Data

Tools

Indexes

Applications

Experiments

Papers

An open API service providing mapping between scientific papers and software projects that are mentioned in them.

Papers: 10.1371/journal.pcbi.1008316

https://doi.org/10.1371/journal.pcbi.1008316

Ten simple rules for writing Dockerfiles for reproducible data science

Cited by: 36
Author(s): Daniel Nüst, Vanessa Sochat, Ben Marwick, Stephen J. Eglen, T. Head, Tony Hirst, Benjamin D. Evans
Published: over 4 years ago

Software Mentions 11

cran: git2r
Provides Access to Git Repositories
Papers that mentioned: 4
Very Likely Science (95)
cran: RColorBrewer
ColorBrewer Palettes
Papers that mentioned: 490
Very Likely Science (83)
cran: rJava
Low-Level R to Java Interface
Papers that mentioned: 28
Very Likely Science (75)
cran: RNetCDF
Interface to 'NetCDF' Datasets
Papers that mentioned: 4
Very Likely Science (75)
pypi: docker
A Python library for the Docker Engine API.
Papers that mentioned: 39
Very Likely Science (100)
pypi: docker-compose
Multi-container orchestration for Docker
Papers that mentioned: 10
Very Likely Science (85)
pypi: jupyter
Jupyter metapackage. Install all the Jupyter components in one go.
Papers that mentioned: 39
Very Likely Science (90)
pypi: jupyter-repo2docker
Repo2docker: Turn code repositories into Jupyter enabled Docker Images
Papers that mentioned: 1
Very Likely Science (100)
pypi: podman
Bindings for Podman RESTful API
Papers that mentioned: 2
Very Likely Science (65)
pypi: uszipcode
USA zipcode programmable database, includes 2020 census data and geometry information.
Papers that mentioned: 2
Very Likely Science (65)
pypi: yml
A fast, safe, pure Python YAML and JSON parser
Papers that mentioned: 12
Very Likely Science (65)