Scrapy、Scrapy-redis组件

目录

• Scrapy
  • 一、安装
  • 二、基本使用
  • 1. 基本命令
  • 2.项目结构以及爬虫应用简介
  • 3. 小试牛刀
  • 4. 选择器
  • 5. 格式化处理
  • 6.中间件
  • 7. 自定制命令
  • 8. 自定义扩展
  • 9. 避免重复访问
  • 10.其他
  • 11.TinyScrapy
• scrapy-redis组件
  • 1. URL去重
  • 2. 调度器
  • 3. 数据持久化
  • 4. 起始URL相关
  • scrapy-redis示例

 

Scrapy

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

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

Scrapy主要包括了以下组件：

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

Scrapy运行流程大概如下：

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

一、安装

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

二、基本使用

1. 基本命令

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

2.项目结构以及爬虫应用简介

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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

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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：

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1	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

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#!/usr/bin/env python # -*- coding:utf-8 -*- from scrapy.selector import Selector, HtmlXPathSelector from scrapy.http import HtmlResponse html = """<!DOCTYPE html> <html>     <head lang="en">         <meta charset="UTF-8">         <title></title>     </head>     <body>         <ul>             <li class="item-"><a id='i1' href="link.html">first item</a></li>             <li class="item-0"><a id='i2' href="llink.html">first item</a></li>             <li class="item-1"><a href="llink2.html">second item<span>vv</span></a></li>         </ul>         <div><a href="llink2.html">second item</a></div>     </body> </html> """ response = HtmlResponse(url='http://example.com', body=html,encoding='utf-8') # hxs = HtmlXPathSelector(response) # print(hxs) # hxs = Selector(response=response).xpath('//a') # print(hxs) # hxs = Selector(response=response).xpath('//a[2]') # print(hxs) # hxs = Selector(response=response).xpath('//a[@id]') # print(hxs) # hxs = Selector(response=response).xpath('//a[@id="i1"]') # print(hxs) # hxs = Selector(response=response).xpath('//a[@href="link.html"][@id="i1"]') # print(hxs) # hxs = Selector(response=response).xpath('//a[contains(@href, "link")]') # print(hxs) # hxs = Selector(response=response).xpath('//a[starts-with(@href, "link")]') # print(hxs) # hxs = Selector(response=response).xpath('//a[re:test(@id, "i\d+")]') # print(hxs) # hxs = Selector(response=response).xpath('//a[re:test(@id, "i\d+")]/text()').extract() # print(hxs) # hxs = Selector(response=response).xpath('//a[re:test(@id, "i\d+")]/@href').extract() # print(hxs) # hxs = Selector(response=response).xpath('/html/body/ul/li/a/@href').extract() # print(hxs) # hxs = Selector(response=response).xpath('//body/ul/li/a/@href').extract_first() # print(hxs)   # ul_list = Selector(response=response).xpath('//body/ul/li') # for item in ul_list: #     v = item.xpath('./a/span') #     # 或 #     # v = item.xpath('a/span') #     # 或 #     # v = item.xpath('*/a/span') #     print(v)

# -*- coding: utf-8 -*-
import scrapy
from scrapy.selector import HtmlXPathSelector
from scrapy.http.request import Request
from scrapy.http.cookies import CookieJar
from scrapy import FormRequest

class ChouTiSpider(scrapy.Spider):
    # 爬虫应用的名称，通过此名称启动爬虫命令
    name = "chouti"
    # 允许的域名
    allowed_domains = ["chouti.com"]

    cookie_dict = {}
    has_request_set = {}

    def start_requests(self):
        url = 'http://dig.chouti.com/'
        # return [Request(url=url, callback=self.login)]
        yield Request(url=url, callback=self.login)

    def login(self, response):
        cookie_jar = CookieJar()
        cookie_jar.extract_cookies(response, response.request)
        for k, v in cookie_jar._cookies.items():
            for i, j in v.items():
                for m, n in j.items():
                    self.cookie_dict[m] = n.value

