hexsha
string
size
int64
ext
string
lang
string
max_stars_repo_path
string
max_stars_repo_name
string
max_stars_repo_head_hexsha
string
max_stars_repo_licenses
list
max_stars_count
int64
max_stars_repo_stars_event_min_datetime
string
max_stars_repo_stars_event_max_datetime
string
max_issues_repo_path
string
max_issues_repo_name
string
max_issues_repo_head_hexsha
string
max_issues_repo_licenses
list
max_issues_count
int64
max_issues_repo_issues_event_min_datetime
string
max_issues_repo_issues_event_max_datetime
string
max_forks_repo_path
string
max_forks_repo_name
string
max_forks_repo_head_hexsha
string
max_forks_repo_licenses
list
max_forks_count
int64
max_forks_repo_forks_event_min_datetime
string
max_forks_repo_forks_event_max_datetime
string
content
string
avg_line_length
float64
max_line_length
int64
alphanum_fraction
float64
qsc_code_num_words_quality_signal
int64
qsc_code_num_chars_quality_signal
float64
qsc_code_mean_word_length_quality_signal
float64
qsc_code_frac_words_unique_quality_signal
float64
qsc_code_frac_chars_top_2grams_quality_signal
float64
qsc_code_frac_chars_top_3grams_quality_signal
float64
qsc_code_frac_chars_top_4grams_quality_signal
float64
qsc_code_frac_chars_dupe_5grams_quality_signal
float64
qsc_code_frac_chars_dupe_6grams_quality_signal
float64
qsc_code_frac_chars_dupe_7grams_quality_signal
float64
qsc_code_frac_chars_dupe_8grams_quality_signal
float64
qsc_code_frac_chars_dupe_9grams_quality_signal
float64
qsc_code_frac_chars_dupe_10grams_quality_signal
float64
qsc_code_frac_chars_replacement_symbols_quality_signal
float64
qsc_code_frac_chars_digital_quality_signal
float64
qsc_code_frac_chars_whitespace_quality_signal
float64
qsc_code_size_file_byte_quality_signal
float64
qsc_code_num_lines_quality_signal
float64
qsc_code_num_chars_line_max_quality_signal
float64
qsc_code_num_chars_line_mean_quality_signal
float64
qsc_code_frac_chars_alphabet_quality_signal
float64
qsc_code_frac_chars_comments_quality_signal
float64
qsc_code_cate_xml_start_quality_signal
float64
qsc_code_frac_lines_dupe_lines_quality_signal
float64
qsc_code_cate_autogen_quality_signal
float64
qsc_code_frac_lines_long_string_quality_signal
float64
qsc_code_frac_chars_string_length_quality_signal
float64
qsc_code_frac_chars_long_word_length_quality_signal
float64
qsc_code_frac_lines_string_concat_quality_signal
float64
qsc_code_cate_encoded_data_quality_signal
float64
qsc_code_frac_chars_hex_words_quality_signal
float64
qsc_code_frac_lines_prompt_comments_quality_signal
float64
qsc_code_frac_lines_assert_quality_signal
float64
qsc_codepython_cate_ast_quality_signal
float64
qsc_codepython_frac_lines_func_ratio_quality_signal
float64
qsc_codepython_cate_var_zero_quality_signal
bool
qsc_codepython_frac_lines_pass_quality_signal
float64
qsc_codepython_frac_lines_import_quality_signal
float64
qsc_codepython_frac_lines_simplefunc_quality_signal
float64
qsc_codepython_score_lines_no_logic_quality_signal
float64
qsc_codepython_frac_lines_print_quality_signal
float64
qsc_code_num_words
int64
qsc_code_num_chars
int64
qsc_code_mean_word_length
int64
qsc_code_frac_words_unique
null
qsc_code_frac_chars_top_2grams
int64
qsc_code_frac_chars_top_3grams
int64
qsc_code_frac_chars_top_4grams
int64
qsc_code_frac_chars_dupe_5grams
int64
qsc_code_frac_chars_dupe_6grams
int64
qsc_code_frac_chars_dupe_7grams
int64
qsc_code_frac_chars_dupe_8grams
int64
qsc_code_frac_chars_dupe_9grams
int64
qsc_code_frac_chars_dupe_10grams
int64
qsc_code_frac_chars_replacement_symbols
int64
qsc_code_frac_chars_digital
int64
qsc_code_frac_chars_whitespace
int64
qsc_code_size_file_byte
int64
qsc_code_num_lines
int64
qsc_code_num_chars_line_max
int64
qsc_code_num_chars_line_mean
int64
qsc_code_frac_chars_alphabet
int64
qsc_code_frac_chars_comments
int64
qsc_code_cate_xml_start
int64
qsc_code_frac_lines_dupe_lines
int64
qsc_code_cate_autogen
int64
qsc_code_frac_lines_long_string
int64
qsc_code_frac_chars_string_length
int64
qsc_code_frac_chars_long_word_length
int64
qsc_code_frac_lines_string_concat
null
qsc_code_cate_encoded_data
int64
qsc_code_frac_chars_hex_words
int64
qsc_code_frac_lines_prompt_comments
int64
qsc_code_frac_lines_assert
int64
qsc_codepython_cate_ast
int64
qsc_codepython_frac_lines_func_ratio
int64
qsc_codepython_cate_var_zero
int64
qsc_codepython_frac_lines_pass
int64
qsc_codepython_frac_lines_import
int64
qsc_codepython_frac_lines_simplefunc
int64
qsc_codepython_score_lines_no_logic
int64
qsc_codepython_frac_lines_print
int64
effective
string
hits
int64
1a48273fcffbd81bf82e527381a62c49f570d938
3,794
py
Python
2021/d25/d25.py
btharper/aoc
c4e265515da4b61b9e6704652a1d1175ddfd3f92
[ "Apache-2.0" ]
null
null
null
2021/d25/d25.py
btharper/aoc
c4e265515da4b61b9e6704652a1d1175ddfd3f92
[ "Apache-2.0" ]
null
null
null
2021/d25/d25.py
btharper/aoc
c4e265515da4b61b9e6704652a1d1175ddfd3f92
[ "Apache-2.0" ]
null
null
null
from collections import defaultdict, Counter, deque from functools import cache from itertools import product, pairwise from multiprocessing import Pool import math import re non_digits = re.compile('[^0-9]+') def sign(a, b, step=1): return int(math.copysign(step, b-a)) def autorange(a,b, step=1): if a == b:re...
29.410853
82
0.495783
596
3,794
3.010067
0.218121
0.014493
0.01505
0.015608
0.221293
0.17447
0.157191
0.148272
0.148272
0.123746
0
0.048077
0.342119
3,794
128
83
29.640625
0.670673
0.091987
0
0.23301
0
0
0.097955
0.018309
0
0
0
0
0.048544
1
0.058252
false
0.029126
0.058252
0.009709
0.174757
0.009709
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1a4c9682da4b81a0f168d8e9419bc7e161393b09
26,025
py
Python
build/releases/release-0.573py3/ob/ltr.py
farinacci/lispers.net
e1ed6e0f0a242b13ad629afb0fc1c7072b19b30c
[ "Apache-2.0" ]
26
2019-02-01T19:12:21.000Z
2022-03-25T04:40:38.000Z
build/releases/release-0.572py3/ob/ltr.py
farinacci/lispers.net
e1ed6e0f0a242b13ad629afb0fc1c7072b19b30c
[ "Apache-2.0" ]
3
2019-10-29T17:49:19.000Z
2022-03-20T21:21:31.000Z
build/releases/release-0.569/ob/ltr.py
farinacci/lispers.net
e1ed6e0f0a242b13ad629afb0fc1c7072b19b30c
[ "Apache-2.0" ]
4
2019-02-02T16:50:48.000Z
2020-10-29T03:10:58.000Z
#!/usr/bin/python # ----------------------------------------------------------------------------- # # Copyright 2013-2019 lispers.net - Dino Farinacci <farinacci@gmail.com> # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may o...
44.035533
152
0.621134
3,415
26,025
4.720937
0.157833
0.003163
0.004776
0.006947
0.092979
0.073998
0.053964
0.035852
0.035852
0.025183
0
0.171525
0.238117
26,025
590
153
44.110169
0.641567
0.181979
0
0.106776
0
0.002053
0.062872
0.003351
0
0
0.001699
0
0
1
0.022587
false
0.002053
0.024641
0
0.080082
0.051335
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1a52dc51601a35116aee6d656ad33ca1c1841e16
7,660
py
Python
tests/integration/test_autocommit.py
michaelcraige/neo4j-python-driver
27d0ce3f1941c4b29d0f050c6186a4f48ae4d30a
[ "Apache-2.0" ]
1
2021-05-18T14:11:39.000Z
2021-05-18T14:11:39.000Z
tests/integration/test_autocommit.py
michaelcraige/neo4j-python-driver
27d0ce3f1941c4b29d0f050c6186a4f48ae4d30a
[ "Apache-2.0" ]
null
null
null
tests/integration/test_autocommit.py
michaelcraige/neo4j-python-driver
27d0ce3f1941c4b29d0f050c6186a4f48ae4d30a
[ "Apache-2.0" ]
null
null
null
#!/usr/bin/env python # -*- encoding: utf-8 -*- # Copyright (c) 2002-2019 "Neo4j," # Neo4j Sweden AB [http://neo4j.com] # # This file is part of Neo4j. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the L...
33.160173
78
0.607441
978
7,660
4.623722
0.247444
0.050862
0.017691
0.029191
0.353383
0.303184
0.225343
0.194162
0.172932
0.145511
0
0.017749
0.264491
7,660
230
79
33.304348
0.784878
0.179896
0
0.326531
0
0.013605
0.132202
0.006882
0
0
0
0.004348
0.238095
1
0.142857
false
0
0.034014
0
0.176871
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1a5e520e42f56529133381c93cca81b7e91fe302
4,060
py
Python
tests/db/test_client.py
wxnacy/lfsdb
ff200e682ebafb9c806b8d5935c535d77b439981
[ "MIT" ]
null
null
null
tests/db/test_client.py
wxnacy/lfsdb
ff200e682ebafb9c806b8d5935c535d77b439981
[ "MIT" ]
null
null
null
tests/db/test_client.py
wxnacy/lfsdb
ff200e682ebafb9c806b8d5935c535d77b439981
[ "MIT" ]
null
null
null
#!/usr/bin/env python # -*- coding:utf-8 -*- # Author: wxnacy@gmail.com """ 随机方法 """ import pytest import os from wpy.path import read_dict from wpy.randoms import ( random_str ) from lfsdb import FileStorage from lfsdb.db import FileStorageError from lfsdb.db.errors import FSQueryError from lfsdb.d...
22.065217
82
0.599754
590
4,060
3.913559
0.19661
0.033781
0.052404
0.041143
0.257254
0.216977
0.174101
0.157644
0.104807
0.07709
0
0.014921
0.24064
4,060
183
83
22.185792
0.734025
0.02734
0
0.325581
0
0
0.076239
0
0
0
0
0.005464
0.139535
1
0.093023
false
0
0.077519
0
0.178295
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1a5fe65ea13d858d4fe548293ae1aefcbe8c803b
865
py
Python
days/dec6/dec6.py
denysvitali/aoc-2020
b0b3460c5043e4ce78a6ef00a40cc817953f6c43
[ "MIT" ]
null
null
null
days/dec6/dec6.py
denysvitali/aoc-2020
b0b3460c5043e4ce78a6ef00a40cc817953f6c43
[ "MIT" ]
null
null
null
days/dec6/dec6.py
denysvitali/aoc-2020
b0b3460c5043e4ce78a6ef00a40cc817953f6c43
[ "MIT" ]
null
null
null
import re example = "".join(open("example.txt").readlines()) puzzle = "".join(open("puzzle.txt").readlines()) problem_input = puzzle def parse_group(input: str): votes = input.split("\n") votes_map = dict() for vote in votes: for el in vote: if el not in votes_map: vo...
20.116279
50
0.552601
125
865
3.688
0.312
0.086768
0.071584
0.099783
0.273319
0.273319
0.273319
0.273319
0.273319
0.273319
0
0.008361
0.308671
865
42
51
20.595238
0.762542
0
0
0.322581
0
0
0.05896
0
0
0
0
0
0
1
0.096774
false
0
0.032258
0
0.225806
0.064516
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1a60a5f260cfd69458005fdf8f18f4a31de9980c
1,154
py
Python
integration_tests/web/test_issue_378.py
KharchenkoDmitriy/python-slack-sdk
5340ee337a2364e84c38d696c107f19c341dd6eb
[ "MIT" ]
null
null
null
integration_tests/web/test_issue_378.py
KharchenkoDmitriy/python-slack-sdk
5340ee337a2364e84c38d696c107f19c341dd6eb
[ "MIT" ]
null
null
null
integration_tests/web/test_issue_378.py
KharchenkoDmitriy/python-slack-sdk
5340ee337a2364e84c38d696c107f19c341dd6eb
[ "MIT" ]
null
null
null
import asyncio import logging import os import unittest from integration_tests.env_variable_names import SLACK_SDK_TEST_USER_TOKEN from integration_tests.helpers import async_test from slack import WebClient class TestWebClient(unittest.TestCase): """Runs integration tests with real Slack API https://github...
32.055556
118
0.740035
153
1,154
5.320261
0.392157
0.055283
0.047912
0.039312
0.358722
0.307125
0.307125
0.307125
0.307125
0.184275
0
0.009454
0.175043
1,154
35
119
32.971429
0.845588
0.085789
0
0.083333
0
0
0.055769
0.055769
0
0
0
0
0.083333
1
0.125
false
0.041667
0.291667
0
0.458333
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1a6106088407de4e7e1d70c09e88f77cac779b4b
7,199
py
Python
tune/iterative/asha.py
fugue-project/tune
bf2288ddcb29c8345d996a9b22c0910da9002da1
[ "Apache-2.0" ]
14
2021-03-03T20:02:09.000Z
2021-11-10T20:32:22.000Z
tune/iterative/asha.py
fugue-project/tune
bf2288ddcb29c8345d996a9b22c0910da9002da1
[ "Apache-2.0" ]
26
2021-04-30T19:56:06.000Z
2022-01-18T04:40:00.000Z
tune/iterative/asha.py
fugue-project/tune
bf2288ddcb29c8345d996a9b22c0910da9002da1
[ "Apache-2.0" ]
2
2021-04-30T03:12:21.000Z
2022-02-05T12:13:37.000Z
from threading import RLock from typing import Any, Callable, Dict, Iterable, List, Optional, Set, Tuple from triad import to_uuid from tune.concepts.flow import ( Monitor, Trial, TrialDecision, TrialJudge, TrialReport, TrialReportHeap, ) class RungHeap: def __init__(self, n: int): ...
33.640187
87
0.592999
838
7,199
4.836516
0.144391
0.041944
0.026647
0.022206
0.220331
0.175672
0.132248
0.067604
0.067604
0.020232
0
0.002786
0.301986
7,199
213
88
33.798122
0.803781
0.031115
0
0.241379
0
0
0.014066
0
0
0
0
0
0
1
0.149425
false
0
0.022989
0.045977
0.350575
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1a68ae4c6daaddebc3deeeeee768f2c7fe6d1bdb
1,936
py
Python
cuppa/methods/markdown_to_html.py
pwj58/cuppa
6c598a124c5aa52b459637ca1865cda2e2d300bd
[ "BSL-1.0" ]
25
2015-09-24T07:04:45.000Z
2022-02-19T03:31:03.000Z
cuppa/methods/markdown_to_html.py
pwj58/cuppa
6c598a124c5aa52b459637ca1865cda2e2d300bd
[ "BSL-1.0" ]
46
2015-05-20T12:48:12.000Z
2022-01-10T10:38:55.000Z
cuppa/methods/markdown_to_html.py
pwj58/cuppa
6c598a124c5aa52b459637ca1865cda2e2d300bd
[ "BSL-1.0" ]
13
2015-07-12T09:55:03.000Z
2021-07-02T15:32:12.000Z
# Copyright Jamie Allsop 2015-2015 # Distributed under the Boost Software License, Version 1.0. # (See accompanying file LICENSE_1_0.txt or copy at # http://www.boost.org/LICENSE_1_0.txt) #------------------------------------------------------------------------------- # MarkdownToHtmlMethod #--...
29.333333
154
0.547521
216
1,936
4.689815
0.402778
0.039487
0.032577
0.023692
0.100691
0.051333
0
0
0
0
0
0.011339
0.271178
1,936
65
155
29.784615
0.706591
0.192149
0
0.051282
0
0
0.083495
0
0
0
0
0
0
1
0.128205
false
0
0.102564
0
0.384615
0.025641
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1a68c8384b519235047d4e9148d15734f7c8bc80
3,718
py
Python
WIN_EventLog/OS_gathering/files/extracting.py
exastro-playbook-collection/OS-Windows2019
79c4f13e75ae1d4380d30f503f04ffb4dcf52ecf
[ "Apache-2.0" ]
null
null
null
WIN_EventLog/OS_gathering/files/extracting.py
exastro-playbook-collection/OS-Windows2019
79c4f13e75ae1d4380d30f503f04ffb4dcf52ecf
[ "Apache-2.0" ]
null
null
null
WIN_EventLog/OS_gathering/files/extracting.py
exastro-playbook-collection/OS-Windows2019
79c4f13e75ae1d4380d30f503f04ffb4dcf52ecf
[ "Apache-2.0" ]
1
2021-09-29T05:39:41.000Z
2021-09-29T05:39:41.000Z
import re import json import sys import os args = sys.argv if (len(args) < 2): sys.exit(1) path = args[1] if(path[-1:] == "/"): path = path[:-1] result_filedata_list = [] registry_info = {} target_filepath_list = [] target_filepath_list.append('/1/stdout.txt') target_filepath_list.append('/3/stdout.txt') f...
