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  • Scrapy框架

    Scrapy

    Scrapy是一个为了爬取网站数据,提取结构性数据而编写的应用框架。 其可以应用在数据挖掘,信息处理或存储历史数据等一系列的程序中。
    其最初是为了页面抓取 (更确切来说, 网络抓取 )所设计的, 也可以应用在获取API所返回的数据(例如 Amazon Associates Web Services ) 或者通用的网络爬虫。Scrapy用途广泛,可以用于数据挖掘、监测和自动化测试。

    Scrapy 使用了 Twisted异步网络库来处理网络通讯。整体架构大致如下

    Scrapy主要包括了以下组件:

    • 引擎(Scrapy)
      用来处理整个系统的数据流处理, 触发事务(框架核心)
    • 调度器(Scheduler)
      用来接受引擎发过来的请求, 压入队列中, 并在引擎再次请求的时候返回. 可以想像成一个URL(抓取网页的网址或者说是链接)的优先队列, 由它来决定下一个要抓取的网址是什么, 同时去除重复的网址
    • 下载器(Downloader)
      用于下载网页内容, 并将网页内容返回给蜘蛛(Scrapy下载器是建立在twisted这个高效的异步模型上的)
    • 爬虫(Spiders)
      爬虫是主要干活的, 用于从特定的网页中提取自己需要的信息, 即所谓的实体(Item)。用户也可以从中提取出链接,让Scrapy继续抓取下一个页面
    • 项目管道(Pipeline)
      负责处理爬虫从网页中抽取的实体,主要的功能是持久化实体、验证实体的有效性、清除不需要的信息。当页面被爬虫解析后,将被发送到项目管道,并经过几个特定的次序处理数据。
    • 下载器中间件(Downloader Middlewares)
      位于Scrapy引擎和下载器之间的框架,主要是处理Scrapy引擎与下载器之间的请求及响应。
    • 爬虫中间件(Spider Middlewares)
      介于Scrapy引擎和爬虫之间的框架,主要工作是处理蜘蛛的响应输入和请求输出。
    • 调度中间件(Scheduler Middewares)
      介于Scrapy引擎和调度之间的中间件,从Scrapy引擎发送到调度的请求和响应。

    Scrapy运行流程大概如下:

    1. 引擎从调度器中取出一个链接(URL)用于接下来的抓取
    2. 引擎把URL封装成一个请求(Request)传给下载器
    3. 下载器把资源下载下来,并封装成应答包(Response)
    4. 爬虫解析Response
    5. 解析出实体(Item),则交给实体管道进行进一步的处理
    6. 解析出的是链接(URL),则把URL交给调度器等待抓取

    一、安装

    Linux:
        pip3 install scrapy 
    
    Windows:
        pip3 install wheel
        D:twisted.wheel
        pip3 install D:twisted.wheel
        
        pip3 install scrapy 报错:twisted安装错误
        
        pywin32
    
    
    PS: 
        - python3对twisted未完全支持
        - python2    对Scrapy支持更好些
    
    import scrapy
    View Code

    二、基本使用

    1. 基本命令

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    Django:
        django-admin startproject mysite
        cd mysite
        python manage.py startapp app01
         
     
    Scrapy:
        # 创建项目,在当前目录中创建中创建一个项目文件(类似于Django)
        scrapy startproject sp1
            生成目录如下:
                sp1
                    - sp1
                        - spiders          目录,放置创建的爬虫应用
                        - middlewares.py    中间件
                        - items.py          格式化,与pipelines.py一同做持久化
                        - pipelines.py      持久化
                        - settings.py       配置文件
                    - scrapy.cfg            配置
             
        # 创建爬虫应用
        cd sp1
        scrapy genspider xiaohuar xiaohuar.com      # 创建了xiaohuar.py
        scrapy genspider baidu baidu.com        # 创建了baidu.py
         
        # 展示爬虫应用列表
        scrapy list
     
        # 执行爬虫,进入project
        scrapy crawl baidu
        scrapy crawl baidu --nolog

    文件说明:

    • scrapy.cfg  项目的主配置信息。(真正爬虫相关的配置信息在settings.py文件中)
    • items.py    设置数据存储模板,用于结构化数据,如:Django的Model
    • pipelines    数据处理行为,如:一般结构化的数据持久化
    • settings.py 配置文件,如:递归的层数、并发数,延迟下载等
    • spiders      爬虫目录,如:创建文件,编写爬虫规则

    注意:一般创建爬虫文件时,以网站域名命名

    2. 基本操作

    2.1  selector作筛选

    hxs = Selector(response=response)
    # print(hxs)
    user_list = hxs.xpath('//div[@class="item masonry_brick"]')
    for item in user_list:
        price = item.xpath('./span[@class="price"]/text()').extract_first()
        url = item.xpath('div[@class="item_t"]/div[@class="class"]//a/@href').extract_first()
        print(price,url)
    
    result = hxs.xpath('/a[re:test(@href,"http://www.xiaohuar.com/list-1-d+.html")]/@href')
    print(result)
    result = ['http://www.xiaohuar.com/list-1-1.html','http://www.xiaohuar.com/list-1-2.html']
    View Code