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

    def check_login(self, response):
        req = Request(
            url='http://dig.chouti.com/',
            method='GET',
            callback=self.show,
            cookies=self.cookie_dict,
            dont_filter=True
        )
        yield req

    def show(self, response):
        # print(response)
        hxs = HtmlXPathSelector(response)
        news_list = hxs.select('//div[@id="content-list"]/div[@class="item"]')
        for new in news_list:
            # temp = new.xpath('div/div[@class="part2"]/@share-linkid').extract()
            link_id = new.xpath('*/div[@class="part2"]/@share-linkid').extract_first()
            yield Request(
                url='http://dig.chouti.com/link/vote?linksId=%s' %(link_id,),
                method='POST',
                cookies=self.cookie_dict,
                callback=self.do_favor
            )

        page_list = hxs.select('//div[@id="dig_lcpage"]//a[re:test(@href, "/all/hot/recent/\d+")]/@href').extract()
        for page in page_list:

            page_url = 'http://dig.chouti.com%s' % page
            import hashlib
            hash = hashlib.md5()
            hash.update(bytes(page_url,encoding='utf-8'))
            key = hash.hexdigest()
            if key in self.has_request_set:
                pass
            else:
                self.has_request_set[key] = page_url
                yield Request(
                    url=page_url,
                    method='GET',
                    callback=self.show
                )

    def do_favor(self, response):
        print(response.text)

示例：自动登陆抽屉并点赞

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

5. 格式化处理

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

import scrapy
from scrapy.selector import HtmlXPathSelector
from scrapy.http.request import Request
from scrapy.http.cookies import CookieJar
from scrapy import FormRequest

class XiaoHuarSpider(scrapy.Spider):
    # 爬虫应用的名称，通过此名称启动爬虫命令
    name = "xiaohuar"
    # 允许的域名
    allowed_domains = ["xiaohuar.com"]

    start_urls = [
        "http://www.xiaohuar.com/list-1-1.html",
    ]
    # custom_settings = {
    #     'ITEM_PIPELINES':{
    #         'spider1.pipelines.JsonPipeline': 100
    #     }
    # }
    has_request_set = {}

    def parse(self, response):
        # 分析页面
        # 找到页面中符合规则的内容（校花图片），保存
        # 找到所有的a标签，再访问其他a标签，一层一层的搞下去

        hxs = HtmlXPathSelector(response)

        items = hxs.select('//div[@class="item_list infinite_scroll"]/div')
        for item in items:
            src = item.select('.//div[@class="img"]/a/img/@src').extract_first()
            name = item.select('.//div[@class="img"]/span/text()').extract_first()
            school = item.select('.//div[@class="img"]/div[@class="btns"]/a/text()').extract_first()
            url = "http://www.xiaohuar.com%s" % src
            from ..items import XiaoHuarItem
            obj = XiaoHuarItem(name=name, school=school, url=url)
            yield obj

        urls = hxs.select('//a[re:test(@href, "http://www.xiaohuar.com/list-1-\d+.html")]/@href')
        for url in urls:
            key = self.md5(url)
            if key in self.has_request_set:
                pass
            else:
                self.has_request_set[key] = url
                req = Request(url=url,method='GET',callback=self.parse)
                yield req

    @staticmethod
    def md5(val):
        import hashlib
        ha = hashlib.md5()
        ha.update(bytes(val, encoding='utf-8'))
        key = ha.hexdigest()
        return key

spiders/xiahuar.py

import scrapy

class XiaoHuarItem(scrapy.Item):
    name = scrapy.Field()
    school = scrapy.Field()
    url = scrapy.Field()

items

import json
import os
import requests

class JsonPipeline(object):
    def __init__(self):
        self.file = open('xiaohua.txt', 'w')

    def process_item(self, item, spider):
        v = json.dumps(dict(item), ensure_ascii=False)
        self.file.write(v)
        self.file.write('\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

6.中间件

class SpiderMiddleware(object):

    def process_spider_input(self,response, spider):
        """
        下载完成，执行，然后交给parse处理
        :param response:
        :param spider:
        :return:
        """
        pass

    def process_spider_output(self,response, result, spider):
        """
        spider处理完成，返回时调用
        :param response:
        :param result:
        :param spider:
        :return: 必须返回包含 Request 或 Item 对象的可迭代对象(iterable)
        """
        return result

    def process_spider_exception(self,response, exception, spider):
        """
        异常调用
        :param response:
        :param exception:
        :param spider:
        :return: None,继续交给后续中间件处理异常；含 Response 或 Item 的可迭代对象(iterable)，交给调度器或pipeline
        """
        return None

    def process_start_requests(self,start_requests, spider):
        """
        爬虫启动时调用
        :param start_requests:
        :param spider:
        :return: 包含 Request 对象的可迭代对象
        """
        return start_requests

