From b82c4eaedbc59a08a04e854eb0eaa7621f057092 Mon Sep 17 00:00:00 2001 From: shy3130 <415333856@qq.com> Date: Sun, 30 Aug 2026 19:05:09 +0800 Subject: [PATCH] =?UTF-8?q?feat(minute):=20=E5=88=86=E9=92=9F=E7=BA=A27?= =?UTF-8?q?=E6=96=B0=E5=A2=9E=E3=80=8CN=E6=97=A5=E5=86=85=E6=B6=A8?= =?UTF-8?q?=E5=81=9C=E8=BF=87=E3=80=8D=E6=9D=A1=E4=BB=B6=20+=20minute=5Ffi?= =?UTF-8?q?lter=20=E6=97=A5=E7=BA=BF=E7=AA=97=E5=8F=A3=E5=A5=91=E7=BA=A6?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit 分钟策略此前只能访问当日分钟窗口, 无法叠加日线维度条件。本次为 minute_filter 后端扩展可选日线历史契约: - 契约: 策略声明 META["daily_history_bars"] (0-250) + filter_minute_history 接受 daily 关键字 (加载期校验, 纯分钟策略零改动); 引擎聚合各策略声明 (minute_daily_history_bars) 后由 ScreenerService 1m 分支装配 context.daily_history (enriched 日线窗口), run() 以 daily= 注入 - 分钟红7: require_limit_up (默认开) + limit_up_days (5-60, 默认20) 参数; 涨停判定复用 enriched 预计算信号 signal_limit_up (收盘封板) 或 signal_broken_limit_up (炸板盘中触及), 任一命中即算涨停过, 输出 recent_limit_ups 次数列; 日线窗口缺失时失败闭合 (宁可漏过不可错报) - 测试 25 项: 涨停信号过滤/炸板计数/回看窗口边界(第20日含第21日不含)/ 失败闭合/开关旁路/加载校验(缺 daily 关键字与超范围)/引擎注入/服务装配 实盘验证: 用户参数(bars=6)基线 24 只 → 要求涨停过后 6 只, 全部带 recent_limit_ups; 全量 1112 项后端测试通过。 --- backend/app/services/screener.py | 8 + .../app/strategy/builtin/minute_red_streak.py | 61 +++++- backend/app/strategy/engine.py | 39 +++- backend/tests/test_minute_strategy.py | 192 +++++++++++++++++- 4 files changed, 285 insertions(+), 15 deletions(-) diff --git a/backend/app/services/screener.py b/backend/app/services/screener.py index 134cc90..c11cf64 100644 --- a/backend/app/services/screener.py +++ b/backend/app/services/screener.py @@ -390,12 +390,20 @@ class ScreenerService: # 分钟策略数据源是本地当日分钟K分区 (单分区文件直读), 与日线 # enriched 历史窗口无关, 不走 required_history_bars 日线路径。 history = self._load_minute_history(as_of, current) + # 策略声明 META["daily_history_bars"] 时额外装配日线 enriched 窗口, + # 供分钟策略叠加日线维度条件 (如 N 日内涨停过)。 + daily_history = None + if engine is not None: + daily_bars = engine.minute_daily_history_bars(strategy_ids) + if daily_bars > 0: + daily_history = self._load_enriched_history(as_of, daily_bars) return StrategyDataContext( asset_type=self.asset_type, timeframe=timeframe, as_of=as_of, current=current, history=history, + daily_history=daily_history, market=None, cache_key=cache_key, ) diff --git a/backend/app/strategy/builtin/minute_red_streak.py b/backend/app/strategy/builtin/minute_red_streak.py index 58bf2d3..9d2119d 100644 --- a/backend/app/strategy/builtin/minute_red_streak.py +++ b/backend/app/strategy/builtin/minute_red_streak.py @@ -4,6 +4,11 @@ (symbol, datetime, open, high, low, close, volume, amount), 由 ScreenerService.build_strategy_context 的 1m 分支从本地 kline_minute 分区注入; 策略本身不感知数据来源 (本地同步 / 盘中增量刷新对它透明)。 + +META["daily_history_bars"] 声明叠加日线维度的条件 (N 日内涨停过): +引擎会以 daily= 关键字注入日线 enriched 窗口, 涨停判定直接复用 +enriched 预计算信号 — signal_limit_up (收盘封板) 或 signal_broken_limit_up +(炸板: 盘中触及涨停未封住), 任一命中即算"盘中涨停过"。 """ import polars as pl @@ -11,10 +16,12 @@ import polars as pl META = { "id": "minute_red_streak", "name": "分钟红7", - "description": "开盘前7根1分钟K至少5根收红, 且最高的2根(按最高价)都是红K", + "description": "开盘前7根1分钟K至少5根收红, 最高的2根(按最高价)都是红K, 且近20日盘中触及过涨停", "tags": ["分钟", "形态", "短线"], "asset_types": ["stock"], "timeframes": ["1m"], + # 日线 enriched 窗口 (交易日语义, 含 as_of): 覆盖 limit_up_days 参数上限 + "daily_history_bars": 60, "params": [ { "id": "bars", @@ -49,6 +56,21 @@ META = { "type": "bool", "default": False, }, + { + "id": "require_limit_up", + "label": "要求N日内涨停过", + "type": "bool", + "default": True, + }, + { + "id": "limit_up_days", + "label": "涨停回看天数", + "type": "int", + "default": 20, + "min": 5, + "max": 60, + "step": 1, + }, ], "order_by": "red_count", "descending": True, @@ -60,12 +82,41 @@ ENTRY_SIGNALS: list[str] = [] EXIT_SIGNALS: list[str] = [] -def filter_minute_history(df: pl.DataFrame, params: dict) -> pl.DataFrame: +def _recent_limit_ups(daily: pl.DataFrame | None, lookback: int) -> pl.DataFrame: + """日线窗口 → (symbol, recent_limit_ups) 近 lookback 个交易日的涨停次数。 + + 涨停过 = signal_limit_up (收盘封板) 或 signal_broken_limit_up (炸板触及)。 + 日线窗口缺失 / 无涨停信号列 → 返回空表 (调用方 inner join 即失败闭合, + 宁可漏过不可错报)。 + """ + empty = pl.DataFrame(schema={"symbol": pl.Utf8, "recent_limit_ups": pl.UInt32}) + if daily is None or daily.is_empty(): + return empty + if not {"signal_limit_up", "signal_broken_limit_up"}.issubset(daily.columns): + return empty + return ( + daily.select("symbol", "date", "signal_limit_up", "signal_broken_limit_up") + .sort(["symbol", "date"]) + .filter(pl.int_range(pl.len()).over("symbol") >= pl.len().over("symbol") - lookback) + .group_by("symbol") + .agg( + recent_limit_ups=( + pl.col("signal_limit_up").fill_null(False) + | pl.col("signal_broken_limit_up").fill_null(False) + ).sum() + ) + .filter(pl.col("recent_limit_ups") > 0) + ) + + +def filter_minute_history(df: pl.DataFrame, params: dict, *, daily: pl.DataFrame | None = None) -> pl.DataFrame: """红K形态过滤: 全向量化, 无逐行 Python 循环。 - 每标的按时间取当日最早 bars 根 (开盘窗口); 不足 bars 根不触发 - 红 = close > open; 窗口内红K数 >= min_red - 按 rank_by (high / close) 降序取前 top_red 根, 同值取时间更晚者, 需全红 + - require_limit_up: 近 limit_up_days 个交易日盘中触及过涨停 (日线维度, + 由 daily 窗口的预计算涨停信号判定; 窗口缺失时失败闭合不触发) """ bars = int(params.get("bars") or 7) min_red = min(int(params.get("min_red") or 5), bars) @@ -99,7 +150,7 @@ def filter_minute_history(df: pl.DataFrame, params: dict) -> pl.DataFrame: .agg(top_red_count=pl.col("_red").sum()) ) - return ( + result = ( window.join(top, on="symbol", how="inner") .filter( (pl.col("bars_checked") >= bars) @@ -108,3 +159,7 @@ def filter_minute_history(df: pl.DataFrame, params: dict) -> pl.DataFrame: ) .drop("bars_checked") ) + if params.get("require_limit_up", True): + lookback = max(5, min(int(params.get("limit_up_days") or 20), 60)) + result = result.join(_recent_limit_ups(daily, lookback), on="symbol", how="inner") + return result diff --git a/backend/app/strategy/engine.py b/backend/app/strategy/engine.py index 42dd140..517e897 100644 --- a/backend/app/strategy/engine.py +++ b/backend/app/strategy/engine.py @@ -155,6 +155,9 @@ class StrategyDataContext: as_of: date current: pl.DataFrame | None = None history: pl.DataFrame | None = None + # 仅 1m 分支: 策略声明 META["daily_history_bars"] 时注入的日线 enriched 窗口, + # 供分钟策略叠加日线维度条件 (如 N 日内涨停过); 未声明时为 None。 + daily_history: pl.DataFrame | None = None market: Any | None = None cache_key: str | None = None @@ -201,6 +204,9 @@ class StrategyDef: composite: CompositeSpec | None = None # 仅 backend=="composite" 时非空 # 仅 backend=="minute_filter" 时非空: 输入为当日分钟K窗口, 输出为命中标的行 filter_minute_history_fn: Callable[[pl.DataFrame, dict], pl.DataFrame] | None = None + # 仅 minute_filter: META["daily_history_bars"] 声明需要的日线历史窗口 (0=不需要; + # >0 时 filter_minute_history 必须接受 daily 关键字, 引擎注入 context.daily_history) + minute_daily_bars: int = 0 @dataclass @@ -493,6 +499,7 @@ class StrategyEngine: matrix_strategy = getattr(mod, "MATRIX_STRATEGY", None) composite_spec: CompositeSpec | None = None + minute_daily_bars = 0 if execution_backend == "matrix_native": from app.backtest.matrix import MatrixStrategy @@ -535,6 +542,22 @@ class StrategyEngine: raise ValueError( "minute_filter strategy must declare timeframes == ['1m']" ) + # 可选日线历史窗口: 声明 daily_history_bars 时 fn 必须接受 daily 关键字, + # 引擎会把 context.daily_history (enriched 日线窗口) 注入进来。 + minute_daily_bars = int(meta.get("daily_history_bars") or 0) + if minute_daily_bars < 0 or minute_daily_bars > 250: + raise ValueError( + "minute_filter daily_history_bars must be within [0, 250]" + ) + if minute_daily_bars > 0: + import inspect + + sig = inspect.signature(filter_minute_history_fn) + if "daily" not in sig.parameters: + raise ValueError( + "minute_filter daily_history_bars requires " + "filter_minute_history to accept a 'daily' keyword" + ) elif filter_history_fn is None or filter_fn is not None: raise ValueError("python_history_legacy strategy must declare only filter_history") @@ -559,6 +582,7 @@ class StrategyEngine: matrix_strategy=matrix_strategy, composite=composite_spec, filter_minute_history_fn=filter_minute_history_fn, + minute_daily_bars=minute_daily_bars, ) def reload(self) -> None: @@ -673,6 +697,16 @@ class StrategyEngine: return None return max(0, int(value)) + def minute_daily_history_bars(self, strategy_ids: list[str]) -> int: + """1m 分支需要的日线 enriched 窗口大小: 各 minute_filter 策略声明的 + META["daily_history_bars"] 取 max, 未声明 (纯分钟策略) 为 0。""" + required = 0 + for strategy_id in strategy_ids: + strategy = self.get(strategy_id) + if strategy.execution_backend == "minute_filter": + required = max(required, strategy.minute_daily_bars) + return required + def required_history_bars( self, strategy_ids: list[str], @@ -917,7 +951,10 @@ class StrategyEngine: strategy_id=strategy_id, exit_signal_hits=exit_signal_hits, ) - df = s.filter_minute_history_fn(history, params) + if s.minute_daily_bars > 0: + df = s.filter_minute_history_fn(history, params, daily=context.daily_history) + else: + df = s.filter_minute_history_fn(history, params) # 基础过滤/展示列 (name/total_shares/change_pct 等) 来自 enriched 快照, # 在命中结果上事后联表, 避免把 enriched 列铺到全市场分钟行上。 if current is not None and not current.is_empty(): diff --git a/backend/tests/test_minute_strategy.py b/backend/tests/test_minute_strategy.py index b20d480..894f580 100644 --- a/backend/tests/test_minute_strategy.py +++ b/backend/tests/test_minute_strategy.py @@ -52,7 +52,7 @@ def test_pattern_hits_five_red_of_seven_with_red_top_two(): (10.5, 10.7, 10.80), # 红 (10.7, 10.8, 10.90), # 红 (最高) ] - out = minute_red_streak.filter_minute_history(_bars("600000.SH", candles), {}) + out = minute_red_streak.filter_minute_history(_bars("600000.SH", candles), {"require_limit_up": False}) assert out["symbol"].to_list() == ["600000.SH"] row = out.row(0, named=True) assert row["red_count"] == 5 @@ -61,7 +61,7 @@ def test_pattern_hits_five_red_of_seven_with_red_top_two(): def test_pattern_insufficient_bars_never_triggers(): - out = minute_red_streak.filter_minute_history(_bars("600000.SH", [(10.0, 10.2, 10.3)] * 6), {}) + out = minute_red_streak.filter_minute_history(_bars("600000.SH", [(10.0, 10.2, 10.3)] * 6), {"require_limit_up": False}) assert out.is_empty() @@ -76,7 +76,7 @@ def test_pattern_green_at_top_blocks_hit(): (11.5, 11.0, 12.00), # 绿 (最高) (11.0, 11.4, 11.90), # 红 (次高) ] - out = minute_red_streak.filter_minute_history(_bars("600000.SH", candles), {}) + out = minute_red_streak.filter_minute_history(_bars("600000.SH", candles), {"require_limit_up": False}) assert out.is_empty() @@ -91,9 +91,9 @@ def test_pattern_rank_by_close_uses_close_not_high(): (11.4, 11.1, 11.50), # 绿 (high 最高, 并列) (11.1, 11.5, 11.55), # 红 (close 最高) ] - by_high = minute_red_streak.filter_minute_history(_bars("600000.SH", candles), {}) + by_high = minute_red_streak.filter_minute_history(_bars("600000.SH", candles), {"require_limit_up": False}) by_close = minute_red_streak.filter_minute_history( - _bars("600000.SH", candles), {"rank_by_close": True} + _bars("600000.SH", candles), {"rank_by_close": True, "require_limit_up": False} ) assert by_high.is_empty() assert by_close["symbol"].to_list() == ["600000.SH"] @@ -107,7 +107,7 @@ def test_pattern_sorts_unordered_input_by_datetime(): (10.6, 10.5, 10.65), (10.5, 10.7, 10.80), (10.7, 10.8, 10.90), ]), ]).sample(fraction=1.0, shuffle=True, seed=7) - out = minute_red_streak.filter_minute_history(bars, {}) + out = minute_red_streak.filter_minute_history(bars, {"require_limit_up": False}) assert out["symbol"].to_list() == ["600000.SH"] assert out.row(0, named=True)["close"] == 10.8 # 最后一根(时间最大)的收盘 @@ -124,7 +124,7 @@ def test_pattern_three_way_high_tie_prefers_later_bars(): (10.5, 10.6, 10.90), # 红 (并列最高, 中间) (10.6, 10.8, 10.90), # 红 (并列最高, 最晚) ] - out = minute_red_streak.filter_minute_history(_bars("600000.SH", candles), {}) + out = minute_red_streak.filter_minute_history(_bars("600000.SH", candles), {"require_limit_up": False}) assert out["symbol"].to_list() == ["600000.SH"] assert out.row(0, named=True)["top_red_count"] == 2 @@ -141,8 +141,8 @@ def test_pattern_min_red_threshold_respected(): (10.5, 10.8, 10.90), # 红 ] bars = _bars("600000.SH", candles) - assert minute_red_streak.filter_minute_history(bars, {"min_red": 5}).is_empty() - assert not minute_red_streak.filter_minute_history(bars, {"min_red": 4}).is_empty() + assert minute_red_streak.filter_minute_history(bars, {"min_red": 5, "require_limit_up": False}).is_empty() + assert not minute_red_streak.filter_minute_history(bars, {"min_red": 4, "require_limit_up": False}).is_empty() def test_pattern_uses_opening_bars_even_if_day_turns_green(): @@ -159,7 +159,7 @@ def test_pattern_uses_opening_bars_even_if_day_turns_green(): (10.8, 10.0, 10.85), # 开盘窗口外的绿 (10.0, 9.5, 10.05), # 开盘窗口外的绿 ] - out = minute_red_streak.filter_minute_history(_bars("600000.SH", candles), {}) + out = minute_red_streak.filter_minute_history(_bars("600000.SH", candles), {"require_limit_up": False}) assert out["symbol"].to_list() == ["600000.SH"] row = out.row(0, named=True) assert row["red_count"] == 5 @@ -180,10 +180,84 @@ def test_pattern_opening_window_miss_not_rescued_by_late_reds(): (10.8, 10.9, 11.00), # 红 (窗口外) (10.9, 11.0, 11.10), # 红 (窗口外) ] - out = minute_red_streak.filter_minute_history(_bars("600000.SH", candles), {}) + out = minute_red_streak.filter_minute_history(_bars("600000.SH", candles), {"require_limit_up": False}) assert out.is_empty() +# ── 涨停条件 (日线维度) ───────────────────────────────────────────── + + +_HIT_CANDLES = [ + (10.0, 10.2, 