Welcome to the JupyterHub Deployment Docs for ENGR114 2020Q1


This documentation serves as a record of the JupyterHub Deployment for ENGR114 Winter 2020 at Portland Commmunity College.


The GitHub repo for the deployment can be found here:

https://github.com/ProfessorKazarinoff/jupyterhub-ENGR114-2020Q1


Click the menu items on the left to view the deployment steps.

Or start Here and click the arrows at the bottom of each page.

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What is JupyterHub?

JupyterHub is a cloud server-hosted distributed Jupyter notebook deployment. JupyterHub allows users to log into a server and write Python code within a web browswer without installing any software on their local machine. After JupyterHub is deployed, anywhere you have an internet connection, you can bring up a Jupyter notebook in your browser and write/run Python code. The Jupyter notebook interface that JupyterHub provides is the same Jupyter notebook interface you can run locally. Because JupyterHub runs in a web browser, it even works on tablets and phones.

Why JupyterHub?

Why Jupyter Hub? I am teaching an engineering programming course Winter quarter 2020. In previous quarters, I've taught MATLAB for the programming class. But now, I am teaching Python and cover the same concepts and learning outcomes.

When we use Python in the class, I would like to spend the class time coding and solving problems. I don't want to spend time during class downloading Python, creating virtual environments, troubleshooting installs, dealing with system vs. non-system versions of Python, installing packages, dealing with folder structure, explaining the difference between conda and pip, teaching command-line arguments, going over Python on Windows compared to Python on MacOS... One solution is to use JupyterHub.

A series of blog posts documents my first JupyterHub deployment in Summer 2018. This documentation builds upon that previous experience.

A deployment of JupyterHub Winter 2019 documents my second JupyterHub installation. This documentation closely follows the same steps with only a few minor alterations.

Main Steps

  • Install PuTTY, generate SSH keys
  • Create a new Ubuntu 18.04 server on Digital Ocean
  • Install JupyterHub and Python packages
  • Aquire and link domain name to server
  • Aquire SSL cirt
  • Create Cookie Secret, Proxy Auth Token, and dhparam.pem
  • Install and configure Nginx
  • Configure JupyterHub
  • Google Authentication
  • Create a custom login page
  • Cull idle servers script