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A demo of JupyterLab Rich Context Extensions
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Demos the Rich Context work on JupyterLab, by building together the databus, metadata, and commenting features with some sample data and notebooks.

This uses repo2docker to create a Dockerfile, build it, and start it up:

python3 -m pip install jupyter-repo2docker
# Mount only `src` directory so we don't clobber `build` directory with built files.
jupyter-repo2docker -v "$PWD/src:/home/$USER/src" .

Now you can edit any files in the src directory in JupyterLab and those edits will be reflected in your host directory.


Q: How do I collaborate with someone else on Binder so we share the same comment service? A: You have to share a link to your running Binder with your private token included.

Q: Why use repo2docker instead of a Dockerfile? A: We want it to be able to run on Binder so we need to make sure it works with their workflow. It's better to have one tool to run local and hosted usage so that we only need to make things work once.

Q: Shouldn't we check in the dependencies into this repo with submodules or subtree? A: Possibly... It is simpler just to clone in the binder/postBuild, but if we included it in the repo then it wouldn't have to be re-cloned on every build (better caching).

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