10.30), # 红 + (10.2, 10.1, 10.25), # 绿 (低高点) + (10.1, 10.4, 10.50), # 红 + (10.4, 10.6, 10.70), # 红 (次高) + (10.6, 10.5, 10.65), # 绿 (低高点) + (10.5, 10.7, 10.80), # 红 + (10.7, 10.8, 10.90), # 红 (最高) +] + + +def _daily( + symbol: str, + days: int, + flag_on: set[int] | None = None, + *, + broken: bool = False, +) -> pl.DataFrame: + """days 个交易日的日线帧; flag_on 指定第几天 (0=最早) 触发涨停信号。""" + flag_on = flag_on or set() + base = date(2026, 8, 25) + return pl.DataFrame({ + "symbol": [symbol] * days, + "date": [base - _dt.timedelta(days=days - i) for i in range(days)], + "signal_limit_up": [i in flag_on and not broken for i in range(days)], + "signal_broken_limit_up": [i in flag_on and broken for i in range(days)], + }) + + +def test_pattern_limit_up_condition_filters_by_daily_signals(): + bars = pl.concat([ + _bars("600001.SH", _HIT_CANDLES), + _bars("600002.SH", _HIT_CANDLES), + _bars("600003.SH", _HIT_CANDLES), + ]) + daily = pl.concat([ + _daily("600001.SH", 20, {3}), # 收盘涨停 → 过 + _daily("600002.SH", 20, {15}, broken=True), # 炸板触及 → 过 + _daily("600003.SH", 20), # 无涨停 → 剔除 + ]) + out = minute_red_streak.filter_minute_history(bars, {}, daily=daily) + assert sorted(out["symbol"].to_list()) == ["600001.SH", "600002.SH"] + assert sorted(out["recent_limit_ups"].to_list()) == [1, 1] + + +def test_pattern_limit_up_lookback_window_boundary(): + # 25 个交易日, 涨停仅发生在第 5 天 (0=最早): 回看 20 日窗口 = 最后 20 根 + # (索引 5..24), 第 5 天在窗外 → 不命中; 回看放宽到 25 → 命中 + bars = _bars("600000.SH", _HIT_CANDLES) + daily = _daily("600000.SH", 25, {4}) + assert minute_red_streak.filter_minute_history(bars, {}, daily=daily).is_empty() + out = minute_red_streak.filter_minute_history( + bars, {"limit_up_days": 25}, daily=daily + ) + assert out["symbol"].to_list() == ["600000.SH"] + + +def test_pattern_limit_up_fails_closed_without_daily(): + # 日线窗口缺失时失败闭合 (宁可漏过不可错报) + out = minute_red_streak.filter_minute_history(_bars("600000.SH", _HIT_CANDLES), {}) + assert out.is_empty() + + +def test_pattern_limit_up_disabled_ignores_daily(): + out = minute_red_streak.filter_minute_history( + _bars("600000.SH", _HIT_CANDLES), {"require_limit_up": False} + ) + assert out["symbol"].to_list() == ["600000.SH"] + assert "recent_limit_ups" not in out.columns + + # ── 引擎加载与运行 ────────────────────────────────────────────────── @@ -225,6 +299,75 @@ def test_minute_filter_backend_validation(tmp_path): assert any("timeframes" in e["error"] for e in engine.load_errors()) +def test_minute_filter_daily_history_validation(tmp_path): + # 声明 daily_history_bars: fn 必须接受 daily 关键字, 且范围 [0, 250] + (tmp_path / "m_daily_ok.py").write_text( + 'import polars as pl\n' + 'META = {"id": "m_daily_ok", "name": "x", "asset_types": ["stock"], ' + '"timeframes": ["1m"], "daily_history_bars": 20}\n' + 'EXECUTION_BACKEND = "minute_filter"\n' + 'def filter_minute_history(df, params, *, daily=None):\n' + ' return df.group_by("symbol").agg(close=pl.col("close").max())\n' + ) + (tmp_path / "m_daily_kw.py").write_text( + 'import polars as pl\n' + 'META = {"id": "m_daily_kw", "name": "x", "asset_types": ["stock"], ' + '"timeframes": ["1m"], "daily_history_bars": 20}\n' + 'EXECUTION_BACKEND = "minute_filter"\n' + 'def filter_minute_history(df, params):\n' + ' return df.group_by("symbol").agg(close=pl.col("close").max())\n' + ) + (tmp_path / "m_daily_range.py").write_text( + 'import polars