• R install using Littler copied from rocker https://github.com/rocker-org/rocker
• R kernel for Jupyter provided by https://github.com/IRkernel/IRkernel
• R2Py from http://rpy.sourceforge.net/
• REVEAL slideshows from @damianavila https://github.com/damianavila/RISE
• • bash kernel

• R kernel
• Python kernel + R2Py R cell magic

• pull image from Dockerhub and run default

docker run --rm -it -p 8888:8888 cfljam/pyrat

Pull the image from Dockerhub and run a notebook server locally on port 8888 with Documents dir on host mounted

docker run --rm -it -p 8888:8888 \
-v ~/Documents/:/Documents cfljam/socker \
sh -c " ipython notebook --ip=0.0.0.0 --port=8888 \
--no-browser --notebook-dir=/Documents"

We invoke the notebook servers in a sh call to avoid kernel instability in OSX and Windows VM hosts ( See ipython/ipython#7062)

• this example uses Virtualbox as host
• install and configure docker-machine https://docs.docker.com/machine/#getting-started-with-docker-machine-using-a-local-vm
• clone the repo from Github

git clone https://github.com/cfljam/pyRat
cd pyRat

• if you are behind a proxy , insert lines at the head of the dockerfile

ENV http_proxy  http://my.proxy.url:my_proxy_port
ENV https_proxy  https://my.proxy.url:my_proxy_port

• to avoid running as root you might want to add a user with a

RUN useradd <my_login>

• and make this the default with a USER line

USER <my_login>

• build the image (you can call it anything you want-but in this case repo name, no other tags)

docker build -t cfljam/pyrat .

• ensure that there is a port forwarding rule for port 8888 on the virtual host (on Virtualbox in this case)
• run the container, sharing default Virtualbox shared directory mapping /Users

docker run --rm -p 8888:8888 -v /Users/:/Users -it cfljam/pyrat

• point your browser to localhost:8888 . You should see something like the screen below. Navigate the links to where you want to work and select new to create content.