def __init__(self, data_provider, output, common):
GlobalSessionToolBox.__init__(self, data_provider, output, common)
self.main_template, self.invasion_template = self.get_template()
self.relevant_scenes_exist_value = self.do_relevant_scenes_exist()
self.relevant_scif = self.scif[self.scif['template_name'].isin(
self.relevant_scenes_exist_value)]
def __init__(self, data_provider, output, common):
GlobalSessionToolBox.__init__(self, data_provider, output, common)
self.ps_data_provider = PsDataProvider(data_provider)
self.own_manufacturer = int(self.data_provider.own_manufacturer.param_value.values[0])
self.all_templates = self.data_provider[Data.ALL_TEMPLATES]
self.project_templates = {}
self.parse_template()
self.store_type = self.store_info['store_type'].iloc[0]
self.survey = Survey(self.data_provider, output, ps_data_provider=self.ps_data_provider, common=self.common)
self.att2 = self.store_info['additional_attribute_2'].iloc[0]
self.results_df = pd.DataFrame(columns=['kpi_name', 'kpi_fk', 'numerator_id', 'numerator_result',
'denominator_id', 'denominator_result', 'result', 'score',
'identifier_result', 'identifier_parent', 'should_enter'])
self.products = self.data_provider[Data.PRODUCTS]
scif = self.scif[['brand_fk', 'facings', 'product_type']].groupby(by='brand_fk').sum()
self.mpis = self.matches \
.merge(self.products, on='product_fk', suffixes=['', '_p']) \
.merge(self.scene_info, on='scene_fk', suffixes=['', '_s']) \
.merge(self.all_templates[['template_fk', TEMPLATE_GROUP]], on='template_fk') \
.merge(scif, on='brand_fk')[COLUMNS]
self.mpis['store_fk'] = self.store_id
self.calculations = {
COMBO: self.calculate_combo,
POSM_AVAILABILITY: self.calculate_posm_availability,
SCORING: self.calculate_scoring,
SHARE_OF_EMPTY: self.calculate_share_of_empty,
SOS: self.calculate_sos,
SURVEY: self.calculate_survey,
}
def __init__(self, data_provider, output):
GlobalSessionToolBox.__init__(self, data_provider, output)
self.templates = {}
self.parse_template()
self.rds_conn = PSProjectConnector(self.project_name,
DbUsers.CalculationEng)
self.scif = self.data_provider[Data.SCENE_ITEM_FACTS]
self.match_product_in_scene = self.data_provider[Data.MATCHES]
self.match_display_in_scene = self.data_provider.match_display_in_scene
self._filter_display_in_scene()
self.match_scene_item_facts = pd.merge(
self.scif,
self.match_product_in_scene,
how='right',
left_on=['item_id', 'scene_id'],
right_on=['product_fk',
'scene_fk']) # Merges scif with mpis on product_fk
self.match_scene_item_facts.rename(columns={
'product_fk_x': 'product_fk',
'scene_fk_x': Consts.SCENE_FK
},
inplace=True)
self._filter_scif_and_mpis_by_template_name_scene_type_and_category_name(
)
self._filter_scif_by_by_template_name_scene_type_and_category_name()
# self.own_manufacturer_fk = int(self.data_provider.own_manufacturer.param_value.values[0])
self.results_df = pd.DataFrame(columns=[
'kpi_name', 'kpi_fk', 'numerator_id', 'numerator_result',
'context_id', 'denominator_id', 'denominator_result', 'result',
'score'
])
def __init__(self, data_provider, output, common):
GlobalSessionToolBox.__init__(self, data_provider, output, common)
self.mpis = self.matches.merge(self.scene_info, on='scene_fk')[COLUMNS]
self.results_df = pd.DataFrame(
columns=[FK, NUMERATOR_ID, DENOMINATOR_ID, CONTEXT_ID, RESULT, SCORE]
)
def __init__(self, data_provider, output):
GlobalSessionToolBox.__init__(self, data_provider, output)
self.scif = self.data_provider[Data.SCENE_ITEM_FACTS]
self.visit_date = datetime.combine(self.data_provider[Data.VISIT_DATE], datetime.min.time())
self.relevant_template = self.retrieve_price_target_df()
self.mpis = self.data_provider[Data.MATCHES]
self.manufacturer_fk = self.data_provider.own_manufacturer.param_value.values[0] if \
self.data_provider.own_manufacturer.param_value.values[0] else 2
def __init__(self, data_provider, output):
GlobalSessionToolBox.__init__(self, data_provider, output)
self.adjacency = Adjancency(data_provider)
self.block = Block(data_provider)
self.kpi_static_data = self.common.get_kpi_static_data()
self.ps_data_provider = PsDataProvider(data_provider)
self._scene_types = None
self.external_targets = self.ps_data_provider.get_kpi_external_targets(
)
def __init__(self, data_provider, output):
GlobalSessionToolBox.__init__(self, data_provider, output)
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]
self.assortment = Assortment(self.data_provider, self.output)
self.ps_data = PsDataProvider(self.data_provider, self.output)
