# Spiders

Spiders are classes which define how a certain site (or a group of sites) will be scraped, including how to perform the crawl (i.e. follow links) and how to extract structured data from their pages (i.e. scraping items). In other words, Spiders are the place where you define the custom behaviour for crawling and parsing pages for a particular site (or, in some cases, a group of sites).

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

1. 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 iterating the `start()` method, which by default yields a `Request` object for each URL in the `start_urls` spider attribute, with the `parse` method set as `callback` function to handle each `Response`.

2. In the callback function, you parse the response (web page) and return item objects, `Request` objects, or an iterable of these objects. Those Requests will also contain a callback (maybe the same) and will then be downloaded by Scrapy and then their response handled by the specified callback.

3. In callback functions, you parse the page contents, typically using Selectors (but you can also use BeautifulSoup, lxml or whatever mechanism you prefer) and generate items with the parsed data.

4. Finally, the items returned from the spider will be typically persisted to a database (in some Item Pipeline) or written to a file using Feed exports.

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

## scrapy.Spider

class scrapy.spiders.Spider

class scrapy.Spider(*args: Any, **kwargs: Any)

  Base class that any spider must subclass.

  It provides a default `start()` implementation that sends requests based on the `start_urls` class attribute and calls the `parse()` method for each response.

  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.

    If the spider scrapes a single domain, a common practice is to name the spider after the domain, with or without the TLD. So, for example, a spider that crawls `mywebsite.com` would often be called `mywebsite`.

  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 (or their subdomains) won’t be followed if `OffsiteMiddleware` is enabled.

    Let’s say your target url is `https://www.example.com/1.html`, then add `'example.com'` to the list.

  start_urls: list[str]

    Start URLs. See `start()`.

  custom_settings

    A dictionary of settings that will be overridden from the project wide configuration when running this spider. It must be defined as a class attribute since the settings are updated before instantiation.

    For a list of available built-in settings see: Built-in settings reference.

  crawler

    This attribute is set by the `from_crawler()` class method after initializing the class, and links to the `Crawler` object to which this spider instance is bound.

    Crawlers encapsulate a lot of components in the project for their single entry access (such as extensions, middlewares, signals managers, etc). See Crawler API to know more about them.

  settings

    Configuration for running this spider. This is a `Settings` instance, see the Settings topic for a detailed introduction on this subject.

  logger

    Python logger created with the Spider’s `name`. You can use it to send log messages through it as described on Logging from Spiders.

  state

    A dict you can use to persist some spider state between batches. See Keeping persistent state between batches to know more about it.

  from_crawler(crawler, *args, **kwargs)

    This is the class method used by Scrapy to create your spiders.

    You probably won’t need to override this directly because the default implementation acts as a proxy to the `__init__()` method, calling it with the given arguments `args` and named arguments `kwargs`.

    Nonetheless, this method sets the `crawler` and `settings` attributes in the new instance so they can be accessed later inside the spider’s code.

    Changed in version 2.11: The settings in `crawler.settings` can now be modified in this method, which is handy if you want to modify them based on arguments. As a consequence, these settings aren’t the final values as they can be modified later by e.g. add-ons. For the same reason, most of the `Crawler` attributes aren’t initialized at this point.

    The final settings and the initialized `Crawler` attributes are available in the `start()` method, handlers of the `engine_started` signal and later.

    Parameters:

      - crawler (`Crawler` instance) – crawler to which the spider will be bound

      - args (list) – arguments passed to the `__init__()` method

      - kwargs (dict) – keyword arguments passed to the `__init__()` method

  classmethod update_settings(settings)

    The `update_settings()` method is used to modify the spider’s settings and is called during initialization of a spider instance.

    It takes a `Settings` object as a parameter and can add or update the spider’s configuration values. This method is a class method, meaning that it is called on the `Spider` class and allows all instances of the spider to share the same configuration.

    While per-spider settings can be set in `custom_settings`, using `update_settings()` allows you to dynamically add, remove or change settings based on other settings, spider attributes or other factors and use setting priorities other than `'spider'`. Also, it’s easy to extend `update_settings()` in a subclass by overriding it, while doing the same with `custom_settings` can be hard.

