See the CUDA-based Julia docker stack for GPU accelerated docker images. |
---|
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.
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:
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.PATCH
≥ 1.7.3
.
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
PRs accepted.
This project follows the Contributor Covenant Code of Conduct.
Community support: Open a new discussion here.
Commercial support: Contact b-data by email.
Copyright © 2020 b-data GmbH
Distributed under the terms of the MIT License.