This post is the second in a series of three blog posts that cover the basics of running R in Docker. The three parts are:
In this post, we will discuss how to install packages in an image using
rocker/tidyverse as the base image. The basic steps are the same for extending
rocker/r-ver...or any Docker image, for that matter.
In Part 1 we saw that it was quite easy to run an instance of RStudio Server with the tidyverse installed:
$: docker run -d --name rstudio -p 80:8787 rocker/tidyverse
What do we do if we find we really need the
ggthemes package consistently in our work?
ggthemes is not part of the
it will not be available in the RStudio Server container that we just started. One option would be to simply ask users to install it if they need it, by running
install.packages("ggthemes") from the console prompt in RStudio. This would, of course, work...to a point. But remember that the package would only be available in
the container in which the package was installed. If you remove the container, and start up a new one, you would need to repeat the package install.
It would be much better to create an image with the environment you want, so that the package install happens once for all the future containers that need it, without any additional effort required at container runtime.
Creating our own image requires writing a Dockerfile, which is a sort of script that defines the image filesystem and environment. There are many useful things that you
can do in a Dockerfile to control the image environment. Here, we only need two know two Dockerfile instructions:
FROM, which identifies the image to serve as the base
for our new image, and
RUN, which runs a command in the image assembly process. The following Dockerfile customizes the
image to include
FROM rocker/tidyverse RUN R -e 'install.packages("ggthemes")'
To build the image (which we'll call tidyverse-ggthemes), put the Dockerfile (and be sure to name it "Dockerfile") in an empty directory (whch is usually inside a directory structure maintained in a source control repository, but for now, any empty directory will do). Then, from the directory where the Dockerfile lives, run:
$: docker build -t tidyverse-ggthemes .
If the image build succeeded, you should see
tidyverse-ggthemes in the list of images produced by running
docker images. You can also do a quick
test to verify that the package was installed properly:
$: docker run -ti --rm tidyverse-ggthemes R -e 'library(ggthemes)'
If you see:
Error in library(ggthemes) : there is no package called ‘ggthemes’ Execution haltedthen something is wrong...make sure the Dockerfile and build command are exactly as above. If instead you see:
> library(ggthemes) >Then all is well! (This command also illustrates how it's possible to pass arguments to the process executable when running a container.)
You can now run RStudio Server from this image, and
ggthemes will be installed and ready to use:
$: docker run -d --name rstudio -p 80:8787 tidyverse-ggthemes
In the third and final post in this series, we will see how to use Docker to reproduce research results in the form of an RMarkdown document knitted by a Docker container.