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scrapy
作为一款强大的爬虫框架,当然要好好学习一番,本文便是本人学习和使用scrapy
过后的一个总结,内容比较基础,算是入门笔记吧,主要讲述scrapy
的基本概念和使用方法。
scrapy framework
首先附上scrapy
经典图如下:
scrapy
框架包含以下几个部分
-
Scrapy Engine
引擎 -
Spiders
爬虫 -
Scheduler
调度器 -
Downloader
下载器 -
Item Pipeline
项目管道 -
Downloader Middlewares
下载器中间件 -
Spider Middlewares
爬虫中间件
spider process
其爬取过程简述如下:
- 引擎从爬虫获取首个待爬取的链接
url
,并传递给调度器 - 调度器将链接存入队列
- 引擎向调度器请求要爬取的链接,并将请求得到的链接经下载器中间件传递给下载器
- 下载器从网上下载网页,下载后的网页经下载器中间件传递给引擎
- 引擎将网页经爬虫中间件传递给爬虫
- 爬虫对网页进行解析,将得到的
Items
和新的链接经爬虫中间件交给引擎 - 引擎将从爬虫得到的
Items
交给项目管道,将新的链接请求requests
交给调度器 - 此后循环2~7步,直到没有待爬取的链接为止
需要说明的是,项目管道(Item Pipeline
)主要完成数据清洗,验证,持久化存储等工作;下载器中间件(Downloader Middlewares
)作为下载器和引擎之间的的钩子(hook
),用于监听或修改下载请求或已下载的网页,比如修改请求包的头部信息等;爬虫中间件(Spider Middlewares
)作为爬虫和引擎之间的钩子(hook
),用于处理爬虫的输入输出,即网页response
和爬虫解析网页后得到的Items
和requests
。
Items
至于什么是Items
,个人认为就是经爬虫解析后得到的一个数据单元,包含一组数据,比如爬取的是某网站的商品信息,那么每爬取一个网页可能会得到多组商品信息,每组信息包含商品名称,价格,生产日期,商品样式等,那我们便可以定义一组Item
from scrapy.item import Item
from scrapy.item import Field
class GoodsItem(Item):
name = Field()
price = Field()
date = Field()
types = Field()
Field()
实质就是一个字典Dict()
类型的扩展,如上代码所示,一组Item
对应一个商品信息,单个网页可能包含一个或多个商品,所有Item
信息都需要在Spider
中赋值,然后经引擎交给Item Pipeline
。具体实现在后续博文的实例中会有体现,本文旨在简单记述scrapy
的基本概念和使用方法。
Install
with pip
pip install scrapy
or conda
conda install -c conda-forge scrapy
基本指令如下:
D:\WorkSpace>scrapy --help
Scrapy 1.5.0 - no active project
Usage:
scrapy <command> [options] [args]
Available commands:
bench Run quick benchmark test
fetch Fetch a URL using the Scrapy downloader
genspider Generate new spider using pre-defined templates
runspider Run a self-contained spider (without creating a project)
settings Get settings values
shell Interactive scraping console
startproject Create new project
version Print Scrapy version
view Open URL in browser, as seen by Scrapy
[ more ] More commands available when run from project directory
Use "scrapy <command> -h" to see more info about a command
如果需要使用虚拟环境,需要安装virtualenv
pip install virtualenv
scrapy startproject
scrapy startproject <project-name> [project-dir]
使用该指令可以生成一个新的scrapy
项目,以demo
为例
$ scrapy startproject demo
...
You can start your first spider with:
cd demo
scrapy genspider example example.com
$ cd demo
$ tree
.