39.553191
84
0.516945
368
3,718
4.964674
0.206522
0.135194
0.078818
0.057471
0.58347
0.528736
0.492611
0.349206
0.269294
0.269294
0
0.008861
0.392953
3,718
93
85
39.978495
0.80062
0
0
0.428571
0
0
0.075599
0
0
0
0
0
0
1
0
false
0
0.047619
0
0.047619
0.011905
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1a6a4b81633f72d324dbf4acc99d2ef2ff1a4ab9
5,603
py
Python
src/datamanager/dataset.py
iN1k1/deep-pyramidal-representations-peron-re-identification
18eacd3b7bde2c4767ba290b655cb0f5c72ed8fe
[ "MIT" ]
13
2019-08-09T08:33:27.000Z
2020-12-21T08:51:33.000Z
src/datamanager/dataset.py
iN1k1/deep-pyramidal-representations-peron-re-identification
18eacd3b7bde2c4767ba290b655cb0f5c72ed8fe
[ "MIT" ]
5
2021-03-19T02:17:23.000Z
2022-03-11T23:53:44.000Z
src/datamanager/dataset.py
iN1k1/deep-pyramidal-representations-peron-re-identification
18eacd3b7bde2c4767ba290b655cb0f5c72ed8fe
[ "MIT" ]
4
2019-11-06T08:02:21.000Z
2021-01-13T20:34:23.000Z
import pickle import os import numpy as np from .utils import make_dataset_images, find_classes from operator import itemgetter import copy class Dataset(object): def __init__(self, name, root_folder, im_size=None, in_memory=False): super(Dataset, self).__init__() self.name = name self.ima...
33.35119
130
0.598786
752
5,603
4.24734
0.168883
0.030056
0.028178
0.035066
0.36819
0.316531
0.285535
0.285535
0.251722
0.224796
0
0.002786
0.295377
5,603
167
131
33.550898
0.806231
0.107799
0
0.087719
0
0
0.008454
0
0
0
0
0.005988
0
1
0.140351
false
0.017544
0.052632
0.04386
0.289474
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1a6b3b67a196647e34aaaebda16a46305f5a9bec
1,565
py
Python
ada_loss/chainer_impl/ada_loss_transforms.py
kumasento/gradient-scaling
0ca435433b9953e33656173c4d60ebd61c5c5e87
[ "MIT" ]
7
2020-08-12T12:04:28.000Z
2021-11-22T15:56:08.000Z
ada_loss/chainer_impl/ada_loss_transforms.py
kumasento/gradient-scaling
0ca435433b9953e33656173c4d60ebd61c5c5e87
[ "MIT" ]
1
2021-10-07T08:37:39.000Z
2021-10-08T02:41:39.000Z
ada_loss/chainer_impl/ada_loss_transforms.py
kumasento/gradient-scaling
0ca435433b9953e33656173c4d60ebd61c5c5e87
[ "MIT" ]
null
null
null
""" Implement the transformations we need to use to convert a link to an adaptive loss scaled link. """ # NOTE: this file is deprecated import chainer import chainer.links as L import chainer.initializers as I # pylint: disable=unused-wildcard-import from ada_loss.chainer_impl.links import * __all__ = [ "Ada...
24.84127
86
0.623642
169
1,565
5.579882
0.443787
0.041357
0.034995
0.04772
0.282078
0.26299
0.26299
0.26299
0.26299
0.26299
0
0.003559
0.281789
1,565
62
87
25.241935
0.835409
0.120767
0
0.3
0
0
0.074738
0.038117
0
0
0
0
0.05
1
0.075
false
0
0.1
0
0.35
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1a6d9e1b1f6a95c204998e268f6dedde3030bfcb
4,451
py
Python
atlas/foundations_rest_api/src/acceptance/v2beta/test_artifact_loading.py
DeepLearnI/atlas
8aca652d7e647b4e88530b93e265b536de7055ed
[ "Apache-2.0" ]
296
2020-03-16T19:55:00.000Z
2022-01-10T19:46:05.000Z
atlas/foundations_rest_api/src/acceptance/v2beta/test_artifact_loading.py
DeepLearnI/atlas
8aca652d7e647b4e88530b93e265b536de7055ed
[ "Apache-2.0" ]
57
2020-03-17T11:15:57.000Z
2021-07-10T14:42:27.000Z
atlas/foundations_rest_api/src/acceptance/v2beta/test_artifact_loading.py
DeepLearnI/atlas
8aca652d7e647b4e88530b93e265b536de7055ed
[ "Apache-2.0" ]
38
2020-03-17T21:06:05.000Z
2022-02-08T03:19:34.000Z
from foundations_spec import * from acceptance.api_acceptance_test_case_base import APIAcceptanceTestCaseBase from acceptance.v2beta.jobs_tests_helper_mixin_v2 import JobsTestsHelperMixinV2 class TestArtifactLoading(JobsTestsHelperMixinV2, APIAcceptanceTestCaseBase): url = '/api/v2beta/projects/{_project_name}/...
38.704348
121
0.682768
473
4,451
6.021142
0.230444
0.054073
0.065309
0.073736
0.420646
0.300913
0.268258
0.204354
0.064256
0.064256
0
0.018182
0.221523
4,451
115
122
38.704348
0.803752
0
0
0.139535
0
0
0.184228
0.022692
0
0
0
0
0.034884
1
0.069767
false
0
0.127907
0
0.255814
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1a6deb9d77ae7f9dd3a6a89e5e68c8dd4e802884
16,234
py
Python
model/state_encoder_model.py
lil-lab/cerealbar_generation
41153537c0bd8aed97f2ea841165477a8c480d58
[ "MIT" ]
null
null
null
model/state_encoder_model.py
lil-lab/cerealbar_generation
41153537c0bd8aed97f2ea841165477a8c480d58
[ "MIT" ]
null
null
null
model/state_encoder_model.py
lil-lab/cerealbar_generation
41153537c0bd8aed97f2ea841165477a8c480d58
[ "MIT" ]
null
null
null
import os, sys, copy import pickle import math import time import numpy as np from typing import Dict, Any, List, Set, Tuple import torch import torch.nn.functional as F from torch import nn from torch.nn.utils.rnn import pad_sequence import torch.nn.utils.rnn as rnn_utils from agent.environment.position import Pos...
44.721763
132
0.620549
2,037
16,234
4.598429
0.136475
0.051671
0.029892
0.03459
0.33223
0.236468
0.180634
0.115192
0.096402
0.07804
0
0.013766
0.284034
16,234
362
133
44.845304
0.792136
0.049526
0
0.21843
0
0
0.059947
0.012665
0
0
0
0
0.006826
1
0.017065
false
0.003413
0.068259
0.003413
0.102389
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1a6e8546353af8e6a5051dfc50d1bb801c40b2af
2,247
py
Python
tensorlayer/layers/noise.py
Howdy-Personally/tensorlayer-master
bb92e4e187419d5e7ded8331d5c7cbf5615ee744
[ "Apache-2.0" ]
4,484
2017-12-27T03:28:35.000Z
2021-12-02T14:42:58.000Z
tensorlayer/layers/noise.py
Howdy-Personally/tensorlayer-master
bb92e4e187419d5e7ded8331d5c7cbf5615ee744
[ "Apache-2.0" ]
549
2017-12-28T07:19:52.000Z
2021-11-05T02:34:20.000Z
tensorlayer/layers/noise.py
Howdy-Personally/tensorlayer-master
bb92e4e187419d5e7ded8331d5c7cbf5615ee744
[ "Apache-2.0" ]
1,076
2017-12-27T12:25:46.000Z
2021-11-24T09:12:36.000Z
#! /usr/bin/python # -*- coding: utf-8 -*- import tensorflow as tf import tensorlayer as tl from tensorlayer import logging from tensorlayer.decorators import deprecated_alias from tensorlayer.layers.core import Layer __all__ = [ 'GaussianNoise', ] class GaussianNoise(Layer): """ The :class:`GaussianNo...
27.072289
114
0.595461
283
2,247
4.583039
0.374558
0.03084
0.012336
0.01542
0
0
0
0
0
0
0
0.01601
0.277259
2,247
82
115
27.402439
0.782635
0.377837
0
0
0
0
0.076507
0.018547
0
0
0
0
0
1
0.1
false
0.025
0.125
0
0.325
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1a700cc75c7db30432b3bee2d9bb6579a2ada503
2,195
py
Python
examples/example_plots.py
lupify/pynverse
b943b49a0a398a00d4e712f492721f3dfa77ed52
[ "MIT" ]
46
2016-10-30T19:59:36.000Z
2022-03-01T10:59:11.000Z
examples/example_plots.py
Phibedy/pynverse
afa62d1f8f59110cced17471e57d7a1b6ab4f1df
[ "MIT" ]
3
2018-04-04T10:50:57.000Z
2021-12-03T16:55:57.000Z
examples/example_plots.py
Phibedy/pynverse
afa62d1f8f59110cced17471e57d7a1b6ab4f1df
[ "MIT" ]
9
2016-12-09T00:32:26.000Z
2022-01-17T12:24:29.000Z
from pynverse import inversefunc, piecewise import numpy as np import matplotlib.pyplot as plt import scipy cube = lambda x: x**3 invcube = inversefunc(cube) invcube_a = lambda x: scipy.special.cbrt(x) square = lambda x: x**2 invsquare = inversefunc(square, domain=0) invsquare_a = lambda x: x**(1/2.) ...
30.486111
102
0.62779
421
2,195
3.232779
0.194774
0.092579
0.052902
0.066128
0.133725
0.099927
0.076414
0.076414
0.076414
0.044085
0
0.109984
0.146697
2,195
72
103
30.486111
0.616658
0
0
0.037736
0
0
0.047059
0
0
0
0
0
0
1
0.018868
false
0
0.075472
0
0.09434
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1a70a409960397bfd1f99c4022d1a0d3e8addf9d
174
py
Python
modulo 3/aulas/5.5 - Funcao fatorial.py
GabrielBrotas/Python
9441b6b86ff3cb7fa5921b508c484075adac08b3
[ "MIT" ]
null
null
null
modulo 3/aulas/5.5 - Funcao fatorial.py
GabrielBrotas/Python
9441b6b86ff3cb7fa5921b508c484075adac08b3
[ "MIT" ]
null
null
null
modulo 3/aulas/5.5 - Funcao fatorial.py
GabrielBrotas/Python
9441b6b86ff3cb7fa5921b508c484075adac08b3
[ "MIT" ]
null
null
null
def fatorial(num=1): f = 1 for c in range(num, 1, -1): f *= c return f n = int(input('Digite um numero: ')) print(f'O fatorial de {n}: {fatorial(n)}')
15.818182
42
0.528736
31
174
2.967742
0.612903
0.086957
0
0
0
0
0
0
0
0
0
0.032258
0.287356
174
10
43
17.4
0.709677
0
0
0
0
0
0.289017
0
0
0
0
0
0
1
0.142857
false
0
0
0
0.285714
0.142857
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1a714779778dd4a1ce1758b9319d7fbb68580ce1
6,017
py
Python
Kijiji-Scraper.py
YounesZ/Kijiji-Scraper
23d19a8551e18d7478e814d0e71669ae7087f248
[ "MIT" ]
null
null
null
Kijiji-Scraper.py
YounesZ/Kijiji-Scraper
23d19a8551e18d7478e814d0e71669ae7087f248
[ "MIT" ]
null
null
null
Kijiji-Scraper.py
YounesZ/Kijiji-Scraper
23d19a8551e18d7478e814d0e71669ae7087f248
[ "MIT" ]
null
null
null
#!C:\Python34\scrapper\Scripts # Place url, linking to ad list, with desired search filters here. url_to_scrape = "http://www.kijiji.ca/b-canot-kayak-paddle-board/quebec/kayak/k0c329l9001" # Set the delay in (s) that the programs waits before scraping again. scrape_delay = 600 # 600 = 10 mins # Set filename to stor...
31.668421
114
0.592156
820
6,017
4.236585
0.268293
0.043178
0.052389
0.074842
0.208693
0.123201
0.07369
0.055843
0.042602
0
0
0.007478
0.266578
6,017
189
115
31.835979
0.779742
0.112016
0
0.275168
0
0.006711
0.247043
0
0
0
0
0
0
1
0.040268
false
0.013423
0.053691
0
0.107383
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1a74249a03f2cae7503b71c858c78b242c87a346
424
py
Python
tests/test_rrpproxy_check_contact.py
ByteInternet/rrpproxy
9f644c8ed31f963f4eadc1dafea35e59006f89fc
[ "MIT" ]
3
2020-10-20T12:12:36.000Z
2021-12-11T19:10:20.000Z
tests/test_rrpproxy_check_contact.py
ByteInternet/rrpproxy
9f644c8ed31f963f4eadc1dafea35e59006f89fc
[ "MIT" ]
null
null
null
tests/test_rrpproxy_check_contact.py
ByteInternet/rrpproxy
9f644c8ed31f963f4eadc1dafea35e59006f89fc
[ "MIT" ]
null
null
null
from unittest.mock import patch from tests.test_rrpproxy_base import TestRRPProxyBase class TestRRPProxyCheckContact(TestRRPProxyBase): @patch('rrpproxy.RRPProxy.call') def test_calls_call_correctly(self, call_mock): response = self.proxy.check_contact('CONTACT-A') call_mock.assert_called_on...
32.615385
78
0.773585
51
424
6.176471
0.588235
0.07619
0.095238
0
0
0
0
0
0
0
0
0
0.134434
424
12
79
35.333333
0.858311
0
0
0
0
0
0.122642
0.051887
0
0
0
0
0.25
1
0.125
false
0
0.25
0
0.5
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1a75d4ccd2e54ea0708b468c31e7fe2bd3fd2f92
310
py
Python
docker-wrapper/parse_docker_args.py
Duke-GCB/docker-wrapper
004ca5cd067a177ec96ac40702b2f8cb9d57e440
[ "MIT" ]
null
null
null
docker-wrapper/parse_docker_args.py
Duke-GCB/docker-wrapper
004ca5cd067a177ec96ac40702b2f8cb9d57e440
[ "MIT" ]
null
null
null
docker-wrapper/parse_docker_args.py
Duke-GCB/docker-wrapper
004ca5cd067a177ec96ac40702b2f8cb9d57e440
[ "MIT" ]
null
null
null
import os def parse_mount(volume_spec): # Docker volumes may be "/src:dest:ro" or simply "/src" components = volume_spec.split(':') perm = 'w' # assume write perm if not specified src_path = components[0] # check if ro specified if components[-1] == 'ro': perm = 'r' return (src_path, perm)
25.833333
57
0.664516
47
310
4.276596
0.659574
0.099502
0
0
0
0
0
0
0
0
0
0.008097
0.203226
310
11
58
28.181818
0.805668
0.354839
0
0
0
0
0.02551
0
0
0
0
0
0
1
0.125
false
0
0.125
0
0.375
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1a76a52e6e7d5bdeb177ef8e685d702c16d3b2ac
20,415
py
Python
find_dups.py
colinrcooper/filedups
7a2271c84df85f45c9f67ab18976bebe347bc256
[ "MIT" ]
null
null
null
find_dups.py
colinrcooper/filedups
7a2271c84df85f45c9f67ab18976bebe347bc256
[ "MIT" ]
null
null
null
find_dups.py
colinrcooper/filedups
7a2271c84df85f45c9f67ab18976bebe347bc256
[ "MIT" ]
null
null
null
from __future__ import print_function import os, sys if sys.version_info[0] != 3 or sys.version_info[1] < 0: print('Your Python version is too old! Please use Python 3.0 or higher.') sys.exit(1) import hashlib import fnmatch import configparser import argparse import platform os.chdir(os.path.di...
48.262411
235
0.611903
2,035
20,415
6.092875
0.174447
0.03097
0.015082
0.017743
0.151706
0.079684
0.042584
0.037584
0.019356
0.015243
0
0.017927
0.240411
20,415
422
236
48.376777
0.781647
0.072692
0
0.173789
0
0
0.200703
0.025967
0
0
0
0
0
1
0.051282
false
0
0.019943
0
0.111111
0.150997
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1a79ab06520a99ff01196eabd99831377f229eee
13,208
py
Python
devday/devday/tests/test_utils_devdata.py
stefanbethke/devday_website
c4820e03b9dbb22a63b84f9d338f3a165a6d0354
[ "BSD-3-Clause" ]
null
null
null
devday/devday/tests/test_utils_devdata.py
stefanbethke/devday_website
c4820e03b9dbb22a63b84f9d338f3a165a6d0354
[ "BSD-3-Clause" ]
null
null
null
devday/devday/tests/test_utils_devdata.py
stefanbethke/devday_website
c4820e03b9dbb22a63b84f9d338f3a165a6d0354
[ "BSD-3-Clause" ]
null
null
null
from io import StringIO from cms.constants import TEMPLATE_INHERITANCE_MAGIC from cms.models import Page from cms.models.pluginmodel import CMSPlugin from cms.models.static_placeholder import StaticPlaceholder from django.conf import settings from django.contrib.auth import get_user_model from django.contrib.sites.mod...
43.022801
79
0.619397
1,514
13,208
5.243065
0.171731
0.084656
0.055682
0.039305
0.293777
0.177375
0.128244
0.094482
0.075082
0.075082
0
0.014637
0.275818
13,208
306
80
43.163399
0.815264
0.019534
0
0.116541
0
0
0.116743
0.001623
0
0
0
0.003268
0.199248
1
0.101504
false
0.003759
0.06391
0.007519
0.184211
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1a79eeac88453654638db9192535898ef31080d0
2,499
py
Python
xmantissa/suspension.py
jonathanj/mantissa
53e5502aba23ce99be78b27f923a276593033fe8
[ "MIT" ]
6
2016-02-17T15:04:53.000Z
2021-08-20T09:44:10.000Z
xmantissa/suspension.py
jonathanj/mantissa
53e5502aba23ce99be78b27f923a276593033fe8
[ "MIT" ]
62
2015-02-04T23:40:55.000Z
2021-02-18T19:56:02.000Z
xmantissa/suspension.py
jonathanj/mantissa
53e5502aba23ce99be78b27f923a276593033fe8
[ "MIT" ]
8
2015-11-15T17:26:42.000Z
2020-12-02T06:36:52.000Z
from twisted.python.components import registerAdapter from axiom.attributes import reference from axiom.item import Item from nevow.page import Element from xmantissa.ixmantissa import INavigableElement, INavigableFragment from xmantissa.webnav import Tab from zope.interface import implements, Interface class ISuspend...
