Why can mutable default arguments cause bugs in Python?

Diagnoses shared mutable function defaults and explains safe initialization without turning the behavior into a superstition.

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TL;DR

Python evaluates default argument expressions when the function is defined, not each time it is called. A default such as items=[] therefore creates one list reused by every call that omits the argument. If the function appends to it, later callers see earlier state. The usual fix is a non-mutable sentinel such as None, followed by items = [] inside the function when no value was supplied.

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Definition-time default evaluation, aliasing across calls, sentinel choices, and the ability to recognize intentional versus accidental state.

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Core answer
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Overview
A default list that remembers earlier calls is one of Python's most common production surprises because the function owns one reused object.
Python evaluates default argument expressions when the function is defined, not each time it is called. A default such as items=[] therefore creates one list reused by every call that omits the argument. If the function appends to it, later callers see earlier state. The usual fix is a non-mutable sentinel such as None, followed by items = [] inside the function when no value was supplied.
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Stronger answer
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The same issue applies to dictionaries, sets, user-defined mutable objects, and defaults such as whose value should be fresh even though it is not mutable. If is a valid business value, I use a private sentinel object so missing and explicit remain distinct. Defaults that are immutable values, such as a timeout number or enum, are normally safe because calls cannot change that object in place.

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Saying the default is created on every call.
Fixing the problem with another mutable sentinel.
Using None without considering whether it is a valid input.
Treating hidden mutable defaults as an acceptable service cache.

Why can mutable default arguments cause bugs in Python?

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