def __init__(self, data_provider, output):
self.output = output
self.data_provider = data_provider
self.ps_data_provider = PsDataProvider(data_provider)
self.kpi_result_values = self.ps_data_provider.get_result_values()
self.common_v2 = Common(self.data_provider)
self.store_id = self.data_provider[Data.STORE_FK]
self.scif = self.data_provider[Data.SCENE_ITEM_FACTS]
self.assortment = Assortment(self.data_provider)
self.own_manufacturer_fk = int(
self.data_provider.own_manufacturer.param_value.values[0])
self.kpi_static_data = self.common_v2.kpi_static_data[[
'pk', StaticKpis.TYPE
]]
# self.custom_entity = self.ps_data_provider.get_custom_entities(Consts.PRODUCT_GROUP)
self.visit_date = self.data_provider[Data.VISIT_DATE]
self.project_name = self.data_provider.project_name
self.rds_conn = PSProjectConnector(self.project_name,
DbUsers.CalculationEng)
self.external_targets = self._retrieve_completeness_external_targets()
self.products_trax_cat = self._get_products_with_trax_categories()
self.ass_groups_present = {
Consts.DISTR_SNACKS: 0,
Consts.DISTR_SABRA: 0
}
def run_project_calculations(self):
self.timer.start()
eye_hand_lvl_template_path = os.path.join(os.path.dirname(os.path.dirname(os.path.realpath(__file__))),
'JNJDE', 'Data', 'eye_level_jnjde.xlsx')
eye_hand_lvl_template = pd.read_excel(eye_hand_lvl_template_path)
common = Common(self.data_provider)
jnj_generator = JNJGenerator(self.data_provider, self.output, common)
jnj_generator.linear_sos_out_of_store_discovery_report()
# KPI 2 - Share of Shelf
jnj_generator.sos_vs_target_calculation()
# KPI 3 - OOS
jnj_generator.calculate_auto_assortment()
# KPI 4 - Share of shelf - Hand & Eye
# KPI 12 - New H&E KPI
# KPI 13 - Share of shelf - Hand & Eye (Sub-Category)
jnj_generator.eye_hand_level_sos_calculation(eye_hand_lvl_template)
jnj_generator.eye_hand_level_sos_calculation_de(eye_hand_lvl_template)
# KPI 5 IR - Activation compliance vs plans
jnj_generator.promo_calc(sales_reps_date='2018-09-30', calc_brand_level=True)
# KPI 9 - MSL
jnj_generator.assortment_calculation()
# KPI 10 - New Display compliance
jnj_generator.display_compliance_calculation()
# Competitor KPI's
jnj_generator.sos_brand_out_of_sub_category()
jnj_generator.competitor_eye_hand_level_sos(eye_hand_lvl_template)
common.commit_results_data()
self.timer.stop('KPIGenerator.run_project_calculations')
def __init__(self, output, data_provider):
super(PNGJP_SAND2Util, self).__init__(data_provider)
self.output = output
self.data_provider = data_provider
self.project_name = data_provider.project_name
self.session_uid = self.data_provider.session_uid
self.scif = self.data_provider[Data.SCENE_ITEM_FACTS]
self.all_products = self.data_provider[Data.ALL_PRODUCTS]
self.match_product_in_scene = self.data_provider[Data.MATCHES]
self.scene_info = self.data_provider[Data.SCENES_INFO]
self.all_templates = self.data_provider[Data.ALL_TEMPLATES]
self.match_product_in_scene['count'] = 1
self.matches_product = self.match_product_in_scene.merge(
self.scif,
on=[ScifConsts.PRODUCT_FK, ScifConsts.SCENE_FK],
how='left')
self.rds_conn = PSProjectConnector(self.project_name,
DbUsers.CalculationEng)
self.match_display_in_scene = self.get_match_display_in_scene()
self.visit_date = self.data_provider[Data.VISIT_DATE]
self.common = Common(self.data_provider)
self.kpi_static_data = self.common.get_kpi_static_data()
self.external_targets = self.get_all_kpi_external_targets()
self.all_targets_unpacked = self.unpack_all_external_targets()
self.bay_shelf_info = self.get_bay_shelf_combination_from_custom_entity(
)
self.bay_shelf_entity_type_fk = self.get_bay_shelf_entity_type_fk()
shelf_range_template_path = Path(
__file__).parent / '../Data/shelf_range_template.xlsx'
self.shelf_range_template = pd.read_excel(shelf_range_template_path)
self.session_info = self.data_provider[Data.SESSION_INFO]
self.store_fk = self.session_info['store_fk'].values[0]
def __init__(self, data_provider, output):
self.output = output
self.data_provider = data_provider
self.common = Common(self.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.scif = self.data_provider[Data.SCENE_ITEM_FACTS]
self.rds_conn = PSProjectConnector(self.project_name,