self.kpi_external_targets = self.ps_data.get_kpi_external_targets(key_fields=Consts.KEY_FIELDS,
data_fields=Consts.DATA_FIELDS)
def __init__(self, data_provider, output):
GlobalSessionToolBox.__init__(self, data_provider, output)
self.assortment = Assortment(data_provider)
self.ps_data = PsDataProvider(data_provider)
self.display_in_scene = data_provider.match_display_in_scene
self.static_display = data_provider.static_display
self.manufacturer_fk = int(self.manufacturer_fk)
self._add_display_data_to_scif()
self._add_client_name_and_sub_brand_data()
def __init__(self, data_provider, common):
GlobalSessionToolBox.__init__(self, data_provider, None)
self.filtered_mdis = self._get_filtered_match_display_in_scene()
self.store_number_1 = self.store_info.store_number_1[0]
self.filtered_scif = self._get_filtered_scif()
self.ps_data_provider = PsDataProvider(data_provider)
self.target = self._get_case_count_targets()
self.matches = self.get_filtered_matches()
self.excluded_product_fks = self._get_excluded_product_fks()
self.adj_graphs_per_scene = {}
self.common = common
def __init__(self, data_provider, common):
GlobalSessionToolBox.__init__(self, data_provider, None)
# self.matches = self.get_filtered_matches()
self.store_number = self.store_info.store_number_1.iloc[0]
self.ps_data_provider = PsDataProvider(self.data_provider, self.output)
self.rds_conn = PSProjectConnector(self.project_name, DbUsers.CalcAdmin)
self.custom_entity = self.get_custom_entity()
self.targets = self.ps_data_provider.get_kpi_external_targets(kpi_fks=[6006],
key_fields=['store_number_1', 'product_fk'],
key_filters={'store_number_1': self.store_number})
self.common = common
def __init__(self, data_provider, output, common):
GlobalSessionToolBox.__init__(self, data_provider, output, common)
self.scene_types = self.scif['template_name'].unique().tolist()
self.gz = self.store_info['additional_attribute_4'].iloc[0]
self.city = self.store_info['address_city'].iloc[0]
self.relevant_targets = self._get_relevant_external_targets(
kpi_operation_type='acomodo_cigarros')
self.invasion_targets = self._get_relevant_external_targets(
kpi_operation_type='invasion')
self._determine_target_product_fks()
self.leading_products = self._get_leading_products_from_scif()
self.scene_realograms = self._calculate_scene_realograms()
self.ps_data_provider = PsDataProvider(self.data_provider)
self.match_product_in_probe_state_reporting = self.ps_data_provider.get_match_product_in_probe_state_reporting(
)
def __init__(self, data_provider, output):
GlobalSessionToolBox.__init__(self, data_provider, output)
self.ps_data_provider = PsDataProvider(self.data_provider, self.output)
self.results_df = pd.DataFrame(columns=[
'kpi_name', 'kpi_fk', 'numerator_id', 'numerator_result',
'denominator_id', 'denominator_result', 'result', 'score',
'identifier_result', 'identifier_parent', 'should_enter', 'target'
])
self.templates = {}
self.parse_template()
self.own_manuf_fk = int(
self.data_provider.own_manufacturer.param_value.values[0])
self.scif = self.scif[self.scif['product_type'] != 'Irrelevant']
self.scene_survey_results = self.get_scene_survey_response()
self.session_survey_results = self.get_session_survey_response()
self.custom_entities = self.ps_data_provider.get_custom_entities(1002)
def __init__(self, data_provider, output, common):
GlobalSessionToolBox.__init__(self, data_provider, output, common)
self.common_v2 = common
self.ps_data_provider = PsDataProvider(data_provider)
self.store_type = self.store_info['store_type'].iloc[0]
self.templates = {}
self.parse_template()
self.own_manuf_fk = int(self.data_provider.own_manufacturer.param_value.values[0])
self.template_fk = self.scif.template_fk.iloc[0]
self.survey_response = self.data_provider[Data.SURVEY_RESPONSES]
self.assortment_template = self.templates[ASSORTMENT]
self.match_product_in_scene = self.data_provider['matches']
self.important_survey = self.survey_response[self.survey_response.question_fk.isin([22])]
# self.survey = Survey(self.data_provider, output=output, ps_data_provider=self.ps_data_provider,
# common=self.common_v2)
self.results_df = pd.DataFrame(columns=['kpi_name', 'kpi_fk', 'numerator_id', 'numerator_result',
'denominator_id', 'denominator_result', 'result', 'score',
'identifier_result', 'identifier_parent', 'should_enter'])
def __init__(self, data_provider, output, common):
GlobalSessionToolBox.__init__(self, data_provider, output, common)
self.ps_data_provider = PsDataProvider(data_provider)
