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
fe224e1ffb01067a1145784abb7281fb2243b190
1,788
py
Python
smartfields/processors/video.py
suhaibroomy/django-smartfields
e9331dc74f72d0254608526f8816aa4bb8f1fca4
[ "MIT" ]
null
null
null
smartfields/processors/video.py
suhaibroomy/django-smartfields
e9331dc74f72d0254608526f8816aa4bb8f1fca4
[ "MIT" ]
null
null
null
smartfields/processors/video.py
suhaibroomy/django-smartfields
e9331dc74f72d0254608526f8816aa4bb8f1fca4
[ "MIT" ]
null
null
null
import re import six from smartfields.processors.base import ExternalFileProcessor from smartfields.utils import ProcessingError __all__ = [ 'FFMPEGProcessor' ] class FFMPEGProcessor(ExternalFileProcessor): duration_re = re.compile(r'Duration: (?P<hours>\d+):(?P<minutes>\d+):(?P<seconds>\d+)') progress_r...
39.733333
91
0.599553
207
1,788
5.057971
0.415459
0.007641
0.031519
0.034384
0.047755
0.047755
0.047755
0.047755
0.047755
0
0
0.009302
0.278523
1,788
44
92
40.636364
0.802326
0
0
0
0
0.076923
0.217562
0.068792
0
0
0
0
0
1
0.051282
false
0
0.102564
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
fe22b8aac4f7560fc1450a1ab43865faaf7aecdc
2,192
py
Python
tests/test_vmtkScripts/test_vmtksurfaceconnectivity.py
ramtingh/vmtk
4d6f58ce65d73628353ba2b110cbc29a2e7aa7b3
[ "Apache-2.0" ]
null
null
null
tests/test_vmtkScripts/test_vmtksurfaceconnectivity.py
ramtingh/vmtk
4d6f58ce65d73628353ba2b110cbc29a2e7aa7b3
[ "Apache-2.0" ]
null
null
null
tests/test_vmtkScripts/test_vmtksurfaceconnectivity.py
ramtingh/vmtk
4d6f58ce65d73628353ba2b110cbc29a2e7aa7b3
[ "Apache-2.0" ]
1
2019-06-18T23:41:11.000Z
2019-06-18T23:41:11.000Z
## Program: VMTK ## Language: Python ## Date: January 12, 2018 ## Version: 1.4 ## Copyright (c) Richard Izzo, Luca Antiga, All rights reserved. ## See LICENSE file for details. ## This software is distributed WITHOUT ANY WARRANTY; without even ## the implied warranty of MERCHANTABILITY or FITNES...
35.354839
117
0.764599
253
2,192
6.339921
0.391304
0.074813
0.074813
0.114713
0.508105
0.479426
0.46384
0.46384
0.431421
0.393392
0
0.008108
0.156022
2,192
61
118
35.934426
0.858919
0.218978
0
0.411765
0
0
0.100771
0.084766
0
0
0
0
0.088235
1
0.117647
false
0
0.117647
0
0.264706
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe23546882c9babc55f9bce0abdfba0776ff09c5
653
py
Python
sssoon/forms.py
Kingpin-Apps/django-sssoon
2a44d0d19e70dcd3127f9425c0ed4ba52355a1d2
[ "BSD-3-Clause" ]
2
2018-04-20T08:28:10.000Z
2018-05-04T15:32:30.000Z
sssoon/forms.py
KINGH242/django-sssoon
2a44d0d19e70dcd3127f9425c0ed4ba52355a1d2
[ "BSD-3-Clause" ]
2
2018-05-16T13:45:14.000Z
2020-07-29T22:01:37.000Z
sssoon/forms.py
Kingpin-Apps/django-sssoon
2a44d0d19e70dcd3127f9425c0ed4ba52355a1d2
[ "BSD-3-Clause" ]
null
null
null
from django import forms from nocaptcha_recaptcha.fields import NoReCaptchaField class NewsletterForm(forms.Form): email = forms.EmailField(label='Email', required=True, widget=forms.TextInput(attrs={ 'id': 'newsletter-email', ...
40.8125
70
0.444104
45
653
6.422222
0.711111
0
0
0
0
0
0
0
0
0
0
0
0.456355
653
16
71
40.8125
0.814085
0
0
0
0
0
0.169725
0
0
0
0
0
0
1
0
false
0
0.153846
0
0.384615
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe242c827a7e391a419864c9504b7e2daf4968d1
1,054
py
Python
simple_run_menu.py
william01110111/simple_run_menu
804c6bb8d6c63c3a4d4c6d3377601bd44fb0eeea
[ "MIT" ]
null
null
null
simple_run_menu.py
william01110111/simple_run_menu
804c6bb8d6c63c3a4d4c6d3377601bd44fb0eeea
[ "MIT" ]
null
null
null
simple_run_menu.py
william01110111/simple_run_menu
804c6bb8d6c63c3a4d4c6d3377601bd44fb0eeea
[ "MIT" ]
null
null
null
#! /bin/python3 # simple run menu import os import stat def is_file_executable(path): executable = stat.S_IEXEC | stat.S_IXGRP | stat.S_IXOTH if not os.path.isfile(path): return False st = os.stat(path) mode = st.st_mode if not mode & executable: return False return True def get_files_in_dir(directory): i...
22.425532
83
0.685009
154
1,054
4.461039
0.383117
0.021834
0.026201
0.037846
0
0
0
0
0
0
0
0.006849
0.16888
1,054
46
84
22.913043
0.777397
0.028463
0
0.058824
0
0
0.016634
0
0
0
0
0
0
1
0.147059
false
0
0.058824
0
0.411765
0.029412
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe2476b1a28089e744d395040c690305385ddcb6
1,792
py
Python
mne/io/cnt/tests/test_cnt.py
stevemats/mne-python
47051833f21bb372d60afc3adbf4305648ac7f69
[ "BSD-3-Clause" ]
1,953
2015-01-17T20:33:46.000Z
2022-03-30T04:36:34.000Z
mne/io/cnt/tests/test_cnt.py
LiFeng-SECUC/mne-python
732bb1f994e64e41a8e95dcc10dc98c22cac95c0
[ "BSD-3-Clause" ]
8,490
2015-01-01T13:04:18.000Z
2022-03-31T23:02:08.000Z
mne/io/cnt/tests/test_cnt.py
LiFeng-SECUC/mne-python
732bb1f994e64e41a8e95dcc10dc98c22cac95c0
[ "BSD-3-Clause" ]
1,130
2015-01-08T22:39:27.000Z
2022-03-30T21:44:26.000Z
# Author: Jaakko Leppakangas <jaeilepp@student.jyu.fi> # Joan Massich <mailsik@gmail.com> # # License: BSD-3-Clause import os.path as op import numpy as np from numpy.testing import assert_array_equal import pytest from mne import pick_types from mne.datasets import testing from mne.io.tests.test_raw import...
32
74
0.65346
259
1,792
4.362934
0.474903
0.030973
0.026549
0.046018
0.118584
0.058407
0
0
0
0
0
0.041817
0.226004
1,792
55
75
32.581818
0.772891
0.179688
0
0.058824
0
0
0.082702
0
0
0
0
0
0.235294
1
0.058824
false
0
0.264706
0
0.323529
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe24a27fb5e1b1af1324c59e811661bad02c4101
792
py
Python
parliament_proposal_fetcher.py
Track-your-parliament/track-your-parliament-data
1ab9d9fe5cf4921e4cc792d0e3db3263557daafd
[ "MIT" ]
null
null
null
parliament_proposal_fetcher.py
Track-your-parliament/track-your-parliament-data
1ab9d9fe5cf4921e4cc792d0e3db3263557daafd
[ "MIT" ]
null
null
null
parliament_proposal_fetcher.py
Track-your-parliament/track-your-parliament-data
1ab9d9fe5cf4921e4cc792d0e3db3263557daafd
[ "MIT" ]
null
null
null
import urllib.request, json import pandas as pd baseUrl = 'https://avoindata.eduskunta.fi/api/v1/tables/VaskiData' parameters = 'rows?columnName=Eduskuntatunnus&columnValue=LA%25&perPage=100' page = 0 df = '' while True: print(f'Fetching page number {page}') with urllib.request.urlopen(f'{baseUrl}/{parameters...
29.333333
94
0.641414
100
792
5.04
0.63
0.051587
0.087302
0
0
0
0
0
0
0
0
0.015873
0.204545
792
27
95
29.333333
0.784127
0
0
0
0
0
0.319042
0.163934
0
0
0
0
0
1
0
false
0
0.105263
0
0.105263
0.052632
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe2717913fd1b6cb1c949e299c54e281bc41335e
2,899
py
Python
examples/Catboost_regression-scorer_usage.py
emaldonadocruz/UTuning
b32207bcbeb80e4c07e098bcbe4d5ce8b3fee778
[ "BSD-3-Clause" ]
null
null
null
examples/Catboost_regression-scorer_usage.py
emaldonadocruz/UTuning
b32207bcbeb80e4c07e098bcbe4d5ce8b3fee778
[ "BSD-3-Clause" ]
null
null
null
examples/Catboost_regression-scorer_usage.py
emaldonadocruz/UTuning
b32207bcbeb80e4c07e098bcbe4d5ce8b3fee778
[ "BSD-3-Clause" ]
null
null
null
# -*- coding: utf-8 -*- """ Created on Mon Sep 20 16:15:37 2021 @author: em42363 """ # In[1]: Import functions ''' CatBoost is a high-performance open source library for gradient boosting on decision trees ''' from catboost import CatBoostRegressor from sklearn.model_selection import train_test_split import pandas a...
26.354545
102
0.703001
434
2,899
4.534562
0.373272
0.02439
0.014228
0.02439
0.259146
0.215447
0.195122
0.034553
0
0
0
0.034994
0.162125
2,899
109
103
26.59633
0.775216
0.119007
0
0.043478
0
0
0.123344
0.059845
0
0
0
0
0
1
0.021739
false
0
0.217391
0
0.26087
0.065217
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe27a69a39058bf33d488a199887b8c07ffdf22c
1,683
py
Python
sujson/_logger.py
PotasnikM/translator-to-suJSON
abb2001c78d431bd2087754666bc896ba0543dfd
[ "MIT" ]
2
2019-07-01T12:45:25.000Z
2020-06-23T11:48:08.000Z
sujson/_logger.py
PotasnikM/translator-to-suJSON
abb2001c78d431bd2087754666bc896ba0543dfd
[ "MIT" ]
17
2019-04-25T10:46:40.000Z
2020-11-10T09:28:55.000Z
sujson/_logger.py
PotasnikM/translator-to-suJSON
abb2001c78d431bd2087754666bc896ba0543dfd
[ "MIT" ]
3
2019-06-22T19:51:08.000Z
2021-02-08T09:17:55.000Z
import logging from platform import system from tqdm import tqdm from multiprocessing import Lock loggers = {} # https://stackoverflow.com/questions/38543506/ class TqdmLoggingHandler(logging.Handler): def __init__(self, level=logging.NOTSET): super(TqdmLoggingHandler, self).__init__(level) def emit...
29.017241
110
0.655971
193
1,683
5.663212
0.414508
0.029277
0.095151
0.025618
0.120769
0.120769
0.120769
0
0
0
0
0.039514
0.218063
1,683
57
111
29.526316
0.791033
0.087344
0
0
0
0
0.079051
0.055336
0
0
0
0
0
1
0.076923
false
0
0.102564
0
0.25641
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe27abc65b6073ec58be633f81761077a129a312
1,243
py
Python
face-detect.py
Gicehajunior/face-recognition-detection-OpenCv-Python
6551285ce5b4532d8b6f3ad6b8e9a29564673ea9
[ "Unlicense" ]
null
null
null
face-detect.py
Gicehajunior/face-recognition-detection-OpenCv-Python
6551285ce5b4532d8b6f3ad6b8e9a29564673ea9
[ "Unlicense" ]
null
null
null
face-detect.py
Gicehajunior/face-recognition-detection-OpenCv-Python
6551285ce5b4532d8b6f3ad6b8e9a29564673ea9
[ "Unlicense" ]
null
null
null
import cv2 import sys import playsound face_cascade = cv2.CascadeClassifier('cascades/haarcascade_frontalface_default.xml') # capture video using cv2 video_capture = cv2.VideoCapture(0) while True: # capture frame by frame, i.e, one by one ret, frame = video_capture.read() gray = cv2.cvtColor(frame...
28.25
85
0.563154
153
1,243
4.51634
0.522876
0.034732
0.031838
0.037627
0
0
0
0
0
0
0
0.040719
0.328238
1,243
43
86
28.906977
0.786826
0.134352
0
0.068966
0
0
0.116822
0.041122
0
0
0.003738
0
0
1
0
false
0.034483
0.103448
0
0.103448
0.068966
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe27fecf1f48f5d4699cad091ca66149a513fe9b
7,938
py
Python
sis/enrollments.py
ryanlovett/sis-cli
5efe5b9344b547c3f1365ef63a0ad33ec013fcca
[ "Apache-2.0" ]
null
null
null
sis/enrollments.py
ryanlovett/sis-cli
5efe5b9344b547c3f1365ef63a0ad33ec013fcca
[ "Apache-2.0" ]
null
null
null
sis/enrollments.py
ryanlovett/sis-cli
5efe5b9344b547c3f1365ef63a0ad33ec013fcca
[ "Apache-2.0" ]
null
null
null
# vim:set et sw=4 ts=4: import logging import sys import jmespath from . import sis, classes # logging logging.basicConfig(stream=sys.stdout, level=logging.WARNING) logger = logging.getLogger(__name__) # SIS endpoint enrollments_uri = "https://apis.berkeley.edu/sis/v2/enrollments" # apparently some courses have LA...
37.620853
105
0.68317
984
7,938
5.340447
0.208333
0.015985
0.018268
0.018839
0.341009
0.24529
0.213701
0.172788
0.156422
0.114558
0
0.00725
0.20068
7,938
210
106
37.8
0.820961
0.163769
0
0.205882
0
0
0.210957
0.087163
0
0
0
0
0
1
0.095588
false
0
0.029412
0.014706
0.257353
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe292b4982f3dd8af18a6b88ccaadbbba6d158ef
8,012
py
Python
imitation_learning/generate_demonstrations/gen_envs.py
HaiDangDang/2020-flatland
abbf2f7f62fabf6da0937f80c2181f1c457ce24a
[ "MIT" ]
1
2021-02-21T02:54:35.000Z
2021-02-21T02:54:35.000Z
imitation_learning/generate_demonstrations/gen_envs.py
HaiDangDang/2020-flatland
abbf2f7f62fabf6da0937f80c2181f1c457ce24a
[ "MIT" ]
null
null
null
imitation_learning/generate_demonstrations/gen_envs.py
HaiDangDang/2020-flatland
abbf2f7f62fabf6da0937f80c2181f1c457ce24a
[ "MIT" ]
null
null
null
from flatland.envs.agent_utils import RailAgentStatus from flatland.envs.malfunction_generators import malfunction_from_params, MalfunctionParameters from flatland.envs.observations import GlobalObsForRailEnv from flatland.envs.rail_env import RailEnv from flatland.envs.rail_generators import sparse_rail_generator from...
29.240876
96
0.623689
982
8,012
4.898167
0.226069
0.043243
0.04657
0.030561
0.33264
0.296258
0.259044
0.245738
0.208108
0.208108
0
0.026302
0.259735
8,012
273
97
29.347985
0.784691
0.079256
0
0.176796
0
0
0.076505
0.003261
0
0
0
0
0
1
0.049724
false
0
0.082873
0
0.160221
0.121547
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe2e74a698807b4b6d0cf881031198f5da548dd4
1,891
py
Python
Image Recognition/utils/BayesianModels/Bayesian3Conv3FC.py
AlanMorningLight/PyTorch-BayesianCNN
5de7133f09dd10135bf605efbdd26c18f2a4df13
[ "MIT" ]
1
2020-02-10T12:58:25.000Z
2020-02-10T12:58:25.000Z
utils/BayesianModels/Bayesian3Conv3FC.py
SulemanKhurram/ThesisExperiments
4fdf7b6558c87a096dcdc374c35085ac946d3a58
[ "MIT" ]
null
null
null
utils/BayesianModels/Bayesian3Conv3FC.py
SulemanKhurram/ThesisExperiments
4fdf7b6558c87a096dcdc374c35085ac946d3a58
[ "MIT" ]
null
null
null
import torch.nn as nn from utils.BBBlayers import BBBConv2d, BBBLinearFactorial, FlattenLayer class BBB3Conv3FC(nn.Module): """ Simple Neural Network having 3 Convolution and 3 FC layers with Bayesian layers. """ def __init__(self, outputs, inputs): super(BBB3Conv3FC, self).__init__() ...
35.679245
89
0.599683
229
1,891
4.886463
0.340611
0.022341
0.062556
0.040214
0.124218
0.124218
0.088472
0.088472
0
0
0
0.069733
0.28715
1,891
53
90
35.679245
0.760386
0.060814
0
0.052632
0
0
0.034618
0
0
0
0
0
0
1
0.052632
false
0.026316
0.052632
0
0.157895
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe2fc61a568a0e2538b7b1f99349a5186a485475
8,657
py
Python
custom_scripts/load_animals.py
nphilou/influence-release
bcf3603705b6ff172bcb62123aef0248afa77a05
[ "MIT" ]
null
null
null
custom_scripts/load_animals.py
nphilou/influence-release
bcf3603705b6ff172bcb62123aef0248afa77a05
[ "MIT" ]
null
null
null
custom_scripts/load_animals.py
nphilou/influence-release
bcf3603705b6ff172bcb62123aef0248afa77a05
[ "MIT" ]
null
null
null
import os from tensorflow.contrib.learn.python.learn.datasets import base import numpy as np import IPython from subprocess import call from keras.preprocessing import image from influence.dataset import DataSet from influence.inception_v3 import preprocess_input BASE_DIR = 'data' # TODO: change def fill(X, Y, id...
