It's not about writing code as much as it is about exploring the data.
If you're writing a lot of code in them, it's probably better to put that code into libraries that get imported and reused.
And I do agree that default code environment is unbearable. Particularly the auto insertion of completing quotation marks, which has me continually fighting with the editor to get correct code into a tiny web text box.
Oh I won't argue you with you there. I just find myself rotating quite a bit because I have to do both deployment as well as writing code for experimentations.
What I'm specifically talking about is even that kinda hacky experiment code you end up writing. I don't try to implement whole projects in there, but even just "train this model" type code ends up being a hassle because of how bad the editors are.
My above comment was more referencing wishing I could spend more time writing experiment code in jupyter without copying and pasting all the time.
If you're writing a lot of code in them, it's probably better to put that code into libraries that get imported and reused.
And I do agree that default code environment is unbearable. Particularly the auto insertion of completing quotation marks, which has me continually fighting with the editor to get correct code into a tiny web text box.