Charles Waldman writes:

"""
Problem description:

	Run the following script:

import test.test_cpickle
for x in xrange(1000000):
    reload(test.test_cpickle)

Watch Python's memory use go up up and away!

In the course of debugging this I also saw that cPickle is
inconsistent with pickle - if you attempt a pickle.load or pickle.dump
on a closed file, you get a ValueError, whereas the corresponding
cPickle operations give an IOError.  Since cPickle is advertised as
being compatible with pickle, I changed these exceptions to match.
"""

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