Python Code Smells Tool

The tool analyzes Python code to surface maintainability risks and actionable smells. It uses AST-based measurements to quantify complexity, nesting, and size, and it flags anti-patterns such as long methods, large classes, and magic numbers. Results are organized per file with severity levels and concrete refactoring suggestions, enabling developers to prioritize changes. The analysis can run on single files or entire repositories, providing a project-wide view of technical debt. Conceptually, the tool applies fixed heuristics and configurable thresholds to determine when a pattern is considered a smell, then aggregates findings into a structured report for review and CI integration. Beneficiaries include individual developers seeking cleaner code, teams enforcing coding standards, and managers tracking quality trends. Unique value lies in its combination of precise AST-based metrics, practical remediation guidance, and seamless CI-friendly output that supports large Python codebases. Core features include configurable complexity thresholds, detection of unused imports, code duplication checks, and recognition of hard-coded strings. Use cases span pre-commit checks, pull-request reviews, and ongoing quality assessments. The tool emphasizes actionable outputs over generic warnings, focusing on concrete refactor opportunities, naming improvements, and modularization opportunities. It complements linters by adding structural quality insights rather than style-only feedback, helping teams reduce technical debt over time.