Multi-arch (linux/amd64, linux/arm64/v8) docker images:

• glcr.b-data.ch/jupyterlab/max/base
• glcr.b-data.ch/jupyterlab/max/scipy
• glcr.b-data.ch/jupyterlab/mojo/base
• glcr.b-data.ch/jupyterlab/mojo/scipy

Images considered stable for Mojo versions ≥ 24.3.0.

🔬 Check out jupyterlab/mojo/scipy at https://demo.jupyter.b-data.ch.

Build chain

base → scipy

Features

• JupyterLab: A web-based interactive development environment for Jupyter notebooks, code, and data. The images include
  • code-server: Code - OSS in the browser.
  • Git: A distributed version-control system for tracking changes in source code.
  • Git LFS: A Git extension for versioning large files.
  • MAX: A high-performance generative AI framework.
  • Mojo: A programming language for AI developers.
  • Neovim: Vim-fork focused on extensibility and usability. (24.4.0+)
  • Pandoc: A universal markup converter.
  • Python: An interpreted, object-oriented, high-level programming language with dynamic semantics.
  • Quarto: A scientific and technical publishing system built on Pandoc.
    ℹ️ scipy image
  • TinyTeX: A lightweight, cross-platform, portable, and easy-to-maintain LaTeX distribution based on TeX Live.
    ℹ️ scipy image
  • Zsh: A shell designed for interactive use, although it is also a powerful scripting language.

👉 See the Version Matrix for detailed information.

ℹ️ Regading Magic, see [(JupyterLab) MAX/Mojo docker stack] Why is Magic not installed?

The following extensions are pre-installed for code-server:

• .gitignore Generator
• Black Formatter
  ℹ️ devtools subtags
• Docker
  ℹ️ docker subtags
• EditorConfig
• ESLint
  ℹ️ devtools subtags
• Git Graph
• GitHub Pull Requests and Issues
• GitLab Workflow
• GitLens — Git supercharged
  ℹ️ Pinned to version 11.7.0 due to unsolicited AI content
• Excel Viewer
• hadolint
  ℹ️ docker subtags
• Jupyter
• LaTeX Workshop
  ℹ️ scipy image
• markdownlint
• Mojo
• Path Intellisense
• Prettier - Code formatter
  ℹ️ devtools subtags
• Project Manager
• Python
• Quarto
  ℹ️ scipy image
• Resource Monitor
• ShellCheck
  ℹ️ devtools and docker subtags
• YAML

Subtags

• {MOJO_VERSION,latest}-root: Container runs as root
• {MOJO_VERSION,latest}-devtools: Includes the requirements according to
  • coder/code-server > Docs > Contributing
  • microsoft/vscode-python > Wiki > Coding
• {MOJO_VERSION,latest}-devtools-root: The combination of both
• {MOJO_VERSION,latest}-docker: Includes
  • docker-ce-cli
  • docker-buildx-plugin
  • docker-compose-plugin
  • docker-scan-plugin (amd64 only)
• {MOJO_VERSION,latest}-docker-root: The combination of both
• {MOJO_VERSION,latest}-devtools-docker: The combination of both
• {MOJO_VERSION,latest}-devtools-docker-root: The combination of all three

ℹ️ See also Notes on subtag devtools.

• Prerequisites
• Install
• Usage
• Misc
• Similar projects
• Contributing
• Support
• License

This projects requires an installation of docker.

To install docker, follow the instructions for your platform:

• Install Docker Engine | Docker Documentation > Supported platforms
• Post-installation steps for Linux

latest:

cd base && docker build \
  --build-arg MOJO_VERSION=24.6.0 \
  --build-arg PYTHON_VERSION=3.12.8 \
  -t jupyterlab/mojo/base \
  -f latest.Dockerfile .

version:

cd base && docker build \
  -t jupyterlab/mojo/base:MAJOR.MINOR.PATCH \
  -f MAJOR.MINOR.PATCH.Dockerfile .

For MAJOR.MINOR.PATCH ≥ 24.3.0.

Create an empty directory using docker:

docker run --rm \
  -v "${PWD}/jupyterlab-jovyan":/dummy \
  alpine chown 1000:100 /dummy

It will be bind mounted as the JupyterLab user's home directory and automatically populated.

self built:

docker run -it --rm \
  -p 8888:8888 \
  -u root \
  -v "${PWD}/jupyterlab-jovyan":/home/jovyan \
  -e NB_UID=$(id -u) \
  -e NB_GID=$(id -g) \
  jupyterlab/mojo/base[:MAJOR.MINOR.PATCH]

from the project's GitLab Container Registries:

docker run -it --rm \
  -p 8888:8888 \
  -u root \
  -v "${PWD}/jupyterlab-jovyan":/home/jovyan \
  -e NB_UID=$(id -u) \
  -e NB_GID=$(id -g) \
  IMAGE[:MAJOR[.MINOR[.PATCH]]]

IMAGE being one of

• glcr.b-data.ch/jupyterlab/max/base
• glcr.b-data.ch/jupyterlab/max/scipy
• glcr.b-data.ch/jupyterlab/mojo/base
• glcr.b-data.ch/jupyterlab/mojo/scipy

The use of the -v flag in the command mounts the empty directory on the host (${PWD}/jupyterlab-jovyan in the command) as /home/jovyan in the container.

-e NB_UID=$(id -u) -e NB_GID=$(id -g) instructs the startup script to switch the user ID and the primary group ID of ${NB_USER} to the user and group ID of the one executing the command.

The server logs appear in the terminal.

Create an empty home directory:

mkdir "${PWD}/jupyterlab-root"

Use the following command to run the container as root:

podman run -it --rm \
  -p 8888:8888 \
  -u root \
  -v "${PWD}/jupyterlab-root":/home/root \
  -e NB_USER=root \
  -e NB_UID=0 \
  -e NB_GID=0 \
  -e NOTEBOOK_ARGS="--allow-root" \
  IMAGE[:MAJOR[.MINOR[.PATCH]]]

Creating a home directory might not be required. Also

docker run -it --rm \
  -p 8888:8888 \
  -v "${PWD}/jupyterlab-jovyan":/home/jovyan \
  IMAGE[:MAJOR[.MINOR[.PATCH]]]

might be sufficient.

To add a JupyterLab Launcher icon for marimo:

1. Terminal: Install marimo and click

   pip install marimo click

2. Terminal: Install jupyter-marimo-proxy

   pip install git+https://github.com/b-data/jupyter-marimo-proxy.git@jupyterlab-docker-stack

3. Restart the container

• modularml/mojo

What makes this project different:

1. Multi-arch: linux/amd64, linux/arm64/v8
   ℹ️ Runs on Apple M series using Docker Desktop.
2. Base image: Debian instead of Ubuntu
   ℹ️ Upcoming: CUDA-based images use Ubuntu.
3. IDE: code-server next to JupyterLab
   ℹ️ code-server = Code - OSS in the browser.
4. Just Python – no Conda / Mamba

See Notes for tweaks, settings, etc.

PRs accepted. Please submit to the GitLab repository.

This project follows the Contributor Covenant Code of Conduct.

Community support: Open a new discussion here. Commercial support: Contact b-data by email.

b-data tailors the JupyterLab images to your needs, e.g.

• Integration of self-signed CA certificates to enable communication with web services on the intranet.
• Setting up the necessary environment variables so that everything works behind a corporate proxy server.

Additionally, the JupyterHub setup can be customised to allow

• authentication with AD/LDAP
• mounting CIFS/SMB file shares

and much more.

Copyright © 2024 b-data GmbH

Distributed under the terms of the MIT License, with exceptions.