Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Add reticulate and earthdatalogin R packages to base image #4

Open
ateucher opened this issue Apr 2, 2024 · 5 comments
Open

Add reticulate and earthdatalogin R packages to base image #4

ateucher opened this issue Apr 2, 2024 · 5 comments
Labels
enhancement New feature or request

Comments

@ateucher
Copy link
Member

ateucher commented Apr 2, 2024

Related to #5

@ateucher ateucher added the enhancement New feature or request label Apr 2, 2024
@ateucher ateucher transferred this issue from NASA-Openscapes/corn Apr 2, 2024
@ateucher ateucher changed the title Add reticulate R package to base image Add reticulate and earthdatalogin R package to base image Apr 2, 2024
@ateucher ateucher changed the title Add reticulate and earthdatalogin R package to base image Add reticulate and earthdatalogin R packages to base image Apr 2, 2024
@eeholmes
Copy link

@ateucher See packages here that Carl added which includes these plus a few others. This is my update to py-rocket.

https://github.com/nmfs-opensci/container-images/tree/main/images/py-rocket-geospatial

@ateucher
Copy link
Member Author

Brilliant, thanks @eeholmes - those are pretty much the packages I was thinking about! Can you tell me again why you use a base image with rocker/verse + the conda stuff, then you add the geospatial via /rocker_scripts/install_geospatial.sh, rather than using the rocker/geospiatal image as the base?

@ateucher
Copy link
Member Author

I do probably think it's a good idea to replicate the conda python environment from corn, as I am sure there is likely a set of users who will jump between both. Also from an administrative standpoint, managing one kind of python environment is easier. I am sure there must be a way to pull the conda setup from corn more efficiently than manual copy/paste.

@eeholmes
Copy link

The conda version is bigger, which doesn't matter for JupyterHub so much but does for Codespaces, Binder etc.

It is possible that using the conda-lock file from the Openscapes/python image would allow us to completely duplicate the Python environment wo having such a big image.

I am not sure of the implications of using venv w a conda-lock file on using the py-rocket as a base image for other Py-R images.

@eeholmes
Copy link

Also this is relevant: Pangeo design goals https://pangeo-docker-images.readthedocs.io/en/latest/topic/design.html

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
enhancement New feature or request
Projects
None yet
Development

No branches or pull requests

2 participants