• 爬虫性能相关


    性能相关

    在编写爬虫时,性能的消耗主要在IO请求中,当单进程单线程模式下请求URL时必然会引起等待,从而使得请求整体变慢。

    import requests
    
    def fetch_async(url):
        response = requests.get(url)
        return response
    
    
    url_list = ['http://www.github.com', 'http://www.bing.com']
    
    for url in url_list:
        fetch_async(url)
    1.同步执行
    from concurrent.futures import ThreadPoolExecutor
    import requests
    
    
    def fetch_async(url):
        response = requests.get(url)
        return response
    
    
    url_list = ['http://www.github.com', 'http://www.bing.com']
    pool = ThreadPoolExecutor(5)
    for url in url_list:
        pool.submit(fetch_async, url)
    pool.shutdown(wait=True)
    2.多线程执行
    from concurrent.futures import ThreadPoolExecutor
    import requests
    
    def fetch_async(url):
        response = requests.get(url)
        return response
    
    
    def callback(future):
        print(future.result())
    
    
    url_list = ['http://www.github.com', 'http://www.bing.com']
    pool = ThreadPoolExecutor(5)
    for url in url_list:
        v = pool.submit(fetch_async, url)
        v.add_done_callback(callback)
    pool.shutdown(wait=True)
    2.多线程+回调函数执行
    from concurrent.futures import ProcessPoolExecutor
    import requests
    
    def fetch_async(url):
        response = requests.get(url)
        return response
    
    
    url_list = ['http://www.github.com', 'http://www.bing.com']
    pool = ProcessPoolExecutor(5)
    for url in url_list:
        pool.submit(fetch_async, url)
    pool.shutdown(wait=True)
    3.多进程执行
    from concurrent.futures import ProcessPoolExecutor
    import requests
    
    
    def fetch_async(url):
        response = requests.get(url)
        return response
    
    
    def callback(future):
        print(future.result())
    
    
    url_list = ['http://www.github.com', 'http://www.bing.com']
    pool = ProcessPoolExecutor(5)
    for url in url_list:
        v = pool.submit(fetch_async, url)
        v.add_done_callback(callback)
    pool.shutdown(wait=True)
    3.多进程+回调函数执行

    通过上述代码均可以完成对请求性能的提高,对于多线程和多进行的缺点是在IO阻塞时会造成了线程和进程的浪费,所以异步IO回事首选:

    import asyncio
    
    
    @asyncio.coroutine
    def func1():
        print('before...func1......')
        yield from asyncio.sleep(5)
        print('end...func1......')
    
    
    tasks = [func1(), func1()]
    
    loop = asyncio.get_event_loop()
    loop.run_until_complete(asyncio.gather(*tasks))
    loop.close()
    1.asyncio示例1
    import asyncio
    
    
    @asyncio.coroutine
    def fetch_async(host, url='/'):
        print(host, url)
        reader, writer = yield from asyncio.open_connection(host, 80)
    
        request_header_content = """GET %s HTTP/1.0
    Host: %s
    
    """ % (url, host,)
        request_header_content = bytes(request_header_content, encoding='utf-8')
    
        writer.write(request_header_content)
        yield from writer.drain()
        text = yield from reader.read()
        print(host, url, text)
        writer.close()
    
    tasks = [
        fetch_async('www.cnblogs.com', '/wupeiqi/'),
        fetch_async('dig.chouti.com', '/pic/show?nid=4073644713430508&lid=10273091')
    ]
    
    loop = asyncio.get_event_loop()
    results = loop.run_until_complete(asyncio.gather(*tasks))
    loop.close()
    1.asyncio示例2
    import aiohttp
    import asyncio
    
    @asyncio.coroutine
    def fetch_async(url):
        print(url)
        response = yield from aiohttp.request('GET', url)
        # data = yield from response.read()
        # print(url, data)
        print(url, response)
        response.close()
    
    tasks = [fetch_async('http://www.google.com/'), fetch_async('http://www.chouti.com/')]
    
    event_loop = asyncio.get_event_loop()
    results = event_loop.run_until_complete(asyncio.gather(*tasks))
    event_loop.close()
    2.asyncio + aiohttp
    import asyncio
    import requests
    
