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Show HN: Pyscn – Python code quality analyzer for vibe coders

(github.com)
136 points d-yoda | 1 comments | 05 Oct 25 13:22 UTC | HN request time: 0.279s | source

Hi HN! I built pyscn for Python developers in the vibe coding era. If you're using Cursor, Claude, or ChatGPT to ship Python code fast, you know the feeling: features work, tests pass, but the codebase feels... messy.

Common vibe coding artifacts:

• Code duplication (from copy-pasted snippets)

• Dead code from quick iterations

• Over-engineered solutions for simple problems

• Inconsistent patterns across modules

pyscn performs structural analysis:

• APTED tree edit distance + LSH

• Control-Flow Graph (CFG) analysis

• Coupling Between Objects (CBO)

• Cyclomatic Complexity

Try it without installation:

  uvx pyscn analyze .          # Using uv (fastest)
  pipx run pyscn analyze .     # Using pipx
  (Or install: pip install pyscn)
Built with Go + tree-sitter. Happy to dive into the implementation details!
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aDyslecticCrow ◴[05 Oct 25 15:37 UTC] No.45482348[source]▶
Current AI is most proficient in java-script and python because of the vast training data. But in the long-run, i feel like languages with good static analysis, static type checks, clear language rules, memory leak detection, fuzzing, test oriented code, and any number of other similar tooling is gonna be the true game-changer. Directed learning using this tooling could improve the models beyond their training set, or simply allow humans to constrain AI output within certain bounds.
replies(2): >>45482424 #>>45482497 #
1. d-yoda ◴[05 Oct 25 15:52 UTC] No.45482497[source]▶
Great point! Golang is indeed one of those languages with strong "vibe coding resistance" - it's personally one of my favorites for that reason. On the flip side, I think there's a future where tools like pyscn work alongside AI to make languages with large communities like Python even more dominant.