mirror of
https://ghfast.top/https://github.com/aeroxw/tick-stock-panel.git
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shy3130
716897f41a
- intraday_features: 会话对齐特征帧构造器(vwap/涨跌幅/1·3·5分钟放量比/ 日内与开盘30分钟高低点距离, 滚动窗口不跨午休, 只用已收盘bar防未来函数) - custom_signals: timeframe=daily|intraday 双 schema, 盘中条件支持 cross_up/cross_down 穿越算子; 输出为当日条件上升沿(首bar不触发, null特征判false绝不误报) - 旧4个分时穿越信号列名零迁移(评估器回映射历史列名, 存量监控规则不动) - 引擎单点注入 csgi_ 列: 监控/分钟策略/分钟回测共用同一构造器; 日线策略引用盘中信号显式报错 - 回放验证 API /api/custom-signals/intraday/replay(本地历史分钟K重放, 区间≤60天标的≤200, 先验证再配置监控) - 能力门槛: 分钟K能力(订阅池)或全量分钟能力(本地分区); 回放仅需本地历史 验证: 新增16个测试(特征数值/边界/旧4信号黄金等价/引擎注入/回放端点), 受影响回归109个全过, ruff对齐基线, docs/features.md 同步
317 lines
13 KiB
Python
317 lines
13 KiB
Python
"""自定义信号 API 路由 — HTTP 请求 → 调用 custom_signals 模块 → 返回响应。
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只做胶水：校验 → 持久化 → 失效缓存。不含表达式编译逻辑。
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"""
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from __future__ import annotations
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from pathlib import Path
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from fastapi import APIRouter, HTTPException, Request
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from pydantic import BaseModel
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from app.strategy import custom_signals
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from app.strategy.intraday_features import INTRADAY_FEATURES
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router = APIRouter(prefix="/api/custom-signals", tags=["custom-signals"])
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def _data_dir(request: Request) -> Path:
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return request.app.state.repo.store.data_dir
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def _invalidate(request: Request) -> None:
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"""失效自定义信号表达式缓存, 并清掉含旧信号列的计算缓存。
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信号增删会改变注入列集合: 只清表达式缓存不够, repo 内存缓存 /
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strategy 磁盘缓存里算好的历史窗口仍不含新 csg_ 列 (或仍含已删列),
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需要一并清除, 否则创建信号后立即运行策略仍会报缺列。
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盘中信号定义缓存(intraday)一并失效, 下一分钟 bucket 即生效。
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"""
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custom_signals.invalidate_intraday_cache()
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from app.indicators.pipeline import invalidate_custom_signals
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invalidate_custom_signals()
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from app.services import strategy_cache
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strategy_cache.clear_cache(_data_dir(request))
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repo = request.app.state.repo
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if hasattr(repo, "clear_cache"):
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repo.clear_cache()
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class ConditionModel(BaseModel):
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left: str # 字段名（日线在白名单 / 盘中在特征白名单）
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op: str # > >= < <= == != ; 盘中额外: cross_up cross_down
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right: str # "field:xxx" 或数字字符串
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leftDays: int = 0 # 左字段取几日前 (0=当日, 默认; 盘中信号必须为 0)
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rightDays: int = 0 # 右字段取几日前 (仅 right 为字段时有意义; 盘中信号必须为 0)
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class SignalModel(BaseModel):
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id: str
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name: str
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kind: str # entry | exit | both
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conditions: list[ConditionModel]
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enabled: bool = True
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timeframe: str = "daily" # daily | intraday(分钟K特征, 输出当日条件上升沿)
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min_bars: int = 0 # 仅 intraday: 当日最少已完成 bar 数, 不足不触发
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class IntradayReplayRequest(BaseModel):
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"""盘中信号历史回放 — 用本地分钟K重放触发时点, 不消耗盘中数据能力。"""
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signal_id: str
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start_date: str # YYYY-MM-DD
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end_date: str # YYYY-MM-DD
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symbols: list[str]
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asset_type: str = "stock"
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class AIGenerateRequest(BaseModel):
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description: str
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# ── 字段选项 / 运算符 ───────────────────────────────────
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@router.get("/options")
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def get_options():
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"""返回可选字段与运算符，供前端下拉框使用。"""
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# 字段带中文标签（取自 ENRICHED_COLUMNS，回退为字段名本身）
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from app.indicators.pipeline import ENRICHED_COLUMNS, ENRICHED_COLUMNS_BY_CATEGORY
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allowed = custom_signals.ALLOWED_FIELDS
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fields = [
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{"key": f, "label": ENRICHED_COLUMNS.get(f, f)}
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for f in sorted(allowed)
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]
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# 字段分组 (只包含白名单内的字段, 供前端 optoptgroup 渲染)
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_GROUP_LABELS = {
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"basic": "基础", "ma": "均线 MA", "ema": "指数均线 EMA",
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"macd": "MACD", "boll": "布林带 BOLL", "kdj": "KDJ",
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"atr": "ATR", "volume": "量价", "extremes": "极值",
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"momentum": "动量", "volatility": "波动率", "rsi": "RSI",
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}
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# 行情类字段不在 ENRICHED_COLUMNS_BY_CATEGORY 里, 单独归一组
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quote_fields = {"open", "high", "low", "close", "volume", "amount",
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"turnover_rate", "consecutive_limit_ups", "consecutive_limit_downs"}
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groups = [{"key": "quote", "label": "行情",
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"fields": [{"key": f, "label": ENRICHED_COLUMNS.get(f, f)}
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for f in sorted(allowed & quote_fields)]}]
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for cat, label in _GROUP_LABELS.items():
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cat_fields = [f for f in ENRICHED_COLUMNS_BY_CATEGORY.get(cat, []) if f in allowed]
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if cat_fields:
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groups.append({"key": cat, "label": label,
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"fields": [{"key": f, "label": ENRICHED_COLUMNS.get(f, f)} for f in cat_fields]})
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# 注册表因子 (虚拟/自定义/复合): 历史路径由 compute_signals 复用评分物化
