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
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、创建项目
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)
scrapy genspider [-t template] <name> <domain>
- 穿件爬虫应用
如:scrapy gensipider -t basic oldboy oldboy.com
scrapy gensipider -t xmlfeed autohome autohome.com.cn
查看所有命令:scrapy gensipider -l
查看模板命令:scrapy gensipider -d 模板名称
scrapy list
- 展示爬虫应用列表
scrapy crawl 爬虫应用名称
- 运行单独爬虫应用
创建实例:
创建项目
shuais-MacBook-Pro:~ dandyzhang$ scrapy startproject scrapy_test
New Scrapy project 'scrapy_test', using template directory '/Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/scrapy/templates/project', created in:
/Users/dandyzhang/scrapy_test
You can start your first spider with:
cd scrapy_test
scrapy genspider example example.com
进入创建的项目
shuais-MacBook-Pro:~ dandyzhang$ cd scrapy_test/
创建爬虫应用1
shuais-MacBook-Pro:scrapy_test dandyzhang$ scrapy genspider chouti chouti.com
Created spider 'chouti' using template 'basic' in module:
scrapy_test.spiders.chouti
创建爬虫应用2
shuais-MacBook-Pro:scrapy_test dandyzhang$ scrapy genspider cnblogs cnblogs.com
Created spider 'cnblogs' using template 'basic' in module:
scrapy_test.spiders.cnblogs
2、项目结构以及爬虫应用简介
上面的实例,创建好了一个完整的项目:
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
此时,发现之前根据命令创建了2个应用都存储在spiders文件夹内,现在以其中的chouti为例,来撰写第一个爬虫
import scrapy
class ChoutiSpider(scrapy.Spider):
name = 'chouti' # 外部scrapy调用的爬虫应用名称
allowed_domains = ['chouti.com'] # 允许的域名
start_urls = ['http://dig.chouti.com/'] # 起始url
def parse(self, response): # 访问起始url并获取结果后的回调函数
print(response.text) # response就是返回结果
查看结果:
如果是window用户可能会遇到编码问题:
import sys,os
sys.stdout=io.TextIOWrapper(sys.stdout.buffer,encoding='gb18030')
3、小试牛刀
如上,需要在抽屉网中抓去热榜的所有标题,图中的框已经标好,从content-list入手,抓取每一个item中class为part2的share-title
class ChoutiSpider(scrapy.Spider):
name = 'chouti'
allowed_domains = ['chouti.com']
start_urls = ['http://dig.chouti.com/']
def parse(self, response):
"""
1.获取想要的内容
2.如果分页,继续下载内容
:param response:
:return:
"""
# 获取当前页的内容
item_list = Selector(response=response).xpath('//div[@id="content-list"]/div[@class="item"]')
# /子标签
# //起始位置时,是在全局进行查找;非起始位置是在当前标签的子子孙孙内部找
# ./当前对象下面找
# 获取index为0的对象中的第一个满足条件的文本
# obj = item_list[0].xpath('./div[@class="news-content"]//div[@class="part2"]/@share-title').extract_first()
obj_list = item_list.xpath('./div[@class="news-content"]//div[@class="part2"]/@share-title').extract()
print(obj_list) # 获取的结果是列表
如果抓取的是标签的内容而不是属性的话:
obj = item_list[0].xpath('./div[@class="news-content"]//div[@class="show-content"]/text()').extract()
执行命令:
shuais-MacBook-Pro:scrapy_test dandyzhang$ scrapy crawl chouti --nolog
结果:
此时,如果分页内的也需要抓取呢?
