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
b0f8d8e1a99343fc9166ec575752cd7be6e45cee
827
py
Python
Pytorch/5-CNN/nn_Sequential.py
pengchenyu111/PaperCodeReplication
7b8681654e25b7d707f4b4d7ebcfb85ffc0fd52a
[ "Apache-2.0" ]
null
null
null
Pytorch/5-CNN/nn_Sequential.py
pengchenyu111/PaperCodeReplication
7b8681654e25b7d707f4b4d7ebcfb85ffc0fd52a
[ "Apache-2.0" ]
null
null
null
Pytorch/5-CNN/nn_Sequential.py
pengchenyu111/PaperCodeReplication
7b8681654e25b7d707f4b4d7ebcfb85ffc0fd52a
[ "Apache-2.0" ]
null
null
null
import torch from torch import nn from torch.nn import Conv2d, MaxPool2d, Flatten, Linear, Sequential from torch.utils.tensorboard import SummaryWriter class Tudui(nn.Module): def __init__(self): super(Tudui, self).__init__() self.model1 = Sequential( Conv2d(3, 32, 5, padding=2), ...
22.972222
67
0.584039
103
827
4.601942
0.398058
0.056962
0.056962
0.113924
0.162447
0.122363
0.122363
0.122363
0
0
0
0.079796
0.287787
827
35
68
23.628571
0.724958
0
0
0.103448
0
0
0.007255
0
0
0
0
0
0
1
0.068966
false
0
0.137931
0
0.275862
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
b0fb6f704b8d712fad268b480c2d25cc8bc409f5
1,232
py
Python
src/brewlog/utils/query.py
zgoda/brewlog
13a930b328f81d01a2be9aca07d3b14703b80faa
[ "BSD-3-Clause" ]
3
2019-03-11T04:30:06.000Z
2020-01-26T03:21:52.000Z
src/brewlog/utils/query.py
zgoda/brewlog
13a930b328f81d01a2be9aca07d3b14703b80faa
[ "BSD-3-Clause" ]
23
2019-02-06T20:37:37.000Z
2020-06-01T07:08:35.000Z
src/brewlog/utils/query.py
zgoda/brewlog
13a930b328f81d01a2be9aca07d3b14703b80faa
[ "BSD-3-Clause" ]
null
null
null
from typing import Optional from flask import url_for from flask_sqlalchemy import BaseQuery from ..ext import db from ..models import Brew, BrewerProfile def public_or_owner(query: BaseQuery, user: Optional[BrewerProfile]) -> BaseQuery: """Filter Brew query of all non-accessible objects. :param query: que...
29.333333
84
0.649351
161
1,232
4.795031
0.372671
0.041451
0.051813
0.072539
0.202073
0.202073
0.11658
0.11658
0.11658
0.11658
0
0.002151
0.24513
1,232
41
85
30.04878
0.827957
0.184253
0
0.076923
0
0
0.019588
0
0
0
0
0
0
1
0.076923
false
0
0.192308
0
0.346154
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
b0feb9c47583568b91cc55ff1a17eb9a915a0f41
1,626
py
Python
framework/repository/info.py
jarret/bitcoin_helpers
4b6155ea3b004ad58a717b36cd58138d058281b1
[ "MIT" ]
null
null
null
framework/repository/info.py
jarret/bitcoin_helpers
4b6155ea3b004ad58a717b36cd58138d058281b1
[ "MIT" ]
null
null
null
framework/repository/info.py
jarret/bitcoin_helpers
4b6155ea3b004ad58a717b36cd58138d058281b1
[ "MIT" ]
null
null
null
#!/usr/bin/env python3 # Copyright (c) 2017 The Bitcoin Core developers # Distributed under the MIT software license, see the accompanying # file COPYING or http://www.opensource.org/licenses/mit-license.php. import json import os import sys from framework.path.path import Path from framework.file.io import read_file...
36.954545
79
0.674662
229
1,626
4.615721
0.471616
0.05298
0.060549
0.049196
0.058657
0.058657
0.058657
0.058657
0
0
0
0.004032
0.237392
1,626
43
80
37.813953
0.848387
0.305658
0
0.153846
0
0
0.108794
0.062557
0
0
0
0
0.076923
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
b0ffaa7976be25e795d5abe04edf6fd2fd0631eb
1,540
py
Python
cookie_manager/security_decorator.py
ScholarPack/cookie-manager
342eaf19d4ebbe83319306e4a3afcc3988f61d3d
[ "MIT" ]
10
2020-02-26T14:13:05.000Z
2021-07-30T02:16:47.000Z
cookie_manager/security_decorator.py
ScholarPack/cookie-manager
342eaf19d4ebbe83319306e4a3afcc3988f61d3d
[ "MIT" ]
13
2020-02-26T10:42:09.000Z
2021-09-30T13:26:23.000Z
cookie_manager/security_decorator.py
ScholarPack/cookie-manager
342eaf19d4ebbe83319306e4a3afcc3988f61d3d
[ "MIT" ]
3
2020-03-29T00:49:23.000Z
2020-07-24T16:26:20.000Z
from functools import wraps from typing import List, Any from cookie_manager import CookieManager class CookieSecurityDecorator: _cookie_manager = None _request = None _cookie_name = None def init_app(self, request: Any, cookie_manager: CookieManager, cookie_name: str): """ Initialise...
34.222222
96
0.619481
182
1,540
5.049451
0.412088
0.127312
0.055495
0
0
0
0
0
0
0
0
0.000946
0.313636
1,540
44
97
35
0.868496
0.274026
0
0
0
0
0.00582
0
0
0
0
0
0
1
0.16
false
0
0.12
0
0.56
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
7c0015d18f7709ad1f58810e4e4fbcf0c3ae1358
6,394
py
Python
mutagen/aiff.py
lucienimmink/scanner.py
cecaa0a570ba8058321dea1c8efa9f77868effb3
[ "MIT" ]
2
2022-03-14T15:34:14.000Z
2022-03-23T17:05:42.000Z
mutagen/aiff.py
lucienimmink/scanner.py
cecaa0a570ba8058321dea1c8efa9f77868effb3
[ "MIT" ]
null
null
null
mutagen/aiff.py
lucienimmink/scanner.py
cecaa0a570ba8058321dea1c8efa9f77868effb3
[ "MIT" ]
2
2020-09-17T08:27:12.000Z
2021-08-23T11:13:52.000Z
# -*- coding: utf-8 -*- # Copyright (C) 2014 Evan Purkhiser # 2014 Ben Ockmore # 2019-2020 Philipp Wolfer # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either ...
25.99187
78
0.610416
775
6,394
4.900645
0.304516
0.034229
0.022117
0.007899
0.095313
0.065824
0.065824
0.065824
0.046867
0.02317
0
0.023434
0.285893
6,394
245
79
26.097959
0.808366
0.22568
0
0.148936
0
0
0.062591
0
0
0
0.004783
0
0.007092
1
0.120567
false
0.014184
0.042553
0.028369
0.333333
0.007092
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
7c037d89e3a9bf24f7302ca98b6d3dd08cac776e
11,062
py
Python
ML/meanvel.py
lewisfish/Triton-dolphin
bc7256485e1bd943e0b9b3017c214c82e26905f3
[ "MIT" ]
null
null
null
ML/meanvel.py
lewisfish/Triton-dolphin
bc7256485e1bd943e0b9b3017c214c82e26905f3
[ "MIT" ]
null
null
null
ML/meanvel.py
lewisfish/Triton-dolphin
bc7256485e1bd943e0b9b3017c214c82e26905f3
[ "MIT" ]
null
null
null
from concurrent import futures from itertools import repeat import pathlib from pathlib import Path import pickle import time from typing import List, Tuple, Union import cv2 as cv2 import hdbscan import numpy as np import pims from sklearn.cluster import KMeans from sklearn.preprocessing import StandardScaler from tq...
28.29156
176
0.626831
1,396
11,062
4.919771
0.235673
0.020384
0.024461
0.015725
0.365609
0.32484
0.289458
0.238497
0.231363
0.213891
0
0.023091
0.248328
11,062
390
177
28.364103
0.802886
0.334207
0
0.148387
0
0
0.02228
0.003058
0
0
0
0
0.012903
1
0.070968
false
0
0.129032
0
0.251613
0.006452
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
7c094dc9f6789987096d646f2920ee372eb6f1b8
3,409
py
Python
zero_paper/models.py
PLsergent/zero-paper
4663e0e9976447419b5da5cdd32e57dccfc32125
[ "MIT" ]
null
null
null
zero_paper/models.py
PLsergent/zero-paper
4663e0e9976447419b5da5cdd32e57dccfc32125
[ "MIT" ]
null
null
null
zero_paper/models.py
PLsergent/zero-paper
4663e0e9976447419b5da5cdd32e57dccfc32125
[ "MIT" ]
null
null
null
from django.db import models from django.contrib.auth.models import User from django.utils import timezone from django.dispatch import receiver import os import shutil class Folder(models.Model): name = models.CharField(max_length=128) parent_folder = models.ForeignKey("self", null=True, blank=True, on_delete...
29.903509
94
0.661484
423
3,409
5.184397
0.250591
0.032832
0.03648
0.043776
0.400821
0.376197
0.316461
0.273142
0.176927
0.176927
0
0.005693
0.227046
3,409
113
95
30.168142
0.826565
0.086536
0
0.265823
0
0
0.027294
0
0
0
0
0
0
1
0.101266
false
0
0.075949
0.037975
0.481013
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
9fd494efb313bbd651da7b57c11d4c1658a52fc3
1,610
py
Python
example/torch_classifier.py
KevinEloff/deep-chain-apps
0952845e93f0c0592f04275fe99b122ff831901f
[ "Apache-1.1" ]
null
null
null
example/torch_classifier.py
KevinEloff/deep-chain-apps
0952845e93f0c0592f04275fe99b122ff831901f
[ "Apache-1.1" ]
null
null
null
example/torch_classifier.py
KevinEloff/deep-chain-apps
0952845e93f0c0592f04275fe99b122ff831901f
[ "Apache-1.1" ]
null
null
null
""" Module that provide a classifier template to train a model on embeddings. With use the pathogen vs human dataset as an example. The embedding of 100k proteins come from the protBert model. The model is built with pytorch_ligthning, a wrapper on top of pytorch (similar to keras with tensorflow) Feel feel to build ...
36.590909
90
0.775776
248
1,610
4.854839
0.467742
0.032392
0.047342
0.048173
0.049834
0
0
0
0
0
0
0.013091
0.145963
1,610
43
91
37.44186
0.862545
0.51118
0
0
0
0
0.012987
0
0
0
0
0
0
1
0
false
0
0.235294
0
0.235294
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
9fd54ac2fec1187dcd8824c5cc8a001bad343192
5,589
py
Python
towavfile.py
streamsoftdev/audiomods
0e3d27fcd9af0a0f6a9de512112425e093f82dda
[ "Apache-2.0" ]
null
null
null
towavfile.py
streamsoftdev/audiomods
0e3d27fcd9af0a0f6a9de512112425e093f82dda
[ "Apache-2.0" ]
null
null
null
towavfile.py
streamsoftdev/audiomods
0e3d27fcd9af0a0f6a9de512112425e093f82dda
[ "Apache-2.0" ]
null
null
null
#Copyright 2022 Nathan Harwood # #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...
33.668675
113
0.580247
687
5,589
4.524017
0.294032
0.028958
0.048263
0.015444
0.136744
0.080759
0.067568
0.046976
0.025097
0
0
0.013813
0.313473
5,589
166
114
33.668675
0.796195
0.096976
0
0.167939
0
0
0.086594
0.004171
0
0
0.001192
0
0
1
0.083969
false
0
0.030534
0.007634
0.198473
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
9fd5c810c4ce10644e6de28ce2355f1bd5e61c6a
6,857
py
Python
test/blast/sample_data.py
UdoGi/dark-matter
3d49e89fa5e81f83144119f6216c5774176d203b
[ "MIT" ]
10
2016-03-09T09:43:14.000Z
2021-04-03T21:46:12.000Z
test/blast/sample_data.py
terrycojones/dark-matter
67d16f870db6b4239e17e542bc6e3f072dc29c75
[ "MIT" ]
332
2015-01-07T12:37:30.000Z
2022-01-20T15:48:11.000Z
test/blast/sample_data.py
terrycojones/dark-matter
67d16f870db6b4239e17e542bc6e3f072dc29c75
[ "MIT" ]
4
2016-03-08T14:56:39.000Z
2021-01-27T08:11:27.000Z
# Sample BLAST parameters. PARAMS = { 'application': 'BLASTN', 'blast_cutoff': [ None, None ], 'database': 'manx-shearwater', 'database_length': 17465129, 'database_letters': None, 'database_name': [], 'database_sequences': 70016, 'date': '', 'dropoff_1st_pass': [...
27.538153
70
0.392737
518
6,857
5.019305
0.279923
0.023077
0.065769
0.114231
0.577308
0.529231
0.463077
0.440769
0.440769
0.440769
0
0.105351
0.473968
6,857
248
71
27.649194
0.61547
0.009625
0
0.460581
0
0
0.340454
0.107395
0
0
0
0
0
1
0
false
0.004149
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
9fd91ec0b1f55cd338e90af15b11bcbae0dc4915
1,471
py
Python
neurgoo/misc/plot_utils.py
NISH1001/neurgoo
83b2f4928d362b2b3c2f80ff6afe4c4768d6cc74
[ "MIT" ]
2
2022-03-02T11:59:19.000Z
2022-03-18T17:59:28.000Z
neurgoo/misc/plot_utils.py
NISH1001/neurgoo
83b2f4928d362b2b3c2f80ff6afe4c4768d6cc74
[ "MIT" ]
1
2022-03-03T14:07:19.000Z
2022-03-03T14:07:19.000Z
neurgoo/misc/plot_utils.py
NISH1001/neurgoo
83b2f4928d362b2b3c2f80ff6afe4c4768d6cc74
[ "MIT" ]
null
null
null
#!/usr/bin/env python3 from typing import Dict, List try: import matplotlib.pyplot as plt MATPLOTLIB = True except: MATPLOTLIB = False from loguru import logger from .eval import EvalData def plot_losses(losses): if not MATPLOTLIB: logger.error("Maplotlib not installed. Halting the plot p...
23.349206
77
0.650578
212
1,471
4.410377
0.367925
0.051337
0.051337
0.083422
0.387166
0.346524
0.346524
0.233155
0.233155
0.158289
0
0.003493
0.221618
1,471
62
78
23.725806
0.8131
0.074099
0
0.153846
0
0
0.124907
0
0
0
0
0
0
1
0.076923
false
0.025641
0.102564
0
0.230769
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
9fdabb9fe3ddfe1efb0455a952de16d9ff31f05a
3,277
py
Python
LPSelectiveSearch.py
ksdsouza/license-plate-detector
900a032768d9c623b7ecb1ec7abd07651fda2b16
[ "MIT" ]
null
null
null
LPSelectiveSearch.py
ksdsouza/license-plate-detector
900a032768d9c623b7ecb1ec7abd07651fda2b16
[ "MIT" ]
null
null
null
LPSelectiveSearch.py
ksdsouza/license-plate-detector
900a032768d9c623b7ecb1ec7abd07651fda2b16
[ "MIT" ]
null
null
null
import itertools import os import sys import cv2 import numpy as np from SelectiveSearch import SelectiveSearch images_path = "Images" annotations = "Annotations" cv2.setUseOptimized(True) selective_search = SelectiveSearch() train_images = [] train_labels = [] SS_IMG_SIZE = (224, 224) # chunk = int(sys.argv[1]) ...
30.06422
97
0.523039
414
3,277
3.966184
0.275362
0.033496
0.016443
0.009744
0.17296
0.154689
0.154689
0.154689
0.154689
0.154689
0
0.051494
0.336283
3,277
108
98
30.342593
0.703448
0.578273
0
0
0
0
0.044428
0
0
0
0
0
0.051282
1
0.051282
false
0
0.153846
0
0.282051
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
9fde09067036bce742f20360db8b7e67c431adac
3,636
py
Python
core/tests/test_office.py
cjmash/art-backend
fb1dfd69cca9cda1d8714bd7066c3920d1a97312
[ "MIT" ]
null
null
null
core/tests/test_office.py
cjmash/art-backend
fb1dfd69cca9cda1d8714bd7066c3920d1a97312
[ "MIT" ]
null
null
null
core/tests/test_office.py
cjmash/art-backend
fb1dfd69cca9cda1d8714bd7066c3920d1a97312
[ "MIT" ]
null
null
null
from django.contrib.auth import get_user_model from django.db import transaction from rest_framework.exceptions import ValidationError from ..models import OfficeBlock, OfficeFloor, OfficeFloorSection from core.tests import CoreBaseTestCase User = get_user_model() class OfficeBlockModelTest(CoreBaseTestCase): ...
