初始化工程
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"""全局实时行情服务。
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集中管理全市场行情拉取 + enriched 缓存，供盘中选股、自选股等所有模块复用。
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架构:
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- 后台线程轮询数据源 get_by_universes(["CN_Equity_A", "CN_Index"])
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- 拉取行情 → 写 kline_daily (不复权) + 增量计算 enriched → 写盘 + 更新缓存
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- _enriched_cache 是唯一的盘中数据源 (OHLCV + 全套技术指标)
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- _live_agg_cache 是递推状态 (只加载一次, 盘中不变)
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数据流 (每轮 ~15s):
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1. API 拉取 → raw_records (临时变量)
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2. raw_records → 写 kline_daily (不复权原始价格)
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3. raw_records → 更新 _enriched_cache 的 OHLCV
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4. 增量计算 enriched 指标 (~50ms)
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5. 写 kline_daily_enriched + 替换 _enriched_cache
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6. 通知 SSE
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生命周期:
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- 服务启动时读取 preferences，若 enabled 则自动启动线程
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- 运行中可通过 API 切换开关
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- 关闭时停止线程
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"""
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from __future__ import annotations
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import logging
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import threading
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import time
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from datetime import date, datetime, time as dt_time
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import polars as pl
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logger = logging.getLogger(__name__)
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class QuoteService:
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"""全局实时行情服务 — 单例。"""
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CORE_INDEX_SYMBOLS = ("000001.SH", "399001.SZ", "399006.SZ", "000680.SH")
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# 档位 → 最小轮询间隔 (秒)
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TIER_MIN_INTERVAL = {
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"expert": 1.0,
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"pro": 2.0,
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"starter": 3.0,
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}
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DEFAULT_INTERVAL = 10.0
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MAX_INTERVAL = 60.0
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def __init__(self) -> None:
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self._lock = threading.Lock()
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self._running = False
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self._enabled = False # 全局开关 (持久化到 preferences)
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self._interval = self.DEFAULT_INTERVAL
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self._thread: threading.Thread | None = None
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self._repo = None # 延迟注入, 避免循环导入
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self._update_event = threading.Event() # SSE 通知: 行情更新后 set
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self._alert_event = threading.Event() # SSE 通知: 有告警时 set
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self._depth_update_event = threading.Event() # SSE 通知: depth 五档修正后 set (刷新连板梯队)
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self._pending_alerts: list[dict] = [] # 待推送的告警
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self._max_pending_alerts: int = 1000 # 背压上限: 超出丢弃最旧
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self._strategy_monitor = None # 延迟注入
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self._app_state = None # 延迟注入 (FastAPI app.state)
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# 拉取元信息 (给 SSE / status 用)
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self._fetch_time: float = 0.0 # perf_counter (用于计算 quote_age_ms)
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self._fetch_ms: float = 0.0 # 拉取耗时 (毫秒)
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self._fetched_at: float = 0.0 # 拉取完成的 Unix 时间戳 (毫秒)
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self._symbol_count: int = 0
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self._index_symbol_count: int = 0
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self._index_quotes_cache: pl.DataFrame | None = None
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# ================================================================
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# 生命周期
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# ================================================================
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def start(self, interval: float = 0.0) -> None:
