benz0li
MModular
•Created by benz0li on 1/5/2025 in #community-showcase
Mojo dev container for standard library development
Multi-arch (
🔥 All prerequisites installed for Mojo standard library development. Parent image:
ℹ️ Runs on Apple M series using Docker Desktop[^1]. 1. Base image: Debian instead of Ubuntu 1. Just Python – no Conda / Mamba
linux/amd64, linux/arm64/v8) Mojo dev container.🔥 All prerequisites installed for Mojo standard library development. Parent image:
glcr.b-data.ch/mojo/base:nightly
👉 Open in GitHub Codespaces
ℹ️ For further information, see https://github.com/benz0li/mojo-dev-container
What makes this dev container different:
1. Multi-arch: linux/amd64, linux/arm64/v8ℹ️ Runs on Apple M series using Docker Desktop[^1]. 1. Base image: Debian instead of Ubuntu 1. Just Python – no Conda / Mamba
2 replies
MModular
•Created by benz0li on 1/5/2025 in #community-showcase
MAX/Mojo Data Science dev containers
Multi-arch (
ℹ️ Runs on Apple M series using Docker Desktop. 1. Base image: Debian instead of Ubuntu
ℹ️ CUDA-based images use Ubuntu. 1. IDE: JupyterLab next to VS Code 1. Just Python – no Conda / Mamba
linux/amd64, linux/arm64/v8) MAX/Mojo Data Science dev containers:
Parent images: MAX/Mojo docker stack
* CUDA MAX base
* CUDA MAX nightly base
* CUDA MAX scipy
* CUDA MAX nightly scipy
* MAX base
* MAX nightly base
* MAX scipy
* MAX nightly scipy
* Mojo base
* Mojo nightly base
* Mojo scipy
* Mojo nightly scipy
👉 Open in GitHub Codespaces
ℹ️ For further information, see https://github.com/b-data/data-science-devcontainers
What makes these dev containers different:
1. Multi-arch: linux/amd64, linux/arm64/v8ℹ️ Runs on Apple M series using Docker Desktop. 1. Base image: Debian instead of Ubuntu
ℹ️ CUDA-based images use Ubuntu. 1. IDE: JupyterLab next to VS Code 1. Just Python – no Conda / Mamba
2 replies
MModular
•Created by benz0li on 1/5/2025 in #community-showcase
(CUDA-based) JupyterLab MAX/Mojo docker stack
Multi-arch (
ℹ️ Runs on Apple M series using Docker Desktop. 1. Base image: Debian instead of Ubuntu
ℹ️ CUDA-based images use Ubuntu. 1. IDE: code-server next to JupyterLab
ℹ️ code-server =
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
ℹ️ For further information, see https://github.com/b-data/jupyterlab-mojo-docker-stack
What makes these images different from the modularml/mojo ones?
1. Multi-arch: linux/amd64, linux/arm64/v8ℹ️ Runs on Apple M series using Docker Desktop. 1. Base image: Debian instead of Ubuntu
ℹ️ CUDA-based images use Ubuntu. 1. IDE: code-server next to JupyterLab
ℹ️ code-server =
Code - OSS in the browser.
1. Just Python – no Conda / Mamba4 replies