feat(postcodes/BR): bulk-import 5,692 municipality CEPs (#1039)#1446
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Adds Brazilian postcodes via the Maahzuka/database-CEPS mirror (despite
the repo name suggesting Latin America scope, the data inside is purely
Brazilian Correios CEP municipality coverage).
1. bin/scripts/sync/import_brazil_postcodes.py — pipeline reading the
xlsx via openpyxl streaming. Picks each municipality's CEP_INICIAL
as the canonical postcode, formats as '#####-###'. State resolution
via UF -> states.iso2 direct match (BR's 27 states use the same
2-letter codes in source and CSC dataset).
2. contributions/postcodes/BR.json — 5,692 records covering all 27
states with 100% state_id + 98% coordinate resolution.
Coverage note
- This is municipality-level coverage, not full address-level. Brazil
has ~145,000 unique CEPs total but Correios paywalls full data.
Each Brazilian municipality gets one canonical 'primary' code here,
useful for geocoding and form auto-fill while keeping PR scope tight.
Validation (zero errors)
- All codes match countries.postal_code_regex (^\d{5}-\d{3}$)
- All FKs resolve, all state_codes agree with state.iso2
License & attribution
- Mirror: github.com/Maahzuka/database-CEPS
- Original publisher: Correios (Brazilian postal service)
- Each row: source: 'correios'
Refs: #1039
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
Contributor
CSC Validation ReportPR Format
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Adds Brazilian postcodes via the Maahzuka/database-CEPS mirror.
5,692 records, 100% state_id + 98% coordinate resolution.
Municipality-level coverage (one CEP per Brazilian município, using each muni's CEP_INICIAL as canonical). Full address-level Brazilian CEPs (~145k) are paywalled by Correios; this gives geocoding-grade coverage of every BR municipality.
Refs: #1039