Developed a configurable jet-count source for DY weight calculations in the columnflow/columnflow repository, enabling analysis teams to specify jet selection criteria without relying on hardcoded logic. This feature introduced a dedicated njet column, allowing users to define which jet collection to use for DY weights, thereby improving flexibility and reducing maintenance overhead. The implementation leveraged Python and applied data analysis and physics analysis skills to ensure accurate and adaptable calculations across different datasets. By shifting to a configuration-driven approach, the work enhanced maintainability and facilitated faster iteration for physics analyses requiring customizable jet multiplicity in their workflows.