Mastering AI-Powered Python Code Analysis with Griffe

Harnessing Griffe for Advanced Code Introspection

This tutorial introduces Griffe as the centerpiece of an AI-powered code analysis tool. Griffe's introspection abilities allow real-time loading and traversal of Python packages, enabling in-depth analysis of modules, classes, and functions. By integrating Griffe with libraries like NetworkX for dependency mapping and Matplotlib for visualization, raw Python codebases are transformed into meaningful insights.

Building the AI Code Analyzer

The core of the approach is encapsulated in the AICodeAnalyzer class, which provides methods to analyze entire packages or simpler modules. It recursively inspects package components, collects metrics such as total modules, classes, functions, and captures API surface details including docstrings, inheritance trees, and method counts.

The class calculates a complexity score combining counts of classes, functions, modules, inheritance depth, and documentation coverage. It also identifies potential risks such as large API surfaces, poor documentation, and deep inheritance hierarchies.

Comparing and Visualizing Packages

The analyzer supports comparing two packages side-by-side, evaluating complexity, API size, and documentation coverage to recommend the better-balanced package.

Visualization methods create dashboards displaying component distribution, API visibility, documentation coverage, and complexity scores using Matplotlib charts.

Demonstration and Usage

The main() function demonstrates analyzing core Python modules (datetime, os, sys), gracefully falling back from deep Griffe analysis to simpler introspection when needed. It prints detailed metrics and generates a visual dashboard for one successfully analyzed package. It also compares datetime and os packages, outputting a recommendation based on analysis.

This framework offers robust, insightful AI-driven code analysis by combining Griffe's deep inspection with custom metrics and visual tools. It facilitates architectural review and informed development decisions, and can be extended with further analysis capabilities.