TermiNexus
f1c8633345
P1 性能优化（避免循环内 N+1 / N 次 DB 查询）： - shop_order_views._batch_images: 移除 ThreadPoolExecutor 掩盖的 N 次查询，改单次批量 + Python 侧分组 - product_query.DashouHuiyuanList: 5N 查询 -> 3 次批量预取 + 本地闭包判断 - roles.GetRolePermissionView / 用户列表: 循环内 RolePermission/Permission/UserRole/Role -> 批量 __in 预取 - guanli / zuzhang 杜次分红 4.2/4.3: 循环内 update_or_create + 单条 delete -> bulk_create + bulk_update + 批量 delete - admin_config QQ 群配置: 循环内 exists/first/save/create -> 批量预取 + bulk_create + bulk_update - jituan 服务层多处合并统计查询、批量预取 map - rank 多处循环 N+1 改批量预取 - backend 多处循环内 count/create 改批量 - config/orders/merchant_ops 多处循环 N+1 改批量预取 其他改动： - users/views/kefu.py 拆分为 kefu_base/kefu_dashou/kefu_orders/kefu_punishment/kefu_withdraw 5 个文件 - 删除遗留脚本 check_prod_uid.py / create_rbac_tables.sql
560 lines
21 KiB
Python
560 lines
21 KiB
Python
"""财务子模块统计（订单/会员/其他充值），供 /jituan/houtai/*；旧 /houtai/* 不变。"""
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from datetime import date, datetime
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from decimal import Decimal
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from django.db.models import Case, Count, DecimalField, Q, Sum, Value, When
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from django.db.models.functions import TruncDate, TruncMonth, TruncYear
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from jituan.constants import DATA_SCOPE_ALL
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from jituan.models import ClubHuiyuanPrice
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from jituan.services.club_context import (
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filter_queryset_by_club,
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resolve_club_id_from_request,
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resolve_club_scope,
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)
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from jituan.services.club_penalty import filter_gsfenhong_qs, filter_penalty_qs
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from orders.models import Order, Penalty
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from products.czjilu_types import CZJILU_LEIXING_SHANGJIA, exclude_penalty_from_cz_qs
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from products.models import Czjilu, Gsfenhong, Huiyuan, ShangpinLeixing
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from rank.models import Bankuai
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def _meta(request):
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return {
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'club_id': resolve_club_id_from_request(request),
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'scope': resolve_club_scope(request),
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}
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def _parse_time_range(granularity, year, month, summary_date):
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now = date.today()
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if granularity == 'day':
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if not year or not month:
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return None, '按日统计需要年份和月份'
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start_date = date(int(year), int(month), 1)
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end_date = date(int(year), int(month) + 1, 1) if int(month) < 12 else date(int(year) + 1, 1, 1)
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trunc_func = TruncDate('CreateTime')
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if not summary_date:
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summary_date = now.strftime('%Y-%m-%d')
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summary_q = datetime.strptime(summary_date, '%Y-%m-%d').date()
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elif granularity == 'month':
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if not year:
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return None, '按月统计需要年份'
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y = int(year)
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start_date = date(y, 1, 1)
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end_date = date(y + 1, 1, 1)
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trunc_func = TruncMonth('CreateTime')
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if not summary_date:
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summary_date = now.strftime('%Y-%m')
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summary_q = datetime.strptime(summary_date + '-01', '%Y-%m-%d').date()
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elif granularity == 'year':
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y = int(year or now.year)
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start_date = date(y, 1, 1)
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end_date = date(y + 1, 1, 1)
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trunc_func = TruncYear('CreateTime')
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if not summary_date:
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summary_date = str(y)
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summary_q = date(y, 1, 1)
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else:
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return None, '无效的颗粒度'
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start_dt = datetime.combine(start_date, datetime.min.time())
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end_dt = datetime.combine(end_date, datetime.min.time())
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return {
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'start_dt': start_dt,
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'end_dt': end_dt,
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'trunc_func': trunc_func,
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'summary_q': summary_q,
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'granularity': granularity,
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'year': int(year) if year is not None else None,
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'month': int(month) if month is not None else None,
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}, None
