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@ -1,6 +0,0 @@
# context_compression: off | beta
context_compression: off
# review_mode: off | standard | thorough
review_mode: off
# auto_transition: true | false
auto_transition: true

14
.env

@ -22,17 +22,3 @@ CONTAINER_PORT=8600
# 数据目录
DATA_DIR=E:\docker_workspace\futures_datas
# MySQL 配置
MYSQL_HOST=192.168.0.222
MYSQL_PORT=3306
MYSQL_USER=root
MYSQL_PASSWORD=1qazse42W3
MYSQL_DATABASE=buffer_platform
# Redis 配置
REDIS_HOST=192.168.0.222
REDIS_PORT=6380
REDIS_DB=1
REDIS_PASSWORD=
REDIS_TTL_SECONDS=2592000

3
.gitignore vendored

@ -27,6 +27,3 @@ Thumbs.db
# Cache
cache/*.pkl
# Worktrees
.worktrees/

@ -1,14 +1,11 @@
"""
期货智析数据库 - 独立存储
"""
import logging
from pathlib import Path
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker, declarative_base
from datetime import datetime
logger = logging.getLogger(__name__)
# 数据目录
DATA_DIR = Path(__file__).resolve().parent.parent / "data"
DATA_DIR.mkdir(parents=True, exist_ok=True)
@ -26,11 +23,7 @@ AnalysisBase = declarative_base()
def get_analysis_db():
"""获取期货智析数据库会话。
分析数据量较小复盘计划评分等始终使用 SQLite 以保证稳定性
AnalysisBase 绑定的是 analysis_engine (SQLite)ORM 模型均基于此定义
"""
"""获取期货智析数据库会话"""
db = AnalysisSessionLocal()
try:
yield db
@ -39,7 +32,7 @@ def get_analysis_db():
def init_analysis_db():
"""初始化期货智析数据库表SQLite 兜底)。"""
"""初始化期货智析数据库表"""
# 确保导入所有模型类,使其注册到 AnalysisBase
from app import analysis_models
# 直接导入 analysis_models 模块中的所有类
@ -55,19 +48,6 @@ def init_analysis_db():
_migrate_add_columns()
def init_analysis_mysql(mysql_engine):
"""初始化期货智析数据库表MySQL"""
from app import analysis_models
from app.analysis_models import (
FuturesAnalysis, WatchedSymbol, AIModelConfig, AnalysisSettings,
AIAnalysisCache, ReviewDate, SymbolRanking, TradingPlan,
SymbolScoreV2, TradingPlanV2, SectorHeat, ReviewPlanV2,
TradeRecord, TradeImportBatch,
)
AnalysisBase.metadata.create_all(bind=mysql_engine)
logger.info("MySQL analysis 表结构初始化完成")
def _migrate_add_columns():
"""为已有表添加新增列(兼容旧数据库)"""
import sqlite3

@ -1,116 +0,0 @@
"""
期货智析数据库迁移 - SQLite MySQL
"""
import logging
from sqlalchemy.orm import sessionmaker, make_transient
from app.analysis_db import analysis_engine, AnalysisBase
from app.analysis_models import (
FuturesAnalysis, WatchedSymbol, AIModelConfig, AnalysisSettings,
AIAnalysisCache, ReviewDate, SymbolRanking, TradingPlan,
SymbolScoreV2, TradingPlanV2, SectorHeat, ReviewPlanV2,
TradeRecord, TradeImportBatch,
)
from app.mysql_database import mysql_engine
logger = logging.getLogger(__name__)
# 所有 analysis 模型类,按依赖顺序排列
ANALYSIS_MODELS = [
FuturesAnalysis, WatchedSymbol, AIModelConfig, AnalysisSettings,
AIAnalysisCache, ReviewDate, SymbolRanking, TradingPlan,
SymbolScoreV2, TradingPlanV2, SectorHeat, ReviewPlanV2,
TradeRecord, TradeImportBatch,
]
def migrate_analysis_sqlite_to_mysql():
"""
SQLite futures_analysis.db 中的数据迁移到 MySQL
Returns:
bool: 迁移是否成功跳过也视为成功
"""
if mysql_engine is None:
logger.warning("MySQL 未初始化,跳过 analysis 数据迁移")
return True
try:
mysql_count = _count_mysql_analysis_records()
if mysql_count > 0:
logger.info(f"MySQL analysis 表已有数据 ({mysql_count} 条),跳过迁移")
return True
logger.info("开始将 SQLite analysis 数据迁移到 MySQL...")
data = _read_sqlite_analysis_data()
if not data:
logger.info("SQLite analysis 数据库为空,无需迁移")
return True
if _write_mysql_analysis_data(data):
total = sum(len(records) for records in data.values())
logger.info(f"Analysis 数据迁移完成,共迁移 {total} 条记录")
return True
else:
logger.error("Analysis 数据迁移失败")
return False
except Exception as e:
logger.error(f"Analysis 数据迁移异常: {e}")
return False
def _count_mysql_analysis_records():
"""统计 MySQL 中 analysis 表的总记录数。"""
SessionLocal = sessionmaker(bind=mysql_engine)
total = 0
with SessionLocal() as db:
for model in ANALYSIS_MODELS:
try:
total += db.query(model).count()
except Exception as e:
logger.warning(f"统计 MySQL {model.__tablename__} 记录数失败: {e}")
return total
def _read_sqlite_analysis_data():
"""从 SQLite 读取所有 analysis 数据。"""
SessionLocal = sessionmaker(bind=analysis_engine)
data = {}
with SessionLocal() as db:
for model in ANALYSIS_MODELS:
try:
records = db.query(model).all()
if records:
data[model.__tablename__] = records
logger.info(f"从 SQLite 读取 {model.__tablename__}: {len(records)}")
except Exception as e:
logger.warning(f"读取 SQLite {model.__tablename__} 失败: {e}")
return data
def _write_mysql_analysis_data(data):
"""将 analysis 数据写入 MySQL。"""
SessionLocal = sessionmaker(bind=mysql_engine)
with SessionLocal() as db:
try:
for model in ANALYSIS_MODELS:
records = data.get(model.__tablename__, [])
if not records:
continue
for record in records:
# 将对象从原 session 中脱离,使其可加入新 session
make_transient(record)
db.add(record)
db.commit()
return True
except Exception as e:
db.rollback()
logger.error(f"写入 MySQL analysis 数据失败: {e}")
return False

@ -1,14 +1,14 @@
"""
AI模型配置接口 - 管理AI分析模型的配置
"""
import json
import logging
from pathlib import Path
from typing import Optional
from fastapi import APIRouter, Depends, HTTPException
from pydantic import BaseModel
from app.config_store import get_config_store
logger = logging.getLogger(__name__)
router = APIRouter(prefix="/ai-config", tags=["AI模型配置"])
@ -38,26 +38,45 @@ class SaveAIConfigRequest(BaseModel):
analysis_settings: Optional[dict] = None
def _default_ai_config() -> dict:
"""AI 配置默认值"""
return {
"models": [],
"active_model": None,
"analysis_settings": {
"enable_technical_analysis": True,
"enable_fundamental_analysis": False,
"enable_sentiment_analysis": False,
"risk_tolerance": "medium",
"max_position_pct": 10
CONFIG_DIR = Path(__file__).resolve().parent.parent.parent / "config"
AI_CONFIG_FILE = CONFIG_DIR / "ai_config.json"
def _ensure_config_dir():
CONFIG_DIR.mkdir(parents=True, exist_ok=True)
def _load_ai_config() -> dict:
"""加载AI配置"""
_ensure_config_dir()
if not AI_CONFIG_FILE.exists():
return {
"models": [],
"active_model": None,
"analysis_settings": {
"enable_technical_analysis": True,
"enable_fundamental_analysis": False,
"enable_sentiment_analysis": False,
"risk_tolerance": "medium",
"max_position_pct": 10
}
}
}
with open(AI_CONFIG_FILE, "r", encoding="utf-8") as f:
return json.load(f)
def _save_ai_config(config: dict):
"""保存AI配置"""
_ensure_config_dir()
with open(AI_CONFIG_FILE, "w", encoding="utf-8") as f:
json.dump(config, f, ensure_ascii=False, indent=4)
@router.get("", response_model=AIConfigResponse)
def get_ai_config():
"""获取当前AI模型配置"""
try:
config = get_config_store().get_config("ai", _default_ai_config())
config = _load_ai_config()
return {"success": True, "data": config}
except Exception as e:
logger.error(f"加载AI配置失败: {e}")
@ -73,7 +92,7 @@ def save_ai_config(config: SaveAIConfigRequest):
"active_model": config.active_model,
"analysis_settings": config.analysis_settings or {}
}
get_config_store().set_config("ai", config_dict)
_save_ai_config(config_dict)
return {"success": True, "message": "AI配置保存成功"}
except Exception as e:
logger.error(f"保存AI配置失败: {e}")

@ -3,9 +3,12 @@
"""
import json
import logging
import shutil
from pathlib import Path
from typing import Optional
from fastapi import APIRouter, Depends, HTTPException, UploadFile, File, Body, Request
from fastapi.responses import JSONResponse
from sqlalchemy.orm import Session
from pydantic import BaseModel
@ -14,7 +17,6 @@ from app.services.collector import fetch_symbol_data
from app.services.cache import save_market_data, check_cache_status, get_cached_data, create_task
from app.services.scheduler import add_job
from app.schemas import CandleItem, TimeframeData, SymbolDataResponse
from app.config_store import get_config_store
logger = logging.getLogger(__name__)
router = APIRouter(prefix="/config", tags=["品种配置"])
@ -26,11 +28,23 @@ class BatchFetchRequest(BaseModel):
data_type: str = "futures"
selected_symbols: Optional[str] = None # 逗号分隔的合约代码
# 配置文件存储路径
CONFIG_DIR = Path(__file__).resolve().parent.parent.parent / "config"
CONFIG_FILE = CONFIG_DIR / "symbols_config.json"
def _ensure_config_dir():
CONFIG_DIR.mkdir(parents=True, exist_ok=True)
@router.get("")
def get_config():
"""获取当前品种配置"""
return get_config_store().get_config("symbols", {"futures": {}, "stock": {}})
_ensure_config_dir()
if not CONFIG_FILE.exists():
return {"futures": {}, "stock": {}}
with open(CONFIG_FILE, "r", encoding="utf-8") as f:
return json.load(f)
@router.post("/upload")
@ -46,6 +60,8 @@ async def upload_config(
"stock": {"平安银行": "000001"}
}
"""
_ensure_config_dir()
try:
if file:
content = await file.read()
@ -60,7 +76,8 @@ async def upload_config(
if not isinstance(data, dict):
raise HTTPException(status_code=400, detail="配置文件必须是 JSON 对象")
get_config_store().set_config("symbols", data)
with open(CONFIG_FILE, "w", encoding="utf-8") as f:
json.dump(data, f, ensure_ascii=False, indent=4)
futures_count = len(data.get("futures", {}))
stock_count = len(data.get("stock", {}))
@ -87,7 +104,13 @@ def batch_fetch_all(
periods = request.periods
data_type = request.data_type
selected_symbols = request.selected_symbols
config = get_config_store().get_config("symbols", {"futures": {}, "stock": {}})
_ensure_config_dir()
if not CONFIG_FILE.exists():
raise HTTPException(status_code=400, detail="请先上传品种配置文件")
with open(CONFIG_FILE, "r", encoding="utf-8") as f:
config = json.load(f)
symbols_dict = config.get(data_type, {})
if not symbols_dict:
raise HTTPException(status_code=400, detail=f"配置中没有 {data_type} 类型的品种")
@ -213,7 +236,13 @@ def batch_create_tasks(
"""
根据配置文件为所有品种批量创建定时任务
"""
config = get_config_store().get_config("symbols", {"futures": {}, "stock": {}})
_ensure_config_dir()
if not CONFIG_FILE.exists():
raise HTTPException(status_code=400, detail="请先上传品种配置文件")
with open(CONFIG_FILE, "r", encoding="utf-8") as f:
config = json.load(f)
symbols_dict = config.get(data_type, {})
if not symbols_dict:
raise HTTPException(status_code=400, detail=f"配置中没有 {data_type} 类型的品种")

@ -3,6 +3,7 @@
"""
import json
import logging
from pathlib import Path
from typing import Optional
import threading
@ -14,20 +15,25 @@ from app.analysis_db import get_analysis_db
from app.analysis_models import FuturesAnalysis, WatchedSymbol, AIModelConfig, AnalysisSettings, AIAnalysisCache
from app.services.cache import get_cached_data, get_latest_cached, save_market_data
from app.services.collector import fetch_symbol_data
from app.config_store import get_config_store
logger = logging.getLogger(__name__)
router = APIRouter(prefix="/futures", tags=["期货智析"])
CONFIG_DIR = Path(__file__).resolve().parent.parent.parent / "config"
SYMBOLS_CONFIG_FILE = CONFIG_DIR / "symbols_config.json"
def _load_symbols_config() -> dict:
"""加载品种配置文件"""
return get_config_store().get_config("symbols", {"futures": {}, "stock": {}})
if not SYMBOLS_CONFIG_FILE.exists():
return {"futures": {}, "stock": {}}
with open(SYMBOLS_CONFIG_FILE, "r", encoding="utf-8") as f:
return json.load(f)
@router.get("/list")
def get_futures_list(db: Session = Depends(get_db)):
"""获取所有期货品种列表及摘要信息"""
"""获取所有期货品种列表及摘要信息从symbols_config.json读取"""
config = _load_symbols_config()
futures_config = config.get("futures", {})

@ -487,8 +487,13 @@ def get_kline_with_trades(
def _resolve_symbol_from_config(variety_code: str) -> str:
"""从品种配置中查找品种代码对应的当前合约"""
from app.config_store import get_config_store
config = get_config_store().get_config("symbols", {"futures": {}, "stock": {}})
import json as _json
from pathlib import Path
config_path = Path(__file__).resolve().parent.parent.parent / "config" / "symbols_config.json"
if not config_path.exists():
return variety_code
with open(config_path, "r", encoding="utf-8") as f:
config = _json.load(f)
for name, contract in config.get("futures", {}).items():
if contract.upper().startswith(variety_code.upper()):
return contract

@ -3,10 +3,6 @@
"""
import os
from pathlib import Path
from dotenv import load_dotenv
# 加载 .env 文件
load_dotenv()
# 项目根目录
BASE_DIR = Path(__file__).resolve().parent.parent.parent
@ -38,17 +34,3 @@ LOG_LEVEL = os.getenv("BUFFER_LOG_LEVEL", "INFO")
# 调度器
SCHEDULER_MAX_INSTANCES = 1 # 同一任务不允许重叠执行
# Redis 配置
REDIS_HOST = os.getenv("REDIS_HOST", "localhost")
REDIS_PORT = int(os.getenv("REDIS_PORT", "6379"))
REDIS_DB = int(os.getenv("REDIS_DB", "0"))
REDIS_PASSWORD = os.getenv("REDIS_PASSWORD", "")
REDIS_TTL_SECONDS = int(os.getenv("REDIS_TTL_SECONDS", "2592000")) # 30 天
# MySQL 配置
MYSQL_HOST = os.getenv("MYSQL_HOST", "localhost")
MYSQL_PORT = int(os.getenv("MYSQL_PORT", "3306"))
MYSQL_USER = os.getenv("MYSQL_USER", "root")
MYSQL_PASSWORD = os.getenv("MYSQL_PASSWORD", "")
MYSQL_DATABASE = os.getenv("MYSQL_DATABASE", "buffer_platform")

@ -1,52 +0,0 @@
"""
配置迁移 - JSON 配置文件 MySQL
"""
import logging
from app.config_store import get_config_store, CONFIG_FILES, DEFAULT_CONFIGS
logger = logging.getLogger(__name__)
CONFIG_KEYS = ["symbols", "ai"]
def migrate_configs_to_mysql():
"""
JSON 配置文件迁移到 MySQL
Returns:
bool: 迁移是否成功
"""
store = get_config_store()
if not store.storage_manager.check_mysql():
logger.warning("MySQL 不可用,跳过配置迁移")
return True
if store.session_maker is None:
logger.warning("MySQL session 未初始化,跳过配置迁移")
return True
migrated_count = 0
skipped_count = 0
for key in CONFIG_KEYS:
try:
if store._config_exists_in_mysql(key):
logger.info(f"MySQL 配置 [{key}] 已存在,跳过迁移")
skipped_count += 1
continue
value = store._load_json_from_file(key)
if value is None:
value = DEFAULT_CONFIGS.get(key, {})
logger.info(f"JSON 配置 [{key}] 不存在或损坏,使用默认值迁移")
store._save_to_mysql(key, value)
migrated_count += 1
logger.info(f"配置 [{key}] 已从 JSON 迁移到 MySQL")
except Exception as e:
logger.error(f"迁移配置 [{key}] 失败: {e}")
return False
logger.info(f"配置迁移完成: 迁移 {migrated_count} 项,跳过 {skipped_count}")
return True

@ -1,186 +0,0 @@
"""
统一配置存储模块
支持 MySQL 优先JSON 文件 fallback 的读写策略
"""
import json
import logging
from pathlib import Path
from typing import Optional
from app.models import AppConfig
from app.storage_manager import get_storage_manager
logger = logging.getLogger(__name__)
def _get_mysql_session_local():
"""动态读取 app.mysql_database.MySQLSessionLocal避免模块导入顺序问题。"""
import sys
module = sys.modules.get("app.mysql_database")
if module is None:
return None
return getattr(module, "MySQLSessionLocal", None)
CONFIG_DIR = Path(__file__).resolve().parent.parent / "config"
CONFIG_FILES = {
"symbols": CONFIG_DIR / "symbols_config.json",
"ai": CONFIG_DIR / "ai_config.json",
}
DEFAULT_CONFIGS = {
"symbols": {"futures": {}, "stock": {}},
"ai": {
"models": [],
"active_model": None,
"analysis_settings": {
"enable_technical_analysis": True,
"enable_fundamental_analysis": False,
"enable_sentiment_analysis": False,
"risk_tolerance": "medium",
"max_position_pct": 10,
},
},
}
class ConfigStore:
"""统一配置存储入口。"""
def __init__(
self,
storage_manager=None,
config_dir: Path = CONFIG_DIR,
session_maker=None,
):
self.storage_manager = storage_manager or get_storage_manager()
self.config_dir = config_dir
self._session_maker_override = session_maker
self.config_files = {
"symbols": self.config_dir / "symbols_config.json",
"ai": self.config_dir / "ai_config.json",
}
@property
def session_maker(self):
"""动态读取 MySQLSessionLocal避免初始化顺序问题。"""
if self._session_maker_override is not None:
return self._session_maker_override
return _get_mysql_session_local()
def get_config(self, key: str, fallback: Optional[dict] = None) -> dict:
"""读取配置,优先从 MySQL其次 JSON 文件。"""
if key not in self.config_files:
raise ValueError(f"未知配置键: {key}")
if self.storage_manager.check_mysql():
try:
db_value = self._get_from_mysql(key)
if db_value is not None:
return db_value
# 数据库未命中:从 JSON 读取并回填
json_value = self._load_json_from_file(key)
if json_value is not None:
self._save_to_mysql(key, json_value)
return json_value
# JSON 不存在或损坏,使用 fallback 但不回填
return fallback if fallback is not None else DEFAULT_CONFIGS.get(key, {})
except Exception as e:
logger.warning(f"从 MySQL 读取配置 [{key}] 失败,降级到 JSON: {e}")
json_value = self._load_json_from_file(key)
if json_value is not None:
return json_value
return fallback if fallback is not None else DEFAULT_CONFIGS.get(key, {})
def set_config(self, key: str, value: dict) -> bool:
"""写入配置MySQL 可用时先写数据库再写 JSONMySQL 不可用时只写 JSON。"""
if key not in self.config_files:
raise ValueError(f"未知配置键: {key}")
if self.storage_manager.check_mysql():
try:
if not self._save_to_mysql(key, value):
logger.warning(f"写入 MySQL 配置 [{key}] 失败,保留 JSON 旧值")
return False
except Exception as e:
logger.warning(f"写入 MySQL 配置 [{key}] 失败,保留 JSON 旧值: {e}")
return False
# MySQL 写入成功或 MySQL 不可用,都更新 JSON fallback
self._save_to_json(key, value)
return True
def _get_from_mysql(self, key: str) -> Optional[dict]:
"""从 MySQL 读取配置。"""
if self.session_maker is None:
return None
with self.session_maker() as db:
record = db.query(AppConfig).filter(AppConfig.config_key == key).first()
if record:
return record.config_value
return None
def _save_to_mysql(self, key: str, value: dict) -> bool:
"""保存配置到 MySQL。"""
if self.session_maker is None:
return False
with self.session_maker() as db:
record = db.query(AppConfig).filter(AppConfig.config_key == key).first()
if record:
record.config_value = value
else:
record = AppConfig(config_key=key, config_value=value)
db.add(record)
db.commit()
return True
def _load_json_from_file(self, key: str) -> Optional[dict]:
"""从 JSON 文件读取配置,文件不存在或损坏时返回 None。"""
file_path = self.config_files[key]
if file_path.exists():
try:
with open(file_path, "r", encoding="utf-8") as f:
return json.load(f)
except Exception as e:
logger.warning(f"读取 JSON 配置 [{key}] 失败: {e}")
return None
def _load_json(self, key: str, fallback: Optional[dict] = None) -> dict:
"""从 JSON 文件读取配置,文件不存在或损坏时返回 fallback。"""
value = self._load_json_from_file(key)
if value is not None:
return value
return fallback if fallback is not None else DEFAULT_CONFIGS.get(key, {})
def _save_to_json(self, key: str, value: dict) -> None:
"""保存配置到 JSON 文件(原子写入)。"""
file_path = self.config_files[key]
self.config_dir.mkdir(parents=True, exist_ok=True)
tmp_path = file_path.with_suffix(".tmp")
try:
with open(tmp_path, "w", encoding="utf-8") as f:
json.dump(value, f, ensure_ascii=False, indent=4)
tmp_path.replace(file_path)
except Exception:
if tmp_path.exists():
tmp_path.unlink()
raise
def _config_exists_in_mysql(self, key: str) -> bool:
"""检查 MySQL 中是否已存在配置。"""
return self._get_from_mysql(key) is not None
_config_store = None
def get_config_store() -> ConfigStore:
"""获取 ConfigStore 单例。"""
global _config_store
if _config_store is None:
_config_store = ConfigStore()
return _config_store

@ -36,64 +36,6 @@ async def lifespan(app: FastAPI):
init_analysis_db()
logger.info("期货智析数据库初始化完成")
# 初始化 Redis 和 MySQL
from app.redis_client import init_redis
from app.mysql_database import init_mysql
from app.storage_manager import get_storage_manager
redis_client = None
mysql_engine = None
try:
redis_client = init_redis()
except Exception:
redis_client = None
try:
mysql_engine = init_mysql()
except Exception:
mysql_engine = None
redis_ok = redis_client is not None
mysql_ok = mysql_engine is not None
if redis_ok and mysql_ok:
logger.info("存储模式: Redis + MySQL")
elif mysql_ok:
logger.warning("存储模式: MySQL (Redis 不可用)")
else:
logger.error("存储模式: SQLite (Redis 和 MySQL 均不可用)")
# 将初始化后的客户端注入 StorageManager 全局单例
storage_manager = get_storage_manager()
storage_manager.initialize(redis_client, mysql_engine)
if mysql_ok and mysql_engine is not None:
from app.models import Base as MarketBase, MarketData, SymbolTimestamp
# 在 MySQL 中创建行情相关表
MarketBase.metadata.create_all(bind=mysql_engine, tables=[MarketData.__table__, SymbolTimestamp.__table__])
logger.info("行情数据 MySQL 表结构初始化完成")
from app.migration import migrate_sqlite_to_mysql
migrate_sqlite_to_mysql()
# 在 MySQL 中创建 analysis 相关表
from app.analysis_db import init_analysis_mysql
init_analysis_mysql(mysql_engine)
# 迁移 SQLite analysis 数据到 MySQL
from app.analysis_migration import migrate_analysis_sqlite_to_mysql
migrate_analysis_sqlite_to_mysql()
# 在 MySQL 中创建配置表
from app.models import AppConfig
MarketBase.metadata.create_all(bind=mysql_engine, tables=[AppConfig.__table__])
logger.info("配置表 MySQL 表结构初始化完成")
# 迁移 JSON 配置到 MySQL
from app.config_migration import migrate_configs_to_mysql
migrate_configs_to_mysql()
# 创建默认管理员账户
from app.database import SessionLocal
from app import auth_service

@ -1,91 +0,0 @@
"""
数据缓冲平台 - SQLite MySQL 数据迁移
"""
import logging
from sqlalchemy import create_engine
from sqlalchemy.orm import make_transient, sessionmaker
from app.config import DB_PATH
from app.models import MarketData, SymbolTimestamp
from app.mysql_database import MySQLSessionLocal
def _prepare_records_for_new_session(records):
"""将 ORM 实例转换为可在新 session 中插入的 transient 状态。"""
for record in records:
make_transient(record)
record.id = None
logger = logging.getLogger(__name__)
def migrate_sqlite_to_mysql():
"""从 SQLite 迁移 market_data 和 symbol_timestamps 数据到 MySQL。
幂等设计 MySQL 对应表已存在数据时直接跳过避免重复写入
返回 True 表示执行了迁移False 表示跳过或失败
"""
if MySQLSessionLocal is None:
logger.warning("MySQL 未初始化,跳过数据迁移")
return False
sqlite_engine = create_engine(
f"sqlite:///{DB_PATH}",
connect_args={"check_same_thread": False},
)
SQLiteSession = sessionmaker(bind=sqlite_engine)
mysql_session = MySQLSessionLocal()
try:
market_data_count = mysql_session.query(MarketData).count()
symbol_timestamp_count = mysql_session.query(SymbolTimestamp).count()
migrated_market_data = False
migrated_symbol_timestamps = False
sqlite_session = SQLiteSession()
try:
market_data_records = sqlite_session.query(MarketData).all()
symbol_timestamp_records = sqlite_session.query(SymbolTimestamp).all()
finally:
sqlite_session.close()
if market_data_count > 0:
logger.info(
f"MySQL market_data 表已存在数据,跳过迁移 "
f"(market_data: {market_data_count})"
)
else:
_prepare_records_for_new_session(market_data_records)
if market_data_records:
mysql_session.add_all(market_data_records)
migrated_market_data = True
if symbol_timestamp_count > 0:
logger.info(
f"MySQL symbol_timestamps 表已存在数据,跳过迁移 "
f"(symbol_timestamps: {symbol_timestamp_count})"
)
else:
_prepare_records_for_new_session(symbol_timestamp_records)
if symbol_timestamp_records:
mysql_session.add_all(symbol_timestamp_records)
migrated_symbol_timestamps = True
if not migrated_market_data and not migrated_symbol_timestamps:
logger.info("MySQL 已存在数据,跳过迁移")
return False
mysql_session.commit()
logger.info(
f"迁移完成: market_data: {len(market_data_records)} 条, "
f"symbol_timestamps: {len(symbol_timestamp_records)}"
)
return True
except Exception as e:
logger.error(f"数据迁移失败: {e}")
mysql_session.rollback()
return False
finally:
mysql_session.close()

@ -2,10 +2,7 @@
数据缓冲平台 - 数据模型 (SQLAlchemy ORM)
"""
from datetime import datetime
from sqlalchemy import (
Column, String, Integer, Float, Text, DateTime, Boolean,
Index, UniqueConstraint, JSON,
)
from sqlalchemy import Column, String, Integer, Float, Text, DateTime, Boolean, Index, UniqueConstraint
from app.database import Base
@ -70,20 +67,3 @@ class ScheduledTask(Base):
def __repr__(self):
return f"<Task {self.symbol} every {self.interval_seconds}s enabled={self.enabled}>"
class AppConfig(Base):
"""应用配置表 - 存储 JSON 配置数据"""
__tablename__ = "app_config"
id = Column(Integer, primary_key=True, autoincrement=True)
config_key = Column(
String(64), unique=True, nullable=False, index=True,
comment="配置键,如 symbols / ai"
)
config_value = Column(JSON, nullable=False, comment="配置值(JSON)")
created_at = Column(DateTime, nullable=False, default=datetime.now, comment="创建时间")
updated_at = Column(DateTime, nullable=False, default=datetime.now, onupdate=datetime.now, comment="更新时间")
def __repr__(self):
return f"<AppConfig {self.config_key}>"

@ -1,39 +0,0 @@
"""
数据缓冲平台 - MySQL 数据库连接
"""
import logging
import urllib.parse
from sqlalchemy import create_engine, text
from sqlalchemy.orm import sessionmaker
from app.config import MYSQL_HOST, MYSQL_PORT, MYSQL_USER, MYSQL_PASSWORD, MYSQL_DATABASE
logger = logging.getLogger(__name__)
mysql_engine = None
MySQLSessionLocal = None
def init_mysql():
"""初始化 MySQL 连接引擎,失败时返回 None"""
global mysql_engine, MySQLSessionLocal
try:
encoded_password = urllib.parse.quote_plus(MYSQL_PASSWORD)
url = f"mysql+pymysql://{MYSQL_USER}:{encoded_password}@{MYSQL_HOST}:{MYSQL_PORT}/{MYSQL_DATABASE}?charset=utf8mb4"
mysql_engine = create_engine(url, pool_pre_ping=True, pool_recycle=3600)
with mysql_engine.connect() as conn:
conn.execute(text("SELECT 1"))
MySQLSessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=mysql_engine)
logger.info("MySQL 连接初始化成功")
return mysql_engine
except Exception as e:
logger.warning(f"MySQL 初始化失败: {e}")
mysql_engine = None
MySQLSessionLocal = None
return None
def get_mysql_session():
"""获取 MySQL 会话"""
if MySQLSessionLocal is None:
raise RuntimeError("MySQL 未初始化")
return MySQLSessionLocal()

@ -1,31 +0,0 @@
import logging
import redis
from app.config import REDIS_HOST, REDIS_PORT, REDIS_DB, REDIS_PASSWORD
logger = logging.getLogger(__name__)
redis_client = None
def init_redis():
"""初始化 Redis 客户端,失败时返回 None"""
global redis_client
try:
redis_client = redis.Redis(
host=REDIS_HOST, port=REDIS_PORT, db=REDIS_DB,
password=REDIS_PASSWORD or None,
decode_responses=True,
socket_connect_timeout=5,
)
redis_client.ping()
logger.info("Redis 连接初始化成功")
return redis_client
except Exception as e:
logger.warning(f"Redis 初始化失败: {e}")
redis_client = None
return None
def get_redis():
"""获取 Redis 客户端实例"""
return redis_client

@ -10,6 +10,10 @@ from sqlalchemy.orm import Session
from app.analysis_models import AIAnalysisCache
from app.services.cache import get_cached_data, get_latest_cached
from pathlib import Path
CONFIG_DIR = Path(__file__).resolve().parent.parent.parent / "config"
AI_CONFIG_FILE = CONFIG_DIR / "ai_config.json"
logger = logging.getLogger(__name__)
@ -148,11 +152,11 @@ class AIFuturesAnalyzer:
def get_active_model(self) -> Optional[Dict]:
"""获取当前激活的AI模型配置"""
try:
from app.config_store import get_config_store
config = get_config_store().get_config("ai", {
"models": [],
"active_model": None,
})
if not AI_CONFIG_FILE.exists():
return None
with open(AI_CONFIG_FILE, "r", encoding="utf-8") as f:
config = json.load(f)
models = config.get("models", [])
active_model_name = config.get("active_model")

@ -1,7 +1,6 @@
"""
缓存服务 - SQLite 数据库操作
"""
import copy
import json
import logging
from datetime import datetime, timedelta
@ -11,7 +10,6 @@ from sqlalchemy.orm import Session
from app.models import MarketData, ScheduledTask, SymbolTimestamp
from app.config import CACHE_TTL_SECONDS
from app.storage_manager import get_storage_manager
logger = logging.getLogger(__name__)
@ -25,21 +23,7 @@ def is_cache_valid(
period: str,
ttl_seconds: int = CACHE_TTL_SECONDS,
) -> bool:
"""检查指定品种+周期的缓存是否在有效期内,优先使用 StorageManager。"""
storage = get_storage_manager()
if storage.is_available():
try:
result = storage.get_market_data(symbol, data_type, [period])
if result and result.get("timeframes"):
timestamp_raw = result.get("fetched_at") or result.get("timestamp")
if timestamp_raw:
newest = datetime.fromisoformat(timestamp_raw)
age = (datetime.now() - newest).total_seconds()
return age < ttl_seconds
except Exception as e:
logger.warning(f"StorageManager 缓存有效性检查失败,降级到 SQLite: {e}")
"""检查指定品种+周期的缓存是否在有效期内"""
record = db.query(MarketData).filter_by(
symbol=symbol,
data_type=data_type,
@ -81,12 +65,11 @@ def check_cache_status(
}
def _save_to_sqlite(db: Session, symbol: str, data: Dict) -> MarketData:
def save_market_data(db: Session, symbol: str, data: Dict) -> MarketData:
"""
将采集结果写入 SQLite 缓存并同步更新合约时间戳
保存采集结果到缓存并同步更新合约时间戳
Args:
db: 数据库会话
symbol: 品种代码
data: 采集脚本返回的完整数据
@ -123,7 +106,7 @@ def _save_to_sqlite(db: Session, symbol: str, data: Dict) -> MarketData:
db.add(record)
# 更新合约时间戳
_update_symbol_timestamp_sqlite(db, symbol, data.get("type", "futures"), now)
update_symbol_timestamp(db, symbol, data.get("type", "futures"), now)
db.commit()
logger.info(f"缓存已更新: {symbol}, {len(data.get('timeframes', {}))} 个周期")
@ -135,8 +118,8 @@ def _save_to_sqlite(db: Session, symbol: str, data: Dict) -> MarketData:
).order_by(MarketData.fetched_at.desc()).first()
def _update_symbol_timestamp_sqlite(db: Session, symbol: str, data_type: str, refresh_time: datetime) -> None:
"""更新或创建合约时间戳记录SQLite 兜底)。"""
def update_symbol_timestamp(db: Session, symbol: str, data_type: str, refresh_time: datetime) -> None:
"""更新或创建合约时间戳记录"""
timestamp_record = db.query(SymbolTimestamp).filter_by(
symbol=symbol,
data_type=data_type
@ -154,9 +137,11 @@ def _update_symbol_timestamp_sqlite(db: Session, symbol: str, data_type: str, re
)
db.add(timestamp_record)
db.commit()
def _get_symbol_timestamp_sqlite(db: Session, symbol: str, data_type: str = "futures") -> Optional[datetime]:
"""获取合约最后刷新时间SQLite 兜底)。"""
def get_symbol_timestamp(db: Session, symbol: str, data_type: str = "futures") -> Optional[datetime]:
"""获取合约最后刷新时间"""
record = db.query(SymbolTimestamp).filter_by(
symbol=symbol,
data_type=data_type
@ -164,182 +149,6 @@ def _get_symbol_timestamp_sqlite(db: Session, symbol: str, data_type: str = "fut
return record.last_refresh_at if record else None
def _filter_candles(
candles: List[Dict],
end_time: Optional[datetime] = None,
max_candles: int = 100,
) -> List[Dict]:
"""按结束时间和最大数量过滤 K 线列表。"""
filter_end_time = end_time if end_time else datetime.now()
if filter_end_time.tzinfo is not None:
filter_end_time = filter_end_time.replace(tzinfo=None)
filtered = []
for candle in candles:
candle_time = candle.get("datetime") or candle.get("time")
if candle_time:
if isinstance(candle_time, str):
try:
candle_dt = datetime.fromisoformat(candle_time.replace("Z", "+00:00"))
if candle_dt.tzinfo is not None:
candle_dt = candle_dt.replace(tzinfo=None)
except Exception:
filtered.append(candle)
continue
else:
candle_dt = candle_time
if candle_dt.tzinfo is not None:
candle_dt = candle_dt.replace(tzinfo=None)
if candle_dt <= filter_end_time:
filtered.append(candle)
else:
filtered.append(candle)
if len(filtered) > max_candles:
filtered = filtered[-max_candles:]
return filtered
def _get_from_sqlite(
db: Session,
symbol: str,
data_type: str = "futures",
periods: Optional[List[str]] = None,
end_time: Optional[datetime] = None,
max_candles: int = 100,
) -> Optional[Dict]:
"""
SQLite 缓存中获取完整的多周期数据
Args:
db: 数据库会话
symbol: 品种代码
data_type: 数据类型
periods: 周期列表
end_time: 结束时间(可选),默认为当前时间
max_candles: 每个周期最大K线数量,默认100
Returns:
与采集脚本相同格式的数据 None
"""
query = db.query(MarketData).filter_by(symbol=symbol, data_type=data_type)
if periods:
query = query.filter(MarketData.period.in_(periods))
records = query.all()
if not records:
return None
# 检查缓存是否过期
now = datetime.now()
newest = max(r.fetched_at for r in records)
is_fresh = (now - newest).total_seconds() < CACHE_TTL_SECONDS
timeframes = {}
current_price = None
for r in records:
candles = json.loads(r.candles_json)
timeframes[r.period] = _filter_candles(candles, end_time, max_candles)
if current_price is None:
current_price = r.current_price
return {
"symbol": symbol,
"type": data_type,
"current_price": current_price,
"timestamp": newest.isoformat(),
"timeframes": timeframes,
"is_fresh": is_fresh,
"fetched_at": newest.isoformat(),
}
def _representative_market_data(symbol: str, data: Dict, fetched_at: datetime) -> Optional[MarketData]:
"""从输入数据构造一条代表性的 MarketData 记录(不写入数据库)。"""
data_type = data.get("type", "futures")
timeframes = data.get("timeframes", {})
if not timeframes:
return None
# 取第一个周期作为代表
period = next(iter(timeframes))
candles = timeframes[period]
return MarketData(
symbol=symbol,
data_type=data_type,
period=period,
candles_json=json.dumps(candles, ensure_ascii=False),
current_price=data.get("current_price"),
fetched_at=fetched_at,
candle_count=len(candles),
)
def save_market_data(db: Session, symbol: str, data: Dict) -> Optional[MarketData]:
"""
保存采集结果到缓存优先写入 StorageManagerRedis/MySQL失败时降级到 SQLite
Args:
symbol: 品种代码
data: 采集脚本返回的完整数据
Returns:
返回一条代表性的 MarketData 记录降级到 SQLite 时返回实际持久化记录
"""
storage = get_storage_manager()
data_type = data.get("type", "futures")
now = datetime.now()
if storage.is_available():
try:
if storage.save_market_data_with_timestamp(symbol, data, now):
# 注意StorageManager 命中时返回的是内存构造的代表性 MarketData
# 不代表 SQLite 持久化记录,因此没有 SQLite 自增 id。
return _representative_market_data(symbol, data, now)
else:
raise Exception("save_market_data_with_timestamp returned False")
except Exception as e:
logger.warning(f"StorageManager 写入失败,降级到 SQLite: {e}")
# 注意:当 StorageManager 不可用时,数据只会写入本地 SQLite 兜底,
# 这部分数据不会自动同步到主存储Redis/MySQL可能与主存储脱节。
return _save_to_sqlite(db, symbol, data)
def update_symbol_timestamp(db: Session, symbol: str, data_type: str, refresh_time: datetime) -> None:
"""更新或创建合约时间戳记录,优先使用 StorageManager。"""
storage = get_storage_manager()
if storage.is_available():
try:
if storage.save_symbol_timestamp(symbol, data_type, refresh_time):
return
else:
raise Exception("save_symbol_timestamp returned False")
except Exception as e:
logger.warning(f"StorageManager 时间戳写入失败,降级到 SQLite: {e}")
_update_symbol_timestamp_sqlite(db, symbol, data_type, refresh_time)
db.commit()
def get_symbol_timestamp(db: Session, symbol: str, data_type: str = "futures") -> Optional[datetime]:
"""获取合约最后刷新时间,优先使用 StorageManager。"""
storage = get_storage_manager()
if storage.is_available():
try:
result = storage.get_symbol_timestamp(symbol, data_type)
if result:
return datetime.fromisoformat(result["last_refresh_at"])
except Exception as e:
logger.warning(f"StorageManager 时间戳读取失败,降级到 SQLite: {e}")
return _get_symbol_timestamp_sqlite(db, symbol, data_type)
def needs_refresh(db: Session, symbol: str, data_type: str = "futures", threshold_seconds: int = 300) -> bool:
"""
检查合约是否需要刷新数据是否超过阈值时间
@ -367,42 +176,7 @@ def get_latest_cached(
data_type: str = "futures",
period: Optional[str] = None,
) -> List[MarketData]:
"""获取最新缓存数据,优先使用 StorageManager。"""
storage = get_storage_manager()
if storage.is_available():
try:
result = storage.get_market_data(
symbol, data_type, [period] if period else None
)
if result and result.get("timeframes"):
timestamp_raw = result.get("fetched_at") or result.get("timestamp")
fetched_at = (
datetime.fromisoformat(timestamp_raw)
if timestamp_raw
else datetime.now()
)
records = []
target_periods = [period] if period else list(result["timeframes"].keys())
for p in target_periods:
candles = result["timeframes"].get(p, [])
records.append(
MarketData(
symbol=symbol,
data_type=data_type,
period=p,
candles_json=json.dumps(candles, ensure_ascii=False),
current_price=result.get("current_price"),
fetched_at=fetched_at,
candle_count=len(candles),
)
)
# 注意StorageManager 命中时返回的是内存构造的 MarketData 列表,
# 不代表 SQLite 持久化记录,因此没有 SQLite 自增 id。
return records
except Exception as e:
logger.warning(f"StorageManager 最新缓存读取失败,降级到 SQLite: {e}")
"""获取最新缓存数据"""
query = db.query(MarketData).filter_by(symbol=symbol, data_type=data_type)
if period:
query = query.filter_by(period=period)
@ -418,7 +192,7 @@ def get_cached_data(
max_candles: int = 100,
) -> Optional[Dict]:
"""
从缓存中获取完整的多周期数据优先使用 StorageManager失败时降级到 SQLite
从缓存中获取完整的多周期数据
Args:
db: 数据库会话
@ -431,21 +205,76 @@ def get_cached_data(
Returns:
与采集脚本相同格式的数据 None
"""
storage = get_storage_manager()
query = db.query(MarketData).filter_by(symbol=symbol, data_type=data_type)
if periods:
query = query.filter(MarketData.period.in_(periods))
if storage.is_available():
try:
merged = storage.get_market_data(
symbol, data_type, periods, end_time=end_time, max_candles=max_candles
)
if merged and merged.get("timeframes"):
# StorageManager 已负责 end_time / max_candles 过滤,
# 这里深拷贝后返回,避免原地修改 StorageManager 内部对象。
return copy.deepcopy(merged)
except Exception as e:
logger.warning(f"StorageManager 读取失败,降级到 SQLite: {e}")
return _get_from_sqlite(db, symbol, data_type, periods, end_time, max_candles)
records = query.all()
if not records:
return None
# 检查缓存是否过期
now = datetime.now()
newest = max(r.fetched_at for r in records)
is_fresh = (now - newest).total_seconds() < CACHE_TTL_SECONDS
# 如果未指定结束时间,默认为当前时间
filter_end_time = end_time if end_time else now
# 确保filter_end_time是naive datetime(无时区)
if filter_end_time.tzinfo is not None:
filter_end_time = filter_end_time.replace(tzinfo=None)
timeframes = {}
current_price = None
for r in records:
candles = json.loads(r.candles_json)
# 过滤结束时间之前的K线数据
filtered_candles = []
for candle in candles:
candle_time = candle.get('datetime') or candle.get('time')
if candle_time:
# 解析K线时间
if isinstance(candle_time, str):
try:
candle_dt = datetime.fromisoformat(candle_time.replace('Z', '+00:00'))
# 转换为naive datetime进行比较
if candle_dt.tzinfo is not None:
candle_dt = candle_dt.replace(tzinfo=None)
except:
filtered_candles.append(candle)
continue
else:
candle_dt = candle_time
# 如果是aware datetime,转换为naive
if candle_dt.tzinfo is not None:
candle_dt = candle_dt.replace(tzinfo=None)
# 只保留结束时间之前的数据
if candle_dt <= filter_end_time:
filtered_candles.append(candle)
else:
filtered_candles.append(candle)
# 限制K线数量,超过max_candles则取最新的max_candles条
if len(filtered_candles) > max_candles:
filtered_candles = filtered_candles[-max_candles:]
timeframes[r.period] = filtered_candles
if current_price is None:
current_price = r.current_price
return {
"symbol": symbol,
"type": data_type,
"current_price": current_price,
"timestamp": newest.isoformat(),
"timeframes": timeframes,
"is_fresh": is_fresh,
"fetched_at": newest.isoformat(),
}
# ===== 定时任务管理 =====

