class_docstr: A SageMakerClient that implements the API calls locally.
  
  Used for doing local training and hosting local endpoints. It still needs access to
  a boto client to interact with S3 but it won't perform any SageMaker call.
  
  Implements the methods with the same signature as the boto SageMakerClient.
  
  Args:
  
  Returns:
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docstr: Creates a processing job in Local Mode
  
  Args:
    ProcessingJobName(str): local processing job name.
    AppSpecification(dict): Identifies the container and application to run.
    ProcessingResources(dict): Identifies the resources to use for local processing.
    Environment(dict, optional): Describes the environment variables to pass
      to the container. (Default value = None)
    ProcessingInputs(dict, optional): Describes the processing input data.
      (Default value = None)
    ProcessingOutputConfig(dict, optional): Describes the processing output
      configuration. (Default value = None)
    **kwargs: Keyword arguments
  
  Returns:
code: def create_processing_job(
      self,
      ProcessingJobName,
      AppSpecification,
      ProcessingResources,
      Environment=None,
      ProcessingInputs=None,
      ProcessingOutputConfig=None,
      **kwargs,
  ):
      """Creates a processing job in Local Mode
  
      Args:
        ProcessingJobName(str): local processing job name.
        AppSpecification(dict): Identifies the container and application to run.
        ProcessingResources(dict): Identifies the resources to use for local processing.
        Environment(dict, optional): Describes the environment variables to pass
          to the container. (Default value = None)
        ProcessingInputs(dict, optional): Describes the processing input data.
          (Default value = None)
        ProcessingOutputConfig(dict, optional): Describes the processing output
          configuration. (Default value = None)
        **kwargs: Keyword arguments
  
      Returns:
  
      """
      Environment = Environment or {}
      ProcessingInputs = ProcessingInputs or []
      ProcessingOutputConfig = ProcessingOutputConfig or {}
  
      container_entrypoint = None
      if "ContainerEntrypoint" in AppSpecification:
          container_entrypoint = AppSpecification["ContainerEntrypoint"]
  
      container_arguments = None
      if "ContainerArguments" in AppSpecification:
          container_arguments = AppSpecification["ContainerArguments"]
  
      if "ExperimentConfig" in kwargs:
          logger.warning(
              "Experiment configuration is not supported in local mode."
          )
      if "NetworkConfig" in kwargs:
          logger.warning(
              "Network configuration is not supported in local mode."
          )
      if "StoppingCondition" in kwargs:
          logger.warning(
              "Stopping condition is not supported in local mode."
          )
  
      container = _SageMakerContainer(
          ProcessingResources["ClusterConfig"]["InstanceType"],
          ProcessingResources["ClusterConfig"]["InstanceCount"],
          AppSpecification["ImageUri"],
          sagemaker_session=self.sagemaker_session,
          container_entrypoint=container_entrypoint,
          container_arguments=container_arguments,
      )
      processing_job = _LocalProcessingJob(container)
      logger.info("Starting processing job")
      processing_job.start(
          ProcessingInputs,
          ProcessingOutputConfig,
          Environment,
          ProcessingJobName,
      )
  
      LocalSagemakerClient._processing_jobs[
          ProcessingJobName
      ] = processing_job
  
imports: from __future__ import absolute_import, annotations
  import logging
  import platform
  from datetime import datetime
  from typing import Dict
  import boto3
  from botocore.exceptions import ClientError
  import jsonschema
  from sagemaker.config import SAGEMAKER_PYTHON_SDK_LOCAL_MODE_CONFIG_SCHEMA, SESSION_DEFAULT_S3_BUCKET_PATH, SESSION_DEFAULT_S3_OBJECT_KEY_PREFIX_PATH, load_local_mode_config, load_sagemaker_config, validate_sagemaker_config
  from sagemaker.local.image import _SageMakerContainer
  from sagemaker.local.utils import get_docker_host
  from sagemaker.local.entities import _LocalEndpointConfig, _LocalEndpoint, _LocalModel, _LocalProcessingJob, _LocalTrainingJob, _LocalTransformJob, _LocalPipeline
  from sagemaker.session import Session
  from sagemaker.utils import get_config_value, _module_import_error, resolve_value_from_config, format_tags
label_desc: Use image node_id 2 for calling the LocalSagemakerClient obj's underlying member method code with example usage: obj.create_processing_job(ProcessingJobName, AppSpecification, ProcessingResources, Environment, ProcessingInputs, ProcessingOutputConfig) without return types