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
1b5f7954aad61486e350eecf97b6bdff9243ba31
3,053
py
Python
src/dcm/agent/plugins/builtin/add_user.py
JPWKU/unix-agent
8f1278fc8c2768a8d4d54af642a881bace43652f
[ "Apache-2.0" ]
null
null
null
src/dcm/agent/plugins/builtin/add_user.py
JPWKU/unix-agent
8f1278fc8c2768a8d4d54af642a881bace43652f
[ "Apache-2.0" ]
22
2015-09-15T20:52:34.000Z
2016-03-11T22:44:24.000Z
src/dcm/agent/plugins/builtin/add_user.py
JPWKU/unix-agent
8f1278fc8c2768a8d4d54af642a881bace43652f
[ "Apache-2.0" ]
3
2015-09-11T20:21:33.000Z
2016-09-30T08:30:19.000Z
# # Copyright (C) 2014 Dell, 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 wri...
38.64557
76
0.613167
393
3,053
4.597964
0.394402
0.0487
0.046486
0.030991
0.199225
0.130603
0.130603
0.064195
0.064195
0.064195
0
0.003704
0.292499
3,053
78
77
39.141026
0.83287
0.180478
0
0.081633
0
0
0.125553
0
0
0
0
0
0
1
0.061224
false
0
0.081633
0.020408
0.22449
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
1b5fd3a5f2909fd769f16c7c3cdc54935db82b2c
1,980
py
Python
src/gui/dev/pkg1/faceDetectionImageTest2.py
chaitanyasanoriya/Unified-Machine-Learning-Tool
d88b60ee11a9a0bd203fa52d344263d64cfeaff4
[ "Apache-2.0" ]
null
null
null
src/gui/dev/pkg1/faceDetectionImageTest2.py
chaitanyasanoriya/Unified-Machine-Learning-Tool
d88b60ee11a9a0bd203fa52d344263d64cfeaff4
[ "Apache-2.0" ]
null
null
null
src/gui/dev/pkg1/faceDetectionImageTest2.py
chaitanyasanoriya/Unified-Machine-Learning-Tool
d88b60ee11a9a0bd203fa52d344263d64cfeaff4
[ "Apache-2.0" ]
null
null
null
import cv2 import os import sys import shutil import subprocess face_cascade = cv2.CascadeClassifier('Face_cascade.xml') original_path = sys.argv #original_path = "D:\College Stuff\Machine Learning\Tests\Minor Project\Test 1 - without ED\data\Anne" #new_path = original_path + "1" #os.rename(original_path,new_path) i=0 ...
34.137931
137
0.621717
312
1,980
3.733974
0.301282
0.06867
0.038627
0.034335
0.260086
0.16309
0.16309
0.16309
0.16309
0.16309
0
0.044371
0.237374
1,980
58
137
34.137931
0.727152
0.263636
0
0.090909
0
0
0.019337
0
0
0
0
0
0
1
0
false
0
0.113636
0
0.113636
0.045455
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
1b6165f24d43dbdd11df9d5296ecf6c542bdc293
3,763
py
Python
hangman.py
Telluu/hangman-game
994e930244c90cf18c0f0eba4afafb0af21081a1
[ "MIT" ]
null
null
null
hangman.py
Telluu/hangman-game
994e930244c90cf18c0f0eba4afafb0af21081a1
[ "MIT" ]
null
null
null
hangman.py
Telluu/hangman-game
994e930244c90cf18c0f0eba4afafb0af21081a1
[ "MIT" ]
null
null
null
#!/usr/bin/env python3 import string import random import os import sys import time import json def main(): lives = 8 guessed = set() # Opening words database try: words = open('words.json') except IOError: print('Can\'t locate words.json in local directory.') time.sleep...
30.346774
78
0.495615
414
3,763
4.434783
0.342995
0.038126
0.017974
0.018519
0.115468
0.115468
0.075163
0.075163
0.075163
0.075163
0
0.007243
0.376296
3,763
123
79
30.593496
0.775032
0.130481
0
0.309524
0
0
0.164005
0.041462
0
0
0
0
0
1
0.02381
false
0
0.071429
0
0.095238
0.238095
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
1b65190211132ca843abf01b535bda46f144ac3f
6,593
py
Python
libraries/mosek/9.3/tools/examples/python/concurrent1.py
TimDSF/SBSOS_ShapeSegmentation
e30495dcf71dc63d1d54f3b73132fcfa75d7647e
[ "MIT" ]
null
null
null
libraries/mosek/9.3/tools/examples/python/concurrent1.py
TimDSF/SBSOS_ShapeSegmentation
e30495dcf71dc63d1d54f3b73132fcfa75d7647e
[ "MIT" ]
null
null
null
libraries/mosek/9.3/tools/examples/python/concurrent1.py
TimDSF/SBSOS_ShapeSegmentation
e30495dcf71dc63d1d54f3b73132fcfa75d7647e
[ "MIT" ]
null
null
null
# # Copyright: Copyright (c) MOSEK ApS, Denmark. All rights reserved. # # File: concurrent1.py # # Purpose: Demonstrates a simple implementation of a concurrent optimizer. # # The concurrent optimizer starts a few parallel optimizations # of the same problem using different algori...
32.160976
94
0.66965
924
6,593
4.754329
0.288961
0.012292
0.014569
0.015024
0.297291
0.252675
0.208514
0.190303
0.140223
0.112907
0
0.011422
0.229789
6,593
205
95
32.160976
0.853683
0.440012
0
0.193878
0
0
0.04124
0
0
0
0
0
0
1
0.071429
false
0
0.020408
0.010204
0.153061
0.040816
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
1b6c2f674f5f13eb386f7e948241adeb8392fa33
1,235
py
Python
setup.py
jeffmahler/visualization
9844dd0e58b4635967cad332268bdc9aec93bc25
[ "Apache-2.0" ]
8
2017-12-21T02:25:00.000Z
2020-10-27T19:45:07.000Z
setup.py
jeffmahler/visualization
9844dd0e58b4635967cad332268bdc9aec93bc25
[ "Apache-2.0" ]
11
2017-11-10T03:01:55.000Z
2022-01-10T22:37:25.000Z
setup.py
jeffmahler/visualization
9844dd0e58b4635967cad332268bdc9aec93bc25
[ "Apache-2.0" ]
18
2017-10-04T23:35:12.000Z
2021-08-27T23:34:33.000Z
""" Visualization setup file. """ from setuptools import setup requirements = ["imageio", "numpy", "matplotlib", "trimesh[easy]", "autolab_core", "pyrender"] exec(open("visualization/version.py").read()) setup( name="visualization", version=__version__, description="Visualization toolkit for the Berkele...
34.305556
94
0.666397
120
1,235
6.766667
0.641667
0.116995
0.153941
0.128079
0.128079
0.128079
0.128079
0
0
0
0
0.00999
0.189474
1,235
35
95
35.285714
0.801199
0.020243
0
0
0
0
0.588186
0.075707
0
0
0
0
0
1
0
false
0
0.035714
0
0.035714
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
1b6c315db32834647331ebec872b7a205cd925ba
18,024
py
Python
model_optimizer_pkg/model_optimizer_pkg/model_optimizer_node.py
jsspric/aws-deepracer-model-optimizer-pkg
5593c02dfa311b4178a77eeebf78fb224616fc5e
[ "Apache-2.0" ]
4
2021-04-28T07:53:17.000Z
2021-10-30T02:41:54.000Z
deepracer_follow_the_leader_ws/install/model_optimizer_pkg/lib/python3.8/site-packages/model_optimizer_pkg/model_optimizer_node.py
amitjain-3/working_add
ddd3b10d854477e86bf7a8558b3d447ec03a8a5f
[ "Apache-2.0" ]
null
null
null
deepracer_follow_the_leader_ws/install/model_optimizer_pkg/lib/python3.8/site-packages/model_optimizer_pkg/model_optimizer_node.py
amitjain-3/working_add
ddd3b10d854477e86bf7a8558b3d447ec03a8a5f
[ "Apache-2.0" ]
3
2021-04-30T06:30:28.000Z
2021-10-30T02:41:38.000Z
#!/usr/bin/env python ################################################################################# # Copyright Amazon.com, Inc. or its affiliates. All Rights Reserved. # # # # Licensed under the Apache License, Version 2.0 ...
51.05949
114
0.568409
1,910
18,024
5.186387
0.205236
0.050878
0.031799
0.038159
0.39572
0.351504
0.262366
0.257016
0.240662
0.240662
0
0.002704
0.364015
18,024
352
115
51.204545
0.861467
0.417887
0
0.144509
0
0
0.087778
0.042229
0
0
0
0
0
1
0.046243
false
0
0.057803
0
0.144509
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
1b6fa0d06ddf808de323e30136b2cb3ba0e36dbf
1,217
py
Python
filter_plugins/in_loop_list.py
jtyr/ansible-lvm_disk_extend
f7aca8c2cb752f233216666c7a820e8d6a9ffa1e
[ "MIT" ]
7
2016-08-31T13:00:29.000Z
2021-10-01T08:46:25.000Z
filter_plugins/in_loop_list.py
jtyr/ansible-lvm_disk_extend
f7aca8c2cb752f233216666c7a820e8d6a9ffa1e
[ "MIT" ]
null
null
null
filter_plugins/in_loop_list.py
jtyr/ansible-lvm_disk_extend
f7aca8c2cb752f233216666c7a820e8d6a9ffa1e
[ "MIT" ]
8
2017-01-31T19:08:27.000Z
2021-11-05T05:42:17.000Z
from ansible.module_utils.six import string_types def in_loop_list( val, loop_var, path=[], module='stat', param='exists', param_val=True): """Verifies if any of the loop results have the desired value""" ret = False for result in loop_var['results']: item = result['item'] for f...
25.893617
79
0.457683
120
1,217
4.533333
0.425
0.044118
0.055147
0
0
0
0
0
0
0
0
0.001529
0.462613
1,217
46
80
26.456522
0.830275
0.078883
0
0.121212
0
0
0.02973
0
0
0
0
0
0
1
0.060606
false
0
0.030303
0.030303
0.181818
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
1b71400982dc54036bfed93c9d3caf4be2635a78
2,883
py
Python
.tools/parser.py
Balnian/vcpkg-explorer
b67adfabd39dcf63e8f8e59f8a70ba162d6b9699
[ "MIT" ]
null
null
null
.tools/parser.py
Balnian/vcpkg-explorer
b67adfabd39dcf63e8f8e59f8a70ba162d6b9699
[ "MIT" ]
null
null
null
.tools/parser.py
Balnian/vcpkg-explorer
b67adfabd39dcf63e8f8e59f8a70ba162d6b9699
[ "MIT" ]
null
null
null
import argparse, os, json, io def dir_path(string): if os.path.isdir(string): return string else: raise NotADirectoryError(string) def dir_path(string): if os.path.isdir(string): return string else: raise NotADirectoryError(string) # Parse CONTROL File def simpleInse...
27.990291
109
0.645855
373
2,883
4.97319
0.310992
0.033962
0.016173
0.021024
0.202695
0.186523
0.113208
0.086253
0.086253
0.086253
0
0.00695
0.201526
2,883
103
110
27.990291
0.798871
0.136316
0
0.179104
0
0
0.100969
0
0
0
0
0
0
1
0.134328
false
0
0.014925
0
0.19403
0.029851
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
1b740de940b94786b8dade107ab2abfb4ca34794
859
py
Python
calendars/urls/calendar.py
mouradmourafiq/django-calendar
5cec7f8ac49637a02e331064d470255d1cbaf096
[ "BSD-2-Clause" ]
7
2015-02-23T11:59:02.000Z
2021-03-01T18:09:35.000Z
calendars/urls/calendar.py
mouradmourafiq/django-calendar
5cec7f8ac49637a02e331064d470255d1cbaf096
[ "BSD-2-Clause" ]
null
null
null
calendars/urls/calendar.py
mouradmourafiq/django-calendar
5cec7f8ac49637a02e331064d470255d1cbaf096
[ "BSD-2-Clause" ]
1
2016-09-15T11:37:08.000Z
2016-09-15T11:37:08.000Z
# -*- coding: utf-8 -*- ''' Created on Mar 20, 2011 @author: Mourad Mourafiq @copyright: Copyright © 2011 other contributers: ''' from django.conf.urls import patterns, include, url from calendars.views import calendar_tables as calendar_tables from calendars.views import events as events urlpatterns = patterns(''...
40.904762
163
0.706636
117
859
4.991453
0.435897
0.143836
0.061644
0.082192
0
0
0
0
0
0
0
0.014417
0.111758
859
21
164
40.904762
0.749672
0.14319
0
0
0
0.1
0.33882
0.192044
0
0
0
0
0
1
0
false
0
0.3
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
1b751be946e14f92ef6596264ea0fe477e367ac0
3,724
py
Python
sdk/identity/azure-identity/tests/test_chained_token_credential_async.py
rsdoherty/azure-sdk-for-python
6bba5326677468e6660845a703686327178bb7b1
[ "MIT" ]
2,728
2015-01-09T10:19:32.000Z
2022-03-31T14:50:33.000Z
sdk/identity/azure-identity/tests/test_chained_token_credential_async.py
rsdoherty/azure-sdk-for-python
6bba5326677468e6660845a703686327178bb7b1
[ "MIT" ]
17,773
2015-01-05T15:57:17.000Z
2022-03-31T23:50:25.000Z
sdk/identity/azure-identity/tests/test_chained_token_credential_async.py
rsdoherty/azure-sdk-for-python
6bba5326677468e6660845a703686327178bb7b1
[ "MIT" ]
1,916
2015-01-19T05:05:41.000Z
2022-03-31T19:36:44.000Z
# ------------------------------------ # Copyright (c) Microsoft Corporation. # Licensed under the MIT License. # ------------------------------------ from azure.core.credentials import AccessToken from azure.core.exceptions import ClientAuthenticationError from azure.identity import CredentialUnavailableError, ClientS...
34.165138
112
0.741407
431
3,724
6.180974
0.220418
0.051051
0.036036
0.04955
0.556306
0.438063
0.416291
0.368994
0.31494
0.272523
0
0.003812
0.154672
3,724
108
113
34.481481
0.84244
0.038131
0
0.337838
0
0
0.040934
0.006342
0
0
0
0
0.148649
1
0
false
0.013514
0.094595
0
0.094595
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
1b752507440aeed9f54d65f404fbb19a93263529
2,538
py
Python
needy/generators/xcconfig.py
carlbrown/needy
5a70726c9846f86a88be896ec39740296d503835
[ "MIT" ]
65
2015-07-21T01:40:17.000Z
2019-06-10T10:46:28.000Z
needy/generators/xcconfig.py
bittorrent/needy
31e57ad09d5fc22126e10b735c586262a50139d7
[ "MIT" ]
110
2015-07-21T01:41:40.000Z
2017-01-18T23:13:30.000Z
needy/generators/xcconfig.py
bittorrent/needy
31e57ad09d5fc22126e10b735c586262a50139d7
[ "MIT" ]
4
2015-07-20T02:45:43.000Z
2016-07-31T21:48:39.000Z
from ..generator import Generator from ..platforms import available_platforms from ..target import Target import os class XCConfigGenerator(Generator): @staticmethod def identifier(): return 'xcconfig' def __xcconfig(self, needy, target, sdk, arch): header_search_paths = [] libr...
47.886792
128
0.64342
277
2,538
5.66065
0.223827
0.091199
0.114796
0.143495
0.502551
0.485969
0.445153
0.409439
0.25
0.204082
0
0.025403
0.193459
2,538
52
129
48.807692
0.740596
0
0
0
0
0
0.234043
0.092987
0
0
0
0
0
1
0.076923
false
0
0.102564
0.025641
0.25641
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
1b770811d02f4fdde6f9b0fafb36764cd7c74385
6,166
py
Python
NLPEngine/app.py
hmi-digital/bot_platform
91a26e566b07fa309774d0333a6bccf3d64cccc5
[ "MIT" ]
null
null
null
NLPEngine/app.py
hmi-digital/bot_platform
91a26e566b07fa309774d0333a6bccf3d64cccc5
[ "MIT" ]
null
null
null
NLPEngine/app.py
hmi-digital/bot_platform
91a26e566b07fa309774d0333a6bccf3d64cccc5
[ "MIT" ]
null
null
null
# -*- coding: utf-8 -*- import json import os import re import sys, getopt import threading from warnings import simplefilter import flask from flask import request, abort, make_response, jsonify from utils import nlp_config from utils import log_util from core import train_model, predict_model from pubsub import cons...
33.879121
114
0.641421
789
6,166
4.852978
0.243346
0.028206
0.028728
0.054845
0.426482
0.374771
0.30034
0.276051
0.244189
0.244189
0
0.007676
0.218294
6,166
181
115
34.066298
0.786722
0.028381
0
0.321918
0
0
0.223596
0.022727
0
0
0
0
0
1
0.054795
false
0
0.10274
0.006849
0.191781
0.013699
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
1b775b82a0dc44534647e77cf8aa3514bf4dd4f3
1,587
py
Python
tests/models/status/test_remained.py
vikian050194/forty
7ef68fb06bb22a3008351c5a651eaa46b635d433
[ "MIT" ]
null
null
null
tests/models/status/test_remained.py
vikian050194/forty
7ef68fb06bb22a3008351c5a651eaa46b635d433
[ "MIT" ]
7
2021-03-15T17:18:36.000Z
2021-04-26T09:40:53.000Z
tests/models/status/test_remained.py
vikian050194/forty
7ef68fb06bb22a3008351c5a651eaa46b635d433
[ "MIT" ]
null
null
null
from datetime import timedelta, date from forty.managers.project_manager import Config from forty.views import RemainedStatusView from forty.models import StatusModel from forty.tools import ActionsBuilder as A from ..model_test_case import ModelTestCase class TestStatusModelRemainedMethod(ModelTestCase): def _...