self.own_manufacturer = int(
self.data_provider.own_manufacturer.param_value.values[0])
self.templates = {}
self.parse_template()
self.store_type = self.store_info['store_type'].iloc[0]
self.survey = Survey(self.data_provider,
output,
ps_data_provider=self.ps_data_provider,
common=self.common)
self.att2 = self.store_info['additional_attribute_2'].iloc[0]
self.products = self.data_provider[Data.PRODUCTS]
self.survey = self.data_provider.survey_responses
self.results_df = pd.DataFrame(columns=[
'kpi_name', 'kpi_fk', 'numerator_id', 'numerator_result',
'denominator_id', 'denominator_result', 'result', 'score',
'identifier_result', 'identifier_parent', 'should_enter'
])
def __init__(self, data_provider, output):
GlobalSessionToolBox.__init__(self, data_provider, output)
self.templates = {}
self.parse_template()
self.match_product_in_scene = self.data_provider[Data.MATCHES]
self.match_scene_item_facts = pd.merge(
self.scif,
self.match_product_in_scene,
how='right',
left_on=['item_id', 'scene_id'],
right_on=['product_fk',
'scene_fk']) # Merges scif with mpis on product_fk
self.block = Block(data_provider)
self.own_manufacturer_fk = int(
self.data_provider.own_manufacturer.param_value.values[0])
self.results_df = pd.DataFrame(columns=[
'kpi_name', 'kpi_fk', 'numerator_id', 'numerator_result',
'context_id', 'denominator_id', 'denominator_result', 'result',
'score'
])
def __init__(self, data_provider, output, common):
GlobalSessionToolBox.__init__(self, data_provider, output, common)
self.ps_data_provider = PsDataProvider(self.data_provider, self.output)
self.own_manufacturer = self.data_provider[Data.OWN_MANUFACTURER].iloc[0]['param_value']
self.products = data_provider[Data.PRODUCTS]
self.store_areas = self.get_store_area_df() \
.rename(columns={"store_area_name": LOCATION, 'store_area_fk': 'location_fk'})
key_packages = self.scif[[PRODUCT_FK, KEY_PACKAGE]] \
.drop_duplicates()
product_facings = self.scif[[SCENE_FK, 'location_type_fk', PRODUCT_FK, FACINGS, 'facings_ign_stack']] \
.rename(columns={'facings_ign_stack': 'SKUs', 'location_type_fk': LOCATION})
survey_response = self.ps_data_provider.get_scene_surveys_responses() \
.rename(columns={'question_fk': 'survey_question_fk', 'selected_option_text': 'scene_survey_response'})
try:
self.mpis = self.matches \
.merge(self.products, how='left', on=PRODUCT_FK, suffixes=['', '_p']) \
.merge(self.scene_info, how='left', on=SCENE_FK, suffixes=['', '_s']) \
.merge(self.templates, how='left', on=TEMPLATE_FK, suffixes=['', '_t']) \
.merge(self.store_areas, how='left', on=SCENE_FK, suffixes=['', '_sa']) \
.merge(key_packages, how='left', on=PRODUCT_FK, suffixes=['', '_kp']) \
.merge(product_facings, how='left', on=[SCENE_FK, PRODUCT_FK], suffixes=['', '_pf']) \
.merge(survey_response, how='left', on=SCENE_FK, suffixes=['', '_sr'])[MPIS_COLUMNS]
self.mpis.loc[:, 'Own-Manufacturer'] = self.own_manufacturer
except ValueError:
self.mpis = pd.DataFrame()
self.kpi_templates = self.get_kpi_template(PATH, 'Data')
self.results_df = pd.DataFrame(
columns=RESULTS_COLUMNS)
self.scene_availability_df = pd.DataFrame(
columns=RESULTS_COLUMNS)
self.calculations = {
COMPLIANT_BAY_COUNT: self.calculate_compliant_bay,
SCENE_AVAILABILITY: self.calculate_scene_availability,
SHARE_OF_SCENES: self.calculate_share_of_scenes,
FACINGS_SOS: self.calculate_facings_sos,
}
def __init__(self, data_provider, output):
GlobalSessionToolBox.__init__(self, data_provider, output)
self.templates = {}
self.scene_kpi_results_fix = {}
self.scene_kpi_ratio_pass = {}
self.scenes_result = self.data_provider.scene_kpi_results
def __init__(self, data_provider, output):
GlobalSessionToolBox.__init__(self, data_provider, output)
self.assortment = Assortment(self.data_provider)
self.ps_data = PsDataProvider(self.data_provider, self.output)
self.result_values = self.ps_data.get_result_values()
self.db_handler = DBHandler(self.data_provider.project_name, self.data_provider.session_uid)
def __init__(self, data_provider, output):
GlobalSessionToolBox.__init__(self, data_provider, output)
def __init__(self, data_provider, common):
GlobalSessionToolBox.__init__(self, data_provider, None)
self.filtered_mdis = self._get_filtered_match_display_in_scene()
self.filtered_scif = self._get_filtered_scif()
self.matches = self.get_filtered_matches()
self.common = common
def __init__(self, data_provider, output):
GlobalSessionToolBox.__init__(self, data_provider, output)
self.assortment = Assortment(self.data_provider, self.output)