Python Package

Reducing Complexity

Techniques to measure and reduce cyclomatic and cognitive complexity in Python code.

Early Access: Until 2026-12-31

Back Overview Requirements

mgpy treats complexity as a measurable refactoring target: hotspots should be visible, comparable and trackable across baselines.

Key points

CLI: On Windows the examples use the recommended py -3.12 -m <module> ... form (for example py -3.12 -m manifestguard ...). On Linux/macOS this usually maps to python3.12 -m ....
The built-in AST analyzer is the default engine and keeps trend data stable over time.
Early returns, smaller helper functions and clearer responsibilities reduce violations faster than formatting-only cleanups.
Always save a baseline checkpoint before larger structural changes.

Recommended mgpy workflow

Capture the current hotspots with a fixed threshold first.
Break the worst functions into smaller, testable steps instead of moving the whole module tree at once.
After each refactor, compare the result against the stored baseline.

Quick start

py -3.12 -m manifestguard complexity --threshold 12
py -3.12 -m manifestguard baseline --save-label pre-refactor
py -3.12 -m manifestguard baseline --compare pre-refactor

Requirements



Installation interpreter	Python 3.12 + pip	Recommended default path for installation and CLI calls.
Project target versions	Python 3.8 to 3.12	These are the project/runtime targets mgpy can analyze.
mgpy runtime	Validated on Python 3.10 to 3.13	The tool runtime itself is covered for this range.
CLI invocation	Windows: py -3.12 -m manifestguard	Linux/macOS usually maps to python3.12 -m manifestguard.
Runtime packages	tomlkit, click, pydantic, packaging, watchdog, PyNaCl, rfc8785	tomli is only added for Python below 3.11.
Offline / wheel install	Optional via pip --no-index or wheel	Useful for air-gapped or approved bundle distribution paths.