): request = prepare_request(next_link) pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) response = pipeline_response.http_response if response.status_code not in [200]: error = self._deserialize.failsafe_deserialize(_models.ErrorDefinition, response) map_error(status_code=response.status_code, response=response, error_map=error_map) raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) return pipeline_response return ItemPaged( get_next, extract_data ) list.metadata = {'url': '/providers/Microsoft.Authorization/accessReviewScheduleDefinitions/{scheduleDefinitionId}/instances'} # type: ignore def get_by_id( self, schedule_definition_id, # type: str id, # type: str **kwargs # type: Any ): # type: (...) -> "_models.AccessReviewInstance" """Get single access review instance assigned for my approval. :param schedule_definition_id: The id of the access review schedule definition. :type schedule_definition_id: str :param id: The id of the access review instance. :type id: str :keyword callable cls: A custom type or function that will be passed the direct response :return: AccessReviewInstance, or the result of cls(response) :rtype: ~azure.mgmt.authorization.v2021_03_01_preview.models.AccessReviewInstance :raises: ~azure.core.exceptions.HttpResponseError """ cls = kwargs.pop('cls', None) # type: ClsType["_models.AccessReviewInstance"] error_map = { 401: ClientAuthenticationError, 404: ResourceNotFoundError, 409: ResourceExistsError } error_map.update(kwargs.pop('error_map', {})) api_version = "2021-03-01-preview" accept = "application/json" # Construct URL url = self.get_by_id.metadata['url'] # type: ignore path_format_arguments = { 'scheduleDefinitionId': self._serialize.url("schedule_definition_id", schedule_definition_id, 'str'), 'id': self._serialize.url("id", id, 'str'), } url = self._client.format_url(url, **path_format_arguments) # Construct parameters query_parameters = {} # type: Dict[str, Any] query_parameters['api-version'] = self._serialize.query("api_version", api_version, 'str') # Construct headers header_parameters = {} # type: Dict[str, Any] header_parameters['Accept'] = self._serialize.header("accept", accept, 'str') request = self._client.get(url, query_parameters, header_parameters) pipeline_response = self._client._pipeline.run(request, stream=False, **kwargs) response = pipeline_response.http_response if response.status_code not in [200]: map_error(status_code=response.status_code, response=response, error_map=error_map) error = self._deserialize.failsafe_deserialize(_models.ErrorDefinition, response) raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat) deserialized = self._deserialize('AccessReviewInstance', pipeline_response) if cls: return cls(pipeline_response, deserialized, {}) return deserialized get_by_id.metadata = {'url': '/providers/Microsoft.Authorization/accessReviewScheduleDefinitions/{scheduleDefinitionId}/instances/{id}'} # type: ignore

793f76b65644d9095d5683b97171095ae3f2182e

py

Python

truvari/annos/bed_anno.py

mlinderm/truvari

e84804b20214775ba625819568e74a1920c99a06

truvari/annos/bed_anno.py

mlinderm/truvari

e84804b20214775ba625819568e74a1920c99a06

truvari/annos/bed_anno.py

mlinderm/truvari

e84804b20214775ba625819568e74a1920c99a06

""" Annotate over a generic bedfile Need to build the 'tree maker' first? Need to make sure and set it so --multimatch And also, need to specify that col[3] (bed name) must be the INFO=;oaiwef and the header lines "^#" must be the header information """

793f7756b5fa6a9793124091250f6b248f6045e0

py

Python

fatiando/mesher/mesh.py

XuesongDing/fatiando

57a0e0802fde2e53628511d3a7a2964e69bb309a

2015-03-08T08:50:45.000Z

2022-03-20T08:19:05.000Z

fatiando/mesher/mesh.py

XuesongDing/fatiando

57a0e0802fde2e53628511d3a7a2964e69bb309a

2015-01-12T17:04:57.000Z

2021-01-08T23:36:11.000Z

fatiando/mesher/mesh.py

XuesongDing/fatiando

57a0e0802fde2e53628511d3a7a2964e69bb309a

2015-01-29T18:51:22.000Z

2022-03-25T12:35:43.000Z

""" Meshes (collections) of geometric objects. Meshes behave like lists/arrays of geometric objects (they are iterables). """ from __future__ import division, absolute_import from future.builtins import range, object, super import numpy as np import scipy.special import scipy.interpolate import copy as cp from .. import gridder from .geometry import Square, Prism, Sphere, Tesseroid class SquareMesh(object): """ A 2D regular mesh of squares. For all purposes, :class:`~fatiando.mesher.SquareMesh` can be used as a list of :class:`~fatiando.mesher.Square`. The order of the squares in the list is: x directions varies first, then y. Parameters: * bounds : list = [x1, x2, y1, y2] Boundaries of the mesh * shape : tuple = (ny, nx) Number of squares in the y and x dimension, respectively * props : dict Physical properties of each square in the mesh. Each key should be the name of a physical property. The corresponding value should be a list with the values of that particular property on each square of the mesh. Examples: >>> mesh = SquareMesh((0, 4, 0, 6), (2, 2)) >>> for s in mesh: ... print s x1:0 | x2:2 | y1:0 | y2:3 x1:2 | x2:4 | y1:0 | y2:3 x1:0 | x2:2 | y1:3 | y2:6 x1:2 | x2:4 | y1:3 | y2:6 >>> print mesh[1] x1:2 | x2:4 | y1:0 | y2:3 >>> print mesh[-1] x1:2 | x2:4 | y1:3 | y2:6 With physical properties:: >>> mesh = SquareMesh((0, 4, 0, 6), (2, 1), {'slowness':[3.4, 8.6]}) >>> for s in mesh: ... print s x1:0 | x2:4 | y1:0 | y2:3 | slowness:3.4 x1:0 | x2:4 | y1:3 | y2:6 | slowness:8.6 Or:: >>> mesh = SquareMesh((0, 4, 0, 6), (2, 1)) >>> mesh.addprop('slowness', [3.4, 8.6]) >>> for s in mesh: ... print s x1:0 | x2:4 | y1:0 | y2:3 | slowness:3.4 x1:0 | x2:4 | y1:3 | y2:6 | slowness:8.6 """ def __init__(self, bounds, shape, props=None): ny, nx = shape size = int(nx * ny) x1, x2, y1, y2 = bounds dx = (x2 - x1)/nx dy = (y2 - y1)/ny self.bounds = bounds self.shape = tuple(int(i) for i in shape) self.size = size self.dims = (dx, dy) # props has to be None, not {} by default because {} would be permanent # for all instaces of the class (like a class variable) and changes # to one instace would lead to changes in another (and a huge mess) if props is None: self.props = {} else: self.props = props # The index of the current square in an iteration. Needed when mesh is # used as an iterator self.i = 0 # List of masked squares. Will return None if trying to access them self.mask = [] def __len__(self): return self.size def __getitem__(self, index): # To walk backwards in the list if index < 0: index = self.size + index if index in self.mask: return None ny, nx = self.shape j = index//nx i = index - j*nx x1 = self.bounds[0] + self.dims[0] * i x2 = x1 + self.dims[0] y1 = self.bounds[2] + self.dims[1] * j y2 = y1 + self.dims[1] props = dict([p, self.props[p][index]] for p in self.props) return Square((x1, x2, y1, y2), props=props) def __iter__(self): self.i = 0 return self def next(self): if self.i >= self.size: raise StopIteration square = self.__getitem__(self.i) self.i += 1 return square def addprop(self, prop, values): """ Add physical property values to the cells in the mesh. Different physical properties of the mesh are stored in a dictionary. Parameters: * prop : str Name of the physical property * values : list or array The value of this physical property in each square of the mesh. For the ordering of squares in the mesh see :class:`~fatiando.mesher.SquareMesh` """ self.props[prop] = values def get_xs(self): """ Get a list of the x coordinates of the corners of the cells in the mesh. If the mesh has nx cells, get_xs() will return nx + 1 values. """ dx, dy = self.dims x1, x2, y1, y2 = self.bounds ny, nx = self.shape xs = np.arange(x1, x2 + dx, dx, 'f') if len(xs) == nx + 2: return xs[0:-1] elif len(xs) == nx: xs = xs.tolist() xs.append(x2) return np.array(xs) else: return xs def get_ys(self): """ Get a list of the y coordinates of the corners of the cells in the mesh. If the mesh has ny cells, get_ys() will return ny + 1 values. """ dx, dy = self.dims x1, x2, y1, y2 = self.bounds ny, nx = self.shape ys = np.arange(y1, y2, dy, 'f') if len(ys) == ny + 2: return ys[0:-1] elif len(ys) == ny: ys = ys.tolist() ys.append(y2) return np.array(ys) else: return ys def copy(self): """ Return a deep copy of the current instance.""" return cp.deepcopy(self) class PointGrid(object): """ A regular grid of 3D point sources (spheres of unit volume). Use this as a 1D list of :class:`~fatiando.mesher.Sphere`. Grid points are ordered like a C matrix, first each row in a column, then change columns. In this case, the x direction (North-South) are the rows and y (East-West) are the columns. Parameters: * area : list = [x1, x2, y1, y2] The area where the grid will be spread out * z : float or 1d-array The z coordinates of each point in the grid (remember, z is positive downward). * shape : tuple = (nx, ny) The number of points in the x and y directions * props : dict Physical properties of each point in the grid. Each key should be the name of a physical property. The corresponding value should be a list with the values of that particular property for each point in the grid. Examples:: >>> g = PointGrid([0, 10, 2, 6], 200, (2, 3)) >>> g.shape (2, 3) >>> g.size 6 >>> g[0].center array([ 0., 2., 200.]) >>> g[-1].center array([ 10., 6., 200.]) >>> for p in g: ... p.center array([ 0., 2., 200.]) array([ 0., 4., 200.]) array([ 0., 6., 200.]) array([ 10., 2., 200.]) array([ 10., 4., 200.]) array([ 10., 6., 200.]) >>> g.x.reshape(g.shape) array([[ 0., 0., 0.], [ 10., 10., 10.]]) >>> g.y.reshape(g.shape) array([[ 2., 4., 6.], [ 2., 4., 6.]]) >>> g.dx, g.dy (10.0, 2.0) """ def __init__(self, area, z, shape, props=None): self.area = area self.shape = shape if props is None: self.props = {} else: self.props = props nx, ny = shape self.size = nx*ny self.z = np.zeros(self.size) + z self.radius = scipy.special.cbrt(3. / (4. * np.pi)) self.x, self.y = gridder.regular(area, shape) # The spacing between points self.dx, self.dy = gridder.spacing(area, shape) def __len__(self): return self.size def __getitem__(self, index): if not isinstance(index, int): raise IndexError('Invalid index type. Should be int.') if index >= self.size or index < -self.size: raise IndexError('Grid index out of range.') # To walk backwards in the list if index < 0: index = self.size + index props = dict([p, self.props[p][index]] for p in self.props) sphere = Sphere(self.x[index], self.y[index], self.z[index], self.radius, props=props) return sphere def __iter__(self): self.i = 0 return self def next(self): if self.i >= self.size: raise StopIteration sphere = self.__getitem__(self.i) self.i += 1 return sphere def addprop(self, prop, values): """ Add physical property values to the points in the grid. Different physical properties of the grid are stored in a dictionary. Parameters: * prop : str Name of the physical property. * values : list or array Value of this physical property in each point of the grid """ self.props[prop] = values def split(self, shape): """ Divide the grid into subgrids. .. note:: Remember that x is the North-South direction and y is East-West. Parameters: * shape : tuple = (nx, ny) Number of subgrids along the x and y directions, respectively. Returns: * subgrids : list List of :class:`~fatiando.mesher.PointGrid` Examples:: >>> import numpy as np >>> z = np.linspace(0, 1100, 12) >>> g = PointGrid((0, 3, 0, 2), z, (4, 3)) >>> g.addprop('bla', [1, 2, 3, ... 4, 5, 6, ... 7, 8, 9, ... 10, 11, 12]) >>> grids = g.split((2, 3)) >>> for s in grids: ... s.props['bla'] array([1, 4]) array([2, 5]) array([3, 6]) array([ 7, 10]) array([ 8, 11]) array([ 9, 12]) >>> for s in grids: ... s.x array([ 0., 1.]) array([ 0., 1.]) array([ 0., 1.]) array([ 2., 3.]) array([ 2., 3.]) array([ 2., 3.]) >>> for s in grids: ... s.y array([ 0., 0.]) array([ 1., 1.]) array([ 2., 2.]) array([ 0., 0.]) array([ 1., 1.]) array([ 2., 2.]) >>> for s in grids: ... s.z array([ 0., 300.]) array([ 100., 400.]) array([ 200., 500.]) array([ 600., 900.]) array([ 700., 1000.]) array([ 800., 1100.]) """ nx, ny = shape totalx, totaly = self.shape if totalx % nx != 0 or totaly % ny != 0: raise ValueError( 'Cannot split! nx and ny must be divisible by grid shape') x1, x2, y1, y2 = self.area xs = np.linspace(x1, x2, totalx) ys = np.linspace(y1, y2, totaly) mx, my = (totalx//nx, totaly//ny) dx, dy = self.dx*(mx - 1), self.dy*(my - 1) subs = [] for i, xstart in enumerate(xs[::mx]): for j, ystart in enumerate(ys[::my]): area = [xstart, xstart + dx, ystart, ystart + dy] props = {} for p in self.props: pmatrix = np.reshape(self.props[p], self.shape) props[p] = pmatrix[i*mx:(i + 1)*mx, j*my:(j + 1)*my].ravel() zmatrix = np.reshape(self.z, self.shape) zs = zmatrix[i*mx:(i + 1)*mx, j*my:(j + 1)*my].ravel() subs.append(PointGrid(area, zs, (mx, my), props)) return subs def copy(self): """ Return a deep copy of the current instance.""" return cp.deepcopy(self) class PrismRelief(object): """ A 3D model of a relief (topography) using prisms. Use to generate: * topographic model * basin model * Moho model * etc PrismRelief can used as list of prisms. It acts as an iteratior (so you can loop over prisms). It also has a ``__getitem__`` method to access individual elements in the mesh. In practice, PrismRelief should be able to be passed to any function that asks for a list of prisms, like :func:`fatiando.gravmag.prism.gz`. Parameters: * ref : float Reference level. Prisms will have: * bottom on zref and top on z if z > zref; * bottom on z and top on zref otherwise. * dims : tuple = (dy, dx) Dimensions of the prisms in the y and x directions * nodes : list of lists = [x, y, z] Coordinates of the center of the top face of each prism.x, y, and z are lists with the x, y and z coordinates on a regular grid. """ def __init__(self, ref, dims, nodes): x, y, z = nodes if len(x) != len(y) != len(z): raise ValueError( "nodes has x, y, z coordinate arrays of different lengths") self.x, self.y, self.z = x, y, z self.size = len(x) self.ref = ref self.dy, self.dx = dims self.props = {} # The index of the current prism in an iteration. Needed when mesh is # used as an iterator self.i = 0 def __len__(self): return self.size def __iter__(self): self.i = 0 return self def __getitem__(self, index): # To walk backwards in the list if index < 0: index = self.size + index xc, yc, zc = self.x[index], self.y[index], self.z[index] x1 = xc - 0.5 * self.dx x2 = xc + 0.5 * self.dx y1 = yc - 0.5 * self.dy y2 = yc + 0.5 * self.dy if zc <= self.ref: z1 = zc z2 = self.ref else: z1 = self.ref z2 = zc props = dict([p, self.props[p][index]] for p in self.props) return Prism(x1, x2, y1, y2, z1, z2, props=props) def next(self): if self.i >= self.size: raise StopIteration prism = self.__getitem__(self.i) self.i += 1 return prism def addprop(self, prop, values): """ Add physical property values to the prisms. .. warning:: If the z value of any point in the relief is below the reference level, its corresponding prism will have the physical property value with oposite sign than was assigned to it. Parameters: * prop : str Name of the physical property. * values : list List or array with the value of this physical property in each prism of the relief. """ def correct(v, i): if self.z[i] > self.ref: return -v return v self.props[prop] = [correct(v, i) for i, v in enumerate(values)] def copy(self): """ Return a deep copy of the current instance.""" return cp.deepcopy(self) class PrismMesh(object): """ A 3D regular mesh of right rectangular prisms. Prisms are ordered as follows: first layers (z coordinate), then EW rows (y) and finaly x coordinate (NS). .. note:: Remember that the coordinate system is x->North, y->East and z->Down Ex: in a mesh with shape ``(3,3,3)`` the 15th element (index 14) has z index 1 (second layer), y index 1 (second row), and x index 2 (third element in the column). :class:`~fatiando.mesher.PrismMesh` can used as list of prisms. It acts as an iteratior (so you can loop over prisms). It also has a ``__getitem__`` method to access individual elements in the mesh. In practice, :class:`~fatiando.mesher.PrismMesh` should be able to be passed to any function that asks for a list of prisms, like :func:`fatiando.gravmag.prism.gz`. To make the mesh incorporate a topography, use :meth:`~fatiando.mesher.PrismMesh.carvetopo` Parameters: * bounds : list = [xmin, xmax, ymin, ymax, zmin, zmax] Boundaries of the mesh. * shape : tuple = (nz, ny, nx) Number of prisms in the x, y, and z directions. * props : dict Physical properties of each prism in the mesh. Each key should be the name of a physical property. The corresponding value should be a list with the values of that particular property on each prism of the mesh. Examples: >>> from fatiando.mesher import PrismMesh >>> mesh = PrismMesh((0, 1, 0, 2, 0, 3), (1, 2, 2)) >>> for p in mesh: ... print p x1:0 | x2:0.5 | y1:0 | y2:1 | z1:0 | z2:3 x1:0.5 | x2:1 | y1:0 | y2:1 | z1:0 | z2:3 x1:0 | x2:0.5 | y1:1 | y2:2 | z1:0 | z2:3 x1:0.5 | x2:1 | y1:1 | y2:2 | z1:0 | z2:3 >>> print mesh[0] x1:0 | x2:0.5 | y1:0 | y2:1 | z1:0 | z2:3 >>> print mesh[-1] x1:0.5 | x2:1 | y1:1 | y2:2 | z1:0 | z2:3 One with physical properties:: >>> props = {'density':[2670.0, 1000.0]} >>> mesh = PrismMesh((0, 2, 0, 4, 0, 3), (1, 1, 2), props=props) >>> for p in mesh: ... print p x1:0 | x2:1 | y1:0 | y2:4 | z1:0 | z2:3 | density:2670 x1:1 | x2:2 | y1:0 | y2:4 | z1:0 | z2:3 | density:1000 or equivalently:: >>> mesh = PrismMesh((0, 2, 0, 4, 0, 3), (1, 1, 2)) >>> mesh.addprop('density', [200, -1000.0]) >>> for p in mesh: ... print p x1:0 | x2:1 | y1:0 | y2:4 | z1:0 | z2:3 | density:200 x1:1 | x2:2 | y1:0 | y2:4 | z1:0 | z2:3 | density:-1000 You can use :meth:`~fatiando.mesher.PrismMesh.get_xs` (and similar methods for y and z) to get the x coordinates of the prisms in the mesh:: >>> mesh = PrismMesh((0, 2, 0, 4, 0, 3), (1, 1, 2)) >>> print mesh.get_xs() [ 0. 1. 2.] >>> print mesh.get_ys() [ 0. 4.] >>> print mesh.get_zs() [ 0. 3.] The ``shape`` of the mesh must be integer! >>> mesh = PrismMesh((0, 2, 0, 4, 0, 3), (1, 1, 2.5)) Traceback (most recent call last): ... AttributeError: Invalid mesh shape (1, 1, 2.5). shape must be integers """ celltype = Prism def __init__(self, bounds, shape, props=None): nz, ny, nx = shape if not isinstance(nx, int) or not isinstance(ny, int) or \ not isinstance(nz, int): raise AttributeError( 'Invalid mesh shape {}. shape must be integers'.format( str(shape))) size = int(nx * ny * nz) x1, x2, y1, y2, z1, z2 = bounds dx = (x2 - x1)/nx dy = (y2 - y1)/ny dz = (z2 - z1)/nz self.shape = tuple(int(i) for i in shape) self.size = size self.dims = (dx, dy, dz) self.bounds = bounds if props is None: self.props = {} else: self.props = props # The index of the current prism in an iteration. Needed when mesh is # used as an iterator self.i = 0 # List of masked prisms. Will return None if trying to access them self.mask = [] # Wether or not to change heights to z coordinate self.zdown = True def __len__(self): return self.size def __getitem__(self, index): if index >= self.size or index < -self.size: raise IndexError('mesh index out of range') # To walk backwards in the list if index < 0: index = self.size + index if index in self.mask: return None nz, ny, nx = self.shape k = index//(nx*ny) j = (index - k*(nx*ny))//nx i = (index - k*(nx*ny) - j*nx) x1 = self.bounds[0] + self.dims[0] * i x2 = x1 + self.dims[0] y1 = self.bounds[2] + self.dims[1] * j y2 = y1 + self.dims[1] z1 = self.bounds[4] + self.dims[2] * k z2 = z1 + self.dims[2] props = dict([p, self.props[p][index]] for p in self.props) return self.celltype(x1, x2, y1, y2, z1, z2, props=props) def __iter__(self): self.i = 0 return self def next(self): if self.i >= self.size: raise StopIteration prism = self.__getitem__(self.i) self.i += 1 return prism def addprop(self, prop, values): """ Add physical property values to the cells in the mesh. Different physical properties of the mesh are stored in a dictionary. Parameters: * prop : str Name of the physical property. * values : list or array Value of this physical property in each prism of the mesh. For the ordering of prisms in the mesh see :class:`~fatiando.mesher.PrismMesh` """ self.props[prop] = values def carvetopo(self, x, y, height, below=False): """ Mask (remove) prisms from the mesh that are above the topography. Accessing the ith prism will return None if it was masked (above the topography). Also mask prisms outside of the topography grid provided. The topography height information does not need to be on a regular grid, it will be interpolated. Parameters: * x, y : lists x and y coordinates of the grid points * height : list or array Array with the height of the topography * below : boolean Will mask prisms below the input surface if set to *True*. """ nz, ny, nx = self.shape x1, x2, y1, y2, z1, z2 = self.bounds dx, dy, dz = self.dims # The coordinates of the centers of the cells xc = np.arange(x1, x2, dx) + 0.5 * dx # Sometimes arange returns more due to rounding if len(xc) > nx: xc = xc[:-1] yc = np.arange(y1, y2, dy) + 0.5 * dy if len(yc) > ny: yc = yc[:-1] zc = np.arange(z1, z2, dz) + 0.5 * dz if len(zc) > nz: zc = zc[:-1] XC, YC = np.meshgrid(xc, yc) topo = scipy.interpolate.griddata((x, y), height, (XC, YC), method='cubic').ravel() if self.zdown: # -1 if to transform height into z coordinate topo = -1 * topo # griddata returns a masked array. If the interpolated point is out of # of the data range, mask will be True. Use this to remove all cells # below a masked topo point (ie, one with no height information) if np.ma.isMA(topo): topo_mask = topo.mask else: topo_mask = [False for i in range(len(topo))] c = 0 for cellz in zc: for h, masked in zip(topo, topo_mask): if below: if (masked or (cellz > h and self.zdown) or (cellz < h and not self.zdown)): self.mask.append(c) else: if (masked or (cellz < h and self.zdown) or (cellz > h and not self.zdown)): self.mask.append(c) c += 1 def get_xs(self): """ Return an array with the x coordinates of the prisms in mesh. """ x1, x2, y1, y2, z1, z2 = self.bounds dx, dy, dz = self.dims nz, ny, nx = self.shape xs = np.arange(x1, x2 + dx, dx) if xs.size > nx + 1: return xs[:-1] return xs def get_ys(self): """ Return an array with the y coordinates of the prisms in mesh. """ x1, x2, y1, y2, z1, z2 = self.bounds dx, dy, dz = self.dims nz, ny, nx = self.shape ys = np.arange(y1, y2 + dy, dy) if ys.size > ny + 1: return ys[:-1] return ys def get_zs(self): """ Return an array with the z coordinates of the prisms in mesh. """ x1, x2, y1, y2, z1, z2 = self.bounds dx, dy, dz = self.dims nz, ny, nx = self.shape zs = np.arange(z1, z2 + dz, dz) if zs.size > nz + 1: return zs[:-1] return zs def get_layer(self, i): """ Return the set of prisms corresponding to the ith layer of the mesh. Parameters: * i : int The index of the layer Returns: * prisms : list of :class:`~fatiando.mesher.Prism` The prisms in the ith layer Examples:: >>> mesh = PrismMesh((0, 2, 0, 2, 0, 2), (2, 2, 2)) >>> layer = mesh.get_layer(0) >>> for p in layer: ... print p x1:0 | x2:1 | y1:0 | y2:1 | z1:0 | z2:1 x1:1 | x2:2 | y1:0 | y2:1 | z1:0 | z2:1 x1:0 | x2:1 | y1:1 | y2:2 | z1:0 | z2:1 x1:1 | x2:2 | y1:1 | y2:2 | z1:0 | z2:1 >>> layer = mesh.get_layer(1) >>> for p in layer: ... print p x1:0 | x2:1 | y1:0 | y2:1 | z1:1 | z2:2 x1:1 | x2:2 | y1:0 | y2:1 | z1:1 | z2:2 x1:0 | x2:1 | y1:1 | y2:2 | z1:1 | z2:2 x1:1 | x2:2 | y1:1 | y2:2 | z1:1 | z2:2 """ nz, ny, nx = self.shape if i >= nz or i < 0: raise IndexError('Layer index %d is out of range.' % (i)) start = i * nx * ny end = (i + 1) * nx * ny layer = [self.__getitem__(p) for p in range(start, end)] return layer def layers(self): """ Returns an iterator over the layers of the mesh. Examples:: >>> mesh = PrismMesh((0, 2, 0, 2, 0, 2), (2, 2, 2)) >>> for layer in mesh.layers(): ... for p in layer: ... print p x1:0 | x2:1 | y1:0 | y2:1 | z1:0 | z2:1 x1:1 | x2:2 | y1:0 | y2:1 | z1:0 | z2:1 x1:0 | x2:1 | y1:1 | y2:2 | z1:0 | z2:1 x1:1 | x2:2 | y1:1 | y2:2 | z1:0 | z2:1 x1:0 | x2:1 | y1:0 | y2:1 | z1:1 | z2:2 x1:1 | x2:2 | y1:0 | y2:1 | z1:1 | z2:2 x1:0 | x2:1 | y1:1 | y2:2 | z1:1 | z2:2 x1:1 | x2:2 | y1:1 | y2:2 | z1:1 | z2:2 """ nz, ny, nx = self.shape for i in range(nz): yield self.get_layer(i) def dump(self, meshfile, propfile, prop): r""" Dump the mesh to a file in the format required by UBC-GIF program MeshTools3D. Parameters: * meshfile : str or file Output file to save the mesh. Can be a file name or an open file. * propfile : str or file Output file to save the physical properties *prop*. Can be a file name or an open file. * prop : str The name of the physical property in the mesh that will be saved to *propfile*. .. note:: Uses -10000000 as the dummy value for plotting topography Examples: >>> from StringIO import StringIO >>> meshfile = StringIO() >>> densfile = StringIO() >>> mesh = PrismMesh((0, 10, 0, 20, 0, 5), (1, 2, 2)) >>> mesh.addprop('density', [1, 2, 3, 4]) >>> mesh.dump(meshfile, densfile, 'density') >>> print meshfile.getvalue().strip() 2 2 1 0 0 0 2*10 2*5 1*5 >>> print densfile.getvalue().strip() 1.0000 3.0000 2.0000 4.0000 """ if prop not in self.props: raise ValueError("mesh doesn't have a '%s' property." % (prop)) isstr = False if isinstance(meshfile, str): isstr = True meshfile = open(meshfile, 'w') nz, ny, nx = self.shape x1, x2, y1, y2, z1, z2 = self.bounds dx, dy, dz = self.dims meshfile.writelines([ "%d %d %d\n" % (ny, nx, nz), "%g %g %g\n" % (y1, x1, -z1), "%d*%g\n" % (ny, dy), "%d*%g\n" % (nx, dx), "%d*%g" % (nz, dz)]) if isstr: meshfile.close() values = np.fromiter(self.props[prop], dtype=np.float) # Replace the masked cells with a dummy value values[self.mask] = -10000000 reordered = np.ravel(np.reshape(values, self.shape), order='F') np.savetxt(propfile, reordered, fmt='%.4f') def copy(self): """ Return a deep copy of the current instance.""" return cp.deepcopy(self) class TesseroidMesh(PrismMesh): """ A 3D regular mesh of tesseroids. Tesseroids are ordered as follows: first layers (height coordinate), then N-S rows and finaly E-W. Ex: in a mesh with shape ``(3,3,3)`` the 15th element (index 14) has height index 1 (second layer), y index 1 (second row), and x index 2 ( third element in the column). This class can used as list of tesseroids. It acts as an iteratior (so you can loop over tesseroids). It also has a ``__getitem__`` method to access individual elements in the mesh. In practice, it should be able to be passed to any function that asks for a list of tesseroids, like :func:`fatiando.gravmag.tesseroid.gz`. To make the mesh incorporate a topography, use :meth:`~fatiando.mesher.TesseroidMesh.carvetopo` Parameters: * bounds : list = [w, e, s, n, top, bottom] Boundaries of the mesh. ``w, e, s, n`` in degrees, ``top`` and ``bottom`` are heights (positive upward) and in meters. * shape : tuple = (nr, nlat, nlon) Number of tesseroids in the radial, latitude, and longitude directions. * props : dict Physical properties of each tesseroid in the mesh. Each key should be the name of a physical property. The corresponding value should be a list with the values of that particular property on each tesseroid of the mesh. Examples: >>> from fatiando.mesher import TesseroidMesh >>> mesh = TesseroidMesh((0, 1, 0, 2, 3, 0), (1, 2, 2)) >>> for p in mesh: ... print p w:0 | e:0.5 | s:0 | n:1 | top:3 | bottom:0 w:0.5 | e:1 | s:0 | n:1 | top:3 | bottom:0 w:0 | e:0.5 | s:1 | n:2 | top:3 | bottom:0 w:0.5 | e:1 | s:1 | n:2 | top:3 | bottom:0 >>> print mesh[0] w:0 | e:0.5 | s:0 | n:1 | top:3 | bottom:0 >>> print mesh[-1] w:0.5 | e:1 | s:1 | n:2 | top:3 | bottom:0 One with physical properties:: >>> props = {'density':[2670.0, 1000.0]} >>> mesh = TesseroidMesh((0, 2, 0, 4, 3, 0), (1, 1, 2), props=props) >>> for p in mesh: ... print p w:0 | e:1 | s:0 | n:4 | top:3 | bottom:0 | density:2670 w:1 | e:2 | s:0 | n:4 | top:3 | bottom:0 | density:1000 or equivalently:: >>> mesh = TesseroidMesh((0, 2, 0, 4, 3, 0), (1, 1, 2)) >>> mesh.addprop('density', [200, -1000.0]) >>> for p in mesh: ... print p w:0 | e:1 | s:0 | n:4 | top:3 | bottom:0 | density:200 w:1 | e:2 | s:0 | n:4 | top:3 | bottom:0 | density:-1000 You can use :meth:`~fatiando.mesher.PrismMesh.get_xs` (and similar methods for y and z) to get the x coordinates of the tesseroidss in the mesh:: >>> mesh = TesseroidMesh((0, 2, 0, 4, 3, 0), (1, 1, 2)) >>> print mesh.get_xs() [ 0. 1. 2.] >>> print mesh.get_ys() [ 0. 4.] >>> print mesh.get_zs() [ 3. 0.] You can iterate over the layers of the mesh:: >>> mesh = TesseroidMesh((0, 2, 0, 2, 2, 0), (2, 2, 2)) >>> for layer in mesh.layers(): ... for p in layer: ... print p w:0 | e:1 | s:0 | n:1 | top:2 | bottom:1 w:1 | e:2 | s:0 | n:1 | top:2 | bottom:1 w:0 | e:1 | s:1 | n:2 | top:2 | bottom:1 w:1 | e:2 | s:1 | n:2 | top:2 | bottom:1 w:0 | e:1 | s:0 | n:1 | top:1 | bottom:0 w:1 | e:2 | s:0 | n:1 | top:1 | bottom:0 w:0 | e:1 | s:1 | n:2 | top:1 | bottom:0 w:1 | e:2 | s:1 | n:2 | top:1 | bottom:0 The ``shape`` of the mesh must be integer! >>> mesh = TesseroidMesh((0, 2, 0, 4, 0, 3), (1, 1, 2.5)) Traceback (most recent call last): ... AttributeError: Invalid mesh shape (1, 1, 2.5). shape must be integers """ celltype = Tesseroid def __init__(self, bounds, shape, props=None): super().__init__(bounds, shape, props) self.zdown = False self.dump = None

