index int64 0 1,000k | blob_id stringlengths 40 40 | code stringlengths 7 10.4M |
|---|---|---|
13,400 | 66b05fcc12f1a35173c8529051a0fbffed291a4e | from operator import itemgetter #Needed funcion to sort all scheduled trips
input_file = open('c_no_hurry.in') #File to open
first_line = input_file.readline()
#Gets the first information from the file
n_rows, n_columns, n_vehicles, n_rides, bonus, max_steps = tuple(map(int, first_line.split(' ')))
def greate... |
13,401 | 069ae919ec3ace8b76fc919b8afd465e5762307b | from django.db import models
from datetime import datetime, date
class Article(models.Model):
title = models.CharField(max_length=500)
date = models.DateField(auto_now_add=False, auto_now=False)
description = models.CharField(max_length=2000)
def __str__(self):
return self.title
|
13,402 | ec0336135f8464f0e17b6eec00293cebf55a9fb9 | from django.urls import path
from .views import ProductListView, ProductDetailView
urlpatterns = [
path('', ProductListView.as_view(), name='products-list'),
path('details/<str:slug>', ProductDetailView.as_view(), name='products-details'),
]
|
13,403 | d30600e5e49ef563d721b34e9164a512d7061c03 | class Dependence:
def __init__(self, x, p):
self.x = x # integer
self.p = set(p) # set
def __repr__(self):
s = str(x) + " <-";
for item in p:
s += " " + str(item)
return s
def __eq__(self, obj):
if (obj is None):
return False
... |
13,404 | 7f3d11976e29f89ab765e720e01a4396fbe3dd15 | import datetime
import os
import pickle
import h2o.automl
import pandas as pd
import xgboost as xg
from sklearn.metrics import mean_absolute_error, mean_squared_error, r2_score
from sklearn.model_selection import train_test_split
from sklearn.pipeline import Pipeline
from sklearn.preprocessing import StandardScaler, P... |
13,405 | 0fa8c506baf3973f362efe7a888323475d10e270 | from django.urls import re_path
from . import views
urlpatterns = [
re_path(r'^reg$',views.reg_view),
re_path(r'^login',views.login_view),
re_path(r'^logout',views.logout_view),
re_path(r'^register$',views.register_view),
] |
13,406 | f94b461d8932761cf0f50be8a13b47f9c9286055 | {
'name': 'Fleet asset',
'version': '8.0.1.0.0',
'license': 'AGPL-3',
'category': 'Generic Modules/Fleet Asset',
'author': 'Andrean Wijaya',
'website': '-',
'depends': ['account','fleet','account_asset'],
'data': [
'views/fleet_asset_view.xml',
],
'installable'... |
13,407 | 2ab49eee147eb66a4d68953d6ae1dbbb15b67cc3 | # -*- coding: utf-8 -*-
# Define here the models for your scraped items
#
# See documentation in:
# http://doc.scrapy.org/en/latest/topics/items.html
import scrapy
from scrapy.item import Item, Field
class MusicItem(scrapy.Item):
# define the fields for your item here like:
# name = scrapy.Field()
song = F... |
13,408 | 44bee7009a10419851132b42fcad2401b5f22a8b | num=input()
rev=num[::-1]
if num==rev:
print('yes')
else:
print('no')
|
13,409 | dcd321144436a1da130f16c05ac41b2c49c16cb5 | items=list(range(11,21))
for index, item in enumerate(items):
print(index, item)
|
13,410 | bac42a3e34f14106548df2dce672ca976eadd41e | from __future__ import annotations
import requests
import time
from typing import List, TypedDict, Generator
from dataclasses import dataclass
@dataclass
class RedditComment:
"""
A basic reddit comment.
This class excludes much of the data that comes with
a reddit comment in favor of simplicity.
... |
13,411 | 3a5f832d44c6a55004dc94ec1b25a485ceb5d8eb | # -*- coding: utf-8 -*-
# Resource object code
#
# Created: ๅจๆฅ 11ๆ 29 16:49:48 2015
# by: The Resource Compiler for PyQt (Qt v4.8.6)
#
# WARNING! All changes made in this file will be lost!
from PyQt4 import QtCore
qt_resource_data = "\
\x00\x00\x14\x1c\
\x89\
\x50\x4e\x47\x0d\x0a\x1a\x0a\x00\x00\x00\x0d\x49\x4... |
13,412 | a398975505e8363b3fcf339a2a23af33ec555463 | import numpy as np
from SenselUse import sensel
import threading
import matplotlib.pyplot as plt
from matplotlib.colors import ListedColormap
import os
enter_pressed = False
plt.figure(figsize=(15, 7))
COUNT = 1
# my_cmap = plt.cm.RdBu(np.arange(plt.cm.RdBu.N))
# my_cmap[:,0:3] *= 0.5
# my_cmap = ListedColormap(my... |
13,413 | e7591b2c55992ba48026d012d75a9febac41ac39 | #DEPENDENCIES
#Allow Path Access to the Prelude's Directory
import sys
if not(".." in sys.path):
sys.path.append("..")
