Activation and execution of cells is slower when using Conda Run

Conda run seems to be very slow

• Possibly because conda run is slow
• Or we have python extension running conda run for all conda environments and we’re running as well
• Or other

@rchiodo @IanMatthewHuff You might recall, that running conda activate on CI can cause issues specially when run in parallel. And we have code that retries the activation (basically conda isn’t designed to activate multiple environments at the same time, due to some file locking issue).

Hence I believe using conda run in parallel (in python extension & then also running in jupyter) could be causing issues.

This is all hypothetical.

[rchiodo]

Note to self. this command was super useful for debugging this stuff:

It clears the memento storage, forcing all the environment caching to rerun.

[rchiodo]

I did find a typo that may be causing the caching to be skipped for somethings (this line here should read await Promise.race([cacheInfo.promise, latestInfo])).

Effectively that race always returns immediately but then the cacheInfo isn’t completed so we always wait for the latestInfo promise. That should be cached on the python side though, so not sure it makes much of a difference.

I’m going to try moving all of the kernel warmup code into a single execution to see if I can speed that up a little.