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.PNGCNTEST.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.PNGCNTEST.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.PNGCNTEST.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)