python-testing-patterns

name	python-testing-patterns
description	pytest-specific testing patterns — fixtures, mocking, parameterization, async testing, and configuration. Use when writing Python tests with pytest, setting up pytest infrastructure, or needing pytest-specific patterns. For TDD process and philosophy (red-green-refactor, vertical slicing), use the `tdd` skill instead.

Python Testing Patterns

pytest-specific tooling patterns for Python projects. For the TDD process (red-green-refactor, vertical slicing, tracer bullets), see the tdd skill — it is language-agnostic and should be used alongside this skill.

When to Use This Skill

• Writing tests with pytest specifically
• Setting up pytest fixtures, conftest, and configuration
• Parameterized testing patterns
• Mocking with unittest.mock in Python
• Testing async Python code
• pytest markers and plugins
• Debugging failing pytest tests

Core Concepts

Test Structure (AAA Pattern)

• Arrange: Set up test data and preconditions
• Act: Execute the code under test
• Assert: Verify the results

Test Types

• Unit Tests: Test individual functions/classes in isolation
• Integration Tests: Test interaction between components — prefer these; they exercise real code paths through public APIs
• Functional Tests: Test complete features end-to-end

Test Coverage

• Aim for meaningful coverage, not just high percentages
• Focus testing effort on critical paths and complex logic, not every edge case

Test Isolation

• Tests should be independent
• No shared state between tests
• Each test should clean up after itself

Quick Start

# test_example.py
def add(a, b):
    return a + b

def test_add():
    """Basic test example."""
    result = add(2, 3)
    assert result == 5

def test_add_negative():
    """Test with negative numbers."""
    assert add(-1, 1) == 0

# Run with: pytest test_example.py

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", [
    ("[e-mail]", True),
    ("[e-mail]", 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": "[e-mail]"}
    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"})

Testing Best Practices

Test Organization

# tests/
#   __init__.py
#   conftest.py           # Shared fixtures
#   test_unit/            # Unit tests
#     test_models.py
#     test_utils.py
#   test_integration/     # Integration tests
#     test_api.py
#     test_database.py
#   test_e2e/            # End-to-end tests
#     test_workflows.py

Test Naming Convention

A common pattern: test_<unit>_<scenario>_<expected_outcome>. Adapt to your team's preferences.

# Pattern: test_<unit>_<scenario>_<expected>
def test_create_user_with_valid_data_returns_user():
    ...

def test_create_user_with_duplicate_email_raises_conflict():
    ...

def test_get_user_with_unknown_id_returns_none():
    ...

# Good test names - clear and descriptive
def test_user_creation_with_valid_data():
    """Clear name describes what is being tested."""
    pass

def test_login_fails_with_invalid_password():
    """Name describes expected behavior."""
    pass

def test_api_returns_404_for_missing_resource():
    """Specific about inputs and expected outcomes."""
    pass

# Bad test names - avoid these
def test_1():  # Not descriptive
    pass

def test_user():  # Too vague
    pass

def test_function():  # Doesn't explain what's tested
    pass

Testing Retry Behavior

Verify that retry logic works correctly using mock side effects.

from unittest.mock import Mock

def test_retries_on_transient_error():
    """Test that service retries on transient failures."""
    client = Mock()
    # Fail twice, then succeed
    client.request.side_effect = [
        ConnectionError("Failed"),
        ConnectionError("Failed"),
        {"status": "ok"},
    ]

    service = ServiceWithRetry(client, max_retries=3)
    result = service.fetch()

    assert result == {"status": "ok"}
    assert client.request.call_count == 3

def test_gives_up_after_max_retries():
    """Test that service stops retrying after max attempts."""
    client = Mock()
    client.request.side_effect = ConnectionError("Failed")

    service = ServiceWithRetry(client, max_retries=3)

    with pytest.raises(ConnectionError):
        service.fetch()

    assert client.request.call_count == 3

def test_does_not_retry_on_permanent_error():
    """Test that permanent errors are not retried."""
    client = Mock()
    client.request.side_effect = ValueError("Invalid input")

    service = ServiceWithRetry(client, max_retries=3)

    with pytest.raises(ValueError):
        service.fetch()

    # Only called once - no retry for ValueError
    assert client.request.call_count == 1

Mocking Time with Freezegun

Use freezegun to control time in tests for predictable time-dependent behavior.

from freezegun import freeze_time
from datetime import datetime, timedelta

@freeze_time("2026-01-15 10:00:00")
def test_token_expiry():
    """Test token expires at correct time."""
    token = create_token(expires_in_seconds=3600)
    assert token.expires_at == datetime(2026, 1, 15, 11, 0, 0)

@freeze_time("2026-01-15 10:00:00")
def test_is_expired_returns_false_before_expiry():
    """Test token is not expired when within validity period."""
    token = create_token(expires_in_seconds=3600)
    assert not token.is_expired()

@freeze_time("2026-01-15 12:00:00")
def test_is_expired_returns_true_after_expiry():
    """Test token is expired after validity period."""
    token = Token(expires_at=datetime(2026, 1, 15, 11, 30, 0))
    assert token.is_expired()

def test_with_time_travel():
    """Test behavior across time using freeze_time context."""
    with freeze_time("2026-01-01") as frozen_time:
        item = create_item()
        assert item.created_at == datetime(2026, 1, 1)

        # Move forward in time
        frozen_time.move_to("2026-01-15")
        assert item.age_days == 14

Test Markers

# test_markers.py
import pytest

@pytest.mark.slow
def test_slow_operation():
    """Mark slow tests."""
    import time
    time.sleep(2)


@pytest.mark.integration
def test_database_integration():
    """Mark integration tests."""
    pass


@pytest.mark.skip(reason="Feature not implemented yet")
def test_future_feature():
    """Skip tests temporarily."""
    pass


@pytest.mark.skipif(os.name == "nt", reason="Unix only test")
def test_unix_specific():
    """Conditional skip."""
    pass


@pytest.mark.xfail(reason="Known bug #123")
def test_known_bug():
    """Mark expected failures."""
    assert False


# Run with:
# pytest -m slow          # Run only slow tests
# pytest -m "not slow"    # Skip slow tests
# pytest -m integration   # Run integration tests

Coverage Reporting

# Install coverage
pip install pytest-cov

# Run tests with coverage
pytest --cov=myapp tests/

# Generate HTML report
pytest --cov=myapp --cov-report=html tests/

# Fail if coverage below threshold
pytest --cov=myapp --cov-fail-under=80 tests/

# Show missing lines
pytest --cov=myapp --cov-report=term-missing tests/

For advanced patterns (async testing, monkeypatching, property-based testing, database testing, CI/CD integration, and configuration), see references/advanced-patterns.md