feat(analytics): real computations + 15-min snapshot refresh job
PR3 of Phase B. Replaces the no-op stubs in analytics.service.ts with
working drizzle queries and adds the recurring BullMQ job that warms
the cache.
Computations:
- computePipelineFunnel: groups interests by pipeline_stage filtered by
port + range + not archived; emits 8-row stages array with conversion
pct relative to 'open' as the funnel top.
- computeOccupancyTimeline: per day in range, counts berths covered by
an active reservation (start_date ≤ day, end_date IS NULL OR ≥ day);
emits {date, occupied, total, occupancyPct}.
- computeRevenueBreakdown: sums invoices.total grouped by status +
currency; filters out archived rows.
- computeLeadSourceAttribution: counts interests by source descending;
null source bucketed as 'unspecified'.
Public API (getPipelineFunnel, getOccupancyTimeline, etc.) reads
analytics_snapshots first; falls back to compute + writeSnapshot. TTL
15 minutes (matches the cron interval).
Cron:
- queue/scheduler.ts registers 'analytics-refresh' on maintenance with
pattern '*/15 * * * *'.
- queue/workers/maintenance.ts dispatches to refreshSnapshotsForPort
for every port; per-port try/catch so one bad port doesn't kill the
sweep.
Tests: tests/integration/analytics-service.test.ts (9 cases). Pipeline
funnel math (incl. zero state), occupancy timeline shape/percentages
with seeded reservations, revenue grouped by status + currency, lead
source attribution incl. null bucketing, cache hit (mutate snapshot
directly → next read returns mutated value), refreshSnapshotsForPort
warms every metric×range combo.
Vitest 690/690 (+9). tsc + lint clean.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-28 14:54:46 +02:00
|
|
|
|
/**
|
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|
|
* Analytics service integration tests — exercise the four computations
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|
* against a seeded port + assert the cache layer reads/writes correctly.
|
|
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|
|
|
*/
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|
|
import { describe, it, expect } from 'vitest';
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import { eq, and } from 'drizzle-orm';
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import { db } from '@/lib/db';
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import { interests } from '@/lib/db/schema/interests';
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import { invoices } from '@/lib/db/schema/financial';
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import { berthReservations } from '@/lib/db/schema/reservations';
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import { analyticsSnapshots } from '@/lib/db/schema/insights';
|
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import {
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computePipelineFunnel,
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computeOccupancyTimeline,
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computeRevenueBreakdown,
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computeLeadSourceAttribution,
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getPipelineFunnel,
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refreshSnapshotsForPort,
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ALL_METRICS,
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ALL_RANGES,
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SNAPSHOT_TTL_MS,
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} from '@/lib/services/analytics.service';
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import { makePort, makeClient, makeBerth, makeYacht } from '../helpers/factories';
|
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describe('analytics service', () => {
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describe('computePipelineFunnel', () => {
|
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it('aggregates interests by stage with conversion percentages', async () => {
|
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const port = await makePort();
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const client = await makeClient({ portId: port.id });
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// 3 open, 2 details_sent, 1 visited
|
refactor(sales): consolidate pipeline stages + wire EOI auto-advance
The 8→9 stage refresh from earlier today only updated constants.ts and the DB —
20 component/service files still hardcoded the old enum, leaving labels blank,
filter dropdowns wrong, kanban columns mismatched, and the analytics funnel
silently dropping new-stage rows. The platform also never advanced
pipelineStage on EOI lifecycle events: documents.service.ts wrote eoiStatus
but left the user-visible stage stuck.
This commit closes both gaps:
1. Single source of truth in src/lib/constants.ts — adds STAGE_LABELS,
STAGE_BADGE, STAGE_DOT, STAGE_WEIGHTS, STAGE_TRANSITIONS plus
stageLabel / stageBadgeClass / stageDotClass / safeStage /
canTransitionStage helpers. components/clients/pipeline-constants.ts
becomes a re-export shim so existing imports keep working.
2. 18 stale-enum surfaces migrated — interest list (table, card, filters,
form, stage picker), pipeline board, client card, berth interests tab,
portal client interests page, dashboard pipeline / funnel / revenue-
forecast charts, settings pipeline_weights default, dashboard.service
weights, analytics.service funnel stages, alert-rules stale-interest
filter, interest-scoring stage rank.
