hexsha stringlengths 40 40 | size int64 5 2.06M | ext stringclasses 10
values | lang stringclasses 1
value | max_stars_repo_path stringlengths 3 248 | max_stars_repo_name stringlengths 5 125 | max_stars_repo_head_hexsha stringlengths 40 78 | max_stars_repo_licenses listlengths 1 10 | max_stars_count int64 1 191k ⌀ | max_stars_repo_stars_event_min_datetime stringlengths 24 24 ⌀ | max_stars_repo_stars_event_max_datetime stringlengths 24 24 ⌀ | max_issues_repo_path stringlengths 3 248 | max_issues_repo_name stringlengths 5 125 | max_issues_repo_head_hexsha stringlengths 40 78 | max_issues_repo_licenses listlengths 1 10 | max_issues_count int64 1 67k ⌀ | max_issues_repo_issues_event_min_datetime stringlengths 24 24 ⌀ | max_issues_repo_issues_event_max_datetime stringlengths 24 24 ⌀ | max_forks_repo_path stringlengths 3 248 | max_forks_repo_name stringlengths 5 125 | max_forks_repo_head_hexsha stringlengths 40 78 | max_forks_repo_licenses listlengths 1 10 | max_forks_count int64 1 105k ⌀ | max_forks_repo_forks_event_min_datetime stringlengths 24 24 ⌀ | max_forks_repo_forks_event_max_datetime stringlengths 24 24 ⌀ | content stringlengths 5 2.06M | avg_line_length float64 1 1.02M | max_line_length int64 3 1.03M | alphanum_fraction float64 0 1 | count_classes int64 0 1.6M | score_classes float64 0 1 | count_generators int64 0 651k | score_generators float64 0 1 | count_decorators int64 0 990k | score_decorators float64 0 1 | count_async_functions int64 0 235k | score_async_functions float64 0 1 | count_documentation int64 0 1.04M | score_documentation float64 0 1 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
9b84b07bfeb0b1498473bf71e8cf00668429868a | 1,138 | py | Python | datastruct/TreeNode.py | cocobear/LeetCode-in-Python | b4ecd5cb7122467ee479f38497faaabb17e6025e | [
"MIT"
] | null | null | null | datastruct/TreeNode.py | cocobear/LeetCode-in-Python | b4ecd5cb7122467ee479f38497faaabb17e6025e | [
"MIT"
] | null | null | null | datastruct/TreeNode.py | cocobear/LeetCode-in-Python | b4ecd5cb7122467ee479f38497faaabb17e6025e | [
"MIT"
] | null | null | null | class TreeNode:
def __init__(self, x):
self.val = x
self.left = None
self.right = None
def __str__(self, depth=0):
ret = ''
if self.right != None:
ret += self.right.__str__(depth + 1)
if not self.val:
ret += '\n'
else:
... | 27.756098 | 63 | 0.51406 | 1,066 | 0.889816 | 0 | 0 | 599 | 0.5 | 0 | 0 | 120 | 0.100167 |
9b88125439c00c982850039874ca9e2e40963ded | 17,936 | py | Python | src/test_quality_measures.py | hackalog/dimension_reduction | 18c54256f4b1f1fbfe0b99e86b6701e708b7c85c | [
"MIT"
] | 1 | 2018-10-22T11:45:45.000Z | 2018-10-22T11:45:45.000Z | src/test_quality_measures.py | hackalog/dimension_reduction | 18c54256f4b1f1fbfe0b99e86b6701e708b7c85c | [
"MIT"
] | null | null | null | src/test_quality_measures.py | hackalog/dimension_reduction | 18c54256f4b1f1fbfe0b99e86b6701e708b7c85c | [
"MIT"
] | null | null | null | import hypothesis.strategies as st
from hypothesis.extra.numpy import arrays
from hypothesis import given
import unittest
import numpy as np
from sklearn.base import BaseEstimator
import inspect
import src.quality_measures as qm
from .logging import logger
# old functions to test against while refactoring
def old_ce... | 42.301887 | 79 | 0.575992 | 1,747 | 0.097402 | 0 | 0 | 13,815 | 0.770239 | 0 | 0 | 1,085 | 0.060493 |
9b884dfe98e3224d03e56b0ff9073cf479be11aa | 797 | py | Python | addons/odoo_elasticsearch/models/trend_search_mapping.py | marionumza/vocal_v12 | 480990e919c9410903e06e7813ee92800bd6a569 | [
"Unlicense"
] | null | null | null | addons/odoo_elasticsearch/models/trend_search_mapping.py | marionumza/vocal_v12 | 480990e919c9410903e06e7813ee92800bd6a569 | [
"Unlicense"
] | null | null | null | addons/odoo_elasticsearch/models/trend_search_mapping.py | marionumza/vocal_v12 | 480990e919c9410903e06e7813ee92800bd6a569 | [
"Unlicense"
] | 1 | 2021-05-05T07:59:08.000Z | 2021-05-05T07:59:08.000Z | import logging
_logger = logging.getLogger(__name__)
from odoo import api, fields, models
class TrendSearchMapping(models.Model):
_name = 'trend.search.mapping'
_order = "sequence"
name = fields.Char(string="Keywords", required=True, help="Name of product")
trend_search_mapping_id = fields.Many2one('e... | 30.653846 | 99 | 0.667503 | 705 | 0.884567 | 0 | 0 | 378 | 0.474279 | 0 | 0 | 208 | 0.260979 |
9b897b3e2e2a162da4ba6ef2e1e00007c3d0d7d3 | 25,363 | py | Python | src/python/twitter/common/app/application.py | wfarner/commons | 42988a7a49f012665174538cca53604c7846ee86 | [
"Apache-2.0"
] | 1 | 2019-12-20T14:13:27.000Z | 2019-12-20T14:13:27.000Z | src/python/twitter/common/app/application.py | wfarner/commons | 42988a7a49f012665174538cca53604c7846ee86 | [
"Apache-2.0"
] | null | null | null | src/python/twitter/common/app/application.py | wfarner/commons | 42988a7a49f012665174538cca53604c7846ee86 | [
"Apache-2.0"
] | 1 | 2019-12-20T14:13:29.000Z | 2019-12-20T14:13:29.000Z | # ==================================================================================================
# Copyright 2011 Twitter, Inc.
# --------------------------------------------------------------------------------------------------
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use thi... | 34.791495 | 101 | 0.674644 | 23,829 | 0.939518 | 242 | 0.009541 | 720 | 0.028388 | 0 | 0 | 8,667 | 0.341718 |
9b89b21d0ec82cd3eb4f531c62145aac5544814d | 3,838 | py | Python | nas/gui/end_registration_window.py | RolandZitny/BC-NAS | df2b1c643e5dce3b48c72026b4f83f895f33b822 | [
"MIT"
] | null | null | null | nas/gui/end_registration_window.py | RolandZitny/BC-NAS | df2b1c643e5dce3b48c72026b4f83f895f33b822 | [
"MIT"
] | null | null | null | nas/gui/end_registration_window.py | RolandZitny/BC-NAS | df2b1c643e5dce3b48c72026b4f83f895f33b822 | [
"MIT"
] | null | null | null | import base64
import os
import matplotlib.pyplot as plt
import cv2
import numpy as np
from PyQt5 import uic
from PyQt5 import QtWidgets
from PyQt5 import QtMultimedia
from PyQt5 import QtMultimediaWidgets
from PyQt5.QtGui import QImage, QPixmap
from PyQt5.QtWidgets import QDesktopWidget
from nas.gui.login_stimulation_w... | 32.252101 | 94 | 0.647473 | 3,238 | 0.843669 | 0 | 0 | 384 | 0.100052 | 0 | 0 | 824 | 0.214695 |
9b8af184786b7b838926fd6c07d47b9fd8a6c329 | 445 | py | Python | testing/matplotlib_test.py | deranderemark/CigarTracer | 3f1172683c57dc7f28dd7517132014b23adfff90 | [
"Apache-2.0"
] | null | null | null | testing/matplotlib_test.py | deranderemark/CigarTracer | 3f1172683c57dc7f28dd7517132014b23adfff90 | [
"Apache-2.0"
] | 1 | 2022-02-06T15:50:07.000Z | 2022-02-06T15:50:07.000Z | testing/matplotlib_test.py | deranderemark/CigarTracer | 3f1172683c57dc7f28dd7517132014b23adfff90 | [
"Apache-2.0"
] | null | null | null | import matplotlib.pyplot as plt
# Diagramm und Achsen definieren
fig, ax = plt.subplots()
# Werte für Tabelle erstellen
table_data=[
["1", 30, 34],
["2", 20, 223],
["3", 33, 2354],
["4", 25, 234],
["5", 12, 929]
]
#Tabelle erstellen
table = ax.table(cellText=table_data, loc='center', colLabels=[... | 17.8 | 84 | 0.633708 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 157 | 0.35123 |
9b8bb3b48e86a641ba4d24045654d0c3bccfafdb | 5,242 | py | Python | venv/Lib/site-packages/func_timeout/StoppableThread.py | lijj0812/UIAutoDemo | 3e13380adeb6cf92410676ff7c125dbee598427f | [
"Apache-2.0"
] | 1 | 2021-01-12T14:39:01.000Z | 2021-01-12T14:39:01.000Z | venv/Lib/site-packages/func_timeout/StoppableThread.py | lijj0812/UIAutoDemo | 3e13380adeb6cf92410676ff7c125dbee598427f | [
"Apache-2.0"
] | 2 | 2021-06-16T19:56:35.000Z | 2021-06-16T19:57:49.000Z | venv/Lib/site-packages/func_timeout/StoppableThread.py | lijj0812/UIAutoDemo | 3e13380adeb6cf92410676ff7c125dbee598427f | [
"Apache-2.0"
] | 1 | 2020-09-17T07:56:53.000Z | 2020-09-17T07:56:53.000Z | '''
Copyright (c) 2016, 2017, 2019 Timothy Savannah All Rights Reserved.
Licensed under the Lesser GNU Public License Version 3, LGPLv3. You should have recieved a copy of this with the source distribution as
LICENSE, otherwise it is available at https://github.com/kata198/func_timeout/LICENSE
'''
import ... | 39.119403 | 166 | 0.647844 | 4,804 | 0.916444 | 0 | 0 | 0 | 0 | 0 | 0 | 3,819 | 0.728539 |
9b8fd2bf80fa07a3bd7f3ddd5254592ae0988fc9 | 190 | py | Python | pics/admin.py | Joseph-Odhiambo/Gallary | f8dfab1149f11de94519afe597fe87f4ed28b9a5 | [
"MIT"
] | 1 | 2021-05-19T12:58:15.000Z | 2021-05-19T12:58:15.000Z | pics/admin.py | HASSAN1A/Gallery | a73bd93bcecbb830b4d676c9e9dd306880cac6f2 | [
"MIT"
] | null | null | null | pics/admin.py | HASSAN1A/Gallery | a73bd93bcecbb830b4d676c9e9dd306880cac6f2 | [
"MIT"