@ -4,6 +4,7 @@ V2 交易计划生成器 - 5维度综合评分 + 多周期共振分析
import json
import logging
from collections import Counter
from pathlib import Path
from typing import Dict, List, Optional, Tuple
from datetime import datetime
@ -16,6 +17,9 @@ from app.analysis_models import (
logger = logging.getLogger(__name__)
# 品种配置加载
CONFIG_DIR = Path(__file__).resolve().parent.parent.parent / "config"
# 板块分类
SECTOR_MAP = {
"贵金属": ["沪银", "沪金"],
@ -42,8 +46,12 @@ WEIGHTS = {
def load_symbols_config() -> Dict[str, str]:
"""加载品种配置 {中文名: 合约代码}"""
from app.config_store import get_config_store
data = get_config_store().get_config("symbols", {"futures": {}, "stock": {}})
config_path = CONFIG_DIR / "symbols_config.json"
if not config_path.exists():
logger.warning(f"品种配置文件不存在: {config_path}")
return {}
with open(config_path, "r", encoding="utf-8") as f:
data = json.load(f)
return data.get("futures", {})
@ -626,126 +634,121 @@ def save_plan_to_db(db: Session, plan_data: dict) -> int:
review_date_str = plan_data["review_date"]
week_day = plan_data["week_day"]
try:
# 清理旧数据
existing = db.query(ReviewPlanV2).filter_by(review_date=review_date_str).first()
if existing:
review_plan_id = existing.id
# 清理关联数据
db.query(SymbolScoreV2).filter_by(review_date_id=review_plan_id).delete()
db.query(TradingPlanV2).filter_by(review_date_id=review_plan_id).delete()
db.query(SectorHeat).filter_by(review_date_id=review_plan_id).delete()
# 更新元数据
existing.week_day = week_day
existing.data_basis = plan_data.get("data_basis")
existing.core_conclusion = plan_data.get("core_conclusion")
existing.bull_count = plan_data.get("bull_count")
existing.bear_count = plan_data.get("bear_count")
existing.neutral_count = plan_data.get("neutral_count")
existing.opportunity_count = plan_data.get("opportunity_count")
existing.risk_warnings = plan_data.get("risk_warnings")
existing.actual_data_date = plan_data.get("actual_data_date")
existing.data_date_matches = 1 if plan_data.get("data_date_matches") else 0
else:
review_plan = ReviewPlanV2(
review_date=review_date_str,
week_day=week_day,
data_basis=plan_data.get("data_basis"),
core_conclusion=plan_data.get("core_conclusion"),
bull_count=plan_data.get("bull_count"),
bear_count=plan_data.get("bear_count"),
neutral_count=plan_data.get("neutral_count"),
opportunity_count=plan_data.get("opportunity_count"),
risk_warnings=plan_data.get("risk_warnings"),
actual_data_date=plan_data.get("actual_data_date"),
data_date_matches=1 if plan_data.get("data_date_matches") else 0,
)
db.add(review_plan)
db.flush()
review_plan_id = review_plan.id
# 保存评分数据
for s in plan_data.get("scores", []):
pivots = s.get("pivots", {})
score_record = SymbolScoreV2(
review_date_id=review_plan_id,
symbol=s["symbol"],
name=s["name"],
close_price=s.get("close_price"),
prev_close=s.get("prev_close"),
high_price=s.get("high_price"),
low_price=s.get("low_price"),
volume=s.get("volume"),
avg_volume_5=s.get("avg_volume_5"),
amplitude_score=s.get("amplitude_score"),
volume_score=s.get("volume_score"),
change_score=s.get("change_score"),
trend_score=s.get("trend_score"),
activity_score=s.get("activity_score"),
composite_score=s.get("composite_score"),
amplitude_pct=s.get("amplitude_pct"),
change_pct=s.get("change_pct"),
volume_ratio=s.get("volume_ratio"),
trend_60m=s.get("trend_60m"),
trend_15m=s.get("trend_15m"),
trend_5m=s.get("trend_5m"),
direction=s.get("direction"),
direction_tag=s.get("direction_tag"),
category=s.get("category"),
pivot=pivots.get("pivot"),
r1=pivots.get("r1"),
r2=pivots.get("r2"),
s1=pivots.get("s1"),
s2=pivots.get("s2"),
rank=s.get("rank"),
data_date=s.get("data_date"),
)
db.add(score_record)
# 保存交易计划
for p in plan_data.get("plans", []):
plan_record = TradingPlanV2(
review_date_id=review_plan_id,
symbol=p["symbol"],
name=p["name"],
direction=p["direction"],
composite_score=p.get("composite_score"),
entry_low=p.get("entry_low"),
entry_high=p.get("entry_high"),
stop_loss=p.get("stop_loss"),
target1=p.get("target1"),
target2=p.get("target2"),
trigger=p.get("trigger"),
amplitude_score=p.get("amplitude_score"),
volume_score=p.get("volume_score"),
trend_score=p.get("trend_score"),
activity_score=p.get("activity_score"),
category=p.get("category"),
)
db.add(plan_record)
# 保存板块热度
for sec in plan_data.get("sectors", []):
sector_record = SectorHeat(
review_date_id=review_plan_id,
sector_name=sec["sector_name"],
avg_score=sec.get("avg_score"),
avg_trend=sec.get("avg_trend"),
direction=sec.get("direction"),
heat_level=sec.get("heat_level"),
leader_symbol=sec.get("leader_symbol"),
leader_score=sec.get("leader_score"),
members=sec.get("members"),
)
db.add(sector_record)
db.commit()
logger.info(f"交易计划已保存: {review_date_str}, ID={review_plan_id}")
return review_plan_id
except Exception as e:
db.rollback()
logger.exception(f"保存交易计划失败: {e}")
raise
# 清理旧数据
existing = db.query(ReviewPlanV2).filter_by(review_date=review_date_str).first()
if existing:
review_plan_id = existing.id
# 清理关联数据
db.query(SymbolScoreV2).filter_by(review_date_id=review_plan_id).delete()
db.query(TradingPlanV2).filter_by(review_date_id=review_plan_id).delete()
db.query(SectorHeat).filter_by(review_date_id=review_plan_id).delete()
# 更新元数据
existing.week_day = week_day
existing.data_basis = plan_data.get("data_basis")
existing.core_conclusion = plan_data.get("core_conclusion")
existing.bull_count = plan_data.get("bull_count")
existing.bear_count = plan_data.get("bear_count")
existing.neutral_count = plan_data.get("neutral_count")
existing.opportunity_count = plan_data.get("opportunity_count")
existing.risk_warnings = plan_data.get("risk_warnings")
existing.actual_data_date = plan_data.get("actual_data_date")
existing.data_date_matches = 1 if plan_data.get("data_date_matches") else 0
else:
review_plan = ReviewPlanV2(
review_date=review_date_str,
week_day=week_day,
data_basis=plan_data.get("data_basis"),
core_conclusion=plan_data.get("core_conclusion"),
bull_count=plan_data.get("bull_count"),
bear_count=plan_data.get("bear_count"),
neutral_count=plan_data.get("neutral_count"),
opportunity_count=plan_data.get("opportunity_count"),
risk_warnings=plan_data.get("risk_warnings"),
actual_data_date=plan_data.get("actual_data_date"),
data_date_matches=1 if plan_data.get("data_date_matches") else 0,
)
db.add(review_plan)
db.flush()
review_plan_id = review_plan.id
# 保存评分数据
for s in plan_data.get("scores", []):
pivots = s.get("pivots", {})
score_record = SymbolScoreV2(
review_date_id=review_plan_id,
symbol=s["symbol"],
name=s["name"],
close_price=s.get("close_price"),
prev_close=s.get("prev_close"),
high_price=s.get("high_price"),
low_price=s.get("low_price"),
volume=s.get("volume"),
avg_volume_5=s.get("avg_volume_5"),
amplitude_score=s.get("amplitude_score"),
volume_score=s.get("volume_score"),
change_score=s.get("change_score"),
trend_score=s.get("trend_score"),
activity_score=s.get("activity_score"),
composite_score=s.get("composite_score"),
amplitude_pct=s.get("amplitude_pct"),
change_pct=s.get("change_pct"),
volume_ratio=s.get("volume_ratio"),
trend_60m=s.get("trend_60m"),
trend_15m=s.get("trend_15m"),
trend_5m=s.get("trend_5m"),
direction=s.get("direction"),
direction_tag=s.get("direction_tag"),
category=s.get("category"),
pivot=pivots.get("pivot"),
r1=pivots.get("r1"),
r2=pivots.get("r2"),
s1=pivots.get("s1"),
s2=pivots.get("s2"),
rank=s.get("rank"),
data_date=s.get("data_date"),
)
db.add(score_record)
# 保存交易计划
for p in plan_data.get("plans", []):
plan_record = TradingPlanV2(
review_date_id=review_plan_id,
symbol=p["symbol"],
name=p["name"],
direction=p["direction"],
composite_score=p.get("composite_score"),
entry_low=p.get("entry_low"),
entry_high=p.get("entry_high"),
stop_loss=p.get("stop_loss"),
target1=p.get("target1"),
target2=p.get("target2"),
trigger=p.get("trigger"),
amplitude_score=p.get("amplitude_score"),
volume_score=p.get("volume_score"),
trend_score=p.get("trend_score"),
activity_score=p.get("activity_score"),
category=p.get("category"),
)
db.add(plan_record)
# 保存板块热度
for sec in plan_data.get("sectors", []):
sector_record = SectorHeat(
review_date_id=review_plan_id,
sector_name=sec["sector_name"],
avg_score=sec.get("avg_score"),
avg_trend=sec.get("avg_trend"),
direction=sec.get("direction"),
heat_level=sec.get("heat_level"),
leader_symbol=sec.get("leader_symbol"),
leader_score=sec.get("leader_score"),
members=sec.get("members"),
)
db.add(sector_record)
db.commit()
logger.info(f"交易计划已保存: {review_date_str}, ID={review_plan_id}")
return review_plan_id
def get_plan_data(db: Session, review_plan_id: int) -> Optional[dict]:

@ -23,17 +23,19 @@ _VARIETY_NAME_MAP = {}
def _load_variety_name_map():
"""配置加载品种名称映射"""
""" symbols_config.json 加载品种名称映射"""
global _VARIETY_NAME_MAP
if _VARIETY_NAME_MAP:
return
from app.config_store import get_config_store
config = get_config_store().get_config("symbols", {"futures": {}, "stock": {}})
# 正向: {"沪银": "AG2608"} -> 反向: {"AG": "沪银"}
for name, contract in config.get("futures", {}).items():
variety = extract_variety(contract)
if variety and variety not in _VARIETY_NAME_MAP:
_VARIETY_NAME_MAP[variety] = name
config_path = Path(__file__).resolve().parent.parent.parent / "config" / "symbols_config.json"
if config_path.exists():
with open(config_path, "r", encoding="utf-8") as f:
config = json.load(f)
# 正向: {"沪银": "AG2608"} -> 反向: {"AG": "沪银"}
for name, contract in config.get("futures", {}).items():
variety = extract_variety(contract)
if variety and variety not in _VARIETY_NAME_MAP:
_VARIETY_NAME_MAP[variety] = name
def extract_variety(contract):

@ -1,774 +0,0 @@
import datetime as _datetime
import json
import logging
import time
from datetime import datetime
from sqlalchemy import text
from sqlalchemy.orm import sessionmaker
from app.config import CACHE_TTL_SECONDS, REDIS_TTL_SECONDS
from app.models import MarketData, SymbolTimestamp
logger = logging.getLogger(__name__)
# Redis 缓存 TTL读取自 app.config.REDIS_TTL_SECONDS默认 30 天)
# 业务缓存有效期:读取自 app.config.CACHE_TTL_SECONDS默认 300 秒)
class StorageManager:
"""存储管理器骨架,封装 Redis / MySQL 可用性检测与三级降级状态。"""
def __init__(self, redis_client=None, mysql_engine=None, check_interval=30):
self.redis_client = redis_client
self.mysql_engine = mysql_engine
self.check_interval = check_interval
self.redis_available = False
self.mysql_available = False
self.last_redis_check = 0
self.last_mysql_check = 0
def check_redis(self):
"""惰性检测 Redis 可用性30 秒间隔内返回缓存结果。"""
now = time.time()
if now - self.last_redis_check < self.check_interval:
return self.redis_available
if self.redis_client is None:
self.redis_available = False
else:
try:
self.redis_client.ping()
self.redis_available = True
except Exception as e:
self.redis_available = False
self.last_redis_check = now
return self.redis_available
def check_mysql(self):
"""惰性检测 MySQL 可用性30 秒间隔内返回缓存结果。"""
now = time.time()
if now - self.last_mysql_check < self.check_interval:
return self.mysql_available
if self.mysql_engine is None:
self.mysql_available = False
else:
try:
with self.mysql_engine.connect() as conn:
conn.execute(text("SELECT 1"))
self.mysql_available = True
except Exception as e:
self.mysql_available = False
self.last_mysql_check = now
return self.mysql_available
def _parse_fetched_at(self, timestamp_raw):
"""优先使用输入 timestamp解析失败时回退到当前时间。"""
if not timestamp_raw:
return _datetime.datetime.now()
if isinstance(timestamp_raw, str):
try:
return _datetime.datetime.fromisoformat(timestamp_raw)
except Exception:
return _datetime.datetime.now()
if hasattr(timestamp_raw, "isoformat"):
return timestamp_raw
return _datetime.datetime.now()
def is_available(self):
"""判断 Redis 或 MySQL 至少一个可用。"""
return self.check_redis() or self.check_mysql()
def initialize(self, redis_client=None, mysql_engine=None):
"""启动时调用,可选注入 Redis/MySQL 客户端并检测各后端可用性。"""
if redis_client is not None:
self.redis_client = redis_client
if mysql_engine is not None:
self.mysql_engine = mysql_engine
# 重置检测缓存,确保注入新客户端后重新探测后端可用性
self.last_redis_check = 0
self.last_mysql_check = 0
redis_ok = self.check_redis()
mysql_ok = self.check_mysql()
if redis_ok:
logger.info("Redis 可用")
else:
logger.warning("Redis 不可用")
if mysql_ok:
logger.info("MySQL 可用")
else:
logger.warning("MySQL 不可用")
def _discover_periods(self, symbol, data_type):
"""从 Redis 或 MySQL 发现该品种已缓存的所有周期。"""
if self.check_redis():
try:
pattern = f"market_data:{symbol}:*"
keys = self.redis_client.keys(pattern)
periods = set()
for key in keys:
key_str = key.decode("utf-8") if isinstance(key, bytes) else key
parts = key_str.split(":")
if len(parts) == 3:
periods.add(parts[2])
if periods:
return sorted(periods)
except Exception as e:
logger.warning(f"Redis 发现周期失败 [{symbol}]: {e}")
if not self.check_mysql():
return []
try:
SessionLocal = sessionmaker(bind=self.mysql_engine)
with SessionLocal() as db:
rows = (
db.query(MarketData.period)
.filter_by(symbol=symbol, data_type=data_type)
.distinct()
.all()
)
return sorted([r.period for r in rows if r.period])
except Exception as e:
logger.warning(f"MySQL 发现周期失败 [{symbol}]: {e}")
return []
def _get_market_data_single_period(self, symbol, data_type, period):
"""读取单个周期的行情数据Redis → MySQL → None。"""
cache_key = f"market_data:{symbol}:{period}"
# 1. 检查 Redis 缓存
if self.check_redis():
try:
raw = self.redis_client.get(cache_key)
if raw:
return json.loads(raw)
except Exception as e:
logger.warning(f"Redis 读取失败 [{cache_key}]: {e}")
# 2. Redis 未命中,检查 MySQL 可用性
if not self.check_mysql():
return None
# 3. 从 MySQL 读取
try:
SessionLocal = sessionmaker(bind=self.mysql_engine)
with SessionLocal() as db:
record = (
db.query(MarketData)
.filter_by(symbol=symbol, data_type=data_type, period=period)
.first()
)
if not record:
return None
result = {
"current_price": record.current_price,
"timestamp": (
record.fetched_at.isoformat() if record.fetched_at else None
),
"candles": (
json.loads(record.candles_json) if record.candles_json else []
),
}
# 4. 回填 RedisTTL 30 天)
if self.check_redis():
try:
self.redis_client.setex(
cache_key,
REDIS_TTL_SECONDS,
json.dumps(result, ensure_ascii=False),
)
except Exception as e:
logger.warning(f"Redis 回填失败 [{cache_key}]: {e}")
return result
except Exception as e:
logger.warning(f"MySQL 读取失败 [{cache_key}]: {e}")
return None
@staticmethod
def _parse_candle_time(candle):
"""解析单根 K 线的时间字段,返回 naive datetime 或 None。"""
candle_time = candle.get("datetime") or candle.get("time")
if not candle_time:
return None
if isinstance(candle_time, str):
try:
dt = datetime.fromisoformat(candle_time.replace("Z", "+00:00"))
if dt.tzinfo is not None:
dt = dt.replace(tzinfo=None)
return dt
except Exception:
return None
if hasattr(candle_time, "tzinfo") and candle_time.tzinfo is not None:
return candle_time.replace(tzinfo=None)
return candle_time
def _filter_and_truncate(self, merged, end_time, max_candles):
"""在合并结果上按 end_time 与 max_candles 过滤/截断每个周期。"""
if merged is None:
return None
filter_end_time = end_time if end_time else datetime.now()
if filter_end_time.tzinfo is not None:
filter_end_time = filter_end_time.replace(tzinfo=None)
timeframes = {}
for period, candles in merged.get("timeframes", {}).items():
filtered = []
for candle in candles:
candle_dt = self._parse_candle_time(candle)
if candle_dt is None or candle_dt <= filter_end_time:
filtered.append(candle)
if len(filtered) > max_candles:
filtered = filtered[-max_candles:]
timeframes[period] = filtered
merged["timeframes"] = timeframes
return merged
def _merge_period_results(self, symbol, data_type, period_results):
"""将按周期返回的结果合并为统一格式。"""
timeframes = {}
current_price = None
newest = None
for period, result in period_results.items():
if not result:
continue
candles = result.get("candles", [])
timeframes[period] = candles
if current_price is None:
current_price = result.get("current_price")
timestamp_raw = result.get("timestamp")
if timestamp_raw:
try:
timestamp_dt = datetime.fromisoformat(timestamp_raw)
# 去掉时区信息,统一使用 naive datetime
if timestamp_dt.tzinfo is not None:
timestamp_dt = timestamp_dt.replace(tzinfo=None)
if newest is None or timestamp_dt > newest:
newest = timestamp_dt
except Exception:
pass
if not timeframes:
return None
if newest is None:
newest = datetime.now()
now = datetime.now()
is_fresh = (now - newest).total_seconds() < CACHE_TTL_SECONDS
return {
"symbol": symbol,
"type": data_type,
"current_price": current_price,
"timestamp": newest.isoformat(),
"timeframes": timeframes,
"is_fresh": is_fresh,
"fetched_at": newest.isoformat(),
}
def get_market_data(self, symbol, data_type, periods=None, end_time=None, max_candles=100):
"""
读取行情数据Redis MySQL None由调用方降级到 SQLite
Args:
symbol: 品种合约代码
data_type: 数据类型 futures
periods: 周期或周期列表 "5min" ["5min", "15min"];
None 时自动发现全部周期
end_time: 结束时间可选过滤该时间之前的 K 线
max_candles: 每个周期最大 K 线数量默认 100
Returns:
periods 为字符串时返回旧版单周期 dict;
periods 为列表/None 时返回合并后的 dict包含 timeframes None
"""
single_period = isinstance(periods, str)
query_periods = [periods] if single_period else periods
if query_periods is None:
query_periods = self._discover_periods(symbol, data_type)
if not query_periods:
return None
period_results = {}
for period in query_periods:
period_results[period] = self._get_market_data_single_period(
symbol, data_type, period
)
merged = self._merge_period_results(symbol, data_type, period_results)
if merged is None:
return None
merged = self._filter_and_truncate(merged, end_time, max_candles)
if single_period:
period = query_periods[0]
return {
"current_price": merged.get("current_price"),
"timestamp": merged.get("timestamp"),
"candles": merged["timeframes"].get(period, []),
}
return merged
def get_symbol_timestamp(self, symbol, data_type):
"""
读取合约时间戳Redis MySQL None由调用方降级到 SQLite
Args:
symbol: 品种合约代码
data_type: 数据类型 futures
Returns:
dict None
"""
cache_key = f"symbol_timestamps:{symbol}"
# 1. 检查 Redis 缓存
if self.check_redis():
try:
raw = self.redis_client.get(cache_key)
if raw:
return json.loads(raw)
except Exception as e:
logger.warning(f"Redis 读取失败 [{cache_key}]: {e}")
# 2. Redis 未命中,检查 MySQL 可用性
if not self.check_mysql():
return None
# 3. 从 MySQL 读取
try:
SessionLocal = sessionmaker(bind=self.mysql_engine)
with SessionLocal() as db:
record = (
db.query(SymbolTimestamp)
.filter_by(symbol=symbol, data_type=data_type)
.first()
)
if not record:
return None
result = {
"last_refresh_at": (
record.last_refresh_at.isoformat()
if record.last_refresh_at
else None
),
"refresh_count": record.refresh_count,
}
# 4. 回填 RedisTTL 30 天)
if self.check_redis():
try:
self.redis_client.setex(
cache_key,
REDIS_TTL_SECONDS,
json.dumps(result, ensure_ascii=False),
)
except Exception as e:
logger.warning(f"Redis 回填失败 [{cache_key}]: {e}")
return result
except Exception as e:
logger.warning(f"MySQL 读取失败 [{cache_key}]: {e}")
return None
def save_market_data(self, symbol, data):
"""
保存行情数据先删 Redis 缓存再写 MySQLMySQL 成功后回填 Redis
Args:
symbol: 品种合约代码
data: 采集脚本返回的数据包含 timeframes, current_price, timestamp, type
Returns:
bool: MySQL 写入是否成功
"""
data_type = data.get("type", "futures")
timeframes = data.get("timeframes", {})
current_price = data.get("current_price")
fetched_at = self._parse_fetched_at(data.get("timestamp"))
cache_keys = [f"market_data:{symbol}:{period}" for period in timeframes.keys()]
# 1. 删除 Redis 缓存
if self.check_redis() and cache_keys:
try:
self.redis_client.delete(*cache_keys)
except Exception as e:
logger.warning(f"Redis 删除缓存失败 [{symbol}]: {e}")
# 2. 写入 MySQL事务
if not self.check_mysql():
logger.warning(f"MySQL 不可用,无法写入行情数据 [{symbol}]")
return False
try:
SessionLocal = sessionmaker(bind=self.mysql_engine)
with SessionLocal() as db:
try:
for period, candles in timeframes.items():
candles_json = json.dumps(candles, ensure_ascii=False)
record = (
db.query(MarketData)
.filter_by(symbol=symbol, data_type=data_type, period=period)
.first()
)
if record:
record.candles_json = candles_json
record.current_price = current_price
record.fetched_at = fetched_at
record.candle_count = len(candles)
else:
record = MarketData(
symbol=symbol,
data_type=data_type,
period=period,
candles_json=candles_json,
current_price=current_price,
fetched_at=fetched_at,
candle_count=len(candles),
)
db.add(record)
db.commit()
except Exception:
db.rollback()
raise
except Exception as e:
logger.error(f"MySQL 写入行情数据失败 [{symbol}]: {e}")
return False
# 3. MySQL 成功,回填 Redis失败仅记录日志
if self.check_redis():
for period, candles in timeframes.items():
cache_key = f"market_data:{symbol}:{period}"
cache_value = {
"current_price": current_price,
"timestamp": fetched_at.isoformat(),
"candles": candles,
}
try:
self.redis_client.setex(
cache_key,
REDIS_TTL_SECONDS,
json.dumps(cache_value, ensure_ascii=False),
)
except Exception as e:
logger.warning(f"Redis 更新失败 [{cache_key}]: {e}")
return True
def save_symbol_timestamp(self, symbol, data_type, refresh_time):
"""
保存合约时间戳先删 Redis 缓存再写 MySQLMySQL 成功后回填 Redis
Args:
symbol: 品种合约代码
data_type: 数据类型 futures
refresh_time: 刷新时间datetime
Returns:
bool: MySQL 写入是否成功
"""
cache_key = f"symbol_timestamps:{symbol}"
# 1. 删除 Redis 缓存
if self.check_redis():
try:
self.redis_client.delete(cache_key)
except Exception as e:
logger.warning(f"Redis 删除缓存失败 [{cache_key}]: {e}")
# 2. 写入 MySQL事务
if not self.check_mysql():
logger.warning(f"MySQL 不可用,无法写入合约时间戳 [{symbol}]")
return False
try:
SessionLocal = sessionmaker(bind=self.mysql_engine)
with SessionLocal() as db:
try:
record = (
db.query(SymbolTimestamp)
.filter_by(symbol=symbol, data_type=data_type)
.first()
)
if record:
record.last_refresh_at = refresh_time
record.refresh_count += 1
else:
record = SymbolTimestamp(
symbol=symbol,
data_type=data_type,
last_refresh_at=refresh_time,
refresh_count=1,
)
db.add(record)
db.commit()
except Exception:
db.rollback()
raise
except Exception as e:
logger.error(f"MySQL 写入合约时间戳失败 [{symbol}]: {e}")
return False
# 3. MySQL 成功,回填 Redis失败仅记录日志
if self.check_redis():
cache_value = {
"last_refresh_at": refresh_time.isoformat(),
"refresh_count": record.refresh_count,
}
try:
self.redis_client.setex(
cache_key,
REDIS_TTL_SECONDS,
json.dumps(cache_value, ensure_ascii=False),
)
except Exception as e:
logger.warning(f"Redis 更新失败 [{cache_key}]: {e}")
return True
def save_market_data_with_timestamp(self, symbol, data, refresh_time):
"""
在同一 MySQL 事务中原子写入行情数据与合约时间戳
Redis 缓存的删除/回填在事务外进行失败仅记录日志不影响 MySQL 写入
Args:
symbol: 品种合约代码
data: 采集脚本返回的数据包含 timeframes, current_price, timestamp, type
refresh_time: 刷新时间datetime
Returns:
bool: MySQL 写入是否成功
"""
data_type = data.get("type", "futures")
timeframes = data.get("timeframes", {})
current_price = data.get("current_price")
fetched_at = self._parse_fetched_at(data.get("timestamp"))
market_cache_keys = [
f"market_data:{symbol}:{period}" for period in timeframes.keys()
]
timestamp_cache_key = f"symbol_timestamps:{symbol}"
cache_keys = market_cache_keys + [timestamp_cache_key]
# 1. 删除 Redis 缓存
if self.check_redis() and cache_keys:
try:
self.redis_client.delete(*cache_keys)
except Exception as e:
logger.warning(f"Redis 删除缓存失败 [{symbol}]: {e}")
# 2. 写入 MySQL同一事务
if not self.check_mysql():
logger.warning(f"MySQL 不可用,无法写入行情数据与时间戳 [{symbol}]")
return False
try:
SessionLocal = sessionmaker(bind=self.mysql_engine)
with SessionLocal() as db:
try:
for period, candles in timeframes.items():
candles_json = json.dumps(candles, ensure_ascii=False)
record = (
db.query(MarketData)
.filter_by(symbol=symbol, data_type=data_type, period=period)
.first()
)
if record:
record.candles_json = candles_json
record.current_price = current_price
record.fetched_at = fetched_at
record.candle_count = len(candles)
else:
record = MarketData(
symbol=symbol,
data_type=data_type,
period=period,
candles_json=candles_json,
current_price=current_price,
fetched_at=fetched_at,
candle_count=len(candles),
)
db.add(record)
timestamp_record = (
db.query(SymbolTimestamp)
.filter_by(symbol=symbol, data_type=data_type)
.first()
)
if timestamp_record:
timestamp_record.last_refresh_at = refresh_time
timestamp_record.refresh_count += 1
refresh_count = timestamp_record.refresh_count
else:
timestamp_record = SymbolTimestamp(
symbol=symbol,
data_type=data_type,
last_refresh_at=refresh_time,
refresh_count=1,
)
db.add(timestamp_record)
refresh_count = 1
db.commit()
except Exception:
db.rollback()
raise
except Exception as e:
logger.error(f"MySQL 写入行情数据与时间戳失败 [{symbol}]: {e}")
return False
# 3. MySQL 成功,回填 Redis失败仅记录日志
if self.check_redis():
for period, candles in timeframes.items():
cache_key = f"market_data:{symbol}:{period}"
cache_value = {
"current_price": current_price,
"timestamp": fetched_at.isoformat(),
"candles": candles,
}
try:
self.redis_client.setex(
cache_key,
REDIS_TTL_SECONDS,
json.dumps(cache_value, ensure_ascii=False),
)
except Exception as e:
logger.warning(f"Redis 更新失败 [{cache_key}]: {e}")
timestamp_cache_value = {
"last_refresh_at": refresh_time.isoformat(),
"refresh_count": refresh_count,
}
try:
self.redis_client.setex(
timestamp_cache_key,
REDIS_TTL_SECONDS,
json.dumps(timestamp_cache_value, ensure_ascii=False),
)
except Exception as e:
logger.warning(f"Redis 更新失败 [{timestamp_cache_key}]: {e}")
return True
def delete_cache(self, symbol, periods):
"""
批量删除 Redis 行情数据缓存键
Args:
symbol: 品种合约代码
periods: 周期列表 ["5min", "15min"]
"""
if not self.check_redis():
return
cache_keys = [f"market_data:{symbol}:{period}" for period in periods]
if not cache_keys:
return
try:
self.redis_client.delete(*cache_keys)
except Exception as e:
logger.warning(f"Redis 批量删除缓存失败 [{symbol}]: {e}")
def cache_get(self, key):
"""
通用 Redis 缓存读取
Args:
key: 缓存键
Returns:
反序列化后的值 None
"""
if not self.check_redis():
return None
try:
raw = self.redis_client.get(key)
if raw:
return json.loads(raw)
except Exception as e:
logger.warning(f"Redis 读取失败 [{key}]: {e}")
return None
def cache_set(self, key, value, ttl=None):
"""
通用 Redis 缓存写入
Args:
key: 缓存键
value: 缓存值 JSON 序列化
ttl: 过期时间默认 REDIS_TTL_SECONDS
Returns:
bool: 是否成功
"""
if not self.check_redis():
return False
if ttl is None:
ttl = REDIS_TTL_SECONDS
try:
self.redis_client.setex(
key, ttl, json.dumps(value, ensure_ascii=False, default=str)
)
return True
except Exception as e:
logger.warning(f"Redis 写入失败 [{key}]: {e}")
return False
def cache_delete(self, key):
"""
通用 Redis 缓存删除
Args:
key: 缓存键
"""
if not self.check_redis():
return
try:
self.redis_client.delete(key)
except Exception as e:
logger.warning(f"Redis 删除失败 [{key}]: {e}")
_storage_manager = None
def get_storage_manager():
"""获取全局 StorageManager 单例。"""
global _storage_manager
if _storage_manager is None:
_storage_manager = StorageManager()
return _storage_manager

Binary file not shown.

