On a related note, pickling of arrays of float64 objects, as generated by the numpy package for example, are wildly inefficient with memory. A half-million float64's requires about 4 megabytes, but the pickle file I generated from a numpy.ndarray of this size was 42 megabytes.
I know that numpy has its own pickle protocol, and that it's supposed to help with this problem. Still, if this is a general problem with Python and pickling numbers, it might be worth solving it in the language itself. -- http://mail.python.org/mailman/listinfo/python-list