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"""启动后台行情轮询线程。"""
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if self._running:
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return
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if interval <= 0:
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from app.services import preferences
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interval = preferences.get_realtime_quote_interval()
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self._interval = self._clamp_interval(interval)
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self._running = True
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self._enabled = True
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self._thread = threading.Thread(target=self._poll_loop, daemon=True)
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self._thread.start()
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self._save_enabled(True)
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logger.info("行情服务已启动, 轮询间隔 %.1fs", self._interval)
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def stop(self) -> None:
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"""停止后台行情轮询线程。"""
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self._running = False
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self._enabled = False
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if self._thread:
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self._thread.join(timeout=10)
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self._thread = None
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self._save_enabled(False)
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logger.info("行情服务已停止")
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def enable(self) -> bool:
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"""开启自动行情 (不立即启动线程，等下一个交易时段)。
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none/free 档无实时行情权限,拒绝开启并返回 False;
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starter+ 正常启动。返回值表示是否真正开启。
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"""
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if not self.is_realtime_allowed():
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logger.warning("实时行情开启被拒:当前档位(none/free)无实时行情权限")
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return False
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self._enabled = True
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self._save_enabled(True)
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if not self._running:
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from app.services import preferences
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self._interval = self._clamp_interval(preferences.get_realtime_quote_interval())
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self._running = True
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self._thread = threading.Thread(target=self._poll_loop, daemon=True)
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self._thread.start()
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logger.info("行情服务已启用, 轮询间隔 %.1fs", self._interval)
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def disable(self) -> None:
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"""关闭自动行情。"""
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self.stop()
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logger.info("行情服务已关闭")
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def boot_check(self) -> None:
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"""启动时检查 preferences，若 enabled 则自动启动。
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none/free 档无实时行情权限:即使 preferences 标记为 enabled,
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也不启动,并同步 preferences 为关闭(避免 UI 误显示已开启)。
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"""
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from app.services import preferences
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if not self.is_realtime_allowed():
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if preferences.get_realtime_quotes_enabled():
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self._save_enabled(False)
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logger.info("实时行情未启动:当前档位(none/free)无实时行情权限")
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return
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if preferences.get_realtime_quotes_enabled():
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self.start()
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def set_repo(self, repo) -> None:
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"""注入 KlineRepository, 用于实时落盘。"""
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self._repo = repo
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def set_app_state(self, app_state) -> None:
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"""注入 FastAPI app.state, 用于获取 strategy_monitor 等单例。"""
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self._app_state = app_state
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def set_interval(self, interval: float) -> float:
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"""运行时更新轮询间隔（立即生效）。"""
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clamped = self._clamp_interval(interval)
