Available Container Images

JupyerHub makes use of a container image to execute your code/commands. You must use a container image that contains the software you wish to use. We use images provided by Nautilus which are based on Jupyter Docker Stacks. However, additional images can be created for specific needs.

All images include GPU Nvidia and CUDA support, and will provide access to GPU resources if selected during container launch.

General Container Images

The following general purpose containers are available for use.

Name	Image	Software
Stack Minimal	minimal-notebook	Ubuntu 20.04 JupyterLab 4.0.2 Python 3.10.12 Git 2.25.1 Cuda 11.7.r11.7 vi nano tzdata unzip
Stack R	r-notebook	(everything in minimal-notebook) R 4.3.1 IRKernel to support R code in Jupyter notebooks tidyverse packages 2.0.0 caret, crayon, devtools, forecast, hexbin, htmltools, htmlwidgets, nycflights13, randomforest, rcurl, rmarkdown, rodbc, rsqlite, shiny, tidymodels, unixodbc packages from conda-forge
Stack SciPy	scipy-notebook	(everything in minimal-notebook) altair, beautifulsoup4, bokeh, bottleneck, cloudpickle, conda-forge::blas=*=openblas, cython, dask, dill, h5py, matplotlib-base, numba, numexpr, openpyxl, pandas, patsy, protobuf, pytables, scikit-image, scikit-learn, scipy, seaborn, sqlalchemy, statsmodel, sympy, widgetsnbextension, xlrd packages ipympl and ipywidgets for interactive visualizations and plots in Python notebooks Facets for visualizing machine learning datasets
Stack Tensorflow	tensorflow-notebook	(everything in scipy-notebook) tensorflow 2.11.0 machine learning library
Stack Datascience	datascience-notebook	(everything in tensorflow-notebook) rpy2 package The Julia 1.7.2 compiler and base environment IJulia to support Julia code in Jupyter notebooks HDF5, Gadfly, RDatasets packages
Stack PRP	prp-notebook	(everything in tensorflow-notebook) astropy, bowtie, fastai, keras, nbgitpuller, opencv-python, psycopg2-binary, tensorflow-probability, torch 1.13.1, torchvision, visualdl, CommPy packages
R Studio	r-studio	(everything in minimal-notebook)

The following diagram shows the relationship of the above container images.

graph LR;
    A[minimum-notebook]-->B[r-notebook];
    A-->G[r-studio];
    A-->C[scipy-notebook]-->D[tensorflow-notebook]-->E[datascience-notebook];
    D-->F[prp-notebook];

Custom Container Images

Name	Image	Course	Software
Eclipse C/C++ Desktop	eclipse-notebook	COMPE 160 Introduction to Computer Programming	(everything in minimal-notebook) Eclipse IDE for C/C++ Developers 2022-03 release for Linux x86_64 icedtea-netx net-tools dbus-x11 firefox xfce4 xfce4-panel xfce4-session xfce4-settings xorg xubuntu-icon-theme gpg curl lsb-core
Kube Notebook	kube-notebook	Research for Interacting with Kubernetes	(everything in minimal-notebook) kubectl rclone vim git unzip zip curl wget
SageMath Notebook	sagemath-notebook	MATH 522 Number Theory	(everything in scipy-notebook) sage
GIS Notebook	gis-notebook	GEOG 582 GIS Programming with Python	(everything in scipy-notebook) geopandas geoplot rasterio laspy netcdf4 psycopg2 networkx pysal beautifulsoup4 selenium
Health Informatics Notebook	health-informatics-notebook	P H 700A Principle Program Data Structures in Public Health	(everything in scipy-notebook) biopython pytest

The following diagram shows the relationship between the general and custom container images.

graph LR;
    A[minimum-notebook]-->B[Eclipse-Desktop];
    A-->C[Scipy-Notebook]-->D[SageMath-Notebook];
    A-->F[Kube-Notebook];
    C-->E[GIS-Notebook];
    C-->G[Health-Informatics-Notebook]