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|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
8c6244ecbd5d5dcdadf1afca3843b490369335f7 | 448 | py | Python | projects/utils.py | Matheus158257/projects | 26a6148046533476e625a872a2950c383aa975a8 | [
"Apache-2.0"
] | null | null | null | projects/utils.py | Matheus158257/projects | 26a6148046533476e625a872a2950c383aa975a8 | [
"Apache-2.0"
] | null | null | null | projects/utils.py | Matheus158257/projects | 26a6148046533476e625a872a2950c383aa975a8 | [
"Apache-2.0"
] | null | null | null | # -*- coding: utf-8 -*-
import re
def to_camel_case(snake_str):
components = snake_str.split("_")
# We capitalize the first letter of each component except the first one
# with the 'title' method and join them together.
return components[0] + "".join(x.title() for x in components[1:])
def to_snake_c... | 29.866667 | 75 | 0.620536 |
e8b567474bb7ca24c06eabd95a56732ed43dbeae | 2,451 | py | Python | components/amp-utility/python/math2.py | ekmixon/AliOS-Things | 00334295af8aa474d818724149726ca93da4645d | [
"Apache-2.0"
] | 4,538 | 2017-10-20T05:19:03.000Z | 2022-03-30T02:29:30.000Z | components/amp-utility/python/math2.py | ekmixon/AliOS-Things | 00334295af8aa474d818724149726ca93da4645d | [
"Apache-2.0"
] | 1,088 | 2017-10-21T07:57:22.000Z | 2022-03-31T08:15:49.000Z | components/amp-utility/python/math2.py | willianchanlovegithub/AliOS-Things | 637c0802cab667b872d3b97a121e18c66f256eab | [
"Apache-2.0"
] | 1,860 | 2017-10-20T05:22:35.000Z | 2022-03-27T10:54:14.000Z | # * coding: UTF8 *
"""
该模块实现相应CPython模块的子集，如下所示,math 模块提供一些用于处理浮点数的基本函数。
函数
------------------------------
"""
def acos(x):
"""
返回 ``x`` 的反余弦函数
"""
pass
def acosh(x):
"""
返回 ``x`` 的反双曲余弦函数
"""
pass
def asin(x):
"""
返回 ``x`` 的反正弦函数
"""
pass
def asinh(x):
"""
返回 ``x... | 10.128099 | 125 | 0.406773 |
ad6f2aebf296207e62466ca924c4a8f4b5d70388 | 9,980 | py | Python | Dockerfiles/gedlab-khmer-filter-abund/pymodules/python2.7/lib/python/pygsl/roots.py | poojavade/Genomics_Docker | 829b5094bba18bbe03ae97daf925fee40a8476e8 | [
"Apache-2.0"
] | 1 | 2019-07-29T02:53:51.000Z | 2019-07-29T02:53:51.000Z | Dockerfiles/gedlab-khmer-filter-abund/pymodules/python2.7/lib/python/pygsl/roots.py | poojavade/Genomics_Docker | 829b5094bba18bbe03ae97daf925fee40a8476e8 | [
"Apache-2.0"
] | 1 | 2021-09-11T14:30:32.000Z | 2021-09-11T14:30:32.000Z | Dockerfiles/gedlab-khmer-filter-abund/pymodules/python2.7/lib/python/pygsl/roots.py | poojavade/Genomics_Docker | 829b5094bba18bbe03ae97daf925fee40a8476e8 | [
"Apache-2.0"
] | 2 | 2016-12-19T02:27:46.000Z | 2019-07-29T02:53:54.000Z | #!/usr/bin/env python
# Author : Pierre Schnizer
"""
Wrapper over the functions as described in Chapter 31 of the
reference manual.
Routines for finding the root of a function of one variable.
Example: searching the root of a quadratic using brent:
def quadratic(x, params):
a = params[0]
b = params[1]
c... | 35.642857 | 79 | 0.682164 |
d11d637eadf43c2839b31f388da13293fdf2d813 | 318 | py | Python | Python/M01_ProgrammingBasics/L04_ForLoop/Lab/Solutions/P08_NumberSequence.py | todorkrastev/softuni-software-engineering | cfc0b5eaeb82951ff4d4668332ec3a31c59a5f84 | [
"MIT"
] | null | null | null | Python/M01_ProgrammingBasics/L04_ForLoop/Lab/Solutions/P08_NumberSequence.py | todorkrastev/softuni-software-engineering | cfc0b5eaeb82951ff4d4668332ec3a31c59a5f84 | [
"MIT"
] | null | null | null | Python/M01_ProgrammingBasics/L04_ForLoop/Lab/Solutions/P08_NumberSequence.py | todorkrastev/softuni-software-engineering | cfc0b5eaeb82951ff4d4668332ec3a31c59a5f84 | [
"MIT"
] | 1 | 2022-02-23T13:03:14.000Z | 2022-02-23T13:03:14.000Z | import sys
max_num = -sys.maxsize
min_num = sys.maxsize
current = 0
numbers = int(input())
for each in range(numbers):
current = int(input())
if current > max_num:
max_num = current
if current < min_num:
min_num = current
print(f'Max number: {max_num}')
print(f'Min number: {min_num}') | 17.666667 | 31 | 0.647799 |
66f4abb4826842959fe78154457dc458e8da5b2d | 1,487 | py | Python | project_euler_problems/integer right triangle/solution.py | gbrls/CompetitiveCode | b6f1b817a655635c3c843d40bd05793406fea9c6 | [
"MIT"
] | 165 | 2020-10-03T08:01:11.000Z | 2022-03-31T02:42:08.000Z | project_euler_problems/integer right triangle/solution.py | gbrls/CompetitiveCode | b6f1b817a655635c3c843d40bd05793406fea9c6 | [
"MIT"
] | 383 | 2020-10-03T07:39:11.000Z | 2021-11-20T07:06:35.000Z | project_euler_problems/integer right triangle/solution.py | gbrls/CompetitiveCode | b6f1b817a655635c3c843d40bd05793406fea9c6 | [
"MIT"
] | 380 | 2020-10-03T08:05:04.000Z | 2022-03-19T06:56:59.000Z | import time
time_start = time.time()
import math
triples = {} # a dictionary of lists to hold results, the key is the perimeter p
for n in range(1000):
triples[n]=[]
p=100 # start by generating pythagorean triples with 2 digits, will use them to generate the rest
for a in range(1,p//2):
for b in ... | 38.128205 | 108 | 0.535306 |
0f7f43e74a2e9911249c4904484d3a3d367d76da | 6,159 | py | Python | 4_DeepLearning-Advanced/3-Regularisierung_Dropout_Layer.py | felixdittrich92/DeepLearning-tensorflow-keras | 2880d8ed28ba87f28851affa92b6fa99d2e47be9 | [
"Apache-2.0"
] | null | null | null | 4_DeepLearning-Advanced/3-Regularisierung_Dropout_Layer.py | felixdittrich92/DeepLearning-tensorflow-keras | 2880d8ed28ba87f28851affa92b6fa99d2e47be9 | [
"Apache-2.0"
] | null | null | null | 4_DeepLearning-Advanced/3-Regularisierung_Dropout_Layer.py | felixdittrich92/DeepLearning-tensorflow-keras | 2880d8ed28ba87f28851affa92b6fa99d2e47be9 | [
"Apache-2.0"
] | null | null | null | '''
Regularisierungstechniken: Techniken gegen Overfitting
Der Dropout Layer deaktiviert eine gegebene Prozentzahl von zufällig gewählten Neuronen
um ein Overfitting zu vermeiden.
-> nach Conv2D oder Activation zu setzen
Werte bis maximal 10% da das Modell sonst nichts lernt ;)
-> gibt etwas besseres -> BatchNorma... | 32.078125 | 98 | 0.662932 |
0e47aea5d9a95f1109c1be30dfae884a7f8be3e6 | 5,652 | py | Python | car/car/trail.py | cdxxiaoge/StreetRoller | 3bb9b4ee8ddad9c1582f1aaf572591a09e5d3400 | [
"Apache-2.0"
] | null | null | null | car/car/trail.py | cdxxiaoge/StreetRoller | 3bb9b4ee8ddad9c1582f1aaf572591a09e5d3400 | [
"Apache-2.0"
] | null | null | null | car/car/trail.py | cdxxiaoge/StreetRoller | 3bb9b4ee8ddad9c1582f1aaf572591a09e5d3400 | [
"Apache-2.0"
] | null | null | null | from math import *
import pygame
import time
from pygame.locals import *
import json
def Coordinate_trans(y):
# 600为生成的窗口的高度
# 生成窗口screen_show = pygame.display.set_mode((1000, 600), 0, 32)
# 只需转换y坐标，即可使得以左下角为坐标原点
y = 600-y
return y
# 将接收的字符串转化为列表
# 和郭定联调的时候用
# def invert(re):
# # 此处固定油门值和方向... | 29.591623 | 100 | 0.506546 |
7eeb7db1cbda5d6082c499252d96c90270723760 | 422 | py | Python | leetcode/LongestCommonPrefix/py/LongestCommonPrefix_002.py | cc13ny/all-in | bc0b01e44e121ea68724da16f25f7e24386c53de | [
"MIT"
] | 1 | 2015-12-16T04:01:03.000Z | 2015-12-16T04:01:03.000Z | leetcode/LongestCommonPrefix/py/LongestCommonPrefix_002.py | cc13ny/all-in | bc0b01e44e121ea68724da16f25f7e24386c53de | [
"MIT"
] | 1 | 2016-02-09T06:00:07.000Z | 2016-02-09T07:20:13.000Z | leetcode/LongestCommonPrefix/py/LongestCommonPrefix_002.py | cc13ny/all-in | bc0b01e44e121ea68724da16f25f7e24386c53de | [
"MIT"
] | 2 | 2019-06-27T09:07:26.000Z | 2019-07-01T04:40:13.000Z | class Solution:
# @param {string[]} strs
# @return {string}
def longestCommonPrefix(self, strs):
res = ''
if strs == []:
return res
lens = [len(s) for s in strs]
mi = min(lens)
for i in range(mi):
a = set([s[i] for s in strs])
if l... | 23.444444 | 41 | 0.417062 |
6978b1d2a7e63215f6c792fb79d5e97d64a0d212 | 39,998 | py | Python | Python/GuiStepscope/ui_SS.py | jimwaschura/Automation | f655feeea74ff22ebe44d8b68374ba6983748f60 | [
"BSL-1.0"
] | null | null | null | Python/GuiStepscope/ui_SS.py | jimwaschura/Automation | f655feeea74ff22ebe44d8b68374ba6983748f60 | [
"BSL-1.0"
] | null | null | null | Python/GuiStepscope/ui_SS.py | jimwaschura/Automation | f655feeea74ff22ebe44d8b68374ba6983748f60 | [
"BSL-1.0"
