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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
56652a7a9ad8a080d50971b9bce49832c3f1c49d | 6,853 | py | Python | util.py | jacklxc/ScientificDiscourseTagging | d75514b631b95d39451abd2396f57c3da1c19801 | [
"Apache-2.0"
] | 15 | 2020-01-17T16:45:09.000Z | 2022-01-18T08:44:16.000Z | util.py | jacklxc/ScientificDiscourseTagging | d75514b631b95d39451abd2396f57c3da1c19801 | [
"Apache-2.0"
] | 3 | 2020-12-01T07:34:57.000Z | 2021-08-09T23:07:19.000Z | util.py | jacklxc/ScientificDiscourseTagging | d75514b631b95d39451abd2396f57c3da1c19801 | [
"Apache-2.0"
] | 2 | 2019-05-30T18:52:09.000Z | 2020-06-01T13:36:33.000Z | import codecs
import numpy
import glob
import re
from sklearn.metrics import f1_score
def read_passages(filename, is_labeled):
str_seqs = []
str_seq = []
label_seqs = []
label_seq = []
for line in codecs.open(filename, "r", "utf-8"):
lnstrp = line.strip()
if lnstrp == "":
... | 34.265 | 121 | 0.59069 | 926 | 6,853 | 4.115551 | 0.176026 | 0.039885 | 0.018893 | 0.017843 | 0.19365 | 0.178693 | 0.166623 | 0.145106 | 0.138546 | 0.109683 | 0 | 0.007708 | 0.299577 | 6,853 | 199 | 122 | 34.437186 | 0.78625 | 0.03327 | 0 | 0.233333 | 0 | 0 | 0.038025 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.066667 | false | 0.011111 | 0.027778 | 0 | 0.172222 | 0.011111 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
5669105e25d30b05664f89f0df0423f50da1ae02 | 2,965 | py | Python | examples/Kane1985/Chapter6/Ex11.5.py | nouiz/pydy | 20c8ca9fc521208ae2144b5b453c14ed4a22a0ec | [
"BSD-3-Clause"
] | 298 | 2015-01-31T11:43:22.000Z | 2022-03-15T02:18:21.000Z | examples/Kane1985/Chapter6/Ex11.5.py | nouiz/pydy | 20c8ca9fc521208ae2144b5b453c14ed4a22a0ec | [
"BSD-3-Clause"
] | 359 | 2015-01-17T16:56:42.000Z | 2022-02-08T05:27:08.000Z | examples/Kane1985/Chapter6/Ex11.5.py | nouiz/pydy | 20c8ca9fc521208ae2144b5b453c14ed4a22a0ec | [
"BSD-3-Clause"
] | 109 | 2015-02-03T13:02:45.000Z | 2021-12-21T12:57:21.000Z | #!/usr/bin/env python
# -*- coding: utf-8 -*-
"""Exercise 11.5 from Kane 1985."""
from __future__ import division
from sympy import expand, solve, symbols, trigsimp
from sympy import sin, tan, pi
from sympy.physics.mechanics import Point, ReferenceFrame, RigidBody
from sympy.physics.mechanics import dot, dynamicsymbol... | 31.88172 | 74 | 0.66914 | 562 | 2,965 | 3.379004 | 0.261566 | 0.025276 | 0.021064 | 0.036335 | 0.153239 | 0.082675 | 0.06793 | 0.038968 | 0 | 0 | 0 | 0.036768 | 0.165261 | 2,965 | 92 | 75 | 32.228261 | 0.730505 | 0.157504 | 0 | 0 | 0 | 0 | 0.027441 | 0 | 0 | 0 | 0 | 0 | 0.051724 | 1 | 0 | false | 0 | 0.12069 | 0 | 0.12069 | 0.051724 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
566a183503f12d2d76263243546091eed83cab3c | 3,706 | py | Python | seahub/drafts/utils.py | weimens/seahub | 5ecf78ed7a2ddc72a23961804ee41be21c24893f | [
"Apache-2.0"
] | 420 | 2015-01-03T11:34:46.000Z | 2022-03-10T07:15:41.000Z | seahub/drafts/utils.py | weimens/seahub | 5ecf78ed7a2ddc72a23961804ee41be21c24893f | [
"Apache-2.0"
] | 735 | 2015-01-04T21:22:51.000Z | 2022-03-31T09:26:07.000Z | seahub/drafts/utils.py | weimens/seahub | 5ecf78ed7a2ddc72a23961804ee41be21c24893f | [
"Apache-2.0"
] | 379 | 2015-01-05T17:08:03.000Z | 2022-03-06T00:11:50.000Z | import hashlib
import os
import logging
import posixpath
from seaserv import seafile_api
from seahub.utils import normalize_file_path, check_filename_with_rename
from seahub.tags.models import FileUUIDMap
logger = logging.getLogger(__name__)
def create_user_draft_repo(username, org_id=-1):
repo_name = 'Drafts... | 28.953125 | 92 | 0.658662 | 522 | 3,706 | 4.337165 | 0.151341 | 0.130742 | 0.058304 | 0.056537 | 0.523852 | 0.430212 | 0.380742 | 0.347615 | 0.320671 | 0.292403 | 0 | 0.001801 | 0.250675 | 3,706 | 127 | 93 | 29.181102 | 0.813468 | 0.009714 | 0 | 0.445652 | 0 | 0.01087 | 0.062671 | 0.018062 | 0 | 0 | 0 | 0 | 0 | 1 | 0.065217 | false | 0.021739 | 0.108696 | 0 | 0.228261 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
566d06f55eb168bd0c5dd0836c75fd3bf4352b95 | 781 | py | Python | Questions/Airline Iternary/solution.py | leander-dsouza/Abhyudaya_2020 | 54ec7608c5caa14310b635ac8e8b090156ca0ea4 | [
"MIT"
] | 1 | 2020-07-13T17:28:27.000Z | 2020-07-13T17:28:27.000Z | Questions/Airline Iternary/solution.py | leander-dsouza/Abhyudaya_2020 | 54ec7608c5caa14310b635ac8e8b090156ca0ea4 | [
"MIT"
] | null | null | null | Questions/Airline Iternary/solution.py | leander-dsouza/Abhyudaya_2020 | 54ec7608c5caa14310b635ac8e8b090156ca0ea4 | [
"MIT"
] | null | null | null | def get_itinerary(flights, starting_point, current_itinerary):
if not flights:
return current_itinerary + [starting_point]
updated_itinerary = None
for index, (city_1, city_2) in enumerate(flights):
if starting_point == city_1:
child_itinerary = get_itinerary(
f... | 31.24 | 98 | 0.653009 | 94 | 781 | 5.148936 | 0.361702 | 0.165289 | 0.078512 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.01005 | 0.235595 | 781 | 24 | 99 | 32.541667 | 0.80067 | 0 | 0 | 0 | 0 | 0 | 0.005122 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.055556 | false | 0 | 0 | 0 | 0.166667 | 0.055556 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
566e992466a08d95a9769f7efc588017224e9ab9 | 2,632 | py | Python | SubShift.py | nsaftarli/SubShift | fa1ac906b569fb7dd238e0241b84cd20c1ba2387 | [
"MIT"
] | null | null | null | SubShift.py | nsaftarli/SubShift | fa1ac906b569fb7dd238e0241b84cd20c1ba2387 | [
"MIT"
] | null | null | null | SubShift.py | nsaftarli/SubShift | fa1ac906b569fb7dd238e0241b84cd20c1ba2387 | [
"MIT"
] | null | null | null | import re
import numpy as np
def timestamp_to_num(ts):
num_list = []
ts_list = re.split('[:,]', ts)
for i in ts_list:
num_list.append(int(i))
return np.array(num_list)
def main(filename, delta, output, direction):
buff = []
# Read file
with open(filename, 'r') as f:
conte... | 24.37037 | 84 | 0.612082 | 389 | 2,632 | 3.922879 | 0.233933 | 0.05308 | 0.032765 | 0.031455 | 0.121232 | 0.121232 | 0.065531 | 0.065531 | 0.065531 | 0.065531 | 0 | 0.039583 | 0.270517 | 2,632 | 107 | 85 | 24.598131 | 0.755208 | 0.098024 | 0 | 0.085714 | 0 | 0 | 0.029648 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.114286 | false | 0 | 0.028571 | 0 | 0.242857 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
5672916d34e9bf0fa027e7668987fc3274ffeb22 | 7,445 | py | Python | code/training/i_vector_extraction.py | oananovac/Speaker_Recognition_System | 526eb2467190efeeeb2256849f53cde648b3a294 | [
"MIT"
] | null | null | null | code/training/i_vector_extraction.py | oananovac/Speaker_Recognition_System | 526eb2467190efeeeb2256849f53cde648b3a294 | [
"MIT"
] | null | null | null | code/training/i_vector_extraction.py | oananovac/Speaker_Recognition_System | 526eb2467190efeeeb2256849f53cde648b3a294 | [
"MIT"
] | null | null | null | import numpy as np
from scipy.linalg import eigh
import voice_activity_detector
import features_extraction
import statistics
import utils
def get_sigma(ubm, space_dimension):
sigma = np.zeros(shape=(len(ubm.covariances) * len(ubm.covariances[0])))
k = 0
for i in range(len(ubm.covariances[0])):
fo... | 33.236607 | 92 | 0.58724 | 932 | 7,445 | 4.433476 | 0.17382 | 0.073572 | 0.013553 | 0.026621 | 0.334221 | 0.233785 | 0.172798 | 0.172798 | 0.17062 | 0.130203 | 0 | 0.00924 | 0.302216 | 7,445 | 223 | 93 | 33.38565 | 0.786141 | 0.021222 | 0 | 0.180723 | 0 | 0 | 0.020739 | 0.007142 | 0 | 0 | 0 | 0 | 0 | 1 | 0.060241 | false | 0 | 0.036145 | 0 | 0.13253 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
56756d9a6a2f6b3681bd9d47482a96048107979e | 947 | py | Python | Anaconda-files/Program_15d.py | arvidl/dynamical-systems-with-applications-using-python | db747f550337a7e7ec4a0851b188dd6e2e816a64 | [
"BSD-2-Clause"
] | 106 | 2018-10-10T18:04:02.000Z | 2022-03-11T06:32:38.000Z | Anaconda-files/Program_15d.py | arvidl/dynamical-systems-with-applications-using-python | db747f550337a7e7ec4a0851b188dd6e2e816a64 | [
"BSD-2-Clause"
] | null | null | null | Anaconda-files/Program_15d.py | arvidl/dynamical-systems-with-applications-using-python | db747f550337a7e7ec4a0851b188dd6e2e816a64 | [
"BSD-2-Clause"
] | 54 | 2018-02-06T09:47:42.000Z | 2022-03-25T15:41:43.000Z | # Program 15d: Plotting a Newton fractal.
# See Figure 15.7.
from PIL import Image
width = height = 512
image = Image.new('RGB', (width, height))
xmin, xmax = -1.5, 1.5
ymin, ymax = -1.5, 1.5
max_iter = 20
h = 1e-6 # Step size
eps = 1e-3 # Maximum error
def f(z):
return z**3 - 1.0 # Complex function.
# Dra... | 26.305556 | 71 | 0.531151 | 152 | 947 | 3.289474 | 0.513158 | 0.016 | 0.012 | 0.016 | 0.044 | 0 | 0 | 0 | 0 | 0 | 0 | 0.06192 | 0.317846 | 947 | 35 | 72 | 27.057143 | 0.712074 | 0.211193 | 0 | 0 | 0 | 0 | 0.032564 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.041667 | false | 0 | 0.041667 | 0.041667 | 0.125 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
5675e78e6bff192c2a34c289667d015bc90abcc8 | 870 | py | Python | bonga.py | AfonsoFGarcia/BigBongaClock | bc75f27d7f37a989e2efb417b74f1adfc2821c94 | [
"MIT"
] | 1 | 2015-06-22T16:08:38.000Z | 2015-06-22T16:08:38.000Z | bonga.py | AfonsoFGarcia/BigBongaClock | bc75f27d7f37a989e2efb417b74f1adfc2821c94 | [
"MIT"
] | 1 | 2020-09-08T20:38:24.000Z | 2020-09-08T20:38:24.000Z | bonga.py | AfonsoFGarcia/BigBongaClock | bc75f27d7f37a989e2efb417b74f1adfc2821c94 | [
"MIT"
] | null | null | null | import time
import tweepy as twitter
import os
superhour = time.localtime().tm_hour
hour = superhour % 12
if hour == 0:
hour = 12
sentence = "Tenho %d lágrima%s no canto do mostrador, %s nos Açores%s"
if superhour >= 12:
if hour == 1:
sentence = sentence % (hour, "", "12 lágrimas", "")
else:
sentence = sente... | 26.363636 | 71 | 0.705747 | 121 | 870 | 4.917355 | 0.338843 | 0.129412 | 0.134454 | 0.110924 | 0.352941 | 0.258824 | 0.258824 | 0.258824 | 0.258824 | 0.258824 | 0 | 0.017568 | 0.149425 | 870 | 32 | 72 | 27.1875 | 0.786486 | 0 | 0 | 0.192308 | 0 | 0 | 0.201149 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.115385 | 0 | 0.115385 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
5679b4a709d6dc06439e297747d31c23263a2fac | 1,816 | py | Python | newserver.py | pedrohhcunha/Encryption-system | 2d1be01ab00e3e089f4db2ba391b1d294fbc8a72 | [
"MIT"
] | null | null | null | newserver.py | pedrohhcunha/Encryption-system | 2d1be01ab00e3e089f4db2ba391b1d294fbc8a72 | [
"MIT"
] | null | null | null | newserver.py | pedrohhcunha/Encryption-system | 2d1be01ab00e3e089f4db2ba391b1d294fbc8a72 | [
"MIT"
] | null | null | null | #! /usr/bin/env python
# import thread
import threading
import os.path
import random
import hashlib
import socket
import time
import os
import copy
import socket
letters = 'ABCDEFGHIJKLMNOPQRSTUVWXYZ'
host = ''
port = 9093
pega_mensagem = ''
addr = (host, port)
serv_socket = socket.socket(socket.AF_INET, socket.SOCK_... | 28.825397 | 65 | 0.675661 | 214 | 1,816 | 5.588785 | 0.439252 | 0.150502 | 0.037625 | 0.043478 | 0.108696 | 0.108696 | 0.058528 | 0.058528 | 0.058528 | 0 | 0 | 0.016937 | 0.219714 | 1,816 | 62 | 66 | 29.290323 | 0.8271 | 0.0837 | 0 | 0.042553 | 0 | 0 | 0.106088 | 0.031344 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.191489 | 0 | 0.191489 | 0.148936 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
567f65f38faefff2b824b29b2ea7a8229dd32be4 | 8,294 | py | Python | model/networks.py | ifding/dynamic-analysis-firmware | 4d786c2280527ff38ba615974dd227c4f44c93b2 | [
"MIT"
] | 17 | 2019-01-18T12:45:38.000Z | 2021-12-03T19:55:25.000Z | model/networks.py | ifding/dynamic-analysis-firmware | 4d786c2280527ff38ba615974dd227c4f44c93b2 | [
"MIT"
] | 3 | 2018-06-27T19:08:21.000Z | 2019-12-18T09:29:11.000Z | model/networks.py | ifding/dynamic-analysis-firmware | 4d786c2280527ff38ba615974dd227c4f44c93b2 | [
"MIT"
] | 7 | 2018-07-28T17:58:23.000Z | 2021-01-02T17:16:20.000Z | """
Neural network modules for WaveNet
References :
https://arxiv.org/pdf/1609.03499.pdf
https://github.com/ibab/tensorflow-wavenet
https://qiita.com/MasaEguchi/items/cd5f7e9735a120f27e2a
https://github.com/musyoku/wavenet/issues/4
"""
import torch
import numpy as np
from utils.exceptions import Input... | 31.777778 | 103 | 0.618278 | 1,016 | 8,294 | 4.858268 | 0.163386 | 0.026945 | 0.02107 | 0.037277 | 0.435981 | 0.384724 | 0.326985 | 0.241086 | 0.241086 | 0.241086 | 0 | 0.025797 | 0.284905 | 8,294 | 260 | 104 | 31.9 | 0.806441 | 0.266578 | 0 | 0.177419 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.16129 | false | 0 | 0.024194 | 0 | 0.322581 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
56804b24fb35ab2abb9bf99473495ce4e51fa000 | 3,643 | py | Python | metrics/f2_structured_metadata.py | MaastrichtU-IDS/fair-enough-metrics | deb238a84385e1f94c0e2321b4b3ebdc231094d3 | [
"MIT"
] | 1 | 2022-01-28T09:42:20.000Z | 2022-01-28T09:42:20.000Z | metrics/f2_structured_metadata.py | MaastrichtU-IDS/fair-enough-metrics | deb238a84385e1f94c0e2321b4b3ebdc231094d3 | [
"MIT"
] | null | null | null | metrics/f2_structured_metadata.py | MaastrichtU-IDS/fair-enough-metrics | deb238a84385e1f94c0e2321b4b3ebdc231094d3 | [
"MIT"
] | 1 | 2022-01-29T03:39:37.000Z | 2022-01-29T03:39:37.000Z | import requests
import yaml
from fair_test import FairTest, FairTestEvaluation
class MetricTest(FairTest):
metric_path = 'f2-structured-metadata'
applies_to_principle = 'F2'
title = 'Metadata is structured'
description = """Tests whether a machine is able to find structured metadata. This could be (fo... | 52.042857 | 201 | 0.639308 | 483 | 3,643 | 4.786749 | 0.438923 | 0.036332 | 0.04282 | 0.050606 | 0.196367 | 0.16609 | 0.114187 | 0.07526 | 0.056228 | 0.056228 | 0 | 0.08188 | 0.228932 | 3,643 | 69 | 202 | 52.797101 | 0.741189 | 0.123799 | 0 | 0.036364 | 0 | 0.072727 | 0.518681 | 0.006907 | 0 | 0 | 0 | 0 | 0 | 1 | 0.018182 | false | 0 | 0.054545 | 0 | 0.254545 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
56812e1d2c9fb35b48bbbc87de532ca4299da390 | 1,017 | py | Python | tests/runtime/redis/test_redis.py | igboyes/virtool-workflow | 1ef9a4b0bada1963ff9be0470dfe74b32c9e7ccf | [
"MIT"
] | null | null | null | tests/runtime/redis/test_redis.py | igboyes/virtool-workflow | 1ef9a4b0bada1963ff9be0470dfe74b32c9e7ccf | [
"MIT"
] | null | null | null | tests/runtime/redis/test_redis.py | igboyes/virtool-workflow | 1ef9a4b0bada1963ff9be0470dfe74b32c9e7ccf | [
"MIT"
] | null | null | null | import asyncio
from virtool_workflow_runtime._redis import connect, VIRTOOL_JOBS_CHANNEL, job_id_queue
from virtool_workflow_runtime.runtime import execute_from_redis
JOB_IDs = [str(n) for n in range(3)]
async def assert_correct_job_ids():
queue = job_id_queue()
for id_ in JOB_IDs:
_id = await queue.... | 28.25 | 87 | 0.73353 | 148 | 1,017 | 4.594595 | 0.277027 | 0.079412 | 0.044118 | 0.092647 | 0.135294 | 0.097059 | 0 | 0 | 0 | 0 | 0 | 0.00361 | 0.182891 | 1,017 | 35 | 88 | 29.057143 | 0.814681 | 0 | 0 | 0.086957 | 0 | 0 | 0.011811 | 0 | 0 | 0 | 0 | 0 | 0.217391 | 1 | 0 | false | 0 | 0.130435 | 0 | 0.130435 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
5683642aced3575289798f545fc9efd887e19acc | 3,363 | py | Python | dustmaker/cmd/thumbnail.py | msg555/dustmaker | 8ce54e7e6b29af75d72ca42051881df26624b6fc | [
"Apache-2.0"
] | 11 | 2015-09-29T07:48:30.000Z | 2019-05-05T20:44:48.000Z | dustmaker/cmd/thumbnail.py | msg555/dustmaker | 8ce54e7e6b29af75d72ca42051881df26624b6fc | [
"Apache-2.0"
] | 5 | 2016-10-16T00:30:18.000Z | 2022-02-12T20:04:11.000Z | dustmaker/cmd/thumbnail.py | msg555/dustmaker | 8ce54e7e6b29af75d72ca42051881df26624b6fc | [
"Apache-2.0"
] | 3 | 2016-10-15T20:51:03.000Z | 2019-03-21T03:31:47.000Z | #!/usr/bin/env python3
"""
Sample script to extract and set level thumbnails.
