xszheng2020/the_stack_dedup_python_hits_4 · Datasets at Hugging Face

3796aeeebdfefccb95189994b9d723808d418a1f

762

py

Python

setup.py

malma28/macord

325d1c14406e66dd2fba82889d9c50ff118ad6c0

[ "MIT" ]

null

setup.py

malma28/macord

325d1c14406e66dd2fba82889d9c50ff118ad6c0

[ "MIT" ]

null

setup.py

malma28/macord

325d1c14406e66dd2fba82889d9c50ff118ad6c0

[ "MIT" ]

null

import setuptools setuptools.setup( name='macord', version='0.0.1', description='a simple discord api for python', url='https://github.com/malma28/macord', author='Malma', author_email='adamakmal789@gmail.com', license='MIT', packages=[ 'macord' ], requires=[ 'aiohttp', 'requests' ], classifiers=[ 'Development Status :: Pre Alpha', 'License :: OSI Approved :: MIT License', 'Operating System :: Unix :: Windows', 'Programming Language :: Python :: 3', 'Programming Language :: Python :: 3.7', 'Programming Language :: Python :: 3.8', 'Programming Language :: Python :: 3.9', 'Programming Language :: Python :: 3.10' ] )

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37bbf0c0a402babdb72c6dbd0e755c674cc93bc3

443

py

Python

.environment/lib/python3.8/site-packages/docplex/mp/ds_utils.py

LuisMi1245/QPath-and-Snakes

48f784da67d9720c955890a28543c9863e02a455

[ "MIT" ]

null

.environment/lib/python3.8/site-packages/docplex/mp/ds_utils.py

LuisMi1245/QPath-and-Snakes

48f784da67d9720c955890a28543c9863e02a455

[ "MIT" ]

1

2019-11-14T09:30:19.000Z

2019-11-22T23:23:27.000Z

docplex/mp/ds_utils.py

ctzhu/docplex

783d2137bedfe8b01553cf31035803085fb8819a

[ "Apache-2.0" ]

null

# -------------------------------------------------------------------------- # Source file provided under Apache License, Version 2.0, January 2004, # http://www.apache.org/licenses/ # (c) Copyright IBM Corp. 2015, 2021 # -------------------------------------------------------------------------- # gendoc: ignore try: import scipy.sparse as sp except ImportError: sp = None def is_scipy_sparse(m): return sp and sp.issparse(m)

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80815eec65ea9da134c0df6575a85cb822bc25df

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py

Python

start.py

Cribstone/home-assistant

328b9a84c0169c8067f2aa8d07392519de8a5e35

[ "MIT" ]

1

2022-01-09T18:02:24.000Z

start.py

jwveldhuis/home-assistant

f07622e0d77ceac236d631245a2486f249812666

[ "MIT" ]

null

start.py

jwveldhuis/home-assistant

f07622e0d77ceac236d631245a2486f249812666

[ "MIT" ]

null

#!/usr/bin/python2 """ Starts home assistant with all possible functionality. """ import homeassistant.bootstrap homeassistant.bootstrap.from_config_file("home-assistant.conf")

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80d3fa63c2a4410e6747ae715946aaa07f86803d

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py

Python

packages/jet_bridge_base/jet_bridge_base/paginators/pagination.py

F2210/jet-bridge

72b1af5cd7df585a4026d65170d3607f8cdf6bea

[ "MIT" ]

1,247

2019-01-10T22:22:08.000Z

2022-03-29T20:54:32.000Z

packages/jet_bridge_base/jet_bridge_base/paginators/pagination.py

F2210/jet-bridge

72b1af5cd7df585a4026d65170d3607f8cdf6bea

[ "MIT" ]

12

2019-03-15T20:06:14.000Z

2022-01-07T10:28:20.000Z

packages/jet_bridge_base/jet_bridge_base/paginators/pagination.py

F2210/jet-bridge

72b1af5cd7df585a4026d65170d3607f8cdf6bea

[ "MIT" ]

130

2019-02-26T17:36:53.000Z

2022-03-17T22:46:27.000Z

class Pagination(object): count = None def paginate_queryset(self, request, queryset, handler): raise NotImplementedError def get_paginated_response(self, request, data): raise NotImplementedError

22.8

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80d8ceb0f3f0864e1ed718fa4a0dcf2a1584c071

134

py

Python

torcs-client/run.py

CinNec/torcs

15c71e3636d4c167d3297d381e7c053d8a18723e

[ "MIT" ]

null

torcs-client/run.py

CinNec/torcs

15c71e3636d4c167d3297d381e7c053d8a18723e

[ "MIT" ]

null

torcs-client/run.py

CinNec/torcs

15c71e3636d4c167d3297d381e7c053d8a18723e

[ "MIT" ]

null

#! /usr/bin/env python3 from pytocl.main import main from my_driver import MyDriver if __name__ == '__main__': main(MyDriver())

16.75

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80e95d23934edf9dcfda048536a22067a2d1c532

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py

Python

src/knarrow/__init__.py

InCogNiTo124/knarrow

b0a19273a27e68899d982bcc0bf0938c60d3ec26

[ "Apache-2.0" ]

2

2021-10-10T11:12:53.000Z

2021-12-14T13:55:30.000Z

src/knarrow/__init__.py

InCogNiTo124/knarrow

b0a19273a27e68899d982bcc0bf0938c60d3ec26

[ "Apache-2.0" ]

17

2021-09-30T21:51:28.000Z

2022-03-27T23:33:17.000Z

src/knarrow/__init__.py

InCogNiTo124/knarrow

b0a19273a27e68899d982bcc0bf0938c60d3ec26

[ "Apache-2.0" ]

null

from .main import find_knee __all__ = ["find_knee"]

13.25

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4.125

0.75

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80ef7ec9cc419c3df64840b1a0c930211b5f3d93

64

py

Python

watchdog_kj_kultura/main/__init__.py

watchdogpolska/watchdog-kj-kultura

ea1a5c52ef2a174c012cc08eff5fdd7aa3b911b0

[ "MIT" ]

null

watchdog_kj_kultura/main/__init__.py

watchdogpolska/watchdog-kj-kultura

ea1a5c52ef2a174c012cc08eff5fdd7aa3b911b0

[ "MIT" ]

138

2016-12-10T19:18:18.000Z

2019-06-10T19:32:40.000Z

watchdog_kj_kultura/main/__init__.py

watchdogpolska/watchdog-kj-kultura

ea1a5c52ef2a174c012cc08eff5fdd7aa3b911b0

[ "MIT" ]

null

default_app_config = 'watchdog_kj_kultura.main.apps.MainConfig'

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80fb052e49ac9c8cd9bbd5621238ef8ea2807b4d

192

py

Python

category/forms.py

Moisestuli/karrata

962ce0c573214bfc83720727c9cacae823a8c372

[ "MIT" ]

null

category/forms.py

Moisestuli/karrata

962ce0c573214bfc83720727c9cacae823a8c372

[ "MIT" ]

null

category/forms.py

Moisestuli/karrata

962ce0c573214bfc83720727c9cacae823a8c372

[ "MIT" ]

null

from django import forms from category.models import Category class CategoriaForm(forms.ModelForm): class Meta: model = Category fields = ('nome','descricao','upload')

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80fc8504b29f6d34a034668feb50331ead6fcc58

414

py

Python

mp_sort/virtenv/lib/python3.6/site-packages/transcrypt/development/automated_tests/transcrypt/div_issues/issue387/__init__.py

ang-jason/fip_powerx_mini_projects-foxtrot

37e3671969b516369e2d1c7cab5890b75c489f56

[ "MIT" ]

2,200

2016-10-12T16:47:13.000Z

2022-03-30T16:40:35.000Z

mp_sort/virtenv/lib/python3.6/site-packages/transcrypt/development/automated_tests/transcrypt/div_issues/issue387/__init__.py

ang-jason/fip_powerx_mini_projects-foxtrot

37e3671969b516369e2d1c7cab5890b75c489f56

[ "MIT" ]

672

2016-10-12T16:36:48.000Z

2022-03-25T00:57:04.000Z

mp_sort/virtenv/lib/python3.6/site-packages/transcrypt/development/automated_tests/transcrypt/div_issues/issue387/__init__.py

ang-jason/fip_powerx_mini_projects-foxtrot

37e3671969b516369e2d1c7cab5890b75c489f56

[ "MIT" ]

230

2016-10-20T14:31:40.000Z

2022-03-16T15:57:15.000Z

import div_issues.issue387.test1 import div_issues.issue387.test1.test2 def run387 (autoTester): autoTester.check (div_issues.issue387.test1.getReport ()) autoTester.check ('From test: ', div_issues.issue387.test1.test2.C.__module__) autoTester.check (__name__) class D: pass autoTester.check ('From test:', D.__module__) autoTester.check (D.__name__)

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0386c9960c429274be0e0da283b610ed1735af00

58

py

Python

ldapplugin/__init__.py

ScottWales/LdapPlugin

1c629689a47fee5dc4343efb5977badab761df3c

[ "BSD-3-Clause" ]

null

ldapplugin/__init__.py

ScottWales/LdapPlugin

1c629689a47fee5dc4343efb5977badab761df3c

[ "BSD-3-Clause" ]

null

ldapplugin/__init__.py

ScottWales/LdapPlugin

1c629689a47fee5dc4343efb5977badab761df3c

[ "BSD-3-Clause" ]

null

# Ldap Plugin python package from ldapplugin.api import *

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null

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0399d68e56fa3499dfcecc64bfc6bd1999f6dc6f

745

py

Python

schema.py

Brotchu/DistributedDopingTest

50ba29eac3540b43b019ac75d0b2d0339b7b6767

[ "MIT" ]

null

schema.py

Brotchu/DistributedDopingTest

50ba29eac3540b43b019ac75d0b2d0339b7b6767

[ "MIT" ]

null

schema.py

Brotchu/DistributedDopingTest

50ba29eac3540b43b019ac75d0b2d0339b7b6767

[ "MIT" ]

null

from enum import unique from mongoengine import (DateTimeField, DictField, Document, EmbeddedDocument, StringField) class DateAvailability(EmbeddedDocument): date = DateTimeField(required=True) location = StringField(required=True) class Athlete(Document): name = StringField(required=True) email = StringField(required=True) password = StringField(required=True) # TODO: hash it!! nationality = StringField(required=True) location = StringField(required=True) # availability = db.ListField(db.EmbeddedDocumentField(DateAvailability)) availability = DictField() meta = {'collection': 'athlete'} class Emails(Document): email = StringField(required=True, unique=True)

28.653846

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03b94b39b4fb4557a2f3c3ee807549e0e833cbdc

216

py

Python

treesearchsolverpy/__init__.py

fontanf/treesearchsolverpy

5e59eef3cac31ab67eb904de7d9733e36be737d8

[ "MIT" ]

null

treesearchsolverpy/__init__.py

fontanf/treesearchsolverpy

5e59eef3cac31ab67eb904de7d9733e36be737d8

[ "MIT" ]

null

treesearchsolverpy/__init__.py

fontanf/treesearchsolverpy

5e59eef3cac31ab67eb904de7d9733e36be737d8

[ "MIT" ]

null

from .greedy import greedy from .best_first_search import best_first_search from .iterative_beam_search import iterative_beam_search __all__ = [ 'greedy', 'best_first_search', 'iterative_beam_search', ]

21.6

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03e5ff502639b89e15828b8e07168aa0ff0b57ba

511

py

Python

gan_server_api/serializers.py

luojie1024/HACK_GAN_MB

a709cf7a88649584b05a4bd71bc3fbe8fa212646

[ "Apache-2.0" ]

6

2018-06-06T08:27:43.000Z

2019-12-11T04:23:14.000Z

gan_server_api/serializers.py

luojie1024/HACK_GAN_img2img

a709cf7a88649584b05a4bd71bc3fbe8fa212646

[ "Apache-2.0" ]

2

2018-10-23T07:11:51.000Z

2019-05-18T01:20:47.000Z

gan_server_api/serializers.py

luojie1024/HACK_GAN_MB

a709cf7a88649584b05a4bd71bc3fbe8fa212646

[ "Apache-2.0" ]

3

2018-06-06T11:32:56.000Z

2019-04-10T05:35:46.000Z

# -*- coding: utf-8 -*- ''' # @Time : 5/23/18 11:14 AM # @Author : luojie # @File : serializers.py.py # @Desc : ''' from django.contrib.auth.models import User, Group from rest_framework import serializers class UserSerializer(serializers.HyperlinkedModelSerializer): class Meta: model = User fields = ('url', 'username', 'email', 'groups') class GroupSerializer(serializers.HyperlinkedModelSerializer): class Meta: model = Group fields = ('url', 'name')

22.217391

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03f1f9c096fd8d1032ecc1fdde32673bb7cd25b6

98

py

Python

custom_components/ds_air/__init__.py

kamingchan/ha-dsair

097f32d4feb67f043f93bcc0b50bdb3f24f5d522

[ "MIT" ]

7

2021-01-20T09:59:10.000Z

2022-01-30T16:49:37.000Z

custom_components/ds_air/__init__.py

kamingchan/ha-dsair

097f32d4feb67f043f93bcc0b50bdb3f24f5d522

[ "MIT" ]

null

custom_components/ds_air/__init__.py

kamingchan/ha-dsair

097f32d4feb67f043f93bcc0b50bdb3f24f5d522

[ "MIT" ]

3

2021-02-04T09:48:28.000Z

2021-06-12T09:37:42.000Z

""" Platform for DS-AIR of Daikin https://www.daikin-china.com.cn/newha/products/4/19/DS-AIR/ """

19.6

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2061b42f8d840fb0464c230c74ade9d1444bf495

1,064

py

Python

yinwei/L4/ling-psutil.py

qsyPython/Python_play_now

278b6d5d30082f8f93b26902c854737c4919405a

[ "MIT" ]

2

2018-03-29T08:26:17.000Z

2019-06-17T10:56:19.000Z

yinwei/L4/ling-psutil.py

qsyPython/Python_play_now

278b6d5d30082f8f93b26902c854737c4919405a

[ "MIT" ]

1

2022-03-22T20:26:08.000Z

yinwei/L4/ling-psutil.py

qsyPython/Python_play_now

278b6d5d30082f8f93b26902c854737c4919405a

[ "MIT" ]

1

2019-02-18T10:44:20.000Z

#psutil是一个跨平台库（http://code.google.com/p/psutil/），能够轻松实现获取系统运行的进程和系统利用率（包括CPU、内存、磁盘、网络等）信息。它主要应用于系统监控，分析和限制系统资源及进程的管理 import psutil #使用cpu_times获取cpu的完整信息 #print(psutil.cpu_times())#scputimes(user=6157.05, nice=0.0, system=3130.85, idle=177492.17) #psutil.cpu_count()#获取cpu的逻辑个数 #print(psutil.cpu_count()) #8 #获取cpu的所有逻辑信息 #print(psutil.cpu_times_percent())#scputimes(user=0.0, nice=0.0, system=0.0, idle=0.0) #获取内存的所有信息 #print(psutil.virtual_memory())#svmem(total=17179869184, available=6949957632, percent=59.5, used=10303217664, free=5019918336, active=6379835392, inactive=1930039296, wired=1993342976) #获取磁盘的详细信息 #print(psutil.disk_partitions())#[sdiskpart(device='/dev/disk1', mountpoint='/', fstype='hfs', opts='rw,local,rootfs,dovolfs,journaled,multilabel')] #返回当前登录系统的用户信息 print(psutil.users()) #suser(name='yinwei', terminal='console', host=None, started=1526260224.0, pid=100), suser(name='yinwei', terminal='ttys000', host=None, started=1526268416.0, pid=785), suser(name='yinwei', terminal='ttys002', host=None, started=1526278912.0, pid=2704)]

46.26087

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1,064

5.547945

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0.051852

0.085185

0

0.154455

0.050752

1,064

22

254

48.363636

0.647525

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true

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null

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null

0

1

0

1

0

1

0

4

208b10ccbcfdc7225ca4b1e2124121609c595d53

132

py

Python

test.py

steerapi/line-sticker-data

8ca82e86b3093e2e1fe04a5e8826579ba0c1a139

[ "MIT" ]

null

test.py

steerapi/line-sticker-data

8ca82e86b3093e2e1fe04a5e8826579ba0c1a139

[ "MIT" ]

null

test.py

steerapi/line-sticker-data

8ca82e86b3093e2e1fe04a5e8826579ba0c1a139

[ "MIT" ]

null

from linestickerdata import get_image_paths paths = get_image_paths(folder="dataofficial", n=5, num_workers=1, seed=0) print(paths)

33

74

0.810606

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132

4.857143

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0.254902

0

0.024793

0.083333

132

4

75

33

0.818182

0

0.090226

0

1

0

false

0

0.333333

0

0.333333

1

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null

0

1

0

1

0

null

0

1

0

4

208f0c9e3aba0a81b5b26e35733e09f2a813bb22

313

py

Python

HackerRank/BasicCalculator_master/BasicCalculator.py

Naga-kalyan/competitive_programming

e9501b16ac327c7f6700a0970d0804e1f9ef5f1b

[ "MIT" ]

8

2020-09-02T13:30:41.000Z

2022-01-31T07:45:31.000Z

HackerRank/BasicCalculator_master/BasicCalculator.py

Naga-kalyan/competitive_programming

e9501b16ac327c7f6700a0970d0804e1f9ef5f1b

[ "MIT" ]

null

HackerRank/BasicCalculator_master/BasicCalculator.py

Naga-kalyan/competitive_programming

e9501b16ac327c7f6700a0970d0804e1f9ef5f1b

[ "MIT" ]

1

2021-02-15T13:44:22.000Z

T = int(input()) a=list(map(int,input().split())) for i in range(0,T): b = input() if(b == '+'): print(a[0]+a[1]) elif(b == '-'): print(a[0]-a[1]) elif(b == '*'): print(a[0]*a[1]) elif(b == '/'): print(a[0]//a[1]) elif(b == '%'): print(a[0]%a[1])

20.866667

32

0.373802

52

313

2.25

0.326923

0.25641

0.299145

0.34188

0.564103

0

0.050926

0.309904

313

14

33

22.357143

0.490741

0

0.015974

0

1

0

false

0

0.357143

0

null

1

0

1

0

null

0

4

20985d39e9f1c5a2c3e60c77442ba83bb27fdf44

111

py

Python

tests/test_tools.py

rpatil524/mcfly

1bfdd58ad3b01b31250487fc820a031e1cc57ff7

[ "Apache-2.0" ]

356

2016-05-31T15:23:30.000Z

2022-03-30T22:15:36.000Z

tests/test_tools.py

rpatil524/mcfly

1bfdd58ad3b01b31250487fc820a031e1cc57ff7

[ "Apache-2.0" ]

250

2016-05-24T12:30:41.000Z

2022-02-02T16:38:06.000Z

tests/test_tools.py

rpatil524/mcfly

1bfdd58ad3b01b31250487fc820a031e1cc57ff7

[ "Apache-2.0" ]

92

2016-12-23T13:50:23.000Z

2022-02-02T14:19:00.000Z

import os def safe_remove(path): try: os.remove(path) except FileNotFoundError: pass

12.333333

29

0.612613

13

111

5.153846

0.769231

0.298507

0

0.315315

111

8

30

13.875

0.881579

0

1

0.166667

false

0.166667

0

0.333333

0

1

0

null

1

0

1

0

null

0

1

0

4

20e997c9712caa9d3af6c65263fff1bf37ccff95

94

py

Python

states_app/apps.py

germapat/states

1e18afb3695bc7135a7f8142f9ff58bd9a81bb70

[ "MIT" ]

null

states_app/apps.py

germapat/states

1e18afb3695bc7135a7f8142f9ff58bd9a81bb70

[ "MIT" ]

3

2020-02-12T01:10:25.000Z

2021-06-10T21:45:01.000Z

states_app/apps.py

germapat/states

1e18afb3695bc7135a7f8142f9ff58bd9a81bb70

[ "MIT" ]

null

from django.apps import AppConfig class StatesAppConfig(AppConfig): name = 'states_app'

15.666667

33

0.765957

11

94

6.454545

0.909091

0

0.159574

94

5

34

18.8

0.898734

0

0.106383

0

1

0

false

0

0.333333

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

4

4556f47479c4e2c53b821362e6bc84d5ce1cf926

179

py

Python

stats/management/commands/update_plots.py

openkamer/openkamer

732facf01f2bb4d1649b0c6892466ae9e0982bd6

[ "MIT" ]

33

2016-05-12T13:16:23.000Z

2022-03-11T10:21:26.000Z

stats/management/commands/update_plots.py

openkamer/openkamer

732facf01f2bb4d1649b0c6892466ae9e0982bd6

[ "MIT" ]

69

2016-05-23T15:35:39.000Z

2021-12-13T19:46:21.000Z

stats/management/commands/update_plots.py

openkamer/openkamer

732facf01f2bb4d1649b0c6892466ae9e0982bd6

[ "MIT" ]