3. Documents tab wired into interest detail — replaced the placeholder in
interest-tabs.tsx with InterestDocumentsTab + InterestFilesTab so the
EOI launcher is back where salespeople work.
4. Auto-advance — new advanceStageIfBehind() in interests.service.ts
(forward-only, no-op if interest is already past the target). Called
from documents.service.ts on send (→ eoi_sent), Documenso completed
webhook (→ eoi_signed), and manual signed-EOI upload (→ eoi_signed).
5. Transition guard — canTransitionStage() blocks egregious skips
(e.g. completed → open, open → contract_signed). Enforced in
changeInterestStage before the DB write.
Tests updated to reflect the 9-stage model. tsc clean, vitest 832/832,
ESLint clean on every file touched.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-01 23:33:53 +02:00
|
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|
|
for (const stage of [
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|
'open',
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|
'open',
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'open',
|
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|
'details_sent',
|
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|
|
'details_sent',
|
|
|
|
|
|
'in_communication',
|
|
|
|
|
|
]) {
|
feat(analytics): real computations + 15-min snapshot refresh job
PR3 of Phase B. Replaces the no-op stubs in analytics.service.ts with
working drizzle queries and adds the recurring BullMQ job that warms
the cache.
Computations:
- computePipelineFunnel: groups interests by pipeline_stage filtered by
port + range + not archived; emits 8-row stages array with conversion
pct relative to 'open' as the funnel top.
- computeOccupancyTimeline: per day in range, counts berths covered by
an active reservation (start_date ≤ day, end_date IS NULL OR ≥ day);
emits {date, occupied, total, occupancyPct}.
- computeRevenueBreakdown: sums invoices.total grouped by status +
currency; filters out archived rows.
- computeLeadSourceAttribution: counts interests by source descending;
null source bucketed as 'unspecified'.
Public API (getPipelineFunnel, getOccupancyTimeline, etc.) reads
analytics_snapshots first; falls back to compute + writeSnapshot. TTL
15 minutes (matches the cron interval).
Cron:
- queue/scheduler.ts registers 'analytics-refresh' on maintenance with
pattern '*/15 * * * *'.
- queue/workers/maintenance.ts dispatches to refreshSnapshotsForPort
for every port; per-port try/catch so one bad port doesn't kill the
sweep.
Tests: tests/integration/analytics-service.test.ts (9 cases). Pipeline
funnel math (incl. zero state), occupancy timeline shape/percentages
with seeded reservations, revenue grouped by status + currency, lead
source attribution incl. null bucketing, cache hit (mutate snapshot
directly → next read returns mutated value), refreshSnapshotsForPort
warms every metric×range combo.
Vitest 690/690 (+9). tsc + lint clean.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-28 14:54:46 +02:00
|
|
|
|
await db.insert(interests).values({
|
|
|
|
|
|
portId: port.id,
|
|
|
|
|
|
clientId: client.id,
|
|
|
|
|
|
pipelineStage: stage,
|
|
|
|
|
|
});
|
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
const result = await computePipelineFunnel(port.id, '30d');
|
|
|
|
|
|
|
|
|
|
|
|
const open = result.stages.find((s) => s.stage === 'open');
|
|
|
|
|
|
const details = result.stages.find((s) => s.stage === 'details_sent');
|
refactor(sales): consolidate pipeline stages + wire EOI auto-advance
The 8→9 stage refresh from earlier today only updated constants.ts and the DB —
20 component/service files still hardcoded the old enum, leaving labels blank,
filter dropdowns wrong, kanban columns mismatched, and the analytics funnel
silently dropping new-stage rows. The platform also never advanced
pipelineStage on EOI lifecycle events: documents.service.ts wrote eoiStatus
but left the user-visible stage stuck.
This commit closes both gaps:
1. Single source of truth in src/lib/constants.ts — adds STAGE_LABELS,
STAGE_BADGE, STAGE_DOT, STAGE_WEIGHTS, STAGE_TRANSITIONS plus
stageLabel / stageBadgeClass / stageDotClass / safeStage /
canTransitionStage helpers. components/clients/pipeline-constants.ts
becomes a re-export shim so existing imports keep working.