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def _summary_date_filter(granularity, summary_q, field_prefix='CreateTime'):
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if granularity == 'day':
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return {f'{field_prefix}__date': summary_q}
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if granularity == 'month':
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return {f'{field_prefix}__year': summary_q.year, f'{field_prefix}__month': summary_q.month}
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return {f'{field_prefix}__year': summary_q.year}
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def _penalty_trunc_func(granularity):
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if granularity == 'day':
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return TruncDate('UpdateTime')
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if granularity == 'month':
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return TruncMonth('UpdateTime')
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return TruncYear('UpdateTime')
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def _penalty_fenhong_aggregates():
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"""罚款分红只统计已入账（BonusCredited），与 process_fadan_fenhong 一致。"""
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zero = Value(Decimal('0.00'), output_field=DecimalField(max_digits=12, decimal_places=2))
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return {
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'fenhong_amount': Sum(
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Case(
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When(BonusCredited=True, then='ApplicantBonusAmount'),
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default=zero,
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output_field=DecimalField(max_digits=12, decimal_places=2),
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)
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),
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'fenhong_count': Count(
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'id',
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filter=Q(BonusCredited=True, ApplicantBonusAmount__gt=0),
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),
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}
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def _czjilu_finance_qs(request, start_dt, end_dt, cz_types):
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"""充值财务 czjilu：已支付；type4 排除罚款误标。"""
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qs = filter_queryset_by_club(
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Czjilu.query.filter(
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CreateTime__gte=start_dt,
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CreateTime__lt=end_dt,
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leixing__in=cz_types,
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zhuangtai=3,
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),
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request,
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)
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if CZJILU_LEIXING_SHANGJIA in cz_types:
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qs = exclude_penalty_from_cz_qs(qs)
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return qs
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def _czjilu_summary_qs(request, lx, granularity, summary_q):
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filter_kwargs = {'leixing': lx, 'zhuangtai': 3}
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filter_kwargs.update(_summary_date_filter(granularity, summary_q))
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qs = filter_queryset_by_club(Czjilu.query.filter(**filter_kwargs), request)
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if lx == CZJILU_LEIXING_SHANGJIA:
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qs = exclude_penalty_from_cz_qs(qs)
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return qs
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def build_order_types_payload():
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types = ShangpinLeixing.query.filter(shenhezhuangtai=1).values('id', 'jieshao')
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return list(types)
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def build_order_finance_payload(
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request,
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granularity,
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year,
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month,
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type_id=0,
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order_source=0,
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summary_date=None,
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):
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parsed, err = _parse_time_range(granularity, year, month, summary_date)
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if err:
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return None, err
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start_dt = parsed['start_dt']
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end_dt = parsed['end_dt']
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trunc_func = parsed['trunc_func']
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summary_q = parsed['summary_q']
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granularity = parsed['granularity']
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filters = {
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'CreateTime__gte': start_dt,
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'CreateTime__lt': end_dt,
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'Status__in': [1, 2, 3, 4, 5, 6, 7, 8],
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}
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if int(type_id or 0) != 0:
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filters['ProductTypeID'] = type_id
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if int(order_source or 0) in [1, 2]:
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filters['Platform'] = int(order_source)
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order_base = filter_queryset_by_club(
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Order.query.filter(**filters), request, club_field='ClubID',
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)
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qs = order_base.annotate(period=trunc_func).values('period').annotate(
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order_count=Count('id'),
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order_amount=Sum('Amount'),
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success_count=Count('id', filter=Q(Status=3)),
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success_amount=Sum('Amount', filter=Q(Status=3)),
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refund_count=Count('id', filter=Q(Status=5)),
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PlayerCommission_sum=Sum('PlayerCommission', filter=Q(Status=3)),
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dianpu_fenhong_sum=Sum('pingtai_kuozhan__ShopIncome', filter=Q(Status=3, Platform=1)),
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platform_success_amount=Sum('Amount', filter=Q(Status=3, Platform=1)),
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merchant_success_amount=Sum('Amount', filter=Q(Status=3, Platform=2)),
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platform_dashou=Sum('PlayerCommission', filter=Q(Status=3, Platform=1)),
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merchant_dashou=Sum('PlayerCommission', filter=Q(Status=3, Platform=2)),
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).order_by('period')
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time_series = []
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for item in qs:
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period_str = (
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item['period'].strftime('%Y-%m-%d') if granularity == 'day'
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else item['period'].strftime('%Y-%m') if granularity == 'month'
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else item['period'].strftime('%Y')
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)
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platform_profit = (item['platform_success_amount'] or 0) - (item['platform_dashou'] or 0) - (item['dianpu_fenhong_sum'] or 0)
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merchant_profit = (item['merchant_success_amount'] or 0) - (item['merchant_dashou'] or 0)
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time_series.append({
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'date': period_str,
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'order_count': item['order_count'],
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'order_amount': float(item['order_amount'] or 0),
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'success_count': item['success_count'],
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'success_amount': float(item['success_amount'] or 0),
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'refund_count': item['refund_count'],
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'dashou_fencheng': float(item['PlayerCommission_sum'] or 0),
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'dianpu_fenhong': float(item['dianpu_fenhong_sum'] or 0),
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'profit': round(float(platform_profit + merchant_profit), 2),
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})
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summary_qs = filter_queryset_by_club(Order.query.filter(**filters), request, club_field='ClubID')
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# 合并 13 次独立 count/aggregate → 1 次 aggregate
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_summary_agg = summary_qs.aggregate(
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total_order_count=Count('id'),
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total_order_amount=Sum('Amount'),
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total_success_count=Count('id', filter=Q(Status=3)),
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total_success_amount=Sum('Amount', filter=Q(Status=3)),
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total_refund_count=Count('id', filter=Q(Status=5)),
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total_dashou=Sum('PlayerCommission', filter=Q(Status=3)),
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total_dianpu_fenhong=Sum('pingtai_kuozhan__ShopIncome', filter=Q(Status=3, Platform=1)),
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platform_amount=Sum('Amount', filter=Q(Status=3, Platform=1)),
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merchant_amount=Sum('Amount', filter=Q(Status=3, Platform=2)),
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platform_dashou_sum=Sum('PlayerCommission', filter=Q(Status=3, Platform=1)),
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merchant_dashou_sum=Sum('PlayerCommission', filter=Q(Status=3, Platform=2)),
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)
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total_order_count = _summary_agg['total_order_count'] or 0
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total_order_amount = _summary_agg['total_order_amount'] or 0
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total_success_count = _summary_agg['total_success_count'] or 0
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total_success_amount = _summary_agg['total_success_amount'] or 0
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total_refund_count = _summary_agg['total_refund_count'] or 0
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total_dashou = _summary_agg['total_dashou'] or 0
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total_dianpu_fenhong = _summary_agg['total_dianpu_fenhong'] or 0
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platform_amount = _summary_agg['platform_amount'] or 0
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merchant_amount = _summary_agg['merchant_amount'] or 0
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platform_dashou_sum = _summary_agg['platform_dashou_sum'] or 0