"""
import argparse
import io
import os
import sys
from dustmaker import DFReader, DFWriter
from dustmaker.cmd.common import (
run_utility,
CliUtility,
)
from dustmaker.variable import VariableBool
class Thumbnail(CliUtility):
... | 30.297297 | 96 | 0.549509 | 364 | 3,363 | 4.964286 | 0.368132 | 0.029884 | 0.056447 | 0.046486 | 0.153846 | 0.119535 | 0.119535 | 0.119535 | 0.119535 | 0.119535 | 0 | 0.008287 | 0.354148 | 3,363 | 110 | 97 | 30.572727 | 0.823665 | 0.063039 | 0 | 0.321839 | 0 | 0 | 0.153871 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.022989 | false | 0 | 0.114943 | 0 | 0.195402 | 0.022989 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
568673ef2cde487c729769189c6ebe595faadce9 | 2,170 | py | Python | kts/ui/leaderboard.py | konodyuk/kts | 3af5ccbf1d2089cb41d171626fcde4b0ba5aa8a7 | [
"MIT"
] | 18 | 2019-02-14T13:10:07.000Z | 2021-11-26T07:10:13.000Z | kts/ui/leaderboard.py | konodyuk/kts | 3af5ccbf1d2089cb41d171626fcde4b0ba5aa8a7 | [
"MIT"
] | 2 | 2019-02-17T14:06:42.000Z | 2019-09-15T18:05:54.000Z | kts/ui/leaderboard.py | konodyuk/kts | 3af5ccbf1d2089cb41d171626fcde4b0ba5aa8a7 | [
"MIT"
] | 2 | 2019-09-15T13:12:42.000Z | 2020-04-15T14:05:54.000Z | import time
from kts.ui.components import HTMLRepr, Column, Field, Title, ThumbnailField, Raw
from kts.util.formatting import format_value
def format_experiment_date(date):
delta = time.time() - date
if delta < 60 * 60 * 24:
return format_value(delta, time=True) + ' ago'
else:
return form... | 38.070175 | 160 | 0.595392 | 298 | 2,170 | 4.224832 | 0.312081 | 0.04448 | 0.051628 | 0.042891 | 0.238284 | 0.196187 | 0.123114 | 0.084194 | 0.084194 | 0.084194 | 0 | 0.020013 | 0.263134 | 2,170 | 56 | 161 | 38.75 | 0.767355 | 0.014286 | 0 | 0 | 0 | 0 | 0.096578 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.136364 | false | 0 | 0.068182 | 0.068182 | 0.363636 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
5687b2eebefd1922fec6386607f4531267b31693 | 2,726 | py | Python | dags/etl_store_dag.py | nileshvarshney/airflow | 6bb31a3acdd5a9c8bb74ddb01a851adb99602b9b | [
"Apache-2.0"
] | null | null | null | dags/etl_store_dag.py | nileshvarshney/airflow | 6bb31a3acdd5a9c8bb74ddb01a851adb99602b9b | [
"Apache-2.0"
] | null | null | null | dags/etl_store_dag.py | nileshvarshney/airflow | 6bb31a3acdd5a9c8bb74ddb01a851adb99602b9b | [
"Apache-2.0"
] | null | null | null | # import python libraries
from airflow import DAG
from datetime import datetime, timedelta
from airflow.operators.bash_operator import BashOperator
from airflow.operators.python_operator import PythonOperator
from datacleaner import data_cleaner
from airflow.operators.mysql_operator import MySqlOperator
from airflow.op... | 32.843373 | 210 | 0.733309 | 356 | 2,726 | 5.275281 | 0.297753 | 0.025559 | 0.063365 | 0.038339 | 0.309904 | 0.309904 | 0.242279 | 0.187433 | 0.096912 | 0.056443 | 0 | 0.014145 | 0.144167 | 2,726 | 82 | 211 | 33.243902 | 0.790827 | 0.147469 | 0 | 0.185185 | 0 | 0.037037 | 0.307759 | 0.208496 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.12963 | 0 | 0.12963 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
568d890d93930eebca3929a03cee09545033af9c | 1,976 | py | Python | Pibow/sprinkles.py | ShineTop/Unicorn-HAT | 9ff1388ee627a8e81f361929e9e9b708db4e2832 | [
"MIT"
] | null | null | null | Pibow/sprinkles.py | ShineTop/Unicorn-HAT | 9ff1388ee627a8e81f361929e9e9b708db4e2832 | [
"MIT"
] | null | null | null | Pibow/sprinkles.py | ShineTop/Unicorn-HAT | 9ff1388ee627a8e81f361929e9e9b708db4e2832 | [
"MIT"
] | null | null | null | #!/usr/bin/python3
"""
Sprinkles - Pibow
This program lights up and turns off random LEDS using the colors of the
Pibow Zero Candy case
....................
Functions:
- sprinkles: Lights up and turns off random LEDs
....................
Author: Paul Ryan
This program was written on a Raspberry Pi using the Geany... | 27.830986 | 72 | 0.508097 | 199 | 1,976 | 4.844221 | 0.442211 | 0.043568 | 0.105809 | 0.143154 | 0.212656 | 0.108921 | 0.108921 | 0.078838 | 0 | 0 | 0 | 0.018056 | 0.271255 | 1,976 | 70 | 73 | 28.228571 | 0.651389 | 0.321356 | 0 | 0.068966 | 0 | 0 | 0.052941 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.034483 | false | 0 | 0.275862 | 0 | 0.310345 | 0.103448 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
56920c08dfcb1a77f8cde28ba7bdd1f09b763b05 | 4,387 | py | Python | src/luh3417/snapshot/__init__.py | HenryJobst/luh3417 | 680c21739d2afb9559e4d8bdf4eedeaf5a6b1e28 | [
"WTFPL"
] | 1 | 2020-12-02T15:47:11.000Z | 2020-12-02T15:47:11.000Z | src/luh3417/snapshot/__init__.py | HenryJobst/luh3417 | 680c21739d2afb9559e4d8bdf4eedeaf5a6b1e28 | [
"WTFPL"
] | null | null | null | src/luh3417/snapshot/__init__.py | HenryJobst/luh3417 | 680c21739d2afb9559e4d8bdf4eedeaf5a6b1e28 | [
"WTFPL"
] | null | null | null | import subprocess
import re
from typing import Sequence, Text
from luh3417.luhfs import LocalLocation, Location, SshLocation
from luh3417.luhssh import SshManager
from luh3417.utils import LuhError
def rsync_files(source: Location, target: Location, delete: bool = False):
"""
Use rsync to copy files from a ... | 29.442953 | 114 | 0.664235 | 542 | 4,387 | 5.197417 | 0.226937 | 0.044728 | 0.039759 | 0.040469 | 0.457579 | 0.389776 | 0.336528 | 0.28044 | 0.28044 | 0.28044 | 0 | 0.009338 | 0.218828 | 4,387 | 148 | 115 | 29.641892 | 0.812664 | 0.073627 | 0 | 0.163043 | 0 | 0 | 0.152691 | 0.028035 | 0 | 0 | 0 | 0 | 0 | 1 | 0.076087 | false | 0 | 0.065217 | 0 | 0.173913 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
5692c81d7e2760ade8f07b80322678af0eaf034a | 988 | py | Python | Longest Palindrome.py | sugia/leetcode | 6facec2a54d1d9f133f420c9bce1d1043f57ebc6 | [
"Apache-2.0"
] | null | null | null | Longest Palindrome.py | sugia/leetcode | 6facec2a54d1d9f133f420c9bce1d1043f57ebc6 | [
"Apache-2.0"
] | null | null | null | Longest Palindrome.py | sugia/leetcode | 6facec2a54d1d9f133f420c9bce1d1043f57ebc6 | [
"Apache-2.0"
] | null | null | null | '''
Given a string which consists of lowercase or uppercase letters, find the length of the longest palindromes that can be built with those letters.
This is case sensitive, for example "Aa" is not considered a palindrome here.
Note:
Assume the length of given string will not exceed 1,010.
Example:
Input:
"abccccd... | 21.021277 | 145 | 0.508097 | 128 | 988 | 3.898438 | 0.546875 | 0.04008 | 0.03006 | 0.056112 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.022414 | 0.412955 | 988 | 46 | 146 | 21.478261 | 0.837931 | 0.446356 | 0 | 0.105263 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.052632 | false | 0 | 0 | 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 |
569a7754edeb369bfa7791b3bdcf74473cb3053f | 3,780 | py | Python | GUI/Toolbox/metadata.py | Guillermo-Hidalgo-Gadea/RPi4Toolbox | 47a265aa9828f144155c097efc8ff36bd435099f | [
"MIT"
] | null | null | null | GUI/Toolbox/metadata.py | Guillermo-Hidalgo-Gadea/RPi4Toolbox | 47a265aa9828f144155c097efc8ff36bd435099f | [
"MIT"
] | null | null | null | GUI/Toolbox/metadata.py | Guillermo-Hidalgo-Gadea/RPi4Toolbox | 47a265aa9828f144155c097efc8ff36bd435099f | [
"MIT"
] | 1 | 2021-10-15T16:14:48.000Z | 2021-10-15T16:14:48.000Z | # Metadata module to save metadata as dictionary, save trial metadata as yaml and export metadata as csv
import yaml
import datetime
import pandas as pd
from pathlib import Path
class Metadata:
def __init__(self):
base_path = Path().parent
self.metadata_dir = (base_path / "RPi4Toolbox/GUI/Toolbox/... | 43.953488 | 127 | 0.636508 | 436 | 3,780 | 5.415138 | 0.263761 | 0.100805 | 0.031766 | 0.033884 | 0.166878 | 0.130453 | 0.121982 | 0.121982 | 0.081321 | 0.05252 | 0 | 0.003492 | 0.242328 | 3,780 | 86 | 128 | 43.953488 | 0.82088 | 0.18836 | 0 | 0.193548 | 0 | 0 | 0.126111 | 0.025354 | 0 | 0 | 0 | 0 | 0 | 1 | 0.064516 | false | 0 | 0.064516 | 0 | 0.145161 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
569ec3463a6b9dc7fdb5c4eccfb276fd52b756ed | 1,190 | py | Python | jobya/companies/management/commands/setup_company.py | xblzbjs/Jobya | b936ce37da86bfe8326a532dab3887fae6c65e45 | [
"MIT"
] | null | null | null | jobya/companies/management/commands/setup_company.py | xblzbjs/Jobya | b936ce37da86bfe8326a532dab3887fae6c65e45 | [
"MIT"
] | 2 | 2022-02-08T01:15:52.000Z | 2022-03-31T04:24:15.000Z | jobya/companies/management/commands/setup_company.py | xblzbjs/Jobya | b936ce37da86bfe8326a532dab3887fae6c65e45 | [
"MIT"
] | null | null | null | from django.core.management.base import BaseCommand
from django.db import transaction
from jobya.companies.models import Company
from jobya.companies.tests.factories import CompanyFactory
class Command(BaseCommand):
help = "Set up company data"
def add_arguments(self, parser):
parser.add_argument(
... | 29.02439 | 67 | 0.607563 | 130 | 1,190 | 5.492308 | 0.5 | 0.056022 | 0.084034 | 0.047619 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.001174 | 0.284034 | 1,190 | 40 | 68 | 29.75 | 0.836854 | 0 | 0 | 0.060606 | 0 | 0 | 0.20084 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.090909 | false | 0 | 0.121212 | 0 | 0.272727 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
569fd8ab2bfa51b46a8fc425da22db12d4345b01 | 2,188 | py | Python | presenter.py | liordon/motion_detector | 7c22062bb3a8b254d9e4a3d6d88a89d89320785a | [
"Unlicense"
] | null | null | null | presenter.py | liordon/motion_detector | 7c22062bb3a8b254d9e4a3d6d88a89d89320785a | [
"Unlicense"
] | null | null | null | presenter.py | liordon/motion_detector | 7c22062bb3a8b254d9e4a3d6d88a89d89320785a | [
"Unlicense"
] | null | null | null | import ast
import datetime
import cv2
import psutil
from utils import *
def presenter_log(message: str):
log("PRST", message)
def present_annotated_frames_from_stream(pipe_reader, pid):
presenter_log("presenter presents")
while pipe_reader.poll(3) or psutil.pid_exists(pid):
message = pipe_read... | 33.661538 | 91 | 0.612431 | 286 | 2,188 | 4.513986 | 0.451049 | 0.069713 | 0.03718 | 0.044152 | 0.201394 | 0.17196 | 0.108443 | 0 | 0 | 0 | 0 | 0.036825 | 0.280165 | 2,188 | 64 | 92 | 34.1875 | 0.782857 | 0.094607 | 0 | 0.173913 | 0 | 0 | 0.061772 | 0 | 0 | 0 | 0.002025 | 0 | 0 | 1 | 0.043478 | false | 0 | 0.108696 | 0 | 0.152174 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
56a0677ee2c20f71870059ac35a9ec0979418868 | 3,412 | py | Python | mllearn/problem_transform/klabelsets.py | Lxinyuelxy/multi-label-learn | ab347e9c9ccac1503f22c7b76e0b3e9a4e8214da | [
"MIT"
] | 4 | 2018-11-19T13:34:53.000Z | 2020-01-11T11:58:13.000Z | mllearn/problem_transform/klabelsets.py | Lxinyuelxy/multi-label-learn | ab347e9c9ccac1503f22c7b76e0b3e9a4e8214da | [
"MIT"
] | null | null | null | mllearn/problem_transform/klabelsets.py | Lxinyuelxy/multi-label-learn | ab347e9c9ccac1503f22c7b76e0b3e9a4e8214da | [
"MIT"
] | 3 | 2019-04-14T18:13:33.000Z | 2021-04-05T14:45:56.000Z | import copy
import random
import numpy as np
from sklearn.svm import SVC
class RandomKLabelsets:
"""RandomKLabelsets
Reference Paper:
Min-Ling Zhang and Zhi-Hua Zhou. A Review on Multi-Label Learning Algorithms
"""
def __init__(self, classifier=SVC(kernel='rbf')):
self.classifier = clas... | 36.297872 | 87 | 0.566823 | 425 | 3,412 | 4.451765 | 0.225882 | 0.057082 | 0.088795 | 0.02907 | 0.118922 | 0.02537 | 0 | 0 | 0 | 0 | 0 | 0.014354 | 0.326202 | 3,412 | 93 | 88 | 36.688172 | 0.808612 | 0.033411 | 0 | 0.075 | 0 | 0 | 0.012199 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.1125 | false | 0 | 0.05 | 0 | 0.275 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
56a0e67715f2ad6066c4212bdf3b6c7670e86244 | 406 | py | Python | users/tests/test_view.py | VladaDidko/skill- | 861c08376e2bc9b9a5a44e3a8560324ee53ce2d0 | [
"Unlicense"
] | null | null | null | users/tests/test_view.py | VladaDidko/skill- | 861c08376e2bc9b9a5a44e3a8560324ee53ce2d0 | [
"Unlicense"
] | 18 | 2019-05-28T17:20:34.000Z | 2022-03-11T23:50:12.000Z | users/tests/test_view.py | VladaDidko/skill- | 861c08376e2bc9b9a5a44e3a8560324ee53ce2d0 | [
"Unlicense"
] | 3 | 2019-05-27T09:51:54.000Z | 2019-12-12T20:35:29.000Z | from django.test import TestCase, Client
from django.urls import reverse
class TestViews(TestCase):
def setUp(self):
self.client = Client()
self.register_url = reverse('register')
self.profile_url = reverse('profile')
def test_register(self):
response = self.client.get(self.register_url)
self.assertEqual... | 29 | 58 | 0.768473 | 53 | 406 | 5.792453 | 0.471698 | 0.065147 | 0.09772 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.008357 | 0.115764 | 406 | 14 | 58 | 29 | 0.846797 | 0 | 0 | 0 | 0 | 0 | 0.083538 | 0 | 0 | 0 | 0 | 0 | 0.181818 | 1 | 0.181818 | false | 0 | 0.181818 | 0 | 0.454545 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
56a142df9367848a23bc2307ae8b5ba73cf7b0ac | 976 | py | Python | incidences/forms.py | atlasfoo/risk_audit_websys | df43a48699b16d0d0bade3f597d889bfe20eda7b | [
"MIT"
] | null | null | null | incidences/forms.py | atlasfoo/risk_audit_websys | df43a48699b16d0d0bade3f597d889bfe20eda7b | [
"MIT"
] | 13 | 2021-05-28T05:22:16.000Z | 2021-06-02T05:49:07.000Z | incidences/forms.py | atlasfoo/risksys | df43a48699b16d0d0bade3f597d889bfe20eda7b | [
"MIT"
] | null | null | null | from django import forms
from incidences.models import Incidence
class IncidenceForm(forms.ModelForm):
class Meta:
model = Incidence
fields = ['name', 'description', 'risk', 'causes', 'effects', 'controls']
widgets = {
'name': forms.TextInput(attrs={'class': 'form-control', 'p... | 39.04 | 98 | 0.571721 | 84 | 976 | 6.642857 | 0.440476 | 0.107527 | 0.150538 | 0.143369 | 0.335125 | 0.335125 | 0 | 0 | 0 | 0 | 0 | 0 | 0.259221 | 976 | 24 | 99 | 40.666667 | 0.771784 | 0 | 0 | 0 | 0 | 0 | 0.320697 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.095238 | 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 |
56a2df9338d095c9e041cd414ec3dfeb1e4f74ab | 2,206 | py | Python | Detector.py | Corzair1/EyeC | 0e90f8d296833c6d4b9d8eeeeed48d3a05d52ffb | [
"MIT"
] | null | null | null | Detector.py | Corzair1/EyeC | 0e90f8d296833c6d4b9d8eeeeed48d3a05d52ffb | [
"MIT"
] | null | null | null | Detector.py | Corzair1/EyeC | 0e90f8d296833c6d4b9d8eeeeed48d3a05d52ffb | [
"MIT"
] | null | null | null | import cv2 as cv
import numpy as np
from urllib.request import urlopen
import os
import datetime
import time
import sys
#change to your ESP32-CAM ip
url="http://192.168.31.184:81/stream"
CAMERA_BUFFRER_SIZE=4096
stream=urlopen(url)
bts=b''
while True:
try:
while True:
bts+=stream.read(CAMERA_BU... | 29.413333 | 106 | 0.497733 | 282 | 2,206 | 3.801418 | 0.489362 | 0.058769 | 0.025187 | 0.020522 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.07478 | 0.381686 | 2,206 | 75 | 107 | 29.413333 | 0.711144 | 0.06573 | 0 | 0.040816 | 0 | 0 | 0.036425 | 0 | 0 | 0 | 0.001943 | 0 | 0 | 1 | 0 | false | 0.020408 | 0.142857 | 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 |
56a3e14dbfe824cc296d28795afa04041f550530 | 3,489 | py | Python | imdb/imdb/spiders/imdb_3.py | KarolinaSzwedo/WebscrapingProject | fb59c476df8632a449290f9a4374501673729d7c | [
"MIT"
] | 1 | 2021-05-02T20:21:26.000Z | 2021-05-02T20:21:26.000Z | imdb/imdb/spiders/imdb_3.py | KarolinaSzwedo/WebscrapingProject | fb59c476df8632a449290f9a4374501673729d7c | [
