The idea is simple: write an object's Blueprint once, then whenever you need that object in your @pydantic.dev models, just pass in the parameters. In #machinelearning and #neuroai, we build a lot of Tensors from various parameterisations...

You can also pre-process the raw data using @hooks. The @env:MY_VARIABLE hook loads data from an environment variable. The @value:path.to.val hook references a value in the raw input data. The @import:foo.bar dynamically imports a Python object.

There is an API for building custom @hooks - they're just functions.

👩‍💻 Want to try it? `uv add cyantic` `pip install cyantic` (renamed from 'cast' 🤫)