For detailed requirements and install instructions see irkernel.github.io
This package is available on CRAN:
install.packages('IRkernel') IRkernel::installspec() # to register the kernel in the current R installation jupyter labextension install @techrah/text-shortcuts # for RStudio’s shortcuts
IRkernel::installspec() will install a kernel with the name “ir” and a
display name of “R”. Multiple calls will overwrite the kernel with a kernel spec pointing to the last
R interpreter you called that commands from. You can install kernels for multiple versions of R
by supplying a
displayname argument to the
installspec() call (You still need to
install these packages in all interpreters you want to run as a jupyter kernel!):
# in R 3.3 IRkernel::installspec(name = 'ir33', displayname = 'R 3.3') # in R 3.2 IRkernel::installspec(name = 'ir32', displayname = 'R 3.2')
By default, it installs the kernel per-user. To install system-wide,
user = FALSE. To install in the
sys.prefix of the currently
jupyter command line utility, use
sys_prefix = TRUE.
Now both R versions are available as an R kernel in the notebook.
If you encounter problems during installation
- Have a look at the full installation instructions!
- Search the existing open and closed issues.
- If you are sure that this is a new problem, file an issue.
Running the notebook
If you have Jupyter installed, you can create a notebook using IRkernel from the dropdown menu.
You can also start other interfaces with an R kernel:
# “ir” is the kernel name installed by the above `IRkernel::installspec()` # change if you used a different name! jupyter qtconsole --kernel=ir jupyter console --kernel=ir
Run a stable release in a Docker container
Refer to the jupyter/docker-stacks r-notebook repository
If you have a Docker daemon running, e.g. reachable on localhost, start a container with:
docker run -d -p 8888:8888 jupyter/r-notebook
Open localhost:8888 in your browser. All notebooks from your session will be saved in the current directory.
On other platforms without docker, this can be started using
docker-machine by replacing “localhost” with an IP from
docker-machine ip <MACHINE>. With the deprecated
boot2docker, this IP will be
Develop and run from source in a Docker container
make docker_dev_image #builds dev image and installs IRkernel dependencies from github make docker_dev #mounts source, installs, and runs Jupyter notebook; docker_dev_image is a prerequisite make docker_test #builds the package from source then runs the tests via R CMD check; docker_dev_image is a prerequisite
How does it know where to install?
The IRKernel does not have any Python dependencies whatsoever, and
does not know anything about any other Jupyter/Python installations
you may have. It only requires the
jupyter command to be available
$PATH. To install the kernel, it prepares a kernelspec directory
kernel.json and so on), and passes it to the command
jupyter kernelspec install [options] prepared_kernel_dir/,
where options such as
--sys-prefix are given based on the options.