@ -15,19 +15,6 @@ services:
- BUFFER_LOG_LEVEL=INFO
- MAX_WORKERS=2
- TZ=Asia/Shanghai
- REDIS_HOST=redis
- REDIS_PORT=6379
- REDIS_DB=0
- REDIS_PASSWORD=${REDIS_PASSWORD:-}
- REDIS_TTL_SECONDS=${REDIS_TTL_SECONDS:-2592000}
- MYSQL_HOST=mysql
- MYSQL_PORT=3306
- MYSQL_USER=root
- MYSQL_PASSWORD=${MYSQL_PASSWORD:-buffer123}
- MYSQL_DATABASE=${MYSQL_DATABASE:-buffer_platform}
depends_on:
- redis
- mysql
volumes:
# 数据持久化 - SQLite数据库
- ./data:/app/data
@ -44,35 +31,6 @@ services:
networks:
- futures-network
redis:
image: redis:7-alpine
container_name: futures-redis
restart: unless-stopped
ports:
- "6379:6379"
volumes:
- redis-data:/data
networks:
- futures-network
mysql:
image: mysql:8.0
container_name: futures-mysql
restart: unless-stopped
environment:
MYSQL_ROOT_PASSWORD: ${MYSQL_PASSWORD:-buffer123}
MYSQL_DATABASE: ${MYSQL_DATABASE:-buffer_platform}
ports:
- "3306:3306"
volumes:
- mysql-data:/var/lib/mysql
networks:
- futures-network
networks:
futures-network:
driver: bridge
volumes:
redis-data:
mysql-data:

@ -1,102 +0,0 @@
---
change: analysis-storage-refactor
design-doc: docs/superpowers/specs/2026-07-04-analysis-storage-refactor-design.md
base-ref: 82de2f9
archived-with: 2026-07-04-analysis-storage-refactor
---
# Analysis Storage Refactor - 实施计划
> 基于 [Design Doc](docs/superpowers/specs/2026-07-04-analysis-storage-refactor-design.md) 拆分的可执行任务。
> 目标:将 `futures_analysis.db`14 张表)迁移到 MySQL并引入 Redis 缓存层,与行情数据存储策略保持一致。
---
## 任务总览
| # | 任务 | 依赖 |
|---|------|------|
| T1 | 扩展 StorageManager 通用缓存方法 | - |
| T2 | 创建 analysis_migration.py 迁移脚本 | T1 |
| T3 | 修改 analysis_db.py 支持 MySQL/SQLite 动态切换 | T1 |
| T4 | 在 main.py lifespan 中集成迁移和表初始化 | T2, T3 |
| T5 | 编写测试用例 | T1-T4 |
---
## T1: 扩展 StorageManager 通用缓存方法
**文件**: `app/storage_manager.py`
**任务**:
1. 新增 `cache_get(key)` 方法
2. 新增 `cache_set(key, value, ttl)` 方法
3. 新增 `cache_delete(key)` 方法
**验收**:
- 方法支持 Redis 命中/未命中
- 缓存 TTL 可配置
- 通用方法不依赖具体业务
---
## T2: 创建 analysis_migration.py 迁移脚本
**文件**: `app/analysis_migration.py`
**任务**:
1. 实现 `migrate_analysis_sqlite_to_mysql()` 函数
2. 检测 MySQL analysis 表是否已有数据
3. 从 SQLite 读取全部数据
4. 批量写入 MySQL
5. 记录迁移日志
**验收**:
- 幂等性MySQL 有数据时跳过迁移
- 迁移失败不影响应用启动
---
## T3: 修改 analysis_db.py 使用 StorageManager
**文件**: `app/analysis_db.py`
**任务**:
1. 修改 `get_analysis_db()` 使用 StorageManager
2. 实现 MySQL 不可用时降级到 SQLite
3. 保持 API 接口不变
**验收**:
- API 调用透明切换存储后端
- 降级时功能正常
---
## T4: 在 main.py lifespan 中集成
**文件**: `app/main.py`
**任务**:
1. 在 lifespan 中创建 analysis 表MySQL
2. 调用迁移函数
3. 记录启动日志
**验收**:
- 启动时自动创建 14 张表
- 自动迁移 SQLite 数据
---
## T5: 编写测试用例
**文件**: `tests/test_analysis_storage.py`
**任务**:
1. 测试 Redis 缓存命中场景
2. 测试 Redis 缓存未命中回源 MySQL
3. 测试 MySQL 不可用降级到 SQLite
4. 测试数据迁移完整性
**验收**:
- 所有测试通过
- 覆盖三级降级场景

@ -1,129 +0,0 @@
---
change: config-to-mysql
design-doc: docs/superpowers/specs/2026-07-04-config-to-mysql-design.md
base-ref: 4956086
archived-with: config-to-mysql
---
# Config to MySQL - 实施计划
> 基于 [Design Doc](docs/superpowers/specs/2026-07-04-config-to-mysql-design.md) 拆分的可执行任务。
> 目标:将 `symbols_config.json``ai_config.json` 迁移到 MySQL保留 JSON 文件作为 fallback。
---
## 任务总览
| # | 任务 | 依赖 |
|---|------|------|
| T1 | 新增 AppConfig 模型和 ConfigStore | - |
| T2 | 创建 config_migration.py 迁移脚本 | T1 |
| T3 | 在 main.py lifespan 中集成 | T1, T2 |
| T4 | 修改配置 API | T1 |
| T5 | 修改业务使用方 | T1 |
| T6 | 编写测试用例 | T1-T5 |
---
## T1: 新增 AppConfig 模型和 ConfigStore
**文件**:
- `app/models.py`
- `app/config_store.py`
**任务**:
1. 在 `app/models.py` 中新增 `AppConfig` 模型
2. 创建 `app/config_store.py``ConfigStore`
3. 实现 `get_config(key, fallback)`
4. 实现 `set_config(key, value)`
5. 实现 `load_from_json(key, fallback)``save_to_json(key, value)`
6. 实现 `get_config_store()` 单例函数
**验收**:
- `ConfigStore` 支持 MySQL 命中、未命中回填、JSON fallback
- `set_config` 始终写入 JSONMySQL 可用时同时写入数据库
---
## T2: 创建 config_migration.py 迁移脚本
**文件**: `app/config_migration.py`
**任务**:
1. 定义配置映射key → file path → default
2. 实现 `migrate_configs_to_mysql()`
3. 检测数据库是否已有配置
4. 从 JSON 读取并写入 MySQL
**验收**:
- 幂等性:数据库已有数据时跳过
- 缺失配置时从 JSON 迁移
---
## T3: 在 main.py lifespan 中集成
**文件**: `app/main.py`
**任务**:
1. 在 MySQL 初始化后创建 `app_config`
2. 调用 `migrate_configs_to_mysql()`
3. 记录迁移日志
**验收**:
- 启动时自动创建配置表
- 自动迁移 JSON 配置
---
## T4: 修改配置 API
**文件**:
- `app/api/config.py`
- `app/api/ai_config.py`
**任务**:
1. `config.py``get_config``upload_config` 使用 `ConfigStore`
2. `ai_config.py``_load_ai_config``_save_ai_config` 使用 `ConfigStore`
3. 保持 API 接口签名不变
**验收**:
- 上传配置同时写入数据库和 JSON 文件
- 读取配置优先从数据库
---
## T5: 修改业务使用方
**文件**:
- `app/api/futures_analysis.py`
- `app/api/trade_review.py`
- `app/services/trade_parser.py`
- `app/services/plan_generator.py`
- `app/services/ai_analysis.py`
**任务**:
1. 替换所有 `_load_symbols_config()` / `load_symbols_config()``ConfigStore.get_config("symbols")`
2. 替换 `_load_ai_config()``ConfigStore.get_config("ai")`
**验收**:
- 所有读取点统一使用 `ConfigStore`
- 不修改业务逻辑
---
## T6: 编写测试用例
**文件**: `tests/test_config_store.py`
**任务**:
1. 测试 MySQL 命中场景
2. 测试 MySQL 未命中时读取 JSON 并回填
3. 测试 MySQL 不可用时读取 JSON
4. 测试 `set_config` 双写
5. 测试迁移幂等性
6. 运行全部测试套件确保无回归
**验收**:
- 所有测试通过
- 测试覆盖核心降级场景

@ -1,448 +0,0 @@
---
change: storage-cache-refactor
design-doc: docs/superpowers/specs/2026-07-04-storage-cache-refactor-design.md
base-ref: 8b5e43f4915cef786208a8132460f87b8b191765
archived-with: 2026-07-04-storage-cache-refactor
---
# Storage Cache Refactor - 实施计划
> 基于 [Design Doc](docs/superpowers/specs/2026-07-04-storage-cache-refactor-design.md) 拆分的可执行任务。
> 目标:引入 Redis缓存+ MySQL持久化+ SQLite兜底三级存储架构改造现有 cache.py 内部封装 StorageManagerAPI 层零改动。
---
## 任务总览
| # | 任务 | 预估 | 依赖 |
|---|------|------|------|
| T1 | 添加 redis/pymysql 依赖 | 5min | - |
| T2 | config.py 新增 Redis/MySQL 配置项 | 10min | - |
| T3 | docker-compose.yml 新增 Redis/MySQL 服务 | 10min | T2 |
| T4 | 创建 app/mysql_database.py | 20min | T2 |
| T5 | 创建 app/redis_client.py | 20min | T2 |
| T6 | lifespan 中初始化 Redis/MySQL 连接 | 15min | T4, T5 |
| T7 | MySQL 表结构初始化(复用 ORM 模型) | 15min | T4, T6 |
| T8 | 创建 app/storage_manager.py 骨架 + 降级检测 | 30min | T4, T5, T6 |
| T9 | StorageManager 读取逻辑Redis → MySQL → SQLite | 30min | T8 |
| T10 | StorageManager 写入逻辑 + 双写一致性 | 30min | T8 |
| T11 | 创建数据迁移脚本 app/migration.py | 25min | T4, T7 |
| T12 | 启动时自动触发迁移 | 10min | T11 |
| T13 | 改造 cache.py 内部封装 StorageManager | 30min | T9, T10 |
| T14 | 验证Redis 缓存命中/未命中场景 | 15min | T13 |
| T15 | 验证:降级到 MySQL / SQLite 场景 | 15min | T13 |
| T16 | 验证:双写一致性 + 数据迁移完整性 | 15min | T13 |
---
## 详细任务
### T1: 添加 redis/pymysql 依赖
**文件**: `requirements.txt`
**操作**:
- 在 `requirements.txt` 末尾追加:
```
redis>=5.0.0
pymysql>=1.1.0
cryptography>=42.0.0
```
- `cryptography` 是 PyMySQL 启用加密连接所需的可选依赖
**验证**: `pip install -r requirements.txt` 成功安装无报错
---
### T2: config.py 新增 Redis/MySQL 配置项
**文件**: `app/config.py`
**操作**:
- 在现有配置末尾新增以下配置块(参考 Design Doc §7.1
```python
# Redis 配置
REDIS_HOST = os.getenv("REDIS_HOST", "localhost")
REDIS_PORT = int(os.getenv("REDIS_PORT", "6379"))
REDIS_DB = int(os.getenv("REDIS_DB", "0"))
REDIS_PASSWORD = os.getenv("REDIS_PASSWORD", "")
REDIS_TTL_SECONDS = int(os.getenv("REDIS_TTL_SECONDS", "2592000")) # 30 天
# MySQL 配置
MYSQL_HOST = os.getenv("MYSQL_HOST", "localhost")
MYSQL_PORT = int(os.getenv("MYSQL_PORT", "3306"))
MYSQL_USER = os.getenv("MYSQL_USER", "root")
MYSQL_PASSWORD = os.getenv("MYSQL_PASSWORD", "")
MYSQL_DATABASE = os.getenv("MYSQL_DATABASE", "buffer_platform")
```
**验证**: `from app.config import REDIS_HOST, MYSQL_HOST` 无报错,默认值正确
---
### T3: docker-compose.yml 新增 Redis/MySQL 服务
**文件**: `docker-compose.yml`
**操作**:
- 在 `services` 下新增 `redis``mysql` 服务(参考 Design Doc §7.2
```yaml
redis:
image: redis:7-alpine
container_name: futures-redis
restart: unless-stopped
ports:
- "6379:6379"
volumes:
- redis-data:/data
networks:
- futures-network
mysql:
image: mysql:8.0
container_name: futures-mysql
restart: unless-stopped
environment:
MYSQL_ROOT_PASSWORD: ${MYSQL_PASSWORD:-buffer123}
MYSQL_DATABASE: ${MYSQL_DATABASE:-buffer_platform}
ports:
- "3306:3306"
volumes:
- mysql-data:/var/lib/mysql
networks:
- futures-network
```
- 在顶层新增 `volumes` 声明:
```yaml
volumes:
redis-data:
mysql-data:
```
- 在 `buffer-platform``environment` 中新增 Redis/MySQL 环境变量传递
**验证**: `docker-compose config` 解析无语法错误
---
### T4: 创建 app/mysql_database.py
**文件**: `app/mysql_database.py`(新建)
**操作**:
- 创建 MySQL 连接引擎和 SessionLocal参考现有 `app/database.py` 的结构:
```python
from sqlalchemy import create_engine, text
from sqlalchemy.orm import sessionmaker
from app.config import MYSQL_HOST, MYSQL_PORT, MYSQL_USER, MYSQL_PASSWORD, MYSQL_DATABASE
mysql_engine = None
MySQLSessionLocal = None
def init_mysql():
"""初始化 MySQL 连接引擎,失败时返回 None"""
global mysql_engine, MySQLSessionLocal
try:
url = f"mysql+pymysql://{MYSQL_USER}:{MYSQL_PASSWORD}@{MYSQL_HOST}:{MYSQL_PORT}/{MYSQL_DATABASE}?charset=utf8mb4"
mysql_engine = create_engine(url, pool_pre_ping=True, pool_recycle=3600)
with mysql_engine.connect() as conn:
conn.execute(text("SELECT 1"))
MySQLSessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=mysql_engine)
return mysql_engine
except Exception as e:
logger.warning(f"MySQL 初始化失败: {e}")
mysql_engine = None
MySQLSessionLocal = None
return None
def get_mysql_session():
"""获取 MySQL 会话"""
if MySQLSessionLocal is None:
raise RuntimeError("MySQL 未初始化")
return MySQLSessionLocal()
```
**验证**: 手动调用 `init_mysql()`,在无 MySQL 环境下返回 `None` 不抛异常
---
### T5: 创建 app/redis_client.py
**文件**: `app/redis_client.py`(新建)
**操作**:
- 封装 Redis 连接池和客户端:
```python
import redis
from app.config import REDIS_HOST, REDIS_PORT, REDIS_DB, REDIS_PASSWORD
redis_client = None
def init_redis():
"""初始化 Redis 客户端,失败时返回 None"""
global redis_client
try:
redis_client = redis.Redis(
host=REDIS_HOST, port=REDIS_PORT, db=REDIS_DB,
password=REDIS_PASSWORD or None,
decode_responses=True,
socket_connect_timeout=5,
)
redis_client.ping()
return redis_client
except Exception as e:
logger.warning(f"Redis 初始化失败: {e}")
redis_client = None
return None
def get_redis():
"""获取 Redis 客户端实例"""
return redis_client
```
**验证**: 手动调用 `init_redis()`,在无 Redis 环境下返回 `None` 不抛异常
---
### T6: lifespan 中初始化 Redis/MySQL 连接
**文件**: `app/main.py`
**操作**:
- 在 `lifespan` 函数中,`Base.metadata.create_all` 之后新增:
```python
# 初始化 Redis 和 MySQL
from app.redis_client import init_redis
from app.mysql_database import init_mysql
redis_ok = init_redis() is not None
mysql_ok = init_mysql() is not None
if redis_ok and mysql_ok:
logger.info("存储模式: Redis + MySQL")
elif mysql_ok:
logger.warning("存储模式: MySQL (Redis 不可用)")
else:
logger.error("存储模式: SQLite (Redis 和 MySQL 均不可用)")
```
**验证**: 应用启动日志中输出存储模式信息,无 Redis/MySQL 时降级提示正常
---
### T7: MySQL 表结构初始化(复用 ORM 模型)
**文件**: `app/main.py`(修改 lifespan
**操作**:
- 在 T6 初始化代码之后,如果 MySQL 可用,使用现有 ORM 模型创建表:
```python
if mysql_ok:
from app.mysql_database import mysql_engine
from app.models import Base as MarketBase
# 在 MySQL 中创建行情相关表
MarketBase.metadata.create_all(bind=mysql_engine)
logger.info("MySQL 表结构初始化完成")
```
- 注意:只需创建 `market_data``symbol_timestamps` 两张表,`scheduled_tasks` 等低频表仍留在 SQLite
**验证**: MySQL 中可查到 `market_data``symbol_timestamps` 表结构
---
### T8: 创建 app/storage_manager.py 骨架 + 降级检测
**文件**: `app/storage_manager.py`(新建)
**操作**:
- 实现 `StorageManager` 类骨架,包含:
- `__init__`: 持有 redis_client / mysql_engine 引用,初始化降级状态标志
- `check_redis()` / `check_mysql()`: 惰性恢复检测30 秒间隔,参考 Design Doc §4.1
- `is_available()`: 判断 Redis 或 MySQL 至少一个可用
- `initialize()`: 启动时调用,检测各后端可用性并输出日志
- 全局单例 `get_storage_manager()` 工厂函数
- 本任务只实现骨架和降级检测,不包含具体读写逻辑
**验证**: 实例化 `StorageManager` 后,`check_redis()` / `check_mysql()` 在无服务环境下返回 `False`
---
### T9: StorageManager 读取逻辑Redis → MySQL → SQLite
**文件**: `app/storage_manager.py`(续写)
**操作**:
- 实现 `get_market_data(symbol, data_type, periods)` 方法:
1. 检查 Redis 缓存key 格式:`market_data:{symbol}:{period}`,参考 Design Doc §2.1
2. Redis 命中 → 反序列化 JSON 返回
3. Redis 未命中 → 检查 MySQL 可用性
4. MySQL 可用 → 从 MySQL 读取 → 回填 RedisTTL 30 天)→ 返回
5. MySQL 不可用 → 返回 `None`(由调用方降级到 SQLite
- 实现 `get_symbol_timestamp(symbol, data_type)` 方法:
- 类似逻辑key 格式:`symbol_timestamps:{symbol}`
**验证**: 单元测试或手动测试:
- 无 Redis/MySQL 时返回 `None`
- 有 MySQL 时从 MySQL 读取并回填 Redis
---
### T10: StorageManager 写入逻辑 + 双写一致性
**文件**: `app/storage_manager.py`(续写)
**操作**:
- 实现 `save_market_data(symbol, data)` 方法(参考 Design Doc §3.2
1. 删除 Redis 缓存(`market_data:{symbol}:{period}`
2. 写入 MySQL事务
3. MySQL 成功 → 更新 Redis 缓存
4. MySQL 失败 → 记录日志,返回 False不更新 Redis
5. Redis 更新失败 → 仅记录日志,不影响返回
- 实现 `save_symbol_timestamp(symbol, data_type, refresh_time)` 方法:
- 类似双写逻辑
- 实现 `delete_cache(symbol, periods)` 方法:
- 批量删除 Redis 缓存键
**验证**:
- MySQL 写入成功 → Redis 缓存同步更新
- MySQL 写入失败 → Redis 不更新,返回 False
- Redis 更新失败 → 不影响 MySQL 写入结果
---
### T11: 创建数据迁移脚本 app/migration.py
**文件**: `app/migration.py`(新建)
**操作**:
- 实现 `migrate_sqlite_to_mysql()` 函数(参考 Design Doc §6.1
1. 创建 SQLite 引擎(复用 `DB_PATH`
2. 检查 MySQL `market_data` 表是否为空
3. 为空时从 SQLite 读取全部 `market_data` 记录
4. 批量写入 MySQL
5. 同样迁移 `symbol_timestamps`
6. 输出迁移记录数日志
- 幂等设计MySQL 已有数据时跳过
**验证**:
- MySQL 表为空时,迁移成功,数据条数一致
- MySQL 表非空时,跳过迁移,日志提示
---
### T12: 启动时自动触发迁移
**文件**: `app/main.py`(修改 lifespan
**操作**:
- 在 T7 表结构初始化之后新增:
```python
if mysql_ok:
from app.migration import migrate_sqlite_to_mysql
migrate_sqlite_to_mysql()
```
**验证**: 首次启动时日志输出迁移信息,再次启动时跳过迁移
---
### T13: 改造 cache.py 内部封装 StorageManager
**文件**: `app/services/cache.py`(修改)
**操作**:
- 改造 `save_market_data()` 函数(参考 Design Doc §5.1
- 优先调用 `storage.save_market_data(symbol, data)` 双写
- 失败时降级到现有 SQLite 写入逻辑 `_save_to_sqlite()`
- 改造 `get_cached_data()` 函数:
- 优先调用 `storage.get_market_data(symbol, data_type, periods)` 读取
- 返回 `None` 时降级到现有 SQLite 读取逻辑 `_get_from_sqlite()`
- 改造 `update_symbol_timestamp()``get_symbol_timestamp()`
- 类似封装,优先走 StorageManager
- 保持所有函数的外部签名不变API 层零改动
- 现有 SQLite 逻辑提取为内部 `_save_to_sqlite()` / `_get_from_sqlite()` 私有函数
**验证**:
- 现有 API 接口 `/api/v1/data/latest/{symbol}` 返回数据格式不变
- 现有 API 接口 `/api/v1/data/batch-fetch` 行为不变
- 无 Redis/MySQL 时完全降级到 SQLite行为与改造前一致
---
### T14: 验证 - Redis 缓存命中/未命中场景
**操作**:
- 启动 Redis + MySQL 服务
- 调用刷新接口写入数据
- 调用读取接口,验证首次从 MySQL 读取并回填 Redis
- 再次调用读取接口,验证从 Redis 缓存命中(检查日志)
- 等待 TTL 过期或手动删除 Redis key验证回源 MySQL
**验证标准**:
- 日志中可见 "Redis 缓存命中" / "Redis 未命中,从 MySQL 读取" 信息
- 返回数据格式正确
---
### T15: 验证 - 降级到 MySQL / SQLite 场景
**操作**:
- 停止 Redis 服务,调用读取接口
- 验证自动降级到 MySQL日志输出 "Redis 不可用"
- 停止 Redis + MySQL 服务,调用读取接口
- 验证降级到 SQLite日志输出 "存储模式: SQLite"
- 恢复 Redis 服务,等待 30 秒后验证自动恢复
**验证标准**:
- 各降级场景下接口正常返回,无 500 错误
- 日志清晰标识当前存储模式
---
### T16: 验证 - 双写一致性 + 数据迁移完整性
**操作**:
- 双写一致性:
1. 调用刷新接口写入数据
2. 分别查询 MySQL 和 Redis验证数据一致
3. 模拟 Redis 写入失败(停止 Redis验证 MySQL 数据不受影响
- 数据迁移完整性:
1. 清空 MySQL 表
2. 重启应用触发迁移
3. 对比 SQLite 和 MySQL 数据条数一致
**验证标准**:
- MySQL 和 Redis 中数据内容一致
- Redis 故障不影响 MySQL 持久化
- 迁移前后数据条数一致
---
## 依赖关系图
```
T1 (依赖) ──┐
T2 (配置) ──┼── T3 (docker-compose)
├── T4 (mysql_database.py)
└── T5 (redis_client.py)
T4 + T5 ─────── T6 (lifespan 初始化)
T7 (MySQL 建表)
T8 (StorageManager 骨架)
T9 T10 (读/写逻辑)
T13 (cache.py 改造)
│ ╲
T14 T15 T16 (验证)
T4 + T7 ──── T11 (迁移脚本) ──── T12 (启动迁移)
```
## 关键约束
1. **API 层零改动**: `app/api/data.py` 不修改,所有变更封装在 `cache.py``storage_manager.py` 内部
2. **SQLite 保留**: 不删除 SQLite 相关代码,作为最终兜底
3. **幂等迁移**: 数据迁移脚本可重复执行MySQL 有数据时跳过
4. **渐进式降级**: 无 Redis/MySQL 时系统行为与改造前完全一致

@ -1,20 +0,0 @@
# 验证报告: analysis-storage-refactor
## 代码审查
| 级别 | 问题 | 状态 |
|------|------|------|
| CRITICAL | 迁移写入使用 `db.expunge(record)` 会导致 `InvalidRequestError` | 已修复,改用 `make_transient` |
| CRITICAL | `get_analysis_db()` 在 MySQL Session 创建失败时抛出 `UnboundLocalError` | 已修复,增加异常降级 |
| IMPORTANT | 启动流程中 MySQL 初始化/迁移未做错误隔离 | 部分接受:`get_analysis_db` 已增加降级lifespan 中 `init_analysis_mysql` 依赖 MySQL 可用性判断,异常会被顶层捕获 |
| IMPORTANT | 测试覆盖补充 | 已补充 MySQL Session 创建失败降级测试 |
## 分支处理
- 分支:`feature/20260704/analysis-storage-refactor`
- 处理方式合并到当前分支refactor3.0
- 合并后提交:`2797447`
## 结论
验证通过,可以归档。

@ -1,66 +0,0 @@
# Config to MySQL - 验证报告
- **Change**: config-to-mysql
- **日期**: 2026-07-04
- **验证人**: AI Agent
- **分支**: feature/20260704/config-to-mysql
## 验证项
| # | 检查项 | 结果 | 证据 |
|---|--------|------|------|
| 1 | tasks.md 全部完成 | ✅ | 所有 18 个子任务已勾选 |
| 2 | 实现符合 Design Doc | ✅ | 单表 `app_config`、统一 `ConfigStore`、JSON fallback |
| 3 | 实现符合 proposal | ✅ | symbols + ai 配置迁移到 MySQL保留 JSON fallback |
| 4 | 测试通过 | ✅ | `python -m pytest tests/` 110 passed, 2 xfailed |
| 5 | 新增测试覆盖核心场景 | ✅ | `tests/test_config_store.py` 8 个用例覆盖命中/未命中/降级/迁移 |
| 6 | 无硬编码密钥 | ✅ | 代码审查未发现 |
| 7 | 无 SQL 注入风险 | ✅ | 使用 SQLAlchemy ORM 参数化查询 |
## 代码审查
**审查方式**: general_purpose_task 子代理审查
### 已修复问题
| 级别 | 问题 | 修复方式 |
|------|------|----------|
| CRITICAL | MySQL 写入失败时 JSON 已更新但 MySQL 仍为旧值 | `set_config` 改为先写 MySQL成功后再写 JSON失败返回 False 并保留 JSON 旧值 |
| IMPORTANT | JSON 文件直接覆盖写入 | 使用临时文件 + `replace` 原子写入 |
| IMPORTANT | JSON 损坏时回填 MySQL 默认值 | 新增 `_load_json_from_file`,损坏时返回 Noneget_config 使用 fallback 但不回填 |
| IMPORTANT | `_save_to_mysql` 返回 False 时未处理 | `set_config` 检查 `_save_to_mysql` 返回值 |
| MINOR | 多处未使用导入/变量 | 已清理 |
### 接受的风险
| 级别 | 问题 | 接受原因 |
|------|------|----------|
| IMPORTANT | AI 配置中的 `api_key` 以明文存入 MySQL JSON 字段 | 超出本次 change 范围JSON 文件原本也是明文存储,风险未扩大;建议后续单独 change 增加加密或敏感字段隔离 |
## 分支处理
- [ ] 本地合并到主分支
- [ ] 推送并创建 PR
- [ ] 保持分支
- [ ] 丢弃工作
## 结论
### 重新验证发现的问题
**问题**: 应用启动时配置迁移被跳过MySQL app_config 表为空。
**根因**: `app.mysql_database.MySQLSessionLocal``init_mysql()` 执行前被 `app.config_store` 模块通过 `from app.mysql_database import MySQLSessionLocal` 导入,捕获了初始值 `None`。后续 `init_mysql()` 重新赋值模块变量后,`app.config_store` 中的名称仍指向 `None`,导致 `ConfigStore` 无法获取有效的 MySQL session迁移被跳过。
**修复**:
- `app/config_store.py`: 改为通过 `sys.modules` 动态读取 `app.mysql_database.MySQLSessionLocal`,始终获取最新值
- `app/config_migration.py`: 使用 `store.session_maker` 检查 MySQL session 是否初始化
**修复验证**:
- 清理 app_config 表后启动应用,日志显示成功迁移 symbols 和 ai 配置
- 数据库查询确认 `symbols` 配置包含 38 个品种(与 JSON 文件一致)
- 全部测试套件 110 passed, 2 xfailed
## 结论
验证通过。实现符合设计,测试覆盖核心场景,代码审查和手动验证发现的问题均已修复。

@ -1,197 +0,0 @@
# Verification Report: storage-cache-refactor
## Summary
| 维度 | 状态 |
|--------------|-----------------------------------------------|
| 完整性 (Completeness) | 20/20 任务已勾选14/14 需求已实现 |
| 正确性 (Correctness) | 14/14 需求有测试覆盖8 个测试文件 |
| 一致性 (Coherence) | 遵循设计决策双写顺序正确API 层零改动 |
---
## 1. 完整性验证 (Completeness)
### 1.1 tasks.md 任务勾选状态
全部 20 个任务均已勾选 `[x]`,覆盖 7 个分组:
| 分组 | 任务数 | 状态 |
|--------------------|--------|------|
| 1. 依赖与配置 | 3 | 全部完成 |
| 2. 数据库模型与初始化 | 4 | 全部完成 |
| 3. 数据迁移 | 2 | 全部完成 |
| 4. 存储管理层 | 5 | 全部完成 |
| 5. 双写与缓存一致性 | 3 | 全部完成 |
| 6. 接口改造 | 3 | 全部完成 |
| 7. 测试与验证 | 6 | 全部完成 |
### 1.2 Delta Spec 需求实现映射
**redis-cache-layer (4 需求)**
| 需求 | 实现文件 | 实现状态 |
|------------------------|-----------------------------------|----------|
| Redis 缓存连接管理 | `app/redis_client.py` | ✅ 已实现 |
| 行情数据缓存读取 | `app/storage_manager.py` L147-200 | ✅ 已实现 |
| Redis 缓存 TTL 管理 | `app/config.py` L43 (REDIS_TTL_SECONDS=2592000) | ✅ 已实现 |
| Redis 缓存失效 | `app/storage_manager.py` L413-420 (save_market_data), L578-583 (save_market_data_with_timestamp) | ✅ 已实现 |
**mysql-persistence (4 需求)**
| 需求 | 实现文件 | 实现状态 |
|------------------------|-----------------------------------|----------|
| MySQL 连接管理 | `app/mysql_database.py` | ✅ 已实现 |
| 行情数据持久化存储 | `app/storage_manager.py` L427-460 | ✅ 已实现 |
| MySQL 表结构迁移 | `app/migration.py` | ✅ 已实现 |
| MySQL 事务支持 | `app/storage_manager.py` L430-457 (commit/rollback) | ✅ 已实现 |
**storage-fallback (3 需求)**
| 需求 | 实现文件 | 实现状态 |
|------------------------|-----------------------------------|----------|
| 三级降级策略 | `app/storage_manager.py` L32-87 + `app/services/cache.py` 各函数 | ✅ 已实现 |
| 降级状态检测 | `app/storage_manager.py` L32-67 (惰性检测 30s 间隔) | ✅ 已实现 |
| 降级恢复 | `app/storage_manager.py` L32-67 (超过 check_interval 后重新探测) | ✅ 已实现 |
**dual-write-consistency (3 需求)**
| 需求 | 实现文件 | 实现状态 |
|------------------------|-----------------------------------|----------|
| 刷新接口双写 | `app/storage_manager.py` L553-676 (save_market_data_with_timestamp) | ✅ 已实现 |
| 双写顺序保证 | `app/storage_manager.py` L578-661 (先删 Redis → 写 MySQL → 回填 Redis) | ✅ 已实现 |
| 缓存回填一致性 | `app/storage_manager.py` L186-195 (回填 TTL 30 天) | ✅ 已实现 |
---
## 2. 正确性验证 (Correctness)
### 2.1 测试覆盖矩阵
| 场景 | 测试文件 | 覆盖状态 |
|----------------------------|------------------------------------------------|----------|
| Redis 缓存命中 | `test_redis_cache_scenarios.py` TestRedisCacheHitMiss | ✅ 已覆盖 |
| Redis 缓存未命中回源 MySQL | `test_redis_cache_scenarios.py` TestRedisCacheHitMiss | ✅ 已覆盖 |
| Redis 不可用降级到 MySQL | `test_fallback_scenarios.py` TestStorageManagerFallback, TestApiFallbackResponses | ✅ 已覆盖 |
| Redis+MySQL 均不可用降级到 SQLite | `test_fallback_scenarios.py` TestApiFallbackResponses | ✅ 已覆盖 |
| 双写一致性 | `test_dual_write_and_migration.py` TestDualWriteConsistency, `test_storage_manager.py` TestStorageManagerWriteLogic | ✅ 已覆盖 |
| 迁移完整性 | `test_migration.py` TestMigrateSqliteToMysql, `test_dual_write_and_migration.py` TestMigrationIntegrity | ✅ 已覆盖 |
| 惰性恢复检测 | `test_storage_manager.py` TestStorageManagerSkeleton, `test_fallback_scenarios.py` TestStorageManagerFallback | ✅ 已覆盖 |
| MySQL 失败回滚 | `test_storage_manager.py` TestStorageManagerWriteLogic | ✅ 已覆盖 |
| Redis 失败不影响持久化 | `test_dual_write_and_migration.py` TestDualWriteConsistency | ✅ 已覆盖 |
| 启动时降级日志 | `test_main_lifespan.py`, `test_fallback_scenarios.py` TestLifespanFallbackLogs | ✅ 已覆盖 |
| API 层零改动 | `app/api/data.py` 中无 storage_manager/redis/mysql 引用 | ✅ 已确认 |
### 2.2 测试文件清单
| 测试文件 | 测试类/函数数 | 描述 |
|---------------------------------------|---------------|------|
| `test_storage_manager.py` | 5 类 ~25 测试 | StorageManager 骨架、读取、写入、配置、原子写入 |
| `test_redis_cache_scenarios.py` | 4 类 ~8 测试 | Redis 缓存命中/未命中场景(含 FakeRedis 集成测试) |
| `test_fallback_scenarios.py` | 3 类 ~6 测试 | 降级场景(含 API 层 TestClient 集成测试) |
| `test_dual_write_and_migration.py` | 2 类 ~5 测试 | 双写一致性 + 端到端迁移验证 |
| `test_migration.py` | 1 类 ~3 测试 | SQLite→MySQL 迁移脚本单元测试 |
| `test_cache_storage_integration.py` | 5 类 ~20 测试 | cache.py 与 StorageManager 集成降级测试 |
| `test_mysql_database.py` | 1 测试 | MySQL 密码 URL 编码验证 |
| `test_main_lifespan.py` | ~8 测试 | lifespan 初始化、存储模式、迁移触发 |
---
## 3. 一致性验证 (Coherence)
### 3.1 架构决策遵循情况
| 设计决策 | 实现情况 | 验证详情 |
|-----------------------------|----------|----------|
| Redis + MySQL + SQLite 三级架构 | ✅ 遵循 | `StorageManager` 封装三级逻辑,`cache.py` 各函数先尝试 StorageManager 再降级 SQLite |
| StorageManager 抽象层 | ✅ 遵循 | `app/storage_manager.py` 提供统一接口,`cache.py` 通过 `get_storage_manager()` 调用 |
| 双写顺序:先删 Redis → 写 MySQL → 回填 Redis | ✅ 遵循 | `save_market_data_with_timestamp` L578-661 实现正确 |
| TTL 30 天 | ✅ 遵循 | `REDIS_TTL_SECONDS = 2592000``config.py` 中配置,所有 `setex` 调用使用该值 |
| 惰性恢复30 秒间隔) | ✅ 遵循 | `check_interval=30` 默认值,`check_redis`/`check_mysql` 实现惰性检测 |
| 启动时检测可用性 | ✅ 遵循 | `main.py` lifespan 中调用 `init_redis()`/`init_mysql()` 并注入 StorageManager |
| API 层零改动 | ✅ 遵循 | `app/api/data.py` 仅引用 `app.services.cache` 函数,无任何 storage 相关引用 |
| 数据迁移幂等 | ✅ 遵循 | `migrate_sqlite_to_mysql()` 检查 MySQL 表是否已有数据,有则跳过 |
### 3.2 双写顺序验证
`save_market_data_with_timestamp` (L553-676) 执行顺序:
1. **L578-583**: 删除 Redis 缓存(`market_data:{symbol}:{period}` + `symbol_timestamps:{symbol}`
2. **L590-643**: 写入 MySQL同一事务写入 MarketData + SymbolTimestamp失败则 rollback 并返回 False
3. **L645-674**: MySQL 成功后回填 Redis失败仅记录 warning 日志,不影响返回值)
此顺序与设计文档 §3.2 写入流程图完全一致,属于标准 Cache-Aside 更新模式。
### 3.3 三级降级路径验证
| 路径 | 触发条件 | 实现位置 | 行为 |
|------|----------|----------|------|
| 正常模式 | Redis + MySQL 均可用 | `StorageManager.get_market_data` | Redis → MySQL → 回填 Redis |
| Redis 降级 | Redis 不可用MySQL 可用 | `StorageManager.check_redis()` 返回 False | 直接 MySQL 读取/写入 |
| SQLite 降级 | Redis + MySQL 均不可用 | `cache.py` 各函数 try/except 块 | 降级到 `_get_from_sqlite` / `_save_to_sqlite` |
---
## 4. 安全检查
| 检查项 | 状态 | 详情 |
|--------------------------|------|------|
| 无硬编码密钥 | ✅ 通过 | Redis/MySQL 密码均通过 `os.getenv()` 读取,默认值为空字符串 |
| MySQL 密码 URL 编码 | ✅ 通过 | `mysql_database.py` L20: `urllib.parse.quote_plus(MYSQL_PASSWORD)` |
| 无 unsafe/eval/exec 操作 | ✅ 通过 | 全项目 grep 无匹配 |
| 无敏感信息泄露 | ✅ 通过 | 日志中仅记录连接状态,不输出密码/连接串 |
| docker-compose 密码 | ⚠️ 注意 | 使用 `${MYSQL_PASSWORD:-buffer123}` 作为默认值,仅用于开发环境,可接受 |
---
## 5. Issues
### CRITICAL
无。
### WARNING
无。
### SUGGESTION
1. **xfail 测试标记**`test_redis_cache_scenarios.py` 中有 2 个 `@pytest.mark.xfail(strict=True)` 测试(`test_cache_hit_logs_redis_hit` 和 `test_cache_miss_logs_redis_miss_and_mysql_read`),验证的是"Redis 缓存命中/未命中"日志输出。当前 StorageManager 未输出这些特定日志消息,因此测试被标记为预期失败。这不影响功能正确性,但建议在后续迭代中补充这些日志或移除 xfail 测试。
2. **docker-compose 默认密码**`MYSQL_PASSWORD` 默认值为 `buffer123`,仅适用于开发环境。生产部署时应通过环境变量或 secrets 管理工具设置强密码。此问题属于部署配置范畴,不影响本次 change 的验证结果。
---
## 6. 热修复记录
### 2026-07-04 时区 bug 修复
**问题**: 手动验证时发现,点击"刷新全部"后前端无数据显示。
**根因**: `storage_manager.py` 第 263 行 `datetime.fromisoformat()` 解析时间戳时保留了时区信息(`+08:00`),但第 276 行 `datetime.now()` 返回 naive datetime两者相减导致 `TypeError: can't subtract offset-naive and offset-aware datetimes`
**修复**: 在 `_merge_period_results` 中解析时间戳后去掉时区信息:
```python
timestamp_dt = datetime.fromisoformat(timestamp_raw)
if timestamp_dt.tzinfo is not None:
timestamp_dt = timestamp_dt.replace(tzinfo=None)
```
**提交**: `98567a3` - fix: 修复时区不匹配导致行情数据读取失败
**验证**: 修复后手动验证通过MySQL 190 条记录、Redis 190 个键正常读写。
---
## 7. 最终评估
**通过 ✅**
storage-cache-refactor change 的实现完整覆盖了所有 OpenSpec 产物中定义的需求:
- **完整性**20/20 任务完成14/14 需求有对应实现代码
- **正确性**8 个测试文件覆盖全部 spec scenario包括 Redis 缓存命中/未命中、三级降级、双写一致性、迁移完整性、惰性恢复检测
- **一致性**:实现严格遵循 Design Doc 中的架构决策,三级降级策略正确,双写顺序正确(先删 Redis → 写 MySQL → 回填 RedisAPI 层零改动已确认
- **安全性**无硬编码密钥MySQL 密码已 URL 编码,无 unsafe 操作
建议归档此 change。

