xszheng2020/the_stack_dedup_python_hits_5 · Datasets at Hugging Face

403d3295d177b69f952dbbed91d9fcc96e28b4f6

85

py

Python

CodeWars/8 Kyu/Evil or Odious.py

anubhab-code/Competitive-Programming

de28cb7d44044b9e7d8bdb475da61e37c018ac35

[ "MIT" ]

null

CodeWars/8 Kyu/Evil or Odious.py

anubhab-code/Competitive-Programming

de28cb7d44044b9e7d8bdb475da61e37c018ac35

[ "MIT" ]

null

CodeWars/8 Kyu/Evil or Odious.py

anubhab-code/Competitive-Programming

de28cb7d44044b9e7d8bdb475da61e37c018ac35

[ "MIT" ]

null

def evil(n): return 'It\'s {}!'.format(('Evil', 'Odious')[bin(n).count('1') % 2])

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4049e05ba6976cf224f8a8a6ad81e8007c2cc11d

3,983

py

Python

unittests/LoggerTests.py

girlrilaz/blood-donation-prediction-3

065fb6936c6e930328d685b8bed1c4017bea4b60

[ "MIT" ]

null

unittests/LoggerTests.py

girlrilaz/blood-donation-prediction-3

065fb6936c6e930328d685b8bed1c4017bea4b60

[ "MIT" ]

null

unittests/LoggerTests.py

girlrilaz/blood-donation-prediction-3

065fb6936c6e930328d685b8bed1c4017bea4b60

[ "MIT" ]

null

#!/usr/bin/env python """ model tests """ import os, sys import csv import unittest from ast import literal_eval import pandas as pd sys.path.insert(1, os.path.join('..', os.getcwd())) ## import model specific functions and variables from src.logger import update_train_log, update_predict_log, update_processing_log class LoggerTest(unittest.TestCase): """ test the essential functionality """ def test_01_train(self): """ ensure log file is created """ log_file = os.path.join("logs", "model_train", "train-test.log") if os.path.exists(log_file): os.remove(log_file) ## update the log data_shape = (100,10) eval_test = {'rmse':0.5} runtime = "00:00:01" model_version = 0.1 model_version_note = "test model" update_train_log(data_shape,eval_test, runtime, model_version, model_version_note, test=True) self.assertTrue(os.path.exists(log_file)) def test_02_train(self): """ ensure that content can be retrieved from log file """ log_file = os.path.join("logs", "model_train", "train-test.log") ## update the log data_shape = (100,10) eval_test = {'rmse':0.5} runtime = "00:00:01" model_version = 0.1 model_version_note = "test model" update_train_log(data_shape,eval_test, runtime, model_version, model_version_note, test=True) df = pd.read_csv(log_file) logged_eval_test = [literal_eval(i) for i in df['eval_test'].copy()][-1] self.assertEqual(eval_test, logged_eval_test) def test_03_predict(self): """ ensure log file is created """ log_file = os.path.join("logs" ,"model_predict" ,"predict-test.log") if os.path.exists(log_file): os.remove(log_file) ## update the log y_pred = [0] y_proba = [0.6, 0.4] runtime = "00:00:02" model_version = 0.1 query = ['united_states', 24, 'aavail_basic', 8] update_predict_log(y_pred, y_proba, query, runtime, model_version, test=True) self.assertTrue(os.path.exists(log_file)) def test_04_predict(self): """ ensure that content can be retrieved from log file """ log_file = os.path.join("logs" , "model_predict" ,"predict-test.log") ## update the log y_pred = [0] y_proba = [0.6, 0.4] runtime = "00:00:02" model_version = 0.1 query = ['united_states', 24, 'aavail_basic', 8] update_predict_log(y_pred, y_proba, query, runtime, model_version, test=True) df = pd.read_csv(log_file) logged_y_pred = [literal_eval(i) for i in df['y_pred'].copy()][-1] self.assertEqual(y_pred,logged_y_pred) def test_05_process(self): """ ensure log file is created """ log_file = os.path.join("logs" ,"data_processing" , "process-test.log") if os.path.exists(log_file): os.remove(log_file) ## update the log filename = "iris.csv" update_processing_log(filename, test=True) self.assertTrue(os.path.exists(log_file)) def test_06_process(self): """ ensure that content can be retrieved from log file """ log_file = os.path.join("logs", "data_processing", "process-test.log") ## update the log filename = "iris.csv" update_processing_log(filename, test=True) df = pd.read_csv(log_file) filename_test = [i for i in df['filepath'].copy()][-1] self.assertEqual(filename, filename_test) ### Run the tests if __name__ == '__main__': unittest.main()

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407b5de3e06ac64e04b12a17a42d64f984326447

146

py

Python

plugin-builder-tool/printer.py

ChrisDryden/Aurora-Musical-Plugin

46b787b40a8fd1ba134b38f47da7a015fc7fddb5

[ "Apache-2.0" ]

48

2017-04-15T12:23:00.000Z

2021-12-11T14:32:36.000Z

plugin-builder-tool/printer.py

ChrisDryden/Aurora-Musical-Plugin

46b787b40a8fd1ba134b38f47da7a015fc7fddb5

[ "Apache-2.0" ]

3

2019-04-14T05:13:39.000Z

2022-02-07T00:57:22.000Z

plugin-builder-tool/printer.py

ChrisDryden/Aurora-Musical-Plugin

46b787b40a8fd1ba134b38f47da7a015fc7fddb5

[ "Apache-2.0" ]

13

2017-04-13T21:19:53.000Z

2021-01-20T17:05:43.000Z

def iprint(text): print ("INFO: " + str(text)) def dprint(desc, content): print ("-" * 20 + desc + "-" * 20) print (content) print ("-" * 40)

20.857143

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null

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5

dc173d6832388c8d951ce7f1936a03f2521fef9e

142

py

Python

third_party/python-pinyin/tests/utils.py

zh794390558/DeepSpeech

34178893327ad359cb816e55d7c66a10244fa08a

[ "Apache-2.0" ]

1

2021-05-14T23:27:13.000Z

third_party/python-pinyin/tests/utils.py

zh794390558/DeepSpeech

34178893327ad359cb816e55d7c66a10244fa08a

[ "Apache-2.0" ]

null

third_party/python-pinyin/tests/utils.py

zh794390558/DeepSpeech

34178893327ad359cb816e55d7c66a10244fa08a

[ "Apache-2.0" ]

null

#!/usr/bin/env python3 def has_module(module): try: __import__(module) return True except ImportError: pass

14.2

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5

9050cdcadaad170b489ac570e2669df4a1ef65c4

56

py

Python

apps/dataviz/models/__init__.py

Sasha-P/dataviz

ccef27b41636ce30bc9abbe8ae47a5ec807e2712

[ "MIT" ]

null

apps/dataviz/models/__init__.py

Sasha-P/dataviz

ccef27b41636ce30bc9abbe8ae47a5ec807e2712

[ "MIT" ]

null

apps/dataviz/models/__init__.py

Sasha-P/dataviz

ccef27b41636ce30bc9abbe8ae47a5ec807e2712

[ "MIT" ]

null

from .region import Region from .country import Country

18.666667

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0.821429

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5

9053a6594084a6fb1fe0b16ae9bd2d56c1fe2d29

5,866

py

Python

src/integrationtest/python/handler/iam_policy_tests.py

claytonbrown/aws-monocyte

8b029844781d7f1de929204f62c930345a5ecbf2

[ "Apache-2.0" ]

20

2015-02-17T15:08:44.000Z

2018-06-13T11:20:50.000Z

src/integrationtest/python/handler/iam_policy_tests.py

Scout24/aws-monocyte

8b029844781d7f1de929204f62c930345a5ecbf2

[ "Apache-2.0" ]

10

2015-04-28T12:00:33.000Z

2017-09-12T12:27:59.000Z

src/integrationtest/python/handler/iam_policy_tests.py

Scout24/aws-monocyte

8b029844781d7f1de929204f62c930345a5ecbf2

[ "Apache-2.0" ]

6

2015-05-17T22:37:17.000Z

2018-02-28T17:20:06.000Z

import json import logging import boto3 import unittest2 from mock import MagicMock from monocyte.handler import iam as iam_handler class IamAPolicyTests(unittest2.TestCase): def setUp(self): self.arn = '' logging.captureWarnings(True) self.iam_handler = iam_handler.IamPolicy(MagicMock) self.iam_handler.dry_run = True def tearDown(self): self._delete_policy(self.arn) def _create_policy(self, policy): iam = boto3.client('iam') policy_response = iam.create_policy( PolicyName='monocyteIntegrationTest', PolicyDocument=json.dumps(policy)) return policy_response['Policy']['Arn'] def _delete_policy(self, arn): iam = boto3.client('iam') iam.delete_policy(PolicyArn=arn) def _uniq(self, resources): uniq_names = [] for resource in resources: name = resource.wrapped['PolicyName'] if not name.startswith('monocyteIntegrationTest'): continue uniq_names.append(name) return uniq_names def test_right_policy_returns_no_failure(self): policy = { "Version": "2012-10-17", "Statement": { "Effect": "Allow", "Action": "s3:testaction", "Resource": "arn:aws:s3:::example_bucket" } } self.arn = self._create_policy(policy) unwanted_resource = self.iam_handler.fetch_unwanted_resources() self.assertEqual([], self._uniq(unwanted_resource)) def test_action_wildcard_policy_returns_failure(self): policy = { "Version": "2012-10-17", "Statement": { "Effect": "Allow", "Action": "*", "Resource": "arn:aws:s3:::example_bucket" } } self.arn = self._create_policy(policy) unwanted_resource = self.iam_handler.fetch_unwanted_resources() self.assertEqual(['monocyteIntegrationTest'], self._uniq(unwanted_resource)) def test_resource_wildcard_with_elb_policy_returns_no_failure(self): policy = { "Version": "2012-10-17", "Statement": [ { "Effect": "Allow", "Action": [ "elasticloadbalancing:*" ], "Resource": "*" } ] } self.arn = self._create_policy(policy) unwanted_resource = self.iam_handler.fetch_unwanted_resources() self.assertEqual([], self._uniq(unwanted_resource)) def test_resource_only_wildcard_with_returns_failure(self): policy = { "Version": "2012-10-17", "Statement": [ { "Effect": "Allow", "Action": [ "s3:*" ], "Resource": "*" } ] } self.arn = self._create_policy(policy) unwanted_resource = self.iam_handler.fetch_unwanted_resources() self.assertEqual([], self._uniq(unwanted_resource)) def test_resource_only_wildcard_list_returns_failure(self): policy = { "Version": "2012-10-17", "Statement": [ { "Effect": "Allow", "Action": [ "s3:*" ], "Resource": ["*"] } ] } self.arn = self._create_policy(policy) unwanted_resource = self.iam_handler.fetch_unwanted_resources() self.assertEqual([], self._uniq(unwanted_resource)) def test_action_with_wildcard_returns_no_failure(self): policy = { "Version": "2012-10-17", "Statement": [ { "Effect": "Allow", "Action": "s3:*", "Resource": "arn:aws:s3:::example_bucket" } ] } self.arn = self._create_policy(policy) unwanted_resource = self.iam_handler.fetch_unwanted_resources() self.assertEqual([], self._uniq(unwanted_resource)) def test_action_with_wildcard_returns_failure(self): policy = { "Version": "2012-10-17", "Statement": [ { "Effect": "Allow", "Action": "*", "Resource": "arn:aws:s3:::example_bucket" } ] } self.arn = self._create_policy(policy) unwanted_resource = self.iam_handler.fetch_unwanted_resources() self.assertEqual(['monocyteIntegrationTest'], self._uniq(unwanted_resource)) def test_wildcards_returns_failure(self): policy = { "Version": "2012-10-17", "Statement": [ { "Effect": "Allow", "Action": "*", "Resource": "*" } ] } self.arn = self._create_policy(policy) unwanted_resource = self.iam_handler.fetch_unwanted_resources() self.assertEqual(['monocyteIntegrationTest'], self._uniq(unwanted_resource)) def test_wildcards_as_list_returns_failure(self): policy = { "Version": "2012-10-17", "Statement": [ { "Effect": "Allow", "Action": ["*"], "Resource": ["*"] } ] } self.arn = self._create_policy(policy) unwanted_resource = self.iam_handler.fetch_unwanted_resources() self.assertEqual(['monocyteIntegrationTest'], self._uniq(unwanted_resource)) if __name__ == "__main__": unittest2.main()

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90bc5e1b61bdf10b03c6f21f48b3348bedbac5ed

176

py

Python

tencentApi/__init__.py

shenchucheng/tencentapi

36086052d6f154ea5f82793903e40320095be0c2

[ "MIT" ]

null

tencentApi/__init__.py

shenchucheng/tencentapi

36086052d6f154ea5f82793903e40320095be0c2

[ "MIT" ]

null

tencentApi/__init__.py

shenchucheng/tencentapi

36086052d6f154ea5f82793903e40320095be0c2

[ "MIT" ]

null

#!/usr/bin/env python3 # -*- coding:UTF-8 -*- # File Name: __init__.py # Author: Shechucheng # Created Time: 2020-05-21 17:30:35 from .api import Api from .cns import CnsApi

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5

90e166afb3e784bb1f416b296a790bd2e84f2c9a

8,993

py

Python

opportunity/om1_creating_datasets.py

mmalekzadeh/privacy-autoencoder

7d72a7122844c4b84275af085080faa034bfc1f1

[ "MIT" ]

18

2017-10-19T18:28:34.000Z

2021-09-03T12:26:48.000Z

opportunity/om1_creating_datasets.py

mmalekzadeh/privacy-autoencoder

7d72a7122844c4b84275af085080faa034bfc1f1

[ "MIT" ]

1

2018-04-11T07:31:22.000Z

2018-04-17T07:44:14.000Z

opportunity/om1_creating_datasets.py

mmalekzadeh/privacy-autoencoder

7d72a7122844c4b84275af085080faa034bfc1f1

[ "MIT" ]

9

2017-10-22T15:24:05.000Z

2021-04-07T15:48:23.000Z

#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created in September 2017 This module merges seperated files in the OPPORTUNITY Activity Recognition DataSet. It enables to create customized training and testing dataset. @author: mmalekzadeh """ import numpy as np ### Loading, Merging and Creating Training and Testing Datasets def merge_opp_data(number_of_features, **options): train_data = np.zeros((0,number_of_features)) test_data = np.zeros((0,number_of_features)) args_train = options.get("train") args_test = options.get("test") ## Subject 1 #### Drill if 10 in args_train: train_data = np.concatenate((train_data,np.loadtxt("S1-Drill.txt"))) print("Info: S1 Drill as train") if 10 in args_test: test_data = np.concatenate((test_data,np.loadtxt("S1-Drill.txt"))) print("Info: S1 Drill as test") #### ADL1 if 11 in args_train: train_data = np.concatenate((train_data,np.loadtxt("S1-ADL1.txt"))) print("Info: S1 ADL1 as train") if 11 in args_test: test_data = np.concatenate((test_data,np.loadtxt("S1-ADL1.txt"))) print("Info: S1 ADL1 as test") #### ADL2 if 12 in args_train: train_data = np.concatenate((train_data,np.loadtxt("S1-ADL2.txt"))) print("Info: S1 ADL2 as train") if 12 in args_test: test_data = np.concatenate((test_data,np.loadtxt("S1-ADL2.txt"))) print("Info: S1 ADL2 as test") #### ADL3 if 13 in args_train: train_data = np.concatenate((train_data,np.loadtxt("S1-ADL3.txt"))) print("Info: S1 ADL3 as train") if 13 in args_test: test_data = np.concatenate((test_data,np.loadtxt("S1-ADL3.txt"))) print("Info: S1 ADL3 as test") #### ADL4 if 14 in args_train: train_data = np.concatenate((train_data,np.loadtxt("S1-ADL4.txt"))) print("Info: S1 ADL4 as train") if 14 in args_test: test_data = np.concatenate((test_data,np.loadtxt("S1-ADL4.txt"))) print("Info: S1 ADL4 as test") #### ADL5 if 15 in args_train: train_data = np.concatenate((train_data,np.loadtxt("S1-ADL5.txt"))) print("Info: S1 ADL5 as train") if 15 in args_test: test_data = np.concatenate((test_data,np.loadtxt("S1-ADL5.txt"))) print("Info: S1 ADL5 as test") ## Subject 2 #### Drill if 20 in args_train: train_data = np.concatenate((train_data,np.loadtxt("S2-Drill.txt"))) print("Info: S2 Drill as train") if 20 in args_test: test_data = np.concatenate((test_data,np.loadtxt("S2-Drill.txt"))) print("Info: S2 Drill as test") #### ADL1 if 21 in args_train: train_data = np.concatenate((train_data,np.loadtxt("S2-ADL1.txt"))) print("Info: S2 ADL1 as train") if 21 in args_test: test_data = np.concatenate((test_data,np.loadtxt("S2-ADL1.txt"))) print("Info: S2 ADL1 as test") #### ADL2 if 22 in args_train: train_data = np.concatenate((train_data,np.loadtxt("S2-ADL2.txt"))) print("Info: S2 ADL2 as train") if 22 in args_test: test_data = np.concatenate((test_data,np.loadtxt("S2-ADL2.txt"))) print("Info: S2 ADL2 as test") #### ADL3 if 23 in args_train: train_data = np.concatenate((train_data,np.loadtxt("S2-ADL3.txt"))) print("Info: S2 ADL3 as train") if 23 in args_test: test_data = np.concatenate((test_data,np.loadtxt("S2-ADL3.txt"))) print("Info: S2 ADL3 as test") #### ADL4 if 24 in args_train: train_data = np.concatenate((train_data,np.loadtxt("S2-ADL4.txt"))) print("Info: S2 ADL4 as train") if 24 in args_test: test_data = np.concatenate((test_data,np.loadtxt("S2-ADL4.txt"))) print("Info: S2 ADL4 as test") #### ADL5 if 25 in args_train: train_data = np.concatenate((train_data,np.loadtxt("S2-ADL5.txt"))) print("Info: S2 ADL5 as train") if 25 in args_test: test_data = np.concatenate((test_data,np.loadtxt("S2-ADL5.txt"))) print("Info: S2 ADL5 as test") ## Subject 3 #### Drill if 30 in args_train: train_data = np.concatenate((train_data,np.loadtxt("S3-Drill.txt"))) print("Info: S3 Drill as train") if 30 in args_test: test_data = np.concatenate((test_data,np.loadtxt("S3-Drill.txt"))) print("Info: S3 Drill as test") #### ADL1 if 31 in args_train: train_data = np.concatenate((train_data,np.loadtxt("S3-ADL1.txt"))) print("Info: S3 ADL1 as train") if 31 in args_test: test_data = np.concatenate((test_data,np.loadtxt("S3-ADL1.txt"))) print("Info: S3 ADL1 as test") #### ADL2 if 32 in args_train: train_data = np.concatenate((train_data,np.loadtxt("S3-ADL2.txt"))) print("Info: S3 ADL2 as train") if 32 in args_test: test_data = np.concatenate((test_data,np.loadtxt("S3-ADL2.txt"))) print("Info: S3 ADL2 as test") #### ADL3 if 33 in args_train: train_data = np.concatenate((train_data,np.loadtxt("S3-ADL3.txt"))) print("Info: S3 ADL3 as train") if 33 in args_test: test_data = np.concatenate((test_data,np.loadtxt("S3-ADL3.txt"))) print("Info: S3 ADL3 as test") #### ADL4 if 34 in args_train: train_data = np.concatenate((train_data,np.loadtxt("S3-ADL4.txt"))) print("Info: S3 ADL4 as train") if 34 in args_test: test_data = np.concatenate((test_data,np.loadtxt("S3-ADL4.txt"))) print("Info: S3 ADL4 as test") #### ADL5 if 35 in args_train: train_data = np.concatenate((train_data,np.loadtxt("S3-ADL5.txt"))) print("Info: S3 ADL5 as train") if 35 in args_test: test_data = np.concatenate((test_data,np.loadtxt("S3-ADL5.txt"))) print("Info: S3 ADL5 as test") ## Subject 4 #### Drill if 40 in args_train: train_data = np.concatenate((train_data,np.loadtxt("S4-Drill.txt"))) print("Info: S4 Drill as train") if 40 in args_test: test_data = np.concatenate((test_data,np.loadtxt("S4-Drill.txt"))) print("Info: S4 Drill as test") #### ADL1 if 41 in args_train: train_data = np.concatenate((train_data,np.loadtxt("S4-ADL1.txt"))) print("Info: S4 ADL1 as train") if 41 in args_test: test_data = np.concatenate((test_data,np.loadtxt("S4-ADL1.txt"))) print("Info: S4 ADL1 as test") #### ADL2 if 42 in args_train: train_data = np.concatenate((train_data,np.loadtxt("S4-ADL2.txt"))) print("Info: S4 ADL2 as train") if 42 in args_test: test_data = np.concatenate((test_data,np.loadtxt("S4-ADL2.txt"))) print("Info: S4 ADL2 as test") #### ADL3 if 43 in args_train: train_data = np.concatenate((train_data,np.loadtxt("S4-ADL3.txt"))) print("Info: S4 ADL3 as train") if 43 in args_test: test_data = np.concatenate((test_data,np.loadtxt("S4-ADL3.txt"))) print("Info: S4 ADL3 as test") #### ADL4 if 44 in args_train: train_data = np.concatenate((train_data,np.loadtxt("S4-ADL4.txt"))) print("Info: S4 ADL4 as train") if 44 in args_test: test_data = np.concatenate((test_data,np.loadtxt("S4-ADL4.txt"))) print("Info: S4 ADL4 as test") #### ADL5 if 45 in args_train: train_data = np.concatenate((train_data,np.loadtxt("S4-ADL5.txt"))) print("Info: S4 ADL5 as train") if 45 in args_test: test_data = np.concatenate((test_data,np.loadtxt("S4-ADL5.txt"))) print("Info: S4 ADL5 as test") ### Saving Datasets ### np.save("training_dataset.npy", train_data) print("Info: Training Dataset with shape {} is saved".format(train_data.shape)) np.save("testing_dataset.npy", test_data) print("Info: Testing Dataset with shape {} is saved".format(test_data.shape)) return; ### Choosing Desired Files for Making Dataset """ Here you can choose your desired files to creat your training and testing dataset --> Example: merge_opp_data(number_of_features = 116, train =[10,11,12,13,14], test=[15]) 0 is for Drills and 1,2,3,4,5 are respectively for ADLs e.g. 23 means S2-ADL3 (data of activity #3 from subject #2) Each entry of OPPORTUNITY Dataset contains 116 columns [time, ...113 sensory values... , Locomotion, Gestures] """ merge_opp_data(number_of_features = 116, train = [10,11,12,13,14], test = [15] )

