async-testing-expert

name	Async Testing Expert
description	Comprehensive pytest skill for async Python testing with proper mocking, fixtures, and patterns from production-ready test suites. Use when writing or improving async tests for Python applications, especially FastAPI backends with database interactions.

Async Testing Expert

Expert guidance for writing comprehensive async Python tests using pytest, based on production patterns from a 387-test FastAPI backend test suite.

When to Use This Skill

Activate this skill when:

• Writing async tests for FastAPI applications
• Testing async database operations (PostgreSQL, MySQL, etc.)
• Setting up pytest fixtures for async applications
• Creating mock objects for database connections
• Testing services with dependency injection
• Writing DAO (Data Access Object) layer tests
• Testing async API endpoints

Core Principles

1. Test Organization

tests/
├── conftest.py           # Shared fixtures (app, client, event_loop, faker)
├── fakes.py              # Reusable mock objects (FakeConnection, FakeRecord)
├── test_<module>_dao.py  # DAO layer tests
├── test_<module>_service.py  # Service layer tests
├── test_<module>_router.py   # API endpoint tests
└── test_<module>_dto.py      # DTO validation tests

2. Naming Conventions

• Test files: test_<module>_<layer>.py
• Test functions: test_<what>_<scenario> (e.g., test_create_calls_execute, test_fetch_by_id_error_maps_to_500)
• Be descriptive: readers should understand what's being tested without reading the code

3. Always Use Type Hints

async def test_fetch_user_success(faker: Faker) -> None:
    user_id: int = faker.random_int(1, 100)
    conn: FakeConnection = FakeConnection()
    # ...

Essential Fixtures (conftest.py)

FastAPI Application Fixtures

import asyncio
import pytest
from fastapi.testclient import TestClient
from httpx import AsyncClient, ASGITransport
from faker import Faker

@pytest.fixture(scope='session')
def app():
    """Create a FastAPI app instance for testing."""
    from src.config.factory import create_app
    return create_app()

@pytest.fixture(scope='session')
def client(app):
    """Provides a synchronous TestClient for FastAPI."""
    with TestClient(app) as c:
        yield c

@pytest.fixture
async def async_client(app):
    """Provides an asynchronous AsyncClient for FastAPI using ASGI transport."""
    transport = ASGITransport(app=app)
    async with AsyncClient(transport=transport, base_url='http://test') as ac:
        yield ac

@pytest.fixture
def event_loop():
    """Create a new event loop for each test."""
    loop = asyncio.new_event_loop()
    yield loop
    loop.close()

@pytest.fixture
def faker():
    """Provide a Faker instance configured for Brazilian Portuguese."""
    return Faker('pt_BR')  # Adjust locale as needed

Mock Objects for Database Testing (fakes.py)

FakeRecord - Simulate Query Results

class FakeRecord:
    """Simulate a database record with a .result() method and optional rowcount."""
    def __init__(self, data, rowcount=None):
        self._data = data
        self.rowcount = rowcount if rowcount is not None else (
            data if isinstance(data, int) else 1
        )

    def result(self):
        return self._data

FakeConnection - Full Database Mock

class FakeConnection:
    """Simulate a psqlpy/asyncpg Connection with execute, fetch, fetch_val, and fetch_row."""
    def __init__(self):
        self.execute_return = None
        self.fetch_return = None
        self.fetch_row_return = None
        self.fetch_val_return = None
        self.execute_calls = []
        self.fetch_calls = []
        self.fetch_val_calls = []

    def transaction(self):
        return FakeTransactionContext(self)

    async def __aenter__(self):
        return self

    async def __aexit__(self, exc_type, exc, tb):
        return False

    async def execute(self, stmt, parameters=None):
        self.execute_calls.append((stmt, parameters))
        if isinstance(self.execute_return, Exception):
            raise self.execute_return

        # Support list of return values for multiple execute calls
        if (isinstance(self.execute_return, list) and
            len(self.execute_return) > 0 and
            all(isinstance(item, list) for item in self.execute_return)):
            return FakeRecord(self.execute_return.pop(0))

        return FakeRecord(self.execute_return)

    async def execute_many(self, stmt, parameters_list=None):
        """Simulate execute_many for bulk operations."""
        if parameters_list is None:
            parameters_list = []

        self.execute_calls.append((stmt, parameters_list))

        if isinstance(self.execute_return, Exception):
            raise self.execute_return

        total_rows = len(parameters_list) if parameters_list else 0
        return FakeRecord(data=total_rows, rowcount=total_rows)

    async def fetch(self, stmt, parameters=None):
        self.fetch_calls.append((stmt, parameters))
        return FakeRecord(self.fetch_return)

