code: def __init__(self, globals_dict: dict) -> None:
      args = {"average": "weighted"}
      score_func = pycaret.internal.metrics.BinaryMulticlassScoreFunc(
          pycaret.internal.metrics.EncodedDecodedLabelsScoreFunc(
              metrics.precision_score,
              pycaret.internal.metrics.get_pos_label(globals_dict),
          ),
          kwargs_if_binary={"average": "binary"},
      )
      super().__init__(
          id="precision",
          name="Precision",
          display_name="Prec.",
          score_func=score_func,
          scorer=metrics.make_scorer(
              score_func,
              **args,
          ),
          args=args,
      )
  
imports: from typing import Any, Dict, Optional, Union
  from sklearn import metrics
  from sklearn.metrics._scorer import _BaseScorer
  import pycaret.containers.base_container
  import pycaret.internal.metrics
  from pycaret.containers.metrics.base_metric import MetricContainer
label_desc: Use image node_id 1 to create a new PrecisionMetricContainer object from inherited base classes: ClassificationMetricContainer with example: obj = PrecisionMetricContainer(globals_dict)