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
31d4b6913b04eb19080a816c2290d803b8ff2f23
8,618
py
Python
cogeo_mosaic/backends/base.py
drnextgis/cogeo-mosaic
034d0124a2da894c2bb432b1c0cebba7f716edbd
[ "MIT" ]
null
null
null
cogeo_mosaic/backends/base.py
drnextgis/cogeo-mosaic
034d0124a2da894c2bb432b1c0cebba7f716edbd
[ "MIT" ]
null
null
null
cogeo_mosaic/backends/base.py
drnextgis/cogeo-mosaic
034d0124a2da894c2bb432b1c0cebba7f716edbd
[ "MIT" ]
null
null
null
"""cogeo_mosaic.backend.base: base Backend class.""" import abc import itertools from typing import Any, Dict, List, Optional, Sequence, Tuple, Type, Union import attr import mercantile from cachetools import TTLCache, cached from cachetools.keys import hashkey from morecantile import TileMatrixSet from rio_tiler.con...
36.058577
137
0.636343
1,066
8,618
5.012195
0.196998
0.047165
0.06326
0.018716
0.215235
0.126708
0.108179
0.091709
0.073741
0.065132
0
0.005534
0.245185
8,618
238
138
36.210084
0.815834
0.206428
0
0.152318
0
0
0.0178
0
0
0
0
0
0
1
0.145695
false
0
0.13245
0
0.443709
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
31d61f0a33b68e1cb755859a34a3948798308cb2
5,190
py
Python
userge/core/methods/decorators/on_filters.py
wildyvpn-network/bot
87459495000bd6004b8f62a9cb933c164da9ef29
[ "MIT" ]
null
null
null
userge/core/methods/decorators/on_filters.py
wildyvpn-network/bot
87459495000bd6004b8f62a9cb933c164da9ef29
[ "MIT" ]
null
null
null
userge/core/methods/decorators/on_filters.py
wildyvpn-network/bot
87459495000bd6004b8f62a9cb933c164da9ef29
[ "MIT" ]
null
null
null
# pylint: disable=missing-module-docstring # # Copyright (C) 2020 by UsergeTeam@Github, < https://github.com/UsergeTeam >. # # This file is part of < https://github.com/UsergeTeam/Userge > project, # and is released under the "GNU v3.0 License Agreement". # Please see < https://github.com/uaudith/Userge/blob/master/LIC...
43.613445
89
0.527746
515
5,190
5.114563
0.234951
0.060744
0.079727
0.075171
0.462794
0.220957
0.188307
0.090357
0
0
0
0.002504
0.384393
5,190
118
90
43.983051
0.821909
0.563391
0
0
0
0
0.004004
0
0
0
0
0
0
1
0.02381
false
0
0.071429
0
0.142857
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
31d8a178060a23e17a236c26a55e351c521d366e
3,823
py
Python
RepositoryBootstrap/EnvironmentDiffs.py
davidbrownell/v3-Common_Environment
8f42f256e573cbd83cbf9813db9958025ddf12f2
[ "BSL-1.0" ]
null
null
null
RepositoryBootstrap/EnvironmentDiffs.py
davidbrownell/v3-Common_Environment
8f42f256e573cbd83cbf9813db9958025ddf12f2
[ "BSL-1.0" ]
1
2018-06-08T06:45:16.000Z
2018-06-08T06:45:16.000Z
RepositoryBootstrap/EnvironmentDiffs.py
davidbrownell/v3-Common_Environment
8f42f256e573cbd83cbf9813db9958025ddf12f2
[ "BSL-1.0" ]
1
2018-06-08T04:15:17.000Z
2018-06-08T04:15:17.000Z
# ---------------------------------------------------------------------- # | # | EnvironmentDiffs.py # | # | David Brownell <db@DavidBrownell.com> # | 2018-06-02 22:19:34 # | # ---------------------------------------------------------------------- # | # | Copyright David Brownell 2018-22. # | Distrib...
36.409524
126
0.437876
272
3,823
5.944853
0.448529
0.06679
0.083488
0.014842
0.152134
0.118738
0.076685
0.076685
0
0
0
0.008892
0.176301
3,823
104
127
36.759615
0.504605
0.405441
0
0.207547
0
0
0.004103
0
0
0
0
0
0.037736
1
0.075472
false
0.018868
0.169811
0
0.301887
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
31da9f9cf7a9feda53f89aeafcbeadfbe26ac626
7,837
py
Python
tests/model/test_ocrd_mets.py
wrznr/pyocrd
25c4dd8c60285b7877803e2b627d72c8c0a4ab1e
[ "Apache-2.0" ]
null
null
null
tests/model/test_ocrd_mets.py
wrznr/pyocrd
25c4dd8c60285b7877803e2b627d72c8c0a4ab1e
[ "Apache-2.0" ]
null
null
null
tests/model/test_ocrd_mets.py
wrznr/pyocrd
25c4dd8c60285b7877803e2b627d72c8c0a4ab1e
[ "Apache-2.0" ]
null
null
null
from datetime import datetime from os.path import join from tests.base import TestCase, main, assets, copy_of_directory from ocrd_utils import ( initLogging, VERSION, MIMETYPE_PAGE ) from ocrd_models import OcrdMets # pylint: disable=protected-access,deprecated-method,too-many-public-methods class TestOcr...
44.528409
139
0.643486
1,041
7,837
4.685879
0.192123
0.132226
0.095941
0.072161
0.466175
0.417179
0.287618
0.234727
0.159492
0.140221
0
0.030323
0.208881
7,837
175
140
44.782857
0.756452
0.045808
0
0.087591
0
0
0.210073
0.024374
0
0
0
0
0.372263
1
0.160584
false
0.007299
0.036496
0
0.20438
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
31db05913c960fafbf96871656aa566e21ebbd4d
7,862
py
Python
robo_gym/envs/ur/ur_avoidance_basic.py
psFournier/robo-gym
0e67a36c0cbeac885c53b92de8f3f1f13e286c9a
[ "MIT" ]
236
2020-04-15T10:50:45.000Z
2022-03-31T14:28:52.000Z
robo_gym/envs/ur/ur_avoidance_basic.py
psFournier/robo-gym
0e67a36c0cbeac885c53b92de8f3f1f13e286c9a
[ "MIT" ]
36
2020-07-13T17:11:32.000Z
2022-02-21T14:01:33.000Z
robo_gym/envs/ur/ur_avoidance_basic.py
psFournier/robo-gym
0e67a36c0cbeac885c53b92de8f3f1f13e286c9a
[ "MIT" ]
51
2020-04-24T08:58:31.000Z
2022-03-18T17:14:23.000Z
""" Environment for basic obstacle avoidance controlling a robotic arm from UR. In this environment the obstacle is only moving up and down in a vertical line in front of the robot. The goal is for the robot to stay within a predefined minimum distance to the moving obstacle. When feasible the robot should continue to...
47.077844
197
0.672602
1,085
7,862
4.599078
0.23318
0.022445
0.028858
0.019639
0.290782
0.222044
0.173948
0.129259
0.085772
0.085772
0
0.020736
0.239379
7,862
167
197
47.077844
0.813712
0.307174
0
0.086957
0
0
0.082066
0.04507
0
0
0
0
0
1
0.054348
false
0
0.054348
0
0.228261
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
31dd0da78d51189eef9e478f249f06c8a43016ca
1,789
py
Python
config/constants.py
flopezag/fiware-tsc-dashboard
af80673707c9b2fb85c9f4aa12bce12a20ef4431
[ "Apache-2.0" ]
null
null
null
config/constants.py
flopezag/fiware-tsc-dashboard
af80673707c9b2fb85c9f4aa12bce12a20ef4431
[ "Apache-2.0" ]
37
2017-02-23T09:08:58.000Z
2019-08-13T09:34:40.000Z
config/constants.py
flopezag/fiware-tsc-dashboard
af80673707c9b2fb85c9f4aa12bce12a20ef4431
[ "Apache-2.0" ]
2
2017-12-19T15:06:33.000Z
2019-05-02T17:24:45.000Z
#!/usr/bin/env python # -*- encoding: utf-8 -*- ## # Copyright 2017 FIWARE Foundation, e.V. # 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.apach...
31.946429
108
0.755729
258
1,789
5.096899
0.612403
0.045627
0.019772
0.024335
0
0
0
0
0
0
0
0.013926
0.157071
1,789
55
109
32.527273
0.85809
0.756288
0
0
0
0
0.335013
0.118388
0
0
0
0
0
1
0
false
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
31dd79c83f754d036eb084c170cefc01374db92c
633
py
Python
src/GUI/Plotter.py
sbooeshaghi/pegasus
32ca075b38a72a7955209657a8326ac749f658a3
[ "BSD-2-Clause" ]
1
2021-08-31T13:30:25.000Z
2021-08-31T13:30:25.000Z
src/GUI/Plotter.py
pachterlab/pegasus
32ca075b38a72a7955209657a8326ac749f658a3
[ "BSD-2-Clause" ]
1
2020-10-27T16:42:55.000Z
2020-10-27T16:42:55.000Z
src/GUI/Plotter.py
pachterlab/pegasus
32ca075b38a72a7955209657a8326ac749f658a3
[ "BSD-2-Clause" ]
null
null
null
#!/usr/bin/env python # -*- coding: utf-8 -*- import pyqtgraph as pg import numpy as np class CustomWidget(pg.GraphicsWindow): pg.setConfigOption('background', 'w') pg.setConfigOption('foreground', 'k') def __init__(self, parent=None, **kargs): pg.GraphicsWindow.__init__(self, **kargs) sel...
31.65
77
0.63981
77
633
5.051948
0.649351
0.082262
0
0
0
0
0
0
0
0
0
0.005894
0.195893
633
20
78
31.65
0.75835
0.066351
0
0
0
0
0.147458
0
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
31de64f0189fb656e61e3cf8d36bbc5c08efed8c
2,733
py
Python
tests/test_collapsible.py
TehMillhouse/sphinxawesome-theme
5130b8b4c2546ceaccf37353fa6a0bfb4526303c
[ "MIT" ]
17
2020-07-10T12:05:07.000Z
2022-03-08T03:40:49.000Z
tests/test_collapsible.py
TehMillhouse/sphinxawesome-theme
5130b8b4c2546ceaccf37353fa6a0bfb4526303c
[ "MIT" ]
475
2020-05-22T09:44:25.000Z
2022-03-27T08:01:23.000Z
tests/test_collapsible.py
TehMillhouse/sphinxawesome-theme
5130b8b4c2546ceaccf37353fa6a0bfb4526303c
[ "MIT" ]
10
2020-12-23T11:14:57.000Z
2022-02-13T08:51:02.000Z
"""Tests for collapsible definition lists. When the option ``html_collapsible_definitions`` is ``True``, some HTML classes should be added to some definition lists but not all of them. """ from pathlib import Path import pytest from sphinx.application import Sphinx from .util import parse_html @pytest.mark.sphinx...
30.032967
80
0.642883
373
2,733
4.621984
0.270777
0.031323
0.037123
0.034803
0.602088
0.522622
0.522622
0.522622
0.522622
0.522622
0
0.005457
0.19539
2,733
90
81
30.366667
0.778536
0.181851
0
0.619048
0
0.031746
0.208352
0.053563
0
0
0
0
0.285714
1
0.047619
false
0
0.063492
0
0.111111
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
31df4d7e972bd1519fc475be70b05e383b709299
1,618
py
Python
Iris Network/Conclusion/task.py
jetbrains-academy/Machine-Learning-101
7b583dbff1e90115296dcaeac78ca88363c158c9
[ "MIT" ]
null
null
null
Iris Network/Conclusion/task.py
jetbrains-academy/Machine-Learning-101
7b583dbff1e90115296dcaeac78ca88363c158c9
[ "MIT" ]
10
2021-11-22T16:51:52.000Z
2022-02-14T12:57:57.000Z
Iris Network/Conclusion/task.py
jetbrains-academy/Machine-Learning-101
7b583dbff1e90115296dcaeac78ca88363c158c9
[ "MIT" ]
null
null
null
import numpy as np import pandas as pd import matplotlib.pyplot as plt from network import NN from evaluate import accuracy def read_data(fpath): iris = pd.read_csv(fpath) iris.loc[iris['species'] == 'virginica', 'species'] = 0 iris.loc[iris['species'] == 'versicolor', 'species'] = 1 iris.loc[iris['sp...
33.708333
105
0.65513
257
1,618
3.988327
0.346304
0.053659
0.073171
0.085854
0.218537
0.165854
0.062439
0.062439
0
0
0
0.02024
0.175525
1,618
47
106
34.425532
0.748126
0.037701
0
0
0
0.055556
0.238249
0.027044
0
0
0
0
0
1
0.083333
false
0
0.138889
0
0.277778
0.138889
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
31e177fb5a84a661f6f3ed3c32e0ead9540dfcd1
1,160
py
Python
agentless/crypto.py
tinyauth/agentless
50f30dbb11007fd58c057a38c61783bff282603f
[ "Apache-2.0" ]
null
null
null
agentless/crypto.py
tinyauth/agentless
50f30dbb11007fd58c057a38c61783bff282603f
[ "Apache-2.0" ]
null
null
null
agentless/crypto.py
tinyauth/agentless
50f30dbb11007fd58c057a38c61783bff282603f
[ "Apache-2.0" ]
null
null
null
from cryptography.hazmat.backends import default_backend from cryptography.hazmat.primitives import hashes, serialization from cryptography.hazmat.primitives.asymmetric import padding, rsa backend = default_backend() def generate_private_key(): key = rsa.generate_private_key( public_exponent=65537, ...
25.777778
66
0.712931
129
1,160
6.170543
0.356589
0.113065
0.065327
0.075377
0.109296
0
0
0
0
0
0
0.016164
0.2
1,160
44
67
26.363636
0.841595
0
0
0.117647
0
0
0.008621
0
0
0
0
0
0
1
0.117647
false
0.029412
0.088235
0.058824
0.323529
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
31e1ce88e4424fa367dbbc4289f23529ddd13fe8
1,939
py
Python
sphinx/source/tutorial/exercises/stocks.py
minrk/bokeh
ae4366e508355afc06b5fc62f1ee399635ab909d
[ "BSD-3-Clause" ]
null
null
null
sphinx/source/tutorial/exercises/stocks.py
minrk/bokeh
ae4366e508355afc06b5fc62f1ee399635ab909d
[ "BSD-3-Clause" ]
null
null
null
sphinx/source/tutorial/exercises/stocks.py
minrk/bokeh
ae4366e508355afc06b5fc62f1ee399635ab909d
[ "BSD-3-Clause" ]
null
null
null
import numpy as np import pandas as pd from bokeh.plotting import * # Here is some code to read in some stock data from the Yahoo Finance API AAPL = pd.read_csv( "http://ichart.yahoo.com/table.csv?s=AAPL&a=0&b=1&c=2000", parse_dates=['Date']) GOOG = pd.read_csv( "http://ichart.yahoo.com/table.csv?s=GOOG&...
34.017544
85
0.638473
303
1,939
4.026403
0.405941
0.019672
0.029508
0.042623
0.337705
0.277049
0.277049
0.277049
0.277049
0.201639
0
0.020492
0.244972
1,939
56
86
34.625
0.812842
0.421351
0
0.133333
0
0.133333
0.320618
0.037239
0
0
0
0
0
1
0
false
0
0.1
0
0.1
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
31e29f3d6b52be28f77756b4ec61862d6adf938c
1,828
py
Python
nni/retiarii/converter/visualize.py
qfyin/nni
59a1ccf8eba68b94974e84fc3834f38d851faf89
[ "MIT" ]
3
2021-02-23T14:01:43.000Z
2021-03-29T16:19:32.000Z
nni/retiarii/converter/visualize.py
qfyin/nni
59a1ccf8eba68b94974e84fc3834f38d851faf89
[ "MIT" ]
1
2021-01-17T08:53:56.000Z
2021-01-17T08:53:56.000Z
nni/retiarii/converter/visualize.py
qfyin/nni
59a1ccf8eba68b94974e84fc3834f38d851faf89
[ "MIT" ]
1
2020-12-21T11:15:54.000Z
2020-12-21T11:15:54.000Z
import graphviz def convert_to_visualize(graph_ir, vgraph): for name, graph in graph_ir.items(): if name == '_training_config': continue with vgraph.subgraph(name='cluster'+name) as subgraph: subgraph.attr(color='blue') cell_node = {} ioput = {'_inpu...
43.52381
124
0.516958
196
1,828
4.545918
0.27551
0.062851
0.058361
0.051627
0.253648
0.253648
0.184063
0.184063
0.105499
0.105499
0
0.003276
0.332057
1,828
41
125
44.585366
0.726454
0
0
0
0
0
0.123085
0
0
0
0
0
0
1
0.054054
false
0
0.027027
0
0.081081
0.027027
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
31e59bd3f15670f0f52fb2ebf16c987e7332b1b1
885
py
Python
customBackground.py
VisweshK/Jashmup
ca0cf639000734c5aea8583d9477af9a387f6d46
[ "MIT" ]
null
null
null
customBackground.py
VisweshK/Jashmup
ca0cf639000734c5aea8583d9477af9a387f6d46
[ "MIT" ]
null
null
null
customBackground.py
VisweshK/Jashmup
ca0cf639000734c5aea8583d9477af9a387f6d46
[ "MIT" ]
null
null
null
''' This is the class to create a scrolling background. Because the background was so large, it was made to be a .jpg. ''' import pygame, os class Background(pygame.sprite.Sprite): # Initialize the sprite. def __init__(self,disp): pygame.sprite.Sprite.__init__(self) self.image = pygame...
