On Mon, Jul 30, 2018 at 9:20 AM, Sunil Tech <sunil.tech...@gmail.com> wrote: > Hi Team, > > I am investigating how the memory allocation happens in Python > For Eg: > *Case 1:* > >>>> a = 10 >>>> b = 10 >>>> c = 10 >>>> id(a), id(b), id(c) > (140621897573616, 140621897573616, 140621897573616) >>>> a += 1 >>>> id(a) > 140621897573592 > > > *Case 2:* > >>>> x = 500 >>>> y = 500 >>>> id(x) > 4338740848 >>>> id(y) > 4338741040 > > > *Case 3:* > >>>> s1 = 'hello' >>>> s2 = 'hello' >>>> id(s1), id(s2) > (4454725888, 4454725888) >>>> s1 == s2 > True >>>> s1 is s2 > True >>>> s3 = 'hello, world!' >>>> s4 = 'hello, world!' >>>> id(s3), id(s4) > (4454721608, 4454721664) >>>> s3 == s4 > True >>>> s3 is s4 > False > > Python memory allocation is varying in all these use cases. Please help me > understand. > > Thanks, > Sunil. G > _______________________________________________ > Tutor maillist - Tutor@python.org > To unsubscribe or change subscription options: > https://mail.python.org/mailman/listinfo/tutor
An id is not guaranteed to be a memory address. In the cases you cited, your version of python caches small integers, and apparently small strings because its convenient and efficient to do so. Other implementations of python may take a different approach. I think it would be unwise to ever assume that a value is cached in your day to day programming -- Joel Goldstick http://joelgoldstick.com/blog http://cc-baseballstats.info/stats/birthdays _______________________________________________ Tutor maillist - Tutor@python.org To unsubscribe or change subscription options: https://mail.python.org/mailman/listinfo/tutor
