2f593c30f6
Prevent partner duplicates via ANAF CUI verification and dual PL/SQL search. Fix address matching with street-level comparison and diacritics normalization. Show partner/address comparison in order detail modal. - New anaf_service.py: batch ANAF API client with chunking, retry, cache - PL/SQL: dual CUI search (bare/RO+bare/RO space+bare), 3-tier address search (street+city+id_loc → city+id_loc → create), strip_diacritics at storage for addresses and partner names - SQLite: anaf_cache table, 12 new order columns for partner/address data - import_service: cod_fiscal_override param, return partner/address from Oracle - sync_service: ANAF batch integration, denomination mismatch detection, cache pre-population trigger - Router: enriched order_detail with partner_info + addresses JSON - UI: collapsible Detalii Partener + Adrese Comparativ sections in modal, auto-expand on mismatch, ANAF badges, mobile address cards - Dashboard: address quality attention indicator - New scan_duplicate_partners.py script for one-time duplicate audit Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
50 lines
1.7 KiB
Python
50 lines
1.7 KiB
Python
#!/usr/bin/env python3
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"""One-time script to find duplicate partners by CUI (bare number, ignoring RO prefix)."""
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import sys, os, csv
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sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..'))
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# Setup Oracle env same as start.sh
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from api.app import database
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def scan_duplicates():
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database.init_oracle()
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conn = database.get_oracle_connection()
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try:
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with conn.cursor() as cur:
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cur.execute("""
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SELECT bare_cui, COUNT(*) as cnt,
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LISTAGG(id_part||':'||denumire, ', ') WITHIN GROUP (ORDER BY id_part) as partners
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FROM (SELECT id_part, denumire,
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TRIM(REGEXP_REPLACE(UPPER(TRIM(cod_fiscal)), '^RO\\s*', '')) as bare_cui
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FROM nom_parteneri WHERE NVL(sters,0)=0
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AND cod_fiscal IS NOT NULL AND LENGTH(TRIM(cod_fiscal)) >= 3)
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GROUP BY bare_cui HAVING COUNT(*) > 1
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ORDER BY cnt DESC
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""")
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rows = cur.fetchall()
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finally:
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database.pool.release(conn)
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database.close_oracle()
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# Output markdown + CSV
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print(f"\n## Duplicate Partners Report\n")
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print(f"Found {len(rows)} CUIs with duplicate partners.\n")
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print("| CUI | Count | Partners |")
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print("|-----|-------|----------|")
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for row in rows:
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print(f"| {row[0]} | {row[1]} | {row[2][:100]} |")
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# CSV output
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csv_path = os.path.join(os.path.dirname(__file__), 'duplicate_partners.csv')
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with open(csv_path, 'w', newline='') as f:
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writer = csv.writer(f)
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writer.writerow(['bare_cui', 'count', 'partners'])
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for row in rows:
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writer.writerow(row)
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print(f"\nCSV saved: {csv_path}")
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if __name__ == '__main__':
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scan_duplicates()
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