mangum VS turf

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.

to measure distances and convert between our parameters I'm using TurfJS, for which binding is even more trivial:

Turf.js is an open-source geospatial analysis library that can process various location data, such as the center of gravity and distance calculations.

Isochrones are manually calculated using turf.js assuming 1.2m/s walking speed after the subway trip. These are simple buffers around each station/prior isochrone and do not take the street network into account.

Not to take away from you learning, which I think is awesome, I was wondering if you know about http://turfjs.org/ which provides a lot of simple modules … and is surprisingly hard to find. Their `distance` modules may be relevant in this case.

you can use client side libraries like Turfjs to do buffers https://github.com/Turfjs/turf/tree/master/packages/turf-buffer

Tools: custom Javascript (with heavy use of turf.js) for data processing and creating the 3D model, Blender, 3D printing, lost wax casting

I've integrated https://turfjs.org/ with mapbox before and it was pretty fun

References Amazon Location Service Turf.js MapLibre GL JS Leaflet OpenLayers Cesium Mapbox GL JS