darts

I would recommend Darts in Python [1]. It's easy to use (think fit()/predict()) and includes * Statistical models (ETS, (V)ARIMA(X), etc) * ML models (sklearn models, LGBM, etc) * Many recent deep learning models (N-BEATS, TFT, etc) * Seamlessly works on multi-dimensional series * Models can be trained on multiple series * Several models support taking in external data (covariates), known either in the past only, or also in the future * Many models offer rich support for probabilistic forecasts * Model evaluation is easy: Darts has many metrics, offers backtest etc * Deep learning scales to large datasets, using GPUs, TPUs, etc * You can do reconciliation of forecasts at different hierarchical levels * There's even now an explainability module for some of the models - showing you what matters for computing the forecasts * (coming soon): a

To be fair, Darts looks pretty good relative to forecast: https://github.com/unit8co/darts I would generally prefer R for this kind of stuff as the experts generally write the code, but Darts seems OK and is well-tested, at the very least (haven't had a chance to use it in anger yet).