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Description
Problem
It would be interesting to set up some basic tests to see how the number of installed extensions could impact the loading time of the JupyterLab application.
For example does the loading time grow linearly with the number of installed extensions?
Proposed Solution
Set up a (recurring?) job that would pull the latest JupyterLab stable (or dev) version and install a given number of extensions (for example 10 or 100). And measure the time it takes for the splash animation to disappear.
Additional context
This can be relevant for large organizations and JupyterLab deployments that include many third-party extensions.