sss

Signed-off-by: TsssIANHE <TIANHE@GMAIL.COM>

Author: tianhe

backend_api_python/app/config/api_keys.py

@@ -68,6 +68,42 @@ def GROK_API_KEY(cls):
         from app.utils.config_loader import load_addon_config
         val = load_addon_config().get('grok', {}).get('api_key')
         return val if val else ''
+    
+    @property
+    def TAVILY_API_KEYS(cls):
+        """Tavily Search API keys (comma-separated for rotation)"""
+        env_val = os.getenv('TAVILY_API_KEYS', '').strip()
+        if env_val:
+            return [k.strip() for k in env_val.split(',') if k.strip()]
+        from app.utils.config_loader import load_addon_config
+        val = load_addon_config().get('tavily', {}).get('api_keys', '')
+        if val:
+            return [k.strip() for k in val.split(',') if k.strip()]
+        return []
+    
+    @property
+    def BOCHA_API_KEYS(cls):
+        """Bocha Search API keys (comma-separated for rotation)"""
+        env_val = os.getenv('BOCHA_API_KEYS', '').strip()
+        if env_val:
+            return [k.strip() for k in env_val.split(',') if k.strip()]
+        from app.utils.config_loader import load_addon_config
+        val = load_addon_config().get('bocha', {}).get('api_keys', '')
+        if val:
+            return [k.strip() for k in val.split(',') if k.strip()]
+        return []
+    
+    @property
+    def SERPAPI_KEYS(cls):
+        """SerpAPI keys (comma-separated for rotation)"""
+        env_val = os.getenv('SERPAPI_KEYS', '').strip()
+        if env_val:
+            return [k.strip() for k in env_val.split(',') if k.strip()]
+        from app.utils.config_loader import load_addon_config
+        val = load_addon_config().get('serpapi', {}).get('api_keys', '')
+        if val:
+            return [k.strip() for k in val.split(',') if k.strip()]
+        return []
 
 
 class APIKeys(metaclass=MetaAPIKeys):

backend_api_python/app/data_sources/__init__.py

@@ -1,8 +1,61 @@
 """
 数据源模块
 支持多种市场的K线数据获取
+
+改进版本（参考 daily_stock_analysis 项目）:
+- 熔断器保护 (circuit_breaker)
+- 数据缓存 (cache_manager)
+- 防封禁策略 (rate_limiter)
+- 多数据源自动切换 (data_manager)
 """
 from app.data_sources.factory import DataSourceFactory
+from app.data_sources.circuit_breaker import (
+    CircuitBreaker,
+    get_ashare_circuit_breaker,
+    get_realtime_circuit_breaker
+)
+from app.data_sources.cache_manager import (
+    DataCache,
+    get_realtime_cache,
+    get_kline_cache,
+    get_stock_info_cache
+)
+from app.data_sources.rate_limiter import (
+    RateLimiter,
+    get_eastmoney_limiter,
+    get_tencent_limiter,
+    get_akshare_limiter,
+    get_random_user_agent,
+    random_sleep,
+    retry_with_backoff
+)
+from app.data_sources.data_manager import (
+    AShareDataManager,
+    get_ashare_data_manager
+)
 
-__all__ = ['DataSourceFactory']
+__all__ = [
+    # 工厂
+    'DataSourceFactory',
+    # 熔断器
+    'CircuitBreaker',
+    'get_ashare_circuit_breaker',
+    'get_realtime_circuit_breaker',
+    # 缓存
+    'DataCache',
+    'get_realtime_cache',
+    'get_kline_cache',
+    'get_stock_info_cache',
+    # 限流器
+    'RateLimiter',
+    'get_eastmoney_limiter',
+    'get_tencent_limiter',
+    'get_akshare_limiter',
+    'get_random_user_agent',
+    'random_sleep',
+    'retry_with_backoff',
+    # 数据管理器
+    'AShareDataManager',
+    'get_ashare_data_manager',
+]
 

