转载-爬取拉勾网数据代码

import requests as re
import json
import pandas as pd
import time
import random
'''其中三个编码是全国、深圳和广州，但是哪个是哪个不记得了'''
#%E6%B7%B1%E5
#%E5%B9%BF%E5%B7%9E
#%E5%85%A8%E5%9B%BD
#获取网页url
def get_url(keyword,pn):
   base_url1 = "https://www.lagou.com/jobs/list_%E6%95%B0%E6%8D%AE%E5%88%86%E6%9E%90?labelWords=&fromSearch=true&suginput="    #不需要cookie的url
   base_url = "https://www.lagou.com/jobs/positionAjax.json?px=default&city=%E6%B7%B1%E5%BD&needAddtionalResult=false"

   base_headers = {"Accept": "application/json, text/javascript, */*; q=0.01",
                   "Host": "www.lagou.com",
                   "Referer": "https://www.lagou.com/jobs/list_%E6%95%B0%E6%8D%AE%E5%88%86%E6%9E%90?labelWords=&fromSearch=true&suginput=",
                   'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/74.0.3729.169 Safari/537.36'
                   }
   data = {
           "first": "true",
           "pn": "{}".format(pn),
           "kd": "{}".format(keyword)
           }

   session = re.Session()      #创建cookie存储
   session.get(url=base_url1,headers=base_headers)        #通过网址url1建立cookie
   response = session.post(url=base_url, headers=base_headers, data=data)
   response.encoding = 'utf-8'
   #print(response)

   return response

#解析网页信息
def total_Count(response):

   page = response.json()
   # print(page)
   total_count = page['content']['positionResult']['totalCount']   #totalCount为总个数
   pn_count = int(total_count)//15 + 1
   #页数
   print('职位总数{},共{}页'.format(total_count,pn_count))
   return pn_count

def parse_url(response):
   page = response.json()
   for i in range(1,16):
       jobs_list = page['content']['positionResult']['result']
       print(jobs_list)
       page_info_list = []             #用于存储data
       for i in jobs_list:
           job_info = []
           job_info.append(i['city'])
           job_info.append(i['companyFullName'])
           job_info.append(i['companyShortName'])
           job_info.append(i['companySize'])
           job_info.append(i['financeStage'])
           job_info.append(i['district'])
           job_info.append(i['positionName'])
           job_info.append(i['workYear'])
           job_info.append(i['education'])
           job_info.append(i['salary'])
           job_info.append(i['positionAdvantage'])
           job_info.append(i['industryField'])
           page_info_list.append(job_info)
       print(page_info_list)
       return page_info_list

def save_data(page_info_list):
   columns = ['城市','公司全名', '公司简称', '公司规模', '融资阶段', '区域', '职位名称', '工作经验', '学历要求', '工资', '职位福利', '行业']
   df = pd.DataFrame(data=page_info_list,
                     columns=columns)
   #print(df)
   df.to_csv('/Users/liyili2/Downloads/data2.csv', index=False,encoding='utf-8')
   print('保存完成')

#     #调用中心
def main():
   keyword = input('输入查找内容:')      #输入搜索内容
   a = get_url(keyword,pn=1)            #获取respones
   b = total_Count(a)
   print(b)# 获得数据总个数和页数
   total_info = []                     #用来储存每页parse_url
   for i in range(1,int(b)+1):         #实现翻页效果
       a = get_url(keyword, pn=i)
       c = parse_url(a)
       total_info += c
       time.sleep(20)
       print('成功获取第{}页'.format(i))
   d = save_data(total_info)

if __name__ =="__main__":
   main()