Unpack dict based on pydantic BaseModel into model

deserialize_pydantic.py

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from pydantic import BaseModel
from typing import Optional, Type, TypeVar


Model = TypeVar("Model", bound=BaseModel)


def _load_model(t: Type[Model], o: dict) -> Model:
    populated_keys = o.keys()
    required_keys = set(t.schema()['required'])
    missing_keys = required_keys.difference(populated_keys)
    if missing_keys:
        raise ValueError(f'Required keys missing: {missing_keys}')
    all_definition_keys = t.schema()['properties'].keys()
    return t(**{k: v for k, v in o.items() if k in all_definition_keys})

if __name__ == '__main__':
    class Car(BaseModel):
        year: Optional[int]
        name: str
        company: str
        
    car_dict = {'name': 'Uncivic', 'company': 'Fonda'}
    car = _load_model(Car, car_dict)
    print(car)
    

So I forked to https://gist.github.com/meadsteve/2f720bc3a6ca9f1166ec3d1f3ed14ed8 It adds a TypeVar Model which has to be an instance of BaseModel

So I forked to https://gist.github.com/meadsteve/2f720bc3a6ca9f1166ec3d1f3ed14ed8 It adds a TypeVar Model which has to be an instance of BaseModel

Nice, works perfectly, I merged it. Thanks! :)

If pydantic ever changes to having Config.extra = 'forbid' as default or the application uses it a lot, this solution will not handle unspecified fields nicely anymore, which is logical, but kind of the purpose of how it is written to just care about the explicitly optional fields and drop the rest.

Thanks, man I love it.

An option to throw on unknown/extraneous items could be useful. Ideally respecting the Config.extra of the model by default.

Hi - can this deal with nested dictionaries as well?

@mg3146 pydantic has support for nested dictionaries so I think it should work

nice, thanks!

All credit for writing this goes to @meadsteve, it has worked great for adding typing to code generators. Not sure if it is possible to move gists between github accounts. Anyhow, thank you for an awesome snippet