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
b5f0389774cedeaa041026bfccf255de23607efa
3,560
py
Python
app/profiles/schemas/update.py
MrPeker/acikkaynak-service
21c3f2faaa84342d2fa95709293bc84d1e2a23ae
[ "Apache-2.0" ]
5
2021-02-28T22:29:13.000Z
2021-11-29T00:24:28.000Z
app/profiles/schemas/update.py
MrPeker/acikkaynak-service
21c3f2faaa84342d2fa95709293bc84d1e2a23ae
[ "Apache-2.0" ]
null
null
null
app/profiles/schemas/update.py
MrPeker/acikkaynak-service
21c3f2faaa84342d2fa95709293bc84d1e2a23ae
[ "Apache-2.0" ]
3
2021-03-03T19:56:30.000Z
2021-03-06T22:10:35.000Z
import graphene from app.common.library import graphql from app.common.models import City from ..models import Profile from .queries import ProfileNode # queries class Query(graphene.ObjectType): pass # mutations class ProfileUpdateMutation(graphene.Mutation): Output = ProfileNode class Arguments: ...
31.504425
85
0.601404
387
3,560
5.369509
0.26615
0.057748
0.040423
0.024543
0.133782
0.084697
0.084697
0.030799
0
0
0
0.000804
0.301124
3,560
112
86
31.785714
0.834405
0.09382
0
0.026316
0
0
0.054121
0
0
0
0
0.008929
0
1
0.013158
false
0.026316
0.065789
0
0.171053
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b5f230d3037e9e1528cdc347b55ec3805c78a481
3,352
py
Python
scripts/plot_fits.py
trichter/robust_earthquake_spectra
ef816e30944293e27c0d5da4d31ec2184e6d187b
[ "MIT" ]
8
2021-07-23T13:01:29.000Z
2022-03-27T17:57:36.000Z
scripts/plot_fits.py
trichter/robust_earthquake_spectra
ef816e30944293e27c0d5da4d31ec2184e6d187b
[ "MIT" ]
null
null
null
scripts/plot_fits.py
trichter/robust_earthquake_spectra
ef816e30944293e27c0d5da4d31ec2184e6d187b
[ "MIT" ]
null
null
null
# Copyright 2021 Tom Eulenfeld, MIT license import matplotlib as mpl import matplotlib.gridspec as gridspec import matplotlib.pyplot as plt import numpy as np import pickle from qopen.core import get_pair, Gsmooth from qopen.rt import G as G_func def set_gridlabels(ax, i, n, N, xlabel='frequency (Hz)', ylabel=None):...
34.204082
77
0.568019
524
3,352
3.545802
0.370229
0.022605
0.008073
0.006459
0.057589
0.025834
0.025834
0.025834
0.025834
0
0
0.062016
0.268795
3,352
97
78
34.556701
0.696042
0.012232
0
0
0
0
0.0822
0.025688
0
0
0
0
0
1
0.05
false
0
0.0875
0.0125
0.1625
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b5f407423805cba0b85dc8b97c1c27b8ba3da9b6
225
py
Python
answers/Aryan Goyal/Day 10/Que 1.py
arc03/30-DaysOfCode-March-2021
6d6e11bf70280a578113f163352fa4fa8408baf6
[ "MIT" ]
22
2021-03-16T14:07:47.000Z
2021-08-13T08:52:50.000Z
answers/Aryan Goyal/Day 10/Que 1.py
arc03/30-DaysOfCode-March-2021
6d6e11bf70280a578113f163352fa4fa8408baf6
[ "MIT" ]
174
2021-03-16T21:16:40.000Z
2021-06-12T05:19:51.000Z
answers/Aryan Goyal/Day 10/Que 1.py
arc03/30-DaysOfCode-March-2021
6d6e11bf70280a578113f163352fa4fa8408baf6
[ "MIT" ]
135
2021-03-16T16:47:12.000Z
2021-06-27T14:22:38.000Z
def pangram(s): a = "abcdefghijklmnopqrstuvwxyz" for i in a: if i not in s.lower(): return False return True # main string1 = input() if(pangram(string1) == True): print("Yes") else: print("No")
17.307692
35
0.6
31
225
4.354839
0.677419
0
0
0
0
0
0
0
0
0
0
0.012048
0.262222
225
12
36
18.75
0.801205
0.017778
0
0
0
0
0.141553
0.118721
0
0
0
0
0
1
0.090909
false
0
0
0
0.272727
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
b5f8afd3209dc9c313d59f605ef9e611cf525951
9,348
py
Python
tests/test_reliable_redis_backend.py
thread/django-lightweight-queue
2c67eb13a454fa1a02f8445c26915b6e9261fdad
[ "BSD-3-Clause" ]
23
2015-04-29T04:47:02.000Z
2022-03-11T12:43:01.000Z
tests/test_reliable_redis_backend.py
thread/django-lightweight-queue
2c67eb13a454fa1a02f8445c26915b6e9261fdad
[ "BSD-3-Clause" ]
23
2015-02-27T14:30:47.000Z
2021-12-02T14:18:34.000Z
tests/test_reliable_redis_backend.py
thread/django-lightweight-queue
2c67eb13a454fa1a02f8445c26915b6e9261fdad
[ "BSD-3-Clause" ]
1
2015-08-18T12:27:08.000Z
2015-08-18T12:27:08.000Z
import datetime import unittest import contextlib import unittest.mock from typing import Any, Dict, Tuple, Mapping, Iterator, Optional import fakeredis from django_lightweight_queue.job import Job from django_lightweight_queue.types import QueueName from django_lightweight_queue.backends.reliable_redis import ( R...
28.5
81
0.578947
1,009
9,348
5.234886
0.14668
0.081219
0.056797
0.068345
0.68989
0.6649
0.641992
0.634419
0.611132
0.593715
0
0.010722
0.321566
9,348
327
82
28.587156
0.822138
0.006846
0
0.576471
0
0
0.147769
0.010886
0
0
0
0
0.109804
1
0.047059
false
0
0.043137
0
0.109804
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b5f91ae2a0e4966e6263d4fa5ec3616c068ac79a
653
py
Python
src/waldur_slurm/migrations/0019_fill_allocation_user_usage.py
geant-multicloud/MCMS-mastermind
81333180f5e56a0bc88d7dad448505448e01f24e
[ "MIT" ]
26
2017-10-18T13:49:58.000Z
2021-09-19T04:44:09.000Z
src/waldur_slurm/migrations/0019_fill_allocation_user_usage.py
geant-multicloud/MCMS-mastermind
81333180f5e56a0bc88d7dad448505448e01f24e
[ "MIT" ]
14
2018-12-10T14:14:51.000Z
2021-06-07T10:33:39.000Z
src/waldur_slurm/migrations/0019_fill_allocation_user_usage.py
geant-multicloud/MCMS-mastermind
81333180f5e56a0bc88d7dad448505448e01f24e
[ "MIT" ]
32
2017-09-24T03:10:45.000Z
2021-10-16T16:41:09.000Z
from django.db import migrations def fill_allocation_user_usage(apps, schema_editor): AllocationUserUsage = apps.get_model('waldur_slurm', 'AllocationUserUsage') for item in AllocationUserUsage.objects.all(): item.allocation = item.allocation_usage.allocation item.year = item.allocation_usage...
28.391304
79
0.715161
70
653
6.414286
0.5
0.124722
0.126949
0.10245
0
0
0
0
0
0
0
0.007491
0.182236
653
22
80
29.681818
0.833333
0
0
0
0
0
0.140888
0.045942
0
0
0
0
0
1
0.066667
false
0
0.066667
0
0.333333
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
b5ffeb36473c0df68ff9596c309080a9ed5b0766
4,584
py
Python
environments/env_locust.py
jwallnoefer/projectivesimulation
b8f7b3d7d492b5d5f6df7f9f0802bead33c946ca
[ "Apache-2.0" ]
14
2018-02-13T17:39:58.000Z
2021-07-06T18:09:28.000Z
environments/env_locust.py
jwallnoefer/projectivesimulation
b8f7b3d7d492b5d5f6df7f9f0802bead33c946ca
[ "Apache-2.0" ]
null
null
null
environments/env_locust.py
jwallnoefer/projectivesimulation
b8f7b3d7d492b5d5f6df7f9f0802bead33c946ca
[ "Apache-2.0" ]
8
2018-03-22T04:12:31.000Z
2021-01-31T19:14:28.000Z
# -*- coding: utf-8 -*- """ Copyright 2018 Alexey Melnikov and Katja Ried. Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. Please acknowledge the authors when re-using this code and maintain this notice intact. Code written by Katja Ried...
49.290323
128
0.695681
676
4,584
4.594675
0.338757
0.057952
0.019317
0.017708
0.191565
0.140373
0.08886
0.08886
0.08886
0.073406
0
0.021407
0.215314
4,584
92
129
49.826087
0.842091
0.506545
0
0
0
0
0
0
0
0
0
0
0
1
0.175
false
0
0.025
0
0.25
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
bd0162bf0a28c31d37370edf04366759674e96cb
1,174
py
Python
masktools/superskims/slit.py
adwasser/masktools
c96c8f375f0e94ee2791466d0ce6d31007f58022
[ "MIT" ]
null
null
null
masktools/superskims/slit.py
adwasser/masktools
c96c8f375f0e94ee2791466d0ce6d31007f58022
[ "MIT" ]
null
null
null
masktools/superskims/slit.py
adwasser/masktools
c96c8f375f0e94ee2791466d0ce6d31007f58022
[ "MIT" ]
null
null
null
from __future__ import (absolute_import, division, print_function, unicode_literals) class Slit: def __init__(self, x, y, length, width, pa, name): ''' Representation of a slit in a mask. Coordinates are relative to the mask, so that the x-axis is along the lon...
39.133333
98
0.581772
168
1,174
3.964286
0.422619
0.066066
0.033033
0.042042
0
0
0
0
0
0
0
0.014851
0.311755
1,174
29
99
40.482759
0.809406
0.457411
0
0
0
0.076923
0.120075
0
0
0
0
0
0
1
0.153846
false
0
0.076923
0
0.384615
0.076923
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
bd0183d07de9ad7a1f13f37bb28f41e2ff5b5a7b
1,940
py
Python
gemmforge/instructions/builders/alloctor_builder.py
ravil-mobile/gemmforge
6381584c2d1ce77eaa938de02bc4f130f19cb2e4
[ "MIT" ]
null
null
null
gemmforge/instructions/builders/alloctor_builder.py
ravil-mobile/gemmforge
6381584c2d1ce77eaa938de02bc4f130f19cb2e4
[ "MIT" ]
2
2021-02-01T16:31:22.000Z
2021-05-05T13:44:43.000Z
gemmforge/instructions/builders/alloctor_builder.py
ravil-mobile/gemmforge
6381584c2d1ce77eaa938de02bc4f130f19cb2e4
[ "MIT" ]
null
null
null
from .abstract_builder import AbstractBuilder from gemmforge.symbol_table import SymbolType, Symbol from gemmforge.basic_types import RegMemObject, ShrMemObject from gemmforge.instructions import RegisterAlloc, ShrMemAlloc from gemmforge.basic_types import GeneralLexicon from abc import abstractmethod class AbstractA...
28.955224
72
0.723196
231
1,940
5.722944
0.255411
0.074887
0.059002
0.064297
0.538578
0.446293
0.427383
0.355522
0.22239
0.22239
0
0.00253
0.185052
1,940
66
73
29.393939
0.83365
0
0
0.352941
0
0
0.043814
0.043814
0
0
0
0
0
1
0.176471
false
0.019608
0.117647
0
0.411765
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
bd0555b1790f397fc8d762146f856a6acab0847d
3,043
py
Python
Python3/809.expressive-words.py
610yilingliu/leetcode
30d071b3685c2131bd3462ba77c6c05114f3f227
[ "MIT" ]
null
null
null
Python3/809.expressive-words.py
610yilingliu/leetcode
30d071b3685c2131bd3462ba77c6c05114f3f227
[ "MIT" ]
null
null
null
Python3/809.expressive-words.py
610yilingliu/leetcode
30d071b3685c2131bd3462ba77c6c05114f3f227
[ "MIT" ]
null
null
null
# # @lc app=leetcode id=809 lang=python3 # # [809] Expressive Words # # https://leetcode.com/problems/expressive-words/description/ # # algorithms # Medium (46.84%) # Likes: 320 # Dislikes: 823 # Total Accepted: 45.2K # Total Submissions: 96.2K # Testcase Example: '"heeellooo"\n["hello", "hi", "helo"]' # # Somet...
29.833333
141
0.57049
449
3,043
3.799555
0.367483
0.023447
0.021102
0.014068
0.069168
0.053927
0
0
0
0
0
0.02307
0.302005
3,043
101
142
30.128713
0.780132
0.578048
0
0
0
0
0
0
0
0
0
0
0
1
0.034483
false
0
0
0
0.137931
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
bd068843b439a58814f27d16075e43744d08bd52
1,601
py
Python
settings/Microscope_settings.py
bopopescu/Lauecollect
60ae2b05ea8596ba0decf426e37aeaca0bc8b6be
[ "MIT" ]
null
null
null
settings/Microscope_settings.py
bopopescu/Lauecollect
60ae2b05ea8596ba0decf426e37aeaca0bc8b6be
[ "MIT" ]
1
2019-10-22T21:28:31.000Z
2019-10-22T21:39:12.000Z
settings/Microscope_settings.py
bopopescu/Lauecollect
60ae2b05ea8596ba0decf426e37aeaca0bc8b6be
[ "MIT" ]
2
2019-06-06T15:06:46.000Z
2020-07-20T02:03:22.000Z
Size = (1255, 1160) Position = (39, 26) ScaleFactor = 1.0 ZoomLevel = 32.0 Orientation = 0 Mirror = False NominalPixelSize = 0.125 filename = 'Z:\\All Projects\\Crystallization\\2018.08.27.caplilary with crystals inspection\\2018.08.27 CypA 2.jpg' ImageWindow.Center = (649, 559) ImageWindow.ViewportCenter = (2.41796875...
37.232558
116
0.775141
224
1,601
5.375
0.357143
0.13289
0.037375
0.024917
0.142857
0
0
0
0
0
0
0.175365
0.102436
1,601
42
117
38.119048
0.662491
0
0
0
0
0.02381
0.065584
0.043098
0
0
0
0
0
1
0
false
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
bd07434502bfcaa7d1b29853452ba88cedddad3e
3,259
py
Python
model_rocke3d.py
projectcuisines/gcm_ana
cd9f7d47dd4a9088bcd7556b4955d9b8e09b9741
[ "MIT" ]
1
2021-09-29T18:03:56.000Z
2021-09-29T18:03:56.000Z
model_rocke3d.py
projectcuisines/thai_trilogy_code
cd9f7d47dd4a9088bcd7556b4955d9b8e09b9741
[ "MIT" ]
null
null
null
model_rocke3d.py
projectcuisines/thai_trilogy_code
cd9f7d47dd4a9088bcd7556b4955d9b8e09b9741
[ "MIT" ]
null
null
null
# -*- coding: utf-8 -*- """Utilities for the ROCKE3D output.""" import dask.array as da import xarray as xr from grid import reverse_along_dim, roll_da_to_pm180 from model_um import calc_um_rel from names import rocke3d __all__ = ("adjust_rocke3d_grid", "calc_rocke3d_rei", "calc_rocke3d_rel") calc_rocke3d_rel = calc...
30.745283
83
0.666769
490
3,259
4.25102
0.383673
0.020163
0.013442
0.012482
0.163226
0.131541
0.131541
0.131541
0.131541
0.131541
0
0.074542
0.246701
3,259
105
84
31.038095
0.773931
0.505063
0
0
0
0
0.104788
0.051353
0
0
0
0
0
1
0.046512
false
0
0.116279
0
0.209302
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
bd080979389c4fa7ca1e77a7f150acdec97764c3
4,090
py
Python
models/wordcloud.py
mcxwx123/RecGFI
6e872c3b8c5398959b119e5ba14e665bbb45c56b
[ "MIT" ]
9
2022-01-28T14:24:35.000Z
2022-01-30T05:05:03.000Z
models/wordcloud.py
mcxwx123/RecGFI
6e872c3b8c5398959b119e5ba14e665bbb45c56b
[ "MIT" ]
null
null
null
models/wordcloud.py
mcxwx123/RecGFI
6e872c3b8c5398959b119e5ba14e665bbb45c56b
[ "MIT" ]
1
2022-01-28T14:24:41.000Z
2022-01-28T14:24:41.000Z
from wordcloud import WordCloud,STOPWORDS import matplotlib.pyplot as plt import numpy as np import pandas as pd import re import multidict as multidict from collections import Counter import json import datetime import os plt.switch_backend('agg') def removePunctuation(text): text = re.sub(r'[{}]+'.format('!,;:?`"...
29.854015
138
0.596822
539
4,090
4.48423
0.306122
0.019859
0.023169
0.016549
0.343401
0.316094
0.29127
0.29127
0.272238
0.272238
0
0.038797
0.243765
4,090
136
139
30.073529
0.742645
0.027873
0
0.258621
0
0.034483
0.063508
0.030998
0
0
0
0
0
1
0.043103
false
0
0.086207
0
0.172414
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
bd08ddc4c6e6b83523aa9e949593219788ab5e5c
2,996
py
Python
favorites_updater.py
techonerd/moepoi
6440f39653bc3560e39429570bd25b7c564b7f54
[ "MIT" ]
36
2020-07-21T16:19:48.000Z
2022-03-21T15:31:02.000Z
favorites_updater.py
gaesant/moepoi
cd478ca00afa5140bb8057c7d37b1ccb2fcbe3b6
[ "MIT" ]
1
2022-02-18T07:41:14.000Z
2022-02-18T07:41:14.000Z
favorites_updater.py
gaesant/moepoi
cd478ca00afa5140bb8057c7d37b1ccb2fcbe3b6
[ "MIT" ]
176
2020-07-22T19:24:14.000Z
2022-03-30T23:42:58.000Z
from python_graphql_client import GraphqlClient import pathlib import re import os root = pathlib.Path(__file__).parent.resolve() client = GraphqlClient(endpoint="https://graphql.anilist.co") TOKEN = os.environ.get("ANILIST_TOKEN", "") def replace_chunk(content, marker, chunk, inline=False): r = re.compile( ...
23.046154
94
0.502003
274
2,996
5.364964
0.332117
0.032653
0.016327
0.027211
0.383673
0.326531
0.326531
0.287755
0.287755
0.287755
0
0.000519
0.357477
2,996
129
95
23.224806
0.763117
0.017356
0
0.34188
0
0
0.412585
0
0
0
0
0
0
1
0.025641
false
0
0.034188
0.008547
0.08547
0.025641
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
bd101452c6ae5bad47e4c2d957dbf69805a1b869
3,462
py
Python
SRC/common/IO/GUI/DIR.py
usnistgov/OOF3D
4fd423a48aea9c5dc207520f02de53ae184be74c
[ "X11" ]
31
2015-04-01T15:59:36.000Z
2022-03-18T20:21:47.000Z
SRC/common/IO/GUI/DIR.py
usnistgov/OOF3D
4fd423a48aea9c5dc207520f02de53ae184be74c
[ "X11" ]
3
2015-02-06T19:30:24.000Z
2017-05-25T14:14:31.000Z
SRC/common/IO/GUI/DIR.py
usnistgov/OOF3D
4fd423a48aea9c5dc207520f02de53ae184be74c
[ "X11" ]
7
2015-01-23T15:19:22.000Z
2021-06-09T09:03:59.000Z
# -*- python -*- # This software was produced by NIST, an agency of the U.S. government, # and by statute is not subject to copyright in the United States. # Recipients of this software assume all responsibilities associated # with its operation, modification and maintenance. However, to # facilitate maintenance we ...
25.455882
75
0.624783
366
3,462
5.852459
0.519126
0.031746
0.041083
0.012605
0.030812
0
0
0
0
0
0
0.013867
0.250144
3,462
135
76
25.644444
0.811248
0.209705
0
0.068627
0
0
0.445956
0.066544
0
0
0
0
0
1
0.009804
false
0
0.009804
0
0.019608
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
bd12daa2d90f5e59ee73aa4f239e4f3eb0699f08
4,366
py
Python
chapter_01/main_chapter01_00.py
couldbebetter/simulations_radar_systems_design
fcb23964e10c7ebb9cb1beabadc257e970a2c1de
[ "MIT" ]
20
2018-02-02T06:46:14.000Z
2022-01-05T21:25:50.000Z
chapter_01/main_chapter01_00.py
couldbebetter/simulations_radar_systems_design
fcb23964e10c7ebb9cb1beabadc257e970a2c1de
[ "MIT" ]
null
null
null
chapter_01/main_chapter01_00.py
couldbebetter/simulations_radar_systems_design
fcb23964e10c7ebb9cb1beabadc257e970a2c1de
[ "MIT" ]
5
2018-05-31T16:42:07.000Z
2020-07-30T22:29:43.000Z
# -*- coding: utf-8 -*- """ Created on 21 October 2017 implements Listing 1.2. MATLAB Program “fig1_12.m” in Mahafza radar book @author: Ashiv Dhondea """ import numpy as np import RadarBasics as RB import RadarConstants as RC import RadarEquations as RE # Importing what's needed for nice plots. import matplotlib...
40.803738
113
0.682776
785
4,366
3.549045
0.22293
0.046662
0.021536
0.040201
0.703877
0.655779
0.633166
0.549533
0.494257
0.450826
0
0.05715
0.082226
4,366
106
114
41.188679
0.638133
0.115208
0
0.186667
0
0
0.166276
0.013031
0
0
0
0
0
1
0
false
0
0.08
0
0.08
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
bd14232c1edf5c76909d75642903193968483bbc
1,087
py
Python
tests/jekpost_tests.py
arjunkrishnababu96/jekpost
2ddcb337e98c534426d83f1bd6fbde1f45f59225
[ "MIT" ]
1
2018-10-05T16:53:02.000Z
2018-10-05T16:53:02.000Z
tests/jekpost_tests.py
arjunkrishnababu96/jekpost
2ddcb337e98c534426d83f1bd6fbde1f45f59225
[ "MIT" ]
null
null
null
tests/jekpost_tests.py
arjunkrishnababu96/jekpost
2ddcb337e98c534426d83f1bd6fbde1f45f59225
[ "MIT" ]
null
null
null
import unittest import jekpost.jekpost_create as jek from datetime import date class JekpostTests(unittest.TestCase): def test_date_gets_formatted(self): """ Check 31-DEC-2016 (2016-12-31) 1-NOV-2015 (2015-11-01) 11-JAN-2015 (2015-01-11) """ sam...
31.970588
68
0.580497
132
1,087
4.537879
0.371212
0.033389
0.053422
0
0
0
0
0
0
0
0
0.142287
0.308188
1,087
33
69
32.939394
0.654255
0.084637
0
0
0
0
0.080253
0.022175
0
0
0
0
0.095238
1
0.095238
false
0
0.142857
0
0.285714
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
bd1639f542971f0b9d004e950fd65037d1434c94
4,788
py
Python
data/fidt_generate.py
PPGod95/FIDTM
b5582c5cc485496d85af2043ffd6e4266f354f3b
[ "MIT" ]
null
null
null
data/fidt_generate.py
PPGod95/FIDTM
b5582c5cc485496d85af2043ffd6e4266f354f3b
[ "MIT" ]
null
null
null
data/fidt_generate.py
PPGod95/FIDTM
b5582c5cc485496d85af2043ffd6e4266f354f3b
[ "MIT" ]
null
null
null
# -*- coding: utf-8 -*- """ @Project : @FileName: @Author :penghr @Time :2021/11/xx xx:xx @Desc : FIDTM-train/dataset/FIDTM/ ├── test │ ├── gt_fidt_map │ │ └── IMG_8.h5 │ ├── g...
33.71831
131
0.539474
672
4,788
3.714286
0.209821
0.050481
0.050481
0.064103
0.325321
0.213942
0.103365
0.055288
0.03766
0.03766
0
0.032592
0.314327
4,788
141
132
33.957447
0.706975
0.268797
0
0
0
0
0.071303
0
0
0
0
0
0
1
0.013158
false
0
0.092105
0
0.118421
0.039474
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
bd166a19a710f2d8a3cb312cb57d84d5ce6d3bb6
356
py
Python
tests/urls.py
maykinmedia/djadyen
8bde7172c72d68975d4a77c7ef6bed73412619dc
[ "BSD-3-Clause" ]
3
2018-10-19T06:57:50.000Z
2020-11-12T11:20:37.000Z
tests/urls.py
maykinmedia/djadyen
8bde7172c72d68975d4a77c7ef6bed73412619dc
[ "BSD-3-Clause" ]
16
2017-02-14T12:37:58.000Z
2019-04-25T07:55:42.000Z
tests/urls.py
maykinmedia/djadyen
8bde7172c72d68975d4a77c7ef6bed73412619dc
[ "BSD-3-Clause" ]
2
2018-05-16T10:08:34.000Z
2019-09-29T23:31:04.000Z
try: from django.urls import path, include except: from django.conf.urls import url as path, include from django.contrib import admin urlpatterns = [ path(r'^admin/', admin.site.urls), path(r'^app/', include('tests.app.urls')), path(r'^adyen/notifications/', include('djadyen.notifications.urls', n...
27.384615
107
0.702247
47
356
5.319149
0.468085
0.12
0.072
0
0
0
0
0
0
0
0
0
0.143258
356
12
108
29.666667
0.819672
0
0
0
0
0
0.258427
0.132022
0
0
0
0
0
1
0
false
0
0.3
0
0.3
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
bd17b046c9a2e0dbd7f153a5a1f41fd0257f99eb
5,610
py
Python
src/Commands.py
rkpop/kokobot
d19d68e12a7e6c0a25373ae5404e46632d59c40f
[ "MIT" ]
3
2018-07-25T23:55:58.000Z
2018-10-17T05:50:18.000Z
src/Commands.py
rkpop/kokobot
d19d68e12a7e6c0a25373ae5404e46632d59c40f
[ "MIT" ]
null
null
null
src/Commands.py
rkpop/kokobot
d19d68e12a7e6c0a25373ae5404e46632d59c40f
[ "MIT" ]
1
2018-12-01T05:18:48.000Z
2018-12-01T05:18:48.000Z
import asyncio from discord.ext import commands from src.BaseCog import BaseCog from src.DB import DB from src.Reasons import Reasons class Commands(BaseCog): def __init__(self, bot, config): super().__init__(bot, config) self.reasons = Reasons() HELP_MESSAGE = """ Command: `/kkb <action>...
31.166667
86
0.587344
691
5,610
4.596237
0.222865
0.035894
0.035264
0.036209
0.448048
0.406801
0.36335
0.311083
0.293136
0.293136
0
0.012438
0.312121
5,610
179
87
31.340782
0.810573
0.012656
0
0.382353
0
0
0.231714
0
0
0
0
0
0
1
0.014706
false
0
0.036765
0
0.080882
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
bd184a22649fd3e0a64f5b17ec6b9f8201e73eaa
2,981
py
Python
src/lur/grade.py
qlurkin/lur_python
39564f276b3c03a073d4922627634b67c3af2052
[ "MIT" ]
null
null
null
src/lur/grade.py
qlurkin/lur_python
39564f276b3c03a073d4922627634b67c3af2052
[ "MIT" ]
null
null
null
src/lur/grade.py
qlurkin/lur_python
39564f276b3c03a073d4922627634b67c3af2052
[ "MIT" ]
null
null
null
from cmath import nan from sqlite3 import DatabaseError import pandas as pd import numpy as np import json def load_from_csv(path): dt = pd.read_csv(path, sep=';', dtype={'matricule': object}) return dt.set_index('matricule') def fix_matricule(matricule): if matricule.startswith('195'): return '19...
31.378947
101
0.606172
406
2,981
4.330049
0.307882
0.015927
0.044369
0.025597
0.133106
0
0
0
0
0
0
0.02
0.211674
2,981
95
102
31.378947
0.728085
0
0
0.074074
0
0
0.154259
0
0
0
0
0
0
1
0.135802
false
0
0.061728
0.037037
0.358025
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
bd1bc728b1d732bdeadd112c3709dd6ba324fe1b
5,705
py
Python
simulate_position_covariance_data.py
ronniyjoseph/Hybrid-Calibration
7f24a8a5f67d647a47d4559566f7461cb3be57ac
[ "AFL-3.0" ]
null
null
null
simulate_position_covariance_data.py
ronniyjoseph/Hybrid-Calibration
7f24a8a5f67d647a47d4559566f7461cb3be57ac
[ "AFL-3.0" ]
9
2019-10-23T03:30:33.000Z
2020-02-19T05:25:27.000Z
simulate_position_covariance_data.py
ronniyjoseph/Hybrid-Calibration
7f24a8a5f67d647a47d4559566f7461cb3be57ac
[ "AFL-3.0" ]
null
null
null
import os import numpy import copy import argparse from matplotlib import pyplot from src.radiotelescope import RadioTelescope from src.radiotelescope import BaselineTable from src.skymodel import SkyRealisation from simulate_beam_covariance_data import compute_baseline_covariance from simulate_beam_covariance_data im...
46.382114
117
0.713234
636
5,705
6.069182
0.245283
0.025648
0.030829
0.038083
0.351554
0.315026
0.196114
0.180052
0.125907
0.096891
0
0.013623
0.202279
5,705
122
118
46.762295
0.834542
0.098335
0
0.074074
0
0
0.097214
0.055913
0
0
0
0
0
1
0.037037
false
0
0.17284
0
0.246914
0.049383
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
bd1d6496d7db8cd8d21e423c19bb1534688474e4
24,456
py
Python
anthill/event/admin.py
anthill-services/anthill-event
3c303f33e4c150ce2dfed4f3534ec40e935ecfb8
[ "MIT" ]
null
null
null
anthill/event/admin.py
anthill-services/anthill-event
3c303f33e4c150ce2dfed4f3534ec40e935ecfb8
[ "MIT" ]
null
null
null
anthill/event/admin.py
anthill-services/anthill-event
3c303f33e4c150ce2dfed4f3534ec40e935ecfb8
[ "MIT" ]
1
2017-12-03T22:03:10.000Z
2017-12-03T22:03:10.000Z
from anthill.common.validate import validate from anthill.common import admin as a, update from . model.event import EventNotFound, CategoryNotFound, EventFlags, EventEndAction import ujson import collections EVENT_END_ACTION_DESCRIPTION = """ <b>Send Message</b><br>A message with detailed information about event ...
36.392857
124
0.5294
2,457
24,456
5.171754
0.111518
0.027701
0.033997
0.035256
0.65279
0.592744
0.551507
0.522625
0.466121
0.413866
0
0.001618
0.342738
24,456
671
125
36.447094
0.788914
0
0
0.509158
0
0.016484
0.236639
0.018851
0
0
0
0
0
1
0.034799
false
0
0.009158
0.027473
0.10989
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
bd1d74e5ac367e134c8e0a19a4b10cfe4ee5fb88
15,704
py
Python
main.py
opt12/gym-jsbsim-eee
fa61d0d4679fd65b5736fc562fe268714b4e08d8
[ "MIT" ]
7
2020-11-10T07:33:40.000Z
2021-06-23T07:25:43.000Z
main.py
opt12/gym-jsbsim-eee
fa61d0d4679fd65b5736fc562fe268714b4e08d8
[ "MIT" ]
null
null
null
main.py
opt12/gym-jsbsim-eee
fa61d0d4679fd65b5736fc562fe268714b4e08d8
[ "MIT" ]
5
2020-07-12T00:10:59.000Z
2021-06-22T09:13:13.000Z
import sys, os # sys.path.append(os.path.join(os.path.dirname(__file__)) #TODO: Is this a good idea? Dunno! It works! # print(os.path.join(os.path.dirname(__file__))) import argparse import markov_pilot.environment.properties as prp from markov_pilot.environment.environment import NoFGJsbSimEnv_multi, J...
59.037594
219
0.707972
2,071
15,704
5.061806
0.201352
0.024897
0.032433
0.022894
0.409425
0.338167
0.26252
0.228084
0.178575
0.142898
0
0.020727
0.201223
15,704
265
220
59.260377
0.814971
0.310303
0
0.136054
0
0
0.139292
0.004097
0
0
0
0.003774
0
1
0.020408
false
0
0.095238
0
0.136054
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
bd1d8b232aa33e6da7911055afde86063303f3d6
19,781
py
Python
atm/core.py
HDI-Project/ATM
dde454a95e963a460843a61bbb44d18982984b17
[ "MIT" ]
554
2017-12-19T06:43:11.000Z
2022-03-26T04:24:55.000Z
atm/core.py
BTHUNTERCN/ATM
dde454a95e963a460843a61bbb44d18982984b17
[ "MIT" ]
128
2017-12-19T21:30:32.000Z
2021-04-19T17:03:39.000Z
atm/core.py
BTHUNTERCN/ATM
dde454a95e963a460843a61bbb44d18982984b17
[ "MIT" ]
140
2017-12-20T03:47:04.000Z
2022-03-17T01:50:24.000Z
# -*- coding: utf-8 -*- """Core ATM module. This module contains the ATM class, which is the one responsible for executing and orchestrating the main ATM functionalities. """ import logging import random import time from datetime import datetime, timedelta from operator import attrgetter from tqdm import tqdm from...
40.954451
95
0.547495
2,186
19,781
4.830741
0.16011
0.051515
0.057955
0.009659
0.492045
0.479356
0.464583
0.464583
0.452083
0.443182
0
0.005054
0.36985
19,781
482
96
41.039419
0.842118
0.408473
0
0.25974
0
0
0.059423
0
0
0
0
0
0
1
0.025974
false
0.004329
0.04329
0
0.099567
0.021645
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
bd225009cbeb540acf88e600f37e2294b3fa16ce
742
py
Python
dbcollection/datasets/leeds_sports_pose/leeds_sports_pose/__init__.py
dbcollection/dbcollection
a36f57a11bc2636992e26bba4406914162773dd9
[ "MIT" ]
23
2017-09-20T19:23:26.000Z
2022-01-09T16:18:11.000Z
dbcollection/datasets/leeds_sports_pose/leeds_sports_pose/__init__.py
dbcollection/dbcollection
a36f57a11bc2636992e26bba4406914162773dd9
[ "MIT" ]
148
2017-07-23T14:28:28.000Z
2022-01-13T00:35:17.000Z
dbcollection/datasets/leeds_sports_pose/leeds_sports_pose/__init__.py
dbcollection/dbcollection
a36f57a11bc2636992e26bba4406914162773dd9
[ "MIT" ]
6
2018-01-12T15:47:57.000Z
2021-02-09T06:32:39.000Z
""" Leeds Sports Pose (LSP) Dataset download/process functions. """ from dbcollection.datasets import BaseDataset from .keypoints import Keypoints, KeypointsOriginal urls = ( 'http://sam.johnson.io/research/lsp_dataset_original.zip', { 'url': 'http://sam.johnson.io/research/lsp_dataset.zip', ...
