CRAN checks License: GPL-3

R build status R build status R build status

Authors: Brian Schilder, Alan Murphy, Nathan Skene

README updated: Jan-02-2024


If you use rworkflows, please cite:

Schilder, B.M., Murphy, A.E. & Skene, N.G. rworkflows: automating reproducible practices for the R community. Nat Commun 15, 149 (2024).


rworkflows is a suite of tools to make it easy for R developers to implement reproducible best practices on GitHub.

It includes three main components:
1. templateR template: a CRAN/Bioc-compatible R package template that automatically generates essential documentation using package metadata.
2. rworkflows R package: a lightweight CRAN package to automatically set up short, customisable workflows that trigger the rworkflows action.
3. rworkflows action: an open-source action available on the GitHub Actions Marketplace.

rworkflows action steps

GitHub Actions are a powerful way to automatically launch workflows every time you push changes to a GitHub repository. This is a form of Continuous Integration/Deployment (CI/CD), which helps ensure that your code is always working as expected (without having to manually check each time).

Here, we have designed a robust, reusable, and flexible action specifically for the development of R packages. We also provide an R function to automatically generate a workflow file that calls the rworkflows composite action:

Currently, rworkflows action can perform the following tasks (with options to enable/disable/modify each step):

  1. 🐳 Builds a Docker container to run subsequent steps within.
  2. 🐍 Builds and/or activates a custom conda environment.
  3. 🛠️ Installs system dependencies
  4. 🛠️ Installs LaTeX dependencies.
  5. 🛠 Installs R dependencies.
  6. ✅ Builds and checks your R package (with CRAN and/or Bioconductor checks).
  7. 📋 Runs unit tests.
  8. 📋 Runs code coverage tests and uploads the results to Codecov.
  9. 🚀 (Re)builds and launches a documentation website for your R package.
  10. 🐳 Pushes a Docker container (with Rstudio and all dependencies pre-installed) to your choice of container registry (e.g. GitHub Container Registry, DockerHub).
  11. 🔭 Generates workflow telemetry report.
  12. 🎖 Updates relevant badges added to your README with rworkflows::use_badges().

Importantly, this workflow is designed to work with any R package out-of-the-box. This means you won’t have to manually edit any yaml files, just run the rworkflows::use_workflow() function and you’re ready to go within seconds!

Note: rworkflows uses, was inspired by, and benefits from the work of many other projects, especially:
biocthis, usethis, actions/, r-lib/actions, bioc-actions, JamesIves/github-pages-deploy-action, docker/build-push-action, bioconductor_docker. For more details on how these projects relate to rworkflows, please see below.


Install and create the workflow in your R package’s project folder.

## in R

#### Install rworkflows R package ####
### For the stable CRAN release
if(!require("rworkflows")) install.packages("rworkflows")

### Or, for the latest development version
# if(!require("rworkflows")) remotes::install_github("neurogenomics/rworkflows")

### Create workflow file
path <- rworkflows::use_workflow()

Push to GitHub, and let everything else run automatically! You can check the status of your workflow by clicking on the Actions tab in your GitHub repo.

## in the Terminal
git add .
git commit -m "Added rworkflows"
git push

Note: If you want to skip running GitHub Actions on a particular push, simply add “[skip ci]” somewhere in the commit message, e.g.: git commit -m "Update README [skip ci]"



Get started

Introductory vignette for using rworkflows.


Copy-and-paste instructions for creating a Docker or Singularity container with the rworkflows R package pre-installed.

Dependency graph.

Interactive graph showing all the GitHub repos that currently use the rworkflows action.


rworkflows: taming the Wild West of R packages

Talk on the background, motivation, and utility of rworkflows.

Getting into the flow with rworkflows: an introductory tutorial

Step-by-step tutorial showing how to use rworkflows in an R package.

GitHub Secrets

To use certain features of rworkflows, you may need to set up one or more GitHub Secrets:


rworkflows builds upon the work of many others, especially the following:


This workflow is largely inspired by the workflow generated by the use_bioc_github_action() function within the biothis package, developed by @lcolladotor.

Key changes in rworkflows


biocthis was in turn inspired by usethis.


A general set of GitHub Actions maintained by the core GitHub team.


A set of GitHub Actions for R development maintained by the Rstudio/Posit team.


Bioconductor-oriented GitHub Actions created by @grimbough.


Builds and deploys the GitHub Pages documentation website in the rworkflows GHA workflows.


A set of GitHub Actions for building/pushing Docker containers.


Uses the official bioconductor/bioconductor_docker Docker container.

NOTE: Whenever a new version of Bioconductor is released, the bioconductor/bioconductor_docker container will often lag behind the actual Bioconductor releases for up to several days, due to the time it takes to update the container. This means that sometimes “devel” in Bioconductor/bioconductor_docker is actually referring to the current “release” version of Bioconductor (i.e. the previous Bioc version’s “devel”). For further details, see this Issue, and the Bioconductor release schedule.


This Dockerfile was partly adapted from the scFlow Dockerfile. Unlike other Dockerfiles, this one does not require any manual editing when applying to different R packages. This means that users who are unfamiliar with Docker do not have to troubleshoot making this file correctly. It also means that it will continue to work even if your R package dependencies change.


A very useful command line tool for testing GitHub Actions locally.


Runner images for each OS provided by GitHub.


GitHub Action to setup Miniconda and conda environments.

Session Info

## R version 4.3.1 (2023-06-16)
## Platform: aarch64-apple-darwin20 (64-bit)
## Running under: macOS Sonoma 14.2.1
## Matrix products: default
## BLAS:   /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/lib/libRblas.0.dylib 
## LAPACK: /Library/Frameworks/R.framework/Versions/4.3-arm64/Resources/lib/libRlapack.dylib;  LAPACK version 3.11.0
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
## time zone: America/New_York
## tzcode source: internal
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods   base     
## loaded via a namespace (and not attached):
##  [1] gtable_0.3.4        jsonlite_1.8.8      renv_1.0.3         
##  [4] dplyr_1.1.4         compiler_4.3.1      BiocManager_1.30.22
##  [7] tidyselect_1.2.0    rvcheck_0.2.1       scales_1.3.0       
## [10] yaml_2.3.8          fastmap_1.1.1       here_1.0.1         
## [13] ggplot2_3.4.4       R6_2.5.1            generics_0.1.3     
## [16] knitr_1.45          yulab.utils_0.1.2   tibble_3.2.1       
## [19] desc_1.4.3          dlstats_0.1.7       rprojroot_2.0.4    
## [22] munsell_0.5.0       pillar_1.9.0        RColorBrewer_1.1-3 
## [25] rlang_1.1.2         utf8_1.2.4          cachem_1.0.8       
## [28] badger_0.2.3        xfun_0.41           fs_1.6.3           
## [31] memoise_2.0.1.9000  cli_3.6.2           magrittr_2.0.3     
## [34] rworkflows_1.0.1    digest_0.6.33       grid_4.3.1         
## [37] rstudioapi_0.15.0   lifecycle_1.0.4     vctrs_0.6.5        
## [40] data.table_1.14.10  evaluate_0.23       glue_1.6.2         
## [43] fansi_1.0.6         colorspace_2.1-0    rmarkdown_2.25     
## [46] tools_4.3.1         pkgconfig_2.0.3     htmltools_0.5.7