xszheng2020/the_stack_dedup_python_hits_4 · Datasets at Hugging Face

5098242411472871796fcb0e267b5dd5db17fdab

376

py

Python

zcrmsdk/src/com/zoho/crm/api/org/__init__.py

zoho/zohocrm-python-sdk-2.0

3a93eb3b57fed4e08f26bd5b311e101cb2995411

[ "Apache-2.0" ]

null

zcrmsdk/src/com/zoho/crm/api/org/__init__.py

zoho/zohocrm-python-sdk-2.0

3a93eb3b57fed4e08f26bd5b311e101cb2995411

[ "Apache-2.0" ]

null

zcrmsdk/src/com/zoho/crm/api/org/__init__.py

zoho/zohocrm-python-sdk-2.0

3a93eb3b57fed4e08f26bd5b311e101cb2995411

[ "Apache-2.0" ]

null

from .license_details import LicenseDetails from .api_exception import APIException from .action_response import ActionResponse from .response_handler import ResponseHandler from .org import Org from .success_response import SuccessResponse from .file_body_wrapper import FileBodyWrapper from .response_wrapper import ResponseWrapper from .org_operations import OrgOperations

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50b8f80c0e6c225c807d00700e8b543b0bb26461

210

py

Python

robo/initial_design/__init__.py

lebrice/RoBO

0cb58a1622d3a540f7714b239f0cedf048b6fd9f

[ "BSD-3-Clause" ]

455

2015-04-02T06:12:13.000Z

2022-02-28T10:54:29.000Z

robo/initial_design/__init__.py

lebrice/RoBO

0cb58a1622d3a540f7714b239f0cedf048b6fd9f

[ "BSD-3-Clause" ]

66

2015-04-07T15:20:55.000Z

2021-06-04T16:40:46.000Z

robo/initial_design/__init__.py

lebrice/RoBO

0cb58a1622d3a540f7714b239f0cedf048b6fd9f

[ "BSD-3-Clause" ]

188

2015-04-14T09:42:34.000Z

2022-03-31T21:04:53.000Z

from .init_grid import init_grid from .init_random_uniform import init_random_uniform from .init_latin_hypercube_sampling import init_latin_hypercube_sampling from .init_random_normal import init_random_normal

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50c5d94783098d9d54d406b34ba077d5e64962dc

263

py

Python

newsApp/cachingHelper.py

adityabansal/newsAroundMe

06d30c8a281baae90f916aa0b0bfe3b4db9d2293

[ "MIT" ]

9

2017-06-22T18:42:54.000Z

2021-03-28T18:58:44.000Z

newsApp/cachingHelper.py

adityabansal/newsAroundMe

06d30c8a281baae90f916aa0b0bfe3b4db9d2293

[ "MIT" ]

8

2016-10-08T12:50:50.000Z

2022-03-11T23:13:17.000Z

newsApp/cachingHelper.py

adityabansal/newsAroundMe

06d30c8a281baae90f916aa0b0bfe3b4db9d2293

[ "MIT" ]

3

2018-01-18T11:01:32.000Z

2018-11-20T08:33:30.000Z

import os import bmemcached def getCache(): servers = os.environ.get('MEMCACHIER_SERVERS', '').split(',') user = os.environ.get('MEMCACHIER_USERNAME', '') passw = os.environ.get('MEMCACHIER_PASSWORD', '') return bmemcached.Client(servers, user, passw)

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50c8bc637e51eb8f4d052f9687bf7503ee9881a4

138

py

Python

ckeditor/apps.py

mitodl/open-discussions

ab6e9fac70b8a1222a84e78ba778a7a065c20541

[ "BSD-3-Clause" ]

12

2017-09-27T21:23:27.000Z

2020-12-25T04:31:30.000Z

ckeditor/apps.py

mitodl/open-discussions

ab6e9fac70b8a1222a84e78ba778a7a065c20541

[ "BSD-3-Clause" ]

3,293

2017-06-30T18:16:01.000Z

2022-03-31T18:01:34.000Z

ckeditor/apps.py

mitodl/open-discussions

ab6e9fac70b8a1222a84e78ba778a7a065c20541

[ "BSD-3-Clause" ]

1

2020-04-13T12:19:57.000Z

"""ckeditor apps""" from django.apps import AppConfig class CkeditorConfig(AppConfig): """CKEditor config""" name = "ckeditor"

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0fabe62d503e1131e0be423f333f90981340ea32

67

py

Python

tests/__init__.py

MikeTrizna/biocode_fims

3274561d33b77301d037a3367a8c07507b5fe3a0

[ "MIT" ]

1

2019-01-07T20:35:48.000Z

tests/__init__.py

MikeTrizna/biocode_fims

3274561d33b77301d037a3367a8c07507b5fe3a0

[ "MIT" ]

1

2021-03-25T21:46:11.000Z

tests/__init__.py

MikeTrizna/biocode_fims

3274561d33b77301d037a3367a8c07507b5fe3a0

[ "MIT" ]

null

# -*- coding: utf-8 -*- """Unit test package for biocode_fims."""

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4

0faef270c92a619ec083628d12b673718d9aa666

285

py

Python

powertools/vendorize.py

philipov/powertools

49c6ad84cf360388983a7cbb0b74c22f27d25172

[ "MIT" ]

null

powertools/vendorize.py

philipov/powertools

49c6ad84cf360388983a7cbb0b74c22f27d25172

[ "MIT" ]

null

powertools/vendorize.py

philipov/powertools

49c6ad84cf360388983a7cbb0b74c22f27d25172

[ "MIT" ]

null

#-- powertools.vendorize ''' script to vendorize dependencies for a module ''' #-------------------------------------------------------------------------------------------------# #-------------------------------------------------------------------------------------------------#

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1

0

null

0

1

0

4

0fc2d0e7e9a0947100490a4d5359e3c547560404

93

py

Python

Candidate/apps.py

Poornartha/Odonata

71e8dfc4e8d93c6ecc1a3a155459b7e43bd28cdb

[ "MIT" ]

null

Candidate/apps.py

Poornartha/Odonata

71e8dfc4e8d93c6ecc1a3a155459b7e43bd28cdb

[ "MIT" ]

null

Candidate/apps.py

Poornartha/Odonata

71e8dfc4e8d93c6ecc1a3a155459b7e43bd28cdb

[ "MIT" ]

null

from django.apps import AppConfig class CandidateConfig(AppConfig): name = 'Candidate'

15.5

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7.1

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4

0fda5a20ffaaee7c5bb6f260fbd045e55f227441

158

py

Python

pytorch_tabular/models/tabnet/__init__.py

Actis92/pytorch_tabular

78dabf5e7b97d8ff24db4bc83d9d0a2273941bbe

[ "MIT" ]

560

2020-12-31T15:31:56.000Z

2022-03-30T20:29:06.000Z

pytorch_tabular/models/tabnet/__init__.py

Actis92/pytorch_tabular

78dabf5e7b97d8ff24db4bc83d9d0a2273941bbe

[ "MIT" ]

60

2021-02-04T05:54:33.000Z

2022-03-31T07:40:34.000Z

pytorch_tabular/models/tabnet/__init__.py

Actis92/pytorch_tabular

78dabf5e7b97d8ff24db4bc83d9d0a2273941bbe

[ "MIT" ]

63

2021-01-28T16:12:22.000Z

2022-03-31T07:31:41.000Z

from .config import TabNetModelConfig from .tabnet_model import TabNetModel, TabNetBackbone __all__ = ["TabNetModel", "TabNetModelConfig", "TabNetBackbone"]

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ba2a53cd71d41d9da32e721bbf3be64f407f6c60

26

py

Python

test1.py

shl418/test

6c7c93bf74e085300ee7c8f25eea1c557ce8c8e4

[ "MIT" ]

null

test1.py

shl418/test

6c7c93bf74e085300ee7c8f25eea1c557ce8c8e4

[ "MIT" ]

null

test1.py

shl418/test

6c7c93bf74e085300ee7c8f25eea1c557ce8c8e4

[ "MIT" ]

null

num = 1 num = 2 num2 = 3

5.2

8

0.5

6

26

2.166667

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0.25

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0

1

0

1

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null

0

4

e841533556b1206f91b7be678e18c0cb3444fc89

89

py

Python

back_end/Logging/apps.py

xk12138/visualization_analysis

483d236fb1a24b6912b0fa7f31f8b63c40f06eb1

[ "MIT" ]

1

2020-06-09T04:07:21.000Z

back_end/Logging/apps.py

xk12138/visualization_analysis

483d236fb1a24b6912b0fa7f31f8b63c40f06eb1

[ "MIT" ]

null

back_end/Logging/apps.py

xk12138/visualization_analysis

483d236fb1a24b6912b0fa7f31f8b63c40f06eb1

[ "MIT" ]

null

from django.apps import AppConfig class LoggingConfig(AppConfig): name = 'Logging'

14.833333

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1

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4

e8446f3d671ea050e0a6dc03f510ac960404aa84

322

py

Python

sourceCode/mainProgram/models/DatabaseManipulator.py

Jictyvoo/FilaLanche_SENAI

edc4ac0ce316f2000112c3ad9a92c6d55ee705e3

[ "MIT" ]

null

sourceCode/mainProgram/models/DatabaseManipulator.py

Jictyvoo/FilaLanche_SENAI

edc4ac0ce316f2000112c3ad9a92c6d55ee705e3

[ "MIT" ]

null

sourceCode/mainProgram/models/DatabaseManipulator.py

Jictyvoo/FilaLanche_SENAI

edc4ac0ce316f2000112c3ad9a92c6d55ee705e3

[ "MIT" ]

null

class DatabaseManipulator: def __init__(self, conexao): self.__conexao = conexao self.__cursor = self.__conexao.cursor() def getConexao(self): return self.__conexao def setConexao(self, conexao): self.__conexao = conexao def getCursor(self): return self.__cursor

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false

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4

e8b93b2e721dbe2201812f8c9543c069d2a0e0e7

162

py

Python

example/application/run.py

wesbarnett/apache-flask

b843353ec909358003c7384953b4a645778e05e0

[ "Apache-2.0" ]

3

2021-04-20T08:06:37.000Z

2022-03-02T14:12:11.000Z

example/application/run.py

wesbarnett/apache-flask

b843353ec909358003c7384953b4a645778e05e0

[ "Apache-2.0" ]

null

example/application/run.py

wesbarnett/apache-flask

b843353ec909358003c7384953b4a645778e05e0

[ "Apache-2.0" ]

2

2021-03-11T03:31:38.000Z

2021-05-01T14:53:03.000Z

import sys sys.path.insert(0, '/var/www/apache-flask/application') from app import app as application if __name__ == '__main__': application.run(port=8080)

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e8c9f18652ed5d2bcb3fee7923070056938f113a

27

py

Python

custom_components/smsapi/__init__.py

dderek2/ha-addons

899653726b25eb62f80c5415dec4d97451007a71

[ "Apache-2.0" ]

1

2021-01-15T15:26:34.000Z

custom_components/smsapi/__init__.py

dderek2/ha-addons

899653726b25eb62f80c5415dec4d97451007a71

[ "Apache-2.0" ]

1

2021-02-08T15:00:00.000Z

custom_components/smsapi/__init__.py

dderek2/ha-addons

899653726b25eb62f80c5415dec4d97451007a71

[ "Apache-2.0" ]

1

2020-07-21T22:31:15.000Z

"""The smsapi component."""

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1

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0

1

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4

fa0e00c08e64a8acecb12eeefb0327008bf3365c

27

py

Python

dmrpp_generator/version.py

ghrcdaac/dmrpp-file-generator-docker

50efe42856743bc993adfe79493b04054b1c2551

[ "Apache-2.0" ]

2

2021-09-21T19:01:38.000Z

2021-12-22T10:28:16.000Z

dmrpp_generator/version.py

ghrcdaac/dmrpp-file-generator-docker

50efe42856743bc993adfe79493b04054b1c2551

[ "Apache-2.0" ]

10

2021-01-25T14:27:10.000Z

2022-03-11T15:28:32.000Z

dmrpp_generator/version.py

ghrcdaac/dmrpp-file-generator-docker

50efe42856743bc993adfe79493b04054b1c2551

[ "Apache-2.0" ]

7

2020-08-06T22:01:46.000Z

2022-03-09T22:01:35.000Z

__version__ = "v3.2.1.beta"

27

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1

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null

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4

fa1d038787f62882acfbcfc9b5e74b78a09fe73b

139

py

Python

mnist.py

simuloid/mnist

a58245d2811addc62d141b512c7d564ec9be249a

[ "MIT" ]

null

mnist.py

simuloid/mnist

a58245d2811addc62d141b512c7d564ec9be249a

[ "MIT" ]

null

mnist.py

simuloid/mnist

a58245d2811addc62d141b512c7d564ec9be249a

[ "MIT" ]

null

import tensorflow as tf (x_train, y_train), (x_test, y_test) = tf.keras.datasets.mnist.load_data() print(x_train[-1]) print(y_train[-1])

19.857143

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139

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6

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fa2293de2c0c2f38f60af026a031cb34605d9ad0

148

py

Python

ExamProject/accounts/admin.py

BoykaTopalova/photoclub

ae11e5128515f6fd49debf20a75892fe86761c57

[ "MIT" ]

null

ExamProject/accounts/admin.py

BoykaTopalova/photoclub

ae11e5128515f6fd49debf20a75892fe86761c57

[ "MIT" ]

null

ExamProject/accounts/admin.py

BoykaTopalova/photoclub

ae11e5128515f6fd49debf20a75892fe86761c57

[ "MIT" ]

null

from django.contrib import admin # Register your models here. from ExamProject.accounts.models import UserProfile admin.site.register(UserProfile)

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148

6.526316

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fa3c91712977d961ad8edb3eab55d7e5efa68065

87

py

Python

hoodly/apps.py

AudreyCherrie/ihood

7a9de0f8d2c59c117ab6db33037e76e4425f27e9

[ "Unlicense" ]

null

hoodly/apps.py

AudreyCherrie/ihood

7a9de0f8d2c59c117ab6db33037e76e4425f27e9

[ "Unlicense" ]

3

2020-06-06T00:27:43.000Z

2021-09-08T01:36:53.000Z

hoodly/apps.py

AudreyCherrie/ihood

7a9de0f8d2c59c117ab6db33037e76e4425f27e9

[ "Unlicense" ]

null

from django.apps import AppConfig class HoodlyConfig(AppConfig): name = 'hoodly'

14.5

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6.5

0.9

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17.4

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null

0

1

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1

0

4

fa428bdb9998d8c4d5f5bc5f4441c21899a2fbcc

2,456

py

Python

active_learning_ts/evaluation/evaluator.py

hassberg/active_learning_ts

7ebdabd3349d3ac4ea2761a8aa869b8d222a2d83

[ "MIT" ]

null

active_learning_ts/evaluation/evaluator.py

hassberg/active_learning_ts

7ebdabd3349d3ac4ea2761a8aa869b8d222a2d83

[ "MIT" ]

null

active_learning_ts/evaluation/evaluator.py

hassberg/active_learning_ts

7ebdabd3349d3ac4ea2761a8aa869b8d222a2d83

[ "MIT" ]

null

from typing import List from active_learning_ts.data_blackboard import Blackboard from active_learning_ts.evaluation.evaluation_metric import EvaluationMetric from active_learning_ts.experiments.blueprint import Blueprint class Evaluator: """ Holds a list of the evaluation metrics, calls them to evaluate after every round """ def __init__(self, evaluation_metrics: List[EvaluationMetric], blackboard: Blackboard, blueprint: Blueprint): self.evaluation_metrics = evaluation_metrics for em in evaluation_metrics: em.post_init(blackboard, blueprint) def signal_learn_stop(self): for em in self.evaluation_metrics: em.signal_learn_stop() def signal_learn_start(self): for em in self.evaluation_metrics: em.signal_learn_start() def signal_round_stop(self): for em in self.evaluation_metrics: em.signal_round_stop() def signal_round_start(self): for em in self.evaluation_metrics: em.signal_round_start() def signal_query_stop(self): for em in self.evaluation_metrics: em.signal_query_stop() def signal_query_start(self): for em in self.evaluation_metrics: em.signal_query_start() def signal_evaluation_start(self): for em in self.evaluation_metrics: em.signal_evaluation_start() def signal_evaluation_stop(self): for em in self.evaluation_metrics: em.signal_evaluation_stop() def signal_knowledge_discovery_start(self): for em in self.evaluation_metrics: em.signal_knowledge_discovery_start() def signal_knowledge_discovery_stop(self): for em in self.evaluation_metrics: em.signal_knowledge_discovery_stop() def evaluate(self) -> None: """ Evaluates all evaluation metrics :return: None """ for em in self.evaluation_metrics: em.eval() def get_evaluations(self): """ returns a list of the evaluations of all evaluation metrics :return: list of the evaluations of all evaluation metrics """ out = [] f = lambda x: '[' + ', '.join([str(a) for a in x]) + ']' if isinstance(x, list) else str(x) [out.append('"' + type(x).__name__ + '" : ' + f(x.get_evaluation())) for x in self.evaluation_metrics] return '{\n' + ',\n'.join(out) + '\n}\n'

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5.035948

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null

1

0

null

0

1

0

4

fa684f7d23b046ec22712585e4b66911628f4759

2,954

py

Python

tests/test_0070-argmin-and-argmax.py

sjperkins/awkward-1.0

75dbd5d06a012ff9d1da56f898b747cea2b1d2a9

[ "BSD-3-Clause" ]

null

tests/test_0070-argmin-and-argmax.py

sjperkins/awkward-1.0

75dbd5d06a012ff9d1da56f898b747cea2b1d2a9

[ "BSD-3-Clause" ]

null

tests/test_0070-argmin-and-argmax.py

sjperkins/awkward-1.0

75dbd5d06a012ff9d1da56f898b747cea2b1d2a9

[ "BSD-3-Clause" ]

null

# BSD 3-Clause License; see https://github.com/scikit-hep/awkward-1.0/blob/master/LICENSE from __future__ import absolute_import import sys import pytest import numpy import awkward1 def test_2d(): array = awkward1.from_iter([ [3.3, 2.2, 5.5, 1.1, 4.4], [4.4, 2.2, 1.1, 3.3, 5.5], [2.2, 1.1, 4.4, 3.3, 5.5]], highlevel=False) assert awkward1.to_list(array.argmin(axis=0)) == [2, 2, 1, 0, 0] assert awkward1.to_list(array.argmin(axis=1)) == [3, 2, 1] def test_3d(): array = awkward1.from_iter([ [[ 3.3, 2.2, 5.5, 1.1, 4.4], [ 4.4, 2.2, 1.1, 3.3, 5.5], [ 2.2, 1.1, 4.4, 3.3, 5.5]], [[-3.3, 2.2, -5.5, 1.1, 4.4], [ 4.4, -2.2, 1.1, -3.3, 5.5], [ 2.2, 1.1, 4.4, 3.3, -5.5]]], highlevel=False) assert awkward1.to_list(array.argmin(axis=0)) == [ [1, 0, 1, 0, 0], [0, 1, 0, 1, 0], [0, 0, 0, 0, 1]] assert awkward1.to_list(array.argmin(axis=1)) == [ [2, 2, 1, 0, 0], [0, 1, 0, 1, 2]] assert awkward1.to_list(array.argmin(axis=2)) == [ [3, 2, 1], [2, 3, 4]] assert awkward1.to_list(array.argmin(axis=-1)) == [ [3, 2, 1], [2, 3, 4]] assert awkward1.to_list(array.argmin(axis=-2)) == [ [2, 2, 1, 0, 0], [0, 1, 0, 1, 2]] assert awkward1.to_list(array.argmin(axis=-3)) == [ [1, 0, 1, 0, 0], [0, 1, 0, 1, 0], [0, 0, 0, 0, 1]] def test_jagged(): array = awkward1.from_iter([[2.2, 1.1, 3.3], [], [4.4, 5.5], [5.5], [-4.4, -5.5, -6.6]], highlevel=False) assert awkward1.to_list(array.argmin(axis=1)) == [1, None, 0, 0, 2] index2 = awkward1.layout.Index64(numpy.array([4, 3, 2, 1, 0], dtype=numpy.int64)) array2 = awkward1.layout.IndexedArray64(index2, array) assert awkward1.to_list(array2.argmin(axis=1)) == [2, 0, 0, None, 1] index3 = awkward1.layout.Index64(numpy.array([4, 3, -1, 4, 0], dtype=numpy.int64)) array2 = awkward1.layout.IndexedArray64(index3, array) assert awkward1.to_list(array2.argmin(axis=1)) == [2, 0, None, 2, 1] assert awkward1.to_list(array2.argmin(axis=-1)) == [2, 0, None, 2, 1] def test_missing(): array = awkward1.from_iter([[[2.2, 1.1, 3.3]], [[]], [None, None, None], [[-4.4, -5.5, -6.6]]], highlevel=False) assert awkward1.to_list(array.argmin(axis=2)) == [[1], [None], [None, None, None], [2]] def test_highlevel(): array = awkward1.Array([ [3.3, 1.1, 5.5, 1.1, 4.4], [4.4, 2.2, 1.1, 6.6 ], [2.2, 3.3, -1.1 ]]) assert awkward1.argmin(array) == 11 assert awkward1.argmax(array) == 8 assert awkward1.to_list(awkward1.argmin(array, axis=0)) == [2, 0, 2, 0, 0] assert awkward1.to_list(awkward1.argmax(array, axis=0)) == [1, 2, 0, 1, 0] assert awkward1.to_list(awkward1.argmin(array, axis=1)) == [1, 2, 2] assert awkward1.to_list(awkward1.argmax(array, axis=1)) == [2, 3, 1]

