Scrapy入门教程

在这篇入门教程中,我们假定你已经安装了Scrapy。如果你还没有安装,那么请参考安装指南

我们将使用开放目录项目(dmoz)作为抓取的例子。

这篇入门教程将引导你完成如下任务:

  1. 创建一个新的Scrapy项目
  2. 定义提取的Item
  3. 写一个Spider用来爬行站点,并提取Items
  4. 写一个Item Pipeline用来存储提取出的Items

Scrapy是由Python编写的。如果你是Python新手,你也许希望从了解Python开始,以期最好的使用Scrapy。如果你对其它编程语言熟悉,想快速的学习Python,这里推荐 Dive Into Python。如果你对编程是新手,且想从Python开始学习编程,请看下面的对非程序员的Python资源列表

新建工程

在抓取之前,你需要新建一个Scrapy工程。进入一个你想用来保存代码的目录,然后执行:

Microsoft Windows XP [Version 5.1.2600]
(C) Copyright 1985-2001 Microsoft Corp.

T:\>scrapy startproject tutorial
T:\>

这个命令会在当前目录下创建一个新目录tutorial,它的结构如下:

复制代码
T:\tutorial>tree /f
Folder PATH listing
Volume serial number is 0006EFCF C86A:7C52
T:.
│  scrapy.cfg
│
└─tutorial
    │  items.py
    │  pipelines.py
    │  settings.py
    │  __init__.py
    │
    └─spiders
            __init__.py
复制代码

这些文件主要是:

  • scrapy.cfg: 项目配置文件
  • tutorial/: 项目python模块, 呆会代码将从这里导入
  • tutorial/items.py: 项目items文件
  • tutorial/pipelines.py: 项目管道文件
  • tutorial/settings.py: 项目配置文件
  • tutorial/spiders: 放置spider的目录

 

定义Item

Items是将要装载抓取的数据的容器,它工作方式像python里面的字典,但它提供更多的保护,比如对未定义的字段填充以防止拼写错误。

它通过创建一个scrapy.item.Item类来声明,定义它的属性为scrpy.item.Field对象,就像是一个对象关系映射(ORM).
我们通过将需要的item模型化,来控制从dmoz.org获得的站点数据,比如我们要获得站点的名字,url和网站描述,我们定义这三种属性的域。要做到这点,我们编辑在tutorial目录下的items.py文件,我们的Item类将会是这样

from scrapy.item import Item, Field 
class DmozItem(Item):
    title = Field()
    link = Field()
    desc = Field()

刚开始看起来可能会有些困惑,但是定义这些item能让你用其他Scrapy组件的时候知道你的 items到底是什么。

 

 

我们的第一个爬虫(Spider)

Spider是用户编写的类,用于从一个域(或域组)中抓取信息。

他们定义了用于下载的URL的初步列表,如何跟踪链接,以及如何来解析这些网页的内容用于提取items。

要建立一个Spider,你必须为scrapy.spider.BaseSpider创建一个子类,并确定三个主要的、强制的属性:

  • name:爬虫的识别名,它必须是唯一的,在不同的爬虫中你必须定义不同的名字.
  • start_urls:爬虫开始爬的一个URL列表。爬虫从这里开始抓取数据,所以,第一次下载的数据将会从这些URLS开始。其他子URL将会从这些起始URL中继承性生成。
  • parse():爬虫的方法,调用时候传入从每一个URL传回的Response对象作为参数,response将会是parse方法的唯一的一个参数,

这个方法负责解析返回的数据、匹配抓取的数据(解析为item)并跟踪更多的URL。

 

这是我们的第一只爬虫的代码,将其命名为dmoz_spider.py并保存在tutorial\spiders目录下。

复制代码
from scrapy.spider import BaseSpider

class DmozSpider(BaseSpider):
    name = "dmoz"
    allowed_domains = ["dmoz.org"]
    start_urls = [
        "http://www.dmoz.org/Computers/Programming/Languages/Python/Books/",
        "http://www.dmoz.org/Computers/Programming/Languages/Python/Resources/"
    ]

    def parse(self, response):
        filename = response.url.split("/")[-2]
        open(filename, 'wb').write(response.body)
复制代码

 

 

