Goals:
Walk through a options within a Jupyter Notebook session
Initial Screen Navigation and Options
Upon connecting, you are presented with a simple Jupyter Notebook screen and just a few options:
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Drop-Down Menu Bar
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Active Work Area
Whatever you’re currently working on
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Opening a New Blank Notebook
From the Dropdown: File->New->Notebook | |
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From the Right side of the File Management Tab: New->Notebook |
Kernels
A Jupyter kernel is the computational engine behind the code execution in Jupyter notebooks.
Most users think of this as the “compiler” or programming language used when running code cells.
The Kernel empowers you to execute code in different programming languages like Python, R, or Julia or others and instantly view the outcomes within the notebook interface.
After opening a new notebook, you will be prompted to select a kernel
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Default Kernels on ARCC HPC Resources include:
HPC-wide kernels are titled by packages installed and available when launched Users can also create user-defined kernels from conda environments (Covered in a subsequent module. See Creating Jupyter Kernels from Conda Environments) |
Running a Jupyter Notebook with Python 3 Kernel
If we select the default Python 3 (ipykernel), we are presented with the file explorer showing our home directory as it’s root location.
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What Packages are Available in our Kernel?
In our notebook, we can provide a python command, to list available packages: Click on the package list image to the right to see output |