32.454545
81
0.683473
234
2,499
7.299145
0.384615
0.02459
0.012295
0.044496
0.11007
0
0
0
0
0
0
0.000527
0.240496
2,499
76
82
32.881579
0.899368
0.088836
0
0.076923
0
0
0.02843
0
0
0
0
0
0
1
0.096154
false
0.019231
0.134615
0
0.384615
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1a7b4acea6211e0f11b6ce0b1340e0ebd3c19df0
1,889
py
Python
setup.py
brianredbeard/mischief
b58210eae304614ee6102fc4e29af4ce4d07de8f
[ "MIT" ]
null
null
null
setup.py
brianredbeard/mischief
b58210eae304614ee6102fc4e29af4ce4d07de8f
[ "MIT" ]
null
null
null
setup.py
brianredbeard/mischief
b58210eae304614ee6102fc4e29af4ce4d07de8f
[ "MIT" ]
null
null
null
############################################## # The MIT License (MIT) # Copyright (c) 2019 Kevin Walchko # see LICENSE for full details ############################################## from __future__ import print_function from setuptools import setup from build_utils import BuildCommand from build_utils import Publis...
30.467742
78
0.654314
187
1,889
6.44385
0.545455
0.049793
0.058091
0.082988
0
0
0
0
0
0
0
0.005239
0.191636
1,889
61
79
30.967213
0.78389
0.043939
0
0.039216
0
0
0.353801
0.018713
0
0
0
0
0
1
0
false
0
0.137255
0
0.137255
0.019608
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1a7bf867c1b1bbf1814a6ce1e2bd6f07d0bcafef
9,244
py
Python
metadamage/main.py
ChristianMichelsen/metadamage
f2cd8b24ae93f50c8e64202b484c5cba973ae167
[ "MIT" ]
3
2021-01-18T12:12:01.000Z
2021-01-18T15:10:43.000Z
metadamage/main.py
ChristianMichelsen/metadamage
f2cd8b24ae93f50c8e64202b484c5cba973ae167
[ "MIT" ]
7
2021-03-03T08:35:56.000Z
2021-11-04T08:34:54.000Z
metadamage/main.py
ChristianMichelsen/metadamage
f2cd8b24ae93f50c8e64202b484c5cba973ae167
[ "MIT" ]
1
2021-03-25T11:34:49.000Z
2021-03-25T11:34:49.000Z
# Scientific Library import matplotlib.pyplot as plt import numpy as np import pandas as pd # Standard Library from collections import defaultdict from concurrent.futures import ThreadPoolExecutor from functools import partial from importlib import reload import logging import os from pathlib import Path # Third Part...
23.521628
93
0.545219
1,160
9,244
4.081034
0.235345
0.034854
0.050697
0.053232
0.246092
0.199409
0.134981
0.109421
0.090621
0.068019
0
0.038037
0.343033
9,244
392
94
23.581633
0.741479
0.082756
0
0.293919
0
0
0.103248
0.004742
0
0
0
0
0
1
0.010135
false
0
0.050676
0
0.077703
0.006757
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1a7e3e87f84ae18c2e3e70c21079daec01376fa1
2,433
py
Python
compaction.py
robbassi/kvs
3242a70f9f214f90b2fa540f1049e836b62932d2
[ "MIT" ]
1
2020-10-07T16:47:07.000Z
2020-10-07T16:47:07.000Z
compaction.py
robbassi/kvs
3242a70f9f214f90b2fa540f1049e836b62932d2
[ "MIT" ]
7
2020-10-07T17:42:13.000Z
2020-12-15T00:43:41.000Z
compaction.py
robbassi/kvs
3242a70f9f214f90b2fa540f1049e836b62932d2
[ "MIT" ]
1
2020-10-07T16:49:06.000Z
2020-10-07T16:49:06.000Z
import sys from common import TOMBSTONE, Value from binio import kv_iter, kv_writer from typing import List, Optional, Tuple from os import scandir, stat from sstable import SSTable MIN_THRESHOLD = 4 MIN_SIZE = 50000000 class Bucket: def __init__(self): self.min = 0 self.max = 0 self.avg ...
31.192308
86
0.594328
304
2,433
4.641447
0.259868
0.029766
0.031892
0.022679
0.065202
0.065202
0
0
0
0
0
0.00944
0.303329
2,433
77
87
31.597403
0.823009
0
0
0.060606
0
0.015152
0.043157
0
0
0
0
0
0
1
0.136364
false
0.015152
0.090909
0.030303
0.333333
0.030303
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1a7ee06ae12edb30e9d03447739bff0ec37db3b6
8,002
py
Python
mrl/configs/make_continuous_agents.py
nicolascastanet/mrl
0623c40c3e03c6a4d3e495426eae765d9f8aa751
[ "MIT" ]
null
null
null
mrl/configs/make_continuous_agents.py
nicolascastanet/mrl
0623c40c3e03c6a4d3e495426eae765d9f8aa751
[ "MIT" ]
null
null
null
mrl/configs/make_continuous_agents.py
nicolascastanet/mrl
0623c40c3e03c6a4d3e495426eae765d9f8aa751
[ "MIT" ]
null
null
null
from mrl.import_all import * from argparse import Namespace import gym import time def make_ddpg_agent(base_config=default_ddpg_config, args=Namespace(env='InvertedPendulum-v2', tb='', parent_folder='/tmp/mrl', ...
35.564444
142
0.622969
1,006
8,002
4.690855
0.137177
0.045772
0.045772
0.050858
0.619411
0.536978
0.506463
0.478491
0.458148
0.458148
0
0.006972
0.265059
8,002
225
143
35.564444
0.795443
0.022744
0
0.362903
0
0
0.062644
0
0
0
0
0
0
1
0.032258
false
0
0.040323
0
0.104839
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1a80808d8e9e323c40e1bbd90918908a6dd8d9e0
4,036
py
Python
gpuexperiments/old/sharedmemory.py
hughperkins/gpu-experiments
3e5064e45682494be97190558807672b602f1c76
[ "BSD-2-Clause" ]
2
2016-07-05T05:52:18.000Z
2018-04-14T07:35:36.000Z
gpuexperiments/old/sharedmemory.py
hughperkins/gpu-experiments
3e5064e45682494be97190558807672b602f1c76
[ "BSD-2-Clause" ]
null
null
null
gpuexperiments/old/sharedmemory.py
hughperkins/gpu-experiments
3e5064e45682494be97190558807672b602f1c76
[ "BSD-2-Clause" ]
null
null
null
# Note that this will erase your nvidia cache, ~/.nv/ComputeCache This may or may not be an undesirable side-effect for you. For example, cutorch will take 1-2 minutes or so to start after this cache has been emptied. from __future__ import print_function, division import time import string import random import nump...
27.834483
219
0.652131
590
4,036
4.284746
0.291525
0.031646
0.047468
0.047073
0.294304
0.27057
0.200158
0.177215
0.090981
0.090981
0
0.022472
0.206145
4,036
144
220
28.027778
0.766542
0.106789
0
0.180328
0
0
0.379694
0.110153
0
0
0
0
0
1
0.032787
false
0
0.090164
0
0.139344
0.081967
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1a80cfa10b9df2618d9406f7d94897169d17a59a
4,827
py
Python
activities/boss_db.py
jhuapl-boss/boss-tools
2ace8ce2985ffa3c442ed85134d26c76fb5d984f
[ "Apache-2.0" ]
1
2018-08-04T21:57:34.000Z
2018-08-04T21:57:34.000Z
activities/boss_db.py
jhuapl-boss/boss-tools
2ace8ce2985ffa3c442ed85134d26c76fb5d984f
[ "Apache-2.0" ]
16
2018-05-21T16:28:10.000Z
2021-03-17T20:15:25.000Z
activities/boss_db.py
jhuapl-boss/boss-tools
2ace8ce2985ffa3c442ed85134d26c76fb5d984f
[ "Apache-2.0" ]
3
2018-02-08T16:45:59.000Z
2018-03-22T15:26:14.000Z
# Copyright 2020 The Johns Hopkins University Applied Physics Laboratory # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required...
33.061644
117
0.617982
619
4,827
4.720517
0.298869
0.024641
0.027379
0.031485
0.501027
0.501027
0.45859
0.450376
0.442847
0.442847
0
0.004695
0.293971
4,827
145
118
33.289655
0.8527
0.443132
0
0.474576
0
0
0.272293
0.039809
0
0
0
0
0
1
0.050847
false
0.033898
0.033898
0
0.135593
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1a81385c1aeda3274db449a3e0247ddc02d27f2f
15,454
py
Python
DataWrangler.py
AlexLamson/DataWrangler
3d4b64c30d708a55f4423a486ec9559f087c5acd
[ "MIT" ]
12
2018-08-15T15:12:52.000Z
2021-11-21T16:04:52.000Z
DataWrangler.py
AlexLamson/DataWrangler
3d4b64c30d708a55f4423a486ec9559f087c5acd
[ "MIT" ]
19
2018-06-04T15:11:01.000Z
2019-10-09T13:16:02.000Z
DataWrangler.py
AlexLamson/DataWrangler
3d4b64c30d708a55f4423a486ec9559f087c5acd
[ "MIT" ]
1
2019-04-09T16:23:30.000Z
2019-04-09T16:23:30.000Z
import sublime import sublime_plugin from collections import defaultdict from math import log10, floor, ceil import threading from subprocess import check_output import re import itertools # pass in a variable name and an optional default value # to get what that value is set to in settings def settings(name, default...
32.81104
123
0.631616
2,026
15,454
4.650543
0.132774
0.045001
0.013373
0.014859
0.686691
0.650074
0.624177
0.617173
0.606135
0.597856
0
0.004473
0.262197
15,454
470
124
32.880851
0.821873
0.155623
0
0.625514
0
0
0.047375
0.004878
0
0
0
0
0
1
0.057613
false
0
0.032922
0.004115
0.156379
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1a8180645e23b18d704d5f3aab84f4eda829d302
507
py
Python
resources/rasanlu/test.py
pmelet/tcnlu
4ad9267de4f2d3d269be5e7adb70686d4935865c
[ "Apache-2.0" ]
1
2018-09-13T08:36:15.000Z
2018-09-13T08:36:15.000Z
resources/rasanlu/test.py
pmelet/tcnlu
4ad9267de4f2d3d269be5e7adb70686d4935865c
[ "Apache-2.0" ]
6
2018-09-13T09:37:32.000Z
2018-09-26T07:54:59.000Z
resources/rasanlu/test.py
pmelet/tcnlu
4ad9267de4f2d3d269be5e7adb70686d4935865c
[ "Apache-2.0" ]
null
null
null
import sys, json, random from rasa_nlu.model import Interpreter from pprint import pprint interpreter = Interpreter.load("models\\current\\nlu") responses_file = sys.argv[1] responses = json.load(open(responses_file)) while True: question = input("> ") response = interpreter.parse(question) pprint(respo...
24.142857
54
0.70217
61
507
5.786885
0.52459
0.073654
0
0
0
0
0
0
0
0
0
0.002375
0.169625
507
20
55
25.35
0.836105
0
0
0.125
0
0
0.063116
0
0
0
0
0
0
1
0
false
0
0.1875
0
0.1875
0.3125
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1a89de4b46f00e88cfbed3e6547fad63b83b5448
31,473
py
Python
sapextractor/algo/prod/obj_centr_log.py
aarkue/sap-meta-explorer
613bf657bbaa72a3781a84664e5de7626516532f
[ "Apache-2.0" ]
null
null
null
sapextractor/algo/prod/obj_centr_log.py
aarkue/sap-meta-explorer
613bf657bbaa72a3781a84664e5de7626516532f
[ "Apache-2.0" ]
null
null
null
sapextractor/algo/prod/obj_centr_log.py
aarkue/sap-meta-explorer
613bf657bbaa72a3781a84664e5de7626516532f
[ "Apache-2.0" ]
null
null
null
import pandas as pd from dateutil import parser from pm4pymdl.objects.mdl.exporter import exporter as mdl_exporter from pm4pymdl.objects.ocel.exporter import exporter as ocel_exporter from sapextractor.utils.dates import timestamp_column_from_dt_tm from pandas.core.frame import DataFrame from sapextractor.database_conn...
71.205882
293
0.722302
3,892
31,473
5.457091
0.079394
0.055558
0.026932
0.047648
0.712275
0.616366
0.49814
0.423655
0.345591
0.308395
0
0.006957
0.114002
31,473
441
294
71.367347
0.754707
0.127951
0
0.174051
0
0.012658
0.264639
0.048249
0
0
0
0.002268
0
1
0.006329
false
0
0.022152
0
0.031646
0.246835
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1a8c55fdde1ff4ebdfeb884f8d8ccf37742a0471
2,676
py
Python
src/tempgen/parsers/docx.py
k5md/Templated-Generator
f3cd2bc6c7de6f68fa1e5835471e8eaa9163d530
[ "MIT" ]
null
null
null
src/tempgen/parsers/docx.py
k5md/Templated-Generator
f3cd2bc6c7de6f68fa1e5835471e8eaa9163d530
[ "MIT" ]
null
null
null
src/tempgen/parsers/docx.py
k5md/Templated-Generator
f3cd2bc6c7de6f68fa1e5835471e8eaa9163d530
[ "MIT" ]
null
null
null
import docx from tempgen.parsers.parser import AbstractParser class Parser(AbstractParser): def paragraph_replace_text(self, paragraph, str, replace_str): ''' https://github.com/python-openxml/python-docx/issues/30#issuecomment-881106471 ''' count = 0 search_pos = 0 ...
39.940299
125
0.563901
312
2,676
4.676282
0.24359
0.057574
0.047978
0.047978
0.201508
0.190541
0.05072
0.05072
0.05072
0.05072
0
0.009029
0.337818
2,676
67
126
39.940299
0.814334
0.029148
0
0.271186
0
0
0.013592
0
0
0
0
0
0
1
0.084746
false
0
0.033898
0
0.169492
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1a90e4197c82e64e65616870e1cd90e24176a9dd
466
py
Python
tf/easytensorflow.py
mutazag/mdsi_deeplearn
45776b3ec3ed952d59477c5f29e444c4de277f11
[ "MIT" ]
null
null
null
tf/easytensorflow.py
mutazag/mdsi_deeplearn
45776b3ec3ed952d59477c5f29e444c4de277f11
[ "MIT" ]
null
null
null
tf/easytensorflow.py
mutazag/mdsi_deeplearn
45776b3ec3ed952d59477c5f29e444c4de277f11
[ "MIT" ]
null
null
null
# https://github.com/easy-tensorflow/easy-tensorflow/blob/master/1_TensorFlow_Basics/Tutorials/1_Graph_and_Session.ipynb #%% import tensorflow as tf # tf.disable_eager_execution() #%% a = 2 b = 3 c = tf.add(a, b, name='Add') print(c) #%% # to run the graph, put it in a session and run sess = tf.Session() print(s...
13.314286
120
0.665236
77
466
3.935065
0.532468
0.092409
0.079208
0.085809
0
0
0
0
0
0
0
0.010309
0.167382
466
34
121
13.705882
0.770619
0.521459
0
0.181818
0
0
0.028708
0
0
0
0
0
0
1
0
false
0
0.090909
0
0.090909
0.363636
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1a92064954db18af7514af8bb12eb3b5c7406db8
639
py
Python
msk/consumer.py
wingkwong/aws-playground
5d395bb63e6f47bb4a536bab9e34ca0744e79c5d
[ "MIT" ]
1
2021-09-10T05:21:39.000Z
2021-09-10T05:21:39.000Z
msk/consumer.py
wingkwong/aws-playground
5d395bb63e6f47bb4a536bab9e34ca0744e79c5d
[ "MIT" ]
null
null
null
msk/consumer.py
wingkwong/aws-playground
5d395bb63e6f47bb4a536bab9e34ca0744e79c5d
[ "MIT" ]
null
null
null
from kafka import KafkaConsumer from json import loads # Define Amazon MSK Brokers brokers=['<YOUR_MSK_BROKER_1>:9092', '<YOUR_MSK_BROKER_2>:9092'] # Define Kafka topic to be consumed from kafka_topic='<YOUR_KAFKA_TOPIC>' # A Kafka client that consumes records from a Kafka cluster consumer = KafkaConsumer( ...
31.95
64
0.690141
83
639
5.108434
0.60241
0.09434
0.061321
0
0
0
0
0
0
0
0
0.021912
0.214398
639
19
65
33.631579
0.822709
0.192488
0
0
0
0
0.173828
0.09375
0
0
0
0
0
1
0
false
0
0.142857
0
0.142857
0.071429
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1a9611f6590b2309ddd6925053805e4c14110715
12,176
py
Python
MNIST_VAE.py
federicobergamin/Variational-Autoencoders
6cae335c82ec55aa5fa9f260e7daa2ad6ace453e
[ "MIT" ]
1
2019-12-23T12:12:13.000Z
2019-12-23T12:12:13.000Z
MNIST_VAE.py
federicobergamin/Variational-Autoencoders
6cae335c82ec55aa5fa9f260e7daa2ad6ace453e
[ "MIT" ]
null
null
null
MNIST_VAE.py
federicobergamin/Variational-Autoencoders
6cae335c82ec55aa5fa9f260e7daa2ad6ace453e
[ "MIT" ]
null
null
null
''' We are going to learn a latent space and a generative model for the MNIST dataset. ''' import numpy as np import torch import torch.utils import torch.utils.data from torch.utils.tensorboard import SummaryWriter import torchvision import torch.nn.functional as F from torchvision import datasets, transforms, utils...
