code: def test_2():
      (
          train_inputs,
          train_targets,
          holdout_inputs,
          holdout_targets,
      ) = get_pima_data()
  
      feature_engineer = FeatureEngineer()
      feature_engineer.add_step(set_nan_0)
      feature_engineer.add_step(impute_negative_one_0)
      feature_engineer.add_step(standard_scale_0)
      feature_engineer(
          "pre_cv",
          train_inputs=train_inputs.copy(),
          holdout_inputs=holdout_inputs.copy(),
      )
  
      expected_train_inputs = [
          [
              -0.468521,
              -0.962876,
              0.636364,
              0.548821,
              -0.929624,
              -0.48321,
              -0.618238,
              0.363422,
          ],
          [
              1.717911,
              1.488081,
              0.454545,
              -1.646464,
              -0.929624,
              -0.917113,
              -0.235491,
              0.571092,
          ],
          [
              -0.468521,
              -0.862837,
              0.636364,
              0.109764,
              0.408471,
              -0.285982,
              -0.837632,
              -1.713275,
          ],
          [
              -0.780869,
              0.337632,
              -1.727273,
              0.987878,
              1.450776,
              1.686305,
              1.691360,
              0.778761,
          ],
      ]
      expected_holdout_inputs = [
          [
              1.093216,
              0.612739,
              1.181818,
              0.987878,
              -0.929624,
              0.437190,
              -0.289147,
              4.309145,
          ]
      ]
  
      assert_array_almost_equal(
          feature_engineer.datasets["train_inputs"],
          expected_train_inputs,
      )
      assert_array_almost_equal(
          feature_engineer.datasets["holdout_inputs"],
          expected_holdout_inputs,
      )
  
imports: from hyperparameter_hunter import Environment, CVExperiment, FeatureEngineer, EngineerStep
  from hyperparameter_hunter.callbacks.recipes import dataset_recorder
  import numpy
  from numpy.testing import assert_array_almost_equal
  import pandas
  from pandas.testing import assert_frame_equal
  import pytest
  from sklearn.ensemble import AdaBoostClassifier
  from sklearn.preprocessing import StandardScaler
label_desc: Use image node_id 10 for calling a global function with example usage: test_2() without return types