"MIT"
] | null | null | null | imdb/imdb/spiders/imdb_3.py | KarolinaSzwedo/WebscrapingProject | fb59c476df8632a449290f9a4374501673729d7c | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
import scrapy
from scrapy import Request
class Movie(scrapy.Item):
# define all items to scrape
title = scrapy.Field()
genres = scrapy.Field()
when = scrapy.Field()
director = scrapy.Field()
stars = scrapy.Field()
country = scrapy.Field... | 50.565217 | 162 | 0.5953 | 431 | 3,489 | 4.742459 | 0.310905 | 0.053816 | 0.046967 | 0.016145 | 0.129159 | 0.112524 | 0.085127 | 0.034247 | 0 | 0 | 0 | 0.011864 | 0.251075 | 3,489 | 68 | 163 | 51.308824 | 0.770379 | 0.220407 | 0 | 0 | 0 | 0.083333 | 0.274575 | 0.196231 | 0 | 0 | 0 | 0 | 0 | 1 | 0.020833 | false | 0 | 0.041667 | 0 | 0.375 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
56a469688cdd8e5eda3a9186b703e25f8c24b34a | 14,742 | py | Python | main.py | odgon/monitoring-vertica | 300cc2bbe490dddc331475732cb6d5766a128efb | [
"MIT"
] | 3 | 2020-07-29T19:30:25.000Z | 2022-03-20T13:57:28.000Z | main.py | odgon/monitoring-vertica | 300cc2bbe490dddc331475732cb6d5766a128efb | [
"MIT"
] | null | null | null | main.py | odgon/monitoring-vertica | 300cc2bbe490dddc331475732cb6d5766a128efb | [
"MIT"
] | null | null | null | from fastapi import FastAPI
from vc import vc
import json
from fastapi.openapi.utils import get_openapi
from fastapi.openapi.docs import (
get_redoc_html,
get_swagger_ui_html,
get_swagger_ui_oauth2_redirect_html,
)
with open('config.json') as jf:
d = json.load(jf)
vh = d['vertica']['host']
vpo ... | 31.035789 | 353 | 0.574413 | 1,737 | 14,742 | 4.64882 | 0.173287 | 0.043344 | 0.043344 | 0.04644 | 0.482848 | 0.418947 | 0.344644 | 0.301672 | 0.290402 | 0.254241 | 0 | 0.006691 | 0.310609 | 14,742 | 474 | 354 | 31.101266 | 0.787858 | 0 | 0 | 0.441975 | 0 | 0.017284 | 0.526591 | 0.06824 | 0 | 0 | 0 | 0 | 0 | 1 | 0.071605 | false | 0.004938 | 0.012346 | 0.002469 | 0.232099 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b05ff6c3393fdf9cff7387c667789a685e86381 | 6,465 | py | Python | drive.py | 7th-mod-korea/when_they_cry_converter | 92956d40c02ece1b0536fbddc9799553e11af93c | [
"MIT"
] | 1 | 2020-03-10T01:16:34.000Z | 2020-03-10T01:16:34.000Z | drive.py | 7th-mod-korea/when_they_cry_converter | 92956d40c02ece1b0536fbddc9799553e11af93c | [
"MIT"
] | null | null | null | drive.py | 7th-mod-korea/when_they_cry_converter | 92956d40c02ece1b0536fbddc9799553e11af93c | [
"MIT"
] | null | null | null | from __future__ import print_function
import pickle
import os.path
import sys
import hashlib
from googleapiclient.discovery import build
from google_auth_oauthlib.flow import InstalledAppFlow
from google.auth.transport.requests import Request
from apiclient import errors
from googleapiclient.http import MediaIoBaseDown... | 39.662577 | 106 | 0.605878 | 746 | 6,465 | 5.049598 | 0.257373 | 0.047783 | 0.037961 | 0.020706 | 0.341917 | 0.336607 | 0.285638 | 0.285638 | 0.285638 | 0.285638 | 0 | 0.00701 | 0.29389 | 6,465 | 163 | 107 | 39.662577 | 0.818182 | 0.058778 | 0 | 0.27907 | 0 | 0 | 0.1221 | 0.032911 | 0 | 0 | 0 | 0 | 0 | 1 | 0.046512 | false | 0.007752 | 0.077519 | 0 | 0.139535 | 0.062016 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b08aa7fb58998cc3b6424f138688be5f547dfe9 | 15,841 | py | Python | minecraftcogs/chatrelay.py | jinkhya/Charfred_Cogs | d6afc4c02e668c046ba40e9a7afae68004658f6d | [
"MIT"
] | null | null | null | minecraftcogs/chatrelay.py | jinkhya/Charfred_Cogs | d6afc4c02e668c046ba40e9a7afae68004658f6d | [
"MIT"
] | null | null | null | minecraftcogs/chatrelay.py | jinkhya/Charfred_Cogs | d6afc4c02e668c046ba40e9a7afae68004658f6d | [
"MIT"
] | null | null | null | import logging
import asyncio
from concurrent.futures import CancelledError
from discord.ext import commands
from utils import Config, permission_node
log = logging.getLogger('charfred')
formats = {
'MSG': '[**{}**] {}: {}',
'STF': '**{}**: {}',
'DTH': '[**{}**] {} {}',
'ME': '[**{}**] {}: {}',
'S... | 40.307888 | 99 | 0.540496 | 1,751 | 15,841 | 4.804683 | 0.175328 | 0.037085 | 0.028527 | 0.013075 | 0.370498 | 0.288839 | 0.233092 | 0.176631 | 0.144538 | 0.121716 | 0 | 0.002334 | 0.350862 | 15,841 | 392 | 100 | 40.410714 | 0.815813 | 0.028155 | 0 | 0.375405 | 0 | 0 | 0.221528 | 0.010455 | 0 | 0 | 0 | 0 | 0 | 1 | 0.012945 | false | 0.02589 | 0.016181 | 0.003236 | 0.064725 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b0aff3db58f48e9ba786715261c204ed5990700 | 7,504 | py | Python | Code/SubwayMap.py | VGarK/Mapz | e09654b261ae25fbc73c677432aff5e26f43e42f | [
"MIT"
] | null | null | null | Code/SubwayMap.py | VGarK/Mapz | e09654b261ae25fbc73c677432aff5e26f43e42f | [
"MIT"
] | null | null | null | Code/SubwayMap.py | VGarK/Mapz | e09654b261ae25fbc73c677432aff5e26f43e42f | [
"MIT"
] | null | null | null | # This file has all the functions required to load the information of a city.
# - Definition of the class Station
# - Definition of the class CityInfo
# - Read functions from files
# - Structure of the information
#
__authors__='TO_BE_FILLED'
__group__='DL01'
# __________________________________________________________... | 41.458564 | 136 | 0.597415 | 852 | 7,504 | 4.880282 | 0.211268 | 0.00938 | 0.010101 | 0.00962 | 0.214045 | 0.181818 | 0.13468 | 0.125301 | 0.106061 | 0.074074 | 0 | 0.005912 | 0.301173 | 7,504 | 181 | 137 | 41.458564 | 0.786995 | 0.315165 | 0 | 0.227642 | 0 | 0 | 0.04919 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.089431 | false | 0 | 0 | 0 | 0.138211 | 0.162602 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b0ce22e9f3f3849e6cb4645ba1ee7779174285d | 5,290 | py | Python | deprecated/converters/gw100_converter.py | materials-data-facility/connect | 9ec5b61750bf6fa579bf3ec122f31880d3c049b8 | [
"Apache-2.0"
] | 1 | 2019-09-13T18:35:56.000Z | 2019-09-13T18:35:56.000Z | deprecated/converters/gw100_converter.py | materials-data-facility/connect_server | 9ec5b61750bf6fa579bf3ec122f31880d3c049b8 | [
"Apache-2.0"
] | 15 | 2018-11-01T18:08:11.000Z | 2021-12-06T17:55:03.000Z | deprecated/converters/gw100_converter.py | materials-data-facility/connect | 9ec5b61750bf6fa579bf3ec122f31880d3c049b8 | [
"Apache-2.0"
] | 1 | 2020-11-30T17:02:41.000Z | 2020-11-30T17:02:41.000Z | import json
import sys
import os
from tqdm import tqdm
from mdf_refinery.validator import Validator
from mdf_refinery.parsers.tab_parser import parse_tab
# VERSION 0.3.0
# This is the converter for the GW100 dataset.
# Arguments:
# input_path (string): The file or directory where the data resides.
# NOTE: D... | 31.488095 | 548 | 0.520038 | 546 | 5,290 | 4.957875 | 0.457875 | 0.038788 | 0.011082 | 0.008866 | 0.096047 | 0.096047 | 0.074621 | 0.074621 | 0.074621 | 0.074621 | 0 | 0.022425 | 0.359357 | 5,290 | 167 | 549 | 31.676647 | 0.776335 | 0.320605 | 0 | 0.142857 | 0 | 0.028571 | 0.364586 | 0.008472 | 0 | 0 | 0 | 0 | 0 | 1 | 0.014286 | false | 0 | 0.085714 | 0 | 0.1 | 0.042857 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b1083dfb47666192fcefb6373fe2fcf7bc0a2fb | 9,098 | py | Python | backend/backend.py | Mishelles/vk-spotify-playlist-transfer | 4c15a9e35b1ff9aa81c7d36c53ef69b54d5a6914 | [
"MIT"
] | 1 | 2021-04-16T21:48:21.000Z | 2021-04-16T21:48:21.000Z | backend/backend.py | Mishelles/vk-spotify-playlist-transfer | 4c15a9e35b1ff9aa81c7d36c53ef69b54d5a6914 | [
"MIT"
] | 8 | 2021-04-05T17:16:10.000Z | 2021-10-12T13:31:19.000Z | backend/backend.py | Mishelles/vk-spotify-playlist-transfer | 4c15a9e35b1ff9aa81c7d36c53ef69b54d5a6914 | [
"MIT"
] | null | null | null | import os
import uuid
import json
import yaml
import re
from nltk.tokenize import RegexpTokenizer
import requests
from fastapi import FastAPI, HTTPException
from fastapi.middleware.cors import CORSMiddleware
from get_root_access_token_for_sp import get_token
from pydantic import BaseModel
from vkaudiotoken import (... | 30.530201 | 125 | 0.62783 | 1,097 | 9,098 | 4.958979 | 0.220602 | 0.036397 | 0.016728 | 0.013787 | 0.348529 | 0.287684 | 0.231618 | 0.207353 | 0.161765 | 0.148897 | 0 | 0.012273 | 0.238734 | 9,098 | 298 | 126 | 30.530201 | 0.773174 | 0.009453 | 0 | 0.223141 | 0 | 0.004132 | 0.162412 | 0.016172 | 0 | 0 | 0 | 0 | 0 | 1 | 0.053719 | false | 0.012397 | 0.049587 | 0.004132 | 0.169421 | 0.045455 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b121f96edfab2bb880eeea95628f1c1be9789b4 | 8,616 | py | Python | src/Noncircular/Calculations/_Appendix13_7_c.py | thepvguy/calctoys | f7ef4e422d8a27cc387c1a24b5fb6e318d774f57 | [
"Unlicense"
] | 7 | 2018-07-17T08:01:34.000Z | 2021-06-14T03:33:58.000Z | src/Noncircular/Calculations/_Appendix13_7_c.py | thepvguy/calctoys | f7ef4e422d8a27cc387c1a24b5fb6e318d774f57 | [
"Unlicense"
] | null | null | null | src/Noncircular/Calculations/_Appendix13_7_c.py | thepvguy/calctoys | f7ef4e422d8a27cc387c1a24b5fb6e318d774f57 | [
"Unlicense"
] | 6 | 2018-10-01T10:29:58.000Z | 2022-01-24T22:34:16.000Z | import math
# TODO: Implement acceptibility tests
class Appendix13_7_cParams:
def __init__(
self,
internal_pressure,
corner_radius,
short_side_half_length,
long_side_half_length,
thickness,
eval_at_outer_walls = False):
... | 32.636364 | 163 | 0.558264 | 1,412 | 8,616 | 3.139518 | 0.097026 | 0.069479 | 0.059553 | 0.043988 | 0.57681 | 0.46808 | 0.397248 | 0.37266 | 0.36499 | 0.233476 | 0 | 0.046191 | 0.28389 | 8,616 | 264 | 164 | 32.636364 | 0.672285 | 0.220636 | 0 | 0.019868 | 0 | 0 | 0.072878 | 0 | 0 | 0 | 0 | 0.003788 | 0 | 1 | 0.15894 | false | 0 | 0.013245 | 0.019868 | 0.324503 | 0.357616 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b1344dd323e948e9f6017df3b1661af235dfa13 | 1,619 | py | Python | tests/api_resources/test_file_link.py | bhch/async-stripe | 75d934a8bb242f664e7be30812c12335cf885287 | [
"MIT",
"BSD-3-Clause"
] | 8 | 2021-05-29T08:57:58.000Z | 2022-02-19T07:09:25.000Z | tests/api_resources/test_file_link.py | bhch/async-stripe | 75d934a8bb242f664e7be30812c12335cf885287 | [
"MIT",
"BSD-3-Clause"
] | 5 | 2021-05-31T10:18:36.000Z | 2022-01-25T11:39:03.000Z | tests/api_resources/test_file_link.py | bhch/async-stripe | 75d934a8bb242f664e7be30812c12335cf885287 | [
"MIT",
"BSD-3-Clause"
] | 1 | 2021-05-29T13:27:10.000Z | 2021-05-29T13:27:10.000Z | from __future__ import absolute_import, division, print_function
import stripe
import pytest
pytestmark = pytest.mark.asyncio
TEST_RESOURCE_ID = "link_123"
class TestFileLink(object):
async def test_is_listable(self, request_mock):
resources = await stripe.FileLink.list()
request_mock.assert... | 33.040816 | 67 | 0.683138 | 190 | 1,619 | 5.547368 | 0.278947 | 0.104364 | 0.092979 | 0.066414 | 0.612903 | 0.597723 | 0.571158 | 0.491461 | 0.387097 | 0.324478 | 0 | 0.009471 | 0.217418 | 1,619 | 48 | 68 | 33.729167 | 0.822415 | 0 | 0 | 0.277778 | 0 | 0 | 0.079679 | 0 | 0 | 0 | 0 | 0 | 0.277778 | 1 | 0 | false | 0 | 0.083333 | 0 | 0.111111 | 0.027778 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b15a52f6be4dc16088c1fb00a71fbd34c59ea53 | 762 | py | Python | L1Trigger/GlobalTriggerAnalyzer/python/l1GtBeamModeFilter_cfi.py | ckamtsikis/cmssw | ea19fe642bb7537cbf58451dcf73aa5fd1b66250 | [
"Apache-2.0"
] | 852 | 2015-01-11T21:03:51.000Z | 2022-03-25T21:14:00.000Z | L1Trigger/GlobalTriggerAnalyzer/python/l1GtBeamModeFilter_cfi.py | ckamtsikis/cmssw | ea19fe642bb7537cbf58451dcf73aa5fd1b66250 | [
"Apache-2.0"
] | 30,371 | 2015-01-02T00:14:40.000Z | 2022-03-31T23:26:05.000Z | L1Trigger/GlobalTriggerAnalyzer/python/l1GtBeamModeFilter_cfi.py | ckamtsikis/cmssw | ea19fe642bb7537cbf58451dcf73aa5fd1b66250 | [
"Apache-2.0"
] | 3,240 | 2015-01-02T05:53:18.000Z | 2022-03-31T17:24:21.000Z | import FWCore.ParameterSet.Config as cms
l1GtBeamModeFilter = cms.EDFilter("L1GtBeamModeFilter",
# input tag for input tag for ConditionInEdm products
CondInEdmInputTag = cms.InputTag("conditionsInEdm"),
# input tag for the L1 GT EVM product
L1GtEvmReadoutRecordTag = cms.InputTag("gtEvmDigis"),
... | 34.636364 | 71 | 0.675853 | 91 | 762 | 5.659341 | 0.582418 | 0.062136 | 0.064078 | 0.069903 | 0.081553 | 0 | 0 | 0 | 0 | 0 | 0 | 0.017637 | 0.255906 | 762 | 21 | 72 | 36.285714 | 0.890653 | 0.528871 | 0 | 0 | 0 | 0 | 0.123563 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.142857 | 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 |
3b168867b6c2192e22d3fb03d5618d1c3ca2e893 | 3,177 | py | Python | python/Day11/seating.py | joelbygger/adventofcode20 | 35f9f4fa9bf051f420a22400c896bc7d26dc44d7 | [
"MIT"
] | null | null | null | python/Day11/seating.py | joelbygger/adventofcode20 | 35f9f4fa9bf051f420a22400c896bc7d26dc44d7 | [
"MIT"
] | null | null | null | python/Day11/seating.py | joelbygger/adventofcode20 | 35f9f4fa9bf051f420a22400c896bc7d26dc44d7 | [
"MIT"
] | null | null | null | import copy
def _direction():
# If array index start at 0, 0 and we say that is top left, (x, y)
yield -1, -1 # UL
yield -1, 0 # L
yield -1, 1 # UR
yield 0, -1 # U
yield 0, 1 # D
yield 1, -1 # DL
yield 1, 0 # R
yield 1, 1 # DR
# def _in_matrix(pos, seats):
# return 0 <... | 28.621622 | 103 | 0.537299 | 433 | 3,177 | 3.736721 | 0.212471 | 0.072312 | 0.058714 | 0.013597 | 0.118665 | 0.10136 | 0.021014 | 0 | 0 | 0 | 0 | 0.023188 | 0.348442 | 3,177 | 110 | 104 | 28.881818 | 0.758454 | 0.063582 | 0 | 0.182927 | 0 | 0 | 0.002026 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.170732 | false | 0 | 0.012195 | 0.060976 | 0.353659 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b1770ba8b608be4e3ab9c20fe2c9cb9f117e749 | 1,408 | py | Python | main.py | LucioC/sortable | 4301188933eeec96b7da3f906d80fc35ad154032 | [
"Apache-2.0"
] | null | null | null | main.py | LucioC/sortable | 4301188933eeec96b7da3f906d80fc35ad154032 | [
"Apache-2.0"
] | null | null | null | main.py | LucioC/sortable | 4301188933eeec96b7da3f906d80fc35ad154032 | [
"Apache-2.0"
] | null | null | null | import os
import json
from challenge import FileReader, Product, Listing, MatchSearch
import challenge
reader = FileReader()
search = MatchSearch()
products = reader.read_products('products.txt');
listings = reader.read_listings('listings.txt');
listings = listings[0:1000]
result = search.match_listings(listings, pro... | 22.709677 | 78 | 0.734375 | 211 | 1,408 | 4.7109 | 0.293839 | 0.042254 | 0.027163 | 0.030181 | 0.086519 | 0.060362 | 0.060362 | 0.060362 | 0 | 0 | 0 | 0.004115 | 0.137074 | 1,408 | 61 | 79 | 23.081967 | 0.813992 | 0.010653 | 0 | 0.146341 | 0 | 0 | 0.136265 | 0.036049 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.097561 | 0 | 0.097561 | 0.146341 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b19ff6520a92cbe9bced32400b4df1a8b799dfb | 1,057 | py | Python | Executables/PythonScriptTakingArguments.py | SimioLLC/RunExecutableStep | 377fde62b3ce022a54c7f60d8d1fe70880ce610c | [
"MIT"
] | 2 | 2021-12-12T14:30:51.000Z | 2022-02-08T07:31:50.000Z | Executables/PythonScriptTakingArguments.py | SimioLLC/RunExecutableStep | 377fde62b3ce022a54c7f60d8d1fe70880ce610c | [
"MIT"
] | 2 | 2021-05-20T17:17:11.000Z | 2022-02-09T06:58:22.000Z | Executables/PythonScriptTakingArguments.py | SimioLLC/RunExecutableStep | 377fde62b3ce022a54c7f60d8d1fe70880ce610c | [
"MIT"
