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 |
|---|---|---|---|---|---|---|---|---|---|---|---|
902c53953f96d81d2d9c0ff53f7274dd73824b95 | Python | PieceZhang/face_detect_yolov4_yolov4tiny_ssd | /picture.py | UTF-8 | 877 | 2.75 | 3 | [
"Apache-2.0"
] | permissive | import cv2
image_origin = cv2.imread('ssd.png')
assert image_origin is not None, 'Image is not found, No such file or directory'
image_data = cv2.resize(image_origin, (300, 300))
cost_time = 136.06
image_data = cv2.putText(image_data, 'Model: SSD_300',
(10, 25), cv2.FONT_HERSHEY_COMPLEX_SMALL... | true |
a84cde0c8cf35c6f59928e1d0c8bd382cc347223 | Python | nsbejrFire/microbitRobot | /session_02/ex02_blink_maqueen_led.py | UTF-8 | 355 | 2.96875 | 3 | [] | no_license | from microbit import * # tell python code will run on micro:bit
display.clear() # makes sure all display LEDs are off
while True:
pin8.write_digital(1) # turn Maqueen's left LED on
sleep(1000) # sleep for 1000 milliseconds = 1 second
pin8.write_digital(0) # turn Maqueen's left LED off
sleep(1000) # slee... | true |
f51ce40e94e394fabe01e5a36ec9153534264464 | Python | KaspariK/leetcode-python | /two-sum-1/solution.py | UTF-8 | 391 | 3 | 3 | [] | no_license | from typing import List
class Solution:
def twoSum(self, nums: List[int], target: int) -> List[int]:
target_dict = {}
response = []
for i, num in enumerate(nums):
if num in target_dict:
response = [target_dict.get(num), i]
break
else... | true |
b648611ddaa22fe52e39185fcaac3fa928a2dd85 | Python | leolion0/490-Lesson-2 | /weights.py | UTF-8 | 229 | 3.40625 | 3 | [] | no_license | infile = open("lbs.txt", 'r')
lbs = list()
count = 0
line = infile.readline()
while line !="":
lbs.append(float(line))
count += 1
line = infile.readline()
kilos = [n*0.453592 for n in lbs]
# print(lbs)
print(kilos) | true |
2dd165ae49b4ca928a8f46a6228e155cca7d62a3 | Python | vs-zhang/lc_py | /020/is_valid_parentheses.py | UTF-8 | 461 | 3.546875 | 4 | [] | no_license | class Solution(object):
def is_valid_parentheses(self, s):
stack = []
pair = ['()', '[]', '{}']
for i in range(0, len(s)):
stack.append(s[i])
if len(stack) >= 2 and stack[-2]+stack[-1] in pair:
stack.pop()
stack.pop()
return len... | true |
69be7f05ba96c2e765b3f9f4b495c33de10aab98 | Python | branrickman/py_pi_monte_carlo | /src/main.py | UTF-8 | 4,373 | 3.296875 | 3 | [] | no_license | import pygame
from random import randint
from math import sqrt
pygame.init()
SCREEN_SIDE_SIZE: int = 901
assert SCREEN_SIDE_SIZE % 2 != 0, "Error: SCREEN_SIDE_SIZE must be an odd integer"
FPS = 200
screen = pygame.display.set_mode((SCREEN_SIDE_SIZE, SCREEN_SIDE_SIZE))
pygame.display.set_caption("Monte Carlo Pi Calc... | true |
f546bff96ec82d85a5111b4e17cdfa799369d1cc | Python | migbro/kfdrc-toolbox | /vcf_validation/vcf_exact.py | UTF-8 | 452 | 3.0625 | 3 | [] | no_license | #!/usr/bin/env python
# reads vcf and checks line-by-line to see if content is the same. quite crude.
import sys
import gzip
def open_vcf(vcf_fn):
if vcf_fn[-3:] == '.gz':
return gzip.open(vcf_fn, 'rb')
else:
return open(vcf_fn)
vcf1 = open_vcf(sys.argv[1])
vcf2 = open_vcf(sys.argv[2])
f... | true |
303ab156d3ec852c98baeac39de74d45f97f6e97 | Python | EngrDevDom/Everyday-Coding-in-Python | /Message Box in Python/Show_Error.py | UTF-8 | 193 | 2.9375 | 3 | [] | no_license | # Show_Error.py
from tkinter import *
from tkinter import messagebox
top = Tk()
top.title("Messagebox")
top.geometry("100x100")
messagebox.showerror("Error", "This is Error!")
top.mainloop()
| true |
cbbe6334bda96ba0e043292ce0ad67454f6b59b6 | Python | STORMRECLUSE/EpilepsyVIP-master | /DCEpy/ML/anomaly_detect.py | UTF-8 | 17,334 | 2.71875 | 3 | [] | no_license | '''
This file is structured similarly to scikit-learn's perceptron code, currently in beta. Similar structures.
'''
from __future__ import print_function
from __future__ import division
import numpy as np
import six, warnings
from sklearn.utils.fixes import signature
def lin_func(data,x1,y1,m):
if type(x1) is floa... | true |
e589228d2846ae2c944a7dab10abd83a9381aeec | Python | TryhardAlan/Personal-learning | /03_circle_statement/alan_02_summation.py | UTF-8 | 134 | 3.78125 | 4 | [] | no_license | # calculator 0-100 summation
i = 0
sum_1 = 0
while i <= 100:
sum_1 = sum_1 + i
i += 1
print("0-100 sumation is %d!" % sum_1)
| true |
8b09e7bef300e5a8eb4cdfac2048553505b6a7a7 | Python | asmeurer/Miscellaneous-Useful-Scripts | /Comics_Downloader.py | UTF-8 | 8,650 | 2.6875 | 3 | [
"MIT"
] | permissive | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
# Modified from getben.py, which is in ~/Downloads/comic/ as of 20080116
"""
Comics Downloader.py
Downloads comic strips from http://comics.com/ for use with the ACMEReader
program. By default, it downloads all the strips from today to the last strip
found for each strip... | true |
26b91a7dc04bc10b30dd431023a7ea5db2a2ad6b | Python | bradicator/matrixstream | /ota2d.py | UTF-8 | 4,250 | 3 | 3 | [] | no_license | import numpy as np
"""
Implementation of offline tensor analysis from Beyond Streams and Graphs:
Dynamic Tensor Analysis.
"""
class ota2d(object):
def __init__(self, tensor, r1 = 3, r2 = 3):
"""r1, r2 are number of PC we wish to retain"""
self.t = tensor
self.r1 = r1
self.r2 = r2
... | true |
0e41777772c07303731eb80ecbaa33bce330cbce | Python | Walter1412/python_exercise | /users/serializers.py | UTF-8 | 945 | 2.546875 | 3 | [] | no_license | from rest_framework import serializers
from users.models import Account as UsersAccountModel
class AccountSerializer(serializers.Serializer):
name = serializers.CharField(required=True)
password = serializers.CharField(required=True)
def create(self, validated_data):
print(validated_data)
... | true |
452e0ab5b4ec844be68cac6ee605ab1b706fe2f5 | Python | aitutor22/tetris | /blocks.py | UTF-8 | 6,291 | 2.625 | 3 | [] | no_license | import random
from collections import OrderedDict
class Block(object):
shapes_length = {
"i": [4, 1],
"o": [2, 2],
"t": [3, 2],
"s": [3, 2],
"z": [3, 2],
"j": [3, 2],
"l": [3, 2],
}
shapes_buffer = {
"i": [(0, 0), (-2, 1), (0, 0), (-1, 2)],
... | true |
86ffece104ebd3f8c8356520875233c7ec84fe89 | Python | hjlarry/practise-py | /standard_library/FileSystem/io_example.py | UTF-8 | 1,429 | 3.5 | 4 | [] | no_license | import io
print("一、 字符串IO操作")
output = io.StringIO()
output.write("something to buffer. ")
# file: a file-like object (stream); defaults to the current sys.stdout.
print("And so does this", file=output, end=" ")
print(output.getvalue())
output.close() # discard buffer memory
input = io.StringIO("Intial value for re... | true |
18d29f8ed69b0a375e3f2454e5d9da4bcb38874d | Python | maximebriol/process_data | /notebooks/pretty_printer.py | UTF-8 | 364 | 2.578125 | 3 | [] | no_license | import tempfile
import pathlib
import pandas
import processing_data
def print(table: processing_data.Table) -> pandas.DataFrame:
with tempfile.TemporaryDirectory() as folder:
path = pathlib.Path(folder).joinpath("dump.csv")
with path.open("w") as stream:
stream.write(table.to_csv())
... | true |
72cb4394285ff4f9530ad15a67d5192df7d20f1a | Python | ecell/ecell4-vis | /ec4vis/visualizer/panel.py | UTF-8 | 2,216 | 2.546875 | 3 | [] | no_license | # coding: utf-8
"""ec4vis.visualizer.panel --- visualizer panel
"""
import wx, wx.aui
# this allows module-wise execution
try:
import ec4vis
except ImportError:
import sys, os
p = os.path.abspath(__file__); sys.path.insert(0, p[:p.rindex(os.sep+'ec4vis')])
from ec4vis.logger import debug, log_call
from ec... | true |
b34cfbcebaeae6ff5ead89cf08608be2819d5108 | Python | Ting-Kim/CodingTest_with_py | /greedy/n3109.py | UTF-8 | 1,170 | 3.0625 | 3 | [] | no_license | # / - \ 순으로 탐색
# 점마다 /-\ 순으로 반복해서 진행하며, 진행 성공한 경우 o체크 + 다음 process로..
def search(x, y):
if y == m-1:
graph[x][y] = 'o' # 방문 체크
# answer += 1
return True
for i in range(3):
nx = x + dx[i]
ny = y + dy[i]
if 0 <= nx < n and 0 <= ny < m and graph[nx][ny] == '.':
... | true |
bb056329a0828c60af59bace875a91f6b09fff5e | Python | hwuachen/git-trump-tweets | /vocabulary.py | UTF-8 | 1,132 | 3.1875 | 3 | [] | no_license | import csv
import nltk
from pprint import pprint
grouped_by_source = {}
with open('trump_tweets.csv') as csvfile:
reader = csv.DictReader(csvfile)
for row in reader:
text = row['text']
platform = row['source']
try:
grouped_by_source[platform] = grouped_by_source[platform] ... | true |
53b2cb2631ad1f3b760383f583e9ba9cbc184437 | Python | caitlinstanton/ece-5725 | /lab3/two_wheel.py | UTF-8 | 2,477 | 3.21875 | 3 | [
"MIT"
] | permissive | # Brandon Quinlan (bmq4) and Caitlin Stanton (cs968)
# ECE5725, Lab 3, Due 3/21
import RPi.GPIO as GPIO
# Function for setting direction of a servo
# PWM_number is a pointer to a GPIO.PWM object
# Direction is a string equal to one of: - "stop"
# - "clockwise"
# ... | true |
12a29e6ef0d9ed3a73e4eac4d97f2ef4c3d6079a | Python | geostash/geostash | /ogr_check.py | UTF-8 | 254 | 2.828125 | 3 | [] | no_license | from osgeo import ogr
driver_name_list = [ogr.GetDriver(id).GetName() for id in range(ogr.GetDriverCount())]
for driver_name in sorted(driver_name_list):
ds = ogr.GetDriverByName(driver_name)
if ds is not None:
print(driver_name)
| true |
dae05fbd3027e45b5de7eba0a64026048adbf667 | Python | milySW/DataScience | /ML projects/wroclaw_flats/functions/eda/change_df.py | UTF-8 | 5,971 | 2.9375 | 3 | [] | no_license | from bs4 import BeautifulSoup
import requests
import datetime
import numpy as np
def repair_time(data, path):
currentDT = datetime.datetime.now()
today = str(currentDT.day) + "." + str(currentDT.month) + "." + str(currentDT.year)
today_date = datetime.datetime.strptime(today, "%d.%m.%Y").date()
for i... | true |
f6fcd629f260e216f134ff331f52362151059c7b | Python | xpeditionist/Python | /12_2.py | UTF-8 | 590 | 2.96875 | 3 | [] | no_license | import mysql.connector as ms
try:
id = int(input("Enter Id: "))
name=input("Enter Name: ")
price=int(input("Enter price: "))
sql="insert into products values(%d,'%s','%s')"
con = ms.connect(
host="localhost",
user="root",
passwd="1234",
database="mydb")
cursor=con.cursor()
cursor.execu... | true |
f68d9c1a94219cc628a1e25ab09d531f8e9fa8a7 | Python | CarterJMcKenzie/AerospaceStructures | /SolidMotors.py | UTF-8 | 5,263 | 2.625 | 3 | [] | no_license | import numpy as np
import matplotlib.pyplot as plt
import configparser
import FMM
class Propellant:
def __init__(self, propellant_name):
config = configparser.ConfigParser()
config.read('PropellantCatalog.ini')
self.density = float(config[propellant_name]['density'])
self.a = floa... | true |
a62a60224f3cefc4dabad3ec79fb407c55332675 | Python | Chris-Behan/TweetQueueBackend | /tests/test_user.py | UTF-8 | 2,229 | 2.6875 | 3 | [] | no_license | from .context import tweetqueue
from datetime import datetime, timedelta
import pytest
from tweetqueue import user
from replit import db
user_data = {
'access_token_key': 'test_access_token',
'access_token_secret': 'test secret',
'id': '3213213123',
'name': 'Chris Behan',
'twe... | true |
dea8d899077372c7ec9a3d0fbbe6bf056eee4e9d | Python | GabrielDiDomenico/EulerProblems | /problem48/problem48.py | UTF-8 | 134 | 2.9375 | 3 | [] | no_license | def solution():
i=1
result=0
while(i<1001):
result+=pow(i,i)
i+=1
return result
print solution() | true |
