def test_calculate_display_size_correct_results_length(self):
"""
test result length
"""
scene_tool_box = PngcnSceneKpis(self.ProjectConnector_mock,
self.common_mock, 16588190,
self.data_provider_mock)
mock_df_products_size = self.mock_object('_get_display_size_of_product_in_scene',
path='Projects.PNGCN_PROD.SceneKpis.KPISceneToolBox.PngcnSceneKpis')
# test that we don't return any thing when the used df is empty
mock_df_products_size.return_value = pd.DataFrame(
[{'item_id': 2, 'scene_id': 3, 'product_size': 0.25}])
# test that we write the correct results to DB
data_scif = [{u'scene_id': 16588190, u'item_id': 123, u'manufacturer_fk': 4, u'rlv_sos_sc': 1, u'status': 1},
{u'scene_id': 16588190, u'item_id': 125,
u'manufacturer_fk': 3, u'rlv_sos_sc': 1, u'status': 1},
{u'scene_id': 16588190, u'item_id': 136, u'manufacturer_fk': 3, u'rlv_sos_sc': 1, u'status': 1}]
scene_tool_box.scif = pd.DataFrame(data_scif)
data_df_products_size = [{'item_id': 123, 'scene_id': 16588190, 'product_size': 1.245},
{'item_id': 124, 'scene_id': 16588190, 'product_size': 0.285},
{'item_id': 125, 'scene_id': 16588190, 'product_size': 1.225},
{'item_id': 126, 'scene_id': 16588190, 'product_size': 0.232},
{'item_id': 136, 'scene_id': 16588190, 'product_size': 0}]
mock_df_products_size.return_value = pd.DataFrame(data_df_products_size)
scene_tool_box.common.write_to_db_result = MagicMock()
# scene_tool_box.png_manufacturer_fk = 4
scene_tool_box.calculate_display_size()
kpi_results = scene_tool_box.common.write_to_db_result.mock_calls[0][2]
if kpi_results:
# test that we write 8 fields to DB
self.assertEqual(len(kpi_results), 8, 'expects to write 8 parameters to db')
def test_calculate_display_size_correct_results_sanity(self):
"""
test if the numerator is greater then denominator (if the subgroup is greater then containing group)
"""
scene_tool_box = PngcnSceneKpis(self.ProjectConnector_mock,
self.common_mock, 16588190,
self.data_provider_mock)
mock_df_products_size = self.mock_object('_get_display_size_of_product_in_scene',
path='Projects.PNGCN_PROD.SceneKpis.KPISceneToolBox.PngcnSceneKpis')
# test that we write the correct results to DB
data_scif = [{u'scene_id': 16588190, u'item_id': 123, u'manufacturer_fk': 4, u'rlv_sos_sc': 1, u'status': 1},
{u'scene_id': 16588190, u'item_id': 125,
u'manufacturer_fk': 3, u'rlv_sos_sc': 1, u'status': 1},
{u'scene_id': 16588190, u'item_id': 136, u'manufacturer_fk': 3, u'rlv_sos_sc': 1, u'status': 1}]
scene_tool_box.scif = pd.DataFrame(data_scif)
data_df_products_size = [{'item_id': 123, 'scene_id': 16588190, 'product_size': 1.245},
{'item_id': 124, 'scene_id': 16588190, 'product_size': 0.285},
{'item_id': 125, 'scene_id': 16588190, 'product_size': 1.225},
{'item_id': 126, 'scene_id': 16588190, 'product_size': 0.232},
{'item_id': 136, 'scene_id': 16588190, 'product_size': 0}]
mock_df_products_size.return_value = pd.DataFrame(data_df_products_size)
scene_tool_box.common.write_to_db_result = MagicMock()
scene_tool_box.calculate_display_size()
kpi_results = scene_tool_box.common.write_to_db_result.mock_calls[0][2]
if kpi_results:
numerator = kpi_results['numerator_result']
denominator = kpi_results['denominator_result']
# test if the numerator is greater then denominator (if the subgroup is greater then containing group)
self.assertGreaterEqual(denominator, numerator,
'the numerator cant be greater then denominator')
def test_calculate_display_size_correct_results_type(self):
"""
test that the type of the numerator and denominator is float
"""
scene_tool_box = PngcnSceneKpis(self.ProjectConnector_mock,
self.common_mock, 16588190,
self.data_provider_mock)
mock_df_products_size = self.mock_object('_get_display_size_of_product_in_scene',
path='Projects.PNGCN_PROD.SceneKpis.KPISceneToolBox.PngcnSceneKpis')
# test that we don't return any thing when the used df is empty
mock_df_products_size.return_value = pd.DataFrame(
[{'item_id': 2, 'scene_id': 3, 'product_size': 0.25}])
# test that we write the correct results to DB
data_scif = [{u'scene_id': 16588190, u'item_id': 123, u'manufacturer_fk': 4, u'rlv_sos_sc': 1, u'status': 1},
{u'scene_id': 16588190, u'item_id': 125,
u'manufacturer_fk': 3, u'rlv_sos_sc': 1, u'status': 1},
{u'scene_id': 16588190, u'item_id': 136, u'manufacturer_fk': 3, u'rlv_sos_sc': 1, u'status': 1}]
scene_tool_box.scif = pd.DataFrame(data_scif)
data_df_products_size = [{'item_id': 123, 'scene_id': 16588190, 'product_size': 1.245},
{'item_id': 124, 'scene_id': 16588190, 'product_size': 0.285},
{'item_id': 125, 'scene_id': 16588190, 'product_size': 1.225},
{'item_id': 126, 'scene_id': 16588190, 'product_size': 0.232},
{'item_id': 136, 'scene_id': 16588190, 'product_size': 0}]
mock_df_products_size.return_value = pd.DataFrame(data_df_products_size)
scene_tool_box.common.write_to_db_result = MagicMock()
scene_tool_box.calculate_display_size()
kpi_results = scene_tool_box.common.write_to_db_result.mock_calls[0][2]
if kpi_results:
numerator = kpi_results['numerator_result']
denominator = kpi_results['denominator_result']
# test that the type of the numerator and denominator is float
self.assertIsInstance(denominator, float)
self.assertIsInstance(numerator, float)