DbUsers.CalculationEng)
self.kpi_static_data = self.common.get_kpi_static_data()
self.kpi_results_queries = []
self.pepsico_fk = self.get_relevant_pk_by_name(Const.MANUFACTURER,
Const.PEPSICO)
self.k_engine = BaseCalculationsGroup(data_provider, output)
self.categories_to_calculate = self.get_relevant_categories_for_session(
)
self.toolbox = GENERALToolBox(data_provider)
self.main_shelves = [
scene_type
for scene_type in self.scif[Const.TEMPLATE_NAME].unique().tolist()
if Const.MAIN_SHELF in scene_type
]
def run_project_calculations(self):
self.timer.start()
data_path = os.path.join(os.path.dirname(os.path.realpath(__file__)),
'Data')
survey_template_path = os.path.join(data_path, 'SurveyTemplate.xlsx')
eye_hand_lvl_template_path = os.path.join(data_path,
'eye_level_jnjuk.xlsx')
exclusive_template_path = os.path.join(data_path,
'KPI Exclusions Template.xlsx')
survey_template = pd.read_excel(survey_template_path,
sheetname='Sheet1')
eye_hand_lvl_template = pd.read_excel(eye_hand_lvl_template_path)
exclusive_template = pd.read_excel(exclusive_template_path)
common = Common(self.data_provider)
jnj_generator = JNJGenerator(self.data_provider, self.output, common,
exclusive_template)
jnj_generator.linear_sos_out_of_store_discovery_report()
jnj_generator.secondary_placement_location_quality(survey_template)
jnj_generator.secondary_placement_location_visibility_quality(
survey_template)
jnj_generator.share_of_shelf_manufacturer_out_of_sub_category()
jnj_generator.calculate_auto_assortment(in_balde=False)
jnj_generator.promo_calc_recovery()
jnj_generator.eye_hand_level_sos_calculation(eye_hand_lvl_template)
jnj_generator.general_assortment_calculation()
jnj_generator.osa_calculation()
common.commit_results_data()
jnj_generator.tool_box.commit_osa_queries()
self.timer.stop('KPIGenerator.run_project_calculations')
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.scif = self.data_provider[Data.SCENE_ITEM_FACTS]
self.rds_conn = PSProjectConnector(self.project_name, DbUsers.CalculationEng)
self.tools = RBUSGENERALToolBox(self.data_provider, self.output, rds_conn=self.rds_conn)
self.old_common = common_old(data_provider)
self.kpi_static_data = self.old_common.get_kpi_static_data()
# self.kpi_results_queries = []
self.templates_path = os.path.join(os.path.dirname(os.path.realpath(__file__)), '..', 'Data')
self.template_dict = self.get_df_from_excel_path()
self.template_dict = self.template_dict[self.template_dict['Template for KPI'] != 'none']\
.set_index('Template for KPI')['KPI Level 3 Name'].to_dict()
self.excluded_sub_categories = self.get_excluded_sub_categories(self.get_df_from_excel_path())
self.common_new = Common(data_provider)
self.manufacturer_fk = self.data_provider[Data.OWN_MANUFACTURER]['param_value'].iloc[0]
self.ps_data = PsDataProvider(self.data_provider, self.output)
self.templates = self.data_provider[Data.TEMPLATES]
self.sub_brands = self.ps_data.get_custom_entities(1001)
def __init__(self, data_provider, output, common=None):
self.output = output
self.data_provider = data_provider
# self.common = common
self.common = Common(self.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.templates = self.data_provider[Data.TEMPLATES]
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] if self.data_provider[Data.STORE_FK] is not None \
else self.session_info['store_fk'].values[0]
self.all_templates = self.data_provider[Data.ALL_TEMPLATES]
self.store_type = self.data_provider.store_type
self.rds_conn = PSProjectConnector(self.project_name,
DbUsers.CalculationEng)
self.kpi_static_data = self.common.get_kpi_static_data()
self.kpi_results_queries = []
self.scif = self.data_provider[Data.SCENE_ITEM_FACTS]
self.kpi_results = pd.DataFrame(
columns=['kpi_fk', 'numerator', 'denominator', 'result', 'score'])
def __init__(self, data_provider, output):
self.output = output
self.data_provider = data_provider
self.common = Common(self.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.current_date = datetime.now()
self.session_info = self.data_provider[Data.SESSION_INFO]
self.scene_info = self.data_provider[Data.SCENES_INFO]
self.store_info = self.data_provider[Data.STORE_INFO]
