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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
7b536c74a499700274615fbbe02eea4fcc503cc5 | Python | CelsoAntunesNogueira/Phyton3 | /ex030 - descobrindo o numero par.py | UTF-8 | 205 | 4.03125 | 4 | [
"MIT"
] | permissive | a = int(input('Digite um número que irei dizer se é par ou não!'))
b = a % 2
print('O número foi {}'.format(a))
if b == 0:
print('Esse número é par!')
else:
print('Esse número é ímpar!')
| true |
596d2eea5906d536011f76be3696e8e66eb2241a | Python | Buzonxxxx/python-learning | /lecture4/hw4.py | UTF-8 | 1,970 | 4.3125 | 4 | [] | no_license | # -*-coding:UTF-8 -*-
# 試以 EX02_07.py 的程式碼為基礎，撰寫三個函數
# list_zip(city)
# 傳入值為城市名稱可列出所有某城市裡面所有區域的郵遞區號
# ex. 呼叫 list_zip("台北市")，則列出所有台北市內所有區域的郵遞區號
# area_to_zip(area)
# 傳入值為區域名稱回傳此區域的郵遞區號
# ex. 呼叫 area_to_zip("信義區") ，回傳 (‘台北市’,110) , (‘基隆市’,201)
# zip_to_area(zip)
# 傳入值為郵遞區號回傳區域名稱
# ex. 呼叫 area_to_zip(106) ，回傳... | true |
ff7762f7b516eb3ede0dd6b3ad0578858fba8808 | Python | Aasthaengg/IBMdataset | /Python_codes/p03265/s385452962.py | UTF-8 | 722 | 2.546875 | 3 | [] | no_license | import bisect, collections, copy, heapq, itertools, math, string, sys
input = lambda: sys.stdin.readline().rstrip()
sys.setrecursionlimit(10**7)
INF = float('inf')
def I(): return int(input())
def F(): return float(input())
def SS(): return input()
def LI(): return [int(x) for x in input().split()]
def LI_(): return [... | true |
46314c4b81231c9bf12d6031a878af28b1bf5cd0 | Python | caige13/Integral-Calculator | /Integral Calculator/DoubleIntegralOptions.py | UTF-8 | 2,262 | 2.84375 | 3 | [] | no_license | import DOUBLEINTEGRALCLASS
def evaluateDoubleIntegral(m,n,a,b,c,d,function):
FunctionOf = False
m = int(m)
n = int(n)
checkx = []
checky = []
checky = a.split("y")
checky.append(b.split("y"))
checkx = c.split("x")
checkx.append(d.split("x"))
if len(checky)... | true |
98de1696a788a984093c0a8d70bf38e613eabc7e | Python | gerardcl/renfe-cli | /src/renfe/utils.py | UTF-8 | 4,869 | 2.65625 | 3 | [
"BSD-3-Clause"
] | permissive | import sys
import os
import json
import logging
import optparse
from pathlib import Path
class RenfeException(Exception):
def __init__(self, *args, **kwargs):
Exception.__init__(self, *args, **kwargs)
class ConfigurationMgmt():
_config_location = '.renfe_default_stations.json'
_logging_levels = ... | true |
476b5dab13b1e1ba7a1104325a9ad86a52b6234a | Python | FanWu-fan/Cs_231n | /chapter2/前向传播代码.py | UTF-8 | 999 | 3.140625 | 3 | [] | no_license | import math
x =3
y = -4
#前向传播
sigy = 1.0 / (1 + math.exp(-y)) #(1)
num = x+sigy #(2)
sigx = 1.0 / (1 + math.exp(-x)) #(3)
xpy = x+y #(4)
xpysqr = xpy**2 #(5)
den = sigx + xpysqr #(6)
invden = 1.0/den #(7)
f = num*invden ... | true |
1c4fba16206de578a64c5bb0947dd1749fe8bd37 | Python | elarbee/euler | /11/11.py | UTF-8 | 1,740 | 3.28125 | 3 | [] | no_license |
grid_file = file("./grid.txt")
# Create 2D Grid
grid_matrix = []
for line in grid_file:
line_list = str(line).replace('\n','').split(" ")
grid_matrix.append(map(int,line_list))
max_product = 0
def vertical_pairs():
m = 0
for x in range(0,20):
for y in range(0,17):
a = grid_matri... | true |
446707b14a019744fb79a3a20e1e803e9fa800b5 | Python | Snehal-610/Python_Set | /CalenderMethod.py | UTF-8 | 859 | 3.53125 | 4 | [] | no_license | # Calender Methods
import calendar
year = 2012
month = 11
# print(calendar.month(year, month))
# print(calendar.calendar(2021,0.5,1,6))
# weekdays = calendar.Calendar(firstweekday = 2)
#
# for day in obj.iterweekdays():
# print(day)
MonthDate1 = calendar.Calendar()
# for dates in MonthDate1.itermonthdates(2021... | true |
5e367ff2249ad0560f0d5cbfd20f7e354e45a650 | Python | BarbarianElf/cnn_speech_recognition | /main.py | UTF-8 | 6,471 | 2.53125 | 3 | [] | no_license | """
main file
for CNN Speech Recognition project
Created on January 12th 2021
@authors: Niv Ben Ami & Ziv Zango
"""
from keras.models import load_model
import os
import numpy
import data_utils
import config
import cnn
def get_data(feature_type=None):
try:
x_data = numpy.load("saved_data/x_data_" + feat... | true |
834633e62ba9da9bcfa768d3a27fa9a07f9d0d9d | Python | i-aditya-kaushik/geeksforgeeks_DSA | /Hashing/sort_by_freq.py | UTF-8 | 143 | 3.265625 | 3 | [] | no_license | def sortByFreq(a,n):
a.sort()
a = sorted(a,key = lambda x:a.count(x),reverse=True)
for x in a:
print(x,end=" ")
print() | true |
b597ad298175da1c8abae5d636905602405e0634 | Python | aman212yadav/COMPUTER_NETWORK | /ERROR_DETECTION_AND_CORRECTION/checksum.py | UTF-8 | 441 | 3.21875 | 3 | [] | no_license | def getOnesComplement(n):
n=list(bin(n)[2:])
for i in range(len(n)):
if n[i]=='0':
n[i]='1'
else:
n[i]='0'
return "".join(n)
print("Enter data received : ",end=" ")
data_received=list(map(int,input().split()))
if int(getOnesComplement(su... | true |
7b739c80f8421322cc01470a3c6b4ebd3e932f24 | Python | jaebee94/TIL | /SWEA/SWEA_D1/SWEA_D1_2063.py | UTF-8 | 593 | 3.421875 | 3 | [] | no_license | # 2063. 중간값 찾기
