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jupyter/docker-stacks

Ready-to-run Docker images bundling JupyterLab, Jupyter Notebook and common scientific Python tools for personal or team use.

Open-source alternative to:Google Colab

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What is it?

Jupyter Docker Stacks is a set of prebuilt Docker images that package Jupyter applications and interactive computing tools. Each image is published on Quay.io and can be pulled and started with a single docker run command, which launches a Jupyter Server with the JupyterLab frontend on a mapped host port.

The images come in several variants, such as base-notebook, scipy-notebook and datascience-notebook, each adding a different set of libraries on top of a common base. Images are built for both x86_64 and aarch64, and some variants include CUDA-enabled builds of PyTorch and TensorFlow. Users can mount a local directory into the container to keep their work on the host, or use the images as a base for their own project Dockerfiles and for JupyterHub deployments.

Key features

  • 01Prebuilt images published on Quay.io for x86_64 and aarch64
  • 02JupyterLab is the default frontend, with Jupyter Notebook available by environment variable
  • 03Multiple variants with scientific and data science libraries preinstalled
  • 04CUDA-enabled PyTorch and TensorFlow images for supported platforms
  • 05Local directories can be mounted into the container to persist work

Use cases

  • Starting a personal JupyterLab environment with one Docker command
  • Running JupyterHub so a team shares a consistent notebook setup
  • Using a stack image as the base for a project-specific Dockerfile
  • Trying out notebook-based data analysis without installing Python locally

Quick start

  1. 1

    Install Docker (get Docker from the Docker docs)

  2. 2

    Start a JupyterLab server with the scipy-notebook image

    docker run -p 10000:8888 quay.io/jupyter/scipy-notebook:2026-07-28
  3. 3

    Open the URL with the printed token in your browser

Things to know

  • Requires Docker to be installed and running.
  • Images are only published to Quay.io since 2023-10-20; older Docker Hub images are no longer updated.
  • Images are large because they bundle many scientific Python tools.

In collections

Data science courses & tools

Topics

#jupyter#docker#jupyterlab#python#notebook#data-science#ipython#ipython-notebook#jupyter-notebook#jupyter-notebooks

FAQ

What is docker-stacks?
Ready-to-run Docker images bundling JupyterLab, Jupyter Notebook and common scientific Python tools for personal or team use. Jupyter Docker Stacks is a set of prebuilt Docker images that package Jupyter applications and interactive computing tools. Each image is published on Quay.io and can be pulled and started with a single docker run command, which launches a Jupyter Server with the JupyterLab frontend on a mapped host port.
Is docker-stacks free to use? What license does it have?
docker-stacks is open source under the BSD-3-Clause license. Check the license terms before using it in commercial products.
Is docker-stacks still maintained?
Actively maintained. The last commit to docker-stacks was on Nov 3, 2026.
What can I use docker-stacks for?
Starting a personal JupyterLab environment with one Docker command Running JupyterHub so a team shares a consistent notebook setup Using a stack image as the base for a project-specific Dockerfile Trying out notebook-based data analysis without installing Python locally
How do I install docker-stacks?
Install Docker (get Docker from the Docker docs) Start a JupyterLab server with the scipy-notebook image: docker run -p 10000:8888 quay.io/jupyter/scipy-notebook:2026-07-28 Open the URL with the printed token in your browser
Where can I get docker-stacks?
The source code and installation instructions are on GitHub: https://github.com/jupyter/docker-stacks

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