blob_id stringlengths 40 40 | language stringclasses 1
value | repo_name stringlengths 5 133 | path stringlengths 2 333 | src_encoding stringclasses 30
values | length_bytes int64 18 5.47M | score float64 2.52 5.81 | int_score int64 3 5 | detected_licenses listlengths 0 67 | license_type stringclasses 2
values | text stringlengths 12 5.47M | download_success bool 1
class |
|---|---|---|---|---|---|---|---|---|---|---|---|
4483b5d884084baa1adcb7081aef1b6e21cb9a61 | Python | abhidurg/CSE_480_Database_Systems | /proj08/wait_die_shedule.py | UTF-8 | 7,563 | 2.90625 | 3 | [] | no_license | class Action:
"""
This is the Action class.
"""
def __init__(self, object_, transaction, type_):
self.object_ = object_
self.transaction = transaction
assert type_ in ("WRITE", "COMMIT", "ROLLBACK", "LOCK", "UNLOCK", "WAIT")
self.type_ = type_
def __str__(self):
return f"Action('... | true |
81dbd093cab21233ebebfa94e49f02f141dea0dd | Python | truboprovod4uk/My-Project | /sinX.py | UTF-8 | 2,659 | 3.4375 | 3 | [] | no_license | # Це не мій проект, програма написана по прикладу з ютуба
# Ця програма генерує координатну сітку та синусоїду, приймаючи дані від користувача
from tkinter import *
import math
root = Tk()
root.title("Графік фунції")
root.geometry('1240x640')
canvas = Canvas(root, width=900, height=640, bg='#002')
canvas.pack(side='ri... | true |
526ac0ca6af79b634f4ee51403f84c8d7a121745 | Python | Shurui-Zhang/Biometrics | /biometrics.py | UTF-8 | 7,487 | 2.546875 | 3 | [] | no_license | #!pip install removebg
import cv2 as cv
import torchvision.models.segmentation as segmentation
import numpy
import torch
from torchvision import transforms
from PIL import Image
from torchvision.datasets import ImageFolder
from torch.utils.data import DataLoader
from sklearn.neighbors import KNeighborsClas... | true |
560da9b167d3608df28bb4fcff90bfe8a3a44334 | Python | kwendim/sentence_extractor | /new_textifier.py | UTF-8 | 4,026 | 3.046875 | 3 | [] | no_license | """Extracts the title, content and date from the blogs and saves it in a file that is organized into sentences. The name of the file will be the date followed by the article title.
Argument passed should be the absolute path to the folder containing the website data. When giving path, start from the "/" folder"""
__aut... | true |
c3fe8b65722d5325f3abf1d2369553632e933c52 | Python | ikikohei/atcoder | /EDPC/D_knapsack.py | UTF-8 | 584 | 3.015625 | 3 | [] | no_license | def knapsack(N,W,items):
dp = [[0 for i in range(W+1)] for j in range(N+1)]
for n in range(N):
for w in range(W):
if items[n][0] <= w+1:
dp[n+1][w+1] = max(dp[n][w+1],dp[n][w+1-items[n][0]]+items[n][1])
else:
dp[n+1][w+1] = dp[n][w+1]
return dp... | true |
9a23231487f9c4b3c7ad52de71dda7005520116a | Python | MKDevil/Python | /学习/0标准库/lib_string.py | UTF-8 | 2,110 | 3.90625 | 4 | [] | no_license | #!/usr/bin/env python
# -*- coding:utf-8 -*-
import string
################################### 字符串常量 ###################################
# ascii_lowercase 生成小写字母 a~z
print('小写字母：', string.ascii_lowercase)
# ascii_uppercase 生成大写字母 A~Z
print('大写字母：', string.ascii_uppercase)
# ascii_letters 生成所有的字母，a~z + A~Z... | true |
1ea5227e42395c4db8154e6cf2b33a243d58f7f6 | Python | gumuxiansheng/BFSUCitation | /export.py | UTF-8 | 2,230 | 2.609375 | 3 | [] | no_license | import xlwt
wb = xlwt.Workbook(encoding='utf-8', style_compression=0)
ws = wb.add_sheet('export', cell_overwrite_ok=True)
ws2 = wb.add_sheet('citation', cell_overwrite_ok=True)
colNames = ['AU', 'TI', 'SO', 'VL', 'IS', 'BP', 'EP', 'DI', 'PD', 'PY', 'AB', 'ZR', 'TC', 'ZB', 'Z8', 'ZS',
'Z9', 'SN', 'EI', 'UT... | true |
3a5e978e04a542f4a3051b2c30545b960fddd00f | Python | suseongKim87/python-study | /응용1/mod2.py | UTF-8 | 264 | 3.5625 | 4 | [] | no_license | PI = 3.141592
class Math:
def solv(self, r):
return PI*(r**2) #반지름을 계산하는 클래스, r**2는 r의 제곱.
def sum(a,b):
return a+b
if __name__=="__main__":
print(PI)
a = Math()
print(a.solv(2))
print(sum(PI,4.4)) | true |
75ef2bcedebb7524b11ceaecfbcaeb10bd81cffa | Python | AustinAkerley/crypto | /crypto/cryptanalysis/pollard.py | UTF-8 | 625 | 3.328125 | 3 | [] | no_license | # Title: Pollard's p-1 Factorization Algorithm
# Creator: Austin Akerley
# Date Created: 05/17/2020
# Last Editor: Austin Akerley
# Date Last Edited: 05/17/2020
# Associated Book Page Nuber: 139
# INPUT(s) -
# N - type: int, desc: integer to be factored into p and q, note: p*q = N
from crypto.src.fast_power import fa... | true |
1f18c885822ba15d6542e386f42f1e1a7627905f | Python | cchan19/region_classification | /work/feature_extracting/Basic_feature/Code_Basic_feature_1/feature.py | UTF-8 | 68,772 | 2.75 | 3 | [] | no_license | import time
import numpy as np
import sys
import datetime
import pandas as pd
import os
from Config import config
# 用字典查询代替类型转换，可以减少一部分计算时间
date2position = {}
datestr2dateint = {}
str2int = {}
date2int = {}
for i in range(24):
str2int[str(i).zfill(2)] = i
# 访问记录内的时间从2018年10月1日起，共182天
# 将日期按日历排列
for i in range(182... | true |
ec560887d6a722946ee492eb7991f55a190be42f | Python | AK-1121/code_extraction | /python/python_7777.py | UTF-8 | 92 | 3.015625 | 3 | [] | no_license | # How do I print a Celsius symbol with matplotlib?
ax.set_xlabel('Temperature ($^\circ$C)')
| true |
3fc5b97db4907104c33052bb141f5e13fc7692e8 | Python | knighton/deepzen | /deepzen/api/base/core/cast.py | UTF-8 | 875 | 2.71875 | 3 | [] | no_license | class BaseCastAPI(object):
def cast(self, x, dtype=None, device=None, copy=False):
raise NotImplementedError
def cast_to_cpu(self, x, dtype, copy=False):
return self.cast(x, dtype, self.cpu(), copy)
def cast_to_gpu(self, x, dtype, gpu=None, copy=False):
return self.cast(x, dtype, s... | true |
04d60a62b037b423cf0ff90a2a6ef2a450c138cd | Python | Guilhermesav/Assessment2 | /ok.py | UTF-8 | 1,520 | 3.078125 | 3 | [] | no_license | import threading, time,multiprocessing
lista_tamanhos = [1000, 2000, 3000, 4000, 5000]
if __name__ == '__main__':
for tam in lista_tamanhos:
lista = [1.3, 10.4, 40.0, 59.87, 33.01, 101.4]*tam
tamanho = len(lista)
def calcPorcent(lista, inicio, fim):
for i in range(... | true |
f6b18ed443cbcd69ebd6c87fc002987aa5a7e8d9 | Python | eboling/MBTS-Water-Tiers | /gen_tiers.py | UTF-8 | 1,589 | 2.53125 | 3 | [] | no_license | import sys
from numpy import loadtxt, arange, ones
from scipy import stats
from rate_tier import RateTier, TierSystem
from RawQData import RawQData
data_file_dir = sys.argv[1]
tier_file_name = sys.argv[2]
spreadsheet_file_name = sys.argv[3]
raw = RawQData(data_file_dir)
lines = loadtxt(tier_file_name)
#print lines
r... | true |
bd9d9fb1da81c85732962429ae943f51c52e7307 | Python | conceptslearningmachine-FEIN-85-1759293/affiliates | /affiliates/links/tests/test_models.py | UTF-8 | 929 | 2.53125 | 3 | [
"MIT",
"BSD-3-Clause"
] | permissive | from datetime import date
from nose.tools import eq_
from affiliates.base.tests import TestCase
from affiliates.links.models import Link
from affiliates.links.tests import DataPointFactory, LinkFactory
class LinkTests(TestCase):
def test_manager_total_link_clicks(self):
for clicks in (4, 6, 9, 10): # =... | true |
8941efe0b69af32e43f78600ecb5ae41ca0d6266 | Python | magdacisowska/AdventOfCode | /AOC/day5.py | UTF-8 | 1,411 | 3.78125 | 4 | [] | no_license | def is_gonna_react(a, b):
low_up = a.isupper() and b.islower()
up_low = a.islower() and b.isupper()
same_sign = a.lower() == b.lower()
return (low_up or up_low) and same_sign
def react(input):
new_polymer = []
old_polymer = list(reversed(input))
while old_polymer:
current_unit = ... | true |
180d6d68c232abb4ba3e49474ce7005a49191109 | Python | AnastasiaMazur/test_octopus_task | /encryption_decryption.py | UTF-8 | 1,119 | 2.875 | 3 | [] | no_license | import base64
import os
from Crypto import Random
from Crypto.PublicKey import RSA
from settings import PRIVATE_KEY_FILENAME
def generate_keys():
if os.path.exists(PRIVATE_KEY_FILENAME):
print("GET KEY FROM PATH")
with open(PRIVATE_KEY_FILENAME, 'r') as f:
PRIVATE_KEY = RSA.importKey(f... | true |
80437243415280ea32f1dcecd97be3e9a4968ba2 | Python | jumbokh/micropython_class | /ESP32/Lab/Dust/pms5003.py | UTF-8 | 3,562 | 3.09375 | 3 | [] | no_license | """
Program to read data from PLANTOWER PMS5003
Modified from program to read data from NovaFitness SDS011 by
Nils Jacob Berland
njberland@gmail.com / njberland@sensar.io
+47 40800410
Modified by
Szymon Jakubiak
Measured values of PM1, PM2.5 and PM10 are in ug/m^3
Number of pa... | true |
d74b7c1683e2eb5230b34e175b894e236a2833fb | Python | herowhj/weixin_crawler_2.0 | /utils/time.py | UTF-8 | 673 | 2.890625 | 3 | [] | no_license | def get_internet_time():
"""
:return: 获取百度服务器时间
"""
import requests,time,datetime
try:
r = requests.get(url="http://www.baidu.com")
date = r.headers['Date']
#将GMT时间转换成北京时间
net_time = time.mktime(datetime.datetime.strptime(date[5:25], "%d %b %Y %H:%M:%S").timetuple())+... | true |
7e85a37f9b7cc6ab92fea8c3fe17a132b68a161a | Python | ninastijepovic/MasterThesis | /hera_sim/visibilities/simulators.py | UTF-8 | 13,973 | 2.53125 | 3 | [
"MIT"
] | permissive | from __future__ import division
from builtins import object
import warnings
import healpy
import numpy as np
from cached_property import cached_property
from pyuvsim import analyticbeam as ab
from pyuvsim.simsetup import (
initialize_uvdata_from_params,
initialize_catalog_from_params,
uvdata_to_telescope_c... | true |
c111c58750c12fb8ab344a4176468cc873ed6468 | Python | laxminagln/IOSD-UIETKUK-HacktoberFest-Meetup-2019 | /Beginner/age.py | UTF-8 | 296 | 3.78125 | 4 | [
"Apache-2.0"
] | permissive | while True:
try:
a = int(input("enter your age :"))
if a > 18:
print("Adult")
elif 10 < a <= 18:
print("Teen")
elif a <= 10:
print("Child")
break
except ValueError:
print("enter valid age")
break
| true |
c40e07411d8abc5540de0bc15810940894d58900 | Python | samuelcharles007/TheSelfTaughtProgrammer | /Odd_or_evenusingloop.py | UTF-8 | 104 | 3.375 | 3 | [] | no_license | l=input("Type a Int")
r=input("Type another int")
i=[]
for i in range(int(l),int(r)):
print(i)
| true |
1e75fedd8d82ee9b9159f872729f4eb4466f79a2 | Python | Comradgrimo/Py_sql_qt | /lesson_1.py | UTF-8 | 5,402 | 3.78125 | 4 | [] | no_license | # 1. Написать функцию host_ping(), в которой с помощью утилиты ping будет проверяться доступность сетевых узлов.