首先,先获取以下分页内部的url:
import scrapy
from scrapy.selector import Selector, HtmlXPathSelector
from scrapy.http import Request
class ChoutiSpider(scrapy.Spider):
name = 'chouti'
allowed_domains = ['chouti.com']
start_urls = ['http://dig.chouti.com/']
def parse(self, response):
"""
1.获取想要的内容
2.如果分页,继续下载内容
:param response:
:return:
"""
url_list = Selector(response=response).xpath('//div[@id="dig_lcpage"]//a/@href').extract()
print(url_list)
运行结果:
shuais-MacBook-Pro:scrapy_test dandyzhang$ scrapy crawl chouti --nolog
['/all/hot/recent/2', '/all/hot/recent/3', '/all/hot/recent/4', '/all/hot/recent/5', '/all/hot/recent/6', '/all/hot/recent/7', '/all/hot/recent/8', '/all/hot/recent/9', '/all/hot/recent/10', '/all/hot/recent/2']
此时需要先拼接url,然后抓取数据:
# -*- coding: utf-8 -*-
import scrapy
from scrapy.selector import Selector, HtmlXPathSelector
from scrapy.http import Request # 这里导入了一个Request,用来迭代
class ChoutiSpider(scrapy.Spider):
name = 'chouti'
allowed_domains = ['chouti.com']
start_urls = ['http://dig.chouti.com/']
def parse(self, response):
"""
1.获取想要的内容
2.如果分页,继续下载内容
:param response:
:return:
"""
item_list = Selector(response=response).xpath('//div[@id="content-list"]/div[@class="item"]')
obj_list = item_list.xpath('./div[@class="news-content"]//div[@class="part2"]/@share-title').extract()
print(obj_list)
url_list = Selector(response=response).xpath('//div[@id="dig_lcpage"]//a/@href').extract()
for url in url_list:
url = 'http://dig.chouti.com' + url
yield Request(url=url) # 迭代处理
这里可以在settings配置文件内设置下钻的深度:
DEPTH_LIMIT = 2
可以发现产生来了多个列表文件:
a、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
b、HtmlXpathSelector用于结构化HTML代码并提供选择器功能
4、选择器
from scrapy.selector import Selector, HtmlXPathSelector # 一个是新版本,一个是旧版本,后面会被取消
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) # 对象
# print(hxs)
# hxs = Selector(response=response).xpath('//a') # 取全局内所有a标签
# print(hxs)
# hxs = Selector(response=response).xpath('//a[2]') # 取全局内index为2的a标签
# print(hxs)
# hxs = Selector(response=response).xpath('//a[@id]') # 取全局所有有id属性的a标签
# print(hxs)
# hxs = Selector(response=response).xpath('//a[@id="i1"]') # 取全局所有id="i1"的a标签
# print(hxs)
# hxs = Selector(response=response).xpath('//a[@href="link.html"][@id="i1"]') # 取全局所有href为link.html并且id为i1的a标签
# print(hxs)
# hxs = Selector(response=response).xpath('//a[contains(@href, "link")]') # 取全局所有href有link字符串的a标签
# print(hxs)
# hxs = Selector(response=response).xpath('//a[starts-with(@href, "link")]') # 取全局所有href以link字符串开头的a标签
# print(hxs)
# hxs = Selector(response=response).xpath('//a[re:test(@id, "i\d+")]') # 正则 取全局所有a标签,id属性是i+数字的
# print(hxs)
# hxs = Selector(response=response).xpath('//a[re:test(@id, "i\d+")]/text()').extract() # 正则 取全局所有a标签,id属性是i+数字的 内部的值
# print(hxs)
# hxs = Selector(response=response).xpath('//a[re:test(@id, "i\d+")]/@href').extract() # 正则 取全局所有a标签,id属性是i+数字的 href属性值
# 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)
抽屉点赞:
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 = {} # 发送过请求的集合
def start_requests(self): # 继承Spider,Spider内部先执行的是start_requests方法
url = 'http://dig.chouti.com/'
# return [Request(url=url, callback=self.login)]
yield Request(url=url, callback=self.login) # 爬取网页,指定回调函数;其实Request默认的callback是parse,
# 这也解释了为什么新建的爬虫应用内部都是def parse(self, response):方法。可以像这样重写start_requests方法,指定callback
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 # 指定回调函数
)
yield req
def check_login(self, response):
req = Request(
url='http://dig.chouti.com/',
method='GET',
callback=self.show, # 定义callback
cookies=self.cookie_dict,
dont_filter=True # 不被去重过滤
)
yield req
def show(self, response):
# print(response)
hxs = HtmlXPathSelector(response) # 实例化标签对象
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() # 获取id
yield Request( # 点赞
url='http://dig.chouti.com/link/vote?linksId=%s' %(link_id,),
method='POST',
cookies=self.cookie_dict,
