xszheng2020/the_stack_dedup_python_hits_4 · Datasets at Hugging Face

a226dba6af5a014817ca7d72839affa297276e43

184

py

Python

virtual/bin/django-admin.py

Nyagah-Tech/hoodapp

1dfca4860dd2113c01881ebc7e487d377e2cee3a

[ "MIT" ]

null

virtual/bin/django-admin.py

Nyagah-Tech/hoodapp

1dfca4860dd2113c01881ebc7e487d377e2cee3a

[ "MIT" ]

7

2020-06-06T01:17:57.000Z

2022-02-10T10:13:46.000Z

virtual/bin/django-admin.py

Nyagah-Tech/hoodapp

1dfca4860dd2113c01881ebc7e487d377e2cee3a

[ "MIT" ]

null

#!/home/dan/Documents/moringa-school-project/Django/hoods/virtual/bin/python3 from django.core import management if __name__ == "__main__": management.execute_from_command_line()

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null

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4

bf431c8b5239baba42b2fe7497fc5905bcc6e33b

53

py

Python

Jarvis.SensorClient.Py/Jarvis.SensorClient.Py/jarvis_sensorclient/__init__.py

ztepsic/jarvis

8ac6ef5b25052c32c41c5af4488418e07d91d3a7

[ "MIT" ]

null

Jarvis.SensorClient.Py/Jarvis.SensorClient.Py/jarvis_sensorclient/__init__.py

ztepsic/jarvis

8ac6ef5b25052c32c41c5af4488418e07d91d3a7

[ "MIT" ]

7

2016-12-07T22:57:20.000Z

2017-01-30T20:51:00.000Z

Jarvis.SensorClient.Py/Jarvis.SensorClient.Py/jarvis_sensorclient/__init__.py

ztepsic/jarvis

8ac6ef5b25052c32c41c5af4488418e07d91d3a7

[ "MIT" ]

null

""" The jarvis sensor client application package. """

17.666667

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1

0

null

0

1

0

4

bf4beab6806ef9003a8217e3ae973e5835738b56

304

py

Python

src/smac_plus/__init__.py

TonghanWang/NDQ

575f2e243bac1a567c072dbea8e093aaa4959511

[ "Apache-2.0" ]

63

2020-02-23T09:37:15.000Z

2022-01-17T01:30:50.000Z

src/smac_plus/__init__.py

fringsoo/NDQ

e243ba917e331065e82c6634cb1d756873747be5

[ "Apache-2.0" ]

14

2020-04-20T02:20:11.000Z

2022-03-12T00:16:33.000Z

src/smac_plus/__init__.py

mig-zh/NDQ

5720e3e8b529724e8d96a9a24c73bca24a11e7f9

[ "Apache-2.0" ]

16

2020-03-12T02:57:52.000Z

2021-11-27T13:07:08.000Z

from __future__ import absolute_import from __future__ import division from __future__ import print_function from smac_plus.starcraft2.starcraft2 import StarCraft2Env from smac_plus.tracker1 import Tracker1Env from smac_plus.join1 import Join1Env __all__ = ["StarCraft2Env", "Tracker1Env", "Join1Env"]

30.4

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304

6.405405

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0

null

0

1

0

1

0

4

bf70156c7670a599b8b06960704bc5d794a62ccb

164

py

Python

py_roads/simple-arc.py

jadnohra/daisy

105c0f37c6adbe85ce830375c5e2fc89cbcc6cc9

[ "MIT" ]

3

2021-09-26T10:50:35.000Z

2022-01-25T02:44:37.000Z

py_roads/simple-arc.py

jadnohra/daisy

105c0f37c6adbe85ce830375c5e2fc89cbcc6cc9

[ "MIT" ]

1

2021-09-09T14:19:31.000Z

py_roads/simple-arc.py

jadnohra/daisy

105c0f37c6adbe85ce830375c5e2fc89cbcc6cc9

[ "MIT" ]

null

from pyroad import * class Road(PyRoad): def build(self, b, params): b.curve('A').start_at([0,0]).tangent_at_start([1,0]).end_at([0,200]).shape('arc')

27.333333

89

0.628049

29

164

3.413793

0.724138

0.060606

0

0.057143

0.146341

164

6

89

27.333333

0.65

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0.024242

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null

0

1

0

null

0

1

0

1

0

4

bf9af5db4553693be0629dcda59aa6484432a1f2

221

py

Python

django/contrib/auth/tests/__init__.py

benjaoming/django

6dbe979b4d9396e1b307c7d27388c97c13beb21c

[ "BSD-3-Clause" ]

1

2015-01-09T08:45:54.000Z

django/contrib/auth/tests/__init__.py

benjaoming/django

6dbe979b4d9396e1b307c7d27388c97c13beb21c

[ "BSD-3-Clause" ]

null

django/contrib/auth/tests/__init__.py

benjaoming/django

6dbe979b4d9396e1b307c7d27388c97c13beb21c

[ "BSD-3-Clause" ]

null

# The password for the fixture data users is 'password' # For testing that auth backends can be referenced using a convenience import from django.contrib.auth.tests.test_auth_backends import ImportedModelBackend # NOQA

44.2

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5.59375

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221

4

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true

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1

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null

0

1

0

1

0

1

0

4

bfbd0068215fb8ba0316dc2558fe1a66701be3bf

225

py

Python

guildmaster/apps.py

mrogaski/umami

22879e9f8fcba510c7945c808512b9cf1dbeaa2c

[ "MIT" ]

2

2018-03-08T02:54:12.000Z

2018-03-10T04:57:32.000Z

guildmaster/apps.py

AIE-Guild/umami

22879e9f8fcba510c7945c808512b9cf1dbeaa2c

[ "MIT" ]

50

2015-01-08T21:22:11.000Z

2019-12-21T08:00:11.000Z

guildmaster/apps.py

mrogaski/umami

22879e9f8fcba510c7945c808512b9cf1dbeaa2c

[ "MIT" ]

2

2015-04-20T18:14:03.000Z

2018-03-10T05:07:23.000Z

from django.apps import AppConfig class GuildmasterConfig(AppConfig): name = 'guildmaster' verbose_name = 'Guildmaster' def ready(self) -> None: import guildmaster.conf # pylint: disable=unused-import

22.5

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null

0

1

0

1

0

4

44a36bdf877900d5ec2475f8477f9fd636f2bbb7

165

py

Python

ToDo/tasks/admin.py

SMarkus27/Django-Todo

3b18249dcb7b70337b5bd5f632f35de7b0f9ae93

[ "MIT" ]

null

ToDo/tasks/admin.py

SMarkus27/Django-Todo

3b18249dcb7b70337b5bd5f632f35de7b0f9ae93

[ "MIT" ]

null

ToDo/tasks/admin.py

SMarkus27/Django-Todo

3b18249dcb7b70337b5bd5f632f35de7b0f9ae93

[ "MIT" ]

null

from django.contrib import admin from .models import Tasks class TasksAdmin(admin.ModelAdmin): list_display=('id','task') admin.site.register(Tasks,TasksAdmin)

23.571429

37

0.781818

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165

5.818182

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165

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1

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false

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0

1

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null

0

1

0

1

0

4

44a93f3710848d76e918b6c391f7d950179e8e69

131

py

Python

backend/cars/urls.py

Sparrow0hawk/django-postgres

d7a18a77bc3dd8320191d9448e254bb1100b2650

[ "Xnet", "X11" ]

null

backend/cars/urls.py

Sparrow0hawk/django-postgres

d7a18a77bc3dd8320191d9448e254bb1100b2650

[ "Xnet", "X11" ]

null

backend/cars/urls.py

Sparrow0hawk/django-postgres

d7a18a77bc3dd8320191d9448e254bb1100b2650

[ "Xnet", "X11" ]

null

from django.urls import path from . import views urlpatterns = [ path("<int:pk>/", views.car_details, name='car_details'), ]

21.833333

61

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131

4.888889

0.666667

0.227273

0

0.160305

131

6

62

21.833333

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0.151515

0

1

0

false

0

0.4

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0

null

1

0

1

0

null

0

1

0

4

44aa87f70760505b12f8ce8d4e0d230ea856e615

705

py

Python

test/test_letters.py

bharjr01/countdown-bot

d494cf8020f25bf8ed2df5752fd8fb65eb962b4d

[ "MIT" ]

null

test/test_letters.py

bharjr01/countdown-bot

d494cf8020f25bf8ed2df5752fd8fb65eb962b4d

[ "MIT" ]

null

test/test_letters.py

bharjr01/countdown-bot

d494cf8020f25bf8ed2df5752fd8fb65eb962b4d

[ "MIT" ]

null

from unittest import TestCase import src.letters class TestLetters(TestCase): def test_generate_random_letters(self): for i in range(0, 10): with self.subTest(): result = src.letters.generate(i) num_vowels = count_vowels(result) num_consonants = count_consonants(result) self.assertEqual(num_vowels, i) self.assertEqual(num_consonants, 9-i) def count_vowels(haystack): return count(src.letters.__VOWELS, haystack) def count_consonants(haystack): return count(src.letters.__CONSONANTS, haystack) def count(needles, haystack): return [c in needles for c in haystack].count(True)

23.5

57

0.660993

85

705

5.305882

0.388235

0.088692

0.079823

0.097561

0.128603

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0.007605

0.253901

705

29

58

24.310345

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0.235294

false

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null

0

1

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null

0

1

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1

0

4

44b4f998fb344a43c6a10b8cadbeb7cf6261b610

146

py

Python

starter_code/api_keys.py

PopeStarkiller/api_challenge

e2596f6c32725bd7812716eed079089918ec2868

[ "ADSL" ]

null

starter_code/api_keys.py

PopeStarkiller/api_challenge

e2596f6c32725bd7812716eed079089918ec2868

[ "ADSL" ]

null

starter_code/api_keys.py

PopeStarkiller/api_challenge

e2596f6c32725bd7812716eed079089918ec2868

[ "ADSL" ]

null

# OpenWeatherMap API Key weather_api_key = "48ae7399e76d973a4b9ac9efe89908a3" # Google API Key g_key = "AIzaSyBrlKm1v_NyDl4nT9LOZWE5s_sQa2D5Hoc"

24.333333

52

0.842466

15

146

7.866667

0.666667

0.152542

0

0.198473

0.10274

146

5

53

29.2

0.70229

0.253425

0

0.669811

0

1

0

false

0

1

0

null

0

1

0

1

null

0

4

44cea8f9d32eda0d474f8b33d7c7c2bbcabbba62

243

py

Python

vocto/__init__.py

0xflotus/voctomix

3156f3546890e6ae8d379df17e5cc718eee14b15

[ "MIT" ]

521

2015-01-07T21:43:30.000Z

2022-03-17T22:07:13.000Z

vocto/__init__.py

0xflotus/voctomix

3156f3546890e6ae8d379df17e5cc718eee14b15

[ "MIT" ]

241

2015-05-27T10:11:09.000Z

2022-02-11T03:29:20.000Z

vocto/__init__.py

0xflotus/voctomix

3156f3546890e6ae8d379df17e5cc718eee14b15

[ "MIT" ]

111

2015-08-13T20:06:52.000Z

2022-03-11T09:48:46.000Z

#!/usr/bin/env python3 import gi gi.require_version('Gst', '1.0') from gi.repository import Gst import os # set GST debug dir for dot files if not 'GST_DEBUG_DUMP_DOT_DIR' in os.environ: os.environ['GST_DEBUG_DUMP_DOT_DIR'] = os.getcwd()

24.3

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0.744856

45

243

3.822222

0.577778

0.139535

0.174419

0.209302

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0.014286

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243

9

55

27

0.804762

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0.265957

0.234043

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true

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0.5

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null

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1

0

null

0

1

0

1

0

4

44d2cdaffd1e9b6a885b10d2a603521ea40f0ffe

118

py

Python

python/decorator.py

markthethomas/patterns

74d392d24601c1ec4c420fbe2739de09ddc414bc

[ "MIT" ]

1

2015-12-15T17:19:21.000Z

python/decorator.py

markthethomas/patterns

74d392d24601c1ec4c420fbe2739de09ddc414bc

[ "MIT" ]

null

python/decorator.py

markthethomas/patterns

74d392d24601c1ec4c420fbe2739de09ddc414bc

[ "MIT" ]

null

""" Sample implementation of python decorators, both using the @ syntactic sugar and the usual way of doing things """

29.5

58

0.771186

17

118

5.352941

0.882353

0

0.161017

118

4

59

29.5

0.919192

0.932203

0

null

0

null

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null

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null

true

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null

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null

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1

0

1

0

null

0

1

0

4

44d61b5506b0751556509f1a1a328f3a5dc46b58

3,517

py

Python

mmpy_bot/wrappers.py

Leanny/mmpy_bot

fd16db4f1b07130fbf95568fb242387f0c7973e2

[ "MIT" ]

196

2018-05-31T23:45:34.000Z

2022-03-20T09:06:55.000Z

mmpy_bot/wrappers.py

Leanny/mmpy_bot

fd16db4f1b07130fbf95568fb242387f0c7973e2

[ "MIT" ]

216

2018-05-31T19:18:46.000Z

2022-03-21T17:09:38.000Z

mmpy_bot/wrappers.py

tgly307/mmpy_bot

0ae52d9db86ac018f3d48dd52c11e4996f549073

[ "MIT" ]

107

2018-06-01T05:12:27.000Z

2022-02-25T12:40:10.000Z

from functools import cached_property from typing import Dict class EventWrapper: """Wrapper around the body of a mattermost network event, e.g. new posts or webhook requests. Contains cached properties for convenient variable access. Arguments: - body: dictionary, body of the network request that contains this event. """ def __init__( self, body: Dict, ): self.body = body class Message(EventWrapper): @cached_property def id(self): return self.body["data"]["post"]["id"] @cached_property def user_id(self): return self.body["data"]["post"]["user_id"] @cached_property def text(self): return self.body["data"]["post"]["message"].strip() @cached_property def channel_id(self): return self.body["data"]["post"]["channel_id"] @cached_property def channel_name(self): return self.body["data"]["channel_name"] @cached_property def is_direct_message(self): return self.body["data"]["channel_type"] == "D" @cached_property def mentions(self): return self.body["data"].get("mentions", []) @cached_property def parent_id(self): return self.body["data"]["post"]["parent_id"] @cached_property def reply_id(self): return self.root_id or self.id @cached_property def root_id(self): return self.body["data"]["post"]["root_id"] @cached_property def sender_name(self): return self.body["data"].get("sender_name", "").strip().strip("@") @cached_property def team_id(self): return self.body["data"].get("team_id", "").strip() class WebHookEvent(EventWrapper): """Wrapper around an incoming webhook post request. Arguments: - request_id: str, unique identifier of this web request - webhook_id: str, the webhook id that was triggered. """ def __init__( self, *args, request_id: str, webhook_id: str, **kwargs, ): super().__init__(*args, **kwargs) self.request_id = request_id self.webhook_id = webhook_id # Whether a web response was already sent to this request or not. self.responded = False @cached_property def text(self) -> str: return self.body.get("text") @cached_property def channel_name(self) -> str: return self.body.get("channel", self.body.get("channel_name")) @cached_property def props(self) -> Dict: return self.body.get("props", {}) @cached_property def type(self) -> Dict: return self.body.get("type") class ActionEvent(WebHookEvent): """Wrapper around an incoming webhook event that was triggered by an action, e.g. pressing a button or submitting a form.""" @cached_property def channel_id(self): return self.body.get("channel_id") @cached_property def context(self): return self.body.get("context") @cached_property def data_source(self): return self.body.get("data_source") @cached_property def post_id(self): return self.body.get("post_id") @cached_property def team_id(self): return self.body.get("team_id") @cached_property def trigger_id(self): return self.body.get("trigger_id") @cached_property def user_id(self): return self.body.get("user_id") @cached_property def user_name(self): return self.body.get("user_name")

24.594406

87

0.63122

448

3,517

4.776786

0.203125

0.097196

0.190654

0.159813

0.473364

0.345327

0.166355

0.119626

0.040187

0

0.246233

3,517

142

88

24.767606

0.807243

0.168041

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0.091226

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0.276596

false

0

0.021277

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null

0

1

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null

0

1

0

1

0

4

44e5f90874892e08ae1b51c2476865e17744482f

188

py

Python

vk_types/attachments/audio_msg.py

kz159/vk_types

84496ca22e34f0991a2d8dc353601272fb9f2108

[ "MIT" ]

3

2020-03-25T09:05:49.000Z

2022-02-05T01:41:18.000Z

vk_types/attachments/audio_msg.py

kz159/vk_types

84496ca22e34f0991a2d8dc353601272fb9f2108

[ "MIT" ]

null

vk_types/attachments/audio_msg.py

kz159/vk_types

84496ca22e34f0991a2d8dc353601272fb9f2108

[ "MIT" ]

2

2020-05-10T11:48:25.000Z

2021-12-02T09:22:54.000Z

from ..base import BaseModel from typing import List class AudioMsg(BaseModel): duration: int = None waveform: List[int] = None link_ogg: str = None link_mp3: str = None

18.8

30

0.68617

26

188

4.884615

0.615385

0.110236

0

0.006944

0.234043

188

9

31

20.888889

0.875

0

1

0

true

0

0.285714

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null

0

1

0

null

0

1

0

1

0

4

44ec256013e7de886bd5fb633a0ca14cd3cf641b

260

py

Python

BlackJack/Card.py

camicasii/Casino

0534092c1b2746d5561761b65bad1a97982a54f6

[ "MIT" ]

null

BlackJack/Card.py

camicasii/Casino

0534092c1b2746d5561761b65bad1a97982a54f6

[ "MIT" ]

null

BlackJack/Card.py

camicasii/Casino

0534092c1b2746d5561761b65bad1a97982a54f6

[ "MIT" ]

null

#conjunto de cartas class Card: def __init__(self,suit,value): super().__init__() self.suit =suit self.value = value #reescribimos la salida al imprimir def __repr__(self): return " of ".join((self.value,self.suit))

26

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0.623077

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260

4.545455

0.606061

0.16

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0.261538

260

9

51

28.888889

0.78125

0.2

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0.019417

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1

0.285714

false

0

0.142857

0.571429

0

null

0

1

0

null

0

1

0

1

0

4

44fca21724c6f8258d01b5a8142962fa7756bf11

190

py

Python

data/serializers.py

rajat-np/yt-search

3bf66403283744a57fa5efa029c4c45bb5e9292d

[ "MIT" ]

null

data/serializers.py

rajat-np/yt-search

3bf66403283744a57fa5efa029c4c45bb5e9292d

[ "MIT" ]

null

data/serializers.py

rajat-np/yt-search

3bf66403283744a57fa5efa029c4c45bb5e9292d

[ "MIT" ]

null

from rest_framework import serializers from .models import Video class VideoSerializer(serializers.ModelSerializer): class Meta: model = Video exclude = ['source_id']

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44fdf4003997f13456d94936966cd24d33d1eb3e

283

py

Python

tasks.py

Kami/libcloud-tests

564f24488952ec8d53e20994ec7769a0a423b539

[ "Apache-2.0" ]

null

tasks.py

Kami/libcloud-tests

564f24488952ec8d53e20994ec7769a0a423b539

[ "Apache-2.0" ]

2

2020-02-28T22:50:33.000Z

2021-02-09T21:54:43.000Z

tasks.py

Kami/libcloud-tests

564f24488952ec8d53e20994ec7769a0a423b539

[ "Apache-2.0" ]

1

2020-02-28T21:29:23.000Z

from invoke import task @task def lint(context, target="tests tasks.py"): context.run("flake8 {}".format(target)) context.run("pylint {}".format(target)) context.run("isort --check-only --recursive {}".format(target)) context.run("black --check {}".format(target))

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7849ea00b3cb1b7ba0e57af968d121b71d997a68