32.387755
68
0.696912
197
1,587
5.441624
0.324873
0.083955
0.106343
0.086754
0.441231
0.441231
0.334888
0.334888
0.334888
0.334888
0
0.017067
0.187776
1,587
48
69
33.0625
0.814585
0
0
0.212121
0
0
0
0
0
0
0
0
0.242424
1
0.151515
false
0
0.181818
0.030303
0.393939
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
1b7b8c103d8d9616e435f7c21cd9decd8e6f142c
2,650
py
Python
tests/pconv_rfr.py
DesignStripe/torch_pconv
49e781bef96c511660ec35fcba68cf734710b10b
[ "BSD-3-Clause" ]
1
2021-08-13T18:22:07.000Z
2021-08-13T18:22:07.000Z
tests/pconv_rfr.py
DesignStripe/torch_pconv
49e781bef96c511660ec35fcba68cf734710b10b
[ "BSD-3-Clause" ]
null
null
null
tests/pconv_rfr.py
DesignStripe/torch_pconv
49e781bef96c511660ec35fcba68cf734710b10b
[ "BSD-3-Clause" ]
null
null
null
############################################################################### # BSD 3-Clause License # # Copyright (c) 2018, NVIDIA CORPORATION. All rights reserved. # # Author & Contact: Guilin Liu (guilinl@nvidia.com) ############################################################################### """ Code by Guilin...
33.974359
118
0.569057
328
2,650
4.466463
0.375
0.054608
0.076451
0.030717
0.063481
0
0
0
0
0
0
0.030036
0.271321
2,650
77
119
34.415584
0.728638
0.176981
0
0.155556
0
0
0
0
0
0
0
0
0
1
0.133333
false
0
0.066667
0.044444
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
1b7c9765a8a3c6eb3b11ae701c1e55797770abd3
7,543
py
Python
rs.py
rozium/rs-backend
9a5f81daf5b87a960436a95c91896b01860e3636
[ "MIT" ]
null
null
null
rs.py
rozium/rs-backend
9a5f81daf5b87a960436a95c91896b01860e3636
[ "MIT" ]
1
2019-04-05T13:23:13.000Z
2019-04-05T13:23:13.000Z
rs.py
rozium/rs-backend
9a5f81daf5b87a960436a95c91896b01860e3636
[ "MIT" ]
null
null
null
#!/usr/bin/env python # Rumah Sahaja backend import jwt import hashlib import datetime from functools import wraps from flask_sqlalchemy import SQLAlchemy from flask import Flask, request, jsonify, make_response from flask_cors import CORS app = Flask(__name__) app.config.from_pyfile('rs.cfg') __DEBUG__ = True __Fr...
31.560669
136
0.580141
863
7,543
4.951333
0.172654
0.046806
0.058507
0.029487
0.428973
0.397847
0.326235
0.296747
0.270536
0.251814
0
0.008438
0.167307
7,543
239
137
31.560669
0.671868
0.018163
0
0.314136
0
0
0.137371
0
0
0
0
0
0
1
0.073298
false
0.015707
0.036649
0.010471
0.350785
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
1b829b263e7d55960edfb8d2e11a2f4d079044be
1,334
py
Python
powerforecast/base.py
htpauleta/PowerForecast
f0e24e94c9dc62e56d2b770b85f6284ab96d697c
[ "Apache-2.0" ]
null
null
null
powerforecast/base.py
htpauleta/PowerForecast
f0e24e94c9dc62e56d2b770b85f6284ab96d697c
[ "Apache-2.0" ]
null
null
null
powerforecast/base.py
htpauleta/PowerForecast
f0e24e94c9dc62e56d2b770b85f6284ab96d697c
[ "Apache-2.0" ]
1
2020-12-07T02:21:12.000Z
2020-12-07T02:21:12.000Z
""" @Project : PowerForecast @Module : base.py @Author : HjwGivenLyy [1752929469@qq.com] @Created : 3/12/19 1:47 PM @Desc : basic module of entire project """ import numpy as np from sklearn.metrics import mean_squared_error, mean_absolute_error from sklearn.model_selection import train_test_split FI...
30.318182
73
0.656672
197
1,334
4.147208
0.390863
0.0306
0.034272
0.053856
0.265606
0.221542
0.162791
0.162791
0.122399
0.122399
0
0.033597
0.241379
1,334
43
74
31.023256
0.773715
0.144678
0
0
0
0
0.061443
0.048976
0
0
0
0
0
1
0.083333
false
0
0.125
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
1b845d9705a2fcbc398aa92244efea0721f73204
3,331
py
Python
utils/metrics.py
raghuch/SABER
fb0f26152b009f923aaf572cef80940f2f256330
[ "MIT" ]
5
2019-11-22T12:42:38.000Z
2020-07-14T14:51:47.000Z
utils/metrics.py
raghuch/SABER
fb0f26152b009f923aaf572cef80940f2f256330
[ "MIT" ]
null
null
null
utils/metrics.py
raghuch/SABER
fb0f26152b009f923aaf572cef80940f2f256330
[ "MIT" ]
1
2021-02-02T08:43:00.000Z
2021-02-02T08:43:00.000Z
import Levenshtein as Lev import numpy as np from utils.model_utils import get_most_probable from ignite.metrics import Metric, Accuracy from ignite.metrics.metric import reinit__is_reduced from datasets.librispeech import get_vocab_list, sequence_to_string import torch def werCalc(s1, s2): """ Computes the Wo...
31.424528
74
0.650555
451
3,331
4.616408
0.301552
0.057637
0.051873
0.053794
0.529299
0.529299
0.511047
0.447646
0.447646
0.364073
0
0.018898
0.237466
3,331
106
75
31.424528
0.800787
0.160612
0
0.373333
0
0
0.015013
0
0
0
0
0
0
1
0.133333
false
0
0.093333
0.013333
0.333333
0.013333
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
1b8ba167116b4e06f9ce668216dc0aca60bfda34
3,416
py
Python
docs/update_readme.py
KarlTDebiec/PipeScaler
b990ece8f3dd2c3506c226ed871871997fc57beb
[ "BSD-3-Clause" ]
1
2022-02-07T03:47:53.000Z
2022-02-07T03:47:53.000Z
docs/update_readme.py
KarlTDebiec/PipeScaler
b990ece8f3dd2c3506c226ed871871997fc57beb
[ "BSD-3-Clause" ]
49
2022-01-17T15:16:22.000Z
2022-03-28T03:00:39.000Z
docs/update_readme.py
KarlTDebiec/PipeScaler
b990ece8f3dd2c3506c226ed871871997fc57beb
[ "BSD-3-Clause" ]
null
null
null
#!/usr/bin/env python # update_readme.py # # Copyright (C) 2020-2021 Karl T Debiec # All rights reserved. # # This software may be modified and distributed under the terms of the # BSD license. """Updates readme.""" import re from inspect import cleandoc, getfile from os.path import dirname, join, splitext fr...
28.705882
85
0.658372
435
3,416
4.983908
0.347126
0.041974
0.01845
0.017989
0.098708
0.072878
0.02952
0.02952
0.02952
0
0
0.003833
0.236241
3,416
118
86
28.949153
0.827137
0.278103
0
0
0
0.018519
0.087855
0.029716
0
0
0
0
0
1
0.074074
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
1b8e709913bd8c5a373bf4dc6fb3e19539c1836c
7,060
py
Python
inventory_to_shippo_labels.py
ramanshahdatascience/t-shirts
a49edfeddd6f8eb51979464cce260b0288c75f4a
[ "BSD-3-Clause" ]
1
2022-02-28T03:44:10.000Z
2022-02-28T03:44:10.000Z
inventory_to_shippo_labels.py
ramanshahdatascience/t-shirts
a49edfeddd6f8eb51979464cce260b0288c75f4a
[ "BSD-3-Clause" ]
null
null
null
inventory_to_shippo_labels.py
ramanshahdatascience/t-shirts
a49edfeddd6f8eb51979464cce260b0288c75f4a
[ "BSD-3-Clause" ]
null
null
null
#! /usr/bin/env python3 '''Usage: ./inventory_to_shippo_labels.py tshirt_inventory.xlsx labels.csv''' import copy import csv import math import re from sys import argv import warnings import openpyxl # Measured masses of t-shirts by size, in oz SHIRT_WEIGHTS = {'MXS': 3.45 / 1, 'MS': 11.45 / 3, ...
35.124378
82
0.565156
896
7,060
4.362723
0.327009
0.02814
0.016628
0.015349
0.14505
0.101561
0.064722
0.041954
0.041954
0.041954
0
0.029821
0.297026
7,060
200
83
35.3
0.757808
0.177337
0
0.057143
0
0.021429
0.162626
0
0
0
0
0
0.035714
1
0.014286
false
0.014286
0.05
0
0.078571
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
1b8f165c611bb069dfd9e9a4299c2c9de8f14d21
1,299
py
Python
projecteuler/projectEuler13.py
qingfengxia/python-projecteuler
a2cba042fe7256364f6a5fa55df805a87da9a301
[ "BSD-2-Clause-FreeBSD" ]
null
null
null
projecteuler/projectEuler13.py
qingfengxia/python-projecteuler
a2cba042fe7256364f6a5fa55df805a87da9a301
[ "BSD-2-Clause-FreeBSD" ]
null
null
null
projecteuler/projectEuler13.py
qingfengxia/python-projecteuler
a2cba042fe7256364f6a5fa55df805a87da9a301
[ "BSD-2-Clause-FreeBSD" ]
null
null
null
# -*- coding: utf-8 -*- from __future__ import print_function, unicode_literals, absolute_import, division """ Work out the first ten digits of the sum of the following one-hundred 50-digit numbers. """ from projecteulerhelper import * ########################################## def ProjectEuler13()...
34.184211
88
0.585835
187
1,299
3.989305
0.497326
0.033512
0.053619
0.064343
0.092493
0.050938
0.050938
0
0
0
0
0.034056
0.254042
1,299
37
89
35.108108
0.73581
0.227868
0
0.086957
0
0
0.103194
0
0
0
0
0
0
1
0.086957
false
0
0.086957
0
0.217391
0.130435
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
1b909b1dba2bfad79729fc3069bd4e37223b3379
2,758
py
Python
merc/features/rfc1459/info.py
merc-devel/merc
15e010db2474b5d9f9720fc83983b03c95063a02
[ "MIT" ]
4
2015-02-15T03:37:34.000Z
2017-03-27T12:39:10.000Z
merc/features/rfc1459/info.py
merc-devel/merc
15e010db2474b5d9f9720fc83983b03c95063a02
[ "MIT" ]
null
null
null
merc/features/rfc1459/info.py
merc-devel/merc
15e010db2474b5d9f9720fc83983b03c95063a02
[ "MIT" ]
null
null
null
import collections import datetime from merc import feature from merc import message INFO_TEMPLATE = """\ ____ __/ / /___ _ ___ ________ /_ . __/ ' \/ -_) __/ __/ /_ __/_/_/_/\__/_/ \__/ /_/_/ The Modern Extensible Relay Chat daemon, version {version}. Copyright (C) {year}, #merc-devel This softwar...
22.422764
79
0.652284
353
2,758
4.858357
0.461756
0.03207
0.029738
0.025656
0.058309
0.058309
0.034985
0
0
0
0
0.024276
0.22335
2,758
122
80
22.606557
0.776377
0
0
0.044444
0
0
0.298042
0.007614
0
0
0
0
0
1
0.066667
false
0
0.044444
0.022222
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
1b90ae9be207fedc1b292b926c40882eae131319
1,878
py
Python
divizor_master.py
Andrey-Mel/DZ_lesson_5
0f80a352c6d349738b22780942c7738c7d33e2fe
[ "MIT" ]
null
null
null
divizor_master.py
Andrey-Mel/DZ_lesson_5
0f80a352c6d349738b22780942c7738c7d33e2fe
[ "MIT" ]
null
null
null
divizor_master.py
Andrey-Mel/DZ_lesson_5
0f80a352c6d349738b22780942c7738c7d33e2fe
[ "MIT" ]
null
null
null
'''Необходимо реализовать модуль divisor_master. Все функции модуля принимают на вход натуральные числа от 1 до 1000. Модуль содержит функции: 1) проверка числа на простоту (простые числа - это те числа у которых делители единица и они сами); 2) выводит список всех делителей числа; 3) выводит самый большой простой дел...
24.38961
117
0.609691
248
1,878
4.524194
0.375
0.026738
0.030303
0.046346
0.055258
0
0
0
0
0
0
0.027068
0.2918
1,878
76
118
24.710526
0.816541
0.306177
0
0.177778
0
0
0.20047
0.017228
0
0
0
0
0
1
0.066667
false
0
0.022222
0
0.088889
0.133333
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
1b91bc419d87130534d251b58ff87a17cca48671
640
py
Python
django/i_dont_need_this/web/otp.py
AakashKhatu/iDontNeedThis
9b50a9377555fe990a7f21372e339a3f264800a9
[ "MIT" ]
2
2019-04-04T13:37:17.000Z
2019-04-04T13:38:09.000Z
django/i_dont_need_this/web/otp.py
AakashKhatu/iDontNeedThis
9b50a9377555fe990a7f21372e339a3f264800a9
[ "MIT" ]
null
null
null
django/i_dont_need_this/web/otp.py
AakashKhatu/iDontNeedThis
9b50a9377555fe990a7f21372e339a3f264800a9
[ "MIT" ]
1
2019-04-04T03:50:46.000Z
2019-04-04T03:50:46.000Z
import requests import random def send_otp(number): url = "https://www.fast2sms.com/dev/bulk" otp = random.randint(10000, 99999) querystring = {"authorization": "ZM2aEdmsy3WHNI8xejK6kiJ4hCYrBuwfn9t5QSLpov0VRb7lcP0qHGS5fkgWtPNX2YhFrQy9JnBOZTD6", "sender_id": "FSTSMS", "language": "engli...
33.684211
119
0.621875
57
640
6.929825
0.754386
0
0
0
0
0
0
0
0
0
0
0.059305
0.235938
640
18
120
35.555556
0.748466
0
0
0
0
0
0.365625
0.125
0
0
0
0
0
1
0.066667
false
0
0.133333
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
1b923877a3fa52e1bcbc2ba2772f7f2b28266243
3,084
py
Python
CoreConceptsPy/GdalPy/test/networks_test.py
spatial-ucsb/ConceptsOfSpatialInformation
73d54a37ced14bc5ecb064f9d1ab8b1af8cd3c5a
[ "Apache-2.0" ]
18
2015-03-03T22:57:20.000Z
2020-06-17T10:17:58.000Z
CoreConceptsPy/GdalPy/test/networks_test.py
spatial-ucsb/ConceptsOfSpatialInformation
73d54a37ced14bc5ecb064f9d1ab8b1af8cd3c5a
[ "Apache-2.0" ]
1
2017-02-23T20:06:06.000Z
2017-02-23T20:06:06.000Z
CoreConceptsPy/GdalPy/test/networks_test.py
spatial-ucsb/ConceptsOfSpatialInformation
73d54a37ced14bc5ecb064f9d1ab8b1af8cd3c5a
[ "Apache-2.0" ]
16
2015-02-13T02:05:36.000Z
2018-09-07T04:02:13.000Z
#!/usr/bin/env python # -*- coding: utf-8 -*- """ Abstract: Unit tests for the implementations of the core concept 'network' """ __author__ = "Michel Zimmer" __copyright__ = "Copyright 2014" __credits__ = ["Michel Zimmer"] __license__ = "" __version__ = "0.1" __maintainer__ = "" __email__ = "" __date__ = "December 2...
22.844444
75
0.498379
390
3,084
3.789744
0.2
0.138701
0.17862
0.087957
0.47226
0.368742
0.301083
0.240189
0.205007
0.186739
0
0.064008
0.34144
3,084
134
76
23.014925
0.663712
0.087224
0
0.253521
0
0
0.038661
0
0
0
0
0
0.197183
1
0.15493
false
0
0.070423
0
0.239437
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
1b933659f87b8cf39336c9379fc5288ae062f439
6,714
py
Python
onap_data_provider/resources/sdc_properties_mixins.py
onap/integration-data-provider
0565394ecbd96730bf982909693514ab88703708
[ "Apache-2.0" ]
null
null
null
onap_data_provider/resources/sdc_properties_mixins.py
onap/integration-data-provider
0565394ecbd96730bf982909693514ab88703708
[ "Apache-2.0" ]
null
null
null
onap_data_provider/resources/sdc_properties_mixins.py
onap/integration-data-provider
0565394ecbd96730bf982909693514ab88703708
[ "Apache-2.0" ]
null
null
null
"""SDC properties mixins module.""" """ Copyright 2021 Deutsche Telekom AG 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 r...
40.203593
112
0.613196
740
6,714
5.433784
0.22027
0.04377
0.022382
0.024372
0.323303
0.263865
0.172096
0.142253
0.142253
0.114897
0
0.001931
0.30563
6,714
166
113
40.445783
0.860575
0.212243
0
0.326316
0
0
0.119053
0.029312
0
0
0
0
0
1
0.052632
false
0
0.084211
0
0.168421
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
1b94671a381123d62794de44e17b4732cff5ed86
3,193
py
Python
simple_kg/discovery/entropy_pmi_new_word_discovery/utils.py
xiangking/simpleKG
d1464ec649022e17b2352b6249749af1b064526e
[ "MIT" ]
1
2021-09-18T18:02:44.000Z
2021-09-18T18:02:44.000Z
simple_kg/discovery/entropy_pmi_new_word_discovery/utils.py
xiangking/simpleKG
d1464ec649022e17b2352b6249749af1b064526e
[ "MIT" ]
null
null
null
simple_kg/discovery/entropy_pmi_new_word_discovery/utils.py
xiangking/simpleKG
d1464ec649022e17b2352b6249749af1b064526e
[ "MIT" ]
null
null
null
import re import math import codecs import random import numpy as np def is_not_chinese(uchar:str): """ 判断一个unicode是否是汉字 :param uchar: (str) 待判断的字符 """ if uchar.isalpha() is True: return False elif uchar >= u'\u4e00' and uchar <= u'\u9fa5': return False else: retur...
