Unit testing

Enables automated verification of code behavior.

Python unit testing: verifying that a function returns the correct sum; Test-driven development: writing a failing test before implementing addition logic; Continuous integration: ensuring addition logic passes tests on each commit.

pytest, unittest, test-driven development, software testing, Python projects

def function_name():

def ...():

function_name: valid Python identifier (snake_case recommended)

• assert statements
• test fixtures
• pytest.mark
• unittest.TestCase
• test discovery

• def test_addition(self): (method in unittest.TestCase) – provides access to setup/teardown and assertion helpers but requires class inheritance
• def test_addition() -> None: (explicit return type annotation) – improves readability and static checking but adds verbosity
• def test_addition(a
• b): (parameterized test) – allows testing multiple inputs but requires parametrization decorator.

Missing colon after the parameter list – causes a SyntaxError because the function definition is incomplete.; Using a capitalized name like TestAddition – may still execute but violates the test discovery convention that expects functions to start with 'test_', leading to the test being ignored.; Defining the function inside another function without proper indentation – results in an IndentationError or creates an unintended local function that test runners cannot find.

def test_subtraction(): – tests a different arithmetic operation; class TestAddition(unittest.TestCase): – provides class-based test structure with more setup options; def test_addition_pass(): – naming convention that explicitly indicates the expected outcome.

Coming from JavaScript: may forget to include parentheses after the function name – Python requires parentheses even for zero‑argument functions → include empty parentheses.; Coming from C: may use a semicolon to terminate the function definition – Python uses a colon and indentation, not a semicolon → remove the semicolon and add a colon.

• def test_subtraction()
• def test_multiplication()
• def test_division()
• class TestCase

Do not use this pattern when testing asynchronous code without proper async/await handling, as the test will not await coroutines; Performance impact is negligible because defining a test function adds no runtime overhead; Boundary condition: the function name must be unique within its module and must start with 'test_' to be discovered by most test runners.

Enables early detection of regressions in addition logic, facilitating safe refactoring and reliable continuous integration.

Defining a test function is like writing a recipe card that lists the ingredients and expected result before you start cooking.

In pytest, test functions are discovered automatically if they start with 'test_' and reside in files matching test_*.py or *_test.py.