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0

null

0

5

90f41cf8aa879c5a3d298e9ffa2ab004222a4cdf

442

py

Python

clickhouse_orm/__init__.py

SuadeLabs/infi.clickhouse_orm

cd724c213224583bff5e78cc63221ecec769c317

[ "BSD-3-Clause" ]

3

2022-01-07T15:50:59.000Z

2022-01-20T02:21:46.000Z

clickhouse_orm/__init__.py

SuadeLabs/infi.clickhouse_orm

cd724c213224583bff5e78cc63221ecec769c317

[ "BSD-3-Clause" ]

3

2021-07-28T21:55:25.000Z

2021-08-14T11:30:08.000Z

clickhouse_orm/__init__.py

SuadeLabs/infi.clickhouse_orm

cd724c213224583bff5e78cc63221ecec769c317

[ "BSD-3-Clause" ]

null

from inspect import isclass from .database import * # noqa: F401, F403 from .engines import * # noqa: F401, F403 from .fields import * # noqa: F401, F403 from .funcs import * # noqa: F401, F403 from .migrations import * # noqa: F401, F403 from .models import * # noqa: F401, F403 from .query import * # noqa: F401, F403 from .system_models import * # noqa: F401, F403 __all__ = [c.__name__ for c in locals().values() if isclass(c)]

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null

0

1

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1

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5

2902d2c63c3ab22b1b0c50e445448c8975632c71

158

py

Python

audio/__init__.py

TWoolhouse/Libraries

26079ed387cb800cb97f20980720ae094008c7bf

[ "MIT" ]

1

2020-10-11T15:34:56.000Z

audio/__init__.py

TWoolhouse/Libraries

26079ed387cb800cb97f20980720ae094008c7bf

[ "MIT" ]

null

audio/__init__.py

TWoolhouse/Libraries

26079ed387cb800cb97f20980720ae094008c7bf

[ "MIT" ]

null

from .base import Status from .controller import Controller from .stream import Gate, Queue, Mixer, Buffer from .track import File from . import proc, ffmpeg

26.333333

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0.791139

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null

0

1

0

1

0

1

0

5

291dca5c431f4ad2266da0bbae1420e63a006364

246

py

Python

casperlabs_client/key_holders/__init__.py

CasperLabs/client-py

12955d2b88bc439f94a1cc33a063fda0c20ef8ab

[ "Apache-2.0" ]

2

2021-05-12T06:43:45.000Z

2021-10-02T11:45:41.000Z

casperlabs_client/key_holders/__init__.py

CasperLabs/client-py

12955d2b88bc439f94a1cc33a063fda0c20ef8ab

[ "Apache-2.0" ]

24

2020-06-30T14:55:20.000Z

2021-01-05T18:18:29.000Z

casperlabs_client/key_holders/__init__.py

CasperLabs/client-py

12955d2b88bc439f94a1cc33a063fda0c20ef8ab

[ "Apache-2.0" ]

1

2020-06-22T15:32:38.000Z

# -*- coding: utf-8 -*- from .key_holder import KeyHolder # noqa:F401 from .ed25519 import ED25519Key # noqa:F401 from .secp256k1 import SECP256K1Key # noqa:F401 from .helper_methods import class_from_algorithm, key_holder_object # noqa:F401

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246

5.411765

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null

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0

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0

1

0

5

292fa2b5469828f652f7b986eea97d1f5ae9e6e5

2,696

py

Python

tests/selenium/test_edit.py

adament/dash-table

878f02cada45ff76d32d4b712f5ef3c23447fa52

[ "MIT" ]

null

tests/selenium/test_edit.py

adament/dash-table

878f02cada45ff76d32d4b712f5ef3c23447fa52

[ "MIT" ]

null

tests/selenium/test_edit.py

adament/dash-table

878f02cada45ff76d32d4b712f5ef3c23447fa52

[ "MIT" ]

null

import dash from utils import get_props, read_write_modes from dash_table import DataTable import pytest def get_app(props=dict()): app = dash.Dash(__name__) baseProps = get_props() baseProps.update(props) app.layout = DataTable(**baseProps) return app @pytest.mark.parametrize("props", read_write_modes) def test_edit001_can_delete_dropdown(test, props): test.start_server(get_app(props)) target = test.table("table") cell = target.cell(0, "bbb") cell.click() assert cell.is_dropdown() cell.get().find_element_by_css_selector(".Select-clear").click() assert cell.get().find_element_by_css_selector(".Select-placeholder") is not None assert test.get_log_errors() == [] @pytest.mark.parametrize("props", read_write_modes) def test_edit002_can_delete_dropown_and_set(test, props): test.start_server(get_app(props)) target = test.table("table") cell = target.cell(0, "bbb") cell.click() assert cell.is_dropdown() cell.get().find_element_by_css_selector(".Select-clear").click() assert cell.get().find_element_by_css_selector(".Select-placeholder") is not None cell.get().find_element_by_css_selector(".Select-arrow").click() cell.get().find_element_by_css_selector(".Select-option").click() assert len(cell.get().find_elements_by_css_selector(".Select-placeholder")) == 0 assert test.get_log_errors() == [] @pytest.mark.parametrize("props", read_write_modes) def test_edit003_can_edit_dropdown(test, props): test.start_server(get_app(props)) target = test.table("table") cell = target.cell(0, "bbb") cell.get().find_element_by_css_selector(".Select-arrow").click() cell.get().find_element_by_css_selector(".Select-arrow").click() for i in range(len(cell.get().find_elements_by_css_selector(".Select-option"))): option = cell.get().find_elements_by_css_selector(".Select-option")[i] value = option.get_attribute("innerHTML") option.click() assert ( cell.get() .find_element_by_css_selector(".Select-value-label") .get_attribute("innerHTML") == value ) cell.get().find_element_by_css_selector(".Select-arrow").click() assert test.get_log_errors() == [] @pytest.mark.parametrize("props", read_write_modes) def test_edit004_edit_focused(test, props): test.start_server(get_app(props)) target = test.table("table") c1 = target.cell(3, 1) c1.click() test.send_keys("abc") # Selected everything again on click c1.click() test.send_keys("def") assert c1.get_text() == "def" assert test.get_log_errors() == []

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0.600229

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102

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0.15873

0

null

0

1

0

null

0

5

293dc94c95075ceaed89040d9506c9c696678102

37

py

Python

__init__.py

yombo/module-amazonalexa

83450a6addd99b46fbbdf004b55654f6427af363

[ "Apache-2.0" ]

null

__init__.py

yombo/module-amazonalexa

83450a6addd99b46fbbdf004b55654f6427af363

[ "Apache-2.0" ]

null

__init__.py

yombo/module-amazonalexa

83450a6addd99b46fbbdf004b55654f6427af363

[ "Apache-2.0" ]

null

from .amazonalexa import AmazonAlexa

18.5

36

0.864865

4

37

8

0.75

0

0.108108

37

1

37

0.969697

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

294030a6401eee4eebf44da6b23dfe9bf319f21e

125

py

Python

Plugins/GUI/Script_Window/__init__.py

bvbohnen/X4_Customizer

6f865008690916a66a44c97331d9a2692baedb35

[ "MIT" ]

25

2018-12-10T12:52:11.000Z

2022-01-29T14:42:57.000Z

Plugins/GUI/Script_Window/__init__.py

bvbohnen/X4_Customizer

6f865008690916a66a44c97331d9a2692baedb35

[ "MIT" ]

4

2019-08-01T19:09:11.000Z

2022-01-02T01:47:42.000Z

Plugins/GUI/Script_Window/__init__.py

bvbohnen/X4_Customizer

6f865008690916a66a44c97331d9a2692baedb35

[ "MIT" ]

6

2019-02-16T08:39:04.000Z

2021-12-21T06:11:58.000Z

from .Widget_Plugins import Widget_Plugins from .Widget_Script import Widget_Script from .Script_Window import Script_Window

31.25

42

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18

125

5.777778

0.333333

0.192308

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0.096

125

4

43

31.25

0.920354

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true

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1

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null

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1

0

1

0

1

0

5

298238f1eb0e9374f66c555c382308fbbc4f9d19

35

py

Python

__init__.py

rmanocha/oaklibapi

e59b57b4e63fc792c5f8cfe05e1242daf5cc7b2a

[ "Apache-2.0" ]

null

__init__.py

rmanocha/oaklibapi

e59b57b4e63fc792c5f8cfe05e1242daf5cc7b2a

[ "Apache-2.0" ]

null

__init__.py

rmanocha/oaklibapi

e59b57b4e63fc792c5f8cfe05e1242daf5cc7b2a

[ "Apache-2.0" ]

null

from .api import OaklandLibraryAPI

17.5

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0.857143

4

35

7.5

1

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35

1

35

0.967742

0

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true

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1

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null

0

1

0

null

0

1

0

1

0

5

463f1f744567d40378ed143cb7a34b6c847f14be

122

py

Python

thermoplotting/split/__init__.py

Van-der-Ven-Group/thermoplotting

d826d728f406896b7a56207f3f4e9b4176de0e97

[ "MIT" ]

10

2015-04-28T18:53:00.000Z

2020-09-23T13:29:07.000Z

thermoplotting/split/__init__.py

Van-der-Ven-Group/thermoplotting

d826d728f406896b7a56207f3f4e9b4176de0e97

[ "MIT" ]

1

2019-05-20T19:20:24.000Z

thermoplotting/split/__init__.py

goirijo/thermoplotting

d826d728f406896b7a56207f3f4e9b4176de0e97

[ "MIT" ]

4

2015-08-03T18:36:46.000Z

2022-03-30T23:13:04.000Z

from __future__ import absolute_import from . import clustcompare from .subtract import Subtracter from .detect import *

20.333333

38

0.827869

15

122

6.4

0.533333

0

0.139344

122

5

39

24.4

0.914286

0

1

0

true

0

1

0

1

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1

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null

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1

0

null

0

1

0

1

0

1

0

5

4668f507f66410a970717cd4cdc1307cb61a9b08

361

py

Python

monitor/models.py

davcastroruiz/django-ssh-monitor

c0d55076cc4a3312ebd7d706d0fc15c78f8ed03b

[ "MIT" ]

4

2019-03-09T00:14:47.000Z

2020-06-01T12:29:51.000Z

monitor/models.py

davcastroruiz/django-ssh-monitor

c0d55076cc4a3312ebd7d706d0fc15c78f8ed03b

[ "MIT" ]

null

monitor/models.py

davcastroruiz/django-ssh-monitor

c0d55076cc4a3312ebd7d706d0fc15c78f8ed03b

[ "MIT" ]

null

from django.db import models from django.core.urlresolvers import reverse # Create your models here. class Connection(models.Model): alias = models.CharField(max_length=100) username = models.CharField(max_length=1000) password = models.CharField(max_length=250) port = models.CharField(max_length=4) ip = models.CharField(max_length=100)

30.083333

48

0.761773

49

361

5.510204

0.530612

0.277778

0.333333

0.444444

0.2

0

0.045307

0.144044

361

11

49

32.818182

0.828479

0.066482

0

1

0

false

0.125

0.25

0

1

0

null

1

0

null

0

1

0

1

0

5

46a0a1d76b956a0007fed1efba96adf4fece0f56

132

py

Python

pythonrc.py

l-zeuch/doots

5a861f96cac67410341e1d4fde09e7dadf72c9ef

[ "BSD-3-Clause" ]

1

2022-01-13T20:18:00.000Z

pythonrc.py

l-zeuch/doots

5a861f96cac67410341e1d4fde09e7dadf72c9ef

[ "BSD-3-Clause" ]

null

pythonrc.py

l-zeuch/doots

5a861f96cac67410341e1d4fde09e7dadf72c9ef

[ "BSD-3-Clause" ]

null

# Do not create a history file in $HOME. # (I really hate clutter) import readline readline.write_history_file = lambda *args: None

26.4

48

0.765152

21

132

4.714286

0.857143

0.222222

0

0.159091

132

4

49

33

0.891892

0.469697

0

1

0

true

0

0.5

0

0.5

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null

1

0

1

0

null

0

1

0

1

0

5

d3b3c8c1518fb0fe3942233ed5781b695e4dd1fb

71

py

Python

test_world.py

schmiermax/Coursera_Capstone

fdee32cb477688ebc0b466872f90333018777c94

[ "BSD-3-Clause" ]

null

test_world.py

schmiermax/Coursera_Capstone

fdee32cb477688ebc0b466872f90333018777c94

[ "BSD-3-Clause" ]

null

test_world.py

schmiermax/Coursera_Capstone

fdee32cb477688ebc0b466872f90333018777c94

[ "BSD-3-Clause" ]

null

import numpy as np print("Hello World!") print(np.linspace(0.1,0.5,3))

17.75

29

0.704225

15

71

3.333333

0.8

0

0.078125

0.098592

71

4

29

17.75

0.703125

0

0.166667

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

d3d3080557da75b2433b2a85b5e25e41d759eaec

503

py

Python

chainerrl/wrappers/__init__.py

mmilk1231/chainerrl

d351f9f5d1bb1dbaf98c8c629312884eb940de7a

[ "MIT" ]

1

2019-08-19T15:23:54.000Z

chainerrl/wrappers/__init__.py

mmilk1231/chainerrl

d351f9f5d1bb1dbaf98c8c629312884eb940de7a

[ "MIT" ]

null

chainerrl/wrappers/__init__.py

mmilk1231/chainerrl

d351f9f5d1bb1dbaf98c8c629312884eb940de7a

[ "MIT" ]

1

2019-08-08T19:13:53.000Z

from chainerrl.wrappers.cast_observation import CastObservation # NOQA from chainerrl.wrappers.cast_observation import CastObservationToFloat32 # NOQA from chainerrl.wrappers.continuing_time_limit import ContinuingTimeLimit # NOQA from chainerrl.wrappers.randomize_action import RandomizeAction # NOQA from chainerrl.wrappers.render import Render # NOQA from chainerrl.wrappers.scale_reward import ScaleReward # NOQA from chainerrl.wrappers.vector_frame_stack import VectorFrameStack # NOQA

38.692308

80

0.850895

57

503

7.368421

0.421053

0.216667

0.35

0.357143

0.2

0

0.004454

0.107356

503

12

81

41.916667

0.930958

0.067594

0

1

0

true

0

1

0

1

0

null

1

0

null

0

1

0

1

0

5

3101cc8fc23245d01eb02f8ed49defcc45d2f570

335

py

Python

tests/hubstorage/test_utils.py

pardo/python-scrapinghub

13915e3b9549c7e8773f4e9f0481399ca537d4fd

[ "BSD-3-Clause" ]

163

2015-01-23T12:27:14.000Z

2022-03-01T07:53:49.000Z

tests/hubstorage/test_utils.py

pardo/python-scrapinghub

13915e3b9549c7e8773f4e9f0481399ca537d4fd

[ "BSD-3-Clause" ]

132

2015-01-14T14:23:56.000Z

2022-03-18T14:21:30.000Z

tests/hubstorage/test_utils.py

pardo/python-scrapinghub

13915e3b9549c7e8773f4e9f0481399ca537d4fd

[ "BSD-3-Clause" ]

49

2015-01-14T13:48:38.000Z

2022-01-20T17:09:44.000Z

""" Test utils module. """ from scrapinghub.hubstorage.utils import sizeof_fmt def test_sizeof_fmt(): assert sizeof_fmt(1000) == '1000 B' assert sizeof_fmt(1024) == '1 KiB' assert sizeof_fmt(1024 * 1024) == '1 MiB' assert sizeof_fmt(1024 * 1024 + 100) == '1 MiB' assert sizeof_fmt(1024 * 1024 * 1024) == '1 GiB'

23.928571

52

0.653731

49

335

4.306122

0.387755

0.298578

0.35545

0.36019

0.364929

0.255924

0

0.176692

0.20597

335

13

53

25.769231

0.616541

0.053731

0

0.084142

0

0.714286

1

0.142857

true

0

0.142857

0

0.285714

0

null

1

0

null

0

1

0

1

0

5

3117377632af5fbe2773cd137b55bd453e369ca7

122

py

Python

DMOJ/Uncategorized/VPEX_P1_War_on_Two_Fronts.py

Togohogo1/pg

ee3c36acde47769c66ee13a227762ee677591375

[ "MIT" ]

null

DMOJ/Uncategorized/VPEX_P1_War_on_Two_Fronts.py

Togohogo1/pg

ee3c36acde47769c66ee13a227762ee677591375

[ "MIT" ]

1

2021-10-14T18:26:56.000Z

DMOJ/Uncategorized/VPEX_P1_War_on_Two_Fronts.py

Togohogo1/pg

ee3c36acde47769c66ee13a227762ee677591375

[ "MIT" ]