爬虫中间件

class DownMiddleware1(object):
    def process_request(self, request, spider):
        """
        请求需要被下载时，经过所有下载器中间件的process_request调用
        :param request:
        :param spider:
        :return:
            None,继续后续中间件去下载；
            Response对象，停止process_request的执行，开始执行process_response
            Request对象，停止中间件的执行，将Request重新调度器
            raise IgnoreRequest异常，停止process_request的执行，开始执行process_exception
        """
        pass

    def process_response(self, request, response, spider):
        """
        spider处理完成，返回时调用
        :param response:
        :param result:
        :param spider:
        :return:
            Response 对象：转交给其他中间件process_response
            Request 对象：停止中间件，request会被重新调度下载
            raise IgnoreRequest 异常：调用Request.errback
        """
        print('response1')
        return response

    def process_exception(self, request, exception, spider):
        """
        当下载处理器(download handler)或 process_request() (下载中间件)抛出异常
        :param response:
        :param exception:
        :param spider:
        :return:
            None：继续交给后续中间件处理异常；
            Response对象：停止后续process_exception方法
            Request对象：停止中间件，request将会被重新调用下载
        """
        return None

下载器中间件

7. 自定制命令

• 在spiders同级创建任意目录，如：commands
• 在其中创建 crawlall.py 文件 （此处文件名就是自定义的命令）

      from scrapy.commands import ScrapyCommand
      from scrapy.utils.project import get_project_settings
  
      class Command(ScrapyCommand):
  
          requires_project = True
  
          def syntax(self):
              return '[options]'
  
          def short_desc(self):
              return 'Runs all of the spiders'
  
          def run(self, args, opts):
              spider_list = self.crawler_process.spiders.list()
              for name in spider_list:
                  self.crawler_process.crawl(name, **opts.__dict__)
              self.crawler_process.start()

  crawlall.py

• 在settings.py 中添加配置 COMMANDS_MODULE = '项目名称.目录名称'
• 在项目目录执行命令：scrapy crawlall

8. 自定义扩展

自定义扩展时，利用信号在指定位置注册制定操作

from scrapy import signals

class MyExtension(object):
    def __init__(self, value):
        self.value = value

    @classmethod
    def from_crawler(cls, crawler):
        val = crawler.settings.getint('MMMM')
        ext = cls(val)

        crawler.signals.connect(ext.spider_opened, signal=signals.spider_opened)
        crawler.signals.connect(ext.spider_closed, signal=signals.spider_closed)

        return ext

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

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

9. 避免重复访问

scrapy默认使用 scrapy.dupefilter.RFPDupeFilter 进行去重，相关配置有：

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DUPEFILTER_CLASS = 'scrapy.dupefilter.RFPDupeFilter' DUPEFILTER_DEBUG = False JOBDIR = "保存范文记录的日志路径，如：/root/"  # 最终路径为 /root/requests.seen

class RepeatUrl:
    def __init__(self):
        self.visited_url = set()

    @classmethod
    def from_settings(cls, settings):
        """
        初始化时，调用
        :param settings:
        :return:
        """
        return cls()

    def request_seen(self, request):
        """
        检测当前请求是否已经被访问过
        :param request:
        :return: True表示已经访问过；False表示未访问过
        """
        if request.url in self.visited_url:
            return True
        self.visited_url.add(request.url)
        return False

    def open(self):
        """
        开始爬去请求时，调用
        :return:
        """
        print('open replication')

    def close(self, reason):
        """
        结束爬虫爬取时，调用
        :param reason:
        :return:
        """
        print('close replication')

    def log(self, request, spider):
        """
        记录日志
        :param request:
        :param spider:
        :return:
        """
        print('repeat', request.url)

自定义URL去重操作

10.其他

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

# Scrapy settings for step8_king project
#
# For simplicity, this file contains only settings considered important or
# commonly used. You can find more settings consulting the documentation:
#
#     http://doc.scrapy.org/en/latest/topics/settings.html
#     http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html
#     http://scrapy.readthedocs.org/en/latest/topics/spider-middleware.html

# 1. 爬虫名称
BOT_NAME = 'step8_king'

# 2. 爬虫应用路径
SPIDER_MODULES = ['step8_king.spiders']
NEWSPIDER_MODULE = 'step8_king.spiders'

# Crawl responsibly by identifying yourself (and your website) on the user-agent
# 3. 客户端 user-agent请求头
# USER_AGENT = 'step8_king (+http://www.yourdomain.com)'

# Obey robots.txt rules
# 4. 禁止爬虫配置
# ROBOTSTXT_OBEY = False

# Configure maximum concurrent requests performed by Scrapy (default: 16)
# 5. 并发请求数
# CONCURRENT_REQUESTS = 4

# Configure a delay for requests for the same website (default: 0)
# See http://scrapy.readthedocs.org/en/latest/topics/settings.html#download-delay
# See also autothrottle settings and docs
# 6. 延迟下载秒数
# DOWNLOAD_DELAY = 2