self.store_id = self.data_provider[Data.STORE_FK]
self.own_manufacturer_id = int(self.data_provider[Data.OWN_MANUFACTURER][self.data_provider[Data.OWN_MANUFACTURER]['param_name'] == 'manufacturer_id']['param_value'].tolist()[0])
self.scif = self.data_provider[Data.SCENE_ITEM_FACTS]
self.rds_conn = PSProjectConnector(self.project_name, DbUsers.CalculationEng)
self.toolbox = GENERALToolBox(data_provider)
self.assortment = Assortment(self.data_provider, self.output, common=self.common)
self.kpi_static_data = self.common.get_kpi_static_data()
self.kpi_results_queries = []
self.template_path = self.get_template_path()
self.template_data = self.get_template_data()
self.sos_store_policies = self.get_sos_store_policies(self.visit_date.strftime('%Y-%m-%d'))
self.result_values = self.get_result_values()
self.scores = pd.DataFrame()
def __init__(self, data_provider, output):
self.output = output
self.data_provider = data_provider
self.common = Common(self.data_provider)
self.match_display_in_scene = self.data_provider.match_display_in_scene
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.scene_info = self.data_provider[Data.SCENES_INFO]
self.templates = self.data_provider[Data.TEMPLATES]
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.scif = self.data_provider[Data.SCENE_ITEM_FACTS]
self.rds_conn = PSProjectConnector(self.project_name, DbUsers.CalculationEng)
self.ps_data_provider = PsDataProvider(self.data_provider, self.output)
self.kpi_static_data = self.common.get_kpi_static_data()
self.kpi_results_queries = []
self.templates_path = os.path.join(os.path.dirname(os.path.realpath(__file__)), '..', 'Data')
self.excel_file_path = os.path.join(self.templates_path, 'Template.xlsx')
self.external_targets = self.ps_data_provider.get_kpi_external_targets(
kpi_operation_types=["Target Config"],
key_fields=["product_fks", "template_fks", "product_group_fk"],
data_fields=["stacking_exclude", "min_product_facing", "best_shelf_position", "group_facings_count"]
)
def __init__(self, data_provider, output):
self.output = output
self.common = Common(data_provider)
self.data_provider = data_provider
self.project_name = self.data_provider.project_name
self.session_uid = self.data_provider.session_uid
self.manufacturer_fk = None if self.data_provider[Data.OWN_MANUFACTURER]['param_value'].iloc[0] is None else \
int(self.data_provider[Data.OWN_MANUFACTURER]['param_value'].iloc[0])
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].merge(
self.data_provider[Data.ALL_TEMPLATES][[
'template_fk', 'template_name'
]],
on='template_fk',
how='left')
self.store_id = self.data_provider[Data.STORE_FK]
self.store_info = self.data_provider[Data.STORE_INFO]
self.store_type = self.store_info['store_type'].iloc[0]
self.segmentation = self.store_info['additional_attribute_2'].iloc[0]
self.scif = self.data_provider[Data.SCENE_ITEM_FACTS]
self.rds_conn = PSProjectConnector(self.project_name,
DbUsers.CalculationEng)
self.tools = CCMYGENERALToolBox(self.data_provider,
self.output,
rds_conn=self.rds_conn)
self.kpi_static_data = self.get_kpi_static_data()
self.kpi_static_data_new = self.common.get_new_kpi_static_data()
self.template_data = pd.read_excel(TEMPLATE_PATH, 'KPIs').fillna('')
self.kpi_results_queries = []
def __init__(self, data_provider, output=None):
self.data_provider = data_provider
self.output = output
self.project_name = data_provider.project_name
self.session_uid = self.data_provider.session_uid
self.common = Common(data_provider)
self.scene_tool_box = CCUS_SANDSceneToolBox(self.data_provider, self.output, self.common)
class Generator:
def __init__(self, data_provider, output):
self.data_provider = data_provider
self.output = output
self.project_name = data_provider.project_name
self.session_uid = self.data_provider.session_uid
self.common = Common(data_provider)
self.tool_box = MONDELEZUSToolBox(self.data_provider, self.output,
self.common)
self.cstore_tool_box = CSTOREToolBox(self.data_provider, self.output,
self.common)
self.sos_tool_box = MONDELEZUSSOSToolBox(self.data_provider,
self.output, self.common)
@log_runtime('Total Calculations', log_start=True)
def main_function(self):
"""
This is the main KPI calculation function.