1

2021-08-06T03:39:55.000Z

a = list(map(int, input().split())) b = list(map(int, input().split())) print(max((sum(a) - min(a)), (sum(b) - min(b))))

24.4

48

0.540984

22

122

3

0.5

0.212121

0.30303

0.454545

0.606061

0

0.122951

122

4

49

30.5

0.616822

0

1

0

false

0

0.333333

1

0

null

1

0

1

0

null

0

5

3164fa3cfc1bb9ee2d2dfc1adfbd4307355068b5

402

py

Python

instapy_bot/bot/utils/photo.py

7aske/instapy-bot

5bcd6fdd3e54671a91f1687f6fd77fe90ce04e99

[ "RSA-MD" ]

9

2019-03-28T21:00:48.000Z

2021-11-16T01:15:01.000Z

instapy_bot/bot/utils/photo.py

7aske/instapy-bot

5bcd6fdd3e54671a91f1687f6fd77fe90ce04e99

[ "RSA-MD" ]

1

2021-03-01T22:43:34.000Z

2021-03-19T20:03:42.000Z

instapy_bot/bot/utils/photo.py

7aske/instapy-bot

5bcd6fdd3e54671a91f1687f6fd77fe90ce04e99

[ "RSA-MD" ]

5

2019-10-19T10:27:41.000Z

2022-03-20T12:31:03.000Z

class Photo: path = "" caption = "" def __init__(self, path, caption=""): self.path = path self.caption = caption def set_caption(self, caption): self.caption = caption def get_caption(self): return self.caption def __repr__(self) -> str: return "Photo path='{path}' caption='{caption}'".format(path=self.path, caption=self.caption)

22.333333

101

0.60199

47

402

4.93617

0.276596

0.237069

0.232759

0.163793

0

0.263682

402

17

102

23.647059

0.783784

0

0.166667

0

0.097257

0

1

0.333333

false

0

0.166667

0.75

0

null

1

0

null

0

1

0

1

0

5

316c470400776fa8ef9a2f765daa95ccb241794f

39

py

Python

web/env/Main10003/Main10003.py

joney000/Online-Code-Checker-and-Compiler

30ab1741a4c3ad47fc3f15eb7dce2d79cd57f6f7

[ "MIT" ]

19

2017-02-06T01:12:51.000Z

2022-02-05T21:32:24.000Z

web/env/Main10003/Main10003.py

joney000/Online-Code-Checker-and-Compiler-in-Java-CodeOj-codeoj.com-

30ab1741a4c3ad47fc3f15eb7dce2d79cd57f6f7

[ "MIT" ]

1

2017-04-07T10:26:53.000Z

2017-04-07T10:47:17.000Z

web/env/Main10003/Main10003.py

joney000/Online-Code-Checker-and-Compiler-in-Java-CodeOj-codeoj.com-

30ab1741a4c3ad47fc3f15eb7dce2d79cd57f6f7

[ "MIT" ]

10

2017-12-22T21:39:36.000Z

2020-09-24T07:25:52.000Z

print 1 print 2 print 3 print "\n\n"

9.75

12

0.641026

9

39

2.777778

0.555556

0

0.103448

0.25641

39

4

12

9.75

0.758621

0

0.108108

0

null

0

null

1

0

null

0

1

0

null

0

1

0

1

0

5

318bbf6d0c0bc27d0b865b9ae29abc0b75ef9b1e

91

py

Python

src/panoptes/pocs/filterwheel/__init__.py

ASTROGBAE/POCS

ddbc716ba375be92c7af1c8ebd536f9cdbc899da

[ "MIT" ]

69

2015-08-27T01:17:26.000Z

2022-01-05T19:11:09.000Z

src/panoptes/pocs/filterwheel/__init__.py

ASTROGBAE/POCS

ddbc716ba375be92c7af1c8ebd536f9cdbc899da

[ "MIT" ]

1,094

2016-01-19T18:18:06.000Z

2022-03-17T04:28:38.000Z

src/panoptes/pocs/filterwheel/__init__.py

ASTROGBAE/POCS

ddbc716ba375be92c7af1c8ebd536f9cdbc899da

[ "MIT" ]

65

2015-08-27T01:17:28.000Z

2021-02-24T04:12:03.000Z

from panoptes.pocs.filterwheel.filterwheel import AbstractFilterWheel # pragma: no flakes

45.5

90

0.846154

10

91

7.7

0.9

0

0.098901

91

1

91

0.939024

0.186813

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

319312bf66a0ba2a9649797b4a038a9c9b296e04

422

py

Python

instagram_scraper/model/base_model.py

luengwaiban/instagram-python-scraper

d3427afba9865d914a9b5daaafde9f2981ebf1c3

[ "MIT" ]

139

2019-06-02T16:19:06.000Z

2021-09-08T08:16:43.000Z

instagram_scraper/model/base_model.py

luengwaiban/instagram-python-scraper

d3427afba9865d914a9b5daaafde9f2981ebf1c3

[ "MIT" ]

4

2019-06-10T02:06:10.000Z

2020-07-07T04:45:59.000Z

instagram_scraper/model/base_model.py

luengwaiban/instagram-python-scraper

d3427afba9865d914a9b5daaafde9f2981ebf1c3

[ "MIT" ]

16

2019-06-07T10:02:49.000Z

2021-06-03T20:41:33.000Z

# -*- coding:utf-8 -*- from instagram_scraper.model.initializer_model import InitializerModel class BaseModel(InitializerModel): def __init__(self, props=None): if not hasattr(self, '_init_properties_map') or not self._init_properties_map: self._init_properties_map = {} super(BaseModel, self).__init__(props) def get_columns(self): return self._init_properties_map.keys()

28.133333

86

0.71327

51

422

5.45098

0.54902

0.143885

0.258993

0.302158

0

0.002907

0.184834

422

14

87

30.142857

0.805233

0.047393

0

0.05

0

1

0.25

false

0

0.125

0.625

0

null

0

1

0

null

0

1

0

1

0

5

9eefcc124d1ad3a0354290dbfff5ee54f8f34d17

215

py

Python

src/meltano/core/plugin/singer/__init__.py

siilats/meltano

404605c83f441c3fc2b729e26416c6caa8b0ed0b

[ "MIT" ]

122

2021-06-21T17:30:29.000Z

2022-03-25T06:21:38.000Z

src/meltano/core/plugin/singer/__init__.py

siilats/meltano

404605c83f441c3fc2b729e26416c6caa8b0ed0b

[ "MIT" ]

null

src/meltano/core/plugin/singer/__init__.py

siilats/meltano

404605c83f441c3fc2b729e26416c6caa8b0ed0b

[ "MIT" ]

21

2021-06-22T10:08:15.000Z

2022-03-18T08:57:02.000Z

from typing import Dict from meltano.core.plugin import PluginType from .base import * from .catalog import ListExecutor, SelectExecutor from .tap import SingerTap from .target import BookmarkWriter, SingerTarget

23.888889

49

0.827907

27

215

6.592593

0.62963

0

0.130233

215

8

50

26.875

0.951872

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

9ef0f1fdf9d26c0410542a2851de60d182257f05

7,045

py

Python

hood/tests.py

arondasamuel123/Neighbourhood

31eaa661f6dbe2c063303c66d06ddbaafb05ae69

[ "MIT" ]

null

hood/tests.py

arondasamuel123/Neighbourhood

31eaa661f6dbe2c063303c66d06ddbaafb05ae69

[ "MIT" ]

4

2021-03-19T01:12:10.000Z

2021-06-10T18:46:11.000Z

hood/tests.py

arondasamuel123/Neighbourhood

31eaa661f6dbe2c063303c66d06ddbaafb05ae69

[ "MIT" ]

null

from django.test import TestCase from .models import User, Neighbourhood, Profile, Post,Business, Department class UserTestCase(TestCase): def setUp(self): self.super_admin = User(username="arondasamuel123",email="arondasamuel123@gmail.com",name="Samuel Aronda", role_type="SUPER ADMIN",is_superuser=True, is_staff=True, is_active=True) self.admin_user = User(username="jack123",email="jack@gmail.com",name="Jack Doe", role_type="ADMIN",is_superuser=False, is_staff=True, is_active=True) self.user_one = User(username="john123", email="john@gmail.com", name="John Doe", role_type="USER",is_superuser=False, is_staff=False, is_active=True) def test_save_superadmin(self): self.super_admin.save_sadmin() users = User.objects.all() self.assertTrue(len(users) > 0) def test_save_admin(self): self.admin_user.save_admin() users = User.objects.all() self.assertTrue(len(users)> 0) def test_save_user(self): self.user_one.save_user() users = User.objects.all() self.assertTrue(len(users) > 0) class NeighbourhoodTestCase(TestCase): def setUp(self): self.admin_user = User(username="jack123",email="jack@gmail.com",name="Jack Doe", role_type="ADMIN",is_superuser=False, is_staff=True, is_active=True) self.hood_one = Neighbourhood(neighbourhood_name="Langata Estate", neighbourhood_location="Langata", occupants="100",admin_id=self.admin_user) def test_save_neighbourhood(self): self.admin_user.save_admin() self.hood_one.save_hood() hoods = Neighbourhood.objects.all() self.assertTrue(len(hoods)> 0) def test_delete_neighbourhood(self): self.admin_user.save_admin() self.hood_one.save_hood() self.hood_one.delete_hood() hoods = Neighbourhood.objects.all() self.assertTrue(len(hoods) == 0) def test_get_hoof_id(self): self.admin_user.save_admin() self.hood_one.save_hood() self.hood_one.get_hood_id(self.hood_one.id) hoods = Neighbourhood.objects.all() self.assertTrue(len(hoods) > 0) def test_update_hood_occupants(self): self.admin_user.save_admin() self.hood_one.save_hood() self.hood_one.get_hood_id(self.hood_one.id) self.hood_one.update_occupants("200") self.assertTrue(self.hood_one.occupants=="200") class ProfileTestCase(TestCase): def setUp(self): self.admin_user = User(username="jack123",email="jack@gmail.com",name="Jack Doe", role_type="ADMIN",is_superuser=False, is_staff=True, is_active=True) self.user_one = User(username="john123", email="john@gmail.com", name="John Doe", role_type="USER",is_superuser=False, is_staff=False, is_active=True) self.hood_two = Neighbourhood(neighbourhood_name="Langata Estate", neighbourhood_location="Langata", occupants="100",admin_id=self.admin_user) self.profile_one = Profile(bio="I love my neighbourhoood", neighbourhood=self.hood_two, general_location="Langata", user=self.user_one) def test_save_profile(self): self.admin_user.save_admin() self.user_one.save_user() self.hood_two.save_hood() self.profile_one.save_profile() profiles = Profile.objects.all() self.assertTrue(len(profiles) > 0) def test_delete_profile(self): self.admin_user.save_admin() self.user_one.save_user() self.hood_two.save_hood() self.profile_one.save_profile() self.profile_one.delete_profile() profiles = Profile.objects.all() self.assertTrue(len(profiles)==0) def test_get_prof_id(self): self.admin_user.save_admin() self.user_one.save_user() self.hood_two.save_hood() self.profile_one.save_profile() self.profile_one.get_prof_id(self.profile_one.id) profiles = Profile.objects.all() self.assertTrue(len(profiles) > 0) def test_update_bio(self): self.admin_user.save_admin() self.user_one.save_user() self.hood_two.save_hood() self.profile_one.save_profile() self.profile_one.update_bio("This is a new bio") self.assertTrue(self.profile_one.bio=="This is a new bio") class PostModelTestCase(TestCase): def setUp(self): self.user_one = User(username="john123", email="john@gmail.com", name="John Doe", role_type="USER",is_superuser=False, is_staff=False, is_active=True) self.post_one = Post(post="I love my neighbourhood", user=self.user_one) def test_save_post(self): self.user_one.save_user() self.post_one.save_post() posts = Post.objects.all() self.assertTrue(len(posts)> 0) class BusinessModelTestCase(TestCase): def setUp(self): self.user_one = User(username="john123", email="john@gmail.com", name="John Doe", role_type="USER",is_superuser=False, is_staff=False, is_active=True) self.admin_user = User(username="jack123",email="jack@gmail.com",name="Jack Doe", role_type="ADMIN",is_superuser=False, is_staff=True, is_active=True) self.hood_two = Neighbourhood(neighbourhood_name="Langata Estate", neighbourhood_location="Langata", occupants="100",admin_id=self.admin_user) self.business_one = Business(business_name="Elps Hardware Store", business_email="elps@gmail.com",user=self.user_one, neighbourhood=self.hood_two) def test_save_business(self): self.user_one.save_user() self.admin_user.save_admin() self.hood_two.save_hood() self.business_one.save_business() businesses = Business.objects.all() self.assertTrue(len(businesses)> 0) def test_delete_business(self): self.user_one.save_user() self.admin_user.save_admin() self.hood_two.save_hood() self.business_one.save_business() self.business_one.delete_business() businesses = Business.objects.all() self.assertTrue(len(businesses)== 0) class DepartmentModelTestCase(TestCase): def setUp(self): self.admin_user = User(username="jack123",email="jack@gmail.com",name="Jack Doe", role_type="ADMIN",is_superuser=False, is_staff=True, is_active=True) self.hood_two = Neighbourhood(neighbourhood_name="Langata Estate", neighbourhood_location="Langata", occupants="100",admin_id=self.admin_user) self.dept_one = Department(contact_number="0791019910", neighbourhood=self.hood_two, dept_type="health", dept_name="Langata Hospital") def test_save_department(self): self.admin_user.save_admin() self.hood_two.save_hood() self.dept_one.save_dept() departments = Department.objects.all() self.assertTrue(len(departments) > 0)

43.757764

188

0.669269

920

7,045

4.882609

0.1

0.044524

0.060775

0.069457

0.757569

0.740205

0.722173

0.702137

0.700356

0.691006

0

0.013274

0.208659

7,045

161

189

43.757764

0.792466

0

0.609756

0

0.088135

0.003548

0

0.121951

1

0.170732

false

0

0.01626

0

0.235772

0

null

0

1

0

null

0

5

9ef5e410e2ad41ed19824f3d5a0e88f29628bf16

96

py

Python

public_identifiers/__init__.py

strange-dv/django-public-identifiers

1d3f7752b16f48d1004328b5dad7acf6e83a9703

[ "MIT" ]

null

public_identifiers/__init__.py

strange-dv/django-public-identifiers

1d3f7752b16f48d1004328b5dad7acf6e83a9703

[ "MIT" ]

null

public_identifiers/__init__.py

strange-dv/django-public-identifiers

1d3f7752b16f48d1004328b5dad7acf6e83a9703

[ "MIT" ]

null

from .fields import ISBNField, DOIField, ISSNField __all__ = [ISBNField, DOIField, ISSNField]

19.2

50

0.78125

10

96

7.1

0.7

0.478873

0.732394

0

0.135417

96

4

51

24

0.855422

0

1

0

false

0

0.5

0

0.5

0

1

0

null

1

0

1

0

null

0

1

0

5

b414aaa8e33dd54606551330d3484038d8b2d171

61

py

Python

src/authub/asgi.py

fantix/authub

1f8a30fe32c579e556d2b962f258e0f99527a006

[ "BSD-3-Clause" ]

null

src/authub/asgi.py

fantix/authub

1f8a30fe32c579e556d2b962f258e0f99527a006

[ "BSD-3-Clause" ]

null

src/authub/asgi.py

fantix/authub

1f8a30fe32c579e556d2b962f258e0f99527a006

[ "BSD-3-Clause" ]

null

from .http import get_http_app application = get_http_app()

15.25

30

0.803279

10

61

4.5

0.6

0.311111

0.444444

0

0.131148

61

3

31

20.333333

0.849057

0

1

0

false

0

0.5

0

0.5

0

1

0

null

1

0

1

0

null

0

1

0

5

b4294423daf31925bfc9af2bc09086e3cf54eb55

718

py

Python

shop/views.py

adarshkesarwani006/AB-Site

d330fe0adf7e6c3acc54101bac4a609b1cafc402

[ "Info-ZIP" ]

null

shop/views.py

adarshkesarwani006/AB-Site

d330fe0adf7e6c3acc54101bac4a609b1cafc402

[ "Info-ZIP" ]

null

shop/views.py

adarshkesarwani006/AB-Site

d330fe0adf7e6c3acc54101bac4a609b1cafc402

[ "Info-ZIP" ]

null

from django.shortcuts import render # Create your views here. def index(request): return render(request,'index.html') def dehatimotor(request): return render(request,'dehatimotor.html') def motor(request): return render(request,'motor.html') def sheetbody(request): return render(request,'sheetbody.html') def indiamark(request): return render(request,'indiamark.html') def rollpipe(request): return render(request,'rollpipe.html') def submersible(request): return render(request,'submersible.html') def pump(request): return render(request,'pump.html') def cowmat(request): return render(request,'cowmat.html') def blog(request): return render(request,'blog.html')

20.514286

45

0.729805

89

718

5.88764

0.258427

0.248092

0.362595

0.496183

0

0.140669

718

34

46

21.117647

0.849271

0.032033

0

0.176301

0

1

0.47619

false

0

0.047619

0.47619

1

0

null

1

0

null

0

1

0

1

0

5

b435bb9d9c66e733ef382a0c7537391f5e1fdbd3

47

py

Python

src/hanon.py

amypellegrini/hanon-pilgrimage-python

63872d9c82b067c30b21489b0ac99daf4b51aa47

[ "MIT" ]

null

src/hanon.py

amypellegrini/hanon-pilgrimage-python

63872d9c82b067c30b21489b0ac99daf4b51aa47

[ "MIT" ]

null

src/hanon.py

amypellegrini/hanon-pilgrimage-python

63872d9c82b067c30b21489b0ac99daf4b51aa47

[ "MIT" ]

null

#!/usr/bin/env python3 print('Hello World!')

9.4

22

0.659574

7

47

4.428571

1

0

0.02439

0.12766

47

4

23

11.75

0.731707

0.446809

0

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0

1

0

null

0

1

0

1

0

5

b4562dccfad14ac92fbb32170c90ce754b69476c

47

py

Python

yama_util/__init__.py

yamato-kaeng/yama_util

2fa31edf7ba501fc2e01f58511c185c8850d58f5

[ "MIT" ]

null

yama_util/__init__.py

yamato-kaeng/yama_util

2fa31edf7ba501fc2e01f58511c185c8850d58f5

[ "MIT" ]

null

yama_util/__init__.py

yamato-kaeng/yama_util

2fa31edf7ba501fc2e01f58511c185c8850d58f5

[ "MIT" ]

null

from .temp import yama from .temp2 import yama2

23.5

24

0.808511

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47

4.75

0.75

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0.05

0.148936

47

2

24

23.5

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0

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0

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0

1

0

null

0

1

0

1

0

5

b470a1f5fc8e301cd6717c62c7cc817f0cee64e3

47

py

Python

test-hello.py

rfrik/FEM_start

fa46b5b3907be3051576dec4d25e50ddbd6ab1cb

[ "MIT" ]

null

test-hello.py

rfrik/FEM_start

fa46b5b3907be3051576dec4d25e50ddbd6ab1cb

[ "MIT" ]

null

test-hello.py

rfrik/FEM_start

fa46b5b3907be3051576dec4d25e50ddbd6ab1cb

[ "MIT" ]

null

print('hello there world') print('what's up?')

