def hsas_with_stock(instance):
"""
HSA with adequate stock, by District and group
"""
ps = ProductStock.objects.select_related().filter(quantity__gt=0, product__sms_code__in=PRODUCT_CODES)
em = get_em_districts()
ept = get_ept_districts()
em_reports = {}
ept_reports = {}
em_totals = {}
ept_totals = {}
em_users = {}
ept_users = {}
em_total_u = {}
ept_total_u ={}
# There is just no good way to do this. The performance here is going to suck and there's no way around it.
for p in PRODUCT_CODES:
em_totals[p] = 0
ept_totals[p] = 0
em_total_u[p] = 0
ept_total_u[p] = 0
for d in em:
em_reports[d] = {}
em_users[d] = {}
for p in PRODUCT_CODES:
em_reports[d][p] = len([px for px in ps.filter(product__sms_code=p, supply_point__in=hsa_supply_points_below(d)) if px.is_in_adequate_supply()])
em_users[d][p] = len([px for px in ps.filter(product__sms_code=p, supply_point__in=hsa_supply_points_below(d))])
em_totals[p] += em_reports[d][p]
em_total_u[p] += em_users[d][p]
for d in ept:
ept_reports[d] = {}
ept_users[d] = {}
for p in PRODUCT_CODES:
ept_reports[d][p] = len([px for px in ps.filter(product__sms_code=p, supply_point__in=hsa_supply_points_below(d)) if px.is_in_adequate_supply()])
ept_users[d][p] = len([px for px in ps.filter(product__sms_code=p, supply_point__in=hsa_supply_points_below(d))])
ept_totals[p] += ept_reports[d][p]
ept_total_u[p] += ept_users[d][p]
instance.datespan = None
return _common_report(instance, {'product_codes': PRODUCT_CODES,
'em_reports':em_reports,
'em_users':em_users,
'ept_reports':ept_reports,
'ept_users':ept_users,
'em_totals':em_totals,
'ept_totals':ept_totals,
'em_total_u':em_total_u,
'ept_total_u':ept_total_u})
def em_late_reporting(instance):
"""
HSAs who reported late (after 2nd of the month), by District
"""
districts = get_em_districts()
reports = SortedDict()
totals = defaultdict(lambda: 0)
for d in districts:
bd = ReportingBreakdown(hsa_supply_points_below(d),
instance.datespan,
include_late=True,
days_for_late=settings.LOGISTICS_DAYS_UNTIL_LATE_PRODUCT_REPORT,
MNE=True)
reports[d] = _to_totals(bd)
_update_dict(totals, reports[d])
return _common_report(instance, {"reports": reports, "totals": totals})
def em_late_reporting(instance):
"""
HSAs who reported late (after 2nd of the month), by District
"""
districts = get_em_districts()
reports = SortedDict()
totals = defaultdict(lambda: 0)
for d in districts:
bd = ReportingBreakdown(
hsa_supply_points_below(d),
instance.datespan,
include_late=True,
days_for_late=settings.LOGISTICS_DAYS_UNTIL_LATE_PRODUCT_REPORT,
MNE=True)
reports[d] = _to_totals(bd)
_update_dict(totals, reports[d])
return _common_report(instance, {"reports": reports, "totals": totals})
def _district_breakdown(datespan, facility=False):
"""
Breakdown of reporting information, by group and district
"""
em = get_em_districts()
ept = get_ept_districts()
em_reports = SortedDict()
ept_reports = SortedDict()
em_totals = defaultdict(lambda: 0)
ept_totals = defaultdict(lambda: 0)
em_totals.update({'no_stockouts_pct_p':{},
'no_stockouts_p':{},
'stockouts_duration_p':{},
'stockouts_avg_duration_p':{},
'totals_p':{},
'discrepancies_p': {},
'discrepancies_tot_p': {},
'discrepancies_pct_p': {},
'discrepancies_avg_p': {},
'filled_orders_p': {},
'req_times':[]})
ept_totals.update({'no_stockouts_pct_p':{},
'no_stockouts_p':{},
'stockouts_duration_p':{},
'stockouts_avg_duration_p':{},
'totals_p':{},
'discrepancies_p': {},
'discrepancies_pct_p': {},
'discrepancies_tot_p': {},
'discrepancies_avg_p': {},
'filled_orders_p': {},
'req_times':[]})
for d in em:
if facility:
bd = ReportingBreakdown(facility_supply_points_below(d),
datespan, MNE=True)
else:
bd = ReportingBreakdown(hsa_supply_points_below(d),
datespan, MNE=True)
em_reports[d] = _to_totals(bd)
_update_dict(em_totals, em_reports[d])
em_totals['req_times'] += bd.req_times
em_reports[d]['no_stockouts_pct_p'] = bd.no_stockouts_pct_p
em_reports[d]['no_stockouts_p'] = bd.no_stockouts_p
em_reports[d]['totals_p'] = bd.totals_p
em_reports[d]['avg_req_time'] = bd.avg_req_time
