class_docstr: Runs job while capturing environment and logs results.
      
class_docstr_tok: ["Runs","job","while","capturing","environment","and","logs","results","."]
code: def __init__(self, queue, args):
      self.config = args.config
  
      if args.guest:
          self.config["database"]["guest"] = True
  
      self.task_queue = queue
      self.logger = logs.get_logger("LocalExecutor")
      self.logger.setLevel(
          model.parse_verbosity(self.config.get("verbose", None))
      )
      self.logger.debug("Config: ")
      self.logger.debug(self.config)
  
imports: import os
  import sys
  import subprocess
  import argparse
  import json
  import psutil
  import time
  import six
  import signal
  import pdb
  from apscheduler.schedulers.background import BackgroundScheduler
  from studio import fs_tracker, model
  from studio.util import logs
  from studio.queues.local_queue import LocalQueue
  from studio.util.gpu_util import get_available_gpus, get_gpu_mapping, get_gpus_summary
  from studio.artifacts.artifact import Artifact
  from studio.experiments.experiment import Experiment
  from studio.util.util import sixdecode, str2duration, retry, parse_verbosity, check_for_kb_interrupt
label_desc: Use image node_id 1 to create a new LocalExecutor object from inherited base classes: object with example: obj = LocalExecutor(queue, args)