  The classification problem's complexity assessment is an essential element of
many topics in the supervised learning domain. It plays a significant role in
meta-learning -- becoming the basis for determining meta-attributes or
multi-criteria optimization -- allowing the evaluation of the training set
resampling without needing to rebuild the recognition model. The tools
currently available for the academic community, which would enable the
calculation of problem complexity measures, are available only as libraries of
the C++ and R languages. This paper describes the software module that allows
for the estimation of 22 complexity measures for the Python language --
compatible with the scikit-learn programming interface -- allowing for the
implementation of research using them in the most popular programming
environment of the machine learning community.
