Spiders¶

Spiders are classes which define how a certain site (or domain) will be scraped, including how to crawl the site and how to extract scraped items from their pages. In other words, Spiders are the place where you define the custom behaviour for crawling and parsing pages for a particular site.

For spiders, the scraping cycle goes through something like this:

You start by generating the initial Requests to crawl the first URLs, and specify a callback function to be called with the response downloaded from those requests.

The first requests to perform are obtained by calling the start_requests() method which (by default) generates Request for the URLs specified in the start_urls and the parse method as callback function for the Requests.
In the callback function you parse the response (web page) and return either Item objects, Request objects, or an iterable of both. Those Requests will also contain a callback (maybe the same) and will then be followed by downloaded by Scrapy and then their response handled to the specified callback.
In callback functions you parse the page contants, typically using XPath Selectors (but you can also use BeautifuSoup, lxml or whatever mechanism you prefer) and generate items with the parsed data.
Finally the items returned from the spider will be typically persisted in some Item pipeline.

Even though this cycles applies (more or less) to any kind of spider, there are different kind of default spiders bundled into Scrapy for different purposes. We will talk about those types here.

Built-in spiders reference¶

For the examples used in the following spiders reference we’ll assume we have a TestItem declared in a myproject.items module, in your project:

from scrapy.item import Item

class TestItem(Item):
    id = Field()
    name = Field()
    description = Field()

BaseSpider¶

class scrapy.spider.BaseSpider¶

This is the simplest spider, and the one from which every other spider must inherit from (either the ones that come bundled with Scrapy, or the ones that you write yourself). It doesn’t provide any special functionality. It just requests the given start_urls/start_requests, and calls the spider’s method parse for each of the resulting responses.

name¶

A string which defines the name for this spider. The spider name is how the spider is located (and instantiated) by Scrapy, so it must be unique. However, nothing prevents you from instantiating more than one instance of the same spider. This is the most important spider attribute and it’s required.

Is recommended to name your spiders after the domain that their crawl.

allowed_domains¶: An optional list of strings containing domains that this spider is allowed to crawl. Requests for URLs not belonging to the domain names specified in this list won’t be followed if OffsiteMiddleware is enabled.

start_urls¶: Is a list of URLs where the spider will begin to crawl from, when no particular URLs are specified. So, the first pages downloaded will be those listed here. The subsequent URLs will be generated successively from data contained in the start URLs.

start_requests()¶

This method must return an iterable with the first Requests to crawl for this spider.

This is the method called by Scrapy when the spider is opened for scraping when no particular URLs are specified. If particular URLs are specified, the make_requests_from_url() is used instead to create the Requests. This method is also called only once from Scrapy, so it’s safe to implement it as a generator.

The default implementation uses make_requests_from_url() to generate Requests for each url in start_urls.

If you want to change the Requests used to start scraping a domain, this is the method to override. For example, if you need to start by login in using a POST request, you could do:

def start_requests(self):
    return [FormRequest("http://www.example.com/login",
                        formdata={'user': 'john', 'pass': 'secret'},
                        callback=self.logged_in)]

def logged_in(self, response):
    # here you would extract links to follow and return Requests for
    # each of them, with another callback
    pass

make_requests_from_url(url)¶

A method that receives a URL and returns a Request object (or a list of Request objects) to scrape. This method is used to construct the initial requests in the start_requests() method, and is typically used to convert urls to requests.

Unless overridden, this method returns Requests with the parse() method as their callback function, and with dont_filter parameter enabled (see Request class for more info).

parse(response)¶

This is the default callback used by Scrapy to process downloaded responses, when their requests don’t specify a callback.

The parse method is in charge of processing the response and returning scraped data and/or more URLs to follow. Other Requests callbacks have the same requirements as the BaseSpider class.

This method, as well as any other Request callback, must return an iterable of Item objects.

Parameters:	response – the response to parse

log(message[, level, component])¶: Log a message using the scrapy.log.msg() function, automatically populating the spider argument with the name of this spider. For more information see Logging.

