529 lines
20 KiB
Python
529 lines
20 KiB
Python
"""
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Tareas Celery para importación CSV de Clases de Materiales.
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Flujo: scan_file (validación) → insert_valid_rows (commit).
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"""
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import os
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import base64
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import csv
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import json
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import logging
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import re
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import unicodedata
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from typing import Dict, Any, Optional, List, Set
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from core.celery_app import celery_app
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from core.database import CoreSessionLocal
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from core.paths import layout_path
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from .template_config import row_from_template
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logger = logging.getLogger(__name__)
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CLS_IMPORT_FILE_PREFIX = "cls_import_file:"
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CLS_IMPORT_META_PREFIX = "cls_import_meta:"
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CLS_IMPORT_ERROR_LINES_PREFIX = "cls_import_error_lines:"
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CLS_IMPORT_REDIS_TTL = 3600
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def _get_redis():
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import redis
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url = os.getenv("VALKEY_URL", os.getenv("REDIS_URL", "redis://valkey:6379/0"))
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return redis.Redis.from_url(url, decode_responses=False)
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def _worker_upload_dir() -> str:
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return layout_path("imports", "temp")
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def _ensure_worker_has_file_from_redis(job_id: str) -> Optional[str]:
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r = _get_redis()
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data = r.get(f"{CLS_IMPORT_FILE_PREFIX}{job_id}")
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if not data:
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return None
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try:
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raw = base64.b64decode(data)
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except Exception as e:
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logger.warning(f"Classes import: failed to decode file from Redis: {e}")
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return None
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upload_dir = _worker_upload_dir()
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os.makedirs(upload_dir, exist_ok=True)
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file_path = os.path.join(upload_dir, f"cls_{job_id}.csv")
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with open(file_path, "wb") as f:
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f.write(raw)
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return file_path
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def _ensure_worker_has_meta_from_redis(job_id: str, file_path: str) -> bool:
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r = _get_redis()
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data = r.get(f"{CLS_IMPORT_META_PREFIX}{job_id}")
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if not data:
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return False
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try:
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meta = json.loads(data.decode("utf-8"))
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except Exception as e:
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logger.warning(f"Classes import: failed to decode meta from Redis: {e}")
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return False
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meta_path = file_path.replace(".csv", ".meta.json")
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with open(meta_path, "w", encoding="utf-8") as f:
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json.dump(meta, f)
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return True
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def _delete_import_from_redis(job_id: str) -> None:
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try:
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r = _get_redis()
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r.delete(
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f"{CLS_IMPORT_FILE_PREFIX}{job_id}",
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f"{CLS_IMPORT_META_PREFIX}{job_id}",
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f"{CLS_IMPORT_ERROR_LINES_PREFIX}{job_id}",
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)
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except Exception as e:
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logger.warning(f"Classes import: failed to delete Redis keys: {e}")
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def normalize_header(name: Optional[str]) -> str:
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if not name:
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return ""
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name = unicodedata.normalize("NFKD", str(name)).upper()
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name = "".join(ch for ch in name if not unicodedata.combining(ch))
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name = re.sub(r"[^A-Z0-9]+", " ", name)
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return re.sub(r"\s+", " ", name).strip()
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def _validate_row_class(
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row: Dict[str, Any],
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line_num: int,
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valid_material_keys: Optional[Set[str]] = None,
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valid_uom_codes: Optional[Set[str]] = None,
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) -> Optional[Dict[str, Any]]:
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class_code = (row.get("CLASE") or "").strip()
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if not class_code:
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return {"line": line_num, "col": "CLASE", "msg": "Requerido"}
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if len(class_code) > 8:
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return {"line": line_num, "col": "CLASE", "msg": "Máximo 8 caracteres"}
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desc_es = (row.get("DESCRIPCIONE") or "").strip()
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if desc_es and len(desc_es) > 500:
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return {"line": line_num, "col": "DESCRIPCIONE", "msg": "Máximo 500 caracteres"}
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desc_en = (row.get("DESCRIPCIONI") or "").strip()
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if desc_en and len(desc_en) > 500:
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return {"line": line_num, "col": "DESCRIPCIONI", "msg": "Máximo 500 caracteres"}
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material_key = (row.get("CLAVEMAT") or "").strip()
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if material_key:
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if len(material_key) > 10:
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return {"line": line_num, "col": "CLAVEMAT", "msg": "Máximo 10 caracteres"}
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if valid_material_keys is not None and material_key not in valid_material_keys:
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return {"line": line_num, "col": "CLAVEMAT", "msg": "Tipo de material no existe"}
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uom = (row.get("UNIMED") or "").strip()
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if uom:
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if len(uom) > 5:
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return {"line": line_num, "col": "UNIMED", "msg": "Máximo 5 caracteres"}
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if valid_uom_codes is not None and uom not in valid_uom_codes:
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return {"line": line_num, "col": "UNIMED", "msg": "Unidad de medida no existe"}
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fraction = (row.get("FRACCION") or "").strip()
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if fraction and len(fraction) > 20:
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return {"line": line_num, "col": "FRACCION", "msg": "Máximo 20 caracteres"}
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us_fraction = (row.get("FRACCIONAME") or "").strip()
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if us_fraction and len(us_fraction) > 16:
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return {"line": line_num, "col": "FRACCIONAME", "msg": "Máximo 16 caracteres"}
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sub_key = (row.get("CLAVESUB") or "").strip()
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if sub_key and len(sub_key) > 5:
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return {"line": line_num, "col": "CLAVESUB", "msg": "Máximo 5 caracteres"}
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iva_exempt = (row.get("FRACCIONEXENTAIVA") or "").strip()
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if iva_exempt and len(iva_exempt) > 4:
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return {"line": line_num, "col": "FRACCIONEXENTAIVA", "msg": "Máximo 4 caracteres"}
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rev_fisica = row.get("REVFISICA")
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if rev_fisica is not None and rev_fisica != "":
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try:
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v = int(rev_fisica)
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if v < -32768 or v > 32767:
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return {"line": line_num, "col": "REVFISICA", "msg": "Valor fuera de rango"}
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except (ValueError, TypeError):
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return {"line": line_num, "col": "REVFISICA", "msg": "Debe ser número entero"}
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return None
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@celery_app.task(bind=True)
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def scan_file(self, job_id: str, config: str = None):
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logger.info(f"Classes import: starting scan for job {job_id}")
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file_path = _ensure_worker_has_file_from_redis(job_id)
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if not file_path:
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return {"status": "failed", "error": "Archivo no encontrado (expirado o no subido). Sube de nuevo."}
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_ensure_worker_has_meta_from_redis(job_id, file_path)
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error_dir = layout_path("imports", "errors")
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os.makedirs(error_dir, exist_ok=True)
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error_path = os.path.join(error_dir, f"cls_{job_id}.jsonl")
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total_rows = 0
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try:
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with open(file_path, "r", encoding="utf-8-sig") as f:
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total_rows = sum(1 for _ in f) - 1
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except Exception as e:
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return {"status": "failed", "error": str(e)}
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meta_path = file_path.replace(".csv", ".meta.json")
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meta = {}
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if os.path.exists(meta_path):
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try:
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with open(meta_path, "r", encoding="utf-8") as f:
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meta = json.load(f) or {}
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except Exception as e:
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logger.warning(f"Classes import: failed to read meta: {e}")
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tenant_id = meta.get("tenant_id")
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company_id = meta.get("company_id")
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if not tenant_id or not company_id:
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return {"status": "failed", "error": "Falta contexto (tenant/company)"}
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valid_material_keys: Set[str] = set()
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valid_uom_codes: Set[str] = set()
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try:
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with CoreSessionLocal() as session:
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from api.v1.modules.public.reference_data.material_types.models import MaterialType
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from api.v1.modules.a76.general_catalogs.units_of_measure.models import UnitOfMeasure
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for m in session.query(MaterialType.key).all():
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valid_material_keys.add(m[0])
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for u in (
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session.query(UnitOfMeasure.code)
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.filter(
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UnitOfMeasure.tenant_id == tenant_id,
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UnitOfMeasure.company_id == company_id,
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)
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.all()
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):
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valid_uom_codes.add(u[0])
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except Exception as e:
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logger.warning(f"Classes import: could not load FK sets: {e}")
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error_count = 0
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processed_rows = 0
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errors_detail: List[Dict[str, Any]] = []
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try:
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with open(file_path, "r", encoding="utf-8-sig") as f_in, open(
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error_path, "w", encoding="utf-8"
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) as f_err:
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sample = f_in.read(2048)
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f_in.seek(0)
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try:
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dialect = csv.Sniffer().sniff(sample, delimiters=",;\t")
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except Exception:
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dialect = "excel"
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reader = csv.DictReader(f_in, dialect=dialect)
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for i, row in enumerate(reader, start=1):
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if i % 500 == 0:
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self.update_state(
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state="PROGRESS",
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meta={"current": i, "total": total_rows, "errors": error_count},
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)
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row_norm = row_from_template(row, normalize_header)
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err = _validate_row_class(
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row_norm, i,
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valid_material_keys=valid_material_keys,
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valid_uom_codes=valid_uom_codes,
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)
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if err:
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error_count += 1
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f_err.write(json.dumps(err) + "\n")
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if len(errors_detail) < 500:
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errors_detail.append(
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{"line": err["line"], "col": err.get("col", ""), "msg": err.get("msg", "")}
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)
