v1.2.71 - Stats接口性能优化：改用数据库聚合查询替代全量加载

VERSION

@@ -1 +1 @@
-1.2.70
+VERSION=1.2.71

backend/VERSION

@@ -1 +1 @@
-1.2.70
+1.2.71

backend/app/routers/collections.py

@@ -276,68 +276,132 @@ def get_stats(
     current_user: User = Depends(get_current_user),
     db: Session = Depends(get_db)
 ):
-    """获取藏品统计"""
+    """获取藏品统计 - 使用数据库聚合查询优化性能"""
-    # 获取所有藏品
+    from sqlalchemy import case, func
-    if current_user.role == "admin":
+    from sqlalchemy.sql import expression
-        all_collections = db.query(Collection).all()
-    else:
-        all_collections = db.query(Collection).filter(
-            Collection.f99_91_user_id == current_user.f99_90_id
-        ).all()
     
-    # 总数
+    # 基础过滤条件
-    total_count = len(all_collections)
+    if current_user.role == "admin":
+        base_filter = True
+    else:
+        base_filter = Collection.f99_91_user_id == current_user.f99_90_id
+    
+    # 总数 - 使用 COUNT
+    total_count = db.query(func.count(Collection.f99_90_id)).filter(base_filter).scalar() or 0
     
     # 按分类统计
-    from collections import Counter
+    by_category = db.query(
-    by_category = Counter(c.f01_03_category for c in all_collections).items()
+        Collection.f01_03_category,
+        func.count(Collection.f99_90_id)
+    ).filter(base_filter).group_by(Collection.f01_03_category).all()
     
     # 按状态统计
-    by_status = Counter(c.f01_04_status for c in all_collections).items()
+    by_status = db.query(
+        Collection.f01_04_status,
+        func.count(Collection.f99_90_id)
+    ).filter(base_filter).group_by(Collection.f01_04_status).all()
     
     # 按是否评级统计
-    by_graded = Counter(c.f03_20_is_graded for c in all_collections).items()
+    by_graded = db.query(
+        Collection.f03_20_is_graded,
+        func.count(Collection.f99_90_id)
+    ).filter(base_filter).group_by(Collection.f03_20_is_graded).all()
     
-    # 新增：8 个分布统计
+    # 按包装统计
-    by_packaging = Counter(c.f02_12_packaging for c in all_collections if c.f02_12_packaging).items()
+    by_packaging = db.query(
-    by_rarity = Counter(c.f02_13_rarity for c in all_collections if c.f02_13_rarity).items()
+        Collection.f02_12_packaging,
-    by_version = Counter(c.f02_11_version for c in all_collections if c.f02_11_version).items()
+        func.count(Collection.f99_90_id)
-    by_grading_company = Counter(c.f03_21_grading_company for c in all_collections if c.f03_20_is_graded and c.f03_21_grading_company).items()
+    ).filter(base_filter, Collection.f02_12_packaging.isnot(None)).group_by(Collection.f02_12_packaging).all()
-    by_grading_score = Counter(c.f03_22_grading_score for c in all_collections if c.f03_20_is_graded and c.f03_22_grading_score).items()
-    by_special_mark = Counter(c.f04_30_special_mark for c in all_collections if c.f04_30_special_mark).items()
-    by_number_category = Counter(c.f02_14_number_category for c in all_collections if c.f02_14_number_category).items()
     
-    # 总成本： SUM(cost_price + repair_fee + grading_fee) for ALL collections
+    # 按稀有度统计
-    total_cost = sum(
+    by_rarity = db.query(
-        (c.f05_40_cost_price or 0) + (c.f05_43_repair_fee or 0) + (c.f05_44_grading_fee or 0)
+        Collection.f02_13_rarity,
-        for c in all_collections
+        func.count(Collection.f99_90_id)
-    )
+    ).filter(base_filter, Collection.f02_13_rarity.isnot(None)).group_by(Collection.f02_13_rarity).all()
     
-    # 预期利润： SUM(target_price - cost_price) for collections with target_price > 0
+    # 按版本统计
-    expected_profit = sum(
+    by_version = db.query(
-        (c.f05_41_target_price or 0) - (c.f05_40_cost_price or 0)
+        Collection.f02_11_version,
-        for c in all_collections
+        func.count(Collection.f99_90_id)
-        if c.f05_41_target_price and c.f05_41_target_price > 0
+    ).filter(base_filter, Collection.f02_11_version.isnot(None)).group_by(Collection.f02_11_version).all()
-    )
     
-    # 已售商品：状态为 sold 且出售价 > 0
+    # 按评级公司统计
-    sold_collections = [
+    by_grading_company = db.query(
-        c for c in all_collections 
+        Collection.f03_21_grading_company,
-        if c.f01_04_status == 'sold' and c.f05_42_goal_price and c.f05_42_goal_price > 0
+        func.count(Collection.f99_90_id)
-    ]
+    ).filter(base_filter, Collection.f03_20_is_graded == True, Collection.f03_21_grading_company.isnot(None)).group_by(Collection.f03_21_grading_company).all()
     
-    # 总收入：SUM(出售价) for 已售商品（售价>0）
+    # 按评级分数统计
-    total_revenue = sum(
+    by_grading_score = db.query(
-        c.f05_42_goal_price or 0
+        Collection.f03_22_grading_score,
-        for c in sold_collections
+        func.count(Collection.f99_90_id)
-    )
+    ).filter(base_filter, Collection.f03_20_is_graded == True, Collection.f03_22_grading_score.isnot(None)).group_by(Collection.f03_22_grading_score).all()
     