32f144f010db4f772110f69c06930d1bc78795d0 | Python | wangxiaohui2015/python_basics | /basic_04/def_usage.py | UTF-8 | 158 | 3.515625 | 4 | [] | no_license | def cal_num(num):
if num <= 0:
return 0
result = 0
for i in range(num):
result += (i + 1)
return result
print(cal_num(100))
| true |
f0dbc91a306b8f175e30ffc40a616afcd57d372e | Python | anaturrillo/intro-python | /clase_02/repaso_funciones/04.py | UTF-8 | 127 | 2.96875 | 3 | [] | no_license | def calcular():
a = 7
def calculo(b):
print(a + b)
return calculo
miCalculo = calcular()
miCalculo(5)
| true |
eceeaea7872ae823bf75ad9334f4cadc3923e395 | Python | Impavidity/relogic | /relogic/logickit/scripts/convert_tacred_dataset.py | UTF-8 | 4,431 | 2.9375 | 3 | [
"MIT"
] | permissive | import argparse
import os
import json
from collections import defaultdict
def convert_into_group(input_folder, output_folder):
if not os.path.exists(output_folder):
os.makedirs(output_folder)
for split in ["train", "dev", "test"]:
with open(os.path.join(input_folder, "{}.json".format(split))) as fin:
... | true |
090912d5e9711f9b6cfc08c6aafc0603874175c6 | Python | pedroblandim/TrabRedes2 | /embelezador_ethernet.py | UTF-8 | 3,777 | 2.8125 | 3 | [] | no_license | from camada_enlace import Ethernet
from camada_rede import IP
from camada_transporte import Transporte
#Classe que representa a transformação dos dados em linhas legíveis no teminal
class Filtro:
def __init__(self, quadro_ethernet):
self.quadro = quadro_ethernet
self.datagrama_IP = IP.Datagrama(bytes_brutos=self.... | true |
931305c920a56dc609993269e0a749a801f2f839 | Python | alvas-education-foundation/K.Muthu-courses | /21 May 2020/pandas-1.py | UTF-8 | 186 | 3.25 | 3 | [] | no_license | """Pandas program to get the DataFrame ( property_data.csv file)."""
import pandas as pd
# Reading a csv file
data=pd.read_csv('property_data.csv')
print("The DataFrame : ")
print(data) | true |
eb4a86c472b612345cded62438fcca8144385f73 | Python | osnaldy/Python-StartingOut | /chapter9/Date_Printer.py | UTF-8 | 785 | 3.46875 | 3 | [] | no_license | def main():
date = raw_input("Enter the a date in the following format 'mm/dd/yyy': ")
new_date = date.split('/')
print verify_month(new_date) + new_date[1] + ', ' + new_date[2]
def verify_month(rr):
if rr[0] == '01':
return 'January '
if rr[0] == '02':
return 'February '
if rr[... | true |
c3fc7f5497451b77a52362246d749d1ffd3decf4 | Python | kuntzer/sclas | /utils.py | UTF-8 | 5,565 | 3.046875 | 3 | [] | no_license | """
Here are a few utils
"""
import os
import cPickle as pickle
import astropy.io.fits
import gzip
import numpy as np
import matplotlib.colors as colors
import logging
logger = logging.getLogger(__name__)
def writepickle(obj, filepath, protocol = -1):
"""
I write your python object obj into a pickle file at filepa... | true |
1f1cc5409f475a33f5cc3b27ae3016b4d54ed797 | Python | NazaninBayati/SMBFL | /muen/muen.py | UTF-8 | 1,311 | 3.140625 | 3 | [
"MIT"
] | permissive |
# Program to extract number
# of rows using Python
import xlrd
import math
# Give the location of the file
loc = (r'F:\Document\article\journal\results\cal\scores.xlsx')
wb = xlrd.open_workbook(loc)
sheet = wb.sheet_by_index(0)
print(sheet.cell_value(1, 0))
total = sheet.cell_value(1,2)
print(total)
... | true |
827714a703fd473ff337afb9a515120c4dfae594 | Python | lvolkmann/couch-to-coder-python-exercises | /Boolean Expressions/evaluate_boolean_expressions.py | UTF-8 | 377 | 3.46875 | 3 | [
"MIT"
] | permissive | """
Predict the output of each of the boolean expressions below
"""
"Dog" and (5 > 2)
# True
(6 > 2) or ((582 % 17) != 9)
# True
"DOG" == "DOG" and 'cat'
# True
(5 + 2 * 3) == ((5+2) * 3)
# False
not(True or False)
# False
(21 % 2) == (97 % 2)
# True
bool((25 / 5) - 5)
# False
(((2 ** 19) % 2) > 0)
# False
(((18 * 23)... | true |
d37f6b607eb0c6ed56ce78867512e5c76090258b | Python | lawrencetheabhorrence/Data-Analysis-2020 | /hy-data-analysis-with-python-2020/part04-e04_municipalities_of_finland/src/municipalities_of_finland.py | UTF-8 | 584 | 3.125 | 3 | [] | no_license | #!/usr/bin/env python3
import pandas as pd
def municipalities_of_finland():
df = pd.read_csv('src/municipal.tsv', sep='\t')
print(df)
df.index = df["Region 2018"]
df=df[["Population", "Population change from the previous year, %", "Share of Swedish-speakers of the population, %", "Share of foreign cit... | true |
f911a953055afecb1b1bd6b65d2e16af5b0e03e6 | Python | Allentome/python_pacong | /test.py | UTF-8 | 348 | 3 | 3 | [] | no_license | #爬取搜狗首页的页面数据
import requests
if __name__ == "__main__":
#指定url
url = 'https://www.bilibili.com/'
requests = requests.get(url=url)
page_text = requests.text
print(page_text)
# with open('./bilibili.html','w',encoding='utf-8') as fp:
# fp.write(page_text)
print('爬取数据结束')
| true |
4caa50a10c7640090f0279293138221e613264cf | Python | jbae11/raven | /doc/workshop/reducedOrderModeling/inputs/workshop_model.py | UTF-8 | 326 | 2.796875 | 3 | [
"LicenseRef-scancode-warranty-disclaimer",
"Apache-2.0",
"BSD-2-Clause",
"BSD-3-Clause"
] | permissive | import math
def run(self,Input):
a = 1.0
b = 2.0
c = 3.0
l = -1.0
self.y1 = self.x1
self.y2 = self.x1
self.y3 = a*self.x1 + b*self.x2 - c*self.x3
self.y4 = self.x1*self.x1 + self.x1*self.x2*self.x3
self.y5 = math.exp(l*self.x1)
if self.y4 < 5.0:
self.failure = 0.0
else:
self.failure ... | true |
24832f7ad8fdd99c3a80bddadfc4274e3fd69e10 | Python | natsala13/locker_server | /app/forms.py | UTF-8 | 1,262 | 2.59375 | 3 | [] | no_license | from app.models import User
from flask_wtf import FlaskForm
from wtforms import StringField, PasswordField, BooleanField, SubmitField
from wtforms.validators import DataRequired, Email, EqualTo, ValidationError
class LoginForm(FlaskForm):
username = StringField('Username', validators=[DataRequired()])
passwo... | true |
6de51655a5845e7090c67726fe16a32503611c20 | Python | Lucakurotaki/ifpi-ads-algoritmos2020 | /Iteração WHILE/Fabio 03/Fabio 03 Parte 01/Fabio 03 Parte 01 Q01-16/f3_q16_fibonacci_n.py | UTF-8 | 430 | 4.0625 | 4 | [] | no_license | def main():
#Entrada
n = int(input("Digite um número positivo: "))
#Processamento/Saída
if n < 2:
print("Erro. Digite um número maior do que 1.")
