code: def get_best_performing_log(
      log_list: LogListType,
      extractor: ExtractorFnType,
      metric_name: str,
  ) -> Dict:
      logs_eval = [
          get_avg_metric_from_extractor(log, extractor, metric_name)
          for log in log_list
      ]
      return pipe(
          logs_eval,
          partial(zip, log_list),
          partial(sorted, reverse=True, key=lambda x: x[1]),
      )[0][0]
  
file_path: fklearn/src/fklearn/tuning/utils.py
imports: from typing import Any, Dict, Generator, List
  from toolz.curried import reduce, partial, pipe, first, curry
  from fklearn.metrics.pd_extractors import extract
  from fklearn.types import LogListType, LogType, ExtractorFnType, ValidatorReturnType, EvalReturnType
label_desc: Use image node_id 2 for calling a global function with example usage: get_best_performing_log(log_list, extractor, metric_name) and returns: pipe