-    # 总利润（已实现利润）：SUM(出售价 - 成本价 - 修复费 - 评级费) for 已售商品
+    # 按特殊标记统计
-    # 单藏品总成本 = 成本价 + 修复费 + 评级费
+    by_special_mark = db.query(
-    total_profit = sum(
+        Collection.f04_30_special_mark,
-        (c.f05_42_goal_price or 0) - (c.f05_40_cost_price or 0) - (c.f05_43_repair_fee or 0) - (c.f05_44_grading_fee or 0)
+        func.count(Collection.f99_90_id)
-        for c in sold_collections
+    ).filter(base_filter, Collection.f04_30_special_mark.isnot(None)).group_by(Collection.f04_30_special_mark).all()
-    )
+    
+    # 按号码分类统计
+    by_number_category = db.query(
+        Collection.f02_14_number_category,
+        func.count(Collection.f99_90_id)
+    ).filter(base_filter, Collection.f02_14_number_category.isnot(None)).group_by(Collection.f02_14_number_category).all()
+    
+    # 财务统计 - 使用数据库 SUM
+    # 总成本 = SUM(cost_price + repair_fee + grading_fee)
+    cost_result = db.query(
+        func.coalesce(func.sum(
+            func.coalesce(Collection.f05_40_cost_price, 0) +
+            func.coalesce(Collection.f05_43_repair_fee, 0) +
+            func.coalesce(Collection.f05_44_grading_fee, 0)
+        ), 0)
+    ).filter(base_filter).scalar() or 0
+    
+    # 预期利润 = SUM(target_price - cost_price) where target_price > 0
+    target_result = db.query(
+        func.coalesce(func.sum(
+            func.coalesce(Collection.f05_41_target_price, 0) -
+            func.coalesce(Collection.f05_40_cost_price, 0)
+        ), 0)
+    ).filter(base_filter, Collection.f05_41_target_price > 0).scalar() or 0
+    
+    expected_profit = target_result
+    
+    # 已售商品过滤条件
+    sold_filter = base_filter & (Collection.f01_04_status == 'sold') & (Collection.f05_42_goal_price > 0)
+    
+    # 总收入
+    total_revenue = db.query(
+        func.coalesce(func.sum(Collection.f05_42_goal_price), 0)
+    ).filter(sold_filter).scalar() or 0
+    
+    # 总利润 = SUM(goal_price - cost_price - repair_fee - grading_fee)
+    total_profit = db.query(
+        func.coalesce(func.sum(
+            func.coalesce(Collection.f05_42_goal_price, 0) -
+            func.coalesce(Collection.f05_40_cost_price, 0) -
+            func.coalesce(Collection.f05_43_repair_fee, 0) -
+            func.coalesce(Collection.f05_44_grading_fee, 0)
+        ), 0)
+    ).filter(sold_filter).scalar() or 0
+    
+    # 盈亏统计
+    profit_count = db.query(func.count(Collection.f99_90_id)).filter(
+        sold_filter,
+        Collection.f05_42_goal_price > Collection.f05_40_cost_price
+    ).scalar() or 0
+    
+    loss_count = db.query(func.count(Collection.f99_90_id)).filter(
+        sold_filter,
+        Collection.f05_42_goal_price <= Collection.f05_40_cost_price
+    ).scalar() or 0
+    
+    # 目标总价
+    total_target = db.query(
+        func.coalesce(func.sum(func.coalesce(Collection.f05_41_target_price, 0)), 0)
+    ).filter(base_filter).scalar() or 0
     
     return {
         "totalCount": total_count,
@@ -351,16 +415,15 @@ def get_stats(
         "byGradingScore": [{"score": s, "count": n} for s, n in by_grading_score],
         "bySpecialMark": [{"mark": m, "count": n} for m, n in by_special_mark],
         "byNumberCategory": [{"numberCategory": n, "count": c} for n, c in by_number_category],
-        # 盈亏统计（只统计已售且有价格的藏品）
         "byProfitLoss": [
-            {"type": "profit", "label": "盈利", "count": sum(1 for c in sold_collections if c.f05_42_goal_price and c.f05_40_cost_price and c.f05_42_goal_price > c.f05_40_cost_price)},
+            {"type": "profit", "label": "盈利", "count": profit_count},
-            {"type": "loss", "label": "亏损", "count": sum(1 for c in sold_collections if c.f05_42_goal_price and c.f05_40_cost_price and c.f05_42_goal_price <= c.f05_40_cost_price)}
+            {"type": "loss", "label": "亏损", "count": loss_count}
         ],
-        "totalCost": total_cost,
+        "totalCost": float(cost_result),
-        "totalTarget": sum(c.f05_41_target_price or 0 for c in all_collections),
+        "totalTarget": float(total_target),
-        "expectedProfit": expected_profit,
+        "expectedProfit": float(expected_profit),
-        "totalRevenue": total_revenue,
+        "totalRevenue": float(total_revenue),
-        "totalProfit": total_profit
+        "totalProfit": float(total_profit)
     }
 
 

config/VERSION

@@ -1 +1 @@
-VERSION=1.2.70
+VERSION=1.2.71

frontend/package.json

@@ -1,6 +1,6 @@
 {
   "name": "jiachenlong-frontend",
-  "version": "1.2.70",
+  "version": "1.2.71",
   "private": true,
   "description": "甲辰藏品管理系统 - 移动端前端",
   "scripts": {