Opt year data
Brightcells
共有 2 個文件被更改，包括 86 次插入 和 6 次删除
+ 2
- 0
requirements_pywe.txt
@@ -1,3 +1,5 @@ |
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| 1 |
+pywe-component==1.0.1 |
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| 2 |
+pywe-component-preauthcode==1.0.3 |
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| 1 | 3 |
pywe-jssdk==1.1.0 |
| 2 | 4 |
pywe-membercard==1.0.1 |
| 3 | 5 |
pywe-miniapp==1.1.5 |
+ 84
- 6
statistic/views.py
@@ -2,12 +2,13 @@ |
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| 2 | 2 |
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| 3 | 3 |
from django.conf import settings |
| 4 | 4 |
from django.db import transaction |
| 5 |
+from django.db.models import Count, F, Sum |
|
| 5 | 6 |
from django_logit import logit |
| 6 | 7 |
from django_models_ext.provincemodels import ProvinceShortModelMixin |
| 7 | 8 |
from django_response import response |
| 8 | 9 |
from TimeConvert import TimeConvert as tc |
| 9 | 10 |
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| 10 |
-from mch.models import BrandInfo, DistributorInfo, ModelInfo |
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| 11 |
+from mch.models import BrandInfo, DistributorInfo, ModelInfo, SaleclerkInfo |
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| 11 | 12 |
from statistic.models import (ConsumeDistributorSaleStatisticInfo, ConsumeModelSaleStatisticInfo, |
| 12 | 13 |
ConsumeProvinceSaleStatisticInfo, ConsumeSaleStatisticInfo, ConsumeUserStatisticInfo, |
| 13 | 14 |
DistributorSaleStatisticInfo, ModelSaleStatisticInfo, ProvinceSaleStatisticInfo, |
@@ -203,6 +204,83 @@ def __tj_generate(ymd=None): |
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| 203 | 204 |
) |
| 204 | 205 |
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| 205 | 206 |
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| 207 |
+def ytj(brand_id): |
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| 208 |
+ # [消费者维度] 周期内扫描用户人数 |
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+ cusis = ConsumeUserStatisticInfo.objects.filter(brand_id=brand_id, ymd__lt=9999) |
|
| 210 |
+ users = [] |
|
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+ for cusi in cusis: |
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+ users += cusi.users |
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+ scan_user_count = sum(users) |
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+ |
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+ # [消费者维度] 周期内镜头销售支数 |
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+ sell_volume_count = ConsumeSaleStatisticInfo.objects.filter(brand_id=brand_id, ymd__lt=9999).aggregate(Sum('num')).get('num__sum', 0) or 0
|
|
| 217 |
+ |
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| 218 |
+ startd = tc.local_string(months=-12, format='%Y%m%d') |
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+ endd = tc.local_string(format='%Y%m%d') |
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| 220 |
+ |
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+ # [消费者维度] 统计周期内型号扫描排行数据，请按顺序返回 |
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+ models = ConsumeModelSaleStatisticInfo.objects.filter( |
|
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+ brand_id=brand_id, |
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+ ymd__gt=startd, |
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+ ymd__lte=endd, |
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+ status=True |
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+ ).order_by( |
|
| 228 |
+ 'model_name' |
|
| 229 |
+ ).values( |
|
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+ 'model_id', 'model_name' |
|
| 231 |
+ ).annotate( |
|
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+ num=Sum('num')
|
|
| 233 |
+ ).order_by( |
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+ '-num' |
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+ )[:20] |
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+ |
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+ # [经销商维度] 统计周期内销售员排行数据，请按顺序返回 |
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+ salesmen = SaleclerkSaleStatisticInfo.objects.filter( |
|
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+ brand_id=brand_id, |
|
| 240 |
+ ymd__gt=startd, |
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+ ymd__lte=endd, |
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+ status=True |
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+ ).order_by( |
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+ 'clerk_id' |
|
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+ ).values( |
|
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+ 'clerk_id' |
|
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+ ).annotate( |
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+ num=Sum('num')
|
|
| 249 |
+ ).order_by( |
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+ '-num' |
|
