Scrapy
Scrapy是一个可扩展功能齐全的爬虫框架
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
安装: Linux/mac - pip3 install scrapy Windows: - 安装twsited 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-xxxxx.whl - 安装scrapy d. pip3 install scrapy -i http://pypi.douban.com/simple --trusted-host pypi.douban.com - 安装pywin32 e. pip3 install pywin32 -i http://pypi.douban.com/simple --trusted-host pypi.douban.com
快速使用
scrapy startproject weiwu # 创建项目 cd weiwu scrapy genspider chouti chouti.com #创建爬虫应用 scrapy crawl chouti --nolog # 运行爬虫应用
项目结构
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
# -*- coding: utf-8 -*- import scrapy class ChoutiSpider(scrapy.Spider): name = 'chouti' allowed_domains = ['chouti.com'] start_urls = ['http://dig.chouti.com/'] def parse(self, response): print(response.text)
如果windows出现乱码加上以下设置
import sys,os sys.stdout=io.TextIOWrapper(sys.stdout.buffer,encoding='gb18030')
小试牛刀
# -*- coding: utf-8 -*- import scrapy from bs4 import BeautifulSoup from scrapy.selector import HtmlXPathSelector from scrapy.http import Request from ..items import WeiwuItem 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,自动执行parse函数:response封装了响应相关的所有内容。 :param response: :return: """ hxs = HtmlXPathSelector(response=response) # 去下载的页面中:找新闻 items = hxs.xpath("//div[@id='content-list']/div[@class='item']") for item in items: href = item.xpath('.//div[@class="part1"]//a[1]/@href').extract_first() text = item.xpath('.//div[@class="part1"]//a[1]/text()').extract_first() item = WeiwuItem(title=text,href=href) yield item 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)
执行此爬虫文件,则在终端进入项目目录执行如下命令:
scrapy crawl chouti --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
1. spider,编写爬虫程序,去解析并处理请求。
def parse(): - HtmlXPathSelector # 类似BS4的beautifulsoup,用于结构化HTML代码并提供选择器功能解析器 - yield item # 返回item对象到pipeline进行数据持久化 - yield 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
2. item/pipelines # 格式化和持久化
配置:
ITEM_PIPELINES = { 'weiwu.pipelines.WeiwuPipeline': 300, }
使用:
class WeiwuPipeline(object): def process_item(self, item, spider): self.f.write(item['href']+'\n') self.f.flush() # 存到数据库 return item def open_spider(self, spider): """ 爬虫开始执行时,调用 :param spider: :return: """ self.f = open('url.log','w') def close_spider(self, spider): """ 爬虫关闭时,被调用 :param spider: :return: """ self.f.close()
选择器
#!/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)
解析器的作用是把字符串转化为对象
- 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, "i\d+")] # 正则[re:test(@标签名,正则表达式)]
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()
应用示例:
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)
PS:浏览器右键打开检查,在elements选择标签右键选copy-->copy xpath可以直接拿到标签的解析结果
示例:自动登录抽屉并点赞
# -*- 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。
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')
start_requests
def start_requests(self): for url in self.start_urls: yield Request(url=url, callback=self.parse2) def start_requests(self): req_list = [] for url in self.start_urls: req_list.append(Request(url=url, callback=self.parse2)) return req_list # 因为scrapy内部会将返回值转换成迭代器。
对于爬虫,循环经历这样的事情:
-
您首先生成用于抓取第一个URL的初始请求,然后指定要使用从这些请求下载的响应调用的回调函数。
第一个执行的请求通过调用 start_requests()(默认情况下)Request为在start_urls和中指定的URL生成的parse方法获取, 并且该方法作为请求的回调函数。
-
在回调函数中,您将解析响应(网页),并返回带有提取的数据,Item对象, Request对象或这些对象的可迭代的对象。这些请求还将包含回调(可能是相同的),然后由Scrapy下载,然后由指定的回调处理它们的响应。
-
在回调函数中,您通常使用选择器来解析页面内容 (但您也可以使用BeautifulSoup,lxml或您喜欢的任何机制),并使用解析的数据生成项目。
-
最后,从爬虫返回的项目通常将持久存储到数据库(在某些项目管道中)或使用Feed导出写入文件。
start_requests()它是爬虫的入口方法,此方法必须返回一个可迭代的对象或者生成器,爬虫将根据这些请求爬取网站
之前在start_urls中存入我们要爬虫的网页链接,但是如果我们要爬虫的链接很多,而且是有一定规律的,我们就需要重写这个方法了,首先我们看看start_requests这个方法是干嘛的:
可见它就是从start_urls中读取链接,然后使用make_requests_from_url生成Request,
那么这就意味我们可以在start_requests方法中根据我们自己的需求往start_urls中写入我们自定义的规律的链接:
Scrapy将start_requests()
方法返回的scrapy.Request
对象列入计划表, 根据收到每个对象的响应, 实例化Response
对象并且调用callback
方法和请求联系在一起(也就是解析,即parse()方法)把响应(response)作为参数返回。
start_reauests()方法的捷径
你可以不用实现start_requests()
方法来从URL连接中生成scrapy.Resquest
对象,而是仅仅定义一个叫做start_urls
的属性,即一个包括url连接的列表。这个列表将会被默认的start_requests()
方法调用来为你的爬虫创建初始的请求。两种方法都可取。
2、parse方法:
此方法来对每一个请求进行下载处理。response属性是TextResponse的一个实例,它拥有页面的内容并且有更深入的方法来处理它;
parse()方法常常用来解析response属性,将提取爬下来的数据作为字典类型或找到新的URL连接并建立新的请求
pipelines
当我们成功获取信息后,要进行信息的验证、储存等工作,这里以储存为例。
当Item在Spider中被收集之后,它将会被传递到Pipeline,一些组件会按照一定的顺序执行对Item的处理。
Pipeline经常进行一下一些操作:
1.清理HTML数据
2.验证爬取的数据(检查item包含某些字段)
3.查重(并丢弃)
4.将爬取结果保存到数据库中
首先在scrapytest/
目录下建立一个文件MyPipelines.py
MyPipelines.py代码如下
from scrapy.exceptions import DropItem import json class MyPipeline(object): def __init__(self): #打开文件 self.file = open('data.json', 'w', encoding='utf-8') #该方法用于处理数据 def process_item(self, item, spider): #读取item中的数据 line = json.dumps(dict(item), ensure_ascii=False) + "\n" #写入文件 self.file.write(line) #返回item return item #该方法在spider被开启时被调用。 def open_spider(self, spider): pass #该方法在spider被关闭时被调用。 def close_spider(self, spider): pass
要使用Pipeline,首先要注册Pipeline
找到settings.py文件,这个文件时爬虫的配置文件
在其中添加
ITEM_PIPELINES = { 'scrapytest.MyPipelines.MyPipeline': 1, }
上面的代码用于注册Pipeline,其中scrapytest.MyPipelines.MyPipeline
为你要注册的类,右侧的’1’为该Pipeline的优先级,范围1~1000,越小越先执行。
进行完以上操作,我们的一个最基本的爬取操作就完成了
这时我们再运行
scrapy crawl MySpider --nolog
就可以在项目根目录下发现data.json文件,里面存储着爬取的信息。
多pipelines(值越小优先级越高)
多pipelines,返回值会传递给下一个pipelines的process_item
PS:如果想要丢弃,不给后续pipeline使用:
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()
process_item(self, item, spider)
对于每个项目管道组件调用此方法。process_item() 必须返回一个带数据的dict,返回一个Item (或任何后代类)对象,返回一个Twisted Deferred或者raise DropItemexception。丢弃的项目不再由其他管道组件处理。
根据配置文件读取相关值,再进行pipeline处理
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: """ path = crawler.settings.get('XL_FILE_PATH') return cls(path) def process_item(self, item, spider): self.f.write(item['href'] + '\n') 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()
POST/请求头/Cookie
POST+请求头:
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, )
cookies:
# 手动: 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 # 自动: class ChoutiSpider(scrapy.Spider): name = 'chouti' allowed_domains = ['chouti.com'] start_urls = ['http://dig.chouti.com/', ] def start_requests(self): for url in self.start_urls: yield Request(url=url, callback=self.parse_index, meta={'cookiejar': True}) def parse_index(self, response): req = Request( url='http://dig.chouti.com/login', method='POST', headers={'Content-Type': 'application/x-www-form-urlencoded; charset=UTF-8'}, body='phone=8613121758648&password=woshiniba&oneMonth=1', callback=self.parse_check_login, meta={'cookiejar': True} ) yield req def parse_check_login(self, response): # print(response.text) yield Request( url='https://dig.chouti.com/link/vote?linksId=19440976', method='POST', callback=self.parse_show_result, meta={'cookiejar': True} ) def parse_show_result(self, response): print(response.text)
配置文件制定是否允许操作cookie:
# Disable cookies (enabled by default) # COOKIES_ENABLED = False
避免重复访问
scrapy默认使用 scrapy.dupefilter.RFPDupeFilter 进行去重,相关配置有:
DUPEFILTER_CLASS = 'scrapy.dupefilter.RFPDupeFilter' DUPEFILTER_DEBUG = False JOBDIR = "保存范文记录的日志路径,如:/root/" # 最终路径为 /root/requests.seen
自定义url去重操作
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)
为请求创建唯一标识:
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。
问题:dont_filter到低在哪里?
