| name | python-testing-patterns |
| description | 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. |
Python Testing Patterns
Comprehensive guide to implementing robust testing strategies in Python using pytest, fixtures, mocking, parameterization, and test-driven development practices.
When to Use This Skill
- Writing unit tests for Python code
- Setting up test suites and test infrastructure
- Implementing test-driven development (TDD)
- Creating integration tests for APIs and services
- Mocking external dependencies and services
- Testing async code and concurrent operations
- Setting up continuous testing in CI/CD
- Implementing property-based testing
- Testing database operations
- Debugging failing tests
Core Concepts
1. Test Types
- Unit Tests: Test individual functions/classes in isolation
- Integration Tests: Test interaction between components
- Functional Tests: Test complete features end-to-end
- Performance Tests: Measure speed and resource usage
2. Test Structure (AAA Pattern)
- Arrange: Set up test data and preconditions
- Act: Execute the code under test
- Assert: Verify the results
3. Test Coverage
- Measure what code is exercised by tests
- Identify untested code paths
- Aim for meaningful coverage, not just high percentages
4. Test Isolation
- Tests should be independent
- No shared state between tests
- Each test should clean up after itself
Quick Start
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
Fundamental Patterns
Pattern 1: Basic pytest Tests
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 ():
calc = Calculator()
calc.subtract(, ) ==
calc.subtract(, ) == -
():
calc = Calculator()
calc.multiply(, ) ==
calc.multiply(, ) ==
():
calc = Calculator()
calc.divide(, ) ==
calc.divide(, ) ==
():
calc = Calculator()
pytest.raises(ValueError, =):
calc.divide(, )
Pattern 2: Fixtures for Setup and Teardown
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."""
database = Database()
database.connect()
database
database.disconnect()
():
results = db.query()
(results) ==
results[][] ==
():
{
: ,
: ,
:
}
():
client = {: app_config, : }
client
client[] =
():
api_client[] ==
api_client[][]
Pattern 3: Parameterized Tests
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, ),
(),
(),
])
():
test_calculator Calculator
calc = Calculator()
calc.add(a, b) == expected
():
(value > ) == expected
Pattern 4: Mocking with unittest.mock
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()
user[] ==
user[] ==
mock_get.assert_called_once_with()
():
client = APIClient()
mock_response = Mock()
mock_response.raise_for_status.side_effect = requests.HTTPError()
patch(, return_value=mock_response):
pytest.raises(requests.HTTPError):
client.get_user()
():
client = APIClient()
mock_post.return_value.json.return_value = {: , : }
mock_post.return_value.raise_for_status.return_value =
user_data = {: , : }
result = client.create_user(user_data)
result[] ==
mock_post.assert_called_once()
call_args = mock_post.call_args
call_args.kwargs[] == user_data
Pattern 5: Testing Exceptions
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 ():
pytest.raises(ValueError) exc_info:
()
(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.
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"
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
Test Naming Convention
A common pattern: test_<unit>_<scenario>_<expected_outcome>. Adapt to your team's preferences.
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():
...
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
def test_1():
pass
def test_user():
pass
def test_function():
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()
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()
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(, , )
frozen_time.move_to()
item.age_days ==
Test Markers
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
Coverage Reporting
pip install pytest-cov
pytest --cov=myapp tests/
pytest --cov=myapp --cov-report=html tests/
pytest --cov=myapp --cov-fail-under=80 tests/
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
