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How does Python handle mutable default arguments in functions, and why can this be problematic?
How does Python handle mutable default arguments in functions, and why can this be problematic?
Jun 14, 2025 am 12:27 AM
Python's default parameters are only initialized once when defined. If mutable objects (such as lists or dictionaries) are used as default parameters, unexpected behavior may be caused. For example, when using an empty list as the default parameter, multiple calls to the function will reuse the same list instead of generating a new list each time. Problems caused by this behavior include: 1. Unexpected sharing of data between function calls; 2. The results of subsequent calls are affected by previous calls, increasing the difficulty of debugging; 3. It causes logical errors and is difficult to detect; 4. It is easy to confuse both novice and experienced developers. To avoid problems, the best practice is to set the default value to None and create a new object inside the function, such as using my_list=None instead of my_list=[] and initializing the list in the function. In addition, it is necessary to carefully determine whether shared state is required, explicitly declare intentions and clearly document API behavior.
Python's handling of mutable default arguments in function definitions can be a bit tricky, and if you're not aware of how it works, it can lead to unexpected behavior.
The issue comes from using a mutable object — like a list or dictionary — as a default argument in a function definition. The key point is that default arguments are evaluated only once , when the function is defined, not each time the function is called.
This might seem like a small detail, but it can cause bugs that are hard to track down.
What happens when you use a mutable default argument?
Let's look at a common example:
def add_item(item, my_list=[]):
my_list.append(item)
return my_list If you call this function multiple times without providing my_list , like this:
print(add_item('a')) # ['a'] print(add_item('b')) # ['a', 'b']
You might expect each call to start with a new empty list, but instead, the same list is reused across all calls.
Why? Because the default value [] was created once when the function was defined, not each time it's called.
Why is this behavior problematic?
This behavior becomes an issue because it goes against what most people actually expect. When writing functions, we usually think of default values ??as being set fresh every time the function runs.
Here are some specific problems this causes:
Accidental data sharing between function calls
One call can affect the result of later calls, which makes debugging harder.Hard-to-catch logic errors
You might spend time chasing down why your list keeps growing even though you didn't intend it to.Confusion for beginners (and sometimes pros)
This is a classic gotcha in Python interviews and real-world code alike.
How to avoid the problem
To prevent this kind of behavior, a common best practice is to use None as the default value and create a new mutable object inside the function:
def add_item(item, my_list=None):
if my_list is None:
my_list = []
my_list.append(item)
return my_list Now calling the function without my_list will correctly give you a fresh list each time.
Other tips:
- Always consider whether a mutable default makes sense for your function.
- If you do want shared state, make it explicit — don't rely on this hidden behavior.
- Document the intended behavior clearly, especially if you're writing a library or API.
In short, Python evaluates default arguments once, which is fine for immutable types like numbers or strings, but leads to surprises with mutable ones. Avoid the trap by using None as a placeholder and initializing the object inside the function.
That's basically how it works — not complicated, but definitely something to watch out for.
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