Python objects fall into two categories: mutable and immutable. The distinction determines whether an object's content can change after creation.Mutable objects like lists, sets, and dictionaries can be modified in place. The object's memory address stays the same even as its contents change.

Adding an element to a list updates the existing object directly.Immutable objects such as integers, strings, and tuples cannot be altered. Operations that seem to modify them actually create entirely new objects with new memory addresses. Assigning x = x + 1 creates a new integer rather than changing the original.

This behavior affects function arguments, recursion, and shared references. Passing a list to a function can result in unexpected changes outside the function scope since the same object gets modified. Understanding this core concept helps developers avoid common bugs and write more predictable code.

The mental model is simple: mutable objects change in place, immutable objects create new values.