Developed a wrapped k-cycle generator for the cayleypy/cayleypy Cayley graph library, expanding its graph analytics capabilities with new data generation features. The implementation included a growth-data CSV export and a layer-size computation tailored to wrapped k-cycle structures, supporting advanced research in permutation groups and graph theory. Comprehensive unit tests were written in Python to ensure correctness and prevent regressions, while detailed documentation and usage examples were added to facilitate adoption by other developers and researchers. The work emphasized maintainability and clarity, integrating seamlessly into the existing codebase and enhancing the library’s utility for mathematical and computational graph analysis tasks.