https://github.com/r-devel/r-dev-env

A containerised development environment for editing and compiling the R source code.
https://github.com/r-devel/r-dev-env

Last synced: 4 months ago
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A containerised development environment for editing and compiling the R source code.

• Host: GitHub
• URL: https://github.com/r-devel/r-dev-env
• Owner: r-devel
• License: mit
• Created: 2023-05-31T13:33:17.000Z (over 2 years ago)
• Default Branch: main
• Last Pushed: 2025-06-19T09:15:45.000Z (5 months ago)
• Last Synced: 2025-07-13T10:47:21.918Z (4 months ago)
• Language: Shell
• Homepage: https://contributor.r-project.org/r-dev-env/
• Size: 8.64 MB
• Stars: 38
• Watchers: 8
• Forks: 15
• Open Issues: 20
• Metadata Files:
  • Readme: .github/README.md
  • Changelog: NEWS.md
  • Contributing: CONTRIBUTING.md
  • License: LICENSE
  • Code of conduct: CODE_OF_CONDUCT.md
  • Citation: CITATION.cff

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• jimsghstars - r-devel/r-dev-env - A containerised development environment for editing and compiling the R source code. (Shell)

README

          
# R Dev Container

![Release](https://img.shields.io/github/v/release/r-devel/r-dev-env)

The aim of the R Dev Container is to provide a standard environment for the

exploration and development of the R source code. A prototype was developed

under Google Summer of Code 2023 and development is continuing under Google

Summer of Code 2024.

## Getting started

### Run in a web browser with GitHub Codespace

Click on the button below followed by "Create Codespace" to create and enter

your own web based containerised develoment environment.

[![Open in GitHub

Codespaces](https://github.com/codespaces/badge.svg)](https://github.com/codespaces/new?hide_repo_select=true&ref=main&repo=647768262&machine=premiumLinux&devcontainer_path=.devcontainer%2Fdevcontainer.json&location=WestUs2)

The [Starting Codespace

section](https://contributor.r-project.org/r-dev-env/container_setup/github_codespace/creating_codespace/)

of the R Dev Container Docs will walk you through the process. Then you can work

through the tutorials in the docs to lean how to use the codespace for R

development.

More details about GitHub codespaces can be found in the [GitHub Codespaces

Docs](https://docs.github.com/en/codespaces/overview). GitHub currently offers

up to 60 hours for free on dual core codespaces.

[![Open in Gitpod](https://img.shields.io/badge/Gitpod-Open%20in%20Gitpod-blue?logo=gitpod&style=for-the-badge)](https://gitpod.io/github.com/r-devel/r-dev-env/tree/main)

The [Starting Gitpod

section](https://contributor.r-project.org/r-dev-env/container_setup/gitpod_workspace/workspacestart/)

of the R Dev Container Docs will walk you through the process. Then you can

work through the tutorials in the docs to lean how to use the codespace for R

development.

More details about Gitpod Workspaces can be found in the

[Gitpod Workspace Docs](https://www.gitpod.io/docs/introduction). Gitpod

currently offers Up to 896 cores, 12,000 GB RAM & GPUs in free tier.

### Run on your local computer

The R Dev Container can also be run locally on your computer.  Running the

environment requires you to have Docker, VSCode, and the VSCode Dev Containers

extension installed.  Upon opening a copy of the [r-dev-env

repository](https://github.com/r-devel/r-dev-env) in VSCode you will be prompted

to start the dev container.

The [Local setup

section](https://contributor.r-project.org/r-dev-env/container_setup/local_setup/localsetup/)

of the R Dev Container Docs will walk you through the process.  Then you can

work through the following the tutorials in the docs to learn how to use the

codespace for R development.

More information about Dev Containers can be found in the [Microsoft

Documentation](https://code.visualstudio.com/docs/devcontainers/containers).

## Project Background

The standard development process used by members of the R Core Team involves an

iterative process of making changes to the source code, re-building R and

exploring/testing the changes made.  This process presents a big hurdle for new

contributors to R, as setting up their system to build R can be non-trivial,

requiring a lot of trouble-shooting, especially on Windows and macOS.  On Linux

and macOS, it is not straight-forward to work with different versions of R

side-by-side and care needs to be taken not to corrupt or over-write the user's

existing version of R/R packages.

For these reasons, we propose to create containerized development environments

for R.  Our focus will be on creating a complete environment, including an IDE,

that will provide a familiar space for R developers to work on contributions to

base R.

## Contributors

GSoC contributor: Atharva Shirdhankar

Mentors: Heather Turner, James Tripp, Iain Emsley