793f786a9803233d334db38aa3df8b8d7f9fd917

py

Python

Software/Python/grove_co2_sensor/grove_co2_example.py

electricpocket/GroveBBB

336b10c903dcacc251bbb2506944e1ca7484c86d

Software/Python/grove_co2_sensor/grove_co2_example.py

electricpocket/GroveBBB

336b10c903dcacc251bbb2506944e1ca7484c86d

Software/Python/grove_co2_sensor/grove_co2_example.py

electricpocket/GroveBBB

336b10c903dcacc251bbb2506944e1ca7484c86d

#!/usr/bin/env python # # GrovePi Example for using the Grove - CO2 Sensor(http://www.seeedstudio.com/depot/Grove-CO2-Sensor-p-1863.html) # # The GrovePi connects the Raspberry Pi and Grove sensors. You can learn more about GrovePi here: http://www.dexterindustries.com/GrovePi # # Have a question about this example? Ask on the forums here: http://www.dexterindustries.com/forum/?forum=grovepi # ''' ## License The MIT License (MIT) GrovePi for the Raspberry Pi: an open source platform for connecting Grove Sensors to the Raspberry Pi. Copyright (C) 2015 Dexter Industries 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. ''' # Connect the CO2 sensor to the RPISER port on the GrovePi import grove_co2_lib import time co2= grove_co2_lib.CO2() while True: [ppm,temp]= co2.read() print("CO2 Conc: %d ppm\t Temp: %d C" %(ppm,temp)) time.sleep(1)

793f7bf40b7b234edb8137e9245bbf40a4537087

py

Python

configs/swa/swa_cascade_s50_rfp_mstrain_aug.py

NEUdeep/TileDetection

f453ac868de195a7859b9bf07c813e46eb35d2d0

2021-03-23T23:43:00.000Z

2022-03-22T12:42:53.000Z

configs/swa/swa_cascade_s50_rfp_mstrain_aug.py

hlcedu/TileDetection

77b5ef4bb4db29f5ffe6a6fa9f87b4bfe8516e4c

2021-09-12T13:04:34.000Z

2022-03-23T07:29:43.000Z

configs/swa/swa_cascade_s50_rfp_mstrain_aug.py

hlcedu/TileDetection

77b5ef4bb4db29f5ffe6a6fa9f87b4bfe8516e4c

2021-03-31T03:21:43.000Z

2021-12-27T08:50:13.000Z

_base_ = ['../tile_round2/cascade_s50_rfp_mstrain.py', '../_base_/swa.py'] only_swa_training = True # whether to perform swa training swa_training = True # load the best pre_trained model as the starting model for swa training swa_load_from = 'work_dirs/round2/cascade_s50_rfp_mstrain_aug_alldata/latest.pth' swa_resume_from = None # swa optimizer swa_optimizer = dict(_delete_=True, type='Adam', lr=7e-5) swa_optimizer_config = dict(grad_clip=None) # swa learning policy swa_lr_config = dict( policy='cyclic', target_ratio=(1, 0.01), cyclic_times=12, step_ratio_up=0.0) swa_total_epochs = 12 # swa checkpoint setting swa_checkpoint_config = dict(interval=1, filename_tmpl='swa_epoch_{}.pth') work_dir = 'work_dirs/round2/swa_cascade_s50_rfp_mstrain_aug'

793f7bf8a56a3147e060b10df36e3a9bd3ab1265

py

Python

setup.py

3rwww1/setuptools_scm_azure_pipelines

24c9db0ce0b3f5bfd5ffe8be9550b97350eefe6b

setup.py

3rwww1/setuptools_scm_azure_pipelines

24c9db0ce0b3f5bfd5ffe8be9550b97350eefe6b

setup.py

3rwww1/setuptools_scm_azure_pipelines

24c9db0ce0b3f5bfd5ffe8be9550b97350eefe6b

#!/usr/bin/env python import setuptools if __name__ == '__main__': setuptools.setup()

793f7cbb82bbc1eb6a8844b9e5e744c7d2816a6d

py

Python

qa/rpc-tests/prioritise_transaction.py

v-core/v

f87e0fb859aae6aa7de8b3816093bf900fdcce42

2018-01-19T19:29:29.000Z

2018-01-19T19:29:29.000Z

qa/rpc-tests/prioritise_transaction.py

v-core/v

f87e0fb859aae6aa7de8b3816093bf900fdcce42

qa/rpc-tests/prioritise_transaction.py

v-core/v

f87e0fb859aae6aa7de8b3816093bf900fdcce42

#!/usr/bin/env python2 # Copyright (c) 2015 The VCoin Core developers # Distributed under the MIT software license, see the accompanying # file COPYING or http://www.opensource.org/licenses/mit-license.php. # # Test PrioritiseTransaction code # from test_framework.test_framework import VCoinTestFramework from test_framework.util import * COIN = 100000000 class PrioritiseTransactionTest(VCoinTestFramework): def __init__(self): self.txouts = gen_return_txouts() def setup_chain(self): print("Initializing test directory "+self.options.tmpdir) initialize_chain_clean(self.options.tmpdir, 1) def setup_network(self): self.nodes = [] self.is_network_split = False self.nodes.append(start_node(0, self.options.tmpdir, ["-debug", "-printpriority=1"])) self.relayfee = self.nodes[0].getnetworkinfo()['relayfee'] def run_test(self): utxos = create_confirmed_utxos(self.relayfee, self.nodes[0], 90) base_fee = self.relayfee*100 # our transactions are smaller than 100kb txids = [] # Create 3 batches of transactions at 3 different fee rate levels for i in xrange(3): txids.append([]) txids[i] = create_lots_of_big_transactions(self.nodes[0], self.txouts, utxos[30*i:30*i+30], (i+1)*base_fee) # add a fee delta to something in the cheapest bucket and make sure it gets mined # also check that a different entry in the cheapest bucket is NOT mined (lower # the priority to ensure its not mined due to priority) self.nodes[0].prioritisetransaction(txids[0][0], 0, int(3*base_fee*COIN)) self.nodes[0].prioritisetransaction(txids[0][1], -1e15, 0) self.nodes[0].generate(1) mempool = self.nodes[0].getrawmempool() print "Assert that prioritised transasction was mined" assert(txids[0][0] not in mempool) assert(txids[0][1] in mempool) high_fee_tx = None for x in txids[2]: if x not in mempool: high_fee_tx = x # Something high-fee should have been mined! assert(high_fee_tx != None) # Add a prioritisation before a tx is in the mempool (de-prioritising a # high-fee transaction). self.nodes[0].prioritisetransaction(high_fee_tx, -1e15, -int(2*base_fee*COIN)) # Add everything back to mempool self.nodes[0].invalidateblock(self.nodes[0].getbestblockhash()) # Check to make sure our high fee rate tx is back in the mempool mempool = self.nodes[0].getrawmempool() assert(high_fee_tx in mempool) # Now verify the high feerate transaction isn't mined. self.nodes[0].generate(5) # High fee transaction should not have been mined, but other high fee rate # transactions should have been. mempool = self.nodes[0].getrawmempool() print "Assert that de-prioritised transaction is still in mempool" assert(high_fee_tx in mempool) for x in txids[2]: if (x != high_fee_tx): assert(x not in mempool) # Create a free, low priority transaction. Should be rejected. utxo_list = self.nodes[0].listunspent() assert(len(utxo_list) > 0) utxo = utxo_list[0] inputs = [] outputs = {} inputs.append({"txid" : utxo["txid"], "vout" : utxo["vout"]}) outputs[self.nodes[0].getnewaddress()] = utxo["amount"] - self.relayfee raw_tx = self.nodes[0].createrawtransaction(inputs, outputs) tx_hex = self.nodes[0].signrawtransaction(raw_tx)["hex"] txid = self.nodes[0].sendrawtransaction(tx_hex) # A tx that spends an in-mempool tx has 0 priority, so we can use it to # test the effect of using prioritise transaction for mempool acceptance inputs = [] inputs.append({"txid": txid, "vout": 0}) outputs = {} outputs[self.nodes[0].getnewaddress()] = utxo["amount"] - self.relayfee raw_tx2 = self.nodes[0].createrawtransaction(inputs, outputs) tx2_hex = self.nodes[0].signrawtransaction(raw_tx2)["hex"] tx2_id = self.nodes[0].decoderawtransaction(tx2_hex)["txid"] try: self.nodes[0].sendrawtransaction(tx2_hex) except JSONRPCException as exp: assert_equal(exp.error['code'], -26) # insufficient fee assert(tx2_id not in self.nodes[0].getrawmempool()) else: assert(False) # This is a less than 1000-byte transaction, so just set the fee # to be the minimum for a 1000 byte transaction and check that it is # accepted. self.nodes[0].prioritisetransaction(tx2_id, 0, int(self.relayfee*COIN)) print "Assert that prioritised free transaction is accepted to mempool" assert_equal(self.nodes[0].sendrawtransaction(tx2_hex), tx2_id) assert(tx2_id in self.nodes[0].getrawmempool()) if __name__ == '__main__': PrioritiseTransactionTest().main()

793f7cc577d79f7a3e08d13e99a84457f0eb0f17

py

Python

assets/cloudformation/function_copy_website/lambda_function.py

mayis214/multi-channel-customer-engagement

46aa67e0feb78d5c68dd1695835d437b9f9c75f9

2021-02-05T03:38:20.000Z

2021-09-04T11:17:33.000Z

assets/cloudformation/function_copy_website/lambda_function.py

mayis214/multi-channel-customer-engagement

46aa67e0feb78d5c68dd1695835d437b9f9c75f9

2020-12-03T15:15:25.000Z

2021-06-04T15:31:05.000Z

assets/cloudformation/function_copy_website/lambda_function.py

mayis214/multi-channel-customer-engagement

46aa67e0feb78d5c68dd1695835d437b9f9c75f9

2020-11-27T21:41:40.000Z

2022-03-29T19:28:24.000Z

import json import boto3 from crhelper import CfnResource import os helper = CfnResource() s3 = boto3.client('s3') s3_resource = boto3.resource('s3') sourceBucket = os.environ['s3sourceBucket'] sourcePrefix = os.environ['s3sourcePrefix'] destinationbucket = os.environ['s3destinationBucket'] def lambda_handler(event, context): helper(event, context) @helper.create @helper.update def copy_website(event, _): bucket = s3_resource.Bucket(sourceBucket) for object in bucket.objects.filter(Prefix=sourcePrefix): file = object.key try: copy_source = {'Bucket': sourceBucket, 'Key': file} s3_resource.meta.client.copy( copy_source, destinationbucket, file.replace(sourcePrefix, "")) except: print("An exception occurred copying: " + file) @helper.delete def delete_website(_, __): for object in s3_resource.Bucket(destinationbucket).objects.all(): s3.delete_object(Bucket=destinationbucket, Key=object.key) bucket = s3_resource.Bucket(destinationbucket) bucket.object_versions.delete()

793f7d23bb63769e42c24564025740593eb9c1e4

py

Python

working version coz cached/GDP_Access/GdpAxsHaitian.py

cyrildarevo/genPassportScore

ff4a761f9b46606ac588ac92e089548a9e834557

2018-09-21T19:32:24.000Z

2018-10-04T14:30:47.000Z

working version coz cached/GDP_Access/GdpAxsHaitian.py

cyrildarevo/genPassportScore

ff4a761f9b46606ac588ac92e089548a9e834557

2020-02-11T08:00:32.000Z

2020-02-11T08:00:32.000Z

working version coz cached/GDP_Access/GdpAxsHaitian.py

cyrildarevo/genPassportScore

ff4a761f9b46606ac588ac92e089548a9e834557

#GDP Access List forHaiti GDPtable = [{'Country': 'Haiti', 'GDP_Access': 8360.0, 'VisaRequirement': 'Freedom of Movement', 'VisaTemplate': 'free'}, {'Country': 'Afghanistan', 'GDP_Access': 8355.6, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Albania', 'GDP_Access': 5200.4, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Algeria', 'GDP_Access': 71314.8, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Andorra', 'GDP_Access': 1205.2, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Angola', 'GDP_Access': 49683.6, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Antigua and Barbuda', 'GDP_Access': 767.5, 'VisaRequirement': 'Electronic Visa', 'VisaTemplate': 'yes2'}, {'Country': 'Argentina', 'GDP_Access': 255086.8, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Armenia', 'GDP_Access': 7725.9, 'VisaRequirement': 'Visa on Arrival', 'VisaTemplate': 'Optional'}, {'Country': 'Australia', 'GDP_Access': 551819.2, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Austria', 'GDP_Access': 166738.0, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Azerbaijan', 'GDP_Access': 16268.0, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Bahamas', 'GDP_Access': 3650.8, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Bahrain', 'GDP_Access': 13958.0, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Bangladesh', 'GDP_Access': 104549.6, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Barbados', 'GDP_Access': 1928.4, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Belarus', 'GDP_Access': 21774.4, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Belgium', 'GDP_Access': 197893.2, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Belize', 'GDP_Access': 727.6, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Benin', 'GDP_Access': 8469.0, 'VisaRequirement': 'Visa not Required', 'VisaTemplate': 'yes'}, {'Country': 'Bhutan', 'GDP_Access': 928.4, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Bolivia', 'GDP_Access': 25985.4, 'VisaRequirement': 'Visa on Arrival', 'VisaTemplate': 'yes-no'}, {'Country': 'Bosnia and Herzegovina', 'GDP_Access': 6982.8, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Botswana', 'GDP_Access': 6690.0, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Brazil', 'GDP_Access': 821987.6, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Brunei', 'GDP_Access': 4785.2, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Bulgaria', 'GDP_Access': 22777.2, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Burkina Faso', 'GDP_Access': 5274.8, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Burundi', 'GDP_Access': 1357.2, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Cambodia', 'GDP_Access': 15576.4, 'VisaRequirement': 'Visa on Arrival', 'VisaTemplate': 'Optional'}, {'Country': 'Cameroon', 'GDP_Access': 13602.4, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Canada', 'GDP_Access': 660964.8, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Cape Verde', 'GDP_Access': 1209.6, 'VisaRequirement': 'Visa on Arrival', 'VisaTemplate': 'yes-no'}, {'Country': 'Central African Republic', 'GDP_Access': 796.8, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Chad', 'GDP_Access': 3896.0, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Chile', 'GDP_Access': 110816.8, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'China', 'GDP_Access': 4805844.0, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Colombia', 'GDP_Access': 123678.8, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Comoros', 'GDP_Access': 461.3, 'VisaRequirement': 'Visa on Arrival', 'VisaTemplate': 'yes-no'}, {'Country': 'Republic of the Congo', 'GDP_Access': 16576.4, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Democratic Republic of the Congo', 'GDP_Access': 16576.4, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Costa Rica', 'GDP_Access': 23222.4, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Ivory Coast', 'GDP_Access': 16144.0, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Croatia', 'GDP_Access': 21806.4, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Cuba', 'GDP_Access': 35875.6, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Cyprus', 'GDP_Access': 8524.0, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Czech Republic', 'GDP_Access': 85275.6, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Denmark', 'GDP_Access': 129793.6, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Djibouti', 'GDP_Access': 1041.0, 'VisaRequirement': 'Electronic Visa', 'VisaTemplate': 'yes2'}, {'Country': 'Dominica', 'GDP_Access': 67516.2, 'VisaRequirement': 'Visa not Required', 'VisaTemplate': 'yes'}, {'Country': 'Dominican Republic', 'GDP_Access': 30007.2, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Ecuador', 'GDP_Access': 40924.4, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Egypt', 'GDP_Access': 165951.1, 'VisaRequirement': 'Visa on Arrival', 'VisaTemplate': 'yes-no'}, {'Country': 'El Salvador', 'GDP_Access': 11209.2, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Equatorial Guinea', 'GDP_Access': 4027.6, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Eritrea', 'GDP_Access': 2420.0, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Estonia', 'GDP_Access': 10389.2, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Ethiopia', 'GDP_Access': 40437.0, 'VisaRequirement': 'Electronic Visa', 'VisaTemplate': 'yes2'}, {'Country': 'Fiji', 'GDP_Access': 2021.6, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Finland', 'GDP_Access': 101297.6, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'France', 'GDP_Access': 1033424.0, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Gabon', 'GDP_Access': 7233.5, 'VisaRequirement': 'Electronic Visa', 'VisaTemplate': 'yes2'}, {'Country': 'Gambia', 'GDP_Access': 934.2, 'VisaRequirement': 'Visa not Required', 'VisaTemplate': 'yes'}, {'Country': 'Georgia', 'GDP_Access': 7615.0, 'VisaRequirement': 'Electronic Visa', 'VisaTemplate': 'yes2'}, {'Country': 'Germany', 'GDP_Access': 1473926.4, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Ghana', 'GDP_Access': 18812.8, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Greece', 'GDP_Access': 80276.0, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Grenada', 'GDP_Access': 444.4, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Guatemala', 'GDP_Access': 30264.4, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Guinea', 'GDP_Access': 9446.8, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Guinea-Bissau', 'GDP_Access': 6428.1, 'VisaRequirement': 'Visa on Arrival', 'VisaTemplate': 'Optional'}, {'Country': 'Guyana', 'GDP_Access': 1436.4, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Honduras', 'GDP_Access': 9190.0, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Hungary', 'GDP_Access': 60913.6, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Iceland', 'GDP_Access': 9563.6, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'India', 'GDP_Access': 1305506.0, 'VisaRequirement': 'Electronic Visa', 'VisaTemplate': 'yes2'}, {'Country': 'Indonesia', 'GDP_Access': 913869.9, 'VisaRequirement': 'Visa not Required', 'VisaTemplate': 'yes'}, {'Country': 'Iran', 'GDP_Access': 302344.0, 'VisaRequirement': 'Visa on Arrival', 'VisaTemplate': 'yes-no'}, {'Country': 'Iraq', 'GDP_Access': 79079.6, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Ireland', 'GDP_Access': 133597.6, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Israel', 'GDP_Access': 315548.1, 'VisaRequirement': 'Visa not Required', 'VisaTemplate': 'yes'}, {'Country': 'Italy', 'GDP_Access': 775157.6, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Jamaica', 'GDP_Access': 5716.0, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Japan', 'GDP_Access': 1948854.0, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Jordan', 'GDP_Access': 28340.9, 'VisaRequirement': 'Visa on Arrival', 'VisaTemplate': 'yes-no'}, {'Country': 'Kazakhstan', 'GDP_Access': 64335.6, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Kenya', 'GDP_Access': 55657.7, 'VisaRequirement': 'Visa on Arrival', 'VisaTemplate': 'Optional'}, {'Country': 'Kiribati', 'GDP_Access': 74.4, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'North Korea', 'GDP_Access': 6958.4, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'South Korea', 'GDP_Access': 1384227.0, 'VisaRequirement': 'Visa not Required', 'VisaTemplate': 'yes'}, {'Country': 'Kuwait', 'GDP_Access': 48140.4, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Kyrgyzstan', 'GDP_Access': 3530.5, 'VisaRequirement': 'Electronic Visa', 'VisaTemplate': 'yes2'}, {'Country': 'Laos', 'GDP_Access': 12006.4, 'VisaRequirement': 'Visa on Arrival', 'VisaTemplate': 'yes-no'}, {'Country': 'Latvia', 'GDP_Access': 12127.6, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Lebanon', 'GDP_Access': 20582.8, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Lesotho', 'GDP_Access': 1360.5, 'VisaRequirement': 'Electronic Visa', 'VisaTemplate': 'yes2'}, {'Country': 'Liberia', 'GDP_Access': 856.0, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Libya', 'GDP_Access': 12532.4, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Liechtenstein', 'GDP_Access': 2342.0, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Lithuania', 'GDP_Access': 18905.2, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Luxembourg', 'GDP_Access': 24957.2, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Macedonia', 'GDP_Access': 4566.4, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Madagascar', 'GDP_Access': 7389.9, 'VisaRequirement': 'Visa on Arrival', 'VisaTemplate': 'yes-no'}, {'Country': 'Malawi', 'GDP_Access': 2504.4, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Malaysia', 'GDP_Access': 283047.3, 'VisaRequirement': 'Visa not Required', 'VisaTemplate': 'yes'}, {'Country': 'Maldives', 'GDP_Access': 3164.0, 'VisaRequirement': 'Visa on Arrival', 'VisaTemplate': 'yes-no'}, {'Country': 'Mali', 'GDP_Access': 5999.2, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Malta', 'GDP_Access': 4804.4, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Marshall Islands', 'GDP_Access': 79.6, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Mauritania', 'GDP_Access': 3489.5, 'VisaRequirement': 'Visa on Arrival', 'VisaTemplate': 'yes-no'}, {'Country': 'Mauritius', 'GDP_Access': 8591.1, 'VisaRequirement': 'Visa on Arrival', 'VisaTemplate': 'yes-no'}, {'Country': 'Mexico', 'GDP_Access': 459694.4, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Micronesia', 'GDP_Access': 296.1, 'VisaRequirement': 'Visa not Required', 'VisaTemplate': 'yes'}, {'Country': 'Moldova', 'GDP_Access': 3178.0, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Monaco', 'GDP_Access': 2824.0, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Mongolia', 'GDP_Access': 4347.6, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Montenegro', 'GDP_Access': 1762.0, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Morocco', 'GDP_Access': 43929.6, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Mozambique', 'GDP_Access': 8641.5, 'VisaRequirement': 'Visa on Arrival', 'VisaTemplate': 'yes-no'}, {'Country': 'Myanmar', 'GDP_Access': 26614.8, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Namibia', 'GDP_Access': 5023.2, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Nauru', 'GDP_Access': 45.6, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Nepal', 'GDP_Access': 17130.4, 'VisaRequirement': 'Visa on Arrival', 'VisaTemplate': 'yes-no'}, {'Country': 'Netherlands', 'GDP_Access': 330298.0, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'New Zealand', 'GDP_Access': 80594.0, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Nicaragua', 'GDP_Access': 5476.8, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Niger', 'GDP_Access': 150513.6, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Nigeria', 'GDP_Access': 150513.6, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Norway', 'GDP_Access': 158582.8, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Oman', 'GDP_Access': 29709.6, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Pakistan', 'GDP_Access': 121597.2, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Palau', 'GDP_Access': 224.7, 'VisaRequirement': 'Visa on Arrival', 'VisaTemplate': 'yes-no'}, {'Country': 'Panama', 'GDP_Access': 24735.2, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Papua New Guinea', 'GDP_Access': 9446.8, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Paraguay', 'GDP_Access': 11847.6, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Peru', 'GDP_Access': 86089.6, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Philippines', 'GDP_Access': 282077.1, 'VisaRequirement': 'Visa not Required', 'VisaTemplate': 'yes'}, {'Country': 'Poland', 'GDP_Access': 209954.4, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Portugal', 'GDP_Access': 87225.6, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Qatar', 'GDP_Access': 83163.0, 'VisaRequirement': 'Electronic Visa', 'VisaTemplate': 'yes2'}, {'Country': 'Romania', 'GDP_Access': 84526.0, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Russia', 'GDP_Access': 610987.6, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Rwanda', 'GDP_Access': 8026.2, 'VisaRequirement': 'Visa not Required', 'VisaTemplate': 'yes'}, {'Country': 'Saint Kitts and Nevis', 'GDP_Access': 378.4, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Saint Lucia', 'GDP_Access': 684.8, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Saint Vincent and the Grenadines', 'GDP_Access': 711.0, 'VisaRequirement': 'Visa not Required', 'VisaTemplate': 'yes'}, {'Country': 'Samoa', 'GDP_Access': 590.8, 'VisaRequirement': 'Visa on Arrival', 'VisaTemplate': 'yes-no'}, {'Country': 'San Marino', 'GDP_Access': 636.8, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Sao Tome and Principe', 'GDP_Access': 148.8, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Saudi Arabia', 'GDP_Access': 273530.8, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Senegal', 'GDP_Access': 11239.9, 'VisaRequirement': 'Visa on Arrival', 'VisaTemplate': 'yes-no'}, {'Country': 'Serbia', 'GDP_Access': 16588.4, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Seychelles', 'GDP_Access': 1035.3, 'VisaRequirement': 'Visa on Arrival', 'VisaTemplate': 'yes-no'}, {'Country': 'Sierra Leone', 'GDP_Access': 1558.8, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Singapore', 'GDP_Access': 291511.8, 'VisaRequirement': 'Visa not Required', 'VisaTemplate': 'yes'}, {'Country': 'Slovakia', 'GDP_Access': 38375.2, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Slovenia', 'GDP_Access': 19547.2, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Solomon Islands', 'GDP_Access': 509.2, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Somalia', 'GDP_Access': 5158.3, 'VisaRequirement': 'Visa on Arrival', 'VisaTemplate': 'yes-no'}, {'Country': 'South Africa', 'GDP_Access': 139719.6, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'South Sudan', 'GDP_Access': 23295.6, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Spain', 'GDP_Access': 525580.4, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Sri Lanka', 'GDP_Access': 61313.7, 'VisaRequirement': 'Visa on Arrival', 'VisaTemplate': 'Optional'}, {'Country': 'Sudan', 'GDP_Access': 23295.6, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Suriname', 'GDP_Access': 2565.5, 'VisaRequirement': 'Visa on Arrival', 'VisaTemplate': 'yes-no'}, {'Country': 'Sweden', 'GDP_Access': 215430.0, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Switzerland', 'GDP_Access': 271430.0, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Syria', 'GDP_Access': 30984.0, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Tajikistan', 'GDP_Access': 2893.6, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Tanzania', 'GDP_Access': 36207.5, 'VisaRequirement': 'Visa on Arrival', 'VisaTemplate': 'yes-no'}, {'Country': 'Thailand', 'GDP_Access': 182151.2, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Timor-Leste', 'GDP_Access': 1901.2, 'VisaRequirement': 'Visa on Arrival', 'VisaTemplate': 'yes-no'}, {'Country': 'Togo', 'GDP_Access': 3357.9, 'VisaRequirement': 'Visa on Arrival', 'VisaTemplate': 'yes-no'}, {'Country': 'Tonga', 'GDP_Access': 174.8, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Trinidad and Tobago', 'GDP_Access': 8120.0, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Tunisia', 'GDP_Access': 16110.0, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Turkey', 'GDP_Access': 424740.0, 'VisaRequirement': 'Electronic Visa', 'VisaTemplate': 'yes2'}, {'Country': 'Turkmenistan', 'GDP_Access': 15170.4, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Tuvalu', 'GDP_Access': 28.0, 'VisaRequirement': 'Visa on Arrival', 'VisaTemplate': 'yes-no'}, {'Country': 'Uganda', 'GDP_Access': 18444.3, 'VisaRequirement': 'Visa on Arrival', 'VisaTemplate': 'Optional'}, {'Country': 'Ukraine', 'GDP_Access': 54660.5, 'VisaRequirement': 'Electronic Visa', 'VisaTemplate': 'yes2'}, {'Country': 'United Arab Emirates', 'GDP_Access': 150974.0, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'United Kingdom', 'GDP_Access': 1049811.6, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'United States', 'GDP_Access': 7756240.0, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Uruguay', 'GDP_Access': 23366.0, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Uzbekistan', 'GDP_Access': 19153.2, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Vanuatu', 'GDP_Access': 334.8, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Venezuela', 'GDP_Access': 84034.0, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Vietnam', 'GDP_Access': 88163.2, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Yemen', 'GDP_Access': 6604.4, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}, {'Country': 'Zambia', 'GDP_Access': 17852.8, 'VisaRequirement': 'Visa on Arrival', 'VisaTemplate': 'Optional'}, {'Country': 'Zimbabwe', 'GDP_Access': 6842.0, 'VisaRequirement': 'Visa is required', 'VisaTemplate': 'no'}]