    2.2 yield Request(url=url,callback=self.parse)   # 迭代去执行

    2.3 代码的实现

    # -*- coding: utf-8 -*-
    import scrapy
    
    class BaiduSpider(scrapy.Spider):
        name = 'baidu'                          # 爬虫应用的名称,通过此名称启动爬虫命令
        allowed_domains = ['baidu.com']         # 允许的域名
        start_urls = ['http://baidu.com/']     # 起始URL
    
        def parse(self, response):
            print(response.text)
            print(response.body)
    baidu.py
    import scrapy
    from scrapy.selector import HtmlXPathSelector,Selector
    from scrapy.http import Request
    
    class XiaohuarSpider(scrapy.Spider):
        name = 'xiaohuar'
        allowed_domains = ['xiaohuar.com']
        start_urls = ['http://www.xiaohuar.com/hua/']            # 起始url
    
        def parse(self, response):
            # 要废弃
            # hxs = HtmlXPathSelector(response)     # 拿到的内容response转换成对象
            # print(hxs)
            # result = hxs.select('//a[@class="item_list"]')        # select:表示查找;//a :是找页面所有的a标签
            ## result = hxs.select('//a[@class="item_list"]').extract()        # .extract()使返回的值result不是对象,而是列表[<a></a>,<a></a>...]
            ## result = hxs.select('//a[@class="item_list"]').extract_one()        # 拿第一个
            ## result = hxs.select('//a[@class="item_list"]/@href').extract_one()        # 表示拿href属性
            ## result = hxs.select('//a[@class="item_list"]/text()').extract_one()        # 表示拿文本内容
    
            ############################# 以上写法不推荐 #############################
    
    
            ############################### 推荐以下方式 ##############################
    
            hxs = Selector(response=response)
            # print(hxs)
            user_list = hxs.xpath('//div[@class="item masonry_brick"]')     # 拿到的是对象,但可以对这个对象进行循环。找到class="item masonry_brick"的所有div标签
            for item in user_list:                                              # 每个item也是对象
                price = item.xpath('.//span[@class="price"]/text()').extract_first()     # 相对于当前标签的找子子孙孙使用.//span...
                # price = item.xpath('//span[@class="price"]/text()').extract_first()是错误的,因为//span...是向整个html里找
                url = item.xpath('div[@class="item_t"]/div[@class="class"]//a/@href').extract_first()
                # / 表示去儿子里找,//表示到子子孙孙里找。但必须是在内部才有意义。最外层//和/ 都是有特殊意义
                print(price,url)
                
            # 上面找的只是第一页索引的内容,下面找的是分页的内容
            result = hxs.xpath('/a[re:test(@href,"http://www.xiaohuar.com/list-1-d+.html")]/@href')    # re:test() 正则查找
            print(result)
            result = ['http://www.xiaohuar.com/list-1-1.html','http://www.xiaohuar.com/list-1-2.html']
    
            # 规则
            for url in result:
                yield Request(url=url,callback=self.parse)      # yield Request(url=url) 只是把url封装起来放到调度器里了,callback=self.parse源源不断的发请求,迭代去执行
    xiaohuar.py

    补充:

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    选择器:
        //          # 子子孙孙
            /           # 儿子
            /@属性名   # 取属性
            /text()     # 取文本
     
         
    特殊:
        item.xpath('./')    # 相对当前子孙中找
        item.xpath('a')     # 相对当前儿子中找           

    三、深入了解

    (一)以下内容 以登录抽屉并点赞来举例进行深入了解

    1. 起始URL

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    不指明callback=self.parse1情况下,默认下载完后执行 parse函数
     
    import scrapy
    from scrapy.http import Request
     
    class ChoutiSpider(scrapy.Spider):
        name = 'chouti'
        allowed_domains = ['chouti.com']
        start_urls = ['http://chouti.com/']
     
        def start_requests(self):       # 看源码,如果我们没有start_requests函数,默认会执行继承的类scrapy.Spider里的start_requests方法
            for url in self.start_urls:
                yield Request(url, dont_filter=True,callback=self.parse1)       # dont_filter=True对爬取的url不去重
     
        def parse1(self, response):
            pass

    2. 如何发POST请求,携带请求头,cookie,数据

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    requests.get(params={},headers={},cookies={})
    requests.post(params={},headers={},cookies={},data={},json={})

    2.1 requests请求相关的参数

    url, 
    method='GET', 
    headers=None, 
    body=None,
    cookies=None,
    ...
    View Code

    2.2 GET请求

    url, 
    method='GET', 
    headers={}, 
    cookies={}, cookiejar            # cookies可以是字典也可以是cookiejar对象
    View Code

    2.3 POST请求

    url, 
    method='GET', 
    headers={}, 
    cookies={}, cookiejar            # cookies可以是字典也可以是cookiejar对象
    body=None,                        # 请求体
        请求头application/x-www-form-urlencoded; charset=UTF-8格式下,数据"phone=86155fa&password=asdf&oneMonth=1" 
        请求头json格式application/json; charset=UTF-8,数据时字典格式"{k1:'v1','k2':'v2'}"
        
        当请求头application/x-www-form-urlencoded; charset=UTF-8格式下,form_data = {'user':'xyp','pwd': 123}需要for循环拼接成"user=xyp$pwd=123"
        但scrapy框架提供了模块可以自动完成拼接
            import urllib.parse
            data = urllib.parse.urlencode({'k1':'v1','k2':'v2'})
            print(data)
            # ---> "k1=v1&k2=v2"  
             
            
        请求头json格式application/json; charset=UTF-8格式下
            json.dumsp({k1:'v1','k2':'v2'})
            
            "{k1:'v1','k2':'v2'}"   
    View Code

    2.4 POST请求示例

     Request(
        url='http://dig.chouti.com/login',
        method='POST',
        headers={'Content-Type': 'application/x-www-form-urlencoded; charset=UTF-8'},
        body='phone=8615131255089&password=pppppppp&oneMonth=1',
        callback=self.check_login
    )
    View Code

