Scrapy、Scrapy-redis组件
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:
- 引擎从调度器中取出一个链接(URL)用于接下来的抓取
- 引擎把URL封装成一个请求(Request)传给下载器
- 下载器把资源下载下来,并封装成应答包(Response)
- 爬虫解析Response
- 解析出实体(Item),则交给实体管道进行进一步的处理
- 解析出的是链接(URL),则把URL交给调度器等待抓取
一、安装
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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
import sys,os sys.stdout=io.TextIOWrapper(sys.stdout.buffer,encoding='gb18030')
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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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)
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
import scrapy class XiaoHuarItem(scrapy.Item): name = scrapy.Field() school = scrapy.Field() url = scrapy.Field()
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
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。
对于pipeline可以做更多,如下:
from scrapy.exceptions import DropItem class CustomPipeline(object): def __init__(self,v): self.value = v def process_item(self, item, spider): # 操作并进行持久化 # return表示会被后续的pipeline继续处理 return item # 表示将item丢弃,不会被后续pipeline处理 # raise DropItem() @classmethod def from_crawler(cls, crawler): """ 初始化时候,用于创建pipeline对象 :param crawler: :return: """ val = crawler.settings.getint('MMMM') return cls(val) def open_spider(self,spider): """ 爬虫开始执行时,调用 :param spider: :return: """ print('000000') def close_spider(self,spider): """ 爬虫关闭时,被调用 :param spider: :return: """ print('111111')
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
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
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()
- 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)
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, # }
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()
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
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'
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