本文主要是介绍使用Xpath和Requests实现爬虫并存储在Excel表里，希望对大家解决编程问题提供一定的参考价值，需要的开发者们随着小编来一起学习吧！
爬的是杭州近期的的新房价
# encoding: utf-8
"""
@author: Ruvik
@software: PyCharm
@file: Spider_House.py
@time: 2020/7/9 20:12
"""# 爬一下链家网上杭州新房的价格
import requests # 进行网络请求
import xlwt # 与excel相关的操作
from lxml import etree # 引入xpath库，方便定位元素
import time # 进行访问频率控制
import random # 随机数生成
import re # 正则表达式# 主程序
def main():base_url = "https://hz.fang.lianjia.com/loupan/pg" # 最基本的网址，后续会根据这个进行翻页操作Savepath = ".\\杭州新房价.xls" # 存储路径datalist = getdata(base_url)savedata(datalist, Savepath)# 获取html源码
def ask_url(url):html=""headers={ # 进行伪装，防止416错误，模拟浏览器头部信息，向豆瓣服务器发送消息"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/83.0.4103.116 Safari/537.36"}try:response = requests.get(url,headers=headers,timeout=10) # 用户代理，表示告诉豆瓣服务器，我们是什么类型的机器、浏览器（本质上是告诉浏览器，我们可以接收什么水平的文件内容）time.sleep(random.randint(3, 6)) # 每隔3-6s执行一次请求# print(response.status_code)html = response.content # 获取网页的html源代码# print(html)print("请求访问成功")except requests.exceptions.RequestException as e:print("超时")print(e)return html# 从html源码中获取信息
def getdata(baseurl):Datalist = [] # 用来存储已经经过处理的信息for i in range(1, 100): # 在1-100页内爬取房价的信息url = baseurl+str(i) # 拼接url网址，进行换页# print(url)data = ask_url(url) # 获取到源代码# 从源代码中提取信息if data != "":html_data = etree.HTML(data)div_list = html_data.xpath('//div[@class="resblock-desc-wrapper"]')# print(len(div_list))for item in div_list:data_item = []# 提取详情链接link = "https://hz.fang.lianjia.com"link += item.xpath('./div/a/@href')[0]data_item.append(link)# print(link)# 提取名字name = item.xpath("./div/a/text()")[0]data_item.append(name)# print(name)# 提取地址loc = item.xpath('./div[@class="resblock-location"]/span/text()')location = loc[0] +"|"+ loc[1] +"|"+ item.xpath('./div[@class="resblock-location"]/a/text()')[0]data_item.append(location)# print(location)# 提取户型room = item.xpath('./a[@class="resblock-room"]/span/text()')rooms = ""for k in range(len(room)):if k < len(room) - 1:rooms += str(room[k]) + "|"else:rooms += str(room[k])# print(rooms)data_item.append(rooms)# 提取大小size = item.xpath('./div[@class="resblock-area"]/span/text()')if len(size) != 0:data_item.append(size[0])# print(size[0])else:data_item.append(" ")# 提取标签tag = item.xpath('./div[@class="resblock-tag"]/span/text()')tags = ""for k in range(len(tag)):if k < len(tag)-1:tags += str(tag[k]) + "|"else:tags += str(tag[k])# print(tags)data_item.append(tags)# 提取价格Price = ""price = item.xpath('./div[@class="resblock-price"]/div/span/text()')for k in range(len(price)):Price += price[k]Price = re.sub('\xa0', "", Price) # 去掉“\xa0”字符# print(Price)data_item.append(Price)Datalist.append(data_item)print(len(Datalist))return Datalist# 将html获取的信息存入Excel表格中def savedata(Datalist,Savapath):col = ("链接", "名字", "地址", "户型", "大小", "标签", "价格") # Excel的表头house_list = xlwt.Workbook(encoding="utf-8", style_compression=0) # 创建workbook对象worksheet = house_list.add_sheet("HouseList", cell_overwrite_ok=True) # 新建工作区，设为可覆盖for i in range(0, 7): # 写入表头worksheet.write(0, i, col[i])for i in range(0, 990): # 写入数据print("正在写入第%d条数据" % (i + 1))item = Datalist[i]for j in range(0, 7):worksheet.write(i + 1, j, item[j])house_list.save(Savapath) # 存储# 程序从这里开始执行
if __name__ == "__main__":main()print("爬取完毕!")
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