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(GPU accelerated) Multi-arch (linux/amd64, linux/arm64/v8) Julia docker images. Please submit Pull Requests to the GitLab repository. Mirror of

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minimal-readme compliant Project Status: Active – The project has reached a stable, usable state and is being actively developed. Donate using Liberapay

See the CUDA-based Julia docker stack for GPU accelerated docker images.

Julia docker stack

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

Images considered stable for Julia versions ≥ 1.7.3.
👉 The current state may eventually be backported to versions ≥ 1.5.4.

Build chain

ver → base → pubtools

Features

glcr.b-data.ch/julia/ver serves as parent image for glcr.b-data.ch/jupyterlab/julia/base.

The other images are counterparts to the JupyterLab images but without

  • code-server
  • IJulia
  • JupyterHub
  • JupyterLab
    • JupyterLab Extensions
    • JupyterLab Integrations
  • Jupyter Notebook
    • Jupyter Notebook Conversion
  • LSP Servers
  • Oh My Zsh
    • Powerlevel10k Theme
    • MesloLGS NF Font

and any configuration thereof.

Table of Contents

Prerequisites

This projects requires an installation of docker.

Install

To install docker, follow the instructions for your platform:

Usage

Build image (ver)

latest:

docker build \
  --build-arg JULIA_VERSION=1.11.1 \
  --build-arg PYTHON_VERSION=3.12.7 \
  -t julia/ver \
  -f ver/latest.Dockerfile .

version:

docker build \
  -t julia/ver:MAJOR.MINOR.PATCH \
  -f ver/MAJOR.MINOR.PATCH.Dockerfile .

For MAJOR.MINOR.PATCH1.7.3.

Run container

self built:

docker run -it --rm julia/ver[:MAJOR.MINOR.PATCH]

from the project's GitLab Container Registries:

docker run -it --rm \
  IMAGE[:MAJOR[.MINOR[.PATCH]]]

IMAGE being one of

Contributing

PRs accepted.

This project follows the Contributor Covenant Code of Conduct.

Support

Community support: Open a new discussion here.

Commercial support: Contact b-data by email.

License

Copyright © 2020 b-data GmbH

Distributed under the terms of the MIT License.