Unable to reliably use single JypyterLab server with multiple conda environments

hi @jonburdo, thanks for the detailed examples! Unfortunately, it doesn’t solve the problem. I’m aware of the standard way of registering kernels. This is what I also describe in my initial post after the words:

You’re absolutely right, in this case it is possible to interrupt the kernel. But the problem with this approach is that it doesn’t actually use the correct environment. It leads to numerous problems. I mentioned one of them in my initial post as well, it was about the jupyter notebook issue #4569. Discourse didn’t allow me post the link to this issue as I already had two other links, but I can do it here: Fails to load dll when in notebook, but not in ipython · Issue #4569 · jupyter/notebook · GitHub

Regarding the custom kernel startup commands, it seems that it is what nb_conda_kernels does. It properly activates the correct environment, but it turns out that it leads to problems with process inheritance, which makes interrupting the kernel impossible. See the related link in my second post in this thread. Based on that, I have also updated the issue description in the nb_conda_kernels repo that I mentioned in my initial post.