class_docstr: Provide python APIs for job submission and management.
  
  It does not provide persistence, all info will be lost if the cluster
  goes down.
docstr: Request a job to exit, fire and forget.
  
  Returns whether or not the job was running.
docstr_tok: ["Request","a","job","to","exit",",","fire","and","forget",".","Returns","whether","or","not","the","job","was","running","."]
code: def stop_job(self, job_id) -> bool:
      """Request a job to exit, fire and forget.
  
      Returns whether or not the job was running.
      """
      job_supervisor_actor = self._get_actor_for_job(job_id)
      if job_supervisor_actor is not None:
          # Actor is still alive, signal it to stop the driver, fire and
          # forget
          job_supervisor_actor.stop.remote()
          return True
      else:
          return False
  
imports: import asyncio
  import copy
  import json
  import logging
  import os
  import psutil
  import random
  import signal
  import string
  import subprocess
  import sys
  import time
  import traceback
  from asyncio.tasks import FIRST_COMPLETED
  from collections import deque
  from typing import Any, Dict, Iterator, List, Optional, Tuple, Union
  from ray.util.scheduling_strategies import NodeAffinitySchedulingStrategy, SchedulingStrategyT
  import ray
  from ray._private.gcs_utils import GcsAioClient
  from ray._private.utils import run_background_task
  import ray._private.ray_constants
  from ray._private.runtime_env.constants import RAY_JOB_CONFIG_JSON_ENV_VAR
  from ray.actor import ActorHandle
  from ray.dashboard.consts import RAY_JOB_ALLOW_DRIVER_ON_WORKER_NODES_ENV_VAR, DEFAULT_JOB_START_TIMEOUT_SECONDS, RAY_JOB_START_TIMEOUT_SECONDS_ENV_VAR
  from ray.dashboard.modules.job.common import JOB_ID_METADATA_KEY, JOB_NAME_METADATA_KEY, JOB_ACTOR_NAME_TEMPLATE, JOB_LOGS_PATH_TEMPLATE, SUPERVISOR_ACTOR_RAY_NAMESPACE, JobInfo, JobInfoStorageClient
  from ray.dashboard.modules.job.utils import file_tail_iterator
  from ray.exceptions import ActorUnschedulableError, RuntimeEnvSetupError
  from ray.job_submission import JobStatus
  from ray._private.event.event_logger import get_event_logger
  from ray.core.generated.event_pb2 import Event
label_desc: Use image node_id 5 for calling the JobManager obj's underlying member method code with example usage: obj.stop_job(job_id) and returns: True, False