I write production code, I also work lots in Jupyter notebooks.
Personally, I think the fact that notebooks are usually easier/funner for me to work with is a big problem. I'm by no means a Clojure expert, but I did do a semi-large project in Clojure a few years ago, and some of the ideas of true REPL-driven development that exist there are things I wish that Python supported.
It's hard to explain without actually learning it for real (and most Python devs mistakenly think Python has REPL-driven development; I sure did before learning Clojure!). But once you get used to being able to interact with your actual source code, and at any point just being able to write new code and immediately print out its value, then with one shortcut make it part of the regular codebase... that just blurs the distinction that exists between Jupyter Notebooks and production code in a way that makes everything much better.
I'd love to hear more about this REPL-driven development. I've heard people bring it up from time to time, but it's clearly very different from the typical "stateless horizontal micro-service" that has become common practice.
What tools are used for "write new code and immediately print out its value, then with one shortcut make it part of the regular codebase" and how does that square with working on a team and getting code reviewed?
Personally, I think the fact that notebooks are usually easier/funner for me to work with is a big problem. I'm by no means a Clojure expert, but I did do a semi-large project in Clojure a few years ago, and some of the ideas of true REPL-driven development that exist there are things I wish that Python supported.
It's hard to explain without actually learning it for real (and most Python devs mistakenly think Python has REPL-driven development; I sure did before learning Clojure!). But once you get used to being able to interact with your actual source code, and at any point just being able to write new code and immediately print out its value, then with one shortcut make it part of the regular codebase... that just blurs the distinction that exists between Jupyter Notebooks and production code in a way that makes everything much better.