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Coroutines

Scrapy :ref:`supports <coroutine-support>` the :ref:`coroutine syntax <async>` (i.e. async def).

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Supported callables

The following callables may be defined as coroutines using async def, and hence use coroutine syntax (e.g. await, async for, async with):

Using Deferred-based APIs

In addition to native coroutine APIs Scrapy has some APIs that return a :class:`~twisted.internet.defer.Deferred` object or take a user-supplied function that returns a :class:`~twisted.internet.defer.Deferred` object. These APIs are also asynchronous but don't yet support native async def syntax. In the future we plan to add support for the async def syntax to these APIs or replace them with other APIs where changing the existing ones isn't possible.

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These APIs have a coroutine-based implementation and a Deferred-based one:

The following user-supplied methods can return :class:`~twisted.internet.defer.Deferred` objects (the methods that can also return coroutines are listed in :ref:`coroutine-support`):

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In most cases you can use these APIs in code that otherwise uses coroutines, by wrapping a :class:`~twisted.internet.defer.Deferred` object into a :class:`~asyncio.Future` object or vice versa. See :ref:`asyncio-await-dfd` for more information about this.

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For example: a custom scheduler needs to define an open() method that can return a :class:`~twisted.internet.defer.Deferred` object. You can write a method that works with Deferreds and returns one directly, or you can write a coroutine and convert it into a function that returns a Deferred with :func:`~scrapy.utils.defer.deferred_f_from_coro_f`.

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General usage

There are several use cases for coroutines in Scrapy.

Code that would return Deferreds when written for previous Scrapy versions, such as downloader middlewares and signal handlers, can be rewritten to be shorter and cleaner:

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.. code-block:: python

    from itemadapter import ItemAdapter


    class DbPipeline:
        def _update_item(self, data, item):
            adapter = ItemAdapter(item)
            adapter["field"] = data
            return item

        def process_item(self, item):
            adapter = ItemAdapter(item)
            dfd = db.get_some_data(adapter["id"])
            dfd.addCallback(self._update_item, item)
            return dfd

becomes:

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.. code-block:: python

    from itemadapter import ItemAdapter


    class DbPipeline:
        async def process_item(self, item):
            adapter = ItemAdapter(item)
            adapter["field"] = await db.get_some_data(adapter["id"])
            return item

Coroutines may be used to call asynchronous code. This includes other coroutines, functions that return Deferreds and functions that return :term:`awaitable objects <awaitable>` such as :class:`~asyncio.Future`. This means you can use many useful Python libraries providing such code:

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.. code-block:: python

    class MySpiderDeferred(Spider):
        # ...
        async def parse(self, response):
            additional_response = await treq.get("https://additional.url")
            additional_data = await treq.content(additional_response)
            # ... use response and additional_data to yield items and requests


    class MySpiderAsyncio(Spider):
        # ...
        async def parse(self, response):
            async with aiohttp.ClientSession() as session:
                async with session.get("https://additional.url") as additional_response:
                    additional_data = await additional_response.text()
            # ... use response and additional_data to yield items and requests

Note

Many libraries that use coroutines, such as aio-libs, require the :mod:`asyncio` loop and to use them you need to :doc:`enable asyncio support in Scrapy<asyncio>`.

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Note

If you want to await on Deferreds while using the asyncio reactor, you need to :ref:`wrap them<asyncio-await-dfd>`.

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Common use cases for asynchronous code include:

Inline requests

The spider below shows how to send a request and await its response all from within a spider callback:

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.. code-block:: python

    from scrapy import Spider, Request


    class SingleRequestSpider(Spider):
        name = "single"
        start_urls = ["https://example.org/product"]

        async def parse(self, response, **kwargs):
            additional_request = Request("https://example.org/price")
            additional_response = await self.crawler.engine.download_async(
                additional_request
            )
            yield {
                "h1": response.css("h1").get(),
                "price": additional_response.css("#price").get(),
            }

You can also send multiple requests in parallel:

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.. code-block:: python

    import asyncio

    from scrapy import Spider, Request


    class MultipleRequestsSpider(Spider):
        name = "multiple"
        start_urls = ["https://example.com/product"]

        async def parse(self, response, **kwargs):
            additional_requests = [
                Request("https://example.com/price"),
                Request("https://example.com/color"),
            ]
            tasks = []
            for r in additional_requests:
                task = self.crawler.engine.download_async(r)
                tasks.append(task)
            responses = await asyncio.gather(*tasks)
            yield {
                "h1": response.css("h1::text").get(),
                "price": responses[0].css(".price::text").get(),
                "color": responses[1].css(".color::text").get(),
            }
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