5

2016-05-17T19:49:05.000Z

2020-06-09T13:37:25.000Z

from django.core.management.base import BaseCommand import stats.models class Command(BaseCommand): def handle(self, *args, **options): stats.models.Plot.create()

17.9

51

0.726257

22

179

5.909091

0.818182

0.169231

0

0.162011

179

9

52

19.888889

0.866667

0

1

0.2

false

0

0.4

0

0.8

0

1

0

null

0

1

0

null

0

1

0

1

0

4

456d4d7f04f366f6f8b543e1b26a7d4f2c3de725

175

py

Python

tests/Conveyor_test.py

kant/conveyr_py

1454c41add37bfc08f96113ec62e8d889c1f7db0

[ "Apache-2.0", "MIT" ]

null

tests/Conveyor_test.py

kant/conveyr_py

1454c41add37bfc08f96113ec62e8d889c1f7db0

[ "Apache-2.0", "MIT" ]

null

tests/Conveyor_test.py

kant/conveyr_py

1454c41add37bfc08f96113ec62e8d889c1f7db0

[ "Apache-2.0", "MIT" ]

null

import unittest from conveyr import Conveyor class ConveyrTest(unittest.TestCase): def test_1(self): conveyr = Conveyor() self.assertIsNotNone(conveyr)

17.5

37

0.714286

19

175

6.526316

0.684211

0

0.007246

0.211429

175

9

38

19.444444

0.891304

0

0.166667

1

0.166667

false

0

0.333333

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

4

4570c81e2feaad256f36ee0a0fb9ffa91dc6e7e2

163

py

Python

problem0443.py

kmarcini/Project-Euler-Python

d644e8e1ec4fac70a9ab407ad5e1f0a75547c8d3

[ "BSD-3-Clause" ]

null

problem0443.py

kmarcini/Project-Euler-Python

d644e8e1ec4fac70a9ab407ad5e1f0a75547c8d3

[ "BSD-3-Clause" ]

null

problem0443.py

kmarcini/Project-Euler-Python

d644e8e1ec4fac70a9ab407ad5e1f0a75547c8d3

[ "BSD-3-Clause" ]

null

########################### # # #443 GCD sequence - Project Euler # https://projecteuler.net/problem=443 # # Code by Kevin Marciniak # ###########################

18.111111

38

0.466258

14

163

5.428571

0.928571

0

0.041667

0.116564

163

8

39

20.375

0.486111

0.570552

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

1

0

null

0

1

0

4

45896ad170203d7edf771d9c908c4da7b7223934

410

py

Python

switchbot_hub/switchbot/abstract_bot_controller.py

masato-ka/switchbot-hub

1bf5b07f25b6a668bd226aeafdea1e4531a5870c

[ "MIT" ]

1

2019-10-10T16:26:17.000Z

switchbot_hub/switchbot/abstract_bot_controller.py

masato-ka/switchbot-hub

1bf5b07f25b6a668bd226aeafdea1e4531a5870c

[ "MIT" ]

null

switchbot_hub/switchbot/abstract_bot_controller.py

masato-ka/switchbot-hub

1bf5b07f25b6a668bd226aeafdea1e4531a5870c

[ "MIT" ]

null

#! /usr/bin/env python3 # -*- coding: utf-8 -*- from abc import ABCMeta, abstractmethod class AbstractBotController(metaclass=ABCMeta): @abstractmethod def press_switch(self): pass @abstractmethod def turn_on_switch(self): pass @abstractmethod def turn_off_switch(self): pass @abstractmethod def get_device_info(self): return (None, None)

17.083333

47

0.653659

45

410

5.8

0.622222

0.260536

0.16092

0.321839

0.386973

0.268199

0

0.006536

0.253659

410

23

48

17.826087

0.846405

0.107317

0

0.5

0

1

0.285714

false

0.214286

0.071429

0.5

0

null

1

0

1

0

null

0

1

0

1

0

4

458ac923e91d74968aafd792f27445c11c2da736

85

py

Python

deep_vision/models_helpers/AbstractModel.py

sharpcodex/deep-vision

f9d87a9eccc927590ceb9e8a4dd15bc85c6fd43b

[ "MIT" ]

1

2020-04-20T21:40:58.000Z

deep_vision/models_helpers/AbstractModel.py

sharpcodex/deep-vision

f9d87a9eccc927590ceb9e8a4dd15bc85c6fd43b

[ "MIT" ]

null

deep_vision/models_helpers/AbstractModel.py

sharpcodex/deep-vision

f9d87a9eccc927590ceb9e8a4dd15bc85c6fd43b

[ "MIT" ]

null

class AbstractModel: def predict(self, image): raise NotImplementedError

21.25

33

0.717647

8

85

7.625

1

0

0.223529

85

3

34

28.333333

0.924242

0

1

0.333333

false

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

4

45cb8959f7efa455ac2b9eec34144a0b79376888

86

py

Python

sdp/course/apps.py

irsisyphus/sdp

8d7cf56a4f40458717d8796a3cfb1183fb6f7343

[ "MIT" ]

2

2017-02-27T07:58:09.000Z

2017-05-31T11:35:09.000Z

sdp/course/apps.py

irsisyphus/sdp

8d7cf56a4f40458717d8796a3cfb1183fb6f7343

[ "MIT" ]

null

sdp/course/apps.py

irsisyphus/sdp

8d7cf56a4f40458717d8796a3cfb1183fb6f7343

[ "MIT" ]

1

2018-08-24T23:21:09.000Z

from django.apps import AppConfig class CourseConfig(AppConfig): name = 'course'

17.2

33

0.755814

10

86

6.5

0.9

0

0.162791

86

4

34

21.5

0.902778

0

0.069767

0

1

0

false

0

0.333333

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

4

aff0ff450f0f6739bba0cf0d732ed148cc060905

276

py

Python

backend/server_delta/server_delta_app/services/customer/customer_consumer_service.py

dalmarcogd/challenge_ms

761f0a588b4c309cf6e226d306df3609c1179b4c

[ "MIT" ]

null

backend/server_delta/server_delta_app/services/customer/customer_consumer_service.py

dalmarcogd/challenge_ms

761f0a588b4c309cf6e226d306df3609c1179b4c

[ "MIT" ]

13

2020-06-05T18:26:43.000Z

2021-06-10T20:36:13.000Z

backend/server_delta/server_delta_app/services/customer/customer_consumer_service.py

dalmarcogd/challenge_ms

761f0a588b4c309cf6e226d306df3609c1179b4c

[ "MIT" ]

null

from .customer_consumer_thread import CustomerConsumerThread class CustomerConsumerService(): def proccess_in_background(self, cpf): CustomerConsumerThread(cpf).start() def proccess(self, cpf): CustomerConsumerThread(cpf).consumer_services(cpf)

27.6

60

0.757246

26

276

7.846154

0.615385

0.107843

0.284314

0.313725

0

0.163043

276

10

61

27.6

0.883117

0

1

0.333333

false

0

0.166667

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

4

b339ac12f7b339ab07d3b4da541129d4ffe4ee0c

393

py

Python

BIZa/2014/Tskipu_a_k/task_2_28.py

YukkaSarasti/pythonintask

eadf4245abb65f4400a3bae30a4256b4658e009c

[ "Apache-2.0" ]

null

BIZa/2014/Tskipu_a_k/task_2_28.py

YukkaSarasti/pythonintask

eadf4245abb65f4400a3bae30a4256b4658e009c

[ "Apache-2.0" ]

null

BIZa/2014/Tskipu_a_k/task_2_28.py

YukkaSarasti/pythonintask

eadf4245abb65f4400a3bae30a4256b4658e009c

[ "Apache-2.0" ]

null

# Задача 2. Вариант 28. #Напишите программу, которая будет выводить на экран наиболее понравившееся вам высказывание, автором которого является Эпикур. Не забудьте о том, что автор должен быть упомянут на отдельной строке. # Цкипуришвили Александр # 25.05.2016 print("Каждый уходит из жизни так, словно только что вошел.") print("\n\t\t\t\t\t Эпикур") input("нажимте Enter для выхода")

43.666667

199

0.765903

59

393

5.101695

0.864407

0.026578

0.0299

0.026578

0

0.032934

0.150127

393

9

200

43.666667

0.868263

0.648855

0

0.714286

0

1

0

true

0

0.666667

0

null

0

1

0

1

0

null

0

1

0

1

0

4

b346a81302a67d33f35fada15f299c7426624dbd

12,367

py

Python

tests/profiler/resources/profiler_config_parser_utils.py

sophiayue1116/sagemaker-debugger

34a74e55b94b056654c2f91c94d2943d2440a05d

[ "Apache-2.0" ]

null

tests/profiler/resources/profiler_config_parser_utils.py

sophiayue1116/sagemaker-debugger

34a74e55b94b056654c2f91c94d2943d2440a05d

[ "Apache-2.0" ]

1

2021-06-25T15:47:58.000Z

tests/profiler/resources/profiler_config_parser_utils.py

sophiayue1116/sagemaker-debugger

34a74e55b94b056654c2f91c94d2943d2440a05d

[ "Apache-2.0" ]

null

# Standard Library import re import time # First Party from smdebug.profiler.profiler_constants import ( CPROFILE_NAME, PROFILING_NUM_STEPS_DEFAULT, PYINSTRUMENT_NAME, ) from smdebug.profiler.python_profiler import cProfileTimer current_step = 3 current_time = time.time() good_start_step = 3 bad_start_step = 1 bad_start_step_2 = 5 num_steps = 2 good_start_time = current_time bad_start_time = current_time - 1000 duration = 500 # These test cases will primarily test the various combinations of start step, num steps, start_time, duration for # detailed profiling. Each test case consists of (detailed_profiling_parameters, expected_enabled, # expected_can_profile, expected_values) where: # - detailed_profiling_parameters refers to fields (if they exist, `None` otherwise) in the detailed profiling config, # i.e. (start_step, num_steps, start_time, duration) # - expected_enabled refers to whether detailed profiling is enabled (no errors parsing config). # - expected_can_profile refers to the expected value of should_save_metrics for detailed profiling # - expected_values refers to expected values of the profile range after parsing, i.e. # (start_step, end_step, start_time, end_time) detailed_profiling_test_cases = [ # Valid case where both start_step and num_steps are provided. Profiler starts at start_step and profiles for # num_steps steps. Profiler will profile current step. ( (good_start_step, num_steps, None, None), True, True, (good_start_step, good_start_step + num_steps, None, None), ), # Valid case where only start_step is provided. Profiler starts at start_step and profiles for # PROFILER_NUM_STEPS_DEFAULT steps. Profiler will profile current step. ( (good_start_step, None, None, None), True, True, (good_start_step, good_start_step + PROFILING_NUM_STEPS_DEFAULT, None, None), ), # Valid case where only num_steps is provided. Profiler starts at current_step and profiles for num_steps steps. # Profiler will profile current step. ( (None, num_steps, None, None), True, True, (current_step, current_step + num_steps, None, None), ), # Valid case where start_time and duration are provided. Profiler starts at start_time and profiles for duration # seconds. Profiler will profile current step. ( (None, None, good_start_time, duration), True, True, (None, None, good_start_time, good_start_time + duration), ), # Valid case where only start_time is provided. Profiler starts at start_time and profiles until the next step. # Profiler will profile current step. ( (None, None, good_start_time, None), True, True, (None, current_step + 1, good_start_time, None), ), # Valid case where only duration is provided. Profiler starts immediately and profiles for duration seconds. # Profiler will profile current step. ((None, None, None, duration), True, True, (None, None, current_time, current_time + duration)), # Valid case where detailed_profiling_enabled is True, but start_step is too small. Profiler starts at # bad_start_step and profiles for PROFILER_NUM_STEPS_DEFAULT steps. because # bad_start_step + PROFILER_NUM_STEPS_DEFAULT < current_step, Profiler does not profile current step. ( (bad_start_step, None, None, None), True, False, (bad_start_step, bad_start_step + PROFILING_NUM_STEPS_DEFAULT, None, None), ), # Valid case where detailed_profiling_enabled is True, but start_time is too small. Profiler starts at start time # and profiles for duration seconds. because bad_start_time + duration is before the current time, Profiler does # not profile current step. ( (None, None, bad_start_time, duration), True, False, (None, None, bad_start_time, bad_start_time + duration), ), # Invalid case where both step and time fields are provided, which is not allowed. No detailed profiling takes # place. ( (good_start_step, num_steps, good_start_time, duration), False, False, (good_start_step, None, good_start_time, None), ), ] # These test cases will primarily test the various combinations of start step, metrics_regex and metrics_name for # dataloader profiling. Each test case consists of (dataloader_parameters, expected_enabled, expected_can_profile, # expected_values) where: # - dataloader_parameters refers to fields (if they exist, `None` otherwise) in the dataloader metrics config, # i.e. (start_step, metrics_regex, metrics__name) # - expected_enabled refers to whether dataloader metrics collection is enabled (no errors parsing config). # - expected_can_profile refers to the expected value should_save_metrics for dataloader # - expected_values refers to expected values of the profile range after parsing, i.e. # (start_step, end_step, metrics_regex) dataloader_test_cases = [ # Valid case where start step and metrics regex are provided. Metrics collection is done for the current step for # the given metrics name. ( (good_start_step, "Dataloader:Event", "Dataloader:Event1"), True, True, ( good_start_step, good_start_step + PROFILING_NUM_STEPS_DEFAULT, re.compile("dataloader:event"), ), ), # Valid case where start step and metrics regex are provided. Metrics collection is done for the current step, but # not for the given metrics name since the regex didn't match the name. ( (good_start_step, "Dataloader:Event2", "Dataloader:Event1"), True, False, (good_start_step, None, re.compile("dataloader:event2")), ), # Valid case where start step is provided. Metrics collection is done for the current step for the given metrics # name. ( (good_start_step, None, "Dataloader:Event1"), True, True, (good_start_step, good_start_step + PROFILING_NUM_STEPS_DEFAULT, re.compile(".*")), ), # Invalid case where start step and metrics regex are provided, but the metrics regex is invalid. No dataloader # metrics collection is done. ((good_start_step, "*", "Dataloader:Event1"), False, False, (None, None, None)), ] # These test cases will primarily test the various combinations of start step, num steps, profiler name and cprofile # timer for python profiling. Each test case consists of (python_profiling_parameters, expected_enabled, # expected_can_profile, expected_values) where: # - python_profiling_parameters refers to fields (if they exist, `None` otherwise) in the python profiling config, # i.e. (start_step, num_steps, profiler_name, cprofile_timer) # - expected_enabled refers to whether python profiling is enabled (no errors parsing config). # - expected_can_profile refers to the expected value hould_save_metrics for python profiling # - expected_values refers to expected values of the profile range after parsing, i.e. # (start_step, end_step, profiler_name, cprofile_timer) python_profiling_test_cases = [ # Valid case where step fields, profiler name and cprofile timer are specified. Profiler starts at start step and # profiles for num_steps steps with cProfile measuring off cpu time. Profiler will profile current step. ( (good_start_step, num_steps, CPROFILE_NAME, cProfileTimer.OFF_CPU_TIME.value), True, True, (good_start_step, good_start_step + num_steps, CPROFILE_NAME, cProfileTimer.OFF_CPU_TIME), ), # Valid case where only step fields are provided. Profiler starts at start_step and profiles for num_steps steps # with cProfile measuring total time. Profiler will profile current step. ( (good_start_step, num_steps, None, None), True, True, (good_start_step, good_start_step + num_steps, CPROFILE_NAME, cProfileTimer.TOTAL_TIME), ), # Valid case where step fields and cprofile timer are provided. Profiler starts at start_step and profiles for # num_steps steps with cProfile measuring cpu time. Profiler will profile current step. ( (good_start_step, num_steps, None, cProfileTimer.CPU_TIME.value), True, True, (good_start_step, good_start_step + num_steps, CPROFILE_NAME, cProfileTimer.CPU_TIME), ), # Valid case where step fields and profiler name are provided. Profiler starts at start_step and profiles for # num_steps steps with Pyinstrument. Profiler will profile current step. ( (good_start_step, num_steps, PYINSTRUMENT_NAME, None), True, True, (good_start_step, good_start_step + num_steps, PYINSTRUMENT_NAME, None), ), # Valid case where step fields, profiler name and cprofile timer are provided. Profiler starts at start_step and # profiles for num_steps steps with Pyinstrument (since use pyinstrument is True, cprofile timer is ignored). # Profiler will profile current step. ( (good_start_step, num_steps, PYINSTRUMENT_NAME, cProfileTimer.CPU_TIME.value), True, True, (good_start_step, good_start_step + num_steps, PYINSTRUMENT_NAME, None), ), # Invalid case where profiler name and cprofile timer are provided. No step or time range has been provided, so # profiler does not profile current step. ( (None, None, CPROFILE_NAME, cProfileTimer.CPU_TIME.value), True, False, (None, None, CPROFILE_NAME, cProfileTimer.CPU_TIME), ), # Invalid case where step fields and profiler name are provided, but the profiler name is invalid. No python # profiling takes place. ( (good_start_step, num_steps, "bad_profiler_name", None), False, False, (None, None, None, None), ), # Invalid case where step fields and cprofile timer are provided, but the cprofile timer is invalid. No python # profiling takes place. ( (good_start_step, num_steps, CPROFILE_NAME, "bad_cprofile_timer"), False, False, (None, None, None, None), ), ] # These test cases will primarily test the various combinations of start step, num steps that are unique to herring # profiling. Each test case consists of (herring_profiling_parameters, expected_profiling_enabled, # expected_can_profile, expected_values) where: # - smdataparallel_profiling_parameters refers to fields (if they exist, `None` otherwise) in the smdataparallel profiling config, # i.e. (start_step, num_steps) # - expected_profiling_enabled refers to whether herring profiling is enabled (no errors parsing config). # - expected_can_profile refers to the expected value of should_save_metrics for herring profiling # - expected_values refers to expected values of the profile range after parsing, i.e. # (start_step, end_step) smdataparallel_profiling_test_cases = [ # Valid case where both start_step and num_steps are provided. Profiler starts at start_step and profiles for # num_steps steps. Profiler will profile current step. ((good_start_step, num_steps), True, True, (good_start_step, good_start_step + num_steps)), # Valid case where only start_step is provided. Profiler starts at start_step and profiles for # PROFILER_NUM_STEPS_DEFAULT steps. Profiler will profile current step. ( (good_start_step, None), True, True, (good_start_step, good_start_step + PROFILING_NUM_STEPS_DEFAULT), ), # Valid case where only num_steps is provided. Profiler starts at current_step and profiles for num_steps steps. # Profiler will profile current step. ((None, num_steps), True, True, (current_step, current_step + num_steps)), # Valid case where detailed_profiling_enabled is True, but start_step is too small. Profiler starts at # bad_start_step and profiles for PROFILER_NUM_STEPS_DEFAULT steps. because # bad_start_step + PROFILING_NUM_STEPS_DEFAULT < current_step, Profiler does not profile current step. ( (bad_start_step_2, None), True, False, (bad_start_step_2, bad_start_step_2 + PROFILING_NUM_STEPS_DEFAULT), ), ]

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0

1

0

1

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null

0

4

2fa4eeea6a9139a5768dd5087fab241b402a5164

177

py

Python

spleeter.py

magemongo/my_karaoke

17c836769a17db303ac7bb4703fb11adc79e6fde

[ "MIT" ]

null

spleeter.py

magemongo/my_karaoke

17c836769a17db303ac7bb4703fb11adc79e6fde

[ "MIT" ]

null

spleeter.py

magemongo/my_karaoke

17c836769a17db303ac7bb4703fb11adc79e6fde

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ Created on Sun May 30 12:32:54 2021 @author: anton """ import os os.system('cmd /c spleeter separate audio/veu_de_flores.mp3 -o /output')

17.7

72

0.632768

29

177

3.793103

0.965517

0

0.099291

0.20339

177

10

72

17.7

0.680851

0.418079

0

0.678161

0.264368

0

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0

true

0

0.5

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null

0

1

0

null

0

1

0

1

0

4

2fe4654d874fd2edd55cfbcbc3d191bb4e519754

170

py

Python

Python diye Programming sekha 2nd/Tracking mails.py

mitul3737/My-Python-Programming-journey-from-Beginning-to-Data-Sciene-Machine-Learning-AI-Deep-Learning

ca2c15c597a64e5a7689ba3a44ce36a1c0828194

[ "MIT" ]

1

2021-05-02T20:30:33.000Z

Python diye Programming sekha 2nd/Tracking mails.py

Mit382/My-Python-Programming-Journey-from-Beginning-to-Data-Sciene-Machine-Learning-AI-Deep-Learning

c19d84dfe6dcf496ff4527724f92e228579b6456

[ "MIT" ]

null

Python diye Programming sekha 2nd/Tracking mails.py

Mit382/My-Python-Programming-Journey-from-Beginning-to-Data-Sciene-Machine-Learning-AI-Deep-Learning

c19d84dfe6dcf496ff4527724f92e228579b6456

[ "MIT" ]

