利用 scrapy-splash 对京东进行模拟点击并进行数据爬取

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scrapy-splash的介绍

scrapy-splash模块主要使用了splash. 所谓的splash, 就是一个javascript渲染服务。它是一个实现了http api的轻量级浏览器，splash是用python实现的，同时使用twisted和qt。twisted（qt）用来让服务具有异步处理能力，以发挥webkit的并发能力。splash的特点如下：

• 并行处理多个网页
• 得到html结果以及（或者）渲染成图片
• 关掉加载图片或使用 adblock plus规则使得渲染速度更快
• 使用javascript处理网页内容
• 使用lua脚本
• 能在splash-jupyter notebooks中开发splash lua scripts
• 能够获得具体的har格式的渲染信息

参考文档：

准备配置

• scrapy框架
• splash安装，windows用户通过虚拟机安装docker,linux直接安装docker

页面分析

首先进入 网站搜索想要的书籍， 这里以 python3.7 书籍为例子。

 

点击搜索后发现京东是通过 js 来加载书籍数据的， 通过下来鼠标可以发现加载了更多的书籍数据（数据也可以通过京东的api来获取）

 

首先是模拟搜索，通过检查可得：

 

然后是模拟下拉，这里选择页面底部的这个元素作为模拟元素：

 

开始爬取

模拟点击的lua脚本并获取页数：

 1 function main(splash, args)
 2   splash.images_enabled = false
 3   splash:set_user_agent('mozilla/5.0 (windows nt 10.0; win64; x64) applewebkit/537.36 (khtml, like gecko) chrome/73.0.3683.103 safari/537.36')
 4   assert(splash:go(args.url))
 5   splash:wait(0.5)
 6   local input = splash:select("#keyword")
 7   input:send_text('python3.7')
 8   splash:wait(0.5)
 9   local form = splash:select('.input_submit')
10   form:click()
11   splash:wait(2)
12   splash:runjs("document.getelementsbyclassname('bottom-search')[0].scrollintoview(true)")
13   splash:wait(6)
14   return splash:html()
15 end

 

同上有模拟下拉的代码：

1 function main(splash, args)
2   splash.images_enabled = false
3   splash:set_user_agent('mozilla/5.0 (windows nt 6.1; wow64) applewebkit/537.36 (khtml, like gecko) chrome/36.0.1985.67 safari/537.36')
4   assert(splash:go(args.url))
5   splash:wait(2)
6   splash:runjs("document.getelementsbyclassname('bottom-search')[0].scrollintoview(true)")
7   splash:wait(6)
8   return splash:html()
9 end

 

选择你想要获取的元素，通过检查获得。附上源码：

 

 

