【转】Python爬虫(6)

官网链接：https://docs.scrapy.org/en/latest/topics/architecture.html

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\r\nHost: %s\r\n\r\n""" % (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\r\nHost: %s\r\n\r\n%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

一介绍

Scrapy一个开源和协作的框架，其最初是为了页面抓取 (更确切来说, 网络抓取 )所设计的，使用它可以以快速、简单、可扩展的方式从网站中提取所需的数据。但目前Scrapy的用途十分广泛，可用于如数据挖掘、监测和自动化测试等领域，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 是基于twisted框架开发而来，twisted是一个流行的事件驱动的python网络框架。因此Scrapy使用了一种非阻塞（又名异步）的代码来实现并发。整体架构大致如下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。

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：

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

一、安装

#Windows平台

    、pip3 install wheel #安装后，便支持通过wheel文件安装软件，wheel文件官网：https://www.lfd.uci.edu/~gohlke/pythonlibs

    、pip3 install lxml

    、pip3 install pyopenssl

    、下载并安装pywin32：https://sourceforge.net/projects/pywin32/files/pywin32/

    、下载twisted的wheel文件：http://www.lfd.uci.edu/~gohlke/pythonlibs/#twisted

    、执行pip3 install 下载目录\Twisted-17.9.-cp36-cp36m-win_amd64.whl

    、pip3 install scrapy

#Linux平台

    、pip3 install scrapy

二、基本使用

1. 基本命令

# 查看帮助

    scrapy -h

    scrapy <command> -h

# 有两种命令：其中Project-only必须切到项目文件夹下才能执行，而Global的命令则不需要

    Global commands:

        startproject #创建项目

        genspider    #创建爬虫程序

                            如：

                              scrapy gensipider -t basic oldboy oldboy.com

                              scrapy gensipider -t xmlfeed autohome autohome.com.cn

        settings     #如果是在项目目录下，则得到的是该项目的配置

        runspider    #运行一个独立的python文件，不必创建项目

        shell        #scrapy shell url地址  在交互式调试，如选择器规则正确与否

        fetch        #独立于程单纯地爬取一个页面，可以拿到请求头

        view         #下载完毕后直接弹出浏览器，以此可以分辨出哪些数据是ajax请求

        version      #scrapy version 查看scrapy的版本，scrapy version -v查看scrapy依赖库的版本

    Project-only commands:

        crawl        #运行爬虫，必须创建项目才行，确保配置文件中ROBOTSTXT_OBEY = False

        check        #检测项目中有无语法错误

        list         #列出项目中所包含的爬虫名

        edit         #编辑器，一般不用

        parse        #scrapy parse url地址 --callback 回调函数  #以此可以验证我们的回调函数是否正确

        bench        #scrapy bentch压力测试

# 官网链接

    https://docs.scrapy.org/en/latest/topics/commands.html

#、执行全局命令：请确保不在某个项目的目录下，排除受该项目配置的影响

scrapy startproject MyProject

cd MyProject

scrapy genspider baidu www.baidu.com

scrapy settings --get XXX #如果切换到项目目录下，看到的则是该项目的配置

scrapy runspider baidu.py

scrapy shell https://www.baidu.com

    response

    response.status

    response.body

    view(response)

scrapy view https://www.taobao.com #如果页面显示内容不全，不全的内容则是ajax请求实现的，以此快速定位问题

scrapy fetch --nolog --headers https://www.taobao.com

scrapy version #scrapy的版本

scrapy version -v #依赖库的版本

#、执行项目命令：切到项目目录下

scrapy crawl baidu

scrapy check

scrapy list

scrapy parse http://quotes.toscrape.com/ --callback parse

scrapy bench

示范用法

示范用法

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

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

# //与/

# text

#、extract与extract_first:从selector对象中解出内容

#、属性：xpath的属性加前缀@

#、嵌套查找

#、设置默认值

#、按照属性查找

#、按照属性模糊查找

#、正则表达式

#、xpath相对路径

#、带变量的xpath

response.selector.css()

response.selector.xpath()

可简写为

response.css()

response.xpath()

# //与/

response.xpath('//body/a/')#

response.css('div a::text')

>>> response.xpath('//body/a') #开头的//代表从整篇文档中寻找,body之后的/代表body的儿子

[]

>>> response.xpath('//body//a') #开头的//代表从整篇文档中寻找,body之后的//代表body的子子孙孙

[<Selector xpath='//body//a' data='<a href="image1.html">Name: My image 1 <'>, <Selector xpath='//body//a' data='<a href="image2.html">Name: My image 2 <'>, <Selector xpath='//body//a' data='<a href="

image3.html">Name: My image 3 <'>, <Selector xpath='//body//a' data='<a href="image4.html">Name: My image 4 <'>, <Selector xpath='//body//a' data='<a href="image5.html">Name: My image 5 <'>]

# text

>>> response.xpath('//body//a/text()')

>>> response.css('body a::text')

#、extract与extract_first:从selector对象中解出内容

>>> response.xpath('//div/a/text()').extract()

