DriConfig

A Pydantic-ish way to manage your project's YAML configurations.

CI/CD
Package

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Documentation: https://dribia.github.io/driconfig

Source Code: https://github.com/dribia/driconfig

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The usage of YAML files to store configurations and parameters is widely accepted in the Python community, especially in Data Science environments. DriConfig provides a clean interface between your Python code and these YAML configuration files.

It is heavily based on Pydantic's Settings Management, preserving its core functionalities and advantages.

Key features

• Subclassing the DriConfig class we create an interface to any YAML configuration file.
• Our project's configurations are then attributes of this class.
• They are automatically filled with the values in the YAML configuration file.
• We can define complex configuration structures using Pydantic models.
• We preserve Pydantic's type casting and validation!

Installation

This project resides in the Python Package Index (PyPI), so it can easily be installed with uv or pip.

Using uv (recommended)

uv is a fast Python package installer and resolver.

uv pip install driconfig

Or add it to your project:

uv add driconfig

Using pip

pip install driconfig

Usage

You can import the DriConfig class from the driconfig package and create your own configuration classes.

from driconfig import DriConfig

Examples

Let's say we have a YAML configuration file config.yaml with the following data:

# config.yaml
model_parameters:
  eta: 0.2
  gamma: 2
  lambda: 1

date_interval:
  start: 2021-01-01
  end: 2021-12-31

Then we can configparse with driconfig as follows:

from datetime import date
from typing import Dict

from driconfig import DriConfig, DriConfigConfigDict
from pydantic import BaseModel


class DateInterval(BaseModel):
  """Model for the `date_interval` configuration."""
  start: date
  end: date


class AppConfig(DriConfig):
   """Interface for the config/config.yaml file."""

    """Configure the YAML file location."""
    model_config = DriConfigConfigDict(
        config_folder=".",
        config_file_name="config.yaml",
    )
   model_parameters: Dict[str, float]
   date_interval: DateInterval

config = AppConfig()
print(config.model_dump_json(indent=4))
"""
{
    "model_parameters": {
        "eta": 0.2,
        "gamma": 2.0,
        "lambda": 1.0
    },
    "date_interval": {
        "start": "2021-01-01",
        "end": "2021-12-31"
    }
}
"""

Contributing

Check the CONTRIBUTING site for guidelines on how to contribute to this project.

License

DriConfig is distributed under the terms of the MIT license. Check the LICENSE file for further details.