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Native R kernel for Jupyter Build Status

For detailed requirements and install instructions see irkernel.github.io

Requirements

Installation

We will soon submit the IRkernel package to CRAN. Until then, you can install it via the devtools package:

install.packages(c('repr', 'IRdisplay', 'crayon', 'pbdZMQ', 'devtools'))
devtools::install_github('IRkernel/IRkernel')
IRkernel::installspec()  # to register the kernel in the current R installation

Per default 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 name and 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')

Now both R versions are available as an R kernel in the notebook.

If you encounter problems during installation

  1. Have a look at the full installation instructions!
  2. Search the existing open and closed issues.
  3. 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

In your browser open the URL http://localhost:8888/. 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 boot2docker ip.

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