The package offers elaborately designed reusable components and interfaces that allow researchers to implement and compare new reinforcement learning algorithms. It supports experimentation through easy-to-run benchmark environments and evaluation tools. The library covers traditional tabular methods through modern deep reinforcement learning approaches, facilitating reproducibility in RL research.