JupyterLab VS nb_conda_kernels

Does this allow to run a long running task in the background so that a user can close & reopen the tab and continue seeing all the output that has been produced thus far?

This is currently being worked on in Jupyter: https://github.com/jupyterlab/jupyterlab/pull/15448

This is a problem with codemirror 6. You can upvote https://github.com/jupyterlab/jupyterlab/issues/14589 and help by contributing (or sponsor someone to do so)

https://github.com/jupyterlab/jupyterlab/issues/12422

That whole issue feels so stupid.

I quite enjoy jupyter lab otherwise, even if a lot of it is brittle and annoying.

Could you add your details to https://github.com/jupyterlab/jupyterlab/issues/14625 it seems like a browser specific kssue

This will be possible in JupyterLab 4.0 and Jupyter Notebook 7 to be released in Q2/Q3 this year, see https://github.com/jupyterlab/jupyterlab/pull/13285

The posted SO is irrelevant. The true answer is that a new dependency included in 3.6 did not have binaries for some platforms. These were now uploaded so after refreshin pip cache you should be good to go. If it still does not work please post details in https://github.com/jupyterlab/jupyterlab/issues/13920

After a quick look I found the same issue here.

Yes, Jupyter notebook has used CodeMirror for nearly a decade. The official Jupyter notebook has never used Monaco, but the Google version (colab) uses Monaco in order to very nicely leverage LSP support (similar to VS Code). There is preliminary work under way right now to switch from CodeMirror 5 to CodeMirror 6 in the official Jupyter project, but that's going to be significant work (see https://github.com/jupyterlab/jupyterlab/pull/11638).

It doesn't seem like there is much overlap between Replit and Jupyter notebooks right now, as far as I can tell...

With the support of a team member with prior experience auditing for accessibility, we pinpointed specific ways in which JupyterLab lacked support for accessibility broken up by WCAG 2.1 standards.

If you use conda there are extensions that can help with this by automatically registering any available conda environments that include ipykernel in your Jupyter Lab environment.

nb_conda_kernels is pretty reliable but not actively maintained. Gator from the mamba folks is new and still a bit rough around the edges but looks like it will be pretty slick eventually.

https://github.com/Anaconda-Platform/nb_conda_kernels

https://github.com/mamba-org/gator

it sounds like what you're trying to do is what https://github.com/Anaconda-Platform/nb_conda_kernels does, except with pipenv. I unfortunately do not have a solution for you for pipenv, but nb_conda_kernels does seamlessly allow you to launch kernels in environments other than the environment Jupyter is running in without having to start multiple instances of jupyter.