    
    @asyncio.coroutine
    def fetch_async(func, *args):
        loop = asyncio.get_event_loop()
        future = loop.run_in_executor(None, func, *args)
        response = yield from future
        print(response.url, response.content)
    
    
    tasks = [
        fetch_async(requests.get, 'http://www.cnblogs.com/wupeiqi/'),
        fetch_async(requests.get, 'http://dig.chouti.com/pic/show?nid=4073644713430508&lid=10273091')
    ]
    
    loop = asyncio.get_event_loop()
    results = loop.run_until_complete(asyncio.gather(*tasks))
    loop.close()
    3.asyncio + requests
    import gevent
    
    import requests
    from gevent import monkey
    
    monkey.patch_all()
    
    
    def fetch_async(method, url, req_kwargs):
        print(method, url, req_kwargs)
        response = requests.request(method=method, url=url, **req_kwargs)
        print(response.url, response.content)
    
    # ##### 发送请求 #####
    gevent.joinall([
        gevent.spawn(fetch_async, method='get', url='https://www.python.org/', req_kwargs={}),
        gevent.spawn(fetch_async, method='get', url='https://www.yahoo.com/', req_kwargs={}),
        gevent.spawn(fetch_async, method='get', url='https://github.com/', req_kwargs={}),
    ])
    
    # ##### 发送请求(协程池控制最大协程数量) #####
    # from gevent.pool import Pool
    # pool = Pool(None)
    # gevent.joinall([
    #     pool.spawn(fetch_async, method='get', url='https://www.python.org/', req_kwargs={}),
    #     pool.spawn(fetch_async, method='get', url='https://www.yahoo.com/', req_kwargs={}),
    #     pool.spawn(fetch_async, method='get', url='https://www.github.com/', req_kwargs={}),
    # ])
    4.gevent + requests
    import grequests
    
    
    request_list = [
        grequests.get('http://httpbin.org/delay/1', timeout=0.001),
        grequests.get('http://fakedomain/'),
        grequests.get('http://httpbin.org/status/500')
    ]
    
    
    # ##### 执行并获取响应列表 #####
    # response_list = grequests.map(request_list)
    # print(response_list)
    
    
    # ##### 执行并获取响应列表(处理异常) #####
    # def exception_handler(request, exception):
    # print(request,exception)
    #     print("Request failed")
    
    # response_list = grequests.map(request_list, exception_handler=exception_handler)
    # print(response_list)
    5.grequests
    from twisted.web.client import getPage, defer
    from twisted.internet import reactor
    
    
    def all_done(arg):
        reactor.stop()
    
    
    def callback(contents):
        print(contents)
    
    
    deferred_list = []
    
    url_list = ['http://www.bing.com', 'http://www.baidu.com', ]
    for url in url_list:
        deferred = getPage(bytes(url, encoding='utf8'))
        deferred.addCallback(callback)
        deferred_list.append(deferred)
    
    dlist = defer.DeferredList(deferred_list)
    dlist.addBoth(all_done)
    
    reactor.run()
    6.Twisted示例
    from tornado.httpclient import AsyncHTTPClient
    from tornado.httpclient import HTTPRequest
    from tornado import ioloop
    
    
    def handle_response(response):
        """
        处理返回值内容(需要维护计数器,来停止IO循环),调用 ioloop.IOLoop.current().stop()
        :param response: 
        :return: 
        """
        if response.error:
            print("Error:", response.error)
        else:
            print(response.body)
    
    
    def func():
        url_list = [
            'http://www.baidu.com',
            'http://www.bing.com',
        ]
        for url in url_list:
            print(url)
            http_client = AsyncHTTPClient()
            http_client.fetch(HTTPRequest(url), handle_response)
    
    
    ioloop.IOLoop.current().add_callback(func)
    ioloop.IOLoop.current().start()
    7.Tornado
    from twisted.internet import reactor
    from twisted.web.client import getPage
    import urllib.parse
    
    
    def one_done(arg):
        print(arg)
        reactor.stop()
    
    post_data = urllib.parse.urlencode({'check_data': 'adf'})
    post_data = bytes(post_data, encoding='utf8')
    headers = {b'Content-Type': b'application/x-www-form-urlencoded'}
    response = getPage(bytes('http://dig.chouti.com/login', encoding='utf8'),
                       method=bytes('POST', encoding='utf8'),
                       postdata=post_data,
                       cookies={},
                       headers=headers)
    response.addBoth(one_done)
    
    reactor.run()
    Twisted更多

    以上均是Python内置以及第三方模块提供异步IO请求模块,使用简便大大提高效率,而对于异步IO请求的本质则是【非阻塞Socket】+【IO多路复用】:

    import select
    import socket
    import time
    
    
    class AsyncTimeoutException(TimeoutError):
        """
        请求超时异常类
        """
    
        def __init__(self, msg):
            self.msg = msg
            super(AsyncTimeoutException, self).__init__(msg)
    
    
    class HttpContext(object):
        """封装请求和相应的基本数据"""
    
        def __init__(self, sock, host, port, method, url, data, callback, timeout=5):
            """
            sock: 请求的客户端socket对象
            host: 请求的主机名
            port: 请求的端口
            port: 请求的端口
            method: 请求方式
            url: 请求的URL
            data: 请求时请求体中的数据
            callback: 请求完成后的回调函数
            timeout: 请求的超时时间
            """
            self.sock = sock
            self.callback = callback
            self.host = host
            self.port = port
            self.method = method
            self.url = url
            self.data = data
    
            self.timeout = timeout
    
            self.__start_time = time.time()
            self.__buffer = []
    
        def is_timeout(self):
            """当前请求是否已经超时"""
            current_time = time.time()
            if (self.__start_time + self.timeout) < current_time:
                return True
    
        def fileno(self):
            """请求sockect对象的文件描述符,用于select监听"""
            return self.sock.fileno()
    
        def write(self, data):
            """在buffer中写入响应内容"""
            self.__buffer.append(data)
    
        def finish(self, exc=None):
            """在buffer中写入响应内容完成,执行请求的回调函数"""
            if not exc:
                response = b''.join(self.__buffer)
                self.callback(self, response, exc)
            else:
                self.callback(self, None, exc)
    
        def send_request_data(self):
            content = """%s %s HTTP/1.0
    Host: %s
    
    %s""" % (
                self.method.upper(), self.url, self.host, self.data,)
    
            return content.encode(encoding='utf8')
    
    
    class AsyncRequest(object):
        def __init__(self):
            self.fds = []
            self.connections = []
    
        def add_request(self, host, port, method, url, data, callback, timeout):
            """创建一个要请求"""
            client = socket.socket()
            client.setblocking(False)
            try:
                client.connect((host, port))
            except BlockingIOError as e:
                pass
                # print('已经向远程发送连接的请求')
            req = HttpContext(client, host, port, method, url, data, callback, timeout)
            self.connections.append(req)
            self.fds.append(req)
    
        def check_conn_timeout(self):
            """检查所有的请求,是否有已经连接超时,如果有则终止"""
            timeout_list = []
            for context in self.connections:
                if context.is_timeout():
                    timeout_list.append(context)
            for context in timeout_list:
                context.finish(AsyncTimeoutException('请求超时'))
                self.fds.remove(context)
                self.connections.remove(context)
    
        def running(self):
            """事件循环,用于检测请求的socket是否已经就绪,从而执行相关操作"""
            while True:
                r, w, e = select.select(self.fds, self.connections, self.fds, 0.05)
    
                if not self.fds:
                    return
    
                for context in r:
                    sock = context.sock
                    while True:
                        try:
                            data = sock.recv(8096)
                            if not data:
                                self.fds.remove(context)
                                context.finish()
                                break
                            else:
                                context.write(data)
                        except BlockingIOError as e:
                            break
                        except TimeoutError as e:
                            self.fds.remove(context)
                            self.connections.remove(context)
                            context.finish(e)
                            break
    
                for context in w:
                    # 已经连接成功远程服务器,开始向远程发送请求数据
                    if context in self.fds:
                        data = context.send_request_data()
                        context.sock.sendall(data)
                        self.connections.remove(context)
    
                self.check_conn_timeout()
    
    
    if __name__ == '__main__':
        def callback_func(context, response, ex):
            """
            :param context: HttpContext对象,内部封装了请求相关信息
            :param response: 请求响应内容
            :param ex: 是否出现异常(如果有异常则值为异常对象;否则值为None)
            :return:
            """
            print(context, response, ex)
    
        obj = AsyncRequest()
        url_list = [
            {'host': 'www.google.com', 'port': 80, 'method': 'GET', 'url': '/', 'data': '', 'timeout': 5,
             'callback': callback_func},
            {'host': 'www.baidu.com', 'port': 80, 'method': 'GET', 'url': '/', 'data': '', 'timeout': 5,
             'callback': callback_func},
            {'host': 'www.bing.com', 'port': 80, 'method': 'GET', 'url': '/', 'data': '', 'timeout': 5,
             'callback': callback_func},
        ]
        for item in url_list:
            print(item)
            obj.add_request(**item)
    
        obj.running()
    史上最牛逼的异步IO模块

    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
          a. pip3 install wheel
          b. 下载twisted http://www.lfd.uci.edu/~gohlke/pythonlibs/#twisted
          c. 进入下载目录,执行 pip3 install Twisted‑17.1.0‑cp35‑cp35m‑win_amd64.whl
          d. pip3 install scrapy
          e. 下载并安装pywin32:https://sourceforge.net/projects/pywin32/files/
    

