缓存优化

backend/app/api/endpoints/events.py

@@ -1,6 +1,7 @@
 # app/api/endpoints/events.py
+import time
 from datetime import timedelta
-from typing import List
+from typing import Dict, List, Tuple
 
 from fastapi import APIRouter, Depends, HTTPException, Query
 from sqlalchemy.orm import Session
@@ -26,6 +27,10 @@ router = APIRouter()
 # 排名轨迹最多返回多少个点，避免长时间跨度下数据过大
 MAX_RANKING_POINTS = 30
 
+# --- 轻量级接口缓存配置 ---
+_UNIFIED_EVENTS_CACHE: Dict[str, Tuple[float, PaginatedUnifiedEventResponse]] = {}
+CACHE_TTL_SECONDS = 60
+# ---------------------------
 
 @router.get("/unified", response_model=PaginatedUnifiedEventResponse)
 def list_unified_events(
@@ -37,6 +42,17 @@ def list_unified_events(
     db: Session = Depends(get_db),
 ):
     """分页返回统一事件，附带各平台热搜、排名轨迹和标签。"""
+    
+    # --- 1. 尝试从缓存读取 ---
+    cache_key = f"{min_hot}:{hours}:{sort_by}:{skip}:{limit}"
+    current_time = time.time()
+    
+    if cache_key in _UNIFIED_EVENTS_CACHE:
+        expire_time, cached_data = _UNIFIED_EVENTS_CACHE[cache_key]
+        if current_time < expire_time:
+            return cached_data
+    # -----------------------
+
     time_limit = utcnow() - timedelta(hours=hours)
 
     # 先查总数，用于前端判断是否还有更多
@@ -149,7 +165,17 @@ def list_unified_events(
         )
 
     has_more = (skip + limit) < total
-    return PaginatedUnifiedEventResponse(total=total, has_more=has_more, data=results)
+    response = PaginatedUnifiedEventResponse(total=total, has_more=has_more, data=results)
+
+    # --- 2. 写入缓存 ---
+    if len(_UNIFIED_EVENTS_CACHE) > 1000:
+        # 防止内存无限增长
+        _UNIFIED_EVENTS_CACHE.clear()
+        
+    _UNIFIED_EVENTS_CACHE[cache_key] = (current_time + CACHE_TTL_SECONDS, response)
+    # ------------------
+
+    return response
 
 
 @router.get("/unified/{event_id}", response_model=UnifiedEventResponse)

backend/app/api/endpoints/preferences.py

@@ -1,4 +1,5 @@
-from typing import List
+import time
+from typing import Any, Dict, List, Tuple
 
 from fastapi import APIRouter, Depends, HTTPException, Query, status
 from sqlalchemy.exc import IntegrityError
@@ -16,6 +17,16 @@ from app.services.matching_service import recommend_events_for_user
 
 router = APIRouter()
 
+# --- 轻量级接口缓存配置 ---
+_RECOMMEND_CACHE: Dict[str, Tuple[float, Any]] = {}
+CACHE_TTL_SECONDS = 60
+
+def _invalidate_user_cache(user_id: int):
+    """清除某个用户的推荐结果缓存（当用户新增或删除关键词时调用）"""
+    keys_to_delete = [k for k in _RECOMMEND_CACHE.keys() if k.startswith(f"{user_id}:")]
+    for k in keys_to_delete:
+        _RECOMMEND_CACHE.pop(k, None)
+# ---------------------------
 
 def _ensure_self_access(path_user_id: int, current_user: AppUser) -> None:
     """校验路径 user_id 是否为当前登录用户本人。"""
@@ -79,6 +90,7 @@ def create_user_preference(
         )
 
     db.refresh(db_obj)
+    _invalidate_user_cache(user_id)  # 失效推荐缓存
     return db_obj
 
 
@@ -107,6 +119,7 @@ def delete_user_preference(
 
     db.delete(preference)
     db.commit()
+    _invalidate_user_cache(user_id)  # 失效推荐缓存
     return None
 
 
@@ -127,6 +140,16 @@ def recommend_events(
     """基于用户兴趣词推荐事件（精确匹配 + 语义匹配）。"""
     _ensure_self_access(user_id, current_user)
 
+    # --- 1. 尝试从缓存读取 ---
+    cache_key = f"{user_id}:{min_hot}:{hours}:{limit}:{semantic_threshold}:{sort_by}"
+    current_time = time.time()
+    
+    if cache_key in _RECOMMEND_CACHE:
+        expire_time, cached_data = _RECOMMEND_CACHE[cache_key]
+        if current_time < expire_time:
+            return cached_data
+    # -----------------------
+
     matched = recommend_events_for_user(
         db,
         user_id=user_id,
@@ -155,8 +178,18 @@ def recommend_events(
             )
         )
 
-    return UserPreferenceRecommendationResponse(
+    response = UserPreferenceRecommendationResponse(
         user_id=user_id,
         total=len(result_data),
         data=result_data,
     )
+
+    # --- 2. 写入缓存 ---
+    if len(_RECOMMEND_CACHE) > 2000:
+        # 防止内存无限增长
+        _RECOMMEND_CACHE.clear()
+        
+    _RECOMMEND_CACHE[cache_key] = (current_time + CACHE_TTL_SECONDS, response)
+    # ------------------
+
+    return response

backend/app/services/delivery_service.py

@@ -2,6 +2,7 @@
 # 由 APScheduler 每分钟调用，检查当前时刻是否有用户需要接收推送，
 # 如匹配则生成摘要邮件并发送，同时写入 DeliveryHistory 防重复。
 import logging
+import os
 from logging.handlers import TimedRotatingFileHandler
 from dataclasses import dataclass, field
 from datetime import datetime, time as dt_time, timedelta, timezone, tzinfo
@@ -50,17 +51,17 @@ logger.setLevel(logging.INFO)
 logger.propagate = False
 
 # 推送时间窗口：实际执行时刻与设定时间的最大容差（分钟）
-DELIVERY_WINDOW_MINUTES = 2
+DELIVERY_WINDOW_MINUTES = int(os.getenv("DELIVERY_WINDOW_MINUTES", 2))
 # 同一用户两次推送之间的最小间隔（分钟）
-MIN_PUSH_INTERVAL_MINUTES = 30
+MIN_PUSH_INTERVAL_MINUTES = int(os.getenv("MIN_PUSH_INTERVAL_MINUTES", 30))
 # 单次推送最多携带的事件数
-MAX_EVENTS_PER_PUSH = 12
+MAX_EVENTS_PER_PUSH = int(os.getenv("MAX_EVENTS_PER_PUSH", 12))
 # 默认模式热度阈值（无关键词或无匹配时使用）
-DEFAULT_MODE_HOT_THRESHOLD = 3
+DEFAULT_MODE_HOT_THRESHOLD = int(os.getenv("DEFAULT_MODE_HOT_THRESHOLD", 3))
 # 默认模式查询时间窗口（小时）
-DEFAULT_MODE_HOURS = 48
+DEFAULT_MODE_HOURS = int(os.getenv("DEFAULT_MODE_HOURS", 24))
 # 用户时区无效时的兜底时区
-DEFAULT_FALLBACK_TIMEZONE = "Asia/Shanghai"
+DEFAULT_FALLBACK_TIMEZONE = os.getenv("DEFAULT_FALLBACK_TIMEZONE", "Asia/Shanghai")
 
 
 # ==========================================