147 lines
6.2 KiB
Python
147 lines
6.2 KiB
Python
import os
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import sys
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import sqlite3
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import json
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# Ruta a la base de datos (un nivel arriba del script)
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ROOT_DIR = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
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if ROOT_DIR not in sys.path:
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sys.path.insert(0, ROOT_DIR)
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import sync_engine # noqa: E402
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from paths import DB_PATH
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_schema_cache = {}
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_tokens_map = None
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def get_location_token(location_id):
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global _tokens_map
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if _tokens_map is None:
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_tokens_map = sync_engine.get_tokens_map()
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return _tokens_map.get(location_id)
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def get_schema_field_id(location_id, object_key, field_name):
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cache_key = (location_id, object_key)
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if cache_key not in _schema_cache:
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token = get_location_token(location_id)
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if not token:
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_schema_cache[cache_key] = {}
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else:
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_schema_cache[cache_key] = sync_engine.ghl_client.get_object_schema(token, location_id, object_key)
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return _schema_cache[cache_key].get(field_name)
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def extract_custom_field_value(cf_json, field_id):
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if not field_id or not cf_json:
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return None
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try:
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cfs = json.loads(cf_json)
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if isinstance(cfs, list):
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for cf in cfs:
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if cf.get("id") == field_id or cf.get("fieldId") == field_id:
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return cf.get("value")
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except Exception:
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pass
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return None
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def analyze_discrepancies():
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if not os.path.exists(DB_PATH):
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print(f"Error: La base de datos local no existe en {DB_PATH}.")
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print("Por favor, ejecuta la sincronización global primero desde el dashboard.")
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sys.exit(1)
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conn = sqlite3.connect(DB_PATH)
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conn.row_factory = sqlite3.Row
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try:
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# 1. Obtener todas las cuentas y mapear sus IDs y nombres
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accounts_rows = conn.execute("SELECT location_id, nombre FROM accounts").fetchall()
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branches = {}
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for r in accounts_rows:
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name = r['nombre']
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# Normalizar nombre de sucursal para comparación (ej. de "85932 - MP - La Viga" a "la viga")
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normalized_name = name.lower()
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for token in ["mp", "-", "859", "0001", "qro", "demo", "plaza"]:
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normalized_name = normalized_name.replace(token, "")
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normalized_name = " ".join(normalized_name.split())
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branches[r['location_id']] = {
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"full_name": name,
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"clean_name": normalized_name
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}
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# 2. Consultar todas las oportunidades y sus contactos asociados
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sql = """
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SELECT o.id as opp_id, o.name as opp_name, o.location_id as opp_loc_id, o.status as opp_status,
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c.id as contact_id, c.first_name, c.last_name, c.custom_fields_json, c.location_id as contact_loc_id
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FROM opportunities o
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JOIN contacts c ON o.contact_id = c.id AND o.location_id = c.location_id
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"""
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opps = conn.execute(sql).fetchall()
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print("=== ANÃLISIS DE DISCREPANCIAS DE SUCURSAL ===")
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print(f"Total de oportunidades con contactos analizadas: {len(opps)}")
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print("Buscando inconsistencias entre la sucursal del contacto (campo custom) y la ubicación real de la oportunidad...\n")
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print("-" * 110)
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discrepancies_count = 0
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missing_schema_locations = set()
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for row in opps:
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opp_loc_id = row['opp_loc_id']
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contact_cf_json = row['custom_fields_json']
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contact_loc_id = row['contact_loc_id']
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# Obtener nombre de la sucursal donde vive la oportunidad
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opp_branch_info = branches.get(opp_loc_id, {"full_name": "Desconocida", "clean_name": ""})
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opp_branch_clean = opp_branch_info["clean_name"]
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# Leer solo el campo personalizado Sucursal resuelto dinamicamente por schema.
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contact_sucursal_val = None
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sucursal_field_id = get_schema_field_id(contact_loc_id, "contact", "Sucursal")
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if not sucursal_field_id:
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missing_schema_locations.add(contact_loc_id)
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else:
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val = str(extract_custom_field_value(contact_cf_json, sucursal_field_id) or "").strip()
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val_lower = val.lower()
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for loc_id, b_info in branches.items():
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b_clean = b_info["clean_name"]
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if b_clean and b_clean in val_lower:
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contact_sucursal_val = b_info["full_name"]
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break
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# Si el contacto tiene un valor de sucursal definido, pero no se parece al de la oportunidad
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if contact_sucursal_val:
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# Normalizar la sucursal del contacto para comparar
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c_suc_clean = contact_sucursal_val.lower()
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for token in ["mp", "-", "859", "0001", "qro", "demo", "plaza"]:
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c_suc_clean = c_suc_clean.replace(token, "")
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c_suc_clean = " ".join(c_suc_clean.split())
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# Si los nombres limpios difieren, hay discrepancia
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if c_suc_clean != opp_branch_clean:
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discrepancies_count += 1
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contact_name = f"{row['first_name'] or ''} {row['last_name'] or ''}".strip()
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print(f"{discrepancies_count:02d}. Oportunidad: {row['opp_name']}")
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print(f" Cliente: {contact_name} (ID: {row['contact_id']})")
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print(f" Ubicación Opp: {opp_branch_info['full_name']} ({opp_loc_id})")
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print(f" Campo Contact: {contact_sucursal_val}")
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print(f" Estado Opp: {row['opp_status'].upper()}")
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print("-" * 110)
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print(f"\nAnálisis finalizado.")
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if missing_schema_locations:
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print(f"Locations sin campo Sucursal resuelto por schema: {len(missing_schema_locations)}")
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if discrepancies_count == 0:
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print("¡Felicidades! No se detectaron discrepancias de sucursal en la base de datos.")
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else:
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print(f"Se encontraron {discrepancies_count} discrepancias de sucursal.")
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print("Se recomienda correr el script 'fix_sucursal_discrepancies.py' para corregir automáticamente.")
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finally:
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conn.close()
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if __name__ == "__main__":
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analyze_discrepancies()
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