├── demo
│ ├── __init__.py
│ ├── items.py
│ ├── middlewares.py
│ ├── pipelines.py
│ ├── __pycache__
│ ├── settings.py
│ └── spiders
│ ├── __init__.py
│ └── __pycache__
└── scrapy.cfg
4 directories, 7 files
可以看到startproject
自动生成了一些文件夹和文件,其中:
-
scrapy.cfg
: 项目配置文件,一般不用修改 -
items.py
: 定义items
的文件,例如上述的GoodsItem
-
middlewares.py
: 中间件代码,默认包含下载器中间件和爬虫中间件 -
pipelines.py
: 项目管道,用于处理spider
返回的items
,包括清洗,验证,持久化等 -
settings.py
: 全局配置文件,包含各类全局变量 -
spiders
: 该文件夹用于存储所有的爬虫文件,注意一个项目可以包含多个爬虫 -
__init__.py
: 该文件指示当前文件夹属于一个python
模块 -
__pycache__
: 存储解释器生成的.pyc
文件(一种跨平台的字节码byte code
),在python2
中该类文件与.py
保存在相同文件夹
scrapy genspider
项目生成以后,可以使用scrapy genspider
指令自动生成一个爬虫文件,比如,如果要爬取花瓣网首页,执行以下指令:
$ cd demo
$ scrapy genspider huaban www.huaban.com
默认生成的爬虫文件huaban.py
如下:
# -*- coding: utf-8 -*-
import scrapy
class HuabanSpider(scrapy.Spider):
name = 'huaban'
allowed_domains = ['www.huaban.com']
start_urls = ['http://www.huaban.com/']
def parse(self, response):
pass
- 爬虫类继承于
scrapy.Spider
-
name
是必须存在的参数,用以标识该爬虫 -
allowed_domains
指代允许爬虫爬取的域名,指定域名之外的链接将被丢弃 -
start_urls
存储爬虫的起始链接,该参数是列表类型,所以可以同时存储多个链接
如果要自定义起始链接,也可以重写scrapy.Spider
类的start_requests
函数,此处不予细讲。
parse
函数是一个默认的回调函数,当下载器下载网页后,会调用该函数进行解析,response
就是请求包的响应数据。至于网页内容的解析方法,scrapy
内置了几种选择器(Selector
),包括xpath
选择器、CSS
选择器和正则匹配。下面是一些选择器的使用示例,方便大家更加直观的了解选择器的用法。
# xpath selector
response.xpath('//a')
response.xpath('./img').extract()
response.xpath('//*[@id="huaban"]').extract_first()
repsonse.xpath('//*[@id="Profile"]/div[1]/a[2]/text()').extract_first()
# css selector
response.css('a').extract()
response.css('#Profile > div.profile-basic').extract_first()
response.css('a[href="test.html"]::text').extract_first()
# re selector
response.xpath('.').re('id:\s*(\d+)')
response.xpath('//a/text()').re_first('username: \s(.*)')
需要说明的是,response
不能直接调用re
,re_first
.
scrapy crawl
假设爬虫编写完了,那就可以使用scrapy crawl
指令开始执行爬取任务了。
当进入一个创建好的scrapy
项目目录时,使用scrapy -h
可以获得相比未创建之前更多的帮助信息,其中就包括用于启动爬虫任务的scrapy crawl
$ scrapy -h
Scrapy 1.5.0 - project: huaban
Usage:
scrapy <command> [options] [args]
Available commands:
bench Run quick benchmark test
check Check spider contracts
crawl Run a spider
edit Edit spider
fetch Fetch a URL using the Scrapy downloader
genspider Generate new spider using pre-defined templates
list List available spiders
parse Parse URL (using its spider) and print the results
runspider Run a self-contained spider (without creating a project)
settings Get settings values
shell Interactive scraping console
startproject Create new project
version Print Scrapy version
view Open URL in browser, as seen by Scrapy
Use "scrapy <command> -h" to see more info about a command
$ scrapy crawl -h
Usage
=====
scrapy crawl [options] <spider>
Run a spider
Options
=======
--help, -h show this help message and exit
-a NAME=VALUE set spider argument (may be repeated)
--output=FILE, -o FILE dump scraped items into FILE (use - for stdout)
--output-format=FORMAT, -t FORMAT
format to use for dumping items with -o
Global Options
--------------
--logfile=FILE log file. if omitted stderr will be used
--loglevel=LEVEL, -L LEVEL
log level (default: DEBUG)
--nolog disable logging completely
--profile=FILE write python cProfile stats to FILE
--pidfile=FILE write process ID to FILE
--set=NAME=VALUE, -s NAME=VALUE
set/override setting (may be repeated)
--pdb enable pdb on failure
从scrapy crawl
的帮助信息可以看出,该指令包含很多可选参数,但必选参数只有一个,就是spider
,即要执行的爬虫名称,对应每个爬虫的名称(name
)。
scrapy crawl huaban
至此,一个scrapy
爬虫任务的创建和执行过程就介绍完了,至于实例,后续博客会陆续介绍。
scrapy shell
最后简要说明一下指令scrapy shell
,这是一个交互式的shell
,类似于命令行形式的python
,当我们刚开始学习scrapy
或者刚开始爬虫某个陌生的站点时,可以使用它熟悉各种函数操作或者选择器的使用,用它来不断试错纠错,熟练掌握scrapy
各种用法。
$ scrapy shell www.huaban.com
2018-05-29 23:58:49 [scrapy.utils.log] INFO: Scrapy 1.5.0 started (bot: scrapybot)
2018-05-29 23:58:49 [scrapy.utils.log] INFO: Versions: lxml 4.2.1.0, libxml2 2.9.5, cssselect 1.0.3, parsel 1.4.0, w3lib 1.19.0, Twisted 17.9.0, Python 3.6.3 (v3.6.3:2c5fed8, Oct 3
2017, 17:26:49) [MSC v.1900 32 bit (Intel)], pyOpenSSL 17.5.0 (OpenSSL 1.1.0h 27 Mar 2018), cryptography 2.2.2, Platform Windows-10-10.0.17134-SP0
