QHub supports user’s creating dashboards that can be shared with other users and groups via ContainDS Dashboards. Currently this dashboarding solution supports Panel, Bokeh, Voila, Streamlit, and Plotly. The solution is general enough to support any webapp. For a more detailed guide on using CDSDashboards see the documentation.
Create a notebook in your jupyterlab environment with the following
code in a notebook named
mydashboard.ipynb in the home directory.
import panel panel.extension() content = panel.pane.Markdown(''' # Hello World This is some content ''') png = panel.panel('https://upload.wikimedia.org/wikipedia/commons/4/47/PNG_transparency_demonstration_1.png', width=300) widget = panel.widgets.TextInput(name='A widget', value='A string') dashboard = panel.Row(content, png, widget) dashboard.servable()
Once you execute the notebook you should see the output shown
above. We will now show how to create a dashboard from this
notebook. Keep in mind that for other dashboarding solutions
e.g. voila the instructions will be slightly different in which case
we recommend visiting the cds
your hub homepage which is at
click the dashboard tab in the hub home menu.
New Dashboard and give the dashboard any name and
description. For now allow
all users and use the
jupyter tree. Note that
bokeh was selected for the framework since panel
uses bokeh under the covers. Choose the conda environment
dashboard. Finally supply a relative path to the dashboard you would
like to launch. In this case
./mydashboard.ipynb since this is the
name of the dashboard created above in the notebook.
Once you have chosen the dashboard you show you will need to then select the resources the dashboard will have available to it.
Once the resources have been chosen the dashboard will launch. This
should provide a dedicated url that you can share with other QHub
users to view the dashboard. In the case of this dashboard the url was
your url will be different. The url will force authentication for the
user to view the dashboard.