Python Functions: Writing Your First Function

Introduction

Python is one of the most popular leading programming languages. A Python function is a piece of code that performs some action when called. It accepts parameters and can be reused wherever necessary. The Python Function allows the coders to structure and organize the code proficiently. It helps in making the code easier to debug and modify applications.

The Python functions are mainly essential for efficient coding because it has the following advantages in code creation.

• Code Reusability: The primary use of Python Functions is to prevent the repetition of code. It is written once with parameters and reused wherever it is called for use.
• Modularity: Python Functions are mainly used to break down complex code into smaller code blocks. This makes the code well-structured and organized.
• Readability: As Python functions are well organized, it is easier to read and understand through code.
• Easier Debugging: Errors and defects are easier to debug and fix in the code without much complexity.

Python functions are widely used in most real-world applications. Some of them are Machine learning, statistics cleaning, data analysis, web and game development, API interactions, file automation and so on.

The Basics of Python Functions: How They Work

In Python, Functions are defined with the keyword “def” followed by a function name. It takes input in the form of parameters and returns the output in the form of data or action. Like other coding languages, It also supports default, keyword, and variable length arguments. The main advantage of Python functions is code reusability and maintainability.

Python Functions are defined in two forms namely, Built-in function and User-Defined function. Built-in functions are predefined functions stored in the Python library for coders to use directly. Some of the Built-in functions are id(), input(), bool(), abs() and max(). User-defined functions are defined using the “def” keyword by the coders. It is customized based on specific needs. It accepts the arguments as parameters and customizes them according to the place where it is called for use.

Code Example:

# Built-In Function
print(len (“ Welcome Everyone”))

#User-defined Function
def greeting(name):
    return f"Hello, {name}!"

print(greeting("TuteDude"))

#Output
Welcome Everyone
Hello TuteDude

Hence Python Functions are used in modular programming to improve code reusability and thereby enhance clarity.

Writing Your First Python Function

The step-by-step guide for defining a Python function is as follows:

1. Start with the def keyword followed by the name of the function and parentheses “()”
2. Define the parameters inside the parentheses if needed to accept input values. [Optional]
3. Set default value for parameters if no inputs are added. [Optional]
4. Write a function body with an indentation.
5. Add a return statement to send a result back to the caller.
6. Call in the function by using its name and parentheses.

Structure of Python Function

def function_name(parameters):
    """ Optional describing the function."""

    # Function body
    return result # Optional return statement

Once it is defined globally, Functions are needed to be called wherever necessary. The best practices for calling a function in Python are as follows:

1. Call the function using parentheses ().
2. Arguments are passed correctly if the function requires parameters
3. Make sure the functions are properly intended.

Structure of Calling a Python Function

#Without arguments
function_name()

#With arguments
function_name(arguments)

Understanding Python Function Parameters and Arguments

Python Functions accept different types of parameters and arguments which allow more flexibility in coding, making them more customized and reuseable. Parameters are the variables listed inside the function definition. Arguments are the values actually passed into the function when it is called.

There are four types of arguments in Python. They are

• Positional arguments
• Keyword arguments
• Default arguments
• Variable-length arguments

Positional Arguments: The argument passed in the same parameter order as defined in the function definition is called a positional arguments. Change in the order of passing the argument may result in functional error.

Keyword Arguments: The argument passed with a parameter name without considering the parameter order is called a keyword argument. Here the change in the order of arguments doesn’t change the code function.

Positional vs. Keyword Arguments: On Keyword Arguments, though you change the order of passing the arguments, the output remains the same. But in Positional arguments, changing the order of passing the arguments results in different outputs for different changes in order or sometimes may lead to a code error.

Keyword argument will result in correct output whereas positional argument may result in false output due to a change in argument order.

Code Example:

def register(name, course):
    print(f"My name is {name} and I have enrolled in the {course} course.")

    introduce("John", Python) # Positional arguments
    introduce(course=”MERN Stack”, name="Bob") # Keyword arguments

#Output
My name is John and I have enrolled in the Python course.
My name is Bob and I have enrolled in the MERN Stack course.

Working with Default Arguments in Python Functions

Python helps to give default values to parameters during function definition if needed. If the Python function is called without any arguments, it will take the default parameter value as arguments to perform the function.

The structure of default parameter values in Python Functions is as follows:
def function_name(parameter1 = value, parameter2 = value)

Code Example:

def register(name, course=”Python”):
    print(f"My name is {name} and I have enrolled in the {course} course.")
    introduce("John")

Output:
My name is John and I have enrolled in the Python course.

Variable-Length Arguments

Variable-length arguments are handled with two keywords *args and **kwargs. Arbitrary positional argument (*args) allows a Python function to enter multiple positional arguments.
The function accepts them as tuples.

Arbitrary keyword argument (**kwargs) allows a python function to enter multiple keyword arguments. The function accepts them as a library.

Code Example:

def course_reg(**data):
    for key, value in data.items():
         print(f"{key}: {value}")
 
def fees(*numbers):
    return sum(numbers)
 
# Calling the function with different details
course_reg(Name="Mary", Age=30, City="Canada")
 
print(“Fees: {fees(20, 40, 60, 80)} )
 
#Output
Name: Mary
Age: 30
City: Canada
Fees: 200

Return Statements and Function Outputs

In the Python function, the return statement allows us to process the data and provide meaningful output. It also allows the result to be sent back from the function to the caller.

Using return statement: Python functions can return any type of data such as a number, string, list or some other function.

Code Example:

def halved(a, b):
    return a/2 + b/2

result = halved(6 , 4)
print("Half:", result) 

#Output
Half: 5

Returning Multiple values

Python functions can return multiple values using tuples.

Code Example:

def get_students():
    name = "Tim"
    age = 30
    return name, age

student_name, student_age = get_details()
print(f"Name: {student_name}, Age: {student_age}")

#Output
Name: Tim, Age: 30

Return vs Print in Python Functions: Key Differences

If the function has no return statement, then it automatically returns no values to the caller. However, It prints the data defined in the function

Code Example:

def greeting():
    print(“Welcome”)

#Output
Welcome

Best Practices for Writing Clean, Efficient Python Functions

• Choose the function name meaningfully which clearly explains the function use.
• Use lowercase letters with an underscore for the larger function name.
• A function should do only one task by breaking a complex function into smaller code for better reusability.
• Docstring should be used for better function documentation.
• Use default parameter values for better results.
• Avoid global variables inside the function.
• Use the return statement instead of using the print function in the function definition.
• Write coding to handle errors using try-catch methods.
• Ensure correct indentation to avoid common function pitfalls.
• Use list comprehension instead of loop for efficient function.

Conclusion

Python function helps to avoid code redundancy thereby improving readability and reusability. The different types of arguments help to enhance flexibility. Hence writing the best Python function ensures clean and maintainable code.

There are still a lot of Python higher functions available for learning and application such as lambda function for expression, higher-order functions like map(), filter(), and decorators to change the behavior of functions or methods.

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