Python Documentation with Docstrings and Type Hints

Docstrings explain public purpose, arguments, return values and important exceptions.

Understanding the Concept

Docstrings explain public purpose, arguments, return values and important exceptions. Type hints complement docstrings but cannot describe all business constraints or side effects.

How this fits into a real test suite

A reliable test starts with a specific expected behavior. Keep the fixture small, arrange the input, call the real code, and assert a result the reader can verify. Add one boundary or failure case so the test does not pass only for a convenient example. In a larger project, run the same test automatically after each change.

Tests are repeatable experiments. Use temporary resources and injected dependencies where possible; when the environment is part of the requirement, add a separate integration test rather than weakening the unit test.

Worked Example

Read the code from the first line to the last. Identify which values are inputs, which operation is being demonstrated and what should happen before running it.

def average_price(prices: list[float]) -> float:
    """Return the arithmetic mean of nonempty price data.

    Raises:
        ValueError: If prices is empty.
    """
    if not prices:
        raise ValueError('prices must not be empty')
    return sum(prices) / len(prices)
print(average_price([4.0, 8.0]))

Walkthrough: What Each Part Does

• The definition average_price creates reusable behavior. Its body runs when called, awaited or instantiated; defining it alone does not run the body of an ordinary function.
• The final check compares actual behavior with an explicit expectation. A successful test tells you that this particular case passed, not that every possible input works.

This demonstration focuses on one practical behavior. Before changing several lines, vary one input or one configuration choice and check whether the result changes for the reason you expected.

Example Output

6.0

The output above was captured by running the example in the available Python environment. The order of concurrent events, durations and platform-dependent values can legitimately differ on your computer.

Important Behavior and Edge Cases

Restating the implementation line by line instead of documenting behavior and relevant restrictions.

Pay particular attention to the documented return values, errors and resource-lifetime rules. A convenient result under normal inputs does not guarantee correct behavior under cancellation, missing data or environmental failure.

Practice Exercise

Document a small helper with one input constraint and one possible error.

Write down the result you expect before running your changed code. Check at least one normal case and one boundary or failure case. If your example starts workers or opens resources, verify how they are cleaned up.

Further reading: official documentation and API reference.

Common Beginner Mistakes

• Restating the implementation line by line instead of documenting behavior and relevant restrictions.
• Writing assertions that check implementation details but fail to validate the behavior that matters to the caller.

Key Takeaways

• Docstrings explain public purpose, arguments, return values and important exceptions.
• Docstrings explain public purpose, arguments, return values and important exceptions. Type hints complement docstrings but cannot describe all business constraints or side effects.
• Practice: Document a small helper with one input constraint and one possible error.