class_docstr: Base class to inherit for concrete executors such as Celery, Kubernetes, Local, Sequential, etc.
  
  :param parallelism: how many jobs should run at one time. Set to ``0`` for infinity.
class_docstr_tok: ["Base","class","to","inherit","for","concrete","executors","such","as","Celery",",","Kubernetes",",","Local",",","Sequential",",","etc",".",":","param","parallelism",":","how","many","jobs","should","run","at","one","time",".","Set","to","``","0","``","for","infinity","."]
docstr: Queues command to task.
docstr_tok: ["Queues","command","to","task","."]
code: def queue_command(
      self,
      task_instance: TaskInstance,
      command: CommandType,
      priority: int = 1,
      queue: str | None = None,
  ):
      """Queues command to task."""
      if task_instance.key not in self.queued_tasks:
          self.log.info("Adding to queue: %s", command)
          self.queued_tasks[task_instance.key] = (
              command,
              priority,
              queue,
              task_instance,
          )
      else:
          self.log.error("could not queue task %s", task_instance.key)
  
imports: from __future__ import annotations
  import logging
  import sys
  import warnings
  from collections import defaultdict
  from dataclasses import dataclass, field
  from typing import TYPE_CHECKING, Any, List, Optional, Sequence, Tuple
  import pendulum
  from airflow.cli.cli_config import DefaultHelpParser
  from airflow.configuration import conf
  from airflow.exceptions import RemovedInAirflow3Warning
  from airflow.stats import Stats
  from airflow.utils.log.logging_mixin import LoggingMixin
  from airflow.utils.state import TaskInstanceState
label_desc: Use image node_id 4 for calling the BaseExecutor obj's underlying member method code with example usage: obj.queue_command(task_instance, command, priority, queue) without return types