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2,954

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0.103846

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0

null

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1

0

1

0

null

0

4

d713afdf80ae410170169158e20f742fce2405cf

16,800

py

Python

gedi/gpCalc.py

Python3pkg/Gedi

9b354b12120b5f8c0d9f18b1aa1f4150516c5fe0

[ "MIT" ]

null

gedi/gpCalc.py

Python3pkg/Gedi

9b354b12120b5f8c0d9f18b1aa1f4150516c5fe0

[ "MIT" ]

null

gedi/gpCalc.py

Python3pkg/Gedi

9b354b12120b5f8c0d9f18b1aa1f4150516c5fe0

[ "MIT" ]

null

#!/usr/bin/env python3 # -*- coding: utf-8 -*- import numpy as np from scipy.linalg import cho_factor, cho_solve from gedi import gpKernel def build_matrix(kern, x, yerr): """ build_matrix() creates the covariance matrix Parameters kern = kernel in use x = range of values of the independent variable (usually time) y = range of values of te dependent variable (the measurments) yerr = error in the measurments Returns K = covariance matrix """ r = x[:, None] - x[None, :] K = kern(r) K = K + yerr**2*np.identity(len(x)) return K def likelihood(kern, x, y, yerr, kepler = False, kepler_params=[]): """ likelihood() calculates the marginal log likelihood. Parameters kern = kernel in use x = range of values of the independent variable (usually time) y = range of values of te dependent variable (the measurments) yerr = error in the measurments Returns log_like = marginal log likelihood """ K = build_matrix(kern, x, yerr) L1 = cho_factor(K) sol = cho_solve(L1, y) n = y.size log_like = -0.5*np.dot(y, sol) \ - np.sum(np.log(np.diag(L1[0]))) \ - n*0.5*np.log(2*np.pi) return log_like def minus_likelihood(kernel, t, y, yerr): """ Calculates -log_likelihood() to be used in scipy.optimize """ return -likelihood(kernel, t, y, yerr) def new_kernel(original_kernel,b): """ new_kernel() updates the parameters of the kernels as the optimizations advances Parameters original_kernel = original kernel in use b = new parameters or new hyperparameters if you prefer using that denomination """ if isinstance(original_kernel,gpKernel.ExpSquared): return gpKernel.ExpSquared(b[0],b[1]) elif isinstance(original_kernel,gpKernel.ExpSineSquared): return gpKernel.ExpSineSquared(b[0],b[1],b[2]) elif isinstance(original_kernel,gpKernel.RatQuadratic): return gpKernel.RatQuadratic(b[0],b[1],b[2]) elif isinstance(original_kernel,gpKernel.Exponential): return gpKernel.Exponential(b[0],b[1]) elif isinstance(original_kernel,gpKernel.Matern32): return gpKernel.Matern32(b[0],b[1]) elif isinstance(original_kernel,gpKernel.Matern52): return gpKernel.Matern52(b[0],b[1]) elif isinstance(original_kernel,gpKernel.WhiteNoise): return gpKernel.WhiteNoise(b[0]) elif isinstance(original_kernel,gpKernel.QuasiPeriodic): return gpKernel.QuasiPeriodic(b[0],b[1],b[2],b[3]) elif isinstance(original_kernel,gpKernel.Sum): k1_params = [] for i, e in enumerate(original_kernel.k1.pars): k1_params.append(b[i]) k2_params = [] for j, e in enumerate(original_kernel.k2.pars): k2_params.append(b[len(original_kernel.k1.pars)+j]) new_k1 = new_kernel(original_kernel.k1,k1_params) new_k2 = new_kernel(original_kernel.k2,k2_params) return new_k1+new_k2 elif isinstance(original_kernel,gpKernel.Product): k1_params = [] for i, e in enumerate(original_kernel.k1.pars): k1_params.append(b[i]) k2_params = [] for j, e in enumerate(original_kernel.k2.pars): k2_params.append(b[len(original_kernel.k1.pars)+j]) new_k1 = new_kernel(original_kernel.k1,k1_params) new_k2 = new_kernel(original_kernel.k2,k2_params) return new_k1*new_k2 else: print('new_kernel: Something is missing') def gradient_likelihood(kern,x,y,yerr): """ gradient_likelihood() identifies the derivatives to use of a given kernel to calculate the gradient Parameters kern = kernel in use x = range of values of the independent variable (usually time) y = range of values of te dependent variable (the measurments) yerr = error in the measurments Returns grad1, grad2, ... = gradients of the kernel derivatives """ cov_matrix = build_matrix(kern,x,yerr) if isinstance(kern,gpKernel.ExpSquared): grad1 = grad_lp(kern.des_dtheta, x, y, yerr, cov_matrix) grad2 = grad_lp(kern.des_dl, x, y, yerr, cov_matrix) return grad1, grad2 elif isinstance(kern,gpKernel.ExpSineSquared): grad1 = grad_lp(kern.dess_dtheta,x,y,yerr,cov_matrix) grad2 = grad_lp(kern.dess_dl,x,y,yerr,cov_matrix) grad3 = grad_lp(kern.dess_dp,x,y,yerr,cov_matrix) return grad1, grad2, grad3 elif isinstance(kern,gpKernel.RatQuadratic): grad1 = grad_lp(kern.drq_dtheta,x,y,yerr,cov_matrix) grad2 = grad_lp(kern.drq_dalpha,x,y,yerr,cov_matrix) grad3 = grad_lp(kern.drq_dl,x,y,yerr,cov_matrix) return grad1, grad2, grad3 elif isinstance(kern,gpKernel.Exponential): grad1 = grad_lp(kern.dexp_dtheta,x,y,yerr,cov_matrix) grad2 = grad_lp(kern.dexp_dl,x,y,yerr,cov_matrix) return grad1, grad2 elif isinstance(kern,gpKernel.Matern32): grad1 = grad_lp(kern.dm32_dtheta,x,y,yerr,cov_matrix) grad2 = grad_lp(kern.dm32_dl,x,y,yerr,cov_matrix) return grad1, grad2 elif isinstance(kern,gpKernel.Matern52): grad1 = grad_lp(kern.dm52_dtheta,x,y,yerr,cov_matrix) grad2 = grad_lp(kern.dm52_dl,x,y,yerr,cov_matrix) return grad1, grad2 elif isinstance(kern,gpKernel.QuasiPeriodic): grad1 = grad_lp(kern.dqp_dtheta,x,y,yerr,cov_matrix) grad2 = grad_lp(kern.dqp_dl1,x,y,yerr,cov_matrix) grad3 = grad_lp(kern.dqp_dl2,x,y,yerr,cov_matrix) grad4 = grad_lp(kern.dqp_dp,x,y,yerr,cov_matrix) return grad1, grad2, grad3, grad4 elif isinstance(kern,gpKernel.WhiteNoise): grad1 = grad_lp(kern.dwn_dtheta,x,y,yerr,cov_matrix) return grad1 elif isinstance(kern,gpKernel.Sum): grad_list = grad_sum(kern,x,y,yerr) for i, e in enumerate(grad_list): if isinstance(e,float): grad_list[i] = [grad_list[i]] total = sum(grad_list, []) return total elif isinstance(kern,gpKernel.Product): return grad_mul(kern,x,y,yerr) else: print('gradient -> Something went wrong!') def grad_lp(kern,x,y,yerr,cov_matrix): """ grad_lp() makes the covariance matrix calculations of the kernel derivatives and calculates the gradient Parameters kern = kernel in use x = range of values of the independent variable (usually time) y = range of values of te dependent variable (the measurments) yerr = error in the measurments cov_matrix = kernel covariance matrix Returns See gradient_likelihood(kernel,x,y,yerr) for more info """ r = x[:, None] - x[None, :] kgrad = kern(r) kinv = np.linalg.inv(cov_matrix) alpha = np.dot(kinv,y) A = np.outer(alpha, alpha) - kinv grad = 0.5 * np.einsum('ij,ij', kgrad, A) return grad def grad_sum(kern,x,y,yerr): """ grad_sum() makes the gradient calculation for the sums of kernels Parameters kern = kernel in use x = range of values of the independent variable (usually time) y = range of values of te dependent variable (the measurments) yerr = error in the measurments Returns See grad_like_sum(kernel,x,y,yerr,original_kernel) for more info """ original_kernel = kern a = kern.__dict__ len_dict = len(kern.__dict__) grad_result = [] for i in np.arange(1,len_dict+1): var = "k{0:d}".format(i) k_i = a[var] if isinstance(k_i,gpKernel.Sum): #to solve the three sums problem calc = grad_sum_aux(k_i,x,y,yerr,original_kernel) else: calc = grad_like_sum(k_i,x,y,yerr,original_kernel) if isinstance(calc, tuple): #to solve the whitenoise problem grad_result.insert(1,calc) else: calc=tuple([calc]) grad_result.insert(1,calc) grad_final = [] for j, e in enumerate(grad_result): grad_final = grad_final + list(grad_result[j]) return grad_final #NoneType -> It might happen if there's no return in gradient_likelihood def grad_like_sum(kern,x,y,yerr,original_kernel): """ grad_like_sum() identifies the derivatives to use of a given kernel to calculate the gradient Parameters kern = kernel in use x = range of values of the independent variable (usually time) y = range of values of te dependent variable (the measurments) yerr = error in the measurments original_kernel = original kernel (original sum) being used Returns grad1, grad2, ... = gradients when using a sum operation """ cov_matrix = build_matrix(kern,x,yerr) if isinstance(kern, gpKernel.ExpSquared): grad1 = grad_lp(kern.des_dtheta, x, y, yerr, cov_matrix) grad2 = grad_lp(kern.des_dl, x, y, yerr, cov_matrix) return grad1, grad2 elif isinstance(kern, gpKernel.ExpSineSquared): grad1 = grad_lp(kern.dess_dtheta,x,y,yerr,cov_matrix) grad2 = grad_lp(kern.dess_dl,x,y,yerr,cov_matrix) grad3 = grad_lp(kern.dess_dp,x,y,yerr,cov_matrix) return grad1, grad2, grad3 elif isinstance(kern, gpKernel.RatQuadratic): grad1 = grad_lp(kern.drq_dtheta,x,y,yerr,cov_matrix) grad2 = grad_lp(kern.drq_dalpha,x,y,yerr,cov_matrix) grad3 = grad_lp(kern.drq_dl,x,y,yerr,cov_matrix) return grad1, grad2, grad3 elif isinstance(kern, gpKernel.Exponential): grad1 = grad_lp(kern.dexp_dtheta,x,y,yerr,cov_matrix) grad2 = grad_lp(kern.dexp_dl,x,y,yerr,cov_matrix) return grad1, grad2 elif isinstance(kern, gpKernel.Matern32): grad1 = grad_lp(kern.dm32_dtheta,x,y,yerr,cov_matrix) grad2 = grad_lp(kern.dm32_dl,x,y,yerr,cov_matrix) return grad1, grad2 elif isinstance(kern, gpKernel.Matern52): grad1 = grad_lp(kern.dm52_dtheta,x,y,yerr,cov_matrix) grad2 = grad_lp(kern.dm52_dl,x,y,yerr,cov_matrix) return grad1, grad2 elif isinstance(kern, gpKernel.QuasiPeriodic): grad1 = grad_lp(kern.dqp_dtheta,x,y,yerr,cov_matrix) grad2 = grad_lp(kern.dqp_dl1,x,y,yerr,cov_matrix) grad3 = grad_lp(kern.dqp_dl2,x,y,yerr,cov_matrix) grad4 = grad_lp(kern.dqp_dp,x,y,yerr,cov_matrix) return grad1, grad2, grad3, grad4 elif isinstance(kern, gpKernel.WhiteNoise): grad1 = grad_lp(kern.dwn_dtheta,x,y,yerr,cov_matrix) return grad1 elif isinstance(kern, gpKernel.Product): return grad_mul_aux(kern,x,y,yerr,original_kernel) else: print('gradient -> Something went very wrong!') def grad_sum_aux(kern,x,y,yerr,original_kernel): """ grad_sum_aux() its necesary when we are dealing with multiple sums, i.e. sum of three or more kernels Parameters kern = kernel in use x = range of values of the independent variable (usually time) y = range of values of te dependent variable (the measurments) yerr = error in the measurments original_kernel = original kernel (original sum) being used Return See grad_like_sum(kernel,x,y,yerr,original_kernel) for more info """ original_kernel = original_kernel a = kern.__dict__ len_dict = len(kern.__dict__) grad_result = [] for i in np.arange(1,len_dict+1): var = "k{0:d}".format(i) k_i = a[var] calc = grad_like_sum(k_i,x,y,yerr,original_kernel) if isinstance(calc, tuple): grad_result.insert(1,calc) else: calc=tuple([calc]) grad_result.insert(1,calc) grad_final = [] for j, e in enumerate(grad_result): grad_final = grad_final + list(grad_result[j]) return grad_final def grad_mul(kern,x,y,yerr): """ grad_mul() makes the gradient calculation of multiplications of kernels Parameters kern = kernel in use x = range of values of the independent variable (usually time) y = range of values of te dependent variable (the measurments) yerr = error in the measurments Returns grad_result = gradients when multiplications are used """ original_kernel = kern cov_matrix = build_matrix(original_kernel,x,yerr) listof_kernels = [kern.__dict__["k2"]] #to put each kernel separately kernel_k1 = kern.__dict__["k1"] while len(kernel_k1.__dict__) == 2: listof_kernels.insert(0,kernel_k1.__dict__["k2"]) kernel_k1=kernel_k1.__dict__["k1"] listof_kernels.insert(0,kernel_k1) #each kernel is now separated kernelaux1=[];kernelaux2 = [] for i, e in enumerate(listof_kernels): kernelaux1.append(listof_kernels[i]) kernelaux2.append(kernel_deriv(listof_kernels[i])) grad_result = [] kernelaux11 = kernelaux1; kernelaux22 = kernelaux2 ii = 0 while ii<len(listof_kernels): kernelaux11 = kernelaux1[:ii] + kernelaux1[ii+1 :] kernels = np.prod(np.array(kernelaux11)) for ij, e in enumerate(kernelaux22[ii]): result = grad_lp(kernelaux2[ii][ij]*kernels,x,y,yerr,cov_matrix) grad_result.insert(0,result) kernelaux11 = kernelaux1;kernelaux22=kernelaux2 ii = ii+1 grad_result = grad_result[::-1] return grad_result def kernel_deriv(kern): """ kernel_deriv() identifies the derivatives to use in a given kernel Parameters kern = kernel being use Returns ... = derivatives of a given kernel """ if isinstance(kern, gpKernel.ExpSquared): return kern.des_dtheta, kern.des_dl elif isinstance(kern, gpKernel.ExpSineSquared): return kern.dess_dtheta, kern.dess_dl, kern.dess_dp elif isinstance(kern, gpKernel.RatQuadratic): return kern.drq_dtheta, kern.drq_dl, kern.drq_dalpha elif isinstance(kern, gpKernel.Exponential): return kern.dexp_dtheta, kern.dexp_dl elif isinstance(kern, gpKernel.Matern32): return kern.dm32_dtheta, kern.dm32_dl elif isinstance(kern, gpKernel.Matern52): return kern.dm52_dtheta, kern.dm52_dl elif isinstance(kern, gpKernel.WhiteNoise): return kern.dwn_dtheta elif isinstance(kern, gpKernel.QuasiPeriodic): return kern.dqp_dtheta, kern.dqp_dl1, kern.dqp_dl2, kern.dqp_dp else: print ('Something went wrong!') def grad_mul_aux(kern,x,y,yerr,original_kernel): """ grad_mul_aux() its necesary when we are dealing with multiple terms of sums and multiplications, example: ES*ESS + ES*ESS*WN + RQ*ES*WN and not having everything breaking apart Parameters kern = kernel in use x = range of values of the independent variable (usually time) y = range of values of te dependent variable (the measurments) yerr = error in the measurments original_kernel = original kernel (original sum) being used Returns See grad_mul(kernel,x,y,yerr) for more info """ original_kernel = original_kernel cov_matrix = build_matrix(original_kernel,x,yerr) listof_kernels = [kern.__dict__["k2"]] #to put each kernel separately kernel_k1 = kern.__dict__["k1"] while len(kernel_k1.__dict__) == 2: listof_kernels.insert(0,kernel_k1.__dict__["k2"]) kernel_k1=kernel_k1.__dict__["k1"] listof_kernels.insert(0,kernel_k1) #each kernel is now separated kernelaux1 = []; kernelaux2 = [] for i, e in enumerate(listof_kernels): kernelaux1.append(listof_kernels[i]) kernelaux2.append(kernel_deriv(listof_kernels[i])) grad_result = [] kernelaux11 = kernelaux1; kernelaux22 = kernelaux2 ii = 0 while ii<len(listof_kernels): kernelaux11 = kernelaux1[:ii] + kernelaux1[ii+1 :] kernels = np.prod(np.array(kernelaux11)) for ij, e in enumerate(kernelaux22[ii]): result = grad_lp(kernelaux2[ii][ij]*kernels,x,y,yerr,cov_matrix) grad_result.insert(0,result) kernelaux11 = kernelaux1;kernelaux22=kernelaux2 ii = ii+1 grad_result = grad_result[::-1] return grad_result ##### END

34.567901

83

0.639524

2,288

16,800

4.52229

0.098776

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0.033633

0.035663

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0.70059

0.687252

0.678168

0.648014

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0.023342

0.263036

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1

0

1

0

null

0

4

d72919f83c13d7022dbde10738af24f7969fc8ad

493

py

Python

scripts/window_switcher/settings.py

tm8r/MayaWindowSwitcher

8905535ee8a31bf4dcb77820c7525e368b7acd82

[ "MIT" ]

17

2020-01-24T01:43:11.000Z

2021-06-18T10:09:23.000Z

scripts/window_switcher/settings.py

tm8r/MayaWindowSwitcher

8905535ee8a31bf4dcb77820c7525e368b7acd82

[ "MIT" ]

3

2020-01-23T13:03:25.000Z

2020-02-28T03:11:18.000Z

scripts/window_switcher/settings.py

tm8r/MayaWindowSwitcher

8905535ee8a31bf4dcb77820c7525e368b7acd82

[ "MIT" ]

2

2020-09-16T14:27:27.000Z

2021-01-01T20:08:09.000Z

# -*- coding: utf-8 -*- from __future__ import absolute_import, division, print_function from maya import cmds _SIMPLE_MODE_KEY = "window_switcher_simple_mode" _SIMPLE_MODE_ENABLED = 1 _SIMPLE_MODE_DISABLED = 0 def is_simple_mode(): return cmds.optionVar(q=_SIMPLE_MODE_KEY) == _SIMPLE_MODE_ENABLED def enable_simple_mode(): cmds.optionVar(iv=(_SIMPLE_MODE_KEY, _SIMPLE_MODE_ENABLED)) def disable_simple_mode(): cmds.optionVar(iv=(_SIMPLE_MODE_KEY, _SIMPLE_MODE_DISABLED))

23.47619

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false

0

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0

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d7344736b05c28871a5e20e7907d7b613d65f7aa

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py

Python

git_profile/admin.py

dhavalsavalia/github-user-finder

a3c2c441a183e05f5c0f08e47e646221207c1c17

[ "MIT" ]

null

git_profile/admin.py

dhavalsavalia/github-user-finder

a3c2c441a183e05f5c0f08e47e646221207c1c17

[ "MIT" ]

1

2017-09-18T21:53:20.000Z

2017-09-21T11:27:02.000Z

git_profile/admin.py

dhavalsavalia/github-user-finder

a3c2c441a183e05f5c0f08e47e646221207c1c17

[ "MIT" ]

null

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

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d76fbc90fefd487e28f8451b449e51e61316bf95

86

py

Python

coding/learn_celery/tasks.py

yatao91/learning_road

e88dc43de98e35922bfc71c222ec71766851e618

[ "MIT" ]

3

2021-05-25T16:58:52.000Z

2022-02-05T09:37:17.000Z

coding/learn_celery/tasks.py

yataosu/learning_road

e88dc43de98e35922bfc71c222ec71766851e618

[ "MIT" ]

null

coding/learn_celery/tasks.py

yataosu/learning_road

e88dc43de98e35922bfc71c222ec71766851e618

[ "MIT" ]

null

# -*- coding: utf-8 -*- from . import app @app.task def add(x, y): return x + y

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d7796961a14d488fc9948036a5c5c1cb7d8a4510

174

py

Python

backend/dhh_auth/api/__init__.py

urshala/DataHubHel

28737b6294fcb232dd92c25e31e4364e0a1bb149

[ "MIT" ]

4

2019-09-04T12:23:50.000Z

2020-02-06T05:42:43.000Z

backend/dhh_auth/api/__init__.py

urshala/DataHubHel

28737b6294fcb232dd92c25e31e4364e0a1bb149

[ "MIT" ]

15

2017-12-07T10:59:59.000Z

2022-03-08T22:50:02.000Z

backend/dhh_auth/api/__init__.py

urshala/DataHubHel

28737b6294fcb232dd92c25e31e4364e0a1bb149

[ "MIT" ]

5

2017-10-30T12:02:57.000Z

2019-09-25T10:41:37.000Z

from ._tokens import TokenViewSet from ._users import ForgetView, MeView, RegisterView __all__ = [ 'ForgetView', 'MeView', 'RegisterView', 'TokenViewSet', ]

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ad1059947db96405f9e22fdedcafebf7ec09f080

185

py

Python

tests/molecular/molecules/utilities/molecule.py

stevenbennett96/stk

6e5af87625b83e0bfc7243bc42d8c7a860cbeb76

[ "MIT" ]

21

2018-04-12T16:25:24.000Z

2022-02-14T23:05:43.000Z

tests/molecular/molecules/utilities/molecule.py

stevenbennett96/stk

6e5af87625b83e0bfc7243bc42d8c7a860cbeb76

[ "MIT" ]

8

2019-03-19T12:36:36.000Z

2020-11-11T12:46:00.000Z

tests/molecular/molecules/utilities/molecule.py

stevenbennett96/stk

6e5af87625b83e0bfc7243bc42d8c7a860cbeb76

[ "MIT" ]

5

2018-08-07T13:00:16.000Z

2021-11-01T00:55:10.000Z

from tests.utilities import is_equivalent_molecule def is_clone_molecule(molecule1, molecule2): assert molecule1 is not molecule2 is_equivalent_molecule(molecule1, molecule2)

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ad20c524a8198522b8ee05e375c74309b74daba9

155

py

Python

Scripts/django-admin.py

emmanuelrutto06/cfehome

6963f742bb6b615cb1781a3b1b5d9c5ee3bae45f

[ "bzip2-1.0.6" ]

null

Scripts/django-admin.py

emmanuelrutto06/cfehome

6963f742bb6b615cb1781a3b1b5d9c5ee3bae45f

[ "bzip2-1.0.6" ]

null

Scripts/django-admin.py

emmanuelrutto06/cfehome

6963f742bb6b615cb1781a3b1b5d9c5ee3bae45f

[ "bzip2-1.0.6" ]

null

#!c:\users\rutto\dev\cfehome\scripts\python.exe from django.core import management if __name__ == "__main__": management.execute_from_command_line()

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ad39dc68d844885f5261a02127f9e3d5aaf96f6a

255

py

Python

src/torch_kitti/__init__.py

andreaconti/torch_k

a5bf09b22d3bef9092d7313dda529af83da15dc6

[ "MIT" ]

6

2021-06-26T18:19:50.000Z

2022-02-04T14:16:56.000Z

src/torch_kitti/__init__.py

andreaconti/torch_k

a5bf09b22d3bef9092d7313dda529af83da15dc6

[ "MIT" ]

3

2020-11-19T14:41:53.000Z

2020-11-20T12:26:02.000Z

src/torch_kitti/__init__.py

andreaconti/torch_kitti

a5bf09b22d3bef9092d7313dda529af83da15dc6

[ "MIT" ]

null

""" Utilities to handle the KITTI Vision Benchmark Suite in PyTorch """ __version__ = "0.2.4" __all__ = ["raw", "depth_completion", "depth_prediction", "transforms", "metrics"] from . import depth_completion, depth_prediction, metrics, raw, transforms

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ad5aaab05161d54e4173d89e39b7f63556f1c43a

33

py

Python

custom_components/slack_state/__init__.py

rdrongow/hass-slack-state

284ac7f1af1d501792baa24fdf3befddded4728b

[ "BSD-3-Clause" ]

1

2018-03-12T03:33:52.000Z

custom_components/slack_state/__init__.py

rdrongow/hass-slack-state

284ac7f1af1d501792baa24fdf3befddded4728b

[ "BSD-3-Clause" ]

null

custom_components/slack_state/__init__.py

rdrongow/hass-slack-state

284ac7f1af1d501792baa24fdf3befddded4728b

[ "BSD-3-Clause" ]

null

"""The slack state component."""