2018-05-29 23:58:49 [scrapy.crawler] INFO: Overridden settings: {'DUPEFILTER_CLASS': 'scrapy.dupefilters.BaseDupeFilter', 'LOGSTATS_INTERVAL': 0}
2018-05-29 23:58:49 [scrapy.middleware] INFO: Enabled extensions:
['scrapy.extensions.corestats.CoreStats',
'scrapy.extensions.telnet.TelnetConsole']
2018-05-29 23:58:50 [scrapy.middleware] INFO: Enabled downloader middlewares:
['scrapy.downloadermiddlewares.httpauth.HttpAuthMiddleware',
'scrapy.downloadermiddlewares.downloadtimeout.DownloadTimeoutMiddleware',
'scrapy.downloadermiddlewares.defaultheaders.DefaultHeadersMiddleware',
'scrapy.downloadermiddlewares.useragent.UserAgentMiddleware',
'scrapy.downloadermiddlewares.retry.RetryMiddleware',
'scrapy.downloadermiddlewares.redirect.MetaRefreshMiddleware',
'scrapy.downloadermiddlewares.httpcompression.HttpCompressionMiddleware',
'scrapy.downloadermiddlewares.redirect.RedirectMiddleware',
'scrapy.downloadermiddlewares.cookies.CookiesMiddleware',
'scrapy.downloadermiddlewares.httpproxy.HttpProxyMiddleware',
'scrapy.downloadermiddlewares.stats.DownloaderStats']
2018-05-29 23:58:50 [scrapy.middleware] INFO: Enabled spider middlewares:
['scrapy.spidermiddlewares.httperror.HttpErrorMiddleware',
'scrapy.spidermiddlewares.offsite.OffsiteMiddleware',
'scrapy.spidermiddlewares.referer.RefererMiddleware',
'scrapy.spidermiddlewares.urllength.UrlLengthMiddleware',
'scrapy.spidermiddlewares.depth.DepthMiddleware']
2018-05-29 23:58:50 [scrapy.middleware] INFO: Enabled item pipelines:
[]
2018-05-29 23:58:50 [scrapy.extensions.telnet] DEBUG: Telnet console listening on 127.0.0.1:6023
2018-05-29 23:58:50 [scrapy.core.engine] INFO: Spider opened
2018-05-29 23:58:50 [scrapy.downloadermiddlewares.redirect] DEBUG: Redirecting (301) to <GET http://huaban.com/> from <GET http://www.huaban.com>
2018-05-29 23:58:50 [scrapy.core.engine] DEBUG: Crawled (200) <GET http://huaban.com/> (referer: None)
[s] Available Scrapy objects:
[s] scrapy scrapy module (contains scrapy.Request, scrapy.Selector, etc)
[s] crawler <scrapy.crawler.Crawler object at 0x03385CB0>
[s] item {}
[s] request <GET http://www.huaban.com>
[s] response <200 http://huaban.com/>
[s] settings <scrapy.settings.Settings object at 0x04CC4D10>
[s] spider <DefaultSpider 'default' at 0x4fa6bf0>
[s] Useful shortcuts:
[s] fetch(url[, redirect=True]) Fetch URL and update local objects (by default, redirects are followed)
[s] fetch(req) Fetch a scrapy.Request and update local objects
[s] shelp() Shell help (print this help)
[s] view(response) View response in a browser
In [1]: view(response)
Out[1]: True
In [2]: response.xpath('//a')
Out[2]:
[<Selector xpath='//a' data='<a id="elevator" class="off" onclick="re'>,
<Selector xpath='//a' data='<a class="plus"></a>'>,
<Selector xpath='//a' data='<a onclick="app.showUploadDialog();">添加采'>,
<Selector xpath='//a' data='<a class="add-board-item">添加画板<i class="'>,
<Selector xpath='//a' data='<a href="/about/goodies/">安装采集工具<i class'>,
<Selector xpath='//a' data='<a class="huaban_security_oauth" logo_si'>]
In [3]: response.xpath('//a').extract()
Out[3]:
['<a id="elevator" class="off" onclick="return false;" title="回到顶部"></a>',
'<a class="plus"></a>',
'<a onclick="app.showUploadDialog();">添加采集<i class="upload"></i></a>',
'<a class="add-board-item">添加画板<i class="add-board"></i></a>',
'<a href="/about/goodies/">安装采集工具<i class="goodies"></i></a>',
'<a class="huaban_security_oauth" logo_size="124x47" logo_type="realname" href="//www.anquan.org" rel="nofollow"> <script src="//static.anquan.org/static/outer/js/aq_auth.js"></script> </a>']
In [4]: response.xpath('//img')
Out[4]: [<Selector xpath='//img' data='<img src="https://d5nxst8fruw4z.cloudfro'>]
In [5]: response.xpath('//a/text()')
Out[5]:
[<Selector xpath='//a/text()' data='添加采集'>,
<Selector xpath='//a/text()' data='添加画板'>,
<Selector xpath='//a/text()' data='安装采集工具'>,
<Selector xpath='//a/text()' data=' '>,
<Selector xpath='//a/text()' data=' '>]
In [6]: response.xpath('//a/text()').extract()
Out[6]: ['添加采集', '添加画板', '安装采集工具', ' ', ' ']
In [7]: response.xpath('//a/text()').extract_first()
Out[7]: '添加采集'
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