code: def get_job_runner(
      parquet_metadata_directory: StrPath,
      cache_mongo_resource: CacheMongoResource,
      queue_mongo_resource: QueueMongoResource,
  ) -> GetJobRunner:
      def _get_job_runner(
          dataset: str,
          config: str,
          app_config: AppConfig,
      ) -> ConfigParquetMetadataJobRunner:
          upsert_response(
              kind="dataset-config-names",
              dataset=dataset,
              dataset_git_revision=REVISION_NAME,
              content={
                  "config_names": [
                      {"dataset": dataset, "config": config}
                  ]
              },
              http_status=HTTPStatus.OK,
          )
  
          return ConfigParquetMetadataJobRunner(
              job_info={
                  "type": ConfigParquetMetadataJobRunner.get_job_type(),
                  "params": {
                      "dataset": dataset,
                      "revision": REVISION_NAME,
                      "config": config,
                      "split": None,
                  },
                  "job_id": "job_id",
                  "priority": Priority.NORMAL,
                  "difficulty": 50,
              },
              app_config=app_config,
              parquet_metadata_directory=parquet_metadata_directory,
          )
  
      return _get_job_runner
  
imports: import io
  from collections.abc import Callable, Mapping
  from http import HTTPStatus
  from pathlib import Path
  from typing import Any, Optional
  from unittest.mock import patch
  import pyarrow
  import pyarrow.parquet
  import pytest
  from datasets import Dataset, Features, Value
  from fsspec.implementations.http import HTTPFile, HTTPFileSystem
  from huggingface_hub import hf_hub_url
  from libcommon.exceptions import PreviousStepFormatError
  from libcommon.parquet_utils import ParquetIndexWithMetadata
  from libcommon.resources import CacheMongoResource, QueueMongoResource
  from libcommon.simple_cache import CachedArtifactError, upsert_response
  from libcommon.storage import StrPath
  from libcommon.utils import Priority, SplitHubFile
  from worker.config import AppConfig
  from worker.dtos import ConfigParquetMetadataResponse, ConfigParquetResponse, ParquetFileMetadataItem
  from worker.job_runners.config.parquet_metadata import ConfigParquetMetadataJobRunner
  from ...constants import CI_USER_TOKEN
  from ...fixtures.hub import hf_api
  from ..utils import REVISION_NAME
label_desc: Use image node_id 2 for calling a global function with example usage: get_job_runner(parquet_metadata_directory, cache_mongo_resource, queue_mongo_resource) and returns: _get_job_runner, ConfigParquetMetadataJobRunner