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Why Do Mutable Default Arguments in Python Lead to Unexpected Behavior?

Patricia Arquette
Patricia ArquetteOriginal
2024-12-22 21:54:13351browse

Why Do Mutable Default Arguments in Python Lead to Unexpected Behavior?

"Least Astonishment" and the Mutable Default Argument

The unexpected behavior of the foo function in Python, where default arguments are bound at function definition instead of execution, has puzzled many. Some even consider it a programming faux pas. However, this behavior has a sound rationale rooted in Python's nature as a language with first-class functions.

Functions in Python are not mere blocks of code; they are objects that are evaluated at the time of their definition. This evaluation includes binding default arguments, which act as "member data" for the function object. Consequently, changes made to default arguments persist across function calls, similar to how state changes in any object are preserved.

To illustrate, consider a function a that prints a message and returns an empty list. Another function b takes a single parameter x with a default value of a(). When b is called without specifying x, it binds x to the result of calling a, which returns an empty list. However, since the empty list is stored as a default argument within b, subsequent calls to b will append to this same list, resulting in the observed behavior where [5] is printed on the first call and [5, 5] on the second.

This behavior follows the principle of "least astonishment," which dictates that the behavior of a program should align with what a programmer would reasonably expect. In this case, once a function object is defined, its default arguments become part of its state, and any modifications to those arguments are reflected in subsequent calls.

While this behavior may seem counterintuitive to some, it is consistent with Python's design philosophy. Functions as first-class objects allows for greater flexibility and encourages a more object-oriented style of programming. Understanding this concept enhances the programmer's grasp of Python's fundamentals and promotes more robust and effective code development.

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