1

2021-05-02T20:30:29.000Z

text="Email us for any feedback here: shahriyarmitul3737@gmail.com py.book@subeen.com book_py@subeen.com thank you" import re print(re.findall(r'[.\w]+@\w+[.]\w+',text))

56.666667

116

0.729412

30

170

4.1

0.7

0.146341

0

0.025641

0.082353

170

3

117

56.666667

0.762821

0

0.333333

0.730994

0.163743

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false

0

0.333333

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0.333333

0

null

0

1

0

1

0

null

0

1

0

4

643bf3396ae5af0451074b67d9795716fbf55c42

192

py

Python

lib_rovpp/policies/rovpp_v2a_policy.py

iReynaldo/lib_rovpp

eb201adc948e9375123c2e2301ee524392dd7b0d

[ "BSD-3-Clause" ]

1

2021-12-05T07:42:35.000Z

lib_rovpp/policies/rovpp_v2a_policy.py

iReynaldo/lib_rovpp

eb201adc948e9375123c2e2301ee524392dd7b0d

[ "BSD-3-Clause" ]

null

lib_rovpp/policies/rovpp_v2a_policy.py

iReynaldo/lib_rovpp

eb201adc948e9375123c2e2301ee524392dd7b0d

[ "BSD-3-Clause" ]

null

from .rovpp_v2a_lite_policy import ROVPPV2aLitePolicy class ROVPPV2aPolicy(ROVPPV2aLitePolicy): name = "ROV++V2a" from .lite_converter import _new_ann_is_better, _best_by_hole_size

24

70

0.8125

25

192

5.76

0.8

0

0.02994

0.130208

192

7

71

27.428571

0.832335

0

0.041667

0

1

0

false

0

0.5

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1

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null

0

1

0

null

0

1

0

1

0

4

ff5745da043e6666b643e1e6762d48d96cde2e43

1,142

py

Python

website/context.py

jomono/dmarc-viewer

0ae8af4c57387884541f5b49132dc598783dafbe

[ "MIT" ]

45

2018-05-28T19:55:51.000Z

2022-01-21T12:49:05.000Z

website/context.py

jomono/dmarc-viewer

0ae8af4c57387884541f5b49132dc598783dafbe

[ "MIT" ]

14

2018-05-28T19:14:18.000Z

2020-06-05T18:32:56.000Z

website/context.py

jomono/dmarc-viewer

0ae8af4c57387884541f5b49132dc598783dafbe

[ "MIT" ]

12

2018-07-19T10:20:47.000Z

2021-07-20T11:50:57.000Z

""" <Program Name> context.py <Author> Lukas Puehringer <luk.puehringer@gmail.com> <Started> Nov 19, 2015 <Copyright> See LICENSE for licensing information. <Purpose> A simple template context processor to add additional data to the template context. Once a context processor is registered in the settings file, e.g.: ``` # in settings.py TEMPLATES = [ { ... 'OPTIONS': { 'context_processors': [ ..., 'website.context.options' ], }, }, ] ``` you can access the variable returned by the context processor function in a template, e.g.: ```  {% if TEMPLATE_SETTINGS.use_minified %} ``` More info at: https://docs.djangoproject.com/en/1.11/ref/templates/api/#writing-your-own-context-processors """ from django.conf import settings def options(request): """Adds TEMPLATE_SETTINGS variable initialized in settings.py to the template context. """ return { "TEMPLATE_SETTINGS" : settings.TEMPLATE_SETTINGS}

22.392157

97

0.596322

125

1,142

5.4

0.616

0.094815

0.038519

0.059259

0

0.011166

0.294221

1,142

51

98

22.392157

0.826303

0.875657

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0.333333

false

0

0.333333

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null

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1

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null

0

1

0

1

0

1

0

4

ff580b553685c8c94d3f66bfd26d72ed90182996

77

py

Python

UI/__init__.py

Manon-des-sources/-

6b82012786089a95fd7e69082dd54d826197544a

[ "MIT" ]

2

2021-03-24T01:59:37.000Z

2021-12-08T09:35:03.000Z

UI/__init__.py

Manon-des-sources/-

6b82012786089a95fd7e69082dd54d826197544a

[ "MIT" ]

null

UI/__init__.py

Manon-des-sources/-

6b82012786089a95fd7e69082dd54d826197544a

[ "MIT" ]

1

2020-05-28T08:14:22.000Z

#!/user/bin/env python3 # 为了让其他目录的代码可以调用本目录下的模块、 # 在本目录下需要建立一个空文件__init__.py

19.25

27

0.805195

8

77

7.25

1

0

0.014085

0.077922

77

4

27

19.25

0.802817

0.922078

0

null

0

null

0

null

0

null

1

null

true

0

null

1

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null

0

1

0

1

0

null

0

1

0

4

ff78bc69ffc4d6033e87be9cb4bf7353ea9a30d4

2,318

py

Python

ssi_views/urls.py

dldevinc/ssi-views

ddbc06a8f85b2275e212cd4632eb450211d029f6

[ "BSD-3-Clause" ]

1

2021-05-12T06:51:04.000Z

ssi_views/urls.py

dldevinc/ssi-views

ddbc06a8f85b2275e212cd4632eb450211d029f6

[ "BSD-3-Clause" ]

null

ssi_views/urls.py

dldevinc/ssi-views

ddbc06a8f85b2275e212cd4632eb450211d029f6

[ "BSD-3-Clause" ]

null

import django from .registry import registry from .views import router if django.VERSION >= (2, 2): # noqa from django.urls import URLPattern, ResolverMatch from django.urls.resolvers import RegexPattern class SSIURLPattern(URLPattern): def resolve(self, path): match = self.pattern.match(path) if match: new_path, args, kwargs = match name = kwargs.pop('name') if name not in registry: return view = registry[name] return ResolverMatch( view, args, kwargs, self.pattern.name, route=str(self.pattern) ) def ssi_url(regex, view, kwargs=None, name=None): pattern = RegexPattern(regex, name=name, is_endpoint=True) return SSIURLPattern(pattern, view, kwargs, name) elif django.VERSION >= (2, 0): from django.urls import URLPattern, ResolverMatch from django.urls.resolvers import RegexPattern class SSIURLPattern(URLPattern): # type: ignore def resolve(self, path): match = self.pattern.match(path) if match: new_path, args, kwargs = match name = kwargs.pop('name') if name not in registry: return view = registry[name] return ResolverMatch(view, args, kwargs, self.pattern.name) def ssi_url(regex, view, kwargs=None, name=None): pattern = RegexPattern(regex, name=name, is_endpoint=True) return SSIURLPattern(pattern, view, kwargs, name) else: from django.core.urlresolvers import RegexURLPattern, ResolverMatch class SSIURLPattern(RegexURLPattern): # type: ignore def resolve(self, path): match = self.regex.search(path) if match: kwargs = match.groupdict() name = kwargs.pop('name') if name not in registry: return view = registry[name] return ResolverMatch(view, (), kwargs, self.name) def ssi_url(regex, view, kwargs=None, name=None): return SSIURLPattern(regex, view, kwargs, name) app_name = 'ssi_views' urlpatterns = [ ssi_url(r'(?P<name>[-\w.]+)/', router, name='router'), ]

33.114286

82

0.587575

252

2,318

5.365079

0.222222

0.051775

0.04142

0.039941

0.733728

0.698965

0

0.002528

0.317515

2,318

69

83

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0.012942

0

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false

0

0.145455

0.018182

0.472727

0

null

0

1

0

1

0

null

0

4

ff7a2b84087d93d1a2dec2d783de9e0c0b13e188

1,606

py

Python

cryptofolio/schema/user_account/__init__.py

JerryBeGood/Cryptofolio

7f09bdbb823e4aa70d8c83532264857e550d1c84

[ "MIT" ]

null

cryptofolio/schema/user_account/__init__.py

JerryBeGood/Cryptofolio

7f09bdbb823e4aa70d8c83532264857e550d1c84

[ "MIT" ]

2

2022-01-20T11:54:33.000Z

2022-01-21T07:13:30.000Z

cryptofolio/schema/user_account/__init__.py

JerryBeGood/Cryptofolio

7f09bdbb823e4aa70d8c83532264857e550d1c84

[ "MIT" ]

null

from ariadne import load_schema_from_path from ariadne.objects import ObjectType from cryptofolio.resolvers import user_account user_account_type_defs = load_schema_from_path( 'cryptofolio/schema/user_account') user_account_mutation = ObjectType("Mutation") user_account_mutation.set_field('signUp', user_account.sign_up_resolver) user_account_mutation.set_field('activateAccount', user_account.activate_account_resolver) user_account_mutation.set_field('generateActivationCode', user_account.generate_activation_code_resolver) user_account_mutation.set_field('signIn', user_account.sign_in_resolver) user_account_mutation.set_field('accountStatus', user_account.account_status_resolver) user_account_mutation.set_field('addExchange', user_account.add_exchange_resolver) user_account_mutation.set_field('generatePswdRecoveryCode', user_account.generate_pswd_recovery_code_resolver) user_account_mutation.set_field('recoverPassword', user_account.recover_password_resolver) user_account_mutation.set_field('deleteAccount', user_account.delete_account_resolver) user_account_mutation.set_field('changePassword', user_account.change_password_resolver) user_account_mutation.set_field('deleteExchange', user_account.delete_exchange_resolver)

48.666667

82

0.688667

159

1,606

6.440252

0.283019

0.279297

0.222656

0.236328

0.405273

0.378906

0.242188

0

0.25467

1,606

32

83

50.1875

0.855472

0

0.119626

0.047975

0

1

0

false

0.142857

0.107143

0

0.107143

0

null

1

0

null

0

1

0

4

ffb5c35d5e7685c15667eb25c482f4ac07fe8174

192

py

Python

venv/lib/python3.8/site-packages/crispy_forms/templates/bootstrap/uni_formset.html.py

Solurix/Flashcards-Django

03c863f6722936093927785a2b20b6b668bb743d

[ "MIT" ]

1

2021-05-16T03:20:23.000Z

venv/lib/python3.8/site-packages/crispy_forms/templates/bootstrap/uni_formset.html.py

Solurix/Flashcards-Django

03c863f6722936093927785a2b20b6b668bb743d

[ "MIT" ]

4

2021-03-30T14:06:09.000Z

2021-09-22T19:26:31.000Z

venv/lib/python3.8/site-packages/crispy_forms/templates/bootstrap/uni_formset.html.py

Solurix/Flashcards-Django

03c863f6722936093927785a2b20b6b668bb743d

[ "MIT" ]

null

BBBB BBBBBBBBBBBBBBBBBBBBBBB BB BBBB BBBBBBB BBBBBBBBBBBBBBBBBBBBBBBBB BBBBBBB BBB BBBB BB BBBBBBB XXXX XXXXXXXXXXXXXXXXXXX BBBBBBB BBBBBBBBBBBBBBBBBBBBBBBBB XXXXXX BBBBBB

21.333333

41

0.807292

17

192

9.117647

0.588235

0.412903

0

0.192708

192

8

42

24

1

0

0.25

0

null

0

null

0

1

0

null

1

0

1

0

null

0

1

0

4

446901b4c52c0a9bfb62fe49f0b9989e911ead84

59

py

Python

pydsp/__main__.py

capn-freako/PyDSP

0a59dab4e2e2bd559fc3fbf8e0cd5376752ff7ed

[ "BSD-2-Clause" ]

null

pydsp/__main__.py

capn-freako/PyDSP

0a59dab4e2e2bd559fc3fbf8e0cd5376752ff7ed

[ "BSD-2-Clause" ]

null

pydsp/__main__.py

capn-freako/PyDSP

0a59dab4e2e2bd559fc3fbf8e0cd5376752ff7ed

[ "BSD-2-Clause" ]

3

2015-07-27T03:01:26.000Z

2022-02-13T11:00:17.000Z

from pydsp import * PyDSP().configure_traits(view=view1)

11.8

36

0.762712

8

59

5.5

0.875

0

0.019231

0.118644

59

4

37

14.75

0.826923

0

1

0

true

0

0.5

0

0.5

0

1

0

null

0

1

0

null

0

1

0

1

0

4

4484648eba7dc6f7215c3185e39edb309e2b1112

164

py

Python

tasks/_constants.py

webtweakers/deploy

59c1c95ca3e0efb6c228f6ad35937a29e28aa6ae

[ "MIT" ]

4

2021-07-01T15:39:09.000Z

2022-03-29T21:26:36.000Z

tasks/_constants.py

webtweakers/deploy

59c1c95ca3e0efb6c228f6ad35937a29e28aa6ae

[ "MIT" ]

null

tasks/_constants.py

webtweakers/deploy

59c1c95ca3e0efb6c228f6ad35937a29e28aa6ae

[ "MIT" ]

null

RED = '\033[1;91m' GREEN = '\033[1;92m' YELLOW = '\033[1;93m' BLUE = '\033[1;94m' BROWN = '\033[1;95m' CYAN = '\033[1;96m' WHITE = '\033[1;97m' COL_END = '\033[0m'

18.222222

21

0.567073

32

164

2.875

0.59375

0.304348

0

0.328571

0.146341

164

8

22

20.5

0.328571

0

0.469512

0

1

0

false

0

null

1

0

1

0

1

0

1

0

null

0

4

922aa68254f6d7d6532202c61b2f31eff7a47b69

184

py

Python

tests/test_controller.py

bigbirdcode/cliptools

992ddf2088462477992734af8eb00453bde3ce85

[ "MIT" ]

null

tests/test_controller.py

bigbirdcode/cliptools

992ddf2088462477992734af8eb00453bde3ce85

[ "MIT" ]

6

2019-04-02T18:25:35.000Z

2019-08-21T20:24:16.000Z

tests/test_controller.py

bigbirdcode/cliptools

992ddf2088462477992734af8eb00453bde3ce85

[ "MIT" ]

null

"""ClipTools clipboard manager and text processing tools with a lines based GUI interface Test Controller part, driving the GUI and the Data """ # Placeholder for future tests pass

16.727273

56

0.782609

27

184

5.333333

0.888889

0

0.173913

184

10

57

18.4

0.947368

0.918478

0

1

0

true

1

0

1

0

null

0

1

0

null

0

1

0

4

923693ed05b2f57559fdbff3b87d19451832c0e9

2,964

py

Python

api/db/models/user.py

bharadwaj-pendyala/opentestdata-api

ff388ff2dd6d43f45e11cb5689d06ba257b23f09

[ "MIT" ]

null

api/db/models/user.py

bharadwaj-pendyala/opentestdata-api

ff388ff2dd6d43f45e11cb5689d06ba257b23f09

[ "MIT" ]

null

api/db/models/user.py

bharadwaj-pendyala/opentestdata-api

ff388ff2dd6d43f45e11cb5689d06ba257b23f09

[ "MIT" ]

null

from werkzeug.security import generate_password_hash, check_password_hash from .. import db from .base import BaseModel from . import EmailConfirmationToken from sqlalchemy import exc class User(BaseModel): __tablename__ = 'users' # fields username = db.Column(db.String(80), unique=True, nullable=False) email = db.Column(db.String(120), unique=True, nullable=False) password_hash = db.Column(db.String(128)) bio = db.Column(db.String(220), nullable=False, default="") has_avatar = db.Column(db.Boolean(), default=False) # TODO if has_avatar is false, maybe we cache the gravatar image url? is_admin = db.Column(db.Boolean(), default=False) is_email_confirmed = db.Column(db.Boolean(), default=False) private_fields = ['is_admin', 'is_email_confirmed', 'created_at', 'updated_at'] public_fields = ['username', 'avatar_url', 'bio'] # relationships ec_token = db.relationship('EmailConfirmationToken', back_populates='user', uselist=False) data = db.relationship('Datum', back_populates='author', uselist=True) actions = db.relationship('Action', back_populates='user', uselist=True) def __repr__(self): return '<User %s>' % self.username @property def avatar_url(self): # TODO get url from cloud storage via id or maybe gravatar return "http://foo.com/img.png" def set_password(self, password): self.password_hash = generate_password_hash(password) def check_password(self, password): return check_password_hash(self.password_hash, password) def has_access_to_field(self, user, field): # users always have access to their own data if user.id == self.id: return True return False def to_obj(self, *args, **kwargs): obj = super().to_obj(*args, **kwargs) obj['data'] = list(map(lambda d: d.to_obj(*args, **kwargs), self.data)) return obj def update_email(self, email, commit=False): if self.ec_token: db.session.delete(self.ec_token) token = EmailConfirmationToken() token.generate_token() self.email = email self.is_email_confirmed = False self.ec_token = token if commit: db.session.commit() @staticmethod def create(username, email, password, bio, is_admin=False): # TODO add avatar upload here? token = EmailConfirmationToken() token.generate_token() user = User(username=username, email=email, is_admin=is_admin, ec_token=token, bio=bio) user.set_password(password) db.session.add(user) db.session.add(token) try: db.session.commit() except exc.IntegrityError as e: db.session.rollback() raise e # TODO email confirmation process should actually send an e-mail at this point! return user

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1

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4

9236f5297281ae19756168b9e88975f013ae6e2f

103

py

Python

contentmanager/apps.py

x-risk/x-risk

b4fc0dd91bf98725f87dded5e535eba0166c18f2

[ "MIT" ]

5

2020-07-31T22:11:39.000Z

2022-02-10T17:50:34.000Z

contentmanager/apps.py

x-risk/x-risk

b4fc0dd91bf98725f87dded5e535eba0166c18f2

[ "MIT" ]

8

2020-07-21T12:54:01.000Z

2022-02-10T01:22:09.000Z

contentmanager/apps.py

x-risk/x-risk

b4fc0dd91bf98725f87dded5e535eba0166c18f2

[ "MIT" ]

null

from django.apps import AppConfig class ContentmanagerConfig(AppConfig): name = 'contentmanager'

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92377892c0a92a51fb2b6e13df5f252ed44bc537

578

py

Python

synthrl/common/value/value.py

kupl/synthrl

0cd9b523e7df66099a344e3307ad8c5517450a5f

[ "MIT" ]

7

2020-08-24T09:18:01.000Z

2021-12-13T04:30:10.000Z

synthrl/common/value/value.py

kupl/synthrl

0cd9b523e7df66099a344e3307ad8c5517450a5f

[ "MIT" ]

12

2020-08-31T09:51:32.000Z

2020-11-27T05:34:50.000Z

synthrl/common/value/value.py

kupl/synthrl

0cd9b523e7df66099a344e3307ad8c5517450a5f

[ "MIT" ]

2

2020-08-24T05:19:25.000Z

2020-11-24T07:44:00.000Z

from abc import ABC from abc import abstractmethod from synthrl.common.utils import classproperty class Value(ABC): @classproperty @classmethod @abstractmethod def N_VALUE(cls): pass def __init__(self, value): self.value = value @classmethod @abstractmethod def sample(cls): pass @abstractmethod def __eq__(self, other): pass def __ne__(self, other): return not self == other def __str__(self): return repr(self) def __repr__(self): return repr(self.value) @property @abstractmethod def index(self): pass

15.210526

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null

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1

0

4

926c8c86068d9f21f744a07f24c9cc50bf86fbe3

10,164

py

Python

python/kwiver/vital/tests/test_covariance.py

mwoehlke-kitware/kwiver

614a488bd2b7fe551ac75eec979766d882709791

[ "BSD-3-Clause" ]

176

2015-07-31T23:33:37.000Z

2022-03-21T23:42:44.000Z

python/kwiver/vital/tests/test_covariance.py

mwoehlke-kitware/kwiver

614a488bd2b7fe551ac75eec979766d882709791

[ "BSD-3-Clause" ]

1,276

2015-05-03T01:21:27.000Z

2022-03-31T15:32:20.000Z

python/kwiver/vital/tests/test_covariance.py

mwoehlke-kitware/kwiver

614a488bd2b7fe551ac75eec979766d882709791

[ "BSD-3-Clause" ]

