Understanding the Difference Between Python's `is` and `==` Operators and Integer Caching

In Python, the is operator tests whether two operands refer to the exact same object, whereas the == operator compares the values of the operands for equality.

Because Python pre‑allocates a pool of small integers (‑5 to 256), variables assigned these values often point to the same object, as demonstrated below:

>> a = 256<br/>>> b = 256<br/>>> a is b<br/>True<br/><br/>>> a = 257<br/>>> b = 257<br/>>> a is b<br/>False<br/><br/>>> a = 257; b = 257<br/>>> a is b<br/>True

For mutable objects like lists, identity and equality differ:

>> [] == []<br/>True<br/>>> [] is []<br/>False

The interpreter assigns the same object reference for cached integers, which can be observed with the id() function:

>> id(256)<br/>10922528<br/>>> a = 256<br/>>> b = 256<br/>>> id(a)<br/>10922528<br/>>> id(b)<br/>10922528<br/><br/>>> id(257)<br/>140084850247312<br/>>> x = 257<br/>>> y = 257<br/>>> id(x)<br/>140084850247440<br/>>> id(y)<br/>140084850247344

When the same value is assigned to multiple variables on a single line, Python may reuse the cached object, but separate assignment statements create distinct objects:

>> a, b = 257, 257<br/>>> id(a)<br/>140640774013296<br/>>> id(b)<br/>140640774013296<br/><br/>>> a = 257<br/>>> b = 257<br/>>> id(a)<br/>140640774013392<br/>>> id(b)<br/>140640774013488

This behavior is a specific optimization for the interactive interpreter, where each line is compiled separately; scripts executed from a .py file are compiled as a whole and do not exhibit the same identity shortcuts.