Turn Examples into Assertions

A worked example becomes more useful when the program can check it for you. One quiz-plan readiness check requires at least three questions, so begin with that promise:

Python’s assert statement expresses an expectation:

def has_enough_questions(question_count):
    return question_count >= 3


assert has_enough_questions(3) is True

Python evaluates the condition after assert.

• If it is True, execution continues silently.

• If it is False, Python raises AssertionError.

Silence is useful here. Think of an assertion as a quiet alarm: it only makes noise when a promise is broken.

Add a helpful message

An assertion can include a message:

assert has_enough_questions(3) is True, "Exactly three questions should be enough."

If the check fails, the message appears with the traceback. It explains the intended behavior, not the internal machinery of the test.

Check both sides of a decision

The phrase “at least three” has an important boundary. Check immediately below it, at it, and above it:

assert has_enough_questions(2) is False
assert has_enough_questions(3) is True
assert has_enough_questions(4) is True

Together, those checks distinguish >= 3 from the easy-to-miss > 3.

Use is True and is False when the contract specifically promises a Boolean. It distinguishes the Boolean True from other truthy values such as 1.

Assertions are developer checks

An assertion is not a friendly way to validate live user input. It is a compact note from the developer to the program: “This behavior must stay true.”

For user input, use the validation and exception-handling techniques from Chapter 10.

Keep checks after refactoring

Once a check captures an important behavior, keep it while you reorganize the code. If the behavior changes accidentally, the failed assertion tells you immediately.

def has_enough_questions(question_count):
    return question_count >= 3


assert has_enough_questions(3) is True
print("Check passed.")