24.945313
145
0.561854
386
3,193
4.53886
0.375648
0.031963
0.013699
0.043379
0.047945
0
0
0
0
0
0
0.020147
0.316004
3,193
128
146
24.945313
0.782051
0.257125
0
0.067797
0
0
0.005666
0
0
0
0
0
0
1
0.135593
false
0
0.084746
0
0.338983
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
1b96e763ec1fd38d58bc97efc3d4e768f050096b
5,323
py
Python
data_loader_UAST.py
kkcookies99/UAST
fff81885aa07901786141a71e5600a08d7cb4868
[ "MIT" ]
null
null
null
data_loader_UAST.py
kkcookies99/UAST
fff81885aa07901786141a71e5600a08d7cb4868
[ "MIT" ]
null
null
null
data_loader_UAST.py
kkcookies99/UAST
fff81885aa07901786141a71e5600a08d7cb4868
[ "MIT" ]
null
null
null
import torch from torch.utils.data import Dataset, DataLoader from pre_ast_path import ASTParser from tqdm import tqdm, trange import multiprocessing from multiprocessing import Process, freeze_support import pickle import config import os import re from gen_graph import get_adj, gen_feature from unified_vocab import u...
33.062112
124
0.629344
746
5,323
4.272118
0.289544
0.041732
0.037653
0.032005
0.283652
0.244117
0.224976
0.18042
0.168811
0.141826
0
0.052058
0.224122
5,323
160
125
33.26875
0.719613
0.054856
0
0.101695
0
0
0.078041
0.005973
0
0
0
0
0
1
0.067797
false
0
0.101695
0.008475
0.237288
0.076271
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
1b97dcc4fee182443ecf7a65d71d064d71890c18
847
py
Python
benedict/serializers/json.py
fabiocaccamo/python-benedict
da061049164efab95ee4360a9c971c5be248fbf2
[ "MIT" ]
365
2019-05-21T05:50:30.000Z
2022-03-29T11:35:35.000Z
benedict/serializers/json.py
fabiocaccamo/python-benedict
da061049164efab95ee4360a9c971c5be248fbf2
[ "MIT" ]
78
2019-11-16T12:22:54.000Z
2022-03-14T12:21:30.000Z
benedict/serializers/json.py
fabiocaccamo/python-benedict
da061049164efab95ee4360a9c971c5be248fbf2
[ "MIT" ]
26
2019-12-16T06:34:12.000Z
2022-02-28T07:16:41.000Z
# -*- coding: utf-8 -*- from __future__ import absolute_import from benedict.serializers.abstract import AbstractSerializer from benedict.utils import type_util from six import text_type import json class JSONSerializer(AbstractSerializer): def __init__(self): super(JSONSerializer, self).__init__() ...
24.911765
60
0.654073
104
847
5.067308
0.413462
0.060721
0.056926
0.072106
0.165085
0
0
0
0
0
0
0.001567
0.246753
847
33
61
25.666667
0.824451
0.024793
0
0.173913
0
0
0.008495
0
0
0
0
0
0
1
0.173913
false
0
0.217391
0
0.695652
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
1b981f9403e35e3edad1513c56a1d0685d8c02e9
5,148
py
Python
docs/report/fa20-523-349/project/RankNet/indycar/online-lstm.py
mikahla1/cybertraining-dsc.github.io
168cadb2f755cb6ad4907e5656bd879d57e01e43
[ "Apache-2.0" ]
4
2020-10-16T21:59:07.000Z
2021-06-27T16:32:50.000Z
docs/report/fa20-523-349/project/RankNet/indycar/online-lstm.py
mikahla1/cybertraining-dsc.github.io
168cadb2f755cb6ad4907e5656bd879d57e01e43
[ "Apache-2.0" ]
8
2020-09-04T13:14:18.000Z
2021-08-19T09:05:27.000Z
docs/report/fa20-523-349/project/RankNet/indycar/online-lstm.py
mikahla1/cybertraining-dsc.github.io
168cadb2f755cb6ad4907e5656bd879d57e01e43
[ "Apache-2.0" ]
25
2020-08-16T17:17:53.000Z
2021-07-08T22:54:34.000Z
from pandas import DataFrame from pandas import Series from pandas import concat from pandas import read_csv from pandas import datetime from sklearn.metrics import mean_squared_error from sklearn.preprocessing import MinMaxScaler from keras.models import Sequential from keras.layers import Dense from keras.layers impo...
34.32
120
0.668221
726
5,148
4.625344
0.242424
0.026802
0.023824
0.016379
0.124479
0.055986
0.055986
0.055986
0.055986
0.055986
0
0.01892
0.219697
5,148
149
121
34.550336
0.817028
0.165113
0
0.06
0
0
0.03004
0.010326
0
0
0
0
0
1
0.11
false
0
0.14
0.02
0.34
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
1b9a65a2e9f2cc5df22b0506c5bd68872b48ef7e
11,625
py
Python
src/hpx_dashboard/server/widgets/widgets.py
jokteur/hpx-dashboard
91ca3876dec389e514f89f34acdb6ec9cac9d1b4
[ "BSD-3-Clause" ]
6
2020-07-31T08:12:09.000Z
2022-01-16T03:35:06.000Z
src/hpx_dashboard/server/widgets/widgets.py
jokteur/hpx-dashboard
91ca3876dec389e514f89f34acdb6ec9cac9d1b4
[ "BSD-3-Clause" ]
23
2020-08-12T08:51:12.000Z
2020-09-29T16:45:54.000Z
src/hpx_dashboard/server/widgets/widgets.py
jokteur/hpx-dashboard
91ca3876dec389e514f89f34acdb6ec9cac9d1b4
[ "BSD-3-Clause" ]
2
2020-10-08T13:55:45.000Z
2022-01-16T03:37:13.000Z
# -*- coding: utf-8 -*- # # HPX - dashboard # # Copyright (c) 2020 - ETH Zurich # All rights reserved # # SPDX-License-Identifier: BSD-3-Clause """ """ import copy from datetime import datetime import json from bokeh.layouts import column, row from bokeh.models.widgets import Button, Div, Toggle, TextAreaInput from...
33.598266
100
0.590624
1,364
11,625
4.771261
0.177419
0.024892
0.014751
0.007376
0.248002
0.139367
0.108021
0.095267
0.072526
0.072526
0
0.00825
0.311828
11,625
345
101
33.695652
0.80525
0.138065
0
0.114035
0
0
0.073475
0.007982
0
0
0
0
0
1
0.074561
false
0
0.04386
0
0.157895
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
1b9e89c2c7b2551425e05e9bab467dd513d23999
15,379
py
Python
src/core/uv_edit/prim.py
Epihaius/panda3dstudio
f5c62ca49617cae1aa5aa5b695200027da99e242
[ "BSD-3-Clause" ]
63
2016-01-02T16:28:47.000Z
2022-01-19T11:29:51.000Z
src/core/uv_edit/prim.py
Epihaius/panda3dstudio
f5c62ca49617cae1aa5aa5b695200027da99e242
[ "BSD-3-Clause" ]
12
2016-06-12T14:14:15.000Z
2020-12-18T16:11:45.000Z
src/core/uv_edit/prim.py
Epihaius/panda3dstudio
f5c62ca49617cae1aa5aa5b695200027da99e242
[ "BSD-3-Clause" ]
17
2016-05-23T00:02:27.000Z
2021-04-25T17:48:27.000Z
from .base import * import array class UVPrimitivePart: def __init__(self, picking_color_id, owner, data_row_range, start_positions, default_positions, geom_prim, pos): self.picking_color_id = picking_color_id self.id = picking_color_id self.owner = owner self.da...
36.185882
91
0.63099
2,053
15,379
4.375548
0.093035
0.072359
0.026494
0.026049
0.516977
0.408549
0.386508
0.354447
0.337638
0.297562
0
0.011423
0.265687
15,379
424
92
36.271226
0.784026
0
0
0.31746
0
0
0.026075
0.006437
0
0
0
0
0
1
0.073016
false
0
0.006349
0.006349
0.107937
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
1ba2705eba4f588807811918b9d16b830ce3ae7b
5,185
py
Python
lyrebird/config.py
voodoocooder/lyrebird
02e6ebdcfd646855f9648293d9b5ef6da1c6603b
[ "MIT" ]
1
2020-12-11T03:20:11.000Z
2020-12-11T03:20:11.000Z
lyrebird/config.py
voodoocooder/lyrebird
02e6ebdcfd646855f9648293d9b5ef6da1c6603b
[ "MIT" ]
null
null
null
lyrebird/config.py
voodoocooder/lyrebird
02e6ebdcfd646855f9648293d9b5ef6da1c6603b
[ "MIT" ]
null
null
null
import codecs import json import os from pathlib import Path import shutil from packaging import version from lyrebird.mock.logger_helper import get_logger from .version import IVERSION from typing import List from flask import Response, abort from lyrebird.mock.console_helper import warning_msg, err_msg import subpro...
35.272109
124
0.615043
671
5,185
4.587183
0.201192
0.035737
0.036387
0.044185
0.215725
0.169591
0.11371
0.103314
0.077973
0.017544
0
0.003671
0.264417
5,185
146
125
35.513699
0.803356
0.007522
0
0.12069
0
0
0.069325
0.014025
0
0
0
0
0
1
0.112069
false
0.017241
0.112069
0.017241
0.327586
0.017241
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
1ba28bfe8ab06942b3b06a80f0ac591f457cd467
1,279
py
Python
LeetCode/Python3/Math/313. Super Ugly Number.py
WatsonWangZh/CodingPractice
dc057dd6ea2fc2034e14fd73e07e73e6364be2ae
[ "MIT" ]
11
2019-09-01T22:36:00.000Z
2021-11-08T08:57:20.000Z
LeetCode/Python3/Math/313. Super Ugly Number.py
WatsonWangZh/LeetCodePractice
dc057dd6ea2fc2034e14fd73e07e73e6364be2ae
[ "MIT" ]
null
null
null
LeetCode/Python3/Math/313. Super Ugly Number.py
WatsonWangZh/LeetCodePractice
dc057dd6ea2fc2034e14fd73e07e73e6364be2ae
[ "MIT" ]
2
2020-05-27T14:58:52.000Z
2020-05-27T15:04:17.000Z
# Write a program to find the nth super ugly number. # Super ugly numbers are positive numbers # whose all prime factors are in the given prime list primes of size k. # Example: # Input: n = 12, primes = [2,7,13,19] # Output: 32 # Explanation: [1,2,4,7,8,13,14,16,19,26,28,32] is the sequence of the first 12 # ...
31.975
80
0.526192
190
1,279
3.547368
0.421053
0.066766
0.066766
0.071217
0.15727
0.059347
0
0
0
0
0
0.070905
0.360438
1,279
40
81
31.975
0.750611
0.487099
0
0.125
0
0
0.00468
0
0
0
0
0
0
1
0.0625
false
0
0
0
0.1875
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
1ba40fa09320088e8373dee62cef5d2fb0a82f5f
3,368
py
Python
third_party_package/RDKit_2015_03_1/rdkit/Chem/EState/EState_VSA.py
Ivy286/cluster_basedfps
7fc216537f570436f008ea567c137d03ba2b6d81
[ "WTFPL" ]
9
2019-04-23T01:46:12.000Z
2021-08-16T07:07:12.000Z
third_party_package/RDKit_2015_03_1/rdkit/Chem/EState/EState_VSA.py
Ivy286/cluster_basedfps
7fc216537f570436f008ea567c137d03ba2b6d81
[ "WTFPL" ]
null
null
null
third_party_package/RDKit_2015_03_1/rdkit/Chem/EState/EState_VSA.py
Ivy286/cluster_basedfps
7fc216537f570436f008ea567c137d03ba2b6d81
[ "WTFPL" ]
5
2016-09-21T03:47:48.000Z
2019-07-30T22:17:35.000Z
# $Id$ # # Copyright (C)2003-2010 greg Landrum and Rational Discovery LLC # # @@ All Rights Reserved @@ # This file is part of the RDKit. # The contents are covered by the terms of the BSD license # which is included in the file license.txt, found at the root # of the RDKit source tree. # """ Hybrid EState-VSA de...
30.618182
102
0.676366
566
3,368
3.922261
0.259717
0.016216
0.010811
0.018018
0.623874
0.595496
0.582883
0.565766
0.543243
0.482883
0
0.049062
0.17696
3,368
109
103
30.899083
0.751804
0.139846
0
0.575758
0
0
0.147023
0
0
0
0
0
0
1
0.045455
false
0
0.060606
0
0.166667
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
1ba69541de6a827ed0694499f2b0ff1f99e24608
2,019
py
Python
examples/extract_clips.py
hannahherbig/gopro-py-api
7f4f87bc34448e95c2ff1230fe85724420db8b4e
[ "MIT" ]
null
null
null
examples/extract_clips.py
hannahherbig/gopro-py-api
7f4f87bc34448e95c2ff1230fe85724420db8b4e
[ "MIT" ]
1
2021-06-11T01:02:30.000Z
2021-06-11T01:02:30.000Z
examples/extract_clips.py
hannahherbig/gopro-py-api
7f4f87bc34448e95c2ff1230fe85724420db8b4e
[ "MIT" ]
null
null
null
import time import numpy as np from goprocam import GoProCamera, constants gpCam = GoProCamera.GoPro() # Extracts clips from latest video latestVideo = gpCam.getVideoInfo() print("Tag count %s" % latestVideo.get(constants.Info.TagCount)) arrayLength = latestVideo[constants.Info.TagCount] if arrayLength % 2 == 0: ...
31.546875
82
0.526003
197
2,019
5.350254
0.411168
0.037951
0.051233
0.071158
0.29981
0.263757
0.263757
0.263757
0.263757
0.263757
0
0.014116
0.333333
2,019
63
83
32.047619
0.768945
0.015849
0
0.315789
0
0
0.115869
0
0
0
0
0
0
1
0
false
0
0.052632
0
0.052632
0.105263
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
1ba76bd8b43fd2bdb2df468a9e9d41baccb0e88c
1,647
py
Python
gogoedu/management/commands/create-examples.py
tuandang98/gogoedu
f98587f9d315e1253d3a3b9e1e4cd9f148184e29
[ "MIT" ]
2
2021-04-27T16:00:32.000Z
2021-05-30T14:00:07.000Z
gogoedu/management/commands/create-misson.py
tuandang98/gogoedu
f98587f9d315e1253d3a3b9e1e4cd9f148184e29
[ "MIT" ]
null
null
null
gogoedu/management/commands/create-misson.py
tuandang98/gogoedu
f98587f9d315e1253d3a3b9e1e4cd9f148184e29
[ "MIT" ]
null
null
null
from django.core.management import BaseCommand from django_gamification.models import BadgeDefinition, Category, UnlockableDefinition, GamificationInterface from gogoedu.models import myUser class Command(BaseCommand): help = 'Generates fake data for the app' def handle(self, *args, **options): cate...
31.075472
112
0.612629
145
1,647
6.862069
0.413793
0.078392
0.102513
0.128643
0
0
0
0
0
0
0
0.022887
0.310261
1,647
52
113
31.673077
0.852993
0
0
0.162791
0
0
0.151184
0
0
0
0
0
0
1
0.023256
false
0
0.069767
0
0.139535
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
1ba9ca4fa4978599705739170468a0038dc28a23
16,675
py
Python
sea/directivity.py
MuriloCardosoSoares/sea
aa105cbbedcde0ddcb1047c28cd4337e7f72ee6d
[ "MIT" ]
5
2020-12-14T14:00:01.000Z
2021-11-22T17:51:55.000Z
sea/directivity.py
MuriloCardosoSoares/sea
aa105cbbedcde0ddcb1047c28cd4337e7f72ee6d
[ "MIT" ]
null
null
null
sea/directivity.py
MuriloCardosoSoares/sea
aa105cbbedcde0ddcb1047c28cd4337e7f72ee6d
[ "MIT" ]
null
null
null
import numpy as np import scipy import scipy.io import pickle from scipy.special import lpmv, spherical_jn, spherical_yn class Directivity: def __init__(self, data_path, rho0, c0, freq_vec, simulated_ir_duration, measurement_radius, sh_order, type, sample_rate=44100, **kwargs): ''...
46.319444
261
0.544168
2,154
16,675
4.061746
0.177344
0.018516
0.022288
0.004801
0.441993
0.399474
0.354555
0.33501
0.324609
0.286661
0
0.019066
0.348906
16,675
359
262
46.448468
0.786774
0.271664
0
0.213018
0
0
0.041862
0
0
0
0
0
0
1
0.029586
false
0.005917
0.029586
0
0.08284
0.065089
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
1bad56ad689387d54b73f03233d0f2cbf354e3cc
1,048
py
Python
migrations/versions/570_create_brief_responses_table.py
uk-gov-mirror/alphagov.digitalmarketplace-api
5a1db63691d0c4a435714837196ab6914badaf62
[ "MIT" ]
25
2015-01-14T10:45:13.000Z
2021-05-26T17:21:41.000Z
migrations/versions/570_create_brief_responses_table.py
uk-gov-mirror/alphagov.digitalmarketplace-api
5a1db63691d0c4a435714837196ab6914badaf62
[ "MIT" ]
641
2015-01-15T11:10:50.000Z
2021-06-15T22:18:42.000Z
migrations/versions/570_create_brief_responses_table.py
uk-gov-mirror/alphagov.digitalmarketplace-api
5a1db63691d0c4a435714837196ab6914badaf62
[ "MIT" ]
22
2015-06-13T15:37:45.000Z
2021-08-19T23:40:49.000Z
"""Create brief responses table Revision ID: 570 Revises: 560 Create Date: 2016-02-10 12:19:22.888832 """ # revision identifiers, used by Alembic. revision = '570' down_revision = '560' from alembic import op import sqlalchemy as sa from sqlalchemy.dialects import postgresql def upgrade(): op.create_table('br...
