mirror of
https://github.com/MBombeck/HealthLog.git
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Marc-André Bombeck
93790aa043
Extend the daily-mean consolidation to cover the high-frequency gait/mobility metrics that previously mapped to no consolidation set and piled up at sampling granularity: walking asymmetry, walking double-support, walking steadiness, and walking heart-rate average. The correct daily reduction for these is the mean, matching the Health-app display; all four stay disjoint from the cumulative (sum) set. Fold the daily-mean drain onto the existing nightly cumulative-drain tick so new high-frequency spot samples no longer accumulate raw between worker reboots. The two passes share one concurrency-1 cron, keeping the maintenance window a single sequential walk. Boot-time discovery stays as the back-fill for accounts that accumulated raw rows before this shipped. Recompute the affected day's rollup bucket after the consolidation commits, the same way the ingest path does, so a rollup-covered read reflects the single consolidated row rather than a stale mean derived from the now soft-deleted per-sample rows. Regular heart-rate / pulse stays raw: it is a discrete clinical reading and feeds correlation and scatter analytics. No schema change.
311 lines
9.0 KiB
TypeScript
311 lines
9.0 KiB
TypeScript
/**
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* v1.7.0 — real-Postgres integration coverage for
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* `consolidateDailyMean()`. Mirrors the consolidate-legacy-steps
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* fixture: the testcontainer is hot before this file loads, so the
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* body truncates + seeds + consolidates.
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*
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* Pins the contracts the unit mocks can't:
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* - per-sample mean-type rows collapse into one daily MEAN row;
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* - the originals are SOFT-deleted (tombstoned, not gone);
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* - manual / Withings (non-APPLE_HEALTH) rows are NOT touched;
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* - PULSE per-sample rows are NEVER drained (kept raw for
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* correlation/scatter);
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* - the pass is idempotent (second run = no-op).
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*/
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import { beforeEach, describe, expect, it } from "vitest";
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import { getPrismaClient, truncateAllTables } from "./setup";
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import { consolidateDailyMean } from "@/lib/measurements/consolidate-daily-mean";
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const TEST_USER_ID = "user-mean-consolidation";
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const SPEED_STATS_ID = "stats:HKQuantityTypeIdentifierWalkingSpeed:2026-05-16";
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beforeEach(async () => {
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await truncateAllTables(getPrismaClient());
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await getPrismaClient().user.create({
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data: {
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id: TEST_USER_ID,
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username: "mean-consolidation",
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email: "mean-consolidation@example.test",
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timezone: "Europe/Berlin",
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},
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});
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});
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describe("consolidateDailyMean (real Postgres)", () => {
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it("collapses per-sample rows into one daily MEAN and soft-deletes the originals", async () => {
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const prisma = getPrismaClient();
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await prisma.measurement.createMany({
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data: [
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{
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userId: TEST_USER_ID,
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type: "WALKING_SPEED",
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value: 1.0,
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unit: "m/s",
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source: "APPLE_HEALTH",
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measuredAt: new Date("2026-05-16T08:00:00.000Z"),
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externalId: "hk-speed-1",
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},
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{
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userId: TEST_USER_ID,
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type: "WALKING_SPEED",
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value: 1.4,
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unit: "m/s",
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source: "APPLE_HEALTH",
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measuredAt: new Date("2026-05-16T14:00:00.000Z"),
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externalId: "hk-speed-2",
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},
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{
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userId: TEST_USER_ID,
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type: "WALKING_SPEED",
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value: 1.2,
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unit: "m/s",
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source: "APPLE_HEALTH",
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measuredAt: new Date("2026-05-16T20:00:00.000Z"),
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externalId: "hk-speed-3",
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},
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],
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});
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const summary = await consolidateDailyMean(prisma, {
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userId: TEST_USER_ID,
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dryRun: false,
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log: () => {},
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});
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expect(summary.totals.daysConsolidated).toBe(1);
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expect(summary.totals.perSampleRowsSoftDeleted).toBe(3);
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expect(summary.totals.dailyRowsUpserted).toBe(1);
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const live = await prisma.measurement.findMany({
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where: { userId: TEST_USER_ID, type: "WALKING_SPEED", deletedAt: null },
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});
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expect(live).toHaveLength(1);
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// MEAN of (1.0, 1.4, 1.2) = 1.2 — NOT the sum (3.6).
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expect(live[0].value).toBeCloseTo(1.2, 6);
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expect(live[0].externalId).toBe(SPEED_STATS_ID);
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const tombstoned = await prisma.measurement.findMany({
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where: {
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userId: TEST_USER_ID,
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type: "WALKING_SPEED",
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deletedAt: { not: null },
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},
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});
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expect(tombstoned).toHaveLength(3);
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});
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it("leaves manual / Withings (non-APPLE_HEALTH) rows untouched", async () => {
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const prisma = getPrismaClient();
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await prisma.measurement.createMany({
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data: [
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{
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userId: TEST_USER_ID,
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type: "RESPIRATORY_RATE",
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value: 14,
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unit: "breaths/min",
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source: "APPLE_HEALTH",
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measuredAt: new Date("2026-05-16T08:00:00.000Z"),
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externalId: "hk-rr-1",
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},
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{
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userId: TEST_USER_ID,
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type: "RESPIRATORY_RATE",
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value: 16,
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unit: "breaths/min",
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source: "APPLE_HEALTH",
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measuredAt: new Date("2026-05-16T09:00:00.000Z"),
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externalId: "hk-rr-2",
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},
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{
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userId: TEST_USER_ID,
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type: "RESPIRATORY_RATE",
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value: 18,
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unit: "breaths/min",
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source: "MANUAL",
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measuredAt: new Date("2026-05-16T10:00:00.000Z"),
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externalId: null,
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},
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],
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});
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await consolidateDailyMean(prisma, {
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userId: TEST_USER_ID,
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dryRun: false,
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log: () => {},
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});
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// The MANUAL row stays live + untouched.
