rpython and numpy

looks like at least a few people connected with pypy have an eye on numpy. there's a very small and limited demo in the svn right now. but other devs have said it is hard and not their main interest. i hope it at least remains possible, at some future date. maybe more promising is some work on ufuncs by one of the enthought people. it shows a good example of how to use rpython to compile a function. maybe i can use this to autogenerate c code for scipy.weave.inline. here's the most relevant example:

from pypy.translator.interactive import Translation
class compdec:
   def __init__(self, func):
       self.func = func
       self.argtypes = None
   def __call__(self, *args):
       argtypes = tuple(type(arg) for arg in args)
       if argtypes != self.argtypes:
           self.argtypes = argtypes
           t = Translation(self.func)
           t.annotate(argtypes)
           self.cfunc = t.compile_c()
       return self.cfunc(*args)
@compdec
def is_prime(n):
   if n < 2:
       return False
   for i in xrange(2, n):
       if n%i == 0:
           return False
   return True
print sum(is_prime(n) for n in xrange(100000))

i think that it would be easy to change the check/recompile to a dict lookup. that __call__ might also be compiled with rpython since args is always a tuple. that would add only 1 c function call overhead and preserve dynamic typing.