📦 Mutable Default Arguments

This is one of the most unexpected “gotchas” in Python, specifically related to the interaction between mutable objects and function definitions.

Default Arguments are Evaluated Once

In Python, the default values for function arguments are calculated and stored only once—when the function is defined (when the Python interpreter first reads the file).

If you use a mutable object (like a list or dict) as a default value, every time the function is called without that argument, it uses the exact same list object stored in the function’s definition.

The Pitfall Example

The results list is created once when add_item is defined.

def add_item(item, results=[]): # DANGEROUS DEFAULT
 results.append(item)
 return results

# First call: uses the original, empty list object
list_1 = add_item("apple") print(f"List 1: {list_1}") # List 1: ['apple']

# Second call: uses the SAME list object, which now contains 'apple'
list_2 = add_item("banana") print(f"List 2: {list_2}") # List 2: ['apple', 'banana'] - NOT a new list!

# This side effect is almost never desired.

2. ✅ The Solution: Use None and an Explicit Check

The standard and safe practice is to use None as the default value for mutable arguments, and then check if the argument is None inside the function body.

• None is immutable, so it is safe to use as a default.

• Inside the function, if the argument is None, a new mutable object (a fresh list or dict) is created every time the function is called.

The Correct Implementation

def add_item_safe(item, results=None): # SAFE DEFAULT
 if results is None: # Check if a new list needs to be created
  results = []

 results.append(item)
 return results

# First call: creates a NEW list []
list_1_safe = add_item_safe("apple")
print(f"List 1 Safe: {list_1_safe}") # List 1 Safe: ['apple']

# Second call: creates another NEW list []
list_2_safe = add_item_safe("banana")
print(f"List 2 Safe: {list_2_safe}") # List 2 Safe: ['banana']

3. 📝 Summary