35.479508
167
0.611644
1,210
8,657
4.047934
0.135537
0.023479
0.046958
0.0343
0.561862
0.53185
0.449367
0.368722
0.307472
0.280114
0
0.021666
0.274922
8,657
243
168
35.625514
0.758643
0.068615
0
0.357542
0
0
0.069921
0.007824
0
0
0
0.004115
0
1
0.03352
false
0
0.044693
0
0.100559
0.055866
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe2fd1a403e44db33fca9bd236a441a4df247ba1
13,000
py
Python
src/qiskit_aws_braket_provider/awsbackend.py
carstenblank/qiskit-aws-braket-provider
539f0c75c2ccf1f6e5e981b92ea74f497fcba237
[ "Apache-2.0" ]
7
2020-09-25T17:16:54.000Z
2021-05-20T10:42:52.000Z
src/qiskit_aws_braket_provider/awsbackend.py
carstenblank/qiskit-aws-braket-provider
539f0c75c2ccf1f6e5e981b92ea74f497fcba237
[ "Apache-2.0" ]
4
2020-09-21T19:33:39.000Z
2020-09-22T12:21:11.000Z
src/qiskit_aws_braket_provider/awsbackend.py
carstenblank/qiskit-aws-braket-provider
539f0c75c2ccf1f6e5e981b92ea74f497fcba237
[ "Apache-2.0" ]
1
2020-09-21T19:32:16.000Z
2020-09-21T19:32:16.000Z
# Copyright 2020 Carsten Blank # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing...
45.138889
144
0.666923
1,664
13,000
4.918269
0.16887
0.058651
0.041056
0.026393
0.417155
0.377199
0.353495
0.34433
0.31085
0.306574
0
0.014246
0.244077
13,000
287
145
45.296167
0.818561
0.089154
0
0.26009
0
0
0.098713
0.039197
0
0
0
0.003484
0.004484
1
0.076233
false
0.008969
0.089686
0.004484
0.255605
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe30812932f608889eaceef38afb76f593b3db27
3,830
py
Python
gpu_bdb/queries/q26/gpu_bdb_query_26.py
VibhuJawa/gpu-bdb
13987b4ef8b92db3b9d2905dec7bd2fd81f42ae9
[ "Apache-2.0" ]
62
2020-05-14T13:33:02.000Z
2020-10-29T13:28:26.000Z
gpu_bdb/queries/q26/gpu_bdb_query_26.py
VibhuJawa/gpu-bdb
13987b4ef8b92db3b9d2905dec7bd2fd81f42ae9
[ "Apache-2.0" ]
104
2020-07-01T21:07:42.000Z
2020-11-13T16:36:04.000Z
gpu_bdb/queries/q26/gpu_bdb_query_26.py
VibhuJawa/gpu-bdb
13987b4ef8b92db3b9d2905dec7bd2fd81f42ae9
[ "Apache-2.0" ]
21
2020-05-14T14:44:40.000Z
2020-11-07T12:08:28.000Z
# # Copyright (c) 2019-2022, NVIDIA CORPORATION. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or ag...
31.138211
115
0.703655
549
3,830
4.621129
0.380692
0.024832
0.030745
0.021285
0.076074
0.069373
0.044935
0
0
0
0
0.014984
0.198433
3,830
122
116
31.393443
0.811401
0.268407
0
0.026316
0
0
0.07709
0
0
0
0
0
0
1
0.039474
false
0
0.092105
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
fe3188f73830a0839c72948677e1605c9ae2ae83
1,586
py
Python
tdclient/test/database_model_test.py
minchuang/td-client-python
6cf6dfbb60119f400274491d3e942d4f9fbcebd6
[ "Apache-2.0" ]
2
2019-02-22T11:56:17.000Z
2019-02-25T10:09:46.000Z
tdclient/test/database_model_test.py
minchuang/td-client-python
6cf6dfbb60119f400274491d3e942d4f9fbcebd6
[ "Apache-2.0" ]
null
null
null
tdclient/test/database_model_test.py
minchuang/td-client-python
6cf6dfbb60119f400274491d3e942d4f9fbcebd6
[ "Apache-2.0" ]
null
null
null
#!/usr/bin/env python from __future__ import print_function from __future__ import unicode_literals try: from unittest import mock except ImportError: import mock from tdclient import models from tdclient.test.test_helper import * def setup_function(function): unset_environ() def test_database(): c...
40.666667
202
0.713745
193
1,586
5.621762
0.295337
0.090323
0.092166
0.04977
0.354839
0.326267
0.326267
0.237788
0.152995
0.152995
0
0.011095
0.147541
1,586
38
203
41.736842
0.79142
0.01261
0
0.064516
0
0
0.20639
0
0
0
0
0
0.290323
1
0.096774
false
0
0.225806
0
0.322581
0.032258
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe31f26debb52795b22561b36355ce06ff7905d8
558
py
Python
setup.py
ballcap231/fireTS
74cc89a14d67edabf31139d1552025d54791f2a9
[ "MIT" ]
null
null
null
setup.py
ballcap231/fireTS
74cc89a14d67edabf31139d1552025d54791f2a9
[ "MIT" ]
null
null
null
setup.py
ballcap231/fireTS
74cc89a14d67edabf31139d1552025d54791f2a9
[ "MIT" ]
null
null
null
from setuptools import setup dependencies = [ 'numpy', 'scipy', 'scikit-learn', ] setup( name='fireTS', version='0.0.7', description='A python package for multi-variate time series prediction', long_description=open('README.md').read(), long_description_content_type="text/markdown", ...
24.26087
76
0.677419
67
558
5.507463
0.835821
0.081301
0
0
0
0
0
0
0
0
0
0.017429
0.177419
558
22
77
25.363636
0.786492
0
0
0
0
0
0.327957
0
0
0
0
0
0
1
0
false
0
0.05
0
0.05
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe3273d41978521818a7243089a132072ef92c5a
883
py
Python
euler/py/project_019.py
heyihan/scodes
342518b548a723916c9273d8ebc1b345a0467e76
[ "BSD-3-Clause" ]
null
null
null
euler/py/project_019.py
heyihan/scodes
342518b548a723916c9273d8ebc1b345a0467e76
[ "BSD-3-Clause" ]
null
null
null
euler/py/project_019.py
heyihan/scodes
342518b548a723916c9273d8ebc1b345a0467e76
[ "BSD-3-Clause" ]
null
null
null
# https://projecteuler.net/problem=19 def is_leap(year): if year%4 != 0: return False if year%100 == 0 and year%400 != 0: return False return True def year_days(year): if is_leap(year): return 366 return 365 def month_days(month, year): if month == 4 or month == 6 or m...
20.534884
61
0.582106
142
883
3.443662
0.338028
0.08589
0.134969
0.04908
0.151329
0
0
0
0
0
0
0.156507
0.312571
883
42
62
21.02381
0.649094
0.075878
0
0.129032
0
0
0
0
0
0
0
0
0
1
0.096774
false
0
0
0
0.387097
0.096774
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe3415df5ab13d93fe351122344f2bd2d2fe4c5f
3,839
py
Python
inference.py
zzhang87/ChestXray
eaafe2f7f5e91bb30fbed02dec1f77ff314434b5
[ "MIT" ]
null
null
null
inference.py
zzhang87/ChestXray
eaafe2f7f5e91bb30fbed02dec1f77ff314434b5
[ "MIT" ]
11
2020-01-28T21:44:26.000Z
2022-03-11T23:19:37.000Z
inference.py
zzhang87/ChestXray
eaafe2f7f5e91bb30fbed02dec1f77ff314434b5
[ "MIT" ]
null
null
null
import keras import numpy as np import pandas as pd import cv2 import os import json import pdb import argparse import math import copy from vis.visualization import visualize_cam, overlay, visualize_activation from vis.utils.utils import apply_modifications from shutil import rmtree import matplotlib.cm as cm from ma...
27.035211
107
0.716593
572
3,839
4.681818
0.332168
0.033607
0.031367
0.034354
0.034354
0.021658
0
0
0
0
0
0.025962
0.147174
3,839
142
108
27.035211
0.791998
0.030998
0
0
0
0
0.094969
0
0
0
0
0
0
1
0.020833
false
0
0.25
0
0.28125
0.010417
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe34376d96d5593399f4f9364cf5da83ea7d813b
530
py
Python
test/DQueueTest.py
MistSun-Chen/py_verifier
7e9161d1fdbb611fe4be5eeb2f89a6286fa7b555
[ "MIT" ]
null
null
null
test/DQueueTest.py
MistSun-Chen/py_verifier
7e9161d1fdbb611fe4be5eeb2f89a6286fa7b555
[ "MIT" ]
null
null
null
test/DQueueTest.py
MistSun-Chen/py_verifier
7e9161d1fdbb611fe4be5eeb2f89a6286fa7b555
[ "MIT" ]
null
null
null
from libTask import Queue from common import configParams from common import common def main(): cp = configParams.ConfigParams("config.json") detectGeneralQueue = Queue.DQueue(cp, len(cp.detect_general_ids), cp.modelPath, common.GENERALDETECT_METHOD_ID, cp.GPUDevices, cp.detect_g...
35.333333
124
0.718868
68
530
5.338235
0.470588
0.055096
0.088154
0.088154
0.220386
0
0
0
0
0
0
0
0.181132
530
15
125
35.333333
0.836406
0
0
0
0
0
0.06968
0
0
0
0
0
0
1
0.090909
false
0
0.272727
0
0.363636
0.090909
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe3599447ec843cd5c9296bccc205dff470707c7
1,417
py
Python
src/Knn-Tensor.py
python-itb/knn-from-scratch
dbc6fb53cffb245a76d35b9ff85ac8cb21877ca8
[ "MIT" ]
null
null
null
src/Knn-Tensor.py
python-itb/knn-from-scratch
dbc6fb53cffb245a76d35b9ff85ac8cb21877ca8
[ "MIT" ]
2
2018-03-20T06:47:32.000Z
2018-10-25T10:54:08.000Z
src/Knn-Tensor.py
python-itb/knn-from-scratch
dbc6fb53cffb245a76d35b9ff85ac8cb21877ca8
[ "MIT" ]
4
2018-03-20T06:43:11.000Z
2019-04-15T16:34:28.000Z
#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Tue Feb 13 18:52:28 2018 @author: amajidsinar """ from sklearn import datasets import matplotlib.pyplot as plt import numpy as np plt.style.use('seaborn-white') iris = datasets.load_iris() dataset = iris.data # only take 0th and 1th column for X data_kno...
21.149254
94
0.687368
244
1,417
3.901639
0.47541
0.080882
0.05042
0.039916
0.042017
0
0
0
0
0
0
0.046025
0.156669
1,417
66
95
21.469697
0.750628
0.321101
0
0
0
0
0.014941
0
0
0
0
0
0
1
0
false
0
0.12
0
0.12
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe35a3606e5ec595f8753af44fd793743da1ae33
2,135
py
Python
de_test_tron2.py
volpepe/detectron2-ResNeSt
1481d50880baa615b873b7a18156c06a5606a85c
[ "Apache-2.0" ]
null
null
null
de_test_tron2.py
volpepe/detectron2-ResNeSt
1481d50880baa615b873b7a18156c06a5606a85c
[ "Apache-2.0" ]
null
null
null
de_test_tron2.py
volpepe/detectron2-ResNeSt
1481d50880baa615b873b7a18156c06a5606a85c
[ "Apache-2.0" ]
null
null
null
import torch, torchvision import detectron2 from detectron2.utils.logger import setup_logger setup_logger() # import some common libraries import numpy as np import os, json, cv2, random # import some common detectron2 utilities from detectron2 import model_zoo from detectron2.engine import DefaultPredic...
40.283019
164
0.710539
293
2,135
5.010239
0.450512
0.066757
0.032698
0
0
0
0
0
0
0
0
0.013575
0.171897
2,135
53
165
40.283019
0.816742
0.129274
0
0
0
0
0.165556
0.047222
0
0
0
0
0
1
0.051282
false
0
0.282051
0
0.358974
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
fe35e371f2d0a2c205ae69e2ee6c811fd9ed1de5
8,916
py
Python
pika/data.py
Pankrat/pika
9f62cbe032e9b4fa0fe1842587ce0702c3926a3d
[ "BSD-3-Clause" ]
null
null
null
pika/data.py
Pankrat/pika
9f62cbe032e9b4fa0fe1842587ce0702c3926a3d
[ "BSD-3-Clause" ]
null
null
null
pika/data.py
Pankrat/pika
9f62cbe032e9b4fa0fe1842587ce0702c3926a3d
[ "BSD-3-Clause" ]
null
null
null
"""AMQP Table Encoding/Decoding""" import struct import decimal import calendar from datetime import datetime from pika import exceptions from pika.compat import unicode_type, PY2, long, as_bytes def encode_short_string(pieces, value): """Encode a string value as short string and append it to pieces list ret...
30.534247
80
0.596456
1,137
8,916
4.628848
0.176781
0.079042
0.057762
0.068402
0.444233
0.372221
0.312939
0.302679
0.295839
0.255368
0
0.014191
0.288694
8,916
291
81
30.639175
0.815673
0.250561
0
0.306358
0
0
0.018185
0
0
0
0
0
0
1
0.040462
false
0.00578
0.034682
0
0.16763
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe372dac70d64a37ad3e688bb47fa5b1bd4ad42e
528
py
Python
tests/fixtures/data_sets/service/dummy/dummy_configurable.py
Agi-dev/pylaas_core
c44866b5e57eb6f05f5b2b8d731f22d62a8c01c2
[ "MIT" ]
null
null
null
tests/fixtures/data_sets/service/dummy/dummy_configurable.py
Agi-dev/pylaas_core
c44866b5e57eb6f05f5b2b8d731f22d62a8c01c2
[ "MIT" ]
2
2021-03-25T21:30:41.000Z
2021-06-01T21:25:37.000Z
tests/fixtures/data_sets/service/dummy/dummy_configurable.py
Agi-dev/pylaas_core
c44866b5e57eb6f05f5b2b8d731f22d62a8c01c2
[ "MIT" ]
null
null
null
from pylaas_core.abstract.abstract_service import AbstractService import time from pylaas_core.interface.technical.container_configurable_aware_interface import ContainerConfigurableAwareInterface class DummyConfigurable(AbstractService, ContainerConfigurableAwareInterface): def __init__(self) -> None: ...
31.058824
118
0.765152
51
528
7.568627
0.568627
0.051813
0.072539
0
0
0
0
0
0
0
0
0.00907
0.164773
528
16
119
33
0.866213
0
0
0
0
0
0
0
0
0
0
0
0
1
0.181818
false
0
0.272727
0
0.636364
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe3be5e4c8643dd88fcaa6473267f6ae2cf76961
1,706
py
Python
examples/peptidecutter/advanced.py
zjuchenyuan/EasyLogin
acc67187d902f20ec64d2d6b9eeb953e2a0ac77d
[ "MIT" ]
33
2016-12-01T01:33:31.000Z
2021-05-12T03:32:27.000Z
examples/peptidecutter/advanced.py
zjuchenyuan/EasyLogin
acc67187d902f20ec64d2d6b9eeb953e2a0ac77d
[ "MIT" ]
2
2018-04-26T06:58:29.000Z
2020-01-11T15:18:14.000Z
examples/peptidecutter/advanced.py
zjuchenyuan/EasyLogin
acc67187d902f20ec64d2d6b9eeb953e2a0ac77d
[ "MIT" ]
4
2017-02-24T11:08:45.000Z
2021-01-13T16:00:33.000Z
from EasyLogin import EasyLogin from pprint import pprint def peptidecutter(oneprotein): a = EasyLogin(proxy="socks5://127.0.0.1:1080") #speed up by using proxy a.post("http://web.expasy.org/cgi-bin/peptide_cutter/peptidecutter.pl", "protein={}&enzyme_number=all_enzymes&special_enzyme=Chym&min_pr...
30.464286
200
0.579132
203
1,706
4.743842
0.458128
0.018692
0.018692
0.047767
0
0
0
0
0
0
0
0.018257
0.293669
1,706
55
201
31.018182
0.780913
0.047479
0
0.297872
0
0.021277
0.183908
0.123244
0
0
0
0
0
1
0.06383
false
0
0.06383
0.021277
0.191489
0.042553
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe3e731bfc56815773233eb7a914918e37d052e2
974
py
Python
metadata_service/api/popular_tables.py
worldwise001/amundsenmetadatalibrary
9914c8b51d38b8bd76d3249eb4f7fcce3e198d09
[ "Apache-2.0" ]
null
null
null
metadata_service/api/popular_tables.py
worldwise001/amundsenmetadatalibrary
9914c8b51d38b8bd76d3249eb4f7fcce3e198d09
[ "Apache-2.0" ]
1
2019-09-21T23:59:46.000Z
2019-09-21T23:59:46.000Z
metadata_service/api/popular_tables.py
worldwise001/amundsenmetadatalibrary
9914c8b51d38b8bd76d3249eb4f7fcce3e198d09
[ "Apache-2.0" ]
1
2019-09-21T23:56:40.000Z
2019-09-21T23:56:40.000Z
from http import HTTPStatus from typing import Iterable, Union, Mapping from flask import request from flask_restful import Resource, fields, marshal from metadata_service.proxy import get_proxy_client popular_table_fields = { 'database': fields.String, 'cluster': fields.String, 'schema': fields.String, ...
