基于bs4+requests的蓝房网爬虫
2018-01-29 本文已影响27人
潇洒坤
1.代码可以直接运行,请下载anaconda并安装,用spyder方便查看变量
或者可以查看生成的excel文件
2.依赖库,命令行运行(WIN10打开命令行快捷键:windows+x组合键,然后按a键):
pip install BeautifulSoup4
pip install requests
3.爬取的网站是蓝房网(厦门),可以进入http://house.lanfw.com/xm/search-y1/进行观察
4.关于如何判断代码是python2还是python3,print('')为python3,print ''为python2
简而言之就是print需要用括号的就是python3,下面代码如是。
5.爬取53个页面并进行解析,程序运行后需要等待大概30秒
# -*- coding: utf-8 -*-
"""
Created on Mon Jan 15 21:35:52 2018
@author: Steven Lei
"""
def getHousesDetails(url):
from bs4 import BeautifulSoup
import requests
request = requests.get(url)
request.encoding = 'utf-8'
soup = BeautifulSoup(request.text,'lxml')
houses = soup.select('.lpList')
housesDetails = []
for house in houses:
#获取楼盘名字
houseName = house.select('.title h2 a')[0].text
#获取楼盘地址
address = house.select('.lpTxt div')[1].select('p')[1].text.strip('楼盘地址: 查看地图')
if(len(address) >= 16):
houseDetailHref = house.select('.title h2 a')[0]['href']
request = requests.get(houseDetailHref)
request.encoding = 'utf-8'
soup = BeautifulSoup(request.text,'lxml')
address = soup.select('.toplpMsg ul li div i')[0].text.strip('楼盘地址:')
#获取楼盘开盘时间
openTime = house.select('.lpTxt div')[1].select('p')[3].text.strip('开盘时间:')
#获取楼盘价格
price = house.select('.price p b')[0].text
#获取楼盘销售状态
def numberToString(number):
switcher = {
1: "在售",
3: "尾盘",
5: "未售",
15: "售罄"
}
return switcher.get(number,'未知')
saleStatusImg = house.select('.title p img')[0]['src']
saleStatusId = int(saleStatusImg.lstrip('/public/images/state_').rstrip('.jpg'))
saleStatus = numberToString(saleStatusId)
#将所有楼盘信息做成楼盘信息字典
houseDetails = {}
houseDetails['houseName'] = houseName
houseDetails['address'] = address
houseDetails['openTime'] = openTime
houseDetails['price'] = price
houseDetails['saleStatus'] = saleStatus
housesDetails.append(houseDetails)
return housesDetails
def getAllHousesDetails():
maxPageNumber = 54
urlBefore = 'http://house.lanfw.com/xm/search-y{}'
allHousesDetails = []
for i in range(1,maxPageNumber+1):
url = urlBefore.format(i)
allHousesDetails.extend(getHousesDetails(url))
import pandas
dataframe = pandas.DataFrame(allHousesDetails)
return dataframe
if __name__ == '__main__':
allHousesDetails = getAllHousesDetails()
allHousesDetails.to_excel('houseDetails2.xlsx')