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Can you explain in more detail what are the current issues being faced with having a single big environment? And I guess also some comment on why having a separate one for each talktorial?

While separating environments could make things easier for people to use the talktorials (in specific circumstances), it does create a significant burden in maintaining each of the environments separately. And maybe even will make things harder for users to add packages to the environments if these are not maintained or kept up to date (since they will probably be harder to maintain if we separate them).

Does it make sense having separate environments but not necessarily one for each talktorial? As in, maybe just having one separate environment for the ML/DL stuff, and the rest in another one. If that makes any sense. Apologies that I'm not that familiar with this project, so I'm just starting to wrap my head around this. Thanks!

While separating environments could make things easier for people to use the talktorials (in specific circumstances), it does create a significant burden in maintaining each of the environments separately.

The reasoning is somewhat opposite. The environment for everything is very heavy and complex. Introducing or updating packages is difficult because we are in dependency hell. It's the main reason, everything is still on python 3.8. With packages not being able to be updated easily, tutorials sometimes make use of deprecated behaviors.

The goal therefore is mainly maintainability. From a user's perspective it is probably more cumbersome to install and activate one environment for every talktorial. There are other complications like the CLI (which I have not looked at so far at all) and the teachopencadd conda package.

Merging environments for groups of talktorials is something, we have in mind and likely will do. This has advantages for usability and the CI. We should probably keep one file per talktorial for the sake of consistency, though.

This is replaced by #417