29.515152
96
0.722793
115
974
5.886957
0.417391
0.134417
0.084195
0.076809
0
0
0
0
0
0
0
0.00246
0.165298
974
32
97
30.4375
0.830258
0.027721
0
0
0
0
0.103115
0
0
0
0
0
0
1
0.090909
false
0
0.227273
0
0.409091
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe3ee793457d0725edb13bd4a978ffe58340aff1
11,708
py
Python
others/Keras_custom_error.py
rahasayantan/Work-For-Reference
e052da538df84034ec5a0fe3b19c4287de307286
[ "MIT" ]
null
null
null
others/Keras_custom_error.py
rahasayantan/Work-For-Reference
e052da538df84034ec5a0fe3b19c4287de307286
[ "MIT" ]
null
null
null
others/Keras_custom_error.py
rahasayantan/Work-For-Reference
e052da538df84034ec5a0fe3b19c4287de307286
[ "MIT" ]
null
null
null
# define custom R2 metrics for Keras backend from keras import backend as K def r2_keras(y_true, y_pred): SS_res = K.sum(K.square( y_true - y_pred )) SS_tot = K.sum(K.square( y_true - K.mean(y_true) ) ) return ( 1 - SS_res/(SS_tot + K.epsilon()) ) # base model architecture definition def model(): ...
31.643243
112
0.656389
1,642
11,708
4.488429
0.227162
0.029308
0.016418
0.010855
0.325373
0.262687
0.191859
0.183718
0.16228
0.153324
0
0.019026
0.214383
11,708
369
113
31.728997
0.782235
0.162965
0
0.276018
0
0
0.059916
0.004747
0
0
0
0
0
1
0.049774
false
0
0.135747
0.004525
0.235294
0.058824
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe4036ba021d5a543848f0719df15257dc0be8cd
7,239
py
Python
tests/ut/python/parallel/test_manual_gatherv2.py
PowerOlive/mindspore
bda20724a94113cedd12c3ed9083141012da1f15
[ "Apache-2.0" ]
3,200
2020-02-17T12:45:41.000Z
2022-03-31T20:21:16.000Z
tests/ut/python/parallel/test_manual_gatherv2.py
zimo-geek/mindspore
665ec683d4af85c71b2a1f0d6829356f2bc0e1ff
[ "Apache-2.0" ]
176
2020-02-12T02:52:11.000Z
2022-03-28T22:15:55.000Z
tests/ut/python/parallel/test_manual_gatherv2.py
zimo-geek/mindspore
665ec683d4af85c71b2a1f0d6829356f2bc0e1ff
[ "Apache-2.0" ]
621
2020-03-09T01:31:41.000Z
2022-03-30T03:43:19.000Z
# Copyright 2020 Huawei Technologies Co., Ltd # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to...
37.703125
117
0.654234
1,016
7,239
4.448819
0.17126
0.016372
0.013274
0.014159
0.565044
0.546018
0.540265
0.530973
0.512389
0.49115
0
0.061707
0.194088
7,239
191
118
37.900524
0.713061
0.088134
0
0.479167
0
0
0.053143
0.006985
0
0
0
0
0
1
0.111111
false
0
0.055556
0
0.180556
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe4088c9d39d6abd819f54e637798544df93b9db
3,396
py
Python
ClemBot.Bot/bot/api/tag_route.py
makayla-moster/ClemBot
26503d25f1fbe2abcf99dbf0f68b17e88ad11a7c
[ "MIT" ]
121
2020-04-25T06:20:28.000Z
2021-06-07T03:08:46.000Z
ClemBot.Bot/bot/api/tag_route.py
makayla-moster/ClemBot
26503d25f1fbe2abcf99dbf0f68b17e88ad11a7c
[ "MIT" ]
180
2020-04-25T04:49:51.000Z
2021-06-22T15:21:30.000Z
ClemBot.Bot/bot/api/tag_route.py
makayla-moster/ClemBot
26503d25f1fbe2abcf99dbf0f68b17e88ad11a7c
[ "MIT" ]
72
2020-04-25T03:28:49.000Z
2021-06-20T20:17:00.000Z
from bot.api.api_client import ApiClient from bot.api.base_route import BaseRoute import typing as t from bot.models import Tag class TagRoute(BaseRoute): def __init__(self, api_client: ApiClient): super().__init__(api_client) async def create_tag(self, name: str, content: str, guild_id: int, user_...
33.294118
114
0.564193
457
3,396
4.030635
0.170678
0.068404
0.043431
0.053203
0.652009
0.598263
0.561346
0.4962
0.366992
0.317047
0
0
0.324794
3,396
101
115
33.623762
0.803314
0
0
0.506849
0
0
0.073814
0.007733
0
0
0
0
0
1
0.013699
false
0
0.054795
0
0.260274
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe40ab7f78d9978c2d19631879cf3439c2112560
2,967
py
Python
formfactor_AL.py
kirichoi/PolymerConnectome
064df932cfca57a97e62dfa9a32d1fa976500906
[ "MIT" ]
null
null
null
formfactor_AL.py
kirichoi/PolymerConnectome
064df932cfca57a97e62dfa9a32d1fa976500906
[ "MIT" ]
null
null
null
formfactor_AL.py
kirichoi/PolymerConnectome
064df932cfca57a97e62dfa9a32d1fa976500906
[ "MIT" ]
null
null
null
# -*- coding: utf-8 -*- """ Created on Mon Sep 7 10:59:00 2020 @author: user """ import numpy as np import multiprocessing as mp import matplotlib.pyplot as plt import time import itertools import ctypes def formfactor(args): # with AL_dist_flat_glo.get_lock: AL_dist_flat_glo_r = np.frombuffer(AL_dist_flat_...
33.337079
110
0.625211
528
2,967
3.291667
0.246212
0.069045
0.115075
0.112198
0.574799
0.478711
0.406214
0.372267
0.27733
0.253165
0
0.052326
0.188406
2,967
88
111
33.715909
0.669435
0.305022
0
0
0
0
0.047151
0.011788
0
0
0
0
0
1
0.042553
false
0
0.12766
0
0.191489
0.021277
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe427f872414bfa986cd9b2c48b6113399437840
1,039
py
Python
utils/tests.py
nanodude/cairocffi
9d6a9a420a91da80f7901ace9945fd864f5d04dc
[ "BSD-3-Clause" ]
null
null
null
utils/tests.py
nanodude/cairocffi
9d6a9a420a91da80f7901ace9945fd864f5d04dc
[ "BSD-3-Clause" ]
null
null
null
utils/tests.py
nanodude/cairocffi
9d6a9a420a91da80f7901ace9945fd864f5d04dc
[ "BSD-3-Clause" ]
null
null
null
# coding: utf-8 import io import cairo # pycairo import cairocffi from pycairo_to_cairocffi import _UNSAFE_pycairo_context_to_cairocffi from cairocffi_to_pycairo import _UNSAFE_cairocffi_context_to_pycairo import pango_example def test(): cairocffi_context = cairocffi.Context(cairocffi.PDFSurface(N...
34.633333
79
0.73821
139
1,039
5.122302
0.33813
0.179775
0.105337
0.046348
0.296348
0.122191
0.122191
0.122191
0.122191
0.122191
0
0.032407
0.168431
1,039
29
80
35.827586
0.791667
0.06256
0
0
0
0
0.012752
0
0
0
0
0
0.25
1
0.05
false
0
0.3
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
fe440692a08637fae6bb18f0a67dbb7336fec900
1,909
py
Python
gentable/gen_test_cases.py
selavy/studies
e17b91ffab193e46fec00cf2b8070dbf1f2c39e3
[ "MIT" ]
null
null
null
gentable/gen_test_cases.py
selavy/studies
e17b91ffab193e46fec00cf2b8070dbf1f2c39e3
[ "MIT" ]
null
null
null
gentable/gen_test_cases.py
selavy/studies
e17b91ffab193e46fec00cf2b8070dbf1f2c39e3
[ "MIT" ]
null
null
null
#!/usr/bin/env python3 import random N = 32 M = 64 # NOTE: 0 is a reserved value randu = lambda x: random.randint(1, 2**x-1) randU32 = lambda: randu(32) randU64 = lambda: randu(64) fmt_by_dtype = { 'u32hex': '0x{:08x}', 'u64hex': '0x{:016x}', } cpp_by_dtype = { 'u32hex': 'uint32_t', 'u64hex': 'ui...
24.474359
83
0.572027
271
1,909
3.940959
0.313653
0.02809
0.05618
0.030899
0.169476
0.142322
0.041199
0
0
0
0
0.060201
0.216867
1,909
77
84
24.792208
0.654181
0.224725
0
0.102041
0
0
0.182561
0.014305
0
0
0
0
0
1
0.081633
false
0
0.020408
0.040816
0.122449
0.265306
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe449c44aa57e39f59499c7b75ef20b3e5b78b64
6,143
py
Python
examples/toy_env/run_toy_env.py
aaspeel/deer
3ced3695f0ca8537337019d2e3ec0ff8bd346d91
[ "BSD-3-Clause" ]
null
null
null
examples/toy_env/run_toy_env.py
aaspeel/deer
3ced3695f0ca8537337019d2e3ec0ff8bd346d91
[ "BSD-3-Clause" ]
null
null
null
examples/toy_env/run_toy_env.py
aaspeel/deer
3ced3695f0ca8537337019d2e3ec0ff8bd346d91
[ "BSD-3-Clause" ]
null
null
null
"""Toy environment launcher. See the docs for more details about this environment. """ import sys import logging import numpy as np from deer.default_parser import process_args from deer.agent import NeuralAgent from deer.learning_algos.q_net_keras import MyQNetwork from Toy_env import MyEnv as Toy_env import deer.e...
39.378205
120
0.689891
764
6,143
5.408377
0.33377
0.029042
0.018877
0.015247
0.055179
0.040658
0.023233
0
0
0
0
0.015886
0.221227
6,143
155
121
39.632258
0.847826
0.447664
0
0.11828
0
0
0.010756
0
0
0
0
0
0
1
0
false
0
0.096774
0
0.354839
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe44a3208c6d0b6455e3244b9bf2ee35ca9096e2
626
py
Python
equilibration/sodium_models/seed_1/post_processing/rdf_calculations.py
Dynamical-Systems-Laboratory/IPMCsMD
7f0662568d37dce7dcd07b648284aa62991d343c
[ "MIT" ]
2
2020-10-30T16:17:01.000Z
2021-08-23T13:58:03.000Z
equilibration/sodium_models/seed_9/post_processing/rdf_calculations.py
atruszkowska/IPMCsMD
d3900ea4da453bcc037fd946a2ae61cc67e316f5
[ "MIT" ]
null
null
null
equilibration/sodium_models/seed_9/post_processing/rdf_calculations.py
atruszkowska/IPMCsMD
d3900ea4da453bcc037fd946a2ae61cc67e316f5
[ "MIT" ]
3
2020-09-14T20:42:47.000Z
2021-12-13T07:58:16.000Z
# ------------------------------------------------------------------ # # RDF and CN related analysis # # ------------------------------------------------------------------ import sys py_path = '../../../../postprocessing/' sys.path.insert(0, py_path) py_path = '../../../../postprocessing/io_operations/' sys.path.inse...
17.885714
68
0.543131
77
626
4.194805
0.480519
0.074303
0.049536
0.086687
0.123839
0.123839
0
0
0
0
0
0.012821
0.127796
626
34
69
18.411765
0.578755
0.376997
0
0.166667
0
0
0.266667
0.181333
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
fe463c850bc48b7b739387d099ca1d849b457791
1,675
py
Python
venv/Lib/site-packages/plotnine/geoms/geom_pointrange.py
EkremBayar/bayar
aad1a32044da671d0b4f11908416044753360b39
[ "MIT" ]
null
null
null
venv/Lib/site-packages/plotnine/geoms/geom_pointrange.py
EkremBayar/bayar
aad1a32044da671d0b4f11908416044753360b39
[ "MIT" ]
1
2020-10-02T21:43:06.000Z
2020-10-15T22:52:39.000Z
venv/Lib/site-packages/plotnine/geoms/geom_pointrange.py
EkremBayar/bayar
aad1a32044da671d0b4f11908416044753360b39
[ "MIT" ]
null
null
null
from ..doctools import document from .geom import geom from .geom_path import geom_path from .geom_point import geom_point from .geom_linerange import geom_linerange @document class geom_pointrange(geom): """ Vertical interval represented by a line with a point {usage} Parameters ---------- ...
29.385965
70
0.577313
194
1,675
4.835052
0.42268
0.057569
0.063966
0.057569
0.284648
0.202559
0.202559
0.202559
0.127932
0.127932
0
0.004177
0.285373
1,675
56
71
29.910714
0.779449
0.216716
0
0.153846
0
0
0.121084
0
0
0
0
0
0
1
0.076923
false
0
0.192308
0
0.461538
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe468cffe0b2fb47619682741847648e0145af63
3,704
py
Python
app/backend-test/core_models/keras-experiments/run02_try_simple_CNN_generate.py
SummaLabs/DLS
2adba47430b456ad0f324e4c8883a896a23b3fbf
[ "MIT" ]
32
2017-09-04T17:40:39.000Z
2021-02-16T23:08:34.000Z
app/backend-test/core_models/keras-experiments/run02_try_simple_CNN_generate.py
AymanNabih/DLS
2adba47430b456ad0f324e4c8883a896a23b3fbf
[ "MIT" ]
3
2017-10-09T12:52:54.000Z
2020-06-29T02:48:38.000Z
app/backend-test/core_models/keras-experiments/run02_try_simple_CNN_generate.py
AymanNabih/DLS
2adba47430b456ad0f324e4c8883a896a23b3fbf
[ "MIT" ]
20
2017-10-07T17:29:50.000Z
2021-01-23T22:01:54.000Z
#!/usr/bin/python # -*- coding: utf-8 -*- __author__ = 'ar' import json import os import skimage.io as skio import matplotlib.pyplot as plt import numpy as np import keras from keras.models import Model from keras.layers import Input, Convolution2D, MaxPooling2D, Flatten, Dense from keras.utils.visualize_util import ...
31.389831
108
0.551026
418
3,704
4.739234
0.301435
0.04846
0.040384
0.055528
0.341747
0.289248
0.25896
0.229682
0.215548
0.215548
0
0.025516
0.280508
3,704
117
109
31.65812
0.717824
0.046976
0
0.145833
0
0
0.085773
0.00644
0
0
0
0
0
1
0.03125
false
0
0.09375
0
0.15625
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
fe4908b1c0b067e1655d4c242e84ebb2602b1af5
11,218
py
Python
src/main.py
srijankr/DAIN
89edec24e63383dfd5ef19f2bfb48d11b75b3dde
[ "Apache-2.0" ]
3
2021-08-19T20:11:45.000Z
2021-08-23T14:20:11.000Z
src/main.py
srijankr/DAIN
89edec24e63383dfd5ef19f2bfb48d11b75b3dde
[ "Apache-2.0" ]
null
null
null
src/main.py
srijankr/DAIN
89edec24e63383dfd5ef19f2bfb48d11b75b3dde
[ "Apache-2.0" ]
null
null
null
#@contact Sejoon Oh (soh337@gatech.edu), Georgia Institute of Technology #@version 1.0 #@date 2021-08-17 #Influence-guided Data Augmentation for Neural Tensor Completion (DAIN) #This software is free of charge under research purposes. #For commercial purposes, please contact the main author. import torch f...
45.97541
201
0.668123
1,505
11,218
4.821262
0.168106
0.020673
0.019294
0.013093
0.375
0.29355
0.246692
0.213341
0.213341
0.191428
0
0.015459
0.204225
11,218
243
202
46.164609
0.797356
0.047602
0
0.179894
0
0.015873
0.125679
0.002343
0
0
0
0
0
1
0.021164
false
0
0.137566
0
0.174603
0.089947
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe4b1dcb47180e465318d2ca261b6bc60c83e970
1,933
py
Python
backend/app/auth/service.py
pers0n4/yoonyaho
cf7518667bc7cefff0f9534a5e0af89b261cfed7
[ "MIT" ]
null
null
null
backend/app/auth/service.py
pers0n4/yoonyaho
cf7518667bc7cefff0f9534a5e0af89b261cfed7
[ "MIT" ]
16
2021-04-04T10:58:24.000Z
2021-05-23T11:52:08.000Z
backend/app/auth/service.py
pers0n4/yoonyaho
cf7518667bc7cefff0f9534a5e0af89b261cfed7
[ "MIT" ]
null
null
null
from datetime import datetime, timedelta import jwt from flask import current_app from app import db from app.user.repository import UserRepository class AuthService: def __init__(self) -> None: self._user_repository = UserRepository(db.session) def create_token(self, data) -> dict: user = ...