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const manualLive = await prisma.measurement.findMany({
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where: {
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userId: TEST_USER_ID,
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type: "RESPIRATORY_RATE",
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source: "MANUAL",
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deletedAt: null,
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},
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});
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expect(manualLive).toHaveLength(1);
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expect(manualLive[0].value).toBe(18);
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// The two APPLE_HEALTH samples collapsed to one daily MEAN (15).
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const hkLive = await prisma.measurement.findMany({
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where: {
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userId: TEST_USER_ID,
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type: "RESPIRATORY_RATE",
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source: "APPLE_HEALTH",
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deletedAt: null,
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},
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});
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expect(hkLive).toHaveLength(1);
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expect(hkLive[0].value).toBeCloseTo(15, 6);
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});
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it("never drains PULSE (kept raw for correlation/scatter)", async () => {
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const prisma = getPrismaClient();
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await prisma.measurement.createMany({
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data: [
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{
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userId: TEST_USER_ID,
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type: "PULSE",
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value: 60,
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unit: "bpm",
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source: "APPLE_HEALTH",
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measuredAt: new Date("2026-05-16T08:00:00.000Z"),
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externalId: "hk-pulse-1",
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},
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{
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userId: TEST_USER_ID,
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type: "PULSE",
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value: 80,
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unit: "bpm",
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source: "APPLE_HEALTH",
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measuredAt: new Date("2026-05-16T09:00:00.000Z"),
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externalId: "hk-pulse-2",
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},
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],
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});
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const summary = await consolidateDailyMean(prisma, {
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userId: TEST_USER_ID,
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dryRun: false,
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log: () => {},
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});
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expect(summary.totals.daysConsolidated).toBe(0);
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// Both raw PULSE rows survive — none tombstoned, none collapsed.
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const live = await prisma.measurement.findMany({
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where: { userId: TEST_USER_ID, type: "PULSE", deletedAt: null },
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});
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expect(live).toHaveLength(2);
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});
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it("consolidates a v1.8.5 gait type and recomputes the DAY rollup", async () => {
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const prisma = getPrismaClient();
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await prisma.measurement.createMany({
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data: [
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{
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userId: TEST_USER_ID,
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type: "WALKING_ASYMMETRY",
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value: 2.0,
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unit: "%",
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source: "APPLE_HEALTH",
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measuredAt: new Date("2026-05-16T08:00:00.000Z"),
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externalId: "hk-asym-1",
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},
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{
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userId: TEST_USER_ID,
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type: "WALKING_ASYMMETRY",
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value: 4.0,
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unit: "%",
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source: "APPLE_HEALTH",
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measuredAt: new Date("2026-05-16T14:00:00.000Z"),
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externalId: "hk-asym-2",
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},
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],
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});
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const summary = await consolidateDailyMean(prisma, {
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userId: TEST_USER_ID,
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dryRun: false,
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log: () => {},
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});
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expect(summary.totals.daysConsolidated).toBe(1);
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// One live daily MEAN row carrying 3.0 (the mean of 2 + 4), not 6.
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const live = await prisma.measurement.findMany({
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where: {
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userId: TEST_USER_ID,
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type: "WALKING_ASYMMETRY",
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deletedAt: null,
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},
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});
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expect(live).toHaveLength(1);
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expect(live[0].value).toBeCloseTo(3.0, 6);
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// T3 — the DAY rollup bucket reflects the single consolidated row, not
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// a pre-drain mean over the now soft-deleted samples.
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const dayRollup = await prisma.measurementRollup.findMany({
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where: {
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userId: TEST_USER_ID,
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type: "WALKING_ASYMMETRY",
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granularity: "DAY",
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},
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});
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expect(dayRollup).toHaveLength(1);
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expect(dayRollup[0].mean).toBeCloseTo(3.0, 6);
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});
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it("is idempotent — a second run is a no-op", async () => {
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const prisma = getPrismaClient();
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await prisma.measurement.createMany({
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data: [
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{
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userId: TEST_USER_ID,
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type: "AUDIO_EXPOSURE_ENV",
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value: 60,
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unit: "dBA",
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source: "APPLE_HEALTH",
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measuredAt: new Date("2026-05-16T08:00:00.000Z"),
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externalId: "hk-env-1",
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},
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{
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userId: TEST_USER_ID,
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type: "AUDIO_EXPOSURE_ENV",
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value: 80,
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unit: "dBA",
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source: "APPLE_HEALTH",
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measuredAt: new Date("2026-05-16T18:00:00.000Z"),
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externalId: "hk-env-2",
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},
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],
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});
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const first = await consolidateDailyMean(prisma, {
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userId: TEST_USER_ID,
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dryRun: false,
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log: () => {},
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});
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expect(first.totals.daysConsolidated).toBe(1);
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expect(first.totals.perSampleRowsSoftDeleted).toBe(2);
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const second = await consolidateDailyMean(prisma, {
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userId: TEST_USER_ID,
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dryRun: false,
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log: () => {},
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});
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expect(second.totals.daysConsolidated).toBe(0);
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expect(second.totals.perSampleRowsSoftDeleted).toBe(0);
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const live = await prisma.measurement.findMany({
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where: {
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userId: TEST_USER_ID,
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type: "AUDIO_EXPOSURE_ENV",
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deletedAt: null,
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},
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});
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expect(live).toHaveLength(1);
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// MEAN of (60, 80) = 70.
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expect(live[0].value).toBeCloseTo(70, 6);
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});
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});
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