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===== Jupyter =====

The School of Computer Science Jupyter server is available at https://jupyter.socs.uoguelph.ca, and is available to all SoCS students, faculty and staff. This page contains information on SoCS specific Jupyter information, including logging in, and our specific environments. For details on how to use Jupyter, please view the [[https://jupyterlab.readthedocs.io/en/latest/getting_started/overview.html|Jupyter Documentation]].

==== How to Start ====

===Logging In===
To begin, point your web browser at https://jupyter.socs.uoguelph.ca and log in with your UoG credentials.

{{:techsupport:services:jupyter_1_singin.png?400|}}

=== Choosing an Environment ===
After logging in, you will be prompted to choose an environment. Each environment contains a different set of software, tailored to specific needs. These environments are listed in more detail in the Jupyter Environments section below.

Choose your desired environment, and click Start

{{:techsupport:services:jupyter_2_serveroptions.png?400|}}

You are now logged into Jupyter and at the main menu.

==== Changing your Environment ====
If you need to change to a different environment, you will need to stop your server and start a new one.

{{:techsupport:services:jupyter_3_controlpanel.png?400|}}

==== Jupyter Environments ====
=== Minimal===
This is a basic Jupyter environment to support Python notebooks. Details of all installed utilities can be found in the [[https://jupyter-docker-stacks.readthedocs.io/en/latest/using/selecting.html#jupyter-minimal-notebook|Jupyter documentation]].

=== Datascience===
This Jupyer environment includes libraries for data analysis from the Julia, Python, and R communities. Details of installed utilites can be found in the [[https://jupyter-docker-stacks.readthedocs.io/en/latest/using/selecting.html#jupyter-datascience-notebook|Jupyter documentation]].

In addition, the following libraries have been added. 

  * TODO List of added libraries to go here

=== SoCS and Java ===

This environment includes the [[http://beakerx.com/|BeakerX]] collection of kernels and utilities. Included are, Python3, Clojure, Java and Kotlin. 

==== Adding Libraries ====
You can add additional libraries to your own notebooks using "pip install package", "conda install package" or "install.packages()" for R. By default these packages only persist as long as your Jupyter session. If you find yourself installing the same package often, contact help@socs.uoguelph.ca and we will get it added to the default environment.