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https://ghfast.top/https://github.com/aeroxw/tick-stock-panel.git
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shy3130
e3a2fbce13
数值字段(int/float) → 信号+因子双通道: - ext_factors: 帧组装时 join 扩展列并注册 kind=base 因子(分组「扩展数据」), 时序模式按 (symbol,交易日) 精确对齐无未来函数, 快照模式仅当日单日帧 注入(历史帧跳过防未来函数) - registry.all_factors 惰性同步(配置目录签名幂等, 以注册表为权威增删); custom_signals.allowed_fields 自动并入 → 信号下拉/因子库/AI提示词/检验 同一份清单; factor 补算入口按需注入 - 失效链: 上传/拉取/配置变更自动清扩展帧缓存+策略缓存, API层补 repo.clear_cache; 写入后下一次计算立即生效 - 列名保留中文(预设表字段名), 非ASCII数值字段只进信号不注册因子 (DSL标识符ASCII-only) string 字段(概念/行业归属) → 仅信号条件通道: - 运算符 包含(contains,字面量匹配非正则)/等于/不等于, 右值为字符串字面量, 可与数值条件混合(强势板块归属 AND 热度阈值) - 前端信号编辑器按字段类型切换运算符与右值输入; /options 暴露 stringFields; AI 提示词含字符串字段清单与 contains 用法 - string 不注册为因子(数值口径), 空值不误报 测试: test_ext_factors 18个(PIT对齐/跨日不泄露/快照门控/写入失效/ contains字面量/中文列名端到端等); 存量因子计数测试补 data/ 运行时隔离 夹具(黄金断言不依赖本机扩展表); 受影响回归148个全过; pnpm build 通过; ruff 对齐 main 基线
538 lines
22 KiB
Python
538 lines
22 KiB
Python
"""自定义信号 — 用户用「字段 + 运算符 + 值」组合出的布尔信号。
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职责:
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- 从 data/user_data/custom_signals/*.json 加载信号定义
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- 把每个信号的 conditions 编译成一条 Polars 布尔表达式（AND 组合）
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- 供 pipeline 在 compute_signals / compute_enriched_today 末尾注入为列
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不知道: 引擎、AI、API、回测、监控。纯函数 + 模块级缓存。
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设计:
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- 信号列名加前缀 ``csg_`` 避免与内置 ``signal_`` 列冲突。
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- 回测/选股/监控都按列名找信号，因此注入列后零特殊处理即可三处生效。
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- 字段白名单 + 固定运算符集，杜绝任意表达式注入。
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- 第一版只支持 AND（多条件同时满足）。
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"""
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from __future__ import annotations
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import json
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import logging
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import re
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from pathlib import Path
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import polars as pl
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logger = logging.getLogger(__name__)
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# ── 常量 ────────────────────────────────────────────────
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PREFIX = "csg_" # 自定义信号列名前缀
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ID_RE = re.compile(r"^[a-z0-9_]{1,40}$")
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OPS = {">", ">=", "<", "<=", "==", "!="}
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# string 扩展字段 (概念/行业归属等) 的运算符: contains 为字面量包含
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# (非正则, 用户输入不进入 pattern 编译), ==/!= 为字符串精确比较。
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STRING_OPS = {"contains", "==", "!="}
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_MAX_STR_RIGHT = 64
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# 字段白名单：只允许这些列出现在条件里（防注入）。均为数值型。
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# 与 ENRICHED_COLUMNS 的数值列保持一致，排除 symbol/date/name 等非数值列。
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ALLOWED_FIELDS: frozenset[str] = frozenset({
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# 行情
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"open", "high", "low", "close", "volume", "amount", "turnover_rate",
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"consecutive_limit_ups", "consecutive_limit_downs",
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# 基础
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"prev_close", "change_pct", "change_amount", "amplitude",
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# 均线 / 指数均线
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"ma5", "ma10", "ma20", "ma30", "ma60",
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"ema5", "ema10", "ema20", "ema30", "ema60",
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# MACD / BOLL / KDJ / ATR
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"macd_dif", "macd_dea", "macd_hist",
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"boll_upper", "boll_lower",
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"kdj_k", "kdj_d", "kdj_j",
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"atr_14",
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# 量价 / 极值 / 动量 / 波动率 / RSI
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"vol_ma5", "vol_ma10", "vol_ratio_5d",
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"high_60d", "low_60d",
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"momentum_5d", "momentum_10d", "momentum_20d", "momentum_30d", "momentum_60d",
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"annual_vol_20d",
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"rsi_6", "rsi_14", "rsi_24",
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# 异动偏离 (交易所异动规则口径, 运行时列)
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"deviate_3d", "deviate_10d", "deviate_30d",
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})