24.733333
78
0.699461
78
742
6.512821
0.474359
0.098425
0.059055
0.070866
0.232283
0.133858
0.133858
0
0
0
0
0
0.172507
742
29
79
25.586207
0.827362
0.172507
0
0
0
0
0.342762
0
0
0
0
0
0
1
0
false
0
0.1
0
0.35
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
bd25018110a4f497d278f0c5fcc41f39296d2cf6
3,505
py
Python
flydra_analysis/flydra_analysis/a2/check_mainbrain_h5_contiguity.py
elhananby/flydra
09b86859b1863700cdea0bbcdd4758da6c83930b
[ "Apache-2.0", "MIT" ]
45
2017-08-25T06:46:56.000Z
2021-08-29T16:42:49.000Z
flydra_analysis/flydra_analysis/a2/check_mainbrain_h5_contiguity.py
elhananby/flydra
09b86859b1863700cdea0bbcdd4758da6c83930b
[ "Apache-2.0", "MIT" ]
7
2017-10-16T10:46:20.000Z
2020-12-03T16:42:55.000Z
flydra_analysis/flydra_analysis/a2/check_mainbrain_h5_contiguity.py
elhananby/flydra
09b86859b1863700cdea0bbcdd4758da6c83930b
[ "Apache-2.0", "MIT" ]
21
2018-04-11T09:06:40.000Z
2021-12-26T23:38:40.000Z
#!/usr/bin/env python from __future__ import print_function import tables import argparse import numpy as np import sys def check_mainbrain_h5_contiguity( filename, slow_but_less_ram=False, shortcircuit=False, verbose=False ): failed_obj_ids = [] if verbose: print("opening %r" % filename) with...
33.066038
90
0.575178
437
3,505
4.389016
0.343249
0.056309
0.056309
0.036496
0.324296
0.253389
0.20438
0.20438
0.17414
0.17414
0
0.014178
0.315835
3,505
105
91
33.380952
0.785655
0.043937
0
0.366667
0
0
0.152558
0.030212
0
0
0
0
0
1
0.033333
false
0
0.077778
0
0.144444
0.122222
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
bd2629883944c343ab1a2e4d82cafb22e7d45e13
2,304
py
Python
reader.py
Birdulon/html-mangareader
dbdbbaa454125896b9de2d918f2ab59a3c06adc2
[ "MIT" ]
1
2021-05-08T14:58:17.000Z
2021-05-08T14:58:17.000Z
reader.py
Birdulon/html-mangareader
dbdbbaa454125896b9de2d918f2ab59a3c06adc2
[ "MIT" ]
null
null
null
reader.py
Birdulon/html-mangareader
dbdbbaa454125896b9de2d918f2ab59a3c06adc2
[ "MIT" ]
null
null
null
import sys import traceback import webbrowser from argparse import ArgumentParser, Namespace from os import path from tkinter import Tk, messagebox, filedialog from mangareader.mangarender import extract_render from mangareader import templates from time import sleep def parse_args() -> Namespace: parser = Argume...
34.909091
100
0.631076
262
2,304
5.324427
0.416031
0.021505
0.020072
0.034409
0.076703
0.035842
0.035842
0
0
0
0
0.001154
0.24783
2,304
65
101
35.446154
0.803808
0
0
0.033898
0
0
0.161458
0.055556
0
0
0
0
0
1
0.033898
false
0.016949
0.152542
0
0.220339
0.016949
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
bd29d7f8357ca28a05195118a23e7f338eea17aa
483
py
Python
Qemu/power_on_qemu.py
I-Rinka/Virtualization-Difference
7727215f5b5cdb8bf18d91ef76685ccd3489e760
[ "MIT" ]
null
null
null
Qemu/power_on_qemu.py
I-Rinka/Virtualization-Difference
7727215f5b5cdb8bf18d91ef76685ccd3489e760
[ "MIT" ]
null
null
null
Qemu/power_on_qemu.py
I-Rinka/Virtualization-Difference
7727215f5b5cdb8bf18d91ef76685ccd3489e760
[ "MIT" ]
null
null
null
#!/usr/bin/env python3 import socket import os import time import threading def power_on(): os.system("sudo bash ./start_vm.sh") if __name__ == "__main__": n=os.fork() if n>0: os.system("sleep 2") os.system("sudo ip addr add 172.19.0.1/24 dev tap1") os.system("...
18.576923
64
0.52588
71
483
3.366197
0.577465
0.133891
0.150628
0.117155
0
0
0
0
0
0
0
0.049844
0.335404
483
25
65
19.32
0.694704
0.138716
0
0
0
0
0.243961
0
0
0
0
0
0
1
0.066667
false
0
0.266667
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
bd2a739ca5325c09ff24414f0ce30e0bab1eacb7
381
py
Python
tests/unit/python/execution_tree/dynamic_init.py
frzfrsfra4/phylanx
001fe7081f3a24e56157cdb21b2d126b8953ff5d
[ "BSL-1.0" ]
83
2017-08-27T15:09:13.000Z
2022-01-18T17:03:41.000Z
tests/unit/python/execution_tree/dynamic_init.py
frzfrsfra4/phylanx
001fe7081f3a24e56157cdb21b2d126b8953ff5d
[ "BSL-1.0" ]
808
2017-08-27T15:35:01.000Z
2021-12-14T17:30:50.000Z
tests/unit/python/execution_tree/dynamic_init.py
frzfrsfra4/phylanx
001fe7081f3a24e56157cdb21b2d126b8953ff5d
[ "BSL-1.0" ]
55
2017-08-27T15:09:22.000Z
2022-03-25T12:07:34.000Z
# Copyright (c) 2018 R. Tohid # # Distributed under the Boost Software License, Version 1.0. (See accompanying # file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt) from phylanx import Phylanx, PhylanxSession @Phylanx def foo(): a = 2 return a def main(): assert (2 == foo()) if _...
17.318182
79
0.671916
56
381
4.357143
0.678571
0.02459
0.07377
0.098361
0
0
0
0
0
0
0
0.043189
0.209974
381
21
80
18.142857
0.767442
0.461942
0
0
0
0
0.040201
0
0
0
0
0
0.1
1
0.2
false
0
0.1
0
0.4
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
bd2af34a041fa744101d9895d1374416d6964a87
1,073
py
Python
indexStackexchange.py
o19s/semantic-search-course
ebe15eaa65c5009fa2d526b4df72bf8dbfb8630f
[ "Apache-2.0" ]
6
2016-03-07T18:41:52.000Z
2016-12-22T20:45:17.000Z
indexStackexchange.py
o19s/semantic-search-course
ebe15eaa65c5009fa2d526b4df72bf8dbfb8630f
[ "Apache-2.0" ]
1
2016-03-07T19:09:19.000Z
2016-03-07T19:09:19.000Z
indexStackexchange.py
o19s/semantic-search-course
ebe15eaa65c5009fa2d526b4df72bf8dbfb8630f
[ "Apache-2.0" ]
null
null
null
import requests import json def openPosts(): data = "" try: f = open("scifi_stackexchange.json") data = f.read() except IOError: stackExchangeData ="https://storage.googleapis.com/quepid-sample-datasets/elasticsearch/scifi_stackexchange.json" resp = requests.get(stackExchan...
26.825
121
0.587139
117
1,073
5.299145
0.470085
0.087097
0.106452
0.074194
0.087097
0
0
0
0
0
0
0.005168
0.278658
1,073
39
122
27.512821
0.795866
0
0
0
0
0
0.240447
0.044734
0
0
0
0
0
1
0.0625
false
0
0.125
0
0.21875
0.09375
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
bd2c89f3c83b146173c4e02b15272145ff176687
1,634
py
Python
Lab01_Introduction/exercise-4.py
rodrigoc-silva/Python-course
327b20738a4b383510faddc0ec26a54be1bbd717
[ "MIT" ]
null
null
null
Lab01_Introduction/exercise-4.py
rodrigoc-silva/Python-course
327b20738a4b383510faddc0ec26a54be1bbd717
[ "MIT" ]
null
null
null
Lab01_Introduction/exercise-4.py
rodrigoc-silva/Python-course
327b20738a4b383510faddc0ec26a54be1bbd717
[ "MIT" ]
null
null
null
#This program shows the amount of each ingredient needed for a numbers of cookies. #constants sugar = 1.5 butter = 1 flour = 2.75 cookies = 48 #input numOfCookies = int(input('Enter the number of cookies:')) #calculation amtSugar = sugar / cookies * numOfCookies amtButter = butter / cookies * numOfCookies amtFlour ...
18.155556
82
0.660343
274
1,634
3.937956
0.266423
0.100093
0.07785
0.088971
0.29101
0.163114
0.163114
0.163114
0.137164
0.137164
0
0.066971
0.195838
1,634
89
83
18.359551
0.754186
0.603427
0
0
0
0
0.255435
0
0
0
0
0
0
1
0
false
0
0
0
0
0.307692
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
bd2ee870e5845b50e43bca14345288b03bd674b2
1,340
py
Python
zombie_infection.py
schana/random-hacking
5eeda2f05681ce9f56f1b9114255c2392e92ee9a
[ "Apache-2.0" ]
null
null
null
zombie_infection.py
schana/random-hacking
5eeda2f05681ce9f56f1b9114255c2392e92ee9a
[ "Apache-2.0" ]
null
null
null
zombie_infection.py
schana/random-hacking
5eeda2f05681ce9f56f1b9114255c2392e92ee9a
[ "Apache-2.0" ]
null
null
null
import random import sys sys.setrecursionlimit(15000) count_columns = 50 count_rows = 40 matrix = [[random.randint(0, 1) for i in range(count_columns)] for j in range(count_rows)] matrix = [[0] * count_columns for _ in range(count_rows)] for _ in range(10): matrix[random.randint(0, count_rows - 1)][random.randin...
24.363636
90
0.590299
217
1,340
3.576037
0.271889
0.028351
0.05799
0.072165
0.203608
0.155928
0.085052
0.085052
0.085052
0
0
0.031185
0.28209
1,340
54
91
24.814815
0.775468
0.074627
0
0.225
0
0
0.001617
0
0
0
0
0
0
1
0.05
false
0
0.05
0
0.125
0.175
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
bd347bef874fe2b7fd02a07a979e78547511f381
216
py
Python
src/Main.py
Yee172/Memory_Revival
e9bf4598564546ada3b9d9bfce7bf35fad348850
[ "MIT" ]
null
null
null
src/Main.py
Yee172/Memory_Revival
e9bf4598564546ada3b9d9bfce7bf35fad348850
[ "MIT" ]
null
null
null
src/Main.py
Yee172/Memory_Revival
e9bf4598564546ada3b9d9bfce7bf35fad348850
[ "MIT" ]
null
null
null
#!/usr/bin/env python3 # -*- coding: utf-8 -*- __author__ = 'Yee_172' __date__ = '2017/12/03' import sys PATH = sys.path[0][:-4] sys.path.append(PATH) from src.Func import * win = MainWin() sys.exit(app.exec_())
14.4
23
0.648148
35
216
3.714286
0.8
0.161538
0
0
0
0
0
0
0
0
0
0.081081
0.143519
216
14
24
15.428571
0.621622
0.199074
0
0
0
0
0.099415
0
0
0
0
0
0
1
0
false
0
0.25
0
0.25
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
bd34863190099e5a1deaa0f914751c6c45b7892c
1,191
py
Python
tools/protonvpn-ips/main.py
alessandrobasi/basi-warninglist
995d3cd94e1dc7afdc09eff11bc1baa352b225e9
[ "MIT" ]
null
null
null
tools/protonvpn-ips/main.py
alessandrobasi/basi-warninglist
995d3cd94e1dc7afdc09eff11bc1baa352b225e9
[ "MIT" ]
null
null
null
tools/protonvpn-ips/main.py
alessandrobasi/basi-warninglist
995d3cd94e1dc7afdc09eff11bc1baa352b225e9
[ "MIT" ]
null
null
null
import requests, os dir_name = os.path.basename(os.path.dirname(os.path.realpath(__file__))) save_path = "../../lists/"+dir_name+"/" def main(): ips = set() with open(save_path+"all.txt","r",encoding="UTF-8") as f: for line in f: ips.add(line[:-1]) url_ = 'https://api.protonmail.c...
31.342105
191
0.577666
173
1,191
3.83815
0.491329
0.060241
0.072289
0.084337
0.131024
0.081325
0
0
0
0
0
0.049724
0.240134
1,191
38
192
31.342105
0.683978
0
0
0
0
0.037037
0.25
0
0
0
0
0
0
1
0.037037
false
0
0.037037
0
0.111111
0.037037
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
bd3567ec2bb0a247f32f1485e666f3eac6f7dc19
2,809
py
Python
dakota/sobol/sobol.py
arfc/dcwrapper
82226f601580be464668fa63df64f037962db57e
[ "BSD-3-Clause" ]
1
2020-03-26T14:09:30.000Z
2020-03-26T14:09:30.000Z
dakota/sobol/sobol.py
mehmeturkmen/dcwrapper
82226f601580be464668fa63df64f037962db57e
[ "BSD-3-Clause" ]
10
2019-10-08T18:46:36.000Z
2019-11-14T19:23:05.000Z
dakota/sobol/sobol.py
mehmeturkmen/dcwrapper
82226f601580be464668fa63df64f037962db57e
[ "BSD-3-Clause" ]
3
2019-10-29T19:23:44.000Z
2020-09-18T13:09:49.000Z
# Dakota Python Driving Script # necessary python modules import dakota.interfacing as di import subprocess import sys import os import multiprocessing sys.path.append('../../scripts') import input as inp import output as oup import external_cym cycdir = '../../cyclus-files/sobol/' # -----------------...
25.770642
62
0.555714
364
2,809
4.200549
0.302198
0.023545
0.031393
0.054938
0.328973
0.299542
0.218443
0.218443
0.158273
0.158273
0
0.005119
0.234959
2,809
108
63
26.009259
0.706375
0.133499
0
0.355263
0
0
0.133651
0.010813
0
0
0
0
0
1
0
false
0
0.105263
0
0.105263
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
bd3a8db83a92cdd76c21b817a1af0e0151e6c4ab
5,690
py
Python
app/hide-and-seek/common/computils/debug.py
loramf/mlforhealthlabpub
aa5a42a4814cf69c8223f27c21324ee39d43c404
[ "BSD-3-Clause" ]
171
2021-02-12T10:23:19.000Z
2022-03-29T01:58:52.000Z
app/hide-and-seek/common/computils/debug.py
loramf/mlforhealthlabpub
aa5a42a4814cf69c8223f27c21324ee39d43c404
[ "BSD-3-Clause" ]
4
2021-06-01T08:18:33.000Z
2022-02-20T13:37:30.000Z
app/hide-and-seek/common/computils/debug.py
loramf/mlforhealthlabpub
aa5a42a4814cf69c8223f27c21324ee39d43c404
[ "BSD-3-Clause" ]
93
2021-02-10T03:21:59.000Z
2022-03-30T19:10:37.000Z
""" Debug helpers. """ import io import logging from typing import Union, Optional, Callable import numpy as np import pandas as pd _printt_log_method = print def set_log_method(log_method: Optional[Callable] = None) -> None: global _printt_log_method # pylint: disable=global-statement if log_method is no...
30.10582
110
0.618102
741
5,690
4.585695
0.233468
0.037081
0.044144
0.030901
0.258682
0.16186
0.128311
0.114185
0.099765
0.084756
0
0.016675
0.25167
5,690
188
111
30.265957
0.781353
0.273814
0
0.284404
0
0
0.114696
0.038316
0
0
0
0
0
1
0.082569
false
0
0.045872
0
0.174312
0.100917
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
bd3b0f2c14b30cd87e31089661c02ceeb62af81c
3,862
py
Python
setup.py
jacklinke/django-directed
8ef8cd8a71e9a03a8628dce6465351f676f542ff
[ "Apache-2.0" ]
2
2022-02-09T10:15:40.000Z
2022-02-22T14:11:03.000Z
setup.py
jacklinke/django-directed
8ef8cd8a71e9a03a8628dce6465351f676f542ff
[ "Apache-2.0" ]
1
2022-02-20T14:49:37.000Z
2022-02-20T14:49:37.000Z
setup.py
jacklinke/django-directed
8ef8cd8a71e9a03a8628dce6465351f676f542ff
[ "Apache-2.0" ]
null
null
null
import os import re import sys from collections import defaultdict try: from setuptools import setup except ImportError: from distutils.core import setup def get_version(*file_paths): """Retrieves the version from django_directed/__init__.py""" filename = os.path.join(os.path.dirname(__file__), *file...
33.877193
108
0.634645
466
3,862
5.126609
0.405579
0.064462
0.052323
0.043533
0.064044
0.046463
0
0
0
0
0
0.010905
0.216468
3,862
113
109
34.176991
0.778586
0.046608
0
0.072917
0
0
0.391293
0.011973
0
0
0
0
0
1
0.020833
false
0
0.09375
0
0.135417
0.03125
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
bd3b1d81b7abc114bb78bcdb8316981a6a5efeb1
2,050
py
Python
cv_utils/object_detection/dataset/utils.py
fadamsyah/cv_utils
487fc65fe4a71f05dd03df31cde21d866968c0b4
[ "MIT" ]
null
null
null
cv_utils/object_detection/dataset/utils.py
fadamsyah/cv_utils
487fc65fe4a71f05dd03df31cde21d866968c0b4
[ "MIT" ]
1
2021-11-01T06:10:29.000Z
2021-11-09T12:47:48.000Z
cv_utils/object_detection/dataset/utils.py
fadamsyah/cv_utils
487fc65fe4a71f05dd03df31cde21d866968c0b4
[ "MIT" ]
null
null
null
import json import os import shutil from copy import deepcopy from pathlib import Path def create_and_overwrite_dir(path_dir): # Create the directory Path(path_dir).mkdir(parents=True, exist_ok=True) # Overwrite the directory for path in os.listdir(path_dir): try: os.remove(os.path.join(p...