#Utilities Dependencies
from Py_Preludes import *
#Typing Dependencies
from typing import List
#Enum Dependencies
from enum import Enum,auto,unique
#Context Extension Dependencies
from SimpleT... |
13,414 | be72e722f1cdb71fe1987559eab0826dfac5c8c5 | a=int(input("Enter limit:"))
b=1
c=1
print(b)
print(c)
for i in range(1,a-1):
d=c+b
print(d)
b=c
c=d |
13,415 | ede30aa8afbc9bdbbaa47b3c9729615df1d5e802 | from sys import stdin
def busquedaBinaria(n, item):
primero = 0
ultimo = len(n)-1
while primero<=ultimo:
mid = (primero + ultimo)//2
if n[mid] == item:
return "esta",mid
else:
if item < n[mid]:
ultimo = mid-1
else:
... |
13,416 | 79fab049a6737b93da1d48b9880e8ff6944f0c5f | import matplotlib.pyplot as plt
from matplotlib import cm
import numpy as np
def speed_up(a):
speed_up = a[0]/a
return speed_up
P = np.array([1,4,16,24,36])
P_square = np.array([1,4,16,25,36])
run_time_square = np.array([1143.29, 298.748,93.9222, 84.9656, 46.224])
run_time_vert = np.array([1140.44,300.6... |
13,417 | b331efb2a21f4ea7b57e24c40a7faf8aaea786f6 | #
# a1pr1.py - Assignment 1, Problem 1
#
# Indexing and slicing puzzles
#
# This is an individual-only problem that you must complete on your own.
#
#
# List puzzles
#
pi = [3, 1, 4, 1, 5, 9]
e = [2, 7, 1]
# Example puzzle (puzzle 0):
# Creating the list [2, 5, 9] from pi and e
answer0 = [e[0]] + pi[-2:]
print(an... |
13,418 | e705c35aaa083db2245f815310a9874ddd42f7b8 | from typing import Tuple, Any
from dataset import Dataset
from relevance_engines.criage_engine import CriageEngine
from link_prediction.models.model import Model
from explanation_builders.explanation_builder import NecessaryExplanationBuilder
class CriageNecessaryExplanationBuilder(NecessaryExplanationBuilder):
"... |
13,419 | 3b99a4d2366b5717708af53c885b60b489799f84 | # Generated by Django 2.2.1 on 2019-05-16 00:27
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('myApp', '0002_auto_20190516_0021'),
]
operations = [
migrations.AlterField(
model_name='customuser',
name='profile_i... |
13,420 | 9c3dce4d6e8fd58197b83dc188ad2b1a474bfb7a | import sqlite3
conn = sqlite3.connect("SnackBar.db")
def initiate_leiding_table(conn):
cursor = conn.cursor()
cursor.execute("""CREATE TABLE leiding (
first text,
last text,
schuld float
)""")
def initiate_snackbar_table(conn):
cursor = conn.cursor()
... |
13,421 | 744e67a418647dd88fcec020f9d38546ba4723dc | # -*- coding: utf-8 -*-
'''
้กต้ข่งฃๆๅจ
'''
__author__ = 'Evan Hung'
import urlparse
import re
from bs4 import BeautifulSoup
class HtmlParser(object):
def parse(self, page_url, html_cont):
if page_url is None or html_cont is None:
return
soup = BeautifulSoup(html_cont, 'html.parser', f... |
13,422 | 2a2bd3714d4b2805a43416861951e615c5e1eb07 | import pyttsx3
engine = pyttsx3.init()
ssound = engine.getProperty('voices')
for sound in ssound:
print('voice')
print('id %s' %sound.id)
print('gender %s' %sound.gender)
print('**************************')