callback=self.do_favor
)
# 获取分页的网址
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: # 加密key请求在已请求的列表中,则pass
pass
else: # 如果没有发送请求,继续发送
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) # 打印以下点赞之后的返回值
处理Cookie:
import scrapy
from scrapy.http.response.html import HtmlResponse
from scrapy.http import Request
from scrapy.http.cookies import CookieJar
class ChoutiSpider(scrapy.Spider):
name = "chouti"
allowed_domains = ["chouti.com"]
start_urls = (
'http://www.chouti.com/',
)
def start_requests(self):
url = 'http://dig.chouti.com/'
yield Request(url=url, callback=self.login, meta={'cookiejar': True}) # 如此设置cookiejar,可以自动获取cookie
def login(self, response):
print(response.headers.getlist('Set-Cookie'))
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.check_login,
meta={'cookiejar': True}
)
yield req
def check_login(self, response):
print(response.text)
注意:settings.py中设置DEPTH_LIMIT = 1来指定“递归”的层数。
这里对于上面的代码简单解释下,基础流程:
首先最初创建的爬虫应用的源码:继承了Spider类,该类内部有一个start_requests方法,这是爬虫执行的起始函数,如果start_urls不为空,爬取此url。即上图的yield Request(url, dont_filter=True)、这也可以解释为什么继续爬取分页的url时,写的是yield Request(url)。此时大家也许不明白,即start_urls不为空,为什么会执行parse函数呢?其实在开始执行的yield Request中有一个默认参数是callback=parse,所以初始化的爬虫应用的流程就一目了然了。
现在解释下点赞的爬虫,前面提到继承了Spider类,第一个执行的是start_requests,此时既然继承了父类Spider,就可以对此类进行重写,已经知道了其实位置是start_requests,毫无疑问重写此方法,内部指定url(外部的start_urls删除),执行爬虫则调用Request方法,指定callback函数,这样根据callback也就形成了一个串行爬虫链。另外要提到的一点yield都知道是一个生成器,在Scrapy内部,spider内部调度yield Request只是其中的一部分,用来爬虫。另外一部分也是通过yield调用来做持久化的,即对于爬取的数据的处理跟保存。下面会讲到这部分,这里先提一下。
5、格式化处理
之前的实例只是一些简单的处理,所以在parse方法中直接处理。如果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。
回到最原始的parse代码,抓取以下热榜标题跟链接
chouti.py
import scrapy
from scrapy.selector import HtmlXPathSelector, Selector
from ..items import ScrapyTestItem
class ChoutiSpider(scrapy.Spider):
name = 'chouti'
allowed_domains = ['chouti.com']
start_urls = ['http://dig.chouti.com/']
def parse(self, response):
item_list = Selector(response=response).xpath('//div[@id="content-list"]/div[@class="item"]')
for item in item_list:
t = item.xpath('./div[@class="news-content"]//div[@class="part1"]/a/text()').extract()
h = item.xpath('./div[@class="news-content"]//div[@class="part1"]/a/@href').extract()
item_obj = ScrapyTestItem(title=t, href=h) # 调用Item
yield item_obj # 这里指向了另一个调度器,持久化调度器
items.py
import scrapy
class ScrapyTestItem(scrapy.Item):
# define the fields for your item here like: 定义要抓取保存的字段
title = scrapy.Field()
href = scrapy.Field()
pipelines.py
class ScrapyTestPipeline(object):
def process_item(self, item, spider):
print(item, spider)
return item
这里需要注意的是跟Django一样,需要注册以下:
在settings文件里面找到下面这段话,去掉注释,其中300代表优先级,稍后进行这个数字的测试。
ITEM_PIPELINES = {
'scrapy_test.pipelines.ScrapyTestPipeline': 300,
}
此时执行爬虫:
语法没写好,抓到2个href了,不要在意这些细节。
此时,了解了yield的另一个功能,当yield Item_obj是就会调度pipelines进行持久化,当然上面我们只是打印了以下结果,可以看到item对应的是字段,spider是爬虫应用函数方法。
所以对于不同的要求可以直接在pipelines里面写到:
class ScrapyTestPipeline1(object):
def process_item(self, item, spider):
print('step 1 输出到屏幕')
return item
class ScrapyTestPipeline2(object):
def process_item(self, item, spider):
print('step 2 保存到文件')
return item
class ScrapyTestPipeline3(object):
def process_item(self, item, spider):
print('step 3 保存到数据库')
return item
注册以下:
ITEM_PIPELINES = {
'scrapy_test.pipelines.ScrapyTestPipeline1': 100,
'scrapy_test.pipelines.ScrapyTestPipeline2': 200,
'scrapy_test.pipelines.ScrapyTestPipeline3': 300,
}
执行结果、注意顺序
假设step3的类没有注册,就只会执行step1 & step2。
那么、如果想在执行到某一个pipeline类终止怎么办?
from scrapy.exceptions import DropItem # 导入DropItem
class ScrapyTestPipeline1(object):
def process_item(self, item, spider):
print('step 1 输出到屏幕')
raise DropItem()
class ScrapyTestPipeline2(object):
def process_item(self, item, spider):
print('step 2 保存到文件')
return item
class ScrapyTestPipeline3(object):
def process_item(self, item, spider):
print('step 3 保存到数据库')
return item
那spider参数是干嘛用的呢?