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merchant_dashou_sum = _summary_agg['merchant_dashou_sum'] or 0
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profit_platform = platform_amount - platform_dashou_sum - total_dianpu_fenhong
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profit_merchant = merchant_amount - merchant_dashou_sum
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total_profit = profit_platform + profit_merchant
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data = {
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**_meta(request),
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'time_series': time_series,
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'summary': {
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'total_order_count': total_order_count,
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'total_order_amount': round(float(total_order_amount), 2),
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'total_success_count': total_success_count,
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'total_success_amount': round(float(total_success_amount), 2),
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'total_refund_count': total_refund_count,
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'total_PlayerCommission': round(float(total_dashou), 2),
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'total_dianpu_fenhong': round(float(total_dianpu_fenhong), 2),
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'total_profit': round(float(total_profit), 2),
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},
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}
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return data, None
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def build_chongzhi_finance_payload(request, granularity, year, month, types=None, summary_date=None):
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if types is None:
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types = [2, 3, 4, 5, 6]
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if isinstance(types, list) and len(types) == 0:
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types = [2, 3, 4, 5, 6]
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parsed, err = _parse_time_range(granularity, year, month, summary_date)
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if err:
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return None, err
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start_dt = parsed['start_dt']
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end_dt = parsed['end_dt']
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trunc_func = parsed['trunc_func']
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summary_q = parsed['summary_q']
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granularity = parsed['granularity']
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time_series_map = {}
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def ensure_date(ds):
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if ds not in time_series_map:
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time_series_map[ds] = {}
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return time_series_map[ds]
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cz_types = [t for t in types if t in [2, 3, 4, 5]]
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if cz_types:
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cz_qs = _czjilu_finance_qs(request, start_dt, end_dt, cz_types).annotate(
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period=trunc_func,
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).values('period', 'leixing').annotate(
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total_count=Count('id'),
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total_amount=Sum('jine'),
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).order_by('period', 'leixing')
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for item in cz_qs:
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period_str = (
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item['period'].strftime('%Y-%m-%d') if granularity == 'day'
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else item['period'].strftime('%Y-%m') if granularity == 'month'
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else item['period'].strftime('%Y')
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)
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lx = item['leixing']
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amount = float(item['total_amount'] or 0)
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count = item['total_count']
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profit = amount if lx == 3 else 0.0
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day_data = ensure_date(period_str)
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day_data[str(lx)] = {
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'count': count,
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'amount': amount,
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'profit': profit,
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'fenhong_count': 0,
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'fenhong_amount': 0.0,
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}
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if 6 in types:
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penalty_trunc = _penalty_trunc_func(granularity)
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penalty_qs = filter_penalty_qs(
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Penalty.query.filter(
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UpdateTime__gte=start_dt,
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UpdateTime__lt=end_dt,
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Status=2,
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),
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request,
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).annotate(period=penalty_trunc).values('period').annotate(
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penalty_count=Count('id'),
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penalty_amount=Sum('FineAmount'),
