Selecting an Image — Docker Stacks documentation (original) (raw)

This section provides details about the first.

Core Stacks#

The Jupyter team maintains a set of Docker image definitions in the jupyter/docker-stacks GitHub repository. The following sections describe these images, including their contents, relationships, and versioning strategy.

jupyter/docker-stacks-foundation#

Source on GitHub |Dockerfile commit history |Quay.io image tags

jupyter/docker-stacks-foundation is a small image supporting a majority of options common across all core stacks. It is the basis for all other stacks on which Jupyter-related applications can be built (e.g., kernel-based containers, nbclient applications, etc.). As such, it does not contain application-level software like JupyterLab, Jupyter Notebook, or JupyterHub.

It contains:

• Package managers
  • conda: “cross-platform, language-agnostic binary package manager”.
  • mamba: “reimplementation of the conda package manager in C++”. We use this package manager by default when installing packages.
• Unprivileged user jovyan (uid=1000, configurable, see options in the common features section of this documentation) in group users (gid=100) with ownership over the /home/jovyan and /opt/conda paths
• tini and a start.sh script as the container entry point - useful for running alternative commands in the container as applications are added (e.g. ipython, jupyter kernelgateway, jupyter lab)
• A run-hooks.sh script, which can source/run files in a given directory
• Options for a passwordless sudo
• Common system libraries like bzip2, ca-certificates, locales
• wget to download external files
• No preinstalled scientific computing packages

jupyter/base-notebook#

Source on GitHub |Dockerfile commit history |Quay.io image tags

jupyter/base-notebook adds base Jupyter Applications like JupyterLab, Jupyter Notebook, JupyterHub, and NBClassic and serves as the basis for all other stacks besides jupyter/docker-stacks-foundation.

It contains:

• Everything in jupyter/docker-stacks-foundation
• Minimally functional Server (e.g., no LaTeX support for saving notebooks as PDFs)
• notebook, jupyterhub-singleuser, and jupyterlab packages
• A start-notebook.py script as the default command
• A start-singleuser.py script useful for launching containers in JupyterHub
• Options for a self-signed HTTPS certificate

Warning

jupyter/base-notebook also contains start-notebook.sh and start-singleuser.sh files to maintain backward compatibility. External config that explicitly refers to those files should instead update to refer to start-notebook.py and start-singleuser.py. The shim .sh files will be removed at some future date.

jupyter/minimal-notebook#

Source on GitHub |Dockerfile commit history |Quay.io image tags

jupyter/minimal-notebook adds command-line tools useful when working in Jupyter applications.

It contains:

• Everything in jupyter/base-notebook
• Common useful utilities likecurl,git,nano (actually nano-tiny),tzdata,unzip, and vi (actually vim-tiny),
• TeX Live for notebook document conversion

jupyter/r-notebook#

Source on GitHub |Dockerfile commit history |Quay.io image tags

jupyter/r-notebook includes popular packages from the R ecosystem listed below:

• Everything in jupyter/minimal-notebook and its ancestor images
• The R interpreter and base environment
• IRKernel to support R code in Jupyter notebooks
• tidyversepackages from conda-forge
• caret,crayon,devtools,forecast,hexbin,htmltools,htmlwidgets,nycflights13,randomforest,rcurl,rmarkdown,rodbc,rsqlite,shiny,tidymodels,unixodbcpackages from conda-forge

jupyter/julia-notebook#

Source on GitHub |Dockerfile commit history |Quay.io image tags

jupyter/julia-notebook includes popular packages from the Julia ecosystem listed below:

• Everything in jupyter/minimal-notebook and its ancestor images
• The Julia compiler and base environment
• IJulia to support Julia code in Jupyter notebook
• Pluto.jl reactive Julia notebook interface, made accessible with jupyter-pluto-proxy
• HDF5 package

jupyter/scipy-notebook#

Source on GitHub |Dockerfile commit history |Quay.io image tags

jupyter/scipy-notebook includes popular packages from the scientific Python ecosystem.

