def test_construct( self, dataframe, feature_set_dataframe, key_id, timestamp_c, feature_add, feature_divide, ): spark_client = Mock() # arrange feature_set = FeatureSet( "name", "entity", "description", [key_id], timestamp_c, [feature_add, feature_divide], ) # act result_df = feature_set.construct(dataframe, spark_client) result_columns = result_df.columns # assert assert (result_columns == key_id.get_output_columns() + timestamp_c.get_output_columns() + feature_add.get_output_columns() + feature_divide.get_output_columns()) assert_dataframe_equality(result_df, feature_set_dataframe) assert result_df.is_cached
def test_columns(self, key_id, timestamp_c, feature_add, feature_divide): # arrange name = "name" entity = "entity" description = "description" # act fs = FeatureSet( name, entity, description, [key_id], timestamp_c, [feature_add, feature_divide], ) out_columns = fs.columns # assert assert ( out_columns == key_id.get_output_columns() + timestamp_c.get_output_columns() + feature_add.get_output_columns() + feature_divide.get_output_columns() )