793f7edc6f7d1cedb1d15845f3794916e7ec3c35

py

Python

pyvisdk/do/vim_esx_cl_iiscsisessionlist_session.py

Infinidat/pyvisdk

f2f4e5f50da16f659ccc1d84b6a00f397fa997f8

pyvisdk/do/vim_esx_cl_iiscsisessionlist_session.py

Infinidat/pyvisdk

f2f4e5f50da16f659ccc1d84b6a00f397fa997f8

pyvisdk/do/vim_esx_cl_iiscsisessionlist_session.py

Infinidat/pyvisdk

f2f4e5f50da16f659ccc1d84b6a00f397fa997f8

import logging from pyvisdk.exceptions import InvalidArgumentError # This module is NOT auto-generated # Inspired by decompiled Java classes from vCenter's internalvim25stubs.jar # Unless states otherside, the methods and attributes were not used by esxcli, # and thus not tested log = logging.getLogger(__name__) def VimEsxCLIiscsisessionlistSession(vim, *args, **kwargs): obj = vim.client.factory.create('{urn:vim25}VimEsxCLIiscsisessionlistSession') # do some validation checking... if (len(args) + len(kwargs)) < 0: raise IndexError('Expected at least 1 arguments got: %d' % len(args)) required = [ ] optional = [ 'Adapter', 'AuthenticationMethod', 'DataPduInOrder', 'DataSequenceInOrder', 'DefaultTime2Retain', 'DefaultTime2Wait', 'ErrorRecoveryLevel', 'FirstBurstLength', 'ID', 'ISID', 'ImmediateData', 'InitialR2T', 'MaxBurstLength', 'MaxConnections', 'MaxOutstandingR2T', 'TSIH', 'Target', 'TargetPortalGroupTag' ] for name, arg in zip(required + optional, args): setattr(obj, name, arg) for name, value in kwargs.items(): if name in required + optional: setattr(obj, name, value) else: raise InvalidArgumentError("Invalid argument: %s. Expected one of %s" % (name, ", ".join(required + optional))) return obj

793f7f5d8aae11ac4517a3c878293c40604e0832

py

Python

cloudkitty/storage/v2/gnocchi.py

chnyda/cloudkitty

9c65b1d2304b8b963e12ef1918b9b23e180131b7

cloudkitty/storage/v2/gnocchi.py

chnyda/cloudkitty

9c65b1d2304b8b963e12ef1918b9b23e180131b7

cloudkitty/storage/v2/gnocchi.py

chnyda/cloudkitty

9c65b1d2304b8b963e12ef1918b9b23e180131b7

# -*- coding: utf-8 -*- # Copyright 2018 Objectif Libre # # 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. # # @author: Luka Peschke # from collections import deque from collections import Iterable import copy import datetime import decimal import time from gnocchiclient import auth as gauth from gnocchiclient import client as gclient from gnocchiclient import exceptions as gexceptions from keystoneauth1 import loading as ks_loading from oslo_config import cfg from oslo_log import log from oslo_utils import uuidutils import six from cloudkitty.storage.v2 import BaseStorage from cloudkitty import utils as ck_utils LOG = log.getLogger(__name__) CONF = cfg.CONF gnocchi_storage_opts = [ cfg.StrOpt( 'gnocchi_auth_type', default='keystone', choices=['keystone', 'basic'], help='(v2) Gnocchi auth type (keystone or basic). Keystone ' 'credentials can be specified through the "auth_section" parameter', ), cfg.StrOpt( 'gnocchi_user', default='', help='(v2) Gnocchi user (for basic auth only)', ), cfg.StrOpt( 'gnocchi_endpoint', default='', help='(v2) Gnocchi endpoint (for basic auth only)', ), cfg.StrOpt( 'api_interface', default='internalURL', help='(v2) Endpoint URL type (for keystone auth only)', ), cfg.IntOpt( 'measure_chunk_size', min=10, max=1000000, default=500, help='(v2) Maximum amount of measures to send to gnocchi at once ' '(defaults to 500).', ), ] CONF.register_opts(gnocchi_storage_opts, 'storage_gnocchi') ks_loading.register_session_conf_options(CONF, 'storage_gnocchi') ks_loading.register_auth_conf_options(CONF, 'storage_gnocchi') RESOURCE_TYPE_NAME_ROOT = 'cloudkitty_metric_' ARCHIVE_POLICY_NAME = 'cloudkitty_archive_policy' GROUPBY_NAME_ROOT = 'groupby_attr_' META_NAME_ROOT = 'meta_attr_' class GnocchiResource(object): """Class representing a gnocchi resource It provides utils for resource_type/resource creation and identifying. """ def __init__(self, name, metric, conn): """Resource_type name, metric, gnocchiclient""" self.name = name self.resource_type = RESOURCE_TYPE_NAME_ROOT + name self.unit = metric['vol']['unit'] self.groupby = { k: v if v else '' for k, v in metric['groupby'].items()} self.metadata = { k: v if v else '' for k, v in metric['metadata'].items()} self._trans_groupby = { GROUPBY_NAME_ROOT + key: val for key, val in self.groupby.items() } self._trans_metadata = { META_NAME_ROOT + key: val for key, val in self.metadata.items() } self._conn = conn self._resource = None self.attributes = self.metadata.copy() self.attributes.update(self.groupby) self._trans_attributes = self._trans_metadata.copy() self._trans_attributes.update(self._trans_groupby) self.needs_update = False def __getitem__(self, key): output = self._trans_attributes.get(GROUPBY_NAME_ROOT + key, None) if output is None: output = self._trans_attributes.get(META_NAME_ROOT + key, None) return output def __eq__(self, other): if self.resource_type != other.resource_type or \ self['id'] != other['id']: return False own_keys = list(self.groupby.keys()) own_keys.sort() other_keys = list(other.groupby.keys()) other_keys.sort() if own_keys != other_keys: return False for key in own_keys: if other[key] != self[key]: return False return True @property def qty(self): if self._resource: return self._resource['metrics']['qty'] return None @property def cost(self): if self._resource: return self._resource['metrics']['cost'] return None def _get_res_type_dict(self): attributes = {} for key in self._trans_groupby.keys(): attributes[key] = {'required': True, 'type': 'string'} attributes['unit'] = {'required': True, 'type': 'string'} for key in self._trans_metadata.keys(): attributes[key] = {'required': False, 'type': 'string'} return { 'name': self.resource_type, 'attributes': attributes, } def create_resource_type(self): """Allows to create the type corresponding to this resource.""" try: self._conn.resource_type.get(self.resource_type) except gexceptions.ResourceTypeNotFound: res_type = self._get_res_type_dict() LOG.debug('Creating resource_type {} in gnocchi'.format( self.resource_type)) self._conn.resource_type.create(res_type) @staticmethod def _get_rfc6902_attributes_add_op(new_attributes): return [{ 'op': 'add', 'path': '/attributes/{}'.format(attr), 'value': { 'required': attr.startswith(GROUPBY_NAME_ROOT), 'type': 'string' } } for attr in new_attributes] def update_resource_type(self): needed_res_type = self._get_res_type_dict() current_res_type = self._conn.resource_type.get( needed_res_type['name']) new_attributes = [attr for attr in needed_res_type['attributes'].keys() if attr not in current_res_type['attributes'].keys()] if not new_attributes: return LOG.info('Adding {} to resource_type {}'.format( [attr.replace(GROUPBY_NAME_ROOT, '').replace(META_NAME_ROOT, '') for attr in new_attributes], current_res_type['name'].replace(RESOURCE_TYPE_NAME_ROOT, ''), )) new_attributes_op = self._get_rfc6902_attributes_add_op(new_attributes) self._conn.resource_type.update( needed_res_type['name'], new_attributes_op) def _create_metrics(self): qty = self._conn.metric.create( name='qty', unit=self.unit, archive_policy_name=ARCHIVE_POLICY_NAME, ) cost = self._conn.metric.create( name='cost', archive_policy_name=ARCHIVE_POLICY_NAME, ) return qty, cost def exists_in_gnocchi(self): """Check if the resource exists in gnocchi. Returns true if the resource exists. """ query = { 'and': [ {'=': {key: value}} for key, value in self._trans_groupby.items() ], } res = self._conn.resource.search(resource_type=self.resource_type, query=query) if len(res) > 1: LOG.warning( "Found more than one metric matching groupby. This may not " "have the behavior you're expecting. You should probably add " "some items to groupby") if len(res) > 0: self._resource = res[0] return True return False def create(self): """Creates the resource in gnocchi.""" if self._resource: return self.create_resource_type() qty_metric, cost_metric = self._create_metrics() resource = self._trans_attributes.copy() resource['metrics'] = { 'qty': qty_metric['id'], 'cost': cost_metric['id'], } resource['id'] = uuidutils.generate_uuid() resource['unit'] = self.unit if not self.exists_in_gnocchi(): try: self._resource = self._conn.resource.create( self.resource_type, resource) # Attributes have changed except gexceptions.BadRequest: self.update_resource_type() self._resource = self._conn.resource.create( self.resource_type, resource) def update(self, metric): for key, val in metric['metadata'].items(): self._resource[META_NAME_ROOT + key] = val self._resource = self._conn.update( self.resource_type, self._resource['id'], self._resource) self.needs_update = False return self._resource class GnocchiResourceCacher(object): """Class allowing to keep created resource in memory to improve perfs. It keeps the last max_size resources in cache. """ def __init__(self, max_size=500): self._resources = deque(maxlen=max_size) def __contains__(self, resource): for r in self._resources: if r == resource: for key, val in resource.metadata.items(): if val != r[key]: r.needs_update = True return True return False def add_resource(self, resource): """Add a resource to the cacher. :param resource: resource to add :type resource: GnocchiResource """ for r in self._resources: if r == resource: return self._resources.append(resource) def get(self, resource): """Returns the resource matching to the parameter. :param resource: resource to get :type resource: GnocchiResource """ for r in self._resources: if r == resource: return r return None def get_by_id(self, resource_id): """Returns the resource matching the given id. :param resource_id: ID of the resource to get :type resource: str """ for r in self._resources: if r['id'] == resource_id: return r return None class GnocchiStorage(BaseStorage): default_op = ['aggregate', 'sum', ['metric', 'cost', 'sum'], ] def _check_archive_policy(self): try: self._conn.archive_policy.get(ARCHIVE_POLICY_NAME) except gexceptions.ArchivePolicyNotFound: definition = [ {'granularity': str(CONF.collect.period) + 's', 'timespan': '{d} days'.format(d=self.get_retention().days)}, ] archive_policy = { 'name': ARCHIVE_POLICY_NAME, 'back_window': 0, 'aggregation_methods': [ 'std', 'count', 'min', 'max', 'sum', 'mean'], 'definition': definition, } self._conn.archive_policy.create(archive_policy) def __init__(self, *args, **kwargs): super(GnocchiStorage, self).__init__(*args, **kwargs) adapter_options = {'connect_retries': 3} if CONF.storage_gnocchi.gnocchi_auth_type == 'keystone': auth_plugin = ks_loading.load_auth_from_conf_options( CONF, 'storage_gnocchi', ) adapter_options['interface'] = CONF.storage_gnocchi.api_interface else: auth_plugin = gauth.GnocchiBasicPlugin( user=CONF.storage_gnocchi.gnocchi_user, endpoint=CONF.storage_gnocchi.gnocchi_endpoint, ) self._conn = gclient.Client( '1', session_options={'auth': auth_plugin}, adapter_options=adapter_options, ) self._cacher = GnocchiResourceCacher() def init(self): self._check_archive_policy() def _check_resource(self, metric_name, metric): resource = GnocchiResource(metric_name, metric, self._conn) if resource in self._cacher: return self._cacher.get(resource) resource.create() self._cacher.add_resource(resource) return resource def _push_measures_to_gnocchi(self, measures): if measures: try: self._conn.metric.batch_metrics_measures(measures) except gexceptions.BadRequest: LOG.warning( 'An exception occured while trying to push measures to ' 'gnocchi. Retrying in 1 second. If this happens again, ' 'set measure_chunk_size to a lower value.') time.sleep(1) self._conn.metric.batch_metrics_measures(measures) # Do not use scope_id, as it is deprecated and will be # removed together with the v1 storage def push(self, dataframes, scope_id=None): if not isinstance(dataframes, list): dataframes = [dataframes] measures = {} nb_measures = 0 for dataframe in dataframes: timestamp = dataframe['period']['begin'] for metric_name, metrics in dataframe['usage'].items(): for metric in metrics: resource = self._check_resource(metric_name, metric) if resource.needs_update: resource.update(metric) if not resource.qty or not resource.cost: LOG.warning('Unexpected continue') continue # resource.qty is the uuid of the qty metric if not measures.get(resource.qty): measures[resource.qty] = [] measures[resource.qty].append({ 'timestamp': timestamp, 'value': metric['vol']['qty'], }) if not measures.get(resource.cost): measures[resource.cost] = [] measures[resource.cost].append({ 'timestamp': timestamp, 'value': metric['rating']['price'], }) nb_measures += 2 if nb_measures >= CONF.storage_gnocchi.measure_chunk_size: LOG.debug('Pushing {} measures to gnocchi.'.format( nb_measures)) self._push_measures_to_gnocchi(measures) measures = {} nb_measures = 0 LOG.debug('Pushing {} measures to gnocchi.'.format(nb_measures)) self._push_measures_to_gnocchi(measures) def _get_ck_resource_types(self): types = self._conn.resource_type.list() return [gtype['name'] for gtype in types if gtype['name'].startswith(RESOURCE_TYPE_NAME_ROOT)] def _check_res_types(self, res_type=None): if res_type is None: output = self._get_ck_resource_types() elif isinstance(res_type, Iterable): output = res_type else: output = [res_type] return sorted(output) @staticmethod def _check_begin_end(begin, end): if not begin: begin = ck_utils.get_month_start() if not end: end = ck_utils.get_next_month() if isinstance(begin, six.text_type): begin = ck_utils.iso2dt(begin) if isinstance(begin, int): begin = ck_utils.ts2dt(begin) if isinstance(end, six.text_type): end = ck_utils.iso2dt(end) if isinstance(end, int): end = ck_utils.ts2dt(end) return begin, end def _get_resource_frame(self, cost_measure, qty_measure, resource): # Getting price price = decimal.Decimal(cost_measure[2]) price_dict = {'price': float(price)} # Getting vol vol_dict = { 'qty': decimal.Decimal(qty_measure[2]), 'unit': resource.get('unit'), } # Formatting groupby = { k.replace(GROUPBY_NAME_ROOT, ''): v for k, v in resource.items() if k.startswith(GROUPBY_NAME_ROOT) } metadata = { k.replace(META_NAME_ROOT, ''): v for k, v in resource.items() if k.startswith(META_NAME_ROOT) } return { 'groupby': groupby, 'metadata': metadata, 'vol': vol_dict, 'rating': price_dict, } def _to_cloudkitty(self, res_type, resource, cost_measure, qty_measure): start = cost_measure[0] stop = start + datetime.timedelta(seconds=cost_measure[1]) # Period period_dict = { 'begin': ck_utils.dt2iso(start), 'end': ck_utils.dt2iso(stop), } return { 'usage': {res_type: [ self._get_resource_frame(cost_measure, qty_measure, resource)], }, 'period': period_dict, } def _get_resource_info(self, resource_ids, start, stop): search = { 'and': [ { 'or': [ { '=': {'id': resource_id}, } for resource_id in resource_ids ], }, ], } resources = [] marker = None while True: resource_chunk = self._conn.resource.search(query=search, details=True, marker=marker, sorts=['id:asc']) if len(resource_chunk) < 1: break marker = resource_chunk[-1]['id'] resources += resource_chunk return {resource['id']: resource for resource in resources} @staticmethod def _dataframes_to_list(dataframes): keys = sorted(dataframes.keys()) return [dataframes[key] for key in keys] def _get_dataframes(self, measures, resource_info): dataframes = {} for measure in measures: resource_type = measure['group']['type'] resource_id = measure['group']['id'] # Raw metrics do not contain all required attributes resource = resource_info[resource_id] dataframe = dataframes.get(measure['cost'][0]) ck_resource_type_name = resource_type.replace( RESOURCE_TYPE_NAME_ROOT, '') if dataframe is None: dataframes[measure['cost'][0]] = self._to_cloudkitty( ck_resource_type_name, resource, measure['cost'], measure['qty']) elif dataframe['usage'].get(ck_resource_type_name) is None: dataframe['usage'][ck_resource_type_name] = [ self._get_resource_frame( measure['cost'], measure['qty'], resource)] else: dataframe['usage'][ck_resource_type_name].append( self._get_resource_frame( measure['cost'], measure['qty'], resource)) return self._dataframes_to_list(dataframes) @staticmethod def _create_filters(filters, group_filters): output = {} if filters: for k, v in filters.items(): output[META_NAME_ROOT + k] = v if group_filters: for k, v in group_filters.items(): output[GROUPBY_NAME_ROOT + k] = v return output def _raw_metrics_to_distinct_measures(self, raw_cost_metrics, raw_qty_metrics): output = [] for cost, qty in zip(raw_cost_metrics, raw_qty_metrics): output += [{ 'cost': cost_measure, 'qty': qty['measures']['measures']['aggregated'][idx], 'group': cost['group'], } for idx, cost_measure in enumerate( cost['measures']['measures']['aggregated']) ] # Sorting by timestamp, metric type and resource ID output.sort(key=lambda x: ( x['cost'][0], x['group']['type'], x['group']['id'])) return output def retrieve(self, begin=None, end=None, filters=None, group_filters=None, metric_types=None, offset=0, limit=100, paginate=True): begin, end = self._check_begin_end(begin, end) metric_types = self._check_res_types(metric_types) # Getting a list of active gnocchi resources with measures filters = self._create_filters(filters, group_filters) # FIXME(lukapeschke): We query all resource types in order to get the # total amount of dataframes, but this could be done in a better way; # ie. by not doing addtional queries once the limit is reached raw_cost_metrics = [] raw_qty_metrics = [] for mtype in metric_types: cost_metrics, qty_metrics = self._single_resource_type_aggregates( begin, end, mtype, ['type', 'id'], filters, fetch_qty=True) raw_cost_metrics += cost_metrics raw_qty_metrics += qty_metrics measures = self._raw_metrics_to_distinct_measures( raw_cost_metrics, raw_qty_metrics) result = {'total': len(measures)} if paginate: measures = measures[offset:limit] if len(measures) < 1: return { 'total': 0, 'dataframes': [], } resource_ids = [measure['group']['id'] for measure in measures] resource_info = self._get_resource_info(resource_ids, begin, end) result['dataframes'] = self._get_dataframes(measures, resource_info) return result def _single_resource_type_aggregates(self, start, stop, metric_type, groupby, filters, fetch_qty=False): search = { 'and': [ {'=': {'type': metric_type}} ] } search['and'] += [{'=': {k: v}} for k, v in filters.items()] cost_op = self.default_op output = ( self._conn.aggregates.fetch( cost_op, search=search, groupby=groupby, resource_type=metric_type, start=start, stop=stop), None ) if fetch_qty: qty_op = copy.deepcopy(self.default_op) qty_op[2][1] = 'qty' output = ( output[0], self._conn.aggregates.fetch( qty_op, search=search, groupby=groupby, resource_type=metric_type, start=start, stop=stop) ) return output @staticmethod def _ungroup_type(rated_resources): output = [] for rated_resource in rated_resources: rated_resource['group'].pop('type', None) new_item = True for elem in output: if rated_resource['group'] == elem['group']: elem['measures']['measures']['aggregated'] \ += rated_resource['measures']['measures']['aggregated'] new_item = False break if new_item: output.append(rated_resource) return output def total(self, groupby=None, begin=None, end=None, metric_types=None, filters=None, group_filters=None): begin, end = self._check_begin_end(begin, end) if groupby is None: groupby = [] request_groupby = [ GROUPBY_NAME_ROOT + elem for elem in groupby if elem != 'type'] # We need to have a least one attribute on which to group request_groupby.append('type') # NOTE(lukapeschke): For now, it isn't possible to group aggregates # from different resource types using custom attributes, so we need # to do one request per resource type. rated_resources = [] metric_types = self._check_res_types(metric_types) filters = self._create_filters(filters, group_filters) for mtype in metric_types: resources, _ = self._single_resource_type_aggregates( begin, end, mtype, request_groupby, filters) for resource in resources: # If we have found something if len(resource['measures']['measures']['aggregated']): rated_resources.append(resource) # NOTE(lukapeschke): We undo what has been done previously (grouping # per type). This is not performant. Should be fixed as soon as # previous note is supported in gnocchi if 'type' not in groupby: rated_resources = self._ungroup_type(rated_resources) output = [] for rated_resource in rated_resources: rate = sum(measure[2] for measure in rated_resource['measures']['measures']['aggregated']) output_elem = { 'begin': begin, 'end': end, 'rate': rate, } for group in groupby: output_elem[group] = rated_resource['group'].get( GROUPBY_NAME_ROOT + group, '') # If we want to group per type if 'type' in groupby: output_elem['type'] = rated_resource['group'].get( 'type', '').replace(RESOURCE_TYPE_NAME_ROOT, '') or '' output.append(output_elem) return output