85

2015-01-25T05:13:38.000Z

2022-01-14T14:59:37.000Z

""" ckwg +31 Copyright 2016-2020 by Kitware, Inc. All rights reserved. Redistribution and use in source and binary forms, with or without modification, are permitted provided that the following conditions are met: * Redistributions of source code must retain the above copyright notice, this list of conditions and the following disclaimer. * Redistributions in binary form must reproduce the above copyright notice, this list of conditions and the following disclaimer in the documentation and/or other materials provided with the distribution. * Neither name of Kitware, Inc. nor the names of any contributors may be used to endorse or promote products derived from this software without specific prior written permission. THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS ``AS IS'' AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE AUTHORS OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. ============================================================================== Tests for Vital python Covariance class """ from __future__ import print_function import unittest import nose.tools import numpy as np from kwiver.vital.types.covariance import Covar2d, Covar2f, Covar3d, Covar3f, Covar4d, Covar4f class TestVitalCovariance(unittest.TestCase): def test_new_identity(self): # Valid dimensions and types c = Covar2d() print("constructed matrix:\n", c.matrix()) c = Covar3d() print("constructed matrix:\n", c.matrix()) c = Covar4d() print("constructed matrix:\n", c.matrix()) c = Covar2f() print("constructed matrix:\n", c.matrix()) c = Covar3f() print("constructed matrix:\n", c.matrix()) c = Covar4f() print("constructed matrix:\n", c.matrix()) def test_new_scalar(self): c = Covar2d(2.0) print("constructed matrix:\n", c.matrix()) c = Covar3d(2.0) print("constructed matrix:\n", c.matrix()) c = Covar4d(2.0) print("constructed matrix:\n", c.matrix()) c = Covar2f(2.0) print("constructed matrix:\n", c.matrix()) c = Covar3f(2.0) print("constructed matrix:\n", c.matrix()) c = Covar4f(2.0) print("constructed matrix:\n", c.matrix()) c = Covar2d(14.675) print("constructed matrix:\n", c.matrix()) c = Covar3d(14.675) print("constructed matrix:\n", c.matrix()) c = Covar4d(14.675) print("constructed matrix:\n", c.matrix()) c = Covar2f(14.675) print("constructed matrix:\n", c.matrix()) c = Covar3f(14.675) print("constructed matrix:\n", c.matrix()) c = Covar4f(14.675) print("constructed matrix:\n", c.matrix()) def test_new_matrix(self): m = np.array([[1, 1], [1, 1]]) c = Covar2d(m) m_out = c.matrix() print("input matrix:\n", m) print("output matrix:\n", m_out) np.testing.assert_array_equal(m_out, m) # Type casting should be handled m = np.array([[1, 1], [1, 1]], dtype=np.float32) c = Covar2d(m) m_out = c.matrix() print("input matrix:\n", m) print("output matrix:\n", m_out) np.testing.assert_array_equal(m_out, m) # Any other numpy array of the correct shape should be acceptable m = np.ndarray((2, 2)) m[:] = 3.0 c = Covar2f(m) m_out = c.matrix() print("input matrix:\n", m) print("output matrix:\n", m_out) np.testing.assert_array_equal(m_out, m) # Diagonally congruent values should be averages when initializing with # matrix m = np.eye(3, dtype=np.double) m[0, 2] = 2.0 m_expected = m.copy() m_expected[0, 2] = 1.0 m_expected[2, 0] = 1.0 c = Covar3d(m) m_out = c.matrix() print("input matrix:\n", m) print("output matrix:\n", m_out) np.testing.assert_array_equal(m_out, m_expected) def test_get_value(self): m = np.ndarray((4, 4)) # [[ 0 2 4 6 ] [[ 0 5 10 15 ] # [ 8 10 12 14 ] -> should -> [ 5 10 15 20 ] # [ 16 18 20 22 ] [ 10 15 20 25 ] # [ 24 26 28 30 ]] [ 15 20 25 30 ]] m.reshape((16,))[:] = list(range(0, 32, 2)) c = Covar4d(m) # Test matrix upper triangle locations nose.tools.assert_equal(c[0, 0], 0) nose.tools.assert_equal(c[0, 1], 5) nose.tools.assert_equal(c[0, 2], 10) nose.tools.assert_equal(c[0, 3], 15) nose.tools.assert_equal(c[1, 1], 10) nose.tools.assert_equal(c[1, 2], 15) nose.tools.assert_equal(c[1, 3], 20) nose.tools.assert_equal(c[2, 2], 20) nose.tools.assert_equal(c[2, 3], 25) nose.tools.assert_equal(c[3, 3], 30) nose.tools.assert_equal(c[0, 1], c[1, 0]) nose.tools.assert_equal(c[0, 2], c[2, 0]) nose.tools.assert_equal(c[0, 3], c[3, 0]) nose.tools.assert_equal(c[1, 2], c[2, 1]) nose.tools.assert_equal(c[1, 3], c[3, 1]) nose.tools.assert_equal(c[2, 3], c[3, 2]) c = Covar4f(m) # Test matrix upper triangle locations nose.tools.assert_equal(c[0, 0], 0) nose.tools.assert_equal(c[0, 1], 5) nose.tools.assert_equal(c[0, 2], 10) nose.tools.assert_equal(c[0, 3], 15) nose.tools.assert_equal(c[1, 1], 10) nose.tools.assert_equal(c[1, 2], 15) nose.tools.assert_equal(c[1, 3], 20) nose.tools.assert_equal(c[2, 2], 20) nose.tools.assert_equal(c[2, 3], 25) nose.tools.assert_equal(c[3, 3], 30) nose.tools.assert_equal(c[0, 1], c[1, 0]) nose.tools.assert_equal(c[0, 2], c[2, 0]) nose.tools.assert_equal(c[0, 3], c[3, 0]) nose.tools.assert_equal(c[1, 2], c[2, 1]) nose.tools.assert_equal(c[1, 3], c[3, 1]) nose.tools.assert_equal(c[2, 3], c[3, 2]) def test_get_oob(self): # 2x2 covariance mat c = Covar2d() _ = c[0, 0] # Valid access nose.tools.assert_raises(IndexError, c.__getitem__, (0, 2)) nose.tools.assert_raises(IndexError, c.__getitem__, (-1, 0)) c = Covar2f() _ = c[0, 0] # Valid access nose.tools.assert_raises(IndexError, c.__getitem__, (0, 2)) nose.tools.assert_raises(IndexError, c.__getitem__, (-1, 0)) def test_set(self): m = np.ndarray((4, 4)) # [[ 0 2 4 6 ] [[ 0 5 10 15 ] # [ 8 10 12 14 ] -> should -> [ 5 10 15 20 ] # [ 16 18 20 22 ] [ 10 15 20 25 ] # [ 24 26 28 30 ]] [ 15 20 25 30 ]] m.reshape((16,))[:] = list(range(0, 32, 2)) c = Covar4d(m) # modify some locations c[0, 1] = 1 c[2, 2] = 3 # Test matrix upper triangle locations nose.tools.assert_equal(c[0, 0], 0) nose.tools.assert_equal(c[0, 1], 1) nose.tools.assert_equal(c[0, 2], 10) nose.tools.assert_equal(c[0, 3], 15) nose.tools.assert_equal(c[1, 1], 10) nose.tools.assert_equal(c[1, 2], 15) nose.tools.assert_equal(c[1, 3], 20) nose.tools.assert_equal(c[2, 2], 3) nose.tools.assert_equal(c[2, 3], 25) nose.tools.assert_equal(c[3, 3], 30) nose.tools.assert_equal(c[0, 1], c[1, 0]) nose.tools.assert_equal(c[0, 2], c[2, 0]) nose.tools.assert_equal(c[0, 3], c[3, 0]) nose.tools.assert_equal(c[1, 2], c[2, 1]) nose.tools.assert_equal(c[1, 3], c[3, 1]) nose.tools.assert_equal(c[2, 3], c[3, 2]) # Set in upper triangle and see it reflect in lower c[0, 2] = 42 nose.tools.assert_equal(c[2, 0], 42) # Change something in lower triangle and see it reflected in upper c[2, 1] = 43 nose.tools.assert_equal(c[1, 2], 43) # FLOAT c = Covar4f(m) # modify some locations c[0, 1] = 1 c[2, 2] = 3 # Test matrix upper triangle locations nose.tools.assert_equal(c[0, 0], 0) nose.tools.assert_equal(c[0, 1], 1) nose.tools.assert_equal(c[0, 2], 10) nose.tools.assert_equal(c[0, 3], 15) nose.tools.assert_equal(c[1, 1], 10) nose.tools.assert_equal(c[1, 2], 15) nose.tools.assert_equal(c[1, 3], 20) nose.tools.assert_equal(c[2, 2], 3) nose.tools.assert_equal(c[2, 3], 25) nose.tools.assert_equal(c[3, 3], 30) nose.tools.assert_equal(c[0, 1], c[1, 0]) nose.tools.assert_equal(c[0, 2], c[2, 0]) nose.tools.assert_equal(c[0, 3], c[3, 0]) nose.tools.assert_equal(c[1, 2], c[2, 1]) nose.tools.assert_equal(c[1, 3], c[3, 1]) nose.tools.assert_equal(c[2, 3], c[3, 2]) # Set in upper triangle and see it reflect in lower c[0, 2] = 42 nose.tools.assert_equal(c[2, 0], 42) # Change something in lower triangle and see it reflected in upper c[2, 1] = 43 nose.tools.assert_equal(c[1, 2], 43) def test_set_oob(self): # 2x2 covariance mat c = Covar2f() c[0, 0] = 1 # Valid set nose.tools.assert_raises(IndexError, c.__setitem__, (0, 2), 1) nose.tools.assert_raises(IndexError, c.__setitem__, (-1, 0), 1) c = Covar2d() c[0, 0] = 1 # Valid set nose.tools.assert_raises(IndexError, c.__setitem__, (0, 2), 1) nose.tools.assert_raises(IndexError, c.__setitem__, (-1, 0), 1)

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92999b1dcd2acbbe8626b303cfb74b75ded4f4d4

147

py

Python

examples/tpa2016_simpletest.py

sommersoft/Adafruit_CircuitPython_TPA2016

6571d0739df0c8f31414441706b2ee1082503716

[ "MIT" ]

null

examples/tpa2016_simpletest.py

sommersoft/Adafruit_CircuitPython_TPA2016

6571d0739df0c8f31414441706b2ee1082503716

[ "MIT" ]

null

examples/tpa2016_simpletest.py

sommersoft/Adafruit_CircuitPython_TPA2016

6571d0739df0c8f31414441706b2ee1082503716

[ "MIT" ]

null

import busio import board import adafruit_tpa2016 i2c = busio.I2C(board.SCL, board.SDA) tpa = adafruit_tpa2016.TPA2016(i2c) tpa.fixed_gain = -16

16.333333

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92a34517ec6eaed77214cb96e9fee02c8b563680

28

py

Python

homeassistant/components/yamaha/__init__.py

domwillcode/home-assistant

f170c80bea70c939c098b5c88320a1c789858958

[ "Apache-2.0" ]

30,023

2016-04-13T10:17:53.000Z

2020-03-02T12:56:31.000Z

homeassistant/components/yamaha/__init__.py

jagadeeshvenkatesh/core

1bd982668449815fee2105478569f8e4b5670add

[ "Apache-2.0" ]

31,101

2020-03-02T13:00:16.000Z

2022-03-31T23:57:36.000Z

homeassistant/components/yamaha/__init__.py

jagadeeshvenkatesh/core

1bd982668449815fee2105478569f8e4b5670add

[ "Apache-2.0" ]

11,956

2016-04-13T18:42:31.000Z

2020-03-02T09:32:12.000Z

"""The yamaha component."""

14

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0.72

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null

0

1

0

null

0

1

0

4

92acbec0dee8327a8954e718ced043083c7ceb07

66

py

Python

Python/CV/practice_image.py

vbsteja/code

0c8f4dc579f5de21b6c55fe6e65c3c8eb5473687

[ "Apache-2.0" ]

null

Python/CV/practice_image.py

vbsteja/code

0c8f4dc579f5de21b6c55fe6e65c3c8eb5473687

[ "Apache-2.0" ]

null

Python/CV/practice_image.py

vbsteja/code

0c8f4dc579f5de21b6c55fe6e65c3c8eb5473687

[ "Apache-2.0" ]

null

import cv2 as cv image = cv.imread("jurassic-park-tour-jeep.jpg")

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1

null

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2b7dcbd0ecfe534f8894fedfc77786e2f7267a8a

46

py

Python

29/02/5.py

pylangstudy/201705

c69de524faa67fa2d96267d5a51ed9794208f0e4

[ "CC0-1.0" ]

null

29/02/5.py

pylangstudy/201705

c69de524faa67fa2d96267d5a51ed9794208f0e4

[ "CC0-1.0" ]

38

2017-05-25T07:08:48.000Z

2017-05-31T01:42:41.000Z

29/02/5.py

pylangstudy/201705

c69de524faa67fa2d96267d5a51ed9794208f0e4

[ "CC0-1.0" ]

null

a = 'True!!' if True else 'False...' print(a)

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null

0

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2bcc0807222452be5cdc5380f61055232032ec90

101

py

Python

auditlog_tests/apps.py

washdrop/django-auditlog

b0717a52d3883a03f0f0ddcc7b5329924a81c423

[ "MIT" ]

252

2020-09-23T13:32:49.000Z

2022-03-29T18:38:59.000Z

auditlog_tests/apps.py

washdrop/django-auditlog

b0717a52d3883a03f0f0ddcc7b5329924a81c423

[ "MIT" ]

121

2020-09-23T12:56:39.000Z

2022-03-31T06:59:09.000Z

auditlog_tests/apps.py

washdrop/django-auditlog

b0717a52d3883a03f0f0ddcc7b5329924a81c423

[ "MIT" ]

89

2020-09-25T07:22:52.000Z

2022-03-29T07:59:35.000Z

from django.apps import AppConfig class AuditlogTestConfig(AppConfig): name = "auditlog_tests"

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2bea204df6bbe0093583f0b468788cce6f4a0d33

412

py

Python

running_modes/transfer_learning/logging/transfer_learning_logger.py

marco-foscato/Lib-INVENT

fe6a65ab7165abd87b25752a6b4208c8703d11f7

[ "Apache-2.0" ]

26

2021-04-30T23:21:17.000Z

2022-03-10T06:33:11.000Z

running_modes/transfer_learning/logging/transfer_learning_logger.py

marco-foscato/Lib-INVENT

fe6a65ab7165abd87b25752a6b4208c8703d11f7

[ "Apache-2.0" ]

6

2021-10-03T08:35:48.000Z

2022-03-24T09:57:39.000Z

running_modes/transfer_learning/logging/transfer_learning_logger.py

marco-foscato/Lib-INVENT

fe6a65ab7165abd87b25752a6b4208c8703d11f7

[ "Apache-2.0" ]

10

2021-04-28T14:08:17.000Z

2022-03-04T04:18:13.000Z

from running_modes.transfer_learning.logging.local_transfer_learning_logger import LocalTransferLearningLogger from running_modes.transfer_learning.logging.base_transfer_learning_logger import BaseTransferLearningLogger class TransferLearningLogger: def __new__(cls, logging_path: str, weights: bool=False) -> BaseTransferLearningLogger: return LocalTransferLearningLogger(logging_path, weights)

41.2

110

0.86165

41

412

8.268293

0.560976

0.188791

0.094395

0.141593

0.230089

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0

null

0

1

0

null

0

1

0

4

920dbf71aec29dfad4e88ea2b95c4242c0bc06d6

27

py

Python

plugins/builtin/help/__init__.py

Alternative-Profit/Ubot

529514307c5431144fd56f6aba928dce1e880d93

[ "Apache-2.0" ]

1

2022-01-04T11:36:06.000Z

plugins/builtin/help/__init__.py

Alternative-Profit/Ubot

529514307c5431144fd56f6aba928dce1e880d93

[ "Apache-2.0" ]

1

2022-01-08T20:18:50.000Z

plugins/builtin/help/__init__.py

Alternative-Profit/Ubot

529514307c5431144fd56f6aba928dce1e880d93

[ "Apache-2.0" ]

3

2022-01-08T20:10:47.000Z

2022-03-12T08:09:32.000Z

"""docs of all commands"""

13.5

26

0.62963

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27

4.25

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1

27

0.73913

0.740741

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null

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null

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null

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null

true

0

null

1

0

null

0

1

0

null

0

1

0

4

9212dec5bf8ac4d39ccfd338820ac3a49671c273

1,433

py

Python

src/camguard/bridge_impl.py

matt-hires/camguard

dde59289b8af105b8ed7ef1d8619747528c5b0a3

[ "MIT" ]

3

2021-12-06T18:26:12.000Z

2022-01-14T10:22:12.000Z

src/camguard/bridge_impl.py

matt-hires/camguard

dde59289b8af105b8ed7ef1d8619747528c5b0a3

[ "MIT" ]

null

src/camguard/bridge_impl.py

matt-hires/camguard

dde59289b8af105b8ed7ef1d8619747528c5b0a3

[ "MIT" ]

null

from abc import ABC, abstractmethod from typing import Any, Callable, List # Handler Bridge class MotionHandlerImpl(ABC): """abstract base class for motion handler implementations """ @abstractmethod def handle_motion(self) -> Any: pass @abstractmethod def shutdown(self) -> None: pass @property @abstractmethod def id(self) -> int: pass # Detector Bridge class MotionDetectorImpl(ABC): """abstract base class for motion detector implementations """ @abstractmethod def register_handler(self, handler: Callable[..., None]) -> None: pass @abstractmethod def shutdown(self) -> None: pass @property @abstractmethod def id(self) -> int: pass # FileStorage Bridge class FileStorageImpl(ABC): """abstract base class for file storage implementations """ @abstractmethod def authenticate(self) -> None: pass @abstractmethod def start(self) -> None: pass @abstractmethod def stop(self) -> None: pass @abstractmethod def enqueue_files(self, files: List[str]) -> None: pass @property @abstractmethod def id(self) -> int: pass class MailClientImpl(ABC): """abstract base class for mail notification implementations """ @abstractmethod def send_mail(self, files: List[str]) -> None: pass

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6.17931

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0

1

0

4

a63277f2a6f3b33c2f1f2f60d18be2a09728833e

123

py

Python

2. Implementation/19. The Hurdle Race.py

trentandraka/Hackerrank-Algorithm-Solutions

a352070b39589931d9ece35bac6b7680bdfee9eb

[ "MIT" ]

null

2. Implementation/19. The Hurdle Race.py

trentandraka/Hackerrank-Algorithm-Solutions

a352070b39589931d9ece35bac6b7680bdfee9eb

[ "MIT" ]

5

2018-10-19T05:43:42.000Z

2018-10-24T09:05:55.000Z

2. Implementation/19. The Hurdle Race.py

trentandraka/Hackerrank-Algorithm-Solutions

a352070b39589931d9ece35bac6b7680bdfee9eb

[ "MIT" ]

22

2018-10-19T06:06:28.000Z

2021-04-15T00:28:11.000Z

n, k = map(int, input().split(' ')) arr = list(map(int, input().split(' '))) print ("0" if max(arr)-k<=0 else max(arr)-k)

24.6

44

0.552846

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123

2.956522

0.565217

0.176471

0.323529

0.470588

0

0.019048

0.146341

123

4

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0

null

0

1

0

1

0

null

0

4

a650216f18ede7b81c36d61bbea4e6a84c0c3bc5

77

py

Python

csie/10compiler/4a/test.py

dk00/old-stuff

e1184684c85fe9bbd1ceba58b94d4da84c67784e

[ "Unlicense" ]

null

csie/10compiler/4a/test.py

dk00/old-stuff

e1184684c85fe9bbd1ceba58b94d4da84c67784e

[ "Unlicense" ]

null

csie/10compiler/4a/test.py

dk00/old-stuff

e1184684c85fe9bbd1ceba58b94d4da84c67784e

[ "Unlicense" ]

null

print 'int ', for i in range(1,65538): print 'a%d = %d,' % (i,i*2), print

12.833333

30

0.532468

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77

2.5625

0.6875

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0.220779

77

5

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null

0

null

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null

0

1

0

null

0

1

0

1

0

4

a65e7e5ac2a5a6aaff5ef556d0b3182ec6fd3319

135

py

Python

images/test.py

Dmendoza3/Phyton

e6c563609724b2dadcd767d2bfc291090ac2f58e

[ "MIT" ]

null

images/test.py

Dmendoza3/Phyton

e6c563609724b2dadcd767d2bfc291090ac2f58e

[ "MIT" ]

null

images/test.py

Dmendoza3/Phyton

e6c563609724b2dadcd767d2bfc291090ac2f58e

[ "MIT" ]

null

x = 344444444 b0,b1,b2,b3 = [c for c in x.to_bytes(4,"big")] y = b0 << 24 | b1 << 16 | b2 << 8 | b3 << 0 print(b0,b1,b2,b3) print(y)

16.875

46

0.533333

31

135

2.290323

0.612903

0.112676

0.169014

0.225352

0

0.269231

0.22963

135

8

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0

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1

0

1

0

1

0

1

0

null

0

4

a66b00b11daf14ea285ab106d536593da5f09407

123

py

Python

data_salmon/dataset/__init__.py

htryppcook/data_salmon

8fecbba5db4433fa8472cd156bebde854b5eb692

[ "MIT" ]

null

data_salmon/dataset/__init__.py

htryppcook/data_salmon

8fecbba5db4433fa8472cd156bebde854b5eb692

[ "MIT" ]

null

data_salmon/dataset/__init__.py

htryppcook/data_salmon

8fecbba5db4433fa8472cd156bebde854b5eb692

[ "MIT" ]

null

from .dataset import Dataset from .output_formats import output_formats __all__ = [ 'Dataset', 'output_formats' ]