29.942857
107
0.714695
139
1,048
5.208633
0.381295
0.135359
0.103591
0.116022
0.223757
0.223757
0.223757
0.09116
0
0
0
0.034973
0.126908
1,048
34
108
30.823529
0.756284
0.132634
0
0
0
0
0.244173
0.08768
0
0
0
0
0
1
0.1
false
0
0.15
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
1baf04303536b99a3ebb6d62d4ffeb153d15b182
2,224
py
Python
tests/stages/test_sklearn_stages.py
blakeNaccarato/pdpcli
ad3ca6c2eccb552bfb4450b5cce02b30c5087282
[ "MIT" ]
15
2021-02-24T18:22:45.000Z
2022-01-06T22:08:46.000Z
tests/stages/test_sklearn_stages.py
blakeNaccarato/pdpcli
ad3ca6c2eccb552bfb4450b5cce02b30c5087282
[ "MIT" ]
1
2022-01-07T08:13:07.000Z
2022-01-07T08:13:07.000Z
tests/stages/test_sklearn_stages.py
blakeNaccarato/pdpcli
ad3ca6c2eccb552bfb4450b5cce02b30c5087282
[ "MIT" ]
1
2022-01-06T22:08:44.000Z
2022-01-06T22:08:44.000Z
import numpy import pandas from sklearn.decomposition import PCA from sklearn.feature_extraction.text import TfidfVectorizer from sklearn.linear_model import LogisticRegression from pdpcli.stages.sklearn_stages import SklearnPredictor, SklearnTransformer def test_sklearn_predictor() -> None: df = pandas.DataFram...
25.563218
77
0.600719
257
2,224
5.027237
0.272374
0.100619
0.03483
0.065015
0.458204
0.458204
0.458204
0.458204
0.396285
0.396285
0
0.013707
0.245504
2,224
86
78
25.860465
0.756257
0
0
0.376812
0
0
0.091727
0
0
0
0
0
0.086957
1
0.057971
false
0
0.086957
0
0.144928
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
1bb5310f158638846addef3485329fd1186a5a2c
3,823
py
Python
src/naima/tests/test_saveread.py
zblz/naima
4e7b85dfcbc00d5e4474c2f339ace0e565c9ffcd
[ "BSD-3-Clause" ]
32
2015-01-02T03:09:58.000Z
2022-03-04T15:30:53.000Z
src/naima/tests/test_saveread.py
Tyrannosaurusxuan/naima
4e7b85dfcbc00d5e4474c2f339ace0e565c9ffcd
[ "BSD-3-Clause" ]
97
2015-01-28T20:09:44.000Z
2021-11-01T23:16:12.000Z
src/naima/tests/test_saveread.py
Tyrannosaurusxuan/naima
4e7b85dfcbc00d5e4474c2f339ace0e565c9ffcd
[ "BSD-3-Clause" ]
45
2015-01-16T09:17:15.000Z
2022-03-31T08:33:46.000Z
# Licensed under a 3-clause BSD style license - see LICENSE.rst import os import astropy.units as u import numpy as np from astropy.io import ascii from astropy.tests.helper import pytest from astropy.utils.data import get_pkg_data_filename from ..analysis import read_run, save_run from ..model_fitter import Interact...
30.584
73
0.69762
546
3,823
4.70696
0.241758
0.028016
0.049805
0.029572
0.319066
0.29572
0.271595
0.245914
0.245914
0.245914
0
0.010003
0.18938
3,823
124
74
30.830645
0.819297
0.018572
0
0.25
0
0
0.068036
0.032284
0
0
0
0
0.135417
1
0.041667
false
0
0.177083
0
0.21875
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
1bb7506d3b4ef13debad4f463bd0c3cecc4860d0
7,513
py
Python
twccli/commands/net.py
TW-NCHC/TWCC-CLI
743be786440ff6f9689c6a10cc2131565e51d391
[ "Apache-2.0" ]
12
2019-04-27T07:45:02.000Z
2020-11-13T08:16:18.000Z
twccli/commands/net.py
twcc/TWCC-CLI
743be786440ff6f9689c6a10cc2131565e51d391
[ "Apache-2.0" ]
23
2021-03-05T07:53:37.000Z
2022-03-20T03:12:33.000Z
twccli/commands/net.py
TW-NCHC/TWCC-CLI
743be786440ff6f9689c6a10cc2131565e51d391
[ "Apache-2.0" ]
6
2019-02-27T00:19:11.000Z
2020-11-13T08:16:19.000Z
from twccli.twcc.services.compute import GpuSite, VcsSite, VcsSecurityGroup, VcsServerNet from twccli.twcc.util import isNone, mk_names from twccli.twcc.services.compute import getServerId, getSecGroupList from twccli.twcc.services.compute_util import list_vcs from twccli.twccli import pass_environment, logger from twc...
33.540179
231
0.591508
920
7,513
4.7
0.248913
0.020814
0.019426
0.025439
0.317761
0.237512
0.199815
0.140148
0.140148
0.140148
0
0.010071
0.286304
7,513
223
232
33.690583
0.796345
0.119526
0
0.285714
0
0.011905
0.203536
0.009839
0
0
0
0
0
1
0.041667
false
0.02381
0.071429
0
0.125
0.005952
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
1bb7fb2a1b9c93628680395b5402a95c58d49234
16,609
py
Python
qsiprep/cli/recon_plot.py
arokem/qsiprep
f0a12fa002ea99cad97f2b5e40c1517d0569e14c
[ "BSD-3-Clause" ]
null
null
null
qsiprep/cli/recon_plot.py
arokem/qsiprep
f0a12fa002ea99cad97f2b5e40c1517d0569e14c
[ "BSD-3-Clause" ]
null
null
null
qsiprep/cli/recon_plot.py
arokem/qsiprep
f0a12fa002ea99cad97f2b5e40c1517d0569e14c
[ "BSD-3-Clause" ]
null
null
null
#!/usr/bin/env python import warnings import os import sys import os.path as op from argparse import ArgumentParser from argparse import RawTextHelpFormatter import nibabel as nb import numpy as np from qsiprep.niworkflows.viz.utils import slices_from_bbox from qsiprep.interfaces.converters import fib2amps, mif2amps fr...
43.252604
90
0.617858
2,188
16,609
4.438757
0.146709
0.025535
0.014415
0.013386
0.449959
0.411347
0.389003
0.341845
0.323105
0.309308
0
0.016133
0.272262
16,609
384
91
43.252604
0.787375
0.037088
0
0.295238
0
0
0.076393
0.001378
0
0
0
0
0
1
0.025397
false
0
0.063492
0
0.098413
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
1bb83da1c4ee56bb7f6b29451e7244bad2be8a01
2,740
py
Python
tests/regressiontests/aggregation_regress/tests.py
huicheese/Django-test3
ac11d2dce245b48392e52d1f4acfd5e7433b243e
[ "BSD-3-Clause" ]
null
null
null
tests/regressiontests/aggregation_regress/tests.py
huicheese/Django-test3
ac11d2dce245b48392e52d1f4acfd5e7433b243e
[ "BSD-3-Clause" ]
null
null
null
tests/regressiontests/aggregation_regress/tests.py
huicheese/Django-test3
ac11d2dce245b48392e52d1f4acfd5e7433b243e
[ "BSD-3-Clause" ]
null
null
null
from django.conf import settings from django.test import TestCase from django.db.models import Count, Max from regressiontests.aggregation_regress.models import * class AggregationTests(TestCase): def test_aggregates_in_where_clause(self): """ Regression test for #12822: DatabaseError: aggregate...
38.055556
82
0.626642
356
2,740
4.69382
0.356742
0.020946
0.031119
0.035907
0.399761
0.399761
0.363854
0.363854
0.363854
0.312388
0
0.016427
0.289051
2,740
71
83
38.591549
0.841376
0.364599
0
0.424242
0
0
0.178389
0.049233
0
0
0
0
0.060606
1
0.090909
false
0
0.121212
0
0.242424
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
1bbaf70e6d7277e8e9e2216ee33cc6779be14e8e
3,884
py
Python
Node.py
recep-yildirim/Astar-Algorithm
77936f42fac464d73ef6024ef808a188008801e7
[ "MIT" ]
null
null
null
Node.py
recep-yildirim/Astar-Algorithm
77936f42fac464d73ef6024ef808a188008801e7
[ "MIT" ]
null
null
null
Node.py
recep-yildirim/Astar-Algorithm
77936f42fac464d73ef6024ef808a188008801e7
[ "MIT" ]
null
null
null
class Node () : def __init__ (self , table , index = None) : self.__table = table self.__index = index self.__weight = self.__calculateWeight () self.__left_child = None self.__forward_child = None self.__right_child = None self.__parent = None def getTab...
31.577236
132
0.555098
414
3,884
4.879227
0.125604
0.035644
0.041584
0.071287
0.480198
0.421782
0.412871
0.412871
0.353465
0.242574
0
0.012039
0.337024
3,884
123
133
31.577236
0.772427
0
0
0.193182
0
0
0.010811
0
0
0
0
0
0
1
0.193182
false
0
0
0.068182
0.329545
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
1bbb61f6bb7f5635828fad04e429c28202fefb4b
732
py
Python
http/flask/validation.py
hanwhhanwh/python-test
ac97ae83fc9eac3157ff7dc39d6295bc5b15d589
[ "MIT" ]
null
null
null
http/flask/validation.py
hanwhhanwh/python-test
ac97ae83fc9eac3157ff7dc39d6295bc5b15d589
[ "MIT" ]
null
null
null
http/flask/validation.py
hanwhhanwh/python-test
ac97ae83fc9eac3157ff7dc39d6295bc5b15d589
[ "MIT" ]
null
null
null
from jsonschema import validate # A sample schema, like what we'd get from json.load() schema = { "type" : "object", "properties" : { "price" : {"type" : "number", "minimum": 0, "maximum": 39}, "name" : {"type" : "string"}, }, } # If no exception is raised by validate(), the instance is valid. validate(instanc...
28.153846
72
0.61612
84
732
5.345238
0.595238
0.066815
0.084633
0.111359
0.129176
0
0
0
0
0
0
0.011945
0.199454
732
25
73
29.28
0.754266
0.204918
0
0
0
0
0.26087
0
0
0
0
0
0
1
0
false
0
0.083333
0
0.083333
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
1bc3974da46b2e7222bd0a8f654b8b44516aed96
1,789
py
Python
Python/min-cost-climbing-stairs.py
RideGreg/LeetCode
b70818b1e6947bf29519a24f78816e022ebab59e
[ "MIT" ]
1
2022-01-30T06:55:28.000Z
2022-01-30T06:55:28.000Z
Python/min-cost-climbing-stairs.py
RideGreg/LeetCode
b70818b1e6947bf29519a24f78816e022ebab59e
[ "MIT" ]
null
null
null
Python/min-cost-climbing-stairs.py
RideGreg/LeetCode
b70818b1e6947bf29519a24f78816e022ebab59e
[ "MIT" ]
1
2021-12-31T03:56:39.000Z
2021-12-31T03:56:39.000Z
# Time: O(n) # Space: O(1) # 746 # On a staircase, the i-th step has some non-negative cost cost[i] assigned (0 indexed). # # Once you pay the cost, you can either climb one or two steps. # You need to find minimum cost to reach the top of the floor, # and you can either start from the step with index 0, or the step ...
28.396825
88
0.546115
294
1,789
3.319728
0.343537
0.015369
0.015369
0.032787
0.147541
0.120902
0.055328
0.032787
0.032787
0
0
0.060048
0.301845
1,789
62
89
28.854839
0.721377
0.446059
0
0
0
0
0
0
0
0
0
0
0
1
0.166667
false
0
0
0
0.444444
0.111111
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
1bc4943ecdbf1164bdb164129e61d0599e4b4509
398
py
Python
PyMOTW/source/fnmatch/fnmatch_fnmatch.py
axetang/AxePython
3b517fa3123ce2e939680ad1ae14f7e602d446a6
[ "Apache-2.0" ]
1
2019-01-04T05:47:50.000Z
2019-01-04T05:47:50.000Z
PyMOTW/source/fnmatch/fnmatch_fnmatch.py
axetang/AxePython
3b517fa3123ce2e939680ad1ae14f7e602d446a6
[ "Apache-2.0" ]
1
2020-07-18T03:52:03.000Z
2020-07-18T04:18:01.000Z
PyMOTW/source/fnmatch/fnmatch_fnmatch.py
axetang/AxePython
3b517fa3123ce2e939680ad1ae14f7e602d446a6
[ "Apache-2.0" ]
2
2021-03-06T04:28:32.000Z
2021-03-06T04:59:17.000Z
#!/usr/bin/env python3 # encoding: utf-8 # # Copyright (c) 2008 Doug Hellmann All rights reserved. # """Test an individual filename with a pattern. """ #end_pymotw_header import fnmatch import os pattern = 'fnmatch_*.py' print('Pattern :', pattern) print() files = os.listdir('.') for name in sorted(files): print...
18.952381
55
0.678392
53
398
5.037736
0.716981
0
0
0
0
0
0
0
0
0
0
0.023952
0.160804
398
20
56
19.9
0.775449
0.38191
0
0
0
0
0.175214
0
0
0
0
0
0
1
0
false
0
0.222222
0
0.222222
0.333333
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
1bc877b0af569563991836c407b7a62985a32bd0
3,767
py
Python
evaluation_metrics.py
87ZGitHub/sfd.pytorch
66108ab35d8b1c1601c326b151141d9115a1409e
[ "MIT" ]
124
2018-07-08T14:36:06.000Z
2021-04-08T14:01:20.000Z
evaluation_metrics.py
87ZGitHub/sfd.pytorch
66108ab35d8b1c1601c326b151141d9115a1409e
[ "MIT" ]
21
2018-07-09T07:17:40.000Z
2020-08-11T12:26:13.000Z
evaluation_metrics.py
87ZGitHub/sfd.pytorch
66108ab35d8b1c1601c326b151141d9115a1409e
[ "MIT" ]
25
2018-07-09T04:51:21.000Z
2021-04-06T15:40:45.000Z
import numpy as np from anchor import compute_iou import torch def AP(prediction, gt, iou_threshold): """compute average precision of detection, all the coordinate should be (top left bottom right) Args: predict_bboxes (ndarray): should be a N * (4 + 1 + 1) ndarray N is number of boxe...
36.221154
80
0.622511
519
3,767
4.396917
0.283237
0.062664
0.02454
0.023663
0.088519
0.05872
0.05872
0.032428
0.032428
0
0
0.01686
0.291479
3,767
103
81
36.572816
0.838142
0.361826
0
0
0
0
0
0
0
0
0
0
0
1
0.037037
false
0
0.055556
0
0.12963
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
1bcaf2077f60c60393a9163a728dc944be68b9aa
4,151
py
Python
ml_src/utils.py
JaredDobry/imdb_scraper
70056e8bbed49470fa6cbb42e930c95c437bdee3
[ "MIT" ]
null
null
null
ml_src/utils.py
JaredDobry/imdb_scraper
70056e8bbed49470fa6cbb42e930c95c437bdee3
[ "MIT" ]
2
2021-11-17T22:43:26.000Z
2021-11-17T22:43:38.000Z
ml_src/utils.py
JaredDobry/imdb_scraper
70056e8bbed49470fa6cbb42e930c95c437bdee3
[ "MIT" ]
null
null
null
import random import pickle import pathlib import numpy as np import pandas as pd from json import loads from os.path import exists from typing import Any, Dict, List, Tuple from metrics import Category, Feature def unpickle_file(file: pathlib.Path) -> Any: abs_path = str(file) if not abs_path.endswith(".pick...
33.208
111
0.631414
590
4,151
4.286441
0.315254
0.052195
0.019771
0.020166
0.080664
0.051404
0.051404
0.051404
0.035587
0
0
0.010859
0.267887
4,151
124
112
33.475806
0.821323
0.14093
0
0.090909
0
0.011364
0.075949
0.009564
0
0
0
0
0.011364
1
0.102273
false
0
0.102273
0.022727
0.306818
0.011364
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
1bcb75a52c153491e5a8fa2aab5c85e45ee3a1cd
1,564
py
Python
desertbot/modules/commands/Gif.py
Helle-Daryd/DesertBot
0b497db135a4c08dfbdb59108f830ba12fdc6465
[ "MIT", "BSD-3-Clause" ]
7
2018-03-20T17:10:10.000Z
2021-11-17T18:58:04.000Z
desertbot/modules/commands/Gif.py
Helle-Daryd/DesertBot
0b497db135a4c08dfbdb59108f830ba12fdc6465
[ "MIT", "BSD-3-Clause" ]
109
2015-08-20T13:16:35.000Z
2022-01-21T19:40:35.000Z
desertbot/modules/commands/Gif.py
Helle-Daryd/DesertBot
0b497db135a4c08dfbdb59108f830ba12fdc6465
[ "MIT", "BSD-3-Clause" ]
7
2018-03-29T05:55:01.000Z
2021-02-05T19:19:39.000Z
""" Created on Dec 05, 2013 @author: StarlitGhost """ import random from twisted.plugin import IPlugin from zope.interface import implementer from desertbot.message import IRCMessage from desertbot.moduleinterface import IModule from desertbot.modules.commandinterface import BotCommand from desertbot.response import...
