Python爬虫之爬取我爱我家二手房数据

一、问题说明

首先，运行下述代码，复现问题：

# -*-coding:utf-8-*-
import re
import requests
from bs4 import BeautifulSoup

cookie = 'PHPSESSID=aivms4ufg15sbrj0qgboo3c6gj; HMF_CI=4d8ff20092e9832daed8fe5eb0475663812603504e007aca93e6630c00b84dc207; _ga=GA1.2.556271139.1620784679; gr_user_id=4c878c8f-406b-46a0-86ee-a9baf2267477; _dx_uzZo5y=68b673b0aaec1f296c34e36c9e9d378bdb2050ab4638a066872a36f781c888efa97af3b5; smidV2=20210512095758ff7656962db3adf41fa8fdc8ddc02ecb00bac57209becfaa0; yfx_c_g_u_id_10000001=_ck21051209583410015104784406594; __TD_deviceId=41HK9PMCSF7GOT8G; zufang_cookiekey=["%7B%22url%22%3A%22%2Fzufang%2F_%25E9%2595%25BF%25E6%2598%25A5%25E6%25A1%25A5%3Fzn%3D%25E9%2595%25BF%25E6%2598%25A5%25E6%25A1%25A5%22%2C%22x%22%3A%220%22%2C%22y%22%3A%220%22%2C%22name%22%3A%22%E9%95%BF%E6%98%A5%E6%A1%A5%22%2C%22total%22%3A%220%22%7D","%7B%22url%22%3A%22%2Fzufang%2F_%25E8%258B%258F%25E5%25B7%259E%25E8%25A1%2597%3Fzn%3D%25E8%258B%258F%25E5%25B7%259E%25E8%25A1%2597%22%2C%22x%22%3A%220%22%2C%22y%22%3A%220%22%2C%22name%22%3A%22%E8%8B%8F%E5%B7%9E%E8%A1%97%22%2C%22total%22%3A%220%22%7D","%7B%22url%22%3A%22%2Fzufang%2F_%25E8%258B%258F%25E5%25B7%259E%25E6%25A1%25A5%3Fzn%3D%25E8%258B%258F%25E5%25B7%259E%25E6%25A1%25A5%22%2C%22x%22%3A%220%22%2C%22y%22%3A%220%22%2C%22name%22%3A%22%E8%8B%8F%E5%B7%9E%E6%A1%A5%22%2C%22total%22%3A%220%22%7D"]; ershoufang_cookiekey=["%7B%22url%22%3A%22%2Fzufang%2F_%25E9%2595%25BF%25E6%2598%25A5%25E6%25A1%25A5%3Fzn%3D%25E9%2595%25BF%25E6%2598%25A5%25E6%25A1%25A5%22%2C%22x%22%3A%220%22%2C%22y%22%3A%220%22%2C%22name%22%3A%22%E9%95%BF%E6%98%A5%E6%A1%A5%22%2C%22total%22%3A%220%22%7D","%7B%22url%22%3A%22%2Fershoufang%2F_%25E8%258B%258F%25E5%25B7%259E%25E6%25A1%25A5%3Fzn%3D%25E8%258B%258F%25E5%25B7%259E%25E6%25A1%25A5%22%2C%22x%22%3A%220%22%2C%22y%22%3A%220%22%2C%22name%22%3A%22%E8%8B%8F%E5%B7%9E%E6%A1%A5%22%2C%22total%22%3A%220%22%7D"]; zufang_BROWSES=501465046,501446051,90241951,90178388,90056278,90187979,501390110,90164392,90168076,501472221,501434480,501480593,501438374,501456072,90194547,90223523,501476326,90245144; historyCity=["\u5317\u4eac"]; _gid=GA1.2.23153704.1621410645; Hm_lvt_94ed3d23572054a86ed341d64b267ec6=1620784715,1621410646; _Jo0OQK=4958FA78A5CC420C425C480565EB46670E81832D8173C5B3CFE61303A51DE43E320422D6C7A15892C5B8B66971ED1B97A7334F0B591B193EBECAAB0E446D805316B26107A0B847CA53375B268E06EC955BB75B268E06EC955BB9D992FB153179892GJ1Z1OA==; ershoufang_BROWSES=501129552; domain=bj; 8fcfcf2bd7c58141_gr_session_id=61676ce2-ea23-4f77-8165-12edcc9ed902; 8fcfcf2bd7c58141_gr_session_id_61676ce2-ea23-4f77-8165-12edcc9ed902=true; yfx_f_l_v_t_10000001=f_t_1620784714003__r_t_1621471673953__v_t_1621474304616__r_c_2; Hm_lpvt_94ed3d23572054a86ed341d64b267ec6=1621475617'
headers = {
    'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/90.0.4430.72 Safari/537.36',
    'Cookie': cookie.encode("utf-8").decode("latin1")
}

def run():
    base_url = 'https://bj.5i5j.com/ershoufang/xichengqu/n%d/'
    for page in range(1, 11):
        url = base_url % page
        print(url)
        html = requests.get(url, headers=headers).text
        soup = BeautifulSoup(html, 'lxml')
        try:
            for li in soup.find('div', class_='list-con-box').find('ul', class_='pList').find_all('li'):
                title = li.find('h3', class_='listTit').get_text()  # 名称
                # print(title)
        except Exception as e:
            print(e)
            print(html)
            break

if __name__ == '__main__':
    run()

