feat(seed): add standalone seed scripts for districts, plans, and market data
- scripts/seed-districts.ts: Vietnam district/ward data for HCM, Hanoi, Da Nang with sample properties - scripts/seed-plans.ts: Subscription plans (FREE, AGENT_PRO, INVESTOR, ENTERPRISE) - scripts/import-market-data.ts: Market index data across all 3 cities with realistic pricing - All scripts are idempotent (upsert/ON CONFLICT DO NOTHING) - Refactored prisma/seed.ts to import shared data from scripts, removing duplication Co-Authored-By: Paperclip <noreply@paperclip.ing>
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Ho Ngoc Hai
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scripts/import-market-data.ts
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283
scripts/import-market-data.ts
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/**
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* Import sample market data for development.
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*
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* Generates MarketIndex records across HCM, Hanoi, and Da Nang
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* with realistic pricing for Vietnamese real estate.
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*
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* Usage: npx tsx scripts/import-market-data.ts
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* Idempotent: uses upsert on compound unique constraint.
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*/
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import { PrismaClient, PropertyType } from '@prisma/client';
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const prisma = new PrismaClient();
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// =============================================================================
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// Market data configuration — avg price per m2 (VND) by city/district
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// =============================================================================
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interface DistrictPricing {
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district: string;
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avgPriceM2: Record<string, number>; // keyed by PropertyType
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}
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const MARKET_DATA: Record<string, DistrictPricing[]> = {
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'Hồ Chí Minh': [
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{
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district: 'Quận 1',
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avgPriceM2: {
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APARTMENT: 120_000_000,
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TOWNHOUSE: 250_000_000,
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OFFICE: 80_000_000,
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SHOPHOUSE: 300_000_000,
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},
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},
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{
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district: 'Quận 3',
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avgPriceM2: {
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APARTMENT: 90_000_000,
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TOWNHOUSE: 180_000_000,
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OFFICE: 60_000_000,
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},
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},
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{
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district: 'Quận 7',
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avgPriceM2: {
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APARTMENT: 65_000_000,
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TOWNHOUSE: 130_000_000,
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LAND: 85_000_000,
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},
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},
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{
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district: 'Thủ Đức',
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avgPriceM2: {
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APARTMENT: 55_000_000,
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TOWNHOUSE: 100_000_000,
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LAND: 60_000_000,
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VILLA: 120_000_000,
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},
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},
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{
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district: 'Quận Bình Thạnh',
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avgPriceM2: {
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APARTMENT: 70_000_000,
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TOWNHOUSE: 140_000_000,
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},
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},
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{
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district: 'Quận Phú Nhuận',
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avgPriceM2: {
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APARTMENT: 80_000_000,
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TOWNHOUSE: 160_000_000,
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},
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},
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{
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district: 'Quận Tân Bình',
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avgPriceM2: {
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APARTMENT: 50_000_000,
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TOWNHOUSE: 110_000_000,
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LAND: 55_000_000,
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},
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},
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{
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district: 'Quận Gò Vấp',
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avgPriceM2: {
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APARTMENT: 45_000_000,
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TOWNHOUSE: 90_000_000,
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LAND: 50_000_000,
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},
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},
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],
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'Hà Nội': [
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{
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district: 'Hoàn Kiếm',
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avgPriceM2: {
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APARTMENT: 110_000_000,
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TOWNHOUSE: 350_000_000,
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SHOPHOUSE: 400_000_000,
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},
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},
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{
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district: 'Ba Đình',
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avgPriceM2: {
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APARTMENT: 95_000_000,
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TOWNHOUSE: 220_000_000,
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VILLA: 200_000_000,
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},
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},
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{
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district: 'Đống Đa',
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avgPriceM2: {
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APARTMENT: 75_000_000,
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TOWNHOUSE: 180_000_000,
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},
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},
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{
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district: 'Hai Bà Trưng',
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avgPriceM2: {
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APARTMENT: 70_000_000,
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TOWNHOUSE: 170_000_000,
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},
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},
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{
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district: 'Cầu Giấy',
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avgPriceM2: {
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APARTMENT: 65_000_000,
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TOWNHOUSE: 150_000_000,
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OFFICE: 55_000_000,
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},
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},
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{
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district: 'Tây Hồ',
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avgPriceM2: {
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APARTMENT: 80_000_000,
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VILLA: 180_000_000,
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TOWNHOUSE: 160_000_000,