168

py

Python

Aula_55/dao/cliente_dao.py

Mateus-Silva11/AulasPython

d34dc4f62ade438e68b0a80e0baac4d6ec0d378e

[ "MIT" ]

null

Aula_55/dao/cliente_dao.py

Mateus-Silva11/AulasPython

d34dc4f62ade438e68b0a80e0baac4d6ec0d378e

[ "MIT" ]

null

Aula_55/dao/cliente_dao.py

Mateus-Silva11/AulasPython

d34dc4f62ade438e68b0a80e0baac4d6ec0d378e

[ "MIT" ]

null

from Aula_55.dao.base_dao import BaseDao from Aula_55.model.cliente import Cliente class ClienteDao(BaseDao): def __init__(self): super().__init__(Cliente)

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7850801f562e00d12847354d76e539232b992778

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py

Python

pyuavcan/transport/serial/__init__.py

sritank/public_regulated_data_types

d77d293aa3b500ec06b94d8997b8e55e0e5ac068

[ "MIT" ]

null

pyuavcan/transport/serial/__init__.py

sritank/public_regulated_data_types

d77d293aa3b500ec06b94d8997b8e55e0e5ac068

[ "MIT" ]

null

pyuavcan/transport/serial/__init__.py

sritank/public_regulated_data_types

d77d293aa3b500ec06b94d8997b8e55e0e5ac068

[ "MIT" ]

null

# # Copyright (c) 2019 UAVCAN Development Team # This software is distributed under the terms of the MIT License. # Author: Pavel Kirienko <pavel.kirienko@zubax.com> # """ Serial transport overview +++++++++++++++++++++++++ The serial transport is experimental and is not yet part of the UAVCAN specification. Future revisions may break wire compatibility until the transport is formally specified. Context: https://forum.uavcan.org/t/alternative-transport-protocols/324, also see the discussion at https://forum.uavcan.org/t/yukon-design-megathread/390/115?u=pavel.kirienko. The serial transport is designed for OSI L1 byte-level serial links: - UART, RS-232/485/422 (the recommended rates are: 115200 bps, 921600 bps, 3 Mbps, 10 Mbps, 100 Mbps); copper or fiber optics. - USB CDC ACM. It is also suitable for raw transport log storage, because one-dimensional flat binary files are structurally similar to serial byte-level links. This transport module contains no media sublayers because the media abstraction is handled directly by the `PySerial <https://pypi.org/project/pyserial>`_ library and the underlying operating system. The serial transport supports all transfer categories: +--------------------+--------------------------+---------------------------+ | Supported transfers| Unicast | Broadcast | +====================+==========================+===========================+ |**Message** | Yes | Yes | +--------------------+--------------------------+---------------------------+ |**Service** | Yes | Banned by Specification | +--------------------+--------------------------+---------------------------+ Protocol definition +++++++++++++++++++ The packet header is defined as follows (byte and bit ordering in this definition follow the DSDL specification: least significant byte first, most significant bit first):: uint8 version # Always zero. Discard the frame if not. uint8 priority # 0 = highest, 7 = lowest; the rest are unused. uint16 source node ID # 0xFFFF = anonymous. uint16 destination node ID # 0xFFFF = broadcast. uint16 data specifier uint64 data type hash uint64 transfer ID uint32 frame index EOT # MSB set if last frame of the transfer. void32 # Set to zero when sending, ignore when receiving. For message frames, the data specifier field contains the subject-ID value, so that the most significant bit is always cleared. For service frames, the most significant bit (15th) is always set, and the second-to-most-significant bit (14th) is set for response transfers only; the remaining 14 least significant bits contain the service-ID value. Total header size: 32 bytes (256 bits). The header is prepended before the frame payload; the resulting structure is encoded into its serialized form using the following packet format (influenced by HDLC, SLIP, POPCOP): +------------------------+-----------------------+-----------------------+------------------------+ |Frame delimiter **0x9E**|Escaped header+payload |CRC32C (Castagnoli) |Frame delimiter **0x9E**| +========================+=======================+=======================+========================+ |Single-byte frame |The following bytes are|Four bytes long, |Same frame delimiter as | |delimiter **0x9E**. |escaped: **0x9E** |little-endian byte |at the start. | |Begins a new frame and |(frame delimiter); |order; bytes 0x9E |Terminates the current | |possibly terminates the |**0x8E** (escape |(frame delimiter) and |frame and possibly | |previous frame. |character). An escaped |0x8E (escape character)|begins the next frame. | | |byte is bitwise |are escaped like in | | | |inverted and prepended |the payload. | | | |with the escape |The CRC is computed | | | |character 0x8E. For |over the unescaped | | | |example: byte 0x9E is |(i.e., original form) | | | |transformed into 0x8E |payload, not including | | | |followed by 0x71. |the start delimiter. | | +------------------------+-----------------------+-----------------------+------------------------+ There are no magic bytes in this format because the strong CRC and the data type hash field render the format sufficiently recognizable. The worst case overhead exceeds 100% if every byte of the payload and the CRC is either 0x9E or 0x8E. Despite the overhead, this format is still considered superior to the alternatives since it is robust and guarantees a constant recovery time. Consistent-overhead byte stuffing (COBS) is sometimes employed for similar tasks, but it should be understood that while it offers a substantially lower overhead, it undermines the synchronization recovery properties of the protocol. There is a somewhat relevant discussion at https://github.com/vedderb/bldc/issues/79. The format can share the same serial medium with ASCII text exchanges such as command-line interfaces or real-time logging. The special byte values employed by the format do not belong to the ASCII character set. The last four bytes of a multi-frame transfer payload contain the CRC32C (Castagnoli) hash of the transfer payload in little-endian byte order. The multi-frame transfer logic (decomposition and reassembly) is implemented in a separate transport-agnostic module :mod:`pyuavcan.transport.commons.high_overhead_transport`. Note that we use CRC-32C (Castagnoli) as the frame CRC instead of CRC-32K2 (Koopman-2) which is superior at short data blocks offering the Hamming distance of 6 as opposed to 4. This is because Castagnoli is superior for transfer CRC which is often sufficiently long to flip the balance in favor of Castagnoli rather than Koopman. We could use Koopman for frame CRC and keep Castagnoli for transfer CRC, but such diversity is harmful because it would require implementers to keep two separate CRC tables which may be costly in embedded applications and may deteriorate the performance of CPU caches. Unreliable links and temporal redundancy ++++++++++++++++++++++++++++++++++++++++ The serial transport supports the deterministic data loss mitigation option, where a transfer can be repeated several times to reduce the probability of its loss. This feature is discussed in detail in the documentation for the UDP transport :mod:`pyuavcan.transport.udp`. Usage +++++ >>> import pyuavcan >>> import pyuavcan.transport.serial >>> tr = pyuavcan.transport.serial.SerialTransport('loop://', local_node_id=1234, baudrate=115200) >>> tr.local_node_id 1234 >>> tr.serial_port.baudrate 115200 >>> pm = pyuavcan.transport.PayloadMetadata(0x_bad_c0ffee_0dd_f00d, 1024) >>> ds = pyuavcan.transport.MessageDataSpecifier(12345) >>> pub = tr.get_output_session(pyuavcan.transport.OutputSessionSpecifier(ds, None), pm) >>> sub = tr.get_input_session(pyuavcan.transport.InputSessionSpecifier(ds, None), pm) >>> await_ = tr.loop.run_until_complete >>> await_(pub.send_until(pyuavcan.transport.Transfer(pyuavcan.transport.Timestamp.now(), ... pyuavcan.transport.Priority.LOW, ... 1111, ... fragmented_payload=[]), ... tr.loop.time() + 1.0)) True >>> await_(sub.receive_until(tr.loop.time() + 1.0)) TransferFrom(..., transfer_id=1111, ...) >>> tr.close() Tooling +++++++ Serial data logging ~~~~~~~~~~~~~~~~~~~ The underlying PySerial library provides a convenient method of logging exchange through a serial port into a file. To invoke this feature, embed the name of the serial port into the URI ``spy:///dev/ttyUSB0?file=dump.txt``, where ``/dev/ttyUSB0`` is the name of the serial port, ``dump.txt`` is the name of the log file. TCP/IP tunneling ~~~~~~~~~~~~~~~~ For testing or experimentation it is often convenient to use a virtual link instead of a real one. The underlying PySerial library supports tunneling of raw serial data over TCP connections, which can be leveraged for local testing without accessing any physical serial ports. This option can be accessed by specifying the URI of the form ``socket://<address>:<port>`` instead of a real serial port name when establishing the connection. The location specified in the URL must point to the TCP server port that will forward the data to and from the other end of the link. While such a server can be trivially coded manually by the developer, it is possible to avoid the effort by relying on the TCP connection brokering mode available in Ncat (which is a part of the `Nmap <https://nmap.org>`_ project, thanks Fyodor). For example, one could set up the TCP broker as follows (add ``-v`` to see what's happening; more info at https://nmap.org/ncat/guide/ncat-broker.html) (the port number is chosen at random here):: ncat --broker --listen -p 50905 And then use a serial transport with ``socket://localhost:50905``. All nodes whose transports are configured like that will be able to communicate with each other, as if they were connected to the same bus. Essentially, this can be seen as a virtualized RS-485 bus, where same concerns regarding medium access coordination apply. The location of the URI doesn't have to be ``localhost``, of course -- one can use this approach to link UAVCAN nodes via conventional IP networks. The exchange over the virtual bus can be dumped trivially for analysis:: nc localhost 50905 > dump.bin Inheritance diagram +++++++++++++++++++ .. inheritance-diagram:: pyuavcan.transport.serial._serial pyuavcan.transport.serial._frame pyuavcan.transport.serial._session._base pyuavcan.transport.serial._session._input pyuavcan.transport.serial._session._output :parts: 1 """ from ._serial import SerialTransport as SerialTransport from ._serial import SerialTransportStatistics as SerialTransportStatistics from ._session import SerialSession as SerialSession from ._session import SerialInputSession as SerialInputSession from ._session import SerialOutputSession as SerialOutputSession from ._session import SerialFeedback as SerialFeedback from ._session import SerialInputSessionStatistics as SerialInputSessionStatistics from ._frame import SerialFrame as SerialFrame from ._stream_parser import StreamParser as StreamParser

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7895069a316d456c883029c91de5bc71345a87de

186

py

Python

djangobmf/contrib/task/apps.py

caputomarcos/django-bmf

0d07a7d3f6a3ecfaca6c9376e764add1715cfd33

[ "BSD-3-Clause" ]

1

2020-05-11T08:00:49.000Z

djangobmf/contrib/task/apps.py

caputomarcos/django-bmf

0d07a7d3f6a3ecfaca6c9376e764add1715cfd33

[ "BSD-3-Clause" ]

null

djangobmf/contrib/task/apps.py

caputomarcos/django-bmf

0d07a7d3f6a3ecfaca6c9376e764add1715cfd33

[ "BSD-3-Clause" ]

null

from __future__ import unicode_literals from djangobmf.apps import ContribTemplate class TaskConfig(ContribTemplate): name = 'djangobmf.contrib.task' label = "djangobmf_task"

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78a082198b5c1dc93ddab4dbad99f1ab99f7b92e

15

py

Python

examples/py30-0014-raise-from1.py

jwilk-forks/python-grammar-changes

5cbc14e520fadfef8539760a4ffdbe14b9d02f39

[ "MIT" ]

8

2020-11-21T22:39:41.000Z

2022-03-13T18:45:53.000Z

examples/py30-0014-raise-from1.py

jwilk-forks/python-grammar-changes

5cbc14e520fadfef8539760a4ffdbe14b9d02f39

[ "MIT" ]

1

2021-12-10T10:45:38.000Z

examples/py30-0014-raise-from1.py

jwilk-forks/python-grammar-changes

5cbc14e520fadfef8539760a4ffdbe14b9d02f39

[ "MIT" ]

1

2022-02-07T11:16:38.000Z

raise a from b

7.5

14

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78b386ba7ac7a2bb504dfd2488412f141915e20a

90

py

Python

Trabalho_2/module_control/some_app/apps.py

desenho-sw-g5/scc

ed0496f72643ac004d58126ac486a6e0c47643cd

[ "MIT" ]

3

2017-08-25T01:19:07.000Z

2018-04-17T03:13:59.000Z

Trabalho_2/module_control/some_app/apps.py

desenho-sw-g5/scc

ed0496f72643ac004d58126ac486a6e0c47643cd

[ "MIT" ]

3

2017-09-26T17:27:48.000Z

2017-11-24T10:22:25.000Z

Trabalho_2/module_control/some_app/apps.py

desenho-sw-g5/service_control

ed0496f72643ac004d58126ac486a6e0c47643cd

[ "MIT" ]

null

from django.apps import AppConfig class SomeAppConfig(AppConfig): name = 'some_app'

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153455bf2304976b453fa91c5faacc667195dea9

43

py

Python

tools/extra/pac/pyfpgaflash/opae/tools/fpgaflash/__init__.py

trixirt/opae-sdk

71ac5d4a7923826bc3b6c8e971b5b3b48a08044d

[ "BSD-3-Clause" ]

null

tools/extra/pac/pyfpgaflash/opae/tools/fpgaflash/__init__.py

trixirt/opae-sdk

71ac5d4a7923826bc3b6c8e971b5b3b48a08044d

[ "BSD-3-Clause" ]

null

tools/extra/pac/pyfpgaflash/opae/tools/fpgaflash/__init__.py

trixirt/opae-sdk

71ac5d4a7923826bc3b6c8e971b5b3b48a08044d

[ "BSD-3-Clause" ]

null

from fpgaflash import main __all__=['main']

21.5

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156ad90f8c5cda1ec4c3e1d659021d0cbc8c9973

149

py

Python

hydra/experimental/__init__.py

javakian/hydra

541748d74ec11158bea552ba3c1bee0e9c73078e

[ "MIT" ]

1

2019-12-29T17:58:59.000Z

hydra/experimental/__init__.py

javakian/hydra

541748d74ec11158bea552ba3c1bee0e9c73078e

[ "MIT" ]

6

2021-03-11T06:20:24.000Z

2022-02-27T10:43:29.000Z

hydra/experimental/__init__.py

javakian/hydra

541748d74ec11158bea552ba3c1bee0e9c73078e

[ "MIT" ]

null

29.8

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0.751678

18

149

6

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0.14094

149

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71

37.25

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1

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null

0

1

0

4

159187941720a04b6f6f97c11ebb917d59c46135

121

py

Python

heroku_run.py

PhotoScout/API

24c2040b0a2fcb1ea906c7aa095c9e74d3ca4fa9

[ "MIT" ]

null

heroku_run.py

PhotoScout/API

24c2040b0a2fcb1ea906c7aa095c9e74d3ca4fa9

[ "MIT" ]

null

heroku_run.py

PhotoScout/API

24c2040b0a2fcb1ea906c7aa095c9e74d3ca4fa9

[ "MIT" ]

null

import os from app import app, db db.create_all() app.run(debug=True, host='0.0.0.0', port=int(os.environ.get('PORT')))

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null

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4

15a5e9504591e346eb126cbd88d45e5fdb9016fe

113

py

Python

golumn/__main__.py

ddrscott/golumn

c8c7bb58cbcf084d0882426b3eec759805cb23ff

[ "MIT" ]

2

2018-03-06T16:25:46.000Z

2022-01-15T16:06:14.000Z

golumn/__main__.py

ddrscott/golumnpy

c8c7bb58cbcf084d0882426b3eec759805cb23ff

[ "MIT" ]

14

2017-11-16T09:14:33.000Z

2022-01-13T03:54:33.000Z

golumn/__main__.py

ddrscott/golumnpy

c8c7bb58cbcf084d0882426b3eec759805cb23ff

[ "MIT" ]

1

2020-08-16T15:07:09.000Z

#!/usr/bin/env pythonw import sys from golumn.cli import main if __name__ == '__main__': sys.exit(main())

12.555556

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8

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ec5d176a8f8c1118e23be5253be2b8c6b8c22bda

115

py

Python

salesforce_problems/problem_2.py

loftwah/Daily-Coding-Problem

0327f0b4f69ef419436846c831110795c7a3c1fe

[ "MIT" ]

129

2018-10-14T17:52:29.000Z

2022-01-29T15:45:57.000Z

salesforce_problems/problem_2.py

loftwah/Daily-Coding-Problem

0327f0b4f69ef419436846c831110795c7a3c1fe

[ "MIT" ]

2

2019-11-30T23:28:23.000Z

2020-01-03T16:30:32.000Z

salesforce_problems/problem_2.py

loftwah/Daily-Coding-Problem

0327f0b4f69ef419436846c831110795c7a3c1fe

[ "MIT" ]

60

2019-02-21T09:18:31.000Z

2022-03-25T21:01:04.000Z

"""This problem was asked by Salesforce. Given an array of integers, find the maximum XOR of any two elements. """

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eca10f1927299cfd33eaf47cf679ebbdb2384cb2

208

py

Python

1-beginner/1008.py

alenvieira/uri-online-judge-solutions

ca5ae7064d84af4dae12fc37d4d14ee441e49d06

[ "MIT" ]

null

1-beginner/1008.py

alenvieira/uri-online-judge-solutions

ca5ae7064d84af4dae12fc37d4d14ee441e49d06

[ "MIT" ]

null

1-beginner/1008.py

alenvieira/uri-online-judge-solutions

ca5ae7064d84af4dae12fc37d4d14ee441e49d06

[ "MIT" ]

null

number_employee = int(input('')) hours = int(input()) value_work_hour = float(input()) salary = hours * value_work_hour print('NUMBER = {}'.format(number_employee)) print('SALARY = U$ {:.2f}'.format(salary))

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ecb28c627a92fb40e11f51dcd51a37069b67c455

140

py

Python

amqp_events/types.py

tumb1er/celery-amqp-events

ec9543e4eab97bcbad74597be83555af116a25ea

[ "MIT" ]

1

2021-03-05T20:14:49.000Z

amqp_events/types.py

just-work/celery-amqp-events

a6a2236ceb9ba982bfd733aa0a858da8443a69e9

[ "MIT" ]

21

2020-09-18T07:52:03.000Z

2022-03-06T07:29:21.000Z

amqp_events/types.py

tumb1er/celery-amqp-events

ec9543e4eab97bcbad74597be83555af116a25ea

[ "MIT" ]

2

2020-10-01T12:29:37.000Z

2020-10-31T17:37:07.000Z

try: from typing import Protocol except ImportError: from typing_extensions import Protocol # type: ignore __all__ = ['Protocol']

