neatrl 0.1.5

A Python library for reinforcement learning algorithms

🎯 NeatRL

A clean, modern Python library for reinforcement learning algorithms

NeatRL provides high-quality implementations of popular RL algorithms with a focus on simplicity, performance, and ease of use. Built with PyTorch and designed for both research and production use.

✨ Features

• 🚀 Fast & Efficient: Optimized implementations using PyTorch
• 🎯 Production Ready: Clean APIs and comprehensive error handling
• 📊 Experiment Tracking: Built-in support for Weights & Biases logging
• 🎮 Gymnasium Compatible: Works with all Gymnasium environments
• 🔧 Easy to Extend: Modular design for adding new algorithms
• 📈 State-of-the-Art: Implements modern RL techniques and best practices

🏗️ Supported Algorithms

Current Implementations

• DQN (Deep Q-Network) - Classic value-based RL algorithm
• More algorithms coming soon...

📦 Installation

python -m venv neatrl-env
source neatrl-env/bin/activate  # On Windows use `neatrl-env\Scripts

pip install neatrl

🚀 Quick Start

Train a DQN agent on CartPole in 3 lines:

from neatrl import train_dqn

model = train_dqn(
    env_id="CartPole-v1",
    total_timesteps=10000,
    seed=42
)

📚 Documentation

📖 Complete Documentation

The docs include:

• Detailed usage examples
• Hyperparameter tuning guides
• Environment compatibility
• Experiment tracking setup
• Troubleshooting tips

🤝 Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Development Setup

git clone https://github.com/YuvrajSingh-mist/NeatRL.git
cd NeatRL
pip install -e .[dev]

📋 Changelog

[0.1.4] - 2025-12-13

• Added: Custom agent support for DQN training
• Added: Network architecture display using torchinfo
• Improved: Error handling for custom agent constructors
• Changed: Agent parameter now accepts nn.Module subclasses

[0.1.3] - 2025-12-01

• Initial release with DQN implementation
• Weights & Biases integration
• Video recording capabilities
• Comprehensive documentation

For the complete changelog, see CHANGELOG.md.

📄 License

This project is licensed under the MIT License - see the LICENSE file for details.

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Made with ❤️ for the RL community