[cycomanic]

I would wager that in a large percentage of cases you would see the same or larger gains as you see from going to different languages you would see by going for better algorithms. You example of scientific computing (and point of software engineering is well taken) is a good one, because in scientific computing people tend to research and use the fastest algorithms and once you do python (+numpy) is often fast enough.

[pas]

Using numpy is fast, because it just uses the forever-optimized stuff bundled with it, and uses not much Python. But of course offers a handy interface.

Python suffers from the same problems as C in this regard. It's very powerful, easy to get going, because it doesn't force you into some "better" paradigm/architecture/ideology/thinking. (Like let's say mypy or Rust do.)

And that's okay. 80+% of Python scripts/programs are fine without that rigor, there are more important problems to worry about. (Like making the company profitable sooner instead of spending plus a few more months on figuring out the types/bindings for mypy/Rust.)