（1）、前言
动态页面：HTML文档中的部分是由客户端运行JS脚本生成的，即服务器生成部分HTML文档内容，其余的再由客户端生成
静态页面：整个HTML文档是在服务器端生成的，即服务器生成好了，再发送给我们客户端
这里我们可以观察一个典型的供我们练习爬虫技术的网站：quotes.toscrape.com/js/
我们通过实验来进一步体验下：（这里我使用ubuntu16.0系统）
1、启动终端并激活虚拟环境：source course-python3.5-env/bin/activate
2、爬取页面并分析
1 (course-python3.5-env) bourne@bourne-vm:~$ scrapy shell http://quotes.toscrape.com/js/ 2 2018-05-21 22:50:18 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: scrapybot) 3 2018-05-21 22:50:18 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 3.5.2 (default, Nov 23 2017, 16:37:01) - [GCC 5.4.0 20160609], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-41-generic-x86_64-with-Ubuntu-16.04-xenial 4 2018-05-21 22:50:18 [scrapy.crawler] INFO: Overridden settings: { 'LOGSTATS_INTERVAL': 0, 'DUPEFILTER_CLASS': 'scrapy.dupefilters.BaseDupeFilter'} 5 2018-05-21 22:50:18 [scrapy.middleware] INFO: Enabled extensions: 6 ['scrapy.extensions.memusage.MemoryUsage', 7 'scrapy.extensions.telnet.TelnetConsole', 8 'scrapy.extensions.corestats.CoreStats'] 9 2018-05-21 22:50:18 [scrapy.middleware] INFO: Enabled downloader middlewares:10 ['scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware',11 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware',12 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware',13 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware',14 'scrapy.downloadermiddlewares.retry.RetryMiddleware',15 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware',16 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware',17 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware',18 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware',19 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware',20 'scrapy.downloadermiddlewares.stats.DownloaderStats']21 2018-05-21 22:50:18 [scrapy.middleware] INFO: Enabled spider middlewares:22 ['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware',23 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware',24 'scrapy.spidermiddlewares.referer.RefererMiddleware',25 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware',26 'scrapy.spidermiddlewares.depth.DepthMiddleware']27 2018-05-21 22:50:18 [scrapy.middleware] INFO: Enabled item pipelines:28 []29 2018-05-21 22:50:18 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:602330 2018-05-21 22:50:18 [scrapy.core.engine] INFO: Spider opened31 2018-05-21 22:50:19 [scrapy.core.engine] DEBUG: Crawled (200) 35 [s] item {}36 [s] request 39 [s] spider 40 [s] Useful shortcuts:41 [s] fetch(url[, redirect=True]) Fetch URL and update local objects (by default, redirects are followed)42 [s] fetch(req) Fetch a scrapy.Request and update local objects 43 [s] shelp() Shell help (print this help)44 [s] view(response) View response in a browser45 In [1]: response.css('div.quote')46 Out[1]: [] 代码分析：这里我们爬取了该网页，但我们通过css选择器爬取页面每一条名人名言具体内容时发现没有返回值
我们来看看页面：这是由于每一条名人名言是通过客户端运行一个Js脚本动态生成的
我们将script脚本打开看看发现这里包含了每一条名人名言的具体信息
（2）、问题分析
scrapy爬虫框架没有提供页面js渲染服务，所以我们获取不到信息，所以我们需要一个渲染引擎来为我们提供渲染服务---这就是Splash渲染引擎（大侠出场了）
1、Splash渲染引擎简介：
Splash是为Scrapy爬虫框架提供渲染javascript代码的引擎，它有如下功能：（摘自维基百科）
（1）为用户返回渲染好的html页面
（2）并发渲染多个页面
（3）关闭图片加载，加速渲染
（4）执行用户自定义的js代码
（5）执行用户自定义的lua脚步，类似于无界面浏览器phantomjs
2、Splash渲染引擎工作原理：（我们来类比就一清二楚了）
