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Article
Embedding Containerized Workflows Inside Data Science Notebooks Enhances Reproducibility
bioRxiv
  • Jiaming Hu
  • Ling-Hong Hung
  • Ka Yee Yeung, University of Washington Tacoma
Publication Date
5-2-2018
Document Type
Article
Abstract

Data science notebooks, such as Jupyter, combine text documentation with dynamically editable and executable code and have become popular for sharing computational methods. We present nbdocker, an extension that integrates Docker software containers into Jupyter notebooks. nbdocker transforms notebooks into autonomous, self-contained, executable and reproducible modules that can document and disseminate complicated data science workflows containing code written in different languages and executables requiring different software environments.

DOI
10.1101/309567
Version
open access
Citation Information
Jiaming Hu, Ling-Hong Hung and Ka Yee Yeung. "Embedding Containerized Workflows Inside Data Science Notebooks Enhances Reproducibility" bioRxiv (2018)
Available at: http://works.bepress.com/ky-yeung/7/