Functions

A function is a reusable block of code that performs a single task and can be used repeatedly in programs.

What is a Function?

In Python, a basic function can be declared as follows:

def add_numbers(a:int, b:int) -> int:
    return a+b

In the above example, the following items should be noted:

• The def keyword declares the start of a function
• The name of this function is add_numbers
• The function accepts two arguments, a and b.
  • Each argument can be labelled to show the expected data type (i.e. a:int shows that the a argument is expecting an int).
  • The -> int declares that the function will return an integer (see below).
• Similar to other Python constructs, the declaration line ends with a colon (:).
• In standard circumstances, a Python function will return a value

Functions Are Repeatable

Functions are useful for repeated actions. A famous principle of software development is “Don’t Repeat Yourself” (aka DRY code). As an example, writing the same message to multiple users could be performed as follows:

user1 = "Carl"
user2 = "Jim"
user3 = "Fred"

print("Greetings " + user1 + ", welcome to this program.")
print("Greetings " + user2 + ", welcome to this program.")
print("Greetings " + user3 + ", welcome to this program.")

The same lines are being repeated over and over. This could be re-written as a function:

def greet(user:str) -> str:
    return "Greetings " + user + ", welcome to this program."

user1 = "Carl"
user2 = "Jim"
user3 = "Fred"

print(greet(user1))
print(greet(user2))
print(greet(user3))

Both examples will have the same output, but using the function will require less effort from the programmer and will be much more robust and maintainable.

Looping Over a Function

There are often scenarios where we must execute a function multiple times with different inputs. This repetitive task can be efficiently accomplished using a for loop.

Consider a situation where you have a function that performs a specific task or computation, and you need to apply this function to a collection of values or items. Instead of manually calling the function for each input, which can be tedious and error-prone, you can harness the for loop’s capabilities to automate this process. Looping over a function allows you to:

• Reuse Code: You can encapsulate a specific functionality within a function and then effortlessly apply it to multiple data points without duplicating code.
• Efficiency: Automating repetitive tasks enhances code efficiency, making it easier to maintain and less prone to errors.
• Scalability: As your data set grows, using loops to apply a function becomes indispensable, ensuring your code remains adaptable to various input sizes.

Let’s illustrate this concept with an example using a temperature conversion function, celsius_to_kelvin(), which converts Celsius temperatures to Kelvin:

def celsius_to_kelvin(cels):
    return cels + 273.15

for temperature in [9.1, 8.8, -270.15]:
    print(celsius_to_kelvin(temperature))

Would result in:

282.25
281.95
3.0

During the loop, celsius_to_kelvin() is executed with the values 9.1, 8.8, and -270.15, respectively, demonstrating the power of automating repetitive tasks through function iteration.