I do research in high performance computing. I am well aware of the importance of performance critical, number crunching code that operates on large arrays. I wrote an entire dissertation based around better ways of expressing large computations on dense vectors and matrices for new multicores.
I am, however, self-aware enough to recognize that what I care about is a subset of what everyone in computing cares about. Scientific computing may be important in multiple places, but it is still a single domain. An important domain, sure. But Python is still used in many places were such concerns are not important. Arguments about the utility of number crunching on dense vectors and matrices are great. But the attitude I've seen in this thread is "the domain I care about is so important that my concerns should be elevated above the concerns of other domains." That is not going to fly when it comes to changing a general purpose language used in many domains.
I'm sure you know enormously more than I do about how to do dense-array number crunching. My claim, though, is that it's being applied much more widely than previously, not that there are new and better ways of doing it; so there are fewer and fewer places where such concerns are not important.
In the 1960s, there were those who claimed that the benefit of recursion was not worth the complexity it added to programming languages, except in certain special domains. In the 1970s and 1980s, we had the same argument about depth-first search — SNOBOL's and Prolog's backtracking feature. It turned out that the proponents of recursion were right, and the proponents of backtracking were probably wrong. (Although the backtracking feature of SNOBOL's child Icon directly inspired Python's generators, although implementationally they're maybe more similar to CLU iterators.)
Now, when it comes to matrix and vector manipulation, should we imagine it as a single domain, or as a feature that's useful across a wide range of domains?
And I'm arguing that's still one concern among many when it comes to a language used in so many different places. The arguments here are, I think, unsympathetic to the difficulties of designing and maintaing a general purpose programming language, in particular one with the design goals of Python.
I am, however, self-aware enough to recognize that what I care about is a subset of what everyone in computing cares about. Scientific computing may be important in multiple places, but it is still a single domain. An important domain, sure. But Python is still used in many places were such concerns are not important. Arguments about the utility of number crunching on dense vectors and matrices are great. But the attitude I've seen in this thread is "the domain I care about is so important that my concerns should be elevated above the concerns of other domains." That is not going to fly when it comes to changing a general purpose language used in many domains.