Files
Autoparts-DB/scripts/import_luk_catalog.py
consultoria-as ea29cc31c0 feat(catalog): supplier catalog cleanup, fuzzy matching, and navigation fixes
- Cleaned 137+ fake engine-displacement models from supplier imports
  (v3/v4 scripts: Chevrolet, Ford, Chrysler, Dodge, Jeep, Nissan, etc.)
- Removed 1,251+ corrupted models (INT. prefixes, year-suffix, torque specs,
  empty names, trailing-year variants)
- Migrated supplier tables to master DB (supplier_catalog,
  supplier_catalog_compat, supplier_catalog_interchange)
- Fixed _get_mye_ids_with_parts() to query supplier_catalog_compat from
  master DB so supplier-only vehicles appear for all tenants
- Added fuzzy model matcher with parenthesis stripping, noise suffix removal,
  compact matching, prefix/substring fallback, model aliases, and ±3 year
  proximity
- Matched compat rows: KEEP GREEN +14,152, KNADIAN +3,021, VAZLO +127,500,
  LUK +477, RAYBESTOS +1,743
- Added KNADIAN catalog importer with year-range expansion and future-year
  filtering
- Added VAZLO catalog importer with position parsing and SKU-in-model cleanup
- Added Keep Green, LUK, Yokomitsu, Raybestos catalog importers
- Cache clearing after cleanups (_classify_cache_*, nexus:mye_ids:*,
  nexus:brand_mye_counts:*)

Final match rates:
- KEEP GREEN: 90.3%
- VAZLO: 93.6%
- YOKOMITSU: 100.0%
- KNADIAN: 57.4%
- LUK: 51.0%
- RAYBESTOS: 55.9%
2026-06-09 07:47:42 +00:00

