feat: 修复报错

python-app/app/market/__init__.py

@@ -0,0 +1,4 @@
+from market.config import load_market_config
+from market.factory import create_provider
+
+__all__ = ["load_market_config", "create_provider"]

python-app/app/market/config.py

@@ -0,0 +1,40 @@
+from __future__ import annotations
+
+import os
+from dataclasses import dataclass
+
+
+@dataclass
+class MarketConfig:
+    channel: str
+    provider: str
+    cmes_token: str
+    futu_host: str
+    futu_port: int
+    futu_is_encrypt: bool | None
+    futu_market: str
+
+
+def load_market_config() -> MarketConfig:
+    channel = os.getenv("MARKET_CHANNEL", "cn").strip().lower()
+    provider = os.getenv("MARKET_PROVIDER", "akshare").strip().lower()
+    cmes_token = os.getenv("CMES_TOKEN", "").strip()
+    futu_host = os.getenv("FUTU_HOST", "127.0.0.1").strip()
+    futu_port = int(os.getenv("FUTU_PORT", "11111").strip())
+    futu_encrypt_raw = os.getenv("FUTU_IS_ENCRYPT", "").strip().lower()
+    if futu_encrypt_raw in {"1", "true", "yes", "y"}:
+        futu_is_encrypt = True
+    elif futu_encrypt_raw in {"0", "false", "no", "n"}:
+        futu_is_encrypt = False
+    else:
+        futu_is_encrypt = None
+    futu_market = os.getenv("FUTU_MARKET", "").strip().lower()
+    return MarketConfig(
+        channel=channel,
+        provider=provider,
+        cmes_token=cmes_token,
+        futu_host=futu_host,
+        futu_port=futu_port,
+        futu_is_encrypt=futu_is_encrypt,
+        futu_market=futu_market,
+    )

python-app/app/market/factory.py

@@ -0,0 +1,29 @@
+from __future__ import annotations
+
+from market.config import MarketConfig
+from market.provider_base import MarketDataProvider
+from market.providers.akshare_provider import AkshareCnProvider
+from market.providers.cmes_provider import CmesCnProvider
+
+
+def create_provider(config: MarketConfig) -> MarketDataProvider:
+    if config.channel == "cn" and config.provider == "akshare":
+        return AkshareCnProvider()
+    if config.channel == "cn" and config.provider == "cmesdata":
+        return CmesCnProvider(token=config.cmes_token)
+    if config.provider == "futu" and config.channel in {"cn", "hk", "us"}:
+        from market.providers.futu_provider import FutuProvider
+
+        return FutuProvider(
+            channel=config.channel,
+            host=config.futu_host,
+            port=config.futu_port,
+            is_encrypt=config.futu_is_encrypt,
+            market=config.futu_market,
+        )
+    if config.channel in {"us", "hk"}:
+        raise RuntimeError(
+            f"channel={config.channel} provider={config.provider} 尚未实现，"
+            "请新增 Provider 后接入 factory。"
+        )
+    raise RuntimeError(f"不支持的通道配置: channel={config.channel}, provider={config.provider}")

python-app/app/market/provider_base.py

@@ -0,0 +1,30 @@
+from __future__ import annotations
+
+from abc import ABC, abstractmethod
+from datetime import datetime
+
+import pandas as pd
+
+
+class MarketDataProvider(ABC):
+    @property
+    @abstractmethod
+    def provider_name(self) -> str:
+        raise NotImplementedError
+
+    @property
+    @abstractmethod
+    def channel(self) -> str:
+        raise NotImplementedError
+
+    @abstractmethod
+    def fetch_spot(self) -> pd.DataFrame:
+        raise NotImplementedError
+
+    @abstractmethod
+    def search_spot(self, query: str, limit: int) -> pd.DataFrame:
+        raise NotImplementedError
+
+    @abstractmethod
+    def fetch_daily_kline(self, code: str, start: datetime, end: datetime) -> pd.DataFrame:
+        raise NotImplementedError