37.484536
73
0.668592
417
3,636
5.549161
0.189448
0.123596
0.073034
0.095073
0.626621
0.593345
0.473207
0.372947
0.280467
0.19274
0
0.006877
0.240099
3,636
96
74
37.875
0.830619
0.058581
0
0.305556
0
0
0.032134
0
0
0
0
0
0.208333
1
0.125
false
0.013889
0.069444
0
0.208333
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
9fdf686d8f768389a99935e8b0188491d6cb098b
2,481
py
Python
tests/functional/collection/test_collection_show.py
sirosen/temp-cli-test
416fd3fea17b4c7c2cf35d6ccde63cb5719a1af6
[ "Apache-2.0" ]
47
2016-04-21T19:51:17.000Z
2022-02-25T14:13:30.000Z
tests/functional/collection/test_collection_show.py
sirosen/temp-cli-test
416fd3fea17b4c7c2cf35d6ccde63cb5719a1af6
[ "Apache-2.0" ]
421
2016-04-20T18:45:24.000Z
2022-03-14T14:50:41.000Z
tests/functional/collection/test_collection_show.py
sirosen/temp-cli-test
416fd3fea17b4c7c2cf35d6ccde63cb5719a1af6
[ "Apache-2.0" ]
20
2016-09-10T20:25:27.000Z
2021-10-06T16:02:47.000Z
import pytest def test_collection_show(run_line, load_api_fixtures, add_gcs_login): data = load_api_fixtures("collection_operations.yaml") cid = data["metadata"]["mapped_collection_id"] username = data["metadata"]["username"] epid = data["metadata"]["endpoint_id"] add_gcs_login(epid) _result,...
36.485294
132
0.639258
315
2,481
4.834921
0.279365
0.09455
0.102429
0.041366
0.573211
0.558766
0.540381
0.502955
0.502955
0.502955
0
0.003906
0.174526
2,481
67
133
37.029851
0.739746
0.004031
0
0.436364
0
0.018182
0.405022
0.065614
0
0
0
0
0.054545
1
0.054545
false
0
0.018182
0
0.072727
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
9fdfc62d17a4273e27c2f11b9b40558a4ec8fe41
2,044
py
Python
job.py
mapledyne/ihunttools
28d4f7dbf61b6e3f34c9e1cdfdac2e9afec177d8
[ "MIT" ]
null
null
null
job.py
mapledyne/ihunttools
28d4f7dbf61b6e3f34c9e1cdfdac2e9afec177d8
[ "MIT" ]
2
2021-09-08T02:16:00.000Z
2022-01-13T02:57:26.000Z
job.py
mapledyne/ihunttools
28d4f7dbf61b6e3f34c9e1cdfdac2e9afec177d8
[ "MIT" ]
null
null
null
import argparse import random import ihuntapp if __name__ == "__main__": parser = argparse.ArgumentParser(description='Build an #iHunt job app page.') parser.add_argument('--name', "-n", default="Unnamed job", help='Name of the job') parser.add_argument('--description', "-d", ...
44.434783
99
0.626223
242
2,044
5.198347
0.309917
0.093005
0.175676
0.063593
0.259936
0.201908
0.162162
0.063593
0
0
0
0.010652
0.219178
2,044
45
100
45.422222
0.777569
0
0
0
0
0
0.208415
0
0
0
0
0
0
1
0
false
0
0.078947
0
0.078947
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
9fe1fc1239cc234d72923d2663fd719390f1395d
454
py
Python
epochbot/utils.py
jaloo555/solana-easy-py
8e28b8de52fbe4ee0b8e94a0f9c728114fc91728
[ "MIT" ]
4
2021-09-10T19:20:42.000Z
2022-02-12T00:27:40.000Z
epochbot/utils.py
jaloo555/solana-easy-py
8e28b8de52fbe4ee0b8e94a0f9c728114fc91728
[ "MIT" ]
null
null
null
epochbot/utils.py
jaloo555/solana-easy-py
8e28b8de52fbe4ee0b8e94a0f9c728114fc91728
[ "MIT" ]
1
2021-11-08T15:32:46.000Z
2021-11-08T15:32:46.000Z
def enum(*sequential, **named): enums = dict(zip(sequential, range(len(sequential))), **named) return type('Enum', (), enums) ENDPOINT_URLS_ENUM = enum( MAIN='https://api.mainnet-beta.solana.com', DEV='https://api.devnet.solana.com', TEST='https://api.testnet.solana.com', ) ENDPOINT_URLS = { "...
30.266667
66
0.645374
60
454
4.833333
0.4
0.165517
0.082759
0.131034
0.593103
0.593103
0.593103
0.593103
0.593103
0.593103
0
0
0.129956
454
15
67
30.266667
0.734177
0
0
0
0
0
0.446154
0
0
0
0
0
0
1
0.076923
false
0
0
0
0.153846
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
9fe207c6dcc8198ff87d2e16175a87d21e6112ea
812
py
Python
FrontEnd/mapa_pontos.py
JessicaIsri/WebBot
e9ed911c0306f5e362b577e244e50073336480ea
[ "bzip2-1.0.6" ]
null
null
null
FrontEnd/mapa_pontos.py
JessicaIsri/WebBot
e9ed911c0306f5e362b577e244e50073336480ea
[ "bzip2-1.0.6" ]
1
2021-11-13T10:12:49.000Z
2021-11-16T12:17:01.000Z
FrontEnd/mapa_pontos.py
JessicaIsri/WebBot
e9ed911c0306f5e362b577e244e50073336480ea
[ "bzip2-1.0.6" ]
null
null
null
import pymongo import folium from pymongo import MongoClient db = MongoClient('mongodb+srv://admin:admin@cluster0-vuh1j.azure.mongodb.net/test?retryWrites=true&w=majority') db = db.get_database('BD_EMPRESAS') collection = db.empresas cnpj = [] latitude = [] longitude = [] qtd_range = [] endereco = [] cnpj = db....
24.606061
111
0.730296
109
812
5.33945
0.477064
0.042955
0.103093
0.158076
0.213058
0
0
0
0
0
0
0.028571
0.094828
812
33
112
24.606061
0.763265
0
0
0
0
0.05
0.236162
0.111931
0
0
0
0
0
1
0
false
0
0.15
0
0.15
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
9fe3746b0ca2a17a4da60916603ceccce096325e
6,994
py
Python
hypernets/tests/searchers/evolution_test.py
Enpen/Hypernets
5fbf01412ffaef310855d98f52f8cc169e96246b
[ "Apache-2.0" ]
1,080
2020-06-22T07:44:22.000Z
2022-03-22T07:46:48.000Z
hypernets/tests/searchers/evolution_test.py
Enpen/Hypernets
5fbf01412ffaef310855d98f52f8cc169e96246b
[ "Apache-2.0" ]
24
2020-08-06T02:06:37.000Z
2022-03-31T03:34:35.000Z
hypernets/tests/searchers/evolution_test.py
Enpen/Hypernets
5fbf01412ffaef310855d98f52f8cc169e96246b
[ "Apache-2.0" ]
170
2020-08-14T08:39:18.000Z
2022-03-23T12:58:17.000Z
# -*- coding:utf-8 -*- """ """ import numpy as np from hypernets.core.ops import Identity from hypernets.core.search_space import HyperSpace, Int, Real, Choice, Bool from hypernets.core.searcher import OptimizeDirection from hypernets.searchers.evolution_searcher import Population, EvolutionSearcher def get_space()...
39.965714
120
0.570489
903
6,994
4.328904
0.20598
0.122794
0.00921
0.085955
0.571757
0.481197
0.481197
0.417498
0.417498
0.406242
0
0.090497
0.274807
6,994
174
121
40.195402
0.680205
0.20875
0
0.522523
0
0
0.007468
0
0
0
0
0
0.117117
1
0.054054
false
0
0.054054
0
0.135135
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
9fe62e0a759bb38c6001a97c2d2f6695ebbb34cb
22,748
py
Python
tests/filesystem_tests.py
d-kiss/fakeos
88dff667830efe10841df8b3a5f33a581bd94b69
[ "MIT" ]
1
2017-10-09T10:59:43.000Z
2017-10-09T10:59:43.000Z
tests/filesystem_tests.py
d-kiss/fakeos
88dff667830efe10841df8b3a5f33a581bd94b69
[ "MIT" ]
5
2017-10-06T17:33:37.000Z
2017-10-13T16:31:34.000Z
tests/filesystem_tests.py
rinslow/fakeos
88dff667830efe10841df8b3a5f33a581bd94b69
[ "MIT" ]
null
null
null
import operator import os as _os from pathlib import Path from string import ascii_letters from itertools import chain, permutations from functools import reduce from fakeos import FakeOS from hypothesis import given, assume, example from hypothesis.strategies import text, sets, integers, lists, just from filesyste...
33.403818
86
0.583656
2,957
22,748
4.34021
0.077782
0.057348
0.058906
0.062334
0.685912
0.637447
0.586723
0.563581
0.521583
0.514649
0
0.012003
0.278486
22,748
680
87
33.452941
0.769938
0.001363
0
0.586538
0
0
0.017082
0
0
0
0
0
0.278846
1
0.098077
false
0
0.025
0
0.142308
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
9fe6a6466ba62d142e4c8d8e39066315eacdcdb4
6,129
py
Python
ceed/utils.py
matham/ceed
5d32a99a33325b36dbe74d8b0a22e63abc92aab7
[ "MIT" ]
1
2020-03-02T22:26:44.000Z
2020-03-02T22:26:44.000Z
ceed/utils.py
matham/ceed
5d32a99a33325b36dbe74d8b0a22e63abc92aab7
[ "MIT" ]
null
null
null
ceed/utils.py
matham/ceed
5d32a99a33325b36dbe74d8b0a22e63abc92aab7
[ "MIT" ]
2
2020-01-13T19:42:16.000Z
2020-01-27T14:58:09.000Z
"""Utilities =================== Various tools used in :mod:`ceed`. """ import re import pathlib from collections import deque from typing import List, Tuple, Any, Union __all__ = ( 'fix_name', 'update_key_if_other_key', 'collapse_list_to_counts', 'get_plugin_modules', 'CeedWithID', ) _name_pa...
32.775401
81
0.565019
818
6,129
4.09291
0.273839
0.033453
0.013142
0.019116
0.163082
0.11589
0.044803
0.03405
0.0227
0
0
0.007374
0.314081
6,129
186
82
32.951613
0.78901
0.414586
0
0.146341
0
0
0.060479
0.021992
0
0
0
0
0
1
0.060976
false
0
0.04878
0
0.195122
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
9fe92dc5882b9ab766bfa49539001ca33aa51f84
510
py
Python
chapter1/quest1_4.py
mag6367/Coding_the_Coding_Interview_Python_Solutions
1d97d18d3d9732c25626e20cb3561ce4241b16e8
[ "MIT" ]
1
2017-04-28T13:52:13.000Z
2017-04-28T13:52:13.000Z
chapter1/quest1_4.py
mag6367/Cracking_the_Coding_Interview_Python_Solutions
1d97d18d3d9732c25626e20cb3561ce4241b16e8
[ "MIT" ]
null
null
null
chapter1/quest1_4.py
mag6367/Cracking_the_Coding_Interview_Python_Solutions
1d97d18d3d9732c25626e20cb3561ce4241b16e8
[ "MIT" ]
null
null
null
# question 1.4 from cracking the code interview 4th ed. ''' Write a method to decide if two strings are anagrams or not. ''' # if we sort the two string, they should be the same def areAnagram (str1, str2): # check is strings are valid if not isinstance(str1, str) or not isinstance(str2, str): return False # fir...
24.285714
60
0.727451
83
510
4.46988
0.60241
0.053908
0
0
0
0
0
0
0
0
0
0.03202
0.203922
510
20
61
25.5
0.881773
0.594118
0
0
0
0
0
0
0
0
0
0
0
1
0.166667
false
0
0
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
9febad62a52cd187ba14dbd7516dbb4c9c77a4fc
2,516
py
Python
firmware/measure_magnitude.py
mfkiwl/OpenXcvr
9bea6efd03cd246f16982f0fadafed684ac5ce1c
[ "MIT" ]
14
2020-02-16T15:36:31.000Z
2022-03-27T02:24:40.000Z
firmware/measure_magnitude.py
mfkiwl/OpenXcvr
9bea6efd03cd246f16982f0fadafed684ac5ce1c
[ "MIT" ]
1
2020-11-23T16:16:33.000Z
2020-11-23T16:16:33.000Z
firmware/measure_magnitude.py
mfkiwl/OpenXcvr
9bea6efd03cd246f16982f0fadafed684ac5ce1c
[ "MIT" ]
4
2021-03-29T16:55:03.000Z
2022-01-23T16:43:59.000Z
from baremetal import * from baremetal.signed import number_of_bits_needed from settings import Settings from math import log, pi from matplotlib import pyplot as plt import numpy as np import sys from math import log, ceil from numpy import log10 #settings for 100KS/s # hang attack decay # fast ...
30.313253
131
0.65779
374
2,516
4.237968
0.347594
0.066246
0.022713
0.024606
0.023975
0
0
0
0
0
0
0.067358
0.232909
2,516
82
132
30.682927
0.753886
0.149046
0
0
0
0
0.012676
0
0
0
0
0
0
1
0.018182
false
0
0.163636
0
0.2
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
9fec2b87298b7ce1d8fa49d924c18e361c3fbd3b
737
py
Python
chpt6/Palindrome.py
GDG-Buea/learn-python
9dfe8caa4b57489cf4249bf7e64856062a0b93c2
[ "Apache-2.0" ]
null
null
null
chpt6/Palindrome.py
GDG-Buea/learn-python
9dfe8caa4b57489cf4249bf7e64856062a0b93c2
[ "Apache-2.0" ]
2
2018-05-21T09:39:00.000Z
2018-05-27T15:59:15.000Z
chpt6/Palindrome.py
GDG-Buea/learn-python
9dfe8caa4b57489cf4249bf7e64856062a0b93c2
[ "Apache-2.0" ]
2
2018-05-19T14:59:56.000Z
2018-05-19T15:25:48.000Z
# This program prompts a user to enter an integer and reports whether the integer is a palindrome or not # A number is a palindrome if its reversal is the same as itself. def reverse(number): position1 = number % 10 remainder1 = number // 10 position2 = remainder1 % 10 remainder2 = remainder1 // ...
23.03125
104
0.679783
103
737
4.825243
0.446602
0.110664
0.078471
0
0
0
0
0
0
0
0
0.033929
0.240163
737
32
105
23.03125
0.853571
0.226594
0
0
0
0
0.176367
0
0
0
0
0
0
1
0.176471
false
0
0
0
0.352941
0.058824
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
9ff112f147fc3eea03cddc2ce893a7da503429c2
1,045
py
Python
emilia/modules/sql/admin_sql.py
masterisira/ELIZA_OF-master
02a7dbf48e4a3d4ee0981e6a074529ab1497aafe
[ "Unlicense" ]
null
null
null
emilia/modules/sql/admin_sql.py
masterisira/ELIZA_OF-master
02a7dbf48e4a3d4ee0981e6a074529ab1497aafe
[ "Unlicense" ]
null
null
null
emilia/modules/sql/admin_sql.py
masterisira/ELIZA_OF-master
02a7dbf48e4a3d4ee0981e6a074529ab1497aafe
[ "Unlicense" ]
null
null
null
import threading from typing import Union from sqlalchemy import Column, Integer, String, Boolean from emilia.modules.sql import SESSION, BASE class PermanentPin(BASE): __tablename__ = "permanent_pin" chat_id = Column(String(14), primary_key=True) message_id = Column(Integer) def __init__(self, cha...
24.302326
64
0.677512
130
1,045
5.161538
0.423077
0.089419
0.044709
0.080477
0.113264
0.113264
0.113264
0.113264
0
0
0
0.003708
0.225837
1,045
42
65
24.880952
0.825711
0
0
0
0
0
0.035407
0
0
0
0
0
0
1
0.133333
false
0
0.133333
0.033333
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
9ff624252765d2c5657956ad0fdec3d525d53544
22,024
py
Python
lcfit_utils.py
idekany/lcfit
4a0080fca981afe2b8974db8f5d3484c663b6c13
[ "MIT" ]
null
null
null
lcfit_utils.py
idekany/lcfit
4a0080fca981afe2b8974db8f5d3484c663b6c13
[ "MIT" ]
null
null
null
lcfit_utils.py
idekany/lcfit
4a0080fca981afe2b8974db8f5d3484c663b6c13
[ "MIT" ]
null
null
null
# -*- coding: utf-8 -*- import sys import os import numpy as np import fourier as ff import matplotlib import warnings from matplotlib import pyplot as plt from os.path import isfile matplotlib.use('Agg') def warn(*args, **kwargs): print('WARNING: ', *args, file=sys.stderr, **kwargs) def fit_validate_model(mod...
42.517375
133
0.582047
2,941
22,024
4.220673
0.17171
0.008056
0.009184
0.009667
0.365423
0.32184
0.295416
0.269717
0.240071
0.202691
0
0.027788
0.274519
22,024
517
134
42.599613
0.749093
0.120687
0
0.223141
0
0.008264
0.117861
0
0
0
0
0
0.019284
1
0.038567
false
0
0.022039
0.002755
0.085399
0.013774
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
9ff65d9e76edd0a7d15ce5ca32d68a653fd8c1bc
2,939
py
Python
facetool/annotator.py
yliess86/FaceTool
f93c511e9868b4555225750efbac2228a00fea00
[ "MIT" ]
4
2020-05-03T01:29:23.000Z
2020-07-15T08:13:05.000Z
facetool/annotator.py
yliess86/FaceTool
f93c511e9868b4555225750efbac2228a00fea00
[ "MIT" ]
3
2020-04-30T01:18:02.000Z
2020-05-01T14:52:11.000Z
facetool/annotator.py
yliess86/FaceCrop
f93c511e9868b4555225750efbac2228a00fea00
[ "MIT" ]
1
2020-05-16T21:27:24.000Z
2020-05-16T21:27:24.000Z
# -*- coding: utf-8 -*- """facetool.annotator The files provides a Face Annotator in charge of combining the result of the Face Detector and Face Landmark in a single pandas DataFrame. This Face Annotator is the API built to be used by the end user. """ from facetool.detector import FaceDetector from facetool.landmar...