793f80cdf965f44100be6d0fdb92b9721bd1c029

py

Python

utils/PUMA_helpers.py

NYCPlanning/db-equitable-development-tool

b24d83dc4092489995cabcdcb611642c1c8ee3b2

2021-12-30T21:03:56.000Z

2021-12-30T21:03:56.000Z

utils/PUMA_helpers.py

NYCPlanning/db-equitable-development-tool

b24d83dc4092489995cabcdcb611642c1c8ee3b2

2021-10-20T19:03:04.000Z

2022-03-31T21:02:37.000Z

utils/PUMA_helpers.py

NYCPlanning/db-equitable-development-tool

b24d83dc4092489995cabcdcb611642c1c8ee3b2

import geopandas as gp from shapely.geometry import Point import pandas as pd from numpy import nan import requests from utils.geocode import from_eviction_address geocode_functions = {"from_eviction_address": from_eviction_address} borough_code_mapper = { "037": "BX", "038": "MN", "039": "SI", "040": "BK", "041": "QN", } borough_name_mapper = { "Bronx": "BX", "Brooklyn": "BK", "Manhattan": "MN", "Queens": "QN", "Staten Island": "SI", } census_races = ["anh", "bnh", "hsp", "onh", "wnh"] dcp_pop_races = ["anh", "bnh", "hsp", "wnh"] def puma_to_borough(record): borough_code = record.puma[:3] borough = borough_code_mapper.get(borough_code, None) return borough NYC_PUMAS_url = "https://services5.arcgis.com/GfwWNkhOj9bNBqoJ/arcgis/rest/services/NYC_Public_Use_Microdata_Areas_PUMAs_2010/FeatureServer/0/query?where=1=1&outFields=*&outSR=4326&f=pgeojson" def clean_PUMAs(puma) -> pd.DataFrame: """Re-uses code from remove_state_code_from_PUMA col in access to subway, call this instead Possible refactor: apply to dataframe and ensure that re-named column is label \"puma\" """ puma = str(puma) puma = puma.split(".")[0] if puma == "nan" or puma == nan: return nan elif puma[:2] == "36": puma = puma[2:] elif puma[0] != "0": puma = "0" + puma return puma def NYC_PUMA_geographies() -> gp.GeoDataFrame: res = requests.get( "https://services5.arcgis.com/GfwWNkhOj9bNBqoJ/arcgis/rest/services/NYC_Public_Use_Microdata_Areas_PUMAs_2010/FeatureServer/0/query?where=1=1&outFields=*&outSR=4326&f=pgeojson" ) gdf = gp.GeoDataFrame.from_features(res.json()["features"]) gdf = gdf.set_crs(res.json()["crs"]["properties"]["name"]) gdf.rename(columns={"PUMA": "puma"}, inplace=True) gdf["puma"] = gdf["puma"].apply(clean_PUMAs) return gdf PUMAs = NYC_PUMA_geographies() def assign_PUMA_col(df: pd.DataFrame, lat_col, long_col, geocode_process=None): df.rename(columns={lat_col: "latitude", long_col: "longitude"}, inplace=True) df["puma"] = df.apply(assign_PUMA, axis=1, args=(geocode_process,)) print(f"got {df.shape[0]} evictions to assign PUMAs to ") print(f"assigned PUMAs to {df['puma'].notnull().sum()}") return df def assign_PUMA(record: gp.GeoDataFrame, geocode_process): if pd.notnull(record.latitude) and pd.notnull(record.longitude): return PUMA_from_coord(record) if geocode_process: return geocode_functions[geocode_process](record) def PUMA_from_coord(record): """Don't think I need to make a geodata frame here, shapely object would do""" record_loc = Point(record.longitude, record.latitude) matched_PUMA = PUMAs[PUMAs.geometry.contains(record_loc)] if matched_PUMA.empty: return None return matched_PUMA.puma.values[0] def get_all_NYC_PUMAs(): """Adopted from code in PUMS_query_manager""" geo_ids = [ range(4001, 4019), # Brooklyn range(3701, 3711), # Bronx range(4101, 4115), # Queens range(3901, 3904), # Staten Island range(3801, 3811), # Manhattan ] rv = [] for borough in geo_ids: rv.extend(["0" + str(PUMA) for PUMA in borough]) return rv def get_all_boroughs(): return ["BK", "BX", "MN", "QN", "SI"] def filter_for_recognized_pumas(df): """Written for income restricted indicator but can be used for many other indicators that have rows by puma but include some non-PUMA rows. Sometimes we set nrows in read csv/excel but this approach is more flexible""" return df[df["puma"].isin(get_all_NYC_PUMAs())]

793f82da98f3a6ab3b6583b2f55be105cd018ce6

py

Python

test/functional/p2p_invalid_tx.py

dev-zeo/bitcoin-pos

5fd0ccf8833a8e8e467f7c765fb6780b0b570e97

test/functional/p2p_invalid_tx.py

dev-zeo/bitcoin-pos

5fd0ccf8833a8e8e467f7c765fb6780b0b570e97

test/functional/p2p_invalid_tx.py

dev-zeo/bitcoin-pos

5fd0ccf8833a8e8e467f7c765fb6780b0b570e97

#!/usr/bin/env python3 # Copyright (c) 2015-2019 The Bitcoin Core developers # Distributed under the MIT software license, see the accompanying # file COPYING or http://www.opensource.org/licenses/mit-license.php. """Test node responses to invalid transactions. In this test we connect to one node over p2p, and test tx requests.""" from test_framework.blocktools import create_block, create_coinbase from test_framework.messages import ( COIN, COutPoint, CTransaction, CTxIn, CTxOut, ) from test_framework.mininode import P2PDataStore from test_framework.test_framework import ZeoTestFramework from test_framework.util import ( assert_equal, wait_until, ) from data import invalid_txs class InvalidTxRequestTest(ZeoTestFramework): def set_test_params(self): self.num_nodes = 1 self.extra_args = [[ "-acceptnonstdtxn=1", ]] self.setup_clean_chain = True def bootstrap_p2p(self, *, num_connections=1): """Add a P2P connection to the node. Helper to connect and wait for version handshake.""" for _ in range(num_connections): self.nodes[0].add_p2p_connection(P2PDataStore()) def reconnect_p2p(self, **kwargs): """Tear down and bootstrap the P2P connection to the node. The node gets disconnected several times in this test. This helper method reconnects the p2p and restarts the network thread.""" self.nodes[0].disconnect_p2ps() self.bootstrap_p2p(**kwargs) def run_test(self): node = self.nodes[0] # convenience reference to the node self.bootstrap_p2p() # Add one p2p connection to the node best_block = self.nodes[0].getbestblockhash() tip = int(best_block, 16) best_block_time = self.nodes[0].getblock(best_block)['time'] block_time = best_block_time + 1 self.log.info("Create a new block with an anyone-can-spend coinbase.") height = 1 block = create_block(tip, create_coinbase(height), block_time) block.solve() # Save the coinbase for later block1 = block tip = block.sha256 node.p2p.send_blocks_and_test([block], node, success=True) self.log.info("Mature the block.") self.nodes[0].generatetoaddress(100, self.nodes[0].get_deterministic_priv_key().address) # Iterate through a list of known invalid transaction types, ensuring each is # rejected. Some are consensus invalid and some just violate policy. for BadTxTemplate in invalid_txs.iter_all_templates(): self.log.info("Testing invalid transaction: %s", BadTxTemplate.__name__) template = BadTxTemplate(spend_block=block1) tx = template.get_tx() node.p2p.send_txs_and_test( [tx], node, success=False, expect_disconnect=template.expect_disconnect, reject_reason=template.reject_reason, ) if template.expect_disconnect: self.log.info("Reconnecting to peer") self.reconnect_p2p() # Make two p2p connections to provide the node with orphans # * p2ps[0] will send valid orphan txs (one with low fee) # * p2ps[1] will send an invalid orphan tx (and is later disconnected for that) self.reconnect_p2p(num_connections=2) self.log.info('Test orphan transaction handling ... ') # Create a root transaction that we withhold until all dependent transactions # are sent out and in the orphan cache SCRIPT_PUB_KEY_OP_TRUE = b'\x51\x75' * 15 + b'\x51' tx_withhold = CTransaction() tx_withhold.vin.append(CTxIn(outpoint=COutPoint(block1.vtx[0].sha256, 0))) tx_withhold.vout.append(CTxOut(nValue=50 * COIN - 12000, scriptPubKey=SCRIPT_PUB_KEY_OP_TRUE)) tx_withhold.calc_sha256() # Our first orphan tx with some outputs to create further orphan txs tx_orphan_1 = CTransaction() tx_orphan_1.vin.append(CTxIn(outpoint=COutPoint(tx_withhold.sha256, 0))) tx_orphan_1.vout = [CTxOut(nValue=10 * COIN, scriptPubKey=SCRIPT_PUB_KEY_OP_TRUE)] * 3 tx_orphan_1.calc_sha256() # A valid transaction with low fee tx_orphan_2_no_fee = CTransaction() tx_orphan_2_no_fee.vin.append(CTxIn(outpoint=COutPoint(tx_orphan_1.sha256, 0))) tx_orphan_2_no_fee.vout.append(CTxOut(nValue=10 * COIN, scriptPubKey=SCRIPT_PUB_KEY_OP_TRUE)) # A valid transaction with sufficient fee tx_orphan_2_valid = CTransaction() tx_orphan_2_valid.vin.append(CTxIn(outpoint=COutPoint(tx_orphan_1.sha256, 1))) tx_orphan_2_valid.vout.append(CTxOut(nValue=10 * COIN - 12000, scriptPubKey=SCRIPT_PUB_KEY_OP_TRUE)) tx_orphan_2_valid.calc_sha256() # An invalid transaction with negative fee tx_orphan_2_invalid = CTransaction() tx_orphan_2_invalid.vin.append(CTxIn(outpoint=COutPoint(tx_orphan_1.sha256, 2))) tx_orphan_2_invalid.vout.append(CTxOut(nValue=11 * COIN, scriptPubKey=SCRIPT_PUB_KEY_OP_TRUE)) self.log.info('Send the orphans ... ') # Send valid orphan txs from p2ps[0] node.p2p.send_txs_and_test([tx_orphan_1, tx_orphan_2_no_fee, tx_orphan_2_valid], node, success=False) # Send invalid tx from p2ps[1] node.p2ps[1].send_txs_and_test([tx_orphan_2_invalid], node, success=False) assert_equal(0, node.getmempoolinfo()['size']) # Mempool should be empty assert_equal(2, len(node.getpeerinfo())) # p2ps[1] is still connected self.log.info('Send the withhold tx ... ') with node.assert_debug_log(expected_msgs=["bad-txns-in-belowout"]): node.p2p.send_txs_and_test([tx_withhold], node, success=True) # Transactions that should end up in the mempool expected_mempool = { t.hash for t in [ tx_withhold, # The transaction that is the root for all orphans tx_orphan_1, # The orphan transaction that splits the coins tx_orphan_2_valid, # The valid transaction (with sufficient fee) ] } # Transactions that do not end up in the mempool # tx_orphan_no_fee, because it has too low fee (p2ps[0] is not disconnected for relaying that tx) # tx_orphan_invaid, because it has negative fee (p2ps[1] is disconnected for relaying that tx) wait_until(lambda: 1 == len(node.getpeerinfo()), timeout=12) # p2ps[1] is no longer connected assert_equal(expected_mempool, set(node.getrawmempool())) if __name__ == '__main__': InvalidTxRequestTest().main()

793f8370afede0a2d5f3b99e0b92368dfdae22d0

py

Python

pybind/slxos/v16r_1_00b/routing_system/interface/loopback/ipv6/interface_ospfv3_conf/authentication/__init__.py

shivharis/pybind

4e1c6d54b9fd722ccec25546ba2413d79ce337e6

pybind/slxos/v16r_1_00b/routing_system/interface/loopback/ipv6/interface_ospfv3_conf/authentication/__init__.py

shivharis/pybind

4e1c6d54b9fd722ccec25546ba2413d79ce337e6

pybind/slxos/v16r_1_00b/routing_system/interface/loopback/ipv6/interface_ospfv3_conf/authentication/__init__.py

shivharis/pybind

4e1c6d54b9fd722ccec25546ba2413d79ce337e6

2021-11-05T22:15:42.000Z

2021-11-05T22:15:42.000Z

from operator import attrgetter import pyangbind.lib.xpathhelper as xpathhelper from pyangbind.lib.yangtypes import RestrictedPrecisionDecimalType, RestrictedClassType, TypedListType from pyangbind.lib.yangtypes import YANGBool, YANGListType, YANGDynClass, ReferenceType from pyangbind.lib.base import PybindBase from decimal import Decimal from bitarray import bitarray import __builtin__ import ipsec_auth_key_config import ipsec class authentication(PybindBase): """ This class was auto-generated by the PythonClass plugin for PYANG from YANG module brocade-common-def - based on the path /routing-system/interface/loopback/ipv6/interface-ospfv3-conf/authentication. Each member element of the container is represented as a class variable - with a specific YANG type. YANG Description: Configure ipsec authentication for the interface.The interface IPsec configuration takes precedence over the area IPsec configuration when an area and an interface within that area use IPsec. Therefore, if you configure IPsec for an interface and an area configuration also exists that includes this interface, the interface's IPsec configuration is used by that interface. However, if you disable IPsec on an interface, IPsec is disabled on the interface even if the interface has its own, specific authentication. """ __slots__ = ('_pybind_generated_by', '_path_helper', '_yang_name', '_rest_name', '_extmethods', '__ipsec_auth_key_config','__ipsec',) _yang_name = 'authentication' _rest_name = 'authentication' _pybind_generated_by = 'container' def __init__(self, *args, **kwargs): path_helper_ = kwargs.pop("path_helper", None) if path_helper_ is False: self._path_helper = False elif path_helper_ is not None and isinstance(path_helper_, xpathhelper.YANGPathHelper): self._path_helper = path_helper_ elif hasattr(self, "_parent"): path_helper_ = getattr(self._parent, "_path_helper", False) self._path_helper = path_helper_ else: self._path_helper = False extmethods = kwargs.pop("extmethods", None) if extmethods is False: self._extmethods = False elif extmethods is not None and isinstance(extmethods, dict): self._extmethods = extmethods elif hasattr(self, "_parent"): extmethods = getattr(self._parent, "_extmethods", None) self._extmethods = extmethods else: self._extmethods = False self.__ipsec_auth_key_config = YANGDynClass(base=ipsec_auth_key_config.ipsec_auth_key_config, is_container='container', presence=False, yang_name="ipsec-auth-key-config", rest_name="", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-compact-syntax': None, u'cli-drop-node-name': None, u'cli-sequence-commands': None, u'cli-incomplete-no': None, u'cli-incomplete-command': None}}, namespace='urn:brocade.com:mgmt:brocade-ospfv3', defining_module='brocade-ospfv3', yang_type='container', is_config=True) self.__ipsec = YANGDynClass(base=ipsec.ipsec, is_container='container', presence=False, yang_name="ipsec", rest_name="ipsec", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Configure ipsec authentication for the interface'}}, namespace='urn:brocade.com:mgmt:brocade-ospfv3', defining_module='brocade-ospfv3', yang_type='container', is_config=True) load = kwargs.pop("load", None) if args: if len(args) > 1: raise TypeError("cannot create a YANG container with >1 argument") all_attr = True for e in self._pyangbind_elements: if not hasattr(args[0], e): all_attr = False break if not all_attr: raise ValueError("Supplied object did not have the correct attributes") for e in self._pyangbind_elements: nobj = getattr(args[0], e) if nobj._changed() is False: continue setmethod = getattr(self, "_set_%s" % e) if load is None: setmethod(getattr(args[0], e)) else: setmethod(getattr(args[0], e), load=load) def _path(self): if hasattr(self, "_parent"): return self._parent._path()+[self._yang_name] else: return [u'routing-system', u'interface', u'loopback', u'ipv6', u'interface-ospfv3-conf', u'authentication'] def _rest_path(self): if hasattr(self, "_parent"): if self._rest_name: return self._parent._rest_path()+[self._rest_name] else: return self._parent._rest_path() else: return [u'interface', u'Loopback', u'ipv6', u'ospf', u'authentication'] def _get_ipsec_auth_key_config(self): """ Getter method for ipsec_auth_key_config, mapped from YANG variable /routing_system/interface/loopback/ipv6/interface_ospfv3_conf/authentication/ipsec_auth_key_config (container) """ return self.__ipsec_auth_key_config def _set_ipsec_auth_key_config(self, v, load=False): """ Setter method for ipsec_auth_key_config, mapped from YANG variable /routing_system/interface/loopback/ipv6/interface_ospfv3_conf/authentication/ipsec_auth_key_config (container) If this variable is read-only (config: false) in the source YANG file, then _set_ipsec_auth_key_config is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_ipsec_auth_key_config() directly. """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=ipsec_auth_key_config.ipsec_auth_key_config, is_container='container', presence=False, yang_name="ipsec-auth-key-config", rest_name="", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-compact-syntax': None, u'cli-drop-node-name': None, u'cli-sequence-commands': None, u'cli-incomplete-no': None, u'cli-incomplete-command': None}}, namespace='urn:brocade.com:mgmt:brocade-ospfv3', defining_module='brocade-ospfv3', yang_type='container', is_config=True) except (TypeError, ValueError): raise ValueError({ 'error-string': """ipsec_auth_key_config must be of a type compatible with container""", 'defined-type': "container", 'generated-type': """YANGDynClass(base=ipsec_auth_key_config.ipsec_auth_key_config, is_container='container', presence=False, yang_name="ipsec-auth-key-config", rest_name="", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-compact-syntax': None, u'cli-drop-node-name': None, u'cli-sequence-commands': None, u'cli-incomplete-no': None, u'cli-incomplete-command': None}}, namespace='urn:brocade.com:mgmt:brocade-ospfv3', defining_module='brocade-ospfv3', yang_type='container', is_config=True)""", }) self.__ipsec_auth_key_config = t if hasattr(self, '_set'): self._set() def _unset_ipsec_auth_key_config(self): self.__ipsec_auth_key_config = YANGDynClass(base=ipsec_auth_key_config.ipsec_auth_key_config, is_container='container', presence=False, yang_name="ipsec-auth-key-config", rest_name="", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'cli-compact-syntax': None, u'cli-drop-node-name': None, u'cli-sequence-commands': None, u'cli-incomplete-no': None, u'cli-incomplete-command': None}}, namespace='urn:brocade.com:mgmt:brocade-ospfv3', defining_module='brocade-ospfv3', yang_type='container', is_config=True) def _get_ipsec(self): """ Getter method for ipsec, mapped from YANG variable /routing_system/interface/loopback/ipv6/interface_ospfv3_conf/authentication/ipsec (container) YANG Description: Configure ipsec authentication for the interface """ return self.__ipsec def _set_ipsec(self, v, load=False): """ Setter method for ipsec, mapped from YANG variable /routing_system/interface/loopback/ipv6/interface_ospfv3_conf/authentication/ipsec (container) If this variable is read-only (config: false) in the source YANG file, then _set_ipsec is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_ipsec() directly. YANG Description: Configure ipsec authentication for the interface """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=ipsec.ipsec, is_container='container', presence=False, yang_name="ipsec", rest_name="ipsec", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Configure ipsec authentication for the interface'}}, namespace='urn:brocade.com:mgmt:brocade-ospfv3', defining_module='brocade-ospfv3', yang_type='container', is_config=True) except (TypeError, ValueError): raise ValueError({ 'error-string': """ipsec must be of a type compatible with container""", 'defined-type': "container", 'generated-type': """YANGDynClass(base=ipsec.ipsec, is_container='container', presence=False, yang_name="ipsec", rest_name="ipsec", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Configure ipsec authentication for the interface'}}, namespace='urn:brocade.com:mgmt:brocade-ospfv3', defining_module='brocade-ospfv3', yang_type='container', is_config=True)""", }) self.__ipsec = t if hasattr(self, '_set'): self._set() def _unset_ipsec(self): self.__ipsec = YANGDynClass(base=ipsec.ipsec, is_container='container', presence=False, yang_name="ipsec", rest_name="ipsec", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'info': u'Configure ipsec authentication for the interface'}}, namespace='urn:brocade.com:mgmt:brocade-ospfv3', defining_module='brocade-ospfv3', yang_type='container', is_config=True) ipsec_auth_key_config = __builtin__.property(_get_ipsec_auth_key_config, _set_ipsec_auth_key_config) ipsec = __builtin__.property(_get_ipsec, _set_ipsec) _pyangbind_elements = {'ipsec_auth_key_config': ipsec_auth_key_config, 'ipsec': ipsec, }

793f8382aecc792a01822a24183cee5cb5f842c8

py

Python

flaskr/db.py

ztaylor2/flask-api

73378bcfefe9ac09f6e7c811c1b9aa690b05d8ec

flaskr/db.py

ztaylor2/flask-api

73378bcfefe9ac09f6e7c811c1b9aa690b05d8ec

flaskr/db.py

ztaylor2/flask-api

73378bcfefe9ac09f6e7c811c1b9aa690b05d8ec

"""Set up the sqlite database.""" import sqlite3 import click from flask import current_app, g from flask.cli import with_appcontext def get_db(): """Connect to the database.""" if 'db' not in g: g.db = sqlite3.connect( current_app.config['DATABASE'], detect_types=sqlite3.PARSE_DECLTYPES ) g.db.row_factory = sqlite3.Row return g.db def close_db(e=None): """Close the database.""" db = g.pop('db', None) if db is not None: db.close() def init_db(): """Initialize the database.""" db = get_db() with current_app.open_resource('schema.sql') as f: db.executescript(f.read().decode('utf8')) @click.command('init-db') @with_appcontext def init_db_command(): """Clear the existing data and create new tables.""" init_db() click.echo('Initialized the database.') def init_app(app): """Initialize the app.""" app.teardown_appcontext(close_db) app.cli.add_command(init_db_command)

793f84308769fcb6b5f912c3b8ef38714215d0f6

py

Python

FHIR_Tester_backend/sandbox/resource_tester.py

ideaworld/FHIR_Tester

62844af2de510b65535df5ae60da03a082097df0

FHIR_Tester_backend/sandbox/resource_tester.py

ideaworld/FHIR_Tester

62844af2de510b65535df5ae60da03a082097df0

2020-06-05T17:40:18.000Z

2022-02-11T03:38:16.000Z

FHIR_Tester_backend/sandbox/resource_tester.py

bowen1993/FHIR_Tester

62844af2de510b65535df5ae60da03a082097df0

2016-11-22T01:04:16.000Z

2016-11-22T01:04:16.000Z

import os import sys pro_dir = os.getcwd() sys.path.append(pro_dir) os.environ.setdefault("DJANGO_SETTINGS_MODULE", "FHIR_Tester.settings") from services.genomics_test_generator.fhir_genomics_test_gene import * from services.request_sender import * from services.create_resource import * spec_basepath = 'resources/spec/' resource_basepath = 'resources/json/' def iter_all_cases(resource_type, all_cases, url,id_dict, access_token=None): #test right cases print 'test' isSuccessful = True for case in all_cases['right']: case = set_reference(case,id_dict) response, req_header, res_header = send_create_resource_request(json.dumps(case), url, access_token) if isinstance(response, dict) and 'issue' in response and response['issue'][0]['severity'] == 'information': isSuccessful = isSuccessful and True else: if isinstance(response, str): hint += response elif isinstance(response, dict): hint += response['issue'][0]['diagnostics'] isSuccessful = isSuccessful and False print "%s:Proper %s cases tested:%s" % (resource_type, resource_type, 'success' if isSuccessful else 'fail') isSuccessfulFalse = True for case_with_info in all_cases['wrong']: case = case_with_info['case'] response, req_header, res_header = send_create_resource_request(json.dumps(case), url, access_token) if isinstance(response, dict) and 'issue' in response and response['issue'][0]['severity'] == 'information': isSuccessfulFalse = isSuccessfulFalse and False else: isSuccessfulFalse = isSuccessfulFalse and True print "%s:Improper %s cases tested:%s" % (resource_type, resource_type, 'success' if isSuccessfulFalse else 'fail') return isSuccessful and isSuccessfulFalse def test_a_resource(resource_name, url, access_token=None): print resource_name #setup id_dict = setup(url, access_token) spec_filename = '%s%s.csv' % (spec_basepath, resource_name) print spec_filename all_cases = create_all_test_case4type(spec_filename, resource_name) if not url.endswith('/'): url += '/' isSuccessful = iter_all_cases(resource_name, all_cases, '%s%s' % (url, resource_name),id_dict, access_token) print "%s:All %s cases tested:%s" % (resource_name, resource_name, 'success' if isSuccessful else 'fail') return def create_all_test_case4type(resource_spec_filename,resource_type): #load spec csv_reader = csv.reader(open(resource_spec_filename, 'r')) detail_dict = trans_csv_to_dict(csv_reader) del csv_reader #generate all cases test_cases = create_element_test_cases(detail_dict) right_cases, wrong_cases = create_orthogonal_test_cases(test_cases) #wrap test cases all_cases = {} all_cases['right'] = [] all_cases['wrong'] = [] for case in right_cases: case['resourceType'] = resource_type all_cases['right'].append(case) for case in wrong_cases: case['case']['resourceType'] = resource_type all_cases['wrong'].append(case) #return all cases return all_cases def ana_pre_creation_result(raw_info): processed_info = {} for key in raw_info: if raw_info[key] and 'issue' in raw_info[key]: if raw_info[key]['issue'][0]['severity'] == 'information': processed_info[key] = True else: processed_info[key] = False return processed_info def setup(url, access_token=None): create_res, id_dict = create_pre_resources(url, 'resources', access_token) pre_resource_result = ana_pre_creation_result(create_res) # print pre_resource_result status = True for key in pre_resource_result: status = status and pre_resource_result[key] print "Setup:Setup:%s" % "success" if status else "fail" return id_dict

