R is a free software environment for statistical computing and graphics. It compiles and runs on a wide variety of UNIX platforms, Windows and MacOS. See more at https://www.r-project.org/
The main goal of these images is to keep them minimal, so they can be
used as part of a bigger (web) application, or as a base image.
Currently the (R 4.1.0) r-minimal
image is less than 21MB compressed,
and 35.4MB uncompressed.
All images use Alpine Linux.
The images include the installr
tools that can install R packages from
CRAN or GitHub:
❯ installr -h
Usage: ./installr [ -c | -d ] [ -a pkgs ] [ -t pkgs ] [ -r ] [ -p ] REMOTES ...
Options:
-c install C and C++ compilers and keep them
-d install C and C++ compilers, temporarily
-a install Alpine packages and keep them
-t install Alpine packages, temporarily
-p do not remove pak after the installation (ignored if -r is given).
REMOTES may be:
* package names from CRAN/Bioconductor, e.g. ggplot2
* slugs of GitHub repos, e.g. tidyverse/ggplot2
* GitHub branch, tag or commit, e.g tidyverse/ggplot2@v1.0.0
* URLs to package .tar.gz files, e.g. url::https://x.com/pkg.tar.gz
* path to a local directory, e.g. local::.
Recent r-minimal containers use pak (https://github.com/r-lib/pak) for R packages installation. If you have problems with pak, or need to install a package from a source that pak does not support, but the remotes package does, then install the remotes package first.
To keep the images minimal, they do not include a number of parts and features that most users would prefer to have for interactive R development:
- Recommended R packages are not installed.
- Documentation is not included.
- No X11 support.
- No Java support.
- No OpenMP support.
- No JPEG, PNG or TIFF support.
- No Cairo support.
- No Tcl/Tk support.
- No translations, only English.
- The image does not have C, C++ or Fortran compilers.
- Limited time zone data:
GMT
,UTC
andAmerica/New_York
, see below if you need better time zone data.
Get the image from Docker Hub:
docker pull docker.io/rhub/r-minimal:latest
or from GitHub Packages:
docker pull docker.pkg.github.com/r-hub/r-minimal/r-minimal:latest
All images are available on linux/amd64
and linux/arm64
platforms.
Currently we support the last patch version of the last five minor R
versions. The latest
tag always uses the last R release.
image | R version | tags | note |
---|---|---|---|
R devel | 4.3.0-devel | devel , 4.3.0 , 4.3 , 4.3.0-devel , 4.3-devel |
Built daily |
R next | 4.2.2-RC | next , 4.2.2 , 4.2 , rc , 4.2.2-rc , 4.2-rc |
Built daily |
R release | 4.2.2 | 4.2.2 , 4.2 , release , latest |
|
R 4.1.x | 4.1.3 | 4.1.3 , 4.1 |
|
R 4.0.x | 4.0.5 | 4.0.5 , 4.0 |
|
R 3.6.x | 3.6.3 | 3.6.3 , 3.6 |
|
R 3.5.x | 3.5.3 | 3.5.3 , 3.5 |
One of our main goals is to be able to use rhub/r-minimal
as a base
image, and easily add R packages from CRAN or GitHub to it, to create a
new image. Run installr
from a Dockerfile
to add R packages to the
r-minimal
image:
FROM rhub/r-minimal
RUN installr praise
CMD [ "R", "--slave", "-e", "cat(praise::praise())" ]
Package with compiled code:
FROM rhub/r-minimal
RUN installr -d glue
After the package(s) have been installed, installr
removed the
compilers, as these are typically not needed on the final image. If you
want to keep them use installr -c
instead of installr -d
.
Package with system requirements:
FROM rhub/r-minimal
RUN installr -d -t linux-headers pingr
CMD [ "R", "-q", "-e", "pingr::is_online() || stop('offline')" ]
Similarly to compilers, system packages are removed after the R packages
have been installed. If you want to keep (some of) them, use installr -a
instead of installr -t
. (You can also mix the two.)
Hints on installing some popular R packages:
package | installr command | ~ image size |
---|---|---|
data.table | installr -d data.table |
39.1 MB |
dplyr | installr -d dplyr |
47.8 MB |
ggplot2 | installr -d -t gfortran ggplot2 |
82.1 MB |
h2o | See examples/h2o . |
408.0 MB |
knitr | installr -d knitr |
79.2 MB |
shiny | See examples/shiny . |
84.1 MB |
plumber | See examples/plumber . |
103.1 MB |
rmarkdown | installr -d rmarkdown |
161.3 MB (including pandoc) |
rstan | See examples/rstan . |
344.4 MB |
tidyverse | See examples/tidyverse . |
302.5 MB |
xgboost | installr -d -t "gfortran libexecinfo-dev" -a libexecinfo xegboost |
59.9 MB |
See also the Dockerfile
s in the examples
directory.
Note that package and system dependencies change over time, so if any of these commands do not work any more, please let us know.
See the [examples/rmarkdown/Dockerfile] for installing pandoc.
The image uses R’s internal time zone database, but most time zones are
removed from, to save space. The only supported ones are GMT
, UTC
and America/New_York
. If you need more time zones, then install
Alpine’s time zone package and point R to it:
apk add --no-cache tzdata
export TZDIR=/usr/share/zoneinfo
See also the discussion at r-hub#24
-
The ps package needs the
linux-headers
Alpine package at compile time. Many tidyverse packages depend on ps, so they’ll need it as well:installr -d -t linux-headers ps
-
The arrow package are hard to install, because Alpine Linux does not have the required libraries. For the details, please see: r-hub#7
-
The V8 package does not compile on Alpine Linux by default. Luckily, you can now download a static binary of V8:
DOWNLOAD_STATIC_LIBV8=1 installr -d -t curl-dev V8
-
The prophet package depens on V8, through rstan, and you can use the same trick to install it:
DOWNLOAD_STATIC_LIBV8=1 installr -d -t "linux-headers gfortran curl-dev" prophet
-
The readxl package does not compile on Alpine Linux currently. You can install this branch from GitHub:
installr -d gaborcsardi/readxl@fix/alpine-linux
-
The tidyverse package depends on readxl, so you’ll need to do the same:
installr -d -t "curl-dev libxml2-dev linux-headers gfortran" \ -a "libcurl libxml2" gaborcsardi/readxl@fix/alpine-linux tidyverse
-
To install the magick package, you need both the
imagemagick
andimagemagick-dev
Alpine packages, both at install time and run time:installr -d -a "imagemagick imagemagick-dev" -t "curl-dev" magick
See https://www.r-project.org/Licenses/ for the R licenses
These Dockerfiles are licensed under the MIT License.