tudor
7f82088d53
fix(pipeline): use to_date for DD-MM-YYYY GIAS dates, exclude EES models from daily DAG
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GIAS CSV dates are DD-MM-YYYY format — use to_date() instead of cast().
Exclude int_ks2_with_lineage+ and int_ks4_with_lineage+ from daily DAG
selector since they depend on EES data not yet loaded.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com >
2026-03-26 20:51:40 +00:00
tudor
e7b1ab9f37
fix(pipeline): expand GIAS schema, handle empty strings, scope DAG selectors
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- Declare all 34 columns needed by dbt in GIAS tap schema (target-postgres
only persists columns present in the Singer schema message)
- Use nullif() for empty-string-to-integer/date casts in staging models
- Scope daily DAG dbt build to GIAS models only (stg_gias_establishments+
stg_gias_links+) to avoid errors on unloaded sources
- Scope annual EES DAG similarly; remove redundant dbt test steps
- Make dim_school gracefully handle missing int_ofsted_latest table
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com >
2026-03-26 20:43:24 +00:00
tudor
c576bba06a
fix(meltano): remove catalog capability and switch elt to run
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The `catalog` capability forced Meltano to run --discover and generate
a catalog file (tap.properties.json) before each extraction. This fails
because our Singer SDK taps emit schemas inline and don't need external
catalog files. Removing the capability makes Meltano invoke taps
directly without catalog generation.
Also switch from deprecated `meltano elt` to `meltano run` for
Meltano 4.x compatibility.
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com >
2026-03-26 13:45:23 +00:00
tudor
e815f597ab
fix(dags): use global bin paths and add BashOperator import fallback
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- MELTANO_BIN/DBT_BIN pointed to .venv/bin/ but Dockerfile installs globally
- Add try/except for BashOperator import to handle both Airflow 3 provider
path and legacy path, preventing silent DAG import failures
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com >
2026-03-26 10:47:18 +00:00
tudor
deb4024731
chore(pipeline): bump all dependencies to latest stable versions
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- Airflow 2.11 → 3.1 (BashOperator moved to providers-standard)
- Meltano 3.5 → 4.1 (meltano.yml version 2, meltanolabs target-postgres)
- dbt-postgres 1.9 → 1.10
- singer-sdk 0.39 → 0.53 (all 6 taps)
- Typesense Docker 27.1 → 30.1
- Typesense Python client >=2.0
- Python base image 3.12 → 3.13
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com >
2026-03-26 09:18:11 +00:00
tudor
8f02b5125e
feat(pipeline): add Meltano + dbt + Airflow ELT pipeline scaffold
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Build and Push Docker Images / Build Backend (FastAPI) (push) Successful in 35s
Build and Push Docker Images / Build Frontend (Next.js) (push) Successful in 1m9s
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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
tudor