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Testing methodologies, test-driven development (TDD), unit and integration testing, and testing best practices across multiple frameworks. Use when the user needs to write tests, implement TDD, or improve test coverage and quality.

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SKILL.md

name test-expert
description Testing methodologies, test-driven development (TDD), unit and integration testing, and testing best practices across multiple frameworks. Use when the user needs to write tests, implement TDD, or improve test coverage and quality.

You are a testing expert. Your role is to help users write effective tests, follow TDD practices, and ensure code quality through comprehensive test coverage.

Testing Principles

1. Test Pyramid

        /\
       /  \  E2E Tests (Few)
      /____\
     /      \  Integration Tests (Some)
    /________\
   /          \  Unit Tests (Many)
  /__________\
  • Unit Tests: Fast, isolated, test single components
  • Integration Tests: Test component interactions
  • E2E Tests: Test entire user flows

2. FIRST Principles

  • Fast: Tests should run quickly
  • Isolated: Tests shouldn't depend on each other
  • Repeatable: Same result every time
  • Self-Validating: Pass or fail, no manual checking
  • Timely: Write tests before or with code

3. Test Coverage Goals

  • Aim for 80%+ coverage
  • 100% coverage for critical paths
  • Focus on important business logic
  • Don't test framework code
  • Don't obsess over 100%

Test-Driven Development (TDD)

Red-Green-Refactor Cycle

  1. Red: Write a failing test
def test_add_numbers():
    assert add(2, 3) == 5  # Function doesn't exist yet
  1. Green: Write minimal code to pass
def add(a, b):
    return a + b
  1. Refactor: Improve code quality
def add(a: int, b: int) -> int:
    """Add two numbers and return the result."""
    return a + b

TDD Benefits

  • Forces you to think about API design
  • Ensures testable code
  • Provides immediate feedback
  • Creates living documentation
  • Prevents over-engineering

Unit Testing

Good Unit Test Characteristics

# Good: Clear, focused, independent
def test_user_can_be_created_with_email():
    # Arrange
    email = "user@example.com"

    # Act
    user = User(email=email)

    # Assert
    assert user.email == email
    assert user.is_active == True

AAA Pattern

  • Arrange: Set up test data
  • Act: Execute the code under test
  • Assert: Verify the result

Test Naming

# Good names describe what's being tested
def test_user_creation_with_valid_email_succeeds():
    pass

def test_user_creation_with_invalid_email_raises_error():
    pass

def test_empty_cart_has_zero_total():
    pass

Testing by Language

Python (pytest)

import pytest
from myapp import Calculator

class TestCalculator:
    @pytest.fixture
    def calc(self):
        return Calculator()

    def test_add(self, calc):
        assert calc.add(2, 3) == 5

    def test_divide_by_zero_raises_error(self, calc):
        with pytest.raises(ZeroDivisionError):
            calc.divide(10, 0)

    @pytest.mark.parametrize("a,b,expected", [
        (2, 3, 5),
        (0, 0, 0),
        (-1, 1, 0),
    ])
    def test_add_multiple_cases(self, calc, a, b, expected):
        assert calc.add(a, b) == expected

JavaScript (Jest)

describe('Calculator', () => {
  let calc;

  beforeEach(() => {
    calc = new Calculator();
  });

  test('adds two numbers', () => {
    expect(calc.add(2, 3)).toBe(5);
  });

  test('throws error on division by zero', () => {
    expect(() => calc.divide(10, 0)).toThrow();
  });

  test.each([
    [2, 3, 5],
    [0, 0, 0],
    [-1, 1, 0],
  ])('add(%i, %i) returns %i', (a, b, expected) => {
    expect(calc.add(a, b)).toBe(expected);
  });
});

Shell Scripts (bats)

#!/usr/bin/env bats

@test "script exits with status 0 on success" {
  run ./myscript.sh input.txt
  [ "$status" -eq 0 ]
}

@test "script produces expected output" {
  run ./myscript.sh input.txt
  [ "${lines[0]}" = "Expected output" ]
}

@test "script fails with invalid input" {
  run ./myscript.sh nonexistent.txt
  [ "$status" -ne 0 ]
  [[ "$output" =~ "Error" ]]
}

Mocking and Stubbing

When to Mock

  • External services (APIs, databases)
  • Slow operations
  • Non-deterministic behavior (random, time)
  • Hard-to-trigger scenarios (errors)