# Аргументом функции является список, в котором каждый сетевой узел должен быть представлен именем хоста или ip-адресом.
# В функции необходимо перебирать ip-адреса и проверять их доступность с выводом соотв... | true |
7942d5e162a8d475762bf5af9657985322d8f283 | Python | hackengineer/enet_tensorflow | /utils.py | UTF-8 | 5,852 | 2.890625 | 3 | [] | no_license | import tensorflow as tf
import numpy as np
def process_path_enc(file_path):
'''
Function to process the path containing the images and the
labels for the input pipeline. In this case we work for the
encoder output
Arguments
----------
'file_path' = path containing the images and
... | true |
58b9dbafe87eb8e484a8e896b4cc259fda4be589 | Python | EgehanGundogdu/drf-test-driven-development-exercies | /app/core/tests/test_models.py | UTF-8 | 1,167 | 2.890625 | 3 | [
"MIT"
] | permissive | from django.test import TestCase
from django.contrib.auth import get_user_model
class UserModelTests(TestCase):
def setUp(self):
self.user = get_user_model().objects.create_user(
email="test1@gmail.com", password="super secret"
)
def test_create_user_with_email(self):
"""T... | true |
e85b8529a6197568e727b40623000a9f82c7fed0 | Python | xiguashuiguo/langren | /M_langren.py | UTF-8 | 2,072 | 2.71875 | 3 | [] | no_license | class M_langren(object):
"""狼人游戏的流程控制"""
playerNum = 0
langrenNum = 0
day = 1
mumber = []
langrenList = []
nvwuNum = 0
YuyanNum = 0
Zancun = []
Nvwu_D = True
Nvwu_J = True
JingzhangNum = 0
def __init__(self):
return
def setPlayer(self,P):
... | true |
73866ad8e111316f51d570f0ec89eac841e2400b | Python | blackholemedia/writings | /algorithm/solutions/offer/hassubtree.py | UTF-8 | 2,585 | 2.984375 | 3 | [] | no_license | #-*- coding=utf-8 -*-
from functools import reduce
import sys
if sys.platform == 'linux':
sys.path.append('/home/alta/ds')
from mytree.binarytreefromlist import BinaryTreeFromList
from mytree.tree import TreeNode
else:
sys.path.append('c:\\users\\alta')
from datastructure.mytree.binarytreef... | true |
780da105a891cc88976004347547179172257d78 | Python | EasonPeng-TW/big5_10 | /big5_10.py | UTF-8 | 863 | 3.078125 | 3 | [] | no_license | import pandas as pd
import requests
big5_url = 'https://www.taifex.com.tw/cht/3/largeTraderFutQry'
big5_table = pd.read_html(requests.get(big5_url, headers={'User-agent': 'Mozilla/5.0(Windows NT 6.1; Win64; x64)AppleWebKit/537.36(KHTML, like Gecko)Chrome/63.0.3239.132 Safari/537.36'}).text)
big5_table[3]
big10_call = b... | true |
e7ce5ead997e40a4f4499cadf7037d87b7fe4925 | Python | zhafen/cc | /cc/concept_n_body.py | UTF-8 | 2,100 | 2.59375 | 3 | [] | no_license | import rebound
import augment
########################################################################
class Simulation( object ):
@augment.store_parameters
def __init__(
self,
concept_map,
r_c = 5.,
rep_power = 3.,
att_power = 1.,
inital_dims = ( 10., 10., 10... | true |
4b0585286ff2df8e916efb8fb46717e499f73ea1 | Python | aleph-im/pyaleph | /tests/toolkit/test_batch.py | UTF-8 | 747 | 2.890625 | 3 | [
"MIT"
] | permissive | import pytest
from aleph.toolkit.batch import async_batch
async def async_range(*args):
for i in range(*args):
yield i
@pytest.mark.asyncio
async def test_async_batch():
# batch with a remainder
batches = [b async for b in async_batch(async_range(0, 10), 3)]
assert batches == [[0, 1, 2], [3,... | true |
45e3b61514c33f3cdee0a33845caa990fb574e44 | Python | sy2es94098/MLGame-Summer | /games/easy_game/ml/ml_play_template.py | UTF-8 | 496 | 2.953125 | 3 | [] | no_license | import random
class MLPlay:
def __init__(self):
print("Initial ml script")
def update(self, scene_info: dict):
"""
Generate the command according to the received scene information
"""
# print("AI received data from game :", scene_info)
actions = ["UP", "DOWN", ... | true |
55c08f336f70a4531a1d2188170309835655bd70 | Python | mgilgamesh/DRL-Continuous-Control | /model.py | UTF-8 | 2,231 | 2.6875 | 3 | [] | no_license | import numpy as np
import random
from collections import namedtuple, deque
import torch
import torch.nn.functional as F
import torch.optim as optim
import torch.nn as nn
class Actor(nn.Module):
""" Policy Model """
def __init__(self, state_size, action_size, seed):
super(Actor, self).__init... | true |
dfddfc42c13760ab4ec35e05bf36242fdb22c204 | Python | mcxu/code-sandbox | /PythonSandbox/src/misc/num_subsets_min_max_below_k.py | UTF-8 | 564 | 3.3125 | 3 | [] | no_license | '''
https://leetcode.com/discuss/interview-question/268604/Google-interview-Number-of-subsets
Requirement: O(n^2) time or better.
Example 1:
nums = [2, 4, 5, 7]
k = 8
Output: 5
Explanation: [2], [4], [2, 4], [2, 4, 5], [2, 5]
Example 2:
nums = [1, 4, 3, 2]
k = 8
Output: 15
Explanation: 16 (2^4) - 1 (empty set) = 15
... | true |
647b3208a3698a3c774325e5c1cf33cd3e8d547f | Python | viticlick/adventofcode | /2020/day_02/day2_02.py | UTF-8 | 335 | 3.40625 | 3 | [] | no_license | import re
from operator import xor
f = open('input.txt','r')
counter = 0
for line in f.readlines():
(a,b,c,d) = re.findall('(\d+)-(\d+) (\w): (\w+)', line)[0]
first_occurence = d[int(a) - 1] == c
last_occurence = d[int(b) - 1] == c
if xor(first_occurence, last_occurence):
counter = counter + 1
... | true |
49a03219699c3ce1cef26cb80feea6b3dd96021d | Python | rahul9852-dot/Python-From-Scratch | /Basic Python/Practise_problem/facorial.py | UTF-8 | 383 | 4.25 | 4 | [] | no_license |
# Factorial of given number
# single line of code
# Recursive approach
def fact(n):
return 1 if (n==1 or n==0) else n*fact(n-1)
print(fact(5))
# Iterative approach
def factorial(n):
if n<0:
return 0
elif n==1 or n==0:
return 1
else:
fact=1
while n>1:
fact*=... | true |
d24188f846922dd017fc873a5e1b476b04548a06 | Python | pinartopcam/project | /Assignment.py | UTF-8 | 14,996 | 2.78125 | 3 | [] | no_license | import Preference
import Instructor as i
import Course as c
import TeachingAssistant as t
from random import shuffle
import random
class Assignment:
def __init__(self, preference_list, ta_list, course_list, instructor_list):
self.preference_list = preference_list
self.ta_list = ta_list
self... | true |
e593ecbb7a23b3b4fa3654f25d5b87a47aea6374 | Python | danielgil1/resbaz_2019_nlp | /hangman_resbaz/flaskask/game.py | UTF-8 | 2,191 | 4.125 | 4 | [] | no_license | def hangman(secret_word, guesser, max_mistakes=8, verbose=True, **guesser_args):
"""
This game engine is part of material given by The University of Melbourne - Web Search and Text Analysis
secret_word: a string of lower-case alphabetic characters, i.e., the answer to the game
guesser: a fun... | true |
4a78e566d624a5cb9945273714ed0f81b2c014aa | Python | ngthuyn/BTVN | /10_7.py | UTF-8 | 362 | 3.28125 | 3 | [] | no_license | """Bài 10: Cho list sau: ["www.hust.edu.vn", "www.wikipedia.org", "www.asp.net", "www.amazon.com"].
