> Plus, Fortran already has way better multi-dim array handling built-in - NumPy is basically just a wrapper around that.
I don't think either of these statements is true.
Fortran is hard to beat for performance, but from a usability perspective NumPy (and other Python libraries) has some nice features for array-oriented computation that you can't find even in modern Fortran. The most obvious examples are broadcasting [1] and advanced indexing [2].
NumPy itself contains only C, though some SciPy routines wrap Fortran code. Yes, NumPy drew heavy inspiration from Fortran, but it's hardly a wrapper.
I guess by "indexing" you mean what NumPy calls "advanced indexing". All the basic stuff seems lifted straight from Fortran. But yes, I should probably have been more exact with my statement - NumPy sure has some more helpful syntax that saves some LOC.
I don't think either of these statements is true.
Fortran is hard to beat for performance, but from a usability perspective NumPy (and other Python libraries) has some nice features for array-oriented computation that you can't find even in modern Fortran. The most obvious examples are broadcasting [1] and advanced indexing [2].
NumPy itself contains only C, though some SciPy routines wrap Fortran code. Yes, NumPy drew heavy inspiration from Fortran, but it's hardly a wrapper.
[1] http://docs.scipy.org/doc/numpy/user/basics.broadcasting.htm... [2] http://docs.scipy.org/doc/numpy/reference/arrays.indexing.ht...