else:
n1 = 0
n2 = 1
soma = 0
cont = 1
print(soma)
while cont < n:
... | true |
5e0bd103d5e7338f9775ddc9fe4b1681176fcc41 | Python | krypton08rises/Car-Speed-Estimation-with-Deep-Learning | /detect_road.py | UTF-8 | 2,290 | 3.0625 | 3 | [] | no_license | import cv2
import numpy as np
import matplotlib.pyplot as plt
def draw_lines(img, lines, color=[255, 0, 0], thickness=3):
# If there are no lines to draw, exit.
if lines is None:
return # Make a copy of the original image.
img = np.copy(img) # Create a blank image that matches the original in si... | true |
498cd1f869cd1b38e3d2d7c360e7193767689b52 | Python | the-pawns/test | /crateCsv.py | UTF-8 | 375 | 2.84375 | 3 | [] | no_license | import csv
import random
import datetime
fn ='data.csv'
with open(fn,'w')as fd:
wr=csv.writer(fd)
wr.writerow(['日期','销量'])
startDate=datetime.date(2017,2,21)
for i in range(365):
amount=300+i*5+random.randrange(100)
wr.writerow([str(startDate),amount])
#下一天
starDate=start... | true |
3e4be20291fc3509ee7a54c5c0a20355f48e6bdc | Python | synbiomine/synbiomine-tools | /tools/loadItems.py | UTF-8 | 940 | 2.765625 | 3 | [
"Apache-2.0"
] | permissive | #!/usr/bin/env python
import jargparse
import xmltodict
# THEORETICAL TODO IN ORDER TO UPDATE EXISTING ORGANISM NAMES WHERE A NAME DOES NOT ALREADY EXIST
# load organisms from polen items xml
# replace names in organism tables that match the taxonid
# re-trigger necessary post-processing (probably just search index r... | true |
0378687cedde6622d13d4dedcab639c6e2819c18 | Python | Meghn/Single-Player-MCTS | /Node.py | UTF-8 | 323 | 2.703125 | 3 | [] | no_license | class Node:
def __init__(self, state):
self.state = state
self.wins = 0.0
self.visits = 0.0
self.ressq = 0.0
self.parent = None
self.children = []
self.sputc = 0.0
def AppendChild(self, child):
self.children.append(child)
child.parent = se... | true |
e96767a3d9208cdf8ce5d0498367056fcd6c8dbc | Python | kathdez7/Mision_02 | /cuenta.py | UTF-8 | 369 | 3.640625 | 4 | [] | no_license | # Autor: Katia Hernández Barrera
# Descripcion: Programa nqu calcula el total de la cuenta tomando en cuenta IVA y propina
# Escribe tu programa después de esta línea.
Sub = int (input("inserte el costo de la comida"))
print ("costo de su comida", Sub)
P = (Sub * 0.13)
print ("Propina", P)
I = (Sub * 0.16)
print ... | true |
c6c53d7964eff8b7f17739d1c1b8f3862abb616a | Python | keimlink/python-workshop | /python-workshop/h_functions and_objects/c_nature.py | UTF-8 | 1,458 | 4.15625 | 4 | [] | no_license | """Module nature
Demonstrates how to connect objects.
"""
class Animal(object):
"""An animal"""
def __init__(self, name):
"""Constructor"""
self.name = name
def __repr__(self):
"""Returns string representation."""
return 'Animal: %s' % self.name
class Food(object):
... | true |
eba1be57f55c161058d39880277f603ca6ca73a0 | Python | Curso-de-Python/Clase12 | /ejercicio4.py | UTF-8 | 1,477 | 3.515625 | 4 | [] | no_license | '''
-----------------------------
EJERCICIO N°4
Diagramas de apilamiento
-----------------------------
'''
import matplotlib.pyplot as plt
# ---------------------------
# EJEMPLO 1
meses= [x for x in range(1,13)]
hipoteca= [700, 700, 700,
800, 800, 800,
850, 850, 850,
850, 850, 850]... | true |
c2b823be6c7940ab81ccf6cdb135cf3da2e4ebe1 | Python | BishuPoonia/coding | /Python/tkinters/hexagon.py | UTF-8 | 397 | 4.34375 | 4 | [] | no_license | import turtle
def square():
square = turtle.Turtle()
for i in range(4):
square.forward(50)
square.right(90)
def hexagon():
polygon = turtle.Turtle()
num_sides = 6
side_length = 70
angle = 360.0 / num_sides
for i in range(num_sides):
polygon.forwa... | true |
dca2340c6652fcda24e162e0b1e493dc1a95997d | Python | Mayur907/android-style-transfer | /adain/utils.py | UTF-8 | 2,069 | 2.78125 | 3 | [
"MIT",
"LicenseRef-scancode-unknown-license-reference"
] | permissive | # -*- coding: utf-8 -*-
import numpy as np
import cv2
def preprocess(image, img_size=(224,224)):
"""
# Args
image : rgb-ordered array
"""
image = np.expand_dims(cv2.resize(image.astype(np.float32), img_size), axis=0)
return image
def get_params(t7_file):
import torch... | true |
b9ce06d8b16616949704dc1943558f3a7db370ca | Python | myyel/pyhton | /alistirmalar/Dört Kenarına Göre Şeklin Tipini Bulma.py | UTF-8 | 620 | 3.421875 | 3 | [] | no_license | k1=input("1. kenar: ")
while not k1.isdigit():
print("lütfen bir sayi giriniz")
k1=input("1. kenar: ")
k2=input("2. kenar: ")
while not k2.isdigit():
print("lütfen bir sayi giriniz")
k2=input("2. kenar: ")
k3=input("3. kenar: ")
while not k3.isdigit():
print("lütfen bir sayi giriniz")
k3=i... | true |
d266f742b2b474d173aa85749eda8af7e4c88b00 | Python | dannylee1020/flask-tutorial | /tests.py | UTF-8 | 3,006 | 2.75 | 3 | [] | no_license | from datetime import datetime, timedelta
import unittest
from app import app, db
from app.models import User, Post
class UserModelCase(unittest.TestCase):
def setUp(self):
app.config['SQLALCHEMY_DATABASE_URI'] = 'sqlite://'
db.create_all()
def tearDown(self):
db.session.remove()
... | true |
7946d28a7397048f58e96c49a6648d898da9dbff | Python | Sarcarean/sarcarean.github.io | /CS260/Chapter 3/Chapter_3.py | UTF-8 | 2,438 | 3.890625 | 4 | [] | no_license | from Stack import Stack