28.436364
85
0.621483
170
1,564
5.717647
0.488235
0.053498
0.08642
0.05144
0.131687
0
0
0
0
0
0
0.014134
0.276215
1,564
54
86
28.962963
0.844523
0.029412
0
0.114286
0
0
0.125166
0
0
0
0
0
0
1
0.085714
false
0
0.2
0.057143
0.457143
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
1bcbc87a25327faeab5c975e6b8196f74250bcaa
9,457
py
Python
datalad/distribution/drop.py
psychoinformatics-de/datalad
7435edc1d3c73ae2254fa4bfcb8412a8de6d8d4c
[ "MIT" ]
298
2015-01-25T17:36:29.000Z
2022-03-20T03:38:47.000Z
datalad/distribution/drop.py
psychoinformatics-de/datalad
7435edc1d3c73ae2254fa4bfcb8412a8de6d8d4c
[ "MIT" ]
6,387
2015-01-02T18:15:01.000Z
2022-03-31T20:58:58.000Z
datalad/distribution/drop.py
psychoinformatics-de/datalad
7435edc1d3c73ae2254fa4bfcb8412a8de6d8d4c
[ "MIT" ]
109
2015-01-25T17:49:40.000Z
2022-03-06T06:54:54.000Z
# emacs: -*- mode: python; py-indent-offset: 4; tab-width: 4; indent-tabs-mode: nil -*- # ex: set sts=4 ts=4 sw=4 noet: # ## ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ### ## # # See COPYING file distributed along with the datalad package for the # copyright and license terms. # # ## ### ##...
33.775
91
0.592577
1,112
9,457
4.910971
0.311151
0.020143
0.019227
0.013184
0.058231
0.058231
0.049441
0.032961
0.032961
0.032961
0
0.001067
0.306122
9,457
279
92
33.896057
0.831149
0.232315
0
0.087179
0
0
0.183312
0.007573
0
0
0
0.003584
0
1
0.015385
false
0
0.061538
0
0.112821
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
1bcc04e91758981f791ffbb36211c7f01c585bd9
13,552
py
Python
music-dl.py
SyTemossy/music-dl
ada8ecc92e85e5fbe5936684915bf4fe1bab5583
[ "MIT" ]
null
null
null
music-dl.py
SyTemossy/music-dl
ada8ecc92e85e5fbe5936684915bf4fe1bab5583
[ "MIT" ]
null
null
null
music-dl.py
SyTemossy/music-dl
ada8ecc92e85e5fbe5936684915bf4fe1bab5583
[ "MIT" ]
null
null
null
import argparse import sys import os import urllib import requests import json import random commands = [] path = sys.path[0] dpath = sys.path[0] autocreate = False netease_api = { 'music_url': 'http://music.163.com/song/media/outer/url?id=', 'playlist': 'https://api.surmon.me/music/list/', ...
37.333333
396
0.516824
1,566
13,552
4.408685
0.227969
0.008691
0.013036
0.01825
0.343424
0.280852
0.228418
0.187283
0.132242
0.123841
0
0.058596
0.331316
13,552
362
397
37.436464
0.703266
0.011954
0
0.304878
0
0.036585
0.254973
0.016205
0
0
0
0
0
1
0.04878
false
0.033537
0.02439
0
0.137195
0.057927
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
1bcc76036f4adee6ab1ac6897a215f0d51bec9a3
4,604
py
Python
python/federatedml/param/data_split_param.py
hubert-he/FATE
6758e150bd7ca7d6f788f9a7a8c8aea7e6500363
[ "Apache-2.0" ]
3,787
2019-08-30T04:55:10.000Z
2022-03-31T23:30:07.000Z
python/federatedml/param/data_split_param.py
hubert-he/FATE
6758e150bd7ca7d6f788f9a7a8c8aea7e6500363
[ "Apache-2.0" ]
1,439
2019-08-29T16:35:52.000Z
2022-03-31T11:55:31.000Z
python/federatedml/param/data_split_param.py
hubert-he/FATE
6758e150bd7ca7d6f788f9a7a8c8aea7e6500363
[ "Apache-2.0" ]
1,179
2019-08-29T16:18:32.000Z
2022-03-31T12:55:38.000Z
#!/usr/bin/env python # -*- coding: utf-8 -*- # # Copyright 2019 The FATE Authors. 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/lic...
43.028037
112
0.691138
636
4,604
4.831761
0.253145
0.042304
0.063456
0.06248
0.352424
0.323462
0.267491
0.215099
0.215099
0.143508
0
0.00795
0.235013
4,604
106
113
43.433962
0.864566
0.400521
0
0
0
0
0.177028
0
0
0
0
0
0
1
0.045455
false
0
0.045455
0
0.136364
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
1bd10a1e1d8c38d5a012608be42f9224c3b3f533
6,258
py
Python
reid/trainers.py
xueping187/weakly-supervised-person-re-id
3cfe98264dcdb667c132727a57ab80da5a9e6a8f
[ "Apache-2.0" ]
2
2021-09-14T03:39:43.000Z
2021-09-14T03:41:04.000Z
reid/trainers.py
xueping187/weakly-supervised-person-re-id
3cfe98264dcdb667c132727a57ab80da5a9e6a8f
[ "Apache-2.0" ]
null
null
null
reid/trainers.py
xueping187/weakly-supervised-person-re-id
3cfe98264dcdb667c132727a57ab80da5a9e6a8f
[ "Apache-2.0" ]
null
null
null
from __future__ import print_function, absolute_import import time import torch from torch.autograd import Variable import torch.nn.functional as F import numpy as np #from .evaluation_metrics import accuracy from .utils.meters import AverageMeter def MIL(element_logits, seq_len, batch_size, labels): ''' elemen...
42.283784
143
0.592681
871
6,258
4.123995
0.221584
0.033408
0.017539
0.01559
0.2951
0.244154
0.222439
0.193207
0.161192
0.142261
0
0.03151
0.269735
6,258
147
144
42.571429
0.754486
0.171461
0
0.079208
0
0
0.02054
0
0
0
0
0
0.009901
1
0.079208
false
0
0.069307
0
0.207921
0.039604
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
1bd1b91cc7621a6826da68a2e74632538595b5f6
6,618
py
Python
basicsr/models/basicvsr_model.py
IanYeung/ReCp
1a7ace0e1ca3c262e24a222f3f0ab0d5674e9410
[ "Apache-2.0", "MIT" ]
null
null
null
basicsr/models/basicvsr_model.py
IanYeung/ReCp
1a7ace0e1ca3c262e24a222f3f0ab0d5674e9410
[ "Apache-2.0", "MIT" ]
null
null
null
basicsr/models/basicvsr_model.py
IanYeung/ReCp
1a7ace0e1ca3c262e24a222f3f0ab0d5674e9410
[ "Apache-2.0", "MIT" ]
null
null
null
import logging from copy import deepcopy import os.path as osp from tqdm import tqdm import torch from torch.nn.parallel import DistributedDataParallel from basicsr.models.video_base_model import VideoBaseModel from basicsr.utils import imwrite, tensor2img from basicsr.utils.dist_util import get_dist_info from basicsr....
39.628743
80
0.531581
742
6,618
4.520216
0.256065
0.022958
0.014311
0.016696
0.16607
0.15653
0.128205
0.10316
0.10316
0.039952
0
0.006204
0.366727
6,618
166
81
39.86747
0.794083
0.048202
0
0.102941
0
0
0.076972
0.009402
0
0
0
0
0.007353
1
0.044118
false
0
0.080882
0
0.139706
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
1bd2c291602bab4b785fdad8e90b37c866fe0baa
28,100
py
Python
service/doc_etl.py
wisebobo/doc_ocr_by_template
299601c9c5275cf6ad1bbdca071060df5ede0c7b
[ "MIT" ]
6
2019-11-29T10:10:58.000Z
2022-01-29T07:01:48.000Z
service/doc_etl.py
wisebobo/doc_ocr_by_template
299601c9c5275cf6ad1bbdca071060df5ede0c7b
[ "MIT" ]
7
2019-12-17T05:14:17.000Z
2022-02-10T01:08:50.000Z
service/doc_etl.py
wisebobo/doc_ocr_by_template
299601c9c5275cf6ad1bbdca071060df5ede0c7b
[ "MIT" ]
3
2019-12-17T09:44:28.000Z
2022-01-12T09:54:00.000Z
# -*- coding:utf-8 -*- import re, sys import time, logging from collections import OrderedDict from util.MRZ import MRZ, MRZOCRCleaner from util.ctc2hanzi import ctc_code from util.name2pinyin import ChineseName from util.CHN_ID_Verify import CHNIdNumber from util.log import logging_elapsed_time class doc_etl(object)...
38.545953
134
0.478221
3,147
28,100
4.004131
0.104862
0.037854
0.022697
0.013412
0.481152
0.409967
0.336243
0.263868
0.239981
0.222601
0
0.028856
0.382135
28,100
728
135
38.598901
0.696694
0.022811
0
0.283582
0
0.003731
0.102499
0.001386
0
0
0
0
0
1
0.031716
false
0.007463
0.014925
0.001866
0.089552
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
1bd3506d46da04e4e4dbb22df73bd65177767e36
4,238
py
Python
MidControl.py
qchen59/CSC520_Pente_AI
fa2c3c530ccd59f442c4e448787ef066165a4906
[ "Apache-2.0" ]
null
null
null
MidControl.py
qchen59/CSC520_Pente_AI
fa2c3c530ccd59f442c4e448787ef066165a4906
[ "Apache-2.0" ]
1
2022-03-31T23:06:59.000Z
2022-03-31T23:06:59.000Z
MidControl.py
qchen59/CSC520_Pente_AI
fa2c3c530ccd59f442c4e448787ef066165a4906
[ "Apache-2.0" ]
1
2022-03-31T22:07:46.000Z
2022-03-31T22:07:46.000Z
import ConsecutivePieces as Cp import math import copy def mid_control_streaks(board, turn): """ Uses the 'calculate_streaks' method to work out the heuristic values. Then the heuristic values of the pieces that are in the middle 5x5 area of the board is doubled. This will bump up the final score as well....
47.088889
120
0.522888
606
4,238
3.646865
0.176568
0.027149
0.032579
0.031674
0.560181
0.514932
0.514932
0.486878
0.486878
0.486878
0
0.038462
0.380368
4,238
89
121
47.617978
0.803123
0.337659
0
0.563636
0
0
0
0
0
0
0
0
0
1
0.036364
false
0
0.054545
0
0.145455
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
1bd438755efdfb68b94d3ed6b17ddefd4e151daa
1,237
py
Python
mpi/python/intercomm.py
tyohei/examples
38652f48aca2b668bcc116ba401795d4be2f8f18
[ "MIT" ]
1
2020-09-14T17:29:02.000Z
2020-09-14T17:29:02.000Z
mpi/python/intercomm.py
tyohei/examples
38652f48aca2b668bcc116ba401795d4be2f8f18
[ "MIT" ]
8
2020-09-05T10:19:39.000Z
2021-05-07T10:04:27.000Z
mpi/python/intercomm.py
tyohei/examples
38652f48aca2b668bcc116ba401795d4be2f8f18
[ "MIT" ]
null
null
null
from mpi4py import MPI import common def main(): comm = MPI.COMM_WORLD print_mpi = common.create_print_mpi(comm) print_mpi('Hello World!') if comm.rank == 0 or comm.rank == 1: intracomm = comm.Split(color=0, key=comm.rank) else: intracomm = comm.Split(color=1, key=comm.rank) ...
27.488889
76
0.579628
160
1,237
4.26875
0.25625
0.093704
0.070278
0.048316
0.193265
0.193265
0.193265
0.108346
0.076135
0
0
0.020047
0.31447
1,237
44
77
28.113636
0.785377
0.065481
0
0.1875
0
0
0.064292
0
0
0
0
0
0
1
0.03125
false
0
0.0625
0
0.09375
0.15625
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
1bd6be2fc7c5b1b45e6116789f9a3be537751a34
6,970
py
Python
data/gta5_dataset.py
Jo-wang/ProDA
58910b1fe2bdbf79d0e12708b77b6df4f386bb49
[ "MIT" ]
193
2021-03-25T07:29:56.000Z
2022-03-30T08:56:44.000Z
caco_proda_finetune/data/gta5_dataset.py
jxhuang0508/CaCo
0106d93fd6277ca843572a6aa01bdf2d1caca117
[ "MIT" ]
43
2021-04-13T02:13:18.000Z
2022-03-31T11:14:58.000Z
caco_proda_finetune/data/gta5_dataset.py
jxhuang0508/CaCo
0106d93fd6277ca843572a6aa01bdf2d1caca117
[ "MIT" ]
35
2021-03-26T09:29:58.000Z
2022-01-20T17:40:08.000Z
# Copyright (c) Microsoft Corporation. # Licensed under the MIT License. import os import sys import torch import numpy as np import scipy.misc as m import matplotlib.pyplot as plt import matplotlib.image as imgs from PIL import Image import random import scipy.io as io from tqdm import tqdm from scipy import stats ...
34.50495
114
0.545194
915
6,970
4.039344
0.310383
0.006494
0.005682
0.026515
0.143939
0.120671
0.102814
0.074134
0.055195
0.036797
0
0.09403
0.31033
6,970
201
115
34.676617
0.674849
0.106456
0
0
0
0
0.068067
0
0
0
0
0.00995
0
1
0.047945
false
0
0.10274
0.006849
0.212329
0.020548
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
1bd8344c5079ad7625f96055dc71a256fa657bdc
14,857
py
Python
neural-net/neural-net.py
MrTeuthis/traffic-toronto
9bf33ddc437ec138e78539f35260ec46761f0fd2
[ "MIT" ]
null
null
null
neural-net/neural-net.py
MrTeuthis/traffic-toronto
9bf33ddc437ec138e78539f35260ec46761f0fd2
[ "MIT" ]
null
null
null
neural-net/neural-net.py
MrTeuthis/traffic-toronto
9bf33ddc437ec138e78539f35260ec46761f0fd2
[ "MIT" ]
null
null
null
import tensorflow as tf import random as rand import numpy as np import pickle import random import argparse import pprint from mpl_toolkits.mplot3d import Axes3D import matplotlib.pyplot as plt from matplotlib import cm from matplotlib.ticker import LinearLocator, FormatStrFormatter from matplotlib.animation import Fu...
39.938172
179
0.622871
2,134
14,857
4.215558
0.142455
0.032681
0.050022
0.075033
0.635394
0.581036
0.514896
0.495665
0.483659
0.45309
0
0.027055
0.2238
14,857
371
180
40.045822
0.753035
0.073299
0
0.489796
0
0
0.106778
0.003571
0
0
0
0
0
1
0.010204
false
0
0.044218
0.006803
0.064626
0.112245
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
1bd84f91db30e70500d6e6134cbbca69df24cc6b
4,175
py
Python
tests/torch_api/test_process_group.py
woqidaideshi/bagua
0ee96da598685748519d58d24ce983499cb36721
[ "MIT" ]
635
2021-06-11T03:03:11.000Z
2022-03-31T14:52:57.000Z
tests/torch_api/test_process_group.py
zhjc/bagua
eeaa2bf8950248a2e72ce2e471bbf08cb3b8b985
[ "MIT" ]
181
2021-06-10T12:27:19.000Z
2022-03-31T04:08:19.000Z
tests/torch_api/test_process_group.py
shjwudp/bagua
7e1b438e27e3119b23e472f5b9217a9862932bef
[ "MIT" ]
71
2021-06-10T13:16:53.000Z
2022-03-22T09:26:22.000Z
import os import unittest import torch import torch.distributed as c10d import bagua.torch_api as bagua from tests.internal.common_utils import find_free_port from tests.internal.multi_process import MultiProcessTestCase, setup_bagua_env from tests import skip_if_cuda_not_available class Result(object): def __i...
32.617188
87
0.661796
564
4,175
4.583333
0.244681
0.043327
0.040619
0.026306
0.426306
0.348162
0.238685
0.138878
0.138878
0.138878
0
0.024329
0.232096
4,175
127
88
32.874016
0.781971
0.067545
0
0.16129
0
0
0.043243
0.01287
0
0
0
0
0.075269
1
0.075269
false
0
0.096774
0
0.204301
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
1bd948d6210c3b20eae27d41f0ad6a8b33ca0641
1,209
py
Python
laskarit/viikko2/unicafe/src/kassapaate.py
miikara/landlord
1f9a2ae2485adb8837a9b1d0668cc0708aec4d5f
[ "MIT" ]
1
2021-05-16T22:41:55.000Z
2021-05-16T22:41:55.000Z
laskarit/viikko2/unicafe/src/kassapaate.py
miikara/landlord
1f9a2ae2485adb8837a9b1d0668cc0708aec4d5f
[ "MIT" ]
null
null
null
laskarit/viikko2/unicafe/src/kassapaate.py
miikara/landlord
1f9a2ae2485adb8837a9b1d0668cc0708aec4d5f
[ "MIT" ]
null
null
null
class Kassapaate: def __init__(self): self.kassassa_rahaa = 100000 self.edulliset = 0 self.maukkaat = 0 def syo_edullisesti_kateisella(self, maksu): if maksu >= 240: self.kassassa_rahaa = self.kassassa_rahaa + 240 self.edulliset += 1 return ma...
26.866667
59
0.544251
129
1,209
4.922481
0.24031
0.113386
0.16063
0.066142
0.579528
0.431496
0.091339
0
0
0
0
0.057718
0.383788
1,209
44
60
27.477273
0.794631
0
0
0.384615
0
0
0
0
0
0
0
0
0
1
0.153846
false
0
0
0
0.410256
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
1bdb8ff2ab04650c354ff55f8bfdaf2310b0c2ee
4,135
py
Python
multiuploader/utils.py
dicos/django-multiuploader
5fc7c782486bfab367e372b90efadb9c61e6e257
[ "MIT" ]
null
null
null
multiuploader/utils.py
dicos/django-multiuploader
5fc7c782486bfab367e372b90efadb9c61e6e257
[ "MIT" ]
null
null
null
multiuploader/utils.py
dicos/django-multiuploader
5fc7c782486bfab367e372b90efadb9c61e6e257
[ "MIT" ]
null
null
null
import os import time import urllib import logging import mimetypes from hashlib import sha1 from random import choice from wsgiref.util import FileWrapper from django.conf import settings from django.core.files import File from django.http import HttpResponse, StreamingHttpResponse from django.utils.tim...
