Mpall ((better)) May 2026

args = parser.parse_args()

formatter = logging.Formatter( '%(asctime)s - %(levelname)s - %(message)s', datefmt='%Y-%m-%d %H:%M:%S' ) # Console handler console = logging.StreamHandler(sys.stdout) console.setLevel(logging.DEBUG if verbose else logging.INFO) console.setFormatter(formatter) self.logger.addHandler(console) # File handler (if specified) if log_file: file_handler = logging.FileHandler(log_file) file_handler.setLevel(logging.DEBUG) file_handler.setFormatter(formatter) self.logger.addHandler(file_handler) args = parser

@staticmethod def run(cmd: List[str], timeout: int, env: Optional[Dict] = None) -> Tuple[int, str, str]: """Run command, return (exit_code, stdout, stderr).""" try: result = subprocess.run( cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE, timeout=timeout, env=env if env else os.environ.copy(), text=True ) return result.returncode, result.stdout, result.stderr except subprocess.TimeoutExpired: return -1, "", f"Command timed out after timeout seconds" except Exception as e: return -2, "", str(e) def worker(task_id: int, args_template: List[str], replacements: Dict[str, str], timeout: int, retries: int, env: Dict) -> TaskResult: """ Worker function executed in a separate process. Builds command by replacing placeholders and runs it. """ start_time = time.time() Feature: mpall Purpose Execute a command across multiple

I'll produce a complete feature called (Multi-Process All-in-One Launcher) – a command-line tool to run commands across multiple processes, with logging, retries, timeouts, and output aggregation. Feature: mpall Purpose Execute a command across multiple parallel processes (e.g., for batch processing, stress testing, or parallel data transformation) with unified output handling and error recovery. Files Structure mpall/ ├── mpall.py # Main CLI implementation ├── README.md # Documentation └── tests/ # Unit tests mpall.py (Complete Implementation) #!/usr/bin/env python3 """ mpall - Multi-Process All-in-One Launcher Run a command across multiple parallel processes with logging, retries, timeouts, and aggregated output. """ for batch processing

# Execute with retries for attempt in range(retries + 1): exit_code, stdout, stderr = CommandExecutor.run(cmd, timeout, env) if exit_code == 0: return TaskResult( task_id=task_id, args=tuple(replacements.items()), success=True, stdout=stdout.strip(), stderr=stderr.strip(), exit_code=exit_code, duration=time.time() - start_time, retries=attempt ) if attempt < retries: time.sleep(1) # Wait before retry

## Quick Test