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Implement comprehensive testing strategies with pytest, fixtures, mocking, and test-driven development. Use when writing Python tests, setting up test suites, or implementing testing best practices.

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python-testing-patterns — detailed patterns and worked examples

Fundamental Patterns

Pattern 1: Basic pytest Tests

# test_calculator.py
import pytest

class Calculator:
    """Simple calculator for testing."""

    def add(self, a: float, b: float) -> float:
        return a + b

    def subtract(self, a: float, b: float) -> float:
        return a - b

    def multiply(self, a: float, b: float) -> float:
        return a * b

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


def test_addition():
    """Test addition."""
    calc = Calculator()
    assert calc.add(2, 3) == 5
    assert calc.add(-1, 1) == 0
    assert calc.add(0, 0) == 0


def test_subtraction():
    """Test subtraction."""
    calc = Calculator()
    assert calc.subtract(5, 3) == 2
    assert calc.subtract(0, 5) == -5


def test_multiplication():
    """Test multiplication."""
    calc = Calculator()
    assert calc.multiply(3, 4) == 12
    assert calc.multiply(0, 5) == 0


def test_division():
    """Test division."""
    calc = Calculator()
    assert calc.divide(6, 3) == 2
    assert calc.divide(5, 2) == 2.5


def test_division_by_zero():
    """Test division by zero raises error."""
    calc = Calculator()
    with pytest.raises(ValueError, match="Cannot divide by zero"):
        calc.divide(5, 0)

Pattern 2: Fixtures for Setup and Teardown

# test_database.py
import pytest
from typing import Generator

class Database:
    """Simple database class."""

    def __init__(self, connection_string: str):
        self.connection_string = connection_string
        self.connected = False

    def connect(self):
        """Connect to database."""
        self.connected = True

    def disconnect(self):
        """Disconnect from database."""
        self.connected = False

    def query(self, sql: str) -> list:
        """Execute query."""
        if not self.connected:
            raise RuntimeError("Not connected")
        return [{"id": 1, "name": "Test"}]


@pytest.fixture
def db() -> Generator[Database, None, None]:
    """Fixture that provides connected database."""
    # Setup
    database = Database("sqlite:///:memory:")
    database.connect()

    # Provide to test
    yield database

    # Teardown
    database.disconnect()


def test_database_query(db):
    """Test database query with fixture."""
    results = db.query("SELECT * FROM users")
    assert len(results) == 1
    assert results[0]["name"] == "Test"


@pytest.fixture(scope="session")
def app_config():
    """Session-scoped fixture - created once per test session."""
    return {
        "database_url": "postgresql://localhost/test",
        "api_key": "test-key",
        "debug": True
    }


@pytest.fixture(scope="module")
def api_client(app_config):
    """Module-scoped fixture - created once per test module."""
    # Setup expensive resource
    client = {"config": app_config, "session": "active"}
    yield client
    # Cleanup
    client["session"] = "closed"


def test_api_client(api_client):
    """Test using api client fixture."""
    assert api_client["session"] == "active"
    assert api_client["config"]["debug"] is True

Pattern 3: Parameterized Tests

# test_validation.py
import pytest

def is_valid_email(email: str) -> bool:
    """Check if email is valid."""
    return "@" in email and "." in email.split("@")[1]


@pytest.mark.parametrize("email,expected", [
    ("user@example.com", True),
    ("test.user@domain.co.uk", True),
    ("invalid.email", False),
    ("@example.com", False),
    ("user@domain", False),
    ("", False),
])
def test_email_validation(email, expected):
    """Test email validation with various inputs."""
    assert is_valid_email(email) == expected


@pytest.mark.parametrize("a,b,expected", [
    (2, 3, 5),
    (0, 0, 0),
    (-1, 1, 0),
    (100, 200, 300),
    (-5, -5, -10),
])
def test_addition_parameterized(a, b, expected):
    """Test addition with multiple parameter sets."""
    from test_calculator import Calculator
    calc = Calculator()
    assert calc.add(a, b) == expected


# Using pytest.param for special cases
@pytest.mark.parametrize("value,expected", [
    pytest.param(1, True, id="positive"),
    pytest.param(0, False, id="zero"),
    pytest.param(-1, False, id="negative"),
])
def test_is_positive(value, expected):
    """Test with custom test IDs."""
    assert (value > 0) == expected

Pattern 4: Mocking with unittest.mock

# test_api_client.py
import pytest
from unittest.mock import Mock, patch, MagicMock
import requests

class APIClient:
    """Simple API client."""