32.559055
103
0.648126
502
4,135
5.23506
0.388446
0.022831
0.01484
0.019406
0.060122
0.060122
0.040335
0.040335
0.040335
0.040335
0
0.01216
0.244256
4,135
126
104
32.81746
0.8288
0.159613
0
0.076923
0
0
0.10217
0.028632
0
0
0
0
0
1
0.102564
false
0
0.205128
0.012821
0.435897
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
59ef80c6d5b9db80f94f7e583695d33684b37cea
672
py
Python
students/K33402/Barabanov Denis/lr1/task2/server.py
dEbAR38/ITMO_ICT_WebDevelopment_2020-2021
208cbc6d2b6d40c3043d35ce773a3433b377f671
[ "MIT" ]
null
null
null
students/K33402/Barabanov Denis/lr1/task2/server.py
dEbAR38/ITMO_ICT_WebDevelopment_2020-2021
208cbc6d2b6d40c3043d35ce773a3433b377f671
[ "MIT" ]
null
null
null
students/K33402/Barabanov Denis/lr1/task2/server.py
dEbAR38/ITMO_ICT_WebDevelopment_2020-2021
208cbc6d2b6d40c3043d35ce773a3433b377f671
[ "MIT" ]
null
null
null
import socket sock = socket.socket() sock.bind(('', 9090)) sock.listen(1) conn, addr = sock.accept() print(conn) while True: data = conn.recv(1024) data = str(data.decode()) print(data) if not data=='pifagor': conn.send('Такой задачи нет'.encode()) break else: conn.send('вве...
24.888889
63
0.541667
88
672
4.136364
0.511364
0.087912
0.065934
0.087912
0.181319
0.181319
0.181319
0.181319
0
0
0
0.03527
0.282738
672
27
64
24.888889
0.719917
0
0
0.16
0
0
0.139673
0
0
0
0
0
0
1
0
false
0
0.04
0
0.04
0.08
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
59f050a0b633204f5e3438dac473652fa6b25572
12,025
py
Python
src/striemann/tests/test_striemann.py
madedotcom/striemann
fc6089bc5f1b96118ffe6474594798763d19c050
[ "MIT" ]
null
null
null
src/striemann/tests/test_striemann.py
madedotcom/striemann
fc6089bc5f1b96118ffe6474594798763d19c050
[ "MIT" ]
16
2018-05-29T14:52:57.000Z
2020-05-14T12:33:32.000Z
src/striemann/tests/test_striemann.py
madedotcom/striemann
fc6089bc5f1b96118ffe6474594798763d19c050
[ "MIT" ]
null
null
null
from expects import expect from icdiff_expects import equal from unittest import mock import striemann.metrics import json class Test: def test_gauges(self): transport = striemann.metrics.InMemoryTransport() metrics = striemann.metrics.Metrics(transport, source="test") metrics.recordGauge(...
30.0625
86
0.490728
1,067
12,025
5.412371
0.147142
0.063723
0.04329
0.041558
0.695065
0.65974
0.625628
0.594978
0.50632
0.487273
0
0.007111
0.380208
12,025
399
87
30.137845
0.767745
0.004241
0
0.589124
0
0
0.138573
0
0
0
0
0
0.060423
1
0.063444
false
0.021148
0.015106
0
0.096677
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
59f073559061a5de8a0cd772dadf4560b56bd0fb
5,128
py
Python
paper/figures/HD189733/viz.py
j-faria/wobble
041cd58fa8fb87bb5b41ee23bd1ea716bab7051b
[ "MIT" ]
38
2016-06-03T13:15:49.000Z
2021-12-01T00:02:11.000Z
paper/figures/HD189733/viz.py
j-faria/wobble
041cd58fa8fb87bb5b41ee23bd1ea716bab7051b
[ "MIT" ]
63
2016-09-17T13:38:16.000Z
2021-02-05T16:27:10.000Z
paper/figures/HD189733/viz.py
j-faria/wobble
041cd58fa8fb87bb5b41ee23bd1ea716bab7051b
[ "MIT" ]
17
2017-05-04T03:03:16.000Z
2022-01-10T17:56:43.000Z
from ipywidgets import interact, interactive, fixed, interact_manual import ipywidgets as widgets from ipywidgets import Layout import starry from ylm_rot import get_ylm_coeffs import matplotlib.pyplot as pl import numpy as np vslider = \ widgets.FloatSlider( value=0.1, min=0.1, max=10.0, step=0.01, ...
25.89899
88
0.608034
766
5,128
3.972585
0.25718
0.06211
0.020703
0.076241
0.425896
0.388432
0.351298
0.320407
0.309234
0.301019
0
0.064712
0.228549
5,128
198
89
25.89899
0.704499
0.058892
0
0.431953
0
0
0.085168
0
0
0
0
0
0
1
0.011834
false
0
0.04142
0.005917
0.059172
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
59f0dcccc30e5c47e03c3762b37daf71a44fb738
14,101
py
Python
tests/test_simple.py
FFY00/mousebender
df0b7f7408c952ea8d124ab2c8c9b8c24ea77d06
[ "BSD-3-Clause" ]
21
2020-04-10T03:53:44.000Z
2022-01-12T08:31:56.000Z
tests/test_simple.py
FFY00/mousebender
df0b7f7408c952ea8d124ab2c8c9b8c24ea77d06
[ "BSD-3-Clause" ]
34
2020-04-10T19:56:29.000Z
2022-01-27T22:10:22.000Z
tests/test_simple.py
sthagen/mousebender
849844440f024adb9efe19c4774bae1ed45335f6
[ "BSD-3-Clause" ]
8
2020-04-10T03:09:00.000Z
2021-11-04T11:17:38.000Z
"""Tests for mousebender.simple.""" import warnings import importlib_resources import packaging.version import pytest from mousebender import simple from .data import simple as simple_data class TestProjectURLConstruction: """Tests for mousebender.simple.create_project_url().""" @pytest.mark.parametrize(...
37.403183
346
0.556344
1,499
14,101
5.070047
0.140093
0.050526
0.037632
0.016842
0.613026
0.545263
0.494079
0.481184
0.438421
0.388684
0
0.115761
0.312035
14,101
376
347
37.50266
0.667663
0.022906
0
0.432927
0
0.064024
0.388497
0.184978
0
0
0
0
0.091463
1
0.073171
false
0
0.02439
0.003049
0.112805
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
59f5273b29007b20b07871db2635217e7e4a6330
1,743
py
Python
danceschool/register/forms.py
django-danceschool/django-danceschool
65ae09ffdcb0821e82df0e1f634fe13c0384a525
[ "BSD-3-Clause" ]
32
2017-09-12T04:25:25.000Z
2022-03-21T10:48:07.000Z
danceschool/register/forms.py
django-danceschool/django-danceschool
65ae09ffdcb0821e82df0e1f634fe13c0384a525
[ "BSD-3-Clause" ]
97
2017-09-01T02:43:08.000Z
2022-01-03T18:20:34.000Z
danceschool/register/forms.py
django-danceschool/django-danceschool
65ae09ffdcb0821e82df0e1f634fe13c0384a525
[ "BSD-3-Clause" ]
19
2017-09-26T13:34:46.000Z
2022-03-21T10:48:10.000Z
from django import forms from django.utils.translation import gettext_lazy as _ from django.db.models import F from dal import autocomplete from danceschool.core.models import Customer class CustomerGuestAutocompleteForm(forms.Form): ''' This form can be used to search for customers and names on the guest ...
35.571429
79
0.583477
181
1,743
5.546961
0.618785
0.02988
0.021912
0.027888
0
0
0
0
0
0
0
0.003416
0.32817
1,743
48
80
36.3125
0.853971
0.277108
0
0
0
0
0.135332
0.020259
0
0
0
0
0
1
0.034483
false
0
0.172414
0
0.241379
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
59f6a0718d51a789e27b2f717d206af701b1445f
3,093
py
Python
SIR_functions.py
TheNewExecutor/CoronaVirus
779cd9f8338ce3b9f2a0383a5a526e694c65e3ee
[ "MIT" ]
null
null
null
SIR_functions.py
TheNewExecutor/CoronaVirus
779cd9f8338ce3b9f2a0383a5a526e694c65e3ee
[ "MIT" ]
null
null
null
SIR_functions.py
TheNewExecutor/CoronaVirus
779cd9f8338ce3b9f2a0383a5a526e694c65e3ee
[ "MIT" ]
null
null
null
from scipy.integrate import solve_ivp import numpy as np import matplotlib.pyplot as plt from sklearn.metrics import mean_squared_error from hyperopt import hp, fmin, tpe from typing import Tuple def SIR(t, y, N, kappa, tau, nu): """ Expresses SIR model in initial value ODE format, including time, ...
28.118182
87
0.590365
412
3,093
4.371359
0.383495
0.026652
0.008329
0.018323
0
0
0
0
0
0
0
0.01012
0.297123
3,093
109
88
28.376147
0.818307
0.436793
0
0
0
0
0.035162
0
0
0
0
0
0
1
0.131579
false
0
0.157895
0
0.394737
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
59f93eebbd7e541b8c3908f89c9876035051096e
854
py
Python
src/lcm_zmq_integration/xserver.py
bthcode/cmake_scipy_ctypes_example
64a7afdd825f0bb6a50cb174f4ced231b3017c8d
[ "BSD-3-Clause" ]
null
null
null
src/lcm_zmq_integration/xserver.py
bthcode/cmake_scipy_ctypes_example
64a7afdd825f0bb6a50cb174f4ced231b3017c8d
[ "BSD-3-Clause" ]
null
null
null
src/lcm_zmq_integration/xserver.py
bthcode/cmake_scipy_ctypes_example
64a7afdd825f0bb6a50cb174f4ced231b3017c8d
[ "BSD-3-Clause" ]
null
null
null
#!/usr/bin/env python """ Example Script to show LCM serialized data transported on by very simple ZeroMQ pub/sub message server/client """ import zmq from example_lcm import image_t import time # # Set up a simple ZMQ publisher # - socket type is zmq.PUB, meaning fire and forget publisher # - socket connection...
20.333333
63
0.625293
135
854
3.933333
0.533333
0.022599
0
0
0
0
0
0
0
0
0
0.036107
0.254098
854
41
64
20.829268
0.797488
0.41452
0
0
0
0
0.03719
0
0
0
0
0
0
1
0
false
0
0.15
0
0.15
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
59f95b02645ef93d80f48dd3f5a6fd77148ddf83
6,799
py
Python
python/misc/dataFrameToDatabase/dataFrameToDatabase.py
jlucas-esri/Geospatial-Center-Code
a8a1c7028d254690af788cbdd9cbdf859a422413
[ "Apache-2.0" ]
14
2020-09-22T22:11:35.000Z
2022-02-05T07:50:06.000Z
python/misc/dataFrameToDatabase/dataFrameToDatabase.py
jlucas-esri/Geospatial-Center-Code
a8a1c7028d254690af788cbdd9cbdf859a422413
[ "Apache-2.0" ]
2
2020-09-23T15:14:40.000Z
2021-08-24T15:04:11.000Z
python/misc/dataFrameToDatabase/dataFrameToDatabase.py
apfister/Geospatial-Center
a8a1c7028d254690af788cbdd9cbdf859a422413
[ "Apache-2.0" ]
6
2020-11-20T17:22:30.000Z
2021-11-12T13:22:20.000Z
import logging import time import pandas as pd from pandas.errors import EmptyDataError import sqlalchemy from typing import Union, List class DataFrameToDatabase: def __init__(self, df:Union[pd.DataFrame, pd.io.parsers.TextFileReader], dbTableName:str, driver:str, ...
36.358289
117
0.508016
644
6,799
5.212733
0.240683
0.047662
0.041704
0.011618
0.263628
0.257671
0.227882
0.177242
0.177242
0.177242
0
0.000499
0.410943
6,799
186
118
36.553763
0.837703
0.123695
0
0.266129
0
0
0.090506
0
0
0
0
0
0
1
0.040323
false
0.040323
0.048387
0
0.112903
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
59fa8411dfa74bbeb8be27d4bcf88306bb7fbf17
5,508
py
Python
pdfstream/servers/xpd_server.py
st3107/pdfstream
6e1829d889e5f5400386513efe993ad0596da8a5
[ "BSD-3-Clause" ]
null
null
null
pdfstream/servers/xpd_server.py
st3107/pdfstream
6e1829d889e5f5400386513efe993ad0596da8a5
[ "BSD-3-Clause" ]
34
2020-07-08T16:24:52.000Z
2020-11-21T17:55:13.000Z
pdfstream/servers/xpd_server.py
st3107/pdfstream
6e1829d889e5f5400386513efe993ad0596da8a5
[ "BSD-3-Clause" ]
1
2020-10-05T14:51:32.000Z
2020-10-05T14:51:32.000Z
"""The analysis server. Process raw image to PDF.""" import typing as tp import databroker from bluesky.callbacks.zmq import Publisher from databroker.v2 import Broker from event_model import RunRouter from ophyd.sim import NumpySeqHandler from pdfstream.callbacks.analysis import AnalysisConfig, VisConfig, ExportConf...
35.535484
112
0.642157
641
5,508
5.340094
0.291732
0.01636
0.01636
0.016652
0.056091
0.02454
0.02454
0.02454
0
0
0
0.00073
0.253813
5,508
154
113
35.766234
0.832117
0.157771
0
0.154545
0
0.009091
0.098598
0
0
0
0
0
0
1
0.090909
false
0.018182
0.1
0.009091
0.309091
0.009091
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
59fadeeb36901e3065564a09daa8450d35a9d7e8
2,965
py
Python
src/tests/snn/test_snn.py
ibm-research-tokyo/diffsnn
9299fc5e8542c6fde33a287f81e7ae3682b2fd9d
[ "Apache-2.0" ]
20
2021-06-01T02:42:43.000Z
2022-02-14T07:08:34.000Z
src/tests/snn/test_snn.py
ibm-research-tokyo/diffsnn
9299fc5e8542c6fde33a287f81e7ae3682b2fd9d
[ "Apache-2.0" ]
null
null
null
src/tests/snn/test_snn.py
ibm-research-tokyo/diffsnn
9299fc5e8542c6fde33a287f81e7ae3682b2fd9d
[ "Apache-2.0" ]
null
null
null
#!/usr/bin/env python # -*- coding: utf-8 -*- ''' Title ''' __author__ = 'Hiroshi Kajino <KAJINO@jp.ibm.com>' __copyright__ = 'Copyright IBM Corp. 2020, 2021' from copy import deepcopy import unittest import torch from diffsnn.pp.snn import FullyObsSigmoidSNN from .base import (TestBase, GenFullyOb...
31.542553
95
0.568971
293
2,965
5.617747
0.324232
0.066829
0.087485
0.054678
0.555893
0.53706
0.465371
0.352369
0.292831
0.26367
0
0.019841
0.320067
2,965
93
96
31.88172
0.796627
0.084317
0
0.546875
0
0
0.093587
0.00783
0
0
0
0
0.046875
1
0.109375
false
0
0.078125
0
0.25
0.09375
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
9401e5967de0c4feb25f57d65b0bb881a0b235ab
12,940
py
Python
tacker/sol_refactored/controller/vnflcm_view.py
h1r0mu/tacker
8c69dda51fcfe215c4878a86b82018d2b96e5561
[ "Apache-2.0" ]
116
2015-10-18T02:57:08.000Z
2022-03-15T04:09:18.000Z
tacker/sol_refactored/controller/vnflcm_view.py
h1r0mu/tacker
8c69dda51fcfe215c4878a86b82018d2b96e5561
[ "Apache-2.0" ]
6
2016-11-07T22:15:54.000Z
2021-05-09T06:13:08.000Z
tacker/sol_refactored/controller/vnflcm_view.py
h1r0mu/tacker
8c69dda51fcfe215c4878a86b82018d2b96e5561
[ "Apache-2.0" ]
166
2015-10-20T15:31:52.000Z
2021-11-12T08:39:49.000Z
# Copyright (C) 2021 Nippon Telegraph and Telephone Corporation # 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/LICE...
35.258856
79
0.55
1,522
12,940
4.551905
0.193167
0.030312
0.016888
0.018476
0.356813
0.318274
0.269342
0.239752
0.205398
0.149394
0
0.009431
0.352628
12,940
366
80
35.355191
0.817596
0.1051
0
0.29927
0
0
0.066025
0.004072
0
0
0
0.002732
0
1
0.127737
false
0.018248
0.032847
0.058394
0.346715
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
940225d04a3a801bd3feb67c187f2cbc8efcab81
2,059
py
Python
project-metrics/metrics_service/apis/codecov.py
rsimha/amp-github-apps
140652c6538e9fc3c3870b12f777c3cba14bf098
[ "Apache-2.0" ]
36
2019-02-07T03:43:54.000Z
2022-03-04T12:55:02.000Z
project-metrics/metrics_service/apis/codecov.py
rsimha/amp-github-apps
140652c6538e9fc3c3870b12f777c3cba14bf098
[ "Apache-2.0" ]
450
2018-11-21T22:36:39.000Z
2022-01-26T18:40:49.000Z
project-metrics/metrics_service/apis/codecov.py
rsimha/amp-github-apps
140652c6538e9fc3c3870b12f777c3cba14bf098
[ "Apache-2.0" ]
42
2018-11-21T22:31:11.000Z
2022-03-08T06:46:20.000Z
"""Module for fetching code coverage info from Codecov.""" from agithub import base as agithub_base from flask_api import status import logging from typing import Any, Dict, Optional, Text import env class CodecovApiError(Exception): """Errors encountered while querying the Codecov API.""" def __init__(self, s...
