ASGI is a standard for Python asynchronous web apps and servers to communicate with each other, and positioned as an asynchronous successor to WSGI. You can read more at https://asgi.readthedocs.io/en/latest/
This package includes ASGI base libraries, such as:
- Sync-to-async and async-to-sync function wrappers,
- Server base classes,
- A WSGI-to-ASGI adapter, in
These allow you to wrap or decorate async or sync functions to call them from the other style (so you can call async functions from a synchronous thread, or vice-versa).
- AsyncToSync lets a synchronous subthread stop and wait while the async function is called on the main thread's event loop, and then control is returned to the thread when the async function is finished.
- SyncToAsync lets async code call a synchronous function, which is run in a threadpool and control returned to the async coroutine when the synchronous function completes.
The idea is to make it easier to call synchronous APIs from async code and asynchronous APIs from synchronous code so it's easier to transition code from one style to the other. In the case of Channels, we wrap the (synchronous) Django view system with SyncToAsync to allow it to run inside the (asynchronous) ASGI server.
Note that exactly what threads things run in is very specific, and aimed to keep maximum compatibility with old synchronous code. See "Synchronous code & Threads" below for a full explanation.
This is a drop-in replacement for
threading.local that works with both
threads and asyncio Tasks. Even better, it will proxy values through from a
task-local context to a thread-local context when you use
to run things in a threadpool, and vice-versa for
If you instead want true thread- and task-safety, you can set
thread_critical on the Local object to ensure this instead.
Server base classes
StatelessServer class which provides all the hard work of
writing a stateless server (as in, does not handle direct incoming sockets
but instead consumes external streams or sockets to work out what is happening).
An example of such a server would be a chatbot server that connects out to a central chat server and provides a "connection scope" per user chatting to it. There's only one actual connection, but the server has to separate things into several scopes for easier writing of the code.
You can see an example of this being used in frequensgi.
Allows you to wrap a WSGI application so it appears as a valid ASGI application.
Simply wrap it around your WSGI application like so:
asgi_application = WsgiToAsgi(wsgi_application)
The WSGI application will be run in a synchronous threadpool, and the wrapped
ASGI application will be one that accepts
http class messages.
Please note that not all extended features of WSGI may be supported (such as file handles for incoming POST bodies).
asgiref requires Python 3.5 or higher.
Please refer to the main Channels contributing docs.
To run tests, make sure you have installed the
tests extra with the package:
cd asgiref/ pip install -e .[tests] pytest
Building the documentation
The documentation uses Sphinx:
cd asgiref/docs/ pip install sphinx
To build the docs, you can use the default tools:
sphinx-build -b html . _build/html # or `make html`, if you've got make set up cd _build/html python -m http.server
...or you can use
sphinx-autobuild to run a server and rebuild/reload
your documentation changes automatically:
pip install sphinx-autobuild sphinx-autobuild . _build/html
Synchronous code & threads
asgiref.sync module provides two wrappers that let you go between
asynchronous and synchronous code at will, while taking care of the rough edges
Unfortunately, the rough edges are numerous, and the code has to work especially hard to keep things in the same thread as much as possible. Notably, the restrictions we are working with are:
- All synchronous code called through
SyncToAsyncand marked with
thread_sensitiveshould run in the same thread as each other (and if the outer layer of the program is synchronous, the main thread)
- If a thread already has a running async loop,
AsyncToSynccan't run things on that loop if it's blocked on synchronous code that is above you in the call stack.
The first compromise you get to might be that
thread_sensitive code should
just run in the same thread and not spawn in a sub-thread, fulfilling the first
restriction, but that immediately runs you into the second restriction.
The only real solution is to essentially have a variant of ThreadPoolExecutor
that executes any
thread_sensitive code on the outermost synchronous
thread - either the main thread, or a single spawned subthread.
This means you now have two basic states:
- If the outermost layer of your program is synchronous, then all async code
AsyncToSyncwill run in a per-call event loop in arbitary sub-threads, while all
thread_sensitivecode will run in the main thread.
- If the outermost layer of your program is asynchronous, then all async code
runs on the main thread's event loop, and all
thread_sensitivesynchronous code will run in a single shared sub-thread.
Cruicially, this means that in both cases there is a thread which is a shared
resource that all
thread_sensitive code must run on, and there is a chance
that this thread is currently blocked on its own
AsyncToSync call. Thus,
AsyncToSync needs to act as an executor for thread code while it's blocking.
CurrentThreadExecutor class provides this functionality; rather than
simply waiting on a Future, you can call its
run_until_future method and
it will run submitted code until that Future is done. This means that code
inside the call can then run code on your thread.
Maintenance and Security
To report security issues, please contact email@example.com. For GPG signatures and more security process information, see https://docs.djangoproject.com/en/dev/internals/security/.
To report bugs or request new features, please open a new GitHub issue.
This repository is part of the Channels project. For the shepherd and maintenance team, please see the main Channels readme.