Spreadsheet in the Jupyter notebook:
- Try it out using binder:
- Or check out the documentation at https://ipysheet.readthedocs.io/
Create a table and drive a value using ipywidgets:
Perform a calculation on slider change:
Change cell style depending on the value using renderers:
Populate table using cell ranges:
$ conda install -c conda-forge ipysheet
$ pip install ipysheet
Note: You will need NodeJS to build the extension package.
jlpm command is JupyterLab's pinned version of
yarn that is installed with JupyterLab. You may use
npm in lieu of
# Clone the repo to your local environment # Change directory to the ipysheet 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 run 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 run 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 run 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
pip uninstall ipysheet
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
folder is located. Then you can remove the symlink named
ipysheet within that folder.