['Name: My image 1 ', 'Name: My image 2 ', 'Name: My image 3 ', 'Name: My image 4 ', 'Name: My image 5 ']

>>> response.css('div a::text').extract()

['Name: My image 1 ', 'Name: My image 2 ', 'Name: My image 3 ', 'Name: My image 4 ', 'Name: My image 5 ']

>>> response.xpath('//div/a/text()').extract_first()

'Name: My image 1 '

>>> response.css('div a::text').extract_first()

'Name: My image 1 '

#、属性：xpath的属性加前缀@

>>> response.xpath('//div/a/@href').extract_first()

'image1.html'

>>> response.css('div a::attr(href)').extract_first()

'image1.html'

#、嵌套查找

>>> response.xpath('//div').css('a').xpath('@href').extract_first()

'image1.html'

#、设置默认值

>>> response.xpath('//div[@id="xxx"]').extract_first(default="not found")

'not found'

#、按照属性查找

response.xpath('//div[@id="images"]/a[@href="image3.html"]/text()').extract()

response.css('#images a[@href="image3.html"]/text()').extract()

#、按照属性模糊查找

response.xpath('//a[contains(@href,"image")]/@href').extract()

response.css('a[href*="image"]::attr(href)').extract()

response.xpath('//a[contains(@href,"image")]/img/@src').extract()

response.css('a[href*="imag"] img::attr(src)').extract()

response.xpath('//*[@href="image1.html"]')

response.css('*[href="image1.html"]')

#、正则表达式

response.xpath('//a/text()').re(r'Name: (.*)')

response.xpath('//a/text()').re_first(r'Name: (.*)')

#、xpath相对路径

>>> res=response.xpath('//a[contains(@href,"3")]')[]

>>> res.xpath('img')

[<Selector xpath='img' data='<img src="data:image3_thumb.jpg">'>]

>>> res.xpath('./img')

[<Selector xpath='./img' data='<img src="data:image3_thumb.jpg">'>]

>>> res.xpath('.//img')

[<Selector xpath='.//img' data='<img src="data:image3_thumb.jpg">'>]

>>> res.xpath('//img') #这就是从头开始扫描

[<Selector xpath='//img' data='<img src="data:image1_thumb.jpg">'>, <Selector xpath='//img' data='<img src="data:image2_thumb.jpg">'>, <Selector xpath='//img' data='<img src="data:image3_thumb.jpg">'>, <Selector xpa

th='//img' data='<img src="data:image4_thumb.jpg">'>, <Selector xpath='//img' data='<img src="data:image5_thumb.jpg">'>]

#、带变量的xpath

>>> response.xpath('//div[@id=$xxx]/a/text()',xxx='images').extract_first()

'Name: My image 1 '

>>> response.xpath('//div[count(a)=$yyy]/@id',yyy=).extract_first() #求有5个a标签的div的id

'images'

选择器示例用法

# -*- 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 Spiders

#在项目目录下新建：entrypoint.py

from scrapy.cmdline import execute

execute(['scrapy', 'crawl', 'xiaohua'])

默认只能在cmd中执行爬虫，如果想在pycharm中执行需要做

强调：配置文件的选项必须是大写，如X='1'

# -*- coding: utf-8 -*-

import scrapy

from scrapy.linkextractors import LinkExtractor

from scrapy.spiders import CrawlSpider, Rule

class BaiduSpider(CrawlSpider):

    name = 'xiaohua'

    allowed_domains = ['www.xiaohuar.com']

    start_urls = ['http://www.xiaohuar.com/v/']

    # download_delay = 1

    rules = (

        Rule(LinkExtractor(allow=r'p\-\d\-\d+\.html$'), callback='parse_item',follow=True,),

    )

    def parse_item(self, response):

        if url:

            print('======下载视频==============================', url)

            yield scrapy.Request(url,callback=self.save)

    def save(self,response):

        print('======保存视频==============================',response.url,len(response.body))

        import time

        import hashlib

        m=hashlib.md5()

        m.update(str(time.time()).encode('utf-8'))

        m.update(response.url.encode('utf-8'))

        filename=r'E:\\mv\\%s.mp4' %m.hexdigest()

        with open(filename,'wb') as f:

            f.write(response.body)

模版：CrawlSpider

https://docs.scrapy.org/en/latest/topics/spiders.html

三. 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('\n')

        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('')

    def close_spider(self,spider):

        """

        爬虫关闭时，被调用

        :param spider:

        :return:

        """

        print('')

自定义pipeline

四.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

五. 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

六. 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')

七. 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

八.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

九.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

十、爬取亚马逊商品信息

1、

scrapy startproject Amazon

cd Amazon

scrapy genspider spider_goods www.amazon.cn

2、settings.py

ROBOTSTXT_OBEY = False

#请求头

DEFAULT_REQUEST_HEADERS = {

    'Referer':'https://www.amazon.cn/',

    'User-Agent':'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/62.0.3202.75 Safari/537.36'

