Pydantic Validation Example

This simple example uses a --config option to load a configuration from a YAML file and uses pydantic to validate the file before continuing.

An example typer app:

simple_app.py

from typing import Any, Dict

from pydantic import BaseModel
import typer
from typer_config import yaml_loader, conf_callback_factory


class AppConfig(BaseModel):
    arg1: str
    opt1: str
    opt2: str


def validator_loader(param_value: str) -> Dict[str, Any]:
    conf = yaml_loader(param_value)
    AppConfig.validate(conf)  # raises an exception if not valid
    return conf


validator_callback = conf_callback_factory(validator_loader)

app = typer.Typer()


@app.command()
def main(
    arg1: str,
    config: str = typer.Option(
        "",
        callback=validator_callback,
        is_eager=True,  # THIS IS REALLY IMPORTANT (1)
    ),
    opt1: str = typer.Option(...),
    opt2: str = typer.Option("hello"),
):
    typer.echo(f"{opt1} {opt2} {arg1}")


if __name__ == "__main__":
    app()

1. You must use is_eager=True in the parameter definition because that will cause it to be processed first. If you don't use is_eager, then your parameter values will depend on the order in which they were processed (read: unpredictably).

With a config file:

config.yml

arg1: stuff
opt1: things
opt2: nothing

And invoked with python:

$ python simple_app.py --config config.yml
things nothing stuff

$ python simple_app.py --config config.yml others
things nothing others

$ python simple_app.py --config config.yml --opt1 people
people nothing stuff

Note: this package also provides json_conf_callback, toml_conf_callback, and dotenv_conf_callback for those file formats.