def get_excel_data(self, location):
aggregation_level = self.loc_level
filters = {}
filters[
'aggregation_level'] = aggregation_level # this report is needed district wise only
export_filters = [['Generated at', india_now()]]
if location:
try:
locs = SQLLocation.objects.get(
location_id=location).get_ancestors(include_self=True)
for loc in locs:
export_filters.append(
[loc.location_type.name.title(), loc.name])
location_key = '%s_id' % loc.location_type.code
filters.update({
location_key: loc.location_id,
})
except SQLLocation.DoesNotExist:
pass
order_by = ('state_name', 'district_name')
if self.report_type == 'month':
filters['month'] = self.config['month']
excel_rows = self.month_wise(filters, order_by)
else:
filters['month__in'] = generate_quarter_months(
self.quarter, self.year)
excel_rows = self.quarter_wise(filters, order_by,
aggregation_level)
export_filters.append(['Report Layout', self.layout.title()])
export_filters.append(['Data Period', self.report_type.title()])
return [[self.title, excel_rows], ['Export Info', export_filters]]
def get_poshan_progress_dashboard_data(domain,
year,
month,
quarter,
data_period,
step,
location_filters,
include_test=False,
beta=False):
aggregation_level = location_filters.get('aggregation_level', 1)
filters = location_filters
value_fields = PPR_COLS_TO_FETCH[:]
unique_id = ''
if data_period == 'month':
filters['month'] = date(year, month, 1)
else:
months = generate_quarter_months(quarter, year)
if aggregation_level == 1:
unique_id = 'state_id'
value_fields.append('state_id')
else:
unique_id = 'district_id'
value_fields.append('district_id')
# including only launched states and districts
filters['num_launched_awcs__gt'] = 0
order_by = ('state_name', 'district_name')
if aggregation_level == 1:
value_fields.remove('district_name')
response = {}
if step == 'aggregated':
value_fields.append('num_launched_states')
if data_period == 'month':
data = fetch_month_data(value_fields, order_by, filters,
include_test, domain)
else:
data = fetch_quarter_data(value_fields, order_by, filters,
include_test, domain, months,
data_period, unique_id)
response = calculate_aggregated_row(data, aggregation_level, beta)
elif step == 'comparative':
if data_period == 'month':
data = fetch_month_data(value_fields, order_by, filters,
include_test, domain)
else:
data = fetch_quarter_data(value_fields, order_by, filters,
include_test, domain, months,
data_period, unique_id)
response = calculate_comparative_rows(data, aggregation_level, beta)
return response
def get_poshan_progress_dashboard_data(domain,
year,
month,
quarter,
data_format,
step,
location_filters,
include_test=False):
aggregation_level = location_filters.get('aggregation_level', 1)
filters = location_filters
value_fields = PPR_COLS_TO_FETCH[:]
unique_id = ''
if data_format == 'month':
filters['month'] = date(year, month, 1)
else:
filters['month__in'] = generate_quarter_months(quarter, year)
if aggregation_level == 1:
unique_id = 'state_id'
value_fields.append('state_id')
else:
unique_id = 'district_id'
value_fields.append('district_id')
order_by = ('state_name', 'district_name')
if aggregation_level == 1:
value_fields.remove('district_name')
response = {}
queryset = PoshanProgressReportView.objects.filter(**filters).order_by(
*order_by)
if not include_test:
queryset = apply_exclude(domain, queryset)
if step == 'aggregated':
data = queryset.aggregate(
num_launched_states=Sum('num_launched_states'),
num_launched_districts=Sum('num_launched_districts'),
num_launched_blocks=Sum('num_launched_blocks'),
num_launched_awcs=Sum('num_launched_awcs'),
awc_days_open=Sum('awc_days_open'),
expected_visits=Sum('expected_visits'),
valid_visits=Sum('valid_visits'),
pse_eligible=Sum('pse_eligible'),
pse_attended_21_days=Sum('pse_attended_21_days'),
wer_eligible=Sum('wer_eligible'),
wer_weighed=Sum('wer_weighed'),
trimester_3=Sum('trimester_3'),
counsel_immediate_bf=Sum('counsel_immediate_bf'),
height_eligible=Sum('height_eligible'),
height_measured_in_month=Sum('height_measured_in_month'),
thr_eligible=Sum('thr_eligible'),
thr_rations_21_plus_distributed=Sum(
'thr_rations_21_plus_distributed'),
lunch_eligible=Sum('lunch_eligible'),
lunch_count_21_days=Sum('lunch_count_21_days'),
)
response = calculate_aggregated_row(data, aggregation_level,
data_format)
elif step == 'comparative':
data = queryset.values(*value_fields)
response = calculate_comparative_rows(deepcopy(data),
aggregation_level, data_format,
unique_id)
return response