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
9ba44cd9d91cc8c729aafc0cddc794fc2187f3f9
25,015
py
Python
lizardanalysis/calculations/aep_pep_test.py
JojoReikun/ClimbingLizardDLCAnalysis
6cc38090217a3ffd4860ef6d06ba7967d3c10b7c
[ "MIT" ]
1
2021-03-09T19:12:44.000Z
2021-03-09T19:12:44.000Z
lizardanalysis/calculations/aep_pep_test.py
JojoReikun/ClimbingLizardDLCAnalysis
6cc38090217a3ffd4860ef6d06ba7967d3c10b7c
[ "MIT" ]
null
null
null
lizardanalysis/calculations/aep_pep_test.py
JojoReikun/ClimbingLizardDLCAnalysis
6cc38090217a3ffd4860ef6d06ba7967d3c10b7c
[ "MIT" ]
null
null
null
def aep_pep_test(**kwargs): """ Calculates two different things: 1.) The x and y coordinates of the AEP and PEP, relative to the coxa of a respective leg 2.) The swing phases and the stance phases, identifying on a frame by frame basis Return: results data frame with 30 key value pairs: x6 all...
49.534653
136
0.625625
3,469
25,015
4.327472
0.163159
0.025313
0.013056
0.013589
0.355582
0.298428
0.252864
0.210631
0.17526
0.161338
0
0.011959
0.267959
25,015
504
137
49.632937
0.807831
0.318729
0
0.229323
0
0
0.092941
0.021352
0
0
0
0.003968
0
1
0.026316
false
0.041353
0.078947
0.003759
0.12782
0.003759
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
9ba99aa02744fe90eebce52ab7ecf4ce0854c775
1,367
py
Python
Medium/918. Maximum Sum Circular Subarray/solution (1).py
czs108/LeetCode-Solutions
889f5b6a573769ad077a6283c058ed925d52c9ec
[ "MIT" ]
3
2020-05-09T12:55:09.000Z
2022-03-11T18:56:05.000Z
Medium/918. Maximum Sum Circular Subarray/solution (1).py
czs108/LeetCode-Solutions
889f5b6a573769ad077a6283c058ed925d52c9ec
[ "MIT" ]
null
null
null
Medium/918. Maximum Sum Circular Subarray/solution (1).py
czs108/LeetCode-Solutions
889f5b6a573769ad077a6283c058ed925d52c9ec
[ "MIT" ]
1
2022-03-11T18:56:16.000Z
2022-03-11T18:56:16.000Z
# 918. Maximum Sum Circular Subarray # Runtime: 1028 ms, faster than 5.09% of Python3 online submissions for Maximum Sum Circular Subarray. # Memory Usage: 18.6 MB, less than 33.98% of Python3 online submissions for Maximum Sum Circular Subarray. import math class Solution: def maxSubarraySumCircular(self, num...
35.973684
106
0.567666
199
1,367
3.683417
0.266332
0.098226
0.081855
0.106412
0.3397
0.298772
0.236016
0.210096
0.210096
0.060027
0
0.036677
0.321873
1,367
38
107
35.973684
0.754045
0.175567
0
0.16
0
0
0
0
0
0
0
0
0
1
0.12
false
0
0.04
0
0.32
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
9ba9d75f770e59ab5f8bd4c1745fa1e171a92981
10,644
py
Python
testing.py
gustxsr/learning-with-assemblies
4158829adf4500a9ae868ca7c64ffef90753c66b
[ "MIT" ]
null
null
null
testing.py
gustxsr/learning-with-assemblies
4158829adf4500a9ae868ca7c64ffef90753c66b
[ "MIT" ]
null
null
null
testing.py
gustxsr/learning-with-assemblies
4158829adf4500a9ae868ca7c64ffef90753c66b
[ "MIT" ]
null
null
null
import numpy as np import matplotlib.pyplot as plt from scipy.signal import convolve from matplotlib.gridspec import GridSpec import matplotlib as mpl rng = np.random.default_rng() def k_cap(input, cap_size): """ Given a vector input it returns the highest cap_size entries from cap_zie ...
37.087108
217
0.613209
1,541
10,644
4.079169
0.162881
0.031817
0.043907
0.015272
0.312281
0.288419
0.221444
0.200127
0.165447
0.156857
0
0.018678
0.280722
10,644
286
218
37.216783
0.802377
0.24643
0
0.12987
0
0
0.011966
0.007313
0
0
0
0
0
1
0.097403
false
0
0.032468
0
0.194805
0.025974
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
9bab281692147103f4b861c83d053ce8c6a1c16f
4,398
py
Python
src/chatstats.py
brendancsmith/cohort-facebook
a7b37d14b7152349930bc10f69cb72446d6c3581
[ "MIT" ]
null
null
null
src/chatstats.py
brendancsmith/cohort-facebook
a7b37d14b7152349930bc10f69cb72446d6c3581
[ "MIT" ]
null
null
null
src/chatstats.py
brendancsmith/cohort-facebook
a7b37d14b7152349930bc10f69cb72446d6c3581
[ "MIT" ]
null
null
null
from collections import Counter, defaultdict from datetime import datetime from statistics import mean from dateutil.parser import parse as parse_datetime from dateutil import rrule def num_comments_by_user(comments): commenters = (comment['from']['name'] for comment in comments) counter = Counter(commenters...
29.918367
91
0.648931
463
4,398
6.023758
0.226782
0.03227
0.038724
0.064539
0.260308
0.236285
0.199355
0.199355
0.199355
0.15848
0
0.001237
0.264666
4,398
146
92
30.123288
0.861163
0.013643
0
0.268041
0
0
0.028598
0
0
0
0
0.006849
0
1
0.092784
false
0
0.051546
0
0.237113
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
9bae71f7a1d534c3b03ab7c28df3edc847994f0b
2,125
py
Python
utils/lsms/compositional_histogram_cutoff.py
allaffa/HydraGNN
b48f75cd3fe1b0d03bae9af3e6bdc2bb29f8b9c6
[ "BSD-3-Clause" ]
1
2022-01-30T16:50:51.000Z
2022-01-30T16:50:51.000Z
utils/lsms/compositional_histogram_cutoff.py
allaffa/HydraGNN
b48f75cd3fe1b0d03bae9af3e6bdc2bb29f8b9c6
[ "BSD-3-Clause" ]
1
2022-02-03T11:45:53.000Z
2022-02-09T17:59:37.000Z
utils/lsms/compositional_histogram_cutoff.py
kshitij-v-mehta/HydraGNN
d27958270b2beb35f98e4403239e3c5c77ad4a04
[ "BSD-3-Clause" ]
null
null
null
import os import shutil import numpy as np from tqdm import tqdm import matplotlib.pyplot as plt def find_bin(comp, nbins): bins = np.linspace(0, 1, nbins) for bi in range(len(bins) - 1): if comp > bins[bi] and comp < bins[bi + 1]: return bi return nbins - 1 def compositional_histogr...
27.960526
91
0.610353
289
2,125
4.346021
0.363322
0.071656
0.017516
0.019108
0.028662
0
0
0
0
0
0
0.011251
0.288941
2,125
75
92
28.333333
0.819987
0.091294
0
0
0
0
0.066353
0.028736
0
0
0
0
0
1
0.035714
false
0
0.089286
0
0.178571
0.017857
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
9bb0067ad50b3ebfd94976cc78cce86faed75925
1,256
py
Python
PointMatcher/actions/export.py
daisatojp/PointMatcher
927bd4dd676b18da763ccaab2f429f27de281710
[ "MIT" ]
2
2021-01-05T03:42:50.000Z
2022-03-16T07:17:02.000Z
PointMatcher/actions/export.py
daisatojp/PointMatcher
927bd4dd676b18da763ccaab2f429f27de281710
[ "MIT" ]
4
2021-01-07T06:28:01.000Z
2021-01-18T11:59:56.000Z
PointMatcher/actions/export.py
daisatojp/PointMatcher
927bd4dd676b18da763ccaab2f429f27de281710
[ "MIT" ]
null
null
null
import os.path as osp from PyQt5.QtGui import QIcon from PyQt5.QtWidgets import QAction from PyQt5.QtWidgets import QFileDialog from PointMatcher.utils.filesystem import icon_path class ExportAction(QAction): def __init__(self, parent): super(ExportAction, self).__init__('Export', parent) self.p ...
35.885714
75
0.642516
149
1,256
5.342282
0.442953
0.069095
0.048995
0.060302
0.065327
0.065327
0.065327
0.065327
0
0
0
0.004242
0.249204
1,256
34
76
36.941176
0.839873
0
0
0
0
0
0.071656
0
0
0
0
0
0
1
0.068966
false
0
0.172414
0
0.275862
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
9bb514fb57dd5b2a6965770909c4eb7274835dca
3,453
py
Python
secistsploit/modules/auxiliary/whatweb.py
reneaicisneros/SecistSploit
b4e1bb0a213bee39c3bb79ab36e03e19122b80c0
[ "MIT" ]
15
2018-12-06T16:03:32.000Z
2021-06-23T01:17:00.000Z
secistsploit/modules/auxiliary/whatweb.py
reneaicisneros/SecistSploit
b4e1bb0a213bee39c3bb79ab36e03e19122b80c0
[ "MIT" ]
null
null
null
secistsploit/modules/auxiliary/whatweb.py
reneaicisneros/SecistSploit
b4e1bb0a213bee39c3bb79ab36e03e19122b80c0
[ "MIT" ]
6
2019-03-01T04:10:00.000Z
2020-02-26T08:43:54.000Z
# -*- coding: UTF-8 -*- import os from secistsploit.core.exploit import * from secistsploit.core.http.http_client import HTTPClient class Exploit(HTTPClient): __info__ = { "name": "whatweb", "description": "whatweb", "authors": ( "jjiushi", ), "references": ( ...
34.188119
141
0.435274
316
3,453
4.708861
0.35443
0.020161
0.032258
0.046371
0.561828
0.538978
0.538978
0.538978
0.479839
0.479839
0
0.059175
0.417608
3,453
100
142
34.53
0.680756
0.006082
0
0.444444
0
0.033333
0.254811
0.013411
0
0
0
0
0
1
0.022222
false
0
0.044444
0
0.144444
0.088889
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
9bb942cefeb3547baf593097bb2c4998d052f1b8
3,285
py
Python
pygnss/__init__.py
nmerlene/pygnss
9dc59e57cf5a4bdf0ca56c2b6a23d622ffda4c5a
[ "MIT" ]
null
null
null
pygnss/__init__.py
nmerlene/pygnss
9dc59e57cf5a4bdf0ca56c2b6a23d622ffda4c5a
[ "MIT" ]
null
null
null
pygnss/__init__.py
nmerlene/pygnss
9dc59e57cf5a4bdf0ca56c2b6a23d622ffda4c5a
[ "MIT" ]
null
null
null
from pathlib import Path import logging import xarray from time import time from typing import Union # from .io import opener from .rinex2 import rinexnav2, _scan2 from .rinex3 import rinexnav3, _scan3 # for NetCDF compression. too high slows down with little space savings. COMPLVL = 1 def readrinex(rinexfn: Path, o...
28.318966
120
0.595129
449
3,285
4.329621
0.302895
0.018519
0.010802
0.030864
0.388889
0.375514
0.350823
0.290123
0.220165
0.175926
0
0.010879
0.272451
3,285
115
121
28.565217
0.80251
0.094977
0
0.4125
0
0
0.116541
0
0
0
0
0
0
1
0.05
false
0
0.1
0
0.25
0.0375
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
9bb96ea949af7533581d8e4cca76f381e779a9b0
5,201
py
Python
classroom/pref_graph.py
norabelrose/whisper
79642bab696f3e166b6af61a447602e8e5d58270
[ "MIT" ]
null
null
null
classroom/pref_graph.py
norabelrose/whisper
79642bab696f3e166b6af61a447602e8e5d58270
[ "MIT" ]
null
null
null
classroom/pref_graph.py
norabelrose/whisper
79642bab696f3e166b6af61a447602e8e5d58270
[ "MIT" ]
null
null
null
from typing import TYPE_CHECKING import networkx as nx from .fas import eades_fas if TYPE_CHECKING: # Prevent circular import from .pref_dag import PrefDAG class PrefGraph(nx.DiGraph): """ `PrefGraph` represents a possibly cyclic set of preferences over clips as a weighted directed graph. Edge weigh...
42.284553
104
0.635455
715
5,201
4.513287
0.283916
0.006817
0.012395
0.013945
0.206384
0.159281
0.111559
0.076852
0.056399
0.056399
0
0.007368
0.269371
5,201
122
105
42.631148
0.841842
0.344357
0
0.232877
0
0
0.077065
0.010132
0
0
0
0
0
1
0.164384
false
0.013699
0.068493
0
0.383562
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
9bbcdfbd01a5563f9c4786b31c8c24dcfa3b565b
683
py
Python
hisitter/reviews/permissions.py
babysitter-finder/backend
5c37c6876ca13b5794ac44e0342b810426acbc76
[ "MIT" ]
1
2021-02-25T01:02:40.000Z
2021-02-25T01:02:40.000Z
hisitter/reviews/permissions.py
babysitter-finder/backend
5c37c6876ca13b5794ac44e0342b810426acbc76
[ "MIT" ]
null
null
null
hisitter/reviews/permissions.py
babysitter-finder/backend
5c37c6876ca13b5794ac44e0342b810426acbc76
[ "MIT" ]
1
2020-11-23T20:57:47.000Z
2020-11-23T20:57:47.000Z
""" Reviews permissions.""" # Python import logging # Django Rest Framework from rest_framework.permissions import BasePermission class IsServiceOwner(BasePermission): """ This permission allow determine if the user is a client, if not permission is denied. """ def has_permission(self, request,...
28.458333
75
0.628111
79
683
5.379747
0.594937
0.061176
0.042353
0.051765
0.084706
0.084706
0
0
0
0
0
0
0.297218
683
23
76
29.695652
0.885417
0.2694
0
0
0
0
0.098925
0
0
0
0
0
0
1
0.083333
false
0
0.166667
0
0.5
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
9bbd9c4b8b498fde19563e3848c89d37d52b9838
1,678
py
Python
pk.py
CnybTseng/SOSNet
9f1e96380388dde75fe0737ec0b3516669054205
[ "MIT" ]
null
null
null
pk.py
CnybTseng/SOSNet
9f1e96380388dde75fe0737ec0b3516669054205
[ "MIT" ]
null
null
null
pk.py
CnybTseng/SOSNet
9f1e96380388dde75fe0737ec0b3516669054205
[ "MIT" ]
null
null
null
import sys import torch import timeit sys.path.append('../JDE') from mot.models.backbones import ShuffleNetV2 from sosnet import SOSNet if __name__ == '__main__': print('SOSNet PK ShuffleNetV2') model1 = ShuffleNetV2( stage_repeat={'stage2': 4, 'stage3': 8, 'stage4': 4}, stage_out_ch...
37.288889
85
0.567342
198
1,678
4.671717
0.409091
0.071351
0.077838
0.048649
0.372973
0.372973
0.372973
0.372973
0.372973
0.372973
0
0.056106
0.277712
1,678
45
86
37.288889
0.707096
0
0
0.363636
0
0
0.159021
0
0
0
0
0
0
1
0
false
0
0.113636
0
0.113636
0.136364
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
9bbda2f39a11084b661e8fe58491f418c2a36b6f
2,255
py
Python
test/generate_netmhcpan_functions.py
til-unc/mhcgnomes
0bfbe193daeb7cd38d958222f6071dd657e9fb6e
[ "Apache-2.0" ]
6
2020-10-27T15:31:32.000Z
2020-11-29T03:26:06.000Z
test/generate_netmhcpan_functions.py
til-unc/mhcgnomes
0bfbe193daeb7cd38d958222f6071dd657e9fb6e
[ "Apache-2.0" ]
4
2020-10-27T14:57:16.000Z
2020-11-04T21:56:39.000Z
test/generate_netmhcpan_functions.py
pirl-unc/mhcgnomes
0bfbe193daeb7cd38d958222f6071dd657e9fb6e
[ "Apache-2.0" ]
null
null
null
import pandas as pd NETMHCPAN_3_0_DEST = "test_netmhcpan_3_0_alleles.py" NETMHCPAN_3_0_SOURCE = "netmhcpan_3_0_alleles.txt" NETMHCPAN_4_0_DEST = "test_netmhcpan_4_0_alleles.py" NETMHCPAN_4_0_SOURCE = "netmhcpan_4_0_alleles.txt" special_chars = " *:-,/." def generate(src, dst, exclude=set()): alleles = set() ...
