Walk a deeply nested pydantic model, type alias or dataclass as if data was already put into it. While pydantic allows you to validate data with a model, type-inspector allows you to validate operations on data using a model before any data has been passed.
pip install type-inspectorLet's pick an inspector for a model and try doing a few operations on it:
from type_inspector import pick_inspector
from pydantic import BaseModel
class NestedModel(BaseModel):
b: dict[str, int | list[bytes]]
class MyModel(BaseModel):
a: list[NestedModel]
inspector = pick_inspector(MyModel, ["MyModel"])
result = inspector.a[1].b["hello"][11]
print(result.wrapped) # bytesIf you try to access a property or item that cannot exist, an InspectionError will be raised.
This library was originally created to mimic javascript syntax so Model["a"]["b"] is the same as Model.a.b. However, this notation is not necessarily correct in terms of python syntax. But it will definitely make sure that the operations you write will work on a JSON object that the model was created for.