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pn-new-crm/src/lib/services/analytics.service.ts
Matt Ciaccio 8699f81879
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chore(style): codebase em-dash sweep + minor layout polish
Replaces every em-dash and en-dash with regular ASCII hyphens
across comments, JSX strings, and dev-facing logs. Mostly cosmetic
but stops the inconsistent mix that crept in over the last few
months (some files used em-dashes in comments, others didn't,
some used both).

Bundles two small dashboard-layout tweaks that touch a couple of
already-modified files:
- (dashboard)/layout.tsx main padding goes from p-6 to pt-3 px-6
  pb-6 so page content sits closer to the topbar.
- Sidebar now receives the ports list it needs for the footer
  port switcher.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
2026-05-04 22:57:01 +02:00

341 lines
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/**
* Phase B analytics service. Reads pre-computed snapshots from
* `analytics_snapshots`; recomputes on demand if older than `SNAPSHOT_TTL_MS`.
* The recurring `analytics-refresh` BullMQ job (PR3) warms the table
* every 15 minutes per port × per metric.
*/
import { and, between, eq, isNull, sql } from 'drizzle-orm';
import { db } from '@/lib/db';
import { analyticsSnapshots } from '@/lib/db/schema/insights';
import { interests } from '@/lib/db/schema/interests';
import { invoices } from '@/lib/db/schema/financial';
import { berthReservations } from '@/lib/db/schema/reservations';
import { PIPELINE_STAGES } from '@/lib/constants';
import {
ALL_RANGES,
isCustomRange,
rangeToBounds,
type CustomDateRange,
type DateRange,
type PresetDateRange,
} from '@/lib/analytics/range';
// Re-export the shared types for callers that already import from this
// module - keeps the existing public API intact.
export { ALL_RANGES, isCustomRange, rangeToBounds };
export type { DateRange, PresetDateRange, CustomDateRange };
export type MetricBase =
| 'pipeline_funnel'
| 'occupancy_timeline'
| 'revenue_breakdown'
| 'lead_source_attribution';
/**
* Snapshot key. Only preset ranges are cached - custom ranges have an
* unbounded combinatorial space so we always recompute them on demand
* (avoids polluting `analytics_snapshots` with one-off rows).
*/
export type MetricId = `${MetricBase}.${PresetDateRange}`;
export const ALL_METRICS: readonly MetricBase[] = [
'pipeline_funnel',
'occupancy_timeline',
'revenue_breakdown',
'lead_source_attribution',
] as const;
export const SNAPSHOT_TTL_MS = 15 * 60 * 1000; // 15 minutes
// ─── Output shapes ────────────────────────────────────────────────────────────
export interface PipelineFunnelData {
stages: Array<{ stage: string; count: number; conversionPct: number }>;
/** Counts of terminal lost/cancelled outcomes in the range. Surfaces below
* the funnel so users can see leakage without it polluting the conversion
* math. Total = sum of these counts. */
lost: { count: number; byOutcome: Record<string, number> };
}
export interface OccupancyTimelineData {
points: Array<{ date: string; occupied: number; total: number; occupancyPct: number }>;
}
export interface RevenueBreakdownData {
bars: Array<{ status: string; amount: number; currency: string }>;
}
export interface LeadSourceAttributionData {
slices: Array<{ source: string; count: number }>;
}
export type SnapshotData =
| PipelineFunnelData
| OccupancyTimelineData
| RevenueBreakdownData
| LeadSourceAttributionData;
// ─── Cache layer ──────────────────────────────────────────────────────────────
export async function readSnapshot<T extends SnapshotData>(
portId: string,
metricId: MetricId,
): Promise<T | null> {
const row = await db.query.analyticsSnapshots.findFirst({
where: and(eq(analyticsSnapshots.portId, portId), eq(analyticsSnapshots.metricId, metricId)),
});
if (!row) return null;
const age = Date.now() - row.computedAt.getTime();
if (age > SNAPSHOT_TTL_MS) return null;
return row.data as T;
}
export async function writeSnapshot(
portId: string,
metricId: MetricId,
data: SnapshotData,
): Promise<void> {
await db
.insert(analyticsSnapshots)
.values({ portId, metricId, data })
.onConflictDoUpdate({
target: [analyticsSnapshots.portId, analyticsSnapshots.metricId],
set: { data, computedAt: new Date() },
});
}
// Range helpers (rangeToBounds, rangeToDays, rangeSpanDays) moved to
// @/lib/analytics/range - that file is client-safe (no DB imports) so it
// can be used from React components AND this server module.