35.234375
107
0.501552
247
2,255
4.267206
0.291498
0.094877
0.083491
0.068311
0.098672
0.047438
0.047438
0
0
0
0
0.021122
0.391131
2,255
63
108
35.793651
0.74654
0
0
0.122449
0
0
0.281846
0.07945
0
0
0
0
0.040816
1
0.020408
false
0
0.040816
0
0.081633
0.040816
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
9bbf5d23053e93f4be3618d38f8307dfe71dd5b9
2,156
py
Python
美团爬取商家信息/paquxinxi.py
13060923171/Crawl-Project2
effab1bf31979635756fc272a7bcc666bb499be2
[ "MIT" ]
14
2020-10-27T05:52:20.000Z
2021-11-07T20:24:55.000Z
美团爬取商家信息/paquxinxi.py
13060923171/Crawl-Project2
effab1bf31979635756fc272a7bcc666bb499be2
[ "MIT" ]
1
2021-09-17T07:40:00.000Z
2021-09-17T07:40:00.000Z
美团爬取商家信息/paquxinxi.py
13060923171/Crawl-Project2
effab1bf31979635756fc272a7bcc666bb499be2
[ "MIT" ]
8
2020-11-18T14:23:12.000Z
2021-11-12T08:55:08.000Z
import requests import re import json headers = { "Origin": "https://bj.meituan.com", "Host": "apimobile.meituan.com", "Referer": "https://bj.meituan.com/s/%E7%81%AB%E9%94%85/", "Cookie": "uuid=692a53319ce54d0c91f3.1597223761.1.0.0; ci=1; rvct=1; _lxsdk_cuid=173e1f47707c8-0dcd4ff30b4ae3-3323765-e1000-1...
33.169231
185
0.590909
299
2,156
4.197324
0.474916
0.035857
0.01992
0.023904
0.105976
0.100398
0
0
0
0
0
0.103819
0.222635
2,156
65
186
33.169231
0.644988
0.042672
0
0
0
0.074074
0.337543
0.084021
0
0
0
0
0
1
0.055556
false
0.018519
0.055556
0
0.111111
0.055556
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
32cada166139a42c2081b8a48a2bcd39a15cb5ab
2,612
py
Python
create_categories.py
Botomatik/JackBot
58651d8b5a5bcead2a2eb79849019cb4f972b7cd
[ "MIT" ]
null
null
null
create_categories.py
Botomatik/JackBot
58651d8b5a5bcead2a2eb79849019cb4f972b7cd
[ "MIT" ]
null
null
null
create_categories.py
Botomatik/JackBot
58651d8b5a5bcead2a2eb79849019cb4f972b7cd
[ "MIT" ]
null
null
null
# -*- coding: utf-8 -*- """ Program to batch create categories. The program expects a generator containing a list of page titles to be used as base. The following command line parameters are supported: -always (not implemented yet) Don't ask, just do the edit. -overwrite (not implemented yet). -parent...
25.359223
78
0.630551
305
2,612
5.357377
0.459016
0.03672
0.029376
0.033048
0
0
0
0
0
0
0
0.005644
0.253828
2,612
102
79
25.607843
0.832735
0.326187
0
0.058824
0
0
0.106605
0
0
0
0
0.009804
0
1
0.039216
false
0
0.176471
0
0.215686
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
32cae26d8eb99a201dc12930e81a1edb58d4cace
10,287
py
Python
avod/core/losses.py
Zengyi-Qin/TLNet
11fa48160158b550ad2dc810ed564eebe17e8f5e
[ "Apache-2.0" ]
114
2019-03-13T01:42:22.000Z
2022-03-31T07:56:04.000Z
avod/core/losses.py
Zengyi-Qin/TLNet
11fa48160158b550ad2dc810ed564eebe17e8f5e
[ "Apache-2.0" ]
12
2019-03-26T08:18:13.000Z
2021-05-19T14:36:27.000Z
avod/core/losses.py
Zengyi-Qin/TLNet
11fa48160158b550ad2dc810ed564eebe17e8f5e
[ "Apache-2.0" ]
22
2019-03-22T10:44:49.000Z
2021-04-01T00:11:07.000Z
"""Classification and regression loss functions for object detection. Localization losses: * WeightedL2LocalizationLoss * WeightedSmoothL1LocalizationLoss Classification losses: * WeightedSoftmaxClassificationLoss * WeightedSigmoidClassificationLoss """ from abc import ABCMeta from abc import abstractmethod impo...
44.150215
129
0.636726
1,247
10,287
5.026464
0.159583
0.053606
0.035099
0.03127
0.654595
0.591417
0.577377
0.558392
0.524729
0.515156
0
0.013124
0.28152
10,287
232
130
44.340517
0.834934
0.448722
0
0.22619
0
0
0.000803
0
0
0
0
0
0
1
0.083333
false
0.011905
0.047619
0
0.285714
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
32cd6811a8df581555a9e17bfebdb7625e6646ac
19,282
py
Python
routing/views.py
iqqmuT/tsari
343ef5cf08ee24bdb710e94c0b6fb334264e5677
[ "MIT" ]
null
null
null
routing/views.py
iqqmuT/tsari
343ef5cf08ee24bdb710e94c0b6fb334264e5677
[ "MIT" ]
2
2020-02-11T22:09:10.000Z
2020-06-05T18:02:28.000Z
routing/views.py
iqqmuT/tsari
343ef5cf08ee24bdb710e94c0b6fb334264e5677
[ "MIT" ]
null
null
null
import json from datetime import datetime, timedelta from dateutil import parser as dateparser from django.contrib.auth.decorators import user_passes_test from django.db.models import Q from django.http import HttpResponseNotFound, JsonResponse from django.shortcuts import render from django.utils import timezone fro...
36.041121
256
0.587283
2,311
19,282
4.635223
0.10688
0.041449
0.01587
0.011202
0.428305
0.352595
0.289955
0.233383
0.190721
0.155246
0
0.009713
0.295198
19,282
534
257
36.108614
0.778514
0.151281
0
0.240106
0
0
0.087877
0
0
0
0
0
0
1
0.055409
false
0.005277
0.026385
0
0.150396
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
32cf5c6af409ad539e05135e062b11460576c4f6
5,575
py
Python
my_ner.py
shouxieai/nlp-bilstm_crf-ner
907381325eeb0a2c29004e1c617bea7312579ba8
[ "Apache-2.0" ]
16
2021-12-14T10:51:25.000Z
2022-03-30T10:10:09.000Z
my_ner.py
shouxieai/nlp-bilstm-ner
907381325eeb0a2c29004e1c617bea7312579ba8
[ "Apache-2.0" ]
1
2022-03-23T04:28:50.000Z
2022-03-23T04:28:50.000Z
my_ner.py
shouxieai/nlp-bilstm-ner
907381325eeb0a2c29004e1c617bea7312579ba8
[ "Apache-2.0" ]
2
2021-12-08T02:48:01.000Z
2021-12-13T13:03:25.000Z
import os from torch.utils.data import Dataset,DataLoader import torch import torch.nn as nn from sklearn.metrics import f1_score def build_corpus(split, make_vocab=True, data_dir="data"): """读取数据""" assert split in ['train', 'dev', 'test'] word_lists = [] tag_lists = [] with open(os.path.join(dat...
32.794118
130
0.63139
794
5,575
4.142317
0.201511
0.036485
0.033445
0.015202
0.209182
0.148373
0.09395
0.09395
0.067498
0.043174
0
0.013932
0.253274
5,575
169
131
32.988166
0.776123
0.010404
0
0.055118
0
0
0.019056
0
0
0
0
0
0.015748
1
0.062992
false
0
0.03937
0
0.173228
0.007874
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
32cfbeee160a6e50ceb471701c99ace872cbfe2b
362
py
Python
leetcode/409.py
windniw/just-for-fun
54e5c2be145f3848811bfd127f6a89545e921570
[ "Apache-2.0" ]
1
2019-08-28T23:15:25.000Z
2019-08-28T23:15:25.000Z
leetcode/409.py
windniw/just-for-fun
54e5c2be145f3848811bfd127f6a89545e921570
[ "Apache-2.0" ]
null
null
null
leetcode/409.py
windniw/just-for-fun
54e5c2be145f3848811bfd127f6a89545e921570
[ "Apache-2.0" ]
null
null
null
""" link: https://leetcode.com/problems/longest-palindrome problem: 问用s中字符组成的最长回文串长度 solution: map 记录字符出现次数 """ class Solution: def longestPalindrome(self, s: str) -> int: m, res = collections.defaultdict(int), 0 for x in s: m[x] += 1 for x in m: res += m[x] // 2...
18.1
54
0.558011
48
362
4.208333
0.666667
0.039604
0.059406
0
0
0
0
0
0
0
0
0.01992
0.30663
362
19
55
19.052632
0.784861
0.290055
0
0
0
0
0
0
0
0
0
0
0
1
0.125
false
0
0
0
0.375
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
32cfc631e8d4a50ff93f3a9a349602c8342fb97a
847
py
Python
nickenbot/config.py
brlafreniere/nickenbot
f13ec78057ec25823eb16df6ffab3a32eddfd3ca
[ "MIT" ]
1
2016-08-10T12:20:58.000Z
2016-08-10T12:20:58.000Z
nickenbot/config.py
brlafreniere/nickenbot
f13ec78057ec25823eb16df6ffab3a32eddfd3ca
[ "MIT" ]
null
null
null
nickenbot/config.py
brlafreniere/nickenbot
f13ec78057ec25823eb16df6ffab3a32eddfd3ca
[ "MIT" ]
null
null
null
import yaml import os import sys current_dir = os.path.dirname(os.path.realpath(__file__)) project_dir = os.path.realpath(os.path.join(current_dir, "..")) class ConfigManager: network = None config = None @classmethod def load(clss): if clss.network: config_filepath = os.path.join...
27.322581
95
0.615112
106
847
4.764151
0.358491
0.071287
0.059406
0.079208
0.158416
0.158416
0.158416
0.158416
0
0
0
0.001621
0.271547
847
30
96
28.233333
0.816856
0
0
0.16
0
0
0.088548
0.024793
0
0
0
0
0
1
0.08
false
0
0.12
0
0.36
0.04
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
32d046c8c2ed3ece0b08aa280a40083f8b7d16ab
2,277
py
Python
qna/views.py
channprj/KU-PL
7fc3719b612a819ed1bd443695d7f13f509ee596
[ "MIT" ]
null
null
null
qna/views.py
channprj/KU-PL
7fc3719b612a819ed1bd443695d7f13f509ee596
[ "MIT" ]
null
null
null
qna/views.py
channprj/KU-PL
7fc3719b612a819ed1bd443695d7f13f509ee596
[ "MIT" ]
null
null
null
from django.shortcuts import render from django.shortcuts import redirect from django.shortcuts import get_object_or_404 from django.utils import timezone from .forms import QuestionForm from .forms import AnswerForm from .models import Question from .models import Answer def question_list(request): questions = Qu...
35.030769
101
0.665349
272
2,277
5.4375
0.194853
0.047329
0.02975
0.037863
0.592292
0.53144
0.515213
0.515213
0.46856
0.46856
0
0.00678
0.222661
2,277
64
102
35.578125
0.828814
0
0
0.462963
0
0
0.104569
0.080844
0
0
0
0
0
1
0.092593
false
0
0.148148
0
0.388889
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
32d33f3c862ddf8043ee8ce09e1a526264e7c51a
1,648
py
Python
python/tests/test_oci.py
miku/labe
2d784f418e24ab6fef9f76791c9fdd02dd505657
[ "MIT" ]
null
null
null
python/tests/test_oci.py
miku/labe
2d784f418e24ab6fef9f76791c9fdd02dd505657
[ "MIT" ]
null
null
null
python/tests/test_oci.py
miku/labe
2d784f418e24ab6fef9f76791c9fdd02dd505657
[ "MIT" ]
1
2021-09-16T10:51:00.000Z
2021-09-16T10:51:00.000Z
""" Unit tests for labe. Most not mocked yet, hence slow. """ import collections import socket import pytest import requests from labe.oci import get_figshare_download_link, get_terminal_url def no_internet(host="8.8.8.8", port=53, timeout=3): """ Host: 8.8.8.8 (google-public-dns-a.google.com) OpenPort...
30.518519
88
0.662621
221
1,648
4.809955
0.434389
0.011289
0.065851
0.064911
0.374412
0.312324
0.263405
0.169332
0.169332
0.097836
0
0.062126
0.18932
1,648
53
89
31.09434
0.733533
0.086772
0
0.171429
0
0
0.303256
0
0
0
0
0
0.114286
1
0.085714
false
0
0.142857
0
0.285714
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
32d559b8ce0d7d1c7f26302620ef00f9255a82dc
26,404
py
Python
pyNastran/bdf/cards/test/test_dynamic.py
ACea15/pyNastran
5ffc37d784b52c882ea207f832bceb6b5eb0e6d4
[ "BSD-3-Clause" ]
293
2015-03-22T20:22:01.000Z
2022-03-14T20:28:24.000Z
pyNastran/bdf/cards/test/test_dynamic.py
ACea15/pyNastran
5ffc37d784b52c882ea207f832bceb6b5eb0e6d4
[ "BSD-3-Clause" ]
512
2015-03-14T18:39:27.000Z
2022-03-31T16:15:43.000Z
pyNastran/bdf/cards/test/test_dynamic.py
ACea15/pyNastran
5ffc37d784b52c882ea207f832bceb6b5eb0e6d4
[ "BSD-3-Clause" ]
136
2015-03-19T03:26:06.000Z
2022-03-25T22:14:54.000Z
"""tests dynamic cards and dynamic load cards""" import unittest from io import StringIO import numpy as np import pyNastran from pyNastran.bdf.bdf import BDF, read_bdf, CrossReferenceError from pyNastran.bdf.cards.test.utils import save_load_deck #ROOT_PATH = pyNastran.__path__[0] class TestDynamic(unittest.TestCas...
34.069677
97
0.549879
3,542
26,404
3.966403
0.121683
0.042708
0.028685
0.028828
0.581821
0.549434
0.52623
0.473486
0.451491
0.419105
0
0.068243
0.325708
26,404
774
98
34.113695
0.720849
0.15581
0
0.532491
0
0.00722
0.067482
0
0
0
0
0
0.030686
1
0.028881
false
0
0.01083
0
0.041516
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
32d6f22794e1af28d1b004461271504fb7680002
4,691
py
Python
src/kv/benchmark/runbench.py
showapicxt/iowow
a29ac5b28f1b6c2817061c2a43b7222176458876
[ "MIT" ]
242
2015-08-13T06:38:10.000Z
2022-03-17T13:49:56.000Z
src/kv/benchmark/runbench.py
showapicxt/iowow
a29ac5b28f1b6c2817061c2a43b7222176458876
[ "MIT" ]
44
2018-04-08T07:12:02.000Z
2022-03-04T06:15:01.000Z
src/kv/benchmark/runbench.py
showapicxt/iowow
a29ac5b28f1b6c2817061c2a43b7222176458876
[ "MIT" ]
18
2016-01-14T09:50:34.000Z
2022-01-26T23:07:40.000Z
import subprocess import argparse import os import random from collections import OrderedDict from parse import parse from bokeh.io import export_png from bokeh.plotting import figure, output_file, show, save from bokeh.models import ColumnDataSource, FactorRange from bokeh.transform import factor_cmap from bokeh.layou...
31.273333
99
0.568322
610
4,691
4.293443
0.337705
0.020619
0.011455
0.017182
0.148148
0.113784
0.092402
0.07942
0.030546
0.030546
0
0.050723
0.277126
4,691
149
100
31.483221
0.721616
0.005756
0
0.080645
0
0
0.118833
0.027885
0
0
0
0
0
1
0.040323
false
0
0.096774
0
0.137097
0.032258
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
32db89f97cc25f33ad056f8860c98d1fafd8baab
2,652
py
Python
chapt05/triangle.py
ohlogic/PythonOpenGLSuperBible4Glut
a0d01caaeb811002c191c28210268b5fcbb8b379
[ "MIT" ]
null
null
null
chapt05/triangle.py
ohlogic/PythonOpenGLSuperBible4Glut
a0d01caaeb811002c191c28210268b5fcbb8b379
[ "MIT" ]
null
null
null
chapt05/triangle.py
ohlogic/PythonOpenGLSuperBible4Glut
a0d01caaeb811002c191c28210268b5fcbb8b379
[ "MIT" ]
null
null
null
#!/usr/bin/python3 # Demonstrates OpenGL color triangle # Ben Smith # benjamin.coder.smith@gmail.com # # based heavily on ccube.cpp # OpenGL SuperBible # Program by Richard S. Wright Jr. import math from OpenGL.GL import * from OpenGL.GLUT import * from OpenGL.GLU import * ESCAPE = b'\033' xRot...
21.737705
83
0.562217
294
2,652
5.003401
0.530612
0.024473
0.014276
0.008158
0.054385
0.025833
0.025833
0
0
0
0
0.062245
0.35181
2,652
121
84
21.917355
0.793485
0.286199
0
0
0
0
0.013857
0
0
0
0
0
0
1
0.083333
false
0
0.083333
0
0.166667
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
32e2062c20d3f7d54552e963b99e3b7f219ffa2e
19,175
py
Python
ScreenTrainer.py
ZihaoChen0319/CMB-Segmentation
99c5788baacc280ca5dbe02f3e18403e399fb238
[ "Apache-2.0" ]
null
null
null
ScreenTrainer.py
ZihaoChen0319/CMB-Segmentation
99c5788baacc280ca5dbe02f3e18403e399fb238
[ "Apache-2.0" ]
null
null
null
ScreenTrainer.py
ZihaoChen0319/CMB-Segmentation
99c5788baacc280ca5dbe02f3e18403e399fb238
[ "Apache-2.0" ]
null
null
null
import torch.nn as nn import os import torch.optim as optim from tqdm import tqdm import numpy as np import torch import torch.nn.functional as nnf import SimpleITK as sitk import json from scipy import ndimage import medpy.io as mio from Utils import find_binary_object from MyDataloader import get_train_...