Viết chương trình để in ra hậu tố (vn, org, net, com) trong các tên miền website trong list trên."""
a=["www.hust.edu.vn", "www.wikipedia.org", "www.asp.net", "www.amazon.com"]
for i in range(len(a)):
b=a[i].spli... | true |
8cff65427411babec7c2a49d84ee678f94a4f1d6 | Python | JianYiheng/leetcode-dialog | /226.invert-binary-tree-m1.py | UTF-8 | 698 | 3.1875 | 3 | [] | no_license | from typing import List
class TreeNode:
def __init__(self, x):
self.val = x
self.left = None
self.right = None
class Solution:
def invertTree(self, root: TreeNode) -> TreeNode:
if not root: return None
TreeList = [root]
while 1:
ptr_node = TreeList... | true |
4c422743f4496441d2dc98efa0416f91aabd91c5 | Python | megansmcguire/saucerbot | /saucerbot/groupme/handlers/saucer.py | UTF-8 | 4,518 | 2.8125 | 3 | [] | no_license | # -*- coding: utf-8 -*-
import logging
import random
from typing import List, Union
from lowerpines.endpoints.bot import Bot
from lowerpines.endpoints.message import Message
from lowerpines.message import ComplexMessage, RefAttach
from saucerbot.groupme.handlers import registry
from saucerbot.groupme.models import S... | true |
9a76630f2e801e479bb26b06d262280d0adf1ef3 | Python | jdurakie/raycaster | /meshbuilder.py | UTF-8 | 708 | 2.703125 | 3 | [] | no_license | from Triangle import Triangle as T
from colormanip import RED, GREEN, BLUE, YELLOW, CYAN, MAGENTA
def makeBox():
A = (22, 26, 20)
B = (42, 26, 20)
C = (42, 6, 20)
D = (22, 6, 20)
E = (22, 26, 40)
F = (42, 26, 40)
G = (42, 6, 40)
H = (22, 6, 40)
tris = [
T(A, B, C, color=R... | true |
046dd0bf748e8e4c084a1dda6d5f31995c058e10 | Python | slichlyter12/Aristotle | /tests/selenium/TestStudentUseCases.py | UTF-8 | 10,860 | 2.546875 | 3 | [] | no_license | import json
import unittest
import HTMLTestRunner
import time
from selenium import webdriver
class Test_Student_Use_Cases(unittest.TestCase):
@classmethod
def setUpClass(self):
self.driver = webdriver.Chrome()
self.driver.implicitly_wait(5)
def test_login_error(self):
... | true |
63b218c32269fc23b20329308f27fd390ac6048f | Python | 863752027z/lab_server | /micro_detect/get_file.py | UTF-8 | 1,173 | 2.625 | 3 | [] | no_license | import os
import torch.utils.data as Data
from torchvision import transforms, datasets
def get_path(base_path):
path_list = []
for root, dirs, files in os.walk(base_path):
for i in range(len(dirs)):
temp_path = base_path + '/' + dirs[i]
path_list.append(temp_path)
break... | true |
bd245d25908174a44c070e4c0f1e61f966ea00ac | Python | tastypotinc/Taiwan_Stock_info | /python_code_for_ref/old_version_get_stock/html_parser.py | UTF-8 | 6,074 | 2.96875 | 3 | [] | no_license | #!/usr/bin/env python
# -*- coding: utf-8 -*-
#這裡將日盛網頁資料，分成index, data兩個檔案切出需要的文字後，再合併
#最後再重新整理資料，因為網頁的資料表格，有橫、直之分，所以資料有些分散
#要注意網頁的編碼、<p>標籤會多一次的取值
#import htmldom
from htmldom import htmldom
def html_parser(path_time,path_stock,path_file):
#print(path_time)
#print(path_file)
#print(path_file)
print("w... | true |
7c3cc3f23d778f253d196186767ddf79987c8f39 | Python | eegnom1807/raspy_led_pwm | /test_files/led.py | UTF-8 | 249 | 2.953125 | 3 | [] | no_license | import RPi.GPIO as GPIO
import time
GPIO.setmode(GPIO.BOARD)
GPIO.setup(7, GPIO.OUT)
led = GPIO.PWM(7, 100)
led.start(0)
while True:
led.start(0)
for i in range(0, 100, 25):
print(i)
led.ChangeDutyCycle(i)
time.sleep(0.5)
| true |
7d85888493b1250740d3078308ae266802048f4f | Python | esineokov/ml | /lesson/8/exercise/1.py | UTF-8 | 454 | 3.03125 | 3 | [] | no_license | class Data:
data = None
def __init__(self, data):
Data.data = data
@classmethod
def parse(cls):
return list(map(int, cls.data.split("-")))
@staticmethod
def validation():
day, month, year = tuple(Data.parse())
return 1 <= day <= 31 and 1 <= month <= 12 and yea... | true |
8688242a391fe2f3a775ea64efc3980735e91c1a | Python | tranquansp/KerasTools | /Dev/rl/agents/pg.py | UTF-8 | 2,591 | 3 | 3 | [
"MIT"
] | permissive | #!/usr/bin/env python3
# Policy algorithm by https://github.com/DeepReinforcementLearning/DeepReinforcementLearningInAction
# Distributed there under the MIT license
import catch
import numpy as np
import keras
grid_size = 10
l1 = grid_size*grid_size*3
l2 = 150
l3 = 3
learning_rate = 0.001
def generate_model():
... | true |
e860a91a4766c1c0997010178744c262d5dd2b2a | Python | frank12a/Gemma- | /XXX.py | UTF-8 | 1,736 | 3.9375 | 4 | [] | no_license | class Foo(object):
pass
class Bar(Foo):
pass
class WW(Foo):
pass
# obj = Bar()
# obj1 = WW()
# isinstance用于判断，对象是否是指定类的实例 （错误的）
# isinstance用于判断，对象是否是指定类或其派生类的实例
# print(isinstance(obj, Foo))
# print(isinstance(obj, Bar))
# print(isinstance(obj1, Foo))
# print(type(obj) == Bar)
# print(type(obj) == ... | true |
05013dc748902d5b680fb6aece184c36d3627476 | Python | ice-bear-git/PyQt5-learn | /GUI/Basic-train/PyQtGraph/graph.py | UTF-8 | 3,555 | 2.59375 | 3 | [] | no_license | # import pyqtgraph.examples
# pyqtgraph.examples.run()
#!/bin/bash
# -*- coding: UTF-8 -*-
import pyqtgraph as pg
import sys
import numpy as np
import PyQt5
# 基本控件都在这里面
from PyQt5.QtWidgets import QApplication, QMainWindow, QDesktopWidget, QStyleFactory, QWidget
from PyQt5.QtGui import QPalette, QColor
from PyQt5.Qt... | true |
11195cf9bec61a758e7daf6be9d8b0ab2aa7d8b9 | Python | PhilippeOlivier/wsp | /tools/generate.py | UTF-8 | 3,387 | 2.96875 | 3 | [] | no_license | # -*- coding: utf-8 -*-
################################################################################
#
# This script generates a batch of 'num_instances' instances of size
# 'num_items'. Every instance shares the same item weights, but has a different
# cost matrix. This script takes as its only argument batch n... | true |
10ca4a6c709a74ed60bb1c1d17b19782ddd1d356 | Python | byAbaddon/Advanced-Course-PYTHON-May-2020 | /3.0 Multidimensional Lists - Lab/04. Symbol in Matrix.py | UTF-8 | 337 | 3.53125 | 4 | [] | no_license | import sys
size_matrix = int(input())
matrix = []
for _ in range(size_matrix):
matrix.append(input())
symbol = input()
for row in range(len(matrix)):
for col in range(len(matrix[row])):
if matrix[row][col] == symbol:
print((row,col))
sys.exit()
print(symbol, 'does not occur... | true |
71961edab22183c51747f3f7ff6806efc044b51a | Python | ahmedeltaweel/searchly | /main.py | UTF-8 | 707 | 2.640625 | 3 | [
"MIT"
] | permissive | import sys
from utils import process_docs, valid_pathes, perform_scored_search
def main():
"""
Main application entrypoint, bootstrap the indexer and db.
