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This page documents the complete data flow for event reads in OOOC Fête Finder, from Postgres storage through processing layers to public delivery.

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Runtime source order

In production (DATA_MODE=remote), the source priority is:
  1. Postgres event store (primary)
  2. Local CSV fallback (data/events.csv) if Postgres data is unavailable
Google Sheets is NOT used as a live runtime source. It’s only used in admin for backup preview and import operations.

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Data read pipeline

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Step 1: Entry point

All public event reads start with the runtime service: 
// features/data-management/runtime-service.ts
import { getLiveEvents } from '@/features/data-management/runtime-service'

const result = await getLiveEvents({
  includeFeaturedProjection: true,
  includeEngagementProjection: true
})

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Step 2: Source chain

The runtime service delegates to the data manager: 
// features/data-management/data-manager.ts
export class DataManager {
  static async getEventsData(): Promise<DataManagerResult> {
    // Try sources in priority order based on DATA_MODE
  }
}

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Step 3: Source resolution

For DATA_MODE=remote: 
// Source priority
const sources: SourceDescriptor[] = [
  loadFromStore,      // Postgres event store
  loadFromLocalCSV    // Fallback CSV
]
Each source is attempted in order until one succeeds with valid data. 
interface SourceDescriptor {
  id: 'local' | 'store' | 'test'
  load: (warnings: string[]) => Promise<SourceAttemptResult>
}

interface SourceAttemptSuccess {
  success: true
  events: Event[]
  count: number
  source: 'local' | 'store' | 'test'
  warnings: string[]
  lastUpdate: string
}

​
Step 4: CSV processing

Once raw CSV data is retrieved from a source, it goes through processCSVData(): 
// features/data-management/data-processor.ts
export async function processCSVData(
  csvContent: string,
  source: 'local' | 'remote' | 'store',
  enableLocalFallback: boolean = true,
  options: {
    populateCoordinates?: boolean
    referenceDate?: Date
  } = {}
): Promise<ProcessedDataResult>

​
Step 5: Event key hydration

Every event must have a stable, unique eventKey: 
// features/data-management/assembly/event-key.ts
import { ensureUniqueEventKeys } from './assembly/event-key'

const keyedRows = ensureUniqueEventKeys(csvRows, {
  stableKeys: EXPECTED_HEADERS
})
Key generation rules:
  • Existing valid keys are preserved
  • Missing keys are generated from normalized row content using SHA-256
  • Collisions are resolved deterministically with salt
Event keys follow the pattern evt_[a-z0-9]{12,20} and are immutable after first generation.

​
Step 6: Event assembly

Each CSV row is transformed into a typed Event object: 
// features/data-management/assembly/event-assembler.ts
const events: Event[] = keyedRows.rows.map((row, index) =>
  assembleEvent(row, index, {
    dateNormalizationContext: dateContext
  })
)
Assembly handles:
  • Field normalization and transformation
  • Date parsing with context-aware inference
  • Genre and venue type categorization
  • URL validation and sanitization

​
Step 7: Quality checks

Before returning, events undergo validation: 
// features/data-management/validation/quality-checks.ts
export function performEventQualityChecks(events: Event[]): {
  passed: boolean
  errors: string[]
}
Checks include:
  • Required fields present (name, date, location)
  • Valid date formats
  • Reasonable coordinate bounds
  • No duplicate event keys

​
Step 8: Coordinate population

Coordinates are populated from durable KV storage: 
// features/maps/event-coordinate-populator.ts
const populator = new EventCoordinatePopulator()
await populator.populateCoordinatesForEvents(events, {
  batchSize: 10,
  onProgress: (processed, total, current) => {
    log.info('maps', `Geocoded ${processed}/${total}`)
  }
})
Coordinate storage uses KV key pattern maps:locations:v1:<normalized_address>. Coordinates are prewarmed on admin writes to reduce live geocoding API calls.