    2.5 cookie

    Request(
        url='http://dig.chouti.com/login',
        method='POST',
        headers={'Content-Type': 'application/x-www-form-urlencoded; charset=UTF-8'},
        body='phone=8615131255089&password=pppppppp&oneMonth=1',
        cookies=self.cookie_dict,
        callback=self.check_login
    )
    View Code

    具体代码实现:

    #以下代码是循环不停的,加上去重操作
    # -*- coding: utf-8 -*-
    import scrapy
    from scrapy.http import Request
    from scrapy.selector import Selector
    
    class ChoutiSpider(scrapy.Spider):
        name = 'chouti'
        allowed_domains = ['chouti.com']
        start_urls = ['http://chouti.com/']
        cookie_dict = {}
        """
        1. 发送一个GET请求,抽屉
           获取cookie
           
        2. 用户密码POST登录:携带上一次cookie
           返回值:9999表示登录成功
           
        3. 为所欲为,携带cookie,点赞
        """
        def start_requests(self):       # 看源码,如果我们没有start_requests函数,默认会执行继承的类scrapy.Spider里的start_requests方法
            for url in self.start_urls:
                yield Request(url, dont_filter=True,callback=self.parse1)       # dont_filter=True对爬取的url不去重
    
        def parse1(self,response):
            # response.text 首页所有内容
            from scrapy.http.cookies import CookieJar
            cookie_jar = CookieJar() # 对象,对象中封装了 cookies
            cookie_jar.extract_cookies(response, response.request) # 去响应中获取cookies
    
            for k, v in cookie_jar._cookies.items():
                for i, j in v.items():
                    for m, n in j.items():
                        self.cookie_dict[m] = n.value
            post_dict = {
                'phone': '8615131255089',
                'password': 'woshiniba',
                'oneMonth': 1,
            }
            import urllib.parse
    
            # 目的:发送POST进行登录
            yield Request(
                url="http://dig.chouti.com/login",
                method='POST',
                cookies=self.cookie_dict,       # 或者cookies=self.cookie_jar 也行
                body=urllib.parse.urlencode(post_dict),     # 要发送的body数据
                headers={'Content-Type':'application/x-www-form-urlencoded; charset=UTF-8'},
                callback=self.parse2                        # 回调函数
            )
    
        def parse2(self,response):
            print(response.text)        # 这里需根据response判断是否登录成功,此处省略判断
            # 获取新闻列表
            yield Request(url='http://dig.chouti.com/',cookies=self.cookie_dict,callback=self.parse3)
    
        def parse3(self,response):
    
            # 找div,class=part2, 获取share-linkid属性,得到文章id
            hxs = Selector(response)
            link_id_list = hxs.xpath('//div[@class="part2"]/@share-linkid').extract()       # 取到当前页面所有的文章id
            print(link_id_list)
            for link_id in link_id_list:
                # 获取每一个ID去点赞
                base_url = "http://dig.chouti.com/link/vote?linksId=%s" %(link_id,)
                yield Request(url=base_url,method="POST",cookies=self.cookie_dict,callback=self.parse4)
    
    
            #################### 以上只是把首页文章全部点赞 ####################
            
            
            ####################### 分页每个文章都点赞 ####################### 
            
            page_list = hxs.xpath('//div[@id="dig_lcpage"]//a/@href').extract()     # 拿到所有的页码
            for page in page_list:
                #page : /all/hot/recent/2
                page_url = "http://dig.chouti.com%s" %(page,)
                yield Request(url=page_url,method='GET',callback=self.parse3)       # 循环不同页码点赞
    
        def parse4(self, response):
            print(response.text)
    自动登录抽屉并点赞

    (二)以下内容 以获取煎蛋文章标题和url来举例进行持久化的了解

    3. 持久化

    3.1 获取煎蛋文章标题和url:具体代码及持久化详细注释

    # -*- coding: utf-8 -*-
    import scrapy
    from scrapy.http import Request
    from scrapy.selector import Selector
    
    class JianDanSpider(scrapy.Spider):
        name = 'jiandan'
        allowed_domains = ['jandan.net']
        start_urls = ['http://jandan.net/']
    
        def start_requests(self):
            for url in self.start_urls:
                yield Request(url, dont_filter=True,callback=self.parse1)
        def parse1(self,response):
            # response.text 首页所有内容
            hxs = Selector(response)
            a_list = hxs.xpath('//div[@class="indexs"]/h2')
            for tag in a_list:
                url = tag.xpath('./a/@href').extract_first()
                text = tag.xpath('./a/text()').extract_first()
                from ..items import Sp2Item
                yield Sp2Item(url=url,text=text)        # 创建特殊的对象直接交给pipeline,没有做持久化操作,只是把工作转交给了pipeline
            #以上获取的是首页文章的文本和url
            # 获取页码 [url,url]
            """
            for url in url_list:
                yield Request(url=url,callback=self.parse1)
            """
    jiandan.py
    import scrapy
    
    class Sp2Item(scrapy.Item):
        # define the fields for your item here like:
        # name = scrapy.Field()
        url = scrapy.Field()
        text = scrapy.Field()
    items.py
    # -*- coding: utf-8 -*-
    
    # Define your item pipelines here
    #
    # Don't forget to add your pipeline to the ITEM_PIPELINES setting
    # See: http://doc.scrapy.org/en/latest/topics/item-pipeline.html
    
    
    class Sp2Pipeline(object):
        def __init__(self):
            self.f = None
    
        def process_item(self, item, spider):
            """
    