# 중간값은 통계 집단의 수치를 크기 순으로 배열 했을 때 전체의 중앙에 위치하는 수치를 뜻한다.
# 입력으로 N 개의 점수가 주어졌을 때, 중간값을 출력하라
def median(N, score):
idx = len(score) // 2
for i in range(len(score)-1, 0, -1):
for j in range(0, i):
if score[j] > score[j+1]:
score[j], score[j+1] = score[j+1], score... | true |
a6659f812f853fcfe36844d7eb31162aa6494fa6 | Python | alwin1031/UV-Vis | /conc.py | UTF-8 | 1,931 | 3.171875 | 3 | [] | no_license | import pandas as pd
import matplotlib.pyplot as plt
from matplotlib.ticker import FormatStrFormatter
def pre_read(pre_df):
for i in range(len(pre_df.iloc[:,0])):
if pre_df.iloc[i,0] == 'Data Points':
skip_line = i+2
break
return skip_line
def Abs280(df):
for i i... | true |
6c0fcecc3465f2e05a0b829024805c8e3c2b1714 | Python | sourcebots/zone-script | /main.py | UTF-8 | 2,038 | 2.828125 | 3 | [] | no_license | import glob
import json
import re
import socket
import time
from enum import Enum
from pathlib import Path
from threading import Event
sock = socket.socket(socket.AF_UNIX, socket.SOCK_STREAM)
class State(Enum):
CONNECT = 1
MESSAGE = 2
DONE = 3
def poll(robot_root_path: str, zone_id: int, stop_event: Ev... | true |
bcd811e4a5122eb4d8d145b61694754815c32a64 | Python | k19421/MatplotlibClass | /Python数据可视化利器Matplotlib，绘图入门篇，布局自动调整命令/3.py | UTF-8 | 615 | 3.203125 | 3 | [] | no_license | # 多绘图区不规则布局
import matplotlib.pyplot as plt
def example_plot(ax, fontsize=12):
ax.plot([1, 2])
ax.locator_params(nbins=3)
ax.set_xlabel('x-label', fontsize=fontsize)
ax.set_ylabel('y-label', fontsize=fontsize)
ax.set_title('Title', fontsize=fontsize)
fig1 = plt.figure()
ax1 = plt.subplot(221)... | true |
6c55f15bb75e1cca779204f1302da1946f6775f6 | Python | zc-cris/python_demo01 | /进阶07_模块/demo03_practice.py | UTF-8 | 666 | 3.59375 | 4 | [] | no_license | # zc-cris
'''
给标签进行分组匹配:
可以在分组中利用（?P<name>正则表达式）的方式来给分组规则进行别名，获取到的匹配结果可以直接使用group(’name‘)的方式来获取
复合分组规则的匹配内容，我们称之为命名分组和引用分组；如果不想起名，可以使用序号的方式来引用分组规则（不推荐，示例：<(\w+)>\w+</\1>）
'''
import re
search = re.search('<(?P<name>\w+)>\w+</(?P=name)>', '<h2>cris</h2>')
print(search) # <_sre.SRE_Match object; sp... | true |
21327236681470f37e276cded5c36cc7c945a01d | Python | py-graphit/py-graphit | /graphit/graph_io/io_cwl_format.py | UTF-8 | 2,341 | 2.53125 | 3 | [
"Apache-2.0"
] | permissive | # -*- coding: utf-8 -*-
#
# Copyright (C) 2016-2018
# Author: Marc van Dijk (marcvdijk@gmail.com)
# file: io_cwl_format.py
"""
Functions for importing data structures in Common Workflow Language format.
The Common Workflow Language (CWL) is a specification for describing analysis
workflows and tools in a way that ma... | true |
df39dd464eb13f9f059a3e1cd9b63e96822cf85b | Python | jswelling/TweetHandling | /TweetHandling/src/Decoder.py | UTF-8 | 6,405 | 2.59375 | 3 | [] | no_license | #! /usr/bin/env python
# -*- coding: utf-8 -*-
"""
Created on Thu Feb 12 11:54:12 2015
@author: ColdJB
"""
import sys
import cPickle as pickle
import re
import os.path
import datetime
import types
from collections import defaultdict
# directory = '\\Primack\\Primack Projects\\01 Projects\\2015_hpi_twitter\\World Vap... | true |
89cb6c488487d228f0636d1488adceb20a12d339 | Python | forchain/GANshion | /homework/HW2/Q3_2.py | UTF-8 | 12,212 | 2.5625 | 3 | [] | no_license | # %%
# -*- coding: utf-8 -*-
# Author : Ali Mirzaei
# Date : 19/09/2017
from tensorflow.keras.models import Sequential, Model
from tensorflow.keras.layers import Dense, Input, Flatten, Reshape, Conv2DTranspose, concatenate
from tensorflow.keras.datasets import mnist
from tensorflow.keras.optimizers import Adam, SGD
... | true |
140d3eea61536ebba9df8a90731436929fbb74fe | Python | mahendra-ramajayam/megnet | /megnet/data/local_env.py | UTF-8 | 1,597 | 2.984375 | 3 | [
"BSD-3-Clause"
] | permissive | from pymatgen.analysis.local_env import *
class MinimumDistanceNNAll(MinimumDistanceNN):
"""
Determine bonded sites by fixed cutoff
Args:.
cutoff (float): cutoff radius in Angstrom to look for trial
near-neighbor sites (default: 4.0).
