Two surfaces wired up so the user can "get a vibe of the market":
**Per-listing** — each PropertyCard now shows a small pill next to the
price when the listing's total_price moved >=1% over a 14-day lookback
(e.g. "↓ £200 (-4%) in 14d"). Drops render green, rises render red.
Computed from `price_history_json` by the daily aggregator and
denormalised onto the listing row so the streaming endpoint just
passes it through.
**Macro** — new always-visible inline strip above the chip strip
showing today's median total price, median £/m², and listing count
for the current filter's bedroom band, each with a 30-day % delta:
"Rent · 1-2 bed · 30d: Median £2,500 ↓ -4% · £/m² £50 ↓ -2% · Listings 4,200 ↑ +5%".
Both data sources are populated daily at 04:00 UTC by a new Celery
beat task that fires 1h after the 03:00 RENT scrape and feeds two
sinks: a per-listing update pass and an upsert to a new
`dailylistingaggregate` table keyed on
(snapshot_date, listing_type, min_bedrooms, max_bedrooms).
## Backend
- `models/listing.py`: Listing parent gains `price_14d_ago` + `price_
change_pct_14d` nullable floats (inherited by RentListing/BuyListing).
New `DailyListingAggregate` table model with unique constraint on
(date, type, min_bed, max_bed).
- Alembic `a8b9c0d1e2f3`: adds the two columns to both listing tables
and creates the aggregate table + date index.
- `services/market_aggregator.py` (new): `compute_trend_for_listing`,
`update_per_listing_trend` (batched, idempotent), `_stats` (median
+ mean filtered to positive finite values), `compute_aggregate_
snapshot` (dialect-aware MySQL / SQLite upsert), `fetch_trend_
series` (range query for the API).
- `tasks/market_tasks.py` (new): `compute_daily_market_aggregates_task`
Celery task wrapping both stages.
- `tasks/listing_tasks.py:setup_periodic_tasks`: registers the daily
task at 04:00 UTC alongside the existing scrape schedules.
- `celery_app.py`: includes the new tasks module.
- `api/app.py`: new `GET /api/market_trend?listing_type=&min_bedrooms=&
max_bedrooms=&days=` endpoint returning the daily series.
- `ui_exporter.py`: GeoJSON feature properties now carry
`price_14d_ago` and `price_change_pct_14d` so the frontend can
render the badge without an extra round-trip.
## Frontend
- `types/index.ts`: new `MarketTrendPoint`; `PropertyProperties` gains
the two optional trend fields.
- `components/PropertyCard.tsx`: derived `trendBadge` (>=1% threshold,
null-safe) rendered as a small pill on both card variants.
- `hooks/useMarketTrend.ts` (new): fetches the trend series, derives
current-vs-oldest deltas per metric (% change rounded to 1dp).
- `components/MarketTrendStrip.tsx` (new): compact inline strip with
three metric cells. Hidden when the aggregator hasn't produced any
rows yet (graceful start during the first week post-launch).
- `App.tsx`: renders the strip above the chip strip whenever the
active queryParameters are known.
## Tests
- pytest: 10 new (trend math edge cases including null history,
malformed JSON, only-recent entries, drops, rises, zero current
price; _stats empty / nonpositive filtering; upsert idempotency on
an in-memory SQLite seed). 34 decision + aggregator tests pass.
- vitest: 8 new (useMarketTrend fetch URL, two-point delta,
single-point null delta, empty series; PropertyCard trend badge
arrow direction + sign for drops/rises, noise threshold, null
guard). 229 tests pass total, tsc clean.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
Init OTel metrics at module level in celery_app.py so prefork child
processes inherit the MeterProvider and PrometheusMetricReader from
the parent. Previously, worker_process_init created a separate
MeterProvider in each child, disconnected from the HTTP server in
the main process — so all scrape/celery/OCR metrics were silently
lost.
Update Grafana dashboard with API Performance and Frontend Performance
sections, synced from the live cluster dashboard.
worker_ready fires in the main process after pool workers are forked,
so init_metrics() never ran in the child processes. Add a
worker_process_init handler to initialize OTel metrics in each worker.
Type-annotated metric variables (e.g. `geojson_cache_operations: Counter`)
don't exist as importable names until init_metrics() runs. Switch all
`from api.metrics import <metric>` to `import api.metrics as m` and
access instruments as attributes at runtime to avoid ImportError.
Structured logging via JsonFormatter replaces uvicorn's default format so
Loki can parse timestamps and fields. 14 business metrics (scrape stats,
throttle events, circuit breaker state, cache hit rate, OCR success rate,
Celery task lifecycle) are defined in a shared metrics module and
instrumented across the scraper pipeline, API, and workers. Celery
workers expose a Prometheus HTTP endpoint on configurable ports.
FastAPI router with CRUD endpoints for POIs, distance calculation
trigger, and distance queries. Streaming GeoJSON endpoint now accepts
include_poi_distances=true to inject travel times into features.
Celery task wraps the distance calculator with progress reporting.
The crawler subdirectory was the only active project. Moving it to the
repo root simplifies paths and removes the unnecessary nesting. The
vqa/ and immoweb/ directories were legacy/unused and have been removed.
Updated .drone.yml, .gitignore, .claude/ docs, and skills to reflect
the new flat structure.