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self._interval = clamped
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from app.services import preferences
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preferences.set_realtime_quote_interval(clamped)
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logger.info("轮询间隔已更新为 %.1fs", clamped)
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return clamped
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def get_min_interval(self) -> float:
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"""返回当前档位允许的最小间隔。"""
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return self._tier_min_interval()
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def wait_for_update(self, timeout: float = 30.0) -> bool:
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"""阻塞等待下一次行情更新 (供 SSE 线程使用)。"""
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self._update_event.clear()
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return self._update_event.wait(timeout=timeout)
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def wait_for_alert(self, timeout: float = 30.0) -> bool:
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"""阻塞等待告警 (供 SSE 线程使用)。"""
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self._alert_event.clear()
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return self._alert_event.wait(timeout=timeout)
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def notify_depth_updated(self) -> None:
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"""五档盘口修正完成后调用: 通知 SSE 推送 depth_updated, 触发连板梯队刷新。
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与行情/告警通道独立 — 只刷新连板梯队, 不连带刷新 watchlist 等。
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"""
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self._depth_update_event.set()
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def wait_for_depth_update(self, timeout: float = 30.0) -> bool:
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"""阻塞等待 depth 修正 (供 SSE 线程使用)。"""
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self._depth_update_event.clear()
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return self._depth_update_event.wait(timeout=timeout)
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def pop_alerts(self) -> list[dict]:
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"""取走所有待推送的告警 (线程安全)。"""
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with self._lock:
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alerts = self._pending_alerts
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self._pending_alerts = []
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return alerts
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# ================================================================
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# 档位感知间隔限制
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# ================================================================
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@staticmethod
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def _current_tier() -> str:
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"""获取当前档位名（小写）。"""
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from app.tickflow.policy import tier_label
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return tier_label().split()[0].split("+")[0].strip().lower()
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@classmethod
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def is_realtime_allowed(cls) -> bool:
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"""当前档位是否允许使用实时行情。
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none/free 档走 free-api 服务器,无实时行情权限 → 不允许;
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starter+ 付费档走付费端点,有实时行情 → 允许。
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"""
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return cls._current_tier() not in ("none", "free")
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@classmethod
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def _tier_min_interval(cls) -> float:
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tier = cls._current_tier()
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return cls.TIER_MIN_INTERVAL.get(tier, cls.DEFAULT_INTERVAL)
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def _clamp_interval(self, interval: float) -> float:
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return max(self._tier_min_interval(), min(self.MAX_INTERVAL, interval))
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# ================================================================
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# 行情数据访问
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# ================================================================
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def get_enriched_today(self) -> tuple[pl.DataFrame, date | None]:
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"""返回今天 enriched 数据 + 日期 (线程安全)。
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所有页面统一通过此方法获取实时行情 + 技术指标。
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"""
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if not self._repo:
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return pl.DataFrame(), None
