<div align="center">
  <img src="res/logo.png" alt="pymocd logo" width="40%">  
  
  **Python Multi-Objective Evolutionary Algorithms for Community Detection**  
  
  Efficient and high-performance community detection in large-scale graphs, built with Rust for speed and scalability.
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## Overview  
**pymocd** is a Rust-powered Python library designed for efficient multi-objective evolutionary algorithms in community detection. It enhances performance over traditional methods, making it ideal for large-scale graph analysis. This project continues from [re-mocd](https://github.com/0l1ve1r4/re-mocd).  

## Features  
- High-performance Rust backend for computational efficiency  
- Multi-objective optimization for better community structures  
- Scalable to large graphs  
- Easy-to-use Python API  

## Installation and Usage

Visit the [documentation](#) (TODO) for detailed instructions and examples.

## Contributing  

Contributions are welcome! If you have ideas for improvements, feel free to submit issues or pull, this project is licensed under the **GPL-3.0 or later**.  

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  <a href="https://github.com/0l1ve1r4">
    <img src="https://avatars.githubusercontent.com/u/82629748?v=4" width="50" height="50" style="border-radius: 50%;">
  </a>
  <a href="https://github.com/ol1veir4s">
    <img src="https://avatars.githubusercontent.com/u/202351572?v=4" width="50" height="50" style="border-radius: 50%;">
  </a>
  <a href="https://github.com/matt-cornell">
    <img src="https://avatars.githubusercontent.com/u/107312119?v=4" width="50" height="50" style="border-radius: 50%;">
  </a>
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