Commit 35bdaca0 authored by Adam Caprez's avatar Adam Caprez
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Merge branch 'craneJupyter' into 'master'

Fixed Crane Link

See merge request !280
parents 1d28242c fe288bed
title = "Jupyter Notebooks"
description = "How to access and use a Jupyter Notebook"
weight = 20
hidden = "true"
- [Connecting to JupyterHub](#connecting-to-jupyterhub)
- [Running Code](#running-code)
- [Opening a Terminal](#opening-a-terminal)
- [Using Custom Packages](#using-custom-packages)
## Connecting to JupyterHub
Jupyter defines it's notebooks ("Jupyter Notebooks") as
an open-source web application that allows you to create and share documents that contain live code,
equations, visualizations and narrative text. Uses include: data cleaning and transformation, numerical simulation,
statistical modeling, data visualization, machine learning, and much more.
1. To open a Jupyter notebook, go to the address of the cluster, below [Crane]( will be used as an example, sign in using your hcc credentials (NOT your
campus credentials).
{{< figure src="/images/jupyterLogin.png" >}}
2. Select your preferred authentication method.
{{< figure src="/images/jupyterPush.png" >}}
3. Choose a job profile. Select "Noteboook via SLURM Job | Small (1 core, 4GB RAM, 8 hours)" for light tasks such as debugging or small-scale testing.
Select the other options based on your computing needs. Note that a SLURM Job will save to your "work" directory.
{{< figure src="/images/jupyterjob.png" >}}
## Running Code
1. Select the "New" dropdown menu and select the file type you want to create.
{{< figure src="/images/jupyterNew.png" >}}
2. A new tab will open, where you can enter your code. Run your code by selecting the "play" icon.
{{< figure src="/images/jupyterCode.png">}}
## Opening a Terminal
1. From your user home page, select "terminal" from the "New" drop-down menu.
{{< figure src="/images/jupyterTerminal.png">}}
2. A terminal opens in a new tab. You can enter [Linux commands]({{< relref "basic_linux_commands" >}})
at the prompt.
{{< figure src="/images/jupyterTerminal2.png">}}
## Using Custom Packages
Many popular `python` and `R` packages are already installed and available within Jupyter Notebooks.
However, it is possible to install custom packages to be used in notebooks by creating a custom Anaconda
Environment. Detailed information on how to create such an environment can be found at
[Using an Anaconda Environment in a Jupyter Notebook on Crane]({{< relref "/applications/user_software/using_anaconda_package_manager#using-an-anaconda-environment-in-a-jupyter-notebook-on-crane" >}}).
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