Clarified async documentation.
This commit is contained in:
parent
6ef4c8aa9f
commit
4216225480
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@ -144,7 +144,6 @@ databrowse
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datafile
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dataset
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datasets
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datastores
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datatype
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datetimes
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Debian
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@ -8,15 +8,15 @@ Asynchronous support
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Django has support for writing asynchronous ("async") views, along with an
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entirely async-enabled request stack if you are running under
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:doc:`ASGI </howto/deployment/asgi/index>` rather than WSGI. Async views will
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still work under WSGI, but with performance penalties, and without the ability
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to have efficient long-running requests.
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:doc:`ASGI </howto/deployment/asgi/index>`. Async views will still work under
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WSGI, but with performance penalties, and without the ability to have efficient
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long-running requests.
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We're still working on asynchronous support for the ORM and other parts of
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Django; you can expect to see these in future releases. For now, you can use
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the :func:`sync_to_async` adapter to interact with normal Django, as well as
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use a whole range of Python asyncio libraries natively. See below for more
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details.
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We're still working on async support for the ORM and other parts of Django.
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You can expect to see this in future releases. For now, you can use the
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:func:`sync_to_async` adapter to interact with the sync parts of Django.
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There is also a whole range of async-native Python libraries that you can
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integrate with.
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.. versionchanged:: 3.1
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@ -40,20 +40,21 @@ class-based view, this means making its ``__call__()`` method an ``async def``
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coroutine, ensure you set the ``_is_coroutine`` attribute of the view
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to ``asyncio.coroutines._is_coroutine`` so this function returns ``True``.
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Under a WSGI server, asynchronous views will run in their own, one-off event
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loop. This means that you can do things like parallel, async HTTP calls to APIs
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without any issues, but you will not get the benefits of an asynchronous
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request stack.
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Under a WSGI server, async views will run in their own, one-off event loop.
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This means you can use async features, like parallel async HTTP requests,
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without any issues, but you will not get the benefits of an async stack.
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If you want these benefits - which are mostly around the ability to service
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hundreds of connections without using any Python threads (enabling slow
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streaming, long-polling, and other exciting response types) - you will need to
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deploy Django using :doc:`ASGI </howto/deployment/asgi/index>` instead.
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The main benefits are the ability to service hundreds of connections without
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using Python threads. This allows you to use slow streaming, long-polling, and
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other exciting response types.
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If you want to use these, you will need to deploy Django using
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:doc:`ASGI </howto/deployment/asgi/index>` instead.
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.. warning::
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You will only get the benefits of a fully-asynchronous request stack if you
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have *no synchronous middleware* loaded into your site; if there is a piece
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have *no synchronous middleware* loaded into your site. If there is a piece
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of synchronous middleware, then Django must use a thread per request to
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safely emulate a synchronous environment for it.
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@ -63,22 +64,30 @@ deploy Django using :doc:`ASGI </howto/deployment/asgi/index>` instead.
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on debug logging for the ``django.request`` logger and look for log
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messages about *`"Synchronous middleware ... adapted"*.
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In either ASGI or WSGI mode, though, you can safely use asynchronous support to
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run code in parallel rather than serially, which is especially handy when
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dealing with external APIs or datastores.
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In both ASGI and WSGI mode, you can still safely use asynchronous support to
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run code in parallel rather than serially. This is especially handy when
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dealing with external APIs or data stores.
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If you want to call a part of Django that is still synchronous (like the ORM)
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you will need to wrap it in a :func:`sync_to_async` call, like this::
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If you want to call a part of Django that is still synchronous, like the ORM,
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you will need to wrap it in a :func:`sync_to_async` call. For example::
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from asgiref.sync import sync_to_async
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results = sync_to_async(MyModel.objects.get)(pk=123)
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results = sync_to_async(Blog.objects.get)(pk=123)
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You may find it easier to move any ORM code into its own function and call that
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entire function using :func:`sync_to_async`. If you accidentally try to call
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part of Django that is still synchronous-only from an async view, you will
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trigger Django's :ref:`asynchronous safety protection <async-safety>` to
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protect your data from corruption.
