User environment and interface

When your users log in to their hub, they are presented with a configured environment with base libraries, user interfaces and languages installed. This allows them to start working immediately, without having to install packages themselves.

Customize your user environment

While all hubs come with a default environment, it is possible to create a custom user environment for the hub. Here are a few ways that you can do this.

Create your own docker image

Our hubs use docker images to provide the user environment. You can build and bring your own docker image, which gives you full control over your user environment.

In order to do this, we need to define an environment in a repository, generate a Docker image from that environment, push the Docker image to an image registry, and tell your JupyterHub to pull from that registry. See the sections below for more detail.

A quick overview

We recommend using the repo2docker tool to define and build your user environment. This is the tool used by the Binder project, and is a good standard to follow for defining clear and reproducible computational environments.

To use repo2docker to build user environments for your hub, you’ll need to:

  1. Create a repository that hosts the files that will define your environment.

  2. Add files in the repository that define your user environment. Here are a few good resources for defining these files:

  3. Create a Docker image registry account. This will be the place where you store user images once they are built, so that the hub can access them.

    Tip

    We recommend using the quay.io image registry for your Docker images. This is a public registry service run by Red Hat, and is reliable to use.

  4. Set up a GitHub Action to automatically build a Docker image using the repo2docker action, and push it to a registry.

  5. Configure your hub to pull the user image from the registry above, either via the configurator (to do it yourself) or by opening a support ticket (to request that a 2i2c engineer do this for you).

Tip

By following these steps, you have also created a Binder-ready repository, and we recommend trying to build your reposity on mybinder.org in order to test things out.

An in-depth guide

To help you get started, we’ve created an environment generation guide and a small template repository that will guide you through the process. Go to the repository by clicking the button below, and follow the instructions in the README for next steps.

Go to user environment template

Temporarily install packages for a session

You can temporarily install packages in your environment that will just last the duration of your user session. They will get wiped out when your user server is stopped, to ensure that you always start from the ‘default’ environment.

The recommended way is to put %pip install <list-of-packages> or %conda install <list-of-packages> in the first cell of any notebook you distribute, so when run it’ll install necessary packages. For R, you can use install.packages("package-name") as you normally would.

Warning

While tempting, do not use !pip install --user <packages> to install packages. This makes the base environment different for different users, causing hard-to debug-issues. This could also render your user server unable to start, due to conflicting packages. See this blog post on using pip in Jupyter for some helpful explanation.

Create multiple environments for users to select

If your hub’s community has workflows that differ significantly, it can be useful to create multiple user environments for your hub. This uses Jupyter Hub User Profiles to create a menu of environment options when a user launches a new session.

To add multiple environments for your hub, take these steps:

  1. Follow the steps in Create your own docker image for each environment you wish to offer your hub’s users. You should have one repository per environment, and each one should push to a Docker image registry via the repo2docker action.

  2. Open a support request requesting that your hub be set up to serve multiple user environments. A 2i2c engineer will assist you in configuring the hub to set up multiple environments.

The default user environment

The default environment for all community hubs is defined in this folder. It is configured with the following:

Default user interfaces

The 2i2c hubs offer the following user interfaces by default:

Jupyter Notebook (Classic)

The original single-document interface for creating Jupyter Notebooks.

JupyterLab

JupyterLab layout

JupyterLab is a more modern version of the classic Jupyter notebook from the Jupyter project. It is more customizable and better supports advanced use cases - particularly around dask. Many research organizations use this.

RStudio

RStudio

RStudio is an IDE for R, created by the RStudio company.

Ask for changes to the default environmen

If you are using the default environment, and think that one or two packages should be installed by default on it, please send a support request and request an update to the default environment.

Accessing user interfaces

There are three main interfaces available on the 2i2c JupyterHubs. There are a few different ways that you may encourage users to switch between them.

by changing your URL

You may switch between user interfaces interactively by altering the URL of your session. For example, here is the general structure of a URL for your personal 2i2c JupyterHub session:

https://<your-hub>.pilot.2i2c.cloud/user/<your-username>/<your-interface>

You can replace the contents of <your-interface> to be one of the following:

  • JupyterLab: /lab

  • Jupyter Notebook: /tree

  • RStudio: /rstudio

by changing the hub defaults

A Hub Administrator can also configure the default interface that users see. To do so, see the configurator interface guide.