starlette VS mangum

Fast Execution: FastAPI is built on top of Starlette and Pydantic, making it one of the fastest Python frameworks for building APIs.

The framework's efficiency comes from its use of Starlette for building asynchronous web services and Pydantic for robust data validation and serialization, powered by Python's type hints. Pydantic has recently announced the official release of Pydantic V2 (June 2023), which is a ground-up rewrite that offers many new features and performance improvements, so make sure to be using that instead of V1.

Uvicorn + Starlette 8k requests/s

Starlette documentation

Same here, but without these weird utils it doesn't get any better.

I have 7 YoE with Django. Its great at so many things. You see some code, like middlewares, and immediately understand what's going on.

Now, we also have Starlette. The base of all new, fancy asgi libraries. Here's the base middleware class.

https://github.com/encode/starlette/blob/8d7a1cacfb3e1a30cbb...

In the last couple of years I heard 'we're running fastapi on production. Wanna join us?' so many times... but the reality is that it's still not suitable for prod. Who wants to work with a code like that if you have a readable, stable Django? I'm clueless.

Set up Starlette, a tool we'll use to make async requests

I never used websockets in FastAPI so I wouldn't know how to guide you more, but Middleware in Websockets are 100% supported by Starlette : https://github.com/encode/starlette/issues/641

Websockets are the way but I would not recommend django as it's still not fully async. I would go for other tools.

Hey! I was in the same place as you are, and the best solution I found was to use Mangum (https://mangum.io/). I believe it also works with Django. Mangum is an adapter that transforms lambda events into the corresponding structure to be received by your Framework API endpoints. We are currently using it with FastAPI and it's great. We code our backend without thinking about whether it will run on Lambda, and Magum takes care of the rest.

In the real world I'm never using static cloud resources. It's all serverless, containers, or horizontal auto-scaling. I let the infrastructure handle asynchronous scaling when needed. For FastAPI specifically I've used Mangum: https://mangum.io/ to provide the asynchronous invocation below the ASGI layer. Then all my FastAPI code can just be synchronous.

I discovered https://github.com/jordaneremieff/mangum which basically transforms a fastapi app to be compatible with aws lambda.

Should I create only 1 apigtw resource with 1 lambda and use mangum + fastapi for my rest api ?

Mangum: For the integration of the Aws Lambda and the Api Gateway with the FastApi

If you go the lambda route, you can use DRF (or any ASGI app) using https://mangum.io/

Yes, it's possible to wrap any asgi app to run in a lambda. Check out Mangum https://github.com/jordaneremieff/mangum

But we do not have a handler function, do we? We have a Mangum object wrapping the FastAPI application. Luckily, the Mangum object acts as a handler function, so we can just add the following in example/src/app/__init__.py:

I've used fastapi in a lambda. The package Mangum simplifies the conversion of lambda handler to a more tradition request.