Design Goals

1. compatible with Pangeo BinderHubs and JupyterHubs

2. compatible with Repo2Docker Python configuration files

3. reproducible build process and explicit conda package lists

4. small size, fast build

5. easy to customize

Everything stems from the Dockerfile in the base-image folder. The base-image configures default settings for Conda and Dask with condarc.yml and dask_config.yml files. The base-image is not meant to run on its own, it is the common foundation for -notebook images that install Python packages including JupyerLab and lab extensions. Lists of Conda packages for each image are specified in an environment.yml in each -notebook folder, and compatible Dask and Jupyter packages are guaranteed by specifying the pangeo-notebook conda metapackage.

You can pre-solve for compatible environments locally with conda-lock to convert the environment.yml file to a conda-linux-64.lock file which is an explicit list of compatible packages solved by Conda. The major advantage of doing this is that if you rebuild at a later date the resulting Conda environment is identical, which improves reproducibility. For this reason, when building off of the base-image, any existing conda-linux-64.lock file takes precedence over the environment.yml file.