BaseSpider example¶

Let’s see an example:

from scrapy import log # This module is useful for printing out debug information
from scrapy.spider import BaseSpider

class MySpider(BaseSpider):
    name = 'example.com'
    allowed_domains = ['example.com']
    start_urls = [
        'http://www.example.com/1.html',
        'http://www.example.com/2.html',
        'http://www.example.com/3.html',
    ]

    def parse(self, response):
        self.log('A response from %s just arrived!' % response.url)

SPIDER = MySpider()

Another example returning multiples Requests and Items from a single callback:

from scrapy.selector import HtmlXPathSelector
from scrapy.spider import BaseSpider
from scrapy.http import Request
from myproject.items import MyItem

class MySpider(BaseSpider):
    name = 'example.com'
    allowed_domains = ['example.com']
    start_urls = [
        'http://www.example.com/1.html',
        'http://www.example.com/2.html',
        'http://www.example.com/3.html',
    ]

    def parse(self, response):
        hxs = HtmlXPathSelector(response)
        for h3 in hxs.select('//h3').extract():
            yield MyItem(title=h3)

        for url in hxs.select('//a/@href').extract():
            yield Request(url, callback=self.parse)

SPIDER = MySpider()

CrawlSpider¶

class scrapy.contrib.spiders.CrawlSpider¶

This is the most commonly used spider for crawling regular websites, as it provides a convenient mechanism for following links by defining a set of rules. It may not be the best suited for your particular web sites or project, but it’s generic enough for several cases, so you can start from it and override it as need more custom functionality, or just implement your own spider.

Apart from the attributes inherited from BaseSpider (that you must specify), this class supports a new attribute:

rules¶: Which is a list of one (or more) Rule objects. Each Rule defines a certain behaviour for crawling the site. Rules objects are described below .

Crawling rules¶

class scrapy.contrib.spiders.Rule(link_extractor, callback=None, cb_kwargs=None, follow=None, process_links=None)¶

link_extractor is a Link Extractor object which defines how links will be extracted from each crawled page.

callback is a callable or a string (in which case a method from the spider object with that name will be used) to be called for each link extracted with the specified link_extractor. This callback receives a response as its first argument and must return a list containing Item and/or Request objects (or any subclass of them).

cb_kwargs is a dict containing the keyword arguments to be passed to the callback function

follow is a boolean which specified if links should be followed from each response extracted with this rule. If callback is None follow defaults to True, otherwise it default to False.

process_links is a callable, or a string (in which case a method from the spider object with that name will be used) which will be called for each list of links extracted from each response using the specified link_extractor. This is mainly used for filtering purposes.

CrawlSpider example¶

Let’s now take a look at an example CrawlSpider with rules:

from scrapy.contrib.spiders import CrawlSpider, Rule
from scrapy.contrib.linkextractors.sgml import SgmlLinkExtractor
from scrapy.selector import HtmlXPathSelector
from scrapy.item import Item

class MySpider(CrawlSpider):
    name = 'example.com'
    allowed_domains = ['example.com']
    start_urls = ['http://www.example.com']

    rules = (
        # Extract links matching 'category.php' (but not matching 'subsection.php')
        # and follow links from them (since no callback means follow=True by default).
        Rule(SgmlLinkExtractor(allow=('category\.php', ), deny=('subsection\.php', ))),

        # Extract links matching 'item.php' and parse them with the spider's method parse_item
        Rule(SgmlLinkExtractor(allow=('item\.php', )), callback='parse_item'),
    )

    def parse_item(self, response):
        self.log('Hi, this is an item page! %s' % response.url)

        hxs = HtmlXPathSelector(response)
        item = Item()
        item['id'] = hxs.select('//td[@id="item_id"]/text()').re(r'ID: (\d+)')
        item['name'] = hxs.select('//td[@id="item_name"]/text()').extract()
        item['description'] = hxs.select('//td[@id="item_description"]/text()').extract()
        return item

SPIDER = MySpider()

This spider would start crawling example.com’s home page, collecting category links, and item links, parsing the latter with the parse_item method. For each item response, some data will be extracted from the HTML using XPath, and a Item will be filled with it.

XMLFeedSpider¶

class scrapy.contrib.spiders.XMLFeedSpider¶

XMLFeedSpider is designed for parsing XML feeds by iterating through them by a certain node name. The iterator can be chosen from: iternodes, xml, and html. It’s recommended to use the iternodes iterator for performance reasons, since the xml and html iterators generate the whole DOM at once in order to parse it. However, using html as the iterator may be useful when parsing XML with bad markup.