15.666667

26

0.680851

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47

4

0.875

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0.106383

47

2

27

23.5

0.761905

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0.446809

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0

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1

0

null

0

1

0

1

0

5

c3056e650c1ae8780fcf29ef0729d231733b0c6b

172

py

Python

python/ray/train/rl/__init__.py

jianoaix/ray

1701b923bc83905f8961c06a6a173e3eba46a936

[ "Apache-2.0" ]

null

python/ray/train/rl/__init__.py

jianoaix/ray

1701b923bc83905f8961c06a6a173e3eba46a936

[ "Apache-2.0" ]

null

python/ray/train/rl/__init__.py

jianoaix/ray

1701b923bc83905f8961c06a6a173e3eba46a936

[ "Apache-2.0" ]

null

from ray.train.rl.rl_predictor import RLPredictor from ray.train.rl.rl_trainer import RLTrainer, load_checkpoint __all__ = ["RLPredictor", "RLTrainer", "load_checkpoint"]

34.4

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c34a4e5fa9ebfce18b8dc4f31c581ce8bd0bbba4

33

py

Python

u3dunpack/writer/__init__.py

smalls0098/u3d-studio

b5fb9875afdebaf457ee75c3ab42e4e828a88680

[ "MIT" ]

1

2020-07-27T03:43:47.000Z

u3dunpack/writer/__init__.py

smalls0098/u3d-assets-tools

b5fb9875afdebaf457ee75c3ab42e4e828a88680

[ "MIT" ]

null

u3dunpack/writer/__init__.py

smalls0098/u3d-assets-tools

b5fb9875afdebaf457ee75c3ab42e4e828a88680

[ "MIT" ]

1

2021-10-03T11:23:14.000Z

from . import ResourceConverter

16.5

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1

33

0.964286

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1

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1

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1

0

null

0

1

0

1

0

5

c34cb5e7c72a84aad2151633d4c4ecfba6ba3ffc

4,351

py

Python

tests/functional/tabloid/test_dbp_1940_20061108_2141.py

reevespaul/firebird-qa

98f16f425aa9ab8ee63b86172f959d63a2d76f21

[ "MIT" ]

null

tests/functional/tabloid/test_dbp_1940_20061108_2141.py

reevespaul/firebird-qa

98f16f425aa9ab8ee63b86172f959d63a2d76f21

[ "MIT" ]

null

tests/functional/tabloid/test_dbp_1940_20061108_2141.py

reevespaul/firebird-qa

98f16f425aa9ab8ee63b86172f959d63a2d76f21

[ "MIT" ]

null

#coding:utf-8 # # id: functional.tabloid.dbp_1940_20061108_2141 # title: Common SQL. Check correctness of the results # decription: # tracker_id: # min_versions: ['3.0'] # versions: 3.0 # qmid: None import pytest from firebird.qa import db_factory, isql_act, Action # version: 3.0 # resources: None substitutions_1 = [] init_script_1 = """""" db_1 = db_factory(from_backup='tabloid-dbp-1940.fbk', init=init_script_1) test_script_1 = """ set list on; select dateadd(n-1 second to dat) f01 ,(select count(*) from (select vi, sum(bv) as s from bbb where dateadd(n-1 second to dat)>=tm group by vi having sum(bv) between 85 and 170) t ) f02 from ( select row_number() over(order by qi) n from bbb rows 30 ) z cross join ( select min(tm) as dat from bbb b where exists ( select vi, sum(bv) from bbb where b.tm>=tm group by vi having sum(bv)=255 ) ) q order by 1,2 ; """ act_1 = isql_act('db_1', test_script_1, substitutions=substitutions_1) expected_stdout_1 = """ F01 2003-01-01 01:11:00.0000 F02 1 F01 2003-01-01 01:11:01.0000 F02 3 F01 2003-01-01 01:11:02.0000 F02 4 F01 2003-01-01 01:11:03.0000 F02 4 F01 2003-01-01 01:11:04.0000 F02 3 F01 2003-01-01 01:11:05.0000 F02 3 F01 2003-01-01 01:11:06.0000 F02 3 F01 2003-01-01 01:11:07.0000 F02 3 F01 2003-01-01 01:11:08.0000 F02 3 F01 2003-01-01 01:11:09.0000 F02 3 F01 2003-01-01 01:11:10.0000 F02 4 F01 2003-01-01 01:11:11.0000 F02 5 F01 2003-01-01 01:11:12.0000 F02 4 F01 2003-01-01 01:11:13.0000 F02 4 F01 2003-01-01 01:11:14.0000 F02 3 F01 2003-01-01 01:11:15.0000 F02 3 F01 2003-01-01 01:11:16.0000 F02 3 F01 2003-01-01 01:11:17.0000 F02 4 F01 2003-01-01 01:11:18.0000 F02 4 F01 2003-01-01 01:11:19.0000 F02 4 F01 2003-01-01 01:11:20.0000 F02 4 F01 2003-01-01 01:11:21.0000 F02 4 F01 2003-01-01 01:11:22.0000 F02 4 F01 2003-01-01 01:11:23.0000 F02 4 F01 2003-01-01 01:11:24.0000 F02 4 F01 2003-01-01 01:11:25.0000 F02 4 F01 2003-01-01 01:11:26.0000 F02 4 F01 2003-01-01 01:11:27.0000 F02 4 F01 2003-01-01 01:11:28.0000 F02 4 F01 2003-01-01 01:11:29.0000 F02 4 """ @pytest.mark.version('>=3.0') def test_1(act_1: Action): act_1.expected_stdout = expected_stdout_1 act_1.execute() assert act_1.clean_expected_stdout == act_1.clean_stdout

36.258333

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null

0

5

c3565906c40b9112ce06f9013b4e8fb51eb374e8

82

py

Python

src/spaceone/inventory/connector/aws_ecs_connector/__init__.py

jean1042/plugin-aws-cloud-services

1cf192557b03478af33ae81f40b2a49f735716bb

[ "Apache-2.0" ]

4

2020-06-22T01:48:07.000Z

2020-08-24T00:51:09.000Z

src/spaceone/inventory/connector/aws_ecs_connector/__init__.py

jean1042/plugin-aws-cloud-services

1cf192557b03478af33ae81f40b2a49f735716bb

[ "Apache-2.0" ]

2

2020-07-20T01:58:32.000Z

2020-08-04T07:41:37.000Z

src/spaceone/inventory/connector/aws_ecs_connector/__init__.py

jean1042/plugin-aws-cloud-services

1cf192557b03478af33ae81f40b2a49f735716bb

[ "Apache-2.0" ]

6

2020-06-22T09:19:40.000Z

2020-09-17T06:35:37.000Z

from spaceone.inventory.connector.aws_ecs_connector.connector import ECSConnector

41

81

0.902439

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82

7.2

0.8

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1

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1

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null

0

1

0

1

0

1

0

5

c35c9eea358c4ba7234a6dbe42bb4679136225a8

167

py

Python

accounts/admin.py

fedeuhr/smartket

3490d9a3b6a1960141e8af26c89c12a0983be7ab

[ "MIT" ]

null

accounts/admin.py

fedeuhr/smartket

3490d9a3b6a1960141e8af26c89c12a0983be7ab

[ "MIT" ]

null

accounts/admin.py

fedeuhr/smartket

3490d9a3b6a1960141e8af26c89c12a0983be7ab

[ "MIT" ]

null

from django.contrib import admin from .models import UserLibrary,User,Profile admin.site.register(User) admin.site.register(UserLibrary) admin.site.register(Profile)

23.857143

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0.832335

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6.043478

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0.071856

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null

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1

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1

0

null

0

1

0

1

0

5

6f165c36c3685a6609f32debd7c950d0f600eab5

47

py

Python

tests/components/vulcan/__init__.py

mtarjoianu/core

44e9146463ac505eb3d1c0651ad126cb25c28a54

[ "Apache-2.0" ]

30,023

2016-04-13T10:17:53.000Z

2020-03-02T12:56:31.000Z

tests/components/vulcan/__init__.py

mtarjoianu/core

44e9146463ac505eb3d1c0651ad126cb25c28a54

[ "Apache-2.0" ]

24,710

2016-04-13T08:27:26.000Z

2020-03-02T12:59:13.000Z

tests/components/vulcan/__init__.py

mtarjoianu/core

44e9146463ac505eb3d1c0651ad126cb25c28a54

[ "Apache-2.0" ]

11,956

2016-04-13T18:42:31.000Z

2020-03-02T09:32:12.000Z

"""Tests for the Uonet+ Vulcan integration."""

23.5

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0.702128

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5.5

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0.804878

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null

0

1

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5

6f2b5a7491c3f89b2dfc9df59e8bc629adaeefc9

228

py

Python

runner.py

soarqin/rg350_installer

ca373398d98fd12c9903fb84f4ac4f6b3d185816

[ "MIT" ]

null

runner.py

soarqin/rg350_installer

ca373398d98fd12c9903fb84f4ac4f6b3d185816

[ "MIT" ]

null

runner.py

soarqin/rg350_installer

ca373398d98fd12c9903fb84f4ac4f6b3d185816

[ "MIT" ]

null

class Runner: def __init__(self, installer): self.installer = installer installer.set_runner(self) pass def process(self): return True def key_event(self, keys): return True

19

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228

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0.320175

228

11

35

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null

0

null

0

1

0

1

0

1

0

5

6f2ccee750ea7fd4397510a3008298e205cfec0b

30

py

Python

modules/moderation.py

sebj/r-CompetitiveOverwatch-Sidebar-Bot

7211db7bedd208847afdb452821e1275fda35e80

[ "MIT" ]

null

modules/moderation.py

sebj/r-CompetitiveOverwatch-Sidebar-Bot

7211db7bedd208847afdb452821e1275fda35e80

[ "MIT" ]

2

2017-05-05T12:46:45.000Z

2017-11-30T01:06:38.000Z

modules/moderation.py

sebj/r-CompetitiveOverwatch-Sidebar-Bot

7211db7bedd208847afdb452821e1275fda35e80

[ "MIT" ]

null

def poll_new(subreddit): pass

15

24

0.8

5

30

4.6

1

0

0.1

30

2

25

15

0.851852

0

1

0.5

false

0.5

0

0.5

0

1

0

null

0

1

0

null

0

1

0

1

0

5

6f3e010f859331a5f424ea233f64c3700bc4cef1

145

py

Python

torchsketch/networks/gnn/graph_attention_network/__init__.py

songyzh/torchsketch

42bca1b31ab9699d9b6d77a102b1f46bba82fb33

[ "MIT" ]

182

2020-03-25T01:59:11.000Z

2022-03-29T08:58:47.000Z

torchsketch/networks/gnn/graph_attention_network/__init__.py

songyzh/torchsketch

42bca1b31ab9699d9b6d77a102b1f46bba82fb33

[ "MIT" ]

5

2020-03-25T13:16:50.000Z

2022-02-19T09:51:39.000Z

torchsketch/networks/gnn/graph_attention_network/__init__.py

songyzh/torchsketch

42bca1b31ab9699d9b6d77a102b1f46bba82fb33

[ "MIT" ]

17

2020-03-25T12:40:49.000Z

2022-03-28T06:34:40.000Z

from torchsketch.networks.gnn.graph_attention_network.graph_attention_network import GraphAttentionNetwork __all__ = ['GraphAttentionNetwork']

48.333333

107

0.875862

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145

8.5

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0

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145

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108

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0

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6f50404b0dab09de4587fbdc55d4f0d7ebd0f380

177

py

Python

filters/admin.py

TobWul/Koble

a308fded6915cb4237e8ba303196d754acf26563

[ "MIT" ]

null

filters/admin.py

TobWul/Koble

a308fded6915cb4237e8ba303196d754acf26563

[ "MIT" ]

7

2020-06-05T20:36:44.000Z

2022-02-10T09:31:10.000Z

filters/admin.py

TobWul/Koble

a308fded6915cb4237e8ba303196d754acf26563

[ "MIT" ]

null

from django.contrib import admin # Register your models here. from filters.models import Filter, NegativeFilter admin.site.register(Filter) admin.site.register(NegativeFilter)

25.285714

49

0.830508

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177

6.391304

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0.096045

177

7

50

25.285714

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0.146893

0

1

0

true

0

0.5

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1

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null

0

1

0

1

0

5

6f759e515917128a54f28d1d93ccf5c65db8584d

52

py

Python

hello_world.py

unit1202/hello_world

1ea5fd7fe2052689f48bad0a74a32a86442290fb

[ "MIT" ]

null

hello_world.py

unit1202/hello_world

1ea5fd7fe2052689f48bad0a74a32a86442290fb

[ "MIT" ]

null

hello_world.py

unit1202/hello_world

1ea5fd7fe2052689f48bad0a74a32a86442290fb

[ "MIT" ]

null

#Hello World in Python 3.x print ("Hello World!")

17.333333

27

0.673077

9

52

3.888889

0.777778

0.571429

0

0.02381

0.192308

52

2

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0.809524

0.480769

0

0.5

0

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0

true

0

1

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null

1

0

1

0

null

0

1

0

1

0

5

48c6843a417a742b82d90af7c6eb0d98bbf41c01

145

py

Python

test/test_utils.py

mo-seph/inver-synth

d8c41871e7a58c1dacf492f2e7636f46b8e1ee1a

[ "Apache-2.0" ]

null

test/test_utils.py

mo-seph/inver-synth

d8c41871e7a58c1dacf492f2e7636f46b8e1ee1a

[ "Apache-2.0" ]

null

test/test_utils.py

mo-seph/inver-synth

d8c41871e7a58c1dacf492f2e7636f46b8e1ee1a

[ "Apache-2.0" ]

null

from models.common.utils import utils class TestUtils: def test_load_audio(self): assert utils.load_audio is not None # TODO

14.5

43

0.703448

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145

4.714286

0.809524

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9

44

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0.9

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1

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1

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5

48dbfc9da054a79fc3b8239d22a80fef7a234267

227

py

Python

Framework/plugins/fedavg/default.py

AnganMitra/federatedLearn

f5c0d22fd677fbe8d5b90e5e018825ad89d596e5

[ "MIT" ]

null

Framework/plugins/fedavg/default.py

AnganMitra/federatedLearn

f5c0d22fd677fbe8d5b90e5e018825ad89d596e5

[ "MIT" ]

null

Framework/plugins/fedavg/default.py

AnganMitra/federatedLearn

f5c0d22fd677fbe8d5b90e5e018825ad89d596e5

[ "MIT" ]

null

from federated_averaging import always_average def register(plugin_keys): plugin_keys["always_fedavg"] = always_average def get_plugin(key): if key == "always_fedavg": return always_average return None

17.461538

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227

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0.202532

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0.193833

227

12

50

18.916667

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0

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1

0

null

0

1

0

1

0

5

48dcae7e258eb9bbc9e3ec0ee07d42fba6a7a70d

147

py

Python

setup.py

astropy/pytest-openfiles

2bc5b0f74971d596ac5fcbfec5414ea7e9e9bd83

[ "BSD-3-Clause" ]

6

2018-01-13T10:57:15.000Z

2020-05-26T23:27:30.000Z

setup.py

astropy/pytest-openfiles

2bc5b0f74971d596ac5fcbfec5414ea7e9e9bd83

[ "BSD-3-Clause" ]

27

2017-10-10T16:07:47.000Z

2021-12-31T05:50:25.000Z

setup.py

astropy/pytest-openfiles

2bc5b0f74971d596ac5fcbfec5414ea7e9e9bd83

[ "BSD-3-Clause" ]

10

2017-10-04T17:46:56.000Z

2020-11-12T18:06:39.000Z

#!/usr/bin/env python import os from setuptools import setup setup(use_scm_version={'write_to': os.path.join('pytest_openfiles', 'version.py')})

21

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6

84

24.5

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0

1

0

true

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1

0

null

0

1

0

1

0

1

0

5

48f5378ced5877a65636958a438791b15b4cf701

119

py

Python

representjs/data/__init__.py

myutman/contracode

f2a589e1efd2788874fd0468d1ecc30d6a14c396

[ "Apache-2.0" ]

null

representjs/data/__init__.py

myutman/contracode

f2a589e1efd2788874fd0468d1ecc30d6a14c396

[ "Apache-2.0" ]

null

representjs/data/__init__.py

myutman/contracode

f2a589e1efd2788874fd0468d1ecc30d6a14c396

[ "Apache-2.0" ]

null

from .jsonl_dataset import get_csnjs_dataset from .old_dataloader import javascript_dataloader from .util import Timer

29.75

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119

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0

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3

50

39.666667

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0

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0

true

0

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1

0

1

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1

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5

5b0e002055676b268e7d3e1eba209abc3013c530

158

py

Python

lib.py

laurcor55/cloud-identifier

563afa9551a4ad5e60df5e760bd0cf511b97eb33

[ "MIT" ]

null

lib.py

laurcor55/cloud-identifier

563afa9551a4ad5e60df5e760bd0cf511b97eb33

[ "MIT" ]

null

lib.py

laurcor55/cloud-identifier

563afa9551a4ad5e60df5e760bd0cf511b97eb33

[ "MIT" ]

null

from torch import nn from torch.autograd import Variable import torch import matplotlib.pyplot as plt import numpy as np from torchvision import transforms

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null

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5b0e947ff8373b725f9790d2600e9103ff0ab36b

246

py

Python

rec_to_nwb/processing/nwb/components/device/header/fl_header_device_builder.py

jihyunbak/rec_to_nwb

6e65f8bf0a4faa4d986483ec2442ba19d70c92a9

[ "Apache-2.0" ]

8

2020-05-29T13:48:35.000Z

2021-11-19T04:24:48.000Z

rec_to_nwb/processing/nwb/components/device/header/fl_header_device_builder.py

jihyunbak/rec_to_nwb

6e65f8bf0a4faa4d986483ec2442ba19d70c92a9

[ "Apache-2.0" ]

8

2020-07-13T00:42:35.000Z

2020-11-16T16:17:12.000Z

rec_to_nwb/processing/nwb/components/device/header/fl_header_device_builder.py

jihyunbak/rec_to_nwb

6e65f8bf0a4faa4d986483ec2442ba19d70c92a9

[ "Apache-2.0" ]

1

2020-08-28T01:34:35.000Z

from rec_to_nwb.processing.nwb.components.device.header.fl_header_device import FlHeaderDevice class FlHeaderDeviceBuilder: @staticmethod def build(name, global_configuration): return FlHeaderDevice(name, global_configuration)

27.333333

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7.148148

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null

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5

d28998b78b56b92e6d76d1ec60e2bc1ce5bb29c2

223

py

Python

route/api.py

apanly/python_learn_master

93a214241812f77a006cc8350a7bad6c4eec6c89

[ "BSD-3-Clause" ]

5

2020-11-29T14:21:18.000Z

2021-10-07T04:11:29.000Z

route/api.py

apanly/python_learn_master

93a214241812f77a006cc8350a7bad6c4eec6c89

[ "BSD-3-Clause" ]

null

route/api.py

apanly/python_learn_master

93a214241812f77a006cc8350a7bad6c4eec6c89

[ "BSD-3-Clause" ]

2

2020-11-30T09:55:53.000Z

2022-03-19T12:49:40.000Z

# -*- coding: utf-8 -*- ''' 专门为wapi程序准备的初始化入口 ''' ''' 统一拦截处理和统一错误处理 ''' from api.interceptors.Auth import * from api.interceptors.ErrorHandler import * ''' 蓝图功能，对所有的url进行蓝图功能配置 ''' from api.controllers.route import *

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1

0

1

0

5

d2c18d56fc8576c344ad7d355c995a5387fcbcc0

293

py

Python

tests/use_case/__init__.py

mathisi-ai/message-passing-neural-network

d6e27fcf05d06268a461e5f9d9cf81b7e3a5dc09

[ "MIT" ]

null

tests/use_case/__init__.py

mathisi-ai/message-passing-neural-network

d6e27fcf05d06268a461e5f9d9cf81b7e3a5dc09

[ "MIT" ]

