Scrapy进阶

当我们使用scrapy框架爬取网站的时候，我们会有一个入口的url，一个名为start_urls,我们爬取的第一个网页是从这一开始的。

需求：

　　现在我们有一个这样的需求，比如说我们对起始的URL有一个相对应的处理函数，对后面的爬取的url又要进行一个新的处理那么我们需要两个处理函数。

　　如果我们想对起始的url的处理函数不为默认的parser那我们应该怎么修改呢

在父类的中我们可以看到一个名为start_requests的函数他就控制了起始url使用什么调用什么回调函数所以我们只要重写他就可以了，在scrapy中yield一个Request对象（已经可以设置callback了）

那么scrapy框架会自动将其放入调度器，然后爬取

class ZhipinSpider(scrapy.Spider):

    name = 'zhipin'

    allowed_domains = ['zhipin.com']

    start_urls = ['xxx.com']

    # 方案一

    def start_requests(self):

            for url in self.start_urls:

                yield Request(url=url,callback=self.parse2)

    # 方案二

    def start_requests(self):

    req_list = []

    for url in self.start_urls:

        req_list.append(Request(url=url,callback=self.parse2))

    return req_list

    def parser(self, response):

        pass

    def parser2(self, response):

        pass

这里使用yield和返回一个列表的效果是一样的，因为在scrapy内部会使用iter()方法最后返回的都是一个可迭代对象。

解析器

parser中的参数是一个response对象我们需要用解析器来对其进行解析

有两种方式一种是他内部实现了我们可以直接对其进行解析

response.xpath('//div[@id='content-list']/div[@class='item']')

还有一种是导入模块的方式进行解析：

from scrapy.selector import HtmlXPathSelector

。。。

def parser(self, response):

    hxs = HtmlXPathSelector(respone=response)

    items = hxs.xpath("//div[@id='content-list']/div[@class='item']")

查找规则：

hxs = Selector(response=response).xpath('//div') # 去子子孙孙下找div标签

hxs = Selector(response=response).xpath('/div')  # 去儿子下找div 标签

hxs = Selector(response=response).xpath('//div[2]') # 去子子孙孙下找第二个div标签

hxs = Selector(response=response).xpath('//a[@id]') # 找有id属性的a标签

hxs = Selector(response=response).xpath('//a[@id="i1"]') # 找id="i1"的所有a标签（id不重复，但是可能不是id的情况下）

hxs = Selector(response=response).xpath('//a[@href="link.html"][@id="i1"]') # 且的关系

hxs = Selector(response=response).xpath('//a[contains(@href, "link")]') # 有这两个属性的a标签

hxs = Selector(response=response).xpath('//a[re:test(@id, "i\d+")]') # 使用正则来匹配

解析得到的类型：

标签对象：  xpath('/html/body/ul/li/a/@href')

列表：     xpath('/html/body/ul/li/a/@href').extract()

值：       xpath('//body/ul/li/a/@href').extract_first()

如何独立使用scrapy的解析器：

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')

obj = response.xpath('//a[@id="i1"]/text()').extract_first()

print(obj)

单独应用

格式化处理items持久化处理pipleline

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。

当yield一个item对象时会直接去pipeline中执行持久化操作

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

spider.py

import scrapy

class XiaoHuarItem(scrapy.Item):

    name = scrapy.Field()

    school = scrapy.Field()

    url = scrapy.Field()

items.py

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

pipeline

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。

pipeline更多的方法

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('')

more_pipeline

去重：

要在settings文件中配置相应的类

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

自定义：

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)

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

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

下载中间件

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）

如果想运行所有的爬虫：

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

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

settings

巴特西

Scrapy进阶

需求：

解析器

格式化处理items持久化处理pipleline

去重：

中间件

自定制命令

其他

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