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r-docker

Docker image for running R code in OpenSAFELY, both locally and in production.

Installation requirements to build this image

  • docker
  • docker-compose
  • just

Building

just build

Under the hood, this builds ./Dockerfile using docker-compose and buildkit.

We currently build a lot of packages, so an initial build on a fresh checkout can take a long time (e.g. an hour). However, to alleviate this, the Dockerfile is carefully designed to use local buildkit cache, so subequent rebuilds should be very fast.

Adding new packages

⚠️ To do this you will need:

  • Enough bandwidth to comfortably push potentionally gigabytes worth of Docker layers.
  • Several hours worth of CPU time to re-compile all the packages (if this is the first time you've done this and don't have them cached locally).
  • Push access to ghcr.io.

If you don't have all these things then please don't start.

Confirm that the package is suitable to add

Before adding a package, check with an OpenSAFELY team member with R experience to approve the package.

Install the package within Docker

To add a package, it must be available on CRAN. We cannot currently install things from Github or other locations.

just add-package PACKAGE

This will attempt to install and build the package and its dependencies, and update the renv.lock. It will then rebuild the R image with the new lock file and test it.

Note that the first time you do this it will need to compile every included R package (because you won't have the R package builds cached locally). This can take several hours. (When we solve the caching problem here we'll be able to do this all in CI.)

Push the new Docker image to Github Container Registry

You will need to configure authentication to GitHub's container registry first. See GitHub's documentation.

When you have authentication configured, run:

just publish

Commit changes to this repository

Commit and push the small resulting change (should only be a few extra lines in packages.csv and renv.lock) to a branch, then get the changes merged via pull request.

The review is a trivial exercise because the Docker image has already been pushed to GitHub.

Deploy the new Docker image

The updated image will need pulling into production. This is covered separately in the tech team manual. If you don't have access, ask in #tech.

Troubleshooting

System dependencies

If the package requires any system build dependencies (e.g. -dev packages with headers), they should be added to build-dependencies.txt. If it requires runtime dependencies, they should be added to dependencies.txt. Packages don't advertise their system dependencies, so you may need to figure them out by trying to add the package and reading any error output on failure.

Installing an older version

If the package still fails to build, you may be able to install an older version.

Find a previous version at https://cran.r-project.org/src/contrib/Archive/{PACKAGE}/, and attempt to install it specifically with

just add-package PACKAGE@VERSION

Building, testing, and publishing the rstudio image

The rstudio image is based on the r image including rstudio-server. To build run

just build-rstudio

To test that rstudio-server appears at http://localhost:8787 run

just test-rstudio

And then push the new rstudio image to the GitHub container registry with

just publish-rstudio