goodgo-platform/scripts/import-market-data.ts

/**
 * Import sample market data for development.
 *
 * Generates MarketIndex records across HCM, Hanoi, and Da Nang
 * with realistic pricing for Vietnamese real estate.
 *
 * Usage: npx tsx scripts/import-market-data.ts
 * Idempotent: uses upsert on compound unique constraint.
 */

import { PrismaPg } from '@prisma/adapter-pg';
import { PrismaClient, type PropertyType } from '@prisma/client';
import pg from 'pg';

const pool = new pg.Pool({ connectionString: process.env['DATABASE_URL'] });
const adapter = new PrismaPg(pool);
const prisma = new PrismaClient({ adapter });

// =============================================================================
// Market data configuration — avg price per m2 (VND) by city/district
// =============================================================================

interface DistrictPricing {
  district: string;
  avgPriceM2: Record<string, number>; // keyed by PropertyType
}

const MARKET_DATA: Record<string, DistrictPricing[]> = {
  'Hồ Chí Minh': [
    {
      district: 'Quận 1',
      avgPriceM2: {
        APARTMENT: 120_000_000,
        TOWNHOUSE: 250_000_000,
        OFFICE: 80_000_000,
        SHOPHOUSE: 300_000_000,
      },
    },
    {
      district: 'Quận 3',
      avgPriceM2: {
        APARTMENT: 90_000_000,
        TOWNHOUSE: 180_000_000,
        OFFICE: 60_000_000,
      },
    },
    {
      district: 'Quận 7',
      avgPriceM2: {
        APARTMENT: 65_000_000,
        TOWNHOUSE: 130_000_000,
        LAND: 85_000_000,
      },
    },
    {
      district: 'Thủ Đức',
      avgPriceM2: {
        APARTMENT: 55_000_000,
        TOWNHOUSE: 100_000_000,
        LAND: 60_000_000,
        VILLA: 120_000_000,
      },
    },
    {
      district: 'Quận Bình Thạnh',
      avgPriceM2: {
        APARTMENT: 70_000_000,
        TOWNHOUSE: 140_000_000,
      },
    },
    {
      district: 'Quận Phú Nhuận',
      avgPriceM2: {
        APARTMENT: 80_000_000,
        TOWNHOUSE: 160_000_000,
      },
    },
    {
      district: 'Quận Tân Bình',
      avgPriceM2: {
        APARTMENT: 50_000_000,
        TOWNHOUSE: 110_000_000,
        LAND: 55_000_000,
      },
    },
    {
      district: 'Quận Gò Vấp',
      avgPriceM2: {
        APARTMENT: 45_000_000,
        TOWNHOUSE: 90_000_000,
        LAND: 50_000_000,
      },
    },
  ],
  'Hà Nội': [
    {
      district: 'Hoàn Kiếm',
      avgPriceM2: {
        APARTMENT: 110_000_000,
        TOWNHOUSE: 350_000_000,
        SHOPHOUSE: 400_000_000,
      },
    },
    {
      district: 'Ba Đình',
      avgPriceM2: {
        APARTMENT: 95_000_000,
        TOWNHOUSE: 220_000_000,
        VILLA: 200_000_000,
      },
    },
    {
      district: 'Đống Đa',
      avgPriceM2: {
        APARTMENT: 75_000_000,
        TOWNHOUSE: 180_000_000,
      },
    },
    {
      district: 'Hai Bà Trưng',
      avgPriceM2: {
        APARTMENT: 70_000_000,
        TOWNHOUSE: 170_000_000,
      },
    },
    {
      district: 'Cầu Giấy',
      avgPriceM2: {
        APARTMENT: 65_000_000,
        TOWNHOUSE: 150_000_000,
        OFFICE: 55_000_000,
      },
    },
    {
      district: 'Tây Hồ',
      avgPriceM2: {
        APARTMENT: 80_000_000,
        VILLA: 180_000_000,
        TOWNHOUSE: 160_000_000,
      },
    },
    {
      district: 'Nam Từ Liêm',
      avgPriceM2: {
        APARTMENT: 55_000_000,
        TOWNHOUSE: 120_000_000,
        LAND: 65_000_000,
      },
    },
  ],
  'Đà Nẵng': [
    {
      district: 'Hải Châu',
      avgPriceM2: {
        APARTMENT: 45_000_000,
        TOWNHOUSE: 100_000_000,
        SHOPHOUSE: 120_000_000,
      },
    },
    {
      district: 'Thanh Khê',
      avgPriceM2: {
        APARTMENT: 35_000_000,
        TOWNHOUSE: 70_000_000,
        LAND: 40_000_000,
      },
    },
    {
      district: 'Sơn Trà',
      avgPriceM2: {
        APARTMENT: 40_000_000,
        TOWNHOUSE: 80_000_000,
        VILLA: 95_000_000,
      },
    },
    {
      district: 'Ngũ Hành Sơn',
      avgPriceM2: {
        APARTMENT: 42_000_000,
        VILLA: 110_000_000,
        LAND: 55_000_000,
      },
    },
    {
      district: 'Liên Chiểu',
      avgPriceM2: {
        APARTMENT: 28_000_000,
        TOWNHOUSE: 55_000_000,
        LAND: 30_000_000,
      },
    },
    {
      district: 'Cẩm Lệ',
      avgPriceM2: {
        APARTMENT: 30_000_000,
        TOWNHOUSE: 60_000_000,
        LAND: 35_000_000,
      },
    },
  ],
};