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true

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null

0

1

0

null

0

1

0

4

ad71f5f0c35080acdba882675f3a452b2ae1512d

4,017

py

Python

boto3_type_annotations/boto3_type_annotations/workmail/client.py

cowboygneox/boto3_type_annotations

450dce1de4e066b939de7eac2ec560ed1a7ddaa2

[ "MIT" ]

119

2018-12-01T18:20:57.000Z

2022-02-02T10:31:29.000Z

boto3_type_annotations/boto3_type_annotations/workmail/client.py

cowboygneox/boto3_type_annotations

450dce1de4e066b939de7eac2ec560ed1a7ddaa2

[ "MIT" ]

15

2018-11-16T00:16:44.000Z

2021-11-13T03:44:18.000Z

boto3_type_annotations/boto3_type_annotations/workmail/client.py

cowboygneox/boto3_type_annotations

450dce1de4e066b939de7eac2ec560ed1a7ddaa2

[ "MIT" ]

11

2019-05-06T05:26:51.000Z

2021-09-28T15:27:59.000Z

from typing import Optional from botocore.client import BaseClient from typing import Dict from typing import Union from botocore.paginate import Paginator from botocore.waiter import Waiter from typing import List class Client(BaseClient): def associate_delegate_to_resource(self, OrganizationId: str, ResourceId: str, EntityId: str) -> Dict: pass def associate_member_to_group(self, OrganizationId: str, GroupId: str, MemberId: str) -> Dict: pass def can_paginate(self, operation_name: str = None): pass def create_alias(self, OrganizationId: str, EntityId: str, Alias: str) -> Dict: pass def create_group(self, OrganizationId: str, Name: str) -> Dict: pass def create_resource(self, OrganizationId: str, Name: str, Type: str) -> Dict: pass def create_user(self, OrganizationId: str, Name: str, DisplayName: str, Password: str) -> Dict: pass def delete_alias(self, OrganizationId: str, EntityId: str, Alias: str) -> Dict: pass def delete_group(self, OrganizationId: str, GroupId: str) -> Dict: pass def delete_mailbox_permissions(self, OrganizationId: str, EntityId: str, GranteeId: str) -> Dict: pass def delete_resource(self, OrganizationId: str, ResourceId: str) -> Dict: pass def delete_user(self, OrganizationId: str, UserId: str) -> Dict: pass def deregister_from_work_mail(self, OrganizationId: str, EntityId: str) -> Dict: pass def describe_group(self, OrganizationId: str, GroupId: str) -> Dict: pass def describe_organization(self, OrganizationId: str) -> Dict: pass def describe_resource(self, OrganizationId: str, ResourceId: str) -> Dict: pass def describe_user(self, OrganizationId: str, UserId: str) -> Dict: pass def disassociate_delegate_from_resource(self, OrganizationId: str, ResourceId: str, EntityId: str) -> Dict: pass def disassociate_member_from_group(self, OrganizationId: str, GroupId: str, MemberId: str) -> Dict: pass def generate_presigned_url(self, ClientMethod: str = None, Params: Dict = None, ExpiresIn: int = None, HttpMethod: str = None): pass def get_paginator(self, operation_name: str = None) -> Paginator: pass def get_waiter(self, waiter_name: str = None) -> Waiter: pass def list_aliases(self, OrganizationId: str, EntityId: str, NextToken: str = None, MaxResults: int = None) -> Dict: pass def list_group_members(self, OrganizationId: str, GroupId: str, NextToken: str = None, MaxResults: int = None) -> Dict: pass def list_groups(self, OrganizationId: str, NextToken: str = None, MaxResults: int = None) -> Dict: pass def list_mailbox_permissions(self, OrganizationId: str, EntityId: str, NextToken: str = None, MaxResults: int = None) -> Dict: pass def list_organizations(self, NextToken: str = None, MaxResults: int = None) -> Dict: pass def list_resource_delegates(self, OrganizationId: str, ResourceId: str, NextToken: str = None, MaxResults: int = None) -> Dict: pass def list_resources(self, OrganizationId: str, NextToken: str = None, MaxResults: int = None) -> Dict: pass def list_users(self, OrganizationId: str, NextToken: str = None, MaxResults: int = None) -> Dict: pass def put_mailbox_permissions(self, OrganizationId: str, EntityId: str, GranteeId: str, PermissionValues: List) -> Dict: pass def register_to_work_mail(self, OrganizationId: str, EntityId: str, Email: str) -> Dict: pass def reset_password(self, OrganizationId: str, UserId: str, Password: str) -> Dict: pass def update_primary_email_address(self, OrganizationId: str, EntityId: str, Email: str) -> Dict: pass def update_resource(self, OrganizationId: str, ResourceId: str, Name: str = None, BookingOptions: Dict = None) -> Dict: pass

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ad7df4e0ebcace66f6ad436b9e3d7b6277b4f5c3

38

py

Python

foiamachine/local/lib/python2.7/encodings/koi8_u.py

dwillis/foiamachine

26d3b02870227696cdaab639c39d47b2a7a42ae5

[ "Unlicense", "MIT" ]

3

2021-08-07T04:01:55.000Z

2021-08-07T05:12:11.000Z

foiamachine/local/lib/python2.7/encodings/koi8_u.py

dwillis/foiamachine

26d3b02870227696cdaab639c39d47b2a7a42ae5

[ "Unlicense", "MIT" ]

null

foiamachine/local/lib/python2.7/encodings/koi8_u.py

dwillis/foiamachine

26d3b02870227696cdaab639c39d47b2a7a42ae5

[ "Unlicense", "MIT" ]

1

2021-08-05T22:51:14.000Z

/usr/lib/python2.7/encodings/koi8_u.py

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null

0

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4

ad8e9fee89bd3c3f6edb6cfb89263d5127c3c72b

203

py

Python

tests/conftest.py

aalto-speech/aalto-asr-preprocessor

792a618aeca940274a21d0698ee741277d8d8fc5

[ "MIT" ]

null

tests/conftest.py

aalto-speech/aalto-asr-preprocessor

792a618aeca940274a21d0698ee741277d8d8fc5

[ "MIT" ]

18

2021-06-07T14:12:13.000Z

2022-02-02T13:58:27.000Z

tests/conftest.py

aalto-speech/aalto-asr-preprocessor

792a618aeca940274a21d0698ee741277d8d8fc5

[ "MIT" ]

null

"""Configuration file for pytest. Load long test strings from separate files in the `data/` directory. """ from typing import List pytest_plugins: List[str] = ["tests.fi.data.parl_long_test_strings"]

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0

4

ad8ec39f569905492139f8d5417522fc34fe92e7

548

py

Python

tests/di/declarative/mod_plugins.py

dlski/python-di

04dcdf58f3cf820e2d2ba5086e4e89822ae1f409

[ "MIT" ]

8

2021-02-05T16:17:31.000Z

2022-03-03T00:01:33.000Z

tests/di/declarative/mod_plugins.py

dlski/python-di

04dcdf58f3cf820e2d2ba5086e4e89822ae1f409

[ "MIT" ]

null

tests/di/declarative/mod_plugins.py

dlski/python-di

04dcdf58f3cf820e2d2ba5086e4e89822ae1f409

[ "MIT" ]

null

""" Module containing implementations of concrete data providers """ from typing import Collection from tests.di.declarative.mod_abstract import DataProvider class LetterDataProvider(DataProvider): """ Concrete data provider returning collection containing "A" and "B" """ def all(self) -> Collection[str]: return list("AB") class NumberDataProvider(DataProvider): """ Concrete data provider returning collection containing "1" and "2" """ def all(self) -> Collection[str]: return list("12")

21.076923

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null

0

1

0

1

0

4

ad92ecf6ed3ad559952e31dbd985f9a72958c169

122

py

Python

dogowner/admin.py

ErezCohenn/Beyond-07-team-1

37eed5bf1b0902b21f7c824acfd25634c40270db

[ "MIT" ]

1

2022-03-03T12:03:17.000Z

dogowner/admin.py

ErezCohenn/Beyond-07-team-1

37eed5bf1b0902b21f7c824acfd25634c40270db

[ "MIT" ]

38

2022-03-07T14:14:48.000Z

2022-03-31T18:37:52.000Z

dogowner/admin.py

ErezCohenn/Beyond-07-team-1

37eed5bf1b0902b21f7c824acfd25634c40270db

[ "MIT" ]

5

2022-02-28T18:55:09.000Z

2022-03-06T08:04:40.000Z

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

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a8f6bd595c0c07172ee947aad977e8ee31c2a0eb

84

py

Python

examples/ch02/assign.py

zarcode/book-real-world-haskell

a824fcdf5de4fca49043fd45c8d889681c0173d6

[ "BSD-2-Clause" ]

40

2017-06-03T08:48:32.000Z

2021-11-24T16:28:07.000Z

examples/ch02/assign.py

zarcode/book-real-world-haskell

a824fcdf5de4fca49043fd45c8d889681c0173d6

[ "BSD-2-Clause" ]

3

2017-02-14T06:25:36.000Z

2017-09-04T01:39:38.000Z

examples/ch02/assign.py

zarcode/book-real-world-haskell

a824fcdf5de4fca49043fd45c8d889681c0173d6

[ "BSD-2-Clause" ]

31

2017-02-14T00:59:54.000Z

2021-07-25T13:04:29.000Z

## snippet assign x = 10 x = 11 # value of x is now 11 print x ## /snippet assign

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null

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1

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4

a8f803df9fa3b710ce5aca8900ba34274f884860

249

py

Python

vjudge_interface/requests/get_problem_data.py

Quinas/vjudge-interface

3302ae084f7781bc465443c9fd957065bce67fc0

[ "MIT" ]

null

vjudge_interface/requests/get_problem_data.py

Quinas/vjudge-interface

3302ae084f7781bc465443c9fd957065bce67fc0

[ "MIT" ]

3

2021-03-31T19:28:18.000Z

2021-12-13T20:24:37.000Z

vjudge_interface/requests/get_problem_data.py

Quinas/vjudge_interface

3302ae084f7781bc465443c9fd957065bce67fc0

[ "MIT" ]

null

from .request import Request class GetProblemData(Request): def __init__(self, problem_id: int): super().__init__() self.problem_id = problem_id self.path = "problem/{}".format(problem_id) self.method = "get"

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0

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null

1

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null

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4

d107c3b9aae27d689ca4db30ac720b1d98723bd7

63

py

Python

tutorials/config/paths.py

MJC598/SystemID

64365555a42e669529df2ac17d06c3b7ce25782d

[ "MIT" ]

null

tutorials/config/paths.py

MJC598/SystemID

64365555a42e669529df2ac17d06c3b7ce25782d

[ "MIT" ]

null

tutorials/config/paths.py

MJC598/SystemID

64365555a42e669529df2ac17d06c3b7ce25782d

[ "MIT" ]

null

""" Paths that affect the entire project are contained here """

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0

4

d137aaedfd3b1fddf405eff43424b83083d9cae3

62

py

Python

pyffect/_types.py

aknay/pyffect

9be1102b114e7665ae46d732636bd1614dec1de8

[ "MIT" ]

null

pyffect/_types.py

aknay/pyffect

9be1102b114e7665ae46d732636bd1614dec1de8

[ "MIT" ]

null

pyffect/_types.py

aknay/pyffect

9be1102b114e7665ae46d732636bd1614dec1de8

[ "MIT" ]

null

from typing import TypeVar T = TypeVar('T') E = TypeVar('E')

12.4

26

0.66129

10

62

4.1

0.6

0.390244

0

0.177419

62

4

27

15.5

0.803922

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0.032258

0

1

0

false

0

0.333333

0

0.333333

0

1

0

null

1

0

1

0

null

0

1

0

4

d13a6f4d82e2fa5865dcb6144dd13dfe0de0e210

118

py

Python

rested/__init__.py

hmarment/rested

526c2c8ab1e0cb51389af12afdcb27bf8ef92b45

[ "MIT" ]

null

rested/__init__.py

hmarment/rested

526c2c8ab1e0cb51389af12afdcb27bf8ef92b45

[ "MIT" ]

null

rested/__init__.py

hmarment/rested

526c2c8ab1e0cb51389af12afdcb27bf8ef92b45

[ "MIT" ]

null

__version__ = '0.0.1' from .integration import Integration from .resource import Resource from .client import Rested

19.666667

36

0.79661

16

118

5.625

0.5625

0

0.029412

0.135593

118

5

37

23.6

0.852941

0

0.042373

0

1

0

false

0

0.75

0

0.75

0

1

0

null

0

1

0

null

0

1

0

1

0

4

d15b34f606f70d14988a2f6da96f9e4fa5afcfe7

173

py

Python

python_django/sdk_lpl/models/VerificationModel.py

NextINpact/LaPresseLibreSDK

8908a96e9aad18734464bf0742be9be6c0367e93

[ "MIT" ]

34

2016-05-09T09:20:32.000Z

2021-05-28T07:25:08.000Z

python_django/sdk_lpl/models/VerificationModel.py

NextINpact/LaPresseLibreSDK

8908a96e9aad18734464bf0742be9be6c0367e93

[ "MIT" ]

10

2016-05-06T09:48:32.000Z

2021-06-25T20:01:25.000Z

python_django/sdk_lpl/models/VerificationModel.py

NextINpact/LaPresseLibreSDK

8908a96e9aad18734464bf0742be9be6c0367e93

[ "MIT" ]

7

2016-07-05T15:57:32.000Z

2018-11-05T21:04:58.000Z

class VerificationModel(object): def __init__(self, password, mail, code): self.Password = password self.Mail = mail self.CodeUtilisateur = code

28.833333

45

0.65896

18

173

6.111111

0.555556

0.218182

0

0.254335

173

5

46

34.6

0.852713

0

1

0.2

false

0.4

0

0.4

0

1

0

null

1

0

1

0

null

0

1

0

4

d174e6c8da258c9425f4654a100a4cbf60b382ef

383

py

Python

pipocoin/services/pipocoin_messages/stats.py

bondiolipietro/pipocoin-python

e4abc019c2eb704d70899a2e441ee4be23aaeb4c

[ "MIT" ]

1

2021-08-05T23:18:35.000Z

pipocoin/services/pipocoin_messages/stats.py

bondiolipietro/pipocoin-twitter-bot-python

e4abc019c2eb704d70899a2e441ee4be23aaeb4c

[ "MIT" ]

null

pipocoin/services/pipocoin_messages/stats.py

bondiolipietro/pipocoin-twitter-bot-python

e4abc019c2eb704d70899a2e441ee4be23aaeb4c

[ "MIT" ]

null

def success_get_stats(user): return f"✅ Successfully get stats.\n\n👤 Id: {user.get_id()}\n" \ + f"🤡 Username: {user.get_name()}\n🪙 Balance: {user.get_balance()}" def fail_error_occurred(): return "❌ An error occurred while trying to get your stats." def fail_not_registered_user(): return "❌ You aren't registered. Please create an account to use $pipo bot."

31.916667

80

0.684073

65

383

3.969231

0.569231

0.081395

0

0.177546

383

11

81

34.818182

0.8

0

0.605744

0

1

0.428571

false

0

0.428571

0.857143

0

null

0

1

0

null

0

1

0

1

0

4

0f09c0448c3209c05dd50efd35574db1bfa4a53e

134

py

Python

Functions/function_demo.py

manish1822510059/Python-1000-program

d03c1920fe63a7e32ac5bd9a13e2766d7a25756c

[ "Apache-2.0" ]

1

2021-03-06T03:33:42.000Z

Functions/function_demo.py

manish1822510059/Python-1000-programs

d03c1920fe63a7e32ac5bd9a13e2766d7a25756c

[ "Apache-2.0" ]

null

Functions/function_demo.py

manish1822510059/Python-1000-programs

d03c1920fe63a7e32ac5bd9a13e2766d7a25756c

[ "Apache-2.0" ]

null

def square(n): print("Square of ",n,"is",(n*n)) def cude(n): print("Cube of ",n,"is",(n*n*n)) cude(3) square(4)

19.142857

41

0.485075

25

134

2.6

0.4

0.092308

0.153846

0.184615

0.215385

0

0.02

0.253731

134

7

42

19.142857

0.63

0

0.170543

0

1

0.333333

false

0

0.333333

1

0

null

0

1

0

1

0

null

0

1

0

4

0f0eda29712455856af5e44d9840d9208f88ca82

206

py

Python

dodecahedron/tests/test_app.py

msarfati/dodecahedron

bf4216fc914db909986dbe4dd0c5919ba051bd40

[ "MIT" ]

2

2016-03-01T11:01:25.000Z

2016-03-03T01:10:27.000Z

dodecahedron/tests/test_app.py

msarfati/dodecahedron

bf4216fc914db909986dbe4dd0c5919ba051bd40

[ "MIT" ]

null

dodecahedron/tests/test_app.py

msarfati/dodecahedron

bf4216fc914db909986dbe4dd0c5919ba051bd40

[ "MIT" ]

null

from ..mixins.test import TestCaseMixin from nose.plugins.attrib import attr class DodecahedronTestCase(TestCaseMixin): # @attr('single') def test_testing(self): self.assertEqual(2, 1+1)

20.6

42

0.723301

25

206

5.92

0.72

0

0.017544

0.169903

206

9

43

22.888889

0.847953

0.072816

0

0.2

1

0.2

false

0

0.4

0

0.8

0

1

0

null

0

1

0

null

0

1

0

1

0

4

0f459bf992bc98cbcd462d25c94ca876103a59dd

30

py

Python

oldstuff/tutorial2/tutorial2/lib/python3.8/tokenize.py

miusuarioamigo/python-Le

dbb653255dab7d11b87f25eec94bcce63a86aa42

[ "MIT" ]

6

2020-08-04T13:12:42.000Z

2020-08-16T13:26:19.000Z

oldstuff/tutorial2/tutorial2/lib/python3.8/tokenize.py

miusuarioamigo/python-Le

dbb653255dab7d11b87f25eec94bcce63a86aa42

[ "MIT" ]

19

2020-02-03T10:46:48.000Z

2022-01-13T03:06:15.000Z

oldstuff/tutorial2/tutorial2/lib/python3.8/tokenize.py

miusuarioamigo/python-Le

dbb653255dab7d11b87f25eec94bcce63a86aa42

[ "MIT" ]

6

2021-04-02T11:36:48.000Z

2022-03-22T09:39:34.000Z

/usr/lib/python3.8/tokenize.py

30

0.8

6

30

4

1

0

0.066667

0

30

1

30

0.733333

0

null

0

null

0

1

0

null

0

1

0

null

0

1

0

4

0f4fb3ab6f046dbc34a96cb4830bea6e4660fab7

151

py

Python

transformation/transformation.py

dpazel/music_rep

2f9de9b98b13df98f1a0a2120b84714725ce527e

[ "MIT" ]

1

2021-05-06T19:45:54.000Z

transformation/transformation.py

dpazel/music_rep

2f9de9b98b13df98f1a0a2120b84714725ce527e

[ "MIT" ]

null

transformation/transformation.py

dpazel/music_rep

2f9de9b98b13df98f1a0a2120b84714725ce527e

[ "MIT" ]

null

""" File: transformation.py Purpose: Base class for tranformation classes. """ class Transformation(object): def __init__(self): pass

11.615385

46

0.682119

16

151

6.1875

0.875

0

0.211921

151

12

47

12.583333

0.831933

0.470199

0

1

0.333333

false

0.333333

0

0.666667

0

1

0

null

0

null

0

1

0

1

0

1

0

4

0f5c5533ab0bdcea3024107d83fa32ca7c1416ab

43

py

Python

arc111.py

hythof/atc

12cb94ebe693e1f469ce0d982bc2924b586552cd

[ "CC0-1.0" ]

null

arc111.py

hythof/atc

12cb94ebe693e1f469ce0d982bc2924b586552cd

[ "CC0-1.0" ]

null

arc111.py

hythof/atc

12cb94ebe693e1f469ce0d982bc2924b586552cd

[ "CC0-1.0" ]

null

N,*A = [x for x in open(0).read().split()]

21.5

42

0.534884

10

43

2.3

0.9

0

0.027778

0.162791

43

1

43

0.611111

0

1

0

true

0

1

0

null

0

1

0

null

0

1

0

4

0f7217bf6339af329939054ec9b25225530145a9

173

py

Python

29_count_the_number.py

rahulbohra/Python-Basic

7dfadde341e9d02fdcb37f70cce10e8b689f36c9

[ "MIT" ]

null

29_count_the_number.py

rahulbohra/Python-Basic

7dfadde341e9d02fdcb37f70cce10e8b689f36c9

[ "MIT" ]

null

29_count_the_number.py

rahulbohra/Python-Basic

7dfadde341e9d02fdcb37f70cce10e8b689f36c9

[ "MIT" ]

null

count = 0; print 'Before Loop starts : ', count for numbers in [2.6,56,12,7,8,49,36,123]: count = count + 1 print count, numbers print 'After Loop starts : ', count

24.714286

41

0.647399

30

173

3.733333

0.666667

0.178571

0.267857

0

0.125

0.213873

173

6

42

28.833333

0.698529

0

0.236994

0

null

0

null

0.5

0

null

0

1

0

1

0

null

0

1

0

1

0

4

0f908c007ffb48075363a75c570203a0fc89be7b

920

py

Python

Python_FileIO/Models/Os_Detail.py

JE-Chen/je_old_repo

a8b2f1ac2eec25758bd15b71c64b59b27e0bcda5

[ "MIT" ]

null

Python_FileIO/Models/Os_Detail.py

JE-Chen/je_old_repo

a8b2f1ac2eec25758bd15b71c64b59b27e0bcda5

[ "MIT" ]

null

Python_FileIO/Models/Os_Detail.py

JE-Chen/je_old_repo

a8b2f1ac2eec25758bd15b71c64b59b27e0bcda5

[ "MIT" ]

null

import platform import os class Os_Detail(): def __init__(self): pass def Os_Name(self): return os.name def Os_System(self): return platform.system() def Os_Machine(self): return platform.machine() def Os_Platform(self): return platform.platform() def Os_Uname(self): return platform.uname() def Os_Version(self): return platform.version() def Os_MacVer(self): return platform.mac_ver() def Os_All_Detial(self): print(f"system: {platform.system()}", f"machine: {platform.machine()}", f"platform: {platform.platform()}", f"uname: {platform.uname()}", f"version: {platform.version()}", f"mac_ver: {platform.mac_ver()}",sep='\n') def Python_Ver(self): return platform.python_version()

23.589744

57

0.556522

103

920

4.786408

0.242718

0.081136

0.255578

0

0.318478

920

39

58

23.589744

0.786284

0

0.19479

0.023783

0

1

0.357143

false

0.035714

0.071429

0.285714

0.75

0.035714

0

null

0

1

0

null

0

1

0

1

0

4

7e58062e8849a71b7d0a7c44c72b213b8026a754

268

py

Python

segment.py

archity/image-manipulation

8d16150adaecb22cafeb94318b2482d73a5ef121

[ "MIT" ]

null

segment.py

archity/image-manipulation

8d16150adaecb22cafeb94318b2482d73a5ef121

[ "MIT" ]

null

segment.py

archity/image-manipulation

8d16150adaecb22cafeb94318b2482d73a5ef121

[ "MIT" ]

null

import pixellib from pixellib.instance import instance_segmentation segment_image = instance_segmentation() segment_image.load_model("mask_rcnn_coco.h5") segment_image.segmentImage("IMG_20180724_151202.jpg", show_bboxes=True, output_image_name="image_new.jpg")

38.285714

107

0.839552

36

268

5.861111

0.666667

0.170616

0.255924

0.303318

0

0.060484

0.074627

268

6

108

44.666667

0.790323

0

0.20229

0.087786

0

1

0

false

0

0.4

0

0.4

0

null

0

1

0

1

0

null

0

1

0

4

7e80fb70ba87783a77944dcaca2ce17baf5bdcb9

235

py

Python

app/user_management/__init__.py

tranaj2/Crockpot

435a3c89fffeb94dbab24845fac11a75c795444a

[ "MIT" ]

null

app/user_management/__init__.py

tranaj2/Crockpot

435a3c89fffeb94dbab24845fac11a75c795444a

[ "MIT" ]

5

2018-02-21T03:40:48.000Z

2018-04-17T06:38:48.000Z

app/user_management/__init__.py

tranaj2/CrockPot

435a3c89fffeb94dbab24845fac11a75c795444a

[ "MIT" ]

null

""" User Management module provides endpoints for the managing a User """ from flask import Blueprint user_mgmt = Blueprint('user_mgmt', __name__) # pylint: disable=C0103 from app.user_management import views #pylint: disable=C0413

29.375

73

0.782979

32

235

5.53125

0.65625

0.158192

0.19209

0

0.039409

0.13617

235

7

74

33.571429

0.832512

0.468085

0

0.076923

0

1

0

false

0

0.666667

0

0.666667

0

null

0

1

0

1

0

null

0

1

0

1

0

4

7e97c83beb7895da9655aa046369c3d6cc22df94

123

py

Python

opalescence/ui/__init__.py

killerbat00/opalescense

f5ba7ae8420672f7834b7db6f938e9366db4b895

[ "MIT" ]

3

2017-05-02T10:01:37.000Z

2021-09-01T14:12:45.000Z

opalescence/ui/__init__.py

killerbat00/opalescense

f5ba7ae8420672f7834b7db6f938e9366db4b895

[ "MIT" ]

4

2017-05-03T16:33:41.000Z

2021-03-30T04:32:10.000Z

opalescence/ui/__init__.py

killerbat00/opalescense

f5ba7ae8420672f7834b7db6f938e9366db4b895

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ The UI for opalescence is implemented in this package. Currently, only a cli is provided. """

