[Python知识库]某房屋中介网站爬虫实例

• url: https://hangzhou.anjuke.com/community/
  相比较房天下, 只需要在请求头中加入cookie即可(不带cookie会被封ip)
  直接上代码：

from bs4 import BeautifulSoup
import requests
import re
import pandas as pd
import time
#需要杭州: 区域，地址，板块，房价，小区名，楼龄等信息
columns = ["名称", "竣工时间", "版块", "单价", "周边", "物业类型", "权属类别", "竣工时间", "产权年限", "总户数", "建筑面积", "容积率", "绿化率",
           "建筑类型", "所属商圈", "统一供暖", "供水供电", "停车位", "物业费", "停车费", "车位管理费", "物业公司", "小区地址", "开发商"]

headers = {
    'User-Agent':
    "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 \
            (KHTML, like Gecko) Chrome/98.0.4758.102 Safari/537.36",
    "cookie" : "你的cookie",
    "referer": "https://hangzhou.anjuke.com/community/"
}

def getUrl(URL):
    headers2 = {
    'User-Agent':
    "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 \
            (KHTML, like Gecko) Chrome/98.0.4758.102 Safari/537.36",
    "cookie" : "你的cookie",
    "referer": "https://hangzhou.anjuke.com/community/"
}
    re2 = requests.get(URL, headers=headers2)
    soup2 = BeautifulSoup(re2.text, "html.parser")
    return soup2


def getLabel(html, isprint=True):
    info = html.find("div", {"class":"info-list"})
    label1 = info.find_all("div", {"class":"column-1"})
    label2 = info.find_all("div", {"class":"column-2"})
    Label1 = []
    Label2 = []
    Label = []
    for i in range(len(label1)):
        lab1str = label1[i].text.replace("\n", ":").replace(" ", "")[:-1]
        if isprint == True:
            print(lab1str)
        Label1.append(lab1str[lab1str.find(":")+1::])
    for j in range(len(label2)):
        lab2str = label2[j].find("div", {"class":"hover-value"}).text.replace(" ", "").replace("\n", "")
        if isprint == True:
            print("{0}:{1}".format(label2[j].div.text, lab2str))
        Label2.append(lab2str)
    #print(Label1)
    Label = Label2 + Label1
    return Label



def getPage(url):
    df = pd.DataFrame(columns=columns)
    response = requests.get(url, headers=headers)
    print(response.status_code)
    soup = BeautifulSoup(response.text, "html.parser")
    title = soup.find_all("a", {"class":"li-row"})
    #print(title[0])
    for i in range(len(title)):
        Label0 = []
        Info = []
        print(title[i].attrs["href"])
        name = title[i].find("div", {"class":"nowrap-min li-community-title"}).text
        Label0.append(name)
        year = title[i].find("span", {"class":"year"})
        if year == None:
            Label0.append("无")
        else:
            Label0.append(year.text)
        location = title[i].find("span", {"class":""})
        if location == None:
            Label0.append("无")
        else:
            Label0.append(location.text)
        price_rural = title[i].find("div", {"class":"community-price"})
        if price_rural == None:
            Label0.append("无")
        else:
            price = re.findall(r"\d+元/m2", price_rural.text.replace(" ", ""))[0]
            Label0.append(price)
        tags = []
        tag = title[i].find_all("span", {"class":"prop-tag"})
        for span in tag:
            tags.append(span.text)
        Label0.append(tags)
        sonpage = getUrl(title[i].attrs["href"])
        res = getLabel(sonpage)
        Info = Label0 + res
        print(Info)
        df.loc[i] = Info
        time.sleep(3) # 增加间隔, 防止被封
    return df

headers是list页面的请求头

headers2是某条内容的请求头, 二者使用的cookie不同

只需要在调试模式下对内容标签做简单的分析和整理, 就能够得到其组织关系和页面跳转的规则. 之前已经写过多期爬虫实例, 不再赘述. 简单爬个42页