279 lines
7.1 KiB
Markdown
279 lines
7.1 KiB
Markdown
---
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name: python-testing-patterns
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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.
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---
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# Python Testing Patterns
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Comprehensive guide to implementing robust testing strategies in Python using pytest, fixtures, mocking, parameterization, and test-driven development practices.
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## When to Use This Skill
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- Writing unit tests for Python code
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- Setting up test suites and test infrastructure
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- Implementing test-driven development (TDD)
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- Creating integration tests for APIs and services
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- Mocking external dependencies and services
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- Testing async code and concurrent operations
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- Setting up continuous testing in CI/CD
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- Implementing property-based testing
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- Testing database operations
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- Debugging failing tests
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## Core Concepts
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### 1. Test Types
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- **Unit Tests**: Test individual functions/classes in isolation
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- **Integration Tests**: Test interaction between components
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- **Functional Tests**: Test complete features end-to-end
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- **Performance Tests**: Measure speed and resource usage
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### 2. Test Structure (AAA Pattern)
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- **Arrange**: Set up test data and preconditions
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- **Act**: Execute the code under test
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- **Assert**: Verify the results
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### 3. Test Coverage
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- Measure what code is exercised by tests
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- Identify untested code paths
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- Aim for meaningful coverage, not just high percentages
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### 4. Test Isolation
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- Tests should be independent
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- No shared state between tests
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- Each test should clean up after itself
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## Quick Start
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```python
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# test_example.py
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def add(a, b):
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return a + b
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def test_add():
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"""Basic test example."""
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result = add(2, 3)
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assert result == 5
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def test_add_negative():
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"""Test with negative numbers."""
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assert add(-1, 1) == 0
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# Run with: pytest test_example.py
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```
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## Detailed patterns and worked examples
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Detailed pattern documentation lives in `references/details.md`. Read that file when the navigation tier above is insufficient.
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## Testing Best Practices
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### Test Organization
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```python
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# tests/
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# __init__.py
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# conftest.py # Shared fixtures
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# test_unit/ # Unit tests
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# test_models.py
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# test_utils.py
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# test_integration/ # Integration tests
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# test_api.py
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# test_database.py
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# test_e2e/ # End-to-end tests
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# test_workflows.py
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```
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### Test Naming Convention
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A common pattern: `test_<unit>_<scenario>_<expected_outcome>`. Adapt to your team's preferences.
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```python
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# Pattern: test_<unit>_<scenario>_<expected>
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def test_create_user_with_valid_data_returns_user():
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...
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def test_create_user_with_duplicate_email_raises_conflict():
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...
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def test_get_user_with_unknown_id_returns_none():
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...
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# Good test names - clear and descriptive
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def test_user_creation_with_valid_data():
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"""Clear name describes what is being tested."""
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pass
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def test_login_fails_with_invalid_password():
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"""Name describes expected behavior."""
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pass
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def test_api_returns_404_for_missing_resource():
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"""Specific about inputs and expected outcomes."""
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pass
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# Bad test names - avoid these
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def test_1(): # Not descriptive
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pass
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def test_user(): # Too vague
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pass
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def test_function(): # Doesn't explain what's tested
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pass
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```
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### Testing Retry Behavior
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Verify that retry logic works correctly using mock side effects.
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```python
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from unittest.mock import Mock
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def test_retries_on_transient_error():
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"""Test that service retries on transient failures."""
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client = Mock()
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# Fail twice, then succeed
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client.request.side_effect = [
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ConnectionError("Failed"),
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ConnectionError("Failed"),
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{"status": "ok"},
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]
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service = ServiceWithRetry(client, max_retries=3)
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result = service.fetch()
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assert result == {"status": "ok"}
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assert client.request.call_count == 3
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def test_gives_up_after_max_retries():
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"""Test that service stops retrying after max attempts."""
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client = Mock()
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client.request.side_effect = ConnectionError("Failed")
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service = ServiceWithRetry(client, max_retries=3)
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with pytest.raises(ConnectionError):
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service.fetch()
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assert client.request.call_count == 3
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def test_does_not_retry_on_permanent_error():
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"""Test that permanent errors are not retried."""
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client = Mock()
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client.request.side_effect = ValueError("Invalid input")
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service = ServiceWithRetry(client, max_retries=3)
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with pytest.raises(ValueError):
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service.fetch()
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# Only called once - no retry for ValueError
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assert client.request.call_count == 1
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```
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### Mocking Time with Freezegun
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Use freezegun to control time in tests for predictable time-dependent behavior.
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```python
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from freezegun import freeze_time
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from datetime import datetime, timedelta
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@freeze_time("2026-01-15 10:00:00")
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def test_token_expiry():
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"""Test token expires at correct time."""
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token = create_token(expires_in_seconds=3600)
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assert token.expires_at == datetime(2026, 1, 15, 11, 0, 0)
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@freeze_time("2026-01-15 10:00:00")
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def test_is_expired_returns_false_before_expiry():
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"""Test token is not expired when within validity period."""
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token = create_token(expires_in_seconds=3600)
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assert not token.is_expired()
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@freeze_time("2026-01-15 12:00:00")
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def test_is_expired_returns_true_after_expiry():
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"""Test token is expired after validity period."""
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token = Token(expires_at=datetime(2026, 1, 15, 11, 30, 0))
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assert token.is_expired()
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def test_with_time_travel():
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"""Test behavior across time using freeze_time context."""
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with freeze_time("2026-01-01") as frozen_time:
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item = create_item()
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assert item.created_at == datetime(2026, 1, 1)
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# Move forward in time
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frozen_time.move_to("2026-01-15")
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assert item.age_days == 14
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```
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### Test Markers
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```python
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# test_markers.py
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import pytest
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@pytest.mark.slow
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def test_slow_operation():
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"""Mark slow tests."""
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import time
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time.sleep(2)
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@pytest.mark.integration
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def test_database_integration():
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"""Mark integration tests."""
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pass
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@pytest.mark.skip(reason="Feature not implemented yet")
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def test_future_feature():
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"""Skip tests temporarily."""
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pass
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@pytest.mark.skipif(os.name == "nt", reason="Unix only test")
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def test_unix_specific():
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"""Conditional skip."""
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pass
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@pytest.mark.xfail(reason="Known bug #123")
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def test_known_bug():
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"""Mark expected failures."""
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assert False
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# Run with:
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# pytest -m slow # Run only slow tests
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# pytest -m "not slow" # Skip slow tests
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# pytest -m integration # Run integration tests
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```
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### Coverage Reporting
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```bash
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# Install coverage
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pip install pytest-cov
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# Run tests with coverage
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pytest --cov=myapp tests/
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# Generate HTML report
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pytest --cov=myapp --cov-report=html tests/
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# Fail if coverage below threshold
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pytest --cov=myapp --cov-fail-under=80 tests/
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# Show missing lines
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pytest --cov=myapp --cov-report=term-missing tests/
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```
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For advanced patterns (async testing, monkeypatching, property-based testing, database testing, CI/CD integration, and configuration), see [references/advanced-patterns.md](references/advanced-patterns.md)
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