|
13,423 | 83f8c193a287a07e096a190df7736b4c103aeaa4 | #!/usr/bin/env python
## Create a schema for the table and then create the table.
from google.cloud import bigquery
client = bigquery.Client()
table_id = "innate-entry-286804.rns_sample_dataset.rns_db_4"
schema=[
bigquery.SchemaField('itemid','STRING',mode='REQUIRED'),
bigquery.SchemaField('quantity','STRI... |
13,424 | 0aa1e216b5f136bd30251a4d3b1b1b24f6c8466f | # Used by the network to perform actions and getting new states
from Grab_screen import grab_screen
class Game_state:
def __init__(self, agent, game):
self._agent = agent
self._game = game
# get_state(): Accepts an array of actions and performs the action on the Dino
# Returns... |
13,425 | 43d0988b7f6e79345bae3f48040486a00b7a49d5 | from rest_framework import serializers
from .models import *
class ForecastSerializer(serializers.ModelSerializer):
class Meta():
model = Forecast
fields = ('place_name','cyclone_id','cyclone_name','image_link','time_of_last_forecast','created_at') |
13,426 | de81d6098282e7e405bcacc9f5d518ceb8f3a881 | import sys
infile = sys.argv[1]
with open(infile) as inputf:
lines = inputf.readlines()
dna = lines[0].strip()
k = int(lines[1].strip())
matrix = []
for line in lines[2:]:
values = line.strip().split()
linevals = []
for val in values:
linevals.append(float(val))
matrix.append(linevals)
trans = {'A': ... |
13,427 | 595297e304abd3ecd44084e0584a2387176bc2cb | import sys
from PySide6 import QtWidgets
from productiveware.widgets.main_window import MainWidget
if __name__ == '__main__':
app = QtWidgets.QApplication()
main_window = MainWidget()
sys.exit(app.exec())
|
13,428 | 1e11380d8b13bd2a60fcd53e1116dba06d51bc38 | #!/usr/bin/python3
# coding = utf-8
"""
@author:m1n9yu3
@file:main.py
@time:2021/01/12
"""
import threading
from tmp.get_data import *
from tmp.keyword_get import ask_url, search_key
'''
target : ็ฎๆ
http://floor.huluxia.com/post/detail/ANDROID/2.3?platform=2&market_id=tool_baidu&post_id={ๅธๅญid}&page_no={้กตๆฐ}
ๅธๅญid ไพๆฌก้ๅข... |
13,429 | 6efb43fc22c94ece22322f6a841a9e07df8fe06a | from help import *
import math
import re
import sys
def settings(str):
return dict(re.findall("\n[\s]+[-][\S]+[\s]+[-][-]([\S]+)[^\n]+= ([\S]+)",str))
def coerce(s1):
"""
Converts value to Boolean, if value is not a boolean string it converts it to integer.
Parameters
--------... |
13,430 | e638123ed947787fc611d5580f5908e93fea8afc | ''' ะคะพัะผะฐัะธัะพะฒะฐะฝะธะต ัััะพะบ
'''
name = 'John'
age = 34
# print('My name is ' + name + '. I\'m ' + str(age ))
# print('My name is % (name)s. I\'m %(age)d' %{'name': name, 'age': age}) #ะฝะต ัะฐะฑะพัะฐะตั!!!
#print('My name is %s. I\'m %d' % ('David', age))
print('Title: %s, Price: %f' %('Sony', 40)) #Title: Sony, Price: 40.... |
13,431 | e924c622706ed88627ff31dba68fb4a620a65a6b | import predictor
import pandas as pd
active_drivers = [['Daniel Ricciardo','McLaren'],
['Mick Schumacher','Haas F1 Team'],
['Carlos Sainz','Ferrari'],
['Valtteri Bottas','Mercedes'],
['Lance Stroll','Aston Martin'],
[... |
13,432 | dda07b23dc1fa4266a687b5cbab4d6e19f710ffc | # Copyright (c) 2020, Vladimir Efimov
# All rights reserved.
#
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import sys
import modules.text_processor_normalize as tpn
from modules.term_scoring import get_term_score
def count_term_entries(s... |
13,433 | 96adad4aa658cd8f0a06f33ef3294b1d9f15eb35 | import streamlit as st
import pandas as pd
import os
from PIL import Image
from datetime import datetime
import streamlit.components.v1 as stc
import base64
import time
timestr = time.strftime("%Y%m%d-%H%M%S")
import sqlite3
conn = sqlite3.connect('data.db')
c = conn.cursor()
metadata_wiki = """
"""
HTML_BANNER ... |
13,434 | 269db89ad962d2707c4dd8bc6d8fec63a37851e1 | from .base import BaseResourceTest
from test.factories import DatasetGenerationJobFactory
from src.master.resources.dataset_generation_job import DatasetGenerationJobResource, DatasetGenerationJobListResource
import os
from src.master.resources.datasets import load_dataset_as_csv
from src.models import Dataset, Dataset... |
13,435 | 9066aa06aef0e1f77c7f902aa3d4822923b06092 | #doing linear searches
names = ["Bill", "Charlie", "Fred", "Alien"]
if "Aunty" in names:
print("Found")
else:
print("Not Found")
|
13,436 | cfb3de6ff3c83ed3cef2527064a1a1d9151c1ef8 |
import pandas.tools.plotting as pdplt
import matplotlib.pylab as plt
import seaborn as sns
import subprocess
import pandas as pd
import numpy as np
import serial
from sklearn.tree import DecisionTreeClassifier, export_graphviz
from Tkinter import *
import Tkinter as Tk
class EnterInterface:
def __init__(self, ma... |
13,437 | ed6645a367407c554fd8aad9dc14b038d3cb4626 | #!/usr/bin/env python
# coding: utf-8
import os
import re
import time
import json
defaults = "--single-transaction --skip-lock-tables --compact --skip-opt --quick --no-create-info" \
"--master-data --skip-extended-insert"
# ignore_tables = ["soccerda.ndb_apply_status"]
def dump_mysql(conn, schemas, misc = defau... |
13,438 | 5dd88a0800664d6e8d42caef784f2751ed44b2f1 | from models.detector import face_detector
import numpy as np
from models.parser import face_parser
import cv2, os
part_colors = [[255, 0, 0], [255, 85, 0], [255, 170, 0],
[255, 0, 85], [255, 0, 170],
[0, 255, 0], [85, 255, 0], [170, 255, 0],
[0, 255, 85], [0, 255, 170],
... |
13,439 | 0a45ac8d436f16359163b89b9ad21a855c5d4b3f | class LogUtil:
def __init__(self):
"""
Initiate Log Util.
