[Galanwe]

My take:

- The UI is over bloated and bugged, sometimes things scroll, sometimes they don't, sometimes you have to refresh the page. You cannot easily change the UI as lots of CSS parts have hard coded fixed sizes.

- The settings are all over the place, from py files in ~/.jupyter to ini files to auto generated command line parameters.

- The overall architecture is monolithic and hard to break down, jupyter proxy is a good example of the hacks you have to go to to reuse parts of jupyter

- The front end technology (Lumino) is ad hoc and cannot be reused, I had to write my own react components basically reimplementing the whole protocol, come on its 2025.

- The whole automation around nbconvert is error prone and fragile

[agoose77]

This is mixing quite a few different things (backend, frontend, auxiliary CLI utilities).

No time to write a lengthy reply here, but I think it's worth separating legitimate like-for-like comparison with a wider feeling on the ecosystem.