15.375

42

0.731707

14

123

5.928571

0.428571

0.46988

0

0.186992

123

8

43

15.375

0.83

0

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false

0

0.333333

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0.333333

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null

1

0

1

0

null

0

1

0

4

a67aa6d23239792cf5a910d9ba28d6c6aecbe284

419

py

Python

locators/login.py

rokimaru/selenium_opencart

b0a4ec0405e05d874111b284e609f7806289b9c2

[ "Apache-2.0" ]

null

locators/login.py

rokimaru/selenium_opencart

b0a4ec0405e05d874111b284e609f7806289b9c2

[ "Apache-2.0" ]

null

locators/login.py

rokimaru/selenium_opencart

b0a4ec0405e05d874111b284e609f7806289b9c2

[ "Apache-2.0" ]

null

from selenium.webdriver.common.by import By class LoginPageLocators: INPUT_EMAIL = (By.CSS_SELECTOR, "#input-email") INPUT_PASS = (By.CSS_SELECTOR, "#input-password") LOGIN_BUTTON = (By.CSS_SELECTOR, "input.btn") FORGOTTEN_PASSWORD = (By.XPATH, "//a[@class='list-group-item' and text()='Forgotten Password']") TRANSACTIONS = (By.XPATH, "//a[@class='list-group-item' and text()='Transactions']")

41.9

101

0.692124

54

419

5.240741

0.481481

0.053004

0.137809

0.190813

0.233216

0

0.131265

419

9

102

46.555556

0.777473

0

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0

1

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false

0.285714

0.142857

0

1

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null

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0

1

0

null

0

1

0

1

0

4

a67e98a5e60d9385ad52b609abb58c21b0d4f786

195

py

Python

app/characterbuilder/views.py

mohit4/Saga

fa2b9e2b557e8222b2b72028a448a3bec6a85e80

[ "MIT" ]

null

app/characterbuilder/views.py

mohit4/Saga

fa2b9e2b557e8222b2b72028a448a3bec6a85e80

[ "MIT" ]

null

app/characterbuilder/views.py

mohit4/Saga

fa2b9e2b557e8222b2b72028a448a3bec6a85e80

[ "MIT" ]

null

from django.shortcuts import render from django.views.generic import TemplateView # Create your views here. class HomePageView(TemplateView): """Home Page""" template_name = 'index.html'

27.857143

45

0.764103

24

195

6.166667

0.791667

0.135135

0

0.14359

195

7

46

27.857143

0.886228

0.174359

0

0.064103

0

1

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false

0

0.5

0

1

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null

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1

0

null

0

1

0

1

0

4

a68e7dccf0dbdbdfbcef2539ec0696c8f8b2bec7

9,695

py

Python

v0/aia_eis_v0/ml_sl/svm/svm_ovr_main.py

DreamBoatOve/aia_eis

458b4d29846669b10db4da1b3e86c0b394614ceb

[ "MIT" ]

1

2022-03-02T12:57:19.000Z

v0/aia_eis_v0/ml_sl/svm/svm_ovr_main.py

DreamBoatOve/aia_eis

458b4d29846669b10db4da1b3e86c0b394614ceb

[ "MIT" ]

null

v0/aia_eis_v0/ml_sl/svm/svm_ovr_main.py

DreamBoatOve/aia_eis

458b4d29846669b10db4da1b3e86c0b394614ceb

[ "MIT" ]

null

import sys sys.path.append('../../') from ml_sl.ml_critrions import cal_accuracy, cal_kappa from utils.file_utils.filename_utils import get_date_prefix from utils.file_utils.dataset_reader_pack.ml_dataset_reader import get_T_V_T_dataset from ml_sl.svm.multiclass_svm_0 import Multiclass_SVM """ SVM Linear Adjustable parameters: C: 1e-5 ~ 1e5, step factor 10 tol, default 0.01 max_iter: 1000 ~ 9000, step size 2000 Poly Adjustable parameters: C: 1e-5 ~ 1e5, step factor 10 tol, default 0.01 max_iter: 1000 ~ 9000, step size 2000 power: 2 ~ 10, step size 1 constant: default 1 qua_coe: 1e-5 ~ 1e5, step factor 10 Rbf Adjustable parameters: C: 1e-5 ~ 1e5, step factor 10 tol: default 0.01 max_iter: 1000 ~ 9000, step size 2000 sigma: 1e-5 ~ 1e5, step factor 10 """ training_dataset, validation_dataset, test_dataset = get_T_V_T_dataset(file_path='../../datasets/ml_datasets/normed') # ---------------- casual test of Multiclass-SVM (linear kernel)---------------- def svm_ovr_linear_tr_va(svm_para_dict, kernel_para_dict): global training_dataset, validation_dataset vali_data_list = [] vali_label_list = [] for vali in validation_dataset: vali_label_list.append(vali[0]) vali_data_list.append(vali[1]) multi_svm = Multiclass_SVM(svm_para_dict=svm_para_dict, kernel_para_dict=kernel_para_dict,\ unlabeled_dataset_list=vali_data_list, labeled_dataset_list=training_dataset,\ label_list=[2,4,5,6,7,8,9]) svm_model_pickle_name = get_date_prefix()+'svm_ovr_linear_test_pickle.file' multi_svm.create_svm_ovr_classifer(svm_model_pickle_name) sample_label_prob_dict_list = multi_svm.classify_ovr(svm_model_pickle_name) acc = cal_accuracy(sample_label_prob_dict_list, vali_label_list) kappa = cal_kappa(sample_label_prob_dict_list, vali_label_list) print('Accuracy={0}, Kappa={1}'.format(acc, kappa)) # if __name__ == '__main__': # svm_para_dict = {'C': 10, 'max_iter':1000} # kernel_para_dict = {'type':'linear', 'paras':None} # svm_ovr_linear_tr_va(svm_para_dict, kernel_para_dict) # R(RC)_IS_lin-kk_res.txt: Accuracy=0.13829787234042554, Kappa=0.01957249549317538 # ---------------- casual test of Multiclass-SVM (linear kernel)---------------- # ---------------- casual test of Multiclass-SVM (Poly kernel)---------------- def svm_ovr_poly_tr_va(svm_para_dict, kernel_para_dict): global training_dataset, validation_dataset vali_data_list = [] vali_label_list = [] for vali in validation_dataset: vali_label_list.append(vali[0]) vali_data_list.append(vali[1]) multi_svm = Multiclass_SVM(svm_para_dict=svm_para_dict, kernel_para_dict=kernel_para_dict,\ unlabeled_dataset_list=vali_data_list, labeled_dataset_list=training_dataset,\ label_list=[2,4,5,6,7,8,9]) svm_model_pickle_name = get_date_prefix()+'svm_ovr_poly_test_pickle.file' multi_svm.create_svm_ovr_classifer(svm_model_pickle_name) sample_label_prob_dict_list = multi_svm.classify_ovr(svm_model_pickle_name) acc = cal_accuracy(sample_label_prob_dict_list, vali_label_list) kappa = cal_kappa(sample_label_prob_dict_list, vali_label_list) print('Accuracy={0}, Kappa={1}'.format(acc, kappa)) # if __name__ == '__main__': # svm_para_dict = {'C': 10, 'max_iter':1000} # kernel_para_dict = {'type':'poly', 'paras':[2,1,1]} # svm_ovr_poly_tr_va(svm_para_dict, kernel_para_dict) # R(RC)_IS_lin-kk_res.txt: Accuracy=0.1276595744680851, Kappa=-0.020251489080079454 # ---------------- casual test of Multiclass-SVM (Poly kernel)---------------- # ---------------- casual test of Multiclass-SVM (Rbf kernel)---------------- def svm_ovr_rbf_tr_va(svm_para_dict, kernel_para_dict): global training_dataset, validation_dataset vali_data_list = [] vali_label_list = [] for vali in validation_dataset: vali_label_list.append(vali[0]) vali_data_list.append(vali[1]) multi_svm = Multiclass_SVM(svm_para_dict=svm_para_dict, kernel_para_dict=kernel_para_dict,\ unlabeled_dataset_list=vali_data_list, labeled_dataset_list=training_dataset,\ label_list=[2,4,5,6,7,8,9]) svm_model_pickle_name = get_date_prefix() + 'svm_ovr_rbf_test_pickle.file' multi_svm.create_svm_ovr_classifer(svm_model_pickle_name) sample_label_prob_dict_list = multi_svm.classify_ovr(svm_model_pickle_name) acc = cal_accuracy(sample_label_prob_dict_list, vali_label_list) kappa = cal_kappa(sample_label_prob_dict_list, vali_label_list) print('Accuracy={0}, Kappa={1}'.format(acc, kappa)) # if __name__ == '__main__': # svm_para_dict = {'C': 10, 'max_iter':1000} # kernel_para_dict = {'type':'rbf', 'paras': 10} # svm_ovr_rbf_tr_va(svm_para_dict, kernel_para_dict) # R(RC)_IS_lin-kk_res.txt: Accuracy=0.22340425531914893, Kappa=0.1066267413097253 # ---------------- casual test of Multiclass-SVM (Rbf kernel)---------------- # ---------------- Train SVM on TV and Test on Test-dataset ---------------- def svm_ovr_TV_te(svm_para_dict, kernel_para_dict): global training_dataset, validation_dataset, test_dataset TV_dataset = training_dataset + validation_dataset te_data_list = [] te_label_list = [] for te in test_dataset: te_label_list.append(te[0]) te_data_list.append(te[1]) # Repeat for 10 times for i in range(10): """ 2020_05_08_svm_linear_C=1e-05_iter=1000_pickle_0.file 2020_05_08_svm_poly_C=0.01_iter=1000_P=2_q=1_pickle_0.file 2020_05_08_svm_rbf_C=0.0001_iter=1000_sigma=0.0001_pickle_9.file """ multi_svm = Multiclass_SVM(svm_para_dict=svm_para_dict, kernel_para_dict=kernel_para_dict, \ unlabeled_dataset_list=te_data_list, labeled_dataset_list=TV_dataset, \ label_list=[2, 4, 5, 6, 7, 8, 9]) kernel_type = kernel_para_dict['type'] svm_model_pickle_name = get_date_prefix() if kernel_type == 'linear': C_str = str(svm_para_dict['C']) iter_str = str(svm_para_dict['max_iter']) svm_model_pickle_name += 'svm_ovr_final_{0}_C={1}_iter={2}_pickle_{3}.file'.format(kernel_type, C_str, iter_str, str(i)) elif kernel_type == 'poly': C_str = str(svm_para_dict['C']) iter_str = str(svm_para_dict['max_iter']) para_list = kernel_para_dict['paras'] q_str = str(para_list[1]) svm_model_pickle_name += 'svm_ovr_final_{0}_C={1}_iter={2}_q={3}_pickle_{4}.file'.format(kernel_type, C_str, iter_str, q_str, str(i)) elif kernel_type == 'rbf': C_str = str(svm_para_dict['C']) iter_str = str(svm_para_dict['max_iter']) sigma_str = str(kernel_para_dict['paras']) svm_model_pickle_name += 'svm_ovr_final_{0}_C={1}_iter={2}_sigma={3}_pickle_{4}.file'.format(kernel_type, C_str, sigma_str, iter_str, str(i)) multi_svm.create_svm_ovr_classifer(svm_model_pickle_name) sample_label_prob_dict_list = multi_svm.classify_ovr(svm_model_pickle_name) acc = cal_accuracy(sample_label_prob_dict_list, te_label_list) kappa = cal_kappa(sample_label_prob_dict_list, te_label_list) print('Accuracy={0}, Kappa={1}'.format(acc, kappa)) if __name__ == '__wmain__': # ---------------------- SVM_OvR-Linear ---------------------- # ------------- iter = 5000, C = 0.1 ------------- # svm_para_dict = {'C': 0.1, 'max_iter': 5000} # kernel_para_dict = {'type':'linear', 'paras':None} # svm_ovr_TV_te(svm_para_dict, kernel_para_dict) # ------------- iter = 5000, C = 0.1 ------------- # ---------------------- SVM_OvR-Linear ---------------------- # ---------------------- SVM_OvR-Poly ---------------------- # ------------- iter = 3000, C = 1, q = 100 ------------- # In poly, the power is default as 2, () ** q(=2); and the constant is default as 1 # svm_para_dict = {'C': 1, 'max_iter' : 3000} # kernel_para_dict = {'type' : 'poly', 'paras' : [2, 1, 100]} # svm_ovr_TV_te(svm_para_dict, kernel_para_dict) # ------------- iter = 3000, C = 1, q = 100 ------------- # ---------------------- SVM_OvR-Poly ---------------------- # ---------------------- SVM_OvR-RBF ---------------------- # ------------- iter = 7000, C = 0.01, sigma = 100000 ------------- # svm_para_dict = {'C' : 0.01, 'max_iter' : 7000} # kernel_para_dict = {'type' : 'rbf', 'paras' : 100000} # svm_ovr_TV_te(svm_para_dict, kernel_para_dict) # ------------- iter = 7000, C = 0.01, sigma = 100000 ------------- # ------------- iter = 5000, C = 0.001, sigma = 10 ------------- # svm_para_dict = {'C': 0.001, 'max_iter': 5000} # kernel_para_dict = {'type': 'rbf', 'paras': 10} # svm_ovr_TV_te(svm_para_dict, kernel_para_dict) # ------------- iter = 5000, C = 0.001, sigma = 10 ------------- # ------------- iter = 5000, C = 0.01, sigma = 0.001 ------------- svm_para_dict = {'C': 0.01, 'max_iter': 5000} kernel_para_dict = {'type': 'rbf', 'paras': 0.001} svm_ovr_TV_te(svm_para_dict, kernel_para_dict) # ------------- iter = 5000, C = 0.01, sigma = 0.001 ------------- # ---------------------- SVM_OvR-RBF ---------------------- # python svm_ovr_main.py # ---------------- Train SVM on TV and Test on Test-dataset ----------------

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null

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null

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4

a6abe108e25f70e9849b7f6c804af61e7f5c0c73

218

py

Python

profiles/forms/quota_form.py

LaudateCorpus1/squest

98304f20c1d966fb3678d348ffd7c5be438bb6be

[ "Apache-2.0" ]

null

profiles/forms/quota_form.py

LaudateCorpus1/squest

98304f20c1d966fb3678d348ffd7c5be438bb6be

[ "Apache-2.0" ]

null

profiles/forms/quota_form.py

LaudateCorpus1/squest

98304f20c1d966fb3678d348ffd7c5be438bb6be

[ "Apache-2.0" ]

1

2022-03-24T03:37:12.000Z

from Squest.utils.squest_model_form import SquestModelForm from profiles.models import Quota class QuotaForm(SquestModelForm): class Meta: model = Quota fields = ["name", "attribute_definitions"]

24.222222

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0

1

0

4

a6b280b3a28a600b1a22e6682b826ae7a3b47f60

61

py

Python

prom2teams/__init__.py

cloudstrike/prom2teams

5fb387f97bb4e44677ae8d3efcfc7200a8041eea

[ "Apache-2.0" ]

180

2017-09-04T21:07:00.000Z

2022-03-10T11:05:02.000Z

prom2teams/__init__.py

cloudstrike/prom2teams

5fb387f97bb4e44677ae8d3efcfc7200a8041eea

[ "Apache-2.0" ]

162

2017-08-24T08:54:33.000Z

2022-03-26T20:08:04.000Z

prom2teams/__init__.py

cloudstrike/prom2teams

5fb387f97bb4e44677ae8d3efcfc7200a8041eea

[ "Apache-2.0" ]

75

2017-11-08T11:04:31.000Z

2022-03-04T12:34:37.000Z

import os root = os.path.abspath(os.path.dirname(__file__))

15.25

49

0.754098

10

61

4.2

0.7

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0

0.098361

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1

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null

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1

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4

a6d1ece4f824494efdd649c8c5b26dd370cafa1f

555

py

Python

meiduo_mall/utils/fastdfs/storage.py

zzZaida/meiduo_backend

c4f94ea7f9c47a08d3e37fb0ac2c1ec1dcf2c18b

[ "MIT" ]

null

meiduo_mall/utils/fastdfs/storage.py

zzZaida/meiduo_backend

c4f94ea7f9c47a08d3e37fb0ac2c1ec1dcf2c18b

[ "MIT" ]

4

2020-05-11T20:27:56.000Z

2021-11-02T15:46:08.000Z

meiduo_mall/utils/fastdfs/storage.py

zzZaida/meiduo_backend

c4f94ea7f9c47a08d3e37fb0ac2c1ec1dcf2c18b

[ "MIT" ]

null

from django.core.files.storage import Storage class FastDFSStorage(Storage): """自定义文件存储系统""" def _save(self, name, content, max_length=None): pass def _open(self, name, mode='rb'): pass def url(self, name): # name=Remote file_id #'Remote file_id': 'group1/M00/00/02/wKjllFzhEE6AFbTWAALd0X8OZb4408.jpg', #http://192.168.229.148:8888/+group1/M00/00/02/wKjllFzhEE6AFbTWAALd0X8OZb4408.jpg # return 'http://192.168.229.148:8888/' + name return 'http://image.meiduo.site:8888/' + name

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null

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1

0

1

0

1

0

4

a6d55f92462c093fe73c53ea9214e4919d54db57

8,339

py

Python

ml/rl/common.py

xiaoshenxian/mlxsx

a20558482f0d71bdd099aaff8be16ac29d4b98e2

[ "Apache-2.0" ]

2

2019-06-16T03:06:52.000Z

2019-06-21T03:38:12.000Z

ml/rl/common.py

xiaoshenxian/mlxsx

a20558482f0d71bdd099aaff8be16ac29d4b98e2

[ "Apache-2.0" ]