17.571429

54

0.666667

18

123

4.555556

0.944444

0

0.01

0.186992

123

6

55

20.5

0.81

0.910569

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

1

0

null

0

1

0

4

7e9b9ff14d239daad89050be3bd0ee8a8b76b147

3,241

py

Python

tests/test_executor_execute_method.py

leonidasnascimento/sosi_crawler_executor

51d4d7e7533d0a473f061583b2c0266b0eca9011

[ "Apache-2.0" ]

null

tests/test_executor_execute_method.py

leonidasnascimento/sosi_crawler_executor

51d4d7e7533d0a473f061583b2c0266b0eca9011

[ "Apache-2.0" ]

null

tests/test_executor_execute_method.py

leonidasnascimento/sosi_crawler_executor

51d4d7e7533d0a473f061583b2c0266b0eca9011

[ "Apache-2.0" ]

null

import unittest from sosi_crawler_executor.crawler import Executor class test_executor_execute_method(unittest.TestCase): """ Test class responsible to perform tests routines against "execute" method """ def test_should_raise_exception_for_missing_dependencies(self): """ Should raise an exception for missing dependencies """ try: Executor('tests/dependecies_missing.json', 'tests/executor_config.json').execute() pass except Exception as ex: self.assertTrue(str(ex).__contains__('is required. This crawler cannot run')) pass pass pass def test_should_raise_exception_for_missing_msg_queue_target_error_topic(self): """ Should raise exception given a missing "Error Topic" parameter (empty or none) """ try: Executor('tests/dependecies_configuration_missing_param.json', 'msg_queue_target_error_topic').execute() pass except Exception as ex: self.assertTrue(str(ex).__eq__('The param "msg_queue_target_error_topic" must be provided')) pass pass pass def test_should_raise_exception_for_missing_msg_queue_target_topic(self): """ Should raise exception given a missing "Target Topic" parameter (empty or none) """ try: Executor('tests/dependecies_configuration_missing_param.json', 'msg_queue_target_topic').execute() pass except Exception as ex: self.assertTrue(str(ex).__eq__('The param "msg_queue_target_topic" must be provided')) pass pass pass def test_should_raise_exception_for_missing_crawling_args(self): """ Should raise exception given a missing "Crawling Args" parameter (empty or none) """ try: Executor('tests/dependecies_configuration_missing_param.json', 'crawling_args').execute() pass except Exception as ex: self.assertTrue(str(ex).__eq__('The param "crawler_args" must be provided')) pass pass pass def test_should_raise_exception_for_none_crawler_result_obj(self): """ """ try: Executor('tests/dependecies_none_crawler_result_obj.json', 'tests/executor_config.json').execute() pass except Exception as ex: self.assertTrue(str(ex).__eq__('Crawling result cannot be null')) pass pass pass def test_should_execute_crawler_successfully_not_posting_to_service(self): """ """ try: Executor('tests/dependecies_result_status_false.json', 'tests/executor_config.json').execute() pass except Exception as ex: self.assertTrue(False) pass pass pass def test_should_execute_crawler_successfully_posting_to_service(self): """ """ try: Executor('tests/dependecies.json', 'tests/executor_config.json').execute() pass except Exception as ex: self.assertTrue(False) pass pass pass

32.737374

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3,241

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0.098953

0.768586

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false

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0.030303

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0.151515

0

null

0

1

0

null

0

1

0

4

7ea479acbda07c8995d8abc429e6c08525717364

655

py

Python

crashOnSelf.py

binnev/what-can-be-computed

58d01ef09096bda2d0a1876575b992d47fcd0470

[ "CC-BY-4.0" ]

null

crashOnSelf.py

binnev/what-can-be-computed

58d01ef09096bda2d0a1876575b992d47fcd0470

[ "CC-BY-4.0" ]

null

crashOnSelf.py

binnev/what-can-be-computed

58d01ef09096bda2d0a1876575b992d47fcd0470

[ "CC-BY-4.0" ]

null

# SISO program crashOnSelf.py # This is a placeholder program that would solve the problem # CrashOnSelf *if* there existed a working implementation of # crashOnString. In fact, of course, neither of these programs can # work as intended since they both attempt to solve uncomputable # problems. import utils from utils import rf from crashOnString import crashOnString def crashOnSelf(progString): return crashOnString(progString, progString) def testcrashOnSelf(): # There is nothing meaningful to assert in this test, because # crashOnString is an oracle function that does nothing in our # implementation. crashOnSelf("asdf")

29.772727

66

0.777099

85

655

5.988235

0.658824

0

0.175573

655

21

67

31.190476

0.942593

0.641221

0

0.017778

0

1

0.285714

false

0

0.428571

0.142857

0.857143

0

null

0

null

0

1

0

1

0

4

0e4644becc56125f25fa1011f17b42a0b6cdae45

438

py

Python

gui/wdg/PossibleGraphWidget.py

redb0/global-optimization

82a9624f5b92fa012e4dadec8451053f590e71db

[ "MIT" ]

2

2018-08-02T20:39:24.000Z

2020-12-02T08:37:23.000Z

gui/wdg/PossibleGraphWidget.py

redb0/global-optimization

82a9624f5b92fa012e4dadec8451053f590e71db

[ "MIT" ]

null

gui/wdg/PossibleGraphWidget.py

redb0/global-optimization

82a9624f5b92fa012e4dadec8451053f590e71db

[ "MIT" ]

null

from PyQt5 import QtCore from PyQt5.QtWidgets import QWidget class PossibleGraphWidget(QWidget): """Родительский класс для виджетов возможных графиков""" def get_widget(self): """Метод конструирования виджета""" pass def translate(self, s, s_1: str): return QtCore.QCoreApplication.translate(s, s_1) def delete_graph(self, w): """Метод удаления виджетв""" return w.deleteLater

24.333333

60

0.680365

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0.666667

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0.226027

438

17

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25.764706

0.855457

0.23516

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1

0.333333

false

0.111111

0.222222

0.111111

0.888889

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null

0

null

0

1

0

1

0

1

0

4

0e4efaa10871263920900e7fa7ca8e1ad1a32545

64

py

Python

production/tests/__init__.py

GoVanguard/SeleniumBase

29241d58ccba23bb94ebf4c4a51fad578c4aceb8

[ "MIT" ]

null

production/tests/__init__.py

GoVanguard/SeleniumBase

29241d58ccba23bb94ebf4c4a51fad578c4aceb8

[ "MIT" ]

null

production/tests/__init__.py

GoVanguard/SeleniumBase

29241d58ccba23bb94ebf4c4a51fad578c4aceb8

[ "MIT" ]

null

"""All GoVanguard selenium tests are located in this folder."""

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63

0.75

9

64

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64

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0.890625

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1

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null

0

1

0

4

0e6496ca1247f68935a3e7121564123e6cb0509f

137

py

Python

August 2/number.py

rithulkamesh/python-comp

0d3fe963d0713b60857240491da68ff7d8320d1a

[ "MIT" ]

1

2021-08-21T15:31:48.000Z

August 2/number.py

rithulkamesh/python-comp

0d3fe963d0713b60857240491da68ff7d8320d1a

[ "MIT" ]

null

August 2/number.py

rithulkamesh/python-comp

0d3fe963d0713b60857240491da68ff7d8320d1a

[ "MIT" ]

null

l = int(input("Enter number of lines: ")) for i in range (1, l+1): for z in range(1, i + 1): print(z, end = " ") print()

22.833333

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0.50365

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137

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0

0.042105

0.306569

137

6

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22.833333

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0

null

1

0

1

0

null

0

4

0e6b84c3e07235369711fec898d4c175f663686c

22,675

py

Python

ebl/tests/corpus/test_chapter_merge.py

ElectronicBabylonianLiterature/dictionary

5977a57314cf57f94f75cd12520f178b1d6a6555

[ "MIT" ]

null

ebl/tests/corpus/test_chapter_merge.py

ElectronicBabylonianLiterature/dictionary

5977a57314cf57f94f75cd12520f178b1d6a6555

[ "MIT" ]

null

ebl/tests/corpus/test_chapter_merge.py

ElectronicBabylonianLiterature/dictionary

5977a57314cf57f94f75cd12520f178b1d6a6555

[ "MIT" ]

null

import attr import pytest from ebl.transliteration.domain.text_id import TextId from ebl.corpus.domain.chapter import Chapter, Classification from ebl.corpus.domain.line import Line, LineVariant, ManuscriptLine from ebl.corpus.domain.manuscript import Manuscript from ebl.transliteration.domain.stage import Stage from ebl.dictionary.domain.word import WordId from ebl.transliteration.domain.museum_number import MuseumNumber from ebl.transliteration.domain.atf import Surface from ebl.transliteration.domain.enclosure_tokens import BrokenAway from ebl.transliteration.domain.labels import ColumnLabel, SurfaceLabel from ebl.transliteration.domain.line_number import LineNumber from ebl.transliteration.domain.markup import StringPart from ebl.transliteration.domain.normalized_akkadian import AkkadianWord, Caesura from ebl.transliteration.domain.note_line import NoteLine from ebl.transliteration.domain.sign_tokens import Reading from ebl.transliteration.domain.text_line import TextLine from ebl.transliteration.domain.tokens import Joiner, ValueToken from ebl.transliteration.domain.word_tokens import Word from ebl.transliteration.domain.genre import Genre MANUSCRIPT_ID = 1 LABELS = (ColumnLabel.from_int(1),) TEXT_LINE = TextLine( LineNumber(1), ( Word.of([Reading.of_name("kur")], unique_lemma=(WordId("word1"),), alignment=0), Word.of( [Reading.of_name("ra")], unique_lemma=(WordId("word2"),), alignment=None ), ), ) NEW_MANUSCRIPT_ID = 2 NEW_LABELS = (SurfaceLabel.from_label(Surface.REVERSE),) NEW_TEXT_LINE = TextLine( LineNumber(1), (Word.of([Reading.of_name("kur")]), Word.of([Reading.of_name("pa")])) ) MANUSCRIPT_LINE = ManuscriptLine(MANUSCRIPT_ID, LABELS, TEXT_LINE) @pytest.mark.parametrize( "old,new,expected", [ (MANUSCRIPT_LINE, MANUSCRIPT_LINE, MANUSCRIPT_LINE), ( MANUSCRIPT_LINE, ManuscriptLine(NEW_MANUSCRIPT_ID, NEW_LABELS, NEW_TEXT_LINE), ManuscriptLine( NEW_MANUSCRIPT_ID, NEW_LABELS, TEXT_LINE.merge(NEW_TEXT_LINE) ), ), ], ) def test_merge_manuscript_line(old, new, expected): assert old.merge(new) == expected RECONSTRUCTION = ( AkkadianWord.of((ValueToken.of("buāru"),), unique_lemma=(WordId("buāru I"),)), ) RECONSTRUCTION_WITHOUT_LEMMA = (AkkadianWord.of((ValueToken.of("buāru"),)),) IS_SECOND_LINE_OF_PARALLELISM = True IS_BEGINNING_OF_SECTION = True NOTE = None LINE = Line( LineNumber(1), (LineVariant(RECONSTRUCTION, NOTE, (MANUSCRIPT_LINE,)),), IS_SECOND_LINE_OF_PARALLELISM, IS_BEGINNING_OF_SECTION, ) @pytest.mark.parametrize( "old,new,expected", [ ( LineVariant( ( AkkadianWord.of( (ValueToken.of("buāru"),), has_variant_alignmnet=True ), ), manuscripts=( ManuscriptLine( MANUSCRIPT_ID, LABELS, TextLine( LineNumber(1), ( Word.of( [Reading.of_name("kur")], alignment=0, variant=Word.of([Reading.of_name("kur")]), ), ), ), ), ), ), LineVariant( ( AkkadianWord.of( (ValueToken.of("kurkur"),), has_variant_alignmnet=False ), ), manuscripts=( ManuscriptLine( MANUSCRIPT_ID, LABELS, TextLine( LineNumber(1), ( Word.of( [Reading.of_name("kur")], alignment=None, variant=None, ), ), ), ), ), ), LineVariant( ( AkkadianWord.of( (ValueToken.of("kurkur"),), has_variant_alignmnet=True ), ), manuscripts=( ManuscriptLine( MANUSCRIPT_ID, LABELS, TextLine( LineNumber(1), ( Word.of( [Reading.of_name("kur")], alignment=0, variant=Word.of([Reading.of_name("kur")]), ), ), ), ), ), ), ), ], ) def test_merge_line_variant(old, new, expected): assert old.merge(new) == expected @pytest.mark.parametrize( "old,new,expected", [ (LINE, LINE, LINE), ( Line( LineNumber(1), ( LineVariant( RECONSTRUCTION, NOTE, ( ManuscriptLine( MANUSCRIPT_ID, LABELS, TextLine( LineNumber(1), ( Word.of( [ Reading.of( [ ValueToken.of("ku"), BrokenAway.close(), ] ), Joiner.hyphen(), Reading.of_name("nu"), Joiner.hyphen(), Reading.of_name("si"), ], unique_lemma=(WordId("word"),), alignment=0, ), ), ), ), ), ), ), IS_SECOND_LINE_OF_PARALLELISM, IS_BEGINNING_OF_SECTION, ), Line( LineNumber(2), ( LineVariant( ( AkkadianWord.of((ValueToken.of("kur"),)), AkkadianWord.of((ValueToken.of("ra"),)), ), NOTE, ( ManuscriptLine( MANUSCRIPT_ID, LABELS, TextLine( LineNumber(1), ( Word.of( [ Reading.of( [ ValueToken.of("ku"), BrokenAway.close(), ] ), Joiner.hyphen(), Reading.of_name("nu"), Joiner.hyphen(), Reading.of_name("si"), ] ), ), ), ), ), ), ), IS_SECOND_LINE_OF_PARALLELISM, IS_BEGINNING_OF_SECTION, ), Line( LineNumber(2), ( LineVariant( ( AkkadianWord.of((ValueToken.of("kur"),)), AkkadianWord.of((ValueToken.of("ra"),)), ), NOTE, ( ManuscriptLine( MANUSCRIPT_ID, LABELS, TextLine( LineNumber(1), ( Word.of( [ Reading.of( [ ValueToken.of("ku"), BrokenAway.close(), ] ), Joiner.hyphen(), Reading.of_name("nu"), Joiner.hyphen(), Reading.of_name("si"), ], unique_lemma=(WordId("word"),), alignment=0, ), ), ), ), ), ), ), IS_SECOND_LINE_OF_PARALLELISM, IS_BEGINNING_OF_SECTION, ), ), ( Line( LineNumber(1), (LineVariant(RECONSTRUCTION, NOTE, (MANUSCRIPT_LINE,)),), IS_SECOND_LINE_OF_PARALLELISM, IS_BEGINNING_OF_SECTION, ), Line( LineNumber(2), ( LineVariant( RECONSTRUCTION, NOTE, (ManuscriptLine(MANUSCRIPT_ID, LABELS, NEW_TEXT_LINE),), ), ), IS_SECOND_LINE_OF_PARALLELISM, IS_BEGINNING_OF_SECTION, ), Line( LineNumber(2), ( LineVariant( RECONSTRUCTION, NOTE, ( ManuscriptLine( MANUSCRIPT_ID, LABELS, TEXT_LINE.merge(NEW_TEXT_LINE) ), ), ), ), IS_SECOND_LINE_OF_PARALLELISM, IS_BEGINNING_OF_SECTION, ), ), ( Line( LineNumber(1), ( LineVariant( RECONSTRUCTION, NOTE, ( ManuscriptLine( MANUSCRIPT_ID, LABELS, TextLine( LineNumber(1), ( Word.of( [ Reading.of( [ ValueToken.of("ku"), BrokenAway.close(), ] ), Joiner.hyphen(), Reading.of_name("nu"), Joiner.hyphen(), Reading.of_name("si"), ], unique_lemma=(WordId("word"),), alignment=0, ), ), ), ), MANUSCRIPT_LINE, ), ), ), IS_SECOND_LINE_OF_PARALLELISM, IS_BEGINNING_OF_SECTION, ), Line( LineNumber(1), ( LineVariant( RECONSTRUCTION, NOTE, ( ManuscriptLine(MANUSCRIPT_ID, LABELS, NEW_TEXT_LINE), ManuscriptLine(MANUSCRIPT_ID, LABELS, NEW_TEXT_LINE), ), ), ), IS_SECOND_LINE_OF_PARALLELISM, IS_BEGINNING_OF_SECTION, ), Line( LineNumber(1), ( LineVariant( RECONSTRUCTION, NOTE, ( ManuscriptLine(MANUSCRIPT_ID, LABELS, NEW_TEXT_LINE), ManuscriptLine( MANUSCRIPT_ID, LABELS, TEXT_LINE.merge(NEW_TEXT_LINE) ), ), ), ), IS_SECOND_LINE_OF_PARALLELISM, IS_BEGINNING_OF_SECTION, ), ), ( Line( LineNumber(1), (LineVariant(RECONSTRUCTION, NOTE, tuple()),), IS_SECOND_LINE_OF_PARALLELISM, IS_BEGINNING_OF_SECTION, ), Line( LineNumber(1), (LineVariant(RECONSTRUCTION, NOTE, tuple()),), True, True ), Line( LineNumber(1), (LineVariant(RECONSTRUCTION, NOTE, tuple()),), True, True ), ), ( Line( LineNumber(1), ( LineVariant( RECONSTRUCTION, NoteLine((StringPart("a note"),)), tuple() ), ), IS_SECOND_LINE_OF_PARALLELISM, IS_BEGINNING_OF_SECTION, ), Line( LineNumber(1), ( LineVariant( RECONSTRUCTION, NoteLine((StringPart("new note"),)), tuple() ), ), IS_SECOND_LINE_OF_PARALLELISM, IS_BEGINNING_OF_SECTION, ), Line( LineNumber(1), ( LineVariant( RECONSTRUCTION, NoteLine((StringPart("new note"),)), tuple() ), ), IS_SECOND_LINE_OF_PARALLELISM, IS_BEGINNING_OF_SECTION, ), ), ( Line(LineNumber(1), (LineVariant(RECONSTRUCTION),)), Line(LineNumber(1), (LineVariant(RECONSTRUCTION_WITHOUT_LEMMA),)), Line(LineNumber(1), (LineVariant(RECONSTRUCTION),)), ), ( Line( LineNumber(1), (LineVariant(RECONSTRUCTION, None, (MANUSCRIPT_LINE,)),) ), Line( LineNumber(1), ( LineVariant( RECONSTRUCTION_WITHOUT_LEMMA, None, (MANUSCRIPT_LINE.update_alignments([]),), ), ), ), Line( LineNumber(1), (LineVariant(RECONSTRUCTION, None, (MANUSCRIPT_LINE,)),) ), ), ( Line( LineNumber(1), (LineVariant(RECONSTRUCTION, None, (MANUSCRIPT_LINE,)),) ), Line( LineNumber(1), ( LineVariant( (Caesura.certain(),), None, (MANUSCRIPT_LINE.update_alignments([]),), ), ), ), Line( LineNumber(1), ( LineVariant( (Caesura.certain(),), None, (MANUSCRIPT_LINE.update_alignments([None]),), ), ), ), ), ], ) def test_merge_line(old: Line, new: Line, expected: Line) -> None: assert old.merge(new) == expected TEXT_ID = TextId(Genre.LITERATURE, 0, 0) CLASSIFICATION = Classification.ANCIENT STAGE = Stage.NEO_BABYLONIAN VERSION = "A" CHAPTER_NAME = "I" ORDER = 1 MANUSCRIPT = Manuscript(MANUSCRIPT_ID) MUSEUM_NUMBER = MuseumNumber.of("K.1") CHAPTER = Chapter( TEXT_ID, CLASSIFICATION, STAGE, VERSION, CHAPTER_NAME, ORDER, (MANUSCRIPT,), (MUSEUM_NUMBER,), (LINE,), ) NEW_CLASSIFICATION = Classification.MODERN NEW_STAGE = Stage.MIDDLE_ASSYRIAN NEW_VERSION = "B" NEW_CHAPTER_NAME = "II" NEW_ORDER = 2 NEW_MANUSCRIPT = Manuscript(2, siglum_disambiguator="b") NOTE = NoteLine((StringPart("a note"),)) NEW_LINE = Line( LineNumber(1), ( LineVariant( RECONSTRUCTION, NOTE, (ManuscriptLine(MANUSCRIPT_ID, LABELS, NEW_TEXT_LINE),), ), ), IS_SECOND_LINE_OF_PARALLELISM, IS_BEGINNING_OF_SECTION, ) ANOTHER_NEW_LINE = Line( LineNumber(2), ( LineVariant( RECONSTRUCTION, NOTE, ( ManuscriptLine( MANUSCRIPT_ID, LABELS, attr.evolve(NEW_TEXT_LINE, line_number=LineNumber(2)), ), ), ), ), IS_SECOND_LINE_OF_PARALLELISM, IS_BEGINNING_OF_SECTION, ) NEW_PARATEXT = Line( LineNumber(1), ( LineVariant( RECONSTRUCTION, NOTE, ( ManuscriptLine( MANUSCRIPT_ID, LABELS, TEXT_LINE, (NoteLine((StringPart("paratext"),)),), ), ), ), ), IS_SECOND_LINE_OF_PARALLELISM, IS_BEGINNING_OF_SECTION, ) OLD_LINE = Line( LineNumber(2), ( LineVariant( tuple(), None, ( ManuscriptLine( MANUSCRIPT_ID, LABELS, attr.evolve(TEXT_LINE, line_number=LineNumber(2)), ), ), ), ), IS_SECOND_LINE_OF_PARALLELISM, IS_BEGINNING_OF_SECTION, ) @pytest.mark.parametrize( "old,new,expected", [ (CHAPTER, CHAPTER, CHAPTER), ( Chapter( TEXT_ID, CLASSIFICATION, STAGE, VERSION, CHAPTER_NAME, ORDER, (MANUSCRIPT,), (MUSEUM_NUMBER,), (LINE,), ), Chapter( TEXT_ID, NEW_CLASSIFICATION, NEW_STAGE, NEW_VERSION, NEW_CHAPTER_NAME, NEW_ORDER, (MANUSCRIPT, NEW_MANUSCRIPT), (MUSEUM_NUMBER,), (LINE,), ), Chapter( TEXT_ID, NEW_CLASSIFICATION, NEW_STAGE, NEW_VERSION, NEW_CHAPTER_NAME, NEW_ORDER, (MANUSCRIPT, NEW_MANUSCRIPT), (MUSEUM_NUMBER,), (LINE,), ), ), ( Chapter( TEXT_ID, CLASSIFICATION, STAGE, VERSION, CHAPTER_NAME, ORDER, (MANUSCRIPT,), (MUSEUM_NUMBER,), (OLD_LINE, LINE), ), Chapter( TEXT_ID, CLASSIFICATION, STAGE, VERSION, CHAPTER_NAME, ORDER, (MANUSCRIPT,), tuple(), (NEW_LINE, ANOTHER_NEW_LINE), ), Chapter( TEXT_ID, CLASSIFICATION, STAGE, VERSION, CHAPTER_NAME, ORDER, (MANUSCRIPT,), tuple(), (OLD_LINE.merge(NEW_LINE), LINE.merge(ANOTHER_NEW_LINE)), ), ), ( CHAPTER, Chapter( TEXT_ID, CLASSIFICATION, STAGE, VERSION, CHAPTER_NAME, ORDER, (MANUSCRIPT,), (MUSEUM_NUMBER,), (NEW_PARATEXT,), ), Chapter( TEXT_ID, CLASSIFICATION, STAGE, VERSION, CHAPTER_NAME, ORDER, (MANUSCRIPT,), (MUSEUM_NUMBER,), (NEW_PARATEXT,), ), ), ], ) def test_merge_chapter(old, new, expected): assert old.merge(new) == expected

