Versions Compared

Old Version 3

changes.mady.by.user Potter (Esteban Alvarado)

Saved on

compared with

New Version Current

changes.mady.by.user Potter (Esteban Alvarado)

Saved on

Key

  • This line was added.
  • This line was removed.
  • Formatting was changed.
Note

Before reading this section, for Search GAIA API we provide a script u vicornuvicorn_server.py, which already uses  Uvicorn to esexute the serverexecute the server:

Code Block
python uvicorn_server.py


The main thing you need to run a FastAPIGAIA API application in a remote server machine is an ASGI server program like Uvicorn.

There are 3 main alternatives:

  • 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.


Table of Contents

Server Machine and Server Program

Note

There's a small detail about names to have 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 have that in mind 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

You can install an ASGI compatible server with:

  • Uvicorn, a lightning-fast ASGI server, built on uvloop and httptools.


Code Block
languagebash
pip install "uvicorn[standard]"
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.

  • Hypercorn, an ASGI server also compatible with HTTP/2.


Code Block
languagebash
pip install hypercorn

...or any other ASGI server.

Run the Server Program

You can then run your application the same way you have done in the tutorials, but without the --reload option, e.g.:

Code Block
languagebash
$ uvicorn mainapp.webapp:app --host 0.0.0.0 --port 8085

INFO:     Uvicorn running on http://0.0.0.0:8085 (Press CTRL+C to quit)
Code Block
languagebash
$ hypercorn mainapp.webapp:app --bind 0.0.0.0:8085

Running on 0.0.0.0:8085 over http (CTRL + C to quit)
Warning
titleNot for production

Remember to remove the --reload option if you were using it.

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.

Hypercorn with Trio

Starlette and FastAPI (which GAIA API is based on) are based on AnyIO, which makes them compatible with both Python's standard library asyncio and Trio.

Nevertheless, Uvicorn is currently only compatible with asyncio, and it normally uses uvloop, the high-performance drop-in replacement for asyncio.

But if you want to directly use Trio, then you can use Hypercorn as it supports it.

Install Hypercorn with Trio

First you need to install Hypercorn with Trio support:

Code Block
languagebash
pip install "hypercorn[trio]"

Run with Trio

Then you can pass the command line option --worker-class with the value trio:

Code Block
languagebash
hypercorn mainapp.webapp:app --worker-class trio


And that will start Hypercorn with your app using Trio as the backend.

Now you can use Trio internally in your app. Or even better, you can use AnyIO, to keep your code compatible with both Trio and asyncio. 

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. 
Info

For more detail on deployment concepts please visit the official FastAPI documentation