It calculates the score for every KPI set and saves it to the DB.
"""
if self.tool_box.scif.empty:
Log.warning('Scene item facts is empty for this session')
self.cstore_tool_box.main_calculation()
self.sos_tool_box.main_calculation()
for kpi_set_fk in self.tool_box.kpi_new_static_data['pk'].unique(
).tolist():
self.tool_box.main_calculation(kpi_set_fk=kpi_set_fk)
self.common.commit_results_data()
def __init__(self, data_provider, output):
self.output = output
self.data_provider = data_provider
self.common = Common(self.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.scif = self.data_provider[Data.SCENE_ITEM_FACTS]
self.rds_conn = PSProjectConnector(self.project_name,
DbUsers.CalculationEng)
self.kpi_static_data = self.common.get_kpi_static_data()
self.kpi_results_queries = []
self.manufacturer_fk = self.products['manufacturer_fk'][
self.products['manufacturer_name'] ==
'MONDELEZ INTERNATIONAL INC'].iloc[0]
self.store_assortment = pd.DataFrame()
self.assortment = Assortment(self.data_provider, common=self.common)
self.store_number = self.get_store_number()
self.ps_data_provider = PsDataProvider(self.data_provider, self.output)
self.custom_entities = self.ps_data_provider.get_custom_entities(
Const.PPG_ENTITY_TYPE_FK)
def __init__(self, data_provider, output):
self.data_provider = data_provider
self.output = output
self.common = Common(self.data_provider)
self.project_name = data_provider.project_name
self.session_uid = self.data_provider.session_uid
self.tool_box = ToolBox(self.data_provider, self.output, self.common)
class SceneGenerator:
def __init__(self, data_provider, output=None):
self.data_provider = data_provider
self.output = output
self.project_name = data_provider.project_name
self.session_uid = self.data_provider.session_uid
self.common = Common(data_provider)
self.scene_tool_box = CCUSSceneToolBox(self.data_provider, self.output, self.common)
self.pillar_scene_tool_box = PillarsSceneToolBox(self.data_provider, self.output, self.common)
@log_runtime('Total Calculations', log_start=True)
def scene_score(self):
"""
This is the main KPI calculation function.
It calculates the score for every KPI set and saves it to the DB.
"""
if self.scene_tool_box.match_product_in_scene.empty:
Log.warning('Match product in scene is empty for this scene')
else:
self.scene_tool_box.scene_score()
self.pillar_scene_tool_box.is_scene_belong_to_program()
self.common.commit_results_data(result_entity='scene')
del self.scene_tool_box
del self.pillar_scene_tool_box
def __init__(self, data_provider, output):
self.output = output
self.data_provider = data_provider
self.common = Common(self.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_info = self.data_provider[Data.STORE_INFO]
self.store_id = self.data_provider[Data.STORE_FK]
self.scif = self.data_provider[Data.SCENE_ITEM_FACTS]
self.rds_conn = PSProjectConnector(self.project_name,
DbUsers.CalculationEng)
self.match_probe_in_scene = self.get_product_special_attribute_data(
self.session_uid)
self.kpi_static_data = self.common.get_kpi_static_data()
self.kpi_results_queries = []
self.kpis_sheet = pd.read_excel(PATH, Const.KPIS).fillna("")
self.osd_rules_sheet = pd.read_excel(PATH, Const.OSD_RULES).fillna("")
self.kpi_excluding = pd.DataFrame()
self.df = pd.DataFrame()
self.tools = GENERALToolBox(self.data_provider)
self.templates = self.data_provider[Data.ALL_TEMPLATES]
self.psdataprovider = PsDataProvider(self.data_provider)
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.session_id = self.data_provider.session_id
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.scif = self.data_provider[Data.SCENE_ITEM_FACTS]
self.rds_conn = PSProjectConnector(self.project_name,
DbUsers.CalculationEng)
