Repository for building OceanhackWeek 2023 JupyterHub environments (Docker Images) with GitHub Actions CI
Docker images publicly available here. jupyter-image
is the 2021 image, while python
and r
are for their matching profiles on the hub.
This repository contains configuration for the standard environment used during the OceanhackWeek 2023.
When you log into the OceanhackWeek JupyterHub you are running a virtual machine with Ubuntu 22.04,
a variety of command line tools like vim
and git
,
a conda
Python/R environment with compatibly package versions,
and JupyterLab extensions such as ipywidgets
and ipyleaflet
.
By packaging everything up with Docker we help ensure that code written during the hackweek is reproducible and can be run on different physical hardware today and in the future.
There are a handful of helpful make
commands for building and testing images.
py-lock
- Generate a new Python lockfile.py-build
- Build Python Docker container (should regenerate lockfile ifenvironment.yml
was changed).py-lab
- Launch JupyterLab for Python image. Watch the terminal output for a127.0.0.1:8080/...
link with the access token.r-lock
- Generate a new R lockfile.r-build
- Build R Docker container (should regenerate lockfile ifenvironment.yml
was changed).r-lab
- Launch JupyterLab for R image. Watch the terminal output for a127.0.0.1:8080/...
link with the access token. Once in JupyterLab, you should be able to launch RStudio.
Both images use nb_conda_kernels
which allows our users to create their own Conda environments.
This makes it so that we don't have to package everything into the images to start with.
To test that environments can be created, launch JupyterLab in one of the images.
conda create -n <env-name> <requirements>
, and make sure one of the requirements is a Jupyter kernel, likeipykernel
.- Try
conda activate <env-name>
and seeing if it's different than the base environment. - The JupyerLab new notebook/console creation screen should now show options for
<env-name>
. This can sometimes take a few minutes beforenb_conda_kernels
sees it.