31.607143
96
0.638418
130
885
4.276923
0.407692
0.064748
0.048561
0.05036
0.061151
0
0
0
0
0
0
0.00916
0.259887
885
27
97
32.777778
0.839695
0.377401
0
0.133333
0
0
0.046992
0
0
0
0
0
0
1
0.2
false
0
0.066667
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
31e6ea9406db1015334a06a90ed69fe2df85ccfc
1,705
py
Python
src/python/squarepants/file_utils.py
ericzundel/mvn2pants
59776864939515bc0cae28e1b89944ce55b98b21
[ "Apache-2.0" ]
8
2015-04-14T22:37:56.000Z
2021-01-20T19:46:40.000Z
src/python/squarepants/file_utils.py
ericzundel/mvn2pants
59776864939515bc0cae28e1b89944ce55b98b21
[ "Apache-2.0" ]
1
2016-01-13T23:19:14.000Z
2016-01-22T22:47:48.000Z
src/python/squarepants/file_utils.py
ericzundel/mvn2pants
59776864939515bc0cae28e1b89944ce55b98b21
[ "Apache-2.0" ]
3
2015-12-13T08:35:34.000Z
2018-08-01T17:44:59.000Z
import os import shutil from contextlib import contextmanager from tempfile import mkdtemp, mktemp @contextmanager def temporary_dir(): """Returns a temporary directory that gets cleaned up when the context manager exits.""" tempdir = mkdtemp() try: yield tempdir finally: shutil.rmtree(tempdir) @con...
26.230769
97
0.719062
227
1,705
5.361233
0.422907
0.041906
0.042728
0.027938
0.070666
0.070666
0.070666
0.070666
0.070666
0
0
0
0.192375
1,705
64
98
26.640625
0.883805
0.353079
0
0.219512
0
0
0.006567
0
0
0
0
0
0
1
0.121951
false
0
0.097561
0
0.268293
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
31e76ef0dddf511d5e363ce2b9c0502413fbe8c1
1,366
py
Python
docs/DSDC/miniprez/miniprez/continuous_integration.py
thoppe/Presentation_Topics
e9aba07e9ab087b44e6044c6082ba8e873a9b4fd
[ "MIT" ]
2
2018-12-03T17:03:19.000Z
2018-12-10T16:42:39.000Z
docs/DSDC/miniprez/miniprez/continuous_integration.py
thoppe/Presentation_Topics_in_NLP
e9aba07e9ab087b44e6044c6082ba8e873a9b4fd
[ "MIT" ]
1
2019-02-19T15:12:19.000Z
2019-02-19T15:12:19.000Z
docs/DSDC/miniprez/miniprez/continuous_integration.py
thoppe/Presentation_Topics_in_NLP
e9aba07e9ab087b44e6044c6082ba8e873a9b4fd
[ "MIT" ]
1
2019-02-19T12:51:37.000Z
2019-02-19T12:51:37.000Z
import asyncio import os from parser import miniprez_markdown, build_body import logging logger = logging.getLogger("miniprez") async def file_watcher(target_file, sleep_time=0.5): """ Watchs a file. If modified, yield the filename. Yield the filename once to start. """ # Yield the file first ...
24.836364
74
0.678624
190
1,366
4.647368
0.352632
0.06795
0.09966
0.088335
0.138165
0.06342
0
0
0
0
0
0.004766
0.232064
1,366
54
75
25.296296
0.836988
0.040264
0
0
0
0
0.049684
0
0
0
0
0
0
1
0.037037
false
0
0.148148
0
0.185185
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
31e9ecb8c0d331c1cbff40bfe30ea5db0aed7e97
3,943
py
Python
rl_algorithms/dqn/linear.py
yonghangzhou/rl_algorithms
fe373bf77c9007e4e1d7134e1d610131125fa4b7
[ "MIT" ]
1
2020-11-12T07:48:49.000Z
2020-11-12T07:48:49.000Z
rl_algorithms/dqn/linear.py
yonghangzhou/rl_algorithms
fe373bf77c9007e4e1d7134e1d610131125fa4b7
[ "MIT" ]
null
null
null
rl_algorithms/dqn/linear.py
yonghangzhou/rl_algorithms
fe373bf77c9007e4e1d7134e1d610131125fa4b7
[ "MIT" ]
null
null
null
# -*- coding: utf-8 -*- """Linear module for dqn algorithms - Author: Kyunghwan Kim - Contact: kh.kim@medipixel.io """ import math import numpy as np import torch import torch.nn as nn import torch.nn.functional as F from rl_algorithms.common.helper_functions import numpy2floattensor device = torch.device("cuda:0"...
33.700855
87
0.673852
512
3,943
4.980469
0.291016
0.060392
0.032941
0.051765
0.306275
0.241569
0.162353
0.089412
0.065098
0
0
0.005181
0.21684
3,943
116
88
33.991379
0.820596
0.308648
0
0.078431
0
0
0.013598
0
0
0
0
0
0
1
0.156863
false
0
0.117647
0
0.392157
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
31ecb15b99e3ceb267fe3088d539b5b22c952d38
1,346
py
Python
flink-ai-flow/examples/workflow_on_event/workflows/init/init.py
lisy09/flink-ai-extended
011a5a332f7641f66086653e715d0596eab2e107
[ "Apache-2.0", "BSD-2-Clause", "MIT", "ECL-2.0", "BSD-3-Clause" ]
null
null
null
flink-ai-flow/examples/workflow_on_event/workflows/init/init.py
lisy09/flink-ai-extended
011a5a332f7641f66086653e715d0596eab2e107
[ "Apache-2.0", "BSD-2-Clause", "MIT", "ECL-2.0", "BSD-3-Clause" ]
null
null
null
flink-ai-flow/examples/workflow_on_event/workflows/init/init.py
lisy09/flink-ai-extended
011a5a332f7641f66086653e715d0596eab2e107
[ "Apache-2.0", "BSD-2-Clause", "MIT", "ECL-2.0", "BSD-3-Clause" ]
null
null
null
# # Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you under the Apache License, Version 2.0 (the # "License"); you may not...
35.421053
83
0.770431
204
1,346
4.867647
0.465686
0.060423
0.068479
0.084592
0.138973
0.138973
0.076536
0.076536
0
0
0
0.003484
0.147103
1,346
37
84
36.378378
0.861498
0.558692
0
0
0
0
0.236522
0.073043
0
0
0
0
0
1
0.076923
false
0
0.076923
0
0.153846
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
31ee3bc132db64859847221802dd7bff470b9ce3
977
py
Python
platform/radio/efr32_multiphy_configurator/pyradioconfig/parts/bobcat/profiles/Profile_WiSUN.py
SiliconLabs/Gecko_SDK
991121c706578c9a2135b6f75cc88856e8c64bdc
[ "Zlib" ]
82
2016-06-29T17:24:43.000Z
2021-04-16T06:49:17.000Z
platform/radio/efr32_multiphy_configurator/pyradioconfig/parts/bobcat/profiles/Profile_WiSUN.py
SiliconLabs/Gecko_SDK
991121c706578c9a2135b6f75cc88856e8c64bdc
[ "Zlib" ]
2
2017-02-13T10:07:17.000Z
2017-03-22T21:28:26.000Z
platform/radio/efr32_multiphy_configurator/pyradioconfig/parts/bobcat/profiles/Profile_WiSUN.py
SiliconLabs/Gecko_SDK
991121c706578c9a2135b6f75cc88856e8c64bdc
[ "Zlib" ]
56
2016-08-02T10:50:50.000Z
2021-07-19T08:57:34.000Z
from pyradioconfig.parts.ocelot.profiles.Profile_WiSUN import Profile_WiSUN_Ocelot from pyradioconfig.parts.common.profiles.bobcat_regs import build_modem_regs_bobcat from pyradioconfig.parts.common.profiles.profile_common import buildCrcOutputs, buildFecOutputs, buildFrameOutputs, \ buildWhiteOutputs class Profil...
42.478261
117
0.73695
103
977
6.679612
0.359223
0.104651
0.104651
0.081395
0.104651
0
0
0
0
0
0
0
0.188332
977
23
118
42.478261
0.867591
0
0
0
0
0
0.052147
0
0
0
0
0
0
1
0.1
false
0
0.15
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
31ee7dd58797f57d854758b0971c25c71826cd28
2,485
py
Python
smol_opyt/logistic_problem.py
abelsiqueira/smol-opyt
58901906eb3129f4aae9edc7893bba624c5a0686
[ "MIT" ]
null
null
null
smol_opyt/logistic_problem.py
abelsiqueira/smol-opyt
58901906eb3129f4aae9edc7893bba624c5a0686
[ "MIT" ]
5
2021-08-02T02:04:48.000Z
2021-08-02T02:27:57.000Z
smol_opyt/logistic_problem.py
abelsiqueira/smol-opyt
58901906eb3129f4aae9edc7893bba624c5a0686
[ "MIT" ]
null
null
null
from math import log import numpy as np from numpy import linalg as la class LogisticProblem: """Class for the logistic regression method for classification.""" def __init__(self, feat_mtx, y): """Create a Logistic Problem with matrix `feat_mtx` n by p and vector `y` of 0s and 1s with size n. ...
33.133333
107
0.534004
354
2,485
3.60452
0.257062
0.060345
0.043103
0.047022
0.254702
0.239812
0.128527
0.128527
0.128527
0.128527
0
0.020936
0.346479
2,485
74
108
33.581081
0.764778
0.181087
0
0.226415
0
0
0
0
0
0
0
0
0
1
0.113208
false
0
0.056604
0
0.264151
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
9ec50e4a84db3516536add2eb38a5493aef3c343
856
py
Python
examples/PTSD/mpi_tmp/PTSD_cognet.py
zeroknowledgediscovery/cognet
3acc2f05451ccbc228bf9c02e5d357b40b0c3e4f
[ "MIT" ]
null
null
null
examples/PTSD/mpi_tmp/PTSD_cognet.py
zeroknowledgediscovery/cognet
3acc2f05451ccbc228bf9c02e5d357b40b0c3e4f
[ "MIT" ]
null
null
null
examples/PTSD/mpi_tmp/PTSD_cognet.py
zeroknowledgediscovery/cognet
3acc2f05451ccbc228bf9c02e5d357b40b0c3e4f
[ "MIT" ]
null
null
null
from mpi4py.futures import MPIPoolExecutor import numpy as np import pandas as pd from quasinet.qnet import Qnet, qdistance, load_qnet, qdistance_matrix from quasinet.qsampling import qsample, targeted_qsample qnet=load_qnet('../results/PTSD_cognet_test.joblib') w = 304 h = w p_all = pd.read_csv("tmp_samples_as_string...
27.612903
84
0.73715
140
856
4.321429
0.464286
0.019835
0.033058
0
0
0
0
0
0
0
0
0.005376
0.130841
856
31
85
27.612903
0.807796
0
0
0
0
0
0.10035
0.070012
0
0
0
0
0
1
0.074074
false
0
0.185185
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
9ec5885a6003a25f321416770e39cf31583e933d
4,778
py
Python
dfainductor/algorithms/searchers.py
ctlab/DFA-Inductor-py
c9f0906101a4c83f125ab8c487dc2eac7a52d310
[ "MIT" ]
2
2020-06-03T11:27:45.000Z
2021-08-30T04:14:48.000Z
dfainductor/algorithms/searchers.py
ctlab/DFA-Inductor-py
c9f0906101a4c83f125ab8c487dc2eac7a52d310
[ "MIT" ]
1
2021-07-14T18:43:58.000Z
2021-07-14T18:43:58.000Z
dfainductor/algorithms/searchers.py
ctlab/DFA-Inductor-py
c9f0906101a4c83f125ab8c487dc2eac7a52d310
[ "MIT" ]
null
null
null
from typing import List from pysat.solvers import Solver from ..variables import VarPool from .reductions import ClauseGenerator from ..examples import BaseExamplesProvider from ..logging_utils import * from ..statistics import STATISTICS from ..structures import APTA, DFA, InconsistencyGraph class LSUS: _solve...
43.834862
102
0.547928
491
4,778
5.016293
0.240326
0.052781
0.038571
0.022737
0.221681
0.168088
0.142103
0.101502
0.07633
0.07633
0
0.004348
0.374215
4,778
108
103
44.240741
0.819398
0
0
0.159574
0
0
0.0563
0
0
0
0
0
0
1
0.031915
false
0
0.085106
0
0.180851
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
9ec5b4570de1244cfecc950781db192eb22b2b73
22,697
py
Python
lc_sqlalchemy_dbutils/manager.py
libcommon/sqlalchemy-dbutils-py
39b2fb0fc51279a4d1c8a2b6fe250f8cff44d1b1
[ "MIT" ]
null
null
null
lc_sqlalchemy_dbutils/manager.py
libcommon/sqlalchemy-dbutils-py
39b2fb0fc51279a4d1c8a2b6fe250f8cff44d1b1
[ "MIT" ]
null
null
null
lc_sqlalchemy_dbutils/manager.py
libcommon/sqlalchemy-dbutils-py
39b2fb0fc51279a4d1c8a2b6fe250f8cff44d1b1
[ "MIT" ]
null
null
null
## -*- coding: UTF8 -*- ## manager.py ## Copyright (c) 2020 libcommon ## ## Permission is hereby granted, free of charge, to any person obtaining a copy ## of this software and associated documentation files (the "Software"), to deal ## in the Software without restriction, including without limitation the rights ## to...
40.821942
119
0.628233
2,534
22,697
5.48974
0.159037
0.040184
0.021997
0.018115
0.370786
0.306951
0.268277
0.224211
0.186112
0.158076
0
0.003065
0.295546
22,697
555
120
40.895496
0.866971
0.420408
0
0.268868
0
0
0.093229
0.01994
0
0
0
0
0.122642
1
0.146226
false
0.042453
0.056604
0
0.301887
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
9ec70101de03b36989296a10649d2dea72a92c80
1,608
py
Python
kafka_demo_1/producer.py
Aguinore/udemy_kafka_demo
5f8383e1381dba2ddc0fc656b3cdc66b98258aad
[ "MIT" ]
null
null
null
kafka_demo_1/producer.py
Aguinore/udemy_kafka_demo
5f8383e1381dba2ddc0fc656b3cdc66b98258aad
[ "MIT" ]
null
null
null
kafka_demo_1/producer.py
Aguinore/udemy_kafka_demo
5f8383e1381dba2ddc0fc656b3cdc66b98258aad
[ "MIT" ]
null
null
null
from tweepy import StreamListener, OAuthHandler, Stream from configs import Configs import sys class StdOutListener(StreamListener): def __init__(self, kafka_producer, topic): super().__init__() self.kafka_producer = kafka_producer self.topic = topic """ A listener handles tweets tha...
26.8
88
0.697139
188
1,608
5.75
0.43617
0.144311
0.047179
0.038853
0
0
0
0
0
0
0
0.00549
0.20709
1,608
59
89
27.254237
0.842353
0.050995
0
0
0
0
0.071625
0
0
0
0
0
0
1
0.153846
false
0
0.102564
0
0.358974
0.076923
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
9ec74c2b027410af0c055e866b7e76cb8dc5f04e
1,717
py
Python
demo/examples/stability/advection_d2q4.py
bgraille/pylbm
fd4419933e05b85be364232fddedfcb4f7275e1f
[ "BSD-3-Clause" ]
106
2016-09-13T07:19:17.000Z
2022-03-19T13:41:55.000Z
demo/examples/stability/advection_d2q4.py
gouarin/pylbm
fd4419933e05b85be364232fddedfcb4f7275e1f
[ "BSD-3-Clause" ]
53
2017-09-18T04:51:19.000Z
2022-01-19T21:36:23.000Z
demo/examples/stability/advection_d2q4.py
gouarin/pylbm
fd4419933e05b85be364232fddedfcb4f7275e1f
[ "BSD-3-Clause" ]
33
2016-06-17T13:21:17.000Z
2021-11-11T16:57:46.000Z
""" Stability analysis of the D2Q4 solver for the advection equation d_t(u) + c_x d_x(u) + c_y d_y(u) = 0 """ import sympy as sp import pylbm # pylint: disable=invalid-name # symbolic variables U, X, Y = sp.symbols('U, X, Y') # symbolic parameters LA, CX, CY = sp.symbols('lambda, cx, cy', constants=True) S_...