32.910015

88

0.351356

1,305

22,675

5.851341

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0.078313

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0.717784

0.694997

0.669068

0.653745

0.628601

0

0.005856

0.570717

22,675

688

89

32.957849

0.778611

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0.005961

false

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0.031297

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1

0

1

0

1

0

null

0

4

0e74f9792b2322f2896e3b4edd9f5c76b84acc2f

4,459

py

Python

plotly_plots.py

jns-rch/whatsapp-analytics

2f1c0693153b568813e5e6bedafafeec9464d7ca

[ "Apache-2.0" ]

null

plotly_plots.py

jns-rch/whatsapp-analytics

2f1c0693153b568813e5e6bedafafeec9464d7ca

[ "Apache-2.0" ]

null

plotly_plots.py

jns-rch/whatsapp-analytics

2f1c0693153b568813e5e6bedafafeec9464d7ca

[ "Apache-2.0" ]

null

""" Plotter Plot functions with Plotly for standardized plots """ import plotly.express as px from plotly.subplots import make_subplots class Plotter(): def __init__(self, title_x=0.5, title_font_size=24, font_size=14, template='plotly_white', autosize=True, margin={"l":0, "r":0, "t":120, "b":0}, color_discrete_sequence=px.colors.qualitative.T10): self.title_x = title_x self.title_font_size = title_font_size self.font_size = font_size self.template = template self.autosize = autosize self.color_discrete_sequence = color_discrete_sequence self.margin = margin def standardize_plot(self, fig): fig.update_layout(title_font_size=self.title_font_size, title_x=self.title_x, font_size=self.font_size, template=self.template, autosize=self.autosize, margin=self.margin, legend={"orientation":"h", "y":-0.3} ) return fig def barplot(self, data, x, y, color=None, barmode=None, title_text=None, legend_title_text=None, xaxis_title=None, yaxis_title=None, xtickvals=None, ytickvals=None, xtickangle=None, ytickangle=None): fig = px.bar(data_frame=data, x=x, y=y, color=color, barmode=barmode, color_discrete_sequence=self.color_discrete_sequence) fig = fig.update_xaxes(tickvals=xtickvals, tickangle=xtickangle) fig = fig.update_yaxes(tickvals=ytickvals, tickangle=ytickangle) fig = fig.update_layout(title_text=title_text, legend_title_text=legend_title_text, xaxis_title=xaxis_title, yaxis_title=yaxis_title) fig = self.standardize_plot(fig) return fig def pieplot(self, data, values, names, color=None, title_text=None, legend_title_text=None): fig = px.pie(data_frame=data, values=values, names=names, color=color, color_discrete_sequence=self.color_discrete_sequence) fig = fig.update_layout(title_text=title_text, legend_title_text=legend_title_text) fig = self.standardize_plot(fig) return fig def histogram(self, data, x, color=None, title_text=None, legend_title_text=None, xaxis_title=None, yaxis_title=None, xtickvals=None, ytickvals=None, xtickangle=None, ytickangle=None): fig = px.histogram(data_frame=data, x=x, color=color, color_discrete_sequence = self.color_discrete_sequence) fig = fig.update_xaxes(tickvals=xtickvals, tickangle=xtickangle) fig = fig.update_yaxes(tickvals=ytickvals, tickangle=ytickangle) fig = fig.update_layout(title_text=title_text, legend_title_text=legend_title_text, xaxis_title=xaxis_title, yaxis_title=yaxis_title) fig = self.standardize_plot(fig) return fig def boxplot(self, data, x=None, y=None, color=None, title_text=None, legend_title_text=None, xaxis_title=None, yaxis_title=None, xtickvals=None, ytickvals=None, xtickangle=None, ytickangle=None): fig = px.box(data, x, y, color=color, color_discrete_sequence = self.color_discrete_sequence) fig = fig.update_xaxes(tickvals=xtickvals, tickangle=xtickangle) fig = fig.update_yaxes(tickvals=ytickvals, tickangle=ytickangle) fig = fig.update_layout(title_text=title_text, legend_title_text=legend_title_text, xaxis_title=xaxis_title, yaxis_title=yaxis_title) fig = self.standardize_plot(fig) return fig def lineplot(self, data, x, y, color=None, title_text=None, legend_title_text=None, xaxis_title=None, yaxis_title=None, xtickvals=None, ytickvals=None, xtickangle=None, ytickangle=None): fig = px.line(data_frame=data, x=x, y=y, color=color, color_discrete_sequence=self.color_discrete_sequence) fig = fig.update_xaxes(tickvals=xtickvals, tickangle=xtickangle) fig = fig.update_yaxes(tickvals=ytickvals, tickangle=ytickangle) fig = fig.update_layout(title_text=title_text, legend_title_text=legend_title_text, xaxis_title=xaxis_title, yaxis_title=yaxis_title) fig = self.standardize_plot(fig) return fig

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0

4

7eba4b5c426902e753526f50e3a8eac094683239

18,841

py

Python

sql_judge/view/qt_view/resources.py

r4ulill0/gui_dbjudge

7c421c6f2fe1281f95e624242338b3e020ee5f28

[ "MIT" ]

1

2020-12-11T10:45:58.000Z

sql_judge/view/qt_view/resources.py

r4ulill0/gui_dbjudge

7c421c6f2fe1281f95e624242338b3e020ee5f28

[ "MIT" ]

null

sql_judge/view/qt_view/resources.py

r4ulill0/gui_dbjudge

7c421c6f2fe1281f95e624242338b3e020ee5f28

[ "MIT" ]

null

# -*- coding: utf-8 -*- # Resource object code # # Created by: The Resource Compiler for PyQt5 (Qt v5.13.2) # # WARNING! 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\x00\x00\x1a\x00\x00\x00\x1a\x08\x06\x00\x00\x00\xa9\x4a\x4c\xce\ \x00\x00\x00\x06\x62\x4b\x47\x44\x00\xff\x00\xff\x00\xff\xa0\xbd\ \xa7\x93\x00\x00\x00\x9e\x49\x44\x41\x54\x48\x89\xed\x96\xb1\x0d\ \x83\x30\x10\x45\x9f\x53\x30\x87\x47\x48\x96\x84\x3d\x32\x47\xa8\ \x22\x36\x01\x36\xb0\x5c\x3a\x45\x2e\x85\x1d\x4b\xb6\x89\x03\x14\ \x7e\xd2\x15\x70\xe8\xbf\xd3\x51\xd8\x90\x46\x03\x23\x60\x01\x17\ \x94\x95\x9e\xce\xc8\x49\x32\x46\x04\x61\x3d\x7e\x95\x28\xc0\x48\ \xd8\x35\xd2\xbf\x49\xcf\xc8\xb7\xd9\x4c\xa4\xa7\xcf\xad\x67\x38\ \xf1\x07\x57\x32\x51\x01\x0a\xe0\xf2\xa7\xf0\xe3\x88\xfd\xc0\x5a\ \x2b\xf4\xb2\x77\x5b\xdd\xa9\x44\x0a\x7f\x0d\xa9\xe7\xcd\xa2\x2a\ \x34\x51\x13\x35\x51\x13\x7d\x73\xe8\x31\xb1\x56\x90\x2c\xe1\x8b\ \x98\xe8\x5e\x41\x94\x95\xd1\x01\x03\xef\xa9\x4a\x6f\x3e\x33\xd0\ \x4b\x86\xc7\x0b\x49\xf3\x3d\xe7\x02\x0e\xdf\x93\x00\x00\x00\x00\ \x49\x45\x4e\x44\xae\x42\x60\x82\ " qt_resource_name = b"\ \x00\x05\ \x00\x6f\xa6\x53\ \x00\x69\ \x00\x63\x00\x6f\x00\x6e\x00\x73\ \x00\x12\ 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\x00\x00\x00\x00\x00\x00\x00\x00\ \x00\x00\x00\x00\x00\x02\x00\x00\x00\x04\x00\x00\x00\x02\ \x00\x00\x00\x00\x00\x00\x00\x00\ \x00\x00\x00\x54\x00\x00\x00\x00\x00\x01\x00\x00\x0a\xd2\ \x00\x00\x01\x74\x3f\x26\x78\xc0\ \x00\x00\x00\x3a\x00\x00\x00\x00\x00\x01\x00\x00\x02\x48\ \x00\x00\x01\x74\x3f\x27\xa1\xa0\ \x00\x00\x00\x10\x00\x00\x00\x00\x00\x01\x00\x00\x00\x00\ \x00\x00\x01\x72\x7a\x45\xf2\xc0\ \x00\x00\x00\x6c\x00\x00\x00\x00\x00\x01\x00\x00\x0e\xb8\ \x00\x00\x01\x72\xd5\xec\x80\xd0\ " qt_version = [int(v) for v in QtCore.qVersion().split('.')] if qt_version < [5, 8, 0]: rcc_version = 1 qt_resource_struct = qt_resource_struct_v1 else: rcc_version = 2 qt_resource_struct = qt_resource_struct_v2 def qInitResources(): QtCore.qRegisterResourceData(rcc_version, qt_resource_struct, qt_resource_name, qt_resource_data) def qCleanupResources(): QtCore.qUnregisterResourceData(rcc_version, qt_resource_struct, qt_resource_name, qt_resource_data) qInitResources()

55.908012

129

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3.04714

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0.022504

18,841

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130

56.074405

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1

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null

0

1

0

1

0

1

0

null

1

0

4

7ed025ca591e0bb023866d1132e6db9dde2dc481

585

py

Python

prxgt/domain/filter/filter.py

praxigento/teq_test_db_schema_attrs

20ec030dc095c644d22631491e066697203d983d

[ "MIT" ]

null

prxgt/domain/filter/filter.py

praxigento/teq_test_db_schema_attrs

20ec030dc095c644d22631491e066697203d983d

[ "MIT" ]

null

prxgt/domain/filter/filter.py

praxigento/teq_test_db_schema_attrs

20ec030dc095c644d22631491e066697203d983d

[ "MIT" ]

null

__author__ = 'Alex Gusev <alex@flancer64.com>' from prxgt.domain.filter.filter_rule import FilterRule class Filter: """ Top level representation of the filter structure. Filter can contain simple FunctionRule ("customer_id = 23") or can contain a complex ConditionRule. """ def __init__(self, rule: FilterRule): self._rule = rule pass @property def rule(self) -> FilterRule: return self._rule @rule.setter def rule(self, val: FilterRule): self._rule = val def __repr__(self): return repr(self._rule)

24.375

113

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585

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0.549296

0.108696

0.097826

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0.009112

0.249573

585

24

114

24.375

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0.285714

false

0.071429

0.142857

0.571429

0

null

0

null

0

1

0

1

0

1

0

4

7ef71b804afa6e838f19f0ea485651f1b2318ef4

1,022

py

Python

classes/BaseCryptor.py

Alex014/CryptoContainer

22e9b88a3e289b3d75e0102495b6f0e9e09bca0c

[ "MIT" ]

2

2020-09-16T10:37:38.000Z

2021-09-07T10:56:32.000Z

classes/BaseCryptor.py

Alex014/CryptoContainer

22e9b88a3e289b3d75e0102495b6f0e9e09bca0c

[ "MIT" ]

null

classes/BaseCryptor.py

Alex014/CryptoContainer

22e9b88a3e289b3d75e0102495b6f0e9e09bca0c

[ "MIT" ]

1

2020-11-25T02:06:51.000Z

import abc class BaseCryptor: def __init__(self, BLOCK_SIZE): self.__BLOCK_SIZE = BLOCK_SIZE def _pad(self, s): return s + (self.__BLOCK_SIZE - len(s) % self.__BLOCK_SIZE) * chr(self.__BLOCK_SIZE - len(s) % self.__BLOCK_SIZE) def _unpad(self, s): return s[:-ord(s[len(s) - 1:])] @abc.abstractmethod def generate(self): pass @abc.abstractmethod def sign(self, data, key): pass @abc.abstractmethod def verify(self, data, pub_key, signature): pass @abc.abstractmethod def encrypt(self, data, pub_key): pass @abc.abstractmethod def encrypt_multiple(self, data, pub_key): pass @abc.abstractmethod def decrypt(self, data, encrypted_blowfish_key, priv_key): pass @abc.abstractmethod def decrypt_multiple(self, data, encrypted_blowfish_key, priv_key): """ Decrypted multiple items :param data: dictionary of items to be decrypted """ pass

22.711111

121

0.624266

127

1,022

4.755906

0.307087

0.104305

0.231788

0.238411

0.511589

0.403974

0.34106

0.225166

0

0.00135

0.274951

1,022

44

122

23.227273

0.813765

0.071429

0

0.482759

0

1

0.344828

false

0.241379

0.034483

0.068966

0.482759

0

null

0

1

0

null

0

1

0

1

0

4

7d1438420fdcd56fb395e2e50b106dfac70534e4

1,615

py

Python

serene_schema/serene_schema/schema_exceptions.py

NICTA/serene-etl

1d446012c0d08a95b8fbbbe8237735320a2fe2a4

[ "Apache-2.0" ]

null

serene_schema/serene_schema/schema_exceptions.py

NICTA/serene-etl

1d446012c0d08a95b8fbbbe8237735320a2fe2a4

[ "Apache-2.0" ]

null

serene_schema/serene_schema/schema_exceptions.py

NICTA/serene-etl

1d446012c0d08a95b8fbbbe8237735320a2fe2a4

[ "Apache-2.0" ]

null

# Base class class SchemaError(Exception): pass class SchemaBaseError(SchemaError): pass class SchemaAttributeError(SchemaError): pass # Don't catch these exceptions class SchemaBaseUnknownAttribute(SchemaBaseError): pass class SchemaBaseLinkTypeNotSupported(SchemaBaseError): pass class SchemaBaseUnknownObjectType(SchemaBaseError): pass class SchemaBaseUnknownLinkType(SchemaBaseError): pass class SchemaBaseAttributeTypeMismatch(SchemaBaseError): pass class SchemaBaseInvalidObjectType(SchemaBaseError): pass class SchemaBaseInvalidAttributeType(SchemaBaseError): pass class SchemaBaseInvalidAttributeModification(SchemaBaseError): pass class SchemaBaseInvalidAttribute(SchemaBaseError): pass class SchemaBaseInvalidLinkType(SchemaBaseError): pass class SchemaBaseInvalidLinkModification(SchemaBaseError): pass class SchemaBaseEmptyLink(SchemaBaseError): pass class SchemaBaseEmptyObject(SchemaBaseError): pass # Catch these exceptions class SchemaAttributesInvalidDigits(SchemaAttributeError): pass class SchemaAttributesInvalidPhoneNumber(SchemaAttributeError): pass class SchemaAttributesInvalidEmailAddress(SchemaAttributeError): pass class SchemaAttributesInvalidGroupType(SchemaAttributeError): pass class SchemaAttributesInvalidGender(SchemaAttributeError): pass class SchemaAttributesInvalidIATA(SchemaAttributeError): pass class SchemaAttributesInvalidCountryCode(SchemaAttributeError): pass class SchemaAttributesInvalidGeoLocation(SchemaAttributeError): pass

16.479592

64

0.813003

106

1,615

12.386792

0.311321

0.143945

0.219345

0.038081

0

0.139938

1,615

97

65

16.649485

0.945284

0.03839

0

0.5

0

1

0

true

0.5

0

0.5

0

1

null

0

1

0

null

0

1

0

4

7d32ea5ac81520d0643c87868a42abeaedeee026

219

py

Python

django_town/oauth2/management/commands/create_new_service.py

uptown/django-town

4c3b078a8ce5dcc275d65faa4a1cdfb7ebc74a50

[ "MIT" ]

null

django_town/oauth2/management/commands/create_new_service.py

uptown/django-town

4c3b078a8ce5dcc275d65faa4a1cdfb7ebc74a50

[ "MIT" ]

null

django_town/oauth2/management/commands/create_new_service.py

uptown/django-town

4c3b078a8ce5dcc275d65faa4a1cdfb7ebc74a50

[ "MIT" ]

null

from django.core.management.base import BaseCommand from django_town.oauth2.models import Service class Command(BaseCommand): def handle(self, *args, **options): print(Service.objects.create(name=args[0]))

31.285714

51

0.757991

29

219

5.689655

0.793103

0.121212

0

0.010471

0.127854

219

7

52

31.285714

0.853403

0

1

0.2

false

0

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0

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0.2

1

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null

0

1

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null

0

1

0

1

0

4

7d3f41599b0ac3ea2c3bef41b9afa78567a44f38

10,413

py

Python

pysnmp-with-texts/ARUBA-MIB.py

agustinhenze/mibs.snmplabs.com

1fc5c07860542b89212f4c8ab807057d9a9206c7

[ "Apache-2.0" ]

8

2019-05-09T17:04:00.000Z

2021-06-09T06:50:51.000Z

pysnmp-with-texts/ARUBA-MIB.py

agustinhenze/mibs.snmplabs.com

1fc5c07860542b89212f4c8ab807057d9a9206c7

[ "Apache-2.0" ]

4

2019-05-31T16:42:59.000Z

2020-01-31T21:57:17.000Z

pysnmp-with-texts/ARUBA-MIB.py

agustinhenze/mibs.snmplabs.com

1fc5c07860542b89212f4c8ab807057d9a9206c7

[ "Apache-2.0" ]

10

2019-04-30T05:51:36.000Z

2022-02-16T03:33:41.000Z

# # PySNMP MIB module ARUBA-MIB (http://snmplabs.com/pysmi) # ASN.1 source file:///Users/davwang4/Dev/mibs.snmplabs.com/asn1/ARUBA-MIB # Produced by pysmi-0.3.4 at Wed May 1 11:25:46 2019 # On host DAVWANG4-M-1475 platform Darwin version 18.5.0 by user davwang4 # Using Python version 3.7.3 (default, Mar 27 2019, 09:23:15) # ObjectIdentifier, OctetString, Integer = mibBuilder.importSymbols("ASN1", "ObjectIdentifier", "OctetString", "Integer") NamedValues, = mibBuilder.importSymbols("ASN1-ENUMERATION", "NamedValues") ConstraintsUnion, ConstraintsIntersection, ValueRangeConstraint, SingleValueConstraint, ValueSizeConstraint = mibBuilder.importSymbols("ASN1-REFINEMENT", "ConstraintsUnion", "ConstraintsIntersection", "ValueRangeConstraint", "SingleValueConstraint", "ValueSizeConstraint") ObjectGroup, NotificationGroup, ModuleCompliance = mibBuilder.importSymbols("SNMPv2-CONF", "ObjectGroup", "NotificationGroup", "ModuleCompliance") Bits, IpAddress, TimeTicks, ObjectIdentity, Counter64, MibScalar, MibTable, MibTableRow, MibTableColumn, snmpModules, iso, Integer32, Counter32, ModuleIdentity, enterprises, Unsigned32, Gauge32, MibIdentifier, NotificationType = mibBuilder.importSymbols("SNMPv2-SMI", "Bits", "IpAddress", "TimeTicks", "ObjectIdentity", "Counter64", "MibScalar", "MibTable", "MibTableRow", "MibTableColumn", "snmpModules", "iso", "Integer32", "Counter32", "ModuleIdentity", "enterprises", "Unsigned32", "Gauge32", "MibIdentifier", "NotificationType") TextualConvention, DisplayString = mibBuilder.importSymbols("SNMPv2-TC", "TextualConvention", "DisplayString") aruba = MibIdentifier((1, 3, 6, 1, 4, 1, 14823)) products = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1)) arubaEnterpriseMibModules = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 2)) arubaMgmt = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 3)) switchProducts = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 1)) a5000 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 1, 1)) a2400 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 1, 2)) a800 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 1, 3)) a6000 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 1, 4)) a2400E = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 1, 7)) a800E = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 1, 8)) a804 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 1, 9)) a200 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 1, 10)) a2424 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 1, 11)) a6000_SC3 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 1, 12)).setLabel("a6000-SC3") a3200 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 1, 13)) a3200_8 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 1, 14)).setLabel("a3200-8") a3400 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 1, 15)) a3400_32 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 1, 16)).setLabel("a3400-32") a3600 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 1, 17)) a3600_64 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 1, 18)).setLabel("a3600-64") a650 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 1, 19)) a651 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 1, 20)) reserved1 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 1, 21)) reserved2 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 1, 22)) a620 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 1, 23)) s3500_24P = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 1, 24)).setLabel("s3500-24P") s3500_24T = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 1, 25)).setLabel("s3500-24T") s3500_48P = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 1, 26)).setLabel("s3500-48P") s3500_48T = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 1, 27)).setLabel("s3500-48T") s2500_24P = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 1, 28)).setLabel("s2500-24P") s2500_24T = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 1, 29)).setLabel("s2500-24T") s2500_48P = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 1, 30)).setLabel("s2500-48P") s2500_48T = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 1, 31)).setLabel("s2500-48T") a7210 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 1, 32)) a7220 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 1, 33)) a7240 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 1, 34)) s3500_24F = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 1, 35)).setLabel("s3500-24F") aUndefined = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 1, 9999)) apProducts = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2)) a50 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 1)) a52 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 2)) ap60 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 3)) ap61 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 4)) ap70 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 5)) walljackAp61 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 6)) a2E = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 7)) ap1200 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 8)) ap80s = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 9)) ap80m = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 10)) wg102 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 11)) ap40 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 12)) ap41 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 13)) ap65 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 14)) apMw1700 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 15)) apDuowj = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 16)) apDuo = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 17)) ap80MB = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 18)) ap80SB = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 19)) ap85 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 20)) ap124 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 21)) ap125 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 22)) ap120 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 23)) ap121 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 24)) ap1250 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 25)) ap120abg = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 26)) ap121abg = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 27)) ap124abg = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 28)) ap125abg = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 29)) rap5wn = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 30)) rap5 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 31)) rap2wg = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 32)) reserved4 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 33)) ap105 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 34)) ap65wb = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 35)) ap651 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 36)) reserved6 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 37)) ap60p = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 38)) reserved7 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 39)) ap92 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 40)) ap93 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 41)) ap68 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 42)) ap68p = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 43)) ap175p = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 44)) ap175ac = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 45)) ap175dc = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 46)) ap134 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 47)) ap135 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 48)) reserved8 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 49)) ap93h = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 50)) iap23 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 51)) iap23p = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 52)) ap104 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 53)) apUndefined = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 2, 9999)) emsProducts = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 3)) partnerProducts = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 4)) ecsE50 = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 4, 1)) ecsE100C = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 4, 2)) ecsE100A = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 4, 3)) ecsENSM = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 4, 4)) amigopodProducts = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 1, 5)) common = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 2, 1)) switch = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 2, 2)) arubaAp = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 2, 3)) arubaEcs = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 2, 4)) arubaMIBModules = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 2, 1, 1)) wlsxEnterpriseMibModules = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 2, 2, 1)) wlsrEnterpriseMibModules = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 2, 3, 1)) wlsrOutDoorApMibModules = MibIdentifier((1, 3, 6, 1, 4, 1, 14823, 2, 3, 2)) mibBuilder.exportSymbols("ARUBA-MIB", walljackAp61=walljackAp61, ap134=ap134, ap124abg=ap124abg, ap41=ap41, s3500_24T=s3500_24T, ap68=ap68, ap60=ap60, a3600_64=a3600_64, a200=a200, ap68p=ap68p, ap104=ap104, apProducts=apProducts, wlsxEnterpriseMibModules=wlsxEnterpriseMibModules, arubaMIBModules=arubaMIBModules, ap93=ap93, a3400_32=a3400_32, a2E=a2E, ap105=ap105, ap60p=ap60p, ap1250=ap1250, a800E=a800E, a800=a800, s3500_48P=s3500_48P, apDuowj=apDuowj, iap23p=iap23p, partnerProducts=partnerProducts, a650=a650, rap2wg=rap2wg, a7240=a7240, ap61=ap61, switchProducts=switchProducts, a3400=a3400, ap125=ap125, ap121abg=ap121abg, a3200_8=a3200_8, a3200=a3200, ap125abg=ap125abg, s2500_24T=s2500_24T, s2500_48T=s2500_48T, iap23=iap23, apUndefined=apUndefined, ecsE100A=ecsE100A, arubaAp=arubaAp, reserved1=reserved1, s2500_24P=s2500_24P, ecsE50=ecsE50, ap65=ap65, a7210=a7210, ap85=ap85, a5000=a5000, emsProducts=emsProducts, wg102=wg102, a2400E=a2400E, ap93h=ap93h, ap40=ap40, ap124=ap124, reserved8=reserved8, aUndefined=aUndefined, ap80MB=ap80MB, ap92=ap92, reserved7=reserved7, reserved4=reserved4, rap5=rap5, a804=a804, ap1200=ap1200, apMw1700=apMw1700, amigopodProducts=amigopodProducts, a651=a651, arubaMgmt=arubaMgmt, reserved2=reserved2, ecsENSM=ecsENSM, a6000=a6000, common=common, a620=a620, rap5wn=rap5wn, wlsrEnterpriseMibModules=wlsrEnterpriseMibModules, ap175ac=ap175ac, s3500_24P=s3500_24P, ap120abg=ap120abg, a6000_SC3=a6000_SC3, aruba=aruba, a3600=a3600, ap65wb=ap65wb, reserved6=reserved6, ap120=ap120, a52=a52, ap70=ap70, s2500_48P=s2500_48P, a50=a50, wlsrOutDoorApMibModules=wlsrOutDoorApMibModules, ap175dc=ap175dc, ap80s=ap80s, ap135=ap135, ap651=ap651, arubaEnterpriseMibModules=arubaEnterpriseMibModules, switch=switch, ap175p=ap175p, a2424=a2424, ecsE100C=ecsE100C, s3500_24F=s3500_24F, a2400=a2400, ap80m=ap80m, s3500_48T=s3500_48T, ap80SB=ap80SB, products=products, apDuo=apDuo, arubaEcs=arubaEcs, a7220=a7220, ap121=ap121)

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1

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null

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7d4952a67e67259f9be632b926910b8c2512f950

29

py

Python

languages/python/hello_world.py

RishigheshG/ComSoc_archives

d45ac62d89cfe9828f4d7c0b16c9e76653db5d50

[ "MIT" ]