] | null | null | null | # -*- coding: utf-8 -*-
# Form implementation generated from reading ui file 'ui_SS.ui'
#
# Created by: PyQt5 UI code generator 5.15.4
#
# WARNING: Any manual changes made to this file will be lost when pyuic5 is
# run again. Do not edit this file unless you know what you are doing.
from PyQt5 import QtCore, QtGui,... | 68.607204 | 138 | 0.750163 |
697a8c499f6803555e0d7014e3d068aad7ababc1 | 5,787 | py | Python | scripts/jdbc_maven_deploy.py | AldoMyrtaj/duckdb | 3aa4978a2ceab8df25e4b20c388bcd7629de73ed | [
"MIT"
] | 2,816 | 2018-06-26T18:52:52.000Z | 2021-04-06T10:39:15.000Z | scripts/jdbc_maven_deploy.py | AldoMyrtaj/duckdb | 3aa4978a2ceab8df25e4b20c388bcd7629de73ed | [
"MIT"
] | 1,310 | 2021-04-06T16:04:52.000Z | 2022-03-31T13:52:53.000Z | scripts/jdbc_maven_deploy.py | AldoMyrtaj/duckdb | 3aa4978a2ceab8df25e4b20c388bcd7629de73ed | [
"MIT"
] | 270 | 2021-04-09T06:18:28.000Z | 2022-03-31T11:55:37.000Z | # https://central.sonatype.org/pages/manual-staging-bundle-creation-and-deployment.html
# https://issues.sonatype.org/browse/OSSRH-58179
# this is the pgp key we use to sign releases
# if this key should be lost, generate a new one with `gpg --full-generate-key`
# AND upload to keyserver: `gpg --keyserver hkp://keys.... | 38.58 | 139 | 0.719889 |
699a4462c62d0ac4955c1772d4cd5a22fcaa4511 | 2,899 | py | Python | 20-fs-ias-lec/groups/09-loraSense/SenseLink/LoRaSense - Sensor/lib/lora_test_sensor_layer.py | Kyrus1999/BACnet | 5be8e1377252166041bcd0b066cce5b92b077d06 | [
"MIT"
] | 8 | 2020-03-17T21:12:18.000Z | 2021-12-12T15:55:54.000Z | 20-fs-ias-lec/groups/09-loraSense/SenseLink/LoRaSense - Sensor/lib/lora_test_sensor_layer.py | Kyrus1999/BACnet | 5be8e1377252166041bcd0b066cce5b92b077d06 | [
"MIT"
] | 2 | 2021-07-19T06:18:43.000Z | 2022-02-10T12:17:58.000Z | 20-fs-ias-lec/groups/09-loraSense/SenseLink/LoRaSense - Sensor/lib/lora_test_sensor_layer.py | Kyrus1999/BACnet | 5be8e1377252166041bcd0b066cce5b92b077d06 | [
"MIT"
] | 25 | 2020-03-20T09:32:45.000Z | 2021-07-18T18:12:59.000Z | from lora_feed_layer import Lora_Feed_Layer
import os, time, sys
import _thread
class Lora_Test_Sensor_Layer:
def __init__(self, feed_layer):
sys.setrecursionlimit(1500)
self.feed_layer = feed_layer
# Get sensor feed id (so far hard coded in lora_feed_layer)
self.fid = self.feed_... | 39.175676 | 96 | 0.64298 |
38938f5653ca390e7b811ad17b74751d43a5694c | 557 | py | Python | frds/mktstructure/measures/bidask_spread.py | mgao6767/wrds | 7dca2651a181bf38c61ebde675c9f64d6c96f608 | [
"MIT"
] | 1 | 2022-03-06T20:36:06.000Z | 2022-03-06T20:36:06.000Z | mktstructure/measures/bidask_spread.py | mgao6767/mktstructure | 5432c1bed163f838209d34b74c09629bea620ba8 | [
"MIT"
] | null | null | null | mktstructure/measures/bidask_spread.py | mgao6767/mktstructure | 5432c1bed163f838209d34b74c09629bea620ba8 | [
"MIT"
] | null | null | null | import numpy as np
import pandas as pd
from .exceptions import *
name = "BidAskSpread"
description = "Simple average bid-ask spread"
vars_needed = {"Bid Price", "Ask Price", "Mid Point"}
def estimate(data: pd.DataFrame) -> np.ndarray:
if not vars_needed.issubset(data.columns):
raise MissingVariableError... | 27.85 | 78 | 0.684022 |
389c7de74b5f729f8756c1a4e576c8261c8fb5a9 | 30 | py | Python | lib/python3.5/io.py | hwroitzsch/BikersLifeSaver | 469c738fdd6352c44a3f20689b17fa8ac04ad8a2 | [
"MIT"
] | 1 | 2020-08-16T04:04:23.000Z | 2020-08-16T04:04:23.000Z | lib/python3.5/io.py | hwroitzsch/BikersLifeSaver | 469c738fdd6352c44a3f20689b17fa8ac04ad8a2 | [
"MIT"
] | 5 | 2020-06-05T18:53:24.000Z | 2021-12-13T19:49:15.000Z | lib/python3.5/io.py | hwroitzsch/BikersLifeSaver | 469c738fdd6352c44a3f20689b17fa8ac04ad8a2 | [
"MIT"
] | null | null | null | /usr/local/lib/python3.5/io.py | 30 | 30 | 0.766667 |
38c36e059022f6e379b99c67ed78485d629f3ff5 | 1,455 | py | Python | crypto/crypto-snore/src/script.py | NoXLaw/RaRCTF2021-Challenges-Public | 1a1b094359b88f8ebbc83a6b26d27ffb2602458f | [
"MIT"
] | 2 | 2021-08-09T17:08:12.000Z | 2021-08-09T17:08:17.000Z | crypto/crypto-snore/src/script.py | NoXLaw/RaRCTF2021-Challenges-Public | 1a1b094359b88f8ebbc83a6b26d27ffb2602458f | [
"MIT"
] | null | null | null | crypto/crypto-snore/src/script.py | NoXLaw/RaRCTF2021-Challenges-Public | 1a1b094359b88f8ebbc83a6b26d27ffb2602458f | [
"MIT"
] | 1 | 2021-10-09T16:51:56.000Z | 2021-10-09T16:51:56.000Z | from Crypto.Util.number import *
from Crypto.Util.Padding import pad
from Crypto.Cipher import AES
from hashlib import sha224
from random import randrange
import os
p = 148982911401264734500617017580518449923542719532318121475997727602675813514863
g = 2
assert isPrime(p//2) # safe prime
x = randrange(p)
y = pow(g, x,... | 24.661017 | 82 | 0.649485 |
2a6d8c5d0b6cf1d07375bf09c23c353ac3e40fa7 | 388 | py | Python | opencv_tutorial/opencv3_youtube/prog03.py | zeroam/TIL | 43e3573be44c7f7aa4600ff8a34e99a65cbdc5d1 | [
"MIT"
] | null | null | null | opencv_tutorial/opencv3_youtube/prog03.py | zeroam/TIL | 43e3573be44c7f7aa4600ff8a34e99a65cbdc5d1 | [
"MIT"
] | null | null | null | opencv_tutorial/opencv3_youtube/prog03.py | zeroam/TIL | 43e3573be44c7f7aa4600ff8a34e99a65cbdc5d1 | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
"""
Created on Mon Mar 25 14:59:39 2019
@author: jone
"""
import cv2
import os.path
def main():
img_path = os.path.join('Dataset', 'lena_color_512.tif')
img = cv2.imread(img_path)
cv2.namedWindow('Lena', cv2.WINDOW_AUTOSIZE)
cv2.imshow('Lena', img)
cv2.waitKey(0)
... | 18.47619 | 60 | 0.623711 |
87948bb8098da14dc27d2d4b3483e3f2259a8948 | 8,901 | py | Python | Packs/TrustwaveFusion/Integrations/TrustwaveFusion/TrustwaveFusion_test.py | cstone112/content | 7f039931b8cfc20e89df52d895440b7321149a0d | [
"MIT"
] | 2 | 2021-12-06T21:38:24.000Z | 2022-01-13T08:23:36.000Z | Packs/TrustwaveFusion/Integrations/TrustwaveFusion/TrustwaveFusion_test.py | cstone112/content | 7f039931b8cfc20e89df52d895440b7321149a0d | [
"MIT"
] | 87 | 2022-02-23T12:10:53.000Z | 2022-03-31T11:29:05.000Z | Packs/TrustwaveFusion/Integrations/TrustwaveFusion/TrustwaveFusion_test.py | cstone112/content | 7f039931b8cfc20e89df52d895440b7321149a0d | [
"MIT"
] | 2 | 2022-01-05T15:27:01.000Z | 2022-02-01T19:27:43.000Z | import json
import io
import urllib
import pytest
import demistomock as demisto
from TrustwaveFusion import (
Client,
get_ticket_command,
add_ticket_comment_command,
close_ticket_command,
get_finding_command,
get_asset_command,
get_updated_tickets_command,
search_tickets_command,
... | 31.341549 | 147 | 0.688911 |
ea261e3a8fd322339ce9e9cdaeb3081c6d5b87c7 | 427 | py | Python | INBa/2015/RotkinAM/Zadacha_3_21.py | YukkaSarasti/pythonintask | eadf4245abb65f4400a3bae30a4256b4658e009c | [
"Apache-2.0"
] | null | null | null | INBa/2015/RotkinAM/Zadacha_3_21.py | YukkaSarasti/pythonintask | eadf4245abb65f4400a3bae30a4256b4658e009c | [
"Apache-2.0"
] | null | null | null | INBa/2015/RotkinAM/Zadacha_3_21.py | YukkaSarasti/pythonintask | eadf4245abb65f4400a3bae30a4256b4658e009c | [
"Apache-2.0"
] | null | null | null | #Задача № 3, Вариант 21
#Напишите программу, которая выводит имя "Аркадий Петрович Голиков", и запрашивает его псевдоним. Программа должна сцеплять две эти строки и выводить полученную строку, разделяя имя и псевдоним с помощью тире.
#Rotkin A.M.
#29.05.2016
print("Введите псевдоним Аркадия Петровича Голикова:" ')
RN= ... | 42.7 | 209 | 0.765808 |
d81e334cd569d4b366dffdd9a6a7d0fb5b3259f0 | 952 | py | Python | hardware/seat_cam/seat_classifier.py | BlueHC/TTHack-2018--Easy-Rider-1 | 8cd8f66de88ff80751a1083350c38985ac26914d | [
"Apache-2.0"
] | null | null | null | hardware/seat_cam/seat_classifier.py | BlueHC/TTHack-2018--Easy-Rider-1 | 8cd8f66de88ff80751a1083350c38985ac26914d | [
"Apache-2.0"
] | null | null | null | hardware/seat_cam/seat_classifier.py | BlueHC/TTHack-2018--Easy-Rider-1 | 8cd8f66de88ff80751a1083350c38985ac26914d | [
"Apache-2.0"
] | null | null | null | SEAT_X_THRESHOLD = 160
SEAT_Y_THRESHOLD = 120
STANDING_Y_THRESHOLD = 160
def classifySeatType(angleOfColorCode):
return (angleOfColorCode > 90) and "standing" or "seat"
def classifySeatPosition(x, y):
if(x < SEAT_X_THRESHOLD):
if(y < SEAT_Y_THRESHOLD):
return "FRONTLEFT"
else:
... | 26.444444 | 71 | 0.634454 |
dc7ca4fad96059fad955e123ff802ba83e4ffd35 | 1,069 | py | Python | software/supervisor/views/HistoryView.py | ghsecuritylab/project-powerline | 6c0ec13bbfc11c3790c506f644db4fe45021440a | [
"MIT"
] | null | null | null | software/supervisor/views/HistoryView.py | ghsecuritylab/project-powerline | 6c0ec13bbfc11c3790c506f644db4fe45021440a | [
"MIT"
] | null | null | null | software/supervisor/views/HistoryView.py | ghsecuritylab/project-powerline | 6c0ec13bbfc11c3790c506f644db4fe45021440a | [
"MIT"
] | 1 | 2020-03-08T01:50:58.000Z | 2020-03-08T01:50:58.000Z | """
comment
"""
from PyQt5.QtWidgets import QPushButton, QLabel, QWidget
from PyQt5.QtGui import QFont
class HistoryView(QWidget):
def __init__(self, parent):
super(HistoryView, self).__init__(parent)
font_title = QFont()
font_title.setBold(1)
self.ok_bt = QPushButton("OK", self... | 28.131579 | 82 | 0.635173 |
dc939abc45bd2b3dfa7a1c77e38ac312ad4f9e5e | 3,572 | py | Python | Webpage/cruises/migrations/0001_initial.py | ASV-Aachen/Website | bbfc02d71dde67fdf89a4b819b795a73435da7cf | [
"Apache-2.0"
] | null | null | null | Webpage/cruises/migrations/0001_initial.py | ASV-Aachen/Website | bbfc02d71dde67fdf89a4b819b795a73435da7cf | [
"Apache-2.0"
] | 46 | 2022-01-08T12:03:24.000Z | 2022-03-30T08:51:05.000Z | Webpage/cruises/migrations/0001_initial.py | ASV-Aachen/Website | bbfc02d71dde67fdf89a4b819b795a73435da7cf | [
"Apache-2.0"
] | null | null | null | # Generated by Django 3.2.10 on 2022-01-10 08:30
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='cruise',
fields=[
... | 49.611111 | 329 | 0.576428 |
f4fa1037397e3776fd92912a70a689fa3122c608 | 1,257 | py | Python | plotting/modules/styles/axes.py | metxchris/MMM-Explorer | 251b4d7af56241882611bc47e94ec2923e4be8da | [
"MIT"
] | null | null | null | plotting/modules/styles/axes.py | metxchris/MMM-Explorer | 251b4d7af56241882611bc47e94ec2923e4be8da | [
"MIT"
] | null | null | null | plotting/modules/styles/axes.py | metxchris/MMM-Explorer | 251b4d7af56241882611bc47e94ec2923e4be8da | [
"MIT"
] | null | null | null | # 3rd Party Packages
from matplotlib.pyplot import rcParams
# Local Packages
import plotting.modules.plotstyles
def init(style):
Axes = plotting.modules.plotstyles.StyleType.Axes
if style is Axes.WHITE:
rcParams.update({
'axes.grid': False,
'axes.facecolor': '#fff',
... | 27.326087 | 53 | 0.490056 |
762249a7526f8afcd1ca932b36e064bd258ec372 | 2,862 | py | Python | Packs/Active_Directory_Query/Scripts/SendEmailToManager/SendEmailToManager.py | diCagri/content | c532c50b213e6dddb8ae6a378d6d09198e08fc9f | [
"MIT"
] | 799 | 2016-08-02T06:43:14.000Z | 2022-03-31T11:10:11.000Z | Packs/Active_Directory_Query/Scripts/SendEmailToManager/SendEmailToManager.py | diCagri/content | c532c50b213e6dddb8ae6a378d6d09198e08fc9f | [
"MIT"
] | 9,317 | 2016-08-07T19:00:51.000Z | 2022-03-31T21:56:04.000Z | Packs/Active_Directory_Query/Scripts/SendEmailToManager/SendEmailToManager.py | diCagri/content | c532c50b213e6dddb8ae6a378d6d09198e08fc9f | [
"MIT"
] | 1,297 | 2016-08-04T13:59:00.000Z | 2022-03-31T23:43:06.000Z | import demistomock as demisto
from CommonServerPython import *
from CommonServerUserPython import *
from string import Template
import textwrap
email = demisto.get(demisto.args(), 'email')
if not email:
for t in demisto.incidents()[0]['labels']:
if t['type'] == 'Email/from':
email = t['value'].l... | 44.030769 | 125 | 0.657233 |
874f62969a207aa4a820b9617c5d457d3d38c910 | 7,349 | py | Python | kiosk/slackMessages.py | AndiBr/ffksk | ff4bc4ad26d4571eaa1a6ff815b2e6a876f8ba99 | [
"MIT"
] | null | null | null | kiosk/slackMessages.py | AndiBr/ffksk | ff4bc4ad26d4571eaa1a6ff815b2e6a876f8ba99 | [
"MIT"
] | 14 | 2018-09-12T06:59:55.000Z | 2020-02-26T07:17:48.000Z | kiosk/slackMessages.py | AndiBr/ffksk | ff4bc4ad26d4571eaa1a6ff815b2e6a876f8ba99 | [
"MIT"
] | null | null | null | from django.views.decorators.csrf import csrf_exempt
from django.http import HttpResponse
from django.conf import settings
from profil.models import KioskUser
from .slackCommands import slack_sendMessageToResponseUrl, getCancelAttachementForResponse, getOkAttachementForResponse
from .models import Produktpalette, Kios... | 40.827778 | 261 | 0.73425 |
33bb9c16305051e573a90d8484c3049e527b74cc | 300 | py | Python | frappe-bench/apps/erpnext/erpnext/patches/v5_0/project_costing.py | Semicheche/foa_frappe_docker | a186b65d5e807dd4caf049e8aeb3620a799c1225 | [
"MIT"
] | null | null | null | frappe-bench/apps/erpnext/erpnext/patches/v5_0/project_costing.py | Semicheche/foa_frappe_docker | a186b65d5e807dd4caf049e8aeb3620a799c1225 | [
"MIT"
] | null | null | null | frappe-bench/apps/erpnext/erpnext/patches/v5_0/project_costing.py | Semicheche/foa_frappe_docker | a186b65d5e807dd4caf049e8aeb3620a799c1225 | [
"MIT"
] | null | null | null | import frappe
def execute():
frappe.reload_doctype("Project")
frappe.db.sql("update `tabProject` set expected_start_date = project_start_date, \
expected_end_date = completion_date, actual_end_date = act_completion_date, \
estimated_costing = project_value, gross_margin = gross_margin_value") | 42.857143 | 83 | 0.806667 |
1d28793a3c546753adcc460fab95d501a07be2fa | 1,898 | py | Python | unsupervised_learning/agglomerative.py | toorajtaraz/computational_intelligence_mini_projects | 79d1782c3b61ee15ac01dcf377bdc369962adb18 | [
"MIT"
] | 3 | 2022-02-09T21:35:14.000Z | 2022-02-10T15:31:43.000Z | unsupervised_learning/agglomerative.py | toorajtaraz/computational_intelligence_mini_projects | 79d1782c3b61ee15ac01dcf377bdc369962adb18 | [
"MIT"
] | null | null | null | unsupervised_learning/agglomerative.py | toorajtaraz/computational_intelligence_mini_projects | 79d1782c3b61ee15ac01dcf377bdc369962adb18 | [
"MIT"
] | null | null | null | from pathlib import Path
import sys
path = str(Path(Path(__file__).parent.absolute()).parent.absolute())
sys.path.insert(0, path)
from sklearn.cluster import AgglomerativeClustering
from sklearn.metrics import accuracy_score, adjusted_rand_score
from tabulate import tabulate
from mnist_utils.util import _x, _y_int
impo... | 33.298246 | 118 | 0.686512 |
8935b8abf1b2899bcb951d8ecead878699c7770f | 7,650 | py | Python | haferml/preprocess/pipeline.py | emptymalei/haferml | ba193ce1c022c89fb4e88924b7bb7a05b676929a | [
"MIT"
] | 11 | 2021-04-17T18:51:45.000Z | 2021-06-25T19:42:25.000Z | haferml/preprocess/pipeline.py | emptymalei/haferml | ba193ce1c022c89fb4e88924b7bb7a05b676929a | [
"MIT"
] | 3 | 2021-04-29T19:24:15.000Z | 2021-05-21T04:30:54.000Z | haferml/preprocess/pipeline.py | emptymalei/haferml | ba193ce1c022c89fb4e88924b7bb7a05b676929a | [
"MIT"
] | 2 | 2021-06-10T00:55:43.000Z | 2021-12-30T07:37:07.000Z | import pandas as pd
from haferml.preprocess.ingredients import OrderedProcessor, attributes
from loguru import logger
class BasePreProcessor(OrderedProcessor):
"""
Shared methods to transform the datasets
The following example demonstrates how to use it.