20.939024
58
0.438556
225
1,717
3.191111
0.302222
0.02507
0.02507
0.022284
0.083565
0.016713
0
0
0
0
0
0.06256
0.394875
1,717
81
59
21.197531
0.628489
0.159581
0
0.193548
0
0
0.176264
0.030197
0
0
0
0
0
1
0
false
0
0.032258
0
0.032258
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
9ec859c40962ecf3e9c555e76fd3db0d87f04e0f
3,386
py
Python
src/tests/component/test_engine_manager.py
carbonblack/cbc-binary-toolkit
92c90b80e3c3e0b5c2473ef2086d2ce2fb651db4
[ "MIT" ]
8
2020-05-12T18:08:52.000Z
2021-12-27T06:11:00.000Z
src/tests/component/test_engine_manager.py
carbonblack/cbc-binary-toolkit
92c90b80e3c3e0b5c2473ef2086d2ce2fb651db4
[ "MIT" ]
4
2020-05-13T16:07:49.000Z
2020-06-30T18:47:14.000Z
src/tests/component/test_engine_manager.py
carbonblack/cbc-binary-toolkit
92c90b80e3c3e0b5c2473ef2086d2ce2fb651db4
[ "MIT" ]
3
2020-05-16T19:57:57.000Z
2020-11-01T08:43:31.000Z
# -*- coding: utf-8 -*- # ******************************************************* # Copyright (c) VMware, Inc. 2020-2021. All Rights Reserved. # SPDX-License-Identifier: MIT # ******************************************************* # * # * DISCLAIMER. THIS PROGRAM IS PROVIDED TO YOU "AS IS" WITHOUT # * WARRANTIES OR C...
30.781818
107
0.672475
355
3,386
6.230986
0.380282
0.049729
0.072333
0.049729
0.278481
0.278481
0.261302
0.213382
0.18264
0.163653
0
0.005803
0.185765
3,386
109
108
31.06422
0.796518
0.257826
0
0.450704
0
0
0.40429
0.097936
0
0
0
0
0.056338
1
0.070423
false
0.014085
0.112676
0
0.197183
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
9ecbaf805798824811c8f44248c90470a6ab1527
4,458
py
Python
src/form/panel/MultiPanel.py
kaorin/vmd_sizing
e609299a0acaa17bd34487314b05bab6af6819d8
[ "MIT" ]
32
2019-05-05T13:08:51.000Z
2022-03-11T07:13:27.000Z
src/form/panel/MultiPanel.py
kaorin/vmd_sizing
e609299a0acaa17bd34487314b05bab6af6819d8
[ "MIT" ]
3
2019-07-13T03:06:15.000Z
2021-11-03T10:30:15.000Z
src/form/panel/MultiPanel.py
kaorin/vmd_sizing
e609299a0acaa17bd34487314b05bab6af6819d8
[ "MIT" ]
11
2019-07-15T17:49:09.000Z
2022-03-20T10:40:27.000Z
# -*- coding: utf-8 -*- # import wx import wx.lib.newevent from form.panel.BasePanel import BasePanel from form.parts.SizingFileSet import SizingFileSet from module.MMath import MRect, MVector3D, MVector4D, MQuaternion, MMatrix4x4 # noqa from utils import MFileUtils # noqa from utils.MLogger import MLogger # noqa log...
42.056604
136
0.680126
586
4,458
4.87884
0.24744
0.053865
0.050017
0.052466
0.332984
0.264428
0.161945
0.147604
0.103533
0.050367
0
0.008567
0.214446
4,458
106
137
42.056604
0.807824
0.069314
0
0.029851
0
0
0.048379
0.038945
0
0
0
0
0
1
0.119403
false
0
0.104478
0
0.253731
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
9ecd3fdffb0348d1335d2b0ee06d51e7c7681296
1,261
py
Python
androgui.py
nawfling/androguard
67b992ce0feeeb01bc69a99257916487689c3bcf
[ "Apache-2.0" ]
1
2019-03-29T19:24:23.000Z
2019-03-29T19:24:23.000Z
androgui.py
adiltirur/malware_classification
67b992ce0feeeb01bc69a99257916487689c3bcf
[ "Apache-2.0" ]
null
null
null
androgui.py
adiltirur/malware_classification
67b992ce0feeeb01bc69a99257916487689c3bcf
[ "Apache-2.0" ]
null
null
null
#!/usr/bin/env python """Androguard Gui""" import argparse import os import sys from androguard.core import androconf from androguard.gui.mainwindow import MainWindow from PyQt5 import QtWidgets, QtGui if __name__ == '__main__': parser = argparse.ArgumentParser(description="Androguard GUI") parser.add_argum...
31.525
109
0.716891
157
1,261
5.617834
0.598726
0.044218
0.057823
0.07483
0.092971
0
0
0
0
0
0
0.019011
0.165741
1,261
39
110
32.333333
0.819392
0.258525
0
0
0
0
0.103896
0
0
0
0
0
0
1
0
false
0
0.272727
0
0.272727
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
9ecfe7e3194f0f7656e10dd2b39c230900905bf9
887
py
Python
Python/repeated-dna-sequences.py
sm2774us/leetcode_interview_prep_2021
33b41bea66c266b733372d9a8b9d2965cd88bf8c
[ "Fair" ]
null
null
null
Python/repeated-dna-sequences.py
sm2774us/leetcode_interview_prep_2021
33b41bea66c266b733372d9a8b9d2965cd88bf8c
[ "Fair" ]
null
null
null
Python/repeated-dna-sequences.py
sm2774us/leetcode_interview_prep_2021
33b41bea66c266b733372d9a8b9d2965cd88bf8c
[ "Fair" ]
null
null
null
# Time: O(n) # Space: O(n) import collections class Solution(object): def findRepeatedDnaSequences(self, s): """ :type s: str :rtype: List[str] """ dict, rolling_hash, res = {}, 0, [] for i in range(len(s)): rolling_hash = ((rolling_hash << 3) & 0x3fff...
25.342857
79
0.476888
112
887
3.714286
0.4375
0.185096
0.144231
0.048077
0.192308
0.192308
0.120192
0.120192
0
0
0
0.025362
0.377678
887
34
80
26.088235
0.728261
0.096956
0
0
0
0
0
0
0
0
0.013605
0
0
1
0.111111
false
0
0.055556
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
9ed2d77b6c8c12c27e466fb716c2e65ea3ea3aaa
2,579
py
Python
squeeze_and_excitation_networks/datasets/data_loader.py
younnggsuk/CV-Paper-Implementation
fecd67d3f216872976f9b38445ce1c1f9ef1ac02
[ "MIT" ]
4
2021-06-03T13:56:51.000Z
2021-11-05T06:22:25.000Z
densely_connected_convolutional_networks/datasets/data_loader.py
younnggsuk/CV-Paper-Implementation
fecd67d3f216872976f9b38445ce1c1f9ef1ac02
[ "MIT" ]
null
null
null
densely_connected_convolutional_networks/datasets/data_loader.py
younnggsuk/CV-Paper-Implementation
fecd67d3f216872976f9b38445ce1c1f9ef1ac02
[ "MIT" ]
1
2022-03-28T09:34:03.000Z
2022-03-28T09:34:03.000Z
import os import cv2 import albumentations as A from albumentations.pytorch import ToTensorV2 from torch.utils.data import Dataset, DataLoader from sklearn.model_selection import train_test_split __all__ = ['CatDogDataset', 'fetch_dataloader'] class CatDogDataset(Dataset): def __init__(self, file_paths, ...
29.643678
83
0.579294
280
2,579
5.067857
0.303571
0.069767
0.036646
0.042283
0.133897
0.062016
0.062016
0.062016
0.062016
0
0
0.018615
0.333463
2,579
87
84
29.643678
0.806864
0
0
0.125
0
0
0.024031
0
0
0
0
0
0
1
0.0625
false
0
0.09375
0.015625
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
9ed44c7c52a922019ce69deffde3525039c1362a
4,203
py
Python
seq2seq_utils.py
mumbihere/summarizer
c230115c7d2d3bb659e9a0e402266178743f8de6
[ "MIT" ]
null
null
null
seq2seq_utils.py
mumbihere/summarizer
c230115c7d2d3bb659e9a0e402266178743f8de6
[ "MIT" ]
null
null
null
seq2seq_utils.py
mumbihere/summarizer
c230115c7d2d3bb659e9a0e402266178743f8de6
[ "MIT" ]
null
null
null
from keras.preprocessing.text import text_to_word_sequence from keras.models import Sequential from keras.layers import Activation, TimeDistributed, Dense, RepeatVector, recurrent, Embedding from keras.layers.recurrent import LSTM from keras.optimizers import Adam, RMSprop from nltk import FreqDist import numpy as np i...
39.650943
169
0.664287
700
4,203
3.762857
0.198571
0.041002
0.048595
0.030752
0.3694
0.301822
0.268033
0.236902
0.220197
0.180714
0
0.006426
0.22246
4,203
106
170
39.650943
0.799572
0.137045
0
0.275
0
0
0.025442
0.006637
0
0
0
0
0
1
0.0625
false
0
0.1125
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
9ed6cf9a0648712f69e8e03077835798f4836842
4,318
py
Python
venv/Lib/site-packages/gevent/backdoor.py
Kiiwi/Syssel
83705e3fd0edf40f09df950d5ce91c95586573f5
[ "BSD-3-Clause" ]
null
null
null
venv/Lib/site-packages/gevent/backdoor.py
Kiiwi/Syssel
83705e3fd0edf40f09df950d5ce91c95586573f5
[ "BSD-3-Clause" ]
null
null
null
venv/Lib/site-packages/gevent/backdoor.py
Kiiwi/Syssel
83705e3fd0edf40f09df950d5ce91c95586573f5
[ "BSD-3-Clause" ]
null
null
null
# Copyright (c) 2009-2014, gevent contributors # Based on eventlet.backdoor Copyright (c) 2005-2006, Bob Ippolito from __future__ import print_function import sys from code import InteractiveConsole from gevent import socket from gevent.greenlet import Greenlet from gevent.hub import PY3, PYPY, getcurrent from gevent...
29.175676
98
0.598194
515
4,318
4.84466
0.392233
0.009619
0.012024
0.014429
0.078156
0.0501
0
0
0
0
0
0.032938
0.296897
4,318
147
99
29.37415
0.788867
0.27698
0
0.235955
0
0
0.036658
0
0
0
0
0
0
1
0.134831
false
0.011236
0.123596
0.022472
0.348315
0.022472
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
9ed839d6a98ae914dcbccc4b145b5eaa923e4f41
7,385
py
Python
spark/par_decompress_audio.py
droyston/spectralize
572770e7358acc3ec433470659759c17453409f2
[ "MIT" ]
null
null
null
spark/par_decompress_audio.py
droyston/spectralize
572770e7358acc3ec433470659759c17453409f2
[ "MIT" ]
null
null
null
spark/par_decompress_audio.py
droyston/spectralize
572770e7358acc3ec433470659759c17453409f2
[ "MIT" ]
null
null
null
#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Wed Jun 17 16:12:56 2020 @author: dylanroyston """ # import/configure packages import numpy as np import pandas as pd #import pyarrow as pa import librosa import librosa.display from pathlib import Path #import Ipython.display as ipd #import matplotlib.pyp...
27.867925
90
0.59499
908
7,385
4.610132
0.281938
0.0215
0.031056
0.012422
0.150979
0.13999
0.124701
0.124701
0.124701
0.103201
0
0.014404
0.294922
7,385
264
91
27.973485
0.789514
0.209208
0
0.12069
0
0
0.097981
0.030456
0
0
0
0
0
1
0.025862
false
0.008621
0.155172
0
0.189655
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
9eda27b08876015d63b9cfdc12be859142fbbd21
1,073
py
Python
get_ip_list_ru_gov.py
gil9red/SimplePyScripts
c191ce08fbdeb29377639184579e392057945154
[ "CC-BY-4.0" ]
117
2015-12-18T07:18:27.000Z
2022-03-28T00:25:54.000Z
get_ip_list_ru_gov.py
gil9red/SimplePyScripts
c191ce08fbdeb29377639184579e392057945154
[ "CC-BY-4.0" ]
8
2018-10-03T09:38:46.000Z
2021-12-13T19:51:09.000Z
get_ip_list_ru_gov.py
gil9red/SimplePyScripts
c191ce08fbdeb29377639184579e392057945154
[ "CC-BY-4.0" ]
28
2016-08-02T17:43:47.000Z
2022-03-21T08:31:12.000Z
#!/usr/bin/env python3 # -*- coding: utf-8 -*- __author__ = 'ipetrash' """ Скрипт выводит список ip государственных организаций. """ import ipaddress import sys import requests rs = requests.get('https://jarib.github.io/anon-history/RuGovEdits/ru/latest/ranges.json') # Проверка удачного запроса и полученных д...
22.354167
90
0.665424
146
1,073
4.787671
0.527397
0.077253
0.065808
0.097282
0
0
0
0
0
0
0
0.009467
0.212488
1,073
47
91
22.829787
0.817751
0.221808
0
0
0
0.05
0.258486
0
0
0
0
0
0
1
0
false
0
0.15
0
0.15
0.3
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
9edc1088501805cae0cb1dc1f360911a6998aed9
1,337
py
Python
test_collection.py
Rodrun/weatherguess
468ae8f6484ee3e3e82262ae10d845fd2d9b4267
[ "MIT" ]
null
null
null
test_collection.py
Rodrun/weatherguess
468ae8f6484ee3e3e82262ae10d845fd2d9b4267
[ "MIT" ]
null
null
null
test_collection.py
Rodrun/weatherguess
468ae8f6484ee3e3e82262ae10d845fd2d9b4267
[ "MIT" ]
null
null
null
import unittest import requests from collection import Collection class TestCollection(unittest.TestCase): def setUp(self): # Get the sample JSON data self.data = requests.get("http://samples.openweathermap.org/data/2.5/weather?zip=94040,us&appid=b6907d289e10d714a6e88b30761fae22").json() ...
34.282051
145
0.635004
167
1,337
5
0.413174
0.095808
0.035928
0.046707
0.238323
0.173653
0.150898
0.05988
0
0
0
0.035857
0.249065
1,337
38
146
35.184211
0.795817
0.154076
0
0
0
0.047619
0.135721
0
0
0
0
0
0.285714
1
0.190476
false
0
0.142857
0
0.380952
0.047619
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
9edd07604a3a97e4febf7283f02a7a1e61075cbb
36,220
py
Python
exot/util/misc.py
ETHZ-TEC/exot_eengine
7b7ce6cb949e1b0a02e716b03f2f9af751713b29
[ "BSD-3-Clause" ]
null
null
null
exot/util/misc.py
ETHZ-TEC/exot_eengine
7b7ce6cb949e1b0a02e716b03f2f9af751713b29
[ "BSD-3-Clause" ]
null
null
null
exot/util/misc.py
ETHZ-TEC/exot_eengine
7b7ce6cb949e1b0a02e716b03f2f9af751713b29
[ "BSD-3-Clause" ]
null
null
null
# Copyright (c) 2015-2020, Swiss Federal Institute of Technology (ETH Zurich) # All rights reserved. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are met: # # * Redistributions of source code must retain the above copyright...
33.755825
158
0.592601
4,898
36,220
4.281135
0.124745
0.006677
0.012876
0.010873
0.329916
0.268921
0.225666
0.188135
0.167247
0.152129
0
0.006235
0.291496
36,220
1,072
159
33.787313
0.810888
0.398896
0
0.23991
0
0.004484
0.1263
0.006209
0
0
0
0
0.013453
1
0.100897
false
0.002242
0.047085
0.008969
0.273543
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
9ede197b4e22a537f288d32a4de554ea29c1ea06
1,222
py
Python
70_question/dynamic_programming/max_profit_with_k_transactions.py
alvinctk/google-tech-dev-guide
9d7759bea1f44673c2de4f25a94b27368928a59f
[ "Apache-2.0" ]
26
2019-06-07T05:29:47.000Z
2022-03-19T15:32:27.000Z
70_question/dynamic_programming/max_profit_with_k_transactions.py
alvinctk/google-tech-dev-guide
9d7759bea1f44673c2de4f25a94b27368928a59f
[ "Apache-2.0" ]
null
null
null
70_question/dynamic_programming/max_profit_with_k_transactions.py
alvinctk/google-tech-dev-guide
9d7759bea1f44673c2de4f25a94b27368928a59f
[ "Apache-2.0" ]
6
2019-10-10T06:39:28.000Z
2020-05-12T19:50:55.000Z
def maxProfitWithKTransactions(prices, k): n = len(prices) profit = [[0]*n for _ in range(k+1)] """ t := number of transactions d := day at which either buy/sell stock profit[t][d] = max ( previous day profit = profit[t][d-1] , profit sold at this day + max(buy for th...
31.333333
136
0.56383
183
1,222
3.606557
0.300546
0.063636
0.048485
0.084848
0.280303
0.234848
0.137879
0
0
0
0
0.032864
0.302782
1,222
38
137
32.157895
0.741784
0
0
0
0
0
0.096774
0
0
0
0
0
0
1
0.047619
false
0
0
0
0.142857
0.142857
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
9edf6ecb3d424f1fd6e8e155154f4ecebc700938
4,149
py
Python
main.py
rdmaulana/flask-smart-xls-clean
8dde5b56c241312ab252964b159921acd6013839
[ "MIT" ]
null
null
null
main.py
rdmaulana/flask-smart-xls-clean
8dde5b56c241312ab252964b159921acd6013839
[ "MIT" ]
null
null
null
main.py
rdmaulana/flask-smart-xls-clean
8dde5b56c241312ab252964b159921acd6013839
[ "MIT" ]
null
null
null
import pandas as pd import numpy as np import io import time import uuid from flask import Flask, render_template, request, redirect, url_for, Response, session, send_file, make_response, send_from_directory from os.path import join, dirname, realpath from werkzeug.wsgi import FileWrapper app = Flask(__name__) app.co...