            :param item:  爬虫中yield回来的对象
            :param spider: 爬虫对象 obj = JianDanSpider()
            :return:
            """
            if spider.name == 'jiadnan':
                pass
            print(item)
            self.f.write('....')
            # 将item传递给下一个pipeline的process_item方法
            # return item
            # from scrapy.exceptions import DropItem
            # raise DropItem()  下一个pipeline的process_item方法不在执行
    
        @classmethod
        def from_crawler(cls, crawler):
            """
            初始化时候,用于创建pipeline对象
            :param crawler:
            :return:
            """
            # val = crawler.settings.get('MMMM')
            print('执行pipeline的from_crawler,进行实例化对象')
            return cls()
    
        def open_spider(self,spider):
            """
            爬虫开始执行时,调用
            :param spider:
            :return:
            """
            print('打开爬虫')
            self.f = open('a.log','a+')
    
        def close_spider(self,spider):
            """
            爬虫关闭时,被调用
            :param spider:
            :return:
            """
            self.f.close()
    pipelines.py
    ITEM_PIPELINES = {
               'sp2.pipelines.Sp2Pipeline': 300,        # 300是优先级
            }
    settings.py

    3.2 总结

    ① pipeline执行的前提

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    - spider中yield Item对象
    - settings中注册
        ITEM_PIPELINES = {
           'sp2.pipelines.Sp2Pipeline': 300,        # 300为优先级,越小越先执行
           'sp2.pipelines.Sp3Pipeline': 100,
        }

    ② 编写pipeline

    class Sp2Pipeline(object):
        def __init__(self):
            self.f = None
    
        def process_item(self, item, spider):
            """
    
            :param item:  爬虫中yield回来的对象
            :param spider: 爬虫对象 obj = JianDanSpider()
            :return:
            """
            print(item)
            self.f.write('....')
            return item
            # from scrapy.exceptions import DropItem
            # raise DropItem()  下一个pipeline的process_item方法不在执行
    
        @classmethod
        def from_crawler(cls, crawler):
            """
            初始化时候,用于创建pipeline对象
            :param crawler:
            :return:
            """
            # val = crawler.settings.get('MMMM')
            print('执行pipeline的from_crawler,进行实例化对象')
            return cls()
    
        def open_spider(self,spider):
            """
            爬虫开始执行时,调用
            :param spider:
            :return:
            """
            print('打开爬虫')
            self.f = open('a.log','a+')
    
        def close_spider(self,spider):
            """
            爬虫关闭时,被调用
            :param spider:
            :return:
            """
            self.f.close()
    View Code
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    当注册Sp2Pipeline和Sp3Pipeline时,先执行优先级高的__init__函数初始化方法,from_crawler方法,open_spider方法。但是不继续执行优先级高的爬虫方法。
    而是等优先级低的执行完__init__函数初始化方法,from_crawler方法,open_spider方法后才会执行爬虫方法。
     
    PipeLine是全局生效,所有爬虫都会执行,个别做特殊操作: 通过spider.name判断

    ③ pipelines.py可以自定义的方法,及程序运行顺序 

    # class CustomPipeline(object):
    #     def __init__(self,val):
    #         self.val = val
    #
    #     def process_item(self, item, spider):
    #         # 操作并进行持久化
    #
    #         # return表示会被后续的pipeline继续处理
    #         return item
    #
    #         # 表示将item丢弃,不会被后续pipeline处理
    #         # raise DropItem()
    #
    #     @classmethod
    #     def from_crawler(cls, crawler):
    #         """
    #         初始化时候,用于创建pipeline对象
    #         :param crawler:
    #         :return:
    #         """
    #         val = crawler.settings.get('MMMM')
    #         return cls(val)
    #
    #     def open_spider(self,spider):
    #         """
    #         爬虫开始执行时,调用
    #         :param spider:
    #         :return:
    #         """
    #         print('000000')
    #
    #     def close_spider(self,spider):
    #         """
    #         爬虫关闭时,被调用
    #         :param spider:
    #         :return:
    #         """
    #         print('111111')
    
    """
    检测 CustomPipeline类中是否有 from_crawler方法
    如果有:
           obj = 类.from_crawler()
    如果没有:
           obj = 类()
    obj.open_spider()
    
    while True:
        爬虫运行,并且执行parse各种各样的爬虫方法,yield item
        obj.process_item()
    
    obj.close_spider()    
    
    """
    View Code

    以上以例子为了解的内容结束。

    4. 自定义去重规则

    4.1 配置文件中指定

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    scrapy默认使用 scrapy.dupefilter.RFPDupeFilter 进行去重,默认在settings相关配置有:
        DUPEFILTER_CLASS = 'scrapy.dupefilter.RFPDupeFilter'
        DUPEFILTER_DEBUG = False
        JOBDIR = "保存范文记录的日志路径,如:/root/"  # 最终路径为 /root/requests.seen

    4.2 自定义URL去重操作

    class RepeatUrl:
        def __init__(self):
            self.visited_url = set() # 放在当前服务的内存
    
        @classmethod
        def from_settings(cls, settings):
            """
            初始化时,调用
            :param settings:
            :return:
            """
            return cls()
    
        def request_seen(self, request):
            """
            检测当前请求是否已经被访问过
            :param request:
            :return: True表示已经访问过;False表示未访问过
            """
            if request.url in self.visited_url:
                return True
            self.visited_url.add(request.url)
            return False
    
        def open(self):
            """
            开始爬去请求时,调用
            :return:
            """
            print('open replication')
    
        def close(self, reason):
            """
            结束爬虫爬取时,调用
            :param reason:
            :return:
            """
            print('close replication')
    
        def log(self, request, spider):
            """
            记录日志
            :param request:
            :param spider:
            :return:
            """
            print('repeat', request.url)
    rep.py
    DUPEFILTER_CLASS = 'sp2.rep.RepeatUrl'
    settings.py