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+ )[:20] |
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+ clerks = SaleclerkInfo.objects.filter(brand_id=brand_id, status=True) |
|
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+ clerks = {clerk.clerk_id: {'distributor_id': clerk.distributor_id, 'distributor_name': clerk.distributor_name, 'clerk_name': clerk.clerk_name} for clerk in clerks}
|
|
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+ salesmen = [dict(sm, **clerks.get(sm.get('clerk_id', ''), {})) for sm in salesmen]
|
|
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+ |
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+ # [收费者维度] 统计周期内省份销量排行数据，请按顺序返回 |
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+ provinces = ConsumeProvinceSaleStatisticInfo.objects.filter( |
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+ brand_id=brand_id, |
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+ ymd__gt=startd, |
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+ ymd__lte=endd, |
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+ status=True |
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+ ).order_by( |
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+ 'province_code' |
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+ ).values( |
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+ 'province_code' |
|
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+ ).annotate( |
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+ num=Sum('num')
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+ ).order_by( |
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+ '-num' |
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+ ) |
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+ provinces = [dict(p, **{'province_name': ''}) for p in provinces]
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+ |
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+ return {
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+ 'scan_user_count': scan_user_count, |
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+ 'sell_volume_count': sell_volume_count, |
|
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+ 'user_count_increase_pct': -1, # 与上个统计周期数据的用户人数比例 |
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+ 'volume_count_increase_pct': -1, # 与上个统计周期数据的销售支数比例 |
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| 278 |
+ 'models': list(models), |
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+ 'salesmen': salesmen, |
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+ 'provinces': provinces, |
|
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+ } |
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+ |
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+ |
|
| 206 | 284 |
def ymdtj(brand_id, ymd, lastymd): |
| 207 | 285 |
# [消费者维度] 周期内扫描用户人数 |
| 208 | 286 |
try: |
@@ -237,8 +315,8 @@ def ymdtj(brand_id, ymd, lastymd): |
||
| 237 | 315 |
models = [m.data for m in current_models[:20]] |
| 238 | 316 |
|
| 239 | 317 |
# [经销商维度] 统计周期内销售员排行数据，请按顺序返回 |
| 240 |
- salesmen = SaleclerkSaleStatisticInfo.objects.filter(brand_id=brand_id, ymd=ymd, status=True).order_by('-num')[:20]
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|
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- salesmen = [s.data for s in salesmen] |
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+ salesmen = SaleclerkSaleStatisticInfo.objects.filter(brand_id=brand_id, ymd=ymd, status=True).order_by('-num')
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|
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+ salesmen = [s.data for s in salesmen[:20]] |
|
| 242 | 320 |
|
| 243 | 321 |
# [收费者维度] 统计周期内省份销量排行数据，请按顺序返回 |
| 244 | 322 |
provinces = ConsumeProvinceSaleStatisticInfo.objects.filter(brand_id=brand_id, ymd=ymd, status=True).order_by('-num')
|
@@ -259,15 +337,15 @@ def ymdtj(brand_id, ymd, lastymd): |
||
| 259 | 337 |
def v2_tj_distributor(request): |
| 260 | 338 |
brand_id = request.POST.get('brand_id', settings.KODO_DEFAULT_BRAND_ID)
|
| 261 | 339 |
|
| 262 |
- year = tc.local_string(format='%Y') |
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| 340 |
+ # year = tc.local_string(format='%Y') |
|
| 263 | 341 |
month = tc.local_string(format='%Y%m') |
| 264 | 342 |
day = tc.local_string(format='%Y%m%d') |
| 265 | 343 |
|
| 266 |
- lastyear = tc.local_string(tc.several_time_ago(years=1), format='%Y') |
|
| 344 |
+ # lastyear = tc.local_string(tc.several_time_ago(years=1), format='%Y') |
|
| 267 | 345 |
lastmonth = tc.local_string(tc.several_time_ago(months=1), format='%Y%m') |
| 268 | 346 |
lastday = tc.local_string(tc.several_time_ago(days=1), format='%Y%m%d') |
| 269 | 347 |
|
| 270 |
- year_data = ymdtj(brand_id, year, lastyear) |
|
| 348 |
+ year_data = ytj(brand_id) |
|
| 271 | 349 |
month_data = ymdtj(brand_id, month, lastmonth) |
| 272 | 350 |
day_data = ymdtj(brand_id, day, lastday) |
| 273 | 351 |
|