35.161017
134
0.612919
568
4,149
4.316901
0.28169
0.051387
0.028548
0.039967
0.183524
0.138662
0.109299
0.095024
0.095024
0.07708
0
0.010563
0.178597
4,149
118
135
35.161017
0.70892
0.003133
0
0
0
0
0.22104
0.028295
0
0
0
0
0
1
0.054348
false
0
0.086957
0.01087
0.195652
0.021739
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
9edfcae85303a4e73d41bdae85aeda75e4c87673
2,817
py
Python
scripts/wapo/wapo_link_graph_from_mongo.py
feup-infolab/army-ant
7b33120d5160f73d7a41a05e6336489c917fb75c
[ "BSD-3-Clause" ]
5
2018-01-18T14:11:52.000Z
2020-10-23T16:02:25.000Z
scripts/wapo/wapo_link_graph_from_mongo.py
feup-infolab/army-ant
7b33120d5160f73d7a41a05e6336489c917fb75c
[ "BSD-3-Clause" ]
10
2018-02-02T20:19:36.000Z
2020-10-05T08:46:36.000Z
scripts/wapo/wapo_link_graph_from_mongo.py
feup-infolab/army-ant
7b33120d5160f73d7a41a05e6336489c917fb75c
[ "BSD-3-Clause" ]
null
null
null
#!/usr/bin/env python # # wapo_link_graph_from_mongo.py # José Devezas <joseluisdevezas@gmail.com> # 2019-02-05 import logging import sys import warnings import networkx as nx from bs4 import BeautifulSoup from pymongo import MongoClient logging.basicConfig( format='%(asctime)s wapo_link_graph_from_mongo: %(lev...
26.083333
108
0.615903
390
2,817
4.284615
0.338462
0.04608
0.062837
0.020347
0.228007
0.102334
0.102334
0.102334
0.078396
0.078396
0
0.014734
0.253106
2,817
107
109
26.327103
0.779468
0.048278
0
0.164179
0
0
0.179813
0.010093
0
0
0
0
0
1
0.014925
false
0
0.089552
0
0.104478
0.014925
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
9ee566ce8a227cbd2a762122ce0690fc72e66ca6
7,540
py
Python
designScripts/vernierMask.py
smartalecH/BYUqot
5b24759c4a100086937795a80d2eb6597e611819
[ "MIT" ]
5
2019-03-26T17:12:25.000Z
2021-12-27T18:05:52.000Z
designScripts/vernierMask.py
smartalecH/BYUqot
5b24759c4a100086937795a80d2eb6597e611819
[ "MIT" ]
5
2018-05-30T21:05:36.000Z
2018-08-16T05:16:40.000Z
designScripts/vernierMask.py
smartalecH/BYUqot
5b24759c4a100086937795a80d2eb6597e611819
[ "MIT" ]
5
2018-05-30T02:54:07.000Z
2020-08-16T17:18:38.000Z
# ------------------------------------------------------------------ # # vernierMask.py # ------------------------------------------------------------------ # # # A mask design used to align the 3D printer to a silicon photonic chip # # ------------------------------------------------------------------ # # VERSION HIST...
35.233645
96
0.554377
716
7,540
5.826816
0.324022
0.013423
0.018217
0.026846
0.198226
0.198226
0.171381
0.126079
0.1093
0.1093
0
0.021831
0.185942
7,540
213
97
35.399061
0.657869
0.41565
0
0.087912
0
0
0.016275
0
0
0
0
0
0
1
0.054945
false
0
0.054945
0
0.164835
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
9ee5da5b7c789afc93423e16612fb9f6de97baba
3,519
py
Python
src/programy/brainfactory.py
motazsaad/fit-bot-fb-clt
580477aa1ec91855b621d9ae276f2705962f6a87
[ "MIT" ]
null
null
null
src/programy/brainfactory.py
motazsaad/fit-bot-fb-clt
580477aa1ec91855b621d9ae276f2705962f6a87
[ "MIT" ]
null
null
null
src/programy/brainfactory.py
motazsaad/fit-bot-fb-clt
580477aa1ec91855b621d9ae276f2705962f6a87
[ "MIT" ]
4
2019-04-01T15:42:23.000Z
2020-11-05T08:14:27.000Z
""" Copyright (c) 2016-2019 Keith Sterling http://www.keithsterling.com Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, m...
34.165049
127
0.680591
417
3,519
5.573141
0.376499
0.060241
0.036575
0.023236
0.101549
0.101549
0.101549
0.049914
0.049914
0.049914
0
0.00304
0.25206
3,519
102
128
34.5
0.879939
0.310031
0
0.296875
0
0
0.004545
0
0
0
0
0
0
1
0.1875
false
0.015625
0.046875
0.03125
0.421875
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
9ee7fc2118d9db373e3131dcd7ab5c6417b15d3a
5,191
py
Python
conans/search/binary_html_table.py
matthiasng/conan
634eadc319da928084633a344d42785edccb8d6c
[ "MIT" ]
2
2019-01-09T10:01:29.000Z
2019-01-09T10:01:31.000Z
conans/search/binary_html_table.py
matthiasng/conan
634eadc319da928084633a344d42785edccb8d6c
[ "MIT" ]
1
2019-01-09T10:09:41.000Z
2019-01-09T10:09:41.000Z
conans/search/binary_html_table.py
matthiasng/conan
634eadc319da928084633a344d42785edccb8d6c
[ "MIT" ]
null
null
null
import os from collections import OrderedDict, defaultdict from conans.model.ref import PackageReference from conans.util.files import save class RowResult(object): def __init__(self, remote, reference, data): self.remote = remote self.reference = reference self._data = data @propert...
33.275641
98
0.571181
568
5,191
5.102113
0.258803
0.018979
0.024155
0.019324
0.072464
0.072464
0.055901
0.040718
0.040718
0.040718
0
0.003351
0.310152
5,191
155
99
33.490323
0.80592
0.110961
0
0.150442
0
0
0.048829
0
0
0
0
0
0.00885
1
0.106195
false
0
0.035398
0.035398
0.238938
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
9eec590065dcf6f8cc85b4d213651d2aa3e487f2
1,140
py
Python
irancovid-19.py
AmiiirCom/irancovid-19
c8871830e9344c5bf17043c802195911127bc532
[ "MIT" ]
null
null
null
irancovid-19.py
AmiiirCom/irancovid-19
c8871830e9344c5bf17043c802195911127bc532
[ "MIT" ]
null
null
null
irancovid-19.py
AmiiirCom/irancovid-19
c8871830e9344c5bf17043c802195911127bc532
[ "MIT" ]
null
null
null
from covid import Covid import json covid = Covid(source="worldometers") covid.get_data() iran_casses = covid.get_status_by_country_name("iran") confirmed = iran_casses['confirmed'] new_cases = iran_casses['new_cases'] deaths = iran_casses['deaths'] recovered = iran_casses['recovered'] active = iran_casses['active']...
30.810811
71
0.764035
151
1,140
5.331126
0.198676
0.161491
0.130435
0.099379
0.401242
0.356522
0.201242
0.201242
0
0
0
0
0.114912
1,140
37
72
30.810811
0.79782
0
0
0
0
0
0.273444
0.122699
0
0
0
0
0
1
0
false
0
0.0625
0
0.0625
0.03125
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
9eedcf612c173937e475b9b20ab18a1677cc7feb
2,758
py
Python
verres/optim/schedule.py
csxeba/Verres
04230d22b7791f84d86b9eb2272a6314a27580ed
[ "MIT" ]
null
null
null
verres/optim/schedule.py
csxeba/Verres
04230d22b7791f84d86b9eb2272a6314a27580ed
[ "MIT" ]
null
null
null
verres/optim/schedule.py
csxeba/Verres
04230d22b7791f84d86b9eb2272a6314a27580ed
[ "MIT" ]
null
null
null
from typing import Dict import numpy as np import tensorflow as tf import verres as V class ConstantSchedule(tf.keras.optimizers.schedules.LearningRateSchedule): def __init__(self, learning_rate: float): super().__init__() self.learning_rate = float(learning_rate) def __call__(self, step):...
32.069767
118
0.62074
341
2,758
4.771261
0.293255
0.027658
0.055317
0.024585
0.175784
0.084819
0.084819
0.084819
0.084819
0.084819
0
0.005063
0.283901
2,758
85
119
32.447059
0.818734
0
0
0.190476
0
0
0.073241
0
0
0
0
0
0
1
0.126984
false
0.015873
0.063492
0.031746
0.269841
0.015873
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
9eef48e8177814194dd2d1510e39357b5d13bd02
4,383
py
Python
run.py
SamChatfield/final-year-project
9d1ae2cb3009ffbff89cb438cfcde855db8a53ac
[ "MIT" ]
null
null
null
run.py
SamChatfield/final-year-project
9d1ae2cb3009ffbff89cb438cfcde855db8a53ac
[ "MIT" ]
null
null
null
run.py
SamChatfield/final-year-project
9d1ae2cb3009ffbff89cb438cfcde855db8a53ac
[ "MIT" ]
null
null
null
import json import string from datetime import datetime import deap import numpy as np import hmm from discriminator import Discriminator from ea import EA import random_search DEFAULT_PARAMS = { # Discriminator CNN model "model": "CNNModel3", # Algorithm Parameters "states": 5, "symbols": 5, ...
26.72561
98
0.6094
618
4,383
4.072816
0.262136
0.033373
0.023838
0.027811
0.156138
0.126738
0.090187
0.0294
0.0294
0.0294
0
0.026911
0.253936
4,383
163
99
26.889571
0.742813
0.087383
0
0.032
0
0.008
0.201253
0.016291
0
0
0
0
0.064
1
0.032
false
0
0.072
0
0.12
0.064
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
9ef2b9fdb256c9db58c16d3d792f230772a8e948
2,174
py
Python
rrc_example_package/benchmark_rrc/tools/plot/exp_align_obj.py
wq13552463699/TriFinger_Research
6ddfab4531cb4ba05a0fbb41227a734295dce378
[ "BSD-3-Clause" ]
12
2021-05-06T18:00:21.000Z
2022-01-11T14:23:22.000Z
rrc_example_package/benchmark_rrc/tools/plot/exp_align_obj.py
wq13552463699/TriFinger_Research
6ddfab4531cb4ba05a0fbb41227a734295dce378
[ "BSD-3-Clause" ]
3
2021-06-03T16:06:01.000Z
2021-08-15T13:40:09.000Z
rrc_example_package/benchmark_rrc/tools/plot/exp_align_obj.py
wq13552463699/TriFinger_Research
6ddfab4531cb4ba05a0fbb41227a734295dce378
[ "BSD-3-Clause" ]
4
2021-05-12T02:34:34.000Z
2021-07-18T19:54:50.000Z
#!/usr/bin/env python3 ''' This code traverses a directories of evaluation log files and record evaluation scores as well as plotting the results. ''' import os import argparse import json import copy from shutil import copyfile import pandas as pd import seaborn as sns import matplotlib.pyplot as plt from utils import...
35.639344
110
0.689512
310
2,174
4.619355
0.425806
0.075419
0.058659
0.039804
0.082402
0.041899
0
0
0
0
0
0.006948
0.205612
2,174
60
111
36.233333
0.822235
0.25207
0
0
0
0
0.219144
0.014484
0
0
0
0
0
1
0.058824
false
0
0.264706
0
0.323529
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
9ef2bd5f0fee2640fb7fcf65e291ea514c7f1058
286
py
Python
test cases/common/64 custom header generator/makeheader.py
objectx/meson
c0f097c0c74551972f7ec2203cd960824984f058
[ "Apache-2.0" ]
null
null
null
test cases/common/64 custom header generator/makeheader.py
objectx/meson
c0f097c0c74551972f7ec2203cd960824984f058
[ "Apache-2.0" ]
null
null
null
test cases/common/64 custom header generator/makeheader.py
objectx/meson
c0f097c0c74551972f7ec2203cd960824984f058
[ "Apache-2.0" ]
null
null
null
#!/usr/bin/env python3 # NOTE: this file does not have the executable bit set. This tests that # Meson can automatically parse shebang lines. import sys template = '#define RET_VAL %s\n' output = template % (open(sys.argv[1]).readline().strip()) open(sys.argv[2], 'w').write(output)
26
71
0.713287
46
286
4.413043
0.847826
0.068966
0.108374
0
0
0
0
0
0
0
0
0.012195
0.13986
286
10
72
28.6
0.813008
0.475524
0
0
0
0
0.142857
0
0
0
0
0
0
1
0
false
0
0.25
0
0.25
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
9ef65f5bf372723d5444efb6cd95a0880cc13cef
7,366
py
Python
upvote/gae/shared/common/json_utils_test.py
cclauss/upvote
9d526fec72690cde1575dbd32dacf68cbbab81d1
[ "Apache-2.0" ]
null
null
null
upvote/gae/shared/common/json_utils_test.py
cclauss/upvote
9d526fec72690cde1575dbd32dacf68cbbab81d1
[ "Apache-2.0" ]
null
null
null
upvote/gae/shared/common/json_utils_test.py
cclauss/upvote
9d526fec72690cde1575dbd32dacf68cbbab81d1
[ "Apache-2.0" ]
null
null
null
# Copyright 2017 Google Inc. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or a...
33.481818
79
0.691827
878
7,366
5.654897
0.255125
0.04431
0.100705
0.058409
0.604431
0.570393
0.554683
0.513998
0.513998
0.513998
0
0.043745
0.180695
7,366
219
80
33.634703
0.778956
0.133179
0
0.47651
0
0
0.13874
0.040315
0
0
0
0
0.040268
1
0.154362
false
0
0.04698
0
0.255034
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
9ef7f25002d6a0233c11be0350ae657d327330f8
3,728
py
Python
app.py
YukiNagat0/Blog
6f01d1a3e73f1f865b5d22dbdbb27a5acfb3e937
[ "MIT" ]
1
2021-06-24T17:48:37.000Z
2021-06-24T17:48:37.000Z
app.py
YukiNagat0/Blog
6f01d1a3e73f1f865b5d22dbdbb27a5acfb3e937
[ "MIT" ]
null
null
null
app.py
YukiNagat0/Blog
6f01d1a3e73f1f865b5d22dbdbb27a5acfb3e937
[ "MIT" ]
null
null
null
from os import path from typing import Union from datetime import datetime from flask import Flask, request, redirect, render_template from flask_wtf import CSRFProtect from werkzeug.utils import secure_filename from data import db_session from data.posts import Posts from forms.edit_post_form import EditPostForm ...
25.888889
117
0.668455
509
3,728
4.630648
0.208251
0.043275
0.038608
0.025456
0.358082
0.328384
0.30717
0.26644
0.26644
0.163768
0
0.00402
0.199303
3,728
143
118
26.06993
0.785595
0.021996
0
0.347368
0
0
0.131044
0.02967
0
0
0
0
0
1
0.063158
false
0
0.094737
0
0.242105
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
9ef85b894eb9c57e729d7cdbf2e496c34efcf07f
23,685
py
Python
test/test_automl/test_automl.py
ihounie/auto-sklearn
6a72f0df60b0c66ad75b0100d8d22c07da6217bb
[ "BSD-3-Clause" ]
null
null
null
test/test_automl/test_automl.py
ihounie/auto-sklearn
6a72f0df60b0c66ad75b0100d8d22c07da6217bb
[ "BSD-3-Clause" ]
null
null
null
test/test_automl/test_automl.py
ihounie/auto-sklearn
6a72f0df60b0c66ad75b0100d8d22c07da6217bb
[ "BSD-3-Clause" ]
1
2021-04-06T09:38:12.000Z
2021-04-06T09:38:12.000Z
# -*- encoding: utf-8 -*- import os import pickle import sys import time import glob import unittest import unittest.mock import numpy as np import pandas as pd import sklearn.datasets from smac.scenario.scenario import Scenario from smac.facade.roar_facade import ROAR from autosklearn.util.backend import Backend fro...
39.343854
94
0.609246
2,672
23,685
5.100299
0.16018
0.044027
0.036249
0.041972
0.519739
0.477326
0.435134
0.399252
0.37445
0.339081
0
0.012374
0.307368
23,685
601
95
39.409318
0.818348
0.080557
0
0.375271
0
0
0.083961
0.025493
0
0
0
0.001664
0.091106
1
0.041215
false
0.002169
0.047722
0.002169
0.101952
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
9ef906903676953e2a8a6d553c8fc0e08426873c
556
py
Python
estrutura-repeticao-while/ex062.py
TacilioRodriguez/Python
0b98dc8336e014046c579b387013b2871024e3d0
[ "Unlicense" ]
null
null
null
estrutura-repeticao-while/ex062.py
TacilioRodriguez/Python
0b98dc8336e014046c579b387013b2871024e3d0
[ "Unlicense" ]
null
null
null
estrutura-repeticao-while/ex062.py
TacilioRodriguez/Python
0b98dc8336e014046c579b387013b2871024e3d0
[ "Unlicense" ]
null
null
null
""" Melhore o Desafio 061, perguntando para o usuário se ele quer mostrar mais alguns termos. O programa encerra quando ele disser que quer mostrar 0 termos. """ primeiro = int(input('Digite o termo: ')) razao = int(input('Digite a razão: ')) termo = primeiro cont = 1 total = 0 mais = 10 while mais != 0: total = t...
