= SEP-016: Leg Spider =

[[PageOutline(2-5,Contents)]]

||'''SEP:'''||16||
||'''Title:'''||Leg Spider||
||'''Author:'''||Insophia Team||
||'''Created:'''||2010-06-03||
||'''Status'''||Superseded by [wiki:SEP-018]||

== Introduction ==

This SEP introduces a new kind of Spider called {{{LegSpider}}} which provides modular functionality which can be plugged to different spiders.

== Rationale ==

The purpose of Leg Spiders is to define an architecture for building spiders based on smaller well-tested components (aka. Legs) that can be combined to achieve the desired functionality. These reusable components will benefit all Scrapy users by building a repository of well-tested components (legs) that can be shared among different spiders and projects. Some of them will come bundled with Scrapy.

The Legs themselves can be also combined with sub-legs, in a hierarchical fashion. Legs are also spiders themselves, hence the name "Leg Spider".

== {{{LegSpider}}} API ==

A {{{LegSpider}}} is a {{{BaseSpider}}} subclass that adds the following attributes and methods:

 * {{{legs}}}
   * legs composing this spider
 * {{{process_response(response)}}}
   * Process a (downloaded) response and return a list of requests and items
 * {{{process_request(request)}}}
   * Process a request after it has been extracted and before returning it from the spider
 * {{{process_item(item)}}}
   * Process an item after it has been extracted and before returning it from the spider
 * {{{set_spider()}}}
   * Defines the main spider associated with this Leg Spider, which is often used to configure the Leg Spider behavior.

== How Leg Spiders work ==

 1. Each Leg Spider has zero or many Leg Spiders associated with it. When a response arrives, the Leg Spider process it with its {{{process_response}}} method and also the {{{process_response}}} method of all its "sub leg spiders". Finally, the output of all of them is combined to produce the final aggregated output.
 2. Each element of the aggregated output of {{{process_response}}} is processed with either {{{process_item}}} or {{{process_request}}} before being returned from the spider. Similar to {{{process_response}}}, each item/request is processed with all {{{process_{request,item}}}} of the leg spiders composing the spider, and also with those of the spider itself.

== Leg Spider examples ==

=== Regex (HTML) Link Extractor ===

A typical application of LegSpider's is to build Link Extractors. For example:

{{{
#!python
class RegexHtmlLinkExtractor(LegSpider):

    def process_response(self, response):
        if isinstance(response, HtmlResponse):
            allowed_regexes = self.spider.url_regexes_to_follow
            # extract urls to follow using allowed_regexes
            return [Request(x) for x in urls_to_follow]

class MySpider(LegSpider):

    legs = [RegexHtmlLinkExtractor()]
    url_regexes_to_follow = ['/product.php?.*']

    def parse_response(self, response):
        # parse response and extract items
        return items
}}}

=== RSS2 link extractor ===

This is a Leg Spider that can be used for following links from RSS2 feeds.

{{{
#!python
class Rss2LinkExtractor(LegSpider):

    def process_response(self, response):
        if response.headers.get('Content-type') == 'application/rss+xml':
            xs = XmlXPathSelector(response)
            urls = xs.select("//item/link/text()").extract()
            return [Request(x) for x in urls]
}}}

=== Callback dispatcher based on rules ===

Another example could be to build a callback dispatcher based on rules:

{{{
#!python
class CallbackRules(LegSpider):

    def __init__(self, *a, **kw):
        super(CallbackRules, self).__init__(*a, **kw)
        for regex, method_name in self.spider.callback_rules.items():
            r = re.compile(regex)
            m = getattr(self.spider, method_name, None)
            if m:
                self._rules[r] = m

    def process_response(self, response):
        for regex, method in self._rules.items():
            m = regex.search(response.url)
            if m:
                return method(response)
        return []

class MySpider(LegSpider):

    legs = [CallbackRules()]
    callback_rules = {
        '/product.php.*': 'parse_product',
        '/category.php.*': 'parse_category',
    }

    def parse_product(self, response):
        # parse reponse and populate item
        return item
}}}

=== URL Canonicalizers ===

Another example could be for building URL canonicalizers:

{{{
#!python
class CanonializeUrl(LegSpider):

    def process_request(self, request):
        curl = canonicalize_url(request.url, rules=self.spider.canonicalization_rules)
        return request.replace(url=curl)

class MySpider(LegSpider):

    legs = [CanonicalizeUrl()]
    canonicalization_rules = ['sort-query-args', 'normalize-percent-encoding', ...]