1

2020-12-13T10:37:03.000Z

tests/use_case/__init__.py

mathisi-ai/message-passing-neural-network

d6e27fcf05d06268a461e5f9d9cf81b7e3a5dc09

[ "MIT" ]

null

import os from tests.fixtures.environment_variables import * os.environ['TABLE'] = TEST_DATASET os.environ["DATABASE"] = PDB_TEST os.environ["POSTGRES_USERNAME"] = POSTGRES os.environ["POSTGRES_PASSWORD"] = POSTGRES os.environ["POSTGRES_HOST"] = LOCALHOST os.environ["POSTGRES_PORT"] = PORT

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293

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0

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10

51

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0.249147

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1

0

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0

0.25

0

null

1

0

null

0

1

0

5

d2c551558fab03726eeab36207b2f35a518e2dba

359

py

Python

hat/common/context_processors.py

ekhalilbsq/iaso

e6400c52aeb4f67ce1ca83b03efa3cb11ef235ee

[ "MIT" ]

29

2020-12-26T07:22:19.000Z

2022-03-07T13:40:09.000Z

hat/common/context_processors.py

ekhalilbsq/iaso

e6400c52aeb4f67ce1ca83b03efa3cb11ef235ee

[ "MIT" ]

150

2020-11-09T15:03:27.000Z

2022-03-07T15:36:07.000Z

hat/common/context_processors.py

ekhalilbsq/iaso

e6400c52aeb4f67ce1ca83b03efa3cb11ef235ee

[ "MIT" ]

4

2020-11-09T10:38:13.000Z

2021-10-04T09:42:47.000Z

from typing import Dict from django.conf import settings from django.http.request import HttpRequest def appversions(request: HttpRequest) -> Dict[str, str]: prefix = "D-" if settings.DEBUG else "" return {"DEV_SERVER": settings.DEV_SERVER} def environment(request: HttpRequest) -> Dict[str, str]: return {"environment": settings.ENVIRONMENT}

27.615385

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359

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0.147632

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12

57

29.916667

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null

0

1

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1

0

5

d2f16f26ea676c4320adf29f7a12f2a232c244c4

56

py

Python

python-import/hello_world/world/europe/spain.py

syberflea/materials

54f44725b40edf00c1b523d7a85b34a85014d7eb

[ "MIT" ]

3,682

2018-05-07T19:45:24.000Z

2022-03-31T15:19:10.000Z

python-import/hello_world/world/europe/spain.py

sribarrow/materials

c17c4a4d6f8487e59eac1df8c88ca92b73d6d2a5

[ "MIT" ]

148

2018-05-15T21:18:49.000Z

2022-03-21T11:25:39.000Z

python-import/hello_world/world/europe/spain.py

sribarrow/materials

c17c4a4d6f8487e59eac1df8c88ca92b73d6d2a5

[ "MIT" ]

5,535

2018-05-25T23:36:08.000Z

2022-03-31T16:55:52.000Z

# world/europe/spain.py print("Castellano: Hola mundo")

18.666667

31

0.75

8

56

5.25

1

0

0.089286

56

2

32

28

0.823529

0.375

0

0.666667

0

1

0

true

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null

0

1

0

1

0

5

96128d75796abf1e1c6b2700f7be17bc64425a7a

43

py

Python

__init__.py

jkent/pybot

0c70a7c29caa709413e04a411a5fdb22a8dbdb12

[ "MIT" ]

1

2017-06-01T00:52:44.000Z

__init__.py

jkent/pybot

0c70a7c29caa709413e04a411a5fdb22a8dbdb12

[ "MIT" ]

17

2015-03-21T19:35:45.000Z

2019-04-14T05:17:49.000Z

pybot/plugins/__init__.py

jkent/jkent-pybot

0c70a7c29caa709413e04a411a5fdb22a8dbdb12

[ "MIT" ]

1

2015-03-27T22:52:42.000Z

# -*- coding: utf-8 -*- # vim: set ts=4 et

14.333333

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0.488372

8

43

2.625

1

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43

2

24

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0

null

0

null

0

null

0

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1

null

true

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null

0

1

0

1

0

null

0

1

0

5

8249a21dac1fc2eddb80a6348cfe141923b90c86

155

py

Python

HW/HW5/CW5.1.py

kolyasalubov/Lv-639.pythonCore

06f10669a188318884adb00723127465ebdf2907

[ "MIT" ]

null

HW/HW5/CW5.1.py

kolyasalubov/Lv-639.pythonCore

06f10669a188318884adb00723127465ebdf2907

[ "MIT" ]

null

HW/HW5/CW5.1.py

kolyasalubov/Lv-639.pythonCore

06f10669a188318884adb00723127465ebdf2907

[ "MIT" ]

null

def zero_fuel(distance_to_pump, mpg, fuel_left): #Happy Coding! ;) if distance_to_pump<=fuel_left*mpg: return 1 else: return 0

22.142857

48

0.63871

23

155

4

0.652174

0.217391

0.304348

0

0.017699

0.270968

155

6

49

25.833333

0.79646

0.103226

0

1

0.2

false

0

0.6

0

1

0

null

1

0

1

0

null

0

1

0

5

82bee44f8f5400d43fef8cfc693a22bb3b8681e7

37

py

Python

scrapli/transport/plugins/ssh2/__init__.py

verbosemode/scrapli

b3885169dccf24ac65d0d433eae16bcab8288002

[ "MIT" ]

404

2020-02-11T09:05:40.000Z

2022-03-31T05:10:03.000Z

scrapli/transport/plugins/ssh2/__init__.py

verbosemode/scrapli

b3885169dccf24ac65d0d433eae16bcab8288002

[ "MIT" ]

155

2020-02-18T00:21:43.000Z

2022-03-06T16:34:47.000Z

scrapli/transport/plugins/ssh2/__init__.py

verbosemode/scrapli

b3885169dccf24ac65d0d433eae16bcab8288002

[ "MIT" ]

48

2020-04-02T00:24:44.000Z

2022-03-07T18:24:53.000Z

"""scrapli.transport.plugins.ssh2"""

18.5

36

0.72973

4

37

6.75

1

0

0.027778

0.027027

37

1

37

0.722222

0.810811

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

1

0

null

0

1

0

5

82c79556761385f982b8b4c1e040393a402f5b5d

67

py

Python

src/evaluator/__init__.py

JonasFrey96/RPOSE

7da77499ab777ce7ee37b731541982870da8d40b

[ "BSD-3-Clause" ]

null

src/evaluator/__init__.py

JonasFrey96/RPOSE

7da77499ab777ce7ee37b731541982870da8d40b

[ "BSD-3-Clause" ]

null

src/evaluator/__init__.py

JonasFrey96/RPOSE

7da77499ab777ce7ee37b731541982870da8d40b

[ "BSD-3-Clause" ]

null

from .inference import Inferencer from .evaluator import Evaluator

22.333333

33

0.850746

8

67

7.125

0.625

0

0.119403

67

2

34

33.5

0.966102

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

82dd7b80684afbad20d4547da6de492c37c21558

226

py

Python

tests/conftest.py

johannesnicolaus/singlecell

8b3f5719b236fb2b9783e4d2c3b419352bb3bf6f

[ "BSD-3-Clause" ]

null

tests/conftest.py

johannesnicolaus/singlecell

8b3f5719b236fb2b9783e4d2c3b419352bb3bf6f

[ "BSD-3-Clause" ]

null

tests/conftest.py

johannesnicolaus/singlecell

8b3f5719b236fb2b9783e4d2c3b419352bb3bf6f

[ "BSD-3-Clause" ]

null

import pytest @pytest.fixture(scope='session') def my_data_pypath(tmpdir_factory): """temporary directory for storing test data""" pypath = tmpdir_factory.mktemp('singlecell_data', numbered=False) return pypath

22.6

69

0.752212

28

226

5.892857

0.75

0.121212

0.193939

0.278788

0

0.141593

226

9

70

25.111111

0.850515

0.181416

0

0.124294

0

1

0.2

false

0

0.2

0

0.6

0

1

0

null

0

1

0

1

0

null

0

1

0

5

7d5d6b350c3718e86b231cdebffd8ac18d12774f

139

py

Python

Baekjoon/Python/3062.py

KHJcode/Algorithm-study

fa08d3c752fcb3557fd45fb394157926afc0de4a

[ "MIT" ]

2

2020-05-23T01:55:38.000Z

2020-07-07T15:59:00.000Z

Baekjoon/Python/3062.py

KHJcode/Algorithm-study

fa08d3c752fcb3557fd45fb394157926afc0de4a

[ "MIT" ]

null

Baekjoon/Python/3062.py

KHJcode/Algorithm-study

fa08d3c752fcb3557fd45fb394157926afc0de4a

[ "MIT" ]

null

for _ in range(int(input())): n = int(input()) _n = int(str(n)[::-1]) res = str(n + _n) print('YES' if res == res[::-1] else 'NO')

23.166667

44

0.503597

25

139

2.68

0.56

0.238806

0.268657

0.358209

0

0.018349

0.215827

139

5

45

27.8

0.59633

0

0.035971

0

1

0

false

0

0.2

1

0

null

1

0

1

0

null

0

5

7d8575f9d8eccb76c6ea6df32e426bb3a99dafbb

58

py

Python

tests/commands.py

FrostMiser/Frostica

7fe4cf44b71ce36fec74201a25b38d391714f12f

[ "MIT" ]

1

2021-08-10T14:58:44.000Z

tests/commands.py

FrostMiser/Frostica

7fe4cf44b71ce36fec74201a25b38d391714f12f

[ "MIT" ]

3

2021-06-08T21:38:17.000Z

2022-01-13T02:46:07.000Z

tests/commands.py

FrostMiser/Frostica-Adventure-Bot

7fe4cf44b71ce36fec74201a25b38d391714f12f

[ "MIT" ]

1

2019-03-18T05:18:24.000Z

def test_command_char(): assert True # Placeholder

11.6

30

0.706897

7

58

5.571429

1

0

0.224138

58

4

31

14.5

0.866667

0.189655

0

0.5

1

0.5

true

0

0.5

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1

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null

0

1

0

null

0

1

0

1

0

5

7d90b6838c47c60b2c4446634634a22fdb12c407

74

py

Python

deeptech/training/optimizers/__init__.py

penguinmenac3/deeptech

0c7fb170d62f193dbbb2018f7b8d42f713178bb8

[ "MIT" ]

1

2020-10-10T10:11:54.000Z

deeptech/training/optimizers/__init__.py

penguinmenac3/deeptech

0c7fb170d62f193dbbb2018f7b8d42f713178bb8

[ "MIT" ]

null

deeptech/training/optimizers/__init__.py

penguinmenac3/deeptech

0c7fb170d62f193dbbb2018f7b8d42f713178bb8

[ "MIT" ]

null

from deeptech.training.optimizers._smart_optimizer import smart_optimizer

37

73

0.905405

9

74

7.111111

0.777778

0.4375

0

0.054054

74

1

74

0.914286

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

5

8166596b509f1f72bba176a6f6fe2bbe4641cd55

246

py

Python

iotbx/command_line/split_data_cif.py

dperl-sol/cctbx_project

b9e390221a2bc4fd00b9122e97c3b79c632c6664

[ "BSD-3-Clause-LBNL" ]

155

2016-11-23T12:52:16.000Z

2022-03-31T15:35:44.000Z

iotbx/command_line/split_data_cif.py

dperl-sol/cctbx_project

b9e390221a2bc4fd00b9122e97c3b79c632c6664

[ "BSD-3-Clause-LBNL" ]

590

2016-12-10T11:31:18.000Z

2022-03-30T23:10:09.000Z

iotbx/command_line/split_data_cif.py

dperl-sol/cctbx_project

b9e390221a2bc4fd00b9122e97c3b79c632c6664

[ "BSD-3-Clause-LBNL" ]

115

2016-11-15T08:17:28.000Z

2022-02-09T15:30:14.000Z

from __future__ import absolute_import, division, print_function # LIBTBX_SET_DISPATCHER_NAME iotbx.split_data_cif from iotbx.programs import split_data_cif from iotbx.cli_parser import run_program result = run_program(split_data_cif.Program)

27.333333

64

0.865854

37

246

5.27027

0.567568

0.138462

0.184615

0.164103

0.215385

0

0.093496

246

8

65

30.75

0.874439

0.191057

0

1

0

false

0

0.75

0

0.75

0.25

0

null

0

1

0

1

0

null

0

1

0

1

0

5

817366462b9d862616494fd9488a8e4474cb7349

42

py

Python

foundation/forms/views/__init__.py

tbone255/foundation

ca76fdd9b5345fead2d200f829eb67ba77bc865e

[ "MIT" ]

null

foundation/forms/views/__init__.py

tbone255/foundation

ca76fdd9b5345fead2d200f829eb67ba77bc865e

[ "MIT" ]

null

foundation/forms/views/__init__.py

tbone255/foundation

ca76fdd9b5345fead2d200f829eb67ba77bc865e

[ "MIT" ]

null

from .list import * from .object import *

14

21

0.714286

6

42

5

0.666667

0

0.190476

42

2

22

21

0.882353

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

818712260de2aeec62e7d499a8c87e2cc7ecc485

117

py

Python

nodeconductor/ldapsync/admin.py

p-p-m/nodeconductor

bc702302ef65c89793452f0fd6ca9a6bec79782f

[ "Apache-2.0" ]

null

nodeconductor/ldapsync/admin.py

p-p-m/nodeconductor

bc702302ef65c89793452f0fd6ca9a6bec79782f

[ "Apache-2.0" ]

null

nodeconductor/ldapsync/admin.py

p-p-m/nodeconductor

bc702302ef65c89793452f0fd6ca9a6bec79782f

[ "Apache-2.0" ]

null

from django.contrib import admin from nodeconductor.ldapsync import models admin.site.register(models.LdapToGroup)

19.5

41

0.846154

15

117

6.6

0.733333

0

0.094017

117

5

42

23.4

0.933962

0

1

0

true

0

0.666667

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

81917554f945b6226b57948fc8368df61c83d0db

7,065

py

Python

cscs-checks/microbenchmarks/mpi/halo_exchange/halo_cell_exchange.py

jacwah/reframe

d650bbbb2f87c6ae5f354e50b50bcfd98fafe77b

[ "BSD-3-Clause" ]

null

cscs-checks/microbenchmarks/mpi/halo_exchange/halo_cell_exchange.py

jacwah/reframe

d650bbbb2f87c6ae5f354e50b50bcfd98fafe77b

[ "BSD-3-Clause" ]

3

2022-03-11T09:51:33.000Z

2022-03-31T08:20:19.000Z

cscs-checks/microbenchmarks/mpi/halo_exchange/halo_cell_exchange.py

jacwah/reframe

d650bbbb2f87c6ae5f354e50b50bcfd98fafe77b

[ "BSD-3-Clause" ]

null

# Copyright 2016-2022 Swiss National Supercomputing Centre (CSCS/ETH Zurich) # ReFrame Project Developers. See the top-level LICENSE file for details. # # SPDX-License-Identifier: BSD-3-Clause import reframe as rfm import reframe.utility.sanity as sn @rfm.simple_test class HaloCellExchangeTest(rfm.RegressionTest): def __init__(self): self.sourcepath = 'halo_cell_exchange.c' self.build_system = 'SingleSource' self.build_system.cflags = ['-O2'] self.valid_systems = ['daint:gpu', 'dom:gpu', 'daint:mc', 'dom:mc', 'arolla:cn', 'tsa:cn', 'eiger:mc', 'pilatus:mc'] self.valid_prog_environs = ['PrgEnv-cray', 'PrgEnv-gnu', 'PrgEnv-pgi', 'PrgEnv-nvidia'] self.num_tasks = 6 self.num_tasks_per_node = 1 self.num_gpus_per_node = 0 self.executable_opts = ['input.txt'] self.sanity_patterns = sn.assert_eq( sn.count(sn.findall(r'halo_cell_exchange', self.stdout)), 9) self.perf_patterns = { 'time_2_10': sn.extractsingle( r'halo_cell_exchange 6 2 1 1 10 10 10' r' \S+ (?P<time_mpi>\S+)', self.stdout, 'time_mpi', float), 'time_2_10000': sn.extractsingle( r'halo_cell_exchange 6 2 1 1 10000 10000 10000' r' \S+ (?P<time_mpi>\S+)', self.stdout, 'time_mpi', float), 'time_2_1000000': sn.extractsingle( r'halo_cell_exchange 6 2 1 1 1000000 1000000 1000000' r' \S+ (?P<time_mpi>\S+)', self.stdout, 'time_mpi', float), 'time_4_10': sn.extractsingle( r'halo_cell_exchange 6 2 2 1 10 10 10' r' \S+ (?P<time_mpi>\S+)', self.stdout, 'time_mpi', float), 'time_4_10000': sn.extractsingle( r'halo_cell_exchange 6 2 2 1 10000 10000 10000' r' \S+ (?P<time_mpi>\S+)', self.stdout, 'time_mpi', float), 'time_4_1000000': sn.extractsingle( r'halo_cell_exchange 6 2 2 1 1000000 1000000 1000000' r' \S+ (?P<time_mpi>\S+)', self.stdout, 'time_mpi', float), 'time_6_10': sn.extractsingle( r'halo_cell_exchange 6 3 2 1 10 10 10' r' \S+ (?P<time_mpi>\S+)', self.stdout, 'time_mpi', float), 'time_6_10000': sn.extractsingle( r'halo_cell_exchange 6 3 2 1 10000 10000 10000' r' \S+ (?P<time_mpi>\S+)', self.stdout, 'time_mpi', float), 'time_6_1000000': sn.extractsingle( r'halo_cell_exchange 6 3 2 1 1000000 1000000 1000000' r' \S+ (?P<time_mpi>\S+)', self.stdout, 'time_mpi', float) } self.reference = { 'dom:mc': { 'time_2_10': (3.925395e-06, None, 0.50, 's'), 'time_2_10000': (9.721279e-06, None, 0.50, 's'), 'time_2_1000000': (4.934530e-04, None, 0.50, 's'), 'time_4_10': (5.878997e-06, None, 0.50, 's'), 'time_4_10000': (1.495080e-05, None, 0.50, 's'), 'time_4_1000000': (6.791397e-04, None, 0.50, 's'), 'time_6_10': (5.428815e-06, None, 0.50, 's'), 'time_6_10000': (1.540580e-05, None, 0.50, 's'), 'time_6_1000000': (9.179296e-04, None, 0.50, 's') }, 'daint:mc': { 'time_2_10': (1.5e-05, None, 0.50, 's'), 'time_2_10000': (9.1e-05, None, 0.50, 's'), 'time_2_1000000': (7.9e-04, None, 0.50, 's'), 'time_4_10': (3e-05, None, 0.50, 's'), 'time_4_10000': (1.3e-04, None, 0.50, 's'), 'time_4_1000000': (6.791397e-04, None, 0.50, 's'), 'time_6_10': (3.5e-05, None, 0.50, 's'), 'time_6_10000': (1.2e-04, None, 0.50, 's'), 'time_6_1000000': (9.179296e-04, None, 0.50, 's') }, 'dom:gpu': { 'time_2_10': (3.925395e-06, None, 0.50, 's'), 'time_2_10000': (9.721279e-06, None, 0.50, 's'), 'time_2_1000000': (4.934530e-04, None, 0.50, 's'), 'time_4_10': (5.878997e-06, None, 0.50, 's'), 'time_4_10000': (1.495080e-05, None, 0.50, 's'), 'time_4_1000000': (6.791397e-04, None, 0.50, 's'), 'time_6_10': (5.428815e-06, None, 0.50, 's'), 'time_6_10000': (1.540580e-05, None, 0.50, 's'), 'time_6_1000000': (9.179296e-04, None, 0.50, 's') }, 'daint:gpu': { 'time_2_10': (1.5e-05, None, 0.50, 's'), 'time_2_10000': (9.1e-05, None, 0.50, 's'), 'time_2_1000000': (7.9e-04, None, 0.50, 's'), 'time_4_10': (3e-05, None, 0.50, 's'), 'time_4_10000': (1.3e-04, None, 0.50, 's'), 'time_4_1000000': (6.791397e-04, None, 0.50, 's'), 'time_6_10': (3.5e-05, None, 0.50, 's'), 'time_6_10000': (1.2e-04, None, 0.50, 's'), 'time_6_1000000': (9.179296e-04, None, 0.50, 's') }, 'eiger:mc': { 'time_2_10': (3.46e-06, None, 0.50, 's'), 'time_2_10000': (8.51e-06, None, 0.50, 's'), 'time_2_1000000': (2.07e-04, None, 0.50, 's'), 'time_4_10': (4.46e-06, None, 0.50, 's'), 'time_4_10000': (1.08e-05, None, 0.50, 's'), 'time_4_1000000': (3.55e-04, None, 0.50, 's'), 'time_6_10': (4.53e-06, None, 0.50, 's'), 'time_6_10000': (1.04e-05, None, 0.50, 's'), 'time_6_1000000': (3.55e-04, None, 0.50, 's') }, 'pilatus:mc': { 'time_2_10': (3.46e-06, None, 0.50, 's'), 'time_2_10000': (8.51e-06, None, 0.50, 's'), 'time_2_1000000': (2.07e-04, None, 0.50, 's'), 'time_4_10': (4.46e-06, None, 0.50, 's'), 'time_4_10000': (1.08e-05, None, 0.50, 's'), 'time_4_1000000': (3.55e-04, None, 0.50, 's'), 'time_6_10': (4.53e-06, None, 0.50, 's'), 'time_6_10000': (1.04e-05, None, 0.50, 's'), 'time_6_1000000': (3.55e-04, None, 0.50, 's') }, } self.maintainers = ['AJ'] self.strict_check = False self.tags = {'benchmark'} @run_before('compile') def pgi_workaround(self): if self.current_system.name in ['daint', 'dom']: if self.current_environ.name == 'PrgEnv-pgi': self.variables = { 'CUDA_HOME': '$CUDATOOLKIT_HOME', } if self.current_environ.name == 'PrgEnv-nvidia': self.skip_if(self.current_system.name == 'eiger') self.skip_if(self.current_system.name == 'pilatus')

