I just discovered that in a program of mine it was wasting 7MB out of 200MB by storing multiple copies of 0.0. I found this a bit suprising since I'm used to small ints and strings being cached.
I added the apparently nonsensical lines + if age == 0.0: + age = 0.0 # return a common object for the common case and got 7MB of memory back! Eg :- Python 2.5c1 (r25c1:51305, Aug 19 2006, 18:23:29) [GCC 4.1.2 20060814 (prerelease) (Debian 4.1.1-11)] on linux2 Type "help", "copyright", "credits" or "license" for more information. >>> a=0.0 >>> print id(a), id(0.0) 134738828 134738844 >>> Is there any reason why float() shouldn't cache the value of 0.0 since it is by far and away the most common value? A full cache of floats probably doesn't make much sense though since there are so many 'more' of them than integers and defining small isn't obvious. -- Nick Craig-Wood <[EMAIL PROTECTED]> -- http://www.craig-wood.com/nick _______________________________________________ Python-Dev mailing list Python-Dev@python.org http://mail.python.org/mailman/listinfo/python-dev Unsubscribe: http://mail.python.org/mailman/options/python-dev/archive%40mail-archive.com