"""
def __init__(self, cutoff=4.0):
... | true |
1fb541911a546b8cf06dfe41abb3cc06654c1c6e | Python | messi-wpy/CCNU-CS-lab | /python_learn/exercise2/exercise2-2.py | UTF-8 | 293 | 3.625 | 4 | [] | no_license | num_1 = int (input("请输入数字:"))
num_2 = int (input("请在输入一个数字"))
a=num_1*num_2
if num_1>=num_2:
b=num_1
c=num_2
else:
b=num_2
c=num_1
while b % c != 0:
temp = c
c = b % c
b = temp
print("最大公约数:", c)
print("最小公倍数:", a/c)
| true |
cb6426171f608e3c8cfc664372b6b8028c99b972 | Python | avanish-patel/Python_Data_Science | /string.py | UTF-8 | 198 | 3.78125 | 4 | [] | no_license | fname = "Avanish"
lname = "Patel"
fullName = fname + " " + lname
print(fullName)
sentence = "Hi, I'm Avanish Patel"
print(sentence)
# \ is ommiting letter
sentence = 'Hi, I\'m Avanish Patel'
print(sentence)
| true |
ba432bbac8a37602cae74b2c43cde05a0ff87d5a | Python | erikvansebille/STAMM | /LIB/turtle_lib.py | UTF-8 | 10,452 | 2.984375 | 3 | [
"MIT"
] | permissive | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Created on Wed Dec 18 10:46:43 2019
@author: tcandela
"""
# =============================================================================
# IMPORTS
# =============================================================================
import numpy as np
import netCDF_lib as ... | true |
81bc1bfc73c946ecd118a33240f163c9d07ab74f | Python | daniel-zeng/Tic-Tac-Toe | /board.py | UTF-8 | 4,388 | 2.953125 | 3 | [] | no_license | symbols = {0: "-", 1: "O", 2: "X"}
NOUG = 1
CROSS = 2
TIE = 3
width = 3
endGame = {NOUG: 1, CROSS: 0, TIE: 0.5}
class Board:
def __init__(self, case):
self.board = [0] * 9
self.case = case
global endGame
if case == 1:
self.memo = self.loadMemo("win_state.txt")
... | true |
8b73994eeae155bf5354ac306613936f51546bcc | Python | benjspriggs/grading | /lint/test/test_static_member.py | UTF-8 | 756 | 2.703125 | 3 | [] | no_license | #!/usr/bin/env python
# test_static_member.py
# Test for Static Member linter
from unittest import TestCase, main
from lint.lib import StaticMemberLinter
class StaticMemberLinterTest(TestCase):
has_static = "test/fixtures/has-static.cpp"
well_formatted = "test/fixtures/well-formatted.cpp"
def test_lint(s... | true |
0c59286c827f69dc5fbf3caf8071dd8893fa1ae2 | Python | dan99925/HomeWorkHilel | /HomeWork/HW7.py | UTF-8 | 322 | 3.65625 | 4 | [] | no_license |
x1 = int(input("First_coordinate"))
y1 = int(input("Second_coordinate"))
x2 = int(input("coordinate of movement_1"))
y2 = int(input("coordinate of movement_2"))
dx = x1 - x2
dy = y1 - y2
if dx < 0:
dx *= -1
if dy < 0:
dy *= -1
if dx == 1 and dy == 2 or dx == 2 and dy == 1:
print(True)
else:
print(False... | true |
4412d475bf336d19daa5dda576ce4584b7c9c599 | Python | wong2/memobird.py | /memobird.py | UTF-8 | 2,556 | 2.578125 | 3 | [
"MIT"
] | permissive | #-*-coding:utf-8-*-
import requests
from base64 import b64encode
from cStringIO import StringIO
from datetime import datetime
from PIL import Image, ImageOps
class ApiError(Exception):
pass
class Paper(object):
def __init__(self):
self.contents = []
@staticmethod
def _ensure_gbk(text):
... | true |
1c60b2495572da7fa97afc01e1aad4793cb265f7 | Python | Wifi-cable/Robotic_AI_student_project | /otherScripts/doubleMyData.py | UTF-8 | 1,089 | 3.21875 | 3 | [] | no_license | #!/usr/bin/env python3
import cv2
import datetime
import os
import time
import glob
'''
@param: string, folder with images.
Takes all images in "imageFolder" and mirrors them. The flipped images are saved
into the same folder. No immage name can be exidentally used twice because the
name is tied to the unix time st... | true |
fabbfd7a36f3539a5b8b3875bd0268684e51d085 | Python | HuyaneMatsu/hata | /hata/discord/message/message_call/tests/test__put_ended_at_into.py | UTF-8 | 626 | 2.59375 | 3 | [
"LicenseRef-scancode-warranty-disclaimer"
] | permissive | from datetime import datetime as DateTime
import vampytest
from ....utils import datetime_to_timestamp
from ..fields import put_ended_at_into
def test__put_ended_at_into():
"""
Tests whether ``put_ended_at_into`` works as intended.
"""
ended_at = DateTime(2016, 5, 14)
for input_value, defa... | true |
4e7e4c065eb30aa007afd051badd760e10244d60 | Python | ttecles/weather_backend | /tests/test_tu_tiempo_api.py | UTF-8 | 3,747 | 2.578125 | 3 | [] | no_license | import copy
from unittest import TestCase
import httpx
import respx as respx
from httpx import Response
from app.weather import TuTiempoAPI
from tests.base import api_response, day_s, hour_s
class TestTuTiempoAPI(TestCase):
def setUp(self) -> None:
self.api = TuTiempoAPI("api_key", locations=[1])
... | true |
e278b033d9aed39ad7461679ccebb7a87f290e42 | Python | fennisreed/WorldPop-to-USNG | /WP_to_USNG.py | UTF-8 | 2,188 | 2.53125 | 3 | [] | no_license | # WORLDPOP TO USNG CONVERSION
# ---------------------------------------------------------------------------
# DESCRIPTION: A brief script that converts WorldPop gridded population
# estimates to USNG grid cells. Centroids of each intersecting cell from the
# WP estimate are summed for each input geography and joine... | true |
2f2ad5bd43b54b6a5d51ef2fb2530c74158ac99c | Python | bijay007/Python | /fibonacci.py | UTF-8 | 298 | 3.234375 | 3 | [] | no_license | first = 0; next = 1; sum = 0
ask = input ('Enter a limit to calculate its Fibonacci sequence : ')
if ask > 50: print 'Too large. Enter smaller than 50'
else:
for i in range (0,ask):
sum = first + next
first = next
next = sum
print sum
sum = 0
| true |
12a910e3d80376901b09ef362234da7d853a313b | Python | jmwright/cqparts | /tests/partslib/basic.py | UTF-8 | 2,510 | 3.046875 | 3 | [
"Apache-2.0"
] | permissive |
import cadquery
import cqparts
from cqparts.params import *
from cqparts.constraint import Mate
from cqparts.constraint import Fixed, Coincident
from cqparts.utils import CoordSystem
# --------------- Basic Parts ----------------
# Parts with the express intent of being concise, and quick to process
class Box(cqpa... | true |
cdac4fb99bc96b9deb41eb26b476f94b66b41af5 | Python | bennullgraham/letterburb | /route.py | UTF-8 | 16,413 | 2.78125 | 3 | [] | no_license | import heapq
import itertools as it
import math
import operator
import subprocess
import sys
from collections import defaultdict
from functools import lru_cache
from functools import reduce
from pathlib import Path
from random import choice
from random import sample
from typing import Dict
from typing import Iterable
f... | true |
ccb7cc38d99d17fc5a2ebe115bd580dc6453c691 | Python | dr-dos-ok/Code_Jam_Webscraper | /solutions_python/Problem_209/255.py | UTF-8 | 900 | 3.140625 | 3 | [] | no_license | import operator
import math
class Pancake:
def __init__(self, r, h):
self.r = r
self.h = h
self.vert = 2 * math.pi * r * h
self.tot = math.pi * r * r + self.vert
T = int(input())
for t in range(1, T+1):
N, K = [int(_) for _ in input().split(" ")]
pancakes = []
for n in... | true |
9b415a3cc07b1771a8b520af1451b4cfef21a3c8 | Python | givenone/lightstage | /generate_pointcloud_ns.py | UTF-8 | 4,469 | 2.5625 | 3 | [] | no_license | # the resulting .ply file can be viewed for example with meshlab
# sudo apt-get install meshlab
#
# revised by junwon
"""
This script reads a registered pair of color and depth images and generates a
colored 3D point cloud in the PLY format.
"""
from plyfile import PlyData, PlyElement, PlyProperty, PlyListProperty
imp... | true |
8d08837326b98593204d464958437dcbb6bf87e1 | Python | adinosaur/Interns | /Interns.py | UTF-8 | 855 | 2.90625 | 3 | [] | no_license | # -*- coding: UTF-8 –*-
PyIntInterns = {}
PyStrInterns = {}
PyTupleInterns = {}
def obj_intern(o):
obj_type = type(o)
if obj_type is int:
return int_intern(o)
elif obj_type is str:
return str_intern(o)
elif obj_type is tuple:
return tuple_intern(o)
assert False
def int_int... | true |
26c9711dd485a0ed855399472bf04980be1f30bb | Python | guptaShantanu/Python-Programs | /adobe.py | UTF-8 | 419 | 2.875 | 3 | [] | no_license | n=int(input())
m=int(input())
dept=[]
for i in range(n):
temp = list(map(int,input().split()))
dept.append(temp)
i=0
connection=0
ladyCount1=0
ladyCount2 = 0
while i<n:
for k in range(m):
ladyCount2+=dept[i][k]
if ladyCount2==0:
pass
else:
connection+=ladyCount2*ladyCount1
... | true |
8ff834b5e1ab894134f6d2e9c052d243b6326cd6 | Python | zhjr2019/PythonWork | /01_Python_Basis/Python_Karon/05_高级数据类型/jr_08_格式化字符串.py | UTF-8 | 273 | 4.09375 | 4 | [] | no_license | info_tuple = ("小明", 18, 1.75)
# 格式化字符串后面的（）本质上就是元组
print("%s 年龄是 %d 身高是 %.2f" % info_tuple)
info_str = "%s 年龄是 %d 身高是 %.2f" % info_tuple # 元组拼接字符串 生成 一个新的字符串
print(info_str) | true |
983083f283f3db5777303d6c8b30e4b16487ceae | Python | ginny100/Social-Awareness-2 | /Dijkstra_version2.py | UTF-8 | 1,129 | 3.796875 | 4 | [] | no_license | '''
Dijkstra's algorithm for undirected weighted graph
Version 2
Source: protonx.ai
'''
# Create a graph
N = 7
edges = [ [0, 2, 1],
[0, 1, 2],
[0, 6, 3],
[1, 5, 10],
[1, 4, 15],
[2, 1, 4],
[2, 3, 2],
[3, 4, 3],
[4, 5, 5],
[6, 1, ... | true |
9f337eba06c7af6b9c5e514cb18aebc527575e77 | Python | Sunny4552/wave-splash-projects | /AdventureGame.py | UTF-8 | 3,235 | 3.453125 | 3 | [] | no_license | import time
import random
boss = ["Alien", "Predator", "Hydra"]
def print_pause(string):
print(string)
time.sleep(1)
def valid_input(prompt, option1, option2):
while True:
print_pause(prompt)
response = input()
if option1 == response:
break
e... | true |
4a882cc673f867ff563619a2afb5db8481784cc5 | Python | ab-gh/cs50ai | /projects/wk4/shopping/shopping.py | UTF-8 | 6,361 | 3.296875 | 3 | [] | no_license | import csv
import sys
<<<<<<< HEAD
=======
import datetime
>>>>>>> 8878b8963063bf4207d52ab25b1a365dc6f7e2dc
from sklearn.model_selection import train_test_split
from sklearn.neighbors import KNeighborsClassifier
TEST_SIZE = 0.4
def main():
# Check command-line arguments
if len(sys.argv) != 2:
sys.e... | true |
f6e5857ed30231b7b464bd96c8bfd292c32f32d9 | Python | antocaroca/ejercicios-usm-python | /ejercicios_parte_1/diseno_de_algoritmos/suma_de_digitos_al_cubo.py | UTF-8 | 346 | 3.8125 | 4 | [] | no_license | # Entre todos los enteros mayores a 1 hay solamente cuatro que pueden ser representados por la suma de los cubos de sus dígitos.
# FALTA!
start= 149
end = 410
count = 0
lista = []
while start < end:
start += 1
count+=1
lista.append(start)
print(lista)
cubos = []
for cubo in range(1,10):
cubos.appen... | true |
c39d094d51b13d4e60192866aaaf6b165dda299b | Python | izzrak/numpy_cnn | /data_utils.py | UTF-8 | 1,032 | 2.53125 | 3 | [
"MIT"
] | permissive | import numpy as np
import struct
from glob import glob
def load_mnist(path, kind='train'):
"""Load MNIST data from `path`"""
images_path = glob('./%s/%s*3-ubyte' % (path, kind))[0]
labels_path = glob('./%s/%s*1-ubyte' % (path, kind))[0]
with open(labels_path, 'rb') as lbpath:
magic, n = struct.unpack('>I... | true |
fde4a313106110ebb4b7784cd01aa79439269ebb | Python | Equidamoid/freecaddy | /freecaddy/bearings.py | UTF-8 | 1,082 | 2.6875 | 3 | [] | no_license | from dataclasses import dataclass
import Part
from FreeCAD import Base
v = Base.Vector
@dataclass
class BearingDimensions:
d_in: float
d_out: float
h: float
inner_ring: float = None
def hole_shape(self, z_clearance, xy_clearance=0):
"""
Shape of the hole where the bearing is to ... | true |
0e8ea3dd74a243e14411b1bda33b777e9effa050 | Python | vladnire/PythonProjects | /ChatBot/chatbot_functions.py | UTF-8 | 3,264 | 3.0625 | 3 | [] | no_license | from chatterbot import ChatBot
from chatterbot.trainers import ChatterBotCorpusTrainer
from chatterbot.trainers import ListTrainer
from chatterbot.response_selection import get_most_frequent_response
def create_bot(name):
""" We have read_only to false so the chatbot
learns from the user input
Args:
... | true |
11f79c30a3f16375aec7d92998dc385f392f50b6 | Python | whisper0077/programming-contests | /atcoder/ABC/175/B.py | UTF-8 | 260 | 2.796875 | 3 | [] | no_license | import itertools
N = int(input())
*L, = map(int, input().split())
ans = 0
for l in itertools.combinations(L, 3):
l = list(l)
l.sort()
if l[0] != l[1] and l[1] != l[2] and l[0] != l[2]:
if l[2] < (l[0]+l[1]):
ans += 1
print(ans)
| true |
c87412fd49b0290a358f816d60f6c7535841a994 | Python | vishnumenon/SleepTopology | /zerodpersistence.py | UTF-8 | 2,234 | 2.796875 | 3 | [] | no_license | import numpy as np
class Vertex(object):
def __init__(self, x, y, isMax, componentBirths, currComponent=-1):
self.x = x
self.y = y
self.isMax = isMax
self.component = currComponent
if not isMax:
componentBirths[currComponent] = y
self.children = []
d... | true |
87e1384478205b00d05d88055eb998fbd9895ed6 | Python | williamdemeo/Aljebra | /Aljebra/src/closure/OldClosure.py | UTF-8 | 16,891 | 3.03125 | 3 | [] | no_license | ''' Utilities for finding congruence lattice representations of small lattices.