    5. 自定义扩展【基于信号】

    from scrapy import signals
    
    class MyExtension(object):
        def __init__(self, value):
            self.value = value
    
        @classmethod
        def from_crawler(cls, crawler):
            val = crawler.settings.getint('MMMM')
            ext = cls(val)
    
            # 在scrapy中注册信号: spider_opened
            crawler.signals.connect(ext.opened, signal=signals.spider_opened)        # ext.opened触发信号时执行的函数 
                    
            # 在scrapy中注册信号: spider_closed
            crawler.signals.connect(ext.closed, signal=signals.spider_closed)
            
            return ext
    
        def opened(self, spider):
            print('open')
    
        def closed(self, spider):
            print('close')
    extends.py
    EXTENSIONS = {
       # 'scrapy.extensions.telnet.TelnetConsole': None,
    }
    settings.py注册

    6. 中间件

    6.1 爬虫中间件

    SPIDER_MIDDLEWARES = {
       'sp3.middlewares.Sp3SpiderMiddleware': 543,
    }
    settings.py注册
    class Sp3SpiderMiddleware(object):
    
        def process_spider_input(self,response, spider):
            """
            下载完成,执行,然后交给parse处理
            :param response: 
            :param spider: 
            :return: 
            """
            pass
    
        def process_spider_output(self,response, result, spider):
            """
            spider处理完成,返回时调用
            :param response:
            :param result:
            :param spider:
            :return: 必须返回包含 Request 或 Item 对象的可迭代对象(iterable)
            """
            return result
    
        def process_spider_exception(self,response, exception, spider):
            """
            异常调用
            :param response:
            :param exception:
            :param spider:
            :return: None,继续交给后续中间件处理异常;含 Response 或 Item 的可迭代对象(iterable),交给调度器或pipeline
            """
            return None
    
    
        def process_start_requests(self,start_requests, spider):
            """
            爬虫启动时调用
            :param start_requests:
            :param spider:
            :return: 包含 Request 对象的可迭代对象
            """
            return start_requests
    middlewares.py

    6.2 下载中间件

    DOWNLOADER_MIDDLEWARES = {
       'sp3.middlewares.DownMiddleware1': 543,
    }
    settings.py注册
    class DownMiddleware1(object):
        def process_request(self, request, spider):
            """
            请求需要被下载时,经过所有下载器中间件的process_request调用
            :param request: 
            :param spider: 
            :return:  
                None,继续后续中间件去下载;
                Response对象,停止process_request的执行,开始执行process_response
                Request对象,停止中间件的执行,将Request重新调度器
                raise IgnoreRequest异常,停止process_request的执行,开始执行process_exception
            """
            
            
            """
            from scrapy.http import Request
            # print(request)
            # request.method = "POST"
            request.headers['proxy'] = "{'ip_port': '111.11.228.75:80', 'user_pass': ''},"
            return None
            """
            
            
            """
            from scrapy.http import Response
            import requests
            v = request.get('http://www.baidu.com')
            data = Response(url='xxxxxxxx',body=v.content,request=request)
            return data
             """
            
            
            pass
    
    
    
        def process_response(self, request, response, spider):
            """
            spider处理完成,返回时调用
            :param response:
            :param result:
            :param spider:
            :return: 
                Response 对象:转交给其他中间件process_response
                Request 对象:停止中间件,request会被重新调度下载
                raise IgnoreRequest 异常:调用Request.errback
            """
            print('response1')
            return response
    
        def process_exception(self, request, exception, spider):
            """
            当下载处理器(download handler)或 process_request() (下载中间件)抛出异常
            :param response:
            :param exception:
            :param spider:
            :return: 
                None:继续交给后续中间件处理异常;
                Response对象:停止后续process_exception方法
                Request对象:停止中间件,request将会被重新调用下载
            """
            return None
    middlewares.py

    7. 自定义命令【scrapy crawl baidu看源码的入口】

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    在spiders同级创建任意目录,如:commands
    在其中创建 crawlall.py 文件 (此处文件名就是自定义的命令)
    class Command(ScrapyCommand):
    
        requires_project = True
    
        def syntax(self):
            return '[options]'
    
        def short_desc(self):
            return 'Runs all of the spiders'
    
        def run(self, args, opts):
            # 爬虫列表
            spider_list = self.crawler_process.spiders.list()
            for name in spider_list:
                print(name)                                                # #
                # 初始化爬虫
                self.crawler_process.crawl(name, **opts.__dict__)
            # 开始执行所有的爬虫
            self.crawler_process.start()
    crawlall.py
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    在settings.py 中添加配置 COMMANDS_MODULE = '项目名称.目录名称'
    在项目目录执行命令:scrapy crawlall
             
    就多了命令:scrapy crawlall      
    scrapy crawlall --nolog     #---> xxx
    scrapy genspider ooo ooo.com
    scrapy crawlall --nolog    
    '''
        ---> xxx
             ooo
    '''

    8. 其他(scrapy配置文件)

    # -*- coding: utf-8 -*-
    
    # Scrapy settings for step8_king project
    #
    # For simplicity, this file contains only settings considered important or
    # commonly used. You can find more settings consulting the documentation:
    #
    #     http://doc.scrapy.org/en/latest/topics/settings.html
    #     http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html
    #     http://scrapy.readthedocs.org/en/latest/topics/spider-middleware.html
    
