非同期サポート

Djangoは、 ASGI の環境下であれば、完璧な非同期リクエストスタックに対応した非同期("async")ビューをサポートしています。WSGIの環境下でも非同期ビューは動作しますが、パフォーマンス上不利であるうえ、長期的なリクエストを効率的に処理できません。

開発チームはORMや他の機能でも非同期処理が対応できるよう取り組んでいます。この機能は将来リリース予定ですが、現時点では、同期処理と非同期処理のやり取りに、 sync_to_async() アダプターが使えます。さらに同期処理と非同期処理を統合するために、非同期なPythonライブラリがすべて使えます。

非同期ビュー

どのようなビューであれ、呼び出し可能オブジェクトでコルーチンを返すようにすれば、非同期にできます。その際には、一般的に``async def``を使います。関数ベースのビューの場合、``async def``を用いてビュー全体を宣言します。クラスベースのビューの場合、 ``__call__()``メソッドを``async def``で宣言します（``__init__()``でも``as_view()``でもないことに注意）。

注釈

Djangoは``asyncio.iscoroutinefunction``を使って、ビューが非同期かどうかテストします。コルーチンを返す独自のメソッドを実装する場合、ビューの``_is_coroutine``属性を``asyncio.coroutines._is_coroutine``に設定し、この関数が``True``を返すようにしてください。

WSGIサーバーでは、非同期ビューは1回限りのイベントループで実行されます。つまり、非同期HTTPリクエストなどの非同期機能を問題なく使用できるものの、非同期スタックのメリットは得られないことになります。

非同期スタックの主な利点とは、数百もの接続をPythonのスレッドを使わずに処理できることです。これにより、低速ストリーミング、ロングポーリング、その他の便利なレスポンスタイプが使えます。

もしこれらを利用したい場合は、代わりに ASGI を使ってDjangoをデプロイする必要があります。

警告

同期ミドルウェアを使っていない場合にのみ、完全非同期のリクエストスタックの効果があります。もし、同期ミドルウェアがあれば、同期環境を安全にエミュレートするために、Djangoはリクエストごとにスレッドを使ってしまいます。

ミドルウェアは、 both sync and async コンテキストをサポートするように構築できます。 Djangoミドルウェアの一部はこのように構築されていますが、すべてではありません。ミドルウェアが適応する必要があるものを確認するには、 django.request ロガーのデバッグロギングを有効にして、 "Synchronous middleware ... adapted" に関するログメッセージを探します。

ASGIとWSGIの両方のモードで、非同期サポートを使用し、シリアルではなく並行してコードを実行することができます。これは特に、外部APIやデータストアを扱う場合に便利です。

ORMのような、まだ同期的なDjangoの機能を呼び出したい場合、次のように:func:`sync_to_async`でラップする必要があります。

from asgiref.sync import sync_to_async

results = await sync_to_async(Blog.objects.get, thread_sensitive=True)(pk=123)

次のコードのように、ORMのコードを独自の関数に移動して、その関数全体を:func:`sync_to_async`で呼び出す方が簡単だと思うかもしれません。

from asgiref.sync import sync_to_async

def _get_blog(pk):
    return Blog.objects.select_related('author').get(pk=pk)

get_blog = sync_to_async(_get_blog, thread_sensitive=True)

非同期ビューから、同期的なDjangoの機能を誤って呼び出そうとすると、Djangoの<async-safety>が発動して、データが破損しないように保護されます。

パフォーマンス

When running in a mode that does not match the view (e.g. an async view under WSGI, or a traditional sync view under ASGI), Django must emulate the other call style to allow your code to run. This context-switch causes a small performance penalty of around a millisecond.

This is also true of middleware. Django will attempt to minimize the number of context-switches between sync and async. If you have an ASGI server, but all your middleware and views are synchronous, it will switch just once, before it enters the middleware stack.

However, if you put synchronous middleware between an ASGI server and an asynchronous view, it will have to switch into sync mode for the middleware and then back to async mode for the view. Django will also hold the sync thread open for middleware exception propagation. This may not be noticeable at first, but adding this penalty of one thread per request can remove any async performance advantage.

You should do your own performance testing to see what effect ASGI versus WSGI has on your code. In some cases, there may be a performance increase even for a purely synchronous codebase under ASGI because the request-handling code is still all running asynchronously. In general you will only want to enable ASGI mode if you have asynchronous code in your project.

非同期安全性

DJANGO_ALLOW_ASYNC_UNSAFE

Certain key parts of Django are not able to operate safely in an async 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 async 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 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 sync function directly from an async function, without using sync_to_async() or similar, then it can also occur. This is because your code is still running in a thread with an active event loop, even though it may not be declared as async code.

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 functions in its own, sync function, and call that using asgiref.sync.sync_to_async() (or any other way of running sync code in its own thread).

The async context can be imposed upon you by the environment in which you are running your Django code. For example, Jupyter notebooks and IPython interactive shells both transparently provide an active event loop so that it is easier to interact with asynchronous APIs.

If you're using an IPython shell, you can disable this event loop by running:

%autoawait off

as a command at the IPython prompt. This will allow you to run synchronous code without generating SynchronousOnlyOperation errors; however, you also won't be able to await asynchronous APIs. To turn the event loop back on, run:

%autoawait on

If you're in an environment other than IPython (or you can't turn off autoawait in IPython for some reason), you are certain there is no chance of your code being run concurrently, and you absolutely need to run your sync code from an async context, then you can disable the warning by setting the DJANGO_ALLOW_ASYNC_UNSAFE environment variable to any value.

警告

このオプションを有効にした上で、Djangoの async-unsafe パーツへ同時アクセスがあると、データが失われたり壊れたりする可能性があります。十分な注意を払い、本番環境では使用しないでください。

もし、これをPython内部から行いたい場合は、 os.environ:: を使用してください。

import os

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

Async adapter functions

It is necessary to adapt the calling style when calling sync code from an async context, or vice-versa. For this there are two adapter functions, from the asgiref.sync module: async_to_sync() and sync_to_async(). They are used to transition between the 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.

async_to_sync()

async_to_sync(async_function, force_new_loop=False)

Takes an async function and returns a sync function that wraps it. Can be used as either a direct wrapper or a decorator:

from asgiref.sync import async_to_sync

async def get_data(...):
    ...

sync_get_data = async_to_sync(get_data)

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

The async 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 single async invocation 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.

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

sync_to_async()

sync_to_async(sync_function, thread_sensitive=True)[ソース]

Takes a sync function and returns an async function that wraps it. 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, thread_sensitive=False)
async_function = sync_to_async(sensitive_sync_function, thread_sensitive=True)

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

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

Sync functions tend to be written assuming they all run in the main thread, so sync_to_async() has two threading modes:

  • thread_sensitive=True (the default): the sync function will run in the same thread as all other thread_sensitive functions. This will be the main thread, if the main thread is synchronous and you are using the async_to_sync() wrapper.
  • thread_sensitive=False: the sync function will run in a brand new thread which is then closed once the invocation completes.

警告

asgiref version 3.3.0 changed the default value of the thread_sensitive parameter to True. This is a safer default, and in many cases interacting with Django the correct value, but be sure to evaluate uses of sync_to_async() if updating asgiref from a prior version.

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 async_to_sync() above it in the stack to correctly run things on the main thread. If you use asyncio.run() or similar, it will fall back to running thread-sensitive functions in a single, shared thread, but this will not be 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. Also 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 in views.

Rather than introduce potential compatibility issues with this code, we instead opted to add this mode so that all existing Django sync code runs in the same thread and thus is fully compatible with async mode. Note that sync 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 practice this restriction means that you should not pass features of the database connection object when calling sync_to_async(). Doing so will trigger the thread safety checks:

# DJANGO_SETTINGS_MODULE=settings.py python -m asyncio
>>> import asyncio
>>> from asgiref.sync import sync_to_async
>>> from django.db import connection
>>> # In an async context so you cannot use the database directly:
>>> connection.cursor()
...
django.core.exceptions.SynchronousOnlyOperation: You cannot call this from
an async context - use a thread or sync_to_async.
>>> # Nor can you pass resolved connection attributes across threads:
>>> await sync_to_async(connection.cursor)()
...
django.db.utils.DatabaseError: DatabaseWrapper objects created in a thread
can only be used in that same thread. The object with alias 'default' was
created in thread id 4371465600 and this is thread id 6131478528.

Rather, you should encapsulate all database access within a helper function that can be called with sync_to_async() without relying on the connection object in the calling code.

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