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0

1

0

4

ecc55d3781d1846b215952c4eb5ca12dd8cd18ba

3,043

py

Python

configs/data_configs.py

snakch/pixel2style2pixel

63e9c397daf7d4e81dc963a14231990b510ec1a8

[ "Apache-2.0", "BSD-2-Clause", "MIT" ]

null

configs/data_configs.py

snakch/pixel2style2pixel

63e9c397daf7d4e81dc963a14231990b510ec1a8

[ "Apache-2.0", "BSD-2-Clause", "MIT" ]

null

configs/data_configs.py

snakch/pixel2style2pixel

63e9c397daf7d4e81dc963a14231990b510ec1a8

[ "Apache-2.0", "BSD-2-Clause", "MIT" ]

null

from configs import transforms_config from configs.paths_config import dataset_paths DATASETS = { "ffhq_encode": { "transforms": transforms_config.EncodeTransforms, "train_source_root": dataset_paths["ffhq_512"], "train_target_root": dataset_paths["ffhq_512"], "test_source_root": dataset_paths["ffhq_512_val"], "test_target_root": dataset_paths["ffhq_512_val"], }, "ffhq_encode_cond": { "transforms": transforms_config.EncodeTransforms, "train_source_root": dataset_paths["ffhq_512_cond"], "train_target_root": dataset_paths["ffhq_512_cond"], "test_source_root": dataset_paths["ffhq_512_cond_val"], "test_target_root": dataset_paths["ffhq_512_cond_val"], "labels": dataset_paths["ffhq_512_labels"], }, "paired_gens": { "transforms": transforms_config.PairedEncodeTransforms, "train_source_root": dataset_paths["paired_gens_input"], "train_target_root": dataset_paths["paired_gens_output"], "test_source_root": dataset_paths["paired_gens_val_input"], "test_target_root": dataset_paths["paired_gens_val_output"], }, "paired_gens_latent": { "transforms": transforms_config.PairedEncodeTransforms, "train_source_root": dataset_paths["paired_gens_input"], "train_target_root": dataset_paths["paired_gens_output"], "train_latents_root": dataset_paths["paired_gens_latents"], "test_source_root": dataset_paths["paired_gens_val_input"], "test_target_root": dataset_paths["paired_gens_val_output"], "test_latents_root": dataset_paths["paired_gens_val_latents"], }, "ffhq_frontalize": { "transforms": transforms_config.FrontalizationTransforms, "train_source_root": dataset_paths["ffhq"], "train_target_root": dataset_paths["ffhq"], "test_source_root": dataset_paths["celeba_test"], "test_target_root": dataset_paths["celeba_test"], }, "celebs_sketch_to_face": { "transforms": transforms_config.SketchToImageTransforms, "train_source_root": dataset_paths["celeba_train_sketch"], "train_target_root": dataset_paths["celeba_train"], "test_source_root": dataset_paths["celeba_test_sketch"], "test_target_root": dataset_paths["celeba_test"], }, "celebs_seg_to_face": { "transforms": transforms_config.SegToImageTransforms, "train_source_root": dataset_paths["celeba_train_segmentation"], "train_target_root": dataset_paths["celeba_train"], "test_source_root": dataset_paths["celeba_test_segmentation"], "test_target_root": dataset_paths["celeba_test"], }, "celebs_super_resolution": { "transforms": transforms_config.SuperResTransforms, "train_source_root": dataset_paths["celeba_train"], "train_target_root": dataset_paths["celeba_train"], "test_source_root": dataset_paths["celeba_test"], "test_target_root": dataset_paths["celeba_test"], }, }

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null

1

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1

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null

0

4

019dadbea9a7d4c15db215f57cb2a80dd22d4820

9,744

py

Python

fw_babi/lnfw_rnn_cell.py

akandykeller/fast_weights

ea751556387c5ab6254a25847a7b763a27a9179b

[ "MIT" ]

1

2021-07-08T07:50:28.000Z

fw_babi/lnfw_rnn_cell.py

akandykeller/fast_weights

ea751556387c5ab6254a25847a7b763a27a9179b

[ "MIT" ]

null

fw_babi/lnfw_rnn_cell.py

akandykeller/fast_weights

ea751556387c5ab6254a25847a7b763a27a9179b

[ "MIT" ]

null

""" Fast Weights Cell. Ba et al. Using Fast Weights to Attend to the Recent Past https://arxiv.org/abs/1610.06258 """ from tensorflow.contrib.rnn import RNNCell import tensorflow as tf import numpy as np class FastWeightsRNNCell(RNNCell): def __init__(self, num_hidden_units, batch_size, loop_steps=1, decay_rate=0.95, eta=0.5, dropout_keep_prob=1.0): super(FastWeightsRNNCell, self).__init__() self._num_hidden_units = num_hidden_units self._keep_prob = dropout_keep_prob self._batch_size = batch_size self._S = loop_steps self._e = eta self._l = decay_rate @property def state_size(self): return self._num_hidden_units @property def output_size(self): return self._num_hidden_units def zero_state(self, batch_size=None, dtype=None): A = tf.zeros( [self._batch_size, self._num_hidden_units, self._num_hidden_units], dtype=tf.float32) h = tf.zeros( [self._batch_size, self._num_hidden_units], dtype=tf.float32) return (h, A) def __call__(self, inputs, state, scope=None): # Split recurrent input into state and FW state, A = state # Recover vairables from scope W_x = tf.get_variable(name='W_x') b_x = tf.get_variable(name='b_x') W_h = tf.get_variable(name='W_h') gain = tf.get_variable(name='gain') bias = tf.get_variable(name='bias') state = tf.nn.dropout(state, self._keep_prob) state = tf.nn.relu((tf.matmul(inputs, W_x) + b_x) + tf.matmul(state, W_h)) h_s = tf.reshape(state, [self._batch_size, 1, self._num_hidden_units]) A = tf.add(tf.scalar_mul(self._l, A), tf.scalar_mul(self._e, tf.matmul(tf.transpose(h_s, [0, 2, 1]), h_s))) for _ in range(self._S): h_s = tf.reshape(tf.matmul(inputs, W_x) + b_x, tf.shape(h_s)) \ + tf.reshape(tf.matmul(state, W_h), tf.shape(h_s)) \ + tf.matmul(h_s, A) # Apply layernorm mu = tf.reduce_mean(h_s, axis=2) # each sample sigma = tf.sqrt(tf.reduce_mean(tf.square(tf.squeeze(h_s) - mu), axis=1)) h_s = tf.divide(tf.multiply(gain, (tf.squeeze(h_s) - mu)), tf.expand_dims(sigma, -1)) + bias # Apply nonlinearity h_s = tf.nn.relu(h_s) # Expand for future S steps h_s = tf.expand_dims(h_s, 1) # Reshape h_s into h h = tf.reshape(h_s, [self._batch_size, self._num_hidden_units]) return h, (h, A) class FastWeightsLSTMCell(RNNCell): def __init__(self, num_hidden_units, batch_size, loop_steps=1, forget_bias=1.0, layer_norm=True, decay_rate=0.95, eta=0.5, dropout_keep_prob=1.0): super(FastWeightsLSTMCell, self).__init__() # Parameters of gates are concatenated into one multiply for efficiency. self._num_hidden_units = num_hidden_units self._keep_prob = dropout_keep_prob self._batch_size = batch_size self._S = loop_steps self.forget_bias = forget_bias self._e = eta self._l = decay_rate self._layer_norm = layer_norm @property def state_size(self): return self._num_hidden_units @property def output_size(self): return self._num_hidden_units def zero_state(self, batch_size=None, dtype=None): A = tf.zeros( [self._batch_size, 4 * self._num_hidden_units, 4 * self._num_hidden_units], dtype=tf.float32) h = tf.zeros( [self._batch_size, self._num_hidden_units], dtype=tf.float32) c = tf.zeros( [self._batch_size, self._num_hidden_units], dtype=tf.float32) return (h, c, A) def __call__(self, inputs, state, scope=None): # Split recurrent input into state and FW h, c, A = state # Recover vairables from scope W_ifoj = tf.get_variable(name='W_ifoj') # [1, 4 * num_hidden] b_ifoj = tf.get_variable(name='b_ifoj') gain_ifoj = tf.get_variable(name='gain_ifoj') bias_ifoj = tf.get_variable(name='bias_ifoj') gain_state = tf.get_variable(name='gain_state') bias_state = tf.get_variable(name='bias_state') h_x = tf.concat(axis=1, values=[h, inputs]) ifoj = tf.matmul(h_x, W_ifoj) + b_ifoj if self._layer_norm: mu_ifoj = tf.expand_dims(tf.reduce_mean(ifoj, axis=1), -1) # each sample sigma_ifoj = tf.sqrt(tf.reduce_mean(tf.square(tf.squeeze(ifoj) - mu_ifoj), axis=1)) ifoj = tf.divide(tf.multiply(gain_ifoj, (tf.squeeze(ifoj) - mu_ifoj)), tf.expand_dims(sigma_ifoj, -1)) + bias_ifoj i = ifoj[:, :self._num_hidden_units] f = ifoj[:, self._num_hidden_units : 2 * self._num_hidden_units] o = ifoj[:, 2 * self._num_hidden_units : 3 * self._num_hidden_units] j = ifoj[:, 3 * self._num_hidden_units :] ifoj_relu = tf.nn.relu(ifoj) h_s = tf.reshape(ifoj_relu, [self._batch_size, 1, 4 * self._num_hidden_units]) A = tf.add(tf.scalar_mul(self._l, A), tf.scalar_mul(self._e, tf.matmul(tf.transpose(h_s, [0, 2, 1]), h_s))) ifoj_A = tf.squeeze(tf.matmul(h_s, A)) i_A = ifoj_A[:, :self._num_hidden_units] f_A = ifoj_A[:, self._num_hidden_units : 2 * self._num_hidden_units] o_A = ifoj_A[:, 2 * self._num_hidden_units : 3 * self._num_hidden_units] j_A = ifoj_A[:, 3 * self._num_hidden_units :] g = tf.nn.relu(j + j_A) g = tf.nn.dropout(g, self._keep_prob) for _ in range(self._S): new_c = (c * tf.nn.sigmoid(f + f_A + self.forget_bias) + tf.nn.sigmoid(i + i_A) * g) # Apply layernorm if self._layer_norm: mu = tf.expand_dims(tf.reduce_mean(new_c, axis=1), -1) # each sample sigma = tf.sqrt(tf.reduce_mean(tf.square(tf.squeeze(new_c) - mu), axis=1)) new_c = tf.divide(tf.multiply(gain_state, (tf.squeeze(new_c) - mu)), tf.expand_dims(sigma, -1)) + bias_state # Apply nonlinearity new_h = tf.nn.relu(new_c) * tf.nn.sigmoid(o + o_A) # Expand for future S steps new_h = tf.expand_dims(new_h, 1) # Reshape new_h into h new_h = tf.reshape(new_h, [self._batch_size, self._num_hidden_units]) return new_h, (new_h, new_c, A) class FastWeightsRNNCell_Deconv(RNNCell): def __init__(self, num_hidden_units, batch_size, loop_steps=1, decay_rate=0.95, eta=0.5, dropout_keep_prob=1.0): super(FastWeightsRNNCell_Deconv, self).__init__() self._num_hidden_units = num_hidden_units self._keep_prob = dropout_keep_prob self._batch_size = batch_size self._S = loop_steps self._e = eta self._l = decay_rate @property def state_size(self): return self._num_hidden_units @property def output_size(self): return self._num_hidden_units def zero_state(self, batch_size=None, dtype=None): A = tf.zeros( [self._batch_size, self._num_hidden_units, self._num_hidden_units], dtype=tf.float32) A_deconv = tf.zeros( [self._batch_size, self._num_hidden_units, self._num_hidden_units], dtype=tf.float32) h = tf.zeros( [self._batch_size, self._num_hidden_units], dtype=tf.float32) return (h, A, A_deconv) def __call__(self, inputs, state, scope=None): # Split recurrent input into state and FW state, A, A_deconv = state # Recover vairables from scope W_x = tf.get_variable(name='W_x') b_x = tf.get_variable(name='b_x') W_conv = tf.get_variable(name='W_conv') W_h = tf.get_variable(name='W_h') gain = tf.get_variable(name='gain') bias = tf.get_variable(name='bias') state = tf.nn.dropout(state, self._keep_prob) state = tf.nn.relu((tf.matmul(inputs, W_x) + b_x) + tf.matmul(state, W_h)) h_s = tf.reshape(state, [self._batch_size, 1, self._num_hidden_units]) A_deconv_temp = tf.nn.conv2d_transpose(tf.expand_dims(h_s, -1), W_conv, output_shape=[self._batch_size, 1, self._num_hidden_units, self._num_hidden_units], strides=[1,1,1,1], padding='SAME') A_deconv = tf.add(tf.scalar_mul(self._l, A_deconv), tf.scalar_mul(self._e, tf.squeeze(A_deconv_temp))) A = tf.add(tf.scalar_mul(self._l, A), tf.scalar_mul(self._e, tf.matmul(tf.transpose(h_s, [0, 2, 1]), h_s))) for _ in range(self._S): h_s = tf.reshape(tf.matmul(inputs, W_x) + b_x, tf.shape(h_s)) \ + tf.reshape(tf.matmul(state, W_h), tf.shape(h_s)) \ + tf.matmul(h_s, A) \ + tf.matmul(h_s, A_deconv) # Apply layernorm mu = tf.reduce_mean(h_s, axis=2) # each sample sigma = tf.sqrt(tf.reduce_mean(tf.square(tf.squeeze(h_s) - mu), axis=1)) h_s = tf.divide(tf.multiply(gain, (tf.squeeze(h_s) - mu)), tf.expand_dims(sigma, -1)) + bias # Apply nonlinearity h_s = tf.nn.relu(h_s) # Expand for future S steps h_s = tf.expand_dims(h_s, 1) # Reshape h_s into h h = tf.reshape(h_s, [self._batch_size, self._num_hidden_units]) return h, (h, A, A_deconv)

36.223048

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null

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1

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1

0

null

0

4

01ad598427827ed6e83dffb02d5adbb14a40bc1a

1,248

py

Python

Schedule/courses/models.py

f0rdream/party-time

3b596043627383859042a6e70167e4304bab9a92

[ "MIT" ]

null

Schedule/courses/models.py

f0rdream/party-time

3b596043627383859042a6e70167e4304bab9a92

[ "MIT" ]

null

Schedule/courses/models.py

f0rdream/party-time

3b596043627383859042a6e70167e4304bab9a92

[ "MIT" ]

null

from __future__ import unicode_literals from django.contrib.auth.models import User from django.db import models class Student(models.Model): user = models.OneToOneField(User) user_stu_id = models.CharField(max_length=20,blank=False) user_stu_pwd = models.CharField(max_length=100,blank=False) class Course(models.Model): user = models.ForeignKey(User) stu_name = models.CharField(max_length=100,blank=True,null=True) stu_term = models.CharField(max_length=100,blank=True,null=True) course_num = models.CharField(max_length=100,blank=True,null=True) course_name = models.CharField(max_length=100,blank=True,null=True) course_type = models.CharField(max_length=100,blank=True,null=True) course_college = models.CharField(max_length=100,blank=True,null=True) course_teacher = models.CharField(max_length=100,blank=True,null=True) course_major = models.CharField(max_length=100,blank=True,null=True) course_point = models.CharField(max_length=100,blank=True,null=True) day = models.CharField(max_length=100,blank=True,null=True) start_num = models.CharField(max_length=100,blank=True,null=True) end_num = models.CharField(max_length=100,blank=True,null=True) # Create your models here.

52

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4.978723

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0.269231

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0.661325

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0.036804

0.107372

1,248

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null

1

0

null

0

1

0

4

01ff0323be7fbcb4b3040ef12d4d0c37c39c2c0a

254

py

Python

pyradox/convnets/__init__.py

p4vv37/pyradox

cfc8c07d637a1cc189dd8d200f8a55d00405b81f

[ "MIT" ]

61

2021-01-10T09:31:32.000Z

2022-02-13T13:30:48.000Z

pyradox/convnets/__init__.py

p4vv37/pyradox

cfc8c07d637a1cc189dd8d200f8a55d00405b81f

[ "MIT" ]

1

2021-04-24T12:03:19.000Z

pyradox/convnets/__init__.py

p4vv37/pyradox

cfc8c07d637a1cc189dd8d200f8a55d00405b81f

[ "MIT" ]

6

2021-01-17T16:17:35.000Z

2022-02-13T13:30:49.000Z

from .densenets import * from .vgg import * from .inceptionnet import * from .xceptionnet import * from .efficientnet import * from .resnet import * from .inceptionresnet import * from .nasnet import * from .mobilenet import * from .segmentation import *

25.4

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6.5

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null

0

1

0

1

0

1

0

4

bf02f90c6dbf0d8596ef3a6390e1b8d53be2b792

168

py

Python

product/models/__init__.py

puchopsky/pythonPdv

3a53212840c83f577be4b6a48774a4399e1bee04

[ "MIT" ]

null

product/models/__init__.py

puchopsky/pythonPdv

3a53212840c83f577be4b6a48774a4399e1bee04

[ "MIT" ]

null

product/models/__init__.py

puchopsky/pythonPdv

3a53212840c83f577be4b6a48774a4399e1bee04

[ "MIT" ]

null

from .product import Product as _Product from .salePrice import SalePrice as _SalePrice from .saleForm import SaleForm as _SaleForm from .stock import Stock as _Stock

28

46

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24

168

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0

1

0

null

0

1

0

1

0

4

bf240aa22007b568a6e2cbc7b1f766b2c0551253

157

py

Python

blacklisting/api/models.py

rakesht2499/Blacklisting

b1020e388af04d2276f297bfa450f19db7ce9a47

[ "Apache-2.0" ]

1

2020-05-07T10:53:22.000Z

blacklisting/api/models.py

rakesht2499/Blacklisting

b1020e388af04d2276f297bfa450f19db7ce9a47

[ "Apache-2.0" ]

4

2021-03-30T13:13:33.000Z

2021-06-10T19:03:05.000Z

blacklisting/api/models.py

rakesht2499/Blacklisting

b1020e388af04d2276f297bfa450f19db7ce9a47

[ "Apache-2.0" ]

null

from django.db import models class Ipv4(models.Model): ip = models.CharField(max_length=15, unique=True) def __str__(self): return self.ip

19.625

53

0.694268

23

157

4.521739

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0

0.024

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157

7

54

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1

0.2

false

0

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0

null

0

1

0

null

0

1

0

4

170f43d0f36eb117c7a086636b2c5e36682b9fd4

27

py

Python

python/testData/postfix/isNotNone/function.py

jnthn/intellij-community

8fa7c8a3ace62400c838e0d5926a7be106aa8557

[ "Apache-2.0" ]

2

2019-04-28T07:48:50.000Z

2020-12-11T14:18:08.000Z

python/testData/postfix/isNotNone/function.py

Cyril-lamirand/intellij-community

60ab6c61b82fc761dd68363eca7d9d69663cfa39

[ "Apache-2.0" ]

173

2018-07-05T13:59:39.000Z

2018-08-09T01:12:03.000Z

python/testData/postfix/isNotNone/function.py

Cyril-lamirand/intellij-community

60ab6c61b82fc761dd68363eca7d9d69663cfa39

[ "Apache-2.0" ]

2

2020-03-15T08:57:37.000Z

2020-04-07T04:48:14.000Z

def f(a): a.ifnn<caret>

13.5

17

0.555556

6

27

2.5

0.833333

0

0.222222

27

2

17

13.5

0.714286

0

null

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null

0

1

0

null

0

1

0

null

0

1

0

4

1748116b8fd6a397f1af9ca75a02817046405cdb

319

py

Python

Contents/Libraries/Shared/PicartoClientAPI/apis/__init__.py

Sythelux/Picarto.bundle

f2e9e9e75421b15c562c961c8c31090c508166ff

[ "BSD-3-Clause" ]

null

Contents/Libraries/Shared/PicartoClientAPI/apis/__init__.py

Sythelux/Picarto.bundle

f2e9e9e75421b15c562c961c8c31090c508166ff

[ "BSD-3-Clause" ]

5

2018-01-29T23:18:20.000Z

2018-01-29T23:57:15.000Z

Contents/Libraries/Shared/PicartoClientAPI/apis/__init__.py

Sythelux/Picarto.bundle

f2e9e9e75421b15c562c961c8c31090c508166ff

[ "BSD-3-Clause" ]

null

from __future__ import absolute_import # import apis into api package from .bot_api import BotApi from .channel_api import ChannelApi from .multistream_api import MultistreamApi from .public_api import PublicApi from .sensitive_api import SensitiveApi from .user_api import UserApi from .webhook_api import WebhookApi

29

43

0.852665

45

319

5.777778

0.488889

0.242308

0

0.122257

319

10

44

31.9

0.928571

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0

1

0

true

0

1

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1

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null

1

0

null

0

1

0

1

0

1

0

4

1778023afc5b25080b344112b460e3521e4c1928

534

py

Python

super_material/integrate/IntegrandBoundary.py

pleroux0/super_material

b64d74afdeab7639dd1b220f8b23ade22d87c481

[ "BSD-2-Clause" ]