em_reports[d]['discrepancies_pct_p'] = bd.discrepancies_pct_p
em_reports[d]['discrepancies_avg_p'] = bd.discrepancies_avg_p
em_reports[d]['discrepancies_tot_p'] = bd.discrepancies_tot_p
em_reports[d]['discrepancies_p'] = bd.discrepancies_p
em_reports[d]['stockouts_duration_p'] = bd.stockouts_duration_p
em_reports[d]['stockouts_avg_duration_p'] = bd.stockouts_avg_duration_p
_update_dict(em_totals['stockouts_duration_p'], bd.stockouts_duration_p)
_update_dict(em_totals['no_stockouts_p'], bd.no_stockouts_p)
_update_dict(em_totals['discrepancies_p'], bd.discrepancies_p)
_update_dict(em_totals['discrepancies_tot_p'], bd.discrepancies_tot_p)
_update_dict(em_totals['filled_orders_p'], bd.filled_orders_p)
_update_dict(em_totals['totals_p'], bd.totals_p)
for d in ept:
if facility:
bd = ReportingBreakdown(facility_supply_points_below(d),
datespan, MNE=True)
else:
bd = ReportingBreakdown(hsa_supply_points_below(d),
datespan, MNE=True)
ept_reports[d] = _to_totals(bd)
_update_dict(ept_totals, ept_reports[d])
ept_totals['req_times'] += bd.req_times
ept_reports[d]['no_stockouts_pct_p'] = bd.no_stockouts_pct_p
ept_reports[d]['no_stockouts_p'] = bd.no_stockouts_p
ept_reports[d]['totals_p'] = bd.totals_p
ept_reports[d]['discrepancies_pct_p'] = bd.discrepancies_pct_p
ept_reports[d]['discrepancies_avg_p'] = bd.discrepancies_avg_p
ept_reports[d]['discrepancies_tot_p'] = bd.discrepancies_tot_p
ept_reports[d]['discrepancies_p'] = bd.discrepancies_p
ept_reports[d]['avg_req_time'] = bd.avg_req_time
ept_reports[d]['stockouts_duration_p'] = bd.stockouts_duration_p
ept_reports[d]['stockouts_avg_duration_p'] = bd.stockouts_avg_duration_p
_update_dict(ept_totals['no_stockouts_p'], bd.no_stockouts_p)
_update_dict(ept_totals['stockouts_duration_p'], bd.stockouts_duration_p)
_update_dict(ept_totals['discrepancies_p'], bd.discrepancies_p)
_update_dict(ept_totals['discrepancies_tot_p'], bd.discrepancies_tot_p)
_update_dict(ept_totals['filled_orders_p'], bd.filled_orders_p)
_update_dict(ept_totals['totals_p'], bd.totals_p)
for p in ept_totals['stockouts_duration_p']:
ept_totals['stockouts_avg_duration_p'][p] = timedelta(seconds=sum(ept_totals['stockouts_duration_p'][p])/len(ept_totals['stockouts_duration_p'][p]))
for p in em_totals['stockouts_duration_p']:
em_totals['stockouts_avg_duration_p'][p] = timedelta(seconds=sum(em_totals['stockouts_duration_p'][p])/len(em_totals['stockouts_duration_p'][p]))
for p in ept_totals['no_stockouts_p']:
ept_totals['no_stockouts_pct_p'][p] = calc_percentage(ept_totals['no_stockouts_p'][p], ept_totals['totals_p'][p])
for p in em_totals['no_stockouts_p']:
em_totals['no_stockouts_pct_p'][p] = calc_percentage(em_totals['no_stockouts_p'][p], em_totals['totals_p'][p])
for p in ept_totals['discrepancies_p']:
ept_totals['discrepancies_pct_p'][p] = calc_percentage(ept_totals['discrepancies_p'][p], ept_totals['filled_orders_p'][p])
if ept_totals['discrepancies_p'][p]: ept_totals['discrepancies_avg_p'][p] = float(ept_totals['discrepancies_tot_p'][p]) / ept_totals['discrepancies_p'][p]
for p in em_totals['discrepancies_p']:
em_totals['discrepancies_pct_p'][p] = calc_percentage(em_totals['discrepancies_p'][p], em_totals['filled_orders_p'][p])
if em_totals['discrepancies_p'][p]: em_totals['discrepancies_avg_p'][p] = float(em_totals['discrepancies_tot_p'][p]) / em_totals['discrepancies_p'][p]
if len(em_totals['req_times']):
em_totals['req_times'] = timedelta(seconds=sum(em_totals['req_times'])/len(em_totals['req_times']))
else:
em_totals['req_times'] = None
if len(ept_totals['req_times']):
ept_totals['req_times'] = timedelta(seconds=sum(ept_totals['req_times'])/len(ept_totals['req_times']))
else:
ept_totals['req_times'] = None
return {"em_reports": em_reports,
"ept_reports": ept_reports,
"em_totals": em_totals,
"ept_totals": ept_totals}
def hsas_with_stock(instance):
"""
HSA with adequate stock, by District and group
"""
ps = ProductStock.objects.select_related().filter(
quantity__gt=0, product__sms_code__in=PRODUCT_CODES)
em = get_em_districts()
ept = get_ept_districts()
