@misc{15068, keywords = {jupyter, python, reproducibility, docker}, author = {Jessica Forde and Tim Head and Chris Holdgraf and Yuvi Panda and Gladys Nalvarte and M Pacer and Fernando Perez and Benjamin Ragan-Kelley and Erik Sundell}, title = {Reproducible Research Environments with Repo2Docker}, abstract = {Reproducibility challenges in machine learning often center on questions of software engineering practices. Researchers struggle to reproduce another scientist{\textquoteright}s work because they cannot translate a paper into code with similar results or run an author{\textquoteright}s code. repo2docker provides a simple tool for checking the minimum requirements to reproduce a paper by building a Docker image based on a repository path or URL. Its goal is to minimize the effort needed to convert a static repository into a working software environment. By inspecting a repository for standard configuration files used in contemporary software engineering and leveraging containerization methods, repo2docker deterministically reproduces the environment of the author so the researcher can reproduce the author{\textquoteright}s experiments.}, year = {2018}, journal = {ICML 2018 Reproducible Machine Learning}, month = {07/2018}, publisher = {ICML}, url = {https://openreview.net/forum?id=B1lYOwuoxm}, }