3

2020-10-20T00:37:59.000Z

2021-07-17T12:59:52.000Z

super_material/integrate/IntegrandBoundary.py

pleroux0/super_material

b64d74afdeab7639dd1b220f8b23ade22d87c481

[ "BSD-2-Clause" ]

null

super_material/integrate/IntegrandBoundary.py

pleroux0/super_material

b64d74afdeab7639dd1b220f8b23ade22d87c481

[ "BSD-2-Clause" ]

2

2020-10-02T14:31:07.000Z

2021-08-15T10:00:29.000Z

from math import isfinite, isnan class IntegrandBoundary: _value: float _defined_on_boundary: bool def __init__(self, value, defined_on_boundary: bool): assert not isnan(value) self._value = value self._defined_on_boundary = defined_on_boundary def is_finite(self) -> bool: return isfinite(self.value()) def value(self) -> float: return self._value def defined_on_boundary(self) -> bool: return self._defined_on_boundary __all__ = ["IntegrandBoundary"]

21.36

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null

0

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1

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4

179aef6da834baa3854371f6ac54de4263ebd04d

142

py

Python

src/week1-getting-started/Create-Git-Repo-Notebook.py

xzhnshng/databricks-zero-to-mlops

f1691c6f6137ad8b938e64cea4700c7011efb800

[ "CC0-1.0" ]

null

src/week1-getting-started/Create-Git-Repo-Notebook.py

xzhnshng/databricks-zero-to-mlops

f1691c6f6137ad8b938e64cea4700c7011efb800

[ "CC0-1.0" ]

null

src/week1-getting-started/Create-Git-Repo-Notebook.py

xzhnshng/databricks-zero-to-mlops

f1691c6f6137ad8b938e64cea4700c7011efb800

[ "CC0-1.0" ]

null

# Databricks notebook source print("hello world") # COMMAND ---------- print("let's make some changes and commit!") # COMMAND ----------

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142

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1

0

null

0

1

0

1

0

4

bd64114b036e93c8484fe46f411041bf9e5ccc90

89

py

Python

seed.py

erowley2501/fixlet-historian

c1aae462f7385ad4948415a2f26fd09d674e2275

[ "Apache-2.0" ]

5

2018-04-26T20:17:22.000Z

2022-02-03T03:13:25.000Z

seed.py

erowley2501/fixlet-historian

c1aae462f7385ad4948415a2f26fd09d674e2275

[ "Apache-2.0" ]

3

2016-08-11T21:04:38.000Z

2020-03-10T15:29:06.000Z

seed.py

erowley2501/fixlet-historian

c1aae462f7385ad4948415a2f26fd09d674e2275

[ "Apache-2.0" ]

2

2016-08-11T21:06:00.000Z

2019-11-20T15:39:30.000Z

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

12.714286

26

0.685393

11

89

4.818182

0.909091

0

0.168539

89

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27

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1

0

null

0

1

0

1

0

4

bd7a74b49d6034cae8f500d199da349d256934f4

102

py

Python

examples/simple_app/app/routes.py

webdeveloppro/aiohttp-boilerplate

5c74b688e63ec648cf70e3cfa93635ccea07db6a

[ "MIT" ]

4

2018-08-21T15:55:34.000Z

2021-12-14T14:12:12.000Z

examples/simple_app/app/routes.py

webdeveloppro/aiohttp-boilerplate

5c74b688e63ec648cf70e3cfa93635ccea07db6a

[ "MIT" ]

5

2018-05-26T21:15:35.000Z

2020-09-07T08:44:28.000Z

examples/simple_app/app/routes.py

webdeveloppro/aiohttp-boilerplate

5c74b688e63ec648cf70e3cfa93635ccea07db6a

[ "MIT" ]

4

2018-05-07T19:53:29.000Z

2021-11-16T15:49:25.000Z

from . import views def setup_routes(app): app.router.add_route("GET", "/", views.PostListView)

17

56

0.696078

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102

4.928571

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0.147059

102

5

57

20.4

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1

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null

0

1

0

1

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bd83c01ccbb094d9dd58679d848ed2d6daffa1cf

173

py

Python

accounts/apps.py

x3niasweden/fomalhaut-panel

8b4b3d81e2c91bef8f24ccbaf9cf898a47ac38a6

[ "MIT" ]

14

2017-08-01T08:28:00.000Z

2020-08-29T06:55:16.000Z

accounts/apps.py

x3niasweden/fomalhaut-panel

8b4b3d81e2c91bef8f24ccbaf9cf898a47ac38a6

[ "MIT" ]

1

2021-03-29T06:16:34.000Z

accounts/apps.py

x3niasweden/fomalhaut-panel

8b4b3d81e2c91bef8f24ccbaf9cf898a47ac38a6

[ "MIT" ]

12

2017-07-18T02:59:03.000Z

2021-03-23T04:04:58.000Z

# !/usr/bin/env python # -*- coding: utf-8 -*- # created by restran on 2016/01/04 from django.apps import AppConfig class AccountsConfig(AppConfig): name = 'accounts'

19.222222

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0.693642

24

173

5

0.958333

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0.16763

173

8

35

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0

null

0

1

0

1

0

4

bdcb1a8529a333e469aa7e0b822eaedeb27197af

86

py

Python

updatable/__main__.py

anx-bhagmann/updatable

0d84dd440c7bea0790784ceea6dc12962748698e

[ "MIT" ]

23

2017-11-15T09:57:54.000Z

2021-11-09T11:05:36.000Z

updatable/__main__.py

anx-bhagmann/updatable

0d84dd440c7bea0790784ceea6dc12962748698e

[ "MIT" ]

10

2018-04-17T07:46:24.000Z

2021-12-27T21:24:08.000Z

updatable/__main__.py

anx-bhagmann/updatable

0d84dd440c7bea0790784ceea6dc12962748698e

[ "MIT" ]

9

2017-08-25T07:55:22.000Z

2020-10-09T07:19:58.000Z

from updatable.console import _updatable if __name__ == '__main__': _updatable()

17.2

40

0.744186

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86

6

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86

4

41

21.5

0.75

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0

true

0

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1

0

null

0

1

0

1

0

4

bdfe72787217fbeed7e0767f901365fb98bd66f1

73

py

Python

start.py

ronligt/workshop_myrr

f898014301c3bc00179b71b6326803cc32847c6b

[ "MIT" ]

null

start.py

ronligt/workshop_myrr

f898014301c3bc00179b71b6326803cc32847c6b

[ "MIT" ]

null

start.py

ronligt/workshop_myrr

f898014301c3bc00179b71b6326803cc32847c6b

[ "MIT" ]

null

#!/usr/bin/env python from workshop import workshop workshop.example()

12.166667

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0

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5

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true

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0

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null

0

1

0

1

0

4

da0f610075e011ecc42c7e423c570c29d30fd0ad

246

py

Python

vivisect/analysis/arm/renaming.py

rnui2k/vivisect

b7b00f2d03defef28b4b8c912e3a8016e956c5f7

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

716

2015-01-01T14:41:11.000Z

2022-03-28T06:51:50.000Z

vivisect/analysis/arm/renaming.py

rnui2k/vivisect

b7b00f2d03defef28b4b8c912e3a8016e956c5f7

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

266

2015-01-01T15:07:27.000Z

2022-03-30T15:19:26.000Z

vivisect/analysis/arm/renaming.py

rnui2k/vivisect

b7b00f2d03defef28b4b8c912e3a8016e956c5f7

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

159

2015-01-01T16:19:44.000Z

2022-03-21T21:55:34.000Z

def analyze(vw): for fva in vw.getFunctions(): analyzeFunction(vw, fva) def analyzeFunction(vw, fva): fakename = vw.getName(fva+1) if fakename is not None: vw.makeName(fva+1, None) vw.makeName(fva, fakename)

22.363636

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246

4.588235

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246

10

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0

0.25

0

null

1

0

null

0

1

0

4

da68d9a11bb4f2dec0230466c2701915e7666077

202

py

Python

python/testData/deprecation/deprecatedProperty.py

truthiswill/intellij-community

fff88cfb0dc168eea18ecb745d3e5b93f57b0b95

[ "Apache-2.0" ]

2

2019-04-28T07:48:50.000Z

2020-12-11T14:18:08.000Z

python/testData/deprecation/deprecatedProperty.py

truthiswill/intellij-community

fff88cfb0dc168eea18ecb745d3e5b93f57b0b95

[ "Apache-2.0" ]

173

2018-07-05T13:59:39.000Z

2018-08-09T01:12:03.000Z

python/testData/deprecation/deprecatedProperty.py

truthiswill/intellij-community

fff88cfb0dc168eea18ecb745d3e5b93f57b0b95

[ "Apache-2.0" ]

2

2020-03-15T08:57:37.000Z

2020-04-07T04:48:14.000Z

class Foo: @property def bar(self): import warnings warnings.warn("this is deprecated", DeprecationWarning, 2) foo = Foo() foo.<warning descr="this is deprecated">bar</warning>

22.444444

66

0.663366

25

202

5.36

0.64

0.089552

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0

0.006329

0.217822

202

8

67

25.25

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null

0

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1

0

1

0

null

0

1

0

4

e537287b7f781315c86540b3f69460d585384e7b

2,151

py

Python

my_app/migrations/0002_auto_20210417_1252.py

B0und/kotanima_server

01b25531de219d16831d97a76c7e5f6326b6e99d

[ "MIT" ]

1

2021-10-03T20:20:22.000Z

my_app/migrations/0002_auto_20210417_1252.py

Kotanima/kotanima_server

01b25531de219d16831d97a76c7e5f6326b6e99d

[ "MIT" ]

null

my_app/migrations/0002_auto_20210417_1252.py

Kotanima/kotanima_server

01b25531de219d16831d97a76c7e5f6326b6e99d

[ "MIT" ]

null

# Generated by Django 3.1.6 on 2021-04-17 12:52 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('my_app', '0001_initial'), ] operations = [ migrations.AlterField( model_name='redditpost', name='author', field=models.CharField(blank=True, max_length=20), ), migrations.AlterField( model_name='redditpost', name='created_utc', field=models.CharField(blank=True, max_length=10), ), migrations.AlterField( model_name='redditpost', name='dislike', field=models.BooleanField(blank=True, default=None, null=True), ), migrations.AlterField( model_name='redditpost', name='phash', field=models.CharField(blank=True, max_length=16, null=True), ), migrations.AlterField( model_name='redditpost', name='post_id', field=models.CharField(blank=True, max_length=6), ), migrations.AlterField( model_name='redditpost', name='selected', field=models.BooleanField(blank=True, default=False), ), migrations.AlterField( model_name='redditpost', name='source_link', field=models.TextField(blank=True, default=None, null=True), ), migrations.AlterField( model_name='redditpost', name='sub_name', field=models.CharField(blank=True, default=None, max_length=20), ), migrations.AlterField( model_name='redditpost', name='title', field=models.CharField(blank=True, max_length=300), ), migrations.AlterField( model_name='redditpost', name='url', field=models.CharField(blank=True, max_length=64), ), migrations.AlterField( model_name='redditpost', name='wrong_format', field=models.BooleanField(blank=True, default=False), ), ]

31.173913

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0.212585

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1

0

1

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null

0

4

e53ded8f1670dfe2a1b1018150d99e399f8426e0

59

py

Python

tests/__init__.py

jtpaasch/tabu

b39525e43b83deafecb4de27ea41819b5f656cee

[ "MIT" ]

null

tests/__init__.py

jtpaasch/tabu

b39525e43b83deafecb4de27ea41819b5f656cee

[ "MIT" ]

null

tests/__init__.py

jtpaasch/tabu

b39525e43b83deafecb4de27ea41819b5f656cee

[ "MIT" ]

null

# -*- coding: utf-8 -*- """All tests for the project."""

11.8

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0.525424

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59

3.875

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59

4

33

14.75

0.638298

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0

null

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null

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null

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null

true

0

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1

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null

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1

0

1

0

null

0

1

0

4

e548a586c2ebcbc1d2de6fe275c9f1232f3d12e5

268

py

Python

RecoBTag/ImpactParameter/python/candidateTrackCounting3D3rdComputer_cfi.py

SWuchterl/cmssw

769b4a7ef81796579af7d626da6039dfa0347b8e

[ "Apache-2.0" ]

6

2017-09-08T14:12:56.000Z

2022-03-09T23:57:01.000Z

RecoBTag/ImpactParameter/python/candidateTrackCounting3D3rdComputer_cfi.py

SWuchterl/cmssw

769b4a7ef81796579af7d626da6039dfa0347b8e

[ "Apache-2.0" ]

545

2017-09-19T17:10:19.000Z

2022-03-07T16:55:27.000Z

RecoBTag/ImpactParameter/python/candidateTrackCounting3D3rdComputer_cfi.py

SWuchterl/cmssw

769b4a7ef81796579af7d626da6039dfa0347b8e

[ "Apache-2.0" ]

14

2017-10-04T09:47:21.000Z

2019-10-23T18:04:45.000Z

import FWCore.ParameterSet.Config as cms from RecoBTag.ImpactParameter.candidateTrackCounting3D2ndComputer_cfi import * # trackCounting3D3rd btag computer candidateTrackCounting3D3rdComputer = candidateTrackCounting3D2ndComputer.clone( nthTrack = cms.int32(3) )

29.777778

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0.854478

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268

10.363636

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0

0.045267

0.093284

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8

81

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0

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0

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1

0

1

null

0

1

0

null

0

1

0

4

e5b32563dcbe76e221d895f816e4d26469300937

89

py

Python

fizzbuzz/format_list_to_string.py

mthpower/evil-fizz-buzz

c4ea42a5328f8b66d5508551a821aaa79ae80c91

[ "MIT" ]

null

fizzbuzz/format_list_to_string.py

mthpower/evil-fizz-buzz

c4ea42a5328f8b66d5508551a821aaa79ae80c91

[ "MIT" ]

null

fizzbuzz/format_list_to_string.py

mthpower/evil-fizz-buzz

c4ea42a5328f8b66d5508551a821aaa79ae80c91

[ "MIT" ]

null

def format_list_to_string_with_comma(array): return ','.join([str(x) for x in array])

44.5

44

0.730337

16

89

3.75

0.875

0

0.123596

89

2

45

44.5

0.769231

0

0.011111

0

1

0.5

false

0

0.5

1

0

1

0

null

0

1

0

null

0

1

0

1

0

4

e5c011e71d450157209e1e36d22ef161e3f0381f

108

py

Python

api/posts_communities/apps.py

Juangr1803/Foro-AgrodatAI

a8f23afd32d2ec60d25a03c97f5f353fd0ef5e0b

[ "MIT" ]

1

2021-04-19T16:13:39.000Z

api/posts_communities/apps.py

Juangr1803/Foro-AgrodatAI

a8f23afd32d2ec60d25a03c97f5f353fd0ef5e0b

[ "MIT" ]

null

api/posts_communities/apps.py

Juangr1803/Foro-AgrodatAI

a8f23afd32d2ec60d25a03c97f5f353fd0ef5e0b

[ "MIT" ]

null

from django.apps import AppConfig class PostsCommunitiesConfig(AppConfig): name = 'posts_communities'

18

40

0.796296

11

108

7.727273

0.909091

0

0.138889

108

5

41

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0

1

0

false

0

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0

1

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null

0

1

0

1

0

4

e5fd0c899aa61c824625ba0303d6fd5a32545277

460

py

Python

__init__.py

kollad/turbo-ninja

9c3f66b2af64aec01f522d19b309cfdd723e67cf

[ "MIT" ]

null

__init__.py

kollad/turbo-ninja

9c3f66b2af64aec01f522d19b309cfdd723e67cf

[ "MIT" ]

1

2017-12-14T05:35:38.000Z

__init__.py

kollad/turbo-ninja

9c3f66b2af64aec01f522d19b309cfdd723e67cf

[ "MIT" ]

null

from abc import ABCMeta, abstractproperty, abstractmethod __author__ = 'lopalo' class AbstractGameApp(metaclass=ABCMeta): @abstractproperty def name(self): pass @abstractmethod def get_command_processor_class(self, application_settings): pass @abstractmethod def get_user_manager(self, application_settings): pass @abstractmethod def get_content_manager(self, application_settings): pass

19.166667

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0.717391

45

460

7.022222

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0.297468

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460

23

65

20

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0

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false

0.266667

0.066667

0

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0

null

0

1

0

null

0

1

0

1

0

4

00ab2096c93959d93e6806ca9739a6ad8290d9a9

807

py

Python

bot/config/Config.py

WizzardHub/EcoleDirecteOrtBot

d64ea45acbae3ba4b10152a25bf25abf6ba9525d

[ "MIT" ]

null

bot/config/Config.py

WizzardHub/EcoleDirecteOrtBot

d64ea45acbae3ba4b10152a25bf25abf6ba9525d

[ "MIT" ]

null

bot/config/Config.py

WizzardHub/EcoleDirecteOrtBot

d64ea45acbae3ba4b10152a25bf25abf6ba9525d

[ "MIT" ]

null

import os from dotenv import load_dotenv class CustomConfig: def __init__(self): load_dotenv() self._token = os.getenv('DISCORD_TOKEN') self._guild = int(os.getenv('DISCORD_GUILD')) self._channel_inbox = int(os.getenv('DISCORD_CHANNEL_INBOX')) self._channel_homework = int(os.getenv('DISCORD_CHANNEL_HOMEWORK')) self._username = os.getenv('API_USERNAME') self._password = os.getenv('API_PASSWORD') def getToken(self): return self._token def getGuild(self): return self._guild def getInbox(self): return self._channel_inbox def getHomework(self): return self._channel_homework def getUsername(self): return self._username def getPassword(self): return self._password

24.454545

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0.662949

95

807

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807

33

76

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1

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1

0

1

0

4

daa82c6786f1dbbbe57811b0b3e32c2bac2b0412

36

py

Python

advancing_hero/sprites/hero_weapons/__init__.py

EnzoVargasM/advancing-hero2

c90eb65b033706ba622137d19c71b4ca00cdaea2

[ "MIT" ]

null

advancing_hero/sprites/hero_weapons/__init__.py

EnzoVargasM/advancing-hero2

c90eb65b033706ba622137d19c71b4ca00cdaea2

[ "MIT" ]

null

advancing_hero/sprites/hero_weapons/__init__.py

EnzoVargasM/advancing-hero2

c90eb65b033706ba622137d19c71b4ca00cdaea2

[ "MIT" ]

null

""" Init file for sprites module """

