This guide explains pure functions vs functions with side effects through a focused Python example. You will learn the behavior to expect, why it matters in a real program, and how to recognize the common mistakes before applying it in your own project.
What You Will Learn
A pure function returns a result determined only by its inputs and avoids observable side effects. A function that prints, changes a global, writes a file or modifies caller-owned data has side effects.
When and Why to Use It
The following example focuses on a practical use of Pure Functions vs Functions with Side Effects.
Step-by-Step Example
def add_tax(subtotal, tax_rate):
return subtotal * (1 + tax_rate)
def show_total(subtotal, tax_rate):
print(add_tax(subtotal, tax_rate))
print(add_tax(100, 0.2))
show_total(100, 0.2)Understanding the Example
add_tax computes the same result for the same inputs. show_total adds a display side effect even though it reuses the pure calculation.
Expected Output
120.0
120.0Important Behavior and Edge Cases
Purity is a design property, not a built-in Python annotation. Avoid mutating a list supplied as an argument when you intend a pure transformation.
Try It Yourself
Rewrite a function that appends to an argument list so it returns a new list instead.
Common Beginner Mistakes
- Purity is a design property, not a built-in Python annotation. Avoid mutating a list supplied as an argument when you intend a pure transformation.
- Confusing a returned value with printed output, or failing to verify a function’s behavior with different input values.
- Skipping the practice step and assuming the example covers every input. Test at least one normal case and one edge case relevant to this topic.
Key Takeaways
- A pure function returns a result determined only by its inputs and avoids observable side effects.
- add_tax computes the same result for the same inputs.
- Apply the technique deliberately, checking its documented input requirements and failure behavior before integrating it into a larger project.