Start of our widget for Jupyter (this was built off the foundation of the repo https://github.com/cabreraalex/widget-svelte-example)
I had a little bit of trouble trying to get the initial project installed and running using standard Jupyter so I would reccommend following the JupyterLab installation instructions
Also I'm hoping to change the name of this repo/project soon, so I'll update the instructions in this Markdown file to match that soon.
You can install using pip
:
pip install widget_svelte_example
Or if you use jupyterlab:
pip install widget_svelte_example
jupyter labextension install @jupyter-widgets/jupyterlab-manager
I doubt that any of us have Jupyter Notebook 5.2 or earlier, but if anyone does you would likely need to enable the nbextension:
jupyter nbextension enable --py [--sys-prefix|--user|--system] widget_svelte_example
# First install the python package. This will also build the JS packages.
pip install -e .
We need to manually enable our extensions with the notebook / lab frontend:
jupyter labextension install @jupyter-widgets/jupyterlab-manager --no-build
jupyter labextension install .
For classic notebook, you can run, but again, I was unable to get this to work:
jupyter nbextension install --sys-prefix --symlink --overwrite --py widget_svelte_example
jupyter nbextension enable --sys-prefix --py widget_svelte_example
I'm not running on windows, but if you are these additional instructions were included:
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
, but we won't cover the meaning
of those flags here.
To continuously monitor the project for changes and automatically trigger a rebuild, start Jupyter in watch mode:
jupyter lab --watch
And in a separate session, begin watching the source directory for changes:
npm run watch
After a change wait for the build to finish and then refresh your browser and the changes should take effect.
If you make a change to the python code then you will need to restart the notebook kernel to have it take effect.
I've been using Conda to manage my python packages. In order to set this up, I followed the installation instructions for miniconda on: https://docs.conda.io/projects/conda/en/latest/user-guide/install/index.html.
I then created a new environment using:
conda create --name widget-env
This can be activated or deactivated using
conda activate widget-env
or
conda deactivate
Once this environment is set up, install libraries as follows:
conda install numpy
Hopefully this works! Let me know if something doesn't.