] | null | null | null | from django.contrib import admin
from .models import Image,Areas,Category
# Register your models here.
admin.site.register(Image)
admin.site.register(Areas)
admin.site.register(Category) | 19 | 40 | 0.805263 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 28 | 0.147368 |
9b902f255bd9d45e07a2e966eeb8f841dbe8fc88 | 1,985 | py | Python | tests/lamvery/cli_test.py | rdtr/lamvery | e9334a0d258c63e6426c7cd320f691b9f21044c1 | [
"MIT"
] | 101 | 2015-11-12T11:29:20.000Z | 2020-05-24T19:26:37.000Z | tests/lamvery/cli_test.py | rdtr/lamvery | e9334a0d258c63e6426c7cd320f691b9f21044c1 | [
"MIT"
] | 45 | 2015-11-13T05:43:18.000Z | 2017-04-27T18:14:49.000Z | tests/lamvery/cli_test.py | marcy-terui/lamvery | e9334a0d258c63e6426c7cd320f691b9f21044c1 | [
"MIT"
] | 22 | 2016-01-26T00:12:57.000Z | 2019-12-13T09:06:43.000Z | # -*- coding: utf-8 -*-
from unittest import TestCase
from mock import Mock, patch
from lamvery.cli import (
main,
init,
build,
configure,
deploy,
encrypt,
encrypt_file,
events,
decrypt,
set_alias,
invoke,
rollback,
api,
generate
)
class FunctionsTestCase(TestC... | 22.816092 | 53 | 0.594458 | 1,693 | 0.852897 | 0 | 0 | 272 | 0.137028 | 0 | 0 | 441 | 0.222166 |
9b906d0ca190514b42e0b5edafba1d709df76a02 | 569 | py | Python | db-test.py | alexolotl/apt-hunt | 25d2a2d565b0b694a8f5e3442ba429ae99688e54 | [
"MIT"
] | null | null | null | db-test.py | alexolotl/apt-hunt | 25d2a2d565b0b694a8f5e3442ba429ae99688e54 | [
"MIT"
] | null | null | null | db-test.py | alexolotl/apt-hunt | 25d2a2d565b0b694a8f5e3442ba429ae99688e54 | [
"MIT"
] | null | null | null | import sqlite3
from util import post_listing_to_slack
from slackclient import SlackClient
import settings
sc = SlackClient(settings.SLACK_TOKEN)
con = sqlite3.connect('listings.db')
# with con:
# con.row_factory = sqlite3.Row
# cur = con.cursor()
# # print("SQLite version: %s" % data)
# cur.execute("... | 22.76 | 50 | 0.669596 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 382 | 0.671353 |
9b9103f77dd912b77e605c95f3235abd9dcb9a29 | 15,630 | py | Python | src/utils.py | asrashley/dash-live | 1ffbc57896e4e46855a42af6ef79a1865ebfce55 | [
"Apache-2.0"
] | 2 | 2019-11-02T06:26:29.000Z | 2020-05-15T16:54:20.000Z | src/utils.py | asrashley/dash-live | 1ffbc57896e4e46855a42af6ef79a1865ebfce55 | [
"Apache-2.0"
] | 1 | 2020-01-20T17:20:54.000Z | 2020-01-21T08:38:30.000Z | src/utils.py | asrashley/dash-live | 1ffbc57896e4e46855a42af6ef79a1865ebfce55 | [
"Apache-2.0"
] | null | null | null | #############################################################################
#
# 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
#
# ... | 32.63048 | 130 | 0.55675 | 4,140 | 0.264875 | 0 | 0 | 64 | 0.004095 | 0 | 0 | 3,669 | 0.234741 |
9b9174eb28a0ab4b95d4146848ae09c6b7a36f4f | 1,883 | py | Python | network.py | YanhengWang/Draughts | ad19ccbd3c4fc0defda68c45ed8f2dd14969f2a3 | [
"Apache-2.0"
] | null | null | null | network.py | YanhengWang/Draughts | ad19ccbd3c4fc0defda68c45ed8f2dd14969f2a3 | [
"Apache-2.0"
] | 1 | 2020-10-12T00:33:54.000Z | 2020-10-12T00:33:54.000Z | network.py | YanhengWang/Draughts | ad19ccbd3c4fc0defda68c45ed8f2dd14969f2a3 | [
"Apache-2.0"
] | null | null | null | from utils import PATH_LABEL
from utils import PATH_DATA_FOLDER
import pickle
import torch
import torch.nn as nn
import torch.utils.data as dat
class ResBlock(nn.Module):
def __init__(self, inChannels, outChannels):
super(ResBlock, self).__init__()
self.matchDimension = None
if inChannels != outChannels:
... | 27.289855 | 92 | 0.677111 | 1,733 | 0.92034 | 0 | 0 | 0 | 0 | 0 | 0 | 14 | 0.007435 |
9b921382771a3e80faea212dc2044b24ad49e32b | 6,623 | py | Python | src/client/app/__init__.py | ZackPashkin/toloka-kit | 8f650e5d8cdded1949ca633cf78f9b851ce839bb | [
"Apache-2.0"
] | 153 | 2021-02-06T13:41:11.000Z | 2022-03-19T17:51:01.000Z | src/client/app/__init__.py | ZackPashkin/toloka-kit | 8f650e5d8cdded1949ca633cf78f9b851ce839bb | [
"Apache-2.0"
] | 29 | 2021-01-15T12:54:37.000Z | 2022-02-07T07:45:32.000Z | src/client/app/__init__.py | ZackPashkin/toloka-kit | 8f650e5d8cdded1949ca633cf78f9b851ce839bb | [
"Apache-2.0"
] | 17 | 2021-01-29T15:20:04.000Z | 2022-01-30T07:21:03.000Z | __all__ = [
'AppProject',
'App',
'AppItem',
'AppItemsCreateRequest',
'AppBatch',
'AppBatchCreateRequest'
]
import datetime
import decimal
from enum import unique
from typing import Dict, Any, List
from ..primitives.base import BaseTolokaObject
from ..project.field_spec import FieldSpec
from ...... | 30.380734 | 118 | 0.653782 | 6,196 | 0.935528 | 0 | 0 | 640 | 0.096633 | 0 | 0 | 3,868 | 0.584025 |
9b926fbc1417f4ebd631923a6169eb196f0aff02 | 760 | py | Python | WebApp/main/utility/StringUtility.py | georg-wenzel/ml-data-smell-detection | 7dddd401ca1f1a830dfd8b00760659911e5b1086 | [
"MIT"
] | 1 | 2022-03-29T14:46:40.000Z | 2022-03-29T14:46:40.000Z | WebApp/main/utility/StringUtility.py | georg-wenzel/ml-data-smell-detection | 7dddd401ca1f1a830dfd8b00760659911e5b1086 | [
"MIT"
] | null | null | null | WebApp/main/utility/StringUtility.py | georg-wenzel/ml-data-smell-detection | 7dddd401ca1f1a830dfd8b00760659911e5b1086 | [
"MIT"
] | 1 | 2021-06-13T08:24:46.000Z | 2021-06-13T08:24:46.000Z | # Utility functions for Strings (i.e. storing common strings once)
#define common strings
ERR_MISSING_KEY = "The field(s) {0} must be filled in this form."
ERR_INVALID_KEY = "The field '{0}' contains an invalid value."
ERR_UNAUTHORIZED = "The logged in user does not have access to this value: {0}"
MSG_FINISHED_TRAININ... | 54.285714 | 138 | 0.709211 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 496 | 0.652632 |
9b93e34b4881434ea8a11345bd79b7ea4e4e91b3 | 2,184 | py | Python | lib/python2.7/site-packages/pyami/primefactor.py | leschzinerlab/myami-3.2-freeHand | 974b8a48245222de0d9cfb0f433533487ecce60d | [
"MIT"
] | 6 | 2018-05-10T19:12:53.000Z | 2021-05-19T21:11:56.000Z | pyami/primefactor.py | vosslab/ctfeval | 6cfc648f91c318c3a46a959e4771c3d16d8e741a | [
"Apache-2.0"
] | 1 | 2017-04-15T11:04:39.000Z | 2017-04-17T20:21:53.000Z | pyami/primefactor.py | vossman/ctfeval | 6cfc648f91c318c3a46a959e4771c3d16d8e741a | [
"Apache-2.0"
] | 1 | 2019-09-05T20:58:37.000Z | 2019-09-05T20:58:37.000Z | #!/usr/bin/env python
import sys
import math
maxprime = 12
twomult = 2**2
#====================
def prime_factors(n):
""" Return the prime factors of the given number. """
# < 1 is a special case
if n <= 1:
return [1]
factors = []
lastresult = n
while True:
if lastresult == 1:
break
c = 2
while True... | 18.991304 | 63 | 0.594322 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 618 | 0.282967 |
9b94d42c4e5c72f5294c49e1d55e12f33a9b3855 | 2,027 | py | Python | visualization/draw.py | DougMHu/roomba-obstacle-mapping | 019b6108c1967c7daabe7b4795cfac7ef0e79cf7 | [
"MIT"
] | 3 | 2018-05-26T20:41:27.000Z | 2020-10-19T12:40:42.000Z | visualization/draw.py | DougMHu/roomba-obstacle-mapping | 019b6108c1967c7daabe7b4795cfac7ef0e79cf7 | [
"MIT"
] | null | null | null | visualization/draw.py | DougMHu/roomba-obstacle-mapping | 019b6108c1967c7daabe7b4795cfac7ef0e79cf7 | [
"MIT"
] | 1 | 2017-01-31T09:47:21.000Z | 2017-01-31T09:47:21.000Z | # MIT License
# Copyright (c) 2016 Aashiq Ahmed, Shuai Chen, Meha Deora, Douglas Hu
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rig... | 25.658228 | 80 | 0.716823 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1,326 | 0.654169 |
9b96be5064867858493bac891020397805ad69fe | 251 | py | Python | igphotoprofile.py | raflimkamal/python_project | 6d3321612226fa15b9fcafe4a301160f63d81213 | [
"MIT"
] | null | null | null | igphotoprofile.py | raflimkamal/python_project | 6d3321612226fa15b9fcafe4a301160f63d81213 | [
"MIT"
] | null | null | null | igphotoprofile.py | raflimkamal/python_project | 6d3321612226fa15b9fcafe4a301160f63d81213 | [
"MIT"
] | null | null | null | #!/usr/bin/env python
# coding: utf-8
# In[2]:
pip install instaloader
# In[4]:
import instaloader
# In[6]:
ig = instaloader.Instaloader()
dp = input("Enter Insta Username:")
ig.download_profile(dp, profile_pic_only = True)
# In[ ]:
| 8.366667 | 48 | 0.649402 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 91 | 0.36255 |
9b9ade24b6474ca9ac882881c781ddb3dc8e1ab1 | 2,180 | py | Python | activate.py | cassidoxa/bottoman | 9d04331794ffb8bb745fc175c15db6d4a1f5714c | [
"MIT"
] | null | null | null | activate.py | cassidoxa/bottoman | 9d04331794ffb8bb745fc175c15db6d4a1f5714c | [
"MIT"
] | null | null | null | activate.py | cassidoxa/bottoman | 9d04331794ffb8bb745fc175c15db6d4a1f5714c | [
"MIT"
] | null | null | null | import json
import urllib.request
from bottoman import TwitchBot
import config
from db.db import DatabaseManager
def get_user_id_display(user):
"""
uses twitch's API to get a user's token with their (case insensitive)
user name
"""
client_id = config.client_id
token = "srtajsl3jjbhhtfrv... | 29.459459 | 77 | 0.559174 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 812 | 0.372477 |
9b9e8192f42c44f946f004808b8e37a13a83e0b0 | 478 | py | Python | waveshare_snake.py | AndrewCarterUK/MiniGame | 6d699c045e84ee3834f23eb0483245195438eff7 | [
"MIT"
] | null | null | null | waveshare_snake.py | AndrewCarterUK/MiniGame | 6d699c045e84ee3834f23eb0483245195438eff7 | [
"MIT"
] | null | null | null | waveshare_snake.py | AndrewCarterUK/MiniGame | 6d699c045e84ee3834f23eb0483245195438eff7 | [
"MIT"
] | null | null | null | from minigame.waveshare.button import Button
from minigame.waveshare.display import Display
from minigame.games.snake import Snake
WIDTH = 20
HEIGHT = 20
STEP_TIME = 0.5
BLOCK_SIZE = 32
def main():
display = Display()
l_button = Button(5)
r_button = Button(26)
u_button = Button(6)
d_button = Butt... | 19.916667 | 92 | 0.698745 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 10 | 0.020921 |
9b9f8f5cfe54f976ada38f7cf0db4c9ffc2c1571 | 8,636 | py | Python | jumodjango/urls.py | jumoconnect/openjumo | 828d993bfbb83777d10a68de6964c7d5bb2c7bd0 | [
"MIT"
] | 5 | 2015-03-11T18:59:46.000Z | 2018-08-17T17:49:45.000Z | jumodjango/urls.py | kmrifat/openjumo | 828d993bfbb83777d10a68de6964c7d5bb2c7bd0 | [
"MIT"
] | 2 | 2020-06-05T16:52:17.000Z | 2021-02-08T20:24:26.000Z | jumodjango/urls.py | kmrifat/openjumo | 828d993bfbb83777d10a68de6964c7d5bb2c7bd0 | [
"MIT"
] | 6 | 2016-02-04T00:45:30.000Z | 2021-07-07T17:14:50.000Z | from api.api_v1 import api_urls
from django.conf.urls.defaults import *
from django.conf import settings
from django.contrib import admin
admin.autodiscover()
urlpatterns = patterns('',
)
''' RANDOM URLs '''
urlpatterns += patterns('etc.views',
url(r'^about/?$', 'about', name = 'about'),
url(r'^help/?$', 'h... | 45.452632 | 125 | 0.54736 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6,052 | 0.700787 |
9ba08896288342be18a3bdfe4d777157062a927c | 2,830 | py | Python | modules/layers.py | vliu15/munit | 5789d96590519d729f89c9501eba7692fa7054ef | [
"MIT"
] | 3 | 2021-03-04T01:48:03.000Z | 2021-12-16T06:55:10.000Z | modules/layers.py | vliu15/munit | 5789d96590519d729f89c9501eba7692fa7054ef | [
"MIT"
] | null | null | null | modules/layers.py | vliu15/munit | 5789d96590519d729f89c9501eba7692fa7054ef | [
"MIT"
] | null | null | null | # The MIT License
#
# Copyright (c) 2020 Vincent Liu
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, mer... | 36.753247 | 84 | 0.674558 | 1,678 | 0.592933 | 0 | 0 | 280 | 0.09894 | 0 | 0 | 1,183 | 0.418021 |
9ba3741e685c1d558d552dcb021080523937b319 | 721 | py | Python | lab_new/locust/locustfile.py | mwardbopp/f5-big-iq-lab | 70d5b766571f8db8b3bc744e98c183dbdd500089 | [
"Apache-2.0"
] | 18 | 2018-07-17T15:17:16.000Z | 2021-12-05T21:13:26.000Z | lab_new/locust/locustfile.py | mwardbopp/f5-big-iq-lab | 70d5b766571f8db8b3bc744e98c183dbdd500089 | [
"Apache-2.0"
] | 34 | 2018-09-11T04:43:47.000Z | 2021-04-19T15:58:50.000Z | lab_new/locust/locustfile.py | mwardbopp/f5-big-iq-lab | 70d5b766571f8db8b3bc744e98c183dbdd500089 | [
"Apache-2.0"
] | 54 | 2018-07-30T12:23:33.000Z | 2021-06-11T17:54:28.000Z | import time
from locust import HttpUser, task, between
# https://docs.locust.io/en/stable/quickstart.html
class QuickstartUser(HttpUser):
wait_time = between(5, 10)
@task
def index_page(self):
self.client.get("/index.php", verify=False)
self.client.get("/contact", verify=False)
se... | 34.333333 | 105 | 0.65742 | 612 | 0.848821 | 0 | 0 | 413 | 0.572816 | 0 | 0 | 204 | 0.28294 |
9ba44cd9d91cc8c729aafc0cddc794fc2187f3f9 | 25,015 | py | Python | lizardanalysis/calculations/aep_pep_test.py | JojoReikun/ClimbingLizardDLCAnalysis | 6cc38090217a3ffd4860ef6d06ba7967d3c10b7c | [
"MIT"
] | 1 | 2021-03-09T19:12:44.000Z | 2021-03-09T19:12:44.000Z | lizardanalysis/calculations/aep_pep_test.py | JojoReikun/ClimbingLizardDLCAnalysis | 6cc38090217a3ffd4860ef6d06ba7967d3c10b7c | [
"MIT"
] | null | null | null | lizardanalysis/calculations/aep_pep_test.py | JojoReikun/ClimbingLizardDLCAnalysis | 6cc38090217a3ffd4860ef6d06ba7967d3c10b7c | [
"MIT"
] | null | null | null | def aep_pep_test(**kwargs):
"""
Calculates two different things:
1.) The x and y coordinates of the AEP and PEP, relative to the coxa of a respective leg
2.) The swing phases and the stance phases, identifying on a frame by frame basis
Return: results data frame with 30 key value pairs:
x6 all... | 49.534653 | 136 | 0.625625 | 2,785 | 0.111333 | 0 | 0 | 0 | 0 | 0 | 0 | 10,788 | 0.431261 |
9ba6402b03516602907bdd9d7c0d28f9b0666716 | 1,601 | py | Python | python/test.py | drulm/Spark_Knapsack | ef8ab8b6ac6762391b63ff29ebf857a65f98698d | [
"Apache-2.0"
] | 7 | 2018-04-18T00:51:29.000Z | 2021-05-30T12:58:36.000Z | python/test.py | darrell-ulm/Spark_Knapsack | ef8ab8b6ac6762391b63ff29ebf857a65f98698d | [
"Apache-2.0"
] | null | null | null | python/test.py | darrell-ulm/Spark_Knapsack | ef8ab8b6ac6762391b63ff29ebf857a65f98698d | [
"Apache-2.0"
