text: import math
  
  from reg_model.predict import make_prediction
  from reg_model.processing.data_management import load_dataset
  
  
  def test_make_single_prediction():
      # Given
      test_data = load_dataset(file_name='test.csv')
      single_test_json = test_data[0:1]
  
      # When
      subject = make_prediction(input_data=single_test_json)
  
      # Then
      assert subject is not None
      assert isinstance(subject.get('predictions')[0], float)
      assert math.ceil(subject.get('predictions')[0]) == 112476
  
  
  def test_make_multiple_predictions():
      # Given
      test_data = load_dataset(file_name='test.csv')
      original_data_length = len(test_data)
      multiple_test_json = test_data
  
      # When
      subject = make_prediction(input_data=multiple_test_json)
  
      # Then
      assert subject is not None
      assert len(subject.get('predictions')) == 1451
  
      # We expect some rows to be filtered out
      assert len(subject.get('predictions')) != original_data_length
  