793f845876ddfe2b92bb50cc7294d2bcfc8228b4

py

Python

typeidea/blog/migrations/0002_auto_20200221_1454.py

Phoenix-sy/typeidea

e913218872c7f4e9afc290eb42b4ca8c8e4523be

typeidea/blog/migrations/0002_auto_20200221_1454.py

Phoenix-sy/typeidea

e913218872c7f4e9afc290eb42b4ca8c8e4523be

2020-06-06T01:37:34.000Z

2021-09-08T01:49:56.000Z

typeidea/blog/migrations/0002_auto_20200221_1454.py

Phoenix-sy/typeidea

e913218872c7f4e9afc290eb42b4ca8c8e4523be

# -*- coding: utf-8 -*- # Generated by Django 1.11.4 on 2020-02-21 06:54 from __future__ import unicode_literals from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('blog', '0001_initial'), ] operations = [ migrations.AddField( model_name='post', name='pv', field=models.PositiveIntegerField(default=1), ), migrations.AddField( model_name='post', name='uv', field=models.PositiveIntegerField(default=1), ), ]

793f84d95f4cea7dc9443c01f8c8128a0d110de4

py

Python

ctpn/dataset.py

CrazySummerday/ctpn.pytorch

99f6baf2780e550d7b4656ac7a7b90af9ade468f

2019-09-09T07:06:02.000Z

2022-03-07T06:39:11.000Z

ctpn/dataset.py

CrazySummerday/ctpn.pytorch

99f6baf2780e550d7b4656ac7a7b90af9ade468f

2020-09-01T02:31:35.000Z

2021-10-20T08:50:09.000Z

ctpn/dataset.py

CrazySummerday/ctpn.pytorch

99f6baf2780e550d7b4656ac7a7b90af9ade468f

2019-09-11T11:50:42.000Z

2022-01-29T18:22:32.000Z

#-*- coding:utf-8 -*- import os import numpy as np import cv2 import torch from torch.utils.data import Dataset import xml.etree.ElementTree as ET from ctpn.utils import cal_rpn IMAGE_MEAN = [123.68, 116.779, 103.939] ''' 从xml文件中读取图像中的真值框 ''' def readxml(path): gtboxes = [] xml = ET.parse(path) for elem in xml.iter(): if 'object' in elem.tag: for attr in list(elem): if 'bndbox' in attr.tag: xmin = int(round(float(attr.find('xmin').text))) ymin = int(round(float(attr.find('ymin').text))) xmax = int(round(float(attr.find('xmax').text))) ymax = int(round(float(attr.find('ymax').text))) gtboxes.append((xmin, ymin, xmax, ymax)) return np.array(gtboxes) ''' 读取VOC格式数据，返回用于训练的图像、anchor目标框、标签 ''' class VOCDataset(Dataset): def __init__(self, datadir, labelsdir): if not os.path.isdir(datadir): raise Exception('[ERROR] {} is not a directory'.format(datadir)) if not os.path.isdir(labelsdir): raise Exception('[ERROR] {} is not a directory'.format(labelsdir)) self.datadir = datadir self.img_names = os.listdir(self.datadir) self.labelsdir = labelsdir def __len__(self): return len(self.img_names) def generate_gtboxes(self, xml_path, rescale_fac = 1.0): base_gtboxes = readxml(xml_path) gtboxes = [] for base_gtbox in base_gtboxes: xmin, ymin, xmax, ymax = base_gtbox if rescale_fac > 1.0: xmin = int(xmin / rescale_fac) xmax = int(xmax / rescale_fac) ymin = int(ymin / rescale_fac) ymax = int(ymax / rescale_fac) prev = xmin for i in range(xmin // 16 + 1, xmax // 16 + 1): next = 16*i-0.5 gtboxes.append((prev, ymin, next, ymax)) prev = next gtboxes.append((prev, ymin, xmax, ymax)) return np.array(gtboxes) def __getitem__(self, idx): img_name = self.img_names[idx] img_path = os.path.join(self.datadir, img_name) img = cv2.imread(img_path) h, w, c = img.shape rescale_fac = max(h, w) / 1000 if rescale_fac > 1.0: h = int(h / rescale_fac) w = int(w / rescale_fac) img = cv2.resize(img,(w,h)) xml_path = os.path.join(self.labelsdir, img_name.split('.')[0]+'.xml') gtbox = self.generate_gtboxes(xml_path, rescale_fac) if np.random.randint(2) == 1: img = img[:, ::-1, :] newx1 = w - gtbox[:, 2] - 1 newx2 = w - gtbox[:, 0] - 1 gtbox[:, 0] = newx1 gtbox[:, 2] = newx2 [cls, regr] = cal_rpn((h, w), (int(h / 16), int(w / 16)), 16, gtbox) regr = np.hstack([cls.reshape(cls.shape[0], 1), regr]) cls = np.expand_dims(cls, axis=0) m_img = img - IMAGE_MEAN m_img = torch.from_numpy(m_img.transpose([2, 0, 1])).float() cls = torch.from_numpy(cls).float() regr = torch.from_numpy(regr).float() return m_img, cls, regr ################################################################################ class ICDARDataset(Dataset): def __init__(self, datadir, labelsdir): if not os.path.isdir(datadir): raise Exception('[ERROR] {} is not a directory'.format(datadir)) if not os.path.isdir(labelsdir): raise Exception('[ERROR] {} is not a directory'.format(labelsdir)) self.datadir = datadir self.img_names = os.listdir(self.datadir) self.labelsdir = labelsdir def __len__(self): return len(self.img_names) def box_transfer(self, coor_lists, rescale_fac = 1.0): gtboxes = [] for coor_list in coor_lists: coors_x = [int(coor_list[2*i]) for i in range(4)] coors_y = [int(coor_list[2*i+1]) for i in range(4)] xmin = min(coors_x) xmax = max(coors_x) ymin = min(coors_y) ymax = max(coors_y) if rescale_fac > 1.0: xmin = int(xmin / rescale_fac) xmax = int(xmax / rescale_fac) ymin = int(ymin / rescale_fac) ymax = int(ymax / rescale_fac) gtboxes.append((xmin, ymin, xmax, ymax)) return np.array(gtboxes) def box_transfer_v2(self, coor_lists, rescale_fac = 1.0): gtboxes = [] for coor_list in coor_lists: coors_x = [int(coor_list[2 * i]) for i in range(4)] coors_y = [int(coor_list[2 * i + 1]) for i in range(4)] xmin = min(coors_x) xmax = max(coors_x) ymin = min(coors_y) ymax = max(coors_y) if rescale_fac > 1.0: xmin = int(xmin / rescale_fac) xmax = int(xmax / rescale_fac) ymin = int(ymin / rescale_fac) ymax = int(ymax / rescale_fac) prev = xmin for i in range(xmin // 16 + 1, xmax // 16 + 1): next = 16*i-0.5 gtboxes.append((prev, ymin, next, ymax)) prev = next gtboxes.append((prev, ymin, xmax, ymax)) return np.array(gtboxes) def parse_gtfile(self, gt_path, rescale_fac = 1.0): coor_lists = list() with open(gt_path, 'r', encoding="utf-8-sig") as f: content = f.readlines() for line in content: coor_list = line.split(',')[:8] if len(coor_list) == 8: coor_lists.append(coor_list) return self.box_transfer_v2(coor_lists, rescale_fac) def draw_boxes(self,img,cls,base_anchors,gt_box): for i in range(len(cls)): if cls[i]==1: pt1 = (int(base_anchors[i][0]),int(base_anchors[i][1])) pt2 = (int(base_anchors[i][2]),int(base_anchors[i][3])) img = cv2.rectangle(img,pt1,pt2,(200,100,100)) for i in range(gt_box.shape[0]): pt1 = (int(gt_box[i][0]),int(gt_box[i][1])) pt2 = (int(gt_box[i][2]),int(gt_box[i][3])) img = cv2.rectangle(img, pt1, pt2, (100, 200, 100)) return img def __getitem__(self, idx): img_name = self.img_names[idx] img_path = os.path.join(self.datadir, img_name) img = cv2.imread(img_path) h, w, c = img.shape rescale_fac = max(h, w) / 1000 if rescale_fac > 1.0: h = int(h / rescale_fac) w = int(w / rescale_fac) img = cv2.resize(img,(w,h)) gt_path = os.path.join(self.labelsdir, img_name.split('.')[0]+'.txt') gtbox = self.parse_gtfile(gt_path, rescale_fac) # random flip image if np.random.randint(2) == 1: img = img[:, ::-1, :] newx1 = w - gtbox[:, 2] - 1 newx2 = w - gtbox[:, 0] - 1 gtbox[:, 0] = newx1 gtbox[:, 2] = newx2 [cls, regr] = cal_rpn((h, w), (int(h / 16), int(w / 16)), 16, gtbox) regr = np.hstack([cls.reshape(cls.shape[0], 1), regr]) cls = np.expand_dims(cls, axis=0) m_img = img - IMAGE_MEAN m_img = torch.from_numpy(m_img.transpose([2, 0, 1])).float() cls = torch.from_numpy(cls).float() regr = torch.from_numpy(regr).float() return m_img, cls, regr

793f853a94a76980afe6ccf94dbf8caab5ef398c

py

Python

shorttext/stack/stacking.py

trendmicro/PyShortTextCategorization

86d8ad22035243dbeb1c53fe286d6ef8be9a9fd7

shorttext/stack/stacking.py

trendmicro/PyShortTextCategorization

86d8ad22035243dbeb1c53fe286d6ef8be9a9fd7

shorttext/stack/stacking.py

trendmicro/PyShortTextCategorization

86d8ad22035243dbeb1c53fe286d6ef8be9a9fd7

import pickle import numpy as np from keras.layers import Dense, Reshape from keras.models import Sequential from keras.regularizers import l2 import shorttext.utils.classification_exceptions as e import shorttext.utils.kerasmodel_io as kerasio from shorttext.utils.compactmodel_io import CompactIOMachine # abstract class class StackedGeneralization: """ This is an abstract class for any stacked generalization method. It is an intermediate model that takes the results of other classifiers as the input features, and perform another classification. The classifiers must have the :func:`~score` method that takes a string as an input argument. More references: David H. Wolpert, "Stacked Generalization," *Neural Netw* 5: 241-259 (1992). M. Paz Sesmero, Agapito I. Ledezma, Araceli Sanchis, "Generating ensembles of heterogeneous classifiers using Stacked Generalization," *WIREs Data Mining and Knowledge Discovery* 5: 21-34 (2015). """ def __init__(self, intermediate_classifiers={}): """ Initialize the stacking class instance. :param intermediate_classifiers: dictionary, with key being a string, and the values intermediate classifiers, that have the method :func:`~score`, which takes a string as the input argument. :type intermediate_classifiers: dict """ self.classifiers = intermediate_classifiers self.classlabels = [] self.trained = False def register_classifiers(self): """ Register the intermediate classifiers. It must be run before any training. :return: None """ self.classifier2idx = {} self.idx2classifier = {} for idx, key in enumerate(self.classifiers.keys()): self.classifier2idx[key] = idx self.idx2classifier[idx] = key def register_classlabels(self, labels): """ Register output labels. Given the labels, it gives an integer as the index for each label. It is essential for the output model to place. It must be run before any training. :param labels: list of output labels :return: None :type labels: list """ self.classlabels = list(labels) self.labels2idx = {classlabel: idx for idx, classlabel in enumerate(self.classlabels)} def add_classifier(self, name, classifier): """ Add a classifier. Add a classifier to the class. The classifier must have the method :func:`~score` which takes a string as an input argument. :param name: name of the classifier, without spaces and any special characters :param classifier: instance of a classifier, which has a method :func:`~score` which takes a string as an input argument :return: None :type name: str :type classifier: any class with a method :func:`~score` """ self.classifiers[name] = classifier self.register_classifiers() def delete_classifier(self, name): """ Delete a classifier. :param name: name of the classifier to be deleted :return: None :type name: str :raise: KeyError """ del self.classifiers[name] self.register_classifiers() def translate_shorttext_intfeature_matrix(self, shorttext): """ Represent the given short text as the input matrix of the stacking class. :param shorttext: short text :return: input matrix of the stacking class :type shorttext: str :rtype: numpy.ndarray """ feature_matrix = np.zeros((len(self.classifier2idx), len(self.labels2idx))) for key in self.classifier2idx: scoredict = self.classifiers[key].score(shorttext) for label in scoredict: feature_matrix[self.classifier2idx[key], self.labels2idx[label]] = scoredict[label] return feature_matrix def convert_label_to_buckets(self, label): """ Convert the label into an array of bucket. Some classification algorithms, especially those of neural networks, have the output as a serious of buckets with the correct answer being 1 in the correct label, with other being 0. This method convert the label into the corresponding buckets. :param label: label :return: array of buckets :type label: str :rtype: numpy.ndarray """ buckets = np.zeros(len(self.labels2idx), dtype=np.int) buckets[self.labels2idx[label]] = 1 return buckets def convert_traindata_matrix(self, classdict, tobucket=True): """ Returns a generator that returns the input matrix and the output labels for training. :param classdict: dictionary of the training data :param tobucket: whether to convert the label into buckets (Default: True) :return: array of input matrix, and output labels :type classdict: dict :type tobucket: bool :rtype: tuple """ for label in classdict: y = self.convert_label_to_buckets(label) if tobucket else self.labels2idx[label] for shorttext in classdict[label]: X = self.translate_shorttext_intfeature_matrix(shorttext) yield X, y def train(self, classdict, *args, **kwargs): """ Train the stacked generalization. Not implemented. `NotImplemntedException` raised. :param classdict: training data :param args: arguments to be parsed :param kwargs: arguments to be parsed :return: None :type classdict: dict :type args: dict :type kwargs: dict :raise: NotImplementedException """ raise e.NotImplementedException() def score(self, shorttext, *args, **kwargs): """ Calculate the scores for each class labels. Not implemented. `NotImplemntedException` raised. :param shorttext: short text to be scored :param args: arguments to be parsed :param kwargs: arguments to be parsed :return: dictionary of scores for all class labels :type shorttext: str :type args: dict :type kwargs: dict :rtype: dict :raise: NotImplementedException """ raise e.NotImplementedException() class LogisticStackedGeneralization(StackedGeneralization, CompactIOMachine): """ This class implements logistic regression as the stacked generalizer. It is an intermediate model that takes the results of other classifiers as the input features, and perform another classification. This class saves the stacked logistic model, but not the information of the primary model. The classifiers must have the :func:`~score` method that takes a string as an input argument. """ def __init__(self, intermediate_classifiers={}): CompactIOMachine.__init__(self, {'classifier': 'stacked_logistics'}, 'stacked_logistics', ['_stackedlogistics.pkl', '_stackedlogistics.h5', '_stackedlogistics.json']) StackedGeneralization.__init__(self, intermediate_classifiers=intermediate_classifiers) def train(self, classdict, optimizer='adam', l2reg=0.01, bias_l2reg=0.01, nb_epoch=1000): """ Train the stacked generalization. :param classdict: training data :param optimizer: optimizer to use Options: sgd, rmsprop, adagrad, adadelta, adam, adamax, nadam. (Default: 'adam', for adam optimizer) :param l2reg: coefficients for L2-regularization (Default: 0.01) :param bias_l2reg: coefficients for L2-regularization for bias (Default: 0.01) :param nb_epoch: number of epochs for training (Default: 1000) :return: None :type classdict: dict :type optimizer: str :type l2reg: float :type bias_l2reg: float :type nb_epoch: int """ # register self.register_classifiers() self.register_classlabels(classdict.keys()) kmodel = Sequential() kmodel.add(Reshape((len(self.classifier2idx) * len(self.labels2idx),), input_shape=(len(self.classifier2idx), len(self.labels2idx)))) kmodel.add(Dense(units=len(classdict), activation='sigmoid', kernel_regularizer=l2(l2reg), bias_regularizer=l2(bias_l2reg)) ) kmodel.compile(loss='categorical_crossentropy', optimizer=optimizer) Xy = [(xone, yone) for xone, yone in self.convert_traindata_matrix(classdict, tobucket=True)] X = np.array([item[0] for item in Xy]) y = np.array([item[1] for item in Xy]) kmodel.fit(X, y, epochs=nb_epoch) self.model = kmodel self.trained = True def score(self, shorttext): """ Calculate the scores for all the class labels for the given short sentence. Given a short sentence, calculate the classification scores for all class labels, returned as a dictionary with key being the class labels, and values being the scores. If the short sentence is empty, or if other numerical errors occur, the score will be `numpy.nan`. If neither :func:`~train` nor :func:`~loadmodel` was run, it will raise `ModelNotTrainedException`. :param shorttext: a short sentence :return: a dictionary with keys being the class labels, and values being the corresponding classification scores :type shorttext: str :rtype: dict """ if not self.trained: raise e.ModelNotTrainedException() input_matrix = self.translate_shorttext_intfeature_matrix(shorttext) prediction = self.model.predict(np.array([input_matrix])) scoredict = {label: prediction[0][idx] for idx, label in enumerate(self.classlabels)} return scoredict def savemodel(self, nameprefix): """ Save the logistic stacked model into files. Save the stacked model into files. Note that the intermediate classifiers are not saved. Users are advised to save those classifiers separately. If neither :func:`~train` nor :func:`~loadmodel` was run, it will raise `ModelNotTrainedException`. :param nameprefix: prefix of the files :return: None :raise: ModelNotTrainedException :type nameprefix: str """ if not self.trained: raise e.ModelNotTrainedException() stackedmodeldict = {'classifiers': self.classifier2idx, 'classlabels': self.classlabels} pickle.dump(stackedmodeldict, open(nameprefix+'_stackedlogistics.pkl', 'wb')) kerasio.save_model(nameprefix+'_stackedlogistics', self.model) def loadmodel(self, nameprefix): """ Load the model with the given prefix. Load the model with the given prefix of their paths. Note that the intermediate classifiers are not loaded, and users are required to load them separately. :param nameprefix: prefix of the model files :return: None :type nameprefix: str """ stackedmodeldict = pickle.load(open(nameprefix+'_stackedlogistics.pkl', 'rb')) self.register_classlabels(stackedmodeldict['classlabels']) self.classifier2idx = stackedmodeldict['classifiers'] self.idx2classifier = {val: key for key, val in self.classifier2idx.items()} self.model = kerasio.load_model(nameprefix+'_stackedlogistics') self.trained = True

793f85c2e8dfc141c911a993610a1b00c7b3b3d8

py

Python

hexamazer/VideoCapture.py

wonkoderverstaendige/hexamazer

eb08135d3eeeade8614957e082a78178b03b1d3d

hexamazer/VideoCapture.py

wonkoderverstaendige/hexamazer

eb08135d3eeeade8614957e082a78178b03b1d3d

2018-04-12T22:53:48.000Z

2018-04-16T13:14:16.000Z

hexamazer/VideoCapture.py

wonkoderverstaendige/hexamazer

eb08135d3eeeade8614957e082a78178b03b1d3d

import cv2 import threading import time class VideoCapture: def __init__(self, path): self.path = path self.capture = cv2.VideoCapture(self.path) self.running = False self.__get_next = False self.lock = threading.Lock() self.frame_rv, self.frame = self.capture.read() self.thread = None assert self.frame_rv def set(self, property, value): return self.capture.set(property, value) def get(self, property): return self.capture.get(property) def start(self): print('Starting capture!') if self.running: return self.running = True self.thread = threading.Thread(target=self.update, args=()) self.thread.start() return self def update(self): while self.running: if self.__get_next: rv, frame = self.capture.read() with self.lock: self.frame = frame self.frame_rv = rv self.__get_next = False else: time.sleep(0.005) def read(self): with self.lock: frame = self.frame.copy() rv = self.frame_rv self.__get_next = rv return rv, frame def stop(self): self.running = False self.thread.join() def __exit__(self, exec_type, exc_value, traceback): self.capture.release()

793f864149b783d6ca209098e111d244245f71a5

py

Python

qa/rpc-tests/p2p_txexpiringsoon.py

michailduzhanski/crypto-release

4e0f14ccc4eaebee6677f06cff4e13f37608c0f8

2020-02-12T16:22:49.000Z

2020-02-13T16:34:31.000Z

qa/rpc-tests/p2p_txexpiringsoon.py

michailduzhanski/crypto-release

4e0f14ccc4eaebee6677f06cff4e13f37608c0f8

qa/rpc-tests/p2p_txexpiringsoon.py

michailduzhanski/crypto-release

4e0f14ccc4eaebee6677f06cff4e13f37608c0f8

#!/usr/bin/env python # Copyright (c) 2018 The Arnak developers # Distributed under the MIT software license, see the accompanying # file COPYING or https://www.opensource.org/licenses/mit-license.php . import sys; assert sys.version_info < (3,), ur"This script does not run under Python 3. Please use Python 2.7.x." from test_framework.authproxy import JSONRPCException from test_framework.mininode import NodeConn, NetworkThread, CInv, \ msg_mempool, msg_getdata, msg_tx, mininode_lock, SAPLING_PROTO_VERSION from test_framework.test_framework import BitcoinTestFramework from test_framework.util import assert_equal, connect_nodes_bi, fail, \ initialize_chain_clean, p2p_port, start_nodes, sync_blocks, sync_mempools from tx_expiry_helper import TestNode, create_transaction from binascii import hexlify class TxExpiringSoonTest(BitcoinTestFramework): def setup_chain(self): print "Initializing test directory " + self.options.tmpdir initialize_chain_clean(self.options.tmpdir, 3) def setup_network(self): self.nodes = start_nodes(3, self.options.tmpdir) connect_nodes_bi(self.nodes, 0, 1) # We don't connect node 2 def send_transaction(self, testnode, block, address, expiry_height): tx = create_transaction(self.nodes[0], block, address, 10.0, expiry_height) testnode.send_message(msg_tx(tx)) # Sync up with node after p2p messages delivered testnode.sync_with_ping() # Sync nodes 0 and 1 sync_blocks(self.nodes[:2]) sync_mempools(self.nodes[:2]) return tx def verify_inv(self, testnode, tx): # Make sure we are synced before sending the mempool message testnode.sync_with_ping() # Send p2p message "mempool" to receive contents from arnakd node in "inv" message with mininode_lock: testnode.last_inv = None testnode.send_message(msg_mempool()) # Sync up with node after p2p messages delivered testnode.sync_with_ping() with mininode_lock: msg = testnode.last_inv assert_equal(len(msg.inv), 1) assert_equal(tx.sha256, msg.inv[0].hash) def send_data_message(self, testnode, tx): # Send p2p message "getdata" to verify tx gets sent in "tx" message getdatamsg = msg_getdata() getdatamsg.inv = [CInv(1, tx.sha256)] with mininode_lock: testnode.last_notfound = None testnode.last_tx = None testnode.send_message(getdatamsg) def verify_last_tx(self, testnode, tx): # Sync up with node after p2p messages delivered testnode.sync_with_ping() # Verify data received in "tx" message is for tx with mininode_lock: incoming_tx = testnode.last_tx.tx incoming_tx.rehash() assert_equal(tx.sha256, incoming_tx.sha256) def run_test(self): testnode0 = TestNode() connections = [] connections.append(NodeConn('127.0.0.1', p2p_port(0), self.nodes[0], testnode0, "regtest", SAPLING_PROTO_VERSION)) testnode0.add_connection(connections[0]) # Start up network handling in another thread NetworkThread().start() testnode0.wait_for_verack() # Verify mininodes are connected to arnakd nodes peerinfo = self.nodes[0].getpeerinfo() versions = [x["version"] for x in peerinfo] assert_equal(1, versions.count(SAPLING_PROTO_VERSION)) assert_equal(0, peerinfo[0]["banscore"]) # Mine some blocks so we can spend coinbase_blocks = self.nodes[0].generate(200) node_address = self.nodes[0].getnewaddress() # Sync nodes 0 and 1 sync_blocks(self.nodes[:2]) sync_mempools(self.nodes[:2]) # Verify block count assert_equal(self.nodes[0].getblockcount(), 200) assert_equal(self.nodes[1].getblockcount(), 200) assert_equal(self.nodes[2].getblockcount(), 0) # Mininodes send expiring soon transaction in "tx" message to arnakd node self.send_transaction(testnode0, coinbase_blocks[0], node_address, 203) # Assert that the tx is not in the mempool (expiring soon) assert_equal([], self.nodes[0].getrawmempool()) assert_equal([], self.nodes[1].getrawmempool()) assert_equal([], self.nodes[2].getrawmempool()) # Mininodes send transaction in "tx" message to arnakd node tx2 = self.send_transaction(testnode0, coinbase_blocks[1], node_address, 204) # tx2 is not expiring soon assert_equal([tx2.hash], self.nodes[0].getrawmempool()) assert_equal([tx2.hash], self.nodes[1].getrawmempool()) # node 2 is isolated assert_equal([], self.nodes[2].getrawmempool()) # Verify txid for tx2 self.verify_inv(testnode0, tx2) self.send_data_message(testnode0, tx2) self.verify_last_tx(testnode0, tx2) # Sync and mine an empty block with node 2, leaving tx in the mempool of node0 and node1 for blkhash in coinbase_blocks: blk = self.nodes[0].getblock(blkhash, 0) self.nodes[2].submitblock(blk) self.nodes[2].generate(1) # Verify block count assert_equal(self.nodes[0].getblockcount(), 200) assert_equal(self.nodes[1].getblockcount(), 200) assert_equal(self.nodes[2].getblockcount(), 201) # Reconnect node 2 to the network connect_nodes_bi(self.nodes, 0, 2) # Set up test node for node 2 testnode2 = TestNode() connections.append(NodeConn('127.0.0.1', p2p_port(2), self.nodes[2], testnode2, "regtest", SAPLING_PROTO_VERSION)) testnode2.add_connection(connections[-1]) # Verify block count sync_blocks(self.nodes[:3]) assert_equal(self.nodes[0].getblockcount(), 201) assert_equal(self.nodes[1].getblockcount(), 201) assert_equal(self.nodes[2].getblockcount(), 201) # Verify contents of mempool assert_equal([tx2.hash], self.nodes[0].getrawmempool()) assert_equal([tx2.hash], self.nodes[1].getrawmempool()) assert_equal([], self.nodes[2].getrawmempool()) # Confirm tx2 cannot be submitted to a mempool because it is expiring soon. try: rawtx2 = hexlify(tx2.serialize()) self.nodes[2].sendrawtransaction(rawtx2) fail("Sending transaction should have failed") except JSONRPCException as e: assert_equal( "tx-expiring-soon: expiryheight is 204 but should be at least 205 to avoid transaction expiring soon", e.error['message'] ) self.send_data_message(testnode0, tx2) # Sync up with node after p2p messages delivered testnode0.sync_with_ping() # Verify node 0 does not reply to "getdata" by sending "tx" message, as tx2 is expiring soon with mininode_lock: assert_equal(testnode0.last_tx, None) # Verify mininode received a "notfound" message containing the txid of tx2 with mininode_lock: msg = testnode0.last_notfound assert_equal(len(msg.inv), 1) assert_equal(tx2.sha256, msg.inv[0].hash) # Create a transaction to verify that processing of "getdata" messages is functioning tx3 = self.send_transaction(testnode0, coinbase_blocks[2], node_address, 999) self.send_data_message(testnode0, tx3) self.verify_last_tx(testnode0, tx3) # Verify txid for tx3 is returned in "inv", but tx2 which is expiring soon is not returned self.verify_inv(testnode0, tx3) self.verify_inv(testnode2, tx3) # Verify contents of mempool assert_equal({tx2.hash, tx3.hash}, set(self.nodes[0].getrawmempool())) assert_equal({tx2.hash, tx3.hash}, set(self.nodes[1].getrawmempool())) assert_equal({tx3.hash}, set(self.nodes[2].getrawmempool())) # Verify banscore for nodes are still zero assert_equal(0, sum(peer["banscore"] for peer in self.nodes[0].getpeerinfo())) assert_equal(0, sum(peer["banscore"] for peer in self.nodes[2].getpeerinfo())) [c.disconnect_node() for c in connections] if __name__ == '__main__': TxExpiringSoonTest().main()

