Alioth is a great site for selecting the language in which to implement primitives. Usually it's C.
Two of the alioth benchmarks, Partial-sums and Spectral-norm, could be done using Numarray, or would be done with Numarray if most of the program was in Python and there was a need to implement a similar numerical procedure. The speed would be up near the compiled language benchmarks. However the specific wording of these benchmarks prohibits this approach. Spectral-norm must pretend the dataset is infinite, and Partial-sums has to be implemented in a simple dumb loop. Looking over the benchmarks, one gains the impression that Python is a slow language. My first serious Python programming exercise involved converting a 900 line Bash Shell program to a 500 line Python program, with a speedup factor of 17. Using Python allowed an OO structure and advanced containers, meaning the program was more maintainable and portable, which were the main aims of the exercise. The speedup was a surprising and welcome side benefit. I think it was mosly because the Python byte-code interpreter is probably an order of magnitude faster than Bash's direct interpretation, and because in Python system calls to recurse directories and create symbolic links were not forked to separate processes. In fact I would guess that the overall speed of the Python program would be little less than a C program, given that most of the time would be spent in system calls. Its almost possible to make a large Python program arbitrarily fast by profiling it and implementing slow bits as primitives. Size is probably of greater concern. -- http://mail.python.org/mailman/listinfo/python-list
