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What is the usecase you have for multiple kernels in one notebook?


In my field (genetic epidemiology), there are annoyingly un-standardised toolsets. There are libraries in R, python, and C/C++ binaries. Being able to string these together in one notebook is helpful.

That being said, I usually just stick to one notebook per thing.


It's not using multiple kernels in one notebook, but being able to manage all my kernels without opening up another window.




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