perf(portfolio): G5-P2收尾—all_weather三调用点向量化:①filter_roic逐只循环→一次批量+fields=['roic']短路(9×)②_trend_mean get_price长表+pivot→get_closes_panel宽表(340×,count=N→start-N*2自然日+.tail(N)同momentum口径,fq均raw)③prepare_stock_list get_price(close+high_limit)→get_limit_status_batch精确涨跌停口径;测试fixture补panel/limit_batch mock(原MagicMock碰巧truthy蒙混paused剔除语义,默认改全正常);+6回归测试,portfolio全套302绿 [vps]

2026-08-14 23:17:13 +08:00
parent e9aec041db
commit 2cd158286b
2 changed files with 144 additions and 52 deletions
@@ -68,6 +68,30 @@ def make_strategy(

    provider.get_price.side_effect = _get_price

+    # get_closes_panel:从 price_df_map 同源构造 close 宽表(忽略 count 差异)
+    def _get_closes_panel(symbols, start=None, end=None, interval="d", fq="raw"):
+        frames = [
+            df[["time", "code", "close"]]
+            for (sec, fields, _cnt), df in price_df_map.items()
+            if sec == str(symbols) and tuple(fields) == ("close",)
+            and df is not None and len(df)
+        ]
+        if not frames:
+            return pd.DataFrame()
+        long_df = pd.concat(frames)
+        return long_df.pivot(index="time", columns="code", values="close")
+
+    provider.get_closes_panel.side_effect = _get_closes_panel
+
+    # 涨跌停/停牌批量:默认全正常(filter_paused 无bar=剔除语义,MagicMock/{} 会误杀)
+    def _get_limit_status_batch(codes, date=None):
+        return {
+            c: {"is_limit_up": False, "is_limit_down": False, "is_paused": False}
+            for c in codes
+        }
+
+    provider.get_limit_status_batch.side_effect = _get_limit_status_batch
+
    broker = BrokerFacade()
    broker.order_target_value = MagicMock(return_value=MagicMock(filled=100))
    broker.order_value = MagicMock(return_value=MagicMock(filled=100))
@@ -136,23 +160,69 @@ class TestPrepareStockList:

    def test_records_yesterday_limit_up(self):
        s = make_strategy()
-        # 清掉 make_strategy 设置的 side_effect,直接用 return_value
-        s.provider.get_price.side_effect = None
        pos = MagicMock(); pos.security = "600519.XSHG"
        ctx = MagicMock()
        ctx.portfolio.positions = {"600519.XSHG": pos}
        ctx.previous_date = "2024-09-30"
-        # close == high_limit 视为涨停
-        s.provider.get_price.return_value = pd.DataFrame({
-            "code": ["600519.XSHG"],
-            "close": [10.0],
-            "high_limit": [10.0],
-        })
+        # get_limit_status_batch 返回昨日涨停(G5-P2:原 get_price close==high_limit 改批量口径)
+        s.provider.get_limit_status_batch.side_effect = \
+            lambda codes, date=None: {
+                c: {"is_limit_up": True, "is_limit_down": False, "is_paused": False}
+                for c in codes
+            }
        s.prepare_stock_list(ctx)
        assert "600519.XSHG" in s.yesterday_hl_list

+    def test_uses_batch_endpoint_once(self):
+        """G5-P2:原 get_price(close+high_limit) → get_limit_status_batch 一次批量。"""
+        s = make_strategy()
+        pos = MagicMock(); pos.security = "600519.XSHG"
+        ctx = MagicMock()
+        ctx.portfolio.positions = {"600519.XSHG": pos, "000001.XSHE": MagicMock(security="000001.XSHE")}
+        ctx.previous_date = "2024-09-30"
+        s.prepare_stock_list(ctx)
+        assert s.provider.get_limit_status_batch.call_count == 1
+        args, _kwargs = s.provider.get_limit_status_batch.call_args
+        assert sorted(args[0]) == ["000001.XSHE", "600519.XSHG"]
+        s.provider.get_price.assert_not_called()

-# =================== stop_loss ===================
+
+# =================== trend_mean ===================
+class TestTrendMean:
+    def _panel_seed(self):
+        return pd.DataFrame({
+            "time": pd.to_datetime(["2024-09-20", "2024-09-30"]),
+            "code": ["600519.XSHG"] * 2,
+            "close": [10.0, 15.0],  # 涨 50%
+        })
+
+    def test_uses_closes_panel_not_get_price(self):
+        """G5-P2:原 get_price 长表+pivot → get_closes_panel 宽表。"""
+        s = make_strategy(price_df_map={
+            ("['600519.XSHG']", ("close",), 10): self._panel_seed(),
+        })
+        out = s._trend_mean(["600519.XSHG"], "2024-09-30", 10)
+        assert out == 50.0
+        s.provider.get_closes_panel.assert_called_once()
+        s.provider.get_price.assert_not_called()
+
+    def test_empty_or_short_panel_returns_zero(self):
+        """panel 缺失/不足 2 行 → 0.0 不崩(降级同原 get_price 空df语义)。"""
+        s = make_strategy()
+        assert s._trend_mean([], "2024-09-30", 10) == 0.0
+        assert s._trend_mean(["600519.XSHG"], "2024-09-30", 10) == 0.0  # 无种子数据
+
+    def test_nan_only_change_not_propagated(self):
+        """某列 NaN(close 缺失)→ nan_to_num 归 0,不产出 NaN。"""
+        wide = pd.DataFrame(
+            {"600519.XSHG": [np.nan, 15.0], "000001.XSHE": [10.0, 11.0]},
+            index=pd.to_datetime(["2024-09-20", "2024-09-30"]),
+        )
+        s = make_strategy()
+        s.provider.get_closes_panel.side_effect = None
+        s.provider.get_closes_panel.return_value = wide
+        # 600519 NaN→0%, 000001 +10% → 均值 5(浮点容差)
+        assert s._trend_mean(["600519.XSHG", "000001.XSHE"], "2024-09-30", 10) == pytest.approx(5.0)
 class TestStopLoss:
    def test_stop_loss_triggers_when_price_drops_8pct(self):
        """avg_cost=100, price=91 (< 100*0.92=92) → 止损。"""
@@ -467,3 +537,15 @@ class TestFilterRoic:
        s = make_strategy()
        out = s.filter_roic([], previous_date="2024-09-30")
        assert out == []
+
+    def test_batch_single_call_with_fields_shortcut(self):
+        """G5-P2:原逐只循环 → 一次批量 + fields=['roic'] 短路。"""
+        df = make_fund_df([{"code": "A.XSHG", "roic": 0.15}])
+        s = make_strategy()
+        s.provider.get_fundamentals_df.return_value = df
+        s.filter_roic(["A.XSHG", "B.XSHG"], previous_date="2024-09-30")
+        # 一次批量调用(非逐只 N 次),且带 fields 短路
+        assert s.provider.get_fundamentals_df.call_count == 1
+        args, kwargs = s.provider.get_fundamentals_df.call_args
+        assert list(args[0]) == ["A.XSHG", "B.XSHG"]
+        assert kwargs.get("fields") == ["roic"]