    # 1. 爬虫名称
    BOT_NAME = 'step8_king'    
    
    
    # 2. 爬虫应用路径
    SPIDER_MODULES = ['step8_king.spiders']
    NEWSPIDER_MODULE = 'step8_king.spiders'
    
    
    # Crawl responsibly by identifying yourself (and your website) on the user-agent
    # 3. 客户端 user-agent请求头                
    # USER_AGENT = 'step8_king (+http://www.yourdomain.com)'                # user-agent客户端设备
    
    
    # Obey robots.txt rules
    # 4. 禁止爬虫配置
    # ROBOTSTXT_OBEY = False            # 是否遵循爬虫协议                    
    
    
    # Configure maximum concurrent requests performed by Scrapy (default: 16)
    # 5. 并发请求数
    # CONCURRENT_REQUESTS = 4
    
    
    # Configure a delay for requests for the same website (default: 0)
    # See http://scrapy.readthedocs.org/en/latest/topics/settings.html#download-delay
    # See also autothrottle settings and docs
    # 6. 延迟下载秒数
    # DOWNLOAD_DELAY = 2
    
    
    # The download delay setting will honor only one of:        # 如果设置单域名访问并发数和单IP访问并发数会把第五条并发请求数覆盖
    # 7. 单域名访问并发数,并且延迟下次秒数也应用在每个域名
    # CONCURRENT_REQUESTS_PER_DOMAIN = 2
    # 单IP访问并发数,如果有值则忽略:CONCURRENT_REQUESTS_PER_DOMAIN,并且延迟下次秒数也应用在每个IP
    # CONCURRENT_REQUESTS_PER_IP = 3
    
    
    # Disable cookies (enabled by default)
    # 8. 是否支持cookie,cookiejar进行操作cookie
    # COOKIES_ENABLED = True
    # COOKIES_DEBUG = True
    
    
    # Disable Telnet Console (enabled by default)
    # 9. Telnet用于查看当前爬虫的信息,操作爬虫等...            # 对于你的爬虫进行监控
    #    使用telnet ip port ,然后通过命令操作
    # TELNETCONSOLE_ENABLED = True
    # TELNETCONSOLE_HOST = '127.0.0.1'
    # TELNETCONSOLE_PORT = [6023,]
    
    
    # 10. 默认请求头,设置所有的请求头,但是优先级比较低,在爬虫名.py文件中设置请求头优先级高一些
    # 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',
    # }
    
    
    # Configure item pipelines
    # See http://scrapy.readthedocs.org/en/latest/topics/item-pipeline.html
    # 11. 定义pipeline处理请求
    # ITEM_PIPELINES = {
    #    'step8_king.pipelines.JsonPipeline': 700,
    #    'step8_king.pipelines.FilePipeline': 500,
    # }
    
    
    
    # 12. 自定义扩展,基于信号进行调用
    # Enable or disable extensions
    # See http://scrapy.readthedocs.org/en/latest/topics/extensions.html
    # EXTENSIONS = {
    #     # 'step8_king.extensions.MyExtension': 500,
    # }
    
    
    # 13. 爬虫允许的最大深度,可以通过meta查看当前深度;0表示无深度
    # DEPTH_LIMIT = 3
    
    
    # 14. 爬取时,0表示深度优先Lifo(默认);1表示广度优先FiFo
    
    # 后进先出,深度优先
    # DEPTH_PRIORITY = 0
    # SCHEDULER_DISK_QUEUE = 'scrapy.squeue.PickleLifoDiskQueue'
    # SCHEDULER_MEMORY_QUEUE = 'scrapy.squeue.LifoMemoryQueue'
    # 先进先出,广度优先
    
    # DEPTH_PRIORITY = 1
    # SCHEDULER_DISK_QUEUE = 'scrapy.squeue.PickleFifoDiskQueue'
    # SCHEDULER_MEMORY_QUEUE = 'scrapy.squeue.FifoMemoryQueue'
    
    
    # 15. 调度器队列
    # SCHEDULER = 'scrapy.core.scheduler.Scheduler'        # scrapy框架默认的调度器,与14条队列结合
    # from scrapy.core.scheduler import Scheduler
    
    
    # 16. 访问URL去重
    # DUPEFILTER_CLASS = 'step8_king.duplication.RepeatUrl'
    
    
    # Enable and configure the AutoThrottle extension (disabled by default)
    # See http://doc.scrapy.org/en/latest/topics/autothrottle.html
    
    """
    17. 自动限速算法
        from scrapy.contrib.throttle import AutoThrottle
        自动限速设置
        1. 获取最小延迟 DOWNLOAD_DELAY
        2. 获取最大延迟 AUTOTHROTTLE_MAX_DELAY
        3. 设置初始下载延迟 AUTOTHROTTLE_START_DELAY
        4. 当请求下载完成后,获取其"连接"时间 latency,即:请求连接到接受到响应头之间的时间
        5. 用于计算的... AUTOTHROTTLE_TARGET_CONCURRENCY
        target_delay = latency / self.target_concurrency
        new_delay = (slot.delay + target_delay) / 2.0 # 表示上一次的延迟时间
        new_delay = max(target_delay, new_delay)
        new_delay = min(max(self.mindelay, new_delay), self.maxdelay)
        slot.delay = new_delay
    """
    