Created on Jun 12, 2013
@author: williamdemeo at gmail
@see: Itertools documentation at http://docs.python.org/2/library/itertools.html
'''
from org.uacalc.alg.conlat import BasicPartition
from org.uacalc.lat import BasicLattice
from org.ua... | true |
f2bbe391b591f58d735e0b9a5d7460150439dbad | Python | wzdnzd/leetcode | /python3/0023.合并k个排序链表.py | UTF-8 | 2,015 | 3.234375 | 3 | [
"Apache-2.0"
] | permissive | #
# @lc app=leetcode.cn id=23 lang=python3
#
# [23] 合并K个排序链表
#
# https://leetcode-cn.com/problems/merge-k-sorted-lists/description/
#
# algorithms
# Hard (42.88%)
# Likes: 235
# Dislikes: 0
# Total Accepted: 23.8K
# Total Submissions: 51.9K
# Testcase Example: '[[1,4,5],[1,3,4],[2,6]]'
#
# 合并 k 个排序链表，返回合并后的排序链表。... | true |
582ff6e9f961cd9ad80074decb937bc146e4ef20 | Python | nyetwurk/mumble | /scripts/transtate.py | UTF-8 | 1,997 | 2.609375 | 3 | [
"BSD-3-Clause"
] | permissive | #!/usr/bin/env python
#
# Copyright 2005-2017 The Mumble Developers. All rights reserved.
# Use of this source code is governed by a BSD-style license
# that can be found in the LICENSE file at the root of the
# Mumble source tree or at <https://www.mumble.info/LICENSE>.
# Extracts the progress of translations from th... | true |
be8ee938ca6287ab0fe30611fcd4e797f320ce8c | Python | ItManHarry/Pandas | /data/chapter5/SortByIndex.py | UTF-8 | 1,827 | 3.625 | 4 | [] | no_license | import pandas as pd
import random as rd
#创建数据
data = [['N%s' %i,'jack%s@163.com' %i, rd.randint(20, 45), '1%s%s%s%s' %(rd.choice([3,5]), rd.randint(0,9), rd.randint(1000,9999), rd.randint(1000,9999)), rd.choice(['F','M']), rd.choice(['山东','河南','山西','河北','湖南','湖北','北京','上海','广州'])] for i in range(5000)]
columns = ['职号',... | true |
33fc12ec1d256bf8c7da807da5d403a47b5e654e | Python | tlaehdtlr/Go-Algorithm | /삼성/청소년상어(하다맘).py | UTF-8 | 1,908 | 2.65625 | 3 | [] | no_license | dr = [-1, -1, 0, 1, 1, 1, 0, -1]
dc = [0, -1, -1, -1, 0, 1, 1, 1]
def move_shark(sea, fishes):
r, c = fishes[0]
return attack
def move_fish(sea, fishes):
for num in range(1, 17):
if fishes[num]:
r, c = fishes[num]
_, direc = sea[r][c]
for d in range(8):
... | true |
21f4397700cf977e11306f00af527a569159f0ff | Python | jabe1204/test | /hola.py | UTF-8 | 157 | 3.546875 | 4 | [] | no_license | print("Hola Mundo")
print("")
print("Contador normal")
for i in range(10):
print(i)
print("")
print("Contador invertido")
for i in range(10):
print(9-i)
| true |
0b426fdcf8159c9529f29482984386b281b20f82 | Python | Pravin2796/python-practice- | /chapter 10/instanceattribute.py | UTF-8 | 230 | 3.265625 | 3 | [] | no_license | class Employee:
company = "google"
salary = 100
harry = Employee()
rajni = Employee()
# creating instance attribute salary for both objects
harry.salary = 300
# rajni.salary = 400
print(harry.salary)
print(rajni.salary) | true |
ee78118916b96fb5283bd2aec051903680327275 | Python | 594billy/reviews-analytics | /read.py | UTF-8 | 258 | 3.578125 | 4 | [] | no_license | data = []
with open('reviews.txt', 'r') as f:
for line in f:
data.append(line)
print ('總共有', len(data), '筆留言')
sum_len = 0
for comment in data:
sum_len += len(comment)
print('平均留言長度為', sum_len / len(data), '個字') | true |
36976107aaadff337071498e80b8ca2c43a574e2 | Python | Dip-Xd/pokurt | /blog.py | UTF-8 | 726 | 2.84375 | 3 | [] | no_license | from feedparser import parse
from html2markdown import convert
url = "https://blog.pokurt.me/rss/"
def func(url):
feed = parse(url).entries
latest = [
f"""[📝 {feed[i].title}]({feed[i].link}) \n{feed[i].description} - {feed[i].published}\n\n---------------------"""
for i in range(3)
]
... | true |
875744a00d6067f04e53cdd87dd00a7f139096b8 | Python | yooyep/tensorflows- | /204_saver_reload.py | UTF-8 | 2,039 | 2.734375 | 3 | [] | no_license | #%%
# -*- coding: utf-8 -*-
import tensorflow as tf
import numpy as np
import matplotlib.pyplot as plt
import pickle
tf.reset_default_graph()
#--------------- 导入数据 ---------------
x_data = np.linspace(-2,2,100)[:,np.newaxis]
noise = np.random.normal(0,0.1,size=x_data.shape).astype(np.float32)
y_data = x_data**2+noise
... | true |
cfa9678e7b93b1ecee1332da1236d27bf22cdf89 | Python | SantoroPablo/tesis_maestria_dm | /src/vae_esferas/py_classes/CSVSphDataset.py | UTF-8 | 845 | 2.9375 | 3 | [] | no_license | # Clase para cargar el dataset de esferas a partir de
