ml-cleanup

What problem does it solve?

ML project codebases accumulate dead code and duplication that waste time and hinder reproducibility.

Core Features & Use Cases

• Identify dead code, unused imports, and duplicates across experiments.
• Extract shared logic to common modules to reduce maintenance costs.
• Generate a structured cleanup plan with optional automated patches to preserve functionality.

Quick Start

Run ml-cleanup on an experiment directory to identify dead code and generate a cleanup plan.