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return self._repo.get_enriched_latest()
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def get_quotes_compat(self) -> pl.DataFrame:
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"""兼容接口: 返回行情 DataFrame (用于盘中选股等需要 last_price/prev_close 的场景)。
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从 _enriched_cache 取 today 的数据, 只选行情基础列, 补上 last_price 别名。
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不返回指标列, 避免 JOIN live_agg 时列名冲突。
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"""
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df, _ = self.get_enriched_today()
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if df.is_empty():
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return df
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# 只取盘中选股需要的行情基础列
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keep = [c for c in [
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"symbol", "close", "open", "high", "low", "volume", "amount",
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"prev_close", "change_pct", "change_amount", "amplitude", "turnover_rate",
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] if c in df.columns]
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df = df.select(keep)
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# enriched 的 close 等价于 last_price
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if "close" in df.columns and "last_price" not in df.columns:
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df = df.with_columns(pl.col("close").alias("last_price"))
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return df
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def get_index_quotes(self, symbols: list[str] | None = None) -> pl.DataFrame:
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"""返回实时指数行情缓存。不会触发数据源请求。"""
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with self._lock:
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df = self._index_quotes_cache.clone() if self._index_quotes_cache is not None else pl.DataFrame()
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if df.is_empty():
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return df
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if symbols:
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return df.filter(pl.col("symbol").is_in(symbols))
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return df
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def status(self) -> dict:
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"""返回行情服务状态。"""
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age = (time.perf_counter() - self._fetch_time) * 1000 if self._fetch_time else -1
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return {
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"enabled": self._enabled,
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"running": self._running,
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"interval_s": self._interval,
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"symbol_count": self._symbol_count,
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"index_symbol_count": self._index_symbol_count,
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"quote_age_ms": round(age, 0) if age >= 0 else None,
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"is_trading_hours": self._is_trading_hours(),
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"last_fetch_ms": round(self._fetched_at, 0) if self._fetched_at else None,
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}
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def refresh(self) -> dict:
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"""手动触发一次行情拉取。"""
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self._fetch_quotes()
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return self.status()
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# ================================================================
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# 后台轮询
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# ================================================================
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def _poll_loop(self) -> None:
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while self._running and self._enabled:
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try:
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if self._is_trading_hours():
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self._fetch_quotes()
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else:
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logger.debug("非交易时段, 跳过行情轮询")
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except Exception as e: # noqa: BLE001
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logger.warning("行情轮询异常: %s", e)
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waited = 0.0
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while self._running and self._enabled and waited < self._interval:
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time.sleep(0.5)
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waited += 0.5
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def _fetch_quotes(self) -> None:
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"""拉取全市场行情 → 写 daily + 计算 enriched + 更新缓存。"""
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from app.tickflow.client import get_client
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tf = get_client()
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t0 = time.perf_counter()
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now_ts = time.perf_counter()
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try:
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all_index_symbols = set(self._repo.get_index_symbol_set()) if self._repo else set()
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all_index_symbols.update(self.CORE_INDEX_SYMBOLS)
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resp = tf.quotes.get_by_universes(universes=["CN_Equity_A", "CN_Index"])
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except Exception as e: # noqa: BLE001
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logger.warning("行情拉取失败: %s", e)
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return
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if not resp:
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logger.warning("行情数据为空")
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return
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# ---- 解析 API 响应 (临时变量, 用完丢弃) ----
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records = []
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for q in resp:
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ext = q.get("ext") or {}
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last_price = q.get("last_price")
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prev_close = q.get("prev_close")
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change_amount = ext.get("change_amount")
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change_pct = ext.get("change_pct")
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if change_amount is None and last_price is not None and prev_close is not None:
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change_amount = float(last_price) - float(prev_close)
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if change_pct is None and change_amount is not None and prev_close not in (None, 0):
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change_pct = float(change_amount) / float(prev_close) * 100
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records.append({
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"symbol": q.get("symbol"),
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"name": q.get("name") or ext.get("name"),
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"last_price": last_price,
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"prev_close": prev_close,
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"open": q.get("open"),
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"high": q.get("high"),
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"low": q.get("low"),
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"volume": q.get("volume"),
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"amount": q.get("amount"),
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"change_pct": change_pct,
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"change_amount": change_amount,
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"amplitude": ext.get("amplitude"),
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"turnover_rate": ext.get("turnover_rate"),
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"timestamp": q.get("timestamp"),
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"session": q.get("session"),
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})
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index_records = [r for r in records if r.get("symbol") in all_index_symbols]
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stock_records = [r for r in records if r.get("symbol") not in all_index_symbols]
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fetch_ms = (time.perf_counter() - t0) * 1000
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fetched_at = time.time() * 1000
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# ---- 更新元信息 ----
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with self._lock:
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self._fetch_time = now_ts
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self._fetch_ms = fetch_ms
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self._fetched_at = fetched_at
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self._symbol_count = len(stock_records)
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self._index_symbol_count = len(index_records)
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self._index_quotes_cache = self._build_index_quotes(index_records)
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logger.info("行情刷新: %d 只股票, %d 只指数, 耗时 %.0fms", len(stock_records), len(index_records), fetch_ms)
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# ---- 写 kline_daily (不复权原始价格, 只有 OHLCV) ----
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daily_df = self._build_daily(stock_records)
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if not daily_df.is_empty() and self._repo:
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try:
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self._repo.flush_live_daily(daily_df)
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except Exception as e: # noqa: BLE001
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logger.warning("日K写盘失败: %s", e)
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# ---- 构建 API 直接值的补充表 (不写 daily, 只用于 enriched 计算) ----
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quote_extra = self._build_quote_extra(stock_records)
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# ---- 增量计算 enriched + 写盘 + 更新缓存 ----
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if not daily_df.is_empty() and self._repo:
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self._flush_live_enriched(daily_df, quote_extra)
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# ---- 通知 SSE ----
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self._update_event.set()
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# ---- 策略监控 + 告警评估 ----
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self._evaluate_monitors(daily_df, quote_extra)
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# ================================================================
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# 工具
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# ================================================================
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@staticmethod
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def _build_daily(records: list[dict]) -> pl.DataFrame:
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"""将 API records 转为日K格式 DataFrame (只有 OHLCV, 写 kline_daily 用)。"""
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if not records:
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return pl.DataFrame()
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df = pl.DataFrame(records)
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cols_map = {
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"symbol": "symbol",
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"last_price": "close",
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"open": "open",
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"high": "high",
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"low": "low",
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"volume": "volume",
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"amount": "amount",
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}
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select_exprs = []
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for src, dst in cols_map.items():
|
||||
if src in df.columns:
|
||||
select_exprs.append(pl.col(src).alias(dst))
|
||||
if not select_exprs:
|
||||
return pl.DataFrame()
|
||||
result = df.select(select_exprs).with_columns(
|
||||
pl.lit(date.today()).cast(pl.Date).alias("date"),
|
||||
)
|
||||
# 修复: API 在非交易时段可能返回 open/high/low=0 或 null,
|
||||
# 导致蜡烛从 0 开始。用 close 填充这些异常值。
|
||||
for col in ("open", "high", "low"):
|
||||
if col in result.columns:
|
||||
result = result.with_columns(
|
||||
pl.when((pl.col(col) == 0) | pl.col(col).is_null())
|
||||
.then(pl.col("close"))
|
||||
.otherwise(pl.col(col))
|
||||
.alias(col)
|
||||
)
|
||||
return result
|
||||
|
||||
@staticmethod
|
||||
def _build_quote_extra(records: list[dict]) -> pl.DataFrame:
|
||||
"""构建 API 直接提供的补充字段 (不写 daily, 只传给 enriched 计算)。
|
||||
|
||||
包含: prev_close, change_pct, change_amount, amplitude, turnover_rate。
|
||||
"""
|
||||
if not records:
|
||||
return pl.DataFrame()
|
||||
df = pl.DataFrame(records)
|
||||
keep = [c for c in [
|
||||
"symbol", "prev_close", "change_pct", "change_amount",
|
||||
"amplitude", "turnover_rate",
|
||||
] if c in df.columns]
|
||||
if not keep or "symbol" not in keep:
|
||||
return pl.DataFrame()
|
||||
return df.select(keep)
|
||||
|
||||
@staticmethod
|
||||
def _build_index_quotes(records: list[dict]) -> pl.DataFrame:
|
||||
"""构建指数实时行情缓存，不落股票 parquet。
|
||||
|
||||
注意: API 返回的 change_pct/amplitude 是小数 (0.0366 = 3.66%),
|
||||
统一转成百分比输出, 与 _fallback_index_quotes_from_daily 口径一致
|
||||
(前端指数侧不×100, 直接 toFixed(2)% 展示)。
|
||||
"""
|
||||
if not records:
|
||||
return pl.DataFrame()
|
||||
df = pl.DataFrame(records)
|
||||
keep = [c for c in [
|
||||
"symbol", "name", "last_price", "prev_close", "open", "high", "low",
|
||||
"volume", "amount", "change_pct", "change_amount", "amplitude", "timestamp", "session",
|
||||
] if c in df.columns]
|
||||
if not keep or "symbol" not in keep:
|
||||
return pl.DataFrame()
|
||||
df = df.select(keep)
|
||||
# change_pct / amplitude: 小数 → 百分比 (统一指数展示口径)
|
||||
for col in ("change_pct", "amplitude"):
|
||||
if col in df.columns:
|
||||
df = df.with_columns((pl.col(col).cast(pl.Float64) * 100).alias(col))
|
||||
if "last_price" in df.columns and "close" not in df.columns:
|
||||
df = df.with_columns(pl.col("last_price").alias("close"))
|
||||
return df
|
||||
|
||||
@staticmethod
|
||||
def _is_trading_hours() -> bool:
|
||||
now = datetime.now()
|
||||
t = now.time()
|
||||
morning = dt_time(9, 15) <= t <= dt_time(11, 35)
|
||||
afternoon = dt_time(12, 55) <= t <= dt_time(15, 5)
|
||||
return now.weekday() < 5 and (morning or afternoon)
|
||||
|
||||
@staticmethod
|
||||
def _save_enabled(enabled: bool) -> None:
|
||||
from app.services import preferences
|
||||
