Jupyter datascience Dev Container template

🚀 Get started with a Jupyter datascience template

Usage

After creating a GitHub Codespace (or a devcontainer in VS Code), open the Command Palette to find the Dev Containers: Add Dev Container Configuration Files... command. After you run it, VS Code will guide you through the creation of a .devcontainer/devcontainer.json file!

Make sure you click the Show All Definitions... option to see our unofficial templates!

Choosing a base image

You can choose from many base images to tailor the container to your project's needs. If you don't know what this means, that's OK! Just choose the datascience-notebook option. It has many packages for data science from the Julia, Python, and R communities. 🚀

📚 You can learn more about what each of these base images is and what features each of them in the Jupyter Docker Stacks reference page.

Default command

The default command of the base image is set to start the Jupyter server. If you do not use the Jupyter server, comment out "overrideCommand": false of the devcontainer.json.

Credits

This template was originally created by @nathancarter and other contributors in the microsoft/vscode-dev-containers repository. It has since landed here. 🌠