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processed_rows += 1
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except Exception as e:
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logger.error(f"Classes import scan failed: {e}")
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return {"status": "failed", "error": str(e)}
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error_lines_list = []
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try:
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if os.path.exists(error_path):
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with open(error_path, "r", encoding="utf-8") as f:
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for line in f:
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try:
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err = json.loads(line)
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if "line" in err:
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error_lines_list.append(err["line"])
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except Exception:
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pass
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if error_lines_list:
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r = _get_redis()
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r.set(
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f"{CLS_IMPORT_ERROR_LINES_PREFIX}{job_id}",
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json.dumps(error_lines_list).encode("utf-8"),
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ex=CLS_IMPORT_REDIS_TTL,
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)
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except Exception as e:
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logger.warning(f"Classes import: failed to store error lines in Redis: {e}")
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return {
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"status": "waiting_confirmation",
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"job_id": job_id,
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"total_rows": processed_rows,
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"error_count": error_count,
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"valid_rows": processed_rows - error_count,
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"errors": errors_detail,
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}
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def _str_or_none(val: Any, max_len: Optional[int] = None) -> Optional[str]:
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if val is None:
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return None
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s = str(val).strip()
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if not s:
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return None
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if max_len and len(s) > max_len:
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return s[:max_len]
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return s
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def _int_or_none(val: Any) -> Optional[int]:
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if val is None or val == "":
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return None
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try:
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return int(val)
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except (ValueError, TypeError):
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return None
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@celery_app.task(bind=True)
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def insert_valid_rows(self, job_id: str):
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logger.info(f"Classes import: starting commit for job {job_id}")
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file_path = _ensure_worker_has_file_from_redis(job_id)
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if not file_path:
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alt_path = os.path.join(_worker_upload_dir(), f"cls_{job_id}.csv")
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if not os.path.exists(alt_path):
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return {
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"status": "failed",
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"error": "Archivo no encontrado (expirado). Sube y confirma de nuevo.",
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}
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file_path = alt_path
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else:
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_ensure_worker_has_meta_from_redis(job_id, file_path)
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error_dir = layout_path("imports", "errors")
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error_path = os.path.join(error_dir, f"cls_{job_id}.jsonl")
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error_lines = set()
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try:
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r = _get_redis()
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raw = r.get(f"{CLS_IMPORT_ERROR_LINES_PREFIX}{job_id}")
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if raw:
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error_lines = set(json.loads(raw.decode("utf-8")))
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except Exception as e:
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logger.debug(f"Classes import: could not load error lines from Redis: {e}")
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if not error_lines and os.path.exists(error_path):
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with open(error_path, "r", encoding="utf-8") as f:
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for line in f:
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try:
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err = json.loads(line)
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error_lines.add(err["line"])
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except Exception:
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pass
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meta_path = file_path.replace(".csv", ".meta.json")
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tenant_id = None
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company_id = None
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meta = {}
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if os.path.exists(meta_path):
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try:
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with open(meta_path, "r", encoding="utf-8") as f:
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meta = json.load(f) or {}
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tenant_id = meta.get("tenant_id")
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company_id = meta.get("company_id")
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except Exception:
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pass
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if not tenant_id or not company_id:
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return {"status": "failed", "error": "Falta contexto (tenant/company)"}
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from api.v1.modules.a76.classes.models import Class
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valid_material_keys: Set[str] = set()
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valid_uom_codes: Set[str] = set()
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try:
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with CoreSessionLocal() as session:
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from api.v1.modules.public.reference_data.material_types.models import MaterialType
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from api.v1.modules.a76.general_catalogs.units_of_measure.models import UnitOfMeasure
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for m in session.query(MaterialType.key).all():
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valid_material_keys.add(m[0])
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for u in (
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session.query(UnitOfMeasure.code)
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.filter(
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UnitOfMeasure.tenant_id == tenant_id,
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UnitOfMeasure.company_id == company_id,
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)
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.all()
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):