793f8755a15c1e97f67c9f4997dfbe6f73a9bb8c

py

Python

docs/conf.py

dwgoltra/pyjanitor

c5e1a407ec098dbca411118c67090c85d5e687c7

docs/conf.py

dwgoltra/pyjanitor

c5e1a407ec098dbca411118c67090c85d5e687c7

docs/conf.py

dwgoltra/pyjanitor

c5e1a407ec098dbca411118c67090c85d5e687c7

"""Sphinx configuration.""" # -*- coding: utf-8 -*- # # Configuration file for the Sphinx documentation builder. # # This file does only contain a selection of the most common options. For a # full list see the documentation: # http://www.sphinx-doc.org/en/stable/config # -- Path setup -------------------------------------------------------------- import datetime # If extensions (or modules to document with autodoc) are in another directory, # add these directories to sys.path here. If the directory is relative to the # documentation root, use os.path.abspath to make it absolute, like shown here. # import os import sys from pathlib import Path sys.path.insert(0, os.path.abspath(".")) sys.path.insert(0, os.path.abspath("../examples")) # Make a symlink in our sphinx source directory to the top-level # examples/notebooks directory so we can include notebooks in the doc notebooks = Path("./notebooks") if not notebooks.exists(): print("Making symlink to ../examples/notebooks") notebooks.symlink_to("../examples/notebooks") # -- Project information ----------------------------------------------------- project = "pyjanitor" now = datetime.datetime.now() CurrentYear = str(now.year) copyright = CurrentYear + ", PyJanitor devs" author = "Eric J. Ma" # The short X.Y version version = "0.1.0" # The full version, including alpha/beta/rc tags release = "" # -- General configuration --------------------------------------------------- # If your documentation needs a minimal Sphinx version, state it here. # # needs_sphinx = '1.0' # Add any Sphinx extension module names here, as strings. They can be # extensions coming with Sphinx (named 'sphinx.ext.*') or your custom # ones. extensions = [ "sphinx.ext.autodoc", "sphinx.ext.doctest", "sphinx.ext.intersphinx", "sphinx.ext.todo", "sphinx.ext.coverage", "sphinx.ext.viewcode", "sphinx.ext.githubpages", "sphinxcontrib.fulltoc", "nbsphinx", "sphinx.ext.autosummary", ] # Add any paths that contain templates here, relative to this directory. templates_path = ["_templates"] # The suffix(es) of source filenames. # You can specify multiple suffix as a list of string: # # source_suffix = ['.rst', '.md'] source_suffix = [".md", ".rst", ".ipynb"] # The master toctree document. master_doc = "index" # The language for content autogenerated by Sphinx. Refer to documentation # for a list of supported languages. # # This is also used if you do content translation via gettext catalogs. # Usually you set "language" from the command line for these cases. language = None # List of patterns, relative to source directory, that match files and # directories to ignore when looking for source files. # This pattern also affects html_static_path and html_extra_path . exclude_patterns = ["_build", "Thumbs.db", ".DS_Store", "**.ipynb_checkpoints"] # The name of the Pygments (syntax highlighting) style to use. pygments_style = "sphinx" # -- Options for HTML output ------------------------------------------------- # The theme to use for HTML and HTML Help pages. See the documentation for # a list of builtin themes. # html_theme = "alabaster" # Theme options are theme-specific and customize the look and feel of a theme # further. For a list of options available for each theme, see the # documentation. # html_theme_options = {"logo": "logo_title.svg"} # Add any paths that contain custom static files (such as style sheets) here, # relative to this directory. They are copied after the builtin static files, # so a file named "default.css" will overwrite the builtin "default.css". html_static_path = ["_static"] # Custom sidebar templates, must be a dictionary that maps document names # to template names. # # The default sidebars (for documents that don't match any pattern) are # defined by theme itself. Builtin themes are using these templates by # default: ``['localtoc.html', 'relations.html', 'sourcelink.html', # 'searchbox.html']``. # html_sidebars = { "**": ["about.html", "navigation.html", "relations.html", "searchbox.html"] } # -- Options for HTMLHelp output --------------------------------------------- # Output file base name for HTML help builder. htmlhelp_basename = "pyjanitordoc" # -- Options for LaTeX output ------------------------------------------------ latex_elements = { # The paper size ('letterpaper' or 'a4paper'). # # 'papersize': 'letterpaper', # The font size ('10pt', '11pt' or '12pt'). # # 'pointsize': '10pt', # Additional stuff for the LaTeX preamble. # # 'preamble': '', # Latex figure (float) alignment # # 'figure_align': 'htbp', } # Grouping the document tree into LaTeX files. List of tuples # (source start file, target name, title, # author, documentclass [howto, manual, or own class]). latex_documents = [ ( master_doc, "pyjanitor.tex", "pyjanitor Documentation", "Eric J. Ma", "manual", ) ] # -- Options for manual page output ------------------------------------------ # One entry per manual page. List of tuples # (source start file, name, description, authors, manual section). man_pages = [(master_doc, "pyjanitor", "pyjanitor Documentation", [author], 1)] # -- Options for Texinfo output ---------------------------------------------- # Grouping the document tree into Texinfo files. List of tuples # (source start file, target name, title, author, # dir menu entry, description, category) texinfo_documents = [ ( master_doc, "pyjanitor", "pyjanitor Documentation", author, "pyjanitor", "One line description of project.", "Miscellaneous", ) ] # -- Extension configuration ------------------------------------------------- # -- Options for intersphinx extension --------------------------------------- # Example configuration for intersphinx: refer to the Python standard library. intersphinx_mapping = { "https://docs.python.org/": None, "https://pandas.pydata.org/pandas-docs/stable": None, } # -- Options for todo extension ---------------------------------------------- # If true, `todo` and `todoList` produce output, else they produce nothing. todo_include_todos = True # -- Other options ----------------------------------------------------------- autosummary_generate = True # Make _autosummary files and include them

793f8777506f2aa0b78bccc5a959964301cedafb

py

Python

pyPS4Controller/controller.py

sheeshee/pyPS4Controller

e9dc88292e6d79c8428ecfa22330236167b363c6

pyPS4Controller/controller.py

sheeshee/pyPS4Controller

e9dc88292e6d79c8428ecfa22330236167b363c6

pyPS4Controller/controller.py

sheeshee/pyPS4Controller

e9dc88292e6d79c8428ecfa22330236167b363c6

import os import struct import time class Event: def __init__(self, button_id, button_type, value, connecting_using_ds4drv): self.button_id = button_id self.button_type = button_type self.value = value self.connecting_using_ds4drv = connecting_using_ds4drv # L joystick group # def L3_event(self): # L3 has the same mapping on ds4drv as it does when connecting to bluetooth directly return self.button_type == 2 and self.button_id in [1, 0] def L3_at_rest(self): return self.button_id in [1, 0] and self.value == 0 def L3_up(self): return self.button_id == 1 and self.value < 0 def L3_down(self): return self.button_id == 1 and self.value > 0 def L3_left(self): return self.button_id == 0 and self.value < 0 def L3_right(self): return self.button_id == 0 and self.value > 0 def L3_pressed(self): if not self.connecting_using_ds4drv: return self.button_id == 11 and self.button_type == 1 and self.value == 1 return False # cant identify this event when connected through ds4drv def L3_released(self): if not self.connecting_using_ds4drv: return self.button_id == 11 and self.button_type == 1 and self.value == 0 return False # cant identify this event when connected through ds4drv # R joystick group # def R3_event(self): if not self.connecting_using_ds4drv: return self.button_type == 2 and self.button_id in [4, 3] return self.button_type == 2 and self.button_id in [5, 2] def R3_at_rest(self): if not self.connecting_using_ds4drv: return self.button_id in [4, 3] and self.value == 0 return self.button_id in [2, 5] and self.value == 0 def R3_up(self): if not self.connecting_using_ds4drv: return self.button_id == 4 and self.value < 0 return self.button_id == 5 and self.value < 0 def R3_down(self): if not self.connecting_using_ds4drv: return self.button_id == 4 and self.value > 0 return self.button_id == 5 and self.value > 0 def R3_left(self): if not self.connecting_using_ds4drv: return self.button_id == 3 and self.value < 0 return self.button_id == 2 and self.value < 0 def R3_right(self): if not self.connecting_using_ds4drv: return self.button_id == 3 and self.value > 0 return self.button_id == 2 and self.value > 0 def R3_pressed(self): if not self.connecting_using_ds4drv: return self.button_id == 12 and self.button_type == 1 and self.value == 1 return False # cant identify this event when connected through ds4drv def R3_released(self): if not self.connecting_using_ds4drv: return self.button_id == 12 and self.button_type == 1 and self.value == 0 return False # cant identify this event when connected through ds4drv # Square / Triangle / Circle / X Button group # def circle_pressed(self): return self.button_id == 2 and self.button_type == 1 and self.value == 1 def circle_released(self): return self.button_id == 2 and self.button_type == 1 and self.value == 0 def x_pressed(self): return self.button_id == 1 and self.button_type == 1 and self.value == 1 def x_released(self): return self.button_id == 1 and self.button_type == 1 and self.value == 0 def triangle_pressed(self): return self.button_id == 3 and self.button_type == 1 and self.value == 1 def triangle_released(self): return self.button_id == 3 and self.button_type == 1 and self.value == 0 def square_pressed(self): return self.button_id == 0 and self.button_type == 1 and self.value == 1 def square_released(self): return self.button_id == 0 and self.button_type == 1 and self.value == 0 def options_pressed(self): return self.button_id == 9 and self.button_type == 1 and self.value == 1 def options_released(self): return self.button_id == 9 and self.button_type == 1 and self.value == 0 def share_pressed(self): if not self.connecting_using_ds4drv: return self.button_id == 8 and self.button_type == 1 and self.value == 1 return False # cant identify this event when connected through ds4drv def share_released(self): if not self.connecting_using_ds4drv: return self.button_id == 8 and self.button_type == 1 and self.value == 0 return False # cant identify this event when connected through ds4drv # N1 group # def L1_pressed(self): return self.button_id == 4 and self.button_type == 1 and self.value == 1 def L1_released(self): return self.button_id == 4 and self.button_type == 1 and self.value == 0 def R1_pressed(self): return self.button_id == 5 and self.button_type == 1 and self.value == 1 def R1_released(self): return self.button_id == 5 and self.button_type == 1 and self.value == 0 # N2 group # def L2_pressed(self): if not self.connecting_using_ds4drv: return self.button_id == 2 and self.button_type == 2 and (32767 >= self.value >= -32766) return self.button_id == 3 and self.button_type == 2 and (32767 >= self.value >= -32766) def L2_released(self): if not self.connecting_using_ds4drv: return self.button_id == 2 and self.button_type == 2 and self.value == -32767 return self.button_id == 3 and self.button_type == 2 and self.value == -32767 def R2_pressed(self): if not self.connecting_using_ds4drv: return self.button_id == 5 and self.button_type == 2 and (32767 >= self.value >= -32766) return self.button_id == 4 and self.button_type == 2 and (32767 >= self.value >= -32766) def R2_released(self): if not self.connecting_using_ds4drv: return self.button_id == 5 and self.button_type == 2 and self.value == -32767 return self.button_id == 4 and self.button_type == 2 and self.value == -32767 # up / down arrows # def up_arrow_pressed(self): if not self.connecting_using_ds4drv: return self.button_id == 7 and self.button_type == 2 and self.value == -32767 return self.button_id == 10 and self.button_type == 2 and self.value == -32767 def down_arrow_pressed(self): if not self.connecting_using_ds4drv: return self.button_id == 7 and self.button_type == 2 and self.value == 32767 return self.button_id == 10 and self.button_type == 2 and self.value == 32767 def up_down_arrow_released(self): # arrow buttons on release are not distinguishable and if you think about it, # they are following same principle as the joystick buttons which only have 1 # state at rest which is shared between left/ right / up /down inputs if not self.connecting_using_ds4drv: return self.button_id == 7 and self.button_type == 2 and self.value == 0 return self.button_id == 10 and self.button_type == 2 and self.value == 0 # left / right arrows # def left_arrow_pressed(self): if not self.connecting_using_ds4drv: return self.button_id == 6 and self.button_type == 2 and self.value == -32767 return self.button_id == 9 and self.button_type == 2 and self.value == -32767 def right_arrow_pressed(self): if not self.connecting_using_ds4drv: return self.button_id == 6 and self.button_type == 2 and self.value == 32767 return self.button_id == 9 and self.button_type == 2 and self.value == 32767 def left_right_arrow_released(self): # arrow buttons on release are not distinguishable and if you think about it, # they are following same principle as the joystick buttons which only have 1 # state at rest which is shared between left/ right / up /down inputs if not self.connecting_using_ds4drv: return self.button_id == 6 and self.button_type == 2 and self.value == 0 return self.button_id == 9 and self.button_type == 2 and self.value == 0 def playstation_button_pressed(self): if not self.connecting_using_ds4drv: return self.button_id == 10 and self.button_type == 1 and self.value == 1 return False # cant identify this event when connected through ds4drv def playstation_button_released(self): if not self.connecting_using_ds4drv: return self.button_id == 10 and self.button_type == 1 and self.value == 0 return False # cant identify this event when connected through ds4drv class Actions: """ Actions are inherited in the Controller class. In order to bind to the controller events, subclass the Controller class and override desired action events in this class. """ def __init__(self): return def on_x_press(self): print("on_x_press") def on_x_release(self): print("on_x_release") def on_triangle_press(self): print("on_triangle_press") def on_triangle_release(self): print("on_triangle_release") def on_circle_press(self): print("on_circle_press") def on_circle_release(self): print("on_circle_release") def on_square_press(self): print("on_square_press") def on_square_release(self): print("on_square_release") def on_L1_press(self): print("on_L1_press") def on_L1_release(self): print("on_L1_release") def on_L2_press(self, value): print("on_L2_press: {}".format(value)) def on_L2_release(self): print("on_L2_release") def on_R1_press(self): print("on_R1_press") def on_R1_release(self): print("on_R1_release") def on_R2_press(self, value): print("on_R2_press: {}".format(value)) def on_R2_release(self): print("on_R2_release") def on_up_arrow_press(self): print("on_up_arrow_press") def on_up_down_arrow_release(self): print("on_up_down_arrow_release") def on_down_arrow_press(self): print("on_down_arrow_press") def on_left_arrow_press(self): print("on_left_arrow_press") def on_left_right_arrow_release(self): print("on_left_right_arrow_release") def on_right_arrow_press(self): print("on_right_arrow_press") def on_L3_up(self, value): print("on_L3_up: {}".format(value)) def on_L3_down(self, value): print("on_L3_down: {}".format(value)) def on_L3_left(self, value): print("on_L3_left: {}".format(value)) def on_L3_right(self, value): print("on_L3_right: {}".format(value)) def on_L3_at_rest(self): """L3 joystick is at rest after the joystick was moved and let go off""" print("on_L3_at_rest") def on_L3_press(self): """L3 joystick is clicked. This event is only detected when connecting without ds4drv""" print("on_L3_press") def on_L3_release(self): """L3 joystick is released after the click. This event is only detected when connecting without ds4drv""" print("on_L3_release") def on_R3_up(self, value): print("on_R3_up: {}".format(value)) def on_R3_down(self, value): print("on_R3_down: {}".format(value)) def on_R3_left(self, value): print("on_R3_left: {}".format(value)) def on_R3_right(self, value): print("on_R3_right: {}".format(value)) def on_R3_at_rest(self): """R3 joystick is at rest after the joystick was moved and let go off""" print("on_R3_at_rest") def on_R3_press(self): """R3 joystick is clicked. This event is only detected when connecting without ds4drv""" print("on_R3_press") def on_R3_release(self): """R3 joystick is released after the click. This event is only detected when connecting without ds4drv""" print("on_R3_release") def on_options_press(self): print("on_options_press") def on_options_release(self): print("on_options_release") def on_share_press(self): """this event is only detected when connecting without ds4drv""" print("on_share_press") def on_share_release(self): """this event is only detected when connecting without ds4drv""" print("on_share_release") def on_playstation_button_press(self): """this event is only detected when connecting without ds4drv""" print("on_playstation_button_press") def on_playstation_button_release(self): """this event is only detected when connecting without ds4drv""" print("on_playstation_button_release") class Controller(Actions): def __init__( self, interface, connecting_using_ds4drv=True, event_definition=None, event_format=None ): """ Initiate controller instance that is capable of listening to all events on specified input interface :param interface: STRING aka /dev/input/js0 or any other PS4 Duelshock controller interface. You can see all available interfaces with a command "ls -la /dev/input/" :param connecting_using_ds4drv: BOOLEAN. If you are connecting your controller using ds4drv, then leave it set to True. Otherwise if you are connecting directly via directly via bluetooth/bluetoothctl, set it to False otherwise the controller button mapping will be off. """ Actions.__init__(self) self.stop = False self.is_connected = False self.interface = interface self.connecting_using_ds4drv = connecting_using_ds4drv self.debug = False # If you want to see raw event stream, set this to True. self.black_listed_buttons = [] # set a list of blocked buttons if you dont want to process their events if self.connecting_using_ds4drv and event_definition is None: # when device is connected via ds4drv its sending hundreds of events for those button IDs # thus they are blacklisted by default. Feel free to adjust this list to your linking when sub-classing self.black_listed_buttons += [6, 7, 8, 11, 12, 13] self.event_definition = event_definition if event_definition else Event self.event_format = event_format if event_format else "LhBB" self.event_size = struct.calcsize(self.event_format) def listen(self, timeout=30, on_connect=None, on_disconnect=None): """ Start listening for events on a given self.interface :param timeout: INT, seconds. How long you want to wait for the self.interface. This allows you to start listening and connect your controller after the fact. If self.interface does not become available in N seconds, the script will exit with exit code 1. :param on_connect: function object, allows to register a call back when connection is established :param on_disconnect: function object, allows to register a call back when connection is lost :return: None """ def on_disconnect_callback(): self.is_connected = False if on_disconnect is not None: on_disconnect() def on_connect_callback(): self.is_connected = True if on_connect is not None: on_connect() def wait_for_interface(): print("Waiting for interface: {} to become available . . .".format(self.interface)) for i in range(timeout): if os.path.exists(self.interface): print("Successfully bound to: {}.".format(self.interface)) on_connect_callback() return time.sleep(1) print("Timeout({} sec). Interface not available.".format(timeout)) exit(1) def read_events(): try: return _file.read(self.event_size) except IOError: print("Interface lost. Device disconnected?") on_disconnect_callback() exit(1) wait_for_interface() while not self.stop: try: _file = open(self.interface, "rb") event = read_events() while event: (*tv_sec, value, button_type, button_id) = struct.unpack(self.event_format, event) if self.debug: print("button_id: {} button_type: {} value: {}".format(button_id, button_type, value)) if button_id not in self.black_listed_buttons: self.__handle_event(button_id=button_id, button_type=button_type, value=value) event = read_events() except KeyboardInterrupt: print("\nExiting (Ctrl + C)") on_disconnect_callback() exit(1) def __handle_event(self, button_id, button_type, value): event = self.event_definition(button_id=button_id, button_type=button_type, value=value, connecting_using_ds4drv=self.connecting_using_ds4drv) if event.R3_event(): if event.R3_at_rest(): self.on_R3_at_rest() elif event.R3_right(): self.on_R3_right(value) elif event.R3_left(): self.on_R3_left(value) elif event.R3_up(): self.on_R3_up(value) elif event.R3_down(): self.on_R3_down(value) elif event.L3_event(): if event.L3_at_rest(): self.on_L3_at_rest() elif event.L3_up(): self.on_L3_up(value) elif event.L3_down(): self.on_L3_down(value) elif event.L3_left(): self.on_L3_left(value) elif event.L3_right(): self.on_L3_right(value) elif event.circle_pressed(): self.on_circle_press() elif event.circle_released(): self.on_circle_release() elif event.x_pressed(): self.on_x_press() elif event.x_released(): self.on_x_release() elif event.triangle_pressed(): self.on_triangle_press() elif event.triangle_released(): self.on_triangle_release() elif event.square_pressed(): self.on_square_press() elif event.square_released(): self.on_square_release() elif event.L1_pressed(): self.on_L1_press() elif event.L1_released(): self.on_L1_release() elif event.L2_pressed(): self.on_L2_press(value) elif event.L2_released(): self.on_L2_release() elif event.R1_pressed(): self.on_R1_press() elif event.R1_released(): self.on_R1_release() elif event.R2_pressed(): self.on_R2_press(value) elif event.R2_released(): self.on_R2_release() elif event.options_pressed(): self.on_options_press() elif event.options_released(): self.on_options_release() elif event.left_right_arrow_released(): self.on_left_right_arrow_release() elif event.up_down_arrow_released(): self.on_up_down_arrow_release() elif event.left_arrow_pressed(): self.on_left_arrow_press() elif event.right_arrow_pressed(): self.on_right_arrow_press() elif event.up_arrow_pressed(): self.on_up_arrow_press() elif event.down_arrow_pressed(): self.on_down_arrow_press() elif event.playstation_button_pressed(): self.on_playstation_button_press() elif event.playstation_button_released(): self.on_playstation_button_release() elif event.share_pressed(): self.on_share_press() elif event.share_released(): self.on_share_release() elif event.R3_pressed(): self.on_R3_press() elif event.R3_released(): self.on_R3_release() elif event.L3_pressed(): self.on_L3_press() elif event.L3_released(): self.on_L3_release()

