本人倾向于用obs4匹配，数据量不大，怎么简单怎么来了
url为关键词搜索，位置默认全国
最后写入json文件

import requests
import json
from bs4 import BeautifulSoup
# url = 'https://www.liepin.com/zhaopin/?sfrom=click-pc_homepage-centre_searchbox-search_new&d_sfrom=search_fp&key=python'


def get_page():
    """
    获取页数/职业
    """
    page = input('请输入页数:')
    job = input('请输入职业:')

    url = 'https://www.liepin.com/zhaopin/?&key={}'.format(job)
    page_url = '&curPage='
    # 条件:一页/多页
    if page == '1':
        full_url = url
    else:
        for i in range(int(page)):
            full_url = url+page_url+str(i)
            parse(full_url,headers)


def parse(url,headers):
    """
    解析页面/将数据保存到json文件

    """
    response = requests.get(url=url,headers=headers)

    res = response.text
    #创建soup对象
    soup = BeautifulSoup(res,'lxml')
    #定位
    content = soup.select('.sojob-list li')

    # import os
    # os.mkdir('./liepin')
    items = []
    # 组成json对象
    for c in content:
        item = {}
        # 依次为职位，地区，学历，工作经验，年薪
        title = c.select('div h3')[0].get_text().strip()
        area = c.select('p .area')[0].get_text()
        edu = c.select('p .edu')[0].get_text()
        time = c.select('.sojob-item-main div p span')[2].get_text()
        text_warning = c.select('p span')[0].get_text()
        
        item['title'] = title
        item['area'] = area
        item['edu'] = edu
        item['time'] = time
        item['text_warning'] = text_warning
        items.append(item)

    import time
    import hashlib
    # 使用MD5构造一个不重名的文件名
    key = time.time()
    md = hashlib.md5()
    md.update(str(key).encode("utf-8"))
    #加密后的字符串
    file_name = md.hexdigest()
    print('正在下载：%s'%file_name)
    json.dump(items,open('./liepin/'+file_name +'.json','w',encoding="utf-8"),ensure_ascii=False,indent=4)


if __name__ == "__main__":
    
    headers = {
        'User-Agent': 'Mozilla/5.0 (Windows NT 6.3; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/70.0.3538.16 Safari/537.36',
        }
    get_page()

有什么问题可以下面留言，都会回复