Python – Copy Dictionaries

Welcome to The Coding College, your go-to platform for mastering programming concepts! In this tutorial, we’ll learn how to copy dictionaries in Python. Copying dictionaries is a critical task when working with mutable data structures, ensuring you preserve or replicate your data as needed.

Why Copy Dictionaries?

In Python, dictionaries are mutable, meaning changes to one dictionary can inadvertently affect others if they reference the same memory. Copying dictionaries allows you to create an independent replica, safeguarding your data integrity.

Methods to Copy Dictionaries

Python offers several ways to copy dictionaries, including:

  1. Using the copy() Method
  2. Using the dict() Constructor
  3. Using Dictionary Comprehension
  4. Using the copy Module for Deep Copies

Let’s dive into each method with examples.

1. Copying with the copy() Method

The copy() method creates a shallow copy of the dictionary.

Example:

original = {"name": "Alice", "age": 25}  

# Create a copy  
copied = original.copy()  

# Modify the copy  
copied["age"] = 30  

print("Original:", original)  # Output: {'name': 'Alice', 'age': 25}  
print("Copied:", copied)      # Output: {'name': 'Alice', 'age': 30}

Note: A shallow copy replicates the top-level dictionary but does not duplicate nested objects.

2. Copying with the dict() Constructor

The dict() constructor can also create a shallow copy.

Example:

original = {"name": "Alice", "age": 25}  

# Create a copy  
copied = dict(original)  

print("Original:", original)  
print("Copied:", copied)

This method works similarly to the copy() method and is useful for creating a new dictionary with the same key-value pairs.

3. Copying with Dictionary Comprehension

For more control, you can use dictionary comprehension to copy dictionaries.

Example:

original = {"name": "Alice", "age": 25}  

# Create a copy using dictionary comprehension  
copied = {key: value for key, value in original.items()}  

print("Original:", original)  
print("Copied:", copied)

This method is especially helpful if you need to filter or transform data during copying.

4. Creating Deep Copies with the copy Module

A deep copy duplicates the dictionary and all nested objects, ensuring complete independence from the original. Use the copy.deepcopy() method for this.

Example:

import copy  

original = {"name": "Alice", "details": {"age": 25, "city": "New York"}}  

# Create a deep copy  
deep_copied = copy.deepcopy(original)  

# Modify the nested dictionary in the copy  
deep_copied["details"]["age"] = 30  

print("Original:", original)       # Output: {'name': 'Alice', 'details': {'age': 25, 'city': 'New York'}}  
print("Deep Copied:", deep_copied) # Output: {'name': 'Alice', 'details': {'age': 30, 'city': 'New York'}}

Shallow Copy vs. Deep Copy

  • Shallow Copy: Copies only the top-level structure. Changes to nested objects in the copy affect the original.
  • Deep Copy: Copies the entire dictionary, including all nested objects, ensuring full independence.

Example: Shallow Copy Pitfall

original = {"data": [1, 2, 3]}  

# Create a shallow copy  
shallow_copied = original.copy()  

# Modify the nested list  
shallow_copied["data"].append(4)  

print("Original:", original)       # Output: {'data': [1, 2, 3, 4]}  
print("Shallow Copied:", shallow_copied)  # Output: {'data': [1, 2, 3, 4]}

Solution: Use copy.deepcopy() for nested structures.

Practice Exercises

Exercise 1: Shallow Copy

Create a shallow copy of the dictionary:

car = {"brand": "Toyota", "model": "Corolla", "year": 2020}
  • Modify the copy and verify the original remains unchanged.

Exercise 2: Deep Copy

Given the nested dictionary:

person = {"name": "John", "info": {"age": 30, "city": "London"}}
  • Create a deep copy and modify the nested dictionary. Ensure the original is unaffected.

Exercise 3: Copy and Filter Data

Using dictionary comprehension, create a copy of the following dictionary but exclude keys with numeric values less than 20:

numbers = {"a": 10, "b": 30, "c": 20}

Why Learn with The Coding College?

At The Coding College, we prioritize practical learning. By mastering dictionary copying techniques, you’ll handle Python data structures more efficiently, avoiding common pitfalls like unintended side effects.

Conclusion

Copying dictionaries is a vital Python skill, especially when managing mutable data. Whether you need a shallow copy for quick duplication or a deep copy for complex nested data, Python offers tools to suit your needs.

Leave a Comment