While the calls for reproduction studies in Computational Literary Studies (CLS) have become louder, practical aspects, especially the interplay of the components involved in the research process (code, data, environments, infrastructures, etc.) proves to be a hurdle for reproducing research. We present a way to fully reproducible research using a Docker-based approach: We exemplarily implemented it for a network-analytic study on a corpus of about 3,000 theater plays derived from the DraCor project. We demonstrate that the use of highly portable, self-contained digital artifacts (Docker images) containing runnable research environments not only allow for a full reproduction of the study, but also offer ways to implement different scenarios of repeating research (e.g. same code, different data).