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We provide an easy to use Python package for (Multiblock) Partial Least Squares regression of univariate and multivariate outcomes. Four state-of-the-art algorithms have been implemented and optimized for robust performance on large data matrices. The statistical package is designed, such that application is straightforward using the Scikit-learn API, hand in hand with its model selection toolbox.