25.308642
85
0.632683
248
2,050
5.068548
0.366935
0.038982
0.02148
0.022275
0.033413
0.033413
0
0
0
0
0
0.009365
0.270732
2,050
81
86
25.308642
0.831438
0.238049
0
0
0
0
0.07095
0
0
0
0
0
0
1
0.135135
false
0.027027
0.135135
0
0.324324
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
bd41d6fca25f541134f0afce1961c06f85b0df9b
1,806
py
Python
tests/fixtures.py
DNXLabs/ssm-loader
eae0257794126247584150eeb1b74ae05f4fcaf5
[ "Apache-2.0" ]
null
null
null
tests/fixtures.py
DNXLabs/ssm-loader
eae0257794126247584150eeb1b74ae05f4fcaf5
[ "Apache-2.0" ]
2
2020-07-31T05:32:10.000Z
2020-09-07T10:38:24.000Z
tests/fixtures.py
DNXLabs/ssm-loader
eae0257794126247584150eeb1b74ae05f4fcaf5
[ "Apache-2.0" ]
null
null
null
import pytest import os import json import boto3 from click.testing import CliRunner from moto import mock_ssm @pytest.fixture def runner(): return CliRunner() @pytest.fixture(scope='function') def aws_credentials(): """Mocked AWS Credentials for moto.""" os.environ['AWS_ACCESS_KEY_ID'] = 'test' os...
22.860759
75
0.593577
203
1,806
5.103448
0.330049
0.087838
0.052124
0.050193
0.28861
0.188224
0.15251
0.098456
0.098456
0.098456
0
0.005303
0.269103
1,806
78
76
23.153846
0.779545
0.017719
0
0.311475
0
0
0.250141
0.058291
0
0
0
0
0
1
0.114754
false
0
0.098361
0.032787
0.278689
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
bd42f92ac6de47d16f3dec018fcdc491713b5ba6
5,656
py
Python
scripts/plotting/create_num_demos_plots.py
Learning-and-Intelligent-Systems/predicators
0b2e71cacf86ba2bfdc1d9059c3a78016d0a4d7e
[ "MIT" ]
24
2021-11-20T16:35:41.000Z
2022-03-30T03:49:52.000Z
scripts/plotting/create_num_demos_plots.py
Learning-and-Intelligent-Systems/predicators
0b2e71cacf86ba2bfdc1d9059c3a78016d0a4d7e
[ "MIT" ]
214
2021-10-12T01:17:50.000Z
2022-03-31T20:18:36.000Z
scripts/plotting/create_num_demos_plots.py
Learning-and-Intelligent-Systems/predicators
0b2e71cacf86ba2bfdc1d9059c3a78016d0a4d7e
[ "MIT" ]
1
2022-02-15T20:24:17.000Z
2022-02-15T20:24:17.000Z
"""Create plots for learning from varying numbers of demonstrations.""" import os import matplotlib import matplotlib.pyplot as plt import pandas as pd from predicators.scripts.analyze_results_directory import create_dataframes, \ get_df_for_entry pd.options.mode.chained_assignment = None # default='warn' # pl...
37.456954
79
0.572313
708
5,656
4.303672
0.295198
0.059075
0.039383
0.078766
0.218904
0.218904
0.207745
0.207745
0.207745
0.207745
0
0.004938
0.283946
5,656
150
80
37.706667
0.747407
0.161068
0
0.097345
0
0
0.233665
0.025746
0
0
0
0
0
1
0.00885
false
0
0.044248
0
0.053097
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
bd43a1e72c9d194feac6f21f795a8c2f2065d1a1
85,638
py
Python
pyaedt/modeler/stackup_3d.py
pyansys/pyaedt
c7b045fede6bc707fb20a8db7d5680c66d8263f6
[ "MIT" ]
38
2021-10-01T23:15:26.000Z
2022-03-30T18:14:41.000Z
pyaedt/modeler/stackup_3d.py
pyansys/pyaedt
c7b045fede6bc707fb20a8db7d5680c66d8263f6
[ "MIT" ]
362
2021-09-30T17:11:55.000Z
2022-03-31T13:36:20.000Z
pyaedt/modeler/stackup_3d.py
pyansys/pyaedt
c7b045fede6bc707fb20a8db7d5680c66d8263f6
[ "MIT" ]
15
2021-09-30T20:21:02.000Z
2022-02-21T20:22:03.000Z
import os from collections import OrderedDict try: import joblib except ImportError: pass try: import numpy as np except ImportError: pass from pyaedt import constants from pyaedt.generic.general_methods import generate_unique_name from pyaedt.generic.general_methods import pyaedt_function_handler fro...
33.91604
119
0.574768
8,956
85,638
5.197298
0.058062
0.019851
0.023202
0.026941
0.638344
0.566438
0.513352
0.46843
0.441124
0.414248
0
0.010979
0.324646
85,638
2,524
120
33.929477
0.793831
0.222506
0
0.480932
0
0
0.055673
0.009202
0.000706
0
0
0.000396
0
1
0.088983
false
0.001412
0.008475
0.000706
0.184322
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
bd47557928bc51ca7d2e89e0a88949b5b7b0aaa5
1,511
py
Python
data/train/python/bd47557928bc51ca7d2e89e0a88949b5b7b0aaa5urls.py
harshp8l/deep-learning-lang-detection
2a54293181c1c2b1a2b840ddee4d4d80177efb33
[ "MIT" ]
84
2017-10-25T15:49:21.000Z
2021-11-28T21:25:54.000Z
data/train/python/bd47557928bc51ca7d2e89e0a88949b5b7b0aaa5urls.py
vassalos/deep-learning-lang-detection
cbb00b3e81bed3a64553f9c6aa6138b2511e544e
[ "MIT" ]
5
2018-03-29T11:50:46.000Z
2021-04-26T13:33:18.000Z
data/train/python/bd47557928bc51ca7d2e89e0a88949b5b7b0aaa5urls.py
vassalos/deep-learning-lang-detection
cbb00b3e81bed3a64553f9c6aa6138b2511e544e
[ "MIT" ]
24
2017-11-22T08:31:00.000Z
2022-03-27T01:22:31.000Z
from django.conf.urls.defaults import * urlpatterns = patterns('clwmail.admin.views', (r'user/manage/page/(?P<page_num>\d{1,})/$' ,'usermanage'), (r'user/manage/page/$' ,'usermanage'), (r'user/add/$' ,'useradd'), (r'user/...
65.695652
77
0.420913
137
1,511
4.59854
0.328467
0.088889
0.165079
0.071429
0.379365
0.293651
0.293651
0
0
0
0
0.003012
0.340834
1,511
22
78
68.681818
0.629518
0
0
0
0
0
0.505625
0.309729
0
0
0
0
0
1
0
false
0.045455
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
bd49a1d92154f5da9b36b624b1f7c5c860a48554
346
py
Python
remove_duplicates_from_sorted_array.py
lutianming/leetcode
848c7470ff5fd23608cc954be23732f60488ed8a
[ "MIT" ]
null
null
null
remove_duplicates_from_sorted_array.py
lutianming/leetcode
848c7470ff5fd23608cc954be23732f60488ed8a
[ "MIT" ]
null
null
null
remove_duplicates_from_sorted_array.py
lutianming/leetcode
848c7470ff5fd23608cc954be23732f60488ed8a
[ "MIT" ]
null
null
null
class Solution: # @param a list of integers # @return an integer def removeDuplicates(self, A): length = len(A) if length <= 1: return length index = 1 for i in range(1, length): if A[i] != A[i-1]: A[index] = A[i] index ...
24.714286
34
0.459538
44
346
3.613636
0.5
0.037736
0
0
0
0
0
0
0
0
0
0.025773
0.439306
346
13
35
26.615385
0.793814
0.127168
0
0
0
0
0
0
0
0
0
0
0
1
0.090909
false
0
0
0
0.363636
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
bd49d7f152ceeb7bc9bb00c813b8cb8af0d1c6dc
3,704
py
Python
visan/plot/datasetattributespanel.py
ercumentaksoy/visan
57c9257d80622fc0ab03591db48cc2155bd12f1b
[ "MIT", "BSD-3-Clause" ]
7
2020-04-09T05:21:03.000Z
2022-01-23T18:39:02.000Z
visan/plot/datasetattributespanel.py
ercumentaksoy/visan
57c9257d80622fc0ab03591db48cc2155bd12f1b
[ "MIT", "BSD-3-Clause" ]
7
2020-01-05T19:19:20.000Z
2020-05-27T09:41:49.000Z
visan/plot/datasetattributespanel.py
ercumentaksoy/visan
57c9257d80622fc0ab03591db48cc2155bd12f1b
[ "MIT", "BSD-3-Clause" ]
4
2020-04-18T14:11:22.000Z
2021-11-10T02:27:49.000Z
# Copyright (C) 2002-2021 S[&]T, The Netherlands. # All rights reserved. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are met: # # 1. Redistributions of source code must retain the above copyright notice, # this list of condi...
38.583333
105
0.660907
450
3,704
5.382222
0.457778
0.07019
0.038398
0.018993
0.07597
0.056152
0.056152
0.056152
0.056152
0.056152
0
0.009605
0.269168
3,704
95
106
38.989474
0.885113
0.455994
0
0.301887
0
0
0.016145
0
0
0
0
0
0
1
0.09434
false
0.037736
0.037736
0
0.226415
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
bd49f05f95bdcec75ece665e2dc35ecf557cf5b9
3,473
py
Python
iscc_registry/observe.py
titusz/iscc-registry
def03f420e671ec470070bb09b6a78099f7827da
[ "MIT" ]
3
2020-07-06T16:01:54.000Z
2020-08-06T11:03:25.000Z
iscc_registry/observe.py
titusz/iscc-registry
def03f420e671ec470070bb09b6a78099f7827da
[ "MIT" ]
null
null
null
iscc_registry/observe.py
titusz/iscc-registry
def03f420e671ec470070bb09b6a78099f7827da
[ "MIT" ]
null
null
null
# -*- coding: utf-8 -*- """Watching for registration events""" import time from dataclasses import dataclass, asdict import iscc_registry from loguru import logger as log import iscc from iscc_registry.conn import db_client from iscc_registry.publish import get_live_contract from iscc_registry import tools from iscc_re...
30.734513
104
0.657357
486
3,473
4.415638
0.244856
0.089469
0.029823
0.033551
0.419385
0.419385
0.397018
0.34576
0.34576
0.34576
0
0.004919
0.238986
3,473
112
105
31.008929
0.807037
0.043478
0
0.333333
0
0
0.131157
0
0
0
0
0
0
1
0.044444
false
0
0.1
0
0.266667
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
bd4c2d2d1aecd9d7ef7769f96a47de90c8225163
6,400
py
Python
src/CNN_models/train_model.py
ChrisPedder/Medieval_Manuscripts
40bfcf9c273385cfd8aa66e63b2fb80078fef33b
[ "MIT" ]
null
null
null
src/CNN_models/train_model.py
ChrisPedder/Medieval_Manuscripts
40bfcf9c273385cfd8aa66e63b2fb80078fef33b
[ "MIT" ]
5
2020-12-28T15:28:35.000Z
2022-02-10T03:26:44.000Z
src/CNN_models/train_model.py
ChrisPedder/Medieval_Manuscripts
40bfcf9c273385cfd8aa66e63b2fb80078fef33b
[ "MIT" ]
null
null
null
#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Fri Aug 10 11:07:05 2018 @author: chrispedder To train the model, run from the top-level dir as: python3 -m src.CNN_models.train_model --args ... """ import numpy as np import os import argparse import json import tensorflow as tf from abc import ABC, ...
33.333333
85
0.621563
805
6,400
4.767702
0.28323
0.01407
0.035435
0.026055
0.159979
0.09432
0.01876
0
0
0
0
0.011164
0.272188
6,400
191
86
33.507853
0.812795
0.11125
0
0.188406
0
0
0.098288
0
0
0
0
0
0
1
0.123188
false
0.043478
0.065217
0
0.268116
0.007246
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
bd4e4bb56c05d5afc00c0ccb424743f1c99a0f0b
8,063
py
Python
pfb_exporter/transform/sqla.py
znatty22/pfb-edu
24e606895c192b92493c0808d00a10fdf6f5ffa4
[ "Apache-2.0" ]
null
null
null
pfb_exporter/transform/sqla.py
znatty22/pfb-edu
24e606895c192b92493c0808d00a10fdf6f5ffa4
[ "Apache-2.0" ]
null
null
null
pfb_exporter/transform/sqla.py
znatty22/pfb-edu
24e606895c192b92493c0808d00a10fdf6f5ffa4
[ "Apache-2.0" ]
null
null
null
""" Transform SQLAlchemy Models to PFB Schema """ import os import logging import inspect import subprocess from collections import defaultdict import timeit from pprint import pformat from sqlalchemy.dialects.postgresql import UUID from sqlalchemy.inspection import inspect as sqla_inspect from sqlalchemy.orm.properti...
34.60515
79
0.583902
902
8,063
5.037694
0.268293
0.043134
0.039613
0.011444
0.087808
0.029049
0
0
0
0
0
0.001493
0.335607
8,063
232
80
34.75431
0.846369
0.219273
0
0.058824
0
0
0.1556
0.027459
0
0
0
0
0
1
0.044118
false
0.007353
0.176471
0
0.25
0.007353
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
bd55c1befc97ceb37b6df37eb99994c9d21b2ba9
773
py
Python
python/206.reverse-linked-list.py
Wanger-SJTU/leetcode-solutions
eb7f2fb142b8a30d987c5ac8002a96ead0aa56f4
[ "MIT" ]
2
2019-05-13T17:09:15.000Z
2019-09-08T15:32:42.000Z
python/206.reverse-linked-list.py
Wanger-SJTU/leetcode
eb7f2fb142b8a30d987c5ac8002a96ead0aa56f4
[ "MIT" ]
null
null
null
python/206.reverse-linked-list.py
Wanger-SJTU/leetcode
eb7f2fb142b8a30d987c5ac8002a96ead0aa56f4
[ "MIT" ]
null
null
null
# # @lc app=leetcode id=206 lang=python3 # # [206] Reverse Linked List # # Definition for singly-linked list. # class ListNode: # def __init__(self, x): # self.val = x # self.next = None class Solution: def reverseList(self, head: ListNode) -> ListNode: def iterative(head): ...
23.424242
54
0.500647
85
773
4.505882
0.423529
0.083551
0
0
0
0
0
0
0
0
0
0.015521
0.416559
773
32
55
24.15625
0.833703
0.240621
0
0
0
0
0
0
0
0
0
0
0
1
0.166667
false
0
0
0
0.444444
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1f9c7aa01ba17d2af64bca27a27081040ab187d0
2,521
py
Python
tests/default_tags.py
GrAndSE/lighty-template
63834fbb2421506205745bb596ff8ac726361f2a
[ "BSD-3-Clause" ]
1
2018-05-09T19:56:15.000Z
2018-05-09T19:56:15.000Z
tests/default_tags.py
GrAndSE/lighty-template
63834fbb2421506205745bb596ff8ac726361f2a
[ "BSD-3-Clause" ]
null
null
null
tests/default_tags.py
GrAndSE/lighty-template
63834fbb2421506205745bb596ff8ac726361f2a
[ "BSD-3-Clause" ]
null
null
null
'''Module to test default template tags such as if, for, with, include, etc. ''' import unittest from lighty.templates import Template from lighty.templates.loaders import FSLoader class DefaultTagsTestCase(unittest.TestCase): """Test case for if template tag """ def assertResult(self, name, result, val...
36.536232
79
0.568029
249
2,521
5.751004
0.313253
0.100559
0.066341
0.094274
0.159218
0.111732
0
0
0
0
0
0.006572
0.275684
2,521
68
80
37.073529
0.777656
0.09044
0
0.083333
0
0
0.238032
0
0
0
0
0
0.166667
1
0.145833
false
0
0.0625
0
0.25
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1f9c9104d3d243f4e10cfdbb1fb0326c74424885
3,038
py
Python
tests/test_calibration.py
SoyGema/NannyML
323ff404e0e06c479b01d2a63c1c3af9680d95ab
[ "Apache-2.0" ]
null
null
null
tests/test_calibration.py
SoyGema/NannyML
323ff404e0e06c479b01d2a63c1c3af9680d95ab
[ "Apache-2.0" ]
null
null
null
tests/test_calibration.py
SoyGema/NannyML
323ff404e0e06c479b01d2a63c1c3af9680d95ab
[ "Apache-2.0" ]
null
null
null
# Author: Niels Nuyttens <niels@nannyml.com> # # License: Apache Software License 2.0 """Unit tests for the calibration module.""" import numpy as np import pandas as pd import pytest from nannyml.calibration import IsotonicCalibrator, _get_bin_index_edges, needs_calibration from nannyml.exceptions import Invali...