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# 运算符 → Polars 表达式构造器（输入 col_expr, value）
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_OP_BUILDERS = {
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">": lambda c, v: c > v,
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">=": lambda c, v: c >= v,
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"<": lambda c, v: c < v,
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"<=": lambda c, v: c <= v,
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"==": lambda c, v: c == v,
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"!=": lambda c, v: c != v,
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# literal=True: 右值按字面量匹配, 不当正则编译 (用户输入含 .* 等也安全)
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"contains": lambda c, v: c.cast(pl.Utf8).str.contains(v, literal=True),
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}
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def _string_ext_fields() -> frozenset[str]:
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"""string 扩展字段列名 (概念/行业等); 解析/校验按字段 dtype 分发。"""
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try:
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from app.factors.ext_factors import ext_string_fields
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return ext_string_fields()
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except Exception:
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return frozenset()
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def allowed_fields() -> frozenset[str]:
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"""条件可引用字段 = 物化列白名单 并入 注册表因子 与 string 扩展字段。
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因子列在历史路径 (compute_signals) 由 materialize_factor_columns 复用
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评分物化管线补算; 盘中单日快照无滚动窗口, 依赖因子的信号被 inject 以
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缺列告警跳过 (与日期偏移条件同样的优雅降级)。
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string 扩展字段 (ext_{表}_{字段}, 概念/行业归属) 只支持 contains/==/!=,
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在帧组装时由 attach_ext_columns 注入, 不注册为因子 (数值口径约束)。
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"""
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from app.factors.registry import all_factors
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return frozenset(ALLOWED_FIELDS | {spec.id for spec in all_factors()} | _string_ext_fields())
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def materialize_factor_columns(
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df: pl.DataFrame,
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exprs: dict[str, pl.Expr],
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needed: set[str] | None = None,
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) -> pl.DataFrame:
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"""把信号表达式引用、且 df 缺失的注册表因子列补算出来。
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复用评分物化路径 (materialize_scoring_columns) — 与检验/评分同一条计算
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逻辑, 不引入第二套实现。非注册表列不在此处理 (缺列仍由 inject 告警跳过)。
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"""
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if df.is_empty() or not exprs:
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return df
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cols = set(df.columns)
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missing: set[str] = set()
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for name, roots in expression_dependencies(exprs).items():
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if needed is not None and name not in needed:
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continue
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missing.update(root for root in roots if root not in cols)
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if not missing:
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return df
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from app.factors.registry import all_factors
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factor_ids = {spec.id for spec in all_factors()}
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to_compute = missing & factor_ids
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if not to_compute:
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return df
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from app.strategy.scoring import materialize_scoring_columns
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return materialize_scoring_columns(df, sorted(to_compute))
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# ── 持久化（镜像 strategy/config.py 的写法）──────────────
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def _dir(data_dir: Path) -> Path:
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d = data_dir / "user_data" / "custom_signals"
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d.mkdir(parents=True, exist_ok=True)
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return d
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def _path(data_dir: Path, signal_id: str) -> Path:
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return _dir(data_dir) / f"{signal_id}.json"
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def load_all(data_dir: Path) -> list[dict]:
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"""读取全部自定义信号定义。损坏的文件被跳过。"""
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d = _dir(data_dir)
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out: list[dict] = []
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for f in sorted(d.glob("*.json")):
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try:
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out.append(json.loads(f.read_text(encoding="utf-8")))
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except Exception as e:
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logger.warning("custom signal load failed %s: %s", f.name, e)
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return out
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def save_one(data_dir: Path, sig: dict) -> None:
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p = _path(data_dir, sig["id"])
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p.parent.mkdir(parents=True, exist_ok=True)
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p.write_text(json.dumps(sig, ensure_ascii=False, indent=2), encoding="utf-8")
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def delete_one(data_dir: Path, signal_id: str) -> bool:
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p = _path(data_dir, signal_id)
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if p.exists():
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p.unlink()
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return True
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return False
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# ── 校验 ────────────────────────────────────────────────
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MAX_DAYS = 60 # 偏移天数上限 (前N日的 N)
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def _parse_days(c: dict, key: str, i: int) -> int:
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"""解析并校验条件的天数偏移 (leftDays / rightDays)。返回 0..MAX_DAYS。"""
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raw = c.get(key, 0)
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try:
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n = int(raw)
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except (TypeError, ValueError):
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raise ValueError(f"第 {i+1} 个条件: {key} 必须是整数: {raw!r}")
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if n < 0 or n > MAX_DAYS:
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raise ValueError(f"第 {i+1} 个条件: {key} 必须在 0..{MAX_DAYS} 之间: {n}")
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return n
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def _parse_right(right: str, *, string_mode: bool = False) -> tuple[str, object]:
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"""解析右值。返回 ('field', colname) / ('const', float) / ('const_str', str)。
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数值模式接受三种形式:
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- 数字 (int / float / 数字字符串) → 常量
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- "field:字段名" → 字段引用
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- 裸字段名 (在白名单内) → 自动视为字段引用
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(AI 生成偶尔漏写 field: 前缀; 白名单字段名不可能是数字, 无歧义)
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string 模式 (左字段是 string 扩展字段): 只接受非空字符串字面量
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(概念/行业名), 不支持字段引用 —— "字段A包含字段B" 无业务语义且
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会与 field: 前缀解析产生歧义。
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"""
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if string_mode:
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if not isinstance(right, str) or not right.strip():
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raise ValueError("字符串条件的右值必须是非空字符串 (如概念/行业名)")
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if right.startswith("field:"):
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raise ValueError("字符串条件不支持字段引用右值, 请填字符串字面量")
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if len(right) > _MAX_STR_RIGHT:
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raise ValueError(f"字符串右值过长 (≤{_MAX_STR_RIGHT} 字符): {right[:20]}…")
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return ("const_str", right.strip())
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if isinstance(right, (int, float)):
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return ("const", float(right))
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if not isinstance(right, str):
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raise ValueError(f"非法右值: {right!r}")
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allowed = allowed_fields()
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if right.startswith("field:"):
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col = right[len("field:"):]
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if col not in allowed:
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raise ValueError(f"右值字段不在白名单: {col}")
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return ("field", col)
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# 纯数字
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try:
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return ("const", float(right))
