Dashboards#
QHub encourages users to create 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 purpose enough to support any web app. 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 dashboard-based solutions, for example Voila, the instructions will be
slightly different, in which case we recommend visiting the
cds docs. Visit your hub homepage which is at
https://<qhub-url>/hub/dashboards or click the dashboard tab in the hub home menu.
Click 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 saved the dashboard, you will be taken to the screen to select the resources the dashboard will have available to it.
Once the resources have been chosen, click save and 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
https://training.qhub.dev/user/costrouchov@quansight.com/dash-my-awesome-dashboard/, but your url will be different.
The url will force authentication for the user to view the dashboard. The dashboard for the notebook in this example is
shown below.