37.931464
185
0.634938
1,587
12,176
4.686831
0.200378
0.020973
0.02541
0.015058
0.364076
0.323609
0.273998
0.261495
0.244421
0.229901
0
0.024639
0.243348
12,176
320
186
38.05
0.782698
0.224622
0
0.267327
0
0
0.127088
0.050749
0
0
0
0
0
1
0.009901
false
0
0.059406
0
0.069307
0.059406
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1a97c3f3a52c4076a37c5647166b601d480b1378
5,202
py
Python
examples/allennlp/allennlp_simple.py
kevtran23/optuna
4f2fa9c60d9a216ff3cfbc0f3ca12cb32ff53434
[ "MIT" ]
null
null
null
examples/allennlp/allennlp_simple.py
kevtran23/optuna
4f2fa9c60d9a216ff3cfbc0f3ca12cb32ff53434
[ "MIT" ]
null
null
null
examples/allennlp/allennlp_simple.py
kevtran23/optuna
4f2fa9c60d9a216ff3cfbc0f3ca12cb32ff53434
[ "MIT" ]
null
null
null
""" Optuna example that optimizes a classifier configuration for IMDB movie review dataset. This script is based on the example of allentune (https://github.com/allenai/allentune). In this example, we optimize the validation accuracy of sentiment classification using AllenNLP. Since it is too time-consuming to use the...
33.133758
113
0.716455
649
5,202
5.546995
0.360555
0.023333
0.0075
0.010833
0.147222
0.112222
0.076667
0.076667
0.076667
0.065
0
0.016321
0.175509
5,202
156
114
33.346154
0.823036
0.16436
0
0.018868
0
0.028302
0.106368
0
0
0
0
0
0
1
0.04717
false
0
0.113208
0
0.198113
0.04717
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1a98b5e99f3f08c40346d868f154e3474a9471fd
703
py
Python
main/increasing-order-search-tree/increasing-order-search-tree.py
EliahKagan/old-practice-snapshot
1b53897eac6902f8d867c8f154ce2a489abb8133
[ "0BSD" ]
null
null
null
main/increasing-order-search-tree/increasing-order-search-tree.py
EliahKagan/old-practice-snapshot
1b53897eac6902f8d867c8f154ce2a489abb8133
[ "0BSD" ]
null
null
null
main/increasing-order-search-tree/increasing-order-search-tree.py
EliahKagan/old-practice-snapshot
1b53897eac6902f8d867c8f154ce2a489abb8133
[ "0BSD" ]
null
null
null
# Definition for a binary tree node. # class TreeNode: # def __init__(self, x): # self.val = x # self.left = None # self.right = None class Solution: def increasingBST(self, root: TreeNode) -> TreeNode: head = TreeNode(None) link = head def dfs(subroot :...
26.037037
56
0.479374
69
703
4.826087
0.405797
0.081081
0.096096
0
0
0
0
0
0
0
0
0
0.445235
703
26
57
27.038462
0.853846
0.211949
0
0
0
0
0
0
0
0
0
0
0
1
0.133333
false
0
0
0
0.266667
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1a9922af72c1516621850ee44f2b5c699c589d4b
2,715
py
Python
src/lex.py
urlordjames/pointysnake
cac720068d55ffec8e7b220285e460faf6ceaa3e
[ "MIT" ]
1
2020-07-12T14:20:58.000Z
2020-07-12T14:20:58.000Z
src/lex.py
urlordjames/pointysnake
cac720068d55ffec8e7b220285e460faf6ceaa3e
[ "MIT" ]
5
2020-07-16T15:58:41.000Z
2020-07-24T01:42:59.000Z
src/lex.py
urlordjames/pointysnake
cac720068d55ffec8e7b220285e460faf6ceaa3e
[ "MIT" ]
null
null
null
def lex(filename): f = open(filename, "r") src = f.read() f.close() lines = src.split("\n") newlines = [] for line in lines: if len(line) < 1 or line[0] == "#": continue newlines.append(line) tokens = [] for line in newlines: tokens.append(toke...
28.882979
92
0.467403
270
2,715
4.67037
0.318519
0.057098
0.061063
0.099921
0.199841
0.149881
0.118953
0.118953
0.053925
0
0
0.023745
0.317495
2,715
93
93
29.193548
0.656773
0
0
0.130952
0
0
0.150645
0.007735
0
0
0
0
0.011905
1
0.02381
false
0
0.011905
0
0.059524
0.011905
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1a9abd84e1be3db2d14bf1598d2908aacba99eaf
417
py
Python
DailyChallenge/LC_198.py
iphyer/LeetcodeSummary
ad5229bbb8e76083e5c7f0312fa0c8ff78d516a9
[ "MIT" ]
null
null
null
DailyChallenge/LC_198.py
iphyer/LeetcodeSummary
ad5229bbb8e76083e5c7f0312fa0c8ff78d516a9
[ "MIT" ]
null
null
null
DailyChallenge/LC_198.py
iphyer/LeetcodeSummary
ad5229bbb8e76083e5c7f0312fa0c8ff78d516a9
[ "MIT" ]
null
null
null
class Solution: def rob(self, nums: List[int]) -> int: # DP # dp[i]: the max value until house i dp = [0] * len(nums) N = len(nums) if N == 1: return nums[0] if N == 2: return max(nums[0], nums[1]) dp[0] = nums[0] dp[1] = max(nums[0], nums[1]) ...
29.785714
51
0.446043
72
417
2.583333
0.347222
0.064516
0.086022
0.129032
0.139785
0
0
0
0
0
0
0.057252
0.371703
417
13
52
32.076923
0.652672
0.088729
0
0
0
0
0
0
0
0
0
0
0
1
0.090909
false
0
0
0
0.272727
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1a9d1bf580afd0ee0a24298894018f257f2969f5
351
py
Python
MyGame/code/constants.py
Chad474/2dPyGame
22d2c19a5407fa4b539b772facfc5c08e6860ddd
[ "MIT" ]
null
null
null
MyGame/code/constants.py
Chad474/2dPyGame
22d2c19a5407fa4b539b772facfc5c08e6860ddd
[ "MIT" ]
null
null
null
MyGame/code/constants.py
Chad474/2dPyGame
22d2c19a5407fa4b539b772facfc5c08e6860ddd
[ "MIT" ]
null
null
null
import pygame TITLE = 'Gravity' BLOCK_SIZE = 32 SCREEN_WIDTH = 1024 # 32 * 32 SCREEN_HEIGHT = 576 # 32* 18 SCREEN = pygame.display.set_mode((SCREEN_WIDTH, SCREEN_HEIGHT)) COLOR_KEY = (200,0,200) MAX_FPS = 60 def split(frame, x, y, w, h): img = pygame.Surface([w, h]) img.blit(frame, (0,0), (x...
18.473684
64
0.612536
57
351
3.631579
0.596491
0.028986
0.028986
0.038647
0
0
0
0
0
0
0
0.105263
0.242165
351
18
65
19.5
0.672932
0.039886
0
0
0
0
0.022222
0
0
0
0
0
0
1
0.083333
false
0
0.083333
0
0.25
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1a9d7cda48b1e296206076d3d46cfc71b4de07c2
1,852
py
Python
ytdlscript.py
antsareflying/ytdlscript
e03e965bfab1b7148982ea9fef04d06b6b5a84c1
[ "MIT" ]
null
null
null
ytdlscript.py
antsareflying/ytdlscript
e03e965bfab1b7148982ea9fef04d06b6b5a84c1
[ "MIT" ]
null
null
null
ytdlscript.py
antsareflying/ytdlscript
e03e965bfab1b7148982ea9fef04d06b6b5a84c1
[ "MIT" ]
null
null
null
""" MIT License Copyright (c) 2021 Moon Seongmu Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, ...
38.583333
418
0.759179
287
1,852
4.885017
0.560976
0.062767
0.023538
0.038516
0.064194
0.064194
0
0
0
0
0
0.003778
0.142549
1,852
47
419
39.404255
0.879093
0.576674
0
0.142857
0
0.071429
0.572351
0.224806
0
0
0
0
0
1
0.071429
false
0
0.214286
0.071429
0.357143
0.142857
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1a9dcbe44706cc17ddb463f1054c5280c08ef119
36,033
py
Python
grid_generator/body_fitted_grid_generator.py
Mayu14/2D_comp_viscos
a62633d8684b218b52e39d47a13717a1edfa4a46
[ "MIT" ]
1
2020-05-08T18:00:28.000Z
2020-05-08T18:00:28.000Z
grid_generator/body_fitted_grid_generator.py
Mayu14/2D_comp_viscos
a62633d8684b218b52e39d47a13717a1edfa4a46
[ "MIT" ]
null
null
null
grid_generator/body_fitted_grid_generator.py
Mayu14/2D_comp_viscos
a62633d8684b218b52e39d47a13717a1edfa4a46
[ "MIT" ]
1
2020-02-20T09:26:27.000Z
2020-02-20T09:26:27.000Z
# coding: utf-8 from math import sqrt from scipy import interpolate from scipy.spatial import Delaunay import numpy as np from numpy.linalg import norm from naca_4digit_test import Naca_4_digit, Naca_5_digit from joukowski_wing import joukowski_wing_complex, karman_trefftz_wing_complex import matplotlib.pyplot as plt i...
38.537968
219
0.532512
5,149
36,033
3.568266
0.096329
0.016981
0.007838
0.014369
0.41893
0.351657
0.288684
0.241496
0.191313
0.169216
0
0.062446
0.322704
36,033
935
220
38.537968
0.690309
0.062193
0
0.25
0
0
0.016842
0.00663
0
0
0
0
0
1
0.073308
false
0
0.016917
0.015038
0.18985
0.007519
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1a9e2fd106422503a1e5fac850661d45c2df7299
4,238
py
Python
cmp/gnfa.py
kikeXD/Grammar-Analyser
ca8f35c0e36e3d8181dab78bb0231e101f953437
[ "MIT" ]
1
2020-02-13T16:52:57.000Z
2020-02-13T16:52:57.000Z
cmp/gnfa.py
kikeXD/Grammar-Analyser
ca8f35c0e36e3d8181dab78bb0231e101f953437
[ "MIT" ]
null
null
null
cmp/gnfa.py
kikeXD/Grammar-Analyser
ca8f35c0e36e3d8181dab78bb0231e101f953437
[ "MIT" ]
1
2020-02-13T16:44:26.000Z
2020-02-13T16:44:26.000Z
from cmp.regex import Regex from cmp.nfa_dfa import NFA import pydot from pprint import pprint class GNFA: def __init__(self, nfa :NFA): self.nfa = nfa self.states = nfa.states + 2 self.start = 0 self.finals = [nfa.states + 1] self.transitions = { state: {} for state in rang...
37.175439
119
0.51345
489
4,238
4.386503
0.186094
0.125874
0.065268
0.068531
0.386946
0.265268
0.217716
0.100699
0.044755
0
0
0.012141
0.35866
4,238
114
120
37.175439
0.777042
0.173903
0
0.135135
0
0
0.020684
0
0
0
0
0
0.013514
1
0.081081
false
0.013514
0.054054
0.013514
0.22973
0.013514
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1a9e301a01427b553ef254d21db7775e0f228100
4,203
py
Python
python/venv/lib/python2.7/site-packages/openstackclient/tests/image/v2/fakes.py
sjsucohort6/openstack
8471e6e599c3f52319926a582358358ef84cbadb
[ "MIT" ]
null
null
null
python/venv/lib/python2.7/site-packages/openstackclient/tests/image/v2/fakes.py
sjsucohort6/openstack
8471e6e599c3f52319926a582358358ef84cbadb
[ "MIT" ]
null
null
null
python/venv/lib/python2.7/site-packages/openstackclient/tests/image/v2/fakes.py
sjsucohort6/openstack
8471e6e599c3f52319926a582358358ef84cbadb
[ "MIT" ]
null
null
null
# Copyright 2013 Nebula Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to...
27.116129
121
0.520343
414
4,203
5.188406
0.415459
0.0554
0.011639
0.013966
0.111266
0.084264
0.048883
0.048883
0.01257
0.01257
0
0.020349
0.34523
4,203
154
122
27.292208
0.760174
0.145848
0
0.232
0
0.008
0.25399
0.034444
0
0
0
0
0
1
0.016
false
0
0.032
0
0.064
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1aa1225f975c24c5462e87cbb4bbe01830ca0112
2,557
py
Python
wwyfcs/utils/create_examples.py
shc558/wwyfcs
05ca6c94f59f7317e4e597d3df18f549dcadf7c1
[ "MIT" ]
1
2021-03-24T18:00:03.000Z
2021-03-24T18:00:03.000Z
wwyfcs/utils/create_examples.py
shc558/wwyfcs
05ca6c94f59f7317e4e597d3df18f549dcadf7c1
[ "MIT" ]
null
null
null
wwyfcs/utils/create_examples.py
shc558/wwyfcs
05ca6c94f59f7317e4e597d3df18f549dcadf7c1
[ "MIT" ]
null
null
null
# -*- coding: utf-8 -*- import argparse import os import pandas as pd from sklearn.model_selection import train_test_split # load data and tag lines with source characters' names def load_data(args): data = pd.read_csv(args.file_path) data['id:data'] = data[args.id_colname]+':'+data[args.data_colname] return dat...
36.014085
96
0.678138
381
2,557
4.393701
0.293963
0.037634
0.071087
0.026284
0.297491
0.215054
0.20908
0.158303
0.133811
0.133811
0
0.006705
0.183418
2,557
70
97
36.528571
0.795019
0.095424
0
0.214286
0
0
0.164716
0
0
0
0
0
0
1
0.053571
false
0
0.071429
0
0.160714
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1aa1a697528836b8f497782c36ef0f059f0914be
2,445
py
Python
dottyDrawings.py
riyap/DottyDrawings
33691c390ef939507e6499c56ab3e0f33485734f
[ "MIT" ]
null
null
null
dottyDrawings.py
riyap/DottyDrawings
33691c390ef939507e6499c56ab3e0f33485734f
[ "MIT" ]
null
null
null
dottyDrawings.py
riyap/DottyDrawings
33691c390ef939507e6499c56ab3e0f33485734f
[ "MIT" ]
null
null
null
from tkinter import * color = 'black' def red(): global color color = 'red' def orange(): global color color = 'orange' def yellow(): global color color = 'yellow' def green(): global color color = 'lime green' def lime_green(): global color color = 'green' def ...
26.010638
77
0.592229
349
2,445
4.13467
0.197708
0.106722
0.144144
0.116424
0.296604
0.296604
0.264033
0.264033
0.264033
0.264033
0
0.018043
0.251943
2,445
93
78
26.290323
0.770913
0.009816
0
0.333333
0
0
0.08122
0
0
0
0
0
0
1
0.178571
false
0
0.011905
0
0.190476
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1aa5ff8d79fad0cf1844b76d7b3b8225587726b3
1,248
py
Python
search/nlp/qu/alpha_numbers.py
octabytes/search
750124d2de0e349249e3183daccc83ba5a82af36
[ "Apache-2.0" ]
null
null
null
search/nlp/qu/alpha_numbers.py
octabytes/search
750124d2de0e349249e3183daccc83ba5a82af36
[ "Apache-2.0" ]
null
null
null
search/nlp/qu/alpha_numbers.py
octabytes/search
750124d2de0e349249e3183daccc83ba5a82af36
[ "Apache-2.0" ]
null
null
null
alpha_numbers = [ { "alpha": "one", "number": 1 }, { "alpha": "two", "number": 2 }, { "alpha": "three", "number": 3 }, { "alpha": "four", "number": 4 }, { "alpha": "five", "number": 5 }, { ...
14.682353
51
0.310096
91
1,248
4.21978
0.417582
0.0625
0.0625
0
0
0
0
0
0
0
0
0.034591
0.490385
1,248
84
52
14.857143
0.569182
0
0
0.240964
0
0
0.255609
0
0
0
0
0
0
1
0
false
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1aa66e4a88e8039f0db550652234c2a41fa7e240
2,510
py
Python
pdfmerge3/pdfmerge3.py
marciojmo/pdfmerge3
f1fa598000dd304fc85bcb60bb72e35e1121feea
[ "MIT" ]
null
null
null
pdfmerge3/pdfmerge3.py
marciojmo/pdfmerge3
f1fa598000dd304fc85bcb60bb72e35e1121feea
[ "MIT" ]
null
null
null
pdfmerge3/pdfmerge3.py
marciojmo/pdfmerge3
f1fa598000dd304fc85bcb60bb72e35e1121feea
[ "MIT" ]
null
null
null
#!/usr/bin/env python """ Merge pdf files into a single file. EXAMPLES pdfmerge3 -o output.pdf Merges all pdf files from the current folder in lexicographic order and put the result in output.pdf pdfmerge3 -o output.pdf file1.pdf file2.pdf file3.pdf Merges file1.pdf, file2.pdf, file3.pdf (in t...
30.987654
111
0.657371
360
2,510
4.466667
0.327778
0.069652
0.11194
0.026119
0.18408
0.18408
0.073383
0.038557
0
0
0
0.006828
0.241434
2,510
80
112
31.375
0.83771
0.347809
0
0.116279
0
0
0.146465
0
0
0
0
0
0
1
0.069767
false
0
0.069767
0
0.232558
0.139535
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1aa707c8a85977c3cb01e58f2e7d0ab3b1f10872
2,685
py
Python
openGaussBase/testcase/KEYWORDS/restrict/Opengauss_Function_Keyword_Restrict_Case0020.py
opengauss-mirror/Yat
aef107a8304b94e5d99b4f1f36eb46755eb8919e
[ "MulanPSL-1.0" ]
null
null
null
openGaussBase/testcase/KEYWORDS/restrict/Opengauss_Function_Keyword_Restrict_Case0020.py
opengauss-mirror/Yat
aef107a8304b94e5d99b4f1f36eb46755eb8919e
[ "MulanPSL-1.0" ]
null
null
null
openGaussBase/testcase/KEYWORDS/restrict/Opengauss_Function_Keyword_Restrict_Case0020.py
opengauss-mirror/Yat
aef107a8304b94e5d99b4f1f36eb46755eb8919e
[ "MulanPSL-1.0" ]
null
null
null
""" Copyright (c) 2022 Huawei Technologies Co.,Ltd. openGauss is licensed under Mulan PSL v2. You can use this software according to the terms and conditions of the Mulan PSL v2. You may obtain a copy of Mulan PSL v2 at: http://license.coscl.org.cn/MulanPSL2 THIS SOFTWARE IS PROVIDED ON AN "AS IS" BASIS, W...