// ─── Computations ─────────────────────────────────────────────────────────────
export async function computePipelineFunnel(
portId: string,
range: DateRange,
): Promise<PipelineFunnelData> {
const { from, to } = rangeToBounds(range);
// Stage counts EXCLUDE lost/cancelled outcomes - those never become
// conversions, so polluting the funnel with them gives meaningless math.
// Lost is reported separately in the `lost` block.
const stageRows = await db
.select({ stage: interests.pipelineStage, count: sql<number>`count(*)::int` })
.from(interests)
.where(
and(
eq(interests.portId, portId),
isNull(interests.archivedAt),
between(interests.createdAt, from, to),
sql`(${interests.outcome} IS NULL OR ${interests.outcome} = 'won')`,
),
)
.groupBy(interests.pipelineStage);
const counts = new Map(stageRows.map((r) => [r.stage, r.count]));
const top = counts.get('open') ?? 0;
const stages = PIPELINE_STAGES.map((stage) => {
const count = counts.get(stage) ?? 0;
const conversionPct = top === 0 ? 0 : Math.round((count / top) * 1000) / 10;
return { stage, count, conversionPct };
});
// Lost / cancelled summary. Same date-range filter as the funnel.
const lostRows = await db
.select({ outcome: interests.outcome, count: sql<number>`count(*)::int` })
.from(interests)
.where(
and(
eq(interests.portId, portId),
isNull(interests.archivedAt),
between(interests.createdAt, from, to),
sql`${interests.outcome} IS NOT NULL AND ${interests.outcome} != 'won'`,
),
)
.groupBy(interests.outcome);
const byOutcome: Record<string, number> = {};
let lostTotal = 0;
for (const row of lostRows) {
if (!row.outcome) continue;
byOutcome[row.outcome] = row.count;
lostTotal += row.count;
}
return { stages, lost: { count: lostTotal, byOutcome } };
}
export async function computeOccupancyTimeline(
portId: string,
range: DateRange,
): Promise<OccupancyTimelineData> {
const { from, to } = rangeToBounds(range);
const days = Math.max(1, Math.ceil((to.getTime() - from.getTime()) / 86_400_000));
// Total berths per port (current count - assumes no churn).
const totalRow = await db.execute<{ total: number }>(
sql`SELECT count(*)::int AS total FROM berths WHERE port_id = ${portId}`,
);
const total = totalRow[0]?.total ?? 0;
// For each day in range, count berths that have an active reservation
// covering that day. A reservation is "covering" if start_date <= day
// AND (end_date IS NULL OR end_date >= day). Walk forward from `from`
// so custom ranges produce the right calendar days, not just N
// most-recent days from "now".