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entire function using :func:`sync_to_async`. For example::
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from asgiref.sync import sync_to_async
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@sync_to_async
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def get_blog(pk):
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return Blog.objects.select_related('author').get(pk=pk)
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If you accidentally try to call a part of Django that is still synchronous-only
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from an async view, you will trigger Django's
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:ref:`asynchronous safety protection <async-safety>` to protect your data from
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corruption.
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Performance
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-----------
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@ -88,56 +97,56 @@ WSGI, or a traditional sync view under ASGI), Django must emulate the other
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call style to allow your code to run. This context-switch causes a small
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performance penalty of around a millisecond.
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This is true of middleware as well, however. Django will attempt to minimize
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the number of context-switches. If you have an ASGI server, but all your
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middleware and views are synchronous, it will switch just once, before it
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This is also true of middleware. Django will attempt to minimize the number of
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context-switches between sync and async. If you have an ASGI server, but all
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your middleware and views are synchronous, it will switch just once, before it
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enters the middleware stack.
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If, however, you put synchronous middleware between an ASGI server and an
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However, if you put synchronous middleware between an ASGI server and an
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asynchronous view, it will have to switch into sync mode for the middleware and
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then back to asynchronous mode for the view, holding the synchronous thread
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open for middleware exception propagation. This may not be noticeable, but bear
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in mind that even adding a single piece of synchronous middleware can drag your
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whole async project down to running with one thread per request, and the
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associated performance penalties.
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then back to async mode for the view. Django will also hold the sync thread
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open for middleware exception propagation. This may not be noticeable at first,
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but adding this penalty of one thread per request can remove any async
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performance advantage.
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You should do your own performance testing to see what effect ASGI vs. WSGI has
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on your code. In some cases, there may be a performance increase even for
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purely-synchronous codebase under ASGI because the request-handling code is
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still all running asynchronously. In general, though, you will only want to
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enable ASGI mode if you have asynchronous code in your site.
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You should do your own performance testing to see what effect ASGI versus WSGI
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has on your code. In some cases, there may be a performance increase even for
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a purely synchronous codebase under ASGI because the request-handling code is
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still all running asynchronously. In general you will only want to enable ASGI
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mode if you have asynchronous code in your project.
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.. _async-safety:
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Async-safety
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Async safety
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============
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Certain key parts of Django are not able to operate safely in an asynchronous
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Certain key parts of Django are not able to operate safely in an async
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environment, as they have global state that is not coroutine-aware. These parts
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of Django are classified as "async-unsafe", and are protected from execution in
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an asynchronous environment. The ORM is the main example, but there are other
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parts that are also protected in this way.
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an async environment. The ORM is the main example, but there are other parts
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that are also protected in this way.
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If you try to run any of these parts from a thread where there is a *running
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event loop*, you will get a
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:exc:`~django.core.exceptions.SynchronousOnlyOperation` error. Note that you
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don't have to be inside an async function directly to have this error occur. If
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you have called a synchronous function directly from an asynchronous function
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without going through something like :func:`sync_to_async` or a threadpool,
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then it can also occur, as your code is still running in an asynchronous
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context.
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you have called a sync function directly from an async function,
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without using :func:`sync_to_async` or similar, then it can also occur. This is
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because your code is still running in a thread with an active event loop, even
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though it may not be declared as async code.
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If you encounter this error, you should fix your code to not call the offending
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code from an async context; instead, write your code that talks to async-unsafe
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in its own, synchronous function, and call that using
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:func:`asgiref.sync.sync_to_async`, or any other preferred way of running
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synchronous code in its own thread.
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code from an async context. Instead, write your code that talks to async-unsafe
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functions in its own, sync function, and call that using
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:func:`asgiref.sync.sync_to_async` (or any other way of running sync code in
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its own thread).
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If you are *absolutely* in dire need to run this code from an asynchronous
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context - for example, it is being forced on you by an external environment,
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and you are sure there is no chance of it being run concurrently (e.g. you are
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in a Jupyter_ notebook), then you can disable the warning with the
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``DJANGO_ALLOW_ASYNC_UNSAFE`` environment variable.