] | 2 | 2019-05-28T03:13:26.000Z | 2019-11-22T19:50:14.000Z | # --------------------------------------------
# Test the Approximate Knapsack function test
# --------------------------------------------
# Pull in the knapsack library.
import random
from pyspark.sql import SparkSession
from knapsack import knapsack
# Create the SparkContext.
sc = SparkSession \
.builder \
... | 26.245902 | 107 | 0.634603 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 863 | 0.539038 |
9ba65d1715a7fcfaf9934b6a6bcb75b319f1120c | 413 | py | Python | mysite/blog/views.py | josonle/LearningDjango | 62558aa141c5872c2380e5daa336da199a54b0e1 | [
"MIT"
] | 1 | 2019-02-19T07:38:02.000Z | 2019-02-19T07:38:02.000Z | mysite/blog/views.py | josonle/LearningDjango | 62558aa141c5872c2380e5daa336da199a54b0e1 | [
"MIT"
] | null | null | null | mysite/blog/views.py | josonle/LearningDjango | 62558aa141c5872c2380e5daa336da199a54b0e1 | [
"MIT"
] | null | null | null | from django.shortcuts import render,get_object_or_404
from .models import BlogArticles
# Create your views here.
def blog_title(request):
blogs=BlogArticles.objects.all()
return render(request,"blog/titles.html",{"blogs":blogs})
def article(request,a_id):
blog=get_object_or_404(BlogArticles,id=a_id)
publish_time=... | 34.416667 | 80 | 0.79661 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 84 | 0.20339 |
9ba95d022de0cbe77839799064d678253b042077 | 204 | py | Python | tests/test_gluupostgres.py | danilosoarescardoso/cloud-native-edition | b8aa66119dc4440b1ca3741a4065c9ae7feb42fb | [
"Apache-2.0"
] | 1 | 2021-04-04T04:25:49.000Z | 2021-04-04T04:25:49.000Z | tests/test_gluupostgres.py | danilosoarescardoso/cloud-native-edition | b8aa66119dc4440b1ca3741a4065c9ae7feb42fb | [
"Apache-2.0"
] | null | null | null | tests/test_gluupostgres.py | danilosoarescardoso/cloud-native-edition | b8aa66119dc4440b1ca3741a4065c9ae7feb42fb | [
"Apache-2.0"
] | null | null | null | import pygluu.kubernetes.postgres as module0
from pygluu.kubernetes.postgres import Postgres
def test_base_exception():
try:
var0 = module0.Postgres()
except BaseException:
pass
| 20.4 | 47 | 0.72549 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
9ba99aa02744fe90eebce52ab7ecf4ce0854c775 | 1,367 | py | Python | Medium/918. Maximum Sum Circular Subarray/solution (1).py | czs108/LeetCode-Solutions | 889f5b6a573769ad077a6283c058ed925d52c9ec | [
"MIT"
] | 3 | 2020-05-09T12:55:09.000Z | 2022-03-11T18:56:05.000Z | Medium/918. Maximum Sum Circular Subarray/solution (1).py | czs108/LeetCode-Solutions | 889f5b6a573769ad077a6283c058ed925d52c9ec | [
"MIT"
] | null | null | null | Medium/918. Maximum Sum Circular Subarray/solution (1).py | czs108/LeetCode-Solutions | 889f5b6a573769ad077a6283c058ed925d52c9ec | [
"MIT"
] | 1 | 2022-03-11T18:56:16.000Z | 2022-03-11T18:56:16.000Z | # 918. Maximum Sum Circular Subarray
# Runtime: 1028 ms, faster than 5.09% of Python3 online submissions for Maximum Sum Circular Subarray.
# Memory Usage: 18.6 MB, less than 33.98% of Python3 online submissions for Maximum Sum Circular Subarray.
import math
class Solution:
def maxSubarraySumCircular(self, num... | 35.973684 | 106 | 0.567666 | 1,103 | 0.806876 | 0 | 0 | 0 | 0 | 0 | 0 | 244 | 0.178493 |
9ba9d75f770e59ab5f8bd4c1745fa1e171a92981 | 10,644 | py | Python | testing.py | gustxsr/learning-with-assemblies | 4158829adf4500a9ae868ca7c64ffef90753c66b | [
"MIT"
] | null | null | null | testing.py | gustxsr/learning-with-assemblies | 4158829adf4500a9ae868ca7c64ffef90753c66b | [
"MIT"
] | null | null | null | testing.py | gustxsr/learning-with-assemblies | 4158829adf4500a9ae868ca7c64ffef90753c66b | [
"MIT"
] | null | null | null |
import numpy as np
import matplotlib.pyplot as plt
from scipy.signal import convolve
from matplotlib.gridspec import GridSpec
import matplotlib as mpl
rng = np.random.default_rng()
def k_cap(input, cap_size):
"""
Given a vector input it returns the highest cap_size
entries from cap_zie
... | 37.087108 | 217 | 0.613209 | 9,504 | 0.892897 | 0 | 0 | 0 | 0 | 0 | 0 | 3,228 | 0.303269 |
9bab281692147103f4b861c83d053ce8c6a1c16f | 4,398 | py | Python | src/chatstats.py | brendancsmith/cohort-facebook | a7b37d14b7152349930bc10f69cb72446d6c3581 | [
"MIT"
] | null | null | null | src/chatstats.py | brendancsmith/cohort-facebook | a7b37d14b7152349930bc10f69cb72446d6c3581 | [
"MIT"
] | null | null | null | src/chatstats.py | brendancsmith/cohort-facebook | a7b37d14b7152349930bc10f69cb72446d6c3581 | [
"MIT"
] | null | null | null | from collections import Counter, defaultdict
from datetime import datetime
from statistics import mean
from dateutil.parser import parse as parse_datetime
from dateutil import rrule
def num_comments_by_user(comments):
commenters = (comment['from']['name'] for comment in comments)
counter = Counter(commenters... | 29.918367 | 91 | 0.648931 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 224 | 0.050932 |
9bac9dcd120d634f437ebef6f5de2fb78cd0ef74 | 741 | py | Python | app/model/user_signup.py | dwdraugr/YADS | c8036d8196a3158636aaa4f1910033e70ec8ecb4 | [
"Apache-2.0"
] | 3 | 2019-09-02T11:26:58.000Z | 2019-12-06T15:54:38.000Z | app/model/user_signup.py | dwdraugr/YADS | c8036d8196a3158636aaa4f1910033e70ec8ecb4 | [
"Apache-2.0"
] | null | null | null | app/model/user_signup.py | dwdraugr/YADS | c8036d8196a3158636aaa4f1910033e70ec8ecb4 | [
"Apache-2.0"
] | null | null | null | import app.model.model as model
import hashlib
class UserSignup(model.Model):
def __init__(self):
super(UserSignup, self).__init__()
def signup(self, username, password, email):
cursor = self.matchadb.cursor(dictionary=True)
query = [
username,
email,
]... | 35.285714 | 94 | 0.584345 | 692 | 0.933873 | 0 | 0 | 0 | 0 | 0 | 0 | 142 | 0.191633 |
9bae71f7a1d534c3b03ab7c28df3edc847994f0b | 2,125 | py | Python | utils/lsms/compositional_histogram_cutoff.py | allaffa/HydraGNN | b48f75cd3fe1b0d03bae9af3e6bdc2bb29f8b9c6 | [
"BSD-3-Clause"
] | 1 | 2022-01-30T16:50:51.000Z | 2022-01-30T16:50:51.000Z | utils/lsms/compositional_histogram_cutoff.py | allaffa/HydraGNN | b48f75cd3fe1b0d03bae9af3e6bdc2bb29f8b9c6 | [
"BSD-3-Clause"
] | 1 | 2022-02-03T11:45:53.000Z | 2022-02-09T17:59:37.000Z | utils/lsms/compositional_histogram_cutoff.py | kshitij-v-mehta/HydraGNN | d27958270b2beb35f98e4403239e3c5c77ad4a04 | [
"BSD-3-Clause"
] | null | null | null | import os
import shutil
import numpy as np
from tqdm import tqdm
import matplotlib.pyplot as plt
def find_bin(comp, nbins):
bins = np.linspace(0, 1, nbins)
for bi in range(len(bins) - 1):
if comp > bins[bi] and comp < bins[bi + 1]:
return bi
return nbins - 1
def compositional_histogr... | 27.960526 | 91 | 0.610353 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 348 | 0.163765 |
9baf6c3804173cb531cd1c2955cba4bc19bd4390 | 109 | py | Python | CVcontact/urls.py | siavashMehran/Portfolio | a592ec51122d96e8e336365fd3cd039a7f223221 | [
"MIT"
] | null | null | null | CVcontact/urls.py | siavashMehran/Portfolio | a592ec51122d96e8e336365fd3cd039a7f223221 | [
"MIT"
] | null | null | null | CVcontact/urls.py | siavashMehran/Portfolio | a592ec51122d96e8e336365fd3cd039a7f223221 | [
"MIT"
] | null | null | null | from django.urls import path
from .views import contactMe
urlpatterns = [
path('contact', contactMe)
]
| 13.625 | 30 | 0.724771 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 9 | 0.082569 |
9bb0067ad50b3ebfd94976cc78cce86faed75925 | 1,256 | py | Python | PointMatcher/actions/export.py | daisatojp/PointMatcher | 927bd4dd676b18da763ccaab2f429f27de281710 | [
"MIT"
] | 2 | 2021-01-05T03:42:50.000Z | 2022-03-16T07:17:02.000Z | PointMatcher/actions/export.py | daisatojp/PointMatcher | 927bd4dd676b18da763ccaab2f429f27de281710 | [
"MIT"
] | 4 | 2021-01-07T06:28:01.000Z | 2021-01-18T11:59:56.000Z | PointMatcher/actions/export.py | daisatojp/PointMatcher | 927bd4dd676b18da763ccaab2f429f27de281710 | [
"MIT"
] | null | null | null | import os.path as osp
from PyQt5.QtGui import QIcon
from PyQt5.QtWidgets import QAction
from PyQt5.QtWidgets import QFileDialog
from PointMatcher.utils.filesystem import icon_path
class ExportAction(QAction):
def __init__(self, parent):
super(ExportAction, self).__init__('Export', parent)
self.p ... | 35.885714 | 75 | 0.642516 | 1,073 | 0.854299 | 0 | 0 | 0 | 0 | 0 | 0 | 106 | 0.084395 |
9bb08d27951cdcbd92a25a4408ad1a1b8fb55f34 | 1,345 | py | Python | test/test_CommandHead.py | jcandan/WonderPy | ee82322b082e94015258b34b27f23501f8130fa2 | [
"MIT"
] | 46 | 2018-07-31T20:30:41.000Z | 2022-03-23T17:14:51.000Z | test/test_CommandHead.py | jcandan/WonderPy | ee82322b082e94015258b34b27f23501f8130fa2 | [
"MIT"
] | 24 | 2018-08-01T09:59:29.000Z | 2022-02-26T20:57:51.000Z | test/test_CommandHead.py | jcandan/WonderPy | ee82322b082e94015258b34b27f23501f8130fa2 | [
"MIT"
] | 24 | 2018-08-01T19:14:31.000Z | 2021-02-18T13:26:40.000Z | import unittest
from mock import Mock
from test.robotTestUtil import RobotTestUtil
class MyTestCase(unittest.TestCase):
def test_head_turn(self):
robot = RobotTestUtil.make_fake_dash()
robot.stage_cmds = Mock()
m = robot.stage_cmds
robot.commands.head.do_pan_angle (90)
... | 40.757576 | 82 | 0.646097 | 1,210 | 0.899628 | 0 | 0 | 0 | 0 | 0 | 0 | 110 | 0.081784 |
9bb204788fee823d3cdd79e26af5c6bd4b825e8a | 3,866 | py | Python | feature_options.py | soarsmu/HERMES | 9b38eedd1f7fcc3321048cc25d15c38268e6fd0b | [
"MIT"
] | 2 | 2022-01-15T11:31:40.000Z | 2022-03-09T11:27:28.000Z | feature_options.py | soarsmu/HERMES | 9b38eedd1f7fcc3321048cc25d15c38268e6fd0b | [
"MIT"
] | null | null | null | feature_options.py | soarsmu/HERMES | 9b38eedd1f7fcc3321048cc25d15c38268e6fd0b | [
"MIT"
] | null | null | null | import click
class ExperimentOption():
def __init__(self):
self.data_set_size = -1
self.ignore_number = True
self.use_github_issue = True
self.use_jira_ticket = True
self.use_comments = True
self.use_bag_of_word = True
self.positive_weights = [0.5]
s... | 51.546667 | 99 | 0.693999 | 734 | 0.18986 | 0 | 0 | 0 | 0 | 0 | 0 | 585 | 0.151319 |
9bb22f65833ccdf573c2ff6580ffe37f01d473f8 | 247 | py | Python | sciapp/action/advanced/macros.py | Pad0y/imagepy | 23f41b64ade02f94b566b0d23a4b6459c1a1578d | [
"BSD-4-Clause"
] | null | null | null | sciapp/action/advanced/macros.py | Pad0y/imagepy | 23f41b64ade02f94b566b0d23a4b6459c1a1578d | [
"BSD-4-Clause"
] | null | null | null | sciapp/action/advanced/macros.py | Pad0y/imagepy | 23f41b64ade02f94b566b0d23a4b6459c1a1578d | [
"BSD-4-Clause"
] | null | null | null | class Macros:
def __init__(self, title, cmds):
self.title = title
self.cmds = cmds
def __call__(self):
return self
def start(self, app, para=None, callafter=None):
app.run_macros(self.cmds, callafter)
| 22.454545 | 52 | 0.615385 | 246 | 0.995951 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
9bb4070df0345465e234b3e6738bbb40c587c512 | 2,038 | py | Python | py_randomprime/__init__.py | UltiNaruto/py-randomprime | 597d3636c2e40e11ed92d4808200ded879ccb244 | [
"MIT"
] | null | null | null | py_randomprime/__init__.py | UltiNaruto/py-randomprime | 597d3636c2e40e11ed92d4808200ded879ccb244 | [
"MIT"
] | 2 | 2021-05-24T18:05:11.000Z | 2021-05-31T08:07:29.000Z | py_randomprime/__init__.py | henriquegemignani/py-randomprime | aac48b44761cbb8d857a4d72e06dfac17efc1fae | [
"MIT"
] | 2 | 2021-08-18T01:17:19.000Z | 2021-11-26T15:08:34.000Z | import copy
import os
import json
from pathlib import Path
from typing import Callable, Optional
from . import rust, version
class BaseProgressNotifier:
def notify_total_bytes(self, total_size: int):
raise NotImplementedError()
def notify_writing_file(self, file_name: bytes, file_bytes: int):
... | 29.536232 | 111 | 0.723749 | 1,098 | 0.538763 | 0 | 0 | 0 | 0 | 0 | 0 | 118 | 0.0579 |
9bb514fb57dd5b2a6965770909c4eb7274835dca | 3,453 | py | Python | secistsploit/modules/auxiliary/whatweb.py | reneaicisneros/SecistSploit | b4e1bb0a213bee39c3bb79ab36e03e19122b80c0 | [
"MIT"
] | 15 | 2018-12-06T16:03:32.000Z | 2021-06-23T01:17:00.000Z | secistsploit/modules/auxiliary/whatweb.py | reneaicisneros/SecistSploit | b4e1bb0a213bee39c3bb79ab36e03e19122b80c0 | [
"MIT"
] | null | null | null | secistsploit/modules/auxiliary/whatweb.py | reneaicisneros/SecistSploit | b4e1bb0a213bee39c3bb79ab36e03e19122b80c0 | [
"MIT"
] | 6 | 2019-03-01T04:10:00.000Z | 2020-02-26T08:43:54.000Z | # -*- coding: UTF-8 -*-
import os
from secistsploit.core.exploit import *
from secistsploit.core.http.http_client import HTTPClient
class Exploit(HTTPClient):
__info__ = {
"name": "whatweb",
"description": "whatweb",
"authors": (
"jjiushi",
),
"references": (
... | 34.188119 | 141 | 0.435274 | 3,318 | 0.960904 | 0 | 0 | 0 | 0 | 0 | 0 | 1,027 | 0.297423 |
9bb942cefeb3547baf593097bb2c4998d052f1b8 | 3,285 | py | Python | pygnss/__init__.py | nmerlene/pygnss | 9dc59e57cf5a4bdf0ca56c2b6a23d622ffda4c5a | [
"MIT"
] | null | null | null | pygnss/__init__.py | nmerlene/pygnss | 9dc59e57cf5a4bdf0ca56c2b6a23d622ffda4c5a | [
"MIT"
] | null | null | null | pygnss/__init__.py | nmerlene/pygnss | 9dc59e57cf5a4bdf0ca56c2b6a23d622ffda4c5a | [
"MIT"
