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  • 爬虫-scrapy的中间件

    scrapy的中间件

    • 下载中间件

      • 作用:
        • 处于引擎和下载器之间,因此该中间件可以批量拦截整个工程中发起所有的请求和响应
      • 拦截请求可进行的操作
        • 进行代理IP
        • 进行UA伪装
          • request.headers['User-Agent'] = 'xxxx'
      • 拦截响应可进行的操作
        • 篡改响应数据(一般不用)
        • 更换响应对象
      • 在scrapy中使用selenium
        • 爬虫类中定义一个bro的属性(selenium实例化的一个浏览器对象)
        • 爬虫类中重写父类的一个方法closed(self,spider),在该方法中关闭浏览器对象
        • 在中间件中的process_response中通过spider参数获取爬虫类中的bro属性
        • 在中间件中编写相关的浏览器自动化的操作获取页面源码数据
        • 将页面源码数据作为新的响应对象的响应数据
        • 将新的响应对象返回
    • 基于crawlSpier的全站数据爬取

      • crawlSpier和Spider之间的关联?
        • crawlSpier是SPider的一个子类
      • 创建一个基于CrawlSpider的爬虫文件
        • scrapy genspider -t crawl xxx www.xxx.com
    • 一个简单的IP端口测试

      • 项目运行文件设置
      import scrapy
      
      class MidSpider(scrapy.Spider):
          name = 'mid'
          # allowed_domains = ['www.xxx.com']
          start_urls = ['http://www.baidu.com/s?wd=ip']
      
          def parse(self, response):
              page_text = response.text
              with open('./ip.html','w',encoding='utf-8') as fp:
                  fp.write(page_text)
      
      
      • item中不需要任何操作
      • pipelines文件代码
      class MiddleproPipeline(object):
          def process_item(self, item, spider):
              return item
      
      • middlewares文件中代码
      rom scrapy import signals
      import random
      #可被选用的代理IP
      PROXY_http = [
          '153.180.102.104:80',
          '195.208.131.189:56055',
      ]
      PROXY_https = [
          '120.83.49.90:9000',
          '95.189.112.214:35508',
      ]
      #UA池的汇总
      user_agent_list = [
              "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.1 "
              "(KHTML, like Gecko) Chrome/22.0.1207.1 Safari/537.1",
              "Mozilla/5.0 (X11; CrOS i686 2268.111.0) AppleWebKit/536.11 "
              "(KHTML, like Gecko) Chrome/20.0.1132.57 Safari/536.11",
              "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.6 "
              "(KHTML, like Gecko) Chrome/20.0.1092.0 Safari/536.6",
              "Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.6 "
              "(KHTML, like Gecko) Chrome/20.0.1090.0 Safari/536.6",
              "Mozilla/5.0 (Windows NT 6.2; WOW64) AppleWebKit/537.1 "
              "(KHTML, like Gecko) Chrome/19.77.34.5 Safari/537.1",
              "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/536.5 "
              "(KHTML, like Gecko) Chrome/19.0.1084.9 Safari/536.5",
              "Mozilla/5.0 (Windows NT 6.0) AppleWebKit/536.5 "
              "(KHTML, like Gecko) Chrome/19.0.1084.36 Safari/536.5",
              "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.3 "
              "(KHTML, like Gecko) Chrome/19.0.1063.0 Safari/536.3",
              "Mozilla/5.0 (Windows NT 5.1) AppleWebKit/536.3 "
              "(KHTML, like Gecko) Chrome/19.0.1063.0 Safari/536.3",
              "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_8_0) AppleWebKit/536.3 "
              "(KHTML, like Gecko) Chrome/19.0.1063.0 Safari/536.3",
              "Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.3 "
              "(KHTML, like Gecko) Chrome/19.0.1062.0 Safari/536.3",
              "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.3 "
              "(KHTML, like Gecko) Chrome/19.0.1062.0 Safari/536.3",
              "Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.3 "
              "(KHTML, like Gecko) Chrome/19.0.1061.1 Safari/536.3",
              "Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/536.3 "
              "(KHTML, like Gecko) Chrome/19.0.1061.1 Safari/536.3",
              "Mozilla/5.0 (Windows NT 6.1) AppleWebKit/536.3 "
              "(KHTML, like Gecko) Chrome/19.0.1061.1 Safari/536.3",
              "Mozilla/5.0 (Windows NT 6.2) AppleWebKit/536.3 "
              "(KHTML, like Gecko) Chrome/19.0.1061.0 Safari/536.3",
              "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/535.24 "
              "(KHTML, like Gecko) Chrome/19.0.1055.1 Safari/535.24",
              "Mozilla/5.0 (Windows NT 6.2; WOW64) AppleWebKit/535.24 "
              "(KHTML, like Gecko) Chrome/19.0.1055.1 Safari/535.24"
      ]
      class MiddleproDownloaderMiddleware(object):
      
