# Running Sanic
Sanic ships with its own internal web server. Under most circumstances, this is the preferred method for deployment. In addition, you can also deploy Sanic as an ASGI app bundled with an ASGI-able web server, or using gunicorn.
# Sanic Server
After defining an instance of
sanic.Sanic, we can call the run method with the following keyword arguments:
|host|| ||Address to host the server on.|
|port|| ||Port to host the server on.|
|unix|| ||Unix socket name to host the server on (instead of TCP).|
|debug|| ||Enables debug output (slows server).|
|ssl|| ||SSLContext for SSL encryption of worker(s).|
|sock|| ||Socket for the server to accept connections from.|
|workers|| ||Number of worker processes to spawn.|
|loop|| ||An asyncio-compatible event loop. If none is specified, Sanic creates its own event loop.|
|protocol|| ||Subclass of asyncio.protocol.|
|access_log|| ||Enables log on handling requests (significantly slows server).|
In the above example, we decided to turn off the access log in order to increase performance.
# server.py app = Sanic("My App") app.run(host='0.0.0.0', port=1337, access_log=False)
Now, just execute the python script that has
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 processors.
A common way to check this on Linux based operating systems:
Or, let Python do it:
import multiprocessing workers = multiprocessing.cpu_count() app.run(..., workers=workers)
# Running via command
# Sanic CLI
Sanic also has a simple CLI to launch via command line.
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
sanic --help to see all the options.
$ sanic --help usage: sanic [-h] [--host HOST] [--port PORT] [--unix UNIX] [--cert CERT] [--key KEY] [--workers WORKERS] [--debug] module positional arguments: module optional arguments: -h, --help show this help message and exit --host HOST --port PORT --unix UNIX --cert CERT location of certificate for SSL --key KEY location of keyfile for SSL. --workers WORKERS --debug
# As a module
It can also be called directly as a module.
python -m sanic server.app --host=0.0.0.0 --port=1337 --workers=4
With either method (CLI or module), 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)
Sanic is also ASGI-compliant. This means you can use your preferred ASGI webserver to run Sanic. The three main implementations of ASGI are Daphne (opens new window), Uvicorn (opens new window), and Hypercorn (opens new window).
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:
- When using the Sanic webserver, websockets will run using the
websocketspackage. In ASGI mode, there is no need for this package since websockets are managed in the ASGI server.
- The ASGI lifespan protocol https://asgi.readthedocs.io/en/latest/specs/lifespan.html (opens new window), 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
Sanic has experimental support for running on Trio with:
hypercorn -k trio myapp:app
Gunicorn (opens new window) ("Green Unicorn") is a WSGI HTTP Server for UNIX based operating systems. It is 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 (opens new window) for more information.
When running Sanic via
gunicorn, you are losing out on a lot of the performance benefits of
await. Weigh your considerations carefully before making this choice. Gunicorn does provide a lot of configuration options, but it is not the best choice for getting Sanic to run at its fastest.
# Performance considerations
When running in production, make sure you turn off
Sanic will also perform fastest if you turn off
If you still require access logs, but want to enjoy this performance boost, consider using Nginx as a proxy, and letting that handle your access logging. It will be much faster than anything Python can handle.