As far as I'm concerned, CPython as an interpreter technology has not advanced in the past decade - and Python has grown thanks to the data science community efforts and excellent library ecosystem you mention, not due to PSF. PSF can only miss so many opportunities before something comprehensively better starts to eclipse it.
I agree performance is important, and I think we have reason to be optimistic, but with the understanding that that level of improvement, even if currently underway, will just take a lot of effort and time. Meanwhile, as someone fairly new to Python and working on several performance critical pieces, I've been pretty impressed with what you can do with the current compute packages (after taking months to work my way through most of them).
In a recent post linked on HN, Steve Yegge basically nailed it:
> How much new software was written in something other than Python, which might have been written in Python if Guido hadn’t burned everyone’s house down? It’s hard to say, but I can tell you, it hasn’t been good for Python. It’s a huge mess and everyone is miserable.
Note to future language maintainers: don't burn everyone's house down.
Data science may be at the heart of Python's strengths, but it's simply not accurate to suggest Python (whoever that is!) is resting on its laurels, as evidenced by the very active, albeit sprawling, package ecosystem. And while the CPython devs seem to have found their stride in 3.x releases.
It's also inaccurate to suggest numeric computing in Python has a "low performance ceiling," considering you can get near-C performance via JIT or AOT using a package like Numba, and in most cases it's not even necessary because of Numpy and the many other highly optimized compute packages that can do most of the heavy lifting.
I think the main draw of Python is not just that the syntax and language features are approachable, but that the package ecosystem is so broad and active, you are likely to make lighter work of the same job done in another language. I think to displace Python you would have to displace the package ecosystem, which seems as big and broad as it's ever been.