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valid_uom_codes.add(u[0])
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except Exception as e:
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logger.warning(f"Classes import: could not load FK sets: {e}")
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inserted_count = 0
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skipped_invalid = 0
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skipped_details: List[Dict[str, Any]] = []
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response = None
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try:
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with CoreSessionLocal() as session:
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existing_by_code: Dict[str, Class] = {}
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for c in (
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session.query(Class)
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.filter(
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Class.tenant_id == tenant_id,
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Class.company_id == company_id,
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)
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.all()
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):
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existing_by_code[c.class_code] = c
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with open(file_path, "r", encoding="utf-8-sig") as f:
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sample = f.read(2048)
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f.seek(0)
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try:
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dialect = csv.Sniffer().sniff(sample, delimiters=",;\t")
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except Exception:
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dialect = "excel"
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reader = csv.DictReader(f, dialect=dialect)
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for i, row in enumerate(reader, start=1):
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if i in error_lines:
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continue
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row_norm = row_from_template(row, normalize_header)
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err = _validate_row_class(
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row_norm, i,
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valid_material_keys=valid_material_keys,
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valid_uom_codes=valid_uom_codes,
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)
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if err:
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skipped_invalid += 1
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skipped_details.append(
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{"line": i, "reason": f"{err.get('col', '')}: {err.get('msg', '')}"}
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)
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continue
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class_code = _str_or_none(row_norm.get("CLASE"), 8)
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if not class_code:
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skipped_invalid += 1
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continue
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existing = existing_by_code.get(class_code)
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desc_es = _str_or_none(row_norm.get("DESCRIPCIONE"), 500)
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desc_en = _str_or_none(row_norm.get("DESCRIPCIONI"), 500)
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material_key = _str_or_none(row_norm.get("CLAVEMAT"), 10)
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if material_key and material_key not in valid_material_keys:
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material_key = None
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unit_of_measure = _str_or_none(row_norm.get("UNIMED"), 5)
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if unit_of_measure and unit_of_measure not in valid_uom_codes:
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unit_of_measure = None
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fraction = _str_or_none(row_norm.get("FRACCION"), 20)
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us_fraction = _str_or_none(row_norm.get("FRACCIONAME"), 16)
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sub_key = _str_or_none(row_norm.get("CLAVESUB"), 5)
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physical_review = _int_or_none(row_norm.get("REVFISICA"))
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iva_exempt_fraction = _str_or_none(row_norm.get("FRACCIONEXENTAIVA"), 4)
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if existing:
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existing.description_es = desc_es
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existing.description_en = desc_en
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existing.material_key = material_key
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existing.unit_of_measure = unit_of_measure
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existing.fraction = fraction
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existing.us_fraction = us_fraction
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existing.sub_key = sub_key
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existing.physical_review = physical_review
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existing.iva_exempt_fraction = iva_exempt_fraction
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session.add(existing)
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inserted_count += 1
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else:
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new_class = Class(
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tenant_id=tenant_id,
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company_id=company_id,
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class_code=class_code,
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description_es=desc_es,
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description_en=desc_en,
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material_key=material_key,
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unit_of_measure=unit_of_measure,
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fraction=fraction,
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us_fraction=us_fraction,
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sub_key=sub_key,
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physical_review=physical_review,
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iva_exempt_fraction=iva_exempt_fraction,
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)
|
|
session.add(new_class)
|
|
existing_by_code[class_code] = new_class
|
|
inserted_count += 1
|
|
|
|
try:
|
|
session.commit()
|
|
except Exception as db_err:
|
|
session.rollback()
|
|
logger.error(f"Classes import DB error: {db_err}")
|
|
return {"status": "failed", "error": str(db_err)}
|
|
|
|
total_skipped = skipped_invalid
|
|
if inserted_count == 0 and total_skipped > 0:
|
|
response = {
|
|
"status": "warning",
|
|
"inserted": 0,
|
|
"skipped_invalid": skipped_invalid,
|
|
"skipped_missing_fk": 0,
|
|
"skipped_details": skipped_details,
|
|
"message": f"No se insertaron registros. {total_skipped} rechazados.",
|
|
}
|
|
elif inserted_count == 0:
|
|
response = {
|
|
"status": "failed",
|
|
"error": "No hay registros válidos en el archivo CSV",
|
|
"inserted": 0,
|
|
"skipped_invalid": skipped_invalid,
|
|
"skipped_missing_fk": 0,
|
|
"skipped_details": skipped_details,
|
|
}
|
|
else:
|
|
response = {
|
|
"status": "finished",
|
|
"inserted": inserted_count,
|
|
"skipped_invalid": skipped_invalid,
|
|
"skipped_missing_fk": 0,
|
|
"skipped_details": skipped_details,
|
|
}
|
|
|
|
except Exception as e:
|
|
logger.error(f"Classes import task failed: {e}")
|
|
import traceback
|
|
logger.error(traceback.format_exc())
|
|
return {"status": "failed", "error": str(e)}
|
|
|
|
try:
|
|
if file_path and os.path.exists(file_path):
|
|
os.remove(file_path)
|
|
if os.path.exists(error_path):
|
|
os.remove(error_path)
|
|
if os.path.exists(meta_path):
|
|
os.remove(meta_path)
|
|
_delete_import_from_redis(job_id)
|
|
except Exception as cleanup_err:
|
|
logger.warning(f"Classes import cleanup failed: {cleanup_err}")
|
|
|
|
if response is None:
|
|
response = {
|
|
"status": "failed",
|
|
"error": "Error inesperado",
|
|
"inserted": 0,
|
|
"skipped_invalid": skipped_invalid,
|
|
"skipped_missing_fk": 0,
|
|
"skipped_details": skipped_details,
|
|
}
|
|
return response
|