36.283784
124
0.665922
316
2,685
5.509494
0.370253
0.045951
0.082711
0.119472
0.541068
0.541068
0.541068
0.541068
0.479035
0.479035
0
0.009781
0.200372
2,685
74
125
36.283784
0.800652
0.220112
0
0.368421
0
0
0.28071
0.096695
0
0
0
0
0.210526
1
0.157895
false
0
0.105263
0
0.289474
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1aa7f5994534e2c541d01b757ecf3f65fc58d25f
17,858
py
Python
acwingcli/__main__.py
jasonsun0310/acwingcli
ef5de599b8fceeb16563aa4f2ac10db106b374da
[ "MIT" ]
null
null
null
acwingcli/__main__.py
jasonsun0310/acwingcli
ef5de599b8fceeb16563aa4f2ac10db106b374da
[ "MIT" ]
null
null
null
acwingcli/__main__.py
jasonsun0310/acwingcli
ef5de599b8fceeb16563aa4f2ac10db106b374da
[ "MIT" ]
null
null
null
import json import acwingcli.actions as actions import sys import os import acwingcli.commandline_writer as cmdwrite # import acwingcli import argparse import subprocess import acwingcli.update as update import os import websocket import json import threading import psutil import acwingcli.utils as utils import ti...
46.264249
134
0.582708
2,002
17,858
5.039461
0.132368
0.034889
0.033898
0.032709
0.584994
0.541084
0.457924
0.421548
0.398553
0.381207
0
0.004536
0.284018
17,858
385
135
46.384416
0.781636
0.004088
0
0.478632
0
0
0.140198
0.005567
0
0
0
0
0
1
0.037037
false
0.002849
0.099715
0.005698
0.196581
0.014245
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1aa9303e674b4308db627878870a3d77956ca97a
9,760
py
Python
main.py
Readix/TrafficMonitoring
eaaf63b4973d44de37b7593eb4507e65b24b4e95
[ "MIT" ]
null
null
null
main.py
Readix/TrafficMonitoring
eaaf63b4973d44de37b7593eb4507e65b24b4e95
[ "MIT" ]
null
null
null
main.py
Readix/TrafficMonitoring
eaaf63b4973d44de37b7593eb4507e65b24b4e95
[ "MIT" ]
null
null
null
import cv2 import numpy as np import json import os import re import yolo.darknet.darknet as darknet import haversine import imutils as imu from tracker.sort import * #-------------------------------------------- ''' res_path - path to: - calibration.npy - perspective_matrix.npy - mask.png - sides.png...
38.27451
175
0.569365
1,308
9,760
4.087156
0.18578
0.023569
0.01459
0.019641
0.235503
0.150767
0.139169
0.139169
0.095024
0.095024
0
0.054065
0.266598
9,760
254
176
38.425197
0.692791
0.009016
0
0.125
0
0
0.070502
0.00957
0
0
0.000425
0
0
1
0.014423
false
0
0.043269
0
0.067308
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1aad579bb647de889b27f15e5b9e096cbdc98efc
1,400
py
Python
05_topic_modeling/topic_modeling.py
alyonavyshnevska/text_visualization_course
882a49290edf98640d20805ade14d6dfa7903e51
[ "MIT" ]
null
null
null
05_topic_modeling/topic_modeling.py
alyonavyshnevska/text_visualization_course
882a49290edf98640d20805ade14d6dfa7903e51
[ "MIT" ]
1
2019-04-23T01:23:17.000Z
2019-05-01T15:53:20.000Z
05_topic_modeling/topic_modeling.py
alyonavyshnevska/text_visualization_course
882a49290edf98640d20805ade14d6dfa7903e51
[ "MIT" ]
null
null
null
from gensim.models.ldamodel import LdaModel as ldamodel from gensim import corpora import pprint from gensim.test.utils import datapath import pyLDAvis import pyLDAvis.gensim from clean_data import clean as clean def train_model(texts): # turn our tokenized documents into a id <-> term dictionary dictionary =...
30.434783
71
0.730714
184
1,400
5.369565
0.407609
0.080972
0.07085
0.121457
0.135628
0.082996
0
0
0
0
0
0.00613
0.184286
1,400
46
72
30.434783
0.859019
0.182857
0
0
0
0
0.077397
0.041337
0
0
0
0
0
1
0.076923
false
0
0.269231
0
0.384615
0.076923
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1ab294b9434a7343b63cc5b761a5e72a521a3292
3,681
py
Python
pylons/decorators/secure.py
KinSai1975/Menira.py
ca275ce244ee4804444e1827ba60010a55acc07c
[ "BSD-3-Clause" ]
118
2015-01-04T06:55:14.000Z
2022-01-14T08:32:41.000Z
pylons/decorators/secure.py
KinSai1975/Menira.py
ca275ce244ee4804444e1827ba60010a55acc07c
[ "BSD-3-Clause" ]
21
2015-01-03T02:16:28.000Z
2021-03-24T06:10:57.000Z
pylons/decorators/secure.py
KinSai1975/Menira.py
ca275ce244ee4804444e1827ba60010a55acc07c
[ "BSD-3-Clause" ]
53
2015-01-04T03:21:08.000Z
2021-08-04T20:52:01.000Z
"""Security related decorators""" import logging import urlparse from decorator import decorator try: import webhelpers.html.secure_form as secure_form except ImportError: import webhelpers.pylonslib.secure_form as secure_form from pylons.controllers.util import abort, redirect from pylons.decorators.util imp...
32.008696
75
0.653355
460
3,681
5.108696
0.376087
0.038298
0.034043
0.048936
0.182979
0.164255
0.093617
0.05617
0.05617
0.05617
0
0.00401
0.254822
3,681
114
76
32.289474
0.852716
0.38006
0
0.153846
0
0
0.135808
0
0
0
0
0
0
1
0.076923
false
0
0.153846
0
0.307692
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1ab4bfddddae575d022743618b16597b55734005
393
py
Python
ntu_data.py
qiuwch/lt
3a36f325a70a37f8152e8f62387628f6dabcabeb
[ "MIT" ]
null
null
null
ntu_data.py
qiuwch/lt
3a36f325a70a37f8152e8f62387628f6dabcabeb
[ "MIT" ]
null
null
null
ntu_data.py
qiuwch/lt
3a36f325a70a37f8152e8f62387628f6dabcabeb
[ "MIT" ]
null
null
null
import os import glob seq_id = 'S001' # cam_id = 'C001' cam_id = '*' pid = 'P001' rid = 'R001' aid = 'A007' data_root = './data/NTU' seq_path = '{seq_id}{cam_id}{pid}{rid}{aid}_rgb/img_00001.jpg'.format(**locals()) seq_path = os.path.join(data_root, seq_path) print(seq_path) def get_images(path): files = glob...
16.375
81
0.676845
66
393
3.787879
0.469697
0.14
0.064
0
0
0
0
0
0
0
0
0.05988
0.150127
393
24
82
16.375
0.688623
0.038168
0
0
0
0
0.202128
0.130319
0
0
0
0
0
1
0.0625
false
0
0.125
0
0.25
0.125
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1ab581d03430d3b70b00302350af75c95eb520dd
6,876
py
Python
pydax/_schema.py
cclauss/pydax
75c7d7041041043695d693c0f36110a3f4cd1d9c
[ "Apache-2.0" ]
11
2020-11-12T21:51:49.000Z
2021-07-12T15:47:09.000Z
pydax/_schema.py
cclauss/pydax
75c7d7041041043695d693c0f36110a3f4cd1d9c
[ "Apache-2.0" ]
138
2020-11-14T01:35:08.000Z
2021-07-22T05:52:29.000Z
pydax/_schema.py
cclauss/pydax
75c7d7041041043695d693c0f36110a3f4cd1d9c
[ "Apache-2.0" ]
5
2020-12-03T22:04:39.000Z
2021-07-13T17:03:53.000Z
# # Copyright 2020 IBM Corp. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or a...
39.517241
119
0.681792
839
6,876
5.445769
0.281287
0.059532
0.027577
0.015758
0.181659
0.150361
0.150361
0.122784
0.109433
0.109433
0
0.002077
0.22993
6,876
173
120
39.745665
0.860623
0.547993
0
0.037736
0
0
0.073602
0
0
0
0
0
0
1
0.150943
false
0.037736
0.132075
0
0.471698
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1ab79890c8715d44cb5a582ad20c54a470f52918
1,259
py
Python
turngeneration/forms.py
jbradberry/django-turn-generation
dbfec9d0addbff2d8d54597b7520e171938c9107
[ "MIT" ]
null
null
null
turngeneration/forms.py
jbradberry/django-turn-generation
dbfec9d0addbff2d8d54597b7520e171938c9107
[ "MIT" ]
null
null
null
turngeneration/forms.py
jbradberry/django-turn-generation
dbfec9d0addbff2d8d54597b7520e171938c9107
[ "MIT" ]
1
2019-12-12T19:36:15.000Z
2019-12-12T19:36:15.000Z
from django.contrib.contenttypes.models import ContentType from django import forms from . import models class PauseForm(forms.ModelForm): class Meta: model = models.Pause fields = ('reason',) def clean(self): cleaned_data = super(PauseForm, self).clean() if not self.instanc...
29.27907
80
0.652105
141
1,259
5.730496
0.368794
0.10396
0.084158
0.056931
0.55198
0.55198
0.398515
0.398515
0.398515
0.398515
0
0
0.253376
1,259
42
81
29.97619
0.859574
0
0
0.451613
0
0
0.067514
0
0
0
0
0
0
1
0.064516
false
0
0.096774
0
0.354839
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1ab98a6d7dd06d056ddf62a198dd9ded5f6d2846
2,047
py
Python
bot.py
technicalwritingEditor/Discord2FB-Bot
e5e10329ea2056adf451f352c4d582dc281281d1
[ "MIT" ]
3
2018-06-03T00:58:27.000Z
2021-10-06T09:41:11.000Z
bot.py
technicalwritingEditor/Discord2FB-Bot
e5e10329ea2056adf451f352c4d582dc281281d1
[ "MIT" ]
null
null
null
bot.py
technicalwritingEditor/Discord2FB-Bot
e5e10329ea2056adf451f352c4d582dc281281d1
[ "MIT" ]
1
2018-07-13T19:45:33.000Z
2018-07-13T19:45:33.000Z
import discord from discord.ext import commands import facebook from discord.ext.commands import Bot Client = discord.Client() bot = commands.Bot(command_prefix = "/") #Tells what the prefix before every command should be. @bot.event async def on_ready(): ''' Function to just tell us that the bot is not active. Ev...
37.218182
170
0.72936
318
2,047
4.613208
0.408805
0.034083
0.035446
0.046353
0.159509
0.130879
0.130879
0.130879
0.130879
0.130879
0
0.004598
0.149976
2,047
54
171
37.907407
0.838506
0.089888
0
0.206897
0
0
0.332406
0
0
0
0
0
0
1
0
false
0.034483
0.137931
0
0.137931
0.034483
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1ab9ac6dd4bb10c4ea54f939af124df3ccd014f8
561
py
Python
tool/click_demo.py
KEVINYZY/python-tutorial
ae43536908eb8af56c34865f52a6e8644edc4fa3
[ "Apache-2.0" ]
2
2021-01-04T10:44:44.000Z
2022-02-13T07:53:41.000Z
tool/click_demo.py
zm79287/python-tutorial
d0f7348e1da4ff954e3add66e1aae55d599283ee
[ "Apache-2.0" ]
null
null
null
tool/click_demo.py
zm79287/python-tutorial
d0f7348e1da4ff954e3add66e1aae55d599283ee
[ "Apache-2.0" ]
2
2019-02-28T07:53:30.000Z
2021-07-28T07:11:20.000Z
# -*- coding: utf-8 -*- # Author: XuMing <xuming624@qq.com> # Brief: import click @click.command() @click.option('--count', default=1, help="num") @click.option('--rate', type=float, help='rate') @click.option('--gender', type=click.Choice(['man', 'woman']), default='man', help='select sex') @click.option('--center'...
25.5
96
0.632799
74
561
4.689189
0.527027
0.126801
0
0
0
0
0
0
0
0
0
0.012371
0.135472
561
21
97
26.714286
0.703093
0.110517
0
0
0
0
0.222222
0
0
0
0
0
0
1
0.076923
false
0
0.076923
0
0.153846
0.307692
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1abbc4f259e0af349f90eba1f861bc51de4ccaec
2,780
py
Python
vertigo/datasets/fetchers.py
rmarkello/vertigo
35c79faf3a62b9b3941f0c989640c2f5de8f819e
[ "Apache-2.0" ]
null
null
null
vertigo/datasets/fetchers.py
rmarkello/vertigo
35c79faf3a62b9b3941f0c989640c2f5de8f819e
[ "Apache-2.0" ]
null
null
null
vertigo/datasets/fetchers.py
rmarkello/vertigo
35c79faf3a62b9b3941f0c989640c2f5de8f819e
[ "Apache-2.0" ]
null
null
null
# -*- coding: utf-8 -*- """ Functions for fetching datasets from the internet """ from collections import namedtuple import os.path as op from .osf import _get_data_dir, _get_dataset_info from .utils import _fetch_files ANNOT = namedtuple('Surface', ('lh', 'rh')) def fetch_fsaverage(version='fsaverage', data_dir=N...
31.235955
79
0.611871
337
2,780
4.940653
0.439169
0.042042
0.012012
0.046847
0.058859
0
0
0
0
0
0
0.009369
0.270504
2,780
88
80
31.590909
0.811637
0.375899
0
0
0
0
0.147826
0
0
0
0
0
0
1
0.026316
false
0
0.131579
0
0.184211
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1abc0cd17b3be692c4ae6a95012e1e744129a64f
6,798
py
Python
rdkit/ML/ModelPackage/UnitTestPackage.py
kazuyaujihara/rdkit
06027dcd05674787b61f27ba46ec0d42a6037540
[ "BSD-3-Clause" ]
1,609
2015-01-05T02:41:13.000Z
2022-03-30T21:57:24.000Z
rdkit/ML/ModelPackage/UnitTestPackage.py
kazuyaujihara/rdkit
06027dcd05674787b61f27ba46ec0d42a6037540
[ "BSD-3-Clause" ]
3,412
2015-01-06T12:13:33.000Z
2022-03-31T17:25:41.000Z
rdkit/ML/ModelPackage/UnitTestPackage.py
bp-kelley/rdkit
e0de7c9622ce73894b1e7d9568532f6d5638058a
[ "BSD-3-Clause" ]
811
2015-01-11T03:33:48.000Z
2022-03-28T11:57:49.000Z
# # Copyright (C) 2002-2008 greg Landrum and Rational Discovery LLC # """ unit tests for the model and descriptor packager """ import os import random import unittest from xml.dom import minidom from xml.etree import ElementTree as ET from rdkit import Chem from rdkit import RDConfig from rdkit.Chem import Descripto...
38.191011
104
0.597823
811
6,798
4.963009
0.286067
0.017391
0.040248
0.02087
0.354783
0.325217
0.306584
0.24
0.228075
0.175155
0
0.016084
0.268314
6,798
177
105
38.40678
0.793124
0.101059
0
0.328358
0
0.007463
0.119521
0.022164
0
0
0
0
0.186567
1
0.097015
false
0
0.11194
0.007463
0.238806
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1abce33b89f98cb52f1c4e73fa1fee092929d3eb
9,545
py
Python
plugins/logger/standardout/standard_out.py
Ghostkeeper/Luna
0dfc8694538c9d1ad3941602de2d4b6b815db657
[ "CC0-1.0" ]
null
null
null
plugins/logger/standardout/standard_out.py
Ghostkeeper/Luna
0dfc8694538c9d1ad3941602de2d4b6b815db657
[ "CC0-1.0" ]
null
null
null
plugins/logger/standardout/standard_out.py
Ghostkeeper/Luna
0dfc8694538c9d1ad3941602de2d4b6b815db657
[ "CC0-1.0" ]
null
null
null
#!/usr/bin/env python #-*- coding: utf-8 -*- #This software is distributed under the Creative Commons license (CC0) version 1.0. A copy of this license should have been distributed with this software. #The license can also be read online: <https://creativecommons.org/publicdomain/zero/1.0/>. If this online license dif...
42.995495
227
0.753064
1,418
9,545
4.929478
0.188999
0.055794
0.02432
0.018598
0.58598
0.58226
0.550072
0.550072
0.499285
0.492704
0
0.00997
0.148874
9,545
222
228
42.995496
0.850443
0.531378
0
0.3
0
0
0.111032
0
0
0
0
0
0
1
0.063636
false
0
0.027273
0
0.090909
0.172727
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1abe388e69a825f7770361eb67cf1c3461ead767
2,168
py
Python
notes/algo-ds-practice/problems/dp/double_helix.py
Anmol-Singh-Jaggi/interview-notes
65af75e2b5725894fa5e13bb5cd9ecf152a0d652
[ "MIT" ]
6
2020-07-05T05:15:19.000Z
2021-01-24T20:17:14.000Z
notes/algo-ds-practice/problems/dp/double_helix.py
Anmol-Singh-Jaggi/interview-notes
65af75e2b5725894fa5e13bb5cd9ecf152a0d652
[ "MIT" ]
null
null
null
notes/algo-ds-practice/problems/dp/double_helix.py
Anmol-Singh-Jaggi/interview-notes
65af75e2b5725894fa5e13bb5cd9ecf152a0d652
[ "MIT" ]
2
2020-09-14T06:46:37.000Z
2021-06-15T09:17:21.000Z
''' Two finite, strictly increasing, integer sequences are given. Any common integer between the two sequences constitute an intersection point. Take for example the following two sequences where intersection points are printed in bold: First= 3 5 7 9 20 25 30 40 55 56 57 60 62 Second= 1 4 7 11 14 25 44 47 5...
