Scrapy

源码分析

核心组件

Scrapy有以下几大组件：

Scrapy Engine：核心引擎，负责控制和调度各个组件，保证数据流转；
Scheduler：负责管理任务、过滤任务、输出任务的调度器，存储、去重任务都在此控制；
Downloader：下载器，负责在网络上下载网页数据，输入待下载URL，输出下载结果；
Spiders：用户自己编写的爬虫脚本，可自定义抓取意图；
Item Pipeline：负责输出结构化数据，可自定义输出位置；

除此之外，还有两大中间件组件：

Downloader middlewares：介于引擎和下载器之间，可以在网页在下载前、后进行逻辑处理；
Spider middlewares：介于引擎和爬虫之间，可以在调用爬虫输入下载结果和输出请求/数据时进行逻辑处理；

执行流程：

1、引擎从自定义爬虫中获取初始化请求（url 种子）
2、引擎吧该请求放入调度器，同时引擎调度器获取一个带下载的请求（这辆步异步执行）
3、调度器返回给引擎一个待下载的请求
4、引擎发送请求给下载器，中间经历一系列下载器中间件
5、请求下载完成，生成相应对象，返回给引擎，中间经历一系列下载器中间件
6、引擎受到下载返回的响应对象，然后发送给爬虫，执行自定义逻辑，中间经过一系列爬虫中间件
7、爬虫执行对应的回掉方法，处理这个响应，完成用户逻辑后，生成结果对象或新的请求对象给引擎再次经过一系列爬虫中间件
8、引擎吧爬虫返回的结果对象交由结果处理器，把新的请求对象通过引擎在交给调度器
9、从1开始重复执行，直到调度器中没有新的请求

入口 __main__.py——〉execute（项目、运行环境的设置，解析命令，初始化CrawlerProcess，执行run函数）

 http://kaito-kidd.com/2016/11/01/scrapy-code-analyze-architecture/

第一步：
    scrapy startproject xxxx 
    cd xxxx 
    scrapy genspider chouti chouti.com 
    
    # 编写代码
    
    scrapy crawl chouti --nolog 
    
第二步：start_requests
    
第三步：parse函数
    - 解析器
    - yield item 
    - yield Request()
    
第四步：携带cookie
    - 手动
    - 自动
    
第五步：去重规则


第六步：下载中间件 

# -*- coding: utf-8 -*-
import scrapy
from bs4 import BeautifulSoup
from scrapy.selector import HtmlXPathSelector # HtmlXPathSelector scrapy 自带
from .. items import PachongItem
from scrapy.http import Request

class ChoutiSpider(scrapy.Spider):
    name = 'chouti'
    allowed_domains = ['chouti.com']
    start_urls = ['http://dig.chouti.com/']

    def parse(self, response):
        """
        当起始url下载完毕后，自动调用该函数，reponse封装了
        :param response:
        :return:
        """
        # print(response.text)
        # soup = BeautifulSoup(response.text,'lxml')# scrap 继承了lxml
        # div = soup.find(name='id',attrs={"id":'content-list'})
        # print(div)
        hxs = HtmlXPathSelector(response=response)
        # items= hxs.xpath("//div[@id='content-list']/div[@class='item']")[0:4]
        # with open('xxx.log', 'w') as f:  # 注意 打开文件不能写到for循环中
        #     for item in items:
        #         href = item.xpath(".//div[@class='part1']/a[1]/@href").extract_first() #extract_first() 提取第一个
        #         text = item.xpath(".//div[@class='part1']/a[1]/text()").extract_first() #extract_first()
        #         print(text.strip())
        #         f.write(href)

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

        for item in items:

            text = item.xpath(".//div[@class='part1']/a[1]/text()").extract_first()  # extract_first() 解析
            href = item.xpath(".//div[@class='part1']/a[1]/@href").extract_first()  # extract_first() 全部提取
            # print(href,text)
            item = PachongItem(title=text,href=href)
            yield item #自动返回给已注册pipelines中的函数，去做持久化．必须是个对象，pipelines每次都执行

        pages = hxs.xpath("//div[@id='page-area']//a[@class='ct_pagepa']/@href").extract()
        for page_url in pages:
            page_url = "https://dig.chouti.com" + page_url

            yield Request(url=page_url,callback=self.parse)

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

# Define your item pipelines here
#
# Don't forget to add your pipeline to the ITEM_PIPELINES setting
# See: https://doc.scrapy.org/en/latest/topics/item-pipeline.html


class PachongPipeline(object):
    def process_item(self, item, spider):
        # print(item['href'])
        self.f.write(item['href']+"
")
        self.f.flush()
        return item

    def open_spider(self, spider):
        """
        爬虫开始执行时，调用
        :param spider:
        :return:
        """
        self.f= open('ooo.log','w')

    def close_spider(self, spider):
        """
        爬虫关闭时，被调用
        :param spider:
        :return:
        """
        self.f.close()

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

# Scrapy settings for pachong project
#
# For simplicity, this file contains only settings considered important or
# commonly used. You can find more settings consulting the documentation:
#
#     https://doc.scrapy.org/en/latest/topics/settings.html
#     https://doc.scrapy.org/en/latest/topics/downloader-middleware.html
#     https://doc.scrapy.org/en/latest/topics/spider-middleware.html

BOT_NAME = 'pachong'

SPIDER_MODULES = ['pachong.spiders']
NEWSPIDER_MODULE = 'pachong.spiders'


# Crawl responsibly by identifying yourself (and your website) on the user-agent
#USER_AGENT = 'pachong (+http://www.yourdomain.com)'

# Obey robots.txt rules
ROBOTSTXT_OBEY = True

# Configure maximum concurrent requests performed by Scrapy (default: 16)
#CONCURRENT_REQUESTS = 32

# Configure a delay for requests for the same website (default: 0)
# See https://doc.scrapy.org/en/latest/topics/settings.html#download-delay
# See also autothrottle settings and docs
#DOWNLOAD_DELAY = 3
# The download delay setting will honor only one of:
#CONCURRENT_REQUESTS_PER_DOMAIN = 16
#CONCURRENT_REQUESTS_PER_IP = 16

