- Introduction
- Quick start for returning users
- Getting started for new users
- Why Nix? Comparison with Docker+renv/Conda/Guix
- Contributing
- Thanks
- Recommended reading
Introduction
rix is an R package that leverages Nix, a package manager focused on reproducible builds. With Nix, you can create project-specific environments with a custom version of R, its packages, and all system dependencies (e.g., GDAL
). Nix ensures full reproducibility, which is crucial for research and development projects.
Use cases include running web apps (e.g., Shiny, plumber APIs) or targets pipelines with a controlled R environment. Unlike renv, which snapshots package versions, rix provides an entire ecosystem snapshot, including system-level dependencies.
While Nix has a steep learning curve, rix
- simplifies creating Nix expressions, which define reproducible environments.
- lets you work interactively in IDEs like RStudio or VS Code, or use Nix in CI/CD workflows.
- provides helpers that make it easy to build those environments, evaluate the same code in different development environments, and finally to deploy software environments in production.
If you want to watch a 5-Minute video introduction click here.
Nix includes nearly all CRAN and Bioconductor packages, with the ability to install specific package versions or GitHub snapshots. Nix also includes Python, Julia (and many of their respective packages) as well as many, many other tools (up to 100’000 pieces of software as of writing).
If you have R installed, you can start straight away from your R session by first installing rix:
install.packages("rix", repos = c(
"https://ropensci.r-universe.dev",
"https://cloud.r-project.org"
))
library("rix")
Now try to generate an expression using rix()
:
# Choose the path to your project
# This will create two files: .Rprofile and default.nix
path_default_nix <- "."
rix(
r_ver = "4.3.3",
r_pkgs = c("dplyr", "ggplot2"),
system_pkgs = NULL,
git_pkgs = NULL,
ide = "code",
project_path = path_default_nix,
overwrite = TRUE,
print = TRUE
)
This will generate two files, default.nix
and .Rprofile
in project_default_nix
. default.nix
is the environment definition written in the Nix programming language, and .Rprofile
prevents conflicts with library paths from system-installed R versions, offering better control over your environment and improving isolation of Nix environments. .Rprofile
is created by rix_init()
which is called automatically by the main function, rix()
.
Quick Start for Returning Users
Click to expand
If you’re already familiar with Nix and rix, install Nix using the Determinate Systems installer:
You can then use rix to build and enter a Nix-based R environment:
library(rix)
path_default_nix <- "."
rix(
r_ver = "4.3.3",
r_pkgs = c("dplyr", "ggplot2"),
system_pkgs = NULL,
git_pkgs = NULL,
ide = "code",
project_path = path_default_nix,
overwrite = TRUE,
print = TRUE
)
# nix_build() is a wrapper around the command line tool `nix-build`
nix_build(project_path = ".")
If you don’t have R installed, but have the Nix package manager installed, you can run a temporary R session with R using this command (it will build an environment with the latest development version of rix ):
You can then create new development environment definitions, build them, and start using them.Getting started for new users
New to rix and Nix? Start by reading the vignette("a-getting-started")
(online documentation). to learn how to set up and use Nix smoothly.
Docker
Try Nix inside Docker by following this vignette("z-advanced-topic-using-nix-inside-docker")
vignette.
How is Nix different from Docker+renv/{groundhog}/{rang}/(Ana/Mini)Conda/Guix? or Why Nix?
Docker + {renv}
Docker and {renv} provide robust reproducibility by combining package snapshots with system-level dependencies. However, for long-term reproducibility, Nix offers a simpler approach by bundling everything (R, packages, and dependencies) in a single environment.
Ana/Miniconda & Mamba
Conda is similar to Nix, but Nix offers immutable environments, making it more reliable for preventing accidental changes. Nix also supports nearly all CRAN and Bioconductor packages, which Conda lacks.
Nix vs. Guix
Guix, like Nix, focuses on reproducibility, but Nix supports more CRAN/Bioconductor packages and works across Windows, macOS, and Linux.
Is {rix} all there is?
No, there are other tools that you might want to check out, especially if you want to set up polyglot environments (even though it is possible to use rix to set up an environment with R and Python packages for example).
Take a look at https://devenv.sh/ and https://prefix.dev/ if you want to explore other tools that make using Nix easier!
Contributing
Refer to Contributing.md
to learn how to contribute to the package.
Please note that this package is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.
Thanks
Thanks to the Nix community for making Nix possible, and thanks to the community of R users on Nix for their work packaging R and CRAN/Bioconductor packages for Nix (in particular Justin Bedő, Rémi Nicole, nviets, Chris Hammill, László Kupcsik, Simon Lackerbauer, MrTarantoga and every other person from the Matrix Nixpkgs R channel).
Finally, thanks to David Solito for creating rix’s logo!
Recommended reading
- NixOS’s website
- Nixpkgs’s GitHub repository
- Nix for R series from Bruno’s blog. Or, in case you like video tutorials, watch this one on Reproducible R development environments with Nix
- nix.dev tutorials
- INRIA’s Nix tutorial
- Nix pills
- Nix for Data Science
- NixOS explained: NixOS is an entire Linux distribution that uses Nix as its package manager.
- Blog post: Nix with R and devtools
- Blog post: Statistical Rethinking and Nix
- Blog post: Searching and installing old versions of Nix packages