```python
from haferml.preprocess.ingredi... | 32.553191 | 159 | 0.552549 |
7fa90f98747b6771387bccf49d1f8636a8cf57bd | 110 | py | Python | sources/stage03/countdownwhile.py | kantel/pythonschulung2 | b13fb24770dd7789f3845aeb147a720dff272951 | [
"MIT"
] | null | null | null | sources/stage03/countdownwhile.py | kantel/pythonschulung2 | b13fb24770dd7789f3845aeb147a720dff272951 | [
"MIT"
] | null | null | null | sources/stage03/countdownwhile.py | kantel/pythonschulung2 | b13fb24770dd7789f3845aeb147a720dff272951 | [
"MIT"
] | null | null | null | def countdown(n):
while n > 0:
print(n)
n -= 1
print("Whammm … 💥💥💥!!")
countdown(10): | 15.714286 | 27 | 0.454545 |
c3978b69fabf654e0d41c178b1fb684a26631dfe | 61 | py | Python | Python/Courses/Python-Tutorials.Telusko/00.Fundamentals/06.4-Input-expression.py | shihab4t/Books-Code | b637b6b2ad42e11faf87d29047311160fe3b2490 | [
"Unlicense"
] | null | null | null | Python/Courses/Python-Tutorials.Telusko/00.Fundamentals/06.4-Input-expression.py | shihab4t/Books-Code | b637b6b2ad42e11faf87d29047311160fe3b2490 | [
"Unlicense"
] | null | null | null | Python/Courses/Python-Tutorials.Telusko/00.Fundamentals/06.4-Input-expression.py | shihab4t/Books-Code | b637b6b2ad42e11faf87d29047311160fe3b2490 | [
"Unlicense"
] | null | null | null | result = eval(input("Enter an expression: "))
print(result)
| 15.25 | 45 | 0.704918 |
7f166a8c49b8dd221096f58ef67b49eb947c9119 | 5,191 | py | Python | cloud/global/lambda/k8s-job-launcher/service.py | cloud-cds/cds-stack | d68a1654d4f604369a071f784cdb5c42fc855d6e | [
"Apache-2.0"
] | 6 | 2018-06-27T00:09:55.000Z | 2019-03-07T14:06:53.000Z | cloud/global/lambda/k8s-job-launcher/service.py | cloud-cds/cds-stack | d68a1654d4f604369a071f784cdb5c42fc855d6e | [
"Apache-2.0"
] | 3 | 2021-03-31T18:37:46.000Z | 2021-06-01T21:49:41.000Z | cloud/global/lambda/k8s-job-launcher/service.py | cloud-cds/cds-stack | d68a1654d4f604369a071f784cdb5c42fc855d6e | [
"Apache-2.0"
] | 3 | 2020-01-24T16:40:49.000Z | 2021-09-30T02:28:55.000Z | # -*- coding: utf-8 -*-
import os, pykube, yaml, json, copy
from datetime import datetime, timedelta
import dateutil.parser
# REQUIRED env vars:
# kube_job_name
# kube_name
# kube_server
# kube_cert_auth
# kube_user
# kube_pass
# kube_image
#
# OPTIONAL:
# kube_cmd_*
#
# REQUIRED k8s secrets:
# aws-secrets
#
# ENV VA... | 29 | 127 | 0.648045 |
4efe585ffa783e6e1e28fb949b1432a713d6b41c | 1,025 | py | Python | src/python3_learn_video/standard_library.py | HuangHuaBingZiGe/GitHub-Demo | f3710f73b0828ef500343932d46c61d3b1e04ba9 | [
"Apache-2.0"
] | null | null | null | src/python3_learn_video/standard_library.py | HuangHuaBingZiGe/GitHub-Demo | f3710f73b0828ef500343932d46c61d3b1e04ba9 | [
"Apache-2.0"
] | null | null | null | src/python3_learn_video/standard_library.py | HuangHuaBingZiGe/GitHub-Demo | f3710f73b0828ef500343932d46c61d3b1e04ba9 | [
"Apache-2.0"
] | null | null | null | """
Python 标准库中包含一般任务所需要的模块:
PEP 是 Python Enhancement Proposals 的缩写
翻译过来就是Python增强建议书的意思
它是用来规范与定义Python的各种加强与延伸功能的技术规格，好让Python开发社区能有共同遵循的依据
每个PEP都有一个唯一的编号,这个编号一旦给定了就不会再改变
例如，PEP 3000 就是用来定义 Python 3.0 的相关技术规格
而PEP 333 则是Python的Web应用程序界面WSGI（Web Server Gateway Interface 1.0）的规范
关于PEP本身的相关规范是定义在PEP 1，而PEP 8 则定义了 P... | 23.837209 | 68 | 0.516098 |
f665be7e6a8a77931c7ab380d3b70bb22847d4ad | 906 | py | Python | task_7_7.py | YukkaSarasti/pythonintask | eadf4245abb65f4400a3bae30a4256b4658e009c | [
"Apache-2.0"
] | null | null | null | task_7_7.py | YukkaSarasti/pythonintask | eadf4245abb65f4400a3bae30a4256b4658e009c | [
"Apache-2.0"
] | null | null | null | task_7_7.py | YukkaSarasti/pythonintask | eadf4245abb65f4400a3bae30a4256b4658e009c | [
"Apache-2.0"
] | null | null | null | # Задача 7. Вариант 7.
# Разработайте систему начисления очков для задачи 6, в соответствии с которой игрок получал бы большее количество баллов за меньшее количество попыток.
# Videneev P.A.
# 26.05.2016
import random
score=10
x=random.randint(1,2)
if x==1:
name="Сергей Брин"
print("Игра.")
elif x==2:
... | 30.2 | 153 | 0.708609 |
140e5885bd1690a8e4c73fbea1c1622e5a825864 | 87 | py | Python | profil/apps.py | AndiBr/ffksk | ff4bc4ad26d4571eaa1a6ff815b2e6a876f8ba99 | [
"MIT"
] | 7 | 2018-08-02T05:57:10.000Z | 2020-05-18T21:59:43.000Z | blog/profil/apps.py | 3bru/myBlog | 415f35d9a9934f5642abc9bc5ebd2b6b68073822 | [
"MIT"
] | 14 | 2018-09-12T06:59:55.000Z | 2020-02-26T07:17:48.000Z | profil/apps.py | AndiBr/ffksk | ff4bc4ad26d4571eaa1a6ff815b2e6a876f8ba99 | [
"MIT"
] | null | null | null | from django.apps import AppConfig
class ProfilConfig(AppConfig):
name = 'profil'
| 14.5 | 33 | 0.747126 |
141f50c23b33f81c5f7ab52e87c0317fa98a83e2 | 1,730 | py | Python | noticias/migrations/0001_initial.py | miglesias91/dt | 6e00f883ebdb581f87750852f18cf9e3058aae2f | [
"MIT"
] | null | null | null | noticias/migrations/0001_initial.py | miglesias91/dt | 6e00f883ebdb581f87750852f18cf9e3058aae2f | [
"MIT"
] | null | null | null | noticias/migrations/0001_initial.py | miglesias91/dt | 6e00f883ebdb581f87750852f18cf9e3058aae2f | [
"MIT"
] | null | null | null | # Generated by Django 2.2.1 on 2019-05-06 20:49
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies = [
]
operations = [
migrations.CreateModel(
name='Comentario',
fields=[
... | 37.608696 | 121 | 0.563584 |
2c2703e050e28dceceb35ff0e546b72d304f918b | 1,669 | py | Python | tests/test_sharepoint_helper.py | MZH-bust/genutil | f17190ec484d5844f8950908cc07556a5b1429e7 | [
"MIT"
] | null | null | null | tests/test_sharepoint_helper.py | MZH-bust/genutil | f17190ec484d5844f8950908cc07556a5b1429e7 | [
"MIT"
] | null | null | null | tests/test_sharepoint_helper.py | MZH-bust/genutil | f17190ec484d5844f8950908cc07556a5b1429e7 | [
"MIT"
] | null | null | null | import pytest
from genutil import sharepoint_helper
class TestSpFieldText:
@pytest.mark.parametrize(
"test_parameter,expected",
[
pytest.param("20;#Lastname1, Firstname1;#91;#Lastname2, Firstname2;#184;#Lastname3, Firstname3",
("Lastname1, Firstname1; Lastname2... | 52.15625 | 117 | 0.536249 |
9fa52c802c46c68ba344bca229fe97c600df7320 | 1,083 | py | Python | Lehrjahr_2/Modul_122/python/EingabeValidierung.py | severinkaderli/gibb | 5b4952cedacb3885ab4a0eb9fd6c1cab5674e3ee | [
"MIT"
] | 5 | 2015-05-19T14:26:53.000Z | 2016-06-24T17:03:03.000Z | Lehrjahr_2/Modul_122/python/EingabeValidierung.py | severinkaderli/gibb | 5b4952cedacb3885ab4a0eb9fd6c1cab5674e3ee | [
"MIT"
] | null | null | null | Lehrjahr_2/Modul_122/python/EingabeValidierung.py | severinkaderli/gibb | 5b4952cedacb3885ab4a0eb9fd6c1cab5674e3ee | [
"MIT"
] | 6 | 2015-05-26T06:25:05.000Z | 2020-04-30T07:25:30.000Z | #!/usr/bin/python3.4
#
#SCRIPT: EingabeValidierung.py
#AUTHOR: Severin Kaderli
#PURPOSE: Validates user input
#USAGE: ./EingabeValidierung.py 'Begriff'
import re
import sys
def validation(begriff):
#Vorname & Name: 'Severin Kaderli'
if re.search('\w{3,}\s\w{3,}', begriff):
print('Name/Vorname')
#Strasse und Hausn... | 27.769231 | 61 | 0.676824 |
e2238a06865b3167c42d8fa9414ea20f1fc20ddc | 167 | py | Python | authApp/admin.py | xlausae/Web-Service | fbc4b45f34fe5ac69d8da2ffe09e5c32046e27d5 | [
"MIT"
] | null | null | null | authApp/admin.py | xlausae/Web-Service | fbc4b45f34fe5ac69d8da2ffe09e5c32046e27d5 | [
"MIT"
] | 1 | 2022-01-05T23:52:37.000Z | 2022-01-05T23:52:37.000Z | authApp/admin.py | xlausae/Web-Service | fbc4b45f34fe5ac69d8da2ffe09e5c32046e27d5 | [
"MIT"
] | null | null | null | from django.contrib import admin
from .models.user import User
from .models.account import Account
admin.site.register(User)
admin.site.register(Account) | 27.833333 | 38 | 0.760479 |
1a5c44f290fd502f9b38b8f22995fa9b562ab2f9 | 1,218 | py | Python | packages/watchmen-model/src/watchmen_model/admin/__init__.py | Indexical-Metrics-Measure-Advisory/watchmen | c54ec54d9f91034a38e51fd339ba66453d2c7a6d | [
"MIT"
] | null | null | null | packages/watchmen-model/src/watchmen_model/admin/__init__.py | Indexical-Metrics-Measure-Advisory/watchmen | c54ec54d9f91034a38e51fd339ba66453d2c7a6d | [
"MIT"
] | null | null | null | packages/watchmen-model/src/watchmen_model/admin/__init__.py | Indexical-Metrics-Measure-Advisory/watchmen | c54ec54d9f91034a38e51fd339ba66453d2c7a6d | [
"MIT"
] | null | null | null | from .conditional import Conditional
from .enumeration import Enum, EnumItem
from .factor import Factor, FactorEncryptMethod, FactorIndexGroup, FactorType
from .pipeline import Pipeline, PipelineStage, PipelineTriggerType, PipelineUnit
from .pipeline_action import AggregateArithmetic, AggregateArithmeticHolder, DeleteT... | 64.105263 | 117 | 0.863711 |
b391b768252b05b0c8da8719416ed0c050cfd882 | 757 | py | Python | spo/spo/doctype/triage_anonym/triage_anonym.py | libracore/spo | efff6da53a776c4483f06d9ef1acc8a7aa96b28e | [
"MIT"
] | null | null | null | spo/spo/doctype/triage_anonym/triage_anonym.py | libracore/spo | efff6da53a776c4483f06d9ef1acc8a7aa96b28e | [