30.203125
88
0.558717
201
1,933
5.174129
0.273632
0.040385
0.061538
0.084615
0.575
0.550962
0.495192
0.495192
0.495192
0.495192
0
0.013107
0.329022
1,933
63
89
30.68254
0.788743
0.019659
0
0.408163
0
0
0.079852
0
0
0
0
0
0
1
0.081633
false
0.020408
0.102041
0.020408
0.265306
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe4c72b51d2a6fb97aa207f15cdf6884d9d32013
4,843
py
Python
scripts/qlearn.py
kebaek/minigrid
3808c1401ea7846febf88d0a2fb2aa39e4a4913f
[ "MIT" ]
5
2021-09-29T18:53:37.000Z
2022-03-01T08:03:42.000Z
scripts/qlearn.py
kebaek/minigrid
3808c1401ea7846febf88d0a2fb2aa39e4a4913f
[ "MIT" ]
null
null
null
scripts/qlearn.py
kebaek/minigrid
3808c1401ea7846febf88d0a2fb2aa39e4a4913f
[ "MIT" ]
null
null
null
import _init_paths import argparse import random import time import utils import os from collections import defaultdict import numpy as np import csv from progress.bar import IncrementalBar from utils.hash import * def parse_arguments(): parser = argparse.ArgumentParser() # add arguments parser.add_argume...
38.133858
175
0.628536
617
4,843
4.726094
0.243112
0.039095
0.067215
0.01749
0.215706
0.159122
0.125514
0.093964
0.066529
0.066529
0
0.010301
0.258311
4,843
126
176
38.436508
0.801503
0.026843
0
0.118812
0
0
0.148597
0.009354
0
0
0
0
0
1
0.029703
false
0
0.108911
0
0.148515
0.069307
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe4cffed78f06b24cc3c09215a327c208310e601
1,634
py
Python
research/tunnel.py
carrino/FrisPy
db9e59f465ee25d1c037d580c37da8f35b930b50
[ "MIT" ]
null
null
null
research/tunnel.py
carrino/FrisPy
db9e59f465ee25d1c037d580c37da8f35b930b50
[ "MIT" ]
null
null
null
research/tunnel.py
carrino/FrisPy
db9e59f465ee25d1c037d580c37da8f35b930b50
[ "MIT" ]
null
null
null
import math from pprint import pprint import matplotlib.pyplot as plt from scipy.optimize import minimize from frispy import Disc from frispy import Discs from frispy import Model model = Discs.roc mph_to_mps = 0.44704 v = 56 * mph_to_mps rot = -v / model.diameter ceiling = 4 # 4 meter ceiling tunnel_width = 4 # 4 ...
27.694915
113
0.621787
274
1,634
3.649635
0.350365
0.036
0.044
0.04
0.282
0.282
0.216
0.16
0.16
0.16
0
0.04234
0.205018
1,634
58
114
28.172414
0.727483
0.050184
0
0.04878
0
0
0.047896
0
0
0
0
0
0
1
0.02439
false
0
0.170732
0
0.268293
0.073171
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe4e0e23c7947f7d713c88797190743b2b4ea285
1,450
py
Python
openfermioncirq/variational/ansatzes/swap_network_trotter_hubbard_test.py
unpilbaek/OpenFermion-Cirq
d2f5a871bb5aea1e53d280c0a0e4be999b0c8d9d
[ "Apache-2.0" ]
278
2018-07-18T23:43:16.000Z
2022-01-02T21:38:08.000Z
openfermioncirq/variational/ansatzes/swap_network_trotter_hubbard_test.py
unpilbaek/OpenFermion-Cirq
d2f5a871bb5aea1e53d280c0a0e4be999b0c8d9d
[ "Apache-2.0" ]
131
2018-07-18T19:04:58.000Z
2020-08-04T21:05:42.000Z
openfermioncirq/variational/ansatzes/swap_network_trotter_hubbard_test.py
unpilbaek/OpenFermion-Cirq
d2f5a871bb5aea1e53d280c0a0e4be999b0c8d9d
[ "Apache-2.0" ]
101
2018-07-18T21:43:50.000Z
2022-03-04T09:51:02.000Z
# Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distribu...
41.428571
80
0.65931
210
1,450
4.471429
0.414286
0.021299
0.019169
0.021299
0.374867
0.374867
0.374867
0.374867
0.366347
0.366347
0
0.049912
0.212414
1,450
34
81
42.647059
0.772329
0.370345
0
0.470588
0
0
0.027809
0
0
0
0
0
0.352941
1
0.058824
false
0
0.058824
0
0.117647
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe52100e092cba8f28b9f872d87740877e78ee29
5,535
py
Python
functest/opnfv_tests/openstack/shaker/shaker.py
opnfv-poc/functest
4f54b282cabccef2a53e21c77c81b60fe890a8a4
[ "Apache-2.0" ]
null
null
null
functest/opnfv_tests/openstack/shaker/shaker.py
opnfv-poc/functest
4f54b282cabccef2a53e21c77c81b60fe890a8a4
[ "Apache-2.0" ]
null
null
null
functest/opnfv_tests/openstack/shaker/shaker.py
opnfv-poc/functest
4f54b282cabccef2a53e21c77c81b60fe890a8a4
[ "Apache-2.0" ]
null
null
null
#!/usr/bin/env python # Copyright (c) 2018 Orange and others. # # All rights reserved. This program and the accompanying materials # are made available under the terms of the Apache License, Version 2.0 # which accompanies this distribution, and is available at # http://www.apache.org/licenses/LICENSE-2.0 """ Shaker_...
37.910959
79
0.605239
679
5,535
4.740795
0.39028
0.041007
0.036347
0.014911
0.131718
0.082634
0.068966
0.068966
0.068966
0.045356
0
0.012935
0.273713
5,535
145
80
38.172414
0.787811
0.134417
0
0.073395
0
0.009174
0.218935
0.042688
0
0
0
0
0.009174
1
0.045872
false
0.018349
0.055046
0
0.247706
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe5674a5616780733e828478139977dd1166a1db
2,288
py
Python
library/pandas_utils.py
SACGF/variantgrid
515195e2f03a0da3a3e5f2919d8e0431babfd9c9
[ "RSA-MD" ]
5
2021-01-14T03:34:42.000Z
2022-03-07T15:34:18.000Z
library/pandas_utils.py
SACGF/variantgrid
515195e2f03a0da3a3e5f2919d8e0431babfd9c9
[ "RSA-MD" ]
551
2020-10-19T00:02:38.000Z
2022-03-30T02:18:22.000Z
library/pandas_utils.py
SACGF/variantgrid
515195e2f03a0da3a3e5f2919d8e0431babfd9c9
[ "RSA-MD" ]
null
null
null
import os import sys import numpy as np import pandas as pd def get_columns_percent_dataframe(df: pd.DataFrame, totals_column=None, percent_names=True) -> pd.DataFrame: """ @param totals_column: (default = use sum of columns) @param percent_names: Rename names from 'col' => 'col %' Return a dataframe...
28.6
108
0.649913
338
2,288
4.213018
0.281065
0.108146
0.063904
0.042135
0.257725
0.192416
0.183287
0.161517
0.11236
0.11236
0
0.010315
0.237325
2,288
79
109
28.962025
0.805731
0.137675
0
0.039216
0
0
0.013361
0
0
0
0
0
0
1
0.176471
false
0
0.078431
0.039216
0.431373
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe5794e6af44c9c1406d19b02f67dd498db59356
2,676
py
Python
create/create_args_test.py
CarbonROM/android_tools_acloud
0ed5352df639789767d8ea6fe0a510d7a84cfdcc
[ "Apache-2.0" ]
null
null
null
create/create_args_test.py
CarbonROM/android_tools_acloud
0ed5352df639789767d8ea6fe0a510d7a84cfdcc
[ "Apache-2.0" ]
null
null
null
create/create_args_test.py
CarbonROM/android_tools_acloud
0ed5352df639789767d8ea6fe0a510d7a84cfdcc
[ "Apache-2.0" ]
null
null
null
# Copyright 2020 - The Android Open Source Project # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or ...
32.240964
74
0.702167
339
2,676
5.336283
0.454277
0.039801
0.039801
0.039801
0.114981
0.071863
0.071863
0.071863
0.071863
0.071863
0
0.004331
0.223468
2,676
82
75
32.634146
0.866218
0.37855
0
0.093023
0
0
0.004994
0
0
0
0
0
0.069767
1
0.069767
false
0.023256
0.139535
0
0.255814
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe57a342e2e561171bed3dec28d69a69629da501
452
py
Python
setup.py
Kannuki-san/msman
adc275ad0508d65753c8424e7f6b94becee0b855
[ "MIT" ]
null
null
null
setup.py
Kannuki-san/msman
adc275ad0508d65753c8424e7f6b94becee0b855
[ "MIT" ]
null
null
null
setup.py
Kannuki-san/msman
adc275ad0508d65753c8424e7f6b94becee0b855
[ "MIT" ]
null
null
null
#!/usr/bin/env python # -*- coding: utf-8 -*- import sys from cx_Freeze import setup,Executable icondata='icon.ico' base = None # GUI=有効, CUI=無効 にする if sys.platform == 'win32' : base = 'win32GUI' exe = Executable(script = 'main.py', base = base, #icon=icondata ...
17.384615
47
0.550885
52
452
4.769231
0.807692
0
0
0
0
0
0
0
0
0
0
0.022436
0.309735
452
26
48
17.384615
0.772436
0.163717
0
0
0
0
0.16
0
0
0
0
0
0
1
0
false
0
0.153846
0
0.153846
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe57f5cf47823b7ec7c95916bb4e6edc61679b1b
2,903
py
Python
stereotype/roles.py
petee-d/stereotype
33a2efc826fd907bd23ffb4e8f7cba119ff022ce
[ "MIT" ]
6
2021-05-26T10:45:50.000Z
2022-01-31T17:36:10.000Z
stereotype/roles.py
petee-d/stereotype
33a2efc826fd907bd23ffb4e8f7cba119ff022ce
[ "MIT" ]
null
null
null
stereotype/roles.py
petee-d/stereotype
33a2efc826fd907bd23ffb4e8f7cba119ff022ce
[ "MIT" ]
null
null
null
from __future__ import annotations from threading import Lock from typing import List, Set, Optional, Any, Tuple from stereotype.utils import ConfigurationError class Role: __slots__ = ('code', 'name', 'empty_by_default') def __init__(self, name: str, empty_by_default: bool = False): self.name = na...
34.975904
111
0.654151
344
2,903
5.18314
0.241279
0.092541
0.047112
0.050477
0.154795
0.117779
0.089736
0.089736
0.089736
0.089736
0
0.000456
0.244575
2,903
82
112
35.402439
0.812586
0
0
0.081967
0
0
0.093352
0.021702
0
0
0
0
0.016393
1
0.163934
false
0
0.065574
0.081967
0.42623
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe59e0ae9caf8657811351b2ce6b7040c6d723dc
7,175
py
Python
WEB21-1-12/WEB2/power/zvl_test.py
coderdq/vuetest
28ea4f36e2c4e7e80d1ba1777ef312733ef84048
[ "MIT" ]
null
null
null
WEB21-1-12/WEB2/power/zvl_test.py
coderdq/vuetest
28ea4f36e2c4e7e80d1ba1777ef312733ef84048
[ "MIT" ]
null
null
null
WEB21-1-12/WEB2/power/zvl_test.py
coderdq/vuetest
28ea4f36e2c4e7e80d1ba1777ef312733ef84048
[ "MIT" ]
null
null
null
# coding:utf-8 ''' 矢网的测试项,包括增益,带内波动,VSWR 一个曲线最多建10个marker ''' import os import logging from commoninterface.zvlbase import ZVLBase logger = logging.getLogger('ghost') class HandleZVL(object): def __init__(self, ip, offset): self.zvl = None self.ip = ip self.offset = float(offset) def...
34.830097
108
0.557073
879
7,175
4.386803
0.202503
0.058091
0.073911
0.032676
0.486515
0.432313
0.392894
0.280083
0.256743
0.225104
0
0.043612
0.319303
7,175
205
109
35
0.745905
0.106481
0
0.414286
0
0
0.058075
0.011256
0
0
0
0
0
1
0.078571
false
0
0.021429
0
0.192857
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe5a25378e13e098be2b1cdb76f7062e2c91b9b5
2,410
py
Python
kshell/partial_level_density.py
ErlendLima/70Zn
1bf73adec5a3960e195788bc1f4bc79b2086be64
[ "MIT" ]
null
null
null
kshell/partial_level_density.py
ErlendLima/70Zn
1bf73adec5a3960e195788bc1f4bc79b2086be64
[ "MIT" ]
null
null
null
kshell/partial_level_density.py
ErlendLima/70Zn
1bf73adec5a3960e195788bc1f4bc79b2086be64
[ "MIT" ]
null
null
null
from __future__ import division import numpy as np import matplotlib.pyplot as plt import shellmodelutilities as smutil # Set bin width and range bin_width = 0.20 Emax = 14 Nbins = int(np.ceil(Emax/bin_width)) Emax_adjusted = bin_width*Nbins # Trick to get an integer number of bins bins = np.linspace(0,Emax_adjust...
34.927536
170
0.674274
446
2,410
3.515695
0.374439
0.040179
0.044643
0.033163
0.102041
0.102041
0.102041
0.102041
0.102041
0.102041
0
0.068226
0.148548
2,410
68
171
35.441176
0.695906
0.26805
0
0.047619
0
0
0.04298
0.012607
0
0
0
0
0
1
0.02381
false
0
0.119048
0
0.190476
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe5b20986b78369a49dfb31999fcc5213f36f3e2
15,480
py
Python
tests/integration/test_provider_base.py
neuro-inc/platform-buckets-api
ba04edeb8565fa06e5af6d0316957a8816b087b2
[ "Apache-2.0" ]
null
null
null
tests/integration/test_provider_base.py
neuro-inc/platform-buckets-api
ba04edeb8565fa06e5af6d0316957a8816b087b2
[ "Apache-2.0" ]
55
2021-11-16T00:26:52.000Z
2022-03-29T03:16:55.000Z
tests/integration/test_provider_base.py
neuro-inc/platform-buckets-api
ba04edeb8565fa06e5af6d0316957a8816b087b2
[ "Apache-2.0" ]
null
null
null
import abc import secrets from collections.abc import AsyncIterator, Awaitable, Callable, Mapping from contextlib import AbstractAsyncContextManager, asynccontextmanager from dataclasses import dataclass from datetime import datetime, timezone import pytest from aiohttp import ClientSession from yarl import URL from ...
35.022624
88
0.655749
1,686
15,480
5.734282
0.094306
0.124535
0.080575
0.097745
0.738519
0.695801
0.6536
0.618225
0.609433
0.597745
0
0.005208
0.268152
15,480
441
89
35.102041
0.848177
0.000969
0
0.577128
0
0
0.030201
0
0
0
0
0
0.047872
1
0.007979
false
0.010638
0.047872
0.005319
0.103723
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe5bf9f4fe33b1e74de5e5a8a91381afcd0d937c
576
py
Python
appserver/search/views.py
sinag/SWE574-Horuscope
9725dd356cbfd19f0ce88d4a208c872be765bd88
[ "MIT" ]
null
null
null
appserver/search/views.py
sinag/SWE574-Horuscope
9725dd356cbfd19f0ce88d4a208c872be765bd88
[ "MIT" ]
null
null
null
appserver/search/views.py
sinag/SWE574-Horuscope
9725dd356cbfd19f0ce88d4a208c872be765bd88
[ "MIT" ]
1
2020-08-07T12:54:51.000Z
2020-08-07T12:54:51.000Z
from django.http import HttpResponse from django.shortcuts import render, redirect from community.models import Community # Create your views here. def search_basic(request): communities = None if request.POST: community_query = request.POST.get('community_search', False) communities = Commun...
30.315789
88
0.744792
65
576
6.476923
0.492308
0.078385
0.109264
0.142518
0.320665
0.320665
0.320665
0.320665
0.320665
0.320665
0
0
0.161458
576
18
89
32
0.871636
0.039931
0
0.181818
0
0
0.156934
0.087591
0
0
0
0
0
1
0.090909
false
0
0.272727
0
0.545455
0.090909
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe5c97158341c4d0d209389c3a2affb30b2d34bf
9,772
py
Python
qcodes_contrib_drivers/drivers/Oxford/ILM200.py
jenshnielsen/Qcodes_contrib_drivers
dc878cdd99a62f4643a62163a3a6341f98cee440
[ "MIT" ]
null
null
null
qcodes_contrib_drivers/drivers/Oxford/ILM200.py
jenshnielsen/Qcodes_contrib_drivers
dc878cdd99a62f4643a62163a3a6341f98cee440
[ "MIT" ]
2
2020-05-29T11:00:52.000Z
2020-10-09T06:18:11.000Z
qcodes_contrib_drivers/drivers/Oxford/ILM200.py
jenshnielsen/Qcodes_contrib_drivers
dc878cdd99a62f4643a62163a3a6341f98cee440
[ "MIT" ]
1
2020-04-24T01:15:44.000Z
2020-04-24T01:15:44.000Z
# OxfordInstruments_ILM200.py class, to perform the communication between the Wrapper and the device # Copyright (c) 2017 QuTech (Delft) # Code is available under the available under the `MIT open-source license <https://opensource.org/licenses/MIT>`__ # # Pieter Eendebak <pieter.eendebak@tno.nl>, 2017 # Takafumi Fujit...