    二、基本使用

    1. 基本命令

    1. scrapy startproject 项目名称
       - 在当前目录中创建中创建一个项目文件(类似于Django)
     
    2. scrapy genspider [-t template] <name> <domain>
       - 创建爬虫应用
       如:
          scrapy gensipider -t basic oldboy oldboy.com
          scrapy gensipider -t xmlfeed autohome autohome.com.cn
       PS:
          查看所有命令:scrapy gensipider -l
          查看模板命令:scrapy gensipider -d 模板名称
     
    3. scrapy list
       - 展示爬虫应用列表
     
    4. scrapy crawl 爬虫应用名称
       - 运行单独爬虫应用
    

    2.项目结构以及爬虫应用简介

    project_name/
       scrapy.cfg
       project_name/
           __init__.py
           items.py
           pipelines.py
           settings.py
           spiders/
               __init__.py
               爬虫1.py
               爬虫2.py
               爬虫3.py
    

    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

    import scrapy
     
    class XiaoHuarSpider(scrapy.spiders.Spider):
        name = "xiaohuar"                            # 爬虫名称 *****
        allowed_domains = ["xiaohuar.com"]  # 允许的域名
        start_urls = [
            "http://www.xiaohuar.com/hua/",   # 其实URL
        ]
     
        def parse(self, response):
            # 访问起始URL并获取结果后的回调函数
    爬虫1.py
    import sys,os
    sys.stdout=io.TextIOWrapper(sys.stdout.buffer,encoding='gb18030')
    关于windows编码 io

    3. 小试牛刀

    import scrapy
    from scrapy.selector import HtmlXPathSelector
    from scrapy.http.request import Request
     
     
    class DigSpider(scrapy.Spider):
        # 爬虫应用的名称,通过此名称启动爬虫命令
        name = "dig"
     
        # 允许的域名
        allowed_domains = ["chouti.com"]
     
        # 起始URL
        start_urls = [
            'http://dig.chouti.com/',
        ]
     
        has_request_set = {}
     
        def parse(self, response):
            print(response.url)
     
            hxs = HtmlXPathSelector(response)
            page_list = hxs.select('//div[@id="dig_lcpage"]//a[re:test(@href, "/all/hot/recent/d+")]/@href').extract()
            for page in page_list:
                page_url = 'http://dig.chouti.com%s' % page
                key = self.md5(page_url)
                if key in self.has_request_set:
                    pass
                else:
                    self.has_request_set[key] = page_url
                    obj = Request(url=page_url, method='GET', callback=self.parse)
                    yield obj
     
        @staticmethod
        def md5(val):
            import hashlib
            ha = hashlib.md5()
            ha.update(bytes(val, encoding='utf-8'))
            key = ha.hexdigest()
            return key
    

    执行此爬虫文件,则在终端进入项目目录执行如下命令:

    scrapy crawl dig --nolog
    

    对于上述代码重要之处在于:

    • Request是一个封装用户请求的类,在回调函数中yield该对象表示继续访问
    • HtmlXpathSelector用于结构化HTML代码并提供选择器功能