爬爬爬

为了让我们的爬虫工作,我们返回项目主目录执行以下命令

T:\tutorial>scrapy crawl dmoz -o items.json -t json -o items.json -t json

crawl dmoz 命令从dmoz.org域启动爬虫。 你将会获得如下类似输出

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T:\tutorial>scrapy crawl dmoz -o items.json -t json -o items.json -t json
2012-07-13 19:14:45+0800 [scrapy] INFO: Scrapy 0.14.4 started (bot: tutorial)
2012-07-13 19:14:45+0800 [scrapy] DEBUG: Enabled extensions: LogStats, TelnetConsole, CloseSpider, WebService, CoreStats, SpiderState
2012-07-13 19:14:45+0800 [scrapy] DEBUG: Enabled downloader middlewares: HttpAuthMiddleware, DownloadTimeoutMiddleware, UserAgentMiddleware, RetryMiddleware, DefaultHeadersMiddleware, RedirectMiddleware, CookiesMiddleware, HttpCompressionMiddleware, ChunkedTransferMiddleware, DownloaderStats
2012-07-13 19:14:45+0800 [scrapy] DEBUG: Enabled spider middlewares: HttpErrorMiddleware, OffsiteMiddleware, RefererMiddleware, UrlLengthMiddleware, DepthMiddleware
2012-07-13 19:14:45+0800 [scrapy] DEBUG: Enabled item pipelines:
2012-07-13 19:14:45+0800 [dmoz] INFO: Spider opened
2012-07-13 19:14:45+0800 [dmoz] INFO: Crawled 0 pages (at 0 pages/min), scraped 0 items (at 0 items/min)
2012-07-13 19:14:45+0800 [scrapy] DEBUG: Telnet console listening on 0.0.0.0:6023
2012-07-13 19:14:45+0800 [scrapy] DEBUG: Web service listening on 0.0.0.0:6080
2012-07-13 19:14:46+0800 [dmoz] DEBUG: Crawled (200) <GET http://www.dmoz.org/Computers/Programming/Languages/Python/Resources/> (referer: None)
2012-07-13 19:14:46+0800 [dmoz] DEBUG: Crawled (200) <GET http://www.dmoz.org/Computers/Programming/Languages/Python/Books/> (referer: None)
2012-07-13 19:14:46+0800 [dmoz] INFO: Closing spider (finished)
2012-07-13 19:14:46+0800 [dmoz] INFO: Dumping spider stats:
        {'downloader/request_bytes': 486,
         'downloader/request_count': 2,
         'downloader/request_method_count/GET': 2,
         'downloader/response_bytes': 13063,
         'downloader/response_count': 2,
         'downloader/response_status_count/200': 2,
         'finish_reason': 'finished',
         'finish_time': datetime.datetime(2012, 7, 13, 11, 14, 46, 703000),
         'scheduler/memory_enqueued': 2,
         'start_time': datetime.datetime(2012, 7, 13, 11, 14, 45, 500000)}
2012-07-13 19:14:46+0800 [dmoz] INFO: Spider closed (finished)
2012-07-13 19:14:46+0800 [scrapy] INFO: Dumping global stats:
        {}
复制代码

注意包含 [dmoz]的行 ,那对应着我们的爬虫。你可以看到start_urls中定义的每个URL都有日志行。因为这些URL是起始页面,所以他们没有引用(referrers),所以在每行的末尾你会看到 (referer: <None>).
有趣的是,在我们的 parse  方法的作用下,两个文件被创建:分别是 Books 和 Resources,这两个文件中有URL的页面内容。

发生了什么事情?

Scrapy为爬虫的 start_urls属性中的每个URL创建了一个 scrapy.http.Request 对象 ,并将爬虫的parse 方法指定为回调函数。
这些 Request首先被调度,然后被执行,之后通过parse()方法,scrapy.http.Response 对象被返回,结果也被反馈给爬虫。

 

 

提取Item

选择器介绍

我们有很多方法从网站中提取数据。Scrapy 使用一种叫做 XPath selectors的机制,它基于 XPath表达式。如果你想了解更多selectors和其他机制你可以查阅资料http://doc.scrapy.org/topics/selectors.html#topics-selectors
这是一些XPath表达式的例子和他们的含义

  • /html/head/title: 选择HTML文档<head>元素下面的<title> 标签。
  • /html/head/title/text(): 选择前面提到的<title> 元素下面的文本内容
  • //td: 选择所有 <td> 元素
  • //div[@class=”mine”]: 选择所有包含 class=”mine” 属性的div 标签元素

这只是几个使用XPath的简单例子,但是实际上XPath非常强大。如果你想了解更多XPATH的内容,我们向你推荐这个XPath教程http://www.w3schools.com/XPath/default.asp