] | null | null | null | from pathlib import Path
import logging
import xarray
from time import time
from typing import Union
#
from .io import opener
from .rinex2 import rinexnav2, _scan2
from .rinex3 import rinexnav3, _scan3
# for NetCDF compression. too high slows down with little space savings.
COMPLVL = 1
def readrinex(rinexfn: Path, o... | 28.318966 | 120 | 0.595129 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 759 | 0.23105 |
9bb96ea949af7533581d8e4cca76f381e779a9b0 | 5,201 | py | Python | classroom/pref_graph.py | norabelrose/whisper | 79642bab696f3e166b6af61a447602e8e5d58270 | [
"MIT"
] | null | null | null | classroom/pref_graph.py | norabelrose/whisper | 79642bab696f3e166b6af61a447602e8e5d58270 | [
"MIT"
] | null | null | null | classroom/pref_graph.py | norabelrose/whisper | 79642bab696f3e166b6af61a447602e8e5d58270 | [
"MIT"
] | null | null | null | from typing import TYPE_CHECKING
import networkx as nx
from .fas import eades_fas
if TYPE_CHECKING: # Prevent circular import
from .pref_dag import PrefDAG
class PrefGraph(nx.DiGraph):
"""
`PrefGraph` represents a possibly cyclic set of preferences over clips as a weighted directed graph.
Edge weigh... | 42.284553 | 104 | 0.635455 | 5,033 | 0.967699 | 0 | 0 | 881 | 0.169391 | 0 | 0 | 2,223 | 0.427418 |
9bbc0decb0390376acbaa65e5a7c58faddf9f153 | 516 | py | Python | scaffolder/templates/django/views.py | javidgon/wizard | a75a4c10f84c756c2466c9afaaadf3b2c0cf3a43 | [
"MIT"
] | null | null | null | scaffolder/templates/django/views.py | javidgon/wizard | a75a4c10f84c756c2466c9afaaadf3b2c0cf3a43 | [
"MIT"
] | null | null | null | scaffolder/templates/django/views.py | javidgon/wizard | a75a4c10f84c756c2466c9afaaadf3b2c0cf3a43 | [
"MIT"
] | null | null | null | from __future__ import unicode_literals
from django.views import generic
from .models import {% for model in app.models %}{{ model.name }}{% if not loop.last %}, {% endif %}{% endfor %}
{% for model in app.models %}class {{ model.name }}IndexView(generic.ListView):
model = {{ model.name }}
template_name = '... | 30.352941 | 112 | 0.656977 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 77 | 0.149225 |
9bbcdfbd01a5563f9c4786b31c8c24dcfa3b565b | 683 | py | Python | hisitter/reviews/permissions.py | babysitter-finder/backend | 5c37c6876ca13b5794ac44e0342b810426acbc76 | [
"MIT"
] | 1 | 2021-02-25T01:02:40.000Z | 2021-02-25T01:02:40.000Z | hisitter/reviews/permissions.py | babysitter-finder/backend | 5c37c6876ca13b5794ac44e0342b810426acbc76 | [
"MIT"
] | null | null | null | hisitter/reviews/permissions.py | babysitter-finder/backend | 5c37c6876ca13b5794ac44e0342b810426acbc76 | [
"MIT"
] | 1 | 2020-11-23T20:57:47.000Z | 2020-11-23T20:57:47.000Z | """ Reviews permissions."""
# Python
import logging
# Django Rest Framework
from rest_framework.permissions import BasePermission
class IsServiceOwner(BasePermission):
""" This permission allow determine if the user
is a client, if not permission is denied.
"""
def has_permission(self, request,... | 28.458333 | 75 | 0.628111 | 547 | 0.800878 | 0 | 0 | 0 | 0 | 0 | 0 | 267 | 0.390922 |
9bbd9c4b8b498fde19563e3848c89d37d52b9838 | 1,678 | py | Python | pk.py | CnybTseng/SOSNet | 9f1e96380388dde75fe0737ec0b3516669054205 | [
"MIT"
] | null | null | null | pk.py | CnybTseng/SOSNet | 9f1e96380388dde75fe0737ec0b3516669054205 | [
"MIT"
] | null | null | null | pk.py | CnybTseng/SOSNet | 9f1e96380388dde75fe0737ec0b3516669054205 | [
"MIT"
] | null | null | null | import sys
import torch
import timeit
sys.path.append('../JDE')
from mot.models.backbones import ShuffleNetV2
from sosnet import SOSNet
if __name__ == '__main__':
print('SOSNet PK ShuffleNetV2')
model1 = ShuffleNetV2(
stage_repeat={'stage2': 4, 'stage3': 8, 'stage4': 4},
stage_out_ch... | 37.288889 | 85 | 0.567342 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 318 | 0.189511 |
9bbda2f39a11084b661e8fe58491f418c2a36b6f | 2,255 | py | Python | test/generate_netmhcpan_functions.py | til-unc/mhcgnomes | 0bfbe193daeb7cd38d958222f6071dd657e9fb6e | [
"Apache-2.0"
] | 6 | 2020-10-27T15:31:32.000Z | 2020-11-29T03:26:06.000Z | test/generate_netmhcpan_functions.py | til-unc/mhcgnomes | 0bfbe193daeb7cd38d958222f6071dd657e9fb6e | [
"Apache-2.0"
] | 4 | 2020-10-27T14:57:16.000Z | 2020-11-04T21:56:39.000Z | test/generate_netmhcpan_functions.py | pirl-unc/mhcgnomes | 0bfbe193daeb7cd38d958222f6071dd657e9fb6e | [
"Apache-2.0"
] | null | null | null | import pandas as pd
NETMHCPAN_3_0_DEST = "test_netmhcpan_3_0_alleles.py"
NETMHCPAN_3_0_SOURCE = "netmhcpan_3_0_alleles.txt"
NETMHCPAN_4_0_DEST = "test_netmhcpan_4_0_alleles.py"
NETMHCPAN_4_0_SOURCE = "netmhcpan_4_0_alleles.txt"
special_chars = " *:-,/."
def generate(src, dst, exclude=set()):
alleles = set()
... | 35.234375 | 107 | 0.501552 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 689 | 0.305543 |
9bbdac1e6d8dd9f71aa6f189c3f63b6af713637c | 343 | py | Python | Dataset/Leetcode/test/11/489.py | kkcookies99/UAST | fff81885aa07901786141a71e5600a08d7cb4868 | [
"MIT"
] | null | null | null | Dataset/Leetcode/test/11/489.py | kkcookies99/UAST | fff81885aa07901786141a71e5600a08d7cb4868 | [
"MIT"
] | null | null | null | Dataset/Leetcode/test/11/489.py | kkcookies99/UAST | fff81885aa07901786141a71e5600a08d7cb4868 | [
"MIT"
] | null | null | null | class Solution:
def XXX(self, height: List[int]) -> int:
ans, i, j = 0, 0, len(height) - 1
while i < j:
val = min(height[i], height[j])
ans = max(val * (j - i), ans)
if height[i] == val:
i += 1
if height[j] == val:
j -=... | 26.384615 | 44 | 0.390671 | 340 | 0.991254 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
9bbde6aa054a0343fb01e156fb53162fe6c254c5 | 96 | py | Python | python/tests/test_linked_list.py | Leenhazaimeh/data-structures-and-algorithms | d55d55bf8c98e768cb929326b5ec8c18fb5c8384 | [
"MIT"
] | null | null | null | python/tests/test_linked_list.py | Leenhazaimeh/data-structures-and-algorithms | d55d55bf8c98e768cb929326b5ec8c18fb5c8384 | [
"MIT"
] | 10 | 2021-07-29T18:56:48.000Z | 2021-09-11T19:11:00.000Z | python/tests/test_linked_list.py | Leenhazaimeh/data-structures-and-algorithms | d55d55bf8c98e768cb929326b5ec8c18fb5c8384 | [
"MIT"
] | 3 | 2021-08-16T06:16:37.000Z | 2021-12-05T14:29:51.000Z | # from linked_list.linked_list import LinkedList
# def test_import():
# assert LinkedList
| 16 | 48 | 0.75 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 91 | 0.947917 |
9bbf5d23053e93f4be3618d38f8307dfe71dd5b9 | 2,156 | py | Python | 美团爬取商家信息/paquxinxi.py | 13060923171/Crawl-Project2 | effab1bf31979635756fc272a7bcc666bb499be2 | [
"MIT"
] | 14 | 2020-10-27T05:52:20.000Z | 2021-11-07T20:24:55.000Z | 美团爬取商家信息/paquxinxi.py | 13060923171/Crawl-Project2 | effab1bf31979635756fc272a7bcc666bb499be2 | [
"MIT"
] | 1 | 2021-09-17T07:40:00.000Z | 2021-09-17T07:40:00.000Z | 美团爬取商家信息/paquxinxi.py | 13060923171/Crawl-Project2 | effab1bf31979635756fc272a7bcc666bb499be2 | [
"MIT"
] | 8 | 2020-11-18T14:23:12.000Z | 2021-11-12T08:55:08.000Z | import requests
import re
import json
headers = {
"Origin": "https://bj.meituan.com",
"Host": "apimobile.meituan.com",
"Referer": "https://bj.meituan.com/s/%E7%81%AB%E9%94%85/",
"Cookie": "uuid=692a53319ce54d0c91f3.1597223761.1.0.0; ci=1; rvct=1; _lxsdk_cuid=173e1f47707c8-0dcd4ff30b4ae3-3323765-e1000-1... | 33.169231 | 185 | 0.590909 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1,017 | 0.437231 |
9bc11053555c82b404c0a0cf86d08e3626d9e05f | 4,071 | py | Python | entity_resolution/EntityClass.py | GeoJamesJones/ArcGIS-Senzing-Prototype | ebe7f1c3f516525f4bfbf5b4f1446e8c6612a67b | [
"MIT"
] | null | null | null | entity_resolution/EntityClass.py | GeoJamesJones/ArcGIS-Senzing-Prototype | ebe7f1c3f516525f4bfbf5b4f1446e8c6612a67b | [
"MIT"
] | null | null | null | entity_resolution/EntityClass.py | GeoJamesJones/ArcGIS-Senzing-Prototype | ebe7f1c3f516525f4bfbf5b4f1446e8c6612a67b | [
"MIT"
] | null | null | null | from __future__ import annotations
import json
from typing import List, Dict
from entity_resolution import EntityResolution
class Entity:
def __init__(self, entity_fields: List[str],
data: List[str],
source_fields: List[str],
attr_dicts: Li... | 36.675676 | 121 | 0.561778 | 3,942 | 0.968312 | 0 | 0 | 0 | 0 | 0 | 0 | 194 | 0.047654 |
32ca34b8eacf24dc530fada37a04db8272ab0be6 | 523 | py | Python | langcreator/system.py | xzripper/LanguageCreator | 65421063161166d3e4f97e4b874909259b665fce | [
"MIT"
] | 2 | 2021-12-12T16:48:20.000Z | 2021-12-31T17:48:21.000Z | langcreator/system.py | xzripper/LanguageCreator | 65421063161166d3e4f97e4b874909259b665fce | [
"MIT"
] | null | null | null | langcreator/system.py | xzripper/LanguageCreator | 65421063161166d3e4f97e4b874909259b665fce | [
"MIT"
] | null | null | null | import subprocess
import sys
import os
subprocess = subprocess
sys = sys
os = os
def output(command: str, remlstc: bool) -> str:
"""
Get output from console command.
