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97 lines
2.7 KiB
Python
97 lines
2.7 KiB
Python
import random
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from datetime import datetime
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from app.core.settings import settings
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from app.db.mock_database import SessionMockLocal
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from app.db.mock_models import Customer, Order, Vehicle
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VEHICLE_MODELS = [
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"Toyota Corolla",
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"Honda Civic",
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"Chevrolet Onix",
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"Hyundai HB20",
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"Volkswagen T-Cross",
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"Jeep Compass",
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"Fiat Argo",
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"Nissan Kicks",
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"Renault Duster",
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"Ford Ranger",
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]
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CATEGORIES = ["hatch", "sedan", "suv", "pickup"]
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NAMES = [
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"Ana Souza",
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"Bruno Lima",
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"Carla Mendes",
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"Diego Santos",
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"Eduarda Alves",
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"Felipe Rocha",
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"Gabriela Costa",
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"Henrique Martins",
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"Isabela Ferreira",
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"Joao Ribeiro",
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]
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def _cpf_from_index(index: int) -> str:
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return str(10_000_000_000 + index).zfill(11)
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def seed_mock_data() -> None:
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if not settings.mock_seed_enabled:
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return
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rng = random.Random(42)
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db = SessionMockLocal()
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try:
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if db.query(Vehicle).count() == 0:
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vehicles = []
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for idx in range(60):
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model = VEHICLE_MODELS[idx % len(VEHICLE_MODELS)]
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category = CATEGORIES[idx % len(CATEGORIES)]
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base_price = 55_000 + (idx * 1_700)
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noise = rng.randint(-7_000, 9_000)
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vehicles.append(
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Vehicle(
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modelo=f"{model} {2020 + (idx % 6)}",
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categoria=category,
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preco=float(max(35_000, base_price + noise)),
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)
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)
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db.add_all(vehicles)
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db.commit()
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if db.query(Customer).count() == 0:
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customers = []
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for idx in range(120):
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entropy = (idx * 9973) % 10_000
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customers.append(
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Customer(
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cpf=_cpf_from_index(idx),
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nome=f"{NAMES[idx % len(NAMES)]} {idx + 1}",
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score=300 + (entropy % 550),
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limite_credito=float(30_000 + (entropy * 12)),
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possui_restricao=(idx % 11 == 0),
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)
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)
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db.add_all(customers)
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db.commit()
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if db.query(Order).count() == 0:
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orders = []
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for idx in range(40):
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created = datetime(2026, 1, 1, 8, 0, 0)
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orders.append(
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Order(
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numero_pedido=f"PED-{2026}{idx + 1:05d}",
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cpf=_cpf_from_index(idx),
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status="Ativo",
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created_at=created,
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)
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)
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db.add_all(orders)
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db.commit()
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finally:
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db.close()
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