36.7375
78
0.600204
411
2,939
4.201946
0.3382
0.037638
0.015634
0.020845
0.044007
0.044007
0.018529
0.018529
0
0
0
0.01699
0.299081
2,939
80
79
36.7375
0.821359
0.4869
0
0
0
0
0.052632
0
0
0
0
0
0
1
0.066667
false
0
0.2
0
0.333333
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
9ff7ddf37d375ebc0e9b1af36cfd6f7f85ab8e18
1,338
py
Python
pygrn/problems/air_quality.py
nico1as/pyGRN
115d9d42dfbd374fc64393cabefb2a8e245aa6b7
[ "Apache-2.0" ]
7
2018-07-18T16:08:51.000Z
2020-12-09T07:18:35.000Z
pygrn/problems/air_quality.py
nico1as/pyGRN
115d9d42dfbd374fc64393cabefb2a8e245aa6b7
[ "Apache-2.0" ]
3
2018-04-13T11:44:59.000Z
2018-04-19T13:58:06.000Z
pygrn/problems/air_quality.py
nico1as/pyGRN
115d9d42dfbd374fc64393cabefb2a8e245aa6b7
[ "Apache-2.0" ]
6
2018-07-22T01:54:14.000Z
2021-08-04T16:01:38.000Z
from __future__ import print_function import numpy as np import os from datetime import datetime from pygrn.problems import TimeRegression class AirQuality(TimeRegression): def __init__(self, namestr=datetime.now().isoformat(), learn=True, epochs=1, root_dir='./', lamarckian=False): data...
31.857143
77
0.595665
168
1,338
4.559524
0.446429
0.052219
0.062663
0.036554
0.044386
0
0
0
0
0
0
0.01877
0.283259
1,338
41
78
32.634146
0.779979
0
0
0
0
0
0.035127
0.023169
0
0
0
0
0
1
0.030303
false
0
0.151515
0
0.212121
0.030303
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
9ff867269ebc563da12e37b56fdbdcb6807b0b80
3,572
py
Python
vocabulary.py
retrieva/python_stm
862e63e6f03b326cb036b1136dead280c42b9da8
[ "MIT" ]
11
2020-02-07T05:26:08.000Z
2021-11-27T09:51:24.000Z
vocabulary.py
retrieva/python_stm
862e63e6f03b326cb036b1136dead280c42b9da8
[ "MIT" ]
null
null
null
vocabulary.py
retrieva/python_stm
862e63e6f03b326cb036b1136dead280c42b9da8
[ "MIT" ]
1
2020-02-10T02:44:37.000Z
2020-02-10T02:44:37.000Z
# This code is available under the MIT License. # (c)2010-2011 Nakatani Shuyo / Cybozu Labs Inc. # (c)2018-2019 Hiroki Iida / Retrieva Inc. import nltk import re import MeCab stopwords_list = nltk.corpus.stopwords.words('english') recover_list = {"wa":"was", "ha":"has"} wl = nltk.WordNetLemmatizer() def load_corpu...
26.072993
79
0.56075
471
3,572
4.11465
0.261147
0.065015
0.045408
0.02322
0.033024
0
0
0
0
0
0
0.011662
0.327828
3,572
136
80
26.264706
0.795502
0.069429
0
0.09901
0
0
0.017661
0
0
0
0
0
0
1
0.138614
false
0
0.039604
0.039604
0.326733
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
9ffac072e4010a04d6f1b435f72c2103f99a9533
7,664
py
Python
kubb_match/views/rest.py
BartSaelen/kubb_match
848663bb3db5da73b726a956aa887c3eec30db8b
[ "Apache-2.0" ]
2
2015-05-03T13:42:27.000Z
2015-08-07T07:42:29.000Z
kubb_match/views/rest.py
BartSaelen/kubb_match
848663bb3db5da73b726a956aa887c3eec30db8b
[ "Apache-2.0" ]
2
2016-09-15T12:38:22.000Z
2016-09-15T12:41:18.000Z
kubb_match/views/rest.py
BartSaelen/kubb_match
848663bb3db5da73b726a956aa887c3eec30db8b
[ "Apache-2.0" ]
null
null
null
# -*- coding: utf-8 -*- from pyramid.httpexceptions import HTTPBadRequest, HTTPNotFound from pyramid.view import view_defaults, view_config from kubb_match.data.mappers import map_team, map_game from kubb_match.data.models import Team from kubb_match.service.tournament_service import TournamentService class RestView(...
34.678733
87
0.579201
883
7,664
4.826727
0.129105
0.077428
0.06687
0.063351
0.70671
0.580009
0.507274
0.450962
0.359456
0.249648
0
0.002836
0.30976
7,664
220
88
34.836364
0.802836
0.00274
0
0.550505
0
0
0.079702
0
0
0
0
0
0
1
0.085859
false
0
0.025253
0.015152
0.247475
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
9ffb3711d6a34d1adba73090bd3c202a99a4f456
2,651
py
Python
CTCWordBeamSearch-master/tests/test_word_beam_search.py
brucegrapes/htr
9f8f07173ccc740dd8a4dfc7e8038abe36664756
[ "MIT" ]
488
2018-03-01T11:18:26.000Z
2022-03-10T09:29:32.000Z
CTCWordBeamSearch-master/tests/test_word_beam_search.py
brucegrapes/htr
9f8f07173ccc740dd8a4dfc7e8038abe36664756
[ "MIT" ]
60
2018-03-10T18:37:51.000Z
2022-03-30T19:37:18.000Z
CTCWordBeamSearch-master/tests/test_word_beam_search.py
brucegrapes/htr
9f8f07173ccc740dd8a4dfc7e8038abe36664756
[ "MIT" ]
152
2018-03-01T11:18:25.000Z
2022-03-08T23:37:46.000Z
import codecs import numpy as np from word_beam_search import WordBeamSearch def apply_word_beam_search(mat, corpus, chars, word_chars): """Decode using word beam search. Result is tuple, first entry is label string, second entry is char string.""" T, B, C = mat.shape # decode using the "Words" mode of ...
35.346667
115
0.614485
410
2,651
3.87561
0.336585
0.01888
0.01888
0.020138
0.201385
0.172435
0.172435
0.172435
0.172435
0.139711
0
0.027094
0.234251
2,651
74
116
35.824324
0.755665
0.278386
0
0.163265
0
0
0.126461
0
0
0
0
0
0.061224
1
0.081633
false
0
0.061224
0
0.183673
0.163265
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
9ffdc1e59bb26b37e4cdbdb001abd755fccd616d
859
py
Python
src/api/migrations/versions/2021-09-25_add_session_type_and_instructor.py
YACS-RCOS/yacs.n
a04f8e79279826914b942e3a8c709c50f08ff149
[ "MIT" ]
20
2020-02-29T19:03:31.000Z
2022-02-18T21:13:12.000Z
src/api/migrations/versions/2021-09-25_add_session_type_and_instructor.py
YACS-RCOS/yacs.n
a04f8e79279826914b942e3a8c709c50f08ff149
[ "MIT" ]
465
2020-02-29T19:08:18.000Z
2022-03-18T22:21:49.000Z
src/api/migrations/versions/2021-09-25_add_session_type_and_instructor.py
YACS-RCOS/yacs.n
a04f8e79279826914b942e3a8c709c50f08ff149
[ "MIT" ]
19
2020-02-29T01:22:23.000Z
2022-02-14T01:47:09.000Z
"""add session type and instructor Revision ID: 54df4fb8dfe9 Revises: a3be4710680d Create Date: 2021-09-25 03:08:18.501929 """ from alembic import op import sqlalchemy as sa # revision identifiers, used by Alembic. revision = '54df4fb8dfe9' down_revision = 'a3be4710680d' branch_labels = None depends_on = None def...
27.709677
101
0.71362
109
859
5.504587
0.477064
0.08
0.126667
0.076667
0.43
0.35
0.25
0.146667
0
0
0
0.071429
0.152503
859
30
102
28.633333
0.752747
0.364377
0
0
0
0
0.243615
0
0
0
0
0
0
1
0.166667
false
0
0.166667
0
0.333333
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
9ffddf9f2ec970e9ca9b3a8192c022d87d76144d
1,656
py
Python
plot_data.py
qzane/kmeans-cuda
f2a0e8dd6859cf735c95e1365342f4623f0a71ff
[ "MIT" ]
null
null
null
plot_data.py
qzane/kmeans-cuda
f2a0e8dd6859cf735c95e1365342f4623f0a71ff
[ "MIT" ]
null
null
null
plot_data.py
qzane/kmeans-cuda
f2a0e8dd6859cf735c95e1365342f4623f0a71ff
[ "MIT" ]
null
null
null
#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Tue Nov 27 22:31:17 2018 @author: qzane """ import numpy as np import matplotlib.pyplot as plt from argparse import ArgumentParser def read_points(fname): points = [] with open(fname) as f: while(1): tmp = f.readline() ...
25.090909
83
0.532609
204
1,656
4.220588
0.426471
0.075494
0.059233
0.034843
0.181185
0.181185
0.181185
0.102207
0.102207
0.102207
0
0.028521
0.322464
1,656
66
84
25.090909
0.738859
0.057367
0
0.232558
0
0
0.042498
0
0
0
0
0
0.023256
1
0.069767
false
0
0.069767
0
0.186047
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
9fff12642cb00ff3e2ce7ae890c3d2b10cbbe1d1
8,936
py
Python
src/WignerFunctionMeasurement.py
ngchihuan/WignerFunc_Measurement
9c258180da4c1a1ff87b384f0aaf85dc0f92d667
[ "MIT" ]
null
null
null
src/WignerFunctionMeasurement.py
ngchihuan/WignerFunc_Measurement
9c258180da4c1a1ff87b384f0aaf85dc0f92d667
[ "MIT" ]
null
null
null
src/WignerFunctionMeasurement.py
ngchihuan/WignerFunc_Measurement
9c258180da4c1a1ff87b384f0aaf85dc0f92d667
[ "MIT" ]
null
null
null
import os from os.path import join, isfile from shutil import Error from sys import exec_prefix import numpy as np import fit import simple_read_data from tabulate import tabulate import logging np.seterr(all='raise') class DataFormatError(Exception): pass class WrongPathFormat(Exception): pass def check_dat...
31.575972
173
0.57218
1,141
8,936
4.379492
0.208589
0.040024
0.010006
0.014008
0.194717
0.160897
0.160897
0.14969
0.13408
0.129278
0
0.006376
0.315466
8,936
283
174
31.575972
0.810528
0.10385
0
0.280612
0
0
0.096856
0
0
0
0
0
0
1
0.107143
false
0.020408
0.045918
0.005102
0.22449
0.045918
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b000e8e09627008c8e1b4d9bdfd0f7e449d23a7e
1,729
py
Python
falmer/content/models/scheme.py
sussexstudent/services-api
ae735bd9d6177002c3d986e5c19a78102233308f
[ "MIT" ]
2
2017-04-27T19:35:59.000Z
2017-06-13T16:19:33.000Z
falmer/content/models/scheme.py
sussexstudent/falmer
ae735bd9d6177002c3d986e5c19a78102233308f
[ "MIT" ]
975
2017-04-13T11:31:07.000Z
2022-02-10T07:46:18.000Z
falmer/content/models/scheme.py
sussexstudent/services-api
ae735bd9d6177002c3d986e5c19a78102233308f
[ "MIT" ]
3
2018-05-09T06:42:25.000Z
2020-12-10T18:29:30.000Z
from django.db import models from wagtail.admin.edit_handlers import FieldPanel, StreamFieldPanel, MultiFieldPanel from wagtail.core.blocks import StreamBlock from wagtail.core.fields import StreamField from wagtail.images.edit_handlers import ImageChooserPanel from falmer.content import components from falmer.content....
27.887097
97
0.685367
171
1,729
6.730994
0.380117
0.069505
0.044309
0.034752
0.079931
0.079931
0
0
0
0
0
0
0.219202
1,729
61
98
28.344262
0.852593
0
0
0.122449
0
0
0.111625
0.051475
0
0
0
0
0
1
0
false
0
0.204082
0
0.469388
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
b00272462aa831ed8359bfb1b05ac3991b3aef99
956
py
Python
src/marion/marion/tests/test_fields.py
openfun/marion
bf06b64bf78bca16685e62ff14b66897c1dbe80c
[ "MIT" ]
7
2021-04-06T20:33:31.000Z
2021-09-30T23:29:24.000Z
src/marion/marion/tests/test_fields.py
openfun/marion
bf06b64bf78bca16685e62ff14b66897c1dbe80c
[ "MIT" ]
23
2020-09-09T15:01:50.000Z
2022-01-03T08:58:36.000Z
src/marion/marion/tests/test_fields.py
openfun/marion
bf06b64bf78bca16685e62ff14b66897c1dbe80c
[ "MIT" ]
2
2020-12-14T10:07:07.000Z
2021-06-29T00:20:43.000Z
"""Tests for the marion application fields""" from marion.defaults import DocumentIssuerChoices from ..fields import IssuerLazyChoiceField, LazyChoiceField def test_fields_lazy_choice_field(): """ LazyChoiceField class. Choices instance attribute should not be customizable. """ field = LazyChoic...
26.555556
70
0.712343
97
956
6.793814
0.463918
0.060698
0.091047
0.063733
0
0
0
0
0
0
0
0.010363
0.192469
956
35
71
27.314286
0.843264
0.222803
0
0
0
0
0.154506
0.087268
0
0
0
0
0.176471
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
b00495771d6a310aa5e5d77c1c05c91690f9a756
2,331
py
Python
ObjectTrackingDrone/colorpickerusingTello.py
udayagopi587/ArealRobotics_AutonomousDrone
6bc10ee167076086abb3b2eef311ae43f457f21d
[ "MIT" ]
1
2022-03-12T00:47:24.000Z
2022-03-12T00:47:24.000Z
ObjectTrackingDrone/colorpickerusingTello.py
udayagopi587/ArealRobotics_AutonomousDrone
6bc10ee167076086abb3b2eef311ae43f457f21d
[ "MIT" ]
null
null
null
ObjectTrackingDrone/colorpickerusingTello.py
udayagopi587/ArealRobotics_AutonomousDrone
6bc10ee167076086abb3b2eef311ae43f457f21d
[ "MIT" ]
1
2022-03-14T23:42:57.000Z
2022-03-14T23:42:57.000Z
# -*- coding: utf-8 -*- """ Created on Thu Mar 3 12:15:40 2022 @author: udaya """ # -*- coding: utf-8 -*- """ Created on Sun Feb 27 18:06:29 2022 @author: udaya """ import cv2 import numpy as np from djitellopy import Tello frameWidth = 640 frameHeight = 480 ############################### ...
26.793103
81
0.632347
312
2,331
4.641026
0.384615
0.070442
0.075967
0.051796
0.112569
0.044199
0.044199
0
0
0
0
0.060523
0.213213
2,331
87
82
26.793103
0.729008
0.108966
0
0
0
0
0.081611
0
0
0
0.00212
0
0
1
0.056604
false
0.018868
0.056604
0
0.150943
0.037736
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b0050cae1ff0c2350a07478cbaf2f32a1d466c54
16,101
py
Python
climetlab_plugin_tools/create_plugin_cmd.py
ecmwf-lab/climetlab-plugin-tools
52fc1c6c07958ecfb8a5c946f4851725832b3cd0
[ "Apache-2.0" ]
null
null
null
climetlab_plugin_tools/create_plugin_cmd.py
ecmwf-lab/climetlab-plugin-tools
52fc1c6c07958ecfb8a5c946f4851725832b3cd0
[ "Apache-2.0" ]
null
null
null
climetlab_plugin_tools/create_plugin_cmd.py
ecmwf-lab/climetlab-plugin-tools
52fc1c6c07958ecfb8a5c946f4851725832b3cd0
[ "Apache-2.0" ]
null
null
null
# (C) Copyright 2020 ECMWF. # # This software is licensed under the terms of the Apache Licence Version 2.0 # which can be obtained at http://www.apache.org/licenses/LICENSE-2.0. # In applying this licence, ECMWF does not waive the privileges and immunities # granted to it by virtue of its status as an intergovernmenta...
33.266529
143
0.629464
1,976
16,101
4.981781
0.198381
0.021942
0.011174
0.024685
0.243905
0.162942
0.137647
0.105953
0.083503
0.067655
0
0.002619
0.264766
16,101
483
144
33.335404
0.828941
0.028942
0
0.220207
0
0.012953
0.367818
0.052371
0.002591
0
0
0.00207
0.007772
1
0.093264
false
0.002591
0.020725
0.010363
0.261658
0.031088
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b00bb16d432ae4e7eebbd1a8f438f11ad4838ec1
1,141
py
Python
openCVTutorials/openCVimgChangeColorspaceTutorial.py
nahutch/BasketballAI_P1
9a44f80787231df386910c28f17bab465fee013d
[ "Apache-2.0" ]
1
2019-01-24T19:07:08.000Z
2019-01-24T19:07:08.000Z
openCVTutorials/openCVimgChangeColorspaceTutorial.py
nahutch/BasketballAI_P1
9a44f80787231df386910c28f17bab465fee013d
[ "Apache-2.0" ]
null
null
null
openCVTutorials/openCVimgChangeColorspaceTutorial.py
nahutch/BasketballAI_P1
9a44f80787231df386910c28f17bab465fee013d
[ "Apache-2.0" ]
null
null
null
#following tutorial: https://opencv-python-tutroals.readthedocs.io/en/latest/py_tutorials/py_imgproc/py_colorspaces/py_colorspaces.html#converting-colorspaces import numpy as np import cv2 #there are more than 150 color-space conversions methods available in OpenCV #why so many? #gets all possible color space conver...
