Gym is a foundational toolkit for reinforcement learning research and development. It standardizes the interface between learning algorithms and simulated environments, making it easy to implement, test, and benchmark RL agents. The library includes a wide variety of pre-built environments ranging from classic control tasks to Atari games, and its API has become the de facto standard in the RL community. Development has since moved to the community-maintained Gymnasium fork.