31.42029
152
0.627768
377
2,168
3.578249
0.371353
0.017791
0.066716
0.088955
0.171979
0.151223
0.113417
0.044477
0
0
0
0.076308
0.250461
2,168
68
153
31.882353
0.752615
0.506458
0
0
0
0
0.00754
0
0
0
0
0
0
1
0.057143
false
0
0.028571
0
0.171429
0.028571
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1abfc9f54d479adbe3c36baf00a9a7fac7331057
40,724
py
Python
libcst/matchers/_matcher_base.py
dendisuhubdy/LibCST
1acf2c83d132d4f665dd5de3684330463cbd361e
[ "Apache-2.0" ]
null
null
null
libcst/matchers/_matcher_base.py
dendisuhubdy/LibCST
1acf2c83d132d4f665dd5de3684330463cbd361e
[ "Apache-2.0" ]
null
null
null
libcst/matchers/_matcher_base.py
dendisuhubdy/LibCST
1acf2c83d132d4f665dd5de3684330463cbd361e
[ "Apache-2.0" ]
null
null
null
# Copyright (c) Facebook, Inc. and its affiliates. # # This source code is licensed under the MIT license found in the # LICENSE file in the root directory of this source tree. # pyre-strict import collections.abc import re from dataclasses import fields from enum import Enum, auto from typing import ( Callable, ...
38.637571
90
0.651336
5,146
40,724
5.054023
0.108045
0.017225
0.005191
0.005383
0.512227
0.475584
0.415757
0.37946
0.354852
0.336858
0
0.001931
0.262597
40,724
1,053
91
38.674264
0.864136
0.45499
0
0.503145
0
0
0.080959
0.031031
0
0
0
0
0
1
0.138365
false
0.002096
0.016771
0.052411
0.371069
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1ac0100cb9b2c279cea35555f4fa8cbff672edda
4,911
py
Python
visualize/loss_function.py
Drchen-AI/NN_DL_tensorflow2.0
3bf26a0b48e2aa78eecb3910104738612c176678
[ "MIT" ]
null
null
null
visualize/loss_function.py
Drchen-AI/NN_DL_tensorflow2.0
3bf26a0b48e2aa78eecb3910104738612c176678
[ "MIT" ]
null
null
null
visualize/loss_function.py
Drchen-AI/NN_DL_tensorflow2.0
3bf26a0b48e2aa78eecb3910104738612c176678
[ "MIT" ]
null
null
null
# coding:utf8 import torch from torch import nn, optim # nn 神经网络模块 optim优化函数模块 from torch.utils.data import DataLoader from torch.autograd import Variable from torchvision import transforms, datasets from visdom import Visdom # 可视化处理模块 import time import numpy as np # 可视化app viz = Visdom() # 超参数 BATCH_SIZE = 40 LR ...
32.959732
122
0.576461
667
4,911
4.073463
0.296852
0.032389
0.023187
0.023923
0.172617
0.155318
0.142805
0.094222
0.080972
0.038278
0
0.037883
0.268988
4,911
148
123
33.182432
0.718942
0.131134
0
0.12
0
0.03
0.085877
0.048261
0
0
0
0
0
1
0.02
false
0.01
0.08
0
0.12
0.03
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1ac1d6d3fc31da110e9581cf6f625215065fc6d5
3,737
py
Python
Car.py
molenathyhoangxuannguyen/Math_Quiz_1-Car
cbcd31bf12e13fe3a31725a46df9af14214b77c2
[ "MIT" ]
null
null
null
Car.py
molenathyhoangxuannguyen/Math_Quiz_1-Car
cbcd31bf12e13fe3a31725a46df9af14214b77c2
[ "MIT" ]
null
null
null
Car.py
molenathyhoangxuannguyen/Math_Quiz_1-Car
cbcd31bf12e13fe3a31725a46df9af14214b77c2
[ "MIT" ]
null
null
null
#Written by Thy H. Nguyen import turtle from math import pi import random def main(): wns = turtle.Screen() def banh_xe(bichthuy): bichthuy.shape("circle") bichthuy.shapesize(0.1,0.1) bichthuy.speed(10) bichthuy.pensize(6) def ve_hinh_tron(number,cao): fo...
27.07971
107
0.578539
498
3,737
4.214859
0.24498
0.045736
0.068604
0.091472
0.331586
0.264412
0.14626
0.098142
0.041925
0.041925
0
0.106383
0.270538
3,737
137
108
27.277372
0.66361
0.006422
0
0.070796
0
0
0.082435
0
0
0
0
0
0
1
0.070796
false
0
0.026549
0
0.097345
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1ac3f96b97737e3eb3f7b8408474c5d059166aee
442
py
Python
functions/odd_and_even_sum.py
MaggieIllustrations/softuni-github-programming
f5695cb14602f3d2974359f6d8734332acc650d3
[ "MIT" ]
null
null
null
functions/odd_and_even_sum.py
MaggieIllustrations/softuni-github-programming
f5695cb14602f3d2974359f6d8734332acc650d3
[ "MIT" ]
null
null
null
functions/odd_and_even_sum.py
MaggieIllustrations/softuni-github-programming
f5695cb14602f3d2974359f6d8734332acc650d3
[ "MIT" ]
1
2022-01-14T17:12:44.000Z
2022-01-14T17:12:44.000Z
number = input() def get_sums(type_numbers, number): result = 0 if type_numbers == "even": result = sum(list(map(int, filter(lambda x: int(x) % 2 == 0, number)))) elif type_numbers == "odd": result = sum(list(map(int, filter(lambda x: int(x) % 2 == 1, number)))) return result evens_...
24.555556
79
0.615385
68
442
3.852941
0.397059
0.080153
0.099237
0.122137
0.282443
0.282443
0.282443
0.282443
0.282443
0.282443
0
0.014409
0.214932
442
17
80
26
0.740634
0
0
0
0
0
0.131519
0
0
0
0
0
0
1
0.090909
false
0
0
0
0.181818
0.090909
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1ac8d5589ceca70f9e89f1d4ba9ffbf6e4b2d824
1,257
py
Python
yandex_algorithm2/home1c.py
erjan/coding_exercises
53ba035be85f1e7a12b4d4dbf546863324740467
[ "Apache-2.0" ]
null
null
null
yandex_algorithm2/home1c.py
erjan/coding_exercises
53ba035be85f1e7a12b4d4dbf546863324740467
[ "Apache-2.0" ]
null
null
null
yandex_algorithm2/home1c.py
erjan/coding_exercises
53ba035be85f1e7a12b4d4dbf546863324740467
[ "Apache-2.0" ]
null
null
null
''' Как известно, два наиболее распространённых формата записи даты — это европейский (сначала день, потом месяц, потом год) и американски (сначала месяц, потом день, потом год). Системный администратор поменял дату на одном из бэкапов и сейчас хочет вернуть дату обратно. Но он не проверил, в каком формате дата использ...
18.761194
374
0.686555
200
1,257
4.315
0.565
0.024334
0.034762
0.05562
0.095017
0.095017
0.067207
0.067207
0
0
0
0.036765
0.242641
1,257
66
375
19.045455
0.861345
0.679395
0
0.294118
0
0
0.020253
0
0
0
0
0
0
1
0.058824
false
0
0
0
0.352941
0.058824
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1acc2f32cc9a7a1f5f4e8cb7660bd8849614cb8a
3,035
py
Python
app/models/users.py
dwcaraway/govly
c3a134c2d8ae911c0ab05d9b96014a7c18bfac45
[ "MIT" ]
5
2018-03-14T18:55:35.000Z
2021-10-04T00:16:38.000Z
app/models/users.py
dwcaraway/govly
c3a134c2d8ae911c0ab05d9b96014a7c18bfac45
[ "MIT" ]
null
null
null
app/models/users.py
dwcaraway/govly
c3a134c2d8ae911c0ab05d9b96014a7c18bfac45
[ "MIT" ]
null
null
null
# -*- coding: utf-8 -*- """ vitals.models.users ~~~~~~~~~~~~~~~~~~~ :author: Dave Caraway :copyright: © 2014-2015, Fog Mine LLC :license: Proprietary, see LICENSE for more details. """ import base64 import os from flask.ext.security import RoleMixin, UserMixin from ..framework.sql import ( db...
32.634409
110
0.677759
408
3,035
4.911765
0.301471
0.127745
0.149701
0.151697
0.402196
0.337325
0.221058
0.168663
0.132735
0.091816
0
0.02874
0.163097
3,035
92
111
32.98913
0.759843
0.076771
0
0.032787
0
0
0.071506
0
0
0
0
0
0
1
0.032787
false
0.016393
0.065574
0
0.819672
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1acc37fde77112dc03495f8a8ad528c34e34685e
7,273
py
Python
data.py
jgoppert/iekf_analysis
d41ad34b37ef2636e20680accf399ea4a9332811
[ "BSD-3-Clause" ]
5
2018-01-16T06:46:38.000Z
2019-06-19T10:17:12.000Z
data.py
jgoppert/iekf_analysis
d41ad34b37ef2636e20680accf399ea4a9332811
[ "BSD-3-Clause" ]
null
null
null
data.py
jgoppert/iekf_analysis
d41ad34b37ef2636e20680accf399ea4a9332811
[ "BSD-3-Clause" ]
null
null
null
from transforms3d.taitbryan import quat2euler import matplotlib.pyplot as plt import numpy as np from util import X, Xe class Data(object): """ Data object for sim data """ def __init__(self): self.x = [] self.J = [] self.K_mag = [] self.K_gps = [] self.K_accel...
31.621739
78
0.514643
1,076
7,273
3.339219
0.131041
0.038965
0.082661
0.090175
0.641247
0.600612
0.554411
0.509045
0.35931
0.276092
0
0.021381
0.299051
7,273
229
79
31.759825
0.683405
0.011825
0
0.364583
0
0
0.057271
0
0
0
0
0
0
1
0.03125
false
0
0.020833
0.005208
0.0625
0.005208
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1acfcd0292220871f431e4e473efb911e7c66800
1,098
py
Python
conary_test/repositorytest/filecontentstest.py
sassoftware/conary
d418968acd5e11ee17ed6d91ca395ea10a040222
[ "Apache-2.0" ]
43
2015-03-31T01:37:10.000Z
2021-11-14T16:26:48.000Z
conary_test/repositorytest/filecontentstest.py
sassoftware/conary
d418968acd5e11ee17ed6d91ca395ea10a040222
[ "Apache-2.0" ]
9
2015-06-10T16:39:41.000Z
2020-01-27T16:35:01.000Z
conary_test/repositorytest/filecontentstest.py
sassoftware/conary
d418968acd5e11ee17ed6d91ca395ea10a040222
[ "Apache-2.0" ]
9
2015-04-07T08:12:37.000Z
2020-01-26T09:54:18.000Z
# # Copyright (c) SAS Institute Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in w...
28.153846
74
0.640255
146
1,098
4.815068
0.657534
0.085349
0.036984
0.045519
0.056899
0
0
0
0
0
0
0.00489
0.255009
1,098
38
75
28.894737
0.854523
0.504554
0
0.125
0
0
0.032197
0
0
0
0
0
0.125
1
0.0625
false
0
0.125
0
0.25
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1ad07d6aab73d167ba977ffa3a12a00f276ccca7
2,582
py
Python
global_finprint/annotation/urls/assignment.py
GlobalFinPrint/global_finprint
8a91ceaaed42aaa716d8c9f27518ba673ebf351c
[ "Apache-2.0" ]
null
null
null
global_finprint/annotation/urls/assignment.py
GlobalFinPrint/global_finprint
8a91ceaaed42aaa716d8c9f27518ba673ebf351c
[ "Apache-2.0" ]
6
2020-06-05T18:42:32.000Z
2022-01-13T00:48:57.000Z
global_finprint/annotation/urls/assignment.py
GlobalFinPrint/global_finprint
8a91ceaaed42aaa716d8c9f27518ba673ebf351c
[ "Apache-2.0" ]
null
null
null
from django.conf.urls import url, include from django.views.decorators.csrf import csrf_exempt from global_finprint.annotation.views.assignment import VideoAutoAssignView, ManageAssignmentView, ObservationListView, \ AssignmentListView, AssignmentListTbodyView, AssignmentModalBodyView, UnassignModalBodyView, Assig...
52.693878
124
0.755616
282
2,582
6.659574
0.280142
0.038339
0.090522
0.063898
0.056443
0
0
0
0
0
0
0
0.093726
2,582
48
125
53.791667
0.802564
0
0
0
0
0
0.30519
0.20488
0
0
0
0
0
1
0
false
0
0.121212
0
0.121212
0.090909
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1ad0ae27acc8dbfede485ff88f989be820ffa27e
3,512
py
Python
pytext/data/test/data_test.py
NunoEdgarGFlowHub/pytext
2358b2d7c8c4e6800c73f4bd1c9731723e503ed6
[ "BSD-3-Clause" ]
1
2019-02-25T01:50:03.000Z
2019-02-25T01:50:03.000Z
pytext/data/test/data_test.py
NunoEdgarGFlowHub/pytext
2358b2d7c8c4e6800c73f4bd1c9731723e503ed6
[ "BSD-3-Clause" ]
null
null
null
pytext/data/test/data_test.py
NunoEdgarGFlowHub/pytext
2358b2d7c8c4e6800c73f4bd1c9731723e503ed6
[ "BSD-3-Clause" ]
null
null
null
#!/usr/bin/env python3 # Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved import unittest from pytext.common.constants import Stage from pytext.data import Data, RawBatcher, types from pytext.data.sources.data_source import SafeFileWrapper from pytext.data.sources.tsv import TSVDataSource from pyt...
39.909091
85
0.660308
402
3,512
5.634328
0.293532
0.092715
0.030905
0.031788
0.471082
0.418543
0.370861
0.370861
0.339514
0.339514
0
0.011983
0.215831
3,512
87
86
40.367816
0.810458
0.067198
0
0.304348
0
0
0.060226
0.017426
0
0
0
0
0.26087
1
0.086957
false
0
0.115942
0
0.231884
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1ad0bb118d7657c0226c9703cf3e0988adf2f733
1,765
py
Python
main.py
GrDaniel/duplicates_finder
edb5bb601494f50425850ce5bcfb4e37955541ba
[ "MIT" ]
null
null
null
main.py
GrDaniel/duplicates_finder
edb5bb601494f50425850ce5bcfb4e37955541ba
[ "MIT" ]
null
null
null
main.py
GrDaniel/duplicates_finder
edb5bb601494f50425850ce5bcfb4e37955541ba
[ "MIT" ]
null
null
null
import os from itertools import chain from hashlib import sha256 class DuplicatesRemover(object): def __init__(self, search_path: str, file_type: str): self.path = search_path self.f_type = file_type def find_duplicates(self): file_paths = self.collect_file_paths() files_size...
33.942308
104
0.648159
238
1,765
4.457983
0.281513
0.076343
0.067861
0.082941
0.131951
0
0
0
0
0
0
0.012298
0.26289
1,765
51
105
34.607843
0.803228
0.095184
0
0.108108
0
0
0.015424
0.014139
0
0
0
0
0
1
0.162162
false
0
0.081081
0.027027
0.378378
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
46b8e3c90bcd926a8f712d20d77daa3692772f66
6,095
py
Python
test/unit/test_network_util.py
shannonxtreme/DeepReg
373f6c28fed1d7376d5c39340b08a3814804efb2
[ "Apache-2.0" ]
null
null
null
test/unit/test_network_util.py
shannonxtreme/DeepReg
373f6c28fed1d7376d5c39340b08a3814804efb2
[ "Apache-2.0" ]
null
null
null
test/unit/test_network_util.py
shannonxtreme/DeepReg
373f6c28fed1d7376d5c39340b08a3814804efb2
[ "Apache-2.0" ]
null
null
null
# coding=utf-8 """ Tests for deepreg/model/network/util """ import pytest import tensorflow as tf import deepreg.model.network.util as util from deepreg.model.backbone import global_net, local_net, u_net def test_wrong_inputs(): """ Function to test wrong input types passed to build backbone func """ ...
29.587379
88
0.597539
790
6,095
4.403797
0.165823
0.03593
0.016384
0.037942
0.735556
0.688991
0.643001
0.619143
0.582351
0.546996
0
0.022001
0.29155
6,095
205
89
29.731707
0.783696
0.210664
0
0.50365
0
0
0.092908
0.005605
0
0
0
0
0.072993
1
0.058394
false
0
0.029197
0
0.087591
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
46ba3880bb819e029eff762b12b3a9362a955d15
4,841
py
Python
code/tmp_rtrip/test/test_importlib/test_locks.py
emilyemorehouse/ast-and-me
3f58117512e125e1ecbe3c72f2f0d26adb80b7b3
[ "MIT" ]
24
2018-01-23T05:28:40.000Z
2021-04-13T20:52:59.000Z
code/tmp_rtrip/test/test_importlib/test_locks.py
emilyemorehouse/ast-and-me
3f58117512e125e1ecbe3c72f2f0d26adb80b7b3
[ "MIT" ]
17
2017-12-21T18:32:31.000Z
2018-12-18T17:09:50.000Z
code/tmp_rtrip/test/test_importlib/test_locks.py
emilyemorehouse/ast-and-me
3f58117512e125e1ecbe3c72f2f0d26adb80b7b3
[ "MIT" ]
null
null
null
from . import util as test_util init = test_util.import_importlib('importlib') import sys import unittest import weakref from test import support try: import threading except ImportError: threading = None else: from test import lock_tests if threading is not None: class ModuleLockAsRLockTests: ...
