链家全国各省城市房屋数据批量爬取，别再为房屋发愁！

本文主要是介绍链家全国各省城市房屋数据批量爬取，别再为房屋发愁！，希望对大家解决编程问题提供一定的参考价值，需要的开发者们随着小编来一起学习吧！

1、前言

本文爬取的是链家的二手房信息，相信个位小伙伴看完后一定能自己动手爬取链家的其他模块，比如：租房、新房等等模块房屋数据。

话不多说，来到链家首页，点击北京

来到如下页面，这里有全国各个各个省份城市，而且点击某个城市会跳转到以该城市的为定位的页面

点击二手房，来到二手房页面，可以发现链接地址只是在原先的URL上拼接了 /ershoufang/,所以我们之后也可以直接拼接

但注意，以下这种我们不需要的需要排除

多页爬取，规律如下，多的也不用我说了，大家都能看出来

2、基本环境搭建

建立数据库

建表语句

CREATE TABLE `lianjia` (`id` int(11) NOT NULL AUTO_INCREMENT,`city` varchar(100) DEFAULT NULL,`money` varchar(100) DEFAULT NULL,`address` varchar(100) DEFAULT NULL,`house_pattern` varchar(100) DEFAULT NULL,`house_size` varchar(100) DEFAULT NULL,`house_degree` varchar(100) DEFAULT NULL,`house_floor` varchar(100) DEFAULT NULL,`price` varchar(50) DEFAULT NULL,PRIMARY KEY (`id`)
) ENGINE=InnoDB AUTO_INCREMENT=212 DEFAULT CHARSET=utf8mb4 COLLATE=utf8mb4_0900_ai_ci;
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创建scrapy项目

start.py

from scrapy import cmdlinecmdline.execute("scrapy crawl lianjia".split())
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3、代码注释分析

lianjia.py

# -*- coding: utf-8 -*-
import scrapy
import time
from Lianjia.items import LianjiaItemclass LianjiaSpider(scrapy.Spider):name = 'lianjia'allowed_domains = ['lianjia.com']#拥有各个省份城市的URLstart_urls = ['https://www.lianjia.com/city/']def parse(self, response):#参考图1，找到class值为city_list_ul的ul标签，在获取其下的所有li标签ul = response.xpath("//ul[@class='city_list_ul']/li")#遍历ul，每个省份代表一个li标签for li in ul:#参考图2，获取每个省份下的所有城市的li标签data_ul = li.xpath(".//ul/li")#遍历得到每个城市for li_data in data_ul:#参考图3，获取每个城市的URL和名称city = li_data.xpath(".//a/text()").get()#拼接成为二手房链接page_url = li_data.xpath(".//a/@href").get() + "/ershoufang/"#多页爬取for i in range(3):url = page_url + "pg" + str(i+1)print(url)yield scrapy.Request(url=url,callback=self.pageData,meta={"info":city})def pageData(self,response):print("="*50)#获取传过来的城市名称city = response.meta.get("info")#参考图4，找到class值为sellListContent的ul标签，在获取其下的所有li标签detail_li = response.xpath("//ul[@class='sellListContent']/li")#遍历for page_li in detail_li:#参考图5，获取class值判断排除多余的广告if page_li.xpath("@class").get() == "list_app_daoliu":continue#参考图6，获取房屋总价money = page_li.xpath(".//div[@class='totalPrice']/span/text()").get()money = str(money) + "万"#参考图7address = page_li.xpath(".//div[@class='positionInfo']/a/text()").get()#参考图8，获取到房屋的全部数据，进行分割house_data = page_li.xpath(".//div[@class='houseInfo']/text()").get().split("|")#房屋格局house_pattern = house_data[0]#面积大小house_size = house_data[1].strip()#装修程度house_degree = house_data[3].strip()#楼层house_floor = house_data[4].strip()#单价，参考图9price = page_li.xpath(".//div[@class='unitPrice']/span/text()").get().replace("单价","")time.sleep(0.5)item = LianjiaItem(city=city,money=money,address=address,house_pattern=house_pattern,house_size=house_size,house_degree=house_degree,house_floor=house_floor,price=price)yield item1234567891011121314151617181920212223242526272829303132333435363738394041424344454647484950515253545556575859606162636465666768697071727374

3、图片辅助分析

图1

图2

图3

图4

图5

图6

图7

图8

图9

4、完整代码

lianjia.py

# -*- coding: utf-8 -*-
import scrapy
import time
from Lianjia.items import LianjiaItemclass LianjiaSpider(scrapy.Spider):name = 'lianjia'allowed_domains = ['lianjia.com']start_urls = ['https://www.lianjia.com/city/']def parse(self, response):ul = response.xpath("//ul[@class='city_list_ul']/li")for li in ul:data_ul = li.xpath(".//ul/li")for li_data in data_ul:city = li_data.xpath(".//a/text()").get()page_url = li_data.xpath(".//a/@href").get() + "/ershoufang/"for i in range(3):url = page_url + "pg" + str(i+1)print(url)yield scrapy.Request(url=url,callback=self.pageData,meta={"info":city})def pageData(self,response):print("="*50)city = response.meta.get("info")detail_li = response.xpath("//ul[@class='sellListContent']/li")for page_li in detail_li:if page_li.xpath("@class").get() == "list_app_daoliu":continuemoney = page_li.xpath(".//div[@class='totalPrice']/span/text()").get()money = str(money) + "万"address = page_li.xpath(".//div[@class='positionInfo']/a/text()").get()#获取到房屋的全部数据，进行分割house_data = page_li.xpath(".//div[@class='houseInfo']/text()").get().split("|")#房屋格局house_pattern = house_data[0]#面积大小house_size = house_data[1].strip()#装修程度house_degree = house_data[3].strip()#楼层house_floor = house_data[4].strip()#单价price = page_li.xpath(".//div[@class='unitPrice']/span/text()").get().replace("单价","")time.sleep(0.5)item = LianjiaItem(city=city,money=money,address=address,house_pattern=house_pattern,house_size=house_size,house_degree=house_degree,house_floor=house_floor,price=price)yield item12345678910111213141516171819202122232425262728293031323334353637383940414243444546474849505152