def do_math(op, op1, op2):
if op == "*":
result = op1 * op2
elif op == "/":
result = op1 / op2
elif op == "**":
result = op1 ** op2
elif op == "//":
result = op1 // op2
elif op == "+":
result = op1 + op2
elif op == "-":
res... | true |
5beb4994d79951bbd3e36afe1ec13badb74b2f3e | Python | anujarora93/clothing-detection-dataset | /crop_box_example.py | UTF-8 | 1,000 | 2.53125 | 3 | [
"MIT"
] | permissive | # -*- coding: utf-8 -*-
#########################################################
#
# Alejandro German
#
# https://github.com/seralexger/clothing-detection-dataset
#
#########################################################
from PIL import Image
import json
import glob
import random
import matplotlib.pyplot as plt... | true |
3a0ea52042d06cec4f1a23dcc8583e4bb8d8bafe | Python | ManonSabot/Competing_Optimal_Adjustments | /src/TractLSM/SPAC/soil.py | UTF-8 | 15,164 | 2.828125 | 3 | [
"MIT"
] | permissive | # -*- coding: utf-8 -*-
"""
Simple tipping bucket soil water balance model, a proxy for soil
hydrology, with soil layer depths adapted for EucFACE.
This file is part of the TractLSM model.
Copyright (c) 2022 Manon E. B. Sabot
Please refer to the terms of the MIT License, which you should have
received along with th... | true |
bcbcfcc38ee915ae23f3e018ff596b22b4e78c56 | Python | linka/pcap2har | /pcap2har/pcapharconverter.py | UTF-8 | 1,552 | 2.703125 | 3 | [
"BSD-2-Clause"
] | permissive | import json
from har import JsonReprEncoder
from httpsession import HttpSession
from packetdispatcher import PacketDispatcher
from pcap import PcapParser
from pcaputil import ModifiedReader
class PcapHarConverter(object):
""" Representation of PCAP file in the HAR format """
def __init__(self, fileobj, drop_... | true |
ebd35aad5400a8843eaa9bab547e7b3d1c48aad5 | Python | SebastianElvis/ElvisProjs | /python/stock_prediction/module_prediction/nlp.py | UTF-8 | 4,669 | 2.921875 | 3 | [] | no_license | # -*- coding: utf-8 -*-
import pandas as pd
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.linear_model import LogisticRegression
import logging
import re
import jieba
logger = logging.getLogger("django")
zh_pattern = re.compile(u'[\u4e00-\u9fa5]+')
def is_contain_zh(string):
string = ... | true |
745236d1ecdaf7a5cd75382cde19adfcce719f06 | Python | ReedJessen/AonDemo | /client.py | UTF-8 | 3,885 | 2.734375 | 3 | [] | no_license | import requests
import json
import pandas as pd
class IPStreetClient:
def __init__(self):
self.api_key = 'TGk3p1B0olaHdkGSbJSyDaMpDBPHiya688V8HOCT'
self.page_size = 250
def get_semantic_search(self, raw_text, filter={}):
"""accepts a raw text field and optional query filter dict, retu... | true |
fcd508f79e51a9cf1fef52860cf5e4bcebb7cbbf | Python | kiseonjeong/convolutional-neural-network-with-numpy | /function/gate.py | UTF-8 | 868 | 3.09375 | 3 | [
"MIT"
] | permissive | import numpy as np
# Weight and bias for test
W = np.array([0.0, 0.0])
b = 0.0
def gate_and(x1, x2):
# Calculate logical AND gate
x = np.array([x1, x2])
w = np.array([0.5, 0.5])
b = -0.7
tmp = np.sum(W * x) + b
if tmp <= 0:
return 0
else:
return 1
def gate_nand(x1, x2):
... | true |
468d682b464bf2df3847b427c2fec42103f7f6e3 | Python | vaibhavpalve1234/hackerrank | /today.py | UTF-8 | 502 | 2.828125 | 3 | [] | no_license | # def sol1(n,str):
# if len(str)==2*n:
# return str
# sol1(n,str+"(")
# sol1(n,str+")")
# def sol(op,cp,n):
# if op+cp==2*n:
# a=(sol1(op+cp,""))
# print(a)
# return 1
# p1=sol(op+1,cp,n)
# p2=sol(op,cp+1,n)
# return p1+p2
# sol(0,1,2)
def sol(str,res,isstart):
if len(str)=... | true |
05a9fc245d8c1a91bd4bda6be918f9e74863c0e3 | Python | silky/bell-ppls | /env/lib/python2.7/site-packages/observations/r/doctor_aus.py | UTF-8 | 3,252 | 2.859375 | 3 | [] | no_license | # -*- coding: utf-8 -*-
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import csv
import numpy as np
import os
import sys
from observations.util import maybe_download_and_extract
def doctor_aus(path):
"""Doctor Visits in Australia
a cross-section fr... | true |
9158025d8bfc1d1c1682f4812863ca3cdd034a51 | Python | edvinture/python | /ИНТЕРЕСНЫЕ ЗАДАЧИ ДЛЯ ЦИКЛОВ edvin sergei.py | UTF-8 | 983 | 3.421875 | 3 | [] | no_license | # Edvin Kääpa, Sergei Smirnov sptvr19
#1
x = 1000
while True:
print(x)
x +=3
if x == 1018:
break
#2
x = 1
while True:
print(x)
x +=2
if x == 113:
break
#3
x = 90
while True:
print(x)
x -=5
if x == -5:
break
#4
x =... | true |
3cc9c756482abf27ff48fad8df7bea91646c7011 | Python | ZanchiTheo/Localisation-fingerprint-RSSI | /localisation.py | UTF-8 | 3,304 | 3.5 | 4 | [] | no_license | #import des librairies
import serial
import string
import numpy as np
import json
import operator
from operator import itemgetter
import re
# Déclaration du pattern pour trier les AP par nom
pattern = re.compile("AP[0-9]")
# Interaction avec l'utilisateur pour savoir sur quel port écouter
x = "n"
# On ... | true |
d0da2bb68e302dfbf2cbcfffe1b9cd4826d90365 | Python | allenye0119/Amaze | /examples/basic_usage.py | UTF-8 | 637 | 2.8125 | 3 | [
"BSD-3-Clause"
] | permissive | """
This module describes the most basic usage of Amaze: you define a prediction
algorithm, (down)load a dataset and run a cross-validation procedure.
