线程池爬取汽车之家.py

import time
import requests
#线程池、进程池
from concurrent.futures import ThreadPoolExecutor,ProcessPoolExecutor
#多线程：
from threading import Thread
#多进程：
from multiprocessing import Process
#进程池：
from multiprocessing import Pool
from bs4 import BeautifulSoup
#导入cpu_count查看CPU信息获取本机CPU核数：
from multiprocessing import cpu_count

def task(url):
    #format格式化页数：
    response = requests.get("https://www.autohome.com.cn/all/{}/#liststart".format(url))
    #获取编码：
    # print(response.encoding)
    #转码：
    response.encoding = "gbk"
    #获取文本：
    text = response.text
    #解析文本：
    soup = BeautifulSoup(text,"html.parser")
    #获取div：
    div = soup.find(name = "div",attrs={"id":"auto-channel-lazyload-article"})
    #获取img：
    img_list = div.find_all(name = "img")
    #获取第一个链接和长度：
    # print(img_list[0],len(img_list))
    print(response.url)
    for i in img_list:
        print("https:" + i.get("src"))
        break

if __name__ == '__main__':
    """进程池一般开CPU核数、线程池开CPU核数的2-5倍、"""
    # print(cpu_count())
    stat = time.time()
    #开启线程池、4核是4进程乘以2总共是8个线程：
    t = ThreadPoolExecutor(max_workers=cpu_count() * 2)
    for i in range(1,110):
        t.submit(task,i)
    t.shutdown()
    print("耗时：%s" %(time.time() - stat))