30.731343
79
0.684798
261
2,059
5.229885
0.452107
0.043956
0.028571
0
0
0
0
0
0
0
0
0.006687
0.201068
2,059
66
80
31.19697
0.8231
0.272948
0
0
0
0
0.135915
0.033099
0
0
0
0
0
1
0.117647
false
0
0.147059
0
0.382353
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
940234fb7a7c68381fd595779e6eeb95949ac3b9
2,564
py
Python
src/calibrate.py
modi712/Computer-Vision
a34d3d73f883beae812c50b879f4dc8ef679b3ac
[ "MIT" ]
null
null
null
src/calibrate.py
modi712/Computer-Vision
a34d3d73f883beae812c50b879f4dc8ef679b3ac
[ "MIT" ]
null
null
null
src/calibrate.py
modi712/Computer-Vision
a34d3d73f883beae812c50b879f4dc8ef679b3ac
[ "MIT" ]
null
null
null
# Calibrates camera using chessboard video import numpy as np import cv2 import glob # termination criteria criteria = (cv2.TERM_CRITERIA_EPS + cv2.TERM_CRITERIA_MAX_ITER, 30, 0.001) # prepare object points, like (0,0,0), (1,0,0), (2,0,0) ....,(6,5,0) objp = np.zeros((6*7,3), np.float32) objp[:,:2] = np.mgr...
29.136364
101
0.570203
330
2,564
4.412121
0.487879
0.010989
0.010302
0
0
0
0
0
0
0
0
0.152725
0.277301
2,564
87
102
29.471264
0.633028
0.232449
0
0.054054
0
0
0.065495
0.017572
0
0
0
0
0
1
0
false
0
0.081081
0
0.081081
0.108108
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
9404e9100f31206f2975c729bb0ee10df6676295
1,788
py
Python
src/currencycloud/clients/vans.py
icebotariccl/currencycloud-python
03bb0df2743e6669790dee6f2367f9e0500a4610
[ "MIT" ]
null
null
null
src/currencycloud/clients/vans.py
icebotariccl/currencycloud-python
03bb0df2743e6669790dee6f2367f9e0500a4610
[ "MIT" ]
null
null
null
src/currencycloud/clients/vans.py
icebotariccl/currencycloud-python
03bb0df2743e6669790dee6f2367f9e0500a4610
[ "MIT" ]
null
null
null
'''This module provides a class for VANs calls to the CC API''' from currencycloud.http import Http from currencycloud.resources import PaginatedCollection, Van import deprecation class Vans(Http): '''This class provides an interface to the VANs endpoints of the CC API''' def find(self, **kwargs): '...
47.052632
92
0.65604
217
1,788
5.327189
0.345622
0.077855
0.038927
0.044118
0.608131
0.608131
0.545848
0.471453
0.471453
0.471453
0
0.007988
0.229866
1,788
37
93
48.324324
0.831518
0.162192
0
0.48
0
0
0.17663
0.047554
0
0
0
0
0
1
0.16
false
0
0.12
0
0.48
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
94076e38767f1fdb24941a14891524bbde794118
5,703
bzl
Python
tests/util/defs.bzl
guw/rules_pkg
0541b09ca8b68c40e8868fd3c4a748e1bb5eafa3
[ "Apache-2.0" ]
62
2021-09-21T18:58:02.000Z
2022-03-07T02:17:43.000Z
third_party/rules_pkg-0.7.0/tests/util/defs.bzl
Vertexwahn/FlatlandRT
37d09fde38b25eff5f802200b43628efbd1e3198
[ "Apache-2.0" ]
null
null
null
third_party/rules_pkg-0.7.0/tests/util/defs.bzl
Vertexwahn/FlatlandRT
37d09fde38b25eff5f802200b43628efbd1e3198
[ "Apache-2.0" ]
null
null
null
# Copyright 2021 The Bazel Authors. 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 la...
32.403409
95
0.639663
714
5,703
4.956583
0.344538
0.01978
0.028257
0.018084
0.103419
0.046906
0.046906
0.027691
0.027691
0.027691
0
0.002315
0.242504
5,703
175
96
32.588571
0.816898
0.137647
0
0.178295
0
0.007752
0.337872
0.029954
0
0
0
0
0.015504
1
0.046512
false
0.023256
0
0
0.077519
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
940780137a7561bcd2fdc5e84bbb4666938c7d61
4,799
py
Python
systems/cluster_utils.py
cltl/LongTailIdentity
525f6eb10ce6c8eba1d6f462a900fd0ebd0f97a7
[ "Apache-2.0" ]
1
2019-02-07T06:30:35.000Z
2019-02-07T06:30:35.000Z
systems/cluster_utils.py
cltl/LongTailIdentity
525f6eb10ce6c8eba1d6f462a900fd0ebd0f97a7
[ "Apache-2.0" ]
null
null
null
systems/cluster_utils.py
cltl/LongTailIdentity
525f6eb10ce6c8eba1d6f462a900fd0ebd0f97a7
[ "Apache-2.0" ]
null
null
null
import json from collections import defaultdict import random def transform_to_json(data): a_json = {} cluster_id=1 for pid, separate_ids in data.items(): for spid in separate_ids: a_json[spid]=cluster_id cluster_id+=1 return a_json def create_keys_per_name(data): """ ...
36.633588
171
0.635757
629
4,799
4.648649
0.227345
0.071819
0.030096
0.04104
0.163817
0.100205
0.100205
0.056772
0.056772
0.056772
0
0.006733
0.288185
4,799
130
172
36.915385
0.849239
0.267972
0
0.125
0
0
0
0
0
0
0
0
0
1
0.090909
false
0
0.034091
0
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
9407ea96d7707d8b52c8d7cf4a197411ba311970
2,151
py
Python
hypotonic/__init__.py
mscavnicky/hypotonic
499ea821988c34ae5492979f4f8056c4a45b3b1f
[ "MIT" ]
8
2019-01-01T13:50:00.000Z
2020-09-06T16:15:51.000Z
hypotonic/__init__.py
mscavnicky/hypotonic
499ea821988c34ae5492979f4f8056c4a45b3b1f
[ "MIT" ]
1
2019-02-24T12:13:46.000Z
2019-02-24T19:50:49.000Z
hypotonic/__init__.py
mscavnicky/hypotonic
499ea821988c34ae5492979f4f8056c4a45b3b1f
[ "MIT" ]
null
null
null
import logging import importlib import asyncio import aiohttp logger = logging.getLogger('hypotonic') class Hypotonic: def __init__(self, url=None): self.commands = [] self.results = [] self.errors = [] if url: self.commands.append(('get', (url,), {})) async def worker(self, i, session, ...
26.8875
81
0.62901
263
2,151
5.060837
0.338403
0.060105
0.063862
0.047333
0.040571
0
0
0
0
0
0
0.000611
0.239424
2,151
79
82
27.227848
0.812958
0.040446
0
0.101695
0
0
0.033042
0
0
0
0
0
0
1
0.067797
false
0
0.084746
0
0.237288
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
940830c796f500a7ec43a9e9a73df7a17bb2c403
714
py
Python
03. Programacion orientada a objetos/04. clases y objetos/e1.py
Cidryl/python-desde-cero
fade09d13ab0ed0cbb4f45a49a4ad9e3980f3276
[ "MIT" ]
null
null
null
03. Programacion orientada a objetos/04. clases y objetos/e1.py
Cidryl/python-desde-cero
fade09d13ab0ed0cbb4f45a49a4ad9e3980f3276
[ "MIT" ]
null
null
null
03. Programacion orientada a objetos/04. clases y objetos/e1.py
Cidryl/python-desde-cero
fade09d13ab0ed0cbb4f45a49a4ad9e3980f3276
[ "MIT" ]
null
null
null
class Alumno: def declarar(self,nombre,dato): self.nombre=nombre self.puntuacion=dato def visualizar(self): print("Nombre:",self.nombre) print("Puntuacion:",self.puntuacion) def estadistica(self): if self.puntuacion<=4: print("insuficiente")...
22.3125
45
0.592437
70
714
6.042857
0.414286
0.165485
0.085106
0
0
0
0
0
0
0
0
0.02729
0.281513
714
32
46
22.3125
0.797271
0.022409
0
0
0
0
0.094595
0
0
0
0
0
0
1
0.125
false
0
0
0
0.166667
0.25
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
9408773ad197cea530dbf06232c18e80bd339f4d
5,487
py
Python
sagas/corpus/searcher.py
samlet/stack
47db17fd4fdab264032f224dca31a4bb1d19b754
[ "Apache-2.0" ]
3
2020-01-11T13:55:38.000Z
2020-08-25T22:34:15.000Z
sagas/corpus/searcher.py
samlet/stack
47db17fd4fdab264032f224dca31a4bb1d19b754
[ "Apache-2.0" ]
null
null
null
sagas/corpus/searcher.py
samlet/stack
47db17fd4fdab264032f224dca31a4bb1d19b754
[ "Apache-2.0" ]
1
2021-01-01T05:21:44.000Z
2021-01-01T05:21:44.000Z
from bert_serving.client import BertClient import pandas as pd import numpy as np import json import sagas.tracker_fn as tc from sagas.conf.conf import cf def search_in(text, lang): with open(f'{cf.conf_dir}/stack/crawlers/langcrs/all_{lang}.json') as json_file: sents=json.load(json_file) return [s...
34.949045
95
0.612539
694
5,487
4.684438
0.29683
0.01661
0.014765
0.024608
0.144263
0.114734
0.099354
0.099354
0.099354
0.065518
0
0.004501
0.271186
5,487
156
96
35.173077
0.808202
0.131766
0
0.064815
0
0
0.074283
0.018679
0
0
0
0
0
1
0.111111
false
0
0.12963
0
0.314815
0.009259
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
9408ba6fbe5aa752679b16a7faeb0c1c96aadb6e
882
py
Python
Mobility Algorithms/Test/link_identifier_test.py
James-OHara/NCHRP-BSM-Traffic-Measures
d6842c9dc63de8c2d470482fbfd1ec91a9c2ae56
[ "Apache-2.0" ]
null
null
null
Mobility Algorithms/Test/link_identifier_test.py
James-OHara/NCHRP-BSM-Traffic-Measures
d6842c9dc63de8c2d470482fbfd1ec91a9c2ae56
[ "Apache-2.0" ]
null
null
null
Mobility Algorithms/Test/link_identifier_test.py
James-OHara/NCHRP-BSM-Traffic-Measures
d6842c9dc63de8c2d470482fbfd1ec91a9c2ae56
[ "Apache-2.0" ]
null
null
null
import unittest import numpy as np from bsm_stream_vector import LinkIdentifier """Test LinkIndentifier class in bsm_stream_vector to ensure the BSMs are being assigned to the correct Measures Estimation link """ class LinkIdentifierTest(unittest.TestCase): #This test only works if findLink in LinkIndentifier retur...
30.413793
129
0.727891
127
882
4.88189
0.511811
0.03871
0.048387
0.064516
0.135484
0.135484
0.135484
0
0
0
0
0.013699
0.172336
882
29
130
30.413793
0.835616
0.190476
0
0
0
0
0.061017
0
0
0
0
0
0.052632
1
0.105263
false
0
0.157895
0
0.315789
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
940bf9f6bcf066af4e32b8cbf37d9f28635da2d5
8,350
py
Python
TSP/model_free.py
machine-reasoning-ufrgs/graph-nn
7489b7b3d6a4750245e3f506982d98b56a74b6bb
[ "MIT" ]
1
2019-11-04T15:56:00.000Z
2019-11-04T15:56:00.000Z
TSP/model_free.py
machine-reasoning-ufrgs/graph-nn
7489b7b3d6a4750245e3f506982d98b56a74b6bb
[ "MIT" ]
null
null
null
TSP/model_free.py
machine-reasoning-ufrgs/graph-nn
7489b7b3d6a4750245e3f506982d98b56a74b6bb
[ "MIT" ]
2
2019-09-21T12:10:56.000Z
2021-04-17T13:55:32.000Z
import sys, os import tensorflow as tf sys.path.insert(1, os.path.join(sys.path[0], '..')) from graphnn_free import GraphNN from mlp import Mlp def build_network(d): # Define hyperparameters d = d learning_rate = 2e-5 l2norm_scaling = 1e-10 global_norm_gradient_clipping_ratio = 0.65 # Defin...
39.57346
183
0.600719
1,128
8,350
4.219858
0.198582
0.030252
0.027311
0.027731
0.389286
0.329622
0.295378
0.236765
0.214076
0.214076
0
0.012616
0.278563
8,350
210
184
39.761905
0.776726
0.186108
0
0.10596
0
0
0.066894
0
0
0
0
0
0
1
0.006623
false
0
0.02649
0
0.039735
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
940c0b72ebd459534046c762a3ab4ce951637c18
1,593
py
Python
ixnetwork_restpy/pytest_tests/tests/test_async_operation.py
OpenIxia/ixnetwork_restpy
f628db450573a104f327cf3c737ca25586e067ae
[ "MIT" ]
20
2019-05-07T01:59:14.000Z
2022-02-11T05:24:47.000Z
ixnetwork_restpy/pytest_tests/tests/test_async_operation.py
OpenIxia/ixnetwork_restpy
f628db450573a104f327cf3c737ca25586e067ae
[ "MIT" ]
60
2019-04-03T18:59:35.000Z
2022-02-22T12:05:05.000Z
ixnetwork_restpy/pytest_tests/tests/test_async_operation.py
OpenIxia/ixnetwork_restpy
f628db450573a104f327cf3c737ca25586e067ae
[ "MIT" ]
13
2019-05-20T10:48:31.000Z
2021-10-06T07:45:44.000Z
"""Tests to verify the async=True functionality of operations """ import pytest from ixnetwork_restpy import TestPlatform, BadRequestError def test_async_operation(ixnetwork): # uncomment the following to see the full request and response # from ixnetwork_restpy import TestPlatform # ixnetwork.parent.pare...
37.928571
78
0.750157
196
1,593
5.933673
0.382653
0.067068
0.072227
0.089424
0.513328
0.421324
0.421324
0.421324
0.421324
0.326741
0
0.00757
0.170747
1,593
41
79
38.853659
0.872824
0.295041
0
0.086957
0
0
0.233544
0.020739
0
0
0
0
0.130435
1
0.086957
false
0
0.086957
0
0.173913
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
940ddb5e6655f6d1f74858cf98a8d51ff4dc825b
1,452
py
Python
kodistubs/_publish_docs.py
ogero/Deluge-Manager-XBMC
10c4f2a93ac1fffba01209444ba5e597036b968b
[ "MIT" ]
null
null
null
kodistubs/_publish_docs.py
ogero/Deluge-Manager-XBMC
10c4f2a93ac1fffba01209444ba5e597036b968b
[ "MIT" ]
null
null
null
kodistubs/_publish_docs.py
ogero/Deluge-Manager-XBMC
10c4f2a93ac1fffba01209444ba5e597036b968b
[ "MIT" ]
null
null
null
#!/usr/bin/env python # coding: utf-8 # Created on: 24.02.2016 # Author: Roman Miroshnychenko aka Roman V.M. (romanvm@yandex.ua) from __future__ import print_function import os from subprocess import call gh_token = os.environ['GH_TOKEN'] repo_slug= os.environ['TRAVIS_REPO_SLUG'] gh_repo_url = 'https://{gh_token}@git...
33.767442
89
0.631543
199
1,452
4.442211
0.467337
0.047511
0.030543
0.033937
0
0
0
0
0
0
0
0.007563
0.180441
1,452
42
90
34.571429
0.735294
0.083333
0
0
0
0
0.249435
0
0
0
0
0
0
1
0.03125
false
0
0.09375
0
0.125
0.0625
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
940ea273ac1efd7b81d8def3cd0c08c7f2a030f1
12,861
py
Python
self_play_train.py
DrVecctor/GameOfGo
ab8b0313372fe380b44dd7021c00895c971b3e54
[ "MIT" ]
null
null
null
self_play_train.py
DrVecctor/GameOfGo
ab8b0313372fe380b44dd7021c00895c971b3e54
[ "MIT" ]
null
null
null
self_play_train.py
DrVecctor/GameOfGo
ab8b0313372fe380b44dd7021c00895c971b3e54
[ "MIT" ]
1
2020-09-11T16:49:01.000Z
2020-09-11T16:49:01.000Z
import warnings warnings.filterwarnings('ignore') import os os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3' import tensorflow.python.util.deprecation as deprecation deprecation._PRINT_DEPRECATION_WARNINGS = False import json import argparse import multiprocessing import random import shutil import time import tempfile from...
32.892583
154
0.643807
1,718
12,861
4.553551
0.16007
0.036815
0.02825
0.010738
0.288892
0.23188
0.205803
0.167455
0.149048
0.149048
0
0.016622
0.24687
12,861
390
155
32.976923
0.791039
0.015007
0
0.187311
0
0
0.069894
0.002211
0
0
0
0
0
1
0.02719
false
0.003021
0.060423
0
0.102719
0.048338
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
940f45a74fbe5732957c0a584ead0ec8af62f5f8
1,618
py
Python
mooc_ex/xbaoItemPrice.py
ds17/reptiles
99418624ae4b7548bf4dc1ea834e8c75a47a0557
[ "Apache-2.0" ]
null
null
null
mooc_ex/xbaoItemPrice.py
ds17/reptiles
99418624ae4b7548bf4dc1ea834e8c75a47a0557
[ "Apache-2.0" ]
null
null
null
mooc_ex/xbaoItemPrice.py
ds17/reptiles
99418624ae4b7548bf4dc1ea834e8c75a47a0557
[ "Apache-2.0" ]
1
2021-02-20T13:17:42.000Z
2021-02-20T13:17:42.000Z
#D:\Python\Python35\python.exe # -*- coding:utf-8 -*- '淘宝商品价格定向爬虫' import requests,csv,re,os,time i=1 #全局计数变量 def getHTMLtext(url): try: r=requests.get(url) r.encoding=r.apparent_encoding return r.text except: print('获取页面异常') def parsePage(ilt,html): # info=re.findall(r'...