32.144737
115
0.556283
1,147
9,772
4.589364
0.28422
0.018617
0.031345
0.028875
0.237652
0.140957
0.115122
0.079407
0.06345
0.06345
0
0.019994
0.344863
9,772
303
116
32.250825
0.802249
0.360827
0
0.134921
0
0
0.163254
0
0
0
0
0
0
1
0.126984
false
0
0.031746
0
0.222222
0.007937
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe5cdd0275ff0c38add8e228ff02333ee397a98c
4,417
py
Python
load_cifar_10.py
xgxofdream/CNN-Using-Local-CIFAR-10-dataset
8076056da58a5b564ded50f4cdb059585deb900d
[ "Apache-2.0" ]
null
null
null
load_cifar_10.py
xgxofdream/CNN-Using-Local-CIFAR-10-dataset
8076056da58a5b564ded50f4cdb059585deb900d
[ "Apache-2.0" ]
null
null
null
load_cifar_10.py
xgxofdream/CNN-Using-Local-CIFAR-10-dataset
8076056da58a5b564ded50f4cdb059585deb900d
[ "Apache-2.0" ]
null
null
null
import numpy as np import matplotlib.pyplot as plt import pickle """ The CIFAR-10 dataset consists of 60000 32x32 colour images in 10 classes, with 6000 images per class. There are 50000 training images and 10000 test images. The dataset is divided into five training batches and one test batch, each with 10000 image...
36.808333
118
0.699796
645
4,417
4.494574
0.244961
0.096585
0.086927
0.037254
0.361159
0.298034
0.162815
0.12832
0.098655
0.073129
0
0.029047
0.197193
4,417
119
119
37.117647
0.788494
0.150781
0
0.078125
0
0
0.070058
0
0
0
0
0
0
1
0.03125
false
0
0.046875
0
0.109375
0.109375
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe5d25adf1fa45402acfda5811c79b3110e5df76
3,054
py
Python
volatility3/framework/plugins/mac/lsmod.py
leohearts/volatility3
f52bd8d74fc47e63ea2611d0171b63dc589d4fdf
[ "Linux-OpenIB" ]
null
null
null
volatility3/framework/plugins/mac/lsmod.py
leohearts/volatility3
f52bd8d74fc47e63ea2611d0171b63dc589d4fdf
[ "Linux-OpenIB" ]
null
null
null
volatility3/framework/plugins/mac/lsmod.py
leohearts/volatility3
f52bd8d74fc47e63ea2611d0171b63dc589d4fdf
[ "Linux-OpenIB" ]
null
null
null
# This file is Copyright 2019 Volatility Foundation and licensed under the Volatility Software License 1.0 # which is available at https://www.volatilityfoundation.org/license/vsl-v1.0 # """A module containing a collection of plugins that produce data typically found in Mac's lsmod command.""" from volatility3.framewor...
34.704545
114
0.630321
337
3,054
5.599407
0.388724
0.039746
0.063593
0.023847
0.073132
0.073132
0.073132
0.073132
0.073132
0.073132
0
0.013755
0.285855
3,054
87
115
35.103448
0.851444
0.208579
0
0.28
0
0
0.044406
0
0
0
0
0
0
1
0.08
false
0
0.1
0.04
0.34
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe5f1c04bf52b3ba6d57139fe21bba52f39a4f4c
6,901
py
Python
pyscf/prop/esr/uks.py
azag0/pyscf
1e3e27b61b3cfd22c9679d2c9851c13b3ebc5a1b
[ "Apache-2.0" ]
2
2021-08-03T12:32:25.000Z
2021-09-29T08:19:02.000Z
pyscf/prop/esr/uks.py
azag0/pyscf
1e3e27b61b3cfd22c9679d2c9851c13b3ebc5a1b
[ "Apache-2.0" ]
null
null
null
pyscf/prop/esr/uks.py
azag0/pyscf
1e3e27b61b3cfd22c9679d2c9851c13b3ebc5a1b
[ "Apache-2.0" ]
2
2020-06-01T05:31:38.000Z
2022-02-08T02:38:33.000Z
#!/usr/bin/env python # Copyright 2014-2019 The PySCF Developers. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # U...
36.707447
89
0.613534
1,128
6,901
3.580674
0.263298
0.02253
0.035405
0.040852
0.321862
0.281753
0.240654
0.235702
0.195098
0.167863
0
0.060419
0.246921
6,901
187
90
36.903743
0.71676
0.156354
0
0.092308
0
0
0.045643
0
0
0
0
0
0
1
0.038462
false
0
0.084615
0
0.169231
0.023077
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe605cdea9d8787846418bf36b3fc74d17111206
11,661
py
Python
corehq/apps/domain/deletion.py
shyamkumarlchauhan/commcare-hq
99df931bcf56e9fbe15d8fcb0dc98b5a3957fb48
[ "BSD-3-Clause" ]
null
null
null
corehq/apps/domain/deletion.py
shyamkumarlchauhan/commcare-hq
99df931bcf56e9fbe15d8fcb0dc98b5a3957fb48
[ "BSD-3-Clause" ]
null
null
null
corehq/apps/domain/deletion.py
shyamkumarlchauhan/commcare-hq
99df931bcf56e9fbe15d8fcb0dc98b5a3957fb48
[ "BSD-3-Clause" ]
null
null
null
import itertools import logging from datetime import date from django.apps import apps from django.conf import settings from django.db import connection, transaction from django.db.models import Q from dimagi.utils.chunked import chunked from corehq.apps.accounting.models import Subscription from corehq.apps.account...
41.646429
108
0.725924
1,290
11,661
6.266667
0.256589
0.117516
0.027214
0.020411
0.17949
0.120732
0.063582
0.029193
0.029193
0.029193
0
0.000821
0.164051
11,661
279
109
41.795699
0.828478
0.047595
0
0.059091
0
0
0.223795
0.038666
0
0
0
0.003584
0
1
0.086364
false
0
0.104545
0.004545
0.227273
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe609a5c6fba0b3499c6abf7b2ebbe251d3d8901
8,056
py
Python
icosphere/icosphere.py
JackWalpole/icosahedron
5317d8eb9509abe275beb2693730e3efaa986672
[ "MIT" ]
2
2017-10-02T23:36:49.000Z
2021-12-21T06:12:16.000Z
icosphere/icosphere.py
JackWalpole/icosphere
5317d8eb9509abe275beb2693730e3efaa986672
[ "MIT" ]
null
null
null
icosphere/icosphere.py
JackWalpole/icosphere
5317d8eb9509abe275beb2693730e3efaa986672
[ "MIT" ]
null
null
null
"""Subdivided icosahedral mesh generation""" from __future__ import print_function import numpy as np # following: http://blog.andreaskahler.com/2009/06/creating-icosphere-mesh-in-code.html # hierarchy: # Icosphere -> Triangle -> Point class IcoSphere: """ Usage: IcoSphere(level) Maximum supported level =...
37.64486
96
0.544067
1,052
8,056
4.118821
0.19962
0.077544
0.083083
0.106162
0.36649
0.291715
0.17586
0.14355
0.14355
0.14355
0
0.032816
0.303997
8,056
214
97
37.64486
0.739968
0.1893
0
0.037313
0
0
0.042502
0
0
0
0
0
0
1
0.089552
false
0.007463
0.029851
0
0.186567
0.022388
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe6109edbf02869c5f97fef83d0ae614ddf0da76
8,091
py
Python
targets/baremetal-sdk/curie-bsp/setup.py
ideas-detoxes/jerryscript
42523bd6e2b114755498c9f68fd78545f9b33476
[ "Apache-2.0" ]
4,324
2016-11-25T11:25:27.000Z
2022-03-31T03:24:49.000Z
targets/baremetal-sdk/curie-bsp/setup.py
ideas-detoxes/jerryscript
42523bd6e2b114755498c9f68fd78545f9b33476
[ "Apache-2.0" ]
2,099
2016-11-25T08:08:59.000Z
2022-03-12T07:41:20.000Z
targets/baremetal-sdk/curie-bsp/setup.py
lygstate/jerryscript
55acdf2048b390d0f56f12e64dbfb2559f0e70ad
[ "Apache-2.0" ]
460
2016-11-25T07:16:10.000Z
2022-03-24T14:05:29.000Z
#!/usr/bin/env python # Copyright JS Foundation and other contributors, http://js.foundation # # 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....
32.107143
113
0.66024
1,100
8,091
4.607273
0.224545
0.036701
0.04341
0.027624
0.20955
0.143646
0.113852
0.060576
0.053275
0.053275
0
0.006365
0.20393
8,091
251
114
32.23506
0.780469
0.193548
0
0
0
0
0.274537
0.066635
0
0
0
0
0
1
0.077419
false
0
0.019355
0
0.129032
0.025806
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe613281281e5fa651291114e4bc822aff3309a5
2,001
py
Python
duke-cs671-fall21-coupon-recommendation/outputs/rules/RF/17_features/numtrees_30/rule_20.py
apcarrik/kaggle
6e2d4db58017323e7ba5510bcc2598e01a4ee7bf
[ "MIT" ]
null
null
null
duke-cs671-fall21-coupon-recommendation/outputs/rules/RF/17_features/numtrees_30/rule_20.py
apcarrik/kaggle
6e2d4db58017323e7ba5510bcc2598e01a4ee7bf
[ "MIT" ]
null
null
null
duke-cs671-fall21-coupon-recommendation/outputs/rules/RF/17_features/numtrees_30/rule_20.py
apcarrik/kaggle
6e2d4db58017323e7ba5510bcc2598e01a4ee7bf
[ "MIT" ]
null
null
null
def findDecision(obj): #obj[0]: Passanger, obj[1]: Weather, obj[2]: Time, obj[3]: Coupon, obj[4]: Coupon_validity, obj[5]: Gender, obj[6]: Age, obj[7]: Maritalstatus, obj[8]: Children, obj[9]: Education, obj[10]: Occupation, obj[11]: Income, obj[12]: Bar, obj[13]: Coffeehouse, obj[14]: Restaurant20to50, obj[15]: Direct...
37.754717
347
0.571714
289
2,001
3.913495
0.211073
0.123784
0.095491
0.105217
0.392573
0.296198
0.20336
0.121132
0.070734
0
0
0.092534
0.216892
2,001
52
348
38.480769
0.629228
0.54023
0
0.5
0
0
0.10011
0
0
0
0
0
0
1
0.02381
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
fe61ee9fb03a144ec04e2fb8220326b27f35be96
18,786
py
Python
main.py
AdrienCourtois/DexiNed
1198c043f4ed46efd7ad7bc77edf39ba66f0f3b1
[ "MIT" ]
null
null
null
main.py
AdrienCourtois/DexiNed
1198c043f4ed46efd7ad7bc77edf39ba66f0f3b1
[ "MIT" ]
null
null
null
main.py
AdrienCourtois/DexiNed
1198c043f4ed46efd7ad7bc77edf39ba66f0f3b1
[ "MIT" ]
null
null
null
from __future__ import print_function import argparse import os import time, platform import cv2 import torch import torch.optim as optim from torch.utils.data import DataLoader from datasets import DATASET_NAMES, BipedDataset, TestDataset, dataset_info from losses import * from model import DexiNed # from model0C ...
42.406321
121
0.524806
2,107
18,786
4.475083
0.170859
0.026726
0.050483
0.01209
0.42645
0.370877
0.322304
0.303001
0.285396
0.252731
0
0.026567
0.370861
18,786
442
122
42.502262
0.771216
0.103535
0
0.340058
0
0
0.131715
0.00161
0
0
0
0
0
1
0.017291
false
0
0.037464
0
0.060519
0.048991
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe62800d500daa91f541e4f0b0257370caac7c78
5,905
py
Python
src/core/build/pretreat_targets.py
chaoyangcui/test_developertest
151309bf6cdc7e31493a3461d3c7f17a1b371c09
[ "Apache-2.0" ]
null
null
null
src/core/build/pretreat_targets.py
chaoyangcui/test_developertest
151309bf6cdc7e31493a3461d3c7f17a1b371c09
[ "Apache-2.0" ]
null
null
null
src/core/build/pretreat_targets.py
chaoyangcui/test_developertest
151309bf6cdc7e31493a3461d3c7f17a1b371c09
[ "Apache-2.0" ]
1
2021-09-13T12:03:37.000Z
2021-09-13T12:03:37.000Z
#!/usr/bin/env python3 # coding=utf-8 # # Copyright (c) 2021 Huawei Device Co., Ltd. # 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 # # Unle...
39.366667
78
0.573412
746
5,905
4.30563
0.219839
0.03736
0.0467
0.056663
0.307908
0.232254
0.188356
0.146015
0.136364
0.136364
0
0.007667
0.271126
5,905
149
79
39.630872
0.738615
0.11685
0
0.115385
0
0
0.089885
0
0
0
0
0
0
1
0.086538
false
0
0.057692
0
0.211538
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe63a253f1cf19a404c6e2b601535edfb1888800
657
py
Python
tests/testapp/urls.py
lukaszbanasiak/django-contrib-comments
8a99ed810e9e94cb9dff1c362b2c4ebe2e37dead
[ "BSD-3-Clause" ]
1
2018-05-29T08:43:57.000Z
2018-05-29T08:43:57.000Z
tests/testapp/urls.py
lukaszbanasiak/django-contrib-comments
8a99ed810e9e94cb9dff1c362b2c4ebe2e37dead
[ "BSD-3-Clause" ]
null
null
null
tests/testapp/urls.py
lukaszbanasiak/django-contrib-comments
8a99ed810e9e94cb9dff1c362b2c4ebe2e37dead
[ "BSD-3-Clause" ]
1
2018-08-25T01:38:12.000Z
2018-08-25T01:38:12.000Z
from __future__ import absolute_import from django.conf.urls import patterns, url from django_comments.feeds import LatestCommentFeed from custom_comments import views feeds = { 'comments': LatestCommentFeed, } urlpatterns = patterns('', url(r'^post/$', views.custom_submit_comment), url(r'^flag/(\d+)...
26.28
105
0.692542
78
657
5.641026
0.384615
0.045455
0.1
0
0
0
0
0
0
0
0
0
0.121766
657
24
106
27.375
0.762565
0
0
0
0
0
0.232877
0.09589
0
0
0
0
0
1
0
false
0
0.235294
0
0.235294
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe646aafd2f602c63f8aacb84f51c78795b63990
7,537
py
Python
cctbx/maptbx/tst_target_and_gradients.py
rimmartin/cctbx_project
644090f9432d9afc22cfb542fc3ab78ca8e15e5d
[ "BSD-3-Clause-LBNL" ]
null
null
null
cctbx/maptbx/tst_target_and_gradients.py
rimmartin/cctbx_project
644090f9432d9afc22cfb542fc3ab78ca8e15e5d
[ "BSD-3-Clause-LBNL" ]
null
null
null
cctbx/maptbx/tst_target_and_gradients.py
rimmartin/cctbx_project
644090f9432d9afc22cfb542fc3ab78ca8e15e5d
[ "BSD-3-Clause-LBNL" ]
null
null
null
from __future__ import division from cctbx.array_family import flex from cctbx import xray from cctbx import crystal from cctbx import maptbx from cctbx.maptbx import minimization from libtbx.test_utils import approx_equal import random from cctbx.development import random_structure from cctbx import sgtbx if (1): r...
36.235577
80
0.667109
1,089
7,537
4.277319
0.146924
0.025762
0.036496
0.041219
0.681408
0.653499
0.608416
0.588235
0.563332
0.5
0
0.031118
0.21547
7,537
207
81
36.410628
0.756638
0.043784
0
0.502793
0
0
0.009516
0
0
0
0
0
0.089385
1
0.055866
false
0
0.055866
0
0.139665
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe66e2796ab20353c3b7dbe7a834d55cb22ebb8a
1,212
py
Python
open_imagilib/matrix.py
viktor-ferenczi/open-imagilib
3e7328840d58fd49eda28490e9bddf91390b1981
[ "MIT" ]
2
2022-01-17T17:22:01.000Z
2022-01-22T13:11:33.000Z
open_imagilib/matrix.py
viktor-ferenczi/open-imagilib
3e7328840d58fd49eda28490e9bddf91390b1981
[ "MIT" ]
null
null
null
open_imagilib/matrix.py
viktor-ferenczi/open-imagilib
3e7328840d58fd49eda28490e9bddf91390b1981
[ "MIT" ]
null
null
null
""" LED matrix """ __all__ = ['Matrix'] from .colors import Color, on, off from .fonts import font_6x8 class Matrix(list): def __init__(self, source=None) -> None: if source is None: row_iter = ([off for _ in range(8)] for _ in range(8)) elif isinstance(source, list): row...
26.347826
89
0.487624
159
1,212
3.559748
0.36478
0.04947
0.056537
0.038869
0
0
0
0
0
0
0
0.02578
0.391914
1,212
45
90
26.933333
0.742198
0.008251
0
0
0
0
0.045226
0
0
0
0
0
0
1
0.09375
false
0
0.0625
0
0.21875
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe68679524344d1cb6b9cfd2e5daf3c7c5e16099
1,704
py
Python
comprehend.py
korniichuk/cvr-features
ed3569222781258d4de242db3c9b51f19573bacb
[ "Unlicense" ]
null
null
null
comprehend.py
korniichuk/cvr-features
ed3569222781258d4de242db3c9b51f19573bacb
[ "Unlicense" ]
null
null
null
comprehend.py
korniichuk/cvr-features
ed3569222781258d4de242db3c9b51f19573bacb
[ "Unlicense" ]
null
null
null
# -*- coding: utf-8 -*- # Name: comprehend # Version: 0.1a2 # Owner: Ruslan Korniichuk # Maintainer(s): import boto3 def get_sentiment(text, language_code='en'): """Get sentiment. Inspects text and returns an inference of the prevailing sentiment (positive, neutral, mixed, or negative). Args: ...
