ReciPies: A Lightweight Data Transformation Pipeline for Reproducible ML

Jupyter Notebook Python Submitted 24 July 2025 • Published 05 January 2026
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Editor: @crvernon (all papers)
Reviewers: @simonprovost (all reviews), @panagiotisanagnostou (all reviews)

Authors

Robin P. van de Water (0000-0002-2895-4872), Hendrik Schmidt (0000-0001-7699-3983), Patrick Rockenschaub (0000-0002-6499-7933)

Citation

van de Water et al., (2026). ReciPies: A Lightweight Data Transformation Pipeline for Reproducible ML. Journal of Open Source Software, 11(117), 9261, https://doi.org/10.21105/joss.09261

@article{van de Water2026, doi = {10.21105/joss.09261}, url = {https://doi.org/10.21105/joss.09261}, year = {2026}, publisher = {The Open Journal}, volume = {11}, number = {117}, pages = {9261}, author = {van de Water, Robin P. and Schmidt, Hendrik and Rockenschaub, Patrick}, title = {ReciPies: A Lightweight Data Transformation Pipeline for Reproducible ML}, journal = {Journal of Open Source Software} }
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reproducible-research data-preprocessing feature-engineering configuration-as-code preprocessing-pipelines pandas polars provenance time-series benchmarking ml-ops python

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Journal of Open Source Software is an affiliate of the Open Source Initiative.

Journal of Open Source Software is part of Open Journals, which is a NumFOCUS-sponsored project.

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ISSN 2475-9066