Skip to main content

Functions in Python

 

Learning Sections     show

Functions in Python

Functions in Python are reusable blocks of code that perform a specific task. They help in organizing code into manageable sections and avoid repetition. Functions are defined using the def keyword followed by the function name and parentheses ().

Defining a Function

A function is defined using the def keyword. Here's a simple example of a function that takes a parameter and prints a greeting message:


# Defining a function
def greet(name):
    # Function body
    print("Hello, " + name + "!")

# Calling the function
greet("Alice")  # Output: Hello, Alice!
    

Return Statement

The return statement is used to return a value from a function. If no return statement is used, the function returns None by default.


# Function with return statement
def add(a, b):
    return a + b

# Calling the function
result = add(5, 3)
print(result)  # Output: 8
    

Default Arguments

Functions can have default argument values, which are used if no value is provided when the function is called.


# Function with default arguments
def greet(name, message = "Hello"):
    print(message + ", " + name + "!")

# Calling the function
greet("Alice")  # Output: Hello, Alice!
greet("Bob", "Good morning")  # Output: Good morning, Bob!
    

Variable-Length Arguments

Functions can accept a variable number of arguments using the *args and **kwargs syntax.


# Function with *args
def sum_all(*args):
    total = 0
    for num in args:
        total += num
    return total

# Calling the function
result = sum_all(1, 2, 3, 4)
print(result)  # Output: 10
    

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

# Calling the function
print_info(name="Alice", age=25, city="Wonderland")
    

Lambda Functions

Lambda functions are small anonymous functions defined using the lambda keyword. They are useful for short, throwaway functions.


# Lambda function
square = lambda x: x ** 2

# Using the lambda function
print(square(5))  # Output: 25
    

Popular posts from this blog

Introduction to OOPs in Python

  Learning Sections          show Introduction to Object-Oriented Programming (OOP) Object-Oriented Programming (OOP) is a programming paradigm that organizes software design around objects rather than actions and data rather than logic. It revolves around the concept of "objects", which are instances of classes. These objects encapsulate data, in the form of attributes or properties, and behaviors, in the form of methods or functions. OOP promotes modularity, reusability, and extensibility in software development. Key Concepts of OOP: Class: A class is a blueprint or template for creating objects. It defines the attributes (data) and methods (functions) that will characterize any object instantiated from that class. Object: An object is an instance of a class. It is a concrete realization of the class blueprint, containing actual values instead of placeholders for attributes. Encapsulation: Encapsulation is ...

Classes and Objects in Python

  Learning Sections          show Classes and Objects in Python In Python, a class is a blueprint for creating objects. An object is an instance of a class. Classes allow you to logically group data and functions in a way that is easy to manage and reuse. 1. Defining a Class To define a class in Python, you use the class keyword followed by the class name and a colon. Inside the class, you can define attributes and methods. Example: # Define a class class Person : # Class attribute species = 'Human' # Class method def greet ( self ): return 'Hello, I am a person.' # Create an object of the class person1 = Person () # Access class attribute print ( person1 . species ) # Output: Human # Call class method print ( person1 . greet ()) # Output: Hello, I am a person. 2. Creating Objects To create an object of a class, you simply call the class name followed by paren...

Exception Handling in Python

  Learning sections          show Exception Handling in Python Exception handling in Python is done through the use of try , except , else , and finally blocks. This allows you to catch and handle errors gracefully. Below are some examples and explanations: 1. Basic Try-Except The try block lets you test a block of code for errors. The except block lets you handle the error. # Example of basic try-except try : result = 10 / 0 except ZeroDivisionError : print ( "Cannot divide by zero!" ) # Output: # Cannot divide by zero! 2. Handling Multiple Exceptions You can catch multiple exceptions by specifying multiple except blocks. # Example of handling multiple exceptions try : result = 10 / 0 except ZeroDivisionError : print ( "Cannot divide by zero!" ) except TypeError : print ( "Invalid operation!" ) # Output: # Cannot divide by zero! 3. Using Else The e...