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You may still be forced to run sync code from an async context. For example,
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if the requirement is forced on you by an external environment, such as in a
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Jupyter_ notebook. If you are sure there is no chance of the code being run
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concurrently, and you *absolutely* need to run this sync code from an async
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context, then you can disable the warning by setting the
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``DJANGO_ALLOW_ASYNC_UNSAFE`` environment variable to any value.
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.. warning::
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@ -147,6 +156,8 @@ in a Jupyter_ notebook), then you can disable the warning with the
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If you need to do this from within Python, do that with ``os.environ``::
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import os
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os.environ["DJANGO_ALLOW_ASYNC_UNSAFE"] = "true"
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.. _Jupyter: https://jupyter.org/
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@ -154,11 +165,11 @@ If you need to do this from within Python, do that with ``os.environ``::
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Async adapter functions
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=======================
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It is necessary to adapt the calling style when calling synchronous code from
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an asynchronous context, or vice-versa. For this there are two adapter
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functions, made available from the ``asgiref.sync`` package:
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:func:`async_to_sync` and :func:`sync_to_async`. They are used to transition
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between sync and async calling styles while preserving compatibility.
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It is necessary to adapt the calling style when calling sync code from an async
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context, or vice-versa. For this there are two adapter functions, from the
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``asgiref.sync`` module: :func:`async_to_sync` and :func:`sync_to_async`. They
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are used to transition between the calling styles while preserving
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compatibility.
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These adapter functions are widely used in Django. The `asgiref`_ package
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itself is part of the Django project, and it is automatically installed as a
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@ -171,28 +182,31 @@ dependency when you install Django with ``pip``.
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.. function:: async_to_sync(async_function, force_new_loop=False)
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Wraps an asynchronous function and returns a synchronous function in its place.
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Can be used as either a direct wrapper or a decorator::
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Takes an async function and returns a sync function that wraps it. Can be used
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as either a direct wrapper or a decorator::
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from asgiref.sync import async_to_sync
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sync_function = async_to_sync(async_function)
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@async_to_sync
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async def async_function(...):
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async def get_data(...):
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...
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The asynchronous function is run in the event loop for the current thread, if
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one is present. If there is no current event loop, a new event loop is spun up
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specifically for the async function and shut down again once it completes. In
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either situation, the async function will execute on a different thread to the
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calling code.
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sync_get_data = async_to_sync(get_data)
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@async_to_sync
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async def get_other_data(...):
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...
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The async function is run in the event loop for the current thread, if one is
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present. If there is no current event loop, a new event loop is spun up
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specifically for the single async invocation and shut down again once it
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completes. In either situation, the async function will execute on a different
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thread to the calling code.
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Threadlocals and contextvars values are preserved across the boundary in both
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directions.
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:func:`async_to_sync` is essentially a more powerful version of the
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:py:func:`asyncio.run` function available in Python's standard library. As well
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:py:func:`asyncio.run` function in Python's standard library. As well
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as ensuring threadlocals work, it also enables the ``thread_sensitive`` mode of
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:func:`sync_to_async` when that wrapper is used below it.
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@ -201,8 +215,8 @@ as ensuring threadlocals work, it also enables the ``thread_sensitive`` mode of
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.. function:: sync_to_async(sync_function, thread_sensitive=False)
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Wraps a synchronous function and returns an asynchronous (awaitable) function
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in its place. Can be used as either a direct wrapper or a decorator::
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Takes a sync function and returns an async function that wraps it. Can be used
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as either a direct wrapper or a decorator::
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from asgiref.sync import sync_to_async
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@ -220,33 +234,32 @@ in its place. Can be used as either a direct wrapper or a decorator::
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Threadlocals and contextvars values are preserved across the boundary in both
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directions.
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Synchronous functions tend to be written assuming they all run in the main
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Sync functions tend to be written assuming they all run in the main
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thread, so :func:`sync_to_async` has two threading modes:
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* ``thread_sensitive=False`` (the default): the synchronous function will run
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in a brand new thread which is then closed once it completes.
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* ``thread_sensitive=False`` (the default): the sync function will run in a
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brand new thread which is then closed once the invocation completes.
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* ``thread_sensitive=True``: the synchronous function will run in the same
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thread as all other ``thread_sensitive`` functions, and this will be the main
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thread, if the main thread is synchronous and you are using the
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:func:`async_to_sync` wrapper.