1

2021-10-05T11:56:00.000Z

languages/python/hello_world.py

RishigheshG/ComSoc_archives

d45ac62d89cfe9828f4d7c0b16c9e76653db5d50

[ "MIT" ]

1

2021-10-05T16:01:01.000Z

2021-10-09T05:54:25.000Z

languages/python/hello_world.py

RishigheshG/ComSoc_archives

d45ac62d89cfe9828f4d7c0b16c9e76653db5d50

[ "MIT" ]

4

2021-10-05T09:47:08.000Z

2021-10-21T05:54:05.000Z

s = "World" print("Hello "+s)

14.5

17

0.586207

5

29

3.4

0.8

0

0.137931

29

2

17

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0

1

0

null

0

1

0

4

7d499be0af3f3e7e60689affa7c1d98247db5b86

14,108

py

Python

tests/benchmarks/pybench/Constructs.py

juanfra684/Nuitka

0e276895fadabefb598232f2ccf8cc7736c9a85b

[ "Apache-2.0" ]

1

2022-01-01T18:29:24.000Z

tests/benchmarks/pybench/Constructs.py

juanfra684/Nuitka

0e276895fadabefb598232f2ccf8cc7736c9a85b

[ "Apache-2.0" ]

1

2019-02-21T13:05:17.000Z

tests/benchmarks/pybench/Constructs.py

juanfra684/Nuitka

0e276895fadabefb598232f2ccf8cc7736c9a85b

[ "Apache-2.0" ]

null

# Copyright 2020, Kay Hayen, mailto:kay.hayen@gmail.com # # Python test originally created or extracted from other peoples work. The # parts from me are licensed as below. It is at least Free Software where # it's copied from other people. In these cases, that will normally be # indicated. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # from pybench import Test class IfThenElse(Test): version = 2.0 operations = 30*3 # hard to say... rounds = 150000 def test(self): a,b,c = 1,2,3 for i in xrange(self.rounds): if a == 1: if b == 2: if c != 3: c = 3 b = 3 else: c = 2 elif b == 3: b = 2 a = 2 elif a == 2: a = 3 else: a = 1 if a == 1: if b == 2: if c != 3: c = 3 b = 3 else: c = 2 elif b == 3: b = 2 a = 2 elif a == 2: a = 3 else: a = 1 if a == 1: if b == 2: if c != 3: c = 3 b = 3 else: c = 2 elif b == 3: b = 2 a = 2 elif a == 2: a = 3 else: a = 1 if a == 1: if b == 2: if c != 3: c = 3 b = 3 else: c = 2 elif b == 3: b = 2 a = 2 elif a == 2: a = 3 else: a = 1 if a == 1: if b == 2: if c != 3: c = 3 b = 3 else: c = 2 elif b == 3: b = 2 a = 2 elif a == 2: a = 3 else: a = 1 if a == 1: if b == 2: if c != 3: c = 3 b = 3 else: c = 2 elif b == 3: b = 2 a = 2 elif a == 2: a = 3 else: a = 1 if a == 1: if b == 2: if c != 3: c = 3 b = 3 else: c = 2 elif b == 3: b = 2 a = 2 elif a == 2: a = 3 else: a = 1 if a == 1: if b == 2: if c != 3: c = 3 b = 3 else: c = 2 elif b == 3: b = 2 a = 2 elif a == 2: a = 3 else: a = 1 if a == 1: if b == 2: if c != 3: c = 3 b = 3 else: c = 2 elif b == 3: b = 2 a = 2 elif a == 2: a = 3 else: a = 1 if a == 1: if b == 2: if c != 3: c = 3 b = 3 else: c = 2 elif b == 3: b = 2 a = 2 elif a == 2: a = 3 else: a = 1 if a == 1: if b == 2: if c != 3: c = 3 b = 3 else: c = 2 elif b == 3: b = 2 a = 2 elif a == 2: a = 3 else: a = 1 if a == 1: if b == 2: if c != 3: c = 3 b = 3 else: c = 2 elif b == 3: b = 2 a = 2 elif a == 2: a = 3 else: a = 1 if a == 1: if b == 2: if c != 3: c = 3 b = 3 else: c = 2 elif b == 3: b = 2 a = 2 elif a == 2: a = 3 else: a = 1 if a == 1: if b == 2: if c != 3: c = 3 b = 3 else: c = 2 elif b == 3: b = 2 a = 2 elif a == 2: a = 3 else: a = 1 if a == 1: if b == 2: if c != 3: c = 3 b = 3 else: c = 2 elif b == 3: b = 2 a = 2 elif a == 2: a = 3 else: a = 1 if a == 1: if b == 2: if c != 3: c = 3 b = 3 else: c = 2 elif b == 3: b = 2 a = 2 elif a == 2: a = 3 else: a = 1 if a == 1: if b == 2: if c != 3: c = 3 b = 3 else: c = 2 elif b == 3: b = 2 a = 2 elif a == 2: a = 3 else: a = 1 if a == 1: if b == 2: if c != 3: c = 3 b = 3 else: c = 2 elif b == 3: b = 2 a = 2 elif a == 2: a = 3 else: a = 1 if a == 1: if b == 2: if c != 3: c = 3 b = 3 else: c = 2 elif b == 3: b = 2 a = 2 elif a == 2: a = 3 else: a = 1 if a == 1: if b == 2: if c != 3: c = 3 b = 3 else: c = 2 elif b == 3: b = 2 a = 2 elif a == 2: a = 3 else: a = 1 if a == 1: if b == 2: if c != 3: c = 3 b = 3 else: c = 2 elif b == 3: b = 2 a = 2 elif a == 2: a = 3 else: a = 1 if a == 1: if b == 2: if c != 3: c = 3 b = 3 else: c = 2 elif b == 3: b = 2 a = 2 elif a == 2: a = 3 else: a = 1 if a == 1: if b == 2: if c != 3: c = 3 b = 3 else: c = 2 elif b == 3: b = 2 a = 2 elif a == 2: a = 3 else: a = 1 if a == 1: if b == 2: if c != 3: c = 3 b = 3 else: c = 2 elif b == 3: b = 2 a = 2 elif a == 2: a = 3 else: a = 1 if a == 1: if b == 2: if c != 3: c = 3 b = 3 else: c = 2 elif b == 3: b = 2 a = 2 elif a == 2: a = 3 else: a = 1 if a == 1: if b == 2: if c != 3: c = 3 b = 3 else: c = 2 elif b == 3: b = 2 a = 2 elif a == 2: a = 3 else: a = 1 if a == 1: if b == 2: if c != 3: c = 3 b = 3 else: c = 2 elif b == 3: b = 2 a = 2 elif a == 2: a = 3 else: a = 1 if a == 1: if b == 2: if c != 3: c = 3 b = 3 else: c = 2 elif b == 3: b = 2 a = 2 elif a == 2: a = 3 else: a = 1 if a == 1: if b == 2: if c != 3: c = 3 b = 3 else: c = 2 elif b == 3: b = 2 a = 2 elif a == 2: a = 3 else: a = 1 if a == 1: if b == 2: if c != 3: c = 3 b = 3 else: c = 2 elif b == 3: b = 2 a = 2 elif a == 2: a = 3 else: a = 1 def calibrate(self): a,b,c = 1,2,3 for i in xrange(self.rounds): pass class NestedForLoops(Test): version = 2.0 operations = 1000*10*5 rounds = 300 def test(self): l1 = range(1000) l2 = range(10) l3 = range(5) for i in xrange(self.rounds): for i in l1: for j in l2: for k in l3: pass def calibrate(self): l1 = range(1000) l2 = range(10) l3 = range(5) for i in xrange(self.rounds): pass class ForLoops(Test): version = 2.0 operations = 5 * 5 rounds = 10000 def test(self): l1 = range(100) for i in xrange(self.rounds): for i in l1: pass for i in l1: pass for i in l1: pass for i in l1: pass for i in l1: pass for i in l1: pass for i in l1: pass for i in l1: pass for i in l1: pass for i in l1: pass for i in l1: pass for i in l1: pass for i in l1: pass for i in l1: pass for i in l1: pass for i in l1: pass for i in l1: pass for i in l1: pass for i in l1: pass for i in l1: pass for i in l1: pass for i in l1: pass for i in l1: pass for i in l1: pass for i in l1: pass def calibrate(self): l1 = range(1000) for i in xrange(self.rounds): pass

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1

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null

0

1

0

4

7d4a115c324dd830866e4dbc746a2879fafbf09d

77

py

Python

tools/__int__.py

grayondream/algorithm-forth

c2c21419ec7c42b10f229ab41ac10edf7afbe956

[ "Apache-2.0" ]

null

tools/__int__.py

grayondream/algorithm-forth

c2c21419ec7c42b10f229ab41ac10edf7afbe956

[ "Apache-2.0" ]

null

tools/__int__.py

grayondream/algorithm-forth

c2c21419ec7c42b10f229ab41ac10edf7afbe956

[ "Apache-2.0" ]

null

from tools import list_tools, visualization, file_tools, shell_step, iostream

77

0.857143

11

77

5.727273

0.818182

0

0.090909

77

1

77

0.9

0

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0

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0

null

0

1

0

null

0

1

0

1

0

4

adeff2656c09ff9f3898384a93c16493e2488b76

70

py

Python

study/python/CoreySchaferTutorials/01_intro.py

YoungsAppWorkshop/dev_environment_setup

f197c81059ec5f1ce0bd8b5d972034252f29d9d0

[ "MIT" ]

null

study/python/CoreySchaferTutorials/01_intro.py

YoungsAppWorkshop/dev_environment_setup

f197c81059ec5f1ce0bd8b5d972034252f29d9d0

[ "MIT" ]

3

2021-01-06T10:18:17.000Z

2021-09-02T17:55:51.000Z

study/python/CoreySchaferTutorials/01_intro.py

YoungsAppWorkshop/dev_environment_setup

f197c81059ec5f1ce0bd8b5d972034252f29d9d0

[ "MIT" ]

null

#!/usr/bin/env python3 # Print Welcome Message print('Hello, World')

14

23

0.714286

10

70

5

0.9

0

0.016393

0.128571

70

4

24

17.5

0.803279

0.614286

0

0.48

0

1

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true

0

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null

0

1

0

null

0

1

0

1

0

4

adfb0c26a9a68eb8dcf3e0636b544ecfc7b2c5da

20

py

Python

m3u8tool/__version__.py

kurusugawa-computer/m3u8tool

ac5f206d82d726a3be551c5ab2dee7ccf3bbecad

[ "Apache-2.0" ]

2

2020-04-25T12:46:16.000Z

2020-11-09T12:57:42.000Z

govdelivery/__init__.py

DalavanCloud/govdelivery

1e396a11ebbd839bd5196ee23c8e0479e44d7097

[ "CC0-1.0" ]

null

govdelivery/__init__.py

DalavanCloud/govdelivery

1e396a11ebbd839bd5196ee23c8e0479e44d7097

[ "CC0-1.0" ]

1

2020-03-18T15:23:48.000Z

__version__='0.1.1'

10

19

0.7

4

20

2.5

0.75

0

0.157895

0.05

20

1

20

0.368421

0

0.25

0

1

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false

0

1

0

null

0

1

0

1

0

null

0

4

bc0cbc545e49f470405ca428f9bc81b3b1fb036d

31

py

Python

pyplumio/helpers/__init__.py

denpamusic/PyPlumIO

16e8049977cbfbb1bd6c830beb751e65ee270295

[ "MIT" ]

1

2022-03-24T21:44:59.000Z

pyplumio/helpers/__init__.py

denpamusic/PyPlumIO

16e8049977cbfbb1bd6c830beb751e65ee270295

[ "MIT" ]

null

pyplumio/helpers/__init__.py

denpamusic/PyPlumIO

16e8049977cbfbb1bd6c830beb751e65ee270295

[ "MIT" ]

null

"""Contains helper classes."""

15.5

30

0.677419

3

31

7

1

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0.096774

31

1

31

0.75

0.774194

0

null

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null

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null

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null

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null

true

0

null

1

0

null

0

1

0

null

0

1

0

4

bc2deeb4f27b886991931539a4213115e0a162a3

12,675

py

Python

ditto/reader_validation/create_plots.py

daniel-thom/ditto

9ba2d4cfa5e96eeda811f419c18c70b8a548747e

[ "BSD-3-Clause" ]

44

2018-04-02T16:48:53.000Z

2022-02-24T03:49:06.000Z

ditto/reader_validation/create_plots.py

daniel-thom/ditto

9ba2d4cfa5e96eeda811f419c18c70b8a548747e

[ "BSD-3-Clause" ]

267

2018-04-17T22:40:14.000Z

2022-02-04T15:59:32.000Z

ditto/reader_validation/create_plots.py

daniel-thom/ditto

9ba2d4cfa5e96eeda811f419c18c70b8a548747e

[ "BSD-3-Clause" ]

29

2018-05-11T22:55:09.000Z

2022-02-10T17:35:27.000Z

import matplotlib.pyplot as plt import pandas as pd from itertools import combinations import numpy as np import math ## This function creates a dictonary with R0,X0,R1,X1 values for each reader for the plots to use def plots_dict(input_dict): """Create a dictionary of combinations of readers to create bar graphs""" comp_values = {} for name in input_dict.keys(): comp_values[name] = {} for each_reader in input_dict[name].keys(): # each_reader = each_reader.split("_")[0] comp_values[name][each_reader] = {} comp_values[name][each_reader]["R0"] = [] comp_values[name][each_reader]["X0"] = [] comp_values[name][each_reader]["R1"] = [] comp_values[name][each_reader]["X1"] = [] for (k, v) in input_dict[name][each_reader].items(): comp_values[name][each_reader]["R0"].append(v[0]) comp_values[name][each_reader]["X0"].append(v[1]) comp_values[name][each_reader]["R1"].append(v[2]) comp_values[name][each_reader]["X1"].append(v[3]) return comp_values # This function creates the histograms for R0,X0,R1,X1 values for each reader def plots(input_dict): comp_values = plots_dict(input_dict) for comp_key in comp_values.keys(): fig, axes = plt.subplots(4, 4, figsize=(10, 7), tight_layout=True) for row, each_plot in zip(axes, comp_values[comp_key].keys()): for col, each_node, seq_imp in zip( row, comp_values[comp_key][each_plot].keys(), ["R0", "X0", "R1", "X1"] ): if col.is_first_col(): col.set_ylabel( each_plot.split("_")[0], rotation="horizontal", ha="right" ) if col.is_first_row(): col.set_title(seq_imp) v = comp_values[comp_key][each_plot][each_node] col.hist(v) plt.show() # This function creates a dictionary which computes the differences between the R0,X0,R1,X1 values for all the combinations of readers taking two at a time. def differences_dict(input_dict): """Create a dictionary of combinations of readers to create bar graphs""" # Getting the combinations of the formats for each_case in input_dict.keys(): comb = combinations(input_dict[each_case].keys(), 2) x = list(comb) comp_values = {} comp_values[each_case] = {} for each in x: name = each[0].split("_")[0] + " vs " + each[1].split("_")[0] comp_values[each_case][name] = {} comp_values[each_case][name]["R0"] = [] comp_values[each_case][name]["X0"] = [] comp_values[each_case][name]["R1"] = [] comp_values[each_case][name]["X1"] = [] for (k, v), (k1, v1) in zip( input_dict[each_case][each[0]].items(), input_dict[each_case][each[1]].items(), ): comp_values[each_case][name]["R0"].append(abs(v[0] - v1[0])) comp_values[each_case][name]["X0"].append(abs(v[1] - v1[1])) comp_values[each_case][name]["R1"].append(abs(v[2] - v1[2])) comp_values[each_case][name]["X1"].append(abs(v[3] - v1[3])) return comp_values # This function plots the differences of R0,X0,R1,X1 values between any 2 readers def plots_differences(input_dict): comp_values = differences_dict(input_dict) width = 0.2 for each_case in comp_values.keys(): fig, axes = plt.subplots(6, 4, figsize=(10, 7), sharex=True, sharey=True) for row, comp_key in zip(axes, comp_values[each_case].keys()): for col, each_plot in zip(row, comp_values[each_case][comp_key].keys()): if col.is_first_col(): col.set_ylabel(comp_key, rotation="horizontal", ha="right") if col.is_first_row(): col.set_title(each_plot) v = comp_values[each_case][comp_key][each_plot] col.bar(len(v), v, width, color="tab:blue") col.set_ylim(0, 15) col.set_xticks( np.add(y_pos, (width / 2)) ) # set the position of the x ticks # col.set_xticklabels(input_dict[each_case].keys()) # Need consistent names of nodes in reader in order to name each bar # plt.suptitle('Differences of sequence impedances', size=14) fig.tight_layout() plt.show() # Tests for running the plots independently # if __name__ == "__main__": # plots_differences({'ieee_4node': {'cyme_output': {'1': [1.796043190045738, 5.388117303585387, 0.10784685850195197, 0.5904760366014294], '2': [2.0202605985010313, 6.518985500570162, 0.22820004614399358, 0.8158267453203445], '3': [0.2536631703405771, 0.8984713888134145, 0.06581202655980385, 0.24831713333607722], '4': [0.5340964354229437, 2.3119539172019614, 0.23396047634518685, 0.46239954705589636]}, 'gridlabd_output': {'sourcebus': [1.7960358301233543, 5.388107490370064, 1.6037668205527515, 6.415067282211007], 'node2': [11.615625751028661, 11.520529778987775, 9.073598525409436, 5.8609512435066655], 'node3': [1.2918305507375225, 1.2769209930818217, 1.0089298663668416, 0.6470699623879508], 'load4': [0.8640026377752124, 0.41845221416471984, 0.8640056993976751, 0.4184497947877163], 'node1': [11.95788550650638, 12.207304856874984, 9.189536257036401, 6.043847565567804]}, 'opendss_output': {'sourcebus': [0.0002463564270509644, 0.0007390394604267333, 0.00018858267905109123, 0.0007542723977164494], 'n2': [0.29564583680274237, 0.7167450994489304, 0.11638654713225582, 0.2358768460293939], 'n3': [0.06870713919610347, 0.23863115122119738, 0.048858783362332986, 0.18910852255356034], 'n4': [0.5051857600366919, 0.7781653125896516, 0.21133259350889166, 0.4141945608522559]}, 'synergi_output': {'node_61746791326': [0.000999999415454687, 0.0009999923015324673, 0.0009999996415073831, 0.0009999921771822826], 'node_61746791327': [1.4052433405517772, 0.8534261345199505, 1.100207413576314, 0.09925701086833777], 'node_61746839533': [0.5767771891663984, 1.2140898058567755, 0.5400898631419725, 1.138540681909626], 'node_61746842036': [2.2802968553458975, 1.9930774142792114, 1.8176517572334512, 1.1452767401123385]}}}) # plots({'ieee_4node': {'cyme_output': {'1': [1.796043190045738, 5.388117303585387, 0.10784685850195197, 0.5904760366014294], '2': [2.0202605985010313, 6.518985500570162, 0.22820004614399358, 0.8158267453203445], '3': [0.2536631703405771, 0.8984713888134145, 0.06581202655980385, 0.24831713333607722], '4': [0.5340964354229437, 2.3119539172019614, 0.23396047634518685, 0.46239954705589636]}, 'gridlabd_output': {'sourcebus': [1.7960358301233543, 5.388107490370064, 1.6037668205527515, 6.415067282211007], 'node2': [11.615625751028661, 11.520529778987775, 9.073598525409436, 5.8609512435066655], 'node3': [1.2918305507375225, 1.2769209930818217, 1.0089298663668416, 0.6470699623879508], 'load4': [0.8640026377752124, 0.41845221416471984, 0.8640056993976751, 0.4184497947877163], 'node1': [11.95788550650638, 12.207304856874984, 9.189536257036401, 6.043847565567804]}, 'opendss_output': {'sourcebus': [0.0002463564270509644, 0.0007390394604267333, 0.00018858267905109123, 0.0007542723977164494], 'n2': [0.29564583680274237, 0.7167450994489304, 0.11638654713225582, 0.2358768460293939], 'n3': [0.06870713919610347, 0.23863115122119738, 0.048858783362332986, 0.18910852255356034], 'n4': [0.5051857600366919, 0.7781653125896516, 0.21133259350889166, 0.4141945608522559]}, 'synergi_output': {'node_61746791326': [0.000999999415454687, 0.0009999923015324673, 0.0009999996415073831, 0.0009999921771822826], 'node_61746791327': [1.4052433405517772, 0.8534261345199505, 1.100207413576314, 0.09925701086833777], 'node_61746839533': [0.5767771891663984, 1.2140898058567755, 0.5400898631419725, 1.138540681909626], 'node_61746842036': [2.2802968553458975, 1.9930774142792114, 1.8176517572334512, 1.1452767401123385]}}}) # plots({'ieee_4node': {'cyme_output': {'1': [1.796043190045738, 5.388117303585387, 0.10784685850195197, 0.5904760366014294], '2': [2.0202605985010313, 6.518985500570162, 0.22820004614399358, 0.8158267453203445], '3': [0.2536631703405771, 0.8984713888134145, 0.06581202655980385, 0.24831713333607722], '4': [0.5340964354229437, 2.3119539172019614, 0.23396047634518685, 0.46239954705589636]}, 'gridlabd_output': {'sourcebus': [1.7960358301233543, 5.388107490370064, 1.6037668205527515, 6.415067282211007], 'node2': [11.615625751028661, 11.520529778987775, 9.073598525409436, 5.8609512435066655], 'node3': [1.2918305507375225, 1.2769209930818217, 1.0089298663668416, 0.6470699623879508], 'load4': [0.8640026377752124, 0.41845221416471984, 0.8640056993976751, 0.4184497947877163], 'node1': [11.95788550650638, 12.207304856874984, 9.189536257036401, 6.043847565567804]}, 'opendss_output': {'sourcebus': [0.0002463564270509644, 0.0007390394604267333, 0.00018858267905109123, 0.0007542723977164494], 'n2': [0.29564583680274237, 0.7167450994489304, 0.11638654713225582, 0.2358768460293939], 'n3': [0.06870713919610347, 0.23863115122119738, 0.048858783362332986, 0.18910852255356034], 'n4': [0.5051857600366919, 0.7781653125896516, 0.21133259350889166, 0.4141945608522559]}, 'synergi_output': {'node_61746791326': [0.000999999415454687, 0.0009999923015324673, 0.0009999996415073831, 0.0009999921771822826], 'node_61746791327': [1.4052433405517772, 0.8534261345199505, 1.100207413576314, 0.09925701086833777], 'node_61746839533': [0.5767771891663984, 1.2140898058567755, 0.5400898631419725, 1.138540681909626], 'node_61746842036': [2.2802968553458975, 1.9930774142792114, 1.8176517572334512, 1.1452767401123385]}}, 'ieee_13node': {'cyme_output': {'650': [1.6442002249862027, 2.525071217368887, 0.00175590064769382, 0.013818660541591976], '633': [2.191962671993786, 2.7645145724914206, 0.13502678340376117, 0.30258402028428943], '634': [0.03373885959967424, 0.0437948202860033, 0.006851233217346727, 0.01281928879314106], '7': [1.6444948113338582, 2.5248296649991535, 0.0027565424317121945, 0.014811194353743895], 'rg60': [1.6444956621823732, 2.524829864977333, 0.002756707027920302, 0.014813876873885912], '632': [2.1103087225772716, 2.527515777000864, 0.0791161472443358, 0.2320482533916044], '652': [1.2506186991395154, 1.2878722947329384, 1.2506186991395154, 1.2878722947329384], '611': [1.1239472985549395, 1.3770646713358636, 1.1239472985549395, 1.3770646713358636], '692': [2.631742710227492, 2.70681263013228, 0.16404792757812026, 0.44179116013620445], '645': [2.2388323604857887, 2.784026210466048, 0.1850730276433944, 0.31739303544051045], '646':[2.317657028721549, 2.949917446377885, 0.24850513527121498, 0.3676808102436452], '671': [2.630682474394549, 2.706364834017407, 0.16301316760562778, 0.44085146992520197], '675': [2.7067614833052813, 2.7173749384388346, 0.23870615585157873, 0.47708961405564254], '684': [2.6970360888981926, 2.8036701407791496, 0.23157910972791085, 0.5317115549334911], '680': [2.7200580191836536, 3.2662254613120227, 0.19824054093535326, 0.5540558678888127]}, 'gridlabd_output': {}, 'opendss_output': {'sourcebus': [0.17960357997560872, 0.5388107499674782, 0.16044213136336458, 0.6414216083753025], '650': [3.46173977571697e-05, 0.00027688611330264445, 0.00024463297015852746, 0.0011161493255213788], 'rg60': [0.0003803596442662037, 0.0006225803505498496, 0.0005903829452526287, 0.0014616392165030185], '633': [0.38047984831844595, 0.8729366035169337, 0.13271664569004354, 0.28972479926771977], '634': [0.010133922766079825, 0.020570453379602505, 0.006830751758597249, 0.012931935773494248], '671': [0.6108771018713602, 1.3265863413420522, 0.16093756369535386, 0.42423496513300524], '645': [0.4373080269407039, 0.8584390204064538, 0.18280284255143675, 0.32024566175842095], '646': [0.536560726260114, 0.9883607573047537, 0.24564544687076215, 0.36912074589189336], '692': [0.6119751654440972, 1.3274110796789444, 0.16196524206540175, 0.4251679482288616], '675': [0.7447836834016821, 1.3496142794655475, 0.20882248763406844, 0.46165856154276824], '611': [0.47109807838681994, 0.8597942885112269, 0.47109807838681994, 0.8597942885112269], '652': [0.5900525671135924, 0.8394468662430931, 0.5900525671135924, 0.8394468662430931], '670': [0.3852338293138269, 0.8975161336344963, 0.1039477429886314, 0.2879817616207214], '632': [0.2799093266146708, 0.6803831271514527, 0.07670340676752073, 0.21819919790776035], '680': [0.7346431542735055, 1.6877642140995293, 0.19615949605780691, 0.5372620670065573], '684': [0.7244901189090343, 1.397819420078607, 0.22833210323410577, 0.4698019455814719]}, 'synergi_output': {}}})