    # ...
}}}

=== Setting item identifier ===

Another example could be for setting a unique identifier to items, based on certain fields:

{{{
#!python
class ItemIdSetter(LegSpider):

    def process_item(self, item):
        id_field = self.spider.id_field
        id_fields_to_hash = self.spider.id_fields_to_hash
        item[id_field] = make_hash_based_on_fields(item, id_fields_to_hash)
        return item

class MySpider(LegSpider):

    legs = [ItemIdSetter()]
    id_field = 'guid'
    id_fields_to_hash = ['supplier_name', 'supplier_id']

    def process_response(self, item):
        # extract item from response
        return item
}}}

=== Combining multiple leg spiders ===

Here's an example that combines functionality from multiple leg spiders:

{{{
#!python
class MySpider(LegSpider):

    legs = [RegexLinkExtractor(), ParseRules(), CanonicalizeUrl(), ItemIdSetter()]

    url_regexes_to_follow = ['/product.php?.*']

    parse_rules = {
        '/product.php.*': 'parse_product',
        '/category.php.*': 'parse_category',
    }

    canonicalization_rules = ['sort-query-args', 'normalize-percent-encoding', ...]

    id_field = 'guid'
    id_fields_to_hash = ['supplier_name', 'supplier_id']

    def process_product(self, item):
        # extract item from response
        return item

    def process_category(self, item):
        # extract item from response
        return item
}}}



== Leg Spiders vs Spider middlewares ==

A common question that would arise is when one should use Leg Spiders and when to use Spider middlewares. Leg Spiders functionality is meant to implement spider-specific functionality, like link extraction which has custom rules per spider. Spider middlewares, on the other hand, are meant to implement global functionality.

== When not to use Leg Spiders ==

Leg Spiders are not a silver bullet to implement all kinds of spiders, so it's important to keep in mind their scope and limitations, such as:

 * Leg Spiders can't filter duplicate requests, since they don't have access to all requests at the same time. This functionality should be done in a spider or scheduler middleware.
 * Leg Spiders are meant to be used for spiders whose behavior (requests & items to extract) depends only on the current page and not previously crawled pages (aka. "context-free spiders"). If your spider has some custom logic with chained downloads (for example, multi-page items) then Leg Spiders may not be a good fit.

== {{{LegSpider}}} proof-of-concept implementation ==

Here's a proof-of-concept implementation of {{{LegSpider}}}:

{{{
#!python
from scrapy.http import Request
from scrapy.item import BaseItem
from scrapy.spider import BaseSpider
from scrapy.utils.spider import iterate_spider_output


class LegSpider(BaseSpider):
    """A spider made of legs"""

    legs = []

    def __init__(self, *args, **kwargs):
        super(LegSpider, self).__init__(*args, **kwargs)
        self._legs = [self] + self.legs[:]
        for l in self._legs:
            l.set_spider(self)

    def parse(self, response):
        res = self._process_response(response)
        for r in res:
            if isinstance(r, BaseItem):
                yield self._process_item(r)
            else:
                yield self._process_request(r)

    def process_response(self, response):
        return []

    def process_request(self, request):
        return request

    def process_item(self, item):
        return item

    def set_spider(self, spider):
        self.spider = spider

    def _process_response(self, response):
        res = []
        for l in self._legs:
            res.extend(iterate_spider_output(l.process_response(response)))
        return res

    def _process_request(self, request):
        for l in self._legs:
            request = l.process_request(request)
        return request

    def _process_item(self, item):
        for l in self._legs:
            item = l.process_item(item)
        return item
}}}