In March 2025, Gnn Code developed a new Results class for the oemof/oemof-solph repository, focusing on improving access to model outputs. The class was designed in Python using object-oriented programming principles and data analysis techniques, enabling lazy conversion of model variables into pandas DataFrames. By guaranteeing a single conversion per dataset, the implementation reduced memory overhead and streamlined post-processing workflows. This approach provided a clean API for developers and decision-makers to efficiently access and analyze results. The work demonstrated a thoughtful balance between usability and resource management, addressing minimal design requirements while enhancing productivity for users of the library.