] | null | null | null | import sys
import datetime
# Sample program to be initiated by the Simio Step RunExecutable with "Python" ArgumentLogic.
# This runs python scripts with argument convention of: 1st arg is the script name, followed
# by arguments. All args are surrounded with a double-quote.
# The script append-prints the arguments it ... | 30.2 | 93 | 0.639546 | 144 | 1,057 | 4.673611 | 0.5625 | 0.041605 | 0.020802 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.005 | 0.243141 | 1,057 | 34 | 94 | 31.088235 | 0.83625 | 0.321665 | 0 | 0 | 0 | 0 | 0.223629 | 0.091421 | 0 | 0 | 0 | 0 | 0 | 1 | 0.055556 | false | 0 | 0.166667 | 0 | 0.222222 | 0.111111 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b1ca3b503a037398aebee47693ea3fd4611ebf6 | 8,712 | py | Python | app/handlers/gear_handlers.py | lik33v3n/Tower-of-God | 1e6c86939f053739f9e73d56fd1c04d7fb444e8b | [
"MIT"
] | 3 | 2020-06-28T18:04:12.000Z | 2022-02-15T19:46:47.000Z | app/handlers/gear_handlers.py | lik33v3n/Tower-of-God | 1e6c86939f053739f9e73d56fd1c04d7fb444e8b | [
"MIT"
] | null | null | null | app/handlers/gear_handlers.py | lik33v3n/Tower-of-God | 1e6c86939f053739f9e73d56fd1c04d7fb444e8b | [
"MIT"
] | null | null | null | import logging
from contextlib import suppress
from math import fabs
from aiogram.dispatcher import FSMContext
from aiogram.types import CallbackQuery, Message, ReplyKeyboardRemove
from aiogram.utils.exceptions import (MessageToDeleteNotFound,
MessageToEditNotFound)
from app.__ma... | 44.676923 | 184 | 0.609734 | 1,087 | 8,712 | 4.805888 | 0.221711 | 0.038285 | 0.059724 | 0.045559 | 0.453675 | 0.403331 | 0.360452 | 0.312404 | 0.285413 | 0.266271 | 0 | 0.002698 | 0.276745 | 8,712 | 194 | 185 | 44.907216 | 0.82225 | 0.007461 | 0 | 0.343558 | 0 | 0.030675 | 0.152938 | 0.010875 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.07362 | 0 | 0.08589 | 0.006135 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b1d65a917c8c063a1bd09d9e9f6843cb500fb33 | 701 | py | Python | app/project/config.py | caulagi/shakuni | f027810bc72b55da302d6672cd64fdf7c92f1661 | [
"MIT"
] | null | null | null | app/project/config.py | caulagi/shakuni | f027810bc72b55da302d6672cd64fdf7c92f1661 | [
"MIT"
] | null | null | null | app/project/config.py | caulagi/shakuni | f027810bc72b55da302d6672cd64fdf7c92f1661 | [
"MIT"
] | null | null | null | """
project.conf
Configuration module holding all the options
"""
DEBUG = True
import os
BASE_DIR = os.path.abspath(os.path.dirname(__file__))
MONGO_DBNAME = os.environ.get("MONGOHQ_URL") or "mongodb://localhost:27017/shakuni"
THREADS_PER_PAGE = 2
CSRF_ENABLED = True
CSRF_SESSION_KEY = "secret"
SECRET_KEY = "sec... | 21.90625 | 97 | 0.723252 | 90 | 701 | 5.377778 | 0.644444 | 0.090909 | 0.07438 | 0.082645 | 0.095041 | 0 | 0 | 0 | 0 | 0 | 0 | 0.060855 | 0.132668 | 701 | 31 | 98 | 22.612903 | 0.735197 | 0.114123 | 0 | 0 | 0 | 0 | 0.329527 | 0.106036 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.055556 | 0 | 0.055556 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b1e0e175fb077fad4c9db8318a631de85c5f035 | 2,934 | py | Python | Script/train_w2v.py | zrfan/Tencent-Ads-Algo-Comp-2020 | 8b52df4b86b95de581549e61d15a1403f636d530 | [
"MIT"
] | null | null | null | Script/train_w2v.py | zrfan/Tencent-Ads-Algo-Comp-2020 | 8b52df4b86b95de581549e61d15a1403f636d530 | [
"MIT"
] | null | null | null | Script/train_w2v.py | zrfan/Tencent-Ads-Algo-Comp-2020 | 8b52df4b86b95de581549e61d15a1403f636d530 | [
"MIT"
] | 2 | 2020-06-18T05:05:55.000Z | 2020-12-21T06:30:08.000Z | import os
import sys
import numpy as np
import pandas as pd
import logging
import gc
import tqdm
import pickle
import json
import time
import tempfile
from gensim.models import Word2Vec
cwd = os.getcwd()
embed_path = os.path.join(cwd, 'embed_artifact')
# Training corpus for w2v model
corpus_dic = {
'creative': os.p... | 31.212766 | 130 | 0.719496 | 442 | 2,934 | 4.599548 | 0.30543 | 0.035416 | 0.034432 | 0.04427 | 0.182981 | 0.136744 | 0.099361 | 0.042302 | 0.042302 | 0 | 0 | 0.012796 | 0.120995 | 2,934 | 93 | 131 | 31.548387 | 0.775494 | 0.0818 | 0 | 0.058824 | 0 | 0 | 0.183895 | 0.070787 | 0 | 0 | 0 | 0 | 0.029412 | 1 | 0.029412 | false | 0 | 0.176471 | 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 |
3b1f18f1cb1193facb4ab6b88b9e77bb24dc04a6 | 8,632 | py | Python | src/utils.py | huyhoang17/DB_text_minimal | 0d1466889b21cb74a0571a0fb3856902739ea523 | [
"MIT"
] | 30 | 2020-07-20T12:13:27.000Z | 2022-03-08T06:30:31.000Z | src/utils.py | huyhoang17/DB_text_minimal | 0d1466889b21cb74a0571a0fb3856902739ea523 | [
"MIT"
] | 10 | 2020-08-11T10:21:11.000Z | 2022-03-07T15:27:49.000Z | src/utils.py | huyhoang17/DB_text_minimal | 0d1466889b21cb74a0571a0fb3856902739ea523 | [
"MIT"
] | 6 | 2020-09-02T10:58:00.000Z | 2021-08-13T01:43:47.000Z | import os
import gc
import glob
import time
import random
import imageio
import logging
from functools import wraps
import cv2
import numpy as np
import matplotlib.pyplot as plt
import torch
import torchvision.utils as torch_utils
from postprocess import SegDetectorRepresenter
# device = torch.device("cuda" if torch... | 30.394366 | 79 | 0.597544 | 1,197 | 8,632 | 4.086048 | 0.227235 | 0.022899 | 0.020241 | 0.019628 | 0.165406 | 0.114087 | 0.080147 | 0.057248 | 0.044981 | 0.044981 | 0 | 0.02381 | 0.270158 | 8,632 | 283 | 80 | 30.501767 | 0.75254 | 0.052132 | 0 | 0.122066 | 0 | 0 | 0.040541 | 0.003317 | 0 | 0 | 0 | 0 | 0 | 1 | 0.079812 | false | 0 | 0.065728 | 0 | 0.206573 | 0.004695 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b1f289d94d22713713a02c29b3bffd65bfda6e1 | 45,021 | py | Python | example/demos/views.py | bashu/django-uncharted | b285b4dfc8310cb62e7535fb39326916e2c81159 | [
"MIT"
] | 9 | 2015-06-07T06:50:42.000Z | 2020-09-04T05:57:20.000Z | example/demos/views.py | bashu/django-uncharted | b285b4dfc8310cb62e7535fb39326916e2c81159 | [
"MIT"
] | 1 | 2015-09-24T08:17:25.000Z | 2019-03-31T03:51:00.000Z | example/demos/views.py | bashu/django-uncharted | b285b4dfc8310cb62e7535fb39326916e2c81159 | [
"MIT"
] | 2 | 2018-11-13T22:56:05.000Z | 2020-11-18T07:18:49.000Z | # -*- coding: utf-8 -*-
from random import random
from datetime import timedelta
from django.conf import settings
from django.utils import timezone
from django.views.generic import TemplateView
from uncharted.chart import *
class Area100PercentStacked(TemplateView):
template_name = 'area/chart.html'
chart... | 26.420775 | 103 | 0.49046 | 3,629 | 45,021 | 6.049876 | 0.151006 | 0.048007 | 0.022956 | 0.018174 | 0.661581 | 0.631838 | 0.598315 | 0.576452 | 0.551401 | 0.4977 | 0 | 0.053683 | 0.386397 | 45,021 | 1,703 | 104 | 26.436289 | 0.741068 | 0.05051 | 0 | 0.642645 | 0 | 0 | 0.143883 | 0.012346 | 0 | 0 | 0 | 0 | 0 | 1 | 0.014116 | false | 0 | 0.004458 | 0 | 0.064636 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b2534c0418b9126bf14031fac35d279d4d24036 | 2,220 | py | Python | experiment1_meantime.py | mcsosa121/KSRFILS | 75995933771d8338de33cc9bbb5e9416e4242c6b | [
"MIT"
] | null | null | null | experiment1_meantime.py | mcsosa121/KSRFILS | 75995933771d8338de33cc9bbb5e9416e4242c6b | [
"MIT"
] | null | null | null | experiment1_meantime.py | mcsosa121/KSRFILS | 75995933771d8338de33cc9bbb5e9416e4242c6b | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
import time
import numpy
from krypy.linsys import LinearSystem, Cg
from krypy.deflation import DeflatedCg, DeflatedGmres, Ritz
from krypy.utils import Arnoldi, ritz, BoundCG
from krypy.recycling import RecyclingCg
from krypy.recycling.factories import RitzFactory,RitzFactorySimple
from k... | 32.647059 | 93 | 0.644144 | 335 | 2,220 | 4.21194 | 0.307463 | 0.019844 | 0.029766 | 0.054571 | 0.248051 | 0.137491 | 0.109142 | 0.041106 | 0.041106 | 0.041106 | 0 | 0.026286 | 0.211712 | 2,220 | 67 | 94 | 33.134328 | 0.78 | 0.021171 | 0 | 0.206897 | 0 | 0 | 0.055159 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.034483 | false | 0 | 0.155172 | 0 | 0.224138 | 0.051724 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b272c4081ff788cf0e7635f139e4a72c7417fd5 | 3,935 | py | Python | club_crm/api/backend/restaurant.py | VivekChamp/clubcrm | 82036360d867d3dc5406bc71445a98841b5bffbf | [
"MIT"
] | null | null | null | club_crm/api/backend/restaurant.py | VivekChamp/clubcrm | 82036360d867d3dc5406bc71445a98841b5bffbf | [
"MIT"
] | null | null | null | club_crm/api/backend/restaurant.py | VivekChamp/clubcrm | 82036360d867d3dc5406bc71445a98841b5bffbf | [
"MIT"
] | null | null | null | from __future__ import unicode_literals
import frappe
from datetime import datetime, date
from club_crm.club_crm.utils.sms_notification import send_sms
from club_crm.club_crm.utils.push_notification import send_push
from frappe.utils import getdate, get_time, flt
from frappe.utils import escape_html
from frappe import ... | 34.823009 | 148 | 0.581194 | 461 | 3,935 | 4.726681 | 0.177874 | 0.055071 | 0.057825 | 0.061037 | 0.647086 | 0.647086 | 0.625975 | 0.611749 | 0.611749 | 0.594768 | 0 | 0.001452 | 0.300127 | 3,935 | 113 | 149 | 34.823009 | 0.78976 | 0 | 0 | 0.637255 | 0 | 0 | 0.184451 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.029412 | false | 0 | 0.078431 | 0 | 0.107843 | 0.009804 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b28f0284102a05a1095c18ed52c32ed434b06cb | 5,448 | py | Python | keras_vgg_16.py | henniekim/python_keras_vgg_16 | 46f86f8737244cf10155b08eaebe0d5232199215 | [
"MIT"
] | null | null | null | keras_vgg_16.py | henniekim/python_keras_vgg_16 | 46f86f8737244cf10155b08eaebe0d5232199215 | [
"MIT"
] | null | null | null | keras_vgg_16.py | henniekim/python_keras_vgg_16 | 46f86f8737244cf10155b08eaebe0d5232199215 | [
"MIT"
] | null | null | null | from keras.models import Sequential
from keras.layers import Dense, Activation
from keras.layers.pooling import MaxPooling2D
from keras.layers.convolutional import Conv2D
from keras.initializers import he_normal
from keras.initializers import Zeros
from keras.activations import relu
from keras.layers import Flatten
fro... | 34.481013 | 112 | 0.606094 | 684 | 5,448 | 4.692982 | 0.247076 | 0.052336 | 0.056698 | 0.085047 | 0.458255 | 0.445171 | 0.427103 | 0.415265 | 0.415265 | 0.415265 | 0 | 0.038564 | 0.176579 | 5,448 | 157 | 113 | 34.700637 | 0.676995 | 0.147577 | 0 | 0.348837 | 0 | 0 | 0.084691 | 0.027362 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.186047 | 0 | 0.186047 | 0.034884 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b3429811d85f7005761b8ac7ab0e4ba8f27c361 | 10,675 | py | Python | disco/cli/config_time_series.py | NREL/disco | 19afa1c397c6c24e37222f6cbf027eb88833beda | [
"BSD-3-Clause"
] | 2 | 2022-03-11T20:04:34.000Z | 2022-03-14T22:25:29.000Z | disco/cli/config_time_series.py | NREL/disco | 19afa1c397c6c24e37222f6cbf027eb88833beda | [
"BSD-3-Clause"
] | 4 | 2022-03-11T17:48:50.000Z | 2022-03-17T21:39:47.000Z | disco/cli/config_time_series.py | NREL/disco | 19afa1c397c6c24e37222f6cbf027eb88833beda | [
"BSD-3-Clause"
] | null | null | null | #!/usr/bin/env python
"""Creates JADE configuration for stage 1 of pydss_simulation pipeline."""
import logging
import sys
import click
from jade.common import CONFIG_FILE
from jade.loggers import setup_logging
from jade.utils.utils import load_data
from PyDSS.reports.pv_reports import PF1_SCENARIO, CONTROL_MODE_SC... | 34.214744 | 102 | 0.662857 | 1,301 | 10,675 | 5.240584 | 0.177556 | 0.035494 | 0.039601 | 0.050161 | 0.38897 | 0.331769 | 0.262834 | 0.246113 | 0.231153 | 0.213259 | 0 | 0.003049 | 0.231944 | 10,675 | 311 | 103 | 34.324759 | 0.828516 | 0.019953 | 0 | 0.369718 | 0 | 0 | 0.27378 | 0.03445 | 0 | 0 | 0 | 0 | 0.003521 | 1 | 0.010563 | false | 0 | 0.042254 | 0 | 0.06338 | 0.003521 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b36647274e28645db368fe1412571e540dc57c9 | 1,919 | py | Python | vcfp_attack/trainByBayes.py | kenneds6/VCFingerprinting | 2de88766e2b2beeed44a4267c370fe755b5db90d | [
"MIT"
] | null | null | null | vcfp_attack/trainByBayes.py | kenneds6/VCFingerprinting | 2de88766e2b2beeed44a4267c370fe755b5db90d | [
"MIT"
] | null | null | null | vcfp_attack/trainByBayes.py | kenneds6/VCFingerprinting | 2de88766e2b2beeed44a4267c370fe755b5db90d | [
"MIT"
] | null | null | null | #!/usr/bin/python
import os
import sys
import sklearn
from sklearn.naive_bayes import GaussianNB
from sklearn.externals import joblib
import argparse
import numpy as np
import fileUtils
import tools
def saveModel(modelData, fpath):
joblib.dump(modelData, fpath)
def readfile(fpath):
tmpList = []
for li... | 24.922078 | 81 | 0.682126 | 224 | 1,919 | 5.767857 | 0.441964 | 0.049536 | 0.058824 | 0.037152 | 0.041796 | 0 | 0 | 0 | 0 | 0 | 0 | 0.008525 | 0.205315 | 1,919 | 76 | 82 | 25.25 | 0.838689 | 0.008338 | 0 | 0 | 0 | 0 | 0.055731 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.127273 | false | 0 | 0.163636 | 0 | 0.381818 | 0.018182 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b3666930d6995caea754b79c0c21bae3db8e9e7 | 2,472 | py | Python | hosting-scripts/leaseweb_invoices.py | sromanenko/hand-tools | 50be74f07c8f8f6bb89e6470c4370c62c2fbc2e0 | [
"MIT"
] | null | null | null | hosting-scripts/leaseweb_invoices.py | sromanenko/hand-tools | 50be74f07c8f8f6bb89e6470c4370c62c2fbc2e0 | [
"MIT"
] | null | null | null | hosting-scripts/leaseweb_invoices.py | sromanenko/hand-tools | 50be74f07c8f8f6bb89e6470c4370c62c2fbc2e0 | [
"MIT"
] | 1 | 2020-10-05T08:11:13.000Z | 2020-10-05T08:11:13.000Z | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
import requests
import gspread
import config
from oauth2client.service_account import ServiceAccountCredentials as Account
api_url = 'https://api.leaseweb.com/invoices/v1/invoices'
def api_request(url, headers, params=None):
try:
conn = requests.get(url=url... | 28.413793 | 77 | 0.637136 | 276 | 2,472 | 5.528986 | 0.413043 | 0.019659 | 0.039318 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.003729 | 0.240696 | 2,472 | 86 | 78 | 28.744186 | 0.80927 | 0.053803 | 0 | 0 | 0 | 0 | 0.157308 | 0.010287 | 0 | 0 | 0 | 0 | 0 | 1 | 0.045455 | false | 0 | 0.060606 | 0 | 0.136364 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b377d3baccb78698043aba61e68c933edadec23 | 2,499 | py | Python | scrapy_ddiy/utils/common.py | LZC6244/scrapy_ddiy | 1bf7cdd382afd471af0bf7069b377fb364dc4730 | [
"MIT"
] | 9 | 2021-05-17T02:55:16.000Z | 2022-03-28T08:36:50.000Z | scrapy_ddiy/utils/common.py | LZC6244/scrapy_ddiy | 1bf7cdd382afd471af0bf7069b377fb364dc4730 | [
"MIT"
] | null | null | null | scrapy_ddiy/utils/common.py | LZC6244/scrapy_ddiy | 1bf7cdd382afd471af0bf7069b377fb364dc4730 | [
"MIT"
] | 1 | 2022-01-23T06:28:31.000Z | 2022-01-23T06:28:31.000Z | # -*- coding: utf-8 -*-
import ast
import redis
import socket
import hashlib
import pymongo
from scrapy import Request
from w3lib.url import canonicalize_url
from scrapy.utils.python import to_bytes
def get_str_md5(string: str, encoding='utf-8'):
"""
计算字符串的 MD5 值
:param string:
:param encoding:
:r... | 27.163043 | 113 | 0.612245 | 343 | 2,499 | 4.294461 | 0.373178 | 0.032587 | 0.032587 | 0.027155 | 0.100475 | 0.082824 | 0.046164 | 0.046164 | 0 | 0 | 0 | 0.021843 | 0.2489 | 2,499 | 91 | 114 | 27.461538 | 0.76292 | 0.130452 | 0 | 0.070175 | 0 | 0 | 0.117139 | 0 | 0 | 0 | 0 | 0 | 0.017544 | 1 | 0.122807 | false | 0.017544 | 0.140351 | 0 | 0.385965 | 0.017544 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b380e0ffaac00c93adb248541f24f62ceacc3dd | 7,392 | py | Python | src/ctc/toolbox/amm_utils/cpmm/cpmm_trade.py | fei-protocol/checkthechain | ec838f3d0d44af228f45394d9ba8d8eb7f677520 | [
"MIT"
] | 94 | 2022-02-15T19:34:49.000Z | 2022-03-26T19:26:22.000Z | src/ctc/toolbox/amm_utils/cpmm/cpmm_trade.py | fei-protocol/checkthechain | ec838f3d0d44af228f45394d9ba8d8eb7f677520 | [
"MIT"
] | 7 | 2022-03-03T02:58:47.000Z | 2022-03-11T18:41:05.000Z | src/ctc/toolbox/amm_utils/cpmm/cpmm_trade.py | fei-protocol/checkthechain | ec838f3d0d44af228f45394d9ba8d8eb7f677520 | [
"MIT"
] | 7 | 2022-02-15T17:53:07.000Z | 2022-03-17T19:14:17.000Z | from __future__ import annotations
import decimal
from ctc.toolbox import validate_utils
from . import cpmm_spec
def trade(
x_reserves: int | float,
y_reserves: int | float,
x_sold: int | float | None = None,
x_bought: int | float | None = None,
y_sold: int | float | None = None,
y_bought: i... | 28.875 | 80 | 0.597673 | 1,055 | 7,392 | 3.835071 | 0.117536 | 0.102323 | 0.092437 | 0.0435 | 0.635195 | 0.522986 | 0.486159 | 0.47306 | 0.430796 | 0.361592 | 0 | 0.008578 | 0.321834 | 7,392 | 255 | 81 | 28.988235 | 0.798524 | 0.135281 | 0 | 0.484375 | 0 | 0 | 0.035277 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.03125 | false | 0 | 0.020833 | 0 | 0.104167 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b39d14aa460ee7aad9a34f8b5f86ea2f7ba1e12 | 5,144 | py | Python | main_simV4.py | iexarchos/motion_imitation | ea9004f77405c8eb1e8a53650dffa723f86018d9 | [
"Apache-2.0"
] | null | null | null | main_simV4.py | iexarchos/motion_imitation | ea9004f77405c8eb1e8a53650dffa723f86018d9 | [
"Apache-2.0"
] | null | null | null | main_simV4.py | iexarchos/motion_imitation | ea9004f77405c8eb1e8a53650dffa723f86018d9 | [
"Apache-2.0"
] | null | null | null | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Mon Apr 6 14:09:05 2020
@author: yannis
"""
import torch
import random
from pdb import set_trace as bp
from a2c_ppo_acktr.envs import make_vec_envs
from a2c_ppo_acktr.utils import get_vec_normalize
import motion_imitation
import time
import numpy as np
... | 32.974359 | 137 | 0.565708 | 639 | 5,144 | 4.380282 | 0.226917 | 0.051447 | 0.022508 | 0.050018 | 0.674884 | 0.64916 | 0.628796 | 0.591997 | 0.591997 | 0.591997 | 0 | 0.024307 | 0.320179 | 5,144 | 156 | 138 | 32.974359 | 0.776094 | 0.141719 | 0 | 0.564815 | 0 | 0 | 0.056316 | 0.018696 | 0 | 0 | 0 | 0 | 0 | 1 | 0.009259 | false | 0 | 0.074074 | 0 | 0.083333 | 0.046296 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b40b53be905051fc29376c809a528f0f56e00ed | 3,747 | py | Python | distribution/src/assembly/test/test.py | aliyun/alibabacloud-maxcompute-tool-migrate | 22ba9d36c0fe9b79b3d91766a22ec43372b6c540 | [
"Apache-2.0"
] | 19 | 2019-12-17T10:00:59.000Z | 2022-03-20T03:20:42.000Z | distribution/src/assembly/test/test.py | aliyun/alibabacloud-maxcompute-tool-migrate | 22ba9d36c0fe9b79b3d91766a22ec43372b6c540 | [
"Apache-2.0"
] | 73 | 2020-08-13T10:40:16.000Z | 2022-03-21T06:57:36.000Z | distribution/src/assembly/test/test.py | aliyun/alibabacloud-maxcompute-tool-migrate | 22ba9d36c0fe9b79b3d91766a22ec43372b6c540 | [
"Apache-2.0"
] | 6 | 2020-08-13T10:42:21.000Z | 2022-01-13T04:04:24.000Z | #
# Copyright 1999-2021 Alibaba Group Holding 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... | 30.966942 | 76 | 0.631705 | 490 | 3,747 | 4.640816 | 0.340816 | 0.036939 | 0.038698 | 0.028144 | 0.216799 | 0.152595 | 0.129288 | 0.108179 | 0.047493 | 0.047493 | 0 | 0.008065 | 0.271951 | 3,747 | 120 | 77 | 31.225 | 0.825513 | 0.152655 | 0 | 0.235955 | 0 | 0 | 0.144124 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.011236 | false | 0 | 0.089888 | 0 | 0.11236 | 0.05618 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b429026656499e942a38341d6e198b9bfc94595 | 1,740 | py | Python | src/muses/search_index/documents/helpers.py | Aincient/cleo | 933ef372fa7847d943206d72bfb03c201dbafbd6 | [
"Apache-2.0"
] | null | null | null | src/muses/search_index/documents/helpers.py | Aincient/cleo | 933ef372fa7847d943206d72bfb03c201dbafbd6 | [
"Apache-2.0"
] | null | null | null | src/muses/search_index/documents/helpers.py | Aincient/cleo | 933ef372fa7847d943206d72bfb03c201dbafbd6 | [
"Apache-2.0"
] | 3 | 2018-10-01T12:04:36.000Z | 2021-01-07T09:30:50.000Z | import csv
import logging
__all__ = (
'read_synonyms',
)
LOGGER = logging.getLogger(__name__)
def read_synonyms(path):
"""Read synonyms.
Read synonyms from the following format:
word_id;preferred_EN;variant1;variant2;variant3;variant4;variant5
1;Anatolia;anatolia;anatolie;anatolien;;
... | 28.064516 | 75 | 0.543678 | 191 | 1,740 | 4.832461 | 0.513089 | 0.052004 | 0.04117 | 0.03467 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.01444 | 0.363218 | 1,740 | 61 | 76 | 28.52459 | 0.818592 | 0.402299 | 0 | 0.068966 | 0 | 0 | 0.072016 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.034483 | false | 0 | 0.068966 | 0 | 0.137931 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b46710ce31a8de493b043c80a7fb418b77deda4 | 5,503 | py | Python | GxbManager.py | moonmagian/GxbManager | fb6c31ce6b53f049ca1b40129e57ab04189d1a28 | [
"MIT"
] | 3 | 2018-08-31T07:33:12.000Z | 2019-06-10T14:21:38.000Z | GxbManager.py | moonmagian/GxbManager | fb6c31ce6b53f049ca1b40129e57ab04189d1a28 | [
"MIT"
] | null | null | null | GxbManager.py | moonmagian/GxbManager | fb6c31ce6b53f049ca1b40129e57ab04189d1a28 | [
"MIT"
] | 2 | 2018-08-20T14:45:11.000Z | 2018-08-24T09:12:47.000Z | from selenium import webdriver
import selenium
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
from selenium.webdriver.common.by import By
from selenium.common.exceptions import TimeoutException
import re
STATUS_OUTPUT = \
'''Video: {0}
Status... | 32.952096 | 105 | 0.652008 | 662 | 5,503 | 5.294562 | 0.256798 | 0.03709 | 0.031384 | 0.054208 | 0.374893 | 0.269615 | 0.103281 | 0.085021 | 0.085021 | 0.085021 | 0 | 0.007136 | 0.236053 | 5,503 | 166 | 106 | 33.150602 | 0.826594 | 0.133745 | 0 | 0.318966 | 0 | 0.017241 | 0.094527 | 0.004759 | 0 | 0 | 0 | 0.006024 | 0 | 1 | 0.077586 | false | 0.025862 | 0.060345 | 0 | 0.344828 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b46ed8634fc704f45f15531d6f71a175564ad9b | 16,090 | py | Python | statey/fsm.py | cfeenstra67/statey | 6d127ed48265e2e072fbb26486458a4b28a333ec | [
"MIT"
] | 4 | 2021-02-16T19:34:38.000Z | 2022-01-31T16:44:14.000Z | statey/fsm.py | cfeenstra67/statey | 6d127ed48265e2e072fbb26486458a4b28a333ec | [
"MIT"
] | null | null | null | statey/fsm.py | cfeenstra67/statey | 6d127ed48265e2e072fbb26486458a4b28a333ec | [
"MIT"
] | null | null | null | import abc
import dataclasses as dc
import enum
import types as pytypes
from collections import Counter
from functools import wraps, partial
from typing import Sequence, Callable, Type as PyType, Dict, Any, Optional
import networkx as nx
import statey as st
from statey import resource, task, exc
from statey.provider ... | 32.374245 | 97 | 0.636482 | 1,810 | 16,090 | 5.541436 | 0.156354 | 0.021535 | 0.053041 | 0.044666 | 0.325723 | 0.278265 | 0.233699 | 0.223729 | 0.198903 | 0.190628 | 0 | 0.000771 | 0.274332 | 16,090 | 496 | 98 | 32.439516 | 0.858256 | 0.137415 | 0 | 0.386986 | 0 | 0 | 0.041133 | 0.001828 | 0 | 0 | 0 | 0 | 0 | 1 | 0.041096 | false | 0 | 0.044521 | 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 |
3b4761fe2b3dfb5179be295baf3be2ef36b02d3e | 2,555 | py | Python | aicup-python/model/unit.py | arijitgupta42/RAIC-2019 | e17828a4a6ac7990fe340b56276378be2297397f | [
"MIT"
] | null | null | null | aicup-python/model/unit.py | arijitgupta42/RAIC-2019 | e17828a4a6ac7990fe340b56276378be2297397f | [
"MIT"
] | null | null | null | aicup-python/model/unit.py | arijitgupta42/RAIC-2019 | e17828a4a6ac7990fe340b56276378be2297397f | [
"MIT"
] | null | null | null | from .vec2_double import Vec2Double
from .vec2_double import Vec2Double
from .jump_state import JumpState
from .weapon import Weapon
class Unit:
def __init__(self, player_id, id, health, position, size, jump_state, walked_right, stand, on_ground, on_ladder, mines, weapon):
self.player_id = player_id
... | 37.028986 | 132 | 0.585127 | 305 | 2,555 | 4.655738 | 0.134426 | 0.073239 | 0.06338 | 0.050704 | 0.215493 | 0.157746 | 0.112676 | 0.112676 | 0.112676 | 0.112676 | 0 | 0.003359 | 0.300978 | 2,555 | 68 | 133 | 37.573529 | 0.791713 | 0 | 0 | 0.058824 | 0 | 0 | 0.006654 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.058824 | false | 0 | 0.058824 | 0.014706 | 0.161765 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b4832ce003abf03eb474b13d67edabb8d78412f | 305 | py | Python | Python3/Lucky Numbers in a Matrix.py | olma2077/LeetCode | 6a229ae23c5a211bc44de51178ced5bef6a44233 | [
"MIT"
] | 1 | 2020-04-12T09:34:52.000Z | 2020-04-12T09:34:52.000Z | Python3/Lucky Numbers in a Matrix.py | olma2077/LeetCode | 6a229ae23c5a211bc44de51178ced5bef6a44233 | [
"MIT"
] | null | null | null | Python3/Lucky Numbers in a Matrix.py | olma2077/LeetCode | 6a229ae23c5a211bc44de51178ced5bef6a44233 | [
"MIT"
] | null | null | null | class Solution:
def luckyNumbers (self, matrix: List[List[int]]) -> List[int]:
nums = []
for row in matrix:
num = min(row)
i = row.index(num)
if num == max([line[i] for line in matrix]):
nums.append(num)
return nums
| 27.727273 | 66 | 0.478689 | 37 | 305 | 3.945946 | 0.567568 | 0.09589 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.4 | 305 | 10 | 67 | 30.5 | 0.797814 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.111111 | false | 0 | 0 | 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 |
3b4a40f899a77b427cfbccdfdad28f929fa2fc9b | 10,008 | py | Python | modules/jwtoken/handlers/jwtokenhandler.py | umbros/spid-sp-sapspid | 5546aeb2bc968d26537732af8e7aee52d1896e99 | [
"MIT"
] | 6 | 2017-09-30T11:10:22.000Z | 2022-02-04T19:42:28.000Z | modules/jwtoken/handlers/jwtokenhandler.py | umbros/spid-sp-sapspid | 5546aeb2bc968d26537732af8e7aee52d1896e99 | [
"MIT"
] | 4 | 2019-01-30T13:38:42.000Z | 2021-03-28T14:51:31.000Z | modules/jwtoken/handlers/jwtokenhandler.py | umbros/spid-sp-sapspid | 5546aeb2bc968d26537732af8e7aee52d1896e99 | [
"MIT"
] | 4 | 2017-10-06T14:17:50.000Z | 2021-02-18T08:38:19.000Z | from response import ResponseObj
from response import RequestHandler
from request import RequestObjNew
import tornado.web
import traceback
import tornado.gen
import tornado.ioloop
import tornado.concurrent
import logging
from lib.customException import ApplicationException
import globalsObj
import re
import jwtoken.li... | 42.769231 | 135 | 0.611511 | 1,066 | 10,008 | 5.54409 | 0.192308 | 0.096785 | 0.052115 | 0.045685 | 0.575973 | 0.528934 | 0.469543 | 0.439763 | 0.432995 | 0.366328 | 0 | 0.012691 | 0.275679 | 10,008 | 233 | 136 | 42.95279 | 0.802593 | 0.085731 | 0 | 0.378882 | 0 | 0 | 0.109483 | 0.008701 | 0 | 0 | 0 | 0 | 0 | 1 | 0.049689 | false | 0 | 0.086957 | 0 | 0.167702 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b56c27371d7864fd9724c051669c52b7b5c54a4 | 1,796 | py | Python | humans.py | AlexTaguchi/image-segmentation | a0cff755d5b6478bb70e30c623fb62a676cc851a | [
"MIT"
] | null | null | null | humans.py | AlexTaguchi/image-segmentation | a0cff755d5b6478bb70e30c623fb62a676cc851a | [
"MIT"
] | null | null | null | humans.py | AlexTaguchi/image-segmentation | a0cff755d5b6478bb70e30c623fb62a676cc851a | [
"MIT"
] | null | null | null | # Real-time human segmentation with a web camera
# Modules
import cv2
import matplotlib.pyplot as plt
import numpy as np
from PIL import Image
import time
import torch
from torchvision import transforms
# Use GPU if available
device = 'cuda' if torch.cuda.is_available() else 'cpu'
# Load Pretrained DeepLabV3
model =... | 26.411765 | 87 | 0.678174 | 246 | 1,796 | 4.926829 | 0.463415 | 0.049505 | 0.033003 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.046994 | 0.194321 | 1,796 | 67 | 88 | 26.80597 | 0.790601 | 0.242762 | 0 | 0 | 0 | 0 | 0.049144 | 0.015637 | 0 | 0 | 0.002978 | 0 | 0 | 1 | 0 | false | 0 | 0.194444 | 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 |
3b579891ec54a7eaab385d732105f141cf6b521b | 2,276 | py | Python | telesignenterprise/telebureau.py | Coffee-Meets-Bagel/python_telesign_enterprise | 7a9fbed581967c4c2fb9f9d3c1f8853dd67df58d | [
"MIT"
] | 3 | 2021-06-04T22:55:49.000Z | 2021-12-29T00:21:00.000Z | telesignenterprise/telebureau.py | Coffee-Meets-Bagel/python_telesign_enterprise | 7a9fbed581967c4c2fb9f9d3c1f8853dd67df58d | [
"MIT"
] | 2 | 2019-10-30T20:04:51.000Z | 2022-01-04T09:26:18.000Z | telesignenterprise/telebureau.py | Coffee-Meets-Bagel/python_telesign_enterprise | 7a9fbed581967c4c2fb9f9d3c1f8853dd67df58d | [
"MIT"
] | 1 | 2021-07-23T23:34:15.000Z | 2021-07-23T23:34:15.000Z | from __future__ import unicode_literals
from telesign.rest import RestClient
TELEBUREAU_CREATE_RESOURCE = "/v1/telebureau/event"
TELEBUREAU_RETRIEVE_RESOURCE = "/v1/telebureau/event/{reference_id}"
TELEBUREAU_DELETE_RESOURCE = "/v1/telebureau/event/{reference_id}"
class TelebureauClient(RestClient):
"""
Tel... | 44.627451 | 119 | 0.692882 | 268 | 2,276 | 5.690299 | 0.373134 | 0.057705 | 0.04459 | 0.04918 | 0.449836 | 0.415738 | 0.331803 | 0.276721 | 0.276721 | 0.276721 | 0 | 0.001711 | 0.229789 | 2,276 | 50 | 120 | 45.52 | 0.868226 | 0.405536 | 0 | 0.15 | 0 | 0 | 0.096721 | 0.057377 | 0 | 0 | 0 | 0 | 0 | 1 | 0.2 | false | 0 | 0.1 | 0 | 0.5 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b590c3afdc8778783a821b7e7abd8d729518eda | 6,099 | py | Python | old_combine_chrX.py | nikbaya/chrX | 9d7859c60ecf35a5db13b973a7d2e44472a08ca6 | [
"MIT"
] | null | null | null | old_combine_chrX.py | nikbaya/chrX | 9d7859c60ecf35a5db13b973a7d2e44472a08ca6 | [
"MIT"
] | null | null | null | old_combine_chrX.py | nikbaya/chrX | 9d7859c60ecf35a5db13b973a7d2e44472a08ca6 | [
"MIT"
] | null | null | null | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Tue Jul 24 11:26:20 2018
@author: nbaya
"""
import os
import glob
import re
import pandas as pd
from subprocess import call
from joblib import Parallel, delayed
import multiprocessing
import sys
import numpy as np
v3_path = "/Users/nbaya/Documents/lab/u... | 42.950704 | 178 | 0.61174 | 846 | 6,099 | 4.281324 | 0.251773 | 0.022363 | 0.039757 | 0.029818 | 0.66317 | 0.638874 | 0.575097 | 0.525953 | 0.490061 | 0.466041 | 0 | 0.029395 | 0.135432 | 6,099 | 141 | 179 | 43.255319 | 0.6575 | 0.477947 | 0 | 0.333333 | 0 | 0 | 0.215693 | 0.091379 | 0 | 0 | 0 | 0 | 0 | 1 | 0.020833 | false | 0 | 0.1875 | 0 | 0.208333 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b5cff844879ff6c055ff9188fef15716ede158b | 315 | py | Python | 0x03-python-data_structures/10-divisible_by_2.py | oluwaseun-ebenezer/holbertonschool-higher_level_programming | e830f969d3ca71abf0a2f6d4f7c64a82337eccd7 | [
"MIT"
] | null | null | null | 0x03-python-data_structures/10-divisible_by_2.py | oluwaseun-ebenezer/holbertonschool-higher_level_programming | e830f969d3ca71abf0a2f6d4f7c64a82337eccd7 | [
"MIT"
] | null | null | null | 0x03-python-data_structures/10-divisible_by_2.py | oluwaseun-ebenezer/holbertonschool-higher_level_programming | e830f969d3ca71abf0a2f6d4f7c64a82337eccd7 | [
"MIT"
] | null | null | null | #!/usr/bin/python3
# 10-divisible_by_2.py
def divisible_by_2(my_list=[]):
"""Find all multiples of 2 in a list."""
