migration: preserve ladder and rotation slice

app/backend/bootstrap/container.py

@@ -10,12 +10,12 @@ from backend.features.alerts import AlertService
 from backend.features.review import TradeJournalService
 from backend.features.screener import StrategyTrackingService
 from backend.jobs import InProcessJobRunner, JobRegistry, SQLiteJobRunRepository
-from chart_data_provider import MarketChartClient
 from database import ReviewDatabase
-from ifind_client import IfindHttpClient
 from mentor_agent import MentorSkillRegistry
-from realtime_aggregator import WebRealtimeAggregator
 from screener import ScreenerEngine
+from backend.data.providers.ifind_client import IfindHttpClient
+from backend.data.realtime import WebRealtimeAggregator
+from backend.features.market.charts import MarketChartClient
 
 
 @dataclass(frozen=True)

app/backend/data/__init__.py

@@ -1,4 +1,3 @@
-from .gateway import DataGateway, build_data_gateway
 from .policy import DataPolicyError, DataSourcePolicy
 from .quality import DataQualityError, DataQualityGate, QualityEvidence, QualityReport
 
@@ -12,3 +11,11 @@ __all__ = [
     "QualityReport",
     "build_data_gateway",
 ]
+
+
+def __getattr__(name: str):
+    if name in {"DataGateway", "build_data_gateway"}:
+        from .gateway import DataGateway, build_data_gateway
+
+        return {"DataGateway": DataGateway, "build_data_gateway": build_data_gateway}[name]
+    raise AttributeError(name)

app/backend/data/gateway.py

@@ -8,10 +8,10 @@ from backend.data.contracts import DataUsage
 from backend.data.policy import DataSourcePolicy
 from backend.data.providers import IfindProvider, TushareProvider
 from backend.data.quality import DataQualityGate, QualityEvidence, QualityReport
-from chart_data_provider import EastmoneyChartClient, MarketChartClient
+from backend.data.providers.ifind_client import IfindHttpClient
-from ifind_client import IfindHttpClient
+from backend.data.providers.tushare_client import TushareClient
-from realtime_aggregator import WebRealtimeAggregator
+from backend.data.realtime import WebRealtimeAggregator
-from tushare_client import TushareClient
+from backend.features.market.charts import EastmoneyChartClient, MarketChartClient
 
 
 @dataclass(frozen=True)

app/backend/data/providers/ifind.py

@@ -1,6 +1,6 @@
 from __future__ import annotations
 
-from ifind_client import IfindHttpClient
+from backend.data.providers.ifind_client import IfindHttpClient
 
 
 class IfindProvider:

app/backend/data/providers/ifind_client.py

@@ -0,0 +1,385 @@
+from __future__ import annotations
+
+import copy
+import json
+import threading
+import time
+import urllib.error
+import urllib.request
+from datetime import datetime, timedelta
+from typing import Any
+
+
+class IfindError(RuntimeError):
+    pass
+
+
+class IfindHttpClient:
+    BASE_URL = "https://quantapi.51ifind.com/api/v1"
+    AUTH_ENDPOINT = "get_access_token"
+    AUTH_ERROR_CODES = {-1302, -1303, -1304, -4302, -4303}
+
+    def __init__(
+        self,
+        refresh_token: str = "",
+        access_token: str = "",
+        timeout: int = 15,
+    ) -> None:
+        self.timeout = max(3, int(timeout))
+        self._refresh_token = str(refresh_token or "").strip()
+        self._access_token = str(access_token or "").strip()
+        self._access_expires_at: datetime | None = None
+        self._token_lock = threading.Lock()
+        self._cache_lock = threading.Lock()
+        self._cache: dict[str, dict[str, Any]] = {}
+
+    @property
+    def configured(self) -> bool:
+        return bool(self._refresh_token or self._access_token)
+
+    def set_credentials(self, refresh_token: str, access_token: str = "") -> None:
+        refresh_token = str(refresh_token or "").strip()
+        access_token = str(access_token or "").strip()
+        with self._token_lock:
+            refresh_changed = refresh_token != self._refresh_token
+            self._refresh_token = refresh_token
+            if access_token or refresh_changed:
+                self._access_token = access_token
+                self._access_expires_at = None
+        if refresh_changed:
+            with self._cache_lock:
+                self._cache.clear()
+
+    def status(self) -> dict[str, Any]:
+        return {
+            "configured": self.configured,
+            "access_ready": bool(self._access_token),
+            "access_expires_at": (
+                self._access_expires_at.isoformat(timespec="seconds")
+                if self._access_expires_at
+                else ""
+            ),
+        }
+
+    def test_connection(self) -> dict[str, Any]:
+        payload = self.real_time(
+            "000001.SH",
+            ["open", "high", "low", "latest", "preClose"],
+            cache_ttl=0,
+        )
+        return {
+            "ok": bool(payload),
+            "sample_time": str(payload[0].get("time") or "") if payload else "",
+        }
+
+    def real_time(
+        self,
+        codes: str | list[str],
+        indicators: list[str],
+        cache_ttl: int = 10,
+    ) -> list[dict[str, Any]]:
+        code_text = self._codes(codes)
+        payload = self._request(
+            "real_time_quotation",
+            {"codes": code_text, "indicators": ",".join(indicators)},
+            cache_key=f"rq:{code_text}:{','.join(indicators)}",
+            cache_ttl=cache_ttl,
+        )
+        return self._table_rows(payload)
+
+    def history(
+        self,
+        codes: str | list[str],
+        indicators: list[str],
+        start_date: str,
+        end_date: str,
+        cache_ttl: int = 300,
+    ) -> list[dict[str, Any]]:
+        code_text = self._codes(codes)
+        payload = self._request(
+            "cmd_history_quotation",
+            {
+                "codes": code_text,
+                "indicators": ",".join(indicators),
+                "startdate": self._display_date(start_date),
+                "enddate": self._display_date(end_date),
+                "functionpara": {"CPS": "forward1", "Fill": "Omit"},
+            },
+            cache_key=f"hq:{code_text}:{start_date}:{end_date}:{','.join(indicators)}",
+            cache_ttl=cache_ttl,
+        )
+        return self._table_rows(payload)
+
+    def intraday(
+        self,
+        code: str,
+        start_time: str,
+        end_time: str,
+        cache_ttl: int = 20,
+    ) -> list[dict[str, Any]]:
+        indicators = ["open", "high", "low", "close", "volume", "amount", "avgPrice"]
+        payload = self._request(
+            "high_frequency",
+            {
+                "codes": self._codes(code),
+                "indicators": ",".join(indicators),
+                "starttime": start_time,
+                "endtime": end_time,
+                "functionpara": {
+                    "CPS": "forward1",
+                    "Fill": "Previous",
+                    "Timeformat": "LocalTime",
+                    "Interval": "1",
+                    "Limitstart": "09:30:00",
+                    "Limitend": "15:00:00",
+                },
+            },
+            cache_key=f"hf:{code}:{start_time}:{end_time}",
+            cache_ttl=cache_ttl,
+        )
+        return self._table_rows(payload)
+
+    def snapshots(
+        self,
+        codes: str | list[str],
+        indicators: list[str],
+        start_time: str,
+        end_time: str,
+        cache_ttl: int = 8,
+    ) -> list[dict[str, Any]]:
+        code_text = self._codes(codes)
+        payload = self._request(
+            "snap_shot",
+            {
+                "codes": code_text,
+                "indicators": ",".join(indicators),
+                "starttime": start_time,
+                "endtime": end_time,
+            },
+            cache_key=f"ss:{code_text}:{start_time}:{end_time}:{','.join(indicators)}",
+            cache_ttl=cache_ttl,
+        )
+        return self._table_rows(payload)
+
+    def wencai(self, query: str, search_type: str = "stock", cache_ttl: int = 300) -> list[dict[str, Any]]:
+        normalized = " ".join(str(query or "").split())
+        if not normalized:
+            raise IfindError("问财查询不能为空。")
+        payload = self._request(
+            "smart_stock_picking",
+            {"searchstring": normalized, "searchtype": search_type},
+            cache_key=f"wc:{search_type}:{normalized}",
+            cache_ttl=cache_ttl,
+        )
+        return self._table_rows(payload)
+
+    def report_query(
+        self,
+        codes: str | list[str],
+        begin_date: str,
+        end_date: str,
+        cache_ttl: int = 300,
+    ) -> list[dict[str, Any]]:
+        code_text = self._codes(codes)
+        payload = self._request(
+            "report_query",
+            {
+                "codes": code_text,
+                "beginrDate": self._display_date(begin_date),
+                "endrDate": self._display_date(end_date),
+                "outputpara": (
+                    "reportDate:Y,thscode:Y,secName:Y,ctime:Y,"
+                    "reportTitle:Y,pdfURL:Y,seq:Y"
+                ),
+            },
+            cache_key=f"report:{code_text}:{begin_date}:{end_date}",
+            cache_ttl=cache_ttl,
+        )
+        return self._table_rows(payload)
+
+    def _request(
+        self,
+        endpoint: str,
+        body: dict[str, Any],
+        cache_key: str = "",
+        cache_ttl: int = 0,
+    ) -> dict[str, Any]:
+        if not self.configured:
+            raise IfindError("iFinD 尚未配置。")
+        if cache_key and cache_ttl > 0:
+            cached = self._cached(cache_key, cache_ttl)
+            if cached is not None:
+                return cached
+
+        payload = self._post(endpoint, body, self._ensure_access_token())
+        if self._is_auth_error(payload) and self._refresh_token:
+            self._invalidate_access_token()
+            payload = self._post(endpoint, body, self._ensure_access_token(force=True))
+        self._validate_payload(payload)
+        if cache_key and cache_ttl > 0:
+            with self._cache_lock:
+                self._cache[cache_key] = {
+                    "created_at": time.time(),
+                    "payload": copy.deepcopy(payload),
+                }
+        return payload
+
+    def _ensure_access_token(self, force: bool = False) -> str:
+        with self._token_lock:
+            now = datetime.now().astimezone().replace(tzinfo=None)
+            token_valid = bool(self._access_token) and (
+                self._access_expires_at is None
+                or self._access_expires_at > now + timedelta(minutes=2)
+            )
+            if token_valid and not force:
+                return self._access_token
+            if not self._refresh_token:
+                if self._access_token:
+                    return self._access_token
+                raise IfindError("iFinD Refresh Token 尚未配置。")
+            payload = self._post(self.AUTH_ENDPOINT, {}, "", self._refresh_token)
+            self._validate_payload(payload)
+            data = payload.get("data") or {}
+            token = str(data.get("access_token") or "").strip()
+            if not token:
+                raise IfindError("iFinD 未返回 Access Token。")
+            expires_at = self._parse_datetime(data.get("expired_time"))
+            self._access_token = token
+            self._access_expires_at = expires_at
+            return token
+
+    def _post(
+        self,
+        endpoint: str,
+        body: dict[str, Any],
+        access_token: str,
+        refresh_token: str = "",
+    ) -> dict[str, Any]:
+        headers = {
+            "Accept": "application/json",
+            "Content-Type": "application/json",
+            "User-Agent": "XiaobaiReviewWeb/1.0",
+            "ifindlang": "cn",
+        }
+        if access_token:
+            headers["access_token"] = access_token
+        if refresh_token:
+            headers["refresh_token"] = refresh_token
+        request = urllib.request.Request(
+            f"{self.BASE_URL}/{endpoint}",
+            data=json.dumps(body, ensure_ascii=False, separators=(",", ":")).encode("utf-8"),
+            headers=headers,
+            method="POST",
+        )
+        try:
+            with urllib.request.urlopen(request, timeout=self.timeout) as response:
+                payload = json.loads(response.read().decode("utf-8"))
+        except urllib.error.HTTPError as exc:
+            detail = ""
+            try:
+                detail_payload = json.loads(exc.read().decode("utf-8", errors="replace"))
+                detail = str(detail_payload.get("errmsg") or detail_payload.get("message") or "")
+            except (json.JSONDecodeError, OSError):
+                pass
+            raise IfindError(f"iFinD HTTP {exc.code}{f'：{detail[:160]}' if detail else ''}") from exc
+        except (urllib.error.URLError, TimeoutError, OSError, json.JSONDecodeError) as exc:
+            raise IfindError("iFinD 数据请求失败。") from exc
+        if not isinstance(payload, dict):
+            raise IfindError("iFinD 返回格式不正确。")
+        return payload
+
+    def _cached(self, key: str, ttl: int) -> dict[str, Any] | None:
+        with self._cache_lock:
+            cached = self._cache.get(key)
+            if not cached:
+                return None
+            if time.time() - float(cached.get("created_at") or 0) > ttl:
+                self._cache.pop(key, None)
+                return None
+            return copy.deepcopy(cached["payload"])
+
+    def _invalidate_access_token(self) -> None:
+        with self._token_lock:
+            self._access_token = ""
+            self._access_expires_at = None
+
+    @classmethod
+    def _validate_payload(cls, payload: dict[str, Any]) -> None:
+        try:
+            error_code = int(payload.get("errorcode") or 0)
+        except (TypeError, ValueError):
+            error_code = -1
+        if error_code != 0:
+            message = str(payload.get("errmsg") or "未知错误")
+            raise IfindError(f"iFinD 返回错误：{message[:200]}")
+
+    @classmethod
+    def _is_auth_error(cls, payload: dict[str, Any]) -> bool:
+        try:
+            error_code = int(payload.get("errorcode") or 0)
+        except (TypeError, ValueError):
+            error_code = 0
+        message = str(payload.get("errmsg") or "").casefold()
+        return error_code in cls.AUTH_ERROR_CODES or "token" in message or "鉴权" in message
+
+    @staticmethod
+    def _table_rows(payload: dict[str, Any]) -> list[dict[str, Any]]:
+        tables = payload.get("tables") or []
+        if isinstance(tables, dict):
+            tables = [tables]
+        rows: list[dict[str, Any]] = []
+        for block in tables if isinstance(tables, list) else []:
+            if not isinstance(block, dict):
+                continue
+            table = block.get("table") or {}
+            if not isinstance(table, dict):
+                continue
+            times = block.get("time") or []
+            codes = block.get("thscode") or block.get("thscodes") or []
+            if isinstance(codes, str):
+                codes = [codes]
+            lengths = [len(value) for value in table.values() if isinstance(value, list)]
+            row_count = max(lengths or [len(times) if isinstance(times, list) else 0, 1 if table else 0])
+            for index in range(row_count):
+                row: dict[str, Any] = {}
+                if isinstance(times, list) and index < len(times):
+                    row["time"] = times[index]
+                if codes:
+                    row["thscode"] = codes[index] if index < len(codes) else codes[0]
+                for field, values in table.items():
+                    if isinstance(values, list):
+                        row[field] = values[index] if index < len(values) else None
+                    elif index == 0:
+                        row[field] = values
+                rows.append(row)
+        return rows
+
+    @staticmethod
+    def _codes(codes: str | list[str]) -> str:
+        if isinstance(codes, list):
+            values = [str(code or "").strip().upper() for code in codes]
+        else:
+            values = [part.strip().upper() for part in str(codes or "").split(",")]
+        values = [value for value in values if value]
+        if not values:
+            raise IfindError("iFinD 证券代码不能为空。")
+        if len(values) > 100:
+            raise IfindError("iFinD 单次证券代码过多。")
+        return ",".join(values)
+
+    @staticmethod
+    def _display_date(value: str) -> str:
+        compact = str(value or "").replace("-", "")
+        if len(compact) != 8 or not compact.isdigit():
+            raise IfindError("iFinD 日期格式不正确。")
+        return f"{compact[:4]}-{compact[4:6]}-{compact[6:]}"
+
+    @staticmethod
+    def _parse_datetime(value: Any) -> datetime | None:
+        text = str(value or "").strip()
+        if not text:
+            return None
+        try:
+            return datetime.fromisoformat(text)
+        except ValueError:
+            return None

app/backend/data/providers/tushare.py

@@ -2,7 +2,7 @@ from __future__ import annotations
 
 from collections.abc import Callable
 
-from tushare_client import TushareClient
+from backend.data.providers.tushare_client import TushareClient
 
