How to copy a dictionary in Python?

Table of Contents

Introduction

Copying a dictionary in Python is a common task when you want to duplicate a dictionary without affecting the original one. Whether you need a shallow copy or a deep copy, Python provides various methods to achieve this. Understanding how to copy dictionaries effectively ensures that your code remains robust, especially when dealing with mutable objects.

Methods to Copy a Dictionary

Using the copy() Method (Shallow Copy)

The copy() method is a built-in function that creates a shallow copy of a dictionary. A shallow copy means that the copied dictionary is independent of the original dictionary; however, if the dictionary contains nested objects (like lists or other dictionaries), those objects are shared between the original and the copied dictionary.

Example:

Using dict() Constructor (Shallow Copy)

The dict() constructor can also be used to create a shallow copy of a dictionary. It functions similarly to the copy() method.

Example:

Using copy.deepcopy() (Deep Copy)

For a deep copy, where nested objects are also fully copied (not shared), the copy.deepcopy() function from the copy module is used. This method ensures that all levels of the dictionary are copied independently.

Example:

Practical Examples

Example 1: Backup Configuration Settings

You might want to create a copy of configuration settings before modifying them, ensuring that you can revert to the original settings if needed.

Example 2: Safeguarding Data in Nested Structures

When dealing with deeply nested dictionaries, using copy.deepcopy() ensures that all modifications are isolated to the copy, preventing unintended side effects.

Conclusion

Copying a dictionary in Python can be done using various methods, depending on whether you need a shallow or deep copy. The copy() method and dict() constructor are ideal for shallow copies, while copy.deepcopy() is essential for deep copying, especially when dealing with nested structures. Understanding these methods allows you to work with dictionaries more effectively, ensuring that your data remains intact and unmodified when necessary.

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