    async def fetch_val(self, stmt, parameters=None):
        self.fetch_val_calls.append((stmt, parameters))
        if isinstance(self.fetch_val_return, Exception):
            raise self.fetch_val_return
        return self.fetch_val_return

    async def fetch_row(self, stmt, parameters=None):
        """Simulate fetching a single row."""
        self.fetch_calls.append((stmt, parameters))

        if isinstance(self.fetch_row_return, Exception):
            raise self.fetch_row_return

        if self.fetch_row_return is not None:
            return self.fetch_row_return

        if isinstance(self.fetch_return, list) and len(self.fetch_return) > 0:
            return FakeRecord(self.fetch_return.pop(0))

        return FakeRecord(self.fetch_return)

FakeTransaction - Transaction Context Mock

class FakeTransaction:
    """Simulate a database transaction context."""
    def __init__(self, connection):
        self.connection = connection

    async def execute(self, stmt, parameters=None):
        return await self.connection.execute(stmt, parameters)

    async def execute_many(self, stmt, parameters_list=None, parameters=None):
        """Simulate execute_many - delegate to connection's execute_many if available."""
        params = parameters if parameters is not None else parameters_list
        if hasattr(self.connection, 'execute_many'):
            return await self.connection.execute_many(stmt, params)

        # Fallback: simulate by calling execute for each parameter set
        if params is None:
            params = []

        results = []
        for param_set in params:
            result = await self.connection.execute(stmt, param_set)
            results.append(result)

        if results:
            total_rowcount = sum(getattr(r, 'rowcount', 0) for r in results)
            return FakeRecord(data=total_rowcount, rowcount=total_rowcount)
        else:
            return FakeRecord(data=0, rowcount=0)

    async def fetch(self, stmt, parameters=None):
        return await self.connection.fetch(stmt, parameters)

    async def fetch_row(self, stmt, parameters=None):
        return await self.connection.fetch_row(stmt, parameters)

    async def fetch_val(self, stmt, parameters=None):
        return await self.connection.fetch_val(stmt, parameters)

class FakeTransactionContext:
    """Simulate the transaction context manager returned by conn.transaction()."""
    def __init__(self, connection):
        self.connection = connection
        self.transaction = FakeTransaction(connection)

    async def __aenter__(self):
        return self.transaction

    async def __aexit__(self, exc_type, exc, tb):
        return False

Testing Patterns

Pattern 1: DAO Layer Tests (Direct Method Testing)

Use __wrapped__ to bypass connection decorators:

@pytest.mark.asyncio
async def test_create_calls_execute(faker):
    """Test that create method calls execute with correct SQL and parameters."""
    # Arrange: Prepare test data
    create_dto = UserDTO.Create(
        name=faker.name(),
        email=faker.email(),
        cpf=faker.ssn()
    )
    conn = FakeConnection()

    # Act: Call DAO method directly with __wrapped__
    await UserDAO.create.__wrapped__(conn, create_dto)

    # Assert: Verify execute was called with correct SQL
    assert len(conn.execute_calls) == 1
    stmt, params = conn.execute_calls[0]
    assert 'INSERT INTO users' in stmt
    assert isinstance(params, list)
    assert len(params) == len(create_dto.model_dump())

Pattern 2: Testing Exception Handling

@pytest.mark.asyncio
async def test_fetch_by_id_error_maps_to_500():
    """Test that database errors are properly mapped to DAOException."""
    conn = FakeConnection()

    async def broken_fetch_row(stmt, parameters=None):
        raise RustPSQLDriverPyBaseError('db fail')

    conn.fetch_row = broken_fetch_row

    with pytest.raises(DAOException) as exc:
        await UserDAO.fetch_by_id.__wrapped__(conn, 1)

    err = exc.value
    assert err.status_code == 500
    assert 'Erro ao buscar' in err.detail

Pattern 3: Service Layer Tests with Dependency Injection

Create dummy dependencies for isolated testing:

class DummyUserAdapter:
    """Mock adapter for testing service layer."""
    def __init__(self, users):
        self.users = users
        self.called = False

    async def get_users_by_permission(self, _permission_id, _auth_header, _permission_scope):
        self.called = True
        return self.users

class DummyUserDAO:
    """Mock DAO for testing service layer."""
    def __init__(self):
        self.fetch_called = False
        self.create_called = False

    async def fetch_all(self):
        self.fetch_called = True
        return [UserDTO.Read(id=1, name='Test User', email='[e-mail]')]

    async def create(self, dto):
        self.create_called = (dto,)

