Public | Automated Build

Last pushed: 3 years ago
Short Description
Docker Container for Jupyter notebooks with R
Full Description


Docker Container for Jupyter notebooks with R kernel and R Cell Magic

Example Notebooks

To Use

  • 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= --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

To Build Docker Image

git clone
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 .

To run the image

  • 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.
Docker Pull Command
Source Repository