kotlin4example VS fastapi

This tool seems like it is a nice markdown based CMS but I don't see too many features related to the more difficult parts of doing technical documentation. Like having working code samples.

I attempted a Kotlin centric documentation framework a while ago to address this: https://github.com/jillesvangurp/kotlin4example

I mainly use it to generate the documentation for my Elasticsearch Kotlin Client (jillesvangurp/es-kotlin-client). The idea there is that all examples and source samples are correctly compiling Kotlin code that I can get the output of when they run (e.g. a println). Running the tests, actually generates the documentation markdown. Using a dsl and multiline strings, I can mix lambda code blocks, markdown, or markdown inside files. For the lambda blocks, it figures out the source and line numbers using reflection. But it can also grab source samples based on comment markers. For bigger blobs of markdown, it's easier to grab the content from markdown files. For smaller sections of markdown, I can use inline multi line strings or a Kotlin DSL.

The main benefit of this is that my examples update as I change and refactor the code base. Also, since it runs as part of my tests, I know when examples break.

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.