mirror of
https://github.com/marcogll/telegram_new_socias.git
synced 2026-01-13 21:25:16 +00:00
feat: Implement multi-database architecture
This commit introduces a three-database architecture to the application, as specified in the `db_logic.md` file. The changes include: - A SQL initialization script (`db/init/init.sql`) to create the `USERS_ALMA`, `vanity_hr`, and `vanity_attendance` databases and their respective tables. - SQLAlchemy models for all tables, organized into separate files within the `models` directory. - Refactoring of the database connection logic in `modules/database.py` to support connections to all three databases. - Creation of a `modules/logger.py` to handle request logging to the `USERS_ALMA` database. - Updates to `docker-compose.yml` to mount the initialization script and build the bot image locally. - Updates to `.env.example` to include the new database environment variables. - Restoration of the data dictionary to `db_tasks.md`.
This commit is contained in:
google-labs-jules[bot]
@@ -1,14 +1,40 @@
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import logging
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import os
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from datetime import datetime
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from sqlalchemy import Column, DateTime, Integer, MetaData, String, create_engine
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from sqlalchemy.ext.declarative import declarative_base
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from sqlalchemy import create_engine
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from sqlalchemy.orm import sessionmaker
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from models.users_alma_models import Base as BaseUsersAlma, User
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from models.vanity_hr_models import Base as BaseVanityHr, DataEmpleadas, Vacaciones, Permisos
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from models.vanity_attendance_models import Base as BaseVanityAttendance, AsistenciaRegistros, HorarioEmpleadas
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import gspread
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from google.oauth2.service_account import Credentials
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# Configuración de logging
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logging.basicConfig(level=logging.INFO, format="%(asctime)s - %(name)s - %(levelname)s - %(message)s")
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# --- DATABASE (MySQL) SETUP ---
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def _build_engine(db_name_env_var):
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user = os.getenv("MYSQL_USER")
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password = os.getenv("MYSQL_PASSWORD")
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db_name = os.getenv(db_name_env_var)
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host = os.getenv("MYSQL_HOST", "db")
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if not all([user, password, db_name]):
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logging.warning(f"Database connection disabled: missing environment variables for {db_name_env_var}.")
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return None
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try:
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db_url = f"mysql+mysqlconnector://{user}:{password}@{host}:3306/{db_name}"
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return create_engine(db_url, pool_pre_ping=True)
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except Exception as exc:
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logging.error(f"Could not create database engine for {db_name}: {exc}")
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return None
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# Create engines for each database
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engine_users_alma = _build_engine("MYSQL_DATABASE_USERS_ALMA")
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engine_vanity_hr = _build_engine("MYSQL_DATABASE_VANITY_HR")
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engine_vanity_attendance = _build_engine("MYSQL_DATABASE_VANITY_ATTENDANCE")
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# Create sessions for each database
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SessionUsersAlma = sessionmaker(autocommit=False, autoflush=False, bind=engine_users_alma) if engine_users_alma else None
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SessionVanityHr = sessionmaker(autocommit=False, autoflush=False, bind=engine_vanity_hr) if engine_vanity_hr else None
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SessionVanityAttendance = sessionmaker(autocommit=False, autoflush=False, bind=engine_vanity_attendance) if engine_vanity_attendance else None
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# --- GOOGLE SHEETS SETUP ---
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GSHEET_URL = os.getenv("GOOGLE_SHEET_URL")
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@@ -16,15 +42,14 @@ GOOGLE_CREDENTIALS_FILE = os.getenv("GOOGLE_CREDENTIALS_FILE", "google_credentia
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SHEET_COLUMN_INDEX = 40 # AN is the 40th column
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def get_gsheet_client():
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"""Retorna un cliente de gspread autenticado o None si falla."""
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"""Returns an authenticated gspread client or None if it fails."""
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if not GSHEET_URL:
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logging.warning("GOOGLE_SHEET_URL no está configurada. La verificación de duplicados está deshabilitada.")
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logging.warning("GOOGLE_SHEET_URL is not configured. Duplicate checking is disabled.")
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return None
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creds = None
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scopes = ["https://www.googleapis.com/auth/spreadsheets.readonly"]
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# Prioridad 1: Cargar desde variables de entorno
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gsa_creds_dict = {
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"type": os.getenv("GSA_TYPE"),
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"project_id": os.getenv("GSA_PROJECT_ID"),
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@@ -41,139 +66,39 @@ def get_gsheet_client():
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if all(gsa_creds_dict.values()):
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try:
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creds = Credentials.from_service_account_info(gsa_creds_dict, scopes=scopes)
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logging.info("Autenticando con Google Sheets usando variables de entorno.")
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except Exception as e:
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logging.error(f"Error al procesar credenciales de entorno de Google: {e}")
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logging.error(f"Error processing Google credentials from environment: {e}")
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return None
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# Prioridad 2: Cargar desde archivo JSON
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elif os.path.exists(GOOGLE_CREDENTIALS_FILE):
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try:
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creds = Credentials.from_service_account_file(GOOGLE_CREDENTIALS_FILE, scopes=scopes)
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logging.info(f"Autenticando con Google Sheets usando el archivo '{GOOGLE_CREDENTIALS_FILE}'.")