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5

81ca9220ebcb001da5929261630c7b1a4aa772e7

7,933

py

Python

src/probnum/filtsmooth/_kalman_filter_smoother.py

fxbriol/probnum

7e0e94cf9146aaa2b730b02c6d75a022cd629b5c

[ "MIT" ]

null

src/probnum/filtsmooth/_kalman_filter_smoother.py

fxbriol/probnum

7e0e94cf9146aaa2b730b02c6d75a022cd629b5c

[ "MIT" ]

null

src/probnum/filtsmooth/_kalman_filter_smoother.py

fxbriol/probnum

7e0e94cf9146aaa2b730b02c6d75a022cd629b5c

[ "MIT" ]

null

"""Convenience functions for filtering and smoothing.""" from __future__ import annotations import numpy as np from probnum import problems, randprocs, randvars from probnum.filtsmooth import gaussian from probnum.typing import ArrayLike __all__ = ["filter_kalman", "smooth_rts"] def filter_kalman( observations: ArrayLike, locations: ArrayLike, F: ArrayLike, L: ArrayLike, H: ArrayLike, R: ArrayLike, m0: ArrayLike, C0: ArrayLike, prior_model: str = "continuous", ): r"""Estimate a trajectory with a Kalman filter. A Kalman filter estimates the unknown trajectory :math:`X` from a set of observations `Y`. There is a continuous-discrete and a discrete-discrete version (describing whether the prior model and measurement model are continuous/discrete). In a continuous-discrete model, the prior distribution is described by the SDE .. math:: \text{d}X(t) = F X(t) \text{d}t + L \text{d}W(t) driven by Wiener process :math:`W` and subject to initial condition .. math:: X(t_0) \sim N(m_0, C_0). By default, :math:`t_0` is set to the location of the first observation. In a discrete-discrete model, the prior distribution is described by the transition .. math:: X_{n+1} \,|\, X_n \sim N(F X_n, L) subject to the same initial condition. In both cases, the measurement model is (write :math:`X(t_n)=X_n` in the continuous case) .. math:: Y_n \,|\, X_n \sim N(H X_n, R) and the Kalman filter estimates :math:`X` given :math:`Y_n=y_n`, :math:`Y=[y_1, ..., y_N]`. Parameters ---------- observations *(shape=(N, m))* -- A list of noisy observations of the hidden trajectory. locations *(shape=(N, ))* -- Time-locations of the observations. F *(shape=(n, n))* -- State transition matrix. Either the drift matrix in an SDE model, or the transition matrix in a discrete model (depending on the value of `prior_model`). L *(shape=(n, n))* or *(shape=(n, s))* -- Diffusion/dispersion matrix. Either the dispersion matrix in an SDE model, or the diffusion matrix in a discrete model (depending on the value of `prior_model`). In a continuous model, the matrix has shape (n, s) for s-dimensional driving Wiener process. In a discrete model, the matrix has shape (n, n). H *(shape=(m, n))* -- Transition matrix of the (discrete) observation model. R *(shape=(m, m))* -- Covariance matrix of the observation noise. m0 *(shape=(n,))* -- Initial mean of the prior model. C0 *(shape=(n, n))* -- Initial covariance of the prior model. prior_model Either discrete (``discrete``) or continuous (``continuous``). This affects the role of `F` and `L`. Optional. Default is `continuous`. Raises ------ ValueError If `prior_model` is neither ``discrete`` nor ``continuous``. Returns ------- gaussian.FilteringPosterior Filtering distribution as returned by the Kalman filter. """ regression_problem = _setup_regression_problem( H=H, R=R, observations=observations, locations=locations ) prior_process = _setup_prior_process( F=F, L=L, m0=m0, C0=C0, t0=locations[0], prior_model=prior_model ) kalman = gaussian.Kalman(prior_process) return kalman.filter(regression_problem)[0] def smooth_rts( observations: ArrayLike, locations: ArrayLike, F: ArrayLike, L: ArrayLike, H: ArrayLike, R: ArrayLike, m0: ArrayLike, C0: ArrayLike, prior_model: str = "continuous", ): r"""Estimate a trajectory with a Rauch-Tung-Striebel smoother. A Rauch-Tung-Striebel smoother estimates the unknown trajectory :math:`X` from a set of observations `Y`. There is a continuous-discrete and a discrete-discrete version (describing whether the prior model and measurement model are continuous/discrete). In a continuous-discrete model, the prior distribution is described by the SDE .. math:: \text{d}X(t) = F X(t) \text{d}t + L \text{d}W(t) driven by Wiener process :math:`W` and subject to initial condition .. math:: X(t_0) \sim N(m_0, C_0). By default, :math:`t_0` is set to the location of the first observation. In a discrete-discrete model, the prior distribution is described by the transition .. math:: X_{n+1} \,|\, X_n \sim N(F X_n, L) subject to the same initial condition. In both cases, the measurement model is (write :math:`X(t_n)=X_n` in the continuous case) .. math:: Y_n \,|\, X_n \sim N(H X_n, R) and the Rauch-Tung-Striebel smoother estimates :math:`X` given :math:`Y_n=y_n`, :math:`Y=[y_1, ..., y_N]`. Parameters ---------- observations *(shape=(N, m))* -- A list of noisy observations of the hidden trajectory. locations *(shape=(N, ))* -- Time-locations of the observations. F *(shape=(n, n))* -- State transition matrix. Either the drift matrix in an SDE model, or the transition matrix in a discrete model (depending on the value of `prior_model`). L *(shape=(n, n))* or *(shape=(n, s))* -- Diffusion/dispersion matrix. Either the dispersion matrix in an SDE model, or the diffusion matrix in a discrete model (depending on the value of `prior_model`). In a continuous model, the matrix has shape (n, s) for s-dimensional driving Wiener process. In a discrete model, the matrix has shape (n, n). H *(shape=(m, n))* -- Transition matrix of the (discrete) observation model. R *(shape=(m, m))* -- Covariance matrix of the observation noise. m0 *(shape=(n,))* -- Initial mean of the prior model. C0 *(shape=(n, n))* -- Initial covariance of the prior model. prior_model Either discrete (``discrete``) or continuous (``continuous``). This affects the role of `F` and `L`. Optional. Default is `continuous`. Raises ------ ValueError If `prior_model` is neither ``discrete`` nor ``continuous``. Returns ------- gaussian.SmoothingPosterior Smoothing distribution as returned by the Rauch-Tung-Striebel smoother. """ regression_problem = _setup_regression_problem( H=H, R=R, observations=observations, locations=locations ) prior_process = _setup_prior_process( F=F, L=L, m0=m0, C0=C0, t0=locations[0], prior_model=prior_model ) kalman = gaussian.Kalman(prior_process) return kalman.filtsmooth(regression_problem)[0] def _setup_prior_process(F, L, m0, C0, t0, prior_model): zero_shift_prior = np.zeros(F.shape[0]) if prior_model == "discrete": prior = randprocs.markov.discrete.LTIGaussian( transition_matrix=F, noise=randvars.Normal(mean=zero_shift_prior, cov=L), ) elif prior_model == "continuous": prior = randprocs.markov.continuous.LTISDE( drift_matrix=F, force_vector=zero_shift_prior, dispersion_matrix=L ) else: raise ValueError initrv = randvars.Normal(m0, C0) initarg = t0 prior_process = randprocs.markov.MarkovProcess( transition=prior, initrv=initrv, initarg=initarg ) return prior_process def _setup_regression_problem(H, R, observations, locations): zero_shift_mm = np.zeros(H.shape[0]) measmod = randprocs.markov.discrete.LTIGaussian( transition_matrix=H, noise=randvars.Normal(mean=zero_shift_mm, cov=R) ) measurement_models = [measmod] * len(locations) regression_problem = problems.TimeSeriesRegressionProblem( observations=observations, locations=locations, measurement_models=measurement_models, ) return regression_problem

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c48f97469bcb5bbfb857bb45e9d1464e81684949

41

py

Python

import_tensorflow_Code.py

vipulgote1999/Medium_blogs_content

889e155a0bb3fff58f2b684db52c9b5e84af388c

[ "Apache-2.0" ]

1

2020-05-03T06:17:51.000Z

import_tensorflow_Code.py

vipulgote1999/Medium_blogs_content

889e155a0bb3fff58f2b684db52c9b5e84af388c

[ "Apache-2.0" ]

null

import_tensorflow_Code.py

vipulgote1999/Medium_blogs_content

889e155a0bb3fff58f2b684db52c9b5e84af388c

[ "Apache-2.0" ]

null

import tensorflow tensorflow.__version__

13.666667

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null

0

1

0

1

0

5

c4b10a38bc1a23a5615ec743dbd578d234e524ee

143

py

Python

pdfforms/__init__.py

laserK3000/pdfforms

f3c7c29f26ce896aeafa8dde2c78e8f395a5c1fb

[ "MIT" ]

49

2017-08-01T19:24:11.000Z

2022-02-26T18:46:59.000Z

pdfforms/__init__.py

laserK3000/pdfforms

f3c7c29f26ce896aeafa8dde2c78e8f395a5c1fb

[ "MIT" ]

20

2017-11-17T08:53:09.000Z

2022-03-03T09:14:40.000Z

pdfforms/__init__.py

laserK3000/pdfforms

f3c7c29f26ce896aeafa8dde2c78e8f395a5c1fb

[ "MIT" ]

25

2018-03-22T16:31:46.000Z

2022-02-04T16:51:38.000Z

"inspect and fill pdf fillable forms" from .pdfforms import fill_pdfs, inspect_pdfs from .transforms import * from .version import __version__

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5

1ef90372daf0184cac610b6287316da4a390f837

5,552

py

Python

fsdviz/tests/api/test_cwt_api_xlsx.py

AdamCottrill/fsdivz

98dd1f35a08dba26424e2951a40715e01399478c

[ "MIT" ]

null

fsdviz/tests/api/test_cwt_api_xlsx.py

AdamCottrill/fsdivz

98dd1f35a08dba26424e2951a40715e01399478c

[ "MIT" ]

6

2020-02-12T00:03:40.000Z

2020-11-30T01:20:56.000Z

fsdviz/tests/api/test_cwt_api_xlsx.py

AdamCottrill/fsdviz

98dd1f35a08dba26424e2951a40715e01399478c

[ "MIT" ]

null

"""============================================================= c:/1work/fsdviz/fsdviz/tests/api/test_cwt_api_xlsx.py Created: 08 Mar 2021 11:35:22 DESCRIPTION: The tests in this file verify that the Excel download endpoints for cwt events returned the expected results. Essentially, the endpoints return as spreadsheet with basic stocking event information and cwt attributes. A. Cottrill ============================================================= """ import pytest from django.urls import reverse from rest_framework import status from ..pytest_fixtures import usfws, mdnr, superior, huron, cwt_stocking_events # here are the fields we expect to see in our downloaded spreadsheets or api # resposnes used to poplulate spreadsheets: FIELD_NAMES = [ "cwt_number", "tag_type", "seq_lower", "seq_upper", "manufacturer", "tag_reused", "multiple_lakes", "multiple_species", "multiple_strains", "multiple_yearclasses", "multiple_agencies", "stock_id", "agency_stock_id", "agency_code", "lake", "state", "jurisd", "man_unit", "grid10", "primary_location", "secondary_location", "latitude", "longitude", "year", "month", "day", "spc", "strain", "year_class", "mark", "clipcode", "stage", "method", "no_stocked", ] @pytest.mark.django_db def test_xlsx_download_events_xlsx(client, cwt_stocking_events): """Verify that the xlsx endpoint returns an excel spreadsheet with the appropraite keys. """ url = reverse("api:api-cwt-event-list-xlsx") response = client.get(url) assert response.status_code == status.HTTP_200_OK assert response.accepted_media_type == "application/xlsx" assert len(response.data) == 6 expected_fields = set(FIELD_NAMES) observed_fields = set(response.data[0].keys()) assert expected_fields == observed_fields def test_xlsx_download_events_xlsx_event_filters(client, cwt_stocking_events): """Verify that the xlsx endpoint returns an excel spreadsheet with the appropraite keys and subset of the records specified in the url parameters. This endpoint uses the same StockingEventFilter as other endpoints. The filter class has been thoughly tested elsewhere. this test just verifies that it is hooked up properly. """ url = reverse("api:api-cwt-event-list-xlsx") response = client.get(url, {"lake": "SU"}) assert response.status_code == status.HTTP_200_OK assert response.accepted_media_type == "application/xlsx" assert len(response.data) == 2 expected_fields = set(FIELD_NAMES) observed_fields = set(response.data[0].keys()) assert expected_fields == observed_fields # we filtered for one lake, so make sure that our response includes # events from just that lake: lakes = set([x["lake"] for x in response.data]) assert lakes == set( [ "SU", ] ) def test_xlsx_download_events_json(client, cwt_stocking_events): """Verifies that the download stocking events endpoint returns the expected json when json format is speficied. """ url = reverse("api:api-cwt-event-list-xlsx") response = client.get(url, {"format": "json"}) assert response.status_code == status.HTTP_200_OK assert response.accepted_media_type == "application/json" assert len(response.data) == 6 expected_fields = set(FIELD_NAMES) observed_fields = set(response.data[0].keys()) assert expected_fields == observed_fields def test_xlsx_download_events_json_event_filters(client, cwt_stocking_events): """Verifies that the download stocking events endpoint returns the expected json when json format is speficied. This endpoint uses the same StockingEventFilter as other endpoints. The filter class has been thoughly tested elsewhere. this test just verifies that it is hooked up properly. """ url = reverse("api:api-cwt-event-list-xlsx") response = client.get(url, {"format": "json", "lake": "SU"}) assert response.status_code == status.HTTP_200_OK assert response.accepted_media_type == "application/json" assert len(response.data) == 2 expected_fields = set(FIELD_NAMES) observed_fields = set(response.data[0].keys()) assert expected_fields == observed_fields # we filtered for one lake, so make sure that our response includes # events from just that lake: lakes = set([x["lake"] for x in response.data]) assert lakes == set( [ "SU", ] ) def test_xlsx_download_events_xlsx_event_cwt_numbers(client, cwt_stocking_events): """Verify that the xlsx endpoint returns an excel spreadsheet with the appropraite keys and subset of the records specified in the url parameters - specific cwts. This endpoint uses the same StockingEventFilter as other endpoints. """ url = reverse("api:api-cwt-event-list-xlsx") response = client.get(url, {"cwt_number": "111111,222222"}) assert response.status_code == status.HTTP_200_OK assert response.accepted_media_type == "application/xlsx" assert len(response.data) == 2 expected_fields = set(FIELD_NAMES) observed_fields = set(response.data[0].keys()) assert expected_fields == observed_fields # we filtered for one lake, so make sure that our response includes # events from just that lake: cwts = set([x["cwt_number"] for x in response.data]) assert cwts == set(["111111", "222222"])

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0

5

48465ad1b1e1238caa334a882ecfbcb1ddb63548

5,827

py

Python

tests/test_data_api.py

kailukowiak/aws-data-wrangler

ec6dc1fb35073c168e7da70343ec83f68eb4a6dc

[ "Apache-2.0" ]

1

2022-03-11T21:48:51.000Z

tests/test_data_api.py

kailukowiak/aws-data-wrangler

ec6dc1fb35073c168e7da70343ec83f68eb4a6dc

[ "Apache-2.0" ]

