Files
Autoparts-DB/scripts/import_raybestos_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

304 lines
9.4 KiB
Python

#!/usr/bin/env python3
"""
Import Raybestos catalog from Excel into supplier_catalog tables.
Usage:
python scripts/import_raybestos_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', 'RAYBESTOS.xlsx')
SUPPLIER_NAME = 'RAYBESTOS'
TENANT_ID = 31
KNOWN_MAKES = {
'ACURA', 'ALFA', 'AMERICAN', 'ASTON', 'AUDI', 'BMW', 'BUICK', 'CADILLAC',
'CHEVROLET', 'CHRYSLER', 'CITROEN', 'DAEWOO', 'DODGE', 'FIAT', 'FORD',
'GMC', 'GREAT', 'HONDA', 'HYUNDAI', 'INFINITI', 'ISUZU', 'JAGUAR', 'JEEP',
'KIA', 'LAMBORGHINI', 'LAND', 'LEXUS', 'LINCOLN', 'MAZDA', 'MERCEDES',
'MERCURY', 'MINI', 'MITSUBISHI', 'NISSAN', 'PEUGEOT', 'PONTIAC', 'PORSCHE',
'RENAULT', 'ROLLS', 'SATURN', 'SCION', 'SEAT', 'SKODA', 'SMART', 'SUBARU',
'SUZUKI', 'TESLA', 'TOYOTA', 'VOLKSWAGEN', 'VOLSWAGEN', 'VOLVO', 'VW'
}
POS_KEYWORDS = {'DELANTERA', 'TRASERA', 'TAS', 'DEL', 'TRAS', 'FRONT', 'REAR', 'LAT', 'IZQ', 'DER'}
NOTE_KEYWORDS = {'LATIN', 'AMERICA', 'NACIONAL', 'USA', 'EUROPA', 'IMPORTADO'}
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_abbr_year(token):
if not token or not token.isdigit():
return None
n = int(token)
if n < 50:
return 2000 + n
if n < 100:
return 1900 + n
return None
def extract_make(parts):
"""Return (make, make_len) if first words form a known make, else (None, 0)."""
if not parts:
return None, 0
first = parts[0].upper()
if first not in KNOWN_MAKES:
return None, 0
if first == 'ALFA' and len(parts) >= 2 and parts[1].upper() == 'ROMEO':
return 'ALFA ROMEO', 2
if first == 'MERCEDES' and len(parts) >= 2 and parts[1].upper() == 'BENZ':
return 'MERCEDES BENZ', 2
if first == 'ROLLS' and len(parts) >= 2 and parts[1].upper() == 'ROYCE':
return 'ROLLS ROYCE', 2
if first == 'LAND' and len(parts) >= 2 and parts[1].upper() == 'ROVER':
return 'LAND ROVER', 2
if first == 'GREAT' and len(parts) >= 2 and parts[1].upper() == 'WALL':
return 'GREAT WALL', 2
if first == 'AMERICAN' and len(parts) >= 2 and parts[1].upper() == 'MOTORS':
return 'AMERICAN MOTORS', 2
if first == 'ASTON' and len(parts) >= 2 and parts[1].upper() == 'MARTIN':
return 'ASTON MARTIN', 2
# Normalize common typos
if first == 'VOLSWAGEN':
return 'Volkswagen', 1
if first == 'VW':
return 'Volkswagen', 1
return parts[0], 1
def parse_raybestos(carro, last_make):
if not carro:
return None, None, None, None, last_make
s = ' '.join(str(carro).strip().split())
if not s:
return None, None, None, None, last_make
parts = s.split()
# Extract 4-digit year from end
year = None
if parts and re.match(r'^(19|20)\d{2}$', parts[-1]):
year = int(parts[-1])
parts = parts[:-1]
# Extract make
make, make_len = extract_make(parts)
if make:
last_make = make
remaining = parts[make_len:]
elif last_make:
make = last_make
remaining = parts[:]
else:
make = None
remaining = parts[:]
# Extract abbreviated year or year range from remaining
if year is None and remaining:
for i in range(len(remaining)):
# Year range like 17-18, 90-05
m = re.match(r'^(\d{2})-(\d{2})$', remaining[i])
if m:
year = parse_abbr_year(m.group(2)) # use end year
remaining = remaining[:i] + remaining[i + 1:]
break
# Single 2-digit year
if re.match(r'^\d{2}$', remaining[i]):
y = parse_abbr_year(remaining[i])
if y:
year = y
remaining = remaining[:i] + remaining[i + 1:]
break
# Extract position keywords and notes
position = None
cleaned = []
for p in remaining:
pup = p.upper()
if pup in POS_KEYWORDS:
if pup == 'TAS':
position = 'TRASERA'
elif pup in ('DEL', 'FRONT'):
position = 'DELANTERA'
elif pup in ('TRAS', 'REAR'):
position = 'TRASERA'
else:
position = pup.title()
elif pup in NOTE_KEYWORDS:
pass # skip notes
else:
cleaned.append(p)
model = ' '.join(cleaned)
return make, model, position, year, last_make
def extract_interchanges(row):
"""Extract (brand, part_number) pairs from 2 interchange columns."""
interchanges = []
for i in range(2):
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 Raybestos 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['Freno_de_disco']
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[6])
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,
'forward_filled_make': 0,
}
catalog_id_cache = {}
last_make = None
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[7]).strip() if row[7] else ''
if not sku or not name:
continue
stats['rows'] += 1
cache_key = (sku, 'Freno_de_disco')
catalog_id = catalog_id_cache.get(cache_key)
if catalog_id is None:
master_cur.execute(upsert_catalog_sql, (SUPPLIER_NAME, sku, name, 'Freno_de_disco'))
catalog_id = master_cur.fetchone()[0]
catalog_id_cache[cache_key] = catalog_id
stats['catalog_items'] += 1
make, model, position, year, last_make = parse_raybestos(carro_raw, last_make)
if make and carro_raw and not extract_make(carro_raw.split())[0]:
stats['forward_filled_make'] += 1
stats['vehicles_parsed'] += 1
master_cur.execute(insert_compat_sql, (
catalog_id,
make,
model,
year,
position,
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']}")
print(f"Forward-filled makes: {stats['forward_filled_make']}")
master_cur.close()
master_conn.close()
master_conn.close()
if __name__ == '__main__':
main()