New submission from Grant Tang <[EMAIL PROTECTED]>:
#the following code consume about 800M memory, which is normal
n = 100000000
data = [0.0 for i in xrange(n)]
#however, if I assign random number to data list, it will consume extra
2.5G memory.
from random import random
for s in xrange(n):
data[i] = random()
#even if I delete data, only 800M memory released
del data
#call gc.collect() does not help, the extra 2.5G memory not released
import gc
gc.collect()
only when I quit Python, the memory is released. Same effect if I use
random number generator from numpy.
Same effect even if I just say data[i] = atpof("1.26")
I tried it in both Python 2.4 and 2.5 on linux 64bit and 32bit.
----------
components: None
messages: 67833
nosy: gtang
severity: normal
status: open
title: memory leak in random number generation
type: resource usage
versions: Python 2.4, Python 2.5
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Python tracker <[EMAIL PROTECTED]>
<http://bugs.python.org/issue3063>
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