In the spirit of providing researchers with the ability to benchmark optimization strategies on tasks derived from real-world data, our group recently introduced Olympus. This Python package provides users with the ability to benchmark the performance of optimization algorithms on emulated experiments from chemistry and materials science (core classes and their interactions are shown in Figure ). Yet, many features of practical relevance are still lacking from Olympus, preventing researchers from fully capitalizing on its intended usage. In this work, we detail several recent extensions to Olympus. In summary, we contribute the following: