Guided, interactive workshops inside JupyterLab.
Teaching in JupyterLab usually means a notebook with explanation between the code cells. Learners read down it pressing Run, everything has to be a cell in one language, and nothing can tell whether a step was done. This extension separates the instructions from the work: they live in a side panel, one page at a time, and each step is a clickable action that does something real in the JupyterLab session beside it, in a terminal, the editor, a notebook, a kernel or the interface itself. Workshops can check what the learner has done, ask questions, collect values, hold pages until requirements are met, and snapshot the working directory, and the subject can be anything JupyterLab can host, including JupyterLab itself.
A workshop is a directory with a workshop.yaml manifest and Markdown
pages. The format is text based and git friendly. A workshop runs
wherever JupyterLab runs, and can be handed to learners through a
published collection, a Binder link, or a static JupyterLite site that
runs entirely in the browser.
The package is a prebuilt JupyterLab 4 extension with its server
extension, installed into a virtual environment alongside JupyterLab
with uv add jupyterlab jupyterlab-workshop or the pip equivalent, or,
to run workshops without a project of your own, as a tool with
uv tool install "jupyterlab-workshop[lab]" and then
jupyter-workshop launch --root ~/training --collection <url>.
Getting started
walks through the setup, runs an example workshop and scaffolds one of
your own; the jupyter workshop command that comes with the package
lints, self-tests and publishes workshops, and author mode in JupyterLab
edits them in place.
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Launch the showcase on Binder: three short workshops that show what the extension does and why, in a full JupyterLab with a real terminal, from the showcase repository that is also the pattern for publishing a collection of your own. Or try the demo: the Hello JupyterLab example running in JupyterLite, started afresh on every visit.
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How workshops work and the tutorial, which writes a small workshop from nothing and publishes it.
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Using workshops for learners and Deploying workshops for Binder, JupyterHub and locked-down images.
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The documentation for the rest: every action a page can use, checks and forms, variables, layouts, platforms, JupyterLite, publishing, trust, the manifest and settings references, the command line and authoring in JupyterLab.
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Source, issues and contributing: see
CONTRIBUTING.mdin the repository for the development setup.
This package was developed with the help of AI coding assistants, working to the author's design and direction, with the author reviewing what they produce. If you would rather not use software produced that way, that is understood, and this package is not for you.
Apache License 2.0.