41.616438
104
0.71264
480
3,038
4.18125
0.208333
0.036871
0.043348
0.041854
0.63727
0.540608
0.537618
0.510214
0.510214
0.502242
0
0.056559
0.161949
3,038
72
105
42.194444
0.731736
0.066162
0
0.27451
0
0
0.039688
0.017718
0
0
0
0
0.098039
1
0.137255
false
0
0.098039
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
1f9d448358740aaa0c055882926c57c97ff59db8
3,962
py
Python
code/utils.py
liudaizong/IA-Net
f19295d13d1468eb582521131cde3de83dfd18f6
[ "MIT" ]
4
2021-11-02T10:57:12.000Z
2022-02-13T17:53:03.000Z
code/utils.py
liudaizong/IA-Net
f19295d13d1468eb582521131cde3de83dfd18f6
[ "MIT" ]
null
null
null
code/utils.py
liudaizong/IA-Net
f19295d13d1468eb582521131cde3de83dfd18f6
[ "MIT" ]
null
null
null
import copy import nltk import json from gensim.models import KeyedVectors import h5py import numpy as np from torch import nn def clones(module, N): return nn.ModuleList([copy.deepcopy(module) for _ in range(N)]) def load_feature(filename, dataset='ActivityNet'): if dataset == 'ActivityNet': with ...
25.397436
73
0.579253
537
3,962
4.212291
0.22905
0.024757
0.026525
0.04244
0.443413
0.385942
0.342175
0.320955
0.320955
0.280283
0
0.047805
0.287229
3,962
155
74
25.56129
0.753187
0.069409
0
0.477876
0
0
0.029203
0
0
0
0
0
0
1
0.19469
false
0
0.070796
0.035398
0.424779
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1f9e4501c0a3ac77cc15f6de9e5e460d7fd997df
2,654
py
Python
aps_purchasing/tests/forms_tests.py
bitmazk/django-aps-purchasing
ff0316f0eaff5bd39ae40aaa861543d125f33dae
[ "MIT" ]
4
2015-05-18T13:51:16.000Z
2015-05-18T14:47:32.000Z
aps_purchasing/tests/forms_tests.py
bitmazk/django-aps-purchasing
ff0316f0eaff5bd39ae40aaa861543d125f33dae
[ "MIT" ]
null
null
null
aps_purchasing/tests/forms_tests.py
bitmazk/django-aps-purchasing
ff0316f0eaff5bd39ae40aaa861543d125f33dae
[ "MIT" ]
null
null
null
"""Tests for the forms of the ``aps_purchasing`` app.""" import os from django.conf import settings from django.core.files.uploadedfile import SimpleUploadedFile from django.test import TestCase from django.utils.timezone import now from ..forms import QuotationUploadForm from ..models import MPN, Price, Quotation, Q...
37.380282
79
0.629239
297
2,654
5.572391
0.3367
0.032628
0.065257
0.074924
0.371601
0.299698
0.279758
0.178248
0.178248
0.10997
0
0.004063
0.258101
2,654
70
80
37.914286
0.836465
0.037302
0
0.125
0
0
0.230346
0.009827
0
0
0
0
0.142857
1
0.035714
false
0
0.142857
0
0.214286
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1f9eb8e2438d5e8851abb15909ddab5b70595c79
1,839
py
Python
test/test_read_embark_fields_json_file.py
ndlib/mellon-search
30f7eb267e35d77ee6d126789866d44d825c3e0c
[ "Apache-2.0" ]
null
null
null
test/test_read_embark_fields_json_file.py
ndlib/mellon-search
30f7eb267e35d77ee6d126789866d44d825c3e0c
[ "Apache-2.0" ]
null
null
null
test/test_read_embark_fields_json_file.py
ndlib/mellon-search
30f7eb267e35d77ee6d126789866d44d825c3e0c
[ "Apache-2.0" ]
null
null
null
# test_read_embark_fields_json_file.py 2/18/19 sm """ test read_embark_fields_json_file.py """ import json import unittest # add parent directory to path import os import inspect import sys CURRENTDIR = os.path.dirname(os.path.abspath(inspect.getfile( inspect.currentframe()))) PARENTDIR = os.path.dirname(CURRENTD...
32.839286
74
0.694943
213
1,839
5.676056
0.352113
0.074442
0.119107
0.148883
0.3689
0.249793
0.226634
0.177006
0.177006
0.132341
0
0.004152
0.214247
1,839
55
75
33.436364
0.832526
0.169657
0
0
0
0
0.07822
0.072151
0
0
0
0
0.121212
1
0.151515
false
0
0.181818
0
0.393939
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1fa0d3c9b6fdeba10b20b2a6b065d708f3d43858
8,928
py
Python
menu/show_results.py
Jcollier722/PageRemoval
ec14cd3927bbb754883a6a3dcff312ba90cd45db
[ "Apache-2.0" ]
null
null
null
menu/show_results.py
Jcollier722/PageRemoval
ec14cd3927bbb754883a6a3dcff312ba90cd45db
[ "Apache-2.0" ]
null
null
null
menu/show_results.py
Jcollier722/PageRemoval
ec14cd3927bbb754883a6a3dcff312ba90cd45db
[ "Apache-2.0" ]
null
null
null
"""This file is the results window""" import sys sys.path.insert(0, 'menu/') sys.path.insert(1, 'util/') sys.path.insert(2, 'sim/') import tkinter as tk import menu import import_jobs as ij import validate_jobs as validate import show_results as sr import export_results as xr import compare_sim import con...
46.020619
172
0.635529
1,451
8,928
3.742247
0.121985
0.055985
0.034807
0.070718
0.725599
0.678269
0.646777
0.641252
0.635175
0.591529
0
0.044128
0.197917
8,928
193
173
46.259067
0.714146
0.073029
0
0.360902
0
0
0.100979
0
0.015038
0
0
0
0
1
0.007519
false
0
0.097744
0
0.112782
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1fa40e3d5ffd5031f4b30a989255c4474dd77b5f
9,440
py
Python
POP909-Dataset-master/data_process/processor.py
agurdins/RTU_Bachelor
28ed4bf90a8ffdb2b599e549bae5f2b12a795ff1
[ "Apache-2.0" ]
140
2020-08-06T12:15:56.000Z
2022-03-26T11:02:36.000Z
POP909-Dataset-master/data_process/processor.py
agurdins/RTU_Bachelor
28ed4bf90a8ffdb2b599e549bae5f2b12a795ff1
[ "Apache-2.0" ]
5
2020-08-18T08:29:46.000Z
2021-09-25T16:56:49.000Z
POP909-Dataset-master/data_process/processor.py
agurdins/RTU_Bachelor
28ed4bf90a8ffdb2b599e549bae5f2b12a795ff1
[ "Apache-2.0" ]
18
2020-09-21T07:13:44.000Z
2022-03-19T14:30:09.000Z
""" Representation Processor ============ These are core classes of representation processor. Repr Processor: the basic representation processor - Event Processor """ import numpy as np from abc import ABC, abstractmethod import pretty_midi as pyd class ReprProcessor(ABC): """Abstract base class severing as...
30.550162
126
0.500953
1,033
9,440
4.408519
0.181026
0.036891
0.046113
0.019763
0.410408
0.347826
0.197189
0.157664
0.113746
0.113746
0
0.024527
0.395339
9,440
308
127
30.649351
0.773301
0.310699
0
0.301205
0
0
0.073663
0
0
0
0
0
0
1
0.048193
false
0
0.018072
0
0.114458
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1fa5b81e8ddb69f6e5c8f48345327239689cae22
19,461
py
Python
xtb_trading.py
lemassykoi/XTBApi
3b159f0b711e0d445a9cd7fec5c7a499cc623140
[ "MIT" ]
null
null
null
xtb_trading.py
lemassykoi/XTBApi
3b159f0b711e0d445a9cd7fec5c7a499cc623140
[ "MIT" ]
null
null
null
xtb_trading.py
lemassykoi/XTBApi
3b159f0b711e0d445a9cd7fec5c7a499cc623140
[ "MIT" ]
null
null
null
#!/usr/bin/env python3 # adaptation du script FXCM pour XTB ## debug = 1 ## DEBUG ENABLED OR DISABLED from XTBApi.api import * import time import pandas as pd import datetime as dt import talib.abstract as ta ## Maths modules import pyti.bollinger_bands as bb from pyti.relative_strength_index import rela...
40.459459
152
0.590874
2,250
19,461
5.027556
0.188
0.019095
0.030057
0.020156
0.475248
0.450583
0.378448
0.322843
0.282443
0.262995
0
0.029211
0.277016
19,461
480
153
40.54375
0.774769
0.221314
0
0.380682
0
0
0.156666
0.028805
0
0
0
0
0
1
0.065341
false
0.005682
0.048295
0
0.213068
0.085227
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1fa915f1d01ae50c5c5d775a6b404ccefbb0a1db
23,609
py
Python
datanode/src/storage_interface.py
airmap/InterUSS-Platform
fa19af360826b4dd7b841013c0c569a4f282919d
[ "Apache-2.0" ]
null
null
null
datanode/src/storage_interface.py
airmap/InterUSS-Platform
fa19af360826b4dd7b841013c0c569a4f282919d
[ "Apache-2.0" ]
1
2021-03-26T12:13:17.000Z
2021-03-26T12:13:17.000Z
datanode/src/storage_interface.py
isabella232/InterUSS-Platform
fa19af360826b4dd7b841013c0c569a4f282919d
[ "Apache-2.0" ]
2
2019-08-11T20:20:32.000Z
2021-03-26T12:01:43.000Z
"""The InterUSS Platform Data Node storage API server. This flexible and distributed system is used to connect multiple USSs operating in the same general area to share safety information while protecting the privacy of USSs, businesses, operator and consumers. The system is focused on facilitating communication among...
38.264182
80
0.656275
3,170
23,609
4.782019
0.162461
0.004222
0.00475
0.023748
0.509466
0.488687
0.465004
0.432153
0.399565
0.377663
0
0.008301
0.25503
23,609
616
81
38.326299
0.853593
0.400017
0
0.491228
0
0
0.168211
0.004746
0
0
0
0.00487
0
1
0.05848
false
0
0.032164
0.002924
0.134503
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1fb15d8fc5f2340ec039cd29cb846d5d8253d9c0
9,501
py
Python
scormxblock/scormxblock.py
Pearson-Advance/edx_xblock_scorm
eff4f18963424ac090662e03040dc8f003770cd3
[ "Apache-2.0" ]
null
null
null
scormxblock/scormxblock.py
Pearson-Advance/edx_xblock_scorm
eff4f18963424ac090662e03040dc8f003770cd3
[ "Apache-2.0" ]
1
2020-10-27T20:04:30.000Z
2020-10-27T20:04:30.000Z
scormxblock/scormxblock.py
Pearson-Advance/edx_xblock_scorm
eff4f18963424ac090662e03040dc8f003770cd3
[ "Apache-2.0" ]
null
null
null
import json import re import os import pkg_resources import zipfile import shutil import xml.etree.ElementTree as ET from django.conf import settings from django.template import Context, Template from webob import Response from xblock.core import XBlock from xblock.fields import Scope, String, Float, Boolean, Dict fr...
35.059041
131
0.592674
1,064
9,501
5.080827
0.193609
0.020718
0.017758
0.021088
0.303367
0.252312
0.181095
0.167037
0.155198
0.104514
0
0.00533
0.289127
9,501
270
132
35.188889
0.795084
0.022313
0
0.242291
0
0
0.151611
0.044347
0
0
0
0
0
1
0.066079
false
0.008811
0.057269
0.004405
0.259912
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1fb35315892b484eea92d588c1ea5a815edbedc1
4,861
py
Python
src/core/modules/stt.py
pyVoice/pyVoice
62e42a5c6307df2dd2d74bcd20ca64fd81c58851
[ "MIT" ]
1
2020-12-12T12:06:12.000Z
2020-12-12T12:06:12.000Z
src/core/modules/stt.py
pyVoice/pyVoice
62e42a5c6307df2dd2d74bcd20ca64fd81c58851
[ "MIT" ]
24
2021-02-08T19:44:44.000Z
2021-04-10T11:54:53.000Z
src/core/modules/stt.py
pyVoice/pyVoice
62e42a5c6307df2dd2d74bcd20ca64fd81c58851
[ "MIT" ]
null
null
null
""" **Speech to Text (STT) engine** Converts the user speech (audio) into text. """ import threading import traceback import speech_recognition as sr from src import settings from src.core.modules import log, tts, replying def setup() -> None: """ Initializes the STT engine Steps: 1. Creates a...
27.619318
102
0.632174
610
4,861
4.944262
0.254098
0.029178
0.009947
0.013926
0.331233
0.31996
0.265252
0.202255
0.202255
0.202255
0
0.005376
0.272989
4,861
175
103
27.777143
0.848048
0.307138
0
0.37037
0
0
0.151295
0
0
0
0
0
0
1
0.074074
false
0
0.061728
0
0.197531
0.024691
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1fb73cc1aa55107790f427e4e1e4f03476a6ace6
1,493
py
Python
packages/w3af/w3af/core/controllers/profiling/scan_log_analysis/data/errors.py
ZooAtmosphereGroup/HelloPackages
0ccffd33bf927b13d28c8f715ed35004c33465d9
[ "Apache-2.0" ]
null
null
null
packages/w3af/w3af/core/controllers/profiling/scan_log_analysis/data/errors.py
ZooAtmosphereGroup/HelloPackages
0ccffd33bf927b13d28c8f715ed35004c33465d9
[ "Apache-2.0" ]
null
null
null
packages/w3af/w3af/core/controllers/profiling/scan_log_analysis/data/errors.py
ZooAtmosphereGroup/HelloPackages
0ccffd33bf927b13d28c8f715ed35004c33465d9
[ "Apache-2.0" ]
null
null
null
import re from utils.output import KeyValueOutput ERRORS_RE = [re.compile('Unhandled exception "(.*?)"'), re.compile('traceback', re.IGNORECASE), re.compile('w3af-crash'), re.compile('scan was able to continue by ignoring those'), re.compile('The scan will stop')] ...
25.305085
95
0.592096
184
1,493
4.744565
0.440217
0.051546
0.041237
0.052692
0.066438
0.066438
0
0
0
0
0
0.004888
0.314802
1,493
58
96
25.741379
0.848485
0.148694
0
0.294118
0
0
0.172332
0
0
0
0
0
0
1
0.058824
false
0
0.058824
0
0.205882
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1fb8c0338db15cdfd4d8333778bf52ca725b2f55
5,925
py
Python
__main__.py
Naruto0/fplyst
af5c30a5bbd91ace21c3c5305c8e202ba016ba09
[ "MIT" ]
null
null
null
__main__.py
Naruto0/fplyst
af5c30a5bbd91ace21c3c5305c8e202ba016ba09
[ "MIT" ]
3
2021-03-22T17:12:14.000Z
2021-12-13T19:39:39.000Z
__main__.py
Naruto0/fplyst
af5c30a5bbd91ace21c3c5305c8e202ba016ba09
[ "MIT" ]
null
null
null
#! /usr/bin/python3 # # Usage: # # path/to/script$ python3 __main__.py -c <config_file> # # Will create 'YYYY_MM_DD_STREAMNAME_PLAYLIST.txt' file # which will contain currently captured song # # HH:MM Interpret - Song Name # # To capture whole playlist you have to # make crontab scheldule or widows/mac equivalen...
25.320513
89
0.606076
771
5,925
4.485084
0.324254
0.020243
0.011567
0.010989
0.081839
0.052632
0.039329
0.024292
0.024292
0.024292
0
0.008121
0.272574
5,925
233
90
25.429185
0.7942
0.244388
0
0.2
0
0
0.116886
0.004766
0
0
0
0.004292
0
1
0.071429
false
0.007143
0.071429
0
0.192857
0.064286
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1fbb637cd9392b8a2ffe427325fa61c758a9f423
14,341
py
Python
1_ps4/ps4b.py
gyalpodongo/6.0001_psets
b2e12d572d3382921a073e6712a337f98ade7c4a
[ "MIT" ]
null
null
null
1_ps4/ps4b.py
gyalpodongo/6.0001_psets
b2e12d572d3382921a073e6712a337f98ade7c4a
[ "MIT" ]
null
null
null
1_ps4/ps4b.py
gyalpodongo/6.0001_psets
b2e12d572d3382921a073e6712a337f98ade7c4a
[ "MIT" ]
null
null
null
# Problem Set 4B # Name: Gyalpo Dongo # Collaborators: # Time Spent: 9:00 # Late Days Used: 1 import string ### HELPER CODE ### def load_words(file_name): ''' file_name (string): the name of the file containing the list of words to load Returns: a list of valid words. Words are strings ...
36.214646
98
0.619064
1,834
14,341
4.690294
0.173391
0.037201
0.019182
0.009765
0.296908
0.255754
0.208207
0.185189
0.13927
0.104394
0
0.010245
0.305767
14,341
395
99
36.306329
0.853757
0.484206
0
0.192857
0
0
0.053052
0.004989
0
0
0
0.002532
0
1
0.135714
false
0
0.014286
0
0.271429
0.085714
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1fbe01d48c418a25dac0b1a8cdfdd4ff5a631b60
13,996
py
Python
tests/integration/cartography/intel/gcp/test_compute.py
sckevmit/cartography
fefb63b5ec97986dcc29038331d0e5b027b95d5f
[ "Apache-2.0" ]
2,322
2019-03-02T01:07:20.000Z
2022-03-31T20:39:12.000Z
tests/integration/cartography/intel/gcp/test_compute.py
sckevmit/cartography
fefb63b5ec97986dcc29038331d0e5b027b95d5f
[ "Apache-2.0" ]
462
2019-03-07T18:38:11.000Z
2022-03-31T14:55:20.000Z
tests/integration/cartography/intel/gcp/test_compute.py
sckevmit/cartography
fefb63b5ec97986dcc29038331d0e5b027b95d5f
[ "Apache-2.0" ]
246
2019-03-03T02:39:23.000Z
2022-02-24T09:46:38.000Z
import cartography.intel.gcp.compute import tests.data.gcp.compute TEST_UPDATE_TAG = 123456789 def _ensure_local_neo4j_has_test_instance_data(neo4j_session): cartography.intel.gcp.compute.load_gcp_instances( neo4j_session, tests.data.gcp.compute.TRANSFORMED_GCP_INSTANCES, TEST_UPDATE_TAG...