    # 开始自动限速
    # AUTOTHROTTLE_ENABLED = True
    # The initial download delay
    # 初始下载延迟
    # AUTOTHROTTLE_START_DELAY = 5
    # The maximum download delay to be set in case of high latencies
    # 最大下载延迟
    # AUTOTHROTTLE_MAX_DELAY = 10
    # The average number of requests Scrapy should be sending in parallel to each remote server
    # 平均每秒并发数
    # AUTOTHROTTLE_TARGET_CONCURRENCY = 1.0
    
    # Enable showing throttling stats for every response received:
    # 是否显示
    # AUTOTHROTTLE_DEBUG = True
    
    # Enable and configure HTTP caching (disabled by default)
    # See http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html#httpcache-middleware-settings
    
    
    """
    18. 启用缓存
        目的用于将已经发送的请求或相应缓存下来,以便以后使用
        
        from scrapy.downloadermiddlewares.httpcache import HttpCacheMiddleware
        from scrapy.extensions.httpcache import DummyPolicy
        from scrapy.extensions.httpcache import FilesystemCacheStorage
    """
    # 是否启用缓存策略
    # HTTPCACHE_ENABLED = True
    
    # 缓存策略:所有请求均缓存,下次在请求直接访问原来的缓存即可
    # HTTPCACHE_POLICY = "scrapy.extensions.httpcache.DummyPolicy"
    # 缓存策略:根据Http响应头:Cache-Control、Last-Modified 等进行缓存的策略
    # HTTPCACHE_POLICY = "scrapy.extensions.httpcache.RFC2616Policy"
    
    # 缓存超时时间
    # HTTPCACHE_EXPIRATION_SECS = 0
    
    # 缓存保存路径
    # HTTPCACHE_DIR = 'httpcache'
    
    # 缓存忽略的Http状态码
    # HTTPCACHE_IGNORE_HTTP_CODES = []
    
    # 缓存存储的插件
    # HTTPCACHE_STORAGE = 'scrapy.extensions.httpcache.FilesystemCacheStorage'
    
    
    """
    19. 代理,需要在环境变量中设置
        from scrapy.contrib.downloadermiddleware.httpproxy import HttpProxyMiddleware
        
        方式一:使用默认
            os.environ
            {
                http_proxy:http://root:woshiniba@192.168.11.11:9999/
                https_proxy:http://192.168.11.11:9999/
            }
        方式二:使用自定义下载中间件
        
        def to_bytes(text, encoding=None, errors='strict'):
            if isinstance(text, bytes):
                return text
            if not isinstance(text, six.string_types):
                raise TypeError('to_bytes must receive a unicode, str or bytes '
                                'object, got %s' % type(text).__name__)
            if encoding is None:
                encoding = 'utf-8'
            return text.encode(encoding, errors)
            
        class ProxyMiddleware(object):
            def process_request(self, request, spider):
                PROXIES = [
                    {'ip_port': '111.11.228.75:80', 'user_pass': ''},
                    {'ip_port': '120.198.243.22:80', 'user_pass': ''},
                    {'ip_port': '111.8.60.9:8123', 'user_pass': ''},
                    {'ip_port': '101.71.27.120:80', 'user_pass': ''},
                    {'ip_port': '122.96.59.104:80', 'user_pass': ''},
                    {'ip_port': '122.224.249.122:8088', 'user_pass': ''},
                ]
                proxy = random.choice(PROXIES)
                if proxy['user_pass'] is not None:
                    request.meta['proxy'] = to_bytes("http://%s" % proxy['ip_port'])
                    encoded_user_pass = base64.encodestring(to_bytes(proxy['user_pass']))
                    request.headers['Proxy-Authorization'] = to_bytes('Basic ' + encoded_user_pass)
                    print "**************ProxyMiddleware have pass************" + proxy['ip_port']
                else:
                    print "**************ProxyMiddleware no pass************" + proxy['ip_port']
                    request.meta['proxy'] = to_bytes("http://%s" % proxy['ip_port'])
        
        DOWNLOADER_MIDDLEWARES = {
           'step8_king.middlewares.ProxyMiddleware': 500,
        }
        
    """
    
    
    
    """
    20. Https访问
        Https访问时有两种情况:
        1. 要爬取网站使用的可信任证书(默认支持)
            DOWNLOADER_HTTPCLIENTFACTORY = "scrapy.core.downloader.webclient.ScrapyHTTPClientFactory"
            DOWNLOADER_CLIENTCONTEXTFACTORY = "scrapy.core.downloader.contextfactory.ScrapyClientContextFactory"
            
        2. 要爬取网站使用的自定义证书
            DOWNLOADER_HTTPCLIENTFACTORY = "scrapy.core.downloader.webclient.ScrapyHTTPClientFactory"
            DOWNLOADER_CLIENTCONTEXTFACTORY = "step8_king.https.MySSLFactory"
            
            # https.py
            from scrapy.core.downloader.contextfactory import ScrapyClientContextFactory
            from twisted.internet.ssl import (optionsForClientTLS, CertificateOptions, PrivateCertificate)
            
            class MySSLFactory(ScrapyClientContextFactory):
                def getCertificateOptions(self):
                    from OpenSSL import crypto
                    v1 = crypto.load_privatekey(crypto.FILETYPE_PEM, open('/Users/xyp/client.key.unsecure', mode='r').read())
                    v2 = crypto.load_certificate(crypto.FILETYPE_PEM, open('/Users/xyp/client.pem', mode='r').read())
                    return CertificateOptions(
                        privateKey=v1,  # pKey对象
                        certificate=v2,  # X509对象
                        verify=False,
                        method=getattr(self, 'method', getattr(self, '_ssl_method', None))
                    )
        其他:
            相关类
                scrapy.core.downloader.handlers.http.HttpDownloadHandler
                scrapy.core.downloader.webclient.ScrapyHTTPClientFactory
                scrapy.core.downloader.contextfactory.ScrapyClientContextFactory
            相关配置
                DOWNLOADER_HTTPCLIENTFACTORY
                DOWNLOADER_CLIENTCONTEXTFACTORY
    
