Identities: How Python Keeps Track of Values - Practical Programming, Fourth Edition - Dmitry Zinoviev - RutLib.com

Identities: How Python Keeps Track of Values

In , you learned that Python stores each value in a separate object. Every object in Python is tracked by the system and can be distinguished from other objects, even if they hold the same value. This distinguishing feature is called the object’s identity. An object’s identity is usually related to its unique memory address, though it isn’t guaranteed to be the actual address. You can find the identity of an object obj using the built-in function id:

>>> help(id)

Help on built-in function id in module builtins:

id(obj, /)

Return the identity of an object.

This is guaranteed to be unique among simultaneously existing objects.

(CPython uses the object's memory address.)

How cool is that? Let’s try it:

>>> id(-9)

140610723244688

>>> id(23.1)

140610725652592

>>> shoe_size = 8.5

>>> id(shoe_size)

140610727966896

>>> fahrenheit = 77.7

>>> id(fahrenheit)

140610725657616

The identities you get will likely be different from those listed here, as values are stored wherever there’s free space available.

Functions (function objects) also have identities:

>>> id(abs)

139816718551376

>>> id(round)

139816718554336

Because small integers—up to about 250 or so, depending on the version of Python—are used so frequently, Python interns these values when it starts up: it creates them once and reuses the same objects whenever those values appear. Interning improves performance and reduces memory usage. The id function reveals this behavior by showing that repeated uses of the same small integer refer to the same object:

	>>> i = 3
	>>> j = 3
	>>> k = 4 - 1
	>>> id(i)
	11576472
	>>> id(j)
	11576472
	>>> id(k)
	11576472

What that means is that variables i, j, and k refer to the same object. This phenomenon is called aliasing.

Larger integers and all floating-point values aren’t necessarily interned:

	>>> i = 30000000000
	>>> j = 30000000000
	>>> id(i)
	139970772364592
	>>> id(j)
	39970772364496
	>>> f = 0.0
	>>> g = 0.0
	>>> id(f)
	139970777086128
	>>> id(g)
	139970774776848

Python decides for itself when to intern a value. The only reason you need to be aware of it is so that you aren’t surprised when it happens; the output of your program is not affected by when Python decides to intern.