Lara Markus developed a configurable jet-count source for DY weight calculations in the columnflow/columnflow repository, focusing on enhancing analysis flexibility. She replaced the previously hardcoded jet multiplicity with a customizable njet column, allowing analysts to specify alternative jet collections directly through configuration. This approach, implemented in Python and leveraging her skills in data analysis and physics analysis, improved both the maintainability and adaptability of the DY weight calculation process. By enabling analysis-specific jet selection without code changes, Lara’s work reduced maintenance overhead and accelerated dataset iteration, demonstrating a thoughtful application of configuration-driven software development within a scientific computing context.