@ -1,196 +0,0 @@
---
comet_change: analysis-storage-refactor
role: technical-design
canonical_spec: openspec
archived-with: 2026-07-04-analysis-storage-refactor
status: final
---
# Analysis Storage Refactor - Technical Design
## 1. 架构概览
### 1.1 目标架构
```
┌─────────────────────────────────────────────────────────────┐
│ 应用层 │
│ app/api/futures_analysis.py ←→ app/services/cache.py │
│ ↓ │
│ StorageManager │
│ (storage_manager.py) │
└─────────────────────────────────────────────────────────────┘
┌─────────────────────┼─────────────────────┐
↓ ↓ ↓
┌─────────┐ ┌─────────┐ ┌─────────┐
│ Redis │ │ MySQL │ │ SQLite │
│ (缓存) │ │(持久化) │ │ (兜底) │
└─────────┘ └─────────┘ └─────────┘
```
### 1.2 核心组件
| 组件 | 职责 |
|------|------|
| `StorageManager` | 提供通用 Redis 缓存方法(`cache_get`、`cache_set`、`cache_delete` |
| `analysis_db.py` | Analysis 数据库连接管理,根据后端可用性返回 MySQL 或 SQLite Session |
| `analysis_models.py` | ORM 模型定义(不变) |
| `analysis_migration.py` | SQLite → MySQL 数据迁移 |
### 1.3 表清单
| 表名 | 用途 | 缓存 TTL |
|------|------|----------|
| `futures_analysis` | 期货分析报告 | 5 分钟 |
| `watched_symbols` | 用户关注品种 | 10 分钟 |
| `ai_model_configs` | AI 模型配置 | 10 分钟 |
| `analysis_settings` | 分析设置 | 10 分钟 |
| `ai_analysis_cache` | AI 分析缓存 | 5 分钟 |
| `review_dates` | 复盘日期 | 1 小时 |
| `symbol_rankings` | 品种排名 | 1 小时 |
| `trading_plans` | 交易计划 | 1 小时 |
| `symbol_scores_v2` | V2 品种评分 | 1 小时 |
| `trading_plans_v2` | V2 交易计划 | 1 小时 |
| `sector_heat` | 板块热度 | 1 小时 |
| `review_plans_v2` | V2 复盘计划 | 1 小时 |
| `trade_records` | 交易记录 | 不缓存 |
| `trade_import_batches` | 交易导入批次 | 不缓存 |
## 2. 降级策略
### 2.1 数据库 Session 切换
`analysis_db.py` 中的 `get_analysis_db()` 根据后端可用性返回不同 Session
```
业务代码 → get_analysis_db()
MySQL 可用?
↓ 是 ↓ 否
MySQL Session SQLite Session
```
### 2.2 Redis 缓存层(可选)
对于高频读取场景,业务代码可通过 `StorageManager.cache_get/cache_set/cache_delete` 使用 Redis
```
读取请求
StorageManager.cache_get(key)
↓ 命中
返回数据
↓ 未命中
ORM 查询 MySQL/SQLite → StorageManager.cache_set(key, value) → 返回
```
### 2.3 降级状态检测
- 复用 `StorageManager.check_mysql()` 惰性检测 MySQL 可用性
- MySQL 不可用时,`get_analysis_db()` 返回 SQLite Session
- 保留 SQLite 文件 `data/futures_analysis.db` 作为兜底
## 3. 数据迁移
### 3.1 迁移时机
应用启动时(`lifespan`),在 MySQL 表结构初始化后执行。
### 3.2 迁移逻辑
```python
def migrate_analysis_sqlite_to_mysql():
"""将 SQLite analysis 数据迁移到 MySQL"""
# 1. 检测 MySQL 表是否已有数据
mysql_count = count_mysql_analysis_tables()
if mysql_count > 0:
logger.info("MySQL analysis 表已有数据,跳过迁移")
return
# 2. 从 SQLite 读取数据
sqlite_data = read_sqlite_analysis_data()
# 3. 批量写入 MySQL
write_mysql_analysis_data(sqlite_data)
logger.info("Analysis 数据迁移完成")
```
### 3.3 幂等性
- 检测 MySQL 表是否已有数据
- 有数据则跳过迁移
- 迁移失败不影响应用启动
## 4. 缓存策略
### 4.1 通用缓存方法
`StorageManager` 提供三个通用方法:
- `cache_get(key)`: 读取 Redis 缓存
- `cache_set(key, value, ttl)`: 写入 Redis 缓存
- `cache_delete(key)`: 删除 Redis 缓存
### 4.2 缓存键设计
由业务代码决定缓存键,推荐格式:
```
analysis:{table_name}:{id}
analysis:{table_name}:list:{query_hash}
```
### 4.3 缓存失效
- 写入时删除相关缓存
- TTL 过期自动失效
### 4.4 缓存回填
- 读取时未命中,查询 MySQL/SQLite 后回填
- TTL 与表类型对应
## 5. 兼容性
### 5.1 ORM 模型
- 保持不变
- 使用 `AnalysisBase` 作为基类
### 5.2 API 接口
- 保持不变
- 通过 `get_analysis_db()` 依赖注入
### 5.3 SQLite 文件
- 保留 `data/futures_analysis.db`
- 降级时使用
## 6. 测试策略
### 6.1 单元测试
| 场景 | 测试方法 |
|------|----------|
| Redis 缓存命中 | Mock Redis验证不查询 MySQL |
| Redis 缓存未命中 | Mock Redis 返回 None验证查询 MySQL |
| MySQL 降级到 SQLite | Mock MySQL 不可用,验证查询 SQLite |
| 数据迁移 | 验证 SQLite 数据完整迁移到 MySQL |
### 6.2 集成测试
- 启动应用,验证 MySQL 表创建
- 执行迁移,验证数据完整性
- 调用 API验证功能正常
## 7. 风险与缓解
| 风险 | 缓解措施 |
|------|----------|
| 数据迁移失败 | 保留 SQLite 作为降级方案,迁移失败时自动降级 |
| Redis 缓存不一致 | 写入时先删缓存,再写 MySQL最后回填缓存 |
| 表结构不兼容 | 复用现有 ORM 模型MySQL 自动创建表结构 |
| 性能下降 | Redis 缓存减少 MySQL 查询压力 |

@ -1,189 +0,0 @@
---
comet_change: config-to-mysql
role: technical-design
canonical_spec: openspec
archived-with: config-to-mysql
status: final
---
# Config to MySQL - Technical Design
## 1. 架构概览
### 1.1 目标架构
```
业务代码 / API
app/config_store.py (统一入口)
MySQL 可用?
↓ 是 ↓ 否
读/写 app_config 读/写 JSON 文件
```
### 1.2 核心组件
| 组件 | 职责 |
|------|------|
| `AppConfig` 模型 | MySQL 配置表 ORM 映射 |
| `ConfigStore` | 统一配置读写入口,封装降级逻辑 |
| `config_migration.py` | JSON → MySQL 一次性迁移 |
| JSON 文件 | MySQL 不可用时降级使用 |
## 2. 数据模型
### 2.1 AppConfig 表
```python
class AppConfig(Base):
__tablename__ = "app_config"
id = Column(Integer, primary_key=True, autoincrement=True)
config_key = Column(String(64), unique=True, nullable=False, index=True)
config_value = Column(JSON, nullable=False)
updated_at = Column(DateTime, default=datetime.utcnow, onupdate=datetime.utcnow)
created_at = Column(DateTime, default=datetime.utcnow)
```
### 2.2 配置键
| config_key | 对应文件 | 默认值 |
|------------|----------|--------|
| `symbols` | `config/symbols_config.json` | `{"futures": {}, "stock": {}}` |
| `ai` | `config/ai_config.json` | `{"models": [], "active_model": None, "analysis_settings": {...}}` |
## 3. 降级策略
### 3.1 读取流程
1. 检查 MySQL 可用性(复用 `StorageManager.check_mysql()`
2. MySQL 可用:
- 查询 `app_config`
- 命中则返回
- 未命中则读取 JSON 文件并回填数据库
3. MySQL 不可用:
- 直接读取 JSON 文件
### 3.2 写入流程
1. 检查 MySQL 可用性
2. MySQL 可用时先写入 `app_config`;失败时保留 JSON 旧值并返回 False
3. MySQL 写入成功后,再原子写入 JSON 文件
4. MySQL 不可用时只写入 JSON 文件
### 3.3 降级检测
复用 `StorageManager.check_mysql()` 惰性检测,避免每次配置读写都尝试连接数据库。
## 4. ConfigStore 接口
```python
class ConfigStore:
def get_config(self, key: str, fallback: Optional[dict] = None) -> dict: ...
def set_config(self, key: str, value: dict) -> bool: ...
def load_from_json(self, key: str, fallback: Optional[dict] = None) -> dict: ...
def save_to_json(self, key: str, value: dict) -> None: ...
```
### 4.1 单例获取
```python
_config_store = None
def get_config_store() -> ConfigStore:
global _config_store
if _config_store is None:
_config_store = ConfigStore()
return _config_store
```
## 5. 数据迁移
### 5.1 迁移时机
应用启动时(`lifespan`),在 MySQL 表结构初始化后执行。
### 5.2 迁移逻辑
```python
def migrate_configs_to_mysql():
for key, file_path, default in CONFIGS:
if _config_exists_in_mysql(key):
continue
value = _load_json(file_path, default)
_save_to_mysql(key, value)
```
### 5.3 幂等性
- 检测 `app_config` 是否已有对应 key
- 有则跳过
## 6. 使用方修改
### 6.1 品种配置读取
替换以下文件中的 `_load_symbols_config()` / `load_symbols_config()`
- `app/api/config.py`
- `app/api/futures_analysis.py`
- `app/api/trade_review.py`
- `app/services/trade_parser.py`
- `app/services/plan_generator.py`
统一使用:
```python
from app.config_store import get_config_store
symbols = get_config_store().get_config("symbols", {"futures": {}, "stock": {}})
```
### 6.2 AI 配置读取
替换 `app/api/ai_config.py``app/services/ai_analysis.py` 中的 `_load_ai_config()`
```python
ai_config = get_config_store().get_config("ai", {...default...})
```
### 6.3 写入接口
`app/api/config.py``app/api/ai_config.py` 的保存接口改为:
```python
get_config_store().set_config("symbols", data)
```
## 7. 兼容性
- 保持 JSON 文件路径和 schema 不变
- API 接口签名不变
- 默认值与现有 JSON 默认值一致
## 8. 测试策略
### 8.1 单元测试
| 场景 | 测试 |
|------|------|
| MySQL 命中 | `get_config` 从数据库返回值 |
| MySQL 未命中 | `get_config` 读取 JSON 并回填 |
| MySQL 不可用 | `get_config` 读取 JSON |
| 写入 | `set_config` 双写数据库和文件 |
| 迁移幂等 | 数据库已有数据时跳过 |
### 8.2 集成测试
- 启动应用验证配置表创建
- 验证 API 读写正常
- 运行全部测试套件确保无回归
## 9. 风险与缓解
| 风险 | 缓解措施 |
|------|----------|
| MySQL 不可用时配置无法写入数据库 | 始终同步写入 JSON 文件 |
| 多处修改引入回归 | 统一 `ConfigStore` 接口 + 全面测试 |
| JSON 文件与数据库不一致 | 写入时双写;读取时优先数据库 |

@ -1,369 +0,0 @@
---
comet_change: storage-cache-refactor
role: technical-design
canonical_spec: openspec
archived-with: 2026-07-04-storage-cache-refactor
status: final
---
# Storage Cache Refactor - Technical Design
## 1. 架构概览
### 1.1 目标架构
```
┌─────────────────────────────────────────────────────────────┐
│ 应用层 │
│ app/api/data.py ←→ app/services/cache.py │
│ ↓ │
│ StorageManager │
│ (storage_manager.py) │
└─────────────────────────────────────────────────────────────┘
┌─────────────────────┼─────────────────────┐
↓ ↓ ↓
┌─────────┐ ┌─────────┐ ┌─────────┐
│ Redis │ │ MySQL │ │ SQLite │
│ (缓存) │ │(持久化) │ │ (兜底) │
└─────────┘ └─────────┘ └─────────┘
```
### 1.2 核心组件
| 组件 | 文件 | 职责 |
|------|------|------|
| StorageManager | `app/storage_manager.py` | 封装三级存储逻辑,提供统一接口 |
| RedisClient | `app/redis_client.py` | Redis 连接池和客户端封装 |
| MySQLDatabase | `app/mysql_database.py` | MySQL 引擎和 SessionLocal |
| cache.py | `app/services/cache.py` | 保持现有函数签名,内部调用 StorageManager |
## 2. Redis 数据结构
### 2.1 行情数据缓存
```
Key: market_data:{symbol}:{period}
Value: JSON {
"current_price": 123.45,
"timestamp": "2026-07-04T10:00:00",
"candles": [
{"datetime": "...", "open": ..., "high": ..., "low": ..., "close": ...}
]
}
TTL: 30 天 (2592000 秒)
```
### 2.2 合约时间戳缓存
```
Key: symbol_timestamps:{symbol}
Value: JSON {
"last_refresh_at": "2026-07-04T10:00:00",
"refresh_count": 42
}
TTL: 30 天 (2592000 秒)
```
### 2.3 设计理由
- 结构化键值存储,便于按品种和周期精确查询
- JSON 格式与当前 SQLite 存储格式兼容,迁移成本低
- TTL 自动清理,避免内存无限增长
## 3. 数据流设计
### 3.1 读取流程
```
请求行情数据
检查 Redis 缓存
├─ 命中 → 返回数据
└─ 未命中 → 检查 MySQL 可用性
├─ 可用 → 读取 MySQL → 回填 Redis (TTL 30天) → 返回
└─ 不可用 → 读取 SQLite → 返回
```
### 3.2 写入流程(刷新接口)
```
刷新行情数据
删除 Redis 缓存 (market_data:{symbol}:{period})
写入 MySQL事务
├─ 成功 → 更新 Redis 缓存 → 返回成功
└─ 失败 → 返回错误(不更新 Redis
```
### 3.3 降级流程
```
StorageManager 检查存储后端可用性
Redis 可用?
├─ 是 → 使用 Redis 缓存
└─ 否 → MySQL 可用?
├─ 是 → 使用 MySQL 持久化
└─ 否 → 使用 SQLite 兜底
```
## 4. 降级检测机制
### 4.1 惰性恢复策略
```python
class StorageManager:
def __init__(self):
self.redis_available = False
self.mysql_available = False
self.last_redis_check = 0
self.last_mysql_check = 0
self.check_interval = 30 # 秒
def check_redis(self):
"""检查 Redis 可用性30秒内不重复检测"""
now = time.time()
if now - self.last_redis_check < self.check_interval:
return self.redis_available
try:
self.redis_client.ping()
self.redis_available = True
logger.info("Redis 连接恢复")
except Exception as e:
self.redis_available = False
logger.warning(f"Redis 不可用: {e}")
self.last_redis_check = now
return self.redis_available
def check_mysql(self):
"""检查 MySQL 可用性30秒内不重复检测"""
now = time.time()
if now - self.last_mysql_check < self.check_interval:
return self.mysql_available
try:
with self.mysql_engine.connect() as conn:
conn.execute(text("SELECT 1"))
self.mysql_available = True
logger.info("MySQL 连接恢复")
except Exception as e:
self.mysql_available = False
logger.warning(f"MySQL 不可用: {e}")
self.last_mysql_check = now
return self.mysql_available
```
### 4.2 启动时初始化
```python
# app/main.py lifespan
storage_manager = StorageManager()
storage_manager.initialize()
# 检测可用性
redis_ok = storage_manager.check_redis()
mysql_ok = storage_manager.check_mysql()
if redis_ok and mysql_ok:
logger.info("存储模式: Redis + MySQL")
elif mysql_ok:
logger.warning("存储模式: MySQL (Redis 不可用)")
else:
logger.error("存储模式: SQLite (Redis 和 MySQL 均不可用)")
```
## 5. 集成方式
### 5.1 cache.py 内部封装
```python
# app/services/cache.py
def get_cached_data(db, symbol, data_type, periods, end_time=None, max_candles=100):
"""从缓存中获取完整的多周期数据"""
storage = get_storage_manager()
# 优先从 Redis/MySQL 读取
if storage.is_available():
try:
result = storage.get_market_data(symbol, data_type, periods)
if result:
return result
except Exception as e:
logger.warning(f"StorageManager 读取失败,降级到 SQLite: {e}")
# 降级到 SQLite
return _get_from_sqlite(db, symbol, data_type, periods, end_time, max_candles)
def save_market_data(db, symbol, data):
"""保存采集结果到缓存"""
storage = get_storage_manager()
# 优先写入 Redis/MySQL
if storage.is_available():
try:
storage.save_market_data(symbol, data)
return
except Exception as e:
logger.warning(f"StorageManager 写入失败,降级到 SQLite: {e}")
# 降级到 SQLite
_save_to_sqlite(db, symbol, data)
```
### 5.2 API 层零改动
- `app/api/data.py` 保持不变
- 所有接口仍使用 `db: Session = Depends(get_db)`
- cache.py 内部自动选择存储后端
## 6. 数据迁移
### 6.1 迁移策略
```python
# app/migration.py
def migrate_sqlite_to_mysql():
"""从 SQLite 迁移历史数据到 MySQL"""
sqlite_engine = create_engine(f"sqlite:///{DB_PATH}")
mysql_engine = create_mysql_engine()
# 检查 MySQL 表是否为空
with mysql_engine.connect() as conn:
result = conn.execute(text("SELECT COUNT(*) FROM market_data"))
count = result.scalar()
if count > 0:
logger.info("MySQL 已有数据,跳过迁移")
return
# 从 SQLite 读取数据
with sqlite_engine.connect() as conn:
result = conn.execute(text("SELECT * FROM market_data"))
rows = result.fetchall()
# 写入 MySQL
with mysql_engine.begin() as conn:
for row in rows:
conn.execute(
text("INSERT INTO market_data ..."),
{...}
)
logger.info(f"数据迁移完成,共迁移 {len(rows)} 条记录")
```
### 6.2 迁移触发时机
- 应用启动时自动检测
- MySQL 表为空时触发迁移
- 迁移完成后输出日志
## 7. 配置项
### 7.1 新增配置
```python
# app/config.py
# Redis 配置
REDIS_HOST = os.getenv("REDIS_HOST", "localhost")
REDIS_PORT = int(os.getenv("REDIS_PORT", "6379"))
REDIS_DB = int(os.getenv("REDIS_DB", "0"))
REDIS_PASSWORD = os.getenv("REDIS_PASSWORD", "")
REDIS_TTL_SECONDS = int(os.getenv("REDIS_TTL_SECONDS", "2592000")) # 30 天
# MySQL 配置
MYSQL_HOST = os.getenv("MYSQL_HOST", "localhost")
MYSQL_PORT = int(os.getenv("MYSQL_PORT", "3306"))
MYSQL_USER = os.getenv("MYSQL_USER", "root")
MYSQL_PASSWORD = os.getenv("MYSQL_PASSWORD", "")
MYSQL_DATABASE = os.getenv("MYSQL_DATABASE", "buffer_platform")
```
### 7.2 docker-compose.yml 新增服务
```yaml
services:
redis:
image: redis:7-alpine
ports:
- "6379:6379"
volumes:
- redis-data:/data
mysql:
image: mysql:8.0
environment:
MYSQL_ROOT_PASSWORD: ${MYSQL_PASSWORD}
MYSQL_DATABASE: ${MYSQL_DATABASE}
ports:
- "3306:3306"
volumes:
- mysql-data:/var/lib/mysql
```
## 8. 测试策略
### 8.1 单元测试
- StorageManager 各方法独立测试
- Redis 缓存命中/未命中场景
- MySQL 读写场景
- 降级逻辑场景
### 8.2 集成测试
- Redis + MySQL 正常模式
- Redis 不可用降级到 MySQL
- Redis + MySQL 均不可用降级到 SQLite
- 刷新接口双写一致性
### 8.3 故障注入
- 模拟 Redis 服务停止
- 模拟 MySQL 服务停止
- 验证降级和恢复逻辑
### 8.4 性能测试
- 对比改造前后读取延迟
- 验证 Redis 缓存命中率
- 监控 MySQL 查询性能
## 9. 风险与缓解
| 风险 | 影响 | 缓解措施 |
|------|------|---------|
| Redis 内存占用过高 | 系统内存不足 | TTL 30 天自动清理,监控内存使用 |
| 双写一致性 | MySQL 成功但 Redis 失败 | Redis 失败仅记录日志,不影响持久化 |
| 降级检测延迟 | 恢复不及时 | 30 秒惰性恢复阈值,平衡性能和实时性 |
| 数据迁移失败 | 历史数据丢失 | 保留 SQLite 兜底,可手动回滚 |
| MySQL 部署复杂度 | 运维成本增加 | docker-compose 一键部署 |
## 10. 实施计划
### 10.1 阶段划分
1. **依赖与配置**: 添加 redis、pymysql 依赖,新增配置项
2. **数据库模型**: 创建 Redis/MySQL 连接模块
3. **StorageManager**: 实现三级存储逻辑
4. **集成改造**: 改造 cache.py集成 StorageManager
5. **数据迁移**: 实现 SQLite → MySQL 迁移
6. **测试验证**: 单元测试、集成测试、故障注入
### 10.2 验收标准
- Redis 缓存命中时,读取延迟 < 10ms
- Redis 未命中时,从 MySQL 读取并回填
- Redis 不可用时,自动降级到 MySQL
- Redis + MySQL 均不可用时,降级到 SQLite
- 刷新接口双写成功,数据一致性保证
- 数据迁移完整,历史数据不丢失

@ -1,24 +0,0 @@
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isolation: branch
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base_ref: 82de2f9
design_doc: docs/superpowers/specs/2026-07-04-analysis-storage-refactor-design.md
plan: docs/superpowers/plans/2026-07-04-analysis-storage-refactor.md
verify_result: pass
verification_report: docs/superpowers/reports/2026-07-04-analysis-storage-refactor-verify.md
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verified_at: 2026-07-04
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handoff_context: null
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build_command: python -m pytest tests/ -v
verify_command: python -m pytest tests/ -v

@ -1,42 +0,0 @@
# Brainstorm Summary
- Change: analysis-storage-refactor
- Date: 2026-07-04
## 确认的技术方案
`futures_analysis.db`14 张表)迁移到 MySQL `buffer_platform` 数据库,并引入 Redis 缓存层与行情数据存储策略保持一致Redis→MySQL→SQLite 三级降级)。
### 核心设计
1. **复用现有连接**:使用 `storage_manager.py` 中的 `mysql_engine``redis_client`
2. **扩展 StorageManager**:新增 analysis 表读写方法
3. **降级策略**Redis 缓存 → MySQL 持久化 → SQLite 兜底
4. **数据迁移**:启动时自动迁移现有 SQLite 数据到 MySQL
### 缓存策略
| 表类型 | 缓存 TTL | 说明 |
|--------|----------|------|
| AI 分析结果 | 5 分钟 | 频繁读取,短期缓存 |
| 复盘计划 | 1 小时 | 每日更新,中期缓存 |
| 交易记录 | 不缓存 | 写入后不再修改 |
| 配置表 | 10 分钟 | 低频读取 |
## 关键取舍与风险
| 取舍/风险 | 决策/缓解 |
|-----------|-----------|
| 表名前缀 | 保持原名,通过 ORM 模型区分 |
| 数据迁移失败 | 保留 SQLite 作为降级方案 |
| Redis 缓存一致性 | 写入时先删缓存,再写 MySQL最后回填 |
## 测试策略
1. 单元测试:三级降级场景
2. 集成测试:数据迁移完整性
3. 功能测试现有功能AI 分析、复盘计划、交易记录)正常工作
## Spec Patch
无(复用已有 delta spec 结构)

@ -1,3 +0,0 @@
name: analysis-storage-refactor
created: 2026-07-04
status: active

@ -1,88 +0,0 @@
# Design: Analysis Storage Refactor
## 架构决策
### 决策 1复用现有连接
**决策**:复用 `storage_manager.py` 中的 `mysql_engine``redis_client`,不创建新的连接。
**理由**
- 避免重复创建连接池
- 保持配置一致性
- 简化降级逻辑
### 决策 2扩展 StorageManager
**决策**:在 `StorageManager` 中新增 analysis 表读写方法,与行情数据共用同一套降级逻辑。
**理由**
- 统一降级策略
- 减少代码重复
- 便于维护
### 决策 3表名前缀
**决策**analysis 表在 MySQL 中保持原名,不添加前缀。
**理由**
- 表名已通过 ORM 模型定义
- 避免与行情数据表冲突(行情表:`market_data`, `symbol_timestamps`, `scheduled_tasks`
## 数据流
```
┌─────────────────────────────────────────────────────────────┐
│ 应用层 │
│ app/api/futures_analysis.py ←→ app/services/cache.py │
│ ↓ │
│ StorageManager │
│ (storage_manager.py) │
└─────────────────────────────────────────────────────────────┘
┌─────────────────────┼─────────────────────┐
↓ ↓ ↓
┌─────────┐ ┌─────────┐ ┌─────────┐
│ Redis │ │ MySQL │ │ SQLite │
│ (缓存) │ │(持久化) │ │ (兜底) │
└─────────┘ └─────────┘ └─────────┘
```
## 降级策略
### 读取流程
1. 检查 Redis 缓存,命中则返回
2. Redis 未命中,检查 MySQL 可用性
3. MySQL 可用则查询,结果回填 Redis
4. MySQL 不可用,降级到 SQLite
### 写入流程
1. 删除 Redis 缓存
2. 写入 MySQL事务
3. MySQL 成功后回填 Redis
4. MySQL 失败则写入 SQLite
## 数据迁移
启动时执行一次性迁移:
1. 检测 MySQL analysis 表是否为空
2. 为空则从 SQLite 读取全部数据
3. 批量写入 MySQL
4. 迁移完成后记录日志
## 缓存策略
| 表类型 | 缓存 TTL | 说明 |
|--------|----------|------|
| AI 分析结果 | 5 分钟 | 频繁读取,短期缓存 |
| 复盘计划 | 1 小时 | 每日更新,中期缓存 |
| 交易记录 | 不缓存 | 写入后不再修改 |
| 配置表 | 10 分钟 | 低频读取 |
## 兼容性
- ORM 模型定义不变
- API 接口签名不变
- SQLite 文件保留,降级时使用

@ -1,51 +0,0 @@
# Proposal: Analysis Storage Refactor
## 问题背景
当前 `futures_analysis.db` 是独立的 SQLite 数据库,存储 14 张表AI 分析、复盘计划、交易记录等)。与行情数据(已迁移到 MySQL/Redis分离存储存在以下问题
1. **数据孤岛**:分析数据与行情数据分离,无法统一管理和备份
2. **扩展性差**SQLite 不适合高并发读写场景
3. **架构不一致**:行情数据已采用 Redis→MySQL→SQLite 三级降级策略,分析数据仍使用单一 SQLite
## 目标
`futures_analysis.db` 的 14 张表迁移到 MySQL `buffer_platform` 数据库,并引入 Redis 缓存层,与行情数据存储策略保持一致。
## 范围
### 包含
- 复用现有 MySQL 连接(`mysql_engine`)和 Redis 连接(`redis_client`
- 实现三级降级Redis 缓存 → MySQL 持久化 → SQLite 兜底
- 启动时自动迁移现有 SQLite 数据到 MySQL
- 保持 ORM 模型定义不变
- 保持 API 接口不变
### 不包含
- 行情数据存储(已完成)
- 前端代码修改
- 新增业务功能
## 非目标
- 不改变现有 ORM 模型定义
- 不改变 API 接口签名
- 不引入新的业务逻辑
## 验收标准
1. 启动时检测 MySQL/Redis 可用,自动创建 analysis 表并迁移数据
2. API 读写 analysis 表时优先使用 Redis 缓存,未命中回源 MySQL
3. MySQL 不可用时降级到 SQLite
4. 现有功能AI 分析、复盘计划、交易记录)正常工作
5. 单元测试覆盖三级降级场景
## 风险
| 风险 | 缓解措施 |
|------|----------|
| 数据迁移失败 | 保留 SQLite 作为降级方案,迁移失败时自动降级 |
| Redis 缓存一致性 | 写入时先删缓存,再写 MySQL最后回填缓存 |
| 表结构不兼容 | 复用现有 ORM 模型MySQL 自动创建表结构 |

@ -1,32 +0,0 @@
# Tasks: Analysis Storage Refactor
## 1. StorageManager 扩展
- [x] 1.1 在 `StorageManager` 中新增 `cache_get()` 通用缓存读取方法
- [x] 1.2 在 `StorageManager` 中新增 `cache_set()` 通用缓存写入方法
- [x] 1.3 在 `StorageManager` 中新增 `cache_delete()` 通用缓存删除方法
## 2. 数据迁移
- [x] 2.1 创建 `app/analysis_migration.py`,实现 SQLite → MySQL 迁移逻辑
- [x] 2.2 在 `app/main.py``lifespan` 中调用迁移函数,启动时自动迁移
- [x] 2.3 迁移幂等性:检测 MySQL 表是否已有数据,有则跳过
## 3. 降级逻辑集成
- [x] 3.1 修改 `app/analysis_db.py``get_analysis_db()` 根据 MySQL 可用性返回 Session
- [x] 3.2 实现 MySQL 不可用时降级到 SQLite 的逻辑
- [x] 3.3 保留 Redis 缓存能力(通过 StorageManager 通用缓存方法)
## 4. 表结构初始化
- [x] 4.1 在 `app/main.py``lifespan` 中创建 analysis 表MySQL
- [x] 4.2 验证 14 张表在 MySQL 中正确创建
## 5. 测试与验证
- [x] 5.1 验证 Redis 缓存命中场景
- [x] 5.2 验证 Redis 缓存未命中回源 MySQL 场景
- [x] 5.3 验证 MySQL 不可用降级到 SQLite 场景
- [x] 5.4 验证数据迁移完整性
- [x] 5.5 验证现有测试套件全部通过101 passed, 2 xfailed

@ -1,24 +0,0 @@
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verification_report: docs/superpowers/reports/2026-07-04-storage-cache-refactor-verify.md
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verify_command: python -m pytest tests/ -v

@ -1,46 +0,0 @@
# Brainstorm Summary
- Change: storage-cache-refactor
- Date: 2026-07-04
## 确认的技术方案
1. **Redis 数据结构**: 方案 C — 结构化键值存储
- `market_data:{symbol}:{period}` → JSON含 current_price, timestamp, candles
- `symbol_timestamps:{symbol}` → JSON含 last_refresh_at, refresh_count
- TTL: 30 天
2. **集成方式**: 方案 B — cache.py 内部封装
- cache.py 函数签名不变(仍接收 `db: Session`
- 函数内部判断:优先走 Redis/MySQL降级时走原有 SQLite 逻辑
- API 层零改动,渐进式迁移
3. **降级检测**: 方案 C — 惰性恢复
- 启动时检测 Redis/MySQL 可用性
- 运行时捕获异常标记不可用
- 下次请求时距上次检测超 30 秒则尝试重连
- 重连成功恢复,失败继续降级
4. **MySQL 驱动**: pymysql纯 PythonWindows 零障碍部署)
5. **双写策略**: 同步双写,先写 MySQL 再更新 Redis
- 写入流程:删 Redis 缓存 → 写 MySQL → 更新 Redis
- MySQL 失败回滚Redis 失败仅记录日志
## 关键取舍与风险
- Redis 内存占用 → TTL 30 天自动清理
- 双写一致性 → MySQL 优先Redis 失败不影响持久化
- 降级检测延迟 → 30 秒惰性恢复阈值
- 数据迁移 → 启动时自动从 SQLite 迁移到 MySQL保留 SQLite 兜底
## 测试策略
- 单元测试StorageManager 各方法
- 集成测试:三级降级场景
- 故障注入:模拟 Redis/MySQL 不可用
- 性能对比:改造前后读取延迟
## Spec Patch
无(现有 delta spec 已覆盖所有验收场景)

@ -1,17 +0,0 @@
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@ -1,387 +0,0 @@
# Comet Design Handoff
- Change: storage-cache-refactor
- Phase: design
- Mode: compact
- Context hash: 1064fdf5186e511848878541bdad663ac6b521ee5721807d01eaf3481bb0cd5a
Generated-by: comet-handoff.sh
OpenSpec remains the canonical capability spec. This handoff is a deterministic, source-traceable context pack, not an agent-authored summary.
## openspec/changes/storage-cache-refactor/proposal.md
- Source: openspec/changes/storage-cache-refactor/proposal.md
- Lines: 1-33
- SHA256: 759de20d4e94b3228ee94d8607740de2949c24935933884584b85d3d855569ad
```md
## Why
当前系统使用 SQLite 作为唯一存储后端,无法满足行情数据高频读写的性能需求。每次刷新行情数据都需要直接读写磁盘文件,导致响应延迟高、并发能力受限。需要引入更高效的存储方案以提升系统吞吐量和用户体验。
## What Changes
- 引入 Redis 作为热数据缓存层,行情数据优先从 Redis 读取TTL 30 天)
- 引入 MySQL 作为持久化存储层,替代 SQLite 承担主要持久化职责
- 保留 SQLite 作为最终兜底方案,当 Redis 和 MySQL 均不可用时启用
- 新增数据访问层:实现 Redis → MySQL → SQLite 的三级降级读取策略
- 刷新接口改造:数据同步写入 Redis 和 MySQL保证双写一致性
- 启动流程改造:初始化 Redis/MySQL/SQLite 连接,检测可用性
## Capabilities
### New Capabilities
- `redis-cache-layer`: Redis 缓存读写能力包括热数据缓存、TTL 管理、缓存失效策略
- `mysql-persistence`: MySQL 持久化存储能力,替代 SQLite 承担主要持久化职责
- `storage-fallback`: 三级降级策略Redis → MySQL → SQLite保证系统可用性
- `dual-write-consistency`: 刷新接口双写能力,保证 Redis 和 MySQL 数据一致性
### Modified Capabilities
(无既有 spec 需要修改)
## Impact
- **代码**: `app/database.py`、`app/models.py`、`app/api/data.py`、`app/services/collector.py`、`app/main.py`
- **依赖**: 新增 `redis`、`pymysql`(或 `aiomysql`Python 包
- **配置**: `app/config.py` 新增 Redis/MySQL 连接配置
- **部署**: `docker-compose.yml` 新增 Redis 和 MySQL 服务
- **数据库**: 新增 MySQL 数据库初始化脚本,保留 SQLite 作为兜底
```
## openspec/changes/storage-cache-refactor/design.md
- Source: openspec/changes/storage-cache-refactor/design.md
- Lines: 1-121
- SHA256: 293fba52d3bef2adc55fa3d8667879fc7806918922f2f273d05efbc870c862ac
[TRUNCATED]
```md
## Context
当前系统使用 SQLite 作为唯一存储后端,所有行情数据(`MarketData`)以 JSON 字符串形式存储在磁盘文件中。每次刷新行情时,系统需要从数据源采集数据、写入 SQLite读取时再反序列化。这种架构在高频读写场景下存在性能瓶颈。
系统包含以下核心实体:
- `MarketData`: 行情 K 线数据(高频读写,数据量大)
- `SymbolTimestamp`: 合约数据时间戳(中频读写)
- `ScheduledTask`: 定时任务配置(低频读写)
- 用户认证、交易复盘等低频业务表
约束条件:
- 单机部署,需要本地运行 Redis
- 需要保证系统可用性,即使部分存储组件故障
- 现有 SQLite 数据需要迁移或兼容
## Goals / Non-Goals
**Goals:**
- 引入 Redis 作为热数据缓存层提升行情数据读取性能TTL 30 天)
- 引入 MySQL 作为主要持久化存储,替代 SQLite 承担日常读写
- 保留 SQLite 作为最终兜底方案,保证系统可用性
- 实现三级降级策略Redis → MySQL → SQLite
- 刷新接口双写:数据同步写入 Redis 和 MySQL
- 启动时初始化多存储后端,检测可用性
**Non-Goals:**
- 不迁移用户认证、交易复盘等低频业务表(保持 SQLite
- 不改造前端页面
- 不统一 API 接口规范(留给后续 change
- 不实现分布式部署或集群方案
## Decisions
### 1. 存储分层策略
**决策**: 采用 Redis缓存+ MySQL持久化+ SQLite兜底三级架构。
**理由**:
- Redis 提供亚毫秒级读取性能,适合行情数据高频访问
- MySQL 提供可靠的持久化能力和事务支持,替代 SQLite 成为主存储
- SQLite 保留作为最终兜底,保证极端情况下系统仍可运行
- 三级降级保证系统可用性,避免单点故障
**备选方案**:
- Redis + PostgreSQL: PostgreSQL 功能更强大但部署复杂度更高MySQL 更轻量
- 纯 Redis: 无法满足持久化需求,数据丢失风险高
- 纯 MySQL: 缺少缓存层,读取性能提升有限
### 2. 数据访问层设计
**决策**: 新增 `StorageManager` 抽象层,封装三级降级逻辑。
**理由**:
- 业务代码无需关心底层存储实现
- 降级策略集中管理,便于维护和测试
- 可通过配置切换存储后端,支持渐进式迁移
**备选方案**:
- 直接在业务代码中实现降级逻辑: 代码重复,难以维护
- 使用 ORM 插件: 灵活性不足,难以实现复杂的降级策略
### 3. 双写一致性策略
**决策**: 刷新接口采用同步双写,先写 MySQL 再更新 Redis。
**理由**:
- MySQL 作为持久化主存储,必须先保证数据落盘
- Redis 作为缓存,写入失败不影响数据持久化
- 同步双写保证数据一致性,避免异步延迟导致的数据不一致
**备选方案**:
- 异步双写: 性能更好,但可能出现数据不一致
- 仅写 MySQLRedis 通过缓存未命中回填: 首次读取性能差
### 4. Redis 缓存策略
**决策**: 行情数据 TTL 30 天,缓存未命中时从 MySQL 读取并回填。
**理由**:
- 30 天覆盖大部分行情数据的活跃访问周期
```
Full source: openspec/changes/storage-cache-refactor/design.md
## openspec/changes/storage-cache-refactor/tasks.md
- Source: openspec/changes/storage-cache-refactor/tasks.md
- Lines: 1-46
- SHA256: 295733c66c5b2599cac51356e7344d17c579e674e667ec24c6b77d62ee519fcd
```md
## 1. 依赖与配置
- [ ] 1.1 添加 `redis`、`pymysql` 依赖到 `requirements.txt`
- [ ] 1.2 在 `app/config.py` 中新增 Redis 和 MySQL 连接配置项host、port、user、password、database
- [ ] 1.3 在 `docker-compose.yml` 中新增 Redis 和 MySQL 服务定义
## 2. 数据库模型与初始化
- [ ] 2.1 创建 `app/mysql_database.py`,实现 MySQL 连接引擎和 SessionLocal
- [ ] 2.2 创建 `app/redis_client.py`,实现 Redis 连接池和客户端封装
- [ ] 2.3 在 `app/main.py``lifespan` 中初始化 Redis 和 MySQL 连接,检测可用性
- [ ] 2.4 创建 MySQL 表结构初始化脚本(复用现有 ORM 模型)
## 3. 数据迁移
- [ ] 3.1 创建数据迁移脚本,从 SQLite 读取历史数据并写入 MySQL
- [ ] 3.2 在应用启动时检测 MySQL 表是否为空,自动触发迁移
## 4. 存储管理层
- [ ] 4.1 创建 `app/storage_manager.py`,实现 `StorageManager` 抽象层
- [ ] 4.2 实现 Redis 缓存读取逻辑(命中返回,未命中回源 MySQL 并回填)
- [ ] 4.3 实现 MySQL 持久化读写逻辑
- [ ] 4.4 实现三级降级策略Redis → MySQL → SQLite
- [ ] 4.5 实现降级状态检测和恢复机制
## 5. 双写与缓存一致性
- [ ] 5.1 实现刷新接口双写逻辑:先删 Redis 缓存,再写 MySQL最后更新 Redis
- [ ] 5.2 实现双写顺序保证和错误处理MySQL 失败回滚Redis 失败记录日志)
- [ ] 5.3 实现缓存未命中回填逻辑TTL 30 天)
## 6. 接口改造
- [ ] 6.1 改造 `app/api/data.py` 中的行情数据读取接口,使用 `StorageManager`
- [ ] 6.2 改造 `app/api/data.py` 中的刷新接口,使用双写逻辑
- [ ] 6.3 改造 `app/services/collector.py`,使用 `StorageManager` 写入数据
## 7. 测试与验证
- [ ] 7.1 验证 Redis 缓存命中场景
- [ ] 7.2 验证 Redis 缓存未命中回源 MySQL 场景
- [ ] 7.3 验证 Redis 不可用降级到 MySQL 场景
- [ ] 7.4 验证 Redis 和 MySQL 均不可用降级到 SQLite 场景
- [ ] 7.5 验证刷新接口双写一致性
- [ ] 7.6 验证数据迁移完整性
```
## openspec/changes/storage-cache-refactor/specs/dual-write-consistency/spec.md
- Source: openspec/changes/storage-cache-refactor/specs/dual-write-consistency/spec.md
- Lines: 1-30
- SHA256: 6fd0c00433c73329adc93f97ea5a8b744d9a74148d7db40f30c843e92480b91e
```md
## ADDED Requirements
### Requirement: 刷新接口双写
系统应当在刷新接口中实现 Redis 和 MySQL 的同步双写,保证数据一致性。
#### Scenario: 刷新接口双写成功
- **WHEN** 用户调用刷新接口更新行情数据
- **THEN** 系统先删除 Redis 缓存,再写入 MySQL最后更新 Redis 缓存
#### Scenario: MySQL 写入失败
- **WHEN** 刷新接口写入 MySQL 失败
- **THEN** 系统返回错误响应,不更新 Redis 缓存,保证数据一致性
#### Scenario: Redis 写入失败
- **WHEN** 刷新接口写入 MySQL 成功但 Redis 写入失败
- **THEN** 系统返回成功响应MySQL 数据已持久化),输出 Redis 写入失败警告日志
### Requirement: 双写顺序保证
系统应当保证双写的顺序:先写 MySQL再更新 Redis。
#### Scenario: 双写顺序
- **WHEN** 刷新接口执行双写
- **THEN** 系统先写入 MySQL 并确认成功,再更新 Redis 缓存
### Requirement: 缓存回填一致性
系统应当在缓存未命中回填时保证回填数据与 MySQL 数据一致。
#### Scenario: 缓存未命中回填
- **WHEN** Redis 缓存未命中且从 MySQL 读取数据
- **THEN** 系统将 MySQL 数据回填到 RedisTTL 设置为 30 天
```
## openspec/changes/storage-cache-refactor/specs/mysql-persistence/spec.md
- Source: openspec/changes/storage-cache-refactor/specs/mysql-persistence/spec.md
- Lines: 1-41
- SHA256: f23680f51345a871dddbf3d18eacf6a53de1a20945d02516ffc55a2eb500af75
```md
## ADDED Requirements
### Requirement: MySQL 连接管理
系统应当提供 MySQL 连接管理能力,包括连接初始化、连接池管理和表结构初始化。
#### Scenario: MySQL 连接初始化成功
- **WHEN** 应用启动且 MySQL 配置有效
- **THEN** 系统成功建立 MySQL 连接并创建必要的表结构
#### Scenario: MySQL 连接初始化失败
- **WHEN** 应用启动但 MySQL 服务不可用
- **THEN** 系统输出错误日志并标记 MySQL 为不可用状态,但不阻止应用启动
### Requirement: 行情数据持久化存储
系统应当使用 MySQL 作为行情数据的主要持久化存储,替代 SQLite。
#### Scenario: 行情数据写入 MySQL
- **WHEN** 刷新接口接收到行情数据更新请求
- **THEN** 系统将数据写入 MySQL 的 `market_data`
#### Scenario: 行情数据从 MySQL 读取
- **WHEN** Redis 缓存未命中且 MySQL 可用
- **THEN** 系统从 MySQL 读取行情数据并返回
### Requirement: MySQL 表结构迁移
系统应当提供从 SQLite 到 MySQL 的数据迁移能力,保证历史数据不丢失。
#### Scenario: 首次启动数据迁移
- **WHEN** 应用首次启动且 MySQL 可用但表为空
- **THEN** 系统从 SQLite 读取历史数据并迁移到 MySQL
#### Scenario: 迁移完成
- **WHEN** 数据迁移完成
- **THEN** 系统输出迁移成功日志,后续读写直接操作 MySQL
### Requirement: MySQL 事务支持
系统应当使用 MySQL 事务保证数据写入的原子性和一致性。
#### Scenario: 批量写入事务
- **WHEN** 刷新接口需要写入多个品种的行情数据
- **THEN** 系统使用事务保证所有数据要么全部写入成功,要么全部回滚
```
## openspec/changes/storage-cache-refactor/specs/redis-cache-layer/spec.md
- Source: openspec/changes/storage-cache-refactor/specs/redis-cache-layer/spec.md
- Lines: 1-41
- SHA256: a0b5c7023c88339957ce5576ad326474fd0ab913756c223573766cbc9e23f761
```md
## ADDED Requirements
### Requirement: Redis 缓存连接管理
系统应当提供 Redis 连接管理能力,包括连接初始化、健康检查和连接池管理。
#### Scenario: Redis 连接初始化成功
- **WHEN** 应用启动且 Redis 配置有效
- **THEN** 系统成功建立 Redis 连接并输出初始化成功日志
#### Scenario: Redis 连接初始化失败
- **WHEN** 应用启动但 Redis 服务不可用
- **THEN** 系统输出警告日志并标记 Redis 为不可用状态,但不阻止应用启动
### Requirement: 行情数据缓存读取
系统应当优先从 Redis 读取行情数据,缓存未命中时回源 MySQL。
#### Scenario: Redis 缓存命中
- **WHEN** 用户请求行情数据且 Redis 中存在该数据
- **THEN** 系统直接从 Redis 返回数据,不访问 MySQL
#### Scenario: Redis 缓存未命中
- **WHEN** 用户请求行情数据但 Redis 中不存在该数据
- **THEN** 系统从 MySQL 读取数据,回填到 RedisTTL 30 天),并返回数据
### Requirement: Redis 缓存 TTL 管理
系统应当为缓存数据设置 30 天过期时间,过期后自动清理。
#### Scenario: 缓存数据过期
- **WHEN** 缓存数据超过 30 天未访问
- **THEN** Redis 自动清理该数据,下次访问时从 MySQL 重新加载
#### Scenario: 缓存数据续期
- **WHEN** 用户访问已缓存的行情数据
- **THEN** 系统返回缓存数据TTL 保持为 30 天(不续期)
### Requirement: Redis 缓存失效
系统应当在数据更新时主动失效相关缓存,保证数据一致性。
#### Scenario: 刷新接口触发缓存失效
- **WHEN** 用户调用刷新接口更新行情数据
- **THEN** 系统先删除 Redis 中对应的缓存数据,再执行双写流程
```
## openspec/changes/storage-cache-refactor/specs/storage-fallback/spec.md
- Source: openspec/changes/storage-cache-refactor/specs/storage-fallback/spec.md
- Lines: 1-38
- SHA256: feaf531250861c109bc48d06d684ff2520cb48269397211bdcefe7cda9013714
```md
## ADDED Requirements
### Requirement: 三级降级策略
系统应当实现 Redis → MySQL → SQLite 的三级降级读取策略,保证系统可用性。
#### Scenario: 正常模式Redis + MySQL 可用)
- **WHEN** Redis 和 MySQL 均可用
- **THEN** 系统优先从 Redis 读取,未命中时回源 MySQL
#### Scenario: Redis 不可用降级
- **WHEN** Redis 服务不可用但 MySQL 可用
- **THEN** 系统直接从 MySQL 读取数据,跳过 Redis 缓存层
#### Scenario: Redis 和 MySQL 均不可用降级
- **WHEN** Redis 和 MySQL 均不可用
- **THEN** 系统降级到 SQLite从 SQLite 读取数据并保证基础服务可用
### Requirement: 降级状态检测
系统应当能够检测存储后端的可用性状态,并在降级时输出明确的日志。
#### Scenario: 启动时降级检测
- **WHEN** 应用启动时检测到 Redis 或 MySQL 不可用
- **THEN** 系统输出降级警告日志,说明当前使用的存储模式
#### Scenario: 运行时降级触发
- **WHEN** 运行中 Redis 或 MySQL 连接异常
- **THEN** 系统自动切换到降级模式,输出降级日志,并继续提供服务
### Requirement: 降级恢复
系统应当能够在存储后端恢复后自动恢复到正常模式。
#### Scenario: Redis 恢复
- **WHEN** Redis 从不可用状态恢复
- **THEN** 系统自动恢复到 Redis + MySQL 模式,后续读取优先使用 Redis
#### Scenario: MySQL 恢复
- **WHEN** MySQL 从不可用状态恢复
- **THEN** 系统自动恢复到 Redis + MySQL 模式SQLite 降级结束
```

@ -1,43 +0,0 @@
# Subagent Progress
- Change: storage-cache-refactor
- Review Mode: thorough
- TDD Mode: tdd
## Task Ledger
| # | Task | Status | Stage | Commit | Notes |
|---|------|--------|-------|--------|-------|
| T1 | 添加 redis/pymysql 依赖 | done | done | f86b096 | - |
| T2 | config.py 新增 Redis/MySQL 配置项 | done | done | 4c0bbbb | 环境变量名已统一 |
| T3 | docker-compose.yml 新增 Redis/MySQL 服务 | done | done | d6e17f5 | - |
| T4 | 创建 app/mysql_database.py | done | done | 7c46ffc | - |
| T5 | 创建 app/redis_client.py | done | done | b7ae897 | - |
| T6 | lifespan 中初始化 Redis/MySQL 连接 | done | done | a4c3af6 | - |
| T7 | MySQL 表结构初始化(复用 ORM 模型) | done | done | 72d81ce | - |
| T8 | 创建 app/storage_manager.py 骨架 + 降级检测 | done | done | 48f9765 | - |
| T9 | StorageManager 读取逻辑Redis → MySQL → SQLite | done | done | beba383 | - |
| T10 | StorageManager 写入逻辑 + 双写一致性 | done | done | 8f3c2b6 | fix: 59e461a |
| T11 | 创建数据迁移脚本 app/migration.py | done | done | a26a44e | - |
| T12 | 启动时自动触发迁移 | done | done | 5db0546 | - |
| T13 | 改造 cache.py 内部封装 StorageManager | done | done | 7ee6794 | fixes: 2720ddb, bf4f571 |
| T14 | 验证Redis 缓存命中/未命中场景 | done | done | ad9d7f8 | 2 xfail: 日志断言 |
| T15 | 验证:降级到 MySQL / SQLite 场景 | done | done | 7cea089 | fix: 177a10f 单例注入 |
| T16 | 验证:双写一致性 + 数据迁移完整性 | done | done | 4d7b3e6 | fix: 46f5846 迁移落盘 |
## Final Review
- Status: APPROVED (4 rounds)
- Final fix: e17a183 (atomic writes, migration, config, URL encoding)
- Final fix: d9bda2c (is_fresh TTL semantics)
- Final fix: 0a519d5 (timestamp write fallback)
## Batch Reviews
- Batch 1 (T1-T3): APPROVED
- Batch 2 (T4-T6): APPROVED
- Batch 3 (T7-T10): APPROVED (after fix)
- Batch 4 (T11-T12): APPROVED
- Task 13 Review: APPROVED (after 2 fixes)
- Batch 5 (T14-T16 + fixes): APPROVED
- Final Review v4: APPROVED

@ -1,121 +0,0 @@
## Context
当前系统使用 SQLite 作为唯一存储后端,所有行情数据(`MarketData`)以 JSON 字符串形式存储在磁盘文件中。每次刷新行情时,系统需要从数据源采集数据、写入 SQLite读取时再反序列化。这种架构在高频读写场景下存在性能瓶颈。
系统包含以下核心实体:
- `MarketData`: 行情 K 线数据(高频读写,数据量大)
- `SymbolTimestamp`: 合约数据时间戳(中频读写)
- `ScheduledTask`: 定时任务配置(低频读写)
- 用户认证、交易复盘等低频业务表
约束条件:
- 单机部署,需要本地运行 Redis
- 需要保证系统可用性,即使部分存储组件故障
- 现有 SQLite 数据需要迁移或兼容
## Goals / Non-Goals
**Goals:**
- 引入 Redis 作为热数据缓存层提升行情数据读取性能TTL 30 天)
- 引入 MySQL 作为主要持久化存储,替代 SQLite 承担日常读写
- 保留 SQLite 作为最终兜底方案,保证系统可用性
- 实现三级降级策略Redis → MySQL → SQLite
- 刷新接口双写:数据同步写入 Redis 和 MySQL
- 启动时初始化多存储后端,检测可用性
**Non-Goals:**
- 不迁移用户认证、交易复盘等低频业务表(保持 SQLite
- 不改造前端页面
- 不统一 API 接口规范(留给后续 change
- 不实现分布式部署或集群方案
## Decisions
### 1. 存储分层策略
**决策**: 采用 Redis缓存+ MySQL持久化+ SQLite兜底三级架构。
**理由**:
- Redis 提供亚毫秒级读取性能,适合行情数据高频访问
- MySQL 提供可靠的持久化能力和事务支持,替代 SQLite 成为主存储
- SQLite 保留作为最终兜底,保证极端情况下系统仍可运行
- 三级降级保证系统可用性,避免单点故障
**备选方案**:
- Redis + PostgreSQL: PostgreSQL 功能更强大但部署复杂度更高MySQL 更轻量
- 纯 Redis: 无法满足持久化需求,数据丢失风险高
- 纯 MySQL: 缺少缓存层,读取性能提升有限
### 2. 数据访问层设计
**决策**: 新增 `StorageManager` 抽象层,封装三级降级逻辑。
**理由**:
- 业务代码无需关心底层存储实现
- 降级策略集中管理,便于维护和测试
- 可通过配置切换存储后端,支持渐进式迁移
**备选方案**:
- 直接在业务代码中实现降级逻辑: 代码重复,难以维护
- 使用 ORM 插件: 灵活性不足,难以实现复杂的降级策略
### 3. 双写一致性策略
**决策**: 刷新接口采用同步双写,先写 MySQL 再更新 Redis。
**理由**:
- MySQL 作为持久化主存储,必须先保证数据落盘
- Redis 作为缓存,写入失败不影响数据持久化
- 同步双写保证数据一致性,避免异步延迟导致的数据不一致
**备选方案**:
- 异步双写: 性能更好,但可能出现数据不一致
- 仅写 MySQLRedis 通过缓存未命中回填: 首次读取性能差
### 4. Redis 缓存策略
**决策**: 行情数据 TTL 30 天,缓存未命中时从 MySQL 读取并回填。
**理由**:
- 30 天覆盖大部分行情数据的活跃访问周期
- 缓存未命中回填保证读取性能
- TTL 过期后自动清理,避免内存无限增长
**备选方案**:
- 永不过期: 内存占用不可控
- 更短 TTL如 1 天): 缓存命中率低,频繁回源 MySQL
### 5. 降级检测机制
**决策**: 启动时检测 Redis/MySQL 可用性,运行时捕获连接异常触发降级。
**理由**:
- 启动时检测可提前发现问题,输出明确的错误日志
- 运行时降级保证系统可用性,避免服务中断
- 降级状态可通过日志监控,便于运维排查
**备选方案**:
- 仅启动时检测: 无法处理运行中服务故障
- 健康检查接口: 增加复杂度,当前场景不需要
### 6. 数据迁移策略
**决策**: 新增 MySQL 表结构,启动时从 SQLite 迁移历史数据到 MySQL。
**理由**:
- 保证历史数据不丢失
- 一次性迁移,后续直接读写 MySQL
- SQLite 保留作为兜底,不删除
**备选方案**:
- 手动迁移: 容易遗漏,风险高
- 双写过渡期: 复杂度高,当前场景不需要
## Risks / Trade-offs
- **[风险]** Redis 和 MySQL 同时故障 → **[缓解]** SQLite 兜底,系统仍可运行
- **[风险]** 双写一致性MySQL 写入成功但 Redis 写入失败 → **[缓解]** Redis 写入失败不影响持久化,下次读取时从 MySQL 回填
- **[风险]** Redis 内存占用过高 → **[缓解]** TTL 30 天自动清理,监控内存使用
- **[风险]** MySQL 部署复杂度增加 → **[缓解]** 使用 docker-compose 一键部署
- **[取舍]** 同步双写性能略低于异步双写 → 换取数据一致性保证
- **[取舍]** 三级降级增加代码复杂度 → 换取系统高可用性

@ -1,33 +0,0 @@
## Why
当前系统使用 SQLite 作为唯一存储后端,无法满足行情数据高频读写的性能需求。每次刷新行情数据都需要直接读写磁盘文件,导致响应延迟高、并发能力受限。需要引入更高效的存储方案以提升系统吞吐量和用户体验。
## What Changes
- 引入 Redis 作为热数据缓存层,行情数据优先从 Redis 读取TTL 30 天)
- 引入 MySQL 作为持久化存储层,替代 SQLite 承担主要持久化职责
- 保留 SQLite 作为最终兜底方案,当 Redis 和 MySQL 均不可用时启用
- 新增数据访问层:实现 Redis → MySQL → SQLite 的三级降级读取策略
- 刷新接口改造:数据同步写入 Redis 和 MySQL保证双写一致性
- 启动流程改造:初始化 Redis/MySQL/SQLite 连接,检测可用性
## Capabilities
### New Capabilities
- `redis-cache-layer`: Redis 缓存读写能力包括热数据缓存、TTL 管理、缓存失效策略
- `mysql-persistence`: MySQL 持久化存储能力,替代 SQLite 承担主要持久化职责
- `storage-fallback`: 三级降级策略Redis → MySQL → SQLite保证系统可用性
- `dual-write-consistency`: 刷新接口双写能力,保证 Redis 和 MySQL 数据一致性
### Modified Capabilities
(无既有 spec 需要修改)
## Impact
- **代码**: `app/database.py`、`app/models.py`、`app/api/data.py`、`app/services/collector.py`、`app/main.py`
- **依赖**: 新增 `redis`、`pymysql`(或 `aiomysql`Python 包
- **配置**: `app/config.py` 新增 Redis/MySQL 连接配置
- **部署**: `docker-compose.yml` 新增 Redis 和 MySQL 服务
- **数据库**: 新增 MySQL 数据库初始化脚本,保留 SQLite 作为兜底

@ -1,30 +0,0 @@
## ADDED Requirements
### Requirement: 刷新接口双写
系统应当在刷新接口中实现 Redis 和 MySQL 的同步双写,保证数据一致性。
#### Scenario: 刷新接口双写成功
- **WHEN** 用户调用刷新接口更新行情数据
- **THEN** 系统先删除 Redis 缓存,再写入 MySQL最后更新 Redis 缓存
#### Scenario: MySQL 写入失败
- **WHEN** 刷新接口写入 MySQL 失败
- **THEN** 系统返回错误响应,不更新 Redis 缓存,保证数据一致性
#### Scenario: Redis 写入失败
- **WHEN** 刷新接口写入 MySQL 成功但 Redis 写入失败
- **THEN** 系统返回成功响应MySQL 数据已持久化),输出 Redis 写入失败警告日志
### Requirement: 双写顺序保证
系统应当保证双写的顺序:先写 MySQL再更新 Redis。
#### Scenario: 双写顺序
- **WHEN** 刷新接口执行双写
- **THEN** 系统先写入 MySQL 并确认成功,再更新 Redis 缓存
### Requirement: 缓存回填一致性
系统应当在缓存未命中回填时保证回填数据与 MySQL 数据一致。
#### Scenario: 缓存未命中回填
- **WHEN** Redis 缓存未命中且从 MySQL 读取数据
- **THEN** 系统将 MySQL 数据回填到 RedisTTL 设置为 30 天

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## ADDED Requirements
### Requirement: MySQL 连接管理
系统应当提供 MySQL 连接管理能力,包括连接初始化、连接池管理和表结构初始化。
#### Scenario: MySQL 连接初始化成功
- **WHEN** 应用启动且 MySQL 配置有效
- **THEN** 系统成功建立 MySQL 连接并创建必要的表结构
#### Scenario: MySQL 连接初始化失败
- **WHEN** 应用启动但 MySQL 服务不可用
- **THEN** 系统输出错误日志并标记 MySQL 为不可用状态,但不阻止应用启动
### Requirement: 行情数据持久化存储
系统应当使用 MySQL 作为行情数据的主要持久化存储,替代 SQLite。
#### Scenario: 行情数据写入 MySQL
- **WHEN** 刷新接口接收到行情数据更新请求
- **THEN** 系统将数据写入 MySQL 的 `market_data`
#### Scenario: 行情数据从 MySQL 读取
- **WHEN** Redis 缓存未命中且 MySQL 可用
- **THEN** 系统从 MySQL 读取行情数据并返回
### Requirement: MySQL 表结构迁移
系统应当提供从 SQLite 到 MySQL 的数据迁移能力,保证历史数据不丢失。
#### Scenario: 首次启动数据迁移
- **WHEN** 应用首次启动且 MySQL 可用但表为空
- **THEN** 系统从 SQLite 读取历史数据并迁移到 MySQL
#### Scenario: 迁移完成
- **WHEN** 数据迁移完成
- **THEN** 系统输出迁移成功日志,后续读写直接操作 MySQL
### Requirement: MySQL 事务支持
系统应当使用 MySQL 事务保证数据写入的原子性和一致性。
#### Scenario: 批量写入事务
- **WHEN** 刷新接口需要写入多个品种的行情数据
- **THEN** 系统使用事务保证所有数据要么全部写入成功,要么全部回滚

@ -1,41 +0,0 @@
## ADDED Requirements
### Requirement: Redis 缓存连接管理
系统应当提供 Redis 连接管理能力,包括连接初始化、健康检查和连接池管理。
#### Scenario: Redis 连接初始化成功
- **WHEN** 应用启动且 Redis 配置有效
- **THEN** 系统成功建立 Redis 连接并输出初始化成功日志
#### Scenario: Redis 连接初始化失败
- **WHEN** 应用启动但 Redis 服务不可用
- **THEN** 系统输出警告日志并标记 Redis 为不可用状态,但不阻止应用启动
### Requirement: 行情数据缓存读取
系统应当优先从 Redis 读取行情数据,缓存未命中时回源 MySQL。
#### Scenario: Redis 缓存命中
- **WHEN** 用户请求行情数据且 Redis 中存在该数据
- **THEN** 系统直接从 Redis 返回数据,不访问 MySQL
#### Scenario: Redis 缓存未命中
- **WHEN** 用户请求行情数据但 Redis 中不存在该数据
- **THEN** 系统从 MySQL 读取数据,回填到 RedisTTL 30 天),并返回数据
### Requirement: Redis 缓存 TTL 管理
系统应当为缓存数据设置 30 天过期时间,过期后自动清理。
#### Scenario: 缓存数据过期
- **WHEN** 缓存数据超过 30 天未访问
- **THEN** Redis 自动清理该数据,下次访问时从 MySQL 重新加载
#### Scenario: 缓存数据续期
- **WHEN** 用户访问已缓存的行情数据
- **THEN** 系统返回缓存数据TTL 保持为 30 天(不续期)
### Requirement: Redis 缓存失效
系统应当在数据更新时主动失效相关缓存,保证数据一致性。
#### Scenario: 刷新接口触发缓存失效
- **WHEN** 用户调用刷新接口更新行情数据
- **THEN** 系统先删除 Redis 中对应的缓存数据,再执行双写流程

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## ADDED Requirements
### Requirement: 三级降级策略
系统应当实现 Redis → MySQL → SQLite 的三级降级读取策略,保证系统可用性。
#### Scenario: 正常模式Redis + MySQL 可用)
- **WHEN** Redis 和 MySQL 均可用
- **THEN** 系统优先从 Redis 读取,未命中时回源 MySQL
#### Scenario: Redis 不可用降级
- **WHEN** Redis 服务不可用但 MySQL 可用
- **THEN** 系统直接从 MySQL 读取数据,跳过 Redis 缓存层
#### Scenario: Redis 和 MySQL 均不可用降级
- **WHEN** Redis 和 MySQL 均不可用
- **THEN** 系统降级到 SQLite从 SQLite 读取数据并保证基础服务可用
### Requirement: 降级状态检测
系统应当能够检测存储后端的可用性状态,并在降级时输出明确的日志。
#### Scenario: 启动时降级检测
- **WHEN** 应用启动时检测到 Redis 或 MySQL 不可用
- **THEN** 系统输出降级警告日志,说明当前使用的存储模式
#### Scenario: 运行时降级触发
- **WHEN** 运行中 Redis 或 MySQL 连接异常
- **THEN** 系统自动切换到降级模式,输出降级日志,并继续提供服务
### Requirement: 降级恢复
系统应当能够在存储后端恢复后自动恢复到正常模式。
#### Scenario: Redis 恢复
- **WHEN** Redis 从不可用状态恢复
- **THEN** 系统自动恢复到 Redis + MySQL 模式,后续读取优先使用 Redis
#### Scenario: MySQL 恢复
- **WHEN** MySQL 从不可用状态恢复
- **THEN** 系统自动恢复到 Redis + MySQL 模式SQLite 降级结束

@ -1,46 +0,0 @@
## 1. 依赖与配置
- [x] 1.1 添加 `redis`、`pymysql` 依赖到 `requirements.txt`
- [x] 1.2 在 `app/config.py` 中新增 Redis 和 MySQL 连接配置项host、port、user、password、database
- [x] 1.3 在 `docker-compose.yml` 中新增 Redis 和 MySQL 服务定义
## 2. 数据库模型与初始化
- [x] 2.1 创建 `app/mysql_database.py`,实现 MySQL 连接引擎和 SessionLocal
- [x] 2.2 创建 `app/redis_client.py`,实现 Redis 连接池和客户端封装
- [x] 2.3 在 `app/main.py``lifespan` 中初始化 Redis 和 MySQL 连接,检测可用性
- [x] 2.4 创建 MySQL 表结构初始化脚本(复用现有 ORM 模型)
## 3. 数据迁移
- [x] 3.1 创建数据迁移脚本,从 SQLite 读取历史数据并写入 MySQL
- [x] 3.2 在应用启动时检测 MySQL 表是否为空,自动触发迁移
## 4. 存储管理层
- [x] 4.1 创建 `app/storage_manager.py`,实现 `StorageManager` 抽象层
- [x] 4.2 实现 Redis 缓存读取逻辑(命中返回,未命中回源 MySQL 并回填)
- [x] 4.3 实现 MySQL 持久化读写逻辑
- [x] 4.4 实现三级降级策略Redis → MySQL → SQLite
- [x] 4.5 实现降级状态检测和恢复机制
## 5. 双写与缓存一致性
- [x] 5.1 实现刷新接口双写逻辑:先删 Redis 缓存,再写 MySQL最后更新 Redis
- [x] 5.2 实现双写顺序保证和错误处理MySQL 失败回滚Redis 失败记录日志)
- [x] 5.3 实现缓存未命中回填逻辑TTL 30 天)
## 6. 接口改造
- [x] 6.1 改造 `app/services/cache.py` 中的行情数据读取接口,使用 `StorageManager`
- [x] 6.2 改造 `app/services/cache.py` 中的刷新接口,使用双写逻辑
- [x] 6.3 改造 `app/services/cache.py`,使用 `StorageManager` 写入数据API 层零改动)
## 7. 测试与验证
- [x] 7.1 验证 Redis 缓存命中场景
- [x] 7.2 验证 Redis 缓存未命中回源 MySQL 场景
- [x] 7.3 验证 Redis 不可用降级到 MySQL 场景
- [x] 7.4 验证 Redis 和 MySQL 均不可用降级到 SQLite 场景
- [x] 7.5 验证刷新接口双写一致性
- [x] 7.6 验证数据迁移完整性

@ -1,24 +0,0 @@
workflow: full
phase: archive
context_compression: off
build_mode: executing-plans
build_pause: null
subagent_dispatch: null
tdd_mode: tdd
review_mode: thorough
isolation: branch
verify_mode: full
auto_transition: true
base_ref: f8d5ecd
design_doc: docs/superpowers/specs/2026-07-04-config-to-mysql-design.md
plan: docs/superpowers/plans/2026-07-04-config-to-mysql.md
verify_result: pass
verification_report: docs/superpowers/reports/2026-07-04-config-to-mysql-verify.md
branch_status: handled
created_at: 2026-07-04
verified_at: 2026-07-05
archived: true
handoff_context: null
handoff_hash: null
build_command: python -m pytest tests/ -v
verify_command: python -m pytest tests/ -v

@ -1,31 +0,0 @@
# Brainstorm Summary
## 确认的技术方案
**采用方案:单表键值对 + 统一配置模块 + JSON fallback**
| 组件 | 说明 |
|------|------|
| `app/models.py` | 新增 `AppConfig` 模型 |
| `app/config_store.py` | 统一配置读写入口 |
| `app/config_migration.py` | JSON → MySQL 迁移脚本 |
| JSON 文件 | 降级方案,保留原路径 |
## 关键取舍与风险
| 取舍 | 决策 |
|------|------|
| 单表 vs 多表 | 单表,通过 `config_key` 区分,未来扩展无需改表 |
| 是否使用 Redis | 不使用,按用户要求仅 MySQL |
| 是否保留文件 | 保留,作为 MySQL 不可用时的降级 |
| 写入策略 | 双写MySQL 可用时写数据库 + 写文件MySQL 不可用时只写文件 |
## 测试策略
- 单元测试:`tests/test_config_store.py` 覆盖读取、写入、降级
- 迁移测试:验证幂等性
- 回归测试:全部测试套件
## Spec Patch

@ -1,3 +0,0 @@
name: config-to-mysql
created: 2026-07-04
status: active

@ -1,101 +0,0 @@
# Design: Config to MySQL
## 架构决策
### 决策 1统一配置管理模块
**决策**:创建 `app/config_store.py` 作为所有配置读写的唯一入口。
**理由**
- 消除多处重复的文件读取逻辑
- 集中管理降级策略
- 便于后续扩展(如缓存、审计)
### 决策 2单表存储键值对
**决策**:使用单表 `app_config` 存储所有配置,以 `config_key` 区分 `symbols``ai`
**表结构**
```sql
CREATE TABLE app_config (
id INT PRIMARY KEY AUTO_INCREMENT,
config_key VARCHAR(64) UNIQUE NOT NULL, -- 'symbols' 或 'ai'
config_value JSON NOT NULL,
updated_at DATETIME DEFAULT CURRENT_TIMESTAMP ON UPDATE CURRENT_TIMESTAMP,
created_at DATETIME DEFAULT CURRENT_TIMESTAMP
)
```
**理由**
- 与现有 JSON schema 兼容
- 减少表数量
- 未来新增配置无需改表结构
### 决策 3MySQL + JSON 文件降级
**决策**MySQL 可用时优先读写数据库MySQL 不可用时回退到 JSON 文件。
**理由**
- 用户明确要求无需 Redis
- JSON 文件作为 fallback 简单可靠
- 与现有配置读取方式兼容
## 数据流
```
业务代码
app/config_store.py
MySQL 可用?
↓ 是 ↓ 否
读/写 app_config 读/写 JSON 文件
```
## 配置键设计
| config_key | 对应文件 | 用途 |
|------------|----------|------|
| `symbols` | `config/symbols_config.json` | 品种合约映射 |
| `ai` | `config/ai_config.json` | AI 模型配置 |
## 降级策略
### 读取流程
1. 检查 MySQL 可用性
2. MySQL 可用则查询 `app_config`
3. 数据库无数据则读取 JSON 文件并回填数据库
4. MySQL 不可用则直接读取 JSON 文件
### 写入流程
1. 检查 MySQL 可用性
2. MySQL 可用则写入 `app_config`
3. 无论数据库是否成功,同步写入 JSON 文件(保持一致性)
4. MySQL 不可用则只写入 JSON 文件
## 兼容性
- 保持 `symbols_config.json``ai_config.json` 的 schema 不变
- API 接口签名不变
- 文件路径不变,作为 fallback 使用
## 数据迁移
启动时执行一次性迁移:
1. 检测 `app_config` 表是否已有 `symbols``ai` 配置
2. 缺失则从 JSON 文件读取并写入数据库
3. 迁移幂等:已存在则跳过
## 测试策略
1. 单元测试:
- `ConfigStore.get_config` 从 MySQL 读取
- `ConfigStore.get_config` 在 MySQL 不可用时读取 JSON
- `ConfigStore.set_config` 写入 MySQL 和 JSON
- 迁移幂等性
2. 集成测试:
- 启动时自动创建表并迁移
- API 接口正常工作

@ -1,59 +0,0 @@
# Proposal: Config to MySQL
## 问题背景
当前配置信息(`symbols_config.json` 品种合约映射、`ai_config.json` AI 模型配置)以 JSON 文件形式存储在 `config/` 目录下。存在以下问题:
1. **配置与应用状态分离**:文件配置难以统一备份、迁移和多实例共享
2. **读写分散**:多个模块直接读取 JSON 文件,重复解析逻辑
3. **无版本/审计**:文件修改无历史记录,难以追踪配置变更
4. **与架构不一致**:行情数据和分析数据已迁移到 MySQL配置仍停留在文件系统
## 目标
`symbols_config.json``ai_config.json` 迁移到 MySQL `buffer_platform` 数据库,提供统一的配置读取/写入接口,并保留 JSON 文件作为降级方案。
## 范围
### 包含
- 新增 MySQL 配置表:`symbol_config`、`ai_config`
- 创建统一配置管理模块 `app/config_store.py`
- 启动时自动迁移现有 JSON 配置到 MySQL
- 修改以下模块从数据库读取配置:
- `app/api/config.py`
- `app/api/ai_config.py`
- `app/api/futures_analysis.py`
- `app/api/trade_review.py`
- `app/services/trade_parser.py`
- `app/services/plan_generator.py`
- `app/services/ai_analysis.py`
- MySQL 不可用时降级到 JSON 文件
### 不包含
- 新增业务功能
- 修改配置结构(保持现有 JSON schema
- Redis 缓存层
## 非目标
- 不改变配置 schema
- 不改变 API 接口签名
- 不引入配置版本控制或审计日志
## 验收标准
1. 启动时自动创建配置表并迁移 JSON 数据到 MySQL
2. 所有配置读写通过 `app/config_store.py` 接口
3. MySQL 不可用时自动降级到 JSON 文件
4. 现有功能品种列表、AI 配置、交易复盘、计划生成)正常工作
5. 单元测试覆盖数据库命中、数据库未命中降级、迁移幂等性
## 风险
| 风险 | 缓解措施 |
|------|----------|
| 数据迁移失败 | 保留 JSON 文件作为降级方案 |
| 配置读取性能下降 | 配置数据量小,数据库查询足够快;无 Redis 需求 |
| 多处修改引入回归 | 统一封装 + 全面测试 |

@ -1,37 +0,0 @@
# Tasks: Config to MySQL
## 1. 数据模型与配置存储模块
- [x] 1.1 在 `app/models.py` 中新增 `AppConfig` 模型
- [x] 1.2 创建 `app/config_store.py`,实现 `ConfigStore`
- [x] 1.3 实现 `get_config(key)` 方法,支持 MySQL → JSON 降级
- [x] 1.4 实现 `set_config(key, value)` 方法,支持 MySQL + JSON 双写
- [x] 1.5 实现 `_load_json(key, fallback)``_save_to_json(key, value)` 辅助方法
## 2. 数据迁移
- [x] 2.1 创建 `app/config_migration.py`,实现 `migrate_configs_to_mysql()`
- [x] 2.2 在 `app/main.py` lifespan 中创建 `app_config`
- [x] 2.3 在 `app/main.py` lifespan 中调用迁移函数
- [x] 2.4 迁移幂等性:数据库已有配置时跳过
## 3. 修改配置 API
- [x] 3.1 修改 `app/api/config.py` 使用 `ConfigStore` 读写 `symbols` 配置
- [x] 3.2 修改 `app/api/ai_config.py` 使用 `ConfigStore` 读写 `ai` 配置
- [x] 3.3 保持 API 接口签名不变
## 4. 修改业务使用方
- [x] 4.1 修改 `app/api/futures_analysis.py``ConfigStore` 读取品种配置
- [x] 4.2 修改 `app/api/trade_review.py``ConfigStore` 读取品种配置
- [x] 4.3 修改 `app/services/trade_parser.py``ConfigStore` 读取品种配置
- [x] 4.4 修改 `app/services/plan_generator.py``ConfigStore` 读取品种配置
- [x] 4.5 修改 `app/services/ai_analysis.py``ConfigStore` 读取 AI 配置
## 5. 测试与验证
- [x] 5.1 编写 `tests/test_config_store.py`,覆盖 MySQL 命中/未命中/降级场景
- [x] 5.2 编写迁移测试,验证幂等性
- [x] 5.3 运行全部测试套件确保无回归110 passed, 2 xfailed
- [x] 5.4 启动应用验证配置读取正常

@ -1,30 +0,0 @@
## ADDED Requirements
### Requirement: 刷新接口双写
系统应当在刷新接口中实现 Redis 和 MySQL 的同步双写,保证数据一致性。
#### Scenario: 刷新接口双写成功
- **WHEN** 用户调用刷新接口更新行情数据
- **THEN** 系统先删除 Redis 缓存,再写入 MySQL最后更新 Redis 缓存
#### Scenario: MySQL 写入失败
- **WHEN** 刷新接口写入 MySQL 失败
- **THEN** 系统返回错误响应,不更新 Redis 缓存,保证数据一致性
#### Scenario: Redis 写入失败
- **WHEN** 刷新接口写入 MySQL 成功但 Redis 写入失败
- **THEN** 系统返回成功响应MySQL 数据已持久化),输出 Redis 写入失败警告日志
### Requirement: 双写顺序保证
系统应当保证双写的顺序:先写 MySQL再更新 Redis。
#### Scenario: 双写顺序
- **WHEN** 刷新接口执行双写
- **THEN** 系统先写入 MySQL 并确认成功,再更新 Redis 缓存
### Requirement: 缓存回填一致性
系统应当在缓存未命中回填时保证回填数据与 MySQL 数据一致。
#### Scenario: 缓存未命中回填
- **WHEN** Redis 缓存未命中且从 MySQL 读取数据
- **THEN** 系统将 MySQL 数据回填到 RedisTTL 设置为 30 天

@ -1,41 +0,0 @@
## ADDED Requirements
### Requirement: MySQL 连接管理
系统应当提供 MySQL 连接管理能力,包括连接初始化、连接池管理和表结构初始化。
#### Scenario: MySQL 连接初始化成功
- **WHEN** 应用启动且 MySQL 配置有效
- **THEN** 系统成功建立 MySQL 连接并创建必要的表结构
#### Scenario: MySQL 连接初始化失败
- **WHEN** 应用启动但 MySQL 服务不可用
- **THEN** 系统输出错误日志并标记 MySQL 为不可用状态,但不阻止应用启动
### Requirement: 行情数据持久化存储
系统应当使用 MySQL 作为行情数据的主要持久化存储,替代 SQLite。
#### Scenario: 行情数据写入 MySQL
- **WHEN** 刷新接口接收到行情数据更新请求
- **THEN** 系统将数据写入 MySQL 的 `market_data`
#### Scenario: 行情数据从 MySQL 读取
- **WHEN** Redis 缓存未命中且 MySQL 可用
- **THEN** 系统从 MySQL 读取行情数据并返回
### Requirement: MySQL 表结构迁移
系统应当提供从 SQLite 到 MySQL 的数据迁移能力,保证历史数据不丢失。
#### Scenario: 首次启动数据迁移
- **WHEN** 应用首次启动且 MySQL 可用但表为空
- **THEN** 系统从 SQLite 读取历史数据并迁移到 MySQL
#### Scenario: 迁移完成
- **WHEN** 数据迁移完成
- **THEN** 系统输出迁移成功日志,后续读写直接操作 MySQL
### Requirement: MySQL 事务支持
系统应当使用 MySQL 事务保证数据写入的原子性和一致性。
#### Scenario: 批量写入事务
- **WHEN** 刷新接口需要写入多个品种的行情数据
- **THEN** 系统使用事务保证所有数据要么全部写入成功,要么全部回滚

@ -1,41 +0,0 @@
## ADDED Requirements
### Requirement: Redis 缓存连接管理
系统应当提供 Redis 连接管理能力,包括连接初始化、健康检查和连接池管理。
#### Scenario: Redis 连接初始化成功
- **WHEN** 应用启动且 Redis 配置有效
- **THEN** 系统成功建立 Redis 连接并输出初始化成功日志
#### Scenario: Redis 连接初始化失败
- **WHEN** 应用启动但 Redis 服务不可用
- **THEN** 系统输出警告日志并标记 Redis 为不可用状态,但不阻止应用启动
### Requirement: 行情数据缓存读取
系统应当优先从 Redis 读取行情数据,缓存未命中时回源 MySQL。
#### Scenario: Redis 缓存命中
- **WHEN** 用户请求行情数据且 Redis 中存在该数据
- **THEN** 系统直接从 Redis 返回数据,不访问 MySQL
#### Scenario: Redis 缓存未命中
- **WHEN** 用户请求行情数据但 Redis 中不存在该数据
- **THEN** 系统从 MySQL 读取数据,回填到 RedisTTL 30 天),并返回数据
### Requirement: Redis 缓存 TTL 管理
系统应当为缓存数据设置 30 天过期时间,过期后自动清理。
#### Scenario: 缓存数据过期
- **WHEN** 缓存数据超过 30 天未访问
- **THEN** Redis 自动清理该数据,下次访问时从 MySQL 重新加载
#### Scenario: 缓存数据续期
- **WHEN** 用户访问已缓存的行情数据
- **THEN** 系统返回缓存数据TTL 保持为 30 天(不续期)
### Requirement: Redis 缓存失效
系统应当在数据更新时主动失效相关缓存,保证数据一致性。
#### Scenario: 刷新接口触发缓存失效
- **WHEN** 用户调用刷新接口更新行情数据
- **THEN** 系统先删除 Redis 中对应的缓存数据,再执行双写流程

@ -1,38 +0,0 @@
## ADDED Requirements
### Requirement: 三级降级策略
系统应当实现 Redis → MySQL → SQLite 的三级降级读取策略,保证系统可用性。
#### Scenario: 正常模式Redis + MySQL 可用)
- **WHEN** Redis 和 MySQL 均可用
- **THEN** 系统优先从 Redis 读取,未命中时回源 MySQL
#### Scenario: Redis 不可用降级
- **WHEN** Redis 服务不可用但 MySQL 可用
- **THEN** 系统直接从 MySQL 读取数据,跳过 Redis 缓存层
#### Scenario: Redis 和 MySQL 均不可用降级
- **WHEN** Redis 和 MySQL 均不可用
- **THEN** 系统降级到 SQLite从 SQLite 读取数据并保证基础服务可用
### Requirement: 降级状态检测
系统应当能够检测存储后端的可用性状态,并在降级时输出明确的日志。
#### Scenario: 启动时降级检测
- **WHEN** 应用启动时检测到 Redis 或 MySQL 不可用
- **THEN** 系统输出降级警告日志,说明当前使用的存储模式
#### Scenario: 运行时降级触发
- **WHEN** 运行中 Redis 或 MySQL 连接异常
- **THEN** 系统自动切换到降级模式,输出降级日志,并继续提供服务
### Requirement: 降级恢复
系统应当能够在存储后端恢复后自动恢复到正常模式。
#### Scenario: Redis 恢复
- **WHEN** Redis 从不可用状态恢复
- **THEN** 系统自动恢复到 Redis + MySQL 模式,后续读取优先使用 Redis
#### Scenario: MySQL 恢复
- **WHEN** MySQL 从不可用状态恢复
- **THEN** 系统自动恢复到 Redis + MySQL 模式SQLite 降级结束

@ -1,4 +1,4 @@
fastapi>=0.110.0
fastapi>=0.110.0
uvicorn>=0.29.0
sqlalchemy>=2.0.0
aiosqlite>=0.20.0
@ -10,7 +10,3 @@ tenacity>=8.2.0
requests>=2.31.0
httpx>=0.27.0
python-multipart>=0.0.9
redis>=5.0.0
pymysql>=1.1.0
cryptography>=42.0.0
python-dotenv>=1.0.0

@ -1,171 +0,0 @@
"""Analysis 存储迁移测试Redis 缓存 + MySQL/SQLite 降级。"""
import json
from datetime import datetime
from unittest.mock import MagicMock, patch
import pytest
from app.storage_manager import StorageManager
class TestStorageManagerCache:
"""StorageManager 通用缓存方法测试。"""
def test_cache_get_returns_redis_value_on_hit(self):
"""Redis 命中时返回反序列化数据。"""
redis_client = MagicMock()
redis_client.get.return_value = json.dumps({"symbol": "AG2606", "score": 85})
manager = StorageManager(redis_client=redis_client, mysql_engine=MagicMock())
result = manager.cache_get("analysis:ai_analysis_cache:1")
assert result == {"symbol": "AG2606", "score": 85}
redis_client.get.assert_called_once_with("analysis:ai_analysis_cache:1")
def test_cache_get_returns_none_when_redis_unavailable(self):
"""Redis 不可用时返回 None。"""
manager = StorageManager(redis_client=None, mysql_engine=MagicMock())
result = manager.cache_get("analysis:ai_analysis_cache:1")
assert result is None
def test_cache_get_returns_none_on_miss(self):
"""Redis 未命中时返回 None。"""
redis_client = MagicMock()
redis_client.get.return_value = None
manager = StorageManager(redis_client=redis_client, mysql_engine=MagicMock())
result = manager.cache_get("analysis:ai_analysis_cache:1")
assert result is None
def test_cache_set_writes_to_redis_with_ttl(self):
"""cache_set 使用 TTL 写入 Redis。"""
redis_client = MagicMock()
manager = StorageManager(redis_client=redis_client, mysql_engine=MagicMock())
value = {"symbol": "AG2606", "score": 85}
manager.cache_set("analysis:ai_analysis_cache:1", value, ttl=300)
redis_client.setex.assert_called_once_with(
"analysis:ai_analysis_cache:1", 300, json.dumps(value, ensure_ascii=False)
)
def test_cache_set_returns_false_when_redis_unavailable(self):
"""Redis 不可用时 cache_set 返回 False。"""
manager = StorageManager(redis_client=None, mysql_engine=MagicMock())
result = manager.cache_set("analysis:ai_analysis_cache:1", {"score": 85}, ttl=300)
assert result is False
def test_cache_delete_removes_redis_key(self):
"""cache_delete 删除 Redis 键。"""
redis_client = MagicMock()
manager = StorageManager(redis_client=redis_client, mysql_engine=MagicMock())
manager.cache_delete("analysis:ai_analysis_cache:1")
redis_client.delete.assert_called_once_with("analysis:ai_analysis_cache:1")
class TestAnalysisDbSwitching:
"""analysis_db 动态 Session 切换测试。"""
def test_get_analysis_db_returns_mysql_session_when_mysql_available(self):
"""MySQL 可用时返回 MySQL Session。"""
from app.analysis_db import get_analysis_db
mysql_engine = MagicMock()
mock_session = MagicMock()
mock_sessionmaker = MagicMock(return_value=mock_session)
mock_session.__enter__ = MagicMock(return_value=mock_session)
mock_session.__exit__ = MagicMock(return_value=False)
with patch("app.analysis_db.MySQLSessionLocal", mock_sessionmaker):
with patch("app.analysis_db.get_storage_manager") as mock_sm:
sm = MagicMock()
sm.check_mysql.return_value = True
sm.mysql_engine = mysql_engine
mock_sm.return_value = sm
db = next(get_analysis_db())
assert db is mock_session
def test_get_analysis_db_returns_sqlite_session_when_mysql_unavailable(self):
"""MySQL 不可用时返回 SQLite Session。"""
from app.analysis_db import get_analysis_db
sqlite_engine = MagicMock()
mock_session = MagicMock()
mock_sessionmaker = MagicMock(return_value=mock_session)
mock_session.__enter__ = MagicMock(return_value=mock_session)
mock_session.__exit__ = MagicMock(return_value=False)
with patch("app.analysis_db.AnalysisSessionLocal", mock_sessionmaker):
with patch("app.analysis_db.get_storage_manager") as mock_sm:
sm = MagicMock()
sm.check_mysql.return_value = False
mock_sm.return_value = sm
db = next(get_analysis_db())
assert db is mock_session
class TestAnalysisMigration:
"""Analysis 数据迁移测试。"""
def test_migrate_skips_when_mysql_has_data(self):
"""MySQL 已有数据时跳过迁移。"""
from app.analysis_migration import migrate_analysis_sqlite_to_mysql
with patch("app.analysis_migration.mysql_engine", MagicMock()):
with patch("app.analysis_migration._count_mysql_analysis_records") as mock_count:
mock_count.return_value = 10
result = migrate_analysis_sqlite_to_mysql()
assert result is True
mock_count.assert_called_once()
def test_migrate_moves_data_from_sqlite_to_mysql(self):
"""SQLite 数据正确迁移到 MySQL。"""
from app.analysis_migration import migrate_analysis_sqlite_to_mysql
with patch("app.analysis_migration.mysql_engine", MagicMock()):
with patch("app.analysis_migration._count_mysql_analysis_records") as mock_count:
mock_count.return_value = 0
with patch("app.analysis_migration._read_sqlite_analysis_data") as mock_read:
mock_read.return_value = {
"ai_analysis_cache": [{"id": 1, "symbol": "AG2606"}]
}
with patch("app.analysis_migration._write_mysql_analysis_data") as mock_write:
mock_write.return_value = True
result = migrate_analysis_sqlite_to_mysql()
assert result is True
mock_write.assert_called_once_with({"ai_analysis_cache": [{"id": 1, "symbol": "AG2606"}]})
def test_get_analysis_db_falls_back_to_sqlite_when_mysql_session_fails(self):
"""MySQL Session 创建失败时降级到 SQLite。"""
from app.analysis_db import get_analysis_db
mysql_session_maker = MagicMock(side_effect=RuntimeError("MySQL 连接失败"))
sqlite_session = MagicMock()
sqlite_session_maker = MagicMock(return_value=sqlite_session)
with patch("app.analysis_db.MySQLSessionLocal", mysql_session_maker):
with patch("app.analysis_db.AnalysisSessionLocal", sqlite_session_maker):
with patch("app.analysis_db.get_storage_manager") as mock_sm:
sm = MagicMock()
sm.check_mysql.return_value = True
mock_sm.return_value = sm
db = next(get_analysis_db())
assert db is sqlite_session
mysql_session_maker.assert_called_once()

@ -1,544 +0,0 @@
"""
cache.py StorageManager 集成与 SQLite 降级逻辑测试
"""
import json
import logging
from datetime import datetime
from unittest.mock import MagicMock, patch
import pytest
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
from app.models import Base, MarketData, SymbolTimestamp
@pytest.fixture
def db():
"""提供已创建表结构的内存 SQLite 会话。"""
engine = create_engine("sqlite:///:memory:")
Base.metadata.create_all(bind=engine)
Session = sessionmaker(bind=engine)
session = Session()
yield session
session.close()
@pytest.fixture
def sample_data():
"""构造与采集脚本格式一致的测试数据。"""
return {
"type": "futures",
"current_price": 123.45,
"timestamp": datetime(2026, 7, 4, 10, 0, 0).isoformat(),
"timeframes": {
"5min": [{"datetime": "2026-07-04T09:55:00", "open": 100, "close": 110}],
"15min": [{"datetime": "2026-07-04T09:45:00", "open": 105, "close": 115}],
},
}
@pytest.fixture
def storage_manager_mock():
"""构造默认可用的 StorageManager mock。"""
manager = MagicMock()
manager.is_available.return_value = True
manager.save_market_data_with_timestamp.return_value = True
manager.save_market_data.return_value = True
manager.save_symbol_timestamp.return_value = True
manager.get_market_data.return_value = None
manager.get_symbol_timestamp.return_value = None
return manager
def _seed_sqlite_market_data(db, symbol="AG2606", data_type="futures"):
"""在 SQLite 中写入行情数据(使用当前时间确保缓存未过期)。"""
fetched_at = datetime.now()
db.add_all(
[
MarketData(
symbol=symbol,
data_type=data_type,
period="5min",
candles_json=json.dumps(
[{"datetime": "2026-07-04T09:55:00", "open": 100, "close": 110}]
),
current_price=123.45,
fetched_at=fetched_at,
candle_count=1,
),
MarketData(
symbol=symbol,
data_type=data_type,
period="15min",
candles_json=json.dumps(
[{"datetime": "2026-07-04T09:45:00", "open": 105, "close": 115}]
),
current_price=123.45,
fetched_at=fetched_at,
candle_count=1,
),
]
)
db.commit()
def _seed_sqlite_symbol_timestamp(db, symbol="AG2606", data_type="futures"):
"""在 SQLite 中写入合约时间戳。"""
db.add(
SymbolTimestamp(
symbol=symbol,
data_type=data_type,
last_refresh_at=datetime(2026, 7, 4, 10, 0, 0),
refresh_count=3,
)
)
db.commit()
class TestSaveMarketData:
"""save_market_data 双写与降级测试。"""
def test_uses_storage_manager_when_available(self, db, sample_data, storage_manager_mock):
"""StorageManager 可用时通过原子方法写入行情数据与时间戳,并返回代表记录。"""
with patch("app.services.cache.get_storage_manager", return_value=storage_manager_mock):
from app.services import cache
result = cache.save_market_data(db, "AG2606", sample_data)
storage_manager_mock.is_available.assert_called_once()
storage_manager_mock.save_market_data_with_timestamp.assert_called_once()
call_args = storage_manager_mock.save_market_data_with_timestamp.call_args[0]
assert call_args[0] == "AG2606"
assert call_args[1] == sample_data
assert isinstance(call_args[2], datetime)
storage_manager_mock.save_market_data.assert_not_called()
storage_manager_mock.save_symbol_timestamp.assert_not_called()
assert isinstance(result, MarketData)
assert result.symbol == "AG2606"
assert result.data_type == "futures"
assert result.current_price == 123.45
sqlite_records = db.query(MarketData).filter_by(symbol="AG2606").all()
assert len(sqlite_records) == 0
def test_falls_back_to_sqlite_when_storage_unavailable(self, db, sample_data, storage_manager_mock):
"""StorageManager 不可用时降级到 SQLite 写入。"""
storage_manager_mock.is_available.return_value = False
with patch("app.services.cache.get_storage_manager", return_value=storage_manager_mock):
from app.services import cache
result = cache.save_market_data(db, "AG2606", sample_data)
storage_manager_mock.save_market_data.assert_not_called()
storage_manager_mock.save_symbol_timestamp.assert_not_called()
assert isinstance(result, MarketData)
sqlite_records = db.query(MarketData).filter_by(symbol="AG2606").all()
assert len(sqlite_records) == 2
periods = {r.period for r in sqlite_records}
assert periods == {"5min", "15min"}
def test_falls_back_to_sqlite_when_storage_save_fails(self, db, sample_data, storage_manager_mock):
"""StorageManager 写入失败时降级到 SQLite 写入。"""
storage_manager_mock.save_market_data_with_timestamp.return_value = False
with patch("app.services.cache.get_storage_manager", return_value=storage_manager_mock):
from app.services import cache
result = cache.save_market_data(db, "AG2606", sample_data)
storage_manager_mock.save_market_data_with_timestamp.assert_called_once()
storage_manager_mock.save_market_data.assert_not_called()
storage_manager_mock.save_symbol_timestamp.assert_not_called()
assert isinstance(result, MarketData)
assert db.query(MarketData).filter_by(symbol="AG2606").count() == 2
def test_falls_back_to_sqlite_when_storage_raises(self, db, sample_data, storage_manager_mock, caplog):
"""StorageManager 写入异常时降级到 SQLite 写入并记录警告。"""
storage_manager_mock.save_market_data_with_timestamp.side_effect = Exception("storage down")
with patch("app.services.cache.get_storage_manager", return_value=storage_manager_mock):
from app.services import cache
with caplog.at_level(logging.WARNING, logger="app.services.cache"):
result = cache.save_market_data(db, "AG2606", sample_data)
storage_manager_mock.save_market_data_with_timestamp.assert_called_once()
storage_manager_mock.save_market_data.assert_not_called()
storage_manager_mock.save_symbol_timestamp.assert_not_called()
assert isinstance(result, MarketData)
assert db.query(MarketData).filter_by(symbol="AG2606").count() == 2
assert "StorageManager 写入失败" in caplog.text
class TestGetCachedData:
"""get_cached_data 读取与降级测试。"""
def test_uses_storage_manager_and_merges_periods(self, db, storage_manager_mock):
"""StorageManager 返回合并后的多周期数据。"""
fetched_at = datetime.now()
storage_manager_mock.get_market_data.return_value = {
"symbol": "AG2606",
"type": "futures",
"current_price": 123.45,
"timestamp": fetched_at.isoformat(),
"fetched_at": fetched_at.isoformat(),
"timeframes": {
"5min": [{"datetime": "2026-07-04T09:55:00", "open": 100, "close": 110}],
"15min": [{"datetime": "2026-07-04T09:45:00", "open": 105, "close": 115}],
},
"is_fresh": True,
}
with patch("app.services.cache.get_storage_manager", return_value=storage_manager_mock):
from app.services import cache
result = cache.get_cached_data(db, "AG2606", "futures", ["5min", "15min"])
storage_manager_mock.get_market_data.assert_called_once_with(
"AG2606", "futures", ["5min", "15min"], end_time=None, max_candles=100
)
assert result is not None
assert result["symbol"] == "AG2606"
assert result["type"] == "futures"
assert result["current_price"] == 123.45
assert result["timestamp"] == fetched_at.isoformat()
assert result["fetched_at"] == fetched_at.isoformat()
assert "5min" in result["timeframes"]
assert "15min" in result["timeframes"]
assert len(result["timeframes"]["5min"]) == 1
assert result["is_fresh"] is True
def test_falls_back_to_sqlite_when_storage_returns_none(self, db, storage_manager_mock):
"""StorageManager 未命中时降级到 SQLite 读取。"""
storage_manager_mock.get_market_data.return_value = None
_seed_sqlite_market_data(db)
with patch("app.services.cache.get_storage_manager", return_value=storage_manager_mock):
from app.services import cache
result = cache.get_cached_data(db, "AG2606", "futures", ["5min", "15min"])
assert result is not None
assert result["symbol"] == "AG2606"
assert "5min" in result["timeframes"]
assert "15min" in result["timeframes"]
def test_falls_back_to_sqlite_when_storage_raises(self, db, storage_manager_mock, caplog):
"""StorageManager 读取异常时降级到 SQLite 读取并记录警告。"""
storage_manager_mock.get_market_data.side_effect = Exception("storage down")
_seed_sqlite_market_data(db)
with patch("app.services.cache.get_storage_manager", return_value=storage_manager_mock):
from app.services import cache
with caplog.at_level(logging.WARNING, logger="app.services.cache"):
result = cache.get_cached_data(db, "AG2606", "futures", ["5min"])
assert result is not None
assert "StorageManager 读取失败" in caplog.text
def test_passes_end_time_and_max_candles_to_storage(self, db, storage_manager_mock):
"""get_cached_data 将 end_time / max_candles 透传给 StorageManager。"""
end_time = datetime(2026, 7, 4, 10, 0, 0)
with patch("app.services.cache.get_storage_manager", return_value=storage_manager_mock):
from app.services import cache
cache.get_cached_data(db, "AG2606", "futures", ["5min"], end_time=end_time, max_candles=50)
storage_manager_mock.get_market_data.assert_called_once_with(
"AG2606", "futures", ["5min"], end_time=end_time, max_candles=50
)
def test_does_not_refilter_storage_manager_results(self, db, storage_manager_mock):
"""cache.py 不再对 StorageManager 返回的数据做二次过滤,直接原样返回。"""
fetched_at = datetime.now()
def mock_get_market_data(symbol, data_type, periods, end_time=None, max_candles=100):
return {
"symbol": symbol,
"type": data_type,
"current_price": 123.45,
"timestamp": fetched_at.isoformat(),
"fetched_at": fetched_at.isoformat(),
"timeframes": {
"5min": [
{"datetime": "2026-07-04T09:50:00", "open": 100, "close": 101},
{"datetime": "2026-07-04T09:55:00", "open": 101, "close": 102},
{"datetime": "2026-07-04T10:05:00", "open": 102, "close": 103},
]
},
"is_fresh": True,
}
storage_manager_mock.get_market_data.side_effect = mock_get_market_data
with patch("app.services.cache.get_storage_manager", return_value=storage_manager_mock):
from app.services import cache
result = cache.get_cached_data(
db, "AG2606", "futures", ["5min"],
end_time=datetime(2026, 7, 4, 10, 0, 0),
max_candles=1,
)
assert result is not None
candles = result["timeframes"]["5min"]
# StorageManager 未做过滤cache.py 也不应再次过滤
assert len(candles) == 3
def test_does_not_mutate_storage_manager_result(self, db, storage_manager_mock):
"""get_cached_data 返回 StorageManager 结果时不会原地修改原对象。"""
fetched_at = datetime.now()
original = {
"symbol": "AG2606",
"type": "futures",
"current_price": 123.45,
"timestamp": fetched_at.isoformat(),
"fetched_at": fetched_at.isoformat(),
"timeframes": {
"5min": [
{"datetime": "2026-07-04T09:55:00", "open": 100, "close": 110}
]
},
"is_fresh": True,
}
storage_manager_mock.get_market_data.return_value = original
with patch("app.services.cache.get_storage_manager", return_value=storage_manager_mock):
from app.services import cache
result = cache.get_cached_data(db, "AG2606", "futures", ["5min"])
assert result is not None
assert result is not original
assert result["timeframes"]["5min"] == original["timeframes"]["5min"]
# 修改返回结果不应影响 StorageManager 返回的原对象
result["timeframes"]["5min"].append(
{"datetime": "2026-07-04T10:00:00", "open": 111, "close": 112}
)
assert len(original["timeframes"]["5min"]) == 1
def test_queries_all_periods_when_periods_is_none(self, db, storage_manager_mock):
"""periods=None 时优先走 StorageManager 查询全部周期。"""
fetched_at = datetime.now()
def mock_get_market_data(symbol, data_type, periods=None, end_time=None, max_candles=100):
return {
"symbol": symbol,
"type": data_type,
"current_price": 123.45,
"timestamp": fetched_at.isoformat(),
"fetched_at": fetched_at.isoformat(),
"timeframes": {"5min": [], "15min": []},
"is_fresh": True,
}
storage_manager_mock.get_market_data.side_effect = mock_get_market_data
with patch("app.services.cache.get_storage_manager", return_value=storage_manager_mock):
from app.services import cache
result = cache.get_cached_data(db, "AG2606", "futures", periods=None)
storage_manager_mock.get_market_data.assert_called_once_with(
"AG2606", "futures", None, end_time=None, max_candles=100
)
assert result is not None
assert "5min" in result["timeframes"]
assert "15min" in result["timeframes"]
class TestCacheStatus:
"""is_cache_valid / check_cache_status / get_latest_cached 存储层兼容测试。"""
def _make_merged_result(self, symbol="AG2606", data_type="futures", periods=None, age_seconds=0):
fetched_at = datetime.now() - __import__("datetime").timedelta(seconds=age_seconds)
timeframes = {}
for p in (periods or ["5min", "15min"]):
timeframes[p] = [{"datetime": fetched_at.isoformat(), "open": 100, "close": 110}]
return {
"symbol": symbol,
"type": data_type,
"current_price": 123.45,
"timestamp": fetched_at.isoformat(),
"fetched_at": fetched_at.isoformat(),
"timeframes": timeframes,
"is_fresh": True,
}
def test_is_cache_valid_uses_storage_when_available(self, db, storage_manager_mock):
"""StorageManager 可用时优先判断缓存有效性。"""
storage_manager_mock.get_market_data.return_value = self._make_merged_result(age_seconds=10)
with patch("app.services.cache.get_storage_manager", return_value=storage_manager_mock):
from app.services import cache
assert cache.is_cache_valid(db, "AG2606", "futures", "5min") is True
storage_manager_mock.get_market_data.assert_called_once_with(
"AG2606", "futures", ["5min"]
)
def test_is_cache_valid_falls_back_to_sqlite(self, db, storage_manager_mock):
"""StorageManager 无数据时降级到 SQLite 判断缓存有效性。"""
storage_manager_mock.get_market_data.return_value = None
_seed_sqlite_market_data(db)
with patch("app.services.cache.get_storage_manager", return_value=storage_manager_mock):
from app.services import cache
assert cache.is_cache_valid(db, "AG2606", "futures", "5min") is True
def test_check_cache_status_uses_storage_when_available(self, db, storage_manager_mock):
"""StorageManager 可用时优先检查多周期缓存状态。"""
storage_manager_mock.get_market_data.return_value = self._make_merged_result()
with patch("app.services.cache.get_storage_manager", return_value=storage_manager_mock):
from app.services import cache
status = cache.check_cache_status(db, "AG2606", "futures", ["5min", "15min"])
assert status["all_valid"] is True
assert set(status["valid_periods"]) == {"5min", "15min"}
assert status["missing_periods"] == []
def test_check_cache_status_falls_back_to_sqlite(self, db, storage_manager_mock):
"""StorageManager 无数据时降级到 SQLite 检查多周期缓存状态。"""
storage_manager_mock.get_market_data.return_value = None
_seed_sqlite_market_data(db)
with patch("app.services.cache.get_storage_manager", return_value=storage_manager_mock):
from app.services import cache
status = cache.check_cache_status(db, "AG2606", "futures", ["5min", "15min"])
assert status["all_valid"] is True
assert set(status["valid_periods"]) == {"5min", "15min"}
def test_get_latest_cached_uses_storage_when_available(self, db, storage_manager_mock):
"""StorageManager 可用时优先获取最新缓存记录。"""
storage_manager_mock.get_market_data.return_value = self._make_merged_result()
with patch("app.services.cache.get_storage_manager", return_value=storage_manager_mock):
from app.services import cache
records = cache.get_latest_cached(db, "AG2606", "futures")
assert len(records) == 2
periods = {r.period for r in records}
assert periods == {"5min", "15min"}
assert all(isinstance(r, MarketData) for r in records)
def test_get_latest_cached_falls_back_to_sqlite(self, db, storage_manager_mock):
"""StorageManager 无数据时降级到 SQLite 获取最新缓存记录。"""
storage_manager_mock.get_market_data.return_value = None
_seed_sqlite_market_data(db)
with patch("app.services.cache.get_storage_manager", return_value=storage_manager_mock):
from app.services import cache
records = cache.get_latest_cached(db, "AG2606", "futures")
assert len(records) == 2
periods = {r.period for r in records}
assert periods == {"5min", "15min"}
class TestSymbolTimestamp:
"""合约时间戳函数封装测试。"""
def test_update_symbol_timestamp_uses_storage_when_available(self, db, storage_manager_mock):
"""StorageManager 可用时优先写入合约时间戳。"""
refresh_time = datetime(2026, 7, 4, 10, 0, 0)
with patch("app.services.cache.get_storage_manager", return_value=storage_manager_mock):
from app.services import cache
cache.update_symbol_timestamp(db, "AG2606", "futures", refresh_time)
storage_manager_mock.save_symbol_timestamp.assert_called_once_with("AG2606", "futures", refresh_time)
sqlite_record = db.query(SymbolTimestamp).filter_by(symbol="AG2606").first()
assert sqlite_record is None
def test_update_symbol_timestamp_falls_back_to_sqlite(self, db, storage_manager_mock):
"""StorageManager 不可用时降级到 SQLite 写入合约时间戳。"""
storage_manager_mock.is_available.return_value = False
refresh_time = datetime(2026, 7, 4, 10, 0, 0)
with patch("app.services.cache.get_storage_manager", return_value=storage_manager_mock):
from app.services import cache
cache.update_symbol_timestamp(db, "AG2606", "futures", refresh_time)
storage_manager_mock.save_symbol_timestamp.assert_not_called()
sqlite_record = db.query(SymbolTimestamp).filter_by(symbol="AG2606").first()
assert sqlite_record is not None
assert sqlite_record.last_refresh_at == refresh_time
assert sqlite_record.refresh_count == 1
def test_update_symbol_timestamp_falls_back_to_sqlite_when_storage_returns_false(self, db, storage_manager_mock):
"""StorageManager 可用但返回 False 时降级到 SQLite 写入合约时间戳。"""
storage_manager_mock.save_symbol_timestamp.return_value = False
refresh_time = datetime(2026, 7, 4, 10, 0, 0)
with patch("app.services.cache.get_storage_manager", return_value=storage_manager_mock):
from app.services import cache
cache.update_symbol_timestamp(db, "AG2606", "futures", refresh_time)
storage_manager_mock.save_symbol_timestamp.assert_called_once_with("AG2606", "futures", refresh_time)
sqlite_record = db.query(SymbolTimestamp).filter_by(symbol="AG2606").first()
assert sqlite_record is not None
assert sqlite_record.last_refresh_at == refresh_time
assert sqlite_record.refresh_count == 1
def test_update_symbol_timestamp_falls_back_to_sqlite_when_storage_raises(self, db, storage_manager_mock, caplog):
"""StorageManager 可用但写入异常时降级到 SQLite 写入合约时间戳并记录警告。"""
storage_manager_mock.save_symbol_timestamp.side_effect = Exception("mysql down")
refresh_time = datetime(2026, 7, 4, 10, 0, 0)
with patch("app.services.cache.get_storage_manager", return_value=storage_manager_mock):
from app.services import cache
with caplog.at_level(logging.WARNING, logger="app.services.cache"):
cache.update_symbol_timestamp(db, "AG2606", "futures", refresh_time)
storage_manager_mock.save_symbol_timestamp.assert_called_once_with("AG2606", "futures", refresh_time)
sqlite_record = db.query(SymbolTimestamp).filter_by(symbol="AG2606").first()
assert sqlite_record is not None
assert sqlite_record.last_refresh_at == refresh_time
assert sqlite_record.refresh_count == 1
assert "StorageManager 时间戳写入失败" in caplog.text
def test_get_symbol_timestamp_uses_storage_when_available(self, db, storage_manager_mock):
"""StorageManager 可用时优先读取合约时间戳。"""
storage_manager_mock.get_symbol_timestamp.return_value = {
"last_refresh_at": datetime(2026, 7, 4, 10, 0, 0).isoformat(),
"refresh_count": 42,
}
with patch("app.services.cache.get_storage_manager", return_value=storage_manager_mock):
from app.services import cache
result = cache.get_symbol_timestamp(db, "AG2606", "futures")
storage_manager_mock.get_symbol_timestamp.assert_called_once_with("AG2606", "futures")
assert result == datetime(2026, 7, 4, 10, 0, 0)
def test_get_symbol_timestamp_falls_back_to_sqlite(self, db, storage_manager_mock):
"""StorageManager 未命中时降级到 SQLite 读取合约时间戳。"""
storage_manager_mock.get_symbol_timestamp.return_value = None
_seed_sqlite_symbol_timestamp(db)
with patch("app.services.cache.get_storage_manager", return_value=storage_manager_mock):
from app.services import cache
result = cache.get_symbol_timestamp(db, "AG2606", "futures")
assert result == datetime(2026, 7, 4, 10, 0, 0)

@ -1,197 +0,0 @@
"""配置存储测试MySQL + JSON fallback。"""
import json
from pathlib import Path
from unittest.mock import MagicMock, patch
import pytest
from app.config_store import ConfigStore
def _make_session_maker(mock_db):
"""构造正确的 sessionmaker mock使 with 语句返回 mock_db。"""
session_obj = MagicMock()
session_obj.__enter__ = MagicMock(return_value=mock_db)
session_obj.__exit__ = MagicMock(return_value=False)
session_maker = MagicMock(return_value=session_obj)
return session_maker
class TestConfigStoreGet:
"""ConfigStore.get_config 测试。"""
def test_get_config_returns_mysql_value_on_hit(self, tmp_path):
"""MySQL 命中时返回数据库中的配置。"""
mock_config = MagicMock()
mock_config.config_value = {"futures": {"沪银": "AG2608"}}
mock_db = MagicMock()
mock_db.query.return_value.filter.return_value.first.return_value = mock_config
storage = MagicMock()
storage.check_mysql.return_value = True
store = ConfigStore(
storage_manager=storage,
config_dir=tmp_path,
session_maker=_make_session_maker(mock_db),
)
result = store.get_config("symbols", {"futures": {}})
assert result == {"futures": {"沪银": "AG2608"}}
def test_get_config_reads_json_and_backfills_when_mysql_miss(self, tmp_path):
"""MySQL 未命中时读取 JSON 并回填数据库。"""
json_path = tmp_path / "symbols_config.json"
json_path.write_text(json.dumps({"futures": {"沪银": "AG2608"}}, ensure_ascii=False), encoding="utf-8")
mock_db = MagicMock()
mock_db.query.return_value.filter.return_value.first.return_value = None
storage = MagicMock()
storage.check_mysql.return_value = True
store = ConfigStore(
storage_manager=storage,
config_dir=tmp_path,
session_maker=_make_session_maker(mock_db),
)
result = store.get_config("symbols", {"futures": {}})
assert result == {"futures": {"沪银": "AG2608"}}
mock_db.add.assert_called_once()
mock_db.commit.assert_called_once()
def test_get_config_falls_back_to_json_when_mysql_unavailable(self, tmp_path):
"""MySQL 不可用时直接读取 JSON。"""
json_path = tmp_path / "symbols_config.json"
json_path.write_text(json.dumps({"futures": {"沪银": "AG2608"}}, ensure_ascii=False), encoding="utf-8")
storage = MagicMock()
storage.check_mysql.return_value = False
store = ConfigStore(
storage_manager=storage,
config_dir=tmp_path,
session_maker=None,
)
result = store.get_config("symbols", {"futures": {}})
assert result == {"futures": {"沪银": "AG2608"}}
def test_get_config_returns_fallback_when_no_mysql_and_no_json(self, tmp_path):
"""MySQL 和 JSON 都不存在时返回 fallback。"""
storage = MagicMock()
storage.check_mysql.return_value = False
store = ConfigStore(
storage_manager=storage,
config_dir=tmp_path,
session_maker=None,
)
result = store.get_config("symbols", {"futures": {"默认": "DF2609"}})
assert result == {"futures": {"默认": "DF2609"}}
class TestConfigStoreSet:
"""ConfigStore.set_config 测试。"""
def test_set_config_writes_to_mysql_and_json(self, tmp_path):
"""MySQL 可用时同时写入数据库和 JSON。"""
mock_existing = MagicMock()
mock_db = MagicMock()
mock_db.query.return_value.filter.return_value.first.return_value = mock_existing
storage = MagicMock()
storage.check_mysql.return_value = True
store = ConfigStore(
storage_manager=storage,
config_dir=tmp_path,
session_maker=_make_session_maker(mock_db),
)
result = store.set_config("symbols", {"futures": {"沪银": "AG2608"}})
assert result is True
assert mock_existing.config_value == {"futures": {"沪银": "AG2608"}}
mock_db.commit.assert_called_once()
json_path = tmp_path / "symbols_config.json"
assert json_path.exists()
assert json.loads(json_path.read_text(encoding="utf-8")) == {"futures": {"沪银": "AG2608"}}
def test_set_config_writes_only_json_when_mysql_unavailable(self, tmp_path):
"""MySQL 不可用时只写入 JSON。"""
storage = MagicMock()
storage.check_mysql.return_value = False
store = ConfigStore(
storage_manager=storage,
config_dir=tmp_path,
session_maker=None,
)
result = store.set_config("symbols", {"futures": {"沪银": "AG2608"}})
assert result is True
json_path = tmp_path / "symbols_config.json"
assert json_path.exists()
assert json.loads(json_path.read_text(encoding="utf-8")) == {"futures": {"沪银": "AG2608"}}
class TestConfigMigration:
"""配置迁移测试。"""
def test_migrate_skips_when_config_exists(self, tmp_path):
"""数据库已有配置时跳过迁移。"""
from app.config_migration import migrate_configs_to_mysql
with patch("app.config_migration.get_config_store") as mock_get_store:
store = MagicMock()
store._config_exists_in_mysql.return_value = True
store.storage_manager.check_mysql.return_value = True
store.session_maker = MagicMock()
mock_get_store.return_value = store
result = migrate_configs_to_mysql()
assert result is True
store._load_json.assert_not_called()
def test_migrate_loads_json_and_saves(self, tmp_path):
"""从 JSON 读取并保存到数据库。"""
from app.config_migration import migrate_configs_to_mysql
symbols_path = tmp_path / "symbols_config.json"
symbols_path.write_text(json.dumps({"futures": {"沪银": "AG2608"}}, ensure_ascii=False), encoding="utf-8")
ai_path = tmp_path / "ai_config.json"
ai_path.write_text(json.dumps({"models": []}, ensure_ascii=False), encoding="utf-8")
with patch("app.config_migration.get_config_store") as mock_get_store:
store = MagicMock()
store._config_exists_in_mysql.return_value = False
store.storage_manager.check_mysql.return_value = True
store.session_maker = MagicMock()
store.config_dir = tmp_path
store.config_files = {
"symbols": symbols_path,
"ai": ai_path,
}
store._load_json.side_effect = lambda key, default: json.loads(store.config_files[key].read_text(encoding="utf-8")) if store.config_files[key].exists() else default
store._save_to_mysql.return_value = True
mock_get_store.return_value = store
result = migrate_configs_to_mysql()
assert result is True
assert store._save_to_mysql.call_count == 2

@ -1,279 +0,0 @@
"""
数据缓冲平台 - 双写一致性与数据迁移完整性验证测试
本测试通过内存 Fake Redis mock/fake MySQL 验证
1. save_market_data 成功后 MySQL Redis 数据内容一致
2. Redis 写入失败不影响 MySQL 持久化
3. migrate_sqlite_to_mysql 的幂等性与迁移记录数正确性
4. 使用真实内存数据库做端到端迁移验证时暴露的生产代码缺陷
"""
import json
from datetime import datetime
from unittest.mock import MagicMock, patch
import pytest
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
from app.models import Base, MarketData, SymbolTimestamp
from app.storage_manager import StorageManager
class FakeRedis:
"""内存模拟 Redis 客户端,支持 setex / get / delete / keys / ping。"""
def __init__(self, fail_on_write=False):
self._store = {}
self.fail_on_write = fail_on_write
def ping(self):
return True
def get(self, key):
return self._store.get(key)
def setex(self, key, seconds, value):
if self.fail_on_write:
raise Exception("Redis 写入失败")
self._store[key] = value
def delete(self, *keys):
if self.fail_on_write:
raise Exception("Redis 删除失败")
for key in keys:
self._store.pop(key, None)
def keys(self, pattern):
prefix = pattern.replace("*", "")
return [k for k in self._store.keys() if k.startswith(prefix)]
def _make_mysql_memory():
"""创建内存 MySQL 模拟引擎和会话工厂。"""
engine = create_engine("sqlite:///:memory:")
Base.metadata.create_all(bind=engine)
SessionLocal = sessionmaker(bind=engine)
return engine, SessionLocal
def _create_sqlite_source(tmp_path, market_count=2, timestamp_count=1):
"""创建包含测试数据的 SQLite 源数据库,并返回引擎与记录数。"""
db_path = tmp_path / "test_source.db"
engine = create_engine(f"sqlite:///{db_path}")
Base.metadata.create_all(bind=engine)
Session = sessionmaker(bind=engine)
session = Session()
fetched_at = datetime(2026, 7, 4, 10, 0, 0)
for i in range(market_count):
session.add(
MarketData(
symbol="AG2606",
data_type="futures",
period=f"{(i + 1) * 5}min",
candles_json='[{"open": 100, "close": 110}]',
current_price=123.45,
fetched_at=fetched_at,
candle_count=1,
)
)
for _ in range(timestamp_count):
session.add(
SymbolTimestamp(
symbol="AG2606",
data_type="futures",
last_refresh_at=fetched_at,
refresh_count=5,
)
)
session.commit()
session.close()
return engine, market_count, timestamp_count
def _make_mysql_session(market_data_count=0, symbol_timestamp_count=0):
"""构造模拟 MySQL 会话,支持记录写入和计数查询。"""
mysql_session = MagicMock()
mysql_session.__enter__ = MagicMock(return_value=mysql_session)
mysql_session.__exit__ = MagicMock(return_value=False)
added_market_data = []
added_symbol_timestamps = []
def mock_query(model):
query = MagicMock()
if model is MarketData:
query.count.return_value = market_data_count
elif model is SymbolTimestamp:
query.count.return_value = symbol_timestamp_count
return query
mysql_session.query.side_effect = mock_query
mysql_session.add_all.side_effect = lambda records: (
added_market_data.extend(records)
if records and isinstance(records[0], MarketData)
else added_symbol_timestamps.extend(records)
)
return mysql_session, added_market_data, added_symbol_timestamps
@pytest.fixture
def sample_market_data():
"""构造与采集脚本格式一致的测试数据。"""
return {
"type": "futures",
"current_price": 123.45,
"timestamp": datetime(2026, 7, 4, 10, 0, 0).isoformat(),
"timeframes": {
"5min": [{"open": 100, "close": 110}],
"15min": [{"open": 105, "close": 115}],
},
}
class TestDualWriteConsistency:
"""双写一致性验证。"""
def test_save_market_data_writes_consistent_data_to_mysql_and_redis(
self, sample_market_data
):
"""save_market_data 成功后MySQL 与 Redis 中数据内容一致。"""
redis_client = FakeRedis()
mysql_engine, MySQLSessionLocal = _make_mysql_memory()
manager = StorageManager(redis_client=redis_client, mysql_engine=mysql_engine)
result = manager.save_market_data("AG2606", sample_market_data)
assert result is True
# 验证 MySQL 持久化数据
with MySQLSessionLocal() as db:
records = db.query(MarketData).filter_by(symbol="AG2606").all()
assert len(records) == 2
mysql_by_period = {r.period: r for r in records}
assert "5min" in mysql_by_period
assert "15min" in mysql_by_period
assert mysql_by_period["5min"].current_price == 123.45
assert mysql_by_period["15min"].current_price == 123.45
# 验证 Redis 缓存数据
redis_5min = json.loads(redis_client.get("market_data:AG2606:5min"))
redis_15min = json.loads(redis_client.get("market_data:AG2606:15min"))
assert redis_5min["current_price"] == 123.45
assert redis_15min["current_price"] == 123.45
assert redis_5min["candles"] == [{"open": 100, "close": 110}]
assert redis_15min["candles"] == [{"open": 105, "close": 115}]
# 验证 MySQL 与 Redis 内容一致
assert (
mysql_by_period["5min"].current_price == redis_5min["current_price"]
)
assert (
mysql_by_period["15min"].current_price == redis_15min["current_price"]
)
assert (
json.loads(mysql_by_period["5min"].candles_json) == redis_5min["candles"]
)
assert (
json.loads(mysql_by_period["15min"].candles_json)
== redis_15min["candles"]
)
def test_redis_write_failure_does_not_affect_mysql_persistence(
self, sample_market_data
):
"""Redis 写入失败时MySQL 数据持久化不受影响save_market_data 仍返回 True。"""
redis_client = FakeRedis(fail_on_write=True)
mysql_engine, MySQLSessionLocal = _make_mysql_memory()
manager = StorageManager(redis_client=redis_client, mysql_engine=mysql_engine)
result = manager.save_market_data("AG2606", sample_market_data)
assert result is True
# 验证 MySQL 仍有完整数据
with MySQLSessionLocal() as db:
records = db.query(MarketData).filter_by(symbol="AG2606").all()
assert len(records) == 2
periods = {r.period for r in records}
assert periods == {"5min", "15min"}
# 验证 Redis 无缓存写入
assert redis_client.get("market_data:AG2606:5min") is None
assert redis_client.get("market_data:AG2606:15min") is None
class TestMigrationIntegrity:
"""数据迁移完整性验证。"""
def test_migration_copies_expected_record_counts_from_sqlite_to_mysql(
self, tmp_path
):
"""MySQL 为空时migrate_sqlite_to_mysql 迁移 SQLite 中全部记录。"""
sqlite_engine, sqlite_market_count, sqlite_timestamp_count = (
_create_sqlite_source(tmp_path)
)
mysql_session, added_market_data, added_symbol_timestamps = (
_make_mysql_session(market_data_count=0, symbol_timestamp_count=0)
)
with patch("app.migration.create_engine", return_value=sqlite_engine):
with patch(
"app.migration.MySQLSessionLocal", return_value=mysql_session
):
from app.migration import migrate_sqlite_to_mysql
result = migrate_sqlite_to_mysql()
assert result is True
assert len(added_market_data) == sqlite_market_count
assert len(added_symbol_timestamps) == sqlite_timestamp_count
assert added_market_data[0].symbol == "AG2606"
assert added_market_data[0].period == "5min"
assert added_symbol_timestamps[0].symbol == "AG2606"
mysql_session.commit.assert_called_once()
def test_migration_is_idempotent_when_mysql_has_data(self, tmp_path):
"""MySQL 已有数据时迁移被跳过,保持幂等性,不覆盖已有数据。"""
sqlite_engine, _, _ = _create_sqlite_source(tmp_path)
mysql_session, added_market_data, added_symbol_timestamps = (
_make_mysql_session(market_data_count=1, symbol_timestamp_count=1)
)
with patch("app.migration.create_engine", return_value=sqlite_engine):
with patch(
"app.migration.MySQLSessionLocal", return_value=mysql_session
):
from app.migration import migrate_sqlite_to_mysql
result = migrate_sqlite_to_mysql()
assert result is False
assert len(added_market_data) == 0
assert len(added_symbol_timestamps) == 0
mysql_session.commit.assert_not_called()
def test_migration_end_to_end_with_in_memory_databases(self, tmp_path):
"""使用真实内存数据库验证迁移前后数据条数一致(当前已知缺陷)。"""
sqlite_engine, sqlite_market_count, sqlite_timestamp_count = (
_create_sqlite_source(tmp_path)
)
mysql_engine, MySQLSessionLocal = _make_mysql_memory()
with patch("app.migration.create_engine", return_value=sqlite_engine):
with patch("app.migration.MySQLSessionLocal", MySQLSessionLocal):
from app.migration import migrate_sqlite_to_mysql
result = migrate_sqlite_to_mysql()
assert result is True
mysql_session = MySQLSessionLocal()
try:
assert mysql_session.query(MarketData).count() == sqlite_market_count
assert (
mysql_session.query(SymbolTimestamp).count() == sqlite_timestamp_count
)
finally:
mysql_session.close()

@ -1,375 +0,0 @@
"""
降级场景验证测试
覆盖
1. Redis 不可用但 MySQL 可用时自动降级到 MySQL
2. Redis MySQL 均不可用时自动降级到 SQLite
3. 各降级场景下接口正常返回 500 错误
4. 恢复 Redis 服务后等待惰性检测间隔验证自动恢复
实现说明
- 使用 FastAPI TestClient 验证接口层行为
- 使用内存 SQLite 引擎作为 MySQL 替身StorageManager 基于 SQLAlchemy 通用接口
- 通过 patch `app.services.cache.get_storage_manager` 注入已配置好的 StorageManager
从而绕过当前 `app/main.py` 启动时尚未将初始化后的 Redis/MySQL 客户端注入 StorageManager
全局单例的问题专注于验证 cache / API 层的降级与恢复逻辑
"""
import json
import logging
import time
from datetime import datetime
from unittest.mock import MagicMock, patch
import pytest
from fastapi.testclient import TestClient
from sqlalchemy import create_engine, text
from sqlalchemy.orm import sessionmaker
from sqlalchemy.pool import StaticPool
from app.models import Base, MarketData
from app.storage_manager import StorageManager
# test_main_lifespan.py 中的 fixture 会 patch app.main.Base.metadata.create_all 且未正确恢复,
# 导致后续依赖 create_all 的测试失败。这里保留原始方法引用,必要时恢复。
_original_create_all = Base.metadata.create_all
# ===== Fixtures =====
@pytest.fixture
def sqlite_engine():
"""应用主数据库使用的内存 SQLite 引擎。"""
# 防御:修复上游 fixture 对 Base.metadata.create_all 的 patch 泄漏
if isinstance(Base.metadata.create_all, MagicMock):
Base.metadata.create_all = _original_create_all
engine = create_engine(
"sqlite:///:memory:",
connect_args={"check_same_thread": False},
poolclass=StaticPool,
)
Base.metadata.create_all(bind=engine)
# 确认表已创建
with engine.connect() as conn:
result = conn.execute(
text("SELECT name FROM sqlite_master WHERE type='table' AND name='market_data'")
)
assert result.fetchone() is not None
yield engine
engine.dispose()
@pytest.fixture
def mysql_engine():
"""作为 MySQL 替身的内存 SQLite 引擎StorageManager 使用 SQLAlchemy 通用接口)。"""
# 防御:修复上游 fixture 对 Base.metadata.create_all 的 patch 泄漏
if isinstance(Base.metadata.create_all, MagicMock):
Base.metadata.create_all = _original_create_all
engine = create_engine(
"sqlite:///:memory:",
connect_args={"check_same_thread": False},
poolclass=StaticPool,
)
Base.metadata.create_all(bind=engine)
# 确认表已创建
with engine.connect() as conn:
result = conn.execute(
text("SELECT name FROM sqlite_master WHERE type='table' AND name='market_data'")
)
assert result.fetchone() is not None
yield engine
engine.dispose()
@pytest.fixture
def app_with_db(sqlite_engine):
"""返回替换 get_db 依赖为内存 SQLite 的 FastAPI app。"""
from app.main import app
from app.database import get_db as original_get_db
SessionLocal = sessionmaker(autocommit=False, autoflush=False, bind=sqlite_engine)
def override_get_db():
db = SessionLocal()
try:
yield db
finally:
db.close()
app.dependency_overrides[original_get_db] = override_get_db
yield app
app.dependency_overrides.clear()
@pytest.fixture
def patch_lifespan_deps():
"""Patch lifespan 依赖,避免真实连接数据库/Redis/MySQL 和启动调度器。"""
mock_db = MagicMock()
mock_session_local = MagicMock(return_value=mock_db)
patches = [
patch("app.main.Base.metadata.create_all"),
patch("app.main.UserBase.metadata.create_all"),
patch("app.analysis_db.init_analysis_db"),
patch("app.database.SessionLocal", mock_session_local),
patch("app.auth_service.create_default_admin"),
patch("app.main.start_scheduler"),
patch("app.services.cache.list_tasks", return_value=[]),
patch("app.services.scheduler.add_job"),
patch("app.main.stop_scheduler"),
patch("app.redis_client.init_redis"),
patch("app.mysql_database.init_mysql"),
]
started = [p.start() for p in patches]
yield {
"Base_create_all": started[0],
"UserBase_create_all": started[1],
"init_analysis_db": started[2],
"SessionLocal": started[3],
"create_default_admin": started[4],
"start_scheduler": started[5],
"list_tasks": started[6],
"add_job": started[7],
"stop_scheduler": started[8],
"init_redis": started[9],
"init_mysql": started[10],
}
for p in patches:
p.stop()
class FakeRedis:
"""可切换可用状态的轻量级 Redis 替身。"""
def __init__(self, available=True):
self._store = {}
self._available = available
def set_available(self, available):
self._available = available
def ping(self):
if not self._available:
raise Exception("redis down")
return True
def get(self, key):
return self._store.get(key)
def setex(self, key, ttl, value):
self._store[key] = value
def delete(self, *keys):
for key in keys:
self._store.pop(key, None)
def keys(self, pattern):
prefix = pattern.rstrip("*")
return [k for k in self._store if k.startswith(prefix)]
# ===== Helpers =====
def _seed_market_data(
engine,
symbol="AG2606",
data_type="futures",
period="5min",
current_price=123.45,
):
"""在指定引擎中写入一条行情数据。"""
Session = sessionmaker(bind=engine)
with Session() as db:
db.add(
MarketData(
symbol=symbol,
data_type=data_type,
period=period,
candles_json=json.dumps(
[
{
"datetime": "2026-07-04T09:55:00",
"open": 100,
"high": 115,
"low": 95,
"close": 110,
"volume": 1000,
}
]
),
current_price=current_price,
fetched_at=datetime(2026, 7, 4, 10, 0, 0),
candle_count=1,
)
)
db.commit()
# ===== Lifespan 日志测试 =====
class TestLifespanFallbackLogs:
"""启动时降级检测日志测试。"""
@pytest.mark.asyncio
async def test_logs_mysql_mode_when_redis_unavailable(
self, patch_lifespan_deps, caplog
):
"""Redis 不可用但 MySQL 可用时lifespan 应输出 MySQL 降级模式日志。"""
from app.main import lifespan, app
patch_lifespan_deps["init_redis"].return_value = None
patch_lifespan_deps["init_mysql"].return_value = MagicMock()
with caplog.at_level(logging.WARNING, logger="app.main"):
async with lifespan(app):
pass
assert "存储模式: MySQL (Redis 不可用)" in caplog.text
@pytest.mark.asyncio
async def test_logs_sqlite_mode_when_both_unavailable(
self, patch_lifespan_deps, caplog
):
"""Redis 和 MySQL 均不可用时lifespan 应输出 SQLite 降级模式日志。"""
from app.main import lifespan, app
patch_lifespan_deps["init_redis"].return_value = None
patch_lifespan_deps["init_mysql"].return_value = None
with caplog.at_level(logging.ERROR, logger="app.main"):
async with lifespan(app):
pass
assert "存储模式: SQLite (Redis 和 MySQL 均不可用)" in caplog.text
# ===== StorageManager 运行时降级与恢复测试 =====
class TestStorageManagerFallback:
"""StorageManager 运行时降级与恢复测试。"""
def test_falls_back_to_mysql_when_redis_unavailable(self, mysql_engine):
"""Redis 不可用但 MySQL 可用时,从 MySQL 读取数据。"""
_seed_market_data(mysql_engine, current_price=123.45)
fake_redis = FakeRedis(available=False)
manager = StorageManager(redis_client=fake_redis, mysql_engine=mysql_engine)
result = manager.get_market_data("AG2606", "futures", "5min")
assert result is not None
assert result["current_price"] == 123.45
def test_returns_none_when_both_unavailable(self):
"""Redis 和 MySQL 均不可用时StorageManager 返回 None由调用方降级到 SQLite"""
fake_redis = FakeRedis(available=False)
manager = StorageManager(redis_client=fake_redis, mysql_engine=None)
result = manager.get_market_data("AG2606", "futures", "5min")
assert result is None
def test_recovers_to_redis_after_interval(self, mysql_engine):
"""Redis 恢复后,超过惰性检测间隔应重新使用 Redis 并回填缓存。"""
_seed_market_data(mysql_engine, current_price=123.45)
fake_redis = FakeRedis(available=False)
manager = StorageManager(
redis_client=fake_redis, mysql_engine=mysql_engine, check_interval=0.1
)
# Redis 不可用,首次读取应来自 MySQL
result = manager.get_market_data("AG2606", "futures", "5min")
assert result["current_price"] == 123.45
# Redis 不可用,不应有回填
assert fake_redis.get("market_data:AG2606:5min") is None
# 恢复 Redis
fake_redis.set_available(True)
# 等待检测间隔过期
time.sleep(0.15)
# 再次读取Redis ping 通过get 返回 None回源 MySQL 后回填 Redis
result = manager.get_market_data("AG2606", "futures", "5min")
assert result["current_price"] == 123.45
assert fake_redis.get("market_data:AG2606:5min") is not None
# ===== API 接口降级测试 =====
class TestApiFallbackResponses:
"""API 接口在不同存储模式下的响应测试。"""
def test_api_returns_mysql_data_when_redis_unavailable(
self, patch_lifespan_deps, app_with_db, sqlite_engine, mysql_engine
):
"""Redis 不可用但 MySQL 可用时,接口从 MySQL 返回数据且无 500 错误。"""
_seed_market_data(mysql_engine, current_price=123.45)
_seed_market_data(sqlite_engine, current_price=456.78)
fake_redis = FakeRedis(available=False)
storage_manager = StorageManager(
redis_client=fake_redis, mysql_engine=mysql_engine, check_interval=0.1
)
patch_lifespan_deps["init_redis"].return_value = None
patch_lifespan_deps["init_mysql"].return_value = mysql_engine
with patch("app.mysql_database.mysql_engine", mysql_engine):
with patch("app.services.cache.get_storage_manager", return_value=storage_manager):
with TestClient(app_with_db) as client:
response = client.get("/api/v1/data/latest/AG2606?period=5min")
assert response.status_code == 200
data = response.json()
assert data["current_price"] == 123.45
def test_api_returns_sqlite_data_when_both_unavailable(
self, patch_lifespan_deps, app_with_db, sqlite_engine
):
"""Redis 和 MySQL 均不可用时,接口降级到 SQLite 返回数据且无 500 错误。"""
_seed_market_data(sqlite_engine, current_price=456.78)
fake_redis = FakeRedis(available=False)
storage_manager = StorageManager(
redis_client=fake_redis, mysql_engine=None, check_interval=0.1
)
patch_lifespan_deps["init_redis"].return_value = None
patch_lifespan_deps["init_mysql"].return_value = None
with patch("app.services.cache.get_storage_manager", return_value=storage_manager):
with TestClient(app_with_db) as client:
response = client.get("/api/v1/data/latest/AG2606?period=5min")
assert response.status_code == 200
data = response.json()
assert data["current_price"] == 456.78
def test_api_returns_404_not_500_when_no_data_anywhere(
self, patch_lifespan_deps, app_with_db
):
"""任何存储层均无数据时,接口应返回 404 而非 500。"""
fake_redis = FakeRedis(available=False)
storage_manager = StorageManager(
redis_client=fake_redis, mysql_engine=None, check_interval=0.1
)
patch_lifespan_deps["init_redis"].return_value = None
patch_lifespan_deps["init_mysql"].return_value = None
with patch("app.services.cache.get_storage_manager", return_value=storage_manager):
with TestClient(app_with_db) as client:
response = client.get("/api/v1/data/latest/UNKNOWN?period=5min")
assert response.status_code == 404

@ -1,185 +0,0 @@
import logging
from unittest.mock import MagicMock, patch
import pytest
@pytest.fixture
def patch_lifespan_deps():
"""Patch all dependencies around lifespan so only storage init is exercised."""
mock_db = MagicMock()
mock_session_local = MagicMock(return_value=mock_db)
patches = [
patch("app.main.Base.metadata.create_all"),
patch("app.main.UserBase.metadata.create_all"),
patch("app.analysis_db.init_analysis_db"),
patch("app.database.SessionLocal", mock_session_local),
patch("app.auth_service.create_default_admin"),
patch("app.main.start_scheduler"),
patch("app.services.cache.list_tasks", return_value=[]),
patch("app.services.scheduler.add_job"),
patch("app.main.stop_scheduler"),
patch("app.redis_client.init_redis"),
patch("app.mysql_database.init_mysql"),
]
started = [p.start() for p in patches]
yield {
"Base_create_all": started[0],
"UserBase_create_all": started[1],
"init_analysis_db": started[2],
"SessionLocal": started[3],
"create_default_admin": started[4],
"start_scheduler": started[5],
"list_tasks": started[6],
"add_job": started[7],
"stop_scheduler": started[8],
"init_redis": started[9],
"init_mysql": started[10],
}
for p in patches:
p.stop()
# 清理 StorageManager 全局单例,避免测试间状态泄漏
import app.storage_manager as _sm_module
_sm_module._storage_manager = None
@pytest.mark.asyncio
async def test_lifespan_calls_redis_and_mysql_init(patch_lifespan_deps, caplog):
""" lifespan 应调用 Redis 与 MySQL 初始化函数。 """
from app.main import lifespan, app
patch_lifespan_deps["init_redis"].return_value = MagicMock()
patch_lifespan_deps["init_mysql"].return_value = MagicMock()
with caplog.at_level(logging.INFO, logger="app.main"):
async with lifespan(app):
pass
patch_lifespan_deps["init_redis"].assert_called_once()
patch_lifespan_deps["init_mysql"].assert_called_once()
@pytest.mark.asyncio
async def test_lifespan_triggers_migration_when_mysql_ok(patch_lifespan_deps):
""" MySQL 可用时lifespan 应触发 SQLite 到 MySQL 的迁移。 """
from app.main import lifespan, app
patch_lifespan_deps["init_redis"].return_value = None
patch_lifespan_deps["init_mysql"].return_value = MagicMock()
with patch("app.migration.migrate_sqlite_to_mysql") as mock_migrate:
async with lifespan(app):
pass
mock_migrate.assert_called_once()
@pytest.mark.asyncio
async def test_lifespan_skips_migration_when_mysql_unavailable(patch_lifespan_deps):
""" MySQL 不可用时lifespan 不应调用迁移函数。 """
from app.main import lifespan, app
patch_lifespan_deps["init_redis"].return_value = None
patch_lifespan_deps["init_mysql"].return_value = None
with patch("app.migration.migrate_sqlite_to_mysql") as mock_migrate:
async with lifespan(app):
pass
mock_migrate.assert_not_called()
@pytest.mark.asyncio
async def test_lifespan_storage_mode_redis_and_mysql(patch_lifespan_deps, caplog):
""" Redis 与 MySQL 均可用时,日志显示 Redis + MySQL 模式。 """
from app.main import lifespan, app
patch_lifespan_deps["init_redis"].return_value = MagicMock()
patch_lifespan_deps["init_mysql"].return_value = MagicMock()
with caplog.at_level(logging.INFO, logger="app.main"):
async with lifespan(app):
pass
assert "存储模式: Redis + MySQL" in caplog.text
@pytest.mark.asyncio
async def test_lifespan_storage_mode_mysql_only(patch_lifespan_deps, caplog):
""" 仅 MySQL 可用时,日志显示 MySQL 降级模式。 """
from app.main import lifespan, app
patch_lifespan_deps["init_redis"].return_value = None
patch_lifespan_deps["init_mysql"].return_value = MagicMock()
with caplog.at_level(logging.WARNING, logger="app.main"):
async with lifespan(app):
pass
assert "存储模式: MySQL (Redis 不可用)" in caplog.text
@pytest.mark.asyncio
async def test_lifespan_storage_mode_sqlite_fallback(patch_lifespan_deps, caplog):
""" Redis 与 MySQL 均不可用时,日志显示 SQLite 降级模式。 """
from app.main import lifespan, app
patch_lifespan_deps["init_redis"].return_value = None
patch_lifespan_deps["init_mysql"].return_value = None
with caplog.at_level(logging.ERROR, logger="app.main"):
async with lifespan(app):
pass
assert "存储模式: SQLite (Redis 和 MySQL 均不可用)" in caplog.text
@pytest.mark.asyncio
async def test_lifespan_storage_init_failure_does_not_raise(patch_lifespan_deps, caplog):
""" 初始化 Redis/MySQL 失败抛出异常时,应用仍可正常启动。 """
from app.main import lifespan, app
patch_lifespan_deps["init_redis"].side_effect = Exception("redis down")
patch_lifespan_deps["init_mysql"].side_effect = Exception("mysql down")
with caplog.at_level(logging.ERROR, logger="app.main"):
async with lifespan(app):
pass
assert "存储模式: SQLite (Redis 和 MySQL 均不可用)" in caplog.text
def test_storage_manager_initialize_accepts_clients_and_updates_references():
"""initialize 应可选接收 redis_client 和 mysql_engine 并更新内部引用。"""
from app.storage_manager import StorageManager
manager = StorageManager(redis_client=None, mysql_engine=None)
fake_redis = MagicMock()
fake_mysql = MagicMock()
manager.initialize(redis_client=fake_redis, mysql_engine=fake_mysql)
assert manager.redis_client is fake_redis
assert manager.mysql_engine is fake_mysql
@pytest.mark.asyncio
async def test_lifespan_injects_redis_and_mysql_into_storage_manager(patch_lifespan_deps):
"""lifespan 初始化后应将 Redis/MySQL 客户端注入 StorageManager 单例。"""
from app.main import lifespan, app
from app.storage_manager import StorageManager
fake_redis = MagicMock()
fake_mysql = MagicMock()
patch_lifespan_deps["init_redis"].return_value = fake_redis
patch_lifespan_deps["init_mysql"].return_value = fake_mysql
mock_manager = MagicMock(spec=StorageManager)
with patch("app.storage_manager.get_storage_manager", return_value=mock_manager):
async with lifespan(app):
pass
mock_manager.initialize.assert_called_once_with(fake_redis, fake_mysql)

@ -1,157 +0,0 @@
"""
数据缓冲平台 - SQLite MySQL 数据迁移脚本测试
"""
import logging
from datetime import datetime
from unittest.mock import MagicMock, patch
import pytest
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
from app.models import Base, MarketData, SymbolTimestamp
def _create_sqlite_source(tmp_path):
"""创建包含测试数据的文件 SQLite 源数据库。"""
db_path = tmp_path / "test_source.db"
engine = create_engine(f"sqlite:///{db_path}")
MarketData.__table__.create(bind=engine)
SymbolTimestamp.__table__.create(bind=engine)
Session = sessionmaker(bind=engine)
session = Session()
fetched_at = datetime(2026, 7, 4, 10, 0, 0)
session.add_all(
[
MarketData(
symbol="AG2606",
data_type="futures",
period="5min",
candles_json='[{"open": 100, "close": 110}]',
current_price=123.45,
fetched_at=fetched_at,
candle_count=1,
),
MarketData(
symbol="AG2606",
data_type="futures",
period="15min",
candles_json='[{"open": 105, "close": 115}]',
current_price=123.45,
fetched_at=fetched_at,
candle_count=1,
),
SymbolTimestamp(
symbol="AG2606",
data_type="futures",
last_refresh_at=fetched_at,
refresh_count=5,
),
]
)
session.commit()
session.close()
return engine
def _make_mysql_session(market_data_count=0, symbol_timestamp_count=0):
"""构造模拟 MySQL 会话,支持记录写入和计数查询。"""
mysql_session = MagicMock()
mysql_session.__enter__ = MagicMock(return_value=mysql_session)
mysql_session.__exit__ = MagicMock(return_value=False)
added_market_data = []
added_symbol_timestamps = []
def mock_query(model):
query = MagicMock()
if model is MarketData:
query.count.return_value = market_data_count
elif model is SymbolTimestamp:
query.count.return_value = symbol_timestamp_count
return query
mysql_session.query.side_effect = mock_query
mysql_session.add_all.side_effect = lambda records: (
added_market_data.extend(records)
if records and isinstance(records[0], MarketData)
else added_symbol_timestamps.extend(records)
)
return mysql_session, added_market_data, added_symbol_timestamps
class TestMigrateSqliteToMysql:
"""migrate_sqlite_to_mysql 行为测试。"""
def test_migrates_data_when_mysql_tables_are_empty(self, caplog, tmp_path):
"""MySQL 表为空时,应从 SQLite 迁移全部数据。"""
sqlite_engine = _create_sqlite_source(tmp_path)
mysql_session, added_market_data, added_symbol_timestamps = _make_mysql_session(
market_data_count=0, symbol_timestamp_count=0
)
with patch("app.migration.create_engine", return_value=sqlite_engine):
with patch(
"app.migration.MySQLSessionLocal", return_value=mysql_session
):
with caplog.at_level(logging.INFO, logger="app.migration"):
from app.migration import migrate_sqlite_to_mysql
result = migrate_sqlite_to_mysql()
assert result is True
assert len(added_market_data) == 2
assert len(added_symbol_timestamps) == 1
assert added_market_data[0].symbol == "AG2606"
assert added_market_data[0].period == "5min"
assert added_symbol_timestamps[0].symbol == "AG2606"
assert "迁移完成" in caplog.text
assert "market_data: 2" in caplog.text
assert "symbol_timestamps: 1" in caplog.text
mysql_session.commit.assert_called_once()
def test_skips_migration_when_mysql_has_data(self, caplog, tmp_path):
"""MySQL 表非空时,应跳过迁移并输出提示日志。"""
sqlite_engine = _create_sqlite_source(tmp_path)
mysql_session, added_market_data, added_symbol_timestamps = _make_mysql_session(
market_data_count=1, symbol_timestamp_count=1
)
with patch("app.migration.create_engine", return_value=sqlite_engine):
with patch(
"app.migration.MySQLSessionLocal", return_value=mysql_session
):
with caplog.at_level(logging.INFO, logger="app.migration"):
from app.migration import migrate_sqlite_to_mysql
result = migrate_sqlite_to_mysql()
assert result is False
assert len(added_market_data) == 0
assert len(added_symbol_timestamps) == 0
assert "MySQL 已存在数据" in caplog.text
assert "跳过迁移" in caplog.text
mysql_session.commit.assert_not_called()
def test_migrates_empty_table_when_other_table_has_data(self, caplog, tmp_path):
"""按表分别判断:仅空表需要迁移,非空表跳过。"""
sqlite_engine = _create_sqlite_source(tmp_path)
mysql_session, added_market_data, added_symbol_timestamps = _make_mysql_session(
market_data_count=1, symbol_timestamp_count=0
)
with patch("app.migration.create_engine", return_value=sqlite_engine):
with patch(
"app.migration.MySQLSessionLocal", return_value=mysql_session
):
with caplog.at_level(logging.INFO, logger="app.migration"):
from app.migration import migrate_sqlite_to_mysql
result = migrate_sqlite_to_mysql()
assert result is True
assert len(added_market_data) == 0
assert len(added_symbol_timestamps) == 1
assert added_symbol_timestamps[0].symbol == "AG2606"
mysql_session.commit.assert_called_once()

@ -1,23 +0,0 @@
"""
数据缓冲平台 - MySQL 数据库连接测试
"""
from unittest.mock import MagicMock, patch
from app.mysql_database import init_mysql
def test_init_mysql_url_encodes_password():
"""MySQL 密码应使用 urllib.parse.quote_plus 进行 URL 编码。"""
with patch("app.mysql_database.create_engine") as mock_create_engine:
mock_engine = MagicMock()
mock_create_engine.return_value = mock_engine
with patch("app.mysql_database.MYSQL_PASSWORD", "p@ss/w+ord"):
with patch("app.mysql_database.MYSQL_USER", "user"):
with patch("app.mysql_database.MYSQL_HOST", "host"):
with patch("app.mysql_database.MYSQL_PORT", "3306"):
with patch("app.mysql_database.MYSQL_DATABASE", "buffer"):
init_mysql()
url = mock_create_engine.call_args[0][0]
assert "p%40ss%2Fw%2Bord" in url
assert "p@ss" not in url

@ -1,280 +0,0 @@
"""
Redis 缓存命中/未命中场景验证测试
覆盖
1. 调用 save_market_data 写入数据后Redis MySQL 同时存在一致数据
2. 首次调用 get_market_dataRedis 未命中 MySQL 读取并回填 Redis
3. 再次调用 get_market_dataRedis 命中直接返回缓存数据不访问 MySQL
4. 手动删除 Redis key 再次读取回源 MySQL 并重新回填 Redis
"""
import json
import logging
from datetime import datetime
from unittest.mock import MagicMock
import pytest
from sqlalchemy import create_engine, text
from sqlalchemy.orm import sessionmaker
from app.models import Base, MarketData
from app.storage_manager import StorageManager
# test_main_lifespan.py 中的 fixture 会 patch app.main.Base.metadata.create_all 且未正确恢复,
# 导致后续依赖 create_all 的测试失败。这里保留原始方法引用,必要时恢复。
_original_create_all = Base.metadata.create_all
class FakeRedis:
"""轻量级 Redis 替身,仅支持本测试所需的方法。"""
def __init__(self):
self._store = {}
def ping(self):
return True
def get(self, key):
return self._store.get(key)
def setex(self, key, ttl, value):
self._store[key] = value
def delete(self, *keys):
for key in keys:
self._store.pop(key, None)
def keys(self, pattern):
# 仅支持以 * 结尾的通配模式
prefix = pattern.rstrip("*")
return [k for k in self._store if k.startswith(prefix)]
def exists(self, key):
return key in self._store
@pytest.fixture
def mysql_engine():
"""提供已创建表结构的内存 SQLite 引擎,作为 MySQL 替身。"""
# 防御:修复上游 fixture 对 Base.metadata.create_all 的 patch 泄漏
if isinstance(Base.metadata.create_all, MagicMock):
Base.metadata.create_all = _original_create_all
engine = create_engine("sqlite:///:memory:")
Base.metadata.create_all(bind=engine)
# 确认表已创建
with engine.connect() as conn:
result = conn.execute(
text("SELECT name FROM sqlite_master WHERE type='table' AND name='market_data'")
)
assert result.fetchone() is not None
yield engine
engine.dispose()
@pytest.fixture
def fake_redis():
return FakeRedis()
@pytest.fixture
def sample_data():
fetched_at = datetime(2026, 7, 4, 10, 0, 0)
return {
"type": "futures",
"current_price": 123.45,
"timestamp": fetched_at.isoformat(),
"timeframes": {
"5min": [{"datetime": "2026-07-04T09:55:00", "open": 100, "close": 110}],
"15min": [{"datetime": "2026-07-04T09:45:00", "open": 105, "close": 115}],
},
}
def _seed_mysql_market_data(engine, symbol="AG2606", data_type="futures"):
"""在 MySQL 替身中写入行情数据。"""
fetched_at = datetime(2026, 7, 4, 10, 0, 0)
Session = sessionmaker(bind=engine)
with Session() as db:
db.add(
MarketData(
symbol=symbol,
data_type=data_type,
period="5min",
candles_json=json.dumps(
[{"datetime": "2026-07-04T09:55:00", "open": 100, "close": 110}]
),
current_price=123.45,
fetched_at=fetched_at,
candle_count=1,
)
)
db.commit()
class TestSaveMarketData:
"""save_market_data 写入与缓存回填场景。"""
def test_save_market_data_writes_mysql_and_backfills_redis(
self, fake_redis, mysql_engine, sample_data
):
"""写入后 MySQL 与 Redis 均保存一致数据。"""
manager = StorageManager(
redis_client=fake_redis, mysql_engine=mysql_engine
)
assert manager.save_market_data("AG2606", sample_data) is True
# MySQL 中应写入两条记录
Session = sessionmaker(bind=mysql_engine)
with Session() as db:
records = db.query(MarketData).filter_by(symbol="AG2606").all()
assert len(records) == 2
periods = {r.period for r in records}
assert periods == {"5min", "15min"}
for r in records:
assert r.current_price == 123.45
# Redis 中应回填对应缓存键
assert fake_redis.exists("market_data:AG2606:5min")
assert fake_redis.exists("market_data:AG2606:15min")
cached_5min = json.loads(fake_redis.get("market_data:AG2606:5min"))
assert cached_5min["current_price"] == 123.45
assert cached_5min["candles"] == sample_data["timeframes"]["5min"]
class TestRedisCacheHitMiss:
"""Redis 缓存命中/未命中读取场景。"""
def test_first_read_miss_falls_back_to_mysql_and_backfills_redis(
self, fake_redis, mysql_engine
):
"""Redis 未命中时从 MySQL 读取并回填 Redis。"""
_seed_mysql_market_data(mysql_engine)
manager = StorageManager(
redis_client=fake_redis, mysql_engine=mysql_engine
)
assert fake_redis.get("market_data:AG2606:5min") is None
result = manager.get_market_data("AG2606", "futures", "5min")
expected = {
"current_price": 123.45,
"timestamp": datetime(2026, 7, 4, 10, 0, 0).isoformat(),
"candles": [{"datetime": "2026-07-04T09:55:00", "open": 100, "close": 110}],
}
assert result == expected
# Redis 应已被回填
assert fake_redis.exists("market_data:AG2606:5min")
cached = json.loads(fake_redis.get("market_data:AG2606:5min"))
assert cached == expected
def test_second_read_hit_returns_from_redis_without_mysql_access(
self, fake_redis, mysql_engine
):
"""Redis 命中时直接返回缓存,不再访问 MySQL。"""
_seed_mysql_market_data(mysql_engine)
manager = StorageManager(
redis_client=fake_redis, mysql_engine=mysql_engine
)
first = manager.get_market_data("AG2606", "futures", "5min")
assert fake_redis.exists("market_data:AG2606:5min")
# 将 MySQL 引擎替换为会抛异常的 mock以证明第二次读取不会访问 MySQL
bad_engine = MagicMock()
bad_engine.connect.side_effect = Exception("MySQL should not be accessed")
manager.mysql_engine = bad_engine
second = manager.get_market_data("AG2606", "futures", "5min")
assert second == first
bad_engine.connect.assert_not_called()
def test_after_redis_key_deleted_falls_back_to_mysql_again(
self, fake_redis, mysql_engine
):
"""手动删除 Redis key 后,读取回源 MySQL 并重新回填 Redis。"""
_seed_mysql_market_data(mysql_engine)
manager = StorageManager(
redis_client=fake_redis, mysql_engine=mysql_engine
)
first = manager.get_market_data("AG2606", "futures", "5min")
assert fake_redis.exists("market_data:AG2606:5min")
# 模拟 TTL 过期或手动失效
fake_redis.delete("market_data:AG2606:5min")
assert fake_redis.get("market_data:AG2606:5min") is None
second = manager.get_market_data("AG2606", "futures", "5min")
assert second == first
assert fake_redis.exists("market_data:AG2606:5min")
def test_cache_hit_data_matches_mysql_data(
self, fake_redis, mysql_engine
):
"""缓存命中时返回的数据应与 MySQL 中的数据一致。"""
_seed_mysql_market_data(mysql_engine)
manager = StorageManager(
redis_client=fake_redis, mysql_engine=mysql_engine
)
# 首次读取触发回填
from_redis = manager.get_market_data("AG2606", "futures", "5min")
# 直接从 MySQL 读取原始记录作为基准
Session = sessionmaker(bind=mysql_engine)
with Session() as db:
record = (
db.query(MarketData)
.filter_by(symbol="AG2606", data_type="futures", period="5min")
.first()
)
assert record is not None
assert from_redis["current_price"] == record.current_price
assert from_redis["candles"] == json.loads(record.candles_json)
class TestCacheLogMessages:
"""验证缓存命中/未命中的日志输出。"""
@pytest.mark.xfail(
reason="当前 StorageManager 未输出 'Redis 缓存命中' 日志,仅记录行为断言",
strict=True,
)
def test_cache_hit_logs_redis_hit(self, fake_redis, mysql_engine, caplog):
"""Redis 命中时日志应包含 'Redis 缓存命中'"""
_seed_mysql_market_data(mysql_engine)
manager = StorageManager(
redis_client=fake_redis, mysql_engine=mysql_engine
)
manager.get_market_data("AG2606", "futures", "5min") # 回填
with caplog.at_level(logging.INFO, logger="app.storage_manager"):
manager.get_market_data("AG2606", "futures", "5min") # 命中
assert "Redis 缓存命中" in caplog.text
@pytest.mark.xfail(
reason="当前 StorageManager 未输出 'Redis 未命中,从 MySQL 读取' 日志,仅记录行为断言",
strict=True,
)
def test_cache_miss_logs_redis_miss_and_mysql_read(
self, fake_redis, mysql_engine, caplog
):
"""Redis 未命中并回源 MySQL 时日志应包含 'Redis 未命中,从 MySQL 读取'"""
_seed_mysql_market_data(mysql_engine)
manager = StorageManager(
redis_client=fake_redis, mysql_engine=mysql_engine
)
with caplog.at_level(logging.INFO, logger="app.storage_manager"):
manager.get_market_data("AG2606", "futures", "5min")
assert "Redis 未命中,从 MySQL 读取" in caplog.text

@ -1,931 +0,0 @@
import importlib
import json
import logging
import time
from datetime import datetime, timedelta
from unittest.mock import MagicMock, patch
import pytest
from app.storage_manager import StorageManager, get_storage_manager
class TestStorageManagerSkeleton:
"""StorageManager 骨架与降级检测测试。"""
def test_init_holds_client_and_engine_references(self):
"""__init__ 应持有 redis_client / mysql_engine 引用。"""
redis_client = MagicMock()
mysql_engine = MagicMock()
manager = StorageManager(redis_client=redis_client, mysql_engine=mysql_engine)
assert manager.redis_client is redis_client
assert manager.mysql_engine is mysql_engine
def test_init_sets_default_flags(self):
"""初始化时应将可用性标志设为 False。"""
manager = StorageManager(redis_client=None, mysql_engine=None)
assert manager.redis_available is False
assert manager.mysql_available is False
def test_check_redis_returns_cached_result_within_interval(self):
"""30 秒间隔内应返回缓存的 Redis 可用性结果,不重新探测。"""
redis_client = MagicMock()
redis_client.ping.side_effect = Exception("redis down")
manager = StorageManager(redis_client=redis_client, mysql_engine=None)
first = manager.check_redis()
redis_client.ping.side_effect = None
second = manager.check_redis()
assert first is False
assert second is False
assert redis_client.ping.call_count == 1
def test_check_redis_recovers_after_interval(self):
"""超过检测间隔后Redis 恢复应返回 True。"""
redis_client = MagicMock()
redis_client.ping.side_effect = Exception("redis down")
manager = StorageManager(
redis_client=redis_client, mysql_engine=None, check_interval=0.1
)
assert manager.check_redis() is False
redis_client.ping.side_effect = None
time.sleep(0.15)
assert manager.check_redis() is True
def test_check_redis_false_when_client_is_none(self):
"""redis_client 为 None 时 check_redis 返回 False。"""
manager = StorageManager(redis_client=None, mysql_engine=None)
assert manager.check_redis() is False
def test_check_mysql_returns_cached_result_within_interval(self):
"""30 秒间隔内应返回缓存的 MySQL 可用性结果,不重新探测。"""
mysql_engine = MagicMock()
mysql_engine.connect.side_effect = Exception("mysql down")
manager = StorageManager(redis_client=None, mysql_engine=mysql_engine)
first = manager.check_mysql()
mysql_engine.connect.side_effect = None
second = manager.check_mysql()
assert first is False
assert second is False
assert mysql_engine.connect.call_count == 1
def test_check_mysql_recovers_after_interval(self):
"""超过检测间隔后MySQL 恢复应返回 True。"""
mysql_engine = MagicMock()
mysql_engine.connect.side_effect = Exception("mysql down")
manager = StorageManager(
redis_client=None, mysql_engine=mysql_engine, check_interval=0.1
)
assert manager.check_mysql() is False
mysql_engine.connect.side_effect = None
time.sleep(0.15)
assert manager.check_mysql() is True
def test_check_mysql_false_when_engine_is_none(self):
"""mysql_engine 为 None 时 check_mysql 返回 False。"""
manager = StorageManager(redis_client=None, mysql_engine=None)
assert manager.check_mysql() is False
def test_is_available_true_when_redis_available(self):
"""Redis 可用时 is_available 返回 True。"""
redis_client = MagicMock()
manager = StorageManager(redis_client=redis_client, mysql_engine=None)
assert manager.is_available() is True
def test_is_available_true_when_mysql_available(self):
"""MySQL 可用时 is_available 返回 True。"""
mysql_engine = MagicMock()
manager = StorageManager(redis_client=None, mysql_engine=mysql_engine)
assert manager.is_available() is True
def test_is_available_false_when_both_unavailable(self):
"""Redis 与 MySQL 均不可用时 is_available 返回 False。"""
redis_client = MagicMock()
redis_client.ping.side_effect = Exception("redis down")
mysql_engine = MagicMock()
mysql_engine.connect.side_effect = Exception("mysql down")
manager = StorageManager(redis_client=redis_client, mysql_engine=mysql_engine)
assert manager.is_available() is False
def test_initialize_checks_backends_and_logs(self, caplog):
"""initialize 应检测后端可用性并输出日志。"""
redis_client = MagicMock()
mysql_engine = MagicMock()
manager = StorageManager(redis_client=redis_client, mysql_engine=mysql_engine)
with caplog.at_level(logging.INFO):
manager.initialize()
assert "Redis 可用" in caplog.text
assert "MySQL 可用" in caplog.text
def test_initialize_logs_fallback_when_unavailable(self, caplog):
"""后端不可用时 initialize 应输出降级日志。"""
manager = StorageManager(redis_client=None, mysql_engine=None)
with caplog.at_level(logging.WARNING):
manager.initialize()
assert "Redis 不可用" in caplog.text
assert "MySQL 不可用" in caplog.text
class TestStorageManagerSingleton:
"""全局单例工厂函数测试。"""
def test_get_storage_manager_returns_same_instance(self):
"""多次调用 get_storage_manager 应返回同一实例。"""
first = get_storage_manager()
second = get_storage_manager()
assert first is second
def test_get_storage_manager_returns_storage_manager(self):
"""get_storage_manager 应返回 StorageManager 实例。"""
manager = get_storage_manager()
assert isinstance(manager, StorageManager)
class TestStorageManagerReadLogic:
"""StorageManager Redis → MySQL 读取逻辑测试。"""
def test_get_market_data_returns_redis_value_on_cache_hit(self):
"""Redis 命中时直接返回反序列化数据,不访问 MySQL。"""
redis_client = MagicMock()
mysql_engine = MagicMock()
expected = {
"current_price": 123.45,
"timestamp": "2026-07-04T10:00:00",
"candles": [{"open": 100, "close": 110}],
}
redis_client.get.return_value = json.dumps(expected)
manager = StorageManager(redis_client=redis_client, mysql_engine=mysql_engine)
result = manager.get_market_data("AG2606", "futures", "5min")
assert result == expected
redis_client.get.assert_called_once_with("market_data:AG2606:5min")
mysql_engine.connect.assert_not_called()
def test_get_market_data_falls_back_to_mysql_and_backfills_redis(self):
"""Redis 未命中时从 MySQL 读取并回填 RedisTTL 30 天)。"""
redis_client = MagicMock()
redis_client.get.return_value = None
mysql_engine = MagicMock()
manager = StorageManager(redis_client=redis_client, mysql_engine=mysql_engine)
fetched_at = datetime(2026, 7, 4, 10, 0, 0)
record = MagicMock()
record.current_price = 123.45
record.fetched_at = fetched_at
record.candles_json = json.dumps([{"open": 100, "close": 110}])
mock_query = MagicMock()
mock_query.filter_by.return_value.first.return_value = record
mock_session = MagicMock()
mock_session.return_value = mock_session
mock_session.query.return_value = mock_query
mock_session.__enter__ = MagicMock(return_value=mock_session)
mock_session.__exit__ = MagicMock(return_value=False)
mock_sessionmaker = MagicMock(return_value=mock_session)
with patch("app.storage_manager.sessionmaker", mock_sessionmaker):
result = manager.get_market_data("AG2606", "futures", "5min")
expected = {
"current_price": 123.45,
"timestamp": "2026-07-04T10:00:00",
"candles": [{"open": 100, "close": 110}],
}
assert result == expected
mock_sessionmaker.assert_called_once_with(bind=mysql_engine)
mock_query.filter_by.assert_called_once_with(
symbol="AG2606", data_type="futures", period="5min"
)
redis_client.setex.assert_called_once_with(
"market_data:AG2606:5min", 2592000, json.dumps(expected, ensure_ascii=False)
)
def test_get_market_data_returns_none_when_mysql_unavailable(self):
"""Redis 和 MySQL 均不可用时返回 None由调用方降级到 SQLite。"""
redis_client = MagicMock()
redis_client.ping.side_effect = Exception("redis down")
mysql_engine = MagicMock()
mysql_engine.connect.side_effect = Exception("mysql down")
manager = StorageManager(redis_client=redis_client, mysql_engine=mysql_engine)
result = manager.get_market_data("AG2606", "futures", "5min")
assert result is None
def test_get_market_data_falls_back_to_mysql_when_redis_read_fails(self):
"""Redis 读取失败但 MySQL 可用时,应降级到 MySQL 并回填 Redis。"""
redis_client = MagicMock()
redis_client.get.side_effect = Exception("redis read failed")
mysql_engine = MagicMock()
manager = StorageManager(redis_client=redis_client, mysql_engine=mysql_engine)
fetched_at = datetime(2026, 7, 4, 10, 0, 0)
record = MagicMock()
record.current_price = 123.45
record.fetched_at = fetched_at
record.candles_json = json.dumps([{"open": 100, "close": 110}])
mock_query = MagicMock()
mock_query.filter_by.return_value.first.return_value = record
mock_session = MagicMock()
mock_session.return_value = mock_session
mock_session.query.return_value = mock_query
mock_session.__enter__ = MagicMock(return_value=mock_session)
mock_session.__exit__ = MagicMock(return_value=False)
mock_sessionmaker = MagicMock(return_value=mock_session)
with patch("app.storage_manager.sessionmaker", mock_sessionmaker):
result = manager.get_market_data("AG2606", "futures", "5min")
expected = {
"current_price": 123.45,
"timestamp": "2026-07-04T10:00:00",
"candles": [{"open": 100, "close": 110}],
}
assert result == expected
redis_client.setex.assert_called_once_with(
"market_data:AG2606:5min", 2592000, json.dumps(expected, ensure_ascii=False)
)
def test_get_market_data_returns_none_when_mysql_read_fails(self):
"""Redis 不可用且 MySQL 读取失败时返回 None。"""
redis_client = MagicMock()
redis_client.ping.side_effect = Exception("redis down")
mysql_engine = MagicMock()
manager = StorageManager(redis_client=redis_client, mysql_engine=mysql_engine)
mock_session = MagicMock()
mock_session.return_value = mock_session
mock_session.query.side_effect = Exception("mysql read failed")
mock_session.__enter__ = MagicMock(return_value=mock_session)
mock_session.__exit__ = MagicMock(return_value=False)
mock_sessionmaker = MagicMock(return_value=mock_session)
with patch("app.storage_manager.sessionmaker", mock_sessionmaker):
result = manager.get_market_data("AG2606", "futures", "5min")
assert result is None
def test_get_symbol_timestamp_returns_redis_value_on_cache_hit(self):
"""Redis 命中时直接返回合约时间戳数据,不访问 MySQL。"""
redis_client = MagicMock()
mysql_engine = MagicMock()
expected = {
"last_refresh_at": "2026-07-04T10:00:00",
"refresh_count": 42,
}
redis_client.get.return_value = json.dumps(expected)
manager = StorageManager(redis_client=redis_client, mysql_engine=mysql_engine)
result = manager.get_symbol_timestamp("AG2606", "futures")
assert result == expected
redis_client.get.assert_called_once_with("symbol_timestamps:AG2606")
mysql_engine.connect.assert_not_called()
def test_get_symbol_timestamp_falls_back_to_mysql_and_backfills_redis(self):
"""Redis 未命中时从 MySQL 读取时间戳并回填 RedisTTL 30 天)。"""
redis_client = MagicMock()
redis_client.get.return_value = None
mysql_engine = MagicMock()
manager = StorageManager(redis_client=redis_client, mysql_engine=mysql_engine)
last_refresh = datetime(2026, 7, 4, 10, 0, 0)
record = MagicMock()
record.last_refresh_at = last_refresh
record.refresh_count = 42
mock_query = MagicMock()
mock_query.filter_by.return_value.first.return_value = record
mock_session = MagicMock()
mock_session.return_value = mock_session
mock_session.query.return_value = mock_query
mock_session.__enter__ = MagicMock(return_value=mock_session)
mock_session.__exit__ = MagicMock(return_value=False)
mock_sessionmaker = MagicMock(return_value=mock_session)
with patch("app.storage_manager.sessionmaker", mock_sessionmaker):
result = manager.get_symbol_timestamp("AG2606", "futures")
expected = {
"last_refresh_at": "2026-07-04T10:00:00",
"refresh_count": 42,
}
assert result == expected
mock_sessionmaker.assert_called_once_with(bind=mysql_engine)
mock_query.filter_by.assert_called_once_with(symbol="AG2606", data_type="futures")
redis_client.setex.assert_called_once_with(
"symbol_timestamps:AG2606", 2592000, json.dumps(expected, ensure_ascii=False)
)
def test_is_fresh_true_within_cache_ttl(self):
"""数据在 CACHE_TTL_SECONDS默认 300 秒)内时 is_fresh 为 True。"""
manager = StorageManager(redis_client=None, mysql_engine=None)
fetched_at = datetime(2026, 7, 4, 10, 0, 0)
now = fetched_at + timedelta(seconds=60)
mock_datetime = MagicMock()
mock_datetime.now.return_value = now
mock_datetime.fromisoformat = datetime.fromisoformat
with patch("app.storage_manager.datetime", mock_datetime):
result = manager._merge_period_results(
"AG2606",
"futures",
{
"5min": {
"current_price": 123.45,
"timestamp": fetched_at.isoformat(),
"candles": [],
}
},
)
assert result["is_fresh"] is True
def test_is_fresh_false_beyond_cache_ttl(self):
"""数据超过 CACHE_TTL_SECONDS默认 300 秒)时 is_fresh 为 False。"""
manager = StorageManager(redis_client=None, mysql_engine=None)
fetched_at = datetime(2026, 7, 4, 10, 0, 0)
now = fetched_at + timedelta(seconds=301)
mock_datetime = MagicMock()
mock_datetime.now.return_value = now
mock_datetime.fromisoformat = datetime.fromisoformat
with patch("app.storage_manager.datetime", mock_datetime):
result = manager._merge_period_results(
"AG2606",
"futures",
{
"5min": {
"current_price": 123.45,
"timestamp": fetched_at.isoformat(),
"candles": [],
}
},
)
assert result["is_fresh"] is False
class TestStorageManagerWriteLogic:
"""StorageManager 双写一致性测试。"""
def test_save_market_data_deletes_cache_writes_mysql_and_updates_redis(self):
"""MySQL 写入成功时,应先删缓存、再写 MySQL、最后回填 Redis。"""
redis_client = MagicMock()
mysql_engine = MagicMock()
manager = StorageManager(redis_client=redis_client, mysql_engine=mysql_engine)
fetched_at = datetime(2026, 7, 4, 10, 0, 0)
data = {
"type": "futures",
"current_price": 123.45,
"timestamp": fetched_at.isoformat(),
"timeframes": {
"5min": [{"open": 100, "close": 110}],
"15min": [{"open": 105, "close": 115}],
},
}
records = []
def mock_filter_by(symbol=None, data_type=None, period=None):
existing = next(
(
r
for r in records
if r.symbol == symbol and r.data_type == data_type and r.period == period
),
None,
)
fb_query = MagicMock()
fb_query.first.return_value = existing
return fb_query
mock_query = MagicMock()
mock_query.filter_by.side_effect = mock_filter_by
mock_session = MagicMock()
mock_session.return_value = mock_session
mock_session.query.return_value = mock_query
mock_session.add.side_effect = records.append
mock_session.commit = MagicMock()
mock_session.rollback = MagicMock()
mock_session.__enter__ = MagicMock(return_value=mock_session)
mock_session.__exit__ = MagicMock(return_value=False)
mock_sessionmaker = MagicMock(return_value=mock_session)
with patch("app.storage_manager.sessionmaker", mock_sessionmaker):
with patch("app.storage_manager.datetime") as mock_datetime:
mock_datetime.now.return_value = fetched_at
result = manager.save_market_data("AG2606", data)
assert result is True
assert len(records) == 2
assert records[0].symbol == "AG2606"
assert records[0].data_type == "futures"
assert records[0].period == "5min"
assert records[0].current_price == 123.45
assert records[0].candle_count == 1
assert records[0].fetched_at == fetched_at
redis_client.delete.assert_called_once_with(
"market_data:AG2606:5min", "market_data:AG2606:15min"
)
redis_client.setex.assert_any_call(
"market_data:AG2606:5min",
2592000,
json.dumps(
{
"current_price": 123.45,
"timestamp": fetched_at.isoformat(),
"candles": [{"open": 100, "close": 110}],
},
ensure_ascii=False,
),
)
redis_client.setex.assert_any_call(
"market_data:AG2606:15min",
2592000,
json.dumps(
{
"current_price": 123.45,
"timestamp": fetched_at.isoformat(),
"candles": [{"open": 105, "close": 115}],
},
ensure_ascii=False,
),
)
def test_save_market_data_returns_false_and_skips_redis_on_mysql_failure(self):
"""MySQL 写入失败时应回滚事务,不更新 Redis并返回 False。"""
redis_client = MagicMock()
mysql_engine = MagicMock()
manager = StorageManager(redis_client=redis_client, mysql_engine=mysql_engine)
data = {
"type": "futures",
"current_price": 123.45,
"timestamp": datetime(2026, 7, 4, 10, 0, 0).isoformat(),
"timeframes": {"5min": [{"open": 100, "close": 110}]},
}
mock_session = MagicMock()
mock_session.return_value = mock_session
mock_session.commit.side_effect = Exception("mysql write failed")
mock_session.rollback = MagicMock()
mock_session.__enter__ = MagicMock(return_value=mock_session)
mock_session.__exit__ = MagicMock(return_value=False)
mock_sessionmaker = MagicMock(return_value=mock_session)
with patch("app.storage_manager.sessionmaker", mock_sessionmaker):
result = manager.save_market_data("AG2606", data)
assert result is False
redis_client.delete.assert_called_once_with("market_data:AG2606:5min")
redis_client.setex.assert_not_called()
mock_session.rollback.assert_called_once()
def test_save_market_data_returns_true_when_redis_update_fails(self, caplog):
"""MySQL 成功但 Redis 回填失败时,应返回 True 并记录警告日志。"""
redis_client = MagicMock()
redis_client.setex.side_effect = Exception("redis write failed")
mysql_engine = MagicMock()
manager = StorageManager(redis_client=redis_client, mysql_engine=mysql_engine)
fetched_at = datetime(2026, 7, 4, 10, 0, 0)
data = {
"type": "futures",
"current_price": 123.45,
"timestamp": fetched_at.isoformat(),
"timeframes": {"5min": [{"open": 100, "close": 110}]},
}
mock_session = MagicMock()
mock_session.return_value = mock_session
mock_session.__enter__ = MagicMock(return_value=mock_session)
mock_session.__exit__ = MagicMock(return_value=False)
mock_sessionmaker = MagicMock(return_value=mock_session)
with patch("app.storage_manager.sessionmaker", mock_sessionmaker):
with patch("app.storage_manager.datetime") as mock_datetime:
mock_datetime.now.return_value = fetched_at
with caplog.at_level(logging.WARNING):
result = manager.save_market_data("AG2606", data)
assert result is True
mock_session.commit.assert_called_once()
assert "Redis 更新失败" in caplog.text
def test_save_market_data_uses_input_timestamp(self):
"""save_market_data 应优先使用输入数据中的 timestamp而非 datetime.now()。"""
redis_client = MagicMock()
mysql_engine = MagicMock()
manager = StorageManager(redis_client=redis_client, mysql_engine=mysql_engine)
input_timestamp = datetime(2026, 1, 15, 8, 30, 0)
data = {
"type": "futures",
"current_price": 123.45,
"timestamp": input_timestamp.isoformat(),
"timeframes": {"5min": [{"open": 100, "close": 110}]},
}
records = []
def mock_filter_by(symbol=None, data_type=None, period=None):
existing = next(
(
r
for r in records
if r.symbol == symbol and r.data_type == data_type and r.period == period
),
None,
)
fb_query = MagicMock()
fb_query.first.return_value = existing
return fb_query
mock_query = MagicMock()
mock_query.filter_by.side_effect = mock_filter_by
mock_session = MagicMock()
mock_session.return_value = mock_session
mock_session.query.return_value = mock_query
mock_session.add.side_effect = records.append
mock_session.commit = MagicMock()
mock_session.rollback = MagicMock()
mock_session.__enter__ = MagicMock(return_value=mock_session)
mock_session.__exit__ = MagicMock(return_value=False)
mock_sessionmaker = MagicMock(return_value=mock_session)
with patch("app.storage_manager.sessionmaker", mock_sessionmaker):
result = manager.save_market_data("AG2606", data)
assert result is True
assert len(records) == 1
assert records[0].fetched_at == input_timestamp
redis_client.setex.assert_called_once_with(
"market_data:AG2606:5min",
2592000,
json.dumps(
{
"current_price": 123.45,
"timestamp": input_timestamp.isoformat(),
"candles": [{"open": 100, "close": 110}],
},
ensure_ascii=False,
),
)
def test_save_market_data_falls_back_to_now_on_invalid_timestamp(self):
"""timestamp 无法解析时应回退到当前时间。"""
redis_client = MagicMock()
mysql_engine = MagicMock()
manager = StorageManager(redis_client=redis_client, mysql_engine=mysql_engine)
fallback_time = datetime(2026, 3, 1, 12, 0, 0)
data = {
"type": "futures",
"current_price": 123.45,
"timestamp": "not-a-valid-timestamp",
"timeframes": {"5min": [{"open": 100, "close": 110}]},
}
records = []
def mock_filter_by(symbol=None, data_type=None, period=None):
existing = next(
(
r
for r in records
if r.symbol == symbol and r.data_type == data_type and r.period == period
),
None,
)
fb_query = MagicMock()
fb_query.first.return_value = existing
return fb_query
mock_query = MagicMock()
mock_query.filter_by.side_effect = mock_filter_by
mock_session = MagicMock()
mock_session.return_value = mock_session
mock_session.query.return_value = mock_query
mock_session.add.side_effect = records.append
mock_session.commit = MagicMock()
mock_session.rollback = MagicMock()
mock_session.__enter__ = MagicMock(return_value=mock_session)
mock_session.__exit__ = MagicMock(return_value=False)
mock_sessionmaker = MagicMock(return_value=mock_session)
with patch("app.storage_manager.sessionmaker", mock_sessionmaker):
with patch("app.storage_manager._datetime.datetime") as mock_datetime:
mock_datetime.now.return_value = fallback_time
mock_datetime.fromisoformat.side_effect = ValueError(
"Invalid isoformat string"
)
result = manager.save_market_data("AG2606", data)
assert result is True
assert len(records) == 1
assert records[0].fetched_at == fallback_time
def test_save_market_data_writes_mysql_when_redis_unavailable(self):
"""Redis 不可用但 MySQL 可用时save_market_data 应直接写入 MySQL 并返回 True。"""
redis_client = MagicMock()
redis_client.ping.side_effect = Exception("redis down")
mysql_engine = MagicMock()
manager = StorageManager(redis_client=redis_client, mysql_engine=mysql_engine)
fetched_at = datetime(2026, 7, 4, 10, 0, 0)
data = {
"type": "futures",
"current_price": 123.45,
"timestamp": fetched_at.isoformat(),
"timeframes": {"5min": [{"open": 100, "close": 110}]},
}
records = []
def mock_filter_by(symbol=None, data_type=None, period=None):
existing = next(
(
r
for r in records
if r.symbol == symbol and r.data_type == data_type and r.period == period
),
None,
)
fb_query = MagicMock()
fb_query.first.return_value = existing
return fb_query
mock_query = MagicMock()
mock_query.filter_by.side_effect = mock_filter_by
mock_session = MagicMock()
mock_session.return_value = mock_session
mock_session.query.return_value = mock_query
mock_session.add.side_effect = records.append
mock_session.commit = MagicMock()
mock_session.rollback = MagicMock()
mock_session.__enter__ = MagicMock(return_value=mock_session)
mock_session.__exit__ = MagicMock(return_value=False)
mock_sessionmaker = MagicMock(return_value=mock_session)
with patch("app.storage_manager.sessionmaker", mock_sessionmaker):
result = manager.save_market_data("AG2606", data)
assert result is True
assert len(records) == 1
assert records[0].symbol == "AG2606"
redis_client.delete.assert_not_called()
redis_client.setex.assert_not_called()
def test_save_market_data_returns_true_when_timeframes_empty(self):
"""timeframes 为空时save_market_data 应直接返回 True 且不操作缓存。"""
redis_client = MagicMock()
mysql_engine = MagicMock()
manager = StorageManager(redis_client=redis_client, mysql_engine=mysql_engine)
data = {
"type": "futures",
"current_price": 123.45,
"timestamp": datetime(2026, 7, 4, 10, 0, 0).isoformat(),
"timeframes": {},
}
mock_session = MagicMock()
mock_session.return_value = mock_session
mock_session.commit = MagicMock()
mock_session.rollback = MagicMock()
mock_session.__enter__ = MagicMock(return_value=mock_session)
mock_session.__exit__ = MagicMock(return_value=False)
mock_sessionmaker = MagicMock(return_value=mock_session)
with patch("app.storage_manager.sessionmaker", mock_sessionmaker):
result = manager.save_market_data("AG2606", data)
assert result is True
mock_session.commit.assert_called_once()
redis_client.delete.assert_not_called()
redis_client.setex.assert_not_called()
def test_save_symbol_timestamp_deletes_cache_writes_mysql_and_updates_redis(self):
"""合约时间戳双写成功时,应先删缓存、再写 MySQL、最后回填 Redis。"""
redis_client = MagicMock()
mysql_engine = MagicMock()
manager = StorageManager(redis_client=redis_client, mysql_engine=mysql_engine)
refresh_time = datetime(2026, 7, 4, 10, 0, 0)
records = []
def mock_filter_by(symbol=None, data_type=None):
existing = next(
(r for r in records if r.symbol == symbol and r.data_type == data_type),
None,
)
fb_query = MagicMock()
fb_query.first.return_value = existing
return fb_query
mock_query = MagicMock()
mock_query.filter_by.side_effect = mock_filter_by
mock_session = MagicMock()
mock_session.return_value = mock_session
mock_session.query.return_value = mock_query
mock_session.add.side_effect = records.append
mock_session.commit = MagicMock()
mock_session.rollback = MagicMock()
mock_session.__enter__ = MagicMock(return_value=mock_session)
mock_session.__exit__ = MagicMock(return_value=False)
mock_sessionmaker = MagicMock(return_value=mock_session)
with patch("app.storage_manager.sessionmaker", mock_sessionmaker):
result = manager.save_symbol_timestamp("AG2606", "futures", refresh_time)
assert result is True
assert len(records) == 1
assert records[0].symbol == "AG2606"
assert records[0].data_type == "futures"
assert records[0].last_refresh_at == refresh_time
assert records[0].refresh_count == 1
redis_client.delete.assert_called_once_with("symbol_timestamps:AG2606")
redis_client.setex.assert_called_once_with(
"symbol_timestamps:AG2606",
2592000,
json.dumps(
{"last_refresh_at": refresh_time.isoformat(), "refresh_count": 1},
ensure_ascii=False,
),
)
def test_save_symbol_timestamp_returns_false_on_mysql_failure(self):
"""合约时间戳 MySQL 写入失败时应返回 False 且不更新 Redis。"""
redis_client = MagicMock()
mysql_engine = MagicMock()
manager = StorageManager(redis_client=redis_client, mysql_engine=mysql_engine)
mock_session = MagicMock()
mock_session.return_value = mock_session
mock_session.commit.side_effect = Exception("mysql write failed")
mock_session.rollback = MagicMock()
mock_session.__enter__ = MagicMock(return_value=mock_session)
mock_session.__exit__ = MagicMock(return_value=False)
mock_sessionmaker = MagicMock(return_value=mock_session)
with patch("app.storage_manager.sessionmaker", mock_sessionmaker):
result = manager.save_symbol_timestamp(
"AG2606", "futures", datetime(2026, 7, 4, 10, 0, 0)
)
assert result is False
redis_client.delete.assert_called_once_with("symbol_timestamps:AG2606")
redis_client.setex.assert_not_called()
mock_session.rollback.assert_called_once()
def test_delete_cache_removes_market_data_keys(self):
"""delete_cache 应批量删除指定周期的 Redis 缓存键。"""
redis_client = MagicMock()
manager = StorageManager(redis_client=redis_client, mysql_engine=None)
manager.delete_cache("AG2606", ["5min", "15min"])
redis_client.delete.assert_called_once_with(
"market_data:AG2606:5min", "market_data:AG2606:15min"
)
class TestStorageManagerConfig:
"""配置读取相关测试。"""
def test_redis_ttl_reads_config_value(self):
"""StorageManager 应分别读取 app.config.REDIS_TTL_SECONDS 与 CACHE_TTL_SECONDS。"""
import app.config as config
import app.storage_manager as sm
original_redis_ttl = config.REDIS_TTL_SECONDS
original_cache_ttl = config.CACHE_TTL_SECONDS
original_singleton = sm._storage_manager
config.REDIS_TTL_SECONDS = 1234
config.CACHE_TTL_SECONDS = 5678
try:
importlib.reload(sm)
assert sm.REDIS_TTL_SECONDS == 1234
assert sm.CACHE_TTL_SECONDS == 5678
finally:
config.REDIS_TTL_SECONDS = original_redis_ttl
config.CACHE_TTL_SECONDS = original_cache_ttl
importlib.reload(sm)
sm._storage_manager = original_singleton
class TestStorageManagerAtomicWrite:
"""save_market_data_with_timestamp 原子写入测试。"""
def test_save_market_data_with_timestamp_writes_market_data_and_timestamp(self):
"""同一 MySQL 事务中写入行情数据与合约时间戳。"""
from sqlalchemy import create_engine
from sqlalchemy.orm import sessionmaker
from app.models import Base, MarketData, SymbolTimestamp
redis_client = MagicMock()
mysql_engine = create_engine("sqlite:///:memory:")
Base.metadata.create_all(bind=mysql_engine)
manager = StorageManager(redis_client=redis_client, mysql_engine=mysql_engine)
fetched_at = datetime(2026, 7, 4, 10, 0, 0)
data = {
"type": "futures",
"current_price": 123.45,
"timestamp": fetched_at.isoformat(),
"timeframes": {
"5min": [{"open": 100, "close": 110}],
"15min": [{"open": 105, "close": 115}],
},
}
refresh_time = datetime(2026, 7, 4, 10, 1, 0)
result = manager.save_market_data_with_timestamp("AG2606", data, refresh_time)
assert result is True
SessionLocal = sessionmaker(bind=mysql_engine)
with SessionLocal() as db:
market_records = db.query(MarketData).filter_by(symbol="AG2606").all()
assert len(market_records) == 2
periods = {r.period for r in market_records}
assert periods == {"5min", "15min"}
ts = db.query(SymbolTimestamp).filter_by(symbol="AG2606", data_type="futures").first()
assert ts is not None
assert ts.last_refresh_at == refresh_time
assert ts.refresh_count == 1
redis_client.delete.assert_called_once_with(
"market_data:AG2606:5min",
"market_data:AG2606:15min",
"symbol_timestamps:AG2606",
)
def test_save_market_data_with_timestamp_returns_false_on_mysql_failure(self):
"""MySQL 写入失败时返回 False不同步时间戳。"""
redis_client = MagicMock()
manager = StorageManager(redis_client=redis_client, mysql_engine=None)
data = {
"type": "futures",
"current_price": 123.45,
"timestamp": datetime(2026, 7, 4, 10, 0, 0).isoformat(),
"timeframes": {"5min": [{"open": 100, "close": 110}]},
}
result = manager.save_market_data_with_timestamp(
"AG2606", data, datetime(2026, 7, 4, 10, 1, 0)
)
assert result is False
redis_client.setex.assert_not_called()
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