 1 # -*- coding: utf-8 -*-
 2 import scrapy
 3 from scrapy import request
 4 from scrapy_splash import splashrequest
 5 from ..items import jdsplashitem
 6 
 7 
 8 
 9 lua_script = '''
10 function main(splash, args)
11   splash.images_enabled = false
12   splash:set_user_agent('mozilla/5.0 (windows nt 10.0; win64; x64) applewebkit/537.36 (khtml, like gecko) chrome/73.0.3683.103 safari/537.36')
13   assert(splash:go(args.url))
14   splash:wait(0.5)
15   local input = splash:select("#keyword")
16   input:send_text('python3.7')
17   splash:wait(0.5)
18   local form = splash:select('.input_submit')
19   form:click()
20   splash:wait(2)
21   splash:runjs("document.getelementsbyclassname('bottom-search')[0].scrollintoview(true)")
22   splash:wait(6)
23   return splash:html()
24 end
25 '''
26 
27 lua_script2 = '''
28 function main(splash, args)
29   splash.images_enabled = false
30   splash:set_user_agent('mozilla/5.0 (windows nt 6.1; wow64) applewebkit/537.36 (khtml, like gecko) chrome/36.0.1985.67 safari/537.36')
31   assert(splash:go(args.url))
32   splash:wait(2)
33   splash:runjs("document.getelementsbyclassname('bottom-search')[0].scrollintoview(true)")
34   splash:wait(6)
35   return splash:html()
36 end
37 '''
38 
39 class jdbookspider(scrapy.spider):
40     name = 'jd'
41     allowed_domains = ['search.jd.com']
42     start_urls = ['https://search.jd.com']
43 
44     def start_requests(self):
45         #进入搜索页进行搜索
46         for each in self.start_urls:
47             yield splashrequest(each,callback=self.parse,endpoint='execute',
48                 args={'lua_source': lua_script})
49 
50     def parse(self, response):
51         item = jdsplashitem()
52         price = response.css('div.gl-i-wrap div.p-price i::text').getall()
53         page_num = response.xpath("//span[@class= 'p-num']/a[last()-1]/text()").get()
54         #这里使用了 xpath 函数 fn:string(arg):返回参数的字符串值。参数可以是数字、逻辑值或节点集。
55         #可能这就是 xpath 比 css 更精致的地方吧
56         name = response.css('div.gl-i-wrap div.p-name').xpath('string(.//em)').getall()
57         #comment = response.css('div.gl-i-wrap div.p-commit').xpath('string(.//strong)').getall()
58         comment = response.css('div.gl-i-wrap div.p-commit strong a::text').getall()
59         publishstore = response.css('div.gl-i-wrap div.p-shopnum a::attr(title)').getall()
60         href = [response.urljoin(i) for i in response.css('div.gl-i-wrap div.p-img a::attr(href)').getall()]
61         for each in zip(name, price, comment, publishstore,href):
62             item['name'] = each[0]
63             item['price'] = each[1]
64             item['comment'] = each[2]
65             item['p_store'] = each[3]
66             item['href'] = each[4]
67             yield item
68         #这里从第二页开始
69         url = 'https://search.jd.com/search?keyword=python3.7&enc=utf-8&qrst=1&rt=1&stop=1&vt=2&page=%d&s=%d&click=0'
70         for each_page in range(1,int(page_num)):
71             yield splashrequest(url%(each_page*2+1,each_page*60),callback=self.s_parse,endpoint='execute',
72                 args={'lua_source': lua_script2})
73 
74     def s_parse(self, response):
75         item = jdsplashitem()
76         price = response.css('div.gl-i-wrap div.p-price i::text').getall()
77         name = response.css('div.gl-i-wrap div.p-name').xpath('string(.//em)').getall()
78         comment = response.css('div.gl-i-wrap div.p-commit strong a::text').getall()
79         publishstore = response.css('div.gl-i-wrap div.p-shopnum a::attr(title)').getall()
80         href = [response.urljoin(i) for i in response.css('div.gl-i-wrap div.p-img a::attr(href)').getall()]
81         for each in zip(name, price, comment, publishstore, href):
82             item['name'] = each[0]
83             item['price'] = each[1]
84             item['comment'] = each[2]
85             item['p_store'] = each[3]
86             item['href'] = each[4]
87             yield item

 

各个文件的配置：

items.py :

 1 import scrapy
 2 
 3 
 4 class jdsplashitem(scrapy.item):
 5     # define the fields for your item here like:
 6     # name = scrapy.field()
 7     name = scrapy.field()
 8     price = scrapy.field()
 9     p_store = scrapy.field()
10     comment = scrapy.field()
11     href = scrapy.field()
12     pass

settings.py:

1 import scrapy_splash
2 # splash服务器地址
3 splash_url = 'http://192.168.99.100:8050'
4 # 开启splash的两个下载中间件并调整httpcompressionmiddleware的次序
5 downloader_middlewares = {
6 'scrapy_splash.splashcookiesmiddleware': 723,
7 'scrapy_splash.splashmiddleware': 725,
8 'scrapy.downloadermiddlewares.httpcompression.httpcompressionmiddleware': 810,
9 }

 

最后运行代码，可以看到书籍数据已经被爬取了：