# The download delay setting will honor only one of:
# 7. 单域名访问并发数，并且延迟下次秒数也应用在每个域名
# CONCURRENT_REQUESTS_PER_DOMAIN = 2
# 单IP访问并发数，如果有值则忽略：CONCURRENT_REQUESTS_PER_DOMAIN，并且延迟下次秒数也应用在每个IP
# CONCURRENT_REQUESTS_PER_IP = 3

# Disable cookies (enabled by default)
# 8. 是否支持cookie，cookiejar进行操作cookie
# COOKIES_ENABLED = True
# COOKIES_DEBUG = True

# Disable Telnet Console (enabled by default)
# 9. Telnet用于查看当前爬虫的信息，操作爬虫等...
#    使用telnet ip port ，然后通过命令操作
# TELNETCONSOLE_ENABLED = True
# TELNETCONSOLE_HOST = '127.0.0.1'
# TELNETCONSOLE_PORT = [6023,]

# 10. 默认请求头
# Override the default request headers:
# DEFAULT_REQUEST_HEADERS = {
#     'Accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,*/*;q=0.8',
#     'Accept-Language': 'en',
# }

# Configure item pipelines
# See http://scrapy.readthedocs.org/en/latest/topics/item-pipeline.html
# 11. 定义pipeline处理请求
# ITEM_PIPELINES = {
#    'step8_king.pipelines.JsonPipeline': 700,
#    'step8_king.pipelines.FilePipeline': 500,
# }

# 12. 自定义扩展，基于信号进行调用
# Enable or disable extensions
# See http://scrapy.readthedocs.org/en/latest/topics/extensions.html
# EXTENSIONS = {
#     # 'step8_king.extensions.MyExtension': 500,
# }

# 13. 爬虫允许的最大深度，可以通过meta查看当前深度；0表示无深度
# DEPTH_LIMIT = 3

# 14. 爬取时，0表示深度优先Lifo(默认)；1表示广度优先FiFo

# 后进先出，深度优先
# DEPTH_PRIORITY = 0
# SCHEDULER_DISK_QUEUE = 'scrapy.squeue.PickleLifoDiskQueue'
# SCHEDULER_MEMORY_QUEUE = 'scrapy.squeue.LifoMemoryQueue'
# 先进先出，广度优先

# DEPTH_PRIORITY = 1
# SCHEDULER_DISK_QUEUE = 'scrapy.squeue.PickleFifoDiskQueue'
# SCHEDULER_MEMORY_QUEUE = 'scrapy.squeue.FifoMemoryQueue'

# 15. 调度器队列
# SCHEDULER = 'scrapy.core.scheduler.Scheduler'
# from scrapy.core.scheduler import Scheduler

# 16. 访问URL去重
# DUPEFILTER_CLASS = 'step8_king.duplication.RepeatUrl'

# Enable and configure the AutoThrottle extension (disabled by default)
# See http://doc.scrapy.org/en/latest/topics/autothrottle.html

"""
17. 自动限速算法
    from scrapy.contrib.throttle import AutoThrottle
    自动限速设置
    1. 获取最小延迟 DOWNLOAD_DELAY
    2. 获取最大延迟 AUTOTHROTTLE_MAX_DELAY
    3. 设置初始下载延迟 AUTOTHROTTLE_START_DELAY
    4. 当请求下载完成后，获取其"连接"时间 latency，即：请求连接到接受到响应头之间的时间
    5. 用于计算的... AUTOTHROTTLE_TARGET_CONCURRENCY
    target_delay = latency / self.target_concurrency
    new_delay = (slot.delay + target_delay) / 2.0 # 表示上一次的延迟时间
    new_delay = max(target_delay, new_delay)
    new_delay = min(max(self.mindelay, new_delay), self.maxdelay)
    slot.delay = new_delay
"""

# 开始自动限速
# AUTOTHROTTLE_ENABLED = True
# The initial download delay
# 初始下载延迟
# AUTOTHROTTLE_START_DELAY = 5
# The maximum download delay to be set in case of high latencies
# 最大下载延迟
# AUTOTHROTTLE_MAX_DELAY = 10
# The average number of requests Scrapy should be sending in parallel to each remote server
# 平均每秒并发数
# AUTOTHROTTLE_TARGET_CONCURRENCY = 1.0

# Enable showing throttling stats for every response received:
# 是否显示
# AUTOTHROTTLE_DEBUG = True

# Enable and configure HTTP caching (disabled by default)
# See http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html#httpcache-middleware-settings

"""
18. 启用缓存
    目的用于将已经发送的请求或相应缓存下来，以便以后使用

    from scrapy.downloadermiddlewares.httpcache import HttpCacheMiddleware
    from scrapy.extensions.httpcache import DummyPolicy
    from scrapy.extensions.httpcache import FilesystemCacheStorage
"""
# 是否启用缓存策略
# HTTPCACHE_ENABLED = True

