python-testing-patterns

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---
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

```python
# 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
```

## Detailed patterns and worked examples

Detailed pattern documentation lives in `references/details.md`. Read that file when the navigation tier above is insufficient.

## Testing Best Practices

### Test Organization

```python
# 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.

```python
# 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.

```python
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 se