def test_check_weighted_average_1(self):
test_case = 'test_check_weighted_average_1'
self.mock_data_provider()
self.mock_tool_box()
tool_box = CCRUKPIToolBox(self.data_provider, self.output)
tool_box.set_kpi_set(self.data.pos_kpi_set_name,
self.data.pos_kpi_set_type)
params, check_result = self.get_pos_test_case(test_case)
test_result = tool_box.check_weighted_average(params)
self.assertEquals(round(check_result, 6), round(test_result, 6))
class CCRUProjectCalculations:
def __init__(self, data_provider, output):
self.data_provider = data_provider
self.output = output
self.project_name = self.data_provider.project_name
self.rds_conn = self.rds_connection()
self.tool_box = CCRUKPIToolBox(self.data_provider,
self.output,
update_kpi_set=True)
self.session_uid = self.tool_box.session_uid
self.visit_date = self.tool_box.visit_date
self.store_id = self.tool_box.store_id
self.test_store = self.tool_box.test_store
self.pos_kpi_set_name = self.tool_box.pos_kpi_set_name
self.session_info = SessionInfo(data_provider)
self.json = CCRUJsonGenerator()
self.results = {}
self.kpi_source_json = None
def main_function(self):
if str(self.visit_date) < self.tool_box.MIN_CALC_DATE:
Log.warning('Warning. Session cannot be calculated. '
'Visit date is less than {2} - {0}. '
'Store ID {1}.'.format(self.visit_date, self.store_id,
self.tool_box.MIN_CALC_DATE))
return
elif self.tool_box.visit_type in [self.tool_box.SEGMENTATION_VISIT]:
Log.warning(
'Warning. Session with Segmentation visit type has no KPI calculations.'
)
return
elif self.tool_box.visit_type in [self.tool_box.PROMO_VISIT]:
self.calculate_promo_compliance()
return
else:
if self.pos_kpi_set_name not in self.tool_box.ALLOWED_POS_SETS:
Log.warning(
'Warning. Session cannot be calculated. '
'POS KPI Set name in store attribute is invalid - {0}. '
'Store ID {1}.'.format(self.pos_kpi_set_name,
self.store_id))
else:
self.calculate_red_score()
if self.tool_box.visit_type in [self.tool_box.STANDARD_VISIT]:
if not self.tool_box.cooler_assortment.empty:
self.tool_box.set_kpi_set(CCRUConsts.COOLER_AUDIT_SCORE,
CCRUConsts.COOLER_AUDIT_SCORE)
self.calculate_cooler_audit()
Log.debug('KPI calculation stage: {}'.format('Committing results old'))
self.tool_box.commit_results_data_old()
Log.debug('KPI calculation stage: {}'.format('Committing results new'))
self.tool_box.commit_results_data_new()
Log.debug('KPI calculation is completed')
def calculate_red_score(self):
kpi_source_json = self.json.create_kpi_source('KPI_Source.xlsx',
self.pos_kpi_set_name)
kpi_source = {}
for row in kpi_source_json:
# Log.info('SOURCE: {}'.format(row.get(SOURCE)))
kpi_source[row.pop(SOURCE)] = row
if kpi_source:
pass
# elif self.test_store == "Y":
# Log.warning('Warning. Session cannot be calculated: '
# 'Store is a test store. '
# 'Store ID {1}.'
# .format(self.pos_kpi_set_name, self.store_id))
# return
else:
Log.warning(
'Warning. Session cannot be calculated. '
'POS KPI Set name in store attribute is invalid - {0}. '
'Store ID {1}.'.format(self.pos_kpi_set_name, self.store_id))
return
mr_targets = {}
for kpi_set, params in kpi_source.items():
if params.get(MR_TARGET) is not None:
mr_targets.update({kpi_set: params[MR_TARGET]})
mr_targets.update({params[SET]: params[MR_TARGET]})
self.tool_box.mr_targets = mr_targets
kpi_sets_types_to_calculate = [POS] # SPIRITS are excluded
for kpi_set_type in kpi_sets_types_to_calculate:
if kpi_source[kpi_set_type][SET]:
Log.debug('KPI calculation stage: {}'.format(
kpi_source[kpi_set_type][SET]))
self.tool_box.set_kpi_set(kpi_source[kpi_set_type][SET],
kpi_set_type)
self.json.project_kpi_dict['kpi_data'] = []
self.json.create_kpi_data_json(
'kpi_data',
kpi_source[kpi_set_type][FILE],
sheet_name=kpi_source[kpi_set_type][SHEET],
pos_kpi_set_name=self.pos_kpi_set_name)
self.calculate_red_score_kpi_set(
self.json.project_kpi_dict.get('kpi_data')[0],
kpi_source[kpi_set_type][SET],
mr_targets.get(kpi_set_type))
if kpi_source[GAPS][SET]:
Log.debug('KPI calculation stage: {}'.format(
kpi_source[GAPS][SET]))
self.tool_box.set_kpi_set(kpi_source[GAPS][SET], GAPS)
self.json.create_kpi_data_json('gaps',
kpi_source[GAPS][FILE],
sheet_name=kpi_source[GAPS][SHEET])
self.tool_box.calculate_gaps_old(
self.json.project_kpi_dict.get('gaps'))
self.tool_box.calculate_gaps_new(
self.json.project_kpi_dict.get('gaps'), kpi_source[GAPS][SET])
if kpi_source[BENCHMARK][SET]:
Log.debug('KPI calculation stage: {}'.format(
kpi_source[BENCHMARK][SET]))
self.tool_box.set_kpi_set(kpi_source[BENCHMARK][SET], BENCHMARK)
self.json.create_kpi_data_json(
'benchmark',
kpi_source[BENCHMARK][FILE],
sheet_name=kpi_source[BENCHMARK][SHEET])
self.tool_box.calculate_benchmark(
self.json.project_kpi_dict.get('benchmark'),
kpi_source[BENCHMARK][SET])
if kpi_source[CONTRACT][FILE]:
Log.debug('Importing Contract Execution template')
self.json.create_kpi_data_json(
'contract',
kpi_source[CONTRACT][FILE],
sheet_name=kpi_source[CONTRACT][SHEET])
if kpi_source[TOPSKU][SET]:
Log.debug('KPI calculation stage: {}'.format(
kpi_source[TOPSKU][SET]))
include_to_contract = True if self.json.project_kpi_dict.get(
'contract') else False
self.tool_box.set_kpi_set(kpi_source[TOPSKU][SET], TOPSKU)
self.tool_box.calculate_top_sku(include_to_contract,
kpi_source[TOPSKU][SET])
if self.json.project_kpi_dict.get('contract'):
if kpi_source[EQUIPMENT][SET]:
equipment_target_data = self.tool_box.get_equipment_target_data(
)
if equipment_target_data:
if kpi_source[TARGET][SET]:
Log.debug('KPI calculation stage: {}'.format(
kpi_source[TARGET][SET]))
self.tool_box.set_kpi_set(kpi_source[TARGET][SET],
TARGET)
self.json.project_kpi_dict['kpi_data'] = []
self.json.create_kpi_data_json(
'kpi_data',
kpi_source[TARGET][FILE],
sheet_name=kpi_source[TARGET][SHEET])
self.calculate_red_score_kpi_set(
self.json.project_kpi_dict.get('kpi_data')[0],
kpi_source[TARGET][SET])
Log.debug('KPI calculation stage: {}'.format(
kpi_source[EQUIPMENT][SET]))
self.tool_box.set_kpi_set(kpi_source[EQUIPMENT][SET],
EQUIPMENT)
self.tool_box.calculate_equipment_execution(
self.json.project_kpi_dict.get('contract'),
kpi_source[EQUIPMENT][SET],
kpi_source[KPI_CONVERSION][FILE],