27.8
89
0.633094
79
556
4.455696
0.506329
0.09375
0.079545
0
0
0
0
0
0
0
0
0.023585
0.23741
556
20
90
27.8
0.806604
0.27518
0
0
0
0
0.222222
0
0
0
0
0
0
1
0
false
0
0
0
0
0.2
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
9ef958e7d381e2efbcf979fbddc497610f9580d1
3,487
py
Python
Udemy_PythonBootcamp/Sec15_WebScraping.py
gonzalosc2/LearningPython
0210d4cbbb5e154f12007b8e8f825fd3d0022be0
[ "MIT" ]
null
null
null
Udemy_PythonBootcamp/Sec15_WebScraping.py
gonzalosc2/LearningPython
0210d4cbbb5e154f12007b8e8f825fd3d0022be0
[ "MIT" ]
null
null
null
Udemy_PythonBootcamp/Sec15_WebScraping.py
gonzalosc2/LearningPython
0210d4cbbb5e154f12007b8e8f825fd3d0022be0
[ "MIT" ]
null
null
null
#################################### # author: Gonzalo Salazar # course: 2020 Complete Python Bootcamps: From Zero to Hero in Python # purpose: lecture notes # description: Section 15 - Web Scraping # other: N/A #################################### # RULES # 1. always try to get permission before scraping, otherwise I...
32.287037
135
0.694006
533
3,487
4.485929
0.420263
0.054371
0.033459
0.01422
0.120452
0.120452
0.0711
0.049352
0.049352
0.049352
0
0.012745
0.167479
3,487
107
136
32.588785
0.810885
0.503298
0
0.090909
0
0.022727
0.253556
0
0
0
0
0
0
1
0
false
0
0.045455
0
0.045455
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
9ef987b5b2fc09a91874ef390e457aed66cdf6c0
10,220
py
Python
anchore_engine/analyzers/modules/33_binary_packages.py
dspalmer99/anchore-engine
8c61318be6fec5d767426fa4ccd98472cc85b5cd
[ "Apache-2.0" ]
null
null
null
anchore_engine/analyzers/modules/33_binary_packages.py
dspalmer99/anchore-engine
8c61318be6fec5d767426fa4ccd98472cc85b5cd
[ "Apache-2.0" ]
null
null
null
anchore_engine/analyzers/modules/33_binary_packages.py
dspalmer99/anchore-engine
8c61318be6fec5d767426fa4ccd98472cc85b5cd
[ "Apache-2.0" ]
null
null
null
#!/usr/bin/env python3 import sys import os import re import json import traceback import pkg_resources import tarfile from collections import OrderedDict import anchore_engine.analyzers.utils, anchore_engine.utils def get_python_evidence(tfl, member, memberhash, evidence): global binary_package_el full...
41.044177
148
0.545108
1,124
10,220
4.846085
0.19395
0.007711
0.040389
0.049569
0.479897
0.449238
0.385717
0.337066
0.29429
0.263815
0
0.00782
0.324364
10,220
248
149
41.209677
0.781028
0.037867
0
0.387255
0
0.009804
0.140865
0.031552
0
0
0
0
0
1
0.014706
false
0
0.04902
0
0.063725
0.04902
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
9ef9c33373ed6286394fc6556d56b0671f5ed0ac
20,610
py
Python
SF-home-price-prediction/src/preparation.py
apthomas/SF-home-price-prediction
448dac93ef26022bc81fab4665a12f592f9556a1
[ "MIT" ]
null
null
null
SF-home-price-prediction/src/preparation.py
apthomas/SF-home-price-prediction
448dac93ef26022bc81fab4665a12f592f9556a1
[ "MIT" ]
null
null
null
SF-home-price-prediction/src/preparation.py
apthomas/SF-home-price-prediction
448dac93ef26022bc81fab4665a12f592f9556a1
[ "MIT" ]
null
null
null
import pandas as pd import numpy as np import csv import urllib.request import json from datetime import datetime from datetime import timedelta from sklearn.preprocessing import MinMaxScaler import web_scrapers import os def load_real_estate_data(filename, state_attr, state): df = pd.read_csv(filename, encoding...
51.654135
214
0.655313
2,771
20,610
4.636232
0.133165
0.037986
0.034561
0.04141
0.621779
0.54612
0.474741
0.415895
0.372616
0.332451
0
0.023631
0.230034
20,610
399
215
51.654135
0.785935
0.050558
0
0.337621
0
0.028939
0.310465
0.045945
0
0
0
0
0
1
0.07074
false
0
0.032154
0
0.163987
0.012862
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
9efa004ed72e268641173fcd54de72edaac3595f
4,858
py
Python
jupyter_book/yaml.py
akhmerov/jupyter-book
06b8134af1266655717df474438bed2569b14efe
[ "BSD-3-Clause" ]
1
2021-04-26T03:21:49.000Z
2021-04-26T03:21:49.000Z
jupyter_book/yaml.py
akhmerov/jupyter-book
06b8134af1266655717df474438bed2569b14efe
[ "BSD-3-Clause" ]
1
2020-08-26T08:27:27.000Z
2020-08-27T18:00:42.000Z
jupyter_book/yaml.py
phaustin/jupyter-book
674b222d44cc1acb858804782cee4549eef03fb1
[ "BSD-3-Clause" ]
null
null
null
"""A small sphinx extension to let you configure a site with YAML metadata.""" from pathlib import Path # Transform a "Jupyter Book" YAML configuration file into a Sphinx configuration file. # This is so that we can choose more user-friendly words for things than Sphinx uses. # e.g., 'logo' instead of 'html_logo'. # ...
37.083969
87
0.628036
564
4,858
5.189716
0.303191
0.065596
0.025965
0.018449
0.011958
0
0
0
0
0
0
0.000551
0.252573
4,858
130
88
37.369231
0.805563
0.182174
0
0.045455
0
0
0.239827
0.024415
0
0
0
0
0
1
0.022727
false
0
0.011364
0
0.045455
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
9efb34b3c08bdbb3ec7a611587c6c1763f510bd0
5,759
py
Python
ScriptedAgent.py
RaphaelRoyerRivard/Supervised-End-to-end-Weight-sharing-for-StarCraft-II
17171fc95c8385920ab7cab80bd4681ce1bff799
[ "Apache-2.0" ]
null
null
null
ScriptedAgent.py
RaphaelRoyerRivard/Supervised-End-to-end-Weight-sharing-for-StarCraft-II
17171fc95c8385920ab7cab80bd4681ce1bff799
[ "Apache-2.0" ]
null
null
null
ScriptedAgent.py
RaphaelRoyerRivard/Supervised-End-to-end-Weight-sharing-for-StarCraft-II
17171fc95c8385920ab7cab80bd4681ce1bff799
[ "Apache-2.0" ]
null
null
null
__author__ = 'Tony Beltramelli - www.tonybeltramelli.com' # scripted agents taken from PySC2, credits to DeepMind # https://github.com/deepmind/pysc2/blob/master/pysc2/agents/scripted_agent.py import numpy as np import uuid from pysc2.agents import base_agent from pysc2.lib import actions from pysc2.lib import featur...
39.445205
133
0.576489
630
5,759
4.944444
0.196825
0.080899
0.044944
0.058427
0.460353
0.415088
0.359872
0.352167
0.352167
0.339647
0
0.007183
0.323146
5,759
145
134
39.717241
0.791945
0.048272
0
0.478992
0
0
0.045471
0.0042
0
0
0
0
0
1
0.042017
false
0
0.042017
0
0.134454
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
9efb77347037fbe157767ce33cce2fb416895aa6
5,602
py
Python
benchmark/test_tpch.py
serverless-analytics/dask-distributed-vanilla
b4b135ee956dbf9e64d10712558a88eafa080675
[ "BSD-3-Clause" ]
null
null
null
benchmark/test_tpch.py
serverless-analytics/dask-distributed-vanilla
b4b135ee956dbf9e64d10712558a88eafa080675
[ "BSD-3-Clause" ]
null
null
null
benchmark/test_tpch.py
serverless-analytics/dask-distributed-vanilla
b4b135ee956dbf9e64d10712558a88eafa080675
[ "BSD-3-Clause" ]
null
null
null
import time import sys import dask from dask.distributed import ( wait, futures_of, Client, ) from tpch import loaddata, queries #from benchmarks import utils # Paths or URLs to the TPC-H tables. #table_paths = { # 'CUSTOMER': 'hdfs://bu-23-115:9000/tpch/customer.tbl', # 'LINEITEM': 'hdfs://bu-...
35.0125
87
0.593181
626
5,602
5.161342
0.209265
0.034045
0.019808
0.027236
0.236459
0.208604
0.16156
0.028474
0
0
0
0.027851
0.250089
5,602
159
88
35.232704
0.741252
0.275794
0
0.056604
0
0
0.17238
0.04918
0
0
0
0
0
1
0.037736
false
0
0.04717
0
0.113208
0.141509
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
9efc2be79705e76de2137bab964886217cb24983
3,582
py
Python
pika/adapters/tornado_connection.py
hugovk/pika
03542ef616a2a849e8bfb0845427f50e741ea0c6
[ "BSD-3-Clause" ]
1
2019-08-28T10:10:56.000Z
2019-08-28T10:10:56.000Z
pika/adapters/tornado_connection.py
goupper/pika
e2f26db4f41ac7ea6bdc50964a766472460dce4a
[ "BSD-3-Clause" ]
null
null
null
pika/adapters/tornado_connection.py
goupper/pika
e2f26db4f41ac7ea6bdc50964a766472460dce4a
[ "BSD-3-Clause" ]
null
null
null
"""Use pika with the Tornado IOLoop """ import logging from tornado import ioloop from pika.adapters.utils import nbio_interface, selector_ioloop_adapter from pika.adapters import base_connection LOGGER = logging.getLogger(__name__) class TornadoConnection(base_connection.BaseConnection): """The TornadoConne...
38.934783
80
0.634283
354
3,582
6.180791
0.319209
0.021938
0.059415
0.034735
0.076782
0.076782
0.076782
0.076782
0.076782
0.076782
0
0
0.308766
3,582
91
81
39.362637
0.883683
0.373534
0
0.041667
0
0
0.035855
0.01277
0
0
0
0
0
1
0.0625
false
0
0.083333
0
0.208333
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
7300c97c38a22ec9df0ea9ea6a865bb5bd5120e7
1,993
py
Python
utilityFiles/createValidationDatasetFromXYTrainWithCandidates.py
jmfinelli/JavaNeuralDecompiler
fb914fcf4518815a4d00061b562617fc25e2f2b4
[ "Apache-2.0" ]
1
2021-06-30T12:50:28.000Z
2021-06-30T12:50:28.000Z
utilityFiles/createValidationDatasetFromXYTrainWithCandidates.py
jmfinelli/JavaNeuralDecompiler
fb914fcf4518815a4d00061b562617fc25e2f2b4
[ "Apache-2.0" ]
null
null
null
utilityFiles/createValidationDatasetFromXYTrainWithCandidates.py
jmfinelli/JavaNeuralDecompiler
fb914fcf4518815a4d00061b562617fc25e2f2b4
[ "Apache-2.0" ]
null
null
null
import pandas as pd import os.path length_switch = True max_body_length = 50 process_candidates = os.path.exists('./datasets/candidates.output') x_train = open('./datasets/x_train').readlines() x_train = [x.rstrip('\n') for x in x_train] y_train = open('./datasets/y_train').readlines() y_train = [x.rstrip('\n') for x...
39.078431
100
0.697441
290
1,993
4.613793
0.227586
0.089686
0.041854
0.057549
0.292227
0.292227
0.260837
0.201046
0.127803
0.127803
0
0.005734
0.124937
1,993
51
101
39.078431
0.761468
0.035625
0
0.052632
0
0
0.218636
0.104112
0
0
0
0
0
1
0
false
0
0.052632
0
0.052632
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
7303f0aa47265452a8086f8bcf4551e8db1e3810
7,746
py
Python
src/Quiet.X.Tests/i2c_test.py
callwyat/Quiet-Firmware
864c210e44d368a4a683704841067717ebc8ac43
[ "MIT" ]
null
null
null
src/Quiet.X.Tests/i2c_test.py
callwyat/Quiet-Firmware
864c210e44d368a4a683704841067717ebc8ac43
[ "MIT" ]
null
null
null
src/Quiet.X.Tests/i2c_test.py
callwyat/Quiet-Firmware
864c210e44d368a4a683704841067717ebc8ac43
[ "MIT" ]
null
null
null
from quiet_coms import find_quiet_ports from quiet import Quiet import time if 'EXIT_ON_FAIL' not in locals(): VERBOSE = True EXIT_ON_FAIL = True class QuietI2C(Quiet): def __init__(self, coms, **kargs) -> None: Quiet.__init__(self, coms, **kargs) def raw_write(self, addr: int, data: bytearra...
29.340909
113
0.631423
1,070
7,746
4.317757
0.162617
0.050216
0.045022
0.048485
0.50974
0.40974
0.334848
0.23658
0.208225
0.158874
0
0.055209
0.235347
7,746
263
114
29.452471
0.724802
0.005293
0
0.363128
0
0.005587
0.214258
0.038956
0
0
0.032723
0
0
1
0.106145
false
0.022346
0.01676
0.005587
0.145251
0.067039
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
7304d96eed7cd6d1a985ffc90a2d6a94ba9983b7
716
py
Python
WEEKS/CD_Sata-Structures/_RESOURCES/python-prac/Overflow/_Data-Structures/binary-tree/binary-tree-tilt.py
webdevhub42/Lambda
b04b84fb5b82fe7c8b12680149e25ae0d27a0960
[ "MIT" ]
5
2021-06-02T23:44:25.000Z
2021-12-27T16:21:57.000Z
WEEKS/CD_Sata-Structures/_RESOURCES/python-prac/Overflow/_Data-Structures/binary-tree/binary-tree-tilt.py
webdevhub42/Lambda
b04b84fb5b82fe7c8b12680149e25ae0d27a0960
[ "MIT" ]
22
2021-05-31T01:33:25.000Z
2021-10-18T18:32:39.000Z
WEEKS/CD_Sata-Structures/_RESOURCES/python-prac/Overflow/_Data-Structures/binary-tree/binary-tree-tilt.py
webdevhub42/Lambda
b04b84fb5b82fe7c8b12680149e25ae0d27a0960
[ "MIT" ]
3
2021-06-19T03:37:47.000Z
2021-08-31T00:49:51.000Z
# Source : https://leetcode.com/problems/binary-tree-tilt/description/ # Date : 2017-12-26 # Definition for a binary tree node. # class TreeNode: # def __init__(self, x): # self.val = x # self.left = None # self.right = None class Solution: def findTilt(self, root): """ ...
21.058824
70
0.540503
84
716
4.559524
0.47619
0.101828
0.133159
0
0
0
0
0
0
0
0
0.021505
0.350559
716
33
71
21.69697
0.802151
0.379888
0
0.142857
0
0
0
0
0
0
0
0
0
1
0.142857
false
0
0
0
0.428571
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
7305e3962fe9733cd02f16a567ab4d4b8d8a9743
7,581
py
Python
kerastuner/engine/tuner_utils.py
krantirk/keras-tuner
fbc34866bf4e7ff1d60bf8c341a9325b9d5429b3
[ "Apache-2.0" ]
1
2019-07-12T17:17:06.000Z
2019-07-12T17:17:06.000Z
kerastuner/engine/tuner_utils.py
nishantsbi/keras-tuner
fbc34866bf4e7ff1d60bf8c341a9325b9d5429b3
[ "Apache-2.0" ]
null
null
null
kerastuner/engine/tuner_utils.py
nishantsbi/keras-tuner
fbc34866bf4e7ff1d60bf8c341a9325b9d5429b3
[ "Apache-2.0" ]
1
2020-01-02T04:07:22.000Z
2020-01-02T04:07:22.000Z
# Copyright 2019 The Keras Tuner Authors # # 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 # # https://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to...
33.544248
78
0.626962
935
7,581
4.856684
0.26738
0.019819
0.02004
0.014975
0.165162
0.084563
0.060339
0.044924
0
0
0
0.007097
0.275162
7,581
225
79
33.693333
0.81929
0.122939
0
0.082278
0
0
0.05248
0
0
0
0
0.004444
0
1
0.126582
false
0
0.082278
0.006329
0.265823
0.006329
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
7307b7da6fb6d2b5a5aa27d12b5f25e31c28bd7c
319
py
Python
write/5_json_writer.py
pavlovprojects/python_qa_test_data
4066f73c83cdd4ace9d6150726a578c0326daf94
[ "MIT" ]
null
null
null
write/5_json_writer.py
pavlovprojects/python_qa_test_data
4066f73c83cdd4ace9d6150726a578c0326daf94
[ "MIT" ]
null
null
null
write/5_json_writer.py
pavlovprojects/python_qa_test_data
4066f73c83cdd4ace9d6150726a578c0326daf94
[ "MIT" ]
null
null
null
import json data = { "users": [ {"Name": "Dominator", "skill": 100, "gold": 99999, "weapons": ['Sword', 'Atomic Laser']}, {"Name": "Looser", "skill": 1, "gold": -100000, "weapons": [None, None, None]}, ] } with open("example.json", "w") as f: s = json.dumps(data, indent=4) f.write(s)
24.538462
97
0.526646
40
319
4.2
0.725
0.095238
0
0
0
0
0
0
0
0
0
0.065041
0.22884
319
12
98
26.583333
0.617886
0
0
0
0
0
0.282132
0
0
0
0
0
0
1
0
false
0
0.1
0
0.1
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
73087bd098e88fc78614d997333c9cb2a9e486e2
1,231
py
Python
Mini Projects/RockPaperScissors/RPS.py
Snowystar122/Python-Projects
faf05ec388030b8b40ad7a8ca5c2760fb62cf5a3
[ "MIT" ]
null
null
null
Mini Projects/RockPaperScissors/RPS.py
Snowystar122/Python-Projects
faf05ec388030b8b40ad7a8ca5c2760fb62cf5a3
[ "MIT" ]
null
null
null
Mini Projects/RockPaperScissors/RPS.py
Snowystar122/Python-Projects
faf05ec388030b8b40ad7a8ca5c2760fb62cf5a3
[ "MIT" ]
null
null
null
import random as r # Sets up required variables running = True user_wins = 0 comp_wins = 0 answers = ["R", "P", "S"] win_combos = ["PR", "RS", "SP"] # Welcome message print("Welcome to Rock-Paper-Scissors. Please input one of the following:" "\n'R' - rock\n'P' - paper\n'S' - scissors\nto get started.") whil...