This Class contains utilities for helping with Logging
"""
self.META_AE_IP = 'HTTP_X_APPENGINE_USER_IP'
self.FORWARDED_FOR = 'HTTP_X_FORWARDED_FOR'
print('{} - Initialized'.format(__name__))
def... |
13,440 | 7edd2d284ec6ee1c2f70fb5aac9fadee7fcec5b1 | import cv2
import numpy as np
kernel = np.ones((5,5),np.uint8)
print(kernel)
path = './archivos/futbol.jpg'
img = cv2.imread(path)
img = cv2.resize(img,(0,0),fx=0.3,fy=0.3)
imGray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
imgBlur = cv2.GaussianBlur(imGray,(7,7),0)
imgCanny = cv2.Canny(imgBlur,100,200)
imgDilation = cv2.... |
13,441 | 8e18c7fed9d67ef518950b5490ef7703c537b947 | #!/usr/bin/env python
# coding: utf-8
# In[ ]:
import numpy as np
np.set_printoptions(linewidth=500)
np.set_printoptions(precision=8)
import random
# In[ ]:
#ๅคงใใใ่ฟใ
def norm(r):
return(np.sqrt(np.real(np.dot(r.conjugate(),r))))
# In[ ]:
#ในใใณ๏ผใในใใณ๏ผใฎในใใใซใไฝใ๏ผ่ฆๆ ผๅ่พผใฟ๏ผ
def spin1(s1,s0,sm1):
a=np.array([s1,... |
13,442 | 064432b66e4882c5b9ab0e544ce2971aba4bd16d | #1.ํจ์
print('#################### 1.ํจ์ ###################')
def add(num1,num2):
return num1 + num2
print(add(1,2))
def add_mul(num1,num2): #๋ค์ค ๋ฆฌํด๊ฐ์ ํํํํ๋ก ๋ฐํ
return num1 + num2 , num1*num2
print(add_mul(1,2))
my_add , my_mul = add_mul(1,2) #ํํ ์ธํจํน
print(my_add)
print(my_mul)
#2.๋ชจ๋
print('#############... |
13,443 | 9a5d8aff68f1cc9b436294114d5b632eb83cbbd6 | # Bill Karr's Code for Assignment 3, Problem 1
from __future__ import division
import numpy as np
def qr_iteration(A, tol):
n = len(A)
for i in range(n-1,0,-1):
while np.linalg.norm(A[i-1,:i-1]) >= tol:
sigma = A[i][i]
Q,R = np.linalg.qr(A - sigma*np.eye(n,n))
A = n... |
13,444 | 1fa35d0d288b5464dbb6da4f654b93f39c847535 | '''
ํผ๋ณด๋์น ์๋ 0๊ณผ 1๋ก ์์ํ๋ค. 0๋ฒ์งธ ํผ๋ณด๋์น ์๋ 0์ด๊ณ , 1๋ฒ์งธ ํผ๋ณด๋์น ์๋ 1์ด๋ค. ๊ทธ ๋ค์ 2๋ฒ์งธ ๋ถํฐ๋ ๋ฐ๋ก ์ ๋ ํผ๋ณด๋์น ์์ ํฉ์ด ๋๋ค.
์ด๋ฅผ ์์ผ๋ก ์จ๋ณด๋ฉด Fn = Fn-1 + Fn-2 (n>=2)๊ฐ ๋๋ค.
n=17์ผ๋ ๊น์ง ํผ๋ณด๋์น ์๋ฅผ ์จ๋ณด๋ฉด ๋ค์๊ณผ ๊ฐ๋ค.
0, 1, 1, 2, 3, 5, 8, 13, 21, 34, 55, 89, 144, 233, 377, 610, 987, 1597
n์ด ์ฃผ์ด์ก์ ๋, n๋ฒ์งธ ํผ๋ณด๋์น ์๋ฅผ ๊ตฌํ๋ ํ๋ก๊ทธ๋จ์ ์์ฑํ์์ค.
์ฒซ์งธ ์ค์ n์ด ์ฃผ์ด์ง๋ค. n์ 20๋ณด๋ค ์๊ฑฐ๋ ๊ฐ์ ์์ฐ์ ๋๋ 0์ด๋ค.