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},
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},
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{
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district: 'Nam Từ Liêm',
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avgPriceM2: {
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APARTMENT: 55_000_000,
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TOWNHOUSE: 120_000_000,
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LAND: 65_000_000,
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},
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},
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],
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'Đà Nẵng': [
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{
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district: 'Hải Châu',
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avgPriceM2: {
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APARTMENT: 45_000_000,
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TOWNHOUSE: 100_000_000,
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SHOPHOUSE: 120_000_000,
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},
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},
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{
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district: 'Thanh Khê',
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avgPriceM2: {
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APARTMENT: 35_000_000,
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TOWNHOUSE: 70_000_000,
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LAND: 40_000_000,
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},
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},
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{
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district: 'Sơn Trà',
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avgPriceM2: {
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APARTMENT: 40_000_000,
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TOWNHOUSE: 80_000_000,
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VILLA: 95_000_000,
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},
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},
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{
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district: 'Ngũ Hành Sơn',
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avgPriceM2: {
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APARTMENT: 42_000_000,
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VILLA: 110_000_000,
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LAND: 55_000_000,
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},
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},
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{
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district: 'Liên Chiểu',
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avgPriceM2: {
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APARTMENT: 28_000_000,
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TOWNHOUSE: 55_000_000,
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LAND: 30_000_000,
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},
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},
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{
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district: 'Cẩm Lệ',
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avgPriceM2: {
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APARTMENT: 30_000_000,
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TOWNHOUSE: 60_000_000,
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LAND: 35_000_000,
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},
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},
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],
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};
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const PERIODS = ['2025-Q3', '2025-Q4', '2026-Q1'];
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function randomVariation(base: number, pct: number): number {
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return base * (1 + (Math.random() - 0.5) * 2 * pct);
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}
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async function importMarketData() {
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console.log('Importing market data for HCM, Hanoi, Da Nang...\n');
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let total = 0;
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for (const [city, districts] of Object.entries(MARKET_DATA)) {
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console.log(` ${city}:`);
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let cityCount = 0;
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for (const { district, avgPriceM2 } of districts) {
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for (const [propTypeKey, basePrice] of Object.entries(avgPriceM2)) {
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const propertyType = propTypeKey as PropertyType;
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for (const period of PERIODS) {
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const variation = randomVariation(basePrice, 0.08);
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const medianArea = propertyType === 'LAND' ? 100 : propertyType === 'VILLA' ? 200 : 75;
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const totalListings = Math.floor(50 + Math.random() * 400);
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const daysOnMarket = 20 + Math.random() * 70;
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// YoY change: slight uptrend with noise
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const periodIdx = PERIODS.indexOf(period);
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const trendPct = (periodIdx - 1) * 2; // negative for older, positive for newer
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const yoyChange = trendPct + (Math.random() - 0.5) * 10;
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await prisma.marketIndex.upsert({
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where: {
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district_city_propertyType_period: {
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district,
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city,
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propertyType,
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period,
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},
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},
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update: {
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avgPriceM2: variation,
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medianPrice: BigInt(Math.round(variation * medianArea)),
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totalListings,
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daysOnMarket,
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inventoryLevel: Math.floor(totalListings * 0.6),
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absorptionRate: 0.2 + Math.random() * 0.5,
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yoyChange,
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},
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create: {
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district,
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city,
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propertyType,
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period,
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avgPriceM2: variation,
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medianPrice: BigInt(Math.round(variation * medianArea)),
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totalListings,
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daysOnMarket,
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inventoryLevel: Math.floor(totalListings * 0.6),
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absorptionRate: 0.2 + Math.random() * 0.5,
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yoyChange,
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},
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});
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cityCount++;
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total++;
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}
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}
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}
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console.log(` ${cityCount} market index records`);
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}
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console.log(`\nTotal: ${total} market index records imported.`);
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}
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if (require.main === module) {
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importMarketData()
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.catch((e) => {
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console.error('Import market data failed:', e);
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process.exit(1);
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})
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.finally(() => prisma.$disconnect());
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}
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export { importMarketData, MARKET_DATA, PERIODS };
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