          #拦截正常请求
          def process_request(self, request, spider):
              #UA伪装:UA池,每次都使用随机的UA
              request.headers['User-Agent'] = random.choice(user_agent_list)
      
              #使用伪装的代理IP访问
              request.meta['proxy'] = 'http://39.137.77.66:8080'
          #拦截所有的响应
          def process_response(self, request, response, spider):
              # Called with the response returned from the downloader.
      
              # Must either;
              # - return a Response object
              # - return a Request object
              # - or raise IgnoreRequest
              return response
          #拦截发生异常的请求
          def process_exception(self, request, exception, spider):
              #代理ip的设定
              if request.url.split(':')[0] == 'http':
                  request.meta['proxy'] = random.choice(PROXY_http)
              else:
                  request.meta['proxy'] = random.choice(PROXY_https)
      
              return request  #将修正之后的请求对象进行重新发送
      
      • 此时settings文件中需要将中间件打开
      DOWNLOADER_MIDDLEWARES = {
         'middlePro.middlewares.MiddleproDownloaderMiddleware': 543,
      }
      
      
    • 爬取网易新闻的内容

      • 运行文件内容
      import scrapy
      
      from selenium import webdriver
      class WangyiSpider(scrapy.Spider):
          name = 'wangyi'
          # allowed_domains = ['www.xxx.com']
          start_urls = ['https://news.163.com/world/']
      
          #实例化一个浏览器对象,需要添加chromedriver插件
          bro = webdriver.Chrome(executable_path=r'D:爬虫谷歌访问助手chromedriver.exe')
          def parse(self, response):
              div_list = response.xpath('/html/body/div/div[3]/div[4]/div[1]/div/div/ul/li/div/div')
              for div in div_list:
              #xpath表达式需要跳过body标签,遇到body标签常使用//跳过
                  title = div.xpath('.//div[@class="news_title"]//a/text()').extract_first()
                  detail_url = div.xpath('.//div[@class="news_title"]//a/@href').extract_first()
                  yield scrapy.Request(detail_url,self.parse_detail)
                  print(title,detail_url)
      
          def parse_detail(self,response):
              content = response.xpath('//*[@id="endText"]//text()').extract()
              #使用join将列表数据组成字符串
              content = ''.join(content)
              print(content)
          def closed(self,spider):
              self.bro.quit()
      
      • items文件不需要操作
      • pipeline文件的操作
      class WangyiproPipeline(object):
          def process_item(self, item, spider):
              return item
      
      
      • middleware文件中的操作
      from scrapy import signals
      
      from scrapy.http import HtmlResponse
      from time import sleep
      
      
      
      class WangyiproDownloaderMiddleware(object):
      
          def process_request(self, request, spider):
              # Called for each request that goes through the downloader
              # middleware.
      
              # Must either:
              # - return None: continue processing this request
              # - or return a Response object
              # - or return a Request object
              # - or raise IgnoreRequest: process_exception() methods of
              #   installed downloader middleware will be called
              return None
          #spider表示的就是爬虫类实例化的对象
          def process_response(self, request, response, spider):
              #将不符合需求的响应对象修改成符合需求的
              #body:响应数据
              #如何获取爬虫类中生成的浏览器对象呢?
              if request.url == 'https://news.163.com/world/':
                  bro = spider.bro
                  bro.get('https://news.163.com/world/')
                  sleep(2)
        #这里使用了js自动下滑处理动态加载数据          bro.excute_script('window.scrollTo(0,document.body.scrollHeight)')
                  sleep(1)
                  bro.excute_script('window.scrollTo(0,document.body.scrollHeight)')
                  sleep(1)
                  bro.excute_script('window.scrollTo(0,document.body.scrollHeight)')
                  sleep(1)
                  page_text = bro.page_source
      
                  new_response = HtmlResponse(url=bro.current_url,body=page_text,encoding='utf-8',request=request)
      
                  return new_response
              else:
                  return response
      
      
          def process_exception(self, request, exception, spider):
              # Called when a download handler or a process_request()
              # (from other downloader middleware) raises an exception.
      
              # Must either:
              # - return None: continue processing this exception
              # - return a Response object: stops process_exception() chain
              # - return a Request object: stops process_exception() chain
              pass
      
      • 最后在settings文件中加上中间件的配置
      DOWNLOADER_MIDDLEWARES = {
         'wangyiPro.middlewares.WangyiproDownloaderMiddleware': 543,
      }
      
      
    • crawlspider全站数据爬取案例

      • 执行文件内容
      import scrapy
      from scrapy.linkextractors import LinkExtractor
      from scrapy.spiders import CrawlSpider, Rule
      from sunShinePro.items import SunshineproItem,sunConetent
      
      # http://wz.sun0769.com/index.php/question/questionType?type=4&page=30
      class SunSpider(CrawlSpider):
          name = 'sun'
          # allowed_domains = ['www.xxx.com']
      
          start_urls = ['http://wz.sun0769.com/index.php/question/questionType?type=4&page=']
          #链接提取器
              #作用:根据 指定的规则(allow:正则) 提取页面源码中指定的连接,进行对页面中的页码连接提取
          link = LinkExtractor(allow=r'type=4&page=d+')
          link_detail = LinkExtractor(allow='question/d+/d+.shtml')
          rules = (
              #规则解析器:将连接提取器提取到的连接对应的页面源码数据 根据指定规则(callback) 进行数据解析
              Rule(link, callback='parse_item', follow=False),
              Rule(link_detail, callback='parse_detail'),
          )
          def parse_detail(self,response):
              content = response.xpath('/html/body/div[9]/table[2]//tr[1]/td/div[2]//text()').extract()
              content = ''.join(content)
      
              item = sunConetent()
              item['content'] = content
      
              yield item
      
          def parse_item(self, response):
              #注意:如果xpath定位的标签中存在tbody,则需要跳过tbody
              tr_list = response.xpath('//*[@id="morelist"]/div/table[2]//tr/td/table//tr')
              for tr in tr_list:
                  title = tr.xpath('./td[2]/a[2]/text()').extract_first()
                  status = tr.xpath('./td[3]/span/text()').extract_first()
                  item = SunshineproItem()
                  item['title'] = title
                  item['status'] = status
      
                  yield item
      
      
      • items文件内容
      import scrapy
      
      
      class SunshineproItem(scrapy.Item):
          # define the fields for your item here like:
          title = scrapy.Field()
          status = scrapy.Field()
          # pass
      class sunConetent(scrapy.Item):
          content = scrapy.Field()
      
      • pipelines文件内容
      class SunshineproPipeline(object):
          def process_item(self, item, spider):
              if item.__class__.__name__ == 'SunshineproItem':
                  print(item['title'], item['status'])
      
              else:
                  print(item['content'])
              return item
      
      
      • 此案例未使用中间件配置,因此settings文件中只做之间的配置,并且middleware文件不需要变动
    • 爬取网易新闻中的5个模块内的所有内容

      • 创建一个工程:scrapy startproject wangyiPro

      • cd wangyiPro

      • 创建一个爬虫文件:scrapy genspider wangyi www.xxx.com(指定的url,必须要先CD到项目中,保证爬虫文件在spiders目录中)