}

#打开注释

HTTPCACHE_ENABLED = True

HTTPCACHE_EXPIRATION_SECS = 0

HTTPCACHE_DIR = 'httpcache'

HTTPCACHE_IGNORE_HTTP_CODES = []

HTTPCACHE_STORAGE = 'scrapy.extensions.httpcache.FilesystemCacheStorage'

3、items.py

class GoodsItem(scrapy.Item):

    # define the fields for your item here like:

    # name = scrapy.Field()

    #商品名字

    goods_name = scrapy.Field()

    #价钱

    goods_price = scrapy.Field()

    #配送方式

    delivery_method=scrapy.Field()

4、spider_goods.py

# -*- coding: utf-8 -*-

import scrapy

from Amazon.items import  GoodsItem

from scrapy.http import Request

from urllib.parse import urlencode

class SpiderGoodsSpider(scrapy.Spider):

    name = 'spider_goods'

    allowed_domains = ['www.amazon.cn']

    # start_urls = ['http://www.amazon.cn/']

    def __int__(self,keyword=None,*args,**kwargs):

        super(SpiderGoodsSpider).__init__(*args,**kwargs)

        self.keyword=keyword

    def start_requests(self):

        url='https://www.amazon.cn/s/ref=nb_sb_noss_1?'

        paramas={

            '__mk_zh_CN': '亚马逊网站',

            'url': 'search - alias = aps',

            'field-keywords': self.keyword

        }

        url=url+urlencode(paramas,encoding='utf-8')

        yield Request(url,callback=self.parse_index)

    def parse_index(self, response):

        print('解析索引页:%s' %response.url)

        urls=response.xpath('//*[contains(@id,"result_")]/div/div[3]/div[1]/a/@href').extract()

        for url in urls:

            yield Request(url,callback=self.parse_detail)

        next_url=response.urljoin(response.xpath('//*[@id="pagnNextLink"]/@href').extract_first())

        print('下一页的url',next_url)

        yield Request(next_url,callback=self.parse_index)

    def parse_detail(self,response):

        print('解析详情页:%s' %(response.url))

        item=GoodsItem()

        # 商品名字

        item['goods_name'] = response.xpath('//*[@id="productTitle"]/text()').extract_first().strip()

        # 价钱

        item['goods_price'] = response.xpath('//*[@id="priceblock_ourprice"]/text()').extract_first().strip()

        # 配送方式

        item['delivery_method'] = ''.join(response.xpath('//*[@id="ddmMerchantMessage"]//text()').extract())

        return item

5、自定义pipelines

#sql.py

import pymysql

import settings

MYSQL_HOST=settings.MYSQL_HOST

MYSQL_PORT=settings.MYSQL_PORT

MYSQL_USER=settings.MYSQL_USER

MYSQL_PWD=settings.MYSQL_PWD

MYSQL_DB=settings.MYSQL_DB

conn=pymysql.connect(

    host=MYSQL_HOST,

    port=int(MYSQL_PORT),

    user=MYSQL_USER,

    password=MYSQL_PWD,

    db=MYSQL_DB,

    charset='utf8'

)

cursor=conn.cursor()

class Mysql(object):

    @staticmethod

    def insert_tables_goods(goods_name,goods_price,deliver_mode):

        sql='insert into goods(goods_name,goods_price,delivery_method) values(%s,%s,%s)'

        cursor.execute(sql,args=(goods_name,goods_price,deliver_mode))

        conn.commit()

    @staticmethod

    def is_repeat(goods_name):

        sql='select count(1) from goods where goods_name=%s'

        cursor.execute(sql,args=(goods_name,))

        if cursor.fetchone()[0] >= 1:

            return True

if __name__ == '__main__':

    cursor.execute('select * from goods;')

    print(cursor.fetchall())

#pipelines.py

from Amazon.mysqlpipelines.sql import Mysql

class AmazonPipeline(object):

    def process_item(self, item, spider):

        goods_name=item['goods_name']

        goods_price=item['goods_price']

        delivery_mode=item['delivery_method']

        if not Mysql.is_repeat(goods_name):

            Mysql.insert_table_goods(goods_name,goods_price,delivery_mode)

6、创建数据库表

create database amazon charset utf8;

create table goods(

    id int primary key auto_increment,

    goods_name char(30),

    goods_price char(20),

    delivery_method varchar(50)

);

7、settings.py

MYSQL_HOST='localhost'

MYSQL_PORT=''

MYSQL_USER='root'

MYSQL_PWD=''

MYSQL_DB='amazon'

#数字代表优先级程度（1-1000随意设置，数值越低，组件的优先级越高）

ITEM_PIPELINES = {

   'Amazon.mysqlpipelines.pipelines.mazonPipeline': 1,

}

#8、在项目目录下新建：entrypoint.py

from scrapy.cmdline import execute

execute(['scrapy', 'crawl', 'spider_goods','-a','keyword=iphone8'])

https://pan.baidu.com/s/1boCEBT1