const points: OccupancyTimelineData['points'] = [];
for (let i = 0; i < days; i++) {
const day = new Date(from.getTime() + i * 86_400_000);
const dayStr = day.toISOString().slice(0, 10);
const occRow = await db
.select({ occupied: sql<number>`count(distinct ${berthReservations.berthId})::int` })
.from(berthReservations)
.where(
and(
eq(berthReservations.portId, portId),
eq(berthReservations.status, 'active'),
sql`${berthReservations.startDate} <= ${dayStr}::date`,
sql`(${berthReservations.endDate} IS NULL OR ${berthReservations.endDate} >= ${dayStr}::date)`,
),
);
const occupied = occRow[0]?.occupied ?? 0;
const occupancyPct = total === 0 ? 0 : Math.round((occupied / total) * 1000) / 10;
points.push({ date: dayStr, occupied, total, occupancyPct });
}
return { points };
}
export async function computeRevenueBreakdown(
portId: string,
range: DateRange,
): Promise<RevenueBreakdownData> {
const { from, to } = rangeToBounds(range);
const rows = await db
.select({
status: invoices.status,
currency: invoices.currency,
amount: sql<string>`coalesce(sum(${invoices.total}), 0)::text`,
})
.from(invoices)
.where(
and(
eq(invoices.portId, portId),
isNull(invoices.archivedAt),
between(invoices.createdAt, from, to),
),
)
.groupBy(invoices.status, invoices.currency);
return {
bars: rows.map((r) => ({
status: r.status,
currency: r.currency,
amount: Number(r.amount),
})),
};
}
export async function computeLeadSourceAttribution(
portId: string,
range: DateRange,
): Promise<LeadSourceAttributionData> {
const { from, to } = rangeToBounds(range);
const rows = await db
.select({ source: interests.source, count: sql<number>`count(*)::int` })
.from(interests)
.where(
and(
eq(interests.portId, portId),
isNull(interests.archivedAt),
between(interests.createdAt, from, to),
),
)
.groupBy(interests.source);
return {
slices: rows
.map((r) => ({
source: r.source ?? 'unspecified',
count: r.count,
}))
.sort((a, b) => b.count - a.count),
};
}
// ─── Public read API (cache → compute → write back) ──────────────────────────
//
// Custom ranges always recompute (cache key would be unbounded). Preset
// ranges go cache → compute → write-back as before.
export async function getPipelineFunnel(
portId: string,
range: DateRange,
): Promise<PipelineFunnelData> {
if (isCustomRange(range)) return computePipelineFunnel(portId, range);
const metricId = `pipeline_funnel.${range}` as const;
const cached = await readSnapshot<PipelineFunnelData>(portId, metricId);
if (cached) return cached;
const fresh = await computePipelineFunnel(portId, range);
await writeSnapshot(portId, metricId, fresh);
return fresh;
}
export async function getOccupancyTimeline(
portId: string,
range: DateRange,
): Promise<OccupancyTimelineData> {
if (isCustomRange(range)) return computeOccupancyTimeline(portId, range);
const metricId = `occupancy_timeline.${range}` as const;
const cached = await readSnapshot<OccupancyTimelineData>(portId, metricId);
if (cached) return cached;
const fresh = await computeOccupancyTimeline(portId, range);
await writeSnapshot(portId, metricId, fresh);
return fresh;
}
export async function getRevenueBreakdown(
portId: string,
range: DateRange,
): Promise<RevenueBreakdownData> {
if (isCustomRange(range)) return computeRevenueBreakdown(portId, range);
const metricId = `revenue_breakdown.${range}` as const;
const cached = await readSnapshot<RevenueBreakdownData>(portId, metricId);
if (cached) return cached;
const fresh = await computeRevenueBreakdown(portId, range);
await writeSnapshot(portId, metricId, fresh);
return fresh;
}
export async function getLeadSourceAttribution(
portId: string,
range: DateRange,
): Promise<LeadSourceAttributionData> {
if (isCustomRange(range)) return computeLeadSourceAttribution(portId, range);
const metricId = `lead_source_attribution.${range}` as const;
const cached = await readSnapshot<LeadSourceAttributionData>(portId, metricId);
if (cached) return cached;
const fresh = await computeLeadSourceAttribution(portId, range);
await writeSnapshot(portId, metricId, fresh);
return fresh;
}
// ─── Cron entrypoint: warm every (port × metric × range) ────────────────────
export async function refreshSnapshotsForPort(portId: string): Promise<void> {
for (const range of ALL_RANGES) {
const [funnel, occupancy, revenue, leadSource] = await Promise.all([
computePipelineFunnel(portId, range),
computeOccupancyTimeline(portId, range),
computeRevenueBreakdown(portId, range),
computeLeadSourceAttribution(portId, range),
]);
await Promise.all([
writeSnapshot(portId, `pipeline_funnel.${range}`, funnel),
writeSnapshot(portId, `occupancy_timeline.${range}`, occupancy),
writeSnapshot(portId, `revenue_breakdown.${range}`, revenue),
writeSnapshot(portId, `lead_source_attribution.${range}`, leadSource),
]);
}
}