6

2022-03-14T09:32:43.000Z

2022-03-28T08:49:53.000Z

tests/test_data_api.py

Sleekbobby1011/aws-data-wrangler

5ec1b82d7662e81bdc69c35e4174ba8555493653

[ "Apache-2.0" ]

null

import pandas as pd import pytest import awswrangler as wr from ._utils import get_time_str_with_random_suffix @pytest.fixture def redshift_connector(databases_parameters): cluster_id = databases_parameters["redshift"]["identifier"] database = databases_parameters["redshift"]["database"] secret_arn = databases_parameters["redshift"]["secret_arn"] conn = wr.data_api.redshift.connect(cluster_id, database, secret_arn=secret_arn) return conn def create_rds_connector(rds_type, parameters): cluster_id = parameters[rds_type]["arn"] database = parameters[rds_type]["database"] secret_arn = parameters[rds_type]["secret_arn"] conn = wr.data_api.rds.connect(cluster_id, database, secret_arn=secret_arn) return conn @pytest.fixture def mysql_serverless_connector(databases_parameters): return create_rds_connector("mysql_serverless", databases_parameters) @pytest.fixture(scope="function") def mysql_serverless_table(mysql_serverless_connector): name = f"tbl_{get_time_str_with_random_suffix()}" print(f"Table name: {name}") yield name wr.data_api.rds.read_sql_query(f"DROP TABLE IF EXISTS test.{name}", con=mysql_serverless_connector) def test_data_api_redshift_columnless_query(redshift_connector): dataframe = wr.data_api.redshift.read_sql_query("SELECT 1", con=redshift_connector) unknown_column_indicator = "?column?" expected_dataframe = pd.DataFrame([[1]], columns=[unknown_column_indicator]) pd.testing.assert_frame_equal(dataframe, expected_dataframe) def test_data_api_redshift_basic_select(redshift_connector, redshift_table): wr.data_api.redshift.read_sql_query( f"CREATE TABLE public.{redshift_table} (id INT, name VARCHAR)", con=redshift_connector ) wr.data_api.redshift.read_sql_query( f"INSERT INTO public.{redshift_table} VALUES (42, 'test')", con=redshift_connector ) dataframe = wr.data_api.redshift.read_sql_query(f"SELECT * FROM public.{redshift_table}", con=redshift_connector) expected_dataframe = pd.DataFrame([[42, "test"]], columns=["id", "name"]) pd.testing.assert_frame_equal(dataframe, expected_dataframe) def test_data_api_redshift_empty_results_select(redshift_connector, redshift_table): wr.data_api.redshift.read_sql_query( f"CREATE TABLE public.{redshift_table} (id INT, name VARCHAR)", con=redshift_connector ) wr.data_api.redshift.read_sql_query( f"INSERT INTO public.{redshift_table} VALUES (42, 'test')", con=redshift_connector ) dataframe = wr.data_api.redshift.read_sql_query( f"SELECT * FROM public.{redshift_table} where id = 50", con=redshift_connector ) expected_dataframe = pd.DataFrame([], columns=["id", "name"]) pd.testing.assert_frame_equal(dataframe, expected_dataframe) def test_data_api_redshift_column_subset_select(redshift_connector, redshift_table): wr.data_api.redshift.read_sql_query( f"CREATE TABLE public.{redshift_table} (id INT, name VARCHAR)", con=redshift_connector ) wr.data_api.redshift.read_sql_query( f"INSERT INTO public.{redshift_table} VALUES (42, 'test')", con=redshift_connector ) dataframe = wr.data_api.redshift.read_sql_query(f"SELECT name FROM public.{redshift_table}", con=redshift_connector) expected_dataframe = pd.DataFrame([["test"]], columns=["name"]) pd.testing.assert_frame_equal(dataframe, expected_dataframe) def test_data_api_mysql_columnless_query(mysql_serverless_connector): dataframe = wr.data_api.rds.read_sql_query("SELECT 1", con=mysql_serverless_connector) expected_dataframe = pd.DataFrame([[1]], columns=["1"]) pd.testing.assert_frame_equal(dataframe, expected_dataframe) def test_data_api_mysql_basic_select(mysql_serverless_connector, mysql_serverless_table): wr.data_api.rds.read_sql_query( f"CREATE TABLE test.{mysql_serverless_table} (id INT, name VARCHAR(128), missing VARCHAR(256))", con=mysql_serverless_connector, ) wr.data_api.rds.read_sql_query( f"INSERT INTO test.{mysql_serverless_table} (id, name) VALUES (42, 'test')", con=mysql_serverless_connector ) dataframe = wr.data_api.rds.read_sql_query( f"SELECT * FROM test.{mysql_serverless_table}", con=mysql_serverless_connector ) expected_dataframe = pd.DataFrame([[42, "test", None]], columns=["id", "name", "missing"]) pd.testing.assert_frame_equal(dataframe, expected_dataframe) def test_data_api_mysql_empty_results_select(mysql_serverless_connector, mysql_serverless_table): wr.data_api.rds.read_sql_query( f"CREATE TABLE test.{mysql_serverless_table} (id INT, name VARCHAR(128))", con=mysql_serverless_connector ) wr.data_api.rds.read_sql_query( f"INSERT INTO test.{mysql_serverless_table} VALUES (42, 'test')", con=mysql_serverless_connector ) dataframe = wr.data_api.rds.read_sql_query( f"SELECT * FROM test.{mysql_serverless_table} where id = 50", con=mysql_serverless_connector ) expected_dataframe = pd.DataFrame([], columns=["id", "name"]) pd.testing.assert_frame_equal(dataframe, expected_dataframe) def test_data_api_mysql_column_subset_select(mysql_serverless_connector, mysql_serverless_table): wr.data_api.rds.read_sql_query( f"CREATE TABLE test.{mysql_serverless_table} (id INT, name VARCHAR(128))", con=mysql_serverless_connector ) wr.data_api.rds.read_sql_query( f"INSERT INTO test.{mysql_serverless_table} VALUES (42, 'test')", con=mysql_serverless_connector ) dataframe = wr.data_api.rds.read_sql_query( f"SELECT name FROM test.{mysql_serverless_table}", con=mysql_serverless_connector ) expected_dataframe = pd.DataFrame([["test"]], columns=["name"]) pd.testing.assert_frame_equal(dataframe, expected_dataframe)

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784

5,827

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0.050012

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null

0

1

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null

0

5

48539def99baac6154098570654746b9d3f34014

378

gyp

Python

deps/libgdal/gyp-formats/ogr_gpx.gyp

jimgambale/node-gdal

dc5c89fb23f1004732106250c8b7d57f380f9b61

[ "Apache-2.0" ]

462

2015-01-07T23:09:18.000Z

2022-03-30T03:58:09.000Z

deps/libgdal/gyp-formats/ogr_gpx.gyp

jimgambale/node-gdal

dc5c89fb23f1004732106250c8b7d57f380f9b61

[ "Apache-2.0" ]

196

2015-01-07T11:10:35.000Z

2022-03-29T08:50:30.000Z

deps/libgdal/gyp-formats/ogr_gpx.gyp

jimgambale/node-gdal

dc5c89fb23f1004732106250c8b7d57f380f9b61

[ "Apache-2.0" ]

113

2015-01-15T02:24:18.000Z

2021-11-22T06:05:52.000Z

{ "includes": [ "../common.gypi" ], "targets": [ { "target_name": "libgdal_ogr_gpx_frmt", "type": "static_library", "sources": [ "../gdal/ogr/ogrsf_frmts/gpx/ogrgpxdatasource.cpp", "../gdal/ogr/ogrsf_frmts/gpx/ogrgpxdriver.cpp", "../gdal/ogr/ogrsf_frmts/gpx/ogrgpxlayer.cpp" ], "include_dirs": [ "../gdal/ogr/ogrsf_frmts/gpx" ] } ] }

18.9

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5.119048

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56

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null

0

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null

0

1

0

5

485da43e00b524367edc641833f09e5bf2dbec6b

106

py

Python

hallo/test/modules/dailys/test_dailys_spreadsheet.py

SpangleLabs/Hallo

17145d8f76552ecd4cbc5caef8924bd2cf0cbf24

[ "MIT" ]

1

2022-01-27T13:25:01.000Z

hallo/test/modules/dailys/test_dailys_spreadsheet.py

joshcoales/Hallo

17145d8f76552ecd4cbc5caef8924bd2cf0cbf24

[ "MIT" ]

75

2015-09-26T18:07:18.000Z

2022-01-04T07:15:11.000Z

hallo/test/modules/dailys/test_dailys_spreadsheet.py

SpangleLabs/Hallo

17145d8f76552ecd4cbc5caef8924bd2cf0cbf24

[ "MIT" ]

1

2021-04-10T12:02:47.000Z

import unittest class Obj: pass class DailysSpreadsheetTest(unittest.TestCase): pass # TODO

8.153846

47

0.716981

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106

6.909091

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12

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null

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null

0

1

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0

1

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5

486e58978eb4ed6341492daf4452750ff0ce50bc

79

py

Python

dice-incomplete/dice/__main__.py

andredosreis/week-2

ca7c8213f3b4c4397a17aeca81c4b39ef680c7c3

[ "MIT" ]

null

dice-incomplete/dice/__main__.py

andredosreis/week-2

ca7c8213f3b4c4397a17aeca81c4b39ef680c7c3

[ "MIT" ]

null

dice-incomplete/dice/__main__.py

andredosreis/week-2

ca7c8213f3b4c4397a17aeca81c4b39ef680c7c3

[ "MIT" ]

null

from game.director import Director director = Director() director.start_game()

19.75

34

0.810127

10

79

6.3

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0.101266

79

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null

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1

0

null

0

1

0

5

4881775be1b5b3b15bcd7f56fd31f298d451f545

234

py

Python

state/state.py

Gleamo/gleamo-device

6b7c24ad1683e931cacf2ce9c5aa8d3b16616503

[ "BSD-2-Clause" ]

1

2017-05-02T15:15:03.000Z

state/state.py

Gleamo/gleamo-python

6b7c24ad1683e931cacf2ce9c5aa8d3b16616503

[ "BSD-2-Clause" ]

4

2017-05-02T13:50:15.000Z

2017-05-02T16:12:38.000Z

state/state.py

Gleamo/gleamo-python

6b7c24ad1683e931cacf2ce9c5aa8d3b16616503

[ "BSD-2-Clause" ]

null

from colors.color import Color from buzzer.buzzer_pattern import BuzzerPattern class State: def __init__(self, color: Color, buzzer_pattern: BuzzerPattern): self.color = color self.buzzer_pattern = buzzer_pattern

29.25

68

0.75641

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234

5.827586

0.413793

0.307692

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234

7

69

33.428571

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null

1

0

1

0

null

0

1

0

1

0

5

4882a7772478acff8ca36abe5695e106ee8bc849

57

py

Python

example_SetlX_stat_code/stat_python_code/stat_paretoCDF.py

leonmutschke/setlX

a10333405cba3d9d814d7de9e160561bd5fa4f76

[ "BSD-3-Clause" ]

28

2015-01-14T11:12:02.000Z

2022-02-15T21:06:05.000Z

example_SetlX_stat_code/stat_python_code/stat_paretoCDF.py

leonmutschke/setlX

a10333405cba3d9d814d7de9e160561bd5fa4f76

[ "BSD-3-Clause" ]

6

2016-08-01T14:21:37.000Z

2018-06-03T17:15:00.000Z

example_SetlX_stat_code/stat_python_code/stat_paretoCDF.py

leonmutschke/setlX

a10333405cba3d9d814d7de9e160561bd5fa4f76

[ "BSD-3-Clause" ]

18

2015-02-11T21:10:18.000Z

2018-05-02T07:41:41.000Z

from scipy.stats import pareto print(pareto.cdf(6,3,0,3))

28.5

30

0.77193

12

57

3.666667

0.833333

0

0.075472

0.070175

57

2

31

28.5

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0

1

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true

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1

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null

0

1

0

1

0

1

0

5

6fa2b7754fc697ffa50626635b691429ef47a9ba

84

py

Python

opteryx/third_party/abctree/__init__.py

mabel-dev/opteryx

8eb9d1b272476aba738aa2fcf8f8d3a798d6325c

[ "Apache-2.0" ]

1

2022-02-05T18:36:09.000Z

opteryx/third_party/abctree/__init__.py

mabel-dev/opteryx

8eb9d1b272476aba738aa2fcf8f8d3a798d6325c

[ "Apache-2.0" ]

43

2021-12-29T22:33:49.000Z

2022-03-25T20:12:07.000Z

opteryx/third_party/abctree/__init__.py

mabel-dev/opteryx

8eb9d1b272476aba738aa2fcf8f8d3a798d6325c

[ "Apache-2.0" ]

1

2022-01-26T21:44:15.000Z

import pyximport pyximport.install() from .abc_tree import ABCTree # type:ignore

14

44

0.785714

11

84

5.909091

0.818182

0

0.142857

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5

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null

0

1

0

1

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1

0

5

6fb5b4d052de7e486a34452fb98fd76e27c122e8

152

py

Python

suricate/preutils/__init__.py

ogierpaul/suricate

fd43627e5d2a92fe4bf7b562f65ab89ec07ee49c

[ "MIT" ]

1

2019-06-04T22:11:21.000Z

suricate/preutils/__init__.py

ogierpaul/wookie

fd43627e5d2a92fe4bf7b562f65ab89ec07ee49c

[ "MIT" ]

4

2020-03-31T03:52:32.000Z

2020-04-20T20:17:13.000Z

suricate/preutils/__init__.py

ogierpaul/wookie

fd43627e5d2a92fe4bf7b562f65ab89ec07ee49c

[ "MIT" ]

1

2020-04-18T08:51:17.000Z

from suricate.preutils.functionclassifier import FunctionClassifier from suricate.preutils.indextools import concatixnames, addsuffix, createmultiindex

50.666667

83

0.894737

14

152

9.714286

0.642857

0.176471

0.294118

0

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152

2

84

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0

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null

0

1

0

1

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5

6fe1774b5369c3afd6f3bb6008b0c1c213284a00

192

py

Python

students/K33422/laboratory_works/Kirillov_Nikolay/laboratory_work_4/hotel_app/admin.py

NikolayKirillov/ITMO_ICT_WebDevelopment_2020-2021

77ea82c38eb25c8fd61815b92e4cb006708a6de7

[ "MIT" ]

null

students/K33422/laboratory_works/Kirillov_Nikolay/laboratory_work_4/hotel_app/admin.py

NikolayKirillov/ITMO_ICT_WebDevelopment_2020-2021

77ea82c38eb25c8fd61815b92e4cb006708a6de7

[ "MIT" ]

null

students/K33422/laboratory_works/Kirillov_Nikolay/laboratory_work_4/hotel_app/admin.py

NikolayKirillov/ITMO_ICT_WebDevelopment_2020-2021

77ea82c38eb25c8fd61815b92e4cb006708a6de7

[ "MIT" ]

null

from django.contrib import admin from .models import * admin.site.register(Room) admin.site.register(Guest) admin.site.register(Staff) admin.site.register(Cleaning) admin.site.register(User)

21.333333

32

0.807292

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192

5.535714

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0

0.072917

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1

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0

null

0

1

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5

d2043fe4f3cc3799cdd45e8da1b4bb39cba16a36

485

py

Python

gxcutil/ecc/curve.py

ludorumjeoun/gxcutil

a5be3a14394c138de8c2ca04f21828d8d9bcf558

[ "MIT" ]

null

gxcutil/ecc/curve.py

ludorumjeoun/gxcutil

a5be3a14394c138de8c2ca04f21828d8d9bcf558

[ "MIT" ]

null

gxcutil/ecc/curve.py

ludorumjeoun/gxcutil

a5be3a14394c138de8c2ca04f21828d8d9bcf558

[ "MIT" ]

null

from .point import ECCPoint class Curve: @property def p(self)->int: raise NotImplementedError() @property def a(self)->int: raise NotImplementedError() @property def b(self)->int: raise NotImplementedError() @property def n(self)->int: raise NotImplementedError() @property def h(self)->int: raise NotImplementedError() @property def G(self)->ECCPoint: raise NotImplementedError()

17.321429

35

0.610309

48

485

6.166667

0.375

0.222973

0.202703

0.523649

0.709459

0

0.286598

485

27

36

17.962963

0.855491

0

0.6

0

1

0.3

false

0

0.05

0

0.4

0

null

1

0

1

0

null

0

1

0

5

d20665bcb0c66a1640ff3303834fb7eae99dfdcf

85

py

Python

utils/__init__.py

ridhwan-aziz/zipra_bot

de328e518aa6876fa91e96e007c198aae8ff2fd4

[ "MIT" ]

4

2021-11-11T03:44:21.000Z

2022-03-26T14:32:20.000Z

utils/__init__.py

ridhwan-aziz/zipra_bot

de328e518aa6876fa91e96e007c198aae8ff2fd4

[ "MIT" ]

2

2021-11-23T07:02:35.000Z

2022-02-11T13:49:07.000Z

utils/__init__.py

ridhwan-aziz/zipra_bot

de328e518aa6876fa91e96e007c198aae8ff2fd4

[ "MIT" ]

1

2021-11-25T13:30:24.000Z

from utils import chat_action, commands, database, errors, helper, init, lang, parser

85

0.8

12

85

5.583333

1

0

0.117647

85

1

85

0.893333

0

1

0

true

0

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0

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0

null

0

1

0

1

0

1

0

5

d24e0817597f1869fd9992e71dc7c79dfbf3b10a

27

py

Python

utils/__init__.py

dkloz/canvas-api-python

f704b00d91461264350a22451d79ad61db550322

[ "MIT" ]

8

2017-05-30T06:37:19.000Z

2021-09-13T19:56:52.000Z

utils/__init__.py

dkloz/canvas-api-python

f704b00d91461264350a22451d79ad61db550322

[ "MIT" ]

1

2016-05-13T17:37:58.000Z

2016-05-13T17:41:38.000Z

utils/__init__.py

dkloz/canvas-api-python

f704b00d91461264350a22451d79ad61db550322

[ "MIT" ]

10

2016-06-01T15:50:24.000Z

2021-07-07T20:08:52.000Z

# __author__ = 'dimitrios'

13.5

26

0.703704

2

27

7.5

1

0

0.148148

27

1

27

0.652174

0.888889

0

null

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0

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0

1

0

1

0

null

0

1

0

5

d25d45f1527a5fef688013a5bd13c322a6624342

172

py

Python

python-standard-library/exercise2.py

crobert7/Py-Basics

c1d1a1441de6cbee409c59ddda2b11bc7ee16df1

[ "MIT" ]

null

python-standard-library/exercise2.py

crobert7/Py-Basics

c1d1a1441de6cbee409c59ddda2b11bc7ee16df1

[ "MIT" ]

null

python-standard-library/exercise2.py

crobert7/Py-Basics

c1d1a1441de6cbee409c59ddda2b11bc7ee16df1

[ "MIT" ]

null

import emoji print(emoji.emojize('Python is :thumbs_up:')) print(emoji.emojize(':winking_face:', use_aliases=True)) msg = emoji.emojize('Howdy :sun_with_face:') print(msg)

34.4

56

0.755814

26

172

4.807692

0.653846

0.288

0.272

0

0.069767

172

5

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34.4

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0

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1

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1

0

null

0

1

0

5

d281fcc04f73b710cef69fb9413d915c4643a057

325

py

Python

persistence/mongo_impl.py

Leader0721/ManyIP

2964c213b67d3cde7d72f75caa4f79b2b0b8b777

[ "MIT" ]

629

2017-09-04T04:03:08.000Z

2022-03-27T19:49:47.000Z

persistence/mongo_impl.py

Leader0721/ManyIP

2964c213b67d3cde7d72f75caa4f79b2b0b8b777

[ "MIT" ]

7

2017-09-04T11:19:17.000Z

2021-04-10T02:43:33.000Z

persistence/mongo_impl.py

Leader0721/ManyIP

2964c213b67d3cde7d72f75caa4f79b2b0b8b777

[ "MIT" ]

119

2017-09-04T04:03:11.000Z

2021-12-20T07:58:22.000Z

# -*- coding: UTF-8 -*- from persistence.base import Base class Mongo(Base): def __init__(self): pass def list(self): pass def get(self): pass def update(self): pass def delete(self): pass def add(self): pass def handler(self): pass

12.5

33

0.513846

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4.179487

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0

null

0

1

0

1

0

1

0

5

9666f7710ac994a37437e95a6b41c27a6a901974

57

py

Python

vtr_flow/scripts/python_libs/vtr/ace/__init__.py

brycejh/vtr-verilog-to-routing

f61da5eb2d4e008728a01def827d55a0e9f285d0

[ "MIT" ]

682

2015-07-10T00:39:26.000Z

2022-03-30T05:24:53.000Z

vtr_flow/scripts/python_libs/vtr/ace/__init__.py

brycejh/vtr-verilog-to-routing

f61da5eb2d4e008728a01def827d55a0e9f285d0

[ "MIT" ]

1,399

2015-07-24T22:09:09.000Z

2022-03-29T06:22:48.000Z

vtr_flow/scripts/python_libs/vtr/ace/__init__.py

brycejh/vtr-verilog-to-routing

f61da5eb2d4e008728a01def827d55a0e9f285d0

[ "MIT" ]

311

2015-07-09T13:59:48.000Z

2022-03-28T00:15:20.000Z

""" init for the ACE module """ from .ace import run

11.4

27

0.614035

9

57

3.888889

0.888889

0

0.263158

57

4

28

14.25

0.833333

0.403509

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true

0

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1

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null

0

1

0

1

0

1

0

5

96848ce821b9d92b40034bdf24698055a86e731f

120

py

Python

tewn/audio/__init__.py

pundurs/tewn

7b45028a46b2e6e367c009b587e2eea828e5c6b2

[ "MIT" ]