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**_penalty_fenhong_aggregates(),
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).order_by('period')
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for item in penalty_qs:
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period_str = (
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item['period'].strftime('%Y-%m-%d') if granularity == 'day'
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else item['period'].strftime('%Y-%m') if granularity == 'month'
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else item['period'].strftime('%Y')
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)
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day_data = ensure_date(period_str)
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penalty_amt = float(item['penalty_amount'] or 0)
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fenhong_amt = float(item['fenhong_amount'] or 0)
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day_data['6'] = {
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'count': item['penalty_count'],
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'amount': penalty_amt,
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'profit': round(penalty_amt - fenhong_amt, 2),
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'fenhong_count': item['fenhong_count'],
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'fenhong_amount': fenhong_amt,
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}
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time_series = []
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for period_str in sorted(time_series_map.keys()):
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entry = {'date': period_str, 'types': {}}
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for type_code in sorted(time_series_map[period_str].keys()):
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entry['types'][type_code] = time_series_map[period_str][type_code]
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time_series.append(entry)
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summary_result = {'by_type': {}, 'total_count': 0, 'total_amount': 0.0, 'total_profit': 0.0}
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for lx in cz_types:
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agg = _czjilu_summary_qs(request, lx, granularity, summary_q).aggregate(
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count=Count('id'), amount=Sum('jine'),
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)
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count = agg['count'] or 0
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amount = float(agg['amount'] or 0)
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profit = amount if lx == 3 else 0.0
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summary_result['by_type'][str(lx)] = {
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'count': count,
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'amount': round(amount, 2),
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'profit': round(profit, 2),
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'fenhong_count': 0,
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'fenhong_amount': 0.0,
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}
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summary_result['total_count'] += count
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summary_result['total_amount'] += amount
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summary_result['total_profit'] += profit
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if 6 in types:
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penalty_filter = {'Status': 2}
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penalty_filter.update(_summary_date_filter(granularity, summary_q, field_prefix='UpdateTime'))
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agg = filter_penalty_qs(Penalty.query.filter(**penalty_filter), request).aggregate(
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count=Count('id'),
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amount=Sum('FineAmount'),
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**_penalty_fenhong_aggregates(),
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)
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penalty_count = agg['count'] or 0
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penalty_amount = float(agg['amount'] or 0)
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fh_amount = float(agg['fenhong_amount'] or 0)
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fh_count = agg['fenhong_count'] or 0
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profit = round(penalty_amount - fh_amount, 2)
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summary_result['by_type']['6'] = {
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'count': penalty_count,
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'amount': round(penalty_amount, 2),
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'profit': profit,
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'fenhong_count': fh_count,
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'fenhong_amount': round(fh_amount, 2),
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}
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summary_result['total_count'] += penalty_count
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summary_result['total_amount'] += penalty_amount
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summary_result['total_profit'] += profit
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summary_result['total_amount'] = round(summary_result['total_amount'], 2)
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summary_result['total_profit'] = round(summary_result['total_profit'], 2)
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return {
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**_meta(request),
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'time_series': time_series,
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'summary': summary_result,
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}, None
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def build_huiyuan_bankuai_payload(request):
