Dockerize Data Science

Bring your Data Science tasks to Docker! 🐳

This is the code repository for the accompanying Medium article series "How to dockerize [x]":

• "How to dockerize Python environments"
• "How to dockerize Data Science"

Installation

Add the content of dockerize-datascience.sh to your .bashrc or .zshrc file.

Usage

Python

Choose your Python version:

Python version	Command
3.8	python3.8
3.9	python3.9
3.10	python3.10
3.11	python3.11
latest	python

This will run your python script or your interactive Python session in a Docker container. The current directory is mounted into the container. If you want to install dependencies, you should use the Python environment.

Python environment

In order to create a new or use an existing Python environment, run one of the following commands in your project folder:

Python version	Command
3.8	py-env-3.8
3.9	py-env-3.9
3.10	py-env-3.10
3.11	py-env-3.11
latest	py-env

The current directory is mounted into the container.

To delete the environment run py-env-del in your project folder.

Jupyter (JupyterLab)

For Jupyter (to use in the browser) run

jupyter

This uses the franzdiebold/datascience-ultimate Docker image.

The current directory is mounted into the container.

If you want to install dependencies, you should use the Jupyter environment.

Jupyter environment

In order to create a new or use an existing Jupyter environment, run the following command in your project folder:

jupyter-env

or shorter

je

This uses the franzdiebold/datascience-ultimate Docker image.

The current directory is mounted into the container.

To delete the environment run jupyter-env-del.

---

Jupyter Server

For Jupyter Server (to use with a different client software for your notebooks such as JetBrains DataSpell) run

jupyter-server

This uses the franzdiebold/datascience-ultimate-server Docker image.

The current directory is mounted into the container.

If you want to install dependencies, you should use the Jupyter Server environment.

Jupyter Server environment

In order to create a new or use an existing Jupyter Server environment, run the following command in your project folder:

jupyter-server-env

or shorter

jes

This uses the franzdiebold/datascience-ultimate-server Docker image.

The current directory is mounted into the container.

To delete the environment run jupyter-server-env-del.