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pyrat's Introduction

pyRat

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=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)

To Build Docker Image

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 .

To run the image

  • ensure that there is a port forwarding rule for port 8888 on the virtual host (on Virtualbox in this case) Virtualbox port forward rule
  • 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. Jupyter Screen

pyrat's People

Contributors

cfljam avatar

Watchers

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