Why your code needs tests, even the 'small' code

It's easy to think automated tests are for "big projects" or "serious production code". In practice, the moment they're most needed is exactly when a project is small and changing fast — before a bug becomes expensive to find.

What a unit test actually verifies

A unit test checks that a specific piece of code (a function, a method) produces the expected result for known inputs, including edge cases — not just the happy path.

def divide(a, b):
    if b == 0:
        raise ValueError("Cannot divide by zero")
    return a / b


def test_divide_normal():
    assert divide(10, 2) == 5


def test_divide_by_zero_raises():
    import pytest
    with pytest.raises(ValueError):
        divide(10, 0)

The real value: changing code without fear

The biggest benefit of a test suite doesn't show up when you first write the code, but months later, when someone needs to modify it. Without tests, every change is a leap of faith; with tests, a failure tells you exactly what broke before it reaches production.

Edge cases: where bugs actually live

The happy path almost never fails — what fails is the empty input, the unexpected negative value, the duplicate that shouldn't exist. A good test covers those cases explicitly, not just the obvious scenario.

Start with one test, not the perfect suite

You don't need 100% coverage on day one — you need the habit of writing at least one test for every new behavior you add. Explore the Python courses to practice this habit from the fundamentals.