# la lectura de una lista de archivos en un CSV.
# Es una subclase de la clase 'Dataset' de pytorch
import torch
import torchvision
import numpy as np
import pandas as pd
import trimesh
import os
class CSVSphDataset(torch.utils.data.Dataset):
"""
Dataset de... | true |
e5db935263e1624c7a4aa3904b5df2fe18752222 | Python | atshaya-anand/LeetCode-programs | /Easy/nAndDouble-exists.py | UTF-8 | 447 | 2.96875 | 3 | [] | no_license | # https://leetcode.com/problems/check-if-n-and-its-double-exist/
class Solution:
def checkIfExist(self, arr: List[int]) -> bool:
a = set(arr)
count = 0
for i in range(len(arr)):
c = 2*arr[i]
if c == 0:
count +=1
if c... | true |
74fe21e77f500a6a8701a9416515a67c09fabc7a | Python | bmolina-nyc/ByteAcademyWork | /Assessment_1_Practice_2/fake_app/data/schema.py | UTF-8 | 948 | 2.53125 | 3 | [] | no_license | import os
import sqlite3
DIR = os.path.dirname(__file__)
DB = 'practice_db.db'
DBPATH = os.path.join(DIR, DB)
def schema(dbpath = DBPATH):
with sqlite3.connect(dbpath) as conn:
cursor = conn.cursor()
DROPSQL = "DROP TABLE IF EXISTS {tablename};"
cursor.execute(DROPSQL.format(tablename="ts... | true |
6d849d1dd6763943523e1af953ede6c61400d786 | Python | liwangzhi/Classification | /train_labels_csv.py | UTF-8 | 2,305 | 2.765625 | 3 | [] | no_license | """
describe:
@project: 智能广告项目
@author: Jony
@create_time: 2019-07-09 12:21:10
@file: dd.py
"""
import re
from glob import glob
from itertools import chain
import os
import math
import numpy as np
import pandas as pd
import os.path as osp
from tqdm import tqdm
def read_data_path(data_path,hidename):... | true |
0f23433cb58700c040108312999be8527700c174 | Python | mjota/telephone_analyzer | /telephone_analyzer.pyw | UTF-8 | 6,972 | 2.578125 | 3 | [] | no_license | #!/usr/bin/env python
# -*- coding: utf-8 -*-
# -----------------------------------------------------------------------------
# Telephone Analyzer
# Copyright (c) 2012 - Manuel Joaquin Díaz Pol
#
# This program is free software: you can redistribute it and/or modify it under
# the terms of the GNU General Public Licens... | true |
dbd26034c587b200fe6701aa122df6226a492fa3 | Python | xeddmc/AI-bitcoin | /cs221-stuff/util.py | UTF-8 | 2,417 | 3.09375 | 3 | [] | no_license | import time, datetime, copy
from datetime import date
from datetime import timedelta
from datetime import datetime
time_format = '%d/%m/%Y %H:%M:%S'
def time_to_date(t):
return datetime.date(datetime.fromtimestamp(time.mktime(t)))
# return 2d array of data in file
# first index of each row is a Time, second index i... | true |
35eba0435e4816f30291fdae7a46237531694236 | Python | yijaein/cnn_classification | /Tools/mask_dataset_patient_info.py | UTF-8 | 4,220 | 2.625 | 3 | [] | no_license | import csv
import os
import cv2
from Tools.dicom_physical_size import read_diagnosis_csv, read_dicom_pixel_size_csv, object_wh
from Tools import csv_search
def norm_path(path):
path = os.path.normcase(path)
path = os.path.normpath(path)
path = os.path.expanduser(path)
path = os.path.abspath(path)
r... | true |
d67936bf74e5c4feb0fd8ac641926f45f93b52a2 | Python | Wedge-Dev/IT-Automation-with-Python | /1. Crash Course on Python/Week 2 Basic Python Syntax/Expressions and Variables/Expressions, Numbers, and Type Conversions.py | UTF-8 | 559 | 4.46875 | 4 | [] | no_license | #In this scenario, we have a directory with 5 files in it. Each file has a different size: 2048, 4357, 97658, 125, and 8. Fill in the blanks to calculate the average file size by having Python add all the values for you, and then set the files variable to the number of files. Finally, output a message saying "The avera... | true |
e2dd92a1f1ade33509b9ade084fea5163d835346 | Python | Omega094/lc_practice | /serilize_binary_tree/Serilizer.py | UTF-8 | 3,190 | 3.609375 | 4 | [] | no_license | # Definition for a binary tree node.
# class TreeNode(object):
# def __init__(self, x):
# self.val = x
# self.left = None
# self.right = None
import sys
sys.path.append("/Users/jinzhao/leetcode/")
from leetcode.common import *
class Codec:
def serialize(self, root):
"""Encodes... | true |
8be35e4d68d5458fa03c375d73b05eb47e1848d9 | Python | Sampada7K/Programming_Questions | /Regex/findall_emails.py | UTF-8 | 386 | 3 | 3 | [] | no_license | import re
pattern = r'([\w+.-]+)@([\w.]+)'
emails = []
with open('text.txt', 'r') as f:
lines = f.readlines()
for line in lines:
email = re.findall(pattern, line)
emails.append(email[0])
if emails:
print(emails)
with open('emails.txt', 'w') as f:
for email in emails:
f.write(... | true |
04304e071b213ef354a9f240f1e8d523811bd906 | Python | azrael11/kalliope | /Tests/test_dynamic_loading.py | UTF-8 | 4,458 | 3.109375 | 3 | [
"MIT"
] | permissive | import inspect
import os
import unittest
class TestDynamicLoading(unittest.TestCase):
"""
Test case for dynamic loading of python class
This is used to test we can successfully import:
- STT engine
- TTS engine
- Trigger engine
- All core neurons
"""
def setUp(self):
# ge... | true |
d991d295ca5398a0e14445e9a8af33cb7e3aa2a0 | Python | GonzaloGNogales/RoadClassifierVA | /Euclidean_LDA_Classifier/euclidean_lda.py | UTF-8 | 3,170 | 3.453125 | 3 | [] | no_license | import numpy as np
from sklearn.discriminant_analysis import LinearDiscriminantAnalysis
class Euclidean_LDA:
def __init__(self):
# Instantiate a linear discriminant analysis object (LDA) for reducing the data dimensionality
self.lda = LinearDiscriminantAnalysis()
self.centroids = list()
... | true |
e08078831439f6aa071eee3bd302d07c71dd8bd8 | Python | arturoalviar/project-euler-python | /python/problem_25_thousand_digit_fibo_num.py | UTF-8 | 401 | 3.734375 | 4 | [] | no_license | ############################################################
#Problem 25
def thousand_digit_fibo_num(index = 0):
'''Finds the index of the first term in the Fibonacci sequence to contain 1000 digits?'''
a , b = 0 , 1
limit = 100000
while limit > 0:
a , b = b , b + a
index += 1
... | true |
3325686183c831bcd182ec1fd7f014ec20bd3961 | Python | MatthewFletcher/ENG101Python | /HW10P1.py | UTF-8 | 2,504 | 3.328125 | 3 | [] | no_license | # _ _ _ _ _ _ _ _ _ _ _ _
# (c).-.(c) (c).-.(c) (c).-.(c) (c).-.(c) (c).-.(c) (c).-.(c)
# / ._. \ / ._. \ / ._. \ / ._. \ / ._. \ / ._. \
# __\( Y )/__ __\( Y )/__ __\( Y )/__ __\( Y )/__ __\( Y )/__ __\( Y )/__
# (_.... | true |
e3b445263cacce5e32b206c66090017617afc249 | Python | ninilo97/CodeWithGoogle-2019 | /Kick Start 2019/Practice Round/mural.py | UTF-8 | 812 | 2.921875 | 3 | [] | no_license | def simple_beauty(mural):
mural_size_to_check = int((len(mural)+1)/2)
lst = []
for i in range(mural_size_to_check):
lst.append(sum(mural[i:i+mural_size_to_check]))
return max(lst)
def complex_beauty():
mural_size = int(input())
mural = [int(num) for num in str(input())]
mural_size_t... | true |
921f286e45034a68394ddb3c483bb950b6324f0e | Python | shuxiangguo/Python | /Learn/spider/21DaysOfDistributedSpider/ch04/csv_demo/csv_writer_test.py | UTF-8 | 962 | 3.25 | 3 | [] | no_license | # encoding: utf-8
"""
@author: shuxiangguo
@file: csv_writer_test.py
@time: 2018-11-03 01:16:32
"""
import csv
def csv_writer():
headers = ['Username', 'age', 'heigth']
students = [
('zhangsan', 20, 180),
('lisi', 21, 187),
('王五', 22, 178)
]
with open('./studnents.csv', 'w', encoding='utf-8', newline='') as... | true |
26e33398fc17892b63afed5331f4fafed3e1091b | Python | Wizmann/ACM-ICPC | /Leetcode/Algorithm/python/2000/01872-Stone Game VIII.py | UTF-8 | 300 | 2.65625 | 3 | [
"LicenseRef-scancode-warranty-disclaimer"
] | no_license | INF = 10 ** 10
class Solution(object):
def stoneGameVIII(self, stones):
n = len(stones)
pre = sum(stones)
maxi = -INF
for i in xrange(n - 1, 0, -1):
maxi = max(maxi, pre - (0 if i + 1 == n else maxi))
pre -= stones[i]
return maxi
| true |
3c13524027c3beb3a2bb73bbb8473b9d2666fb46 | Python | infinite-Joy/programming-languages | /python-projects/algo_and_ds/merge_intervals_using_stacks.py | UTF-8 | 972 | 3.6875 | 4 | [] | no_license | """
merge intervals
bringing in an n2 solution which is the brute force
so you check each and every and then merge them if fall within the same range
Input: intervals = [[1,3],[2,6],[8,10],[15,18]]
Output: [[1,6],[8,10],[15,18]]
Explanation: Since intervals [1,3] and [2,6] overlaps, merge them into [1,6].