 
 class TushareProvider:

app/backend/data/realtime.py

@@ -0,0 +1,426 @@
+from __future__ import annotations
+
+import copy
+import http.client
+import json
+import time
+import urllib.error
+import urllib.parse
+import urllib.request
+from concurrent.futures import ThreadPoolExecutor
+from dataclasses import dataclass
+from datetime import datetime
+from threading import Lock
+from typing import Any, ClassVar
+
+
+class RealtimeAggregateError(RuntimeError):
+    pass
+
+
+EASTMONEY_INDEX_URL = "https://push2.eastmoney.com/api/qt/ulist.np/get"
+EASTMONEY_SECTOR_URL = "https://push2.eastmoney.com/api/qt/clist/get"
+TENCENT_INDEX_URL = "https://qt.gtimg.cn/q=sh000001,sz399001,sz399006"
+THS_LIMIT_URL = "https://data.10jqka.com.cn/dataapi/limit_up/limit_up_pool"
+XGB_POOL_URL = "https://flash-api.xuangubao.cn/api/pool/detail"
+BROWSER_USER_AGENT = (
+    "Mozilla/5.0 (Windows NT 10.0; Win64; x64) "
+    "AppleWebKit/537.36 (KHTML, like Gecko) "
+    "Chrome/138.0.0.0 Safari/537.36"
+)
+
+
+@dataclass
+class WebRealtimeAggregator:
+    timeout: int = 8
+    retry_attempts: int = 3
+    retry_delay_seconds: float = 0.2
+    response_cache_ttl_seconds: int = 90
+    _sector_cache: ClassVar[dict[str, Any]] = {}
+    _sector_cache_lock: ClassVar[Lock] = Lock()
+    _response_cache: ClassVar[dict[str, dict[str, Any]]] = {}
+    _response_cache_lock: ClassVar[Lock] = Lock()
+
+    def health_snapshot(self, sector: str = "") -> dict[str, Any]:
+        started = time.perf_counter()
+        sources: dict[str, dict[str, Any]] = {}
+        indices: list[dict[str, Any]] = []
+        sector_payload: dict[str, Any] | None = None
+
+        indices, sources["eastmoney_indices"] = self._capture(self.eastmoney_indices)
+        if sector.strip():
+            sector_payload, sources["eastmoney_sector"] = self._capture(
+                lambda: self.eastmoney_sector(sector)
+            )
+        ths_observation, sources["ths_limit_pool"] = self._capture(self.ths_limit_pool)
+        xgb_observation, sources["xgb_limit_pool"] = self._capture(self.xgb_limit_pool)
+
+        index_times = [int(item.get("quote_time_epoch") or 0) for item in indices or []]
+        now = datetime.now().astimezone()
+        max_skew = 120 if now.hour >= 15 else 15
+        index_consistent = bool(index_times) and max(index_times) - min(index_times) <= max_skew
+        ready = (
+            bool(indices)
+            and len(indices) == 3
+            and index_consistent
+            and (not sector.strip() or bool(sector_payload))
+        )
+        return {
+            "ready": ready,
+            "isolated": True,
+            "generated_at": datetime.now().astimezone().isoformat(timespec="seconds"),
+            "elapsed_ms": round((time.perf_counter() - started) * 1000),
+            "indices": indices or [],
+            "index_consistent": index_consistent,
+            "sector": sector_payload,
+            "sources": sources,
+            "observations": {
+                "ths_limit_pool": ths_observation,
+                "xgb_limit_pool": xgb_observation,
+            },
+            "policy": {
+                "integration": "heaven_realtime_fallback",
+                "max_index_time_skew_seconds": max_skew,
+                "notice": "聚合源仅作为盘中观势的实时指数与板块外显，主行情快照仍由Tushare维护。",
+            },
+        }
+
+    def eastmoney_indices(self) -> list[dict[str, Any]]:
+        try:
+            payload = self._get_json(
+                EASTMONEY_INDEX_URL,
+                {
+                    "secids": "1.000001,0.399001,0.399006",
+                    "fltt": "2",
+                    "invt": "2",
+                    "fields": "f12,f14,f2,f3,f4,f15,f16,f17,f18,f6,f124",
+                },
+                referer="https://quote.eastmoney.com/",
+            )
+        except RealtimeAggregateError:
+            return self.tencent_indices()
+        cache_meta = payload.get("_aggregate_cache") or {}
+        rows = list((payload.get("data") or {}).get("diff") or [])
+        result = []
+        for row in rows:
+            code = str(row.get("f12") or "")
+            if code not in {"000001", "399001", "399006"}:
+                continue
+            epoch = int(_number(row.get("f124")))
+            result.append(
+                {
+                    "code": code,
+                    "name": row.get("f14") or code,
+                    "price": _number(row.get("f2")),
+                    "change": _number(row.get("f3")),
+                    "change_amount": _number(row.get("f4")),
+                    "open": _number(row.get("f17")),
+                    "high": _number(row.get("f15")),
+                    "low": _number(row.get("f16")),
+                    "previous_close": _number(row.get("f18")),
+                    "amount_billion": round(_number(row.get("f6")) / 100000000, 2),
+                    "quote_time_epoch": epoch,
+                    "quote_time": (
+                        datetime.fromtimestamp(epoch).astimezone().isoformat(timespec="seconds")
+                        if epoch else ""
+                    ),
+                    "source": (
+                        "eastmoney_push2_cache" if cache_meta else "eastmoney_push2"
+                    ),
+                    "cache_age_seconds": cache_meta.get("age_seconds", 0),
+                }
+            )
+        if len(result) != 3:
+            raise RealtimeAggregateError(f"Eastmoney returned {len(result)}/3 indices")
+        return result
+
+    def tencent_indices(self) -> list[dict[str, Any]]:
+        raw, cache_age = self._get_text(
+            TENCENT_INDEX_URL,
+            referer="https://gu.qq.com/",
+            encoding="gb18030",
+        )
+        result = []
+        for line in raw.splitlines():
+            if '="' not in line:
+                continue
+            fields = line.split('="', 1)[1].rsplit('";', 1)[0].split("~")
+            if len(fields) < 38:
+                continue
+            code = fields[2]
+            if code not in {"000001", "399001", "399006"}:
+                continue
+            try:
+                quote_time = datetime.strptime(fields[30], "%Y%m%d%H%M%S").astimezone()
+            except ValueError as exc:
+                raise RealtimeAggregateError(
+                    f"Tencent returned invalid quote time for {code}"
+                ) from exc
+            result.append(
+                {
+                    "code": code,
+                    "name": fields[1] or code,
+                    "price": _number(fields[3]),
+                    "change": _number(fields[32]),
+                    "change_amount": _number(fields[31]),
+                    "open": _number(fields[5]),
+                    "high": _number(fields[33]),
+                    "low": _number(fields[34]),
+                    "previous_close": _number(fields[4]),
+                    "amount_billion": round(_number(fields[37]) / 10000, 2),
+                    "quote_time_epoch": int(quote_time.timestamp()),
+                    "quote_time": quote_time.isoformat(timespec="seconds"),
+                    "source": "tencent_qt_cache" if cache_age else "tencent_qt",
+                    "cache_age_seconds": cache_age,
+                }
+            )
+        if len(result) != 3:
+            raise RealtimeAggregateError(f"Tencent returned {len(result)}/3 indices")
+        return result
+
+    def eastmoney_sector(self, query: str) -> dict[str, Any]:
+        target = _normalize_sector(query)
+        candidates = self._eastmoney_sector_catalog()
+        matched = _match_sector(candidates, target)
+        if not matched:
+            raise RealtimeAggregateError(f"Eastmoney sector not found: {query}")
+        epoch = int(_number(matched.get("f124")))
+        return {
+            "code": matched.get("f12") or "",
+            "name": matched.get("f14") or query,
+            "price": _number(matched.get("f2")),
+            "change": _number(matched.get("f3")),
+            "change_amount": _number(matched.get("f4")),
+            "turnover_rate": _number(matched.get("f8")),
+            "up_count": int(_number(matched.get("f104"))),
+            "down_count": int(_number(matched.get("f105"))),
+            "leader": matched.get("f128") or "--",
+            "leader_code": matched.get("f140") or "",
+            "leading_pct": _number(matched.get("f136")),
+            "quote_time_epoch": epoch,
+            "quote_time": (
+                datetime.fromtimestamp(epoch).astimezone().isoformat(timespec="seconds")
+                if epoch else ""
+            ),
+            "source": "eastmoney_push2",
+            "match_query": query,
+        }
+
+    def _eastmoney_sector_catalog(self) -> list[dict[str, Any]]:
+        now = time.time()
+        with self._sector_cache_lock:
+            cached = self._sector_cache.get("eastmoney")
+        if cached and now - float(cached.get("created_at") or 0) < 600:
+            return list(cached.get("rows") or [])
+
+        def load_page(page: int) -> list[dict[str, Any]]:
+            payload = self._get_json(
+                EASTMONEY_SECTOR_URL,
+                {
+                    "pn": str(page),
+                    "pz": "100",
+                    "po": "1",
+                    "np": "1",
+                    "fltt": "2",
+                    "invt": "2",
+                    "fid": "f3",
+                    "fs": "m:90+t:2",
+                    "fields": "f12,f14,f2,f3,f4,f8,f104,f105,f128,f136,f140,f124",
+                },
+                referer="https://quote.eastmoney.com/center/boardlist.html",
+            )
+            return list((payload.get("data") or {}).get("diff") or [])
+
+        with ThreadPoolExecutor(max_workers=5) as executor:
+            pages = list(executor.map(load_page, range(1, 6)))
+        rows = [row for page in pages for row in page]
+        if not rows:
+            raise RealtimeAggregateError("Eastmoney sector catalog is empty")
+        with self._sector_cache_lock:
+            self._sector_cache["eastmoney"] = {"created_at": now, "rows": rows}
+        return rows
+
+    def ths_limit_pool(self) -> dict[str, Any]:
+        payload = self._get_json(
+            THS_LIMIT_URL,
+            {"page": "1", "limit": "3", "field": "199112"},
+            referer="https://data.10jqka.com.cn/limit_up/",
+        )
+        data = payload.get("data") or payload
+        return {
+            "available": True,
+            "keys": sorted(str(key) for key in data.keys()) if isinstance(data, dict) else [],
+            "source": "ths_web_dataapi",
+        }
+
+    def xgb_limit_pool(self) -> dict[str, Any]:
+        payload = self._get_json(
+            XGB_POOL_URL,
+            {"pool_name": "limit_up"},
+            referer="https://xuangubao.cn/",
+        )
+        data = payload.get("data") or {}
+        rows = data if isinstance(data, list) else data.get("pool") or data.get("list") or []
+        return {
+            "available": True,
+            "count": len(rows) if isinstance(rows, list) else 0,
+            "source": "xuangubao_web_api",
+        }
+
+    def _capture(self, operation):
+        started = time.perf_counter()
+        try:
+            value = operation()
+            return value, {
+                "ok": True,
+                "elapsed_ms": round((time.perf_counter() - started) * 1000),
+                "error": "",
+            }
+        except Exception as exc:
+            return None, {
+                "ok": False,
+                "elapsed_ms": round((time.perf_counter() - started) * 1000),
+                "error": str(exc)[:500],
+            }
+
+    def _get_json(
+        self,
+        url: str,
+        params: dict[str, str],
+        referer: str,
+    ) -> dict[str, Any]:
+        request_url = f"{url}?{urllib.parse.urlencode(params)}"
+        last_error: Exception | None = None
+        attempts = max(1, int(self.retry_attempts))
+        for attempt in range(attempts):
+            request = urllib.request.Request(
+                request_url,
+                headers={
+                    "Accept": "application/json,text/plain,*/*",
+                    "Connection": "close",
+                    "Referer": referer,
+                    "User-Agent": BROWSER_USER_AGENT,
+                },
+            )
+            try:
+                with urllib.request.urlopen(request, timeout=self.timeout) as response:
+                    content_type = response.headers.get("Content-Type", "")
+                    raw = response.read().decode("utf-8", errors="replace")
+                if "json" not in content_type.lower() and not raw.lstrip().startswith(("{", "[")):
+                    raise RealtimeAggregateError(
+                        f"non-JSON response: {raw[:120].strip()}"
+                    )
+                payload = json.loads(raw)
+                if not isinstance(payload, dict):
+                    raise RealtimeAggregateError("unexpected response shape")
+                if payload.get("rc") not in (None, 0):
+                    raise RealtimeAggregateError(f"provider rc={payload.get('rc')}")
+                with self._response_cache_lock:
+                    self._response_cache[request_url] = {
+                        "created_at": time.time(),
+                        "payload": copy.deepcopy(payload),
+                    }
+                return payload
+            except (
+                urllib.error.URLError,
+                TimeoutError,
+                ConnectionError,
+                OSError,
+                http.client.HTTPException,
+                json.JSONDecodeError,
+                RealtimeAggregateError,
+            ) as exc:
+                last_error = exc
+                if attempt + 1 < attempts and self.retry_delay_seconds > 0:
+                    time.sleep(self.retry_delay_seconds * (attempt + 1))
+
+        now = time.time()
+        with self._response_cache_lock:
+            cached = self._response_cache.get(request_url)
+        cache_age = now - float((cached or {}).get("created_at") or 0)
+        if cached and cache_age <= self.response_cache_ttl_seconds:
+            payload = copy.deepcopy(cached.get("payload") or {})
+            payload["_aggregate_cache"] = {"age_seconds": round(cache_age, 1)}
+            return payload
+        raise RealtimeAggregateError(f"request failed after {attempts} attempts: {last_error}") from last_error
+
+    def _get_text(
+        self,
+        request_url: str,
+        referer: str,
+        encoding: str = "utf-8",
+    ) -> tuple[str, float]:
+        cache_key = f"text:{request_url}"
+        last_error: Exception | None = None
+        attempts = max(1, int(self.retry_attempts))
+        for attempt in range(attempts):
+            request = urllib.request.Request(
+                request_url,
+                headers={
+                    "Accept": "text/plain,*/*",
+                    "Connection": "close",
+                    "Referer": referer,
+                    "User-Agent": BROWSER_USER_AGENT,
+                },
+            )
+            try:
+                with urllib.request.urlopen(request, timeout=self.timeout) as response:
+                    raw = response.read().decode(encoding, errors="replace")
+                if not raw.strip():
+                    raise RealtimeAggregateError("empty text response")
+                with self._response_cache_lock:
+                    self._response_cache[cache_key] = {
+                        "created_at": time.time(),
+                        "payload": raw,
+                    }
+                return raw, 0
+            except (
+                urllib.error.URLError,
+                TimeoutError,
+                ConnectionError,
+                OSError,
+                http.client.HTTPException,
+                RealtimeAggregateError,
+            ) as exc:
+                last_error = exc
+                if attempt + 1 < attempts and self.retry_delay_seconds > 0:
+                    time.sleep(self.retry_delay_seconds * (attempt + 1))
+
+        now = time.time()
+        with self._response_cache_lock:
+            cached = self._response_cache.get(cache_key)
+        cache_age = now - float((cached or {}).get("created_at") or 0)
+        if cached and cache_age <= self.response_cache_ttl_seconds:
+            return str(cached.get("payload") or ""), round(cache_age, 1)
+        raise RealtimeAggregateError(
+            f"text request failed after {attempts} attempts: {last_error}"
+        ) from last_error
+
+
+def _normalize_sector(value: Any) -> str:
+    text = str(value or "").strip().replace(" ", "")
+    for suffix in ("板块", "概念", "行业", "Ⅱ", "Ⅲ", "(A股)", "（A股）"):
+        text = text.replace(suffix, "")
+    aliases = {"元器件": "元件", "电子元器件": "元件"}
+    return aliases.get(text, text)
+
+
+def _match_sector(rows: list[dict[str, Any]], target: str) -> dict[str, Any] | None:
+    exact = [row for row in rows if _normalize_sector(row.get("f14")) == target]
+    if exact:
+        return min(exact, key=lambda row: len(str(row.get("f14") or "")))
+    fuzzy = [
+        row for row in rows
+        if target and (
+            target in _normalize_sector(row.get("f14"))
+            or _normalize_sector(row.get("f14")) in target
+        )
+    ]
+    return min(fuzzy, key=lambda row: len(_normalize_sector(row.get("f14")))) if fuzzy else None
+
+
+def _number(value: Any, default: float = 0.0) -> float:
+    try:
+        return float(value)
+    except (TypeError, ValueError):
+        return default