50.460526
140
0.557445
2,672
19,175
3.783308
0.129117
0.034623
0.027698
0.014245
0.354536
0.28994
0.238204
0.210703
0.195865
0.176674
0
0.026951
0.313064
19,175
379
141
50.593668
0.74051
0.042451
0
0.13125
0
0.003125
0.059674
0.022831
0
0
0
0
0
1
0.025
false
0
0.05
0
0.09375
0.021875
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
32e36a60281e09d72c79ad1807ea74035aa73e60
534
py
Python
examples/earthquakes/main.py
admariner/beneath
a6aa2c220e4a646be792379528ae673f4bef440b
[ "MIT" ]
65
2021-04-27T13:13:09.000Z
2022-01-24T00:26:06.000Z
examples/earthquakes/main.py
admariner/beneath
a6aa2c220e4a646be792379528ae673f4bef440b
[ "MIT" ]
22
2021-10-06T10:30:40.000Z
2021-12-10T11:36:55.000Z
examples/earthquakes/main.py
admariner/beneath
a6aa2c220e4a646be792379528ae673f4bef440b
[ "MIT" ]
4
2021-04-24T15:29:51.000Z
2022-03-30T16:20:12.000Z
import beneath from generators import earthquakes with open("schemas/earthquake.graphql", "r") as file: EARTHQUAKES_SCHEMA = file.read() if __name__ == "__main__": p = beneath.Pipeline(parse_args=True) p.description = "Continually pings the USGS earthquake API" earthquakes = p.generate(earthquakes.ge...
28.105263
76
0.700375
59
534
6.118644
0.59322
0.141274
0
0
0
0
0
0
0
0
0
0
0.196629
534
18
77
29.666667
0.841492
0
0
0
0
0
0.262172
0.048689
0
0
0
0
0
1
0
false
0
0.133333
0
0.133333
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
32e3ce811bff9ec736c02ce8188ebe9e69d6a483
5,073
py
Python
examples/tf_vision/tensorflow_saved_model_service.py
siddharthgee/multi-model-server
bd795b402330b491edd5d2a235b8b8c2ef9fcb58
[ "Apache-2.0" ]
null
null
null
examples/tf_vision/tensorflow_saved_model_service.py
siddharthgee/multi-model-server
bd795b402330b491edd5d2a235b8b8c2ef9fcb58
[ "Apache-2.0" ]
null
null
null
examples/tf_vision/tensorflow_saved_model_service.py
siddharthgee/multi-model-server
bd795b402330b491edd5d2a235b8b8c2ef9fcb58
[ "Apache-2.0" ]
null
null
null
# Copyright 2020 Amazon.com, Inc. or its affiliates. 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. # A copy of the License is located at # http://www.apache.org/licenses/LICENSE-2.0 # or in the "license" file...
38.431818
118
0.640647
623
5,073
5.070626
0.317817
0.037037
0.026591
0.030073
0.120924
0.071225
0.045584
0.045584
0.020893
0
0
0.00487
0.271437
5,073
131
119
38.725191
0.849838
0.342795
0
0
0
0
0.147666
0
0
0
0
0
0.080645
1
0.080645
false
0
0.064516
0.016129
0.209677
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
32e861d95e4d1e621303b5ebac3624de50614805
4,007
py
Python
mazegen/solver.py
alekratz/mazegen
2799a5cf790cec4bab94a147315cc8541c5efec7
[ "MIT" ]
null
null
null
mazegen/solver.py
alekratz/mazegen
2799a5cf790cec4bab94a147315cc8541c5efec7
[ "MIT" ]
null
null
null
mazegen/solver.py
alekratz/mazegen
2799a5cf790cec4bab94a147315cc8541c5efec7
[ "MIT" ]
null
null
null
import random from typing import Optional from .grid import * class Solver: def __init__(self, grid: Grid): self._grid = grid self._backtrack = [] self._pos = (0, 0) self._dir = None self._backtracking = False self._branches = { self._pos: set(self.vali...
32.056
96
0.520839
486
4,007
4.183128
0.236626
0.072307
0.078701
0.084112
0.201181
0.134776
0.117068
0.117068
0.117068
0.117068
0
0.01218
0.385326
4,007
124
97
32.314516
0.813236
0.143499
0
0.28866
0
0
0.013549
0
0
0
0
0.008065
0.041237
1
0.103093
false
0
0.030928
0.051546
0.237113
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
32ea368fa5ba2732d1c51618d8edfc516b6eb773
1,224
py
Python
example/RunModel/Abaqus_Model_Example/process_odb.py
volpatto/UQpy
acbe1d6e655e98917f56b324f019881ea9ccca82
[ "MIT" ]
null
null
null
example/RunModel/Abaqus_Model_Example/process_odb.py
volpatto/UQpy
acbe1d6e655e98917f56b324f019881ea9ccca82
[ "MIT" ]
null
null
null
example/RunModel/Abaqus_Model_Example/process_odb.py
volpatto/UQpy
acbe1d6e655e98917f56b324f019881ea9ccca82
[ "MIT" ]
null
null
null
from odbAccess import * from abaqusConstants import * from textRepr import * import timeit import numpy as np import os import sys start_time = timeit.default_timer() index = sys.argv[-1] # print(index) # index = float(index) index = int(index) # print(index) odbFile = os.path.join(os.getcwd(), "single_element_simul...
27.818182
87
0.684641
190
1,224
4.326316
0.489474
0.036496
0.043796
0.029197
0.043796
0
0
0
0
0
0
0.031884
0.154412
1,224
43
88
28.465116
0.762319
0.081699
0
0
0
0
0.16458
0.042934
0
0
0
0
0
1
0
false
0
0.21875
0
0.21875
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
32eaa0a294af2308ff208fed9c050fd370b31fec
8,526
py
Python
analysis_methods/shuff_time.py
gbrookshire/simulated_rhythmic_sampling
5c9ed507847a75dbe38d10d78b54441ae83f5831
[ "MIT" ]
null
null
null
analysis_methods/shuff_time.py
gbrookshire/simulated_rhythmic_sampling
5c9ed507847a75dbe38d10d78b54441ae83f5831
[ "MIT" ]
null
null
null
analysis_methods/shuff_time.py
gbrookshire/simulated_rhythmic_sampling
5c9ed507847a75dbe38d10d78b54441ae83f5831
[ "MIT" ]
null
null
null
""" Tools to perform analyses by shuffling in time, as in Landau & Fries (2012) and Fiebelkorn et al. (2013). """ import os import yaml import numpy as np import statsmodels.api as sm from statsmodels.stats.multitest import multipletests from .utils import avg_repeated_timepoints, dft # Load the details of the behavi...
29
79
0.62327
1,219
8,526
4.223134
0.231337
0.052448
0.055944
0.015152
0.286908
0.21115
0.17366
0.130536
0.101204
0.101204
0
0.011265
0.281609
8,526
293
80
29.098976
0.829224
0.555712
0
0.144578
0
0
0.05601
0.006608
0
0
0
0
0
1
0.096386
false
0
0.072289
0
0.26506
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
32ef88405f3f3c3db42531c5dfa16c38dbb4d202
1,405
py
Python
Easy/112.PathSum.py
YuriSpiridonov/LeetCode
2dfcc9c71466ffa2ebc1c89e461ddfca92e2e781
[ "MIT" ]
39
2020-07-04T11:15:13.000Z
2022-02-04T22:33:42.000Z
Easy/112.PathSum.py
YuriSpiridonov/LeetCode
2dfcc9c71466ffa2ebc1c89e461ddfca92e2e781
[ "MIT" ]
1
2020-07-15T11:53:37.000Z
2020-07-15T11:53:37.000Z
Easy/112.PathSum.py
YuriSpiridonov/LeetCode
2dfcc9c71466ffa2ebc1c89e461ddfca92e2e781
[ "MIT" ]
20
2020-07-14T19:12:53.000Z
2022-03-02T06:28:17.000Z
""" Given a binary tree and a sum, determine if the tree has a root-to-leaf path such that adding up all the values along the path equals the given sum. Note: A leaf is a node with no children. Example: Given the below binary tree and sum = 22, 5 / \ 4 8 ...
28.673469
84
0.577936
210
1,405
3.847619
0.452381
0.034653
0.059406
0.027228
0.205446
0.089109
0.089109
0
0
0
0
0.052239
0.332384
1,405
48
85
29.270833
0.809168
0.608541
0
0
0
0
0
0
0
0
0
0
0
1
0.142857
false
0
0
0
0.357143
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
32f6cfa5b601a97d41e10a68ea610b54a023b9f0
864
py
Python
src/test.py
ayieko168/Arduino-Oscilloscope
5a0634437010f4303c86aef141f33cc6a628b3dc
[ "MIT" ]
null
null
null
src/test.py
ayieko168/Arduino-Oscilloscope
5a0634437010f4303c86aef141f33cc6a628b3dc
[ "MIT" ]
null
null
null
src/test.py
ayieko168/Arduino-Oscilloscope
5a0634437010f4303c86aef141f33cc6a628b3dc
[ "MIT" ]
null
null
null
import pyqtgraph as pg import pyqtgraph.exporters import numpy as np import math from time import sleep f = 10 t = 0 Samples = 1000 # while True: # y2 = np.sin( 2* np.pi * f * t) # print(y) # t+=0.01 # sleep(0.25) def update(): global f, t, ys, y2 print(len(y2)) if len(y2) == Samples: ...
16.941176
76
0.618056
139
864
3.769784
0.532374
0.01145
0.022901
0.030534
0.045802
0.045802
0.045802
0
0
0
0
0.058735
0.231481
864
51
77
16.941176
0.730422
0.157407
0
0
0
0
0.047288
0
0
0
0
0
0
1
0.033333
false
0
0.2
0
0.233333
0.033333
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
32fcb908b2dfd2baf6aec8baabfb5d1f269220d0
1,577
py
Python
src/plyer_lach/platforms/android/email.py
locksmith47/turing-sim-kivy
f57de9d52494245c56f67dd7e63121434bb0553f
[ "MIT" ]
null
null
null
src/plyer_lach/platforms/android/email.py
locksmith47/turing-sim-kivy
f57de9d52494245c56f67dd7e63121434bb0553f
[ "MIT" ]
null
null
null
src/plyer_lach/platforms/android/email.py
locksmith47/turing-sim-kivy
f57de9d52494245c56f67dd7e63121434bb0553f
[ "MIT" ]
null
null
null
from jnius import autoclass, cast from kivy.logger import Logger from plyer_lach.facades import Email from plyer_lach.platforms.android import activity Intent = autoclass('android.content.Intent') AndroidString = autoclass('java.lang.String') URI = autoclass('android.net.Uri') class AndroidEmail(Email): def _send...
36.674419
89
0.606848
160
1,577
5.85
0.3625
0.048077
0.064103
0.080128
0.07906
0
0
0
0
0
0
0
0.287254
1,577
42
90
37.547619
0.83274
0
0
0
0
0
0.126189
0.055168
0
0
0
0
0
1
0.055556
false
0
0.111111
0.027778
0.222222
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fd032c799cd2f082ede61113614415437237b7bc
40,263
py
Python
src/eventail/async_service/pika/base.py
allo-media/eventail
aed718d733709f1a522fbfec7083ddd8ed7b5039
[ "MIT" ]
2
2019-12-12T15:08:25.000Z
2020-05-19T08:52:06.000Z
src/eventail/async_service/pika/base.py
allo-media/eventail
aed718d733709f1a522fbfec7083ddd8ed7b5039
[ "MIT" ]
10
2021-01-19T15:03:51.000Z
2022-03-08T15:48:22.000Z
src/eventail/async_service/pika/base.py
allo-media/eventail
aed718d733709f1a522fbfec7083ddd8ed7b5039
[ "MIT" ]
null
null
null
# -*- coding: utf-8 -*- # # MIT License # # Copyright (c) 2018-2019 Groupe Allo-Media # # 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 r...
39.014535
108
0.634304
4,882
40,263
5.082548
0.139697
0.025954
0.009954
0.008222
0.36771
0.299077
0.255108
0.224922
0.199694
0.177649
0
0.001231
0.293967
40,263
1,031
109
39.052376
0.871531
0.367956
0
0.327616
0
0
0.068712
0.002774
0
0
0
0
0
1
0.080618
false
0.005146
0.022298
0
0.132075
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
fd0394b6bd7363e7ed4aa89ca0603954bd731b42
889
py
Python
CLI/mainmenue.py
MeatBoyed/PasswordBank2
f4367b22902ce1282772b184899e3d6e899c1cca
[ "MIT" ]
1
2021-02-08T17:45:28.000Z
2021-02-08T17:45:28.000Z
CLI/mainmenue.py
MeatBoyed/PasswordBank2
f4367b22902ce1282772b184899e3d6e899c1cca
[ "MIT" ]
null
null
null
CLI/mainmenue.py
MeatBoyed/PasswordBank2
f4367b22902ce1282772b184899e3d6e899c1cca
[ "MIT" ]
null
null
null
from .mock_api.utils import GetSelection from .viewAccounts import ViewAccounts from .addAccount import AddAccount def MainMenue(): headerMessage = ( """\n\n=========================================================\n===================== Main Menue ========================\n""") print(headerMessage) ...
26.939394
137
0.418448
69
889
5.376812
0.594203
0.016173
0
0
0
0
0
0
0
0
0
0.009091
0.257593
889
32
138
27.78125
0.55303
0
0
0
0
0
0.155763
0.088785
0
0
0
0
0
1
0.043478
false
0.043478
0.130435
0
0.173913
0.217391
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fd06722fb8cfe07ace7e4c46b654df0346766b26
4,181
py
Python
nn_similarity_index/cwt_kernel_mat.py
forgi86/xfer
56d98a66d6adb2466d1a73b52f3b27193930a008
[ "Apache-2.0" ]
244
2018-08-31T18:35:29.000Z
2022-03-20T01:12:50.000Z
nn_similarity_index/cwt_kernel_mat.py
forgi86/xfer
56d98a66d6adb2466d1a73b52f3b27193930a008
[ "Apache-2.0" ]
26
2018-08-29T15:31:21.000Z
2021-06-24T08:05:53.000Z
nn_similarity_index/cwt_kernel_mat.py
forgi86/xfer
56d98a66d6adb2466d1a73b52f3b27193930a008
[ "Apache-2.0" ]
57
2018-09-11T13:40:35.000Z
2022-02-22T14:43:34.000Z
# Copyright 2020 Amazon.com, Inc. or its affiliates. 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. # A copy of the License is located at # # http://www.apache.org/licenses/LICENSE-2.0 # # or in th...
40.201923
112
0.648649
543
4,181
4.907919
0.39779
0.033771
0.06379
0.019512
0.031144
0.019512
0
0
0
0
0
0.012805
0.234155
4,181
103
113
40.592233
0.819488
0.267161
0
0.034483
0
0
0.226645
0.015461
0
0
0
0
0
1
0
false
0
0.224138
0
0.224138
0.068966
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fd0c1d5bae5b02c0610c8254bb0ed033a6e6d1e5
1,079
py
Python
optaux/helper_functions/check_nonvalidated_auxs.py
coltonlloyd/OptAux
3ee1f8cdfa32f1a732ad41d5f854659159694160
[ "MIT" ]
1
2019-06-05T10:41:06.000Z
2019-06-05T10:41:06.000Z
optaux/helper_functions/check_nonvalidated_auxs.py
coltonlloyd/OptAux
3ee1f8cdfa32f1a732ad41d5f854659159694160
[ "MIT" ]
null
null
null
optaux/helper_functions/check_nonvalidated_auxs.py
coltonlloyd/OptAux
3ee1f8cdfa32f1a732ad41d5f854659159694160
[ "MIT" ]
null
null
null
import cobra from optaux import resources resource_dir = resources.__path__[0] met_to_rs = {'EX_pydam_e': ['PDX5PS', 'PYDXK', 'PYDXNK'], 'EX_orot_e': ['DHORTS', 'UPPRT', 'URIK2'], 'EX_thr__L_e': ['PTHRpp', 'THRS'], 'EX_pro__L_e': ['AMPTASEPG', 'P5CR'], 'EX_skm_e': ...
33.71875
68
0.615385
168
1,079
3.630952
0.422619
0.04918
0.068852
0.083607
0.237705
0.211475
0.098361
0.098361
0
0
0
0.020457
0.229842
1,079
32
69
33.71875
0.713598
0
0
0
0
0
0.137963
0
0
0
0
0
0
1
0
false
0
0.08
0
0.08
0.08
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fd105e9dfaa8a1cb5dda8aab7e3ed98167bf73e4
10,430
py
Python
csv-to-mysql.py
LongPhan1912/Youtube-Playlist-Extractor
80b10e0b459c2cb264113cfaff644f5f28650813
[ "CC0-1.0" ]
null
null
null
csv-to-mysql.py
LongPhan1912/Youtube-Playlist-Extractor
80b10e0b459c2cb264113cfaff644f5f28650813
[ "CC0-1.0" ]
null
null
null
csv-to-mysql.py
LongPhan1912/Youtube-Playlist-Extractor
80b10e0b459c2cb264113cfaff644f5f28650813
[ "CC0-1.0" ]
null
null
null
import csv import MySQLdb # installing MySQL: https://dev.mysql.com/doc/refman/8.0/en/osx-installation-pkg.html # how to start, watch: https://www.youtube.com/watch?v=3vsC05rxZ8c # or read this (absolutely helpful) guide: https://www.datacamp.com/community/tutorials/mysql-python # this is mainly created to get a data...
