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281 lines
12 KiB
Plaintext
====================
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Asynchronous support
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====================
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.. currentmodule:: asgiref.sync
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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>`. 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 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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Async views
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===========
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Any view can be declared async by making the callable part of it return a
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coroutine - commonly, this is done using ``async def``. For a function-based
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view, this means declaring the whole view using ``async def``. For a
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class-based view, this means making its ``__call__()`` method an ``async def``
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(not its ``__init__()`` or ``as_view()``).
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.. note::
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Django uses ``asyncio.iscoroutinefunction`` to test if your view is
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asynchronous or not. If you implement your own method of returning a
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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, async views will run in their own, one-off event loop.
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This means you can use async features, like concurrent 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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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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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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Middleware can be built to support :ref:`both sync and async
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<async-middleware>` contexts. Some of Django's middleware is built like
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this, but not all. To see what middleware Django has to adapt, you can turn
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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 both ASGI and WSGI mode, you can still safely use asynchronous support to
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run code concurrently 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. For example::
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from asgiref.sync import sync_to_async
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results = await sync_to_async(Blog.objects.get, thread_sensitive=True)(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`. For example::
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from asgiref.sync import 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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get_blog = sync_to_async(_get_blog, thread_sensitive=True)
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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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When running in a mode that does not match the view (e.g. an async view under
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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 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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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 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 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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============
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.. envvar:: DJANGO_ALLOW_ASYNC_UNSAFE
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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 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 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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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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The async context can be imposed upon you by the environment in which you are
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running your Django code. For example, Jupyter_ notebooks and IPython_
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interactive shells both transparently provide an active event loop so that it is
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easier to interact with asynchronous APIs.
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If you're using an IPython shell, you can disable this event loop by running::
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%autoawait off
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as a command at the IPython prompt. This will allow you to run synchronous code
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without generating :exc:`~django.core.exceptions.SynchronousOnlyOperation`
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errors; however, you also won't be able to ``await`` asynchronous APIs. To turn
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the event loop back on, run::
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%autoawait on
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If you're in an environment other than IPython (or you can't turn off
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``autoawait`` in IPython for some reason), you are *certain* there is no chance
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of your code being run concurrently, and you *absolutely* need to run your sync
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code from an async context, then you can disable the warning by setting the
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:envvar:`DJANGO_ALLOW_ASYNC_UNSAFE` environment variable to any value.
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.. warning::
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If you enable this option and there is concurrent access to the
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async-unsafe parts of Django, you may suffer data loss or corruption. Be
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very careful and do not use this in production environments.
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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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.. _IPython: https://ipython.org
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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 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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dependency when you install Django with ``pip``.
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.. _asgiref: https://pypi.org/project/asgiref/
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``async_to_sync()``
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-------------------
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.. function:: async_to_sync(async_function, force_new_loop=False)
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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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async def get_data(...):
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...
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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 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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``sync_to_async()``
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-------------------
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.. function:: sync_to_async(sync_function, thread_sensitive=True)
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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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async_function = sync_to_async(sync_function, thread_sensitive=False)
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async_function = sync_to_async(sensitive_sync_function, thread_sensitive=True)
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@sync_to_async
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def sync_function(...):
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...
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Threadlocals and contextvars values are preserved across the boundary in both
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directions.
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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=True`` (the default): the sync function will run in the
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same thread as all other ``thread_sensitive`` functions. This will be the
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main 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=False``: the sync function will run in a brand new thread
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which is then closed once the invocation completes.
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.. warning::
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``asgiref`` version 3.3.0 changed the default value of the
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``thread_sensitive`` parameter to ``True``. This is a safer default, and in
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many cases interacting with Django the correct value, but be sure to
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evaluate uses of ``sync_to_async()`` if updating ``asgiref`` from a prior
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version.
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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 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. 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 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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