"MIT"
] | 6 | 2019-08-23T18:36:26.000Z | 2019-11-12T13:12:12.000Z | spo/spo/doctype/triage_anonym/triage_anonym.py | libracore/spo | efff6da53a776c4483f06d9ef1acc8a7aa96b28e | [
"MIT"
] | 1 | 2021-08-14T22:22:43.000Z | 2021-08-14T22:22:43.000Z | # -*- coding: utf-8 -*-
# Copyright (c) 2021, libracore and contributors
# For license information, please see license.txt
from __future__ import unicode_literals
import frappe
from frappe.model.document import Document
class TriageAnonym(Document):
pass
@frappe.whitelist()
def create_view(triage):
triage = ... | 30.28 | 60 | 0.705416 |
37be1c3916379c29617d9c3b907cc99e6464ba73 | 7,279 | py | Python | public/chart/integrations/django/samples/fusioncharts/fusioncharts.py | AizaDapitan/PMC-IMS_V3 | 271ce3193edbf5182a9e232666ca417561ba2d16 | [
"MIT"
] | 14 | 2016-11-03T19:06:21.000Z | 2021-11-24T09:05:09.000Z | public/chart/integrations/django/samples/fusioncharts/fusioncharts.py | AizaDapitan/PMC-IMS_V3 | 271ce3193edbf5182a9e232666ca417561ba2d16 | [
"MIT"
] | 15 | 2019-12-10T06:22:19.000Z | 2022-03-11T23:46:49.000Z | asset/integrations/django/samples/fusioncharts/fusioncharts.py | Piusshungu/catherine-junior-school | 5356f4ff5a5c8383849d32e22a60d638c35b1a48 | [
"MIT"
] | 17 | 2016-05-19T13:16:34.000Z | 2021-04-30T14:38:42.000Z | from django.http import HttpResponse
import json
from collections import OrderedDict
from io import StringIO
from enum import Enum
# Common base class for FC
class FusionCharts:
baseTemplate = """
<script type="text/javascript">
FusionCharts.ready(function () {
__TS__
... | 38.109948 | 146 | 0.642671 |
03b0abad2f1180c326c8ff4e5635ae9383d4d60e | 211 | py | Python | exercises/de/exc_02_10_02.py | Jette16/spacy-course | 32df0c8f6192de6c9daba89740a28c0537e4d6a0 | [
"MIT"
] | 2,085 | 2019-04-17T13:10:40.000Z | 2022-03-30T21:51:46.000Z | exercises/de/exc_02_10_02.py | Jette16/spacy-course | 32df0c8f6192de6c9daba89740a28c0537e4d6a0 | [
"MIT"
] | 79 | 2019-04-18T14:42:55.000Z | 2022-03-07T08:15:43.000Z | exercises/de/exc_02_10_02.py | Jette16/spacy-course | 32df0c8f6192de6c9daba89740a28c0537e4d6a0 | [
"MIT"
] | 361 | 2019-04-17T13:34:32.000Z | 2022-03-28T04:42:45.000Z | import spacy
nlp = spacy.load("en_core_web_md")
doc = nlp("TV and books")
token1, token2 = doc[0], doc[2]
# Berechne die Ähnlichkeit der Tokens "TV" und "books"
similarity = ____.____(____)
print(similarity)
| 19.181818 | 54 | 0.71564 |
03b22613da1e00791064aaba800cb937ecbc8cfb | 19,876 | py | Python | tests/onegov/org/test_views_event.py | politbuero-kampagnen/onegov-cloud | 20148bf321b71f617b64376fe7249b2b9b9c4aa9 | [
"MIT"
] | null | null | null | tests/onegov/org/test_views_event.py | politbuero-kampagnen/onegov-cloud | 20148bf321b71f617b64376fe7249b2b9b9c4aa9 | [
"MIT"
] | null | null | null | tests/onegov/org/test_views_event.py | politbuero-kampagnen/onegov-cloud | 20148bf321b71f617b64376fe7249b2b9b9c4aa9 | [
"MIT"
] | null | null | null | import babel.dates
import pytest
import transaction
from datetime import datetime, date, timedelta
from onegov.event.models import Event
from tests.shared.utils import create_image
from tests.shared.utils import get_meta
from webtest.forms import Upload
def test_view_occurrences(client):
client.login_admin()
... | 35.877256 | 79 | 0.65808 |
20e571ccfa4e143408b118c60b2c630d41411c45 | 1,479 | py | Python | ProjectEuler_plus/euler_107.py | byung-u/HackerRank | 4c02fefff7002b3af774b99ebf8d40f149f9d163 | [
"MIT"
] | null | null | null | ProjectEuler_plus/euler_107.py | byung-u/HackerRank | 4c02fefff7002b3af774b99ebf8d40f149f9d163 | [
"MIT"
] | null | null | null | ProjectEuler_plus/euler_107.py | byung-u/HackerRank | 4c02fefff7002b3af774b99ebf8d40f149f9d163 | [
"MIT"
] | null | null | null | #!/usr/bin/env python3
from operator import itemgetter
# reference
# https://inanemathgeek.wordpress.com/2012/10/15/euler-107-back-to-python/
class DisjointSet (dict):
def add(self, item):
self[item] = item
def find(self, item):
parent = self[item]
while self[parent] != parent:
... | 22.753846 | 74 | 0.53144 |
4551eb718bb93c5ee16fe9448ac412aa299f9024 | 2,620 | py | Python | project/api/recycling_street/resources.py | DanielGrams/cityservice | c487c34b5ba6541dcb441fe903ab2012c2256893 | [
"MIT"
] | null | null | null | project/api/recycling_street/resources.py | DanielGrams/cityservice | c487c34b5ba6541dcb441fe903ab2012c2256893 | [
"MIT"
] | 35 | 2022-01-24T22:15:59.000Z | 2022-03-31T15:01:35.000Z | project/api/recycling_street/resources.py | DanielGrams/cityservice | c487c34b5ba6541dcb441fe903ab2012c2256893 | [
"MIT"
] | null | null | null | from flask_apispec import doc, marshal_with, use_kwargs
from sqlalchemy.sql.expression import func
from project.api import add_api_resource
from project.api.recycling_street.schemas import (
RecyclingStreetEventListRequestSchema,
RecyclingStreetEventListResponseSchema,
RecyclingStreetSchema,
)
from project... | 31.95122 | 88 | 0.698855 |
445fe7c65041b7e865a893dd15174ffdf0a25fd9 | 174 | py | Python | Python/zzz_training_challenge/Python_Challenge/solutions/ch04_strings/intro/intro_capitalize_title.py | Kreijeck/learning | eaffee08e61f2a34e01eb8f9f04519aac633f48c | [
"MIT"
] | null | null | null | Python/zzz_training_challenge/Python_Challenge/solutions/ch04_strings/intro/intro_capitalize_title.py | Kreijeck/learning | eaffee08e61f2a34e01eb8f9f04519aac633f48c | [
"MIT"
] | null | null | null | Python/zzz_training_challenge/Python_Challenge/solutions/ch04_strings/intro/intro_capitalize_title.py | Kreijeck/learning | eaffee08e61f2a34e01eb8f9f04519aac633f48c | [
"MIT"
] | null | null | null | # Beispielprogramm für das Buch "Python Challenge"
#
# Copyright 2020 by Michael Inden
text = "this is a very special string"
print(text.capitalize())
print(text.title())
| 17.4 | 50 | 0.741379 |
929ef66aaa6f78fb52c438df6e2022105f4b678d | 700 | py | Python | create_slides.py | oakoneric/programmierung-ss19 | 819a789020d7e280b1cb54f14494674e6772adce | [
"MIT"
] | 9 | 2019-04-10T21:32:59.000Z | 2019-07-29T14:58:17.000Z | create_slides.py | oakoneric/programmierung-ss19 | 819a789020d7e280b1cb54f14494674e6772adce | [
"MIT"
] | null | null | null | create_slides.py | oakoneric/programmierung-ss19 | 819a789020d7e280b1cb54f14494674e6772adce | [
"MIT"
] | 1 | 2021-07-19T14:07:26.000Z | 2021-07-19T14:07:26.000Z | import os
import io
# here = os.getcwd
here = os.path.dirname(os.path.abspath(__file__))
# settings for final titlepage folder
# path = input('Type the destinations path: ')
filename = input('Type the files name: ')
# prepare filenames and files
tempFilename = 'tempfile'
texExt = '.tex'
pdfExt = '.pdf'
tempTexFile ... | 25 | 95 | 0.74 |
4709f098eb2f74124699c28dae5548a41a0ec66a | 209 | py | Python | exercises/de/exc_03_14_03.py | Jette16/spacy-course | 32df0c8f6192de6c9daba89740a28c0537e4d6a0 | [
"MIT"
] | 2,085 | 2019-04-17T13:10:40.000Z | 2022-03-30T21:51:46.000Z | exercises/de/exc_03_14_03.py | Jette16/spacy-course | 32df0c8f6192de6c9daba89740a28c0537e4d6a0 | [
"MIT"
] | 79 | 2019-04-18T14:42:55.000Z | 2022-03-07T08:15:43.000Z | exercises/de/exc_03_14_03.py | Jette16/spacy-course | 32df0c8f6192de6c9daba89740a28c0537e4d6a0 | [
"MIT"
] | 361 | 2019-04-17T13:34:32.000Z | 2022-03-28T04:42:45.000Z | from spacy.lang.de import German
nlp = German()
people = ["David Bowie", "Angela Merkel", "Lady Gaga"]
# Erstelle eine Liste von Patterns für den PhraseMatcher
patterns = [nlp(person) for person in people]
| 23.222222 | 56 | 0.732057 |
f3c103405b5f6135605bd6cd8acdc1e9f6246bb0 | 572 | py | Python | python/pickle/custom_unpickling.py | zeroam/TIL | 43e3573be44c7f7aa4600ff8a34e99a65cbdc5d1 | [
"MIT"
] | null | null | null | python/pickle/custom_unpickling.py | zeroam/TIL | 43e3573be44c7f7aa4600ff8a34e99a65cbdc5d1 | [
"MIT"
] | null | null | null | python/pickle/custom_unpickling.py | zeroam/TIL | 43e3573be44c7f7aa4600ff8a34e99a65cbdc5d1 | [
"MIT"
] | null | null | null | import pickle
class foobar:
def __init__(self):
self.a = 35
self.b = "test"
self.c = lambda x: x * x
def __getstate__(self):
attributes = self.__dict__.copy()
del attributes["c"]
return attributes
def __setstate__(self, state):
self.... | 22.88 | 52 | 0.627622 |
ca9fa9df6fed5ad6d06e8883ae2eb20849b61fb9 | 1,920 | py | Python | examples/keras-iris-pipeline/train_model_and_transform.py | pcrete/skil-python | 672a1aa9e8af020c960ab9ee280cbb6b194afc3f | [
"Apache-2.0"
] | 23 | 2018-09-19T13:34:27.000Z | 2022-02-14T09:49:35.000Z | examples/keras-iris-pipeline/train_model_and_transform.py | pcrete/skil-python | 672a1aa9e8af020c960ab9ee280cbb6b194afc3f | [
"Apache-2.0"
] | 33 | 2018-10-18T07:58:05.000Z | 2019-05-16T08:24:12.000Z | examples/keras-iris-pipeline/train_model_and_transform.py | pcrete/skil-python | 672a1aa9e8af020c960ab9ee280cbb6b194afc3f | [
"Apache-2.0"
] | 11 | 2018-10-21T18:58:57.000Z | 2022-02-14T09:49:36.000Z | from pydatavec.utils import download_file