"""
from __future__ import (absolute_import, division, print_function,
unicode_literals)
from amaze import SVD
from amaze import Dataset
from a... | true |
8f8f1834db5b7ce19f08648cefb450a6cd4d1694 | Python | fuyongde/python | /basic/niki.py | UTF-8 | 59 | 3.171875 | 3 | [
"Apache-2.0"
] | permissive | def niki_abs(x, y):
return x + y
print(niki_abs(1, 3)) | true |
93b66199f0d052dc55e48f76db9de2aef1e9b191 | Python | jbell1991/Intro-Python-II | /src/player.py | UTF-8 | 607 | 4.15625 | 4 | [] | no_license | # Write a class to hold player information, e.g. what room they are in
# currently.
class Player:
def __init__(self, name, current_room, inventory=None):
self.name = name
self.current_room = current_room
self.inventory = []
def move(self, direction):
if self.current_room.move[di... | true |
2cd8b3fb6681ba0767ca2e871d90eb41057b4a50 | Python | domzae/TaxiFareWebsite | /app.py | UTF-8 | 2,631 | 2.921875 | 3 | [] | no_license | import streamlit as st
import pandas as pd
import datetime
import requests
import pydeck as pdk
'''
# Taxi Fare Calculator
'''
# map starting coords
pickup_lon = -73.9798156
pickup_lat = 40.7614327
dropoff_lon = -73.8803331
dropoff_lat = 40.6513111
date = st.sidebar.date_input("Pickup Date", datetime.date(2021,5,28)... | true |
e3237b6d448189cf5cc706321f5f2c3e081ff808 | Python | purpl3F0x/NeuroKit | /neurokit2/signal/signal_rate.py | UTF-8 | 2,816 | 3.171875 | 3 | [
"MIT"
] | permissive | # -*- coding: utf-8 -*-
import numpy as np
import pandas as pd
from .signal_interpolate import signal_interpolate
from .signal_formatpeaks import _signal_formatpeaks_sanitize
def signal_rate(peaks, sampling_rate=1000, desired_length=None):
"""Calculate signal rate from a series of peaks.
Parameters
---... | true |
caff94d40d951cee6183dcdf41326009057dfe63 | Python | sharmar0790/python-samples | /misc/generateDimensionalArray.py | UTF-8 | 212 | 3.296875 | 3 | [] | no_license |
x,y = 3,5
r = list()
for i in range(0,x):
l = list()
for j in range(0,y):
if 0 < j < y and 0 < i < x:
l.append(j*i)
else:
l.append(0)
r.append(l)
print(r)
| true |
ceb9c2f790f868838e69b426f71ad5bfe3f27db5 | Python | lioraodg/WebScraping | /scraping.py | UTF-8 | 1,547 | 2.78125 | 3 | [] | no_license | #!/usr/bin/env python
import urllib2
import re
from bs4 import BeautifulSoup
import time
from joblib import Parallel, delayed
import multiprocessing
#
#Get links
#
start = time.time()
nsubpages = 10 #331 folded pages by eye
num_cores = multiprocessing.cpu_count()
print "Running on ", num_cores, " CPU cores"
real_l... | true |
a0ca0ddadad36ab786b183200e34a5fccd9a63e6 | Python | kadensungbincho/Online_Lectures | /fastcampus/office_automation_all_in_one/pythonIntermediate/9th/9th-2.py | UTF-8 | 397 | 2.703125 | 3 | [] | no_license | from selenium import webdriver
driver = webdriver.Chrome('../chromedriver')
try:
driver.get('http://news.naver.com')
elem = driver.find_element_by_id('right.ranking_contents')
lis = elem.find_elements_by_tag_name('li')
for li in lis:
a_tag = li.find_element_by_tag_name('a')
prin... | true |
7a2438afc385e5da51300695c716c2cf83e52291 | Python | WPettersson/kidney_utils | /tests/test_graph.py | UTF-8 | 2,194 | 3.390625 | 3 | [] | no_license | """Test cases for the Graph class."""
from kidney_utils.graph import Graph
from nose.tools import eq_
def test_treewidth_complete_graphs():
"""Test treewidth algorithm, which is approximate and not exact.
"""
def test_kn(size):
"""Test on complete graphs."""
graph = Graph()
for o... | true |
b75ce71cb85702c6204e4843492bf2f9b6187f35 | Python | TheChickenBoy/kattis | /python3/10kindaofpeople.py | UTF-8 | 1,341 | 2.796875 | 3 | [] | no_license | import sys
import heapq
def floodfill(x, y):
unvisited = []
heapq.heappush(unvisited, (x, y))
while unvisited:
pos = heapq.heappop(unvisited)
x, y = pos[0], pos[1]
if m[x][y] == sp:
m[x][y] = other
if x > 0 and m[x-1][y] == sp:
hea... | true |
463aa0749e5336097975433c7fea7a3b5d965430 | Python | DanielShangHai/python | /DanielShanghai/0000/AddNumToPic.py | UTF-8 | 2,437 | 2.8125 | 3 | [] | no_license | from PIL import Image, ImageDraw, ImageFont
__author__ = 'DanielSong'
def add_num(img,number):
#生成pad和数字
if number >= 10000:
strNumber = '...'