2. 18 stale-enum surfaces migrated — interest list (table, card, filters,
form, stage picker), pipeline board, client card, berth interests tab,
portal client interests page, dashboard pipeline / funnel / revenue-
forecast charts, settings pipeline_weights default, dashboard.service
weights, analytics.service funnel stages, alert-rules stale-interest
filter, interest-scoring stage rank.
3. Documents tab wired into interest detail — replaced the placeholder in
interest-tabs.tsx with InterestDocumentsTab + InterestFilesTab so the
EOI launcher is back where salespeople work.
4. Auto-advance — new advanceStageIfBehind() in interests.service.ts
(forward-only, no-op if interest is already past the target). Called
from documents.service.ts on send (→ eoi_sent), Documenso completed
webhook (→ eoi_signed), and manual signed-EOI upload (→ eoi_signed).
5. Transition guard — canTransitionStage() blocks egregious skips
(e.g. completed → open, open → contract_signed). Enforced in
changeInterestStage before the DB write.
Tests updated to reflect the 9-stage model. tsc clean, vitest 832/832,
ESLint clean on every file touched.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-01 23:33:53 +02:00
|
|
|
|
const visited = result.stages.find((s) => s.stage === 'in_communication');
|
feat(analytics): real computations + 15-min snapshot refresh job
PR3 of Phase B. Replaces the no-op stubs in analytics.service.ts with
working drizzle queries and adds the recurring BullMQ job that warms
the cache.
Computations:
- computePipelineFunnel: groups interests by pipeline_stage filtered by
port + range + not archived; emits 8-row stages array with conversion
pct relative to 'open' as the funnel top.
- computeOccupancyTimeline: per day in range, counts berths covered by
an active reservation (start_date ≤ day, end_date IS NULL OR ≥ day);
emits {date, occupied, total, occupancyPct}.
- computeRevenueBreakdown: sums invoices.total grouped by status +
currency; filters out archived rows.
- computeLeadSourceAttribution: counts interests by source descending;
null source bucketed as 'unspecified'.
Public API (getPipelineFunnel, getOccupancyTimeline, etc.) reads
analytics_snapshots first; falls back to compute + writeSnapshot. TTL
15 minutes (matches the cron interval).
Cron:
- queue/scheduler.ts registers 'analytics-refresh' on maintenance with
pattern '*/15 * * * *'.
- queue/workers/maintenance.ts dispatches to refreshSnapshotsForPort
for every port; per-port try/catch so one bad port doesn't kill the
sweep.
Tests: tests/integration/analytics-service.test.ts (9 cases). Pipeline
funnel math (incl. zero state), occupancy timeline shape/percentages
with seeded reservations, revenue grouped by status + currency, lead
source attribution incl. null bucketing, cache hit (mutate snapshot
directly → next read returns mutated value), refreshSnapshotsForPort
warms every metric×range combo.
Vitest 690/690 (+9). tsc + lint clean.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-28 14:54:46 +02:00
|
|
|
|
expect(open?.count).toBe(3);
|
|
|
|
|
|
expect(open?.conversionPct).toBe(100);
|
|
|
|
|
|
expect(details?.count).toBe(2);
|
|
|
|
|
|
expect(details?.conversionPct).toBeCloseTo(66.7, 0);
|
|
|
|
|
|
expect(visited?.count).toBe(1);
|
|
|
|
|
|
expect(visited?.conversionPct).toBeCloseTo(33.3, 0);
|
|
|
|
|
|
});
|
|
|
|
|
|
|
|
|
|
|
|
it('returns zeros when port has no interests', async () => {
|
|
|
|
|
|
const port = await makePort();
|
|
|
|
|
|
const result = await computePipelineFunnel(port.id, '30d');
|
refactor(sales): consolidate pipeline stages + wire EOI auto-advance
The 8→9 stage refresh from earlier today only updated constants.ts and the DB —
20 component/service files still hardcoded the old enum, leaving labels blank,
filter dropdowns wrong, kanban columns mismatched, and the analytics funnel
silently dropping new-stage rows. The platform also never advanced
pipelineStage on EOI lifecycle events: documents.service.ts wrote eoiStatus
but left the user-visible stage stuck.