For setting the iterator and the tag name, you must define the following class attributes:

iterator¶

A string which defines the iterator to use. It can be either:

'iternodes' - a fast iterator based on regular expressions

'html' - an iterator which uses HtmlXPathSelector. Keep in mind this uses DOM parsing and must load all DOM in memory which could be a problem for big feeds

'xml' - an iterator which uses XmlXPathSelector. Keep in mind this uses DOM parsing and must load all DOM in memory which could be a problem for big feeds

It defaults to: 'iternodes'.

itertag¶

A string with the name of the node (or element) to iterate in. Example:

itertag = 'product'

namespaces¶

A list of (prefix, uri) tuples which define the namespaces available in that document that will be processed with this spider. The prefix and uri will be used to automatically register namespaces using the register_namespace() method.

You can then specify nodes with namespaces in the itertag attribute.

Example:

class YourSpider(XMLFeedSpider):

    namespaces = [('n', 'http://www.sitemaps.org/schemas/sitemap/0.9')]
    itertag = 'n:url'
    # ...

Apart from these new attributes, this spider has the following overrideable methods too:

adapt_response(response)¶: A method that receives the response as soon as it arrives from the spider middleware and before start parsing it. It can be used used for modifying the response body before parsing it. This method receives a response and returns response (it could be the same or another one).

parse_node(response, selector)¶: This method is called for the nodes matching the provided tag name (itertag). Receives the response and an XPathSelector for each node. Overriding this method is mandatory. Otherwise, you spider won’t work. This method must return either a Item object, a Request object, or an iterable containing any of them.

process_results(response, results)¶: This method is called for each result (item or request) returned by the spider, and it’s intended to perform any last time processing required before returning the results to the framework core, for example setting the item IDs. It receives a list of results and the response which originated that results. It must return a list of results (Items or Requests).”“”

XMLFeedSpider example¶

These spiders are pretty easy to use, let’s have at one example:

from scrapy import log
from scrapy.contrib.spiders import XMLFeedSpider
from myproject.items import TestItem

class MySpider(XMLFeedSpider):
    name = 'example.com'
    allowed_domains = ['example.com']
    start_urls = ['http://www.example.com/feed.xml']
    iterator = 'iternodes' # This is actually unnecesary, since it's the default value
    itertag = 'item'

    def parse_node(self, response, node):
        log.msg('Hi, this is a <%s> node!: %s' % (self.itertag, ''.join(node.extract())))

        item = Item()
        item['id'] = node.select('@id').extract()
        item['name'] = node.select('name').extract()
        item['description'] = node.select('description').extract()
        return item

SPIDER = MySpider()

Basically what we did up there was creating a spider that downloads a feed from the given start_urls, and then iterates through each of its item tags, prints them out, and stores some random data in an Item.

CSVFeedSpider¶

class scrapy.contrib.spiders.CSVFeedSpider¶

This spider is very similar to the XMLFeedSpider, except that it iterates over rows, instead of nodes. The method that gets called in each iteration is parse_row().

delimiter¶: A string with the separator character for each field in the CSV file Defaults to ',' (comma).

headers¶: A list of the rows contained in the file CSV feed which will be used for extracting fields from it.

parse_row(response, row)¶: Receives a response and a dict (representing each row) with a key for each provided (or detected) header of the CSV file. This spider also gives the opportunity to override adapt_response and process_results methods for pre and post-processing purposes.

CSVFeedSpider example¶

Let’s see an example similar to the previous one, but using a CSVFeedSpider:

from scrapy import log
from scrapy.contrib.spiders import CSVFeedSpider
from myproject.items import TestItem

class MySpider(CSVFeedSpider):
    name = 'example.com'
    allowed_domains = ['example.com']
    start_urls = ['http://www.example.com/feed.csv']
    delimiter = ';'
    headers = ['id', 'name', 'description']

    def parse_row(self, response, row):
        log.msg('Hi, this is a row!: %r' % row)

        item = TestItem()
        item['id'] = row['id']
        item['name'] = row['name']
        item['description'] = row['description']
        return item

SPIDER = MySpider()