为了方便使用XPaths,Scrapy提供XPathSelector 类, 有两种口味可以选择, HtmlXPathSelector (HTML数据解析) 和XmlXPathSelector (XML数据解析)。 为了使用他们你必须通过一个 Response 对象对他们进行实例化操作。你会发现Selector对象展示了文档的节点结构。因此,第一个实例化的selector必与根节点或者是整个目录有关 。
Selectors 有三种方法

  • path():返回selectors列表, 每一个select表示一个xpath参数表达式选择的节点.
  • extract():返回一个unicode字符串,该字符串为XPath选择器返回的数据
  • re(): 返回unicode字符串列表,字符串作为参数由正则表达式提取出来

尝试在shell中使用Selectors

为了演示Selectors的用法,我们将用到 内建的Scrapy shell,这需要系统已经安装IPython (一个扩展python交互环境) 。

附IPython下载地址:http://pypi.python.org/pypi/ipython#downloads

要开始shell,首先进入项目顶层目录,然后输入

T:\tutorial>scrapy crawl dmoz -o items.json -t json -o items.json -t json

输出结果类似这样:

复制代码
2012-07-16 10:58:13+0800 [scrapy] INFO: Scrapy 0.14.4 started (bot: tutorial)
2012-07-16 10:58:13+0800 [scrapy] DEBUG: Enabled extensions: TelnetConsole, CloseSpider, WebService, CoreStats, SpiderState
2012-07-16 10:58:13+0800 [scrapy] DEBUG: Enabled downloader middlewares: HttpAuthMiddleware, DownloadTimeoutMiddleware, UserAgentMiddleware, RetryMiddleware, DefaultHeadersMiddleware, RedirectMiddleware, CookiesMiddleware, HttpCompressionMiddleware, ChunkedTransferMiddleware, DownloaderStats
2012-07-16 10:58:13+0800 [scrapy] DEBUG: Enabled spider middlewares: HttpErrorMiddleware, OffsiteMiddleware, RefererMiddleware, UrlLengthMiddleware, DepthMiddleware
2012-07-16 10:58:13+0800 [scrapy] DEBUG: Enabled item pipelines:
2012-07-16 10:58:13+0800 [scrapy] DEBUG: Telnet console listening on 0.0.0.0:6023
2012-07-16 10:58:13+0800 [scrapy] DEBUG: Web service listening on 0.0.0.0:6080
2012-07-16 10:58:13+0800 [dmoz] INFO: Spider opened
2012-07-16 10:58:18+0800 [dmoz] DEBUG: Crawled (200) <GET http://www.dmoz.org/Computers/Programming/Languages/Python/Books/> (referer: None)
[s] Available Scrapy objects:
[s]   hxs        <HtmlXPathSelector xpath=None data=u'<html><head><meta http-equiv="Content-Ty'>
[s]   item       {}
[s]   request    <GET http://www.dmoz.org/Computers/Programming/Languages/Python/Books/>
[s]   response   <200 http://www.dmoz.org/Computers/Programming/Languages/Python/Books/>
[s]   settings   <CrawlerSettings module=<module 'tutorial.settings' from 'T:\tutorial\tutorial\settings.pyc'>>
[s]   spider     <DmozSpider 'dmoz' at 0x1f68230>
[s] Useful shortcuts:
[s]   shelp()           Shell help (print this help)
[s]   fetch(req_or_url) Fetch request (or URL) and update local objects
[s]   view(response)    View response in a browser
WARNING: Readline services not available or not loaded.WARNING: Proper color support under MS Windows requires the pyreadline library.
You can find it at:
http://ipython.org/pyreadline.html
Gary's readline needs the ctypes module, from:
http://starship.python.net/crew/theller/ctypes
(Note that ctypes is already part of Python versions 2.5 and newer).

Defaulting color scheme to 'NoColor'Python 2.7.3 (default, Apr 10 2012, 23:31:26) [MSC v.1500 32 bit (Intel)]
Type "copyright", "credits" or "license" for more information.

IPython 0.13 -- An enhanced Interactive Python.
?         -> Introduction and overview of IPython's features.
%quickref -> Quick reference.
help      -> Python's own help system.
object?   -> Details about 'object', use 'object??' for extra details.