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4

dab550ce6c6e30be4cdeedae5de283d05677301c

4,498

py

Python

results_t+2s_greater_n/n32_t22_s8_collisions.py

FreeDisciplina/CollisionOffset

076842adb67fbf7301c313469597396066eaafe5

[ "MIT" ]

null

results_t+2s_greater_n/n32_t22_s8_collisions.py

FreeDisciplina/CollisionOffset

076842adb67fbf7301c313469597396066eaafe5

[ "MIT" ]

null

results_t+2s_greater_n/n32_t22_s8_collisions.py

FreeDisciplina/CollisionOffset

076842adb67fbf7301c313469597396066eaafe5

[ "MIT" ]

null

import matplotlib.pyplot as plt import numpy as np plt.rc('text', usetex=True) plt.rc('font', family='serif') n_t_s = [11.0035179121, 11.0063260785, 11.0105281059, 11.0042204663, 11.0216740429, 10.9715435540, 10.9950604670, 11.0042204663, 10.9851303735, 11.0126245389, 11.0182001788, 10.9858419370, 11.0579917228, 11.0402897210, 11.0021117765, 10.9454438364, 10.9787104591, 11.0161118382, 10.9801395776, 10.9657842847, 10.9188632373, 11.0077281146, 10.9366379390, 10.9992953870, 10.9837061927, 10.8925428166, 10.9971794809, 10.9403135971, 10.9432473959, 10.9865531498, 10.9285183753, 10.9751314569, 10.9657842847, 10.9592775057, 10.9001120630, 11.0056245492, 10.9255544399, 10.9815672819, 10.9607259948, 10.9240701856, 10.9395792143, 10.9614496944, 10.9787104591, 10.9541963104, 10.9181178510, 10.9794251953, 10.9571020416, 10.9571020416, 10.9417812423, 10.9068905956, 10.9351650496, 10.9083926208, 10.9607259948, 10.9068905956, 10.9744145898, 10.9693865213, 10.8887432489, 10.9439799143, 10.9031286768, 10.9277779621, 10.9292584086, 10.9307373376, 10.8384160758, 10.8970891283, 10.8603110549, 10.9248125036, 10.9173720795, 10.9469062745, 10.9505558970, 10.9061389962, 10.9483672316, 10.9483672316, 10.9410476063, 10.9038818457, 10.9016211583, 10.8447057644, 10.9113919878, 10.8818787076, 10.8734441125, 10.9113919878, 10.8657332709, 10.9023751145, 10.9218409371, 10.9098930838, 10.8757493514, 10.9098930838, 10.8864586957, 10.9031286768, 10.8726748803, 10.8587580999, 10.8849336479, 10.8910241901, 10.8540891799, 10.8780509127, 10.8587580999, 10.8265484873, 10.8415643477, 10.8392037881, 10.8649599151, 10.8564255286, 10.8121773055, 10.8556471660, 10.8849336479, 10.8273427042, 10.8328900142, 10.8525295094, 10.8902642770, 10.8749813477, 10.8579809951, 10.8695938432, 10.8803488082, 10.8811139607, 10.8940598463, 10.9008668080, 10.7821791938, 10.8587580999, 10.8217739820, 10.8376279332, 10.8462739113, 10.8454900509, 10.8925428166, 10.8177831218, 10.7780771295, 10.8478403556, 10.8407779236, 10.8392037881, 10.7739633684, 10.8431359111, 10.7532167492, 10.8241632097, 10.7756102808, 10.8811139607, 10.7821791938, 10.8249587405, 10.8478403556, 10.7984718011, 10.8726748803, 10.8217739820, 10.8185821775, 10.7944158664, 10.8603110549, 10.8089641749, 10.7780771295, 10.9046346217, 10.8145824659, 10.8193807909, 10.8241632097, 10.7706638929, 10.8201789624, 10.7228075312, 10.7523806466, 10.7623820387, 10.7813597135, 10.8097681287, 10.8000909876, 10.7960396088, 10.7615512324, 10.8081597729, 10.7846348456, 10.7338627197, 10.7623820387, 10.8486229404, 10.7507069862, 10.7992816215, 10.7623820387, 10.7805397675, 10.8008998999, 10.7673568541, 10.8025163651, 10.7338627197, 10.8065496220, 10.7456743240, 10.7253662579, 10.8169836233, 10.8049376721, 10.7788984760, 10.7706638929, 10.8049376721, 10.7756102808, 10.7236609444, 10.7911628886, 10.7532167492, 10.7490313820, 10.7168194613, 10.7431513941, 10.7598881832, 10.6724253420, 10.7236609444, 10.7481928496, 10.7330153217, 10.7193888209, 10.7870863246, 10.7582232147, 10.7338627197, 10.7176764231, 10.7236609444, 10.7347096202, 10.7423094361, 10.7090838126, 10.7279204546, 10.7338627197, 10.6821167650, 10.7895336450, 10.7287708495, 10.7064960181, 10.6821167650, 10.6856248397, 10.6794800995, 10.7159619903, 10.6952282915, 10.7013064620, 10.7142455177, 10.7523806466, 10.7296207436, 10.6908710093, 10.6706562491, 10.7228075312, 10.7245138531, 10.6987046668, 10.7142455177, 10.6733090756, 10.7364019313, 10.5943246039, 10.6812384118, 10.7245138531, 10.6688849843, 10.6978363580, 10.6644472845, 10.7397806098, 10.6821167650, 10.6348110502, 10.7064960181, 10.7047682394, 10.7673568541, 10.6329951971, 10.6987046668, 10.7330153217, 10.6537407787, 10.6943578872, 10.7108064337, 10.6653359172, 10.6626683755, 10.6960981710, 10.6653359172, 10.6329951971, 10.6741922681, 10.6438561898, 10.6741922681, 10.7099453802, 10.6348110502, 10.7142455177, 10.6247954559, 10.6626683755, 10.6465587102, 10.6697708885, 10.7116669736,] fig, ax1 = plt.subplots() ax1.plot(np.arange(0,256), n_t_s) ax1.grid(True, linestyle='--', which='major', color='lightgrey', alpha=0.5) ax1.tick_params(labelsize='large', width=3) ax1.set_axisbelow(True) ax1.set_title('Number of collisions on each offset ($n=32, t=22, s=8$)', fontsize=12, fontweight='bold') ax1.set_xlabel('offset ($[0, 2^8]$)', fontsize=12) ax1.set_ylabel('$\log_2(\#\mathrm{collisions})$', fontsize=12) plt.savefig('n32_t22_s8_collisions.pdf') plt.savefig('n32_t22_s8_collisions.png') plt.show()

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null

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4

dabf78dbbfda7cca34751ed418d70c873f579b13

284

py

Python

src/gimelstudio/core/__init__.py

Correct-Syntax/GimelStudio

db6e2db35730e11bcb25f5ba82823e68b86003f1

[ "Apache-2.0" ]

134

2021-02-27T08:28:09.000Z

2022-03-30T17:46:27.000Z

src/gimelstudio/core/__init__.py

Correct-Syntax/GimelStudio

db6e2db35730e11bcb25f5ba82823e68b86003f1

[ "Apache-2.0" ]

127

2021-04-13T13:34:20.000Z

2022-02-14T21:16:12.000Z

src/gimelstudio/core/__init__.py

Correct-Syntax/GimelStudio

db6e2db35730e11bcb25f5ba82823e68b86003f1

[ "Apache-2.0" ]

20

2021-03-23T20:06:05.000Z

2022-01-20T18:24:53.000Z

from .datatypes import RenderImage from .eval_info import EvalInfo from .output_eval import OutputNodeEval from .renderer import Renderer from .glsl_renderer import GLSLRenderer from .registry import RegisterNode, UnregisterNode, NODE_REGISTRY from .project_file import ProjectFileIO

35.5

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1

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4

dac94dc109779ceb5090b8e6491fd4ebf2ae6e98

1,192

py

Python

setup.py

nvie/pluck

8cb1186568e0b24d0f89f4ef4b79eea2b8944456

[ "BSD-2-Clause-FreeBSD" ]

7

2015-02-09T14:02:34.000Z

2020-09-01T04:32:08.000Z

setup.py

nvie/pluck

8cb1186568e0b24d0f89f4ef4b79eea2b8944456

[ "BSD-2-Clause-FreeBSD" ]

null

setup.py

nvie/pluck

8cb1186568e0b24d0f89f4ef4b79eea2b8944456

[ "BSD-2-Clause-FreeBSD" ]

null

from setuptools import setup import pluck setup( name='pluck', version=pluck.__version__, description='Plucks values from an iterable.', long_description=(open('README.rst').read() + '\n\n' + open('HISTORY.rst').read()), url='http://github.com/nvie/pluck/', license=pluck.__license__, author=pluck.__author__, author_email='vincent@3rdcloud.com', py_modules=['pluck'], classifiers=[ 'Development Status :: 5 - Production/Stable', 'Intended Audience :: Developers', 'Natural Language :: English', 'License :: OSI Approved :: BSD License', 'Operating System :: OS Independent', 'Programming Language :: Python', 'Programming Language :: Python :: 2', 'Programming Language :: Python :: 2.6', 'Programming Language :: Python :: 2.7', 'Programming Language :: Python :: 3', 'Programming Language :: Python :: 3.0', 'Programming Language :: Python :: 3.1', 'Programming Language :: Python :: 3.2', 'Programming Language :: Python :: 3.3', 'Topic :: Software Development :: Libraries :: Python Modules', ], )

34.057143

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null

1

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null

0

1

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4

daedf07840e24bf7e9f0383407cd8793f020c529

128

py

Python

python/flask-intro/program/__init__.py

zkan/100DaysOfCode

3c713ead94a9928e2d0f8d794e49ec202dc64ba3

[ "MIT" ]

2

2019-05-01T00:32:30.000Z

2019-11-20T05:23:05.000Z

python/flask-intro/program/__init__.py

zkan/100DaysOfCode

3c713ead94a9928e2d0f8d794e49ec202dc64ba3

[ "MIT" ]

15

2020-09-05T18:35:04.000Z

2022-03-11T23:44:47.000Z

python/flask-intro/program/__init__.py

zkan/100DaysOfCode

3c713ead94a9928e2d0f8d794e49ec202dc64ba3

[ "MIT" ]

null

from flask import Flask app = Flask(__name__) # This has to happen after the Flask app is created from program import routes

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51

0.773438

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128

4.52381

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null

0

1

0

1

0

4

daf2b0a998e073b704932654890b222d94f6b0ee

2,117

py

Python

tests/test_gazpar_sensor.py

Vebryn/home-assistant-gazpar

2d9998b7ba2d5bf089b045488b59f23f8f4b4d8d

[ "MIT" ]

4

2022-01-21T23:35:09.000Z

2022-02-17T13:31:24.000Z

tests/test_gazpar_sensor.py

Vebryn/home-assistant-gazpar

2d9998b7ba2d5bf089b045488b59f23f8f4b4d8d

[ "MIT" ]

3

2022-01-26T08:34:18.000Z

2022-01-27T12:44:39.000Z

tests/test_gazpar_sensor.py

Vebryn/home-assistant-gazpar

2d9998b7ba2d5bf089b045488b59f23f8f4b4d8d

[ "MIT" ]

1

2022-01-25T21:47:38.000Z

from custom_components.gazpar.sensor import CONF_PCE_IDENTIFIER, CONF_TESTMODE, setup_platform from custom_components.gazpar.sensor import CONF_USERNAME, CONF_PASSWORD, CONF_WAITTIME, CONF_TMPDIR, CONF_SCAN_INTERVAL import os import logging import json # -------------------------------------------------------------------------------------------- class TestGazparSensor: logger = logging.getLogger(__name__) _entities = [] # ---------------------------------- def add_entities(self, entities: list, flag: bool): self._entities.extend(entities) # ---------------------------------- def test_live(self): config = { CONF_USERNAME: os.environ["GRDF_USERNAME"], CONF_PASSWORD: os.environ["GRDF_PASSWORD"], CONF_PCE_IDENTIFIER: os.environ["PCE_IDENTIFIER"], CONF_WAITTIME: 30, CONF_TMPDIR: "./tmp", CONF_SCAN_INTERVAL: 600, CONF_TESTMODE: False } setup_platform(None, config, self.add_entities) for entity in self._entities: entity.update() state = entity.state attributes = entity.device_state_attributes TestGazparSensor.logger.info(f"state={state}") TestGazparSensor.logger.info(f"attributes={json.dumps(attributes, indent=2)}") # ---------------------------------- def test_sample(self): config = { CONF_USERNAME: os.environ["GRDF_USERNAME"], CONF_PASSWORD: os.environ["GRDF_PASSWORD"], CONF_PCE_IDENTIFIER: os.environ["PCE_IDENTIFIER"], CONF_WAITTIME: 30, CONF_TMPDIR: "./tmp", CONF_SCAN_INTERVAL: 600, CONF_TESTMODE: True } setup_platform(None, config, self.add_entities) for entity in self._entities: entity.update() state = entity.state attributes = entity.device_state_attributes TestGazparSensor.logger.info(f"state={state}") TestGazparSensor.logger.info(f"attributes={json.dumps(attributes, indent=2)}")

33.078125

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null

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1

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4

dafb863b986c1825bd3327110f9f040f716ab8d0

23

py

Python

cantools/version.py

Saildrone/cantools

06d6bd8527259ace31fdfa68812f1991bf1bcb5b

[ "MIT" ]

1

2021-12-28T07:02:34.000Z

cantools/version.py

Artnoc1/cantools

fe487b7da5b6080f5f5b5c40d12b3cb568bc2bfc

[ "MIT" ]

3

2020-05-05T21:45:16.000Z

2021-01-09T01:25:57.000Z

cantools/version.py

Saildrone/cantools

06d6bd8527259ace31fdfa68812f1991bf1bcb5b

[ "MIT" ]

null

__version__ = '33.2.0'

11.5

22

0.652174

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23

2.75

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0.2

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null

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1

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null

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4

9755653ef52d467c9c3d0aa80929143976633444

155

py

Python

AtividadesPy/Questao-1.py

FlavioJunior2021/Python

54626c62526726237ea646bbfc438c5394eb19b5

[ "MIT" ]

1

2021-09-13T19:26:53.000Z

AtividadesPy/Questao-1.py

FlavioJunior2021/Python

54626c62526726237ea646bbfc438c5394eb19b5

[ "MIT" ]

null

AtividadesPy/Questao-1.py

FlavioJunior2021/Python

54626c62526726237ea646bbfc438c5394eb19b5

[ "MIT" ]

null

print('Digite seu nome:') nome = input() print('Digite sua idade:') idade = int(input()) podeVotar = idade>=16 print(nome,'tem',idade,'anos:',podeVotar)

17.222222

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0.677419

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155

4.772727

0.545455

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0.014599

0.116129

155

8

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null

0

1

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4

9765c10c80ba93f399bafb524da18f9cd48ba941

81

py

Python

spider/modules/NullURLError.py

isKEKE/AC03

dff76cfc0d9524429eb11f3bca189dd54716c527

[ "MIT" ]

null

spider/modules/NullURLError.py

isKEKE/AC03

dff76cfc0d9524429eb11f3bca189dd54716c527

[ "MIT" ]

null

spider/modules/NullURLError.py

isKEKE/AC03

dff76cfc0d9524429eb11f3bca189dd54716c527

[ "MIT" ]

null

# _*_ coding: utf-8 _*_ class NullURLError(Exception): '''空URL异常''' pass

16.2

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null

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9767c29e07eb8818f72695c213fc7e3f6c6959f8

114

py

Python

thegiant/helpers.py

ybrs/the-giant

23a1125c8eaa7a434047541b3998517033c866d8

[ "BSD-2-Clause" ]

2

2016-08-27T11:47:23.000Z

2016-08-27T11:47:28.000Z

thegiant/helpers.py

ybrs/the-giant

23a1125c8eaa7a434047541b3998517033c866d8

[ "BSD-2-Clause" ]

null

thegiant/helpers.py

ybrs/the-giant

23a1125c8eaa7a434047541b3998517033c866d8

[ "BSD-2-Clause" ]

null

OK = '+OK\r\n' def reply(v): ''' formats the value as a redis reply ''' return '$%s\r\n%s\r\n' % (len(v), v)

14.25

37

0.526316

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null

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977548308481f500e45f0071719507f15e3e272d

165

py

Python

IsabelaFunctions/version.py

de-oliveira/IsabelaFunctions

6ea9f181f1e9eda90db3e2542d72eaf00caf977b

[ "MIT" ]

null

IsabelaFunctions/version.py

de-oliveira/IsabelaFunctions

6ea9f181f1e9eda90db3e2542d72eaf00caf977b

[ "MIT" ]

null

IsabelaFunctions/version.py

de-oliveira/IsabelaFunctions

6ea9f181f1e9eda90db3e2542d72eaf00caf977b

[ "MIT" ]

null

# -*- coding: utf-8 -*- def get_version_info(): """Provide the package version""" VERSION = '0.0.2' return VERSION __version__ = get_version_info()

13.75

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4.52381

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0.031008

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null

1

0

null

0

1

0

4

97c2b52018dd17103e2e6a039bff9a3bbb9f2822

56

py

Python

laed/dataset/__init__.py

jaywalnut310/NeuralDialog-LAED

606f4f10fccea9081674c8e01ae2c47e2ba3d4a3

[ "Apache-2.0" ]

195

2018-04-22T05:05:26.000Z

2022-01-10T06:30:50.000Z

laed/dataset/__init__.py

jaywalnut310/NeuralDialog-LAED

606f4f10fccea9081674c8e01ae2c47e2ba3d4a3

[ "Apache-2.0" ]

6

2018-05-29T12:29:56.000Z

2019-12-11T04:07:05.000Z

laed/dataset/__init__.py

jaywalnut310/NeuralDialog-LAED

606f4f10fccea9081674c8e01ae2c47e2ba3d4a3

[ "Apache-2.0" ]

44

2018-05-29T07:37:55.000Z

2021-05-31T08:06:30.000Z

# @Time : 12/4/17 4:28 PM # @Author : Tiancheng Zhao

28

0.589286

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1

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1

0

null

0

1

0

4

97cbfc6334b5873f07311eaca74d938b7e373c52

2,776

py

Python

api/handler/roleApiHandler.py

xin1195/userbase

716dcf7ddc4b6f1c7bfe28c57a355c3bcd816b2f

[ "Apache-2.0" ]

null

api/handler/roleApiHandler.py

xin1195/userbase

716dcf7ddc4b6f1c7bfe28c57a355c3bcd816b2f

[ "Apache-2.0" ]

null

api/handler/roleApiHandler.py

xin1195/userbase

716dcf7ddc4b6f1c7bfe28c57a355c3bcd816b2f

[ "Apache-2.0" ]

null

#!/usr/bin/env python3 # -*- coding:utf-8 -*- # Created by LiuXin # Time 2016/8/25. from tornado import gen from api.handler.baseApiHandler import ApiBaseHandler from api.model.roleModel import get_role_list, del_role_one, del_role_list, create_role, update_role from api.model.roleModel import get_role_one from common.decoratorLib import auth_token class ApiRoleRetrieveHandler(ApiBaseHandler): """ 获取公司类列表 """ def __init__(self, application, request, **kwargs): super().__init__(application, request, **kwargs) self.role_id = self.get_argument("role_id", "") self.role_name = self.get_argument("role_name", "") @auth_token @gen.coroutine def get(self, *args, **kwargs): if self.role_id: role_list = yield get_role_one(self) else: role_list = yield get_role_list(self) self.change_to_jsonp(role_list) @auth_token @gen.coroutine def post(self, *args, **kwargs): if self.role_id: role_list = yield get_role_one(self) else: role_list = yield get_role_list(self) self.change_to_jsonp(role_list) class ApiRoleCreateHandler(ApiBaseHandler): def __init__(self, application, request, **kwargs): super().__init__(application, request, **kwargs) self.role_id = self.get_argument("role_id", "") self.role_name = self.get_argument("role_name", "") self.system_list = self.get_arguments("system", strip=True) self.node_list = self.get_arguments("node", strip=True) @auth_token @gen.coroutine def post(self, *args, **kwargs): flag = yield create_role(self) self.change_to_jsonp(flag) class ApiRoleUpdateHandler(ApiBaseHandler): def __init__(self, application, request, **kwargs): super().__init__(application, request, **kwargs) self.role_id = self.get_argument("role_id", "") self.role_name = self.get_argument("role_name", "") self.system_list = self.get_arguments("system", strip=True) self.node_list = self.get_arguments("node", strip=True) @auth_token @gen.coroutine def post(self, *args, **kwargs): flag = yield update_role(self) self.change_to_jsonp(flag) class ApiRoleDeleteHandler(ApiBaseHandler): def __init__(self, application, request, **kwargs): super().__init__(application, request, **kwargs) self.role_id = self.get_argument("role_id", "") @auth_token @gen.coroutine def post(self, *args, **kwargs): if type(self.role_id) == list: flag = yield del_role_list(self) self.change_to_jsonp(flag) else: flag = yield del_role_one(self) self.change_to_jsonp(flag)

