python_ scrapy_ Fang Tianxia

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scrapy- Explain

xpath Select node The common tag elements are as follows .

Mark	describe
extract	The extracted content is converted to Unicode character string , The return data type is list
/	Select from root node
//	Match the selected current node, select the node in the document
.	node
@	attribute
*	Any element node
@*	Any attribute node
node()	Any type of node

Climb to take the house world - Prelude

analysis
1、 website ：url：https://sh.newhouse.fang.com/house/s/.
2、 Determine what data to crawl ：1) Web address ：page.2) Location name ：name.3) Price ：price.4) Address ：address.5) Phone number ：tel
2、 Analyze the web page .

 open url after , We can see the data we need , Then you can see that there are still pagination .

 You can see the opening url Then look at the page elements , All the data we need are in a pair of ul tag .

 open li A couple of labels , What we need name Is in a Under the label , And there are unclear spaces around the text, such as line feed, need special treatment .
 What we need price Is in 55000 Under the label , Be careful , Some houses have been bought without price display , Step on this pit carefully .
 We can find the corresponding by analogy address and tel.

 The pagination tag element shows , Of the current page a Of class="active". In opening the home page is a The text of is 1, It means the first page .

Climb to take the house world - Before the specific implementation process

First new scrapy project
1) Switch to the project folder ：Terminal Input... On the console scrapy startproject hotel,hotel It's the project name of the demo , You can customize it according to your own needs .
2) On demand items.py Folder configuration parameters . Five parameters are needed in the analysis , Namely ：page,name,price,address,tel. The configuration code is as follows ：

class HotelItem(scrapy.Item):
   #  The parameters here should correspond to the specific parameters of the crawler implementation 
   page = scrapy.Field()
   name = scrapy.Field()
   price = scrapy.Field()
   address = scrapy.Field()
   tel = scrapy.Field()

3) Build our new reptile Branch . Switch to spiders Folder ,Terminal Input... On the console scrapy genspider house sh.newhouse.fang.comhouse Is the crawler name of the project , You can customize ,sh.newhouse.fang.com It's an area selection for crawling .
stay spider Under the folder we created house.py The file .
The code implementation and explanation are as follows

import scrapy
from ..items import *
class HouseSpider(scrapy.Spider):
  name = 'house'
  #  Crawling area restrictions 
  allowed_domains = ['sh.newhouse.fang.com']
  #  The main page of crawling 
  start_urls = ['https://sh.newhouse.fang.com/house/s/',]
  def start_requests(self):
      for url in self.start_urls:
          #  Return the module name passed by the function , There are no brackets . It's a convention .
          yield scrapy.Request(url=url,callback=self.parse)
  def parse(self, response):
      items = []
      #  Get the value displayed on the current page 
      for p in response.xpath('//a[@class="active"]/text()'):
          # extract Convert the extracted content to Unicode character string , The return data type is list
          currentpage=p.extract()
      #  Determine the last page 
      for last in  response.xpath('//a[@class="last"]/text()'):
          lastpage=last.extract()
      #  Switch to the nearest layer of tags .// Select the node in the document from the current node that matches the selection , Regardless of their location   / Select from root node 
      for each in response.xpath('//div[@class="nl_con clearfix"]/ul/li/div[@class="clearfix"]/div[@class="nlc_details"]'):
          item=HotelItem()
          #  name 
          name=each.xpath('//div[@class="house_value clearfix"]/div[@class="nlcd_name"]/a/text()').extract()
          #  Price 
          price=each.xpath('//div[@class="nhouse_price"]/span/text()').extract()
          #  Address 
          address=each.xpath('//div[@class="relative_message clearfix"]/div[@class="address"]/a/@title').extract()
          #  Telephone 
          tel=each.xpath('//div[@class="relative_message clearfix"]/div[@class="tel"]/p/text()').extract()
          #  all item The parameters in it have to do with us items The meaning of the parameters in it corresponds to 
          item['name'] = [n.replace(' ', '').replace("\n", "").replace("\t", "").replace("\r", "") for n in name]
          item['price'] = [p for p in price]
          item['address'] = [a for a in address]
          item['tel'] = [s for s in tel]
          item['page'] = ['https://sh.newhouse.fang.com/house/s/b9'+(str)(eval(p.extract())+1)+'/?ctm=1.sh.xf_search.page.2']
          items.append(item)
      print(item)
      #  When crawling to the last page , Class label last Automatically switch to the home page 
      if lastpage==' home page ':
          pass
      else:
          #  If it's not the last page , Continue crawling to the next page of data , Know all the data 
          yield scrapy.Request(url='https://sh.newhouse.fang.com/house/s/b9'+(str)(eval(currentpage)+1)+'/?ctm=1.sh.xf_search.page.2', callback=self.parse)

4) stay spiders Run the crawler under ,Terminal Input... On the console scrapy crawl house.
The results are shown in the following figure

The overall project structure is shown on the right tts The folder is used to store data on my side txt file . There is no need for this project .

If you find any errors, please contact wechat ：sunyong8860
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