items.py

# -*- coding: utf-8 -*-
import scrapyclass LianjiaItem(scrapy.Item):#城市city = scrapy.Field()#总价money = scrapy.Field()#地址address = scrapy.Field()# 房屋格局house_pattern = scrapy.Field()# 面积大小house_size = scrapy.Field()# 装修程度house_degree = scrapy.Field()# 楼层house_floor = scrapy.Field()# 单价price = scrapy.Field()
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pipelines.py

import pymysqlclass LianjiaPipeline:def __init__(self):dbparams = {'host': '127.0.0.1','port': 3306,'user': 'root',  #数据库账号'password': 'root',	#数据库密码'database': 'lianjia', #数据库名称'charset': 'utf8'}#初始化数据库连接self.conn = pymysql.connect(**dbparams)self.cursor = self.conn.cursor()self._sql = Nonedef process_item(self, item, spider):#执行sqlself.cursor.execute(self.sql,(item['city'],item['money'],item['address'],item['house_pattern'],item['house_size'],item['house_degree'],item['house_floor'],item['price']))self.conn.commit()  #提交return item@propertydef sql(self):if not self._sql:#数据库插入语句self._sql = """insert into lianjia(id,city,money,address,house_pattern,house_size,house_degree,house_floor,price)values(null,%s,%s,%s,%s,%s,%s,%s,%s)"""return self._sqlreturn self._sql
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settings.py

# -*- coding: utf-8 -*-BOT_NAME = 'Lianjia'SPIDER_MODULES = ['Lianjia.spiders']
NEWSPIDER_MODULE = 'Lianjia.spiders'LOG_LEVEL="ERROR"# Crawl responsibly by identifying yourself (and your website) on the user-agent
#USER_AGENT = 'Lianjia (+http://www.yourdomain.com)'# Obey robots.txt rules
ROBOTSTXT_OBEY = False# Configure maximum concurrent requests performed by Scrapy (default: 16)
#CONCURRENT_REQUESTS = 32# Configure a delay for requests for the same website (default: 0)
# See https://docs.scrapy.org/en/latest/topics/settings.html#download-delay
# See also autothrottle settings and docs
#DOWNLOAD_DELAY = 3
# The download delay setting will honor only one of:
#CONCURRENT_REQUESTS_PER_DOMAIN = 16
#CONCURRENT_REQUESTS_PER_IP = 16# Disable cookies (enabled by default)
#COOKIES_ENABLED = False# Disable Telnet Console (enabled by default)
#TELNETCONSOLE_ENABLED = False# Override the default request headers:
DEFAULT_REQUEST_HEADERS = {'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8','Accept-Language': 'en',"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/84.0.4147.135 Safari/537.36 Edg/84.0.522.63"
}# Enable or disable spider middlewares
# See https://docs.scrapy.org/en/latest/topics/spider-middleware.html
#SPIDER_MIDDLEWARES = {
#    'Lianjia.middlewares.LianjiaSpiderMiddleware': 543,
#}# Enable or disable downloader middlewares
# See https://docs.scrapy.org/en/latest/topics/downloader-middleware.html
#DOWNLOADER_MIDDLEWARES = {
#    'Lianjia.middlewares.LianjiaDownloaderMiddleware': 543,
#}# Enable or disable extensions
# See https://docs.scrapy.org/en/latest/topics/extensions.html
#EXTENSIONS = {
#    'scrapy.extensions.telnet.TelnetConsole': None,
#}# Configure item pipelines
# See https://docs.scrapy.org/en/latest/topics/item-pipeline.html
ITEM_PIPELINES = {'Lianjia.pipelines.LianjiaPipeline': 300,
}# Enable and configure the AutoThrottle extension (disabled by default)
# See https://docs.scrapy.org/en/latest/topics/autothrottle.html
#AUTOTHROTTLE_ENABLED = True
# The initial download delay
#AUTOTHROTTLE_START_DELAY = 5
# The maximum download delay to be set in case of high latencies
#AUTOTHROTTLE_MAX_DELAY = 60
# The average number of requests Scrapy should be sending in parallel to
# each remote server
#AUTOTHROTTLE_TARGET_CONCURRENCY = 1.0
# Enable showing throttling stats for every response received:
#AUTOTHROTTLE_DEBUG = False# Enable and configure HTTP caching (disabled by default)
# See https://docs.scrapy.org/en/latest/topics/downloader-middleware.html#httpcache-middleware-settings
#HTTPCACHE_ENABLED = True
#HTTPCACHE_EXPIRATION_SECS = 0
#HTTPCACHE_DIR = 'httpcache'
#HTTPCACHE_IGNORE_HTTP_CODES = []
#HTTPCACHE_STORAGE = 'scrapy.extensions.httpcache.FilesystemCacheStorage'
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