[p4wnc6]

While I agree broadly that the benchmark example in the post is not representative or useful as a comparison between D and NumPy, I disagree with your strong insistence on Numba in this case.

There is still a lot of Python code that the Numba-to-LLVM compiler cannot handle. Yes, it is true that Numba can do a decent job of removing CPython virtual machine overhead, even for functions in which you statically type the arguments merely as 'pyobject' -- but not universally.

And there are also a ton of super basic things, for example creating a new array inside the body of a function when using Numba in 'nopython' mode [1], that Numba doesn't handle. These things will improve over time, but they may not improve quickly enough for a given use case, and the D language and this ndarray implementation may be a fair competitor to Numba in the short-to-medium term (and could even be superior in the long run, who knows).

A fairer alternative would be comparing with the use of Cython, which for my money still hands down beats anything like D or Nim/Pymod for performance enhancement without sacrificing pleasantness of design and development.

Though, of course, none of this stuff holds a candle to Haskell :)

[1] < http://stackoverflow.com/questions/30427081/creating-numpy-a... >

[tadlan]

Actually, Numba array allocation in nopython mode is allowed now.

What other numerical features are missing?