feat(screener): run_all 渐进式返回, 快策略先出、慢策略后台补算

策略页全量 run_all 需 ~2 分钟, 期间卡片全空。现在按历史耗时升序执行,
首返时限 (strategy_run_all_first_return_s, 默认 15s) 内算完的策略随
响应返回, 慢策略转后台继续算并逐个写入策略缓存, 前端轮询
cached-summary 逐个点亮卡片数字 (未出的显示脉冲占位)。

后端:
- services/strategy_run_queue: 单飞 daemon 工作线程 + handle 状态。
  相同 key (资产/周期/日期/策略集) 且未完成的请求搭车现有执行不重算;
  已完成的重跑即新执行。后端全局同时只跑一个 run_all, 补上前端
  防重入之外的第二道 Numba 并发防线
- run_all 渐进分支 (仅日线 + summary_only): 逐策略增量写缓存 (同日
  按 sid 合并), 收尾整体重写保持旧口径; 结果带 computed_at 时间戳;
  分钟周期与明细请求保持整段阻塞不变
- 历史耗时落盘 user_data/strategy_run_timings.json, 次日起快策略自动
  排前; cached-summary 透传 computed_at

前端:
- 请求通用 30s 超时 + 慢接口豁免清单 (run_all/run/backtest/factor 等
  300s), 避免一个挂起请求占满 HTTP/1.1 连接拖死全站
- Screener: 收到 pending 后 summaryQuery 每 2s 轮询, 以
  computed_at >= started_at 判新 (防同日旧缓存冒充), 8 分钟兜底;
  StrategyCard 三种尺寸新增 computing 脉冲占位

验证: 新增 13 测试 (排序/落盘/搭车/串行化/端点行为/旧路径兼容),
全量套件 1762 passed; pnpm build 通过。

backend/app/api/screener.py

@@ -1,6 +1,7 @@
 """Screener API。"""
 from __future__ import annotations
 
+import contextlib
 import glob as _glob
 import logging
 import math
@@ -14,8 +15,9 @@ from typing import Any, Optional
 from fastapi import APIRouter, HTTPException, Query, Request
 from pydantic import BaseModel
 
+from app.config import settings
 from app.db_safe import is_valid_ext_ident, quote_ident
-from app.services import strategy_cache
+from app.services import strategy_cache, strategy_run_queue
 from app.services.screener import ScreenerService
 from app.strategy import config as strategy_config
 
@@ -379,6 +381,9 @@ def get_cached_summary(request: Request):
         sid: {
             "total": int(result.get("total") or 0),
             "as_of": result.get("as_of"),
+            # 渐进式 run_all 写入的计算时间戳; 监控实时叠加/旧缓存无此字段 → None,
+            # 前端视为新鲜 (有值即为最新一轮实时结果)
+            "computed_at": result.get("computed_at"),
         }
         for sid, result in results.items()
         if isinstance(result, dict)
@@ -497,6 +502,98 @@ def market_snapshot(request: Request):
     return {"as_of": str(as_of), "rows": rows}
 
 
+def _run_all_progressive(
+    *,
+    repo,
+    engine,
+    svc: ScreenerService,
+    as_of,
+    asset_type: str,
+    timeframe: str,
+    all_ids: list[str],
+    params_map: dict,
+    overrides_map: dict,
+    first_return_s: float,
+    t_total: float,
+) -> dict:
+    """run_all 渐进式执行: 快策略随响应先返回, 慢策略后台算完逐个落缓存。
+
+    执行全程在单飞执行器里 (见 services/strategy_run_queue.py): 相同请求
+    搭车现有执行, 不同请求排队; HTTP 侧只轮询状态快照到首返时限。
+    """
+    data_dir = repo.store.data_dir
+    key = (asset_type, timeframe, str(as_of), tuple(sorted(all_ids)))
+    ordered_ids = strategy_run_queue.order_strategy_ids(
+        all_ids, strategy_run_queue.load_run_timings(data_dir)
+    )
+
+    def job(handle: strategy_run_queue.StrategyRunHandle) -> None:
+        context = svc.build_strategy_context(
+            engine,
+            as_of,
+            ordered_ids,
+            timeframe=timeframe,
+            params_map=params_map,
+            overrides_map=overrides_map,
+        )
+        all_results: dict[str, dict] = {}
+        elapsed_map: dict[str, float] = {}
+        for sid in ordered_ids:
+            t0 = time.perf_counter()
+            single = engine.run_all(
+                context,
+                params_map=params_map,
+                overrides_map=overrides_map,
+                strategy_ids=[sid],
+                parallel=False,
+            )
+            result = single[sid]
+            payload = {
+                "total": result.total,
+                "as_of": str(as_of),
+                "rows": _safe(asdict(result)).get("rows", []),
+                "computed_at": int(time.time() * 1000),
+            }
+            all_results[sid] = payload
+            elapsed_map[sid] = (time.perf_counter() - t0) * 1000
+            # 逐策略增量落盘 (write_cache 同日按 sid 合并), 前端轮询即可逐个看到
+            try:
+                strategy_cache.write_cache(data_dir, str(as_of), {sid: payload})
+            except Exception:
+                logger.warning("run_all 渐进写入缓存失败: %s", sid, exc_info=True)
+            handle.complete(sid, {k: v for k, v in payload.items() if k != "rows"})
+        # 收尾: 与旧版口径一致的整体重写 + 耗时落盘供下次排序
+        if all_results:
+            with contextlib.suppress(Exception):
+                strategy_cache.write_cache(data_dir, str(as_of), all_results)
+        strategy_run_queue.record_run_timings(data_dir, elapsed_map)
+
+    handle = strategy_run_queue.MANAGER.get_or_submit(key, ordered_ids, job)
+    deadline = time.perf_counter() + first_return_s
+    snap = handle.snapshot()
+    while not snap["done"] and time.perf_counter() < deadline:
+        time.sleep(0.2)
+        snap = handle.snapshot()
+
+    done_results = snap["results"]
+    if snap["error"] and not done_results:
+        raise HTTPException(status_code=500, detail=snap["error"])
+    logger.info(
+        "run_all: first return %.1fms (%d done, %d pending)",
+        (time.perf_counter() - t_total) * 1000,
+        len(done_results),
+        len(snap["pending"]),
+    )
+    return {
+        "as_of": str(as_of),
+        "results": done_results,
+        "pending": snap["pending"],
+        "complete": snap["done"] and not snap["error"],
+        "error": snap["error"],
+        "started_at": snap["started_at_ms"],
+    }
+
+
 @router.post("/run_all")
 def run_all(request: Request, body: Optional[dict] = None):
     """批量运行指定策略；注册、路由和执行均由 StrategyEngine 负责。"""
@@ -556,6 +653,26 @@ def run_all(request: Request, body: Optional[dict] = None):
         for sid in all_ids
     }
     overrides_map = {sid: all_overrides.get(sid, {}) for sid in all_ids}
+
+    # 渐进式返回 (页面首屏路径): 按历史耗时升序执行, 首返时限内算完的随响应
+    # 返回, 慢策略转后台继续算并逐个写入策略缓存, 前端轮询 cached-summary 点亮。
+    # 仅日线 + summary_only (策略页卡片) 启用; 分钟/明细请求保持整段阻塞。
+    first_return_s = settings.strategy_run_all_first_return_s
+    if body.get("summary_only") and timeframe == "1d" and first_return_s > 0:
+        return _run_all_progressive(
+            repo=repo,
+            engine=engine,
+            svc=svc,
+            as_of=as_of,
+            asset_type=asset_type,
+            timeframe=timeframe,
+            all_ids=all_ids,
+            params_map=params_map,
+            overrides_map=overrides_map,
+            first_return_s=first_return_s,
+            t_total=t_total,
+        )
+
     try:
         context = svc.build_strategy_context(
             engine,