from pydatavec import Schema, TransformProcess
from keras.models import Sequential
from keras.layers import Dense
from keras.optimizers import Adam
import numpy as np
import os
import pyspark
# Download dataset, if not already downloaded.
filename = "iris.data"
temp_filename ... | 31.47541 | 80 | 0.746875 |
1b148593b33a4653cd7028c98a6405abf5446441 | 2,859 | py | Python | gateway-os/software/fang-module/src/capture.py | LucasRGoes/ladon-io | ab55219b461e918cc0ba45e6cdc9bcdfbce8c0d6 | [
"MIT"
] | 1 | 2018-04-29T22:33:42.000Z | 2018-04-29T22:33:42.000Z | gateway-os/software/fang-module/src/capture.py | LucasRGoes/ladon-io | ab55219b461e918cc0ba45e6cdc9bcdfbce8c0d6 | [
"MIT"
] | null | null | null | gateway-os/software/fang-module/src/capture.py | LucasRGoes/ladon-io | ab55219b461e918cc0ba45e6cdc9bcdfbce8c0d6 | [
"MIT"
] | null | null | null | ## IMPORTS ##
import logging # Logging: provides a set of convenience functions for simple logging usage
import time # Time: provides various time-related functions
import numpy as np # NumPy: the fundamental package for scientific computing with Python
import cv2 # OpenCV: usage ranges from interactive art, to ... | 25.526786 | 134 | 0.696048 |
1b6aed3239219e427e2668a5e8e6a9e193529dd3 | 10,834 | py | Python | classification_snips/rest.py | Ilgmi/IWIbot | c5ac71865fbb11f1676ec3239b96bab8e22257ee | [
"Apache-2.0"
] | null | null | null | classification_snips/rest.py | Ilgmi/IWIbot | c5ac71865fbb11f1676ec3239b96bab8e22257ee | [
"Apache-2.0"
] | null | null | null | classification_snips/rest.py | Ilgmi/IWIbot | c5ac71865fbb11f1676ec3239b96bab8e22257ee | [
"Apache-2.0"
] | null | null | null | # -*- coding: utf-8 -*-
import atexit
import json
import os
import sys
import cf_deployment_tracker
import metrics_tracker_client
# use natural language toolkit
import nltk
from classifier.classifier import Classifier
from classifier.trainer import SnipsNluTrainer
from classifier.cos_context import CosContext
from cla... | 31.958702 | 132 | 0.665498 |
945ca5fd6e31990de4bd1fa8a66ef4f88b1feb0e | 2,669 | py | Python | server/weather/WeatherServer.py | EveryOtherUsernameWasAlreadyTaken/BIS | e132ce42dcc74e634231398dfecb08834d478cba | [
"MIT"
] | 3 | 2019-07-09T08:51:20.000Z | 2019-09-16T17:27:54.000Z | server/weather/WeatherServer.py | thomasw-mitutoyo-ctl/BIS | 08525cc12164902dfe968ae41beb6de0cd5bc411 | [
"MIT"
] | 24 | 2019-06-17T12:33:35.000Z | 2020-03-27T08:17:35.000Z | server/weather/WeatherServer.py | EveryOtherUsernameWasAlreadyTaken/BIS | e132ce42dcc74e634231398dfecb08834d478cba | [
"MIT"
] | 1 | 2020-03-24T17:54:07.000Z | 2020-03-24T17:54:07.000Z | #!/usr/bin/python
import logging.handlers
import json
from OpenWeatherMapWeatherSource import OpenWeatherMapWeatherSource
from RestWeatherProvider import RestWeatherProvider
from RestWeatherSource import RestWeatherSource
from WeatherDataRepository import WeatherDataRepository
SERVER_ADDRESS = "localhost"
SERVER_POR... | 35.586667 | 106 | 0.693893 |
04a40f404e8d4d3dfc76a77b84b800cb1818bf90 | 220 | py | Python | divvydash/dashboard/serializers.py | Sawyer-Middeleer/divvy-dash | 5ef1738d47516949f7288b56b5c92a5c7d1d9d42 | [
"MIT"
] | null | null | null | divvydash/dashboard/serializers.py | Sawyer-Middeleer/divvy-dash | 5ef1738d47516949f7288b56b5c92a5c7d1d9d42 | [
"MIT"
] | 5 | 2020-06-06T01:45:31.000Z | 2021-06-10T19:59:14.000Z | divvydash/dashboard/serializers.py | Sawyer-Middeleer/divvy-dash | 5ef1738d47516949f7288b56b5c92a5c7d1d9d42 | [
"MIT"
] | null | null | null | from rest_framework import serializers
from dashboard.models import Station
# station serializer
class StationSerializer(serializers.ModelSerializer):
class Meta:
model = Station
fields = '__all__'
| 22 | 53 | 0.754545 |
b62d18be64587ba593ca69919ae293cc6abeefff | 914 | py | Python | 03 Python/Entwicklung eines IoT-Devices/aufgabe/src/my_iot_device/pubsub.py | DennisSchulmeister/dhbwka-wwi-iottech-quellcodes | 58f86907af31187f267a9ea476f061cc59098ebd | [
"CC-BY-4.0"
] | null | null | null | 03 Python/Entwicklung eines IoT-Devices/aufgabe/src/my_iot_device/pubsub.py | DennisSchulmeister/dhbwka-wwi-iottech-quellcodes | 58f86907af31187f267a9ea476f061cc59098ebd | [
"CC-BY-4.0"
] | null | null | null | 03 Python/Entwicklung eines IoT-Devices/aufgabe/src/my_iot_device/pubsub.py | DennisSchulmeister/dhbwka-wwi-iottech-quellcodes | 58f86907af31187f267a9ea476f061cc59098ebd | [
"CC-BY-4.0"
] | 1 | 2020-10-10T20:24:05.000Z | 2020-10-10T20:24:05.000Z | import os, threading
class PublishSubscribeBroker:
"""
Diese Klasse implementiert einen einfachen lokalen Message Broker
zur Umsetzung des Publish/Subscribe (oder auch Observer) Patterns.
Beliebige Threads können üb er die publish()-Methode beliebige
Nachrichten an beliebige Topics senden, wob... | 41.545455 | 71 | 0.752735 |
b657ba3d09f7194dcdbae22eb1b695209990959f | 3,564 | py | Python | tensorflow/basic-rl/tutorial2/mouse.py | gopala-kr/ds-notebooks | bc35430ecdd851f2ceab8f2437eec4d77cb59423 | [
"MIT"
] | 1 | 2019-05-10T09:16:23.000Z | 2019-05-10T09:16:23.000Z | tensorflow/basic-rl/tutorial2/mouse.py | gopala-kr/ds-notebooks | bc35430ecdd851f2ceab8f2437eec4d77cb59423 | [
"MIT"
] | null | null | null | tensorflow/basic-rl/tutorial2/mouse.py | gopala-kr/ds-notebooks | bc35430ecdd851f2ceab8f2437eec4d77cb59423 | [
"MIT"
] | 1 | 2019-05-10T09:17:28.000Z | 2019-05-10T09:17:28.000Z | import cellular
import qlearn
import time
import random
import shelve
directions = 8
def pickRandomLocation():
while 1:
x = random.randrange(world.width)
y = random.randrange(world.height)
cell = world.getCell(x, y)
if not (cell.wall or len(cell.agents) > 0):
... | 25.826087 | 98 | 0.549383 |
1524152a0d63060884bdea5d6e5cb97a69ead42f | 2,391 | py | Python | src/data_science/data_science/automation/control.py | viclule/api_models_deployment_framework | 7595cf0b4f3e277925b968014102d7561547bcd4 | [
"MIT"
] | null | null | null | src/data_science/data_science/automation/control.py | viclule/api_models_deployment_framework | 7595cf0b4f3e277925b968014102d7561547bcd4 | [
"MIT"
] | null | null | null | src/data_science/data_science/automation/control.py | viclule/api_models_deployment_framework | 7595cf0b4f3e277925b968014102d7561547bcd4 | [
"MIT"
] | null | null | null | from simple_pid import PID
from data_science.tools.threading_utilities import StoppableThread
class PIDController():
"""Implements a PID controller in a stoppable thread."""
def __init__(self, kp, ki, kd, bottom_output_limit=0, upper_output_limit=1,
sample_time=0.1):
self.pid = PID(... | 29.8875 | 79 | 0.570891 |
bf04ecc363f0f38d69eb0f6e972bc9ab718aa546 | 460 | py | Python | ANN/e09/lagrange.py | joao-frohlich/BCC | 9ed74eb6d921d1280f48680677a2140c5383368d | [
"Apache-2.0"
] | 10 | 2020-12-08T20:18:15.000Z | 2021-06-07T20:00:07.000Z | ANN/e09/lagrange.py | joao-frohlich/BCC | 9ed74eb6d921d1280f48680677a2140c5383368d | [
"Apache-2.0"
] | 2 | 2021-06-28T03:42:13.000Z | 2021-06-28T16:53:13.000Z | ANN/e09/lagrange.py | joao-frohlich/BCC | 9ed74eb6d921d1280f48680677a2140c5383368d | [
"Apache-2.0"
] | 2 | 2021-01-14T19:59:20.000Z | 2021-06-15T11:53:21.000Z | Xi = [i / 10 for i in range(-50, 25, 5)]
Yi = [
0.11,
-1.04,
-5,
4.97,
0.74,
-2.15,
3.3,
-0.92,
-4.79,
1.99,
1.71,
3.68,
2.81,
-3.71,
-1.1,
]
grau = len(Yi)
Ai = [1 for i in range(grau)]
for i in range(grau):
t = 1
for j in range(grau):
if i ... | 14.375 | 46 | 0.393478 |
bf1f2ba561202c8770d46aa8edd6a6a825f0e3c6 | 1,454 | py | Python | exercises/pt/test_04_10.py | Jette16/spacy-course | 32df0c8f6192de6c9daba89740a28c0537e4d6a0 | [
"MIT"
] | 2,085 | 2019-04-17T13:10:40.000Z | 2022-03-30T21:51:46.000Z | exercises/pt/test_04_10.py | Jette16/spacy-course | 32df0c8f6192de6c9daba89740a28c0537e4d6a0 | [
"MIT"
] | 79 | 2019-04-18T14:42:55.000Z | 2022-03-07T08:15:43.000Z | exercises/pt/test_04_10.py | Jette16/spacy-course | 32df0c8f6192de6c9daba89740a28c0537e4d6a0 | [
"MIT"
] | 361 | 2019-04-17T13:34:32.000Z | 2022-03-28T04:42:45.000Z | def test():
assert len(TRAINING_DATA) == 4, "Os dados de treinamento devem estar errados - deveriam ser 4 exemplos."
assert all(
len(entry) == 2 and isinstance(entry[1], dict) for entry in TRAINING_DATA
), "Formato dos dados de treinamento incorreto. O esperado é uma lista de tuplas onde o segundo e... | 48.466667 | 126 | 0.654746 |
bd94530a9c9b2c9ec54b675cfd04ea6cc88ac987 | 362 | py | Python | books/PythonCleanCode/ch8_unittest/test_mutate_testing_1.py | zeroam/TIL | 43e3573be44c7f7aa4600ff8a34e99a65cbdc5d1 | [
"MIT"
] | null | null | null | books/PythonCleanCode/ch8_unittest/test_mutate_testing_1.py | zeroam/TIL | 43e3573be44c7f7aa4600ff8a34e99a65cbdc5d1 | [
"MIT"
] | null | null | null | books/PythonCleanCode/ch8_unittest/test_mutate_testing_1.py | zeroam/TIL | 43e3573be44c7f7aa4600ff8a34e99a65cbdc5d1 | [
"MIT"
] | null | null | null | import unittest
from mrstatus import MergeRequestStatus as Status
from mutate_testing_1 import evaluate_merge_request
class TestMergeRequestEvaluation(unittest.TestCase):
def test_approved(self):
result = evaluate_merge_request(3, 0)
self.assertEqual(result, Status.APPROVED)
if __na... | 24.133333 | 53 | 0.740331 |
da717e5247c1df278caac823a5630920195f0c9f | 1,104 | py | Python | pacExtract.py | Gelbana/bbtag-stuff | 25384ef633e58b4d69684478863ec9ca9802f2f6 | [
"MIT"
] | null | null | null | pacExtract.py | Gelbana/bbtag-stuff | 25384ef633e58b4d69684478863ec9ca9802f2f6 | [
"MIT"
] | null | null | null | pacExtract.py | Gelbana/bbtag-stuff | 25384ef633e58b4d69684478863ec9ca9802f2f6 | [
"MIT"
] | null | null | null | import os,struct
"""Dantarion's bb extractor code adapted to work with bbtag to an extent
Honestly its probably the samem bug thanks to him"""
count = 0
directory = ""
total = len(os.listdir(directory))
for filename in os.listdir(directory):
count += 1
print "Extracting: %s (%d/%d)" %(filename, count, ... | 26.285714 | 128 | 0.664855 |
e51fba5dd572bc90b936b65062328c3fdf0a3b3a | 12,034 | py | Python | scripts/signal_marker_processing/notebook/pds_widgets.py | CsabaWirnhardt/cbm | 1822addd72881057af34ac6a7c2a1f02ea511225 | [
"BSD-3-Clause"
] | 17 | 2021-01-18T07:27:01.000Z | 2022-03-10T12:26:21.000Z | scripts/signal_marker_processing/notebook/pds_widgets.py | CsabaWirnhardt/cbm | 1822addd72881057af34ac6a7c2a1f02ea511225 | [
"BSD-3-Clause"
] | 4 | 2021-04-29T11:20:44.000Z | 2021-12-06T10:19:17.000Z | scripts/signal_marker_processing/notebook/pds_widgets.py | CsabaWirnhardt/cbm | 1822addd72881057af34ac6a7c2a1f02ea511225 | [
"BSD-3-Clause"
] | 47 | 2021-01-21T08:25:22.000Z | 2022-03-21T14:28:42.000Z | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# This file is part of CbM (https://github.com/ec-jrc/cbm).
# Author : Daniele Borio
# Credits : GTCAP Team
# Copyright : 2021 European Commission, Joint Research Centre
# License : 3-Clause BSD
import geopandas as gpd
from ipyfilechooser import FileChooser
from ... | 34.780347 | 89 | 0.526674 |
e5a1612dde9792ed8cd2d427cc89e5ea9e4dc2d1 | 3,249 | py | Python | official/nlp/tinybert/preprocess.py | leelige/mindspore | 5199e05ba3888963473f2b07da3f7bca5b9ef6dc | [
"Apache-2.0"
] | 77 | 2021-10-15T08:32:37.000Z | 2022-03-30T13:09:11.000Z | official/nlp/tinybert/preprocess.py | leelige/mindspore | 5199e05ba3888963473f2b07da3f7bca5b9ef6dc | [
"Apache-2.0"
] | 3 | 2021-10-30T14:44:57.000Z | 2022-02-14T06:57:57.000Z | official/nlp/tinybert/preprocess.py | leelige/mindspore | 5199e05ba3888963473f2b07da3f7bca5b9ef6dc | [
"Apache-2.0"
] | 24 | 2021-10-15T08:32:45.000Z | 2022-03-24T18:45:20.000Z | # 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 agreed to... | 41.653846 | 113 | 0.673746 |
e5db70cd7996697ee6c1ad5d16d29b75fc6556aa | 25 | py | Python | main/test.py | McUtty/FlowerPlan | b0998835356e8e10fe53cad447bc559df2ac7175 | [
"MIT"
] | null | null | null | main/test.py | McUtty/FlowerPlan | b0998835356e8e10fe53cad447bc559df2ac7175 | [
"MIT"
] | null | null | null | main/test.py | McUtty/FlowerPlan | b0998835356e8e10fe53cad447bc559df2ac7175 | [
"MIT"
] | null | null | null | # ' zweite Version'
new
| 8.333333 | 19 | 0.64 |
00d44698f2f2830669df896e2708bb76c340a38e | 201 | py | Python | stuff/solve_equation_qr.py | patcher1/numerik | ad24c8522d61970a3a881e034a7940d43ba486be | [
"BSD-3-Clause"
] | null | null | null | stuff/solve_equation_qr.py | patcher1/numerik | ad24c8522d61970a3a881e034a7940d43ba486be | [
"BSD-3-Clause"
] | null | null | null | stuff/solve_equation_qr.py | patcher1/numerik | ad24c8522d61970a3a881e034a7940d43ba486be | [
"BSD-3-Clause"
] | 1 | 2019-10-01T14:36:03.000Z | 2019-10-01T14:36:03.000Z | import numpy as np
import scipy.linalg
def solve_with_qr(A, b):
Q, R = np.linalg.qr(A)
btilde = np.dot(Q.T, b)
x= scipy.linalg.solve(R, btilde) #numpy.linalg or scipy.linalg?
