Jlab extension for showing course levels and structure
Project description
jupyterlab_courselevels
JupyterLab extension to display cells in colors based on their intended audience level; the color codes follows the logic of ski tracks
- green : basic - all students should know that
- blue : intermediate - if you want to dig a little more
- red : advanced - for the geeks
in addition some cells may show up with a surrounding frame, to emphasize the course structure
Requirements
- JupyterLab >= 4.0.0
Install
To install the extension, execute:
pip install jupyterlab_courselevels
Uninstall
To remove the extension, execute:
pip uninstall jupyterlab_courselevels
misc commands
command | keybinding | comment |
---|---|---|
courselevels:toggle-basic |
Ctrl-\ Ctrl-X |
|
courselevels:toggle-intermediate |
Ctrl-\ Ctrl-Y |
|
courselevels:toggle-advanced |
Ctrl-\ Ctrl-Z |
|
courselevels:toggle-frame |
Ctrl-\ Ctrl-M |
|
courselevels:toggle-licence |
Ctrl-\ Ctrl-L |
|
convenience:metadata-clean-selected |
Alt-Cmd-7 |
clean metadata on selected cells |
convenience:metadata-clean-all |
Ctrl-Alt-7 |
clean metadata on all cells |
as well as for adding/removing an admonition around a cell
command | keybinding |
---|---|
courselevels:toggle-admonition |
Ctrl-\ Ctrl-A |
courselevels:toggle-admonition-tip |
Ctrl-\ Ctrl-T |
courselevels:toggle-admonition-note |
Ctrl-\ Ctrl-N |
courselevels:toggle-attention |
|
courselevels:toggle-caution |
|
courselevels:toggle-danger |
|
courselevels:toggle-error |
|
courselevels:toggle-hint |
|
courselevels:toggle-important |
|
courselevels:toggle-seealso |
|
courselevels:toggle-warning |
persistence
this is done by adding the following tags in each cell
level_basic
level_intermediate
level_advanced
framed_cell
rendering
for the record, in nb-courselevels - i.e. in the classic notebook - we had added e.g.
data-tag-basic=true
in the DOM element; here we rely on the jupyterlab-celltagsclasses
extension, which will instead set the cell-tag-level_basic
class, but it does not
matter that we don't use the same means here
Development
Development install
Note: You will need NodeJS to build the extension package.
The jlpm
command is JupyterLab's pinned version of
yarn that is installed with JupyterLab. You may use
yarn
or npm
in lieu of jlpm
below.
# Clone the repo to your local environment
# Change directory to the jupyterlab_courselevels directory
# Install package in development mode
pip install -e "."
# Link your development version of the extension with JupyterLab
jupyter labextension develop . --overwrite
# Rebuild extension Typescript source after making changes
jlpm build
You can watch the source directory and run JupyterLab at the same time in different terminals to watch for changes in the extension's source and automatically rebuild the extension.
# Watch the source directory in one terminal, automatically rebuilding when needed
jlpm watch
# Run JupyterLab in another terminal
jupyter lab
With the watch command running, every saved change will immediately be built locally and available in your running JupyterLab. Refresh JupyterLab to load the change in your browser (you may need to wait several seconds for the extension to be rebuilt).
By default, the jlpm build
command generates the source maps for this extension to make it easier to debug using the browser dev tools. To also generate source maps for the JupyterLab core extensions, you can run the following command:
jupyter lab build --minimize=False
Development uninstall
pip uninstall jupyterlab_courselevels
In development mode, you will also need to remove the symlink created by jupyter labextension develop
command. To find its location, you can run jupyter labextension list
to figure out where the labextensions
folder is located. Then you can remove the symlink named jupyterlab-courselevels
within that folder.
Packaging the extension
See RELEASE
Project details
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