• Everything in jupyter/minimal-notebook and its ancestor images
• altair,beautifulsoup4,bokeh,bottleneck,cloudpickle,conda-forge::blas=*=openblas,cython,dask,dill,h5py,jupyterlab-git,matplotlib-base,numba,numexpr,openpyxl,pandas,patsy,protobuf,pytables,scikit-image,scikit-learn,scipy,seaborn,sqlalchemy,statsmodel,sympy,widgetsnbextension,xlrdpackages
• ipympl andipywidgetsfor interactive visualizations and plots in Python notebooks
• Facetsfor visualizing machine learning datasets

jupyter/tensorflow-notebook#

Source on GitHub |Dockerfile commit history |Quay.io image tags

jupyter/tensorflow-notebook includes popular Python deep learning libraries.

• Everything in jupyter/scipy-notebook and its ancestor images
• TensorFlow machine learning library
• Jupyter Server Proxy to support TensorBoard

jupyter/pytorch-notebook#

Source on GitHub |Dockerfile commit history |Quay.io image tags

jupyter/pytorch-notebook includes popular Python deep learning libraries.

• Everything in jupyter/scipy-notebook and its ancestor images
• pytorch machine learning library

jupyter/datascience-notebook#

Source on GitHub |Dockerfile commit history |Quay.io image tags

jupyter/datascience-notebook includes libraries for data analysis from the Python, R, and Julia communities.

• Everything in the jupyter/scipy-notebook, jupyter/r-notebook, and jupyter/julia-notebook images and their ancestor images
• rpy2 package

jupyter/pyspark-notebook#

Source on GitHub |Dockerfile commit history |Quay.io image tags

jupyter/pyspark-notebook includes Python support for Apache Spark.

• Everything in jupyter/scipy-notebook and its ancestor images
• Apache Spark with Hadoop binaries
• grpcio-status
• grpcio
• pyarrow

jupyter/all-spark-notebook#

Source on GitHub |Dockerfile commit history |Quay.io image tags

jupyter/all-spark-notebook includes Python and R support for Apache Spark.

• Everything in jupyter/pyspark-notebook and its ancestor images
• IRKernel to support R code in Jupyter notebooks
• rcurl,sparklyr,ggplot2packages

CUDA enabled variants#

We provide CUDA accelerated versions of the pytorch-notebook and tensorflow-notebook images. Prepend a CUDA prefix (versioned prefix like cuda12- for pytorch-notebook or just cuda- for tensorflow-notebook) to the image tag to allow PyTorch or TensorFlow operations to use compatible NVIDIA GPUs for accelerated computation. We only build pytorch-notebook for the last two major versions of CUDA. The tensorflow-notebook image only supports the latest CUDA version listed in the officially tested build configurations.

For example, you could use the image quay.io/jupyter/pytorch-notebook:cuda12-python-3.11.8 or quay.io/jupyter/tensorflow-notebook:cuda-latest.

Image Relationships#

The following diagram depicts the build dependency tree of the core images. (i.e., the FROM statements in their Dockerfiles). Any given image inherits the complete content of all ancestor images pointing to it.

Builds#

Every Monday and whenever a pull request is merged, images are rebuilt and pushed to the public container registry.

Versioning via image tags#

Whenever a docker image is pushed to the container registry, it is tagged with:

• the latest tag
• a 12-character git commit SHA like 1ffe43816ba9
• a date formatted like 2023-01-30
• OS version like ubuntu-22.04
• a set of software version tags like python-3.10.8 and lab-3.5.3

Warning

• Tags before 2022-07-05 were sometimes incorrect. Please, do not rely on them.
• Single-platform images have either aarch64- or x86_64- tag prefixes, for example, quay.io/jupyter/base-notebook:aarch64-python-3.11.6

For stability and reproducibility, you should either reference a date formatted tag from a date before the current date (in UTC) or a git commit SHA older than the latest git commit SHA in the default branch of thejupyter/docker-stacks GitHub repository.