[[1,3]... | true |
fa2d74433cce7811f2848d3124931f0b71ca1c17 | Python | JoshCoop1089/Private-Projects | /Python/2018/HackerRank/HackerRank Challenge 'miniMaxSum'.py | UTF-8 | 235 | 3.265625 | 3 | [] | no_license | # -*- coding: utf-8 -*-
"""
Created on Fri Apr 6 22:39:05 2018
@author: joshc
"""
def miniMaxSum(arr):
arr.sort()
arrmin=sum(arr[:-1])
arrmax=sum(arr[1:])
print(arrmin,arrmax)
arr=[1, 2, 3, 4, 5]
miniMaxSum(arr) | true |
8a58d6292eaf188f229139a6d533687028fadfec | Python | rileonard15/offline-insta-slides | /main.py | UTF-8 | 3,887 | 2.53125 | 3 | [] | no_license | import web
import os
import time
import requests
import urllib
import urllib2
import json as simplejson
import dl_image as IMAGES
urls = (
'/', 'IndexHandler',
'/login', 'LoginHandler',
'/filenames', 'FilenameHandler',
)
CLIENT_ID = "" # client ID goes here
CLIENT_SECRET = "" # client SECRET goes here
HAS... | true |
286469f715bf374a8f898bc98b1fd1e90cc2afb7 | Python | vraj152/projectcs520 | /featureExtraction.py | UTF-8 | 2,324 | 3.671875 | 4 | [] | no_license | import numpy as np
"""
Feature of particular image of particular position & index starts from (0,0)
e.g.:
Let's say matrices[5] (from driverFile.py)
Extract feature from 2nd row and 3rd column ; i=1, j=2
i being row number and j being column number
params:
test = input image in Numpy array object
i ... | true |
344b4b5d06c3125f8dfb75894f99dcf1573dc85b | Python | DeanHe/Practice | /LeetCodePython/LargestPalindromicNumber.py | UTF-8 | 1,148 | 4.1875 | 4 | [] | no_license | """
You are given a string num consisting of digits only.
Return the largest palindromic integer (in the form of a string) that can be formed using digits taken from num. It should not contain leading zeroes.
Notes:
You do not need to use all the digits of num, but you must use at least one digit.
The digits can be ... | true |
e1625d7c3ffe17d4805ddf049732f8e650dcaa7c | Python | marko-knoebl/courses-code | /python/2019-05/reading_writing_files/analyze_todos.py | UTF-8 | 908 | 3.546875 | 4 | [] | no_license | # manually downloaded data from jsonplaceholder.typicode.com
# - json file of 200 todos
import json
with open('reading_writing_files/todos.json', encoding='utf-8') as todofile:
todostring = todofile.read()
tododata = json.loads(todostring)
num_todos = len(tododata)
print(f"{num_todos} todos")
num_completed = 0... | true |
a97f66da1a1ce5535d55b1e573f94135e8ee11f8 | Python | lbertoncello/BT-kNN | /sklearn_knn.py | UTF-8 | 1,742 | 2.765625 | 3 | [] | no_license | import numpy as np
from sklearn import neighbors, datasets, model_selection
from sklearn.metrics.pairwise import cosine_similarity
def write_results(results, dataset_dirname):
with open('%s/classifieds.txt' % dataset_dirname, 'w') as f:
for result in results:
f.write("%s\n" % str("".join... | true |
317e1bf5315ec955dc7ae4eede8cac4f9cdf2328 | Python | CPMcshane/DinoLand | /analysis.py | UTF-8 | 4,845 | 4.375 | 4 | [] | no_license | """
This is a python file that uses the sqlite module to perform sql commands.
The purpose of this program is to find which dinosaurs can be placed
safely together in habitats based on each dinosaur's characteristics.
Herbavores, carnivores, and flying dinosaurs must be kept seprate. Territorial
creatures cannot be pl... | true |
dde4e7857bd4b5dd7fa4d8e5cace0be4dc40140b | Python | spratapa/arc_sent_project | /app1.py | UTF-8 | 1,190 | 2.578125 | 3 | [] | no_license | import sys
import numpy as np
import tensorflow as tf
from keras.models import Model,Sequential
from keras.layers import Dense, Input, Dropout, LSTM, Activation
from keras.layers.embeddings import Embedding
from keras.preprocessing import sequence,text
from matplotlib import pyplot
from keras.datasets import imdb
from... | true |
98425dc9e1d51b07a02699e009c26464332dd457 | Python | mcstitzer/dawe_ab10_kindr | /identify_haplotypes/pars_inf_snps.py | UTF-8 | 1,476 | 2.65625 | 3 | [] | no_license | ## find parsimony informative sites in multifasta alignment, output csv file of position and snp.
## relies on aligned fasta, only characters as ACTG-
## prints csv to STDOUT
import sys
from Bio import SeqIO
from Bio.SeqRecord import SeqRecord
from collections import Counter
seqs=list(SeqIO.parse(open('ALL_KINDR_TE_... | true |
7ef602728d013dc381d01c62b8aa6ad310783fdd | Python | OkayHughes/iros2017_pedestrian_forecasting | /code/scene.py | UTF-8 | 9,013 | 3.21875 | 3 | [] | no_license | """Scene module
Module contains the scene class, whose initializer
will train a scene from a given set of training data.
