This API design abstracts away the details of which program is used to evaluate the constrained geometry optimization allowing many different quantum chemistry, semi-empirical, force field, or ML potential programs to be used to generate the necessary values. This strategy is robust to new methodology and program development and avoids being "locked into" a particular software package. Several examples of this are using Python-based geometry optimizers that are agnostic to the backend program to evaluate these constrained geometry optimizations such as geomeTRIC, PyBernie, and PyOptKing. Also, Pythonbased suites of tools that attempt to abstract backends exist, such as ASE and QCEngine, allowing for many additional programs to be used with a simplified interface.