"""
if len(sys.argv) < 2:
sys.exit('Please, provide a valid system dir path')
if not valid_pathes(sys.argv[1:]):
sys.exit('{} ... | true |
26470eee09ecce31079978cab58864fd2b98a0f5 | Python | phuchduong/essencero_restoration | /scripts/legacy/test_codecs.py | UTF-8 | 1,437 | 2.828125 | 3 | [
"Apache-2.0"
] | permissive | # Encodings
# Codec | Aliases | Languages
# cp850 | 850, IBM850 | Western Europe
# cp1252 | windows-1252 | Western Europe
# latin_1 | iso-8859-1, iso8859-1, 8859,... | true |
c0e359bbf80796e23aa10057f2fb92d2caa6a567 | Python | Paccy10/flask-ecommerce-api | /api/models/user.py | UTF-8 | 807 | 2.796875 | 3 | [] | no_license | """ Module for User Model """
from .database import db
from .base import BaseModel
class User(BaseModel):
""" User Model class """
__tablename__ = 'users'
firstname = db.Column(db.String(100), nullable=False)
lastname = db.Column(db.String(100), nullable=False)
email = db.Column(db.String(100),... | true |
46b788e74b608fcc997319150e07782dfc907ff6 | Python | njk8/AI-labs | /lab1/myvacuumagent.py | UTF-8 | 11,814 | 2.59375 | 3 | [] | no_license | from lab1.liuvacuum import *
from random import randint
DEBUG_OPT_DENSEWORLDMAP = False
AGENT_STATE_UNKNOWN = 0
AGENT_STATE_WALL = 1
AGENT_STATE_CLEAR = 2
AGENT_STATE_DIRT = 3
AGENT_STATE_HOME = 4
AGENT_DIRECTION_NORTH = 0
AGENT_DIRECTION_EAST = 1
AGENT_DIRECTION_SOUTH = 2
AGENT_DIRECTION_WEST = 3
... | true |
c075f96228e6d93b781e93b3d164a94db8b1441d | Python | abechoi/My_Python | /ABSP/login.py | UTF-8 | 239 | 3.15625 | 3 | [] | no_license | myFile = open('secretFile.txt')
secret = myFile.read()
print("enter password:")
password = input()
if password == secret:
print("access granted!")
if password == "12345":
print("weak password!")
else:
print("access denied") | true |
9f395f44e360e1ab39842759e355b75279fd6a09 | Python | poudrenoire/dessin | /dessin.py | UTF-8 | 1,169 | 2.734375 | 3 | [
"CC0-1.0"
] | permissive | # Génère des dessins aléatoirement
import turtle
import random
import time
import tkinter
import uuid
screen = turtle.Screen()
screen.colormode(255)
turtle.speed(9)
# Générateur de dessins
for _ in range(25):
turtle.pencolor(random.randint(0,255), random.randint(0,255), random.randint(0,255))
turtle.left(random.r... | true |
3308d861d4caf309be6e36b95c03f8eb757ebc06 | Python | goushan33/PycharmProjects | /learn_notes/leetcode/circul_queue.py | UTF-8 | 687 | 3.984375 | 4 | [] | no_license | #基于数组实现循环队列
class CirculQueue(object):
def __init__(self,capacity):
self.items=[None]*capacity
self.n=capacity
self.head=0
self.tail=0
#入队
def enqueue(self,val):
#队列已满
if (self.tail+1)%self.n==self.head:
return False
self.items[self.tail]... | true |
2820b4c353ef886f77af7648aacb9aac740a73c9 | Python | tianhanl/wiki-scrapper | /get_polling.py | UTF-8 | 1,052 | 2.765625 | 3 | [] | no_license | import sys
# This filed is created to allow get polling data and save them using command line
# Usage: python3 get_polling.py "query"
path = './pollings/'
if __name__ == '__main__':
from sys import argv
import wiki
import re
if len(argv) < 2:
print('usage: python3 get_polling "query"')
els... | true |
3ed25158647eed962f409010c514bf7136f65e09 | Python | ricardojoserf/triangle-position | /tripos.py | UTF-8 | 4,096 | 2.671875 | 3 | [] | no_license | import re, time, os, math, argparse
from geopy.distance import vincenty, great_circle
from mpl_toolkits.basemap import Basemap
import matplotlib.pyplot as plt
import numpy as np
import sys
from plot import drawMap
def get_args():
parser = argparse.ArgumentParser()
parser.add_argument('-c1', '--coordenadas1', requir... | true |
abee29231b412daea132f3307fe118a632b1d979 | Python | ihuei801/leetcode | /MyLeetCode/python/Count of Smaller Numbers After Self.py | UTF-8 | 2,008 | 3.109375 | 3 | [] | no_license | ###
# Merge Sort
# Time Complexity: O(nlogn)
# Space Complexity: O(logn) + O(n)
###
class Solution(object):
def merge_sort(self, nums, start, end, small):
if end - start <= 1:
return
mid = (start + end) / 2
self.merge_sort(nums, start, mid, small)
self.merge_sort(nums, m... | true |
b87a86f5efb9921952db4aedd83024721605ed3e | Python | ynikitenko/lena | /lena/flow/group_by.py | UTF-8 | 2,415 | 3.5625 | 4 | [
"Apache-2.0"
] | permissive | """Group data using :class:`.GroupBy` class."""
import lena.core
import lena.flow
class GroupBy(object):
"""Group values.
Data is added during :meth:`update`.
Groups dictionary is available as :attr:`groups` attribute.
