code: def test_feature_precision(self):
      # feature precision decides the least change that can be made to the feature in
      # optimization, given as 2-decimal place for 'hours_per_week' feature while initiating
      # private Data object.
      assert self.d.get_decimal_precisions()[1] == 2
  
imports: from enum import Enum
  import numpy
  import pandas
  import pytest
  from raiutils.exceptions import UserConfigValidationException
  from sklearn.datasets import load_iris
  import dice_ml
  from dice_ml.utils import helpers
label_desc: Use image node_id 3 for calling the TestPublicDataMethods obj's underlying member method code with example usage: obj.test_feature_precision() without return types