32.150943
78
0.6473
242
1,704
4.528926
0.450413
0.027372
0.029197
0.05292
0.432482
0.432482
0.361314
0.361314
0.361314
0.361314
0
0.014354
0.264085
1,704
52
79
32.769231
0.859649
0.687793
0
0
0
0
0.059957
0
0
0
0
0
0
1
0.142857
false
0
0.071429
0
0.357143
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe6923b1aa562920cf3b40c7be4c7dd797b7d3f4
1,039
py
Python
pbx_gs_python_utils/lambdas/utils/puml_to_slack.py
owasp-sbot/pbx-gs-python-utils
f448aa36c4448fc04d30c3a5b25640ea4d44a267
[ "Apache-2.0" ]
3
2018-12-14T15:43:46.000Z
2019-04-25T07:44:58.000Z
pbx_gs_python_utils/lambdas/utils/puml_to_slack.py
owasp-sbot/pbx-gs-python-utils
f448aa36c4448fc04d30c3a5b25640ea4d44a267
[ "Apache-2.0" ]
1
2019-05-11T14:19:37.000Z
2019-05-11T14:51:04.000Z
pbx_gs_python_utils/lambdas/utils/puml_to_slack.py
owasp-sbot/pbx-gs-python-utils
f448aa36c4448fc04d30c3a5b25640ea4d44a267
[ "Apache-2.0" ]
4
2018-12-27T04:54:14.000Z
2019-05-11T14:07:47.000Z
import base64 import tempfile import requests from osbot_aws.apis import Secrets from osbot_aws.apis.Lambdas import Lambdas def upload_png_file(channel_id, file): bot_token = Secrets('slack-gs-bot').value() my_file = { 'file': ('/tmp/myfile.png', open(file, 'rb'), 'png') } p...
28.081081
86
0.589028
128
1,039
4.609375
0.460938
0.040678
0.045763
0.054237
0
0
0
0
0
0
0
0.007722
0.252166
1,039
36
87
28.861111
0.751609
0
0
0
0
0
0.167469
0
0
0
0
0
0
1
0.074074
false
0
0.185185
0
0.333333
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe694e90c7ac984d467776f89ad0bcfbd5ee4819
2,131
py
Python
src/system_io/input.py
DeseineClement/bigdata-housing-classifier
aa864056c8b25217821f59d16c1ba5725c21a185
[ "MIT" ]
null
null
null
src/system_io/input.py
DeseineClement/bigdata-housing-classifier
aa864056c8b25217821f59d16c1ba5725c21a185
[ "MIT" ]
null
null
null
src/system_io/input.py
DeseineClement/bigdata-housing-classifier
aa864056c8b25217821f59d16c1ba5725c21a185
[ "MIT" ]
null
null
null
from sys import argv from getopt import getopt from os import R_OK, access from string import Template DEFAULT_DATASET_FILE_PATH = "dataset/data.csv" DEFAULT_DATASET_COLUMNS = ['surface (m2)', 'height (m)', 'latitude', 'housing_type', 'longitude', 'country_code', 'city'] DEFAULT_VISU = ["sca...
41.784314
120
0.633975
264
2,131
4.924242
0.310606
0.076154
0.064615
0.073846
0.132308
0.061538
0.061538
0.061538
0
0
0
0.011229
0.247771
2,131
50
121
42.62
0.79975
0
0
0
0
0
0.177851
0
0
0
0
0
0
1
0.02381
false
0
0.095238
0
0.142857
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe6bf9a13a6fe5e608e3131b9e7d5730fd32e4d4
1,490
py
Python
netmiko/example7.py
Tes3awy/Ntemiko-Examples
b29aa3b0de14916f1ebac5b0f1ed7fe37d8740ba
[ "MIT" ]
3
2021-05-20T05:34:49.000Z
2022-02-14T03:35:10.000Z
netmiko/example7.py
Tes3awy/Ntemiko-Examples
b29aa3b0de14916f1ebac5b0f1ed7fe37d8740ba
[ "MIT" ]
null
null
null
netmiko/example7.py
Tes3awy/Ntemiko-Examples
b29aa3b0de14916f1ebac5b0f1ed7fe37d8740ba
[ "MIT" ]
2
2021-08-19T12:34:47.000Z
2022-03-28T15:48:55.000Z
# Must run example4.py first # Read an Excel sheet and save running config of devices using pandas import pandas as pd from netmiko import ConnectHandler # Read Excel file of .xlsx format data = pd.read_excel(io="Example4-Device-Details.xlsx", sheet_name=0) # Convert data to data frame df = pd.DataFrame(data=data) ...
31.702128
85
0.658389
212
1,490
4.533019
0.495283
0.031217
0.067638
0.05411
0.187305
0.187305
0.187305
0
0
0
0
0.014311
0.249664
1,490
46
86
32.391304
0.845259
0.357718
0
0
0
0
0.177282
0.057325
0
0
0
0
0
1
0
false
0.038462
0.076923
0
0.076923
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
fe6cc530fb4e5b20aac699a77d75b91318a5ca68
2,385
py
Python
inference-engine/tests/ie_test_utils/functional_test_utils/layer_tests_summary/utils/constants.py
plaidml/openvino
e784ab8ab7821cc1503d9c5ca6034eea112bf52b
[ "Apache-2.0" ]
null
null
null
inference-engine/tests/ie_test_utils/functional_test_utils/layer_tests_summary/utils/constants.py
plaidml/openvino
e784ab8ab7821cc1503d9c5ca6034eea112bf52b
[ "Apache-2.0" ]
105
2020-06-04T00:23:29.000Z
2022-02-21T13:04:33.000Z
inference-engine/tests/ie_test_utils/functional_test_utils/layer_tests_summary/utils/constants.py
mpapaj/openvino
37b46de1643a2ba6c3b6a076f81d0a47115ede7e
[ "Apache-2.0" ]
1
2020-10-23T06:45:11.000Z
2020-10-23T06:45:11.000Z
# Copyright (C) 2021 Intel Corporation # SPDX-License-Identifier: Apache-2.0 VERIFIED_OP_REFERENCES = [ 'Abs-1', 'Acos-1', 'Add-1', 'Asin-1', 'Asinh-3', 'Assign-6', 'AvgPool-1', 'BatchNormInference-5', 'BatchToSpace-2', 'BinaryConvolution-1', 'Broadcast-1', 'Broadcast-3'...
20.211864
58
0.568134
238
2,385
5.684874
0.52521
0.014782
0.019217
0
0
0
0
0
0
0
0
0.066814
0.240671
2,385
117
59
20.384615
0.680287
0.030189
0
0.017544
0
0
0.6
0.131602
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
fe6ce225addf6075e565169dfeb40c47ef8bca4d
18,542
py
Python
ghub/githubutils.py
mahanthathreyee/ghub
b212ca068ef530d034095e6ef5d964e4e78dc022
[ "MIT" ]
null
null
null
ghub/githubutils.py
mahanthathreyee/ghub
b212ca068ef530d034095e6ef5d964e4e78dc022
[ "MIT" ]
null
null
null
ghub/githubutils.py
mahanthathreyee/ghub
b212ca068ef530d034095e6ef5d964e4e78dc022
[ "MIT" ]
null
null
null
"""Utilities for interacting with GitHub""" import os import json import webbrowser import stat import sys from git import Repo from .context import Context event_dict = { "added_to_project": ( lambda event: "{} added the issue to a project.".format(event["actor"]["login"]) ), "assigned": ( ...
36.936255
99
0.584349
2,146
18,542
4.912861
0.122088
0.093901
0.064877
0.047804
0.63701
0.589111
0.524044
0.485535
0.465617
0.44143
0
0.008335
0.288211
18,542
501
100
37.00998
0.790499
0.010355
0
0.504405
0
0
0.178146
0.004912
0
0
0
0
0
1
0.04185
false
0.002203
0.015419
0
0.129956
0.085903
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe7228704cb0dda0e1c0b7305078fa094d1a0478
2,843
py
Python
influxdb/tests/server_tests/base.py
ocworld/influxdb-python
a6bfe3e4643fdc775c97e1c4f457bc35d86e631e
[ "MIT" ]
2
2019-10-17T05:36:51.000Z
2020-06-30T00:27:22.000Z
influxdb/tests/server_tests/base.py
ocworld/influxdb-python
a6bfe3e4643fdc775c97e1c4f457bc35d86e631e
[ "MIT" ]
null
null
null
influxdb/tests/server_tests/base.py
ocworld/influxdb-python
a6bfe3e4643fdc775c97e1c4f457bc35d86e631e
[ "MIT" ]
null
null
null
# -*- coding: utf-8 -*- """Define the base module for server test.""" from __future__ import absolute_import from __future__ import division from __future__ import print_function from __future__ import unicode_literals import sys from influxdb.tests import using_pypy from influxdb.tests.server_tests.influxdb_instanc...
30.902174
74
0.655645
303
2,843
5.940594
0.343234
0.054444
0.04
0.033333
0.263889
0.166667
0.166667
0.098889
0.098889
0
0
0.000479
0.266268
2,843
91
75
31.241758
0.862416
0.322898
0
0.382979
0
0
0.029252
0
0
0
0
0
0
1
0.170213
false
0
0.191489
0
0.404255
0.021277
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe739da7293d52a3a7c4940166ba21b32df8a642
9,107
py
Python
genemail/testing.py
cadithealth/genemail
d906ad9deec70a6b19b66c244044d4466df2371a
[ "MIT" ]
5
2015-08-13T05:22:54.000Z
2018-08-28T14:14:55.000Z
genemail/testing.py
cadithealth/genemail
d906ad9deec70a6b19b66c244044d4466df2371a
[ "MIT" ]
null
null
null
genemail/testing.py
cadithealth/genemail
d906ad9deec70a6b19b66c244044d4466df2371a
[ "MIT" ]
null
null
null
# -*- coding: utf-8 -*- #------------------------------------------------------------------------------ # file: $Id$ # auth: Philip J Grabner <grabner@cadit.com> # date: 2013/10/21 # copy: (C) Copyright 2013 Cadit Health Inc., All Rights Reserved. #-----------------------------------------------------------------------...
41.584475
88
0.533326
899
9,107
5.302558
0.220245
0.043633
0.041536
0.029369
0.310678
0.28005
0.259702
0.200336
0.155444
0.127124
0
0.017458
0.16976
9,107
218
89
41.775229
0.613014
0.284616
0
0.216783
0
0
0.072536
0.003875
0
0
0
0.004587
0.321678
1
0.13986
false
0.027972
0.020979
0.013986
0.251748
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe75c11d0a13c6adf86f05d6ce0d9f94ca54fb9c
5,410
py
Python
src/training_utils/training.py
JoseLuisRojasAranda/tfmodels
56dce0236f0cc03dd7031aecf305d470c9fb97a9
[ "MIT" ]
1
2020-06-05T23:25:03.000Z
2020-06-05T23:25:03.000Z
src/training_utils/training.py
JoseLuisRojasAranda/tfmodels
56dce0236f0cc03dd7031aecf305d470c9fb97a9
[ "MIT" ]
null
null
null
src/training_utils/training.py
JoseLuisRojasAranda/tfmodels
56dce0236f0cc03dd7031aecf305d470c9fb97a9
[ "MIT" ]
null
null
null
import os from os import path import json import shutil import tensorflow as tf import numpy as np # Importa cosas de Keras API from tensorflow.keras.optimizers import Adam, RMSprop from tensorflow.keras.models import Sequential from tensorflow.keras.utils import plot_model # Importa callbacks del modelo from traini...
35.359477
84
0.697227
717
5,410
5.153417
0.267782
0.029229
0.017862
0.020568
0.200271
0.18295
0.15751
0.117997
0.106631
0.064411
0
0.002079
0.199815
5,410
152
85
35.592105
0.851467
0.302773
0
0.074074
0
0
0.154775
0.011803
0
0
0
0.006579
0
1
0.049383
false
0
0.160494
0
0.234568
0.061728
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe774ebe12faa6fdf372c8d9db66e886229109cb
3,563
py
Python
setup.py
truggles/pudl
6f41664f8243b8f7aafdbbfc8522f96043dbf561
[ "MIT" ]
null
null
null
setup.py
truggles/pudl
6f41664f8243b8f7aafdbbfc8522f96043dbf561
[ "MIT" ]
null
null
null
setup.py
truggles/pudl
6f41664f8243b8f7aafdbbfc8522f96043dbf561
[ "MIT" ]
null
null
null
#!/usr/bin/env python """Setup script to make PUDL directly installable with pip.""" import os from pathlib import Path from setuptools import find_packages, setup install_requires = [ 'coloredlogs', 'datapackage>=1.9.0', 'dbfread', 'goodtables', 'matplotlib', 'networkx>=2.2', 'numpy', ...
30.452991
79
0.641033
419
3,563
5.310263
0.563246
0.026966
0.017079
0.026966
0.033258
0.033258
0
0
0
0
0
0.016181
0.219478
3,563
116
80
30.715517
0.783891
0.156329
0
0.020408
0
0
0.488473
0.078851
0
0
0
0.008621
0
1
0
false
0
0.030612
0
0.030612
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe77c98170bf9d8232497412401b6f749ddb70f7
7,836
py
Python
src/vulnix/nvd.py
dermetfan/vulnix
06daccda0e51098fbdbc65f61b6663c5c6df9358
[ "BSD-3-Clause" ]
217
2016-07-03T10:45:56.000Z
2022-03-30T12:06:51.000Z
src/vulnix/nvd.py
dermetfan/vulnix
06daccda0e51098fbdbc65f61b6663c5c6df9358
[ "BSD-3-Clause" ]
70
2016-06-27T08:47:22.000Z
2022-01-22T19:10:53.000Z
src/vulnix/nvd.py
dermetfan/vulnix
06daccda0e51098fbdbc65f61b6663c5c6df9358
[ "BSD-3-Clause" ]
24
2016-06-27T09:23:50.000Z
2022-01-30T05:32:22.000Z
from BTrees import OOBTree from datetime import datetime, date, timedelta from persistent import Persistent from .vulnerability import Vulnerability import fcntl import glob import gzip import json import logging import os import os.path as p import requests import transaction import ZODB import ZODB.FileStorage DEFAU...
32.786611
79
0.590225
963
7,836
4.660436
0.268951
0.032086
0.018717
0.018939
0.143939
0.113859
0.085784
0.049465
0.049465
0.049465
0
0.004897
0.296325
7,836
238
80
32.92437
0.809032
0.144206
0
0.16185
0
0
0.083627
0.003216
0
0
0
0
0
1
0.115607
false
0
0.086705
0.011561
0.32948
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe7996f8bc015e9c1e0a7458bde9909f14df8fbf
316
py
Python
ScapyDoS-main/simp.py
Zusyaku/Termux-And-Lali-Linux-V2
b1a1b0841d22d4bf2cc7932b72716d55f070871e
[ "Apache-2.0" ]
2
2021-11-17T03:35:03.000Z
2021-12-08T06:00:31.000Z
ScapyDoS-main/simp.py
Zusyaku/Termux-And-Lali-Linux-V2
b1a1b0841d22d4bf2cc7932b72716d55f070871e
[ "Apache-2.0" ]
null
null
null
ScapyDoS-main/simp.py
Zusyaku/Termux-And-Lali-Linux-V2
b1a1b0841d22d4bf2cc7932b72716d55f070871e
[ "Apache-2.0" ]
2
2021-11-05T18:07:48.000Z
2022-02-24T21:25:07.000Z
from scapy.all import * src = input("Source IP: ") target = input("Target IP: ") i=1 while True: for srcport in range(1, 65535): ip = IP(src=src, dst=target) tcp = TCP(sport=srcport, dport=80) pkt = ip / tcp send(pkt, inter= .0001) print("Packet Sent ", i) i=i+1
22.571429
42
0.550633
48
316
3.625
0.625
0.022989
0
0
0
0
0
0
0
0
0
0.063636
0.303797
316
14
43
22.571429
0.727273
0
0
0
0
0
0.107256
0
0
0
0
0
0
1
0
false
0
0.083333
0
0.083333
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
fe7a4e994d80d1a5a6af69534d2790e8dc14f03c
4,354
py
Python
data_importer_ftp.py
supsi-dacd-isaac/oasi-ozone-forecaster
01d23c374e857dcc6d556d073c0380186c2934d2
[ "MIT" ]
null
null
null
data_importer_ftp.py
supsi-dacd-isaac/oasi-ozone-forecaster
01d23c374e857dcc6d556d073c0380186c2934d2
[ "MIT" ]
null
null
null
data_importer_ftp.py
supsi-dacd-isaac/oasi-ozone-forecaster
01d23c374e857dcc6d556d073c0380186c2934d2
[ "MIT" ]
null
null
null
# --------------------------------------------------------------------------- # # Importing section # --------------------------------------------------------------------------- # import os import sys import argparse import logging import json from classes.alerts import SlackClient from influxdb import InfluxDBClient...