# self.tools = RISPARKWINEDEGENERALToolBox(
# self.data_provider, self.output, rds_conn=self.rds_conn)
# self.New_kpi_static_data = self.get_new_kpi_static_data()
self.kpi_results_new_tables_queries = []
# self.store_assortment = PSAssortmentDataProvider(self.data_provider).execute()
self.store_info = self.data_provider[Data.STORE_INFO]
self.current_date = datetime.now()
self.assortment = Assortment(self.data_provider, self.output)
self.store_assortment = self.assortment.store_assortment
self.common = Common(self.data_provider)
def run_project_calculations(self):
self.timer.start()
eye_level_data, exclusion_data = self._parse_templates_for_calculations()
common = Common(self.data_provider)
try:
jnj_generator = JNJGenerator(self.data_provider, self.output, common, exclusion_data)
self.calculate_local_assortment(jnj_generator, self.data_provider, self.output, common, exclusion_data)
# Mobile KPIs with hierarchy
jnj_generator.calculate_auto_assortment(in_balde=False, hierarchy=True,
just_primary=False, filter_sub_categories=False)
jnj_generator.eye_hand_level_sos_calculation(eye_level_data, hierarchy=True)
jnj_generator.promo_calc(hierarchy=True)
jnj_generator.lsos_with_hierarchy()
# API global KPIs
jnj_generator.linear_sos_out_of_store_discovery_report()
jnj_generator.calculate_auto_assortment(in_balde=False)
jnj_generator.promo_calc()
jnj_generator.eye_hand_level_sos_calculation(eye_level_data)
except Exception as e:
print ("Error :{}".format(e))
common.commit_results_data()
self.timer.stop('KPIGenerator.run_project_calculations')
class INBEVNLINBEVBEGenerator:
def __init__(self, data_provider, output):
self.k_engine = BaseCalculationsGroup(data_provider, output)
self.data_provider = data_provider
self.project_name = data_provider.project_name
self.output = output
self.session_uid = self.data_provider.session_uid
self.visit_date = self.data_provider[Data.VISIT_DATE]
self.rds_conn = PSProjectConnector(self.project_name, DbUsers.CalculationEng)
self.session_info = SessionInfo(data_provider)
self.store_id = self.data_provider[Data.STORE_FK]
self.common = Common(self.data_provider)
self.tool_box = INBEVToolBox(self.data_provider, self.output, common=self.common)
@log_runtime('Total Calculations', log_start=True)
def main_function(self):
"""
This is the main KPI calculation function.
It calculates the score for every KPI set and saves it to the DB.
"""
if self.tool_box.scif.empty:
Log.warning('Scene item facts is empty for this session')
return
# self.tool_box.tools.update_templates()
# set_names = ['Product Blocking', 'Linear Share of Shelf', 'OSA', 'Pallet Presence', 'Share of Assortment',
# 'Product Stacking', 'Shelf Level', 'Linear Share of Shelf vs. Target', 'Shelf Impact Score',
# 'Product Group Blocking']
# for kpi_set_name in set_names:
# self.tool_box.main_calculation(set_name=kpi_set_name)
# self.tool_box.save_custom_scene_item_facts_results()
# self.tool_box.save_linear_length_results()
# Log.info('Downloading templates took {}'.format(self.tool_box.download_time))
self.tool_box.main_calculation_poce()
self.tool_box.commit_results_data()
self.common.commit_results_data()
def __init__(self, data_provider, output):
self.output = output
self.data_provider = data_provider
self.common = Common(self.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.scif = self.data_provider[Data.SCENE_ITEM_FACTS]
self.rds_conn = PSProjectConnector(self.project_name,
DbUsers.CalculationEng)
self.kpi_static_data = self.common.get_kpi_static_data()
self.kpi_results_queries = []
self.set_up_template = pd.read_excel(os.path.join(
os.path.dirname(os.path.realpath(__file__)), '..', 'Data',
'gsk_set_up.xlsx'),
sheet_name='Functional KPIs',
keep_default_na=False)
self.gsk_generator = GSKGenerator(self.data_provider, self.output,
self.common, self.set_up_template)
def __init__(self, data_provider, output):
self.output = output
