Dive into Jupyter Labs

Upon connecting, you are presented with the main Jupyter Labs screen and options:

• Drop down menu bar along the top

• Along the left is a collapsable sidebar

• Along the right is another sidebar

• Main work area in the center (Starts with Launcher tab opened)

• Along bottom is a information dock

Has top-level menus that expose actions available in JupyterLab with their keyboard shortcuts. The default menus are:

• File: actions related to files and folders

• Edit: actions related to editing documents and other activities

• View: actions that alter the appearance of JupyterLab

• Run: actions for running code in different activities such as notebooks and code consoles

• Kernel: actions for managing kernels, which are separate processes for running code

• Tabs: a list of the open documents and activities in the dock panel

• Settings: common settings and an advanced settings editor

• Help: a list of JupyterLab and kernel help links

JupyterLab extensions can also create new top-level menus in the menu bar.

Left Sidebar will have a number of default options upon launch.

• File Browser:

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• Run Manager:

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  • Contains a list of tabs in the main work and of running kernels and terminals

• Table of contents

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• Extension manager

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• Older versions may show a Command palette:

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  • provides an easy search and run for JupyterLab commands

  • Newer versions can access this from the View drop-down option or using the keyboard shortcut Command/Ctrl Shift C.

• Upon initial login, the main work area will show the JupyterLab Launcher in a tab.

• Users can launch lab applications in a new tab from the Launcher

  • Any kernels available on the cluster will show up as a kernel option in the launcher (Usually launchable as both a Notebook or Console)

  • Additional lab applications like terminal, file editors, and help menus will show up as options below under ‘Other’

• The main work area in JupyterLab allows users to arrange documents (notebooks, text files, etc.) and other activities (terminals, code consoles, etc.) into panels of tabs.

  • Tabs can be resized or subdivided.

  • Move a tab to a panel by dragging the tab to the center of a tab panel.

  • Subdivide a tab panel by dragging a tab to the left, right, top, or bottom of the panel.

Why run your code in a console instead of a notebook?

• Jupyter Notebooks run code in a linear fashion, based on the explicit linear order according to the cell’s placement in the notebook.

• There are positives and negatives associated with running the cells linearly:

  • Positives:

    • Helpful because it makes the logic of the code, and project easier to understand and visualize in a step-by-step manner.

    • Understanding the origins and processes associated with data collection, computational processes, and output become more straightforward.

  • Negatives:

    • Notebooks do NOT allow code to run functions simultaneously, even when the code natively handles it.

    • Notebooks also do NOT allow code to run based on decisions or conditional statements (such as if, if/else, or switch/case statements)

• Code consoles allow you to run code interactively in a kernel. The cells of a code console show the order in which code was executed in the kernel, as opposed to the explicit ordering of cells in a notebook document. Code consoles also display rich output, just like notebook cells.