app/backend/features/market/__init__.py

@@ -0,0 +1,13 @@
+"""Public market data, search, detail and chart feature."""
+
+from .charts import ChartDataError, EastmoneyChartClient, MarketChartClient
+from .repository import MarketRepositoryMixin
+from .service import MarketServiceMixin
+
+__all__ = [
+    "ChartDataError",
+    "EastmoneyChartClient",
+    "MarketChartClient",
+    "MarketRepositoryMixin",
+    "MarketServiceMixin",
+]

app/backend/features/market/charts.py

@@ -0,0 +1,497 @@
+from __future__ import annotations
+
+import http.client
+import json
+import re
+import time
+import urllib.error
+import urllib.parse
+import urllib.request
+from dataclasses import dataclass
+from datetime import datetime, time as dt_time, timedelta
+from threading import Lock
+from typing import Any, ClassVar
+
+from backend.data.providers.ifind_client import IfindError, IfindHttpClient
+
+
+class ChartDataError(RuntimeError):
+    pass
+
+
+TRENDS_URL = "https://push2delay.eastmoney.com/api/qt/stock/trends2/get"
+BOARD_LIST_URL = "https://push2delay.eastmoney.com/api/qt/clist/get"
+BROWSER_USER_AGENT = (
+    "Mozilla/5.0 (Windows NT 10.0; Win64; x64) "
+    "AppleWebKit/537.36 (KHTML, like Gecko) "
+    "Chrome/138.0.0.0 Safari/537.36"
+)
+INDEX_SECIDS = {
+    "000001.SH": "1.000001",
+    "399001.SZ": "0.399001",
+    "399006.SZ": "0.399006",
+}
+
+
+class MarketChartClient:
+    """Prefer iFinD for display charts and retain Eastmoney as a last resort."""
+
+    def __init__(self, ifind: IfindHttpClient, fallback: "EastmoneyChartClient") -> None:
+        self.ifind = ifind
+        self.fallback = fallback
+
+    def stock_intraday(self, code: str) -> dict[str, Any]:
+        normalized = str(code or "").strip()
+        if not re.fullmatch(r"\d{6}", normalized):
+            raise ChartDataError("Invalid stock code")
+        ifind_code = _stock_market_code(normalized)
+        try:
+            return self._ifind_intraday(ifind_code, "stock", normalized)
+        except (IfindError, ChartDataError):
+            return self.fallback.stock_intraday(normalized)
+
+    def stock_daily(self, code: str, end_date: str, limit: int = 90) -> list[dict[str, Any]]:
+        normalized = str(code or "").strip()
+        if not re.fullmatch(r"\d{6}", normalized):
+            raise ChartDataError("Invalid stock code")
+        return self._ifind_daily(_stock_market_code(normalized), end_date, limit)
+
+    def index_daily(self, identifier: str, end_date: str, limit: int = 90) -> list[dict[str, Any]]:
+        normalized = str(identifier or "").strip().upper()
+        if normalized not in INDEX_SECIDS:
+            raise ChartDataError("Unsupported index")
+        return self._ifind_daily(normalized, end_date, limit)
+
+    def board_daily(self, identifier: str, end_date: str, limit: int = 90) -> list[dict[str, Any]]:
+        normalized = str(identifier or "").strip().upper()
+        if not normalized:
+            raise ChartDataError("Invalid board code")
+        return self._ifind_daily(normalized, end_date, limit)
+
+    def index_intraday(self, identifier: str) -> dict[str, Any]:
+        normalized = str(identifier or "").strip().upper()
+        if normalized not in INDEX_SECIDS:
+            raise ChartDataError("Unsupported index")
+        try:
+            return self._ifind_intraday(normalized, "index", normalized)
+        except (IfindError, ChartDataError):
+            return self.fallback.index_intraday(normalized)
+
+    def board_intraday(self, identifier: str, name: str = "") -> dict[str, Any]:
+        normalized = str(identifier or "").strip().upper()
+        try:
+            return self._ifind_intraday(normalized, "board", normalized, name)
+        except (IfindError, ChartDataError):
+            return self.fallback.board_intraday(normalized, name)
+
+    def _ifind_intraday(
+        self,
+        ifind_code: str,
+        entity_type: str,
+        identifier: str,
+        name: str = "",
+    ) -> dict[str, Any]:
+        if not self.ifind.configured:
+            raise ChartDataError("iFinD is not configured")
+        now = datetime.now().astimezone()
+        rows: list[dict[str, Any]] = []
+        for offset in range(0, 8):
+            candidate = now.date() - timedelta(days=offset)
+            if candidate.weekday() >= 5:
+                continue
+            display_date = candidate.isoformat()
+            rows = self.ifind.intraday(
+                ifind_code,
+                f"{display_date} 09:30:00",
+                f"{display_date} 15:00:00",
+                cache_ttl=20 if offset == 0 else 6 * 60 * 60,
+            )
+            if rows:
+                break
+        points = [point for row in rows if (point := _ifind_point(row))]
+        if not points:
+            raise ChartDataError("No iFinD intraday chart data returned")
+        latest_date = points[-1]["date"]
+        points = [point for point in points if point["date"] == latest_date]
+        previous_close = self._previous_close(ifind_code, latest_date, points[0]["open"])
+        return {
+            "entity_type": entity_type,
+            "identifier": identifier,
+            "name": name,
+            "code": identifier,
+            "trade_date": latest_date,
+            "previous_close": previous_close,
+            "points": points,
+            "source": "ifind",
+        }
+
+    def _ifind_daily(
+        self, ifind_code: str, end_date: str, limit: int
+    ) -> list[dict[str, Any]]:
+        if not self.ifind.configured:
+            raise ChartDataError("iFinD is not configured")
+        compact_end = str(end_date or "").replace("-", "")
+        if not re.fullmatch(r"\d{8}", compact_end):
+            raise ChartDataError("Invalid chart end date")
+        end = datetime.strptime(compact_end, "%Y%m%d")
+        start = (end - timedelta(days=max(190, limit * 3))).strftime("%Y%m%d")
+        try:
+            rows = self.ifind.history(
+                ifind_code,
+                ["open", "high", "low", "close", "volume", "amount"],
+                start,
+                compact_end,
+                cache_ttl=300,
+            )
+        except IfindError as exc:
+            raise ChartDataError("No iFinD daily chart data returned") from exc
+        normalized = []
+        for row in rows:
+            stamp = str(row.get("time") or "").strip()
+            trade_date = stamp[:10]
+            close = _number(row.get("close"))
+            if not re.fullmatch(r"\d{4}-\d{2}-\d{2}", trade_date) or close <= 0:
+                continue
+            normalized.append(
+                {
+                    "trade_date": trade_date,
+                    "open": _number(row.get("open")),
+                    "high": _number(row.get("high")),
+                    "low": _number(row.get("low")),
+                    "close": close,
+                    "volume": _number(row.get("volume")),
+                    "amount_billion": _number(row.get("amount")) / 100_000_000,
+                }
+            )
+        normalized.sort(key=lambda row: row["trade_date"])
+        for index, row in enumerate(normalized):
+            previous = normalized[index - 1]["close"] if index > 0 else 0
+            row["change"] = round((row["close"] / previous - 1) * 100, 4) if previous else 0.0
+
+        market_now = datetime.now().astimezone()
+        today = market_now.strftime("%Y%m%d")
+        market_open = (
+            market_now.weekday() < 5
+            and market_now.time().replace(tzinfo=None) >= dt_time(9, 30)
+        )
+        today_display = market_now.date().isoformat()
+        if normalized and normalized[-1]["trade_date"] == today_display:
+            current_bar = normalized[-1]
+            current_bar_is_valid = (
+                current_bar["open"] > 0
+                and current_bar["high"] >= max(current_bar["open"], current_bar["close"])
+                and 0 < current_bar["low"] <= min(current_bar["open"], current_bar["close"])
+                and (current_bar["volume"] > 0 or current_bar["amount_billion"] > 0)
+            )
+            if not market_open or not current_bar_is_valid:
+                normalized.pop()
+        if compact_end == today and market_open:
+            try:
+                quote_rows = self.ifind.real_time(
+                    ifind_code,
+                    ["open", "high", "low", "latest", "preClose", "volume", "amount"],
+                    cache_ttl=10,
+                )
+                quote = quote_rows[0] if quote_rows else {}
+                latest = _number(quote.get("latest"))
+                previous = _number(quote.get("preClose"))
+                open_price = _number(quote.get("open"))
+                high = _number(quote.get("high"))
+                low = _number(quote.get("low"))
+                volume = _number(quote.get("volume"))
+                amount = _number(quote.get("amount"))
+                quote_date = str(quote.get("time") or "")[:10].replace("-", "")
+                quote_is_current = not quote_date or quote_date == today
+                has_market_activity = volume > 0 or amount > 0
+                if (
+                    latest > 0
+                    and open_price > 0
+                    and high >= max(open_price, latest)
+                    and 0 < low <= min(open_price, latest)
+                    and has_market_activity
+                    and quote_is_current
+                ):
+                    realtime = {
+                        "trade_date": end.strftime("%Y-%m-%d"),
+                        "open": open_price,
+                        "high": high,
+                        "low": low,
+                        "close": latest,
+                        "change": round((latest / previous - 1) * 100, 4) if previous else 0.0,
+                        "volume": volume,
+                        "amount_billion": amount / 100_000_000,
+                        "realtime": True,
+                    }
+                    if normalized and normalized[-1]["trade_date"] == realtime["trade_date"]:
+                        normalized[-1] = realtime
+                    else:
+                        normalized.append(realtime)
