Primitive Data Types vs Non Primitive Data Types in Python

Last Updated : 28 Oct, 2025

Python is a versatile, dynamic language. While it doesn’t explicitly categorize data types as “primitive” or “non-primitive” like Java, understanding these concepts helps organize and manage data efficiently.

Primitive Data Types

Primitive data types are the basic building blocks in Python. They store single values and are immutable, meaning their values cannot be changed after creation.

Examples:

Integer (int): whole numbers

x = 10

Float (float): decimal numbers

y = 10.5

Boolean (bool): True or False values

is_active = True

String (str): sequence of characters

name = "Alice"

Example Code

Python

x = 10 y = 10.5 is_active = True name = "Alice" print(type(x)) print(type(y)) print(type(is_active)) print(type(name))

Output

<class 'int'>
<class 'float'>
<class 'bool'>
<class 'str'>

Non-Primitive Data Types

Non-primitive data types can store multiple values or complex structures. They are generally mutable, meaning their contents can be changed.

Examples:

List (list) – ordered collection of items

numbers = [1, 2, 3, 4]

Tuple (tuple) – ordered collection, immutable but can store multiple items

coordinates = (10.0, 20.0)

Dictionary (dict) – collection of key-value pairs

person = {"name": "Alice", "age": 30}

Set (set) – unordered collection of unique items

unique_numbers = {1, 2, 3, 4}

Example Code:

Python

numbers = [1, 2, 3, 4] coordinates = (10.0, 20.0) person = {"name": "Alice", "age": 30} unique_numbers = {1, 2, 3, 4} print(type(numbers)) print(type(coordinates)) print(type(person)) print(type(unique_numbers))

Output

<class 'list'>
<class 'tuple'>
<class 'dict'>
<class 'set'>

Differences Between Primitive and Non-Primitive Data Types

Feature	Primitive Data Types	Non-Primitive Data Types
Mutability	Immutable	Mutable (tuple is immutable but non-primitive)
Data Representation	Represents a single value	Can represent multiple values or structured data
Example Types	int, float, bool, str	list, tuple, dict, set
Memory Allocation	Less memory, as they are simpler	More memory, can store complex data
Methods and Operations	Limited operations and methods	Rich set of methods and operations
Copying	Copying creates new instances	Can create shallow or deep copies
Use Case	Simple data, basic calculations	Complex data structures, collections

When to Use Primitive and Non-Primitive Data Types

Primitive:

Simple data storage (numbers, booleans, strings)
High-performance needs
Basic operations (arithmetic, logic)

Non-Primitive:

Store collections of data
Need mutability for updates
Represent complex relationships (e.g., dictionaries, sets, or tuples)

Python Data Types
Inbuilt Data Structures in Python

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Primitive Data Types vs Non Primitive Data Types in Python