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except ValueError:
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pass
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# 裸字段名 — 兜底容错, 仍受白名单约束
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if right in allowed:
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return ("field", right)
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raise ValueError(f"非法右值（应为 field:xxx 或数字）: {right!r}")
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def validate(sig: dict) -> None:
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"""校验一个信号定义，非法则抛 ValueError（含中文信息）。"""
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sid = sig.get("id", "")
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if not isinstance(sid, str) or not ID_RE.match(sid):
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raise ValueError(f"信号 id 非法（仅小写字母数字下划线，1-40字符）: {sid!r}")
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if not isinstance(sig.get("name"), str) or not sig["name"].strip():
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raise ValueError("信号 name 不能为空")
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if sig.get("kind") not in ("entry", "exit", "both"):
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raise ValueError("kind 必须是 entry / exit / both")
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timeframe = sig.get("timeframe", TIMEFRAME_DAILY)
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if timeframe not in (TIMEFRAME_DAILY, TIMEFRAME_INTRADAY):
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raise ValueError(f"timeframe 必须是 {TIMEFRAME_DAILY} / {TIMEFRAME_INTRADAY}: {timeframe!r}")
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conds = sig.get("conditions")
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if not isinstance(conds, list) or len(conds) == 0:
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raise ValueError("conditions 不能为空")
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if len(conds) > 8:
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raise ValueError("conditions 最多 8 条")
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if timeframe == TIMEFRAME_INTRADAY:
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_validate_intraday(sig)
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return
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string_fields = _string_ext_fields()
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for i, c in enumerate(conds):
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if not isinstance(c, dict):
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raise ValueError(f"第 {i+1} 个条件格式错误")
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left = c.get("left", "")
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if left not in allowed_fields():
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raise ValueError(f"第 {i+1} 个条件: 字段 {left!r} 不在白名单")
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is_str = left in string_fields
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if is_str:
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if c.get("op") not in STRING_OPS:
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raise ValueError(
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f"第 {i+1} 个条件: 字符串字段 {left!r} 仅支持 "
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f"{'/'.join(sorted(STRING_OPS))} 运算符"
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)
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elif c.get("op") == "contains":
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raise ValueError(f"第 {i+1} 个条件: contains 仅用于字符串扩展字段")
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elif c.get("op") not in OPS:
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raise ValueError(f"第 {i+1} 个条件: 运算符 {c.get('op')!r} 非法")
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_parse_right(c.get("right"), string_mode=is_str) # 会校验右值字段/数字/字符串
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_parse_days(c, "leftDays", i) # 左字段偏移
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_parse_days(c, "rightDays", i) # 右字段偏移
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# ── 编译为 Polars 表达式 ─────────────────────────────────
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def column_name(signal_id: str) -> str:
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"""信号 id → DataFrame 列名（加前缀）。"""
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return f"{PREFIX}{signal_id}"
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def _col(name: str, days: int = 0) -> pl.Expr:
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"""构造列表达式; days>0 时取 N 个交易日前的值 (按 symbol 分组 shift)。"""
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expr = pl.col(name)
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if days > 0:
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expr = expr.shift(days).over("symbol")
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return expr
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def build_expressions(signals: list[dict], allow_shift: bool = True) -> dict[str, pl.Expr]:
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"""把多个自定义信号编译成 {column_name: pl.Expr}。
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- 只处理 enabled != False 的信号。