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
如何给爬虫中所有的请求都携带响应头?
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
1.配置:
DOWNLOADER_MIDDLEWARES = {'xianglong.middlewares.UserAgentDownloaderMiddleware': 543, }
2.编写类:
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 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
方案三:内置下载中间件
配置文件:
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'
下载中间件Downloader Middleware
下载器中间件是介于Scrapy 的 request/response
处理的钩子框架。 是用于全局修改 Scrapy request 和 response 的一个轻量、底层的系统。
-
激活下载器中间件
要激活下载器中间件组件,将其加入到 DOWNLOADER_MIDDLEWARES 设置中。该设置是一个字典(dict),键为中间件类的路径,值为其中间件的顺序(order)。DOWNLOADER_MIDDLEWARES = { 'myproject.middlewares.CustomDownloaderMiddleware': 543, }
关于如何分配中间件的顺序请查看
DOWNLOADER_MIDDLEWARES_BASE
设置,而后根据您想要放置中间件的位置选择一个值。由于每个中间件执行不同的动作,您的中间件可能会依赖于之前(或者之后)执行的中间件,因此顺序是很重要的。如果您想禁止内置的(在 DOWNLOADER_MIDDLEWARES_BASE 中设置并默认启用的)中间件,您必须在项目的 DOWNLOADER_MIDDLEWARES 设置中定义该中间件,并将其值赋为 None。例如,如果您想要关闭 user-agent 中间件:
DOWNLOADER_MIDDLEWARES = { 'myproject.middlewares.CustomDownloaderMiddleware': 543, 'scrapy.contrib.downloadermiddleware.useragent.UserAgentMiddleware': None, }
最后,请注意,有些中间件需要通过特定的设置来启用。更多内容请查看相关中间件文档。
-
编写您自己的下载器中间件
编写下载器中间件十分简单。每个中间件组件是一个定义了以下一个或多个方法的 Python 类:
class scrapy.contrib.downloadermiddleware.DownloaderMiddleware
参数:
* request (Request 对象) – 处理的 request
* spider (Spider 对象) – 该 request 对应的 spider
* process_request(request, spider)当每个 request 通过下载中间件时,该方法被调用。
process_request() 必须返回其中之一: 返回
None
、返回一个Response
对象、返回一个Request
对象或raise IgnoreRequest
。如果其返回
None
,Scrapy 将继续处理该 request,执行其他的中间件的相应方法,直到合适的下载器处理函数(download handler)被调用,该 request 被执行(其 response 被下载)。如果其返回
Response
对象,Scrapy 将不会调用 任何 其他的 process_request()或 process_exception()方法,或相应地下载函数; 其将返回该 response。已安装的中间件的 process_response()方法则会在每个 response 返回时被调用。如果其返回
Request
对象,Scrapy 则停止调用 process_request 方法并重新调度返回的 request。当新返回的 request 被执行后, 相应地中间件链将会根据下载的 response 被调用。如果其 抛出 一个
IgnoreRequest
异常,则安装的下载中间件的 process_exception() 方法会被调用。如果没有任何一个方法处理该异常, 则 request 的 errback(Request.errback)方法会被调用。如果没有代码处理抛出的异常, 则该异常被忽略且不记录(不同于其他异常那样)。参数:
* request (Request 对象) – 处理的 request * spider (Spider 对象) – 该 request 对应的 spider * process_response(request, response, spider)
process_response() 必须返回以下之一: 返回一个 Response 对象、返回一个 Request 对象或 raise 一个 IgnoreRequest 异常。
如果其返回一个
Response
(可以与传入的 response 相同,也可以是全新的对象) 该 response 会被在链中的其他中间件的 process_response()方法处理。如果其返回一个
Request
对象,则中间件链停止,返回的 request 会被重新调度下载。处理类似于 process_request()返回 request 所做的那样。如果其抛出一个
IgnoreRequest
异常,则调用 request 的 errback(Request.errback)。如果没有代码处理抛出的异常,则该异常被忽略且不记录(不同于其他异常那样)。参数:
* request (Request 对象) – response 所对应的 request * response (Response 对象) – 被处理的 response * spider (Spider 对象) – response 所对应的 spider * process_exception(request, exception, spider)
当下载处理器(download handler)或 process_request()(下载中间件)抛出异常(包括 IgnoreRequest 异常)时,Scrapy 调用 process_exception() 。
process_exception()应该返回以下之一: 返回 None、一个 Response 对象、或者一个 Request 对象。