'''
... |
13,445 | a84e61d28571af1d0f51591745022556bc234ea8 | import numpy as np
from smart.ops import SealOps
from smart.seal_matrix import CipherMatrix
class SealKernel:
def __init__(self, vectors, gamma, coef0, degree, kernel_name, seal_ops: SealOps):
self.coef0 = coef0
self.gamma = gamma
self.degree = degree
self.vectors = vectors
... |
13,446 | 925d220066b3902f44a9645b1ac59f152025dcd3 | import requests
import time
import datetime
from Send_Notifications import Get_Technical_Owner ,First_mail
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
from DBConnection_Sagar import Base,cert_data_sagar
import logging
logger_Insert_db_error = logging.getLogger('Certrenewal_Insert_db_er... |
13,447 | 70e458602947075475efae3d984038ac70dcce33 | import serial.tools.list_ports
import urllib
from md5 import md5
from time import time
import socket
IPADDR = '209.20.80.141'
PORTNUM = 11311
def usage():
print 'Usage: cicada.py <serial device> "me@example.com" "My Name" "160 Varick, New York, NY 10031"'
print
print "Run cicada.py to upload your senso... |
13,448 | 8a59fe51813b23d00a0f55a603a18a2a3bd93554 | import random
def numero_aleatorio():
lista=[]
while len(lista)!=5:
num=random.randrange(0,9)
if num not in lista:
lista.append(str(random.randrange(1,9)))
numero="".join(lista)
return numero
def comprueba(secreto,numero):
#Creamos diccionario para guardar los valores ... |
13,449 | 56312a8ac462a5e62acd84aa4459b659ee9bba3f | #!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
Author: David Beam, db4ai
Date: 18 January 2018
Description:
"""
# Include files
import gym
import numpy as np
import tensorflow as tf
import matplotlib.pyplot as plt
from random import uniform
# Include custom files
import functions as func
impo... |
13,450 | 4e1e078cdd8a892e5523c32bafb48f48f1ad347b | def str_rev(str):
rstr = ''
index = len(str)
while index > 0:
rstr += str[ index - 1 ]
index = index - 1
return rstr
print(str_rev('string'))
|
13,451 | b4745c4fce15537556d9906216ddb979934937a7 | #!/usr/bin/python
import matplotlib.pyplot
import matplotlib.mlab
import collections
def Import(filename):
datas=matplotlib.mlab.csv2rec(filename,delimiter='\t')
print "LogCan20:", filename, "OK n=", len(datas)
return datas
def PlotT(datas ):
matplotlib.pyplot.figure()
ax1 = matplotlib.pyplot.subplot(1,1,1)
i... |
13,452 | 8439fca8bd57db3b86645f8d6d154be74d8bb377 | import json
import logging
log = logging.getLogger(__name__)
sh = logging.StreamHandler()
log.addHandler(sh)
def test_rule_access(as_user):
r = as_user.get('/rules')
assert r.status_code == 403
r = as_user.post('/rules', json={'test': 'rule'})
assert r.status_code == 403
|
13,453 | d401eeedfee373acc0953abbb318a551c6509d90 | input = open('allvectors.in', 'r')
output = open('allvectors.out', 'w')
s=int(input.read())
b=[]
for i in range(2**s):
j=2
while(j<=2**s):
if (i%j<=(j/2-1)):
b.append(0)
else:
b.append(1)
j*=2
for k in range(s):
output.write(str(b[s-k-1]))
output.w... |
13,454 | a6a7924aa8e329ca4caa47e69b0063fa76bf7b0f | #!/usr/bin/env python3
import sys
from markup_processor import process
from formatters.html import HtmlFormat
def main():
process(HtmlFormat, sys.stdin, sys.stdout)
if __name__ == '__main__':
main()
|
13,455 | b9dd9907dd3bd0dbfd91cc2e5a2a07daafa2634e | # 10.SQL IS NULL Query:
# IS NULL Syntax:
'''
SELECT column_names
FROM table_name
WHERE column_name IS NULL;
'''
# The IS NULL Operator:
# Always use IS NULL to look for NULL values.
# IS NULL operator is used to test for empty values (NULL values).
'''
SELECT CustomerName, ContactName, Address
FROM... |
13,456 | 764c08e08cda7355219352dd3e5ecd2aa6d66d84 | from django.conf.urls import patterns, include, url
# Uncomment the next two lines to enable the admin:
from django.contrib import admin
from django.views.generic import RedirectView
admin.autodiscover()
urlpatterns = patterns('',
url(r'', include('social_auth.urls')),
url(r'^$', RedirectView.as_view(url='/acc... |
13,457 | 18cf94acdd3ad8c9968909428b8598d019d9867e | #--------------------------------
# Functions for plotting
#--------------------------------
import numpy as np
import matplotlib.pyplot as plt
from matplotlib import cm
def plot_dist_3p(
hst,
xi,
yi,
ax=None,
filled=False,
fcolors=None,
**kwargs,
):
... |