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- 单个信号内多条件用 ``&`` 串联（AND）。
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- allow_shift=False 时, 跳过带日期偏移 (leftDays/rightDays>0) 的信号
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(盘中单日快照上 .shift 跨 symbol 语义不正确, 优雅降级)。
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- 编译失败的信号被跳过并告警（不影响其它信号）。
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"""
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out: dict[str, pl.Expr] = {}
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string_fields = _string_ext_fields()
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for sig in signals:
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if sig.get("enabled") is False:
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continue
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try:
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conds = sig["conditions"]
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col_name = column_name(sig["id"])
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parts: list[pl.Expr] = []
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for c in conds:
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left_days = int(c.get("leftDays", 0) or 0)
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right_days = int(c.get("rightDays", 0) or 0)
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# 盘中路径不支持偏移 → 跳过整个信号
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if not allow_shift and (left_days > 0 or right_days > 0):
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raise ValueError("盘中实时路径不支持日期偏移条件, 已跳过")
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left = c["left"]
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op = c["op"]
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is_str = left in string_fields
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if is_str and op not in STRING_OPS:
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raise ValueError(f"字符串字段 {left!r} 不支持运算符 {op!r}")
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if op == "contains" and not is_str:
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raise ValueError(f"contains 仅用于字符串扩展字段: {left!r}")
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kind, val = _parse_right(c["right"], string_mode=is_str)
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right_expr = _col(val, right_days) if kind == "field" else val
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parts.append(_OP_BUILDERS[op](_col(left, left_days), right_expr))
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combined = parts[0]
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for p in parts[1:]:
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combined = combined & p
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out[col_name] = combined
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except Exception as e:
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logger.warning("custom signal compile failed %s: %s", sig.get("id"), e)
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return out
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def expression_dependencies(exprs: dict[str, pl.Expr] | None = None) -> dict[str, frozenset[str]]:
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"""返回自定义信号列到根字段的依赖映射。"""
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source = exprs if exprs is not None else {}
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return {name: frozenset(_expr_root_columns(expr)) for name, expr in source.items()}
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def inject(
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df: pl.DataFrame,
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exprs: dict[str, pl.Expr],
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needed: set[str] | None = None,
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) -> pl.DataFrame:
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"""把编译好的信号表达式作为列加入 df。
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``needed=None`` 保持历史全量语义；传入集合时只注入被请求的自定义信号。
|
||
缺失依赖会明确告警，避免回测静默丢失信号。
|
||
"""
|
||
if df.is_empty() or not exprs:
|
||
return df
|
||
cols = set(df.columns)
|
||
add: dict[str, pl.Expr] = {}
|
||
for name, expr in exprs.items():
|
||
if needed is not None and name not in needed:
|
||
continue
|
||
# 提取该表达式引用的所有字段列，缺失则跳过（避免运行时报错）
|
||
required = _expr_root_columns(expr)
|
||
if required.issubset(cols):
|
||
add[name] = expr
|
||
else:
|
||
logger.warning(
|
||
"custom signal %s missing dependencies: %s",
|
||
name,
|
||
sorted(required - cols),
|
||
)
|
||
if add:
|
||
df = df.with_columns([e.alias(n) for n, e in add.items()])
|
||
return df
|
||
|
||
|
||
def _expr_root_columns(expr: pl.Expr) -> set[str]:
|
||
"""尽力提取表达式里出现的列名。失败则返回空集（保守跳过）。"""
|
||
try:
|
||
# Polars 的 meta.root_names() 返回表达式引用的根列名
|
||
names = expr.meta.root_names()
|
||
return set(names)
|
||
except Exception:
|
||
return set()
|
||
|
||
|
||
# ══ 盘中信号(timeframe="intraday")═════════════════════════
|
||
# 与日线自定义信号同一套 left/op/right 条件结构, 但:
|
||
# - 字段白名单换成分钟特征(intraday_features.INTRADAY_FEATURES);
|
||
# - 运算符额外支持 cross_up / cross_down(序列上穿/下穿 另一序列或阈值);
|
||
# - 不支持 leftDays/rightDays 日期偏移;
|
||
# - 信号列名前缀 csgi_, 注入对象是分钟特征帧而非日线 enriched。
|
||
