Dirk Eddelbuettel

Iñaki Ucar, Dirk Eddelbuettel

Pre-compiled binary packages provide a convenient way of efficiently distributing software that has been adopted by most Linux package management systems. However, the heterogeneity of the Linux ecosystem, combined with the growing number of R extensions available, poses a scalability problem. As a result, efforts to bring binary R packages to Linux have been scattered, and lack a proper mechanism to fully integrate them with R's package manager. This work reviews past and present of binary distribution for Linux, and presents a path forward by showcasing the `cran2copr' project, an RPM-based proof-of-concept implementation of an automated scalable binary distribution system with the capability of building, maintaining and distributing thousands of packages, while providing a portable and extensible bridge to the system package manager.

Daniel Nüst, Dirk Eddelbuettel, Dom Bennett et al.

The Rocker Project provides widely used Docker images for R across different application scenarios. This article surveys downstream projects that build upon the Rocker Project images and presents the current state of R packages for managing Docker images and controlling containers. These use cases cover diverse topics such as package development, reproducible research, collaborative work, cloud-based data processing, and production deployment of services. The variety of applications demonstrates the power of the Rocker Project specifically and containerisation in general. Across the diverse ways to use containers, we identified common themes: reproducible environments, scalability and efficiency, and portability across clouds. We conclude that the current growth and diversification of use cases is likely to continue its positive impact, but see the need for consolidating the Rockerverse ecosystem of packages, developing common practices for applications, and exploring alternative containerisation software.

Carl Boettiger, Dirk Eddelbuettel

We describe the Rocker project, which provides a widely-used suite of Docker images with customized R environments for particular tasks. We discuss how this suite is organized, and how these tools can increase portability, scaling, reproducibility, and convenience of R users and developers.