运行后会发现，在抓取https://bj.5i5j.com/ershoufang/xichengqu/n1/(也可能是其他页码)时，会报错：'NoneType' object has no attribute 'find'，观察输出的html信息，可以发现html内容为：<HTML><HEAD><script>window.location.href="https://bj.5i5j.com/ershoufang/xichengqu/n1/?wscckey=0f36b400da92f41d_1621823822" rel="external nofollow" ;</script></HEAD><BODY>，但此链接在浏览器访问是可以看到数据的，但链接会被重定向，重定向后的url即为上面这个html的href内容。因此，可以合理的推断，针对部分页码链接，我爱我家不会直接返回数据，但会返回带有正确链接的信息，通过正则表达式获取该链接即可正确抓取数据。

二、解决方法

在下面的完整代码中，采取的解决方法是：

1.首先判断当前html是否含有数据

2.若无数据，则通过正则表达式获取正确链接

3.重新获取html数据

if '<HTML><HEAD><script>window.location.href=' in html:
	url = re.search(r'.*?href="(.+)" rel="external nofollow"  rel="external nofollow" .*?', html).group(1)
	html = requests.get(url, headers=headers).text

三、完整代码

# -*-coding:utf-8-*-
import os
import re
import requests
import csv
import time
from bs4 import BeautifulSoup

folder_path = os.path.split(os.path.abspath(__file__))[0] + os.sep  # 获取当前文件所在目录
cookie = 'PHPSESSID=aivms4ufg15sbrj0qgboo3c6gj; HMF_CI=4d8ff20092e9832daed8fe5eb0475663812603504e007aca93e6630c00b84dc207; _ga=GA1.2.556271139.1620784679; gr_user_id=4c878c8f-406b-46a0-86ee-a9baf2267477; _dx_uzZo5y=68b673b0aaec1f296c34e36c9e9d378bdb2050ab4638a066872a36f781c888efa97af3b5; smidV2=20210512095758ff7656962db3adf41fa8fdc8ddc02ecb00bac57209becfaa0; yfx_c_g_u_id_10000001=_ck21051209583410015104784406594; __TD_deviceId=41HK9PMCSF7GOT8G; zufang_cookiekey=["%7B%22url%22%3A%22%2Fzufang%2F_%25E9%2595%25BF%25E6%2598%25A5%25E6%25A1%25A5%3Fzn%3D%25E9%2595%25BF%25E6%2598%25A5%25E6%25A1%25A5%22%2C%22x%22%3A%220%22%2C%22y%22%3A%220%22%2C%22name%22%3A%22%E9%95%BF%E6%98%A5%E6%A1%A5%22%2C%22total%22%3A%220%22%7D","%7B%22url%22%3A%22%2Fzufang%2F_%25E8%258B%258F%25E5%25B7%259E%25E8%25A1%2597%3Fzn%3D%25E8%258B%258F%25E5%25B7%259E%25E8%25A1%2597%22%2C%22x%22%3A%220%22%2C%22y%22%3A%220%22%2C%22name%22%3A%22%E8%8B%8F%E5%B7%9E%E8%A1%97%22%2C%22total%22%3A%220%22%7D","%7B%22url%22%3A%22%2Fzufang%2F_%25E8%258B%258F%25E5%25B7%259E%25E6%25A1%25A5%3Fzn%3D%25E8%258B%258F%25E5%25B7%259E%25E6%25A1%25A5%22%2C%22x%22%3A%220%22%2C%22y%22%3A%220%22%2C%22name%22%3A%22%E8%8B%8F%E5%B7%9E%E6%A1%A5%22%2C%22total%22%3A%220%22%7D"]; ershoufang_cookiekey=["%7B%22url%22%3A%22%2Fzufang%2F_%25E9%2595%25BF%25E6%2598%25A5%25E6%25A1%25A5%3Fzn%3D%25E9%2595%25BF%25E6%2598%25A5%25E6%25A1%25A5%22%2C%22x%22%3A%220%22%2C%22y%22%3A%220%22%2C%22name%22%3A%22%E9%95%BF%E6%98%A5%E6%A1%A5%22%2C%22total%22%3A%220%22%7D","%7B%22url%22%3A%22%2Fershoufang%2F_%25E8%258B%258F%25E5%25B7%259E%25E6%25A1%25A5%3Fzn%3D%25E8%258B%258F%25E5%25B7%259E%25E6%25A1%25A5%22%2C%22x%22%3A%220%22%2C%22y%22%3A%220%22%2C%22name%22%3A%22%E8%8B%8F%E5%B7%9E%E6%A1%A5%22%2C%22total%22%3A%220%22%7D"]; zufang_BROWSES=501465046,501446051,90241951,90178388,90056278,90187979,501390110,90164392,90168076,501472221,501434480,501480593,501438374,501456072,90194547,90223523,501476326,90245144; historyCity=["\u5317\u4eac"]; _gid=GA1.2.23153704.1621410645; Hm_lvt_94ed3d23572054a86ed341d64b267ec6=1620784715,1621410646; _Jo0OQK=4958FA78A5CC420C425C480565EB46670E81832D8173C5B3CFE61303A51DE43E320422D6C7A15892C5B8B66971ED1B97A7334F0B591B193EBECAAB0E446D805316B26107A0B847CA53375B268E06EC955BB75B268E06EC955BB9D992FB153179892GJ1Z1OA==; ershoufang_BROWSES=501129552; domain=bj; 8fcfcf2bd7c58141_gr_session_id=61676ce2-ea23-4f77-8165-12edcc9ed902; 8fcfcf2bd7c58141_gr_session_id_61676ce2-ea23-4f77-8165-12edcc9ed902=true; yfx_f_l_v_t_10000001=f_t_1620784714003__r_t_1621471673953__v_t_1621474304616__r_c_2; Hm_lpvt_94ed3d23572054a86ed341d64b267ec6=1621475617'
headers = {
    'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/90.0.4430.72 Safari/537.36',
    'Cookie': cookie.encode("utf-8").decode("latin1")
}