      • wangyi文件中内容

      import scrapy
      from wangyiPro.items import WangyiproItem
      from selenium import webdriver
      class WangyiSpider(scrapy.Spider):
          name = 'wangyi'
          # allowed_domains = ['www.xxx.com']
          # 根据起始url解析出五大板块对应的详情页的url
          start_urls = ['https://news.163.com/']
          model_detail_urls = []#五个板块详情页的url
      
          bro = webdriver.Chrome(executable_path=r'D:爬虫谷歌访问助手chromedriver.exe')
          def parse(self, response):
              #解析出五大板块对应的详情页的url
              model_list = []  #存储的就是五个板块对应的li标签
              indexs = [3,4,6,7,8]
              li_list = response.xpath('//*[@id="index2016_wrap"]/div[1]/div[2]/div[2]/div[2]/div[2]/div/ul/li')
      
              for index in indexs:
                  model_list.append(li_list[index])
      
              for li in model_list:
                  #五个板块对应详情页的url
                  detail_url = li.xpath('./a/@href').extract_first()
                  self.model_detail_urls.append(detail_url)
                  yield scrapy.Request(detail_url,callback=self.parse_detail)
          #解析:新闻标题和新闻详情页的url
          def parse_detail(self,response):
              div_list = response.xpath('/html/body/div/div[3]/div[4]/div[1]/div/div/ul/li/div/div')
              for div in div_list:
                  title = div.xpath('.//div[@class="news_title"]/h3/a/text()').extract_first()
                  new_detail_url = div.xpath('.//div[@class="news_title"]/h3/a/@href').extract_first()
      
                  item = WangyiproItem()
                  item['title'] = title
                  #需要通过请求传参将item传递给news_parse
                  yield scrapy.Request(new_detail_url,callback=self.news_parse,meta={'item':item})
          #用来解析新闻内容
          def news_parse(self,response):
              content = response.xpath('//*[@id="endText"]//text()').extract()
              content = ''.join(content)
      
              item = response.meta['item']
              item['content'] = content
      
              yield item
          def closed(self,spider):
              self.bro.quit()
      
      • items中定义字段
      import scrapy
      
      
      class WangyiproItem(scrapy.Item):
          # define the fields for your item here like:
          title = scrapy.Field()
          content = scrapy.Field()
          pass
      
      • pipelines文件内容
      class WangyiproPipeline(object):
          fp = None
          def open_spider(self,spider):
              self.fp = open('./wangyi.txt','w',encoding='utf-8')
          def process_item(self, item, spider):
              self.fp.write(item['title']+':'+item['content']+'
      ')
              return item
          def close_spider(self,spider):
              self.fp.close()
      
      • middlewares文件内容
      from scrapy.http import HtmlResponse
      from time import sleep
      
      
      class WangyiproDownloaderMiddleware(object):
      
      
          def process_request(self, request, spider):
      
              return None
      
          # 可以拦截所有的响应对象:该方法拦截5个指定的响应对象且进行替换操作,其他的响应对象不做处理
          def process_response(self, request, response, spider):
              #定位到5个指定的响应对象
              if request.url in spider.model_detail_urls:
                  print(request.url)
                  bro = spider.bro
                  bro.get(request.url)
                  sleep(2)
                  bro.execute_script('window.scrollTo(0,document.body.scrollHeight)')
                  sleep(2)
                  bro.execute_script('window.scrollTo(0,document.body.scrollHeight)')
                  sleep(2)
                  bro.execute_script('window.scrollTo(0,document.body.scrollHeight)')
                  sleep(2)
                  page_text = bro.page_source
                  new_response = HtmlResponse(url=request.url,body=page_text,encoding='utf-8',request=request)
      
                  return new_response
              else:
                  return response #将原始的响应对象进行返回
      
          def process_exception(self, request, exception, spider):
      
              pass
      
      
      • 最后在settings文件中做如下配置
      #不遵从爬虫Robots协议
      ROBOTSTXT_OBEY = False
      #UA伪装
      USER_AGENT = 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/75.0.3770.100 Safari/537.36'
      #开启下载中间件
      DOWNLOADER_MIDDLEWARES = {
         'wangyiPro.middlewares.WangyiproDownloaderMiddleware': 543,
      }
      #开启管道
      ITEM_PIPELINES = {
         'wangyiPro.pipelines.WangyiproPipeline': 300,
      }
      #显示打印错误信息
      LOG_LEVEL = 'ERROR'
      
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  • 原文地址:https://www.cnblogs.com/Godisgirl/p/11061618.html
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