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I primarily use Jupyter Lab. I have some frustrations but I generally like being able to manage multiple kernels from one notebook, having multiple views into one notebook, having context-sensitive help, and having some of the other features that were only in Lab.

That being said, I'm glad they've switched course and continue to work on Notebook once it became clear some people preferred it to Lab. With some of the added features and the ability to switch between Lab and Notebook more easily, I may give Notebook another try.




How does mixing and matching kernels in one notebook work? Can you directly exchange data between cells of different kernel types somehow? Do you go through the filesystem or some kind of in-memory serialization?

(I'm sorry for the questions that could be answered from documentation, but I can't find the docs on this feature! I have been wanting to specify data cells in a notebook, like the markdown cells, and then reference their contents from a code cell)


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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