793f8fc234368d73c13e9f5906a6535c551d84c2

py

Python

code/python/ProcuretoPaySCIM/v1/fds/sdk/ProcuretoPaySCIM/model/location_resource.py

factset/enterprise-sdk

3fd4d1360756c515c9737a0c9a992c7451d7de7e

2022-02-07T16:34:18.000Z

2022-03-30T08:04:57.000Z

code/python/ProcuretoPaySCIM/v1/fds/sdk/ProcuretoPaySCIM/model/location_resource.py

factset/enterprise-sdk

3fd4d1360756c515c9737a0c9a992c7451d7de7e

2022-02-07T05:25:57.000Z

2022-03-07T14:18:04.000Z

code/python/ProcuretoPaySCIM/v1/fds/sdk/ProcuretoPaySCIM/model/location_resource.py

factset/enterprise-sdk

3fd4d1360756c515c9737a0c9a992c7451d7de7e

""" FactSet SCIM API FactSet's SCIM API implementation. # noqa: E501 The version of the OpenAPI document: 1.0.0 Generated by: https://openapi-generator.tech """ import re # noqa: F401 import sys # noqa: F401 from fds.sdk.ProcuretoPaySCIM.model_utils import ( # noqa: F401 ApiTypeError, ModelComposed, ModelNormal, ModelSimple, cached_property, change_keys_js_to_python, convert_js_args_to_python_args, date, datetime, file_type, none_type, validate_get_composed_info, OpenApiModel ) from fds.sdk.ProcuretoPaySCIM.exceptions import ApiAttributeError def lazy_import(): from fds.sdk.ProcuretoPaySCIM.model.location_resource_meta import LocationResourceMeta from fds.sdk.ProcuretoPaySCIM.model.location_resource_reference import LocationResourceReference globals()['LocationResourceMeta'] = LocationResourceMeta globals()['LocationResourceReference'] = LocationResourceReference class LocationResource(ModelNormal): """NOTE: This class is auto generated by OpenAPI Generator. Ref: https://openapi-generator.tech Do not edit the class manually. Attributes: allowed_values (dict): The key is the tuple path to the attribute and the for var_name this is (var_name,). The value is a dict with a capitalized key describing the allowed value and an allowed value. These dicts store the allowed enum values. attribute_map (dict): The key is attribute name and the value is json key in definition. discriminator_value_class_map (dict): A dict to go from the discriminator variable value to the discriminator class name. validations (dict): The key is the tuple path to the attribute and the for var_name this is (var_name,). The value is a dict that stores validations for max_length, min_length, max_items, min_items, exclusive_maximum, inclusive_maximum, exclusive_minimum, inclusive_minimum, and regex. additional_properties_type (tuple): A tuple of classes accepted as additional properties values. """ allowed_values = { } validations = { } @cached_property def additional_properties_type(): """ This must be a method because a model may have properties that are of type self, this must run after the class is loaded """ lazy_import() return (bool, date, datetime, dict, float, int, list, str, none_type,) # noqa: E501 _nullable = False @cached_property def openapi_types(): """ This must be a method because a model may have properties that are of type self, this must run after the class is loaded Returns openapi_types (dict): The key is attribute name and the value is attribute type. """ lazy_import() return { 'schemas': ([str],), # noqa: E501 'id': (str,), # noqa: E501 'external_id': (str,), # noqa: E501 'name': (str,), # noqa: E501 'description': (str,), # noqa: E501 'address1': (str,), # noqa: E501 'address2': (str,), # noqa: E501 'address3': (str,), # noqa: E501 'locality': (str,), # noqa: E501 'region': (str,), # noqa: E501 'postal_code': (str,), # noqa: E501 'country': (str,), # noqa: E501 'phone_number': (str,), # noqa: E501 'main_location': (bool, date, datetime, dict, float, int, list, str, none_type,), # noqa: E501 'meta': (LocationResourceMeta,), # noqa: E501 } @cached_property def discriminator(): return None attribute_map = { 'schemas': 'schemas', # noqa: E501 'id': 'id', # noqa: E501 'external_id': 'externalId', # noqa: E501 'name': 'name', # noqa: E501 'description': 'description', # noqa: E501 'address1': 'address1', # noqa: E501 'address2': 'address2', # noqa: E501 'address3': 'address3', # noqa: E501 'locality': 'locality', # noqa: E501 'region': 'region', # noqa: E501 'postal_code': 'postalCode', # noqa: E501 'country': 'country', # noqa: E501 'phone_number': 'phoneNumber', # noqa: E501 'main_location': 'mainLocation', # noqa: E501 'meta': 'meta', # noqa: E501 } read_only_vars = { 'id', # noqa: E501 'name', # noqa: E501 'description', # noqa: E501 'address1', # noqa: E501 'address2', # noqa: E501 'address3', # noqa: E501 'locality', # noqa: E501 'region', # noqa: E501 'postal_code', # noqa: E501 'country', # noqa: E501 'phone_number', # noqa: E501 } _composed_schemas = {} @classmethod @convert_js_args_to_python_args def _from_openapi_data(cls, *args, **kwargs): # noqa: E501 """LocationResource - a model defined in OpenAPI Keyword Args: _check_type (bool): if True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True _path_to_item (tuple/list): This is a list of keys or values to drill down to the model in received_data when deserializing a response _spec_property_naming (bool): True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default) _configuration (Configuration): the instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done. _visited_composed_classes (tuple): This stores a tuple of classes that we have traveled through so that if we see that class again we will not use its discriminator again. When traveling through a discriminator, the composed schema that is is traveled through is added to this set. For example if Animal has a discriminator petType and we pass in "Dog", and the class Dog allOf includes Animal, we move through Animal once using the discriminator, and pick Dog. Then in Dog, we will make an instance of the Animal class but this time we won't travel through its discriminator because we passed in _visited_composed_classes = (Animal,) schemas ([str]): [optional] # noqa: E501 id (str): [optional] # noqa: E501 external_id (str): [optional] # noqa: E501 name (str): Name of the location.. [optional] # noqa: E501 description (str): Description of the location.. [optional] # noqa: E501 address1 (str): First line of location's address.. [optional] # noqa: E501 address2 (str): Second line of location's address.. [optional] # noqa: E501 address3 (str): Third line of location's address.. [optional] # noqa: E501 locality (str): City of location.. [optional] # noqa: E501 region (str): State or province of location.. [optional] # noqa: E501 postal_code (str): Postal code of location.. [optional] # noqa: E501 country (str): Country of location.. [optional] # noqa: E501 phone_number (str): Phone number of location.. [optional] # noqa: E501 main_location (bool, date, datetime, dict, float, int, list, str, none_type): [optional] # noqa: E501 meta (LocationResourceMeta): [optional] # noqa: E501 """ _check_type = kwargs.pop('_check_type', True) _spec_property_naming = kwargs.pop('_spec_property_naming', False) _path_to_item = kwargs.pop('_path_to_item', ()) _configuration = kwargs.pop('_configuration', None) _visited_composed_classes = kwargs.pop('_visited_composed_classes', ()) self = super(OpenApiModel, cls).__new__(cls) if args: raise ApiTypeError( "Invalid positional arguments=%s passed to %s. Remove those invalid positional arguments." % ( args, self.__class__.__name__, ), path_to_item=_path_to_item, valid_classes=(self.__class__,), ) self._data_store = {} self._check_type = _check_type self._spec_property_naming = _spec_property_naming self._path_to_item = _path_to_item self._configuration = _configuration self._visited_composed_classes = _visited_composed_classes + (self.__class__,) for var_name, var_value in kwargs.items(): if var_name not in self.attribute_map and \ self._configuration is not None and \ self._configuration.discard_unknown_keys and \ self.additional_properties_type is None: # discard variable. continue setattr(self, var_name, var_value) return self required_properties = set([ '_data_store', '_check_type', '_spec_property_naming', '_path_to_item', '_configuration', '_visited_composed_classes', ]) @convert_js_args_to_python_args def __init__(self, *args, **kwargs): # noqa: E501 """LocationResource - a model defined in OpenAPI Keyword Args: _check_type (bool): if True, values for parameters in openapi_types will be type checked and a TypeError will be raised if the wrong type is input. Defaults to True _path_to_item (tuple/list): This is a list of keys or values to drill down to the model in received_data when deserializing a response _spec_property_naming (bool): True if the variable names in the input data are serialized names, as specified in the OpenAPI document. False if the variable names in the input data are pythonic names, e.g. snake case (default) _configuration (Configuration): the instance to use when deserializing a file_type parameter. If passed, type conversion is attempted If omitted no type conversion is done. _visited_composed_classes (tuple): This stores a tuple of classes that we have traveled through so that if we see that class again we will not use its discriminator again. When traveling through a discriminator, the composed schema that is is traveled through is added to this set. For example if Animal has a discriminator petType and we pass in "Dog", and the class Dog allOf includes Animal, we move through Animal once using the discriminator, and pick Dog. Then in Dog, we will make an instance of the Animal class but this time we won't travel through its discriminator because we passed in _visited_composed_classes = (Animal,) schemas ([str]): [optional] # noqa: E501 id (str): [optional] # noqa: E501 external_id (str): [optional] # noqa: E501 name (str): Name of the location.. [optional] # noqa: E501 description (str): Description of the location.. [optional] # noqa: E501 address1 (str): First line of location's address.. [optional] # noqa: E501 address2 (str): Second line of location's address.. [optional] # noqa: E501 address3 (str): Third line of location's address.. [optional] # noqa: E501 locality (str): City of location.. [optional] # noqa: E501 region (str): State or province of location.. [optional] # noqa: E501 postal_code (str): Postal code of location.. [optional] # noqa: E501 country (str): Country of location.. [optional] # noqa: E501 phone_number (str): Phone number of location.. [optional] # noqa: E501 main_location (bool, date, datetime, dict, float, int, list, str, none_type): [optional] # noqa: E501 meta (LocationResourceMeta): [optional] # noqa: E501 """ _check_type = kwargs.pop('_check_type', True) _spec_property_naming = kwargs.pop('_spec_property_naming', False) _path_to_item = kwargs.pop('_path_to_item', ()) _configuration = kwargs.pop('_configuration', None) _visited_composed_classes = kwargs.pop('_visited_composed_classes', ()) if args: raise ApiTypeError( "Invalid positional arguments=%s passed to %s. Remove those invalid positional arguments." % ( args, self.__class__.__name__, ), path_to_item=_path_to_item, valid_classes=(self.__class__,), ) self._data_store = {} self._check_type = _check_type self._spec_property_naming = _spec_property_naming self._path_to_item = _path_to_item self._configuration = _configuration self._visited_composed_classes = _visited_composed_classes + (self.__class__,) for var_name, var_value in kwargs.items(): if var_name not in self.attribute_map and \ self._configuration is not None and \ self._configuration.discard_unknown_keys and \ self.additional_properties_type is None: # discard variable. continue setattr(self, var_name, var_value) if var_name in self.read_only_vars: raise ApiAttributeError(f"`{var_name}` is a read-only attribute. Use `from_openapi_data` to instantiate " f"class with read only attributes.")

793f90dccd966192aaadf4aedaaabc8ac8097a25

py

Python

test/functional/p2p_node_network_limited.py

KiPa-SuJi/PaydayCoin-Core

d807d95550d955bfa9ffda2b39cad745422224e5

2020-06-12T10:12:49.000Z

2020-07-31T19:43:09.000Z

test/functional/p2p_node_network_limited.py

KiPa-SuJi/PaydayCoin-Core

d807d95550d955bfa9ffda2b39cad745422224e5

test/functional/p2p_node_network_limited.py

KiPa-SuJi/PaydayCoin-Core

d807d95550d955bfa9ffda2b39cad745422224e5

2020-12-04T13:34:46.000Z

2020-12-04T13:34:46.000Z

#!/usr/bin/env python3 # Copyright (c) 2017-2019 The PaydayCoin Core developers # Distributed under the MIT software license, see the accompanying # file COPYING or http://www.opensource.org/licenses/mit-license.php. """Tests NODE_NETWORK_LIMITED. Tests that a node configured with -prune=550 signals NODE_NETWORK_LIMITED correctly and that it responds to getdata requests for blocks correctly: - send a block within 288 + 2 of the tip - disconnect peers who request blocks older than that.""" from test_framework.messages import CInv, msg_getdata, msg_verack, NODE_BLOOM, NODE_NETWORK_LIMITED, NODE_WITNESS from test_framework.mininode import P2PInterface, mininode_lock from test_framework.test_framework import PaydayCoinTestFramework from test_framework.util import ( assert_equal, disconnect_nodes, connect_nodes_bi, wait_until, ) class P2PIgnoreInv(P2PInterface): firstAddrnServices = 0 def on_inv(self, message): # The node will send us invs for other blocks. Ignore them. pass def on_addr(self, message): self.firstAddrnServices = message.addrs[0].nServices def wait_for_addr(self, timeout=5): test_function = lambda: self.last_message.get("addr") wait_until(test_function, timeout=timeout, lock=mininode_lock) def send_getdata_for_block(self, blockhash): getdata_request = msg_getdata() getdata_request.inv.append(CInv(2, int(blockhash, 16))) self.send_message(getdata_request) class NodeNetworkLimitedTest(PaydayCoinTestFramework): def set_test_params(self): self.setup_clean_chain = True self.num_nodes = 3 self.extra_args = [['-prune=550', '-addrmantest'], [], []] def disconnect_all(self): disconnect_nodes(self.nodes[0], 1) disconnect_nodes(self.nodes[1], 0) disconnect_nodes(self.nodes[2], 1) disconnect_nodes(self.nodes[2], 0) disconnect_nodes(self.nodes[0], 2) disconnect_nodes(self.nodes[1], 2) def setup_network(self): self.add_nodes(self.num_nodes, self.extra_args) self.start_nodes() def run_test(self): node = self.nodes[0].add_p2p_connection(P2PIgnoreInv()) expected_services = NODE_BLOOM | NODE_WITNESS | NODE_NETWORK_LIMITED self.log.info("Check that node has signalled expected services.") assert_equal(node.nServices, expected_services) self.log.info("Check that the localservices is as expected.") assert_equal(int(self.nodes[0].getnetworkinfo()['localservices'], 16), expected_services) self.log.info("Mine enough blocks to reach the NODE_NETWORK_LIMITED range.") connect_nodes_bi(self.nodes, 0, 1) blocks = self.nodes[1].generatetoaddress(292, self.nodes[1].get_deterministic_priv_key().address) self.sync_blocks([self.nodes[0], self.nodes[1]]) self.log.info("Make sure we can max retrieve block at tip-288.") node.send_getdata_for_block(blocks[1]) # last block in valid range node.wait_for_block(int(blocks[1], 16), timeout=3) self.log.info("Requesting block at height 2 (tip-289) must fail (ignored).") node.send_getdata_for_block(blocks[0]) # first block outside of the 288+2 limit node.wait_for_disconnect(5) self.log.info("Check local address relay, do a fresh connection.") self.nodes[0].disconnect_p2ps() node1 = self.nodes[0].add_p2p_connection(P2PIgnoreInv()) node1.send_message(msg_verack()) node1.wait_for_addr() #must relay address with NODE_NETWORK_LIMITED assert_equal(node1.firstAddrnServices, 1036) self.nodes[0].disconnect_p2ps() node1.wait_for_disconnect() # connect unsynced node 2 with pruned NODE_NETWORK_LIMITED peer # because node 2 is in IBD and node 0 is a NODE_NETWORK_LIMITED peer, sync must not be possible connect_nodes_bi(self.nodes, 0, 2) try: self.sync_blocks([self.nodes[0], self.nodes[2]], timeout=5) except: pass # node2 must remain at height 0 assert_equal(self.nodes[2].getblockheader(self.nodes[2].getbestblockhash())['height'], 0) # now connect also to node 1 (non pruned) connect_nodes_bi(self.nodes, 1, 2) # sync must be possible self.sync_blocks() # disconnect all peers self.disconnect_all() # mine 10 blocks on node 0 (pruned node) self.nodes[0].generatetoaddress(10, self.nodes[0].get_deterministic_priv_key().address) # connect node1 (non pruned) with node0 (pruned) and check if the can sync connect_nodes_bi(self.nodes, 0, 1) # sync must be possible, node 1 is no longer in IBD and should therefore connect to node 0 (NODE_NETWORK_LIMITED) self.sync_blocks([self.nodes[0], self.nodes[1]]) if __name__ == '__main__': NodeNetworkLimitedTest().main()

793f911c9e5bdd7d6fcd8d614d9c8555f09cb406

py

Python

python/ray/serve/config.py

mgelbart/ray

4cec2286572e368a4bd64aae467751a384eff62d

2018-05-08T05:52:34.000Z

2020-04-01T10:09:55.000Z

python/ray/serve/config.py

mgelbart/ray

4cec2286572e368a4bd64aae467751a384eff62d

2018-05-17T05:55:28.000Z

2020-03-18T06:49:49.000Z

python/ray/serve/config.py

mgelbart/ray

4cec2286572e368a4bd64aae467751a384eff62d

2018-04-27T10:50:59.000Z

2020-02-24T02:41:43.000Z

import inspect import json from enum import Enum from typing import Any, Callable, Dict, List, Optional, Tuple, Union import pydantic from google.protobuf.json_format import MessageToDict from pydantic import ( BaseModel, NonNegativeFloat, PositiveFloat, NonNegativeInt, PositiveInt, validator, ) from ray import cloudpickle from ray.serve.constants import ( DEFAULT_GRACEFUL_SHUTDOWN_TIMEOUT_S, DEFAULT_GRACEFUL_SHUTDOWN_WAIT_LOOP_S, DEFAULT_HEALTH_CHECK_PERIOD_S, DEFAULT_HEALTH_CHECK_TIMEOUT_S, DEFAULT_HTTP_HOST, DEFAULT_HTTP_PORT, ) from ray.serve.generated.serve_pb2 import ( DeploymentConfig as DeploymentConfigProto, DeploymentLanguage, AutoscalingConfig as AutoscalingConfigProto, ReplicaConfig as ReplicaConfigProto, ) from ray.serve.utils import ServeEncoder class AutoscalingConfig(BaseModel): # Please keep these options in sync with those in # `src/ray/protobuf/serve.proto`. # Publicly exposed options min_replicas: NonNegativeInt = 1 max_replicas: PositiveInt = 1 target_num_ongoing_requests_per_replica: NonNegativeInt = 1 # Private options below. # Metrics scraping options # How often to scrape for metrics metrics_interval_s: PositiveFloat = 10.0 # Time window to average over for metrics. look_back_period_s: PositiveFloat = 30.0 # Internal autoscaling configuration options # Multiplicative "gain" factor to limit scaling decisions smoothing_factor: PositiveFloat = 1.0 # How frequently to make autoscaling decisions # loop_period_s: float = CONTROL_LOOP_PERIOD_S # How long to wait before scaling down replicas downscale_delay_s: NonNegativeFloat = 600.0 # How long to wait before scaling up replicas upscale_delay_s: NonNegativeFloat = 30.0 @validator("max_replicas") def max_replicas_greater_than_or_equal_to_min_replicas(cls, v, values): if "min_replicas" in values and v < values["min_replicas"]: raise ValueError( f"""max_replicas ({v}) must be greater than """ f"""or equal to min_replicas """ f"""({values["min_replicas"]})!""" ) return v # TODO(architkulkarni): implement below # The number of replicas to start with when creating the deployment # initial_replicas: int = 1 # The num_ongoing_requests_per_replica error ratio (desired / current) # threshold for overriding `upscale_delay_s` # panic_mode_threshold: float = 2.0 # TODO(architkulkarni): Add reasonable defaults class DeploymentConfig(BaseModel): """Configuration options for a deployment, to be set by the user. Args: num_replicas (Optional[int]): The number of processes to start up that will handle requests to this deployment. Defaults to 1. max_concurrent_queries (Optional[int]): The maximum number of queries that will be sent to a replica of this deployment without receiving a response. Defaults to 100. user_config (Optional[Any]): Arguments to pass to the reconfigure method of the deployment. The reconfigure method is called if user_config is not None. graceful_shutdown_wait_loop_s (Optional[float]): Duration that deployment replicas will wait until there is no more work to be done before shutting down. graceful_shutdown_timeout_s (Optional[float]): Controller waits for this duration to forcefully kill the replica for shutdown. health_check_period_s (Optional[float]): Frequency at which the controller will health check replicas. health_check_timeout_s (Optional[float]): Timeout that the controller will wait for a response from the replica's health check before marking it unhealthy. """ num_replicas: PositiveInt = 1 max_concurrent_queries: Optional[int] = None user_config: Any = None graceful_shutdown_timeout_s: NonNegativeFloat = ( DEFAULT_GRACEFUL_SHUTDOWN_TIMEOUT_S # noqa: E501 ) graceful_shutdown_wait_loop_s: NonNegativeFloat = ( DEFAULT_GRACEFUL_SHUTDOWN_WAIT_LOOP_S # noqa: E501 ) health_check_period_s: PositiveFloat = DEFAULT_HEALTH_CHECK_PERIOD_S health_check_timeout_s: PositiveFloat = DEFAULT_HEALTH_CHECK_TIMEOUT_S autoscaling_config: Optional[AutoscalingConfig] = None # This flag is used to let replica know they are deplyed from # a different language. is_cross_language: bool = False # This flag is used to let controller know which language does # the deploymnent use. deployment_language: Any = DeploymentLanguage.PYTHON version: Optional[str] = None prev_version: Optional[str] = None class Config: validate_assignment = True extra = "forbid" arbitrary_types_allowed = True # Dynamic default for max_concurrent_queries @validator("max_concurrent_queries", always=True) def set_max_queries_by_mode(cls, v, values): # noqa 805 if v is None: v = 100 else: if v <= 0: raise ValueError("max_concurrent_queries must be >= 0") return v def to_proto(self): data = self.dict() if data.get("user_config"): data["user_config"] = cloudpickle.dumps(data["user_config"]) if data.get("autoscaling_config"): data["autoscaling_config"] = AutoscalingConfigProto( **data["autoscaling_config"] ) return DeploymentConfigProto(**data) def to_proto_bytes(self): return self.to_proto().SerializeToString() @classmethod def from_proto(cls, proto: DeploymentConfigProto): data = MessageToDict( proto, including_default_value_fields=True, preserving_proto_field_name=True, use_integers_for_enums=True, ) if "user_config" in data: if data["user_config"] != "": data["user_config"] = cloudpickle.loads(proto.user_config) else: data["user_config"] = None if "autoscaling_config" in data: data["autoscaling_config"] = AutoscalingConfig(**data["autoscaling_config"]) if "prev_version" in data: if data["prev_version"] == "": data["prev_version"] = None if "version" in data: if data["version"] == "": data["version"] = None return cls(**data) @classmethod def from_proto_bytes(cls, proto_bytes: bytes): proto = DeploymentConfigProto.FromString(proto_bytes) return cls.from_proto(proto) @classmethod def from_default(cls, ignore_none: bool = False, **kwargs): """Creates a default DeploymentConfig and overrides it with kwargs. Only accepts the same keywords as the class. Passing in any other keyword raises a ValueError. Args: ignore_none (bool): When True, any valid keywords with value None are ignored, and their values stay default. Invalid keywords still raise a TypeError. Raises: TypeError: when a keyword that's not an argument to the class is passed in. """ config = cls() valid_config_options = set(config.dict().keys()) # Friendly error if a non-DeploymentConfig kwarg was passed in for key, val in kwargs.items(): if key not in valid_config_options: raise TypeError( f'Got invalid Deployment config option "{key}" ' f"(with value {val}) as keyword argument. All Deployment " "config options must come from this list: " f"{list(valid_config_options)}." ) if ignore_none: kwargs = {key: val for key, val in kwargs.items() if val is not None} for key, val in kwargs.items(): config.__setattr__(key, val) return config class ReplicaConfig: def __init__( self, deployment_def: Union[Callable, str], init_args: Optional[Tuple[Any]] = None, init_kwargs: Optional[Dict[Any, Any]] = None, ray_actor_options=None, ): # Validate that deployment_def is an import path, function, or class. self.import_path = None if isinstance(deployment_def, str): self.func_or_class_name = deployment_def self.import_path = deployment_def elif inspect.isfunction(deployment_def): self.func_or_class_name = deployment_def.__name__ if init_args: raise ValueError("init_args not supported for function deployments.") if init_kwargs: raise ValueError("init_kwargs not supported for function deployments.") elif inspect.isclass(deployment_def): self.func_or_class_name = deployment_def.__name__ else: raise TypeError( "Deployment must be a function or class, it is {}.".format( type(deployment_def) ) ) self.serialized_deployment_def = cloudpickle.dumps(deployment_def) self.init_args = init_args if init_args is not None else () self.init_kwargs = init_kwargs if init_kwargs is not None else {} if ray_actor_options is None: self.ray_actor_options = {} else: self.ray_actor_options = ray_actor_options self.resource_dict = {} self._validate() def _validate(self): if not isinstance(self.ray_actor_options, dict): raise TypeError("ray_actor_options must be a dictionary.") disallowed_ray_actor_options = { "args", "kwargs", "max_concurrency", "max_restarts", "max_task_retries", "name", "namespace", "lifetime", "placement_group", "placement_group_bundle_index", "placement_group_capture_child_tasks", "max_pending_calls", "scheduling_strategy", } for option in disallowed_ray_actor_options: if option in self.ray_actor_options: raise ValueError( f"Specifying {option} in ray_actor_options is not allowed." ) # TODO(suquark): reuse options validation of remote function/actor. # Ray defaults to zero CPUs for placement, we default to one here. if self.ray_actor_options.get("num_cpus") is None: self.ray_actor_options["num_cpus"] = 1 num_cpus = self.ray_actor_options["num_cpus"] if not isinstance(num_cpus, (int, float)): raise TypeError("num_cpus in ray_actor_options must be an int or a float.") elif num_cpus < 0: raise ValueError("num_cpus in ray_actor_options must be >= 0.") self.resource_dict["CPU"] = num_cpus if self.ray_actor_options.get("num_gpus") is None: self.ray_actor_options["num_gpus"] = 0 num_gpus = self.ray_actor_options["num_gpus"] if not isinstance(num_gpus, (int, float)): raise TypeError("num_gpus in ray_actor_options must be an int or a float.") elif num_gpus < 0: raise ValueError("num_gpus in ray_actor_options must be >= 0.") self.resource_dict["GPU"] = num_gpus # Serve deployments use Ray's default for actor memory. self.ray_actor_options.setdefault("memory", None) memory = self.ray_actor_options["memory"] if memory is not None and not isinstance(memory, (int, float)): raise TypeError( "memory in ray_actor_options must be an int, a float, or None." ) elif memory is not None and memory <= 0: raise ValueError("memory in ray_actor_options must be > 0.") self.resource_dict["memory"] = memory object_store_memory = self.ray_actor_options.get("object_store_memory") if not isinstance(object_store_memory, (int, float, type(None))): raise TypeError( "object_store_memory in ray_actor_options must be an int, float " "or None." ) elif object_store_memory is not None and object_store_memory < 0: raise ValueError("object_store_memory in ray_actor_options must be >= 0.") self.resource_dict["object_store_memory"] = object_store_memory if self.ray_actor_options.get("resources") is None: self.ray_actor_options["resources"] = {} custom_resources = self.ray_actor_options["resources"] if not isinstance(custom_resources, dict): raise TypeError("resources in ray_actor_options must be a dictionary.") self.resource_dict.update(custom_resources) @classmethod def from_proto( cls, proto: ReplicaConfigProto, deployment_language: DeploymentLanguage ): deployment_def = None if proto.serialized_deployment_def != b"": if deployment_language == DeploymentLanguage.PYTHON: deployment_def = cloudpickle.loads(proto.serialized_deployment_def) else: # TODO use messagepack deployment_def = cloudpickle.loads(proto.serialized_deployment_def) init_args = ( cloudpickle.loads(proto.init_args) if proto.init_args != b"" else None ) init_kwargs = ( cloudpickle.loads(proto.init_kwargs) if proto.init_kwargs != b"" else None ) ray_actor_options = ( json.loads(proto.ray_actor_options) if proto.ray_actor_options != "" else None ) return ReplicaConfig(deployment_def, init_args, init_kwargs, ray_actor_options) @classmethod def from_proto_bytes( cls, proto_bytes: bytes, deployment_language: DeploymentLanguage ): proto = ReplicaConfigProto.FromString(proto_bytes) return cls.from_proto(proto, deployment_language) def to_proto(self): data = { "serialized_deployment_def": self.serialized_deployment_def, } if self.init_args: data["init_args"] = cloudpickle.dumps(self.init_args) if self.init_kwargs: data["init_kwargs"] = cloudpickle.dumps(self.init_kwargs) if self.ray_actor_options: data["ray_actor_options"] = json.dumps( self.ray_actor_options, cls=ServeEncoder ) return ReplicaConfigProto(**data) def to_proto_bytes(self): return self.to_proto().SerializeToString() class DeploymentMode(str, Enum): NoServer = "NoServer" HeadOnly = "HeadOnly" EveryNode = "EveryNode" FixedNumber = "FixedNumber" class HTTPOptions(pydantic.BaseModel): # Documentation inside serve.start for user's convenience. host: Optional[str] = DEFAULT_HTTP_HOST port: int = DEFAULT_HTTP_PORT middlewares: List[Any] = [] location: Optional[DeploymentMode] = DeploymentMode.HeadOnly num_cpus: int = 0 root_url: str = "" root_path: str = "" fixed_number_replicas: Optional[int] = None fixed_number_selection_seed: int = 0 @validator("location", always=True) def location_backfill_no_server(cls, v, values): if values["host"] is None or v is None: return DeploymentMode.NoServer return v @validator("fixed_number_replicas", always=True) def fixed_number_replicas_should_exist(cls, v, values): if values["location"] == DeploymentMode.FixedNumber and v is None: raise ValueError( "When location='FixedNumber', you must specify " "the `fixed_number_replicas` parameter." ) return v class Config: validate_assignment = True extra = "forbid" arbitrary_types_allowed = True

