import random
from datetime import datetime

from app.core.settings import settings
from app.db.mock_database import SessionMockLocal
from app.db.mock_models import Customer, Order, Vehicle


VEHICLE_MODELS = [
    "Toyota Corolla",
    "Honda Civic",
    "Chevrolet Onix",
    "Hyundai HB20",
    "Volkswagen T-Cross",
    "Jeep Compass",
    "Fiat Argo",
    "Nissan Kicks",
    "Renault Duster",
    "Ford Ranger",
]

CATEGORIES = ["hatch", "sedan", "suv", "pickup"]
NAMES = [
    "Ana Souza",
    "Bruno Lima",
    "Carla Mendes",
    "Diego Santos",
    "Eduarda Alves",
    "Felipe Rocha",
    "Gabriela Costa",
    "Henrique Martins",
    "Isabela Ferreira",
    "Joao Ribeiro",
]


def _cpf_from_index(index: int) -> str:
    """Gera um CPF numerico deterministico de 11 digitos a partir do indice."""
    return str(10_000_000_000 + index).zfill(11)


def seed_mock_data() -> None:
    """Popula dados mock iniciais de veiculos, clientes e pedidos quando habilitado."""
    if not settings.mock_seed_enabled:
        return

    rng = random.Random(42)
    db = SessionMockLocal()
    try:
        if db.query(Vehicle).count() == 0:
            vehicles = []
            for idx in range(60):
                model = VEHICLE_MODELS[idx % len(VEHICLE_MODELS)]
                category = CATEGORIES[idx % len(CATEGORIES)]
                base_price = 55_000 + (idx * 1_700)
                noise = rng.randint(-7_000, 9_000)
                vehicles.append(
                    Vehicle(
                        modelo=f"{model} {2020 + (idx % 6)}",
                        categoria=category,
                        preco=float(max(35_000, base_price + noise)),
                    )
                )
            db.add_all(vehicles)
            db.commit()

        if db.query(Customer).count() == 0:
            customers = []
            for idx in range(120):
                entropy = (idx * 9973) % 10_000
                customers.append(
                    Customer(
                        cpf=_cpf_from_index(idx),
                        nome=f"{NAMES[idx % len(NAMES)]} {idx + 1}",
                        score=300 + (entropy % 550),
                        limite_credito=float(30_000 + (entropy * 12)),
                        possui_restricao=(idx % 11 == 0),
                    )
                )
            db.add_all(customers)
            db.commit()

        if db.query(Order).count() == 0:
            orders = []
            for idx in range(40):
                created = datetime(2026, 1, 1, 8, 0, 0)
                orders.append(
                    Order(
                        numero_pedido=f"PED-{2026}{idx + 1:05d}",
                        cpf=_cpf_from_index(idx),
                        status="Ativo",
                        created_at=created,
                    )
                )
            db.add_all(orders)
            db.commit()
    finally:
        db.close()