    For example, suppose a spider needs to modify `FEEDS`:

        import scrapy

        class MySpider(scrapy.Spider):
            name = "myspider"
            custom_feed = {
                "/home/user/documents/items.json": {
                    "format": "json",
                    "indent": 4,
                }
            }

            @classmethod
            def update_settings(cls, settings):
                super().update_settings(settings)
                settings.setdefault("FEEDS", {}).update(cls.custom_feed)

  async start() → AsyncIterator[Any]

    Yield the initial `Request` objects to send.

    Added in version 2.13.

    For example:

        from scrapy import Request, Spider

        class MySpider(Spider):
            name = "myspider"

            async def start(self):
                yield Request("https://toscrape.com/")

    The default implementation reads URLs from `start_urls` and yields a request for each with `dont_filter` enabled. It is functionally equivalent to:

        async def start(self):
            for url in self.start_urls:
                yield Request(url, dont_filter=True)

    You can also yield items. For example:

        async def start(self):
            yield {"foo": "bar"}

    To write spiders that work on Scrapy versions lower than 2.13, define also a synchronous `start_requests()` method that returns an iterable. For example:

        def start_requests(self):
            yield Request("https://toscrape.com/")

    See also

    Start requests

  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 `Spider` class.

    This method, as well as any other Request callback, must return a `Request` object, an item object, an iterable of `Request` objects and/or item objects, or `None`.

    Parameters:

      response (`Response`) – the response to parse

  log(message[, level, component])

    Wrapper that sends a log message through the Spider’s `logger`, kept for backward compatibility. For more information see Logging from Spiders.

  closed(reason)

    Called when the spider closes. This method provides a shortcut to signals.connect() for the `spider_closed` signal.

Let’s see an example:

    import scrapy

    class MySpider(scrapy.Spider):
        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.logger.info("A response from %s just arrived!", response.url)

Return multiple Requests and items from a single callback:

    import scrapy

    class MySpider(scrapy.Spider):
        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):
            for h3 in response.xpath("//h3").getall():
                yield {"title": h3}

            for href in response.xpath("//a/@href").getall():
                yield scrapy.Request(response.urljoin(href), self.parse)

Instead of `start_urls` you can use `start()` directly; to give data more structure you can use `Item` objects:

    import scrapy
    from myproject.items import MyItem

    class MySpider(scrapy.Spider):
        name = "example.com"
        allowed_domains = ["example.com"]

        async def start(self):
            yield scrapy.Request("http://www.example.com/1.html", self.parse)
            yield scrapy.Request("http://www.example.com/2.html", self.parse)
            yield scrapy.Request("http://www.example.com/3.html", self.parse)

        def parse(self, response):
            for h3 in response.xpath("//h3").getall():
                yield MyItem(title=h3)

            for href in response.xpath("//a/@href").getall():
                yield scrapy.Request(response.urljoin(href), self.parse)

## Spider arguments

Spiders can receive arguments that modify their behaviour. Some common uses for spider arguments are to define the start URLs or to restrict the crawl to certain sections of the site, but they can be used to configure any functionality of the spider.

Spider arguments are passed through the `crawl` command using the `-a` option. For example:

    scrapy crawl myspider -a category=electronics

Spiders can access arguments in their __init__ methods:

    import scrapy

    class MySpider(scrapy.Spider):
        name = "myspider"

        def __init__(self, category=None, *args, **kwargs):
            super(MySpider, self).__init__(*args, **kwargs)
            self.start_urls = [f"http://www.example.com/categories/{category}"]
            # ...

The default __init__ method will take any spider arguments and copy them to the spider as attributes. The above example can also be written as follows:

    import scrapy

    class MySpider(scrapy.Spider):
        name = "myspider"

        async def start(self):
            yield scrapy.Request(f"http://www.example.com/categories/{self.category}")

If you are running Scrapy from a script, you can specify spider arguments when calling `CrawlerProcess.crawl` or `CrawlerRunner.crawl`:

    process = CrawlerProcess()
    process.crawl(MySpider, category="electronics")

Keep in mind that spider arguments are only strings. The spider will not do any parsing on its own. If you were to set the `start_urls` attribute from the command line, you would have to parse it on your own into a list using something like `ast.literal_eval()` or `json.loads()` and then set it as an attribute. Otherwise, you would cause iteration over a `start_urls` string (a very common python pitfall) resulting in each character being seen as a separate url.

A valid use case is to set the http auth credentials used by `HttpAuthMiddleware`:

    scrapy crawl myspider -a http_user=myuser -a http_pass=mypassword

Spider arguments can also be passed through the Scrapyd `schedule.json` API. See Scrapyd documentation.

### scrapy-spider-metadata parameters

Another alternative to pass spider arguments is the library scrapy-spider-metadata.

This allows for Scrapy spiders to define, validate, document and pre-process their arguments as Pydantic models.

The example shows how to define typed parameters where a string argument is automatically converted to an integer:

    import scrapy
    from pydantic import BaseModel
    from scrapy_spider_metadata import Args

    class MyParams(BaseModel):
        pages: int

    class BookSpider(Args[MyParams], scrapy.Spider):
        name = "bookspider"
        start_urls = ["http://books.toscrape.com/catalogue"]

        async def start(self):
            for start_url in self.start_urls:
                for index in range(1, self.args.pages + 1):
                    yield scrapy.Request(f"{start_url}/page-{index}.html")

        def parse(self, response):
            book_links = response.css("article.product_pod h3 a::attr(href)").getall()
            for book_link in book_links:
                yield response.follow(book_link, self.parse_book)

        def parse_book(self, response):
            yield {
                "title": response.css("h1::text").get(),
                "price": response.css("p.price_color::text").get(),
            }

This spider can be called from the command line:

    scrapy crawl bookspider -a pages=2

## Start requests

Start requests are `Request` objects yielded from the `start()` method of a spider or from the `process_start()` method of a spider middleware.

See also

Start request order

### Delaying start request iteration

You can override the `start()` method as follows to pause its iteration whenever there are scheduled requests:

    async def start(self):
        async for item_or_request in super().start():
            if self.crawler.engine.needs_backout():
                await self.crawler.signals.wait_for(signals.scheduler_empty)
            yield item_or_request

This can help minimize the number of requests in the scheduler at any given time, to minimize resource usage (memory or disk, depending on `JOBDIR`).

## Generic Spiders

Scrapy comes with some useful generic spiders that you can use to subclass your spiders from. Their aim is to provide convenient functionality for a few common scraping cases, like following all links on a site based on certain rules, crawling from Sitemaps, or parsing an XML/CSV feed.

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

    import scrapy

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

### CrawlSpider

class scrapy.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 needed for more custom functionality, or just implement your own spider.

  Apart from the attributes inherited from Spider (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. If multiple rules match the same link, the first one will be used, according to the order they’re defined in this attribute.

  This spider also exposes an overridable method:

  parse_start_url(response, **kwargs)

    This method is called for each response produced for the URLs in the spider’s `start_urls` attribute. It allows to parse the initial responses and must return either an item object, a `Request` object, or an iterable containing any of them.

#### Crawling rules

class scrapy.spiders.Rule(link_extractor: LinkExtractor | None = None, callback: CallbackT | str | None = None, cb_kwargs: dict[str, Any] | None = None, follow: bool | None = None, process_links: ProcessLinksT | str | None = None, process_request: ProcessRequestT | str | None = None, errback: Callable[[Failure], Any] | str | None = None)

  `link_extractor` is a Link Extractor object which defines how links will be extracted from each crawled page. Each produced link will be used to generate a `Request` object, which will contain the link’s text in its `meta` dictionary (under the `link_text` key). If omitted, a default link extractor created with no arguments will be used, resulting in all links being extracted.

  `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 either a single instance or an iterable of item objects and/or `Request` objects (or any subclass of them). As mentioned above, the received `Response` object will contain the text of the link that produced the `Request` in its `meta` dictionary (under the `link_text` key)

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

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

  `process_request` 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 every `Request` extracted by this rule. This callable should take said request as first argument and the `Response` from which the request originated as second argument. It must return a `Request` object or `None` (to filter out the request).

  `errback` is a callable or a string (in which case a method from the spider object with that name will be used) to be called if any exception is raised while processing a request generated by the rule. It receives a `Twisted Failure` instance as first parameter.

  Warning

  Because of its internal implementation, you must explicitly set callbacks for new requests when writing `CrawlSpider`-based spiders; unexpected behaviour can occur otherwise.

#### CrawlSpider example

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

    import scrapy
    from scrapy.spiders import CrawlSpider, Rule
    from scrapy.linkextractors import LinkExtractor

    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(LinkExtractor(allow=(r"category\.php",), deny=(r"subsection\.php",))),
            # Extract links matching 'item.php' and parse them with the spider's method parse_item
            Rule(LinkExtractor(allow=(r"item\.php",)), callback="parse_item"),
        )

        def parse_item(self, response):
            self.logger.info("Hi, this is an item page! %s", response.url)
            item = scrapy.Item()
            item["id"] = response.xpath('//td[@id="item_id"]/text()').re(r"ID: (\d+)")
            item["name"] = response.xpath('//td[@id="item_name"]/text()').get()
            item["description"] = response.xpath(
                '//td[@id="item_description"]/text()'
            ).get()
            item["link_text"] = response.meta["link_text"]
            url = response.xpath('//td[@id="additional_data"]/@href').get()
            return response.follow(
                url, self.parse_additional_page, cb_kwargs=dict(item=item)
            )

        def parse_additional_page(self, response, item):
            item["additional_data"] = response.xpath(
                '//p[@id="additional_data"]/text()'
            ).get()
            return item

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 an `Item` will be filled with it.

### XMLFeedSpider

class scrapy.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.

  To set 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 `Selector`. 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 `Selector`. 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 overridable methods too:

  adapt_response(response)

    A method that receives the response as soon as it arrives from the spider middleware, before the spider starts parsing it. It can be used to modify the response body before parsing it. This method receives a response and also returns a 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 `Selector` for each node. Overriding this method is mandatory. Otherwise, your spider won’t work. This method must return an 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 those results. It must return a list of results (items or requests).

  Warning

  Because of its internal implementation, you must explicitly set callbacks for new requests when writing `XMLFeedSpider`-based spiders; unexpected behaviour can occur otherwise.

#### XMLFeedSpider example

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

    from scrapy.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 unnecessary, since it's the default value
        itertag = "item"

        def parse_node(self, response, node):
            self.logger.info(
                "Hi, this is a <%s> node!: %s", self.itertag, "".join(node.getall())
            )

            item = TestItem()
            item["id"] = node.xpath("@id").get()
            item["name"] = node.xpath("name").get()
            item["description"] = node.xpath("description").get()
            return item

Basically what we did up there was to create 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.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).

  quotechar

    A string with the enclosure character for each field in the CSV file Defaults to `'"'` (quotation mark).

  headers

    A list of the column names in the CSV file.

  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.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 = ";"
        quotechar = "'"
        headers = ["id", "name", "description"]

        def parse_row(self, response, row):
            self.logger.info("Hi, this is a row!: %r", row)

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

### SitemapSpider

class scrapy.spiders.SitemapSpider

  SitemapSpider allows you to crawl a site by discovering the URLs using Sitemaps.

  It supports nested sitemaps and discovering sitemap urls from robots.txt.

  sitemap_urls

    A list of urls pointing to the sitemaps whose urls you want to crawl.

    You can also point to a robots.txt and it will be parsed to extract sitemap urls from it.

  sitemap_rules

    A list of tuples `(regex, callback)` where:

    - `regex` is a regular expression to match urls extracted from sitemaps. `regex` can be either a str or a compiled regex object.

    - callback is the callback to use for processing the urls that match the regular expression. `callback` can be a string (indicating the name of a spider method) or a callable.

