Python 爬虫数据解析--xpath案例

标签：fan   class   tor   imp   爬虫   数据解析   end   mac   for   

代码如下：

import requests
from lxml import etree

if __name__ == "__main__":
    headers = {
                    ‘User-Agent‘: ‘Mozilla/5.0 (Macintosh; Intel Mac OS X 10_12_0) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/73.0.3683.103 Safari/537.36‘
            }
            url = ‘https://www.aqistudy.cn/historydata/‘
            page_text = requests.get(url=url, headers=headers).text
            tree = etree.HTML(page_text)
            #解析到热门城市和所有城市对应的a标签
            # //div[@class="bottom"]/ul/li/          热门城市a标签的层级关系
            # //div[@class="bottom"]/ul/div[2]/li/a  全部城市a标签的层级关系
            a_list = tree.xpath(‘//div[@class="bottom"]/ul/li/a | //div[@class="bottom"]/ul/div[2]/li/a‘)
            all_city_names = []
            for a in a_list:
                    city_name = a.xpath(‘./text()‘)[0]
                    all_city_names.append(city_name)
            print(all_city_names,len(all_city_names))

运行效果：

案例二：爬取58二手房中的房源信息

代码如下：

import requests
from lxml import etree

if __name__ == "__main__":
    headers = {
        ‘User-Agent‘:‘Mozilla/5.0 (Macintosh; Intel Mac OS X 10_12_0) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/73.0.3683.103 Safari/537.36‘
    }
    #爬取到页面源码数据
    url = ‘https://bj.58.com/ershoufang/‘
    page_text = requests.get(url=url,headers=headers).text

    #数据解析
    tree = etree.HTML(page_text)
    #存储的就是li标签对象
    li_list = tree.xpath(‘//ul[@class="house-list-wrap"]/li‘)
    fp = open(‘58.txt‘,‘w‘,encoding=‘utf-8‘)
    for li in li_list:
        #局部解析
        title = li.xpath(‘./div[2]/h2/a/text()‘)[0]
        print(title)
        fp.write(title+‘\n‘)

运行效果：

Python 爬虫数据解析--xpath案例

标签：fan   class   tor   imp   爬虫   数据解析   end   mac   for   

原文地址：https://blog.51cto.com/13760351/2512753