RESTinio VS fastapi

In my past job, we used https://github.com/Stiffstream/restinio and absolutely loved it. It's not as active but it honestly didn't need much.

Here's a C++ REST framework for you to use too: https://github.com/Stiffstream/restinio

I had a good experience using restinio for a small ASIO HTTP server recently.

It uses restinio https://github.com/Stiffstream/restinio with great success ;)

For networking, pick a networking library. Restinio is a fair choice for HTTP. But, again, feel free to pick others.

You may find this worthwhile: https://github.com/Stiffstream/restinio/issues/101 FWIW, I used Restbed successfully for 3.5 years before switching personal projects to Restino. I've left the job that used Restbed, but I think they are still using it.

Contrary to the direction most people go, I've been writing REST APIs as C++ servers using two different fairly full featured C++ REST frameworks: first using https://github.com/Corvusoft/restbed and more lately using https://github.com/Stiffstream/restinio. These can be peers with any other server, while living on embedded and/or high compute devices for video encode/decode/analysis, deployed ML models, encryption for and remote process communications, model data collection and similar expensive or in-field processing. In both high compute and in-field-no-internet situations creating REST APIs in C++ enables speed and system controls not present in the majority of the mainstream REST frameworks. It's a big world, and here comes ubiquitous high compute...

If you need an embedded C++ HTTP server then there are plenty of libraries/frameworks (in random order): Crow, RESTinio, Boost.Beast, cpp-httplib, http_backend, Pistache, RestBed, served, proxygen, Simple-Web-Server, drogon, oat++.

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.