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Why Does Python's ` =` Operator Behave Differently with Lists Than with Other Data Types?

Mary-Kate Olsen
Release: 2024-12-17 03:54:25
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Why Does Python's ` =` Operator Behave Differently with Lists Than with Other Data Types?

Understanding the Unexpected Behavior of =" on Lists in Python

Python's = operator can exhibit unexpected behavior when applied to lists. This unexpected behavior stems from Python's implementation of special methods for modifying and combining objects.

iadd and add Special Methods

The = operator attempts to invoke the iadd special method on the object it is applied to. If iadd is not available, it resorts to using add instead. These special methods are crucial for understanding the behavior of =.

__iadd__: In-Place Addition

The iadd method performs in-place addition, modifying the object it acts upon. When = is used on an object that supports __iadd__, the object is directly modified. This is the case for mutable types like lists.

__add__: Regular Addition

On the other hand, the add method creates a new object to represent the result of the addition. This is typically used for immutable types like tuples, strings, and integers, which are copied instead of modified.

Behavior on Lists

When = is used on a list object, Python attempts to call __iadd__. Since lists are mutable, they support __iadd__. This results in the list being modified in place, affecting all instances of the class.

In contrast, when = is used with a list object, add is called, and a new list is created. This explains why in the example given, f.bar = [3] modifies both f.bar and g.bar, while f.bar = f.bar [4] creates a new list object and modifies only f.bar.

Conclusion

By understanding the difference between iadd and __add__, it becomes clear why = behaves differently on lists compared to other types. The key takeaway is that = modifies an object directly if it supports __iadd__, while = creates a new object using __add__.

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