爬私房摄交圈.py

import os
import time
# 导入发送请求模块：
import requests
# 导入解析文本模块：
from bs4 import BeautifulSoup
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
print("开始爬取")

# 返回上一级目录：
# base_path = os.path.dirname(os.path.abspath(__file__))
base_path = "D:s27day67"
# 路径和图片文件夹拼接：
img_path = os.path.join(base_path, "img")
# 获取响应：
response = requests.get("https://pinkgirl.baklib.com/4a1d/346e")
# 将请求结果交给bs4解析：
soup = BeautifulSoup(response.text, "html.parser")
# 经过分析定位到<div class="content mt-5">：
div_obj = soup.find(name="div", attrs={"class": "content mt-5"})
# print(div_obj)
div_obj1 = div_obj.find_all(name="div", attrs={"class": "editor_js--qiniu_image__picture"})
for d1 in div_obj1:
    img = d1.find(name="img")
    img_src = img.get("src")
    img_response = requests.get(img_src)
    file_path = os.path.join(img_path, img_src.rsplit("/", 1)[-1])
    with open(file_path,"wb+") as f:
        f.write(img_response.content)