# 缓存策略：所有请求均缓存，下次在请求直接访问原来的缓存即可
# HTTPCACHE_POLICY = "scrapy.extensions.httpcache.DummyPolicy"
# 缓存策略：根据Http响应头：Cache-Control、Last-Modified 等进行缓存的策略
# HTTPCACHE_POLICY = "scrapy.extensions.httpcache.RFC2616Policy"

# 缓存超时时间
# HTTPCACHE_EXPIRATION_SECS = 0

# 缓存保存路径
# HTTPCACHE_DIR = 'httpcache'

# 缓存忽略的Http状态码
# HTTPCACHE_IGNORE_HTTP_CODES = []

# 缓存存储的插件
# HTTPCACHE_STORAGE = 'scrapy.extensions.httpcache.FilesystemCacheStorage'

"""
19. 代理，需要在环境变量中设置
    from scrapy.contrib.downloadermiddleware.httpproxy import HttpProxyMiddleware

    方式一：使用默认
        os.environ
        {
            http_proxy:http://root:woshiniba@192.168.11.11:9999/
            https_proxy:http://192.168.11.11:9999/
        }
    方式二：使用自定义下载中间件

    def to_bytes(text, encoding=None, errors='strict'):
        if isinstance(text, bytes):
            return text
        if not isinstance(text, six.string_types):
            raise TypeError('to_bytes must receive a unicode, str or bytes '
                            'object, got %s' % type(text).__name__)
        if encoding is None:
            encoding = 'utf-8'
        return text.encode(encoding, errors)

    class ProxyMiddleware(object):
        def process_request(self, request, spider):
            PROXIES = [
                {'ip_port': '111.11.228.75:80', 'user_pass': ''},
                {'ip_port': '120.198.243.22:80', 'user_pass': ''},
                {'ip_port': '111.8.60.9:8123', 'user_pass': ''},
                {'ip_port': '101.71.27.120:80', 'user_pass': ''},
                {'ip_port': '122.96.59.104:80', 'user_pass': ''},
                {'ip_port': '122.224.249.122:8088', 'user_pass': ''},
            ]
            proxy = random.choice(PROXIES)
            if proxy['user_pass'] is not None:
                request.meta['proxy'] = to_bytes（"http://%s" % proxy['ip_port']）
                encoded_user_pass = base64.encodestring(to_bytes(proxy['user_pass']))
                request.headers['Proxy-Authorization'] = to_bytes('Basic ' + encoded_user_pass)
                print "**************ProxyMiddleware have pass************" + proxy['ip_port']
            else:
                print "**************ProxyMiddleware no pass************" + proxy['ip_port']
                request.meta['proxy'] = to_bytes("http://%s" % proxy['ip_port'])

    DOWNLOADER_MIDDLEWARES = {
       'step8_king.middlewares.ProxyMiddleware': 500,
    }

"""

"""
20. Https访问
    Https访问时有两种情况：
    1. 要爬取网站使用的可信任证书(默认支持)
        DOWNLOADER_HTTPCLIENTFACTORY = "scrapy.core.downloader.webclient.ScrapyHTTPClientFactory"
        DOWNLOADER_CLIENTCONTEXTFACTORY = "scrapy.core.downloader.contextfactory.ScrapyClientContextFactory"

    2. 要爬取网站使用的自定义证书
        DOWNLOADER_HTTPCLIENTFACTORY = "scrapy.core.downloader.webclient.ScrapyHTTPClientFactory"
        DOWNLOADER_CLIENTCONTEXTFACTORY = "step8_king.https.MySSLFactory"

        # https.py
        from scrapy.core.downloader.contextfactory import ScrapyClientContextFactory
        from twisted.internet.ssl import (optionsForClientTLS, CertificateOptions, PrivateCertificate)

        class MySSLFactory(ScrapyClientContextFactory):
            def getCertificateOptions(self):
                from OpenSSL import crypto
                v1 = crypto.load_privatekey(crypto.FILETYPE_PEM, open('/Users/wupeiqi/client.key.unsecure', mode='r').read())
                v2 = crypto.load_certificate(crypto.FILETYPE_PEM, open('/Users/wupeiqi/client.pem', mode='r').read())
                return CertificateOptions(
                    privateKey=v1,  # pKey对象
                    certificate=v2,  # X509对象
                    verify=False,
                    method=getattr(self, 'method', getattr(self, '_ssl_method', None))
                )
    其他：
        相关类
            scrapy.core.downloader.handlers.http.HttpDownloadHandler
            scrapy.core.downloader.webclient.ScrapyHTTPClientFactory
            scrapy.core.downloader.contextfactory.ScrapyClientContextFactory
        相关配置
            DOWNLOADER_HTTPCLIENTFACTORY
            DOWNLOADER_CLIENTCONTEXTFACTORY