# Disable cookies (enabled by default)
#COOKIES_ENABLED = False

# Disable Telnet Console (enabled by default)
#TELNETCONSOLE_ENABLED = False

# 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',
#}

# Enable or disable spider middlewares
# See https://doc.scrapy.org/en/latest/topics/spider-middleware.html
#SPIDER_MIDDLEWARES = {
#    'pachong.middlewares.PachongSpiderMiddleware': 543,
#}

# Enable or disable downloader middlewares
# See https://doc.scrapy.org/en/latest/topics/downloader-middleware.html
#DOWNLOADER_MIDDLEWARES = {
#    'pachong.middlewares.PachongDownloaderMiddleware': 543,
#}

# Enable or disable extensions
# See https://doc.scrapy.org/en/latest/topics/extensions.html
#EXTENSIONS = {
#    'scrapy.extensions.telnet.TelnetConsole': None,
#}

# Configure item pipelines
# See https://doc.scrapy.org/en/latest/topics/item-pipeline.html
ITEM_PIPELINES = {
   'pachong.pipelines.PachongPipeline': 300,#300 优先级
}

# Enable and configure the AutoThrottle extension (disabled by default)
# See https://doc.scrapy.org/en/latest/topics/autothrottle.html
#AUTOTHROTTLE_ENABLED = True
# The initial download delay
#AUTOTHROTTLE_START_DELAY = 5
# The maximum download delay to be set in case of high latencies
#AUTOTHROTTLE_MAX_DELAY = 60
# The average number of requests Scrapy should be sending in parallel to
# each remote server
#AUTOTHROTTLE_TARGET_CONCURRENCY = 1.0
# Enable showing throttling stats for every response received:
#AUTOTHROTTLE_DEBUG = False

# Enable and configure HTTP caching (disabled by default)
# See https://doc.scrapy.org/en/latest/topics/downloader-middleware.html#httpcache-middleware-settings
#HTTPCACHE_ENABLED = True
#HTTPCACHE_EXPIRATION_SECS = 0
#HTTPCACHE_DIR = 'httpcache'
#HTTPCACHE_IGNORE_HTTP_CODES = []
#HTTPCACHE_STORAGE = 'scrapy.extensions.httpcache.FilesystemCacheStorage'
DEPTH_LIMIT = 2  #爬取深度两层

http://www.cnblogs.com/wupeiqi/articles/6229292.html

scrapy  代码注释

start_request

　　start_request中的url 为起始url，是一个生成器，返回一个可迭代对象

spider中初始的request是通过调用 start_requests() 来获取的。 start_requests() 读取 start_urls 中的URL， 并以 parse 为回调函数生成 Request 。

该方法必须返回一个可迭代对象(iterable)。该对象包含了spider用于爬取的第一个Request。

当spider启动爬取并且未制定URL时，该方法被调用。 当指定了URL时，make_requests_from_url() 将被调用来创建Request对象。 该方法仅仅会被Scrapy调用一次，因此您可以将其实现为生成器。

该方法的默认实现是使用 start_urls 的url生成Request。

如果您想要修改最初爬取某个网站的Request对象，您可以重写(override)该方法。 例如，如果您需要在启动时以POST登录某个网站，你可以这么写:
def start_requests(self):
    return [scrapy.FormRequest("http://www.example.com/login",
                               formdata={'user': 'john', 'pass': 'secret'},
                               callback=self.logged_in)]

def logged_in(self, response):
    # here you would extract links to follow and return Requests for
    # each of them, with another callback
    pass

# -*- coding: utf-8 -*-
import scrapy
from bs4 import BeautifulSoup
from scrapy.selector import HtmlXPathSelector
from scrapy.http import Request
from ..items import XianglongItem
from scrapy.http import HtmlResponse
from scrapy.http.response.html import HtmlResponse

"""
obj = ChoutiSpider()
obj.start_requests()

"""
class ChoutiSpider(scrapy.Spider):
    name = 'chouti'
    allowed_domains = ['chouti.com']
    start_urls = ['https://dig.chouti.com/',]

    def start_requests(self):
        for url in self.start_urls:
            yield Request(
                url=url,
                callback=self.parse,
                headers={'User-Agent':'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/63.0.3239.132 Safari/537.36'}
            )

    def parse(self, response):
        """
        当起始URL下载完毕后，自动执行parse函数：response封装了响应相关的所有内容。
        :param response:
        :return:
        """
        pages = response.xpath('//div[@id="page-area"]//a[@class="ct_pagepa"]/@href').extract()
        for page_url in pages:
            page_url = "https://dig.chouti.com" + page_url
            yield Request(url=page_url,callback=self.parse,headers={'User-Agent':'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/63.0.3239.132 Safari/537.36'})

数据解析

　　功能：将字符串转换成对象

- 方式一：
    response.xpath('//div[@id='content-list']/div[@class='item']')
- 方式二：
    hxs = HtmlXPathSelector(response=response)
    items = hxs.xpath("//div[@id='content-list']/div[@class='item']")
查找规则：
//a
//div/a
//a[re:test(@id, "id+")]            

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

解析：
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()

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)

pipelines

在setting中配置pipeline

ITEM_PIPELINES = {
   'pachong.pipelines.PachongPipeline': 300,#300 值越小 优先级越高  0~1000
   'pachong.pipelines.DBPipeline': 300,#300 优先级
}

多pipelines ，pipelines返回值会传递给下一个pipelines的process_item

　　想要丢弃： 使用rasie DropItem

示例

from scrapy.exceptions import DropItem
class FilePipeline(object):

    def process_item(self, item, spider):
        print('写入文件',item['href'])

        # return item
        raise DropItem()

pipelines 方法有4种：

　　    1）   __init__()  构造方法

　　　2）　open_spider()

　　　3）   close_spider()

　　　4）　from_crawler(),  属于类方法，可以进行类定制

当根据配置文件：
    ITEM_PIPELINES = {
       'xianglong.pipelines.FilePipeline': 300,
       'xianglong.pipelines.DBPipeline': 301,
    }
找到相关的类：FilePipeline之后，会优先判断类中是否含有 from_crawler
    如果有：
        obj = FilePipeline.from_crawler()
    没有则：
        obj = FilePipeline()
    #执行顺序
    obj.open_spider(..)
    ob.process_item(..)
    obj.close_spider(..)

