Central compute environment definition(s) for ESM VFC.
You can just use the env file to install everything with Conda.
Note, however, that this env file does not specify any of the Jupyter and Dask configs that we also set in this repo.
You can use docker images that come with a fully working (repo2docker-built) Jupyter environment and run them with docker.
Assuming you want to expose your work directory to /work
in the container, and run:
docker pull esmvfc/esm-vfc-stacks:latest
docker run \
-v ${HOME}/work/:/work -w /work \
-p 8888:8888 esmvfc/esm-vfc-stacks:latest \
jupyter lab --no-browser --ip="0.0.0.0" --port="8888"
If you want to run a specific version of this image, replace the tag latest
accordingly.
All available versions are found on Dockerhub.
To run from your work/
dir with Singularity:
cd ${HOME}/work/
singularity run \
-B $(mktemp -d):/run/user \
docker://esmvfc/esm-vfc-stacks:<tag> \
jupyer lab --no-browser --ip="0.0.0.0"
If you want to run a specific version of this image, replace the tag latest
accordingly.
All available versions are found on Dockerhub.
Modify the env file or any of the Binder config or Dask config with a pull request.
There are no Github-based releases.
Instead, we use calver to build whenever something is pushed to master
and tag it as YYYY.MM.DD-<Git SHA>
on dockerhub.