return x
| 22.333333 | 67 | 0.656716 |
97c29ab667d858b438feeabaabcf4a0bbea9fb64 | 3,516 | py | Python | frappe-bench/apps/erpnext/erpnext/education/doctype/course_scheduling_tool/course_scheduling_tool.py | Semicheche/foa_frappe_docker | a186b65d5e807dd4caf049e8aeb3620a799c1225 | [
"MIT"
] | 1 | 2021-04-29T14:55:29.000Z | 2021-04-29T14:55:29.000Z | frappe-bench/apps/erpnext/erpnext/education/doctype/course_scheduling_tool/course_scheduling_tool.py | Semicheche/foa_frappe_docker | a186b65d5e807dd4caf049e8aeb3620a799c1225 | [
"MIT"
] | null | null | null | frappe-bench/apps/erpnext/erpnext/education/doctype/course_scheduling_tool/course_scheduling_tool.py | Semicheche/foa_frappe_docker | a186b65d5e807dd4caf049e8aeb3620a799c1225 | [
"MIT"
] | 1 | 2021-04-29T14:39:01.000Z | 2021-04-29T14:39:01.000Z | # -*- coding: utf-8 -*-
# Copyright (c) 2015, Frappe Technologies Pvt. Ltd. and contributors
# For license information, please see license.txt
from __future__ import unicode_literals
import frappe
import calendar
from frappe import _
from frappe.model.document import Document
from frappe.utils import add_days, getdate... | 30.573913 | 78 | 0.73322 |
e72b7110fcec9c2f1cbfe15fc7cf748258169fc1 | 20,748 | py | Python | Vargi_Bots/ros_packages/pkg_task5/scripts/node_t5_ur5_2_package_sort.py | ROBODITYA/Eyantra-2021-Vargi-Bots | f1c6a82c46e6e84486a4832b3fbcd02625849447 | [
"MIT"
] | 1 | 2021-07-13T07:05:29.000Z | 2021-07-13T07:05:29.000Z | Vargi_Bots/ros_packages/pkg_task5/scripts/node_t5_ur5_2_package_sort.py | TejasPhutane/Eyantra-2021-Vargi-Bots | ab84a1304101850be8c0f69cfe6de70d53c33189 | [
"MIT"
] | 1 | 2021-06-05T07:58:03.000Z | 2021-06-05T07:58:03.000Z | Vargi_Bots/ros_packages/pkg_task5/scripts/node_t5_ur5_2_package_sort.py | ROBODITYA/Eyantra-2021-Vargi-Bots | f1c6a82c46e6e84486a4832b3fbcd02625849447 | [
"MIT"
] | null | null | null | #!/usr/bin/env python
''' This node is used for controlling the ur5_2 robot, sort packages into its respctive coloured bins. '''
import sys
import copy
import math
from threading import Thread
from datetime import datetime, date, timedelta
import rospy
import moveit_commander
import moveit_msgs.msg
import geometry_ms... | 43.135135 | 155 | 0.646231 |
e781b78c5e3e2fb7e57c82d6173258279e9c05f7 | 3,558 | py | Python | scr_fr/my_classifier.py | Times125/Emotion-Analyse | b5d9f23fdf6c75f57f5cf20d58834a095b0c7e1e | [
"Apache-2.0"
] | 11 | 2018-01-16T06:39:00.000Z | 2021-11-28T11:46:41.000Z | scr_fr/my_classifier.py | Times125/Emotion-Analyse | b5d9f23fdf6c75f57f5cf20d58834a095b0c7e1e | [
"Apache-2.0"
] | null | null | null | scr_fr/my_classifier.py | Times125/Emotion-Analyse | b5d9f23fdf6c75f57f5cf20d58834a095b0c7e1e | [
"Apache-2.0"
] | 2 | 2019-08-16T14:53:37.000Z | 2019-08-17T02:01:22.000Z | #! /usr/bin/env python
# -*- coding: utf-8 -*-
"""
@Author:lch02
@Time: 2017/12/26 18:23
@Description:
"""
import config
import os
import itertools
import nltk
import pickle
import collections
from nltk.classify import SklearnClassifier
from nltk.metrics import *
from sklearn.svm import LinearSVC
__author__ = 'lch0... | 32.054054 | 87 | 0.686622 |
e7a189b26694a49f89e4ba932a226e1973f2cd61 | 1,103 | py | Python | Course_1/Week_04/ZhiyuanRandomizedSelection.py | KnightZhang625/Stanford_Algorithm | 7dacbbfa50e7b0e8380cf500df24af60cb9f42df | [
"Apache-2.0"
] | null | null | null | Course_1/Week_04/ZhiyuanRandomizedSelection.py | KnightZhang625/Stanford_Algorithm | 7dacbbfa50e7b0e8380cf500df24af60cb9f42df | [
"Apache-2.0"
] | 1 | 2020-07-16T08:03:22.000Z | 2020-07-16T08:09:34.000Z | Course_1/Week_04/ZhiyuanRandomizedSelection.py | KnightZhang625/Stanford_Algorithm | 7dacbbfa50e7b0e8380cf500df24af60cb9f42df | [
"Apache-2.0"
] | null | null | null | import random
def MySwap(MyInput,index1,index2):
temp = MyInput[index1]
MyInput[index1] = MyInput[index2]
MyInput[index2] = temp
def partition(MyInput,left,right):
i = left+1 # first element in the right
j = left+1 # last element in the right +1
while j <= right:
if MyInput[j] < ... | 27.575 | 83 | 0.600181 |
e7cbe3c39a4463f9ace01d8dd611b8447e48a472 | 26,100 | py | Python | Paddle_Industry_Practice_Sample_Library/Football_Action/PaddleVideo/paddlevideo/loader/pipelines/augmentations_ava.py | linuxonly801/awesome-DeepLearning | b063757fa130c4d56aea5cce2e592610f1e169f9 | [
"Apache-2.0"
] | 5 | 2022-01-30T07:35:58.000Z | 2022-02-08T05:45:20.000Z | Paddle_Industry_Practice_Sample_Library/Football_Action/PaddleVideo/paddlevideo/loader/pipelines/augmentations_ava.py | linuxonly801/awesome-DeepLearning | b063757fa130c4d56aea5cce2e592610f1e169f9 | [
"Apache-2.0"
] | 1 | 2022-01-14T02:33:28.000Z | 2022-01-14T02:33:28.000Z | Paddle_Industry_Practice_Sample_Library/Football_Action/PaddleVideo/paddlevideo/loader/pipelines/augmentations_ava.py | linuxonly801/awesome-DeepLearning | b063757fa130c4d56aea5cce2e592610f1e169f9 | [
"Apache-2.0"
] | 1 | 2022-01-24T16:27:01.000Z | 2022-01-24T16:27:01.000Z | # Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserve.
#
# 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 applic... | 35.704514 | 98 | 0.59705 |
99b0bcc9f1e4b19fadfd6fa0d77a8f916d627785 | 5,318 | py | Python | app/t1health_app/static/fusioncharts-suite-xt/integrations/django/samples/fusioncharts/samples/rendering_map_using_json_example.py | siyaochen/Tier1Health | 536591a7534bbb3fb27fe889bfed9de152ec1864 | [
"MIT"
] | 30 | 2018-04-01T09:08:40.000Z | 2022-01-23T07:30:07.000Z | app/t1health_app/static/fusioncharts-suite-xt/integrations/django/samples/fusioncharts/samples/rendering_map_using_json_example.py | siyaochen/Tier1Health | 536591a7534bbb3fb27fe889bfed9de152ec1864 | [
"MIT"
] | 14 | 2018-07-17T08:33:35.000Z | 2021-09-29T17:26:15.000Z | asset/integrations/django/samples/fusioncharts/samples/rendering_map_using_json_example.py | Piusshungu/catherine-junior-school | 5356f4ff5a5c8383849d32e22a60d638c35b1a48 | [
"MIT"
] | 17 | 2016-05-19T13:16:34.000Z | 2021-04-30T14:38:42.000Z | #!/usr/bin/python
# -*- coding: UTF-8 -*-
from django.shortcuts import render
from django.http import HttpResponse
# Include the `fusioncharts.py` file that contains functions to embed the charts.
from ..fusioncharts import FusionCharts
from collections import OrderedDict
# Loading Data from a Ordered Dictionary
# E... | 20.375479 | 97 | 0.306882 |
4193d928f439cf8e5e3c37fc52fbe8be3de163cc | 16,067 | py | Python | controller/RobotRotine.py | paulowiz/AiesecBot | ac77cc5426ed6382772603afa8015208020c0fba | [
"MIT"
] | 6 | 2019-10-18T17:47:30.000Z | 2021-03-18T06:04:06.000Z | controller/RobotRotine.py | paulowiz/AiesecBot | ac77cc5426ed6382772603afa8015208020c0fba | [
"MIT"
] | 1 | 2020-09-24T08:17:29.000Z | 2020-09-28T08:16:39.000Z | controller/RobotRotine.py | paulowiz/AiesecBot | ac77cc5426ed6382772603afa8015208020c0fba | [
"MIT"
] | 3 | 2019-10-20T18:40:20.000Z | 2021-04-15T01:27:59.000Z | import psycopg2.extras
import json
import pandas as pd
from pandas.io.json import json_normalize
import pandas.io.json as pd_json
from database.conexao import conexao
from api import graphqlconsume, querygraphql
from pandas.io.json import json_normalize
import pandas.io.json as pd_json
import datetime
import time
impor... | 50.209375 | 150 | 0.417813 |
6ba65df4d499ef7535b432f6657771daf15a347a | 1,414 | py | Python | algorithms/sorting/find_median.py | PlamenHristov/HackerRank | 2c875995f0d51d7026c5cf92348d9fb94fa509d6 | [
"MIT"
] | null | null | null | algorithms/sorting/find_median.py | PlamenHristov/HackerRank | 2c875995f0d51d7026c5cf92348d9fb94fa509d6 | [
"MIT"
] | null | null | null | algorithms/sorting/find_median.py | PlamenHristov/HackerRank | 2c875995f0d51d7026c5cf92348d9fb94fa509d6 | [
"MIT"
] | null | null | null | import sys
def quickSelect(A, k):
if len(A) == 1: return A[0]
p, L, R = A[0], [], []
for i in A:
if i < p: L.append(i)
if i > p: R.append(i)
if len(L) > k:
return quickSelect(L, k)
elif len(L) == k:
return p
else:
return quickSelect(R, k - len(L) - 1)
... | 20.492754 | 100 | 0.458274 |
6bdc32a6c8ac9b21feb339e004a0bc13641924b8 | 2,070 | py | Python | ppyt/commands/filter_stocks.py | yusukemurayama/ppytrading | 9804d0de870d77bf8a1c847736a636b1342d4600 | [
"MIT"
] | 4 | 2016-08-16T07:47:15.000Z | 2017-12-11T10:08:47.000Z | ppyt/commands/filter_stocks.py | yusukemurayama/ppytrading | 9804d0de870d77bf8a1c847736a636b1342d4600 | [
"MIT"
] | null | null | null | ppyt/commands/filter_stocks.py | yusukemurayama/ppytrading | 9804d0de870d77bf8a1c847736a636b1342d4600 | [
"MIT"
] | 2 | 2018-06-15T04:43:15.000Z | 2020-05-02T07:47:15.000Z | # coding: utf-8
import logging
import os
from ppyt.commands import CommandBase
from ppyt.models.orm import start_session, Stock
logger = logging.getLogger(__name__)
plogger = logging.getLogger('print')
class Command(CommandBase):
"""バックテストなどの対象になる銘柄を絞り込むコマンドです。"""
def _add_options(self, parser):
"""... | 32.34375 | 76 | 0.61256 |
d4520f585ef780b0bb1749cb79110141741baf75 | 508 | pyde | Python | sketches/mira3/mira3.pyde | kantel/processingpy | 74aae222e46f68d1c8f06307aaede3cdae65c8ec | [
"MIT"
] | 4 | 2018-06-03T02:11:46.000Z | 2021-08-18T19:55:15.000Z | sketches/mira3/mira3.pyde | kantel/processingpy | 74aae222e46f68d1c8f06307aaede3cdae65c8ec | [
"MIT"
] | null | null | null | sketches/mira3/mira3.pyde | kantel/processingpy | 74aae222e46f68d1c8f06307aaede3cdae65c8ec | [
"MIT"
] | 3 | 2019-12-23T19:12:51.000Z | 2021-04-30T14:00:31.000Z | a = .4
b = 1.0
def setup():
size(600, 600)
background(235, 215, 182)
colorMode(HSB, 255, 100, 100)
stroke(0)
strokeWeight(1)
this.surface.setTitle("Mira-Abbildung")
noLoop()
def draw():
x = 4.
y = .0
for i in range(120000):
x1 = b*y + f(x)
y = -x + f(x1)
... | 18.142857 | 52 | 0.438976 |
d487e5fb3ddf78cfce2e1f6d3aa3700105144346 | 29,260 | py | Python | zarvest_azim-vau.py | Zusyaku/Termux-And-Lali-Linux-V2 | b1a1b0841d22d4bf2cc7932b72716d55f070871e | [
"Apache-2.0"
] | 2 | 2021-11-17T03:35:03.000Z | 2021-12-08T06:00:31.000Z | zarvest_azim-vau.py | Zusyaku/Termux-And-Lali-Linux-V2 | b1a1b0841d22d4bf2cc7932b72716d55f070871e | [
"Apache-2.0"
] | null | null | null | zarvest_azim-vau.py | Zusyaku/Termux-And-Lali-Linux-V2 | b1a1b0841d22d4bf2cc7932b72716d55f070871e | [
"Apache-2.0"
] | 2 | 2021-11-05T18:07:48.000Z | 2022-02-24T21:25:07.000Z | # uncompyle6 version 3.7.4
# Python bytecode 2.7
# Decompiled from: Python 2.7.18 (default, Jul 8 2020, 22:53:57)
# [GCC 4.2.1 Compatible Android (5220042 based on r346389c) Clang 8.0.7 (https://
# Embedded file name: vinz
import requests, bs4, sys, os, subprocess, requests, sys, random
reload(sys)
sys.setdefaultenco... | 38.961385 | 565 | 0.465789 |
7aaba634c5a4e6210de3acfbda3c4b9092125ee0 | 38 | py | Python | 0_hello_world/solution.py | sourabhedake/hackerrank-30-days-of-code | c2d4ff6e8d9b4b1a2bb72a3b0a675b9ae09a8a5d | [
"MIT"
] | null | null | null | 0_hello_world/solution.py | sourabhedake/hackerrank-30-days-of-code | c2d4ff6e8d9b4b1a2bb72a3b0a675b9ae09a8a5d | [
"MIT"
] | null | null | null | 0_hello_world/solution.py | sourabhedake/hackerrank-30-days-of-code | c2d4ff6e8d9b4b1a2bb72a3b0a675b9ae09a8a5d | [
"MIT"
] | null | null | null | print('Hello, World.')
