# Tests unitarios
def test_create_product_with_valid_data():
    pass

def test_create_product_with_invalid_code_should_raise_exception():
    pass

# Tests de integración
def test_integration_product_repository_save_and_retrieve():
    pass

# Tests de UI
def test_ui_product_form_validates_required_fields():
    pass

def test_feature_description():
    # Given (Arrange)
    setup_data = create_test_data()
    
    # When (Act)
    result = system_under_test.execute(setup_data)
    
    # Then (Assert)
    assert result.is_valid()
    assert result.meets_expectations()

def test_load_10000_products_performance():
    """Test: Cargar 10,000 productos en tiempo aceptable."""
    start_time = time.time()
    
    products = generate_sample_products(10000)
    load_products_to_database(products)
    
    end_time = time.time()
    loading_time = end_time - start_time
    
    assert loading_time < 60.0  # Máximo 1 minuto

def test_concurrent_sales_processing():
    """Test: Procesar ventas concurrentes sin degradación."""
    import threading
    
    def process_sale_thread():
        return sales_service.create_sale(sample_sale_data)
    
    threads = []
    for _ in range(50):  # 50 ventas simultáneas
        thread = threading.Thread(target=process_sale_thread)
        threads.append(thread)
    
    start_time = time.time()
    
    for thread in threads:
        thread.start()
    
    for thread in threads:
        thread.join()
    
    end_time = time.time()
    total_time = end_time - start_time
    
    assert total_time < 10.0  # Máximo 10 segundos

import psutil
import gc

def test_memory_usage_stability():
    """Test: Uso de memoria estable durante operaciones prolongadas."""
    process = psutil.Process()
    initial_memory = process.memory_info().rss
    
    # Simular 1000 operaciones
    for i in range(1000):
        product_service.create_product(generate_sample_product())
        if i % 100 == 0:
            gc.collect()  # Forzar garbage collection
    
    final_memory = process.memory_info().rss
    memory_increase = final_memory - initial_memory
    
    # No debe aumentar más de 100MB
    assert memory_increase < 100 * 1024 * 1024

def test_sql_injection_prevention():
    """Test: Prevención de inyección SQL en búsquedas."""
    malicious_input = "'; DROP TABLE products; --"
    
    # Intentar inyección SQL
    results = product_service.search_products(malicious_input)
    
    # Verificar que no se ejecutó código malicioso
    assert products_table_exists()
    assert isinstance(results, list)

def test_input_validation_security():
    """Test: Validación robusta de entrada de datos."""
    dangerous_inputs = [
        "<script>alert('xss')</script>",
        "../../etc/passwd",
        "SELECT * FROM users",
        "../../../windows/system32"
    ]
    
    for dangerous_input in dangerous_inputs:
        with pytest.raises(ValidationException):
            product_service.create_product({
                "name": dangerous_input,
                "price": 100
            })

def test_session_security():
    """Test: Seguridad en manejo de sesiones."""
    # Autenticar usuario
    auth_result = auth_service.authenticate("admin", "password")
    token = auth_result.token
    
    # Verificar expiración de sesión
    time.sleep(SESSION_TIMEOUT + 1)
    
    validation_result = auth_service.validate_token(token)
    assert not validation_result.is_valid

def test_password_encryption():
    """Test: Las contraseñas se almacenan encriptadas."""
    password = "plain_password"
    user_data = {
        "username": "testuser",
        "password": password
    }
    
    user_service.create_user(user_data)
    
    # Verificar que la contraseña no se almacena en texto plano
    stored_user = user_repository.find_by_username("testuser")
    assert stored_user.password_hash != password
    assert len(stored_user.password_hash) > 50  # Hash largo

# tests/fixtures/product_fixtures.py

import factory
from decimal import Decimal
from src.domain.entities.product import Product
from src.domain.value_objects.money import Money

class ProductFactory(factory.Factory):
    class Meta:
        model = Product
    
    code = factory.Sequence(lambda n: f"P{n:03d}")
    name = factory.Faker('catch_phrase')
    price = factory.LazyAttribute(lambda obj: Money(Decimal(str(factory.Faker('pydecimal', left_digits=4, right_digits=2, positive=True)))))
    stock_min = factory.Faker('pyint', min_value=1, max_value=10)
    stock_max = factory.Faker('pyint', min_value=50, max_value=200)
    category = factory.Faker('word')

# Uso en tests
def test_example_with_factory():
    product = ProductFactory()
    assert product.code.startswith('P')
    assert isinstance(product.price, Money)

# tests/fixtures/database_fixtures.py

import pytest
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
from src.db.models import Base

@pytest.fixture(scope="session")
def test_engine():
    """Motor de base de datos de prueba."""
    engine = create_engine("sqlite:///:memory:", echo=False)
    Base.metadata.create_all(engine)
    return engine