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0.077642

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0.647402

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1

0

1

0

null

0

4

8aeb8daf0ce8b9c871af9294c9f533d07b1c65fc

127

py

Python

example/auth.py

DommertTech/flask-turboduck

bd5ad776991ae7d7b6a0ca6b30580e251ce4d3ae

[ "MIT" ]

2

2017-05-30T17:14:41.000Z

2017-05-30T20:09:36.000Z

example/auth.py

DommertTech/flask-turboduck

bd5ad776991ae7d7b6a0ca6b30580e251ce4d3ae

[ "MIT" ]

null

example/auth.py

DommertTech/flask-turboduck

bd5ad776991ae7d7b6a0ca6b30580e251ce4d3ae

[ "MIT" ]

null

from flask_turboduck.auth import Auth from app import app, db from models import User auth = Auth(app, db, user_model=User)

15.875

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127

4.363636

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0.104167

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127

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0

1

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null

0

1

0

1

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4

8afd077285386e70d2b5c9fee04e9be76fa4f31d

261

py

Python

guet/commands/strategies/error_strategy.py

sturzl/guet

b8c453f07968b689b303e20e7a31b405c02c54ef

[ "Apache-2.0" ]

null

guet/commands/strategies/error_strategy.py

sturzl/guet

b8c453f07968b689b303e20e7a31b405c02c54ef

[ "Apache-2.0" ]

null

guet/commands/strategies/error_strategy.py

sturzl/guet

b8c453f07968b689b303e20e7a31b405c02c54ef

[ "Apache-2.0" ]

null

from guet.commands.strategies.strategy import CommandStrategy class ErrorStrategy(CommandStrategy): def __init__(self, error_message: str): self.error_message = error_message def apply(self): print(self.error_message) exit(1)

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null

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1

0

1

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4

c11650df023369f6d0ed59233a6319896154951f

65

py

Python

ptm/templates/adventure_template/travels/__init__.py

acrius/path_to_mordor

e6cfbf6a70a8bce7120469a77fad4df8a4e5bfe4

[ "MIT" ]

null

ptm/templates/adventure_template/travels/__init__.py

acrius/path_to_mordor

e6cfbf6a70a8bce7120469a77fad4df8a4e5bfe4

[ "MIT" ]

null

ptm/templates/adventure_template/travels/__init__.py

acrius/path_to_mordor

e6cfbf6a70a8bce7120469a77fad4df8a4e5bfe4

[ "MIT" ]

null

""" The package contains modules describing scrapping rules. """

16.25

56

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65

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65

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0

null

0

1

0

4

c1be4dbd2c34dc49daa55abc42c809f71398f0b5

25

py

Python

ceph_deploy/__init__.py

491852809/ceph-deploy

b057610d4287620f203170e346e592d62edc45ee

[ "MIT" ]

null

ceph_deploy/__init__.py

491852809/ceph-deploy

b057610d4287620f203170e346e592d62edc45ee

[ "MIT" ]

null

ceph_deploy/__init__.py

491852809/ceph-deploy

b057610d4287620f203170e346e592d62edc45ee

[ "MIT" ]

null

__version__ = '1.5.39'

6.25

22

0.6

4

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2.75

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3

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8.333333

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null

0

1

0

1

0

null

0

4

c1cca14eb43d144cada38ce1fec4891bba59b95e

1,083

py

Python

state.py

ranjithcoder/J.A.R.V.I.S-1

fe3d22e5be0b00f79c0cc7def85f4ec9b1393859

[ "MIT" ]

64

2021-05-13T17:04:30.000Z

2022-03-24T07:43:27.000Z

state.py

ranjithcoder/J.A.R.V.I.S-1

fe3d22e5be0b00f79c0cc7def85f4ec9b1393859

[ "MIT" ]

7

2021-05-13T21:02:52.000Z

2022-02-10T08:03:17.000Z

state.py

ranjithcoder/J.A.R.V.I.S-1

fe3d22e5be0b00f79c0cc7def85f4ec9b1393859

[ "MIT" ]

31

2021-05-22T06:49:07.000Z

2022-03-26T09:01:42.000Z

state = {"andaman and nicobar islands": "Andaman and Nicobar Islands","andhra pradesh":"Andhra Pradesh","arunachal pradesh":"Arunachal Pradesh","assam":"Assam","bihar":"Bihar","chandigarh":"Chandigarh","Chhattisgarh":"Chhattisgarh","dadra":"Dadra and Nagar Haveli and Daman and Diu","Nagar Haveli":"Dadra and Nagar Haveli and Daman and Diu","daman":"Dadra and Nagar Haveli and Daman and Diu","diu":"Dadra and Nagar Haveli and Daman and Diu","delhi":"Delhi","goa":"Goa","gujarat":"Gujarat","haryana":"Haryana","himachal pradesh":"Himachal Pradesh","jammu and kashmir":"Jammu and Kashmir","jharkhand":"Jharkhand","karnataka":"Karnataka","kerala":"Kerala","ladakh":"Ladakh","lakshadweep":"Lakshadweep","madhya pradesh":"Madhya Pradesh","maharashtra":"Maharashtra","manipur":"Manipur","meghalaya":"Meghalaya","mizoram":"Mizoram","nagaland":"Nagaland","odisha":"Odisha","puducherry":"Puducherry","punjab":"Punjab","skkim":"Skkim","tamil nadu":"Tamil Nadu","telangana":"Telangana","tripura":"Tripura","uttarakhand":"Uttarakhand","uttar pradesh":"Uttar Pradesh","west bengal":"West Bengal"}

1,083

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0.361538

0.069009

0.065245

0.095358

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0

null

0

1

0

1

0

null

0

4

de16359694d3a7c96282dea4681708af016da6b4

99

py

Python

contrapartes/apps.py

shiminasai/interteam-1

1be77a529025a226fb759fb3e04811d854f90f66

[ "MIT" ]

null

contrapartes/apps.py

shiminasai/interteam-1

1be77a529025a226fb759fb3e04811d854f90f66

[ "MIT" ]

null

contrapartes/apps.py

shiminasai/interteam-1

1be77a529025a226fb759fb3e04811d854f90f66

[ "MIT" ]

3

2018-06-07T15:36:04.000Z

2019-04-01T19:25:43.000Z

from django.apps import AppConfig class ContrapartesConfig(AppConfig): name = 'contrapartes'

16.5

36

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10

99

7.7

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99

5

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1

0

4

a9a675d0bd24032753f1f2d18221c2e7bd4b7cb6

521

py

Python

tests/analyzer/test_datasource_codes.py

CMSgov/qpp-claims-to-quality-public

1e2da9494faf9e316a17cbe899284db9e61d0902

[ "CC0-1.0" ]

13

2018-09-28T14:02:59.000Z

2021-12-07T21:31:54.000Z

tests/analyzer/test_datasource_codes.py

CMSgov/qpp-claims-to-quality-public

1e2da9494faf9e316a17cbe899284db9e61d0902

[ "CC0-1.0" ]

1

2018-10-01T17:49:05.000Z

2018-10-09T01:10:56.000Z

tests/analyzer/test_datasource_codes.py

CMSgov/qpp-claims-to-quality-public

1e2da9494faf9e316a17cbe899284db9e61d0902

[ "CC0-1.0" ]

1

2021-02-08T18:32:16.000Z

"""Tests for reading code objects from JSON.""" from claims_to_quality.analyzer.datasource import code_reader import pytest def test_load_quality_codes(): """Test that load_quality_codes load the full list of quality codes.""" assert len(code_reader.load_quality_codes()) > 0 def test_load_measure_definition_missing_file(): """Test that load_quality_codes throws the expected error if file is missing.""" with pytest.raises(IOError): code_reader.load_quality_codes(json_path='missing_path')

32.5625

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4.986842

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0.211082

0.100264

0.263852

0

0.002237

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521

15

85

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0.845638

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true

0

0.285714

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null

0

1

0

null

0

1

0

1

0

4

a9d3382001a8b418c0a3fb6c65430dd6b88d4be4

229

py

Python

scale/util/host.py

stevevarner/scale

9623b261db4ddcf770f00df16afc91176142bb7c

[ "Apache-2.0" ]

null

scale/util/host.py

stevevarner/scale

9623b261db4ddcf770f00df16afc91176142bb7c

[ "Apache-2.0" ]

null

scale/util/host.py

stevevarner/scale

9623b261db4ddcf770f00df16afc91176142bb7c

[ "Apache-2.0" ]

null

"""Defines the named tuple for host locations""" from __future__ import unicode_literals from collections import namedtuple # Named tuple represents a host location HostAddress = namedtuple('HostAddress', ['hostname', 'port'])

28.625

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0.126638

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7

62

32.714286

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null

0

1

0

null

0

1

0

1

0

4

a9ebdf089ed711a11266825ffa05e6a4bbe3df84

7,100

py

Python

IBP_Adv_Training/utils/datasets.py

JmfanBU/AdvIBP

00cffbacbac4d42856cd88f3183781cd845db35a

[ "MIT" ]

2

2021-06-07T13:00:13.000Z

2021-12-02T08:10:30.000Z

IBP_Adv_Training/utils/datasets.py

BU-DEPEND-Lab/AdvIBP

783d3fec25098b9323a2b30e0d2b13a6da24d5af

[ "MIT" ]

null

IBP_Adv_Training/utils/datasets.py

BU-DEPEND-Lab/AdvIBP

783d3fec25098b9323a2b30e0d2b13a6da24d5af

[ "MIT" ]

1

2021-06-07T13:00:15.000Z

# Copyright (C) 2020, Jiameng Fan <jmfan@bu.edu> # # This program is licenced under the MIT License, # contained in the LICENCE file in this directory. import multiprocessing import torch from torch.utils import data from functools import partial import torchvision.transforms as transforms import torchvision.datasets as datasets # compute image statistics (by Andreas # https://discuss.pytorch.org/t/computing-the-mean-and-std-of-dataset/34949/4) def get_stats(loader): mean = 0.0 for images, _ in loader: batch_samples = images.size(0) reshaped_img = images.view(batch_samples, images.size(1), -1) mean += reshaped_img.mean(2).sum(0) w = images.size(2) h = images.size(3) mean = mean / len(loader.dataset) var = 0.0 for images, _ in loader: batch_samples = images.size(0) images = images.view(batch_samples, images.size(1), -1) var += ((images - mean.unsqueeze(1))**2).sum([0, 2]) std = torch.sqrt(var / (len(loader.dataset)*w*h)) return mean, std # load MNIST of Fashion-MNIST def mnist_loaders( dataset, batch_size, shuffle_train=True, shuffle_test=False, normalize_input=False, num_examples=None, test_batch_size=None ): mnist_train = dataset( "./data", train=True, download=True, transform=transforms.ToTensor() ) mnist_test = dataset( "./data", train=False, download=True, transform=transforms.ToTensor() ) if num_examples: indices = list(range(num_examples)) mnist_train = data.Subset(mnist_train, indices) mnist_test = data.Subset(mnist_test, indices) train_loader = torch.utils.data.DataLoader( mnist_train, batch_size=batch_size, shuffle=shuffle_train, pin_memory=True, num_workers=min(multiprocessing.cpu_count(), 2) ) if test_batch_size: batch_size = test_batch_size test_loader = torch.utils.data.DataLoader( mnist_test, batch_size=batch_size, shuffle=shuffle_test, pin_memory=True, num_workers=min(multiprocessing.cpu_count(), 2) ) std = [1.0] mean = [0.0] train_loader.std = std test_loader.std = std train_loader.mean = mean test_loader.mean = mean return train_loader, test_loader def cifar_loaders( batch_size, shuffle_train=True, shuffle_test=False, train_random_transform=False, normalize_input=False, num_examples=None, test_batch_size=None ): if normalize_input: std = [0.2023, 0.1994, 0.2010] mean = [0.4914, 0.4822, 0.4465] normalize = transforms.Normalize(mean=mean, std=std) else: std = [1.0, 1.0, 1.0] mean = [0, 0, 0] normalize = transforms.Normalize(mean=mean, std=std) if train_random_transform: if normalize_input: train = datasets.CIFAR10( './data', train=True, download=True, transform=transforms.Compose([ transforms.RandomHorizontalFlip(), transforms.RandomCrop(32, 4), transforms.ToTensor(), normalize, ]) ) else: train = datasets.CIFAR10( './data', train=True, download=True, transform=transforms.Compose([ transforms.RandomHorizontalFlip(), transforms.RandomCrop(32, 4), transforms.ToTensor(), ]) ) else: train = datasets.CIFAR10( './data', train=True, download=True, transform=transforms.Compose([transforms.ToTensor(), normalize]) ) test = datasets.CIFAR10( './data', train=False, transform=transforms.Compose([transforms.ToTensor(), normalize]) ) if num_examples: indices = list(range(num_examples)) train = data.Subset(train, indices) test = data.Subset(test, indices) train_loader = torch.utils.data.DataLoader( train, batch_size=batch_size, shuffle=shuffle_train, pin_memory=True, num_workers=min(multiprocessing.cpu_count(), 6) ) if test_batch_size: batch_size = test_batch_size test_loader = torch.utils.data.DataLoader( test, batch_size=max(batch_size, 1), shuffle=shuffle_test, pin_memory=True, num_workers=min(multiprocessing.cpu_count(), 6) ) train_loader.std = std test_loader.std = std train_loader.mean = mean test_loader.mean = mean return train_loader, test_loader def svhn_loaders( batch_size, shuffle_train=True, shuffle_test=False, train_random_transform=False, normalize_input=False, num_examples=None, test_batch_size=None ): if normalize_input: mean = [0.43768206, 0.44376972, 0.47280434] std = [0.19803014, 0.20101564, 0.19703615] normalize = transforms.Normalize(mean=mean, std=std) else: std = [1.0, 1.0, 1.0] mean = [0, 0, 0] normalize = transforms.Normalize(mean=mean, std=std) if train_random_transform: if normalize_input: train = datasets.SVHN( './data', split='train', download=True, transform=transforms.Compose([ transforms.RandomCrop(32, 4), transforms.ToTensor(), normalize, ]) ) else: train = datasets.SVHN( './data', split='train', download=True, transform=transforms.Compose([ transforms.RandomCrop(32, 4), transforms.ToTensor(), ]) ) else: train = datasets.SVHN( './data', split='train', download=True, transform=transforms.Compose([transforms.ToTensor(), normalize]) ) test = datasets.SVHN( './data', split='test', download=True, transform=transforms.Compose([transforms.ToTensor(), normalize]) ) if num_examples: indices = list(range(num_examples)) train = data.Subset(train, indices) test = data.Subset(test, indices) train_loader = torch.utils.data.DataLoader( train, batch_size=batch_size, shuffle=shuffle_train, pin_memory=True, num_workers=min(multiprocessing.cpu_count(), 6) ) if test_batch_size: batch_size = test_batch_size test_loader = torch.utils.data.DataLoader( test, batch_size=max(batch_size, 1), shuffle=shuffle_test, pin_memory=True, num_workers=min(multiprocessing.cpu_count(), 6) ) train_loader.std = std test_loader.std = std train_loader.mean = mean test_loader.mean = mean mean, std = get_stats(train_loader) print('dataset mean = ', mean.numpy(), 'std = ', std.numpy()) return train_loader, test_loader # when new loaders is added, they must be registered here loaders = { "mnist": partial(mnist_loaders, datasets.MNIST), "fashion-mnist": partial(mnist_loaders, datasets.FashionMNIST), "cifar": cifar_loaders, "svhn": svhn_loaders, }

34.299517

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7,100

5.135654

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0.036466

0.065217

0.761805

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7,100

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0.790626

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0

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0

null

0

1

0

1

0

null

0

4

a9f075b294f67a4f61534ce13e58b9747ea7f44f

82

py

Python

analog_ec/layout/passives/resistor/__init__.py

xyabc/bag_analog_ec

e92b4ce8d6422d9a5731381bb3feeba54dfe33a9

[ "BSD-3-Clause" ]

1

2021-08-03T12:32:46.000Z

analog_ec/layout/passives/resistor/__init__.py

xyabc/bag_analog_ec

e92b4ce8d6422d9a5731381bb3feeba54dfe33a9

[ "BSD-3-Clause" ]

null

analog_ec/layout/passives/resistor/__init__.py

xyabc/bag_analog_ec

e92b4ce8d6422d9a5731381bb3feeba54dfe33a9

[ "BSD-3-Clause" ]

1

2020-01-07T04:54:47.000Z

# -*- coding: utf-8 -*- """This package contains various resistor generators."""

20.5

56

0.658537

9

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0.014286

0.146341

82

3

57

27.333333

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true

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1

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1

0

null

0

1

0

4

e71182a1c8aeb7a9cf0312259e532c6e2dbe224c

474

py

Python

stamper/routes.py

ISTU-Labs/stumper

ef9d528fc6b9b78090a1613ffe737ed87d4b2d05

[ "MIT" ]

null

stamper/routes.py

ISTU-Labs/stumper

ef9d528fc6b9b78090a1613ffe737ed87d4b2d05

[ "MIT" ]

null

stamper/routes.py

ISTU-Labs/stumper

ef9d528fc6b9b78090a1613ffe737ed87d4b2d05

[ "MIT" ]

null

def includeme(config): config.add_static_view('js', 'static/js', cache_max_age=3600) config.add_static_view('css', 'static/css', cache_max_age=3600) config.add_static_view('static', 'static', cache_max_age=3600) config.add_static_view('dz', 'static/dropzone', cache_max_age=3600) config.add_route('add-image', '/api/1.0/add-image') config.add_route('image-upload', '/upload') config.add_route('login', '/login') config.add_route('home', '/')

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e7136aae4caa65a99d8bb2a08bfb3c05d1458a38

40

py

Python

CPAC/GUI/__init__.py

danlurie/C-PAC

5ddc2d4fa71eb13728d6156f73cb6e7621dda69d

[ "BSD-3-Clause" ]

null

CPAC/GUI/__init__.py

danlurie/C-PAC

5ddc2d4fa71eb13728d6156f73cb6e7621dda69d

[ "BSD-3-Clause" ]

null

CPAC/GUI/__init__.py

danlurie/C-PAC

5ddc2d4fa71eb13728d6156f73cb6e7621dda69d

[ "BSD-3-Clause" ]

1

2017-02-21T18:16:06.000Z

from mainUI import run __all__ =['run']

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e73855a6af3cddc7a75d50cfb2e35b31c4d237d8

198

py

Python

Waveforms/results/hAsymmetric_4_1.py

keefemitman/PostNewtonian

853d6577cb0002da5eebe1cb55f0c28fbc114324

[ "MIT" ]

18

2015-03-26T01:04:36.000Z

2022-02-01T19:26:21.000Z

Waveforms/results/hAsymmetric_4_1.py

keefemitman/PostNewtonian

853d6577cb0002da5eebe1cb55f0c28fbc114324

[ "MIT" ]

4

2015-01-08T23:46:29.000Z

2017-09-20T19:13:51.000Z

Waveforms/results/hAsymmetric_4_1.py

keefemitman/PostNewtonian

853d6577cb0002da5eebe1cb55f0c28fbc114324

[ "MIT" ]

3

2016-05-13T02:36:14.000Z

2021-11-23T21:36:32.000Z

-4*sqrt(2)*sqrt(pi)*nu*(18*I*S_lambda*nu - 6*I*S_lambda + 18*S_n*nu - 6*S_n + 17*I*Sigma_lambda*delta*nu - 6*I*Sigma_lambda*delta + 17*Sigma_n*delta*nu - 6*Sigma_n*delta)*r(0)**3*v(0)**13/(105*c**3)

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null

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4

e7c842de9f6bbe055c45a2c5e9db2d30a45e3ed9

362

py

Python

Test/Joints/test.py

Krande/CalculiX-Examples

26f50ef87d885e16564f336a76b94defcff107de

[ "MIT" ]

null

Test/Joints/test.py

Krande/CalculiX-Examples

26f50ef87d885e16564f336a76b94defcff107de

[ "MIT" ]

null

Test/Joints/test.py

Krande/CalculiX-Examples

26f50ef87d885e16564f336a76b94defcff107de

[ "MIT" ]

null

#!/usr/bin/python import os import multiprocessing # Enable multithreading for ccx os.environ['OMP_NUM_THREADS'] = str(multiprocessing.cpu_count()) os.system("param.py par.pre.fbl") os.system("cgx -b pre.fbl") os.system("cgx -b dist.fbl") os.system("cgx -b kin.fbl") os.system("param.py par.pre2.fbl") os.system("cgx -b pre2.fbl") os.system("cgx -b kin2.fbl")

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null

0

1

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4

e7d04b22c113107b1c0c867f2546e3a0f6dc092d

139

py

Python

ex12.py

analuisadev/Campinas-Tech-Exercises

32af47d82f687e46d033c07b40aa5d5069383ba0

[ "MIT" ]

1

2021-11-06T12:23:28.000Z

ex12.py

analuisadev/Campinas-Tech-Exercises

32af47d82f687e46d033c07b40aa5d5069383ba0

[ "MIT" ]

null

ex12.py

analuisadev/Campinas-Tech-Exercises

32af47d82f687e46d033c07b40aa5d5069383ba0

[ "MIT" ]

null

print ('{:=^40}'.format(' SEJA BEM VINDO(A) ')) name = str(input('Informe o seu nome: ')) print (f'Olá {name}, o seu nome é muito bonito!')

