fklearn: Functional Machine Learning

fklearn uses functional programming principles to make it easier to solve real problems with Machine Learning.

The name is a reference to the widely known scikit-learn library.

fklearn Principles

1. Validation should reflect real-life situations.
2. Production models should match validated models.
3. Models should be production-ready with few extra steps.
4. Reproducibility and in-depth analysis of model results should be easy to achieve.

Documentation | Getting Started | API Docs | Contributing |

Installation

To install via pip:

pip install fklearn

To install with optional dependencies:

pip install fklearn[lgbm]       # LightGBM support
pip install fklearn[xgboost]    # XGBoost support
pip install fklearn[catboost]   # CatBoost support
pip install fklearn[all_models] # All model backends
pip install fklearn[all]        # All models + tools

Development with UV

Setup

uv sync --extra devel

Running Tests

uv run pytest --cov=src/

Linting

uv run ruff check src/ tests/
uv run ruff format src/ tests/

Adding Dependencies

uv add <package-name>          # runtime dependency
uv add --dev <package-name>    # dev dependency

License

Apache License 2.0