I agree - Jupyter notebook is really the key feature Python has that makes it attractive for research/scientific computing. I would say the REPL too but until very recently it was extremely shoddy so I doubt many people did any serious work in it.
Very obvious example - you can't paste code containing blank lines.
Another example: navigating this history is done line by line instead of using whole inputs.
It's just bare minimum effort - probably gnu readline piped directly into the interpreter or something.
I think they did improve it a lot very recently by importing the REPL from some other Python interpreter but I haven't upgraded to use that version yet so I don't know how good it is now.
> probably gnu readline piped directly into the interpreter or something
That is more or less how the REPL originally was implemented. I think there's more under the hood there now.
I still don't think what you describe qualifies as "shoddy". There are certainly limitations to the REPL, but "shoddy" to me implies that it's not really usable. I definitely would not agree with that.
The predecessors were really popular before it too - MATLAB in engineering in particular, Mathematica also popular in Physics and Maths departments particularly where the symbolic functionality was more useful. I used both in academia and IPython (later renamed Jupyter) was clearly a natural extension of those but open source, and without the baggage of MATLAB (only one function definition per file, etc.)
> I would say the REPL too but until very recently it was extremely shoddy
Can you elaborate? I've been using the Python REPL for more than two decades now, and I've never found it to be "shoddy". Indeed, in pretty much every Python project I work on, one of the first features I add for development is a standard way to load a REPL with all of the objects that the code works with set up properly, so I can inspect them.