Jupyter Notebook provides a great platform to produce human-readable documents containing code, equations, analysis, and their descriptions. Some even consider it a powerful development when combining it with NBDev. For such an integral tool, the out of the box start up is not the best. Each use requires starting the Jupyter web application from the command line and entering your token or password. The entire web application relies on that terminal window being open. Some might “daemonize” the process and then use nohup to detach it from their terminal, but that’s not the most elegant and maintainable solution.

Lucky for us, Jupyter has already come up with a solution to this problem by coming out with an extension of Jupyter Notebooks that runs as a sustainable web application and has built-in user authentication. To add a cherry on top, it can be managed and sustained through Docker allowing for isolated development environments.

By the end of this post we will leverage the power of JupyterHub to access a Jupyter Notebook instance which can be accessed without a terminal, from multiple devices within your network, and a more user friendly authentication method.

Prerequisites

A basic knowledge of Docker and the command line would be beneficial in setting this up.

I recommend doing this on the most powerful device you have and one that is turned on for most of the day, preferably all day. One of the benefits of this setup is that you will be able to use Jupyter Notebook from any device on your network, but have all the computation happen on the device we configure.

#machine-learning #data-science #jupyter-notebook #docker #tools