If remlstc is True, it's return an output without a useless newline.
:param command: The command.
:param remlstc: R... | 27.526316 | 158 | 0.692161 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 230 | 0.439771 |
32cada166139a42c2081b8a48a2bcd39a15cb5ab | 2,612 | py | Python | create_categories.py | Botomatik/JackBot | 58651d8b5a5bcead2a2eb79849019cb4f972b7cd | [
"MIT"
] | null | null | null | create_categories.py | Botomatik/JackBot | 58651d8b5a5bcead2a2eb79849019cb4f972b7cd | [
"MIT"
] | null | null | null | create_categories.py | Botomatik/JackBot | 58651d8b5a5bcead2a2eb79849019cb4f972b7cd | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
"""
Program to batch create categories.
The program expects a generator containing a list of page titles to be used as
base.
The following command line parameters are supported:
-always (not implemented yet) Don't ask, just do the edit.
-overwrite (not implemented yet).
-parent... | 25.359223 | 78 | 0.630551 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1,135 | 0.434533 |
32cae26d8eb99a201dc12930e81a1edb58d4cace | 10,287 | py | Python | avod/core/losses.py | Zengyi-Qin/TLNet | 11fa48160158b550ad2dc810ed564eebe17e8f5e | [
"Apache-2.0"
] | 114 | 2019-03-13T01:42:22.000Z | 2022-03-31T07:56:04.000Z | avod/core/losses.py | Zengyi-Qin/TLNet | 11fa48160158b550ad2dc810ed564eebe17e8f5e | [
"Apache-2.0"
] | 12 | 2019-03-26T08:18:13.000Z | 2021-05-19T14:36:27.000Z | avod/core/losses.py | Zengyi-Qin/TLNet | 11fa48160158b550ad2dc810ed564eebe17e8f5e | [
"Apache-2.0"
] | 22 | 2019-03-22T10:44:49.000Z | 2021-04-01T00:11:07.000Z | """Classification and regression loss functions for object detection.
Localization losses:
* WeightedL2LocalizationLoss
* WeightedSmoothL1LocalizationLoss
Classification losses:
* WeightedSoftmaxClassificationLoss
* WeightedSigmoidClassificationLoss
"""
from abc import ABCMeta
from abc import abstractmethod
impo... | 44.150215 | 129 | 0.636726 | 9,902 | 0.962574 | 0 | 0 | 572 | 0.055604 | 0 | 0 | 5,310 | 0.516185 |
32cd6811a8df581555a9e17bfebdb7625e6646ac | 19,282 | py | Python | routing/views.py | iqqmuT/tsari | 343ef5cf08ee24bdb710e94c0b6fb334264e5677 | [
"MIT"
] | null | null | null | routing/views.py | iqqmuT/tsari | 343ef5cf08ee24bdb710e94c0b6fb334264e5677 | [
"MIT"
] | 2 | 2020-02-11T22:09:10.000Z | 2020-06-05T18:02:28.000Z | routing/views.py | iqqmuT/tsari | 343ef5cf08ee24bdb710e94c0b6fb334264e5677 | [
"MIT"
] | null | null | null | import json
from datetime import datetime, timedelta
from dateutil import parser as dateparser
from django.contrib.auth.decorators import user_passes_test
from django.db.models import Q
from django.http import HttpResponseNotFound, JsonResponse
from django.shortcuts import render
from django.utils import timezone
fro... | 36.041121 | 256 | 0.587283 | 0 | 0 | 0 | 0 | 2,272 | 0.11783 | 0 | 0 | 4,904 | 0.25433 |
32cf5c6af409ad539e05135e062b11460576c4f6 | 5,575 | py | Python | my_ner.py | shouxieai/nlp-bilstm_crf-ner | 907381325eeb0a2c29004e1c617bea7312579ba8 | [
"Apache-2.0"
] | 16 | 2021-12-14T10:51:25.000Z | 2022-03-30T10:10:09.000Z | my_ner.py | shouxieai/nlp-bilstm-ner | 907381325eeb0a2c29004e1c617bea7312579ba8 | [
"Apache-2.0"
] | 1 | 2022-03-23T04:28:50.000Z | 2022-03-23T04:28:50.000Z | my_ner.py | shouxieai/nlp-bilstm-ner | 907381325eeb0a2c29004e1c617bea7312579ba8 | [
"Apache-2.0"
] | 2 | 2021-12-08T02:48:01.000Z | 2021-12-13T13:03:25.000Z | import os
from torch.utils.data import Dataset,DataLoader
import torch
import torch.nn as nn
from sklearn.metrics import f1_score
def build_corpus(split, make_vocab=True, data_dir="data"):
"""读取数据"""
assert split in ['train', 'dev', 'test']
word_lists = []
tag_lists = []
with open(os.path.join(dat... | 32.794118 | 130 | 0.63139 | 2,404 | 0.427682 | 0 | 0 | 0 | 0 | 0 | 0 | 262 | 0.046611 |
32cf7fd469a0aec109e44e66849bad3789086158 | 245 | py | Python | test.py | karttur/geoimagine03-support | 3971db215382bd16f207eca3ef1d9d81e4298b41 | [
"BSD-3-Clause"
] | null | null | null | test.py | karttur/geoimagine03-support | 3971db215382bd16f207eca3ef1d9d81e4298b41 | [
"BSD-3-Clause"
] | null | null | null | test.py | karttur/geoimagine03-support | 3971db215382bd16f207eca3ef1d9d81e4298b41 | [
"BSD-3-Clause"
] | null | null | null | '''
Created on 28 Jan 2021
@author: thomasgumbricht
'''
from string import whitespace
def CheckWhitespace(s):
'''
'''
return True in [c in s for c in whitespace]
s = 'dumsnut'
print (CheckWhitespace(s)) | 13.611111 | 51 | 0.591837 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 80 | 0.326531 |
32cfbeee160a6e50ceb471701c99ace872cbfe2b | 362 | py | Python | leetcode/409.py | windniw/just-for-fun | 54e5c2be145f3848811bfd127f6a89545e921570 | [
"Apache-2.0"
] | 1 | 2019-08-28T23:15:25.000Z | 2019-08-28T23:15:25.000Z | leetcode/409.py | windniw/just-for-fun | 54e5c2be145f3848811bfd127f6a89545e921570 | [
"Apache-2.0"
] | null | null | null | leetcode/409.py | windniw/just-for-fun | 54e5c2be145f3848811bfd127f6a89545e921570 | [
"Apache-2.0"
] | null | null | null |
"""
link: https://leetcode.com/problems/longest-palindrome
problem: 问用s中字符组成的最长回文串长度
solution: map 记录字符出现次数
"""
class Solution:
def longestPalindrome(self, s: str) -> int:
m, res = collections.defaultdict(int), 0
for x in s:
m[x] += 1
for x in m:
res += m[x] // 2... | 18.1 | 54 | 0.558011 | 243 | 0.595588 | 0 | 0 | 0 | 0 | 0 | 0 | 161 | 0.394608 |
32cfc631e8d4a50ff93f3a9a349602c8342fb97a | 847 | py | Python | nickenbot/config.py | brlafreniere/nickenbot | f13ec78057ec25823eb16df6ffab3a32eddfd3ca | [
"MIT"
] | 1 | 2016-08-10T12:20:58.000Z | 2016-08-10T12:20:58.000Z | nickenbot/config.py | brlafreniere/nickenbot | f13ec78057ec25823eb16df6ffab3a32eddfd3ca | [
"MIT"
] | null | null | null | nickenbot/config.py | brlafreniere/nickenbot | f13ec78057ec25823eb16df6ffab3a32eddfd3ca | [
"MIT"
] | null | null | null | import yaml
import os
import sys
current_dir = os.path.dirname(os.path.realpath(__file__))
project_dir = os.path.realpath(os.path.join(current_dir, ".."))
class ConfigManager:
network = None
config = None
@classmethod
def load(clss):
if clss.network:
config_filepath = os.path.join... | 27.322581 | 95 | 0.615112 | 689 | 0.813459 | 0 | 0 | 620 | 0.731995 | 0 | 0 | 85 | 0.100354 |
32d046c8c2ed3ece0b08aa280a40083f8b7d16ab | 2,277 | py | Python | qna/views.py | channprj/KU-PL | 7fc3719b612a819ed1bd443695d7f13f509ee596 | [
"MIT"
] | null | null | null | qna/views.py | channprj/KU-PL | 7fc3719b612a819ed1bd443695d7f13f509ee596 | [
"MIT"
] | null | null | null | qna/views.py | channprj/KU-PL | 7fc3719b612a819ed1bd443695d7f13f509ee596 | [
"MIT"
] | null | null | null | from django.shortcuts import render
from django.shortcuts import redirect
from django.shortcuts import get_object_or_404
from django.utils import timezone
from .forms import QuestionForm
from .forms import AnswerForm
from .models import Question
from .models import Answer
def question_list(request):
questions = Qu... | 35.030769 | 101 | 0.665349 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 272 | 0.119455 |
32d33f3c862ddf8043ee8ce09e1a526264e7c51a | 1,648 | py | Python | python/tests/test_oci.py | miku/labe | 2d784f418e24ab6fef9f76791c9fdd02dd505657 | [
"MIT"
] | null | null | null | python/tests/test_oci.py | miku/labe | 2d784f418e24ab6fef9f76791c9fdd02dd505657 | [
"MIT"
] | null | null | null | python/tests/test_oci.py | miku/labe | 2d784f418e24ab6fef9f76791c9fdd02dd505657 | [
"MIT"
] | 1 | 2021-09-16T10:51:00.000Z | 2021-09-16T10:51:00.000Z | """
Unit tests for labe. Most not mocked yet, hence slow.
"""
import collections
import socket
import pytest
import requests
from labe.oci import get_figshare_download_link, get_terminal_url
def no_internet(host="8.8.8.8", port=53, timeout=3):
"""
Host: 8.8.8.8 (google-public-dns-a.google.com)
OpenPort... | 30.518519 | 88 | 0.662621 | 0 | 0 | 0 | 0 | 1,072 | 0.650485 | 0 | 0 | 653 | 0.396238 |
32d559b8ce0d7d1c7f26302620ef00f9255a82dc | 26,404 | py | Python | pyNastran/bdf/cards/test/test_dynamic.py | ACea15/pyNastran | 5ffc37d784b52c882ea207f832bceb6b5eb0e6d4 | [
"BSD-3-Clause"
] | 293 | 2015-03-22T20:22:01.000Z | 2022-03-14T20:28:24.000Z | pyNastran/bdf/cards/test/test_dynamic.py | ACea15/pyNastran | 5ffc37d784b52c882ea207f832bceb6b5eb0e6d4 | [
"BSD-3-Clause"
] | 512 | 2015-03-14T18:39:27.000Z | 2022-03-31T16:15:43.000Z | pyNastran/bdf/cards/test/test_dynamic.py | ACea15/pyNastran | 5ffc37d784b52c882ea207f832bceb6b5eb0e6d4 | [
"BSD-3-Clause"
] | 136 | 2015-03-19T03:26:06.000Z | 2022-03-25T22:14:54.000Z | """tests dynamic cards and dynamic load cards"""
import unittest
from io import StringIO
import numpy as np
import pyNastran
from pyNastran.bdf.bdf import BDF, read_bdf, CrossReferenceError
from pyNastran.bdf.cards.test.utils import save_load_deck
#ROOT_PATH = pyNastran.__path__[0]
class TestDynamic(unittest.TestCas... | 34.069677 | 97 | 0.549879 | 26,049 | 0.986555 | 0 | 0 | 0 | 0 | 0 | 0 | 6,107 | 0.231291 |
32d6f22794e1af28d1b004461271504fb7680002 | 4,691 | py | Python | src/kv/benchmark/runbench.py | showapicxt/iowow | a29ac5b28f1b6c2817061c2a43b7222176458876 | [
"MIT"
] | 242 | 2015-08-13T06:38:10.000Z | 2022-03-17T13:49:56.000Z | src/kv/benchmark/runbench.py | showapicxt/iowow | a29ac5b28f1b6c2817061c2a43b7222176458876 | [
"MIT"
] | 44 | 2018-04-08T07:12:02.000Z | 2022-03-04T06:15:01.000Z | src/kv/benchmark/runbench.py | showapicxt/iowow | a29ac5b28f1b6c2817061c2a43b7222176458876 | [
"MIT"
] | 18 | 2016-01-14T09:50:34.000Z | 2022-01-26T23:07:40.000Z | import subprocess
import argparse
import os
import random
from collections import OrderedDict
from parse import parse
from bokeh.io import export_png
from bokeh.plotting import figure, output_file, show, save
from bokeh.models import ColumnDataSource, FactorRange
from bokeh.transform import factor_cmap
from bokeh.layou... | 31.273333 | 99 | 0.568322 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 733 | 0.156257 |
32d7c7852b8b937ddf9034af3749422522ced7eb | 2,792 | py | Python | tests/utils/test_parser.py | ccechatelier/bcdi | cbe3b7960414b03f8e98336c3fcd7b367de441ca | [
"CECILL-B"
] | 18 | 2020-04-30T08:48:39.000Z | 2022-03-30T14:42:01.000Z | tests/utils/test_parser.py | ccechatelier/bcdi | cbe3b7960414b03f8e98336c3fcd7b367de441ca | [
"CECILL-B"
] | 78 | 2019-06-30T03:45:58.000Z | 2022-03-23T15:04:44.000Z | tests/utils/test_parser.py | ccechatelier/bcdi | cbe3b7960414b03f8e98336c3fcd7b367de441ca | [
"CECILL-B"
] | 16 | 2019-07-03T17:18:53.000Z | 2022-01-12T15:54:56.000Z | # -*- coding: utf-8 -*-
# BCDI: tools for pre(post)-processing Bragg coherent X-ray diffraction imaging data
# (c) 07/2017-06/2019 : CNRS UMR 7344 IM2NP
# (c) 07/2019-05/2021 : DESY PHOTON SCIENCE
# authors:
# Jerome Carnis, carnis_jerome@yahoo.fr
from pathlib import Path
import unittest
from bcdi.u... | 34.469136 | 87 | 0.690544 | 2,105 | 0.75394 | 0 | 0 | 0 | 0 | 0 | 0 | 700 | 0.250716 |
32d936fc21c284d747f6a37882f102cf2a32a1e5 | 567 | py | Python | src/directory-starter/README_text.py | hannahweber244/directory-starter | 0cb12b6e9dfe9c3a6eb5029d7d0b6cb5da52b44b | [
"MIT"
] | null | null | null | src/directory-starter/README_text.py | hannahweber244/directory-starter | 0cb12b6e9dfe9c3a6eb5029d7d0b6cb5da52b44b | [
"MIT"
] | null | null | null | src/directory-starter/README_text.py | hannahweber244/directory-starter | 0cb12b6e9dfe9c3a6eb5029d7d0b6cb5da52b44b | [
"MIT"
] | null | null | null | """
# [REPO NAME]
## Table of contents
[Here you can use a table of contents to keep your README structured.]