236 lines
6.7 KiB
Python

#!/usr/bin/env python3
"""
Import LUK catalog from Excel into supplier_catalog tables.
Usage:
python scripts/import_luk_catalog.py
"""
import os
import re
import sys
from collections import Counter
from datetime import datetime
import psycopg2
from openpyxl import load_workbook
MASTER_DB_URL = os.environ.get('MASTER_DB_URL', 'postgresql://postgres@localhost/nexus_autoparts')
TENANT_DB_URL = os.environ.get('TENANT_DB_URL', 'postgresql://postgres@localhost/tenant_refaccionaria_rached')
EXCEL_PATH = os.path.join(os.path.dirname(__file__), '..', 'data', 'LUK.xlsx')
SUPPLIER_NAME = 'LUK'
TENANT_ID = 31
MULTI_WORD_MAKES = {
('ALFA', 'ROMEO'): 'ALFA ROMEO',
('MERCEDES', 'BENZ'): 'MERCEDES BENZ',
('MG', 'ROVER'): 'MG ROVER',
}
NOTE_KEYWORDS = {
'VOLANTE', 'SÓLIDO', 'SOLIDO', 'TIPO', 'CAJA', 'PLANO',
'ESCALÓN', 'ESCALON', 'MOTOR', 'EMBRAGUE', 'DOBLE', 'HUMEDO',
}
def connect_master():
return psycopg2.connect(MASTER_DB_URL)
def connect_tenant():
return psycopg2.connect(TENANT_DB_URL)
def normalize_name(name):
if not name:
return ''
return ' '.join(str(name).replace('\n', ' ').split())
def parse_luk(carro):
"""Parse CARRO_PERTENECIENTE into make, model, year."""
if not carro:
return None, None, None
s = ' '.join(str(carro).strip().split())
if not s:
return None, None, None
parts = s.split()
# Extract year (last occurrence of 19xx or 20xx)
year = None
year_idx = None
for i in range(len(parts)):
if re.match(r'^(19|20)\d{2}$', parts[i]):
year = int(parts[i])
year_idx = i
# Extract make
make = parts[0] if parts else ''
make_len = 1
if len(parts) >= 2:
key2 = (parts[0].upper(), parts[1].upper())
if key2 in MULTI_WORD_MAKES:
make = MULTI_WORD_MAKES[key2]
make_len = 2
elif len(parts) >= 3 and parts[0].upper() == 'CHRYSLER' and parts[1] == '/' and parts[2].upper() == 'DODGE':
make = 'CHRYSLER / DODGE'
make_len = 3
# Remaining parts between make and year
if year_idx is not None:
remaining = parts[make_len:year_idx] + parts[year_idx + 1:]
else:
remaining = parts[make_len:]
# Clean note keywords
cleaned = [p for p in remaining if p.upper() not in NOTE_KEYWORDS]
model = ' '.join(cleaned)
# If empty after cleaning, use original remaining text
if not model and remaining:
model = ' '.join(remaining)
return make, model, year
def extract_interchanges(row):
"""Extract (brand, part_number) pairs from 4 interchange columns."""
interchanges = []
for i in range(4):
marca_col = 2 + i * 2
inter_col = 3 + i * 2
if marca_col < len(row) and row[marca_col]:
brand = str(row[marca_col]).strip()
pn = str(row[inter_col]).strip() if inter_col < len(row) and row[inter_col] else ''
if brand and pn:
interchanges.append((brand, pn))
return interchanges
def main():
print(f"[{datetime.now().isoformat()}] Starting LUK import...")
if not os.path.exists(EXCEL_PATH):
print(f"ERROR: Excel not found at {EXCEL_PATH}")
sys.exit(1)
print(f"Loading {EXCEL_PATH}...")
wb = load_workbook(EXCEL_PATH, read_only=True, data_only=True)
ws = wb['KIT_CLUTCH']
master_conn = connect_master()
master_conn = connect_master()
master_cur = master_conn.cursor()
# Pre-scan: determine most common name per SKU
print("Pre-scanning SKUs...")
sku_name_counter = Counter()
for row in ws.iter_rows(min_row=2, values_only=True):
sku = str(row[1]).strip() if row[1] else ''
name = normalize_name(row[10])
if sku and name:
sku_name_counter[(sku, name)] += 1
sku_best_name = {}
for (sku, name), count in sku_name_counter.items():
if sku not in sku_best_name or count > sku_best_name[sku][1]:
sku_best_name[sku] = (name, count)
print(f" Found {len(sku_best_name)} unique SKUs")
upsert_catalog_sql = """
INSERT INTO supplier_catalog (supplier_name, sku, name, category)
VALUES (%s, %s, %s, %s, %s)
ON CONFLICT (supplier_name, sku, category) DO UPDATE SET
name = EXCLUDED.name,
category = EXCLUDED.category
RETURNING id
"""
insert_compat_sql = """
INSERT INTO supplier_catalog_compat
(catalog_id, make, model, year, engine, model_year_engine_id, source)
VALUES (%s, %s, %s, %s, %s, %s, %s)
ON CONFLICT (catalog_id, make, model, year, engine) DO NOTHING
"""
insert_interchange_sql = """
INSERT INTO supplier_catalog_interchange (catalog_id, brand, part_number)
VALUES (%s, %s, %s)
ON CONFLICT DO NOTHING
"""
stats = {
'rows': 0,
'catalog_items': 0,
'compat_rows': 0,
'interchange_rows': 0,
'vehicles_parsed': 0,
}
catalog_id_cache = {}
for idx, row in enumerate(ws.iter_rows(min_row=2, values_only=True)):
if idx % 1000 == 0 and idx > 0:
print(f" ...{idx} rows processed")
if not row or not row[1]:
continue
sku = str(row[1]).strip()
name = sku_best_name.get(sku, ('', 0))[0]
carro_raw = str(row[11]).strip() if row[11] else ''
if not sku or not name:
continue
stats['rows'] += 1
cache_key = (sku, 'KIT_CLUTCH')
catalog_id = catalog_id_cache.get(cache_key)
if catalog_id is None:
master_cur.execute(upsert_catalog_sql, (SUPPLIER_NAME, sku, name, 'KIT_CLUTCH'))
catalog_id = master_cur.fetchone()[0]
catalog_id_cache[cache_key] = catalog_id
stats['catalog_items'] += 1
parsed = parse_luk(carro_raw)
stats['vehicles_parsed'] += 1
master_cur.execute(insert_compat_sql, (
catalog_id,
parsed[0],
parsed[1],
parsed[2],
None,
None,
'import_text',
))
stats['compat_rows'] += 1
interchanges = extract_interchanges(row)
for brand, pn in interchanges:
master_cur.execute(insert_interchange_sql, (catalog_id, brand, pn))
stats['interchange_rows'] += 1
master_conn.commit()
print(f"\n{'='*60}")
print("IMPORT COMPLETE")
print(f"{'='*60}")
print(f"Total rows read: {stats['rows']}")
print(f"Catalog items: {stats['catalog_items']}")
print(f"Compat rows: {stats['compat_rows']}")
print(f"Interchange rows: {stats['interchange_rows']}")
print(f"Vehicles parsed: {stats['vehicles_parsed']}")
master_cur.close()
master_conn.close()
master_conn.close()
if __name__ == '__main__':
main()