In [1]:
复制代码

Shell载入后,你将获得回应,这些内容被存储在本地变量 response 中,所以如果你输入response.body 你将会看到response的body部分,或者输入response.headers 来查看它的 header部分。
Shell也实例化了两种selectors,一个是解析HTML的  hxs 变量,一个是解析 XML 的 xxs 变量。我们来看看里面有什么:

复制代码
In [1]: hxs.path('//title')
Out[1]: [<HtmlXPathSelector xpath='//title' data=u'<title>Open Directory - Computers: Progr'>]

In [2]: hxs.path('//title').extract()
Out[2]: [u'<title>Open Directory - Computers: Programming: Languages: Python: Books</title>']

In [3]: hxs.path('//title/text()')
Out[3]: [<HtmlXPathSelector xpath='//title/text()' data=u'Open Directory - Computers: Programming:'>]

In [4]: hxs.path('//title/text()').extract()
Out[4]: [u'Open Directory - Computers: Programming: Languages: Python: Books']

In [5]: hxs.path('//title/text()').re('(\w+):')
Out[5]: [u'Computers', u'Programming', u'Languages', u'Python']

In [6]:
复制代码

 

 

提取数据

现在我们尝试从网页中提取数据。
你可以在控制台输入 response.body, 检查源代码中的 XPaths 是否与预期相同。然而,检查HTML源代码是件很枯燥的事情。为了使事情变得简单,我们使用Firefox的扩展插件Firebug。更多信息请查看Using Firebug for scraping Using Firefox for scraping.
txw1958注:事实上我用的是Google Chrome的Inspect Element功能,而且可以提取元素的XPath。
检查源代码后,你会发现我们需要的数据在一个 <ul>元素中,而且是第二个<ul>。
我们可以通过如下命令选择每个在网站中的 <li> 元素:

T:\tutorial>scrapy crawl dmoz -o items.json -t json -o items.json -t json

然后是网站描述:

T:\tutorial>scrapy crawl dmoz -o items.json -t json -o items.json -t json

网站标题:

T:\tutorial>scrapy crawl dmoz -o items.json -t json -o items.json -t json

网站链接:

T:\tutorial>scrapy crawl dmoz -o items.json -t json -o items.json -t json

如前所述,每个path()调用返回一个selectors列表,所以我们可以结合path()去挖掘更深的节点。我们将会用到这些特性,所以:

复制代码
sites = T:\tutorial>scrapy crawl dmoz -o items.json -t json -o items.json -t json
for site in sites:
    title = site.path('a/text()').extract()
    link = site.path('a/@href').extract()
    desc = site.path('text()').extract()
    print title, link, desc
复制代码

 

Note
更多关于嵌套选择器的内容,请阅读Nesting selectorsWorking with relative XPaths

将代码添加到爬虫中:

txw1958注:代码有修改,绿色注释掉的代码为原教程的,你懂的

复制代码
from scrapy.spider import BaseSpider
from scrapy.selector import HtmlXPathSelector

class DmozSpider(BaseSpider):
    name = "dmoz"
    allowed_domains = ["dmoz.org"]
    start_urls = [
        "http://www.dmoz.org/Computers/Programming/Languages/Python/Books/",
        "http://www.dmoz.org/Computers/Programming/Languages/Python/Resources/"
]    
  
    def parse(self, response):
        hxs = HtmlXPathSelector(response)
        sites = hxs.path('//fieldset/ul/li')
        #sites = T:\tutorial>scrapy crawl dmoz -o items.json -t json -o items.json -t json
        for site in sites:
            title = site.path('a/text()').extract()
            link = site.path('a/@href').extract()
            desc = site.path('text()').extract()
            #print title, link, desc
            print title, link
复制代码

现在我们再次抓取dmoz.org,你将看到站点在输出中被打印 ,运行命令

T:\tutorial>scrapy crawl dmoz -o items.json -t json -o items.json -t json

 

 

使用条目(Item)

Item 对象是自定义的python字典,使用标准字典类似的语法,你可以获取某个字段(即之前定义的类的属性)的值:

>>> item = DmozItem() 
>>> item['title'] = 'Example title' 
>>> item['title'] 
'Example title'

Spiders希望将其抓取的数据存放到Item对象中。为了返回我们抓取数据,spider的最终代码应当是这样:

复制代码
from scrapy.spider import BaseSpider
from scrapy.selector import HtmlXPathSelector

from tutorial.items import DmozItem

class DmozSpider(BaseSpider):
   name = "dmoz"
   allowed_domains = ["dmoz.org"]
   start_urls = [
       "http://www.dmoz.org/Computers/Programming/Languages/Python/Books/",
       "http://www.dmoz.org/Computers/Programming/Languages/Python/Resources/"
   ]

   def parse(self, response):
       hxs = HtmlXPathSelector(response)
       sites = hxs.path('//fieldset/ul/li')
       #sites = T:\tutorial>scrapy crawl dmoz -o items.json -t json -o items.json -t json
       items = []
       for site in sites:
           item = DmozItem()
           item['title'] = site.path('a/text()').extract()
           item['link'] = site.path('a/@href').extract()
           item['desc'] = site.path('text()').extract()
           items.append(item)
       return items
复制代码

