I think in general Python's biggest challenge is that it doesn't scale well. This is an agglomeration of issues around the same theme: bad packaging when there's a lot of cross-cutting dependencies, slow performance, no concurrency, typing as second-class citizens, etc. All of that is barely noticeable when you're just getting started on a small experimental project, but incredibly painful in large production systems.
I strongly suspect that devs' satisfaction with Python is strongly correlated with the size of the codebase they're working on. Generally people using Python for one-off projects or self-contained tools tend to be pretty happy. People stuck in sprawling enterprise codebases, with O(million) lines of code to wrangle, seem almost universally miserable with the language.
What I've observed a lot is that many startups or greenfield projects start with Python to get an MVP out the door as fast as possible. Then as the scope of the software expands they feel increasingly bogged down and trapped in the language.
I strongly suspect that devs' satisfaction with Python is strongly correlated with the size of the codebase they're working on. Generally people using Python for one-off projects or self-contained tools tend to be pretty happy. People stuck in sprawling enterprise codebases, with O(million) lines of code to wrangle, seem almost universally miserable with the language.
What I've observed a lot is that many startups or greenfield projects start with Python to get an MVP out the door as fast as possible. Then as the scope of the software expands they feel increasingly bogged down and trapped in the language.