New submission from Adrian Teng:
A particular usage pattern of hashlib will cause a memory leak.
This leaks:
import hashlib
import sys
if __name__ == '__main__':
data_sha1 = "hello world"
data_md5 = "hello world"
for i in xrange(int(1e6)):
hashlib.sha1(data_sha1)
hashlib.md5(data_md5)
if i % 1000 == 0:
print sys.getrefcount(data_sha1), ",", sys.getrefcount(data_md5)
-------
this doesn't leak:
import hashlib
import sys
if __name__ == '__main__':
data_sha1 = "hello world"
data_md5 = "hello world"
for i in xrange(int(1e6)):
sha1 = hashlib.sha1()
sha1.update(data_sha1)
md5 = hashlib.md5()
md5.update(data_md5)
if i % 1000 == 0:
print sys.getrefcount(data_sha1), ", ", sys.getrefcount(data_md5)
See attached for leak memory profiling in linux
----------
components: Library (Lib)
files: memoryleak_min.py
messages: 213961
nosy: ateng
priority: normal
severity: normal
status: open
title: hashlib memory leak
type: resource usage
versions: Python 2.7
Added file: http://bugs.python.org/file34489/memoryleak_min.py
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Python tracker <rep...@bugs.python.org>
<http://bugs.python.org/issue20967>
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