xpath实战

#  1、爬取58二手房信息
import  requests

from lxml import etree

#需求：爬取58二手房中的房源信息

if __name__ == '__main__':

    #爬取到页面源码数据

    url ="https://bj.58.com/ershoufang/"

    # 进行UA伪装

    headers = {

        'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:77.0) Gecko/20100101 Firefox/77.0'

    }

    page_text = requests.get(url = url,headers=headers).text

    # 数据解析

    tree = etree.HTML(page_text)

    # 存储的是li标签对象

    li_list = tree.xpath('//ul[@class="houst-list-wrap"]/li')

    fp = open('58.txt','w',encoding='utf-8')

    for li in li_list:

        # ./ 就代表li

        #局部解析   一个要加上.

        title = li.xpath('./div[2]/h2/a/text()')[0]

        print(title,'over')

        fp.write(title,'\n')
2、解析下载图片信息  http://pic.netbian.com/4kmeinv/
    解决乱码的两种方法：
      #1、response.encoding = 'utf-8'
      #2、通用的处理中文乱码的解决方案
　　　img_name = img_name.encode('iso-8859-1').decode('gbk')

import  requests

from lxml import etree

import os

#需求：爬取58二手房中的房源信息

if __name__ == '__main__':

    #爬取到页面源码数据

    url ="http://pic.netbian.com/4kmeinv/"

    # 进行UA伪装

    headers = {

        'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:77.0) Gecko/20100101 Firefox/77.0'

    }

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

    #response.encoding = 'utf-8'

    page_text = response.text

    #数据解析：src的属性值  alt属性

    tree = etree.HTML(page_text)

    li_list = tree.xpath('//div[@class="slist"]/ul/li')

    if not os.path.exists('./piclibs'):

        os.mkdir('./piclibs')

    for li in li_list:

        img_src = 'http://pic.netbian.com'+li.xpath('./a/img/@src')[0]

        img_name = li.xpath('./a/img/@alt')[0]+'.jpg'

        #通用的处理中文乱码的解决方案

        img_name = img_name.encode('iso-8859-1').decode('gbk')

        #print(img_name,img_src)

        #请求图片数据进行持久化存储

        img_data = requests.get(url=img_src,headers = headers).content

        img_path = 'piclibs/'+img_name

        with open(img_path,'wb') as fp:

            fp.write(img_data)

            print(img_name,'下载成功！！！')
3、全国城市 历史检测数据  https://www.aqistudy.cn/historydata/

import  requests

from lxml import etree

import os

#需求：解析出所有城市名称

if __name__ == '__main__':

    #爬取到页面源码数据

    url ="https://www.aqistudy.cn/historydata/"

    # 进行UA伪装

    headers = {

        'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:77.0) Gecko/20100101 Firefox/77.0'

    }

    page_text = requests.get(url =url,headers = headers).text

    tree = etree.HTML(page_text)

    #解析热门城市和所有城市对应的a标签

    # div[@class="bottom"]/ul/li/a  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

    all_city_names = []

    a_list = tree.xpath('//div[@class="bottom"]/ul/li/a | //div[@class="bottom"]/ul/div[2]/li/a')

    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))

4、获取简历 sc.chinaz.com 免费简历

巴特西

xpath实战

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