self.data_provider = data_provider
self.common = Common(self.data_provider)
self.templates_path = os.path.join(
os.path.dirname(os.path.realpath(__file__)), '..', 'Data')
self.excel_file_path = os.path.join(self.templates_path,
'Template.xlsx')
self.project_name = self.data_provider.project_name
self.session_uid = self.data_provider.session_uid
self.products = self.data_provider[Data.PRODUCTS]
self.templates = self.data_provider[Data.TEMPLATES]
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_name = self.store_info.store_name[0]
self.scif = self.data_provider[Data.SCENE_ITEM_FACTS]
self.rds_conn = PSProjectConnector(self.project_name,
DbUsers.CalculationEng)
self.kpi_static_data = self.common.get_kpi_static_data()
self.kpi_results_queries = []
self.empty_product_ids = self.all_products.query(
'product_name.str.contains("empty", case=False) or'
' product_name.str.contains("irrelevant", case=False)',
engine='python')['product_fk'].values
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 __init__(self, data_provider, output):
self.output = output
self.data_provider = data_provider
self.common = Common(self.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.scif = self.data_provider[Data.SCENE_ITEM_FACTS]
self.ps_data_provider = PsDataProvider(self.data_provider, self.output)
self.manufacturer_fk = None if self.data_provider[Data.OWN_MANUFACTURER]['param_value'].iloc[0] is None else \
int(self.data_provider[Data.OWN_MANUFACTURER]['param_value'].iloc[0])
self.set_up_template = pd.read_excel(os.path.join(
os.path.dirname(os.path.realpath(__file__)), '..', 'Data',
'gsk_set_up.xlsx'),
sheet_name='Functional KPIs',
keep_default_na=False)
self.gsk_generator = GSKGenerator(self.data_provider, self.output,
self.common, self.set_up_template)
self.targets = self.ps_data_provider.get_kpi_external_targets()
self.sequence = Sequence(self.data_provider)
self.set_up_data = {
('planogram', Const.KPI_TYPE_COLUMN): Const.NO_INFO,
('secondary_display', Const.KPI_TYPE_COLUMN): Const.NO_INFO,
('promo', Const.KPI_TYPE_COLUMN): Const.NO_INFO
}
class Generator:
# SUPER_CATS = ['Yogurt', 'RBG', 'Mexican', 'Soup']
SUPER_CATS = ['Yogurt', 'RBG', 'Soup', 'Mexican']
# SUPER_CATS = ['Mexican'] # Overwriting for testing purposes
SUPER_CATS = ['Snacks', 'Yogurt']
def __init__(self, data_provider, output):
self.data_provider = data_provider
self.output = output
self.common = Common(self.data_provider)
self.project_name = data_provider.project_name
self.session_uid = self.data_provider.session_uid
self.toolboxes = {}
self.load_toolboxes()
@log_runtime('Total Calculations', log_start=True)
def main_function(self):
for cat in self.SUPER_CATS:
if self.toolboxes[cat].scif.empty:
Log.warning('Distribution is empty for this session')
continue
template_path = self.find_template(cat)
# ResultUploader(self.project_name, template_path)
# EntityUploader(self.project_name, template_path)
# AtomicFarse(self.project_name, template_path)
self.toolboxes[cat].main_calculation(template_path)
self.common.commit_results_data()
def load_toolboxes(self):
ToolBox = 'imma lazy and no like red lines'
for cat in self.SUPER_CATS:
exec('from Projects.GMIUS.{0}.Utils.KPIToolBox import ToolBox'.
format(cat))
self.toolboxes[cat] = ToolBox(self.data_provider, self.output,
self.common)
def find_template(self, cat):
''' screw maintaining 4 hardcoded template paths... '''
path = os.path.join(os.path.dirname(os.path.realpath(__file__)),
'Data')
files = os.listdir(path)
candidates = [
f for f in files
if f.split(' ')[0] == cat and f.split('.')[-1] == 'xlsx'
]
versioned_candidates = []
all_vers = []
for x in candidates:
all_vers += x.split(' v')[-1].replace('.xlsx', '').split('.')
max_digits = len(max(all_vers, key=len))
for x in candidates:
version_comps = x.split(' v')[-1].replace('.xlsx', '').split('.')
