new_contents: import unittest
  
  import lightgbm as lgb
  
  from sklearn.datasets import load_iris
  
  class TestLightgbm(unittest.TestCase):
      # Based on the "simple_example" from their documentation:
      # https://github.com/Microsoft/LightGBM/blob/master/examples/python-guide/simple_example.py
      def test_simple(self):
          # Load a dataset aleady on disk
          iris = load_iris()
  
          lgb_train = lgb.Dataset(iris.data[:100], iris.target[:100])
          lgb_eval = lgb.Dataset(iris.data[100:], iris.target[100:], reference=lgb_train)
  
          params = {
              'task': 'train',
              'boosting_type': 'gbdt',
              'objective': 'regression',
              'metric': {'l2', 'auc'},
              'num_leaves': 31,
              'learning_rate': 0.05,
              'feature_fraction': 0.9,
              'bagging_fraction': 0.8,
              'bagging_freq': 5,
              'verbose': 0
          }
  
          # Run only one round for faster test
          gbm = lgb.train(params, lgb_train, num_boost_round=1, valid_sets=lgb_eval, early_stopping_rounds=1)
  
          self.assertEqual(1, gbm.best_iteration)
  
subject: Add test for the lightgbm package