stats step 2: World Bank, IMF WEO, OWID, Energy-Charts, Rijksfinanciën, US Treasury, USAspending collectors + tables, timers

src/lib/server/db/schema/stats.ts

@@ -202,3 +202,155 @@ export const statsBisPolicyRate = statsSchema.table(
 	},
 	(t) => [primaryKey({ columns: [t.refArea, t.freq, t.period] })]
 );
+
+// ── A3 World Bank indicators, A4 IMF WEO (DataMapper) ─────────────────────────────────────
+
+export const statsWbIndicator = statsSchema.table(
+	'wb_indicator',
+	{
+		indicatorId: text('indicator_id').notNull(),
+		countryIso3: text('country_iso3').notNull(),
+		year: integer('year').notNull(),
+		value: doublePrecision('value')
+	},
+	(t) => [primaryKey({ columns: [t.indicatorId, t.countryIso3, t.year] })]
+);
+
+export const statsImfWeo = statsSchema.table(
+	'imf_weo',
+	{
+		/** WEO round the values come from, e.g. '2026-10' (October 2026 WEO). */
+		vintage: text('vintage').notNull(),
+		indicator: text('indicator').notNull(),
+		countryIso3: text('country_iso3').notNull(),
+		year: integer('year').notNull(),
+		value: doublePrecision('value'),
+		isForecast: boolean('is_forecast').notNull()
+	},
+	(t) => [primaryKey({ columns: [t.vintage, t.indicator, t.countryIso3, t.year] })]
+);
+
+// ── A9 Our World in Data (Maddison GDP per capita, energy dataset) ───────────────────────
+
+export const statsOwidMaddison = statsSchema.table(
+	'owid_maddison',
+	{
+		entity: text('entity').notNull(),
+		/** null for OWID regions (Western Europe, World, …). */
+		iso3: text('iso3'),
+		year: integer('year').notNull(),
+		/** International-$ at 2011 prices. */
+		gdpPc: doublePrecision('gdp_pc')
+	},
+	(t) => [primaryKey({ columns: [t.entity, t.year] })]
+);
+
+export const statsOwidEnergy = statsSchema.table(
+	'owid_energy',
+	{
+		country: text('country').notNull(),
+		iso3: text('iso3'),
+		year: integer('year').notNull(),
+		/** Selected OWID columns as-is: {"solar_share_elec": 21.3, "energy_per_capita": 40000, …}. */
+		values: jsonb('values').$type<Record<string, number>>().notNull()
+	},
+	(t) => [primaryKey({ columns: [t.country, t.year] })]
+);
+
+// ── A10 Energy-Charts (Fraunhofer ISE): day-ahead prices, cross-border physical flows ─────
+
+export const statsEcDayaheadPrice = statsSchema.table(
+	'ec_dayahead_price',
+	{
+		bzn: text('bzn').notNull(),
+		ts: timestamptz('ts').notNull(),
+		eurMwh: doublePrecision('eur_mwh')
+	},
+	(t) => [primaryKey({ columns: [t.bzn, t.ts] })]
+);
+
+export const statsEcCrossborder = statsSchema.table(
+	'ec_crossborder',
+	{
+		/** Lower-case Energy-Charts country code, e.g. 'nl'. */
+		country: text('country').notNull(),
+		/** Neighbour name as Energy-Charts reports it ('Belgium', …, 'sum'). */
+		neighbour: text('neighbour').notNull(),
+		ts: timestamptz('ts').notNull(),
+		/** GW; positive = import into `country`, negative = export. */
+		gw: doublePrecision('gw')
+	},
+	(t) => [primaryKey({ columns: [t.country, t.neighbour, t.ts] })]
+);
+
+// ── A13 Rijksfinanciën (NL central-government budget tables) ──────────────────────────────
+
+export const statsRfBudgetTable = statsSchema.table(
+	'rf_budget_table',
+	{
+		year: integer('year').notNull(),
+		/** OWB (budget), O1/O2 (supplementary budgets), JV (annual report). */
+		phase: text('phase').notNull(),
+		/** Rijksfinanciën row index, unique within year + phase (includes chapter/article/vuo). */
+		rowKey: text('row_key').notNull(),
+		/** U = expenditure, O = revenue, V = commitments. */
+		vuo: char('vuo', { length: 1 }).notNull(),
+		chapter: text('chapter').notNull(),
+		chapterName: text('chapter_name').notNull(),
+		article: text('article'),
+		articleName: text('article_name'),
+		detail: jsonb('detail').$type<Record<string, unknown>>().notNull().default({}),
+		/** Thousand euro. */
+		amountEurK: doublePrecision('amount_eur_k')
+	},
+	(t) => [
+		primaryKey({ columns: [t.year, t.phase, t.rowKey] }),
+		index('rf_budget_table_chapter_idx').on(t.year, t.vuo, t.chapter)
+	]
+);
+
+// ── A11 US Treasury Fiscal Data (Monthly Treasury Statement, Debt to the Penny) ───────────
+
+const mtsColumns = {
+	recordDate: date('record_date', { mode: 'string' }).notNull(),
+	classificationId: text('classification_id').notNull(),
+	parentId: text('parent_id'),
+	description: text('description').notNull(),
+	level: integer('level'),
+	printOrder: integer('print_order'),
+	/** Net amount for the month and fiscal year to date, USD. */
+	netMonth: doublePrecision('net_month'),
+	netFytd: doublePrecision('net_fytd'),
+	grossMonth: doublePrecision('gross_month')
+};
+
+export const statsUstMtsReceipts = statsSchema.table('ust_mts_receipts', mtsColumns, (t) => [
+	primaryKey({ columns: [t.recordDate, t.classificationId] })
+]);
+
+export const statsUstMtsOutlays = statsSchema.table('ust_mts_outlays', { ...mtsColumns }, (t) => [
+	primaryKey({ columns: [t.recordDate, t.classificationId] })
+]);
+
+export const statsUstDebtDaily = statsSchema.table('ust_debt_daily', {
+	recordDate: date('record_date', { mode: 'string' }).primaryKey(),
+	debtHeldPublic: doublePrecision('debt_held_public'),
+	intragovHoldings: doublePrecision('intragov_holdings'),
+	totalDebt: doublePrecision('total_debt')
+});
+
+// ── A12 USAspending (budgetary resources per top-tier agency and fiscal year) ─────────────
+
+export const statsUsasAgencyFy = statsSchema.table(
+	'usas_agency_fy',
+	{
+		toptierCode: text('toptier_code').notNull(),
+		fiscalYear: integer('fiscal_year').notNull(),
+		agencyName: text('agency_name').notNull(),
+		abbreviation: text('abbreviation'),
+		budgetaryResources: doublePrecision('budgetary_resources'),
+		obligated: doublePrecision('obligated'),
+		outlayed: doublePrecision('outlayed')
+	},
+	(t) => [primaryKey({ columns: [t.toptierCode, t.fiscalYear] })]
+);