:attr:`groups` is a mapping of *keys* (defined by *group_by*)
to lists of item... | true |
c6eae374051020483d4800b01b6d0898a5d935c1 | Python | Aasthaengg/IBMdataset | /Python_codes/p03545/s786987870.py | UTF-8 | 345 | 2.6875 | 3 | [] | no_license | def main():
S = list(str(input()))
LenP = 3
ans = 0
for i in range(2**LenP):
P = ["-"]*LenP
for j in range(LenP):
if i >> j & 1:
P[j] = "+"
Res = [None] * (len(S)+len(P))
Res[1::2],Res[::2] = P,S
ResEval = "".join(Res)
if eval(ResEval) == 7:
ans = ResEval+"=7"
print(ans)
break
if __name... | true |
3f1f758fe269fa14b1be6ef4e429322743450bef | Python | ahmad0790/stock-trading-machine-learning-algos | /DTLearner.py | UTF-8 | 7,547 | 2.953125 | 3 | [] | no_license | """
Name: Ahmad Khan
GT ID: akhan361
"""
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import time
from scipy import stats
import datetime as dt
class DTLearner(object):
def __init__(self, leaf_size = 1, verbose = False):
pass # move along, these aren't the drones you're looking... | true |
b7747baf6a008469937415e9da53f2a9b2679a0f | Python | MichalKacprzak99/Vpython | /lab6/zad2.py | UTF-8 | 856 | 3.015625 | 3 | [] | no_license | import random
import numpy as np
import matplotlib.pyplot as plt
plt.style.use('classic')
x0=0
y0=0
X=[]
Y=[]
X.append(x0)
Y.append(y0)
sum=0
tmp=0
i=1
while(sum<10**6):
r = random.uniform(0, 100)
if r < 1.0:
x = 0
y = 0.16*y0
elif r < 86.0:
x = 0.85*x0 + 0.04*y0
y = ... | true |
4179ac05fd53902821f1a25fbafadb50a16e036b | Python | timber8/ComputerVision | /demo.py | UTF-8 | 7,580 | 3.109375 | 3 | [] | no_license | import cv2
#to show the image
import numpy as np
from math import cos, sin
import os
def find_biggest_contour(image):
# Copy
image = image.copy()
image, contours, hierarchy = cv2.findContours(image, cv2.RETR_LIST, cv2.CHAIN_APPROX_SIMPLE)
# Isolate largest contour
contour_sizes = [(cv2.conto... | true |
0e2cc31f8b44d787a8ca62f3ac5d90ec735a78ae | Python | lzxysf/python | /cli/python_003_variable.py | UTF-8 | 2,991 | 4.34375 | 4 | [] | no_license | # coding=utf-8
# python的数据类型：数字、字符串、复数，列表、元组、字典
import json
a = b = c = 1
a, b, c = 1, 3.4, 'alice'
s = "hello world!"
x = '你好'
print(s[1:7]) # 前包含后不包含
print(s[1:])
print(s[-1:-5]) # 倒着数时候是前不包含后包含
print(s[:-1])
print(s+x)
print(x*2)
# 列表可以包含数字、字符串、另一个列表
# 列表用[]表示，元素之间用,隔开
list = ['runoob', 786, 2.23, 'john', 70.2]... | true |
563421cf4c5c78a911efae765ba929b96b17f24a | Python | alexlwn123/kattis | /Python/Karte.py | UTF-8 | 415 | 2.71875 | 3 | [] | no_license | import sys
deck = set()
line = str(sys.stdin.readline())
for i in range(len(line) // 3):
if (line[i*3: i*3+3]) in deck:
print("GRESKA")
break
else:
deck.add(line[i*3:i*3+3])
else:
P = sum(1 for x in deck if x.startswith('P'))
K = sum(1 for x in deck if x.startswith('K'))
H = sum(1 for x in deck if x.st... | true |
36dfb3d566efde9a99d80a40a6972fc9ab7ef30b | Python | zhushh/PythonCode | /basicStudy/func_local_var.py | UTF-8 | 171 | 3.234375 | 3 | [] | no_license | #!/usr/bin/env python
# Filename: func_local_var.py
def func(x):
print 'x is', x
x = x + 1
print 'change local x to', x
x = 32
func(x)
print 'x is still', x
| true |
010e2385ac90107cf6e0ed7d0e7b666307ce3997 | Python | notbdu/tf-mnist | /mnist_basic_nn.py | UTF-8 | 5,743 | 3.625 | 4 | [
"MIT"
] | permissive | #!/usr/bin/env python
"""
An example of implementing multinomial logistic (softmax) regression with a single layer of
perceptrons using Tensorflow
Ouput: Confidence prediction (as an array) of which class an observation in the class belongs to
"""
import time
import tensorflow as tf
from tensorflow.examples.tutoria... | true |
4cca3d99292b01445cf8ccbeae0529932759081b | Python | vidmo91/imgcode | /imGcode/env_imGcode/Lib/site-packages/matplotlib/tests/test_artist.py | UTF-8 | 9,061 | 2.640625 | 3 | [
"Apache-2.0"
] | permissive | import io
from itertools import chain
import numpy as np
import pytest
import matplotlib.pyplot as plt
import matplotlib.patches as mpatches
import matplotlib.lines as mlines
import matplotlib.path as mpath
import matplotlib.transforms as mtransforms
import matplotlib.collections as mcollections
import matplotlib.ar... | true |
707c841c33d2550c92c6665949ab433af6e7889b | Python | mgarkusha/GB-Python | /Урок1/hw01_normal.py | UTF-8 | 1,383 | 4.40625 | 4 | [] | no_license | # Задача-1: Дано произвольное целое число, вывести самую большую цифру этого числа.
import math
num = int(input('Введите число: '))
razryad=int(math.log10(num))
i=0
while razryad >=0:
k = int(num / (10**razryad))
print ('цифра',k)
num -= 10**razryad*k
razryad -= 1
if i==0 :
bigNumber = k
elif k > bigNumber :
... | true |
283fc1b8f9f273bd39b00f4e510acb1c57949857 | Python | mengjian0502/eee511_team03_finalproject | /eyeclosure/eyeclosure_extract.py | UTF-8 | 1,501 | 2.515625 | 3 | [
"MIT"
] | permissive | """
"""
import numpy as np
import torch
from six.moves import cPickle as pickle
pickle_files = ['./open_eyes.pickle', './closed_eyes.pickle']
i = 0
for pickle_file in pickle_files:
with open(pickle_file, 'rb') as f:
save = pickle.load(f)
if i == 0:
train_dataset = save['train_dataset']... | true |
3ef840bace16b1d0ed336cf18c5904407cdde3d0 | Python | zingpython/kungFuShifu | /day_two/6.py | UTF-8 | 185 | 3.65625 | 4 | [] | no_license |
dictonary = {"A":6,"B":4,"C":1,"D":3,"E":4,"F":1}
search_value = 5
result = []
for key in dictonary.keys():
if dictonary[key] == search_value:
result.append(key)
print(result)
| true |
93495f78f5265a1804dc1087adb55d4b8a7b8ccb | Python | nucleomis/Archivos_Python | /ejercicios 1er año/promedio de altura.py | UTF-8 | 719 | 4.28125 | 4 | [] | no_license | #Cargar por teclado y almacenar en una lista las alturas de 5 personas
# (valores float)
#Obtener el promedio de las mismas.
