Tornado VS fastapi

I am not expert in these but I thought Tornado's ioloop was readable enough for me to learn more event loops. Mostly, it was being implemented in pure Python.

https://github.com/tornadoweb/tornado/blob/branch4.5/tornado...

(Had to be in 4.5 because the newer versions 5.x and 6.x, it's switched to Python's stdlib asyncio)

I am a bit confused, Tornado is web server like a apache http server, or a framework like django, or both?

For Python, I use Tornado.

tornado? this https://github.com/tornadoweb/tornado ?

I'm writing a Node app that talks to a server that uses Tornado, a Python networking framework. The server uses WebSocket and structured JSON to expose RPCs, like sign_on called with the following message:

I've been using Python's Tornado (http://www.tornadoweb.org/) for years now.

Now on version 6, it's fast, well maintained, mature, and has good docs with readable code.

@bdarnell has done an excellent job maintaining it.

Here's one example:

Tornado supported async style co-routines before asyncio was a thing. Now it uses asyncio under the hood by default -- and it did so with an exceptionally smooth transition.

Tornado is another micro framework aimed at a specific use case: asynchronous networking applications. Tornado is well-suited for creating services that open a great many network connections and keep them alive that is, anything involving WebSockets or long polling. Moreover, It requires Python 3.5 or higher and drops Python 2 support entirely.

How to fix tornado.util.TimeoutError: Operation timed out after 5 seconds on tornado test debug?

Here's an official demo chat app using websocket: https://github.com/tornadoweb/tornado/tree/master/demos/websocket, though you should read the docs on websocket for understanding the code.

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.