Show HN: Python Code Harmonizer – Semantic analysis for clean maintainable code (github.com)

Python Code Harmonizer is an open-source “semantic code debugger” that analyzes program meaning—rather than just syntax—to find logical mismatches between what a function says it does (Intent) and what its body actually does (Execution). Built around the authors’ DIVE‑V2 full‑stack philosophy and the ICE Framework (Intent, Context, Execution), it parses Python’s AST with ast_semantic_parser.py to extract meaning-keywords, computes a semantic‑distance score between Intent and Execution (disharmony threshold ≈ 0.5), and flags functions whose names contradict their behavior (e.g., get_user_by_id calling db.delete_user → “DISHARMONY”). The tool is pip-installable, runs from the CLI (harmonizer examples/test_code.py), and includes a test suite and pre-commit hooks for integration into dev workflows. This approach is significant because it targets a class of bugs linters and type checkers miss: naming/intent drift, wrong API calls, and regressions introduced during refactors. For AI/ML teams, it can speed code review, catch semantic regressions that break pipelines, and improve maintainability. Caveats: effectiveness depends on robust intent extraction and heuristics—function names, docstrings, and context must be informative—so expect false positives/negatives and a need to tune the parser and scoring for your codebase. The project is on GitHub and designed for contribution and extension.