Parisa Gregg continues a series on RStudio Connect and Python:
FastAPI is a light web framework and as you can probably tell by the name, it’s fast. It provides a similar functionality to Flask in that it allows the building of web applications and APIs, however it is newer and uses the ASGI (Asynchronous Server Gateway Interface) framework. One of the nice features of FastAPI is it is built on OpenAPI and JSON Schema standards which means it has the ability to provide automatic interactive API documentation with SwaggerUI. You also get validation for most Python data types with Pydantic. FastAPI is therefore another popular choice for data scientists when creating APIs to interact with and visualize data.
In this blog post we will go through how to deploy a simple machine learning API to RStudio Connect.
I’ve taken pretty well to FastAPI for rapid API development. I haven’t had to worry about scaling it out too much, so I’m not sure how well that works in practice. Still, for single-user or few-user apps, FastAPI definitely works well.