Run a Server Manually¶
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Use the fastapi run
Command¶
In short, use fastapi run
to serve your FastAPI application:
$ <font color="#4E9A06">fastapi</font> run <u style="text-decoration-style:single">main.py</u>
<font color="#3465A4">INFO </font> Using path <font color="#3465A4">main.py</font>
<font color="#3465A4">INFO </font> Resolved absolute path <font color="#75507B">/home/user/code/awesomeapp/</font><font color="#AD7FA8">main.py</font>
<font color="#3465A4">INFO </font> Searching for package file structure from directories with <font color="#3465A4">__init__.py</font> files
<font color="#3465A4">INFO </font> Importing from <font color="#75507B">/home/user/code/</font><font color="#AD7FA8">awesomeapp</font>
╭─ <font color="#8AE234"><b>Python module file</b></font> ─╮
│ │
│ 🐍 main.py │
│ │
╰──────────────────────╯
<font color="#3465A4">INFO </font> Importing module <font color="#4E9A06">main</font>
<font color="#3465A4">INFO </font> Found importable FastAPI app
╭─ <font color="#8AE234"><b>Importable FastAPI app</b></font> ─╮
│ │
│ <span style="background-color:#272822"><font color="#FF4689">from</font></span><span style="background-color:#272822"><font color="#F8F8F2"> main </font></span><span style="background-color:#272822"><font color="#FF4689">import</font></span><span style="background-color:#272822"><font color="#F8F8F2"> app</font></span><span style="background-color:#272822"> </span> │
│ │
╰──────────────────────────╯
<font color="#3465A4">INFO </font> Using import string <font color="#8AE234"><b>main:app</b></font>
<font color="#4E9A06">╭─────────── FastAPI CLI - Production mode ───────────╮</font>
<font color="#4E9A06">│ │</font>
<font color="#4E9A06">│ Serving at: http://0.0.0.0:8000 │</font>
<font color="#4E9A06">│ │</font>
<font color="#4E9A06">│ API docs: http://0.0.0.0:8000/docs │</font>
<font color="#4E9A06">│ │</font>
<font color="#4E9A06">│ Running in production mode, for development use: │</font>
<font color="#4E9A06">│ │</font>
<font color="#4E9A06">│ </font><font color="#8AE234"><b>fastapi dev</b></font><font color="#4E9A06"> │</font>
<font color="#4E9A06">│ │</font>
<font color="#4E9A06">╰─────────────────────────────────────────────────────╯</font>
<font color="#4E9A06">INFO</font>: Started server process [<font color="#06989A">2306215</font>]
<font color="#4E9A06">INFO</font>: Waiting for application startup.
<font color="#4E9A06">INFO</font>: Application startup complete.
<font color="#4E9A06">INFO</font>: Uvicorn running on <b>http://0.0.0.0:8000</b> (Press CTRL+C to quit)
That would work for most of the cases. 😎
You could use that command for example to start your FastAPI app in a container, in a server, etc.
ASGI Servers¶
Let's go a little deeper into the details.
FastAPI uses a standard for building Python web frameworks and servers called ASGI. FastAPI is an ASGI web framework.
The main thing you need to run a FastAPI application (or any other ASGI application) in a remote server machine is an ASGI server program like Uvicorn, this is the one that comes by default in the fastapi
command.
There are several alternatives, including:
- Uvicorn: a high performance ASGI server.
- Hypercorn: an ASGI server compatible with HTTP/2 and Trio among other features.
- Daphne: the ASGI server built for Django Channels.
- Granian: A Rust HTTP server for Python applications.
- NGINX Unit: NGINX Unit is a lightweight and versatile web application runtime.
Server Machine and Server Program¶
There's a small detail about names to keep in mind. 💡
The word "server" is commonly used to refer to both the remote/cloud computer (the physical or virtual machine) and also the program that is running on that machine (e.g. Uvicorn).
Just keep in mind that when you read "server" in general, it could refer to one of those two things.
When referring to the remote machine, it's common to call it server, but also machine, VM (virtual machine), node. Those all refer to some type of remote machine, normally running Linux, where you run programs.
Install the Server Program¶
When you install FastAPI, it comes with a production server, Uvicorn, and you can start it with the fastapi run
command.
But you can also install an ASGI server manually.
Make sure you create a virtual environment, activate it, and then you can install the server application.
For example, to install Uvicorn:
$ pip install "uvicorn[standard]"
---> 100%
A similar process would apply to any other ASGI server program.
Tip
By adding the standard
, Uvicorn will install and use some recommended extra dependencies.
That including uvloop
, the high-performance drop-in replacement for asyncio
, that provides the big concurrency performance boost.
When you install FastAPI with something like pip install "fastapi[standard]"
you already get uvicorn[standard]
as well.
Run the Server Program¶
If you installed an ASGI server manually, you would normally need to pass an import string in a special format for it to import your FastAPI application:
$ uvicorn main:app --host 0.0.0.0 --port 80
<span style="color: green;">INFO</span>: Uvicorn running on http://0.0.0.0:80 (Press CTRL+C to quit)
Note
The command uvicorn main:app
refers to:
main
: the filemain.py
(the Python "module").app
: the object created inside ofmain.py
with the lineapp = FastAPI()
.
It is equivalent to:
from main import app
Each alternative ASGI server program would have a similar command, you can read more in their respective documentation.
Warning
Uvicorn and other servers support a --reload
option that is useful during development.
The --reload
option consumes much more resources, is more unstable, etc.
It helps a lot during development, but you shouldn't use it in production.
Deployment Concepts¶
These examples run the server program (e.g Uvicorn), starting a single process, listening on all the IPs (0.0.0.0
) on a predefined port (e.g. 80
).
This is the basic idea. But you will probably want to take care of some additional things, like:
- Security - HTTPS
- Running on startup
- Restarts
- Replication (the number of processes running)
- Memory
- Previous steps before starting
I'll tell you more about each of these concepts, how to think about them, and some concrete examples with strategies to handle them in the next chapters. 🚀