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Central - data hub spine. Adapters -> NATS/JetStream -> archive.
- Python 90.5%
- HTML 9.1%
- PLpgSQL 0.4%
First half of the split PR L (events-tab + map deferred to L-b). Only FIRMS
declared enrichment_locations, so apply_enrichment silently bypassed every
other adapter. This declares it for all 12.
Pre-read finding (resolved per PM): apply_enrichment is a FLAT lookup
(event.data.get(lat_path)); FIRMS/usgs_quake already carry top-level
latitude/longitude in event.data, but the other point adapters kept coords
only in Geo.centroid where the flat path can't reach them. Per PM (option b),
the 5 centroid-only adapters now also write top-level latitude/longitude into
event.data, mirroring their existing Geo.centroid (lon, lat) — 2-3 lines each,
no framework refactor. Geo retained for existing rendering uses.
Declarations (verbatim):
firms [("latitude","longitude")] (unchanged)
usgs_quake [("latitude","longitude")] (already top-level in data)
nwis [("latitude","longitude")] + centroid mirror
eonet [("latitude","longitude")] + centroid mirror
gdacs [("latitude","longitude")] + centroid mirror
wfigs_incidents [("latitude","longitude")] + centroid mirror (inline data)
inciweb [("latitude","longitude")] + centroid mirror (inline data)
wfigs_perimeters [] # polygons, no point
nws [] # forecast zones/counties, no point
swpc_alerts [] # space weather, no coordinate
swpc_kindex [] # space weather, no coordinate
swpc_protons [] # space weather, no coordinate
Centroid mirror is `latitude = centroid[1]; longitude = centroid[0]` (centroid
is GeoJSON (lon, lat)); guarded on centroid presence so coordinate-less events
get no lat/lon keys (apply_enrichment then skips them).
map_render_kind concept dropped — the existing /events map is already
geometry-kind-agnostic (renders any row's data-geometry via L.geoJSON), so it
was unnecessary. Events-tab enhancements are PR L-b.
Tests (test_enrichment_locations_coverage.py, 6, all registry-derived):
- every adapter explicitly declares enrichment_locations in its own class body
- declarations are valid list[(str,str)]
- point adapters all use the canonical ("latitude","longitude") paths
- >=5 point adapters are non-empty (regression guard)
- synthetic-event builders prove the keys resolve: usgs_quake._feature_to_event
and nwis._build_event (the two adapters with isolated builders; the four
inline-build adapters are covered by the post-merge live smoke).
Verification: full pytest 552 passed, 1 skipped (was 546; +6). grep
subject_for_event/_ADAPTER_REGISTRY and grep 100.64.0./192.168.1. in src empty.
Follow-ups (NOT here): consumer-doc per-adapter _enriched.geocoder notes for
the newly-enriched adapters belong in L-b's doc pass; live end-to-end smoke
runs post-merge (USGS quake + one other) per the acceptance bar.
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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Central
Central is the data hub spine for the infrastructure. Adapters normalize upstream sources into a canonical event shape, publish CloudEvents to NATS/JetStream, and archive to TimescaleDB for historical query. Single-LXC deployment.
Status
Phase 0 — scaffold. Not yet operational.
Architecture
- Python 3.12 (uv-managed)
- NATS + JetStream for live event bus
- TimescaleDB + PostGIS for archive and geospatial query
- One supervisor process managing adapter lifecycle
- One archive consumer process persisting events to TimescaleDB
- Both processes systemd-managed
Testing
See docs/test-database.md for test database setup.
License
MIT. See LICENSE.