print (input()) | 19 | 22 | 0.657895 |
8fd198938954c34b225872073f0240effef11453 | 2,922 | py | Python | 3_DeepLearning-CNNs/04_CNN_Optimization/4-CrossValidation/CNN.py | felixdittrich92/DeepLearning-tensorflow-keras | 2880d8ed28ba87f28851affa92b6fa99d2e47be9 | [
"Apache-2.0"
] | null | null | null | 3_DeepLearning-CNNs/04_CNN_Optimization/4-CrossValidation/CNN.py | felixdittrich92/DeepLearning-tensorflow-keras | 2880d8ed28ba87f28851affa92b6fa99d2e47be9 | [
"Apache-2.0"
] | null | null | null | 3_DeepLearning-CNNs/04_CNN_Optimization/4-CrossValidation/CNN.py | felixdittrich92/DeepLearning-tensorflow-keras | 2880d8ed28ba87f28851affa92b6fa99d2e47be9 | [
"Apache-2.0"
] | null | null | null | '''
Cross-Validation: Kreuzvalidierung teilt die Trainingsdaten in Validierungs und Trainingsdaten
auf und verschiebt dabei k mal die Validierungsdaten
Bsp.: k = 5
k=1 ersten 20 % Validierung
k=2 zweiten 20 % Validierung
k=3 dritten 20 % Validierung
k=4 vierten 20 % Validierung
k=5 fünften 20 % Validierung
trainiert... | 28.930693 | 101 | 0.70397 |
8f5ce411530067b07f3c0b280c92e1938e802a7f | 1,697 | py | Python | ___Python/Marco/PythonProj/p01/m_01.py | uvenil/PythonKurs201806 | 85afa9c9515f5dd8bec0c546f077d8cc39568fe8 | [
"Apache-2.0"
] | null | null | null | ___Python/Marco/PythonProj/p01/m_01.py | uvenil/PythonKurs201806 | 85afa9c9515f5dd8bec0c546f077d8cc39568fe8 | [
"Apache-2.0"
] | null | null | null | ___Python/Marco/PythonProj/p01/m_01.py | uvenil/PythonKurs201806 | 85afa9c9515f5dd8bec0c546f077d8cc39568fe8 | [
"Apache-2.0"
] | null | null | null | from datetime import date
torsten = ["Torsten", "Aachen", date(1967, 1, 1), ["C"]]
michael = ["Michael", "Moormerland", date(1981, 10, 1), ["Javascript"]]
karpoo = ["Karpoo", "Düsseldorf", date(1969, 1, 1), ["ABAP"]]
carsten = ["Carsten", "Aachen", date(1971, 1, 1), ["Basic"]]
thomas = ["Thomas", "Bielefeld", da... | 32.634615 | 113 | 0.665881 |
7434ac4e96914777e615f34deee73dda7b4d031e | 155 | py | Python | official_examples/Reinforcement_Learning_GameSolution_Examples/ma_cartpole/env_config.py | RuichunWang/ModelArts-Lab | cfa9a853e3a76a21eac2818f055b36978ac2bb69 | [
"Apache-2.0"
] | 1,045 | 2019-05-09T02:50:43.000Z | 2022-03-31T06:22:11.000Z | official_examples/Reinforcement_Learning_GameSolution_Examples/ma_cartpole/env_config.py | RuichunWang/ModelArts-Lab | cfa9a853e3a76a21eac2818f055b36978ac2bb69 | [
"Apache-2.0"
] | 1,468 | 2019-05-16T00:48:18.000Z | 2022-03-08T04:12:44.000Z | official_examples/Reinforcement_Learning_GameSolution_Examples/ma_cartpole/env_config.py | RuichunWang/ModelArts-Lab | cfa9a853e3a76a21eac2818f055b36978ac2bb69 | [
"Apache-2.0"
] | 1,077 | 2019-05-09T02:50:53.000Z | 2022-03-27T11:05:32.000Z | import numpy as np
from gym.spaces import Discrete, Box
action_space = Discrete(2)
observation_space = Box(-np.inf, np.inf, shape=(4,), dtype=np.float32)
| 25.833333 | 70 | 0.748387 |
7af273469ea201d32c9e2b5c9162124b4144c71b | 818 | py | Python | Python/zzz_training_challenge/Python_Challenge/solutions/tests/ch08_binary_trees/ex07_rotation_test.py | Kreijeck/learning | eaffee08e61f2a34e01eb8f9f04519aac633f48c | [
"MIT"
] | null | null | null | Python/zzz_training_challenge/Python_Challenge/solutions/tests/ch08_binary_trees/ex07_rotation_test.py | Kreijeck/learning | eaffee08e61f2a34e01eb8f9f04519aac633f48c | [
"MIT"
] | null | null | null | Python/zzz_training_challenge/Python_Challenge/solutions/tests/ch08_binary_trees/ex07_rotation_test.py | Kreijeck/learning | eaffee08e61f2a34e01eb8f9f04519aac633f48c | [
"MIT"
] | null | null | null | # Beispielprogramm für das Buch "Python Challenge"
#
# Copyright 2020 by Michael Inden
from ch08_binary_trees.solutions.ex05_levelorder import levelorder
from ch08_binary_trees.solutions.ex07_rotation import rotate_left, rotate_right
from ch08_binary_trees.intro import ExampleTrees
def test_rotate_left():
root =... | 27.266667 | 79 | 0.717604 |
247a299743742f83e5ba7bb59c28a136843df63f | 14,984 | py | Python | bets/util.py | Thames1990/BadBatBets | 8dffb69561668b8991bf4103919e4b254d4ca56a | [
"MIT"
] | null | null | null | bets/util.py | Thames1990/BadBatBets | 8dffb69561668b8991bf4103919e4b254d4ca56a | [
"MIT"
] | null | null | null | bets/util.py | Thames1990/BadBatBets | 8dffb69561668b8991bf4103919e4b254d4ca56a | [
"MIT"
] | null | null | null | import logging
from django.core.exceptions import ValidationError
logger = logging.getLogger(__name__)
def key_gen():
"""
Generates a random key for bets, placed bets and accounts.
:return: Random key between 0 and 2147483647 (max size for django's PositiveIntegerField)
"""
from random import Sy... | 29.848606 | 117 | 0.663775 |
d96902bd487601832b3c3809e0bcb9e76bebc24a | 942 | py | Python | app/urls.py | StevenMedina/MovieAPI | 805e79d396e197383bce6095febf0252231a1018 | [
"MIT"
] | null | null | null | app/urls.py | StevenMedina/MovieAPI | 805e79d396e197383bce6095febf0252231a1018 | [
"MIT"
] | null | null | null | app/urls.py | StevenMedina/MovieAPI | 805e79d396e197383bce6095febf0252231a1018 | [
"MIT"
] | null | null | null | from django.conf import settings
from django.conf.urls.static import static
from django.contrib import admin
from django.urls import include
from django.urls import path
from django.views.generic.base import TemplateView
from movie.api import router
from . import views
admin_str = 'Administración Omnibnk'
admin.sit... | 20.042553 | 67 | 0.649682 |
30b38fb488de21f603b469585b8b48c78cf4d52d | 4,541 | py | Python | modelclass.py | bian0505/Pad_Me | c05b899b85a99d982948741e9da10e0a72d054d8 | [
"MIT"
] | null | null | null | modelclass.py | bian0505/Pad_Me | c05b899b85a99d982948741e9da10e0a72d054d8 | [
"MIT"
] | null | null | null | modelclass.py | bian0505/Pad_Me | c05b899b85a99d982948741e9da10e0a72d054d8 | [
"MIT"
] | null | null | null | #https://arxiv.org/pdf/1506.02640.pdf
#import torch
import torch.nn as nn
import torch.nn.functional as F
class Region_Mask(nn.Module):
def __init__(self):
super().__init__()
# input,250*250*3
self.conv1=nn.Conv2d(3,64,7)
self.bt1 = nn.BatchNorm2d(64)
#-->24... | 28.030864 | 60 | 0.45915 |
30bdacbb46badbe60f0872154abcebc6c0a0e0fb | 17,332 | py | Python | src/test/tests/plots/pseudocolor.py | visit-dav/vis | c08bc6e538ecd7d30ddc6399ec3022b9e062127e | [
"BSD-3-Clause"
] | 226 | 2018-12-29T01:13:49.000Z | 2022-03-30T19:16:31.000Z | src/test/tests/plots/pseudocolor.py | visit-dav/vis | c08bc6e538ecd7d30ddc6399ec3022b9e062127e | [
"BSD-3-Clause"
] | 5,100 | 2019-01-14T18:19:25.000Z | 2022-03-31T23:08:36.000Z | src/test/tests/plots/pseudocolor.py | visit-dav/vis | c08bc6e538ecd7d30ddc6399ec3022b9e062127e | [
"BSD-3-Clause"
] | 84 | 2019-01-24T17:41:50.000Z | 2022-03-10T10:01:46.000Z | # ----------------------------------------------------------------------------
# CLASSES: nightly
#
# Test Case: pseudocolor.py
#
# Tests: meshes - 2D rectilinear, 3D curvilinear.
# plots - pseudocolor
#
# Defect ID: '1016, '987
#
# Programmer: Kevin Griffin
# Date: March 19, 20... | 31.172662 | 96 | 0.663513 |
30fcea78f0405efae179bbb9c4cb7fa77c4b3c73 | 2,607 | py | Python | Nearest Neighbors/NearestNeighbors.py | moeinmd1380/MachineLearning | 3f5490fb379a217be5bca993b6e3983d151db11c | [
"Unlicense"
] | null | null | null | Nearest Neighbors/NearestNeighbors.py | moeinmd1380/MachineLearning | 3f5490fb379a217be5bca993b6e3983d151db11c | [
"Unlicense"
] | null | null | null | Nearest Neighbors/NearestNeighbors.py | moeinmd1380/MachineLearning | 3f5490fb379a217be5bca993b6e3983d151db11c | [
"Unlicense"
] | null | null | null | from sklearn.datasets import load_breast_cancer
import pandas as pd
import numpy as np
import random
class NearestNeighbors:
def __init__(self, data, k=1, measure='e'):
self.x = []
self.y = []
self.data = data
validMeasure = ['e', 'm', 'manhattan', 'euclid']
if measure in v... | 29.965517 | 93 | 0.59954 |
eb7ac06b81df123f83b3fc0d3e1cc731fdc60a36 | 1,686 | py | Python | ___Python/Carsten/p03_lambda/m06_anwendung.py | uvenil/PythonKurs201806 | 85afa9c9515f5dd8bec0c546f077d8cc39568fe8 | [
"Apache-2.0"
] | null | null | null | ___Python/Carsten/p03_lambda/m06_anwendung.py | uvenil/PythonKurs201806 | 85afa9c9515f5dd8bec0c546f077d8cc39568fe8 | [
"Apache-2.0"
] | null | null | null | ___Python/Carsten/p03_lambda/m06_anwendung.py | uvenil/PythonKurs201806 | 85afa9c9515f5dd8bec0c546f077d8cc39568fe8 | [
"Apache-2.0"
] | null | null | null | from datetime import date
from p01_kennenlernen import meinebibliothek
from p01_kennenlernen.meinebibliothek import celsius_to_fahrenheit
torsten = ["Torsten", "Aachen", date(1967, 1, 1), ["C"]]
michael = ["Michael", "Moormerland", date(1981, 1, 10), ["Javascript"]]
karpoo = ["Karpoo", "Düsseldorf", date(1969,... | 39.209302 | 137 | 0.67675 |
69042f62df8a2763b9c77b5f0065ef4b5b0695c9 | 6,504 | py | Python | zencad/examples/4.Assemble/robot.py | Spiritdude/zencad | 4e63b1a6306dd235f4daa2791b10249f7546c95b | [
"MIT"
] | 5 | 2018-04-11T14:11:40.000Z | 2018-09-12T19:03:36.000Z | zencad/examples/4.Assemble/robot.py | Spiritdude/zencad | 4e63b1a6306dd235f4daa2791b10249f7546c95b | [
"MIT"
] | null | null | null | zencad/examples/4.Assemble/robot.py | Spiritdude/zencad | 4e63b1a6306dd235f4daa2791b10249f7546c95b | [
"MIT"
] | null | null | null | #!/usr/bin/env python3
from zencad import *
import zencad.assemble
import time
import numpy
class HeadAssemble(zencad.assemble.unit):
def __init__(self):
super().__init__()
self.add(cylinder(r=8, h=5).up(3) + cylinder(r=4, h=3))
eye0 = self.add(cylinder(r=3, h=3).rotateX(
d... | 32.039409 | 87 | 0.505843 |
15f8d0728e29960d7f11dfc55512723fc2053173 | 847 | py | Python | Zhihu/Python/cv2_example.py | leoatchina/MachineLearning | 071f2c0fc6f5af3d9550cfbeafe8d537c35a76d3 | [
"MIT"
] | 1,107 | 2016-09-21T02:18:36.000Z | 2022-03-29T02:52:12.000Z | Zhihu/Python/cv2_example.py | leoatchina/MachineLearning | 071f2c0fc6f5af3d9550cfbeafe8d537c35a76d3 | [
"MIT"
] | 18 | 2016-12-22T10:24:47.000Z | 2022-03-11T23:18:43.000Z | Zhihu/Python/cv2_example.py | leoatchina/MachineLearning | 071f2c0fc6f5af3d9550cfbeafe8d537c35a76d3 | [
"MIT"
] | 776 | 2016-12-21T12:08:08.000Z | 2022-03-21T06:12:08.000Z | from NN.Basic.Networks import *
from c_CvDTree.Tree import *
from Util.Util import DataUtil
def cv2_example():
pass
def visualize_nn():
x, y = DataUtil.gen_xor()
nn = NNDist()
nn.add("ReLU", (x.shape[1], 6))
nn.add("ReLU", (6,))
nn.add("Softmax", (y.shape[1],))
nn.fit(x, y, epoch=1000, ... | 21.717949 | 56 | 0.586777 |
ba7f6f8acc5c733eece17ace367166751fcd3614 | 2,320 | py | Python | day03/tresureIsland.py | nurmatthias/100DaysOfCode | 22002e4b31d13e6b52e6b9222d2e91c2070c5744 | [