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Step 9: Projection layers

Finally, runtime service applies optional projections: 
// Apply featured spotlight status
if (includeFeaturedProjection) {
  await applyFeaturedProjectionToEvents(events)
}

// Apply engagement counts
if (includeEngagementProjection) {
  const repo = await getEventEngagementRepository()
  const stats = await repo.getCalendarSyncCountsByEventKeys(
    events.map(e => e.eventKey)
  )
  
  for (const event of events) {
    event.calendarSyncCount = stats.get(event.eventKey) ?? 0
  }
}

​
Public delivery

Processed events are delivered through Next.js rendering:

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ISR routes (homepage)

// app/page.tsx
export const revalidate = 300 // 5 minutes

export default async function Home() {
  return (
    <Suspense fallback={<Loading />}>
      <HomeEventsSection />
    </Suspense>
  )
}

​
Server component data fetch

// Inside HomeEventsSection server component
const eventsResult = await getLiveEvents()

if (!eventsResult.success) {
  return <ErrorState />
}

return <EventGrid events={eventsResult.data} />

​
Admin write flow

When admins save or import data:

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Save to Postgres

// features/data-management/actions.ts
export async function saveEventsToStore(
  csvContent: string
): Promise<SaveResult> {
  const store = await LocalEventStore.getInstance()
  await store.saveCsv(csvContent)
  
  // Warm coordinate cache
  const events = await processCSVData(csvContent, 'store')
  await warmupCoordinateCache(events)
  
  return { success: true }
}

​
Revalidation

After successful save: 
// features/data-management/runtime-service.ts
export async function fullRevalidation(): Promise<FullRevalidationResult> {
  // Revalidate cache tags
  for (const tag of EVENTS_CACHE_TAGS) {
    revalidateTag(tag)
  }
  
  // Revalidate specific paths
  for (const path of EVENTS_LAYOUT_PATHS) {
    revalidatePath(path)
  }
  
  return {
    success: true,
    cacheRefreshed: true,
    pageRevalidated: true,
    message: 'Full revalidation completed'
  }
}
Revalidation is asynchronous. Public pages may serve stale data briefly until background regeneration completes.

​
Coordinate warm-up

Admin writes trigger coordinate cache warm-up: 
// Warm-up flow
export async function warmupCoordinateCache(events: Event[]) {
  const populator = new EventCoordinatePopulator()
  
  // This writes to KV: maps:locations:v1:<address>
  await populator.populateCoordinatesForEvents(events)
  
  // Auto-upgrade estimated coordinates when geocoding available
  await populator.upgradeEstimatedCoordinates()
  
  // Prune stale location keys
  await populator.pruneStaleKeys(events)
}
Featured (spotlight) events are managed separately: 
// features/events/featured/service.ts
export async function applyFeaturedProjectionToEvents(
  events: Event[]
): Promise<void> {
  const repo = await getFeaturedScheduleRepository()
  const activeEntry = await repo.getActiveEntry()
  
  if (!activeEntry) return
  
  for (const event of events) {
    if (event.eventKey === activeEntry.eventKey) {
      event.isFeatured = true
    }
  }
}
Featured scheduling is Postgres-backed (app_featured_event_schedule). Legacy CSV Featured column values are rejected on save.

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Data mode configuration

The DATA_MODE environment variable controls source behavior:
ModePrimary SourceFallbackUse Case
remotePostgres storeLocal CSVProduction
localLocal CSVNoneDevelopment
testTest fixturesNoneTesting
DATA_MODE is required in production deploys. The app fails fast at startup if missing.

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Metrics and observability

Runtime service tracks basic metrics: 
// Telemetry only, not a data cache
const metrics = {
  errors: 0,
  totalFetchMs: 0,
  fetchCount: 0,
  lastReset: Date.now()
}
Metrics are available at GET /api/admin/data-store/status.

Architecture overview

System architecture and rendering contracts

Event identity

Stable event keys and share link model

Admin workflow

Day-to-day admin operations

Geocoding

Coordinate population and caching

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