ReciPies: A Lightweight Data Transformation Pipeline for Reproducible ML

ReciPies: A Lightweight Data Transformation Pipeline for Reproducible ML - Published in JOSS (2026)

https://github.com/rvandewater/recipies

Science Score: 87.0%

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    Published in Journal of Open Source Software
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JOSS Publication

ReciPies: A Lightweight Data Transformation Pipeline for Reproducible ML
Published
January 05, 2026
Volume 11, Issue 117, Page 9261
Authors
Robin P. van de Water ORCID
Hasso Plattner Institute, University of Potsdam, Potsdam, Germany, Hasso Plattner Institute for Digital Health at Mount Sinai, Icahn School of Medicine at Mount Sinai, New York City, NY, USA
Hendrik Schmidt ORCID
Hasso Plattner Institute, University of Potsdam, Potsdam, Germany
Patrick Rockenschaub ORCID
Innsbruck Medical University, Innsbruck, Austria
Editor
Chris Vernon ORCID
Tags
reproducible-research data-preprocessing feature-engineering configuration-as-code preprocessing-pipelines pandas polars provenance time-series benchmarking ml-ops python