这里我们假定三个小伙伴：（1--懒惰的我 ， 2 --提供外卖服务的小哥，3---本人喜欢吃的家味道餐饮点）
今天正好天气不好，1呆在宿舍睡了一早上起来，发现肚子饿了，它就想去自己爱吃的家味道餐饮点餐，他在床上大喊一声我要吃大鸡腿，但3并没有返回东西给他，这是后怎么办呢，2出场了，1打来自己了饿了吗APP点了一份荷叶饭，这是外卖小哥收到订单，就为他去3那，拿了他爱吃的荷叶饭给了1，1顿时兴高采烈！
Client----相当于1 /Splash---相当于2 /Web server---相当于3
即：我们将下载请求告诉Splash ，然后Splash帮我们去下载并渲染页面，最后将渲染好的页面返回给我们
（3）、安装Splash
启动终端：
sudo apt-get install docker docker.io（安装docker镜像）
sudo docker pull scrapyhub/splash（用docker安装Splash）
安装过程比较缓慢，小伙伴们安心等待即可
启动Splash:
sudo docker run -p 8050:8050 scrapinghub/splash（这里我们在本机8050端口开启了Splash服务）
得到上面输出，表明该引擎已启动
我们使用命令查看，可以看见8050端口已经开启服务了
（4）、Splash简要使用说明
Splash为我们提供了多种端点的服务，具体参见http://splash.readthedocs.io/en/stable/api.html#render-html
1、下面我们以render.html端点来体验下：（这里我们使用requests库）
实验：
首先：我们在本机8050端口开启splash 服务：sudo docker run -p 8050:8050 scrapinghub/splash
接着：激活虚拟环境source course-python3.5-env/bin/activate----启动ipython:
import requestsfrom scrapy.selector import Selectorsplash_url = 'http://localhost:8050/render.html'args = { 'url':'http://quotes.toscrape.com/js','timeout':10,'image':0}response = requests.get(splash_url,params = args) sel = Selector(response)sel.css('div.quote span.text::text').extract() 得到如下输出：
2、下面我们来介绍另一个重要的端点：execute端点
execute端点简介：它被用来提供如下服务：当用户想在页面中执行自己定义的Js代码，如：用js代码模拟浏览器进行页面操作（滑动滚动条啊，点击啊等等）
这里：我们将execute看成是一个可以模拟用户行为的浏览器，而用户的行为我们通过lua脚本进行定义：
比如：
打开url页面
等待加载和渲染
执行js代码
获取http响应头部
获取cookies
实验：
ln [1]: import requestsIn [2]: import json#编写lua脚本，：访问属性In [3]: lua = ''' ...: function main(splash) ...: splash:go('http:example.com') #打开页面 ...: splash:wait(0.5) #等待加载 ...: local title = splash:evaljs('document.title') #执行js代码 ...: return {title = title} #{中的内容类型python中的键值对} ...: end ...: '''In [4]: splash_url = 'http://localhost:8050/execute' #定义端点地址In [5]: headers = { 'content-type':'application/json'}In [6]: data = json.dumps({ 'lua_source':lua}) #做成json对象In [7]: response = requests.post(splash_url,headers = headers,data=data) #使用post请求In [8]: response.contentOut[8]: b'{"title": "Example Domain"}'In [9]: response.json()Out[9]: { 'title': 'Example Domain'} Splash对象常用属性和方法总结：参考官网http://splash.readthedocs.io/en/stable/scripting-overview.html#和书本
splash:args属性----传入用户参数的表，通过该属性可以访问用户传入的参数，如splash.args.url、splash.args.wait
spalsh.images_enabled属性---用于开启/禁止图片加载，默认值为True
splash:go方法---请求url页面
splash:wait方法---等待渲染的秒数
splash:evaljs方法---在当前页面下，执行一段js代码，并返回最后一句表达式的值
splash:runjs方法---在当前页面下，执行一段js代码
splash:url方法---获取当前页面的url
splash:html方法---获取当前页面的HTML文档
splash:get_cookies---获取cookies信息
（5）、在Scrapy 中使用Splash
1、安装：scrapy-splash
pip install scrapy-splash
2、在scrapy_splash中定义了一个SplashRequest类，用户只需使用scrapy_splash.SplashRequst来替代scrapy.Request发送请求
该构造器常用参数如下：
url---待爬取的url地址
headers---请求头
cookies---cookies信息
args---传递给splash的参数，如wait\timeout\images\js_source等
cache_args--针对参数重复调用或数据量大大情况，让Splash缓存该参数
endpoint---Splash服务端点
splash_url---Splash服务器地址，默认为None
实验：https://github.com/scrapy-plugins/scrapy-splash(这里有很多使用例子供大家学习)
step1:新建项目和爬虫（先用终端开启splash服务：sudo docker run -p 8050:8050 scrapinghub/splash，这里我创建了一个project目录--进入目录scrapy startproject dynamic_page ---cd dynamic_page ---scrapy genspider spider quotes.toscrape.com/js/）创建好的项目树形目录如下：
step2：改写settIngs.py文件这里小伙伴们可参考github（https://github.com/scrapy-plugins/scrapy-splash）---上面有详细的说明
在最后添加如下内容:
2 #Splash服务器地址 93 SPLASH_URL = 'http://localhost:8050' 94 95 #开启两个下载中间件，并调整HttpCompressionMiddlewares的次序 96 DOWNLOADER_MIDDLEWARES = { 97 'scrapy_splash.SplashCookiesMiddleware': 723, 98 'scrapy_splash.SplashMiddleware':725, 99 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware':810, 100 }101 102 #设置去重过滤器103 DUPEFILTER_CLASS = 'scrapy_splash.SplashAwareDupeFilter'104 105 #用来支持cache_args（可选）106 SPIDER_MIDDLEWARES = {107 'scrapy_splash.SplashDeduplicateArgsMiddleware':100,108 }109 110 DUPEFILTER_CLASS ='scrapy_splash.SplashAwareDupeFilter'111 112 HTTPCACHE_STORAGE ='scrapy_splash.SplashAwareFSCacheStorage' 113 step3:修改spider.py文件
1 # -*- coding: utf-8 -*- 2 import scrapy 3 from scrapy_splash import SplashRequest #重新定义了请求 4 5 class SpiderSpider(scrapy.Spider): 6 name = 'spider' 7 allowed_domains = ['quotes.toscrape.com'] 8 start_urls = ['http://quotes.toscrape.com/js/'] 9 10 def start_requests(self): #重新定义起始爬取点 11 for url in self.start_urls: 12 yield SplashRequest(url,args = { 'timeout':8,'images':0}) 13 14 def parse(self, response): #页面解析函数，这里我们使用了CSS选择器 15 authors = response.css('div.quote small.author::text').extract() #选中名人并返回一个列表 16 quotes = response.css('div.quote span.text::text').extract() #选中名言并返回一个列表 17 yield from (dict(zip(['author','quote'],item)) for item in zip(authors,quotes)) #使用zip()函数--小伙伴们自行百度菜鸟教程即可 18构造了一个元祖再进行遍历，再次使用zip结合dict构造器做成了列表，由于yield ，所以我们使用生成器解析返回 19 20 next_url = response.css('ul.pager li.next a::attr(href)').extract_first() 21 if next_url: 22 complete_url = response.urljoin(next_url)#构造了翻页的绝对url地址 23 yield SplashRequest(complete_url,args = { 'timeout':8,'images':0})~ step4:运行爬虫，得到如下输出（scrapy crawl spider -o result.csv）---将其写入csv文件，这里普及下小知识点：csv文件简单理解就是如excet类型的文件格式，只不过excel拿表格分割，而csv文件以逗号分割而已
（6）、项目实战（我们以爬取京东商城商品冰淇淋为例吧）
---我是个吃货，夏天快到了我们来爬京东中的冰淇淋信息吧---
第一步：分析页面
打开京东商城，输入关键字：冰淇淋，滑动滚动条，我们发现随着滚动条向下滑动，越来越多的商品信息被刷新了，这说明该页面部分是ajax加载
我们打开scrapy shell 爬取该页面，如下图：
(course-python3.5-env) bourne@bourne-vm:~/project/dynamic_page$ scrapy shell 'https://search.jd.com/Search?keyword=%E5%86%B0%E6%B7%87%E6%B7%8B&enc=utf-8'2018-05-22 20:31:50 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: dynamic_page)2018-05-22 20:31:50 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 3.5.2 (default, Nov 23 2017, 16:37:01) - [GCC 5.4.0 20160609], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-41-generic-x86_64-with-Ubuntu-16.04-xenial2018-05-22 20:31:50 [scrapy.crawler] INFO: Overridden settings: { 'NEWSPIDER_MODULE': 'dynamic_page.spiders', 'BOT_NAME': 'dynamic_page', 'DUPEFILTER_CLASS': 'scrapy_splash.SplashAwareDupeFilter', 'LOGSTATS_INTERVAL': 0, 'ROBOTSTXT_OBEY': True, 'HTTPCACHE_STORAGE': 'scrapy_splash.SplashAwareFSCacheStorage', 'SPIDER_MODULES': ['dynamic_page.spiders']}2018-05-22 20:31:50 [scrapy.middleware] INFO: Enabled extensions:['scrapy.extensions.corestats.CoreStats', 'scrapy.extensions.telnet.TelnetConsole', 'scrapy.extensions.memusage.MemoryUsage']2018-05-22 20:31:50 [scrapy.middleware] INFO: Enabled downloader middlewares:['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', 'scrapy.downloadermiddlewares.retry.RetryMiddleware', 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', 'scrapy_splash.SplashCookiesMiddleware', 'scrapy_splash.SplashMiddleware', 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', 