+            except IfindError:
+                pass
+        if not normalized:
+            raise ChartDataError("No iFinD daily chart data returned")
+        return normalized[-max(20, min(180, int(limit))):]
+
+    def _previous_close(self, code: str, trade_date: str, fallback: float) -> float:
+        today = datetime.now().astimezone().date().isoformat()
+        if trade_date == today:
+            try:
+                quote = self.ifind.real_time(code, ["preClose"], cache_ttl=20)
+                value = _number((quote[0] if quote else {}).get("preClose"))
+                if value > 0:
+                    return value
+            except IfindError:
+                pass
+        end = datetime.strptime(trade_date, "%Y-%m-%d")
+        try:
+            rows = self.ifind.history(
+                code,
+                ["close"],
+                (end - timedelta(days=12)).strftime("%Y%m%d"),
+                end.strftime("%Y%m%d"),
+                cache_ttl=6 * 60 * 60,
+            )
+            closes = [_number(row.get("close")) for row in rows if _number(row.get("close")) > 0]
+            if len(closes) >= 2:
+                return closes[-2]
+        except IfindError:
+            pass
+        return fallback
+
+
+@dataclass
+class EastmoneyChartClient:
+    """Isolated display-only minute chart source.
+
+    The returned data must not be used by market snapshots, scoring, screening,
+    or divination. Its only consumer is a chart-rendering endpoint.
+    """
+
+    timeout: int = 6
+    cache_ttl_seconds: int = 20
+    retry_attempts: int = 2
+    _cache: ClassVar[dict[str, dict[str, Any]]] = {}
+    _cache_lock: ClassVar[Lock] = Lock()
+    _board_catalog: ClassVar[dict[str, dict[str, str]]] = {}
+    _board_catalog_at: ClassVar[float] = 0.0
+    _board_catalog_lock: ClassVar[Lock] = Lock()
+
+    def stock_intraday(self, code: str) -> dict[str, Any]:
+        normalized = str(code or "").strip()
+        if not re.fullmatch(r"\d{6}", normalized):
+            raise ChartDataError("Invalid stock code")
+        market = "1" if normalized.startswith(("5", "6", "9")) else "0"
+        return self._intraday(f"{market}.{normalized}", "stock", normalized)
+
+    def index_intraday(self, identifier: str) -> dict[str, Any]:
+        normalized = str(identifier or "").strip().upper()
+        secid = INDEX_SECIDS.get(normalized)
+        if not secid:
+            raise ChartDataError("Unsupported index")
+        return self._intraday(secid, "index", normalized)
+
+    def board_intraday(self, identifier: str, name: str = "") -> dict[str, Any]:
+        normalized = str(identifier or "").strip().upper()
+        if re.fullmatch(r"BK\d{4}", normalized):
+            board_code = normalized
+        else:
+            board_code = self._resolve_board_code(name or identifier)
+        return self._intraday(f"90.{board_code}", "board", board_code)
+
+    def _intraday(self, secid: str, entity_type: str, identifier: str) -> dict[str, Any]:
+        cache_key = f"{entity_type}:{identifier}"
+        cached = self._get_cached(cache_key)
+        if cached is not None:
+            return cached
+
+        payload = self._request_json(
+            TRENDS_URL,
+            {
+                "secid": secid,
+                "fields1": "f1,f2,f3,f4,f5,f6,f7,f8,f9,f10,f11,f12,f13",
+                "fields2": "f51,f52,f53,f54,f55,f56,f57,f58",
+                "iscr": "0",
+                "ndays": "1",
+            },
+            "https://quote.eastmoney.com/",
+        )
+        data = payload.get("data") or {}
+        points = [point for raw in data.get("trends") or [] if (point := _parse_trend(raw))]
+        if not points:
+            raise ChartDataError("No intraday chart data returned")
+
+        result = {
+            "entity_type": entity_type,
+            "identifier": identifier,
+            "name": str(data.get("name") or ""),
+            "code": str(data.get("code") or identifier),
+            "trade_date": points[-1]["date"],
+            "previous_close": _number(data.get("preClose")),
+            "points": points,
+        }
+        with self._cache_lock:
+            self._cache[cache_key] = {"created_at": time.time(), "payload": result}
+        return result
+
+    def _get_cached(self, cache_key: str) -> dict[str, Any] | None:
+        with self._cache_lock:
+            cached = self._cache.get(cache_key)
+        if not cached:
+            return None
+        if time.time() - float(cached.get("created_at") or 0) > self.cache_ttl_seconds:
+            with self._cache_lock:
+                self._cache.pop(cache_key, None)
+            return None
+        return dict(cached["payload"])
+
+    def _resolve_board_code(self, name: str) -> str:
+        normalized = _normalize_name(name)
+        if not normalized:
+            raise ChartDataError("Board name is required")
+        catalog = self._load_board_catalog()
+        item = catalog.get(normalized)
+        if not item:
+            raise ChartDataError("No matching chart board")
+        return item["code"]
+
+    def _load_board_catalog(self) -> dict[str, dict[str, str]]:
+        now = time.time()
+        with self._board_catalog_lock:
+            if self._board_catalog and now - self._board_catalog_at < 6 * 60 * 60:
+                return dict(self._board_catalog)
+
+        rows: list[dict[str, Any]] = []
+        for board_type in ("1", "2", "3"):
+            for page in range(1, 6):
+                payload = self._request_json(
+                    BOARD_LIST_URL,
+                    {
+                        "pn": str(page),
+                        "pz": "100",
+                        "po": "1",
+                        "np": "1",
+                        "fltt": "2",
+                        "invt": "2",
+                        "fid": "f3",
+                        "fs": f"m:90+t:{board_type}",
+                        "fields": "f12,f14",
+                    },
+                    "https://quote.eastmoney.com/center/boardlist.html",
+                )
+                page_rows = (payload.get("data") or {}).get("diff") or []
+                rows.extend(page_rows)
+                if len(page_rows) < 100:
+                    break
+
+        catalog: dict[str, dict[str, str]] = {}
+        for row in rows:
+            code = str(row.get("f12") or "").strip().upper()
+            board_name = str(row.get("f14") or "").strip()
+            if re.fullmatch(r"BK\d{4}", code) and board_name:
+                catalog.setdefault(_normalize_name(board_name), {"code": code, "name": board_name})
+        if not catalog:
+            raise ChartDataError("Board chart directory is unavailable")
+        with self._board_catalog_lock:
+            type(self)._board_catalog = catalog
+            type(self)._board_catalog_at = now
+        return dict(catalog)
+
+    def _request_json(
+        self, url: str, params: dict[str, str], referer: str
+    ) -> dict[str, Any]:
+        request_url = f"{url}?{urllib.parse.urlencode(params)}"
+        last_error: Exception | None = None
+        for attempt in range(max(1, int(self.retry_attempts))):
+            request = urllib.request.Request(
+                request_url,
+                headers={
+                    "Accept": "application/json,text/plain,*/*",
+                    "Connection": "close",
+                    "Referer": referer,
+                    "User-Agent": BROWSER_USER_AGENT,
+                },
+            )
+            try:
+                with urllib.request.urlopen(request, timeout=self.timeout) as response:
+                    payload = json.loads(response.read().decode("utf-8"))
+                if not isinstance(payload, dict):
+                    raise ChartDataError("Invalid intraday chart response")
+                return payload
+            except (
+                urllib.error.URLError,
+                TimeoutError,
+                ConnectionError,
+                OSError,
+                http.client.HTTPException,
+                json.JSONDecodeError,
+                ChartDataError,
+            ) as exc:
+                last_error = exc
+                if attempt + 1 < self.retry_attempts:
+                    time.sleep(0.12)
+        raise ChartDataError("Intraday chart request failed") from last_error
+
+
+def _parse_trend(raw: Any) -> dict[str, Any] | None:
+    fields = str(raw or "").split(",")
+    if len(fields) < 8 or " " not in fields[0]:
+        return None
+    stamp = fields[0].strip()
+    trade_date, trade_time = stamp.split(" ", 1)
+    close = _number(fields[2])
+    if close <= 0:
+        return None
+    return {
+        "date": trade_date,
+        "time": trade_time[:5],
+        "open": _number(fields[1]),
+        "close": close,
+        "high": _number(fields[3]),
+        "low": _number(fields[4]),
+        "volume": _number(fields[5]),
+        "amount": _number(fields[6]),
+        "average": _number(fields[7]),
+    }
+
+
+def _ifind_point(row: dict[str, Any]) -> dict[str, Any] | None:
+    stamp = str(row.get("time") or "").strip()
+    if " " not in stamp:
+        return None
+    trade_date, trade_time = stamp.split(" ", 1)
+    close = _number(row.get("close"))
+    if close <= 0:
+        return None
+    return {
+        "date": trade_date,
+        "time": trade_time[:5],
+        "open": _number(row.get("open")),
+        "close": close,
+        "high": _number(row.get("high")),
+        "low": _number(row.get("low")),
+        "volume": _number(row.get("volume")),
+        "amount": _number(row.get("amount")),
+        "average": _number(row.get("avgPrice")),
+    }
+
+
+def _stock_market_code(code: str) -> str:
+    if code.startswith(("4", "8", "9")):
+        suffix = "BJ"
+    elif code.startswith("6"):
+        suffix = "SH"
+    else:
+        suffix = "SZ"
+    return f"{code}.{suffix}"
+
+
+def _number(value: Any) -> float:
+    try:
+        return float(value or 0)
+    except (TypeError, ValueError):
+        return 0.0
+
+
+def _normalize_name(value: Any) -> str:
+    normalized = re.sub(r"[\s·・（）()\-_/]", "", str(value or "")).casefold()
+    return re.sub(r"(?:概念|行业|[ⅠⅡⅢ])$", "", normalized)