    def __init__(self, base_url: str):
        self.base_url = base_url

    def get_user(self, user_id: int) -> dict:
        """Fetch user from API."""
        response = requests.get(f"{self.base_url}/users/{user_id}")
        response.raise_for_status()
        return response.json()

    def create_user(self, data: dict) -> dict:
        """Create new user."""
        response = requests.post(f"{self.base_url}/users", json=data)
        response.raise_for_status()
        return response.json()


def test_get_user_success():
    """Test successful API call with mock."""
    client = APIClient("https://api.example.com")

    mock_response = Mock()
    mock_response.json.return_value = {"id": 1, "name": "John Doe"}
    mock_response.raise_for_status.return_value = None

    with patch("requests.get", return_value=mock_response) as mock_get:
        user = client.get_user(1)

        assert user["id"] == 1
        assert user["name"] == "John Doe"
        mock_get.assert_called_once_with("https://api.example.com/users/1")


def test_get_user_not_found():
    """Test API call with 404 error."""
    client = APIClient("https://api.example.com")

    mock_response = Mock()
    mock_response.raise_for_status.side_effect = requests.HTTPError("404 Not Found")

    with patch("requests.get", return_value=mock_response):
        with pytest.raises(requests.HTTPError):
            client.get_user(999)


@patch("requests.post")
def test_create_user(mock_post):
    """Test user creation with decorator syntax."""
    client = APIClient("https://api.example.com")

    mock_post.return_value.json.return_value = {"id": 2, "name": "Jane Doe"}
    mock_post.return_value.raise_for_status.return_value = None

    user_data = {"name": "Jane Doe", "email": "jane@example.com"}
    result = client.create_user(user_data)

    assert result["id"] == 2
    mock_post.assert_called_once()
    call_args = mock_post.call_args
    assert call_args.kwargs["json"] == user_data

Pattern 5: Testing Exceptions

# test_exceptions.py
import pytest

def divide(a: float, b: float) -> float:
    """Divide a by b."""
    if b == 0:
        raise ZeroDivisionError("Division by zero")
    if not isinstance(a, (int, float)) or not isinstance(b, (int, float)):
        raise TypeError("Arguments must be numbers")
    return a / b


def test_zero_division():
    """Test exception is raised for division by zero."""
    with pytest.raises(ZeroDivisionError):
        divide(10, 0)


def test_zero_division_with_message():
    """Test exception message."""
    with pytest.raises(ZeroDivisionError, match="Division by zero"):
        divide(5, 0)


def test_type_error():
    """Test type error exception."""
    with pytest.raises(TypeError, match="must be numbers"):
        divide("10", 5)


def test_exception_info():
    """Test accessing exception info."""
    with pytest.raises(ValueError) as exc_info:
        int("not a number")

    assert "invalid literal" in str(exc_info.value)

For advanced patterns including async testing, monkeypatching, temporary files, conftest setup, property-based testing, database testing, CI/CD integration, and configuration files, see references/advanced-patterns.md

Test Design Principles

One Behavior Per Test

Each test should verify exactly one behavior. This makes failures easy to diagnose and tests easy to maintain.

# BAD - testing multiple behaviors
def test_user_service():
    user = service.create_user(data)
    assert user.id is not None
    assert user.email == data["email"]
    updated = service.update_user(user.id, {"name": "New"})
    assert updated.name == "New"

# GOOD - focused tests
def test_create_user_assigns_id():
    user = service.create_user(data)
    assert user.id is not None

def test_create_user_stores_email():
    user = service.create_user(data)
    assert user.email == data["email"]

def test_update_user_changes_name():
    user = service.create_user(data)
    updated = service.update_user(user.id, {"name": "New"})
    assert updated.name == "New"

Test Error Paths

Always test failure cases, not just happy paths.

def test_get_user_raises_not_found():
    with pytest.raises(UserNotFoundError) as exc_info:
        service.get_user("nonexistent-id")

    assert "nonexistent-id" in str(exc_info.value)

def test_create_user_rejects_invalid_email():
    with pytest.raises(ValueError, match="Invalid email format"):
        service.create_user({"email": "not-an-email"})

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Activeupdated 4 months ago
  • Python
  • Testing
  • pytest
  • fixtures
  • mocking
  • tdd
  • unit-testing
  • integration-testing
  • pytest-cov

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README badge for wshobson/agents/python-testing-patterns

Teaches pytest-based testing patterns for Python including fixtures, mocking, test organization, and test-driven development. Covers unit tests, integration tests, async testing, mocking with side effects, time freezing with freezegun, and CI/CD integration.

Generated from the current SKILL.md.

Does this skill cover async testing?
Yes. The skill mentions testing async code and concurrent operations as a core use case, with advanced patterns documented in references/advanced-patterns.md.
What testing framework does this skill use?
pytest. The skill focuses on pytest fixtures, markers, parameterization, mocking, and coverage reporting.
Does this cover mocking and test isolation?
Yes. The skill includes patterns for mocking external dependencies with unittest.mock, testing retry behavior, and organizing tests to ensure isolation and independence.
Can I use this for database and integration testing?
Yes. The skill covers integration tests for APIs and services, testing database operations, and includes test organization patterns for separating unit, integration, and end-to-end tests.
Does this include property-based testing?
Property-based testing is listed as a core concept, with detailed patterns referenced in references/advanced-patterns.md.

Generated from the current SKILL.md. These answers refresh after source changes.