👨🏼‍💻 docker-for-ds

A practical introduction to Docker for data scientists, showing how to use and combine Jupyter and MSSQL Server in local isolated Docker containers.

The medium post here for the longer tutorial.

🐳 Starting with Docker

• Install Docker. This is a straightforward download from the docs.

• Open up the app and make sure there's a green light telling you it's running.

• Follow the hello-world tutorial to double check the installation works properly.

🆙 Walkthrough

We will be running two separate Docker containers:

1. An ubuntu xenial container to run python code in Jupyter notebooks

2. An MSSSQL Server linux container to host our database

Open a terminal in the root of the repo and run the following commands:

docker-compose build

Builds the images with docker-compose.yml acting as the configuration

docker-compose up -d

Spins up the containers

docker-compose exec app bash

Runs bash from inside the 'app' container

You will be inside the container's terminal now, run:

jupyter notebook --ip 0.0.0.0 --no-browser --allow-root

Using the provided token, enter this into your browser

http://localhost:8888/?token=URTOKEN

✅ The token provides a security measure to make sure hackers can't access your code and data!

🎮 Running the notebook will extract Ninja's current Fortnite stats and load them into a fortnite table in your MSSQL instance. View your output table in a database management app. I like to use DBeaver.

How to only build the Jupyter environment

Open a terminal and navigate to /app, then run

docker build -t ds .

builds image with tag 'ds'

docker run --rm -it -p 8888:8888 ds

runs the ds image with notebook ports mapped