48.287037
136
0.661266
1,397
10,430
4.725125
0.219041
0.064081
0.050901
0.038176
0.395698
0.342524
0.28223
0.235419
0.215422
0.189062
0
0.008935
0.216683
10,430
215
137
48.511628
0.799021
0.346309
0
0.288889
0
0
0.124704
0.019231
0
0
0
0
0
1
0.133333
false
0.007407
0.014815
0
0.17037
0.044444
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fd1270311d2747042f749172a656ddde2d001d75
1,221
py
Python
src/topologies/simple.py
sevenEng/Resolving-Consensus
a508701e19bd4ec0df735f5b094487983272dbb6
[ "MIT" ]
null
null
null
src/topologies/simple.py
sevenEng/Resolving-Consensus
a508701e19bd4ec0df735f5b094487983272dbb6
[ "MIT" ]
null
null
null
src/topologies/simple.py
sevenEng/Resolving-Consensus
a508701e19bd4ec0df735f5b094487983272dbb6
[ "MIT" ]
null
null
null
from mininet.net import Mininet from mininet.node import Controller, UserSwitch, IVSSwitch, OVSSwitch from mininet.log import info, setLogLevel setLogLevel("info") import importlib switch_num = 1 def add_switch(net): global switch_num res = "s%s" % str(switch_num) switch_num += 1 return net.addSwitc...
18.784615
69
0.633907
177
1,221
4.254237
0.299435
0.031873
0.027888
0.039841
0.061089
0.061089
0
0
0
0
0
0.010741
0.23751
1,221
64
70
19.078125
0.798067
0.01638
0
0.04878
0
0
0.075897
0
0
0
0
0
0
1
0.097561
false
0
0.097561
0
0.292683
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
fd1396e2ed5013e365c0832fe7ee283e5e1bda20
856
py
Python
lunchapi/permissions.py
pesusieni999/lunchapplication
2aa2a4320a2ad85b39b74c5dcc3d960a46cdb6ef
[ "MIT" ]
null
null
null
lunchapi/permissions.py
pesusieni999/lunchapplication
2aa2a4320a2ad85b39b74c5dcc3d960a46cdb6ef
[ "MIT" ]
null
null
null
lunchapi/permissions.py
pesusieni999/lunchapplication
2aa2a4320a2ad85b39b74c5dcc3d960a46cdb6ef
[ "MIT" ]
null
null
null
from rest_framework import permissions __author__ = "Ville Myllynen" __copyright__ = "Copyright 2017, Ohsiha Project" __credits__ = ["Ville Myllynen"] __license__ = "MIT" __version__ = "1.0" __maintainer__ = "Ville Myllynen" __email__ = "ville.myllynen@student.tut.fi" __status__ = "Development" class IsOwnerOrReadO...
31.703704
73
0.712617
103
856
5.572816
0.718447
0.090592
0
0
0
0
0
0
0
0
0
0.008824
0.205607
856
27
74
31.703704
0.835294
0.315421
0
0
0
0
0.20885
0.051327
0
0
0
0
0
1
0.071429
false
0
0.071429
0
0.357143
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
fd16885dbeb4939e362807cdc853aa44683b010f
18,284
py
Python
alphago/alphago.py
noahwaterfieldprice/alphago
4a7bba6d9758ccf1d2f2d7ae964b5d5d48021ee8
[ "MIT" ]
4
2018-02-12T09:11:26.000Z
2022-01-24T20:46:15.000Z
alphago/alphago.py
noahwaterfieldprice/alphago
4a7bba6d9758ccf1d2f2d7ae964b5d5d48021ee8
[ "MIT" ]
null
null
null
alphago/alphago.py
noahwaterfieldprice/alphago
4a7bba6d9758ccf1d2f2d7ae964b5d5d48021ee8
[ "MIT" ]
3
2018-08-23T15:08:54.000Z
2020-03-13T14:21:08.000Z
from collections import OrderedDict import numpy as np from tqdm import tqdm import tensorflow as tf from .player import MCTSPlayer, RandomPlayer, OptimalPlayer from .evaluator import evaluate from .mcts_tree import MCTSNode, mcts from .utilities import sample_distribution __all__ = ["train_alphago", "self_play", "p...
39.152034
80
0.644553
2,293
18,284
4.924117
0.139555
0.030467
0.018599
0.026038
0.400939
0.347533
0.295279
0.246125
0.232132
0.211762
0
0.014066
0.280683
18,284
466
81
39.236052
0.844434
0.366823
0
0.280374
0
0
0.044378
0.003886
0
0
0
0.008584
0
1
0.056075
false
0
0.037383
0.004673
0.14486
0.037383
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fd1902e85156fc45744e6e48892733db33d5f755
4,373
py
Python
extract_skip_thought.py
youngfly11/ReferCOCO-Pretraining-Detectron2
8c8536a4d822b3cf9140380442a440d42e948c38
[ "Apache-2.0" ]
2
2020-08-14T08:00:53.000Z
2020-11-21T11:01:55.000Z
extract_skip_thought.py
youngfly11/ReferCOCO-Pretraining-Detectron2
8c8536a4d822b3cf9140380442a440d42e948c38
[ "Apache-2.0" ]
null
null
null
extract_skip_thought.py
youngfly11/ReferCOCO-Pretraining-Detectron2
8c8536a4d822b3cf9140380442a440d42e948c38
[ "Apache-2.0" ]
null
null
null
#!/usr/bin/python3.6 # -*- coding: utf-8 -*- # @Time : 2020/6/25 22:41 # @Author : Yongfei Liu # @Email : liuyf3@shanghaitech.edu.cn import numpy as np import os.path as osp import os import pickle from collections import OrderedDict import torch import json from detectron2.data.datasets.builtin_meta import CO...
30.58042
104
0.607363
576
4,373
4.390625
0.262153
0.027679
0.02847
0.039541
0.215896
0.180308
0.166074
0.120996
0.120996
0.120996
0
0.01995
0.266408
4,373
142
105
30.795775
0.768392
0.241482
0
0.090909
0
0
0.125571
0.0637
0
0
0
0
0
1
0.038961
false
0
0.103896
0
0.155844
0.064935
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fd1912c311e861ca371e1043073ef9f199c996c4
4,909
py
Python
pyutil_mongo/cfg.py
chhsiao1981/pyutil_mongo
facea2376b48dd7157d4633ab8128c8daf7e59ef
[ "MIT" ]
null
null
null
pyutil_mongo/cfg.py
chhsiao1981/pyutil_mongo
facea2376b48dd7157d4633ab8128c8daf7e59ef
[ "MIT" ]
null
null
null
pyutil_mongo/cfg.py
chhsiao1981/pyutil_mongo
facea2376b48dd7157d4633ab8128c8daf7e59ef
[ "MIT" ]
null
null
null
# -*- coding: utf-8 -*- """ Attributes: config (dict): Description logger (logging.Logger): Description """ import logging import pymongo logger = None config = {} class MongoMap(object): """Info about MongoDB Attributes: ca (None, optional): ssl-ca cert (None, optional): ssl-cert ...
28.375723
243
0.646771
648
4,909
4.621914
0.162037
0.074124
0.062437
0.032721
0.211352
0.142571
0.039399
0.039399
0.039399
0.039399
0
0.002692
0.243227
4,909
172
244
28.540698
0.803499
0.254023
0
0.12987
0
0
0.077967
0
0
0
0
0
0
1
0.064935
false
0
0.025974
0
0.194805
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
fd1a5012b7966cdeb8f03d71591cc6d8a74c6420
2,337
py
Python
tests/stakkr_compose_test.py
dwade75/stakkr
ae77607e84b5b305ae8f5a14eb8f22237d943a29
[ "Apache-2.0" ]
null
null
null
tests/stakkr_compose_test.py
dwade75/stakkr
ae77607e84b5b305ae8f5a14eb8f22237d943a29
[ "Apache-2.0" ]
null
null
null
tests/stakkr_compose_test.py
dwade75/stakkr
ae77607e84b5b305ae8f5a14eb8f22237d943a29
[ "Apache-2.0" ]
null
null
null
import os import sys import stakkr.stakkr_compose as sc import subprocess import unittest base_dir = os.path.abspath(os.path.dirname(__file__)) sys.path.insert(0, base_dir + '/../') # https://docs.python.org/3/library/unittest.html#assert-methods class StakkrComposeTest(unittest.TestCase): services = { '...
31.16
86
0.670946
297
2,337
5.043771
0.309764
0.080107
0.06008
0.053405
0.218959
0.126836
0.085447
0.085447
0
0
0
0.016498
0.195978
2,337
74
87
31.581081
0.780734
0.026102
0
0.04
0
0
0.139463
0.070392
0
0
0
0
0.34
1
0.18
false
0
0.1
0
0.32
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fd1dc3801dfc8c9bd5d0968ee738990d98e2881b
2,792
py
Python
DQIC/backtesting/run.py
bladezzw/DeepQuantInChina
ce74a9bf8db91e3545ccc3e7af81f80796a536fa
[ "MIT" ]
8
2019-04-14T03:05:19.000Z
2020-02-13T18:35:41.000Z
DQIC/backtesting/run.py
bladezzw/DeepQuantInChina
ce74a9bf8db91e3545ccc3e7af81f80796a536fa
[ "MIT" ]
null
null
null
DQIC/backtesting/run.py
bladezzw/DeepQuantInChina
ce74a9bf8db91e3545ccc3e7af81f80796a536fa
[ "MIT" ]
2
2019-05-08T08:23:50.000Z
2020-01-23T03:54:41.000Z
import os,sys BASE_DIR = os.path.dirname(os.path.dirname(__file__)) sys.path.append(BASE_DIR) import datetime import time from backtesting.backtest import Backtest from backtesting.data import HistoricCSVDataHandler from backtesting.execution import SimulatedExecutionHandler from backtesting.portfolio import Portfolio...
33.638554
78
0.567335
255
2,792
6
0.34902
0.019608
0.036601
0.036601
0.321569
0.266667
0.266667
0.266667
0.266667
0.266667
0
0.02798
0.359957
2,792
82
79
34.04878
0.828204
0.112106
0
0.315789
0
0
0.022913
0
0
0
0
0
0
1
0.035088
false
0
0.140351
0
0.192982
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
fd1e95f3c8250711415f3acb25bf5e3b26c63f39
3,306
py
Python
Emergency/DB/DRAW3D.py
LeeDaeil/CNS_Autonomous
2ae3688cfd654b9669893e3cdf4cdf1ac0748b9f
[ "Apache-2.0" ]
2
2020-03-22T14:35:00.000Z
2020-05-26T05:06:41.000Z
Emergency/DB/DRAW3D.py
LeeDaeil/CNS_Autonomous
2ae3688cfd654b9669893e3cdf4cdf1ac0748b9f
[ "Apache-2.0" ]
null
null
null
Emergency/DB/DRAW3D.py
LeeDaeil/CNS_Autonomous
2ae3688cfd654b9669893e3cdf4cdf1ac0748b9f
[ "Apache-2.0" ]
null
null
null
import matplotlib.pylab as plt import numpy as np import pandas as pd from COMMONTOOL import PTCureve DB = pd.read_csv('0_228.txt') # DB = pd.read_csv('../3차 검증/322.txt') # target_time = 100 # for i in range(0, len(DB)): # if DB['KCNTOMS'].loc[i] != target_time: # DB.drop([i], inplace=True) # else: #...
30.897196
85
0.5366
550
3,306
3.178182
0.223636
0.017162
0.030892
0.030892
0.314645
0.262014
0.229405
0.228833
0.221968
0.221968
0
0.100379
0.201452
3,306
107
86
30.897196
0.561742
0.086509
0
0.055556
0
0
0.066201
0
0
0
0
0
0
1
0
false
0
0.055556
0
0.055556
0.013889
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fd22786701bf4e42b8d3932674e46c80a650982c
678
py
Python
common/common/management/commands/makemessages.py
FSTUM/rallyetool-v2
2f3e2b5cb8655abe023ed1215b7182430b75bb23
[ "MIT" ]
1
2021-10-30T09:31:02.000Z
2021-10-30T09:31:02.000Z
common/common/management/commands/makemessages.py
FSTUM/rallyetool-v2
2f3e2b5cb8655abe023ed1215b7182430b75bb23
[ "MIT" ]
9
2021-11-23T10:13:43.000Z
2022-03-01T15:04:15.000Z
common/common/management/commands/makemessages.py
CommanderStorm/rallyetool-v2
721413d6df8afc9347dac7ee83deb3a0ad4c01bc
[ "MIT" ]
1
2021-10-16T09:07:47.000Z
2021-10-16T09:07:47.000Z
from django.core.management.commands import makemessages class Command(makemessages.Command): def build_potfiles(self): potfiles = super().build_potfiles() for potfile in sorted(set(potfiles)): self._remove_pot_creation_date(potfile) return potfiles @staticmethod def...
27.12
64
0.610619
78
678
5.141026
0.525641
0.082294
0.112219
0.104738
0.074813
0
0
0
0
0
0
0
0.29941
678
24
65
28.25
0.844211
0
0
0
0
0
0.035398
0
0
0
0
0
0
1
0.117647
false
0
0.058824
0
0.294118
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
fd2333a5ba2bad8fcd4a158981a7c15852072e07
6,529
py
Python
app/api/v2/users/views_update.py
Raywire/iReporter
ac58414b84b9c96f0be5e0d477355d0811d8b9c5
[ "MIT" ]
3
2019-01-09T15:17:28.000Z
2019-12-01T18:40:50.000Z
app/api/v2/users/views_update.py
Raywire/iReporter
ac58414b84b9c96f0be5e0d477355d0811d8b9c5
[ "MIT" ]
13
2018-11-30T05:33:13.000Z
2021-04-30T20:46:41.000Z
app/api/v2/users/views_update.py
Raywire/iReporter
ac58414b84b9c96f0be5e0d477355d0811d8b9c5
[ "MIT" ]
3
2018-12-02T16:10:12.000Z
2019-01-04T14:51:04.000Z
"""Views for users""" from flask_restful import Resource from flask import jsonify, request from app.api.v2.users.models import UserModel from app.api.v2.decorator import token_required, get_token from app.api.v2.send_email import send class UserStatus(Resource): """Class with method for updating a specific user...
33.482051
135
0.551386
682
6,529
5.159824
0.205279
0.055413
0.080989
0.037511
0.448423
0.389599
0.366581
0.345553
0.322251
0.280477
0
0.017254
0.351968
6,529
194
136
33.654639
0.814465
0.07214
0
0.581081
0
0.006757
0.224592
0.004165
0
0
0
0
0
1
0.054054
false
0
0.033784
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
fd247bba2b56b1306086374a12025c1833517c10
7,357
py
Python
LoadDataAndPrepare/Make_Dictionaries/4_make_reviews_all_words_vocab_dictionary.py
ngrover2/Automatic_Lexicon_Induction
b58a1d55f294293161dc23ab2e6d669c1c5e90d8
[ "MIT" ]
null
null
null
LoadDataAndPrepare/Make_Dictionaries/4_make_reviews_all_words_vocab_dictionary.py
ngrover2/Automatic_Lexicon_Induction
b58a1d55f294293161dc23ab2e6d669c1c5e90d8
[ "MIT" ]
null
null
null
LoadDataAndPrepare/Make_Dictionaries/4_make_reviews_all_words_vocab_dictionary.py
ngrover2/Automatic_Lexicon_Induction
b58a1d55f294293161dc23ab2e6d669c1c5e90d8
[ "MIT" ]
null
null
null
# -*- coding: utf-8 -*- import sys import os import traceback import ujson from pprint import pprint from textblob import TextBlob as tb from textblob import Word as wd import shutil from collections import defaultdict from gensim.corpora import Dictionary from socialconfig import config class get_reviews_iterable(ob...
42.773256
156
0.740791
1,113
7,357
4.538185
0.14735
0.099782
0.037616
0.036032
0.560285
0.484063
0.403286
0.339735
0.296971
0.249258
0
0.00413
0.144352
7,357
171
157
43.023392
0.798253
0.028952
0
0.128788
0
0
0.129905
0.060538
0
0
0
0
0
1
0.030303
false
0.022727
0.083333
0
0.128788
0.060606
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fd266f079f9daa527e01e31d5df3c4df79e8150b
1,126
py
Python
day 03/day03_part1.py
MischaDy/PyAdventOfCode2020
3e0a1a61ac930d7e30a0104ac617008297508fcb
[ "CC0-1.0" ]
2
2020-12-17T18:49:20.000Z
2021-02-20T16:48:14.000Z
day 03/day03_part1.py
MischaDy/PyAdventOfCode2020
3e0a1a61ac930d7e30a0104ac617008297508fcb
[ "CC0-1.0" ]
null
null
null
day 03/day03_part1.py
MischaDy/PyAdventOfCode2020
3e0a1a61ac930d7e30a0104ac617008297508fcb
[ "CC0-1.0" ]
3
2020-12-20T19:08:32.000Z
2020-12-26T22:11:15.000Z
from helpers.cyclic_list import CyclicList from helpers.coordinates2d import Coordinates2D RUN_TEST = False TEST_SOLUTION = 7 TEST_INPUT_FILE = 'test_input_day_03.txt' INPUT_FILE = 'input_day_03.txt' START = Coordinates2D((0, 0)) # top left corner TRAJECTORY = Coordinates2D((3, 1)) # right 3, down 1 ARGS = [START...
