Analytics Vidhya
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Analytics Vidhya

JupyterHub Docker

JupyterHub allows using the power of notebooks to groups of users. You will be able to create containers with JupyterHub and libraries such as Pandas, Scipy, matplotlib, and Dask for multi-users through a central server.

JupyterHub Docker is an image to create an environment with a JupyterHub Server to share the IT resources and notebook env with Teams or User Groups.

JupyterHub Docker will provide an environment with JupyterLab (Next-Generation Notebook Interface) for every user.

Creating the Container

$ docker pull rancavil/jupyterhub-docker
$ docker run -d --name <your-container-name> -p 8000:8000 rancavil/jupyterhub-docker

You have to set up <your-container-name>.

You can check using the following:

CONTAINER ID        IMAGE                        COMMAND                  CREATED             STATUS              PORTS                    NAMES
ef7a357fbf58 rancavil/jupyterhub-docker "jupyterhub --ip=0.0." 24 seconds ago Up 3 seconds 0.0.0.0:8000->8000/tcp <your-container-name>

Go to your browser:

http://<server-name-or-ip>:8000

You have to use your own <server-name-or-ip>.

Now, you can go in using the following credentials

username: admin
password: change.it!

Important: You must change the password default.

How you’ll see, we access to JupyterLab environment.

Important: You must change the default password using the Terminal option (go to File -> New -> Terminal) or go to the icon:

And use the Linux command passwd inside the terminal:

You must put the current password (change.it!), and enter your new password. Once the password has been changed, just close the terminal window using the cross.

All users for JupyterHub are Linux users created inside the container. To create new users got to JupyterHub Docker, how to add new users.

Now, you’re ready to use JupyterLab in a central environment JupyterHub.

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Rodrigo Ancavil

Rodrigo Ancavil

IT Architect and Software Engineer

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