Scikit-learn Pipelines and Preprocessing Cheat Sheet

Scikit-learn pipelines are workflow tools that chain preprocessing transformers and estimators into a single composable object. Located in sklearn.pipeline and sklearn.compose, they ensure reproducible data transformations, prevent data leakage during cross-validation, and streamline hyperparameter tuning. Pipelines enforce that each transformation step learned from training data (scaling means, encoding categories) is applied identically to validation and test folds. Key mental model: think of pipelines as assembly lines where each station (transformer) modifies the data in a consistent, repeatable way — transformers never see test data during fit, only during transform.