multiples = []
for i in range(len(my_list)):
if my_list[i] % 2 == 0:
multiples.append(True)
else:
multiples.append(False)
return (multiples)
| 21 | 44 | 0.574603 | 45 | 315 | 3.866667 | 0.622222 | 0.103448 | 0.137931 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.035556 | 0.285714 | 315 | 14 | 45 | 22.5 | 0.737778 | 0.231746 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.125 | false | 0 | 0 | 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 |
3b5e8dad9b7d75c51ac3e7b6542b8df80237881b | 5,045 | py | Python | catalyst_utils/views/api.py | uw-it-aca/catalyst-utils | 8f529758098021a76c28caa71f78a4b2d3232c1a | [
"Apache-2.0"
] | null | null | null | catalyst_utils/views/api.py | uw-it-aca/catalyst-utils | 8f529758098021a76c28caa71f78a4b2d3232c1a | [
"Apache-2.0"
] | 107 | 2021-11-10T01:13:22.000Z | 2022-03-31T18:07:49.000Z | catalyst_utils/views/api.py | uw-it-aca/catalyst-utils | 8f529758098021a76c28caa71f78a4b2d3232c1a | [
"Apache-2.0"
] | null | null | null | # Copyright 2022 UW-IT, University of Washington
# SPDX-License-Identifier: Apache-2.0
from django.http import HttpResponse
from django.views import View
from django.utils.decorators import method_decorator
from django.contrib.auth.decorators import login_required
from django.core.exceptions import ObjectDoesNotExist
... | 36.294964 | 78 | 0.619425 | 540 | 5,045 | 5.607407 | 0.244444 | 0.042933 | 0.029723 | 0.031704 | 0.438243 | 0.415786 | 0.376156 | 0.331242 | 0.296235 | 0.227543 | 0 | 0.009967 | 0.284044 | 5,045 | 138 | 79 | 36.557971 | 0.82835 | 0.016254 | 0 | 0.311927 | 0 | 0 | 0.069355 | 0.004839 | 0 | 0 | 0 | 0 | 0 | 1 | 0.082569 | false | 0 | 0.100917 | 0.018349 | 0.385321 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b5f835cc06515c390b13c5d1221de5dc5ebb27d | 784 | py | Python | examples/longify.py | hmckenzie/tea-lang | d88d63ea600c387d086d19bcb0c9ae54cc78cb68 | [
"Apache-2.0"
] | null | null | null | examples/longify.py | hmckenzie/tea-lang | d88d63ea600c387d086d19bcb0c9ae54cc78cb68 | [
"Apache-2.0"
] | null | null | null | examples/longify.py | hmckenzie/tea-lang | d88d63ea600c387d086d19bcb0c9ae54cc78cb68 | [
"Apache-2.0"
] | null | null | null | '''
Author: Eunice Jun (@emjun)
Date created: November, 4, 2019
Purpose: Transform a wide format dataset into long format
Use: python3 longify.py <data_in_wide_format.csv>
'''
import sys
import csv
import pandas as pd
if __name__ == "__main__":
if len(sys.argv) != 2:
print("Misusing script. Must include... | 29.037037 | 114 | 0.640306 | 118 | 784 | 4.016949 | 0.576271 | 0.063291 | 0.067511 | 0.084388 | 0.147679 | 0.147679 | 0.147679 | 0.147679 | 0 | 0 | 0 | 0.016694 | 0.235969 | 784 | 26 | 115 | 30.153846 | 0.774624 | 0.304847 | 0 | 0 | 0 | 0 | 0.274766 | 0.046729 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.266667 | 0 | 0.266667 | 0.133333 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b607bc698224eb54df1cdcf13257fe7d16f4a93 | 2,241 | py | Python | akhelpers/Resnet_AK.py | sahilparekh/autokeras-models | 237b9900fbe83ef8f9882b257f01986289647797 | [
"MIT"
] | null | null | null | akhelpers/Resnet_AK.py | sahilparekh/autokeras-models | 237b9900fbe83ef8f9882b257f01986289647797 | [
"MIT"
] | null | null | null | akhelpers/Resnet_AK.py | sahilparekh/autokeras-models | 237b9900fbe83ef8f9882b257f01986289647797 | [
"MIT"
] | null | null | null | import autokeras as ak
from tensorflow.python.util import nest
from tf2cv.models.resnet import ResNet
LAYER_OPTIONS = [[1, 1, 1, 1], [2, 1, 1, 1], [2, 2, 1, 1], [2, 2, 2, 1], [2, 2, 2, 2], [3, 3, 3, 3],
[3, 4, 6, 3]]
class CustomResnetBlock(ak.Block):
def __init__(self, in_size=(224, 22... | 36.737705 | 106 | 0.599732 | 303 | 2,241 | 4.194719 | 0.336634 | 0.009441 | 0.080252 | 0.059009 | 0.040913 | 0 | 0 | 0 | 0 | 0 | 0 | 0.047438 | 0.294511 | 2,241 | 60 | 107 | 37.35 | 0.756483 | 0.039714 | 0 | 0 | 0 | 0 | 0.015836 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.046512 | false | 0 | 0.069767 | 0 | 0.162791 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b60d399770654bd26d7c840b7fc93de1223aa09 | 766 | py | Python | Codes/data_convertor/change_text_labels.py | AmiirGholamii/semantic-segmentation | 16426afdcf9ef2449d5bc3cb86ca1c269e517dab | [
"MIT"
] | 2 | 2021-05-14T07:44:24.000Z | 2021-05-19T04:48:03.000Z | Codes/data_convertor/change_text_labels.py | AmiirGholamii/semantic-segmentation | 16426afdcf9ef2449d5bc3cb86ca1c269e517dab | [
"MIT"
] | null | null | null | Codes/data_convertor/change_text_labels.py | AmiirGholamii/semantic-segmentation | 16426afdcf9ef2449d5bc3cb86ca1c269e517dab | [
"MIT"
] | null | null | null | import os
import cv2
import numpy as np
directory = "/home/rider/DataSets/Images/Development/humanoid_soccer_dataset/ScreenshotMasks"
for filename in os.listdir(directory):
if filename.endswith(".txt"):
blank_image = np.zeros((480,640), np.uint8)
with open(os.path.join(directory, filename)) as f:
... | 38.3 | 93 | 0.614883 | 98 | 766 | 4.72449 | 0.530612 | 0.064795 | 0.064795 | 0.12311 | 0.174946 | 0 | 0 | 0 | 0 | 0 | 0 | 0.020979 | 0.253264 | 766 | 19 | 94 | 40.315789 | 0.788462 | 0.052219 | 0 | 0.111111 | 0 | 0 | 0.127072 | 0.109116 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.166667 | 0 | 0.166667 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b63d4b72d8214c1ed9a2a8335427946263ee241 | 3,524 | py | Python | src/python/serif/theory/serif_entity_theory.py | BBN-E/text-open | c508f6caeaa51a43cdb0bc27d8ed77e5750fdda9 | [
"Apache-2.0"
] | 2 | 2022-03-24T14:37:51.000Z | 2022-03-24T19:56:45.000Z | src/python/serif/theory/serif_entity_theory.py | BBN-E/text-open | c508f6caeaa51a43cdb0bc27d8ed77e5750fdda9 | [
"Apache-2.0"
] | null | null | null | src/python/serif/theory/serif_entity_theory.py | BBN-E/text-open | c508f6caeaa51a43cdb0bc27d8ed77e5750fdda9 | [
"Apache-2.0"
] | null | null | null | import sys, os
from serif.theory.serif_theory import SerifTheory
from serif.theory.enumerated_type import MentionType
from serif.util.serifxml_utils import CountryIdentifier
class SerifEntityTheory(SerifTheory):
def num_mentions(self):
"""Returns the number or mentions in this Entity"""
return l... | 37.094737 | 77 | 0.619467 | 417 | 3,524 | 5.069544 | 0.215827 | 0.062441 | 0.071902 | 0.045412 | 0.352412 | 0.326869 | 0.32403 | 0.260643 | 0.260643 | 0.173132 | 0 | 0.000838 | 0.322928 | 3,524 | 94 | 78 | 37.489362 | 0.885163 | 0.200908 | 0 | 0.276923 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.107692 | false | 0 | 0.061538 | 0 | 0.430769 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b64d23b87d1099b18fa084331257778ef9465f0 | 1,655 | py | Python | scripts/bing-images-downloader.py | ZZY2357/auto-workflow | bea6f0c67da524fd08cbf282ea72d821f8d1c9ea | [
"MIT"
] | null | null | null | scripts/bing-images-downloader.py | ZZY2357/auto-workflow | bea6f0c67da524fd08cbf282ea72d821f8d1c9ea | [
"MIT"
] | null | null | null | scripts/bing-images-downloader.py | ZZY2357/auto-workflow | bea6f0c67da524fd08cbf282ea72d821f8d1c9ea | [
"MIT"
] | null | null | null | #!/usr/bin/env python3
import requests
from bs4 import BeautifulSoup
import os
import base64
keyword = input('What do you want? ')
save_floder = input('Where do you want to save images?(Default as the current directory) ')
if save_floder == '': save_floder = os.getcwd()
if not os.path.exists(save_floder): os.mkdir(sa... | 34.479167 | 135 | 0.647734 | 248 | 1,655 | 4.197581 | 0.46371 | 0.067243 | 0.04611 | 0.028818 | 0.12488 | 0.12488 | 0.082613 | 0.082613 | 0.082613 | 0.082613 | 0 | 0.034763 | 0.183082 | 1,655 | 47 | 136 | 35.212766 | 0.735207 | 0.128097 | 0 | 0 | 0 | 0.057143 | 0.323141 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.114286 | 0 | 0.114286 | 0.114286 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b6ac29e4ec13d34dbb79b65c428b5255729e775 | 7,313 | py | Python | webex_adaptive_card.py | oborys/webex_card_bot | 823a2a1eca356a5f9e2a1158209c6ce8f715a5cf | [
"MIT"
] | null | null | null | webex_adaptive_card.py | oborys/webex_card_bot | 823a2a1eca356a5f9e2a1158209c6ce8f715a5cf | [
"MIT"
] | null | null | null | webex_adaptive_card.py | oborys/webex_card_bot | 823a2a1eca356a5f9e2a1158209c6ce8f715a5cf | [
"MIT"
] | null | null | null | from flask import Flask, request
import requests
import json
import configparser
from api_interaction import *
# read variables from config
credential = configparser.ConfigParser()
credential.read('cred.prod')
# Import credential
bearer_bot = credential['Webex']['WEBEX_TEAMS_TOKEN']
botEmail = credential['Webex']['... | 41.551136 | 188 | 0.633803 | 812 | 7,313 | 5.615764 | 0.25 | 0.023684 | 0.041009 | 0.045833 | 0.378289 | 0.301754 | 0.294298 | 0.237281 | 0.182895 | 0.182895 | 0 | 0.007756 | 0.224258 | 7,313 | 176 | 189 | 41.551136 | 0.796051 | 0.051142 | 0 | 0.15493 | 0 | 0.014085 | 0.267109 | 0.026567 | 0.007042 | 0 | 0 | 0 | 0 | 1 | 0.070423 | false | 0.007042 | 0.035211 | 0 | 0.147887 | 0.084507 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b6b9817cbd176268a7a34bd88ce4df0849e1e97 | 798 | py | Python | library/ftx/asyncronous/account.py | danyanyam/ftx | 32076bc1135e5a1e2bc800f4fff8dff9d7da18f1 | [
"MIT"
] | 2 | 2021-09-23T22:59:24.000Z | 2021-09-24T05:49:35.000Z | library/ftx/asyncronous/account.py | danyanyam/ftx | 32076bc1135e5a1e2bc800f4fff8dff9d7da18f1 | [
"MIT"
] | null | null | null | library/ftx/asyncronous/account.py | danyanyam/ftx | 32076bc1135e5a1e2bc800f4fff8dff9d7da18f1 | [
"MIT"
] | null | null | null | from library.ftx.base import AsyncBaseApiClass
class Account(AsyncBaseApiClass):
"""https://docs.ftx.com/#account"""
def __init__(self, api_key: str, secret_key: str, subaccount_name: str = None):
super().__init__(api_key, secret_key, subaccount_name)
async def get_account_information(self):
... | 38 | 84 | 0.669173 | 99 | 798 | 5.20202 | 0.353535 | 0.069903 | 0.093204 | 0.116505 | 0.16699 | 0.085437 | 0 | 0 | 0 | 0 | 0 | 0.001529 | 0.180451 | 798 | 20 | 85 | 39.9 | 0.785933 | 0.036341 | 0 | 0 | 0 | 0 | 0.089577 | 0.034202 | 0 | 0 | 0 | 0 | 0.090909 | 1 | 0.090909 | false | 0 | 0.090909 | 0 | 0.545455 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b71296702232873c1e4f5d1eea517c841d75064 | 2,980 | py | Python | slixmpp/plugins/xep_0319/idle.py | anirudhrata/slixmpp | 1fcee0e80a212eeb274d2f560e69099d8a61bf7f | [
"BSD-3-Clause"
] | 86 | 2016-07-04T13:26:02.000Z | 2022-02-19T10:26:21.000Z | slixmpp/plugins/xep_0319/idle.py | anirudhrata/slixmpp | 1fcee0e80a212eeb274d2f560e69099d8a61bf7f | [
"BSD-3-Clause"
] | 10 | 2016-09-30T18:55:41.000Z | 2020-05-01T14:22:47.000Z | slixmpp/plugins/xep_0319/idle.py | anirudhrata/slixmpp | 1fcee0e80a212eeb274d2f560e69099d8a61bf7f | [
"BSD-3-Clause"
] | 45 | 2016-09-30T18:48:41.000Z | 2022-03-18T21:39:33.000Z |
# Slixmpp: The Slick XMPP Library
# Copyright (C) 2013 Nathanael C. Fritz, Lance J.T. Stout
# This file is part of Slixmpp.
# See the file LICENSE for copying permission.
from datetime import datetime, timezone
from typing import Optional
from slixmpp import JID
from slixmpp.stanza import Presence
from slixmpp.plugi... | 33.483146 | 84 | 0.655034 | 388 | 2,980 | 4.871134 | 0.280928 | 0.042328 | 0.033862 | 0.020106 | 0.2 | 0.13545 | 0.078307 | 0.078307 | 0.046561 | 0.046561 | 0 | 0.021108 | 0.236913 | 2,980 | 88 | 85 | 33.863636 | 0.810026 | 0.054362 | 0 | 0 | 0 | 0 | 0.090308 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.12069 | false | 0 | 0.155172 | 0.034483 | 0.413793 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b713daf543427117e79a8f8e7805cb3d4baae6c | 4,687 | py | Python | modules/ImageMagickInterface.py | CollinHeist/TitleCardMaker | a5e90b81177e47d565bb47ed429dbf46d8d696f0 | [
"MIT"
] | 5 | 2022-01-09T09:51:39.000Z | 2022-03-05T15:00:07.000Z | modules/ImageMagickInterface.py | CollinHeist/TitleCardMaker | a5e90b81177e47d565bb47ed429dbf46d8d696f0 | [
"MIT"
] | 17 | 2022-02-14T17:50:51.000Z | 2022-03-30T03:44:06.000Z | modules/ImageMagickInterface.py | CollinHeist/TitleCardMaker | a5e90b81177e47d565bb47ed429dbf46d8d696f0 | [
"MIT"
] | 1 | 2022-01-14T15:08:08.000Z | 2022-01-14T15:08:08.000Z | from shlex import split as command_split
from subprocess import Popen, PIPE
from modules.Debug import log
class ImageMagickInterface:
"""
This class describes an interface to ImageMagick. If initialized with a
valid docker container (name or ID), then all given ImageMagick commands
will be run through... | 33.241135 | 82 | 0.590356 | 558 | 4,687 | 4.910394 | 0.340502 | 0.027372 | 0.010949 | 0.016058 | 0.021898 | 0.021898 | 0 | 0 | 0 | 0 | 0 | 0.001265 | 0.325155 | 4,687 | 140 | 83 | 33.478571 | 0.865002 | 0.485172 | 0 | 0.045455 | 0 | 0 | 0.106393 | 0.021474 | 0 | 0 | 0 | 0 | 0 | 1 | 0.136364 | false | 0 | 0.068182 | 0 | 0.340909 | 0.022727 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b71dd0e376b1aea6b14bf0dfc56584ed3214480 | 3,939 | py | Python | domainbed/lib/Dataset_All.py | zhaoxin94/DomainBed | f880b13a6be82829c7b7c519a7cca54439bda524 | [
"MIT"
] | null | null | null | domainbed/lib/Dataset_All.py | zhaoxin94/DomainBed | f880b13a6be82829c7b7c519a7cca54439bda524 | [
"MIT"
] | null | null | null | domainbed/lib/Dataset_All.py | zhaoxin94/DomainBed | f880b13a6be82829c7b7c519a7cca54439bda524 | [
"MIT"
] | null | null | null | import random
from math import sqrt
import numpy as np
from torch.utils.data import ConcatDataset, Dataset
from torchvision import transforms
class DatasetAll_FDA(Dataset):
"""
Combine Seperated Datasets
"""
def __init__(self, data_list, alpha=1.0):
self.data = ConcatDataset(data_list)
... | 32.553719 | 117 | 0.561056 | 514 | 3,939 | 4.075875 | 0.212062 | 0.038186 | 0.023389 | 0.011456 | 0.466348 | 0.444391 | 0.444391 | 0.444391 | 0.444391 | 0.372792 | 0 | 0.059196 | 0.318101 | 3,939 | 120 | 118 | 32.825 | 0.720774 | 0.049251 | 0 | 0.345679 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.012346 | 1 | 0.098765 | false | 0 | 0.061728 | 0.037037 | 0.259259 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b722402e45e22ead2f85ea3f8f782a3a420b3f1 | 19,001 | py | Python | Main.py | PositivePeriod/Touchable | 8ecb69bd72f16bc0c244c2e983316659d2db1eb5 | [
"MIT"
] | 1 | 2020-07-24T19:29:24.000Z | 2020-07-24T19:29:24.000Z | Main.py | PositivePeriod/Touchable | 8ecb69bd72f16bc0c244c2e983316659d2db1eb5 | [
"MIT"
] | 2 | 2022-01-13T03:01:41.000Z | 2022-03-12T00:40:55.000Z | Main.py | PositivePeriod/Touchable | 8ecb69bd72f16bc0c244c2e983316659d2db1eb5 | [
"MIT"
] | null | null | null | from Canvas import Canvas
from Detector import Detector
from GUI import GUI
from Tracker import Tracker
from Function import *
from Video import Video
from Pen import Pens
from Key import Key
from Image import ImageManager
import tkinter
import tkinter.messagebox
import tkinter.font
import tkinter.simpledialog
import ... | 48.471939 | 131 | 0.495132 | 2,242 | 19,001 | 4.042373 | 0.117306 | 0.035529 | 0.060245 | 0.054507 | 0.507227 | 0.452499 | 0.399537 | 0.346464 | 0.323293 | 0.310714 | 0 | 0.034512 | 0.385453 | 19,001 | 391 | 132 | 48.595908 | 0.741629 | 0.032998 | 0 | 0.381924 | 0 | 0 | 0.054755 | 0 | 0 | 0 | 0 | 0.005115 | 0 | 1 | 0.020408 | false | 0 | 0.046647 | 0 | 0.104956 | 0.029155 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b737ca1f860daa1879d93647b7707dac737931f | 1,057 | py | Python | SUAVE/SUAVE-2.5.0/trunk/SUAVE/Methods/Geometry/Two_Dimensional/Planform/wing_fuel_volume.py | Vinicius-Tanigawa/Undergraduate-Research-Project | e92372f07882484b127d7affe305eeec2238b8a9 | [
"MIT"
] | null | null | null | SUAVE/SUAVE-2.5.0/trunk/SUAVE/Methods/Geometry/Two_Dimensional/Planform/wing_fuel_volume.py | Vinicius-Tanigawa/Undergraduate-Research-Project | e92372f07882484b127d7affe305eeec2238b8a9 | [
"MIT"
] | null | null | null | SUAVE/SUAVE-2.5.0/trunk/SUAVE/Methods/Geometry/Two_Dimensional/Planform/wing_fuel_volume.py | Vinicius-Tanigawa/Undergraduate-Research-Project | e92372f07882484b127d7affe305eeec2238b8a9 | [
"MIT"
] | null | null | null | ## @ingroup Methods-Geometry-Two_Dimensional-Cross_Section-Planform
# wing_fuel_volume.py
#
# Created: Apr 2014, T. Orra
# Modified: Sep 2016, E. Botero
# ----------------------------------------------------------------------
# Correlation-based methods for wing fuel capacity estimation
# ---------------------------... | 25.166667 | 72 | 0.545885 | 115 | 1,057 | 4.886957 | 0.608696 | 0.05694 | 0.074733 | 0.088968 | 0.199288 | 0.199288 | 0.199288 | 0.199288 | 0 | 0 | 0 | 0.034483 | 0.231788 | 1,057 | 42 | 73 | 25.166667 | 0.657635 | 0.685904 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.166667 | false | 0 | 0 | 0 | 0.166667 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b73dd9af423cd6336a9986151cd7a7b2c788948 | 4,559 | py | Python | bycycle/cyclepoints/zerox.py | ryanhammonds/bycycle | c285c5b1bf5de985cea3f0898bf8e2b01171feca | [
"Apache-2.0"
] | 48 | 2019-03-04T22:37:15.000Z | 2022-03-28T16:55:52.000Z | bycycle/cyclepoints/zerox.py | ryanhammonds/bycycle | c285c5b1bf5de985cea3f0898bf8e2b01171feca | [
"Apache-2.0"
] | 83 | 2019-02-01T19:09:23.000Z | 2022-01-10T20:27:29.000Z | bycycle/cyclepoints/zerox.py | ryanhammonds/bycycle | c285c5b1bf5de985cea3f0898bf8e2b01171feca | [
"Apache-2.0"
] | 15 | 2019-06-04T23:22:37.000Z | 2021-12-21T07:49:31.000Z | """Find zero-crossings for individual cycles."""