app/backend/features/market/repository.py

@@ -0,0 +1,222 @@
+from __future__ import annotations
+
+import json
+from datetime import datetime
+from typing import Any
+
+
+class MarketRepositoryMixin:
+    def get_snapshot(self, trade_date: str) -> dict[str, Any] | None:
+        with self.connect() as connection:
+            row = connection.execute(
+                "SELECT payload FROM dashboard_snapshots WHERE trade_date = ?",
+                (trade_date,),
+            ).fetchone()
+        if not row:
+            return None
+        try:
+            return json.loads(row["payload"])
+        except json.JSONDecodeError:
+            return None
+
+    def get_latest_real_snapshot(
+        self, trade_date: str, strictly_before: bool = False
+    ) -> dict[str, Any] | None:
+        operator = "<" if strictly_before else "<="
+        with self.connect() as connection:
+            row = connection.execute(
+                f"""
+                SELECT payload FROM dashboard_snapshots
+                WHERE trade_date {operator} ? AND source != 'demo'
+                ORDER BY trade_date DESC LIMIT 1
+                """,
+                (trade_date,),
+            ).fetchone()
+        if not row:
+            return None
+        try:
+            return json.loads(row["payload"])
+        except json.JSONDecodeError:
+            return None
+
+    def save_snapshot(self, trade_date: str, source: str, payload: dict[str, Any]) -> None:
+        updated_at = datetime.now().astimezone().isoformat(timespec="seconds")
+        record_count = sum(
+            len(payload.get(key) or [])
+            for key in ("limits", "broken", "down_limits", "yesterday_limits")
+        )
+        content = json.dumps(payload, ensure_ascii=False, separators=(",", ":"))
+        with self.connect() as connection:
+            connection.execute(
+                """
+                INSERT INTO dashboard_snapshots
+                    (trade_date, source, payload, record_count, updated_at)
+                VALUES (?, ?, ?, ?, ?)
+                ON CONFLICT(trade_date) DO UPDATE SET
+                    source = excluded.source,
+                    payload = excluded.payload,
+                    record_count = excluded.record_count,
+                    updated_at = excluded.updated_at
+                """,
+                (trade_date, source, content, record_count, updated_at),
+            )
+
+    def get_data_snapshot(self, kind: str, cache_key: str) -> dict[str, Any] | None:
+        with self.connect() as connection:
+            row = connection.execute(
+                "SELECT payload FROM data_snapshots WHERE kind = ? AND cache_key = ?",
+                (kind, cache_key),
+            ).fetchone()
+        if not row:
+            return None
+        try:
+            return json.loads(row["payload"])
+        except json.JSONDecodeError:
+            return None
+
+    def get_latest_data_snapshot(
+        self,
+        kind: str,
+        cache_key_prefix: str,
+        maximum_cache_key: str,
+        exclude_source: str = "",
+    ) -> dict[str, Any] | None:
+        source_clause = " AND source != ?" if exclude_source else ""
+        parameters: list[Any] = [kind, f"{cache_key_prefix}%", maximum_cache_key]
+        if exclude_source:
+            parameters.append(exclude_source)
+        with self.connect() as connection:
+            row = connection.execute(
+                f"""
+                SELECT payload FROM data_snapshots
+                WHERE kind = ? AND cache_key LIKE ? AND cache_key <= ?{source_clause}
+                ORDER BY cache_key DESC LIMIT 1
+                """,
+                parameters,
+            ).fetchone()
+        if not row:
+            return None
+        try:
+            return json.loads(row["payload"])
+        except json.JSONDecodeError:
+            return None
+
+    def save_data_snapshot(
+        self, kind: str, cache_key: str, source: str, payload: dict[str, Any]
+    ) -> None:
+        updated_at = datetime.now().astimezone().isoformat(timespec="seconds")
+        content = json.dumps(payload, ensure_ascii=False, separators=(",", ":"))
+        with self.connect() as connection:
+            connection.execute(
+                """
+                INSERT INTO data_snapshots (kind, cache_key, source, payload, updated_at)
+                VALUES (?, ?, ?, ?, ?)
+                ON CONFLICT(kind, cache_key) DO UPDATE SET
+                    source = excluded.source,
+                    payload = excluded.payload,
+                    updated_at = excluded.updated_at
+                """,
+                (kind, cache_key, source, content, updated_at),
+            )
+
+    def search_stock_master(self, query: str, limit: int = 12) -> list[dict[str, Any]]:
+        text = str(query or "").strip()
+        if not text:
+            return []
+        escaped = text.replace("\\", "\\\\").replace("%", "\\%").replace("_", "\\_")
+        with self.connect() as connection:
+            rows = connection.execute(
+                """
+                SELECT ts_code, code, name, industry, market, list_date
+                FROM stock_master
+                WHERE code = ? OR name = ? OR name LIKE ? ESCAPE '\\'
+                ORDER BY
+                    CASE WHEN code = ? THEN 0 WHEN name = ? THEN 1 ELSE 2 END,
+                    list_date DESC,
+                    code
+                LIMIT ?
+                """,
+                (text, text, f"%{escaped}%", text, text, max(1, min(30, int(limit)))),
+            ).fetchall()
+        return [dict(row) for row in rows]
+
+    def list_snapshot_payloads(self, end_date: str, limit: int = 260) -> list[dict[str, Any]]:
+        with self.connect() as connection:
+            rows = connection.execute(
+                """
+                SELECT trade_date, payload FROM dashboard_snapshots
+                WHERE trade_date <= ? ORDER BY trade_date DESC LIMIT ?
+                """,
+                (end_date, limit),
+            ).fetchall()
+        result: list[dict[str, Any]] = []
+        for row in reversed(rows):
+            try:
+                payload = json.loads(row["payload"])
+            except json.JSONDecodeError:
+                continue
+            payload["_snapshot_date"] = row["trade_date"]
+            result.append(payload)
+        return result
+
+    def start_sync(self, trade_date: str, source: str) -> int:
+        started_at = datetime.now().astimezone().isoformat(timespec="seconds")
+        with self.connect() as connection:
+            cursor = connection.execute(
+                """
+                INSERT INTO sync_runs (trade_date, source, status, started_at)
+                VALUES (?, ?, 'running', ?)
+                """,
+                (trade_date, source, started_at),
+            )
+            return int(cursor.lastrowid)
+
+    def finish_sync(
+        self,
+        sync_id: int,
+        status: str,
+        record_count: int = 0,
+        message: str = "",
+        source: str | None = None,
+    ) -> None:
+        finished_at = datetime.now().astimezone().isoformat(timespec="seconds")
+        with self.connect() as connection:
+            connection.execute(
+                """
+                UPDATE sync_runs
+                SET status = ?, finished_at = ?, record_count = ?, message = ?,
+                    source = COALESCE(?, source)
+                WHERE id = ?
+                """,
+                (status, finished_at, record_count, message[:1000], source, sync_id),
+            )
+
+    def status(self) -> dict[str, Any]:
+        with self.connect() as connection:
+            last_sync = connection.execute(
+                """
+                SELECT id, trade_date, source, status, started_at, finished_at,
+                       record_count, message
+                FROM sync_runs ORDER BY id DESC LIMIT 1
+                """
+            ).fetchone()
+            snapshot_stats = connection.execute(
+                """
+                SELECT COUNT(*) AS dates, COALESCE(SUM(record_count), 0) AS records,
+                       MAX(updated_at) AS updated_at
+                FROM dashboard_snapshots
+                """
+            ).fetchone()
+            watchlist_count = connection.execute("SELECT COUNT(*) FROM watchlist").fetchone()[0]
+            note_count = connection.execute("SELECT COUNT(*) FROM review_notes").fetchone()[0]
+
+        return {
+            "database": str(self.path.name),
+            "snapshot_dates": int(snapshot_stats["dates"]),
+            "snapshot_records": int(snapshot_stats["records"]),
+            "updated_at": snapshot_stats["updated_at"],
+            "last_sync": dict(last_sync) if last_sync else None,
+            "watchlist_count": int(watchlist_count),
+            "note_count": int(note_count),
+        }
+