backend/app/services/strategy_run_queue.py

@@ -0,0 +1,173 @@
+"""策略 run_all 渐进式执行 — 单飞后台执行 + 快策略先返回。
+
+页面进入策略页时 run_all 全量跑需要 ~2 分钟, 用户只能盯着空卡片等。此模块把
+执行拆成「同步等一小段 + 后台继续算」:
+
+- 全局同一时刻只执行一个 run_all (polars/Numba 并发跑两份有崩死风险),
+  请求先到先得, 后来者排队; 相同 key (资产/周期/日期/策略集) 的重复请求
+  直接搭车现有执行, 不重复算。
+- 按历史耗时升序执行: 快策略 (秒级) 在首返时限内完成并随 HTTP 响应返回,
+  慢策略 (分钟级) 留在后台慢慢算。
+- 每个策略算完立刻增量写入 strategy_cache, 前端轮询 cached-summary
+  逐个点亮卡片数字。
+"""
+from __future__ import annotations
+
+import json
+import logging
+import os
+import queue
+import threading
+import time
+from collections.abc import Callable
+from pathlib import Path
+
+logger = logging.getLogger(__name__)
+
+_TIMINGS_FILENAME = "strategy_run_timings.json"
+_timings_lock = threading.Lock()
+
+
+def _timings_path(data_dir: Path) -> Path:
+    return data_dir / "user_data" / _TIMINGS_FILENAME
+
+
+def load_run_timings(data_dir: Path) -> dict[str, float]:
+    """读取各策略上次执行耗时 (ms); 无文件/损坏时返回空。"""
+    with _timings_lock:
+        try:
+            data = json.loads(_timings_path(data_dir).read_text(encoding="utf-8"))
+        except (FileNotFoundError, ValueError, OSError):
+            return {}
+    if not isinstance(data, dict):
+        return {}
+    return {str(k): float(v) for k, v in data.items() if isinstance(v, (int, float))}
+
+
+def record_run_timings(data_dir: Path, elapsed_ms: dict[str, float]) -> None:
+    """批量记录策略耗时 (ms), 与已有文件合并后原子重写。"""
+    if not elapsed_ms:
+        return
+    with _timings_lock:
+        path = _timings_path(data_dir)
+        path.parent.mkdir(parents=True, exist_ok=True)
+        merged: dict[str, float] = {}
+        try:
+            old = json.loads(path.read_text(encoding="utf-8"))
+            if isinstance(old, dict):
+                merged = {str(k): float(v) for k, v in old.items() if isinstance(v, (int, float))}
+        except (FileNotFoundError, ValueError, OSError):
+            pass
+        merged.update({sid: float(ms) for sid, ms in elapsed_ms.items()})
+        tmp = path.with_name(path.name + ".tmp")
+        tmp.write_text(json.dumps(merged, ensure_ascii=False), encoding="utf-8")
+        os.replace(tmp, path)
+
+
+def order_strategy_ids(all_ids: list[str], timings: dict[str, float]) -> list[str]:
+    """快策略先算: 有历史耗时的按耗时升序, 未知耗时的保持原顺序排在后面。"""
+    known = sorted(
+        (timings[sid], i, sid) for i, sid in enumerate(all_ids) if sid in timings
+    )
+    known_ids = {sid for _, _, sid in known}
+    unknown = [sid for sid in all_ids if sid not in known_ids]
+    return [sid for _, _, sid in known] + unknown
+
+
+class StrategyRunHandle:
+    """一次 run_all 的执行状态; 端点线程 (读) 与后台执行线程 (写) 共享。"""
+
+    def __init__(self, key: tuple, ordered_ids: list[str]) -> None:
+        self.key = key
+        self.started_at_ms = int(time.time() * 1000)
+        self._lock = threading.Lock()
+        self._results: dict[str, dict] = {}
+        self._remaining: list[str] = list(ordered_ids)
+        self._error: str | None = None
+        self._done = False
+
+    def complete(self, sid: str, payload: dict) -> None:
+        with self._lock:
+            self._results[sid] = payload
+            if sid in self._remaining:
+                self._remaining.remove(sid)
+
+    def fail(self, message: str) -> None:
+        with self._lock:
+            self._error = message
+            self._done = True
+
+    def finish(self) -> None:
+        with self._lock:
+            self._done = True
+
+    def snapshot(self) -> dict:
+        """线程安全快照: 结果拷贝 + 剩余/错误/完成状态。"""
+        with self._lock:
+            return {
+                "results": dict(self._results),
+                "pending": list(self._remaining),
+                "error": self._error,
+                "done": self._done,
+                "started_at_ms": self.started_at_ms,
+            }
+
+
+class StrategyRunManager:
+    """run_all 单飞管理器。
+
+    - 相同 key 且仍在执行 (含排队中) 的重复请求搭车现有执行, 不重复算
+      (页面 reload / StrictMode / 反复切换); 已完成的不再搭车, 重跑即新执行。
+    - 不同 key 在唯一 daemon 工作线程里排队; 端点在首返时限内等不到也只能
+      先返回 pending, 前端靠轮询缓存拿最终结果。
+    - 工作线程为 daemon: 进程退出不等待剩余计算 (缓存写入均为原子替换,
+      中断只留部分结果, 下次进入页面补算)。
+    """
+
+    def __init__(self) -> None:
+        self._lock = threading.Lock()
+        self._handles: dict[tuple, StrategyRunHandle] = {}
+        self._queue: queue.Queue[tuple[StrategyRunHandle, Callable]] = queue.Queue()
+        self._worker: threading.Thread | None = None
+
+    def get_or_submit(
+        self,
+        key: tuple,
+        ordered_ids: list[str],
+        job: Callable[[StrategyRunHandle], None],
+    ) -> StrategyRunHandle:
+        with self._lock:
+            # 顺手清理已完成的 handle, 防止字典随不同 key 无限增长
+            for k in [k for k, h in self._handles.items() if h.snapshot()["done"]]:
+                del self._handles[k]
+            existing = self._handles.get(key)
+            if existing is not None:
+                return existing
+            handle = StrategyRunHandle(key, ordered_ids)
+            self._handles[key] = handle
+        self._ensure_worker()
+        self._queue.put((handle, job))
+        return handle
+
+    def _ensure_worker(self) -> None:
+        with self._lock:
+            if self._worker is None or not self._worker.is_alive():
+                self._worker = threading.Thread(
+                    target=self._run_loop, name="runall", daemon=True
+                )
+                self._worker.start()
+
+    def _run_loop(self) -> None:
+        while True:
+            handle, job = self._queue.get()
+            try:
+                job(handle)
+            except Exception as e:
+                logger.exception("run_all 后台执行失败: %s", e)
+                handle.fail(str(e))
+            else:
+                handle.finish()
+
+
+# 进程级单例: 与 strategy_cache 的模块级锁同风格, 生命周期跟随进程
+MANAGER = StrategyRunManager()

backend/tests/test_screener_builtin_params.py

@@ -59,7 +59,7 @@ class _CapturingStrategyEngine:
         })
         return ScreenerResult(as_of=context.as_of, strategy=strategy_id)
 
-    def run_all(self, context, *, params_map=None, overrides_map=None, strategy_ids=None):
+    def run_all(self, context, *, params_map=None, overrides_map=None, strategy_ids=None, parallel=True):
         self.calls.append({
             "kind": "run_all",
             "params_map": params_map,
@@ -153,8 +153,13 @@ def test_batch_summary_response_still_writes_full_cache(monkeypatch, tmp_path):
         },
     )
 
-    assert payload == {
-        "as_of": "2026-07-15",
-        "results": {"builtin_strategy": {"total": 0, "as_of": "2026-07-15"}},
-    }
+    assert payload["as_of"] == "2026-07-15"
+    assert payload["results"]["builtin_strategy"]["total"] == 0
+    assert payload["results"]["builtin_strategy"]["as_of"] == "2026-07-15"
+    # 渐进式路径: 全部算完 → complete 且无 pending
+    assert payload["pending"] == []
+    assert payload["complete"] is True
+    assert payload["error"] is None
+    # 渐进式增量写 + 收尾全量写都带 rows, 缓存口径不变
     assert written[0][2]["builtin_strategy"]["rows"] == []
+    assert written[-1][2]["builtin_strategy"]["rows"] == []

backend/tests/test_screener_cache_api.py

@@ -48,7 +48,9 @@ def test_cached_summary_omits_rows_and_counts_realtime_expirations(monkeypatch,
 
     payload = screener_api.get_cached_summary(_request(tmp_path, realtime))
 
-    assert payload["results"] == {"strategy_a": {"total": 2, "as_of": "2026-07-20"}}
+    assert payload["results"] == {
+        "strategy_a": {"total": 2, "as_of": "2026-07-20", "computed_at": None}
+    }
     assert payload["today_ever_counts"] == {"strategy_a": 4}
     assert "rows" not in payload["results"]["strategy_a"]
 

backend/tests/test_screener_run_all_progressive.py

@@ -0,0 +1,236 @@
+"""run_all 渐进式返回的端点行为 — 快策略先返回、慢策略后台落缓存、搭车与旧路径兼容。"""
+from __future__ import annotations
+
+import time
+from dataclasses import dataclass, field
+from datetime import date
+from types import SimpleNamespace
+
+import pytest
+from fastapi import HTTPException
+
+from app.api import screener as screener_api
+from app.config import settings
+from app.services import strategy_cache, strategy_run_queue
+
+AS_OF = "2026-09-04"
+
+
+@dataclass
+class _FakeResult:
+    total: int = 1
+    rows: list = field(default_factory=lambda: [{"symbol": "000001.SZ", "close": 1.0}])
+    as_of: str = AS_OF
+
+
+class _FakeEngine:
+    def __init__(self, delays: dict[str, float]):
+        self._delays = delays
+        self.executed: list[str] = []
+
+    def has(self, sid: str) -> bool:
+        return sid in self._delays
+
+    def get(self, sid: str):
+        return SimpleNamespace(meta={})
+
+    def run_all(self, context, params_map=None, overrides_map=None, *, strategy_ids=None, parallel=True):
+        out = {}
+        for sid in strategy_ids or []:
+            self.executed.append(sid)
+            time.sleep(self._delays[sid])
+            out[sid] = _FakeResult()
+        return out
+
+
+class _FakeService:
+    def __init__(self, repo, asset_type="stock"):
+        pass
+
+    def latest_date(self):
+        return date.fromisoformat(AS_OF)
+
+    def build_strategy_context(self, *args, **kwargs):
+        return SimpleNamespace()
+
+
+def _request(tmp_path, engine):
+    repo = SimpleNamespace(store=SimpleNamespace(data_dir=tmp_path))
+    state = SimpleNamespace(repo=repo, strategy_engine=engine, monitor_engine=None)
+    return SimpleNamespace(app=SimpleNamespace(state=state))
+
+
+def _wait_cache_results(tmp_path, want_ids, timeout=8.0) -> dict:
+    deadline = time.time() + timeout
+    while time.time() < deadline:
+        results = (strategy_cache.read_cache(tmp_path) or {}).get("results") or {}
+        if all(i in results for i in want_ids):
+            return results
+        time.sleep(0.05)
+    return (strategy_cache.read_cache(tmp_path) or {}).get("results") or {}
+
+
+@pytest.fixture()
+def fast_first_return(monkeypatch):
+    monkeypatch.setattr(settings, "strategy_run_all_first_return_s", 0.4)
+
+
+def test_run_all_returns_fast_first_then_background_fills_cache(
+    monkeypatch, tmp_path, fast_first_return
+):
+    engine = _FakeEngine({"fast_a": 0.02, "fast_b": 0.02, "slow_c": 0.8})
+    monkeypatch.setattr(screener_api, "ScreenerService", _FakeService)
+
+    resp = screener_api.run_all(
+        _request(tmp_path, engine),
+        {
+            "as_of": AS_OF,
+            "strategy_ids": ["fast_a", "fast_b", "slow_c"],
+            "asset_type": "stock",
+            "timeframe": "1d",
+            "summary_only": True,
+        },
+    )
+    # 首返: 快策略已完成 (带 total, 无 rows), 慢策略 pending
+    assert set(resp["results"]) == {"fast_a", "fast_b"}
+    assert resp["results"]["fast_a"]["total"] == 1
+    assert "rows" not in resp["results"]["fast_a"]
+    assert resp["pending"] == ["slow_c"]
+    assert resp["complete"] is False
+    assert isinstance(resp["started_at"], int)
+
+    # 后台继续: 慢策略最终也落进缓存, 且带 computed_at
+    results = _wait_cache_results(tmp_path, ["fast_a", "fast_b", "slow_c"])
+    assert set(results) == {"fast_a", "fast_b", "slow_c"}
+    assert all(r.get("computed_at") for r in results.values())
+
+    # 耗时已记录 → 下次按耗时升序 (快策略先算)
+    timings = strategy_run_queue.load_run_timings(tmp_path)
+    assert set(timings) == {"fast_a", "fast_b", "slow_c"}
+    assert timings["slow_c"] > timings["fast_a"]
+
+
+def test_run_all_second_run_orders_by_recorded_timings(
+    monkeypatch, tmp_path, fast_first_return
+):
+    monkeypatch.setattr(screener_api, "ScreenerService", _FakeService)
+    engine = _FakeEngine({"slow_a": 0.5, "fast_b": 0.01})
