Jooby VS fastapi

One of the good things about it is that using asynchrony is optional. If you don't have to call out anywhere to build the response, processing can all stay in the handler's calling thread. If you do, you can return a future and have the library handle the async for you.

One downside is that it is based on Jetty which isn't considered the most performant backend. A lib with a similar API but based on Netty is Jooby [1] which scores well in the Techempower benchmarks.

[1] - https://jooby.io/

Jooby and Helidon SE are among the best.

The code snippet gave me a vibe like it was jooby Looks cool, I suggest maybe start incorporating Project Loom virtual threads in the future.

Speaking of backend development, recently I gave Jooby[1] a try after discovering it was one of the world's top performer in Tech Empower's web framework benchmark[2].

Surprisingly enough, it's terribly easy to put together a REST API with Jooby. I wonder why it's adoption rate is so low.

[1] https://jooby.io/

[2] https://www.techempower.com/benchmarks/

Do you need to use Spring btw? If you want to broaden the tool selection I've had great success with i.e Jooby (https://jooby.io/) together with Kotlin coroutines. Another alternative is the KTOR framework.

Jooby I think is the best bet. https://jooby.io/ watch out for jooby dot org I think someone sniped the domain.

Spring Boot or JAXRS. I personally use Jooby a lot which is similar in style to spark but has annotation support and isn't a singleton.

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.

FastAPI is a modern, fast web framework for building APIs with Python 3.7+ that automatically generates OpenAPI and JSON Schema documentation. While FastAPI simplifies API development, manually creating and updating API documentation can still be a time-consuming task. In this blog post, we’ll explore how to leverage FastAPI’s automatic documentation generation capabilities, specifically focusing on Swagger and ReDoc, and how to streamline the process of documenting your APIs.