 根据配置文件读取相关值，再进行pipeline处理  ——现在使用了from_crawler方法

from scrapy.exceptions import DropItem

class FilePipeline(object):
    def __init__(self,path):
        self.path = path
        self.f = None

    @classmethod
    def from_crawler(cls, crawler):
        """
        初始化时候，用于创建pipeline对象
        :param crawler:
        :return:
        """
        # return cls()

        path = crawler.settings.get('XL_FILE_PATH')
        return cls(path)

    def process_item(self, item, spider):
        self.f.write(item['href']+'
')
        return item


    def open_spider(self, spider):
        """
        爬虫开始执行时，调用
        :param spider:
        :return:
        """
        self.f = open(self.path,'w')

    def close_spider(self, spider):
        """
        爬虫关闭时，被调用
        :param spider:
        :return:
        """
        self.f.close()


class DBPipeline(object):

    def process_item(self, item, spider):

        print('数据库',item)

        return item

    def open_spider(self, spider):
        """
        爬虫开始执行时，调用
        :param spider:
        :return:
        """
        print('打开数据')

    def close_spider(self, spider):
        """
        爬虫关闭时，被调用
        :param spider:
        :return:
        """
        print('关闭数据库')

POST/请求头/Cookie

Post请求头示例

from scrapy.http import Request
req = Request(
    url='http://dig.chouti.com/login',
    method='POST',
    body='phone=8613121758648&password=woshiniba&oneMonth=1',
    headers={'Content-Type': 'application/x-www-form-urlencoded; charset=UTF-8'},
    cookies={},
    callback=self.parse_check_login,
)

第一种

 res.headers.getlist('Set-Cookie')获取cookie

第二种：手动获取

cookie_dict = {}
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():
            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=cookie_dict, # 手动携带
    callback=self.check_login
)
yield req

第三种  自动设置

meta={"cookiejar"=True}

 def start_requests(self):
        for url in self.start_urls:
            yield Request(url=url,callback=self.parse_index,meta={'cookiejar':True})

默认允许操作cookie

 

去重规则

在setting中配置

DUPEFILTER_CLASS = 'scrapy.dupefilter.RFPDupeFilter'  #自定义去重规则
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

和pipelines很像，需要自己编写类，定义去重规则，但是scrapy采用bloomfilter 进行去重

class MyDupeFilter(BaseDupeFilter):

    def __init__(self):
        self.record = set()

    @classmethod
    def from_settings(cls, settings):
        return cls()

    def request_seen(self, request):
        if request.url in self.record:
            print('已经访问过了', request.url)
            return True
        self.record.add(request.url)

    def open(self):  # can return deferred
        pass

    def close(self, reason):  # can return a deferred
        pass

为请求创建唯一标识

http://www.oldboyedu.com?id=1&age=2
http://www.oldboyedu.com?age=2&id=1
如上面的两个url只是请求参数变换位置，其实还是指向同一个地址

对url的识别需要使用到request_fingerprint(request)函数

　　对url排序后hash

from scrapy.http import Request


u1 = Request(url='http://www.oldboyedu.com?id=1&age=2')
u2 = Request(url='http://www.oldboyedu.com?age=2&id=1')

result1 = request_fingerprint(u1)
result2 = request_fingerprint(u2)
print(result1,result2)

问题：记录到低要不要放在数据库？

　　【使用redis集合存储】  访问记录可以放在redis中。

dont_filter

from scrapy.core.scheduler import Scheduler

def enqueue_request(self, request):
# request.dont_filter=False
    # self.df.request_seen(request):
    #   - True,已经访问
    #   - False，未访问
# request.dont_filter=True，全部加入到调度器
if not request.dont_filter and self.df.request_seen(request):
    self.df.log(request, self.spider)
    return False
# 如果往下走，把请求加入调度器
dqok = self._dqpush(request)
        

中间件

请求头USER_AGENT设置

问题：对爬虫中所有请求发送时，携带请求头？

方案一：在每个Request对象中添加一个请求头

方案二：下载中间件

setting中配置：

DOWNLOADER_MIDDLEWARES = {'xianglong.middlewares.UserAgentDownloaderMiddleware': 543,}

编写类：

class UserAgentDownloaderMiddleware(object):

    @classmethod
    def from_crawler(cls, crawler):
        # This method is used by Scrapy to create your spiders.
        s = cls()
        return s

    def process_request(self, request, spider):
        # Called for each request that goes through the downloader
        # middleware.

        # Must either:
        # - return None: continue processing this request
        # - or return a Response object
        # - or return a Request object
        # - or raise IgnoreRequest: process_exception() methods of
        #   installed downloader middleware will be called

        request.headers['User-Agent'] = "Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/63.0.3239.132 Safari/537.36"

        # return None # 继续执行后续的中间件的process_request

        # from scrapy.http import Request
        # return Request(url='www.baidu.com') # 重新放入调度器中，当前请求不再继续处理

        # from scrapy.http import HtmlResponse # 执行从最后一个开始执行所有的process_response
        # return HtmlResponse(url='www.baidu.com',body=b'asdfuowjelrjaspdoifualskdjf;lajsdf')

    def process_response(self, request, response, spider):
        # Called with the response returned from the downloader.

        # Must either;
        # - return a Response object
        # - return a Request object
        # - or raise IgnoreRequest
        return response

    def process_exception(self, request, exception, spider):
        # Called when a download handler or a process_request()
        # (from other downloader middleware) raises an exception.

