160 lines
6.0 KiB
Markdown
160 lines
6.0 KiB
Markdown
# Deploying
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Deploying Sanic is very simple using one of three options: the inbuilt webserver,
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an [ASGI webserver](https://asgi.readthedocs.io/en/latest/implementations.html), or `gunicorn`.
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It is also very common to place Sanic behind a reverse proxy, like `nginx`.
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## Running via Sanic webserver
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After defining an instance of `sanic.Sanic`, we can call the `run` method with the following
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keyword arguments:
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- `host` *(default `"127.0.0.1"`)*: Address to host the server on.
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- `port` *(default `8000`)*: Port to host the server on.
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- `debug` *(default `False`)*: Enables debug output (slows server).
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- `ssl` *(default `None`)*: `SSLContext` for SSL encryption of worker(s).
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- `sock` *(default `None`)*: Socket for the server to accept connections from.
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- `workers` *(default `1`)*: Number of worker processes to spawn.
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- `loop` *(default `None`)*: An `asyncio`-compatible event loop. If none is
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specified, Sanic creates its own event loop.
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- `protocol` *(default `HttpProtocol`)*: Subclass
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of
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[asyncio.protocol](https://docs.python.org/3/library/asyncio-protocol.html#protocol-classes).
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- `access_log` *(default `True`)*: Enables log on handling requests (significantly slows server).
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```python
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app.run(host='0.0.0.0', port=1337, access_log=False)
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```
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In the above example, we decided to turn off the access log in order to increase performance.
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### Workers
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By default, Sanic listens in the main process using only one CPU core. To crank
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up the juice, just specify the number of workers in the `run` arguments.
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```python
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app.run(host='0.0.0.0', port=1337, workers=4)
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```
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Sanic will automatically spin up multiple processes and route traffic between
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them. We recommend as many workers as you have available cores.
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### Running via command
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If you like using command line arguments, you can launch a Sanic webserver by
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executing the module. For example, if you initialized Sanic as `app` in a file
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named `server.py`, you could run the server like so:
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`python -m sanic server.app --host=0.0.0.0 --port=1337 --workers=4`
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With this way of running sanic, it is not necessary to invoke `app.run` in your
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Python file. If you do, make sure you wrap it so that it only executes when
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directly run by the interpreter.
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```python
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if __name__ == '__main__':
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app.run(host='0.0.0.0', port=1337, workers=4)
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```
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## Running via ASGI
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Sanic is also ASGI-compliant. This means you can use your preferred ASGI webserver
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to run Sanic. The three main implementations of ASGI are
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[Daphne](http://github.com/django/daphne), [Uvicorn](https://www.uvicorn.org/),
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and [Hypercorn](https://pgjones.gitlab.io/hypercorn/index.html).
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Follow their documentation for the proper way to run them, but it should look
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something like:
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```
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daphne myapp:app
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uvicorn myapp:app
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hypercorn myapp:app
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```
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A couple things to note when using ASGI:
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1. When using the Sanic webserver, websockets will run using the [`websockets`](https://websockets.readthedocs.io/) package. In ASGI mode, there is no need for this package since websockets are managed in the ASGI server.
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1. The ASGI [lifespan protocol](https://asgi.readthedocs.io/en/latest/specs/lifespan.html) supports
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only two server events: startup and shutdown. Sanic has four: before startup, after startup,
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before shutdown, and after shutdown. Therefore, in ASGI mode, the startup and shutdown events will
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run consecutively and not actually around the server process beginning and ending (since that
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is now controlled by the ASGI server). Therefore, it is best to use `after_server_start` and
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`before_server_stop`.
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1. ASGI mode is still in "beta" as of Sanic v19.6.
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## Running via Gunicorn
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[Gunicorn](http://gunicorn.org/) ‘Green Unicorn’ is a WSGI HTTP Server for UNIX.
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It’s a pre-fork worker model ported from Ruby’s Unicorn project.
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In order to run Sanic application with Gunicorn, you need to use the special `sanic.worker.GunicornWorker`
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for Gunicorn `worker-class` argument:
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```
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gunicorn myapp:app --bind 0.0.0.0:1337 --worker-class sanic.worker.GunicornWorker
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```
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If your application suffers from memory leaks, you can configure Gunicorn to gracefully restart a worker
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after it has processed a given number of requests. This can be a convenient way to help limit the effects
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of the memory leak.
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See the [Gunicorn Docs](http://docs.gunicorn.org/en/latest/settings.html#max-requests) for more information.
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## Other deployment considerations
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### Running behind a reverse proxy
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Sanic can be used with a reverse proxy (e.g. nginx). There's a simple example of nginx configuration:
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```
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server {
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listen 80;
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server_name example.org;
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location / {
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proxy_pass http://127.0.0.1:8000;
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proxy_set_header Host $host;
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proxy_set_header X-Real-IP $remote_addr;
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proxy_set_header X-Forwarded-For $proxy_add_x_forwarded_for;
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}
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}
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```
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If you want to get real client ip, you should configure `X-Real-IP` and `X-Forwarded-For` HTTP headers and set `app.config.PROXIES_COUNT` to `1`; see the configuration page for more information.
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### Disable debug logging for performance
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To improve the performance add `debug=False` and `access_log=False` in the `run` arguments.
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```python
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app.run(host='0.0.0.0', port=1337, workers=4, debug=False, access_log=False)
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```
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Running via Gunicorn you can set Environment variable `SANIC_ACCESS_LOG="False"`
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```
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env SANIC_ACCESS_LOG="False" gunicorn myapp:app --bind 0.0.0.0:1337 --worker-class sanic.worker.GunicornWorker --log-level warning
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```
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Or you can rewrite app config directly
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```python
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app.config.ACCESS_LOG = False
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```
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### Asynchronous support and sharing the loop
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This is suitable if you *need* to share the Sanic process with other applications, in particular the `loop`.
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However, be advised that this method does not support using multiple processes, and is not the preferred way
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to run the app in general.
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Here is an incomplete example (please see `run_async.py` in examples for something more practical):
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```python
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server = app.create_server(host="0.0.0.0", port=8000, return_asyncio_server=True)
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loop = asyncio.get_event_loop()
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task = asyncio.ensure_future(server)
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loop.run_forever()
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``` |