feat(pipeline): add Meltano + dbt + Airflow ELT pipeline scaffold
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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>
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17
pipeline/plugins/extractors/tap-uk-idaci/pyproject.toml
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pipeline/plugins/extractors/tap-uk-idaci/pyproject.toml
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[build-system]
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requires = ["setuptools>=68", "wheel"]
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build-backend = "setuptools.build_meta"
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[project]
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name = "tap-uk-idaci"
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version = "0.1.0"
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description = "Singer tap for UK IDACI deprivation index"
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requires-python = ">=3.10"
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dependencies = [
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"singer-sdk~=0.39",
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"requests>=2.31",
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"pandas>=2.0",
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]
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[project.scripts]
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tap-uk-idaci = "tap_uk_idaci.tap:TapUKIDACI.cli"
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"""tap-uk-idaci: Singer tap for IDACI (Income Deprivation Affecting Children Index)."""
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pipeline/plugins/extractors/tap-uk-idaci/tap_uk_idaci/tap.py
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pipeline/plugins/extractors/tap-uk-idaci/tap_uk_idaci/tap.py
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"""IDACI Singer tap — extracts deprivation index lookup data."""
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from __future__ import annotations
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from singer_sdk import Stream, Tap
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from singer_sdk import typing as th
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class IDACIStream(Stream):
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"""Stream: IDACI scores by LSOA."""
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name = "idaci"
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primary_keys = ["lsoa_code"]
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replication_key = None
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schema = th.PropertiesList(
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th.Property("lsoa_code", th.StringType, required=True),
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th.Property("idaci_score", th.NumberType),
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th.Property("idaci_decile", th.IntegerType),
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).to_dict()
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def get_records(self, context):
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# TODO: Implement IDACI extraction
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# Source: MHCLG IoD 2019 LSOA-level data
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# Available as a static CSV download
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self.logger.warning("IDACI extraction not yet implemented")
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return iter([])
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class TapUKIDACI(Tap):
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"""Singer tap for UK IDACI data."""
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name = "tap-uk-idaci"
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config_jsonschema = th.PropertiesList().to_dict()
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def discover_streams(self):
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return [IDACIStream(self)]
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if __name__ == "__main__":
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TapUKIDACI.cli()
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