    4. 选择器

    #!/usr/bin/env python
    # -*- coding:utf-8 -*-
    from scrapy.selector import Selector, HtmlXPathSelector
    from scrapy.http import HtmlResponse
    html = """<!DOCTYPE html>
    <html>
        <head lang="en">
            <meta charset="UTF-8">
            <title></title>
        </head>
        <body>
            <ul>
                <li class="item-"><a id='i1' href="link.html">first item</a></li>
                <li class="item-0"><a id='i2' href="llink.html">first item</a></li>
                <li class="item-1"><a href="llink2.html">second item<span>vv</span></a></li>
            </ul>
            <div><a href="llink2.html">second item</a></div>
        </body>
    </html>
    """
    response = HtmlResponse(url='http://example.com', body=html,encoding='utf-8')
    # hxs = HtmlXPathSelector(response)
    # print(hxs)
    # hxs = Selector(response=response).xpath('//a') #找到所有的a标签
    # print(hxs)
    # hxs = Selector(response=response).xpath('//a[2]') #找到所有a标签中的第二个
    # print(hxs)
    # hxs = Selector(response=response).xpath('//a[@id]') #找到所有a标签中有id属性的a标签
    # print(hxs)
    # hxs = Selector(response=response).xpath('//a[@id="i1"]') #找到所有a标签中id属性为i1的a标签
    # print(hxs)
    # hxs = Selector(response=response).xpath('//a[@href="link.html"][@id="i1"]')
    # print(hxs) #找到所有a标签中href=...并且id=i1的a标签
    # hxs = Selector(response=response).xpath('//a[contains(@href, "link")]')
    # print(hxs) #找到a标签的href属性里面必须得有link的a标签
    # hxs = Selector(response=response).xpath('//a[starts-with(@href, "link")]')
    # print(hxs) #同上只不过是要求以link开头
    # hxs = Selector(response=response).xpath('//a[re:test(@id, "id+")]')
    # print(hxs)
    # hxs = Selector(response=response).xpath('//a[re:test(@id, "id+")]/text()').extract()
    # print(hxs)
    # hxs = Selector(response=response).xpath('//a[re:test(@id, "id+")]/@href').extract()
    # print(hxs)
    # hxs = Selector(response=response).xpath('/html/body/ul/li/a/@href').extract()
    # print(hxs)
    # hxs = Selector(response=response).xpath('//body/ul/li/a/@href').extract_first()
    # print(hxs)
     
    # ul_list = Selector(response=response).xpath('//body/ul/li')
    # for item in ul_list:
    #     v = item.xpath('./a/span')
    #     # 或
    #     # v = item.xpath('a/span') #在儿子中找a标签下的span标签
    #     # 或
    #     # v = item.xpath('*/a/span') #当前目录下的a标签下的span标签
    #     # 或
    #     # v = item.xpath('.//a/span') #从当前个目录下开始找子子孙孙中的a标签下的子标签
    #     print(v)
    # -*- coding: utf-8 -*-
    import scrapy
    from scrapy.selector import HtmlXPathSelector
    from scrapy.http.request import Request
    from scrapy.http.cookies import CookieJar
    from scrapy import FormRequest
    
    
    class ChouTiSpider(scrapy.Spider):
        # 爬虫应用的名称,通过此名称启动爬虫命令
        name = "chouti"
        # 允许的域名
        allowed_domains = ["chouti.com"]
    
        cookie_dict = {}
        has_request_set = {}
    
        def start_requests(self):
            url = 'http://dig.chouti.com/'
            # return [Request(url=url, callback=self.login)]
            yield Request(url=url, callback=self.login)
    
        def login(self, response):
            cookie_jar = CookieJar()
            cookie_jar.extract_cookies(response, response.request)
            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
    
            req = 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
            )
            yield req
    
        def check_login(self, response):
            req = Request(
                url='http://dig.chouti.com/',
                method='GET',
                callback=self.show,
                cookies=self.cookie_dict,
                dont_filter=True
            )
            yield req
    
        def show(self, response):
            # print(response)
            hxs = HtmlXPathSelector(response)
            news_list = hxs.select('//div[@id="content-list"]/div[@class="item"]')
            for new in news_list:
                # temp = new.xpath('div/div[@class="part2"]/@share-linkid').extract()
                link_id = new.xpath('*/div[@class="part2"]/@share-linkid').extract_first()
                yield Request(
                    url='http://dig.chouti.com/link/vote?linksId=%s' %(link_id,),
                    method='POST',
                    cookies=self.cookie_dict,
                    callback=self.do_favor
                )
    
            page_list = hxs.select('//div[@id="dig_lcpage"]//a[re:test(@href, "/all/hot/recent/d+")]/@href').extract()
            for page in page_list:
    
                page_url = 'http://dig.chouti.com%s' % page
                import hashlib
                hash = hashlib.md5()
                hash.update(bytes(page_url,encoding='utf-8'))
                key = hash.hexdigest()
                if key in self.has_request_set:
                    pass
                else:
                    self.has_request_set[key] = page_url
                    yield Request(
                        url=page_url,
                        method='GET',
                        callback=self.show
                    )
    
