fix: auto-fix code issues (cron)

- 修复重复导入/字段
- 修复异常处理
- 修复PEP8格式问题
- 添加类型注解

backend/performance_manager.py

@@ -55,7 +55,7 @@ class CacheStats:
     expired: int = 0
     hit_rate: float = 0.0
 
-    def update_hit_rate(self):
+    def update_hit_rate(self) -> None:
         """更新命中率"""
         if self.total_requests > 0:
             self.hit_rate = round(self.hits / self.total_requests, 4)
@@ -194,7 +194,7 @@ class CacheManager:
         # 初始化缓存统计表
         self._init_cache_tables()
 
-    def _init_cache_tables(self):
+    def _init_cache_tables(self) -> None:
         """初始化缓存统计表"""
         conn = sqlite3.connect(self.db_path)
 
@@ -234,7 +234,7 @@ class CacheManager:
         except BaseException:
             return 1024  # 默认估算
 
-    def _evict_lru(self, required_space: int = 0):
+    def _evict_lru(self, required_space: int = 0) -> None:
         """LRU 淘汰策略"""
         with self.cache_lock:
             while self.current_memory_size + required_space > self.max_memory_size and self.memory_cache:
@@ -444,7 +444,7 @@ class CacheManager:
 
         return stats
 
-    def save_stats(self):
+    def save_stats(self) -> None:
         """保存缓存统计到数据库"""
         conn = sqlite3.connect(self.db_path)
 
@@ -618,7 +618,7 @@ class DatabaseSharding:
         # 初始化分片
         self._init_shards()
 
-    def _init_shards(self):
+    def _init_shards(self) -> None:
         """初始化分片"""
         # 计算每个分片的 key 范围
         chars = "0123456789abcdef"
@@ -645,7 +645,7 @@ class DatabaseSharding:
             if not os.path.exists(db_path):
                 self._create_shard_db(db_path)
 
-    def _create_shard_db(self, db_path: str):
+    def _create_shard_db(self, db_path: str) -> None:
         """创建分片数据库"""
         conn = sqlite3.connect(db_path)
 
@@ -792,7 +792,7 @@ class DatabaseSharding:
             print(f"迁移失败: {e}")
             return False
 
-    def _update_shard_stats(self, shard_id: str):
+    def _update_shard_stats(self, shard_id: str) -> None:
         """更新分片统计"""
         shard_info = self.shard_map.get(shard_id)
         if not shard_info:
@@ -923,7 +923,7 @@ class TaskQueue:
             except Exception as e:
                 print(f"Celery 初始化失败，使用内存任务队列: {e}")
 
-    def _init_task_tables(self):
+    def _init_task_tables(self) -> None:
         """初始化任务队列表"""
         conn = sqlite3.connect(self.db_path)
 
@@ -953,7 +953,7 @@ class TaskQueue:
         """检查任务队列是否可用"""
         return self.use_celery or True  # 内存模式也可用
 
-    def register_handler(self, task_type: str, handler: Callable):
+    def register_handler(self, task_type: str, handler: Callable) -> None:
         """注册任务处理器"""
         self.task_handlers[task_type] = handler
 
@@ -1014,7 +1014,7 @@ class TaskQueue:
 
         return task_id
 
-    def _execute_task(self, task_id: str):
+    def _execute_task(self, task_id: str) -> None:
         """执行任务（内存模式）"""
         with self.task_lock:
             task = self.tasks.get(task_id)
@@ -1055,7 +1055,7 @@ class TaskQueue:
 
         self._update_task_status(task)
 
-    def _save_task(self, task: TaskInfo):
+    def _save_task(self, task: TaskInfo) -> None:
         """保存任务到数据库"""
         conn = sqlite3.connect(self.db_path)
 
@@ -1084,7 +1084,7 @@ class TaskQueue:
         conn.commit()
         conn.close()
 
-    def _update_task_status(self, task: TaskInfo):
+    def _update_task_status(self, task: TaskInfo) -> None:
         """更新任务状态"""
         conn = sqlite3.connect(self.db_path)
 
@@ -1143,9 +1143,7 @@ class TaskQueue:
         with self.task_lock:
             return self.tasks.get(task_id)
 
-    def list_tasks(
-        self, status: str | None = None, task_type: str | None = None, limit: int = 100
-    ) -> list[TaskInfo]:
+    def list_tasks(self, status: str | None = None, task_type: str | None = None, limit: int = 100) -> list[TaskInfo]:
         """列出任务"""
         conn = sqlite3.connect(self.db_path)
         conn.row_factory = sqlite3.Row
@@ -1333,7 +1331,7 @@ class PerformanceMonitor:
         if metric_type == "db_query" and duration_ms > self.slow_query_threshold:
             self._record_slow_query(metric)
 
-    def _flush_metrics(self):
+    def _flush_metrics(self) -> None:
         """将缓冲区指标写入数据库"""
         if not self.metrics_buffer:
             return
@@ -1362,12 +1360,12 @@ class PerformanceMonitor:
 
         self.metrics_buffer = []
 
-    def _record_slow_query(self, metric: PerformanceMetric):
+    def _record_slow_query(self, metric: PerformanceMetric) -> None:
         """记录慢查询"""
         # 可以发送到专门的慢查询日志或监控系统
         print(f"[SLOW QUERY] {metric.endpoint}: {metric.duration_ms}ms")
 
-    def _trigger_alert(self, metric: PerformanceMetric):
+    def _trigger_alert(self, metric: PerformanceMetric) -> None:
         """触发告警"""
         alert_data = {
             "type": "performance_alert",
@@ -1382,7 +1380,7 @@ class PerformanceMonitor:
             except Exception as e:
                 print(f"告警处理失败: {e}")
 
-    def register_alert_handler(self, handler: Callable):
+    def register_alert_handler(self, handler: Callable) -> None:
         """注册告警处理器"""
         self.alert_handlers.append(handler)
 
@@ -1585,7 +1583,9 @@ class PerformanceMonitor:
 # ==================== 性能装饰器 ====================
 
 
-def cached(cache_manager: CacheManager, key_prefix: str = "", ttl: int = 3600, key_func: Callable | None = None):
+def cached(
+    cache_manager: CacheManager, key_prefix: str = "", ttl: int = 3600, key_func: Callable | None = None
+) -> None:
     """
     缓存装饰器
 
@@ -1598,7 +1598,7 @@ def cached(cache_manager: CacheManager, key_prefix: str = "", ttl: int = 3600, k
 
     def decorator(func: Callable) -> Callable:
         @wraps(func)
-        def wrapper(*args, **kwargs):
+        def wrapper(*args, **kwargs) -> None:
             # 生成缓存键
             if key_func:
                 cache_key = key_func(*args, **kwargs)
@@ -1625,7 +1625,7 @@ def cached(cache_manager: CacheManager, key_prefix: str = "", ttl: int = 3600, k
     return decorator
 
 
-def monitored(monitor: PerformanceMonitor, metric_type: str, endpoint: str | None = None):
+def monitored(monitor: PerformanceMonitor, metric_type: str, endpoint: str | None = None) -> None:
     """
     性能监控装饰器