hypercorn VS uvicorn

In addition [Hypercorn](https://github.com/pgjones/hypercorn) (a ASGI and WSGI) also does not use gunicorn, having migrated many years ago.

You might find some recommendations to use hypercorn rather than uvicorn, I tried that initially but I couldn't resolve an issue with socket permission, I raised it as a bug in their GitHub repo.

for those wishing to use http3 with a Python web framework, the ASGI hypercorn[1] currently supports it.

made a Django example last week with a sample client based on the examples from aioquic[2]: https://github.com/djstein/django-http3-example

this example also includes the first pass at async Django REST Framework using adrift[3] based on these GitHub issues:

- https://github.com/encode/django-rest-framework/pull/8617

- https://github.com/encode/django-rest-framework/issues/8496

sources

[1]: https://github.com/pgjones/hypercorn

[2]: https://github.com/aiortc/aioquic

[2]: https://github.com/em1208/adrf

what about hyopercorn ? looks like it supports http3

By using Hypercorn like so:

We're almost ready to start our server! We'll be using the A2AServer class from Google-A2A which under the hood starts a uvicorn server.

FastAPI and Uvicorn are two essential building blocks when developing high-performance Python APIs.

To run the server, you will also need to install Uvicorn:

So I've decided to create another series of articles, and this time talking about another piece of FastAPI development: ASGI servers, and mainly focusing on 🦄 uvicorn due to the evident synergy between both projects 😎.

Finally, whatever file launches your application (in this case, mine is main.py), it is conventional to include that if __name__ == "main": block at the bottom (shown above), to specify the entrypoint to your application. This isn't strictly necessary in many use cases—for instance, if you're writing a REST API using FastAPI and launching it via uvicorn, you don't need this block. But it also doesn't hurt to have it regardless. It's a helpful reminder of where things begin.

This article is written by Marcelo Trylesinski, a > FastAPI expert and > maintainer of Starlette and > Uvicorn. You can check out more of his work > here. All opinions expressed are his own.

Since, app has selenium minimum running requirement would be 1GB RAM on any OS, and free version of any hosting do not provide that, some that provide are limited by build times or shared cpus.

So it was only logical to go through the pain/pleasure of setting up deployment on VM.

Python Backend is deployed on Azure VM(with 4 GB), since it's built on Fastapi their AWSGI support helps keep the server running on long intervals.

This one is using CF Tunnels to Prod to reduce the latency due to server location.

You can see uvicorn docs to learn more https://www.uvicorn.org/

Uvicorn is a lightning-fast ASGI server implementation, using uvloop and httptools. It is designed to run asynchronous Python web applications, particularly those built with frameworks like FastAPI, Starlette, and others.

Uvicorn - An ASGI web server implementation for Python