26.186047
86
0.688277
156
1,126
4.679487
0.384615
0.073973
0.049315
0.035616
0.158904
0.087671
0
0
0
0
0
0.021372
0.21048
1,126
42
87
26.809524
0.799775
0.052398
0
0.066667
0
0
0.043274
0.019755
0
0
0
0
0.033333
1
0.066667
false
0
0.066667
0
0.2
0.066667
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fd279c40ef3cc1786017d66b7c1e1b885d2e67e1
807
py
Python
binary_tree/e_path_sum.py
dhrubach/python-code-recipes
14356c6adb1946417482eaaf6f42dde4b8351d2f
[ "MIT" ]
null
null
null
binary_tree/e_path_sum.py
dhrubach/python-code-recipes
14356c6adb1946417482eaaf6f42dde4b8351d2f
[ "MIT" ]
null
null
null
binary_tree/e_path_sum.py
dhrubach/python-code-recipes
14356c6adb1946417482eaaf6f42dde4b8351d2f
[ "MIT" ]
null
null
null
############################################### # LeetCode Problem Number : 112 # Difficulty Level : Easy # URL : https://leetcode.com/problems/path-sum/ ############################################### from binary_search_tree.tree_node import TreeNode class BinaryTree: def hasPathSum(self, root: TreeNode, sum: in...
25.21875
59
0.484511
87
807
4.45977
0.471264
0.054124
0.051546
0
0
0
0
0
0
0
0
0.007339
0.324659
807
31
60
26.032258
0.704587
0.122677
0
0
0
0
0
0
0
0
0
0
0
1
0.117647
false
0
0.058824
0
0.470588
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
fd2a6655ca5c2bb5ada546fc62616fc063ba84a1
3,900
py
Python
tests/unit/guests/linux/storage/disk.py
tessia-project/tessia-baselib
07004b7f6462f081a6f7e810954fd7e0d2cdcf6b
[ "Apache-2.0" ]
1
2022-01-27T01:32:14.000Z
2022-01-27T01:32:14.000Z
tests/unit/guests/linux/storage/disk.py
tessia-project/tessia-baselib
07004b7f6462f081a6f7e810954fd7e0d2cdcf6b
[ "Apache-2.0" ]
null
null
null
tests/unit/guests/linux/storage/disk.py
tessia-project/tessia-baselib
07004b7f6462f081a6f7e810954fd7e0d2cdcf6b
[ "Apache-2.0" ]
null
null
null
# Copyright 2017 IBM Corp. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, sof...
30
78
0.646923
483
3,900
5.024845
0.403727
0.02637
0.024722
0.029666
0.181294
0.137618
0.116193
0.116193
0.116193
0.046148
0
0.006186
0.253846
3,900
129
79
30.232558
0.827835
0.319231
0
0.153846
0
0
0.091134
0
0
0
0
0
0.076923
1
0.134615
false
0
0.096154
0
0.288462
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
fd2ae8dc293d1b7377165b6678e015927d2d75d1
5,479
py
Python
kornia/x/trainer.py
AK391/kornia
a2535eb7593ee2fed94d23cc720804a16f9f0e7e
[ "ECL-2.0", "Apache-2.0" ]
null
null
null
kornia/x/trainer.py
AK391/kornia
a2535eb7593ee2fed94d23cc720804a16f9f0e7e
[ "ECL-2.0", "Apache-2.0" ]
null
null
null
kornia/x/trainer.py
AK391/kornia
a2535eb7593ee2fed94d23cc720804a16f9f0e7e
[ "ECL-2.0", "Apache-2.0" ]
null
null
null
import logging from typing import Callable, Dict import torch import torch.nn as nn from torch.utils.data import DataLoader # the accelerator library is a requirement for the Trainer # but it is optional for grousnd base user of kornia. try: from accelerate import Accelerator except ImportError: Accelerator =...
34.459119
95
0.632962
626
5,479
5.479233
0.354633
0.030612
0.025656
0.013411
0.069388
0.046647
0.046647
0.027988
0
0
0
0.002029
0.280343
5,479
158
96
34.677215
0.867867
0.334003
0
0.068182
0
0
0.083474
0.015792
0
0
0
0
0
1
0.113636
false
0
0.102273
0.034091
0.261364
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
fd2c1f1342cad7325a43f5762d5c2d1d94cfe573
2,795
py
Python
datasets/transformations/jpeg_compress.py
bytedance/Hammer
388ed20b3d9b34f33f5357d75f8fe5d726782ec8
[ "MIT" ]
97
2022-02-08T09:00:57.000Z
2022-03-23T05:33:35.000Z
datasets/transformations/jpeg_compress.py
bytedance/Hammer
388ed20b3d9b34f33f5357d75f8fe5d726782ec8
[ "MIT" ]
null
null
null
datasets/transformations/jpeg_compress.py
bytedance/Hammer
388ed20b3d9b34f33f5357d75f8fe5d726782ec8
[ "MIT" ]
7
2022-02-08T15:13:02.000Z
2022-03-19T19:11:13.000Z
# python3.7 """Implements JPEG compression on images.""" import cv2 import numpy as np try: import nvidia.dali.fn as fn import nvidia.dali.types as types except ImportError: fn = None from utils.formatting_utils import format_range from .base_transformation import BaseTransformation __all__ = ['JpegComp...
35.379747
80
0.65975
348
2,795
5.140805
0.413793
0.060369
0.053661
0.027949
0
0
0
0
0
0
0
0.01677
0.253309
2,795
78
81
35.833333
0.840441
0.284079
0
0.093023
0
0
0.008235
0
0
0
0
0
0
1
0.069767
false
0
0.162791
0
0.325581
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
fd2ca1a6e56d2464e000ae2d9a68e5afd6f6c238
2,046
py
Python
venv/VFR/flask_app_3d.py
flhataf/Virtual-Fitting-Room
e5b41849df963cebd3b7deb7e87d643ece5b6d18
[ "MIT" ]
null
null
null
venv/VFR/flask_app_3d.py
flhataf/Virtual-Fitting-Room
e5b41849df963cebd3b7deb7e87d643ece5b6d18
[ "MIT" ]
null
null
null
venv/VFR/flask_app_3d.py
flhataf/Virtual-Fitting-Room
e5b41849df963cebd3b7deb7e87d643ece5b6d18
[ "MIT" ]
null
null
null
# -*- coding: utf-8 -*- """ Created on Mon Feb 15 00:31:35 2021 @author: RayaBit """ from flask import Flask, render_template, Response from imutils.video import VideoStream from skeletonDetector import skeleton import cv2 from skeleton3DDetector import Skeleton3dDetector from visualization import Visualizer import t...
26.571429
115
0.616813
269
2,046
4.572491
0.483271
0.042276
0.026829
0.035772
0.043902
0
0
0
0
0
0
0.05239
0.253666
2,046
77
116
26.571429
0.753111
0.160313
0
0.155556
0
0
0.091069
0.015276
0
0
0
0
0
1
0.066667
false
0
0.155556
0.044444
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
fd2dbbfa0aac3167c6b35b08529f51283edf8826
8,144
py
Python
schedsi/threads/thread.py
z33ky/schedsi
3affe28a3e1d2001c639d7c0423cb105d1991590
[ "CC0-1.0" ]
1
2017-08-03T12:58:53.000Z
2017-08-03T12:58:53.000Z
schedsi/threads/thread.py
z33ky/schedsi
3affe28a3e1d2001c639d7c0423cb105d1991590
[ "CC0-1.0" ]
null
null
null
schedsi/threads/thread.py
z33ky/schedsi
3affe28a3e1d2001c639d7c0423cb105d1991590
[ "CC0-1.0" ]
null
null
null
"""Define the :class:`Thread`.""" import threading from schedsi.cpu import request as cpurequest from schedsi.cpu.time import Time #: Whether to log individual times, or only the sum LOG_INDIVIDUAL = True class _ThreadStats: # pylint: disable=too-few-public-methods """Thread statistics.""" def __init__(s...
32.706827
94
0.608915
1,025
8,144
4.687805
0.187317
0.077836
0.048699
0.029136
0.31155
0.227888
0.150052
0.13257
0.091988
0.064932
0
0.002316
0.310658
8,144
248
95
32.83871
0.85358
0.336198
0
0.232759
0
0
0.005653
0
0
0
0
0
0.189655
1
0.12069
false
0
0.025862
0
0.206897
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
fd2e8e4f0baea2b1df6722ef44a729d6280f10cc
5,552
py
Python
application/src/initializer/auxiliary_methods.py
eyardley/CSC648-SoftwareEngineering-Snapster
6dbe1cf9b34de6d6dbc6be75db3a34583f67c01a
[ "MIT" ]
null
null
null
application/src/initializer/auxiliary_methods.py
eyardley/CSC648-SoftwareEngineering-Snapster
6dbe1cf9b34de6d6dbc6be75db3a34583f67c01a
[ "MIT" ]
3
2021-06-08T21:39:12.000Z
2022-01-13T02:46:20.000Z
application/src/initializer/auxiliary_methods.py
eyardley/CSC648-SoftwareEngineering-Snapster
6dbe1cf9b34de6d6dbc6be75db3a34583f67c01a
[ "MIT" ]
1
2021-05-09T21:01:28.000Z
2021-05-09T21:01:28.000Z
def fill_team_about(db): ############################### # FILL TEAM ABOUT TABLE # ############################### print('Inserting data into team member profiles table') add_about_team_query = ("INSERT INTO team_about " "(name, link, position, image, description,...
52.377358
263
0.568444
719
5,552
4.23644
0.222531
0.010506
0.04432
0.073867
0.395272
0.343073
0.322718
0.317794
0.317794
0.317794
0
0.039896
0.237032
5,552
106
264
52.377358
0.679178
0.012968
0
0.2625
0
0.025
0.562654
0.094878
0
0
0
0
0
1
0.0375
false
0
0
0
0.0375
0.075
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fd3187f8e540b93ec7789114fa6cc6e3969608ec
1,335
py
Python
pyBRML/pyBRML/core.py
anich003/brml_toolkit
de8218bdf333902431d4c0055fcf5cb3dc47d0c1
[ "MIT" ]
null
null
null
pyBRML/pyBRML/core.py
anich003/brml_toolkit
de8218bdf333902431d4c0055fcf5cb3dc47d0c1
[ "MIT" ]
null
null
null
pyBRML/pyBRML/core.py
anich003/brml_toolkit
de8218bdf333902431d4c0055fcf5cb3dc47d0c1
[ "MIT" ]
null
null
null
import copy from pyBRML import utils from pyBRML import Array def multiply_potentials(list_of_potentials): """ Returns the product of each potential in list_of_potentials, useful for calculating joint probabilities. For example, if the joint probability of a system is defined as p(A,B,C) = p(...
35.131579
94
0.743071
190
1,335
5.115789
0.436842
0.030864
0.082305
0.034979
0.055556
0
0
0
0
0
0
0.002825
0.204494
1,335
37
95
36.081081
0.912429
0.534831
0
0
0
0
0
0
0
0
0
0
0
1
0.076923
false
0
0.230769
0
0.384615
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fd3394f2b7968055dc2a5d2b8bdde46ae4644c49
2,098
py
Python
lib/akf_known_uncategories.py
UB-Mannheim/docxstruct
dd6d99b6fd6f5660fdc61a14b60e70a54ac9be85
[ "Apache-2.0" ]
1
2019-03-06T14:59:44.000Z
2019-03-06T14:59:44.000Z
lib/akf_known_uncategories.py
UB-Mannheim/docxstruct
dd6d99b6fd6f5660fdc61a14b60e70a54ac9be85
[ "Apache-2.0" ]
null
null
null
lib/akf_known_uncategories.py
UB-Mannheim/docxstruct
dd6d99b6fd6f5660fdc61a14b60e70a54ac9be85
[ "Apache-2.0" ]
null
null
null
import re class KnownUncategories(object): """ List of known entries in test_data which are no categories, but are recognized as such """ def __init__(self): # un-category regex strings (care for commas) self.uc = [ "Beteiligung", # 1956: is part of B...
31.313433
108
0.515253
229
2,098
4.598253
0.510917
0.034188
0.047483
0.05698
0
0
0
0
0
0
0
0.029088
0.393708
2,098
67
109
31.313433
0.798742
0.306482
0
0.088889
0
0
0.152738
0
0
0
0
0
0
1
0.088889
false
0
0.022222
0.044444
0.222222
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fd33bdf592a5bbf5b20d72627b7e89fa294ef5bf
1,640
py
Python
maps/templatetags/mapas_tags.py
lsalta/mapground
d927d283dab6f756574bd88b3251b9e68f000ca7
[ "MIT" ]
null
null
null
maps/templatetags/mapas_tags.py
lsalta/mapground
d927d283dab6f756574bd88b3251b9e68f000ca7
[ "MIT" ]
3
2020-02-11T23:04:56.000Z
2021-06-10T18:07:53.000Z
maps/templatetags/mapas_tags.py
lsalta/mapground
d927d283dab6f756574bd88b3251b9e68f000ca7
[ "MIT" ]
1
2021-08-20T14:49:09.000Z
2021-08-20T14:49:09.000Z
from django import template register = template.Library() def mostrar_resumen_mapa(context, m, order_by): # print context to_return = { 'mapa': m, 'order_by': order_by, } return to_return @register.inclusion_tag('mapas/lista_mapas.html') def mostrar_mapas(lista_mapas, order_by): to_return = { ...
22.777778
83
0.668902
230
1,640
4.582609
0.33913
0.04649
0.049336
0.026565
0.135674
0.100569
0.100569
0.100569
0.100569
0.100569
0
0.006844
0.198171
1,640
71
84
23.098592
0.794677
0.215244
0
0.25
0
0
0.103336
0.017901
0
0
0
0
0
1
0.175
false
0
0.025
0.05
0.45
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
fd349e3352814cffd9d5b6c0c4f84624bb4c6bc6
1,868
py
Python
app/services/aggregator/aggr.py
maestro-server/report-app
0bf9014400f2979c51c1c544347d5134c73facdf
[ "Apache-2.0" ]
1
2020-05-19T20:18:05.000Z
2020-05-19T20:18:05.000Z
app/services/aggregator/aggr.py
maestro-server/report-app
0bf9014400f2979c51c1c544347d5134c73facdf
[ "Apache-2.0" ]
2
2019-10-21T14:56:04.000Z
2020-03-27T12:48:26.000Z
app/services/aggregator/aggr.py
maestro-server/report-app
0bf9014400f2979c51c1c544347d5134c73facdf
[ "Apache-2.0" ]
null
null
null
import pandas as pd from pydash.objects import get class Aggregator(object): def __init__(self, field, lens=None, sublens='_id', include=[], opts={}): self._field = field self._lens = lens self._sublens = sublens self._result = [] self._transf = [] self._include = ...
23.64557
77
0.556745
207
1,868
4.806763
0.328502
0.042211
0.096482
0.036181
0.138693
0.138693
0.082412
0.082412
0
0
0
0.000798
0.329229
1,868
78
78
23.948718
0.793296
0
0
0.109091
0
0
0.009636
0
0
0
0
0
0
1
0.2
false
0
0.036364
0.054545
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
fd3bd480b9c0a1b8e0dc9e02d722d288943bec44
357
py
Python
DataStructuresAndAlgorithms/sorting algorithms/SelectionSort.py
armaan2k/Training-Exercises
6dd94efb6cd6e0dc6c24e2b7d5e74588a74d190d
[ "MIT" ]
null
null
null
DataStructuresAndAlgorithms/sorting algorithms/SelectionSort.py
armaan2k/Training-Exercises
6dd94efb6cd6e0dc6c24e2b7d5e74588a74d190d
[ "MIT" ]
null
null
null
DataStructuresAndAlgorithms/sorting algorithms/SelectionSort.py
armaan2k/Training-Exercises
6dd94efb6cd6e0dc6c24e2b7d5e74588a74d190d
[ "MIT" ]
null
null
null
def selection_sort(A): n = len(A) for i in range(n - 1): position = i for j in range(i + 1, n): if A[j] < A[position]: position = j temp = A[i] A[i] = A[position] A[position] = temp A = [3, 5, 8, 9, 6, 2] print('Original Array: ', A) selectio...
21
34
0.473389
57
357
2.929825
0.438596
0.161677
0.167665
0
0
0
0
0
0
0
0
0.035556
0.369748
357
16
35
22.3125
0.706667
0
0
0
0
0
0.084034
0
0
0
0
0
0
1
0.071429
false
0
0
0
0.071429
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
fd464df7fbbebbe26bc4d827bb8cf980aecbe03a
13,019
py
Python
src/model/build_models.py
VinGPan/classification_model_search
fab7ce6fc131b858f1b79633e0f7b86d1446c93d
[ "MIT" ]
null
null
null
src/model/build_models.py
VinGPan/classification_model_search
fab7ce6fc131b858f1b79633e0f7b86d1446c93d
[ "MIT" ]
null
null
null
src/model/build_models.py
VinGPan/classification_model_search
fab7ce6fc131b858f1b79633e0f7b86d1446c93d
[ "MIT" ]
null
null
null
import os import os.path import pickle from shutil import copyfile import numpy as np import pandas as pd import xgboost as xgb from sklearn.decomposition import KernelPCA from sklearn.decomposition import PCA from sklearn.ensemble import AdaBoostClassifier from sklearn.ensemble import GradientBoostingClassifier from ...
