**mabby** is a library for simulating multi-armed bandits, with the following features:
* running simulations with different strategies on a configurable set of arms
* tracking for regret, cumulative regret, optimality, reward, and cumulative reward metrics
* visualizing the tracked metrics, allowing comparison between different strategies
**mabby** also currently supports and includes:
* implementations for epsilon-greedy, UCB1, and beta Thompson sampling strategies
* implementations for arms with Bernoulli and Gaussian reward distributions
* custom strategies and arms through sub-classing the abstract `Strategy` and `Arm` classes