Assertions in Python

Python’s built-in assert statement is underrated and deserves more attention than it gets.

In this blog post, we will explore how to use assertions in Python, how they help automatically detect errors, and how they make your code more reliable and easier to debug.

What Are Assertions and Why Use Them?

An assert statement in Python is used for debugging purposes. If the assertion condition evaluates to True, the program continues as normal. However, if the condition evaluates to False, an AssertionError is raised with an optional error message.

Let’s look at a real-world example where assertions can be useful.

Using Assertions in a Discount System

Imagine you’re building an online store in Python, and you need to apply discount coupons. Here’s a simple function called apply_discount:

def apply_discount(product, discount):
    price = int(product["price"] * (1.0 - discount))
    assert 0 <= price <= product["price"], "Discounted price must be within valid range"
    return price

How Assertions Help Here

The assert statement ensures that:

• The discounted price never goes below £0.
• The discount never exceeds the original price.

Example Usage

Let’s define a product (a book called Python Fundamentals) and apply a valid discount:

book = {'name': 'Python Fundamentals', 'price': 1900}  # Price in cents (£19.00)
print(apply_discount(book, 0.25))  # Applying a 25% discount

Output:

1425  # (£14.25 after discount)

Handling Invalid Discounts

Now, let’s see what happens when we try applying a 200% discount, which would result in a negative price:

apply_discount(book, 2.0)

Output:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "<stdin>", line 3, in apply_discount
AssertionError: Discounted price must be within valid range

Since the discount violates our assertion condition, the program throws an error instead of silently producing incorrect results.

Why Use Assertions?

✅ Faster Debugging – Assertions automatically catch logic errors, reducing debugging time.
✅ Better Maintainability – Code with assertions is self-documenting, helping future developers understand constraints.
✅ Prevents Invalid States – Ensures that program logic remains within expected boundaries.

Conclusion

Assertions are a powerful yet simple debugging tool in Python. They help you enforce assumptions in your code, leading to fewer bugs and a more maintainable codebase.

Would you like to learn more about Python debugging techniques? Let me know in the comments! 🚀