If you want to use any of these extensions, feel free to use our examples as a starting point.
You can list the currently installed extensions by running the command in the JupyterLab terminal: jupyter labextension list
!jupyter labextension list
JupyterLab v2.1.4 Known labextensions: app dir: /gpfs/software/juwels/stages/Devel-2019a/software/Jupyter/2019a.2-gcccoremkl-8.3.0-2019.3.199-Python-3.6.8/share/jupyter/lab @bokeh/jupyter_bokeh v2.0.2 enabled OK @jupyter-voila/jupyterlab-preview v1.1.0 enabled OK @jupyter-widgets/jupyterlab-manager v2.0.0 enabled OK @jupyter-widgets/jupyterlab-sidecar v0.5.0 enabled OK @jupyterlab/git v0.20.0 enabled OK @jupyterlab/server-proxy v2.1.0 enabled OK @jupyterlab/toc v4.0.0 enabled OK @krassowski/jupyterlab-lsp v1.0.0 enabled OK @krassowski/jupyterlab_go_to_definition v1.0.0 enabled OK @parente/jupyterlab-quickopen v0.5.0 enabled OK @pyviz/jupyterlab_pyviz v1.0.4 enabled OK @ryantam626/jupyterlab_code_formatter v1.3.1 enabled OK bqplot v0.5.12 enabled OK dask-labextension v2.0.2 enabled OK ipyvolume v0.6.0-alpha.5 enabled OK itkwidgets v0.27.0 enabled OK jupyter-leaflet v0.13.0 enabled OK jupyter-matplotlib v0.7.2 enabled OK jupyter-threejs v2.2.0 enabled OK jupyter-vue v1.3.2 enabled OK jupyter-vuetify v1.4.0 enabled OK jupyterlab-control v1.1.0 enabled OK jupyterlab-dash v0.2.0 enabled OK jupyterlab-datawidgets v6.3.0 enabled OK jupyterlab-gitlab v2.0.0 enabled OK jupyterlab-lmod v0.7.0 enabled OK jupyterlab-plotly v4.8.1 enabled OK jupyterlab-system-monitor v0.6.0 enabled OK jupyterlab-theme-toggle v0.5.0 enabled OK jupyterlab-topbar-extension v0.5.0 enabled OK jupyterlab_iframe v0.2.2 enabled OK nbdime-jupyterlab v2.0.0 enabled OK plotlywidget v4.8.1 enabled OK pvlink v0.3.1 enabled OK
An extension to manage Dask clusters, as well as embed Dask's dashboard plots directly into JupyterLab panes.
Watch this video until the end to unterstand how to use Dask in JupyterLab. At the moment we only offer to use the panels inside of JupyterLab.
We have introduction notebooks for this extensions here (or open the gitlab extension on the left sidebar).
A JupyterLab Git extension for version control using git.
A Table of Contents extension for JupyterLab. This auto-generates a table of contents in the left area when you have a notebook or markdown document open.
The entries are clickable, and scroll the document to the heading in question.
A Python / ThreeJS bridge utilizing the Jupyter widget infrastructure.
The Jupyterlab Leaflet extension enables interactive maps.
You can find several example notebooks here.
A sidecar output widget for JupyterLab
Voilà turns Jupyter notebooks into standalone web applications.
Unlike the usual HTML-converted notebooks, each user connecting to the Voilà tornado application gets a dedicated Jupyter kernel which can execute the callbacks to changes in Jupyter interactive widgets.
This extension allows you to render a Notebook with Voilà, so you can see how your Notebook will look with it.
You can download a test notebook with the following command:
$ wget --no-check-certificate https://jupyter-jsc.fz-juelich.de/static/files/voila_basics.ipynb
and get a preview of it with the button at the top of your notebook.
Quick Open allows you to quickly open a file in JupyterLab by typing part of its name. Just click on the lens symbol at the left sidebar.
Takes a long time on HPC systems.
The LaTeX Extension is an extension for JupyterLab which allows for live-editing of LaTeX documents.
Here you can find a short example.
This is a small Jupyterlab plugin to support using various code formatter on the server side and format code cells/files in Jupyterlab.
Please read the documentation.
3d plotting for Python in the Jupyter notebook based on IPython widgets using WebGL. Please read the documentation.
Jupyter interactive notebook server extension that allows user to interact with environment modules before launching kernels.
The extension use Lmod's Python interface to accomplish module related task like loading, unloading, saving collection, etc.
Leveraging the Jupyter interactive widgets framework, ipympl enables the interactive features of matplotlib in the Jupyter notebook and in JupyterLab.
Besides, the figure canvas element is a proper Jupyter interactive widget which can be positioned in interactive widget layouts.
Please read the documentation.
Tools for diffing and merging of Jupyter notebooks.
Please read the documentation.
Plotly's Python graphing library makes interactive, publication-quality graphs. Examples of how to make line plots, scatter plots, area charts, bar charts, error bars, box plots, histograms, heatmaps, subplots, multiple-axes, polar charts, and bubble charts.
Please read the documentation.