47.688645
118
0.541132
1,325
13,019
5.111698
0.216604
0.032482
0.018603
0.031891
0.242433
0.150746
0.111324
0.088882
0.088882
0.067326
0
0.006846
0.293187
13,019
272
119
47.863971
0.729189
0.074583
0
0.142857
0
0
0.133548
0
0.004762
0
0
0
0
1
0.02381
false
0.009524
0.138095
0
0.166667
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fd4d6ed01b3decd5927f1d836a338350d16f500c
941
py
Python
LC_problems/822.py
Howardhuang98/Blog
cf58638d6d0bbf55b95fe08e43798e7dd14219ac
[ "MIT" ]
null
null
null
LC_problems/822.py
Howardhuang98/Blog
cf58638d6d0bbf55b95fe08e43798e7dd14219ac
[ "MIT" ]
null
null
null
LC_problems/822.py
Howardhuang98/Blog
cf58638d6d0bbf55b95fe08e43798e7dd14219ac
[ "MIT" ]
null
null
null
#!/usr/bin/env python # -*- encoding: utf-8 -*- """ @File : 822.py @Contact : huanghoward@foxmail.com @Modify Time : 2022/3/29 13:19 ------------ """ from typing import List class Solution: def flipgame(self, fronts: List[int], backs: List[int]) -> int: ans = float('+inf') fo...
27.676471
67
0.420829
102
941
3.803922
0.568627
0.036082
0.051546
0.082474
0.092784
0
0
0
0
0
0
0.032505
0.444208
941
34
68
27.676471
0.709369
0.170032
0
0.130435
0
0
0.015524
0
0
0
0
0
0
1
0.043478
false
0
0.043478
0
0.173913
0.043478
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fd4d784f79a128a2168a7d3f9c317a2fb64d12f1
22,795
py
Python
result/analyze.py
kuriatsu/PIE_RAS
8dd33b4d4f7b082337a2645c0a72082374768b52
[ "Apache-2.0" ]
null
null
null
result/analyze.py
kuriatsu/PIE_RAS
8dd33b4d4f7b082337a2645c0a72082374768b52
[ "Apache-2.0" ]
null
null
null
result/analyze.py
kuriatsu/PIE_RAS
8dd33b4d4f7b082337a2645c0a72082374768b52
[ "Apache-2.0" ]
null
null
null
#! /usr/bin/python3 # -*- coding: utf-8 -*- import pickle import pandas as pd import xml.etree.ElementTree as ET import math import seaborn as sns import matplotlib.pyplot as plt import numpy as np import csv import glob import scikit_posthocs as sp from scipy import stats import os from scipy import stats import scik...
44.696078
222
0.612547
3,196
22,795
4.176471
0.098874
0.052592
0.053941
0.075517
0.737114
0.699655
0.64579
0.596344
0.54128
0.529293
0
0.036641
0.176267
22,795
509
223
44.78389
0.674229
0.087037
0
0.506173
0
0.014815
0.158824
0.021922
0
0
0
0
0
1
0
false
0
0.034568
0
0.034568
0.101235
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fd518544ef8c44c965453eb8925336fcec4f3ee3
3,005
py
Python
convert_nbrId_to_orgnr.py
obtitus/barnehagefakta_osm
4539525f6defcc67a087cc57baad996f8d76b8bd
[ "Apache-2.0" ]
1
2018-10-05T17:00:23.000Z
2018-10-05T17:00:23.000Z
convert_nbrId_to_orgnr.py
obtitus/barnehagefakta_osm
4539525f6defcc67a087cc57baad996f8d76b8bd
[ "Apache-2.0" ]
6
2016-05-29T09:33:06.000Z
2019-12-18T20:24:50.000Z
convert_nbrId_to_orgnr.py
obtitus/barnehagefakta_osm
4539525f6defcc67a087cc57baad996f8d76b8bd
[ "Apache-2.0" ]
null
null
null
# Database switched from having nsrId to using orgnr, this script helps with this conversion. import os import re import json import subprocess from glob import glob from utility_to_osm import file_util if __name__ == '__main__': data_dir = 'data' #'barnehagefakta_osm_data/data' nsrId_to_orgnr_filename = 'nsr...
40.608108
110
0.509151
324
3,005
4.512346
0.314815
0.067031
0.106703
0.046512
0.365937
0.305062
0.262654
0.262654
0.213406
0.213406
0
0.00564
0.409983
3,005
73
111
41.164384
0.818951
0.092845
0
0.357143
0
0
0.082751
0.050018
0
0
0
0
0
1
0
false
0
0.107143
0
0.107143
0.071429
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fd543b58f8ff3f846e998d58939fe4d5bc4acf05
5,859
py
Python
main.py
MO-RISE/crowsnest-connector-cluon-n2k
11eaefd8ebe76829ec8fe91f99da9acbc84e5187
[ "Apache-2.0" ]
null
null
null
main.py
MO-RISE/crowsnest-connector-cluon-n2k
11eaefd8ebe76829ec8fe91f99da9acbc84e5187
[ "Apache-2.0" ]
null
null
null
main.py
MO-RISE/crowsnest-connector-cluon-n2k
11eaefd8ebe76829ec8fe91f99da9acbc84e5187
[ "Apache-2.0" ]
null
null
null
"""Main entrypoint for this application""" from pathlib import Path from math import degrees from datetime import datetime import logging import warnings from environs import Env from streamz import Stream from paho.mqtt.client import Client as MQTT from pycluon import OD4Session, Envelope as cEnvelope from pycluo...
30.046154
135
0.70524
769
5,859
5.192458
0.288687
0.010018
0.012021
0.014525
0.326071
0.282995
0.268971
0.237415
0.196844
0.196844
0
0.018235
0.185697
5,859
194
136
30.201031
0.818696
0.122717
0
0.166667
0
0.016667
0.187402
0.025314
0
0
0
0
0
1
0.033333
false
0.016667
0.141667
0
0.233333
0.008333
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fd54b2677eda2400e60664de51925feee4550c09
7,569
py
Python
cocapi/client/api.py
bim-ba/coc-api
69ff957803cb991dfad8df3af752d193171f2ef0
[ "Unlicense" ]
1
2022-03-29T12:39:36.000Z
2022-03-29T12:39:36.000Z
cocapi/client/api.py
bim-ba/coc-api
69ff957803cb991dfad8df3af752d193171f2ef0
[ "Unlicense" ]
null
null
null
cocapi/client/api.py
bim-ba/coc-api
69ff957803cb991dfad8df3af752d193171f2ef0
[ "Unlicense" ]
null
null
null
from typing import Any, Optional from dataclasses import dataclass, field import aiohttp from ..types import aliases from ..types import exceptions @dataclass class BaseMethod: # config base_url: aliases.Url | None = field(init=False, default=None) default_http_method: aliases.RequestMethod | None = fie...
34.880184
143
0.62069
797
7,569
5.771644
0.258469
0.040652
0.041304
0.019565
0.172609
0.148261
0.08
0
0
0
0
0.006826
0.225789
7,569
216
144
35.041667
0.778157
0.027877
0
0.055556
0
0
0.208555
0.104175
0
0
0
0
0
1
0.018519
false
0.018519
0.046296
0
0.444444
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
fd56674cc383ba9fa6321e89c2463e251d94abf2
28,594
py
Python
ratings.py
struct-rgb/ratings
40d56455406cfee9731c564e54ed7610b5a9641c
[ "MIT" ]
null
null
null
ratings.py
struct-rgb/ratings
40d56455406cfee9731c564e54ed7610b5a9641c
[ "MIT" ]
null
null
null
ratings.py
struct-rgb/ratings
40d56455406cfee9731c564e54ed7610b5a9641c
[ "MIT" ]
null
null
null
#!/usr/bin/python3 import re import json import random from pathlib import Path from datetime import date from typing import Any, Callable, Set, Tuple import gi gi.require_version("Gtk", "3.0") from gi.repository import Gtk from tags import Filter, Box, CompilationError, escape, enum_subject_parser_factory, tagset,...
26.305428
148
0.708435
3,978
28,594
4.918301
0.087984
0.036187
0.026987
0.015742
0.485101
0.430411
0.363046
0.329415
0.305597
0.28229
0
0.003033
0.169721
28,594
1,087
149
26.305428
0.821069
0.023641
0
0.304956
0
0
0.094603
0.007787
0
0
0
0.00092
0
1
0.142313
false
0.003812
0.012706
0.027954
0.227446
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
fd567ff8b78d041903de62043964d3c66a7450a4
10,218
py
Python
K64F Python Interfacing Testing/Loop_Read.py
Marnold212/CamLab-K64F
20689b4be38aa329990dbfe13eec43d74b3ae27a
[ "Apache-2.0" ]
null
null
null
K64F Python Interfacing Testing/Loop_Read.py
Marnold212/CamLab-K64F
20689b4be38aa329990dbfe13eec43d74b3ae27a
[ "Apache-2.0" ]
null
null
null
K64F Python Interfacing Testing/Loop_Read.py
Marnold212/CamLab-K64F
20689b4be38aa329990dbfe13eec43d74b3ae27a
[ "Apache-2.0" ]
null
null
null
import numpy as np from serial.serialutil import SerialException import serial.tools.list_ports as port_list import serial import time def Hex_To_Dec(input): # input of form "40048024" return int(input, 16) def Hex_To_Bin(input): # input of form "40048024" return bin(int(input, 16)) def Hex_To_Bytes(input):...
47.305556
224
0.641124
1,496
10,218
4.198529
0.20254
0.028658
0.014011
0.012259
0.465372
0.422067
0.373348
0.338481
0.315555
0.307594
0
0.040964
0.256997
10,218
216
225
47.305556
0.786354
0.368174
0
0.276923
0
0
0.037518
0
0
0
0
0
0
1
0.092308
false
0
0.038462
0.030769
0.215385
0.023077
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fd5ed16b310aacd62d38f7ed79f88685cc24b454
1,189
py
Python
senlerpy/senler.py
tezmen/SenlerPy
ce8ab8512ed795e8e6f1e7ff76f54c6aa2d3cd82
[ "Apache-2.0" ]
2
2019-03-19T08:46:27.000Z
2020-11-12T10:55:59.000Z
senlerpy/senler.py
tezmen/SenlerPy
ce8ab8512ed795e8e6f1e7ff76f54c6aa2d3cd82
[ "Apache-2.0" ]
1
2021-03-30T16:55:09.000Z
2021-03-30T16:55:09.000Z
senlerpy/senler.py
tezmen/SenlerPy
ce8ab8512ed795e8e6f1e7ff76f54c6aa2d3cd82
[ "Apache-2.0" ]
7
2019-03-19T08:47:35.000Z
2021-08-24T11:47:41.000Z
# -*- coding: utf-8 -*- import json import logging from .request import RequestApi from .exceptions import ApiError, WrongId, HttpError logger = logging.getLogger(__name__) class Senler: def __init__(self, secret, vk_group_id=None): self.vk_group = vk_group_id self.__secret = str(secret).strip() self._rq = Re...
25.847826
81
0.735071
172
1,189
4.77907
0.372093
0.110706
0.054745
0.03163
0.043796
0
0
0
0
0
0
0.000988
0.148865
1,189
45
82
26.422222
0.811265
0.017662
0
0.055556
0
0
0.150086
0.062607
0
0
0
0
0
1
0.166667
false
0
0.111111
0.055556
0.416667
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
fd5f3466a377d682676cf2f35cddaec4567f59df
11,354
py
Python
robinhoodbot/main.py
bpk9/Robinhood-Stock-Trading-Bot
c2ab0dd58f5236ee051ad38277c8ba5c46bd0aa4
[ "MIT" ]
null
null
null
robinhoodbot/main.py
bpk9/Robinhood-Stock-Trading-Bot
c2ab0dd58f5236ee051ad38277c8ba5c46bd0aa4
[ "MIT" ]
null
null
null
robinhoodbot/main.py
bpk9/Robinhood-Stock-Trading-Bot
c2ab0dd58f5236ee051ad38277c8ba5c46bd0aa4
[ "MIT" ]
null
null
null
import pyotp import robin_stocks as r import pandas as pd import numpy as np import ta as ta from pandas.plotting import register_matplotlib_converters from ta import * from misc import * from tradingstats import * from config import * #Log in to Robinhood #Put your username and password in a config.py file in the sam...
42.365672
201
0.656068
1,562
11,354
4.62484
0.211908
0.028239
0.011074
0.013566
0.332087
0.276993
0.238234
0.223284
0.181202
0.168605
0
0.009769
0.215607
11,354
267
202
42.524345
0.80137
0.353708
0
0.184211
0
0
0.127116
0.007604
0
0
0
0
0
1
0.085526
false
0.006579
0.065789
0.006579
0.230263
0.118421
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fd618c3a159e9f99d7c6ca6d044db4a500817e13
1,160
py
Python
debug_toolbar/panels/profiling.py
chrismaille/fastapi-debug-toolbar
76d1e78eda4a23fc2b3e3d3c978ee9d8dbf025ae
[ "BSD-3-Clause" ]
36
2021-07-22T08:11:31.000Z
2022-01-31T13:09:26.000Z
debug_toolbar/panels/profiling.py
chrismaille/fastapi-debug-toolbar
76d1e78eda4a23fc2b3e3d3c978ee9d8dbf025ae
[ "BSD-3-Clause" ]
10
2021-07-21T19:39:38.000Z
2022-02-26T15:35:35.000Z
debug_toolbar/panels/profiling.py
chrismaille/fastapi-debug-toolbar
76d1e78eda4a23fc2b3e3d3c978ee9d8dbf025ae
[ "BSD-3-Clause" ]
2
2021-07-28T09:55:13.000Z
2022-02-18T11:29:25.000Z
import typing as t from fastapi import Request, Response from pyinstrument import Profiler from starlette.concurrency import run_in_threadpool from debug_toolbar.panels import Panel from debug_toolbar.types import Stats from debug_toolbar.utils import is_coroutine, matched_endpoint class ProfilingPanel(Panel): ...
30.526316
82
0.70431
139
1,160
5.741007
0.395683
0.070175
0.06015
0.065163
0.077694
0
0
0
0
0
0
0
0.218103
1,160
37
83
31.351351
0.879824
0
0
0
0
0
0.031897
0.018103
0
0
0
0
0
1
0
false
0
0.269231
0
0.5
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fd63367d2463bae216c32c0f3162ba07be04c060
3,003
py
Python
test/system/auto/simple/compaction.py
marciosilva/accumulo
70404cbd1e0a2d2b7c2235009e158979abeef35f
[ "Apache-2.0" ]
3
2021-11-11T05:18:23.000Z
2021-11-11T05:18:43.000Z
test/system/auto/simple/compaction.py
jatrost/accumulo
6be40f2f3711aaa7d0b68b5b6852b79304af3cff
[ "Apache-2.0" ]
1
2021-06-22T09:52:37.000Z
2021-06-22T09:52:37.000Z
test/system/auto/simple/compaction.py
isabella232/accumulo-1
70404cbd1e0a2d2b7c2235009e158979abeef35f
[ "Apache-2.0" ]
1
2021-06-22T09:33:38.000Z
2021-06-22T09:33:38.000Z
# 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 use ...
33.741573
109
0.656011
377
3,003
5.204244
0.461538
0.049949
0.033639
0.01631
0.115189
0.115189
0.115189
0.077472
0.077472
0.077472
0
0.014329
0.2331
3,003
88
110
34.125
0.837603
0.299034
0
0.075472
0
0.018868
0.226174
0.082079
0
0
0
0
0.09434
1
0.056604
false
0.018868
0.09434
0
0.245283
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
b5b97c67425c6b42d928076e5a8d8cb8fc8a23c8
12,107
py
Python
python/lexical_analysis.py
Compiler-Construction-Uni-Freiburg/lecture-notes-2021
56300e6649e32f0594bbbd046a2e19351c57dd0c
[ "BSD-3-Clause" ]
1
2022-01-05T07:11:01.000Z
2022-01-05T07:11:01.000Z
python/lexical_analysis.py
Compiler-Construction-Uni-Freiburg/lecture-notes-2021
56300e6649e32f0594bbbd046a2e19351c57dd0c
[ "BSD-3-Clause" ]
null
null
null
python/lexical_analysis.py
Compiler-Construction-Uni-Freiburg/lecture-notes-2021
56300e6649e32f0594bbbd046a2e19351c57dd0c
[ "BSD-3-Clause" ]
null
null
null
from dataclasses import dataclass from functools import reduce from typing import Callable, Iterable, Iterator ''' The first phase of a compiler is called `lexical analysis` implemented by a `scanner` or `lexer`. It breaks a program into a sequence `lexemes`: meaningful substrings of the input. It also transforms...
