Master Python Optional Arguments Usage [Tutorial]


Author: Bashir Alam
Reviewer: Deepak Prasad

An argument is a value that is passed to the function when it is called. Sometimes, we need to have optional arguments as well, which means even if we will not pass the values, the program shouldn't return any error. In this tutorial, we will learn about Python optional arguments. We will discuss how we can pass Python optional arguments to the methods using various ways. We will cover default arguments, keyword arguments, and keyword arguments using different examples.

In this comprehensive guide, we will delve into everything you need to know about optional arguments in Python—from the basics like default and keyword arguments to advanced techniques like using *args and **kwargs. By the end of this article, you'll gain an in-depth understanding of Python optional arguments and how to use them effectively in various scenarios.


Getting Started with Python Optional Arguments

In Python, optional arguments allow for more flexible and dynamic function calls. Whether you're a beginner or an experienced developer, understanding Python optional arguments can add another tool to your programming toolbox. Let's dive into the basics.

Syntax of Python Arguments

The syntax for declaring an optional argument is straightforward. When defining a function, you assign a default value to the parameter, using the equals (=) sign.

def greet(name="World"):
    print(f"Hello, {name}!")

In this example, name is an optional argument with a default value of "World".

There are different methods to implement optional arguments in Python, each with its own use case.

  • Default Value Arguments: By specifying a default value, you make the argument optional during a function call.
  • Keyword Arguments: You can also provide arguments by explicitly naming each one, allowing you to skip some optional arguments.
  • Variable-length Arguments: Using *args and **kwargs, you can accept a variable number of positional and keyword arguments, respectively.

1. Using Default Values

Here, b is an optional argument.

def add(a, b=0):
    return a + b

# With both arguments
result1 = add(2, 3)  # Output: 5

# Skipping the optional argument
result2 = add(2)  # Output: 2

2. Using Keyword Arguments

With keyword arguments, you can specify values in any order.

def power(base, exponent=2):
    return base ** exponent

# Using keyword to skip the optional argument
result = power(base=3)  # Output: 9

Here when we can call power(base=3) and it will return 9 because the exponent defaults to 2.

3. Using *args and **kwargs

The *args and **kwargs syntax lets you pass a variable number of arguments to a function:

def func(*args, **kwargs):
    print(args)  # Outputs positional arguments
    print(kwargs)  # Outputs keyword arguments

func(1, 2, x=3, y=4)

We can call this function with any number of positional and keyword arguments. For instance, func(1, 2, x=3, y=4) would print both (1, 2) for args and {'x': 3, 'y': 4} for kwargs.


Intermediate Techniques for Using Optional Arguments

1. Leveraging *args for Python Optional Positional Arguments

One of the powerful features of Python is the use of *args for optional positional arguments. This allows you to pass a variable number of non-keyword arguments to a function. Let's delve into how to use *args effectively in Python optional arguments.

# Using *args to accept multiple arguments
def sum_numbers(*args):
    return sum(args)

# Function calls
print(sum_numbers(1, 2, 3))  # Output: 6
print(sum_numbers(1, 2, 3, 4, 5))  # Output: 15

Example 1: Variable-length tuple arguments

def print_names(*names):
    for name in names:

# Using *args to pass variable number of arguments
print_names("Alice", "Bob", "Charlie")  # Outputs: Alice \n Bob \n Charlie

Example 2: Combining *args with normal arguments

def print_data(title, *data):
    for item in data:

# Using *args with other arguments
print_data("Names:", "Alice", "Bob", "Charlie")  # Outputs: Names: \n Alice \n Bob \n Charlie


2. Utilizing **kwargs in Python for Optional Keyword Arguments

The use of **kwargs in Python opens up even more possibilities for optional arguments, specifically for optional keyword arguments. In this section, we'll explore the syntax and functionality of **kwargs and see how it enriches your Python optional arguments toolkit.

2.1 Syntax and Functionality of **kwargs in Python Optional Arguments

The **kwargs syntax in Python allows you to pass a variable number of keyword arguments to a function. Essentially, it collects additional keyword arguments passed to a function into a dictionary. Here's a basic example:

def print_info(**kwargs):
    for key, value in kwargs.items():
        print(f"{key}: {value}")

# Example function call
print_info(name="Alice", age=30, profession="Engineer")

In the example above, kwargs will be a dictionary containing the items {'name': 'Alice', 'age': 30, 'profession': 'Engineer'}.

2.2 Combining **kwargs with Positional Arguments and *args

You can combine **kwargs with positional arguments and *args. However, **kwargs must appear last in the function definition.

def display_data(title, *args, **kwargs):
    print("Positional arguments:", args)
    print("Keyword arguments:", kwargs)

# Example function call
display_data("User Info", "Alice", "Bob", name="Charlie", age=25)

2.3 Using **kwargs to Extend Functionality

One common use of **kwargs is to extend the functionality of a function, allowing it to accept future optional keyword arguments without changing its interface.

def connect_to_database(host, **options):
    print(f"Connecting to {host}...")
    for option, value in options.items():
        print(f" - {option}: {value}")

# Example function call
connect_to_database("localhost", port=3306, user="admin", password="secret")


Advanced Approaches to Python Optional Arguments

1. Mixing Positional and Keyword Arguments Effectively

Understanding how to mix positional and keyword arguments effectively is crucial for leveraging the full power of Python optional arguments. While Python offers considerable flexibility in how you call functions, there are certain rules and best practices that help you combine these types of arguments seamlessly.