@pytest.mark.asyncio
async def test_service_coordinates_dao_and_adapter():
    """Test that service properly coordinates between DAO and adapter."""
    adapter = DummyUserAdapter([])
    dao = DummyUserDAO()
    service = UserService(user_adapter=adapter, user_dao=dao)

    result = await service.get_all_users()

    assert dao.fetch_called
    assert isinstance(result[0], UserDTO.Read)

Pattern 4: Monkeypatching for Connection Mocking

@pytest.mark.asyncio
async def test_assign_with_dal_connection(monkeypatch, faker):
    """Test method that uses DAL connection wrapper."""
    from src.domain.dal import DAL

    conn = FakeConnection()

    # Monkeypatch connection acquisition
    async def fake_get_connection(cls):
        return conn

    monkeypatch.setattr(DAL, '_DAL__get_connection', classmethod(fake_get_connection))

    # Stub other dependencies
    async def fake_verify_scope(id_, scope_type):
        return None

    monkeypatch.setattr(UserDAO, '_verify_scope', fake_verify_scope)

    # Prepare test data
    dto = UserDTO.Assign(user_id=1, role_id=2)

    # Call the actual DAO method (not __wrapped__)
    await UserDAO.assign(10, dto)

    # Verify execution
    assert len(conn.execute_calls) > 0

Pattern 5: Testing Batch Operations

@pytest.mark.asyncio
async def test_sync_calls_execute_many(faker):
    """Test that bulk sync uses execute_many for efficiency."""
    items = [
        UserDTO.Create(name=faker.name(), email=faker.email())
        for _ in range(3)
    ]

    conn = FakeConnection()
    executed = []

    async def fake_execute_many(stmt, parameters=None, **kwargs):
        params = parameters if parameters is not None else kwargs.get('parameters_list')
        executed.append((stmt, params))

    # Patch transaction's execute_many
    original_transaction = conn.transaction

    async def patched_transaction():
        t = await original_transaction().__aenter__()
        t.execute_many = fake_execute_many
        return t

    class PatchedTransactionContext:
        async def __aenter__(self):
            return await patched_transaction()

        async def __aexit__(self, exc_type, exc, tb):
            return False

    conn.transaction = lambda: PatchedTransactionContext()

    await UserDAO.sync.__wrapped__(conn, items)

    # Verify batch execution
    assert len(executed) == 1
    stmt, params = executed[0]
    assert 'INSERT INTO users' in stmt
    assert len(params[0]) == len(items)

Pattern 6: FastAPI Endpoint Testing

@pytest.mark.asyncio
async def test_get_users_endpoint(async_client, monkeypatch):
    """Test GET /users endpoint returns proper response."""
    # Mock the service layer
    async def mock_get_users():
        return [UserDTO.Read(id=1, name='Test', email='[e-mail]')]

    monkeypatch.setattr('src.api.path.users.UserService.get_all', mock_get_users)

    # Make request
    response = await async_client.get('/users')

    # Assert response
    assert response.status_code == 200
    data = response.json()
    assert len(data) == 1
    assert data[0]['name'] == 'Test'

Pattern 7: Testing with Multiple Return Values

@pytest.mark.asyncio
async def test_multiple_queries_with_different_results(faker):
    """Test method that makes multiple queries with different expected results."""
    conn = FakeConnection()

    # Set up multiple return values (will be popped in order)
    conn.execute_return = [
        [{'id': 1, 'status': 'pending'}],  # First query
        [{'id': 2, 'status': 'approved'}]  # Second query
    ]

    # First call gets first result
    result1 = await UserDAO.some_method.__wrapped__(conn, 1)
    assert result1[0]['status'] == 'pending'

    # Second call gets second result
    result2 = await UserDAO.some_method.__wrapped__(conn, 2)
    assert result2[0]['status'] == 'approved'

Pattern 8: Parametrized Tests for Multiple Scenarios

@pytest.mark.asyncio
@pytest.mark.parametrize('status,expected_count', [
    ('pending', 5),
    ('approved', 3),
    ('rejected', 2),
])
async def test_count_by_status(status, expected_count):
    """Test counting users by different status values."""
    conn = FakeConnection()
    conn.fetch_val_return = expected_count

    result = await UserDAO.count_by_status.__wrapped__(conn, status)

    assert result == expected_count
    assert len(conn.fetch_val_calls) == 1

Best Practices Checklist

Before Writing Tests

• Identify the layer being tested (DAO/Service/Router/DTO)
• Determine required fixtures (app, client, faker, etc.)
• Plan mock objects needed (FakeConnection, dummy services, etc.)
• Understand the happy path and error scenarios