32.810298
105
0.641943
1,712
12,107
4.468458
0.202103
0.008627
0.006797
0.013072
0.181961
0.120784
0.069542
0.059608
0.035033
0.025621
0
0.013235
0.22615
12,107
369
106
32.810298
0.798591
0.090278
0
0.258621
0
0
0.068941
0
0
0
0
0
0
1
0.112069
false
0.025862
0.012931
0.047414
0.439655
0.008621
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b5bc0b82b561c3ccd0c214272db1e77e19243f08
4,003
py
Python
rad/rest/client/cli/zpool/cmd_zpool_list.py
guillermomolina/rad-rest-client
c22528764bdf9dddc5ff7d269d7465d34878a7e3
[ "Apache-2.0" ]
1
2021-09-17T13:40:13.000Z
2021-09-17T13:40:13.000Z
rad/rest/client/cli/zpool/cmd_zpool_list.py
guillermomolina/rad-rest-client
c22528764bdf9dddc5ff7d269d7465d34878a7e3
[ "Apache-2.0" ]
null
null
null
rad/rest/client/cli/zpool/cmd_zpool_list.py
guillermomolina/rad-rest-client
c22528764bdf9dddc5ff7d269d7465d34878a7e3
[ "Apache-2.0" ]
1
2021-09-17T16:26:32.000Z
2021-09-17T16:26:32.000Z
# Copyright 2021, Guillermo Adrián Molina # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in ...
43.043011
105
0.572321
422
4,003
5.308057
0.395735
0.026786
0.019643
0.030357
0.160714
0.142857
0.142857
0.049107
0.049107
0.049107
0
0.004552
0.341494
4,003
92
106
43.51087
0.84522
0.142143
0
0.106061
0
0
0.114653
0
0
0
0
0
0
1
0.030303
false
0
0.121212
0
0.19697
0.075758
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b5bcf620df665e14fd0ade4b0917ffe41b1ea768
3,736
py
Python
Sofware/main.py
Mark-MDO47/PiPod
990042ff5ad69d9fc93d1bd5bd684db730156222
[ "MIT" ]
63
2018-08-02T20:50:41.000Z
2022-03-02T02:42:48.000Z
Sofware/main.py
Mark-MDO47/PiPod
990042ff5ad69d9fc93d1bd5bd684db730156222
[ "MIT" ]
2
2018-08-30T16:31:48.000Z
2021-12-02T01:28:23.000Z
Sofware/main.py
Mark-MDO47/PiPod
990042ff5ad69d9fc93d1bd5bd684db730156222
[ "MIT" ]
14
2018-08-05T04:45:07.000Z
2022-02-18T10:56:20.000Z
#!/usr/bin/python3 import playback import display import navigation import device import pygame done = False music = playback.music() view = display.view() menu = navigation.menu() PiPod = device.PiPod() menu.loadMetadata() status = PiPod.getStatus() songMetadata = music.getStatus() displayUpdate = pygame.USEREVENT ...
34.592593
103
0.482869
334
3,736
5.374252
0.317365
0.093593
0.062396
0.066852
0.298607
0.179387
0.083565
0.083565
0.083565
0
0
0.007303
0.413544
3,736
107
104
34.915888
0.811958
0.05166
0
0.352273
0
0
0.069511
0
0
0
0
0
0
1
0
false
0
0.056818
0
0.056818
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
b5bdd10944be47a0eef70a2d5c3fc45fddcfaaf6
5,698
py
Python
src/contentbase/auditor.py
ClinGen/clincoded
5624c74546ce2a44eda00ee632a8de8c2099da10
[ "MIT" ]
30
2015-09-23T20:38:57.000Z
2021-03-10T03:12:46.000Z
src/contentbase/auditor.py
ClinGen/clincoded
5624c74546ce2a44eda00ee632a8de8c2099da10
[ "MIT" ]
2,132
2015-06-08T21:50:35.000Z
2022-02-15T22:44:18.000Z
src/contentbase/auditor.py
ClinGen/clincoded
5624c74546ce2a44eda00ee632a8de8c2099da10
[ "MIT" ]
10
2015-09-25T20:11:25.000Z
2020-12-09T02:58:44.000Z
""" Cross-object data auditing Schema validation allows for checking values within a single object. We also need to perform higher order checking between linked objects. """ from past.builtins import basestring import logging import venusian logger = logging.getLogger(__name__) def includeme(config): config.re...
32.56
92
0.551071
584
5,698
5.207192
0.234589
0.023676
0.029596
0.039461
0.204209
0.186452
0.186452
0.146005
0.092733
0.092733
0
0.007754
0.343629
5,698
174
93
32.747126
0.805348
0.055985
0
0.123188
0
0
0.076363
0
0
0
0
0
0
1
0.07971
false
0
0.021739
0.007246
0.15942
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
b5cdf29e6b6b8257a8b1c9b388ba9bf3693defbc
726
py
Python
config.py
adesolagbenga0052/web-app
c6d6ca3f998897986ac25a1e93477af0a8bfacf6
[ "Apache-2.0" ]
null
null
null
config.py
adesolagbenga0052/web-app
c6d6ca3f998897986ac25a1e93477af0a8bfacf6
[ "Apache-2.0" ]
null
null
null
config.py
adesolagbenga0052/web-app
c6d6ca3f998897986ac25a1e93477af0a8bfacf6
[ "Apache-2.0" ]
null
null
null
"""Flask configuration.""" from os import environ, path basedir = path.abspath(path.dirname(__file__)) class Config: """Base config.""" SECRET_KEY = "qsZ5srBF9-j3tgdMsd11hdbg2VLUyKQYqWFQ1EZyKI6PDVVTLXduxWoM1N0wESR0zFvSPFDs9ogpMjgl9wFxXw" STATIC_FOLDER = 'static' TEMPLATES_FOLDER = 'templates'...
27.923077
106
0.698347
67
726
7.313433
0.58209
0.044898
0.057143
0.110204
0
0
0
0
0
0
0
0.022648
0.209366
726
26
107
27.923077
0.83101
0.045455
0
0
0
0
0.24924
0.168693
0
0
0
0
0
1
0
false
0
0.055556
0
0.944444
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
b5d0213de62ed3ea48e3a10bf0cc5d6b41c2e553
5,979
py
Python
djproject/pictureupload/views.py
missingDown/webForUpload
fbd5ed9e8cfcd4ad906913f4a31c24e87919f9a3
[ "MIT" ]
null
null
null
djproject/pictureupload/views.py
missingDown/webForUpload
fbd5ed9e8cfcd4ad906913f4a31c24e87919f9a3
[ "MIT" ]
null
null
null
djproject/pictureupload/views.py
missingDown/webForUpload
fbd5ed9e8cfcd4ad906913f4a31c24e87919f9a3
[ "MIT" ]
null
null
null
from django.shortcuts import render from django.http import HttpResponse import logging import json import base64 import time # Create your views here. logger = logging.getLogger(__name__) # 文件上传:form-data/Multipart方式 POST方法 def index(request): sendfile = request.FILES.items() haveFiles = False for key,...
38.082803
85
0.632882
648
5,979
5.79784
0.239198
0.061485
0.117115
0.143732
0.566676
0.566676
0.539792
0.539792
0.520096
0.425872
0
0.025232
0.224452
5,979
157
86
38.082803
0.78499
0.078608
0
0.418182
0
0
0.209798
0.025496
0
0
0
0
0
1
0.036364
false
0
0.054545
0
0.281818
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
b5d0c034f7242aa14fa3baca13d703e86f187f17
276
py
Python
torrents/tests/test_file.py
noahgoldman/torwiz
213be5cf3b62d2c18c09e2fe4b869c549c263f32
[ "MIT" ]
1
2015-03-09T01:58:23.000Z
2015-03-09T01:58:23.000Z
torrents/tests/test_file.py
noahgoldman/torwiz
213be5cf3b62d2c18c09e2fe4b869c549c263f32
[ "MIT" ]
3
2015-04-01T22:49:58.000Z
2015-05-01T19:09:11.000Z
torrents/tests/test_file.py
noahgoldman/torwiz
213be5cf3b62d2c18c09e2fe4b869c549c263f32
[ "MIT" ]
null
null
null
from bson.objectid import ObjectId from torrents.file import TorrentFile class TestTorrentFile: def test_get_output_file(self): id1 = ObjectId() file1 = TorrentFile(id1) assert file1.get_output_file() == 'torrent_files/' + str(id1) + '.torrent'
25.090909
82
0.695652
33
276
5.636364
0.606061
0.096774
0.139785
0
0
0
0
0
0
0
0
0.022831
0.206522
276
10
83
27.6
0.826484
0
0
0
0
0
0.07971
0
0
0
0
0
0.142857
1
0.142857
false
0
0.285714
0
0.571429
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
b5d13876f65729d4efb83ad2b61955efd49a0d23
2,444
py
Python
google/cloud/storage/benchmarks/storage_throughput_plots.py
millerantonio810/google-cloud-cpp
71582d922bc22b0dcbc58234f36c726ea3b7c171
[ "Apache-2.0" ]
1
2021-01-16T02:43:50.000Z
2021-01-16T02:43:50.000Z
google/cloud/storage/benchmarks/storage_throughput_plots.py
millerantonio810/google-cloud-cpp
71582d922bc22b0dcbc58234f36c726ea3b7c171
[ "Apache-2.0" ]
null
null
null
google/cloud/storage/benchmarks/storage_throughput_plots.py
millerantonio810/google-cloud-cpp
71582d922bc22b0dcbc58234f36c726ea3b7c171
[ "Apache-2.0" ]
1
2020-05-09T20:12:05.000Z
2020-05-09T20:12:05.000Z
#!/usr/bin/env python3 # Copyright 2020 Google LLC # # 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 ...
26.857143
86
0.657529
347
2,444
4.556196
0.495677
0.037951
0.011385
0.02024
0.024035
0.024035
0
0
0
0
0
0.021619
0.18617
2,444
90
87
27.155556
0.773253
0.296236
0
0.041667
0
0
0.211744
0
0
0
0
0
0
1
0.041667
false
0
0.083333
0
0.145833
0.125
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b5d2438e72ede4149becee229525d2ab304971e9
939
py
Python
vietocr/train.py
lzmisscc/vietocr
df0d9a53e714d08d6b0b4ee52ab46fbc0b991bf3
[ "Apache-2.0" ]
null
null
null
vietocr/train.py
lzmisscc/vietocr
df0d9a53e714d08d6b0b4ee52ab46fbc0b991bf3
[ "Apache-2.0" ]
null
null
null
vietocr/train.py
lzmisscc/vietocr
df0d9a53e714d08d6b0b4ee52ab46fbc0b991bf3
[ "Apache-2.0" ]
null
null
null
import argparse import logging from vietocr.model.trainer import Trainer from vietocr.tool.config import Cfg import sys sys.path.insert(0, './') from char import character logging.basicConfig(level=logging.INFO, ) def main(): parser = argparse.ArgumentParser() parser.add_argument('config', help='see example at ...
28.454545
68
0.707135
115
939
5.591304
0.4
0.062208
0.052877
0.052877
0.065319
0
0
0
0
0
0
0.001282
0.169329
939
32
69
29.34375
0.823077
0.184239
0
0
0
0
0.102497
0
0
0
0
0
0
1
0.045455
false
0
0.272727
0
0.318182
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
b5d4e05a5e5fe08d9de941f7f2c1980a53f27d2a
598
py
Python
Plug-and-play module/SematicEmbbedBlock.py
riciche/SimpleCVReproduction
4075de39f9c61f1359668a413f6a5d98903fcf97
[ "Apache-2.0" ]
923
2020-01-11T06:36:53.000Z
2022-03-31T00:26:57.000Z
Plug-and-play module/SematicEmbbedBlock.py
riciche/SimpleCVReproduction
4075de39f9c61f1359668a413f6a5d98903fcf97
[ "Apache-2.0" ]
25
2020-02-27T08:35:46.000Z
2022-01-25T08:54:19.000Z
Plug-and-play module/SematicEmbbedBlock.py
riciche/SimpleCVReproduction
4075de39f9c61f1359668a413f6a5d98903fcf97
[ "Apache-2.0" ]
262
2020-01-02T02:19:40.000Z
2022-03-23T04:56:16.000Z
import torch.nn as nn """ https://zhuanlan.zhihu.com/p/76378871 arxiv: 1804.03821 ExFuse """ class SematicEmbbedBlock(nn.Module): def __init__(self, high_in_plane, low_in_plane, out_plane): super(SematicEmbbedBlock, self).__init__() self.conv3x3 = nn.Conv2d(high_in_plane, out_plane, 3, 1, 1) ...
29.9
67
0.688963
89
598
4.314607
0.438202
0.072917
0.078125
0.117188
0.09375
0
0
0
0
0
0
0.068323
0.192308
598
20
68
29.9
0.726708
0
0
0
0
0
0
0
0
0
0
0
0
1
0.181818
false
0
0.090909
0
0.454545
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
b5d85732ed11a9abee1adac3c37bfb5f5d7fe0c2
9,874
py
Python
nslsii/__init__.py
ke-zhang-rd/nslsii
d3f942cda8eac713ac625dbcf4285e108c04f154
[ "BSD-3-Clause" ]
null
null
null
nslsii/__init__.py
ke-zhang-rd/nslsii
d3f942cda8eac713ac625dbcf4285e108c04f154
[ "BSD-3-Clause" ]
null
null
null
nslsii/__init__.py
ke-zhang-rd/nslsii
d3f942cda8eac713ac625dbcf4285e108c04f154
[ "BSD-3-Clause" ]
null
null
null
from IPython import get_ipython from ._version import get_versions __version__ = get_versions()['version'] del get_versions def import_star(module, ns): def public(name): return not name.startswith('_') ns.update({name: getattr(module, name) for name in dir(module) if public(name)}) d...
34.404181
79
0.645331
1,272
9,874
4.908805
0.284591
0.016336
0.0213
0.023543
0.110026
0.10394
0.098975
0.098975
0.090006
0.049648
0
0.000557
0.272635
9,874
286
80
34.524476
0.868839
0.480758
0
0.102362
0
0
0.045007
0
0
0
0
0
0
1
0.047244
false
0
0.275591
0.007874
0.346457
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
b5d915f6cc267b773bbe24b2332fae333a3982c5
714
py
Python
fake.py
Wsky51/dfs-node-restapi
bab7605c609d4b53cd11686a576b74c1ae2871b7
[ "Apache-2.0" ]
null
null
null
fake.py
Wsky51/dfs-node-restapi
bab7605c609d4b53cd11686a576b74c1ae2871b7
[ "Apache-2.0" ]
null
null
null
fake.py
Wsky51/dfs-node-restapi
bab7605c609d4b53cd11686a576b74c1ae2871b7
[ "Apache-2.0" ]
null
null
null
"""create fake data to the db file""" from config import data_nodes, get_db from type import DataNodeStatus, DataNode from datetime import timedelta from config import get_second_datetime def create_fake_data_status(data_node: DataNode): now = get_second_datetime() db = get_db() for i in range(100): ...
24.62069
49
0.648459
96
714
4.5
0.427083
0.115741
0.162037
0.078704
0.12963
0.12963
0
0
0
0
0
0.026718
0.266106
714
28
50
25.5
0.79771
0.056022
0
0
0
0
0.011976
0
0
0
0
0
0
1
0.1
false
0
0.2
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
b5db0b0b72cf05ff56cc67988018bcfa4797221d
371
py
Python
tests/pull_keys.py
patleeman/geckoboard_push
52c05db22b3c630d326a9650551720f583f0168f
[ "MIT" ]
null
null
null
tests/pull_keys.py
patleeman/geckoboard_push
52c05db22b3c630d326a9650551720f583f0168f
[ "MIT" ]
null
null
null
tests/pull_keys.py
patleeman/geckoboard_push
52c05db22b3c630d326a9650551720f583f0168f
[ "MIT" ]
null
null
null
''' Module to pull keys from test geckoboard widgets. ''' import os import json def get_keys(): settings_folder = os.path.dirname(__file__) settings_file = os.path.join(settings_folder,'gecko_settings.json') with open(settings_file, 'r') as file: json_data = json.load(file) return json_dat...
23.1875
71
0.692722
52
371
4.538462
0.596154
0.059322
0
0
0
0
0
0
0
0
0
0
0.191375
371
16
72
23.1875
0.786667
0.132075
0
0
0
0
0.088889
0
0
0
0
0
0
1
0.1
false
0
0.2
0
0.4
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
b5db74f8420d00fdc906f19f599f41aad18c69af
2,596
py
Python
pajbot/web/common/menu.py
JoachimFlottorp/pajbot
4fb88c403dedb20d95be80e38da72be1ed064901
[ "MIT" ]
128
2015-12-28T01:02:30.000Z
2019-05-24T21:20:50.000Z
pajbot/web/common/menu.py
JoachimFlottorp/pajbot
4fb88c403dedb20d95be80e38da72be1ed064901
[ "MIT" ]
277
2015-05-03T18:48:57.000Z
2019-05-23T17:41:28.000Z
pajbot/web/common/menu.py
JoachimFlottorp/pajbot
4fb88c403dedb20d95be80e38da72be1ed064901
[ "MIT" ]
96
2015-08-07T18:49:50.000Z
2019-05-20T19:49:27.000Z
from __future__ import annotations from typing import Any, Dict, List, Union import logging from pajbot.web.utils import get_cached_enabled_modules log = logging.getLogger(__name__) class MenuItem: def __init__( self, href: Union[str, List[MenuItem]], menu_id: str, caption: str...