1.1 Rules for Combining Types of Arguments in Python Optional Arguments

When it comes to function definitions in Python, the general rule for combining various types of arguments is:

  • Positional arguments must come before *args
  • *args must come before keyword arguments
  • Keyword arguments must come before **kwargs

Here is a simple example to demonstrate the rules:

def example_function(arg1, arg2, *args, kwarg1="default", **kwargs):

In this example, arg1 and arg2 are positional arguments, *args catches additional optional positional arguments, kwarg1 is a keyword argument with a default value, and **kwargs captures additional optional keyword arguments.

1.2 Real-world Python Examples of Mixing Positional and Keyword Arguments

Dynamic Function Calls

Combining positional and keyword arguments allows for more dynamic function calls, as seen in the Python built-in print function.

print("Hello", "world", sep="-", end="!")
# Output: Hello-world!

In this example, print uses positional arguments to define what to print, and keyword arguments sep and end to customize the output.

Flexible Database Connection

Let's say you are working on a function that connects to a database. Using a combination of positional and keyword arguments makes the function extremely flexible.

def connect_to_database(host, port, *queries, username="root", password="", **config_options):
    print(f"Connecting to {host}:{port}...")
    # of the function

# Example function call
connect_to_database("localhost", 3306, "SELECT * FROM users;", username="admin", timeout=30)

In this example, host and port are positional arguments, *queries captures optional SQL queries, username and password are keyword arguments with default values, and **config_options captures additional optional configuration settings.


2. Argument Unpacking with * and ** in Python Functions

Argument unpacking using * and ** in Python functions serves as a powerful feature for handling Python optional arguments. It allows you to pass multiple arguments easily and adds flexibility to how functions are called. In this section, we will explore the use of these unpacking operators in the context of Python optional arguments.

2.1 How Unpacking Enhances Optional Arguments in Python

Using the * and ** operators allows you to unpack iterable and mapping objects like lists and dictionaries into function arguments. This mechanism makes it easier to work with python optional arguments in dynamic scenarios. You can handle varying numbers of arguments more conveniently, improving the flexibility of your Python code.

Here's an example to highlight the use of argument unpacking in function calls:

# Function definition
def sample_function(a, b, c):
    print(a, b, c)

# List and dictionary containing arguments
arg_list = [1, 2]
arg_dict = {'c': 3}

# Unpacking arguments
sample_function(*arg_list, **arg_dict)  # Output: 1 2 3

2.2 Python Code Examples for Argument Unpacking in Optional Args

Unpacking Lists into Positional Arguments

You can unpack a list or a tuple into positional arguments using the * operator.

# Function to sum numbers
def sum_numbers(a, b, c):
    return a + b + c

# List of arguments
args = [1, 2, 3]

# Unpacking list into function
result = sum_numbers(*args)  # Output will be 6

Unpacking Dictionaries into Keyword Arguments

Dictionaries can be unpacked into keyword arguments using the ** operator.

# Function to display user information
def display_user(name, age, profession):
    print(f"{name}, aged {age}, is a {profession}")

# Dictionary of arguments
kwargs = {'name': 'Alice', 'age': 30, 'profession': 'Engineer'}

# Unpacking dictionary into function
display_user(**kwargs)  # Output: Alice, aged 30, is a Engineer

Combining Positional and Keyword Argument Unpacking

You can combine both positional and keyword argument unpacking in a single function call for maximum flexibility.

# Function to connect to a database
def connect_to_database(host, port, username="root", password=""):
    print(f"Connecting to {host}:{port} as {username}")

# List and dictionary of arguments
args = ["localhost", 3306]
kwargs = {'username': 'admin', 'password': 'secret'}

# Unpacking both list and dictionary into function
connect_to_database(*args, **kwargs)  # Output: Connecting to localhost:3306 as admin


3. Implementing None as a Smart Default Value

In Python, using None as a default value for function arguments offers a versatile approach to handle python optional arguments. This practice has distinct advantages, especially when you want to signal that a function parameter is optional. In this section, we will discuss why and when to use None as a default value, along with Python best practices.

3.1 Why and When to Use None in Python Optional Arguments

Utilizing None as a default value in function parameters allows you to distinguish between a caller who has not provided a value for an argument and a caller who has explicitly provided a None value. This makes None a smart choice for default values in python optional arguments.

When should you use None?

  • When you want to make the argument optional without assuming any default behavior.
  • When the actual default value is mutable, and you want to avoid the potential pitfalls associated with mutable default values.

Here's a simple example:

def greet(name=None):
    if name is None:
        print("Hello, World!")
        print(f"Hello, {name}!")

3.2 Python Best Practices for Using None in Optional Args

Use Immutable Default Values: In Python, default values are evaluated only once, so using mutable default values like lists or dictionaries can lead to unexpected behavior. Using None avoids this issue.