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# 管线补算; 已是物化列的基础因子 (rsi_14 等) 上面已分组, 此处跳过。
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from app.factors.registry import all_factors
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factor_groups: dict[str, list[dict[str, str]]] = {}
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for spec in all_factors():
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if spec.id in allowed:
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continue
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label = spec.label
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if spec.warmup_bars > 1:
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label = f"{label} · 预热{spec.warmup_bars}日"
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if list(spec.asset_types) == ["stock"]:
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label = f"{label} · 仅股票"
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factor_groups.setdefault(spec.group or "因子", []).append({"key": spec.id, "label": label})
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for group_label, group_fields in factor_groups.items():
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groups.append({"key": f"factor:{group_label}", "label": f"因子 · {group_label}", "fields": group_fields})
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fields.extend(group_fields)
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return {
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"fields": fields,
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"groups": groups,
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"maxDays": custom_signals.MAX_DAYS,
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"operators": [">", ">=", "<", "<=", "==", "!="],
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"kinds": [
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{"key": "entry", "label": "入场"},
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{"key": "exit", "label": "出场"},
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{"key": "both", "label": "出入通用"},
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],
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# 盘中信号(timeframe=intraday): 分钟K特征白名单 + 额外穿越算子
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"intraday": {
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"fields": [
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{"key": f, "label": label}
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for f, label in sorted(INTRADAY_FEATURES.items())
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],
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"operators": [">", ">=", "<", "<=", "==", "!=", "cross_up", "cross_down"],
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},
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"timeframes": [
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{"key": "daily", "label": "日线"},
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{"key": "intraday", "label": "盘中(分钟K)"},
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],
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}
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# ── 列表 ───────────────────────────────────────────────
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@router.get("")
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def list_signals(request: Request):
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sigs = custom_signals.load_all(_data_dir(request))
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return {"signals": sigs}
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# ── 新建 / 更新 ────────────────────────────────────────
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@router.post("")
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def save_signal(req: SignalModel, request: Request):
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sig = req.model_dump()
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try:
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custom_signals.validate(sig)
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except ValueError as e:
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raise HTTPException(status_code=400, detail=str(e))
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custom_signals.save_one(_data_dir(request), sig)
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_invalidate(request)
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return {"ok": True, "signal": sig}
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# ── AI 生成 ─────────────────────────────────────────────
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@router.post("/ai/generate")
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async def ai_generate_signal(req: AIGenerateRequest):
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"""AI 根据自然语言描述生成自定义信号条件。
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不落盘：只返回 {name, conditions} 供前端回填表单，由用户确认后走
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常规 save 流程。校验复用 custom_signals.validate()（白名单安全闸门）。
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"""
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from app.services.ai_provider import generate_ai_text
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from app.strategy import custom_signals_ai
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description = req.description.strip()
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if not description:
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raise HTTPException(status_code=400, detail="请先描述信号思路")
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if len(description) > 500:
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raise HTTPException(status_code=400, detail="描述过长（最多 500 字）")
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messages = custom_signals_ai.build_messages(description)
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try:
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# max_tokens=None 不传上限: 推理模型思考 token 计入预算, 显式限制
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# 会挤占正文导致 JSON 截断/0 字 (与四个分析器同因, 见 0ee3aa8)
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text = await generate_ai_text(messages, temperature=0.2, max_tokens=None)
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except RuntimeError as e:
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raise HTTPException(status_code=400, detail=str(e)) from e
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except Exception as e:
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raise HTTPException(status_code=400, detail=f"AI 生成失败: {e}") from e
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try:
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return custom_signals_ai.parse_and_validate(text)
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except ValueError as e:
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raise HTTPException(status_code=400, detail=str(e)) from e
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# ── 删除 ───────────────────────────────────────────────
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@router.delete("/{signal_id}")
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def delete_signal(signal_id: str, request: Request):
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if not custom_signals.ID_RE.match(signal_id):
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raise HTTPException(status_code=400, detail="信号 id 非法")
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deleted = custom_signals.delete_one(_data_dir(request), signal_id)
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if not deleted:
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raise HTTPException(status_code=404, detail="信号不存在")
