SuperSuit is a Python library that provides a collection of lightweight, composable 'microwrappers' for preprocessing reinforcement learning environments. It supports both single-agent Gymnasium environments and multi-agent PettingZoo environments (AEC and Parallel APIs). The wrappers cover common transformations such as color reduction, frame stacking, resizing, dtype conversion, reward clipping, action scaling, and NaN handling. Additionally, it offers vectorization utilities to run multiple environment instances in parallel, including synchronous, asynchronous, and multiprocessing-based vector environments. The library is designed to be used as a preprocessing pipeline before feeding environments into RL algorithms. It is maintained primarily for compatibility with newer versions of PettingZoo and Gymnasium, with the stated intention of eventually merging relevant functionality into PettingZoo's own wrappers.