mirror of https://github.com/scrapy/scrapy.git
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6.5 KiB
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159 lines
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.. _intro-overview:
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==================
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Scrapy at a glance
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==================
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Scrapy (/ˈskreɪpaɪ/) is an application framework for crawling web sites and extracting
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structured data which can be used for a wide range of useful applications, like
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data mining, information processing or historical archival.
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Even though Scrapy was originally designed for `web scraping`_, it can also be
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used to extract data using APIs (such as `Amazon Associates Web Services`_) or
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as a general purpose web crawler.
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Walk-through of an example spider
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=================================
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In order to show you what Scrapy brings to the table, we'll walk you through an
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example of a Scrapy Spider using the simplest way to run a spider.
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Here's the code for a spider that scrapes famous quotes from website
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https://quotes.toscrape.com, following the pagination:
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.. code-block:: python
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import scrapy
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class QuotesSpider(scrapy.Spider):
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name = "quotes"
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start_urls = [
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"https://quotes.toscrape.com/tag/humor/",
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]
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def parse(self, response):
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for quote in response.css("div.quote"):
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yield {
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"author": quote.xpath("span/small/text()").get(),
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"text": quote.css("span.text::text").get(),
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}
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next_page = response.css('li.next a::attr("href")').get()
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if next_page is not None:
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yield response.follow(next_page, self.parse)
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Put this in a text file, name it something like ``quotes_spider.py``
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and run the spider using the :command:`runspider` command::
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scrapy runspider quotes_spider.py -o quotes.jsonl
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When this finishes you will have in the ``quotes.jsonl`` file a list of the
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quotes in JSON Lines format, containing the text and author, which will look like this::
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{"author": "Jane Austen", "text": "\u201cThe person, be it gentleman or lady, who has not pleasure in a good novel, must be intolerably stupid.\u201d"}
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{"author": "Steve Martin", "text": "\u201cA day without sunshine is like, you know, night.\u201d"}
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{"author": "Garrison Keillor", "text": "\u201cAnyone who thinks sitting in church can make you a Christian must also think that sitting in a garage can make you a car.\u201d"}
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...
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What just happened?
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-------------------
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When you ran the command ``scrapy runspider quotes_spider.py``, Scrapy looked for a
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Spider definition inside it and ran it through its crawler engine.
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The crawl started by making requests to the URLs defined in the ``start_urls``
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attribute (in this case, only the URL for quotes in the *humor* category)
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and called the default callback method ``parse``, passing the response object as
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an argument. In the ``parse`` callback, we loop through the quote elements
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using a CSS Selector, yield a Python dict with the extracted quote text and author,
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look for a link to the next page and schedule another request using the same
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``parse`` method as callback.
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Here you will notice one of the main advantages of Scrapy: requests are
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:ref:`scheduled and processed asynchronously <topics-architecture>`. This
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means that Scrapy doesn't need to wait for a request to be finished and
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processed, it can send another request or do other things in the meantime. This
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also means that other requests can keep going even if a request fails or an
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error happens while handling it.
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While this enables you to do very fast crawls (sending multiple concurrent
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requests at the same time, in a fault-tolerant way) Scrapy also gives you
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control over the politeness of the crawl through :ref:`a few settings
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<topics-settings-ref>`. You can do things like setting a download delay between
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each request, limiting the amount of concurrent requests per domain, and
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even :ref:`using an auto-throttling extension <topics-autothrottle>` that tries
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to figure these settings out automatically.
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.. note::
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This is using :ref:`feed exports <topics-feed-exports>` to generate the
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JSON Lines file, you can easily change the export format (XML or CSV, for
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example) or the storage backend (FTP or `Amazon S3`_, for example). You can
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also write an :ref:`item pipeline <topics-item-pipeline>` to store the
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items in a database.
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.. _topics-whatelse:
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What else?
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==========
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You've seen how to extract and store items from a website using Scrapy, but
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this is just the surface. Scrapy provides a lot of powerful features for making
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scraping easy and efficient, such as:
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* Built-in support for :ref:`selecting and extracting <topics-selectors>` data
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from HTML/XML sources using extended CSS selectors and XPath expressions,
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with helper methods for extraction using regular expressions.
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* An :ref:`interactive shell console <topics-shell>` (IPython aware) for trying
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out the CSS and XPath expressions to scrape data, which is very useful when writing or
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debugging your spiders.
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* Built-in support for :ref:`generating feed exports <topics-feed-exports>` in
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multiple formats (JSON, CSV, XML) and storing them in multiple backends (FTP,
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S3, local filesystem)
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* Robust encoding support and auto-detection, for dealing with foreign,
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non-standard and broken encoding declarations.
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* :ref:`Strong extensibility support <extending-scrapy>`, allowing you to plug
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in your own functionality using :ref:`signals <topics-signals>` and a
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well-defined API (middlewares, :ref:`extensions <topics-extensions>`, and
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:ref:`pipelines <topics-item-pipeline>`).
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* A wide range of built-in extensions and middlewares for handling:
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- cookies and session handling
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- HTTP features like compression, authentication, caching
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- user-agent spoofing
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- robots.txt
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- crawl depth restriction
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- and more
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* A :ref:`Telnet console <topics-telnetconsole>` for hooking into a Python
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console running inside your Scrapy process, to introspect and debug your
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crawler
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* Plus other goodies like reusable spiders to crawl sites from `Sitemaps`_ and
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XML/CSV feeds, a media pipeline for :ref:`automatically downloading images
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<topics-media-pipeline>` (or any other media) associated with the scraped
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items, a caching DNS resolver, and much more!
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What's next?
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============
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The next steps for you are to :ref:`install Scrapy <intro-install>`,
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:ref:`follow through the tutorial <intro-tutorial>` to learn how to create
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a full-blown Scrapy project and `join the community`_. Thanks for your
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interest!
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.. _join the community: https://www.scrapy.org/community
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.. _web scraping: https://en.wikipedia.org/wiki/Web_scraping
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.. _Amazon Associates Web Services: https://affiliate-program.amazon.com/welcome/ecs
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.. _Amazon S3: https://aws.amazon.com/s3/
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.. _Sitemaps: https://www.sitemaps.org/index.html
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