26.534884
158
0.718668
180
1,141
4.472222
0.572222
0.029814
0.037267
0.042236
0
0
0
0
0
0
0
0.049163
0.162138
1,141
42
159
27.166667
0.792887
0.404032
0
0
0
0
0.031343
0
0
0
0.00597
0
0
1
0
false
0
0.095238
0
0.095238
0.047619
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b00d6bcbdc91daedbc8ff5cedd805b13268a4bca
7,026
py
Python
src/model1_predict.py
shubhampachori12110095/FashionAI-Clothing-Attribute-Labels-Classification
04fb40948fcae55c379d8e878c41f281948155e8
[ "Apache-2.0" ]
2
2018-12-29T09:10:18.000Z
2020-08-07T03:42:38.000Z
src/model1_predict.py
shubhampachori12110095/FashionAI-Clothing-Attribute-Labels-Classification
04fb40948fcae55c379d8e878c41f281948155e8
[ "Apache-2.0" ]
null
null
null
src/model1_predict.py
shubhampachori12110095/FashionAI-Clothing-Attribute-Labels-Classification
04fb40948fcae55c379d8e878c41f281948155e8
[ "Apache-2.0" ]
3
2018-12-29T09:10:21.000Z
2021-05-23T06:30:35.000Z
# -*- coding: UTF-8 -*- import os import numpy as np import pandas as pd from tqdm import tqdm import json import cv2 from sklearn.model_selection import train_test_split import matplotlib from keras.utils import np_utils from keras.optimizers import * from keras.preprocessing.image import ImageDataGenerator from f...
39.033333
117
0.646883
894
7,026
4.864653
0.213647
0.019315
0.024833
0.03564
0.51966
0.500805
0.472292
0.472292
0.453438
0.437802
0
0.023544
0.208084
7,026
179
118
39.251397
0.758088
0.024765
0
0.454545
0
0.007576
0.182101
0.053934
0
0
0
0
0
1
0.007576
false
0.015152
0.151515
0
0.166667
0.181818
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b00f7bd4e39ef2e25f158e39f9604eb34518aa71
815
py
Python
test_parametrized_tests.py
karianjahi/python_pytest_tutorial
d8cf7bc9d85e75cc3248a35d8abdfd24d76276cd
[ "MIT" ]
null
null
null
test_parametrized_tests.py
karianjahi/python_pytest_tutorial
d8cf7bc9d85e75cc3248a35d8abdfd24d76276cd
[ "MIT" ]
null
null
null
test_parametrized_tests.py
karianjahi/python_pytest_tutorial
d8cf7bc9d85e75cc3248a35d8abdfd24d76276cd
[ "MIT" ]
null
null
null
""" Organizing test and parametrizing """ # Parametrized tests: Run many tests in one # pylint: disable=W0622 # pylint: disable=R0201 # pylint: disable=R0903 import pytest from word_counter import count_words class TestWordCounterParametrization: """ In this case we want to test many tests in one function "...
27.166667
59
0.586503
103
815
4.582524
0.601942
0.042373
0.04661
0.059322
0.067797
0
0
0
0
0
0
0.040404
0.271166
815
29
60
28.103448
0.754209
0.266258
0
0
0
0
0.276867
0.047359
0
0
0
0
0.0625
1
0.0625
false
0
0.125
0
0.3125
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
b0110b071338ec4840e5427dcade83815657e854
1,685
py
Python
src/dep_appearances/cli.py
jdlubrano/dep-appearances
bf752b469463ee8cb7351df37231d250be3bcf47
[ "MIT" ]
null
null
null
src/dep_appearances/cli.py
jdlubrano/dep-appearances
bf752b469463ee8cb7351df37231d250be3bcf47
[ "MIT" ]
null
null
null
src/dep_appearances/cli.py
jdlubrano/dep-appearances
bf752b469463ee8cb7351df37231d250be3bcf47
[ "MIT" ]
null
null
null
from argparse import ArgumentParser import os import pdb import sys from dep_appearances.appearances_report import AppearancesReport def main(): parser = ArgumentParser(description='Find dependencies that are unused and underused in your codebase.') parser.add_argument( 'project_root', metava...
30.089286
108
0.668249
193
1,685
5.658031
0.38342
0.098901
0.019231
0.064103
0.152015
0.152015
0.104396
0
0
0
0
0.003084
0.230267
1,685
55
109
30.636364
0.838859
0
0
0.139535
0
0
0.315134
0.093175
0
0
0
0
0
1
0.023256
false
0
0.186047
0
0.209302
0.209302
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b0134690af47b5e16baf709ce4dca459913ce34e
1,175
py
Python
pyfirmata_tmp36_MQ7_Mysql.py
amy861113/Arduino
7592c2029242fca24245ee1c34b2b9f6043070d1
[ "MIT" ]
null
null
null
pyfirmata_tmp36_MQ7_Mysql.py
amy861113/Arduino
7592c2029242fca24245ee1c34b2b9f6043070d1
[ "MIT" ]
null
null
null
pyfirmata_tmp36_MQ7_Mysql.py
amy861113/Arduino
7592c2029242fca24245ee1c34b2b9f6043070d1
[ "MIT" ]
null
null
null
from pyfirmata import Arduino, util from time import sleep import pymysql def arduino_map(x, in_min, in_max, out_min, out_max): return(x-in_min) * (out_max-out_min) / (in_max-in_min) + out_min PORT = "COM4" uno = Arduino(PORT) sleep(5) it = util.Iterator(uno) it.start() a4 = uno.get_pin('a:4:i') a5 = uno.get_p...
23.5
124
0.612766
175
1,175
4.022857
0.468571
0.021307
0.017045
0.028409
0
0
0
0
0
0
0
0.073144
0.220426
1,175
49
125
23.979592
0.695415
0.048511
0
0.135135
0
0
0.163229
0.021525
0
0
0
0
0
1
0.027027
false
0.027027
0.081081
0.027027
0.108108
0.108108
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b01504199a00f0b0ea4a2e7806f9a6775f0b35bb
11,037
py
Python
BCPNN/backend/_cpu_base_backend.py
KTH-HPC/StreamBrain
37b16e7c8e02e6d2800bcf89630a0f4419e90cd4
[ "BSD-2-Clause" ]
4
2020-10-20T22:15:25.000Z
2022-02-10T10:25:24.000Z
BCPNN/backend/_cpu_base_backend.py
KTH-HPC/StreamBrain
37b16e7c8e02e6d2800bcf89630a0f4419e90cd4
[ "BSD-2-Clause" ]
1
2020-12-16T10:46:50.000Z
2020-12-16T10:46:50.000Z
BCPNN/backend/_cpu_base_backend.py
KTH-HPC/StreamBrain
37b16e7c8e02e6d2800bcf89630a0f4419e90cd4
[ "BSD-2-Clause" ]
1
2020-10-20T22:15:29.000Z
2020-10-20T22:15:29.000Z
import sys import numpy as np from tqdm import tqdm from contextlib import nullcontext class DenseLayer: _update_state = None _softmax_minicolumns = None _update_counters = None _update_weights = None _update_bias = None def __init__( self, in_features, hyp...
35.038095
94
0.552596
1,179
11,037
4.951654
0.10687
0.04779
0.048818
0.039397
0.664782
0.640459
0.627612
0.591641
0.564406
0.545906
0
0.008322
0.357615
11,037
314
95
35.149682
0.815092
0.003896
0
0.606061
0
0
0.003093
0
0
0
0
0
0
1
0.056818
false
0.003788
0.015152
0
0.140152
0.003788
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b01639c2289f47ba698eea2092678bb22c032e75
6,879
py
Python
flux_sensors/flux_sensor.py
Flux-Coordinator/flux-sensors
44968c95e277023c3a6777d653e7b3cb4e333923
[ "MIT" ]
null
null
null
flux_sensors/flux_sensor.py
Flux-Coordinator/flux-sensors
44968c95e277023c3a6777d653e7b3cb4e333923
[ "MIT" ]
1
2018-06-14T18:21:33.000Z
2018-06-14T18:21:33.000Z
flux_sensors/flux_sensor.py
Flux-Coordinator/flux-sensors
44968c95e277023c3a6777d653e7b3cb4e333923
[ "MIT" ]
null
null
null
from flux_sensors.localizer.localizer import Localizer, Coordinates, LocalizerError, PozyxDeviceError from flux_sensors.light_sensor.light_sensor import LightSensor from flux_sensors.config_loader import ConfigLoader from flux_sensors.flux_server import FluxServer, FluxServerError from flux_sensors.models import models...
44.668831
118
0.602704
687
6,879
5.793304
0.235808
0.067839
0.059799
0.028141
0.284673
0.260302
0.195226
0.131156
0.131156
0.111055
0
0.003204
0.319378
6,879
153
119
44.960784
0.84686
0.022532
0
0.291339
0
0
0.135063
0
0
0
0
0
0
1
0.07874
false
0
0.070866
0.007874
0.212598
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
b019647d7984c42bcd98ff6521f630e19b83c858
11,288
py
Python
Network.py
Coldog2333/pytoflow
3cec913fa5a2ddb8133a075d4ff177cceb74f06a
[ "MIT" ]
102
2018-12-29T16:19:18.000Z
2022-01-13T03:54:04.000Z
Network.py
mengxiangyudlut/pytoflow
3cec913fa5a2ddb8133a075d4ff177cceb74f06a
[ "MIT" ]
19
2019-04-26T10:19:14.000Z
2021-11-14T07:36:23.000Z
Network.py
mengxiangyudlut/pytoflow
3cec913fa5a2ddb8133a075d4ff177cceb74f06a
[ "MIT" ]
32
2019-03-04T00:10:06.000Z
2022-01-11T08:19:19.000Z
import math import torch # import torch.utils.serialization # it was removed in torch v1.0.0 or higher version. arguments_strModel = 'sintel-final' SpyNet_model_dir = './models' # The directory of SpyNet's weights def normalize(tensorInput): tensorRed = (tensorInput[:, 0:1, :, :] - 0.485) / 0.229 tensorGre...
47.230126
186
0.589033
1,426
11,288
4.532959
0.153576
0.037902
0.036819
0.023205
0.485767
0.391244
0.318998
0.282178
0.23453
0.209777
0
0.051084
0.264706
11,288
238
187
47.428571
0.727711
0.092931
0
0.236364
0
0
0.027739
0
0
0
0
0
0
1
0.090909
false
0
0.012121
0.006061
0.193939
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
b01bbd168b9b732e58f788ff84aca342f6b50515
2,668
py
Python
storagetest/pkgs/ltp/acl/acl_test.py
liufeng-elva/storage-test2
5364cc00dbe71b106f1bb740bf391e6124788bf4
[ "MIT" ]
null
null
null
storagetest/pkgs/ltp/acl/acl_test.py
liufeng-elva/storage-test2
5364cc00dbe71b106f1bb740bf391e6124788bf4
[ "MIT" ]
null
null
null
storagetest/pkgs/ltp/acl/acl_test.py
liufeng-elva/storage-test2
5364cc00dbe71b106f1bb740bf391e6124788bf4
[ "MIT" ]
null
null
null
#!/usr/bin/python # -*- coding: UTF-8 -*- """ @file : acl_test.py @Time : 2020/11/9 9:25 @Author: Tao.Xu @Email : tao.xu2008@outlook.com """ import os import unittest from storagetest.libs import utils from storagetest.libs.log import log from storagetest.libs.exceptions import PlatformError, NoSuchDir, NoSuchBina...
29.644444
92
0.613943
359
2,668
4.376045
0.345404
0.056015
0.049013
0.026735
0.211967
0.181413
0.168046
0.150223
0.109484
0.109484
0
0.013111
0.256747
2,668
89
93
29.977528
0.779123
0.084708
0
0.216667
0
0
0.136664
0
0
0
0
0
0.033333
1
0.116667
false
0.033333
0.083333
0
0.283333
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
b0204523055a99ef60f353c69bef13df582957e8
15,276
py
Python
library/modules/encoder_decoders/sequence_to_sequence.py
dangitstam/le-traducteur
499005ac198029fd2a7e7469fb250b8b3af6a619
[ "Apache-2.0" ]
6
2018-10-23T10:05:55.000Z
2020-08-30T13:04:51.000Z
library/modules/encoder_decoders/sequence_to_sequence.py
dangitstam/le-traducteur
499005ac198029fd2a7e7469fb250b8b3af6a619
[ "Apache-2.0" ]
1
2018-08-20T21:58:33.000Z
2020-12-29T17:44:04.000Z
library/modules/encoder_decoders/sequence_to_sequence.py
dangitstam/le-traducteur
499005ac198029fd2a7e7469fb250b8b3af6a619
[ "Apache-2.0" ]
1
2022-03-26T05:13:38.000Z
2022-03-26T05:13:38.000Z
from typing import Dict, Optional, Tuple import numpy as np import torch import torch.nn.functional as F from allennlp.common.checks import ConfigurationError from allennlp.common.util import START_SYMBOL, END_SYMBOL from allennlp.data.vocabulary import Vocabulary from allennlp.models.model import Model from allennlp....
48.805112
106
0.645719
1,692
15,276
5.575059
0.208629
0.024807
0.011449
0.009011
0.146719
0.091911
0.078978
0.058624
0.035832
0.035832
0
0.003859
0.28751
15,276
312
107
48.961538
0.862826
0.244043
0
0.06383
0
0
0.03666
0.004014
0
0
0
0.003205
0
1
0.037234
false
0
0.074468
0
0.159574
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
b023ba4b1780ce639f98fb2247c460ffe792c1f6
20,333
py
Python
tests/rewards_tree/test_rewards_flow.py
shuklaayush/badger-system
1274eadbd0b0f3a02efbf40702719ce1d0a96c44
[ "MIT" ]
99
2020-12-02T08:40:48.000Z
2022-03-15T05:21:06.000Z
tests/rewards_tree/test_rewards_flow.py
shuklaayush/badger-system
1274eadbd0b0f3a02efbf40702719ce1d0a96c44
[ "MIT" ]
115
2020-12-15T07:15:39.000Z
2022-03-28T22:21:03.000Z
tests/rewards_tree/test_rewards_flow.py
shuklaayush/badger-system
1274eadbd0b0f3a02efbf40702719ce1d0a96c44
[ "MIT" ]
56
2020-12-11T06:50:04.000Z
2022-02-21T09:17:38.000Z
import json import secrets import brownie from dotmap import DotMap import pytest import pprint from brownie import * from helpers.constants import * from helpers.registry import registry from rich.console import Console FARM_ADDRESS = "0xa0246c9032bC3A600820415aE600c6388619A14D" XSUSHI_ADDRESS = "0x8798249c2E60744...
31.137825
119
0.59278
1,750
20,333
6.698857
0.138857
0.058176
0.084193
0.017402
0.626717
0.609059
0.601638
0.55583
0.51352
0.497654
0
0.028435
0.299513
20,333
652
120
31.185583
0.794636
0.049722
0
0.570916
0
0
0.113231
0.007984
0
0
0.004355
0.001534
0.014363
1
0.014363
false
0
0.019749
0.003591
0.044883
0.005386
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b0249f5db53b2ce54527df608f97d99c1010a240
23,869
py
Python
HCm-uv/HCm-UV_v4.11/HCm-UV_v4.11.py
Borja-Perez-Diaz/HII-CHI-Mistry
d0dafc753c63246bf14b77807a885ddc7bd4bb99
[ "MIT" ]
null
null
null
HCm-uv/HCm-UV_v4.11/HCm-UV_v4.11.py
Borja-Perez-Diaz/HII-CHI-Mistry
d0dafc753c63246bf14b77807a885ddc7bd4bb99
[ "MIT" ]
null
null
null
HCm-uv/HCm-UV_v4.11/HCm-UV_v4.11.py
Borja-Perez-Diaz/HII-CHI-Mistry
d0dafc753c63246bf14b77807a885ddc7bd4bb99
[ "MIT" ]
null
null
null
# Filename: HCm_UV_v4.11.py import string import numpy as np import sys #sys.stderr = open('errorlog.txt', 'w') #Function for interpolation of grids def interpolate(grid,z,zmin,zmax,n): ncol = 9 vec = [] for col in range(ncol): inter = 0 no_inter = 0 for row in range(0,len(grid)): ...
30.759021
453
0.526541
3,539
23,869
3.342187
0.083639
0.023334
0.02232
0.020883
0.498647
0.440227
0.36422
0.319412
0.303855
0.284156
0
0.118509
0.325485
23,869
775
454
30.79871
0.616149
0.016884
0
0.458529
0
0.010955
0.129669
0.025712
0
0
0
0
0
1
0.001565
false
0.01252
0.004695
0
0.007825
0.057903
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b02d1a840f2e9ca574098b991b8f37e1b954c866
979
py
Python
excel2.py
darkless456/Python
1ba37d028e4a818ccfffc18682c1bac15554e3ac
[ "MIT" ]
null
null
null
excel2.py
darkless456/Python
1ba37d028e4a818ccfffc18682c1bac15554e3ac
[ "MIT" ]
null
null
null
excel2.py
darkless456/Python
1ba37d028e4a818ccfffc18682c1bac15554e3ac
[ "MIT" ]
null
null
null
# excel2.py import xlrd def print_xls(path): xlsFile = xlrd.open_workbook(path) try: mySheet = xlsFile.sheets()[0] # 访问第1张表序号0 // xlsFile.sheet_by_name('sheetName') 通过工作表名访问 except: print('no such sheet in file') return print('%d rows, %d cols' % (mySheet.nrows, mySheet.ncols)...