backend_api_python/app/data_sources/cache_manager.py

@@ -0,0 +1,232 @@
+# -*- coding: utf-8 -*-
+"""
+===================================
+数据缓存管理模块
+===================================
+
+参考 daily_stock_analysis 项目实现
+用于缓存实时行情和K线数据，减少重复请求
+
+特性：
+1. TTL (Time To Live) 过期机制
+2. LRU (Least Recently Used) 淘汰策略
+3. 按数据类型分区管理
+"""
+
+import time
+import logging
+from typing import Dict, Any, Optional, List
+from collections import OrderedDict
+from dataclasses import dataclass, field
+from datetime import datetime
+import threading
+
+logger = logging.getLogger(__name__)
+
+
+@dataclass
+class CacheEntry:
+    """缓存条目"""
+    data: Any
+    timestamp: float
+    ttl: float
+    hit_count: int = 0
+    
+    def is_expired(self) -> bool:
+        """检查是否过期"""
+        return time.time() - self.timestamp > self.ttl
+    
+    def age(self) -> float:
+        """返回缓存年龄（秒）"""
+        return time.time() - self.timestamp
+
+
+class DataCache:
+    """
+    数据缓存管理器
+    
+    特性：
+    - TTL 过期机制
+    - 最大容量限制
+    - LRU 淘汰策略
+    - 线程安全
+    """
+    
+    def __init__(
+        self,
+        name: str = "default",
+        default_ttl: float = 600.0,  # 默认10分钟
+        max_size: int = 1000         # 最大缓存条目数
+    ):
+        self.name = name
+        self.default_ttl = default_ttl
+        self.max_size = max_size
+        self._cache: OrderedDict[str, CacheEntry] = OrderedDict()
+        self._lock = threading.RLock()
+        
+        # 统计信息
+        self._hits = 0
+        self._misses = 0
+    
+    def get(self, key: str) -> Optional[Any]:
+        """
+        获取缓存数据
+        
+        Returns:
+            缓存的数据，不存在或过期返回 None
+        """
+        with self._lock:
+            if key not in self._cache:
+                self._misses += 1
+                return None
+            
+            entry = self._cache[key]
+            
+            # 检查是否过期
+            if entry.is_expired():
+                del self._cache[key]
+                self._misses += 1
+                logger.debug(f"[缓存] {self.name}:{key} 已过期，删除")
+                return None
+            
+            # 更新访问顺序（LRU）
+            self._cache.move_to_end(key)
+            entry.hit_count += 1
+            self._hits += 1
+            
+            logger.debug(f"[缓存命中] {self.name}:{key} (年龄: {entry.age():.0f}s/{entry.ttl:.0f}s)")
+            return entry.data
+    
+    def set(
+        self,
+        key: str,
+        data: Any,
+        ttl: Optional[float] = None
+    ) -> None:
+        """
+        设置缓存数据
+        
+        Args:
+            key: 缓存键
+            data: 缓存数据
+            ttl: 过期时间（秒），None 使用默认值
+        """
+        with self._lock:
+            # 检查容量，执行 LRU 淘汰
+            while len(self._cache) >= self.max_size:
+                oldest_key, _ = self._cache.popitem(last=False)
+                logger.debug(f"[缓存] {self.name} 容量已满，淘汰: {oldest_key}")
+            
+            actual_ttl = ttl if ttl is not None else self.default_ttl
+            self._cache[key] = CacheEntry(
+                data=data,
+                timestamp=time.time(),
+                ttl=actual_ttl
+            )
+            
+            logger.debug(f"[缓存更新] {self.name}:{key} TTL={actual_ttl}s")
+    
+    def delete(self, key: str) -> bool:
+        """删除缓存条目"""
+        with self._lock:
+            if key in self._cache:
+                del self._cache[key]
+                logger.debug(f"[缓存] {self.name}:{key} 已删除")
+                return True
+            return False
+    
+    def clear(self) -> int:
+        """清空缓存"""
+        with self._lock:
+            count = len(self._cache)
+            self._cache.clear()
+            logger.info(f"[缓存] {self.name} 已清空 {count} 条记录")
+            return count
+    
+    def cleanup_expired(self) -> int:
+        """清理过期条目"""
+        with self._lock:
+            expired_keys = [
+                key for key, entry in self._cache.items()
+                if entry.is_expired()
+            ]
+            for key in expired_keys:
+                del self._cache[key]
+            
+            if expired_keys:
+                logger.debug(f"[缓存] {self.name} 清理 {len(expired_keys)} 条过期记录")
+            return len(expired_keys)
+    
+    def stats(self) -> Dict[str, Any]:
+        """获取缓存统计信息"""
+        with self._lock:
+            total_requests = self._hits + self._misses
+            hit_rate = self._hits / total_requests if total_requests > 0 else 0
+            
+            return {
+                'name': self.name,
+                'size': len(self._cache),
+                'max_size': self.max_size,
+                'hits': self._hits,
+                'misses': self._misses,
+                'hit_rate': f"{hit_rate:.1%}",
+                'default_ttl': self.default_ttl
+            }
+
+
+# ============================================
+# 全局缓存实例
+# ============================================
+
+# A股实时行情缓存（20分钟TTL，全市场数据量大）
+_ashare_realtime_cache = DataCache(
+    name="ashare_realtime",
+    default_ttl=1200.0,  # 20分钟
+    max_size=6000        # 约5000+股票
+)
+
+# K线数据缓存（5分钟TTL，按需缓存）
+_kline_cache = DataCache(
+    name="kline",
+    default_ttl=300.0,   # 5分钟
+    max_size=500         # 最多500个交易对
+)
+
+# 股票基本信息缓存（1天TTL）
+_stock_info_cache = DataCache(
+    name="stock_info",
+    default_ttl=86400.0,  # 24小时
+    max_size=6000
+)
+
+
+def get_realtime_cache() -> DataCache:
+    """获取实时行情缓存"""
+    return _ashare_realtime_cache
+
+
+def get_kline_cache() -> DataCache:
+    """获取K线数据缓存"""
+    return _kline_cache
+
+
+def get_stock_info_cache() -> DataCache:
+    """获取股票信息缓存"""
+    return _stock_info_cache
+
+
+def generate_kline_cache_key(
+    symbol: str,
+    timeframe: str,
+    limit: int,
+    before_time: Optional[int] = None
+) -> str:
+    """
+    生成K线缓存键
+    
+    格式: symbol:timeframe:limit[:before_time]
+    """
+    key = f"{symbol}:{timeframe}:{limit}"
+    if before_time:
+        key += f":{before_time}"
+    return key