Skip to main content

An intelligent Python code quality analyzer with architectural guidance

Project description

pyscn - Python Code Quality Analyzer

Article PyPI Go License CI

pyscn is a code quality analyzer for Python vibe coders.

Building with Cursor, Claude, or ChatGPT? pyscn performs structural analysis to keep your codebase maintainable.

Working with JavaScript/TypeScript? Check out jscan

Quick Start

# Run analysis without installation
uvx pyscn analyze .
# or
pipx run pyscn analyze .

Demo

https://github.com/user-attachments/assets/07f48070-c0dd-437b-9621-cb3963f863ff

Features

  • 🔍 CFG-based dead code detection – Find unreachable code after exhaustive if-elif-else chains
  • 📋 Clone detection with APTED + LSH – Identify refactoring opportunities with tree edit distance
  • 🔗 Coupling metrics (CBO) – Track architecture quality and module dependencies
  • 📊 Cyclomatic complexity analysis – Spot functions that need breaking down

100,000+ lines/sec • Built with Go + tree-sitter

MCP Integration

Run pyscn analyses straight from AI coding assistants via the Model Context Protocol (MCP). The bundled pyscn-mcp server exposes the same tools used in the CLI to Claude Code, Cursor, ChatGPT, and other MCP clients.

MCP Use Cases

You can interact with pyscn with your AI coding tools:

  1. "Analyze the code quality of the app/ directory"

  2. "Find duplicate code and help me refactor it"

  3. "Show me complex code and help me simplify it"

Claude Code Setup

claude mcp add pyscn-mcp uvx -- pyscn-mcp

Cursor / Claude Desktop Setup

Add to your MCP settings (~/.config/claude-desktop/config.json or Cursor settings):

{
  "mcpServers": {
    "pyscn-mcp": {
      "command": "uvx",
      "args": ["pyscn-mcp"],
      "env": {
        "PYSCN_CONFIG": "/path/to/.pyscn.toml"
      }
    }
  }
}

The instructions like "Analyze the code quality" trigger pyscn via MCP.

Dive deeper in mcp/README.md for setup walkthroughs and docs/MCP_INTEGRATION.md for architecture details.

Installation

# Install with pipx (recommended)
pipx install pyscn

# Or with uv
uv tool install pyscn
Alternative installation methods

Build from source

git clone https://github.com/ludo-technologies/pyscn.git
cd pyscn
make build

Go install

go install github.com/ludo-technologies/pyscn/cmd/pyscn@latest

Common Commands

pyscn analyze

Run comprehensive analysis with HTML report

pyscn analyze .                              # All analyses with HTML report
pyscn analyze --json .                       # Generate JSON report
pyscn analyze --select complexity .          # Only complexity analysis
pyscn analyze --select deps .                # Only dependency analysis
pyscn analyze --select complexity,deps,deadcode . # Multiple analyses

pyscn check

Fast CI-friendly quality gate

pyscn check .                         # Quick pass/fail check
pyscn check --max-complexity 15 .     # Custom thresholds
pyscn check --max-cycles 0 .          # Only allow 0 cycle dependency
pyscn check --select deps .           # Check only for circular dependencies
pyscn check --allow-circular-deps .   # Allow circular dependencies (warning only)

pyscn init

Create configuration file

pyscn init                         # Generate .pyscn.toml

💡 Run pyscn --help or pyscn <command> --help for complete options

Configuration

Create a .pyscn.toml file or add [tool.pyscn] to your pyproject.toml:

# .pyscn.toml
[complexity]
max_complexity = 15

[dead_code]
min_severity = "warning"

[output]
directory = "reports"

⚙️ Run pyscn init to generate a full configuration file with all available options

CI/CD Integration

# GitHub Actions
- uses: actions/checkout@v4
- run: pipx run pyscn check .    # Fail on quality issues

# Pre-commit hook
- repo: local
  hooks:
    - id: pyscn
      name: pyscn check
      entry: pipx run pyscn check .
      language: system
      pass_filenames: false
      types: [python]

Documentation

📚 Development GuideArchitectureTesting

Enterprise Support

For commercial support, custom integrations, or consulting services, contact us at contact@ludo-tech.org

License

MIT License — see LICENSE


Built with ❤️ using Go and tree-sitter

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

If you're not sure about the file name format, learn more about wheel file names.

pyscn-1.5.5-py3-none-win_amd64.whl (7.6 MB view details)

Uploaded Python 3Windows x86-64

pyscn-1.5.5-py3-none-manylinux_2_17_x86_64.whl (7.3 MB view details)

Uploaded Python 3manylinux: glibc 2.17+ x86-64

pyscn-1.5.5-py3-none-macosx_11_0_arm64.whl (6.8 MB view details)

Uploaded Python 3macOS 11.0+ ARM64

File details

Details for the file pyscn-1.5.5-py3-none-win_amd64.whl.

File metadata

  • Download URL: pyscn-1.5.5-py3-none-win_amd64.whl
  • Upload date:
  • Size: 7.6 MB
  • Tags: Python 3, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for pyscn-1.5.5-py3-none-win_amd64.whl
Algorithm Hash digest
SHA256 2363ad829b570f5a7bdf6ec24d099b01b81f623ec7c8a8bad4b26202b9fe145a
MD5 4b163a21808357b553f29343e2b346bd
BLAKE2b-256 6f560cab84a2ffb8cfb6acf4964601715f171f4903724df920946ae3412647c5

See more details on using hashes here.

File details

Details for the file pyscn-1.5.5-py3-none-manylinux_2_17_x86_64.whl.

File metadata

File hashes

Hashes for pyscn-1.5.5-py3-none-manylinux_2_17_x86_64.whl
Algorithm Hash digest
SHA256 6237efad1a260af142ebf38dd231280281a0d5d60a478a1bd7520d823628a032
MD5 156150b8941068618ef9665b91e21aca
BLAKE2b-256 1a1b0aad83c896d79d3243888e794f288857294ee8b3d79f42fadbfe1f445df2

See more details on using hashes here.

File details

Details for the file pyscn-1.5.5-py3-none-macosx_11_0_arm64.whl.

File metadata

  • Download URL: pyscn-1.5.5-py3-none-macosx_11_0_arm64.whl
  • Upload date:
  • Size: 6.8 MB
  • Tags: Python 3, macOS 11.0+ ARM64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.13.7

File hashes

Hashes for pyscn-1.5.5-py3-none-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 824d7451378374b72a19032d2c58ca1fc2bfcaac04b0f78baf31d4ebd106404a
MD5 98338364bc6322f67cc7b578978c2a09
BLAKE2b-256 9248c0aad893b76cec3049bc08fe0ea72a02cd9a0b4b131844a3c2648ab778a5

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page