preferences.save({"realtime_quotes_enabled": enabled})
|
||||
|
||||
# ================================================================
|
||||
# 策略监控
|
||||
# ================================================================
|
||||
|
||||
def _evaluate_monitors(self, daily_df: pl.DataFrame, quote_extra: pl.DataFrame | None) -> None:
|
||||
"""行情更新后评估统一监控规则引擎,并刷新策略结果缓存。"""
|
||||
try:
|
||||
# 获取 enriched 数据 (刚算好的)
|
||||
enriched_today, enriched_date = self.get_enriched_today()
|
||||
if enriched_today.is_empty():
|
||||
return
|
||||
|
||||
all_alerts: list[dict] = []
|
||||
|
||||
# 通用监控规则评估 (统一引擎: signal/price/market/strategy)
|
||||
if self._app_state:
|
||||
engine = getattr(self._app_state, "monitor_engine", None)
|
||||
if engine and engine.rule_count > 0:
|
||||
# 预构建 symbol → name 映射 (enriched 已 drop name 列, 引擎触发时回填用)
|
||||
try:
|
||||
inst_df = self._app_state.repo.get_instruments()
|
||||
if not inst_df.is_empty() and "symbol" in inst_df.columns and "name" in inst_df.columns:
|
||||
engine.set_name_map({
|
||||
row["symbol"]: row["name"]
|
||||
for row in inst_df.select(["symbol", "name"]).iter_rows(named=True)
|
||||
if row.get("name")
|
||||
})
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.debug("name_map 构建失败 (不影响监控): %s", e)
|
||||
rule_events = engine.evaluate(enriched_today)
|
||||
if rule_events:
|
||||
# 落盘到 alerts.jsonl
|
||||
try:
|
||||
from app.services import alert_store
|
||||
alert_store.append_many(
|
||||
self._app_state.repo.store.data_dir, rule_events,
|
||||
)
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.warning("告警落盘失败: %s", e)
|
||||
# 转为 SSE 推送格式 (兼容旧 alert schema)
|
||||
for ev in rule_events:
|
||||
all_alerts.append({
|
||||
"source": ev["source"],
|
||||
"type": ev["type"],
|
||||
"rule_id": ev.get("rule_id"),
|
||||
"strategy_id": ev.get("rule_id") if ev["source"] == "strategy" else None,
|
||||
"symbol": ev["symbol"],
|
||||
"name": ev["name"],
|
||||
"message": ev["message"],
|
||||
"price": ev["price"],
|
||||
"change_pct": ev["change_pct"],
|
||||
"signals": ev["signals"],
|
||||
"severity": ev.get("severity", "info"),
|
||||
})
|
||||
|
||||
# 刷新策略结果缓存 (实时行情开启时，每轮行情更新后自动重算)
|
||||
if self._enabled and self._app_state:
|
||||
self._refresh_strategy_cache(enriched_today, enriched_date)
|
||||
|
||||
# 推入待推送队列 + 通知 SSE (含背压保护)
|
||||
if all_alerts:
|
||||
with self._lock:
|
||||
self._pending_alerts.extend(all_alerts)
|
||||
# 背压: 超出上限丢弃最旧
|
||||
if len(self._pending_alerts) > self._max_pending_alerts:
|
||||
overflow = len(self._pending_alerts) - self._max_pending_alerts
|
||||
self._pending_alerts = self._pending_alerts[overflow:]
|
||||
self._alert_event.set()
|
||||
logger.info("监控评估完成: %d 条通知", len(all_alerts))
|
||||
|
||||
# 系统通知 (可选通道, 由 preferences 开关控制)。
|
||||
# cooldown 去重已在 MonitorRuleEngine 做过, 这里只负责转发。
|
||||
self._maybe_send_system_notifications(all_alerts)
|
||||
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.warning("监控评估失败: %s", e)
|
||||
|
||||
def _maybe_send_system_notifications(self, all_alerts: list[dict]) -> None:
|
||||
"""把告警转发到操作系统通知中心 (由 preferences 开关控制)。
|
||||
|
||||
- 开关关闭: 直接返回
|
||||
- 开关开启: 逐条发系统通知; 失败静默, 不阻断主流程
|
||||
- 去重: 复用 MonitorRuleEngine 的 cooldown, 此处不重复去重
|
||||
- 批量策略事件 (symbol="") 聚合为一条通知, 避免刷屏
|
||||
"""
|
||||
try:
|
||||
from app.services import preferences
|
||||
from app.services import notify_adapter
|
||||
|
||||
if not preferences.get_system_notify_enabled():
|
||||
return
|
||||
|
||||
for ev in all_alerts:
|
||||
# 通知标题: 用 source 分类 (策略/信号/价格/异动)
|
||||
source = ev.get("source", "")
|
||||
source_label = {
|
||||
"strategy": "策略", "signal": "信号",
|
||||
"price": "价格", "market": "异动",
|
||||
}.get(source, source or "通知")
|
||||
|
||||
name = ev.get("name") or ""
|
||||
symbol = ev.get("symbol") or ""
|
||||
message = ev.get("message") or ""
|
||||
|
||||
# 正文: 优先用现成 message, 拼上 symbol/name 让用户一眼定位
|
||||
if symbol:
|
||||
body = f"{symbol} {name} {message}".strip()
|
||||
else:
|
||||
body = message or name
|
||||
|
||||
title = f"Stock Panel · {source_label}"
|
||||
notify_adapter.notify(title, body)
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.debug("系统通知发送异常 (不影响告警主流程): %s", e)
|
||||
|
||||
def _refresh_strategy_cache(self, enriched_today: pl.DataFrame, enriched_date: date | None) -> None:
|
||||
"""利用已计算好的 enriched 数据，运行策略池并写入缓存。"""
|
||||
import math
|
||||
from dataclasses import asdict
|
||||
from app.services import strategy_cache
|
||||
from app.services.screener import PRESET_STRATEGIES, ScreenerService
|
||||
from app.strategy import config as strategy_config
|
||||
|
||||
try:
|
||||
if enriched_date is None:
|
||||
return
|
||||
as_of = enriched_date
|
||||
data_dir = self._repo.store.data_dir
|
||||
svc = ScreenerService(self._repo)
|
||||
engine = getattr(self._app_state, "strategy_engine", None)
|
||||
|
||||
# 确定要运行的策略: 策略监控池中的策略
|
||||
monitor_ids = self._get_monitor_pool_ids()
|
||||
if not monitor_ids:
|
||||
return
|
||||
|
||||
# 一次加载所有 override
|
||||
all_overrides = strategy_config.list_overrides(data_dir)
|
||||
|
||||
# 历史策略: 只在需要时加载
|
||||
shared_history = None
|
||||
history_strats = []
|
||||
if engine:
|
||||
id_set = set(monitor_ids)
|
||||
history_strats = [
|
||||
(sid, s) for sid, s in engine._strategies.items()
|
||||
if s.filter_history_fn and sid in id_set
|
||||
]
|
||||
if history_strats:
|
||||
max_lb = max(s.lookback_days for _, s in history_strats)