null

ml/rl/common.py

xiaoshenxian/mlxsx

a20558482f0d71bdd099aaff8be16ac29d4b98e2

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- import sys import time import tensorflow as tf import numpy as np class RLComponent: def get_eval_op(self): raise NotImplementedError('RLComponent::get_eval_op is not implemented!') def get_target_op(self): raise NotImplementedError('RLComponent::get_target_op is not implemented!') def get_replace_target_op(self): raise NotImplementedError('RLComponent::get_replace_target_op is not implemented!') def get_trainable_variables(self): raise NotImplementedError('RLComponent::get_trainable_variables is not implemented!') class RL: def choose_action(self, sess, random_threshold=1, prob_random_threshold=1, random_sigma=None): action_prob_list, continuous_action_list, action_lower, action_upper=sess.run([self.discrete_action_op, self.continuous_action_op, [], []] if random_threshold>=1 or random_sigma is None else [self.discrete_action_op, self.continuous_action_op, self.get_continuous_lower_op(), self.get_continuous_upper_op()]) discrete_action_list=[] for action_prob, num_actions in zip(action_prob_list, self.discrete_action_num_list): shape=action_prob.shape action_shape=shape[:-1] rand_score=np.random.uniform() action=np.where(rand_score<random_threshold , np.argmax(action_prob, axis=-1) , np.where(rand_score<random_threshold+(1-random_threshold)*prob_random_threshold , np.array([np.random.choice(num_actions, p=probs) for probs in np.reshape(action_prob, (-1, num_actions))], dtype='int32').reshape(action_shape) , np.random.randint(num_actions, size=np.prod(action_shape)).reshape(action_shape))) discrete_action_list.append(action) if random_sigma is not None: actions=continuous_action_list[0] shape=actions.shape rand=np.random.uniform(0, 1, size=np.prod(shape)).reshape(shape) idx=np.where(rand>=random_threshold) actions[idx]=np.random.normal(actions[idx], random_sigma) actions=np.transpose(actions, axes=[-1]+list(range(len(shape)-1))) sh=actions.shape actions=np.clip(actions.reshape((sh[0], -1)), action_lower.reshape((sh[0], 1)), action_upper.reshape((sh[0], 1))) actions=np.transpose(actions.reshape(sh), axes=list(range(1, len(sh)))+[0]) continuous_action_list=[actions] return discrete_action_list+continuous_action_list, action_prob_list def get_discrete_prob(self, sess): return sess.run(self.discrete_action_op) def choose_action_for_placeholder(self, sess, feed_dict, random_threshold=1, prob_random_threshold=1, random_sigma=None): action_prob_list, continuous_action_list, action_lower, action_upper=sess.run([self.discrete_action_op, self.continuous_action_op, [], []] if random_threshold>=1 or random_sigma is None else [self.discrete_action_op, self.continuous_action_op, self.get_continuous_lower_op(), self.get_continuous_upper_op()], feed_dict=feed_dict) discrete_action_list=[] for action_prob, num_actions in zip(action_prob_list, self.discrete_action_num_list): shape=action_prob.shape action_shape=shape[:-1] rand_score=np.random.uniform() action=np.where(rand_score<random_threshold , np.argmax(action_prob, axis=-1) , np.where(rand_score<random_threshold+(1-random_threshold)*prob_random_threshold , np.array([np.random.choice(num_actions, p=probs) for probs in np.reshape(action_prob, (-1, num_actions))], dtype='int32').reshape(action_shape) , np.random.randint(num_actions, size=np.prod(action_shape)).reshape(action_shape))) discrete_action_list.append(action) if random_sigma is not None: actions=continuous_action_list[0] shape=actions.shape rand=np.random.uniform(0, 1, size=np.prod(shape)).reshape(shape) idx=np.where(rand>=random_threshold) actions[idx]=np.random.normal(actions[idx], random_sigma) actions=np.transpose(actions, axes=[-1]+list(range(len(shape)-1))) sh=actions.shape actions=np.clip(actions.reshape((sh[0], -1)), action_lower.reshape((sh[0], 1)), action_upper.reshape((sh[0], 1))) actions=np.transpose(actions.reshape(sh), axes=list(range(1, len(sh)))+[0]) continuous_action_list=[actions] return discrete_action_list+continuous_action_list, action_prob_list def get_discrete_prob_for_placeholder(self, sess, feed_dict): return sess.run(self.discrete_action_op, feed_dict=feed_dict) def get_continuous_lower_op(self): raise NotImplementedError('RL::get_continuous_lower_op is not implemented!') def get_continuous_upper_op(self): raise NotImplementedError('RL::get_continuous_upper_op is not implemented!') def set_summary(self, sess, log_dir, verbose): self.summary=tf.summary.merge_all() self.summary_writer=tf.summary.FileWriter(log_dir, sess.graph) self.summary_verbose=verbose self.total_step=0 def run_summary(self, sess): if self.summary is not None: if self.total_step%self.summary_verbose==0: summary_str=sess.run(self.summary) self.summary_writer.add_summary(summary_str, self.total_step) sys.stderr.write('summary wrote at total_step={}\n'.format(self.total_step)) self.total_step+=1 def run_summary_for_placeholder(self, sess, feed_dict): if self.summary is not None: if self.total_step%self.summary_verbose==0: summary_str=sess.run(self.summary, feed_dict=feed_dict) self.summary_writer.add_summary(summary_str, self.total_step) sys.stderr.write('summary wrote at total_step={}\n'.format(self.total_step)) self.total_step+=1 def run_sess_and_cost(self, sess, for_training, iters): self.replace_target(sess, iters) res=sess.run([self.cost, self.train_op] if for_training else [self.cost]) return res[0] def run_sess_and_cost_for_placeholder(self, sess, for_training, iters, feed_dict): self.replace_target(sess, iters) res=sess.run([self.cost, self.train_op] if for_training else [self.cost], feed_dict=feed_dict) return res[0] def replace_target(self, sess, iters): raise NotImplementedError('RL::replace_target is not implemented!') def run_epoch(self, sess, for_training, verbose=-1): start_time=time.time() costs=0.0 iters=0 try: while True: self.run_summary(sess) cost=self.run_sess_and_cost(sess, for_training, iters) costs+=cost iters+=1 if verbose>=0 and iters%verbose==0: sys.stderr.write('step {0} avg cost: {1:.3f} current cost: {2:.3f} speed: {3:.0f} sps\n'.format(iters, costs/iters, cost, iters*self.batch_size/max(time.time()-start_time, 1))) except tf.errors.OutOfRangeError: pass return costs/(iters if iters!=0 else 1) def run_training(self, sess, verbose=-1): return self.run_epoch(sess, self.train_op, verbose) def run_epoch_for_placeholder(self, sess, data_iterator, for_training, verbose=-1): start_time=time.time() costs=0.0 iters=0 for step, (feed_dict) in enumerate(data_iterator): self.run_summary(sess) cost=self.run_sess_and_cost_for_placeholder(sess, for_training, iters, feed_dict) costs+=cost iters+=1 if verbose>=0 and step%verbose==0: print("step {0} avg cost: {1:.3f} current cost: {2:.3f} speed: {3:.0f} sps".format(step, costs/iters, cost, iters*self.batch_size/(time.time()-start_time))) return costs/(iters if iters!=0 else 1) def run_training_for_placeholder(self, sess, data_iterator, verbose=-1): return self.run_epoch_for_placeholder(sess, self.train_op, data_iterator, verbose)

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null

0

1

0

1

0

null

0

4

5b74ceabe1f5ec5b3b97bbc34a184430690d5e12

184

py

Python

dace/libraries/pblas/nodes/__init__.py

Walon1998/dace

95ddfd3e9a5c654f0f0d66d026e0b64ec0f028a0

[ "BSD-3-Clause" ]

227

2019-03-15T23:39:06.000Z

2022-03-30T07:49:08.000Z

dace/libraries/pblas/nodes/__init__.py

Walon1998/dace

95ddfd3e9a5c654f0f0d66d026e0b64ec0f028a0

[ "BSD-3-Clause" ]

834

2019-07-31T22:49:31.000Z

2022-03-28T14:01:32.000Z

dace/libraries/pblas/nodes/__init__.py

Walon1998/dace

95ddfd3e9a5c654f0f0d66d026e0b64ec0f028a0

[ "BSD-3-Clause" ]

64

2019-03-19T05:40:37.000Z

2022-03-11T15:02:42.000Z

36.8

75

0.820652

25

184

6.04

0.76

0

0.050314

0.13587

184

4

76

46

0.899371

0.396739

0

1

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true

0

1

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1

0

1

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null

0

1

0

null

0

1

0

1

0

4

5b7f74ef8c6a9d44de2851d8b7f832671e9f73c3

1,855

py

Python

st_like.py

XDASADX/InstaStatPy

1454486bfd0674a87a7ab02240eabb038b8bce4b

[ "Apache-2.0" ]

null

st_like.py

XDASADX/InstaStatPy

1454486bfd0674a87a7ab02240eabb038b8bce4b

[ "Apache-2.0" ]

null

st_like.py

XDASADX/InstaStatPy

1454486bfd0674a87a7ab02240eabb038b8bce4b

[ "Apache-2.0" ]

null

import re import requests import os code_addr='https://instagram.com/p/' #os.mkdir(os.getcwd()+'\\data') id='natgeo' d_f=open(os.getcwd()+'\\data\\'+'stat_'+id+'.csv','w') d_f.write('Instagram上'+id+'的统计\n') d_f.write('like'+'\n') r=requests.get('https://www.instagram.com/'+id+'/?hl=en') con=r.content start_i=r'"start_cursor":"[0-9]*"' end_i=r'end_cursor":"[0-9]*"' like=r'"likes":{"count":[0-9]*},"' code_i=r'{"code":"[\w\-]+"' start_cursor=re.findall(start_i,con.decode()) end_cursor=re.findall(end_i,con.decode()) like_list=re.findall(like,con.decode()) code_list=re.findall(code_i,con.decode()) start_var=start_cursor[0] start_var=start_var[16:-1] end_var=end_cursor[0] end_var=end_var[13:-1] like_list_f=[] code_list_f=[] print(code_list) print(len(code_list)) for i in range(0,len(like_list)): a=like_list[i] a=a[17:-3] like_list_f.append(a) d_f.write(a+',') b=code_list[i] b=b[9:-1] code_list_f.append(b) d_f.write(code_addr+b+'\n') pagenum=1 while(start_var!=end_var): print("Page",(pagenum),"has been counted.") pagenum+=1 r=requests.get('https://www.instagram.com/'+id+'/?max_id='+end_var) con=r.content start_i=r'"start_cursor":"[0-9]*"' end_i=r'end_cursor":"[0-9]*"' like=r'"likes":{"count":[0-9]*},"' code_i=r'{"code":"[\w\-]+"' start_cursor=re.findall(start_i,con.decode()) end_cursor=re.findall(end_i,con.decode()) like_list=re.findall(like,con.decode()) code_list=re.findall(code_i,con.decode()) start_var=start_cursor[0] start_var=start_var[16:-1] end_var=end_cursor[0] end_var=end_var[13:-1] for i in range(0,len(like_list)): a=like_list[i] a=a[17:-3] like_list_f.append(a) d_f.write(a+',') b=code_list[i] b=b[9:-1] code_list_f.append(b) d_f.write(code_addr+b+'\n') print (len(like_list_f)) d_f.write('=AVERAGE(A3:A'+str(len(like_list_f)+2)+')') d_f.close()

18.737374

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1

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null

0

4

5ba5834a837b3b864c5e141c71c18be7c64a3028

99

py

Python

code_all/day15/my_project02/main.py

testcg/python

4db4bd5d0e44af807d2df80cf8c8980b40cc03c4

[ "MIT" ]

null

code_all/day15/my_project02/main.py

testcg/python

4db4bd5d0e44af807d2df80cf8c8980b40cc03c4

[ "MIT" ]

null

code_all/day15/my_project02/main.py

testcg/python

4db4bd5d0e44af807d2df80cf8c8980b40cc03c4

[ "MIT" ]

null

# from 包 import 类 from skill_system import SkillManager manager = SkillManager() manager.func01()

16.5

37

0.787879

13

99

5.923077

0.692308

0.493506

0

0.023529

0.141414

99

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1

0

1

0

null

0

1

0

4

5bccd7e61ca8c853abd861f9c680bdfb7ad1d36b

97

py

Python

misclientes/apps.py

mrbrazzi/django-misclientes

8017cc67e243e4384c3f52ae73d06e16f8fb8d5b

[ "Apache-2.0" ]

5

2019-11-12T20:35:37.000Z

2022-03-11T15:02:48.000Z

misclientes/apps.py

mrbrazzi/django-misclientes

8017cc67e243e4384c3f52ae73d06e16f8fb8d5b

[ "Apache-2.0" ]

4

2019-11-11T15:33:42.000Z

2022-01-13T01:50:23.000Z

misclientes/apps.py

mrbrazzi/django-misclientes

8017cc67e243e4384c3f52ae73d06e16f8fb8d5b

[ "Apache-2.0" ]

4

2019-11-11T16:13:20.000Z

2020-04-02T18:32:06.000Z

from django.apps import AppConfig class MisclientesConfig(AppConfig): name = 'misclientes'

16.166667

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7.5

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0

1

0

null

0

1

0

1

0

4

5bcdf409d6844e51f9183ca141abd6b4d33b102b

184

py

Python

tests/test_compass.py

IQTLabs/gamutRF

f9d248581066f0f5175e60de63430a7d9ac5c97f

[ "Apache-2.0" ]

6

2021-09-30T21:14:45.000Z

2022-03-08T21:59:47.000Z

tests/test_compass.py

IQTLabs/gamutRF

f9d248581066f0f5175e60de63430a7d9ac5c97f

[ "Apache-2.0" ]

109

2021-10-19T21:04:59.000Z

2022-03-31T09:41:33.000Z

tests/test_compass.py

IQTLabs/gamutRF

f9d248581066f0f5175e60de63430a7d9ac5c97f

[ "Apache-2.0" ]

4

2021-09-28T17:09:03.000Z

2021-11-24T16:51:04.000Z

import sys import fake_rpi sys.modules['smbus2'] = fake_rpi.smbus from gamutrf import compass def test_compass_heading(): heading = compass.Heading() heading.get_heading()

15.333333

38

0.75

25

184

5.32

0.56

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0

0.006452

0.157609

184

11

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0

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0.428571

0

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null

0

1

0

null

0

1

0

4

5bd159b148fd0f04b6ddfcc92e7eb5f395f4e67d

3,505

py

Python

cmdb/forms.py

bopopescu/sbdb_new

52d57f2dd6e553f60a06c97e7a8631d41f8f2ea6

[ "Apache-2.0" ]

1

2018-12-27T02:30:44.000Z

cmdb/forms.py

Moniter123/adminOps

810fb1400584cdff98df5b0f26e6d4cc922b34f1

[ "Apache-2.0" ]

null

cmdb/forms.py

Moniter123/adminOps

810fb1400584cdff98df5b0f26e6d4cc922b34f1

[ "Apache-2.0" ]

1

2020-07-22T02:38:14.000Z

#! /usr/bin/env python # -*- coding: utf-8 -*- from django import forms from django.forms.widgets import * from .models import Host, Idc, HostGroup class AssetForm(forms.ModelForm): class Meta: model = Host exclude = ("id",) widgets = { 'hostname': TextInput(attrs={'class': 'form-control', 'style': 'width:530px;', 'placeholder': u'必填项'}), 'ip': TextInput(attrs={'class': 'form-control', 'style': 'width:530px;', 'placeholder': u'必填项'}), 'other_ip': TextInput(attrs={'class': 'form-control', 'style': 'width:530px;'}), 'group': Select(attrs={'class': 'form-control', 'style': 'width:530px;'}), 'asset_no': TextInput(attrs={'class': 'form-control', 'style': 'width:530px;'}), 'asset_type': Select(attrs={'class': 'form-control', 'style': 'width:530px;'}), 'status': Select(attrs={'class': 'form-control', 'style': 'width:530px;'}), 'os': TextInput(attrs={'class': 'form-control', 'style': 'width:530px;'}), 'vendor': TextInput(attrs={'class': 'form-control', 'style': 'width:530px;'}), 'cpu_model': TextInput(attrs={'class': 'form-control', 'style': 'width:530px;'}), 'cpu_num': TextInput(attrs={'class': 'form-control', 'style': 'width:530px;'}), 'memory': TextInput(attrs={'class': 'form-control', 'style': 'width:530px;'}), 'disk': TextInput(attrs={'class': 'form-control', 'style': 'width:530px;'}), 'sn': TextInput(attrs={'class': 'form-control', 'style': 'width:530px;'}), 'idc': Select(attrs={'class': 'form-control', 'style': 'width:530px;'}), 'position': TextInput(attrs={'class': 'form-control', 'style': 'width:530px;', 'placeholder': u'物理机写位置，虚机写宿主'}), 'memo': Textarea(attrs={'class': 'form-control', 'style': 'width:530px;'}), } class IdcForm(forms.ModelForm): def clean(self): cleaned_data = super(IdcForm, self).clean() value = cleaned_data.get('name') try: Idc.objects.get(name=value) self._errors['name'] = self.error_class(["%s的信息已经存在" % value]) except Idc.DoesNotExist: pass return cleaned_data class Meta: model = Idc exclude = ("id",) widgets = { 'name': TextInput(attrs={'class': 'form-control','style': 'width:450px;'}), 'address': TextInput(attrs={'class': 'form-control','style': 'width:450px;'}), 'tel': TextInput(attrs={'class': 'form-control','style': 'width:450px;'}), 'contact': TextInput(attrs={'class': 'form-control','style': 'width:450px;'}), 'contact_phone': TextInput(attrs={'class': 'form-control','style': 'width:450px;'}), 'ip_range': TextInput(attrs={'class': 'form-control','style': 'width:450px;'}), 'jigui': TextInput(attrs={'class': 'form-control','style': 'width:450px;'}), 'bandwidth': TextInput(attrs={'class': 'form-control','style': 'width:450px;'}), } class GroupForm(forms.ModelForm): def clean(self): cleaned_data = super(GroupForm, self).clean() value = cleaned_data.get('name') try: HostGroup.objects.get(name=value) self._errors['name'] = self.error_class(["%s的信息已经存在" % value]) except HostGroup.DoesNotExist: pass return cleaned_data class Meta: model = HostGroup exclude = ("id", )

44.935897

124

0.564907

366

3,505

5.363388

0.224044

0.127356

0.178299

0.267448

0.794702

0.776363

0.284259

0.157412

0

0.028003

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3,505

78

125

44.935897

0.695284

0.012268

0

0.322581

0

0.316383

0

1

0.032258

false

0.032258

0.048387

0

0.209677

0

null

0

1

0

1

0

null

0

4

751a4a5d6529fdc793e07cf84c2e4760a7ecdf7d

131

py

Python

jes/jes-v5.020-linux/demos/fib.py

utv-teaching/foundations-computer-science

568e19fd83a3355dab2814229f335abf31bfd7e9

[ "MIT" ]

null

jes/jes-v5.020-linux/demos/fib.py

utv-teaching/foundations-computer-science

568e19fd83a3355dab2814229f335abf31bfd7e9

[ "MIT" ]

null

jes/jes-v5.020-linux/demos/fib.py

utv-teaching/foundations-computer-science

568e19fd83a3355dab2814229f335abf31bfd7e9

[ "MIT" ]

null

def fib(i): count = 0 x = 0 y = 1 while count < i: count = count + 1 x, y = y, x + y return y

13.1

25

0.389313

22

131

2.318182

0.454545

0.235294

0

0.061538

0.503817

131

9

26

14.555556

0.723077

0

1

0.125

false

0

0.25

0

1

0

null

1

0

1

0

1

0

null

0

4

751eaf407fdfca01030f161d0a85cac1edf1d0a4

88

py

Python

000403StepPyThin/000403_02_03_Task_02_other_02_20200106.py

SafonovMikhail/python_000577

739f764e80f1ca354386f00b8e9db1df8c96531d

[ "Apache-2.0" ]

null

000403StepPyThin/000403_02_03_Task_02_other_02_20200106.py

SafonovMikhail/python_000577

739f764e80f1ca354386f00b8e9db1df8c96531d

[ "Apache-2.0" ]

null

000403StepPyThin/000403_02_03_Task_02_other_02_20200106.py

SafonovMikhail/python_000577

739f764e80f1ca354386f00b8e9db1df8c96531d

[ "Apache-2.0" ]

null

x = [x for x in range(int(input()),int(input()) + 1) if x % 3 == 0] print(sum(x)/len(x))

44

67

0.545455

20

88

2.4

0.65

0.333333

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0.041096

0.170455

88

2

68

44

0.616438

0

1

0

false

0

0.5

1

0

null

1

0

1

0

null

0

1

0

4

7547053c90304ec082b84ea351e30fcadb74f355

100

py

Python

login_history/apps.py

farhad0085/dj-user-login-history

3384ce977694c7b03c713a9dc0bc31490a140e87

[ "MIT" ]

null

login_history/apps.py

farhad0085/dj-user-login-history

3384ce977694c7b03c713a9dc0bc31490a140e87

[ "MIT" ]

null

login_history/apps.py

farhad0085/dj-user-login-history

3384ce977694c7b03c713a9dc0bc31490a140e87

[ "MIT" ]

null

from django.apps import AppConfig class LoginHistoryConfig(AppConfig): name = 'login_history'

16.666667

36

0.78

11

100

7

0.909091

0

0.15

100

5

37

20

0.905882

0

0.13

0

1

0

false

0

0.333333

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

4

754dbc4cc65cfc22e5aee3d0c0757504a2dbf0c2

97

py

Python

electivapp/apps/actividades/apps.py

AlanSanchezP/ElectivappServer

1bbb3ccbf33c685fcc0e3298d4ad4ed4d9059ce4

[ "MIT" ]

null

electivapp/apps/actividades/apps.py

AlanSanchezP/ElectivappServer

1bbb3ccbf33c685fcc0e3298d4ad4ed4d9059ce4

[ "MIT" ]

10

2019-02-14T03:40:30.000Z

2019-05-20T22:55:15.000Z

actividades/apps.py

fabianabarca/horas

526c065803f1487a39644eb54f65b7b4f3a036ee

[ "MIT" ]

1

2021-10-14T22:40:39.000Z

from django.apps import AppConfig class ActividadesConfig(AppConfig): name = 'actividades'

16.166667

35

0.773196

10

97

7.5

0.9

0

0.154639

97

5

36

19.4

0.914634

0

0.113402

0

1

0

false

0

0.333333

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

4

f373642774d12f21cc23829ed93050f225d3ed9a

74

py

Python

{{cookiecutter.project_slug + '.git'}}/src/{{cookiecutter.package_name}}/_vendored/__init__.py

douglasdaly/cookiecutter-pypackage

7150d91c74eb01da69ff3a24447667bf643a5de5

[ "MIT" ]

null

{{cookiecutter.project_slug + '.git'}}/src/{{cookiecutter.package_name}}/_vendored/__init__.py

douglasdaly/cookiecutter-pypackage

7150d91c74eb01da69ff3a24447667bf643a5de5

[ "MIT" ]

null

{{cookiecutter.project_slug + '.git'}}/src/{{cookiecutter.package_name}}/_vendored/__init__.py

douglasdaly/cookiecutter-pypackage

7150d91c74eb01da69ff3a24447667bf643a5de5

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ Vendored versions of required libraries. """

12.333333

40

0.608108

8

74

5.625

1

0

0.016393

0.175676

74

5

41

14.8

0.721311

0.851351

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

1

0

null

0

1

0

4

f3afaf9e9062d6dd90c48c593fe9091a1323543a

73

py

Python

applications/baseapp/mixins/__init__.py

ajitjasrotia/django-project-skeleton

70e3e06384dfb018f59b1af8c7c3febf2bbcd47c

[ "MIT" ]

48

2018-01-10T11:21:35.000Z

2021-09-08T23:28:07.000Z

applications/baseapp/mixins/__init__.py

ajitjasrotia/django-project-skeleton

70e3e06384dfb018f59b1af8c7c3febf2bbcd47c

[ "MIT" ]

