django/docs/topics/async.txt

====================
Asynchronous support
====================

.. versionadded:: 3.0

.. currentmodule:: asgiref.sync

Django has developing support for asynchronous ("async") Python, but does not
yet support asynchronous views or middleware; they will be coming in a future
release.

There is limited support for other parts of the async ecosystem; namely, Django
can natively talk :doc:`ASGI </howto/deployment/asgi/index>`, and some async
safety support.

.. _async-safety:

Async-safety
============

Certain key parts of Django are not able to operate safely in an asynchronous
environment, as they have global state that is not coroutine-aware. These parts
of Django are classified as "async-unsafe", and are protected from execution in
an asynchronous environment. The ORM is the main example, but there are other
parts that are also protected in this way.

If you try to run any of these parts from a thread where there is a *running
event loop*, you will get a
:exc:`~django.core.exceptions.SynchronousOnlyOperation` error. Note that you
don't have to be inside an async function directly to have this error occur. If
you have called a synchronous function directly from an asynchronous function
without going through something like :func:`sync_to_async` or a threadpool,
then it can also occur, as your code is still running in an asynchronous
context.

If you encounter this error, you should fix your code to not call the offending
code from an async context; instead, write your code that talks to async-unsafe
in its own, synchronous function, and call that using
:func:`asgiref.sync.async_to_sync`, or any other preferred way of running
synchronous code in its own thread.

If you are *absolutely* in dire need to run this code from an asynchronous
context - for example, it is being forced on you by an external environment,
and you are sure there is no chance of it being run concurrently (e.g. you are
in a Jupyter_ notebook), then you can disable the warning with the
``DJANGO_ALLOW_ASYNC_UNSAFE`` environment variable.

.. warning::

    If you enable this option and there is concurrent access to the
    async-unsafe parts of Django, you may suffer data loss or corruption. Be
    very careful and do not use this in production environments.

If you need to do this from within Python, do that with ``os.environ``::

    os.environ["DJANGO_ALLOW_ASYNC_UNSAFE"] = "true"

.. _Jupyter: https://jupyter.org/

Async adapter functions
=======================

It is necessary to adapt the calling style when calling synchronous code from
an asynchronous context, or vice-versa. For this there are two adapter
functions, made available from the ``asgiref.sync`` package:
:func:`async_to_sync` and :func:`sync_to_async`. They are used to transition
between sync and async calling styles while preserving compatibility.

These adapter functions are widely used in Django. The `asgiref`_ package
itself is part of the Django project, and it is automatically installed as a
dependency when you install Django with ``pip``.

.. _asgiref: https://pypi.org/project/asgiref/

``async_to_sync()``
-------------------

.. function:: async_to_sync(async_function, force_new_loop=False)

Wraps an asynchronous function and returns a synchronous function in its place.
Can be used as either a direct wrapper or a decorator::

    from asgiref.sync import async_to_sync

    sync_function = async_to_sync(async_function)

    @async_to_sync
    async def async_function(...):
        ...

The asynchronous function is run in the event loop for the current thread, if
one is present. If there is no current event loop, a new event loop is spun up
specifically for the async function and shut down again once it completes. In
either situation, the async function will execute on a different thread to the
calling code.

Threadlocals and contextvars values are preserved across the boundary in both
directions.

:func:`async_to_sync` is essentially a more powerful version of the
:py:func:`asyncio.run` function available in Python's standard library. As well
as ensuring threadlocals work, it also enables the ``thread_sensitive`` mode of
:func:`sync_to_async` when that wrapper is used below it.

``sync_to_async()``
-------------------

.. function:: sync_to_async(sync_function, thread_sensitive=False)

Wraps a synchronous function and returns an asynchronous (awaitable) function
in its place. Can be used as either a direct wrapper or a decorator::

    from asgiref.sync import sync_to_async

    async_function = sync_to_async(sync_function)
    async_function = sync_to_async(sensitive_sync_function, thread_sensitive=True)

    @sync_to_async
    def sync_function(...):
        ...

    @sync_to_async(thread_sensitive=True)
    def sensitive_sync_function(...):
        ...

Threadlocals and contextvars values are preserved across the boundary in both
directions.

Synchronous functions tend to be written assuming they all run in the main
thread, so :func:`sync_to_async` has two threading modes:

* ``thread_sensitive=False`` (the default): the synchronous function will run
  in a brand new thread which is then closed once it completes.

* ``thread_sensitive=True``: the synchronous function will run in the same
  thread as all other ``thread_sensitive`` functions, and this will be the main
  thread, if the main thread is synchronous and you are using the
  :func:`async_to_sync` wrapper.

Thread-sensitive mode is quite special, and does a lot of work to run all
functions in the same thread. Note, though, that it *relies on usage of*
:func:`async_to_sync` *above it in the stack* to correctly run things on the
main thread. If you use ``asyncio.run()`` (or other options instead), it will
fall back to just running thread-sensitive functions in a single, shared thread
(but not the main thread).

The reason this is needed in Django is that many libraries, specifically
database adapters, require that they are accessed in the same thread that they
were created in, and a lot of existing Django code assumes it all runs in the
same thread (e.g. middleware adding things to a request for later use by a
view).

Rather than introduce potential compatibility issues with this code, we instead
opted to add this mode so that all existing Django synchronous code runs in the
same thread and thus is fully compatible with asynchronous mode. Note, that
synchronous code will always be in a *different* thread to any async code that
is calling it, so you should avoid passing raw database handles or other
thread-sensitive references around in any new code you write.