The concepts 'deepcopy' and 'copy' are fundamental when you're dealing with complex data structures in Python, especially when these data structures involve mutable objects such as lists or dictionaries. Let's delve into what distinguishes one from the other and their use cases.
The key difference between deepcopy
and copy
in Python lies in how they handle the copying of complex objects that contain other objects.
A copy
in Python, also known as a shallow copy, only copies the memory address references of the object elements, not the actual values. Therefore, if the original element changes, the change is also reflected in the shallow copy because both point to the same memory address. This is useful when you want to create a new instance of a list or a dictionary while keeping the linkage to the original objects.
On the other hand, deepcopy
creates a completely new object, containing actual copies of the elements of the original object. It recursively copies all objects that the original object references. Hence, changes in the original object do not affect the copied object, and vice versa. In more technical terms, deepcopy creates a clone, where there's no reference or association to the original object.
Consider this example in Python:
import copy
# sample list
list1 = [1, [2, 3]]
# using copy for shallow copy
list2 = copy.copy(list1)
# using deepcopy for deepcopy
list3 = copy.deepcopy(list1)
list1[1][0] = 'A'
print(list1) # Output: [1, ['A', 3]]
print(list2) # Output: [1, ['A', 3]]
print(list3) # Output: [1, [2, 3]]
In our example, you can see how the change to list1
affects list2
(the shallow copy) because it points to the same nested list. But list3
(the deep copy) is not affected, as it is an entirely different object with no connection to list1
.
In summary, whether you should use copy
or deepcopy
in Python depends on the functionality you need. If you want changes in the original object to carry over to the copy, you should use copy
. If you want a wholly independent object copied without any reference to the original, then deepcopy
is the way to go.