maintainability 0.4.2

Codebase Maintainability Analyzer

Maintainability 🧠🔍

🌟 Introduction

Welcome to a new era of AI code analysis. Unlike traditional rule-based systems, this Python-based tool uses Language Models for a nuanced understanding of your codebase. Improve maintainability, readability, and overall code health without the rigid constraints of traditional systems.

🚀 Table of Contents

• Introduction
• Features
• Backend Overview
• Frontend Overview
• Contributing
• Team
• License

🌈 Features

• Adaptive Code Analysis: Leverage OpenAI's language models for a comprehensive review.
• User Authentication: Secure role-based access.
• Metrics Storage: All analysis results are securely stored in Supabase.
• API Key Management: Generate and manage API keys for your team.
• Real-time Analytics: A React-based front-end for all your metrics.

📚 Backend Overview

Intent and High-Level Workflow

The pulse of this tool is its Python-based backend. Not only does it analyze your code, but it also takes care of user authentication, metrics storage, and much more. Here's a sneak peek into what happens under the hood:

1. User Authentication: As you log in, your credentials are securely verified.
2. Code Repository Analysis: Next, we sift through your code repositories. Don't worry; files you wish to exclude are respected.
3. Code Maintainability Analysis: This is where the magic happens. OpenAI's language models gauge the quality of your code.
4. Metrics Storage: All the data is then sent for safe-keeping into a Supabase database.

File Groups Analysis

The backend is neatly divided into modules, each responsible for a different aspect of the system. From handling HTTP routes to logging, everything has its place.

Database Interactions (io_operations.py)

This part of the system is your liaison to the Supabase database. It takes care of metrics storage, user and API key management.

Logging (logger.py)

Every action is logged, ensuring complete transparency and aiding in debugging.

HTTP Routes (routes.py and routes_helper.py)

Whether you're interacting via the web front-end or making an API call, these routes serve as the gateway to the system's functionality.

CLI (file_operations.py and main.py)

Batch processing your repositories or integrating into your CI/CD pipeline? The CLI has got you covered.

🎨 Frontend Overview

Backend Communication

The React-based front-end is your window to the tool's analytical capabilities. Using Axios, it communicates with the backend for everything from user authentication to metrics retrieval.

Routing and State Management

We use React Router for client-side routing and manage global state through AppContext.js.

Styling

The UI is crafted with inline React styling complemented by Material UI components, making it sleek and user-friendly.

Deployment

The application is ready for deployment with configurations specified in vercel.json.

🤝 Team

• Jamie Voynow
• Possibly You?

👩‍🚀 Contributing

We welcome contributions from everyone! Reach out to me on twitter @jamievoynow

📜 License

This project is licensed under the MIT License. See LICENSE for more details.