现在我们再次抓取 :

复制代码
2012-07-16 14:52:36+0800 [dmoz] DEBUG: Scraped from <200 http://www.dmoz.org/Computers/Programming/Languages/Python/Books/>
        {'desc': [u'\n\t\t\t\n\t',
                  u' \n\t\t\t\n\t\t\t\t\t\n - Free Python books and tutorials.\n \n'],
         'link': [u'http://www.techbooksforfree.com/perlpython.shtml'],
         'title': [u'Free Python books']}
2012-07-16 14:52:36+0800 [dmoz] DEBUG: Scraped from <200 http://www.dmoz.org/Computers/Programming/Languages/Python/Books/>
        {'desc': [u'\n\t\t\t\n\t',
                  u' \n\t\t\t\n\t\t\t\t\t\n - Annotated list of free online books on Python scripting language. Topics range from beginner to advanced.\n \n
          '],
         'link': [u'http://www.freetechbooks.com/python-f6.html'],
         'title': [u'FreeTechBooks: Python Scripting Language']}
2012-07-16 14:52:36+0800 [dmoz] DEBUG: Crawled (200) <GET http://www.dmoz.org/Computers/Programming/Languages/Python/Resources/> (referer: None)
2012-07-16 14:52:36+0800 [dmoz] DEBUG: Scraped from <200 http://www.dmoz.org/Computers/Programming/Languages/Python/Resources/>
        {'desc': [u'\n\t\t\t\n\t',
                  u' \n\t\t\t\n\t\t\t\t\t\n - A directory of free Python and Zope hosting providers, with reviews and ratings.\n \n'],
         'link': [u'http://www.oinko.net/freepython/'],
         'title': [u'Free Python and Zope Hosting Directory']}
2012-07-16 14:52:36+0800 [dmoz] DEBUG: Scraped from <200 http://www.dmoz.org/Computers/Programming/Languages/Python/Resources/>
        {'desc': [u'\n\t\t\t\n\t',
                  u' \n\t\t\t\n\t\t\t\t\t\n - Features Python books, resources, news and articles.\n \n'],
         'link': [u'http://oreilly.com/python/'],
         'title': [u"O'Reilly Python Center"]}
2012-07-16 14:52:36+0800 [dmoz] DEBUG: Scraped from <200 http://www.dmoz.org/Computers/Programming/Languages/Python/Resources/>
        {'desc': [u'\n\t\t\t\n\t',
                  u' \n\t\t\t\n\t\t\t\t\t\n - Resources for reporting bugs, accessing the Python source tree with CVS and taking part in the development of Python.\n\n'],
         'link': [u'http://www.python.org/dev/'],
         'title': [u"Python Developer's Guide"]}
复制代码

 

保存抓取的数据

保存信息的最简单的方法是通过Feed exports,命令如下:

T:\tutorial>scrapy crawl dmoz -o items.json -t json -o items.json -t json

所有抓取的items将以JSON格式被保存在新生成的items.json 文件中

在像本教程一样的小型项目中,这些已经足够。然而,如果你想用抓取的items做更复杂的事情,你可以写一个 Item Pipeline(条目管道)。因为在项目创建的时候,一个专门用于条目管道的占位符文件已经随着items一起被建立,目录在tutorial/pipelines.py。如果你只需要存取这些抓取后的items的话,就不需要去实现任何的条目管道。

结束语

本教程简要介绍了Scrapy的使用,但是许多其他特性并没有提及。

对于基本概念的了解,请访问Basic concepts

我们推荐你继续学习Scrapy项目的例子dirbot,你将从中受益更深,该项目包含本教程中提到的dmoz爬虫。

Dirbot项目位于https://github.com/scrapy/dirbot

项目包含一个README文件,它详细描述了项目的内容。

如果你熟悉git,你可以checkout它的源代码。或者你可以通过点击Downloads下载tarball或zip格式的文件。

另外这有一个代码片断共享网站,里面共享内容包括爬虫,中间件,扩展应用,脚本等。网站名字叫Scrapy snippets,有好的代码要记得共享哦:-)

 

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