from operator import gt, lt
import numpy as np
###################################################################################################
###################################################################################################
def find_zerox(sig, ... | 34.022388 | 99 | 0.622286 | 626 | 4,559 | 4.412141 | 0.276358 | 0.051774 | 0.025344 | 0.017379 | 0.250905 | 0.179942 | 0.093411 | 0.093411 | 0.093411 | 0.027516 | 0 | 0.01493 | 0.236017 | 4,559 | 133 | 100 | 34.278195 | 0.778065 | 0.554946 | 0 | 0.171429 | 0 | 0 | 0.024621 | 0 | 0 | 0 | 0 | 0 | 0.057143 | 1 | 0.085714 | false | 0 | 0.057143 | 0 | 0.228571 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b7ada4d94b476f49373c95f6b93102fb37d26b1 | 1,327 | py | Python | SampleModels/BasicModel/AnalyseDrifters.py | fearghalodonncha/DeepCurrent | 8dfb19b701a225ead61d6015d95c703478035ce0 | [
"MIT"
] | 32 | 2018-03-31T22:19:25.000Z | 2022-03-14T01:35:23.000Z | SampleModels/BasicModel/AnalyseDrifters.py | fearghalodonncha/DeepCurrent | 8dfb19b701a225ead61d6015d95c703478035ce0 | [
"MIT"
] | 2 | 2020-04-02T06:13:13.000Z | 2021-06-10T07:15:07.000Z | SampleModels/BasicModel/AnalyseDrifters.py | fearghalodonncha/DeepCurrent | 8dfb19b701a225ead61d6015d95c703478035ce0 | [
"MIT"
] | 15 | 2018-06-27T02:55:23.000Z | 2021-09-09T07:51:23.000Z | import numpy as np
import matplotlib.pyplot as plt
def read_drifter(filename):
with open(filename) as f:
lines = f.readlines()
NPD = float(lines[3].split()[0]) ## NPD, number of particles specified on line 4
times_list = lines[4::2]
drifter_list = lines[5::2]
times_np = np.zeros([len(time... | 32.365854 | 86 | 0.568953 | 207 | 1,327 | 3.439614 | 0.275362 | 0.088483 | 0.08427 | 0.08427 | 0.297753 | 0.271067 | 0.220506 | 0.08427 | 0 | 0 | 0 | 0.031024 | 0.271289 | 1,327 | 40 | 87 | 33.175 | 0.705274 | 0.033158 | 0 | 0.117647 | 0 | 0 | 0.015625 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.058824 | false | 0 | 0.058824 | 0 | 0.147059 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b7b8443e086f193aae994977d55ad1ff72e4870 | 9,013 | py | Python | src/trading_algorithm.py | Blocksize-Capital-GmbH/Quant-VM---Crypto-Arbitrage-Software | aefdab0a4a2ded2556bbf0289bdeb21a91da0b91 | [
"Apache-2.0"
] | 1 | 2022-03-20T14:34:51.000Z | 2022-03-20T14:34:51.000Z | src/trading_algorithm.py | Blocksize-Capital-GmbH/Quant-VM---Crypto-Arbitrage-Software | aefdab0a4a2ded2556bbf0289bdeb21a91da0b91 | [
"Apache-2.0"
] | null | null | null | src/trading_algorithm.py | Blocksize-Capital-GmbH/Quant-VM---Crypto-Arbitrage-Software | aefdab0a4a2ded2556bbf0289bdeb21a91da0b91 | [
"Apache-2.0"
] | null | null | null | #!/usr/bin/python3
# -*- coding: utf-8 -*-
import os
import json
import psycopg2
from typing import Dict, List, Tuple, Union
from abc import abstractmethod
import src.helpers
import src.util
from src.base_with_database_logger import BaseWithDatabaseAndLogger
from src.client.custom_sdk_client import CustomClient
from... | 39.704846 | 167 | 0.606235 | 973 | 9,013 | 5.354573 | 0.208633 | 0.042418 | 0.017466 | 0.020729 | 0.200576 | 0.120154 | 0.075624 | 0.06142 | 0.024952 | 0.024952 | 0 | 0.004169 | 0.308 | 9,013 | 226 | 168 | 39.880531 | 0.831169 | 0.055032 | 0 | 0.156977 | 0 | 0 | 0.068682 | 0.002705 | 0 | 0 | 0 | 0.004425 | 0 | 1 | 0.087209 | false | 0.005814 | 0.063953 | 0.040698 | 0.215116 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b7f19efe5226324127b16d1d9afc2df6edb7254 | 1,891 | py | Python | list_2d_2.py | min-xu-ai/py_perf | ba9f07eefc8031a34fe77f19fc6be19d08344bff | [
"MIT"
] | null | null | null | list_2d_2.py | min-xu-ai/py_perf | ba9f07eefc8031a34fe77f19fc6be19d08344bff | [
"MIT"
] | null | null | null | list_2d_2.py | min-xu-ai/py_perf | ba9f07eefc8031a34fe77f19fc6be19d08344bff | [
"MIT"
] | null | null | null | #!/usr/bin/env pypy3
'''
Testing 2D list (list of lists) data structure.
'''
import time
import random
from lib import benchmark, random_tuple
g_list = []
g_size = 0
g_count = 0
g_get_keys = []
g_set_keys = []
def setup(size, density):
''' Populated the table.
:param int size: total entries
:param flo... | 21.735632 | 66 | 0.561079 | 301 | 1,891 | 3.299003 | 0.249169 | 0.060423 | 0.042296 | 0.049345 | 0.209466 | 0.141994 | 0.130916 | 0.07855 | 0.04431 | 0 | 0 | 0.027929 | 0.31835 | 1,891 | 86 | 67 | 21.988372 | 0.742436 | 0.114754 | 0 | 0.292308 | 0 | 0 | 0.004893 | 0 | 0 | 0 | 0 | 0 | 0.030769 | 1 | 0.076923 | false | 0 | 0.046154 | 0 | 0.169231 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b7f2b6e0d9ea9418bfa786631467a10dace678f | 10,622 | py | Python | src/stepfunctions/inputs/placeholders.py | ParidelPooya/aws-step-functions-data-science-sdk-python | 173b4635d8fb3ce569515bcfb6fee1d5a2c29b63 | [
"Apache-2.0"
] | 211 | 2019-11-07T17:56:56.000Z | 2022-03-23T03:04:43.000Z | src/stepfunctions/inputs/placeholders.py | ParidelPooya/aws-step-functions-data-science-sdk-python | 173b4635d8fb3ce569515bcfb6fee1d5a2c29b63 | [
"Apache-2.0"
] | 179 | 2019-11-08T00:47:08.000Z | 2022-03-10T03:03:37.000Z | src/stepfunctions/inputs/placeholders.py | ParidelPooya/aws-step-functions-data-science-sdk-python | 173b4635d8fb3ce569515bcfb6fee1d5a2c29b63 | [
"Apache-2.0"
] | 86 | 2019-11-20T12:59:03.000Z | 2022-03-23T03:04:47.000Z | # Copyright 2019 Amazon.com, Inc. or its affiliates. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License").
# You may not use this file except in compliance with the License.
# A copy of the License is located at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# or in the "license... | 36.129252 | 150 | 0.588119 | 1,194 | 10,622 | 5.10469 | 0.183417 | 0.065463 | 0.035439 | 0.026579 | 0.337818 | 0.264643 | 0.225431 | 0.210336 | 0.16735 | 0.136505 | 0 | 0.001685 | 0.329505 | 10,622 | 293 | 151 | 36.25256 | 0.854114 | 0.365468 | 0 | 0.272059 | 0 | 0 | 0.069477 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.147059 | false | 0 | 0.029412 | 0 | 0.367647 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b8031ca25667feb25f8274399a41253e2becc80 | 1,177 | py | Python | src/mrack/transformers/static.py | dav-pascual/mrack | f31b4ef1f1f847c3e95567ec012323be65a1e177 | [
"Apache-2.0"
] | 2 | 2021-05-26T15:57:13.000Z | 2021-08-21T02:14:01.000Z | src/mrack/transformers/static.py | dav-pascual/mrack | f31b4ef1f1f847c3e95567ec012323be65a1e177 | [
"Apache-2.0"
] | 81 | 2020-10-02T08:30:56.000Z | 2022-03-31T11:47:41.000Z | src/mrack/transformers/static.py | dav-pascual/mrack | f31b4ef1f1f847c3e95567ec012323be65a1e177 | [
"Apache-2.0"
] | 7 | 2020-10-02T08:13:57.000Z | 2022-03-31T11:22:53.000Z | # Copyright 2020 Red Hat Inc.
#
# 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,... | 30.179487 | 74 | 0.725573 | 160 | 1,177 | 5.25625 | 0.63125 | 0.071344 | 0.030916 | 0.03805 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.008386 | 0.189465 | 1,177 | 38 | 75 | 30.973684 | 0.873166 | 0.595582 | 0 | 0 | 0 | 0 | 0.057604 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.090909 | false | 0 | 0.272727 | 0 | 0.818182 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b816baf5eaa46bd1b527f1e92fb14dd928f8b46 | 1,185 | py | Python | data/states/splash.py | andarms/pyweek20 | 79a5ac58c3ca06be61e5a05af0abd78a8c79e8df | [
"MIT"
] | null | null | null | data/states/splash.py | andarms/pyweek20 | 79a5ac58c3ca06be61e5a05af0abd78a8c79e8df | [
"MIT"
] | null | null | null | data/states/splash.py | andarms/pyweek20 | 79a5ac58c3ca06be61e5a05af0abd78a8c79e8df | [
"MIT"
] | null | null | null | import pygame as pg
import state
from .. import util
class SplashState(state._State):
def __init__(self):
super(SplashState, self).__init__()
self.bg_color = (0,0,0)
self.text_color = (155,255,155)
self.duration = 3 #seg
self.image = pg.Surface(util.SCREEN_SIZE)
sel... | 28.214286 | 67 | 0.616034 | 156 | 1,185 | 4.525641 | 0.397436 | 0.067989 | 0.056657 | 0.042493 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.021789 | 0.264135 | 1,185 | 41 | 68 | 28.902439 | 0.787844 | 0.002532 | 0 | 0.129032 | 0 | 0 | 0.031409 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.193548 | 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 |
3b86bd629224d587375d982d9e21ec4c5e570896 | 4,230 | py | Python | root/os/DSAA/DataStructuresAndAlgorithms/python/chutils/chutils/utils/time_get_lock_info.py | chyidl/chyidlTutorial | a033e0a57abf84fdbb61e57736822f9126db6ff7 | [
"MIT"
] | 5 | 2018-10-17T05:57:39.000Z | 2021-07-05T15:38:24.000Z | root/os/DSAA/DataStructuresAndAlgorithms/python/chutils/chutils/utils/time_get_lock_info.py | chyidl/chyidlTutorial | a033e0a57abf84fdbb61e57736822f9126db6ff7 | [
"MIT"
] | 2 | 2021-04-14T00:48:43.000Z | 2021-04-14T02:20:50.000Z | root/os/DSAA/DataStructuresAndAlgorithms/python/chutils/chutils/utils/time_get_lock_info.py | chyidl/chyidlTutorial | a033e0a57abf84fdbb61e57736822f9126db6ff7 | [
"MIT"
] | 3 | 2019-03-02T14:36:19.000Z | 2022-03-18T10:12:09.000Z | #! /usr/bin/env python3
# -*- coding: utf-8 -*-
#
# time_get_lock_info.py
# utils
#
# 🎂"Here's to the crazy ones. The misfits. The rebels.
# The troublemakers. The round pegs in the square holes.
# The ones who see things differently. They're not found
# of rules. And they have no respect for the status quo.
# You can... | 27.647059 | 79 | 0.644681 | 582 | 4,230 | 4.582474 | 0.42268 | 0.035996 | 0.028121 | 0.022497 | 0.028496 | 0 | 0 | 0 | 0 | 0 | 0 | 0.021226 | 0.20922 | 4,230 | 152 | 80 | 27.828947 | 0.775486 | 0.33948 | 0 | 0.023529 | 0 | 0 | 0.270742 | 0.007642 | 0 | 0 | 0 | 0 | 0 | 1 | 0.023529 | false | 0 | 0.047059 | 0 | 0.070588 | 0.364706 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b895d1b25f903e8bc77ab1b05b04c1d12622eea | 5,995 | py | Python | poisson_problem/poisson.py | timudk/solving_pdes_with_neural_nets | 4aeca4ee1aaa6054307e1051879bed3160ffc247 | [
"MIT"
] | 69 | 2019-04-16T06:42:22.000Z | 2021-04-06T02:39:21.000Z | poisson_problem/poisson.py | timudk/solving_pdes_with_neural_nets | 4aeca4ee1aaa6054307e1051879bed3160ffc247 | [
"MIT"
] | null | null | null | poisson_problem/poisson.py | timudk/solving_pdes_with_neural_nets | 4aeca4ee1aaa6054307e1051879bed3160ffc247 | [
"MIT"
] | 19 | 2019-04-16T14:31:47.000Z | 2021-06-05T21:46:53.000Z | import tensorflow as tf
tf.set_random_seed(42)
import numpy as np
from scipy import integrate
import neural_networks
import poisson_problem
import matplotlib.pyplot as plt
import sys, getopt
class sampling_from_dataset:
def __init__(self, filepath, total_samples):
self.filepath = filepath
self.total_samples = ... | 33.121547 | 148 | 0.732944 | 951 | 5,995 | 4.290221 | 0.17245 | 0.027451 | 0.041176 | 0.025735 | 0.388971 | 0.320588 | 0.277941 | 0.231863 | 0.203922 | 0.186765 | 0 | 0.015349 | 0.130609 | 5,995 | 180 | 149 | 33.305556 | 0.76746 | 0.001168 | 0 | 0.069767 | 0 | 0.015504 | 0.097895 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.046512 | false | 0 | 0.054264 | 0 | 0.139535 | 0.03876 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b99148519a93c8543e9564b329c4137fc41b8bf | 1,509 | py | Python | PythonBot.py | quasiyoke/PythonBot | d665a1580b683b8dbf4c68f50e112eb9ec30f8d0 | [
"Apache-2.0"
] | 9 | 2021-07-07T16:57:17.000Z | 2021-11-14T17:45:10.000Z | PythonBot.py | quasiyoke/PythonBot | d665a1580b683b8dbf4c68f50e112eb9ec30f8d0 | [
"Apache-2.0"
] | null | null | null | PythonBot.py | quasiyoke/PythonBot | d665a1580b683b8dbf4c68f50e112eb9ec30f8d0 | [
"Apache-2.0"
] | 2 | 2021-11-20T10:26:18.000Z | 2021-11-26T09:18:13.000Z | from substrateinterface import SubstrateInterface, Keypair
from substrateinterface.exceptions import SubstrateRequestException
from scalecodec.type_registry import load_type_registry_file
import time
substrate = SubstrateInterface(
url='wss://ws.mof.sora.org',
ss58_format=69,
type_registry_preset='default'... | 33.533333 | 117 | 0.732936 | 152 | 1,509 | 7.019737 | 0.585526 | 0.056232 | 0.029991 | 0.037488 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.128728 | 0.155732 | 1,509 | 44 | 118 | 34.295455 | 0.708791 | 0.070245 | 0 | 0 | 0 | 0 | 0.330951 | 0.162974 | 0 | 0 | 0.094353 | 0 | 0 | 1 | 0 | false | 0.032258 | 0.129032 | 0 | 0.129032 | 0.064516 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b9b35f7c92754e4b2f2e40b05e20b3c368edfaa | 2,822 | py | Python | mutalyzer_mutator/mutator.py | mutalyzer/mutator | 43a9fc929e054552ef6a2ed2d0cdf71e49ebf005 | [
"MIT"
] | null | null | null | mutalyzer_mutator/mutator.py | mutalyzer/mutator | 43a9fc929e054552ef6a2ed2d0cdf71e49ebf005 | [
"MIT"
] | null | null | null | mutalyzer_mutator/mutator.py | mutalyzer/mutator | 43a9fc929e054552ef6a2ed2d0cdf71e49ebf005 | [
"MIT"
] | null | null | null | """
Module to mutate sequences based on a variants list.
Assumptions for which no check is performed:
- Only ``deletion insertion`` operations.
- Only exact locations, i.e., no uncertainties such as `10+?`.
- Locations are zero-based right-open with ``start > end``.