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club_id = resolve_club_id_from_request(request)
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price_map = {}
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if resolve_club_scope(request) != DATA_SCOPE_ALL:
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for row in ClubHuiyuanPrice.query.filter(club_id=club_id, is_enabled=True):
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price_map[row.huiyuan_id] = {
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'jiage': float(row.jiage or 0),
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'guanshifc': float(row.guanshifc or 0),
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'zuzhangfc': float(row.zuzhangfc or 0),
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}
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# 批量预取所有 bankuai 和 huiyuan，避免循环内 N+1
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_bankuai_qs = Bankuai.query.all().only('bankuai_id', 'mingcheng')
|
||
_members_by_bankuai = {}
|
||
for m in Huiyuan.query.values('huiyuan_id', 'jieshao', 'bankuai_id'):
|
||
_members_by_bankuai.setdefault(m['bankuai_id'], []).append(m)
|
||
|
||
bankuai_list = []
|
||
for bk in _bankuai_qs:
|
||
members = []
|
||
for m in _members_by_bankuai.get(bk.bankuai_id, []):
|
||
item = dict(m)
|
||
if m['huiyuan_id'] in price_map:
|
||
item['club_price'] = price_map[m['huiyuan_id']]
|
||
members.append(item)
|
||
bankuai_list.append({
|
||
'bankuai_id': bk.bankuai_id,
|
||
'mingcheng': bk.mingcheng,
|
||
'members': members,
|
||
})
|
||
|
||
return {**_meta(request), 'bankuai_list': bankuai_list}
|
||
|
||
|
||
def build_huiyuan_stats_payload(
|
||
request,
|
||
huiyuan_id,
|
||
granularity,
|
||
year,
|
||
month,
|
||
include_guanshi=False,
|
||
include_zuzhang=False,
|
||
summary_date=None,
|
||
):
|
||
if not huiyuan_id:
|
||
return None, '缺少会员ID'
|
||
|
||
parsed, err = _parse_time_range(granularity, year, month, summary_date)
|
||
if err:
|
||
return None, err
|
||
|
||
start_dt = parsed['start_dt']
|
||
end_dt = parsed['end_dt']
|
||
trunc_func = parsed['trunc_func']
|
||
summary_q = parsed['summary_q']
|
||
granularity = parsed['granularity']
|
||
|
||
chongzhi_filter = {
|
||
'huiyuan_id': huiyuan_id,
|
||
'leixing': 1,
|
||
'zhuangtai': 3,
|
||
'CreateTime__gte': start_dt,
|
||
'CreateTime__lt': end_dt,
|
||
}
|
||
fenhong_filter = {
|
||
'huiyuan_id': huiyuan_id,
|
||
'CreateTime__gte': start_dt,
|
||
'CreateTime__lt': end_dt,
|
||
}
|
||
|
||
chongzhi_qs = filter_queryset_by_club(
|
||
Czjilu.query.filter(**chongzhi_filter), request,
|
||
).annotate(period=trunc_func).values('period').annotate(
|
||
chongzhi_count=Count('id'),
|
||
chongzhi_amount=Sum('jine'),
|
||
).order_by('period')
|
||
|
||
fenhong_qs = None
|
||
if include_guanshi or include_zuzhang:
|
||
fenhong_agg = {}
|
||
if include_guanshi:
|
||
fenhong_agg['guanshi_amount'] = Sum('fenhong')
|
||
if include_zuzhang:
|
||
fenhong_agg['zuzhang_amount'] = Sum('zuzhang_fenhong')
|
||
fenhong_qs = filter_gsfenhong_qs(
|
||
Gsfenhong.query.filter(**fenhong_filter), request,
|
||
).annotate(period=trunc_func).values('period').annotate(**fenhong_agg).order_by('period')
|
||
|
||
data_map = {}
|
||
for item in chongzhi_qs:
|
||
period_str = (
|
||
item['period'].strftime('%Y-%m-%d') if granularity == 'day'
|
||
else item['period'].strftime('%Y-%m') if granularity == 'month'
|
||
else item['period'].strftime('%Y')
|
||
)
|
||
data_map[period_str] = {
|
||
'chongzhi_count': item['chongzhi_count'],
|
||
'chongzhi_amount': float(item['chongzhi_amount'] or 0),
|
||
}
|
||
|
||
if fenhong_qs:
|
||
for item in fenhong_qs:
|
||
period_str = (
|
||
item['period'].strftime('%Y-%m-%d') if granularity == 'day'
|
||
else item['period'].strftime('%Y-%m') if granularity == 'month'
|
||
else item['period'].strftime('%Y')
|
||
)
|
||
if period_str not in data_map:
|
||
data_map[period_str] = {'chongzhi_count': 0, 'chongzhi_amount': 0.0}
|
||
if include_guanshi:
|
||
data_map[period_str]['guanshi_amount'] = float(item.get('guanshi_amount') or 0)
|
||
if include_zuzhang:
|
||
data_map[period_str]['zuzhang_amount'] = float(item.get('zuzhang_amount') or 0)
|
||
|
||
time_series = []
|
||
for period_str, vals in data_map.items():
|
||
guanshi = vals.get('guanshi_amount', 0) if include_guanshi else 0
|
||
zuzhang = vals.get('zuzhang_amount', 0) if include_zuzhang else 0
|
||
vals['shouyi'] = round(vals['chongzhi_amount'] - guanshi - zuzhang, 2)
|
||
vals['date'] = period_str
|
||
time_series.append(vals)
|
||
time_series.sort(key=lambda x: x['date'])
|
||
|
||
summary_chongzhi_filter = dict(chongzhi_filter)
|
||
summary_chongzhi_filter.pop('CreateTime__gte', None)
|
||
summary_chongzhi_filter.pop('CreateTime__lt', None)
|
||
summary_chongzhi_filter.update(_summary_date_filter(granularity, summary_q))
|
||
summary_chongzhi = filter_queryset_by_club(
|
||
Czjilu.query.filter(**summary_chongzhi_filter), request,
|
||
).aggregate(total_count=Count('id'), total_amount=Sum('jine'))
|
||
total_chongzhi_count = summary_chongzhi['total_count'] or 0
|
||
total_chongzhi_amount = float(summary_chongzhi['total_amount'] or 0)
|
||
|
||
total_guanshi = 0.0
|
||
total_zuzhang = 0.0
|
||
if include_guanshi or include_zuzhang:
|
||
summary_fenhong_filter = dict(fenhong_filter)
|
||
summary_fenhong_filter.pop('CreateTime__gte', None)
|
||
summary_fenhong_filter.pop('CreateTime__lt', None)
|
||
summary_fenhong_filter.update(_summary_date_filter(granularity, summary_q))
|
||
fenhong_agg = {}
|
||
if include_guanshi:
|
||
fenhong_agg['guanshi_sum'] = Sum('fenhong')
|
||
if include_zuzhang:
|
||
fenhong_agg['zuzhang_sum'] = Sum('zuzhang_fenhong')
|
||
summary_fenhong = filter_gsfenhong_qs(
|
||
Gsfenhong.query.filter(**summary_fenhong_filter), request,
|
||
).aggregate(**fenhong_agg)
|
||
total_guanshi = float(summary_fenhong.get('guanshi_sum') or 0)
|
||
total_zuzhang = float(summary_fenhong.get('zuzhang_sum') or 0)
|
||
|
||
total_shouyi = round(total_chongzhi_amount - total_guanshi - total_zuzhang, 2)
|
||
|
||
return {
|
||
**_meta(request),
|
||
'time_series': time_series,
|
||
'summary': {
|
||
'total_chongzhi_count': total_chongzhi_count,
|
||
'total_chongzhi_amount': total_chongzhi_amount,
|
||
'total_guanshi_fenhong': total_guanshi,
|
||
'total_zuzhang_fenhong': total_zuzhang,
|
||
'total_shouyi': total_shouyi,
|
||
},
|
||
}, None
|