genmon VS datamodel-code-generator

Hey all, I just installed three Unifi cameras around our property. I'd like to set up a few monitors around the home that show the RTSP streams in addition to my generator monitor dashboard (https://github.com/jgyates/genmon) as well as a little webpage that shows the state of our garage doors and driveway gate that I created with a couple Pico Ws (it's a _super basic_ HTML page that just refreshes every thirty seconds). I think I have the general structure pretty well mapped out in my head: three quadrants running VLC instances, plus one quadrant with two Chrome windows showing my simple status page and genmon. Planning to use a simple Python script to set up the windows on boot via xdotool, which then turns the streams and monitor on/off based on inputs from a PIO motion sensor. Might add a button to toggle through fullscreening the videos. Anyway, my question: can a Zero 2 W handle playing back three RTSP streams plus Chrome rendering two very simple sites? Given my experience with the Zero W, I think it wouldn't work. The 2 is pretty beefy, though, except for the limited RAM. I don't care too much; I'll find a use for them eventually anyway, and I can't find them in stock regardless (although they seem to be coming gradually back). What do you all think?

I run GenMon on a raspi out near my generator and my tank has a remote ready gauge. I'm working on having GenMon read the gauge directly via a hall effect sensor. GenMon publishes to MQTT and I integrate with Home Assistant that way. I'm not sure of your propane use case, but if it's for a generator, then this might be useful.

if you good with tinkering with stuff you might use this to do a test idle runs: https://github.com/jgyates/genmon

Like generating pydantic models or dataclasses for an OpenAPI schema? I haven't needed to go in that direction myself, but this[0] looks promising!

Apologies if I've misunderstood your comment

https://koxudaxi.github.io/datamodel-code-generator/

I'm sorry, but you have completely misunderstood the purpose of Open API.

It is not a specification to define your business logic classes and objects -- either client or server side. Its goal is to define the interface of an API, and to provide a single source of truth that requests and responses can be validated against. It contains everything you need to know to make requests to an API; code generation is nice to have (and I use it myself, but mainly on the server side, for routing and validation), but not something required or expected from OpenAPI

For what it's worth, my personal preferred workflow to build an API is as follows:

1. Build the OpenAPI spec first. A smaller spec could easily be done by hand, but I prefer using a design tool like Stoplight [0]; it has the best Web-based OpenAPI (and JSON Schema) editor I have encountered, and integrates with git nearly flawlessly.

2. Use an automated tool to generate the API code implementation. Again, a static generation tool such as datamodel-code-generator [1] (which generates Pydantic models) would suffice, but for Python I prefer the dynamic request routing and validation provided by pyapi-server [2].

3. Finally, I use automated testing tools such as schemathesis [3] to test the implementation against the specification.

[0] https://stoplight.io/

[1] https://koxudaxi.github.io/datamodel-code-generator/

[2] https://pyapi-server.readthedocs.io

[3] https://schemathesis.readthedocs.io

The site also provide a link to the github repo of the underlying program.

Not sure who owns/hosts the site, but its based on this github repo.

That's what datamodel-code-generator propose.

had generally good experience creating typed wrappers for api's with json-schema-to-pydantic[0] converter

[0] https://github.com/koxudaxi/datamodel-code-generator

To save you some work, if you have already an OpenAPI specification at hand, you can use datamodel-code-generator to generate your Pydantic models from the spec.

And there are code generators for it! https://github.com/koxudaxi/datamodel-code-generator/