Metadata-Version: 2.4
Name: rxnopt
Version: 0.0.1
Summary: A multi-objective reaction optimization framework based on Bayesian optimization
Author-email: Zhenzhi Tan <zhenzhitan8@gmail.com>
Maintainer-email: Zhenzhi Tan <tanzhenzhi8@gmail.com>
License: MIT License
        
        Copyright (c) 2025 ReactionOpt
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
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Project-URL: Bug Tracker, https://github.com/yourusername/reactionopt/issues
Project-URL: Documentation, https://reactionopt.readthedocs.io
Project-URL: Homepage, https://github.com/yourusername/reactionopt
Project-URL: Repository, https://github.com/yourusername/reactionopt
Keywords: chemistry,reaction optimization,bayesian optimization,machine learning,catalysis
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering :: Chemistry
Classifier: Topic :: Scientific/Engineering :: Artificial Intelligence
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License-File: LICENSE
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Requires-Dist: botorch>=0.15.0
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Dynamic: license-file

# ReactionOpt

[![Python 3.8+](https://img.shields.io/badge/python-3.8+-blue.svg)](https://www.python.org/downloads/release/python-380/)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![PyPI version](https://badge.fury.io/py/reactionopt.svg)](https://badge.fury.io/py/reactionopt)

A multi-objective reaction optimization framework based on Bayesian Optimization using Botorch & Ax.

## 🎯 Overview

ReactionOpt is a Python package designed for optimizing chemical reactions using advanced machine learning techniques. It leverages Bayesian Optimization to efficiently explore reaction spaces and optimize multiple objectives simultaneously (e.g., yield and enantioselectivity).

### Key Features

- **Multi-objective optimization** for reaction conditions (yield & ee optimization)
- **Bayesian Optimization** powered by [Botorch](https://github.com/pytorch/botorch) & [Ax](https://github.com/facebook/Ax)
- **GPU acceleration** for large-scale optimization
- **Flexible descriptor handling** for various reaction parameters
- **Automated visualization** of optimization results
- **High-throughput experimentation** support

## 🚀 Installation

### From PyPI (Recommended)

```bash
pip install rxnopt
```

### Development Installation

```bash
git clone https://github.com/yourusername/reactionopt.git
cd reactionopt
pip install -e .
```

### With Development Dependencies

```bash
pip install -e ".[dev]"
```

## 📋 Requirements

- Python 3.11+
- PyTorch >= 1.9.0
- Botorch >= 0.6.0
- RDKit >= 2021.9.1
- NumPy, Pandas, Scikit-learn
- Matplotlib, Seaborn (for visualization)
