reflex VS fastapi

Hey thanks for the feedback. We're working on relaxing our dependencies [1] to make reflex more compatible. Do you remember what libraries you had the conflict with?

[1] https://github.com/reflex-dev/reflex/pull/2796

Thanks! Pue looks cool, thanks for sharing. I see some similarities to https://reflex.dev in terms of providing a declarative dom expression language with built-in conditionals and loop primitives.

In the dynamic world of web development, Python has emerged as a dominant force, especially in backend development – the primary focus of this blog post. Although it's worth mentioning that there are ongoing efforts to use Python for the frontend as well, like Reflex (previously known as Pynecone, they presumably had to change their name because of Pinecone vector database), which even garnered support from Y Combinator. Samuel Colvin (creator of Pydantic) is also working on FastUI (he literally just released the first version in December 2023).

They have a ready to use LLM chat App, which makes it more likely I will check it out.

https://github.com/reflex-dev/reflex

We will use Reflex to build this chatbot.

To learn more about Reflex, you can read here: https://reflex.dev/

Reflex is an open-source, full-stack Python framework that makes it easy to build and deploy web apps in minutes. You have most of the features of a frontend library like Reactjs and a backend framework like Django in one with ease in development and deployment. All while developing in a single language PYTHON.

Repo : https://github.com/reflex-dev/reflex

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.

We will create our API using FastAPI, a modern high-performance web framework for building fast APIs with Python. It is designed to be easy to use, efficient, and highly scalable. Some key features of FastAPI include:

FastAPI is a modern, fast, web framework for building APIs with Python 3.7+ based on standard Python type hints. It is designed to be easy to use, fast to run, and secure. In this blog post, we’ll explore the key features of FastAPI and walk through the process of creating a simple API using this powerful framework.