ihavenonickname

<?php

class Node
{
    public $value = null;
    public $left = null;
    public $right = null;
    
    public function __construct($value)
    {

ihavenonickname

import os
import csv
import unicodedata
import sqlite3
from os.path import join, isfile
from collections import namedtuple

Linha = namedtuple('Linha', 'cidade,cargo,partido,candidato,zona')

def ler_dataset(caminho):

ihavenonickname

import matplotlib.pyplot as plt

PIB = [
    ('São Paulo', 628064882),
    ('Rio de Janeiro', 299849795),
    ('Brasília', 197432059),
    ('Belo Horizonte', 87656760),
    ('Curitiba', 78892229),
    ('Manaus', 67572523),
    ('Porto Alegre', 63990644),

ihavenonickname

function [  ] =bissec1(f,a,b,Erro,x, x2),
  //******************************************************************//
  //calcula a raiz de f(x) no intervalo [a,b] pelo método da bissecção
  //Entrada: f = função a ser avaliada
  //         a = limite inferior do intervalo
  //         b = limite superior do intervalo
  //         erro = precisão desejada
  //         x1=limite inferior para plotar o gráfico da função em estudo
  //         x1=limite superior para plotar o gráfico da função em estudo
  //Saída: raiz

ihavenonickname

from bs4 import BeautifulSoup
from requests import Session
from collections import namedtuple

Disciplina = namedtuple('Disciplina', 'nome nota semestre')

def get_disicplinas(cod_aluno, senha, cod_curso):
    session = Session()

    form_login = {'codpessoa': cod_aluno, 'senhabib': senha}

ihavenonickname

import grequests
import json
import unicodedata
from bs4 import BeautifulSoup

def download(urls):
    def catcher(req, ex):
        print(ex)

    reqs = map(grequests.get, urls)

ihavenonickname

import grequests
import json
import unicodedata
from bs4 import BeautifulSoup

def download(urls):
    def catcher(req, ex):
        print(ex)

    reqs = map(grequests.get, urls)

ihavenonickname

import requests
from bs4 import BeautifulSoup
import json
import unicodedata

def normalize(text):
    nfkd_form = unicodedata.normalize('NFKD', text)
    only_ascii = nfkd_form.encode('ASCII', 'ignore')
    return only_ascii.lower().decode()

ihavenonickname

from review import KNNPoint, predict

dataset = [
    KNNPoint([842.0, 2.2, 7.0, 2.0, 2549.0], "medium cost"),
    KNNPoint([1021.0, 0.5, 53.0, 3.0, 2631.0], "high cost"),
    KNNPoint([563.0, 0.5, 41.0, 5.0, 2603.0], "high cost"),
    KNNPoint([615.0, 2.5, 10.0, 6.0, 2769.0], "high cost"),
    KNNPoint([1821.0, 1.2, 44.0, 2.0, 1411.0], "medium cost"),
    KNNPoint([1859.0, 0.5, 22.0, 1.0, 1067.0], "medium cost"),
    KNNPoint([1821.0, 1.7, 10.0, 8.0, 3220.0], "very high cost"),

ihavenonickname

int pixelsize = 4;
int gridsize  = pixelsize * 7 + 5;
Player player;
ArrayList enemies = new ArrayList();
ArrayList bullets = new ArrayList();
int direction = 1;
boolean incy = false;
int score = 0;
PFont f;