'scrapy.downloadermiddlewares.stats.DownloaderStats']2018-05-22 20:31:50 [scrapy.middleware] INFO: Enabled spider middlewares:['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', 'scrapy_splash.SplashDeduplicateArgsMiddleware', 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', 'scrapy.spidermiddlewares.referer.RefererMiddleware', 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', 'scrapy.spidermiddlewares.depth.DepthMiddleware']2018-05-22 20:31:50 [scrapy.middleware] INFO: Enabled item pipelines:[]2018-05-22 20:31:50 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:60242018-05-22 20:31:50 [scrapy.core.engine] INFO: Spider opened2018-05-22 20:31:50 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (302) to from 2018-05-22 20:31:50 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None)2018-05-22 20:31:51 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None)[s] Available Scrapy objects:[s] scrapy scrapy module (contains scrapy.Request, scrapy.Selector, etc)[s] crawler [s] item {}[s] request [s] response <200 https://search.jd.com/Search?keyword=%E5%86%B0%E6%B7%87%E6%B7%8B&enc=utf-8>[s] settings [s] spider [s] Useful shortcuts:[s] fetch(url[, redirect=True]) Fetch URL and update local objects (by default, redirects are followed)[s] fetch(req) Fetch a scrapy.Request and update local objects [s] shelp() Shell help (print this help)[s] view(response) View response in a browserIn [1]: response.css('div.gl-i-wrap')Out[1]: [ , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ]In [2]: len(response.css('div.gl-i-wrap'))Out[2]: 30 得到返回结果发现只有30个冰淇凌的信息，而我们再页面中明明看见了60个冰淇凌信息，这是为什么呢？
答：这也说明了刚开始页面只用30个冰淇淋信息，而我们滑动滑块时，执行了js代码，并向后台发送了ajax请求，浏览器拿到数据后再进一步渲染出另外了30个信息
我们可以点击network选项卡再次确认：
鉴于此，我们就想出了一种解决方案：即用js代码模拟用户滑动滑块到底的行为再结合execute端点提供的js代码执行服务即可（小伙伴们让我们开始实践吧）
首先：模拟用户行为：
启动终端并激活虚拟环境，我们首先使用Request发送请求观察结果
(course-python3.5-env) bourne@bourne-vm:~/project/dynamic_page$ scrapy shell 'https://search.jd.com/Search?keyword=%E5%86%B0%E6%B7%87%E6%B7%8B&enc=utf-8'2018-05-23 10:04:44 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: dynamic_page)2018-05-23 10:04:44 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 3.5.2 (default, Nov 23 2017, 16:37:01) - [GCC 5.4.0 20160609], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-41-generic-x86_64-with-Ubuntu-16.04-xenial2018-05-23 10:04:44 [scrapy.crawler] INFO: Overridden settings: { 'LOGSTATS_INTERVAL': 0, 'ROBOTSTXT_OBEY': True, 'NEWSPIDER_MODULE': 'dynamic_page.spiders', 'HTTPCACHE_STORAGE': 'scrapy_splash.SplashAwareFSCacheStorage', 'BOT_NAME': 'dynamic_page', 'SPIDER_MODULES': ['dynamic_page.spiders'], 'DUPEFILTER_CLASS': 'scrapy_splash.SplashAwareDupeFilter'}2018-05-23 10:04:44 [scrapy.middleware] INFO: Enabled extensions:['scrapy.extensions.telnet.TelnetConsole', 'scrapy.extensions.corestats.CoreStats', 'scrapy.extensions.memusage.MemoryUsage']2018-05-23 10:04:44 [scrapy.middleware] INFO: Enabled downloader middlewares:['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', 'scrapy.downloadermiddlewares.retry.RetryMiddleware', 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', 'scrapy_splash.SplashCookiesMiddleware', 'scrapy_splash.SplashMiddleware', 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', 