Title
Embedding Containerized Workflows Inside Data Science Notebooks Enhances Reproducibility
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.
Disciplinary Repository
bioRxiv
DOI
10.1101/309567
Publisher Policy
open access
Open Access Status
OA Disciplinary Repository
Recommended Citation
Hu, Jiaming; Hung, Ling-Hong; and Yeung, Ka Yee, "Embedding Containerized Workflows Inside Data Science Notebooks Enhances Reproducibility" (2018). School of Engineering and Technology Publications. 271.
https://digitalcommons.tacoma.uw.edu/tech_pub/271