python-app/app/market/providers/__init__.py

@@ -0,0 +1,12 @@
+from market.providers.akshare_provider import AkshareCnProvider
+from market.providers.cmes_provider import CmesCnProvider
+
+__all__ = ["AkshareCnProvider", "CmesCnProvider"]
+
+try:
+    from market.providers.futu_provider import FutuProvider
+
+    __all__.append("FutuProvider")
+except Exception:
+    # Allow non-futu environments to keep using other providers.
+    pass

python-app/app/market/providers/akshare_provider.py

@@ -0,0 +1,63 @@
+from __future__ import annotations
+
+from datetime import datetime
+
+import akshare as ak
+import pandas as pd
+
+from market.provider_base import MarketDataProvider
+
+
+class AkshareCnProvider(MarketDataProvider):
+    @property
+    def provider_name(self) -> str:
+        return "akshare"
+
+    @property
+    def channel(self) -> str:
+        return "cn"
+
+    def fetch_spot(self) -> pd.DataFrame:
+        df = ak.stock_zh_a_spot_em()
+        if df.empty:
+            raise RuntimeError("未获取到 A 股实时行情数据")
+        return df
+
+    def search_spot(self, query: str, limit: int) -> pd.DataFrame:
+        q = query.strip().lower()
+        if not q:
+            return pd.DataFrame()
+
+        df = self.fetch_spot()
+        code = df["代码"].astype(str).str.lower()
+        name = df["名称"].astype(str).str.lower()
+
+        exact = df[(code == q) | (name == q)]
+        if not exact.empty:
+            return exact.head(limit)
+
+        starts = df[code.str.startswith(q) | name.str.startswith(q)]
+        if not starts.empty:
+            return starts.head(limit)
+
+        return df[code.str.contains(q, na=False) | name.str.contains(q, na=False)].head(limit)
+
+    def fetch_daily_kline(self, code: str, start: datetime, end: datetime) -> pd.DataFrame:
+        hist = ak.stock_zh_a_hist(
+            symbol=code,
+            period="daily",
+            start_date=start.strftime("%Y%m%d"),
+            end_date=end.strftime("%Y%m%d"),
+            adjust="qfq",
+        )
+        if hist.empty:
+            raise RuntimeError(f"未获取到 K 线数据: {code}")
+
+        frame = pd.DataFrame(
+            {
+                "date": pd.to_datetime(hist["日期"]),
+                "close": pd.to_numeric(hist["收盘"], errors="coerce"),
+                "volume": pd.to_numeric(hist["成交量"], errors="coerce"),
+            }
+        ).dropna()
+        return frame.sort_values("date").reset_index(drop=True)

python-app/app/market/providers/cmes_provider.py

@@ -0,0 +1,70 @@
+from __future__ import annotations
+
+import importlib
+import os
+from datetime import datetime
+
+import pandas as pd
+
+from market.provider_base import MarketDataProvider
+
+
+class CmesCnProvider(MarketDataProvider):
+    def __init__(self, token: str | None = None) -> None:
+        self._token = token or os.getenv("CMES_TOKEN", "").strip()
+        self._module = importlib.import_module("cmesdata")
+        self._login_once()
+
+    @property
+    def provider_name(self) -> str:
+        return "cmesdata"
+
+    @property
+    def channel(self) -> str:
+        return "cn"
+
+    def _login_once(self) -> None:
+        if not self._token:
+            raise RuntimeError("CMES_TOKEN 未配置，无法使用 cmesdata 通道")
+        self._module.login(self._token)
+
+    @staticmethod
+    def _to_prefixed_code(code: str) -> str:
+        raw = code.strip().upper().replace(".", "")
+        if raw.startswith("SH") or raw.startswith("SZ"):
+            return f"{raw[:2]}.{raw[2:]}"
+        if raw.isdigit() and len(raw) == 6:
+            if raw.startswith(("6", "9")):
+                return f"SH.{raw}"
+            return f"SZ.{raw}"
+        raise RuntimeError("cmesdata 通道仅支持 6 位 A 股代码或 SH./SZ. 前缀代码")
+
+    def fetch_spot(self) -> pd.DataFrame:
+        raise RuntimeError("cmesdata 不支持全市场快照拉取，请通过精确代码查询")
+
+    def search_spot(self, query: str, limit: int) -> pd.DataFrame:
+        _ = limit
+        code = self._to_prefixed_code(query)
+        df = self._module.get_real_hq([code])
+        if df is None or df.empty:
+            raise RuntimeError(f"未获取到实时行情: {code}")
+        return df
+
+    def fetch_daily_kline(self, code: str, start: datetime, end: datetime) -> pd.DataFrame:
+        prefixed = self._to_prefixed_code(code)
+        df = self._module.get_history_data(
+            prefixed,
+            start.strftime("%Y-%m-%d"),
+            end.strftime("%Y-%m-%d"),
+            "D",
+        )
+        if df is None or df.empty:
+            raise RuntimeError(f"未获取到历史 K 线: {prefixed}")
+        frame = pd.DataFrame(
+            {
+                "date": pd.to_datetime(df["时间"]),
+                "close": pd.to_numeric(df["收盘价"], errors="coerce"),
+                "volume": pd.to_numeric(df["成交量"], errors="coerce"),
+            }
+        ).dropna()
+        return frame.sort_values("date").reset_index(drop=True)

python-app/app/market/providers/futu_provider.py

@@ -0,0 +1,207 @@
+from __future__ import annotations
+
+from datetime import datetime
+
+import pandas as pd
+from futu import AuType, KLType, Market, OpenQuoteContext, RET_OK, SecurityType
+
+from market.provider_base import MarketDataProvider
+
+
+class FutuProvider(MarketDataProvider):
+    def __init__(
+        self,
+        channel: str,
+        host: str = "127.0.0.1",
+        port: int = 11111,
+        is_encrypt: bool | None = None,
+        market: str = "",
+    ) -> None:
+        self._channel = channel.strip().lower()
+        self._host = host
+        self._port = int(port)
+        self._is_encrypt = is_encrypt
+        self._market = (market or self._channel).strip().lower()
+        self._ctx = OpenQuoteContext(host=self._host, port=self._port, is_encrypt=self._is_encrypt)
+        self._basicinfo_cache: pd.DataFrame | None = None
+
+    @property
+    def provider_name(self) -> str:
+        return "futu"
+
+    @property
+    def channel(self) -> str:
+        return self._channel
+
+    def __del__(self) -> None:
+        try:
+            self._ctx.close()
+        except Exception:
+            pass
+
+    def _require_market(self) -> Market:
+        if self._market == "cn":
+            return Market.SH
+        if self._market == "hk":
+            return Market.HK
+        if self._market == "us":
+            return Market.US
+        raise RuntimeError(f"不支持的 FUTU_MARKET: {self._market}，可选: cn/hk/us")
+
+    def _normalize_code(self, query: str) -> str:
+        q = query.strip().upper()
+        if not q:
+            return ""
+        if "." in q:
+            return q
+        if self._market == "cn":
+            if q.isdigit() and len(q) == 6:
+                prefix = "SH" if q.startswith(("5", "6", "9")) else "SZ"
+                return f"{prefix}.{q}"
+            return q
+        if self._market == "hk":
+            if q.isdigit():
+                return f"HK.{q.zfill(5)}"
+            return f"HK.{q}"
+        if self._market == "us":
+            return f"US.{q}"
+        return q
+
+    def _snapshot_to_unified(self, df: pd.DataFrame) -> pd.DataFrame:
+        frame = df.copy()
+        if "code" not in frame.columns:
+            raise RuntimeError("Futu 快照返回缺少 code 字段")
+        if "name" not in frame.columns:
+            frame["name"] = ""
+        frame["涨跌额"] = pd.to_numeric(frame.get("last_price"), errors="coerce") - pd.to_numeric(
+            frame.get("prev_close_price"), errors="coerce"
+        )
+        frame["市盈率-动态"] = frame.get("pe_ttm_ratio", frame.get("pe_ratio"))
+        frame["市净率"] = frame.get("pb_ratio")
+        frame["总市值"] = frame.get("total_market_val")
+        frame["流通市值"] = frame.get("circular_market_val")
+        frame["代码"] = frame["code"].astype(str)
+        frame["名称"] = frame["name"]
+        frame["最新价"] = frame.get("last_price")
+        frame["涨跌幅"] = frame.get("change_rate")
+        frame["成交量"] = frame.get("volume")
+        frame["成交额"] = frame.get("turnover")
+        frame["振幅"] = frame.get("amplitude")
+        frame["最高"] = frame.get("high_price")
+        frame["最低"] = frame.get("low_price")
+        frame["今开"] = frame.get("open_price")
+        frame["昨收"] = frame.get("prev_close_price")
+        columns = [
+            "代码",
+            "名称",
+            "最新价",
+            "涨跌幅",
+            "涨跌额",
+            "成交量",
+            "成交额",
+            "振幅",
+            "最高",
+            "最低",
+            "今开",
+            "昨收",
+            "市盈率-动态",
+            "市净率",
+            "总市值",
+            "流通市值",
+        ]
+        return frame[columns]
+
+    def _get_snapshot(self, codes: list[str]) -> pd.DataFrame:
+        ret, data = self._ctx.get_market_snapshot(codes)
+        if ret != RET_OK:
+            raise RuntimeError(f"Futu 获取快照失败: {data}")
+        if data is None or data.empty:
+            return pd.DataFrame()
+        return self._snapshot_to_unified(data)
+
+    def _load_basicinfo(self) -> pd.DataFrame:
+        if self._basicinfo_cache is not None:
+            return self._basicinfo_cache
+        market = self._require_market()
+        ret, data = self._ctx.get_stock_basicinfo(market=market, stock_type=SecurityType.STOCK)
+        if ret != RET_OK:
+            raise RuntimeError(f"Futu 获取股票基础信息失败: {data}")
+        if data is None:
+            self._basicinfo_cache = pd.DataFrame(columns=["code", "name"])
+            return self._basicinfo_cache
+        frame = data.copy()
+        frame["code"] = frame["code"].astype(str)
+        frame["name"] = frame["name"].astype(str)
+        self._basicinfo_cache = frame
+        return frame
+
+    def fetch_spot(self) -> pd.DataFrame:
+        raise RuntimeError("Futu 不支持直接拉取全市场实时快照，请使用 search_spot")
+
+    def search_spot(self, query: str, limit: int) -> pd.DataFrame:
+        q = query.strip()
+        if not q:
+            return pd.DataFrame()
+
+        code = self._normalize_code(q)
+        if code:
+            exact = self._get_snapshot([code])
+            if not exact.empty:
+                return exact.head(limit)
+
+        basic = self._load_basicinfo()
+        q_lower = q.lower()
+        code_col = basic["code"].astype(str)
+        name_col = basic["name"].astype(str)
+        mask = (
+            code_col.str.lower().eq(q_lower)
+            | name_col.str.lower().eq(q_lower)
+            | code_col.str.lower().str.startswith(q_lower)
+            | name_col.str.lower().str.startswith(q_lower)
+            | code_col.str.lower().str.contains(q_lower, na=False)
+            | name_col.str.lower().str.contains(q_lower, na=False)
+        )
+        candidates = basic.loc[mask, "code"].drop_duplicates().head(max(limit * 2, 20)).tolist()
+        if not candidates:
+            return pd.DataFrame()
+        snap = self._get_snapshot(candidates)
+        if snap.empty:
+            return pd.DataFrame()
+        return snap.head(limit)
+
+    def fetch_daily_kline(self, code: str, start: datetime, end: datetime) -> pd.DataFrame:
+        normalized = self._normalize_code(code)
+        page_key = None
+        frames: list[pd.DataFrame] = []
+
+        while True:
+            ret, data, page_key = self._ctx.request_history_kline(
+                normalized,
+                start=start.strftime("%Y-%m-%d"),
+                end=end.strftime("%Y-%m-%d"),
+                ktype=KLType.K_DAY,
+                autype=AuType.QFQ,
+                max_count=1000,
+                page_req_key=page_key,
+            )
+            if ret != RET_OK:
+                raise RuntimeError(f"Futu 获取历史 K 线失败: {data}")
+            if data is not None and not data.empty:
+                frames.append(data.copy())
+            if page_key is None:
+                break
+
+        if not frames:
+            raise RuntimeError(f"未获取到 K 线数据: {normalized}")
+
+        full = pd.concat(frames, ignore_index=True)
+        frame = pd.DataFrame(
+            {
+                "date": pd.to_datetime(full["time_key"]),
+                "close": pd.to_numeric(full["close"], errors="coerce"),
+                "volume": pd.to_numeric(full["volume"], errors="coerce"),
+            }
+        ).dropna()
+        if frame.empty:
+            raise RuntimeError(f"K 线数据为空: {normalized}")
+        return frame.sort_values("date").reset_index(drop=True)