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* ``thread_sensitive=True``: the sync function will run in the same thread as
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all other ``thread_sensitive`` functions. This will be the main thread, if
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the main thread is synchronous and you are using the :func:`async_to_sync`
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wrapper.
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Thread-sensitive mode is quite special, and does a lot of work to run all
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functions in the same thread. Note, though, that it *relies on usage of*
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:func:`async_to_sync` *above it in the stack* to correctly run things on the
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main thread. If you use ``asyncio.run()`` (or other options instead), it will
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fall back to just running thread-sensitive functions in a single, shared thread
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(but not the main thread).
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main thread. If you use ``asyncio.run()`` or similar, it will fall back to
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running thread-sensitive functions in a single, shared thread, but this will
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not be the main thread.
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The reason this is needed in Django is that many libraries, specifically
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database adapters, require that they are accessed in the same thread that they
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were created in, and a lot of existing Django code assumes it all runs in the
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same thread (e.g. middleware adding things to a request for later use by a
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view).
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were created in. Also a lot of existing Django code assumes it all runs in the
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same thread, e.g. middleware adding things to a request for later use in views.
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Rather than introduce potential compatibility issues with this code, we instead
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opted to add this mode so that all existing Django synchronous code runs in the
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same thread and thus is fully compatible with asynchronous mode. Note, that
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synchronous code will always be in a *different* thread to any async code that
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is calling it, so you should avoid passing raw database handles or other
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thread-sensitive references around in any new code you write.
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opted to add this mode so that all existing Django sync code runs in the same
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thread and thus is fully compatible with async mode. Note that sync code will
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always be in a *different* thread to any async code that is calling it, so you
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should avoid passing raw database handles or other thread-sensitive references
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around.
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@ -308,10 +308,10 @@ on your middleware factory function or class:
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asynchronous requests. Defaults to ``False``.
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If your middleware has both ``sync_capable = True`` and
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``async_capable = True``, then Django will pass it the request in whatever form
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it is currently in. You can work out what type of request you have by seeing
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if the ``get_response`` object you are passed is a coroutine function or not
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(using :py:func:`asyncio.iscoroutinefunction`).
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``async_capable = True``, then Django will pass it the request without
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converting it. In this case, you can work out if your middleware will receive
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async requests by checking if the ``get_response`` object you are passed is a
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coroutine function, using :py:func:`asyncio.iscoroutinefunction`.
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The ``django.utils.decorators`` module contains
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:func:`~django.utils.decorators.sync_only_middleware`,
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@ -328,8 +328,7 @@ methods, if they are provided, should also be adapted to match the sync/async
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mode. However, Django will individually adapt them as required if you do not,
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at an additional performance penalty.
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Here's an example of how to detect and adapt your middleware if it supports
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both::
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Here's an example of how to create a middleware function that supports both::
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import asyncio
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from django.utils.decorators import sync_and_async_middleware
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@ -205,25 +205,26 @@ in a test view. For example::
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.. _async-views:
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Asynchronous views
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==================
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Async views
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===========
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.. versionadded:: 3.1
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As well as being synchronous functions, views can also be asynchronous
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functions (``async def``). Django will automatically detect these and run them
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in an asynchronous context. You will need to be using an asynchronous (ASGI)
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server to get the full power of them, however.
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("async") functions, normally defined using Python's ``async def`` syntax.
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Django will automatically detect these and run them in an async context.
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However, you will need to use an async server based on ASGI to get their
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performance benefits.
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Here's an example of an asynchronous view::
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Here's an example of an async view::
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from django.http import HttpResponse
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import datetime
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from django.http import HttpResponse
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async def current_datetime(request):
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now = datetime.datetime.now()
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html = '<html><body>It is now %s.</body></html>' % now
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return HttpResponse(html)
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You can read more about Django's asynchronous support, and how to best use
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asynchronous views, in :doc:`/topics/async`.
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You can read more about Django's async support, and how to best use async
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views, in :doc:`/topics/async`.
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|
|
|
@ -1808,7 +1808,7 @@ creates.
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@mock.patch(...)
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@async_to_sync
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def test_my_thing(self):
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async def test_my_thing(self):
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...
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.. _topics-testing-email:
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