def post(self, request, format=None):
if ShippingModel.objects.filter(appid=request.user.appid).exists():
if GoodsModel.objects.filter(appid=request.user.appid).exists():
if BaseInfoModel.objects.filter(appid=request.user.appid).exists():
contacts = ShippingModel.objects.filter(appid=request.user.appid)
goods_code = contacts.values('goods_code').distinct()
data = []
for i in range(len(goods_code)):
if GoodsModel.objects.filter(appid=request.user.appid, goods_code=goods_code[i]['goods_code']).exists():
if BaseInfoModel.objects.filter(appid=request.user.appid, goods_code=goods_code[i]['goods_code']).exists():
on_hand_stock = GoodsModel.objects.filter(appid=request.user.appid,
goods_code=goods_code[i][
'goods_code']).first().on_hand_stock
total_leadtime = BaseInfoModel.objects.filter(appid=request.user.appid,
goods_code=goods_code[i][
'goods_code']).first().total_leadtime
if on_hand_stock == 0:
today = datetime.date.today()
delta1 = datetime.timedelta(days=29)
delta2 = datetime.timedelta(days=59)
delta3 = datetime.timedelta(days=89)
end_date1 = (today - delta1).strftime('%Y-%m-%d')
end_date2 = (today - delta2).strftime('%Y-%m-%d')
end_date3 = (today - delta3).strftime('%Y-%m-%d')
plan_date = today.strftime('%Y-%m-%d')
shipping_data1 = contacts.filter(goods_code=goods_code[i]['goods_code'], shipping_time__range=[end_date1, today]).aggregate(
Sum('shipping_qty'))
shipping_data2 = contacts.filter(goods_code=goods_code[i]['goods_code'], shipping_time__range=[end_date2, today]).aggregate(
Sum('shipping_qty'))
shipping_data3 = contacts.filter(goods_code=goods_code[i]['goods_code'], shipping_time__range=[end_date3, today]).aggregate(
Sum('shipping_qty'))
analyst = {
"goods_code": goods_code[i]['goods_code'],
"shipping_data1": shipping_data1['shipping_qty__sum'],
"shipping_data2": shipping_data2['shipping_qty__sum'],
"shipping_data3": shipping_data3['shipping_qty__sum'],
"plan_date1": plan_date,
"plan_date2": plan_date,
"plan_date3": plan_date,
"plan_date4": 0,
"oos_lv": "已经断货"
}
data.append(analyst)
else:
today = datetime.date.today()
delta1 = datetime.timedelta(days=29)
delta2 = datetime.timedelta(days=59)
delta3 = datetime.timedelta(days=89)
end_date1 = (today - delta1).strftime('%Y-%m-%d')
end_date2 = (today - delta2).strftime('%Y-%m-%d')
end_date3 = (today - delta3).strftime('%Y-%m-%d')
shipping_data1 = contacts.filter(goods_code=goods_code[i]['goods_code'], shipping_time__range=[end_date1, today]).aggregate(
Sum('shipping_qty'))
shipping_data2 = contacts.filter(goods_code=goods_code[i]['goods_code'], shipping_time__range=[end_date2, today]).aggregate(
Sum('shipping_qty'))
shipping_data3 = contacts.filter(goods_code=goods_code[i]['goods_code'], shipping_time__range=[end_date3, today]).aggregate(
Sum('shipping_qty'))
avg_qty1 = shipping_data1['shipping_qty__sum'] / 30
avg_qty2 = shipping_data2['shipping_qty__sum'] / 60
avg_qty3 = shipping_data3['shipping_qty__sum'] / 90
avg_qty4 = (avg_qty1 + avg_qty2 + avg_qty3) / 3
stock_check1 = int(on_hand_stock / avg_qty1)
stock_check2 = int(on_hand_stock / avg_qty2)
stock_check3 = int(on_hand_stock / avg_qty3)
stock_check4 = int(on_hand_stock / avg_qty4)
plan_day1 = datetime.timedelta(days=stock_check1)
plan_day2 = datetime.timedelta(days=stock_check2)
plan_day3 = datetime.timedelta(days=stock_check3)
plan_day4 = datetime.timedelta(days=stock_check4)
plan_date1 = (today + plan_day1).strftime('%Y-%m-%d')
plan_date2 = (today + plan_day2).strftime('%Y-%m-%d')
plan_date3 = (today + plan_day3).strftime('%Y-%m-%d')