python-app/app/market/service.py

@@ -0,0 +1,164 @@
+from __future__ import annotations
+
+from datetime import datetime, timedelta
+from typing import Any
+from time import time
+
+import pandas as pd
+
+from market.provider_base import MarketDataProvider
+
+
+DISPLAY_FIELDS = [
+    "代码",
+    "名称",
+    "最新价",
+    "涨跌幅",
+    "涨跌额",
+    "成交量",
+    "成交额",
+    "振幅",
+    "最高",
+    "最低",
+    "今开",
+    "昨收",
+    "市盈率-动态",
+    "市净率",
+    "总市值",
+    "流通市值",
+]
+
+
+def _safe(v: Any) -> Any:
+    if v is None:
+        return None
+    if isinstance(v, float) and pd.isna(v):
+        return None
+    return v
+
+
+def build_signals(hist: pd.DataFrame, sma_fast: int, sma_slow: int) -> list[dict[str, Any]]:
+    frame = hist.copy()
+    frame["sma_fast"] = frame["close"].rolling(sma_fast).mean()
+    frame["sma_slow"] = frame["close"].rolling(sma_slow).mean()
+    signals: list[dict[str, Any]] = []
+
+    for i in range(1, len(frame)):
+        prev = frame.iloc[i - 1]
+        curr = frame.iloc[i]
+        if pd.isna(prev["sma_fast"]) or pd.isna(prev["sma_slow"]) or pd.isna(curr["sma_fast"]) or pd.isna(curr["sma_slow"]):
+            continue
+        cross_up = prev["sma_fast"] <= prev["sma_slow"] and curr["sma_fast"] > curr["sma_slow"]
+        cross_down = prev["sma_fast"] >= prev["sma_slow"] and curr["sma_fast"] < curr["sma_slow"]
+        if cross_up:
+            signals.append({"date": curr["date"].strftime("%Y-%m-%d"), "type": "buy", "price": float(curr["close"])})
+        elif cross_down:
+            signals.append({"date": curr["date"].strftime("%Y-%m-%d"), "type": "sell", "price": float(curr["close"])})
+    return signals
+
+
+def resolve_candidates(provider: MarketDataProvider, query: str, limit: int) -> pd.DataFrame:
+    return provider.search_spot(query=query, limit=limit)
+
+
+def _pick_first_candidate(provider: MarketDataProvider, query: str) -> pd.Series:
+    candidates = resolve_candidates(provider, query=query, limit=1)
+    if candidates.empty:
+        raise RuntimeError(f"未找到匹配股票: {query}")
+    row = candidates.iloc[0]
+    code = str(row.get("代码", "")).strip()
+    if not code:
+        raise RuntimeError("行情返回缺少代码字段")
+    return row
+
+
+def _build_info(provider: MarketDataProvider, row: pd.Series) -> dict[str, Any]:
+    code = str(row.get("代码", "")).strip()
+    return {
+        "code": code,
+        "name": str(row.get("名称", "")),
+        "price": _safe(row.get("最新价")),
+        "change_pct": _safe(row.get("涨跌幅")),
+        "change": _safe(row.get("涨跌额")),
+        "volume": _safe(row.get("成交量")),
+        "turnover": _safe(row.get("成交额")),
+        "amplitude": _safe(row.get("振幅")),
+        "high": _safe(row.get("最高")),
+        "low": _safe(row.get("最低")),
+        "open": _safe(row.get("今开")),
+        "prev_close": _safe(row.get("昨收")),
+        "pe": _safe(row.get("市盈率-动态")),
+        "pb": _safe(row.get("市净率")),
+        "market_cap": _safe(row.get("总市值")),
+        "float_market_cap": _safe(row.get("流通市值")),
+        "provider": provider.provider_name,