        # Must either:
        # - return None: continue processing this exception
        # - return a Response object: stops process_exception() chain
        # - return a Request object: stops process_exception() chain
        pass

如return none 继续执行下一个中间件，returen Request(...)返回调度器产生死循环

　四种返回结果如下图

下载中间件： scrapy中如何添加代理

当前进程设置的环境变量，只能在当前进程中使用

加代理，只是在请求头中设置信息

方式一：

　　内置加ip

　　os.envriron['HTTP_PROXY']='http://192.168.0.0.1'

 方式二：自定义下载中间件

import random
                import base64
                import six
                def to_bytes(text, encoding=None, errors='strict'):
                    """Return the binary representation of `text`. If `text`
                    is already a bytes object, return it as-is."""
                    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 MyProxyDownloaderMiddleware(object):
                    def process_request(self, request, spider):
                        proxy_list = [
                            {'ip_port': '111.11.228.75:80', 'user_pass': 'xxx:123'},
                            {'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(proxy_list)
                        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)
                        else:
                            request.meta['proxy'] = to_bytes("http://%s" % proxy['ip_port'])
    

setting配置：

DOWNLOADER_MIDDLEWARES = {
                       # 'xiaohan.middlewares.MyProxyDownloaderMiddleware': 543,
                    }

如何处理https请求

自己定制，不掏钱

DOWNLOA....两个变量需要在setting中配置

DOWNLOADER_HTTPCLIENTFACTORY = "scrapy.core.downloader.webclient.ScrapyHTTPClientFactory"
                    DOWNLOADER_CLIENTCONTEXTFACTORY = "xiaohan.middlewares.MySSLFactory"

    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))
                        )

下载中间件的作用？

　　在每次下载前和下载后对请求和相应可以定制功能。例如：user_Agent / 代理 / cookie

爬虫中间件

class XiaohanSpiderMiddleware(object):
    # Not all methods need to be defined. If a method is not defined,
    # scrapy acts as if the spider middleware does not modify the
    # passed objects.
    def __init__(self):
        pass
    @classmethod
    def from_crawler(cls, crawler):
        # This method is used by Scrapy to create your spiders.
        s = cls()
        return s

    # 每次下载完成之后，未执行parse函数之前。
    def process_spider_input(self, response, spider):
        # Called for each response that goes through the spider
        # middleware and into the spider.

        # Should return None or raise an exception.
        print('process_spider_input',response)
        return None

    def process_spider_output(self, response, result, spider):
        # Called with the results returned from the Spider, after
        # it has processed the response.

        # Must return an iterable of Request, dict or Item objects.
        print('process_spider_output',response)
        for i in result:
            yield i

    def process_spider_exception(self, response, exception, spider):
        # Called when a spider or process_spider_input() method
        # (from other spider middleware) raises an exception.

        # Should return either None or an iterable of Response, dict
        # or Item objects.
        pass

    # 爬虫启动时，第一次执行start_requests时，触发。（只执行一次）
    def process_start_requests(self, start_requests, spider):
        # Called with the start requests of the spider, and works
        # similarly to the process_spider_output() method, except
        # that it doesn’t have a response associated.

        # Must return only requests (not items).

        print('process_start_requests')
        for r in start_requests:
            yield r

setting中配置spidermiddleware

SPIDER_MIDDLEWARES = {
   'xiaohan.middlewares.XiaohanSpiderMiddleware': 543,
}

应用：

　　先定义中间件

　　在setting中配置

扩展：信号

扩展+信号

from scrapy import signals


class MyExtension(object):
    def __init__(self):
        pass

    @classmethod
    def from_crawler(cls, crawler):
        obj = cls()
        # 在爬虫打开时，触发spider_opened信号相关的所有函数：xxxxxxxxxxx
        crawler.signals.connect(obj.xxxxxxxxxxx1, signal=signals.spider_opened)
        # 在爬虫关闭时，触发spider_closed信号相关的所有函数：xxxxxxxxxxx
        crawler.signals.connect(obj.uuuuuuuuuu, signal=signals.spider_closed)
        return obj

    def xxxxxxxxxxx1(self, spider):
        print('open')

    def uuuuuuuuuu(self, spider):
        print('close')

            return obj

EXTENSIONS = {
                'xiaohan.extends.MyExtension':500,
            }

自定义命令

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()

PS：源码
def run(self, args, opts):
    from scrapy.crawler import CrawlerProcess
    CrawlerProcess.crawl
    CrawlerProcess.start
    """
    self.crawler_process对象中含有：_active = {d,}
    """
    self.crawler_process.crawl('chouti',**opts.__dict__)
    self.crawler_process.crawl('cnblogs',**opts.__dict__)
    #
    self.crawler_process.start()

自定义scrapy框架

scrapy-redis 组件

scrapy-redis扩展

自定义扩展

 调度器

引擎调用调度器，默认广度度优先

 

加上scrapy_redis 把调度器和Request放入redis中　　

setting中的配置

　　

 scrapy遍历使用算法

深度优先

　　算法：递归实现

 

广度优先

 

 

 scrapy-redis

目的：帮助开发者实现分布式爬虫程序

scrapy-redis去重规则

# ############ 连接redis 信息 #################
REDIS_HOST = '127.0.0.1'                            # 主机名
REDIS_PORT = 6379                                   # 端口
# REDIS_URL = 'redis://user:pass@hostname:9001'       # 连接URL（优先于以上配置）
REDIS_PARAMS  = {}                                  # Redis连接参数             默认：REDIS_PARAMS = {'socket_timeout': 30,'socket_connect_timeout': 30,'retry_on_timeout': True,'encoding': REDIS_ENCODING,}）
# REDIS_PARAMS['redis_cls'] = 'myproject.RedisClient' # 指定连接Redis的Python模块  默认：redis.StrictRedis
REDIS_ENCODING = "utf-8"


# 自定义去重规则
DUPEFILTER_CLASS = "scrapy_redis.dupefilter.RFPDupeFilter"

from scrapy_redis.dupefilter import RFPDupeFilter
class MyRFPDupeFilter(RFPDupeFilter):
    pass
    
    
# 自定义去重规则
DUPEFILTER_CLASS = "wenwen.dup.MyRFPDupeFilter"

 调度器

# 有引擎来执行：自定义调度器
SCHEDULER = "scrapy_redis.scheduler.Scheduler"

SCHEDULER_QUEUE_CLASS = 'scrapy_redis.queue.FifoQueue'  # 默认使用优先级队列（默认），其他：PriorityQueue（有序集合），FifoQueue（列表）、LifoQueue（列表）
SCHEDULER_QUEUE_KEY = '%(spider)s:requests'  # 调度器中请求存放在redis中的key
SCHEDULER_SERIALIZER = "scrapy_redis.picklecompat"  # 对保存到redis中的数据进行序列化，默认使用pickle
SCHEDULER_PERSIST = True  # 是否在关闭时候保留原来的调度器和去重记录，True=保留，False=清空
SCHEDULER_FLUSH_ON_START = True  # 是否在开始之前清空 调度器和去重记录，True=清空，False=不清空
# SCHEDULER_IDLE_BEFORE_CLOSE = 10  # 去调度器中获取数据时，如果为空，最多等待时间（最后没数据，未获取到）。
SCHEDULER_DUPEFILTER_KEY = '%(spider)s:dupefilter'  # 去重规则，在redis中保存时对应的key  chouti:dupefilter
SCHEDULER_DUPEFILTER_CLASS = 'scrapy_redis.dupefilter.RFPDupeFilter'  # 去重规则对应处理的类
DUPEFILTER_DEBUG = False

 scrapy-redis  和 scrapy功能对比

class RFPDupeFilter(BaseDupeFilter):
    """Request Fingerprint duplicates filter"""

    def __init__(self, path=None, debug=False):
        self.fingerprints = set()
        

    @classmethod
    def from_settings(cls, settings):
        debug = settings.getbool('DUPEFILTER_DEBUG')
        return cls(job_dir(settings), debug)

    def request_seen(self, request):
        # 将request对象转换成唯一标识。
        fp = self.request_fingerprint(request)
        # 判断在集合中是否存在，如果存在则返回True，表示已经访问过。
        if fp in self.fingerprints:
            return True
        # 之前未访问过，将url添加到访问记录中。
        self.fingerprints.add(fp)

    def request_fingerprint(self, request):
        return request_fingerprint(request)

class RFPDupeFilter(BaseDupeFilter):
    """Redis-based request duplicates filter.

    This class can also be used with default Scrapy's scheduler.

    """

    logger = logger

    def __init__(self, server, key, debug=False):
        
        # self.server = redis连接
        self.server = server
        # self.key = dupefilter:123912873234
        self.key = key
        

    @classmethod
    def from_settings(cls, settings):
        
        # 读取配置，连接redis
        server = get_redis_from_settings(settings)

        #  key = dupefilter:123912873234
        key = defaults.DUPEFILTER_KEY % {'timestamp': int(time.time())}
        debug = settings.getbool('DUPEFILTER_DEBUG')
        return cls(server, key=key, debug=debug)

    @classmethod
    def from_crawler(cls, crawler):
        
        return cls.from_settings(crawler.settings)

    def request_seen(self, request):
        
        fp = self.request_fingerprint(request)
        # This returns the number of values added, zero if already exists.
        # self.server=redis连接
        # 添加到redis集合中：1，添加工程；0，已经存在
        added = self.server.sadd(self.key, fp)
        return added == 0

    def request_fingerprint(self, request):
        
        return request_fingerprint(request)

    def close(self, reason=''):
        
        self.clear()

    def clear(self):
        """Clears fingerprints data."""
        self.server.delete(self.key)

将request对象全部放到内存维护的队列：self.q = deque()
将request对象全部放到硬盘维护的队列：文件操作


SCHEDULER_DISK_QUEUE = 'scrapy.squeues.PickleLifoDiskQueue'
SCHEDULER_MEMORY_QUEUE = 'scrapy.squeues.LifoMemoryQueue'
SCHEDULER_PRIORITY_QUEUE = 'queuelib.PriorityQueue'

class Scheduler(object):

    def __init__(self, dupefilter, jobdir=None, dqclass=None, mqclass=None,
                 logunser=False, stats=None, pqclass=None):
        self.df = dupefilter
        self.dqdir = self._dqdir(jobdir)
        self.pqclass = pqclass
        self.dqclass = dqclass
        self.mqclass = mqclass
        self.logunser = logunser
        self.stats = stats

    @classmethod
    def from_crawler(cls, crawler):
        settings = crawler.settings
        dupefilter_cls = load_object(settings['DUPEFILTER_CLASS'])
        dupefilter = dupefilter_cls.from_settings(settings)
        
        pqclass = load_object(settings['SCHEDULER_PRIORITY_QUEUE'])
        dqclass = load_object(settings['SCHEDULER_DISK_QUEUE'])
        mqclass = load_object(settings['SCHEDULER_MEMORY_QUEUE'])
        
        
        logunser = settings.getbool('LOG_UNSERIALIZABLE_REQUESTS', settings.getbool('SCHEDULER_DEBUG'))
        return cls(dupefilter, jobdir=job_dir(settings), logunser=logunser,
                   stats=crawler.stats, pqclass=pqclass, dqclass=dqclass, mqclass=mqclass)

    def has_pending_requests(self):
        return len(self) > 0

    def open(self, spider):
        self.spider = spider
        self.mqs = self.pqclass(self._newmq)
        self.dqs = self._dq() if self.dqdir else None
        return self.df.open()

    def close(self, reason):
        if self.dqs:
            prios = self.dqs.close()
            with open(join(self.dqdir, 'active.json'), 'w') as f:
                json.dump(prios, f)
        return self.df.close(reason)

    def enqueue_request(self, request):
        # request.dont_filter=False
            # self.df.request_seen(request):
            #   - True,已经访问
            #   - False，未访问
        # request.dont_filter=True，全部加入到调度器
        if not request.dont_filter and self.df.request_seen(request):
            self.df.log(request, self.spider)
            return False
        # 如果往下走，把请求加入调度器
        dqok = self._dqpush(request)
        if dqok:
            self.stats.inc_value('scheduler/enqueued/disk', spider=self.spider)
        else:
            self._mqpush(request)
            self.stats.inc_value('scheduler/enqueued/memory', spider=self.spider)
        self.stats.inc_value('scheduler/enqueued', spider=self.spider)
        return True

    def next_request(self):
        request = self.mqs.pop()
        if request:
            self.stats.inc_value('scheduler/dequeued/memory', spider=self.spider)
        else:
            request = self._dqpop()
            if request:
                self.stats.inc_value('scheduler/dequeued/disk', spider=self.spider)
        if request:
            self.stats.inc_value('scheduler/dequeued', spider=self.spider)
        return request

    def __len__(self):
        return len(self.dqs) + len(self.mqs) if self.dqs else len(self.mqs)

    def _dqpush(self, request):
        if self.dqs is None:
            return
        try:
            reqd = request_to_dict(request, self.spider)
            self.dqs.push(reqd, -request.priority)
        except ValueError as e:  # non serializable request
            if self.logunser:
                msg = ("Unable to serialize request: %(request)s - reason:"
                       " %(reason)s - no more unserializable requests will be"
                       " logged (stats being collected)")
                logger.warning(msg, {'request': request, 'reason': e},
                               exc_info=True, extra={'spider': self.spider})
                self.logunser = False
            self.stats.inc_value('scheduler/unserializable',
                                 spider=self.spider)
            return
        else:
            return True

    def _mqpush(self, request):
        self.mqs.push(request, -request.priority)

    def _dqpop(self):
        if self.dqs:
            d = self.dqs.pop()
            if d:
                return request_from_dict(d, self.spider)

    def _newmq(self, priority):
        return self.mqclass()

    def _newdq(self, priority):
        return self.dqclass(join(self.dqdir, 'p%s' % priority))

    def _dq(self):
        activef = join(self.dqdir, 'active.json')
        if exists(activef):
            with open(activef) as f:
                prios = json.load(f)
        else:
            prios = ()
        q = self.pqclass(self._newdq, startprios=prios)
        if q:
            logger.info("Resuming crawl (%(queuesize)d requests scheduled)",
                        {'queuesize': len(q)}, extra={'spider': self.spider})
        return q

    def _dqdir(self, jobdir):
        if jobdir:
            dqdir = join(jobdir, 'requests.queue')
            if not exists(dqdir):
                os.makedirs(dqdir)
            return dqdir

将请求通过pickle进行序列化，然后添加到redis： 列表或有序结合中。
SCHEDULER_QUEUE_CLASS = 'scrapy_redis.queue.LifoQueue' 
                
class Scheduler(object):


def __init__(self, server,
             persist=False,
             flush_on_start=False,
             queue_key=defaults.SCHEDULER_QUEUE_KEY,
             queue_cls=defaults.SCHEDULER_QUEUE_CLASS,
             dupefilter_key=defaults.SCHEDULER_DUPEFILTER_KEY,
             dupefilter_cls=defaults.SCHEDULER_DUPEFILTER_CLASS,
             idle_before_close=0,
             serializer=None):
    
    if idle_before_close < 0:
        raise TypeError("idle_before_close cannot be negative")

    self.server = server
    self.persist = persist
    self.flush_on_start = flush_on_start
    self.queue_key = queue_key
    self.queue_cls = queue_cls
    self.dupefilter_cls = dupefilter_cls
    self.dupefilter_key = dupefilter_key
    self.idle_before_close = idle_before_close
    self.serializer = serializer
    self.stats = None

def __len__(self):
    return len(self.queue)

@classmethod
def from_settings(cls, settings):
    kwargs = {
        'persist': settings.getbool('SCHEDULER_PERSIST'),
        'flush_on_start': settings.getbool('SCHEDULER_FLUSH_ON_START'),
        'idle_before_close': settings.getint('SCHEDULER_IDLE_BEFORE_CLOSE'),
    }

    # If these values are missing, it means we want to use the defaults.
    optional = {
        # TODO: Use custom prefixes for this settings to note that are
        # specific to scrapy-redis.
        'queue_key': 'SCHEDULER_QUEUE_KEY',
        'queue_cls': 'SCHEDULER_QUEUE_CLASS',
        'dupefilter_key': 'SCHEDULER_DUPEFILTER_KEY',
        # We use the default setting name to keep compatibility.
        'dupefilter_cls': 'DUPEFILTER_CLASS',
        'serializer': 'SCHEDULER_SERIALIZER',
    }
    for name, setting_name in optional.items():
        val = settings.get(setting_name)
        if val:
            kwargs[name] = val

    # Support serializer as a path to a module.
    if isinstance(kwargs.get('serializer'), six.string_types):
        kwargs['serializer'] = importlib.import_module(kwargs['serializer'])

    server = connection.from_settings(settings)
    # Ensure the connection is working.
    server.ping()

    return cls(server=server, **kwargs)

@classmethod
def from_crawler(cls, crawler):
    instance = cls.from_settings(crawler.settings)
    # FIXME: for now, stats are only supported from this constructor
    instance.stats = crawler.stats
    return instance

def open(self, spider):
    self.spider = spider

    try:
        self.queue = load_object(self.queue_cls)(
            server=self.server,
            spider=spider,
            key=self.queue_key % {'spider': spider.name},
            serializer=self.serializer,
        )
    except TypeError as e:
        raise ValueError("Failed to instantiate queue class '%s': %s",
                         self.queue_cls, e)

    try:
        self.df = load_object(self.dupefilter_cls)(
            server=self.server,
            key=self.dupefilter_key % {'spider': spider.name},
            debug=spider.settings.getbool('DUPEFILTER_DEBUG'),
        )
    except TypeError as e:
        raise ValueError("Failed to instantiate dupefilter class '%s': %s",
                         self.dupefilter_cls, e)

    if self.flush_on_start:
        self.flush()
    # notice if there are requests already in the queue to resume the crawl
    if len(self.queue):
        spider.log("Resuming crawl (%d requests scheduled)" % len(self.queue))

def close(self, reason):
    if not self.persist:
        self.flush()

def flush(self):
    self.df.clear()
    self.queue.clear()

def enqueue_request(self, request):
    if not request.dont_filter and self.df.request_seen(request):
        self.df.log(request, self.spider)
        return False
    if self.stats:
        self.stats.inc_value('scheduler/enqueued/redis', spider=self.spider)
    self.queue.push(request)
    return True

def next_request(self):
    block_pop_timeout = self.idle_before_close
    request = self.queue.pop(block_pop_timeout)
    if request and self.stats:
        self.stats.inc_value('scheduler/dequeued/redis', spider=self.spider)
    return request

def has_pending_requests(self):
    return len(self) > 0


相关Queue源码：
class Base(object):
    """Per-spider base queue class"""

    def __init__(self, server, spider, key, serializer=None):
        """Initialize per-spider redis queue.

        Parameters
        ----------
        server : StrictRedis
            Redis client instance.
        spider : Spider
            Scrapy spider instance.
        key: str
            Redis key where to put and get messages.
        serializer : object
            Serializer object with ``loads`` and ``dumps`` methods.

