clj-kondo VS fastapi

My best suggestion here would be clj-kondo with flycheck-clj-kondo in Emacs. I really can't recommend it enough and would have killed to have it when I was learning Clojure. Not only will it underline all of those references to (now) undefined vars, but it can tell you about numerous little mistakes like mixing up arguments orders in (say) sequence functions, misplaced docstrings that get discarded, style conventions, etc. It's staggering how good it is even for a language as dynamic as Clojure.

The clj-kondo linters are worth reading.

Sure!

Spec: https://github.com/edn-format/edn

Example (linter config): https://github.com/clj-kondo/clj-kondo/blob/634294183a0aa2ca...

Clj-kondo doesn't produce an AST but you could easily combine the analysis output with the AST produced by rewrite-clj by matching on location.

But if you want full support, you can implement a hook: https://github.com/clj-kondo/clj-kondo/blob/master/doc/hooks.md

Please configure and use tools like clj-kondo and kibit. Kibit will report areas where you could write idiomatic clojure instead. Eg, it should catch all those (if (condition) true false) and ask you to replace it with (condition). Or if you really need a boolean value, use boolean to coerce it.

Try clj-kondo, a Clojure linter which will tell you about arity errors and more, before you even evaluate your code.

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: