#!.venv/bin/python """ Orchestratore dei worker che lanciano le elaborazioni """ # Import necessary libraries import asyncio import logging # Import custom modules for configuration and database connection from utils.config import loader_matlab_elab as setting from utils.connect.send_email import send_error_email from utils.csv.loaders import get_next_csv_atomic from utils.database import WorkflowFlags from utils.database.action_query import check_flag_elab, get_tool_info from utils.database.loader_action import unlock, update_status from utils.general import read_error_lines_from_logs from utils.orchestrator_utils import run_orchestrator, shutdown_event, worker_context # Initialize the logger for this module logger = logging.getLogger() # Delay tra un processamento CSV e il successivo (in secondi) ELAB_PROCESSING_DELAY = 0.2 # Tempo di attesa se non ci sono record da elaborare NO_RECORD_SLEEP = 60 async def worker(worker_id: int, cfg: object, pool: object) -> None: """Esegue il ciclo di lavoro per l'elaborazione dei dati caricati. Il worker preleva un record dal database che indica dati pronti per l'elaborazione, esegue un comando Matlab associato e attende prima di iniziare un nuovo ciclo. Supporta graceful shutdown controllando il shutdown_event tra le iterazioni. Args: worker_id (int): L'ID univoco del worker. cfg (object): L'oggetto di configurazione. pool (object): Il pool di connessioni al database. """ # Imposta il context per questo worker worker_context.set(f"W{worker_id:02d}") debug_mode = logging.getLogger().getEffectiveLevel() == logging.DEBUG logger.info("Avviato") try: while not shutdown_event.is_set(): try: logger.info("Inizio elaborazione") if not await check_flag_elab(pool): record = await get_next_csv_atomic(pool, cfg.dbrectable, WorkflowFlags.DATA_LOADED, WorkflowFlags.DATA_ELABORATED) if record: rec_id, _, tool_type, unit_name, tool_name = [x.lower().replace(" ", "_") if isinstance(x, str) else x for x in record] if tool_type.lower() != "gd": # i tool GD non devono essere elaborati ??? tool_elab_info = await get_tool_info(WorkflowFlags.DATA_ELABORATED, unit_name.upper(), tool_name.upper(), pool) if tool_elab_info: if tool_elab_info["statustools"].lower() in cfg.elab_status: logger.info("Elaborazione ID %s per %s %s", rec_id, unit_name, tool_name) await update_status(cfg, rec_id, WorkflowFlags.START_ELAB, pool) matlab_cmd = f"timeout {cfg.matlab_timeout} ./run_{tool_elab_info['matcall']}.sh \ {cfg.matlab_runtime} {unit_name.upper()} {tool_name.upper()}" proc = await asyncio.create_subprocess_shell( matlab_cmd, cwd=cfg.matlab_func_path, stdout=asyncio.subprocess.PIPE, stderr=asyncio.subprocess.PIPE ) stdout, stderr = await proc.communicate() if proc.returncode != 0: logger.error("Errore durante l'elaborazione") logger.error(stderr.decode().strip()) if proc.returncode == 124: error_type = f"Matlab elab excessive duration: killed after {cfg.matlab_timeout} seconds." else: error_type = f"Matlab elab failed: {proc.returncode}." # da verificare i log dove prenderli # with open(f"{cfg.matlab_error_path}{unit_name}{tool_name}_output_error.txt", "w") as f: # f.write(stderr.decode().strip()) # errors = [line for line in stderr.decode().strip() if line.startswith("Error")] # warnings = [line for line in stderr.decode().strip() if not line.startswith("Error")] errors, warnings = await read_error_lines_from_logs( cfg.matlab_error_path, f"_{unit_name}_{tool_name}*_*_output_error.txt" ) await send_error_email( unit_name.upper(), tool_name.upper(), tool_elab_info["matcall"], error_type, errors, warnings ) else: logger.info(stdout.decode().strip()) await update_status(cfg, rec_id, WorkflowFlags.DATA_ELABORATED, pool) await unlock(cfg, rec_id, pool) await asyncio.sleep(ELAB_PROCESSING_DELAY) else: logger.info( "ID %s %s - %s %s: MatLab calc by-passed.", rec_id, unit_name, tool_name, tool_elab_info["statustools"] ) await update_status(cfg, rec_id, WorkflowFlags.DATA_ELABORATED, pool) await update_status(cfg, rec_id, WorkflowFlags.DUMMY_ELABORATED, pool) await unlock(cfg, rec_id, pool) else: await update_status(cfg, rec_id, WorkflowFlags.DATA_ELABORATED, pool) await update_status(cfg, rec_id, WorkflowFlags.DUMMY_ELABORATED, pool) await unlock(cfg, rec_id, pool) else: logger.info("Nessun record disponibile") await asyncio.sleep(NO_RECORD_SLEEP) else: logger.info("Flag fermo elaborazione attivato") await asyncio.sleep(NO_RECORD_SLEEP) except asyncio.CancelledError: logger.info("Worker cancellato. Uscita in corso...") raise except Exception as e: # pylint: disable=broad-except logger.error("Errore durante l'esecuzione: %s", e, exc_info=debug_mode) await asyncio.sleep(1) except asyncio.CancelledError: logger.info("Worker terminato per shutdown graceful") finally: logger.info("Worker terminato") async def main(): """Funzione principale che avvia l'elab_orchestrator.""" await run_orchestrator(setting.Config, worker) if __name__ == "__main__": asyncio.run(main())