## Overview
[Here you give a short overview over the motivation behind your project and what problem it solves.]
## How to use it
[Here you can explain how your tool/project is usable.]
### Requirements an... | 31.5 | 102 | 0.75485 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 567 | 1 |
32da7030ea8ed7c10970c252248ba50cc03bff1f | 152 | py | Python | kfdda/models/__init__.py | ll1l11/pymysql-test | de5747366bbf23ecb0b1f01059b3a69c8ac4936d | [
"MIT"
] | null | null | null | kfdda/models/__init__.py | ll1l11/pymysql-test | de5747366bbf23ecb0b1f01059b3a69c8ac4936d | [
"MIT"
] | null | null | null | kfdda/models/__init__.py | ll1l11/pymysql-test | de5747366bbf23ecb0b1f01059b3a69c8ac4936d | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
from ..core import db
from ..helpers import JSONSerializer
class BaseModel(db.Model, JSONSerializer):
__abstract__ = True
| 19 | 42 | 0.710526 | 66 | 0.434211 | 0 | 0 | 0 | 0 | 0 | 0 | 23 | 0.151316 |
32db89f97cc25f33ad056f8860c98d1fafd8baab | 2,652 | py | Python | chapt05/triangle.py | ohlogic/PythonOpenGLSuperBible4Glut | a0d01caaeb811002c191c28210268b5fcbb8b379 | [
"MIT"
] | null | null | null | chapt05/triangle.py | ohlogic/PythonOpenGLSuperBible4Glut | a0d01caaeb811002c191c28210268b5fcbb8b379 | [
"MIT"
] | null | null | null | chapt05/triangle.py | ohlogic/PythonOpenGLSuperBible4Glut | a0d01caaeb811002c191c28210268b5fcbb8b379 | [
"MIT"
] | null | null | null | #!/usr/bin/python3
# Demonstrates OpenGL color triangle
# Ben Smith
# benjamin.coder.smith@gmail.com
#
# based heavily on ccube.cpp
# OpenGL SuperBible
# Program by Richard S. Wright Jr.
import math
from OpenGL.GL import *
from OpenGL.GLUT import *
from OpenGL.GLU import *
ESCAPE = b'\033'
xRot... | 21.737705 | 83 | 0.562217 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 851 | 0.32089 |
32e013bad1fb65c5a409199a8b804f1d0f72e07c | 1,379 | py | Python | sdpremote/utils/user.py | gudn/sdpremote | 431234420ea1e0c752432eac6000c11a75851375 | [
"MIT"
] | null | null | null | sdpremote/utils/user.py | gudn/sdpremote | 431234420ea1e0c752432eac6000c11a75851375 | [
"MIT"
] | null | null | null | sdpremote/utils/user.py | gudn/sdpremote | 431234420ea1e0c752432eac6000c11a75851375 | [
"MIT"
] | null | null | null | import binascii
from base64 import b64decode
from typing import Optional
from fastapi import Depends, Header, status
from fastapi.exceptions import HTTPException
def _user_header(authorization: Optional[str] = Header(None)) -> str:
if not authorization:
raise HTTPException(status.HTTP_401_UNAUTHORIZED)
... | 26.018868 | 74 | 0.649021 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 130 | 0.094271 |
32e2062c20d3f7d54552e963b99e3b7f219ffa2e | 19,175 | py | Python | ScreenTrainer.py | ZihaoChen0319/CMB-Segmentation | 99c5788baacc280ca5dbe02f3e18403e399fb238 | [
"Apache-2.0"
] | null | null | null | ScreenTrainer.py | ZihaoChen0319/CMB-Segmentation | 99c5788baacc280ca5dbe02f3e18403e399fb238 | [
"Apache-2.0"
] | null | null | null | ScreenTrainer.py | ZihaoChen0319/CMB-Segmentation | 99c5788baacc280ca5dbe02f3e18403e399fb238 | [
"Apache-2.0"
] | null | null | null | import torch.nn as nn
import os
import torch.optim as optim
from tqdm import tqdm
import numpy as np
import torch
import torch.nn.functional as nnf
import SimpleITK as sitk
import json
from scipy import ndimage
import medpy.io as mio
from Utils import find_binary_object
from MyDataloader import get_train_... | 50.460526 | 140 | 0.557445 | 18,702 | 0.975129 | 0 | 0 | 0 | 0 | 0 | 0 | 2,163 | 0.11278 |
32e36a60281e09d72c79ad1807ea74035aa73e60 | 534 | py | Python | examples/earthquakes/main.py | admariner/beneath | a6aa2c220e4a646be792379528ae673f4bef440b | [
"MIT"
] | 65 | 2021-04-27T13:13:09.000Z | 2022-01-24T00:26:06.000Z | examples/earthquakes/main.py | admariner/beneath | a6aa2c220e4a646be792379528ae673f4bef440b | [
"MIT"
] | 22 | 2021-10-06T10:30:40.000Z | 2021-12-10T11:36:55.000Z | examples/earthquakes/main.py | admariner/beneath | a6aa2c220e4a646be792379528ae673f4bef440b | [
"MIT"
] | 4 | 2021-04-24T15:29:51.000Z | 2022-03-30T16:20:12.000Z | import beneath
from generators import earthquakes
with open("schemas/earthquake.graphql", "r") as file:
EARTHQUAKES_SCHEMA = file.read()
if __name__ == "__main__":
p = beneath.Pipeline(parse_args=True)
p.description = "Continually pings the USGS earthquake API"
earthquakes = p.generate(earthquakes.ge... | 28.105263 | 76 | 0.700375 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 152 | 0.284644 |
32e3ce811bff9ec736c02ce8188ebe9e69d6a483 | 5,073 | py | Python | examples/tf_vision/tensorflow_saved_model_service.py | siddharthgee/multi-model-server | bd795b402330b491edd5d2a235b8b8c2ef9fcb58 | [
"Apache-2.0"
] | null | null | null | examples/tf_vision/tensorflow_saved_model_service.py | siddharthgee/multi-model-server | bd795b402330b491edd5d2a235b8b8c2ef9fcb58 | [
"Apache-2.0"
] | null | null | null | examples/tf_vision/tensorflow_saved_model_service.py | siddharthgee/multi-model-server | bd795b402330b491edd5d2a235b8b8c2ef9fcb58 | [
"Apache-2.0"
] | null | null | null | # Copyright 2020 Amazon.com, Inc. or its affiliates. All Rights Reserved.
# Licensed under the Apache License, Version 2.0 (the "License").
# You may not use this file except in compliance with the License.
# A copy of the License is located at
# http://www.apache.org/licenses/LICENSE-2.0
# or in the "license" file... | 38.431818 | 118 | 0.640647 | 2,649 | 0.522176 | 0 | 0 | 0 | 0 | 0 | 0 | 2,441 | 0.481175 |
32e4f05624819cc83857abc3b6af4086f2c2a88e | 167 | py | Python | setup.py | kimballa/arduino-dbg | 639d73b6d96996218cf9aafde52f3683c9d93775 | [
"BSD-3-Clause"
] | null | null | null | setup.py | kimballa/arduino-dbg | 639d73b6d96996218cf9aafde52f3683c9d93775 | [
"BSD-3-Clause"
] | null | null | null | setup.py | kimballa/arduino-dbg | 639d73b6d96996218cf9aafde52f3683c9d93775 | [
"BSD-3-Clause"
] | null | null | null | # Minimal setup.py
#
# Enables installing requirements as declared in setup.cfg.
# From this directory, run:
# pip install .
from setuptools import setup
setup()
| 18.555556 | 59 | 0.736527 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 124 | 0.742515 |
32e63e4af47da5e138ff28bb64adb55087df265e | 7,113 | py | Python | apps/etl/models.py | diudiu/featurefactory | ee02ad9e3ea66e2eeafe6e11859801f0420c7d9e | [
"MIT"
] | null | null | null | apps/etl/models.py | diudiu/featurefactory | ee02ad9e3ea66e2eeafe6e11859801f0420c7d9e | [
"MIT"
] | null | null | null | apps/etl/models.py | diudiu/featurefactory | ee02ad9e3ea66e2eeafe6e11859801f0420c7d9e | [
"MIT"
] | null | null | null | # -*- coding:utf-8 -*-
"""
common models
"""
from django.db import models
from apps.common.models import BaseModel
from apps.datasource.models import DsInterfaceInfo
class FeatureType(models.Model):
id = models.AutoField(u'主键', primary_key=True)
feature_type_desc = models.CharField(u'特征类型解释', max_length=... | 39.082418 | 111 | 0.707578 | 7,836 | 0.974506 | 0 | 0 | 0 | 0 | 0 | 0 | 2,099 | 0.261037 |
32e861d95e4d1e621303b5ebac3624de50614805 | 4,007 | py | Python | mazegen/solver.py | alekratz/mazegen | 2799a5cf790cec4bab94a147315cc8541c5efec7 | [
"MIT"
] | null | null | null | mazegen/solver.py | alekratz/mazegen | 2799a5cf790cec4bab94a147315cc8541c5efec7 | [
"MIT"
] | null | null | null | mazegen/solver.py | alekratz/mazegen | 2799a5cf790cec4bab94a147315cc8541c5efec7 | [
"MIT"
] | null | null | null | import random
from typing import Optional
from .grid import *
class Solver:
def __init__(self, grid: Grid):
self._grid = grid
self._backtrack = []
self._pos = (0, 0)
self._dir = None
self._backtracking = False
self._branches = {
self._pos: set(self.vali... | 32.056 | 96 | 0.520839 | 3,942 | 0.983778 | 0 | 0 | 442 | 0.110307 | 0 | 0 | 587 | 0.146494 |
32e9f9206385a627a8ad3b33526b3f3d199fd0d3 | 78 | py | Python | practice.py | dajimmy1120/AvatarGAN | be264914223490ee9c23e59ad5a414da1aef4824 | [
"Apache-2.0"
] | null | null | null | practice.py | dajimmy1120/AvatarGAN | be264914223490ee9c23e59ad5a414da1aef4824 | [
"Apache-2.0"
] | null | null | null | practice.py | dajimmy1120/AvatarGAN | be264914223490ee9c23e59ad5a414da1aef4824 | [
"Apache-2.0"
] | null | null | null | from keras_segmentation.pretrained import pspnet_101_voc12
pspnet_101_voc12() | 26 | 58 | 0.897436 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
32ea368fa5ba2732d1c51618d8edfc516b6eb773 | 1,224 | py | Python | example/RunModel/Abaqus_Model_Example/process_odb.py | volpatto/UQpy | acbe1d6e655e98917f56b324f019881ea9ccca82 | [
"MIT"
] | null | null | null | example/RunModel/Abaqus_Model_Example/process_odb.py | volpatto/UQpy | acbe1d6e655e98917f56b324f019881ea9ccca82 | [
"MIT"
] | null | null | null | example/RunModel/Abaqus_Model_Example/process_odb.py | volpatto/UQpy | acbe1d6e655e98917f56b324f019881ea9ccca82 | [
"MIT"
] | null | null | null | from odbAccess import *
from abaqusConstants import *
from textRepr import *
import timeit
import numpy as np
import os
import sys
start_time = timeit.default_timer()
index = sys.argv[-1]
# print(index)
# index = float(index)
index = int(index)
# print(index)
odbFile = os.path.join(os.getcwd(), "single_element_simul... | 27.818182 | 87 | 0.684641 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 312 | 0.254902 |
32eaa0a294af2308ff208fed9c050fd370b31fec | 8,526 | py | Python | analysis_methods/shuff_time.py | gbrookshire/simulated_rhythmic_sampling | 5c9ed507847a75dbe38d10d78b54441ae83f5831 | [
"MIT"
] | null | null | null | analysis_methods/shuff_time.py | gbrookshire/simulated_rhythmic_sampling | 5c9ed507847a75dbe38d10d78b54441ae83f5831 | [
"MIT"
] | null | null | null | analysis_methods/shuff_time.py | gbrookshire/simulated_rhythmic_sampling | 5c9ed507847a75dbe38d10d78b54441ae83f5831 | [
"MIT"
] | null | null | null | """
Tools to perform analyses by shuffling in time, as in Landau & Fries (2012) and
Fiebelkorn et al. (2013).
