Recently I have started to use hydra to manage the configs in my application. I use Structured Configs to create schema for .yaml config files. Structured Configs in Hyda uses dataclasses for type checking. However, I also want to use some kind of validators for some of the parameter I specify in my Structured Configs (something like this).
Do you know if it is somehow possible to use Pydantic for this purpose? When I try to use Pydantic, OmegaConf complains about it:
omegaconf.errors.ValidationError: Input class 'SomeClass' is not a structured config. did you forget to decorate it as a dataclass?
For those of you wondering how this works exactly, here is an example of it:
import hydra
from hydra.core.config_store import ConfigStore
from omegaconf import OmegaConf
from pydantic.dataclasses import dataclass
from pydantic import validator
@dataclass
class MyConfigSchema:
some_var: float
@validator("some_var")
def validate_some_var(cls, some_var: float) -> float:
if some_var < 0:
raise ValueError(f"'some_var' can't be less than 0, got: {some_var}")
return some_var
cs = ConfigStore.instance()
cs.store(name="config_schema", node=MyConfigSchema)
@hydra.main(config_path="/path/to/configs", config_name="config")
def my_app(config: MyConfigSchema) -> None:
# The 'validator' methods will be called when you run the line below
OmegaConf.to_object(config)
if __name__ == "__main__":
my_app()
And config.yaml :
defaults:
- config_schema
some_var: -1 # this will raise a ValueError