Robust optimization aims at pushing optimization techniques to practical applicability by including data uncertainty. Thus, it is crucial to collect algorithms and concepts for robust optimization, and to make them publicly available while being easy-to-use for the practitioner without working deeply into the theoretical background. With ROPI, a robust optimization programming interface for C++, we try to commit to this process. This paper gives an overview on current approaches to robust optimization, outlines the basic properties and functionalities of ROPI, and discusses the differences to other available libraries.