skchange: Fast and Flexible Algorithms for Changepoint Detection

skchange is an open‑source Python library that provides fast and flexible algorithms for detecting structural changes in time series. It offers modular, composable methods based on cost minimisation and statistical tests, and includes features such as anomalous segment detection, high‑dimensional data support, automatic penalty calibration, and a wide range of built‑in costs and tests. The library follows scikit‑learn conventions and uses Numba for high computational performance, with source code and documentation available on GitHub.

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