        def do_favor(self, response):
            print(response.text)
    示例:自动登陆抽屉并点赞

     注意:settings.py中设置DEPTH_LIMIT = 1来指定“递归”的层数。

    5. 格式化处理

    上述实例只是简单的处理,所以在parse方法中直接处理。如果对于想要获取更多的数据处理,则可以利用Scrapy的items将数据格式化,然后统一交由pipelines来处理。

    import scrapy
    from scrapy.selector import HtmlXPathSelector
    from scrapy.http.request import Request
    from scrapy.http.cookies import CookieJar
    from scrapy import FormRequest
    
    
    class XiaoHuarSpider(scrapy.Spider):
        # 爬虫应用的名称,通过此名称启动爬虫命令
        name = "xiaohuar"
        # 允许的域名
        allowed_domains = ["xiaohuar.com"]
    
        start_urls = [
            "http://www.xiaohuar.com/list-1-1.html",
        ]
        # custom_settings = {
        #     'ITEM_PIPELINES':{
        #         'spider1.pipelines.JsonPipeline': 100
        #     }
        # }
        has_request_set = {}
    
        def parse(self, response):
            # 分析页面
            # 找到页面中符合规则的内容(校花图片),保存
            # 找到所有的a标签,再访问其他a标签,一层一层的搞下去
    
            hxs = HtmlXPathSelector(response)
    
            items = hxs.select('//div[@class="item_list infinite_scroll"]/div')
            for item in items:
                src = item.select('.//div[@class="img"]/a/img/@src').extract_first()
                name = item.select('.//div[@class="img"]/span/text()').extract_first()
                school = item.select('.//div[@class="img"]/div[@class="btns"]/a/text()').extract_first()
                url = "http://www.xiaohuar.com%s" % src
                from ..items import XiaoHuarItem
                obj = XiaoHuarItem(name=name, school=school, url=url)
                yield obj
    
            urls = hxs.select('//a[re:test(@href, "http://www.xiaohuar.com/list-1-d+.html")]/@href')
            for url in urls:
                key = self.md5(url)
                if key in self.has_request_set:
                    pass
                else:
                    self.has_request_set[key] = url
                    req = Request(url=url,method='GET',callback=self.parse)
                    yield req
    
        @staticmethod
        def md5(val):
            import hashlib
            ha = hashlib.md5()
            ha.update(bytes(val, encoding='utf-8'))
            key = ha.hexdigest()
            return key
    spiders/xiahuar.py
    import scrapy
    
    
    class XiaoHuarItem(scrapy.Item):
        name = scrapy.Field()
        school = scrapy.Field()
        url = scrapy.Field()
    items
    import json
    import os
    import requests
    
    
    class JsonPipeline(object):
        def __init__(self):
            self.file = open('xiaohua.txt', 'w')
    
        def process_item(self, item, spider):
            v = json.dumps(dict(item), ensure_ascii=False)
            self.file.write(v)
            self.file.write('
    ')
            self.file.flush()
            return item
    
    
    class FilePipeline(object):
        def __init__(self):
            if not os.path.exists('imgs'):
                os.makedirs('imgs')
    
        def process_item(self, item, spider):
            response = requests.get(item['url'], stream=True)
            file_name = '%s_%s.jpg' % (item['name'], item['school'])
            with open(os.path.join('imgs', file_name), mode='wb') as f:
                f.write(response.content)
            return item
    pipelines
    ITEM_PIPELINES = {
       'spider1.pipelines.JsonPipeline': 100,
       'spider1.pipelines.FilePipeline': 300,
    }
    # 每行后面的整型值,确定了他们运行的顺序,item按数字从低到高的顺序,通过pipeline,通常将这些数字定义在0-1000范围内。
    settings

     对于pipeline可以做更多,如下:

    from scrapy.exceptions import DropItem
    
    class CustomPipeline(object):
        def __init__(self,v):
            self.value = v
    
        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.getint('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')
    自定义pipeline

    6.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
    爬虫中间件
    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
    下载器中间件

    7. 自定制命令

    • 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)
    • from scrapy.commands import ScrapyCommand
          from scrapy.utils.project import get_project_settings
      
      
          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):
                  spider_list = self.crawler_process.spiders.list()
                  for name in spider_list:
                      self.crawler_process.crawl(name, **opts.__dict__)
                  self.crawler_process.start()
      crawlall.py
    • 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 