32.394737
95
0.622258
191
1,231
3.86911
0.429319
0.075778
0.064953
0.086604
0.142084
0.104195
0.073072
0
0
0
0
0.010846
0.251015
1,231
37
96
33.27027
0.790672
0.108042
0
0.148148
0
0.037037
0.37054
0.087832
0
0
0
0
0
1
0
false
0
0.037037
0
0.037037
0.222222
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
730b2987ac65ae096f7d5f37854abcd28bec2bf9
1,147
py
Python
pybullet-gym/pybulletgym/agents/agents_baselines.py
SmaleZ/vcl_diayn
b2c47a681675b405d2011bc4a43c3914f3af4ecc
[ "MIT" ]
2
2021-07-12T17:11:35.000Z
2021-07-13T05:56:30.000Z
pybullet-gym/pybulletgym/agents/agents_baselines.py
SmaleZ/vcl_diayn
b2c47a681675b405d2011bc4a43c3914f3af4ecc
[ "MIT" ]
null
null
null
pybullet-gym/pybulletgym/agents/agents_baselines.py
SmaleZ/vcl_diayn
b2c47a681675b405d2011bc4a43c3914f3af4ecc
[ "MIT" ]
null
null
null
from baselines import deepq def add_opts(parser): pass class BaselinesDQNAgent(object): ''' classdocs ''' def __init__(self, opts): self.metadata = { 'discrete_actions': True, } self.opts = opts self.agent = None def configure(self, observation_space_shape, nb_actions): pass def train(self, ...
20.854545
58
0.691369
163
1,147
4.680982
0.472393
0.058978
0.023591
0
0
0
0
0
0
0
0
0.021575
0.191805
1,147
55
59
20.854545
0.80151
0.007847
0
0.04878
0
0
0.026572
0
0
0
0
0
0
1
0.170732
false
0.04878
0.02439
0
0.219512
0.04878
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
730be722fa533a8220a435fcc4009bd19bbb500f
1,426
py
Python
exploit.py
hexcowboy/CVE-2020-8813
0229d52f8b5adb63cc6d5bc757850a01a7800b8d
[ "MIT" ]
null
null
null
exploit.py
hexcowboy/CVE-2020-8813
0229d52f8b5adb63cc6d5bc757850a01a7800b8d
[ "MIT" ]
null
null
null
exploit.py
hexcowboy/CVE-2020-8813
0229d52f8b5adb63cc6d5bc757850a01a7800b8d
[ "MIT" ]
null
null
null
#!/usr/bin/python3 import requests import click from rich import inspect from rich.console import Console from url_normalize import url_normalize from urllib.parse import quote console = Console() def shell_encode(string): return string.replace(" ", "${IFS}") @click.command() @click.option("-u", "--url", prompt...
31
109
0.680224
190
1,426
5.021053
0.478947
0.037736
0.020964
0.041929
0
0
0
0
0
0
0
0.007011
0.19986
1,426
45
110
31.688889
0.829097
0.099579
0
0
0
0
0.294671
0.024295
0
0
0
0
0
1
0.0625
false
0
0.1875
0.03125
0.28125
0.03125
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
73106dc1db1187afa8a045a4fa929befaa9cbf34
5,939
py
Python
torch/jit/_fuser.py
ljhOfGithub/pytorch
c568f7b16f2a98d72ff5b7c6c6161b67b2c27514
[ "Intel" ]
1
2022-03-29T00:44:31.000Z
2022-03-29T00:44:31.000Z
torch/jit/_fuser.py
ljhOfGithub/pytorch
c568f7b16f2a98d72ff5b7c6c6161b67b2c27514
[ "Intel" ]
null
null
null
torch/jit/_fuser.py
ljhOfGithub/pytorch
c568f7b16f2a98d72ff5b7c6c6161b67b2c27514
[ "Intel" ]
1
2022-03-28T21:49:41.000Z
2022-03-28T21:49:41.000Z
import contextlib import torch from typing import List, Tuple @contextlib.contextmanager def optimized_execution(should_optimize): """ A context manager that controls whether the JIT's executor will run optimizations before executing a function. """ stored_flag = torch._C._get_graph_executor_optim...
42.120567
106
0.706348
826
5,939
4.771186
0.300242
0.045674
0.057092
0.039584
0.292312
0.246384
0.201979
0.135752
0.084496
0.071302
0
0.003241
0.220744
5,939
140
107
42.421429
0.848315
0.38525
0
0.246753
0
0
0.023523
0.007172
0
0
0
0
0.025974
1
0.077922
false
0
0.038961
0.012987
0.168831
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
73111dceec02df0e21147895187850aaff39304f
4,420
py
Python
modlit/db/postgres.py
patdaburu/modlit
9c9c153b74f116357e856e4c204c9a83bb15398f
[ "MIT" ]
null
null
null
modlit/db/postgres.py
patdaburu/modlit
9c9c153b74f116357e856e4c204c9a83bb15398f
[ "MIT" ]
null
null
null
modlit/db/postgres.py
patdaburu/modlit
9c9c153b74f116357e856e4c204c9a83bb15398f
[ "MIT" ]
null
null
null
#!/usr/bin/env python # -*- coding: utf-8 -*- # Created by pat on 5/8/18 """ .. currentmodule:: modlit.db.postgres .. moduleauthor:: Pat Daburu <pat@daburu.net> This module contains utilities for working directly with PostgreSQL. """ import json from pathlib import Path from urllib.parse import urlparse, ParseResult ...
32.262774
79
0.640045
604
4,420
4.610927
0.281457
0.031598
0.01939
0.021544
0.400359
0.357271
0.334291
0.334291
0.289767
0.273968
0
0.00619
0.269005
4,420
136
80
32.5
0.855772
0.465158
0
0.285714
0
0
0.023519
0
0
0
0
0
0
1
0.063492
false
0.015873
0.095238
0
0.206349
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
7311ffda56e787743243c236f69f050e734a7937
22,262
py
Python
parser.py
boshijingang/PyLuaCompiler
37cdf73286d020b2d119635d6d2609a5d9debfed
[ "MIT" ]
null
null
null
parser.py
boshijingang/PyLuaCompiler
37cdf73286d020b2d119635d6d2609a5d9debfed
[ "MIT" ]
null
null
null
parser.py
boshijingang/PyLuaCompiler
37cdf73286d020b2d119635d6d2609a5d9debfed
[ "MIT" ]
null
null
null
import lexer import ast class Parser: block_end_tokens = [lexer.TokenKind.KW_RETURN, lexer.TokenKind.EOF, lexer.TokenKind.KW_END, lexer.TokenKind.KW_ELSE, lexer.TokenKind.KW_ELSEIF, lexer.TokenKind.KW_UNTIL] priority_table = { lexer.TokenKind.OP_ADD: {'l...
42.894027
128
0.620519
2,910
22,262
4.478007
0.066323
0.179418
0.149183
0.103139
0.662113
0.612386
0.542322
0.445323
0.39383
0.351777
0
0.005479
0.262106
22,262
519
129
42.894027
0.787788
0.06729
0
0.353919
0
0
0.014361
0
0
0
0
0
0
1
0.095012
false
0
0.004751
0
0.270784
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
7316876aa79ec9dd6b9b2ee309c9f7ea22776613
5,066
py
Python
usbservo/usbservogui.py
ppfenninger/screwball
c4a7273fa47dac6bdf6fcf8ca29c85a77f9e5bd6
[ "MIT" ]
null
null
null
usbservo/usbservogui.py
ppfenninger/screwball
c4a7273fa47dac6bdf6fcf8ca29c85a77f9e5bd6
[ "MIT" ]
null
null
null
usbservo/usbservogui.py
ppfenninger/screwball
c4a7273fa47dac6bdf6fcf8ca29c85a77f9e5bd6
[ "MIT" ]
null
null
null
# ## Copyright (c) 2018, Bradley A. Minch ## All rights reserved. ## ## Redistribution and use in source and binary forms, with or without ## modification, are permitted provided that the following conditions are met: ## ## 1. Redistributions of source code must retain the above copyright ## notic...
49.666667
153
0.647059
685
5,066
4.654015
0.271533
0.040151
0.040778
0.040778
0.376412
0.317127
0.214555
0.187265
0.169699
0.169699
0
0.033743
0.245361
5,066
101
154
50.158416
0.800157
0.263522
0
0
0
0
0.058101
0
0
0
0
0
0
1
0.125
false
0
0.03125
0
0.171875
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
7318d12083b715d2887f9b7cf5b2559fad4d08c0
6,236
py
Python
pychron/core/helpers/logger_setup.py
aelamspychron/pychron
ad87c22b0817c739c7823a24585053041ee339d5
[ "Apache-2.0" ]
1
2019-02-27T21:57:44.000Z
2019-02-27T21:57:44.000Z
pychron/core/helpers/logger_setup.py
aelamspychron/pychron
ad87c22b0817c739c7823a24585053041ee339d5
[ "Apache-2.0" ]
20
2020-09-09T20:58:39.000Z
2021-10-05T17:48:37.000Z
pychron/core/helpers/logger_setup.py
AGESLDEO/pychron
1a81e05d9fba43b797f335ceff6837c016633bcf
[ "Apache-2.0" ]
null
null
null
# =============================================================================== # Copyright 2011 Jake Ross # # 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...
29.837321
103
0.591725
757
6,236
4.772787
0.348745
0.030999
0.016607
0.008857
0.047606
0.023803
0.023803
0.023803
0
0
0
0.012066
0.255773
6,236
208
104
29.980769
0.76643
0.29923
0
0.084746
0
0.008475
0.028251
0
0
0
0
0
0
1
0.067797
false
0
0.067797
0
0.186441
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
7318f31264c2155178f9f5bd08d307cfd0e1de20
7,980
py
Python
picmodels/models/care_advisors/case_management_models/sequence_models/services/create_update_delete.py
bbcawodu/careadvisors-backend
5ebd3c0fc189b2486cea92b2a13c0bd8a0ee3838
[ "MIT" ]
null
null
null
picmodels/models/care_advisors/case_management_models/sequence_models/services/create_update_delete.py
bbcawodu/careadvisors-backend
5ebd3c0fc189b2486cea92b2a13c0bd8a0ee3838
[ "MIT" ]
null
null
null
picmodels/models/care_advisors/case_management_models/sequence_models/services/create_update_delete.py
bbcawodu/careadvisors-backend
5ebd3c0fc189b2486cea92b2a13c0bd8a0ee3838
[ "MIT" ]
null
null
null
import picmodels def create_row_w_validated_params(cls, validated_params, rqst_errors): if 'name' not in validated_params: rqst_errors.append("'name' is a required key in the validated_params argument") return None if cls.check_for_rows_with_given_name(validated_params['name'], rqst_errors): ...
34.545455
166
0.61817
997
7,980
4.598796
0.101304
0.093784
0.041876
0.032715
0.69422
0.660851
0.633152
0.579498
0.539149
0.529989
0
0.000912
0.313283
7,980
230
167
34.695652
0.835766
0
0
0.578378
0
0.027027
0.130827
0
0
0
0
0
0
1
0.048649
false
0
0.005405
0
0.124324
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
731a5b94603a881cbdad31e6b399fc2db646e99b
4,162
py
Python
elegy/optimizer_test.py
sooheon/elegy
cad6f832cac1a34684c4f4f2c4a386cbfa817623
[ "Apache-2.0" ]
null
null
null
elegy/optimizer_test.py
sooheon/elegy
cad6f832cac1a34684c4f4f2c4a386cbfa817623
[ "Apache-2.0" ]
null
null
null
elegy/optimizer_test.py
sooheon/elegy
cad6f832cac1a34684c4f4f2c4a386cbfa817623
[ "Apache-2.0" ]
null
null
null
import jax import elegy import unittest import numpy as np import jax.numpy as jnp import optax class MLP(elegy.Module): """Standard LeNet-300-100 MLP network.""" n1: int n2: int def __init__(self, n1: int = 3, n2: int = 4): super().__init__() self.n1 = n1 self.n2 = n2 ...
30.602941
88
0.606439
525
4,162
4.670476
0.211429
0.165171
0.107667
0.084829
0.609706
0.590538
0.590538
0.590538
0.590538
0.549755
0
0.03391
0.277271
4,162
135
89
30.82963
0.78125
0.008409
0
0.323232
0
0
0.000971
0
0
0
0
0
0.111111
1
0.060606
false
0
0.060606
0
0.171717
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
731a5f37b2d3af866a1a81886741f91cddda5c09
6,929
py
Python
scripts/version.py
nfnty/docker
cdc68f57fdb6bd472b78d6ef6cbc77f430bd5089
[ "MIT" ]
54
2015-03-08T23:45:21.000Z
2021-01-11T12:35:07.000Z
scripts/version.py
nfnty/docker
cdc68f57fdb6bd472b78d6ef6cbc77f430bd5089
[ "MIT" ]
4
2015-04-10T08:58:29.000Z
2015-11-08T08:34:55.000Z
scripts/version.py
nfnty/docker
cdc68f57fdb6bd472b78d6ef6cbc77f430bd5089
[ "MIT" ]
16
2015-04-08T23:54:07.000Z
2020-04-08T22:03:12.000Z
#!/usr/bin/python3 ''' Check image package versions ''' import argparse import distutils.version import re import subprocess from typing import Any, Dict, Sequence, Tuple import lxml.html # type: ignore import requests from termcolor import cprint from utils.image import IMAGES, path_dockerfile TIMEOUT = (31, 181...
35.533333
97
0.593159
788
6,929
5.142132
0.260152
0.029615
0.048371
0.030602
0.181145
0.133761
0.133761
0.096742
0.074531
0.025173
0
0.011368
0.276375
6,929
194
98
35.716495
0.796769
0.04575
0
0.124138
0
0.006897
0.129136
0
0
0
0
0
0
1
0.048276
false
0
0.062069
0
0.144828
0.062069
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
731bcc2e7423a542f77047dce4151ada325579ea
2,441
py
Python
nazrul.py
rakesh0703/Content_Parser_of_works_of_kazi_nazrul
c3e2060effe7b7576ee5b034a9aba3df648d6358
[ "Apache-2.0" ]
null
null
null
nazrul.py
rakesh0703/Content_Parser_of_works_of_kazi_nazrul
c3e2060effe7b7576ee5b034a9aba3df648d6358
[ "Apache-2.0" ]
null
null
null
nazrul.py
rakesh0703/Content_Parser_of_works_of_kazi_nazrul
c3e2060effe7b7576ee5b034a9aba3df648d6358
[ "Apache-2.0" ]
null
null
null
# -- coding: UTF-8 -- """ Spyder Editor This is a temporary script file. """ from bs4 import BeautifulSoup import sys import os import ssl ssl._create_default_https_context = ssl._create_unverified_context import urllib.parse,urllib.request,urllib.error base="https://nazrul-rachanabali.nltr.org/" page=urllib.request....
29.059524
87
0.530111
329
2,441
3.841945
0.337386
0.038766
0.079114
0.079114
0.223101
0.140823
0.107595
0.107595
0.107595
0.107595
0
0.034024
0.229414
2,441
83
88
29.409639
0.637959
0.179025
0
0.087719
0
0
0.097426
0
0
0
0
0
0
1
0
false
0
0.087719
0
0.087719
0.017544
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
731c7020273e619e347b608e87b47d20ed636f00
3,515
py
Python
core/handler.py
mh4x0f/kinproxy
72dd24eb5ff5286c2bb57524124934a54614f9ec
[ "MIT" ]
5
2018-01-20T15:33:14.000Z
2021-06-29T04:26:44.000Z
core/handler.py
mh4x0f/kinproxy
72dd24eb5ff5286c2bb57524124934a54614f9ec
[ "MIT" ]
null
null
null
core/handler.py
mh4x0f/kinproxy
72dd24eb5ff5286c2bb57524124934a54614f9ec
[ "MIT" ]
1
2019-03-08T18:46:05.000Z
2019-03-08T18:46:05.000Z
try: from mitmproxy import controller, proxy from mitmproxy.proxy.server import ProxyServer except: from libmproxy import controller, proxy from libmproxy.proxy.server import ProxyServer from plugins import * from threading import Thread from core.config.settings import SettingsINI # MIT License # # Co...
