And if good optimizations can help run a small simulation in 1 minute instead of 2, multiplied by the number of python users, it is a lot of time gained.
And I suspect, the fib(n) situation is actually quite common. I mean, not everyone who writes python is a "real" developer, there are a lot of scientists who just want the computer to run their formulas, and they write them it the most straightforward way possible. They won't bother with high performance libraries and optimizing their algorithms just to save a few minutes, but they would appreciate if the language could make things a little faster.
And it doesn't matter in the way of "hey look, Python slow, use JS". But it is good information for Python developers and advanced users, the people who non-specialists rely on.