32.85446
118
0.627894
1,720
13,996
4.84593
0.112791
0.063347
0.077744
0.05183
0.716857
0.673905
0.620156
0.55189
0.475465
0.384763
0
0.026151
0.248642
13,996
425
119
32.931765
0.766451
0.034867
0
0.490141
0
0.042254
0.378952
0.2628
0
0
0
0
0.028169
1
0.039437
false
0
0.005634
0
0.053521
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1fc21aa494251b943ab4e4b535ca093a791a6af8
6,208
py
Python
gae/backend/services/slack/slack.py
jlapenna/bikebuds
6e2b54fa2e4fa03e5ff250ca779c269ccc49a2d8
[ "Apache-2.0" ]
9
2018-11-17T00:53:47.000Z
2021-03-16T05:18:01.000Z
gae/backend/services/slack/slack.py
jlapenna/bikebuds
6e2b54fa2e4fa03e5ff250ca779c269ccc49a2d8
[ "Apache-2.0" ]
8
2018-11-28T17:19:07.000Z
2022-02-26T17:46:09.000Z
gae/backend/services/slack/slack.py
jlapenna/bikebuds
6e2b54fa2e4fa03e5ff250ca779c269ccc49a2d8
[ "Apache-2.0" ]
null
null
null
# Copyright 2020 Google LLC # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # https://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, ...
32.846561
92
0.704897
789
6,208
5.301648
0.235741
0.017213
0.02032
0.027731
0.282333
0.219938
0.190294
0.160172
0.123835
0.105188
0
0.006578
0.191849
6,208
188
93
33.021277
0.827188
0.088273
0
0.20979
0
0
0.137088
0.011513
0
0
0
0
0
1
0.062937
false
0
0.132867
0
0.342657
0.006993
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1fc244ac9c29079630ffd294e5609b1a6c46e1ff
3,895
py
Python
ooobuild/lo/drawing/framework/tab_bar_button.py
Amourspirit/ooo_uno_tmpl
64e0c86fd68f24794acc22d63d8d32ae05dd12b8
[ "Apache-2.0" ]
null
null
null
ooobuild/lo/drawing/framework/tab_bar_button.py
Amourspirit/ooo_uno_tmpl
64e0c86fd68f24794acc22d63d8d32ae05dd12b8
[ "Apache-2.0" ]
null
null
null
ooobuild/lo/drawing/framework/tab_bar_button.py
Amourspirit/ooo_uno_tmpl
64e0c86fd68f24794acc22d63d8d32ae05dd12b8
[ "Apache-2.0" ]
null
null
null
# coding: utf-8 # # Copyright 2022 :Barry-Thomas-Paul: Moss # # 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 applicab...
33.869565
166
0.668293
478
3,895
5.303347
0.382845
0.023669
0.019724
0.033531
0.11716
0.091124
0.076134
0.030769
0
0
0
0.013979
0.246983
3,895
114
167
34.166667
0.850324
0.44647
0
0.066667
0
0
0.102839
0.062132
0
0
0
0
0
1
0.177778
false
0
0.066667
0
0.444444
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1fc41c98a94f4ecb65c5c9b1a3aac7dc614e2662
5,087
py
Python
shared/tools/snapshot/utils.py
DougMahoney/metatools
112340102962ff0c3e323564357cc4e848939cf7
[ "Apache-2.0" ]
12
2020-04-10T07:09:24.000Z
2022-03-04T09:22:40.000Z
shared/tools/snapshot/utils.py
DougMahoney/metatools
112340102962ff0c3e323564357cc4e848939cf7
[ "Apache-2.0" ]
5
2020-05-16T18:22:23.000Z
2022-03-29T13:19:27.000Z
shared/tools/snapshot/utils.py
DougMahoney/metatools
112340102962ff0c3e323564357cc4e848939cf7
[ "Apache-2.0" ]
2
2020-12-10T15:17:40.000Z
2021-12-02T17:34:56.000Z
""" Extraction utilities and supporting functions Some operations are used frequently or repeated enough to be factored out. Note that SQL can be used via the POORSQL_BINARY_PATH Download the binary from http://architectshack.com/PoorMansTSqlFormatter.ashx It's a phenominal utility that brilliantly normaliz...
25.691919
94
0.716139
692
5,087
5.231214
0.403179
0.017956
0.014088
0.018785
0.01105
0
0
0
0
0
0
0.00553
0.182426
5,087
198
95
25.691919
0.864871
0.275015
0
0.216667
0
0
0.049559
0.009086
0
0
0
0
0
1
0.083333
false
0.016667
0.05
0.016667
0.291667
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1fc8f64a1c48e617dc27ddaba536434b9f8ea44b
4,915
py
Python
Configuration/GlobalRuns/python/reco_TLR_311X.py
ckamtsikis/cmssw
ea19fe642bb7537cbf58451dcf73aa5fd1b66250
[ "Apache-2.0" ]
852
2015-01-11T21:03:51.000Z
2022-03-25T21:14:00.000Z
Configuration/GlobalRuns/python/reco_TLR_311X.py
ckamtsikis/cmssw
ea19fe642bb7537cbf58451dcf73aa5fd1b66250
[ "Apache-2.0" ]
30,371
2015-01-02T00:14:40.000Z
2022-03-31T23:26:05.000Z
Configuration/GlobalRuns/python/reco_TLR_311X.py
ckamtsikis/cmssw
ea19fe642bb7537cbf58451dcf73aa5fd1b66250
[ "Apache-2.0" ]
3,240
2015-01-02T05:53:18.000Z
2022-03-31T17:24:21.000Z
import FWCore.ParameterSet.Config as cms def customiseCommon(process): ##################################################################################################### #### #### Top level replaces for handling strange scenarios of early collisions #### ## TRACKING: process.newSeedFr...
36.407407
107
0.545677
321
4,915
8.333333
0.376947
0.053458
0.059813
0.065421
0.437383
0.419813
0.379439
0.279252
0.248598
0.248598
0
0.017907
0.125127
4,915
134
108
36.679104
0.604186
0.086063
0
0.403509
0
0
0.010971
0
0
0
0
0
0
1
0.192982
false
0
0.070175
0.035088
0.45614
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1fcc73246e5b2e2deb6ef1a5498a653dfdea012b
3,094
py
Python
pynm/feature/extract/nmf.py
ohtaman/pynm
b003962201e4270d0dab681ede37f2d8edd560f2
[ "MIT" ]
1
2018-08-16T20:48:52.000Z
2018-08-16T20:48:52.000Z
pynm/feature/extract/nmf.py
ohtaman/pynm
b003962201e4270d0dab681ede37f2d8edd560f2
[ "MIT" ]
5
2015-01-12T20:40:46.000Z
2017-11-17T01:27:41.000Z
pynm/feature/extract/nmf.py
ohtaman/pynm
b003962201e4270d0dab681ede37f2d8edd560f2
[ "MIT" ]
null
null
null
# -*- coding:utf-8 -*- import numpy import numpy.random import numpy.linalg from . import svd def svd_init(matrix, dim, seed=None): u, s, v = svd.svd(matrix, dim) ss = numpy.sqrt(numpy.diag(s)) return numpy.maximum(0.001, u.dot(ss)), numpy.maximum(0.001, ss.dot(v)) def random_init(matrix, dim, seed=Non...
29.75
94
0.597931
448
3,094
4.042411
0.241071
0.012148
0.019326
0.019879
0.24296
0.201546
0.153506
0.073992
0.032027
0
0
0.023612
0.260827
3,094
103
95
30.038835
0.768255
0.19554
0
0.188406
0
0
0.007407
0
0
0
0
0
0
1
0.086957
false
0
0.057971
0
0.231884
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1fccf8df9831cb035ab2861081b74267181cefc9
6,052
py
Python
examples/demo_livepeer.py
scout-cool/Bubbletea
f0312d6f1c7fde4098d500e811f0503796973d07
[ "Apache-2.0" ]
10
2021-08-29T14:58:09.000Z
2022-02-07T21:03:07.000Z
examples/demo_livepeer.py
scout-cool/Bubbletea
f0312d6f1c7fde4098d500e811f0503796973d07
[ "Apache-2.0" ]
null
null
null
examples/demo_livepeer.py
scout-cool/Bubbletea
f0312d6f1c7fde4098d500e811f0503796973d07
[ "Apache-2.0" ]
null
null
null
import datetime import datetime from altair.vegalite.v4.schema.core import Legend import pandas from pandas.core.frame import DataFrame import streamlit as st import time import bubbletea st.header("LIVEPEER Stake Movement") urlvars = bubbletea.parse_url_var([{'key':'startdate','type':'datetime'}, {'key':'enddate','t...
28.682464
117
0.594019
676
6,052
5.131657
0.236686
0.039204
0.027674
0.044393
0.400404
0.346786
0.201787
0.182762
0.158547
0.158547
0
0.00811
0.266523
6,052
210
118
28.819048
0.773372
0.008262
0
0.331522
0
0
0.229
0.016667
0
0
0
0
0
1
0.005435
false
0.016304
0.043478
0
0.054348
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1fd17f1089fdee8a486a2a65c3fb934cc9195151
1,072
py
Python
sml_iris_knn_dtc.py
drishtim17/supervisedML
3981d283a9937bfce793237c171fa95764846558
[ "Apache-2.0" ]
null
null
null
sml_iris_knn_dtc.py
drishtim17/supervisedML
3981d283a9937bfce793237c171fa95764846558
[ "Apache-2.0" ]
null
null
null
sml_iris_knn_dtc.py
drishtim17/supervisedML
3981d283a9937bfce793237c171fa95764846558
[ "Apache-2.0" ]
null
null
null
#!/usr/bin/python3 import sklearn from sklearn.datasets import load_iris from sklearn.neighbors import KNeighborsClassifier from sklearn.model_selection import train_test_split from sklearn import tree from sklearn.metrics import accuracy_score #loading iris iris=load_iris() #traning flowers.features is stored in i...
24.363636
99
0.841418
152
1,072
5.769737
0.407895
0.062714
0.051311
0.031927
0.120867
0
0
0
0
0
0
0.004065
0.08209
1,072
43
100
24.930233
0.887195
0.251866
0
0
0
0
0
0
0
0
0
0
0
1
0
false
0
0.285714
0
0.285714
0.238095
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1fd3b3ac45b4ed570227a76c3f4f622771cac325
2,762
py
Python
Python/Exercises/Humanize/humanize.py
Gjacquenot/training-material
16b29962bf5683f97a1072d961dd9f31e7468b8d
[ "CC-BY-4.0" ]
115
2015-03-23T13:34:42.000Z
2022-03-21T00:27:21.000Z
Python/Exercises/Humanize/humanize.py
Gjacquenot/training-material
16b29962bf5683f97a1072d961dd9f31e7468b8d
[ "CC-BY-4.0" ]
56
2015-02-25T15:04:26.000Z
2022-01-03T07:42:48.000Z
Python/Exercises/Humanize/humanize.py
Gjacquenot/training-material
16b29962bf5683f97a1072d961dd9f31e7468b8d
[ "CC-BY-4.0" ]
59
2015-11-26T11:44:51.000Z
2022-03-21T00:27:22.000Z
#!/usr/bin/env python def humanize(n, base=10, digits=1, unit=''): '''convert a floating point number to a human-readable format Parameters ---------- n : float or str number to convert, it can a string representation of a floating point number base : int base to use, eith...
28.474227
77
0.513034
354
2,762
3.932203
0.330508
0.038793
0.034483
0.057471
0.119253
0.08908
0.08908
0.048851
0
0
0
0.051991
0.345402
2,762
96
78
28.770833
0.71792
0.272991
0
0.04
0
0
0.113137
0
0
0
0
0
0
1
0.04
false
0
0.06
0
0.16
0.04
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1fd529b1fbfbcec29e94685aeef6fbda0d26c559
1,337
py
Python
data/Latent.py
YoungjuNa-KR/Gaze_estimator_implementation
95482db40ddef413870f51dadc907910d624ee6e
[ "MIT" ]
null
null
null
data/Latent.py
YoungjuNa-KR/Gaze_estimator_implementation
95482db40ddef413870f51dadc907910d624ee6e
[ "MIT" ]
null
null
null
data/Latent.py
YoungjuNa-KR/Gaze_estimator_implementation
95482db40ddef413870f51dadc907910d624ee6e
[ "MIT" ]
1
2022-02-03T11:11:21.000Z
2022-02-03T11:11:21.000Z
import os import PIL import torch from glob import glob from torch.utils.data import DataLoader from torchvision.transforms.functional import pil_to_tensor class Latent(torch.utils.data.Dataset): def __init__(self, dir_name, transforms=None): # dataset 디렉토리를 기반으로 parse.data_train, test에 따라서 # 각각 다...
29.711111
68
0.604338
189
1,337
4.132275
0.460317
0.038412
0.042254
0
0
0
0
0
0
0
0
0
0.293194
1,337
44
69
30.386364
0.826455
0.169783
0
0
0
0
0.036298
0
0
0
0
0
0
1
0.111111
false
0
0.222222
0.037037
0.444444
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1fd676c1868fb5496119162edb66de118a176730
876
py
Python
scripts/mklanguages.py
yasen-m/dosage
81fe088621ad335cac2a53fcbc7b9b37f49ddce2
[ "MIT" ]
null
null
null
scripts/mklanguages.py
yasen-m/dosage
81fe088621ad335cac2a53fcbc7b9b37f49ddce2
[ "MIT" ]
null
null
null
scripts/mklanguages.py
yasen-m/dosage
81fe088621ad335cac2a53fcbc7b9b37f49ddce2
[ "MIT" ]
null
null
null
#!/usr/bin/python # update languages.py from pycountry import os import codecs import pycountry basepath = os.path.dirname(os.path.dirname(__file__)) def main(): """Update language information in dosagelib/languages.py.""" fn =os.path.join(basepath, 'dosagelib', 'languages.py') encoding = 'utf-8' with...
29.2
83
0.634703
115
876
4.713043
0.4
0.066421
0.055351
0.055351
0
0
0
0
0
0
0
0.011396
0.19863
876
29
84
30.206897
0.760684
0.152968
0
0
0
0
0.191781
0
0
0
0
0
0
1
0.105263
false
0
0.157895
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
1fd6b807f6071d9b5d2c510c8209a51bbbc35084
531
py
Python
reference/for_and_while.py
SeanSyue/TensorflowReferences
2c93f4c770e2713ef4769f287e022d03e7097188
[ "MIT" ]
null
null
null
reference/for_and_while.py
SeanSyue/TensorflowReferences
2c93f4c770e2713ef4769f287e022d03e7097188
[ "MIT" ]
null
null
null
reference/for_and_while.py
SeanSyue/TensorflowReferences
2c93f4c770e2713ef4769f287e022d03e7097188
[ "MIT" ]
null
null
null
import tensorflow as tf x = tf.Variable(0, name='x') model = tf.global_variables_initializer() with tf.Session() as session: for i in range(5): session.run(model) x = x + 1 print(session.run(x)) x = tf.Variable(0., name='x') threshold = tf.constant(5.) model = tf.glob...
19.666667
46
0.589454
76
531
4.039474
0.355263
0.162866
0.071661
0.078176
0.469055
0.469055
0.358306
0.358306
0.358306
0.358306
0
0.015666
0.278719
531
26
47
20.423077
0.785901
0
0
0.470588
0
0
0.003968
0
0
0
0
0
0
1
0
false
0
0.058824
0
0.058824
0.117647
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1fd7ed8a83b56f175881d6f318fa389d67ee450a
732
py
Python
bewerte/muendlich.py
jupfi81/NotenManager
ee96a41088bb898c025aed7b3c904741cb71d004
[ "MIT" ]
null
null
null
bewerte/muendlich.py
jupfi81/NotenManager
ee96a41088bb898c025aed7b3c904741cb71d004
[ "MIT" ]
null
null
null
bewerte/muendlich.py
jupfi81/NotenManager
ee96a41088bb898c025aed7b3c904741cb71d004
[ "MIT" ]
null
null
null
"""Berechnet die mündliche Note""" import csv with open('bewertung.csv', encoding='utf-8', mode='r') as bewertung: TABELLE = [] DATA = csv.reader(bewertung, delimiter=',') for row in DATA: TABELLE.append([element.strip() for element in row]) OUTPUT = [TABELLE[0] + ["Note"]] del TABELLE[0] ...