33.47619
80
0.657183
426
3,515
5.295775
0.392019
0.039007
0.02305
0.022163
0.054078
0.034574
0.034574
0.034574
0.034574
0.034574
0
0.002663
0.252063
3,515
104
81
33.798077
0.855458
0.406828
0
0.196078
0
0
0.037981
0.010926
0
0
0
0
0
1
0.176471
false
0
0.137255
0
0.352941
0.039216
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
731e4596b4a14f1da0dc95574358cfa12ef495f2
319
py
Python
sandbox/wavelets.py
EtalumaSupport/LumaViewPro
ab9678c04fc561e6fce8b774c5d87cc91d6f3e07
[ "MIT" ]
null
null
null
sandbox/wavelets.py
EtalumaSupport/LumaViewPro
ab9678c04fc561e6fce8b774c5d87cc91d6f3e07
[ "MIT" ]
59
2021-03-26T19:22:59.000Z
2021-12-04T00:42:12.000Z
sandbox/wavelets.py
EtalumaSupport/LumaViewPro
ab9678c04fc561e6fce8b774c5d87cc91d6f3e07
[ "MIT" ]
null
null
null
import numpy as np import matplotlib.pyplot as plt from astropy.convolution import RickerWavelet2DKernel ricker_2d_kernel = RickerWavelet2DKernel(5) plt.imshow(ricker_2d_kernel, interpolation='none', origin='lower') plt.xlabel('x [pixels]') plt.ylabel('y [pixels]') plt.colorbar() plt.show() print(ricker_2d_kernel)
22.785714
66
0.793103
44
319
5.613636
0.636364
0.097166
0.17004
0
0
0
0
0
0
0
0
0.020619
0.087774
319
13
67
24.538462
0.828179
0
0
0
0
0
0.090909
0
0
0
0
0
0
1
0
false
0
0.3
0
0.3
0.1
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
731e657c5103db0d7c66fbe61179c7894a85d4d3
5,267
py
Python
tests/test_errors.py
raymundl/firepit
5b913806eef646c02bd55e301b19baa052aa29d5
[ "Apache-2.0" ]
null
null
null
tests/test_errors.py
raymundl/firepit
5b913806eef646c02bd55e301b19baa052aa29d5
[ "Apache-2.0" ]
null
null
null
tests/test_errors.py
raymundl/firepit
5b913806eef646c02bd55e301b19baa052aa29d5
[ "Apache-2.0" ]
null
null
null
import os import pytest from firepit.exceptions import IncompatibleType from firepit.exceptions import InvalidAttr from firepit.exceptions import InvalidStixPath from firepit.exceptions import InvalidViewname from firepit.exceptions import StixPatternError from .helpers import tmp_storage @pytest.fixture def invali...
35.587838
101
0.652933
693
5,267
4.780664
0.17316
0.087534
0.10987
0.088741
0.617567
0.562934
0.52792
0.51796
0.506791
0.483851
0
0.01912
0.175812
5,267
147
102
35.829932
0.744068
0.007974
0
0.463636
0
0
0.243533
0.011688
0
0
0.001533
0
0.009091
1
0.136364
false
0
0.072727
0
0.218182
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
73212f2cfd8e6dccfeaf70d354cab83a3bcc2ae2
3,059
py
Python
src/urls.py
chunky2808/Hire-Me
7a43fb2f555a5f46e285d24c18457c2ce1c0d225
[ "MIT" ]
null
null
null
src/urls.py
chunky2808/Hire-Me
7a43fb2f555a5f46e285d24c18457c2ce1c0d225
[ "MIT" ]
6
2020-02-12T00:41:15.000Z
2022-03-11T23:20:37.000Z
src/urls.py
chunky2808/Hire-Me
7a43fb2f555a5f46e285d24c18457c2ce1c0d225
[ "MIT" ]
null
null
null
"""src URL Configuration The `urlpatterns` list routes URLs to views. For more information please see: https://docs.djangoproject.com/en/1.11/topics/http/urls/ Examples: Function views 1. Add an import: from my_app import views 2. Add a URL to urlpatterns: url(r'^$', views.home, name='home') Clas...
50.147541
119
0.676038
451
3,059
4.436807
0.228381
0.051974
0.015992
0.032484
0.26087
0.225887
0.17991
0.145927
0.083458
0.083458
0
0.003409
0.136973
3,059
60
120
50.983333
0.754545
0.231121
0
0
0
0
0.33275
0.208406
0
0
0
0
0
1
0
false
0
0.235294
0
0.235294
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
7322d738208c1e92a29dc1677393b7f139a60b9b
1,546
py
Python
re_compare/re_compare.py
gchase/re-compare
c717094053fd5938ea7f0a46dcfec75bc077cb7e
[ "MIT" ]
null
null
null
re_compare/re_compare.py
gchase/re-compare
c717094053fd5938ea7f0a46dcfec75bc077cb7e
[ "MIT" ]
null
null
null
re_compare/re_compare.py
gchase/re-compare
c717094053fd5938ea7f0a46dcfec75bc077cb7e
[ "MIT" ]
null
null
null
#!/usr/bin/env python3 import logging import argparse import traceback import os import sys from analysis import Analysis from collector import Collector from config import DEBUG, DEFAULT_LOG_FILE_DIR def is_dir(dirname): if not os.path.isdir(dirname): msg = "{0} is not a directory".format(dirname) ...
24.539683
82
0.641656
181
1,546
5.287293
0.447514
0.068966
0.053292
0.035528
0.15256
0.079415
0
0
0
0
0
0.001676
0.228331
1,546
62
83
24.935484
0.800503
0.013583
0
0.090909
0
0.022727
0.201444
0.016404
0
0
0
0
0
1
0.045455
false
0
0.181818
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
7323e7284674358cab716226cc5bccd1b52ec055
1,216
py
Python
venv/Lib/site-packages/nipype/conftest.py
richung99/digitizePlots
6b408c820660a415a289726e3223e8f558d3e18b
[ "MIT" ]
585
2015-01-12T16:06:47.000Z
2022-03-26T14:51:08.000Z
nipype/conftest.py
tamires-consulting/nipype
b7879d75a63b6500b2e7d2c3eba5aa7670339274
[ "Apache-2.0" ]
2,329
2015-01-01T09:56:41.000Z
2022-03-30T14:24:49.000Z
nipype/conftest.py
tamires-consulting/nipype
b7879d75a63b6500b2e7d2c3eba5aa7670339274
[ "Apache-2.0" ]
487
2015-01-20T01:04:52.000Z
2022-03-21T21:22:47.000Z
import os import shutil from tempfile import mkdtemp import pytest import numpy import py.path as pp NIPYPE_DATADIR = os.path.realpath( os.path.join(os.path.dirname(__file__), "testing/data") ) temp_folder = mkdtemp() data_dir = os.path.join(temp_folder, "data") shutil.copytree(NIPYPE_DATADIR, data_dir) @pytest....
26.434783
76
0.709704
162
1,216
5.179012
0.506173
0.095352
0.023838
0.047676
0.097735
0.097735
0.097735
0.097735
0
0
0
0.008122
0.189967
1,216
45
77
27.022222
0.843655
0.226151
0
0.137931
0
0
0.042965
0
0
0
0
0
0
1
0.103448
false
0
0.206897
0
0.310345
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
73276ed229a6cddfa545672ed9e4e28191eeb79e
2,939
py
Python
pymbolic/mapper/coefficient.py
sv2518/pymbolic
42687a410b1c355beec510b91c18f97e5137795b
[ "MIT" ]
null
null
null
pymbolic/mapper/coefficient.py
sv2518/pymbolic
42687a410b1c355beec510b91c18f97e5137795b
[ "MIT" ]
null
null
null
pymbolic/mapper/coefficient.py
sv2518/pymbolic
42687a410b1c355beec510b91c18f97e5137795b
[ "MIT" ]
null
null
null
__copyright__ = "Copyright (C) 2013 Andreas Kloeckner" __license__ = """ Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, ...
35.841463
77
0.639673
389
2,939
4.660668
0.365039
0.048538
0.03861
0.054054
0.120243
0.090458
0.069498
0.069498
0
0
0
0.005851
0.302144
2,939
81
78
36.283951
0.878108
0
0
0.171875
0
0
0.367472
0
0
0
0
0
0.015625
1
0.078125
false
0
0.015625
0.015625
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
7328644eaa6b2ec01fefc42231719421b2897b5b
1,958
py
Python
day_06/balancer.py
anglerud/advent_of_code_2017
eff27d43cd9eb7c60271887c80cb88f1ae50c48d
[ "MIT" ]
3
2017-12-06T21:23:19.000Z
2020-04-12T09:49:53.000Z
day_06/balancer.py
anglerud/advent_of_code_2017
eff27d43cd9eb7c60271887c80cb88f1ae50c48d
[ "MIT" ]
null
null
null
day_06/balancer.py
anglerud/advent_of_code_2017
eff27d43cd9eb7c60271887c80cb88f1ae50c48d
[ "MIT" ]
null
null
null
#!/usr/bin/env python # coding: utf-8 """ """ import typing as t import attr import click @attr.s(frozen=True) class Memory(object): banks: t.Tuple[int, ...] = attr.ib() def balance(self) -> 'Memory': mem = list(self.banks) num_banks = len(self.banks) # Find the amount of blocks to ...
23.035294
76
0.62666
250
1,958
4.728
0.38
0.083756
0.063452
0.047377
0.275804
0.241963
0.201354
0.201354
0.201354
0.201354
0
0.006098
0.24617
1,958
84
77
23.309524
0.794715
0.12002
0
0.192308
0
0
0.066627
0
0
0
0
0
0
1
0.115385
false
0.019231
0.057692
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
732ac32a2f056f0d1b4317192e07425ea49f8e2a
1,268
bzl
Python
pw_build/selects.bzl
mspang/pigweed
89ff5f98f38b1ff7a1ff0633c590479e9b592a14
[ "Apache-2.0" ]
null
null
null
pw_build/selects.bzl
mspang/pigweed
89ff5f98f38b1ff7a1ff0633c590479e9b592a14
[ "Apache-2.0" ]
1
2021-06-18T13:54:41.000Z
2021-06-18T13:54:41.000Z
pw_build/selects.bzl
mspang/pigweed
89ff5f98f38b1ff7a1ff0633c590479e9b592a14
[ "Apache-2.0" ]
null
null
null
# Copyright 2021 The Pigweed Authors # # 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 # # https://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in ...
39.625
79
0.729495
180
1,268
4.977778
0.538889
0.066964
0.080357
0.080357
0.107143
0.073661
0
0
0
0
0
0.007526
0.161672
1,268
31
80
40.903226
0.835372
0.745268
0
0
0
0
0.463333
0.263333
0
0
0
0
0
1
0
false
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
732bbfe89e64414c6afc65b3cfb58bb41674d875
2,848
py
Python
leboncrevard/job.py
mclbn/leboncrevard
ee1b2a445eeda8f8561b5c62289b994dff38cfa9
[ "ISC" ]
5
2017-03-14T00:28:13.000Z
2019-02-06T15:38:21.000Z
leboncrevard/job.py
mclbn/leboncrevard
ee1b2a445eeda8f8561b5c62289b994dff38cfa9
[ "ISC" ]
null
null
null
leboncrevard/job.py
mclbn/leboncrevard
ee1b2a445eeda8f8561b5c62289b994dff38cfa9
[ "ISC" ]
5
2017-02-25T07:31:26.000Z
2019-02-06T15:38:27.000Z
import smtplib import time from email.mime.text import MIMEText from leboncrevard import scrapper, config class LbcJob: def __init__(self, name, url, interval, recipients): self.name = name self.url = url self.scrapper = scrapper.LbcScrapper(url) self.interval = interval s...
33.904762
81
0.458567
280
2,848
4.592857
0.378571
0.037325
0.020218
0.026439
0.03888
0
0
0
0
0
0
0.002502
0.438553
2,848
83
82
34.313253
0.801751
0.052669
0
0.084507
0
0
0.08581
0
0
0
0
0
0
1
0.070423
false
0.028169
0.056338
0
0.225352
0.112676
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
732c359d55e1699fb9b02c52c8e5453f0946a5bf
13,825
py
Python
tsl/data/datamodule/splitters.py
TorchSpatiotemporal/tsl
da13493b0cf83826bf41fe78a67e8d4ce1d7a8a0
[ "MIT" ]
4
2022-03-21T09:16:33.000Z
2022-03-30T12:24:30.000Z
tsl/data/datamodule/splitters.py
TorchSpatiotemporal/tsl
da13493b0cf83826bf41fe78a67e8d4ce1d7a8a0
[ "MIT" ]
null
null
null
tsl/data/datamodule/splitters.py
TorchSpatiotemporal/tsl
da13493b0cf83826bf41fe78a67e8d4ce1d7a8a0
[ "MIT" ]
null
null
null
import functools from copy import deepcopy from datetime import datetime from typing import Mapping, Callable, Union, Tuple, Optional import numpy as np from tsl.utils.python_utils import ensure_list from ..spatiotemporal_dataset import SpatioTemporalDataset from ..utils import SynchMode __all__ = [ 'Splitter', ...
34.051724
115
0.650922
1,865
13,825
4.552815
0.135657
0.013426
0.010599
0.010011
0.302202
0.168296
0.119185
0.093982
0.054411
0.032976
0
0.00377
0.251646
13,825
405
116
34.135802
0.816934
0.078626
0
0.169492
0
0
0.026497
0
0
0
0
0
0
1
0.145763
false
0.010169
0.030508
0.044068
0.305085
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
732d71e2f7609d24712a7e6d1541ad6047bd54bf
3,483
py
Python
demo.py
bringBackm/SSD
6cbc9018fd7365d7c65cf6d4da90c14cced5e542
[ "MIT" ]
null
null
null
demo.py
bringBackm/SSD
6cbc9018fd7365d7c65cf6d4da90c14cced5e542
[ "MIT" ]
null
null
null
demo.py
bringBackm/SSD
6cbc9018fd7365d7c65cf6d4da90c14cced5e542
[ "MIT" ]
null
null
null
import glob import os import torch from PIL import Image from tqdm import tqdm from ssd.config import cfg from ssd.data.datasets import COCODataset, VOCDataset from ssd.modeling.predictor import Predictor from ssd.modeling.vgg_ssd import build_ssd_model import argparse import numpy as np from ssd.utils.viz import dra...
35.540816
128
0.669251
453
3,483
4.94702
0.300221
0.032129
0.060687
0.034806
0.065149
0.065149
0.065149
0.065149
0.039268
0
0
0.008416
0.215332
3,483
97
129
35.907216
0.811562
0.039621
0
0.025974
0
0
0.149656
0.018557
0
0
0
0
0
1
0.025974
false
0
0.155844
0
0.181818
0.038961
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
7332ce4b3b7c7b972d457f074400634cb61ce765
5,686
py
Python
scripts/data_creation_v3.py
deepchecks/url_classification_dl
029fddb78e019cf288adcc2fd46be3435536d469
[ "CC0-1.0" ]
3
2021-05-22T09:20:54.000Z
2022-03-14T15:58:17.000Z
scripts/data_creation_v3.py
deepchecks/url_classification_dl
029fddb78e019cf288adcc2fd46be3435536d469
[ "CC0-1.0" ]
1
2021-11-15T11:22:48.000Z
2021-12-11T13:32:19.000Z
scripts/data_creation_v3.py
deepchecks/url_classification_dl
029fddb78e019cf288adcc2fd46be3435536d469
[ "CC0-1.0" ]
6
2021-05-15T17:46:22.000Z
2022-03-24T11:24:59.000Z
import whois from datetime import datetime, timezone import math import pandas as pd import numpy as np from pyquery import PyQuery from requests import get class UrlFeaturizer(object): def __init__(self, url): self.url = url self.domain = url.split('//')[-1].split('/')[0] self.today = date...
29.769634
90
0.536933
667
5,686
4.550225
0.203898
0.033608
0.032619
0.029654
0.185502
0.145634
0.145634
0.114003
0.114003
0.106755
0
0.011397
0.33644
5,686
190
91
29.926316
0.793003
0.010025
0
0.26875
0
0
0.048737
0
0
0
0
0
0
1
0.15
false
0
0.04375
0.025
0.4
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
7333549135a1f86b79763216b9dd3553195359bb
5,175
py
Python
rgnn_at_scale/models/gat.py
sigeisler/robustness_of_gnns_at_scale
0f4844711ace599f54c2abc760b53680a80d6a32
[ "MIT" ]
11
2021-11-01T19:54:41.000Z
2022-01-27T11:34:11.000Z
rgnn_at_scale/models/gat.py
sigeisler/robustness_of_gnns_at_scale
0f4844711ace599f54c2abc760b53680a80d6a32
[ "MIT" ]
1
2021-12-13T21:14:56.000Z
2022-01-16T17:37:36.000Z
rgnn_at_scale/models/gat.py
sigeisler/robustness_of_gnns_at_scale
0f4844711ace599f54c2abc760b53680a80d6a32
[ "MIT" ]
2
2021-11-05T00:42:18.000Z
2022-01-12T10:10:30.000Z
from typing import Any, Dict, Tuple import torch from torch_geometric.nn import GATConv from torch_sparse import SparseTensor, set_diag from rgnn_at_scale.aggregation import ROBUST_MEANS from rgnn_at_scale.models.gcn import GCN class RGATConv(GATConv): """Extension of Pytorch Geometric's `GCNConv` to execute a...
