JupyterLab Quick Tips

Derek Caetano-Anolles
  • Updated

JupyterLab is very powerful once you are familiar with the basics, but it also offers lots of additional benefit once you see what else is possible. Here are some shortcuts and helpful hints when using JupyterLab in Terra on Azure.

JupyterLab tips and tricks

The following are some quick tips to help get you better familiarized with JupyterLab.

  • You can open notebook files by double-clicking on the file name on the left-hand side. Note that you can also open multiple notebooks at once! Once you open a notebook file, you will be asked to select a kernel.

  • The Launcher tab (image below) can be used to create a new notebook file by clicking on any of the different kernel options under the “Notebook” section. You can also launch a terminal window from the Launcher tab by selecting the terminal icon under the “Other” section.
    An image of the Launcher Tab in Terra. There are many different options for Notebooks, Consoles, or other files available, with a mixture of Julia, Python, Markdown, and R files, including others.

  • To open a new Launcher window, click on File → New Launcher.

  • The JupyterLab interface includes a directory and file management section on the left-hand side of the screen. You can also create new folders and files, rename files, and drag-and-drop from this section as well.

  • All notebook (.ipynb ) files are synced between your VM storage disk (/home directory) and the workspace storage container.

If  .ipynb  files are moved out of  /home, they will stop syncing.

  • File syncing automatically occurs every 30 seconds. You can also save your files manually by clicking on File → Save, and by clicking on the floppy disk icon to “Save and create checkpoint”.

  • At any time, you can update your VM configuration and storage from the right-hand side panel under the JupyterLab icon.

Accessing DRS URIs in a notebook (AnVIL users)

Note that resolving AnVIL DRS URIs with terra-notebook-utils requires Python 3.10, which is not currently included by default. For step-by-step instructions to specify Python 3.10 instead of allowing the default when creating your JupyterLab virtual cloud environment, see How to add Python 3.10 to your JupyterLab kernel

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