This commit closes both gaps:
1. Single source of truth in src/lib/constants.ts — adds STAGE_LABELS,
STAGE_BADGE, STAGE_DOT, STAGE_WEIGHTS, STAGE_TRANSITIONS plus
stageLabel / stageBadgeClass / stageDotClass / safeStage /
canTransitionStage helpers. components/clients/pipeline-constants.ts
becomes a re-export shim so existing imports keep working.
2. 18 stale-enum surfaces migrated — interest list (table, card, filters,
form, stage picker), pipeline board, client card, berth interests tab,
portal client interests page, dashboard pipeline / funnel / revenue-
forecast charts, settings pipeline_weights default, dashboard.service
weights, analytics.service funnel stages, alert-rules stale-interest
filter, interest-scoring stage rank.
3. Documents tab wired into interest detail — replaced the placeholder in
interest-tabs.tsx with InterestDocumentsTab + InterestFilesTab so the
EOI launcher is back where salespeople work.
4. Auto-advance — new advanceStageIfBehind() in interests.service.ts
(forward-only, no-op if interest is already past the target). Called
from documents.service.ts on send (→ eoi_sent), Documenso completed
webhook (→ eoi_signed), and manual signed-EOI upload (→ eoi_signed).
5. Transition guard — canTransitionStage() blocks egregious skips
(e.g. completed → open, open → contract_signed). Enforced in
changeInterestStage before the DB write.
Tests updated to reflect the 9-stage model. tsc clean, vitest 832/832,
ESLint clean on every file touched.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-01 23:33:53 +02:00
|
|
|
|
expect(result.stages).toHaveLength(9);
|
feat(analytics): real computations + 15-min snapshot refresh job
PR3 of Phase B. Replaces the no-op stubs in analytics.service.ts with
working drizzle queries and adds the recurring BullMQ job that warms
the cache.
Computations:
- computePipelineFunnel: groups interests by pipeline_stage filtered by
port + range + not archived; emits 8-row stages array with conversion
pct relative to 'open' as the funnel top.
- computeOccupancyTimeline: per day in range, counts berths covered by
an active reservation (start_date ≤ day, end_date IS NULL OR ≥ day);
emits {date, occupied, total, occupancyPct}.
- computeRevenueBreakdown: sums invoices.total grouped by status +
currency; filters out archived rows.
- computeLeadSourceAttribution: counts interests by source descending;
null source bucketed as 'unspecified'.
Public API (getPipelineFunnel, getOccupancyTimeline, etc.) reads
analytics_snapshots first; falls back to compute + writeSnapshot. TTL
15 minutes (matches the cron interval).
Cron:
- queue/scheduler.ts registers 'analytics-refresh' on maintenance with
pattern '*/15 * * * *'.
- queue/workers/maintenance.ts dispatches to refreshSnapshotsForPort
for every port; per-port try/catch so one bad port doesn't kill the
sweep.
Tests: tests/integration/analytics-service.test.ts (9 cases). Pipeline
funnel math (incl. zero state), occupancy timeline shape/percentages
with seeded reservations, revenue grouped by status + currency, lead
source attribution incl. null bucketing, cache hit (mutate snapshot
directly → next read returns mutated value), refreshSnapshotsForPort
warms every metric×range combo.
Vitest 690/690 (+9). tsc + lint clean.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-04-28 14:54:46 +02:00
|
|
|
|
expect(result.stages.every((s) => s.count === 0)).toBe(true);
|
|
|
|
|
|
});
|
|
|
|
|
|
});
|
|
|
|
|
|
|
|
|
|
|
|
describe('computeOccupancyTimeline', () => {
|
|
|
|
|
|
it('returns 7 points for 7d range with occupancy percentages', async () => {
|
|
|
|
|
|
const port = await makePort();
|
|
|
|
|
|
await makeBerth({ portId: port.id });
|
|
|
|
|
|
await makeBerth({ portId: port.id });
|
|
|
|
|
|
const client = await makeClient({ portId: port.id });
|
|
|
|
|
|
const yacht = await makeYacht({
|
|
|
|
|
|
portId: port.id,
|
|
|
|
|
|
ownerType: 'client',
|
|
|
|
|
|
ownerId: client.id,
|
|
|
|
|
|
});
|
|
|
|
|
|
const berth = await makeBerth({ portId: port.id });
|
|
|
|
|
|
// Active reservation covering today
|
|
|
|
|
|
await db.insert(berthReservations).values({
|
|
|
|
|
|
portId: port.id,
|
|
|
|
|
|
berthId: berth.id,
|
|
|
|
|
|
clientId: client.id,
|
|
|
|
|
|
yachtId: yacht.id,
|
|
|
|
|
|
status: 'active',
|
|
|
|
|
|
startDate: new Date(Date.now() - 5 * 86_400_000),
|
|
|
|
|
|
createdBy: 'seed',
|
|
|
|
|
|
});
|
|
|
|
|
|
|
|
|
|
|
|
const result = await computeOccupancyTimeline(port.id, '7d');
|
|
|
|
|
|
expect(result.points).toHaveLength(7);
|
|
|
|
|
|
// Last point is today; should reflect 1/3 occupancy.