# Avoid this
def add_item(value, items=[]):
    return items

# Do this
def add_item(value, items=None):
    if items is None:
        items = []
    return items

Explicitly Check for None: Always use is None or is not None to check if an optional argument has been provided.

def process_data(data=None):
    if data is None:
        # Initialize default data
        data = []
    # Continue processing


Using Optional Parameters in Popular Python Libraries

The use of optional parameters is widespread in many popular Python libraries, offering both flexibility and functionality to end-users. In this section, we explore how python optional arguments are implemented in three such libraries: NumPy, pandas, and Django.


1. NumPy Optional Arguments

NumPy, a library for numerical computations, makes extensive use of Python optional arguments to provide flexibility in functions.


numpy.linspace(start, stop, num=50, endpoint=True)

Here, start and stop are mandatory arguments, while num and endpoint are optional.

import numpy as np

# Using only mandatory arguments
array1 = np.linspace(0, 1)

# Using optional arguments
array2 = np.linspace(0, 1, num=20, endpoint=False)

In this example, array2 will contain 20 evenly spaced values from 0 to 1, not including the endpoint because we set endpoint=False.


2. pandas Optional Arguments

The pandas library, popular for data manipulation and analysis, also employs Python optional arguments effectively.


pandas.read_csv(filepath, delimiter=',', header='infer')

Here, filepath is a mandatory argument, and delimiter and header are optional.

import pandas as pd

# Reading a CSV with only the file path
df1 = pd.read_csv('file.csv')

# Reading a CSV with optional arguments
df2 = pd.read_csv('file.csv', delimiter='\t', header=None)

In df2, we specify a tab delimiter and indicate that there is no header row.


3. Django Optional Arguments

Django, a high-level Python web framework, allows for optional arguments in various functionalities, such as model and form definitions.


models.CharField(max_length, blank=False, null=False)

In this Django model field, max_length is required, while blank and null are optional.

from django.db import models

class UserProfile(models.Model):
    username = models.CharField(max_length=30)
    bio = models.CharField(max_length=500, blank=True)

In this example, the bio field is optional due to the blank=True optional argument.


Frequently Asked Questions on Python Optional Arguments

What are Python Optional Arguments?

Optional arguments in Python are function parameters that have default values specified. These arguments are optional during a function call, meaning if you don't provide a value for such an argument, the default value will be used.

How do I Declare an Optional Argument in Python?

To declare an optional argument, you assign a default value to a parameter while defining the function. For example, in the function definition def greet(name="World"), name is an optional argument with a default value of "World".

What's the Difference Between Positional and Keyword Arguments?

Positional arguments are the most common and must be passed in order from left to right. Keyword arguments, often used for optional parameters, can be passed in any order by explicitly naming each argument in the function call.

What Are *args and **kwargs?

*args is used to pass a variable-length list of positional arguments. **kwargs is used for passing a variable-length list of keyword arguments. These are often used to make functions more flexible and can be combined with standard positional and keyword arguments.

Can I Use Mutable Default Values Like Lists or Dictionaries?

It's generally not recommended to use mutable default values like lists or dictionaries because they can lead to unexpected behavior. Instead, you can use None and initialize the mutable object within the function.

How Do I Make My Function Accept Any Number of Arguments?

You can use *args to accept any number of positional arguments and **kwargs to accept any number of keyword arguments. For example, the function definition def example(*args, **kwargs) can accept any number of positional and keyword arguments.

What Is Argument Unpacking?

Argument unpacking allows you to pass multiple arguments to a function by unpacking a list or tuple using * or a dictionary using **. For instance, if you have a list args = [1, 2, 3] and a function def sum(a, b, c), you can call sum(*args) to pass all values in the list as separate arguments.

How Do Popular Libraries Like NumPy and Pandas Use Optional Arguments?

Libraries like NumPy and pandas use Python optional arguments to offer more flexible interfaces. For instance, in NumPy's linspace function, you can optionally specify the number of points you want between a range or whether to include the endpoint. Similarly, in pandas' read_csv, you can optionally specify delimiters, headers, and many other reading options.

What Are the Best Practices for Using Optional Arguments?

Some best practices include using immutable types like None for default values, clearly documenting the function's behavior with Python optional arguments, and being cautious when combining *args and **kwargs with positional and keyword arguments.



Understanding Python optional arguments is critical for writing flexible and efficient code. In this comprehensive guide, we've delved into the basics of optional arguments, the syntax, and best practices. We've also looked at advanced techniques involving *args and **kwargs, as well as practical examples from popular Python libraries like NumPy, pandas, and Django. These concepts serve as essential tools for both beginners and experienced Python developers to write versatile functions that can adapt to various needs.


Additional Resources


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Bashir Alam

Bashir Alam

He is a Computer Science graduate from the University of Central Asia, currently employed as a full-time Machine Learning Engineer at uExel. His expertise lies in Python, Java, Machine Learning, OCR, text extraction, data preprocessing, and predictive models. You can connect with him on his LinkedIn profile.

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