[Python] Deep and Shallow Copying: Understanding Lists, Dictionaries, and More

Python provides two ways to create a copy of an object: deep and shallow copying. Deep copying creates a new and separate copy of the entire object with all the objects inside it, while shallow copying creates a new object with references to the contents of the original object. This distinction can affect how changes to one object impact the other.

In this blog post, we will delve into deep and shallow copying in Python, using objects such as list, dict, str, int. We will compare these two types of copying through practical examples, emphasizing the importance of understanding these concepts for robust coding practices.

Deep Copy

Using the copy Module

Python provides the copy module that contains the deepcopy method to create a deep copy of an object.

import copy

original_list = [1, [2, 3], [4, 5]]
deep_copied_list = copy.deepcopy(original_list)
deep_copied_list[1][0] = 'changed'
print(original_list)  # Output: [1, [2, 3], [4, 5]]

The above code snippet demonstrates the creation of a deep copy using the deepcopy method. The change to deep_copied_list does not affect the original_list.

Shallow Copy

Using the copy Method

A shallow copy can be created using the copy method from the copy module or using the object's built-in copying functionality.

import copy

original_dict = {'a': [1, 2], 'b': [3, 4]}
shallow_copied_dict = copy.copy(original_dict)
shallow_copied_dict['a'][0] = 'changed'
print(original_dict)  # Output: {'a': ['changed', 2], 'b': [3, 4]}

This code snippet highlights that changes to the shallow_copied_dict are reflected in the original_dict, as the shallow copy contains references to the original object's contents.

Copying Various Object Types

In Python, both deep and shallow copying can be performed on different types of objects, such as lists, dictionaries, strings, and integers. The behavior of these copy methods varies between mutable and immutable types. Here's a breakdown:

Lists

Deep Copy

import copy

original_list = [1, [2, 3], [4, 5]]
deep_copied_list = copy.deepcopy(original_list)

Shallow Copy

original_list = [1, [2, 3], [4, 5]]
shallow_copied_list = original_list.copy()
shallow_copied_list[1][0] = 'changed'
print(original_list)  # Output: [1, ['changed', 3], [4, 5]]

For lists, a deep copy creates a completely independent copy, whereas a shallow copy leads to shared references for nested objects.

Dictionaries

Deep Copy

import copy

original_dict = {'a': [1, 2], 'b': [3, 4]}
deep_copied_dict = copy.deepcopy(original_dict)

Shallow Copy

original_dict = {'a': [1, 2], 'b': [3, 4]}
shallow_copied_dict = original_dict.copy()
shallow_copied_dict['a'][0] = 'changed'
print(original_dict)  # Output: {'a': ['changed', 2], 'b': [3, 4]}

With dictionaries, deep copying creates entirely new objects, while shallow copying results in references for nested objects.

Strings and Integers (Immutable Types)

Deep Copy

original_str = "text"
deep_copied_str = copy.deepcopy(original_str)
original_int = 42
deep_copied_int = copy.deepcopy(original_int)

Shallow Copy

original_str = "text"
shallow_copied_str = copy.copy(original_str)
original_int = 42
shallow_copied_int = copy.copy(original_int)

Strings and integers are immutable, meaning that shallow and deep copying behave the same way, creating entirely new objects.

Summary Table

Understanding how copying behaves with different types of objects is vital for effectively working with complex data structures in Python. It provides control over how objects are duplicated and referenced, leading to more accurate and efficient code.

Understanding the difference between deep and shallow copying is vital for manipulating complex data structures in Python. It allows for precise control over how objects are duplicated and referenced, enabling more streamlined and efficient coding practices.

FAQs

1. What is the main difference between deep and shallow copying? Deep copying creates an entirely new object, while shallow copying creates a new object that references the contents of the original object.
2. How can I create a deep copy of a dictionary or list? Use the deepcopy method from the copy module to create a deep copy.
3. Are shallow copies suitable for all types of objects? Shallow copying behaves differently with mutable and immutable objects. Understanding this behavior is crucial when choosing the copy method.
4. Can changes to a shallow copy affect the original object? Yes, changes to a shallow copy of mutable objects like lists and dictionaries can affect the original object.
5. Is it more efficient to use shallow or deep copying? Shallow copying is generally more efficient as it does not recreate the entire object. However, the choice between shallow and deep copying should depend on the specific requirements of the code.