  Performance assessment is a key issue in the process of proposing new machine
learning/statistical estimators. A possible method to complete such task is by
using simulation studies, which can be defined as the procedure of estimating
and comparing properties (such as predictive power) of estimators (and other
statistics) by averaging over many replications given a true distribution;
i.e.: generating a dataset, fitting the estimator, calculating and storing the
predictive power, and then repeating the procedure many times and finally
averaging over the stored predictive powers. Given that, in this paper, we
present sstudy: a Python package designed to simplify the preparation of
simulation studies using SQL database engines as the storage system; more
specifically, we present its basic features, usage examples and references to
the its documentation. We also present a short statistical description of the
simulation study procedure with a simplified explanation of what is being
estimated by it, as well as some examples of applications.
