starlette VS quart

Fast Execution: FastAPI is built on top of Starlette and Pydantic, making it one of the fastest Python frameworks for building APIs.

The framework's efficiency comes from its use of Starlette for building asynchronous web services and Pydantic for robust data validation and serialization, powered by Python's type hints. Pydantic has recently announced the official release of Pydantic V2 (June 2023), which is a ground-up rewrite that offers many new features and performance improvements, so make sure to be using that instead of V1.

Uvicorn + Starlette 8k requests/s

Starlette documentation

Same here, but without these weird utils it doesn't get any better.

I have 7 YoE with Django. Its great at so many things. You see some code, like middlewares, and immediately understand what's going on.

Now, we also have Starlette. The base of all new, fancy asgi libraries. Here's the base middleware class.

https://github.com/encode/starlette/blob/8d7a1cacfb3e1a30cbb...

In the last couple of years I heard 'we're running fastapi on production. Wanna join us?' so many times... but the reality is that it's still not suitable for prod. Who wants to work with a code like that if you have a readable, stable Django? I'm clueless.

Set up Starlette, a tool we'll use to make async requests

I never used websockets in FastAPI so I wouldn't know how to guide you more, but Middleware in Websockets are 100% supported by Starlette : https://github.com/encode/starlette/issues/641

Websockets are the way but I would not recommend django as it's still not fully async. I would go for other tools.

Sorry. It's not Quartz, it's just Quart https://pgjones.gitlab.io/quart/

If you're looking for an experience that's very similar to Flask you can use Quart which is inspired by Flask. Quart even has a guide about how to migrate from a Flask application to using Quart! Flask's own documentation for async views actually recommends using Quart in some cases due to the performance hit from using a new event loop per request.

Flask getting async support is a huge step for the asyncio web ecosystem in Python. I wonder how Flask's ASGI support will evolve in parallel with Quart[1] which bills itself as the ASGI version of Flask and is maintained by a member of the Pallets team. One of the maintainers of Werkzeug even recommended using Quart[2]

[1] https://pgjones.gitlab.io/quart/

[2] https://github.com/pallets/werkzeug/issues/1322#issuecomment...

What we get with the async part of this release - If you would like to run an async library or your own async code from a flask route you can do that now. This is super useful, where let's say we have some async code that fetches data from many sources concurrently, or call multiple a few ML prediction endpoints at the same time (as long as they don't time out) using httpx and respond with some sort of outcome, or finally try that cool new async-only database library. A current (v2) limitation is that the you can't make concurrent requests using just the current asyncio implementation (an alternative with Flask API and ASGI: Quart). Typically in production gunicorn or uwsgi + threads/processes/gevent-eventlet is used and this makes Flask behave asynchronously. More here and here if interested.

For people looking to do async stuff with Flask, there is also Quart! It’s essentially an async port of Flask, with all your favorite, familiar methods!

I agree with the transition issues, Quart has this awkward code to try and get around this.

Appreciate the feedback! I forgot to pimp my favorite web framework, Quart, but I can attest to Flask and even Django being great. I always looked down on Django as too big but then I used it for my current company and I realized I was totally wrong. Easy to pick up, lots of functionality if you want it, but it doesn't force it on you.