code: def env_0():
      """`Environment` fixture that has `holdout_dataset` identical to `train_dataset` and is given
      `experiment_callbacks` consisting of the `lambda_callback` result of :func:`sentinel_checker`
      """
      return Environment(
          train_dataset=get_breast_cancer_data(target="target"),
          results_path=assets_dir,
          holdout_dataset=get_breast_cancer_data(target="target"),
          metrics=["roc_auc_score"],
          cv_type="StratifiedKFold",
          cv_params=dict(n_splits=2, shuffle=True, random_state=32),
          experiment_callbacks=[sentinel_checker()],
      )
  
file_path: hyperparameter_hunter/tests/test_sentinels.py
imports: from hyperparameter_hunter import Environment, CVExperiment, Real, Integer, Categorical, GBRT
  from hyperparameter_hunter import lambda_callback
  from hyperparameter_hunter.sentinels import DatasetSentinel
  from hyperparameter_hunter.settings import G
  from hyperparameter_hunter.utils.learning_utils import get_breast_cancer_data
  import pytest
  import sys
label_desc: Use image node_id 3 for calling a global function with example usage: env_0() and returns: Environment