DS_project

You found these great Docker containers for data science, but they are a hassle to use? These scripts make it easy to start, stop and destroy these containers.

This is a companion-repository for either the Original Jupyter Docker Stacks or the GPU-enabled Docker Stacks.

🎬 Getting started

1. Clone this repository.

git clone git@github.com:OleMussmann/DS_project.git

2. Rename the folder to your liking, cd into folder.

mv DS_project MyDataScienceProject && cd MyDataScienceProject

3. Edit the .env file and choose a docker container for the NOTEBOOK variable, for example:

NOTEBOOK=isbjornlabs/fastai-notebook-cuda10.1:latest

4. For quick testing, just use the workdir folder to preserve your scripts and data. For a serious project, please consider a proper project structure like Cookiecutter Data Science within the workdir.

5. Use the scripts below to start, stop and destroy your data science environments.

📑 Scripts

dc is a (very thin) wrapper around docker-compose, use it just the same. enter_container starts a bash-shell in an existing container, if you prefer to work without Jupyter notebooks.

Jupyter Notebook

action	command
start container	./dc up
stop container	CTRL-C
remove container	./dc down

Bash Shell

action	command
start container	./dc -f docker-compose-bash.yml up
enter container	different terminal: ./enter_container
exit container	different terminal: CTRL-D
stop container	CTRL-C
remove container	./dc -f docker-compose-bash.yml down

Customization

Use environment variables to quickly override settings without editing .env. Starting a different notebook jupyter/tensorflow-notebook on port 1234:

NOTEBOOK=jupyter/tensorflow-notebook PORT=1234 ./dc up