testing-workflow

name	testing-workflow
description	Testing best practices with pytest. Use this skill when writing tests, setting up test infrastructure, or debugging test failures.

Testing Workflow Skill

A comprehensive guide to writing and organizing tests with pytest.

When to Use This Skill

• User asks to "write tests" or "add unit tests"
• Setting up a testing framework
• Test coverage improvements
• Debugging test failures

Testing Setup

Project Structure

project/
├── src/
│   └── mypackage/
│       ├── __init__.py
│       └── module.py
├── tests/
│   ├── __init__.py
│   ├── conftest.py        # Shared fixtures
│   ├── test_module.py
│   └── integration/
│       └── test_api.py
├── pytest.ini
└── requirements-dev.txt

pytest.ini Configuration

[pytest]
testpaths = tests
python_files = test_*.py
python_classes = Test*
python_functions = test_*
addopts = -v --tb=short --cov=src --cov-report=term-missing
filterwarnings = ignore::DeprecationWarning

Test Patterns

1. Basic Unit Test

# tests/test_calculator.py
import pytest
from mypackage.calculator import Calculator

class TestCalculator:
    def test_add_positive_numbers(self):
        calc = Calculator()
        assert calc.add(2, 3) == 5
    
    def test_add_negative_numbers(self):
        calc = Calculator()
        assert calc.add(-1, -1) == -2
    
    def test_divide_by_zero_raises_error(self):
        calc = Calculator()
        with pytest.raises(ZeroDivisionError):
            calc.divide(10, 0)

2. Using Fixtures

# tests/conftest.py
import pytest
from mypackage.database import Database

@pytest.fixture
def db():
    """Provide a test database connection."""
    db = Database(":memory:")
    db.create_tables()
    yield db
    db.close()

@pytest.fixture
def sample_user(db):
    """Create a sample user for testing."""
    user = db.create_user("[e-mail]", "password123")
    return user

3. Parametrized Tests

import pytest

@pytest.mark.parametrize("input,expected", [
    ("hello", "HELLO"),
    ("World", "WORLD"),
    ("", ""),
    ("123", "123"),
])
def test_uppercase(input, expected):
    assert input.upper() == expected

4. Mocking External Dependencies

from unittest.mock import Mock, patch, MagicMock
import pytest

def test_api_call():
    with patch('mypackage.api.requests.get') as mock_get:
        mock_response = Mock()
        mock_response.status_code = 200
        mock_response.json.return_value = {"data": "test"}
        mock_get.return_value = mock_response
        
        result = api.fetch_data()
        
        assert result == {"data": "test"}
        mock_get.assert_called_once()

5. Async Tests

import pytest
import asyncio

@pytest.mark.asyncio
async def test_async_function():
    result = await some_async_function()
    assert result == expected_value

Running Tests

# Run all tests
pytest

# Run specific file
pytest tests/test_module.py

# Run specific test
pytest tests/test_module.py::test_function

# Run with coverage
pytest --cov=src --cov-report=html

# Run only fast tests
pytest -m "not slow"

# Run with verbose output
pytest -v

# Stop on first failure
pytest -x

Best Practices

1. Test one thing per test - Single assertion focus
2. Use descriptive names - test_user_login_with_invalid_password_returns_401
3. Arrange-Act-Assert (AAA) - Clear test structure
4. Don't test implementation - Test behavior, not internals
5. Keep tests fast - Mock slow dependencies
6. Use fixtures - Share setup code efficiently
7. Test edge cases - Empty inputs, None values, boundaries

Common Issues

• Flaky tests: Often due to timing or order dependencies
• Slow tests: Mock external services and databases
• Test pollution: Ensure proper cleanup in fixtures