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null

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1

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null

0

4

70ac9d7607adb1efc65b5401ec56d2e2842e0da7

188

py

Python

convert.py

Phaugt/convert-images

c549ae439096564743b0f90bcebe13d71fa38301

[ "MIT" ]

null

convert.py

Phaugt/convert-images

c549ae439096564743b0f90bcebe13d71fa38301

[ "MIT" ]

null

convert.py

Phaugt/convert-images

c549ae439096564743b0f90bcebe13d71fa38301

[ "MIT" ]

null

from PIL import Image import PIL import os import glob image = Image.open('./images/pythonexplained.png') image = image.convert('RGB') image.save('./images/pythonexplained.webp', 'webp')

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70af78e58631f14d71d816b26c335284b91c6b34

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py

Python

commonroad/tests/common/test_util.py

CommonRoad/commonroad-io

93824961da9c41eb7768b5cf1acbed9a07446dc2

[ "BSD-3-Clause" ]

3

2022-01-05T09:10:18.000Z

2022-03-22T15:09:43.000Z

commonroad/tests/common/test_util.py

CommonRoad/commonroad-io

93824961da9c41eb7768b5cf1acbed9a07446dc2

[ "BSD-3-Clause" ]

null

commonroad/tests/common/test_util.py

CommonRoad/commonroad-io

93824961da9c41eb7768b5cf1acbed9a07446dc2

[ "BSD-3-Clause" ]

null

import math import unittest import numpy as np from commonroad.common.util import Interval, interpolate_angle, subtract_orientations, vectorized_angle_difference, \ AngleInterval class TestUtils(unittest.TestCase): def test_interpolate_angle(self): a = interpolate_angle(x=0.5, xp=np.array([0., 1.]), fp=np.array([0., 2 * np.pi]), degrees=False) b = interpolate_angle(x=0.5, xp=np.array([0., 1.]), fp=np.array([0., 360.]), degrees=True) c = interpolate_angle(x=0.5, xp=np.array([0., 1.]), fp=np.array([-np.pi, np.pi]), degrees=False) d = interpolate_angle(x=0.5, xp=np.array([0., 1.]), fp=np.array([-180., 180.]), degrees=True) self.assertAlmostEqual(a, 0.) self.assertAlmostEqual(b, 0.) self.assertAlmostEqual(c, np.pi) self.assertAlmostEqual(d, 180.) def test_subtract_orientations(self): self.assertAlmostEqual(subtract_orientations(0.1, -0.1), 0.2) self.assertAlmostEqual(subtract_orientations(0.0, -0.1), 0.1) self.assertAlmostEqual(subtract_orientations(-0.1, 0.1), -0.2) self.assertAlmostEqual(subtract_orientations(0.0, 2 * math.pi), 0.0) self.assertAlmostEqual(subtract_orientations(1.9 * math.pi, 0.1 * math.pi), -0.2 * math.pi) def test_vectorized_angle_difference(self): pi = np.pi self.assertEqual(0.0, vectorized_angle_difference(0, 0)) self.assertEqual(0.0, vectorized_angle_difference(2 * pi, 0)) self.assertEqual(0.0, vectorized_angle_difference(4 * pi, 0)) self.assertEqual(0.0, vectorized_angle_difference(-2 * pi, 0)) self.assertEqual(0.0, vectorized_angle_difference(-4 * pi, 0)) self.assertEqual(0.0, vectorized_angle_difference(pi / 2, pi / 2)) self.assertEqual(0.0, vectorized_angle_difference(5 / 2 * pi, pi / 2)) self.assertEqual(0.0, vectorized_angle_difference(9 / 2 * pi, pi / 2)) self.assertEqual(0.0, vectorized_angle_difference(-3 * pi / 2, pi / 2)) self.assertEqual(0.0, vectorized_angle_difference(-7 * pi / 2, pi / 2)) self.assertEqual(0.0, vectorized_angle_difference(pi, pi)) self.assertEqual(0.0, vectorized_angle_difference(3 * pi, pi)) self.assertEqual(0.0, vectorized_angle_difference(5 * pi, pi)) self.assertEqual(0.0, vectorized_angle_difference(-1 * pi, pi)) self.assertEqual(0.0, vectorized_angle_difference(-3 * pi, pi)) self.assertEqual(0.0, vectorized_angle_difference(3 * pi / 2, 3 * pi / 2)) self.assertEqual(0.0, vectorized_angle_difference(7 * pi / 2, 3 * pi / 2)) self.assertAlmostEqual(0.0, vectorized_angle_difference(11 * pi / 2, 3 * pi / 2)) self.assertEqual(0.0, vectorized_angle_difference(-1 * pi / 2, 3 * pi / 2)) self.assertEqual(0.0, vectorized_angle_difference(-5 * pi / 2, 3 * pi / 2)) self.assertEqual(pi / 2, vectorized_angle_difference(pi / 2, 0)) self.assertAlmostEqual(-pi / 2, vectorized_angle_difference(-pi / 2, 0)) self.assertEqual(pi / 2, vectorized_angle_difference(5 * pi / 2, 0)) self.assertAlmostEqual(-pi / 2, vectorized_angle_difference(-5 * pi / 2, 0)) self.assertEqual(pi, vectorized_angle_difference(pi / 2, -pi / 2)) class TestInterval(unittest.TestCase): def test_intersection(self): # empty intersection right a = Interval(-0.5, -0.1) b = Interval(0, 0.9) self.assertEqual(None, a.intersection(b)) # empty intersection left a = Interval(1, 2) b = Interval(0, 0.9) self.assertEqual(None, a.intersection(b)) # single value intersection a = Interval(0.8, 2) b = Interval(2, 3) result = a.intersection(b) self.assertEqual(2, result.start) self.assertEqual(2, result.end) # intersection a = Interval(0.8, 2) b = Interval(0, 0.9) result = a.intersection(b) self.assertEqual(0.8, result.start) self.assertEqual(0.9, result.end) def test_contains(self): a = Interval(-0.5, 0.5) # float self.assertEqual(a.contains(0.1), True) self.assertEqual(a.contains(1.1), False) self.assertEqual(a.contains(-1.1), False) # intervals self.assertEqual(a.contains(Interval(-0.1, 0.1)), True) self.assertEqual(a.contains(Interval(-1.1, 0.1)), False) self.assertEqual(a.contains(Interval(-1.1, 1.1)), False) self.assertEqual(a.contains(Interval(0.6, 1.1)), False) def test_sum(self): a = Interval(-0.5, -0.1) result = a + 5.0 self.assertEqual(4.5, result.start) self.assertEqual(4.9, result.end) def test_substraction(self): a = Interval(-0.5, -0.1) result = a - 5.0 self.assertEqual(-5.5, result.start) self.assertEqual(-0.1 - 5.0, result.end) def test_product(self): a = Interval(-0.5, -0.1) result = a * 2.0 self.assertEqual(-1.0, result.start) self.assertEqual(-0.2, result.end) def test_product_negative(self): a = Interval(-0.5, -0.1) result = a * (-2.0) self.assertEqual(0.2, result.start) self.assertEqual(1.0, result.end) def test_division(self): a = Interval(-0.5, -0.1) result = a / 2.0 self.assertEqual(-0.25, result.start) self.assertEqual(-0.05, result.end) def test_division_negative(self): a = Interval(-0.5, -0.1) result = a / (-2.0) self.assertEqual(0.05, result.start) self.assertEqual(0.25, result.end) def test_round(self): a = Interval(-1.1, -0.1) result = round(a) self.assertEqual(-1, result.start) self.assertEqual(0, result.end) def test_lt(self): a = Interval(-1.1, -0.1) b = Interval(0.1, 0.2) self.assertEqual(a < b, True) self.assertEqual(b < a, False) def test_gt(self): a = Interval(-1.1, -0.1) b = Interval(0.1, 0.2) self.assertEqual(a > b, False) self.assertEqual(b > a, True) def test__contains__(self): self.assertTrue(1.0 in Interval(0, 2)) self.assertTrue(1.0 in Interval(1, 2)) self.assertTrue(2.0 in Interval(0, 2)) self.assertFalse(-1.0 in Interval(0, 2)) self.assertFalse(3.0 in Interval(0, 2)) class TestAngleInterval(unittest.TestCase): def test__contains__(self): interval = AngleInterval(-np.pi / 2, np.pi / 2) self.assertTrue(interval.__contains__(0.0)) self.assertTrue(interval.__contains__(np.pi / 2)) self.assertTrue(interval.__contains__(-np.pi / 2)) self.assertTrue(interval.__contains__(np.pi / 4)) self.assertTrue(interval.__contains__(-np.pi / 4)) self.assertTrue(interval.__contains__(5 * np.pi / 2)) self.assertTrue(interval.__contains__(-5 * np.pi / 2)) self.assertTrue(interval.__contains__(9 * np.pi / 2)) self.assertTrue(interval.__contains__(-9 * np.pi / 2)) self.assertTrue(interval.__contains__(2 * np.pi)) self.assertTrue(interval.__contains__(-2 * np.pi)) self.assertFalse(interval.__contains__(np.pi)) self.assertFalse(interval.__contains__(-np.pi)) self.assertFalse(interval.__contains__(3 * np.pi)) self.assertFalse(interval.__contains__(-3 * np.pi)) self.assertFalse(interval.__contains__(5 * np.pi)) self.assertFalse(interval.__contains__(-5 * np.pi)) # Regression test interval = AngleInterval(-0.1965, 0.2034) self.assertTrue(interval.__contains__(0.0034)) def test_contains(self): interval = AngleInterval(-np.pi / 2, np.pi / 2) self.assertTrue(interval.contains(0.0)) self.assertTrue(interval.contains(np.pi / 2)) self.assertTrue(interval.contains(-np.pi / 2)) self.assertTrue(interval.contains(np.pi / 4)) self.assertTrue(interval.contains(-np.pi / 4)) self.assertTrue(interval.contains(5 * np.pi / 2)) self.assertTrue(interval.contains(-5 * np.pi / 2)) self.assertTrue(interval.contains(9 * np.pi / 2)) self.assertTrue(interval.contains(-9 * np.pi / 2)) self.assertTrue(interval.contains(2 * np.pi)) self.assertTrue(interval.contains(-2 * np.pi)) self.assertFalse(interval.contains(np.pi)) self.assertFalse(interval.contains(-np.pi)) self.assertFalse(interval.contains(3 * np.pi)) self.assertFalse(interval.contains(-3 * np.pi)) self.assertFalse(interval.contains(5 * np.pi)) self.assertFalse(interval.contains(-5 * np.pi)) # Regression test interval = AngleInterval(-0.1965, 0.2034) self.assertTrue(interval.contains(0.0034)) def test_contains_interval(self): interval = AngleInterval(-np.pi / 2, np.pi / 2) other_interval = AngleInterval(-np.pi / 2, np.pi / 2) self.assertTrue(interval.contains(other_interval)) other_interval = AngleInterval(-2 * np.pi / 3, 2 * np.pi / 3) self.assertFalse(interval.contains(other_interval)) other_interval = AngleInterval(3 * np.pi / 4, 5 * np.pi / 4) self.assertFalse(interval.contains(other_interval)) other_interval = AngleInterval(-np.pi / 2, -np.pi / 4) self.assertTrue(interval.contains(other_interval)) if __name__ == '__main__': unittest.main()

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0.626126

1,298

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4.412943

0.067026

0.138792

0.081006

0.136173

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0.747207

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0.639316

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0.571927

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0

1

0

null

0

1

0

4

70b361e04a93c23e8cf93a7f2508631f8f5a6a28

78

py

Python

src/scripts/imdb_wiki/__init__.py

stevensdavid/msc

6ebcaf604ecbed75576326ad23222749ea31642b

[ "MIT" ]

1

2021-02-04T10:15:35.000Z

src/scripts/imdb_wiki/__init__.py

stevensdavid/msc

6ebcaf604ecbed75576326ad23222749ea31642b

[ "MIT" ]

null

src/scripts/imdb_wiki/__init__.py

stevensdavid/msc

6ebcaf604ecbed75576326ad23222749ea31642b

[ "MIT" ]

null

"""Adapted from https://github.com/imdeepmind/processed-imdb-wiki-dataset"""

26

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10

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0

0.051282

78

2

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0.797297

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null

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null

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null

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null

true

0

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1

0

null

0

1

0

1

0

null

0

1

0

4

70c99d17f4121a9caac58df3bc38ff1326238436

148

py

Python

src/__init__.py

rkoschmitzky/logmole

42fde1e485490ef5553d47c49e4353dcb02e5a51

[ "MIT" ]

3

2019-09-29T08:54:50.000Z

2020-08-18T16:07:01.000Z

src/__init__.py

rkoschmitzky/logmole

42fde1e485490ef5553d47c49e4353dcb02e5a51

[ "MIT" ]

1

2022-01-30T14:02:28.000Z

src/__init__.py

rkoschmitzky/logmole

42fde1e485490ef5553d47c49e4353dcb02e5a51

[ "MIT" ]

null

import logging import sys LOG = logging.getLogger("logmole") logging.basicConfig(stream=sys.__stdout__, level=logging.INFO) from logmole import *

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0.797297

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148

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0.101351

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8

63

18.5

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1

0

false

0

0.6

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1

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1

0

null

0

1

0

1

0

4

70e9a3ef5be4d34a7f183149e8c4c43a5d16dbc3

147

py

Python

Cursos/Alura/Python3_Avancando_na_orientacao_a_objetos/models_abc.py

ramonvaleriano/python-

ada70918e945e8f2d3b59555e9ccc35cf0178dbd

[ "MIT" ]

null

Cursos/Alura/Python3_Avancando_na_orientacao_a_objetos/models_abc.py

ramonvaleriano/python-

ada70918e945e8f2d3b59555e9ccc35cf0178dbd

[ "MIT" ]

null

Cursos/Alura/Python3_Avancando_na_orientacao_a_objetos/models_abc.py

ramonvaleriano/python-

ada70918e945e8f2d3b59555e9ccc35cf0178dbd

[ "MIT" ]

null

from abc import ABC #Abstract Base Classes from collections.abc import MutableSequence class Playlist(MutableSequence): filmes = Playlist()

18.375

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0.789116

17

147

6.823529

0.647059

0.155172

0

0.156463

147

7

44

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0

null

0

0.5

null

0

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null

0

1

0

null

0

1

0

1

0

4

70f6a08b4d3408f890a22b78957d4ccf682a6a39

18

py

Python

appium/version.py

AmateurLWY/python-client

c97238216e828266819f82538c77a993fdf39cf2

[ "Apache-2.0" ]

1

2022-03-11T01:18:36.000Z

appium/version.py

AmateurLWY/python-client

c97238216e828266819f82538c77a993fdf39cf2

[ "Apache-2.0" ]

null

appium/version.py

AmateurLWY/python-client

c97238216e828266819f82538c77a993fdf39cf2

[ "Apache-2.0" ]

null

version = '2.1.4'

9

17

0.555556

4

18

2.5

1

0

0.2

0.166667

18

1

18

0.466667

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0.277778

0

1

0

false

0

1

0

null

0

1

0

1

0

null

0

4

70f9221b5b369a284c75207d934a4cb61ffd5e06

133

py

Python

bruteforce/__init__.py

qiwi/bruteforce

9671c811cdbc1740b6ed7ce581618ccd193ed5a8

[ "MIT" ]

10

2020-11-13T15:44:42.000Z

2020-11-24T16:26:20.000Z

bruteforce/__init__.py

qiwi/bruteforce

9671c811cdbc1740b6ed7ce581618ccd193ed5a8

[ "MIT" ]

4

2021-04-12T22:58:59.000Z

2022-01-25T16:24:42.000Z

bruteforce/__init__.py

qiwi/bruteforce

9671c811cdbc1740b6ed7ce581618ccd193ed5a8

[ "MIT" ]

1

2020-11-15T05:51:06.000Z

from __future__ import absolute_import from celery_app import app as celery_app __all__ = ("celery_app",) __author__ = "g.babaev"

16.625

40

0.781955

19

133

4.631579

0.578947

0.306818

0

0.142857

133

7

41

19

0.77193

0

0.135338

0

1

0

false

0

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0

0.5

0

1

0

null

1

0

1

0

null

0

1

0

4

cb4a4b5e84dcc01870d4819d5153723f41500575

79

py

Python

fython/lexem/interpolationx.py

nicolasessisbreton/fython

988f5a94cee8b16b0000501a22239195c73424a1

[ "Apache-2.0" ]

41

2016-01-21T05:14:45.000Z

2021-11-24T20:37:21.000Z

fython/lexem/interpolationx.py

nicolasessisbreton/fython

988f5a94cee8b16b0000501a22239195c73424a1

[ "Apache-2.0" ]

5

2016-01-21T05:36:37.000Z

2016-08-22T19:26:51.000Z

fython/lexem/interpolationx.py

nicolasessisbreton/fython

988f5a94cee8b16b0000501a22239195c73424a1

[ "Apache-2.0" ]

3

2016-01-23T04:03:44.000Z

2016-08-21T15:58:38.000Z

from fython.unit import * class InterpolationX(Unit): unit = l.interpolationx

19.75

27

0.78481

10

79

6.2

0.7

0

0.126582

79

4

28

19.75

0.898551

0

1

0

false

0

0.333333

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

4

cb61d8d6bd46348a9351da2eb71ca6ff815ee9e8

265

py

Python

MyPython/Untitled-1.py

LairdStreak/MyPyPlayGround

e999cfd179d457a6d17c81bf1bacaa7c90e3e1dc

[ "MIT" ]

null

MyPython/Untitled-1.py

LairdStreak/MyPyPlayGround

e999cfd179d457a6d17c81bf1bacaa7c90e3e1dc

[ "MIT" ]

null

MyPython/Untitled-1.py

LairdStreak/MyPyPlayGround

e999cfd179d457a6d17c81bf1bacaa7c90e3e1dc

[ "MIT" ]

null

import pyautogui size = pyautogui.size() print(size) for i in range(10): pyautogui.moveTo(100, 100, duration=0.25) pyautogui.moveTo(200, 100, duration=0.25) pyautogui.moveTo(200, 200, duration=0.25) pyautogui.moveTo(100, 200, duration=0.25)

29.444444

47

0.686792

40

265

4.55

0.375

0.32967

0.241758

0.32967

0.494505

0.351648

0

0.173516

0.173585

265

9

48

29.444444

0.657534

0

1

0

false

0

0.125

0

0.125

0

null

1

0

1

0

null

0

4

cbcd9655bf654dfcffd135b01ffa7ab5cce790d7

166

py

Python

knigavuhe/kvuconst.py

DarkCat09/knigavuhe

435b4f637d91a8af274c68b825923ef3bf6ca28e

[ "Apache-2.0" ]

null

knigavuhe/kvuconst.py

DarkCat09/knigavuhe

435b4f637d91a8af274c68b825923ef3bf6ca28e

[ "Apache-2.0" ]

null

knigavuhe/kvuconst.py

DarkCat09/knigavuhe

435b4f637d91a8af274c68b825923ef3bf6ca28e

[ "Apache-2.0" ]

null

BASEURL = 'https://knigavuhe.org' REQUA = 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/98.0.4758.82 Safari/537.36 OPR/84.0.4316.14'

55.333333

131

0.722892

31

166

3.83871

0.870968

0.084034

0

0.24

0.096386

166

2

132

83

0.553333

0

0.5

0.855422

0

1

0

false

0

null

0

1

0

1

0

1

0

null

0

4

cbd67b5239f455e74d51da5bb833d6a24ea012fc

207

py

Python

xldlib/gui/__init__.py

Alexhuszagh/XLDiscoverer

60937b1f7f2e23af4219eb26519d6b83fb4232d6

[ "Apache-2.0", "MIT" ]

null

xldlib/gui/__init__.py

Alexhuszagh/XLDiscoverer

60937b1f7f2e23af4219eb26519d6b83fb4232d6

[ "Apache-2.0", "MIT" ]

null

xldlib/gui/__init__.py

Alexhuszagh/XLDiscoverer

60937b1f7f2e23af4219eb26519d6b83fb4232d6

[ "Apache-2.0", "MIT" ]

null

20.7

69

0.666667

28

207

4.821429

0.857143

0

0.032051

0.246377

207

9

70

23

0.833333

0.859903

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

1

0

null

0

1

0

4

cbd83f6b4aad9da1d3d545f9ef069b25190c513f

116

py

Python

chapter01/knock07.py

m-star18/NLP100

e199814f81943f7fb693fd5fe87d6df21da07f5b

[ "MIT" ]

1

2020-07-15T17:21:13.000Z

chapter01/knock07.py

m-star18/NLP100

e199814f81943f7fb693fd5fe87d6df21da07f5b

[ "MIT" ]

1

2021-05-04T01:04:57.000Z

2021-05-04T01:05:32.000Z

chapter01/knock07.py

m-star18/NLP100

e199814f81943f7fb693fd5fe87d6df21da07f5b

[ "MIT" ]

null

def make_text(x, y, z): return '{}時の{}は{}'.format(x, y, z) x = 12 y = '気温' z = 22.4 print(make_text(x, y, z))

12.888889

38

0.517241

26

116

2.230769

0.576923

0.103448

0.155172

0.344828

0.37931

0

0.055556

0.224138

116

8

39

14.5

0.588889

0

0.094828

0

1

0.166667

false

0

0.166667

0.333333

0.166667

1

0

null

0

1

0

1

0

null

0

1

0

4

38045d7a23ed5c37ba2000d30e76ec699df08cfd

376

py

Python

handlers/users/infoButton.py

YoshlikMedia/Dssinnercircle

3811ebccedea8e47091d05509ce2867a57675285

[ "MIT" ]

null

handlers/users/infoButton.py

YoshlikMedia/Dssinnercircle

3811ebccedea8e47091d05509ce2867a57675285

[ "MIT" ]

null

handlers/users/infoButton.py

YoshlikMedia/Dssinnercircle

3811ebccedea8e47091d05509ce2867a57675285

[ "MIT" ]

null

from aiogram import types from aiogram.dispatcher.filters import Command from data.text import text, default_button from filters import IsPrivate from loader import dp @dp.message_handler(IsPrivate(), Command('info', prefixes='/!')) @dp.message_handler(IsPrivate(), text=default_button['info']) async def get_plans(m: types.Message): await m.answer(text=text['info'])

26.857143

64

0.771277

53

376

5.377358

0.471698

0.077193

0.119298

0.175439

0

0.106383

376

13

65

28.923077

0.848214

0

0.037333

0

1

0

true

0

0.555556

0

0.555556

0

null

0

1

0

null

0

1

0

1

0

1

0

4

381d2c7a4f8847bb1b962909faecb722c0eff036

2,585

py

Python

inputFiles/ourIA/borderline/le_truc_final.py

dimtion/jml

dba4db760280cc5ed8c384e36e41d6c7a310fb4f

[ "MIT" ]