em_reports = {}
ept_reports = {}
em_totals = {}
ept_totals = {}
em_users = {}
ept_users = {}
em_total_u = {}
ept_total_u = {}
# There is just no good way to do this. The performance here is going to suck and there's no way around it.
for p in PRODUCT_CODES:
em_totals[p] = 0
ept_totals[p] = 0
em_total_u[p] = 0
ept_total_u[p] = 0
for d in em:
em_reports[d] = {}
em_users[d] = {}
for p in PRODUCT_CODES:
em_reports[d][p] = len([
px for px in ps.filter(
product__sms_code=p,
supply_point__in=hsa_supply_points_below(d))
if px.is_in_adequate_supply()
])
em_users[d][p] = len([
px for px in ps.filter(
product__sms_code=p,
supply_point__in=hsa_supply_points_below(d))
])
em_totals[p] += em_reports[d][p]
em_total_u[p] += em_users[d][p]
for d in ept:
ept_reports[d] = {}
ept_users[d] = {}
for p in PRODUCT_CODES:
ept_reports[d][p] = len([
px for px in ps.filter(
product__sms_code=p,
supply_point__in=hsa_supply_points_below(d))
if px.is_in_adequate_supply()
])
ept_users[d][p] = len([
px for px in ps.filter(
product__sms_code=p,
supply_point__in=hsa_supply_points_below(d))
])
ept_totals[p] += ept_reports[d][p]
ept_total_u[p] += ept_users[d][p]
instance.datespan = None
return _common_report(
instance, {
'product_codes': PRODUCT_CODES,
'em_reports': em_reports,
'em_users': em_users,
'ept_reports': ept_reports,
'ept_users': ept_users,
'em_totals': em_totals,
'ept_totals': ept_totals,
'em_total_u': em_total_u,
'ept_total_u': ept_total_u
})
def _district_breakdown(datespan, facility=False):
"""
Breakdown of reporting information, by group and district
"""
em = get_em_districts()
ept = get_ept_districts()
em_reports = SortedDict()
ept_reports = SortedDict()
em_totals = defaultdict(lambda: 0)
ept_totals = defaultdict(lambda: 0)
em_totals.update({
'no_stockouts_pct_p': {},
'no_stockouts_p': {},
'stockouts_duration_p': {},
'stockouts_avg_duration_p': {},
'totals_p': {},
'discrepancies_p': {},
'discrepancies_tot_p': {},
'discrepancies_pct_p': {},
'discrepancies_avg_p': {},
'filled_orders_p': {},
'req_times': []
})
ept_totals.update({
'no_stockouts_pct_p': {},
'no_stockouts_p': {},
'stockouts_duration_p': {},
'stockouts_avg_duration_p': {},
'totals_p': {},
'discrepancies_p': {},
'discrepancies_pct_p': {},
'discrepancies_tot_p': {},
'discrepancies_avg_p': {},
'filled_orders_p': {},
'req_times': []
})
for d in em:
if facility:
bd = ReportingBreakdown(facility_supply_points_below(d),
datespan,
MNE=True)
else:
bd = ReportingBreakdown(hsa_supply_points_below(d),
datespan,
MNE=True)
em_reports[d] = _to_totals(bd)
_update_dict(em_totals, em_reports[d])
em_totals['req_times'] += bd.req_times
em_reports[d]['no_stockouts_pct_p'] = bd.no_stockouts_pct_p
em_reports[d]['no_stockouts_p'] = bd.no_stockouts_p
em_reports[d]['totals_p'] = bd.totals_p
em_reports[d]['avg_req_time'] = bd.avg_req_time
em_reports[d]['discrepancies_pct_p'] = bd.discrepancies_pct_p
em_reports[d]['discrepancies_avg_p'] = bd.discrepancies_avg_p
em_reports[d]['discrepancies_tot_p'] = bd.discrepancies_tot_p
em_reports[d]['discrepancies_p'] = bd.discrepancies_p
em_reports[d]['stockouts_duration_p'] = bd.stockouts_duration_p
em_reports[d]['stockouts_avg_duration_p'] = bd.stockouts_avg_duration_p
_update_dict(em_totals['stockouts_duration_p'],
bd.stockouts_duration_p)
_update_dict(em_totals['no_stockouts_p'], bd.no_stockouts_p)