+    body = {
+        "as_of": AS_OF,
+        "strategy_ids": ["slow_a", "fast_b"],
+        "asset_type": "stock",
+        "timeframe": "1d",
+        "summary_only": True,
+    }
+    req = _request(tmp_path, engine)
+
+    def _wait_executed(count, timeout=8.0):
+        deadline = time.time() + timeout
+        while time.time() < deadline:
+            if len(engine.executed) >= count:
+                return
+            time.sleep(0.05)
+        raise AssertionError(f"执行未到 {count} 个: {engine.executed}")
+
+    # 第一轮: 无耗时记录 → 按传入顺序 slow_a 先算
+    screener_api.run_all(req, body)
+    _wait_executed(2)
+    assert engine.executed == ["slow_a", "fast_b"]
+
+    # 第二轮: 有耗时记录 → fast_b (快) 升序在前, 且首返带上 fast_b。
+    # 若第一轮 handle 还在收尾 (终写缓存/记录耗时), 请求会搭车旧 handle;
+    # 重试直到真正触发新一轮执行。
+    resp2 = None
+    for _ in range(40):
+        engine.executed.clear()
+        resp2 = screener_api.run_all(req, body)
+        if engine.executed:
+            break
+        time.sleep(0.05)
+    assert resp2 is not None and engine.executed, "第二轮未触发新执行"
+    assert engine.executed[0] == "fast_b"
+    assert set(resp2["results"]) == {"fast_b"}
+    _wait_executed(2)
+    assert engine.executed == ["fast_b", "slow_a"]
+
+
+def test_run_all_same_key_piggybacks_running_execution(
+    monkeypatch, tmp_path, fast_first_return
+):
+    engine = _FakeEngine({"fast_a": 0.02, "slow_c": 1.2})
+    monkeypatch.setattr(screener_api, "ScreenerService", _FakeService)
+    body = {
+        "as_of": AS_OF,
+        "strategy_ids": ["fast_a", "slow_c"],
+        "asset_type": "stock",
+        "timeframe": "1d",
+        "summary_only": True,
+    }
+    req = _request(tmp_path, engine)
+    resp1 = screener_api.run_all(req, body)
+    # 第一笔仍在后台跑 slow_c 时, 相同请求搭车: 同一起点, 不重复执行
+    resp2 = screener_api.run_all(_request(tmp_path, engine), body)
+    assert resp2["started_at"] == resp1["started_at"]
+    assert engine.executed.count("fast_a") == 1
+    _wait_cache_results(tmp_path, ["fast_a", "slow_c"])
+    assert engine.executed.count("slow_c") == 1
+    assert engine.executed.count("fast_a") == 1
+
+
+def test_run_all_background_error_without_results_is_500(
+    monkeypatch, tmp_path, fast_first_return
+):
+    class _BoomEngine(_FakeEngine):
+        def run_all(self, context, params_map=None, overrides_map=None, *, strategy_ids=None, parallel=True):
+            raise ValueError("缺少列: volume")
+
+    monkeypatch.setattr(screener_api, "ScreenerService", _FakeService)
+    with pytest.raises(HTTPException) as excinfo:
+        screener_api.run_all(
+            _request(tmp_path, _BoomEngine({"bad_a": 0.01})),
+            {
+                "as_of": AS_OF,
+                "strategy_ids": ["bad_a"],
+                "asset_type": "stock",
+                "timeframe": "1d",
+                "summary_only": True,
+            },
+        )
+    assert excinfo.value.status_code == 500
+    assert "volume" in excinfo.value.detail
+
+
+def test_run_all_minute_timeframe_stays_blocking(monkeypatch, tmp_path, fast_first_return):
+    engine = _FakeEngine({"m1": 0.01})
+    monkeypatch.setattr(screener_api, "ScreenerService", _FakeService)
+    resp = screener_api.run_all(
+        _request(tmp_path, engine),
+        {
+            "as_of": AS_OF,
+            "strategy_ids": ["m1"],
+            "asset_type": "stock",
+            "timeframe": "1m",
+            "summary_only": True,
+        },
+    )
+    # 分钟周期: 整段阻塞、旧响应形状 (无 pending), 且不写日线缓存
+    assert set(resp["results"]) == {"m1"}
+    assert "pending" not in resp
+    assert not ((strategy_cache.read_cache(tmp_path) or {}).get("results") or {})
+
+
+def test_run_all_full_detail_stays_blocking(monkeypatch, tmp_path, fast_first_return):
+    engine = _FakeEngine({"d1": 0.01})
+    monkeypatch.setattr(screener_api, "ScreenerService", _FakeService)
+    resp = screener_api.run_all(
+        _request(tmp_path, engine),
+        {
+            "as_of": AS_OF,
+            "strategy_ids": ["d1"],
+            "asset_type": "stock",
+            "timeframe": "1d",
+        },
+    )
+    # 非 summary 请求: 保持整段阻塞并返回明细
+    assert resp["results"]["d1"]["rows"][0]["symbol"] == "000001.SZ"
+    assert "pending" not in resp

backend/tests/test_strategy_run_queue.py

@@ -0,0 +1,129 @@
+"""strategy_run_queue 单测 — 耗时排序、耗时落盘、handle 状态、单飞管理器。"""
+from __future__ import annotations
+
+import threading
+import time
+
+from app.services import strategy_run_queue as q
+
+
+def test_order_strategy_ids_fast_first_unknown_last():
+    ids = ["slow_a", "mid_b", "fast_c", "new_d", "new_e"]
+    timings = {"slow_a": 5000.0, "fast_c": 100.0, "mid_b": 1000.0}
+    assert q.order_strategy_ids(ids, timings) == ["fast_c", "mid_b", "slow_a", "new_d", "new_e"]
+
+
+def test_run_timings_record_merge_and_load(tmp_path):
+    assert q.load_run_timings(tmp_path) == {}
+    q.record_run_timings(tmp_path, {"a": 100.0})
+    q.record_run_timings(tmp_path, {"b": 200.0, "a": 50.0})
+    assert q.load_run_timings(tmp_path) == {"a": 50.0, "b": 200.0}
+
+
+def test_run_timings_survives_corrupt_file(tmp_path):
+    path = q._timings_path(tmp_path)
+    path.parent.mkdir(parents=True, exist_ok=True)
+    path.write_text("not json", encoding="utf-8")
+    assert q.load_run_timings(tmp_path) == {}
+    q.record_run_timings(tmp_path, {"a": 1.0})
+    assert q.load_run_timings(tmp_path) == {"a": 1.0}
+
+
+def test_handle_snapshot_lifecycle():
+    h = q.StrategyRunHandle(("k",), ["s1", "s2"])
+    snap = h.snapshot()
+    assert snap["pending"] == ["s1", "s2"]
+    assert snap["done"] is False
+
+    h.complete("s1", {"total": 3})
+    snap = h.snapshot()
+    assert snap["results"] == {"s1": {"total": 3}}
+    assert snap["pending"] == ["s2"]
+
+    h.fail("boom")
+    snap = h.snapshot()
+    assert snap["error"] == "boom"
+    assert snap["done"] is True
+
+
+def _wait_done(handle, timeout=5.0) -> None:
+    deadline = time.time() + timeout
+    while time.time() < deadline:
+        if handle.snapshot()["done"]:
+            return
+        time.sleep(0.01)
+    raise AssertionError("handle 未在时限内完成")
+
+
+def test_manager_piggybacks_same_running_key():
+    mgr = q.StrategyRunManager()
+    started = threading.Event()
+    release = threading.Event()
+    calls: list[int] = []
+
+    def job(handle):
+        calls.append(1)
+        started.set()
+        assert release.wait(timeout=5)
+
+    h1 = mgr.get_or_submit(("k",), ["s"], job)
+    assert started.wait(timeout=5)
+    # 执行中: 相同 key 搭车, 不重复提交
+    h2 = mgr.get_or_submit(("k",), ["s"], job)
+    assert h2 is h1
+
+    release.set()
+    _wait_done(h1)
+    assert calls == [1]
+
+    # 已完成后: 同 key 再来 → 新执行 (重跑语义)
+    h3 = mgr.get_or_submit(("k",), ["s"], job)
+    assert h3 is not h1
+    _wait_done(h3)
+    assert calls == [1, 1]
+
+
+def test_manager_piggybacks_same_queued_key():
+    mgr = q.StrategyRunManager()
+    started = threading.Event()
+    release = threading.Event()
+
+    def job(handle):
+        started.set()
+        assert release.wait(timeout=5)
+
+    h1 = mgr.get_or_submit(("a",), ["s"], job)  # 占住唯一 worker
+    assert started.wait(timeout=5)
+    # key b 排队 (未开始), 此时 b 的重复请求应搭车排队中的 handle
+    h2 = mgr.get_or_submit(("b",), ["s"], job)
+    h3 = mgr.get_or_submit(("b",), ["s"], job)
+    assert h2 is h3
+
+    release.set()
+    _wait_done(h1)
+    _wait_done(h2, timeout=10)
+
+
+def test_manager_serializes_different_keys():
+    mgr = q.StrategyRunManager()
+    lock = threading.Lock()
+    active: list[str] = []
+    overlap: list[list[str]] = []
+
+    def make_job(name):
+        def job(handle):
+            with lock:
+                active.append(name)
+                if len(active) > 1:
+                    overlap.append(list(active))
+            time.sleep(0.1)
+            with lock:
+                active.remove(name)
+
+        return job
+
+    h1 = mgr.get_or_submit(("a",), ["s"], make_job("a"))
+    h2 = mgr.get_or_submit(("b",), ["s"], make_job("b"))
+    _wait_done(h1, timeout=10)
+    _wait_done(h2, timeout=10)
+    assert overlap == []

frontend/src/components/screener/StrategyCard.tsx

@@ -94,12 +94,14 @@ interface StrategyCardProps {
   onToggleMonitor?: () => void
   /** 周期徽章 (如 '分钟'); 日线策略不传 */
   timeframeBadge?: string
+  /** 后台计算中 (渐进式 run_all): 数字未出时显示脉冲占位 */
+  computing?: boolean
 }
 
 export function StrategyCard({
   name, description, source, active, count, expiredCount,
   loading, cardSize,
-  onRun, disabled, onSettings, monitored, onToggleMonitor, timeframeBadge,
+  onRun, disabled, onSettings, monitored, onToggleMonitor, timeframeBadge, computing,
 }: StrategyCardProps) {
   const cs = CARD_STYLES[cardSize]
   const activeCls = active
@@ -149,6 +151,9 @@ export function StrategyCard({
                 )}
               </div>
             )}
+            {count == null && !loading && computing && (
+              <span className="mt-1.5 text-sm font-mono font-bold text-muted/50 animate-pulse">···</span>
+            )}
             {loading && <div className="mt-1 h-4 w-10 rounded bg-elevated animate-pulse" />}
           </button>
           <button onClick={(e) => { e.stopPropagation(); onSettings() }}
@@ -176,6 +181,9 @@ export function StrategyCard({
               {count != null && !loading && (
                 <span className={`text-xs font-mono font-bold tabular-nums shrink-0 ${countCls}`}>{count}</span>
               )}
+              {count == null && !loading && computing && (
+                <span className="text-xs font-mono font-bold text-muted/50 animate-pulse shrink-0">···</span>
+              )}
               {loading && <span className="w-5 h-3 rounded bg-elevated animate-pulse shrink-0" />}
             </div>
             <div className="flex items-center gap-1.5 mt-0.5">
@@ -209,6 +217,9 @@ export function StrategyCard({
             {count != null && !loading && (
               <span className={`text-xs font-mono font-bold tabular-nums ${countCls}`}>{count}</span>
             )}
+            {count == null && !loading && computing && (
+              <span className="text-xs font-mono font-bold text-muted/50 animate-pulse">···</span>
+            )}
             {hasExpired && (
               <span className="text-[9px] font-mono text-red-400/70">{'-' + expiredCount}</span>
             )}

