  This work proposes a framework of benchmark functions designed to facilitate
the creation of test cases for numerical optimisation techniques. The
framework, written in Python 3, is designed to be easy to install, use, and
expand. The collection includes some of the most used multi-modal continuous
functions present in literature, which can be instantiated using an arbitrary
number of dimensions. Meta-information of each benchmark function, like search
boundaries and position of known optima, are included and made easily
accessible through class methods. Built-in interactive visualisation
capabilities, baseline techniques, and rigorous testing protocols complement
the features of the framework. The framework can be found here:
\url{https://gitlab.com/luca.baronti/python_benchmark_functions