"""

"""
21. 爬虫中间件
    class SpiderMiddleware(object):

        def process_spider_input(self,response, spider):
            '''
            下载完成，执行，然后交给parse处理
            :param response:
            :param spider:
            :return:
            '''
            pass

        def process_spider_output(self,response, result, spider):
            '''
            spider处理完成，返回时调用
            :param response:
            :param result:
            :param spider:
            :return: 必须返回包含 Request 或 Item 对象的可迭代对象(iterable)
            '''
            return result

        def process_spider_exception(self,response, exception, spider):
            '''
            异常调用
            :param response:
            :param exception:
            :param spider:
            :return: None,继续交给后续中间件处理异常；含 Response 或 Item 的可迭代对象(iterable)，交给调度器或pipeline
            '''
            return None

        def process_start_requests(self,start_requests, spider):
            '''
            爬虫启动时调用
            :param start_requests:
            :param spider:
            :return: 包含 Request 对象的可迭代对象
            '''
            return start_requests

    内置爬虫中间件：
        'scrapy.contrib.spidermiddleware.httperror.HttpErrorMiddleware': 50,
        'scrapy.contrib.spidermiddleware.offsite.OffsiteMiddleware': 500,
        'scrapy.contrib.spidermiddleware.referer.RefererMiddleware': 700,
        'scrapy.contrib.spidermiddleware.urllength.UrlLengthMiddleware': 800,
        'scrapy.contrib.spidermiddleware.depth.DepthMiddleware': 900,

"""
# from scrapy.contrib.spidermiddleware.referer import RefererMiddleware
# Enable or disable spider middlewares
# See http://scrapy.readthedocs.org/en/latest/topics/spider-middleware.html
SPIDER_MIDDLEWARES = {
   # 'step8_king.middlewares.SpiderMiddleware': 543,
}

"""
22. 下载中间件
    class DownMiddleware1(object):
        def process_request(self, request, spider):
            '''
            请求需要被下载时，经过所有下载器中间件的process_request调用
            :param request:
            :param spider:
            :return:
                None,继续后续中间件去下载；
                Response对象，停止process_request的执行，开始执行process_response
                Request对象，停止中间件的执行，将Request重新调度器
                raise IgnoreRequest异常，停止process_request的执行，开始执行process_exception
            '''
            pass

        def process_response(self, request, response, spider):
            '''
            spider处理完成，返回时调用
            :param response:
            :param result:
            :param spider:
            :return:
                Response 对象：转交给其他中间件process_response
                Request 对象：停止中间件，request会被重新调度下载
                raise IgnoreRequest 异常：调用Request.errback
            '''
            print('response1')
            return response

        def process_exception(self, request, exception, spider):
            '''
            当下载处理器(download handler)或 process_request() (下载中间件)抛出异常
            :param response:
            :param exception:
            :param spider:
            :return:
                None：继续交给后续中间件处理异常；
                Response对象：停止后续process_exception方法
                Request对象：停止中间件，request将会被重新调用下载
            '''
            return None

    默认下载中间件
    {
        'scrapy.contrib.downloadermiddleware.robotstxt.RobotsTxtMiddleware': 100,
        'scrapy.contrib.downloadermiddleware.httpauth.HttpAuthMiddleware': 300,
        'scrapy.contrib.downloadermiddleware.downloadtimeout.DownloadTimeoutMiddleware': 350,
        'scrapy.contrib.downloadermiddleware.useragent.UserAgentMiddleware': 400,
        'scrapy.contrib.downloadermiddleware.retry.RetryMiddleware': 500,
        'scrapy.contrib.downloadermiddleware.defaultheaders.DefaultHeadersMiddleware': 550,
        'scrapy.contrib.downloadermiddleware.redirect.MetaRefreshMiddleware': 580,
        'scrapy.contrib.downloadermiddleware.httpcompression.HttpCompressionMiddleware': 590,
        'scrapy.contrib.downloadermiddleware.redirect.RedirectMiddleware': 600,
        'scrapy.contrib.downloadermiddleware.cookies.CookiesMiddleware': 700,
        'scrapy.contrib.downloadermiddleware.httpproxy.HttpProxyMiddleware': 750,
        'scrapy.contrib.downloadermiddleware.chunked.ChunkedTransferMiddleware': 830,
        'scrapy.contrib.downloadermiddleware.stats.DownloaderStats': 850,
        'scrapy.contrib.downloadermiddleware.httpcache.HttpCacheMiddleware': 900,
    }