假设,抓取的name是chouti的时候,不让其继续执行后续的:
from scrapy.exceptions import DropItem
class ScrapyTestPipeline1(object):
def process_item(self, item, spider):
print('step 1 输出到屏幕')
if spider.name == 'chouti':
raise DropItem()
return item
class ScrapyTestPipeline2(object):
def process_item(self, item, spider):
print('step 2 保存到文件')
return item
class ScrapyTestPipeline3(object):
def process_item(self, item, spider):
print('step 3 保存到数据库')
return item
pipelines更多:
假设需要将数据写入文件,首先想到的方法一定是
class ScrapyTestPipeline(object):
def process_item(self, item, spider):
with open('***', 'a+') as f:
f.write('***')
print('step 2 保存到文件')
return item
但是这样会在一次爬虫中频繁的打开文件,浪费IO
此时引入另外的方法
from scrapy.exceptions import DropItem
class CustomPipeline(object):
def __init__(self,v): # v就是类方法返回的参数val
self.value = v
print(self.value)
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
print('****操作****')
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.get('MYPATH') # 类方法获取配置文件参数
print(val)
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')
此时在setting中配置以下文件地址就可以了:
MYPATH = '***path***'
settings参数必须全部大写,小写测试失败,未抓取到。
执行结果
所以以后,可以在from_crawler里面通过参数定义文件名,setting文件设置文件路径,然后打开文件,中间对文件句柄进行追加,一次打开,一次关闭,避免重复操作。
6、中间件
自动化里面Django blog其实已经讲过了中间件的一个大致流程,其实在scrapy中中间件的核心依然是同样的。
上图是Django中中间件的一个基本概念图,而在scrapy中则是:
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(默认有start_urls时,parse时默认的callback函数)
: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、丢给调度器分配下载或者是解析文本
"""
return start_requests
首先爬虫引擎启动全局,到spider的start_urls抓取数据返回start_request,放到任务调度器里面,下载器去任务调度器抓取任务执行。
下载器中间件
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
7、自定制命令
a、在spiders同级创建任意目录,如:commands
b、在其中创建 crawlall.py 文件 (此处文件名就是自定义的命令)-- 如果创建多个文件,其实是相当于创建了多个命令
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() # 去spiders文件夹下获取所有的爬虫文件
for name in spider_list:
self.crawler_process.crawl(name, **opts.__dict__) # 为所有的爬虫创建任务
self.crawler_process.start() # 并发的开始执行
c、在settings.py 中添加配置 COMMANDS_MODULE = '项目名称.目录名称'
d、在项目目录执行命令:scrapy crawlall
PS:scrapy的源码,建议从run开始着手看。
单个爬虫:
import sys
from scrapy.cmdline import execute
if __name__ == '__main__':
execute(["scrapy","github","--nolog"])
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(跟Django的信号很相似)
from scrapy import signals
class MyExtension(object):
def __init__(self, value):
self.value = value
@classmethod
def from_crawler(cls, crawler):
val = crawler.settings.get('MMMM')
ext = cls(val)
crawler.signals.connect(ext.openn, signal=signals.spider_opened)
crawler.signals.connect(ext.closee, signal=signals.spider_closed)
return ext
def openn(self, spider):
print('open')
def closee(self, spider):
print('close')
"""
Scrapy signals
These signals are documented in docs/topics/signals.rst. Please don't add new
signals here without documenting them there.