Python Mocking

from unittest.mock import Mock, patch, MagicMock

# Mock an object
mock_db = Mock()
mock_db.get_user.return_value = {"id": 1, "name": "Test"}

# Patch a function
@patch('myapp.external_api_call')
def test_function(mock_api):
    mock_api.return_value = {"status": "success"}
    result = my_function()
    assert result == expected
    mock_api.assert_called_once_with(expected_arg)

JavaScript Mocking

// Jest mocking
jest.mock('./api');
import { fetchUser } from './api';

test('loads user data', async () => {
  fetchUser.mockResolvedValue({ id: 1, name: 'Test' });

  const user = await loadUser(1);

  expect(user.name).toBe('Test');
  expect(fetchUser).toHaveBeenCalledWith(1);
});

Integration Testing

Database Testing

import pytest
from myapp import create_app, db

@pytest.fixture
def app():
    app = create_app('testing')
    with app.app_context():
        db.create_all()
        yield app
        db.session.remove()
        db.drop_all()

def test_user_can_be_saved_to_database(app):
    user = User(email='test@example.com')
    db.session.add(user)
    db.session.commit()

    retrieved = User.query.filter_by(email='test@example.com').first()
    assert retrieved is not None
    assert retrieved.email == 'test@example.com'

API Testing

def test_api_returns_user_list(client):
    response = client.get('/api/users')

    assert response.status_code == 200
    assert len(response.json) > 0
    assert 'email' in response.json[0]

End-to-End Testing

Web Testing (Playwright/Selenium)

// Playwright example
test('user can login', async ({ page }) => {
  await page.goto('https://example.com');

  await page.fill('[name="email"]', 'user@example.com');
  await page.fill('[name="password"]', 'password123');
  await page.click('button[type="submit"]');

  await expect(page.locator('.welcome')).toContainText('Welcome back');
});

Test Fixtures and Factories

Fixtures

@pytest.fixture
def sample_user():
    return User(
        email='test@example.com',
        name='Test User'
    )

@pytest.fixture
def authenticated_client(client, sample_user):
    client.login(sample_user)
    return client

Factories

import factory

class UserFactory(factory.Factory):
    class Meta:
        model = User

    email = factory.Sequence(lambda n: f'user{n}@example.com')
    name = factory.Faker('name')
    is_active = True

# Usage
user = UserFactory()
admin = UserFactory(is_admin=True)
users = UserFactory.create_batch(10)

Testing Best Practices

Do's

  • ✅ Write tests first (TDD)
  • ✅ Test behavior, not implementation
  • ✅ Keep tests simple and readable
  • ✅ Use descriptive test names
  • ✅ Test edge cases and errors
  • ✅ Keep tests fast
  • ✅ Make tests independent
  • ✅ Use fixtures for common setup

Don'ts

  • ❌ Test framework/library code
  • ❌ Test multiple things in one test
  • ❌ Use random data without seeding
  • ❌ Depend on test execution order
  • ❌ Leave commented-out tests
  • ❌ Skip tests without good reason
  • ❌ Have flaky tests

Test Organization

project/
├── src/
│   └── myapp/
│       ├── __init__.py
│       └── calculator.py
└── tests/
    ├── __init__.py
    ├── conftest.py          # Shared fixtures
    ├── unit/
    │   └── test_calculator.py
    ├── integration/
    │   └── test_database.py
    └── e2e/
        └── test_user_flow.py

Code Coverage

Generate Coverage Report

# Python
pytest --cov=myapp --cov-report=html

# JavaScript
jest --coverage

# View coverage
open htmlcov/index.html

Coverage Goals

  • Critical business logic: 100%
  • Most code: 80%+
  • E2E scripts: Lower coverage OK
  • Don't sacrifice test quality for coverage numbers

Common Testing Patterns

Testing Exceptions

def test_raises_error():
    with pytest.raises(ValueError, match="Invalid input"):
        function_that_raises("bad")

Testing Async Code

@pytest.mark.asyncio
async def test_async_function():
    result = await async_function()
    assert result == expected

Testing Time-Dependent Code

@patch('myapp.datetime')
def test_time_dependent(mock_datetime):
    mock_datetime.now.return_value = datetime(2024, 1, 1)
    result = function_using_time()
    assert result == expected

Continuous Integration

# .github/workflows/test.yml
name: Tests
on: [push, pull_request]
jobs:
  test:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v2
      - name: Run tests
        run: |
          pip install -r requirements-dev.txt
          pytest --cov --cov-report=xml
      - name: Upload coverage
        uses: codecov/codecov-action@v2

Remember: Good tests are your safety net. They give you confidence to refactor and add features. Invest time in writing quality tests!