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Save henriklindgren/f0f05034ac4b36eafdb7c877e5088f33 to your computer and use it in GitHub Desktop.
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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
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
So I forked to https://gist.github.com/meadsteve/2f720bc3a6ca9f1166ec3d1f3ed14ed8 It adds a TypeVar
Model
which has to be an instance of BaseModel