def get_page(url):
    """获取网页原始数据"""
    global headers
    html = requests.get(url, headers=headers).text
    return html

def extract_info(html):
    """解析网页数据，抽取出房源相关信息"""
    host = 'https://bj.5i5j.com'
    soup = BeautifulSoup(html, 'lxml')
    data = []
    for li in soup.find('div', class_='list-con-box').find('ul', class_='pList').find_all('li'):
        try:
            title = li.find('h3', class_='listTit').get_text()  # 名称
            url = host + li.find('h3', class_='listTit').a['href']  # 链接
            info_li = li.find('div', class_='listX')  # 每个房源核心信息都在这里
            p1 = info_li.find_all('p')[0].get_text()  # 获取第一段
            info1 = [i.strip() for i in p1.split('  ·  ')]
            # 户型、面积、朝向、楼层、装修、建成时间
            house_type, area, direction, floor, decoration, build_year = info1
            p2 = info_li.find_all('p')[1].get_text()  # 获取第二段
            info2 = [i.replace(' ', '') for i in p2.split('·')]
            # 小区、位于几环、交通信息
            if len(info2) == 2:
                residence, ring = info2
                transport = ''  # 部分房源无交通信息
            elif len(info2) == 3:
                residence, ring, transport = info2
            else:
                residence, ring, transport = ['', '', '']
            p3 = info_li.find_all('p')[2].get_text()  # 获取第三段
            info3 = [i.replace(' ', '') for i in p3.split('·')]
            # 关注人数、带看次数、发布时间
            try:
                watch, arrive, release_year = info3
            except Exception as e:
                print(info2, '获取带看、发布日期信息出错')
                watch, arrive, release_year = ['', '', '']
            total_price = li.find('p', class_='redC').get_text().strip()  # 房源总价
            univalence = li.find('div', class_='jia').find_all('p')[1].get_text().replace('单价', '')  # 房源单价
            else_info = li.find('div', class_='listTag').get_text()
            data.append([title, url, house_type, area, direction, floor, decoration, residence, ring,
                         transport, total_price, univalence, build_year, release_year, watch, arrive, else_info])
        except Exception as e:
            print('extract_info: ', e)
    return data

def crawl():
    esf_url = 'https://bj.5i5j.com/ershoufang/'  # 主页网址
    fields = ['城区', '名称', '链接', '户型', '面积', '朝向', '楼层', '装修', '小区', '环', '交通情况', '总价', '单价',
              '建成时间', '发布时间', '关注', '带看', '其他信息']
    f = open(folder_path + 'data' + os.sep + '北京二手房-我爱我家.csv', 'w', newline='', encoding='gb18030')
    writer = csv.writer(f, delimiter=',')  # 以逗号分割
    writer.writerow(fields)
    page = 1
    regex = re.compile(r'.*?href="(.+)" rel="external nofollow"  rel="external nofollow" .*?')
    while True:
        url = esf_url + 'n%s/' % page  # 构造页面链接
        if page == 1:
            url = esf_url
        html = get_page(url)
        # 部分页面链接无法获取数据，需进行判断，并从返回html内容中获取正确链接，重新获取html
        if '<HTML><HEAD><script>window.location.href=' in html:
            url = regex.search(html).group(1)
            html = requests.get(url, headers=headers).text
        print(url)
        data = extract_info(html)
        if data:
            writer.writerows(data)
        page += 1
    f.close()

if __name__ == '__main__':
    crawl()  # 启动爬虫

四、数据展示

截至2021年5月23日，共获取数据62943条，基本上将我爱我家官网上北京地区的二手房数据全部抓取下来了。

到此这篇关于Python爬虫之爬取我爱我家二手房数据的文章就介绍到这了,更多相关Python爬取二手房数据内容请搜索我们以前的文章或继续浏览下面的相关文章希望大家以后多多支持我们！

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