|
||||
shared_history = svc._load_enriched_history(as_of, max(1, max_lb))
|
||||
|
||||
results: dict[str, dict] = {}
|
||||
for sid in monitor_ids:
|
||||
try:
|
||||
overrides = all_overrides.get(sid, {})
|
||||
bf = overrides.get("basic_filter") if overrides else None
|
||||
dl = overrides.get("display_limit") if overrides else None
|
||||
if dl is None and overrides and "display_limit" in overrides:
|
||||
dl = 0
|
||||
|
||||
if sid in PRESET_STRATEGIES:
|
||||
r = svc.run_preset(sid, as_of=as_of, precomputed=enriched_today, basic_filter=bf, display_limit=dl)
|
||||
elif engine:
|
||||
r = engine.run(
|
||||
sid, as_of, overrides=overrides or None,
|
||||
precomputed=enriched_today, precomputed_history=shared_history,
|
||||
)
|
||||
if dl is not None and dl > 0:
|
||||
r.rows = r.rows[:dl]
|
||||
r.total = min(r.total, dl)
|
||||
else:
|
||||
continue
|
||||
|
||||
# sanitize NaN/Inf
|
||||
rows = []
|
||||
for row_dict in asdict(r).get("rows", []):
|
||||
for k, v in list(row_dict.items()):
|
||||
if isinstance(v, float) and not math.isfinite(v):
|
||||
row_dict[k] = None
|
||||
rows.append(row_dict)
|
||||
results[sid] = {"total": r.total, "as_of": str(as_of), "rows": rows}
|
||||
except Exception: # noqa: BLE001
|
||||
continue
|
||||
|
||||
if results:
|
||||
strategy_cache.write_cache(data_dir, str(as_of), results)
|
||||
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.warning("策略缓存刷新失败: %s", e)
|
||||
|
||||
def _get_monitor_pool_ids(self) -> list[str]:
|
||||
"""获取策略监控池中的策略 ID 列表。"""
|
||||
from app.services import preferences
|
||||
ids = preferences.get_strategy_monitor_ids()
|
||||
if not ids:
|
||||
return []
|
||||
return [sid for sid in ids if sid]
|
||||
|
||||
@staticmethod
|
||||
def _get_strategy_monitor():
|
||||
"""获取 StrategyMonitorService — 不再使用, 改用 _app_state 注入。"""
|
||||
return None
|
||||
|
||||
# ================================================================
|
||||
# enriched 增量计算
|
||||
# ================================================================
|
||||
|
||||
def _flush_live_enriched(self, daily_df: pl.DataFrame, quote_extra: pl.DataFrame = None) -> None:
|
||||
"""增量计算今天的 enriched: 用昨天的递推状态 + 今天 OHLCV → 只算今天 5500 行。
|
||||
|
||||
quote_extra: API 直接提供的补充字段 (prev_close, change_pct 等),
|
||||
不写 daily, 直接传给 compute_enriched_today 避免重复计算。
|
||||
"""
|
||||
try:
|
||||
today = date.today()
|
||||
t0 = time.perf_counter()
|
||||
|
||||
# ---- 尝试增量路径 ----
|
||||
live_agg = self._repo.get_live_agg()
|
||||
prev_enriched, prev_date = self._repo.get_enriched_latest()
|
||||
|
||||
use_incremental = (
|
||||
not live_agg.is_empty()
|
||||
and not prev_enriched.is_empty()
|
||||
and prev_date is not None
|
||||
)
|
||||
|
||||
if use_incremental:
|
||||
from app.indicators.pipeline import compute_enriched_today
|
||||
instruments = self._repo.get_instruments()
|
||||
# 将 API 直接提供的补充字段 JOIN 到 daily_df
|
||||
today_ohlcv = daily_df
|
||||
if quote_extra is not None and not quote_extra.is_empty():
|
||||
today_ohlcv = daily_df.join(quote_extra, on="symbol", how="left")
|
||||
enriched_today = compute_enriched_today(
|
||||
live_agg=live_agg,
|
||||
prev_enriched=prev_enriched,
|
||||
today_ohlcv=today_ohlcv,
|
||||
instruments=instruments,
|
||||
)
|
||||
if enriched_today.is_empty():
|
||||
logger.warning("增量计算结果为空, 回退到全量计算")
|
||||
use_incremental = False
|
||||
|
||||
# ---- 全量回退路径 ----
|
||||
if not use_incremental:
|
||||
from datetime import timedelta
|
||||
from app.indicators.pipeline import compute_enriched
|
||||
|
||||
logger.info("enriched 全量计算 (live_agg=%s, 上次日期=%s)",
|
||||
"ok" if not live_agg.is_empty() else "空", prev_date)
|
||||
|
||||
cutoff = today - timedelta(days=90)
|
||||
daily_glob = str(self._repo.store.data_dir / "kline_daily" / "**" / "*.parquet")
|
||||
ohlcv_cols = ["symbol", "date", "open", "high", "low", "close", "volume", "amount"]
|
||||
hist_df = (
|
||||
pl.scan_parquet(daily_glob)
|
||||
.filter(pl.col("date") >= cutoff)
|
||||
.sort(["symbol", "date"])
|
||||
.collect()
|
||||
)
|
||||
if hist_df.is_empty():
|
||||
return
|
||||
|
||||
hist_cols = [c for c in ohlcv_cols if c in hist_df.columns]
|
||||
hist_df = hist_df.select(hist_cols).filter(pl.col("date") != today)
|
||||
daily_ohlcv = daily_df.select([c for c in ohlcv_cols if c in daily_df.columns])
|
||||
full_df = pl.concat([hist_df, daily_ohlcv], how="diagonal_relaxed")
|
||||
full_df = full_df.sort(["symbol", "date"])
|
||||
|
||||
factor_path = self._repo.store.data_dir / "adj_factor" / "all.parquet"
|
||||
factors = pl.DataFrame()
|
||||
if factor_path.exists():
|
||||
try:
|
||||
factors = pl.read_parquet(factor_path)
|
||||
except Exception:
|
||||
pass
|
||||
instruments = self._repo.get_instruments()
|
||||
|
||||
enriched_full = compute_enriched(full_df, factors=factors, instruments=instruments)
|
||||
enriched_today = enriched_full.filter(pl.col("date") == today)
|
||||
|
||||
if enriched_today.is_empty():
|
||||
return
|
||||
|
||||
# ---- 写盘 + 更新缓存 ----
|
||||
self._repo.flush_live_enriched(enriched_today)
|
||||
|
||||
elapsed = time.perf_counter() - t0
|
||||
mode_label = "增量" if use_incremental else "全量"
|
||||
logger.info("enriched %s: %d 只, %s, 耗时 %.0fms",
|
||||
mode_label, len(enriched_today), today, elapsed * 1000)
|
||||
except Exception as e: # noqa: BLE001
|
||||
logger.warning("enriched 计算失败: %s", e)
|
||||
Reference in New Issue
Block a user