Workshop pre-requisites:

Install Docker

Follow the instructions at https://docs.docker.com/install/ (for Windows/Linux/MacOS) to install and configure Docker CE.

On most systems, you can use the get-docker script to install Docker. On Ubuntu / Debian, it looks like this:

# Update your OS packages
sudo apt-get update
sudo apt-get upgrade

# Install curl
sudo apt-get -y install curl

# Download the get-docker.sh script
curl -fsSL get.docker.com -o get-docker.sh

# Run the installer script
sudo sh get-docker.sh

# Setup the Docker user
sudo usermod -aG docker $USER

# Install docker-compose. May want to Anaconda Python or pip beforehand
pip install docker-compose

# Logout / login..

# Grab a few images
docker pull ubuntu
docker pull alpine
docker pull postgres
docker pull alpine

Reproducible Data Science with Docker

• ASCIINEMA DEMO: https://asciinema.org/a/165285
• Commandline Interactive Tutorial / Demo (as recorded above) can be found in ./docker-demo. Entry point is menu.sh. Requires dialog, figlet and docker (can be installed using docker-demo/tools/install-docker-ubuntu.sh)

Docker image:

• The final image built by this demo can be found at: https://hub.docker.com/r/cmihai/jupyter/

Docker Compose file and scripts

• Source can be found here: https://github.com/crivetimihai/docker-data-science

How to run the image:

• This image has been published as cmihai/jupyter. Just do a:

docker pull
docker run --init --detach \
    --name jupyter --hostname jupyter \
    -p 8888:8888 \
    --volume ${HOME}/notebooks:/home/jupyter/notebooks:rw \
    --volume ${HOME}/.jupyter:/home/jupyter/.jupyter \
    cmihai/jupyter

Reference and where to learn more:

• Learn Docker here: https://www.katacoda.com/courses/docker
• Learn Shell here: https://www.hackerrank.com/domains/shell/bash