Working with benchmark datasets in the Cuby framework

The development and benchmarking of computational chemistry methods relies on comparison with benchmark data. More and larger benchmark datasets are becoming available, and working efficiently with them is a necessity. The Cuby framework provides rich functionality for working with datasets, comes with many ready-to-use predefined benchmark sets, and interfaces with a wide range of computational chemistry software. Here we review the tools Cuby provides for working with datasets and provide examples of more advanced workflows, such as handling large numbers of computations on HPC resources and reusing previously computed data. Cuby has also been extended recently to include two important benchmark databases, NCIAtlas and GMTKN55.