27.194444
96
0.670072
126
979
4.738095
0.579365
0.026801
0.026801
0.050251
0.073702
0
0
0
0
0
0
0.007634
0.19714
979
35
97
27.971429
0.751908
0.091931
0
0
0
0
0.13438
0.052356
0
0
0
0
0
1
0.058824
false
0
0.058824
0
0.176471
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
b02f9eadae5afd900218c21f9e3251e4c4f3cf07
1,162
py
Python
reth_buffer/reth_buffer/__init__.py
sosp2021/Reth
10c032f44a25049355ebdd97a2cb3299e8c3fb82
[ "MIT" ]
null
null
null
reth_buffer/reth_buffer/__init__.py
sosp2021/Reth
10c032f44a25049355ebdd97a2cb3299e8c3fb82
[ "MIT" ]
1
2021-08-10T02:58:58.000Z
2021-08-10T02:58:58.000Z
reth_buffer/reth_buffer/__init__.py
sosp2021/reth
10c032f44a25049355ebdd97a2cb3299e8c3fb82
[ "MIT" ]
null
null
null
import multiprocessing as mp import portpicker from .client import Client, NumpyLoader, TorchCudaLoader from .sampler import PERSampler from .server.main_loop import main_loop from .utils import get_local_ip def start_server( capacity, batch_size, host=None, port=None, samplers=None, cache_policy=None ): if...
23.24
81
0.645439
148
1,162
4.844595
0.391892
0.072524
0.09484
0.066946
0.089261
0.089261
0
0
0
0
0
0.010333
0.25043
1,162
49
82
23.714286
0.812859
0
0
0.04878
0
0
0.061102
0
0
0
0
0
0
1
0.04878
false
0
0.146341
0
0.243902
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
b02fad481b4d3cb3263f98acf09c40e1f2669bfa
7,171
py
Python
agent.py
FlowerForAlgernon/rainbow
78492ba572e2f8b4b2228d2ca625af94a09ee696
[ "Apache-2.0" ]
1
2022-03-23T02:02:10.000Z
2022-03-23T02:02:10.000Z
agent.py
FlowerForAlgernon/rainbow
78492ba572e2f8b4b2228d2ca625af94a09ee696
[ "Apache-2.0" ]
null
null
null
agent.py
FlowerForAlgernon/rainbow
78492ba572e2f8b4b2228d2ca625af94a09ee696
[ "Apache-2.0" ]
null
null
null
import random import numpy as np import torch import torch.optim as optim import torch.nn.functional as F import torchvision.transforms as T from memory import Transition, ReplayMemory, PrioritizedReplayMemory, NStepMemory from DQN import DQN, DuelingDQN, NoisyDQN, DistributionalDQN class Agent: def __...
48.452703
142
0.647748
923
7,171
4.812568
0.183099
0.043224
0.037821
0.028366
0.352094
0.21792
0.156911
0.147006
0.147006
0.147006
0
0.011534
0.238321
7,171
148
143
48.452703
0.801721
0.048529
0
0.107143
0
0
0.0006
0
0
0
0
0
0
1
0.0625
false
0
0.071429
0
0.196429
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
b0370f00352f25c209bf62c39330309ded5b5b35
413
py
Python
xslt/apply.py
carlosduarteroa/smap
5760631dfaf3e85da26ce68bf542bf254bb92c80
[ "BSD-2-Clause" ]
21
2015-02-06T21:55:59.000Z
2021-04-29T11:23:18.000Z
xslt/apply.py
carlosduarteroa/smap
5760631dfaf3e85da26ce68bf542bf254bb92c80
[ "BSD-2-Clause" ]
9
2015-02-03T10:41:35.000Z
2020-02-18T12:46:10.000Z
xslt/apply.py
carlosduarteroa/smap
5760631dfaf3e85da26ce68bf542bf254bb92c80
[ "BSD-2-Clause" ]
20
2015-02-06T00:09:19.000Z
2020-01-10T13:27:06.000Z
"""Apply a stylesheet to an XML file""" import sys from lxml import etree if len(sys.argv) != 3: print >>sys.stderr, "Usage: %s <stylesheet> <xml doc> ..." % sys.argv[0] sys.exit(1) transform = etree.XSLT(etree.XML(open(sys.argv[1], "r").read())) for xmlfile in sys.argv[2:]: with open(xmlfile, "r") as fp...
27.533333
76
0.639225
67
413
3.925373
0.597015
0.106464
0
0
0
0
0
0
0
0
0
0.014706
0.176755
413
14
77
29.5
0.758824
0.079903
0
0
0
0
0.101604
0
0
0
0
0
0
1
0
false
0
0.2
0
0.2
0.2
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b037c4f526f6d6afd8598b5e5a8cb64d9cc7462a
7,122
py
Python
docs/conf.py
vlukes/io3d
34d048b7f737a5e56610879f6ab103128e8f0750
[ "MIT" ]
8
2016-09-26T01:35:15.000Z
2022-02-23T04:05:23.000Z
docs/conf.py
vlukes/io3d
34d048b7f737a5e56610879f6ab103128e8f0750
[ "MIT" ]
4
2016-05-18T11:04:56.000Z
2018-10-24T11:03:03.000Z
docs/conf.py
vlukes/io3d
34d048b7f737a5e56610879f6ab103128e8f0750
[ "MIT" ]
6
2017-03-24T20:43:21.000Z
2021-08-23T06:05:34.000Z
# -*- coding: utf-8 -*- # # io3d documentation build configuration file, created by # sphinx-quickstart on Mon Nov 27 12:01:57 2017. # # This file is execfile()d with the current directory set to its # containing dir. # # Note that not all possible configuration values are present in this # autogenerated file. # # All ...
32.226244
102
0.664139
888
7,122
5.269144
0.427928
0.010259
0.005984
0.006412
0.089549
0.04424
0.03847
0.022654
0.022654
0.022654
0
0.011389
0.173968
7,122
220
103
32.372727
0.783954
0.739118
0
0.030303
0
0
0.294355
0
0
0
0
0.004545
0
1
0
false
0
0.045455
0
0.045455
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b03a815221b3f33cdcf33d82406be159b843f64d
2,096
py
Python
School-Management-System/teachers/views.py
GisaKaze/Python-Quarantine-Projects
29fabcb7e4046e6f3e9a19403e6d2490fe4b9fc4
[ "MIT" ]
null
null
null
School-Management-System/teachers/views.py
GisaKaze/Python-Quarantine-Projects
29fabcb7e4046e6f3e9a19403e6d2490fe4b9fc4
[ "MIT" ]
null
null
null
School-Management-System/teachers/views.py
GisaKaze/Python-Quarantine-Projects
29fabcb7e4046e6f3e9a19403e6d2490fe4b9fc4
[ "MIT" ]
null
null
null
from django.shortcuts import render, get_object_or_404, redirect from .models import TeacherInfo from .forms import CreateTeacher from django.contrib import messages from django.core.paginator import Paginator # Create your views here. def teacher_list(request): teachers = TeacherInfo.objects.all() paginator ...
30.376812
102
0.705153
243
2,096
5.888889
0.222222
0.069182
0.067086
0.075472
0.246681
0.132774
0.132774
0.065688
0
0
0
0.004162
0.197519
2,096
68
103
30.823529
0.846611
0.010973
0
0.176471
0
0
0.143961
0.052174
0
0
0
0
0
1
0.098039
false
0
0.098039
0
0.333333
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b043e0116441bcee9ae6a5419079e591b49e7c1e
3,267
py
Python
tests/service/test_integer_converter_service.py
NeolithEra/WavesGatewayFramework
e7ba892427e1d0444f2bfdc2922c45ff5f4c4add
[ "MIT" ]
25
2018-03-04T07:49:21.000Z
2022-03-28T05:20:50.000Z
tests/service/test_integer_converter_service.py
NeolithEra/WavesGatewayFramework
e7ba892427e1d0444f2bfdc2922c45ff5f4c4add
[ "MIT" ]
22
2018-03-25T13:19:45.000Z
2020-11-28T17:21:08.000Z
tests/service/test_integer_converter_service.py
NeolithEra/WavesGatewayFramework
e7ba892427e1d0444f2bfdc2922c45ff5f4c4add
[ "MIT" ]
31
2018-03-25T09:45:13.000Z
2022-03-24T05:32:18.000Z
import unittest from unittest.mock import patch from waves_gateway.model import Transaction, TransactionReceiver from waves_gateway.service import IntegerConverterService class IntegerConverterServiceSpec(unittest.TestCase): @patch.multiple( # type: ignore IntegerConverterService, __abstractmethods__=s...
37.551724
94
0.67034
338
3,267
6.136095
0.186391
0.08486
0.154291
0.150434
0.721794
0.674542
0.6027
0.461909
0.417551
0.367406
0
0.056818
0.245791
3,267
86
95
37.988372
0.784903
0.003673
0
0.5
0
0
0.053797
0.026745
0
0
0
0
0.109375
1
0.140625
false
0
0.0625
0.03125
0.25
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b044475c3b8a25898a8527a87ed6dc1d9dadbb1d
6,670
py
Python
live_demo.py
GerryZhang7/ASL-Translator-
3963311d8dd1f010ee5a19b3760b451bc287ab1e
[ "MIT" ]
null
null
null
live_demo.py
GerryZhang7/ASL-Translator-
3963311d8dd1f010ee5a19b3760b451bc287ab1e
[ "MIT" ]
null
null
null
live_demo.py
GerryZhang7/ASL-Translator-
3963311d8dd1f010ee5a19b3760b451bc287ab1e
[ "MIT" ]
null
null
null
#!/usr/bin/env python # -*- coding: utf-8 -*- """ LIVE DEMO This script loads a pre-trained model (for best results use pre-trained weights for classification block) and classifies American Sign Language finger spelling frame-by-frame in real-time """ import string import cv2 import time from processing import square...
33.517588
105
0.553373
831
6,670
4.340554
0.318893
0.024951
0.037427
0.047408
0.324369
0.275575
0.259218
0.242584
0.242584
0.242584
0
0.068587
0.302699
6,670
198
106
33.686869
0.706945
0.214843
0
0.238938
0
0
0.072739
0.005898
0
0
0.000874
0
0.00885
1
0
false
0
0.061947
0
0.061947
0.00885
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b044b434998843e21fedc472b72d6aa6d023641a
8,770
py
Python
prob2020/python/gene_sequence.py
KarchinLab/probabilistic2020
8e0b1b9578bd8189b1690dd2f17476c3305b98dc
[ "Apache-2.0" ]
8
2016-04-30T03:26:40.000Z
2021-09-17T04:47:08.000Z
prob2020/python/gene_sequence.py
KarchinLab/probabilistic2020
8e0b1b9578bd8189b1690dd2f17476c3305b98dc
[ "Apache-2.0" ]
9
2016-08-18T15:19:04.000Z
2019-07-17T18:16:52.000Z
prob2020/python/gene_sequence.py
KarchinLab/probabilistic2020
8e0b1b9578bd8189b1690dd2f17476c3305b98dc
[ "Apache-2.0" ]
7
2016-10-19T03:43:42.000Z
2021-07-31T02:40:20.000Z
"""Fetches gene sequence from gene fasta created by extract_genes.py""" import prob2020.python.utils as utils class GeneSequence(object): def __init__(self, fasta_obj, nuc_context=1.5): self.fasta = fasta_obj self.nuc_context = nuc_context def set_gene(self, bed_line): ...
34.801587
89
0.55382
1,125
8,770
4.113778
0.163556
0.022688
0.010372
0.015557
0.440147
0.415298
0.394987
0.357822
0.32325
0.32325
0
0.015946
0.356442
8,770
251
90
34.940239
0.80404
0.337856
0
0.356522
0
0
0.03378
0.008681
0
0
0
0
0
1
0.078261
false
0.008696
0.008696
0
0.130435
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
b04538316ec8e7dec6961b4c00010c7027a8e97d
1,118
py
Python
src/main/python/request/http_request.py
photowey/pytest-dynamic-framework
4e7b6d74594191006b50831d42e7aae21e154d56
[ "Apache-2.0" ]
null
null
null
src/main/python/request/http_request.py
photowey/pytest-dynamic-framework
4e7b6d74594191006b50831d42e7aae21e154d56
[ "Apache-2.0" ]
null
null
null
src/main/python/request/http_request.py
photowey/pytest-dynamic-framework
4e7b6d74594191006b50831d42e7aae21e154d56
[ "Apache-2.0" ]
null
null
null
# -*- coding:utf-8 -*- # --------------------------------------------- # @file http_request # @description http_request # @author WcJun # @date 2021/07/19 # --------------------------------------------- from src.main.python.request.options import RequestOptions class HttpRequest: """ Http Request """ ...
29.421053
92
0.573345
115
1,118
5.4
0.469565
0.112721
0
0
0
0
0
0
0
0
0
0.012821
0.232558
1,118
37
93
30.216216
0.710956
0.18068
0
0
0
0
0.003356
0
0
0
0
0
0
1
0.105263
false
0
0.052632
0
0.263158
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b04682256b68f1be1d146f950d4cf5cacbc05399
5,728
py
Python
bot/helper/mirror_utils/download_utils/aria2_download.py
vincreator/Eunha
85a702a5b5f30ccea1798122c261d4ff07fe0c0c
[ "Apache-2.0" ]
null
null
null
bot/helper/mirror_utils/download_utils/aria2_download.py
vincreator/Eunha
85a702a5b5f30ccea1798122c261d4ff07fe0c0c
[ "Apache-2.0" ]
null
null
null
bot/helper/mirror_utils/download_utils/aria2_download.py
vincreator/Eunha
85a702a5b5f30ccea1798122c261d4ff07fe0c0c
[ "Apache-2.0" ]
null
null
null
from time import sleep from threading import Thread from bot import aria2, download_dict_lock, download_dict, STOP_DUPLICATE, TORRENT_DIRECT_LIMIT, ZIP_UNZIP_LIMIT, LOGGER, STORAGE_THRESHOLD from bot.helper.mirror_utils.upload_utils.gdriveTools import GoogleDriveHelper from bot.helper.ext_utils.bot_utils import is_mag...
46.569106
138
0.618191
648
5,728
5.265432
0.233025
0.053341
0.036928
0.025791
0.251759
0.137456
0.085873
0.075615
0.025791
0.025791
0
0.004666
0.289106
5,728
122
139
46.95082
0.833251
0.010999
0
0.232143
0
0
0.118665
0.018541
0
0
0
0
0
1
0.053571
false
0.017857
0.071429
0
0.169643
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
b047b2781fee7bef3205107d3cc7277c6707a880
3,407
py
Python
gol.py
AjayMT/game-of-life
681bb92e1d7c0644645af7b77f0106ba2d4c9c20
[ "MIT" ]
null
null
null
gol.py
AjayMT/game-of-life
681bb92e1d7c0644645af7b77f0106ba2d4c9c20
[ "MIT" ]
null
null
null
gol.py
AjayMT/game-of-life
681bb92e1d7c0644645af7b77f0106ba2d4c9c20
[ "MIT" ]
null
null
null
import pygame from pygame.locals import * from pygamehelper import * from vec2d import * from random import randrange class Matrix: def __init__(self, w, h): self.w, self.h = w, h self._data = [] for i in range(self.w * self.h): self._data.append(None) def __getitem__(se...
27.039683
70
0.502495
494
3,407
3.402834
0.172065
0.074955
0.042832
0.023795
0.15586
0.060678
0
0
0
0
0
0.026147
0.360141
3,407
125
71
27.256
0.744954
0
0
0.086022
0
0
0.019378
0
0
0
0
0
0
1
0.139785
false
0
0.053763
0.032258
0.268817
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
b04cbd151462272c28fb0ccf978f4c3ccbb776cd
11,913
py
Python
frontend/alexa/alexa.py
jjanetzki/HackHPI-2017
5345a4b385b92dff8b665818127e85eb1e14b31f
[ "MIT" ]
1
2017-06-17T18:18:55.000Z
2017-06-17T18:18:55.000Z
frontend/alexa/alexa.py
janetzki/Productivity-Bot
5345a4b385b92dff8b665818127e85eb1e14b31f
[ "MIT" ]
null
null
null
frontend/alexa/alexa.py
janetzki/Productivity-Bot
5345a4b385b92dff8b665818127e85eb1e14b31f
[ "MIT" ]
null
null
null
""" This code sample is a part of a simple demo to show beginners how to create a skill (app) for the Amazon Echo using AWS Lambda and the Alexa Skills Kit. For the full code sample visit https://github.com/pmckinney8/Alexa_Dojo_Skill.git """ from __future__ import print_function import requests import json alcohol_...
