home / skills / einverne / dotfiles / test-expert
This skill helps you write effective tests, apply TDD, and improve coverage across Python and JavaScript projects for higher quality.
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---
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
- **F**ast: Tests should run quickly
- **I**solated: Tests shouldn't depend on each other
- **R**epeatable: Same result every time
- **S**elf-Validating: Pass or fail, no manual checking
- **T**imely: 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
```python
def test_add_numbers():
assert add(2, 3) == 5 # Function doesn't exist yet
```
2. **Green**: Write minimal code to pass
```python
def add(a, b):
return a + b
```
3. **Refactor**: Improve code quality
```python
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
```python
# Good: Clear, focused, independent
def test_user_can_be_created_with_email():
# Arrange
email = "[email protected]"
# 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
```python
# 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)
```python
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)
```javascript
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)
```bash
#!/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
```python
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
```javascript
// 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
```python
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='[email protected]')
db.session.add(user)
db.session.commit()
retrieved = User.query.filter_by(email='[email protected]').first()
assert retrieved is not None
assert retrieved.email == '[email protected]'
```
### API Testing
```python
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)
```javascript
// Playwright example
test('user can login', async ({ page }) => {
await page.goto('https://example.com');
await page.fill('[name="email"]', '[email protected]');
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
```python
@pytest.fixture
def sample_user():
return User(
email='[email protected]',
name='Test User'
)
@pytest.fixture
def authenticated_client(client, sample_user):
client.login(sample_user)
return client
```
### Factories
```python
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
```bash
# 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
```python
def test_raises_error():
with pytest.raises(ValueError, match="Invalid input"):
function_that_raises("bad")
```
### Testing Async Code
```python
@pytest.mark.asyncio
async def test_async_function():
result = await async_function()
assert result == expected
```
### Testing Time-Dependent Code
```python
@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
```yaml
# .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!
This skill helps developers design and implement effective tests, adopt test-driven development (TDD), and raise test quality across unit, integration, and end-to-end levels. I focus on practical patterns, tooling tips for Python (pytest) and other ecosystems, and measurable coverage goals to keep your project safe to change. Use this skill to build reliable, fast, and maintainable test suites.
I inspect code layout, testing targets, and current test practices, then recommend concrete tests, fixtures, and CI steps. I guide you through the Red-Green-Refactor TDD loop, suggest what to mock or stub, and translate testing principles into examples and test names. I also provide coverage goals, test organization patterns, and CI configuration snippets to integrate tests into your workflow.
How do I start TDD on an existing codebase?
Begin by writing tests around small, well-understood modules or bugs. Create failing tests that capture desired behavior, implement minimal fixes, then iterate with refactors. Introduce fixtures and dependency injection to make code testable.
When should I mock vs use real services?
Mock for external APIs, slow operations, non-deterministic behavior, or hard-to-trigger errors. Use real services for integration tests with an isolated test environment to validate interactions end-to-end.
What coverage target should I set?
Aim for 80%+ overall and 100% for critical business logic. Prioritize meaningful tests over raw coverage numbers; avoid testing framework code or trivial getters.