else:
strNumber = '%d' %(number)
draw = ImageDraw.Draw(img)
#myfont = ImageFont.truetype('C:/windows/fonts/Arial.ttf', size=50)
... | true |
09438a166e4064d7e38a1570674ab0b7121441c6 | Python | ailomani/manikandan | /mani.42.py | UTF-8 | 70 | 2.953125 | 3 | [] | no_license | m1,i=input().split()
if(len(m1)>len(i)):
print(m1)
else:
print(i)
| true |
1188f8f134d4b4c76dc6e3fafbf5e22b5854355c | Python | tanayrastogi/AI_Project_Path_Planning | /RRT/model.py | UTF-8 | 4,824 | 3 | 3 | [] | no_license | import numpy as np
from math import *
import time
from node import Node,State
from kineticcar import KinCarmodel
from dynpoint import DynPointmodel
from diffdrive import DifferentialDrivemodel
from dyncar import DynCarmodel
from frictioncar import FrictionCarmodel
class Model:
def __init__(self,data,typ... | true |
192d30b55c072a096697f7dbb110e8a68fc4d0c7 | Python | YuraDmitrievtsev/Homework-2 | /4.py | UTF-8 | 343 | 3.25 | 3 | [] | no_license | import turtle
import numpy as np
v0=float(input("V0="))
alpha=float(input("alpha="))
k=float(input("k="))
n=float(input("n="))
dt=0.01
vy=v0*np.sin(alpha/180*np.pi)
vx=v0*np.cos(alpha/180*np.pi)
x=0
y=0
for i in range(5000):
x+=vx*dt
y+=vy*dt
vy-=(10*dt+n*vy)
vx-=n*vx
if(y<0.01):
vy=-k*vy... | true |
08ee7545b923268535ea7f1f830db9b90a60becb | Python | Deep-Space-Industries/localization | /kalman.py | UTF-8 | 589 | 2.59375 | 3 | [] | no_license | import numpy as np
I = np.identity(3)
A_t = np.identity(3)
def z(C_t, x_t, delta_t):
return C_t*x_t + delta_t
def kalman_filter(previous_mu ,previous_sigma,current_u ,z_t, A_t, B_t, R_t, C_t, Q_t):
#Prediction
next_mu_bar= A_t*previous_mu + B_t*current_u
next_sigma_bar= A_t*previous_sigm... | true |
0f46523e8e0a56f313164a81b25fccde17cee4e9 | Python | luxuguang-leo/everyday_leetcode | /00_leetcode/273.integer-to-english-words.py | UTF-8 | 1,460 | 3.625 | 4 | [] | no_license | #
# @lc app=leetcode id=273 lang=python
#
# [273] Integer to English Words
#
# @lc code=start
class Solution(object):
def numberToWords(self, num):
"""
:type num: int
:rtype: str
"""
#三个一组来处理，最多处理四组，每组需要判断后两位是否小于20，因为20以内的数需要查表
#大于20小于99就取出十位和个位来组成就行
lessThan... | true |
f1a699c98289d0678015c5253f7fca180bcd3d87 | Python | mlflow/mlflow | /mlflow/entities/run_data.py | UTF-8 | 3,089 | 2.71875 | 3 | [
"Apache-2.0"
] | permissive | from mlflow.entities._mlflow_object import _MLflowObject
from mlflow.entities.metric import Metric
from mlflow.entities.param import Param
from mlflow.entities.run_tag import RunTag
from mlflow.protos.service_pb2 import Param as ProtoParam
from mlflow.protos.service_pb2 import RunData as ProtoRunData
from mlflow.protos... | true |
b8b44a7144cf08325d7a4caf1c205bc2e4bc2f4c | Python | randomkew/backj | /11047.py | UTF-8 | 132 | 2.96875 | 3 | [] | no_license | x=int(input())
y=list(map(int,input().split()))
y = sorted(y)
sum=0
for i in range(x):
sum+=y[i]*(x-i)
print(sum)
print(sum) | true |
5f4733e188f6e22b84daa1f25be8e46ddaf2b9ce | Python | nithyaraman/pythontraining | /chapter2/src/vowels_and_consonant.py | UTF-8 | 377 | 3.40625 | 3 | [] | no_license | """write the program to print vowels
and consonant letters from gulinux'"""
vowel = ['a', 'e', 'i', 'o', 'u']
vowel_list = []
consonant_list = []
for var in 'gnulinux':
if var in vowel:
vowel_list.append(var)
else:
consonant_list.append(var)
print "cosonant letters in gnuliunx\n", consona... | true |
60dfdee2f0d9691636e238d04851455a655c2862 | Python | 123-IsraZaleta/HuntTI | /TestHuntIt-LenguajeSecundario/problem-2.py | UTF-8 | 2,320 | 3.3125 | 3 | [] | no_license | def main():
j=0
k=0
lineList = []
max_1 = 0
max_2 = 0
player1_score = 0
player2_score = 0
file = './data/dataProblem2.txt' #-------------------PLEASE TYPE THE DOCUMENT PATH--------------------------------
with open(file, 'r+') as file_obj:
for lines in file_obj:
l... | true |
71da2b64fd75511a0961b805988e4f99eda94a46 | Python | L200180020/algostruk | /MODUL_4/T4.py | UTF-8 | 1,018 | 3.0625 | 3 | [] | no_license | class Mahasiswa(object):
def __init__(self, nama, nim, kota, uangsaku):
self.nama = nama
self.nim = nim
self.kotaTinggal = kota
self.uangSaku = uangsaku
l0 = Mahasiswa("luqman", 107, "pojok", 289000)
l1 = Mahasiswa("faris", 113, "serengan", 230000)
l2 = Mahasiswa("ridwan", ... | true |
9632a9a81a7e637562a28376125e8939520ea3a0 | Python | glacierhole/PythonTools | /Kmeans实现.py | UTF-8 | 2,072 | 3.421875 | 3 | [] | no_license | #Kmeans实现
#设定数据集
N=9
classlist = [[10, 2, 1],[1, 3, 1],[1, 2, 2],[2, 5, 2],[2, 5, 3],[2, 6, 3],[3, 2, 4],[3, 3, 4],[3, 3, 5]]
#设定分类值k
k = 3
#预设k个聚类中心
C1 = [1,1,1]
C2 = [2,3,2]
C3 = [5,5,5]
#大循环M次，停止迭代
M=13
for j in range(M):
#根据距离归类
class1 = []
class2 = []
class3 = []
for i in r... | true |
20347c869253c4ccca224264b39b639cb5903bce | Python | fhfmendes04/Desenvolvedor_Python_Junior | /Collections/listas/lists_comprehension.py | UTF-8 | 229 | 3.359375 | 3 | [] | no_license | lista_simples_inteiro = [1, 2, 3, 3, 4, 5]
nova_lista = []
for i in lista_simples_inteiro:
nova_lista.append(i * i)
print(nova_lista)
nova_lista_elegante = [i * i for i in lista_simples_inteiro]
print(nova_lista_elegante) | true |
1046cf80e8b0c5df330cb7be040ee72a81fc65d8 | Python | Gympedies/Collective-intelligence | /gp.py | UTF-8 | 741 | 2.59375 | 3 | [] | no_license | from random import randint, random,choice
from copy import deepcopy
from math import log
class fwrapper:
def __init__(self,function,childcount,name):
self.function=function
self.childcount=childcount
self.name=name
class node:
def __init__(self,fw,children):
self.function=fw.func... | true |
2f3fbfbe01e58b53cc5a9bf327b51c7efe79da86 | Python | LeonardoARGR/Desafios-Python-Curso-em-Video | /Mundo-1/desafio-030.py | UTF-8 | 292 | 3.421875 | 3 | [
"MIT"
] | permissive | cores = {'limpo': '\033[m',
'vermelho': '\033[1;31m',