normed_components = []
for i, comp in enumerate(version_comps):
norm_comp = int(comp) * 10**max_digits
normed_components.append(str(norm_comp))
versioned_candidates.append((float(''.join(normed_components)), x))
template = sorted(versioned_candidates, key=lambda x: x[0])[-1][1]
return os.path.join(path, template)
def __init__(self, data_provider, output):
self.data_provider = data_provider
self.output = output
self.common = Common(self.data_provider)
self.project_name = data_provider.project_name
self.session_uid = self.data_provider.session_uid
self.toolboxes = {}
self.load_toolboxes()
def __init__(self, data_provider, rds_conn=None):
self.data_provider = data_provider
self.common = Common(self.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] # initial 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.all_templates = self.data_provider[Data.ALL_TEMPLATES]
self.scif = self.data_provider[Data.SCENE_ITEM_FACTS] # initial scif
self.rds_conn = PSProjectConnector(
self.project_name,
DbUsers.CalculationEng) if rds_conn is None else rds_conn
self.complete_scif_data()
self.store_areas = self.get_store_areas()
self.kpi_static_data = self.common.get_kpi_static_data()
self.kpi_results_queries = []
self.full_store_info = self.get_store_data_by_store_id()
self.store_info_dict = self.full_store_info.to_dict('records')[0]
self.store_policy_exclusion_template = self.get_store_policy_data_for_exclusion_template(
)
self.displays_template = self.get_display_parameters()
self.toolbox = GENERALToolBox(data_provider)
self.custom_entities = self.get_custom_entity_data()
self.on_display_products = self.get_on_display_products()
self.exclusion_template = self.get_exclusion_template_data()
self.filtered_scif = self.scif # filtered scif acording to exclusion template
self.filtered_matches = self.match_product_in_scene # filtered scif according to exclusion template
self.set_filtered_scif_and_matches_for_all_kpis(
self.scif, self.match_product_in_scene)
self.scene_bay_shelf_product = self.get_facings_scene_bay_shelf_product(
)
self.external_targets = self.get_all_kpi_external_targets()
self.all_targets_unpacked = self.unpack_all_external_targets()
self.kpi_result_values = self.get_kpi_result_values_df()
self.kpi_score_values = self.get_kpi_score_values_df()
# self.displays_template = self.get_display_parameters()
self.full_pallet_len = self.displays_template[self.displays_template[self.DISPLAY_NAME_TEMPL] == \
'HO Agreed Full Pallet'][self.SHELF_LEN_DISPL].values[0]
self.half_pallet_len = self.displays_template[self.displays_template[self.DISPLAY_NAME_TEMPL] == \
'HO Agreed Half Pallet'][self.SHELF_LEN_DISPL].values[0]
self.shelf_len_mixed_shelves = self.calculate_shelf_len_for_mixed_shelves(
)
self.scene_display = self.get_match_display_in_scene()
self.assign_bays_to_bins()
self.filtered_scif_secondary = self.get_initial_secondary_scif()
self.filtered_matches_secondary = self.get_initial_secondary_matches()
self.set_filtered_scif_and_matches_for_all_kpis_secondary(
self.filtered_scif_secondary, self.filtered_matches_secondary)
def __init__(self, data_provider, output, common=None):
self.output = output
self.data_provider = data_provider
# self.common = common
self.common = Common(self.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.templates = self.data_provider[Data.TEMPLATES]
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] if self.data_provider[Data.STORE_FK] is not None \
else self.session_info['store_fk'].values[0]
self.all_templates = self.data_provider[Data.ALL_TEMPLATES]
self.store_type = self.data_provider.store_type
self.rds_conn = PSProjectConnector(self.project_name,
DbUsers.CalculationEng)
self.kpi_static_data = self.common.get_kpi_static_data()
self.kpi_results_queries = []
self.scif = self.data_provider[Data.SCENE_ITEM_FACTS]
self.probe_groups = self.get_probe_group()
self.match_product_in_scene = self.match_product_in_scene.merge(
self.probe_groups, on='probe_match_fk', how='left')
self.is_solid_scene = True if len(self.probe_groups['probe_group_id'].
