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Jupyter.md

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  • title = "Jupyter Notebooks on Crane"
    description = "How to access and use a Jupyter Notebook"
    weight = 20
    • [Connecting to Crane] (#connecting-to-crane)
    • [Running Code] (#running-code)
    • [Opening a Terminal] (#opening-a-terminal)
    • [Using Custom Packages] (#using-custom-packages)

    Connecting to Crane


    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, Sign in to crane.unl.edu 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.