- There is no overlapping between variants locat... | 29.395833 | 79 | 0.665131 | 321 | 2,822 | 5.741433 | 0.376947 | 0.030385 | 0.029843 | 0.033641 | 0.069452 | 0.034726 | 0 | 0 | 0 | 0 | 0 | 0.001355 | 0.21545 | 2,822 | 95 | 80 | 29.705263 | 0.831075 | 0.318214 | 0 | 0.045455 | 0 | 0 | 0.143013 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.090909 | false | 0.022727 | 0.022727 | 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 |
3b9b566f35bb3be3bbe04e1b0c6ea0b1acb1d8bc | 1,791 | py | Python | day11/day11_2.py | DanTGL/AdventOfCode2020 | bf7cd6a4fb7701155785b941facdc1e4859ba297 | [
"MIT"
] | null | null | null | day11/day11_2.py | DanTGL/AdventOfCode2020 | bf7cd6a4fb7701155785b941facdc1e4859ba297 | [
"MIT"
] | null | null | null | day11/day11_2.py | DanTGL/AdventOfCode2020 | bf7cd6a4fb7701155785b941facdc1e4859ba297 | [
"MIT"
] | null | null | null | import copy
from collections import defaultdict
inputs = [list(line) for line in open("day11/input").read().splitlines()]
nodes = defaultdict(lambda: [])
for y in range(len(inputs)):
for x in range(len(inputs[y])):
if inputs[y][x] != ".":
for i in range(-1, 2):
for j in range... | 28.887097 | 87 | 0.460078 | 221 | 1,791 | 3.642534 | 0.230769 | 0.069565 | 0.074534 | 0.074534 | 0.195031 | 0.119255 | 0.119255 | 0.119255 | 0.119255 | 0.119255 | 0 | 0.01687 | 0.404243 | 1,791 | 62 | 88 | 28.887097 | 0.737582 | 0 | 0 | 0.130435 | 0 | 0 | 0.023438 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.021739 | false | 0 | 0.043478 | 0 | 0.086957 | 0.021739 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3b9faf565558a1df6837f883c4af01c1961579e5 | 4,806 | py | Python | centersnap/utils.py | ibaiGorordo/ONNX-CenterSnap-6D-Pose-and-Shape-Estimation | f8f98b08cce5259348616db4150064d713f17445 | [
"MIT"
] | 13 | 2022-03-19T14:42:50.000Z | 2022-03-31T14:04:31.000Z | centersnap/utils.py | ibaiGorordo/ONNX-CenterSnap-6D-Pose-and-Shape-Estimation | f8f98b08cce5259348616db4150064d713f17445 | [
"MIT"
] | null | null | null | centersnap/utils.py | ibaiGorordo/ONNX-CenterSnap-6D-Pose-and-Shape-Estimation | f8f98b08cce5259348616db4150064d713f17445 | [
"MIT"
] | 1 | 2022-03-24T12:56:25.000Z | 2022-03-24T12:56:25.000Z | import numpy as np
import cv2
import open3d as o3d
from .original_repo_utils import *
np.random.seed(3)
MAX_CLASS_NUM = 100 # In the original model there are only 7 classes
segmenation_colors = np.random.randint(0, 255, (MAX_CLASS_NUM, 3)).astype("uint8")
def util_draw_seg(seg_map, image, alpha = 0.5):
# Convert... | 28.105263 | 97 | 0.740117 | 773 | 4,806 | 4.324709 | 0.179819 | 0.025127 | 0.025127 | 0.04487 | 0.488783 | 0.44152 | 0.37242 | 0.3105 | 0.223153 | 0.165121 | 0 | 0.038005 | 0.140449 | 4,806 | 170 | 98 | 28.270588 | 0.771242 | 0.106742 | 0 | 0.134021 | 0 | 0 | 0.00117 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.103093 | false | 0 | 0.041237 | 0 | 0.226804 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
3ba02c62d0d88116daac3eef24c8c51ab27ced29 | 2,519 | py | Python | strokes_gained_calculations.py | brentonworley/strokes-gained | f3390de62a8987fd0a73ddb41837f7dcecb29387 | [
"MIT"
] | null | null | null | strokes_gained_calculations.py | brentonworley/strokes-gained | f3390de62a8987fd0a73ddb41837f7dcecb29387 | [
"MIT"
] | null | null | null | strokes_gained_calculations.py | brentonworley/strokes-gained | f3390de62a8987fd0a73ddb41837f7dcecb29387 | [
"MIT"
] | null | null | null | def calculate_strokes_gained(reference_value, user_putts):
'''Return the strokes gained based on reference and user input'''
return round((reference_value - user_putts), 2)
def calculate_strokes_gained_putting(reference_data, user_input):
'''Return the strokes gained value from a dictionary of user input
... | 45.8 | 121 | 0.687574 | 314 | 2,519 | 5.283439 | 0.254777 | 0.101266 | 0.081977 | 0.047016 | 0.203134 | 0.157926 | 0.112116 | 0.061483 | 0.061483 | 0 | 0 | 0.004199 | 0.243748 | 2,519 | 54 | 122 | 46.648148 | 0.866667 | 0.262406 | 0 | 0.125 | 0 | 0.03125 | 0.111232 | 0.013086 | 0 | 0 | 0 | 0 | 0 | 1 | 0.0625 | false | 0 | 0 | 0 | 0.125 | 0.03125 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
8e535a0eaed4fb2eca117828f9d5fa6d60c950b3 | 8,988 | py | Python | CRF/cnn_word_seg_torch.py | enjlife/bert4torch | 53694060fed0351649f87c79381740851a4a0b42 | [
"Apache-2.0"
] | 5 | 2021-09-09T03:25:58.000Z | 2022-02-22T06:43:08.000Z | CRF/cnn_word_seg_torch.py | enjlife/bert4torch | 53694060fed0351649f87c79381740851a4a0b42 | [
"Apache-2.0"
] | 1 | 2022-02-18T07:46:46.000Z | 2022-02-20T10:05:25.000Z | CRF/cnn_word_seg_torch.py | enjlife/bert4torch | 53694060fed0351649f87c79381740851a4a0b42 | [
"Apache-2.0"
] | null | null | null | import os
import torch.nn
from torch import nn
from crf_torch import CRF
import re
import random
import time
from torch.optim import Adam
import torch.nn.functional as F
from datetime import timedelta
# TODO 准确率计算函数的bug修复
def get_time_dif(start_time):
"""获取已使用时间"""
end_time = time.time()
time_dif = end_t... | 36.836066 | 161 | 0.549622 | 1,213 | 8,988 | 3.892828 | 0.176422 | 0.041931 | 0.011436 | 0.023295 | 0.275307 | 0.212622 | 0.191233 | 0.176832 | 0.155654 | 0.128971 | 0 | 0.024495 | 0.32777 | 8,988 | 244 | 162 | 36.836066 | 0.757034 | 0.022363 | 0 | 0.156398 | 0 | 0.004739 | 0.027607 | 0.003536 | 0 | 0 | 0 | 0.004098 | 0 | 1 | 0.075829 | false | 0 | 0.047393 | 0.004739 | 0.203791 | 0.009479 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
8e54656185e027ab6cdc457485c3e4f7aee1306c | 1,636 | py | Python | gs_quant/backtests/execution_engine.py | skyquant2/gs-quant | b7e648fa7912b13ad1fd503b643389e34587aa1e | [
"Apache-2.0"
] | 2 | 2021-06-22T12:14:38.000Z | 2021-06-23T15:51:08.000Z | gs_quant/backtests/execution_engine.py | skyquant2/gs-quant | b7e648fa7912b13ad1fd503b643389e34587aa1e | [
"Apache-2.0"
] | null | null | null | gs_quant/backtests/execution_engine.py | skyquant2/gs-quant | b7e648fa7912b13ad1fd503b643389e34587aa1e | [
"Apache-2.0"
] | null | null | null | """
Copyright 2019 Goldman Sachs.
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 di... | 33.387755 | 90 | 0.675428 | 209 | 1,636 | 5.162679 | 0.526316 | 0.055607 | 0.055607 | 0.029657 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00817 | 0.251834 | 1,636 | 48 | 91 | 34.083333 | 0.873366 | 0.337408 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.115385 | false | 0.038462 | 0.115385 | 0 | 0.346154 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
8e54b6e75de5f4de964911c5a74139115880c479 | 19,578 | py | Python | biosimulators_opencor/utils.py | biosimulators/Biosimulators_OpenCOR | e00645e372baf7475957af9487856ad9ddd18814 | [
"MIT"
] | null | null | null | biosimulators_opencor/utils.py | biosimulators/Biosimulators_OpenCOR | e00645e372baf7475957af9487856ad9ddd18814 | [
"MIT"
] | null | null | null | biosimulators_opencor/utils.py | biosimulators/Biosimulators_OpenCOR | e00645e372baf7475957af9487856ad9ddd18814 | [
"MIT"
] | null | null | null | """ Utilities for OpenCOR
:Author: Jonathan Karr <karr@mssm.edu>
:Date: 2021-05-28
:Copyright: 2021, BioSimulators Team
:License: MIT
"""
from .data_model import KISAO_ALGORITHM_MAP
from biosimulators_utils.config import get_config, Config # noqa: F401
from biosimulators_utils.data_model import ValueType # noqa: F4... | 38.53937 | 141 | 0.659056 | 2,234 | 19,578 | 5.54342 | 0.149955 | 0.02043 | 0.017846 | 0.014858 | 0.383398 | 0.332122 | 0.276244 | 0.221657 | 0.187419 | 0.171592 | 0 | 0.003321 | 0.246348 | 19,578 | 507 | 142 | 38.615385 | 0.835988 | 0.209521 | 0 | 0.187291 | 0 | 0 | 0.115847 | 0.018057 | 0 | 0 | 0 | 0.001972 | 0 | 1 | 0.040134 | false | 0.010033 | 0.063545 | 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 |
8e559b65f4bffc816f6acc36951ebd073cffa8c9 | 3,407 | py | Python | arpym/statistics/saddle_point_quadn.py | dpopadic/arpmRes | ddcc4de713b46e3e9dcb77cc08c502ce4df54f76 | [
"MIT"
] | 6 | 2021-04-10T13:24:30.000Z | 2022-03-26T08:20:42.000Z | arpym/statistics/saddle_point_quadn.py | dpopadic/arpmRes | ddcc4de713b46e3e9dcb77cc08c502ce4df54f76 | [
"MIT"
] | null | null | null | arpym/statistics/saddle_point_quadn.py | dpopadic/arpmRes | ddcc4de713b46e3e9dcb77cc08c502ce4df54f76 | [
"MIT"
] | 6 | 2019-08-13T22:02:17.000Z | 2022-02-09T17:49:12.000Z | # -*- coding: utf-8 -*-
import numpy as np
from scipy.stats import norm
from scipy.optimize import brentq
from arpym.tools.transpose_square_root import transpose_square_root
def saddle_point_quadn(y, alpha, beta, gamma, mu, sigma2):
"""For details, see here.
Parameters
----------
y : array, shape... | 30.693694 | 79 | 0.528618 | 546 | 3,407 | 3.089744 | 0.221612 | 0.052164 | 0.037344 | 0.037937 | 0.160047 | 0.097214 | 0.089508 | 0.07706 | 0.035566 | 0.035566 | 0 | 0.026304 | 0.330496 | 3,407 | 110 | 80 | 30.972727 | 0.713284 | 0.249486 | 0 | 0.050847 | 0 | 0 | 0.003222 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.067797 | false | 0 | 0.067797 | 0.050847 | 0.20339 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
8e57c1d666f0e679e553435b63623e54ee15e34a | 320 | py | Python | hardware/dht/__init__.py | jpalczewski/pills | ab0cf0feedbdfe069a0dad76c8a45ee9ab4cfc26 | [
"MIT"
] | null | null | null | hardware/dht/__init__.py | jpalczewski/pills | ab0cf0feedbdfe069a0dad76c8a45ee9ab4cfc26 | [
"MIT"
] | null | null | null | hardware/dht/__init__.py | jpalczewski/pills | ab0cf0feedbdfe069a0dad76c8a45ee9ab4cfc26 | [
"MIT"
] | null | null | null | from .DHT22 import sensor
import time
import pigpio
async def poll_once():
pi = pigpio.pi()
s = sensor(pi, 24, LED=None, power=None,DHT11=False)
s.trigger()
time.sleep(0.2)
humidity = s.humidity()
temperature = s.temperature()
s.cancel()
pi.stop()
return (humidity, temperature) | 17.777778 | 56 | 0.6375 | 44 | 320 | 4.613636 | 0.613636 | 0.187192 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.03252 | 0.23125 | 320 | 18 | 57 | 17.777778 | 0.792683 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.230769 | 0 | 0.307692 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
8e5ba2a20b4cea3293ed973ff92b38716b7ec7fc | 2,267 | py | Python | test.py | gadolly/Deep_learning | b29248f97d576c36cad9eb0f67ed834d7a5aadad | [
"MIT"
] | null | null | null | test.py | gadolly/Deep_learning | b29248f97d576c36cad9eb0f67ed834d7a5aadad | [
"MIT"
] | null | null | null | test.py | gadolly/Deep_learning | b29248f97d576c36cad9eb0f67ed834d7a5aadad | [
"MIT"
] | null | null | null | # import the necessary packages
from keras.preprocessing import image as image_utils
from imagenet_utils import decode_predictions
from imagenet_utils import preprocess_input
from vgg16 import VGG16
import numpy as np
import argparse
import cv2
from keras.utils import np_utils
import matplotlib.pyplot as plt
from matpl... | 30.635135 | 71 | 0.736215 | 353 | 2,267 | 4.665722 | 0.402266 | 0.051609 | 0.05343 | 0.02793 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.034179 | 0.148214 | 2,267 | 74 | 72 | 30.635135 | 0.818747 | 0.406264 | 0 | 0 | 0 | 0 | 0.134441 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.27027 | 0 | 0.27027 | 0.162162 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
8e615b3096b4af4bf6362be743bc75af467ed5a8 | 17,468 | py | Python | tests/test_requirements.py | domdfcoding/packing-tape | d8570033c8088c68527db918339c14aa6953264f | [
"MIT"
] | null | null | null | tests/test_requirements.py | domdfcoding/packing-tape | d8570033c8088c68527db918339c14aa6953264f | [
"MIT"
] | null | null | null | tests/test_requirements.py | domdfcoding/packing-tape | d8570033c8088c68527db918339c14aa6953264f | [
"MIT"
] | null | null | null | # stdlib
from typing import List, Sequence, Union
# 3rd party
import pytest
from coincidence.regressions import AdvancedDataRegressionFixture
from coincidence.selectors import min_version, not_windows, only_version
from domdf_python_tools.paths import PathPlus
from packaging.requirements import Requirement
from packag... | 30.916814 | 101 | 0.676551 | 2,184 | 17,468 | 5.277015 | 0.120879 | 0.006074 | 0.006247 | 0.042777 | 0.676443 | 0.632278 | 0.596529 | 0.554013 | 0.533623 | 0.464642 | 0 | 0.043826 | 0.141802 | 17,468 | 564 | 102 | 30.971631 | 0.724968 | 0.012365 | 0 | 0.447205 | 0 | 0.008282 | 0.28293 | 0.081028 | 0 | 0 | 0 | 0 | 0.122153 | 1 | 0.05176 | false | 0 | 0.028986 | 0.008282 | 0.093168 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
8e6171a69d7112d24e0deaed0a6f8f8e780b1f04 | 6,682 | py | Python | tests/ut/python/parallel/test_uniform_candidate_sampler.py | Vincent34/mindspore | a39a60878a46e7e9cb02db788c0bca478f2fa6e5 | [
"Apache-2.0"
] | 2 | 2021-07-08T13:10:42.000Z | 2021-11-08T02:48:57.000Z | tests/ut/python/parallel/test_uniform_candidate_sampler.py | peixinhou/mindspore | fcb2ec2779b753e95c762cf292b23bd81d1f561b | [
"Apache-2.0"
] | null | null | null | tests/ut/python/parallel/test_uniform_candidate_sampler.py | peixinhou/mindspore | fcb2ec2779b753e95c762cf292b23bd81d1f561b | [
"Apache-2.0"
] | null | null | null | # 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... | 41.246914 | 109 | 0.700389 | 923 | 6,682 | 4.777898 | 0.192849 | 0.059864 | 0.032426 | 0.052154 | 0.648753 | 0.641043 | 0.624717 | 0.606576 | 0.599773 | 0.571655 | 0 | 0.03914 | 0.185573 | 6,682 | 161 | 110 | 41.503106 | 0.771224 | 0.09548 | 0 | 0.461538 | 0 | 0 | 0.030353 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.128205 | false | 0 | 0.076923 | 0 | 0.239316 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
8e622edaf8f47d87d5f8233d0e8589b835af46c3 | 3,464 | py | Python | lib/servers/data_vault.py | clayton-ho/EGGs_Control | 312f02488b47cf880c6e6600ce10856a871123df | [
"MIT"
] | null | null | null | lib/servers/data_vault.py | clayton-ho/EGGs_Control | 312f02488b47cf880c6e6600ce10856a871123df | [
"MIT"
] | null | null | null | lib/servers/data_vault.py | clayton-ho/EGGs_Control | 312f02488b47cf880c6e6600ce10856a871123df | [
"MIT"
] | null | null | null | # Copyright (C) 2007 Matthew Neeley
#
# This program is free software: you can redistribute it and/or modify
# it under the terms of the GNU General Public License as published by
# the Free Software Foundation, either version 2 of the License, or
# (at your option) any later version.
#
# This program is distributed i... | 32.679245 | 81 | 0.687356 | 464 | 3,464 | 5.047414 | 0.411638 | 0.020495 | 0.016652 | 0.024338 | 0.055508 | 0.044406 | 0 | 0 | 0 | 0 | 0 | 0.007407 | 0.220554 | 3,464 | 105 | 82 | 32.990476 | 0.86 | 0.374134 | 0 | 0.038462 | 0 | 0 | 0.160057 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.057692 | false | 0.019231 | 0.173077 | 0 | 0.230769 | 0.096154 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |
8e65b59f5232680aea8dce90eae39a5dcfa86850 | 5,465 | py | Python | py-opentsdb.py | langerma/py-opentsdb | d652a96d3a53bf7c6785a1d586427d666bb3da96 | [
"BSD-2-Clause"
] | 2 | 2020-02-20T16:00:11.000Z | 2020-02-20T16:00:21.000Z | py-opentsdb.py | langerma/py-opentsdb | d652a96d3a53bf7c6785a1d586427d666bb3da96 | [
"BSD-2-Clause"
] | null | null | null | py-opentsdb.py | langerma/py-opentsdb | d652a96d3a53bf7c6785a1d586427d666bb3da96 | [
"BSD-2-Clause"
] | null | null | null | import requests
import pandas
try:
# Use ujson if available.
import ujson as json
except Exception:
import json
class OpenTSDBResponseSerie(object):
"""
A single OpenTSDB response serie i.e 1 element of the response
array.
Params:
**kwargs : OpenTSDB response serie ... | 31.589595 | 103 | 0.530101 | 586 | 5,465 | 4.890785 | 0.298635 | 0.004885 | 0.010468 | 0.00977 | 0.171668 | 0.147941 | 0.115143 | 0.110258 | 0.037683 | 0 | 0 | 0.003951 | 0.351693 | 5,465 | 172 | 104 | 31.773256 | 0.804968 | 0.226715 | 0 | 0.202247 | 0 | 0 | 0.05159 | 0.005881 | 0 | 0 | 0 | 0.005814 | 0 | 1 | 0.134831 | false | 0.022472 | 0.044944 | 0.011236 | 0.382022 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 |