During Test Writing

• Use descriptive test names: test_<action>_<scenario>
• Follow Arrange-Act-Assert pattern with clear sections
• Add docstrings explaining what the test validates
• Use type hints for all variables
• Mock at the right level (connection for DAO, service for router)
• Verify both success and failure paths
• Check SQL statements, not just return values
• Validate parameter counts and types

After Writing Tests

• Run tests: pytest tests/test_your_module.py -v
• Check coverage: pytest --cov=src/domain/dao/your_module tests/test_your_module.py
• Verify all code paths are tested
• Remove commented code and print statements
• Ensure tests are isolated (no shared state)
• Run tests multiple times to verify consistency

Common Pitfalls to Avoid

1. Forgetting @pytest.mark.asyncio: All async tests need this decorator
2. Not using wrapped: When testing DAO methods directly, bypass decorators
3. Sharing state between tests: Each test should be independent
4. Over-mocking: Mock at boundaries, not internal implementation details
5. Ignoring SQL validation: Always verify the actual SQL being executed
6. Not testing exceptions: Error paths are critical for robustness
7. Missing type hints: Makes tests harder to understand and maintain
8. Vague test names: Name should describe what and when

Performance Tips

• Use scope='session' for expensive fixtures (app creation)
• Use scope='function' (default) for mutable fixtures
• Mock database connections rather than hitting real databases
• Group related tests in same file for better context
• Use pytest -x to stop on first failure during development
• Run specific test files during development: pytest tests/test_dao.py

Integration with CI/CD

# Run all tests with coverage
pytest --cov=src --cov-report=html --cov-report=term

# Run only unit tests (fast)
pytest tests/ -m "not integration"

# Run with verbose output
pytest -v --tb=short

# Run specific test file
pytest tests/test_user_dao.py -v

# Run tests matching pattern
pytest -k "test_create" -v

Example: Complete Test File

"""Tests for UserDAO database access layer."""
from datetime import datetime
import pytest
from src.domain.dal.dao.user import UserDAO
from src.domain.dal.dao.exception import DAOException
from src.domain.dto.user import UserDTO
from tests.fakes import FakeConnection, FakeRecord


@pytest.mark.asyncio
async def test_create_inserts_user(faker):
    """Test that create method inserts user with correct parameters."""
    create_dto = UserDTO.Create(
        name=faker.name(),
        email=faker.email(),
        cpf=faker.ssn()
    )
    conn = FakeConnection()

    await UserDAO.create.__wrapped__(conn, create_dto)

    assert len(conn.execute_calls) == 1
    stmt, params = conn.execute_calls[0]
    assert 'INSERT INTO users' in stmt
    assert params[0] == create_dto.name


@pytest.mark.asyncio
async def test_fetch_by_id_returns_user(faker):
    """Test that fetch_by_id returns properly formatted UserDTO."""
    fake_row = {
        'id': faker.random_int(1, 100),
        'name': faker.name(),
        'email': faker.email(),
        'created_at': faker.date_time()
    }
    conn = FakeConnection()
    conn.fetch_row_return = FakeRecord(fake_row)

    result = await UserDAO.fetch_by_id.__wrapped__(conn, fake_row['id'])

    assert result.id == fake_row['id']
    assert result.name == fake_row['name']
    assert isinstance(result, UserDTO.Read)


@pytest.mark.asyncio
async def test_fetch_by_id_raises_on_db_error():
    """Test that database errors are properly handled and mapped."""
    conn = FakeConnection()

    async def broken_fetch_row(stmt, parameters=None):
        raise Exception('Connection lost')

    conn.fetch_row = broken_fetch_row

    with pytest.raises(DAOException) as exc:
        await UserDAO.fetch_by_id.__wrapped__(conn, 1)

    assert exc.value.status_code == 500

Quick Reference Commands

# Run single test
pytest tests/test_user_dao.py::test_create_inserts_user -v

# Run all tests in file
pytest tests/test_user_dao.py -v

# Run with coverage for specific module
pytest --cov=src/domain/dao/user tests/test_user_dao.py

# Stop on first failure
pytest -x tests/

# Show local variables on failure
pytest --showlocals tests/

# Run last failed tests
pytest --lf tests/

Summary

This skill provides production-proven patterns for async Python testing:

1. Proper fixture setup for FastAPI apps and async clients
2. Comprehensive mocking with FakeConnection and related classes
3. Layer-specific testing patterns (DAO, Service, Router)
4. Exception handling and error path testing
5. Monkeypatching for dependency injection
6. Batch operation testing patterns
7. Best practices for maintainable, robust tests

When in doubt, follow the "Arrange-Act-Assert" pattern and always verify both the happy path and error scenarios.