39.44702
242
0.697138
1,390
11,913
5.704317
0.182014
0.062051
0.062555
0.05297
0.565015
0.464371
0.399168
0.388952
0.368521
0.334468
0
0.001259
0.200201
11,913
301
243
39.578073
0.830919
0.118526
0
0.366667
0
0.004762
0.218771
0.009278
0
0
0
0.003322
0
1
0.1
false
0
0.014286
0.009524
0.271429
0.02381
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b04d338c3d1c16a12edd8387b7d2185efd9aed7b
474
py
Python
day1.py
kdrag0n/aoc2021
469bd861a7d7c0add14412a705ec4cb1e1b5a10f
[ "MIT" ]
2
2021-12-04T21:15:14.000Z
2021-12-12T09:28:28.000Z
day1.py
kdrag0n/aoc2021
469bd861a7d7c0add14412a705ec4cb1e1b5a10f
[ "MIT" ]
null
null
null
day1.py
kdrag0n/aoc2021
469bd861a7d7c0add14412a705ec4cb1e1b5a10f
[ "MIT" ]
null
null
null
#!/usr/bin/env python3 import sys def ints(itr): return [int(i) for i in itr] with open(sys.argv[1], "r") as f: lines = [l for l in f.read().split("\n") if l] ilist = [] imap = {} total = 0 result = 0 other = 0 last = -1 while True: for l in lines: val = int(l.split()[0]) if last !...
12.810811
50
0.529536
79
474
3.177215
0.506329
0.071713
0.047809
0
0
0
0
0
0
0
0
0.026946
0.295359
474
36
51
13.166667
0.724551
0.044304
0
0
0
0
0.103982
0
0
0
0
0
0
1
0.047619
false
0
0.047619
0.047619
0.142857
0.142857
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b04f12eb656c69facb8b7d0c196d013597b90eb0
11,920
py
Python
esst/utils/historygraph.py
etcher-be/esst
ac41cd0c07af8ca8532997f533756c529c9609a4
[ "MIT" ]
4
2018-06-24T14:03:44.000Z
2019-01-21T01:20:02.000Z
esst/utils/historygraph.py
etcher-be/esst
ac41cd0c07af8ca8532997f533756c529c9609a4
[ "MIT" ]
106
2018-06-24T13:59:52.000Z
2019-11-26T09:05:14.000Z
esst/utils/historygraph.py
theendsofinvention/esst
ac41cd0c07af8ca8532997f533756c529c9609a4
[ "MIT" ]
null
null
null
# coding=utf-8 """ Creates graphic of perfs """ import datetime import typing from collections import namedtuple from tempfile import mktemp import humanize from esst.core import CTX PLT = GRID_SPEC = TICKER = None # https://stackoverflow.com/questions/4931376/generating-matplotlib-graphs-without-a-running-x-serv...
32.747253
117
0.640017
1,508
11,920
4.723475
0.169761
0.030886
0.031588
0.033974
0.458655
0.38846
0.325284
0.265057
0.233329
0.224344
0
0.013602
0.266023
11,920
363
118
32.837466
0.800549
0.163926
0
0.174089
0
0
0.035455
0.005109
0
0
0
0
0
1
0.060729
false
0
0.040486
0.012146
0.153846
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b04f60f28cbb6155e0266d15a62d61ce814d26c3
1,267
py
Python
20.valid-parentheses.py
Qianli-Ma/LeetCode
ebda421c3d652adffca5e547a22937bf1726a532
[ "MIT" ]
null
null
null
20.valid-parentheses.py
Qianli-Ma/LeetCode
ebda421c3d652adffca5e547a22937bf1726a532
[ "MIT" ]
null
null
null
20.valid-parentheses.py
Qianli-Ma/LeetCode
ebda421c3d652adffca5e547a22937bf1726a532
[ "MIT" ]
null
null
null
# # @lc app=leetcode id=20 lang=python3 # # [20] Valid Parentheses # # https://leetcode.com/problems/valid-parentheses/description/ # # algorithms # Easy (36.20%) # Total Accepted: 554.4K # Total Submissions: 1.5M # Testcase Example: '"()"' # # Given a string containing just the characters '(', ')', '{', '}', '[' a...
16.454545
75
0.534333
147
1,267
4.605442
0.557823
0.081241
0.06647
0.053176
0.070901
0
0
0
0
0
0
0.022099
0.285714
1,267
76
76
16.671053
0.725967
0.568272
0
0.153846
0
0
0.012371
0
0
0
0
0
0
1
0.076923
false
0
0
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
b05bf40e3728937480f8f42cb9c975d60036475f
6,911
py
Python
neptune-python-utils/neptune_python_utils/glue_gremlin_client.py
Alfian878787/amazon-neptune-tools
a447da238e99612a290babc66878fe772727a19e
[ "Apache-2.0" ]
null
null
null
neptune-python-utils/neptune_python_utils/glue_gremlin_client.py
Alfian878787/amazon-neptune-tools
a447da238e99612a290babc66878fe772727a19e
[ "Apache-2.0" ]
null
null
null
neptune-python-utils/neptune_python_utils/glue_gremlin_client.py
Alfian878787/amazon-neptune-tools
a447da238e99612a290babc66878fe772727a19e
[ "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://aws.amazon.com/apache2.0/ # # or in the "license" file ac...
46.073333
135
0.570395
763
6,911
5.044561
0.218873
0.031177
0.037412
0.021824
0.665887
0.650818
0.58171
0.58171
0.58171
0.558846
0
0.004337
0.332658
6,911
150
136
46.073333
0.830226
0.261323
0
0.68
0
0
0.04578
0
0
0
0
0
0
1
0.09
false
0.02
0.12
0
0.26
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
b05fe1389ad39d5ec1240e047aa523f2264c0d97
343
py
Python
floyd_warshall/messages/rate_request.py
hrs231/sample-code
91c2972d1a414397d3505d3b4df9ee80b67bcac0
[ "MIT" ]
null
null
null
floyd_warshall/messages/rate_request.py
hrs231/sample-code
91c2972d1a414397d3505d3b4df9ee80b67bcac0
[ "MIT" ]
null
null
null
floyd_warshall/messages/rate_request.py
hrs231/sample-code
91c2972d1a414397d3505d3b4df9ee80b67bcac0
[ "MIT" ]
null
null
null
class RateRequest(object): """" Used by Price Engine Clients to query the Price Engine """ def __init__(self, exch_1, curr_1, exch_2, curr_2): self.exch_1 = exch_1 self.curr_1 = curr_1 self.exch_2 = exch_2 self.curr_2 = curr_2 self.rate = 0 self.path = [] ...
28.583333
67
0.594752
53
343
3.528302
0.45283
0.128342
0.096257
0.106952
0
0
0
0
0
0
0
0.054852
0.309038
343
12
68
28.583333
0.734177
0.163265
0
0
0
0
0
0
0
0
0
0
0
1
0.111111
false
0
0
0
0.222222
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b0618e2deaae21564649c946c7681a44ee75680f
2,613
py
Python
backend/app/api/api_v1/router/file/excel_tool.py
PY-GZKY/fastapi-crawl-admin
6535054994d11e3c31b4caeae65e8fa0f495d2b7
[ "MIT" ]
13
2021-07-25T15:26:04.000Z
2022-03-02T12:12:02.000Z
backend/app/api/api_v1/router/file/excel_tool.py
PY-GZKY/fastapi-crawl-admin
6535054994d11e3c31b4caeae65e8fa0f495d2b7
[ "MIT" ]
1
2021-07-26T03:26:09.000Z
2021-07-26T09:05:38.000Z
backend/app/api/api_v1/router/file/excel_tool.py
PY-GZKY/fastapi-crawl-admin
6535054994d11e3c31b4caeae65e8fa0f495d2b7
[ "MIT" ]
3
2021-07-26T01:44:24.000Z
2021-07-31T14:31:49.000Z
# -*- coding: utf-8 -* # @Time : 2020/12/22 15:58 from fastapi import Depends from motor.motor_asyncio import AsyncIOMotorClient from app.api.db.mongoDB import get_database import pandas as pd import numpy as np from io import BytesIO class ExcelTools: def __init__(self, columns_map=None, order=None): ...
25.871287
87
0.564485
313
2,613
4.571885
0.450479
0.083857
0.068484
0.02935
0.075472
0.041929
0.041929
0
0
0
0
0.01168
0.311902
2,613
101
88
25.871287
0.784205
0.168006
0
0.083333
0
0
0.025292
0
0
0
0
0
0
1
0.083333
false
0.020833
0.125
0
0.3125
0.020833
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b0619b37fbd880320070eeeb51552bb149486090
1,164
py
Python
Lab8/1 + 2 (Simple socket server)/simple_client.py
marianfx/python-labs
7066db410ad19cababb7b66745641e65a28ccd98
[ "MIT" ]
null
null
null
Lab8/1 + 2 (Simple socket server)/simple_client.py
marianfx/python-labs
7066db410ad19cababb7b66745641e65a28ccd98
[ "MIT" ]
null
null
null
Lab8/1 + 2 (Simple socket server)/simple_client.py
marianfx/python-labs
7066db410ad19cababb7b66745641e65a28ccd98
[ "MIT" ]
null
null
null
"""Simple socket client for the simple socket client.""" import sys import socket import time SOCKET_ADDRESS = "127.0.0.1" SOCKET_PORT = 6996 def build_client_tcp(address: str, port: int): """Builds the TCP client.""" try: sock = socket.socket(socket.AF_INET, socket.SOCK_STREAM) sock.connect(...
28.390244
98
0.649485
165
1,164
4.412121
0.381818
0.048077
0.049451
0.046703
0.104396
0.104396
0.104396
0.104396
0
0
0
0.017758
0.225945
1,164
40
99
29.1
0.790233
0.082474
0
0
0
0
0.165399
0
0
0
0
0
0
1
0.066667
false
0
0.1
0
0.166667
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
b062b0f29115369104d664570dbb03f1de934fe3
2,689
py
Python
009/app.py
ilos-vigil/random-script
bf8d45196d4faa6912dc0469a86b8370f43ce7ac
[ "MIT" ]
null
null
null
009/app.py
ilos-vigil/random-script
bf8d45196d4faa6912dc0469a86b8370f43ce7ac
[ "MIT" ]
null
null
null
009/app.py
ilos-vigil/random-script
bf8d45196d4faa6912dc0469a86b8370f43ce7ac
[ "MIT" ]
null
null
null
import bs4 import nltk import json import re import requests with open('./acronym_abbreviation_id.json', 'r') as f: data = f.read() list_acronym_abbreviation = json.loads(data) from_wikipedia = False if from_wikipedia: # Take text with Indonesian language from Wikipedia randomly html = requests.get('h...
38.414286
430
0.661584
386
2,689
4.53886
0.367876
0.050228
0.020548
0.017123
0.214612
0.174658
0.025114
0.025114
0
0
0
0.010314
0.170695
2,689
69
431
38.971014
0.769058
0.144663
0
0.08
0
0.02
0.297155
0.022319
0
0
0
0
0
1
0
false
0
0.1
0
0.1
0.06
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b062c54e4119bba9afb9e6fce3e62bb1a445400e
2,295
py
Python
graphs/page_rank.py
tg12/Python
398d1dbf4b780d1725aeae9a91b4c79f4410e2f0
[ "MIT" ]
null
null
null
graphs/page_rank.py
tg12/Python
398d1dbf4b780d1725aeae9a91b4c79f4410e2f0
[ "MIT" ]
null
null
null
graphs/page_rank.py
tg12/Python
398d1dbf4b780d1725aeae9a91b4c79f4410e2f0
[ "MIT" ]
1
2020-06-26T09:46:17.000Z
2020-06-26T09:46:17.000Z
'''THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE, TITLE AND NON-INFRINGEMENT. IN NO EVENT SHALL THE COPYRIGHT HOLDERS OR ANYONE DISTRIBUTING THE SOFTWARE BE LIABLE FOR ANY DAMAGES OR OT...
25.21978
74
0.616122
301
2,295
4.624585
0.408638
0.031609
0.006466
0.030172
0.076868
0.043103
0
0
0
0
0
0.042966
0.259695
2,295
90
75
25.5
0.776339
0.326797
0
0.071429
0
0
0.083866
0
0
0
0
0
0
1
0.142857
false
0
0
0.02381
0.190476
0.095238
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b064ac81a6a14605eca93bb63e07f0834ed4309a
1,147
py
Python
lairgpt/utils/assets.py
lightonai/lairgpt
7580e1339a39662b2ff636d158c36195eb7fe3fb
[ "MIT" ]
19
2021-05-04T13:54:45.000Z
2022-01-05T15:45:12.000Z
lairgpt/utils/assets.py
lightonai/lairgpt
7580e1339a39662b2ff636d158c36195eb7fe3fb
[ "MIT" ]
null
null
null
lairgpt/utils/assets.py
lightonai/lairgpt
7580e1339a39662b2ff636d158c36195eb7fe3fb
[ "MIT" ]
1
2021-05-28T15:25:12.000Z
2021-05-28T15:25:12.000Z
from enum import Enum from os.path import expanduser from lairgpt.utils.remote import local_dir class Config(Enum): """Settings for preconfigured models instances """ SMALL = { "d_model": 768, "n_heads": 12, "n_layers": 12, "vocab_size": 50262, "max_seq_len": 1024 ...
23.408163
60
0.558849
135
1,147
4.518519
0.377778
0.078689
0.091803
0.111475
0.265574
0.265574
0.265574
0.177049
0.177049
0.177049
0
0.085459
0.316478
1,147
48
61
23.895833
0.692602
0.133391
0
0.358974
0
0
0.232271
0
0
0
0
0
0
1
0
false
0
0.076923
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
b0651029340e768b51b715881e03f9826ce6837f
1,546
py
Python
smart_open/__init__.py
DataTron-io/smart_open
3565eff8f0ffe19d7fd31063753384e0084fb1e0
[ "MIT" ]
1
2020-09-28T06:47:58.000Z
2020-09-28T06:47:58.000Z
smart_open/__init__.py
DataTron-io/smart_open
3565eff8f0ffe19d7fd31063753384e0084fb1e0
[ "MIT" ]
null
null
null
smart_open/__init__.py
DataTron-io/smart_open
3565eff8f0ffe19d7fd31063753384e0084fb1e0
[ "MIT" ]
null
null
null
import shutil from .smart_open_lib import * DEFAULT_CHUNKSIZE = 16*1024*1024 # 16mb def copy_file(src, dest, close_src=True, close_dest=True, make_path=False): """ Copies file from src to dest. Supports s3 and webhdfs (does not include kerberos support) If src does not exist, a FileNotFoundError is rais...
34.355556
138
0.679172
233
1,546
4.360515
0.377682
0.055118
0.027559
0.031496
0.098425
0.098425
0
0
0
0
0
0.010943
0.231565
1,546
44
139
35.136364
0.844276
0.335058
0
0.08
0
0
0.12753
0
0
0
0
0
0
1
0.04
false
0
0.08
0
0.12
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
b068470f8ca662453890dee9ded5d2a25fb6fcdd
4,706
py
Python
guacozy_server/backend/api/utils.py
yinm8315/guacozy-django-react
99a8270cb660052d3b4868b7959a5750968d9cc3
[ "MIT" ]
121
2019-10-28T09:23:05.000Z
2022-03-19T00:30:36.000Z
guacozy_server/backend/api/utils.py
peppelinux/guacozy
ff4ca3fae8b9a5cb379a7a73d39f0d0ea8b6521c
[ "MIT" ]
43
2019-10-28T09:22:59.000Z
2022-03-18T23:01:25.000Z
guacozy_server/backend/api/utils.py
peppelinux/guacozy
ff4ca3fae8b9a5cb379a7a73d39f0d0ea8b6521c
[ "MIT" ]
44
2019-11-05T01:58:05.000Z
2022-03-30T08:05:18.000Z
import rules from backend.models import Folder def add_folder_to_tree_dictionary(folder, resulting_set, include_ancestors=False): """ Adds folder, folder's ancestors and folder's descendants Ancestors are needed to build the traverse path in tree view Descendants are needed because user has permissi...
36.765625
115
0.698683
626
4,706
5.028754
0.167732
0.05432
0.120076
0.063532
0.401842
0.327192
0.260801
0.241423
0.226811
0.203939
0
0
0.236507
4,706
127
116
37.055118
0.876148
0.379728
0
0.057692
0
0
0.023671
0.007647
0
0
0
0
0
1
0.096154
false
0
0.038462
0
0.192308
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
b06a64034b02fc50eab6da81b27b39ddfc4affcc
348
py
Python
web/services/device-service/src/app.py
fhgrings/match-io
0acb0b006ae8d8073f1d148e80275a568c2517ae
[ "MIT" ]
null
null
null
web/services/device-service/src/app.py
fhgrings/match-io
0acb0b006ae8d8073f1d148e80275a568c2517ae
[ "MIT" ]
null
null
null
web/services/device-service/src/app.py
fhgrings/match-io
0acb0b006ae8d8073f1d148e80275a568c2517ae
[ "MIT" ]
null
null
null
from flask import Flask from flask_cors import CORS from src.ext import configuration def minimal_app(**config): app = Flask(__name__) configuration.init_app(app, **config) CORS(app) return app def create_app(**config): app = minimal_app(**config) configuration.load_extension...