1

2018-04-08T16:36:32.000Z

tewn/audio/__init__.py

pundurs/tewn

7b45028a46b2e6e367c009b587e2eea828e5c6b2

[ "MIT" ]

2

2018-04-08T15:24:54.000Z

2018-04-08T17:44:38.000Z

tewn/audio/__init__.py

pundurs/tewn

7b45028a46b2e6e367c009b587e2eea828e5c6b2

[ "MIT" ]

null

from .mic import (MicrophoneInput, MicrophoneInputException) __all__ = ['MicrophoneInput', 'MicrophoneInputException']

30

60

0.816667

8

120

11.75

0.75

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120

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1

0

1

0

null

0

1

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5

736d634cece2efe19e628a0aae08d69fe6515774

174

py

Python

flex/db/.~filters/__init__.py

centergy/flex

4fc11d3ad48e4b5016f53256015e3eed2157daae

[ "MIT" ]

null

flex/db/.~filters/__init__.py

centergy/flex

4fc11d3ad48e4b5016f53256015e3eed2157daae

[ "MIT" ]

null

flex/db/.~filters/__init__.py

centergy/flex

4fc11d3ad48e4b5016f53256015e3eed2157daae

[ "MIT" ]

null

from .ordering import Ordering from .pagination import PageNumberPagination, OffsetLimitPagination, BasePagination from .field_set import FieldSet from .search import Search

34.8

83

0.862069

19

174

7.842105

0.578947

0

0.103448

174

4

84

43.5

0.955128

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true

0

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null

0

1

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null

0

1

0

1

0

1

0

5

7378180376c954f299264c8c2014ecfd1cb131ea

45

py

Python

doc/images/MMMM_D_YYYY.py

oshikiri/vscode-datestrings

2891957004f6b7749012d6704e2fc403c5db5c18

[ "MIT" ]

null

doc/images/MMMM_D_YYYY.py

oshikiri/vscode-datestrings

2891957004f6b7749012d6704e2fc403c5db5c18

[ "MIT" ]

null

doc/images/MMMM_D_YYYY.py

oshikiri/vscode-datestrings

2891957004f6b7749012d6704e2fc403c5db5c18

[ "MIT" ]

null

# datestrings.dateFormat = "MMMM D, YYYY" 14

15

41

0.711111

6

45

5.333333

1

0

0.052632

0.155556

45

2

42

22.5

0.789474

0.866667

0

1

0

true

0

1

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null

0

1

0

1

0

null

0

1

0

5

73aab578974be04c029d9441381dd528f660a4d8

4,514

py

Python

banners.py

Niru-Ninja/Pylfer

42d7917a260028abc2c9490a6b11e642260a6509

[ "MIT" ]

null

banners.py

Niru-Ninja/Pylfer

42d7917a260028abc2c9490a6b11e642260a6509

[ "MIT" ]

null

banners.py

Niru-Ninja/Pylfer

42d7917a260028abc2c9490a6b11e642260a6509

[ "MIT" ]

null

import random def banner00(): print("\n\n") print(" ██▓███ ▓██ ██▓ ██▓ █████▒▓█████ ██▀███ ") print(" ▓██░ ██▒▒██ ██▒▓██▒ ▓██ ▒ ▓█ ▀ ▓██ ▒ ██▒") print(" ▓██░ ██▓▒ ▒██ ██░▒██░ ▒████ ░ ▒███ ▓██ ░▄█ ▒") print(" ▒██▄█▓▒ ▒ ░ ▐██▓░▒██░ ░▓█▒ ░ ▒▓█ ▄ ▒██▀▀█▄ ") print(" ▒██▒ ░ ░ ░ ██▒▓░░██████▒░▒█░ ░▒████▒░██▓ ▒██▒") print(" ▒▓▒░ ░ ░ ██▒▒▒ ░ ▒░▓ ░ ▒ ░ ░░ ▒░ ░░ ▒▓ ░▒▓░") print(" ░▒ ░ ▓██ ░▒░ ░ ░ ▒ ░ ░ ░ ░ ░ ░▒ ░ ▒░") print(" ░░ ▒ ▒ ░░ ░ ░ ░ ░ ░ ░░ ░ ") print(" ░ ░ ░ ░ ░ ░ ░ ") print(" ░ ░ ") print("\n\n\n\n") def banner01(): print("\n\n") print(" _____ _ ___ ") print(" | _ |_ _| | _|___ ___ ") print(" | __| | | | _| -_| _| ") print(" |__| |_ |_|_| |___|_| ") print(" |___| ") print("\n\n\n\n") def banner02(): print("\n\n") print(" ____ _ _ __ ____ ____ ____ ") print(" ( _ \( \/ )( ) ( __)( __)( _ \ ") print(" ) __/ ) / / (_/\ ) _) ) _) ) / ") print(" (__) (__/ \____/(__) (____)(__\_) ") print("\n\n\n\n") def banner03(): print("\n\n") print(" _____ _ __ ") print(" | __ \ | |/ _| ") print(" | |__) | _| | |_ ___ _ __ ") print(" | ___/ | | | | _/ _ \ '__|") print(" | | | |_| | | || __/ | ") print(" |_| \__, |_|_| \___|_| ") print(" __/ | ") print(" |___/ ") print("\n\n\n\n") def banner04(): print("\n\n") print(" ██████╗ ██╗ ██╗██╗ ███████╗███████╗██████╗ ") print(" ██╔══██╗╚██╗ ██╔╝██║ ██╔════╝██╔════╝██╔══██╗") print(" ██████╔╝ ╚████╔╝ ██║ █████╗ █████╗ ██████╔╝") print(" ██╔═══╝ ╚██╔╝ ██║ ██╔══╝ ██╔══╝ ██╔══██╗") print(" ██║ ██║ ███████╗██║ ███████╗██║ ██║") print(" ╚═╝ ╚═╝ ╚══════╝╚═╝ ╚══════╝╚═╝ ╚═╝") print("\n\n\n\n") def banner05(): print("\n\n") print(" _____ ") print(" ___ __ __/ / _/__ ____") print(" / _ \/ // / / _/ -_) __/") print(" / .__/\_, /_/_/ \__/_/ ") print(" /_/ /___/ ") print("\n\n\n\n") def banner06(): print("\n\n") print(" ▄▄▄· ▄· ▄▌▄▄▌ ·▄▄▄▄▄▄ .▄▄▄ ") print(" ▐█ ▄█▐█▪██▌██• ▐▄▄·▀▄.▀·▀▄ █· ") print(" ██▀·▐█▌▐█▪██▪ ██▪ ▐▀▀▪▄▐▀▀▄ ") print(" ▐█▪·• ▐█▀·.▐█▌▐▌██▌.▐█▄▄▌▐█•█▌ ") print(" .▀ ▀ • .▀▀▀ ▀▀▀ ▀▀▀ .▀ ▀ ") print("\n\n\n\n") def banner07(): print("\n\n") print(" __ ___ ") print(" [ | .' ..] ") print(" _ .--. _ __ | | _| |_ .---. _ .--. ") print(" [ '/'`\ \[ \ [ ]| |'-| |-'/ /__\\\[ `/'`\] ") print(" | \__/ | \ '/ / | | | | | \__., | | ") print(" | ;.__/[\_: / [___][___] '.__.'[___] ") print(" [__| \__.' ") print("\n\n\n\n") def banner08(): print("\n\n") print(" ____ __ __ _ _____ ___ ____ ") print(" | \| | || | | |/ _]| \ ") print(" | o ) | || | | __/ [_ | D ) ") print(" | _/| ~ || |___ | |_| _]| / ") print(" | | |___, || || _] [_ | \ ") print(" | | | || || | | || . \ ") print(" |__| |____/ |_____||__| |_____||__|\_| ") print("\n\n\n\n") def banner09(): print("\n\n") print(" █ ▄▄ ▀▄ ▄ █ ▄████ ▄███▄ █▄▄▄▄ ") print(" █ █ █ █ █ █▀ ▀ █▀ ▀ █ ▄▀ ") print(" █▀▀▀ ▀█ █ █▀▀ ██▄▄ █▀▀▌ ") print(" █ █ ███▄ █ █▄ ▄▀ █ █ ") print(" █ ▄▀ ▀ █ ▀███▀ █ ") print(" ▀ ▀ ▀ ") print("\n\n\n\n") def banner10(): print("\n\n") print(' 88""Yb Yb dP 88 888888 888888 88""Yb ') print(' 88__dP YbdP 88 88__ 88__ 88__dP ') print(' 88""" 8P 88 .o 88"" 88"" 88"Yb ') print(' 88 dP 88ood8 88 888888 88 Yb ') print("\n\n\n\n") def printBanner(): chosenFunction = random.randint(0,10) switcher = { 0: banner00, 1: banner01, 2: banner02, 3: banner03, 4: banner04, 5: banner05, 6: banner06, 7: banner07, 8: banner08, 9: banner09, 10: banner10 } func = switcher.get(chosenFunction, lambda: "\n Oops something went wrong: \n\n Pylfer!\n\n i guess... \n\n\n\n") func()

31.788732

120

0.271821

452

4,514

3.579646

0.309735

0.060569

0.25958

0.247837

0.225587

0.185414

0.163782

0

0.041392

0.395215

4,514

142

121

31.788732

0.310623

0

0.20339

0

0.008475

0.659351

0.016232

0

1

0.101695

false

0

0.008475

0

0.110169

0.762712

0

null

0

1

0

1

0

1

0

null

0

1

0

5

73dbb67f6a855bb4a046a7351d59b3a81f45c8f0

786

py

Python

setup.py

asheuh/flaskie

290fd2a6602abdf3b11434e2a72a3428acc0c0f4

[ "MIT" ]

7

2018-06-20T19:06:05.000Z

2019-11-03T02:23:20.000Z

setup.py

asheux/flaskie

290fd2a6602abdf3b11434e2a72a3428acc0c0f4

[ "MIT" ]

23

2018-07-09T13:00:22.000Z

2018-08-04T10:48:42.000Z

setup.py

asheux/flaskie

290fd2a6602abdf3b11434e2a72a3428acc0c0f4

[ "MIT" ]

1

2018-09-22T15:39:20.000Z

from setuptools import setup, find_packages setup( name='flaskie', version='1.0', description='User REST API based on Flask-RESTPlus', url='https://github.com/asheuh/flaskie', author='Brian Mboya', classifiers=[ 'Development Status :: 5 - Production/Stable', 'Intended Audience :: All', 'Topic :: Software Development :: Libraries :: Application Frameworks', 'License :: OSI Approved :: MIT License', 'Programming Language :: Python :: 2', 'Programming Language :: Python :: 2.7', 'Programming Language :: Python :: 3', 'Programming Language :: Python :: 3.4', 'Programming Language :: Python :: 3.5', 'Programming Language :: Python :: 3.6', ], packages=find_packages() )

34.173913

79

0.608142

80

786

5.95

0.6625

0.239496

0.315126

0.218487

0

0.022034

0.249364

786

23

80

34.173913

0.784746

0

0.612452

0

1

0

true

0

0.047619

0

0.047619

0

null

1

0

1

0

null

0

1

0

5

73dc18d649a6afe07a22c1d1b09c4e8f1b2757e3

82

py

Python

authentication/models.py

darkcloudb/DJANGO-twitterclone

1c6c05ce09fa8f780b35927a6c28d3dcdf74e640

[ "MIT" ]

null

authentication/models.py

darkcloudb/DJANGO-twitterclone

1c6c05ce09fa8f780b35927a6c28d3dcdf74e640

[ "MIT" ]

null

authentication/models.py

darkcloudb/DJANGO-twitterclone

1c6c05ce09fa8f780b35927a6c28d3dcdf74e640

[ "MIT" ]

null

from django.db import models # Create your models here. # No model required here

16.4

28

0.768293

13

82

4.846154

0.846154

0

0.182927

82

4

29

20.5

0.940299

0.573171

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

fb4816992fffb3aef5060f6688f871527e64a2a8

91

py

Python

models/baseline/random_model.py

RecKIE7/recsys2021-twitter

72f1cd1c0db84110b682684d588b24665860683d

[ "Apache-2.0" ]

null

models/baseline/random_model.py

RecKIE7/recsys2021-twitter

72f1cd1c0db84110b682684d588b24665860683d

[ "Apache-2.0" ]

null

models/baseline/random_model.py

RecKIE7/recsys2021-twitter

72f1cd1c0db84110b682684d588b24665860683d

[ "Apache-2.0" ]

null

import numpy as np def random_prediction_model(input_features): return np.random.rand()

18.2

44

0.802198

14

91

5

0.857143

0

0.120879

91

4

45

22.75

0.875

0

1

0.333333

false

0

0.333333

1

0

1

0

null

0

1

0

null

0

1

0

1

0

5

fbdfd1c4299617a52c243d1d104c03d56ef45c7c

49

py

Python

jdxapi/models/scripts/__init__.py

jobdataexchange/jdx-api

7815a6463de56423c3b4196648607c4ebe56828c

[ "Apache-2.0" ]

null

jdxapi/models/scripts/__init__.py

jobdataexchange/jdx-api

7815a6463de56423c3b4196648607c4ebe56828c

[ "Apache-2.0" ]

9

2019-12-26T17:39:58.000Z

2022-01-13T01:59:49.000Z

jdxapi/models/scripts/__init__.py

jobdataexchange/jdx-api

7815a6463de56423c3b4196648607c4ebe56828c

[ "Apache-2.0" ]

null

# from jdxapi.models.scripts.populate_db import *

49

0.816327

7

49

5.571429

1

0

0.081633

49

1

49

0.866667

0.959184

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

1

0

null

0

1

0

5

fbe116cf081990e331ead0bfde40f1990aabaa17

194

py

Python

app/annohub/models/language.py

inktrap/annohub

dd91035b18263ce91ea4c922d7e597176fbf6172

[ "MIT" ]

null

app/annohub/models/language.py

inktrap/annohub

dd91035b18263ce91ea4c922d7e597176fbf6172

[ "MIT" ]

null

app/annohub/models/language.py

inktrap/annohub

dd91035b18263ce91ea4c922d7e597176fbf6172

[ "MIT" ]

null

from annohub import db class Language(db.Document): u''' language information''' key = db.StringField(max_length=50, unique=True) name = db.StringField(max_length=50, unique=True)

24.25

53

0.716495

27

194

5.074074

0.62963

0.189781

0.233577

0.321168

0.49635

0

0.02454

0.159794

194

7

54

27.714286

0.815951

0.103093

0

1

0

false

0

0.2

0

0.8

0

1

0

null

0

1

0

1

0

null

0

1

0

5

839261b46829ad23f597326f038d443b8730253d

52

py

Python

test.py

ttkltll2/fisher_review

01070316d1e0854fb03460956b67c5c2ed0030be

[ "MIT" ]

null

test.py

ttkltll2/fisher_review

01070316d1e0854fb03460956b67c5c2ed0030be

[ "MIT" ]

null

test.py

ttkltll2/fisher_review

01070316d1e0854fb03460956b67c5c2ed0030be

[ "MIT" ]

null

#一个函数，可以序列化一个字典，一个列表， dict(a): dict(a.__dict__)

13

21

0.673077

8

52

3.875

0.625

0.322581

0.580645

0

0.134615

52

3

22

17.333333

0.688889

0.384615

0

null

0

null

0

1

0

null

1

0

1

0

null

0

1

0

5

83a1de5c5519e6e7cd5daae0d8a39e4435199c8a

101

py

Python

enthought/preferences/preferences.py

enthought/etsproxy

4aafd628611ebf7fe8311c9d1a0abcf7f7bb5347

[ "BSD-3-Clause" ]

3

2016-12-09T06:05:18.000Z

2018-03-01T13:00:29.000Z

enthought/preferences/preferences.py

enthought/etsproxy

4aafd628611ebf7fe8311c9d1a0abcf7f7bb5347

[ "BSD-3-Clause" ]

1

2020-12-02T00:51:32.000Z

2020-12-02T08:48:55.000Z

enthought/preferences/preferences.py

enthought/etsproxy

4aafd628611ebf7fe8311c9d1a0abcf7f7bb5347

[ "BSD-3-Clause" ]

null

# proxy module from __future__ import absolute_import from apptools.preferences.preferences import *

25.25

46

0.851485

12

101

6.75

0.666667

0

0.108911

101

3

47

33.666667

0.9

0.118812

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

83a4658172eaa4ed2ca9f541759038de0dd089d0

51

py

Python

application/blueprints/frontend/models.py

ChrisRx/flask-base

cb6a48aa4ddd1b89d2bcc1c34d327a94ce4bad6d

[ "MIT" ]

1

2015-04-22T00:10:51.000Z

application/blueprints/frontend/models.py

ChrisRx/flask-base

cb6a48aa4ddd1b89d2bcc1c34d327a94ce4bad6d

[ "MIT" ]

null

application/blueprints/frontend/models.py

ChrisRx/flask-base

cb6a48aa4ddd1b89d2bcc1c34d327a94ce4bad6d

[ "MIT" ]

null

import datetime from ...database import db, Model

12.75

33

0.764706

7

51

5.571429

0.857143

0

0.156863

51

3

34

17

0.906977

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

5

83b2ed2214c00f60d262302a3d79390cf0ac8667

764

py

Python

hyperverlet/transforms.py

Zinoex/hyperverlet

431ef92fa2448ce69c357f01c0862353067bfa8a

[ "MIT" ]

7

2021-08-02T09:10:35.000Z

2022-03-16T13:24:22.000Z

hyperverlet/transforms.py

Zinoex/hyperverlet

431ef92fa2448ce69c357f01c0862353067bfa8a

[ "MIT" ]

2

2021-06-15T11:50:59.000Z

2021-06-16T12:23:51.000Z

hyperverlet/transforms.py

Zinoex/hyperverlet

431ef92fa2448ce69c357f01c0862353067bfa8a

[ "MIT" ]

null

import torch class Coarsening: def __init__(self, coarsening_factor, trajectory_length=None): self.coarsening_factor = coarsening_factor self.trajectory_length = trajectory_length if trajectory_length is not None: assert (trajectory_length - 1) % coarsening_factor == 0 def __call__(self, q, p, t): q, p, t = self.coarse(q), self.coarse(p), self.coarse(t) return q, p, t def coarse(self, x): return x[::self.coarsening_factor] @property def new_trajectory_length(self): return (self.trajectory_length - 1) // self.coarsening_factor + 1 def compute_new_trajectory_length(self, trajectory_length): return (trajectory_length - 1) // self.coarsening_factor + 1

30.56

73

0.674084

97

764

5.020619

0.278351

0.328542

0.205339

0.094456

0.156057

0

0.010221

0.231675

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false

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5

83d98343113547044ce07aff6762d62df53d6125

322

py

Python

tests/paths.py

hectorpatino/feature_raster

34ec69e0e9fbfc697865f76d1c97627ba338bf7e

[ "BSD-3-Clause" ]

null

tests/paths.py

hectorpatino/feature_raster

34ec69e0e9fbfc697865f76d1c97627ba338bf7e

[ "BSD-3-Clause" ]

null

tests/paths.py

hectorpatino/feature_raster

34ec69e0e9fbfc697865f76d1c97627ba338bf7e

[ "BSD-3-Clause" ]

null

small_2018_dataset = r"data/original/raster/small_datasets/2018.tif" small_2010_dataset = r"data/original/raster/small_datasets/2010.tif" envelope_2018 = r"data/original/raster/real_datasets/2018/envelope_2018.img" coberture_2018_binary = r"data/original/vectorial/reals/2018_cobertures/binary/2018_binary_cobertures.shp"

64.4

106

0.854037

49

322

5.326531

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0.199234

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0.129032

0.037267

322

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