What is the difference between a deep and shallow copy in Python?
Table of Contants
Introduction
In Python, copying objects can be done in two primary ways: deep copy and shallow copy. Understanding the difference between these two copying methods is essential for effective memory management and avoiding unintended side effects in your programs. This guide explores the distinctions between deep and shallow copies, their implications, and practical examples.
Difference Between Deep Copy and Shallow Copy
Shallow Copy
A shallow copy creates a new object but inserts references into it to the objects found in the original. This means that changes made to mutable objects within the copied object will affect the original object, as both share references to the same inner objects.
Example of Shallow Copy
Using the copy module’s copy() function, we can create a shallow copy:
In this example, modifying the nested list in the shallow copy also affects the original list because both lists reference the same inner list.
Deep Copy
A deep copy creates a new object and recursively copies all objects found in the original. This means that changes made to the deep copy do not affect the original object, as all objects are distinct and not shared.
Example of Deep Copy
Using the copy module’s deepcopy() function, we can create a deep copy:
In this example, modifying the nested list in the deep copy does not affect the original list, as the inner lists are distinct objects.
Practical Examples
Example 1: Using Shallow Copy
Shallow copies are often sufficient when dealing with immutable objects or when you don't need to modify nested structures. Here’s an example with a simple list:
Example 2: Using Deep Copy
Deep copies are useful when you need to ensure that modifications to a copy do not affect the original object, especially when working with nested mutable structures.
Conclusion
The primary difference between deep and shallow copies in Python lies in how they handle nested objects. A shallow copy only copies the references to the objects, while a deep copy creates entirely new copies of all objects. Understanding these differences is crucial for effective memory management and ensuring that changes in copied objects do not unintentionally affect the original objects. By utilizing the appropriate copy method, you can prevent side effects and maintain the integrity of your data structures in Python programmig.