In Python, function argument transfer is "passing object reference", that is, 1. For mutable objects (such as lists and dictionaries), in-situ modifications (such as append, assignment slice) within the function will directly affect the original object; 2. For immutable objects (such as integers, strings), the original object cannot be changed in the function, and reassigning will only create a new object; 3. The parameter passes a copy of the reference. If the variable is rebinded in the function (such as lst = [...]), the connection with the original object will not be affected without affecting the external variable. Therefore, modifying mutable objects affects the original data, while immutable objects and reassignment do not, which explains why the list is visible externally after modification within the function, while integer changes are only locally.
In Python, the "pass parameter" mechanism is not a simple "pass value" or "pass reference" , but to be more precise: "pass object reference" . This means:
- If it is a mutable object (such as lists, dictionaries), modifications within the function will affect the original object, which looks like "reference pass".
- If it is an immutable object (such as integers, strings, and tuples), the original object cannot be modified in the function, which is like "value transfer".
The following is a clear example to illustrate the performance of this "reference transfer":
? Example: List (mutable object) - similar to "pass by reference"
def modify_list(lst):
lst.append(4)
print("Inside function:", lst)
my_list = [1, 2, 3]
print("Before function call:", my_list)
modify_list(my_list)
print("After function call:", my_list)Output:
Before function call: [1, 2, 3] Inside function: [1, 2, 3, 4] After function call: [1, 2, 3, 4]
? illustrate :
my_list is a list (mutable object). When passing in a function, lst is a reference to the same list object. Therefore, modifications to lst (such as append ) in the function will directly affect the original list.
? Comparison: Integer (immutable object) - will not change the original value
def modify_number(x):
x = x 1
print("Inside function:", x)
num = 10
print("Before function call:", num)
modify_number(num)
print("After function call:", num)Output:
Before function call: 10 Inside function: 11 After function call: 10
? illustrate :
Integers are immutable objects. x = x 1 inside the function creates a new object, x points to the new value, but the original num is not affected.
? Key understanding points
- All variables in Python are references to objects.
- Function parameters pass a copy of the object reference (not the object itself, nor is it a completely independent value).
- Operations on mutable objects (such as
list.append()) will be applied to the original object. - If you reassign a value in the function (such as
lst = [...]), it will disconnect from the original object and no longer affect the original object.
?? Note: Reassignment vs Modify in place
def reassign_list(lst):
lst = [4, 5, 6] # Rebind, does not affect the original list print("Inside (reassign):", lst)
def mutate_list(lst):
lst[:] = [4, 5, 6] # Modify content in place to affect the original list# or use clear extend
print("Inside (mutate):", lst)
original = [1, 2, 3]
reassign_list(original)
print("After reassign:", original) # Output: [1, 2, 3]
mutate_list(original)
print("After mutate:", original) # Output: [4, 5, 6]? the difference :
-
lst = [4,5,6]: Let the formal parameters point to the new object without affecting the outside. -
lst[:] = [4,5,6]: Modify the content of the original object and you can see changes outside.
Summarize
- ? After variable objects such as lists and dictionaries are passed, modifying them in place will affect the original object, which will appear like "pass by reference" .
- ? Immutable objects (int, str, etc.) will not be modified within the function.
- ? Remember: Python is "pass by object reference" , not the kind of reference passing of C.
Basically that's it. By understanding this, you can avoid many pitfalls of function argument transmission.
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