"""
# from scrapy.contrib.downloadermiddleware.httpauth import HttpAuthMiddleware
# Enable or disable downloader middlewares
# See http://scrapy.readthedocs.org/en/latest/topics/downloader-middleware.html
# DOWNLOADER_MIDDLEWARES = {
#    'step8_king.middlewares.DownMiddleware1': 100,
#    'step8_king.middlewares.DownMiddleware2': 500,
# }

settings

11.TinyScrapy

#!/usr/bin/env python
# -*- coding:utf-8 -*-
import types
from twisted.internet import defer
from twisted.web.client import getPage
from twisted.internet import reactor

class Request(object):
    def __init__(self, url, callback):
        self.url = url
        self.callback = callback
        self.priority = 0

class HttpResponse(object):
    def __init__(self, content, request):
        self.content = content
        self.request = request

class ChouTiSpider(object):

    def start_requests(self):
        url_list = ['http://www.cnblogs.com/', 'http://www.bing.com']
        for url in url_list:
            yield Request(url=url, callback=self.parse)

    def parse(self, response):
        print(response.request.url)
        # yield Request(url="http://www.baidu.com", callback=self.parse)

from queue import Queue
Q = Queue()

class CallLaterOnce(object):
    def __init__(self, func, *a, **kw):
        self._func = func
        self._a = a
        self._kw = kw
        self._call = None

    def schedule(self, delay=0):
        if self._call is None:
            self._call = reactor.callLater(delay, self)

    def cancel(self):
        if self._call:
            self._call.cancel()

    def __call__(self):
        self._call = None
        return self._func(*self._a, **self._kw)

class Engine(object):
    def __init__(self):
        self.nextcall = None
        self.crawlling = []
        self.max = 5
        self._closewait = None

    def get_response(self,content, request):
        response = HttpResponse(content, request)
        gen = request.callback(response)
        if isinstance(gen, types.GeneratorType):
            for req in gen:
                req.priority = request.priority + 1
                Q.put(req)

    def rm_crawlling(self,response,d):
        self.crawlling.remove(d)

    def _next_request(self,spider):
        if Q.qsize() == 0 and len(self.crawlling) == 0:
            self._closewait.callback(None)

        if len(self.crawlling) >= 5:
            return
        while len(self.crawlling) < 5:
            try:
                req = Q.get(block=False)
            except Exception as e:
                req = None
            if not req:
                return
            d = getPage(req.url.encode('utf-8'))
            self.crawlling.append(d)
            d.addCallback(self.get_response, req)
            d.addCallback(self.rm_crawlling,d)
            d.addCallback(lambda _: self.nextcall.schedule())

    @defer.inlineCallbacks
    def crawl(self):
        spider = ChouTiSpider()
        start_requests = iter(spider.start_requests())
        flag = True
        while flag:
            try:
                req = next(start_requests)
                Q.put(req)
            except StopIteration as e:
                flag = False

        self.nextcall = CallLaterOnce(self._next_request,spider)
        self.nextcall.schedule()

        self._closewait = defer.Deferred()
        yield self._closewait

    @defer.inlineCallbacks
    def pp(self):
        yield self.crawl()

_active = set()
obj = Engine()
d = obj.crawl()
_active.add(d)

li = defer.DeferredList(_active)
li.addBoth(lambda _,*a,**kw: reactor.stop())

reactor.run()