as pl\n' + 'META = {"id": "m_daily_range", "name": "x", "asset_types": ["stock"], ' + '"timeframes": ["1m"], "daily_history_bars": 300}\n' + 'EXECUTION_BACKEND = "minute_filter"\n' + 'def filter_minute_history(df, params, *, daily=None):\n' + ' return df.group_by("symbol").agg(close=pl.col("close").max())\n' + ) + engine = StrategyEngine(strategy_dirs=[tmp_path]) + assert engine.has("m_daily_ok") + assert engine.get("m_daily_ok").minute_daily_bars == 20 + assert not engine.has("m_daily_kw") + assert not engine.has("m_daily_range") + assert any("'daily' keyword" in e["error"] for e in engine.load_errors()) + assert any("[0, 250]" in e["error"] for e in engine.load_errors()) + + +def test_minute_run_injects_daily_history(tmp_path): + # fn 直接消费 daily (对涨停信号求和), 验证引擎把 context.daily_history 注入 + (tmp_path / "m_use_daily.py").write_text( + 'import polars as pl\n' + 'META = {"id": "m_use_daily", "name": "x", "asset_types": ["stock"], ' + '"timeframes": ["1m"], "daily_history_bars": 10}\n' + 'EXECUTION_BACKEND = "minute_filter"\n' + 'def filter_minute_history(df, params, *, daily=None):\n' + ' if daily is None:\n' + ' return pl.DataFrame(schema={"symbol": pl.Utf8})\n' + ' return daily.group_by("symbol").agg(\n' + ' close=pl.col("signal_limit_up").sum() + 10.0)\n' + ) + engine = StrategyEngine(strategy_dirs=[tmp_path]) + context = StrategyDataContext( + asset_type="stock", + timeframe="1m", + as_of=date(2026, 8, 25), + current=pl.DataFrame({ + "symbol": ["600001.SH"], + "name": ["正常股"], + "total_shares": [1e8], + "float_shares": [5e7], + "amount": [3e8], + "change_pct": [0.01], + }), + history=_bars("600001.SH", [(10.0, 10.2, 10.3)] * 7), + daily_history=_daily("600001.SH", 10, {2}), + ) + result = engine.run("m_use_daily", context) + assert result.total == 1 + assert result.rows[0]["close"] == 11 # 10 + 窗口内 1 次收盘涨停 + + def test_minute_context_run_applies_enriched_basic_filter(tmp_path): (tmp_path / "m_basic.py").write_text(_minute_code("m_basic")) engine = StrategyEngine(strategy_dirs=[tmp_path]) @@ -345,3 +488,30 @@ def test_minute_context_rejects_non_stock_asset(): raise AssertionError("expected ValueError") except ValueError as e: assert "A 股" in str(e) + + +def test_minute_context_loads_daily_history_for_declared_strategies(): + class _FakeEngine: + def minute_daily_history_bars(self, strategy_ids): + return 5 + + daily = _daily("600001.SH", 6, {1}) + repo = _FakeMinuteRepo({date(2026, 8, 25): _bars("600001.SH", [(10.0, 10.2, 10.3)] * 3)}) + repo.get_enriched_history = lambda target_date, lookback_days: daily # type: ignore[method-assign] + repo.get_instruments_asset = lambda asset_type: None # type: ignore[method-assign] + svc = ScreenerService(repo, asset_type="stock") # type: ignore[arg-type] + ctx = svc.build_strategy_context( + _FakeEngine(), date(2026, 8, 25), ["m_x"], timeframe="1m", + current=pl.DataFrame({"symbol": ["600001.SH"], "name": ["x"]}), + ) + assert ctx.daily_history is not None + assert ctx.daily_history.height == 6 # 引擎声明 5 → 装配日线窗口 + + +def test_minute_context_without_engine_skips_daily_history(): + svc = _svc({date(2026, 8, 25): _bars("600001.SH", [(10.0, 10.2, 10.3)] * 3)}) + ctx = svc.build_strategy_context( + None, date(2026, 8, 25), [], timeframe="1m", + current=pl.DataFrame({"symbol": ["600001.SH"]}), + ) + assert ctx.daily_history is None # 无引擎声明 → 不装配日线