flask-tables VS fastapi

This is really a matter of preference. I do not use Flask-Admin on my projects, I have always preferred to design my own admin pages than being forced to accept the choices that are imposed by these big extensions. This allows me to have a consistent UI across admin and non-admin pages.

One are that people often complain is that it is hard and/or tedious to build tables with data, which is one of the building blocks most admin pages need. Last year I wrote a blog article where I show how I build tables in my Flask apps: https://blog.miguelgrinberg.com/post/beautiful-interactive-t....

Check https://blog.miguelgrinberg.com/post/beautiful-interactive-tables-for-your-flask-templates and then the Server Side section. That helps you create an API that paginates and searches, so you don't load all data at once, but the relevant/needed data.

jQuery datatables looks perfect. I've found a github repo using it in conjunction with flask. That's the perfect stack for me!

Looks like you need Datatable. See https://blog.miguelgrinberg.com/post/beautiful-interactive-tables-for-your-flask-templates

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.

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: