Skip to content

Opinionated stacks of ready-to-run Jupyter applications in Docker.

License

Notifications You must be signed in to change notification settings

icecube/docker-stacks

 
 

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Repository files navigation

IceCube Data Science Docker Stacks

Docker Stacks are a set of ready-to-run Docker images containing Jupyter applications, IceCube tools, and interactive computing tools. Note, these need to use Nividia-docker to use system GPUs correctly.

Images available

Several images are provided that layer to a fully enabled image that contains python data science tools, icecube software (combo, skylab, etc).

  • base-notebook - Base notebook based on nvidia Tensorflow images, currently built on Ubuntu 18.04. Adds conda setup for dedicated python toolset based on Jupyter.
  • minimal-notebook - Adds some additional OS tools (tex, etc)
  • scipy-notebook - Adds several conda packages to support Scientific computing (scipy, numpy, astropy, pandas, etc)
  • datascience-notebook - Adds additional data science packages (Julia, R,...)
  • tensorflow-notebook - Adds tensorflow and Keras
  • icecube-notebook - Adds many icetray dependencies packages, test-data, photon tables, etc. Many dependencies are added to the conda install so that compiled icetray works well with "conda python".
  • icetray-notebook - Builds and adds latest combo release to runtime enviroment.

Quick Start

To start the icetray-notebook locally in your docker enviroment, such as Docker Desktop, use:

docker run -ti --rm -v ~/jupyter-notebooks:/home/jovyan -p 8888:8888 icecube/icetray-notebook:latest  start.sh jupyter lab

This command pulls the latesticetraty-notebookfrom Docker Hub if it is not already present on the local host. It then starts an ephemeral container running a Jupyter Notebook server and exposes the server on host port 8888. The command mounts the ~/jupyter-notebooks directory on the host as /home/jovyan/work in the container. Visiting http://<hostname>:8888/?token=<token> in a browser loads JupyterLab, where hostname is the name of the computer running docker and token is the secret token printed in the console. Docker destroys the container after notebook server exit, but any files written to ~/jupyter-notebooks in the container remain intact on the host.

Contributing

Talk to Erik.  @blaufuss on slack.

Jupyter resources

Alternatives

Resources

About

Opinionated stacks of ready-to-run Jupyter applications in Docker.

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages

  • Python 32.0%
  • Dockerfile 22.6%
  • Jupyter Notebook 20.9%
  • Shell 19.1%
  • Makefile 5.4%