Christian Heimes wrote: > Hard computations gain more speed from carefully crafted C or Fortran > code that utilizes features like the L1 and L2 CPU cache, SIMD etc. or > parallelized algorithms. If you start sharing values between multiple > cores you have a serious problem. > > Oh, and use NumPy for the job ;) [...] > It *is* a well known limitation of Python. All the nice 'n shiny syntax > and features are coming with a cost. Python is a powerful language and > good tool for lots of stuff. But Python is and will never become the > übertool that solves every problem perfectly. At some point you need a > different tool to get the raw power of your machine. C (and perhaps > Fortran) are the weapons of choice for number crunching.
Well, and there's always Cython to the rescue when you need it. Stefan -- http://mail.python.org/mailman/listinfo/python-list