Fair, maybe it's always a matter of picking the trap you want :) If you are optimizing for 0->1, Python is great. But if you want code to live and evolve over time with multiple authors, or ever will care about runtime performance, it's a dead end almost from the first line.
But sometimes the productivity benefit is all that matters and you accept you may have to throw it all out later (or invest insanely in making it work)... it's all about making an informed decision.
As with any language it's how you end up architecting your codebase. I do believe python lacks an authoritative resource for what is "good architecture" which leads to a lot of the code scaling problems.