如果其返回
None
,Scrapy 将会继续处理该异常,接着调用已安装的其他中间件的 process_exception()方法,直到所有中间件都被调用完毕,则调用默认的异常处理。如果其返回一个
Response
对象,则已安装的中间件链的 process_response()方法被调用。Scrapy 将不会调用任何其他中间件的 process_exception() 方法。如果其返回一个
Request
对象, 则返回的 request 将会被重新调用下载。这将停止中间件的 process_exception()方法执行,就如返回一个 response 的那样。参数:
* request (是 Request 对象) – 产生异常的 request * exception (Exception 对象) – 抛出的异常 * spider (Spider 对象) – request 对应的 spider
问题:scrapy中如何添加代理?
方式一:内置添加代理功能
# -*- coding: utf-8 -*- import os import scrapy from scrapy.http import Request class ChoutiSpider(scrapy.Spider): name = 'chouti' allowed_domains = ['chouti.com'] start_urls = ['https://dig.chouti.com/'] def start_requests(self): os.environ['HTTP_PROXY'] = "http://192.168.11.11" for url in self.start_urls: yield Request(url=url, callback=self.parse) def parse(self, response): print(response)
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'])
此外需要添加配置文件
DOWNLOADER_MIDDLEWARES = { # 'xiaohan.middlewares.MyProxyDownloaderMiddleware': 543, }
问题:scrapy中如何处理https
# 配置文件
DOWNLOADER_HTTPCLIENTFACTORY = "scrapy.core.downloader.webclient.ScrapyHTTPClientFactory" DOWNLOADER_CLIENTCONTEXTFACTORY = "xiaohan.middlewares.MySSLFactory"
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)) )
下载中间件的作用:在每次下载前和下载后对请求和响应定制功能,例如:USER_AGENT/Cookie/代理
自定义下载器中间件需要以下几个步骤
1. 重写一个类
class CustomMiddleware(object):
2. def process_request(self, request, spider):
必须返回一个值None, Response, Request,IgnoreRequest
建议返回response
return response
3. def process_response(self, request, response, spider):
必须返回一值 Response, Request, IgnoreRequest
建议返回response
return response
4. def process_exception(self, request, exception, spider):
必须返回一个值 Response, Request, None
建议不要写这个函数, 或者直接pass
5. 最后在settings.py文件的DOWNLOADER_MIDDLEWARES = {
'项目名称.middlewares.CustomMiddleware': 1
}
爬虫中间件
配置文件:
SPIDER_MIDDLEWARES = { 'xiaohan.middlewares.XiaohanSpiderMiddleware': 543, }
编写爬虫中间件类:
class XiaohanSpiderMiddleware(object): def __init__(self): pass @classmethod def from_crawler(cls, crawler): 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): print('process_spider_input', response) return None def process_spider_output(self, response, result, spider): print('process_spider_output', response) for i in result: yield i def process_spider_exception(self, response, exception, spider): 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): print('process_start_requests') for r in start_requests: yield r
扩展:信号
单纯扩展:
extends.py
class MyExtension(object): def __init__(self): pass @classmethod def from_crawler(cls, crawler): obj = cls() return obj
配置:
EXTENSIONS = {'xiaohan.extends.MyExtension':500,}
扩展+信号:
extends.py
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
配置:
EXTENSIONS = {'xiaohan.extends.MyExtension':500,}
其他:配置文件
# -*- 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, # }
自定义命令
- 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
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()