feat(backtest): 成交价精简 + 一键寻优全策略 + 预设网格

- 成交价精简为 next_open/next_close，删除 this_close/worst/best 三种
  非真实模式（this_close 有未来函数偏差，worst/best 为压力测试边界）
- 初始资金默认统一为 1,000,000（原 10万/20万）
- 新增 presets.py：18 策略各配 1-2 参数的预设寻优网格（笛卡尔积≤200）
- registry.to_schema() 返回 preset_grid 字段供前端自动填充
- 新增 POST /backtest/optimize-all/run/async：逐策略预设网格寻优 +
  全局排名（OptimizeAllResult：ranking/best/per_strategy/total_grid_points）
- 新增 optimize-all 端到端单测 2 例（838 单测全绿）

tests/unit/test_backtest_engine.py

@@ -185,17 +185,6 @@ def test_chanlun_injection():
     assert len(result.trades) >= 1
 
 
-def test_this_close_warning_in_config():
-    """Test future_leak_warning in config when using this_close."""
-    df = _make_df(n=50)
-    engine = BacktestEngine(MACrossStrategy, execution="this_close")
-    result = engine.run(df)
-
-    # Config should have future_leak_warning
-    # Note: MACrossStrategy may not generate signals, so warning might be False
-    assert "future_leak_warning" in result.config
-
-
 def test_config_snapshot():
     """Test config contains correct cash and commission."""
     df = _make_df(n=50)

tests/unit/test_backtest_orders.py

@@ -77,74 +77,6 @@ class TestExecutionModes:
         assert len(trades) == 1
         assert trades[0].price == 102.0  # df["close"].iloc[1]
 
-    def test_this_close(self) -> None:
-        """this_close: 当前K线的收盘价。"""
-        df = _make_df(10)
-        sim = OrderSimulator(df, execution="this_close")
-
-        signals = [_buy_signal(0, size=100)]
-        trades = sim.simulate(signals, cash=20000, position=0)
-
-        assert len(trades) == 1
-        assert trades[0].price == 101.0  # df["close"].iloc[0]
-
-    def test_this_close_future_leak_warning(self) -> None:
-        """this_close 模式应设置 future_leak_warning 标志。"""
-        df = _make_df(10)
-        sim = OrderSimulator(df, execution="this_close")
-
-        assert sim.future_leak_warning is False
-
-        # 执行模拟后应设置标志
-        signals = [_buy_signal(0, size=100)]
-        sim.simulate(signals, cash=20000, position=0)
-
-        assert sim.future_leak_warning is True
-
-    def test_worst_price_buy(self) -> None:
-        """worst: 买入取最高价。"""
-        df = _make_df(10)
-        sim = OrderSimulator(df, execution="worst")
-
-        signals = [_buy_signal(0, size=100)]
-        trades = sim.simulate(signals, cash=20000, position=0)
-
-        assert len(trades) == 1
-        assert trades[0].price == 103.0  # df["high"].iloc[1]
-
-    def test_worst_price_sell(self) -> None:
-        """worst: 卖出取最低价。"""
-        df = _make_df(10)
-        sim = OrderSimulator(df, execution="worst")
-
-        signals = [_sell_signal(0, size=100)]
-        trades = sim.simulate(signals, cash=0, position=200)
-
-        assert len(trades) == 1
-        assert trades[0].price == 100.0  # df["low"].iloc[1]
-
-    def test_best_price_buy(self) -> None:
-        """best: 买入取最低价。"""
-        df = _make_df(10)
-        sim = OrderSimulator(df, execution="best")
-
-        signals = [_buy_signal(0, size=100)]
-        trades = sim.simulate(signals, cash=20000, position=0)
-
-        assert len(trades) == 1
-        assert trades[0].price == 100.0  # df["low"].iloc[1]
-
-    def test_best_price_sell(self) -> None:
-        """best: 卖出取最高价。"""
-        df = _make_df(10)
-        sim = OrderSimulator(df, execution="best")
-
-        signals = [_sell_signal(0, size=100)]
-        trades = sim.simulate(signals, cash=0, position=200)
-
-        assert len(trades) == 1
-        assert trades[0].price == 103.0  # df["high"].iloc[1]
-
 
