  In reinforcement learning, wrappers are universally used to transform the
information that passes between a model and an environment. Despite their
ubiquity, no library exists with reasonable implementations of all popular
preprocessing methods. This leads to unnecessary bugs, code inefficiencies, and
wasted developer time. Accordingly we introduce SuperSuit, a Python library
that includes all popular wrappers, and wrappers that can easily apply lambda
functions to the observations/actions/reward. It's compatible with the standard
Gym environment specification, as well as the PettingZoo specification for
multi-agent environments. The library is available at
https://github.com/PettingZoo-Team/SuperSuit,and can be installed via pip.