frontend/src/lib/api.ts

@@ -10,6 +10,9 @@ const BASE = ''
 type RequestOptions = RequestInit & {
   /** 为 true 时不弹错误 toast（由调用方自行汇总提示，如多图串行队列） */
   quiet?: boolean
+  /** 请求超时毫秒数; null 关闭。默认 30s — 后端依赖 polars, 偶发挂起时无超时
+   *  会占满浏览器同源连接池, 拖垮整页所有请求 (表现为全部排队"已停止")。 */
+  timeoutMs?: number | null
 }
 
 export class ApiError extends Error {
@@ -22,14 +25,39 @@ export class ApiError extends Error {
   }
 }
 
+const DEFAULT_REQUEST_TIMEOUT_MS = 30_000
+/** 同步计算型接口 (回测/筛选等) 的放宽超时: 合法耗时可能远超轮询类接口。 */
+const COMPUTE_REQUEST_TIMEOUT_MS = 300_000
+
 async function request<T>(path: string, init?: RequestOptions): Promise<T> {
-  const { quiet, ...fetchInit } = init ?? {}
+  const { quiet, timeoutMs = DEFAULT_REQUEST_TIMEOUT_MS, ...fetchInit } = init ?? {}
   const isFormData = fetchInit.body instanceof FormData
   const headers: Record<string, string> = {}
   if (!isFormData) headers['Content-Type'] = 'application/json'
   // 合并调用方传入的 headers (此前会被整体覆盖丢弃)
   Object.assign(headers, fetchInit.headers as Record<string, string> | undefined)
-  const res = await fetch(`${BASE}${path}`, { ...fetchInit, headers })
+  // 自带 signal 的调用方 (上传/串行队列) 由其自行控制中止; 其余走默认超时。
+  const ctl = timeoutMs == null || fetchInit.signal ? undefined : new AbortController()
+  const timeoutSeconds = Math.round((timeoutMs ?? DEFAULT_REQUEST_TIMEOUT_MS) / 1000)
+  let timer: number | undefined
+  if (ctl && timeoutMs != null) timer = window.setTimeout(() => ctl.abort(), timeoutMs)
+  let res: Response
+  try {
+    res = await fetch(`${BASE}${path}`, {
+      ...fetchInit,
+      headers,
+      ...(ctl ? { signal: ctl.signal } : {}),
+    })
+  } catch (err) {
+    if (ctl && err instanceof DOMException && err.name === 'AbortError') {
+      const msg = `请求超时（${timeoutSeconds}s）· ${path.split('?')[0]}`
+      if (!quiet) toast(msg, 'error')
+      throw new ApiError(msg, 0)
+    }
+    throw err
+  } finally {
+    if (timer !== undefined) window.clearTimeout(timer)
+  }
   if (!res.ok) {
     let detail = ''
     try {
@@ -364,6 +392,8 @@ export interface ScreenerResult {
 export interface ScreenerResultSummary {
   total: number
   as_of: string
+  /** 渐进式 run_all 写入的计算时间戳 (Unix ms); 监控实时叠加等来源无此字段 */
+  computed_at?: number | null
 }
 
 export interface ScreenerCachedSummary {
@@ -373,6 +403,20 @@ export interface ScreenerCachedSummary {
   updated_at: number | null
 }
 
+/** run_all 渐进式返回: 快策略已算完, 慢策略后台继续算 */
+export interface ScreenerRunAllSummary {
+  as_of: string | null
+  results: Record<string, ScreenerResultSummary>
+  /** 尚未算完的策略 (后台继续, 逐个写入缓存) */
+  pending?: string[]
+  /** 全部算完时为 true */
+  complete?: boolean
+  /** 后台执行出错时的错误信息 (部分结果仍会返回) */
+  error?: string | null
+  /** 本次执行起点 (Unix ms, 后端时钟), 用于判断缓存结果是否属于本轮 */
+  started_at?: number | null
+}
+
 export interface ScreenerCachedResult {
   result: ScreenerResult | null
   today_ever_rows: Record<string, any> | null
@@ -2464,16 +2508,18 @@ export const api = {
   screenerRunPreset: (strategy_id: string, pool?: string[], asOf?: string, extColumns?: string, assetType: 'stock' | 'etf' = 'stock', timeframe: '1d' | '1m' = '1d') =>
     request<ScreenerResult>('/api/screener/run_preset', {
       method: 'POST',
+      timeoutMs: COMPUTE_REQUEST_TIMEOUT_MS,
       body: JSON.stringify({ strategy_id, pool, as_of: asOf ?? null, ext_columns: extColumns || null, asset_type: assetType, timeframe }),
     }),
   screenerRunCustom: (conditions: string[], orderBy?: string, limit = 30, pool?: string[], extColumns?: string, assetType: 'stock' | 'etf' = 'stock') =>
     request<ScreenerResult>('/api/screener/run', {
       method: 'POST',
+      timeoutMs: COMPUTE_REQUEST_TIMEOUT_MS,
       body: JSON.stringify({ conditions, order_by: orderBy, limit, pool, ext_columns: extColumns || null, asset_type: assetType }),
     }),
   screenerRunAll: (asOf?: string, strategyIds?: string[], assetType: 'stock' | 'etf' = 'stock') =>
-    request<{ as_of: string | null; results: Record<string, ScreenerResultSummary> }>(
-      '/api/screener/run_all', { method: 'POST', body: JSON.stringify({ as_of: asOf ?? null, strategy_ids: strategyIds ?? null, asset_type: assetType, timeframe: '1d', summary_only: true }) },
+    request<ScreenerRunAllSummary>(
+      '/api/screener/run_all', { method: 'POST', timeoutMs: COMPUTE_REQUEST_TIMEOUT_MS, body: JSON.stringify({ as_of: asOf ?? null, strategy_ids: strategyIds ?? null, asset_type: assetType, timeframe: '1d', summary_only: true }) },
     ),
   screenerCachedSummary: () =>
     request<ScreenerCachedSummary>('/api/screener/cached-summary'),
@@ -2563,6 +2609,7 @@ export const api = {
   }) =>
     request<BacktestResult>('/api/backtest/run', {
       method: 'POST',
+      timeoutMs: COMPUTE_REQUEST_TIMEOUT_MS,
       body: JSON.stringify(payload),
     }),
 