31.826087
92
0.562842
102
732
4.039216
0.421569
0.07767
0.058252
0.072816
0.092233
0
0
0
0
0
0
0.039179
0.26776
732
22
93
33.272727
0.729478
0.038251
0
0
0
0
0.055874
0
0
0
0
0
0
1
0
false
0
0.055556
0
0.055556
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1fd7f7aa485ce2ad0b848a0e2bbaa8cf36a6c24a
410
py
Python
python3/tests/test_edit_distance.py
qianbinbin/leetcode
915cecab0c940cd13847683ec55b17b77eb0f39b
[ "MIT" ]
4
2018-03-05T02:27:16.000Z
2021-03-15T14:19:44.000Z
python3/tests/test_edit_distance.py
qianbinbin/leetcode
915cecab0c940cd13847683ec55b17b77eb0f39b
[ "MIT" ]
null
null
null
python3/tests/test_edit_distance.py
qianbinbin/leetcode
915cecab0c940cd13847683ec55b17b77eb0f39b
[ "MIT" ]
2
2018-07-22T10:32:10.000Z
2018-10-20T03:14:28.000Z
from unittest import TestCase from leetcodepy.edit_distance import * solution1 = Solution1() word11 = "horse" word12 = "ros" expected1 = 3 word21 = "intention" word22 = "execution" expected2 = 5 class TestEditDistance(TestCase): def test1(self): self.assertEqual(expected1, solution1.minDistance(wo...
17.083333
74
0.731707
43
410
6.953488
0.627907
0.100334
0
0
0
0
0
0
0
0
0
0.079179
0.168293
410
23
75
17.826087
0.797654
0
0
0
0
0
0.063415
0
0
0
0
0
0.153846
1
0.076923
false
0
0.153846
0
0.307692
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1fd8f8fea0aa37bc2adfbcbf6dda99e537d99a7f
805
py
Python
pageobject/commands/index.py
lukas-linhart/pageobject
6ae83680ae62a94f93cefc394e4f3cc6999aeead
[ "MIT" ]
1
2017-01-12T06:15:36.000Z
2017-01-12T06:15:36.000Z
pageobject/commands/index.py
lukas-linhart/pageobject
6ae83680ae62a94f93cefc394e4f3cc6999aeead
[ "MIT" ]
null
null
null
pageobject/commands/index.py
lukas-linhart/pageobject
6ae83680ae62a94f93cefc394e4f3cc6999aeead
[ "MIT" ]
null
null
null
def index(self, value): """ Return index of the first child containing the specified value. :param str value: text value to look for :returns: index of the first child containing the specified value :rtype: int :raises ValueError: if the value is not found """ self.logger.info('getting ...
47.352941
116
0.690683
119
805
4.563025
0.336134
0.077348
0.081031
0.12523
0.548803
0.548803
0.443831
0.38674
0.38674
0.213628
0
0
0.185093
805
16
117
50.3125
0.827744
0.284472
0
0
0
0
0.377532
0
0
0
0
0
0
1
0.142857
false
0
0
0
0.285714
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1fda8ca8896b2d1bcde84055f16e53f955e23e9c
2,724
py
Python
vlsopt/data_factory/transaction_factory.py
violas-core/bvexchange
74cf3197aad02e0f5e2dac457266d11c9c8cc746
[ "MIT" ]
null
null
null
vlsopt/data_factory/transaction_factory.py
violas-core/bvexchange
74cf3197aad02e0f5e2dac457266d11c9c8cc746
[ "MIT" ]
null
null
null
vlsopt/data_factory/transaction_factory.py
violas-core/bvexchange
74cf3197aad02e0f5e2dac457266d11c9c8cc746
[ "MIT" ]
1
2022-01-05T04:39:47.000Z
2022-01-05T04:39:47.000Z
#!/usr/bin/python3 import operator import sys import json import os sys.path.append(os.path.join(os.path.dirname(os.path.abspath(__file__)), "./")) sys.path.append(os.path.join(os.path.dirname(os.path.abspath(__file__)), "../")) sys.path.append(os.path.join(os.path.dirname(os.path.abspath(__file__)), "../../")) sys.pat...
33.62963
96
0.551762
281
2,724
5.074733
0.256228
0.050491
0.036466
0.042076
0.148668
0.148668
0.148668
0.148668
0.148668
0.148668
0
0.000534
0.312041
2,724
80
97
34.05
0.760406
0.006241
0
0
0
0
0.207394
0.085767
0
0
0
0
0
1
0.078125
false
0
0.09375
0.03125
0.25
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1fdadaa704a4a57bab069bbf9519d57e9bc28d25
3,703
py
Python
tests/test_source.py
j18ter/exchangelib
afb0df65c5533999bca92e25be4c00de5c03043c
[ "BSD-2-Clause" ]
null
null
null
tests/test_source.py
j18ter/exchangelib
afb0df65c5533999bca92e25be4c00de5c03043c
[ "BSD-2-Clause" ]
null
null
null
tests/test_source.py
j18ter/exchangelib
afb0df65c5533999bca92e25be4c00de5c03043c
[ "BSD-2-Clause" ]
null
null
null
from exchangelib.errors import ( ErrorAccessDenied, ErrorFolderNotFound, ErrorInvalidOperation, ErrorItemNotFound, ErrorNoPublicFolderReplicaAvailable, ) from exchangelib.properties import EWSElement from .common import EWSTest class CommonTest(EWSTest): def test_magic(self): self.ass...
34.287037
105
0.533081
309
3,703
6.197411
0.430421
0.063185
0.049608
0.036031
0.032376
0
0
0
0
0
0
0
0.387254
3,703
107
106
34.607477
0.843984
0.063192
0
0.214286
0
0
0.174076
0.079099
0
0
0
0
0.061224
1
0.020408
false
0
0.040816
0
0.071429
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1fdb3bda49808628500a9864a821b84e3138f89c
735
py
Python
{{cookiecutter.project_slug}}/app/utils/mail.py
Bexils/fastapi-project-template
1d6937c5adce7603c77e01f8560032082392fdbd
[ "MIT" ]
4
2021-04-04T23:19:06.000Z
2021-04-10T21:32:23.000Z
{{cookiecutter.project_slug}}/app/utils/mail.py
Bexils/fastapi-project-template
1d6937c5adce7603c77e01f8560032082392fdbd
[ "MIT" ]
null
null
null
{{cookiecutter.project_slug}}/app/utils/mail.py
Bexils/fastapi-project-template
1d6937c5adce7603c77e01f8560032082392fdbd
[ "MIT" ]
null
null
null
import os from datetime import datetime from pathlib import Path from pydantic import EmailStr def send_dummy_mail(subject: str, message: str, to: EmailStr): current_path = os.getcwd() filename = f'{datetime.now().timestamp()} - {subject}.txt' email_text = f'''Subject: {subject} From: no-reply@email.com T...
28.269231
64
0.672109
101
735
4.722772
0.425743
0.0587
0.041929
0.071279
0.318658
0.318658
0.205451
0.205451
0.205451
0.205451
0
0
0.204082
735
26
65
28.269231
0.815385
0
0
0.181818
0
0
0.180707
0.038043
0
0
0
0
0
1
0.045455
false
0
0.181818
0
0.272727
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1fe22fd049d8e5e23653953f62233abe237a47e8
16,692
py
Python
bloodbank_rl/pyomo_models/stochastic_model_runner.py
joefarrington/bloodbank_rl
f285581145034b498f01c9b44f95437ceddb042a
[ "MIT" ]
null
null
null
bloodbank_rl/pyomo_models/stochastic_model_runner.py
joefarrington/bloodbank_rl
f285581145034b498f01c9b44f95437ceddb042a
[ "MIT" ]
null
null
null
bloodbank_rl/pyomo_models/stochastic_model_runner.py
joefarrington/bloodbank_rl
f285581145034b498f01c9b44f95437ceddb042a
[ "MIT" ]
null
null
null
import numpy as np import pandas as pd import pyomo.environ as pyo import mpisppy.utils.sputils as sputils from mpisppy.opt.ef import ExtensiveForm from pathlib import Path import os import sys path_root = Path(os.path.abspath(__file__)).parents[2] sys.path.append(str(path_root)) from bloodbank_rl.environments.plat...
37.679458
107
0.557453
1,917
16,692
4.5759
0.14554
0.053352
0.03762
0.052668
0.499886
0.437187
0.400023
0.337323
0.251026
0.209758
0
0.006013
0.332495
16,692
442
108
37.764706
0.781278
0.054278
0
0.22191
0
0
0.155374
0.051199
0
0
0
0.002262
0
1
0.05618
false
0
0.02809
0.008427
0.160112
0.019663
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1fe41f5dc40be297773f566df8109a75b70ca3b8
3,623
py
Python
ch1/tictactoe.py
T0nyX1ang/Reinforcement-Learning
a86ab92ee628b95c7dbe432c079b7ce04b5e982a
[ "MIT" ]
null
null
null
ch1/tictactoe.py
T0nyX1ang/Reinforcement-Learning
a86ab92ee628b95c7dbe432c079b7ce04b5e982a
[ "MIT" ]
null
null
null
ch1/tictactoe.py
T0nyX1ang/Reinforcement-Learning
a86ab92ee628b95c7dbe432c079b7ce04b5e982a
[ "MIT" ]
null
null
null
import random import json class TTTGame(object): def __init__(self): self._board = [0] * 9 self._end = False with open('learning.json', 'r') as f: self._state = json.loads(f.read()) self._alpha = 0.05 def judge(self, state): if (sum(state[0: 3]) == 3 or \ sum(state[3: 6]) == 3 or \ sum(state[6::]...
27.037313
134
0.619928
576
3,623
3.71875
0.184028
0.134454
0.039216
0.071895
0.592437
0.562092
0.537815
0.523343
0.495798
0.471522
0
0.037847
0.205079
3,623
133
135
27.240602
0.705903
0.048027
0
0.425
0
0
0.042139
0
0
0
0
0
0
1
0.075
false
0
0.016667
0
0.166667
0.083333
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1fe6e5bdf88233acf9a9c841722eff52d327f1f2
13,160
py
Python
Server.py
HackintoshwithUbuntu/Python-Chat-App
d5af370e33a092c52702efed6b1074d458c593ac
[ "MIT" ]
2
2021-08-30T03:19:10.000Z
2021-09-06T21:51:02.000Z
Server.py
HackintoshwithUbuntu/Python-Chat-App
d5af370e33a092c52702efed6b1074d458c593ac
[ "MIT" ]
null
null
null
Server.py
HackintoshwithUbuntu/Python-Chat-App
d5af370e33a092c52702efed6b1074d458c593ac
[ "MIT" ]
null
null
null
# Imports import socket # Communication import threading # Communication with multiple users at once import pickle # Serialising data import hashlib # Hashing passwords from Crypto.Cipher import AES # AES encryption algorithms from Crypto.Random import get_random_bytes # For generating random keys and nonces...
38.820059
115
0.572188
1,491
13,160
4.932931
0.262911
0.008973
0.016315
0.026105
0.13637
0.090551
0.076683
0.055201
0.034534
0.02828
0
0.005237
0.347036
13,160
339
116
38.820059
0.850692
0.336018
0
0.234637
0
0
0.104252
0
0
0
0
0
0
1
0.044693
false
0.039106
0.03352
0
0.106145
0.122905
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1fec0bf47c009cdb0ca6fac21df153c55c6c1431
46,269
py
Python
bot/utils/trackmania.py
NottCurious/TMIndiaBot
824c171fa2f41aa21631796c384f70a34a721364
[ "MIT" ]
1
2022-02-12T16:40:17.000Z
2022-02-12T16:40:17.000Z
bot/utils/trackmania.py
NottCurious/TMIndiaBot
824c171fa2f41aa21631796c384f70a34a721364
[ "MIT" ]
78
2021-10-14T05:32:54.000Z
2022-01-21T09:22:37.000Z
bot/utils/trackmania.py
NottCurious/TMIndiaBot
824c171fa2f41aa21631796c384f70a34a721364
[ "MIT" ]
null
null
null
import asyncio import json import os import shutil import typing from datetime import datetime, timezone, timedelta from matplotlib import pyplot as plt import cv2 import country_converter as coco import flag import requests import discord from bot.api import APIClient from bot.log import get_logger from bot.utils.co...
35.756569
195
0.578832
5,491
46,269
4.674194
0.094336
0.054547
0.019988
0.013909
0.524936
0.399595
0.316606
0.253682
0.216123
0.184797
0
0.017766
0.307787
46,269
1,293
196
35.784223
0.783596
0.028118
0
0.293156
0
0.00715
0.27097
0.041654
0
0
0.000366
0
0
1
0.043922
false
0.003064
0.017365
0.001021
0.11951
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1fed6ebbcca1ccb5af62d7ab28474d73bafe114f
4,535
py
Python
src/vehicle_core/model/throttle_model.py
decabyte/vehicle_core
623e1e993445713ab2ba625ac54be150077c2f1e
[ "BSD-3-Clause" ]
1
2016-12-14T11:48:02.000Z
2016-12-14T11:48:02.000Z
src/vehicle_core/model/throttle_model.py
decabyte/vehicle_core
623e1e993445713ab2ba625ac54be150077c2f1e
[ "BSD-3-Clause" ]
null
null
null
src/vehicle_core/model/throttle_model.py
decabyte/vehicle_core
623e1e993445713ab2ba625ac54be150077c2f1e
[ "BSD-3-Clause" ]
null
null
null
#!/usr/bin/env python # -*- coding: utf-8 -*- # Software License Agreement (BSD License) # # Copyright (c) 2014, Ocean Systems Laboratory, Heriot-Watt University, UK. # All rights reserved. # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the follow...
40.855856
118
0.714443
637
4,535
5.00314
0.416013
0.021964
0.023533
0.018826
0.131785
0.085974
0.085974
0.042673
0.042673
0.042673
0
0.00416
0.204851
4,535
110
119
41.227273
0.879645
0.743771
0
0
0
0
0
0
0
0
0
0
0
1
0.1
false
0
0.2
0
0.4
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1fee9ed72e23e0f9892bd14d8b33f1a360d24471
1,605
py
Python
social_friends_finder/backends/vkontakte_backend.py
haremmaster/django-social-friends-finder
cad63349b19b3c301626c24420ace13c63f45ad7
[ "BSD-3-Clause" ]
19
2015-01-01T16:23:06.000Z
2020-01-02T22:42:17.000Z
social_friends_finder/backends/vkontakte_backend.py
haremmaster/django-social-friends-finder
cad63349b19b3c301626c24420ace13c63f45ad7
[ "BSD-3-Clause" ]
2
2015-01-01T16:34:59.000Z
2015-03-26T10:30:59.000Z
social_friends_finder/backends/vkontakte_backend.py
laplacesdemon/django-social-friends-finder
cad63349b19b3c301626c24420ace13c63f45ad7
[ "BSD-3-Clause" ]
11
2015-01-16T18:39:34.000Z
2021-08-13T00:46:41.000Z
from social_friends_finder.backends import BaseFriendsProvider from social_friends_finder.utils import setting if not setting("SOCIAL_FRIENDS_USING_ALLAUTH", False): from social_auth.backends.contrib.vk import VKOAuth2Backend USING_ALLAUTH = False else: from allauth.socialaccount.models import SocialToken, ...
33.4375
114
0.684112
184
1,605
5.804348
0.380435
0.05618
0.031835
0.043071
0
0
0
0
0
0
0
0.001663
0.250467
1,605
47
115
34.148936
0.886118
0.300312
0
0.090909
0
0
0.103314
0.02729
0
0
0
0
0
1
0.090909
false
0
0.227273
0
0.454545
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1ff9b69a4019a1762d86b4de69764598a30ea2b6
8,228
py
Python
dial/metrics.py
neukg/KAT-TSLF
91bff10312ba5fbbd46978b268a1c97a5d627dcd
[ "MIT" ]
11
2021-11-19T06:17:10.000Z
2022-03-11T07:12:30.000Z
dial/metrics.py
neukg/KAT-TSLF
91bff10312ba5fbbd46978b268a1c97a5d627dcd
[ "MIT" ]
3
2021-11-20T14:00:24.000Z
2022-03-03T19:41:01.000Z
dial/metrics.py
neukg/KAT-TSLF
91bff10312ba5fbbd46978b268a1c97a5d627dcd
[ "MIT" ]
null
null
null
from nltk.translate.bleu_score import corpus_bleu, sentence_bleu, SmoothingFunction from nltk import word_tokenize # import language_evaluation from typing import List from collections import defaultdict, Counter import re import math import sys def mean(lst): return sum(lst) / len(lst) def _calc_ngram_dict(tok...
35.465517
113
0.653986
1,174
8,228
4.356899
0.167802
0.043011
0.037146
0.030499
0.295797
0.235582
0.199805
0.141935
0.12043
0.090714
0
0.045398
0.223627
8,228
232
114
35.465517
0.755322
0.092124
0
0.126984
0
0.010582
0.028099
0.00484
0
0
0
0
0.005291
1
0.111111
false
0
0.037037
0.026455
0.253968
0.010582
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1ffb6e885c207ea205ef242e09f2cabe5866ad26
3,705
py
Python
cameraToWorld.py
blguweb/Tap-Tap-computer
4e2007b5a31e6d5f902b1e3ca58206870331ef07
[ "MIT" ]
null
null
null
cameraToWorld.py
blguweb/Tap-Tap-computer
4e2007b5a31e6d5f902b1e3ca58206870331ef07
[ "MIT" ]
null
null
null
cameraToWorld.py
blguweb/Tap-Tap-computer
4e2007b5a31e6d5f902b1e3ca58206870331ef07
[ "MIT" ]
null
null
null
#!/usr/bin/env python3 # -*- coding: utf-8 -*- import os from typing import NoReturn import cv2 as cv import numpy as np from numpy import mat import xml.etree.ElementTree as ET import math camera_angle = 315 camera_intrinsic = { # # 相机内参矩阵 # 相机内参矩阵 matlab 求得 "camera_matrix": [871.08632815...
