fklearn applies functional programming paradigms to machine learning workflows, providing composable and reusable ML components. It focuses on validation, production readiness, and reproducibility. The library integrates with popular ML backends including LightGBM, XGBoost, and CatBoost, and aims to make production ML models easier to achieve.