144 lines
4.7 KiB
Python
144 lines
4.7 KiB
Python
"""应用配置管理"""
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import os
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from datetime import datetime
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from pydantic_settings import BaseSettings
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class Settings(BaseSettings):
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# Tushare Pro
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tushare_token: str = ""
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# 服务配置
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host: str = "0.0.0.0"
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port: int = 8000
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debug: bool = False
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# 数据库
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database_url: str = "sqlite:///./astock.db"
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# 缓存 TTL（秒）
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cache_ttl_realtime: int = 30 # 实时数据 30 秒
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cache_ttl_daily: int = 300 # 日级数据 5 分钟
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cache_ttl_sector: int = 300 # 板块数据 5 分钟
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cache_ttl_static: int = 86400 # 静态数据 24 小时
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# Tushare 限流
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tushare_request_delay: float = 0.3 # 请求间隔（秒）
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tushare_max_retry: int = 3 # 最大重试次数
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# 筛选参数
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top_sector_count: int = 5 # 关注板块数量
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top_stock_count: int = 20 # 进入技术面筛选的个股数
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candidate_pool_limit: int = 120 # 多路召回后的候选池上限
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llm_prefilter_limit: int = 36 # LLM 初筛保留数量
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llm_prefilter_max_concurrent: int = 6
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llm_final_limit: int = 14 # LLM 深裁决池上限
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min_turnover_rate: float = 2.0 # 最小换手率 %
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max_turnover_rate: float = 30.0 # 最大换手率 %
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min_circ_mv: float = 50.0 # 最小流通市值（亿）
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max_circ_mv: float = 500.0 # 最大流通市值（亿）
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min_list_days: int = 60 # 最小上市天数
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# 买入信号阈值
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buy_score_threshold: int = 60 # 买入最低分
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buy_min_signals: int = 3 # 最少满足信号数
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# 风控
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stop_loss_pct: float = 5.0 # 止损比例 %
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# 趋势突破策略参数
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breakout_min_volume_ratio: float = 1.2 # 突破型最小量比
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pullback_max_shrink_ratio: float = 0.85 # 回踩型最大缩量比
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consolidation_max_range_pct: float = 8.0 # 启动型最大整理振幅 %
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# LLM (DeepSeek)
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deepseek_api_key: str = ""
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deepseek_base_url: str = "https://api.deepseek.com/v1"
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deepseek_model: str = "deepseek-chat"
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llm_max_tokens: int = 2000
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llm_temperature: float = 0.3
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# 告警（Feishu / Lark Incoming Webhook）
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alert_enabled: bool = False
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feishu_webhook_url: str = ""
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alert_dedup_ttl_seconds: int = 300
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alert_max_detail_chars: int = 1200
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alert_app_name: str = "AStock Agent"
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alert_environment: str = "local"
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# 前端
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frontend_url: str = "http://localhost:3002"
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# JWT 认证
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jwt_secret: str = "change-me-in-production"
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jwt_expiry_hours: int = 24
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jwt_algorithm: str = "HS256"
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# 默认管理员（首次启动自动创建）
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admin_username: str = "admin"
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admin_password: str = "admin123"
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model_config = {"env_file": ".env", "env_prefix": "ASTOCK_"}
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settings = Settings()
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def is_trading_hours() -> bool:
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"""判断当前是否在 A 股交易时段（9:30-11:30, 13:00-15:00）"""
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from zoneinfo import ZoneInfo
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now = datetime.now(ZoneInfo("Asia/Shanghai"))
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weekday = now.weekday() # 0=Mon, 6=Sun
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if weekday >= 5:
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return False
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t = now.hour * 100 + now.minute
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return (930 <= t <= 1130) or (1300 <= t <= 1500)
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def is_market_session() -> bool:
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"""判断当前是否在 A 股交易日内（含午休 11:30-13:00）
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午休期间腾讯实时行情仍返回上午收盘价，可用于展示。
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与 is_trading_hours() 的区别：午休时返回 True。
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"""
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from zoneinfo import ZoneInfo
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now = datetime.now(ZoneInfo("Asia/Shanghai"))
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weekday = now.weekday()
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if weekday >= 5:
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return False
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t = now.hour * 100 + now.minute
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return 930 <= t <= 1500
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def is_pre_close() -> bool:
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"""判断是否在收盘后、数据更新前（15:00-15:30 数据尚未完全更新）"""
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from zoneinfo import ZoneInfo
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now = datetime.now(ZoneInfo("Asia/Shanghai"))
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t = now.hour * 100 + now.minute
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return 1500 <= t <= 1530
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def today_trade_date() -> str:
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"""返回上海时区下的今天日期（YYYYMMDD）。"""
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from zoneinfo import ZoneInfo
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return datetime.now(ZoneInfo("Asia/Shanghai")).strftime("%Y%m%d")
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def should_prefer_realtime_today(latest_trade_date: str | None = None) -> bool:
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"""是否应该优先使用“今天”的实时数据。
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规则：
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1. 非交易日直接 False
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2. 交易日内（含午休、收盘后）如果 Tushare 最新交易日还不是今天，则优先实时
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3. 即便 Tushare 最新交易日已经是今天，只要仍处于 15:30 前的延迟窗口，也优先实时
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"""
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if not is_market_session() and not is_pre_close():
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return False
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today = today_trade_date()
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if latest_trade_date and latest_trade_date != today:
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return True
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return is_market_session() or is_pre_close()
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