35.081081
108
0.571649
254
2,596
5.633858
0.330709
0.090846
0.044724
0.050314
0.16492
0.16492
0.11181
0.062893
0
0
0
0.001644
0.296995
2,596
73
109
35.561644
0.782466
0.038521
0
0.033898
0
0
0.265142
0.034497
0
0
0
0
0
1
0.050847
false
0
0.067797
0
0.152542
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
b5db8ac1529ed13c3cad056d88e711f36bbfbbe1
611
py
Python
Python/463.py
FlyAndNotDown/LeetCode
889819ff7f64819e966fc6f9dd80110cf2bf6d3c
[ "MIT" ]
4
2018-06-18T05:39:25.000Z
2022-01-04T07:35:52.000Z
Python/463.py
FlyAndNotDown/LeetCode
889819ff7f64819e966fc6f9dd80110cf2bf6d3c
[ "MIT" ]
20
2019-11-30T03:42:40.000Z
2020-05-17T03:25:43.000Z
Python/463.py
FlyAndNotDown/LeetCode
889819ff7f64819e966fc6f9dd80110cf2bf6d3c
[ "MIT" ]
2
2020-02-08T14:10:42.000Z
2021-09-23T13:51:36.000Z
""" @no 463 @name Island Perimeter """ class Solution: def islandPerimeter(self, grid): """ :type grid: List[List[int]] :rtype: int """ ans = 0 for i in range(len(grid)): for j in range(len(grid[i])): if grid[i][j] == 1: ...
30.55
80
0.392799
93
611
2.580645
0.290323
0.145833
0.116667
0.0875
0.2875
0.275
0.25
0.25
0.133333
0
0
0.072886
0.438625
611
19
81
32.157895
0.626822
0.114566
0
0
0
0
0
0
0
0
0
0
0
1
0.090909
false
0
0
0
0.272727
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b5dde242388a3c0b90abd4420143d4c4d72acbeb
914
py
Python
docker_retag/utils/auth_helper.py
aiopsclub/docker_retag
0019917b0cdd7860c7ff79afdb78101878f5c1b1
[ "MIT" ]
null
null
null
docker_retag/utils/auth_helper.py
aiopsclub/docker_retag
0019917b0cdd7860c7ff79afdb78101878f5c1b1
[ "MIT" ]
null
null
null
docker_retag/utils/auth_helper.py
aiopsclub/docker_retag
0019917b0cdd7860c7ff79afdb78101878f5c1b1
[ "MIT" ]
null
null
null
#!/usr/bin/env python import requests def kv2dict(kvinfo): kv = {} for item in kvinfo.split(","): item_list = item.split("=") kv[item_list[0]] = item_list[1].strip('"') return kv def get_service_realm(registry_url): registry_api_url = ( registry_url if registry_url.endswith("...
26.114286
80
0.682713
120
914
4.916667
0.391667
0.149153
0.094915
0.074576
0.379661
0.379661
0.379661
0.379661
0.379661
0.379661
0
0.016238
0.191466
914
34
81
26.882353
0.782138
0.021882
0
0.25
0
0
0.06495
0.025756
0
0
0
0
0
1
0.166667
false
0
0.041667
0.041667
0.416667
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
b5de2f232c7693a7a9e178d8efeaacaaaf172cb4
1,081
py
Python
app/__init__.py
SomeoneLixin/api-dock
3958a3a3286ae7f8802df9aba5ece2908ca4361e
[ "MIT" ]
4
2018-05-07T15:39:17.000Z
2019-07-03T21:28:10.000Z
app/__init__.py
SomeoneLixin/api-dock
3958a3a3286ae7f8802df9aba5ece2908ca4361e
[ "MIT" ]
4
2020-09-05T10:57:19.000Z
2021-05-09T16:01:22.000Z
app/__init__.py
SomeoneLixin/api-dock
3958a3a3286ae7f8802df9aba5ece2908ca4361e
[ "MIT" ]
1
2018-05-09T07:57:03.000Z
2018-05-09T07:57:03.000Z
from flask import Flask, g from flask_cors import CORS from flask_jwt_extended import JWTManager from config import config from app.models import db, ma from app.models.RevokedToken import RevokedToken def create_app(config_name): app = Flask(__name__) CORS(app, resources={r"/api/*": {"origins": "*"}}) ap...
29.216216
80
0.719704
148
1,081
5
0.398649
0.072973
0.040541
0.056757
0
0
0
0
0
0
0
0
0.174838
1,081
36
81
30.027778
0.829596
0
0
0
0
0
0.167438
0.07123
0
0
0
0
0
1
0.107143
false
0
0.25
0.035714
0.464286
0.071429
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b5df02ad3bc4934c674cd77a38e8acef0d4d0b9f
730
py
Python
Snippets/auto_scroll.py
ColinShark/Pyrogram-Snippets
50ede9ca9206bd6d66c6877217b4a80b4f845294
[ "WTFPL" ]
59
2021-01-07T16:19:48.000Z
2022-02-22T06:56:36.000Z
Snippets/auto_scroll.py
Mrvishal2k2/Pyrogram-Snippets
d4e66876f6aff1252dfb88423fedd66e18057446
[ "WTFPL" ]
4
2019-10-14T14:02:38.000Z
2020-11-06T11:47:03.000Z
Snippets/auto_scroll.py
ColinShark/Pyrogram-Snippets
50ede9ca9206bd6d66c6877217b4a80b4f845294
[ "WTFPL" ]
26
2021-03-02T14:31:51.000Z
2022-03-23T21:19:14.000Z
# Send .autoscroll in any chat to automatically read all sent messages until you call # .autoscroll again. This is useful if you have Telegram open on another screen. from pyrogram import Client, filters from pyrogram.types import Message app = Client("my_account") f = filters.chat([]) @app.on_message(f) def auto_...
25.172414
85
0.710959
102
730
5
0.509804
0.086275
0.101961
0.117647
0.133333
0.133333
0
0
0
0
0
0
0.175342
730
28
86
26.071429
0.847176
0.221918
0
0
0
0
0.111504
0
0
0
0
0
0
1
0.117647
false
0
0.117647
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
b5e13346685449cfbebc7876faf4f41723fbe5c9
2,977
py
Python
_demos/paint.py
imdaveho/intermezzo
3fe4824a747face996e301ca5190caec0cb0a6fd
[ "MIT" ]
8
2018-02-26T16:24:07.000Z
2021-06-30T07:40:52.000Z
_demos/paint.py
imdaveho/intermezzo
3fe4824a747face996e301ca5190caec0cb0a6fd
[ "MIT" ]
null
null
null
_demos/paint.py
imdaveho/intermezzo
3fe4824a747face996e301ca5190caec0cb0a6fd
[ "MIT" ]
null
null
null
from intermezzo import Intermezzo as mzo curCol = [0] curRune = [0] backbuf = [] bbw, bbh = 0, 0 runes = [' ', '░', '▒', '▓', '█'] colors = [ mzo.color("Black"), mzo.color("Red"), mzo.color("Green"), mzo.color("Yellow"), mzo.color("Blue"), mzo.color("Magenta"), mzo.color("Cyan"), mzo.c...
29.186275
88
0.518979
459
2,977
3.285403
0.220044
0.079576
0.079576
0.095491
0.312334
0.253979
0.167109
0.167109
0.125995
0.027851
0
0.024079
0.288546
2,977
101
89
29.475248
0.686025
0
0
0.113636
0
0
0.063151
0
0
0
0
0
0
1
0.068182
false
0
0.011364
0
0.102273
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
b5e16df4333ead8fee7050f33874cfa2a8d52eb0
1,896
py
Python
amt/media_reader_cli.py
lsxta/amt
7dcff9b1ce570abe103d0d8c50fd334f2c93af7d
[ "MIT" ]
5
2021-12-22T08:49:23.000Z
2022-02-22T12:38:40.000Z
amt/media_reader_cli.py
lsxta/amt
7dcff9b1ce570abe103d0d8c50fd334f2c93af7d
[ "MIT" ]
1
2022-01-30T00:51:05.000Z
2022-02-03T04:59:42.000Z
amt/media_reader_cli.py
lsxta/amt
7dcff9b1ce570abe103d0d8c50fd334f2c93af7d
[ "MIT" ]
1
2022-01-29T09:38:16.000Z
2022-01-29T09:38:16.000Z
import logging from .media_reader import MediaReader from .util.media_type import MediaType class MediaReaderCLI(MediaReader): auto_select = False def print_results(self, results): for i, media_data in enumerate(results): print("{:4}| {}\t{} {} ({})".format(i, media_data.global_id, media...
38.693878
188
0.642405
252
1,896
4.615079
0.353175
0.046432
0.027515
0.030954
0
0
0
0
0
0
0
0.002105
0.248418
1,896
48
189
39.5
0.814035
0
0
0
0
0
0.070675
0
0
0
0
0
0
1
0.157895
false
0
0.078947
0
0.368421
0.289474
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b5e250ffeccc9fb9e0d710d9d521ebecc7097405
1,272
py
Python
src/webapi/libs/deps/__init__.py
VisionTale/StreamHelper
29a5e5d5c68401f2c1d1b9cf54a7c68fb41d623a
[ "MIT" ]
null
null
null
src/webapi/libs/deps/__init__.py
VisionTale/StreamHelper
29a5e5d5c68401f2c1d1b9cf54a7c68fb41d623a
[ "MIT" ]
37
2020-12-16T06:30:22.000Z
2022-03-28T03:04:28.000Z
src/webapi/libs/deps/__init__.py
VisionTale/StreamHelper
29a5e5d5c68401f2c1d1b9cf54a7c68fb41d623a
[ "MIT" ]
null
null
null
""" Dependency management package. """ def debug_print(message: str, verbose: bool): """ Print if verbose is set to true. :param message: message to print :param verbose: whether to print :return: """ if verbose: print(message) def download_and_unzip_archive(url: str, zip_file_f...
30.285714
122
0.677673
171
1,272
4.912281
0.368421
0.058333
0.053571
0.05
0.061905
0
0
0
0
0
0
0
0.227201
1,272
41
123
31.02439
0.854527
0.416667
0
0
0
0
0.073353
0
0
0
0
0
0
1
0.117647
false
0
0.176471
0
0.294118
0.294118
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b5e50a13752cec91e8412a4602fb057eaceaa6b0
1,113
py
Python
demos/runner/validate.py
Tanbobobo/DL-starter
be4678171bd51ae9e4f61079fa6422e3378d7ce4
[ "Apache-2.0" ]
null
null
null
demos/runner/validate.py
Tanbobobo/DL-starter
be4678171bd51ae9e4f61079fa6422e3378d7ce4
[ "Apache-2.0" ]
null
null
null
demos/runner/validate.py
Tanbobobo/DL-starter
be4678171bd51ae9e4f61079fa6422e3378d7ce4
[ "Apache-2.0" ]
null
null
null
import torch import wandb def val( criterion=None, metric=None, loader=None, model=None, device=None ): r''' Args: criterion: a differentiable function to provide gratitude for backward metric: a score to save best model loader: a ...
27.146341
98
0.574124
135
1,113
4.607407
0.42963
0.115756
0.104502
0.054662
0.12701
0
0
0
0
0
0
0.001377
0.347709
1,113
40
99
27.825
0.855372
0.281222
0
0
0
0
0.018207
0
0
0
0
0
0
1
0.04
false
0
0.08
0
0.16
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
b5e76e091ee3230443db9902e3df57b4dbeb04c4
4,428
py
Python
plot_fig07e_varying.py
victorcroisfelt/cf-ra-spatial-separability
60611c85079dd13848c70e3192331ea2a9f55138
[ "MIT" ]
null
null
null
plot_fig07e_varying.py
victorcroisfelt/cf-ra-spatial-separability
60611c85079dd13848c70e3192331ea2a9f55138
[ "MIT" ]
null
null
null
plot_fig07e_varying.py
victorcroisfelt/cf-ra-spatial-separability
60611c85079dd13848c70e3192331ea2a9f55138
[ "MIT" ]
2
2022-01-08T12:18:43.000Z
2022-02-23T07:59:18.000Z
######################################## # plot_fig07d_anaa_practical.py # # Description. Script used to actually plot Fig. 07 (d) of the paper. # # Author. @victorcroisfelt # # Date. December 29, 2021 # # This code is part of the code package used to generate the numeric results # of the paper: # # Crois...
30.537931
124
0.630759
676
4,428
3.964497
0.284024
0.047015
0.049627
0.080597
0.428731
0.384701
0.384701
0.375746
0.375373
0.356716
0
0.050973
0.118338
4,428
144
125
30.75
0.635502
0.200316
0
0.20339
0
0
0.114079
0.027341
0
0
0
0
0
1
0.033898
false
0
0.067797
0.033898
0.135593
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b5e97f4578877e1fcf5bd928b8d18930e062681c
6,697
py
Python
Meters/IEC/Datasets/get_time.py
Runamook/PyCharmProjects
1b1a063345e052451f00e3fdea82e31bdd2a0cae
[ "MIT" ]
null
null
null
Meters/IEC/Datasets/get_time.py
Runamook/PyCharmProjects
1b1a063345e052451f00e3fdea82e31bdd2a0cae
[ "MIT" ]
null
null
null
Meters/IEC/Datasets/get_time.py
Runamook/PyCharmProjects
1b1a063345e052451f00e3fdea82e31bdd2a0cae
[ "MIT" ]
null
null
null
import datetime from time import sleep import re import pytz # try: # from .emhmeter import MeterBase, create_input_vars, logger # except ModuleNotFoundError: # from emhmeter import MeterBase, create_input_vars, logger # TODO: Not working class GetTime: def __init__(self, input_vars): self.inpu...
31.441315
102
0.551441
797
6,697
4.486826
0.269762
0.060403
0.040268
0.027964
0.198546
0.14038
0.095638
0.049217
0
0
0
0.047568
0.303121
6,697
212
103
31.589623
0.718663
0.124683
0
0.176871
0
0
0.168437
0.007197
0
0
0
0.004717
0
1
0.061224
false
0
0.027211
0
0.156463
0.006803
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b5ea1cb63e2208d12c4791c91ece989cd820bf44
3,889
py
Python
instagrapi/direct.py
chaulaode1257/instagrapi
cfb8cb53d3a63092c0146f3a0b7a086c760908c9
[ "MIT" ]
11
2021-01-09T22:52:30.000Z
2022-03-22T18:33:38.000Z
instagrapi/direct.py
chaulaode1257/instagrapi
cfb8cb53d3a63092c0146f3a0b7a086c760908c9
[ "MIT" ]
null
null
null
instagrapi/direct.py
chaulaode1257/instagrapi
cfb8cb53d3a63092c0146f3a0b7a086c760908c9
[ "MIT" ]
4
2020-12-26T06:14:53.000Z
2022-01-05T05:00:16.000Z
import re from typing import List from .utils import dumps from .types import DirectThread, DirectMessage from .exceptions import ClientNotFoundError, DirectThreadNotFound from .extractors import extract_direct_thread, extract_direct_message class Direct: def direct_threads(self, amount: int = 20) -> List[Direc...
35.678899
108
0.558498
411
3,889
5.121655
0.272506
0.030404
0.033254
0.038005
0.27886
0.266508
0.236105
0.178147
0.178147
0.098812
0
0.009916
0.325791
3,889
108
109
36.009259
0.792906
0.044484
0
0.255556
0
0
0.133875
0.036856
0
0
0
0
0.055556
1
0.055556
false
0
0.066667
0
0.188889
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
b5eee5ae8e8ac24bba961d0d4420546bd6f06e1d
26,090
py
Python
src/main/python/cybercaptain/visualization/bar.py
FHNW-CyberCaptain/CyberCaptain
07c989190e997353fbf57eb7a386947d6ab8ffd5
[ "MIT" ]
1
2018-10-01T10:59:55.000Z
2018-10-01T10:59:55.000Z
src/main/python/cybercaptain/visualization/bar.py
FHNW-CyberCaptain/CyberCaptain
07c989190e997353fbf57eb7a386947d6ab8ffd5
[ "MIT" ]
null
null
null
src/main/python/cybercaptain/visualization/bar.py
FHNW-CyberCaptain/CyberCaptain
07c989190e997353fbf57eb7a386947d6ab8ffd5
[ "MIT" ]
1
2021-11-01T00:09:00.000Z
2021-11-01T00:09:00.000Z
""" This module contains the visualization bar class. """ import glob import os import re import numpy as np import matplotlib.pyplot as plt import matplotlib.colors as colors import matplotlib.cm as cmx from mpl_toolkits.mplot3d import Axes3D from matplotlib.ticker import FuncFormatter from cybercaptain.utils.exceptio...
41.086614
175
0.617555
3,290
26,090
4.761094
0.128875
0.022983
0.013023
0.013343
0.476251
0.448481
0.417582
0.403601
0.363445
0.331333
0
0.00825
0.279877
26,090
635
176
41.086614
0.825474
0.305979
0
0.452096
0
0
0.109569
0.003581
0
0
0
0
0
1
0.035928
false
0
0.038922
0
0.128743
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