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except Exception as e:
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logging.error(f"Error al procesar el archivo de credenciales '{GOOGLE_CREDENTIALS_FILE}': {e}")
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logging.error(f"Error processing credentials file '{GOOGLE_CREDENTIALS_FILE}': {e}")
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return None
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else:
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logging.warning("No se encontraron credenciales de Google (ni por variables de entorno ni por archivo). La verificación de duplicados está deshabilitada.")
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logging.warning("Google credentials not found (neither environment variables nor file). Duplicate checking is disabled.")
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return None
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try:
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client = gspread.authorize(creds)
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return client
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return gspread.authorize(creds)
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except Exception as e:
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logging.error(f"Error al autorizar cliente de gspread: {e}")
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logging.error(f"Error authorizing gspread client: {e}")
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return None
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def chat_id_exists(chat_id: int) -> bool:
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"""Verifica si un chat_id de Telegram ya existe en la columna AN de la hoja de cálculo."""
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"""Checks if a Telegram chat_id already exists in the Google Sheet."""
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client = get_gsheet_client()
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if not client:
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return False # Si no hay cliente, no podemos verificar, así que asumimos que no existe.
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return False
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try:
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spreadsheet = client.open_by_url(GSHEET_URL)
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worksheet = spreadsheet.get_worksheet(0) # Primera hoja
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# Obtener todos los valores de la columna AN (índice 40)
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worksheet = spreadsheet.get_worksheet(0)
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chat_ids_in_sheet = worksheet.col_values(SHEET_COLUMN_INDEX)
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# El ID de chat puede venir como número o texto, así que comparamos como string
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return str(chat_id) in chat_ids_in_sheet
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except gspread.exceptions.SpreadsheetNotFound:
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logging.error(f"No se pudo encontrar la hoja de cálculo en la URL proporcionada.")
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logging.error("Could not find the spreadsheet at the provided URL.")
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return False
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except Exception as e:
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logging.error(f"Error al leer la hoja de cálculo: {e}")
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logging.error(f"Error reading the spreadsheet: {e}")
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return False
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# --- DATABASE (MySQL) SETUP ---
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# Base para los modelos declarativos
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Base = declarative_base()
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# Clase que mapea a la tabla de logs
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class RequestLog(Base):
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__tablename__ = 'request_logs'
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id = Column(Integer, primary_key=True)
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telegram_id = Column(String(50))
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username = Column(String(100))
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command = Column(String(100))
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message = Column(String(500))
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created_at = Column(DateTime, default=datetime.utcnow)
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def _build_engine():
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"""Crea un engine de SQLAlchemy si hay variables de entorno suficientes."""
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user = os.getenv("MYSQL_USER")
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password = os.getenv("MYSQL_PASSWORD")
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database = os.getenv("MYSQL_DATABASE")
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host = os.getenv("MYSQL_HOST") or "db" # Permitimos override para uso local
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if not all([user, password, database]):
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logging.warning("DB logging deshabilitado: faltan MYSQL_USER/MYSQL_PASSWORD/MYSQL_DATABASE.")
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return None
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try:
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db_url = f"mysql+mysqlconnector://{user}:{password}@{host}:3306/{database}"
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return create_engine(db_url, pool_pre_ping=True)
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except Exception as exc:
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logging.error(f"No se pudo crear el engine de base de datos: {exc}")
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return None
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def _disable_db_logging(reason: str):
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"""Deshabilita el logging a DB después de un error para evitar spam."""
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global engine, SessionLocal
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engine = None
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SessionLocal = None
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logging.warning(f"DB logging deshabilitado: {reason}")
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# Crear el engine y sesión si es posible
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engine = _build_engine()
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metadata = MetaData() if engine else None
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SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=engine) if engine else None
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# Función para inicializar la base de datos
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def init_db():
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global engine, SessionLocal
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if not engine:
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return
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try:
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logging.info("Inicializando la base de datos y creando tablas si no existen...")
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Base.metadata.create_all(bind=engine)
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logging.info("Tablas verificadas/creadas correctamente.")
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except Exception as e:
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logging.error(f"Error al inicializar la base de datos: {e}")
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_disable_db_logging("no se pudo inicializar la base de datos (se omitirán logs).")
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# No propagamos para que el bot pueda seguir levantando aunque no haya DB
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# Función para registrar una solicitud en la base de datos
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def log_request(telegram_id, username, command, message):
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if not SessionLocal:
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logging.debug("Log de DB omitido (DB no configurada).")
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return
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try:
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db_session = SessionLocal()
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except Exception as exc:
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logging.error(f"No se pudo crear sesión DB, se deshabilita el log: {exc}")
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_disable_db_logging("no se pudo abrir sesión")
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return
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try:
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log_entry = RequestLog(
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telegram_id=str(telegram_id),
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username=username,
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command=command,
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message=message
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)
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db_session.add(log_entry)
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db_session.commit()
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logging.info(f"Log guardado: {command} de {username}")
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except Exception as e:
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logging.error(f"Error al guardar el log: {e}")
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db_session.rollback()
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finally:
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db_session.close()
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# Inicializar la base de datos al arrancar el módulo
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init_db()
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