apiflask VS uvicorn

*some options that were mentioned in the thread I linked to include - Starlite (made to bypass perceived shortcomings of FastAPI) - Flama (Starlette w/ Marshmellow instead of Pydantic) - APIFlask (Flask w/ Pydantic) - Django Ninja - Quart-Schema

APIFlask (Flask with Pydantic and all the other good stuff)

It would be interesting to learn if the author has considered the APIFlask extension or Quart-Schema with Quart. Both offer API functionality built on the Flask API.

Good metaphor! For people who are comparing FastAPI to Flask, check out APIFlask, it's at the same compare level with FastAPI:

FastAPI & Uvicorn

This tells Heroku to run uvicorn, which is a web server implementation in Python.

FastAPI uses Uvicorn, an ASGI (Asynchronous Server Gateway Interface) web server implementation for Python.

Now, let’s run our FastAPI application using Uvicorn: uvicorn main:app --reload

Uvicorn + Starlette 8k requests/s

I switched to Hypercorn because Uvicorn currently supports HTTP/1.1 and WebSockets as mentioned at https://www.uvicorn.org

This will set up Chroma and run it as a server with uvicorn, making port 8000 accessible outside the net docker network. The command also mounts a persistent docker volume for Chroma's database, found at chroma/chroma from your project's root.

There's an open discussion under the Uvicorn repository and we prepared a repository for Reproduction GitHub Repo

FastAPI is a popular Python Web framework that developers use to create RESTful APIs. It is based on Pydantic and Python-type hints that assist in the serialization, deserialization, and validation of data. In this tutorial, we will use FastAPI to create a simple "Hello World" application. We test and run the application locally. FastAPI requires a ASGI server to run the application production such as Uvicorn.

- [3] https://github.com/encode/uvicorn/issues/527