"""
import pickle
import numpy as np
import process_data
class Scene():
""" A class which learns stuff from a list of trajectories.
attributes:
num_nl_classes: This is the number ... | true |
745dbe68ea5ba1ef509ebee9f007db14c1ebaf85 | Python | pfig9141/Metody-Numeryczne | /aproksymacja_danych2.py | UTF-8 | 672 | 2.609375 | 3 | [] | no_license | import numpy as np
import matplotlib.pyplot as plt
import scipy.signal as scp
import scipy.io
from scipy.interpolate import interp1d
# dane
data13 = list(scipy.io.loadmat('G:/Dane do Stacjonarny WAT/dysk H/Dane/Dane energetyczne/data_98.mat',
squeeze_me=True).values())[3] # (dysk WAT)
# o... | true |
6fd9692fb41d45ffeb6d0c46031c37368333a99f | Python | alexlikova/Python-Basics-SoftUni | /7. Python Basics - More Exercises/2. Conditional Statements - More Exercises/07. Flower Shop.py | UTF-8 | 682 | 3.78125 | 4 | [] | no_license | import math
number_magnolii = int(input())
number_zumbuli = int(input())
number_roses = int(input())
number_cactus = int(input())
price_present = float(input())
magnolii = 3.25
zumbuli = 4.0
roses = 3.5
cactus = 8.0
price_magnolii = magnolii * number_magnolii
price_zumbuli = zumbuli * number_zumbuli
price_roses = ro... | true |
2909685d07b4df7f713f7940fa408749d72a9a65 | Python | zzuse/fluentPythonLearning | /coroutineUsage.py | UTF-8 | 6,058 | 3.390625 | 3 | [] | no_license | import inspect
def simple_coroutine():
print('-> coroutine started')
x = yield
print('-> coroutine received:', x)
my_coro = simple_coroutine()
print("linspect.getgeneratorstate(my_coro) {}\n----------".format(inspect.getgeneratorstate(my_coro)))
print("my_coro {}\n----------".format(my_coro))
print("lin... | true |
2c01dcc86e41a4a7f8f7e11a3f3c43aed697869c | Python | ProjectsWithPython/FileHandling | /src/EasyFileHandling/tests/test_filehandler.py | UTF-8 | 1,160 | 3.15625 | 3 | [
"MIT"
] | permissive | import unittest
import os
import sys
import io
from EasyFileHandling.main import FileHandler
class FileHandlerTests(unittest.TestCase):
test_filename = 'test.txt'
def setUp(self):
try:
with open(self.test_filename, 'w') as f:
f.write('This is a test file.\nThis is the seco... | true |
0a6e225409e54166075d191a46c6012899175b3f | Python | alaamarashdeh92/CA05---Introduction-to-Functions | /Q7.py | UTF-8 | 213 | 3.671875 | 4 | [] | no_license | # Q 7
# ******
def sum_or_max(my_list):
if len(my_list) %2 == 0 :
return sum(my_list)
if len(my_list) != 0 :
return max(my_list)
list1 = [1,2,3,4,5]
print(sum_or_max(list1))
| true |
7b2e545878985ba30f1abf370c06a0b4aefd36e9 | Python | alexa984/python101 | /week5/MusicLibrary/playlist.py | UTF-8 | 4,141 | 3.4375 | 3 | [] | no_license | import json
import numpy as numpy
import matplotlib.pyplot as plt
from random import shuffle
from song import Song
class Playlist:
def __init__(self, name, repeat=False, shuffle=False):
#everything in song_list should be of class Song
self.name = name
self.song_list = []
self.repeat ... | true |
a1840821ed886302176410f6d95d0e7f1c5f1a57 | Python | DatGuy1/pajbot | /pajbot/utils/find.py | UTF-8 | 328 | 2.90625 | 3 | [
"MIT"
] | permissive | from typing import Callable, Iterable, Optional, TypeVar
T = TypeVar("T")
def find(predicate: Callable[[T], bool], seq: Iterable[T]) -> Optional[T]:
"""Method shamelessly taken from https://github.com/Rapptz/discord.py"""
for element in seq:
if predicate(element):
return element
retu... | true |
db5d9a78128f75b7571359bffb88b34e7f1eb5e9 | Python | dougalferg/OpenVibSpec | /scr/openvibspec/preprocessing.py | UTF-8 | 2,157 | 3.546875 | 4 | [] | no_license | ''' This submodule provides basic preprocessing functionality to work with hyperspectral data/images.
E.g.
- Normalization
- Baseline Correction/Removal
- RGB-Image standardization
- Scatter correction (especially RMieS-correction)
- Data transformations from 3D to 2D and reverse
- ...
@JoshuaButke
github.com/butkej
... | true |
bd75eb24527bf7e4fe9e7e1028e564ac6a5f1adf | Python | KathyCriollo/Deber-Semana_nueve | /Reloj.py | UTF-8 | 267 | 3.25 | 3 | [] | no_license | # -*- coding: utf-8 -*-
import time
fecha_hora = time.strftime("%c")
print ("Fecha y hora " + time.strftime("%c")) #Fecha y hora
print ("Fecha " + time.strftime("%x")) #tiempo
print ("Hora " + time.strftime("%X")) #hora
print ("Fecha y hora son: %s" % fecha_hora ) | true |
cf548c69e9ce4c2451abc433c8c06fe65772587f | Python | MaxwellHsiaotw/projects | /NBA bet program/prediction%.py | UTF-8 | 1,359 | 2.5625 | 3 | [] | no_license | import csv
import datetime
fh = open('C:\\Users\\Maxwell\\Documents\\Python file\\NBA\\file\\betdata.csv', 'r', newline='', encoding = 'utf-8')
fh1 = open('C:\\Users\\Maxwell\\Documents\\Python file\\NBA\\file\\result.csv', 'w', newline='', encoding = 'utf-8')
aa = fh.readline()
reader = csv.reader(fh)
writer = c... | true |
29213ae3eb6fcaaedaa4632e6afc1fb4fbed36b3 | Python | tdb-alcorn/q2 | /q2/config/__init__.py | UTF-8 | 1,544 | 2.59375 | 3 | [
"MIT"
] | permissive | import os
import yaml
import importlib.util
from typing import Dict, List, Any
cwd = os.getcwd()
objects_file = os.path.join(cwd, 'objects.yaml')
object_types = [
'agent',
'environment',
'objective',
'regimen',
]
default_objects = dict()
for ot in object_types:
default_objects[ot] = dict()
def p... | true |
21875b26b0babfe5cae46756257c0c4e0d5a36f4 | Python | liuchenghao2000/1807 | /1807-1/13day/00-拳头.py | UTF-8 | 261 | 3.171875 | 3 | [] | no_license | import random
pc = random.randint(1,100)
for i in range(10):
player = int(input('请输入数字:'))
if player > pc:
print('太大了')
elif player < pc:
print('太小了')
else:
print('答对了')
break
| true |
04be02ac6596fa27b56c0dfc46e27de96d565724 | Python | jpark712/large_pal_prod | /large_pal_prod.py | UTF-8 | 540 | 3.390625 | 3 | [] | no_license | def largest_palindrome(n):
upper_limit = 10**n - 1
lower_limit = 10**(n-1) - 1
largest = 0
for a in range(upper_limit, lower_limit, -1):
for b in range(upper_limit, lower_limit, -1):
prod = a*b
if prod < largest:
break
if (is_palindrome(prod)):... | true |
d2914044d18b97aece908b80cd2fb40f62dd9f61 | Python | dschweim/WeakSupervisionForPopulismDetection | /util.py | UTF-8 | 15,519 | 2.78125 | 3 | [] | no_license | import os
import numpy as np
import re
import pandas as pd
from datetime import datetime
from sklearn.model_selection import train_test_split
from sklearn.metrics import f1_score, precision_score, recall_score, accuracy_score
def generate_train_dev_test_split(df):
"""
Generate train dev test split
:param ... | true |