JupyterLab for data scientists and researchers

Features

• Lightweight docker image with JupyterLab, Python 3.6;
• Well organised bash environment (bash history, non root user, etc.);
• Makefile for fast and easy everyday using;

Docker instalation

Please follow installation instructions from the official site.

Using

Prebuilt image is available from the docker hub

With makefile:

• make pull - pull latest image;
• make run local=path_to_the_project_folder name=name_of_the_container - build a new container and mount local project folder. The container is available by the url http://127.0.0.1:8888/;
• make start name_of_the_container - start specific container
• make stop name_of_the_container - stop specific container
• make stop_all - stop all containers
• make remove name_of_the_container - remove specific container
• make bash name_of_the_container - run bash for specific container

Examples

Workflow

• make pull - pull image from the docker hub;
• make run local=$PWD name=my-lab - create container with name my-lab and mount it to the current directory;
• got to the url http://127.0.0.1:8888/ - use JupyterLab;
• make bash my-lab - if you need access to the bash;
• pip install --user matplotlib - install new package;
• make stop my-lab - stop container;
• make start my-lab - start container;

Build container with specific enviroment

Dockerfile that installs a list of the specific requirements. Can be useful if you are using few containers with the same list of the libraries.