        """
        if serializer is None:
            # Backward compatibility.
            # TODO: deprecate pickle.
            serializer = picklecompat
        if not hasattr(serializer, 'loads'):
            raise TypeError("serializer does not implement 'loads' function: %r"
                            % serializer)
        if not hasattr(serializer, 'dumps'):
            raise TypeError("serializer '%s' does not implement 'dumps' function: %r"
                            % serializer)

        self.server = server
        self.spider = spider
        self.key = key % {'spider': spider.name}
        self.serializer = serializer

    def _encode_request(self, request):
        """Encode a request object"""
        obj = request_to_dict(request, self.spider)
        return self.serializer.dumps(obj)

    def _decode_request(self, encoded_request):
        """Decode an request previously encoded"""
        obj = self.serializer.loads(encoded_request)
        return request_from_dict(obj, self.spider)

    def __len__(self):
        """Return the length of the queue"""
        raise NotImplementedError

    def push(self, request):
        """Push a request"""
        raise NotImplementedError

    def pop(self, timeout=0):
        """Pop a request"""
        raise NotImplementedError

    def clear(self):
        """Clear queue/stack"""
        self.server.delete(self.key)


class FifoQueue(Base):
    """Per-spider FIFO queue"""

    def __len__(self):
        """Return the length of the queue"""
        return self.server.llen(self.key)

    def push(self, request):
        """Push a request"""
        self.server.lpush(self.key, self._encode_request(request))

    def pop(self, timeout=0):
        """Pop a request"""
        if timeout > 0:
            data = self.server.brpop(self.key, timeout)
            if isinstance(data, tuple):
                data = data[1]
        else:
            data = self.server.rpop(self.key)
        if data:
            return self._decode_request(data)


class PriorityQueue(Base):
    """Per-spider priority queue abstraction using redis' sorted set"""

    def __len__(self):
        """Return the length of the queue"""
        return self.server.zcard(self.key)

    def push(self, request):
        """Push a request"""
        data = self._encode_request(request)
        score = -request.priority
        # We don't use zadd method as the order of arguments change depending on
        # whether the class is Redis or StrictRedis, and the option of using
        # kwargs only accepts strings, not bytes.
        self.server.execute_command('ZADD', self.key, score, data)

    def pop(self, timeout=0):
        """
        Pop a request
        timeout not support in this queue class
        """
        # use atomic range/remove using multi/exec
        pipe = self.server.pipeline()
        pipe.multi()
        pipe.zrange(self.key, 0, 0).zremrangebyrank(self.key, 0, 0)
        results, count = pipe.execute()
        if results:
            return self._decode_request(results[0])


class LifoQueue(Base):
    """Per-spider LIFO queue."""

    def __len__(self):
        """Return the length of the stack"""
        return self.server.llen(self.key)

    def push(self, request):
        """Push a request"""
        self.server.lpush(self.key, self._encode_request(request))

    def pop(self, timeout=0):
        """Pop a request"""
        if timeout > 0:
            data = self.server.blpop(self.key, timeout)
            if isinstance(data, tuple):
                data = data[1]
        else:
            data = self.server.lpop(self.key)

        if data:
            return self._decode_request(data)


# TODO: Deprecate the use of these names.
SpiderQueue = FifoQueue
SpiderStack = LifoQueue
SpiderPriorityQueue = PriorityQueue

注意：爬虫爬取数据时存在层级和优先级：爬虫中间件实现

使用scrapy-redis组件

配置：
# ############ 连接redis 信息 #################
REDIS_HOST = '127.0.0.1'                            # 主机名
REDIS_PORT = 6379                                   # 端口
# REDIS_URL = 'redis://user:pass@hostname:9001'       # 连接URL（优先于以上配置）
REDIS_PARAMS  = {}                                  # Redis连接参数             默认：REDIS_PARAMS = {'socket_timeout': 30,'socket_connect_timeout': 30,'retry_on_timeout': True,'encoding': REDIS_ENCODING,}）
# REDIS_PARAMS['redis_cls'] = 'myproject.RedisClient' # 指定连接Redis的Python模块  默认：redis.StrictRedis
REDIS_ENCODING = "utf-8"


# 自定义去重规则
DUPEFILTER_CLASS = "scrapy_redis.dupefilter.RFPDupeFilter"

# ############ 连接redis 信息 #################
REDIS_HOST = '127.0.0.1'                            # 主机名
REDIS_PORT = 6379                                   # 端口
# REDIS_URL = 'redis://user:pass@hostname:9001'       # 连接URL（优先于以上配置）
REDIS_PARAMS  = {}                                  # Redis连接参数             默认：REDIS_PARAMS = {'socket_timeout': 30,'socket_connect_timeout': 30,'retry_on_timeout': True,'encoding': REDIS_ENCODING,}）
# REDIS_PARAMS['redis_cls'] = 'myproject.RedisClient' # 指定连接Redis的Python模块  默认：redis.StrictRedis
REDIS_ENCODING = "utf-8"


# 有引擎来执行：自定义调度器
SCHEDULER = "scrapy_redis.scheduler.Scheduler"
SCHEDULER_QUEUE_CLASS = 'scrapy_redis.queue.LifoQueue'  # 默认使用优先级队列（默认广度优先），其他：PriorityQueue（有序集合），FifoQueue（列表）、LifoQueue（列表）
SCHEDULER_QUEUE_KEY = '%(spider)s:requests'  # 调度器中请求存放在redis中的key
SCHEDULER_SERIALIZER = "scrapy_redis.picklecompat"  # 对保存到redis中的数据进行序列化，默认使用pickle
SCHEDULER_PERSIST = True  # 是否在关闭时候保留原来的调度器和去重记录，True=保留，False=清空
SCHEDULER_FLUSH_ON_START = False  # 是否在开始之前清空 调度器和去重记录，True=清空，False=不清空
# SCHEDULER_IDLE_BEFORE_CLOSE = 10  # 去调度器中获取数据时，如果为空，最多等待时间（最后没数据，未获取到）。
SCHEDULER_DUPEFILTER_KEY = '%(spider)s:dupefilter'  # 去重规则，在redis中保存时对应的key  chouti:dupefilter
SCHEDULER_DUPEFILTER_CLASS = 'scrapy.dupefilter.RFPDupeFilter'  # 去重规则对应处理的类
#去重规则对应处理的类
DUPEFILTER_DEBUG = False

