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Comment by zo1 | Hacker News Reader

You could have a look at Marshmallow perhaps? I use it to great effect with marshmallow-dataclass so I don't have to define the boiler-plate data classes separately to the validation/schema. Essentially the dataclass (with type-hints) becomes the data-validation specification.

Links:

https://pypi.org/project/marshmallow-dataclass/

https://pypi.org/project/marshmallow/

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Worth pointing out Desert, which generates a Marshmallow schema from an Attrs class. You could then integrate this with Apispec or Marshmallow-Jsonschema.

https://pypi.org/project/desert/

https://pypi.org/project/marshmallow-jsonschema/

https://pypi.org/project/apispec/

Thanks, I've had a look at Marshmallow in the past, but it's still doing the extra bits of dealing with the extra bits of serialization, it never really felt all that dissimilar to Pydantic.

What I've really been looking for something that I can just use to check a data structure i'm passing in to a function call is valid. One use case is related to state machines, where I'm providing some data along with a transition name, and want to make sure the combination of transition + data is valid.

Design-by-contract, perhaps? There are a couple libraries like this currently, and you could pretty easily write your own framework for it.

Also, Attrs and Pydantic both support arbitrary additional validation on fields.

Pedantic has a validate_arguments decorator that while in beta, I think does what you want: https://pydantic-docs.helpmanual.io/usage/validation_decorat...

Sounds like you want jsonschema.

I have used a combo of attrs and fastjsonschema to do dataclass validation on instance construction.

It works great for a python stack and you can generate some clean looking code if you have a reusable data class package

I use marshmallow-dataclass in an API client lib I've been continuously working on for a while for work.

It's great stuff, but I'm always looking for alternatives.

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