JupyterLab VS ML-Workspace

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.

Also check out: https://github.com/ml-tooling/ml-workspace, it a nice open source project with lots of packages ready to use.

The other option - no reason why you couldn't host something on the desktop machine - web based IDE like R-Studio or Python - have a look at ml-workspace - https://github.com/ml-tooling/ml-workspace that runs in Docker and would provide interfaces for both Python and R, VSCode as well as a GPU accelerated variant for doing Tensorflow etc - either Windows or Linux can support Docker containers (Linux is less trouble apparently - I only have played with it in Linux personally)

It will be a web based IDE dev kit (like Jupyter Hub, or JupyterLab) if you are familiar with them)

I'll stick with https://github.com/ml-tooling/ml-workspace, is a docker with all tools installed, also the option of using GPU, so I think is better than only for debian. This way anyone can use it.