    """
    
    
    
    """
    21. 爬虫中间件
        class SpiderMiddleware(object):
    
            def process_spider_input(self,response, spider):
                '''
                下载完成,执行,然后交给parse处理
                :param response: 
                :param spider: 
                :return: 
                '''
                pass
        
            def process_spider_output(self,response, result, spider):
                '''
                spider处理完成,返回时调用
                :param response:
                :param result:
                :param spider:
                :return: 必须返回包含 Request 或 Item 对象的可迭代对象(iterable)
                '''
                return result
        
            def process_spider_exception(self,response, exception, spider):
                '''
                异常调用
                :param response:
                :param exception:
                :param spider:
                :return: None,继续交给后续中间件处理异常;含 Response 或 Item 的可迭代对象(iterable),交给调度器或pipeline
                '''
                return None
        
        
            def process_start_requests(self,start_requests, spider):
                '''
                爬虫启动时调用
                :param start_requests:
                :param spider:
                :return: 包含 Request 对象的可迭代对象
                '''
                return start_requests
        
        内置爬虫中间件:
            'scrapy.contrib.spidermiddleware.httperror.HttpErrorMiddleware': 50,
            'scrapy.contrib.spidermiddleware.offsite.OffsiteMiddleware': 500,
            'scrapy.contrib.spidermiddleware.referer.RefererMiddleware': 700,
            'scrapy.contrib.spidermiddleware.urllength.UrlLengthMiddleware': 800,
            'scrapy.contrib.spidermiddleware.depth.DepthMiddleware': 900,
    
    """
    # from scrapy.contrib.spidermiddleware.referer import RefererMiddleware
    # Enable or disable spider middlewares
    # See http://scrapy.readthedocs.org/en/latest/topics/spider-middleware.html
    SPIDER_MIDDLEWARES = {
       # 'step8_king.middlewares.SpiderMiddleware': 543,
    }
    
    
    """
    22. 下载中间件
        class DownMiddleware1(object):
            def process_request(self, request, spider):
                '''
                请求需要被下载时,经过所有下载器中间件的process_request调用
                :param request:
                :param spider:
                :return:
                    None,继续后续中间件去下载;
                    Response对象,停止process_request的执行,开始执行process_response
                    Request对象,停止中间件的执行,将Request重新调度器
                    raise IgnoreRequest异常,停止process_request的执行,开始执行process_exception
                '''
                pass
        
        
        
            def process_response(self, request, response, spider):
                '''
                spider处理完成,返回时调用
                :param response:
                :param result:
                :param spider:
                :return:
                    Response 对象:转交给其他中间件process_response
                    Request 对象:停止中间件,request会被重新调度下载
                    raise IgnoreRequest 异常:调用Request.errback
                '''
                print('response1')
                return response
        
            def process_exception(self, request, exception, spider):
                '''
                当下载处理器(download handler)或 process_request() (下载中间件)抛出异常
                :param response:
                :param exception:
                :param spider:
                :return:
                    None:继续交给后续中间件处理异常;
                    Response对象:停止后续process_exception方法
                    Request对象:停止中间件,request将会被重新调用下载
                '''
                return None
    
        
        默认下载中间件
        {
            'scrapy.contrib.downloadermiddleware.robotstxt.RobotsTxtMiddleware': 100,
            'scrapy.contrib.downloadermiddleware.httpauth.HttpAuthMiddleware': 300,
            'scrapy.contrib.downloadermiddleware.downloadtimeout.DownloadTimeoutMiddleware': 350,
            'scrapy.contrib.downloadermiddleware.useragent.UserAgentMiddleware': 400,
            'scrapy.contrib.downloadermiddleware.retry.RetryMiddleware': 500,
            'scrapy.contrib.downloadermiddleware.defaultheaders.DefaultHeadersMiddleware': 550,
            'scrapy.contrib.downloadermiddleware.redirect.MetaRefreshMiddleware': 580,
            'scrapy.contrib.downloadermiddleware.httpcompression.HttpCompressionMiddleware': 590,
            'scrapy.contrib.downloadermiddleware.redirect.RedirectMiddleware': 600,
            'scrapy.contrib.downloadermiddleware.cookies.CookiesMiddleware': 700,
            'scrapy.contrib.downloadermiddleware.httpproxy.HttpProxyMiddleware': 750,
            'scrapy.contrib.downloadermiddleware.chunked.ChunkedTransferMiddleware': 830,
            'scrapy.contrib.downloadermiddleware.stats.DownloaderStats': 850,
            'scrapy.contrib.downloadermiddleware.httpcache.HttpCacheMiddleware': 900,
        }
    
    """
    # from scrapy.contrib.downloadermiddleware.httpauth import HttpAuthMiddleware
    # Enable or disable downloader middlewares
    # See http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html
    # DOWNLOADER_MIDDLEWARES = {
    #    'step8_king.middlewares.DownMiddleware1': 100,
    #    'step8_king.middlewares.DownMiddleware2': 500,
    # }
    settings.py
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  • 原文地址:https://www.cnblogs.com/lianxuebin/p/8341986.html
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