'scrapy.downloadermiddlewares.stats.DownloaderStats']2018-05-23 10:04:44 [scrapy.middleware] INFO: Enabled spider middlewares:['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', 'scrapy_splash.SplashDeduplicateArgsMiddleware', 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', 'scrapy.spidermiddlewares.referer.RefererMiddleware', 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', 'scrapy.spidermiddlewares.depth.DepthMiddleware']2018-05-23 10:04:44 [scrapy.middleware] INFO: Enabled item pipelines:[]2018-05-23 10:04:44 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:60242018-05-23 10:04:44 [scrapy.core.engine] INFO: Spider opened2018-05-23 10:04:45 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (302) to from 2018-05-23 10:04:47 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None)2018-05-23 10:04:48 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None)[s] Available Scrapy objects:[s] scrapy scrapy module (contains scrapy.Request, scrapy.Selector, etc)[s] crawler [s] item {}[s] request [s] response <200 https://search.jd.com/Search?keyword=%E5%86%B0%E6%B7%87%E6%B7%8B&enc=utf-8>[s] settings [s] spider [s] Useful shortcuts:[s] fetch(url[, redirect=True]) Fetch URL and update local objects (by default, redirects are followed)[s] fetch(req) Fetch a scrapy.Request and update local objects [s] shelp() Shell help (print this help)[s] view(response) View response in a browserIn [1]: response.css('div.gl-i-wrap')Out[1]: [ , , , , , , , , , , , , , , , , , , , , , , , , , , , , , ]In [2]: len(response.css('div.gl-i-wrap'))Out[2]: 30 代码分析：我们使用scrapy.Request发送了请求，但由于页面时动态加载的所有我们只收到了30个冰淇淋的信息
下面我们来使用execute 端点解决这个问题：
(course-python3.5-env) bourne@bourne-vm:~/project/dynamic_page$ scrapy shell 2018-05-23 09:51:58 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: dynamic_page)2018-05-23 09:51:58 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.8, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 18.4.0, Python 3.5.2 (default, Nov 23 2017, 16:37:01) - [GCC 5.4.0 20160609], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Linux-4.13.0-41-generic-x86_64-with-Ubuntu-16.04-xenial2018-05-23 09:51:58 [scrapy.crawler] INFO: Overridden settings: { 'SPIDER_MODULES': ['dynamic_page.spiders'], 'DUPEFILTER_CLASS': 'scrapy_splash.SplashAwareDupeFilter', 'ROBOTSTXT_OBEY': True, 'NEWSPIDER_MODULE': 'dynamic_page.spiders', 'HTTPCACHE_STORAGE': 'scrapy_splash.SplashAwareFSCacheStorage', 'BOT_NAME': 'dynamic_page', 'LOGSTATS_INTERVAL': 0}2018-05-23 09:51:58 [scrapy.middleware] INFO: Enabled extensions:['scrapy.extensions.corestats.CoreStats', 'scrapy.extensions.telnet.TelnetConsole', 'scrapy.extensions.memusage.MemoryUsage']2018-05-23 09:51:58 [scrapy.middleware] INFO: Enabled downloader middlewares:['scrapy.downloadermiddlewares.robotstxt.RobotsTxtMiddleware', 'scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware', 'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware', 'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware', 'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware', 'scrapy.downloadermiddlewares.retry.RetryMiddleware', 'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware', 'scrapy.downloadermiddlewares.redirect.RedirectMiddleware', 'scrapy.downloadermiddlewares.cookies.CookiesMiddleware', 'scrapy_splash.SplashCookiesMiddleware', 'scrapy_splash.SplashMiddleware', 'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware', 'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware', 'scrapy.downloadermiddlewares.stats.DownloaderStats']2018-05-23 09:51:58 [scrapy.middleware] INFO: Enabled spider middlewares:['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware', 'scrapy_splash.SplashDeduplicateArgsMiddleware', 'scrapy.spidermiddlewares.offsite.OffsiteMiddleware', 'scrapy.spidermiddlewares.referer.RefererMiddleware', 'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware', 'scrapy.spidermiddlewares.depth.DepthMiddleware']2018-05-23 09:51:58 [scrapy.middleware] INFO: Enabled item pipelines:[]2018-05-23 09:51:58 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023[s] Available Scrapy objects:[s] scrapy scrapy module (contains scrapy.Request, scrapy.Selector, etc)[s] crawler [s] item {}[s] settings [s] Useful shortcuts:[s] fetch(url[, redirect=True]) Fetch URL and update local objects (by default, redirects are followed)[s] fetch(req) Fetch a scrapy.Request and update local objects [s] shelp() Shell help (print this help)[s] view(response) View response in a browserIn [5]: from scrapy_splash import SplashRequest #使用scrapy.splash.Request发送请求In [6]: url = 'https://search.jd.com/Search?keyword=%E5%86%B0%E6%B7%87%E6%B7%8B&enc=utf-8'In [7]: lua = ''' ...: function main(splash) ...: splash:go(splash.args.url) ...: splash:wait(3) ...: splash:runjs("document.getElementById('footer-2017').scrollIntoView(true)") ...: splash:wait(3) ...: return splash:html() ...: end ...: ''' #自定义lua 脚本模拟用户滑动滑块行为In [8]: fetch(SplashRequest(url,endpoint = 'execute',args= { 'lua_source':lua})) #再次请求，我们可以看到现在已通过本机的8050端点渲染了js代码，并成果返回结果2018-05-23 09:53:55 [scrapy.core.engine] DEBUG: Crawled (200) (referer: None)In [9]: len(response.css('div.gl-i-wrap'))Out[9]: 60 最后的任务就回归到了提取内容了阶段了，小伙伴让我们完成整个代码吧！---这里结合scrapy shell 进行测试
修改spider2.py
1 # -*- coding: utf-8 -*- 2 import scrapy 3 from scrapy_splash import SplashRequest 4 5 lua = ''' #自定义lua脚本 6 function main(splash) 7 splash:go(splash.args.url) 8 splash:wait(3) 9 splash:runjs("document.getElementById('footer-2017').scrollIntoView(true)") 10 splash:wait(3) 11 return splash:html() 12 end 13 ''' 14 15 16 17 class Spider2Spider(scrapy.Spider): 18 name = 'spider2' 19 allowed_domains = ['search.jd.com'] 20 start_urls = ['https://search.jd.com/Search?keyword=%E5%86%B0%E6%B7%87%E6%B7%8B&enc=utf-8'] 21 base_url = 'https://search.jd.com/Search?keyword=%E5%86%B0%E6%B7%87%E6%B7%8B&enc=utf-8' 22 23 def parse(self, response): 24 page_num = int(response.css('span.fp-text i::text').extract_first()) 25 26 for i in range(page_num): 27 url = '%s?page=%s' % (self.base_url , 2*i+1) #通过观察我们发现url页面间有规律 28 yield SplashRequest(url,endpoint = 'execute',args ={ 'lua_source':lua},callback = self.parse_item) 29 30 def parse_item(self,response): #页面解析函数 31 for sel in response.css('div.gl-i-wrap'): 32 yield { 33 'name':sel.css('div.p-name em').extract_first(), 34 'price':sel.css('div.p-price i::text').extract_first(), 35 } 部分输出结果：
这里我一共拿到了4500条数据，距离6000条还差一些，我估计于网页结构有关，还有就是name字段，我处理了好久，就是包含字母，有高手可以解决如上问题，欢迎积极给我留言，供我学习！