'verde': '\033[1;32m'}
n = int(input('Digite um número: '))
if n % 2 == 0:
print(f'Este número é {cores["verde"]}par{cores["limpo"]}')
else:
print(f'Este número é {cores["vermelho"]}impar{cores["limpo"]}')
| true |
3f2328382c1c9b2e01660698f085f015462ea653 | Python | nkaeming/ILPLabWatch | /Services/PortService.py | UTF-8 | 10,346 | 2.984375 | 3 | [] | no_license | import importlib, uuid, pkgutil
import IOHelper.config as configIO
from Models.Observable import Observable
from Models.Observer import Observer
from Models.PersistantObject import PersistantObject
from Ports.AbstractPort import AbstractPort
from Services.TriggerService import TriggerService
class PortService(Observa... | true |
d2f6a292afd27ab34150cad098a7d2528e45db56 | Python | AzharAmin/Text-Summarizer | /TextSummarizer.py | UTF-8 | 3,574 | 3.296875 | 3 | [] | no_license | import string
from nltk.corpus import stopwords
import numpy as np
import networkx as nx
from nltk.cluster import cosine_distance
name = input('Enter .txt file: ')
handle = open(name, 'r')
lines = handle.readlines()
handle = open(name, 'w')
mystr = ''.join([line.strip() for line in lines])+"\n"
handle.w... | true |
e33a807f30091deda7bb47c46fc3bf2031119d1f | Python | sserdoubleh/Research | /ST_DM/GenRegion/src/generate/gen/regionalg.py | UTF-8 | 22,135 | 2.625 | 3 | [
"Apache-2.0"
] | permissive | # -*- coding: utf-8 -*-
########################################################################
#
# Copyright (c) 2019 Baidu.com, Inc. All Rights Reserved
#
########################################################################
import sys
import threading
from region import geometry as mygeo
from region import... | true |
c92a86cebc2a7eb60db4f4f33186c2690313bac2 | Python | hmortonsmith/hmwk2 | /weekend-homework/run_sql_improved_with_classes.py | UTF-8 | 1,599 | 3 | 3 | [] | no_license | import pyodbc
from people_class import *
class ConnSql:
# when we initialise, make the connection
def __init__(self, server='localhost,1433', database='Airport', username='SA', password='Passw0rd2018'):
# Our variables to create a connection
self.server = server
self.database = databas... | true |
bd2aac1db6dbd030b70eb6938fb9f735d9e1f356 | Python | Rayveni/web | /webtrade/attributes/sec_history_manager.py | UTF-8 | 481 | 2.578125 | 3 | [] | no_license | class sec_history_manager:
__slots__ ='ticker','sec_name','currency','start_date','end_date','actual_for','description'
def __init__(self,ticker:str,sec_name:str,currency:str,start_date:str,end_date:str,actual_for:str,description:str):
self.ticker=ticker
self.start_date=start_date
self.s... | true |
21abcf2bea73cbacead1a4833684bd44bc22aad2 | Python | backtothefuture3030/algorithms | /여러 개의 4.py | UTF-8 | 139 | 3.546875 | 4 | [] | no_license | import math
#1 4의 4승 + 4 / 4
print(int(math.pow(4,4) + 4/4))
#2 4의 4승 * 4의 4승 - 4
print(int(math.pow(4,4) * math.pow(4,4) - 4)) | true |
cabc763b3e2c21cea6446ee3a2d308e121d2d776 | Python | luizgallas/uri_iniciante | /1984.py | UTF-8 | 39 | 2.921875 | 3 | [
"Apache-2.0"
] | permissive | seq = input().strip()
print(seq[::-1])
| true |
bd966e38c10029cbf8d7668a2fe72c96ed86b114 | Python | f2015712/Machine-Learning | /Supervised_ML/Classification/knn2.py | UTF-8 | 2,476 | 3.53125 | 4 | [] | no_license | #KNN can be used for non-linear data
import numpy as np
from math import sqrt
import matplotlib.pyplot as plt
import warnings
from matplotlib import style
from collections import Counter
import pandas as pd
import random
style.use('fivethirtyeight')
dataset={'k':[[1,2],[2,3],[3,1]],'r':[[6,5],[7,7],[8,6]]}
new_... | true |
cd4eeb95878de43a524bbf82a64417fae8eddb49 | Python | HarisHad2/exercises | /divisble_by_7.py | UTF-8 | 173 | 3.3125 | 3 | [] | no_license | def divisble_by_7(yyy):
for i in range(1, 1001):
if i % 7 == 0 and i % 2 != 0:
yyy.append(i)
return yyy
yyy = []
print(divisble_by_7(yyy)) | true |
5942dd56ac27496dbf335cf0cfe1c3a2d11d5548 | Python | Akpandita/Video-Captioning-with-LSTM | /frames.py | UTF-8 | 530 | 2.578125 | 3 | [] | no_license | import cv2
num=7010
while(num<=7509):
vidcap = cv2.VideoCapture('./videos/video'+str(num)+'.mp4')
success,image = vidcap.read()
count = 0
success = True
while success and count<=270:
if(count==0 or count==54 or count==108 or count==162 or count==216 or count==270):
cv2.i... | true |
9d422fbdf1e1692cf06cf9faac260196a243f46e | Python | dahan-1996/Autoencoder_test | /AWGN_Autoencoder_versions/Transmitters/test_qpsk.py | UTF-8 | 3,082 | 3.09375 | 3 | [] | no_license | import unittest
from .qpsk import QPSKTransmitter
import numpy as np
class TestTransmitByte(unittest.TestCase):
transmitter = QPSKTransmitter()
def test_transmission(self):
# Transmit an integer value
input_int = np.uint8(100)
output_int = self.transmitter.transmit_byte(input_int)
# Make sure only uint8 in... | true |
0e9765e1e8c3241a6ec6b25d3fbe3aeed6797bc0 | Python | DangerousTod/TanksALot | /flyer.py | UTF-8 | 3,917 | 2.796875 | 3 | [] | no_license | import pygame, sys, os, math, numpy as np
class Cam:
def __init__(self,pos=(0,0,0),center=(0,0,0),x=0,y=0,z=0):
self.pos = list(pos)
def events(self,event):
pass
def update(self,dt,key,rot):
s = dt*10
r = rot*36
if key[pygame.K_s] and s != 1: self.pos[2]-=s #forward
else: self.pos[2]... | true |
a93a9d3352e904618803d57ce6bf0b0645054fd6 | Python | mccoyp/azure-sdk-tools | /scripts/python/verify_agent_os.py | UTF-8 | 984 | 2.515625 | 3 | [
"LicenseRef-scancode-generic-cla",
"MIT"
] | permissive | # Script verifies the operating system for the platform on which it is being run
# Used in build pipelines to verify the build agent os
# Variable: The friendly name or image name of the os to verfy against
from __future__ import print_function
import sys
import platform
os_parameter = sys.argv[1].lower()
if os_parame... | true |