41.075472
119
0.475195
406
4,354
4.955665
0.344828
0.049205
0.014911
0.02833
0.115308
0.102386
0.081511
0.049702
0.049702
0
0
0.003368
0.181672
4,354
105
120
41.466667
0.561325
0.307304
0
0.064516
0
0
0.262097
0.018817
0
0
0
0
0
1
0.016129
false
0.016129
0.16129
0
0.177419
0.016129
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe7b77f497a02a03531071b294b121357332567e
2,791
py
Python
autoindent_code_JASS_war3map_j.py
gil9red/SimplePyScripts
c191ce08fbdeb29377639184579e392057945154
[ "CC-BY-4.0" ]
117
2015-12-18T07:18:27.000Z
2022-03-28T00:25:54.000Z
autoindent_code_JASS_war3map_j.py
gil9red/SimplePyScripts
c191ce08fbdeb29377639184579e392057945154
[ "CC-BY-4.0" ]
8
2018-10-03T09:38:46.000Z
2021-12-13T19:51:09.000Z
autoindent_code_JASS_war3map_j.py
gil9red/SimplePyScripts
c191ce08fbdeb29377639184579e392057945154
[ "CC-BY-4.0" ]
28
2016-08-02T17:43:47.000Z
2022-03-21T08:31:12.000Z
#!/usr/bin/env python3 # -*- coding: utf-8 -*- __author__ = 'ipetrash' import re DEBUG = False def merge_str_literal(text: str) -> str: def _on_match(m: re.Match): return m.group().replace('"+"', '') return re.sub(r'".+?"(\+".+?")+ ', _on_match, text) lines = """ function II1I1_II takes real I...
23.258333
80
0.638839
360
2,791
4.741667
0.25
0.098418
0.094903
0.049209
0.507323
0.437024
0.437024
0.437024
0.437024
0.437024
0
0.041551
0.223934
2,791
119
81
23.453782
0.746537
0.032605
0
0.144928
0
0
0.342194
0.123731
0
0
0
0
0
1
0.028986
false
0
0.014493
0.014493
0.072464
0.028986
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe7bebb9c7d420d8879b0fc07f857afa803296a1
5,656
py
Python
python/addNewData.py
TruX-DTF/fixminer_source
5ab2d6f582743c377eadb21cd466a3a25809bc2d
[ "MIT" ]
5
2021-07-19T12:30:00.000Z
2022-01-14T16:41:00.000Z
python/addNewData.py
SerVal-DTF/fixminer_source
5ab2d6f582743c377eadb21cd466a3a25809bc2d
[ "MIT" ]
10
2020-04-06T09:52:19.000Z
2021-06-01T08:05:25.000Z
python/addNewData.py
SerVal-DTF/fixminer_source
5ab2d6f582743c377eadb21cd466a3a25809bc2d
[ "MIT" ]
5
2019-08-26T11:02:35.000Z
2021-03-23T15:42:09.000Z
from common.commons import * DATA_PATH = os.environ["DATA_PATH"] def core(): clusterPath = join(DATA_PATH, 'shapes') roots = listdir(clusterPath) roots = [i for i in roots if not (i.startswith('.') or i.endswith('.pickle'))] pattern = {} for root in roots: root sizes = listdir(join(...
39.552448
299
0.592999
635
5,656
5.248819
0.2
0.040804
0.091209
0.10141
0.415242
0.380138
0.341134
0.341134
0.341134
0.341134
0
0.003672
0.277758
5,656
142
300
39.830986
0.81224
0.130304
0
0.357143
0
0
0.036145
0
0
0
0
0
0
1
0.035714
false
0
0.071429
0
0.107143
0.026786
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe8041c5c55101ae0dcfff5c78088fd9a509554f
6,805
py
Python
services/ops/LogStatisticsAgent/logstatisticsagent/agent.py
gnmerritt/volttron
ebfbf62bab77d46fd3e8d6aaca1fc4f33932ccf3
[ "Apache-2.0" ]
1
2020-05-26T01:29:50.000Z
2020-05-26T01:29:50.000Z
services/ops/LogStatisticsAgent/logstatisticsagent/agent.py
gnmerritt/volttron
ebfbf62bab77d46fd3e8d6aaca1fc4f33932ccf3
[ "Apache-2.0" ]
null
null
null
services/ops/LogStatisticsAgent/logstatisticsagent/agent.py
gnmerritt/volttron
ebfbf62bab77d46fd3e8d6aaca1fc4f33932ccf3
[ "Apache-2.0" ]
null
null
null
# -*- coding: utf-8 -*- {{{ # vim: set fenc=utf-8 ft=python sw=4 ts=4 sts=4 et: # # Copyright 2019, Battelle Memorial Institute. # # 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...
38.885714
103
0.680235
842
6,805
5.308789
0.349169
0.026846
0.020134
0.021477
0.146085
0.108725
0.057718
0.038926
0.019687
0
0
0.006887
0.231888
6,805
174
104
39.109195
0.848288
0.416605
0
0.052632
0
0
0.108058
0.012682
0
0
0
0
0
1
0.078947
false
0.013158
0.105263
0
0.223684
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe8661c1fd9d01528fabb6e5da9f0d2b06361f3b
2,857
py
Python
fmpy/cswrapper/__init__.py
CSchulzeTLK/FMPy
fde192346c36eb69dbaca60a96e80cdc8ef37b89
[ "CC-BY-3.0", "CC-BY-4.0" ]
225
2017-05-17T22:33:38.000Z
2022-03-29T12:41:52.000Z
fmpy/cswrapper/__init__.py
CSchulzeTLK/FMPy
fde192346c36eb69dbaca60a96e80cdc8ef37b89
[ "CC-BY-3.0", "CC-BY-4.0" ]
381
2017-05-20T13:31:52.000Z
2022-03-31T08:20:47.000Z
fmpy/cswrapper/__init__.py
CSchulzeTLK/FMPy
fde192346c36eb69dbaca60a96e80cdc8ef37b89
[ "CC-BY-3.0", "CC-BY-4.0" ]
90
2017-05-20T13:34:34.000Z
2022-03-31T05:14:57.000Z
def add_cswrapper(filename, outfilename=None): from fmpy import read_model_description, extract, sharedLibraryExtension, platform, __version__ from lxml import etree import os from shutil import copyfile, rmtree if outfilename is None: outfilename = filename model_description = read...
34.841463
125
0.672384
336
2,857
5.556548
0.357143
0.054633
0.042849
0.038565
0.162828
0.151044
0.109266
0.080343
0.080343
0
0
0.002699
0.221911
2,857
81
126
35.271605
0.837157
0.021351
0
0.115385
0
0
0.109996
0
0
0
0
0
0
1
0.038462
false
0
0.115385
0
0.153846
0.019231
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe87946e35b940790f2abaab6a2a55e9294ad44f
7,305
py
Python
echoscope/source/mysql_source.py
treeyh/echoscope
ef8933ce9a5dfe2ac8fb6e82bad8d5fa0d72a6da
[ "MIT" ]
1
2022-01-18T09:19:38.000Z
2022-01-18T09:19:38.000Z
echoscope/source/mysql_source.py
treeyh/echoscope
ef8933ce9a5dfe2ac8fb6e82bad8d5fa0d72a6da
[ "MIT" ]
null
null
null
echoscope/source/mysql_source.py
treeyh/echoscope
ef8933ce9a5dfe2ac8fb6e82bad8d5fa0d72a6da
[ "MIT" ]
1
2022-01-18T09:19:39.000Z
2022-01-18T09:19:39.000Z
# -*- coding: UTF-8 -*- import logging from typing import List from echoscope.config import config from echoscope.util import mysql_util, str_util, log_util from echoscope.model import ds_model, config_model from echoscope.source import source class MysqlSource(source.Source): def __init__(self): self.exclude...
39.701087
411
0.675975
951
7,305
4.921136
0.178759
0.032906
0.061111
0.075214
0.379915
0.350214
0.296154
0.247009
0.13141
0.103419
0
0.001034
0.205613
7,305
183
412
39.918033
0.805445
0.113895
0
0.046296
0
0.018519
0.240057
0.036286
0
0
0
0
0
1
0.064815
false
0.009259
0.055556
0
0.194444
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe8a7abf97fc4938deedb4a0e775164e6040fb1b
1,042
py
Python
test-drf-project/tests/conftest.py
fvlima/drf-view-profiler
a61d48e9835679f812d69d24ea740b947836108c
[ "MIT" ]
30
2019-10-16T12:48:16.000Z
2021-11-23T08:57:27.000Z
test-drf-project/tests/conftest.py
fvlima/drf-view-profiler
a61d48e9835679f812d69d24ea740b947836108c
[ "MIT" ]
null
null
null
test-drf-project/tests/conftest.py
fvlima/drf-view-profiler
a61d48e9835679f812d69d24ea740b947836108c
[ "MIT" ]
1
2021-11-23T07:28:04.000Z
2021-11-23T07:28:04.000Z
from unittest import mock import pytest from django.http import HttpRequest from rest_framework.response import Response from rest_framework.test import APIClient from drf_viewset_profiler.middleware import LineProfilerViewSetMiddleware @pytest.fixture def api_client(): return APIClient() @pytest.fixture def ...
24.809524
100
0.794626
126
1,042
6.246032
0.285714
0.111817
0.101652
0.101652
0.060991
0
0
0
0
0
0
0
0.130518
1,042
41
101
25.414634
0.868653
0
0
0.172414
0
0
0.06334
0.049904
0
0
0
0
0
1
0.172414
false
0
0.206897
0.068966
0.551724
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe8b3957ceddf0ec804e544f4e167363b9d84f54
3,553
py
Python
Examples/VirtualLab/virtual_experiment_f.py
diehlpk/muDIC
b5d90aa62267b4bd0b88ae0a989cf09a51990654
[ "MIT" ]
70
2019-04-15T08:08:23.000Z
2022-03-23T08:24:25.000Z
Examples/VirtualLab/virtual_experiment_f.py
diehlpk/muDIC
b5d90aa62267b4bd0b88ae0a989cf09a51990654
[ "MIT" ]
34
2019-05-03T18:09:43.000Z
2022-02-10T11:36:29.000Z
Examples/VirtualLab/virtual_experiment_f.py
diehlpk/muDIC
b5d90aa62267b4bd0b88ae0a989cf09a51990654
[ "MIT" ]
37
2019-04-25T15:39:23.000Z
2022-03-28T21:40:24.000Z
# This allows for running the example when the repo has been cloned import sys from os.path import abspath sys.path.extend([abspath(".")]) # Example code follows import logging import numpy as np import matplotlib.pyplot as plt import muDIC.vlab as vlab import muDIC as dic """ This example case runs an experiment whe...
36.628866
112
0.731776
554
3,553
4.595668
0.406137
0.009427
0.005892
0.010605
0.070699
0.016496
0.016496
0.010212
0
0
0
0.036651
0.162961
3,553
96
113
37.010417
0.819435
0.249648
0
0
0
0
0.121317
0.014731
0
0
0
0
0
1
0
false
0
0.137255
0
0.137255
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe8d5aa19fb8f623818fa75491db0f6d028311d8
3,203
py
Python
Optimisation Portfolios/HERC.py
BrandonAFong/Ideas
5d38be2dfaba12a534220e3f28a6c9da9aefcdec
[ "MIT" ]
null
null
null
Optimisation Portfolios/HERC.py
BrandonAFong/Ideas
5d38be2dfaba12a534220e3f28a6c9da9aefcdec
[ "MIT" ]
null
null
null
Optimisation Portfolios/HERC.py
BrandonAFong/Ideas
5d38be2dfaba12a534220e3f28a6c9da9aefcdec
[ "MIT" ]
null
null
null
#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Tue Aug 31 22:48:21 2021 @author: apple """ import numpy as np import pandas as pd from HRP import seriation import fastcluster from scipy.cluster.hierarchy import fcluster from gap_statistic import OptimalK from backtest import df_to_matrix #HERC def...
28.345133
84
0.609429
435
3,203
4.34023
0.328736
0.014831
0.023305
0.027542
0.10911
0.055085
0
0
0
0
0
0.015866
0.271933
3,203
113
85
28.345133
0.793739
0.086794
0
0.058824
0
0
0.007898
0
0
0
0
0
0
1
0.044118
false
0
0.102941
0
0.191176
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe908006796adb02dbc2aa1b3ab9fa0ac75b1812
5,574
py
Python
sawyer/mujoco/tasks/transition_pick_and_place_task.py
rlagywjd802/gym-sawyer
385bbeafcccb61afb9099554f6a99b16f1f1a7c5
[ "MIT" ]
null
null
null
sawyer/mujoco/tasks/transition_pick_and_place_task.py
rlagywjd802/gym-sawyer
385bbeafcccb61afb9099554f6a99b16f1f1a7c5
[ "MIT" ]
null
null
null
sawyer/mujoco/tasks/transition_pick_and_place_task.py
rlagywjd802/gym-sawyer
385bbeafcccb61afb9099554f6a99b16f1f1a7c5
[ "MIT" ]
null
null
null
import numpy as np from sawyer.mujoco.tasks.base import ComposableTask class TransitionTask(ComposableTask): """ Task to pick up an object with the robot gripper. Success condition: - Object is grasped and has been lifted above the table """ def __init__(self): pass def compute_...
28.880829
121
0.571582
760
5,574
3.911842
0.142105
0.084763
0.0518
0.065927
0.685167
0.612176
0.54995
0.523713
0.523713
0.506895
0
0.028877
0.329028
5,574
192
122
29.03125
0.766043
0.079117
0
0.669118
0
0
0.054884
0.004755
0
0
0
0
0
1
0.147059
false
0.014706
0.014706
0.022059
0.308824
0.080882
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe90ddd8fb4cfe4289850e4b9709b973ed6310cd
36,485
py
Python
tests/app/test_jinja_filters.py
nealedj/eq-survey-runner
b8e6cddae6068f6c8fd60e21d31d58aaa79bbb34
[ "MIT" ]
null
null
null
tests/app/test_jinja_filters.py
nealedj/eq-survey-runner
b8e6cddae6068f6c8fd60e21d31d58aaa79bbb34
[ "MIT" ]
1
2018-11-05T12:00:51.000Z
2018-11-05T12:00:51.000Z
tests/app/test_jinja_filters.py
nealedj/eq-survey-runner
b8e6cddae6068f6c8fd60e21d31d58aaa79bbb34
[ "MIT" ]
null
null
null
# coding: utf-8 from types import SimpleNamespace from datetime import datetime, timedelta from unittest.mock import patch from dateutil.relativedelta import relativedelta from jinja2 import Undefined, Markup from mock import Mock from app.jinja_filters import ( format_date, format_conditional_date, format_curre...
38.005208
143
0.615952
4,321
36,485
4.926637
0.093265
0.11274
0.123309
0.052847
0.757187
0.680994
0.60668
0.528091
0.441798
0.405909
0
0.046522
0.25531
36,485
959
144
38.044838
0.736732
0.04495
0
0.324324
0
0.001689
0.176201
0.030794
0
0
0
0
0.302365
1
0.14527
false
0.006757
0.013514
0
0.160473
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe90eb5d4db9dcb42eabad6cf0007baab0fc7833
18,598
py
Python
levels/sombie.py
superhasduper/PythonGames
64995d3e0b619006a2cf80d0da3c0fdf97db6fd9
[ "MIT" ]
1
2019-07-07T19:55:39.000Z
2019-07-07T19:55:39.000Z
levels/sombie.py
superhasduper/PythonGames
64995d3e0b619006a2cf80d0da3c0fdf97db6fd9
[ "MIT" ]
null
null
null
levels/sombie.py
superhasduper/PythonGames
64995d3e0b619006a2cf80d0da3c0fdf97db6fd9
[ "MIT" ]
null
null
null
import arcade import os SPRITE_SCALING = 0.5 SPRITE_NATIVE_SIZE = 128 SPRITE_SIZE = int(SPRITE_NATIVE_SIZE * SPRITE_SCALING) SCREEN_WIDTH = SPRITE_SIZE * 14 SCREEN_HEIGHT = SPRITE_SIZE * 10 MOVEMENT_SPEED = 5 COIN_SCALE = 0.7 class Room: """ This class holds all the information about the ...
36.324219
124
0.614367
2,439
18,598
4.481755
0.113161
0.090568
0.051596
0.075016
0.710457
0.682737
0.658311
0.613942
0.605709
0.586955
0
0.016981
0.29073
18,598
512
125
36.324219
0.81169
0.105495
0
0.604046
0
0
0.049861
0
0
0
0
0
0
1
0.028902
false
0
0.00578
0
0.046243
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe916e74f3d8c5dd73c18e07f1aa14f15ee3d8d0
4,869
py
Python
venv/lib/python3.6/site-packages/gevent/testing/openfiles.py
Guillaume-Fernandez/phishfinder
b459a30202fd5dfb1340b43c70363705de7cedd9
[ "MIT" ]
10
2021-03-23T03:46:19.000Z
2022-03-08T07:20:25.000Z
venv/lib/python3.6/site-packages/gevent/testing/openfiles.py
Guillaume-Fernandez/phishfinder
b459a30202fd5dfb1340b43c70363705de7cedd9
[ "MIT" ]
7
2021-05-21T16:51:48.000Z
2022-03-12T00:50:26.000Z
venv/lib/python3.6/site-packages/gevent/testing/openfiles.py
Guillaume-Fernandez/phishfinder
b459a30202fd5dfb1340b43c70363705de7cedd9
[ "MIT" ]
4
2021-04-21T00:49:34.000Z
2021-11-21T09:18:29.000Z
# Copyright (c) 2018 gevent community # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, di...
38.642857
139
0.657835
683
4,869
4.606149
0.401171
0.03719
0.030515
0.022886
0.035601
0.019708
0.019708
0
0
0
0
0.007448
0.255494
4,869
125
140
38.952
0.860414
0.439721
0
0.211268
0
0.014085
0.09191
0.01823
0
0
0
0
0.042254
1
0.084507
false
0
0.112676
0
0.309859
0.014085
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe97b6953c22bb335b56638721adf4a720e34f5f
2,922
py
Python
FAUCovidCrawler/AWSLambda/lambda_function.py
Awannaphasch2016/CDKFAUCovid19Cralwer
a84d90612314cb4d4618da95238617a524b1b280
[ "MIT" ]
null
null
null
FAUCovidCrawler/AWSLambda/lambda_function.py
Awannaphasch2016/CDKFAUCovid19Cralwer
a84d90612314cb4d4618da95238617a524b1b280
[ "MIT" ]
null
null
null
FAUCovidCrawler/AWSLambda/lambda_function.py
Awannaphasch2016/CDKFAUCovid19Cralwer
a84d90612314cb4d4618da95238617a524b1b280
[ "MIT" ]
null
null
null
''' Original code contributor: mentzera Article link: https://aws.amazon.com/blogs/big-data/building-a-near-real-time-discovery-platform-with-aws/ ''' import boto3 import json import twitter_to_es # from Examples.Demo.AWS_Related.TwitterStreamWithAWS.LambdaWithS3Trigger import \ # twitter_to_es from tweet_utils i...
33.204545
142
0.589322
352
2,922
4.798295
0.454545
0.017762
0.038484
0.02013
0.089994
0.040261
0.040261
0.040261
0
0
0
0.014728
0.302875
2,922
87
143
33.586207
0.814433
0.380561
0
0.195122
0
0.02439
0.166854
0.020787
0
0
0
0
0
1
0.02439
false
0
0.097561
0
0.121951
0.170732
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe9913a9a0d00104117bbc4e7f42cf9196b11854
8,791
py
Python
finetune/finetune.py
zaixizhang/MGSSL
fdb7e78bb927d735ed64dc78fb792adb13352e1c
[ "Apache-2.0" ]
43
2021-10-15T01:11:36.000Z
2022-03-31T02:05:41.000Z
finetune/finetune.py
zaixizhang/MGSSL
fdb7e78bb927d735ed64dc78fb792adb13352e1c
[ "Apache-2.0" ]
5
2021-12-09T08:07:22.000Z
2022-03-02T07:34:34.000Z
finetune/finetune.py
zaixizhang/MGSSL
fdb7e78bb927d735ed64dc78fb792adb13352e1c
[ "Apache-2.0" ]
7
2021-11-23T01:15:36.000Z
2022-03-07T16:30:30.000Z
import argparse from loader import MoleculeDataset from torch_geometric.data import DataLoader import torch import torch.nn as nn import torch.nn.functional as F import torch.optim as optim from tqdm import tqdm import numpy as np from model import GNN, GNN_graphpred from sklearn.metrics import roc_auc_score from ...
42.674757
176
0.657604
1,214
8,791
4.594728
0.21911
0.03227
0.060954
0.013625
0.280925
0.219433
0.189315
0.148082
0.148082
0.148082
0
0.015582
0.21158
8,791
205
177
42.882927
0.789208
0.033216
0
0.090909
0
0
0.179783
0.01131
0
0
0
0
0
1
0.019481
false
0.006494
0.103896
0
0.12987
0.077922
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe99a748e2fcbf259f6611afd0ca5930032c99b6
5,703
py
Python
neurokit2/signal/signal_plot.py
gutierrezps/NeuroKit
a30f76e64b4108abdc652a20391dc0288c62501d
[ "MIT" ]
1
2022-03-20T21:09:34.000Z
2022-03-20T21:09:34.000Z
neurokit2/signal/signal_plot.py
Lei-I-Zhang/NeuroKit
a30f76e64b4108abdc652a20391dc0288c62501d
[ "MIT" ]
null
null
null
neurokit2/signal/signal_plot.py
Lei-I-Zhang/NeuroKit
a30f76e64b4108abdc652a20391dc0288c62501d
[ "MIT" ]
null
null
null
# -*- coding: utf-8 -*- import matplotlib.pyplot as plt import numpy as np import pandas as pd from ..events import events_plot from ..stats import standardize as nk_standardize def signal_plot( signal, sampling_rate=None, subplots=False, standardize=False, labels=None, **kwargs ): """Plot signal with events...
33.946429
109
0.57198
681
5,703
4.707783
0.270191
0.063631
0.03587
0.014972
0.122271
0.092327
0.092327
0.064255
0.026825
0.026825
0
0.022606
0.309662
5,703
167
110
34.149701
0.79172
0.307733
0
0.123711
0
0
0.054445
0
0
0
0
0
0
1
0.010309
false
0
0.051546
0
0.061856
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe9d9591df2f2c4858eb64ae4def8e712c9e40a0
1,183
py
Python
migrations/versions/1a89721126f7_only_one_validation_per_mission_user_.py
MTES-MCT/mobilic-api
b3754de2282262fd60a27dc90e40777df9c1e230
[ "MIT" ]
null
null
null
migrations/versions/1a89721126f7_only_one_validation_per_mission_user_.py
MTES-MCT/mobilic-api
b3754de2282262fd60a27dc90e40777df9c1e230
[ "MIT" ]
8
2021-04-19T17:47:55.000Z
2022-02-16T17:40:18.000Z
migrations/versions/1a89721126f7_only_one_validation_per_mission_user_.py
MTES-MCT/mobilic-api
b3754de2282262fd60a27dc90e40777df9c1e230
[ "MIT" ]
null
null
null
"""Only one validation per mission, user and actor Revision ID: 1a89721126f7 Revises: fa96dfc8237d Create Date: 2021-10-14 11:22:01.124488 """ from alembic import op import sqlalchemy as sa # revision identifiers, used by Alembic. revision = "1a89721126f7" down_revision = "fa96dfc8237d" branch_labels = None depends...
23.66
117
0.633136
138
1,183
5.195652
0.492754
0.09484
0.07113
0.083682
0.147838
0.147838
0.147838
0.147838
0.147838
0
0
0.063855
0.298394
1,183
49
118
24.142857
0.8
0.148774
0
0.125
0
0
0.250681
0.13624
0
0
0
0
0
1
0.125
false
0
0.125
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
fe9dfa2f69a678e6192380ed28bf692cc55ff822
1,979
py
Python
packages/facilities/rtdb/python/rtdb2_get.py
Falcons-Robocup/code
2281a8569e7f11cbd3238b7cc7341c09e2e16249
[ "Apache-2.0" ]
2
2021-01-15T13:27:19.000Z
2021-08-04T08:40:52.000Z
packages/facilities/rtdb/python/rtdb2_get.py
Falcons-Robocup/code
2281a8569e7f11cbd3238b7cc7341c09e2e16249
[ "Apache-2.0" ]
null
null
null
packages/facilities/rtdb/python/rtdb2_get.py
Falcons-Robocup/code
2281a8569e7f11cbd3238b7cc7341c09e2e16249
[ "Apache-2.0" ]
5
2018-05-01T10:39:31.000Z
2022-03-25T03:02:35.000Z
# Copyright 2020 Jan Feitsma (Falcons) # SPDX-License-Identifier: Apache-2.0 #!/usr/bin/python import os import sys import argparse from rtdb2 import RtDB2Store, RTDB2_DEFAULT_PATH import rtdb2tools from hexdump import hexdump # Main structure of the program if __name__ == "__main__": # Argument parsing. des...
42.106383
186
0.723598
255
1,979
5.513725
0.513725
0.032006
0.060455
0.024182
0.025605
0
0
0
0
0
0
0.161443
0.145528
1,979
46
187
43.021739
0.670018
0.098535
0
0
0
0.0625
0.443131
0.087838
0
0
0
0
0
1
0
false
0
0.1875
0
0.1875
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
fe9ed7b6294e532592cc4dcafea632566b56df4d
2,219
py
Python
algorithms/A3C/atari/atari_env_deprecated.py
what3versin/reinforce_py
46769da50aea65346cd3a300b55306d25f1f2683
[ "MIT" ]
1
2018-11-09T02:56:27.000Z
2018-11-09T02:56:27.000Z
algorithms/A3C/atari/atari_env_deprecated.py
syd951186545/reinforce_py
46769da50aea65346cd3a300b55306d25f1f2683
[ "MIT" ]
null
null
null
algorithms/A3C/atari/atari_env_deprecated.py
syd951186545/reinforce_py
46769da50aea65346cd3a300b55306d25f1f2683
[ "MIT" ]
null
null
null
from __future__ import print_function from __future__ import division import os import gym import numpy as np from skimage.transform import resize from skimage.color import rgb2gray class Atari(object): s_dim = [84, 84, 1] a_dim = 3 def __init__(self, args, record_video=False): self.env = gym.m...
32.632353
80
0.581794
297
2,219
4.175084
0.360269
0.050806
0.033871
0.022581
0.079032
0.051613
0.051613
0.051613
0
0
0
0.019041
0.313655
2,219
67
81
33.119403
0.795141
0.054529
0
0.037037
0
0
0.013397
0.010526
0
0
0
0
0
1
0.074074
false
0
0.12963
0.018519
0.314815
0.018519
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe9f7091809e30b40cd88cb5967081a6b1484eed
5,935
py
Python
content/_build/jupyter_execute/macm.py
NBCLab/nimare-paper
2b9e70febcfde4ca12420adc3c2910ff622252f2
[ "MIT" ]
3
2020-10-20T10:24:04.000Z
2021-12-20T13:31:01.000Z
content/_build/jupyter_execute/macm.py
NBCLab/nimare-paper
2b9e70febcfde4ca12420adc3c2910ff622252f2
[ "MIT" ]
20
2021-03-07T17:18:48.000Z
2022-03-09T15:13:02.000Z
content/_build/jupyter_execute/macm.py
NBCLab/nimare-paper
2b9e70febcfde4ca12420adc3c2910ff622252f2
[ "MIT" ]
3
2020-05-05T14:42:18.000Z
2021-11-30T19:52:27.000Z
#!/usr/bin/env python # coding: utf-8 # # Meta-Analytic Coactivation Modeling # In[1]: # First, import the necessary modules and functions import os from datetime import datetime import matplotlib.pyplot as plt from myst_nb import glue from repo2data.repo2data import Repo2Data import nimare start = datetime.now(...
36.411043
392
0.752148
895
5,935
4.860335
0.351955
0.01931
0.009195
0.009655
0.165517
0.142989
0.108966
0.076782
0.076782
0.01977
0
0.018387
0.147767
5,935
162
393
36.635802
0.841637
0.532435
0
0.178082
0
0
0.082142
0.020535
0
0
0
0.006173
0
1
0
false
0
0.123288
0
0.123288
0.013699
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fe9f96734192b94aa40844f25ed620f799a5da53
50,863
py
Python
cisco-ios-xe/ydk/models/cisco_ios_xe/CISCO_IPSLA_ECHO_MIB.py
Maikor/ydk-py
b86c4a7c570ae3b2c5557d098420446df5de4929
[ "ECL-2.0", "Apache-2.0" ]
null
null
null
cisco-ios-xe/ydk/models/cisco_ios_xe/CISCO_IPSLA_ECHO_MIB.py
Maikor/ydk-py
b86c4a7c570ae3b2c5557d098420446df5de4929
[ "ECL-2.0", "Apache-2.0" ]
null
null
null
cisco-ios-xe/ydk/models/cisco_ios_xe/CISCO_IPSLA_ECHO_MIB.py
Maikor/ydk-py
b86c4a7c570ae3b2c5557d098420446df5de4929
[ "ECL-2.0", "Apache-2.0" ]
null
null
null
""" CISCO_IPSLA_ECHO_MIB This MIB module defines the templates for IP SLA operations of ICMP echo, UDP echo and TCP connect. The ICMP echo operation measures end\-to\-end response time between a Cisco router and any IP enabled device by computing the time taken between sending an ICMP echo request message to the d...
55.527293
720
0.624855
4,459
50,863
7.037901
0.099574
0.014531
0.017399
0.021127
0.579186
0.565961
0.548818
0.540724
0.524313
0.490918
0
0.012314
0.292708
50,863
915
721
55.587978
0.860014
0.463579
0
0.312268
0
0
0.321841
0.284763
0
0
0
0
0
1
0.055762
false
0
0.018587
0
0.122677
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fea2c153f85345b8df258b2faf5084ce932ff128
4,057
py
Python
example/model-parallel/matrix_factorization/train.py
tkameyama/incubator-mxnet
47b0bdd00e7c5e1c9a448809b02e68c0e4b72e96
[ "Apache-2.0" ]
1
2022-01-22T02:29:24.000Z
2022-01-22T02:29:24.000Z
example/model-parallel/matrix_factorization/train.py
tkameyama/incubator-mxnet
47b0bdd00e7c5e1c9a448809b02e68c0e4b72e96
[ "Apache-2.0" ]
null
null
null
example/model-parallel/matrix_factorization/train.py
tkameyama/incubator-mxnet
47b0bdd00e7c5e1c9a448809b02e68c0e4b72e96
[ "Apache-2.0" ]
null
null
null
# Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you under the Apache License, Version 2.0 (the # "License"); you may not u...
36.881818
98
0.682031
529
4,057
5.073724
0.402647
0.023472
0.031669
0.011923
0.07228
0.031297
0.031297
0.031297
0
0
0
0.018354
0.221099
4,057
109
99
37.220183
0.831013
0.278777
0
0
0
0
0.15528
0.007246
0
0
0
0
0
1
0
false
0
0.107692
0
0.107692
0.046154
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fea4ed769af71f922b55fc3fe0ad5f2f54ffbfef
762
py
Python
scripts/libfranka_gui_gripper_run.py
nbfigueroa/franka_interactive_controllers
7befdd5fbaa3c7a83b931292fab39ab98754a60c
[ "MIT" ]
6
2021-12-08T09:32:57.000Z
2022-03-20T09:22:29.000Z
scripts/libfranka_gui_gripper_run.py
nbfigueroa/franka_interactive_controllers
7befdd5fbaa3c7a83b931292fab39ab98754a60c
[ "MIT" ]
null
null
null
scripts/libfranka_gui_gripper_run.py
nbfigueroa/franka_interactive_controllers
7befdd5fbaa3c7a83b931292fab39ab98754a60c
[ "MIT" ]
3
2022-02-01T12:30:47.000Z
2022-03-24T10:31:04.000Z
#!/usr/bin/env python3 import shlex from tkinter import * from tkinter import messagebox from psutil import Popen top = Tk() top.title("Franka Gripper Control") top.geometry("300x75") def open(): node_process = Popen(shlex.split('rosrun franka_interactive_controllers libfranka_gripper_run 1')) messagebox.showinfo...
25.4
99
0.745407
105
762
5.295238
0.457143
0.079137
0.061151
0.07554
0.284173
0.284173
0.284173
0.284173
0.284173
0.284173
0
0.031627
0.128609
762
29
100
26.275862
0.805723
0.027559
0
0.1
0
0
0.308108
0.137838
0
0
0
0
0
1
0.1
false
0
0.2
0
0.3
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fea64ce26f29e53484b8013f735f948fef203460
12,293
py
Python
client/client_build.py
patriotemeritus/grr
bf2b9268c8b9033ab091e27584986690438bd7c3
[ "Apache-2.0" ]
1
2015-06-24T09:07:20.000Z
2015-06-24T09:07:20.000Z
client/client_build.py
patriotemeritus/grr
bf2b9268c8b9033ab091e27584986690438bd7c3
[ "Apache-2.0" ]
3
2020-02-11T22:29:15.000Z
2021-06-10T17:44:31.000Z
client/client_build.py
wandec/grr
7fb7e6d492d1325a5fe1559d3aeae03a301c4baa
[ "Apache-2.0" ]
null
null
null
#!/usr/bin/env python """This tool builds or repacks the client binaries. This handles invocations for the build across the supported platforms including handling Visual Studio, pyinstaller and other packaging mechanisms. """ import logging import os import platform import time # pylint: disable=unused-import from ...
35.631884
80
0.663467
1,396
12,293
5.732092
0.217765
0.023619
0.035616
0.022494
0.366783
0.307048
0.291927
0.267933
0.242939
0.215196
0
0.004875
0.232409
12,293
344
81
35.735465
0.843154
0.130318
0
0.300429
0
0
0.237352
0.021441
0
0
0
0
0
1
0.021459
false
0
0.04721
0
0.085837
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0
fea677c9a939d2a74e86aae5f8b7734e53289cfd
1,549
py
Python
Greyatom-projects/code.py
naveena41/greyatom-python-for-data-science
3aa63878ff12e0e8cdf0e63bafe9b4a2c082f7b1
[ "MIT" ]
null
null
null
Greyatom-projects/code.py
naveena41/greyatom-python-for-data-science
3aa63878ff12e0e8cdf0e63bafe9b4a2c082f7b1
[ "MIT" ]
null
null
null
Greyatom-projects/code.py
naveena41/greyatom-python-for-data-science
3aa63878ff12e0e8cdf0e63bafe9b4a2c082f7b1
[ "MIT" ]
null
null
null
# -------------- # Code starts here # Create the lists class_1 = ['geoffrey hinton', 'andrew ng', 'sebastian raschka', 'yoshu bengio'] class_2 = ['hilary mason', 'carla gentry', 'corinna cortes'] # Concatenate both the strings new_class = class_1+class_2 print(new_class) # Append the list new_class.append('p...
24.983871
163
0.701097
219
1,549
4.858447
0.415525
0.045113
0.036654
0.028195
0
0
0
0
0
0
0
0.034728
0.182053
1,549
61
164
25.393443
0.805051
0.369916
0
0.130435
0
0
0.276286
0
0
0
0
0
0
1
0
false
0
0
0
0
0.391304
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
0
null
0
0
0
0
0
0
0
0
0
0
0
0
1
0