|
|
|
|
|
|
const today = result.points[result.points.length - 1]!;
|
|
|
|
|
|
expect(today.total).toBe(3);
|
|
|
|
|
|
expect(today.occupied).toBe(1);
|
|
|
|
|
|
expect(today.occupancyPct).toBeCloseTo(33.3, 0);
|
|
|
|
|
|
});
|
|
|
|
|
|
});
|
|
|
|
|
|
|
|
|
|
|
|
describe('computeRevenueBreakdown', () => {
|
|
|
|
|
|
it('groups invoice totals by status and currency', async () => {
|
|
|
|
|
|
const port = await makePort();
|
|
|
|
|
|
const baseInvoice = {
|
|
|
|
|
|
portId: port.id,
|
|
|
|
|
|
clientName: 'Acme',
|
|
|
|
|
|
billingEntityType: 'client' as const,
|
|
|
|
|
|
billingEntityId: 'client-id',
|
|
|
|
|
|
dueDate: '2026-12-31',
|
|
|
|
|
|
currency: 'USD',
|
|
|
|
|
|
subtotal: '0',
|
|
|
|
|
|
createdBy: 'seed',
|
|
|
|
|
|
};
|
|
|
|
|
|
await db.insert(invoices).values([
|
|
|
|
|
|
{ ...baseInvoice, invoiceNumber: 'INV-001', total: '1000', status: 'paid' },
|
|
|
|
|
|
{ ...baseInvoice, invoiceNumber: 'INV-002', total: '500', status: 'paid' },
|
|
|
|
|
|
{ ...baseInvoice, invoiceNumber: 'INV-003', total: '2000', status: 'sent' },
|
|
|
|
|
|
]);
|
|
|
|
|
|
|
|
|
|
|
|
const result = await computeRevenueBreakdown(port.id, '30d');
|
|
|
|
|
|
const paid = result.bars.find((b) => b.status === 'paid');
|
|
|
|
|
|
const sent = result.bars.find((b) => b.status === 'sent');
|
|
|
|
|
|
expect(paid?.amount).toBe(1500);
|
|
|
|
|
|
expect(sent?.amount).toBe(2000);
|
|
|
|
|
|
});
|
|
|
|
|
|
});
|
|
|
|
|
|
|
|
|
|
|
|
describe('computeLeadSourceAttribution', () => {
|
|
|
|
|
|
it('counts interests grouped by source descending', async () => {
|
|
|
|
|
|
const port = await makePort();
|
|
|
|
|
|
const client = await makeClient({ portId: port.id });
|
|
|
|
|
|
for (const source of ['website', 'website', 'website', 'manual', 'referral', 'referral']) {
|
|
|
|
|
|
await db.insert(interests).values({
|
|
|
|
|
|
portId: port.id,
|
|
|
|
|
|
clientId: client.id,
|
|
|
|
|
|
pipelineStage: 'open',
|
|
|
|
|
|
source,
|
|
|
|
|
|
});
|
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
|
|
const result = await computeLeadSourceAttribution(port.id, '30d');
|
|
|
|
|
|
expect(result.slices[0]).toEqual({ source: 'website', count: 3 });
|
|
|
|
|
|
expect(result.slices[1]).toEqual({ source: 'referral', count: 2 });
|
|
|
|
|
|
expect(result.slices[2]).toEqual({ source: 'manual', count: 1 });
|
|
|
|
|
|
});
|
|
|
|
|
|
|
|
|
|
|
|
it('groups null source as "unspecified"', async () => {
|
|
|
|
|
|
const port = await makePort();
|
|
|
|
|
|
const client = await makeClient({ portId: port.id });
|
|
|
|
|
|