oos_notice = plan_day4.days / total_leadtime
if oos_notice >= 3:
oos_lv = "库存过多"
elif 3 > oos_notice >= 2:
oos_lv = "库存充足"
elif 2 > oos_notice >= 1:
oos_notice = plan_day4.days / (total_leadtime + 7)
if oos_notice > 1:
oos_lv = "库存正常"
elif oos_notice <= 1:
oos_lv = "断货风险"
else:
oos_lv = "断货风险极大"
else:
oos_lv = "断货风险极大"
analyst = {
"goods_code": goods_code[i]['goods_code'],
"shipping_data1": shipping_data1['shipping_qty__sum'],
"shipping_data2": shipping_data2['shipping_qty__sum'],
"shipping_data3": shipping_data3['shipping_qty__sum'],
"plan_date1": plan_date1,
"plan_date2": plan_date2,
"plan_date3": plan_date3,
"plan_date4": plan_day4.days,
"oos_lv": oos_lv
}
data.append(analyst)
# end_date = (today + delta).strftime('%Y-%m-%d')
# date = [int(x) for x in date_end.split('-')]
# old = datetime.datetime(date[0], date[1], date[2])
# end_date = (old + delta).strftime('%Y-%m-%d')
else:
continue
else:
continue
ret = FBMsg.ret()
ret['data'] = data
return Response(ret)
else:
return Response(FBMsg.err_req_baseinfo_list())
else:
return Response(FBMsg.err_req_stock_list())
else:
return Response(FBMsg.err_req_shipping_list())
def post(self, request, format=None):
data = DataSolve.datasolve(request)
try:
if data['code'] == "1031":
return Response(FBMsg.err_bad())
except:
if ShippingModel.objects.filter(appid=request.user.appid).exists():
if GoodsModel.objects.filter(appid=request.user.appid).exists():
if BaseInfoModel.objects.filter(appid=request.user.appid).exists():
if ShippingModel.objects.filter(goods_code=data, appid=request.user.appid).exists():
if GoodsModel.objects.filter(goods_code=data, appid=request.user.appid).exists():
if BaseInfoModel.objects.filter(goods_code=data, appid=request.user.appid).exists():
on_hand_stock = GoodsModel.objects.filter(goods_code=data, appid=request.user.appid).first().on_hand_stock
lead_time = BaseInfoModel.objects.filter(goods_code=data,
appid=request.user.appid).first().total_leadtime
today = datetime.date.today()
delta = datetime.timedelta(days=89)
demand_data = ShippingModel.objects.filter(goods_code=data, appid=request.user.appid,
shipping_time__range=[(today - delta).strftime('%Y-%m-%d'), today])
demand = []
for i in range(len(demand_data)):
demand.append({
"goods_code": data,
"forcast_day": demand_data[i].shipping_time,
"forcast_shipping": demand_data[i].shipping_qty,
"forcast_on_hand": 0,
"plan_order_qty": 0,
"oos": ''
})
for j in range(0, 90):
delta = datetime.timedelta(days=j)
a_date = (today - delta).strftime('%Y-%m-%d')
date = [int(x) for x in a_date.split('-')]
b_date = datetime.date(date[0], date[1], date[2])
check_date = 0
for k in demand:
if (k['forcast_day'] - b_date).days == 0:
check_date = 1
if check_date == 0:
demand.append({
"goods_code": data,
"forcast_day": b_date,
"forcast_shipping": 0,
"forcast_on_hand": 0,
"plan_order_qty": 0,
"oos": ''
})
for k in range(1, 91):
delta = datetime.timedelta(days=k)
plan_date = (today + delta).strftime('%Y-%m-%d')
demand.append({
"goods_code": data,
"forcast_day": plan_date,
"forcast_shipping": 0,
"forcast_on_hand": 0,
"plan_order_qty": 0,
"oos": ''
})
ret = FBMsg.ret()
ret["forcast_on_hand"] = on_hand_stock
ret['lead_time'] = lead_time
ret['data'] = demand
return Response(ret)
else:
return Response(FBMsg.err_goods_code())
else:
return Response(FBMsg.err_goods_code())
else:
return Response(FBMsg.err_goods_code())
else:
return Response(FBMsg.err_req_baseinfo_list())
else:
return Response(FBMsg.err_req_stock_list())
else:
return Response(FBMsg.err_req_shipping_list())