# ############ 连接redis 信息 #################
REDIS_HOST = '127.0.0.1'                            # 主机名
REDIS_PORT = 6379                                   # 端口
# REDIS_URL = 'redis://user:pass@hostname:9001'       # 连接URL（优先于以上配置）
REDIS_PARAMS  = {}                                  # Redis连接参数             默认：REDIS_PARAMS = {'socket_timeout': 30,'socket_connect_timeout': 30,'retry_on_timeout': True,'encoding': REDIS_ENCODING,}）
# REDIS_PARAMS['redis_cls'] = 'myproject.RedisClient' # 指定连接Redis的Python模块  默认：redis.StrictRedis
REDIS_ENCODING = "utf-8"


# 有引擎来执行：自定义调度器
SCHEDULER = "scrapy_redis.scheduler.Scheduler"
SCHEDULER_QUEUE_CLASS = 'scrapy_redis.queue.LifoQueue'  # 默认使用优先级队列（默认广度优先），其他：PriorityQueue（有序集合），FifoQueue（列表）、LifoQueue（列表）
SCHEDULER_QUEUE_KEY = '%(spider)s:requests'  # 调度器中请求存放在redis中的key
SCHEDULER_SERIALIZER = "scrapy_redis.picklecompat"  # 对保存到redis中的数据进行序列化，默认使用pickle
SCHEDULER_PERSIST = True  # 是否在关闭时候保留原来的调度器和去重记录，True=保留，False=清空
SCHEDULER_FLUSH_ON_START = False  # 是否在开始之前清空 调度器和去重记录，True=清空，False=不清空
# SCHEDULER_IDLE_BEFORE_CLOSE = 10  # 去调度器中获取数据时，如果为空，最多等待时间（最后没数据，未获取到）。
SCHEDULER_DUPEFILTER_KEY = '%(spider)s:dupefilter'  # 去重规则，在redis中保存时对应的key  chouti:dupefilter
SCHEDULER_DUPEFILTER_CLASS = 'scrapy_redis.dupefilter.RFPDupeFilter'  # 去重规则对应处理的类
DUPEFILTER_DEBUG = False

使用scrapy-redis内置的pipeline做持久化：就是将item对象保存到redis的列表中，如下代码所示

配置：
# ############ 连接redis 信息 #################
REDIS_HOST = '127.0.0.1'                            # 主机名
REDIS_PORT = 6379                                   # 端口
# REDIS_URL = 'redis://user:pass@hostname:9001'       # 连接URL（优先于以上配置）
REDIS_PARAMS  = {}                                  # Redis连接参数             默认：REDIS_PARAMS = {'socket_timeout': 30,'socket_connect_timeout': 30,'retry_on_timeout': True,'encoding': REDIS_ENCODING,}）
# REDIS_PARAMS['redis_cls'] = 'myproject.RedisClient' # 指定连接Redis的Python模块  默认：redis.StrictRedis
REDIS_ENCODING = "utf-8"
ITEM_PIPELINES = {
   'scrapy_redis.pipelines.RedisPipeline': 300,
}
以上功能全部应用的配置：
# ############ 连接redis 信息 #################
REDIS_HOST = '127.0.0.1'                            # 主机名
REDIS_PORT = 6379                                   # 端口
# REDIS_URL = 'redis://user:pass@hostname:9001'       # 连接URL（优先于以上配置）
REDIS_PARAMS  = {}                                  # Redis连接参数             默认：REDIS_PARAMS = {'socket_timeout': 30,'socket_connect_timeout': 30,'retry_on_timeout': True,'encoding': REDIS_ENCODING,}）
# REDIS_PARAMS['redis_cls'] = 'myproject.RedisClient' # 指定连接Redis的Python模块  默认：redis.StrictRedis
REDIS_ENCODING = "utf-8"

DUPEFILTER_CLASS = "scrapy_redis.dupefilter.RFPDupeFilter"

# 有引擎来执行：自定义调度器
SCHEDULER = "scrapy_redis.scheduler.Scheduler"
SCHEDULER_QUEUE_CLASS = 'scrapy_redis.queue.LifoQueue'  # 默认使用优先级队列（默认广度优先），其他：PriorityQueue（有序集合），FifoQueue（列表）、LifoQueue（列表）
SCHEDULER_QUEUE_KEY = '%(spider)s:requests'  # 调度器中请求存放在redis中的key
SCHEDULER_SERIALIZER = "scrapy_redis.picklecompat"  # 对保存到redis中的数据进行序列化，默认使用pickle
SCHEDULER_PERSIST = True  # 是否在关闭时候保留原来的调度器和去重记录，True=保留，False=清空
SCHEDULER_FLUSH_ON_START = False  # 是否在开始之前清空 调度器和去重记录，True=清空，False=不清空
# SCHEDULER_IDLE_BEFORE_CLOSE = 10  # 去调度器中获取数据时，如果为空，最多等待时间（最后没数据，未获取到）。
SCHEDULER_DUPEFILTER_KEY = '%(spider)s:dupefilter'  # 去重规则，在redis中保存时对应的key  chouti:dupefilter
SCHEDULER_DUPEFILTER_CLASS = 'scrapy_redis.dupefilter.RFPDupeFilter'  # 去重规则对应处理的类
DUPEFILTER_DEBUG = False


# 深度和优先级相关
DEPTH_PRIORITY = 1

配置：
    REDIS_START_URLS_BATCH_SIZE = 1
    # REDIS_START_URLS_AS_SET = True # 把起始url放到redis的集合
    REDIS_START_URLS_AS_SET = False # 把起始url放到redis的列表

爬虫：
    from scrapy_redis.spiders import RedisSpider
    from scrapy.http import Request
    from ..items import WenwenItem

    class ChoutiSpider(RedisSpider):
        name = 'chouti'
        allowed_domains = ['chouti.com']

        def parse(self, response):
            # 随着深度的增加、优先级一直在递减
            print(response)


放置起始URL：
    import redis

    conn = redis.Redis(host='127.0.0.1',port=6379)

    # 起始url的Key： chouti:start_urls
    conn.lpush("chouti:start_urls",'https://dig.chouti.com/r/ask/hot/12')

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