const PERIODS = ['2025-Q3', '2025-Q4', '2026-Q1', '2026-Q2'];

function randomVariation(base: number, pct: number): number {
  return base * (1 + (Math.random() - 0.5) * 2 * pct);
}

async function importMarketData() {
  console.warn('Importing market data for HCM, Hanoi, Da Nang...\n');

  let total = 0;

  for (const [city, districts] of Object.entries(MARKET_DATA)) {
    console.warn(`  ${city}:`);
    let cityCount = 0;

    for (const { district, avgPriceM2 } of districts) {
      for (const [propTypeKey, basePrice] of Object.entries(avgPriceM2)) {
        const propertyType = propTypeKey as PropertyType;

        for (const period of PERIODS) {
          const variation = randomVariation(basePrice, 0.08);
          const medianArea = propertyType === 'LAND' ? 100 : propertyType === 'VILLA' ? 200 : 75;
          const totalListings = Math.floor(50 + Math.random() * 400);
          const daysOnMarket = 20 + Math.random() * 70;

          // YoY change: slight uptrend with noise
          const periodIdx = PERIODS.indexOf(period);
          const trendPct = (periodIdx - 1) * 2; // negative for older, positive for newer
          const yoyChange = trendPct + (Math.random() - 0.5) * 10;

          await prisma.marketIndex.upsert({
            where: {
              district_city_propertyType_period: {
                district,
                city,
                propertyType,
                period,
              },
            },
            update: {
              avgPriceM2: variation,
              medianPrice: BigInt(Math.round(variation * medianArea)),
              totalListings,
              daysOnMarket,
              inventoryLevel: Math.floor(totalListings * 0.6),
              absorptionRate: 0.2 + Math.random() * 0.5,
              yoyChange,
            },
            create: {
              district,
              city,
              propertyType,
              period,
              avgPriceM2: variation,
              medianPrice: BigInt(Math.round(variation * medianArea)),
              totalListings,
              daysOnMarket,
              inventoryLevel: Math.floor(totalListings * 0.6),
              absorptionRate: 0.2 + Math.random() * 0.5,
              yoyChange,
            },
          });

          cityCount++;
          total++;
        }
      }
    }

    console.warn(`    ${cityCount} market index records`);
  }

  console.warn(`\nTotal: ${total} market index records imported.`);
}

if (require.main === module) {
  importMarketData()
    .catch((e) => {
      console.error('Import market data failed:', e);
      process.exit(1);
    })
    .finally(() => prisma.$disconnect());
}

export { importMarketData, MARKET_DATA, PERIODS };