13,458 | ddbdb452c9053c042391cb2c246eaac1665441c8 | import unittest
from config.config import Config
TEMPLATE_CONFIG_FILE = 'config/config.ini.template'
class TestConfig(unittest.TestCase):
def setUp(self):
self.config = Config(TEMPLATE_CONFIG_FILE)
def test_get_mongo_url(self):
self.assertEquals(self.config.get_mongo_url(), 'mongodb://USER:PA... |
13,459 | 87076944a9c5f77061eae8120cc7d8536c944421 | # -*- coding: utf-8 -*-
"""
Created on Fri May 24 09:46:47 2019
@author: CDEC
"""
import cv2
import numpy as np
kernel = np.ones((5,5),np.uint8)
for i in range(1,21):
path = 'D:\Documents\OPENCV\Placas\Placa ('+str(i)+").jpg"
img = cv2.imread(path)
numero = 0
caracteres = []
... |
13,460 | ee95a54f73b3c68ff1d2dcd386b972f7b3d51dc5 | from PIL import Image
w = 640
h = 480
image = Image.open('/home/pi/0.jpg')
pixels = image.load()
for i in range(0,w):
for j in range(0,h):
white = True
for each in pixels[i,j]:
if not (each < 80 or each > 155):
white = False
if(white):
pixels[i,j] ... |
13,461 | 065bb34ed1cd9a4e2037f9492a6e3cca6892f787 |
# time: O(nlogn)
# space: O(n)
from collections import Counter
class Solution:
def findLHS(self, nums: List[int]) -> int:
counter = Counter(nums)
max_len = 0
keys = set(list(counter.keys()))
for key in counter.keys():
if key+1 in keys:
max_len = max(max_... |
13,462 | dcf26389c0f841e33f9a2ecc759db2a16e88a295 | # Copyright 2019 Markus Liljergren
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in wri... |
13,463 | ffa669bb82cae0d7b8436040849409a61b4e024b | '''
Task: Jump over numbers
You are given a list of non-negative integers and you start at the left-most integer in this list. After that you need to perform the following step:
Given that the number at the position where you are now is P you need to jump P positions to the right in the list. For example, if you are ... |
13,464 | 04996dc529114fa67376ae400c0def154ffe6ede | from astropy import cosmology as cosmo
import logging
from autoconf import conf
import autofit as af
import autoarray as aa
import autogalaxy as ag
from autolens.lens.model.analysis import AnalysisDataset
from autolens.lens.model.preloads import Preloads
from autolens.interferometer.model.result import Resu... |
13,465 | e6ba87b2b552723a46c7a8a3e005a520fae25bf6 | import json
def hash_str(x):
return abs(hash(json.dumps(x, sort_keys=True))).to_bytes(8, "big").hex()
|
13,466 | bc32faadb10d168466977da0825e7ef4e1b6002e | height = [int(input()) for _ in range(9)]
check = [False] * 9
result = []
def recursive(index):
global result
if index == 9:
answer = 0
count = 0
demo = []
for i in range(9):
if check[i]:
answer += height[i]
count += 1
d... |
13,467 | 4231d0b652ab9071d0443d91d93b89bcbfba615b | import torch
import torch_geometric
from torch_geometric.profile import benchmark
from torch_geometric.testing import (
disableExtensions,
onlyFullTest,
onlyLinux,
withCUDA,
withPackage,
)
from torch_geometric.utils import scatter
# Basic "Gather-Apply-Scatter" patterns commonly used in PyG:
def ... |
13,468 | 7441555938981f54f76db26f8bf7201306bf6080 | import pytest
from scripts.use_pd_array_in_core import use_pd_array
BAD_FILE_0 = "import pandas as pd\npd.array"
BAD_FILE_1 = "\nfrom pandas import array"
GOOD_FILE_0 = "from pandas import array as pd_array"
GOOD_FILE_1 = "from pandas.core.construction import array as pd_array"
PATH = "t.py"
@pytest.mark.parametriz... |
13,469 | ed241a66598331db5e9a5e74dc819614bd9aa89c | print ("Learn the steps of hte 5 sequence tango.")
print ("What step do you wish to learn?")
whichStep = int(input())
if whichStep == 1:
print ("Leader takes a step back.")
elif whichStep == 2:
print ("Side step towards centre of floor.")
elif whichStep == 3:
print ("Leader steps outside of follower.")
e... |
13,470 | 19747cea3b21d22a495f9ada22bfef7bc7efafe8 | def login_disponivel(login,lista):
login = input('Qual รฉ o seu login? ')
i=1
if login in lista:
login1 = login + str(i)
lista.append(login1)
else:
lista.append(login) |
13,471 | db4b1431be679f2484c1f6bc2e1b74ac7a3ee45b | #! /usr/bin/env python
# -*- coding: utf-8 -*-
# vim:fenc=utf-8
#
# Copyright https://github.com/VPerrollaz
#
# Distributed under terms of the %LICENSE% license.
"""
Gรฉnรฉration du graphe permettant de coder un algorithme glouton.
