def __init__(self, data_provider, output):
self.output = output
self.data_provider = data_provider
self.project_name = self.data_provider.project_name
self.session_uid = self.data_provider.session_uid
self.products = self.data_provider[Data.PRODUCTS]
self.all_products = self.data_provider[Data.ALL_PRODUCTS]
self.match_product_in_scene = self.data_provider[Data.MATCHES]
self.visit_date = self.data_provider[Data.VISIT_DATE]
self.session_info = self.data_provider[Data.SESSION_INFO]
self.scene_info = self.data_provider[Data.SCENES_INFO]
self.store_id = self.data_provider[Data.STORE_FK]
self.store_info = self.data_provider[Data.STORE_INFO]
self.store_channel = self.store_info['store_type'].values[0]
if self.store_channel:
self.store_channel = self.store_channel.upper()
self.store_type = self.store_info['additional_attribute_1'].values[0]
self.scif = self.data_provider[Data.SCENE_ITEM_FACTS]
self.rds_conn = PSProjectConnector(self.project_name,
DbUsers.CalculationEng)
self.tools = INBEVCOINBEVCOGENERALToolBox(self.data_provider,
self.output,
rds_conn=self.rds_conn)
self.kpi_static_data = self.get_kpi_static_data()
self.kpi_results_queries = []
self.relative_positioning = parse_template(TEMPLATE_PATH,
'Relative Positioning',
lower_headers_row_index=2)
self.brand_blocking = parse_template(TEMPLATE_PATH,
'Brand Blocking',
lower_headers_row_index=6)
self.purity = parse_template(TEMPLATE_PATH,
'Purity',
lower_headers_row_index=3)
def __init__(self, data_provider, output):
self.output = output
self.data_provider = data_provider
self.project_name = self.data_provider.project_name
self.common = Common(self.data_provider)
self.old_common = oldCommon(self.data_provider)
self.rds_conn = PSProjectConnector(self.project_name,
DbUsers.CalculationEng)
self.session_fk = self.data_provider.session_id
self.match_product_in_scene = self.data_provider[Data.MATCHES]
self.scif = self.data_provider[Data.SCENE_ITEM_FACTS]
self.store_info = self.data_provider[Data.STORE_INFO]
self.store_id = self.data_provider[Data.STORE_FK]
self.survey = Survey(self.data_provider)
self.block = Block(self.data_provider)
self.general_toolbox = GENERALToolBox(self.data_provider)
self.visit_date = self.data_provider[Data.VISIT_DATE]
self.template_path = self.get_relevant_template()
self.gap_data = self.get_gap_data()
self.kpi_weights = parse_template(self.template_path,
Consts.KPI_WEIGHT,
lower_headers_row_index=0)
self.template_data = self.parse_template_data()
self.kpis_gaps = list()
self.passed_availability = list()
self.kpi_static_data = self.old_common.get_kpi_static_data()
self.own_manufacturer_fk = int(
self.data_provider.own_manufacturer.param_value.values[0])
self.parser = Parser
self.all_products = self.data_provider[Data.ALL_PRODUCTS]
def mock_parse_template_data(self):
template_mock = self.mock_object(
'CBCDAIRYILToolBox.parse_template_data')
template_data = parse_template(os.path.join(
os.path.dirname(os.path.realpath(__file__)), 'Data',
'test_template.xlsx'),
Consts.KPI_SHEET,
lower_headers_row_index=1)
template_mock.return_value = template_data
def get_gap_data(self):
"""
This function parse the gap data template and returns the gap priorities.
:return: A dict with the priorities according to kpi_names. E.g: {kpi_name1: 1, kpi_name2: 2 ...}
"""
gap_sheet = parse_template(self.template_path,
Consts.KPI_GAP,
lower_headers_row_index=0)
gap_data = zip(gap_sheet[Consts.KPI_NAME], gap_sheet[Consts.ORDER])
gap_data = {kpi_name: int(order) for kpi_name, order in gap_data}
return gap_data
def parse_template_data(self):
"""
This function responsible to filter the relevant template data..
:return: A DataFrame with filtered Data by store attributes.
"""
kpis_template = parse_template(self.template_path,
Consts.KPI_SHEET,
lower_headers_row_index=1)
relevant_store_info = self.get_store_attributes(
Consts.STORE_ATTRIBUTES_TO_FILTER_BY)
filtered_data = self.filter_template_by_store_att(
kpis_template, relevant_store_info)
return filtered_data