Mutable and Immutable in Python – Key Differences

Updated on August 13, 2024

Article Outline

What is a Mutable Object in Python?What is an Immutable Object in Python?Difference Between Mutable and Immutable Objects Conclusion FAQs

In Python, objects can be classified into two categories: mutable and immutable. In simple terms, mutable objects can be changed after they are created, while immutable objects cannot be altered. Everything is an object with a unique ID assigned upon creation. The type of an object is fixed, but its value can be modified if the object is mutable.

For example, a list remains a list, but its elements can be changed. Understanding the difference between mutable and immutable objects is key to managing data effectively and writing robust Python code. In this article, we will understand the difference between the mutable and immutable, with examples for better understanding.

What is a Mutable Object in Python?

In simple terms, a mutable object in Python is something that can be changed after it is created. This means you can modify, add, or remove elements within the object without creating a new object. Lists, dictionaries, and sets are examples of mutable objects.

Example 1: List

A list is a collection of items that can be changed after it is created. You can add, remove, or modify elements in a list.

#Creation of a List

first = [1, 2, 3]

# Modifying the list

first.append(4)    # Adding an element in the List

first.[0] = 10          # Changing an element in the List

print(first)

Output

[10, 2, 3, 4]

Example 2: Set

A set is an unordered collection of unique elements. You can add or remove elements in a set.

# Creation of  a set

first = {1, 2, 3}

# Modifying the set

first.add(4)        # Adding an element in set

first.remove(2)  # Removing an element in set

print(first)

Output

{1, 3, 4}

Example 3: Dictionary

A dictionary is a collection of key-value pairs. You can add, remove, or modify key-value pairs in a dictionary.

# Creation of  a dictionary

first = {'a': 1, 'b': 2}

# Modifying the dictionary

first['c'] = 3       # Adding a new key-value pair in dictionary

first['a'] = 10     # Changing the value of an existing key in the dictionary

del first['b']       # Removing a key-value pair in the dictionary

print(first)

Output

{'a': 10, 'c': 3}

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What is an Immutable Object in Python?

An immutable object in Python is one that cannot be changed once it is created. This means that after you create an immutable object, its content or state remains constant. Common examples of immutable objects are numbers, strings, and tuples.

Example 1: Numbers

Numbers, such as integers and floats, are immutable. Once a number is created, it cannot be changed.

# Creating a number

first = 5                   # Changing the number creates a new object

first = first + 1

print(first)

Output

Example 2: Strings

Strings are sequences of characters and are immutable. Any modification to a string creates a new string.

# Creation of a string

first = "Hello"    # Changing the string creates a new object

second = first + " World"

print(second)

print(first)

Output

Hello World

Hello

Example 3: Tuples

Tuples are ordered collections of elements and are immutable. Once a tuple is created, its elements cannot be changed.

# Creation of  a tuple

first = (1, 2, 3)

first[0] = 10      #this line will raise a TypeError

# Creation of  a new tuple with modified elements

second = first + (4,)

print(first)

print(second)

Output

Error

Difference Between Mutable and Immutable Objects

Features	Mutable Objects	Immutable Objects
Definition	Can be modified after they are created	Cannot be modified after they are created
Modification Behaviour	Changes affect the original object directly	Any change creates a new object with the modified value
Variable References	Multiple variables can refer to the same mutable object, leading to unexpected changes	Immutable objects are thread-safe and can be shared between threads without the risk of unexpected changes
Use Cases	Ideal for dynamic data structures needing frequent updates, like lists or dictionaries	Suitable as dictionary keys or set elements since their values remain constant and always have the same hash value
Performance	Modifying a mutable object can be quicker and use less memory than creating a new object, especially for large data structures	Often used for constants or values that should not change, like numeric values or strings used for formatting messages

Conclusion

In this article, we learned the difference between mutable and immutable objects in Python. Understanding the mutable and immutable objects helps you modify the programme according to the requirements and makes the writing efficient and predictable.

Mutable objects, like lists and dictionaries, can be changed after creation, making them ideal for dynamic data. However, they can cause unintended consequences if multiple variables reference the same object. Immutable objects, like numbers and strings, cannot be altered once created, ensuring thread safety and suitability for dictionary keys and set elements. Recognising when to use each type improves the performance, reliability, and clarity of your Python programmes.

FAQs

What are mutable objects in Python?

In Python, Mutable objects can be changed after they are created. This means mutable objects can modify, add or remove elements within the object without creating a new object. Some examples of mutable objects are lists, dictionaries and sets.

What are immutable objects in Python?

In Python, Immutable objects cannot be changed once they are created. Any operation that appears to change an immutable object actually creates a new object with the modified value. Numbers, strings, and tuples are examples of immutable objects.

Why are immutable objects useful?

Immutable objects are useful because they ensure data integrity and thread safety. Once created, their values cannot be altered, which makes them suitable for use as dictionary keys, elements in sets, or when you need to guarantee that the data will not change unexpectedly.

What are the advantages of using mutable objects?

Mutable objects allow for efficient modification of data structures, especially when dealing with large datasets. They can be faster and more memory-efficient than creating new objects, as changes are made directly to the existing object.

How do mutable and immutable objects impact programme performance?

Mutable objects, such as lists and dictionaries, can be more performant when frequent modifications are required, as they avoid the overhead of creating new objects. Immutable objects, on the other hand, ensure predictable behaviour and are often used for constants or data that should remain unchanged.

Updated on August 13, 2024

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