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_invalidate(request)
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return {"ok": True}
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# ── 盘中信号历史回放 ────────────────────────────────────
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@router.post("/intraday/replay")
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def intraday_replay(req: IntradayReplayRequest, request: Request):
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"""用本地历史分钟K回放盘中信号的触发时点。
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只读本地分钟分区, 不消耗盘中数据能力 — 用户可先在历史区间验证信号,
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再决定是否配置到监控/分钟策略。昨收取自本地日K(无昨日数据的日子该特征降级)。
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"""
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from datetime import date, timedelta
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import polars as pl
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from app.strategy.intraday_features import build_feature_frame
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try:
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start = date.fromisoformat(req.start_date)
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end = date.fromisoformat(req.end_date)
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except ValueError as e:
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raise HTTPException(status_code=400, detail=f"日期格式错误: {e}") from e
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if start > end:
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raise HTTPException(status_code=400, detail="start_date 不能晚于 end_date")
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if (end - start).days > 60:
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raise HTTPException(status_code=400, detail="回放区间最长 60 天")
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symbols = [s for s in dict.fromkeys(req.symbols) if s]
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if not symbols:
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raise HTTPException(status_code=400, detail="symbols 不能为空")
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if len(symbols) > 200:
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raise HTTPException(status_code=400, detail="单次回放最多 200 只标的")
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# 信号定义必须存在且为盘中类型
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sig = next(
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(s for s in custom_signals.load_all(_data_dir(request)) if s.get("id") == req.signal_id),
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None,
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)
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if sig is None:
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raise HTTPException(status_code=404, detail="信号不存在")
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if sig.get("timeframe") != custom_signals.TIMEFRAME_INTRADAY:
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raise HTTPException(status_code=400, detail="该信号不是盘中(timeframe=intraday)信号")
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exprs = custom_signals.build_intraday_expressions([sig])
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col = custom_signals.intraday_column_name(sig["id"])
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if col not in exprs:
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raise HTTPException(status_code=400, detail="信号编译失败, 请检查条件字段")
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min_bars = int(sig.get("min_bars", 0) or 0)
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repo = request.app.state.repo
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# 昨收映射: 一次性取区间(含前置 15 天)日K, 按「严格早于当日」取最近收盘
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daily = repo.get_daily_batch(symbols, start - timedelta(days=15), end, columns=["symbol", "date", "close"])
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close_by_sym_date: dict[str, dict[date, float]] = {}
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if not daily.is_empty():
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for row in daily.sort(["symbol", "date"]).iter_rows(named=True):
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close_by_sym_date.setdefault(str(row["symbol"]), {})[row["date"]] = float(row["close"])
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triggers: list[dict] = []
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days_scanned = 0
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bars_scanned = 0
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day = start
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while day <= end:
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minute_df = repo.get_minute_batch(symbols, day, asset_type=req.asset_type)
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if minute_df is not None and not minute_df.is_empty():
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days_scanned += 1
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bars_scanned += minute_df.height
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prev_close = {
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sym: closes_map[max(d for d in closes_map if d < day)]
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for sym, closes_map in close_by_sym_date.items()
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if any(d < day for d in closes_map)
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}
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frame = build_feature_frame(minute_df, prev_close=prev_close)
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if not frame.is_empty():
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evaluated = custom_signals.apply_intraday_edges(frame, {col: exprs[col]}).with_columns(
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pl.int_range(pl.len()).over(["symbol", "date"]).alias("_bar_idx")
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)
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if min_bars > 0:
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evaluated = evaluated.with_columns(
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pl.when(pl.col("_bar_idx") + 1 >= min_bars)
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.then(pl.col(col))
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.otherwise(False)
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.alias(col)
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)
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for row in evaluated.filter(pl.col(col)).sort(["datetime", "symbol"]).iter_rows(named=True):
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triggers.append({
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"date": day.isoformat(),
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"time": str(row["datetime"].time()),
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"symbol": row["symbol"],
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})
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day += timedelta(days=1)
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return {
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"signal_id": req.signal_id,
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"start_date": req.start_date,
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"end_date": req.end_date,
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"symbols": symbols,
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"days_scanned": days_scanned,
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"bars_scanned": bars_scanned,
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"triggers": triggers,
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}
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