starlite VS fastapi

For the past one and a half years 😁. Checkout our docs https://starliteproject.dev/

#1286 is the issue tracking the removal of our last internal Pydantic datastructure, and PR #1382 has the addition of attrs based signature modelling. Once those are merged you will be able to use Starlite without Pydantic.

You can go to Open an Issue and open an issue for a feature request/enhancement and describe basically the behavior you are wanting to see.

Falcon FastAPI Sanic Starlite (disclosure: I do work here)

for server side , starliteproject.dev/, only python async framwork worth looking into.

Well, I'm not objective but I'd say Starlite (https://github.com/starlite-api/starlite) is a might fine codebase. You can also learn a lot about tooling and typing going through it.

I have mentioned your concerns to the Starlite discussions board - https://github.com/starlite-api/starlite/discussions/1183

You can find the complete changelog on our v1.51.0 GitHub release page.

It has been an interesting exercise developing this wrapper component. The fact that it seamlessly integrates with the FastAPI framework is just a bonus for me; I didn't plan for it since I hadn't learned FastAPI at the time. I hope you find this post useful. Thank you for reading, and stay safe as always.

FastAPI is a modern, high-performance web framework for building APIs with Python, based on standard Python type hints.

In this tutorial, I will demonstrate how to use Burr, an open source framework (disclosure: I helped create it), using simple OpenAI client calls to GPT4, and FastAPI to create a custom email assistant agent. We’ll describe the challenge one faces and then how you can solve for them. For the application frontend we provide a reference implementation but won’t dive into details for it.

That’s when I found FastAPI.

FastAPI & Uvicorn

Discussion at FastAPI GitHub: https://github.com/tiangolo/fastapi/issues/2696

An API application framework (such as FastAPI)

It’s been my experience that async Python frameworks tend to turn IO bound problems into CPU bound problems with a high enough request rate, because due to their nature they act as unbounded queues.

This ends up made worse if you’re using sync routes.

If you’re constrained on a resource such as a database connection pool, your framework will continue to pull http requests off the wire that a sane client will cancel and retry due to timeouts because it takes too long to get a connection out of the pool. Since there isn’t a straightforward way to cancel the execution of a route handler in every Python http framework I’ve seen exhibit this problem, the problem quickly snowballs.

This is an issue with fastapi, too- https://github.com/tiangolo/fastapi/issues/5759

Fast API.