30.639241
79
0.622185
492
4,841
5.890244
0.256098
0.019324
0.032781
0.041408
0.221532
0.133195
0.115942
0.063492
0
0
0
0.002947
0.299112
4,841
157
80
30.834395
0.851164
0.01384
0
0.16
0
0
0.006524
0
0
0
0
0
0.08
1
0.088
false
0.032
0.072
0.008
0.32
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
46bc10fa6ebc50719d08ff180aa6f6a2e590a585
9,053
py
Python
archived_code/sed_test_AI_64_8.py
jacob975/deep_learning
52a5073589cf78aeadfde8ea51f687bc497a059b
[ "MIT" ]
null
null
null
archived_code/sed_test_AI_64_8.py
jacob975/deep_learning
52a5073589cf78aeadfde8ea51f687bc497a059b
[ "MIT" ]
10
2018-03-14T08:44:12.000Z
2018-11-13T13:45:53.000Z
archived_code/sed_test_AI_64_8.py
jacob975/deep_learning
52a5073589cf78aeadfde8ea51f687bc497a059b
[ "MIT" ]
null
null
null
#!/usr/bin/python3 ''' Abstract: This is a code for test AI with given sed data. Usage: sed_test_AI_64_8.py [source] [id] [directory] [AI] Editor and Practicer: Jacob975 ################################## # Python3 # # This code is made in python3 # ################################...
37.102459
150
0.642218
1,259
9,053
4.444797
0.24305
0.020014
0.025733
0.028592
0.201573
0.145818
0.061115
0.028234
0.023946
0.013581
0
0.022062
0.218933
9,053
243
151
37.255144
0.76934
0.372363
0
0.05
0
0
0.071505
0
0
0
0
0
0
1
0.05
false
0
0.091667
0.008333
0.175
0.158333
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
46bc78afaeb62cb0bbad5b4d159a408a129ad787
677
py
Python
compare_lists/compare.py
Esukhia/text_utils
562065d4dedba127f8aaeee03ca3d9f071805f62
[ "MIT" ]
1
2017-01-26T22:37:57.000Z
2017-01-26T22:37:57.000Z
compare_lists/compare.py
Esukhia/tibtext_utils
562065d4dedba127f8aaeee03ca3d9f071805f62
[ "MIT" ]
null
null
null
compare_lists/compare.py
Esukhia/tibtext_utils
562065d4dedba127f8aaeee03ca3d9f071805f62
[ "MIT" ]
null
null
null
from PyTib.common import open_file, write_file import os monlam = open_file('input/monlam1_total_corrected.txt').split('\n') monlam_entries = [a.split(' | ')[0] for a in monlam] monlam_entries = [a.rstrip('་') for a in monlam_entries] monlam_dict = {a: True for a in monlam_entries} non_monlam = {} in_path = 'input/us...
35.631579
81
0.675037
110
677
3.963636
0.381818
0.119266
0.055046
0.082569
0.137615
0.06422
0
0
0
0
0
0.003521
0.161004
677
18
82
37.611111
0.760563
0
0
0
0
0
0.131462
0.079764
0
0
0
0
0
1
0
false
0
0.125
0
0.125
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
46bc7d4de06ca22e044fe05c60711faebec83394
801
py
Python
lustre/minification.py
half-cambodian-hacker-man/lustre
93e2196a962cafcfd7fa0be93a6b0d563c46ba75
[ "MIT" ]
3
2020-09-06T02:21:09.000Z
2020-09-30T00:05:54.000Z
lustre/minification.py
videogame-hacker/lustre
93e2196a962cafcfd7fa0be93a6b0d563c46ba75
[ "MIT" ]
null
null
null
lustre/minification.py
videogame-hacker/lustre
93e2196a962cafcfd7fa0be93a6b0d563c46ba75
[ "MIT" ]
null
null
null
import typing from starlette.responses import Response, HTMLResponse from starlette.templating import _TemplateResponse try: import htmlmin except ImportError: htmlmin = None def setup_html_minification( response_classes=[HTMLResponse, _TemplateResponse], **minification_config ): assert htmlmin is n...
28.607143
84
0.750312
90
801
6.466667
0.488889
0.072165
0.051546
0.082474
0
0
0
0
0
0
0
0
0.188514
801
27
85
29.666667
0.895385
0
0
0
0
0
0.062422
0
0
0
0
0
0.052632
1
0.105263
false
0
0.263158
0
0.473684
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
46c8ae10d53e8ce4d08d1a08d67812ca60bf79fe
5,407
py
Python
VirusTotalAVBot/modules/virustotal.py
kenanismayilov335/VirusTotal-File-Scan-Bot
369e8bba10ce40cf9e9bdaeba018496e8509cd8d
[ "MIT" ]
null
null
null
VirusTotalAVBot/modules/virustotal.py
kenanismayilov335/VirusTotal-File-Scan-Bot
369e8bba10ce40cf9e9bdaeba018496e8509cd8d
[ "MIT" ]
null
null
null
VirusTotalAVBot/modules/virustotal.py
kenanismayilov335/VirusTotal-File-Scan-Bot
369e8bba10ce40cf9e9bdaeba018496e8509cd8d
[ "MIT" ]
6
2020-11-01T17:46:27.000Z
2022-03-01T14:34:17.000Z
import hashlib import logging import os import requests import time from VirusTotalAVBot import VT_API logger = logging.getLogger("VirusTotal Methods") api_base_url = "https://www.virustotal.com/api/v3" header = {'x-apikey': VT_API} def vthash(filehash: str): """Returns the analysis data class for a file in Vir...
32.572289
118
0.630294
688
5,407
4.832849
0.258721
0.050526
0.057744
0.07218
0.41594
0.355188
0.348271
0.321805
0.321805
0.295338
0
0.011879
0.2371
5,407
165
119
32.769697
0.792727
0.120769
0
0.330189
0
0.018868
0.281316
0.095329
0
0
0
0
0
1
0.066038
false
0
0.056604
0
0.226415
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
46cd1e657ec4409874672e0022455763ebebbf47
1,868
py
Python
CODES/S18 - Selenium WebDriver -_ Working With Web Elements/10-HiddenElements.py
PacktPublishing/-Selenium-WebDriver-With-Python-3.x---Novice-To-Ninja-v-
7be863a0a9c8da7e31a413742da92c2fcfd0b38a
[ "MIT" ]
11
2019-05-17T00:54:17.000Z
2021-11-12T22:12:18.000Z
CODES/S18 - Selenium WebDriver -_ Working With Web Elements/10-HiddenElements.py
PacktPublishing/-Selenium-WebDriver-With-Python-3.x---Novice-To-Ninja-v-
7be863a0a9c8da7e31a413742da92c2fcfd0b38a
[ "MIT" ]
null
null
null
CODES/S18 - Selenium WebDriver -_ Working With Web Elements/10-HiddenElements.py
PacktPublishing/-Selenium-WebDriver-With-Python-3.x---Novice-To-Ninja-v-
7be863a0a9c8da7e31a413742da92c2fcfd0b38a
[ "MIT" ]
12
2019-06-17T00:56:01.000Z
2021-09-29T11:38:53.000Z
from selenium import webdriver import time class HiddenElements(): def testLetsKodeIt(self): baseUrl = "https://letskodeit.teachable.com/pages/practice" driver = webdriver.Firefox() driver.maximize_window() driver.get(baseUrl) driver.implicitly_wait(2) # Find the ...
33.963636
95
0.654711
223
1,868
5.376682
0.426009
0.041701
0.070892
0.079233
0.477064
0.42452
0.379483
0.359466
0.359466
0.323603
0
0.007092
0.245182
1,868
55
96
33.963636
0.843262
0.189507
0
0.428571
0
0
0.15492
0
0
0
0
0
0
1
0.057143
false
0
0.057143
0
0.142857
0.114286
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
46cd3a5d74191e0c2f0c767df32bfdb8ff7e82a4
1,091
py
Python
WPC_CSV2XLSX.py
ChenKuanSun/WPECCrawler
9b98fe7da96768fe102c1c494281103cf66aa6ff
[ "MIT" ]
null
null
null
WPC_CSV2XLSX.py
ChenKuanSun/WPECCrawler
9b98fe7da96768fe102c1c494281103cf66aa6ff
[ "MIT" ]
null
null
null
WPC_CSV2XLSX.py
ChenKuanSun/WPECCrawler
9b98fe7da96768fe102c1c494281103cf66aa6ff
[ "MIT" ]
null
null
null
#CodeMod from Trinh Nguyen http://www.dangtrinh.com/2013/10/python-convert-csv-to-excel.html import csv import os from openpyxl import Workbook from openpyxl.utils import get_column_letter def csv_to_excel(csv_path, excel_path): csv_file = open(csv_path, encoding = 'utf-8-sig') #ChineseFixUTF8 csv.register_dialect('...
34.09375
92
0.71769
186
1,091
4.037634
0.424731
0.046605
0.039947
0.04261
0.066578
0.066578
0.066578
0
0
0
0
0.018809
0.122823
1,091
31
93
35.193548
0.765935
0.109074
0
0
0
0
0.144479
0
0
0
0
0
0
1
0.034483
false
0
0.137931
0
0.172414
0.103448
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
46d17d184f4c0040c0f1034f4461fae1fd05d6e6
1,103
py
Python
{{cookiecutter.company_name}}-cli/setup.py
farooq-teqniqly/cli-cookiecutter
e9a8262d5f11d6bfc313e906fad4e683950e52c3
[ "MIT" ]
null
null
null
{{cookiecutter.company_name}}-cli/setup.py
farooq-teqniqly/cli-cookiecutter
e9a8262d5f11d6bfc313e906fad4e683950e52c3
[ "MIT" ]
null
null
null
{{cookiecutter.company_name}}-cli/setup.py
farooq-teqniqly/cli-cookiecutter
e9a8262d5f11d6bfc313e906fad4e683950e52c3
[ "MIT" ]
null
null
null
import setuptools import os # Change to the setup.py directory to read files relative to it. cwd = os.getcwd() abspath = os.path.abspath(__file__) dname = os.path.dirname(abspath) os.chdir(dname) with open("README.md", "r") as f: long_description = f.read() setuptools.setup( name="{{cookiecutter.company_name...
31.514286
129
0.700816
135
1,103
5.533333
0.585185
0.080321
0.092369
0.072289
0.074967
0
0
0
0
0
0
0.008529
0.149592
1,103
34
130
32.441176
0.787846
0.088849
0
0
0
0
0.376248
0.209581
0
0
0
0
0
1
0
false
0
0.071429
0
0.071429
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
46d1b76cc358cb882e976013873aa0558d4d7221
2,382
py
Python
tests/__init__.py
deniskorobicyn/kozmic-ci
0af754b81891722824c6bea85154590f15931030
[ "BSD-3-Clause" ]
1
2021-06-05T18:36:13.000Z
2021-06-05T18:36:13.000Z
tests/__init__.py
deniskorobicyn/kozmic-ci
0af754b81891722824c6bea85154590f15931030
[ "BSD-3-Clause" ]
null
null
null
tests/__init__.py
deniskorobicyn/kozmic-ci
0af754b81891722824c6bea85154590f15931030
[ "BSD-3-Clause" ]
null
null
null
import os import collections from flask.ext.sqlalchemy import SQLAlchemy from flask.ext.webtest import TestApp, get_scopefunc from kozmic import create_app, db from . import factories class SQLAlchemyMixin(object): @property def db(self): return self.app.extensions['sqlalchemy'].db def create_d...
29.407407
79
0.617968
278
2,382
5.107914
0.291367
0.042254
0.064085
0.042254
0.06831
0
0
0
0
0
0
0
0.281276
2,382
80
80
29.775
0.829439
0
0
0
0
0
0.032746
0.011335
0
0
0
0
0
1
0.174603
false
0
0.095238
0.031746
0.380952
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
46d2957beb8300483d8b056de5349aadf1799cfd
6,046
py
Python
coding/python/tkinter_canvas_image.py
jujumo/memento
9879c74d7b9c64ba2e2a1d8bae20e2d353ccd7bd
[ "MIT" ]
1
2019-08-05T17:53:33.000Z
2019-08-05T17:53:33.000Z
coding/python/tkinter_canvas_image.py
jujumo/memento
9879c74d7b9c64ba2e2a1d8bae20e2d353ccd7bd
[ "MIT" ]
null
null
null
coding/python/tkinter_canvas_image.py
jujumo/memento
9879c74d7b9c64ba2e2a1d8bae20e2d353ccd7bd
[ "MIT" ]
null
null
null
import argparse import logging import sys import numpy as np from PIL import Image, ImageTk import tkinter as tk logger = logging.getLogger('tkcanvasimage') logger.addHandler(logging.StreamHandler(sys.stdout)) class TkDrawable: def __init__(self, scaling_factor=1.0, position=[0, 0]): self._canvas = None ...
30.846939
100
0.610155
754
6,046
4.644562
0.192308
0.089092
0.072816
0.034266
0.23301
0.191319
0.159909
0.137065
0.073672
0.044546
0
0.010405
0.284651
6,046
195
101
31.005128
0.799306
0.032087
0
0.287582
0
0
0.0215
0
0
0
0
0
0.006536
1
0.183007
false
0.013072
0.039216
0.03268
0.333333
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
46d4677b37669cdaf6bf286e4bbbce299572bd25
1,485
py
Python
oddsgym/envs/meta.py
OryJonay/soccer_odds_env
b69401518003099ca355c812f2b26775abc25754
[ "Apache-2.0" ]
11
2020-03-10T10:13:53.000Z
2022-02-06T19:06:27.000Z
oddsgym/envs/meta.py
OryJonay/soccer_odds_env
b69401518003099ca355c812f2b26775abc25754
[ "Apache-2.0" ]
1
2020-04-11T14:14:17.000Z
2020-04-11T14:14:17.000Z
oddsgym/envs/meta.py
OryJonay/soccer_odds_env
b69401518003099ca355c812f2b26775abc25754
[ "Apache-2.0" ]
1
2020-10-05T01:20:28.000Z
2020-10-05T01:20:28.000Z
from .base import BaseOddsEnv from .base_percentage import BasePercentageOddsEnv from .daily_bets import DailyOddsEnv, DailyPercentageOddsEnv class MetaEnvBuilder(type): def __new__(cls, name, bases, attr): def safe_get(attribute): if attribute in attr: return attr[attribute] ...
43.676471
110
0.617508
166
1,485
5.253012
0.337349
0.06422
0.037844
0.036697
0.050459
0
0
0
0
0
0
0
0.280808
1,485
33
111
45
0.816479
0
0
0
0
0
0.214141
0.018855
0
0
0
0
0
1
0.066667
false
0
0.1
0
0.3
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
46dce8abd822089ad9a46a0110574671f9f528d4
1,133
py
Python
auto/appium/demo.py
wuhongnpm/Gardenia
a07b34ddfff8c058b5bfc9ee5832e59c86e7e276
[ "MIT" ]
1
2019-05-01T08:03:06.000Z
2019-05-01T08:03:06.000Z
basic/auto/appium/demo.py
wuhongnpm/Python
1b0d576c8c04db6214b627bbe5530643b1f85da0
[ "MIT" ]
null
null
null
basic/auto/appium/demo.py
wuhongnpm/Python
1b0d576c8c04db6214b627bbe5530643b1f85da0
[ "MIT" ]
null
null
null
# This sample code uses the Appium python client # pip install Appium-Python-Client # Then you can paste this into a file and simply run with Python #adb shell dumpsys window | findstr mCurrentFocus #adb shell getprop ro.product.model from appium import webdriver caps = {} caps["platformName"] = "Android" caps["devi...
31.472222
119
0.761695
156
1,133
5.410256
0.615385
0.047393
0.080569
0.090047
0.127962
0.127962
0.127962
0.127962
0.127962
0.127962
0
0.016362
0.082966
1,133
36
120
31.472222
0.795958
0.203001
0
0
0
0
0.427136
0.258794
0
0
0
0
0
1
0
false
0
0.052632
0
0.052632
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
46e01dbf680d02bed46b7756ac1cd294cfc51cef
2,589
py
Python
weallcode/forms.py
rgroves/weallcode-website
ead60d3272dbbfe610b2d500978d1de44aef6386
[ "MIT" ]
15
2019-05-04T00:24:00.000Z
2021-08-21T16:34:05.000Z
weallcode/forms.py
rgroves/weallcode-website
ead60d3272dbbfe610b2d500978d1de44aef6386
[ "MIT" ]
73
2019-04-24T15:53:42.000Z
2021-08-06T20:41:41.000Z
weallcode/forms.py
rgroves/weallcode-website
ead60d3272dbbfe610b2d500978d1de44aef6386
[ "MIT" ]
20
2019-04-26T20:13:08.000Z
2021-06-21T14:53:21.000Z
from django import forms from django.conf import settings from captcha.fields import ReCaptchaField from captcha.widgets import ReCaptchaV3 from coderdojochi.util import email class ContactForm(forms.Form): widths = ( ("name", "small-6"), ("email", "small-6"), ("interest", "small-6"), ...
