Worked on the mlflow/mlflow repository to enhance codebase health by implementing targeted code linting and refactoring. Focused on Python development, the primary contribution involved systematically removing unused global variable declarations from multiple modules. This cleanup aligned the code with Python best practices, reducing unnecessary references and improving overall readability and maintainability. The approach emphasized careful analysis of variable usage to ensure that only obsolete globals were eliminated, thereby minimizing potential side effects. By concentrating on code linting and refactoring, the work contributed to a cleaner, more maintainable codebase, supporting ongoing development and making future enhancements easier for the team.