# 语义: 信号输出 = 当日条件组合的上升沿(false→true), 首根 bar 不触发。
|
||
|
||
from app.strategy.intraday_features import INTRADAY_FEATURES # noqa: E402
|
||
|
||
TIMEFRAME_DAILY = "daily"
|
||
TIMEFRAME_INTRADAY = "intraday"
|
||
INTRADAY_PREFIX = "csgi_"
|
||
INTRADAY_OPS = OPS | {"cross_up", "cross_down"}
|
||
_EDGE_GROUP = ["symbol", "date"]
|
||
|
||
|
||
def intraday_column_name(signal_id: str) -> str:
|
||
"""盘中信号 id → 分钟帧列名(加 csgi_ 前缀)。"""
|
||
return f"{INTRADAY_PREFIX}{signal_id}"
|
||
|
||
|
||
def _parse_right_intraday(right: object) -> tuple[str, object]:
|
||
"""盘中条件的右值: ('const', float) 或 ('field', 特征名)。"""
|
||
if isinstance(right, (int, float)):
|
||
return ("const", float(right))
|
||
if not isinstance(right, str):
|
||
raise ValueError(f"非法右值: {right!r}")
|
||
if right.startswith("field:"):
|
||
col = right[len("field:"):]
|
||
if col not in INTRADAY_FEATURES:
|
||
raise ValueError(f"盘中右值字段不在白名单: {col}")
|
||
return ("field", col)
|
||
try:
|
||
return ("const", float(right))
|
||
except ValueError:
|
||
pass
|
||
if right in INTRADAY_FEATURES:
|
||
return ("field", right)
|
||
raise ValueError(f"非法盘中右值(应为 field:特征 或数字): {right!r}")
|
||
|
||
|
||
def _validate_intraday(sig: dict) -> None:
|
||
"""校验盘中信号定义, 非法抛 ValueError。"""
|
||
conds = sig.get("conditions")
|
||
for i, c in enumerate(conds):
|
||
if not isinstance(c, dict):
|
||
raise ValueError(f"第 {i+1} 个条件格式错误")
|
||
left = c.get("left", "")
|
||
if left not in INTRADAY_FEATURES:
|
||
raise ValueError(f"第 {i+1} 个条件: 盘中字段 {left!r} 不在白名单")
|
||
if c.get("op") not in INTRADAY_OPS:
|
||
raise ValueError(f"第 {i+1} 个条件: 运算符 {c.get('op')!r} 非法(盘中额外支持 cross_up/cross_down)")
|
||
_parse_right_intraday(c.get("right"))
|
||
if int(c.get("leftDays", 0) or 0) or int(c.get("rightDays", 0) or 0):
|
||
raise ValueError(f"第 {i+1} 个条件: 盘中信号不支持日期偏移(leftDays/rightDays)")
|
||
min_bars = sig.get("min_bars", 0)
|
||
try:
|
||
n = int(min_bars)
|
||
except (TypeError, ValueError):
|
||
raise ValueError(f"min_bars 必须是整数: {min_bars!r}") # noqa: B904
|
||
if n < 0 or n > 240:
|
||
raise ValueError(f"min_bars 必须在 0..240 之间: {n}")
|
||
|
||
|
||
def build_intraday_expressions(signals: list[dict]) -> dict[str, pl.Expr]:
|
||
"""把盘中信号编译为特征帧上的「条件」表达式(AND 组合, 未做上升沿)。
|
||
|
||
表达式在 intraday_features.build_feature_frame 产出的帧上求值;
|
||
上升沿须通过 apply_intraday_edges 在 DataFrame 层两步计算 —
|
||
对已含 .over() 窗口的组合表达式直接 shift().over() 是窗口嵌套,
|
||
Polars 会返回全 null。编译失败的信号跳过并告警。
|
||
"""
|
||
out: dict[str, pl.Expr] = {}
|
||
for sig in signals:
|
||
if sig.get("enabled") is False or sig.get("timeframe") != TIMEFRAME_INTRADAY:
|
||
continue
|
||
try:
|
||
parts: list[pl.Expr] = []
|
||
for c in sig["conditions"]:
|
||
left = pl.col(c["left"])
|
||
kind, val = _parse_right_intraday(c["right"])
|
||
op = c["op"]
|
||
if op == "cross_up":
|
||
# 前一根 bar 未满足 且 当前 bar 满足; 右值为常量时不 shift 字面量
|
||
if kind == "field":
|
||
prev_ok = left.shift(1).over(_EDGE_GROUP) <= pl.col(val).shift(1).over(_EDGE_GROUP)
|
||
cur_ok = left > pl.col(val)
|
||
else:
|
||
prev_ok = left.shift(1).over(_EDGE_GROUP) <= val
|
||
cur_ok = left > val
|
||
parts.append(prev_ok & cur_ok)
|
||
elif op == "cross_down":
|
||
if kind == "field":
|
||
prev_ok = left.shift(1).over(_EDGE_GROUP) >= pl.col(val).shift(1).over(_EDGE_GROUP)
|
||
cur_ok = left < pl.col(val)
|
||
else:
|
||
prev_ok = left.shift(1).over(_EDGE_GROUP) >= val
|
||
cur_ok = left < val
|
||
parts.append(prev_ok & cur_ok)
|
||
else:
|
||
right = pl.col(val) if kind == "field" else val
|
||
parts.append(_OP_BUILDERS[op](left, right))
|
||
combined = parts[0]
|
||
for p in parts[1:]:
|
||
combined = combined & p
|
||
out[intraday_column_name(sig["id"])] = combined
|
||
except Exception as e:
|
||
logger.warning("intraday signal compile failed %s: %s", sig.get("id"), e)
|
||
return out
|
||
|
||
|
||
def apply_intraday_edges(frame: pl.DataFrame, exprs: dict[str, pl.Expr]) -> pl.DataFrame:
|
||
"""对特征帧求值盘中信号: 先算条件列, 再取「当日条件上升沿」为布尔列。
|
||
|
||
上升沿: 条件 false→true 的那根 bar 为 true; 首根 bar(前值为 null)不触发;
|
||
条件含 null(特征不足)视为 false。四条消费路径(监控/实盘/回测/回放)
|
||
必须共用本函数, 保证口径一致。
|
||
"""
|
||
if frame.is_empty() or not exprs:
|
||
return frame
|
||
df = frame.with_columns([e.fill_null(False).alias(n) for n, e in exprs.items()])
|
||
return df.with_columns([
|
||
(
|
||
pl.col(n)
|
||
& ~pl.col(n).shift(1).over(_EDGE_GROUP).fill_null(True)
|
||
).cast(pl.Boolean).alias(n)
|
||
for n in exprs
|
||
])
|
||
|
||
|
||
# ── 盘中信号定义加载(带指纹缓存: 引擎/监控高频路径用) ──────────
|
||
_intraday_cache: dict[Path, tuple[object, list[dict]]] = {}
|
||
|
||
|
||
def _dir_fingerprint(d: Path) -> tuple:
|
||
"""目录内 *.json 的 (文件名, mtime) 指纹 — 创建/删除/编辑都会变化。"""
|
||
try:
|
||
return tuple(sorted((f.name, f.stat().st_mtime_ns) for f in d.glob("*.json")))
|
||
except OSError:
|
||
return ()
|
||
|
||
|
||
def load_intraday_all(data_dir: Path) -> list[dict]:
|
||
"""读取全部启用的盘中信号定义(带缓存)。
|
||
|
||
盘中评估与引擎注入每分钟执行, 不宜每次全量读盘; save/delete 端点
|
||
调用 invalidate_intraday_cache() 主动失效。
|
||
"""
|
||
d = _dir(data_dir)
|
||
fp = _dir_fingerprint(d)
|
||
cached = _intraday_cache.get(data_dir)
|
||
if cached is not None and cached[0] == fp:
|
||
return cached[1]
|
||
sigs = [
|
||
s for s in load_all(data_dir)
|
||
if s.get("timeframe") == TIMEFRAME_INTRADAY and s.get("enabled") is not False
|
||
]
|
||
_intraday_cache[data_dir] = (fp, sigs)
|
||
return sigs
|
||
|
||
|
||
def invalidate_intraday_cache() -> None:
|
||
_intraday_cache.clear()
|