Sanic has three serving options: the inbuilt webserver, an ASGI webserver, or gunicorn.
Sanic’s own webserver is the fastest option, and it can be securely run on the Internet. Still, it is also very common to place Sanic behind a reverse proxy, as shown in Nginx Deployment.
Running via Sanic webserver¶
After defining an instance of sanic.Sanic, we can call the run method with the following keyword arguments:
host (default `”127.0.0.1”`): Address to host the server on.
port (default `8000`): Port to host the server on.
unix (default `None`): Unix socket name to host the server on (instead of TCP).
debug (default `False`): Enables debug output (slows server).
ssl (default `None`): SSLContext for SSL encryption of worker(s).
sock (default `None`): Socket for the server to accept connections from.
workers (default `1`): Number of worker processes to spawn.
loop (default `None`): An asyncio-compatible event loop. If none is specified, Sanic creates its own event loop.
protocol (default `HttpProtocol`): Subclass of asyncio.protocol.
access_log (default `True`): Enables log on handling requests (significantly slows server).
app.run(host='0.0.0.0', port=1337, access_log=False)
In the above example, we decided to turn off the access log in order to increase performance.
By default, Sanic listens in the main process using only one CPU core. To crank up the juice, just specify the number of workers in the run arguments.
app.run(host='0.0.0.0', port=1337, workers=4)
Sanic will automatically spin up multiple processes and route traffic between them. We recommend as many workers as you have available cores.
Running via command¶
If you like using command line arguments, you can launch a Sanic webserver by executing the module. For example, if you initialized Sanic as app in a file named server.py, you could run the server like so:
sanic server.app --host=0.0.0.0 --port=1337 --workers=4
It can also be called directly as a module.
python -m sanic server.app --host=0.0.0.0 --port=1337 --workers=4
With this way of running sanic, it is not necessary to invoke app.run in your Python file. If you do, make sure you wrap it so that it only executes when directly run by the interpreter.
if __name__ == '__main__': app.run(host='0.0.0.0', port=1337, workers=4)
Running via ASGI¶
Follow their documentation for the proper way to run them, but it should look something like:
daphne myapp:app uvicorn myapp:app hypercorn myapp:app
A couple things to note when using ASGI:
1. When using the Sanic webserver, websockets will run using the websockets package. In ASGI mode, there is no need for this package since websockets are managed in the ASGI server. 2. The ASGI lifespan protocol <https://asgi.readthedocs.io/en/latest/specs/lifespan.html>, supports only two server events: startup and shutdown. Sanic has four: before startup, after startup, before shutdown, and after shutdown. Therefore, in ASGI mode, the startup and shutdown events will run consecutively and not actually around the server process beginning and ending (since that is now controlled by the ASGI server). Therefore, it is best to use after_server_start and before_server_stop.
Sanic has experimental support for running on Trio with:
hypercorn -k trio myapp:app
Running via Gunicorn¶
Gunicorn ‘Green Unicorn’ is a WSGI HTTP Server for UNIX. It’s a pre-fork worker model ported from Ruby’s Unicorn project.
In order to run Sanic application with Gunicorn, you need to use the special sanic.worker.GunicornWorker for Gunicorn worker-class argument:
gunicorn myapp:app --bind 0.0.0.0:1337 --worker-class sanic.worker.GunicornWorker
If your application suffers from memory leaks, you can configure Gunicorn to gracefully restart a worker after it has processed a given number of requests. This can be a convenient way to help limit the effects of the memory leak.
See the Gunicorn Docs for more information.
Other deployment considerations¶
Disable debug logging for performance¶
To improve the performance add debug=False and access_log=False in the run arguments.
app.run(host='0.0.0.0', port=1337, workers=4, debug=False, access_log=False)
Running via Gunicorn you can set Environment variable SANIC_ACCESS_LOG=”False”
env SANIC_ACCESS_LOG="False" gunicorn myapp:app --bind 0.0.0.0:1337 --worker-class sanic.worker.GunicornWorker --log-level warning
Or you can rewrite app config directly
app.config.ACCESS_LOG = False
Asynchronous support and sharing the loop¶
This is suitable if you need to share the Sanic process with other applications, in particular the loop. However, be advised that this method does not support using multiple processes, and is not the preferred way to run the app in general.
Here is an incomplete example (please see run_async.py in examples for something more practical):
server = app.create_server(host="0.0.0.0", port=8000, return_asyncio_server=True) loop = asyncio.get_event_loop() task = asyncio.ensure_future(server) loop.run_forever()
Caveat: using this method, calling app.create_server() will trigger “before_server_start” server events, but not “after_server_start”, “before_server_stop”, or “after_server_stop” server events.
For more advanced use-cases, you can trigger these events using the AsyncioServer object, returned by awaiting the server task.
Here is an incomplete example (please see run_async_advanced.py in examples for something more complete):
serv_coro = app.create_server(host="0.0.0.0", port=8000, return_asyncio_server=True) loop = asyncio.get_event_loop() serv_task = asyncio.ensure_future(serv_coro, loop=loop) server = loop.run_until_complete(serv_task) server.after_start() try: loop.run_forever() except KeyboardInterrupt as e: loop.stop() finally: server.before_stop() # Wait for server to close close_task = server.close() loop.run_until_complete(close_task) # Complete all tasks on the loop for connection in server.connections: connection.close_if_idle() server.after_stop()