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null

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4

e7d31c8d901af60026bd61b583e92f51a8805e38

107

py

Python

code_samples/test.py

makuke1234/femto

cb0134797726499deb18756eea4e358ac1487085

[ "MIT" ]

1

2022-02-17T07:04:32.000Z

code_samples/test.py

makuke1234/femto

cb0134797726499deb18756eea4e358ac1487085

[ "MIT" ]

null

code_samples/test.py

makuke1234/femto

cb0134797726499deb18756eea4e358ac1487085

[ "MIT" ]

null

# This is a line comment ''' This is a block comment ''' def main(): print("Hello world!\n"); main()

8.916667

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0.598131

17

107

3.764706

0.705882

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107

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9.727273

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null

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4

e7d3a3d2dd7d635abf6211dac312d86f7d1f2c6f

44

py

Python

gf/__init__.py

Be5yond/gf

0afd90e32adad7e379e71ade9520343bd55d878e

[ "Apache-2.0" ]

1

2021-01-20T11:50:38.000Z

gf/__init__.py

Be5yond/gf

0afd90e32adad7e379e71ade9520343bd55d878e

[ "Apache-2.0" ]

null

gf/__init__.py

Be5yond/gf

0afd90e32adad7e379e71ade9520343bd55d878e

[ "Apache-2.0" ]

1

2021-03-17T09:28:31.000Z

from .main import app __version__ = "0.0.4"

14.666667

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0

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null

0

1

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4

99b11738926080bbd61e62b9cb835968c6ae6fc6

11,158

py

Python

audiomate/corpus/io/tuda.py

comodoro/audiomate

3437f405ff61362ca08d310226eb6e98e5294df5

[ "MIT" ]

null

audiomate/corpus/io/tuda.py

comodoro/audiomate

3437f405ff61362ca08d310226eb6e98e5294df5

[ "MIT" ]

null

audiomate/corpus/io/tuda.py

comodoro/audiomate

3437f405ff61362ca08d310226eb6e98e5294df5

[ "MIT" ]

null

import collections import os import glob import re import audiomate from audiomate import annotations from audiomate import issuers from audiomate.corpus.subset import subview from . import base SPEAKER_IDX_PATTERN = re.compile(r'<speaker_id>(.*?)</speaker_id>') GENDER_PATTERN = re.compile(r'<gender>(.*?)</gender>') TRANSCRIPTION_PATTERN = re.compile(r'<cleaned_sentence>(.*?)</cleaned_sentence>') RAW_TRANSCRIPTION_PATTERN = re.compile(r'<sentence>(.*?)</sentence>') AGE_PATTERN = re.compile(r'<ageclass>(.*?)</ageclass>') NATIVE_PATTERN = re.compile(r'<muttersprachler>(.*?)</muttersprachler>') SUBSETS = ['train', 'dev', 'test'] WAV_FILE_SUFFIXES = [ 'Kinect-Beam', 'Kinect-RAW', 'Realtek', 'Samson', 'Yamaha', 'Microsoft-Kinect-Raw' ] # Wrong transcripts, empty or to short BAD_FILES = { 'train': [ # INVALID AUDIO '2014-03-18-15-29-23', '2014-03-18-15-28-52', '2014-03-24-13-39-24', '2014-08-05-11-08-34', '2014-03-27-11-50-33', '2014-03-21-11-40-39', # TO SHORT FOR THE TRANSCRIPTION '2014-08-04-13-09-09', '2014-08-04-13-14-27', '2014-08-04-13-39-33', '2014-03-20-10-44-06', '2014-08-04-13-39-55', '2014-08-04-13-23-36', '2014-08-04-13-13-57', '2014-08-04-13-15-41', '2014-08-04-13-39-11', '2014-08-04-13-05-54', '2014-08-04-13-05-57', '2014-05-13-11-42-53', '2014-08-04-13-07-47', '2014-08-04-13-08-49', '2014-08-04-13-11-42', '2014-08-04-13-08-28', '2014-08-04-13-11-36', '2014-08-04-13-16-45', '2014-03-17-13-06-10', '2014-08-04-13-14-38', '2014-03-17-13-07-50', '2014-08-27-11-05-29', '2014-08-04-13-06-26', '2014-08-04-13-07-42', '2014-08-04-13-08-45', '2014-03-27-10-47-21', '2014-06-17-13-46-27', '2014-03-17-13-16-59', '2014-03-17-13-09-27', '2014-08-04-13-37-33', '2014-08-04-13-15-34', '2014-08-04-13-15-45', '2014-08-04-13-06-01', '2014-08-04-13-04-58', '2014-08-04-13-16-29', '2014-08-04-13-08-53', '2014-08-04-13-21-42', '2014-08-04-13-40-11', '2014-08-04-13-15-20', '2014-03-17-13-03-26', '2014-08-04-13-21-50', '2014-08-04-13-05-35', '2014-08-04-13-22-57', '2014-08-04-13-22-17', '2014-08-04-13-39-21', '2014-08-04-13-21-58', '2014-08-04-13-23-01', '2014-08-04-13-15-29', '2014-08-04-13-37-12', '2014-08-04-13-37-54', '2014-08-04-13-14-04', '2014-08-04-13-14-57', '2014-08-04-13-11-13', '2014-08-04-13-08-01', '2014-03-17-13-11-22', '2014-08-04-13-37-57', '2014-08-04-13-22-34', '2014-03-17-13-18-30', '2014-08-04-13-04-41', '2014-03-19-14-33-45', '2014-08-04-13-08-56', '2014-08-04-13-05-10', '2014-08-04-13-06-53', '2014-08-04-13-08-17', '2014-08-04-13-14-08', '2014-05-06-12-17-19', '2014-08-04-13-41-10', '2014-08-04-13-22-41', '2014-08-04-13-37-29', '2014-08-04-13-16-58', '2014-03-17-13-20-25', '2014-08-04-13-05-06', '2014-08-04-13-08-10', '2014-03-17-13-05-15', '2014-08-04-13-11-31', '2014-08-04-13-11-53', '2014-08-04-13-13-04', '2014-03-20-10-53-52', '2014-08-04-13-21-34', '2014-08-04-13-05-49', '2014-08-04-13-05-22', '2014-08-04-13-39-00', '2014-08-04-13-05-45', '2014-03-17-13-06-05', '2014-08-04-13-05-42', '2014-08-04-13-15-38', '2014-08-04-13-39-42', '2014-06-17-13-46-39', '2014-08-04-13-22-49', '2014-08-04-13-22-02', '2014-08-04-13-23-22', '2014-08-04-13-05-19', '2014-08-04-13-09-04', '2014-08-04-13-37-16', '2014-08-04-13-39-03', '2014-08-04-13-22-05', '2014-08-04-13-11-18', '2014-08-04-13-09-22', '2014-08-04-13-38-56', '2014-08-04-13-16-37', '2014-08-04-13-07-54', '2014-08-04-13-37-19', '2014-08-04-13-22-53', '2014-05-13-12-01-27', '2014-08-04-13-15-07', '2014-08-04-13-22-37', '2014-08-04-13-39-59', '2014-08-04-13-39-50', '2014-08-04-13-21-54', '2014-08-04-13-11-01', '2014-08-04-13-23-09', '2014-08-04-13-37-41', '2014-08-04-13-13-30', '2014-08-04-13-05-02', '2014-08-04-13-14-30', '2014-08-04-13-39-29', '2014-08-04-13-37-45', '2014-03-17-13-17-22', '2014-08-04-13-40-04', '2014-03-17-13-03-57', '2014-08-04-13-09-27', '2014-08-04-13-06-21', '2014-08-04-13-41-03', '2014-08-04-13-06-49', '2014-08-04-13-16-20', '2014-08-04-13-37-22', '2014-08-04-13-21-29', '2014-08-04-13-06-31', '2014-08-04-13-16-02', '2014-08-04-13-09-13', '2014-03-17-13-14-56', '2014-08-04-13-08-05', '2014-05-06-10-50-37', '2014-08-04-13-14-12', '2014-08-04-13-15-02', '2014-08-04-13-13-49', '2014-08-04-13-40-07', '2014-08-04-13-23-13', '2014-08-04-13-14-53', '2014-08-04-13-08-40', '2014-03-17-13-18-33', '2014-08-04-13-39-16', '2014-08-04-13-23-05', '2014-08-04-13-05-26', '2014-08-04-13-05-30', '2014-08-04-13-06-12', '2014-08-04-13-05-14', '2014-08-04-13-41-18', '2014-03-17-13-15-57', '2014-08-04-13-04-37', '2014-08-04-13-14-00', '2014-08-04-13-15-11', '2014-03-17-13-15-42', '2014-08-04-13-41-22', '2014-03-17-13-04-03', '2014-08-04-13-11-56', '2014-08-04-13-37-49', '2014-08-04-13-14-35', '2014-08-04-13-07-58', '2014-08-04-13-06-09', '2014-08-04-13-10-53', '2014-08-04-13-41-14', '2014-08-04-13-37-36', '2014-08-04-13-10-57', '2014-08-04-13-13-33', '2014-03-17-13-19-59', '2014-08-04-13-13-22', '2014-08-04-13-04-49', '2014-08-04-13-13-37', '2014-08-04-13-23-17', '2014-08-04-13-11-40', '2014-08-04-13-14-42', '2014-08-04-13-09-00', '2014-08-04-13-13-53', '2014-08-04-13-15-49', '2014-03-17-13-13-51', '2014-08-04-13-17-01' ], 'dev': [ # INVALID AUDIO '2015-02-09-13-48-26', '2015-02-09-12-36-46', '2015-01-28-11-49-53', '2015-02-04-12-29-49' ], 'test': [ # INVALID AUDIO '2015-02-04-12-36-32', '2015-02-10-13-45-07', '2015-01-27-14-37-33', '2015-02-10-14-18-26' ] } class TudaReader(base.CorpusReader): """ Reader for the TUDA german distant speech corpus (german-speechdata-package-v2.tar.gz). Note: It only loads files ending in -beamformedSignal.wav .. seealso:: `<https://www.inf.uni-hamburg.de/en/inst/ab/lt/resources/data/acoustic-models.html>`_ Download page """ @classmethod def type(cls): return 'tuda' def _check_for_missing_files(self, path): return [] def _load(self, path): corpus = audiomate.Corpus(path=path) for part in SUBSETS: sub_path = os.path.join(path, part) ids = TudaReader.get_ids_from_folder(sub_path, part) utt_ids = [] for idx in ids: add_ids = TudaReader.load_file(sub_path, idx, corpus) utt_ids.extend(add_ids) subview_filter = subview.MatchingUtteranceIdxFilter(utterance_idxs=utt_ids) subview_corpus = subview.Subview(corpus, filter_criteria=[subview_filter]) corpus.import_subview(part, subview_corpus) TudaReader.create_wav_type_subviews(corpus, utt_ids, prefix='{}_'.format(part)) TudaReader.create_wav_type_subviews(corpus, corpus.utterances.keys()) return corpus @staticmethod def create_wav_type_subviews(corpus, utt_ids, prefix=''): splits = collections.defaultdict(list) for utt_id in utt_ids: wavtype = utt_id.split('_')[-1] splits[wavtype].append(utt_id) for sub_name, sub_utts in splits.items(): subview_filter = subview.MatchingUtteranceIdxFilter(utterance_idxs=sub_utts) subview_corpus = subview.Subview(corpus, filter_criteria=[subview_filter]) corpus.import_subview('{}{}'.format(prefix, sub_name), subview_corpus) @staticmethod def get_ids_from_folder(path, part_name): """ Return all ids from the given folder, which have a corresponding beamformedSignal file. """ valid_ids = set({}) for xml_file in glob.glob(os.path.join(path, '*.xml')): idx = os.path.splitext(os.path.basename(xml_file))[0] if idx not in BAD_FILES[part_name]: valid_ids.add(idx) return valid_ids @staticmethod def load_file(folder_path, idx, corpus): """ Load speaker, file, utterance, labels for the file with the given id. """ xml_path = os.path.join(folder_path, '{}.xml'.format(idx)) wav_paths = [] for wav_suffix in WAV_FILE_SUFFIXES: wav_path = os.path.join(folder_path, '{}_{}.wav'.format(idx, wav_suffix)) if os.path.isfile(wav_path): wav_paths.append(wav_path) if len(wav_paths) == 0: return [] with open(xml_path, 'r', encoding='utf-8') as f: text = f.read() transcription = TudaReader.extract_value(text, TRANSCRIPTION_PATTERN, 'transcription', xml_path) transcription_raw = TudaReader.extract_value(text, RAW_TRANSCRIPTION_PATTERN, 'raw_transcription', xml_path) gender = TudaReader.extract_value(text, GENDER_PATTERN, 'gender', xml_path) is_native = TudaReader.extract_value(text, NATIVE_PATTERN, 'native', xml_path) age_class = TudaReader.extract_value(text, AGE_PATTERN, 'age', xml_path) speaker_idx = TudaReader.extract_value(text, SPEAKER_IDX_PATTERN, 'speaker_idx', xml_path) if speaker_idx not in corpus.issuers.keys(): start_age_class = int(age_class.split('-')[0]) if start_age_class < 12: age_group = issuers.AgeGroup.CHILD elif start_age_class < 18: age_group = issuers.AgeGroup.YOUTH elif start_age_class < 65: age_group = issuers.AgeGroup.ADULT else: age_group = issuers.AgeGroup.SENIOR native_lang = None if is_native == 'Ja': native_lang = 'deu' issuer = issuers.Speaker(speaker_idx, gender=issuers.Gender(gender), age_group=age_group, native_language=native_lang) corpus.import_issuers(issuer) utt_ids = [] for wav_path in wav_paths: wav_name = os.path.split(wav_path)[1] wav_idx = os.path.splitext(wav_name)[0] corpus.new_file(wav_path, wav_idx) utt = corpus.new_utterance(wav_idx, wav_idx, speaker_idx) utt.set_label_list(annotations.LabelList.create_single( transcription, idx=audiomate.corpus.LL_WORD_TRANSCRIPT )) utt.set_label_list(annotations.LabelList.create_single( transcription_raw, idx=audiomate.corpus.LL_WORD_TRANSCRIPT_RAW )) utt_ids.append(wav_idx) return utt_ids @staticmethod def extract_value(text, pattern, value, path): m = pattern.search(text) if m: return m.group(1) else: raise ValueError('Value {} not found in {}'.format(value, path))

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99e102e689ae54ed18924c29b1a7480bcc9cc233

148

py

Python

reddit2telegram/channels/~inactive/chessmemesenglish/app.py

CaringCat/reddit2telegram

aa3195d9964dfe0f5d822b37a41d567d1af423b7

[ "MIT" ]

187

2016-09-20T09:15:54.000Z

2022-03-29T12:22:33.000Z

reddit2telegram/channels/~inactive/chessmemesenglish/app.py

CaringCat/reddit2telegram

aa3195d9964dfe0f5d822b37a41d567d1af423b7

[ "MIT" ]

84

2016-09-22T14:25:07.000Z

2022-03-19T01:26:17.000Z

reddit2telegram/channels/~inactive/chessmemesenglish/app.py

CaringCat/reddit2telegram

aa3195d9964dfe0f5d822b37a41d567d1af423b7

[ "MIT" ]

172

2016-09-21T15:39:39.000Z

2022-03-16T15:15:58.000Z

#encoding:utf-8 subreddit = 'chessmemes' t_channel = '@chessmemesenglish' def send_post(submission, r2t): return r2t.send_simple(submission)

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8200617e96e6ccd9c9e97fbfe5459fe1741a32d8

2,913

py

Python

tangos/live_calculation/builtin_functions/arithmetic.py

Martin-Rey/tangos

49421cade11a6d91b10eceae60fc38d10ff5b30e

[ "BSD-3-Clause" ]

15

2017-12-04T18:05:32.000Z

2021-12-20T22:11:20.000Z

tangos/live_calculation/builtin_functions/arithmetic.py

Martin-Rey/tangos

49421cade11a6d91b10eceae60fc38d10ff5b30e

[ "BSD-3-Clause" ]

99

2017-11-09T16:47:20.000Z

2022-03-07T10:15:12.000Z

tangos/live_calculation/builtin_functions/arithmetic.py

anchwr/tangos

a66740258e0987d90d921cd9c6f92658ce8375a8

[ "BSD-3-Clause" ]

14

2017-11-06T18:46:17.000Z

2021-12-13T10:49:53.000Z

from __future__ import absolute_import from .. import BuiltinFunction, FixedNumericInput import numpy as np import functools from six.moves import zip @BuiltinFunction.register def abs(halos, vals): if not hasattr(vals[0], '__len__'): # Avoid norm failing if abs is called on a single number (issue 110) return arithmetic_unary_op(vals, np.abs) else: return arithmetic_unary_op(vals, functools.partial(np.linalg.norm, axis=-1)) @BuiltinFunction.register def sqrt(halos, vals): return arithmetic_unary_op(vals, np.sqrt) @BuiltinFunction.register def log(halos, vals): return arithmetic_unary_op(vals, np.log) @BuiltinFunction.register def log10(halos, vals): return arithmetic_unary_op(vals, np.log10) @BuiltinFunction.register def subtract(halos, vals1, vals2): return arithmetic_binary_op(vals1, vals2, np.subtract) @BuiltinFunction.register def add(halos, vals1, vals2): return arithmetic_binary_op(vals1, vals2, np.add) @BuiltinFunction.register def divide(halos, vals1, vals2): return arithmetic_binary_op(vals1, vals2, np.divide) @BuiltinFunction.register def multiply(halos, vals1, vals2): return arithmetic_binary_op(vals1, vals2, np.multiply) @BuiltinFunction.register def greater(halos, vals1, vals2): return arithmetic_binary_op(vals1, vals2, np.greater) @BuiltinFunction.register def less(halos, vals1, vals2): return arithmetic_binary_op(vals1, vals2, np.less) @BuiltinFunction.register def equal(halos, vals1, vals2): return arithmetic_binary_op(vals1, vals2, np.equal) @BuiltinFunction.register def greater_equal(halos, vals1, vals2): return arithmetic_binary_op(vals1, vals2, np.greater_equal) @BuiltinFunction.register def less_equal(halos, vals1, vals2): return arithmetic_binary_op(vals1, vals2, np.less_equal) @BuiltinFunction.register def logical_and(halos, vals1, vals2): return arithmetic_binary_op(vals1, vals2, np.logical_and) @BuiltinFunction.register def logical_or(halos, vals1, vals2): return arithmetic_binary_op(vals1, vals2, np.logical_or) @BuiltinFunction.register def logical_not(halos, vals): return arithmetic_unary_op(vals, np.logical_not) @BuiltinFunction.register def power(halos, vals1, vals2): return arithmetic_binary_op(vals1, vals2, np.power) def arithmetic_binary_op(vals1, vals2, op): results = [] for v1,v2 in zip(vals1, vals2): if v1 is not None and v2 is not None: v1 = np.asarray(v1, dtype=float) v2 = np.asarray(v2, dtype=float) result = op(v1,v2) else: result = None results.append(result) return results def arithmetic_unary_op(vals1, op): results = [] for v1 in vals1: if v1 is not None: v1 = np.asarray(v1, dtype=float) result = op(v1) else: result = None results.append(result) return results