"""
import random as rd
from enum import Enum, auto
class Genre(Enum):
"""Enum pou... |
13,472 | 06c424dc5adf8d87e932159faa2ccba85d68dc80 | # Copyright 2018 The TensorFlow Authors All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... |
13,473 | b4fc575a56530582016e5b7044169e033c5a976d | #!/usr/bin/env python
from __future__ import print_function
import pdb
import tracer_func as tracer
import ConfigParser
import argparse
import sys
import os
import subprocess
import pipes
import glob
import shutil
import re
from collections import defaultdict, Counter
from time import sleep
import warnings
import pick... |
13,474 | 0358674298b2f64a864a58fcee4bf25de745d5b1 | # 4/2009 BAS
# read() replicates behavior of pyserial
# readexactly() added, which is probably more useful
# readbuf() dumps current buffer contents
# readpacket() has old broken behavior of read() - lowest level / fastest
import socket
import time
MOXA_DEFAULT_TIMEOUT = 1.0
# Socket modes:
# Nonblocking
# s.se... |
13,475 | bf0300b9271eadd489dd1579ad47fa8cca8cdfb2 | from . import views
from django.urls.conf import include, path
import debug_toolbar
urlpatterns = [
path('register', views.register, name='register'),
path('login', views.login, name='login'),
path('logout', views.logout, name='logout'),
path('__debug__/', include(debug_toolbar.urls), name='logout'),
... |
13,476 | 4c0d61fe0c2233b9b09ddf313e0396aa9fc87e23 | # Generated by Django 2.1.5 on 2019-02-09 14:23
from django.db import migrations, models
import django_mysql.models
class Migration(migrations.Migration):
dependencies = [
('whoweare', '0003_whowearefields_fourthsectionmissionvisionvaluesdescriptionsinlist'),
]
operations = [
migrations... |
13,477 | 2eb0eb97b9ca727e6d002ac2929a0d9771631ff9 | from models import *
from constants import *
from utils import MyDataset
import matplotlib.pyplot as plt
import random
import torch
import itertools
vae_type = 'conv'
dataset = 'Total'
subset = True
model_name = 'Total_VAE__2021-02-04 11:05:04.531770.pt'
model_path = MODELS_ROOT + model_name
if subset:
if dataset... |
13,478 | a95dc47f786c33ffc3b523d45bd418c9e4656a0a | import math
def calcula_trabalho (F,teta,s):
trabalho = F * math.cos(teta) * s
return trabalho |
13,479 | 5517b041a7ee292d1c00b6c3bd7acf4ad6bf42e0 | # Create your views here.
from django.shortcuts import render, redirect, get_object_or_404
from sculptqr.models import QRCode
from django import forms
from django.http import HttpResponse
from django.conf import settings
# For image upload
import os
import shutil
import Image as PILImage
import ImageFilter
import Stri... |
13,480 | 2347d1d881781ddbf231e164a511edef0c66ef65 | from urllib.request import urlretrieve
import os
from os.path import exists, join
import tarfile
if not exists("data"):
os.mkdir("data")
csv_tar_file = "https://storage.googleapis.com/track_data_ncar_ams_3km_csv_small/track_data_ncar_ams_3km_csv_small.tar.gz"
nc_tar_file = "https://storage.googleapis.com/track_da... |
13,481 | f8124ff68bbed7e3633b3f9473bf0eaa9816c03b | '''
240. Write a program to Read a Text File and Print all the Numbers Present in the Text File
'''
|
13,482 | c89081083dfcb1eb21fc5252abe25fb922209ef4 | from django.apps import AppConfig
class BizzConfig(AppConfig):
name = 'bizz'
|
13,483 | 4223de2c4bc64fb1b06900f7b98f112c136b2686 | from django.contrib import admin
from .models import Album, Song
#username : admin
#password : admin1234
admin.site.register(Album)
admin.site.register(Song) |
13,484 | 9b2e32e481f57e7e901bd7881fba4e9c170048de | #!/usr/bin/env python
prime=[2,3,5,7]
n=10000
for i in xrange(11,n):
l=len(prime)
flag=0
for j in xrange(l):
if i % prime[j] == 0:
flag=1
if flag == 0:
prime+=[i]
print len(prime)
print max(prime)
|
13,485 | 68e227171d80be555b737f95fc15ee21367ed784 | from sqlalchemy import Column
from sqlalchemy import Date
from sqlalchemy import ForeignKey
from sqlalchemy import Integer
from sqlalchemy import String
from sqlalchemy.orm import relationship
from wewallet.application.models import Model
class Billing(Model):
__tablename__ = 'billings'
id = Column(Integer, ... |
13,486 | 05084057b80c237ef12f749eb4bd25e2264fd6bb | # ๅๅฐ็นๅพ https://zh.wikipedia.org/wiki/%E5%93%88%E5%B0%94%E7%89%B9%E5%BE%81
import numpy as np
from skimage.feature import haar_like_feature_coord
from skimage.feature import draw_haar_like_feature
feature_coord, _ = haar_like_feature_coord(2, 2, 'type-4')
