Great library for Time series forecasting and anomaly detection. including a bunch of different models and separate tools. All with unified interface so it is easy to compare performance and Mean Average Error.
Darts is a Python library for user-friendly forecasting and anomaly detection on time series. It contains a variety of models, from classics such as ARIMA to deep neural networks. The forecasting models can all be used in the same way, using fit() and predict() functions, similar to scikit-learn.
Darts also offers extensive anomaly detection capabilities. For instance, it is trivial to apply PyOD models on time series to obtain anomaly scores, or to wrap any of Darts forecasting or filtering models to obtain fully fledged anomaly detection models.