On Friday, November 25, 2016 at 6:24:47 AM UTC-5, Nikunj wrote:
> Hi All,
>
> Out of curiosity, I wanted to understand the reason behind having different
> memory location for two identical floats . This is unlike ints or strings.
> Tried googling but couldn't find anything concrete. Any links or references
> would be appreciated!
>
> Example:
>
> For FLOATS:
> ==========
>
> >>> l = 1.3
> >>> id(l)
> 140421602788216
>
> >>> k = 1.3
> >>> id(k)
> 140421602788240
>
> >>> k == l
> True
>
> >>> k is l
> False
>
> For INTS and STRINGS:
> =================
> >>> i = 2
> >>> o = 2
> >>> id(i), id(o)
> (140421602779712, 140421602779712)
>
> >>> i is o
> True
>
> >>> a1 = 'hi'
> >>> a2 = 'hi'
> >>> a1 is a2
> True
It's more complicated than that:
(using Python 2.7.10)
>>> i = 2002
>>> o = 2002
>>> i is o
False
>>> a = 'what!?'
>>> b = 'what!?'
>>> a is b
False
A Python implementation can choose when to reuse immutable objects and
when not to. Reusing a value has a cost, because the values have to
be kept, and then found again. So the cost is only paid when there's
a reasonable chance that the values will actually be needed again.
And that cost has to be weighed against the opposite cost of simply
making a new object instead.
To answer your direct question: floats are so numerous and varied, it's
reasonable to guess that you won't often need the same one. And the cost
to make a new one is so low, that it's simpler just to not reuse any of
them.
--Ned.
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