Docker image to load JupyterHub via Conda, with a few additional packages useful for climate/data analysis.
- Install Docker desktop
- Ensure Docker desktop is running
- Navigate to your project directory (i.e. with Jupyter notebook files)
- Download published image:
docker pull woodwardsh/jupyter-climate:latest
- Run published image:
docker run -i --rm --volume=${PWD}:/home/docker/jupyter-climate -w /home/docker/jupyter-climate -p 8888:8888 -t woodwardsh/jupyter-climate:latest
Help:
Docker run options used:
- -i = interactive
- -t = allow pseudo tty
- -p 8888:8888 = publish container ports to host
- --rm = remove container on exit
- -w PATH = working directory inside the container
- Clone repo & navigate inside:
git clone git@github.com:hannahwoodward/docker-jupyter-climate.git && cd docker-jupyter-climate
- Build image from Dockerfile (takes ~15 minutes):
docker build -t jupyter-climate .
- Navigate to your project directory (i.e. with Jupyter notebook files)
- Run locally built image:
docker run -i --rm --volume=${PWD}:/home/docker/jupyter-climate -w /home/docker/jupyter-climate -p 8888:8888 -t jupyter-climate
Help:
Docker build options used:
- -t = name/tag the image, format
name:tag
docker login
docker tag jupyter-climate woodwardsh/jupyter-climate
docker push woodwardsh/jupyter-climate
- Exit code 137 - need to increase Docker memory e.g. to 4GB
- No space left on device -
docker system prune