25.89
98
0.499034
241
2,589
5.273859
0.410788
0.018883
0.026751
0.036192
0.045633
0
0
0
0
0
0
0.022754
0.354963
2,589
99
99
26.151515
0.738323
0.018926
0
0.096386
0
0
0.22498
0.045311
0
0
0
0
0
1
0.036145
false
0
0.060241
0.012048
0.228916
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
46e0903e5bdf7bf970df5689667d22a05b2773ae
4,411
py
Python
examples/ex4_mathsop/myhdl/construct.py
cfelton/alt.hdl
80cdefd20d4fd46e3a1b6116d4b2090135fe1cdf
[ "MIT" ]
19
2015-01-01T18:37:28.000Z
2021-11-26T14:33:37.000Z
examples/ex4_mathsop/myhdl/construct.py
cfelton/alt.hdl
80cdefd20d4fd46e3a1b6116d4b2090135fe1cdf
[ "MIT" ]
null
null
null
examples/ex4_mathsop/myhdl/construct.py
cfelton/alt.hdl
80cdefd20d4fd46e3a1b6116d4b2090135fe1cdf
[ "MIT" ]
1
2017-07-04T13:15:17.000Z
2017-07-04T13:15:17.000Z
from myhdl import * ggens = [] gclock = None #Signal(bool(0)) greset = None #ResetSignal(0, active=0, async=True) def init(clock=None, reset=None): global ggens,gclock,greset gclock,greset = clock,reset ggens = [] return ggens def end(g=None, dump=False): global ggens if dump: for ...
28.642857
69
0.535706
614
4,411
3.679153
0.188925
0.058433
0.027888
0.034529
0.490483
0.476317
0.462151
0.425852
0.425852
0.390438
0
0.004926
0.30968
4,411
153
70
28.830065
0.736946
0.169803
0
0.542857
0
0
0.004129
0
0
0
0
0.006536
0.066667
1
0.171429
false
0
0.009524
0.019048
0.314286
0.009524
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
46e21454a078b2e8ade7f2191dc1b15307690c29
5,458
py
Python
torchvision/datasets/cifar.py
felixgwu/vision
d5eab760e60bc662961faa08a3a17deaa65d2c75
[ "BSD-3-Clause" ]
4
2018-07-22T19:20:49.000Z
2019-04-30T01:28:58.000Z
torchvision/datasets/cifar.py
felixgwu/vision
d5eab760e60bc662961faa08a3a17deaa65d2c75
[ "BSD-3-Clause" ]
null
null
null
torchvision/datasets/cifar.py
felixgwu/vision
d5eab760e60bc662961faa08a3a17deaa65d2c75
[ "BSD-3-Clause" ]
2
2019-04-30T01:29:02.000Z
2019-05-01T07:36:23.000Z
from __future__ import print_function import torch.utils.data as data from PIL import Image import os import os.path import errno import numpy as np import sys if sys.version_info[0] == 2: import cPickle as pickle else: import pickle class CIFAR10(data.Dataset): base_folder = 'cifar-10-batches-py' url...
32.105882
96
0.563576
617
5,458
4.858995
0.277147
0.051034
0.030354
0.018679
0.288526
0.217145
0.172782
0.100734
0.080053
0.080053
0
0.075662
0.329241
5,458
169
97
32.295858
0.74324
0.030597
0
0.271429
0
0.014286
0.158592
0.069076
0
0
0
0
0
1
0.035714
false
0.007143
0.1
0
0.285714
0.042857
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
46e27dfea306c481f9189b43bf419b95084d4d77
1,780
py
Python
project/modules/modules_helpers.py
MattiaPeiretti/MCDAS
11a12df305949d49201af26c0d71d48be6fcb545
[ "CC0-1.0" ]
null
null
null
project/modules/modules_helpers.py
MattiaPeiretti/MCDAS
11a12df305949d49201af26c0d71d48be6fcb545
[ "CC0-1.0" ]
null
null
null
project/modules/modules_helpers.py
MattiaPeiretti/MCDAS
11a12df305949d49201af26c0d71d48be6fcb545
[ "CC0-1.0" ]
null
null
null
import os import multiprocessing from tqdm import tqdm # Custom Modules import constants import formulas from dataHandler import dataHandler from settingsHandler import SettingsHandler from mcd_interface import MCDInterface settings_handler = SettingsHandler() mcd_interface = MCDInterface(settings_handler.get_setting...
29.180328
87
0.664045
230
1,780
4.934783
0.426087
0.026432
0.039648
0.03348
0
0
0
0
0
0
0
0.015556
0.241573
1,780
60
88
29.666667
0.825185
0.053933
0
0.043478
0
0
0.023795
0
0
0
0
0
0
1
0.108696
false
0
0.173913
0
0.413043
0.043478
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
46e3fc7bf3794e3fe125f3281b40c8afefb840e4
8,160
py
Python
backend/data/connection.py
jiangyy12/application-tracking-system
6de2d98351df65d43c09a5739c3c3dbdf3bf78d3
[ "MIT" ]
1
2021-10-17T16:00:20.000Z
2021-10-17T16:00:20.000Z
backend/data/connection.py
jiangyy12/application-tracking-system
6de2d98351df65d43c09a5739c3c3dbdf3bf78d3
[ "MIT" ]
14
2021-11-01T17:34:51.000Z
2021-11-16T02:48:03.000Z
backend/data/connection.py
jiangyy12/application-tracking-system
6de2d98351df65d43c09a5739c3c3dbdf3bf78d3
[ "MIT" ]
3
2021-11-01T18:00:49.000Z
2021-11-16T19:57:26.000Z
import mysql.connector as conn from mysql.connector import errorcode Connection = conn.connect( host="localhost", port="3306", user="root", password="", database="applicationtrackingsystem" ) print("Connect to the local database outside method success...
32.771084
136
0.552451
829
8,160
5.425814
0.170084
0.006225
0.054913
0.06225
0.576701
0.531125
0.531125
0.507337
0.477101
0.453535
0
0.007657
0.327819
8,160
248
137
32.903226
0.812397
0.126471
0
0.546012
0
0
0.303043
0.03029
0
0
0
0.004032
0
1
0.04908
false
0.018405
0.01227
0
0.104294
0.104294
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
46e55a727f3051ddea52da6c465bbf43323192b6
5,898
py
Python
build/PureCloudPlatformClientV2/models/biography.py
cjohnson-ctl/platform-client-sdk-python
38ce53bb8012b66e8a43cc8bd6ff00cf6cc99100
[ "MIT" ]
10
2019-02-22T00:27:08.000Z
2021-09-12T23:23:44.000Z
libs/PureCloudPlatformClientV2/models/biography.py
rocketbot-cl/genesysCloud
dd9d9b5ebb90a82bab98c0d88b9585c22c91f333
[ "MIT" ]
5
2018-06-07T08:32:00.000Z
2021-07-28T17:37:26.000Z
libs/PureCloudPlatformClientV2/models/biography.py
rocketbot-cl/genesysCloud
dd9d9b5ebb90a82bab98c0d88b9585c22c91f333
[ "MIT" ]
6
2020-04-09T17:43:07.000Z
2022-02-17T08:48:05.000Z
# coding: utf-8 """ Copyright 2016 SmartBear Software Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at http://www.apache.org/licenses/LICENSE-2.0 Unless required by applica...
25.097872
77
0.553238
630
5,898
5.085714
0.252381
0.037453
0.093633
0.031211
0.287453
0.185393
0.169164
0.129838
0.021223
0
0
0.003176
0.359444
5,898
234
78
25.205128
0.844891
0.401831
0
0.081395
0
0
0.062392
0
0
0
0
0
0
1
0.197674
false
0
0.05814
0
0.395349
0.011628
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
46e87d0d702a6085e4175544be3a7b236bbac27f
3,329
py
Python
services/dsrp-api/app/api/application/namespace.py
bcgov/dormant-site-reclamation-program
4710434174a204a292a3128d92c8daf1de2a65a6
[ "Apache-2.0" ]
null
null
null
services/dsrp-api/app/api/application/namespace.py
bcgov/dormant-site-reclamation-program
4710434174a204a292a3128d92c8daf1de2a65a6
[ "Apache-2.0" ]
9
2020-05-06T23:29:43.000Z
2022-03-14T22:58:17.000Z
services/dsrp-api/app/api/application/namespace.py
bcgov/dormant-site-reclamation-program
4710434174a204a292a3128d92c8daf1de2a65a6
[ "Apache-2.0" ]
3
2020-05-08T16:54:22.000Z
2021-01-27T17:28:49.000Z
from flask_restplus import Namespace from app.api.application.resources.application import ApplicationResource, ApplicationListResource, ApplicationReviewResource from app.api.application.resources.application_estimated_cost_override import ApplicationEstimatedCostOverride from app.api.application.resources.applicatio...
67.938776
235
0.828477
300
3,329
8.996667
0.186667
0.040015
0.093368
0.062245
0.302334
0.246758
0.105224
0.105224
0.105224
0.045202
0
0
0.079303
3,329
48
236
69.354167
0.880587
0.009913
0
0
0
0
0.285237
0.275516
0
0
0
0
0
1
0
false
0
0.25
0
0.25
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
46eb67734142a3e1e31aedcc8ef44301ec624a41
743
py
Python
saliency.py
Desaiakshata/Saliecy-detection-using-opencv
8ebc9e461093bf66652ac55b36f737e9a93df787
[ "MIT" ]
null
null
null
saliency.py
Desaiakshata/Saliecy-detection-using-opencv
8ebc9e461093bf66652ac55b36f737e9a93df787
[ "MIT" ]
null
null
null
saliency.py
Desaiakshata/Saliecy-detection-using-opencv
8ebc9e461093bf66652ac55b36f737e9a93df787
[ "MIT" ]
null
null
null
import cv2 import argparse a=argparse.ArgumentParser() a.add_argument("-i","--image", required=True, help="input image path") args=vars(a.parse_args()) image=cv2.imread(args["image"]) # two methods # Static spectral saliency saliency = cv2.saliency.StaticSaliencySpectralResidual_create() (success, salien...
29.72
71
0.755047
87
743
6.37931
0.494253
0.032432
0.068468
0.097297
0.187387
0.187387
0
0
0
0
0
0.031627
0.106326
743
24
72
30.958333
0.804217
0.078062
0
0.125
0
0
0.077626
0
0
0
0
0
0
1
0
false
0
0.125
0
0.125
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
46ee6358447c89093b274edefbf4cb4da8117ae6
9,517
py
Python
website/CubeToaster.py
yuxuibbs/MCC-Competition-Docs
384726c41434c5a07becb6438c3d2409c6ca6eb4
[ "MIT" ]
4
2016-11-13T20:49:33.000Z
2017-12-20T20:03:03.000Z
website/CubeToaster.py
yuxuibbs/MCC-Competition-Docs
384726c41434c5a07becb6438c3d2409c6ca6eb4
[ "MIT" ]
5
2016-12-26T19:14:46.000Z
2022-02-11T03:44:39.000Z
website/CubeToaster.py
yuxuibbs/MCC-Competition-Docs
384726c41434c5a07becb6438c3d2409c6ca6eb4
[ "MIT" ]
2
2016-12-29T12:03:15.000Z
2017-02-16T15:51:02.000Z
from flask import Flask, request, render_template, redirect, url_for, flash, make_response from flask_wtf import FlaskForm from wtforms import StringField, IntegerField, SubmitField, SelectField, widgets from wtforms.validators import Required import os import csv import json import requests # import jellyfish #####...
32.261017
203
0.505201
947
9,517
5.043295
0.265048
0.061977
0.062814
0.057789
0.321608
0.266332
0.23995
0.23995
0.232831
0.232831
0
0.030683
0.304823
9,517
294
204
32.370748
0.691203
0.04886
0
0.282158
0
0
0.548914
0.029199
0
0
0
0
0
1
0.020747
false
0
0.033195
0.004149
0.136929
0.012448
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
46ef02cf00dc2eef4d91549f2257af29dc55234b
747
py
Python
ex036.py
erikamaylim/Python-CursoemVideo
5a6809818c4c55a02ec52379d95f3d20c833df2e
[ "MIT" ]
null
null
null
ex036.py
erikamaylim/Python-CursoemVideo
5a6809818c4c55a02ec52379d95f3d20c833df2e
[ "MIT" ]
null
null
null
ex036.py
erikamaylim/Python-CursoemVideo
5a6809818c4c55a02ec52379d95f3d20c833df2e
[ "MIT" ]
null
null
null
"""Escreva um programa para aprovar o empréstimo bancário para a compra de uma casa. Pergunte o valor da casa, o salário do comprador e em quantos anos ele vai pagar. A prestação mensal não pode exceder 30% do salário ou então o empréstimo será negado.""" casa = float(input('Qual o valor da casa? R$ ')) salario = floa...
43.941176
93
0.702811
125
747
4.2
0.56
0.045714
0.030476
0.045714
0
0
0
0
0
0
0
0.045381
0.174029
747
16
94
46.6875
0.805511
0.333333
0
0
0
0.083333
0.558943
0
0
0
0
0
0
1
0
false
0
0
0
0
0.166667
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
46f1607eb413535d97110e501a2e28d97385688e
1,972
py
Python
src/pyconcepticon/commands/citation.py
concepticon/pyconcepticon
bd336df18545b493f59ed8c22b636ded447dede1
[ "Apache-2.0" ]
5
2019-06-04T02:17:03.000Z
2021-12-28T01:59:16.000Z
src/pyconcepticon/commands/citation.py
concepticon/pyconcepticon
bd336df18545b493f59ed8c22b636ded447dede1
[ "Apache-2.0" ]
36
2019-02-06T11:50:21.000Z
2021-12-28T18:43:11.000Z
src/pyconcepticon/commands/citation.py
concepticon/pyconcepticon
bd336df18545b493f59ed8c22b636ded447dede1
[ "Apache-2.0" ]
5
2019-09-18T13:34:19.000Z
2021-12-28T02:01:44.000Z
""" Print a full bibliographic citation for a Concepticon version """ import html import collections from datetime import date from clldutils.path import git_describe from clldutils.jsonlib import dump from nameparser import HumanName def register(parser): parser.add_argument('--version', default=None) parse...
35.854545
98
0.61359
239
1,972
4.987448
0.443515
0.055369
0.015101
0
0
0
0
0
0
0
0
0.009609
0.208418
1,972
54
99
36.518519
0.754004
0.040061
0
0
0
0.045455
0.233422
0.011141
0
0
0
0
0
1
0.068182
false
0
0.136364
0.022727
0.227273
0.022727
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
46f20ff3199dbbecb63862c20b9f0fbe6430f66b
1,106
py
Python
get_repos.py
Oyekunle-Mark/alpha-tower
46d2e96553909388432ff28f2caf74a359538f5e
[ "MIT" ]
null
null
null
get_repos.py
Oyekunle-Mark/alpha-tower
46d2e96553909388432ff28f2caf74a359538f5e
[ "MIT" ]
1
2021-06-02T00:28:26.000Z
2021-06-02T00:28:26.000Z
get_repos.py
Oyekunle-Mark/alpha-tower
46d2e96553909388432ff28f2caf74a359538f5e
[ "MIT" ]
null
null
null
from requests import get from parameters import build_parameters GITHUB_API_URL = "https://api.github.com/search/repositories" def get_repos_with_most_stars(languages, sort="stars", order="desc", stars=50000): """Fetches the data from the GitHub API Arguments: languages {list} -- the list of languag...
29.891892
100
0.674503
140
1,106
5.221429
0.464286
0.036936
0.032832
0
0
0
0
0
0
0
0
0.015134
0.223327
1,106
36
101
30.722222
0.835856
0.392405
0
0
0
0
0.243156
0.035427
0
0
0
0
0
1
0.083333
false
0
0.166667
0
0.333333
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
46f2dabd5d215702d44606f19c384a3fe040de66
580
py
Python
media.py
Daniatnuom/Programming_Foundations_with_Python
ec5c5af25c74bdb14e2dbce48b6e25b15b016b24
[ "MIT" ]
null
null
null
media.py
Daniatnuom/Programming_Foundations_with_Python
ec5c5af25c74bdb14e2dbce48b6e25b15b016b24
[ "MIT" ]
null
null
null
media.py
Daniatnuom/Programming_Foundations_with_Python
ec5c5af25c74bdb14e2dbce48b6e25b15b016b24
[ "MIT" ]
null
null
null
import webbrowser class Movie(): """ This class provides a way to store movie related information""" VALID_RATINGS = ['G','PG','PG-13','R'] # Make class variables, guideline recommend make constant variables as upper case def __init__(self, movie_title, movie_storyline, poster_image,trailer_youtube): self.tit...
30.526316
83
0.77069
80
580
5.3375
0.5375
0.131148
0.084309
0.098361
0
0
0
0
0
0
0
0.004
0.137931
580
18
84
32.222222
0.85
0.331034
0
0
0
0
0.023747
0
0
0
0
0
0
1
0.2
false
0
0.1
0
0.5
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
46f492ce8bbd51b82ba43d37275a6e3759094db3
5,763
py
Python
src/bat/renamefiles.py
armijnhemel/binaryanalysis
1d186d1f6b711b83a6f8e0ffbcce37284ffa1c16
[ "Apache-2.0" ]
78
2016-09-29T08:26:50.000Z
2022-02-21T23:41:23.000Z
src/bat/renamefiles.py
armijnhemel/binaryanalysis
1d186d1f6b711b83a6f8e0ffbcce37284ffa1c16
[ "Apache-2.0" ]
7
2016-10-14T14:32:00.000Z
2018-03-17T17:28:42.000Z
src/bat/renamefiles.py
armijnhemel/binaryanalysis
1d186d1f6b711b83a6f8e0ffbcce37284ffa1c16
[ "Apache-2.0" ]
50
2016-10-05T06:22:38.000Z
2022-02-03T16:08:48.000Z
#!/usr/bin/python # Binary Analysis Tool # Copyright 2015-2016 Armijn Hemel for Tjaldur Software Governance Solutions # Licensed under Apache 2.0, see LICENSE file for details import shutil import os.path import copy ''' This aggregate scan traverses the unpackreports an tries to rename certain files based on proper...
48.838983
136
0.495402
487
5,763
5.862423
0.338809
0.057793
0.028021
0.021016
0.121191
0.060946
0.032224
0
0
0
0
0.008411
0.422349
5,763
117
137
49.25641
0.849204
0.098907
0
0.1625
0
0
0.065828
0
0
0
0
0
0
1
0.0125
false
0
0.0375
0
0.05
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0