26

2018-04-20T10:46:00.000Z

2019-09-21T06:47:13.000Z

applications/baseapp/mixins/__init__.py

ajitjasrotia/django-project-skeleton

70e3e06384dfb018f59b1af8c7c3febf2bbcd47c

[ "MIT" ]

20

2019-03-09T19:46:10.000Z

2022-03-27T14:57:03.000Z

# isort:skip_file # flake8: noqa from .html_debug import HtmlDebugMixin

14.6

38

0.794521

10

73

5.6

1

0

0.015873

0.136986

73

4

39

18.25

0.873016

0.383562

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

4

34680b7af5a24ff2ba091f8bfe4190aa269d5b51

108

py

Python

pygments_renderer/apps.py

c-bata/django-pygments-renderer

1e9f182c99e741f8c104e211592ca03e628f1363

[ "MIT" ]

null

pygments_renderer/apps.py

c-bata/django-pygments-renderer

1e9f182c99e741f8c104e211592ca03e628f1363

[ "MIT" ]

null

pygments_renderer/apps.py

c-bata/django-pygments-renderer

1e9f182c99e741f8c104e211592ca03e628f1363

[ "MIT" ]

null

from django.apps import AppConfig class PygmentsRendererConfig(AppConfig): name = 'pygments_renderer'

18

40

0.796296

11

108

7.727273

0.909091

0

0.138889

108

5

41

21.6

0.913978

0

0.157407

0

1

0

false

0

0.333333

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

4

caa661a0d0340fb61a6b9d9f223de364d719f2ba

60

py

Python

src/cobra/apps/svnkit/__init__.py

lyoniionly/django-cobra

2427e5cf74b7739115b1224da3306986b3ee345c

[ "Apache-2.0" ]

1

2015-01-27T08:56:46.000Z

src/cobra/apps/svnkit/__init__.py

lyoniionly/django-cobra

2427e5cf74b7739115b1224da3306986b3ee345c

[ "Apache-2.0" ]

null

src/cobra/apps/svnkit/__init__.py

lyoniionly/django-cobra

2427e5cf74b7739115b1224da3306986b3ee345c

[ "Apache-2.0" ]

null

default_app_config = 'cobra.apps.svnkit.config.SvnkitConfig'

60

0.85

8

60

6.125

0.875

0

0.033333

60

1

60

0.844828

0

0.606557

0

1

0

false

0

1

0

null

0

1

0

1

null

0

4

cacd67b46feb99c405c2dfdce686d95f8074414e

87

py

Python

pytest/03_testrun/test_mark.py

dramasamy/training

af7b9352b56c10aaa957062f24f1302a7a4c5797

[ "Apache-2.0" ]

1

2022-03-22T22:31:32.000Z

pytest/03_testrun/test_mark.py

dramasamy/training

af7b9352b56c10aaa957062f24f1302a7a4c5797

[ "Apache-2.0" ]

null

pytest/03_testrun/test_mark.py

dramasamy/training

af7b9352b56c10aaa957062f24f1302a7a4c5797

[ "Apache-2.0" ]

null

import pytest @pytest.mark.sanity def test_sample(): assert type(1) == type(int())

17.4

33

0.689655

13

87

4.538462

0.846154

0

0.013514

0.149425

87

4

34

21.75

0.783784

0

0.25

1

0.25

true

0

0.25

0

0.5

0

1

0

null

0

1

0

null

0

1

0

4

cad3545d87620b1e158d7e04a8277c3c27c46a38

627

py

Python

home/migrations/0002_auto_20200921_1020.py

1705095/HackNsu2_TEAM_RETURN_ZERO

eb5594619754f9ef98bc8383f7ed3f7f553ce703

[ "Apache-2.0" ]

1

2021-05-03T10:22:05.000Z

home/migrations/0002_auto_20200921_1020.py

1705095/HackNsu2_TEAM_RETURN_ZERO

eb5594619754f9ef98bc8383f7ed3f7f553ce703

[ "Apache-2.0" ]

1

2021-03-19T04:27:58.000Z

home/migrations/0002_auto_20200921_1020.py

ArifShariar/HackNsu2_TEAM_RETURN_ZERO

eb5594619754f9ef98bc8383f7ed3f7f553ce703

[ "Apache-2.0" ]

2

2020-10-20T12:58:43.000Z

2020-12-12T15:54:30.000Z

# Generated by Django 3.1.1 on 2020-09-21 04:20 from django.db import migrations class Migration(migrations.Migration): dependencies = [ ('home', '0001_initial'), ] operations = [ migrations.RemoveField( model_name='company_product', name='order_fk', ), migrations.DeleteModel( name='notification', ), migrations.DeleteModel( name='vendor_product', ), migrations.DeleteModel( name='company_product', ), migrations.DeleteModel( name='order', ), ]

20.9

47

0.53748

53

627

6.245283

0.603774

0.253776

0.302115

0.193353

0

0.046798

0.352472

627

29

48

21.62069

0.768473

0.07177

0

0.391304

1

0

0.146552

0

1

0

false

0

0.043478

0

0.173913

0

null

1

0

1

0

null

0

4

cae816abcbc67ce4240cf1b33df5e220fc4bf697

218

py

Python

mne_nirs/io/__init__.py

alexrockhill/mne-nirs

846d5f7dc5c7022d8b4a4af2911f1dff31e678d4

[ "BSD-3-Clause" ]

46

2020-04-17T20:27:13.000Z

2022-03-11T08:03:23.000Z

mne_nirs/io/__init__.py

alexrockhill/mne-nirs

846d5f7dc5c7022d8b4a4af2911f1dff31e678d4

[ "BSD-3-Clause" ]

324

2020-04-14T09:53:15.000Z

2022-03-14T15:26:40.000Z

mne_nirs/io/__init__.py

alexrockhill/mne-nirs

846d5f7dc5c7022d8b4a4af2911f1dff31e678d4

[ "BSD-3-Clause" ]

24

2020-04-14T10:44:27.000Z

2022-03-12T23:46:42.000Z

# Authors: Robert Luke <mail@robertluke.net> # # License: BSD (3-clause) from . import snirf from . import fold from .snirf import write_raw_snirf from .fold import fold_channel_specificity, fold_landmark_specificity

24.222222

69

0.793578

31

218

5.387097

0.612903

0.11976

0

0.005263

0.12844

218

8

70

27.25

0.873684

0.302752

0

1

0

true

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

4

1b667850264e7c098db11564a7744d502095777b

334

py

Python

mamba/core/msg/empty.py

ismaelJimenez/mamba_server

e6e2343291a0df24f226bde0d13e5bfa74cc3650

[ "MIT" ]

null

mamba/core/msg/empty.py

ismaelJimenez/mamba_server

e6e2343291a0df24f226bde0d13e5bfa74cc3650

[ "MIT" ]

null

mamba/core/msg/empty.py

ismaelJimenez/mamba_server

e6e2343291a0df24f226bde0d13e5bfa74cc3650

[ "MIT" ]

null

############################################################################ # # Copyright (c) Mamba Developers. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for # license information. # ############################################################################ class Empty: pass

27.833333

76

0.39521

25

334

5.28

0.88

0

0.110778

334

11

77

30.363636

0.444444

0.434132

0

1

0

true

0.5

0

0.5

0

1

0

null

0

1

0

null

0

1

0

4

1b9be75848814559b7e7261b7be1d6d788d412d7

617

py

Python

cotr/ctrs_texts/migrations/0005_auto_20190731_0944.py

kingsdigitallab/cotr

4afbfdd36d4dd0ee9f56152d3c963453c81e440c

[ "MIT" ]

null

cotr/ctrs_texts/migrations/0005_auto_20190731_0944.py

kingsdigitallab/cotr

4afbfdd36d4dd0ee9f56152d3c963453c81e440c

[ "MIT" ]

27

2020-12-28T17:34:59.000Z

2022-03-12T00:25:43.000Z

ctrs_texts/migrations/0005_auto_20190731_0944.py

kingsdigitallab/ctrs-django

7170b4f15bd9d097d00f215d747a02a9b656768c

[ "MIT" ]

null

# Generated by Django 2.2.3 on 2019-07-31 08:44 from django.db import migrations class Migration(migrations.Migration): dependencies = [ ('ctrs_texts', '0004_auto_20190720_0019'), ] operations = [ migrations.AlterModelOptions( name='abstractedtext', options={'ordering': ['name']}, ), migrations.AlterModelOptions( name='abstractedtexttype', options={'ordering': ['name']}, ), migrations.AlterModelOptions( name='encodedtexttype', options={'ordering': ['name']}, ), ]

23.730769

50

0.562399

50

617

6.86

0.64

0.236152

0.271137

0.169096

0.291545

0

0.072261

0.3047

617

25

51

24.68

0.727273

0.072934

0

0.473684

1

0

0.203509

0.040351

0

1

0

false

0

0.052632

0

0.210526

0

null

1

0

1

0

null

0

4

1bb525959cb409db77278939b5d4c81fee5bb6fa

88

py

Python

sample_config.py

Amarnathcdj/Lunachatbot

b560f2233cbbce4dca99868bb0f3cc85f5ad8717

[ "MIT" ]

null

sample_config.py

Amarnathcdj/Lunachatbot

b560f2233cbbce4dca99868bb0f3cc85f5ad8717

[ "MIT" ]

null

sample_config.py

Amarnathcdj/Lunachatbot

b560f2233cbbce4dca99868bb0f3cc85f5ad8717

[ "MIT" ]

1

2021-03-01T05:03:45.000Z

owner_id = 1243703097 bot_token = "16901971:AAFqdM_SQE1PB2P1xLr67k" bot_id = 1663901971

22

45

0.829545

11

88

6.272727

0.818182

0

0.417722

0.102273

88

3

46

29.333333

0.455696

0

0.352273

0

1

0

false

0

1

0

null

0

1

0

1

0

1

0

null

0

4

9429b346b6876e3d4f458e6e40ee3f6d02fc1474

201

py

Python

face_recognition_server/app.py

yoyota-pose-estimation/face-recognition-server

51edb78dd00b585461174fdcc31a95a5debcadca

[ "MIT" ]

null

face_recognition_server/app.py

yoyota-pose-estimation/face-recognition-server

51edb78dd00b585461174fdcc31a95a5debcadca

[ "MIT" ]

null

face_recognition_server/app.py

yoyota-pose-estimation/face-recognition-server

51edb78dd00b585461174fdcc31a95a5debcadca

[ "MIT" ]

null

from flask import Flask # pylint: disable=invalid-name app = Flask(__name__) @app.route("/healthz") def health(): return ("", 204) @app.route("/") def hello_world(): return "hello world!"

13.4

30

0.651741

26

201

4.846154

0.615385

0.111111

0

0.018072

0.174129

201

14

31

14.357143

0.740964

0.139303

0

0.122807

0

1

0.25

false

0

0.125

0.25

0.625

0

1

0

null

0

null

0

1

0

1

0

4

942cd5943c7d08829f01bbcca4c56eb34b79cb74

154

py

Python

Django_Server/raspberrypi_virtualenv/bin/django-admin.py

ManasUniyal/Friday

6e1ff6541cca98f073e3fd07218b22da165a613b

[ "MIT" ]

1

2021-03-01T11:25:32.000Z

Django_Server/raspberrypi_virtualenv/bin/django-admin.py

ManasUniyal/Friday

6e1ff6541cca98f073e3fd07218b22da165a613b

[ "MIT" ]

null

Django_Server/raspberrypi_virtualenv/bin/django-admin.py

ManasUniyal/Friday

6e1ff6541cca98f073e3fd07218b22da165a613b

[ "MIT" ]

null

#!/home/manas/Desktop/raspberrypi_3/bin/python3 from django.core import management if __name__ == "__main__": management.execute_from_command_line()

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1

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null

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4

94372aceab65ce98fdc6289fc10f08aad45da226

747

py

Python

yard/skills/66-python/cookbook/yh_std_lib_demo.py

paser4se/bbxyard

d09bc6efb75618b2cef047bad9c8b835043446cb

[ "Apache-2.0" ]

1

2016-03-29T02:01:58.000Z

yard/skills/66-python/cookbook/yh_std_lib_demo.py

paser4se/bbxyard

d09bc6efb75618b2cef047bad9c8b835043446cb

[ "Apache-2.0" ]

18

2019-02-13T09:15:25.000Z

2021-12-09T21:32:13.000Z

yard/skills/66-python/cookbook/yh_std_lib_demo.py

paser4se/bbxyard

d09bc6efb75618b2cef047bad9c8b835043446cb

[ "Apache-2.0" ]

2

2020-07-05T01:01:30.000Z

2020-07-08T22:33:06.000Z

#!/usr/bin/env python3 # 系统标准库测试 from yvhai.demo.std.os import OSDemo from yvhai.demo.std.misc import MiscDemo from yvhai.demo.std.shutil import ShUtilDemo from yvhai.demo.std.sys import SysDemo from yvhai.demo.std.datetime import DTDemo from yvhai.demo.std.re import RegexDemo from yvhai.demo.std.logging import LogerDemo from yvhai.demo.std.str import StrDemo from yvhai.demo.std.ds.deque import DequeDemo from yvhai.demo.std.ds.heapq import HeapqDemo from yvhai.demo.std.ds.dict import DictDemo if __name__ == '__main__': OSDemo.demo() MiscDemo.demo() ShUtilDemo.demo() SysDemo.demo() DTDemo.demo() RegexDemo.demo() LogerDemo.demo() StrDemo.demo() DequeDemo.demo() HeapqDemo.demo() DictDemo.demo()

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747

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27.666667

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0.478261

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null

0

1

0

null

0

1

0

1

0

4

947fb1784fe2b80f163016b8fde7f7007f737dfe

457

py

Python

app_ubigeo/api/serializers.py

softlabperu/app_ubigeo

270c588de4f01901aef0433f65b8452771e10d5e

[ "BSD-3-Clause" ]

null

app_ubigeo/api/serializers.py

softlabperu/app_ubigeo

270c588de4f01901aef0433f65b8452771e10d5e

[ "BSD-3-Clause" ]

null

app_ubigeo/api/serializers.py

softlabperu/app_ubigeo

270c588de4f01901aef0433f65b8452771e10d5e

[ "BSD-3-Clause" ]

null

from rest_framework import serializers from app_ubigeo.models import * class DepartamentoSerializer(serializers.ModelSerializer): class Meta: model = Departamento fields = '__all__' class ProvinciaSerializer(serializers.ModelSerializer): class Meta: model = Provincia fields = '__all__' class DistritoSerializer(serializers.ModelSerializer): class Meta: model = Distrito fields = '__all__'

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null

1

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null

0

1

0

4

948a5a52475e167752e7d012fd230ee0ffd66fe0

1,498

py

Python

tests/v1/test_synthetics_test_options.py

MichaelTROEHLER/datadog-api-client-python

12c46626622fb1277bb1e172753b342c671348bd

[ "Apache-2.0" ]

null

tests/v1/test_synthetics_test_options.py

MichaelTROEHLER/datadog-api-client-python

12c46626622fb1277bb1e172753b342c671348bd

[ "Apache-2.0" ]

null

tests/v1/test_synthetics_test_options.py

MichaelTROEHLER/datadog-api-client-python

12c46626622fb1277bb1e172753b342c671348bd

[ "Apache-2.0" ]

null

# coding: utf-8 # Unless explicitly stated otherwise all files in this repository are licensed under the Apache-2.0 License. # This product includes software developed at Datadog (https://www.datadoghq.com/). # Copyright 2019-Present Datadog, Inc. from __future__ import absolute_import import sys import unittest import datadog_api_client.v1 try: from datadog_api_client.v1.model import synthetics_device_id except ImportError: synthetics_device_id = sys.modules[ 'datadog_api_client.v1.model.synthetics_device_id'] try: from datadog_api_client.v1.model import synthetics_test_options_retry except ImportError: synthetics_test_options_retry = sys.modules[ 'datadog_api_client.v1.model.synthetics_test_options_retry'] try: from datadog_api_client.v1.model import synthetics_tick_interval except ImportError: synthetics_tick_interval = sys.modules[ 'datadog_api_client.v1.model.synthetics_tick_interval'] from datadog_api_client.v1.model.synthetics_test_options import SyntheticsTestOptions class TestSyntheticsTestOptions(unittest.TestCase): """SyntheticsTestOptions unit test stubs""" def setUp(self): pass def tearDown(self): pass def testSyntheticsTestOptions(self): """Test SyntheticsTestOptions""" # FIXME: construct object with mandatory attributes with example values # model = SyntheticsTestOptions() # noqa: E501 pass if __name__ == '__main__': unittest.main()

30.571429

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0.126143

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1,498

48

109

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0.860112

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0

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0.37931

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null

0

1

0

1

0

1

0

4

948c10f956f7e7e9df11c3a3507cc0020f781b6a

8,015

py

Python

test_tvmv.py

netfeed/tvmv

7f7885ce454f6d76ae0ffb0ccdf0b4baaee0ccdb

[ "MIT" ]

null

test_tvmv.py

netfeed/tvmv

7f7885ce454f6d76ae0ffb0ccdf0b4baaee0ccdb

[ "MIT" ]

null

test_tvmv.py

netfeed/tvmv

7f7885ce454f6d76ae0ffb0ccdf0b4baaee0ccdb

[ "MIT" ]

