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ipydatatable
Advanced tools
Library to wrap interactive datatables js into a library that helps pandas dataframes
A Custom Jupyter Widget Library
You can install using pip:
pip install ipydatatable
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] ipydatatable
Create a dev environment:
conda create -n ipydatatable-dev -c conda-forge nodejs python jupyterlab=4.0.11
conda activate ipydatatable-dev
Install the python. This will also build the TS package.
pip install -e ".[test, examples]"
When developing your 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 ipydatatable
jupyter nbextension enable --sys-prefix --py ipydatatable
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.
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.
If you make a change to the python code then you will need to restart the notebook kernel to have it take effect.
To update the version, install tbump and use it to bump the version. By default it will also create a tag.
pip install tbump
tbump <new-version>
FAQs
Library to wrap interactive datatables js into a library that helps pandas dataframes
We found that ipydatatable demonstrated a not healthy version release cadence and project activity because the last version was released a year ago. It has 1 open source maintainer collaborating on the project.
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