> they believe that it is OK for large arrays of numbers not to be a core language construct
Well, the Python array is good for most of the use cases. Adding other types to the core language could be useful, but then you get into "which type would be better for me"? Somebody else then would say "but what about a sparse matrix, etc"
I think it's ok to look to numpy for those things.
> writing a matrix product using three loops should be just as efficient than calling a matrix product routine
Well, yes, but actually no.
Because of code vectorization, the loop is going to be more inefficient. Yes, compilers are getting better, but they can't do miracles (especially in languages like C)
By using matrix products you're explicit in your desired end result. This can then be optimized by the libraries and you don't have to worry about all the tricks behind it.
Well, the Python array is good for most of the use cases. Adding other types to the core language could be useful, but then you get into "which type would be better for me"? Somebody else then would say "but what about a sparse matrix, etc"
I think it's ok to look to numpy for those things.
> writing a matrix product using three loops should be just as efficient than calling a matrix product routine
Well, yes, but actually no.
Because of code vectorization, the loop is going to be more inefficient. Yes, compilers are getting better, but they can't do miracles (especially in languages like C)
By using matrix products you're explicit in your desired end result. This can then be optimized by the libraries and you don't have to worry about all the tricks behind it.