"""
engine_started = object()
engine_stopped = object()
spider_opened = object()
spider_idle = object()
spider_closed = object()
spider_error = object()
request_scheduled = object()
request_dropped = object()
response_received = object()
response_downloaded = object()
item_scraped = object()
item_dropped = object()
# for backwards compatibility
stats_spider_opened = spider_opened
stats_spider_closing = spider_closed
stats_spider_closed = spider_closed
item_passed = item_scraped
request_received = request_scheduled
跟pipelines一样,需要注册类在settings文件里。
9、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
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、settings其他设置
# -*- 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 = 'scrapy_test'
# 2. 爬虫应用路径
SPIDER_MODULES = ['scrapy_test.spiders']
NEWSPIDER_MODULE = 'scrapy_test.spiders'
# Crawl responsibly by identifying yourself (and your website) on the user-agent
# 3. 客户端 user-agent请求头 通用配置,也可以在Request内部配置
# USER_AGENT = 'scrapy_test (+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(反爬虫,所有的爬虫都是延迟2秒)
# 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 = {
# 'scrapy_test.pipelines.JsonPipeline': 700,
# 'scrapy_test.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 = {
# # 'scrapy_test.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 queue
# SCHEDULER = 'scrapy.core.scheduler.Scheduler'
# from scrapy.core.scheduler import Scheduler
# 16. 访问URL去重
# DUPEFILTER_CLASS = 'scrapy_test.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,key不可以修改
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 = "scrapy_test.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 = {
# 'scrapy_test.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 = {
# 'scrapy_test.middlewares.DownMiddleware1': 100,
# 'scrapy_test.middlewares.DownMiddleware2': 500,
# }
11、模拟scrapy框架
#!/usr/bin/env python
# -*- coding:utf-8 -*-
from twisted.web.client import getPage, defer
from twisted.internet import reactor
import queue
class Response(object):
def __init__(self, body, request):
self.body = body
self.request = request
self.url = request.url
@property
def text(self):
return self.body.decode('utf-8')
class Request(object):
def __init__(self, url, callback=None):
self.url = url
self.callback = callback
class Scheduler(object):
def __init__(self, engine):
self.q = queue.Queue()
self.engine = engine
def enqueue_request(self, request):
self.q.put(request)
def next_request(self):
try:
req = self.q.get(block=False)
except Exception as e:
req = None
return req
def size(self):
return self.q.qsize()
class ExecutionEngine(object):
def __init__(self):
self._closewait = None
self.running = True
self.start_requests = None
self.scheduler = Scheduler(self)
self.inprogress = set()
def check_empty(self, response):
if not self.running:
self._closewait.callback('......')
def _next_request(self):
while self.start_requests:
try:
request = next(self.start_requests)
except StopIteration:
self.start_requests = None
else:
self.scheduler.enqueue_request(request)
while len(self.inprogress) < 5 and self.scheduler.size() > 0: # 最大并发数为5
request = self.scheduler.next_request()
if not request:
break
self.inprogress.add(request)
d = getPage(bytes(request.url, encoding='utf-8'))
d.addBoth(self._handle_downloader_output, request)
d.addBoth(lambda x, req: self.inprogress.remove(req), request)
d.addBoth(lambda x: self._next_request())
if len(self.inprogress) == 0 and self.scheduler.size() == 0:
self._closewait.callback(None)
def _handle_downloader_output(self, body, request):
"""
获取内容,执行回调函数,并且把回调函数中的返回值获取,并添加到队列中
:param response:
:param request:
:return:
"""
import types
response = Response(body, request)
func = request.callback or self.spider.parse
gen = func(response)
if isinstance(gen, types.GeneratorType):
for req in gen:
self.scheduler.enqueue_request(req)
@defer.inlineCallbacks
def start(self):
self._closewait = defer.Deferred()
yield self._closewait
def open_spider(self, spider, start_requests):
self.start_requests = start_requests
self.spider = spider
reactor.callLater(0, self._next_request)
class Crawler(object):
def __init__(self, spidercls):
self.spidercls = spidercls
self.spider = None
self.engine = None
@defer.inlineCallbacks
def crawl(self):
self.engine = ExecutionEngine()
self.spider = self.spidercls()
start_requests = iter(self.spider.start_requests())
start_requests = iter(start_requests)
self.engine.open_spider(self.spider, start_requests)
yield self.engine.start()
class CrawlerProcess(object):
def __init__(self):
self._active = set()
self.crawlers = set()
def crawl(self, spidercls, *args, **kwargs):
crawler = Crawler(spidercls)
self.crawlers.add(crawler)
d = crawler.crawl(*args, **kwargs)
self._active.add(d)
return d
def start(self):
dl = defer.DeferredList(self._active)
dl.addBoth(self._stop_reactor)
reactor.run()
def _stop_reactor(self, _=None):
reactor.stop()
class Spider(object):
def start_requests(self):
for url in self.start_urls:
yield Request(url)
class ChoutiSpider(Spider):
name = "chouti"
start_urls = [
'http://dig.chouti.com/',
]
def parse(self, response):
print(response.text)
class CnblogsSpider(Spider):
name = "cnblogs"
start_urls = [
'http://www.cnblogs.com/',
]
def parse(self, response):
print(response.text)
if __name__ == '__main__':
spider_cls_list = [ChoutiSpider, CnblogsSpider]
crawler_process = CrawlerProcess()
for spider_cls in spider_cls_list:
crawler_process.crawl(spider_cls)
crawler_process.start()
参见文档:http://www.cnblogs.com/wupeiqi/articles/6229292.html
来源:oschina
链接:https://my.oschina.net/u/4323462/blog/3887161