https://sjz.lianjia.com/zufang/pg1/
https://sjz.lianjia.com/zufang/pg2/
https://sjz.lianjia.com/zufang/pg3/
https://sjz.lianjia.com/zufang/pg4/
https://sjz.lianjia.com/zufang/pg5/
...
https://sjz.lianjia.com/zufang/pg80/

self._ua = UserAgent()
self._headers = {"User-Agent": self._ua.random}  # 调用一个随机的UA

from fake_useragent import UserAgent
from lxml import etree
import asyncio
import aiohttp
import pandas as pdclass LianjiaSpider(object):def __init__(self):self._ua = UserAgent()self._headers = {"User-Agent": self._ua.random}self._data = list()async def get(self,url):async with aiohttp.ClientSession() as session:try:async with session.get(url,headers=self._headers,timeout=3) as resp:if resp.status==200:result = await resp.text()return resultexcept Exception as e:print(e.args)async def parse_html(self):for page in range(1,77):url = "https://sjz.lianjia.com/zufang/pg{}/".format(page)print("正在爬取{}".format(url))html = await self.get(url)   # 获取网页内容html = etree.HTML(html)  # 解析网页self.parse_page(html)   # 匹配我们想要的数据print("正在存储数据....")######################### 数据写入data = pd.DataFrame(self._data)data.to_csv("链家网租房数据.csv", encoding='utf_8_sig')   # 写入文件######################### 数据写入def run(self):loop = asyncio.get_event_loop()tasks = [asyncio.ensure_future(self.parse_html())]loop.run_until_complete(asyncio.wait(tasks))if __name__ == '__main__':l = LianjiaSpider()l.run()

def parse_page(self,html):info_panel = html.xpath("//div[@class='info-panel']")for info in info_panel:region = self.remove_space(info.xpath(".//span[@class='region']/text()"))zone = self.remove_space(info.xpath(".//span[@class='zone']/span/text()"))meters = self.remove_space(info.xpath(".//span[@class='meters']/text()"))where = self.remove_space(info.xpath(".//div[@class='where']/span[4]/text()"))con = info.xpath(".//div[@class='con']/text()")floor = con[0]  # 楼层type = con[1]   # 样式
agent = info.xpath(".//div[@class='con']/a/text()")[0]has = info.xpath(".//div[@class='left agency']//text()")price = info.xpath(".//div[@class='price']/span/text()")[0]price_pre =  info.xpath(".//div[@class='price-pre']/text()")[0]look_num = info.xpath(".//div[@class='square']//span[@class='num']/text()")[0]one_data = {"region":region,"zone":zone,"meters":meters,"where":where,"louceng":floor,"type":type,"xiaoshou":agent,"has":has,"price":price,"price_pre":price_pre,"num":look_num}self._data.append(one_data)  # 添加数据