sktime is a widely used scikit-learn compatible library for learning with time series. sktime is easily extensible by anyone, and interoperable with the pydata/numfocus stack. This tutorial explains how to write your own sktime estimator, e.g., forecaster, classifier, transformer, by using sktime’s extension templates and testing framework. A custom estimator can live in any local code base, and will be compatible with sktime pipelines, or scikit-learn. A continuation of the sktime introductory tutorial at pydata [link]