#Contar cuántas personas son más altas que el promedio y cuántas más bajas.
altura=[]
menor=[]
mayor=[]
for x in range(5):
ingreso=float(input("ingrese una altura: "))
altura.append(ing... | true |
59c6ad7766c5907acae83197faa927afe21e9203 | Python | agronholm/anyio | /src/anyio/streams/buffered.py | UTF-8 | 4,500 | 2.9375 | 3 | [
"MIT"
] | permissive | from __future__ import annotations
from collections.abc import Callable, Mapping
from dataclasses import dataclass, field
from typing import Any
from .. import ClosedResourceError, DelimiterNotFound, EndOfStream, IncompleteRead
from ..abc import AnyByteReceiveStream, ByteReceiveStream
@dataclass(eq=False)
class Buf... | true |
2f06182b39e06d28e9a336f3a9f3b631c483b843 | Python | AreebaShakir/Initial-Tasks | /task3.py | UTF-8 | 893 | 3.015625 | 3 | [] | no_license | from flask import Flask, request, jsonify
import operator
app = Flask(__name__)
def reverse(func):
def inner():
data = request.get_json()
op = data['op']
inverse = {"+": "-",
"-": "+",
"*":"/",
"/":"*"}
data['op... | true |
619e8b2343643c93e5eb255b24b575aaae8b8deb | Python | antrad1978/bigdata | /PySpark/json1.py | UTF-8 | 669 | 2.953125 | 3 | [] | no_license | # Spark
from pyspark import SparkContext
# Spark Streaming
from pyspark.streaming import StreamingContext
# Kafka
from pyspark.streaming.kafka import KafkaUtils
# json parsing
import json
sc = SparkContext(appName="json")
sc.setLogLevel("WARN")
import json
def jsonParse(dataLine):
parsedDict = json.lo... | true |
549e190b1aea9c2f5968a24739e2296afda06d1b | Python | PPodhorodecki/Prework | /02_Typy_danych_w_Pythonie/Zadanie_1-Typy_danych/task.py | UTF-8 | 373 | 3.625 | 4 | [] | no_license | calkowita=5
rzeczywista=3.14
tekst="Python"
tak=True
result="Zmienna {} ma wartość {}".format("całkowita", calkowita)
print(result)
result="Zmienna {} ma wartość {}".format("rzeczywista", rzeczywista)
print(result)
result="Zmienna {} ma wartość {}".format("tekstowa", tekst)
print(result)
result="Zmienna {} ma warto... | true |
42db02aefdf3f91c213a6ec556e61b25e9bb5b2e | Python | FreulonManon/fakenews | /arc.py | UTF-8 | 2,554 | 2.734375 | 3 | [] | no_license | import arcpy
import json
import tweepy
import time
import csv
from tweepy.streaming import StreamListener
#Enter Twitter API Key information obtenu en créant une api twitter
consumer_key = ''
consumer_secret = ''
access_token = ''
access_secret = ''
auth = tweepy.OAuthHandler(consumer_key, consumer_secret)
auth.set... | true |
caa06eb951cd2e06db4c402db3a79fda9d27b8e7 | Python | csc522nbagroup/playoffsandsalary | /all 2.py | UTF-8 | 2,492 | 2.546875 | 3 | [] | no_license | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Fri Nov 9 12:39:30 2018
@author: shaohanwang
"""
import pandas as pd
import numpy as np
train_data=pd.read_csv('all.csv')
train_data['Playoffs'] = train_data['Playoffs'].map({'Y': 1, 'N': 0})
train_data=train_data.dropna(axis='columns')
x=train_data.iloc... | true |
96be8996f29fb4f34eb3e423e662cad74d5c17d7 | Python | AtharvaBhagat/email-using-python | /sendEmailUsingVoice.py | UTF-8 | 1,621 | 2.84375 | 3 | [] | no_license | # pip install pyttsx3
# pip install SpeechRecognition
import pyttsx3
import speech_recognition as rec
import smtplib
from email.message import EmailMessage
from win10toast import ToastNotifier
notify = ToastNotifier()
listener = rec.Recognizer()
engine = pyttsx3.init()
voices = engine.getProperty('voice... | true |
2ac918164fb69f90dd53256157aa2253c55960bc | Python | soareswallace/mit-deep-learning | /tutorial_mnist/plot_images.py | UTF-8 | 275 | 2.9375 | 3 | [
"MIT"
] | permissive | import matplotlib.pyplot as plt
def plot_images(features, labels):
plt.figure(figsize=(10,2))
for i in range(5):
plt.subplot(1, 5, i+1)
plt.xticks([])
plt.yticks([])
plt.grid(False)
plt.imshow(features[i], cmap=plt.cm.binary)
plt.xlabel(labels[i])
plt.show() | true |
542959fbd1899f6b9f0120d07e49f075a1aecc9b | Python | StrikeR2018/TDD | /question1/third_test/test_fizzbuzz.py | UTF-8 | 827 | 3.046875 | 3 | [] | no_license | import unittest
import fizzbuzz
class testCase(unittest.TestCase):
def test_case_1(self):
self.assertEqual(fizzbuzz.fizzBuzz(3), "Fizz")
def test_case_2(self):
self.assertEqual(fizzbuzz.fizzBuzz(5), "Buzz")
def test_case_3(self):
self.assertEqual(fizzbuzz.fizzBuzz(15), "not multiple... | true |
b98482805d6241de565adfe11fe620589ab15bea | Python | BorisMs55/django-handy | /django_handy/url.py | UTF-8 | 1,247 | 2.6875 | 3 | [
"MIT"
] | permissive | from urllib.parse import parse_qs, urlencode, urlsplit, urlunsplit
def simple_urljoin(*parts, append_slash=False):
"""Normalize url parts and join them with a slash."""
