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backend/app/screener/engine.py

@@ -5,6 +5,8 @@ pandas 逐股计算（复用 app/indicators，指标按 (族, 参数) 去重计
 """
 from __future__ import annotations
 
+import asyncio
+import time
 from dataclasses import dataclass
 from datetime import datetime
 from typing import Callable
@@ -108,6 +110,10 @@ _IND_SUFFIX = {"kdj_k": "K", "kdj_d": "D", "kdj_j": "J",
                "boll_upper": "上轨", "boll_mid": "中轨", "boll_lower": "下轨",
                "zhixing_dkx": "多空线", "zhixing_trend": "趋势线"}
 
+# 不消费族参数的指标（展示名不拼参数串）：趋势线固定 EMA(EMA(C,10),10)，
+# m1~m4 只属于多空线，拼上会误导（如「知行 趋势线(14,28,57,114)」）
+_IND_PARAMLESS = {"zhixing_trend"}
+
 
 def _family_of(indicator: str) -> str:
     fam = INDICATOR_FAMILY.get(indicator)
@@ -139,6 +145,8 @@ def indicator_label(indicator: str, params: dict) -> str:
     fam = FAMILIES[_family_of(indicator)]
     suffix = _IND_SUFFIX.get(indicator)
     name = f"{fam.label} {suffix}".strip() if suffix else fam.label
+    if indicator in _IND_PARAMLESS:
+        return name
     return name + _params_str(params)
 
 
@@ -352,8 +360,17 @@ def _item_from_row(row) -> dict:
     }
 
 
-async def run_screen(session: AsyncSession, conds: ScreenConditions, limit: int) -> dict:
-    """主流程：预筛 -> 逐股指标过滤 -> 组装 items + indicator_labels。"""
+async def run_screen_events(session: AsyncSession, conds: ScreenConditions, limit: int):
+    """事件流版主流程：预筛 -> 逐股指标过滤 -> 组装 items + indicator_labels。
+
+    逐步 yield 进度事件（含累计耗时 ms），最后 yield {"type": "result", "result": {...}}，
+    供 /screener/run 流式响应下发；阶段事件结构见 api.py 的 NDJSON 约定。
+    """
+    t0 = time.perf_counter()
+
+    def _ev(**kw) -> dict:
+        return {"ms": round((time.perf_counter() - t0) * 1000), **kw}
+
     if not conds.indicator and not conds.snapshot:
         raise ValueError("筛选条件为空")
 
@@ -362,6 +379,7 @@ async def run_screen(session: AsyncSession, conds: ScreenConditions, limit: int)
     )
     if target_date is None:
         raise DataNotReadyError("全市场数据未同步：请先在选股页点击「同步市场数据」")
+    yield _ev(type="stage", key="date", msg=f"数据基准日 {target_date:%Y-%m-%d}")
 
     if any(c.field != "close" for c in conds.snapshot):
         if await session.scalar(select(func.max(DailySnapshot.trade_date))) is None:
@@ -370,7 +388,9 @@ async def run_screen(session: AsyncSession, conds: ScreenConditions, limit: int)
                 "市值/市盈率等条件无法使用，纯指标条件不受影响"
             )
 
+    yield _ev(type="stage", key="prefilter", msg="最新交易日截面预筛…")
     cand = await _prefilter(session, conds, target_date)
+    yield _ev(type="candidates", count=len(cand), msg=f"预筛完成：{len(cand)} 只候选")
 
     labels: dict[str, str] = {}
     for c in conds.indicator:
@@ -388,6 +408,7 @@ async def run_screen(session: AsyncSession, conds: ScreenConditions, limit: int)
     else:
         # 圈定 K 线窗口：按 candles 全量交易日序列回溯 needed 根（不再受同步窗口限制）
         need = _max_needed_bars(conds)
+        yield _ev(type="stage", key="bars", msg=f"载入 K 线窗口（每股回溯 {need} 根）…")
         dates_res = await session.execute(
             select(Candle.ts).where(Candle.timeframe == "1d").distinct()
             .order_by(Candle.ts.desc()).limit(need)
@@ -395,8 +416,12 @@ async def run_screen(session: AsyncSession, conds: ScreenConditions, limit: int)
         min_date = min(r[0] for r in dates_res)
         bars = await _load_bars(session, cand["ts_code"].tolist(), target_date, min_date)
         cand_rows = {r["ts_code"]: r for _, r in cand.iterrows()}
+        total = len(cand)
 
-        for ts_code, g in bars.groupby("ts_code", sort=False):
+        for i, (ts_code, g) in enumerate(bars.groupby("ts_code", sort=False), 1):
+            if i % 500 == 0 or i == total:
+                yield _ev(type="progress", done=i, total=total)
+                await asyncio.sleep(0)  # 让出事件循环，流式响应即时下发
             row = cand_rows.get(ts_code)
             if row is None:
                 continue
@@ -415,13 +440,22 @@ async def run_screen(session: AsyncSession, conds: ScreenConditions, limit: int)
                     ind_values[c.value_indicator] = None if s is None or s.iloc[-1] != s.iloc[-1] else float(s.iloc[-1])
             if ok:
                 items.append(_item_from_row(row) | {"indicators": ind_values})
+        yield _ev(type="stage", key="filter_done", msg=f"指标过滤完成：{len(items)} 只命中")
 
     # 默认总市值降序（缺失排最后），截断 limit
     items.sort(key=lambda x: (x["total_mv"] is None, -(x["total_mv"] or 0)))
-    return {
+    yield _ev(type="result", result={
         "conditions": conds,
         "trade_date": target_date,
         "total": len(items),
         "items": items[:limit],
         "indicator_labels": labels,
-    }
+    })
+
+
+async def run_screen(session: AsyncSession, conds: ScreenConditions, limit: int) -> dict:
+    """兼容包装：跑完事件流，返回最终 result（一次性拿全量，无进度）。"""
+    async for ev in run_screen_events(session, conds, limit):
+        if ev["type"] == "result":
+            return ev["result"]
+    raise RuntimeError("run_screen_events 未产出 result")  # pragma: no cover