AlphaPy

Why we included this project

AlphaPy is a Python AutoML framework aimed at two forecasting problems at once: building trading systems and predicting sporting-event outcomes. You describe an experiment in a YAML config file, and the framework handles feature engineering, model selection, and evaluation, running blended or stacked ensembles across scikit-learn, Keras, XGBoost, LightGBM, and CatBoost. The MarketFlow component targets trading-system development and portfolio analysis, while SportFlow covers sports prediction, so one codebase serves both. Its documentation walks through the full pipeline from data preparation to backtesting, which makes it a decent reference for structuring an AutoML-style workflow around pandas and scikit-learn. One caveat: active development has moved to the commercial AlphaPy Pro edition, so treat the open-source version as a starting point rather than something you will get long-term support for.