parts = list(map(str, parts))
schemes, netlocs, paths, queries, fragments = zip(*(urlsplit(part) for part in parts))
scheme = _last(s... | true |
74c78bc28df423b759eb70b1ecad935248610bc1 | Python | Uthreloss/hearts_pepper | /scripts/make_map.py | UTF-8 | 2,191 | 2.84375 | 3 | [
"MIT"
] | permissive | #!/usr/bin/env python
from pepper_controller import PepperController
import numpy
# pip install pillow
try:
from PIL import Image
except ImportError:
import Image
robotIP = "westey.local" #Stevey
PORT = 9559
class MakeMap(PepperController):
def startingVariables(self):
## Verbal confirmation i... | true |
d571080961ba901443d8276cf27c5e64000dab00 | Python | LancerEnk/softwareTesting_Work3 | /Code_ForModified/Task9/wrong_5_032.py | UTF-8 | 601 | 3.984375 | 4 | [] | no_license | # Task 9: wrong_5_032
# 错误原因：使用replace()函数对首字母进行处理时，只是将替换后的首字母赋给了b，但没有给b增加非首字母的字符串，因此应该在后续为b补上a的后续字母。
# 修改方法：为b赋予a的后续字符串，使用python中string的截取方法。
def fun(input):
a = input
if a[0].isupper() == True:
return(a)
elif a[0].isupper() == False:
b = a[0].replace(a[0],a[0].upper(),1)
b+=a[1:]
return(b)
# 获取输入数值时的代... | true |
5b6514e1053ccaeecb2adf26937b71e2a674f430 | Python | maliciousgroup/BugBountyConsole | /src/core/command/ExitCommand.py | UTF-8 | 585 | 2.546875 | 3 | [] | no_license | import asyncio
from src.core.command.base.BaseCommand import BaseCommand
class ExitCommand(BaseCommand):
helper: dict = {
'name': 'exit',
'help': 'This command will gracefully exit the application',
'usage': 'exit'
}
def __init__(self, command: str, print_queue: asy... | true |
dc43503080966efb3cc6ee909b8a2eb569c589ba | Python | zhongsangyang/PythonSimpleTest | /testPython/com/ht/pachogn/testnew.py | UTF-8 | 4,170 | 2.859375 | 3 | [] | no_license | # coding=utf-8
import urllib
import json
from urllib import request
import re
import os
class CrawlOptAnalysis(object):
def __init__(self,search_word="美女"):
self.search_word = search_word
self.headers={
'User-Agent': 'Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko)... | true |
b829943cbe955cb595d080f8811fb2cf2b289a7a | Python | sumsar01/Lattice-gauge-theory | /Spin_1_fields/Projector_advanced.py | UTF-8 | 2,480 | 2.578125 | 3 | [] | no_license | from Gauss_law_advanced import *
from Storage import *
from qutip import *
from itertools import product
import itertools as itertools
import numpy as np
###############################################################################
# Making projection
################################################################... | true |
e924030346aa50175885f0203c7ce0678c2f3dd5 | Python | Scoowy/PythonLuisa | /tareanro1sb_a---expresiones-regulares-lfbermeo-main/src/problem2.py | UTF-8 | 372 | 3.15625 | 3 | [
"MIT"
] | permissive | import re
# Completar la función regex_ayuda para que tome una expresión regular (como una cadena) y
# una cadena a la que desea aplicar la expresión regular.
# La función debe devolver una lista con todas las apariciones del patrón en la cadena.
def regex_ayuda(patron, cadena_entrada):
pattern = re.compile(patr... | true |
c762eb94b2994f9ca2566fb73bba5b0f176d1fe1 | Python | Nivek-Stack/CPS3320 | /Project2/WordFinder.py | UTF-8 | 881 | 4.15625 | 4 | [] | no_license | from dictionary import *
dictionary = Dictionary()
# pip install dictionary
# words.txt OR A.txt
words = [] # Empty List that will store everything from the word file.
new_words = [] # Empty List to make Strings later on.
f = open('words.txt', 'r') # Opens the File in read mode only.
words = f.read().splitl... | true |
44d7f596e9fad288916c6c4b9ad87bb858eec3d3 | Python | leandrogpv/chatbot-whats | /bot_whats.py | UTF-8 | 6,036 | 2.796875 | 3 | [] | no_license | # -*- coding: utf-8 -*-
from time import sleep
from selenium.webdriver.common.keys import Keys
'''
Bugs identificados a serem corrigios:
*_Caso houver mensagens diferentes do mesmo remetente que chegaram no mesmo
minuto ele nao considera como duas mensagens e acaba nao lendo a ultima
*_Caso nao h... | true |
664fac06d8c70d7fdc08bb21d3eb88db5bce74c3 | Python | chandlersupple/Color-Pass-Filter | /ColorPassFilter.py | UTF-8 | 2,876 | 3.234375 | 3 | [
"MIT"
] | permissive | # Chandler Supple, 6/2/2018
# The algorithm may be unresponsive for a few seconds after having initialized depending on the file size.
# To add, some '.jpg' images may not work due to the PIL library.
import io
import pygame
from PIL import Image
from urllib2 import urlopen
url = raw_input('Image Url (png, jpg): ')
... | true |
c8fec20fce52112171d2941c2bc50bb41483bf07 | Python | Charleezy/WinrateForFamiliarChamps | /api_wrapper/api_wrapper.py | UTF-8 | 6,318 | 2.84375 | 3 | [] | no_license | from urllib.parse import urlencode
import urllib.request
from urllib.error import HTTPError
from API_KEY import API_KEY
import time
import logging
import json
import threading
import queue
SHORT_TIME_LIMIT = 11
SHORT_MAX_REQUESTS = 10
LONG_TIME_LIMIT = 605
LONG_MAX_REQUESTS = 500
MAX_REQUEST_HTTP_CODE = 429
HIGHES... | true |
387c054696079f389983c3bfdae887a398fe4b05 | Python | brenda151295/scripts_AmazonBooks | /insertTableSalesRank.py | UTF-8 | 1,752 | 2.734375 | 3 | [] | no_license | # Importing MongoClient.
from pymongo import MongoClient
# Importing MySQL Connector.
import mysql.connector
import pymysql
# Connecting to MySQL.
mysql_conn = mysql.connector.connect(user='root', password='1234', port="3306", host='127.0.0.1', database='books_dataset')
# Geting the product details from 'asin'.
def... | true |
a99267e5f9797818aa37abe12a12462b266fea13 | Python | spuddie1984/Python3-Basics-Book-My-Solutions | /Graphical User Interfaces/review_exercises_geometry_manager.py | UTF-8 | 694 | 3.65625 | 4 | [] | no_license | import tkinter as tk
'''
1. Try to re-create all the screenshots in this section without looking
at the source code
'''
window = tk.Tk()
frame1 = tk.Frame(master=window, width=500, height=100, bg="red")
frame1.pack(fill=tk.BOTH, side=tk.LEFT, expand=True)
frame2 = tk.Frame(master=window, width=100, bg="yellow")
frame... | true |
aa6e9b87ddcd785d96235d43b41c314d9967ab60 | Python | LukeChai/PythonExercise | /python basic/dataStructure.py | UTF-8 | 1,399 | 4.375 | 4 | [] | no_license | #!/usr/bin/python
# -*- coding: utf-8 -*-
# Filename: dataStructure.py
# 数据结构
# 列表的基本操作
a = [3, 2, 34, 12.3]
print(a)
# 添加一个元素到列表后面
a.append(15)
print(a)
# 查看元素的位置
print(a.index(34))
# 移除一个元素
a.remove(2)
print(a)
# 翻转列表
a.reverse()
print(a)
# 排序
a.sort()
print(a)
# 元组的基本操作，元组的值不会被改变
b = ("a", "b", "c")
print(b)
print... | true |
92ef8c5b517957114740debdaab86be468889bf8 | Python | jacenfox/psd-tools2 | /src/psd_tools/utils.py | UTF-8 | 2,746 | 2.84375 | 3 | [
"MIT"
] | permissive | # -*- coding: utf-8 -*-
from __future__ import absolute_import, division, unicode_literals, print_function
import sys
import struct
import array
try:
unichr = unichr
except NameError:
unichr = chr
def unpack(fmt, data):
fmt = str(">" + fmt)
return struct.unpack(fmt, data)
def read_fmt(fmt, fp):
... | true |
f6187ec82a6e8091edc5f45deface464fdd87115 | Python | AbbyGeek/CodeWars | /8kyu/Calculate Average.py | UTF-8 | 112 | 3.078125 | 3 | [] | no_license | def find_average(array):
if len(array) == 0:
return 0
else:
return sum(array)/len(array) | true |