"""
import os
import yaml
import numpy as np
import statsmodels.api as sm
from statsmodels.stats.multitest import multipletests
from .utils import avg_repeated_timepoints, dft
# Load the details of the behavi... | 29 | 79 | 0.62327 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5,588 | 0.655407 |
32eb29b8500dc60a31bfc242ef317ed9ccbd65b5 | 1,411 | py | Python | configs/common/ARM_A7.py | baz21/g5 | e81b0df094c5ff80fbbcc37618e81e206a3c9de9 | [
"BSD-3-Clause"
] | null | null | null | configs/common/ARM_A7.py | baz21/g5 | e81b0df094c5ff80fbbcc37618e81e206a3c9de9 | [
"BSD-3-Clause"
] | null | null | null | configs/common/ARM_A7.py | baz21/g5 | e81b0df094c5ff80fbbcc37618e81e206a3c9de9 | [
"BSD-3-Clause"
] | null | null | null |
from m5.objects import *
# https://en.wikipedia.org/wiki/Raspberry_Pi
# https://en.wikipedia.org/wiki/ARM_Cortex-A7
# Instruction Cache
class ARM_A7_ICache(Cache):
tag_latency = 1
data_latency = 1
response_latency = 1
mshrs = 2
tgts_per_mshr = 8
size = '16kB' # OK
assoc = 2
is_read_... | 20.75 | 57 | 0.649894 | 1,197 | 0.848335 | 0 | 0 | 0 | 0 | 0 | 0 | 358 | 0.253721 |
32ebbb19735d64f55f4b8caaf8724aa49e1ddf29 | 172 | py | Python | webapp/models/__init__.py | xaldey/otus_blog | 32600506d447c0b76c7e0323389d17428d197181 | [
"Apache-2.0"
] | null | null | null | webapp/models/__init__.py | xaldey/otus_blog | 32600506d447c0b76c7e0323389d17428d197181 | [
"Apache-2.0"
] | null | null | null | webapp/models/__init__.py | xaldey/otus_blog | 32600506d447c0b76c7e0323389d17428d197181 | [
"Apache-2.0"
] | null | null | null | from .create_db import Session, engine, Base
from .models import User, Post, Tag
__all__ = [
"Session",
"engine",
"Base",
"User",
"Post",
"Tag",
]
| 14.333333 | 44 | 0.569767 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 40 | 0.232558 |
32ef88405f3f3c3db42531c5dfa16c38dbb4d202 | 1,405 | py | Python | Easy/112.PathSum.py | YuriSpiridonov/LeetCode | 2dfcc9c71466ffa2ebc1c89e461ddfca92e2e781 | [
"MIT"
] | 39 | 2020-07-04T11:15:13.000Z | 2022-02-04T22:33:42.000Z | Easy/112.PathSum.py | YuriSpiridonov/LeetCode | 2dfcc9c71466ffa2ebc1c89e461ddfca92e2e781 | [
"MIT"
] | 1 | 2020-07-15T11:53:37.000Z | 2020-07-15T11:53:37.000Z | Easy/112.PathSum.py | YuriSpiridonov/LeetCode | 2dfcc9c71466ffa2ebc1c89e461ddfca92e2e781 | [
"MIT"
] | 20 | 2020-07-14T19:12:53.000Z | 2022-03-02T06:28:17.000Z | """
Given a binary tree and a sum, determine if the tree has a root-to-leaf path
such that adding up all the values along the path equals the given sum.
Note: A leaf is a node with no children.
Example:
Given the below binary tree and sum = 22,
5
/ \
4 8
... | 28.673469 | 84 | 0.577936 | 468 | 0.333096 | 0 | 0 | 0 | 0 | 0 | 0 | 920 | 0.654804 |
32f125ad1d76b4e0fde9ddfeb972aeb7353e40c7 | 42 | py | Python | downloads.py | Jamal135/fine-grained-sentiment-app | 4754cefd77ccfa99b15a7721c3471aeacec650c9 | [
"MIT"
] | null | null | null | downloads.py | Jamal135/fine-grained-sentiment-app | 4754cefd77ccfa99b15a7721c3471aeacec650c9 | [
"MIT"
] | null | null | null | downloads.py | Jamal135/fine-grained-sentiment-app | 4754cefd77ccfa99b15a7721c3471aeacec650c9 | [
"MIT"
] | null | null | null | import nltk
nltk.download('vader_lexicon') | 21 | 30 | 0.833333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 15 | 0.357143 |
32f16560a7eafdb17a4951c61d182a0eaa97e4e4 | 880 | py | Python | src/Tools/Button.py | hieuhdh/Multi-tasking-program | 2f064a554f647247c84979b7a27f0797d1e1b5af | [
"MIT"
] | null | null | null | src/Tools/Button.py | hieuhdh/Multi-tasking-program | 2f064a554f647247c84979b7a27f0797d1e1b5af | [
"MIT"
] | null | null | null | src/Tools/Button.py | hieuhdh/Multi-tasking-program | 2f064a554f647247c84979b7a27f0797d1e1b5af | [
"MIT"
] | null | null | null | from tkinter import*
from tkinter import Button, font
from tkinter.font import BOLD
import tkinter.ttk as ttk
from tkhtmlview import HTMLLabel
from tkhtmlview import HTMLText
def frameButton(frame, xx, yy, text, backgroundcolor, foregroundcolor, cmd, images):
def IN(e):
button['background'] = back... | 40 | 303 | 0.659091 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 137 | 0.155682 |
32f6cfa5b601a97d41e10a68ea610b54a023b9f0 | 864 | py | Python | src/test.py | ayieko168/Arduino-Oscilloscope | 5a0634437010f4303c86aef141f33cc6a628b3dc | [
"MIT"
] | null | null | null | src/test.py | ayieko168/Arduino-Oscilloscope | 5a0634437010f4303c86aef141f33cc6a628b3dc | [
"MIT"
] | null | null | null | src/test.py | ayieko168/Arduino-Oscilloscope | 5a0634437010f4303c86aef141f33cc6a628b3dc | [
"MIT"
] | null | null | null | import pyqtgraph as pg
import pyqtgraph.exporters
import numpy as np
import math
from time import sleep
f = 10
t = 0
Samples = 1000
# while True:
# y2 = np.sin( 2* np.pi * f * t)
# print(y)
# t+=0.01
# sleep(0.25)
def update():
global f, t, ys, y2
print(len(y2))
if len(y2) == Samples:
... | 16.941176 | 76 | 0.618056 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 186 | 0.215278 |
32f73e3a96427c84bfa7bd842e7e9ab6eeb893b6 | 931 | py | Python | Aula07/Exercicio2.py | PabloSchumacher/TrabalhosPython | 828edd35eb40442629211bc9f1477f75fb025d74 | [
"bzip2-1.0.6",
"MIT"
] | null | null | null | Aula07/Exercicio2.py | PabloSchumacher/TrabalhosPython | 828edd35eb40442629211bc9f1477f75fb025d74 | [
"bzip2-1.0.6",
"MIT"
] | null | null | null | Aula07/Exercicio2.py | PabloSchumacher/TrabalhosPython | 828edd35eb40442629211bc9f1477f75fb025d74 | [
"bzip2-1.0.6",
"MIT"
] | null | null | null | #--- Exercicio 2 - Dicionários
#--- Escreva um programa que leia os dados de 11 jogadores
#--- Jogador: Nome, Posicao, Numero, PernaBoa
#--- Crie um dicionario para armazenar os dados
#--- Imprima todos os jogadores e seus dados
lista_jogador = []
for i in range(0,11):
dicionario_jogador = {'Nome':'', 'Posicao':'... | 46.55 | 177 | 0.688507 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 628 | 0.667375 |
32f8e7bf61b54b514d134bdb102d258bdc2af2ce | 669 | py | Python | Tiny ImageNet Challenge/train_data.py | Vishal-V/Mastering-TensorFlow-2.x | 83e18cf84dc5c391c5f902978ee5a80e1be4a31d | [
"MIT"
] | 3 | 2020-05-15T16:57:39.000Z | 2020-09-16T20:53:58.000Z | Tiny ImageNet Challenge/train_data.py | Vishal-V/Mastering-Tensorflow | 83e18cf84dc5c391c5f902978ee5a80e1be4a31d | [
"MIT"
] | null | null | null | Tiny ImageNet Challenge/train_data.py | Vishal-V/Mastering-Tensorflow | 83e18cf84dc5c391c5f902978ee5a80e1be4a31d | [
"MIT"
] | 4 | 2020-03-30T16:11:41.000Z | 2020-09-15T20:28:27.000Z | # Iterate over epochs.
for epoch in range(3):
print(f'Epoch {epoch+1}')
# Iterate over the batches of the dataset.
for step, x_batch_train in enumerate(train_data):
with tf.GradientTape() as tape:
reconstructed = autoencoder(x_batch_train)
# Compute reconstruction loss
loss = mse_loss(x_b... | 35.210526 | 74 | 0.707025 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 224 | 0.334828 |
32f92084cffe12b7f31fc3604eb9852e4502b8d7 | 1,422 | py | Python | utils/generate_topics.py | ahoho/scholar | fe1b7ba590563e245e7765d100cfff091ba20c54 | [
"Apache-2.0"
] | null | null | null | utils/generate_topics.py | ahoho/scholar | fe1b7ba590563e245e7765d100cfff091ba20c54 | [
"Apache-2.0"
] | null | null | null | utils/generate_topics.py | ahoho/scholar | fe1b7ba590563e245e7765d100cfff091ba20c54 | [
"Apache-2.0"
] | null | null | null | ################################################################
# Generate top-N words for topics, one per line, to stdout
################################################################
import os
import sys
import argparse
import numpy as np
import file_handling as fh
def get_top_n_topic_words(beta, vocab, n=30):
... | 25.392857 | 70 | 0.563291 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 386 | 0.271449 |
32fc43425ea47a93c10fa87eeeea81ca0922ca0c | 918 | py | Python | AutomateboringStuff/3. Functions/try_nd_except.py | gabriel-marchetti/Exercicios-Python | 0f1eac7eee48081cf899d25bed0ec5dbc70a3542 | [
"MIT"
] | 2 | 2021-12-21T23:28:02.000Z | 2021-12-21T23:28:03.000Z | AutomateboringStuff/3. Functions/try_nd_except.py | gabriel-marchetti/Exercicios-Python | 0f1eac7eee48081cf899d25bed0ec5dbc70a3542 | [
"MIT"
] | 1 | 2021-12-22T12:05:11.000Z | 2021-12-22T13:02:52.000Z | AutomateboringStuff/3. Functions/try_nd_except.py | gabriel-marchetti/Exercicios-Python | 0f1eac7eee48081cf899d25bed0ec5dbc70a3542 | [
"MIT"
] | null | null | null | # Quando tivermos um programa onde claramente temos um caso
# indesejável, então podemos usar a função do python dita
# try_and_except.
# Vamos supor que desejamos fazer uma função que faça uma
# divisão, então podemos fazer a seguinte estrutura de
# código
def divisão(divideBy):
return 42 / divideBy
# veja que n... | 20.863636 | 59 | 0.713508 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 531 | 0.568522 |
32fcb908b2dfd2baf6aec8baabfb5d1f269220d0 | 1,577 | py | Python | src/plyer_lach/platforms/android/email.py | locksmith47/turing-sim-kivy | f57de9d52494245c56f67dd7e63121434bb0553f | [
"MIT"
] | null | null | null | src/plyer_lach/platforms/android/email.py | locksmith47/turing-sim-kivy | f57de9d52494245c56f67dd7e63121434bb0553f | [
"MIT"
] | null | null | null | src/plyer_lach/platforms/android/email.py | locksmith47/turing-sim-kivy | f57de9d52494245c56f67dd7e63121434bb0553f | [
"MIT"
] | null | null | null | from jnius import autoclass, cast
from kivy.logger import Logger
from plyer_lach.facades import Email
from plyer_lach.platforms.android import activity
Intent = autoclass('android.content.Intent')
AndroidString = autoclass('java.lang.String')
URI = autoclass('android.net.Uri')
class AndroidEmail(Email):
def _send... | 36.674419 | 89 | 0.606848 | 1,252 | 0.793912 | 0 | 0 | 0 | 0 | 0 | 0 | 229 | 0.145212 |
32ff2b91e7cdacd12f1c52a76ec14a6214fafa45 | 452 | py | Python | main.py | rishi-chauhan/sudoku | 2b07954b2f3ab5146ab0f96eb4d0509a3ea45eb2 | [
"MIT"
] | null | null | null | main.py | rishi-chauhan/sudoku | 2b07954b2f3ab5146ab0f96eb4d0509a3ea45eb2 | [
"MIT"
] | null | null | null | main.py | rishi-chauhan/sudoku | 2b07954b2f3ab5146ab0f96eb4d0509a3ea45eb2 | [
"MIT"
] | null | null | null | """Main class for sudoku game. Run this to solve the game."""
