Some DfE supporting-files CSVs have a UTF-8 BOM on the first column,
causing it to be named '\ufefftime_period' instead of 'time_period'.
This trips Singer schema validation ('time_period' is a required property).
Strip the BOM from all column names after read_csv.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
DfE supporting-files CSVs (spc_school_level_underlying_data, AppsandOffers
SchoolLevel) are Latin-1 encoded. Add _encoding class attribute to base
stream class and override to 'latin-1' for census and admissions streams.
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Pipeline:
- EES tap: split KS4 into performance + info streams, fix admissions filename
(SchoolLevel keyword match), fix census filename (yearly suffix), remove
phonics (no school-level data on EES), change endswith → in for matching
- stg_ees_ks4: rewrite to filter long-format data and extract Attainment 8,
Progress 8, EBacc, English/Maths metrics; join KS4 info for context
- stg_ees_admissions: map real CSV columns (total_number_places_offered, etc.)
- stg_ees_census: update source reference, stub with TODO for data columns
- Remove stg_ees_phonics, fact_phonics (no school-level EES data)
- Add ees_ks4_performance + ees_ks4_info sources, remove ees_ks4 + ees_phonics
- Update int_ks4_with_lineage + fact_ks4_performance with new KS4 columns
- Annual EES DAG: remove stg_ees_phonics+ from selector
Backend:
- models.py: replace all models to point at marts.* tables with schema='marts'
(DimSchool, DimLocation, KS2Performance, FactOfstedInspection, etc.)
- data_loader.py: rewrite load_school_data_as_dataframe() using raw SQL joining
dim_school + dim_location + fact_ks2_performance; update get_supplementary_data()
- database.py: remove migration machinery, keep only connection setup
- app.py: remove check_and_migrate_if_needed, remove /api/admin/reimport-ks2
endpoints (pipeline handles all imports)
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
- Fix publication slugs (KS4, Phonics, Admissions were wrong)
- Split KS2 into two streams: ees_ks2_attainment (long format) and
ees_ks2_info (wide format context data)
- Target specific filenames instead of keyword matching
- Handle school_urn vs urn column naming
- Pivot KS2 attainment from long to wide format in dbt staging
- Add all ~40 KS2 columns the backend needs (GPS, absence, gender,
disadvantaged breakdowns, context demographics)
- Pass through all columns in int_ks2_with_lineage and fact_ks2
Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
