Shallow vs. Deep Copy in Python: When to Use Which?

Understanding Shallow Copy, Deep Copy, and Assignment Operations

Inefficiency of Normal Assignment

Normal assignment operations simply create a reference to the existing object, rather than creating a new one. This can lead to unforeseen modifications, as changes to the original object will be reflected in the copied object as well.

Shallow Copy: Surface-Level Duplication

The shallow copy method constructs a new object and inserts references to the existing objects contained within the original object. This means that changes to the original object's child objects will also be reflected in the shallow copy.

Deep Copy: Complete Replication

The deep copy method creates a new object and recursively inserts copies of the objects found in the original object. This ensures that any changes made to the original object's child objects will not affect the deep copy.

Implications for Mutable and Immutable Objects

These copy operations have different implications for mutable and immutable objects:

• Immutable Objects (e.g., strings, tuples): Shallow and deep copies do not make a difference, as immutable objects cannot be modified.
• Mutable Objects (e.g., lists, dictionaries): Shallow copies retain references to the original object's child objects, while deep copies create new instances of these child objects.

Example

Consider the following code:

import copy

a = "deepak"
b = (1, 2, 3, 4)
c = [1, 2, 3, 4]
d = {1: 10, 2: 20, 3: 30}

a1 = copy.copy(a)
b1 = copy.copy(b)
c1 = copy.copy(c)
d1 = copy.copy(d)

For immutable objects like strings and tuples (a and b in this case), both shallow and deep copies will create new objects with different memory addresses. However, for mutable objects like lists and dictionaries (c and d), shallow copies will create new references to the original objects, while deep copies will create new instances of these objects.

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