爬取全程无忧岗位

思路：
【郑重说明，少量爬取公开数据仅供分析以及爬虫学习使用】
1.确定起始URL：https://search.51job.com/list/000000,000000,0000,00,9,99,%E5%A4%A7%E6%95%B0%E6%8D%AE,2,1.html
2.观察网页内容：
在这里插入图片描述
3.寻找字段
4.完整代码
注释代码里面，很好理解
# -*- coding: utf-8 -*-
# @Time    : 2019/6/5 18:45
# @Author  : baby
# @File    : get_51.py
import requests
from lxml import etree
import pandas as pd
import logging



class Job:
    def __init__(self):
        self.headers = {'User-Agent':'换成你自己的'}
    def get_URL(self):
        logging.captureWarnings(True)
        file_List = []
        for i in range(1,4):  #215
            start_urls = 'https://search.51job.com/list/000000,000000,0000,00,9,99,%25E6%2595%25B0%25E6%258D%25AE%25E6%258C%2596%25E6%258E%2598,2,{}.html'.format(i)
            response = requests.get(start_urls, headers=self.headers, timeout=10,verify=False)
            response.encoding = 'gbk'
            if response.status_code == 200:
                print("主页start_urls爬取成功，等待解析：",start_urls)
                HTML = etree.HTML(response.text)
                job_URL = HTML.xpath('//div[@id="resultList"]/div[@class="el"]/p/span/a/@href')
                for url in job_URL:
                    html = requests.get(url, headers=self.headers,verify=False,timeout=5)
                    if html.status_code == 200:
                        print("爬取当前岗位成功：", url)
                    html.encoding = 'gbk'
                    job_html = etree.HTML(html.text)
                    #---
                    if job_html.xpath('//div[3]//div[@class="cn"]/h1/@title'):
                        jobName = str(job_html.xpath('//div[3]//div[@class="cn"]/h1/@title')[0])  # 工作岗位
                    else:
                        jobName = 'nan'
                    #---
                    if job_html.xpath('//div[@class="cn"]/strong/text()'):
                        jobSalary = str(job_html.xpath('//div[@class="cn"]/strong/text()')[0])  # 薪水

                    else:
                        jobSalary = 'nan'
                    #---
                    if job_html.xpath('//div[@class="cn"]/p[@class="msg ltype"]/@title'):
                        job_item = job_html.xpath('//div[@class="cn"]/p[@class="msg ltype"]/@title')[
                            0]  # pattern = re.compile(r'(\S+)\s*\|')
                        conten_List = str(job_item).split("\xa0\xa0|\xa0\xa0")
                        jobPlace = str(conten_List[0])  # 工作地点
                        jobExperience = str(conten_List[1])  # 工作经验
                        jobEducation = str(conten_List[2])  # 教育要求
                        jobNumber = str(conten_List[3])  # 招收人数
                    else:
                        jobPlace = 'nan'  # 工作地点
                        jobExperience = 'nan'  # 工作经验
                        jobEducation = 'nan'  # 教育要求
                        jobNumber = 'nan'  # 招收人数
                    #---
                    if job_html.xpath('//div[@class="bmsg job_msg inbox"]/p/text()'):
                        job_Imformation_List = job_html.xpath('//div[@class="bmsg job_msg inbox"]/p/text()')
                        jobSkills = ''
                        for i in range(0, len(job_Imformation_List)):
                            jobSkills = jobSkills + str(job_Imformation_List[i]) + '\n'  # 工作技能要求
                    else:
                        jobSkills = 'nan'
                    #---
                    file_List.append([jobName,jobSalary,jobPlace,jobExperience,jobEducation,jobNumber,jobSkills])
                    # yield file_List

            else:
                # print("当前页爬取失败进入下一页")
                pass
        return  file_List

    def save_File(self):
        self.itemName = ['职位名','薪资','工作地点','工作经验','学历','招牌人数','招牌条件']
        file_List = Job.get_URL(self)
        df = pd.DataFrame(file_List)
        df.to_excel('data1.xlsx',header=self.itemName)
        print("文件保存完成!")

if __name__ == '__main__':
    j = Job()
    j.save_File()
爬取全程无忧岗位

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