19.333333
42
0.672414
44
348
5.090909
0.386364
0.160714
0.142857
0
0
0
0
0
0
0
0
0
0.241379
348
18
43
19.333333
0.848485
0
0
0.166667
0
0
0
0
0
0
0
0
0
1
0.166667
false
0
0.25
0
0.583333
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
b06d15947556e9e4b04c29a89022d993e3d2bccf
4,357
py
Python
src/face_utils/save_figure.py
hankyul2/FaceDA
73006327df3668923d4206f81d4976ca1240329d
[ "Apache-2.0" ]
null
null
null
src/face_utils/save_figure.py
hankyul2/FaceDA
73006327df3668923d4206f81d4976ca1240329d
[ "Apache-2.0" ]
null
null
null
src/face_utils/save_figure.py
hankyul2/FaceDA
73006327df3668923d4206f81d4976ca1240329d
[ "Apache-2.0" ]
null
null
null
import os import numpy as np import matplotlib.pyplot as plt from PIL import Image import albumentations as A from pathlib import Path import torch from torch import nn from src_backup.cdan import get_model from src.backbone.iresnet import get_arcface_backbone class MyModel(nn.Module): def __init__(self, backbo...
36.008264
116
0.627037
593
4,357
4.448567
0.261383
0.026535
0.026535
0.031842
0.191433
0.144807
0.134193
0.112206
0.075815
0.075815
0
0.036665
0.223778
4,357
121
116
36.008264
0.743347
0
0
0.221154
0
0
0.078935
0.018128
0
0
0
0
0
1
0.076923
false
0
0.096154
0
0.230769
0.019231
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b070934d7222c882ff718596c5213477b01b49fc
2,481
py
Python
tests/unit/tests_standard_lib/tests_sample_generation/test_time_parser.py
monishshah18/pytest-splunk-addon
1600f2c7d30ec304e9855642e63511780556b406
[ "Apache-2.0" ]
39
2020-06-09T17:37:21.000Z
2022-02-08T01:57:35.000Z
tests/unit/tests_standard_lib/tests_sample_generation/test_time_parser.py
monishshah18/pytest-splunk-addon
1600f2c7d30ec304e9855642e63511780556b406
[ "Apache-2.0" ]
372
2020-04-15T13:55:09.000Z
2022-03-31T17:14:56.000Z
tests/unit/tests_standard_lib/tests_sample_generation/test_time_parser.py
isabella232/pytest-splunk-addon
5e6ae2b47df7a1feb6f358bbbd1f02197b5024f6
[ "Apache-2.0" ]
22
2020-05-06T10:43:45.000Z
2022-03-16T15:50:08.000Z
import pytest from datetime import datetime from freezegun import freeze_time from pytest_splunk_addon.standard_lib.sample_generation.time_parser import ( time_parse, ) @pytest.fixture(scope="session") def tp(): return time_parse() def generate_parameters(): result = [] for s in ("s", "sec", "secs"...
37.590909
80
0.523176
343
2,481
3.71137
0.323615
0.150825
0.091909
0.098979
0.115475
0.089552
0.089552
0
0
0
0
0.150707
0.25917
2,481
65
81
38.169231
0.541893
0
0
0
0
0
0.116888
0.010077
0
0
0
0
0.035088
1
0.070175
false
0
0.070175
0.017544
0.192982
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
c660dc00601aa00fc2df39ad1285ba2cbf2bab57
3,426
py
Python
recbole/utils/inferred_lm.py
ghazalehnt/RecBole
f1219847005e2c8d72b8c3cd5c49a138fe83276d
[ "MIT" ]
null
null
null
recbole/utils/inferred_lm.py
ghazalehnt/RecBole
f1219847005e2c8d72b8c3cd5c49a138fe83276d
[ "MIT" ]
null
null
null
recbole/utils/inferred_lm.py
ghazalehnt/RecBole
f1219847005e2c8d72b8c3cd5c49a138fe83276d
[ "MIT" ]
null
null
null
import time import torch from recbole.config import Config from recbole.utils import get_model, init_seed import gensim import gensim.downloader as api from recbole.data import create_dataset, data_preparation import numpy as np URL_FIELD = "item_url" class ItemLM: def __init__(self, checkpoint_file, model_name,...
40.305882
140
0.613543
473
3,426
4.150106
0.264271
0.042792
0.020377
0.028018
0.057565
0.042282
0.030565
0.030565
0.030565
0.030565
0
0.008495
0.278459
3,426
84
141
40.785714
0.785599
0.011384
0
0.054054
0
0
0.047858
0.006499
0
0
0
0
0
1
0.027027
false
0.013514
0.108108
0.013514
0.162162
0.067568
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
c6690d881a99354cf92a13a7b705df947e112eb1
5,009
py
Python
menu.py
kokohi28/stock-prediction
82d18cbb6366d522a01252e0cdc6eafa9fffea6d
[ "MIT" ]
11
2020-06-15T12:38:57.000Z
2021-12-08T13:34:28.000Z
menu.py
kokohi28/stock-prediction
82d18cbb6366d522a01252e0cdc6eafa9fffea6d
[ "MIT" ]
null
null
null
menu.py
kokohi28/stock-prediction
82d18cbb6366d522a01252e0cdc6eafa9fffea6d
[ "MIT" ]
5
2020-12-17T16:58:36.000Z
2022-02-08T09:29:28.000Z
import os import const as CONST from datetime import datetime # Const MENU_ROOT = 0 MENU_SPECIFY_DATE = 1 MENU_SPECIFY_PERCENT_TRAINED = 2 currMenu = MENU_ROOT stockList = ['AAPL', '^DJI', '^HSI', '^GSPC'] def welcomeMessage(): print('##############################################################################'...
27.075676
89
0.502296
467
5,009
5.342612
0.301927
0.033667
0.042084
0.050501
0.340681
0.291784
0.228457
0.228457
0.202806
0.132265
0
0.027151
0.345578
5,009
185
90
27.075676
0.733984
0.023558
0
0.503356
0
0
0.287851
0.036263
0
0
0
0
0
1
0.060403
false
0.013423
0.020134
0
0.194631
0.201342
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
c6692746527064fc0f46c5e36e6e97f09870ae4f
3,410
py
Python
demo/infinity/triton_client.py
dumpmemory/transformer-deploy
36993d8dd53c7440e49dce36c332fa4cc08cf9fb
[ "Apache-2.0" ]
698
2021-11-22T17:42:40.000Z
2022-03-31T11:16:08.000Z
demo/infinity/triton_client.py
dumpmemory/transformer-deploy
36993d8dd53c7440e49dce36c332fa4cc08cf9fb
[ "Apache-2.0" ]
38
2021-11-23T13:45:04.000Z
2022-03-31T10:36:45.000Z
demo/infinity/triton_client.py
dumpmemory/transformer-deploy
36993d8dd53c7440e49dce36c332fa4cc08cf9fb
[ "Apache-2.0" ]
58
2021-11-24T11:46:21.000Z
2022-03-29T08:45:16.000Z
# Copyright 2022, Lefebvre Dalloz Services # # 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 ag...
46.712329
117
0.72346
458
3,410
5.20524
0.469432
0.045302
0.058725
0.037752
0.171141
0.171141
0.171141
0.171141
0.118289
0.118289
0
0.017248
0.183871
3,410
72
118
47.361111
0.839382
0.202346
0
0.085106
0
0
0.280059
0.012579
0
0
0
0
0.021277
1
0
false
0
0.085106
0
0.085106
0.06383
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
c66969c34948d04bc70f6e069bd8dabc5e27f5b6
2,361
py
Python
mf/knnbased.py
waashk/extended-pipeline
1f8cdfcd1530a9dd502ea0d76d89b5010d19daf7
[ "MIT" ]
null
null
null
mf/knnbased.py
waashk/extended-pipeline
1f8cdfcd1530a9dd502ea0d76d89b5010d19daf7
[ "MIT" ]
null
null
null
mf/knnbased.py
waashk/extended-pipeline
1f8cdfcd1530a9dd502ea0d76d89b5010d19daf7
[ "MIT" ]
null
null
null
import numpy as np from tqdm import tqdm from scipy.sparse import csr_matrix, hstack, vstack from sklearn.neighbors import NearestNeighbors class MFKnn(object): """ Implementation of """ def __init__(self, metric, k): self.k = k self.metric = metric def fit(self, X, y): # self.X_train = X self.y_tr...
23.147059
105
0.647183
386
2,361
3.826425
0.243523
0.021666
0.033852
0.037915
0.280298
0.212593
0.131347
0.131347
0.131347
0.131347
0
0.020419
0.191021
2,361
101
106
23.376238
0.75288
0.047861
0
0.065574
0
0
0.00764
0
0
0
0
0
0
1
0.065574
false
0
0.065574
0.016393
0.196721
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
c66bd961fbf8bcb3556ef3c4fc46854f04ab9b95
581
py
Python
general-practice/Exercises solved/codingbat/Warmup2/string_match.py
lugabrielbueno/Projeto
f012c5bb9ce6f6d7c9e8196cc7986127dba3eba0
[ "MIT" ]
null
null
null
general-practice/Exercises solved/codingbat/Warmup2/string_match.py
lugabrielbueno/Projeto
f012c5bb9ce6f6d7c9e8196cc7986127dba3eba0
[ "MIT" ]
null
null
null
general-practice/Exercises solved/codingbat/Warmup2/string_match.py
lugabrielbueno/Projeto
f012c5bb9ce6f6d7c9e8196cc7986127dba3eba0
[ "MIT" ]
null
null
null
#Given 2 strings, a and b, return the number of the positions where they contain the same length 2 substring. So "xxcaazz" and "xxbaaz" yields 3, since the "xx", "aa", and "az" substrings appear in the same place in both strings. #string_match('xxcaazz', 'xxbaaz') → 3 #string_match('abc', 'abc') → 2 #string_match('abc...
34.176471
229
0.593804
105
581
3.27619
0.447619
0.127907
0.034884
0.023256
0
0
0
0
0
0
0
0.029954
0.253012
581
16
230
36.3125
0.75576
0.55938
0
0
0
0
0
0
0
0
0
0
0
1
0.1
false
0
0
0
0.2
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
c66f914aa66ae752fa396361357e16cd39293db5
10,951
py
Python
courses/views.py
mdavoodi/konkourse-python
50f2904e7bbb31f00c4dd66fb55cd644ea3c4eee
[ "MIT" ]
4
2015-06-23T22:17:50.000Z
2019-01-17T21:32:02.000Z
courses/views.py
mdavoodi/konkourse-python
50f2904e7bbb31f00c4dd66fb55cd644ea3c4eee
[ "MIT" ]
null
null
null
courses/views.py
mdavoodi/konkourse-python
50f2904e7bbb31f00c4dd66fb55cd644ea3c4eee
[ "MIT" ]
null
null
null
from django.shortcuts import render, redirect, render_to_response from django.template.context import RequestContext from account.views import login from models import Course from website.views import index from forms import CourseForm, CourseInitialForm from account.util import createImage from django.core.context_pro...
37.892734
116
0.649621
1,250
10,951
5.504
0.1512
0.052326
0.050145
0.028779
0.440698
0.408866
0.334884
0.257703
0.20814
0.184157
0
0.00303
0.246462
10,951
288
117
38.024306
0.830708
0
0
0.320158
0
0
0.07287
0.027303
0
0
0
0
0
1
0.067194
false
0
0.083004
0
0.29249
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
c67157381752f709d6b39cd4632427d8936411ad
2,701
py
Python
rx/operators/observable/delaywithselector.py
yutiansut/RxPY
c3bbba77f9ebd7706c949141725e220096deabd4
[ "ECL-2.0", "Apache-2.0" ]
1
2018-11-16T09:07:13.000Z
2018-11-16T09:07:13.000Z
rx/operators/observable/delaywithselector.py
yutiansut/RxPY
c3bbba77f9ebd7706c949141725e220096deabd4
[ "ECL-2.0", "Apache-2.0" ]
null
null
null
rx/operators/observable/delaywithselector.py
yutiansut/RxPY
c3bbba77f9ebd7706c949141725e220096deabd4
[ "ECL-2.0", "Apache-2.0" ]
1
2020-05-08T08:23:08.000Z
2020-05-08T08:23:08.000Z
from rx.core import ObservableBase, AnonymousObservable, typing from rx.disposables import CompositeDisposable, \ SingleAssignmentDisposable, SerialDisposable def delay_with_selector(self, subscription_delay=None, delay_duration_mapper=None) -> ObservableBase: """Time shifts the observ...
32.154762
108
0.585339
265
2,701
5.8
0.301887
0.045543
0.039037
0.03123
0.178269
0.106701
0.106701
0.106701
0.065062
0
0
0.00734
0.344317
2,701
83
109
32.542169
0.860531
0.226953
0
0.215686
0
0
0
0
0
0
0
0
0
1
0.156863
false
0
0.039216
0
0.254902
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
c6715e41c59947802aabe44b258270730dfcbb52
719
py
Python
w2/palindrome.py
connorw72/connorapcsptri3
2e885644ed2a8d478e5ce193f94b02ad03c6e6b3
[ "MIT" ]
null
null
null
w2/palindrome.py
connorw72/connorapcsptri3
2e885644ed2a8d478e5ce193f94b02ad03c6e6b3
[ "MIT" ]
3
2022-03-14T21:10:05.000Z
2022-03-28T21:11:17.000Z
w2/palindrome.py
connorw72/connorapcsptri3
2e885644ed2a8d478e5ce193f94b02ad03c6e6b3
[ "MIT" ]
2
2022-03-10T06:11:11.000Z
2022-03-11T06:11:11.000Z
class Palindrome: def __init__(self, test): self.test = test def __call__(self): test_strip = list([n for n in self.test if n.isalpha() or n.isnumeric()]) self.test = "".join(test_strip) self.test = self.test.lower() #Test to see if the phrase/word is a palindrome ...
31.26087
81
0.585535
100
719
4.09
0.47
0.176039
0.08802
0.117359
0
0
0
0
0
0
0
0.001965
0.292072
719
23
82
31.26087
0.801572
0.126565
0
0
0
0
0.137161
0
0
0
0
0
0
1
0.157895
false
0
0
0
0.315789
0.105263
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
c672a5daf5acf1852874d76a788a6d4edc536ca3
3,890
py
Python
sat-competition-2018/xof-state/sha3-xof.py
cipherboy/sat
65cbcebf03ffdfd64d49359ebb1d654c73e2c720
[ "MIT" ]
1
2019-01-19T23:04:50.000Z
2019-01-19T23:04:50.000Z
sat-competition-2018/xof-state/sha3-xof.py
cipherboy/sat
65cbcebf03ffdfd64d49359ebb1d654c73e2c720
[ "MIT" ]
null
null
null
sat-competition-2018/xof-state/sha3-xof.py
cipherboy/sat
65cbcebf03ffdfd64d49359ebb1d654c73e2c720
[ "MIT" ]
null
null
null
#!/usr/bin/env python3 import hash_framework as hf hf.config.model_dir = "/home/cipherboy/GitHub/sat/sat-competition-2018/models" import time, sys, os, random run = False release = False if '--run' in sys.argv: run = True if '--release' in sys.argv: release = True if '-h' in sys.argv or '--help' in sys.argv:...
28.814815
103
0.554756
607
3,890
3.453048
0.253707
0.033397
0.038168
0.009542
0.191317
0.133111
0.120706
0.067748
0.025763
0.025763
0
0.030699
0.271465
3,890
134
104
29.029851
0.708892
0.005398
0
0.163636
0
0.009091
0.184074
0.013961
0
0
0
0
0
1
0.036364
false
0.009091
0.018182
0
0.063636
0.145455
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
c6739210f1e8d51ce9d34502997456a48bfc0ddd
3,357
py
Python
methinks/db.py
andreasgrv/methinks
5c65fdb84e35b8082ee35963431a352e06f4af44
[ "BSD-3-Clause" ]
null
null
null
methinks/db.py
andreasgrv/methinks
5c65fdb84e35b8082ee35963431a352e06f4af44
[ "BSD-3-Clause" ]
null
null
null
methinks/db.py
andreasgrv/methinks
5c65fdb84e35b8082ee35963431a352e06f4af44
[ "BSD-3-Clause" ]
null
null
null
import os import datetime import xxhash import json from flask_sqlalchemy import SQLAlchemy from methinks.utils import str_to_date from methinks.config import get_default_conf db = SQLAlchemy() class Entry(db.Model): __tablename__ = 'entry' id = db.Column(db.Integer, primary_key=True) hexid = db.Colum...
31.373832
89
0.593983
416
3,357
4.661058
0.254808
0.077359
0.030944
0.027849
0.104177
0.104177
0.104177
0.104177
0.104177
0.052604
0
0.001662
0.282991
3,357
106
90
31.669811
0.803905
0
0
0.151163
0
0
0.048853
0
0
0
0
0
0.011628
1
0.127907
false
0
0.081395
0.05814
0.406977
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
c6742b09c8b11bbe5babccf11451efdfb75310ee
2,797
py
Python
dense_estimation/points_estimation.py
zouzhenhong98/kitti-tools
30b7d5c799ca2a44fe88522f6d46ad2a53c61d53
[ "MIT" ]
7
2020-01-03T13:05:36.000Z
2021-08-03T07:51:43.000Z
dense_estimation/points_estimation.py
zouzhenhong98/kitti-tools
30b7d5c799ca2a44fe88522f6d46ad2a53c61d53
[ "MIT" ]
null
null
null
dense_estimation/points_estimation.py
zouzhenhong98/kitti-tools
30b7d5c799ca2a44fe88522f6d46ad2a53c61d53
[ "MIT" ]
3
2020-07-07T03:35:06.000Z
2021-07-21T11:40:38.000Z
''' point clouds estimation: transfer sparse map to dense map, work for both depth and reflectance. ''' import sys sys.path.append("..") from utils import data_provider from utils import velo_2_cam import numpy as np # fetch image and point clouds: coordinates and reflectance def rawData(pc_path_, img_path_): ...
