Functions

Functions allow programmers to organise code into reusable components. A function groups a set of related instructions under a single name. Once the function has been defined, it can be called whenever that task needs to be performed again.

Functions are important because they make programs shorter, clearer and easier to maintain. Most Python libraries are built around functions and methods that perform specialised tasks.

Creating a Simple Function

A function is defined using the def keyword. The indented lines below the function definition form the function body.

# Define a simple function

def welcome():
    print("Welcome to Python.")
    print("Functions help organise code.")
    print("This function prints three lines.")

# Call the function
welcome()

Functions with Parameters

Parameters allow information to be passed into a function. This makes the same function work with different inputs.

# A function with one parameter

def calculate_square(number):
    result = number ** 2
    print("Input:", number)
    print("Square:", result)

calculate_square(5)
calculate_square(12)

Returning Values

Many functions return a value rather than printing directly. Returning values allows the output of one function to be used in later calculations.

# A function that returns an average

def average(a, b, c):
    result = (a + b + c) / 3
    return result

student_average = average(72, 81, 77)

print("Average mark:", student_average)

Recursive Functions

A recursive function is a function that calls itself. Recursion is useful when a problem can be broken down into smaller versions of the same problem. Every recursive function needs a base case, which stops the recursion, and a recursive case, which calls the function again.

# Recursive factorial function

def factorial(n):
    # Base case: stop when n is zero
    if n == 0:
        return 1

    # Recursive case: call the function again
    return n * factorial(n - 1)

print(factorial(5))

Fibonacci Sequence

The Fibonacci sequence is a classic example of recursion. Each number is the sum of the two previous numbers. The first two values are usually defined as 0 and 1.

# Recursive Fibonacci function

def fibonacci(n):
    # Base cases
    if n <= 1:
        return n

    # Recursive case
    return fibonacci(n - 1) + fibonacci(n - 2)

for i in range(10):
    print(fibonacci(i))

Recursive Sum

A recursive sum adds a number to the sum of all smaller positive integers. This example shows how recursion can represent a mathematical definition directly.

# Add all numbers from 1 to n recursively

def recursive_sum(n):
    # Base case
    if n == 1:
        return 1

    # Recursive case
    return n + recursive_sum(n - 1)

print(recursive_sum(10))

Recursion versus Loops

Many problems can be solved using either recursion or loops. Loops are often faster and use less memory, while recursion can be clearer when the problem is naturally recursive.

# Iterative version of factorial using a loop

def factorial_loop(n):
    result = 1

    for value in range(1, n + 1):
        result = result * value

    return result

print(factorial_loop(5))

In the next activity, we conclude the session and review the main concepts covered.