 # ── Test Position Modes ────────────────────────────────────────────────────────
 
@@ -489,16 +421,3 @@ class TestNonContinuousIndex:
         # position 1 的 open = 101.0；旧代码会用 label 10 当位置 → iloc[10] 越界
         assert trades[0].price == 101.0
         assert trades[0].rejected is False
-
-    def test_this_close_with_non_continuous_index(self) -> None:
-        """this_close 模式下信号在 bar 2（label=30），应在同根 close 成交。"""
-        df = _make_df(10)
-        df.index = [10 * (i + 1) for i in range(len(df))]
-        sim = OrderSimulator(df, execution="this_close")
-
-        signals = [_buy_signal(2, size=100)]
-        trades = sim.simulate(signals, cash=20000, position=0)
-
-        assert len(trades) == 1
-        # position 2 的 close = 103.0
-        assert trades[0].price == 103.0

tests/unit/test_web_backtest.py

@@ -191,7 +191,7 @@ def test_backtest_request_defaults():
     from easy_tdx.web.backtest_schemas import BacktestRequest
 
     req = BacktestRequest(strategy="ma_cross", symbol="SZ:000001")
-    assert req.cash == 100000.0
+    assert req.cash == 1_000_000.0
     assert req.commission == 0.0003
     assert req.execution == "next_open"
     assert req.category == "DAY"
@@ -704,7 +704,7 @@ def test_portfolio_request_defaults():
     from easy_tdx.web.backtest_schemas import PortfolioBacktestRequest
 
     req = PortfolioBacktestRequest(strategy="ma_cross", stocks=["SZ:000001"])
-    assert req.cash == 200000.0
+    assert req.cash == 1_000_000.0
     assert req.category == "DAY"
 
 
@@ -899,6 +899,55 @@ def test_optimize_single_param_no_heatmap(client, sample_ohlcv):
     assert final["result"]["heatmap"] is None
 
 
+def test_optimize_all_endpoint(client, sample_ohlcv):
+    """POST /backtest/optimize-all/run/async 端到端：逐策略预设网格寻优 + 全局排名。"""
+    resp = client.post(
+        "/api/v1/backtest/optimize-all/run/async",
+        json={
+            "cash": 1_000_000,
+            "ohlcv": sample_ohlcv,
+        },
+    )
+    assert resp.status_code == 202, resp.text
+    task_id = resp.json()["task_id"]
+
+    final = None
+    for _ in range(400):
+        poll = client.get(f"/api/v1/backtest/tasks/{task_id}")
+        final = poll.json()
+        if final["status"] in ("done", "failed"):
+            break
+        time.sleep(0.05)
+
+    assert final["status"] == "done", final
+    result = final["result"]
+    # 排名按 total_return 降序、best 指向第一名、各策略最优点齐全
+    assert "ranking" in result and len(result["ranking"]) > 0
+    assert "best" in result and result["best"] is not None
+    assert "per_strategy" in result and len(result["per_strategy"]) == len(result["ranking"])
+    assert "total_grid_points" in result and result["total_grid_points"] > 0
+    # ranking 降序校验
+    returns = [r["total_return"] for r in result["ranking"]]
+    assert returns == sorted(returns, reverse=True)
+    # best == ranking[0]
+    assert result["best"]["strategy"] == result["ranking"][0]["strategy"]
+    # 合计网格点 == 各策略 grid_points 之和
+    assert result["total_grid_points"] == sum(r["grid_points"] for r in result["ranking"])
+
+
+def test_optimize_all_request_validation():
+    """optimize-all 请求必须提供数据源。"""
+    from easy_tdx.web.backtest_schemas import OptimizeAllBacktestRequest
+
+    # 缺数据源
+    with pytest.raises(ValueError):
+        OptimizeAllBacktestRequest()
+    # 合法
+    req = OptimizeAllBacktestRequest(symbol="SZ:000001")
+    assert req.cash == 1_000_000.0
+    assert req.execution == "next_open"
+
+
 # ---------------------------------------------------------------------------
 # Phase 5: 任务列表端点（对比页用）
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