@pytest.fixture
def test_session(test_engine):
    """Sesión de base de datos limpia para cada test."""
    Session = sessionmaker(bind=test_engine)
    session = Session()
    
    yield session
    
    session.rollback()
    session.close()

# tests/utils/data_generators.py

def generate_realistic_product_catalog(size=1000):
    """Generar catálogo realista de productos."""
    categories = ["Electronics", "Office Supplies", "Furniture", "Tools"]
    brands = ["HP", "Dell", "Logitech", "Canon", "Epson"]
    
    products = []
    for i in range(size):
        category = random.choice(categories)
        brand = random.choice(brands)
        
        product_data = {
            "code": f"P{i+1:05d}",
            "name": f"{brand} {category} Item {i+1}",
            "price": Decimal(str(round(random.uniform(10.0, 5000.0), 2))),
            "category": category,
            "brand": brand,
            "stock_min": random.randint(5, 20),
            "stock_max": random.randint(50, 200)
        }
        products.append(product_data)
    
    return products

# scripts/generate_quality_report.py

def generate_quality_dashboard():
    """Generar dashboard de métricas de calidad."""
    
    # Ejecutar tests y obtener métricas
    test_results = run_test_suite()
    coverage_data = get_coverage_metrics()
    performance_data = get_performance_metrics()
    
    dashboard = {
        "timestamp": datetime.now(),
        "test_summary": {
            "total_tests": test_results["total"],
            "passed": test_results["passed"],
            "failed": test_results["failed"],
            "pass_rate": test_results["passed"] / test_results["total"] * 100
        },
        "coverage": {
            "overall": coverage_data["overall"],
            "domain": coverage_data["domain"],
            "application": coverage_data["application"],
            "infrastructure": coverage_data["infrastructure"],
            "presentation": coverage_data["presentation"]
        },
        "performance": {
            "avg_test_time": performance_data["avg_time"],
            "slowest_tests": performance_data["slowest"],
            "memory_usage": performance_data["memory"]
        }
    }
    
    # Generar reporte HTML
    generate_html_dashboard(dashboard)
    
    return dashboard

def check_quality_thresholds(metrics):
    """Verificar umbrales de calidad y generar alertas."""
    
    alerts = []
    
    # Verificar cobertura mínima
    if metrics["coverage"]["overall"] < 95.0:
        alerts.append({
            "type": "coverage",
            "severity": "high",
            "message": f"Coverage below threshold: {metrics['coverage']['overall']}%"
        })
    
    # Verificar tasa de éxito de tests
    if metrics["test_summary"]["pass_rate"] < 100.0:
        alerts.append({
            "type": "test_failure",
            "severity": "critical",
            "message": f"Tests failing: {metrics['test_summary']['failed']}"
        })
    
    # Verificar performance
    if metrics["performance"]["avg_test_time"] > 100:  # ms
        alerts.append({
            "type": "performance",
            "severity": "medium",
            "message": f"Slow test execution: {metrics['performance']['avg_test_time']}ms"
        })
    
    return alerts

# scripts/review_test_health.py

def analyze_test_health():
    """Analizar salud de la suite de tests."""
    
    metrics = {
        "obsolete_tests": find_obsolete_tests(),
        "duplicate_tests": find_duplicate_tests(),
        "slow_tests": find_slow_tests(),
        "flaky_tests": find_flaky_tests(),
        "low_value_tests": find_low_value_tests()
    }
    
    return generate_test_health_report(metrics)

def test_complete_inventory_workflow():
    """Test: Flujo completo desde recepción hasta venta."""
    
    # 1. Recibir mercancía
    product = create_product("Laptop Dell", 1500.00)
    inventory_service.process_entry(product.id, quantity=10, supplier="Dell Inc")
    
    # 2. Verificar stock
    current_stock = inventory_service.get_current_stock(product.id)
    assert current_stock == 10
    
    # 3. Procesar venta
    sale_result = sales_service.create_sale([
        {"product_id": product.id, "quantity": 2, "price": 1500.00}
    ])
    assert sale_result.is_success
    
    # 4. Verificar actualización automática
    updated_stock = inventory_service.get_current_stock(product.id)
    assert updated_stock == 8
    
    # 5. Generar reporte
    report = report_service.generate_inventory_report()
    assert product.id in report.products

def test_user_error_handling():
    """Test: Manejo robusto de errores de usuario."""
    
    error_scenarios = [
        {"action": "invalid_barcode", "input": "123", "expected": "Invalid barcode format"},
        {"action": "insufficient_stock", "input": {"product_id": 1, "quantity": 999}, "expected": "Insufficient stock"},
        {"action": "duplicate_product", "input": {"code": "P001"}, "expected": "Product code already exists"},
        {"action": "invalid_price", "input": {"price": -100}, "expected": "Price must be positive"}
    ]
    
    for scenario in error_scenarios:
        with pytest.raises(BusinessRuleException) as exc_info:
            execute_user_action(scenario["action"], scenario["input"])
        
        assert scenario["expected"] in str(exc_info.value)