33.080357
129
0.550877
508
3,705
3.877953
0.326772
0.025381
0.025888
0.022335
0.164975
0.070558
0.045178
0.041117
0
0
0
0.123357
0.302024
3,705
112
130
33.080357
0.638438
0.145479
0
0
0
0
0.052214
0
0
0
0
0
0
1
0.078947
false
0
0.092105
0
0.25
0.131579
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1ffb6f2d2eca765ba18ee0ccc397d70767e06533
5,004
py
Python
compilers/labs/lab2/gui.py
vampy/university
9496cb63594dcf1cc2cec8650b8eee603f85fdab
[ "MIT" ]
6
2015-06-22T19:43:13.000Z
2019-07-15T18:08:41.000Z
compilers/labs/lab2/gui.py
vampy/university
9496cb63594dcf1cc2cec8650b8eee603f85fdab
[ "MIT" ]
null
null
null
compilers/labs/lab2/gui.py
vampy/university
9496cb63594dcf1cc2cec8650b8eee603f85fdab
[ "MIT" ]
1
2015-09-26T09:01:54.000Z
2015-09-26T09:01:54.000Z
#!/usr/bin/python import os from log import Log from enum import IntEnum, unique from grammar import Grammar from automaton import FiniteAutomaton @unique class Command(IntEnum): GRAMMAR_READ = 1 GRAMMAR_DISPLAY = 2 GRAMMAR_VERIFY = 3 AUTOMATON_READ = 4 AUTOMATON_DISPLAY = 5 CONVERT_RG_TO_FA...
33.139073
108
0.552158
559
5,004
4.78712
0.187835
0.036996
0.06577
0.044843
0.396861
0.245889
0.188341
0.176756
0.085949
0.085949
0
0.008634
0.351918
5,004
150
109
33.36
0.816528
0.010991
0
0.310345
0
0
0.082103
0
0
0
0
0
0
1
0.043103
false
0
0.043103
0
0.241379
0.198276
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1ffec07dcf5a4c57c0d689934f15fff735336375
2,382
py
Python
ml-scripts/ss_calib/scripts/ss_charge_cali.py
YashengFu/exo-200_scripts
d33a1a2eeda5f072409656b96e8730f2de53ee0b
[ "MIT" ]
null
null
null
ml-scripts/ss_calib/scripts/ss_charge_cali.py
YashengFu/exo-200_scripts
d33a1a2eeda5f072409656b96e8730f2de53ee0b
[ "MIT" ]
null
null
null
ml-scripts/ss_calib/scripts/ss_charge_cali.py
YashengFu/exo-200_scripts
d33a1a2eeda5f072409656b96e8730f2de53ee0b
[ "MIT" ]
null
null
null
import numpy as np import time import argparse import pandas as pd import matplotlib matplotlib.use("Agg") import matplotlib.pyplot as plt from scipy import special from tqdm import tqdm from scipy.optimize import curve_fit from utils.build_hist import build_hist class SS_Charge: """ read calibration data and ...
38.419355
184
0.673804
360
2,382
4.163889
0.369444
0.046698
0.045364
0.036024
0.029353
0
0
0
0
0
0
0.02697
0.206129
2,382
61
185
39.04918
0.765732
0.026029
0
0
0
0.019231
0.107205
0.043403
0
0
0
0
0
1
0.096154
false
0
0.192308
0
0.365385
0.038462
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
1fff4ed247e76eafdf9461ae3d7ab7dc88f2b73c
97,747
py
Python
ExoplanetPocketknife.py
ScottHull/Exoplanet-Pocketknife
15b49ff3612adc3b31a78c27379fb8b2f47c6c8f
[ "CC0-1.0" ]
null
null
null
ExoplanetPocketknife.py
ScottHull/Exoplanet-Pocketknife
15b49ff3612adc3b31a78c27379fb8b2f47c6c8f
[ "CC0-1.0" ]
null
null
null
ExoplanetPocketknife.py
ScottHull/Exoplanet-Pocketknife
15b49ff3612adc3b31a78c27379fb8b2f47c6c8f
[ "CC0-1.0" ]
null
null
null
# python /usr/bin/env/python # /// The Exoplanet Pocketknife # /// Scott D. Hull, The Ohio State University 2015-2017 # /// All usage must include proper citation and a link to the Github repository # /// https://github.com/ScottHull/Exoplanet-Pocketknife import os, csv, time, sys, shutil, subprocess from threading ...
46.7689
207
0.541234
11,946
97,747
4.141972
0.093253
0.016734
0.020049
0.005497
0.655032
0.597534
0.547757
0.512409
0.478779
0.445938
0
0.061092
0.32932
97,747
2,089
208
46.791288
0.693671
0.121917
0
0.455182
0
0.023109
0.195014
0.073073
0
0
0
0
0
1
0.014706
false
0.035714
0.005602
0
0.022409
0.07493
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
9500f8ddc8a192d5b326bf23ad973aa2e9a8109b
4,074
py
Python
tools/extract_observable.py
pauxy-qmc/pauxy
1da80284284769b59361c73cfa3c2d914c74a73f
[ "Apache-2.0" ]
16
2020-08-05T17:17:17.000Z
2022-03-18T04:06:18.000Z
tools/extract_observable.py
pauxy-qmc/pauxy
1da80284284769b59361c73cfa3c2d914c74a73f
[ "Apache-2.0" ]
4
2020-05-17T21:28:20.000Z
2021-04-22T18:05:50.000Z
tools/extract_observable.py
pauxy-qmc/pauxy
1da80284284769b59361c73cfa3c2d914c74a73f
[ "Apache-2.0" ]
5
2020-05-18T01:03:18.000Z
2021-04-13T15:36:29.000Z
#!/usr/bin/env python '''Exctact element of green's function''' import argparse import sys import numpy import os import pandas as pd import json _script_dir = os.path.abspath(os.path.dirname(__file__)) sys.path.append(os.path.join(_script_dir, 'analysis')) import matplotlib.pyplot as plt # from pauxy.analysis.extract...
33.393443
82
0.579774
462
4,074
4.993506
0.333333
0.034677
0.051582
0.035111
0.172952
0.136108
0.066753
0.066753
0.046814
0
0
0.0041
0.281541
4,074
121
83
33.669421
0.784079
0.138684
0
0.075
0
0
0.148961
0
0
0
0
0
0
1
0.025
false
0
0.1125
0
0.15
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
950130b7d174e4ab134e14783a96e2c70ef6e914
12,854
py
Python
datasets.py
shivakanthsujit/FMMRNet
12742398e3b981938a69e44b3f37d285904929b4
[ "MIT" ]
null
null
null
datasets.py
shivakanthsujit/FMMRNet
12742398e3b981938a69e44b3f37d285904929b4
[ "MIT" ]
null
null
null
datasets.py
shivakanthsujit/FMMRNet
12742398e3b981938a69e44b3f37d285904929b4
[ "MIT" ]
null
null
null
import glob import os import albumentations as A import kaggle import numpy as np import PIL import pytorch_lightning as pl import torch from albumentations.pytorch import ToTensorV2 from torch.utils.data import random_split from torch.utils.data.dataloader import DataLoader from utils import show_images def get_tr...
33.300518
119
0.628131
1,688
12,854
4.531398
0.115521
0.043143
0.028762
0.033991
0.691463
0.64649
0.619427
0.61629
0.532357
0.517061
0
0.011941
0.257274
12,854
385
120
33.387013
0.789253
0.032597
0
0.51634
0
0
0.050416
0.007918
0
0
0
0
0.009804
1
0.101307
false
0
0.039216
0.026144
0.218954
0.01634
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
9505115c9cbc7843483152234defea7c4da55e5d
663
py
Python
29_Tree/Step03/wowo0709.py
StudyForCoding/BEAKJOON
84e1c5e463255e919ccf6b6a782978c205420dbf
[ "MIT" ]
null
null
null
29_Tree/Step03/wowo0709.py
StudyForCoding/BEAKJOON
84e1c5e463255e919ccf6b6a782978c205420dbf
[ "MIT" ]
3
2020-11-04T05:38:53.000Z
2021-03-02T02:15:19.000Z
29_Tree/Step03/wowo0709.py
StudyForCoding/BEAKJOON
84e1c5e463255e919ccf6b6a782978c205420dbf
[ "MIT" ]
null
null
null
import sys input = sys.stdin.readline from collections import deque def bfs(v): dp = [-1 for _ in range(V+1)] dp[v] = 0 q = deque() q.append(v) while q: cv = q.popleft() for nc,nv in tree[cv]: if dp[nv] == -1: # 아직 들르지 않았다면, dp[nv] = dp[cv] + nc ...
24.555556
43
0.517345
117
663
2.905983
0.470085
0.044118
0.088235
0.097059
0.105882
0
0
0
0
0
0
0.024176
0.313725
663
27
44
24.555556
0.723077
0.131222
0
0
0
0
0
0
0
0
0
0
0
1
0.041667
false
0
0.083333
0
0.166667
0.041667
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
95086bdd5bed5808e0d9ba240d94e656c6d84fab
1,624
py
Python
_scripts/pandoc_wiki_filter.py
BenjaminPollak/coursebook
4646102b5f4c3d283885ba1b221da71a5e509eeb
[ "CC-BY-3.0", "CC-BY-4.0" ]
null
null
null
_scripts/pandoc_wiki_filter.py
BenjaminPollak/coursebook
4646102b5f4c3d283885ba1b221da71a5e509eeb
[ "CC-BY-3.0", "CC-BY-4.0" ]
null
null
null
_scripts/pandoc_wiki_filter.py
BenjaminPollak/coursebook
4646102b5f4c3d283885ba1b221da71a5e509eeb
[ "CC-BY-3.0", "CC-BY-4.0" ]
null
null
null
#!/usr/bin/env python3 """ Pandoc filter to change each relative URL to absolute """ from panflute import run_filter, Str, Header, Image, Math, Link, RawInline import sys import re base_raw_url = 'https://raw.githubusercontent.com/illinois-cs241/coursebook/master/' class NoAltTagException(Exception): pass def ...
28.491228
84
0.640394
216
1,624
4.717593
0.546296
0.034347
0.019627
0
0
0
0
0
0
0
0
0.004237
0.273399
1,624
56
85
29
0.859322
0.343596
0
0
0
0
0.097421
0
0
0
0
0
0
1
0.071429
false
0.035714
0.107143
0.035714
0.357143
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
9508ac69c9c25e71d33441ccd8a681ec504ce33e
8,793
py
Python
PA_multiagent_game/multiagent_utils.py
salesforce/RIRL
6f137955bfbe2054be18bb2b15d0e6aedb972b06
[ "BSD-3-Clause" ]
null
null
null
PA_multiagent_game/multiagent_utils.py
salesforce/RIRL
6f137955bfbe2054be18bb2b15d0e6aedb972b06
[ "BSD-3-Clause" ]
null
null
null
PA_multiagent_game/multiagent_utils.py
salesforce/RIRL
6f137955bfbe2054be18bb2b15d0e6aedb972b06
[ "BSD-3-Clause" ]
null
null
null
# # Copyright (c) 2022, salesforce.com, inc. # All rights reserved. # SPDX-License-Identifier: BSD-3-Clause # For full license text, see the LICENSE file in the repo root or https://opensource.org/licenses/BSD-3-Clause # import sys import glob sys.path.insert(0, '..') import numpy as np import matplotlib import matp...
35.313253
230
0.585579
1,270
8,793
3.750394
0.196063
0.010917
0.008398
0.021415
0.282385
0.152425
0.109595
0.063405
0.046609
0.046609
0
0.016365
0.277266
8,793
248
231
35.455645
0.733124
0.113158
0
0.07362
0
0
0.095213
0.030984
0
0
0
0
0.01227
1
0.02454
false
0
0.067485
0
0.116564
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
950dcd67a7917370bcc5ec2201e9aaf688e1aa85
2,062
py
Python
postgres/python-asyncio/main.py
Gelbpunkt/idlebench
fe370f9fa6335cf738a91ca818638aedf0cf1ba3
[ "Apache-2.0" ]
null
null
null
postgres/python-asyncio/main.py
Gelbpunkt/idlebench
fe370f9fa6335cf738a91ca818638aedf0cf1ba3
[ "Apache-2.0" ]
null
null
null
postgres/python-asyncio/main.py
Gelbpunkt/idlebench
fe370f9fa6335cf738a91ca818638aedf0cf1ba3
[ "Apache-2.0" ]
4
2020-08-16T22:23:42.000Z
2020-08-17T20:15:33.000Z
import asyncio import asyncpg VALUES = [ 356091260429402122, "Why are you reading", 9164, 6000000, 14, 0, 0, 0, 463318425901596672, "https://i.imgur.com/LRV2QCK.png", 15306, ["Paragon", "White Sorcerer"], 0, 0, 647, "Leader", None, 0, "10.0",...
25.45679
88
0.511639
228
2,062
4.552632
0.587719
0.013487
0.078035
0.042389
0.102119
0.102119
0.102119
0.102119
0
0
0
0.16156
0.303589
2,062
80
89
25.775
0.561281
0
0
0.323944
0
0.056338
0.491271
0.059651
0
0
0
0
0
1
0
false
0.014085
0.028169
0
0.028169
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
950e90e9549308bcb8380f5876c0fc12c6f68485
1,112
py
Python
fv-courseware/exercise-01/counter_formal.py
DonaldKellett/nmigen-beginner
260ae76a5277e36ec9909aaf6b76acab320aed88
[ "MIT" ]
1
2020-11-09T13:34:02.000Z
2020-11-09T13:34:02.000Z
fv-courseware/exercise-01/counter_formal.py
DonaldKellett/nmigen-beginner
260ae76a5277e36ec9909aaf6b76acab320aed88
[ "MIT" ]
null
null
null
fv-courseware/exercise-01/counter_formal.py
DonaldKellett/nmigen-beginner
260ae76a5277e36ec9909aaf6b76acab320aed88
[ "MIT" ]
null
null
null
from nmigen import * from nmigen.asserts import Assert from nmigen.cli import main_parser, main_runner __all__ = ["Counter"] """ Simple counter with formal verification See slides 50-60 in https://zipcpu.com/tutorial/class-verilog.pdf """ class Counter(Elaboratable): def __init__(self, fv_mode = False): self.fv_m...
25.272727
55
0.695144
175
1,112
4.205714
0.365714
0.134511
0.040761
0.065217
0.142663
0.142663
0.084239
0.084239
0.084239
0
0
0.01826
0.16277
1,112
44
56
25.272727
0.772288
0
0
0.060606
0
0
0.015
0
0
0
0
0
0.060606
1
0.090909
false
0
0.090909
0.030303
0.272727
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
9510db3851814a40d1e201c8697a846d403a09e9
731
py
Python
mnist/download.py
hiroog/cppapimnist
30d7e01954fc43da2eea5fe3ebf034b37e79cfd1
[ "MIT" ]
null
null
null
mnist/download.py
hiroog/cppapimnist
30d7e01954fc43da2eea5fe3ebf034b37e79cfd1
[ "MIT" ]
null
null
null
mnist/download.py
hiroog/cppapimnist
30d7e01954fc43da2eea5fe3ebf034b37e79cfd1
[ "MIT" ]
null
null
null
#!/usr/bin/python3 import urllib.request import os import gzip DOWNLOAD_URL='http://yann.lecun.com/exdb/mnist/' file_list=[ 'train-images-idx3-ubyte', 'train-labels-idx1-ubyte', 't10k-images-idx3-ubyte', 't10k-labels-idx1-ubyte' ] for name in file_list: if not os.path.exists( name ): gz_name= name + '.gz'...
30.458333
118
0.575923
104
731
3.951923
0.423077
0.087591
0.072993
0.053528
0.194647
0.111922
0.111922
0.111922
0
0
0
0.017078
0.27907
731
23
119
31.782609
0.762808
0.023256
0
0.117647
0
0
0.204225
0.126761
0
0
0
0
0
1
0
false
0
0.176471
0
0.176471
0.117647
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
951110f9319a47de447b38bde1aba4ab72ddd1bd
2,651
py
Python
arch/arm64/tests/a64_tbnz.py
Samsung/ADBI
3e424c45386b0a36c57211da819021cb1929775a
[ "Apache-2.0" ]
312
2016-02-04T11:03:17.000Z
2022-03-18T11:30:10.000Z
arch/arm64/tests/a64_tbnz.py
NickHardwood/ADBI
3e424c45386b0a36c57211da819021cb1929775a
[ "Apache-2.0" ]
4
2016-02-04T11:05:40.000Z
2017-07-27T04:22:27.000Z
arch/arm64/tests/a64_tbnz.py
NickHardwood/ADBI
3e424c45386b0a36c57211da819021cb1929775a
[ "Apache-2.0" ]
85
2016-02-04T12:48:30.000Z
2021-01-14T06:23:24.000Z
import random from common import * class test_a64_tbnz(TemplateTest): def gen_rand(self): regs = list(set(GPREGS) - {'x0', 'w0'}) while True: yield {'insn' : random.choice(['tbz', 'tbnz']), 'reg' : random.choice(regs), 'bit' : random.randint(...
38.42029
94
0.488118
305
2,651
4.091803
0.311475
0.038462
0.067308
0.028846
0.205128
0.145833
0.145833
0.145833
0.092949
0.092949
0
0.036374
0.367409
2,651
68
95
38.985294
0.707812
0
0
0.183333
0
0
0.09619
0
0
0
0.018861
0
0
1
0.083333
false
0
0.033333
0
0.133333
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0