this tutorial shows the proper way to dockerize ipython notebooks.
while sharing notebooks through traditional means is often sufficient for data science workflows, this tutorial will allow us to work our way up to more complicated data science tasks, including distributed ml models through tensorflow + kubernetes.
download docker for mac
there are a couple of good data science base images: dataquestio and floyd-hub.
FROM dataquestio/python2-starter
copy local notebooks from src
to /home/ds/notebooks
.
COPY src /home/ds/notebooks
do docker build -t mynameisvinn/ipython .
dont forget the period!
do docker run -d -p 8888:1111 mynameisvinn/ipython
.
to access the dockerized notebook, go to CONTAINER_IP:1111
. note: you can find CONTAINER_IP with docker-machine ip default
.
do docker stop $(docker ps -a -q)