26.52459
128
0.549444
222
1,618
3.900901
0.432432
0.04157
0.034642
0.030023
0.157044
0.157044
0.157044
0.157044
0.157044
0.157044
0
0.011933
0.223115
1,618
60
129
26.966667
0.677009
0.277503
0
0
0
0
0.157082
0.079828
0
0
0
0
0
1
0.108108
false
0
0.027027
0
0.162162
0.054054
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
9411e487e97666c6453fbbd22292c525e1819e7a
2,359
py
Python
appCore/apps/replica/cms/views/template.py
jadedgamer/alifewellplayed.com
b7b3dee8d3b9526c7cfe77078570a29394ef7e76
[ "MIT" ]
4
2017-04-22T11:03:01.000Z
2018-01-16T22:28:15.000Z
appCore/apps/replica/cms/views/template.py
alifewellplayed/alifewellplayed.com
b7b3dee8d3b9526c7cfe77078570a29394ef7e76
[ "MIT" ]
10
2017-04-06T19:54:42.000Z
2017-11-07T06:53:10.000Z
appCore/apps/replica/cms/views/template.py
alifewellplayed/alifewellplayed.com
b7b3dee8d3b9526c7cfe77078570a29394ef7e76
[ "MIT" ]
1
2017-12-14T12:49:40.000Z
2017-12-14T12:49:40.000Z
from django.conf import settings from django.template import RequestContext from django.shortcuts import render_to_response, render, get_object_or_404, redirect from django.views.decorators.cache import cache_page from django.views.generic.list import ListView from django.contrib import messages from replica import se...
36.859375
86
0.694786
272
2,359
5.919118
0.349265
0.037267
0.020497
0.026087
0.088199
0.043478
0.043478
0
0
0
0
0.004787
0.203052
2,359
63
87
37.444444
0.851596
0.010598
0
0.137931
0
0
0.135877
0.063438
0
0
0
0
0
1
0.068966
false
0
0.155172
0.017241
0.37931
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
9411f20ddc93846bc9ba0efb924f787c448b3493
1,844
py
Python
cogs.py
Paarf/BoxBot
da323ddf30e368bed077ef75f843eb6e43902bd3
[ "MIT" ]
null
null
null
cogs.py
Paarf/BoxBot
da323ddf30e368bed077ef75f843eb6e43902bd3
[ "MIT" ]
null
null
null
cogs.py
Paarf/BoxBot
da323ddf30e368bed077ef75f843eb6e43902bd3
[ "MIT" ]
null
null
null
# -*- coding: utf-8 -*- import discord from discord.ext import commands class Commands: def __init__(self, bot): self.bot = bot # you can use events here too async def on_message(self, msg): print(msg.content) # or commands like this @commands.command() async d...
34.148148
122
0.646421
241
1,844
4.858921
0.373444
0.040991
0.085397
0.098207
0.242528
0.226302
0.081981
0
0
0
0
0.052338
0.222885
1,844
53
123
34.792453
0.764829
0.038503
0
0.138889
0
0
0.205711
0.072844
0
0
0
0
0
1
0.055556
false
0
0.055556
0
0.138889
0.027778
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
941744eaeedb8147966109fc40c6847481dcda99
13,358
py
Python
quantlib/test/test_hybridhestonhullwhite_process.py
yuyingfeng/pyql
ceb838581ad4db73a0208bc51bde2771bb534e5f
[ "BSD-3-Clause" ]
null
null
null
quantlib/test/test_hybridhestonhullwhite_process.py
yuyingfeng/pyql
ceb838581ad4db73a0208bc51bde2771bb534e5f
[ "BSD-3-Clause" ]
null
null
null
quantlib/test/test_hybridhestonhullwhite_process.py
yuyingfeng/pyql
ceb838581ad4db73a0208bc51bde2771bb534e5f
[ "BSD-3-Clause" ]
2
2016-08-24T20:56:14.000Z
2022-01-03T05:58:42.000Z
from __future__ import division from __future__ import print_function from .unittest_tools import unittest import numpy as np from quantlib.settings import Settings from quantlib.instruments.option import ( EuropeanExercise) from quantlib.instruments.payoffs import PAYOFF_TO_STR from quantlib.models.shortrate...
30.778802
86
0.564381
1,435
13,358
5.111498
0.174913
0.029993
0.009816
0.017996
0.451125
0.381731
0.357737
0.333197
0.3182
0.3182
0
0.048304
0.344438
13,358
433
87
30.849885
0.789311
0.012726
0
0.345638
0
0
0.03669
0
0
0
0
0
0.020134
1
0.02349
false
0
0.060403
0.003356
0.09396
0.060403
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
9419dfff89fc658e4d5b9784d855175327b46249
13,470
py
Python
microutil/napari_wrappers.py
Hekstra-Lab/microutil
ab3b7b51754bf90ef35d6eea1c7b35cece638f0e
[ "BSD-3-Clause" ]
2
2021-07-06T05:31:51.000Z
2021-10-05T13:29:59.000Z
microutil/napari_wrappers.py
Hekstra-Lab/microutil
ab3b7b51754bf90ef35d6eea1c7b35cece638f0e
[ "BSD-3-Clause" ]
16
2021-02-08T22:36:42.000Z
2021-11-01T22:36:02.000Z
microutil/napari_wrappers.py
Hekstra-Lab/microutil
ab3b7b51754bf90ef35d6eea1c7b35cece638f0e
[ "BSD-3-Clause" ]
null
null
null
__all__ = [ "manual_segmentation", "correct_watershed", "correct_decreasing_cell_frames", ] import warnings import numpy as np import xarray as xr from .array_utils import axis2int from .segmentation import ( napari_points_to_peak_mask, peak_mask_to_napari_points, watershed_single_frame_presee...
31.619718
129
0.607275
1,791
13,470
4.40536
0.18593
0.023701
0.011534
0.015209
0.279848
0.225349
0.1782
0.165273
0.117617
0.090494
0
0.013799
0.289829
13,470
425
130
31.694118
0.810997
0.2902
0
0.219917
0
0
0.055682
0.005546
0
0
0
0
0
1
0.13278
false
0
0.041494
0
0.190871
0.008299
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
941bf67ace09cea1fa8be060142fbc460a1ab4a9
1,433
py
Python
pypy/module/posix/app_startfile.py
olliemath/pypy
8b873bd0b8bf76075aba3d915c260789f26f5788
[ "Apache-2.0", "OpenSSL" ]
1
2021-06-02T23:02:09.000Z
2021-06-02T23:02:09.000Z
pypy/module/posix/app_startfile.py
olliemath/pypy
8b873bd0b8bf76075aba3d915c260789f26f5788
[ "Apache-2.0", "OpenSSL" ]
1
2021-03-30T18:08:41.000Z
2021-03-30T18:08:41.000Z
pypy/module/posix/app_startfile.py
olliemath/pypy
8b873bd0b8bf76075aba3d915c260789f26f5788
[ "Apache-2.0", "OpenSSL" ]
1
2022-03-30T11:42:37.000Z
2022-03-30T11:42:37.000Z
# NOT_RPYTHON class CFFIWrapper(object): def __init__(self): import cffi ffi = cffi.FFI() ffi.cdef(""" HINSTANCE ShellExecuteA(HWND, LPCSTR, LPCSTR, LPCSTR, LPCSTR, INT); HINSTANCE ShellExecuteW(HWND, LPCWSTR, LPCWSTR, LPCWSTR, LPCWSTR, INT); """) self.NULL =...
32.568182
79
0.597348
165
1,433
5.072727
0.357576
0.041816
0.028674
0.026284
0.107527
0.107527
0.107527
0.107527
0.107527
0.107527
0
0.005952
0.296581
1,433
43
80
33.325581
0.824405
0.007676
0
0.054054
0
0
0.159267
0
0
0
0
0
0
1
0.054054
false
0
0.027027
0
0.108108
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
941fa2d0f2957a837877bc52e0cf20be207d8edc
2,147
py
Python
Revoke.py
locobastos/IBM-Informix-Comparison-Script
bd624a73e24a1d994e5d3c266d49a7f12d972611
[ "MIT" ]
null
null
null
Revoke.py
locobastos/IBM-Informix-Comparison-Script
bd624a73e24a1d994e5d3c266d49a7f12d972611
[ "MIT" ]
null
null
null
Revoke.py
locobastos/IBM-Informix-Comparison-Script
bd624a73e24a1d994e5d3c266d49a7f12d972611
[ "MIT" ]
null
null
null
# coding=utf-8 class Revoke: """ A revoke is described by : - The database on which it exists - The privilege revoked - The user on wich the revoke applies - The table on which the revoke applies - The owner of the table on which the revoke applies """ def __in...
37.017241
94
0.647415
269
2,147
4.996283
0.234201
0.073661
0.095238
0.083333
0.334077
0.286458
0.266369
0.243304
0.243304
0.243304
0
0.00719
0.287378
2,147
57
95
37.666667
0.871242
0.432231
0
0
0
0
0.002752
0
0
0
0
0
0
1
0.111111
false
0
0
0
0.222222
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
94216394fa225ea1e01514370a7ab54fc7850fd6
4,394
py
Python
StateTracing/dataloader.py
junchenfeng/diagnosis_tracing
4e26e2ad0c7abc547f22774b6c9c299999a152c3
[ "MIT" ]
null
null
null
StateTracing/dataloader.py
junchenfeng/diagnosis_tracing
4e26e2ad0c7abc547f22774b6c9c299999a152c3
[ "MIT" ]
null
null
null
StateTracing/dataloader.py
junchenfeng/diagnosis_tracing
4e26e2ad0c7abc547f22774b6c9c299999a152c3
[ "MIT" ]
1
2020-09-08T13:42:16.000Z
2020-09-08T13:42:16.000Z
from torch import tensor from numpy.random import choice,shuffle max_len = 128 def random_cut(length): s = choice(length-max_len+1) return s,s+max_len def differeniate(statesA,statesB): return [[i,b] for i,(a,b) in enumerate(zip(map(int,statesA),map(int,statesB))) if b!=a] def generate_targe...
26.46988
92
0.466318
553
4,394
3.616637
0.242315
0.007
0.012
0.0165
0.07
0.051
0.007
0
0
0
0
0.024962
0.39827
4,394
165
93
26.630303
0.731467
0.087619
0
0.121739
0
0
0.020822
0
0
0
0
0
0
1
0.095652
false
0
0.026087
0.008696
0.191304
0.06087
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
9421e29a0bf88b5d1d33c777e246e5747fbbdf1c
467
py
Python
classification/classifier.py
mjbaucas/OneWordSpeechRecognition
8b6ec3e59c77b574d0f6e29cd50aaa8106a0c106
[ "CC-BY-4.0" ]
null
null
null
classification/classifier.py
mjbaucas/OneWordSpeechRecognition
8b6ec3e59c77b574d0f6e29cd50aaa8106a0c106
[ "CC-BY-4.0" ]
null
null
null
classification/classifier.py
mjbaucas/OneWordSpeechRecognition
8b6ec3e59c77b574d0f6e29cd50aaa8106a0c106
[ "CC-BY-4.0" ]
null
null
null
from keras.models import load_model from numpy import array, asarray, shape from dataset import DatasetGenerator def classify_sound(model, sound_file): model = load_model(model) LABELS = 'no yes'.split() dsGen = DatasetGenerator(label_set=LABELS) x = array(dsGen.process_wav_file(sound_file)) x = asarray(x).resh...
22.238095
46
0.717345
71
467
4.605634
0.56338
0.055046
0
0
0
0
0
0
0
0
0
0.03599
0.167024
467
20
47
23.35
0.804627
0.036403
0
0
0
0
0.013363
0
0
0
0
0
0
1
0.066667
false
0
0.2
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
9423171d16250d6171ddafca3f4c87c148dbefd2
489
py
Python
00_Original/34_Netzwerkkommunikation/E-Mail/Erstellen_komplexer_E-Mails/email_mit_anhang.py
felixdittrich92/Python3_book
cd0e2b55aa72c51927d347b70199fb9ed928e06f
[ "MIT" ]
null
null
null
00_Original/34_Netzwerkkommunikation/E-Mail/Erstellen_komplexer_E-Mails/email_mit_anhang.py
felixdittrich92/Python3_book
cd0e2b55aa72c51927d347b70199fb9ed928e06f
[ "MIT" ]
null
null
null
00_Original/34_Netzwerkkommunikation/E-Mail/Erstellen_komplexer_E-Mails/email_mit_anhang.py
felixdittrich92/Python3_book
cd0e2b55aa72c51927d347b70199fb9ed928e06f
[ "MIT" ]
null
null
null
#!/usr/bin/env python # -*- coding: utf-8 -*- from email.mime.multipart import MIMEMultipart from email.mime.image import MIMEImage from email.mime.text import MIMEText msg = MIMEMultipart() msg["Subject"] = "Hallo Welt" msg["From"] = "Donald Duck <don@ld.de>" msg["To"] = "Onkel Dagobert <d@gobert.de>" text = MIMETe...
22.227273
58
0.697342
75
489
4.533333
0.666667
0.079412
0.114706
0
0
0
0
0
0
0
0
0.002331
0.122699
489
21
59
23.285714
0.79021
0.08589
0
0
0
0
0.276404
0
0
0
0
0
0
1
0
false
0
0.214286
0
0.214286
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
9427c1c57cf677a2859c3b47d370c6f3bd16a79d
543
py
Python
asyncqtpy/common.py
codelv/asyncqtpy
def6207aa44c7de794345816fff514103c2440bb
[ "BSD-2-Clause" ]
null
null
null
asyncqtpy/common.py
codelv/asyncqtpy
def6207aa44c7de794345816fff514103c2440bb
[ "BSD-2-Clause" ]
null
null
null
asyncqtpy/common.py
codelv/asyncqtpy
def6207aa44c7de794345816fff514103c2440bb
[ "BSD-2-Clause" ]
null
null
null
# © 2018 Gerard Marull-Paretas <gerard@teslabs.com> # © 2014 Mark Harviston <mark.harviston@gmail.com> # © 2014 Arve Knudsen <arve.knudsen@gmail.com> # BSD License """Mostly irrelevant, but useful utilities common to UNIX and Windows.""" import logging def with_logger(cls): """Class decorator to add a logger to ...
30.166667
73
0.714549
78
543
4.858974
0.602564
0.021108
0.042216
0
0
0
0
0
0
0
0
0.026726
0.173112
543
17
74
31.941176
0.81069
0.493554
0
0
0
0
0.103448
0.103448
0
0
0
0
0.125
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
9427fe62f70bac3dffa9c51e9108759e4dbc47d2
13,665
pyp
Python
plugins/Py-RoundedTube/Py-RoundedTube.pyp
tdapper/cinema4d_py_sdk
32b1d2b63fe28510c83c66065394042900000e92
[ "Apache-2.0" ]
113
2015-12-11T11:00:49.000Z
2022-03-27T01:33:12.000Z
plugins/Py-RoundedTube/Py-RoundedTube.pyp
tdapper/cinema4d_py_sdk
32b1d2b63fe28510c83c66065394042900000e92
[ "Apache-2.0" ]
3
2016-04-04T12:45:28.000Z
2019-04-12T08:33:38.000Z
plugins/Py-RoundedTube/Py-RoundedTube.pyp
tdapper/cinema4d_py_sdk
32b1d2b63fe28510c83c66065394042900000e92
[ "Apache-2.0" ]
50
2015-11-16T11:13:02.000Z
2022-03-26T07:05:25.000Z
""" RoundedTube Copyright: MAXON Computer GmbH Written for Cinema 4D R18 Modified Date: 05/12/2018 """ import os import math import sys import c4d from c4d import plugins, utils, bitmaps, gui # Be sure to use a unique ID obtained from www.plugincafe.com PLUGIN_ID = 1025250 class RoundedTube(plugins.ObjectData): ...
38.064067
195
0.589901
2,021
13,665
3.892133
0.158832
0.032418
0.097254
0.082126
0.52924
0.414315
0.302568
0.226799
0.201627
0.198195
0
0.040902
0.298646
13,665
358
196
38.170391
0.779841
0.143798
0
0.297189
0
0
0.004458
0
0
0
0
0
0
1
0.048193
false
0.008032
0.02008
0.004016
0.124498
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
942a08b6947bb2c1cb07c5fce687f9f20cbf31ee
1,548
py
Python
scripts/models/checkpoint.py
daniele21/DL_soccer_prediction_v2
97bafe911fd8883d6679cf55fd0fff34db67ef06
[ "MIT" ]
null
null
null
scripts/models/checkpoint.py
daniele21/DL_soccer_prediction_v2
97bafe911fd8883d6679cf55fd0fff34db67ef06
[ "MIT" ]
null
null
null
scripts/models/checkpoint.py
daniele21/DL_soccer_prediction_v2
97bafe911fd8883d6679cf55fd0fff34db67ef06
[ "MIT" ]
null
null
null
# -*- coding: utf-8 -*- from scripts.utils.saving import save_soccer_model def checkpoint(model, early_stopping=True): losses = model.losses patience_rate = model.es_patience if(len(losses['train']) > 1 and len(losses['eval']) > 1 and early_stopping): last_train_loss = losses['train'][-2] ...
33.652174
102
0.605943
191
1,548
4.492147
0.219895
0.177156
0.06993
0.074592
0.305361
0.305361
0.247086
0.198135
0.090909
0
0
0.017691
0.306202
1,548
45
103
34.4
0.781192
0.352067
0
0.210526
0
0
0.027411
0
0
0
0
0
0
1
0.052632
false
0
0.052632
0
0.263158
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