"Apache-2.0"
] | null | null | null | day03/tresureIsland.py | nurmatthias/100DaysOfCode | 22002e4b31d13e6b52e6b9222d2e91c2070c5744 | [
"Apache-2.0"
] | null | null | null | day03/tresureIsland.py | nurmatthias/100DaysOfCode | 22002e4b31d13e6b52e6b9222d2e91c2070c5744 | [
"Apache-2.0"
] | null | null | null | print('''
*******************************************************************************
| | | |
_________|________________.=""_;=.______________|_____________________|_______
| | ,-"_,="" `"=.| |
|_______________... | 49.361702 | 79 | 0.483621 |
305abd85991fd71cd06562807fc2688d86b9031b | 4,111 | py | Python | official/cv/unet/ascend310_quant_infer/acc.py | leelige/mindspore | 5199e05ba3888963473f2b07da3f7bca5b9ef6dc | [
"Apache-2.0"
] | 77 | 2021-10-15T08:32:37.000Z | 2022-03-30T13:09:11.000Z | official/cv/unet/ascend310_quant_infer/acc.py | leelige/mindspore | 5199e05ba3888963473f2b07da3f7bca5b9ef6dc | [
"Apache-2.0"
] | 3 | 2021-10-30T14:44:57.000Z | 2022-02-14T06:57:57.000Z | official/cv/unet/ascend310_quant_infer/acc.py | leelige/mindspore | 5199e05ba3888963473f2b07da3f7bca5b9ef6dc | [
"Apache-2.0"
] | 24 | 2021-10-15T08:32:45.000Z | 2022-03-24T18:45:20.000Z | # 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 agreed to... | 38.420561 | 106 | 0.621017 |
06352f1ce3e902d60016054675df6f820e081b75 | 134 | py | Python | Python/Sets/symmetric_difference.py | rho2/HackerRank | 4d9cdfcabeb20212db308d8e4f2ac1b8ebf7d266 | [
"MIT"
] | null | null | null | Python/Sets/symmetric_difference.py | rho2/HackerRank | 4d9cdfcabeb20212db308d8e4f2ac1b8ebf7d266 | [
"MIT"
] | null | null | null | Python/Sets/symmetric_difference.py | rho2/HackerRank | 4d9cdfcabeb20212db308d8e4f2ac1b8ebf7d266 | [
"MIT"
] | null | null | null | _ = input()
m = set(input().split())
_ = input()
n = set(input().split())
print('\n'.join(sorted(m.symmetric_difference(n),key=int))) | 22.333333 | 59 | 0.626866 |
06768b3cb29cbcf986f79e95010805379017e771 | 541 | py | Python | pacman-termux/test/pacman/tests/query005.py | Maxython/pacman-for-termux | 3b208eb9274cbfc7a27fca673ea8a58f09ebad47 | [
"MIT"
] | 23 | 2021-05-21T19:11:06.000Z | 2022-03-31T18:14:20.000Z | source/pacman-6.0.1/test/pacman/tests/query005.py | Scottx86-64/dotfiles-1 | 51004b1e2b032664cce6b553d2052757c286087d | [
"Unlicense"
] | 11 | 2021-05-21T12:08:44.000Z | 2021-12-21T08:30:08.000Z | source/pacman-6.0.1/test/pacman/tests/query005.py | Scottx86-64/dotfiles-1 | 51004b1e2b032664cce6b553d2052757c286087d | [
"Unlicense"
] | 1 | 2021-09-26T08:44:40.000Z | 2021-09-26T08:44:40.000Z | self.description = "Query info on a package (new date)"
p = pmpkg("foobar")
p.files = ["bin/foobar"]
p.desc = "test description"
p.groups = ["foo"]
p.url = "http://www.archlinux.org"
p.license = "GPL2"
p.arch = "i686"
# test new style date
p.builddate = "1196640127"
p.packager = "Arch Linux"
self.addpkg2db("local", p... | 24.590909 | 55 | 0.68207 |
88f296242331f04383991447a02ce3ddb9286322 | 6,094 | py | Python | DDPG/DDPG.py | Wen2chao/RL-Algorithm- | 6cb31f2e02a90fceef498c7ee46a4d06eb976005 | [
"MIT"
] | 19 | 2020-06-09T07:48:10.000Z | 2022-03-27T04:52:36.000Z | DDPG/DDPG.py | Wen2chao/RL-Algorithm- | 6cb31f2e02a90fceef498c7ee46a4d06eb976005 | [
"MIT"
] | 1 | 2020-09-17T07:39:35.000Z | 2021-08-02T02:31:52.000Z | DDPG/DDPG.py | Wen2chao/RL-Algorithm- | 6cb31f2e02a90fceef498c7ee46a4d06eb976005 | [
"MIT"
] | 12 | 2020-03-28T08:19:26.000Z | 2022-03-21T11:08:08.000Z | import gym
import torch
import random
import collections
import numpy as np
import torch.nn as nn
import torch.optim as optim
import torch.nn.functional as F
import matplotlib.pyplot as plt
class ReplayBuffer():
def __init__(self, buffer_maxlen):
self.buffer = collections.deque(maxlen=buffer_... | 32.763441 | 109 | 0.607975 |
cc6d2f174eeb52bb3482a84a69f2fb42607df327 | 1,871 | py | Python | gui/mplwidget.py | lhalb/gfmanager | 449f071b3239faa672b7f06122dfc9bc23e68d79 | [
"MIT"
] | 1 | 2022-01-18T12:53:17.000Z | 2022-01-18T12:53:17.000Z | gui/mplwidget.py | lhalb/gfmanager | 449f071b3239faa672b7f06122dfc9bc23e68d79 | [
"MIT"
] | null | null | null | gui/mplwidget.py | lhalb/gfmanager | 449f071b3239faa672b7f06122dfc9bc23e68d79 | [
"MIT"
] | null | null | null | # # Imports
# from PyQt5 import QtWidgets
# from matplotlib.figure import Figure
# from matplotlib.backends.backend_qt5agg import FigureCanvasQTAgg as Canvas
# import matplotlib
# # Ensure using PyQt5 backend
# matplotlib.use('QT5Agg')
# # Matplotlib canvas class to create figure
# class MplCanvas(Canvas):
# def ... | 31.711864 | 102 | 0.684661 |
aec6bc21fc9a432ff5676c8f5297f1677b1bdc06 | 4,219 | py | Python | Packs/IntegrationsAndIncidentsHealthCheck/Scripts/IntegrationsCheck_Widget_IntegrationsErrorsInfo/test_data/constants.py | diCagri/content | c532c50b213e6dddb8ae6a378d6d09198e08fc9f | [
"MIT"
] | 799 | 2016-08-02T06:43:14.000Z | 2022-03-31T11:10:11.000Z | Packs/IntegrationsAndIncidentsHealthCheck/Scripts/IntegrationsCheck_Widget_IntegrationsErrorsInfo/test_data/constants.py | diCagri/content | c532c50b213e6dddb8ae6a378d6d09198e08fc9f | [
"MIT"
] | 9,317 | 2016-08-07T19:00:51.000Z | 2022-03-31T21:56:04.000Z | Packs/IntegrationsAndIncidentsHealthCheck/Scripts/IntegrationsCheck_Widget_IntegrationsErrorsInfo/test_data/constants.py | diCagri/content | c532c50b213e6dddb8ae6a378d6d09198e08fc9f | [
"MIT"
] | 1,297 | 2016-08-04T13:59:00.000Z | 2022-03-31T23:43:06.000Z | FAILED_TABLE = '''[{"brand": "Active Directory Query v2", "category": "Data Enrichment & Threat Intelligence",
"information": "Failed to access LDAP server. Please validate the server host and port are configured correctly (85)",
"instance": "Active Directory Query v2_instance_1"},
... | 82.72549 | 236 | 0.462669 |
9da19e1a92f35bd49cb8f7091e3974109ca78bd4 | 74 | py | Python | etl/mappings/med_regex.py | cloud-cds/cds-stack | d68a1654d4f604369a071f784cdb5c42fc855d6e | [
"Apache-2.0"
] | 6 | 2018-06-27T00:09:55.000Z | 2019-03-07T14:06:53.000Z | etl/mappings/med_regex.py | cloud-cds/cds-stack | d68a1654d4f604369a071f784cdb5c42fc855d6e | [
"Apache-2.0"
] | 3 | 2021-03-31T18:37:46.000Z | 2021-06-01T21:49:41.000Z | etl/mappings/med_regex.py | cloud-cds/cds-stack | d68a1654d4f604369a071f784cdb5c42fc855d6e | [
"Apache-2.0"
] | 3 | 2020-01-24T16:40:49.000Z | 2021-09-30T02:28:55.000Z | med_regex = [
{
'fid': 'xxx',
'pos': 'regex',
}
]
| 10.571429 | 23 | 0.310811 |
d1a96deddfadcfd342b8711b987bbcf432eb2d27 | 1,531 | py | Python | gshiw/quotes_web/config/migrations/0001_initial.py | superlead/gsw | fc2bb539e3721cc554b4116b553befd653d2ec74 | [
"MIT"
] | null | null | null | gshiw/quotes_web/config/migrations/0001_initial.py | superlead/gsw | fc2bb539e3721cc554b4116b553befd653d2ec74 | [
"MIT"
] | null | null | null | gshiw/quotes_web/config/migrations/0001_initial.py | superlead/gsw | fc2bb539e3721cc554b4116b553befd653d2ec74 | [
"MIT"
] | null | null | null | # -*- coding: utf-8 -*-
# Generated by Django 1.11.7 on 2017-12-11 14:02
from __future__ import unicode_literals
from django.conf import settings
from django.db import migrations, models
import django.db.models.deletion
class Migration(migrations.Migration):
initial = True
dependencies = [
migratio... | 41.378378 | 154 | 0.63096 |
ae2e0c09f3d8f2bc6169ae725bfe2a443fe4f960 | 7,550 | py | Python | analysis/deanonymize.py | yashpatel5400/anonychain | 921804832839f3639477cfc441f138bc2f5ad685 | [
"MIT"
] | 1 | 2018-08-31T07:16:40.000Z | 2018-08-31T07:16:40.000Z | analysis/deanonymize.py | yashpatel5400/anonychain | 921804832839f3639477cfc441f138bc2f5ad685 | [
"MIT"
] | null | null | null | analysis/deanonymize.py | yashpatel5400/anonychain | 921804832839f3639477cfc441f138bc2f5ad685 | [
"MIT"
] | 1 | 2018-07-01T18:03:01.000Z | 2018-07-01T18:03:01.000Z | """
__author__ = Yash Patel
__name__ = deanonymize.py
__description__ = Runs spectral clustering for deanonymization on the BTC network,
also calculating accuracy and drawing outputs in the process
"""
import pickle
import time
import networkx as nx
import matplotlib.pyplot as plt
import numpy as np
fr... | 37.376238 | 97 | 0.615364 |
8873a9d67525638b7a4ee21fbe019fc8599eac23 | 1,384 | py | Python | euler-41.py | TFabijo/euler | 58dc07b9adb236890556ccd5d75ca9dbd2b50df9 | [
"MIT"
] | null | null | null | euler-41.py | TFabijo/euler | 58dc07b9adb236890556ccd5d75ca9dbd2b50df9 | [
"MIT"
] | null | null | null | euler-41.py | TFabijo/euler | 58dc07b9adb236890556ccd5d75ca9dbd2b50df9 | [
"MIT"
] | null | null | null | # pri tem problemu moremo z zvijačo malo zmjšati vsa možna števila, ki ji bomo pregledali za potenciačne rešitve
# recimo vsota stevk 9 pandigalega stevila je 45, ki je deljivo s 3 zato nemore biti prastevilo
# 8 pandigalno stevilo vsota stevk je 36 delivo s 3 nemore biti prastevilo
# 7 pangigalno stevilo vsota stev... | 30.086957 | 113 | 0.611994 |
ee720f9c8de150e5f5cbb1168ba46729b11ceeec | 128 | py | Python | Pythonjunior2020/Woche1/Aufgabe_1_3_3.py | Zeyecx/HPI-Potsdam | ed45ca471cee204dde74dd2c3efae3877ee71036 | [
"MIT"
] | null | null | null | Pythonjunior2020/Woche1/Aufgabe_1_3_3.py | Zeyecx/HPI-Potsdam | ed45ca471cee204dde74dd2c3efae3877ee71036 | [
"MIT"
] | null | null | null | Pythonjunior2020/Woche1/Aufgabe_1_3_3.py | Zeyecx/HPI-Potsdam | ed45ca471cee204dde74dd2c3efae3877ee71036 | [
"MIT"
] | null | null | null | # 1.3.3, Woche 1, Block 3, Aufgabe 3
# Dekleration
kleidung = ["Hose","T-Shirt"]
# Ausgabe
print(kleidung[1]+"\n"+kleidung[0]) | 18.285714 | 36 | 0.648438 |
4e6d420a5190ab6b4c02e99434d9a0eb80562e7d | 2,355 | py | Python | _Dist/NeuralNetworks/_Tests/Madelon/TestAdvancedNN.py | leoatchina/MachineLearning | 071f2c0fc6f5af3d9550cfbeafe8d537c35a76d3 | [
"MIT"
] | 1,107 | 2016-09-21T02:18:36.000Z | 2022-03-29T02:52:12.000Z | _Dist/NeuralNetworks/_Tests/Madelon/TestAdvancedNN.py | leoatchina/MachineLearning | 071f2c0fc6f5af3d9550cfbeafe8d537c35a76d3 | [
"MIT"
] | 18 | 2016-12-22T10:24:47.000Z | 2022-03-11T23:18:43.000Z | _Dist/NeuralNetworks/_Tests/Madelon/TestAdvancedNN.py | leoatchina/MachineLearning | 071f2c0fc6f5af3d9550cfbeafe8d537c35a76d3 | [
"MIT"
] | 776 | 2016-12-21T12:08:08.000Z | 2022-03-21T06:12:08.000Z | import os
import sys
root_path = os.path.abspath("../../../../")
if root_path not in sys.path:
sys.path.append(root_path)
from _Dist.NeuralNetworks.c_BasicNN.NN import Basic
from _Dist.NeuralNetworks.e_AdvancedNN.NN import Advanced
from _Dist.NeuralNetworks._Tests.TestUtil import draw_acc
from _Dist.NeuralNetworks... | 33.642857 | 89 | 0.736306 |
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