null

import imp import os import os.path import unittest tvmv = imp.load_source('tvmv', 'tvmv') tvmv.VERBOSE = False class TestSeasonParsing(unittest.TestCase): def test_s01e08(self): result = tvmv.parse_season("American.Dad.S01E08.HDTV.x264") self.assertEqual('01', result.group(1)) self.assertEqual('08', result.group(2)) def test_07e09(self): result = tvmv.parse_season("Cutthroat+Kitchen+07e09+hdtv+x264") self.assertEqual('07', result.group(1)) self.assertEqual('09', result.group(2)) def test_s11e23(self): result = tvmv.parse_season("American.Dad.S11E23.HDTV.x264") self.assertEqual('11', result.group(1)) self.assertEqual('23', result.group(2)) def test_parent(self): result = tvmv.parse_season("American.Dad.S11E23.HDTV.x264/episode.mp4") self.assertEqual('11', result.group(1)) self.assertEqual('23', result.group(2)) def test_1x10(self): result = tvmv.parse_season("American Dad 1x10 HDTV x264") self.assertEqual('1', result.group(1)) self.assertEqual('10', result.group(2)) def test_10x01(self): result = tvmv.parse_season("American Dad 10x01 HDTV x264") self.assertEqual('10', result.group(1)) self.assertEqual('01', result.group(2)) def test_110(self): result = tvmv.parse_season("American Dad 110 HDTV x264") self.assertEqual('1', result.group(1)) self.assertEqual('10', result.group(2)) def test_1001(self): result = tvmv.parse_season("American Dad 1001 HDTV x264") self.assertEqual('10', result.group(1)) self.assertEqual('01', result.group(2)) def test_none(self): result = tvmv.parse_season("American Dad HDTV x264") self.assertEqual(None, result) def test_slash_season(self): result = tvmv.parse_season("511 - Mac and Charlie Write a Movie.avi") self.assertEqual('5', result.group(1)) self.assertEqual('11', result.group(2)) def test_number_in_ep(self): result = tvmv.parse_season("205 - 100 Dollar Baby.avi") self.assertEqual('2', result.group(1)) self.assertEqual('05', result.group(2)) class TestNameParsing(unittest.TestCase): def test_s01e08(self): result = tvmv.parse_name("American.Dad.S01E08.HDTV.x264") self.assertEqual('American Dad', result) def test_1x10(self): result = tvmv.parse_name("American Dad 1x10 HDTV x264") self.assertEqual('American Dad', result) def test_110(self): result = tvmv.parse_name("American Dad 110 HDTV x264") self.assertEqual('American Dad', result) def test_sunny(self): result = tvmv.parse_name("It's Always Sunny in Philadelphia 1001 HDTV x264") self.assertEqual("It's Always Sunny in Philadelphia", result) def test_none(self): result = tvmv.parse_name("American Dad HDTV x264") self.assertEqual(None, result) def test_archer(self): result = tvmv.parse_name("Archer.2009.S06E11.HDTV.x264") self.assertEqual("Archer 2009", result) class TestTvParsing(unittest.TestCase): def test_name_single_number_season(self): parsed = tvmv.parse_path('files', "files/American.Dad.S01E08.HDTV.x264/American Dad - 108.mp4") check = tvmv.Show('American Dad', episode=tvmv.Episode(1, 8, '.mp4')) self.assertEqual(check, parsed) def test_name_single_number_season_x(self): parsed = tvmv.parse_path('files', "files/American.Dad.S01E08.HDTV.x264/American Dad - 1x08.mp4") check = tvmv.Show('American Dad', episode=tvmv.Episode(1, 8, '.mp4')) self.assertEqual(check, parsed) def test_check_dir(self): parsed = tvmv.parse_path('files', "files/American.Dad.S01E07.HDTV.x264/107.mp4") check = tvmv.Show('American Dad', episode=tvmv.Episode(1, 7, '.mp4')) self.assertEqual(check, parsed) def test_check_dir_no_files(self): parsed = tvmv.parse_path('files', "American.Dad.S01E07.HDTV.x264/107.mp4") check = tvmv.Show('American Dad', episode=tvmv.Episode(1, 7, '.mp4')) self.assertEqual(check, parsed) def test_name_double_digit_season(self): parsed = tvmv.parse_path('files', "files/American.Dad.S11E08.HDTV.x264/American Dad - 1108.mp4") check = tvmv.Show('American Dad', episode=tvmv.Episode(11, 8, '.mp4')) self.assertEqual(check, parsed) def test_am_good_filename(self): parsed = tvmv.parse_path('files', "files/American.Dad.S11E09.HDTV.x264/American.Dad.S11E09.HDTV.x264.mp4") check = tvmv.Show('American Dad', episode=tvmv.Episode(11, 9, '.mp4')) self.assertEqual(check, parsed) def test_bb_good_filename(self): parsed = tvmv.parse_path('files', "files/Bobs.Burgers.S05E15.HDTV.x264.mp4") check = tvmv.Show('Bobs Burgers', episode=tvmv.Episode(5, 15, '.mp4')) self.assertEqual(check, parsed) def test_spaced_name(self): parsed = tvmv.parse_path('files', "files/It's Always Sunny in Philadelphia S10E10 (1920x1080).mkv") check = tvmv.Show("It's Always Sunny in Philadelphia", episode=tvmv.Episode(10, 10, '.mkv')) self.assertEqual(check, parsed) def test_spaced_name_no_files(self): parsed = tvmv.parse_path('files', "It's Always Sunny in Philadelphia S10E10 (1920x1080).mkv") check = tvmv.Show("It's Always Sunny in Philadelphia", episode=tvmv.Episode(10, 10, '.mkv')) self.assertEqual(check, parsed) def test_one_up(self): parsed = tvmv.parse_path('files', "It's Always Sunny In Philadelphia/Season 3/309 - Sweet Dee's Dating A Retarted Person.avi") check = tvmv.Show("It's Always Sunny In Philadelphia", episode=tvmv.Episode(3, 9, '.avi')) self.assertEqual(check, parsed) def test_one_up_none(self): parsed = tvmv.parse_path('files', "files/Season 3/309 - Sweet Dee's Dating A Retarted Person.avi") self.assertEqual(None, parsed) def test_number_in_name(self): parsed = tvmv.parse_path('files', "files/It's Always Sunny In Philadelphia/Season 2/205 - 100 Dollar Baby.avi") check = tvmv.Show("It's Always Sunny In Philadelphia", episode=tvmv.Episode(2, 5, '.avi')) self.assertEqual(check, parsed) class TestFormatFromPath(unittest.TestCase): def test_name(self): parsed = tvmv.parse_path('files', "files/American.Dad.S01E08.HDTV.x264/American Dad - 108.mp4") result = parsed.format("{show}/{show}") self.assertEqual("American Dad/American Dad", result) def test_season(self): parsed = tvmv.parse_path('files', "files/American.Dad.S01E08.HDTV.x264/American Dad - 108.mp4") result = parsed.format("{season}") self.assertEqual("1", result) def test_padded_season(self): parsed = tvmv.parse_path('files', "files/American.Dad.S01E08.HDTV.x264/American Dad - 108.mp4") result = parsed.format("{season.pad(2)}") self.assertEqual("01", result) def test_episode(self): parsed = tvmv.parse_path('files', "files/American.Dad.S01E08.HDTV.x264/American Dad - 108.mp4") result = parsed.format("{episode}") self.assertEqual("8", result) def test_padded_episode(self): parsed = tvmv.parse_path('files', "files/American.Dad.S01E08.HDTV.x264/American Dad - 108.mp4") result = parsed.format("{episode.pad(2)}") self.assertEqual("08", result) def test_1x8_combo(self): parsed = tvmv.parse_path('files', "files/American.Dad.S01E08.HDTV.x264/American Dad - 108.mp4") result = parsed.format("{season}x{episode}") self.assertEqual("1x8", result) def test_padded_combo(self): parsed = tvmv.parse_path('files', "files/American.Dad.S01E08.HDTV.x264/American Dad - 108.mp4") result = parsed.format("s{season.pad(2)}e{episode.pad(2)}") self.assertEqual("s01e08", result) if __name__ == '__main__': unittest.main()

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134

0.663007

1,083

8,015

4.800554

0.116343

0.099442

0.051164

0.069436

0.841893

0.740527

0.715715

0.630698

0.595307

0.521831

0

0.069937

0.193637

8,015

187

135

42.860963

0.734489

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0.337838

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0.013514

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0.106051

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0.310811

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0.243243

false

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0.027027

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0.297297

0

null

0

1

0

null

0

1

0

4

84a12da679314b90e0d272c2c5df43f5e76f853b

288

py

Python

app/Fron_end/bd/models.py

IsaiRL/Proyecto-PS

588a72710f9b2742943e83b46fb101940a6ca52b

[ "MIT" ]

null

app/Fron_end/bd/models.py

IsaiRL/Proyecto-PS

588a72710f9b2742943e83b46fb101940a6ca52b

[ "MIT" ]

null

app/Fron_end/bd/models.py

IsaiRL/Proyecto-PS

588a72710f9b2742943e83b46fb101940a6ca52b

[ "MIT" ]

null

from django.db import models # Create your models here. class IPs(models.Model): ip = models.GenericIPAddressField(null=False, blank=False, unique=True) ultima_peticion = models.DateTimeField(null=False, blank=False) intentos = models.IntegerField(null=False, blank=False, default=0)

36

72

0.788194

39

288

5.794872

0.641026

0.119469

0.185841

0.252212

0

0.003861

0.100694

288

7

73

41.142857

0.868726

0.083333

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false

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0.2

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null

0

1

0

1

0

null

0

1

0

4

84c44206df00eb1931caed2c776070ccb2d9abaf

47

py

Python

ex4-7.py

yiyidhuang/PythonCrashCrouse2nd

3512f9ab8fcf32c6145604a37e2a62feddf174d1

[ "MIT" ]

null

ex4-7.py

yiyidhuang/PythonCrashCrouse2nd

3512f9ab8fcf32c6145604a37e2a62feddf174d1

[ "MIT" ]

null

ex4-7.py

yiyidhuang/PythonCrashCrouse2nd

3512f9ab8fcf32c6145604a37e2a62feddf174d1

[ "MIT" ]

null

numbers = list(range(3, 31, 3)) print(numbers)

15.666667

31

0.680851

8

47

4

0.75

0

0.097561

0.12766

47

2

32

23.5

0.682927

0

1

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false

0

0.5

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null

0

1

0

null

0

1

0

4

84c8deab8f6125677768b52551f21022ce3a046a

242

py

Python

otp/distributed/ObjectServerAI.py

TheFamiliarScoot/open-toontown

678313033174ea7d08e5c2823bd7b473701ff547

[ "BSD-3-Clause" ]

99

2019-11-02T22:25:00.000Z

2022-02-03T03:48:00.000Z

otp/distributed/ObjectServerAI.py

TheFamiliarScoot/open-toontown

678313033174ea7d08e5c2823bd7b473701ff547

[ "BSD-3-Clause" ]

42

2019-11-03T05:31:08.000Z

2022-03-16T22:50:32.000Z

otp/distributed/ObjectServerAI.py

TheFamiliarScoot/open-toontown

678313033174ea7d08e5c2823bd7b473701ff547

[ "BSD-3-Clause" ]

57

2019-11-03T07:47:37.000Z

2022-03-22T00:41:49.000Z

from direct.directnotify import DirectNotifyGlobal from direct.distributed.DistributedObjectAI import DistributedObjectAI class ObjectServerAI(DistributedObjectAI): notify = DirectNotifyGlobal.directNotify.newCategory('ObjectServerAI')

34.571429

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242

11.052632

0.578947

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0

0.078512

242

6

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40.333333

0.941704

0

0.057851

0

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0.5

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1

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null

0

1

0

4

84df5b01533b8d32dfc55fb8f5bbf1ebfc07e8a4

80

py

Python

tests/test_files/async_def.py

cepbuch/flake8-class-attributes-order

8597c045fd576cb79fd2be3f10d95b92394e57c0

[ "MIT" ]

38

2019-02-15T18:09:08.000Z

2022-01-20T04:04:15.000Z

tests/test_files/async_def.py

cepbuch/flake8-class-attributes-order

8597c045fd576cb79fd2be3f10d95b92394e57c0

[ "MIT" ]

25

2019-04-21T12:58:09.000Z

2022-02-08T07:38:57.000Z

tests/test_files/async_def.py

cepbuch/flake8-class-attributes-order

8597c045fd576cb79fd2be3f10d95b92394e57c0

[ "MIT" ]

14

2019-04-21T13:00:05.000Z

2021-08-30T06:49:36.000Z

class A: def foo(self): pass async def bar(self): pass

11.428571

24

0.4875

11

80

3.545455

0.727273

0.410256

0

0.425

80

6

25

13.333333

0.847826

0

0.4

0

1

0.2

false

0.4

0

0.4

0

1

0

null

1

0

1

0

null

0

1

0

4

ca252e0c312a32945854be9ca7995fedcca7825e

67

py

Python

deduckt/main.py

metacraft-labs/python-deduckt

16f2b0419ba143131dd729f570158bb50288da90

[ "MIT" ]

20

2018-01-08T14:06:06.000Z

2021-08-25T03:02:02.000Z

deduckt/main.py

metacraft-labs/python-deduckt

16f2b0419ba143131dd729f570158bb50288da90

[ "MIT" ]

4

2018-05-22T06:55:54.000Z

2019-02-17T11:46:57.000Z

deduckt/main.py

metacraft-labs/python-deduckt

16f2b0419ba143131dd729f570158bb50288da90

[ "MIT" ]

6

2018-01-15T12:14:32.000Z

2019-10-15T14:19:13.000Z

if __name__ == '__main__': from deduckt import main main()

16.75

28

0.641791

8

67

4.375

0.75

0

0.253731

67

3

29

22.333333

0.7

0

0.119403

0

1

0

true

0

0.333333

0

0.333333

0

1

0

null

0

1

0

null

0

1

0

1

0

4

ca5cb5bdb085d847ab2f87fae741c07a98c66b17

80

py

Python

Phoster/compile.py

blueraspberrypi/phoster

67f961adf40e3251d79bc6e4b9bc9684b6ecc90b

[ "MIT" ]

1

2020-07-15T13:49:31.000Z

Phoster/compile.py

blueraspberrypi/phoster

67f961adf40e3251d79bc6e4b9bc9684b6ecc90b

[ "MIT" ]

null

Phoster/compile.py

blueraspberrypi/phoster

67f961adf40e3251d79bc6e4b9bc9684b6ecc90b

[ "MIT" ]

null

from distutils.core import setup import py2exe setup(console=['phoster.py'])

20

33

0.7625

11

80

5.545455

0.818182

0

0.014286

0.125

80

4

34

20

0.857143

0

0.128205

0

1

0

true

0

0.666667

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

4

ca78b422ef93fe886fcd5cd6f95c38d2bff95a25

771

py

Python

Scene.py

nemosupremo/Colosseum--Year-3XXX

93cd723e60f2f8fe57637cdabad2b1a644c9c279

[ "MIT" ]

1

2021-01-09T16:04:48.000Z

Scene.py

nemosupremo/Colosseum--Year-3XXX

93cd723e60f2f8fe57637cdabad2b1a644c9c279

[ "MIT" ]

null

Scene.py

nemosupremo/Colosseum--Year-3XXX

93cd723e60f2f8fe57637cdabad2b1a644c9c279

[ "MIT" ]

null

class Scene(object): MAIN = None setup = False destroyed = False handles = [] handleFunc = {} def __init__(self, MainObj): self.MAIN = MainObj self.createHandleFunctions() def createHandleFunctions(self): pass def setUp(self): self.setup = True def mainLoop(self): pass def destroy(self): self.destroyed = True def isSetUp(self): return self.setup def isDestroyed(self): return self.destroyed def handlesCall(self, call): return call in self.handles def handleCall(self, call, args): return self.handleFunc[call](*args) def canChangeChar(self): return False def canLeaveGame(self): return False

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1

0

4

ca8b6b52ecc8b59e1365c0ea8d064f7b01b4c4e8

2,339

py

Python

Cartwheel/lib/Python26/Lib/site-packages/OpenGL/raw/GL/EXT/multisample.py

MontyThibault/centre-of-mass-awareness

58778f148e65749e1dfc443043e9fc054ca3ff4d

[ "MIT" ]

null

Cartwheel/lib/Python26/Lib/site-packages/OpenGL/raw/GL/EXT/multisample.py

MontyThibault/centre-of-mass-awareness

58778f148e65749e1dfc443043e9fc054ca3ff4d

[ "MIT" ]

null

Cartwheel/lib/Python26/Lib/site-packages/OpenGL/raw/GL/EXT/multisample.py

MontyThibault/centre-of-mass-awareness

58778f148e65749e1dfc443043e9fc054ca3ff4d

[ "MIT" ]

null

'''OpenGL extension EXT.multisample The official definition of this extension is available here: http://oss.sgi.com/projects/ogl-sample/registry/EXT/multisample.txt Automatically generated by the get_gl_extensions script, do not edit! ''' from OpenGL import platform, constants, constant, arrays from OpenGL import extensions from OpenGL.GL import glget import ctypes EXTENSION_NAME = 'GL_EXT_multisample' GL_MULTISAMPLE_EXT = constant.Constant( 'GL_MULTISAMPLE_EXT', 0x809D ) GL_SAMPLE_ALPHA_TO_MASK_EXT = constant.Constant( 'GL_SAMPLE_ALPHA_TO_MASK_EXT', 0x809E ) GL_SAMPLE_ALPHA_TO_ONE_EXT = constant.Constant( 'GL_SAMPLE_ALPHA_TO_ONE_EXT', 0x809F ) GL_SAMPLE_MASK_EXT = constant.Constant( 'GL_SAMPLE_MASK_EXT', 0x80A0 ) GL_1PASS_EXT = constant.Constant( 'GL_1PASS_EXT', 0x80A1 ) GL_2PASS_0_EXT = constant.Constant( 'GL_2PASS_0_EXT', 0x80A2 ) GL_2PASS_1_EXT = constant.Constant( 'GL_2PASS_1_EXT', 0x80A3 ) GL_4PASS_0_EXT = constant.Constant( 'GL_4PASS_0_EXT', 0x80A4 ) GL_4PASS_1_EXT = constant.Constant( 'GL_4PASS_1_EXT', 0x80A5 ) GL_4PASS_2_EXT = constant.Constant( 'GL_4PASS_2_EXT', 0x80A6 ) GL_4PASS_3_EXT = constant.Constant( 'GL_4PASS_3_EXT', 0x80A7 ) GL_SAMPLE_BUFFERS_EXT = constant.Constant( 'GL_SAMPLE_BUFFERS_EXT', 0x80A8 ) GL_SAMPLES_EXT = constant.Constant( 'GL_SAMPLES_EXT', 0x80A9 ) GL_SAMPLE_MASK_VALUE_EXT = constant.Constant( 'GL_SAMPLE_MASK_VALUE_EXT', 0x80AA ) GL_SAMPLE_MASK_INVERT_EXT = constant.Constant( 'GL_SAMPLE_MASK_INVERT_EXT', 0x80AB ) GL_SAMPLE_PATTERN_EXT = constant.Constant( 'GL_SAMPLE_PATTERN_EXT', 0x80AC ) GL_MULTISAMPLE_BIT_EXT = constant.Constant( 'GL_MULTISAMPLE_BIT_EXT', 0x20000000 ) glSampleMaskEXT = platform.createExtensionFunction( 'glSampleMaskEXT', dll=platform.GL, extension=EXTENSION_NAME, resultType=None, argTypes=(constants.GLclampf, constants.GLboolean,), doc = 'glSampleMaskEXT( GLclampf(value), GLboolean(invert) ) -> None', argNames = ('value', 'invert',), ) glSamplePatternEXT = platform.createExtensionFunction( 'glSamplePatternEXT', dll=platform.GL, extension=EXTENSION_NAME, resultType=None, argTypes=(constants.GLenum,), doc = 'glSamplePatternEXT( GLenum(pattern) ) -> None', argNames = ('pattern',), ) def glInitMultisampleEXT(): '''Return boolean indicating whether this extension is available''' return extensions.hasGLExtension( EXTENSION_NAME )

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0.295238

0.106431

0.183836

0.203187

0.385316

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0.081733

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0.175

0.1

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null

0

1

0

1

0

null

0

1

0

4

ca96757218b3a2f3445c0ef6429030c1be6d1426

124

py

Python

src/__init__.py

heyhpython/desktop

e75ffddf9526e8fd1adaca69c315005e202bf84b

[ "MIT" ]

null

src/__init__.py

heyhpython/desktop

e75ffddf9526e8fd1adaca69c315005e202bf84b

[ "MIT" ]

null

src/__init__.py

heyhpython/desktop

e75ffddf9526e8fd1adaca69c315005e202bf84b

[ "MIT" ]

null

""" @author: yuhao.he @contact: <hawl.yuhao.he@gmail.com> @version: 0.0.1 @file: __init__.py.py @time: 2021/10/27 14:11 """

15.5

35

0.653226

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124

3.347826

0.826087

0.181818

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0.135135

0.104839

124

7

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0.558559

0.927419

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null

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1

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null

0

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4

045f00f5b6aaa9638f1ae95823077ee76ae94007

73

py

Python

salt/cli/__init__.py

markgras/salt

d66cd3c935533c63870b83228b978ce43e0ef70d

[ "Apache-2.0" ]

9,425

2015-01-01T05:59:24.000Z

2022-03-31T20:44:05.000Z

salt/cli/__init__.py

markgras/salt

d66cd3c935533c63870b83228b978ce43e0ef70d

[ "Apache-2.0" ]

33,507

2015-01-01T00:19:56.000Z

2022-03-31T23:48:20.000Z

salt/cli/__init__.py

markgras/salt

d66cd3c935533c63870b83228b978ce43e0ef70d

[ "Apache-2.0" ]

5,810

2015-01-01T19:11:45.000Z

2022-03-31T02:37:20.000Z

""" The management of salt command line utilities are stored in here """

18.25

64

0.739726

11

73

4.909091

1

0

0.178082

73

3

65

24.333333

0.9

0.876712

0

null

0

null

0

null

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null

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true

0

null

1

0

null

0

1

0

1

0

null

0

1

0

4

046a52ff392852c4ba1432020c4349f6fdb49103

434

py

Python

juq/service/group_service.py

inhzus/juq

2721f1361eed3d4e7da36d67f924942faef24650

[ "MIT" ]

14

2019-04-09T23:34:56.000Z

2022-01-17T14:19:51.000Z

juq/service/group_service.py

inhzus/juq

2721f1361eed3d4e7da36d67f924942faef24650

[ "MIT" ]

null

juq/service/group_service.py

inhzus/juq

2721f1361eed3d4e7da36d67f924942faef24650

[ "MIT" ]

4

2020-03-29T15:29:59.000Z

2022-01-17T14:19:44.000Z

# -*- coding: utf-8 -*- # created by inhzus from juq.handler import group_handler, repo_handler from .utils import filter_empty_params # noinspection PyShadowingBuiltins def info(id_: str, **_): return group_handler.get_group_info(id_=id_) # noinspection PyShadowingBuiltins def repos(group_id: str, type: str, offset: int, **_): return '\n'.join(map(repr, repo_handler.get_group_repos(**filter_empty_params(locals()))))

27.125

94

0.748848

59

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0.559322

0.078176

0.110749

0

0.002632

0.124424

434

15

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28.933333

0.805263

0.241935

0

0.006173

0

1

0.333333

false

0

0.333333

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null

0

null

0

1

0

1

0

4

0472b745d5b6b80f8b4c4fbd40558659279d2a11

135

py

Python

main.py

quicksandznzn/text-correction-ernie

4813a8ad9ded375731c19db39dbae49e275d98a4

[ "Apache-2.0" ]

null

main.py

quicksandznzn/text-correction-ernie

4813a8ad9ded375731c19db39dbae49e275d98a4

[ "Apache-2.0" ]

null

main.py

quicksandznzn/text-correction-ernie

4813a8ad9ded375731c19db39dbae49e275d98a4

[ "Apache-2.0" ]

null

from paddlenlp import Taskflow text_correction = Taskflow("text_correction",home_path='./') res = text_correction('把我的收集拿来') print(res)

33.75

60

0.792593

17

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0.647059

0.407767

0.427184

0

0.074074

135

4

61

33.75

0.824

0

0.176471

0

1

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false

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0.25

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0.25

1

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null

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null

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