equipment_target_data)
if kpi_source[CONTRACT][SET]:
Log.debug('KPI calculation stage: {}'.format(
kpi_source[CONTRACT][SET]))
self.tool_box.set_kpi_set(kpi_source[CONTRACT][SET], CONTRACT)
self.tool_box.calculate_contract_execution(
self.json.project_kpi_dict.get('contract'),
kpi_source[CONTRACT][SET])
# Log.debug('KPI calculation stage: {}'.format('Committing results old'))
# self.tool_box.commit_results_data_old()
#
# Log.debug('KPI calculation stage: {}'.format('Committing results new'))
# self.tool_box.commit_results_data_new()
def calculate_red_score_kpi_set(self,
kpi_data,
kpi_set_name,
set_target=None):
score = 0
score += self.tool_box.check_availability(kpi_data)
score += self.tool_box.check_facings_sos(kpi_data)
score += self.tool_box.check_share_of_cch(kpi_data)
score += self.tool_box.check_number_of_skus_per_door_range(kpi_data)
score += self.tool_box.check_number_of_doors(kpi_data)
score += self.tool_box.check_number_of_scenes(kpi_data)
score += self.tool_box.check_number_of_scenes_no_tagging(kpi_data)
score += self.tool_box.check_customer_cooler_doors(kpi_data)
score += self.tool_box.check_atomic_passed(kpi_data)
score += self.tool_box.check_atomic_passed_on_the_same_scene(kpi_data)
score += self.tool_box.check_sum_atomics(kpi_data)
score += self.tool_box.check_dummies(kpi_data)
score += self.tool_box.check_weighted_average(kpi_data)
score += self.tool_box.check_kpi_scores(kpi_data)
score = round(float(score), 3)
self.tool_box.create_kpi_groups(kpi_data.values()[0])
self.tool_box.write_to_kpi_results_old(
pd.DataFrame(
[(kpi_set_name, self.session_uid, self.store_id,
self.visit_date.isoformat(), format(score, '.3f'), None)],
columns=[
'kps_name', 'session_uid', 'store_fk', 'visit_date',
'score_1', 'kpi_set_fk'
]), 'level1')
set_target = set_target if set_target is not None else 100
self.tool_box.update_kpi_scores_and_results(
{
'KPI ID': 0,
'KPI name Eng': kpi_set_name,
'KPI name Rus': kpi_set_name,
'Parent': 'root'
}, {
'target': set_target,
'weight': None,
'result': score,
'score': score,
'weighted_score': score,
'level': 0
})
# INTEGRATION is excluded from calculation starting 2020
#
# if kpi_set_type == POS:
# Log.debug('KPI calculation stage: {}'.format(kpi_source[INTEGRATION][SET]))
# self.tool_box.prepare_hidden_set(kpi_data, kpi_source[INTEGRATION][SET])
def calculate_promo_compliance(self):
self.json.create_kpi_data_json('promo',
'KPI_Promo_Tracking.xlsx',
sheet_name='2019')
kpi_data = self.json.project_kpi_dict.get('promo')
Log.debug('KPI calculation stage: {}'.format('Promo Compliance'))
self.tool_box.calculate_promo_compliance_store(kpi_data)
Log.debug('KPI calculation stage: {}'.format('Committing results new'))
self.tool_box.common.commit_results_data()
def calculate_cooler_audit(self):
self.json.create_kpi_data_json('cooler_audit',
'Cooler_Quality.xlsx',
sheet_name='ALL')
kpi_data = self.json.project_kpi_dict.get('cooler_audit')[0]
group_model_map = pd.read_excel(os.path.join(self.json.base_path,
'Cooler_Quality.xlsx'),
sheet_name=GROUP_MODEL_MAP)
self.tool_box.calculate_cooler_kpis(kpi_data, group_model_map)
def rds_connection(self):
if not hasattr(self, '_rds_conn'):
self._rds_conn = PSProjectConnector(self.project_name,
DbUsers.CalculationEng)
try:
pd.read_sql_query('select pk from probedata.session limit 1',
self._rds_conn.db)
except:
self._rds_conn.disconnect_rds()
self._rds_conn = PSProjectConnector(self.project_name,
DbUsers.CalculationEng)
return self._rds_conn