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python之scrapy入门教程
看这篇文章的人，我假设你们都已经学会了python（派森），然后下面的知识都是python的扩展（框架）。
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：
- 创建一个新的Scrapy项目
- 定义提取的Item
- 写一个Spider用来爬行站点，并提取Items
- 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 tutorialT:\>
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：
T:\tutorial>tree /fFolder PATH listingVolume serial number is 0006EFCF C86A:7C52T:.│ scrapy.cfg│└─tutorial │ items.py │ pipelines.py │ settings.py │ __init__.py │ └─spiders __init__.py
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。
from scrapy.spider import BaseSpiderclass 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)
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
crawl dmoz 命令从dmoz.org域启动爬虫。 你将会获得如下类似输出
T:\tutorial>scrapy crawl dmoz2012-07-13 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, SpiderState2012-07-13 19:14:45+0800 [scrapy] DEBUG: Enabled downloader middlewares: HttpAuthMiddleware, DownloadTimeoutMiddleware, UserAgentMiddleware, RetryMiddleware, DefaultHeadersMiddleware, RedirectMiddleware, CookiesMiddleware, HttpCompressionMiddleware, ChunkedTransferMiddleware, DownloaderStats2012-07-13 19:14:45+0800 [scrapy] DEBUG: Enabled spider middlewares: HttpErrorMiddleware, OffsiteMiddleware, RefererMiddleware, UrlLengthMiddleware, DepthMiddleware2012-07-13 19:14:45+0800 [scrapy] DEBUG: Enabled item pipelines:2012-07-13 19:14:45+0800 [dmoz] INFO: Spider opened2012-07-13 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 0.0.0.0:60232012-07-13 19:14:45+0800 [scrapy] DEBUG: Web service listening on 0.0.0.0:60802012-07-13 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: {}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 shell http://www.dmoz.org/Computers/Programming/Languages/Python/Books/
输出结果类似这样：
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, SpiderState2012-07-16 10:58:13+0800 [scrapy] DEBUG: Enabled downloader middlewares: HttpAuthMiddleware, DownloadTimeoutMiddleware, UserAgentMiddleware, RetryMiddleware, DefaultHeadersMiddleware, RedirectMiddleware, CookiesMiddleware, HttpCompressionMiddleware, ChunkedTransferMiddleware, DownloaderStats2012-07-16 10:58:13+0800 [scrapy] DEBUG: Enabled spider middlewares: HttpErrorMiddleware, OffsiteMiddleware, RefererMiddleware, UrlLengthMiddleware, DepthMiddleware2012-07-16 10:58:13+0800 [scrapy] DEBUG: Enabled item pipelines:2012-07-16 10:58:13+0800 [scrapy] DEBUG: Telnet console listening on 0.0.0.0:60232012-07-16 10:58:13+0800 [scrapy] DEBUG: Web service listening on 0.0.0.0:60802012-07-16 10:58:13+0800 [dmoz] INFO: Spider opened2012-07-16 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=http://www.mamicode.com/u‘<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 browserWARNING: 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.htmlGary‘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]: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：
In [1]: hxs.path(‘//title‘)Out[1]: [<HtmlXPathSelector xpath=‘//title‘ data=http://www.mamicode.com/u‘Open Directory - Computers: Progr‘>]><div></div></div><p> </p><p> </p><p><strong>提取数据</strong></p><p>现在我们尝试从网页中提取数据。 <br />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<em>Using Firebug for scraping </em><em>和</em><em>Using Firefox for scraping.</em><br />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。<br />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>。 <br />我们可以通过如下命令选择每个在网站中的 <li> 元素:</p><div><pre class="shadow-none p-3 mb-5 bg-light rounded">hxs.path(‘//ul/li‘) </pre></div><p>然后是网站描述:</p><div><pre class="shadow-none p-3 mb-5 bg-light rounded">hxs.path(‘//ul/li/text()‘).extract()</pre></div><p>网站标题:</p><div><pre class="shadow-none p-3 mb-5 bg-light rounded">hxs.path(‘//ul/li/a/text()‘).extract()</pre></div><p>网站链接:</p><div><pre class="shadow-none p-3 mb-5 bg-light rounded">hxs.path(‘//ul/li/a/@href‘).extract()</pre></div><p>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:</p><div><div></div><pre class="shadow-none p-3 mb-5 bg-light rounded">sites = hxs.path(‘//ul/li‘)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</pre><div></div></div><p> </p><p>Note <br />更多关于嵌套选择器的内容，请阅读<em>Nesting selectors</em> 和 <em>Working with relative XPaths</em></p><p>将代码添加到爬虫中：</p><p>txw1958注：代码有修改，绿色注释掉的代码为原教程的，你懂的</p><div><div></div><pre class="shadow-none p-3 mb-5 bg-light rounded">from scrapy.spider import BaseSpiderfrom scrapy.selector import HtmlXPathSelectorclass 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 = hxs.path(‘//ul/li‘) 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</pre><div></div></div><p>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</p><div><pre class="shadow-none p-3 mb-5 bg-light rounded">T:\tutorial>scrapy crawl dmoz</pre></div><p> </p><p> </p><p><strong>使用条目</strong><strong>(Item)</strong></p><p>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:</p><div><pre class="shadow-none p-3 mb-5 bg-light rounded">>>> item = DmozItem() >>> item[‘title‘] = ‘Example title‘ >>> item[‘title‘] ‘Example title‘ </pre></div><p>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:</p><div><div></div><pre class="shadow-none p-3 mb-5 bg-light rounded">from scrapy.spider import BaseSpiderfrom scrapy.selector import HtmlXPathSelectorfrom tutorial.items import DmozItemclass 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 = hxs.path(‘//ul/li‘) 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</pre><div></div></div><p>现在我们再次抓取 : </p><div><div></div><pre class="shadow-none p-3 mb-5 bg-light rounded">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"]}</pre><div></div></div><p><br /> </p><p><strong>保存抓取的数据</strong></p><p>保存信息的最简单的方法是通过<em>Feed exports</em>，命令如下：</p><div><pre class="shadow-none p-3 mb-5 bg-light rounded">T:\tutorial>scrapy crawl dmoz -o items.json -t json</pre></div><p>所有抓取的items将以JSON格式被保存在新生成的items.json 文件中<br /><br />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。</p><p><br /><br /><strong>结束语</strong></p><p>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。</p><p>对于基本概念的了解，请访问<em>Basic concepts</em></p><p>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。</p><p>Dirbot项目位于https://github.com/scrapy/dirbot</p><p>项目包含一个README文件，它详细描述了项目的内容。</p><p>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。</p><p>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:-)</p><p> </p><p>文件源码附件稍后上传……</p><p><strong> </strong></p><p>python之scrapy入门教程</p></span> </div> <nav class="p-0 mb-4 bg-white text-left"> <a href="/itag/60/" title="des" class="tag" target="_blank">des</a> <a href="/itag/13/" title="blog" class="tag" target="_blank">blog</a> <a href="/itag/2/" title="http" class="tag" target="_blank">http</a> <a href="/itag/736/" title="io" class="tag" target="_blank">io</a> <a href="/itag/743/" title="ar" class="tag" target="_blank">ar</a> </nav> <div class="alert alert-secondary alert-dismissible fade show font-weight-light" role="alert"> <i class="bi bi-info-square-fill"></i> 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