codeclinic 0.1.1

X-ray your Python project: import graph + stub maturity metrics + Graphviz viz + CLI

CodeClinic (codeclinic)

Diagnose your Python project: import dependencies → maturity metrics (stub ratio) → Graphviz visualization.

Install

pip install codeclinic
# or, from source (dev):
pip install -e .

Note: Rendering SVG/PNG requires the Graphviz system tool (dot) in your PATH. macOS: brew install graphviz; Ubuntu: sudo apt-get install graphviz.

Quick start

codeclinic --path ./src --out results

This prints a summary + adjacency list and writes:

• results/analysis.json (project analysis data)
• results/stub_report.json (detailed stub function report)
• results/dependency_graph.dot (DOT source)
• results/dependency_graph.svg (rendered visualization)

Marking stubs

from codeclinic import stub

@stub
def todo_api():
    pass

@stub will (1) mark the function for static counting and (2) emit a warnings.warn when it’s actually called.

Config

You can keep settings in pyproject.toml under [tool.codeclinic] or in a codeclinic.toml file:

[tool.codeclinic]
paths = ["src"]
include = ["**/*.py"]
exclude = ["**/tests/**", "**/.venv/**"]
aggregate = "package"     # "module" | "package"
format = "svg"            # svg | png | pdf | dot
output = "build/cc_graph"
count_private = false

CLI flags override config.

Output Formats

All-in-One (Default)

codeclinic --path ./src --out results

Generates complete analysis with all output files in a single directory.

JSON Data Only

codeclinic --path ./src --out results --format json

Generates only JSON files (analysis + stub report) without visualization.

Specific Visualization Formats

codeclinic --path ./src --out results --format svg    # SVG visualization
codeclinic --path ./src --out results --format png    # PNG visualization  
codeclinic --path ./src --out results --format pdf    # PDF visualization

Stub Function Reports

The stub_report.json file contains detailed information about all @stub decorated functions:

{
  "metadata": {
    "total_stub_functions": 5,
    "modules_with_stubs": 3,
    "function_stubs": 3,
    "method_stubs": 2
  },
  "stub_functions": [
    {
      "module_name": "myproject.utils",
      "file_path": "/path/to/utils.py", 
      "function_name": "incomplete_feature",
      "full_name": "incomplete_feature",
      "docstring": "This feature is not yet implemented.",
      "is_method": false,
      "class_name": null,
      "graph_depth": 2
    }
  ]
}

Each stub function includes:

• File location and module information
• Function/method name with full qualified name (e.g., ClassName.method_name)
• Docstring extracted from the function
• Graph depth - dependency level for implementation prioritization
• Method classification - whether it's a standalone function or class method

CLI

codeclinic --path PATH [--out OUTPUT_DIR] [--format svg|png|pdf|dot|json] [--aggregate module|package]

How it works

• Parses your code with ast (no import-time side effects).
• Builds an internal import graph (absolute & relative imports resolved).
• Counts public functions/methods and @stub-decorated ones to compute a stub ratio per node.
• Renders a Graphviz graph with node colors by ratio (green→yellow→red).

Roadmap

• Smell detectors (circulars, forbidden deps, god packages, layer rules).
• HTML/PDF report with dashboards.
• Plugin entry points: codeclinic.detector.

License

MIT