await db.insert(interests).values({
|
|
|
|
|
|
portId: port.id,
|
|
|
|
|
|
clientId: client.id,
|
|
|
|
|
|
pipelineStage: 'open',
|
|
|
|
|
|
source: null,
|
|
|
|
|
|
});
|
|
|
|
|
|
|
|
|
|
|
|
const result = await computeLeadSourceAttribution(port.id, '30d');
|
|
|
|
|
|
expect(result.slices.find((s) => s.source === 'unspecified')?.count).toBe(1);
|
|
|
|
|
|
});
|
|
|
|
|
|
});
|
|
|
|
|
|
|
|
|
|
|
|
describe('cache', () => {
|
|
|
|
|
|
it('getPipelineFunnel writes a snapshot and returns it on subsequent calls', async () => {
|
|
|
|
|
|
const port = await makePort();
|
|
|
|
|
|
const client = await makeClient({ portId: port.id });
|
|
|
|
|
|
await db.insert(interests).values({
|
|
|
|
|
|
portId: port.id,
|
|
|
|
|
|
clientId: client.id,
|
|
|
|
|
|
pipelineStage: 'open',
|
|
|
|
|
|
});
|
|
|
|
|
|
|
|
|
|
|
|
const first = await getPipelineFunnel(port.id, '30d');
|
|
|
|
|
|
// Snapshot written.
|
|
|
|
|
|
const row = await db.query.analyticsSnapshots.findFirst({
|
|
|
|
|
|
where: and(
|
|
|
|
|
|
eq(analyticsSnapshots.portId, port.id),
|
|
|
|
|
|
eq(analyticsSnapshots.metricId, 'pipeline_funnel.30d'),
|
|
|
|
|
|
),
|
|
|
|
|
|
});
|
|
|
|
|
|
expect(row).toBeDefined();
|
|
|
|
|
|
expect(row?.data).toEqual(first);
|
|
|
|
|
|
|
|
|
|
|
|
// Mutate the snapshot row directly to confirm cache is being read,
|
|
|
|
|
|
// not recomputed.
|
|
|
|
|
|
const sentinel = { stages: [{ stage: 'sentinel', count: 999, conversionPct: 0 }] };
|
|
|
|
|
|
await db
|
|
|
|
|
|
.update(analyticsSnapshots)
|
|
|
|
|
|
.set({ data: sentinel })
|
|
|
|
|
|
.where(
|
|
|
|
|
|
and(
|
|
|
|
|
|
eq(analyticsSnapshots.portId, port.id),
|
|
|
|
|
|
eq(analyticsSnapshots.metricId, 'pipeline_funnel.30d'),
|
|
|
|
|
|
),
|
|
|
|
|
|
);
|
|
|
|
|
|
const second = await getPipelineFunnel(port.id, '30d');
|
|
|
|
|
|
expect(second).toEqual(sentinel);
|
|
|
|
|
|
});
|
|
|
|
|
|
|
|
|
|
|
|
it('refreshSnapshotsForPort warms every metric × range combo', async () => {
|
|
|
|
|
|
const port = await makePort();
|
|
|
|
|
|
await refreshSnapshotsForPort(port.id);
|
|
|
|
|
|
const rows = await db
|
|
|
|
|
|
.select({ metricId: analyticsSnapshots.metricId })
|
|
|
|
|
|
.from(analyticsSnapshots)
|
|
|
|
|
|
.where(eq(analyticsSnapshots.portId, port.id));
|
|
|
|
|
|
const expected = ALL_METRICS.length * ALL_RANGES.length;
|
|
|
|
|
|
expect(rows).toHaveLength(expected);
|
|
|
|
|
|
});
|
|
|
|
|
|
|
|
|
|
|
|
it('snapshot ttl constant is 15 minutes', () => {
|
|
|
|
|
|
expect(SNAPSHOT_TTL_MS).toBe(15 * 60 * 1000);
|
|
|
|
|
|
});
|
|
|
|
|
|
});
|
|
|
|
|
|
});
|