jupyter-optmwidgets 0.1.4

Jupyter Widgets for DIVE virtual learning environment.

OPTM Widgets

Jupyter Widgets for DIVE virtual learning environment. The project aims to integrate interactive learning tools into jupyter notebook. E.g.,

• JSXGraph for interactive demonstration of Mathematics,
• mermaid and flowchart for drawing diagrams with domain-specific languages, and
• OPTLite for serverless visualization of python program execution.

Example notebooks can be found under the examples folder.

Installation

You can install using pip:

pip install optmwidgets

or conda:

conda install -c dive optmwidgets

or mamba:

mamba install -c dive optmwidgets

If you are using Jupyter Notebook 5.2 or earlier, you may also need to enable the nbextension:

jupyter nbextension enable --py [--sys-prefix|--user|--system] optmwidgets

Development Installation

Create a dev environment:

conda create -n optmwidgets-dev -c conda-forge nodejs python jupyterlab
conda activate optmwidgets-dev

Install the python. This will also build the TS package.

pip install -e ".[test, examples]"

When developing the extensions, you need to manually enable your extensions with the notebook / lab frontend. For lab, this is done by the command:

jupyter labextension develop --overwrite .
jlpm run build

For classic notebook, you need to run:

jupyter nbextension install --sys-prefix --symlink --overwrite --py optmwidgets
jupyter nbextension enable --sys-prefix --py optmwidgets

Note that the --symlink flag doesn't work on Windows, so you will here have to run the install command every time that you rebuild your extension. For certain installations you might also need another flag instead of --sys-prefix.

How to see your changes

Typescript:

If you use JupyterLab to develop then 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 widget.

# Watch the source directory in one terminal, automatically rebuilding when needed
jlpm run watch
# Run JupyterLab in another terminal
jupyter lab

After a change wait for the build to finish and then refresh your browser and the changes should take effect.

Python:

If you make a change to the python code then you will need to restart the notebook kernel to have it take effect.