unique().tolist()) <= 1 else False
self.toolbox = GENERALToolBox(self.data_provider)
self.commontools = PEPSICOUKCommonToolBox(self.data_provider,
self.rds_conn)
self.custom_entities = self.commontools.custom_entities
self.on_display_products = self.commontools.on_display_products
self.exclusion_template = self.commontools.exclusion_template
self.filtered_scif = self.commontools.filtered_scif
self.filtered_matches = self.commontools.filtered_matches
self.excluded_matches = self.compare_matches()
self.filtered_matches = self.filtered_matches.merge(
self.probe_groups, on='probe_match_fk', how='left')
self.scene_bay_shelf_product = self.commontools.scene_bay_shelf_product
self.external_targets = self.commontools.external_targets
self.own_manuf_fk = self.all_products[
self.all_products['manufacturer_name'] ==
self.PEPSICO]['manufacturer_fk'].values[0]
self.block = Block(self.data_provider,
custom_scif=self.filtered_scif,
custom_matches=self.filtered_matches)
self.adjacency = Adjancency(self.data_provider,
custom_scif=self.filtered_scif,
custom_matches=self.filtered_matches)
self.block_results = pd.DataFrame(columns=['Group Name', 'Score'])
self.kpi_results = pd.DataFrame(
columns=['kpi_fk', 'numerator', 'denominator', 'result', 'score'])
self.passed_blocks = {}
def __init__(self, output, data_provider):
super(PepsicoUtil, self).__init__(data_provider)
self.output = output
self.common = Common(self.data_provider)
# self.common_v1 = CommonV1(self.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] if self.data_provider[Data.STORE_FK] is not None \
else self.session_info['store_fk'].values[0]
self.scif = self.data_provider[Data.SCENE_ITEM_FACTS]
self.rds_conn = PSProjectConnector(self.project_name, DbUsers.CalculationEng)
self.display_scene = self.get_match_display_in_scene()
self.kpi_static_data = self.common.get_kpi_static_data()
self.kpi_results_queries = []
self.probe_groups = self.get_probe_group()
self.match_product_in_scene = self.match_product_in_scene.merge(self.probe_groups, on='probe_match_fk',
how='left')
self.toolbox = GENERALToolBox(self.data_provider)
self.commontools = PEPSICOUKCommonToolBox(self.data_provider, self.rds_conn)
self.all_templates = self.commontools.all_templates
self.custom_entities = self.commontools.custom_entities
self.on_display_products = self.commontools.on_display_products
self.exclusion_template = self.commontools.exclusion_template
self.filtered_scif = self.commontools.filtered_scif.copy()
self.filtered_matches = self.commontools.filtered_matches.copy()
self.filtered_matches = self.filtered_matches.merge(self.probe_groups, on='probe_match_fk', how='left')
self.filtered_scif_secondary = self.commontools.filtered_scif_secondary.copy()
self.filtered_matches_secondary = self.commontools.filtered_matches_secondary.copy()
self.scene_bay_shelf_product = self.commontools.scene_bay_shelf_product
self.ps_data = PsDataProvider(self.data_provider, self.output)
self.full_store_info = self.commontools.full_store_info.copy()
self.external_targets = self.commontools.external_targets
self.assortment = Assortment(self.commontools.data_provider, self.output)
self.lvl3_ass_result = self.get_lvl3_relevant_assortment_result()
self.own_manuf_fk = self.all_products[self.all_products['manufacturer_name'] == self.PEPSICO]['manufacturer_fk'].values[0]
self.scene_kpi_results = self.get_results_of_scene_level_kpis()
self.kpi_results_check = pd.DataFrame(columns=['kpi_fk', 'numerator', 'denominator', 'result', 'score',
'context'])
self.sos_vs_target_targets = self.construct_sos_vs_target_base_df()
self.all_targets_unpacked = self.commontools.all_targets_unpacked.copy()
self.block_results = pd.DataFrame(columns=['Group Name', 'Score'])
self.hero_type_custom_entity_df = self.get_hero_type_custom_entity_df()
def __init__(self, data_provider, rds_conn, targets_from_template):
self.data_provider = data_provider
self.common = Common(self.data_provider)
self.rds_conn = rds_conn
self.visit_date = self.data_provider[Data.VISIT_DATE]
self.all_products = data_provider['all_products']
self.targets_from_template = targets_from_template
self.ext_targets = self.get_all_kpi_external_targets()
self.ext_targets = self.post_process_ext_targets(self.ext_targets)
self.session_uid = self.data_provider.session_uid
self.is_old_visit = self.check_if_the_current_session_has_json()
def __init__(self, data_provider, output):
self.k_engine = BaseCalculationsGroup(data_provider, output)
self.data_provider = data_provider
self.project_name = data_provider.project_name
self.output = output
self.session_uid = self.data_provider.session_uid
self.visit_date = self.data_provider[Data.VISIT_DATE]
self.rds_conn = PSProjectConnector(self.project_name, DbUsers.CalculationEng)
self.session_info = SessionInfo(data_provider)
self.store_id = self.data_provider[Data.STORE_FK]
self.common = Common(self.data_provider)
self.tool_box = INBEVToolBox(self.data_provider, self.output, common=self.common)
