Methodological statisticians spend an appreciable amount of their time writing code for simulation studies. Every paper introducing a new method has a simulation section in which the new method is compared across several metrics to preexisting methods under various scenarios. Given the formulaic nature of the simulation studies in most statistics papers, there is a lot of code that can be reused. We have developed an R package, called the "simulator", that streamlines the process of performing simulations by creating a common infrastructure that can be easily used and reused across projects. The simulator allows the statistician to focus exclusively on those aspects of the simulation that are specific to the particular paper being written. Code for simulations written with the simulator is succinct, highly readable, and easily shared with others. The modular nature of simulations written with the simulator promotes code reusability, which saves time and facilitates reproducibility. Other benefits of using the simulator include the ability to "step in" to a simulation and change one aspect without having to rerun the entire simulation from scratch, the straightforward integration of parallel computing into simulations, and the ability to rapidly generate plots and tables with minimal effort.