1

2015-10-07T19:18:55.000Z

inputFiles/ourIA/borderline/le_truc_final.py

dimtion/jml

dba4db760280cc5ed8c384e36e41d6c7a310fb4f

[ "MIT" ]

1

2015-10-07T19:28:25.000Z

2015-10-08T19:01:47.000Z

inputFiles/ourIA/borderline/le_truc_final.py

dimtion/jml

dba4db760280cc5ed8c384e36e41d6c7a310fb4f

[ "MIT" ]

null

# DU CODE sérieux def une_fonction(): """ ͏͏ ͏͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏͏ ͏ ͏ ͏ ͏ ͏͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏͏ ͏ ͏ ͏͏ ͏͏ ͏ ͏ ͏ ͏͏ ͏ ͏͏ ͏͏ ͏ ͏͏ ͏ ͏͏ ͏ ͏͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏͏ ͏͏ ͏ ͏ ͏͏ ͏ ͏ ͏͏ ͏͏ ͏ ͏ ͏͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏͏ ͏͏ ͏ ͏ ͏ ͏ ͏͏ ͏͏ ͏ ͏͏ ͏ ͏ ͏ ͏ ͏͏ ͏ ͏ ͏͏ ͏͏ ͏͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏͏ ͏͏ ͏͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏͏ ͏͏ ͏ ͏ ͏ ͏ ͏ ͏͏ ͏ ͏ ͏͏ ͏ ͏ ͏͏ ͏ ͏ ͏͏ ͏ ͏ ͏ ͏ ͏͏ ͏͏ ͏ ͏͏ ͏͏ ͏ ͏͏ ͏ ͏͏ ͏ ͏͏ ͏͏ ͏͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏͏ ͏ ͏ ͏͏ ͏͏͏ ͏ ͏͏ ͏͏ ͏͏ ͏ ͏ ͏ ͏͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏͏ ͏ ͏͏ ͏͏ ͏ ͏ ͏ ͏͏ ͏ ͏ ͏͏ ͏ ͏ ͏ ͏͏ ͏͏ ͏ ͏ ͏͏ ͏ ͏ ͏͏ ͏͏ ͏͏ ͏ ͏ ͏ ͏ ͏ ͏͏ ͏ ͏ ͏ ͏͏ ͏͏ ͏ ͏ ͏͏ ͏ ͏ ͏ ͏ ͏ ͏͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏͏ ͏͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏͏ ͏ ͏͏ ͏ ͏͏ ͏ ͏͏ ͏ ͏ ͏͏ ͏͏ ͏͏ ͏͏ ͏͏ ͏ ͏ ͏ ͏ ͏͏ ͏ ͏ ͏͏ ͏͏͏ ͏ ͏͏ ͏͏ ͏͏ ͏ ͏͏ ͏ ͏͏ ͏͏ ͏͏ ͏͏ ͏ ͏ ͏ ͏͏ ͏͏ ͏͏ ͏͏ ͏ ͏͏ ͏͏ ͏ ͏ ͏ ͏ ͏ ͏ ͏͏ ͏ ͏͏ ͏͏ ͏ ͏ ͏ ͏͏ ͏ ͏ ͏͏ ͏ ͏ ͏ ͏͏ ͏͏ ͏ ͏ ͏͏ ͏ ͏͏ ͏͏ ͏͏ ͏͏ Ceci est une fonction qui marche܁ ͏ ͏ ͏ ͏ ܁ Le but est de retourner un truc qui gagne...܁͏ ͏ ͏ ͏܁ En effeit celle-ci est très forte܁͏ ͏͏ ͏ ܁ """ pass def deux_fonctions(): """܁͏ ͏ ͏͏ ͏ ܁ Trois petits chats,܁ ͏ ͏͏ ܁ trois petits chats,܁͏͏ ͏͏ ͏͏ ͏܁ qui viennent et qui repartent...܁ ͏ ͏ ͏ ܁ """ pass def trois_fonction(): """܁ ͏ ͏͏ ܁ Je suis dans une famille modeste܁ ͏͏ ͏͏ ܁ L'injustice et la guerre sont des choses que je détèste,܁͏ ͏ ͏ ͏ ܁ J'ai pas connu mon père, il était capitaine܁͏ ͏܁ """ pass def quatre_fonctions(): """܁ ͏ ܁ La dernière et ultime...܁ ͏ ܁ Bafouille...܁͏ ͏ ͏͏ ܁ """ return "HELLO" # Convert the list of nodes to a matrix : # graph = une_fonction.__doc__.split('\n')[0].replace(chr(32), '0').replace(chr(160), '1').replace(chr(0x34f), '2').replace(chr(0xad), '3') # exec(''.join(chr(int(graph[i:i+4], 4)) for i in range(0, len(graph), 4)))

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1

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4

3832e7207780d15becd48805c0b5e5680749f1f2

293

py

Python

misc/pynmz/__init__.py

yuanguohuo/namazu

2791652194b5465a9a1469917bf8163a797a16fa

[ "Apache-2.0" ]

458

2016-04-29T03:37:23.000Z

2022-02-16T20:34:34.000Z

misc/pynmz/__init__.py

yuanguohuo/namazu

2791652194b5465a9a1469917bf8163a797a16fa

[ "Apache-2.0" ]

125

2015-03-19T04:37:16.000Z

2016-04-28T07:32:18.000Z

misc/pynmz/__init__.py

yuanguohuo/namazu

2791652194b5465a9a1469917bf8163a797a16fa

[ "Apache-2.0" ]

36

2016-05-16T00:10:53.000Z

2022-01-12T10:12:39.000Z

from . import common LOG = common.init_logger() # Eventlet misusage detection (Do NOT use this with a non-eventlet blocking function) # import eventlet.debug # LOG.debug('eventlet.debug.hub_blocking_detection(True, resolution=3)') # eventlet.debug.hub_blocking_detection(True, resolution=10)

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4

698d1d860fadd4ea33a3aeb37e9eef3d6329e661

2,589

py

Python

array_api_tests/function_stubs/creation_functions.py

pmeier/array-api-tests

b47e667af1f216572862bb23c8b1d5ed2e9f0a3a

[ "MIT" ]

1

2022-01-04T10:43:33.000Z

array_api_tests/function_stubs/creation_functions.py

pmeier/array-api-tests

b47e667af1f216572862bb23c8b1d5ed2e9f0a3a

[ "MIT" ]

null

array_api_tests/function_stubs/creation_functions.py

pmeier/array-api-tests

b47e667af1f216572862bb23c8b1d5ed2e9f0a3a

[ "MIT" ]

null

""" Function stubs for creation functions. NOTE: This file is generated automatically by the generate_stubs.py script. Do not modify it directly. See https://github.com/data-apis/array-api/blob/master/spec/API_specification/creation_functions.md """ from __future__ import annotations from ._types import (List, Optional, SupportsBufferProtocol, SupportsDLPack, Tuple, Union, array, device, dtype) from collections.abc import Sequence def arange(start: Union[int, float], /, stop: Optional[Union[int, float]] = None, step: Union[int, float] = 1, *, dtype: Optional[dtype] = None, device: Optional[device] = None) -> array: pass def asarray(obj: Union[float, NestedSequence[bool|int|float], SupportsDLPack, SupportsBufferProtocol], /, *, dtype: Optional[dtype] = None, device: Optional[device] = None, copy: Optional[bool] = None) -> array: pass def empty(shape: Union[int, Tuple[int, ...]], *, dtype: Optional[dtype] = None, device: Optional[device] = None) -> array: pass def empty_like(x: array, /, *, dtype: Optional[dtype] = None, device: Optional[device] = None) -> array: pass def eye(n_rows: int, n_cols: Optional[int] = None, /, *, k: Optional[int] = 0, dtype: Optional[dtype] = None, device: Optional[device] = None) -> array: pass def from_dlpack(x: object, /) -> array: pass def full(shape: Union[int, Tuple[int, ...]], fill_value: Union[int, float], *, dtype: Optional[dtype] = None, device: Optional[device] = None) -> array: pass def full_like(x: array, /, fill_value: Union[int, float], *, dtype: Optional[dtype] = None, device: Optional[device] = None) -> array: pass def linspace(start: Union[int, float], stop: Union[int, float], /, num: int, *, dtype: Optional[dtype] = None, device: Optional[device] = None, endpoint: bool = True) -> array: pass def meshgrid(*arrays: Sequence[array], indexing: str = 'xy') -> List[array, ...]: pass def ones(shape: Union[int, Tuple[int, ...]], *, dtype: Optional[dtype] = None, device: Optional[device] = None) -> array: pass def ones_like(x: array, /, *, dtype: Optional[dtype] = None, device: Optional[device] = None) -> array: pass def zeros(shape: Union[int, Tuple[int, ...]], *, dtype: Optional[dtype] = None, device: Optional[device] = None) -> array: pass def zeros_like(x: array, /, *, dtype: Optional[dtype] = None, device: Optional[device] = None) -> array: pass __all__ = ['arange', 'asarray', 'empty', 'empty_like', 'eye', 'from_dlpack', 'full', 'full_like', 'linspace', 'meshgrid', 'ones', 'ones_like', 'zeros', 'zeros_like']

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6993da70582b57a1c7d97bcb7196747431aeb33f

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py

Python

models/transaction.py

MaferMazu/blockchain-network-simulator

3f2184b2c05681184eee40168b142e5d0af581b1

[ "MIT" ]

null

models/transaction.py

MaferMazu/blockchain-network-simulator

3f2184b2c05681184eee40168b142e5d0af581b1

[ "MIT" ]

1

2021-12-08T03:28:16.000Z

2021-12-08T23:17:53.000Z

models/transaction.py

MaferMazu/blockchain-network-simulator

3f2184b2c05681184eee40168b142e5d0af581b1

[ "MIT" ]

null

"""Class Transaction""" class Transaction: """Docs.""" def __init__(self): # Crea una transacción # hash # de quien # para quien # timestamp # monto en satoshis # fee pass def read_transaction_config(config_file, node_file, dir): """Read the config file""" # Config file # frecuencia : Número de transacciones por minuto # NumEntradasMin : Número de entradas Mínimo # NumEntradasMax : Número de entradas Máximo # NumSalidasMin : Número de salidas Mínimo # NumSalidasMax : Número de salidas Máximo # Node file # nombre: puerto # dir # Directorio en donde vamos a tener todos los logs tipo nodo.log def gen_dummy_transaction(target): """Genera una transaccion al target"""

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4

69ae0e8e7f1f74a4fc34978f30aa53e14eb12d7d

594

py

Python

Properties/PropertyDTO/ReadPathsFromPropertyDTO.py

MarcoAP/EngineIngestionPySpark

408f748742b7fa9303a5d02f3780bd8434b4fdd6

[ "Apache-2.0" ]

null

Properties/PropertyDTO/ReadPathsFromPropertyDTO.py

MarcoAP/EngineIngestionPySpark

408f748742b7fa9303a5d02f3780bd8434b4fdd6

[ "Apache-2.0" ]

null

Properties/PropertyDTO/ReadPathsFromPropertyDTO.py

MarcoAP/EngineIngestionPySpark

408f748742b7fa9303a5d02f3780bd8434b4fdd6

[ "Apache-2.0" ]

null

from Enums.PropertiesCatalogEnum import PropertiesCatalogEnum from Properties.LoadProperties import LoadProperties class ReadPathsFromPropertyDTO(object): def getWindowsPathsFrom (self): return LoadProperties(PropertyEnum=PropertiesCatalogEnum.RPF).getProperty("Windows-Paths-From", "path") def getLinuxPathsFrom (self): return LoadProperties(PropertyEnum=PropertiesCatalogEnum.RPF).getProperty("Linux-Paths-From", "path") def getMacOSPathsFrom (self): return LoadProperties(PropertyEnum=PropertiesCatalogEnum.RPF).getProperty("MacOS-Paths-From", "path")

45.692308

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null

0

1

0

1

0

4

69d8cad0d501beb2fbc3c919223ab3e694dd7023

80

py

Python

web_payments_dummy/django_dummy/__init__.py

devkral/web-payments-connector

722e155ff22098e651c3bcf76bfb8fd0a9518252

[ "BSD-2-Clause", "BSD-3-Clause" ]

6

2018-03-09T10:59:45.000Z

2021-08-03T03:22:22.000Z

web_payments_dummy/django_dummy/__init__.py

devkral/web-payments-connector

722e155ff22098e651c3bcf76bfb8fd0a9518252

[ "BSD-2-Clause", "BSD-3-Clause" ]

1

2018-11-05T12:47:13.000Z

web_payments_dummy/django_dummy/__init__.py

devkral/web-payments-connector

722e155ff22098e651c3bcf76bfb8fd0a9518252

[ "BSD-2-Clause", "BSD-3-Clause" ]

null

default_app_config = "web_payments_dummy.django_dummy.apps.DummyPaymentsConfig"

40

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false

0

1

0

null

0

1

0

1

null

0

4

69da72be93e8fd1836ba08807abd7a20a3b80bb6

147

py

Python

argueserver/plugins/__init__.py

UKPLab/argotario

cb817460e2c1cae1d2edb86eeb3ab238c592de4b

[ "Apache-2.0" ]

8

2017-12-13T18:41:51.000Z

2021-12-14T20:56:33.000Z

argueserver/plugins/__init__.py

UKPLab/argotario

cb817460e2c1cae1d2edb86eeb3ab238c592de4b

[ "Apache-2.0" ]

1

2019-12-18T03:02:27.000Z

2019-12-23T19:06:07.000Z

argueserver/plugins/__init__.py

UKPLab/argotario

cb817460e2c1cae1d2edb86eeb3ab238c592de4b

[ "Apache-2.0" ]

2

2017-08-14T13:24:16.000Z

2021-02-16T08:52:22.000Z

__all__ = ['arguments', 'domains', 'events', 'fallacies', 'feedback', 'pointsOverTime', 'sessions', 'spamReports', 'topics', 'users', 'languages']

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0

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1

0

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null

0

4

69e24555d94eb669e08ff33397cfe46ce348e8fd

192

py

Python

couchdb/design_document.py

mqzry/pycouchdb

1592b1b501e6e2dea3009a83e9c937da70b49af8

[ "MIT" ]

null

couchdb/design_document.py

mqzry/pycouchdb

1592b1b501e6e2dea3009a83e9c937da70b49af8

[ "MIT" ]

10

2016-08-02T17:24:05.000Z

2016-09-06T17:06:06.000Z

couchdb/design_document.py

mqzry/pycouchdb

1592b1b501e6e2dea3009a83e9c937da70b49af8

[ "MIT" ]

null

from document import Document class DesignDocument(Document): def __init__(self, database, doc_id, rev): super(DesignDocument, self).__init__(database, '_design/{0}'.format(doc_id), rev)

27.428571

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0.765625

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0.784884

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0

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null

0

1

0

1

0

4

0e00cd6e4e78ad3b7cac354183b146c289ba5640

118

py

Python

emilientools/__init__.py

emilienschultz/emilientools

4a5b73c92b69f368a163beae91b5046569c9090d

[ "MIT" ]

null

emilientools/__init__.py

emilienschultz/emilientools

4a5b73c92b69f368a163beae91b5046569c9090d

[ "MIT" ]

null

emilientools/__init__.py

emilienschultz/emilientools

4a5b73c92b69f368a163beae91b5046569c9090d

[ "MIT" ]

null

""" description du package """ __version__ = '0.0.1' from .bigbang import * from . import bigbang import os as os

9.833333

22

0.677966

17

118

4.470588

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0

0.031915

0.20339

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11

23

10.727273

0.776596

0.186441

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null

1

0

null

0

1

0

1

0

4

384de4054db1f6471cd112176df071a59caf4da9

100

py

Python

dreamplacefpga/ops/demandMap/__init__.py

rachelselinar/DREAMPlaceFPGA

b8dd961718144a7c2471dd670379c3d1923171f9

[ "BSD-3-Clause" ]

20

2021-11-05T13:20:50.000Z

2022-03-22T17:16:08.000Z

dreamplacefpga/ops/demandMap/__init__.py

rachelselinar/DREAMPlaceFPGA

b8dd961718144a7c2471dd670379c3d1923171f9

[ "BSD-3-Clause" ]

1

2022-01-25T07:35:26.000Z

2022-01-26T03:08:45.000Z

dreamplacefpga/ops/demandMap/__init__.py

rachelselinar/DREAMPlaceFPGA

b8dd961718144a7c2471dd670379c3d1923171f9

[ "BSD-3-Clause" ]

5

2021-11-16T14:33:37.000Z

2022-03-16T02:21:51.000Z

## # @file __init__.py # @author Rachel Selina Rajarathnam (DREAMPlaceFPGA) # @date Nov 2020 #

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0.2

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1

0

4

385ad913118c6312ae684013431c119cbb6a5438

144

py

Python

hover/recipes/__init__.py

haochuanwei/hover

53eb38c718e44445b18a97e391b7f90270802b04

[ "MIT" ]

251

2020-11-22T15:02:30.000Z

2022-03-23T23:29:28.000Z

hover/recipes/__init__.py

haochuanwei/hover

53eb38c718e44445b18a97e391b7f90270802b04

[ "MIT" ]

22

2020-12-03T07:50:27.000Z

2022-02-26T01:43:41.000Z

hover/recipes/__init__.py

haochuanwei/hover

53eb38c718e44445b18a97e391b7f90270802b04

[ "MIT" ]

14

2020-11-18T06:46:02.000Z

2022-03-03T08:14:18.000Z

""" ???+ note "High-level functions to produce an interactive annotation interface." """ from .stable import simple_annotator, linked_annotator

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4

38623fcde8009b8d9b3f7af4d9a666cb8a98ee8f

40

py

Python

rootfs/usr/lib/python2.7/dist-packages/mcpi/block.py

kappaIO-Dev/kappaIO-sdk-armhf-crosscompile

66fc5fc21e6235f7a3be72a7ccac68e2224b7fb2

[ "MIT" ]

null

rootfs/usr/lib/python2.7/dist-packages/mcpi/block.py

kappaIO-Dev/kappaIO-sdk-armhf-crosscompile

66fc5fc21e6235f7a3be72a7ccac68e2224b7fb2

[ "MIT" ]

null

rootfs/usr/lib/python2.7/dist-packages/mcpi/block.py

kappaIO-Dev/kappaIO-sdk-armhf-crosscompile

66fc5fc21e6235f7a3be72a7ccac68e2224b7fb2

[ "MIT" ]

null

../../../../share/pyshared/mcpi/block.py

40

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0

null

0

1

0

4

3865c6bcdfa3851066f7c0fc9ced780f3f714f2a

1,820

py

Python

venv/Lib/site-packages/tobiiresearch/implementation/StreamErrorData.py

mintzer/pupillometry-rf-back

cfa86fa984a49dce0123798f8de5b838c02e10d5

[ "CC-BY-4.0" ]

null

venv/Lib/site-packages/tobiiresearch/implementation/StreamErrorData.py

mintzer/pupillometry-rf-back

cfa86fa984a49dce0123798f8de5b838c02e10d5

[ "CC-BY-4.0" ]

null

venv/Lib/site-packages/tobiiresearch/implementation/StreamErrorData.py

mintzer/pupillometry-rf-back

cfa86fa984a49dce0123798f8de5b838c02e10d5

[ "CC-BY-4.0" ]

null

STREAM_ERROR_SOURCE_USER = "stream_error_source_user" STREAM_ERROR_SOURCE_STREAM_PUMP = "stream_error_source_stream_pump" STREAM_ERROR_SOURCE_SUBSCRIPTION_GAZE_DATA = "stream_error_source_subscription_gaze_data" STREAM_ERROR_SOURCE_SUBSCRIPTION_USER_POSITION_GUIDE = "stream_error_source_subscription_user_position_guide" STREAM_ERROR_SOURCE_SUBSCRIPTION_EXTERNAL_SIGNAL = "stream_error_source_subscription_external_signal" STREAM_ERROR_SOURCE_SUBSCRIPTION_TIME_SYNCHRONIZATION_DATA = \ "stream_error_source_subscription_time_synchronization_data" STREAM_ERROR_SOURCE_SUBSCRIPTION_EYE_IMAGE = "stream_error_source_subscription_eye_image" STREAM_ERROR_SOURCE_SUBSCRIPTION_NOTIFICATION = "stream_error_source_subscription_notification" STREAM_ERROR_CONNECTION_LOST = "stream_error_connection_lost" STREAM_ERROR_INSUFFICIENT_LICENSE = "stream_error_insufficient_license" STREAM_ERROR_NOT_SUPPORTED = "stream_error_not_supported" STREAM_ERROR_TOO_MANY_SUBSCRIBERS = "stream_error_too_many_subscribers" STREAM_ERROR_INTERNAL_ERROR = "stream_error_internal_error" STREAM_ERROR_USER_ERROR = "stream_error_user_error" class StreamErrorData(object): '''Provides information about a stream error. ''' def __init__(self, data): if not isinstance(data, dict): raise ValueError("You shouldn't create StreamErrorData objects yourself.") self._system_time_stamp = data["system_time_stamp"] self._error = data["error"] self._source = data["source"] self._message = data["message"] @property def system_time_stamp(self): return self._system_time_stamp @property def source(self): return self._source @property def error(self): return self._error @property def message(self): return self._message

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py

Python

admit/util/filter/__init__.py

astroumd/admit

bbf3d79bb6e1a6f7523553ed8ede0d358d106f2c

[ "MIT" ]

4

2017-03-01T17:26:28.000Z

2022-03-03T19:23:06.000Z

admit/util/filter/__init__.py

teuben/admit

1cae54d1937c9af3f719102838df716e7e6d655c

[ "MIT" ]

48

2016-10-04T01:25:33.000Z

2021-09-08T14:51:10.000Z

admit/util/filter/__init__.py

teuben/admit

1cae54d1937c9af3f719102838df716e7e6d655c

[ "MIT" ]

2

2016-11-10T14:10:22.000Z

2017-03-30T18:58:05.000Z

"""Filter Package -------------- This package is the root module for spectral filtering utilities. """

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38869a3f81794f010da06077210eb84e97ec53e2

77

py

Python

src/altinn_model_publisher/organizations/__init__.py

Informasjonsforvaltning/altinn-model-publisher

61c1c2125c7a66099e713644d157dfcff2d46b90

[ "Apache-2.0" ]

null

src/altinn_model_publisher/organizations/__init__.py

Informasjonsforvaltning/altinn-model-publisher

61c1c2125c7a66099e713644d157dfcff2d46b90

[ "Apache-2.0" ]

24

2020-10-21T05:50:48.000Z

2021-08-24T10:56:10.000Z

src/altinn_model_publisher/organizations/__init__.py

Informasjonsforvaltning/altinn-model-publisher

61c1c2125c7a66099e713644d157dfcff2d46b90

[ "Apache-2.0" ]

null

"""Organizations package. Modules: organizations shortname_orgs """

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38c5d833e74bc0a5231a48be073ac79eb4eed506

92

py

Python

MyApp/ToDo_List/apps.py

ArkapravaNandy/To-Do-List

f1295ac9efdd5cda11e16d0afb8bdc260e63bcbe

[ "bzip2-1.0.6" ]

null

MyApp/ToDo_List/apps.py

ArkapravaNandy/To-Do-List

f1295ac9efdd5cda11e16d0afb8bdc260e63bcbe

[ "bzip2-1.0.6" ]

null

MyApp/ToDo_List/apps.py

ArkapravaNandy/To-Do-List

f1295ac9efdd5cda11e16d0afb8bdc260e63bcbe

[ "bzip2-1.0.6" ]

null

from django.apps import AppConfig class TodoListConfig(AppConfig): name = 'ToDo_List'

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2a25f487bfd8611e6592ad193b80a4bc891928eb

150

py

Python

app/core/__init__.py

garybake/playwithfastapi

ab1d4f8aefb475932590f78fc230ab4a049c1c41

[ "MIT" ]

null

app/core/__init__.py

garybake/playwithfastapi

ab1d4f8aefb475932590f78fc230ab4a049c1c41

[ "MIT" ]

null

app/core/__init__.py

garybake/playwithfastapi

ab1d4f8aefb475932590f78fc230ab4a049c1c41

[ "MIT" ]

null

from app.core.config import settings # noqa: F401 from fastapi.templating import Jinja2Templates templates = Jinja2Templates(directory="templates")

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