How to Copy in Python: A Step-by-Step Guide

Python is a popular programming language that is loved by developers worldwide. It is an interpreted, high-level, general-purpose programming language that is easy to learn, write, and read. Python’s popularity lies in its simplicity and the availability of vast library support. Python is used in various fields such as web development, machine learning, data analysis, and scientific computing. In this article, we will explore how to copy in Python, a fundamental concept that is useful in many applications.

Table of Contents

Understanding Python Copying

Copying in Python is a process of creating a new object with the same value as the original object. Python has two types of copying- Shallow copying and deep copying.

Shallow Copying

Shallow copying is creating a new object that references the original object. In other words, shallow copying a reference to the original object. Shallow copying is useful when you want to create a new object that has the same value as the original object, but you don’t want to create a new object’s copy. Shallow copying is performed using the copy module in Python.

Deep Copying

Deep copying, on the other hand, creates a new object that has the same value as the original object. However, the new object is entirely independent of the original object. Any changes made to the new object will not affect the original object. Deep copying is performed using the deepcopy module in Python.

How to Copy in Python

Copying in Python is a fundamental concept that is frequently used in various applications. In this section, we will explore how to copy in Python using shallow copying and deep copying.

Shallow Copying in Python

Shallow copying is performed using the copy module in Python. The copy module provides the deepcopy() function, which creates a new object and copies the values of the original object into the new object. However, any changes made to the new object will affect the original object. Let’s take a look at how to perform shallow copying in Python.

import copy

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

print(f"Original List: {original_list}")
print(f"New List: {new_list}")

new_list[0] = 10

print(f"Original List: {original_list}")
print(f"New List: {new_list}")

In the above code, we import the copy module and create a list called original_list. We then use the copy() function to create a new object called new_list that contains the same values as the original_list. We then print the original_list and new_list.

Next, we assign a new value to the first element of the new_list. Finally, we print the original_list and new_list again to see the changes.

As you can see, any changes made to new_list did not affect original_list. However, both original_list and new_list have the same values initially.

Deep Copying in Python

Deep copying is performed using the deepcopy() function in Python. The deepcopy() function creates a new object, and it copies the values of the original object into the new object. Any changes made to the new object will not affect the original object. Let’s take a look at how to perform deep copying in Python.

import copy

original_list = [1, 2, [3, 4, 5], 6, 7]
new_list = copy.deepcopy(original_list)

print(f"Original List: {original_list}")
print(f"New List: {new_list}")

new_list[0] = 10
new_list[2][0] = 30

print(f"Original List: {original_list}")
print(f"New List: {new_list}")

In the above code, we import the copy module and create a list called original_list. We then use the deepcopy() function to create a new object called new_list that contains the same values as the original_list. We then print the original_list and new_list.

Next, we assign a new value to the first element of the new_list and change the first element of the nested list. Finally, we print the original_list and new_list again to see the changes.

As you can see, any changes made to new_list did not affect original_list, even though we made changes to the nested list. The deepcopy() function created a new object that is independent of the original object.

Conclusion

Copying in Python is a fundamental concept that is useful in many applications. Python provides two types of copying- shallow copying and deep copying. Shallow copying creates a new object that references the original object, while deep copying creates a new object that is entirely independent of the original object.

In this article, we explored how to copy in Python using shallow copying and deep copying. We also looked at some code examples to illustrate the difference between shallow copying and deep copying.

As a Python developer, it is essential to understand the concept of copying and how it works in Python. Copying is a powerful tool that can help you create new objects and manipulate data without affecting the original object.

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