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Base Image Update

We've just updated our Base images with some big changes, including:

  • Python 3.8 is now the default Python version
  • R 4.0 is now the default R version
  • Jupyterlab 3 is now in use
  • The latest CUDA versions have been added

To update, simply restart your Client and the new images will automatically become available.

JupyterLab 3

JupyterLab 3 brings many improvements. Two interesting changes worth noting are the improved extension system and visual debugger.

JupyterLab 3 Bases now ship with 2 kernels. The standard Python kernel and the xeus-python kernel. The xeus-python kernel supports visual debugging, so it should be used when you wish to activate this feature.

An example showing how to activate the visual debugger in JupyterLab 3.An example showing how to activate the visual debugger in JupyterLab 3.

An example showing how to activate the visual debugger in JupyterLab 3.

JupyterLab extensions can now be distributed as prebuilt extensions, which do not require a user to rebuild JupyterLab or have Node.js installed. Extensions now can be directly distributed via a package manager like pip or conda and install much faster! Developers are still updating extensions to use this new system, but many are already supported. Double check the documentation for your extensions and it may be much easier to configure your Projects.

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Still need Python 3.7 or JupyterLab 2?

If you still need Python 3.7 or JupyterLab 2 for some reason, a new Base has been added titled (Legacy) Python 3.7 w/ Jupyterlab 2. This Base will continue to update for security and minor improvements, but if possible you should move to the latest Python 3.8 w/ JupyterLab 3 Base.