dekun
86 lines
2.8 KiB
Python
86 lines
2.8 KiB
Python
"""品种推荐 SSE 推送与后台刷新。"""
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from __future__ import annotations
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import json
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import logging
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import queue
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import threading
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import time
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from typing import Callable, Optional
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from db_conn import connect_db
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from kline_stream import sse_format
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from recommend_store import load_recommend_cache, recommend_cache_stale, refresh_recommend_cache
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logger = logging.getLogger(__name__)
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CHECK_INTERVAL_SEC = 3600
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class RecommendStreamHub:
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def __init__(self) -> None:
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self._lock = threading.Lock()
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self._subs: list[queue.Queue] = []
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def subscribe(self) -> queue.Queue:
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q: queue.Queue = queue.Queue(maxsize=8)
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with self._lock:
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self._subs.append(q)
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return q
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def unsubscribe(self, q: queue.Queue) -> None:
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with self._lock:
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try:
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self._subs.remove(q)
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except ValueError:
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pass
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def broadcast(self, event: str, data: dict) -> None:
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msg = {"event": event, "data": data}
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with self._lock:
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subs = list(self._subs)
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for q in subs:
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try:
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q.put_nowait(msg)
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except queue.Full:
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pass
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recommend_hub = RecommendStreamHub()
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def start_recommend_worker(
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*,
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db_path: str,
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get_capital_fn: Callable,
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quote_fn: Callable[[str], Optional[dict]],
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init_tables_fn: Callable | None = None,
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get_mode_fn: Callable[[], str] | None = None,
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interval: int = CHECK_INTERVAL_SEC,
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) -> None:
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"""后台每日刷新推荐（每小时检查一次是否需更新），并推送给 SSE 订阅者。"""
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def _loop() -> None:
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while True:
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try:
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conn = connect_db(db_path)
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try:
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if init_tables_fn:
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init_tables_fn(conn)
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capital = float(get_capital_fn(conn) or 0)
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mode = get_mode_fn() if get_mode_fn else "simulation"
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cached = load_recommend_cache(conn)
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if recommend_cache_stale(cached.get("updated_at")):
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refresh_recommend_cache(conn, capital, quote_fn, trading_mode=mode)
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cached = load_recommend_cache(conn)
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logger.info("品种推荐每日刷新完成，capital=%.2f rows=%d", capital, len(cached.get("rows") or []))
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payload = {**cached, "capital": capital}
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finally:
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conn.close()
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recommend_hub.broadcast("recommend", {"ok": True, **payload})
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except Exception as exc:
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logger.warning("recommend worker failed: %s", exc)
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time.sleep(max(300, interval))
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threading.Thread(target=_loop, daemon=True, name="recommend-worker").start()
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