前言：之前是写了链家的爬虫，但是实际看下来数据质量不是特别好，所以想把房天下的小区数据也爬下来看看怎么样，但是实际爬取中，发现房天下的反爬技术要稍高一点，目前碰到的有：
1、自动检测ip地址，在正常网页中会跳转到新地址，request没办法，不过可以解析新地址并返回后重新连接，问题不大；
2、不同页面的布局也会不一样，这个目前没有好的解决办法，我目前是用try except来判断；
3、如果速度太快的话会ban ip，这个通过分布式爬虫或者自动换ip可以解决，不过我这次的代码里还没改；
import requests
from bs4 import BeautifulSoup
import re
import openpyxl
from math import radians, cos, sin, asin, sqrt
import pandas as pd
import numpy as np
import json
import math
from urllib.request import urlopen, quote
headers = {
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/69.0.3497.100 Safari/537.36',
'cookie': 'global_cookie=ndhzo4i3v9myct7aqau6zp6si10k0ncoeps; __utmz=147393320.1568695301.1.1.utmcsr=shbbs.fang.com|utmccn=(referral)|utmcmd=referral|utmcct=/esf~-1/538150834_538150842.htm; __utma=147393320.1476417876.1568695301.1568695301.1568771948.2; __utmc=147393320; Captcha=434D58793841766F7637624862786B682B684D4B454431767946477634343578436B6978474361474C45335739576D5139355553557463676C6150554F45377962612B456F624974536F383D; newhouse_user_guid=35B671E8-BF35-888C-AC78-ED09FB6489C8; newhouse_chat_guid=3262F18D-7EFB-AE4D-CC6E-D47888369019; g_sourcepage=esf_xq%5Elb_pc; __utmt_t0=1; __utmt_t1=1; __utmt_t2=1; unique_cookie=U_7eu0ocfmua6k7nyn858kd6mb727k0omb896*20; __utmb=147393320.60.10.1568771948'
}
'''第一步：爬取小区信息'''
def export_communityInfo(xiaoquInfo_dict):
'''导出小区信息'''
with open('浦东地区小区信息.txt', 'a', encoding='utf-8') as file:
file.write('||'.join(xiaoquInfo_dict.values()))
file.write('\n')
def get_true_url(old_url):
'''获得正确的url'''
# print(old_url)
r = requests.get(url=old_url, headers=headers)
if r'<title>跳转...</title>' in r.text:
soup = BeautifulSoup(r.text, 'lxml')
new_url = soup.find(name='a', attrs={'class': 'btn-redir'}).attrs['href']
return new_url
return old_url
# print(get_true_url('https://liananxilu35nong.fang.com'))
def get_region_dict():
'''获得浦东地区不同区域的url和名称，以字典形式输出'''
url = r"https://sh.esf.fang.com/housing/25__0_0_0_0_1_0_0_0/"
true_url = get_true_url(url)
r = requests.get(url=true_url, headers=headers)
soup = BeautifulSoup(r.text, 'lxml')
a = soup.find(name='p', attrs={'id': 'shangQuancontain', 'class': 'contain'})
pudong_dict = {}
for i in a.find_all(name='a'):
if i.string != '不限':
pudong_dict[i.string] = r"https://sh.esf.fang.com" + i.attrs['href']
return pudong_dict
def get_region_url(old_url):
'''获得这个区域的其它page_url'''
# url = r'https://sh.esf.fang.com/housing/25_1646_0_0_0_0_1_0_0_0/'
true_url = get_true_url(old_url)
r = requests.get(url=true_url, headers=headers)
soup = BeautifulSoup(r.text, 'lxml')
page_url = soup.find(name='div', attrs={'class': 'fanye gray6'})
page_url_list = []
page_url_list.append(old_url)
for j in page_url.find_all(name='a'):
if 'href' in j.attrs:
temp_url = r'https://sh.esf.fang.com/' + j.attrs['href'][1:]
page_url_list.append(temp_url)
page_urls = set(page_url_list)
return page_urls
def get_xiaoqu_url(old_url):
'''获得某区域某一页的小区信息和url'''
# old_url = r'https://sh.esf.fang.com/housing/25_5920_0_0_0_0_1_0_0_0/'
true_url = get_true_url(old_url)
r = requests.get(url=true_url, headers=headers)
soup = BeautifulSoup(r.text, 'lxml')
xiaoqu_url_dict = {}
for i in soup.find_all(name='a', attrs={'class': 'plotTit', 'target': '_blank'}):
xiaoqu_name = i.string
xiaoqu_url = 'https:/' + i.attrs['href'][1:]
xiaoqu_url_dict[xiaoqu_name] = xiaoqu_url
# print('{}的url是{}'.format(xiaoqu_name, xiaoqu_url))
return xiaoqu_url_dict
def get_xiaoqu_info(key, xiaoqu_name, old_url):
'''获得小区的有用信息'''
useful_dict = {'地区': '', '小区名称': '', '均价': '', '建筑年代': '', '建筑类型': '', '房屋总数': '', '小区位置': '', '楼栋总数': '', '物业公司': '', '开发商': ''}
# old_url = r'https://jinqinyuan.fang.com/'
try:
true_url = get_true_url(old_url)
r = requests.get(url=true_url, headers=headers)
r.encoding = 'gb2312'
soup = BeautifulSoup(r.text, 'lxml')
xiaoqu_price = soup.find(name='span', attrs={'class': 'prib'}).string
useful_dict['地区'] = key
useful_dict['小区名称'] = xiaoqu_name
if xiaoqu_price == '暂无均价':
print('{}无均价数据'.format(xiaoqu_name))
return 0
useful_dict['均价'] = xiaoqu_price
xiaoqu_info = soup.find(name='div', attrs={'class': 'Rinfolist'})
for info in xiaoqu_info.select('li'):
info = str(info)
if re.search('''<li.*?b>(.*?)<.*?/b>(.*?)</.*?''', info):
infos = re.search('''<li.*?b>(.*?)<.*?/b>(.*?)</.*?''', info)
temp_key = infos.group(1)
temp_value = infos.group(2)
if temp_key in useful_dict.keys():
useful_dict[temp_key] = temp_value
print('{}的信息已爬取'.format(xiaoqu_name))
return useful_dict
except:
return 0
def xiaoqu_pachong():
'''获取所有小区名字和链接'''
# 首先获取浦东地区所有区域的名称和url，比如：惠南: url1
pudong_dict = get_region_dict()
# print(pudong_dict)
#遍历每个分区
for key, value in pudong_dict.items():
print('开始{}的爬取：'.format(key))
region_urls = get_region_url(value) #先获得每个分区的所有子url
for page_url in region_urls:
xiaoqu_url_dict = get_xiaoqu_url(page_url) #获得每个页面的所有小区名称和url
for xiaoqu_name, xiaoqu_url in xiaoqu_url_dict.items():
# print(xiaoqu_name, xiaoqu_url)
useful_dict = get_xiaoqu_info(key, xiaoqu_name, xiaoqu_url)
if useful_dict:
export_communityInfo(useful_dict)
print('{}已爬取完毕'.format(key))
print('--------------------------------------------------------------------')
xiaoqu_pachong()