+        "channel": provider.channel,
+    }
+
+
+def build_realtime_info(provider: MarketDataProvider, query: str) -> dict[str, Any]:
+    row = _pick_first_candidate(provider, query=query)
+    info = _build_info(provider=provider, row=row)
+    now = datetime.now()
+    price = info.get("price")
+    volume = info.get("volume")
+    realtime_point = {
+        "date": now.strftime("%Y-%m-%d"),
+        "close": float(price) if price is not None else None,
+        "volume": float(volume) if volume is not None else 0.0,
+    }
+    return {
+        "info": info,
+        "realtime_point": realtime_point,
+        "source": "realtime",
+        "updated_at": now.strftime("%Y-%m-%d %H:%M:%S"),
+    }
+
+
+_DASHBOARD_CACHE: dict[str, tuple[float, dict[str, Any]]] = {}
+_DASHBOARD_CACHE_TTL_SECONDS = 15.0
+
+
+def build_dashboard(
+    provider: MarketDataProvider,
+    query: str,
+    days: int,
+    sma_fast: int,
+    sma_slow: int,
+) -> dict[str, Any]:
+    if sma_fast >= sma_slow:
+        raise RuntimeError("sma_fast must be less than sma_slow")
+
+    row = _pick_first_candidate(provider, query=query)
+    code = str(row.get("代码", "")).strip()
+    cache_key = "|".join([provider.provider_name, provider.channel, code, str(days), str(sma_fast), str(sma_slow)])
+    now = time()
+    cached = _DASHBOARD_CACHE.get(cache_key)
+    if cached is not None and now - cached[0] <= _DASHBOARD_CACHE_TTL_SECONDS:
+        return cached[1]
+
+    end = datetime.now()
+    lookback_days = max(days + (sma_slow * 3), days + 30)
+    start = end - timedelta(days=lookback_days)
+    hist = provider.fetch_daily_kline(code=code, start=start, end=end).tail(days).reset_index(drop=True)
+    if hist.empty:
+        raise RuntimeError(f"未获取到 K 线数据: {code}")
+
+    signals = build_signals(hist, sma_fast=sma_fast, sma_slow=sma_slow)
+    hist["sma_fast"] = hist["close"].rolling(sma_fast).mean()
+    hist["sma_slow"] = hist["close"].rolling(sma_slow).mean()
+
+    points = [
+        {
+            "date": d.strftime("%Y-%m-%d"),
+            "close": float(c),
+            "sma_fast": _safe(f),
+            "sma_slow": _safe(s),
+            "volume": float(v),
+        }
+        for d, c, f, s, v in zip(hist["date"], hist["close"], hist["sma_fast"], hist["sma_slow"], hist["volume"])
+    ]
+
+    result = {"info": _build_info(provider=provider, row=row), "points": points, "signals": signals}
+    _DASHBOARD_CACHE[cache_key] = (now, result)
+    return result

python-app/app/market/types.py

@@ -0,0 +1,32 @@
+from __future__ import annotations
+
+from dataclasses import dataclass
+from datetime import datetime
+from typing import Any
+
+
+@dataclass
+class SpotRow:
+    code: str
+    name: str
+    price: Any
+    change_pct: Any
+    change: Any
+    volume: Any
+    turnover: Any
+    amplitude: Any
+    high: Any
+    low: Any
+    open: Any
+    prev_close: Any
+    pe: Any
+    pb: Any
+    market_cap: Any
+    float_market_cap: Any
+
+
+@dataclass
+class KlineRow:
+    date: datetime
+    close: float
+    volume: float