_update_dict(em_totals['discrepancies_p'], bd.discrepancies_p)
_update_dict(em_totals['discrepancies_tot_p'], bd.discrepancies_tot_p)
_update_dict(em_totals['filled_orders_p'], bd.filled_orders_p)
_update_dict(em_totals['totals_p'], bd.totals_p)
for d in ept:
if facility:
bd = ReportingBreakdown(facility_supply_points_below(d),
datespan,
MNE=True)
else:
bd = ReportingBreakdown(hsa_supply_points_below(d),
datespan,
MNE=True)
ept_reports[d] = _to_totals(bd)
_update_dict(ept_totals, ept_reports[d])
ept_totals['req_times'] += bd.req_times
ept_reports[d]['no_stockouts_pct_p'] = bd.no_stockouts_pct_p
ept_reports[d]['no_stockouts_p'] = bd.no_stockouts_p
ept_reports[d]['totals_p'] = bd.totals_p
ept_reports[d]['discrepancies_pct_p'] = bd.discrepancies_pct_p
ept_reports[d]['discrepancies_avg_p'] = bd.discrepancies_avg_p
ept_reports[d]['discrepancies_tot_p'] = bd.discrepancies_tot_p
ept_reports[d]['discrepancies_p'] = bd.discrepancies_p
ept_reports[d]['avg_req_time'] = bd.avg_req_time
ept_reports[d]['stockouts_duration_p'] = bd.stockouts_duration_p
ept_reports[d][
'stockouts_avg_duration_p'] = bd.stockouts_avg_duration_p
_update_dict(ept_totals['no_stockouts_p'], bd.no_stockouts_p)
_update_dict(ept_totals['stockouts_duration_p'],
bd.stockouts_duration_p)
_update_dict(ept_totals['discrepancies_p'], bd.discrepancies_p)
_update_dict(ept_totals['discrepancies_tot_p'], bd.discrepancies_tot_p)
_update_dict(ept_totals['filled_orders_p'], bd.filled_orders_p)
_update_dict(ept_totals['totals_p'], bd.totals_p)
for p in ept_totals['stockouts_duration_p']:
ept_totals['stockouts_avg_duration_p'][p] = timedelta(
seconds=sum(ept_totals['stockouts_duration_p'][p]) /
len(ept_totals['stockouts_duration_p'][p]))
for p in em_totals['stockouts_duration_p']:
em_totals['stockouts_avg_duration_p'][p] = timedelta(
seconds=sum(em_totals['stockouts_duration_p'][p]) /
len(em_totals['stockouts_duration_p'][p]))
for p in ept_totals['no_stockouts_p']:
ept_totals['no_stockouts_pct_p'][p] = calc_percentage(
ept_totals['no_stockouts_p'][p], ept_totals['totals_p'][p])
for p in em_totals['no_stockouts_p']:
em_totals['no_stockouts_pct_p'][p] = calc_percentage(
em_totals['no_stockouts_p'][p], em_totals['totals_p'][p])
for p in ept_totals['discrepancies_p']:
ept_totals['discrepancies_pct_p'][p] = calc_percentage(
ept_totals['discrepancies_p'][p], ept_totals['filled_orders_p'][p])
if ept_totals['discrepancies_p'][p]:
ept_totals['discrepancies_avg_p'][p] = float(
ept_totals['discrepancies_tot_p']
[p]) / ept_totals['discrepancies_p'][p]
for p in em_totals['discrepancies_p']:
em_totals['discrepancies_pct_p'][p] = calc_percentage(
em_totals['discrepancies_p'][p], em_totals['filled_orders_p'][p])
if em_totals['discrepancies_p'][p]:
em_totals['discrepancies_avg_p'][p] = float(
em_totals['discrepancies_tot_p']
[p]) / em_totals['discrepancies_p'][p]
if len(em_totals['req_times']):
em_totals['req_times'] = timedelta(
seconds=sum(em_totals['req_times']) / len(em_totals['req_times']))
else:
em_totals['req_times'] = None
if len(ept_totals['req_times']):
ept_totals['req_times'] = timedelta(
seconds=sum(ept_totals['req_times']) /
len(ept_totals['req_times']))
else:
ept_totals['req_times'] = None
return {
"em_reports": em_reports,
"ept_reports": ept_reports,
"em_totals": em_totals,
"ept_totals": ept_totals
}
