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Author SHA1 Message Date
TudorandClaude Opus 5 de853b90b3 feat(places): London localities and postcode districts 
The GIAS town field puts 1,819 London schools under the single value
'London', so it cannot answer 'schools in Battersea' — a query that appears in
the baseline. No single field can: parliamentary constituency gives Battersea
but not Canary Wharf, admin_ward gives Canary Wharf but not Battersea, and
neither gives Clapham or Shoreditch. So a locality is curated, defined by the
postcode districts it covers, which needs no new ingestion.

A locality may not shadow a published town: the registry raises rather than
silently costing a page that carries real demand. One below the threshold is
logged rather than raising, because a locality can legitimately be too small.

The pipeline seed mirrors the module, with a test guarding the drift — the
same arrangement gias_codes has, and for the same reason: the backend image
does not contain pipeline/.

Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_015mWQnpye9F299NVRCCSRvj
 2026-08-21 18:11:56 +01:00
TudorandClaude Fable 5 3710529e49 fix(api): map blank-name GIAS sentinel codes to empty string, not Unknown
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ReligiousCharacter 99 (~4k schools) and AdmissionsPolicy 9 (~5.6k) carry a
code with a blank name in the GIAS CSV; the generator skipped them so they
hit the Unknown(<code>) path — wrongly triggering the Faith-priority tag
and polluting filters. Blank-only codes now map to "" (byte-identical to
the old name pipeline); accepted_values lists extended to match the seed.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
 2026-07-09 22:04:53 +01:00
TudorandClaude Fable 5 e188c2ff4b feat: GIAS code->name dictionaries generated from live bulk CSV 
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
 2026-07-09 10:38:19 +01:00
tudorandClaude Opus 4.6 8f02b5125e feat(pipeline): add Meltano + dbt + Airflow ELT pipeline scaffold
Build and Push Docker Images / Build Backend (FastAPI) (push) Successful in 35s
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Build and Push Docker Images / Build Frontend (Next.js) (push) Successful in 1m9s
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Build and Push Docker Images / Build Integrator (push) Successful in 56s
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Build and Push Docker Images / Build Kestra Init (push) Successful in 32s
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Replaces the hand-rolled integrator with a production-grade ELT pipeline
using Meltano (Singer taps), dbt Core (medallion architecture), and
Apache Airflow (orchestration). Adds Typesense for search and PostGIS
for geospatial queries.

- 6 custom Singer taps (GIAS, EES, Ofsted, Parent View, FBIT, IDACI)
- dbt project: 12 staging, 5 intermediate, 12 mart models
- 3 Airflow DAGs (daily/monthly/annual schedules)
- Typesense sync + batch geocoding scripts
- docker-compose: add Airflow, Typesense; upgrade to PostGIS
- Portainer stack definition matching live deployment topology

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
 2026-03-26 08:37:53 +00:00