Python Raising Exceptions Tutorial – Complete Guide

The world of programming is full of endless possibilities, particularly when it comes to Python – a versatile and powerful programming language. Among its various aspects, one important technique that you’ll often come across is the concept of ‘Exceptions’ and ‘raising exceptions’.

What is Python Raising Exceptions?

Python exceptions are events that occur during the execution of a program, indicating that an error has occurred. Raising an exception, meanwhile, is a way for Python to stop normal execution suddenly when certain error conditions are met.

Exceptions allow for flexibility, making it easier to identify errors or abnormal conditions in our code. They provide a way for us to control the flow of the program and prevent it from crashing abruptly upon encountering errors.

Understanding Python exceptions and how to raise them enriches your problem-solving ability in programming. It allows you to write and understand better, efficient, and fault-tolerant code, making you a more skilled programmer overall. Perhaps most importantly, it’s a crucial aspect of Python that you’ll encounter in numerous real-world coding situations, simply because errors are quite common in any kind of program.

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Generating an Exception

Here is a basic example where we attempt to divide a number by zero. Python naturally raises a ZeroDivisionError exception.

try:
    x = 5 / 0
except ZeroDivisionError:
    print("Sorry, you can't divide by zero!")

Raising an Exception

You can use the ‘raise’ statement to raise an exception in your code intentionally. In the example below, we raise a TypeError if the input is not an integer.

def check_integer(num):
    if not isinstance(num, int):
        raise TypeError("Input must be an integer")
    else:
        print("Input is an integer")

check_integer('hello')

Raising an Exception with a Custom Message

You can also provide a custom error message when raising an exception. This message will be outputted when the exception is raised.

def check_integer(num):
    if not isinstance(num, int):
        raise TypeError("Input must be an integer. You entered a string.")
    else:
        print("Input is an integer")

check_integer('hello')

Catching Multiple Exceptions

Python allows you to catch multiple exceptions. Let’s take a look at how to do this.

try:
    x = 5 / 0
    check_integer('hello')
except (ZeroDivisionError, TypeError):
    print("An error occurred!")

That’s the basics of Python exceptions! As you can see, they can be incredibly useful for controlling the flow of your program and handling errors in an organized way.

Using the Finally Clause

The ‘finally’ clause in Python is used in exception handling to enclose the sections of code that must be executed regardless of whether an exception has been raised. The ‘finally’ clause is always executed.

try:
    print("Hello World")
    x = 5 / 0
except (ZeroDivisionError, TypeError):
    print("An error occurred!")
finally:
    print("This line is always executed")

Defining Custom Exceptions

In Python, users can define their own exceptions by creating a new class. This new class must be a derived class of the built-in Python BaseException class, or any derived class thereof.

class CustomError(BaseException):
    pass

try:
    raise CustomError
except CustomError:
    print("A custom error occurred!")

Passing Values to Custom Exceptions

You can also pass values or arguments to your custom exceptions, to give more meaningful output when the exception is raised.

class CustomError(BaseException):
    def __init__(self, message):
        self.message = message

try:
    raise CustomError("This is a custom error message")
except CustomError as e:
    print(e.message)

Chaining Exceptions

Python 3 introduced a new syntax for raising exceptions, known as “Exception chaining”, where one exception can be linked to another as a cause. We can add ‘from’ after ‘raise’ to chain exceptions.

try:
    5 / 0
except ZeroDivisionError as e:
    raise RuntimeError("A runtime error occurred") from e

Using the assert Statement

The ‘assert’ keyword is used when debugging code. The assert keyword lets you test if a condition in your code returns true, if not, the program will raise an AssertionError.

x = 5
assert x > 10, "x is less than 10"

The ability to create, raise and catch exceptions is a powerful tool in Python, allowing you to elegantly respond to errors and alter your program’s flow as necessary.

Where to Go Next?

Now that you’ve made your first strides in Python exceptions, we encourage you to capitalize on this momentum and continue learning this powerful and versatile language. The world of Python stretches far beyond what we’ve covered, including areas such as game development, AI, data science, and more.

A great place to continue your Python education is our Python Mini-Degree. This comprehensive collection of courses is designed for a range of experience levels to give you the most effective and interactive learning experiences.

With a structured and project-based curriculum, you’ll gain hands-on experience creating games, building apps, and developing AI chatbots. Our courses cover coding basics, algorithms, object-oriented programming, game development, and more using libraries like Pygame, Tkinter, and Kivy.

Our instructors are experienced, certified, and committed to teaching in an engaging and simple-to-understand manner. At Zenva, we strive to provide accessible, high-quality education that empowers learners to reach their goals.

We understand that every learner’s journey is unique. Therefore, we offer a wide range of coding courses tailored to a diverse set of objectives and skill levels. Feel free to explore our Python courses and find the one that fits your learning goals!

Conclusion

Diving into Python exceptions has hopefully demonstrated Python’s immense potential and flexibility. Handling errors more efficiently allows you to create more robust and sustainable code, enhancing your overall coding skill set. Above all, remember that mastering a programming language is a marathon, not a sprint. Continuous learning and practice are key to becoming a successful coder.

We’re proud to be your partners on this journey. Let’s continue these exciting adventures in Python together with our comprehensive Python Mini-Degree. Join us and empower yourself with in-demand coding skills in a practical, project-based, and fun learning environment! See you there!

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