Jupyter Hub
Other custom configuration
Use the File Manager to place custom configuration under /app/data/customconfig.py. See the docs for more information.
Extensions
It's possible to enable and install extensions. However, as note in Notebook persistence, the extensions installed using pip or conda are not part of the backup and thus they need to re-installed when the notebook image is changed.
Sharing
To share notebooks between users with a shared directory (/shared): Create /app/data/shared directory and make it accessible by all users. Open a JupyterHub Web Terminal. mkdir /app/data/shared chmod 0777 /app/data/shared Then, edit ...
Multiple user environments
By default, the app allows a user to create multiple environments. You can disable this by setting allow_named_servers to False in /app/data/customconfig.py. c.JupyterHub.allow_named_servers = False
Notebook persistence
All notebooks are part of the application backup and persisted across updates. Libraries installed using conda are not part of the backup and are part of the notebook container. Idle notebooks are shutdown over time but they are not destroyed. This ...
Notebook Memory limit
By default, notebooks are given 500M (including swap). This can be changed by editing /app/data/customconfig.py. c.Spawner.mem_limit = '1G' To apply the configuration, restart the app using the Restart button. Info: Remove existing notebook ...
Selecting a notebook image
By default, the app uses the jupyter/datascience-notebook. The upstream Jupyterhub project maintains many other notebook images. To use a different notebook image, use the File Manager to place custom configuration under /app/data/customconfig.py. ...
How it works
The JupyterHub app is run as a container (like any other DANIAN App). The hub app manages user login and creates a separate container for each user's notebooks. The notebook container is created from the c.DockerSpawner.image setting (see the other ...
How to order Jupyter Hub?
1. Login at: https://cloud.danian.co 2. Manage Apps - Add an App 3. Select: Jupyter Hub 4. Select vCPU / RAM If you don't know how much you will need to use, just leave the default. 5. Select Disk Storage Size If you don't know how much you will need ...