The scikit-multilearn is a Python library for performing multi-label classification. It is compatible with the scikit-learn and scipy ecosystems and uses sparse matrices for all internal operations; provides native Python implementations of popular multi-label classification methods alongside a novel framework for label space partitioning and division and includes modern algorithm adaptation methods, network-based label space division approaches, which extracts label dependency information and multi-label embedding classifiers. The library provides Python wrapped access to the extensive multi-label method stack from Java libraries and makes it possible to extend deep learning single-label methods for multi-label tasks. The library allows multi-label stratification and data set management. The implementation is more efficient in problem transformation than other established libraries, has good test coverage and follows PEP8. The project is BSD-licensed.