参考版

点击下载

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

scrapy-redis是一个基于redis的scrapy组件，通过它可以快速实现简单分布式爬虫程序，该组件本质上提供了三大功能：

• scheduler - 调度器
• dupefilter - URL去重规则（被调度器使用）
• pipeline   - 数据持久化

回到顶部

scrapy-redis组件

1. URL去重

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定义去重规则（被调度器调用并应用）       a. 内部会使用以下配置进行连接Redis           # REDIS_HOST = 'localhost'                            # 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"                            # redis编码类型             默认：'utf-8'           b. 去重规则通过redis的集合完成，集合的Key为：               key = defaults.DUPEFILTER_KEY % {'timestamp': int(time.time())}         默认配置：             DUPEFILTER_KEY = 'dupefilter:%(timestamp)s'                    c. 去重规则中将url转换成唯一标示，然后在redis中检查是否已经在集合中存在               from scrapy.utils import request         from scrapy.http import Request                   req = Request(url='http://www.cnblogs.com/wupeiqi.html')         result = request.request_fingerprint(req)         print(result) # 8ea4fd67887449313ccc12e5b6b92510cc53675c                             PS:             - URL参数位置不同时，计算结果一致；             - 默认请求头不在计算范围，include_headers可以设置指定请求头             示例：                 from scrapy.utils import request                 from scrapy.http import Request                                   req = Request(url='http://www.baidu.com?name=8&id=1',callback=lambda x:print(x),cookies={'k1':'vvvvv'})                 result = request.request_fingerprint(req,include_headers=['cookies',])                                   print(result)                                   req = Request(url='http://www.baidu.com?id=1&name=8',callback=lambda x:print(x),cookies={'k1':666})                                   result = request.request_fingerprint(req,include_headers=['cookies',])                                   print(result)           """ # Ensure all spiders share same duplicates filter through redis. # DUPEFILTER_CLASS = "scrapy_redis.dupefilter.RFPDupeFilter"

2. 调度器

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""" 调度器，调度器使用PriorityQueue（有序集合）、FifoQueue（列表）、LifoQueue（列表）进行保存请求，并且使用RFPDupeFilter对URL去重           a. 调度器         SCHEDULER_QUEUE_CLASS = 'scrapy_redis.queue.PriorityQueue'          # 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         SCHEDULER_DUPEFILTER_CLASS = 'scrapy_redis.dupefilter.RFPDupeFilter'# 去重规则对应处理的类     """ # Enables scheduling storing requests queue in redis. SCHEDULER = "scrapy_redis.scheduler.Scheduler"   # Default requests serializer is pickle, but it can be changed to any module # with loads and dumps functions. Note that pickle is not compatible between # python versions. # Caveat: In python 3.x, the serializer must return strings keys and support # bytes as values. Because of this reason the json or msgpack module will not # work by default. In python 2.x there is no such issue and you can use # 'json' or 'msgpack' as serializers. # SCHEDULER_SERIALIZER = "scrapy_redis.picklecompat"   # Don't cleanup redis queues, allows to pause/resume crawls. # SCHEDULER_PERSIST = True   # Schedule requests using a priority queue. (default) # SCHEDULER_QUEUE_CLASS = 'scrapy_redis.queue.PriorityQueue'   # Alternative queues. # SCHEDULER_QUEUE_CLASS = 'scrapy_redis.queue.FifoQueue' # SCHEDULER_QUEUE_CLASS = 'scrapy_redis.queue.LifoQueue'   # Max idle time to prevent the spider from being closed when distributed crawling. # This only works if queue class is SpiderQueue or SpiderStack, # and may also block the same time when your spider start at the first time (because the queue is empty). # SCHEDULER_IDLE_BEFORE_CLOSE = 10

3. 数据持久化

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2. 定义持久化，爬虫yield Item对象时执行RedisPipeline           a. 将item持久化到redis时，指定key和序列化函数               REDIS_ITEMS_KEY = '%(spider)s:items'         REDIS_ITEMS_SERIALIZER = 'json.dumps'           b. 使用列表保存item数据

4. 起始URL相关

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""" 起始URL相关       a. 获取起始URL时，去集合中获取还是去列表中获取？True，集合；False，列表         REDIS_START_URLS_AS_SET = False    # 获取起始URL时，如果为True，则使用self.server.spop；如果为False，则使用self.server.lpop     b. 编写爬虫时，起始URL从redis的Key中获取         REDIS_START_URLS_KEY = '%(name)s:start_urls'           """ # If True, it uses redis' ``spop`` operation. This could be useful if you # want to avoid duplicates in your start urls list. In this cases, urls must # be added via ``sadd`` command or you will get a type error from redis. # REDIS_START_URLS_AS_SET = False   # Default start urls key for RedisSpider and RedisCrawlSpider. # REDIS_START_URLS_KEY = '%(name)s:start_urls'

scrapy-redis示例

# DUPEFILTER_CLASS = "scrapy_redis.dupefilter.RFPDupeFilter"
#
#
# from scrapy_redis.scheduler import Scheduler
# from scrapy_redis.queue import PriorityQueue
# SCHEDULER = "scrapy_redis.scheduler.Scheduler"
# SCHEDULER_QUEUE_CLASS = 'scrapy_redis.queue.PriorityQueue'          # 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 = 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
# SCHEDULER_DUPEFILTER_CLASS = 'scrapy_redis.dupefilter.RFPDupeFilter'# 去重规则对应处理的类
#
#
#
# REDIS_HOST = '10.211.55.13'                           # 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"                              # redis编码类型             默认：'utf-8'

配置文件

import scrapy

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

    def parse(self, response):
        for i in range(0,10):
            yield

爬虫文件