36.443662
119
0.636329
673
5,175
4.695394
0.322437
0.03481
0.020886
0.018987
0.231013
0.215823
0.215823
0.215823
0.215823
0.215823
0
0.007632
0.2657
5,175
141
120
36.702128
0.823947
0.341063
0
0.140625
0
0
0.082517
0
0
0
0
0
0.0625
1
0.078125
false
0.015625
0.09375
0.03125
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
7334d673ab4fa7b6545531cff68878e44e4b4835
902
py
Python
code/renderer/randomize/material.py
jonathangranskog/shading-scene-representations
9c9033a1ca05095c7e2ccfeb4da3046b687bef3d
[ "MIT" ]
21
2020-09-28T10:38:04.000Z
2022-03-12T08:46:09.000Z
code/renderer/randomize/material.py
jonathangranskog/shading-scene-representations
9c9033a1ca05095c7e2ccfeb4da3046b687bef3d
[ "MIT" ]
null
null
null
code/renderer/randomize/material.py
jonathangranskog/shading-scene-representations
9c9033a1ca05095c7e2ccfeb4da3046b687bef3d
[ "MIT" ]
1
2020-12-16T14:56:21.000Z
2020-12-16T14:56:21.000Z
import numpy as np import pyrr import os class Material(): def __init__(self, color=np.ones(3, dtype=np.float32), emission=np.zeros(3, dtype=np.float32), roughness=1.0, ior=15.0, id=0, texture=None, texture_frequency=np.array([1.0, 1.0])): self.color = color self.emission = emission self.ro...
32.214286
184
0.586475
119
902
4.361345
0.319328
0.154143
0.030829
0.057803
0
0
0
0
0
0
0
0.02454
0.277162
902
28
185
32.214286
0.771472
0
0
0
0
0
0.056478
0
0
0
0
0
0
1
0.08
false
0
0.12
0
0.28
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
7335cb0ff48cfe398a0b353de5f1570850d9c8fa
3,752
py
Python
frappe/core/doctype/sms_settings/sms_settings.py
ektai/erp2Dodock
5ad64b01cba9b07437f9a27751101258679379e8
[ "MIT" ]
null
null
null
frappe/core/doctype/sms_settings/sms_settings.py
ektai/erp2Dodock
5ad64b01cba9b07437f9a27751101258679379e8
[ "MIT" ]
null
null
null
frappe/core/doctype/sms_settings/sms_settings.py
ektai/erp2Dodock
5ad64b01cba9b07437f9a27751101258679379e8
[ "MIT" ]
null
null
null
# -*- coding: utf-8 -*- # Copyright (c) 2015, Frappe Technologies Pvt. Ltd. and Contributors # License: GNU General Public License v3. See license.txt from __future__ import unicode_literals import frappe from frappe import _, throw, msgprint from frappe.utils import nowdate from frappe.model.document import Documen...
27.188406
98
0.711354
544
3,752
4.691176
0.279412
0.094044
0.032915
0.028213
0.094044
0.054075
0.032132
0.032132
0
0
0
0.006534
0.14339
3,752
138
99
27.188406
0.787492
0.074627
0
0.04902
0
0
0.166096
0
0
0
0
0
0
1
0.068627
false
0.009804
0.088235
0
0.205882
0.029412
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
73360c2d69e50730324e4dc6677481e54cc8e26d
1,850
py
Python
tardis/model/tests/test_csvy_model.py
Youssef15015/tardis
adde5b0114f23634fe5afef6937b285174ad6b55
[ "BSD-3-Clause" ]
null
null
null
tardis/model/tests/test_csvy_model.py
Youssef15015/tardis
adde5b0114f23634fe5afef6937b285174ad6b55
[ "BSD-3-Clause" ]
2
2019-06-10T11:24:50.000Z
2019-06-18T17:28:59.000Z
tardis/model/tests/test_csvy_model.py
Youssef15015/tardis
adde5b0114f23634fe5afef6937b285174ad6b55
[ "BSD-3-Clause" ]
1
2019-06-10T10:21:41.000Z
2019-06-10T10:21:41.000Z
import numpy as np import numpy.testing as npt import tardis import os from astropy import units as u from tardis.io.config_reader import Configuration from tardis.model import Radial1DModel import pytest DATA_PATH = os.path.join(tardis.__path__[0],'model','tests','data') @pytest.fixture(scope="module", params=['conf...
44.047619
107
0.682162
235
1,850
4.957447
0.276596
0.122747
0.08412
0.061803
0.256652
0.103863
0.103863
0.103863
0.072103
0
0
0.007102
0.238919
1,850
41
108
45.121951
0.820313
0
0
0
0
0
0.113095
0.079004
0
0
0
0
0.114286
1
0.057143
false
0
0.228571
0.028571
0.314286
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
73391ce9c005d2972ce3d22ec1870d858657b9ce
34,911
py
Python
wepppy/taudem/topaz_emulator.py
hwbeeson/wepppy
6358552df99853c75be8911e7ef943108ae6923e
[ "BSD-3-Clause" ]
null
null
null
wepppy/taudem/topaz_emulator.py
hwbeeson/wepppy
6358552df99853c75be8911e7ef943108ae6923e
[ "BSD-3-Clause" ]
null
null
null
wepppy/taudem/topaz_emulator.py
hwbeeson/wepppy
6358552df99853c75be8911e7ef943108ae6923e
[ "BSD-3-Clause" ]
null
null
null
from typing import List import os import json from os.path import join as _join from os.path import exists as _exists import math from osgeo import gdal, osr import numpy as np from scipy.ndimage import label from subprocess import Popen, PIPE from pprint import pprint from wepppy.all_your_base.geo import read_tif...
37.619612
120
0.540661
4,038
34,911
4.455176
0.129767
0.011506
0.013341
0.005058
0.328849
0.2408
0.186882
0.175875
0.13274
0.105281
0
0.013155
0.359829
34,911
927
121
37.660194
0.791803
0.105669
0
0.252366
0
0
0.04188
0.00158
0
0
0
0.002158
0.015773
1
0.056782
false
0.004732
0.023659
0.01735
0.116719
0.01735
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
733a0eff21e557f8f32c9d92815d4f668db0c2d8
47,930
py
Python
PyRSM/utils.py
chdahlqvist/RSMmap
53984967d612eaf4feb90ba4972109638f6cf70a
[ "MIT" ]
3
2021-05-18T16:40:13.000Z
2022-03-17T15:32:31.000Z
PyRSM/utils.py
chdahlqvist/RSMmap
53984967d612eaf4feb90ba4972109638f6cf70a
[ "MIT" ]
null
null
null
PyRSM/utils.py
chdahlqvist/RSMmap
53984967d612eaf4feb90ba4972109638f6cf70a
[ "MIT" ]
1
2022-01-19T11:04:21.000Z
2022-01-19T11:04:21.000Z
""" Set of functions used by the PyRSM class to compute detection maps and optimize the parameters of the RSM algorithm and PSF-subtraction techniques via the auto-RSM and auto-S/N frameworks """ __author__ = 'Carl-Henrik Dahlqvist' from scipy.interpolate import Rbf import pandas as pd import numpy.linalg as la from v...
38.590982
242
0.614542
6,641
47,930
4.223611
0.107363
0.019894
0.00984
0.008984
0.526436
0.490677
0.428037
0.378873
0.350743
0.332775
0
0.0151
0.287023
47,930
1,241
243
38.622079
0.805695
0.202671
0
0.359331
0
0
0.039688
0
0
0
0
0
0
1
0.033426
false
0.001393
0.023677
0
0.097493
0.018106
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
733a51b0598b93f7ddad878e61c9f58e36f463d6
4,618
py
Python
src/custom_dataset.py
devJWSong/transformer-multiturn-dialogue-pytorch
4ddedaef45f31d75e88bdb909a4451173faec4c8
[ "MIT" ]
11
2021-03-22T10:22:42.000Z
2021-09-15T23:50:46.000Z
src/custom_dataset.py
devjwsong/transformer-chatbot-pytorch
4ddedaef45f31d75e88bdb909a4451173faec4c8
[ "MIT" ]
1
2021-12-10T04:52:39.000Z
2021-12-10T04:52:40.000Z
src/custom_dataset.py
devjwsong/transformer-chatbot-pytorch
4ddedaef45f31d75e88bdb909a4451173faec4c8
[ "MIT" ]
null
null
null
from torch.utils.data import Dataset from tqdm import tqdm import torch import pickle import json class CustomDataset(Dataset): def __init__(self, args, tokenizer, data_type): assert data_type in ["train", "valid", "test"] print(f"Loading {data_type} data...") with open(f"{args.t...
38.483333
129
0.529017
580
4,618
3.968966
0.201724
0.078193
0.047785
0.02954
0.219809
0.16073
0.128584
0.046916
0.046916
0.046916
0
0.007473
0.362495
4,618
120
130
38.483333
0.774457
0.038545
0
0.045455
0
0
0.052121
0.019404
0
0
0
0
0.056818
1
0.079545
false
0
0.056818
0.022727
0.215909
0.068182
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
733b44cae4895b7b97c2632f68beb2990e9371cb
370
py
Python
benchmark_python_lkml.py
Ladvien/rust_lookml_parser
a99a9663f2e0ccd0e7eff0fb6ec4f4496032265c
[ "MIT" ]
null
null
null
benchmark_python_lkml.py
Ladvien/rust_lookml_parser
a99a9663f2e0ccd0e7eff0fb6ec4f4496032265c
[ "MIT" ]
null
null
null
benchmark_python_lkml.py
Ladvien/rust_lookml_parser
a99a9663f2e0ccd0e7eff0fb6ec4f4496032265c
[ "MIT" ]
null
null
null
import lkml from time import time_ns from rich import print FILE_PATH = "/Users/ladvien/rusty_looker/src/resources/test.lkml" with open(FILE_PATH, "r") as f: lookml = f.read() startTime = time_ns() // 1_000_000 result = lkml.load(lookml) print(result) executionTime = (time_ns() // 1_000_000) - startTime print('...
26.428571
65
0.735135
57
370
4.596491
0.578947
0.068702
0.053435
0.076336
0.099237
0
0
0
0
0
0
0.043887
0.137838
370
14
66
26.428571
0.777429
0
0
0
0
0
0.212938
0.137466
0
0
0
0
0
1
0
false
0
0.272727
0
0.272727
0.272727
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
733c41f200ce9ccff635234faca97343a23e5190
1,595
py
Python
Linear_Regression.py
svdeepak99/TSA-Twitter_Sentiment_Analysis
41c13682ccc110025c5fbd396c0982d54febc6cc
[ "MIT" ]
null
null
null
Linear_Regression.py
svdeepak99/TSA-Twitter_Sentiment_Analysis
41c13682ccc110025c5fbd396c0982d54febc6cc
[ "MIT" ]
null
null
null
Linear_Regression.py
svdeepak99/TSA-Twitter_Sentiment_Analysis
41c13682ccc110025c5fbd396c0982d54febc6cc
[ "MIT" ]
null
null
null
from keras.models import Sequential, load_model from keras.layers import Dense import csv import numpy as np import os LOAD_MODEL = False with open("Linear_Regression/Normalized_Attributes.csv", "r", newline='') as fp: reader = csv.reader(fp) headings = next(reader) dataset = np.array(list(read...
32.55102
116
0.680251
238
1,595
4.466387
0.344538
0.09031
0.039511
0.067733
0.19285
0.19285
0.088429
0.060207
0.060207
0
0
0.023478
0.145455
1,595
48
117
33.229167
0.75642
0
0
0.055556
0
0
0.208145
0.155139
0
0
0
0
0
1
0
false
0
0.138889
0
0.138889
0.166667
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
733c8d8b8ea4cf5eaafe8785802f0c3c067c38ff
3,141
py
Python
UserCode/bressler/multibubblescintillationcheck.py
cericdahl/SBCcode
90a7841a5c1208d64f71a332289d9005a011aa21
[ "MIT" ]
4
2018-08-27T18:02:34.000Z
2020-06-09T21:19:04.000Z
UserCode/bressler/multibubblescintillationcheck.py
SBC-Collaboration/SBC-Analysis
90a7841a5c1208d64f71a332289d9005a011aa21
[ "MIT" ]
null
null
null
UserCode/bressler/multibubblescintillationcheck.py
SBC-Collaboration/SBC-Analysis
90a7841a5c1208d64f71a332289d9005a011aa21
[ "MIT" ]
4
2019-06-20T21:36:26.000Z
2020-11-10T17:23:14.000Z
#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Tue Mar 2 19:33:02 2021 @author: bressler """ import SBCcode as sbc import numpy as np import pulse_integrator as pi import gc def check_multibub_scintillation(run, event, at0, PMTgain, PMTwindow): tstart = PMTwindow[0] t_end= PMTwindow[1] sc...
36.523256
97
0.539
391
3,141
4.230179
0.421995
0.006046
0.018138
0.022975
0.102781
0.055623
0.055623
0
0
0
0
0.035173
0.348297
3,141
86
98
36.523256
0.772838
0.155365
0
0.042553
0
0
0.096686
0.030413
0
0
0
0
0
1
0.042553
false
0
0.085106
0
0.148936
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
733e97b6658e7e2eb8c13752d62cc0a274acaa1f
1,533
py
Python
ceibacli/job_schedulers/slurm.py
cffbots/ceiba-cli
7e77199c1fe919f024c4707b65578fec320713a6
[ "Apache-2.0" ]
2
2020-11-10T08:52:15.000Z
2020-11-10T08:52:17.000Z
ceibacli/job_schedulers/slurm.py
cffbots/ceiba-cli
7e77199c1fe919f024c4707b65578fec320713a6
[ "Apache-2.0" ]
24
2020-09-22T09:58:38.000Z
2021-01-14T11:02:33.000Z
ceibacli/job_schedulers/slurm.py
cffbots/ceiba-cli
7e77199c1fe919f024c4707b65578fec320713a6
[ "Apache-2.0" ]
1
2022-02-03T13:46:07.000Z
2022-02-03T13:46:07.000Z
"""Interface to the `SLURM job scheduler <https://slurm.schedmd.com/documentation.html>`_ .. autofunction:: create_slurm_script """ from pathlib import Path from typing import Any, Dict, List from ..utils import Options def create_slurm_script(opts: Options, jobs: List[Dict[str, Any]], jobs_metadata: List[Options]...
29.480769
104
0.666014
203
1,533
4.931034
0.428571
0.032967
0.044955
0.033966
0
0
0
0
0
0
0
0
0.209393
1,533
51
105
30.058824
0.825908
0.242661
0
0
0
0
0.19106
0.048203
0
0
0
0
0
1
0.071429
false
0
0.107143
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
733ee42203016605540515b9f13fedcc898ddec0
5,290
py
Python
thumbor/url.py
wking/thumbor
97a55594a67e3cf3b5e7d09cde5944bc821eeb1e
[ "MIT" ]
null
null
null
thumbor/url.py
wking/thumbor
97a55594a67e3cf3b5e7d09cde5944bc821eeb1e
[ "MIT" ]
null
null
null
thumbor/url.py
wking/thumbor
97a55594a67e3cf3b5e7d09cde5944bc821eeb1e
[ "MIT" ]
null
null
null
#!/usr/bin/python # -*- coding: utf-8 -*- # thumbor imaging service # https://github.com/thumbor/thumbor/wiki # Licensed under the MIT license: # http://www.opensource.org/licenses/mit-license # Copyright (c) 2011 globo.com timehome@corp.globo.com import re from urllib import quote class Url(object): unsafe_o...
31.117647
119
0.479017
579
5,290
4.24525
0.188256
0.043938
0.058584
0.029292
0.065907
0.03987
0.020342
0.020342
0
0
0
0.004399
0.355388
5,290
169
120
31.301775
0.716422
0.04518
0
0.045455
0
0.022727
0.19413
0.098156
0
0
0
0
0
1
0.030303
false
0
0.015152
0.007576
0.189394
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
73401ec9a9c7c85f7251558930f267232a9f7bb1
3,275
py
Python
blackjack/game.py
cuiqui/blackjack
5ecb0ae1c065fa284c2209222f6f958e1f514249
[ "MIT" ]
null
null
null
blackjack/game.py
cuiqui/blackjack
5ecb0ae1c065fa284c2209222f6f958e1f514249
[ "MIT" ]
null
null
null
blackjack/game.py
cuiqui/blackjack
5ecb0ae1c065fa284c2209222f6f958e1f514249
[ "MIT" ]
null
null
null
import constants as c from deck import Deck from player import Human, RandomAI class Game: def __init__(self): self.deck = None self.players = None self.scores = None self.rounds_left = None self.game_over = False def new(self): self.game_over = F...
31.490385
102
0.487328
386
3,275
4.059585
0.300518
0.051053
0.044671
0.021698
0.028079
0
0
0
0
0
0
0.006817
0.41771
3,275
103
103
31.796117
0.814893
0.164275
0
0.115942
0
0.014493
0.097021
0
0
0
0
0
0
1
0.101449
false
0
0.043478
0
0.173913
0.086957
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