attrs VS transitions

Full support for validation and serialisation of attrs classes and msgspec Structs. Where previously only Pydantic models and types where supported, you can now mix and match any of these three libraries. In addition to this, adding support for another modelling library has been greatly simplified with the new plugin architecture

Pydantic is by far not the only library of its kind, with prominent members of the same class being attrs, cattrs or even plain dataclasses for some use cases.

Anything requiring e.g. setattr, getattr, delattr? Without looking far,

https://github.com/python-attrs/attrs/blob/main/src/attr/_ma...

I was looking for an example of using locals() to "fill a data class from kwargs" or something similar to that. The example here doesn't use locals().

That aside, I generally wouldn't use the kwargs approach shown in this example either. I'd use [dataclasses](https://docs.python.org/3/library/dataclasses.html ) or [attrs](https://www.attrs.org/) instead.

hynek: developer of attrs

I continue to be surprised how easy it can be to consume a SOAP API with the right client libraries. Such as https://docs.python-zeep.org/en/master/ for Python. Now that's not to say it will always work, you can design a terrible API with any mechanism, no SOAP or REST client will help you if the other end has desided to succumb to madness and done something like turn their entire API into just "two endpoints" and driven by the payload content you post to the inbound endpoint, and you have to sit there polling the outbound endpoint with the inbound endpoints response ID because to find out what the eventual response is...

But horror story aside, consuming a decent SOAP endpoint with a good client library can be practically magical.

Between attrs (https://www.attrs.org/), cattrs (https://cattrs.readthedocs.io/), and the aforementioned zeep soap client I've got a serialisation pipeline from soap endpoint into an attrs dataclass with type hints and basic type validation down to a snippet so small it fits right here (type hints removed to minimise size).

  from zeep import helpers

attrs has at least two.

Start with that you know, if you know Excel well, why not start there? I usually recommend Python if you’re new to programming, then you can pick whatever additional libraries you think would benefit the model, and the syntax is highly forgiving. Sounds to me like you’re describing a pretty big finite state machine, with 288 states. Once you encode your idea and some tests, you’ll have the vocabulary (and means) to expand to other model variations such as applying probabilities to different transition states, and opening a whole world of probabilistic models and hidden Markov models, but gotta walk before running :)

BTW, did you check this?

https://github.com/pytransitions/transitions/blob/master/exa...

Transitions

In Python's ecosystem of libraries, there's a nice one called transitions (which I've used in my robotics work). transitions (as the name suggests) lets you define your state machines more declaratively in terms of transitions between states, the rules that govern those transitions, and the triggers that cause these transitions to happen.