@@ -2656,6 +2703,7 @@ export const api = {
   }) =>
     request<FactorBacktestResult>('/api/backtest/factor/run', {
       method: 'POST',
+      timeoutMs: COMPUTE_REQUEST_TIMEOUT_MS,
       body: JSON.stringify(payload),
     }),
 
@@ -2673,6 +2721,7 @@ export const api = {
   }) =>
     request<FactorBatchResult>('/api/backtest/factor/batch', {
       method: 'POST',
+      timeoutMs: COMPUTE_REQUEST_TIMEOUT_MS,
       body: JSON.stringify(payload),
     }),
 

frontend/src/pages/Screener.tsx

@@ -124,6 +124,9 @@ export function Screener() {
   const [expiredCounts, setExpiredCounts] = useState<Record<string, number>>({})
   // 各策略显示上限 (null = 全部)
   const [strategyLimits, setStrategyLimits] = useState<Record<string, number | null>>({})
+  // run_all 渐进式返回后仍在后台计算的策略 (startedAt 为后端时钟, 用于判断缓存新旧)
+  const [pendingRun, setPendingRun] = useState<{ ids: string[]; startedAt: number } | null>(null)
+  const pendingRunIds = useMemo(() => new Set(pendingRun?.ids ?? []), [pendingRun])
 
   // 筛选条件变化时同步到 map（供切换策略时读取最新值）
   useEffect(() => {
@@ -161,10 +164,12 @@ export function Screener() {
 
   // 卡片首屏只读取轻量摘要；明细在点击策略或“全部”时按需加载。
   // 摘要只覆盖日线缓存; 分钟策略命中数来自手动单跑。
+  // run_all 渐进式返回后后台仍在算 → 轮询摘要, 算完的策略逐个点亮。
   const summaryQuery = useQuery({
     queryKey: QK.screenerCachedSummary,
     queryFn: api.screenerCachedSummary,
     enabled: assetType === 'stock',
+    refetchInterval: pendingRun ? 2000 : false,
   })
 
   const fullCachedQuery = useQuery({
@@ -273,6 +278,13 @@ export function Screener() {
         counts[id] = item.total
       }
       setHitCounts(prev => ({ ...prev, ...counts }))
+      // 渐进式返回: 慢策略后台继续算, 开启摘要轮询逐个点亮
+      setPendingRun(
+        data.pending?.length
+          ? { ids: [...data.pending], startedAt: data.started_at ?? 0 }
+          : null,
+      )
+      if (data.error) toast(`策略计算失败：${data.error}`, 'error')
       qc.invalidateQueries({ queryKey: ['screener-cached'] })
     },
   })
@@ -315,7 +327,27 @@ export function Screener() {
     }
     setHitCounts(counts)
     setExpiredCounts(expired)
-  }, [summaryQuery.data, asOf])
+    // 渐进式: computed_at 晚于本轮起点的策略已算完, 从 pending 中移除;
+    // 无 computed_at (监控实时叠加/旧缓存) 视为新鲜。容差吸收前后端时钟差。
+    if (pendingRun) {
+      const arrived = (id: string) => {
+        const r = summaryQuery.data!.results[id]
+        if (!r || r.as_of !== asOf) return false
+        return r.computed_at == null || r.computed_at >= pendingRun.startedAt - 2000
+      }
+      const rest = pendingRun.ids.filter(id => !arrived(id))
+      if (rest.length !== pendingRun.ids.length) {
+        setPendingRun(rest.length ? { ...pendingRun, ids: rest } : null)
+      }
+    }
+  }, [summaryQuery.data, asOf, pendingRun])
+
+  // 渐进式兜底: 后台计算最长等 8 分钟, 防止异常时无限轮询
+  useEffect(() => {
+    if (!pendingRun) return
+    const t = setTimeout(() => setPendingRun(null), 8 * 60 * 1000)
+    return () => clearTimeout(t)
+  }, [pendingRun])
 
   // 当前单策略缓存更新后同步明细；参数保存的强制重算结果仍由 run 直接覆盖。
   useEffect(() => {
@@ -817,6 +849,7 @@ export function Screener() {
                   count={hitCounts[id]}
                   expiredCount={expiredCounts[id]}
                   loading={runAll.isPending}
+                  computing={pendingRunIds.has(id)}
                   cardSize={cardSize}
                   onRun={() => handleRun(s)}
                   disabled={run.isPending && activeStrategy === s.id}