image = draw_haar_like_feature(np.zeros((2, 2)),
... |
13,487 | c9ec8624aa734f68254c1ca27da802247557698e | import time, sys, os
from selenium import webdriver
from selenium.webdriver.common.desired_capabilities import DesiredCapabilities
from wifi24 import Wifi24
sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), "{}/{}".format(os.path.pardir,os.path.pardir))))
from assertion import Assert
from networ... |
13,488 | ac76d43729ff54487238008aaed7ff2f9a01c7de | import notes_pakets.corp_notes as modelo
class Action:
def new_note(self, usuario):
print(f"Hola {usuario[1]}\nIniciamos")
title = input("Introduce el titulo de nota: ")
description = input("Ingrese la nota a guardar: ")
nota = modelo.Note(usuario[0], title, description)
... |
13,489 | b5644dc2ff6701ea7774832d523db37e91c8efb0 | import json
from pathlib import Path
import cv2
import pandas as pd
from tqdm import tqdm
def load_web_icon_dataset(dataset_path):
dataset_path = Path(dataset_path)
images = []
alt_texts = []
for json_path in tqdm(list(dataset_path.glob('*.json'))):
try:
with open(str(json_path),... |
13,490 | d5cdb46b01411bd58d69f1cb1437ecdf730a21ed | # coding: utf-8
import sys
import web
import url
sys.path.append('./controllers')
urls = url.urls
if __name__ == "__main__":
app = web.application(urls, globals())
app.run()
|
13,491 | 84093f2c0f5bed38cba70de6282953a3764b2a3c | # -*- coding: utf-8 -*-
from setuptools import setup
with open('README.rst') as f:
long_description = f.read()
setup(
name='dj-email-url',
version='0.1.0',
url='https://github.com/migonzalvar/dj-email-url',
license='BSD',
author='Miguel Gonzalez',
author_email='migonzalvar@gmail.com',
... |
13,492 | 5cc2c95d912ba6692a2f9827f192a05b2e3c6b82 | from datetime import datetime
from flask import jsonify, make_response, request, render_template
from flask_httpauth import HTTPTokenAuth
from flask_login import login_required
import json
from app.mod_user.models import AuthorizationError, User, UserEntry
from . import api_module as mod_api
from . import controllers a... |
13,493 | 9561c85e08a529b565b5e6da9e5d22e79b3c42b4 | import pandas as pd
import numpy as np
import logging
import os
import tarfile
from tempfile import TemporaryFile
from kgx.utils import make_path
from .transformer import Transformer
from typing import Dict, List, Optional
LIST_DELIMITER = '|'
_column_types = {
'publications' : list,
'qualifiers' : list,
... |
13,494 | f92603209d8d298a8858bbd6cba8d72ac58253b9 | import random
p = 0.5
max_unanswered_calls = 4
max_nr_days = 100
successes = 0
for d in range(max_nr_days):
if random.random() > p and random.random() > p and random.random() > p and random.random() > p and random.random() <= p:
successes += 1
print(successes/max_nr_days)
... |
13,495 | 2641713d05c390402c4ef075bc672335462e63ef | '''
1. ๋ฌธ์ ๋ถ์
- ํ ์ธ๋ฐ์ ๊ธ์ก์ด ์ผ๋ง์ธ๊ฐ?
- ํ ์ธ๋ ๊ธ์ก์ด ์ผ๋ง์ธ๊ฐ?
2. ํ ์ธ๋ฐ์ ๊ธ์ก : ๊น์์ค ๊ธ์ก์ ์๋ฏธ
3. ํ ์ธ๋ ๊ธ์ก : ํ ์ธ๋ฐ์ ๊ธ์ก์ ๋นผ๊ณ ์ค์ ์ง๋ถํ ๊ธ์ก
4. ํ ์ธ์จ = (ํ ์ธ์ก / ์ํ์ก) * 100 = (2,000 / 10,000) * 100 = 0.2 * 100 = 20%
5. ํ ์ธ ์ ์ฉ๋ ๊ฐ๊ฒฉ = ์ํ์ก * (100% - ํ ์ธ์จ) = 10,000 * (1.00 - 0.1) = 9,000์
1) ๋งค๊ฐ๋ณ์์ ์ดํด
2) ๋ฐํ์ ์ดํด
'''
#๋ค์๊ณผ ๊ฐ์ด import๋ฅผ ์ฌ์ฉํ ์ ์์ต๋๋ค.
#import m... |
13,496 | 804b6acbf9057afd432c20bb08e02cfbe0390509 | '''
6. ZigZag Conversion
The string "PAYPALISHIRING" is written in a zigzag pattern
on a given number of rows like this: (you may want to display
this pattern in a fixed font for better legibility)
P A H N
A P L S I I G
Y I R
P I N
A L S I G
Y A H R
P I
And then read line by line: "PAHNAPLSII... |
13,497 | 75caa344cd346acbbd07b413133d6c4306576ad3 | s=input()
s = s[::-1]
print(s) |
13,498 | a3dfcbcafaaa634f396f1d7320a67293b2d952b1 | from django.test import TestCase
from django.test.client import Client
from model_mommy import mommy
from .models import Vehicle
# Create your tests here.
class ReserveTestCase(TestCase):
def setUp(self):
self.vehicle = mommy.make(
'vehicle.Vehicle', reservation_code='1', _quantity=10
... |
13,499 | b65c5d2453428a07ddefe880529a53e4340f8c4d | import sqlite3
import glob
from sklearn.feature_extraction.text import CountVectorizer
import numpy as np
import scipy.spatial.distance as distance
def insert_similarity_name(cur, sim_name):
cur.execute("INSERT INTO similarity (name) VALUES (?)",
(sim_name,)
)
sim_id = cur.execute("SELECT * FRO... |
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