difference between positional and keyword arguments

1. Positional Arguments

How they work: The arguments you pass are matched to the function’s parameters based solely on their order (i.e., their position). The first argument is assigned to the first parameter, the second to the second, and so on.

Example:

python

def describe_pet(animal_type, pet_name):
    """Display information about a pet."""
    print(f"\nI have a {animal_type}.")
    print(f"My {animal_type}'s name is {pet_name}.")

# Positional argument passing
describe_pet('hamster', 'Harry')

Output:

text

I have a hamster.
My hamster's name is Harry.
  • 'hamster' (1st argument) is assigned to animal_type (1st parameter).
  • 'Harry' (2nd argument) is assigned to pet_name (2nd parameter).

What happens if you mess up the order?
You get logical errors that can be hard to debug.

python

describe_pet('Harry', 'hamster') # Oops! Wrong order.

Output:

text

I have a Harry.
My Harry's name is hamster. # This is nonsense.

2. Keyword Arguments

How they work: You explicitly name each argument when you call the function using the syntax parameter_name=value. This means the order of the arguments does not matter.

Example:

python

def describe_pet(animal_type, pet_name):
    """Display information about a pet."""
    print(f"\nI have a {animal_type}.")
    print(f"My {animal_type}'s name is {pet_name}.")

# Keyword argument passing
describe_pet(animal_type='hamster', pet_name='Harry')
describe_pet(pet_name='Harry', animal_type='hamster') # Order doesn't matter!

Output (for both calls):

text

I have a hamster.
My hamster's name is Harry.

Why use them?

  1. Clarity: It’s immediately clear what each value represents.
  2. Flexibility: You can specify arguments in any order.
  3. Skipping Defaults: They are essential when you want to use a default value for an early parameter but provide an argument for a later one.

3. Mixing Positional and Keyword Arguments

You can mix both styles in a single function call, but there is one strict rule:

Positional arguments must come before any keyword arguments.

Example:

python

def describe_pet(animal_type, pet_name, age):
    """Display information about a pet."""
    print(f"\nI have a {animal_type} named {pet_name}. It is {age} years old.")

# Valid: Two positional, one keyword
describe_pet('hamster', 'Harry', age=3)

# Valid: One positional, two keyword
describe_pet('hamster', pet_name='Harry', age=3)
describe_pet('hamster', age=3, pet_name='Harry') # Order of keywords doesn't matter

# INVALID: Keyword before positional
# describe_pet(animal_type='hamster', 'Harry', 3) # This will cause a SyntaxError

4. Practical Example: The print() Function

The built-in print() function is a perfect example of these concepts in action. Its signature looks conceptually like this:
print(*objects, sep=' ', end='\n', file=sys.stdout, flush=False)

  • *objects: Takes any number of positional arguments.
  • sependfileflush: Are all keyword-only parameters with default values.

python

# Using only positional arguments
print('Hello', 'World', '!') # Output: Hello World !

# Using a mix of positional and keyword arguments
print('Hello', 'World', sep='-') # Output: Hello-World
print('Hello', end=' ') # Changes the end character from newline to a space
print('World')           # Output: Hello World (on the same line)

Summary & Key Differences

FeaturePositional ArgumentsKeyword Arguments
BasisOrder (Position)Name (Keyword)
Syntaxfunction(value1, value2)function(param1=value1, param2=value2)
Order ImportanceCritical. Wrong order causes errors.Irrelevant. Order doesn’t matter.
ClarityLess clear. You must know the parameter order.Very clear. Acts as built-in documentation.
Use CaseFor required parameters where the meaning is obvious (e.g., add(x, y)).For optional parameters, parameters with defaults, or to improve readability.
Rule in a CallMust be listed before keyword arguments.Must be listed after positional arguments.

Best Practice: For functions with more than two or three parameters, or parameters that aren’t immediately obvious, use keyword arguments to make your code self-documenting and much easier to read and maintain.

Similar Posts

  • Functions as Parameters in Python

    Functions as Parameters in Python In Python, functions are first-class objects, which means they can be: Basic Concept When we pass a function as a parameter, we’re essentially allowing one function to use another function’s behavior. Simple Examples Example 1: Basic Function as Parameter python def greet(name): return f”Hello, {name}!” def farewell(name): return f”Goodbye, {name}!” def…

  • Dictionaries

    Python Dictionaries: Explanation with Examples A dictionary in Python is an unordered collection of items that stores data in key-value pairs. Dictionaries are: Creating a Dictionary python # Empty dictionary my_dict = {} # Dictionary with initial values student = { “name”: “John Doe”, “age”: 21, “courses”: [“Math”, “Physics”, “Chemistry”], “GPA”: 3.7 } Accessing Dictionary Elements…

  • Basic Character Classes

    Basic Character Classes Pattern Description Example Matches [abc] Matches any single character in the brackets a, b, or c [^abc] Matches any single character NOT in the brackets d, 1, ! (not a, b, or c) [a-z] Matches any character in the range a to z a, b, c, …, z [A-Z] Matches any character in the range A to Z A, B, C, …, Z [0-9] Matches…

  • Tuples

    In Python, a tuple is an ordered, immutable (unchangeable) collection of elements. Tuples are similar to lists, but unlike lists, they cannot be modified after creation (no adding, removing, or changing elements). Key Features of Tuples: Syntax: Tuples are defined using parentheses () (or without any brackets in some cases). python my_tuple = (1, 2, 3, “hello”) or (without…

  • What is Quantum Computing? A Beginner’s Guide to the Future of Technology

    What is Quantum Computing? Quantum computing is a revolutionary approach to computation that leverages the principles of quantum mechanics to perform complex calculations far more efficiently than classical computers. Unlike classical computers, which use bits (0s and 1s) as the smallest unit of information, quantum computers use quantum bits (qubits), which can exist in multiple…

  •  List operators,List Traversals

    In Python, lists are ordered, mutable collections that support various operations. Here are the key list operators along with four basic examples: List Operators in Python 4 Basic Examples 1. Concatenation (+) Combines two lists into one. python list1 = [1, 2, 3] list2 = [4, 5, 6] combined = list1 + list2 print(combined) # Output: [1, 2, 3,…

Leave a Reply

Your email address will not be published. Required fields are marked *