前言:对于我们任何一个漂泊在外的打工者,租房似乎都是我们必经的一个经历,对于我们而言,选择性价比最高,最适合自己的房源至关重要,本文就将利用爬虫技术采集蘑菇租房网上指定的房源信息,后续可以利用这些信息进行机器筛选,比价等等,从而更加方便的找到自己心仪的房源。
爬虫第一步,找到目标网站,确定数据来源,我们打开蘑菇租房网,可以看到如下所示的界面
同样的,我们打开F12,查看network请求,可以看到它的数据直接在这个接口里返回的
分析网页,发现我们可以直接采用requests库请求获取网页数据,然后通过etree解析网页资源,获取我们想要的数据
首先是获取列表页的数据
page = self.getPageCount()
# page = 1
page_link = self.pageurl.replace('@position',str(13))
print(page)
for offset in range(page):
# 拼接URL
pageUrl = page_link.replace('@page',str(offset))
print(pageUrl)
# 通过requests获取数据
response = requests.get(url=pageUrl,headers=get_header())
print(response.text)
# html=response.content
# html_doc=str(html,'utf-8')
# 通过etree解析文档
tree = etree.HTML(response.text)
# 通过xpath提取链接
links = tree.xpath('//div[@class="roomCardSmall-box"]//a/@href')
print(links)
names = tree.xpath('//div[@class="roomCardSmall-box"]//a/@title')
types = tree.xpath('//div[@class="roomCardSmall-box"]//a//div[@class="text-content-middle"]//h2[1]/text()')
desps = tree.xpath('//div[@class="roomCardSmall-box"]//a//div[@class="text-content-middle"]//h2[2]/text()')
positions = tree.xpath('//div[@class="roomCardSmall-box"]//a//div[@class="text-content-middle"]//p/text()')
因为列表页包含分页,所以需要先行获取分页数
def getPageCount(self):
req = requests.get(self.baseUrl,headers=get_header())
print(req.text)
tree = etree.HTML(req.text)
# 通过xpath提取链接
page = tree.xpath('//div[@class="pageBox"]/div[@class="page-box"]/span/text()')
if(len(page)>0):
return int(page[0][1:3])
else:
return 0
获取到列表页数据后,我们可以提取详情页的链接地址,对详情页的地址发起请求,获取并解析详情页的数据
for i in range(len(links)):
item = {}
item['name'] = names[i]
item['type'] = types[i]
item['desp'] = desps[i]
item['position'] = positions[i]
link = links[i]
req = requests.get(link,headers=get_header())
html_doc = str(req.content,'utf-8')
print(html_doc)
tree = etree.HTML(html_doc)
item['pay_type'] = tree.xpath('//div[@class="w460 price mt10"]/div[@class="info"]/span[@class="type"]/text()')[0]
item['pay_price'] = tree.xpath('//div[@class="w460 price mt10"]/div[@class="info"]/span[@class="num orange"]/text()')[0]
item['pay_price_unit'] = tree.xpath('//div[@class="w460 price mt10"]/div[@class="info"]/span[@class="num orange"]/i/text()')[0]
item['phone'] = tree.xpath('//div[@class="w460 room-call"]//div[@class="phone orange"]/text()')[0]
data.append(item)
time.sleep(random.random()*8)
time.sleep(random.random()*8)
注意此处,我进行了随机延时操作,这是为了避免被网站的反爬虫策略识别到
获取到数据后我们还是老规矩,保存到Excel或者数据库
# # 保存数据到excel文件
def saveToCsv(self,data):
wb = Workbook()
ws = wb.active
ws.append(['标题', '类型', '描述', '地理位置', '房租支付方式', '房租', '房租单位','手机号'])
for item in data:
line = [item['name'], item['type'],item['desp'],item['position'],item['pay_type'],item['pay_price'],item['pay_price_unit'],item['phone']]
ws.append(line)
wb.save('蘑菇租房_上海.xlsx')
至此,整个爬虫工作就算完成了,完整的代码如下,需要的自取,请记得安装第三方库如lxml
,下篇文章我将介绍利用浏览器的插件进行无编程的爬虫
import requests
from lxml import etree
from openpyxl import Workbook
from myutils import get_header
from selenium import webdriver
from selenium.webdriver.common.by import By
import time
import random
# 爬虫处理类
# 目标网站 蘑菇租房:http://www.mgzf.com/list/qy13_
class Spider:
# 目标网站列表页的基本链接
baseUrl = 'http://www.mgzf.com/list/qy@position_'
pageurl = 'http://www.mgzf.com/list/pg@page/qy@position_/?searchWord=&paraName='
# 自定义的header
# 爬取的页数总和
def getPageCount(self):
req = requests.get(self.baseUrl,headers=get_header())
print(req.text)
tree = etree.HTML(req.text)
# 通过xpath提取链接
page = tree.xpath('//div[@class="pageBox"]/div[@class="page-box"]/span/text()')
if(len(page)>0):
return int(page[0][1:3])
else:
return 0
def buffer(self,browser):
for i in range(50):
time.sleep(0.3)
browser.execute_script('window.scrollBy(0,300)', '')
def getDataByBrowswer(self):
data = []
print('开始爬虫')
browser = webdriver.Chrome('C://Users/Administrator/AppData/Local/Google/Chrome/Application/chromedriver.exe')
page_link = self.pageurl.replace('@position',str(13))
page = 1
for offset in range(page):
pageUrl = page_link.replace('@page',str(offset+1))
browser.get(pageUrl)
time.sleep(30)
self.buffer(browser)
links = browser.find_elements_by_xpath('//div[@class="roomCardSmall-box"]//a')
types = browser.find_elements_by_xpath('//div[@class="roomCardSmall-box"]//a//div[@class="text-content-middle"]//h2[1]')
desps = browser.find_elements_by_xpath('//div[@class="roomCardSmall-box"]//a//div[@class="text-content-middle"]//h2[2]')
positions = browser.find_elements_by_xpath('//div[@class="roomCardSmall-box"]//a//div[@class="text-content-middle"]//p')
for i in range(len(links)):
item = {}
link = links[i].get_attribute('href')
item['name'] = links[i].text
item['type'] = types[i].text
item['desp'] = desps[i].text
item['position'] = positions[i].text
browser.get(link)
time.sleep(30)
self.buffer(browser)
item['pay_type'] = browser.find_element_by_xpath('//div[@class="w460 price mt10"]/div[@class="info"]/span[@class="type"]').text
item['pay_price'] = browser.find_element_by_xpath('//div[@class="w460 price mt10"]/div[@class="info"]/span[@class="num orange"]').text
item['pay_price_unit'] = browser.find_element_by_xpath('//div[@class="w460 price mt10"]/div[@class="info"]/span[@class="num orange"]/i').text
item['phone'] = browser.find_element_by_xpath('//div[@class="w460 room-call"]//div[@class="phone orange"]').text
data.append(item)
print(data)
browser.close()
return data
# 列表页处理函数、批量获取详情页链接地址
def getData(self):
data = []
print('开始爬虫')
page = self.getPageCount()
# page = 1
page_link = self.pageurl.replace('@position',str(13))
print(page)
for offset in range(page):
# 拼接URL
pageUrl = page_link.replace('@page',str(offset))
print(pageUrl)
# 通过requests获取数据
response = requests.get(url=pageUrl,headers=get_header())
print(response.text)
# html=response.content
# html_doc=str(html,'utf-8')
# 通过etree解析文档
tree = etree.HTML(response.text)
# 通过xpath提取链接
links = tree.xpath('//div[@class="roomCardSmall-box"]//a/@href')
print(links)
names = tree.xpath('//div[@class="roomCardSmall-box"]//a/@title')
types = tree.xpath('//div[@class="roomCardSmall-box"]//a//div[@class="text-content-middle"]//h2[1]/text()')
desps = tree.xpath('//div[@class="roomCardSmall-box"]//a//div[@class="text-content-middle"]//h2[2]/text()')
positions = tree.xpath('//div[@class="roomCardSmall-box"]//a//div[@class="text-content-middle"]//p/text()')
for i in range(len(links)):
item = {}
item['name'] = names[i]
item['type'] = types[i]
item['desp'] = desps[i]
item['position'] = positions[i]
link = links[i]
req = requests.get(link,headers=get_header())
html_doc = str(req.content,'utf-8')
print(html_doc)
tree = etree.HTML(html_doc)
item['pay_type'] = tree.xpath('//div[@class="w460 price mt10"]/div[@class="info"]/span[@class="type"]/text()')[0]
item['pay_price'] = tree.xpath('//div[@class="w460 price mt10"]/div[@class="info"]/span[@class="num orange"]/text()')[0]
item['pay_price_unit'] = tree.xpath('//div[@class="w460 price mt10"]/div[@class="info"]/span[@class="num orange"]/i/text()')[0]
item['phone'] = tree.xpath('//div[@class="w460 room-call"]//div[@class="phone orange"]/text()')[0]
data.append(item)
time.sleep(random.random()*8)
time.sleep(random.random()*8)
return data
# # 保存数据到excel文件
def saveToCsv(self,data):
wb = Workbook()
ws = wb.active
ws.append(['标题', '类型', '描述', '地理位置', '房租支付方式', '房租', '房租单位','手机号'])
for item in data:
line = [item['name'], item['type'],item['desp'],item['position'],item['pay_type'],item['pay_price'],item['pay_price_unit'],item['phone']]
ws.append(line)
wb.save('蘑菇租房_上海.xlsx')
# # 开始爬虫
def startSpider(self):
data = self.getData()
self.saveToCsv(data)
# data = self.getDataByBrowswer()
# self.saveToCsv(data)
if __name__ == "__main__":
spider = Spider()
spider.startSpider()