爬虫爬取链家网信息并可视化

import requests
import parsel
import time
import random
import csv

header = {
    'User-Agent' : 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/107.0.0.0 Safari/537.36'
}
city = input("所在城市首字母缩写 或者全拼：")
detail_list = []

def get_city_region_url(city):
    """获取城市每个区域的url
    返回url以及对应的区域名字"""
    url = f"https://{city}.lianjia.com/ershoufang/"
    response = requests.get(url=url,headers=header)
    selector = parsel.Selector(response.text)
    region_text = selector.css('body > div:nth-child(12) > div > div.position > dl:nth-child(2) > dd > div:nth-child(1) > div > a::text').getall()
    region_url = selector.css('body > div:nth-child(12) > div > div.position > dl:nth-child(2) > dd > div:nth-child(1) > div > a::attr(href)').getall()
    region = dict(zip(region_url,region_text))
    return region

def get_city_region(city):
    region = get_city_region_url(city)
    region_url_list = list(region.keys())
    for region_url in region_url_list:
        url = f"https://{city}.lianjia.com/{region_url}"
        print(f"正在爬取{region[region_url]}的二手房信息")
        response = requests.get(url=url,headers=header)
        selector = parsel.Selector(response.text)
        #获取每个城市区域内房子信息最大页数
        max_page = eval(selector.css('.contentBottom .page-box .house-lst-page-box::attr(page-data)').get())['totalPage']
        #爬取每个区的每一页
        i = 1 #用以计数，达到最大页数之后停止
        while True:
            url_page = url+'pg'+str(i)
            response = requests.get(url=url_page, headers=header )
            #获取每一页的全部信息
            selector = parsel.Selector(response.text)
            href = selector.css('.sellListContent li .title a::attr(href)').getall()
            for link in href:
                time.sleep(random.random()*0.05)
                #循环访问每一个详情页面
                response_1 = requests.get(url=link,headers=header)
                selector_1 = parsel.Selector(response_1.text)
                content_list = []#每一页的内容写入列表
                content_list.append(region[region_url])
                content_list.append(selector_1.css('.title .main::text').get())   #标题
                content_list.append(selector_1.css('.price .total::text').get())               #价格
                global attr_list
                attr_list = selector_1.css('.base .content .label::text').getall() #房屋具体属性
                attr_list = attr_list[:11] #定义全局变量 拿到属性具体值为了容易保存到csv文件
                content_list_1 = selector_1.css('.base .content li::text').getall()#属性的具体值
                content_list.extend(content_list_1[:11])
                content_list.append(link)
                print(content_list)
                print(attr_list)
                detail_list.append(content_list)
                if(attr_list[-1]=='别墅类型'):
                    continue
            print(f"已经爬取完第{i}页内容")
            #当达到最大页数 停止
            i+=1
            if i == max_page:
                break

def load_csv(data_list):
    with open('qingdao2房源.csv',mode='w',encoding='utf-8',newline='') as f:
        attr = []
        attr.extend(['所在区','标题','售价'])
        attr.extend(attr_list)
        writer = csv.DictWriter(f,fieldnames=attr)
        writer.writeheader() #写入表头
        writer = csv.writer(f)
        writer.writerows(data_list)
    print('保存成功')

get_city_region(city)
load_csv(detail_list)