793f925198a3ccb544a87e0e170e3eaeeadee3cd

py

Python

examples/basic_shapes.py

abey79/lines

09fbd84f9eaaba40d24b07227e8c95c0493a75c2

2019-10-23T09:19:34.000Z

2022-02-16T21:44:12.000Z

examples/basic_shapes.py

abey79/lines

09fbd84f9eaaba40d24b07227e8c95c0493a75c2

2020-11-13T14:06:02.000Z

2021-09-29T08:18:44.000Z

examples/basic_shapes.py

abey79/lines

09fbd84f9eaaba40d24b07227e8c95c0493a75c2

2020-11-06T22:21:00.000Z

2021-06-09T18:40:02.000Z

from lines import Cube, Cylinder, Pyramid, Scene def main(): # Setup the scene scene = Scene() scene.add(Cube(translate=(2, 0, 0))) scene.add(Pyramid()) scene.add(Cylinder(scale=(0.5, 0.5, 1), translate=(-2, 0, 0))) scene.look_at((2, 6, 1.5), (0, 0, 0)) scene.perspective(70, 0.1, 10) # Render and display the scene scene.render().show(show_hidden=True) if __name__ == "__main__": main()

793f92e4ae60427a625e83cd3f9b430b5f63dcc7

py

Python

cea/plots/solar_technology_potentials/2_photovoltaic_thermal_potential.py

AlexJew/CityEnergyAnalyst

6eb372c79e5100a2d0abce78561ae368fb409cd1

cea/plots/solar_technology_potentials/2_photovoltaic_thermal_potential.py

AlexJew/CityEnergyAnalyst

6eb372c79e5100a2d0abce78561ae368fb409cd1

cea/plots/solar_technology_potentials/2_photovoltaic_thermal_potential.py

AlexJew/CityEnergyAnalyst

6eb372c79e5100a2d0abce78561ae368fb409cd1

from __future__ import division from __future__ import print_function import math import pandas as pd import plotly.graph_objs as go from plotly.offline import plot import cea.plots.solar_technology_potentials from cea.plots.variable_naming import LOGO, COLOR, NAMING __author__ = "Shanshan Hsieh" __copyright__ = "Copyright 2018, Architecture and Building Systems - ETH Zurich" __credits__ = ["Shanshan Hsieh"] __license__ = "MIT" __version__ = "0.1" __maintainer__ = "Daren Thomas" __email__ = "cea@arch.ethz.ch" __status__ = "Production" class PvtMonthlyPlot(cea.plots.solar_technology_potentials.SolarTechnologyPotentialsPlotBase): """Implement the pv-electricity-potential plot""" name = "PVT Electricity/Thermal Potential" def __init__(self, project, parameters, cache): super(PvtMonthlyPlot, self).__init__(project, parameters, cache) self.input_files = [(self.locator.PVT_totals, [])] + [(self.locator.PVT_results, [building]) for building in self.buildings] self.__data_frame = None self.__E_analysis_fields_used = None self.__Q_analysis_fields_used = None @property def data_frame(self): """This get's used a couple of times in the calculations, avoid hitting the PlotCache each time""" if self.__data_frame is None: self.__data_frame = self.PVT_hourly_aggregated_kW return self.__data_frame @property def E_analysis_fields_used(self): if self.__E_analysis_fields_used is None: self.__E_analysis_fields_used = self.data_frame.columns[ self.data_frame.columns.str.endswith('_E_kWh')].tolist() return self.__E_analysis_fields_used @property def Q_analysis_fields_used(self): if self.__Q_analysis_fields_used is None: self.__Q_analysis_fields_used = self.data_frame.columns[ self.data_frame.columns.str.endswith('_Q_kWh')].tolist() return self.__Q_analysis_fields_used @property def layout(self): analysis_range = calc_range(self.data_frame, self.E_analysis_fields_used, self.Q_analysis_fields_used) return go.Layout(barmode='stack', yaxis=dict(title='PVT Electricity/Heat production [MWh]', rangemode='tozero', scaleanchor='y2', range=analysis_range), yaxis2=dict(overlaying='y', anchor='x', range=analysis_range)) def calc_graph(self): # calculate graph graph = [] data_frame = self.data_frame monthly_df = (data_frame.set_index("DATE").resample("M").sum() / 1000).round(2) # to MW monthly_df["month"] = monthly_df.index.strftime("%B") E_total = monthly_df[self.E_analysis_fields_used].sum(axis=1) Q_total = monthly_df[self.Q_analysis_fields_used].sum(axis=1) for field in self.Q_analysis_fields_used: y = monthly_df[field] total_perc = (y.divide(Q_total) * 100).round(2).values total_perc_txt = ["(" + str(x) + " %)" for x in total_perc] trace1 = go.Bar(x=monthly_df["month"], y=y, yaxis='y2', name=field.split('_kWh', 1)[0], text=total_perc_txt, marker=dict(color=COLOR[field], line=dict(color="rgb(105,105,105)", width=1)), opacity=1, width=0.3, offset=0, legendgroup=field.split('_Q_kWh', 1)[0]) graph.append(trace1) for field in self.E_analysis_fields_used: y = monthly_df[field] total_perc = (y / E_total * 100).round(2).values total_perc_txt = ["(" + str(x) + " %)" for x in total_perc] trace2 = go.Bar(x=monthly_df["month"], y=y, name=field.split('_kWh', 1)[0], text=total_perc_txt, marker=dict(color=COLOR[field]), width=0.3, offset=-0.35, legendgroup=field.split('_E_kWh', 1)[0]) graph.append(trace2) return graph def calc_table(self): analysis_fields_used = [] total_perc = [] data_frame = self.data_frame E_analysis_fields_used = self.E_analysis_fields_used Q_analysis_fields_used = self.Q_analysis_fields_used # calculation for electricity production E_total = (data_frame[E_analysis_fields_used].sum(axis=0) / 1000).round(2).tolist() # to MW # calculate top three potentials E_anchors = [] E_names = [] monthly_df = (data_frame.set_index("DATE").resample("M").sum() / 1000).round(2) # to MW monthly_df["month"] = monthly_df.index.strftime("%B") monthly_df.set_index("month", inplace=True) if sum(E_total) > 0: E_total_perc = [str(x) + " (" + str(round(x / sum(E_total) * 100, 1)) + " %)" for x in E_total] for field in E_analysis_fields_used: E_anchors.append(', '.join(calc_top_three_anchor_loads(monthly_df, field))) E_names.append(NAMING[field].split(' ')[6] + ' (' + field.split('_kWh', 1)[0] + ')') else: E_total_perc = ['0 (0%)'] * len(E_total) for field in E_analysis_fields_used: E_anchors.append('-') E_names.append(NAMING[field].split(' ')[6] + ' (' + field.split('_kWh', 1)[0] + ')') analysis_fields_used.extend(E_analysis_fields_used) total_perc.extend(E_total_perc) # calculation for heat production Q_total = (data_frame[Q_analysis_fields_used].sum(axis=0) / 1000).round(2).tolist() # to MW Q_names = [] Q_anchors = [] if sum(Q_total) > 0: Q_total_perc = [str(x) + " (" + str(round(x / sum(Q_total) * 100, 1)) + " %)" for x in Q_total] for field in Q_analysis_fields_used: Q_anchors.append(', '.join(calc_top_three_anchor_loads(monthly_df, field))) Q_names.append(NAMING[field].split(' ')[6] + ' (' + field.split('_kWh', 1)[0] + ')') else: Q_total_perc = ['0 (0%)'] * len(Q_total) for field in Q_analysis_fields_used: Q_anchors.append('-') Q_names.append(NAMING[field].split(' ')[6] + ' (' + field.split('_kWh', 1)[0] + ')') analysis_fields_used.extend(Q_analysis_fields_used) total_perc.extend(Q_total_perc) column_names = ['Surfaces', 'Total electricity production [MWh/yr]', 'Months with the highest potentials', 'Surfaces ', 'Total heat production [MWh/yr]', 'Months with the highest potentials'] column_values = [E_names, E_total_perc, E_anchors, Q_names, Q_total_perc, Q_anchors] table_df = pd.DataFrame({cn: cv for cn, cv in zip(column_names, column_values)}, columns=column_names) return table_df def pvt_district_monthly(data_frame, analysis_fields, title, output_path): E_analysis_fields_used = data_frame.columns[data_frame.columns.isin(analysis_fields[0:5])].tolist() Q_analysis_fields_used = data_frame.columns[data_frame.columns.isin(analysis_fields[5:10])].tolist() range = calc_range(data_frame, E_analysis_fields_used, Q_analysis_fields_used) # CALCULATE GRAPH traces_graphs = calc_graph(E_analysis_fields_used, Q_analysis_fields_used, data_frame) # CALCULATE TABLE traces_table = calc_table(E_analysis_fields_used, Q_analysis_fields_used, data_frame) # PLOT GRAPH traces_graphs.append(traces_table) layout = go.Layout(images=LOGO, title=title, barmode='stack', yaxis=dict(title='PVT Electricity/Heat production [MWh]', domain=[0.35, 1], rangemode='tozero', scaleanchor='y2', range=range), yaxis2=dict(overlaying='y', anchor='x', domain=[0.35, 1], range=range)) fig = go.Figure(data=traces_graphs, layout=layout) plot(fig, auto_open=False, filename=output_path) return {'data': traces_graphs, 'layout': layout} def calc_range(data_frame, E_analysis_fields_used, Q_analysis_fields_used): monthly_df = (data_frame.set_index("DATE").resample("M").sum() / 1000).round(2) # to MW monthly_df["month"] = monthly_df.index.strftime("%B") E_total = monthly_df[E_analysis_fields_used].sum(axis=1) Q_total = monthly_df[Q_analysis_fields_used].sum(axis=1) y_axis_max = math.ceil(max(E_total.max(), Q_total.max())) y_asix_min = min(0, min(Q_total.min(), E_total.min())) return [y_asix_min, y_axis_max] def calc_graph(E_analysis_fields_used, Q_analysis_fields_used, data_frame): # calculate graph graph = [] monthly_df = (data_frame.set_index("DATE").resample("M").sum() / 1000).round(2) # to MW monthly_df["month"] = monthly_df.index.strftime("%B") E_total = monthly_df[E_analysis_fields_used].sum(axis=1) Q_total = monthly_df[Q_analysis_fields_used].sum(axis=1) for field in Q_analysis_fields_used: y = monthly_df[field] total_perc = (y.divide(Q_total) * 100).round(2).values total_perc_txt = ["(" + str(x) + " %)" for x in total_perc] trace1 = go.Bar(x=monthly_df["month"], y=y, yaxis='y2', name=field.split('_kWh', 1)[0], text=total_perc_txt, marker=dict(color=COLOR[field], line=dict(color="rgb(105,105,105)", width=1)), opacity=1, width=0.3, offset=0, legendgroup=field.split('_Q_kWh', 1)[0]) graph.append(trace1) for field in E_analysis_fields_used: y = monthly_df[field] total_perc = (y / E_total * 100).round(2).values total_perc_txt = ["(" + str(x) + " %)" for x in total_perc] trace2 = go.Bar(x=monthly_df["month"], y=y, name=field.split('_kWh', 1)[0], text=total_perc_txt, marker=dict(color=COLOR[field]), width=0.3, offset=-0.35, legendgroup=field.split('_E_kWh', 1)[0]) graph.append(trace2) return graph def calc_table(E_analysis_fields_used, Q_analysis_fields_used, data_frame): analysis_fields_used = [] total_perc = [] # calculation for electricity production E_total = (data_frame[E_analysis_fields_used].sum(axis=0) / 1000).round(2).tolist() # to MW # calculate top three potentials E_anchors = [] E_names = [] monthly_df = (data_frame.set_index("DATE").resample("M").sum() / 1000).round(2) # to MW monthly_df["month"] = monthly_df.index.strftime("%B") monthly_df.set_index("month", inplace=True) if sum(E_total) > 0: E_total_perc = [str(x) + " (" + str(round(x / sum(E_total) * 100, 1)) + " %)" for x in E_total] for field in E_analysis_fields_used: E_anchors.append(calc_top_three_anchor_loads(monthly_df, field)) E_names.append(NAMING[field].split(' ')[6] + ' (' + field.split('_kWh', 1)[0] + ')') else: E_total_perc = ['0 (0%)'] * len(E_total) for field in E_analysis_fields_used: E_anchors.append('-') E_names.append(NAMING[field].split(' ')[6] + ' (' + field.split('_kWh', 1)[0] + ')') analysis_fields_used.extend(E_analysis_fields_used) total_perc.extend(E_total_perc) # calculation for heat production Q_total = (data_frame[Q_analysis_fields_used].sum(axis=0) / 1000).round(2).tolist() # to MW Q_names = [] Q_anchors = [] if sum(Q_total) > 0: Q_total_perc = [str(x) + " (" + str(round(x / sum(Q_total) * 100, 1)) + " %)" for x in Q_total] for field in Q_analysis_fields_used: Q_anchors.append(calc_top_three_anchor_loads(monthly_df, field)) Q_names.append(NAMING[field].split(' ')[6] + ' (' + field.split('_kWh', 1)[0] + ')') else: Q_total_perc = ['0 (0%)'] * len(Q_total) for field in Q_analysis_fields_used: Q_anchors.append('-') Q_names.append(NAMING[field].split(' ')[6] + ' (' + field.split('_kWh', 1)[0] + ')') analysis_fields_used.extend(Q_analysis_fields_used) total_perc.extend(Q_total_perc) table = go.Table(domain=dict(x=[0, 1], y=[0.0, 0.2]), header=dict(values=['Surfaces', 'Total electricity production [MWh/yr]', 'Months with the highest potentials', 'Surfaces', 'Total heat production [MWh/yr]', 'Months with the highest potentials']), cells=dict(values=[E_names, E_total_perc, E_anchors, Q_names, Q_total_perc, Q_anchors])) return table def calc_top_three_anchor_loads(data_frame, field): data_frame = data_frame.sort_values(by=field, ascending=False) anchor_list = data_frame[:3].index.values return anchor_list def main(): """Test this plot""" import cea.config import cea.inputlocator import cea.plots.cache config = cea.config.Configuration() locator = cea.inputlocator.InputLocator(config.scenario) cache = cea.plots.cache.PlotCache(config.project) # cache = cea.plots.cache.NullPlotCache() weather_path = locator.get_weather_file() PvtMonthlyPlot(config.project, {'buildings': None, 'scenario-name': config.scenario_name, 'weather': weather_path}, cache).plot(auto_open=True) PvtMonthlyPlot(config.project, {'buildings': locator.get_zone_building_names()[0:2], 'scenario-name': config.scenario_name, 'weather': weather_path}, cache).plot(auto_open=True) PvtMonthlyPlot(config.project, {'buildings': [locator.get_zone_building_names()[0]], 'scenario-name': config.scenario_name, 'weather': weather_path}, cache).plot(auto_open=True) if __name__ == '__main__': main()

793f93bb640dea8d0bfa33dbd16683dab3070d89

py

Python

examples/nD_multiscale_image.py

mrocklin/napari

b61d9ae570e30091a97b6c76e37cd95fe5b296b6

2022-03-01T19:38:06.000Z

2022-03-01T19:38:06.000Z

examples/nD_multiscale_image.py

mrocklin/napari

b61d9ae570e30091a97b6c76e37cd95fe5b296b6

2020-06-11T21:02:03.000Z

2021-02-02T19:10:19.000Z

examples/nD_multiscale_image.py

mrocklin/napari

b61d9ae570e30091a97b6c76e37cd95fe5b296b6

2020-07-19T18:03:35.000Z

2020-07-19T18:03:35.000Z

""" Displays an nD multiscale image """ from skimage.transform import pyramid_gaussian import napari import numpy as np # create multiscale from random data base = np.random.random((1536, 1536)) base = np.array([base * (8 - i) / 8 for i in range(8)]) print('base shape', base.shape) multiscale = list( pyramid_gaussian(base, downscale=2, max_layer=2, multichannel=False) ) print('multiscale level shapes: ', [p.shape for p in multiscale]) with napari.gui_qt(): # add image multiscale napari.view_image(multiscale, contrast_limits=[0, 1], multiscale=True)

793f978012241efbd22ad38a243fb9578449b9c2

py

Python

tests/test_loadtweets.py

rmotr-group-projects/wdd-w2-twitter-commands

404ddb6e9121eab562c113610b3b54f296e6c47e

tests/test_loadtweets.py

rmotr-group-projects/wdd-w2-twitter-commands

404ddb6e9121eab562c113610b3b54f296e6c47e

2020-06-05T22:15:17.000Z

2022-03-11T23:56:03.000Z

tests/test_loadtweets.py

ine-rmotr-projects/wdd-w2-twitter-commands

404ddb6e9121eab562c113610b3b54f296e6c47e

2016-09-03T12:58:21.000Z

2016-11-15T16:52:57.000Z

from django.utils.six import StringIO from django.core.management import call_command from django.test import TestCase from django.core.management.base import CommandError from twitter.models import Tweet, User class LoadTweetsTestCase(TestCase): def setUp(self): super(LoadTweetsTestCase, self).setUp() self.user = User.objects.create_user( username='rmotr_com', password='password123') self.out = StringIO() def test_load_tweets_command(self): """Should import tweets from twitter API when given username is valid""" self.assertEqual(Tweet.objects.count(), 0) args = [self.user.username] call_command('loadtweets', stdout=self.out, *args) self.assertEqual(Tweet.objects.count(), 10) self.assertTrue( 'Finished. 10 tweets have been imported.' in self.out.getvalue()) for tweet in Tweet.objects.all(): self.assertEqual(tweet.user, self.user) def test_load_tweets_command_count(self): """Should import the amount of tweets specified in the --count argument""" self.assertEqual(Tweet.objects.count(), 0) args = [self.user.username, "--count=20"] call_command('loadtweets', stdout=self.out, *args) self.assertEqual(Tweet.objects.count(), 20) self.assertTrue( 'Finished. 20 tweets have been imported.' in self.out.getvalue()) for tweet in Tweet.objects.all(): self.assertEqual(tweet.user, self.user) def test_load_tweets_command_username_not_found(self): """Should raise CommandError when given username does not exist""" self.assertEqual(Tweet.objects.count(), 0) args = ["INVALID"] with self.assertRaises(CommandError) as e: call_command('loadtweets', stdout=self.out, *args) self.assertEqual(e.exception.args[0], 'User "INVALID" does not exist') self.assertEqual(Tweet.objects.count(), 0) def test_load_tweets_command_invalid_username(self): """Should raise TypeError when given username is not a string""" self.assertEqual(Tweet.objects.count(), 0) args = [123] with self.assertRaises(TypeError) as e: call_command('loadtweets', stdout=self.out, *args) self.assertEqual(e.exception.args[0], "'int' object is not subscriptable") self.assertEqual(Tweet.objects.count(), 0) def test_load_tweets_command_repeated_tweets(self): """Should not load tweets that already exists in the DB""" self.assertEqual(Tweet.objects.count(), 0) args = [self.user.username, "--count=20"] call_command('loadtweets', stdout=self.out, *args) self.assertTrue( 'Finished. 20 tweets have been imported.' in self.out.getvalue()) self.assertEqual(Tweet.objects.count(), 20) for tweet in Tweet.objects.all(): self.assertEqual(tweet.user, self.user) args = [self.user.username, "--count=50"] call_command('loadtweets', stdout=self.out, *args) self.assertTrue( 'Finished. 30 tweets have been imported.' in self.out.getvalue()) self.assertEqual(Tweet.objects.count(), 50)

793f98b9cc535a2591a86d797ad1c0eb05830b70

py

Python

airbyte-integrations/connectors/source-youtube-analytics/unit_tests/test_source.py

OTRI-Unipd/OTRI-airbyte

50eeeb773f75246e86c6e167b0cd7d2dda6efe0d

2022-03-02T13:46:05.000Z

2022-03-05T12:31:28.000Z

airbyte-integrations/connectors/source-youtube-analytics/unit_tests/test_source.py

OTRI-Unipd/OTRI-airbyte

50eeeb773f75246e86c6e167b0cd7d2dda6efe0d

2021-10-07T17:20:29.000Z

2021-12-27T13:07:09.000Z

airbyte-integrations/connectors/source-youtube-analytics/unit_tests/test_source.py

OTRI-Unipd/OTRI-airbyte

50eeeb773f75246e86c6e167b0cd7d2dda6efe0d

2022-03-11T06:21:24.000Z

2022-03-11T06:21:24.000Z

# # Copyright (c) 2021 Airbyte, Inc., all rights reserved. # import json import os from unittest.mock import MagicMock from airbyte_cdk.sources.streams.http.auth.core import NoAuth from source_youtube_analytics.source import SourceYoutubeAnalytics def test_check_connection(requests_mock): access_token = "token" mock_oauth_call = requests_mock.post("https://oauth2.googleapis.com/token", json={"access_token": access_token, "expires_in": 0}) mock_jobs_call = requests_mock.get("https://youtubereporting.googleapis.com/v1/jobs", json={}) source = SourceYoutubeAnalytics() logger_mock, config_mock = MagicMock(), MagicMock() assert source.check_connection(logger_mock, config_mock) == (True, None) assert mock_oauth_call.called_once assert mock_jobs_call.called_once assert mock_jobs_call.last_request.headers["Authorization"] == "Bearer " + access_token def test_streams(requests_mock): requests_mock.get("https://youtubereporting.googleapis.com/v1/jobs", json={}) with open(os.path.join(os.path.dirname(__file__), "../source_youtube_analytics/defaults/channel_reports.json")) as fp: channel_reports = json.load(fp) source = SourceYoutubeAnalytics() source.get_authenticator = MagicMock(return_value=NoAuth()) config_mock = MagicMock() streams = source.streams(config_mock) assert len(streams) == len(channel_reports)

793f9a0b3767df7e83b01b93a4b5add02b4506bc

py

Python

LeetCode/Linked List/21. Merge Two Sorted Lists/solution.py

Ceruleanacg/Crack-Interview

994dc0eee2f576fc543c90b82398dc8d957cdf09

2018-09-04T15:51:30.000Z

2021-06-04T08:47:07.000Z

LeetCode/Linked List/21. Merge Two Sorted Lists/solution.py

Ceruleanacg/Crack-Interview

994dc0eee2f576fc543c90b82398dc8d957cdf09

LeetCode/Linked List/21. Merge Two Sorted Lists/solution.py

Ceruleanacg/Crack-Interview

994dc0eee2f576fc543c90b82398dc8d957cdf09

2018-11-03T09:36:25.000Z

2020-05-27T17:51:08.000Z

# Definition for singly-linked list. class ListNode: def __init__(self, x): self.val = x self.next = None class Solution: def mergeTwoLists(self, l1, l2): """ :type l1: ListNode :type l2: ListNode :rtype: ListNode """ mock_node = ListNode(0) cur_node = mock_node while l1 and l2: if l1.val < l2.val: cur_node.next = l1 l1 = l1.next else: cur_node.next = l2 l2 = l2.next cur_node = cur_node.next cur_node.next = l1 or l2 return mock_node.next

793f9b88526befd86d41e4d2c7c71250f35ef0ad

py

Python

produtos/admin.py

maldonadopereira/djangoice

c577abd3aed4a1ffd7de6ea4c5a5c6f53f9987fc

2022-03-13T16:18:43.000Z

2022-03-13T16:18:46.000Z

produtos/admin.py

maldonadopereira/djangoice

c577abd3aed4a1ffd7de6ea4c5a5c6f53f9987fc

produtos/admin.py

maldonadopereira/djangoice

c577abd3aed4a1ffd7de6ea4c5a5c6f53f9987fc

from django.contrib import admin from .models import Produto, Fornecedor class ListandoProduto(admin.ModelAdmin): list_display = ('id', 'nome_produto', 'preco_produto','fornecedor' ,'disponivel') list_display_links = ('id', 'nome_produto') search_fields = ('nome_receita',) list_filter = ('disponivel',) list_editable = ('disponivel',) list_per_page = 20 class ListandoFornecedor(admin.ModelAdmin): list_display = ('id', 'nome_fornecedor', 'telefone_fornecedor') list_display_links = ('id', 'nome_fornecedor') search_fields = ('nome_fornecedor',) list_per_page = 20 admin.site.register(Produto, ListandoProduto,) admin.site.register(Fornecedor, ListandoFornecedor,)

793f9cf3b5b48c076230b07dd3067141e3eb9bc2

py

Python

test/test_inline_response_200_42_utilisation_totals.py

scubawhere/scubawhere-api-python-client

9f8578e251492c7667f785df7b7c9d66e71f5c8e

test/test_inline_response_200_42_utilisation_totals.py

scubawhere/scubawhere-api-python-client

9f8578e251492c7667f785df7b7c9d66e71f5c8e

test/test_inline_response_200_42_utilisation_totals.py

scubawhere/scubawhere-api-python-client

9f8578e251492c7667f785df7b7c9d66e71f5c8e

# coding: utf-8 """ Scubawhere API Documentation This is the documentation for scubawhere's RMS API. This API is only to be used by authorized parties with valid auth tokens. [Learn about scubawhere](http://www.scubawhere.com) to become an authorized consumer of our API OpenAPI spec version: 1.0.0 Contact: bryan@scubawhere.com Generated by: https://github.com/swagger-api/swagger-codegen.git 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. """ from __future__ import absolute_import import os import sys import unittest import swagger_client from swagger_client.rest import ApiException from swagger_client.models.inline_response_200_42_utilisation_totals import InlineResponse20042UtilisationTotals class TestInlineResponse20042UtilisationTotals(unittest.TestCase): """ InlineResponse20042UtilisationTotals unit test stubs """ def setUp(self): pass def tearDown(self): pass def testInlineResponse20042UtilisationTotals(self): """ Test InlineResponse20042UtilisationTotals """ model = swagger_client.models.inline_response_200_42_utilisation_totals.InlineResponse20042UtilisationTotals() if __name__ == '__main__': unittest.main()

793f9fab0523a6a76b98f3895515cb386dd74da2

py

Python

Java/Ema/TestTools/QATools/Series100Consumer100-View-001/verifyTest.py

TransFICC/Elektron-SDK