from board import Board
# ENTRIES contains the values of each cell
ENTRIES = [0, 0, 0, 2, 6, 0, 7, 0, 1, 6, 8, 0, 0, 7, 0, 0, 9, 0, 1,
9, 0, 0, 0, 4, 5, 0, 0, 8, 2, 0, 1, 0, 0, 0, 4, 0, 0,
0, 4, 6, 0, 2, 9, 0, 0, 0, 5, 0, 0, 0, 3, 0, 2... | 37.666667 | 67 | 0.446903 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 103 | 0.227876 |
fd00768ed39187f9b978abbf6c4d123c662329a9 | 121 | py | Python | fuzzer/fuzzing_strategies/base_strategy/base_strategy.py | Dyfox100/Libstemmer_Fuzzer | 263d6e64e007116a348d994851aa05e4c0c35358 | [
"MIT"
] | null | null | null | fuzzer/fuzzing_strategies/base_strategy/base_strategy.py | Dyfox100/Libstemmer_Fuzzer | 263d6e64e007116a348d994851aa05e4c0c35358 | [
"MIT"
] | null | null | null | fuzzer/fuzzing_strategies/base_strategy/base_strategy.py | Dyfox100/Libstemmer_Fuzzer | 263d6e64e007116a348d994851aa05e4c0c35358 | [
"MIT"
] | null | null | null | import abc
class Abstract_Strategy(metaclass=abc.ABCMeta):
@abc.abstractmethod
def generate(self):
pass
| 17.285714 | 47 | 0.710744 | 108 | 0.892562 | 0 | 0 | 56 | 0.46281 | 0 | 0 | 0 | 0 |
fd009473c74aa4ae5995e6b6bc84914f1edd33ca | 2,215 | py | Python | netbox/dcim/migrations/0100_application.py | fireman0865/PingBox | 0f00eaf88b88e9441fffd5173a1501e56c13db03 | [
"Apache-2.0"
] | 1 | 2021-09-23T00:06:51.000Z | 2021-09-23T00:06:51.000Z | netbox/dcim/migrations/0100_application.py | fireman0865/PingBox | 0f00eaf88b88e9441fffd5173a1501e56c13db03 | [
"Apache-2.0"
] | 2 | 2021-06-08T21:05:10.000Z | 2021-09-08T01:46:58.000Z | netbox/dcim/migrations/0100_application.py | fireman0865/PingBox | 0f00eaf88b88e9441fffd5173a1501e56c13db03 | [
"Apache-2.0"
] | null | null | null | # Generated by Django 2.2.10 on 2020-03-04 09:21
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
dependencies = [
('virtualization', '0013_deterministic_ordering'),
('dcim', '0099_powerfeed_negative_voltage'),
]
operations... | 55.375 | 219 | 0.628442 | 2,088 | 0.942664 | 0 | 0 | 0 | 0 | 0 | 0 | 584 | 0.263657 |
fd00db8ee275e84aadc9a08c115a590eab1c8a65 | 1,934 | py | Python | pam_notify.py | aNNufriy/pamNotifier | 088ec0cb87c026a0fbc8e6275fc891bf653af645 | [
"MIT"
] | 1 | 2020-03-21T21:37:57.000Z | 2020-03-21T21:37:57.000Z | pam_notify.py | aNNufriy/pamNotifier | 088ec0cb87c026a0fbc8e6275fc891bf653af645 | [
"MIT"
] | null | null | null | pam_notify.py | aNNufriy/pamNotifier | 088ec0cb87c026a0fbc8e6275fc891bf653af645 | [
"MIT"
] | null | null | null | #!/usr/bin/env python
import os
import sys
import smtplib
import time
import syslog
import telegram
import yaml
from email.MIMEMultipart import MIMEMultipart
from email.MIMEText import MIMEText
# Author:: Alexander Schedrov (schedrow@gmail.com)
# Copyright:: Copyright (c) 2019 Alexander Schedrov
# License:: MIT
def ... | 33.344828 | 97 | 0.635471 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 373 | 0.192865 |
fd032c799cd2f082ede61113614415437237b7bc | 40,263 | py | Python | src/eventail/async_service/pika/base.py | allo-media/eventail | aed718d733709f1a522fbfec7083ddd8ed7b5039 | [
"MIT"
] | 2 | 2019-12-12T15:08:25.000Z | 2020-05-19T08:52:06.000Z | src/eventail/async_service/pika/base.py | allo-media/eventail | aed718d733709f1a522fbfec7083ddd8ed7b5039 | [
"MIT"
] | 10 | 2021-01-19T15:03:51.000Z | 2022-03-08T15:48:22.000Z | src/eventail/async_service/pika/base.py | allo-media/eventail | aed718d733709f1a522fbfec7083ddd8ed7b5039 | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
#
# MIT License
#
# Copyright (c) 2018-2019 Groupe Allo-Media
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the r... | 39.014535 | 108 | 0.634304 | 38,561 | 0.95749 | 1,104 | 0.027413 | 1,124 | 0.02791 | 0 | 0 | 18,631 | 0.462618 |
fd0394b6bd7363e7ed4aa89ca0603954bd731b42 | 889 | py | Python | CLI/mainmenue.py | MeatBoyed/PasswordBank2 | f4367b22902ce1282772b184899e3d6e899c1cca | [
"MIT"
] | 1 | 2021-02-08T17:45:28.000Z | 2021-02-08T17:45:28.000Z | CLI/mainmenue.py | MeatBoyed/PasswordBank2 | f4367b22902ce1282772b184899e3d6e899c1cca | [
"MIT"
] | null | null | null | CLI/mainmenue.py | MeatBoyed/PasswordBank2 | f4367b22902ce1282772b184899e3d6e899c1cca | [
"MIT"
] | null | null | null | from .mock_api.utils import GetSelection
from .viewAccounts import ViewAccounts
from .addAccount import AddAccount
def MainMenue():
headerMessage = (
"""\n\n=========================================================\n===================== Main Menue ========================\n""")
print(headerMessage)
... | 26.939394 | 137 | 0.418448 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 353 | 0.397075 |
fd03c109230a47c1540cdcf65dcdedac9302a120 | 7,342 | py | Python | dataset.py | Intelligent-Computing-Lab-Yale/Energy-Separation-Training | 9336862a10c915a482d427e8a36367f648e7dd40 | [
"MIT"
] | 2 | 2022-03-31T02:36:52.000Z | 2022-03-31T06:13:25.000Z | dataset.py | Intelligent-Computing-Lab-Yale/Energy-Separation-Training | 9336862a10c915a482d427e8a36367f648e7dd40 | [
"MIT"
] | null | null | null | dataset.py | Intelligent-Computing-Lab-Yale/Energy-Separation-Training | 9336862a10c915a482d427e8a36367f648e7dd40 | [
"MIT"
] | null | null | null | import torch
import torchvision
from torchvision import datasets, transforms
from torch.utils.data import DataLoader
import os
def get10(batch_size, data_root='/tmp/public_dataset/pytorch', train=True, val=True, **kwargs):
data_root = os.path.expanduser(os.path.join(data_root, 'cifar10-data'))
num_workers = kw... | 40.120219 | 96 | 0.578725 | 389 | 0.052983 | 0 | 0 | 0 | 0 | 0 | 0 | 1,066 | 0.145192 |
fd04dad88b99035b710b66d225ec5a6739f0249b | 25,604 | py | Python | tests/st/ops/cpu/test_scatter_arithmetic_op.py | PowerOlive/mindspore | bda20724a94113cedd12c3ed9083141012da1f15 | [
"Apache-2.0"
] | 3,200 | 2020-02-17T12:45:41.000Z | 2022-03-31T20:21:16.000Z | tests/st/ops/cpu/test_scatter_arithmetic_op.py | zimo-geek/mindspore | 665ec683d4af85c71b2a1f0d6829356f2bc0e1ff | [
"Apache-2.0"
] | 176 | 2020-02-12T02:52:11.000Z | 2022-03-28T22:15:55.000Z | tests/st/ops/cpu/test_scatter_arithmetic_op.py | zimo-geek/mindspore | 665ec683d4af85c71b2a1f0d6829356f2bc0e1ff | [
"Apache-2.0"
] | 621 | 2020-03-09T01:31:41.000Z | 2022-03-30T03:43:19.000Z | # Copyright 2021 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 a... | 39.757764 | 82 | 0.594712 | 3,480 | 0.135916 | 0 | 0 | 18,762 | 0.732776 | 0 | 0 | 854 | 0.033354 |
fd06722fb8cfe07ace7e4c46b654df0346766b26 | 4,181 | py | Python | nn_similarity_index/cwt_kernel_mat.py | forgi86/xfer | 56d98a66d6adb2466d1a73b52f3b27193930a008 | [
"Apache-2.0"
] | 244 | 2018-08-31T18:35:29.000Z | 2022-03-20T01:12:50.000Z | nn_similarity_index/cwt_kernel_mat.py | forgi86/xfer | 56d98a66d6adb2466d1a73b52f3b27193930a008 | [
"Apache-2.0"
] | 26 | 2018-08-29T15:31:21.000Z | 2021-06-24T08:05:53.000Z | nn_similarity_index/cwt_kernel_mat.py | forgi86/xfer | 56d98a66d6adb2466d1a73b52f3b27193930a008 | [
"Apache-2.0"
] | 57 | 2018-09-11T13:40:35.000Z | 2022-02-22T14:43:34.000Z | # Copyright 2020 Amazon.com, Inc. or its affiliates. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License").
# You may not use this file except in compliance with the License.
# A copy of the License is located at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# or in th... | 40.201923 | 112 | 0.648649 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1,908 | 0.45635 |
fd067b6667868f936c5b7ba2c71c491e3eeb9190 | 844 | py | Python | venv/Lib/site-packages/traits/observation/events.py | richung99/digitizePlots | 6b408c820660a415a289726e3223e8f558d3e18b | [
"MIT"
] | 1 | 2022-01-18T17:56:51.000Z | 2022-01-18T17:56:51.000Z | venv/Lib/site-packages/traits/observation/events.py | richung99/digitizePlots | 6b408c820660a415a289726e3223e8f558d3e18b | [
"MIT"
] | null | null | null | venv/Lib/site-packages/traits/observation/events.py | richung99/digitizePlots | 6b408c820660a415a289726e3223e8f558d3e18b | [
"MIT"
] | null | null | null | # (C) Copyright 2005-2021 Enthought, Inc., Austin, TX
# All rights reserved.
#
# This software is provided without warranty under the terms of the BSD
# license included in LICENSE.txt and may be redistributed only under
# the conditions described in the aforementioned license. The license
# is also available online at... | 29.103448 | 71 | 0.760664 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 516 | 0.611374 |
fd077dfb9ba449d6f886f45f49324f828fa9d71b | 827 | py | Python | src/run_hid_4_network2.py | Naresh1318/Effect_of_injected_noise_in_deep_NN | 0d001ea2c4d33011204247cb4c066b0da6632c04 | [
"Unlicense"
] | 2 | 2016-09-11T08:47:29.000Z | 2016-11-19T10:29:47.000Z | src/run_hid_4_network2.py | Naresh1318/Effect_of_injected_noise_in_deep_NN | 0d001ea2c4d33011204247cb4c066b0da6632c04 | [
"Unlicense"
] | null | null | null | src/run_hid_4_network2.py | Naresh1318/Effect_of_injected_noise_in_deep_NN | 0d001ea2c4d33011204247cb4c066b0da6632c04 | [
"Unlicense"
] | null | null | null | import mnist_loader
import network2
import numpy as np
training_data, validation_data, test_data = mnist_loader.load_data_wrapper()
eta = 0.9
m_b_s = 10
epochs = 30
trials = 10
trial_ev = []
for t in xrange(trials):
net = network2.Network([784, 50, 50, 50, 50, 10], cost=network2.CrossEntropyCost)
net.defaul... | 33.08 | 131 | 0.732769 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 151 | 0.182588 |
fd08718d6dac06e0024584cff9f9907168ac0518 | 1,918 | py | Python | wsm/backend/asyncwhois/base.py | Rayologist/windows-sshd-manager | 4f78a0cdaa12fe3c2a785aca31066c3be886878b | [
"Apache-2.0"
] | 9 | 2022-02-09T09:09:43.000Z | 2022-02-09T09:10:06.000Z | wsm/backend/asyncwhois/base.py | Rayologist/windows-sshd-manager | 4f78a0cdaa12fe3c2a785aca31066c3be886878b | [
"Apache-2.0"
] | null | null | null | wsm/backend/asyncwhois/base.py | Rayologist/windows-sshd-manager | 4f78a0cdaa12fe3c2a785aca31066c3be886878b | [
"Apache-2.0"
] | null | null | null | from abc import ABC, abstractmethod
from typing import List, Any
from ipaddress import IPv4Address
from dataclasses import dataclass, FrozenInstanceError
from types import SimpleNamespace
from enum import Enum, auto
class Kind(Enum):
CREATE_WHOIS = auto()
GET_WHOIS = auto()
GET_WHOIS_BY_IP = auto()
GE... | 22.302326 | 77 | 0.688738 | 1,660 | 0.865485 | 0 | 0 | 1,024 | 0.533889 | 375 | 0.195516 | 43 | 0.022419 |
fd0c1d5bae5b02c0610c8254bb0ed033a6e6d1e5 | 1,079 | py | Python | optaux/helper_functions/check_nonvalidated_auxs.py | coltonlloyd/OptAux | 3ee1f8cdfa32f1a732ad41d5f854659159694160 | [
"MIT"
] | 1 | 2019-06-05T10:41:06.000Z | 2019-06-05T10:41:06.000Z | optaux/helper_functions/check_nonvalidated_auxs.py | coltonlloyd/OptAux | 3ee1f8cdfa32f1a732ad41d5f854659159694160 | [
"MIT"
] | null | null | null | optaux/helper_functions/check_nonvalidated_auxs.py | coltonlloyd/OptAux | 3ee1f8cdfa32f1a732ad41d5f854659159694160 | [
"MIT"
] | null | null | null | import cobra
from optaux import resources
resource_dir = resources.__path__[0]
met_to_rs = {'EX_pydam_e': ['PDX5PS', 'PYDXK', 'PYDXNK'],
'EX_orot_e': ['DHORTS', 'UPPRT', 'URIK2'],
'EX_thr__L_e': ['PTHRpp', 'THRS'],
'EX_pro__L_e': ['AMPTASEPG', 'P5CR'],
'EX_skm_e': ... | 33.71875 | 68 | 0.615385 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 189 | 0.175162 |
fd0f8e0645346f82a2ff9bdf244ca7d9bf72405b | 186 | py | Python | xauto/common/futils.py | sababa11/xauto | 107e59344b4624941387a4dff0d439719075ebf4 | [
"Apache-2.0"
] | null | null | null | xauto/common/futils.py | sababa11/xauto | 107e59344b4624941387a4dff0d439719075ebf4 | [
"Apache-2.0"
] | null | null | null | xauto/common/futils.py | sababa11/xauto | 107e59344b4624941387a4dff0d439719075ebf4 | [
"Apache-2.0"
] | null | null | null | import os
import sys
def get_workdir():
"""
get_workdir() -> workdir: [str]
Returns the current workdir.
"""
return os.path.realpath(os.path.dirname(sys.argv[0]))
| 15.5 | 57 | 0.629032 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 81 | 0.435484 |
fd105e9dfaa8a1cb5dda8aab7e3ed98167bf73e4 | 10,430 | py | Python | csv-to-mysql.py | LongPhan1912/Youtube-Playlist-Extractor | 80b10e0b459c2cb264113cfaff644f5f28650813 | [
"CC0-1.0"
] | null | null | null | csv-to-mysql.py | LongPhan1912/Youtube-Playlist-Extractor | 80b10e0b459c2cb264113cfaff644f5f28650813 | [
"CC0-1.0"
] | null | null | null | csv-to-mysql.py | LongPhan1912/Youtube-Playlist-Extractor | 80b10e0b459c2cb264113cfaff644f5f28650813 | [
"CC0-1.0"
] | null | null | null | import csv
import MySQLdb
# installing MySQL: https://dev.mysql.com/doc/refman/8.0/en/osx-installation-pkg.html
# how to start, watch: https://www.youtube.com/watch?v=3vsC05rxZ8c
# or read this (absolutely helpful) guide: https://www.datacamp.com/community/tutorials/mysql-python
# this is mainly created to get a data... | 48.287037 | 136 | 0.661266 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 5,935 | 0.569032 |