35.405063
111
0.598498
354
2,797
4.49435
0.333333
0.018856
0.015085
0.028284
0.099937
0.049026
0.049026
0
0
0
0
0.031778
0.279943
2,797
79
111
35.405063
0.758193
0.231677
0
0
0
0
0.137412
0
0
0
0
0
0.022222
1
0.066667
false
0.022222
0.088889
0
0.2
0.111111
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
c6770cd7813960cae894c7947e2f76b45e5169f4
1,014
py
Python
tests/run_compiler.py
yshrdbrn/ogle
529337203b1bd3ec66c08f4ed153dba5fc8349a1
[ "MIT" ]
null
null
null
tests/run_compiler.py
yshrdbrn/ogle
529337203b1bd3ec66c08f4ed153dba5fc8349a1
[ "MIT" ]
null
null
null
tests/run_compiler.py
yshrdbrn/ogle
529337203b1bd3ec66c08f4ed153dba5fc8349a1
[ "MIT" ]
null
null
null
from ogle.code_generator.code_generator import CodeGenerator from ogle.lexer.lexer import Lexer from ogle.parser.parser import Parser from ogle.semantic_analyzer.semantic_analyzer import SemanticAnalyzer def _get_errors_warnings(all_errors): errors = [e for e in all_errors if 'Error' in e[1]] warnings = [e for...
36.214286
82
0.759369
134
1,014
5.522388
0.291045
0.172973
0.068919
0.101351
0.348649
0.348649
0.348649
0.3
0.3
0.3
0
0.002345
0.158777
1,014
27
83
37.555556
0.865182
0
0
0.416667
0
0
0.012821
0
0
0
0
0
0
1
0.125
false
0
0.166667
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
c678c38909ca5f9f3348fe7d0e9471e1720d3bee
817
py
Python
graph/dfs_dict_attempt2.py
automoto/python-code-golf
1a4e0b5984e64620637de9d80e82c6e89997f4af
[ "MIT" ]
null
null
null
graph/dfs_dict_attempt2.py
automoto/python-code-golf
1a4e0b5984e64620637de9d80e82c6e89997f4af
[ "MIT" ]
null
null
null
graph/dfs_dict_attempt2.py
automoto/python-code-golf
1a4e0b5984e64620637de9d80e82c6e89997f4af
[ "MIT" ]
null
null
null
# !depth first search !dfs !graph # dict of nodes as the key and sets for the edges(children) graph = {'A': set(['B', 'C', 'D']), 'B': set(['E', 'F']), 'C': set([]), 'D': set(['G', 'H']), 'E': set([]), 'F': set(['I', 'J']), 'G': set(['K']), 'H': set([]), 'I': set([]), 'J': set([]), 'K': ...
24.029412
63
0.597307
125
817
3.864
0.408
0.136646
0.066253
0
0
0
0
0
0
0
0
0
0.203182
817
34
63
24.029412
0.741935
0.405141
0
0
0
0
0.075472
0
0
0
0
0
0
1
0.05
false
0
0
0
0.05
0.05
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
c67973e1c48ecff18bf6a4fc82b259940ef31d3c
4,561
py
Python
tools/fastq_pair_names/fastq_pair_names.py
Neato-Nick/pico_galaxy
79666612a9ca2d335622bc282a4768bb43d91419
[ "MIT" ]
18
2015-06-09T13:57:09.000Z
2022-01-14T21:05:54.000Z
tools/fastq_pair_names/fastq_pair_names.py
Neato-Nick/pico_galaxy
79666612a9ca2d335622bc282a4768bb43d91419
[ "MIT" ]
34
2015-04-02T19:26:08.000Z
2021-06-17T18:59:24.000Z
tools/fastq_pair_names/fastq_pair_names.py
Neato-Nick/pico_galaxy
79666612a9ca2d335622bc282a4768bb43d91419
[ "MIT" ]
24
2015-02-25T13:40:19.000Z
2021-09-08T20:40:40.000Z
#!/usr/bin/env python """Extract paired read names from FASTQ file(s). The input file should be a valid FASTQ file(s), the output is two tabular files - the paired read names (without suffixes), and unpaired read names (including any unrecognised pair names). Note that the FASTQ variant is unimportant (Sanger, Solexa...
31.027211
86
0.611489
657
4,561
4.127854
0.302892
0.058997
0.033186
0.043142
0.347345
0.255162
0.185103
0.173304
0.141593
0.141593
0
0.045967
0.241614
4,561
146
87
31.239726
0.738075
0.232186
0
0.181818
0
0.040404
0.195396
0.061871
0
0
0
0
0.212121
1
0
false
0
0.050505
0
0.050505
0.030303
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
c6798f3695e83af119f05e4fdd4f14111d00889d
2,903
py
Python
code/05_speech_to_text/main_05_b_wake_word.py
padmalcom/AISpeechAssistant
b7501a23a8f513acb5043f3c7bb06df129bdc2cc
[ "Apache-2.0" ]
1
2021-09-08T09:21:16.000Z
2021-09-08T09:21:16.000Z
code/05_speech_to_text/main_05_b_wake_word.py
padmalcom/AISpeechAssistant
b7501a23a8f513acb5043f3c7bb06df129bdc2cc
[ "Apache-2.0" ]
null
null
null
code/05_speech_to_text/main_05_b_wake_word.py
padmalcom/AISpeechAssistant
b7501a23a8f513acb5043f3c7bb06df129bdc2cc
[ "Apache-2.0" ]
2
2022-02-06T09:54:40.000Z
2022-03-01T07:52:51.000Z
from loguru import logger import yaml import time import pyaudio import struct import os import sys from vosk import Model, SpkModel, KaldiRecognizer import json import text2numde from TTS import Voice import multiprocessing CONFIG_FILE = "config.yml" SAMPLE_RATE = 16000 FRAME_LENGTH = 512 class VoiceAssistant():...
27.130841
86
0.709955
356
2,903
5.679775
0.466292
0.04451
0.029674
0.012859
0
0
0
0
0
0
0
0.011638
0.171202
2,903
107
87
27.130841
0.828761
0.054426
0
0.02439
0
0
0.238964
0
0
0
0
0
0
1
0.02439
false
0
0.146341
0
0.182927
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
c6832c12d1f11f0fd4b7b74f990fd950eb68d5c6
2,506
py
Python
functions/formatString.py
Steve-Xyh/AutoAoxiang
a8f1abed0f17b967456b1fa539c0aae79dac1d01
[ "WTFPL" ]
7
2020-02-17T08:12:14.000Z
2021-12-29T09:41:35.000Z
functions/formatString.py
Steve-Xyh/AutoAoxiang
a8f1abed0f17b967456b1fa539c0aae79dac1d01
[ "WTFPL" ]
null
null
null
functions/formatString.py
Steve-Xyh/AutoAoxiang
a8f1abed0f17b967456b1fa539c0aae79dac1d01
[ "WTFPL" ]
1
2020-07-24T07:16:14.000Z
2020-07-24T07:16:14.000Z
#!/usr/bin/env python3 # -*- coding: utf-8 -*- import datetime import colorama colorama.init(autoreset=True) logData = { '所在位置': 'Location', '是否经停湖北': '否', '接触湖北籍人员': '否', '接触确诊疑似': '否', '今日体温': '37.2度以下', '有无疑似或异常': '无', '是否隔离': '否', } def log_line(dic: dict, color=True): ''' 中文...
25.571429
111
0.541899
322
2,506
4.164596
0.304348
0.03132
0.056674
0.080537
0.50261
0.50261
0.445936
0.430276
0.404922
0.404922
0
0.022283
0.265762
2,506
97
112
25.835052
0.706522
0.0834
0
0.383333
0
0
0.124271
0
0
0
0
0
0
1
0.066667
false
0
0.033333
0
0.166667
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
c6843679e999329dca1a8986c704607c2cb84a96
433
py
Python
2 - Automation tools with IP hiding techniques/checkValidJson.py
Phong940253/facebook-data-extraction
fa64680dcff900db4d852af06ff792ccf4d5be33
[ "MIT" ]
null
null
null
2 - Automation tools with IP hiding techniques/checkValidJson.py
Phong940253/facebook-data-extraction
fa64680dcff900db4d852af06ff792ccf4d5be33
[ "MIT" ]
null
null
null
2 - Automation tools with IP hiding techniques/checkValidJson.py
Phong940253/facebook-data-extraction
fa64680dcff900db4d852af06ff792ccf4d5be33
[ "MIT" ]
null
null
null
import json import glob groupPost = glob.glob("rawData/*/*/*.json") pagePost = glob.glob("rawData/*/*.json") groupPagePost = groupPost + pagePost def is_json(myjson): try: json.load(myjson) except ValueError as e: return False return True for postFile in groupPagePost: with open(pos...
19.681818
52
0.628176
55
433
4.909091
0.6
0.059259
0.111111
0.140741
0
0
0
0
0
0
0
0.003086
0.251732
433
21
53
20.619048
0.830247
0
0
0
0
0
0.092379
0
0
0
0
0
0
1
0.0625
false
0
0.125
0
0.3125
0.0625
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
c686c1dded95c4fb11f50e8f958330e48395c1cb
304
py
Python
34.PySimpleGUI.py
sarincr/GUI-With-Tkinter-using-Python
3b57fc4aeed9e4a3018fc940bafdb4160ec853fc
[ "MIT" ]
null
null
null
34.PySimpleGUI.py
sarincr/GUI-With-Tkinter-using-Python
3b57fc4aeed9e4a3018fc940bafdb4160ec853fc
[ "MIT" ]
null
null
null
34.PySimpleGUI.py
sarincr/GUI-With-Tkinter-using-Python
3b57fc4aeed9e4a3018fc940bafdb4160ec853fc
[ "MIT" ]
null
null
null
import PySimpleGUI as PySG lay = [ [PySG.Text("What's your name?")], [PySG.Input()], [PySG.Button('Ok')] ] wd = PySG.Window('Python Simple GUI', lay) event, values = wd.read() print('Hello', values[0]) wd.close()
21.714286
48
0.457237
33
304
4.212121
0.757576
0
0
0
0
0
0
0
0
0
0
0.005348
0.384868
304
13
49
23.384615
0.737968
0
0
0
0
0
0.134868
0
0
0
0
0
0
1
0
false
0
0.125
0
0.125
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
c688fe0af58ac798c7af0c9f68af25aff660071c
5,304
py
Python
models/ScrabbleGAN.py
iambhuvi/ScrabbleGAN
30dce26a1a103a0fd6ce7269d6ccdcaccb32fd3b
[ "MIT" ]
9
2021-02-02T06:31:32.000Z
2021-11-03T11:19:58.000Z
models/ScrabbleGAN.py
iambhuvi/ScrabbleGAN
30dce26a1a103a0fd6ce7269d6ccdcaccb32fd3b
[ "MIT" ]
1
2021-12-01T12:13:14.000Z
2021-12-01T12:13:14.000Z
models/ScrabbleGAN.py
iambhuvi/ScrabbleGAN
30dce26a1a103a0fd6ce7269d6ccdcaccb32fd3b
[ "MIT" ]
6
2021-02-02T06:31:49.000Z
2022-01-21T14:33:43.000Z
import torch import torch.nn as nn import torch.nn.functional as F import torch.utils.data from models.model_utils import BigGAN as BGAN from utils.data_utils import * import pandas as pd class Recognizer(nn.Module): def __init__(self, cfg): super(Recognizer, self).__init__() input_size = 1 ...
37.617021
112
0.572587
784
5,304
3.664541
0.202806
0.034807
0.063348
0.04873
0.350505
0.269405
0.204664
0.204664
0.183084
0.132962
0
0.020985
0.299208
5,304
140
113
37.885714
0.751951
0.061086
0
0.277778
0
0
0.00503
0
0
0
0
0
0
1
0.046296
false
0
0.064815
0
0.148148
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
c689b60ebca7bfda5e5401b93bdc1651fc7b24be
2,745
py
Python
jobbing/controllers/providers_controller.py
davidall-amdocs/jobbing
b13311da07606366dfbe2eb737483a5820038557
[ "Apache-2.0" ]
null
null
null
jobbing/controllers/providers_controller.py
davidall-amdocs/jobbing
b13311da07606366dfbe2eb737483a5820038557
[ "Apache-2.0" ]
1
2021-06-10T03:34:07.000Z
2021-06-10T03:34:07.000Z
jobbing/controllers/providers_controller.py
davidall-amdocs/jobbing
b13311da07606366dfbe2eb737483a5820038557
[ "Apache-2.0" ]
1
2022-02-14T15:51:01.000Z
2022-02-14T15:51:01.000Z
from flask import abort from jobbing.models.user_profile import UserProfile # noqa: E501 from jobbing.models.service import Service # noqa: E501 from jobbing.DBModels import Profile as DBProfile from jobbing.DBModels import Service as DBService from jobbing.login import token_required @token_required def get_provi...
34.746835
82
0.647723
315
2,745
5.368254
0.285714
0.06505
0.028386
0.022472
0.107037
0.056771
0
0
0
0
0
0.010687
0.284153
2,745
78
83
35.192308
0.849873
0.135155
0
0.037736
0
0
0
0
0
0
0
0
0
1
0.037736
false
0
0.113208
0
0.188679
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
c68c3919e177e8d1de7b30c2a650b62b74c47975
6,811
py
Python
bin/extract_bcs.py
dmaticzka/bctools
e4733b1f59a151f8158a8173a3cde48a5d119bc2
[ "Apache-2.0" ]
null
null
null
bin/extract_bcs.py
dmaticzka/bctools
e4733b1f59a151f8158a8173a3cde48a5d119bc2
[ "Apache-2.0" ]
3
2016-04-24T14:26:17.000Z
2017-04-28T15:17:20.000Z
bin/extract_bcs.py
dmaticzka/bctools
e4733b1f59a151f8158a8173a3cde48a5d119bc2
[ "Apache-2.0" ]
2
2016-05-06T03:57:25.000Z
2018-11-06T10:57:32.000Z
#!/usr/bin/env python import argparse import logging import re from sys import stdout from Bio.SeqIO.QualityIO import FastqGeneralIterator # avoid ugly python IOError when stdout output is piped into another program # and then truncated (such as piping to head) from signal import signal, SIGPIPE, SIG_DFL signal(SIGPIP...
39.143678
198
0.707238
959
6,811
4.895725
0.241919
0.03983
0.028967
0.017891
0.204899
0.161022
0.119915
0.094782
0.072417
0.059638
0
0.002646
0.167817
6,811
173
199
39.369942
0.825688
0.12377
0
0.227941
0
0.014706
0.322293
0.004203
0
0
0
0
0
1
0
false
0
0.044118
0
0.044118
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
c68e39b0e1053cfb768407c21209e2d2583bacc2
1,226
py
Python
main.py
pranavbaburaj/sh
dc0da9e10e7935310ae40d350c1897fcd65bce8f
[ "MIT" ]
4
2021-01-30T12:25:21.000Z
2022-03-13T07:23:19.000Z
main.py
pranavbaburaj/sh
dc0da9e10e7935310ae40d350c1897fcd65bce8f
[ "MIT" ]
3
2021-02-26T13:11:17.000Z
2021-06-04T17:26:05.000Z
main.py
pranavbaburaj/sh
dc0da9e10e7935310ae40d350c1897fcd65bce8f
[ "MIT" ]
1
2021-02-08T10:18:29.000Z
2021-02-08T10:18:29.000Z
import pyfiglet as figlet import click as click from project import Project, ApplicationRunner # The application package manager # get from package import PackageManager # print out the application name def print_app_name(app_name): figlet_object = figlet.Figlet(font='slant') return figlet_object...
24.52
69
0.693312
157
1,226
5.216561
0.312102
0.094017
0.065934
0.053724
0
0
0
0
0
0
0
0
0.212887
1,226
50
70
24.52
0.848705
0.170473
0
0
0
0
0.070907
0
0
0
0
0
0
1
0.178571
false
0
0.142857
0
0.357143
0.107143
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
c6904f6da38987f613861eec004342d5edfec9c2
1,339
py
Python
src/21.py
peter-hunt/project-euler-solution
ce5be80043e892e3a95604bd5ebec9dc88c7c037
[ "MIT" ]
null
null
null
src/21.py
peter-hunt/project-euler-solution
ce5be80043e892e3a95604bd5ebec9dc88c7c037
[ "MIT" ]
null
null
null
src/21.py
peter-hunt/project-euler-solution
ce5be80043e892e3a95604bd5ebec9dc88c7c037
[ "MIT" ]
null
null
null
""" Amicable numbers Let d(n) be defined as the sum of proper divisors of n (numbers less than n which divide evenly into n). If d(a) = b and d(b) = a, where a ≠ b, then a and b are an amicable pair and each of a and b are called amicable numbers. For example, the proper divisors of 220 are 1, 2, 4, 5, 10, 11, 20, 22...
21.596774
79
0.551158
203
1,339
3.600985
0.389163
0.049248
0.065663
0.021888
0.032832
0
0
0
0
0
0
0.075145
0.353996
1,339
61
80
21.95082
0.768786
0.38835
0
0.2
0
0
0
0
0
0
0
0
0
1
0.1
false
0.033333
0.033333
0
0.2
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