    For example:

        sitemap_rules = [('/product/', 'parse_product')]

    Rules are applied in order, and only the first one that matches will be used.

    If you omit this attribute, all urls found in sitemaps will be processed with the `parse` callback.

  sitemap_follow

    A list of regexes of sitemap that should be followed. This is only for sites that use Sitemap index files that point to other sitemap files.

    By default, all sitemaps are followed.

  sitemap_alternate_links

    Specifies if alternate links for one `url` should be followed. These are links for the same website in another language passed within the same `url` block.

    For example:

        <url>
            <loc>http://example.com/</loc>
            <xhtml:link rel="alternate" hreflang="de" href="http://example.com/de"/>
        </url>

    With `sitemap_alternate_links` set, this would retrieve both URLs. With `sitemap_alternate_links` disabled, only `http://example.com/` would be retrieved.

    Default is `sitemap_alternate_links` disabled.

  sitemap_filter(entries)

    This is a filter function that could be overridden to select sitemap entries based on their attributes.

    For example:

        <url>
            <loc>http://example.com/</loc>
            <lastmod>2005-01-01</lastmod>
        </url>

    We can define a `sitemap_filter` function to filter `entries` by date:

        from datetime import datetime
        from scrapy.spiders import SitemapSpider

        class FilteredSitemapSpider(SitemapSpider):
            name = "filtered_sitemap_spider"
            allowed_domains = ["example.com"]
            sitemap_urls = ["http://example.com/sitemap.xml"]

            def sitemap_filter(self, entries):
                for entry in entries:
                    date_time = datetime.strptime(entry["lastmod"], "%Y-%m-%d")
                    if date_time.year >= 2005:
                        yield entry

    This would retrieve only `entries` modified on 2005 and the following years.

    Entries are dict objects extracted from the sitemap document. Usually, the key is the tag name and the value is the text inside it.

    It’s important to notice that:

    - as the loc attribute is required, entries without this tag are discarded

    - alternate links are stored in a list with the key `alternate` (see `sitemap_alternate_links`)

    - namespaces are removed, so lxml tags named as `{namespace}tagname` become only `tagname`

    If you omit this method, all entries found in sitemaps will be processed, observing other attributes and their settings.

#### SitemapSpider examples

Simplest example: process all urls discovered through sitemaps using the `parse` callback:

    from scrapy.spiders import SitemapSpider

    class MySpider(SitemapSpider):
        sitemap_urls = ["http://www.example.com/sitemap.xml"]

        def parse(self, response):
            pass  # ... scrape item here ...

Process some urls with certain callback and other urls with a different callback:

    from scrapy.spiders import SitemapSpider

    class MySpider(SitemapSpider):
        sitemap_urls = ["http://www.example.com/sitemap.xml"]
        sitemap_rules = [
            ("/product/", "parse_product"),
            ("/category/", "parse_category"),
        ]

        def parse_product(self, response):
            pass  # ... scrape product ...

        def parse_category(self, response):
            pass  # ... scrape category ...

Follow sitemaps defined in the robots.txt file and only follow sitemaps whose url contains `/sitemap_shop`:

    from scrapy.spiders import SitemapSpider

    class MySpider(SitemapSpider):
        sitemap_urls = ["http://www.example.com/robots.txt"]
        sitemap_rules = [
            ("/shop/", "parse_shop"),
        ]
        sitemap_follow = ["/sitemap_shops"]

        def parse_shop(self, response):
            pass  # ... scrape shop here ...

Combine SitemapSpider with other sources of urls:

    from scrapy.spiders import SitemapSpider

    class MySpider(SitemapSpider):
        sitemap_urls = ["http://www.example.com/robots.txt"]
        sitemap_rules = [
            ("/shop/", "parse_shop"),
        ]

        other_urls = ["http://www.example.com/about"]

        async def start(self):
            async for item_or_request in super().start():
                yield item_or_request
            for url in self.other_urls:
                yield Request(url, self.parse_other)

        def parse_shop(self, response):
            pass  # ... scrape shop here ...

        def parse_other(self, response):
            pass  # ... scrape other here ...