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0.726056

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2,913

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0.182519

0.126459

0.214981

0.145428

0.535992

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0.472276

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0.322471

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0.032581

0.178167

2,913

99

112

29.424242

0.826232

0.022657

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null

0

1

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null

0

1

0

1

0

4

8220a08468d52f91a75829a34aa2c0c06c618aae

44

py

Python

plugins/__init__.py

codacy-badger/nebula-2

81a257f6485da1899a2cb1df348a57332aa4b55c

[ "Apache-2.0" ]

null

plugins/__init__.py

codacy-badger/nebula-2

81a257f6485da1899a2cb1df348a57332aa4b55c

[ "Apache-2.0" ]

null

plugins/__init__.py

codacy-badger/nebula-2

81a257f6485da1899a2cb1df348a57332aa4b55c

[ "Apache-2.0" ]

null

__all__ = ["example"] from plugins import *

14.666667

21

0.704545

5

44

5.4

1

0

0.159091

44

3

22

14.666667

0.72973

0

0.155556

0

1

0

false

0

0.5

0

0.5

0

1

0

null

0

1

0

null

0

1

0

4

82360728700f3e10e95d7ffd22b99ccf75955994

1,445

py

Python

app/models.py

Brayoh-ux/Pitch-App

eab974f34fa14c8158fa2235e6d86bb13429e0b1

[ "MIT" ]

null

app/models.py

Brayoh-ux/Pitch-App

eab974f34fa14c8158fa2235e6d86bb13429e0b1

[ "MIT" ]

null

app/models.py

Brayoh-ux/Pitch-App

eab974f34fa14c8158fa2235e6d86bb13429e0b1

[ "MIT" ]

null

from datetime import datetime from app import db from werkzeug.security import check_password_hash, generate_password_hash from flask_login import UserMixin from app import login # from werkzeug.security import generate_password_hash, check_password_hash @login.user_loader def load_user(id): return User.query.get(int(id)) class User( UserMixin ,db.Model): id = db.Column(db.Integer, primary_key = True) username = db.Column(db.String(30), index = True, unique = True) email = db.Column(db.String(150), index = True, unique =True) image_file = db.Column(db.String(30), index = True, default = 'default.jpeg') password = db.Column(db.String(60)) posts = db.relationship('Post', backref='author', lazy='dynamic') def __repr__(self): return f" User('{ self.username } ', '{ self.email} ', '{ self.image_file } ' )" # 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) class Post(db.Model): id = db.Column(db.Integer, primary_key = True) title = db.Column(db.String(140)) content = db.Column(db.Text) date_posted = db.Column(db.DateTime, default = datetime.utcnow ) user_id = db.Column(db.Integer, db.ForeignKey('user.id')) def __repr__(self): return f" Post('{ self.title } ', '{ self.date_posted} ')"

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88

0.693426

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1,445

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0.082645

0.103306

0.082645

0.261364

0.13843

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0

0.010067

0.175087

1,445

44

89

32.840909

0.802013

0.181315

0

0.16

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0

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false

0.08

0.2

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0.96

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null

0

1

0

null

0

1

0

1

0

4

8245f623cd5ccfa5a144fbaff3101e464d5af79c

358

py

Python

Python-codes-CeV/74-Tuple_Rand.py

engcristian/Python

726a53e9499fd5d0594572298e59e318f98e2d36

[ "MIT" ]

1

2021-02-22T03:53:23.000Z

Python-codes-CeV/74-Tuple_Rand.py

engcristian/Python

726a53e9499fd5d0594572298e59e318f98e2d36

[ "MIT" ]

null

Python-codes-CeV/74-Tuple_Rand.py

engcristian/Python

726a53e9499fd5d0594572298e59e318f98e2d36

[ "MIT" ]

null

''' Generate 5 numbers in a Tuple and show the max and min value ''' from random import randint num = (randint(1, 10),randint(1, 10),randint(1, 10), randint(1, 10),randint(1, 10)) print(f'The values sorted are: ' , end=' ') for n in num: print(f' {n} ', end=" ") print(f'\nThe max value is {max(num)}.') print(f'The min value is {min(num)}')

32.545455

60

0.617318

64

358

3.453125

0.453125

0.180995

0.226244

0.307692

0.226244

0

0.055749

0.198324

358

11

61

32.545455

0.714286

0.167598

0

1

0

0.298969

0

1

0

false

0

0.125

0

0.125

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null

0

1

0

1

0

null

0

1

0

4

418133736b033568ebef3411050f7ce8c36aee56

1,809

py

Python

qcodes/instrument_drivers/Artiq/artiq_driver.py

nulinspiratie/Qcodes

d050d38ac83f532523a39549c3247dfa6096a36e

[ "MIT" ]

2

2017-02-27T06:02:39.000Z

2019-06-03T04:56:59.000Z

qcodes/instrument_drivers/Artiq/artiq_driver.py

nulinspiratie/Qcodes

d050d38ac83f532523a39549c3247dfa6096a36e

[ "MIT" ]

50

2017-04-12T04:03:15.000Z

2022-03-09T00:41:43.000Z

qcodes/instrument_drivers/Artiq/artiq_driver.py

nulinspiratie/Qcodes

d050d38ac83f532523a39549c3247dfa6096a36e

[ "MIT" ]

null

""" Driver for the Zotino and Sampler, CPU by V.Schmitt (May 2019) Modified by R.Savytskyy and M.Johnson (June 2019) """ import socket from qcodes import Instrument class Zotino(Instrument): def __init__(self, name, channel_dict, address, port, **kwargs): super().__init__(name, **kwargs) self.channel_dict = channel_dict self.address = address self.port = port for channel_name, channel_properties in self.channel_dict.items(): self.add_parameter(name=channel_name, unit='V', set_cmd=lambda x, ch=channel_properties['channel']: self.write("0 " + str(ch) + ' ' + str(x)), get_cmd=lambda ch=channel_properties['channel']: self.ask("1 " + str(ch)) ) def write(self, cmd): s = socket.socket(socket.AF_INET, socket.SOCK_STREAM) s.connect((self.address, self.port)) s.sendall(cmd.encode('utf-8')) s.close() def ask(self, cmd): BUFFER_SIZE = 10 s = socket.socket(socket.AF_INET, socket.SOCK_STREAM) s.connect((self.address, self.port)) s.sendall(cmd.encode('utf-8')) data = s.recv(BUFFER_SIZE) s.close() return float(data) class Sampler(Instrument): def __init__(self, name, channel_dict, address, port, **kwargs): super().__init__(name, **kwargs) self.channel_dict = channel_dict self.address = address self.port = port for channel_name, channel_properties in self.channel_dict.items(): self.add_parameter(name=channel_name, unit='V', get_cmd=lambda ch=channel_properties['channel'], average=channel_properties['average']: self.ask("3 " + str(ch) + " " + str(average)) ) def ask(self, cmd): BUFFER_SIZE = 10 s = socket.socket(socket.AF_INET, socket.SOCK_STREAM) s.connect((self.address, self.port)) s.sendall(cmd.encode('utf-8')) data = s.recv(BUFFER_SIZE) s.close() return float(data)

31.189655

143

0.690989

265

1,809

4.532075

0.267925

0.073272

0.062448

0.064946

0.783514

0.755204

0.691923

0

0.011842

0.159757

1,809

58

144

31.189655

0.778289

0.061913

0

0.772727

0

0.031398

0

1

0.113636

false

0

0.045455

0

0.25

0

null

0

1

0

1

0

1

0

null

0

4

41836ddf269b4affa5722f61296d77a3e366c979

79

py

Python

models/MIXER/__init__.py

Juncheng-Dong/ML_MM_Benchmark

ceb9b1563057967cebbec9463190d04406c13cc0

[ "MIT" ]

3

2021-08-23T21:22:08.000Z

2021-12-29T22:17:45.000Z

models/MIXER/__init__.py

Juncheng-Dong/ML_MM_Benchmark

ceb9b1563057967cebbec9463190d04406c13cc0

[ "MIT" ]

null

models/MIXER/__init__.py

Juncheng-Dong/ML_MM_Benchmark

ceb9b1563057967cebbec9463190d04406c13cc0

[ "MIT" ]

3

2021-09-04T01:56:47.000Z

2021-09-19T02:59:31.000Z

from . import MLP_MIXER print("Mixer is GOOD") DukeMixer = MLP_MIXER.MonsterFB

19.75

31

0.78481

12

79

5

0.75

0.266667

0

0.126582

79

4

31

19.75

0.869565

0

0.1625

0

1

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false

0

0.333333

0

0.333333

1

0

null

1

0

1

0

null

0

1

0

4

418936479aa85ef5104762679555ddfde998f019

1,233

py

Python

absspider.py

transferXiang/netspider

fc49a58a22ab97249a0a5385ee724292296855d2

[ "Apache-2.0" ]

null

absspider.py

transferXiang/netspider

fc49a58a22ab97249a0a5385ee724292296855d2

[ "Apache-2.0" ]

null

absspider.py

transferXiang/netspider

fc49a58a22ab97249a0a5385ee724292296855d2

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- import requests from bs4 import BeautifulSoup class AbsUlrCollector: def get_next_page_suffix(self, soup): return '' def parse_page_info(self, soup): return '' def save_page_info(self, info): pass def get_url_list(self, prefix_url, suffix_url='', builder='html.parser', encoding='gb18030'): url = prefix_url + suffix_url print("downloading...%s" % url) page = requests.get(url).content soup = BeautifulSoup(page, builder, from_encoding=encoding) info = self.parse_page_info(soup) self.save_page_info(info) new_suffix_url = self.get_next_page_suffix(soup) if new_suffix_url != '': self.get_url_list(prefix_url, new_suffix_url) class AbsContexParse: def get_context(self, soup): return '' def process_context(self, url, context): return '' def analysis_page(self, url, builder='html.parser', encoding='gb18030'): page = requests.get(url).content soup = BeautifulSoup(page, builder, from_encoding=encoding) context = self.get_context(soup) return self.process_context(url, context) if __name__ == '__main__': pass

24.176471

97

0.648824

153

1,233

4.941176

0.27451

0.059524

0.055556

0.06746

0.335979

0.285714

0.193122

0

0.012821

0.240876

1,233

50

98

24.66

0.794872

0.017032

0

0.322581

0

0.049587

0

1

0.225806

false

0.064516

0.129032

0.516129

0.032258

0

null

0

null

0

1

0

1

0

1

0

4

418aa80888eeaf427ba8cefc4d757984a89ebe5a

101

py

Python

mycreditcards/apps.py

satuomainen/howdoesone-django-admin

529eb3f70215d1679befbab6dfa93dd8aa24d13f

[ "MIT" ]

null

mycreditcards/apps.py

satuomainen/howdoesone-django-admin

529eb3f70215d1679befbab6dfa93dd8aa24d13f

[ "MIT" ]

3

2021-10-05T23:53:38.000Z

2022-02-18T04:02:03.000Z

mycreditcards/apps.py

satuomainen/howdoesone-django-admin

529eb3f70215d1679befbab6dfa93dd8aa24d13f

[ "MIT" ]

null

from django.apps import AppConfig class MycreditcardsConfig(AppConfig): name = 'mycreditcards'

16.833333

37

0.782178

10

101

7.9

0.9

0

0.148515

101

5

38

20.2

0.918605

0

0.128713

0

1

0

false

0

0.333333

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

4

4196acb8c79699b08963bdf085a7eba0ed05db8a

250

py

Python

lib/models/__init__.py

davidaderup/query2labels

5a10c861dda85d94ba01ec6ad4119eef67a9f441

[ "MIT" ]

null

lib/models/__init__.py

davidaderup/query2labels

5a10c861dda85d94ba01ec6ad4119eef67a9f441

[ "MIT" ]

null

lib/models/__init__.py

davidaderup/query2labels

5a10c861dda85d94ba01ec6ad4119eef67a9f441

[ "MIT" ]

null

from .resnet import * from .query2label import Query2Label query2label = Query2Label from .tresnet import tresnetm, tresnetl, tresnetxl, tresnetl_21k from .tresnet2 import tresnetl as tresnetl_v2 from .swin_transformer import build_swin_transformer

31.25

64

0.844

31

250

6.645161

0.483871

0.213592

0

0.036199

0.116

250

7

65

35.714286

0.895928

0

1

0

false

0

0.833333

0

0.833333

0

null

1

0

1

0

null

0

1

0

1

0

4

68e6dba6be46652a9694b9fe48ffec61e6f652b3

81

py

Python

cpp/apps.py

InerstIO/chinese-postman-webpage

8556c5628b9fd7ee00ee16a5f791b25de5b626b9

[ "MIT" ]

null

cpp/apps.py

InerstIO/chinese-postman-webpage

8556c5628b9fd7ee00ee16a5f791b25de5b626b9

[ "MIT" ]

null

cpp/apps.py

InerstIO/chinese-postman-webpage

8556c5628b9fd7ee00ee16a5f791b25de5b626b9

[ "MIT" ]

null

from django.apps import AppConfig class CppConfig(AppConfig): name = 'cpp'

13.5

33

0.728395

10

81

5.9

0.9

0

0.185185

81

5

34

16.2

0.893939

0

0.037037

0

1

0

false

0

0.333333

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

4

68f8b80ffc2f69d5dd245a9d498563937300a0e4

216

py

Python

auth/services.py

uktrade/lite-exporter-frontend

cf42ac37a21236486aa303c8935c44a7eba91ef5

[ "MIT" ]

3

2019-05-31T06:36:17.000Z

2020-02-12T16:02:24.000Z

auth/services.py

uktrade/lite-exporter-frontend

cf42ac37a21236486aa303c8935c44a7eba91ef5

[ "MIT" ]

33

2019-03-28T10:20:14.000Z

2020-07-16T15:12:43.000Z

auth/services.py

uktrade/lite-exporter-frontend

cf42ac37a21236486aa303c8935c44a7eba91ef5

[ "MIT" ]

1

2019-05-01T15:52:02.000Z

from conf.client import post from conf.constants import AUTHENTICATION_URL def authenticate_exporter_user(request, json): data = post(request, AUTHENTICATION_URL, json) return data.json(), data.status_code

27

50

0.791667

29

216

5.724138

0.62069

0.096386

0

0.134259

216

7

51

30.857143

0.887701

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

ec23a6c0c78c92900e45e60d2ab6778e44335952

23

py

Python

cloudmesh/burn/__init__.py

cloudmesh/cloudmesh_pi_burn

0d080c0b6057e2c761e90ebd4144d04b4dff6d6b

[ "Apache-2.0" ]

16

2021-01-16T16:18:08.000Z

2022-03-07T16:09:18.000Z

cloudmesh/burn/__init__.py

cloudmesh/cloudmesh-pi-burn

ad76a310e3ebe2b6111b00de0d2a80693ceeb6f4

[ "Apache-2.0" ]

11

2021-01-16T12:39:56.000Z

2021-05-06T21:57:43.000Z

cloudmesh/burn/__init__.py

cloudmesh/cloudmesh-pi-burn

ad76a310e3ebe2b6111b00de0d2a80693ceeb6f4

[ "Apache-2.0" ]

3

2021-02-07T16:35:05.000Z

2021-04-03T04:48:10.000Z

__version__ = "4.3.29"

11.5

22

0.652174

4

23

2.75

1

0

0.2

0.130435

23

1

23

0.35

0

0.26087

0

1

0

false

0

1

0

null

0

1

0

1

0

null

0

4

6b8100b4f03b802a1262ab7d7f1e20deabef2b55

120

py

Python

ValidationApp/admin.py

cs-fullstack-2019-spring/django-validation-cw-rdunavant

b678fca434ea1c733d378e65de623a428f516a0a

[ "Apache-2.0" ]

null

ValidationApp/admin.py

cs-fullstack-2019-spring/django-validation-cw-rdunavant

b678fca434ea1c733d378e65de623a428f516a0a

[ "Apache-2.0" ]

null

ValidationApp/admin.py

cs-fullstack-2019-spring/django-validation-cw-rdunavant

b678fca434ea1c733d378e65de623a428f516a0a

[ "Apache-2.0" ]

null

from django.contrib import admin from .models import carModel # Register your models here. admin.site.register(carModel)

30

32

0.825

17

120

5.823529

0.647059

0

0.108333

120

4

33

30

0.925234

0.216667

0

1

0

true

0

0.666667

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

4

6b8ea104d14db1f9a5d14cfb54c5e8672d9bf43d

455

py

Python

bmh_lims/conftest.py

BFSSI-Bioinformatics-Lab/bmh_lims

02892449a2c17e629732f5580d62596a72b279b0

[ "MIT" ]

null

bmh_lims/conftest.py

BFSSI-Bioinformatics-Lab/bmh_lims

02892449a2c17e629732f5580d62596a72b279b0

[ "MIT" ]

7

2020-09-28T13:42:56.000Z

2021-01-28T15:48:10.000Z

bmh_lims/conftest.py

bfssi-forest-dussault/bmh_lims

02892449a2c17e629732f5580d62596a72b279b0

[ "MIT" ]

1

2021-01-18T18:15:18.000Z

import pytest from bmh_lims.users.models import User from bmh_lims.users.tests.factories import UserFactory from bmh_lims.database.models import Sample from bmh_lims.database.tests.factories import SampleFactory @pytest.fixture(autouse=True) def media_storage(settings, tmpdir): settings.MEDIA_ROOT = tmpdir.strpath @pytest.fixture def user() -> User: return UserFactory() @pytest.fixture def sample() -> Sample: return SampleFactory()

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6bb3d9994f06886b0bc838a58e392dea3a8b5644

273

py

Python

lib/django-1.5/django/contrib/auth/tests/utils.py

MiCHiLU/google_appengine_sdk

3da9f20d7e65e26c4938d2c4054bc4f39cbc5522

[ "Apache-2.0" ]

790

2015-01-03T02:13:39.000Z

2020-05-10T19:53:57.000Z

AppServer/lib/django-1.5/django/contrib/auth/tests/utils.py

nlake44/appscale

6944af660ca4cb772c9b6c2332ab28e5ef4d849f

[ "Apache-2.0" ]

1,361

2015-01-08T23:09:40.000Z

2020-04-14T00:03:04.000Z

AppServer/lib/django-1.5/django/contrib/auth/tests/utils.py

nlake44/appscale

6944af660ca4cb772c9b6c2332ab28e5ef4d849f

[ "Apache-2.0" ]

155

2015-01-08T22:59:31.000Z

2020-04-08T08:01:53.000Z

from django.conf import settings from django.utils.unittest import skipIf def skipIfCustomUser(test_func): """ Skip a test if a custom user model is in use. """ return skipIf(settings.AUTH_USER_MODEL != 'auth.User', 'Custom user model in use')(test_func)

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