    8. 自定义扩展

    自定义扩展时,利用信号在指定位置注册制定操作

    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)
    
            crawler.signals.connect(ext.spider_opened, signal=signals.spider_opened)
            crawler.signals.connect(ext.spider_closed, signal=signals.spider_closed)
    
            return ext
    
        def spider_opened(self, spider):
            print('open')
    
        def spider_closed(self, spider):
            print('close')
    View Code

    9. 避免重复访问

    scrapy默认使用 scrapy.dupefilter.RFPDupeFilter 进行去重,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
    
    class RepeatUrl:
        def __init__(self):
            self.visited_url = set()
    
        @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)
    自定义URL去重操作

    10.其他

    # -*- 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)'
    
    # Obey robots.txt rules
    # 4. 禁止爬虫配置
    # ROBOTSTXT_OBEY = False
    
    # 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:
    # 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...
    #    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
    # 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'
    # 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/wupeiqi/client.key.unsecure', mode='r').read())
                    v2 = crypto.load_certificate(crypto.FILETYPE_PEM, open('/Users/wupeiqi/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

    11.TinyScrapy

    #!/usr/bin/env python
    # -*- coding:utf-8 -*-
    import types
    from twisted.internet import defer
    from twisted.web.client import getPage
    from twisted.internet import reactor
    
    
    
    class Request(object):
        def __init__(self, url, callback):
            self.url = url
            self.callback = callback
            self.priority = 0
    
    
    class HttpResponse(object):
        def __init__(self, content, request):
            self.content = content
            self.request = request
    
    
    class ChouTiSpider(object):
    
        def start_requests(self):
            url_list = ['http://www.cnblogs.com/', 'http://www.bing.com']
            for url in url_list:
                yield Request(url=url, callback=self.parse)
    
        def parse(self, response):
            print(response.request.url)
            # yield Request(url="http://www.baidu.com", callback=self.parse)
    
    
    
    
    from queue import Queue
    Q = Queue()
    
    
    class CallLaterOnce(object):
        def __init__(self, func, *a, **kw):
            self._func = func
            self._a = a
            self._kw = kw
            self._call = None
    
        def schedule(self, delay=0):
            if self._call is None:
                self._call = reactor.callLater(delay, self)
    
        def cancel(self):
            if self._call:
                self._call.cancel()
    
        def __call__(self):
            self._call = None
            return self._func(*self._a, **self._kw)
    
    
    class Engine(object):
        def __init__(self):
            self.nextcall = None
            self.crawlling = []
            self.max = 5
            self._closewait = None
    
        def get_response(self,content, request):
            response = HttpResponse(content, request)
            gen = request.callback(response)
            if isinstance(gen, types.GeneratorType):
                for req in gen:
                    req.priority = request.priority + 1
                    Q.put(req)
    
    
        def rm_crawlling(self,response,d):
            self.crawlling.remove(d)
    
        def _next_request(self,spider):
            if Q.qsize() == 0 and len(self.crawlling) == 0:
                self._closewait.callback(None)
    
            if len(self.crawlling) >= 5:
                return
            while len(self.crawlling) < 5:
                try:
                    req = Q.get(block=False)
                except Exception as e:
                    req = None
                if not req:
                    return
                d = getPage(req.url.encode('utf-8'))
                self.crawlling.append(d)
                d.addCallback(self.get_response, req)
                d.addCallback(self.rm_crawlling,d)
                d.addCallback(lambda _: self.nextcall.schedule())
    
    
        @defer.inlineCallbacks
        def crawl(self):
            spider = ChouTiSpider()
            start_requests = iter(spider.start_requests())
            flag = True
            while flag:
                try:
                    req = next(start_requests)
                    Q.put(req)
                except StopIteration as e:
                    flag = False
    
            self.nextcall = CallLaterOnce(self._next_request,spider)
            self.nextcall.schedule()
    
            self._closewait = defer.Deferred()
            yield self._closewait
    
        @defer.inlineCallbacks
        def pp(self):
            yield self.crawl()
    
    _active = set()
    obj = Engine()
    d = obj.crawl()
    _active.add(d)
    
    li = defer.DeferredList(_active)
    li.addBoth(lambda _,*a,**kw: reactor.stop())
    
    reactor.run()
    参考版

    点击下载

    更多文档参见:http://scrapy-chs.readthedocs.io/zh_CN/latest/index.html

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  • 原文地址:https://www.cnblogs.com/wuyongqiang/p/7458184.html
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