app/backend/features/market/service.py

@@ -0,0 +1,949 @@
+from __future__ import annotations
+
+import copy
+import re
+from datetime import date, datetime, time as dt_time, timedelta
+from typing import Any
+
+from backend.bootstrap.config import (
+    normalize_date,
+    tushare_code,
+    validate_stock_code,
+    validate_text,
+)
+from backend.data.providers.ifind_client import IfindError
+from backend.data.providers.tushare_client import TushareClient, TushareError
+from backend.features.market.charts import ChartDataError
+from backend.features.sentiment.engine import SENTIMENT_ENGINE_VERSION
+
+
+SEARCH_INDEXES = (
+    {"id": "000001.SH", "code": "000001.SH", "name": "上证指数", "type": "index", "subtitle": "沪市综合指数"},
+    {"id": "399001.SZ", "code": "399001.SZ", "name": "深证成指", "type": "index", "subtitle": "深市成份指数"},
+    {"id": "399006.SZ", "code": "399006.SZ", "name": "创业板指", "type": "index", "subtitle": "创业板核心指数"},
+)
+SEARCH_TYPE_LABELS = {
+    "stock": "股票",
+    "sector": "板块",
+    "theme": "题材",
+    "index": "指数",
+}
+THS_SEARCH_TYPES = {
+    "I": ("sector", "行业板块"),
+    "R": ("sector", "地域板块"),
+    "N": ("theme", "概念题材"),
+}
+
+
+class MarketServiceMixin:
+    def _tushare_client(self) -> TushareClient:
+        gateway = getattr(self, "data_gateway", None)
+        if gateway is not None:
+            return gateway.tushare()
+        # Compatibility for isolated legacy unit-test service stubs.
+        return TushareClient(self.token)
+
+    def get_dashboard(self, trade_date: str, force: bool = False) -> dict[str, Any]:
+        normalized_date = normalize_date(trade_date)
+        now = datetime.now().astimezone()
+        if (
+            normalized_date == now.strftime("%Y%m%d")
+            and now.time().replace(tzinfo=None) < datetime.strptime("09:15", "%H:%M").time()
+        ):
+            previous = self.database.get_latest_real_snapshot(normalized_date, strictly_before=True)
+            if previous:
+                carried = self._carry_dashboard(previous, normalized_date, "盘前沿用最近交易日收盘行情")
+                return self._apply_reason_overrides(self._with_storage(carried, cached=True))
+        if not force:
+            snapshot = self.database.get_snapshot(normalized_date)
+            if snapshot and str((snapshot.get("meta") or {}).get("source") or "") != "demo":
+                snapshot = copy.deepcopy(snapshot)
+                if normalized_date != now.strftime("%Y%m%d"):
+                    snapshot.setdefault("meta", {}).update(
+                        {"realtime": False, "market_status": "closed"}
+                    )
+                if not self._dashboard_sentiment_ready(snapshot):
+                    snapshot = self._enrich_dashboard_sentiment(snapshot, normalized_date)
+                    self.database.save_snapshot(
+                        normalized_date,
+                        str((snapshot.get("meta") or {}).get("source") or "tushare"),
+                        snapshot,
+                    )
+                snapshot.setdefault("meta", {})["requested_date"] = self._display_compact_date(normalized_date)
+                return self._apply_reason_overrides(self._with_storage(snapshot, cached=True))
+            resolved = self.database.get_data_snapshot(
+                "dashboard_request_v1", normalized_date
+            )
+            if resolved and str((resolved.get("meta") or {}).get("source") or "") != "demo":
+                resolved = copy.deepcopy(resolved)
+                resolved.setdefault("meta", {})["requested_date"] = self._display_compact_date(
+                    normalized_date
+                )
+                return self._apply_reason_overrides(
+                    self._with_storage(resolved, cached=True)
+                )
+            if datetime.strptime(normalized_date, "%Y%m%d").weekday() >= 5:
+                previous = self.database.get_latest_real_snapshot(normalized_date)
+                if previous:
+                    carried = self._carry_dashboard(
+                        previous,
+                        normalized_date,
+                        "非交易日沿用最近交易日收盘行情",
+                    )
+                    self.database.save_data_snapshot(
+                        "dashboard_request_v1", normalized_date, "sqlite", carried
+                    )
+                    return self._apply_reason_overrides(
+                        self._with_storage(carried, cached=True)
+                    )
+        return self.sync_dashboard(normalized_date)
+
+    @staticmethod
+    def _dashboard_sentiment_ready(dashboard: dict[str, Any]) -> bool:
+        overview = dashboard.get("overview") or {}
+        return int(overview.get("sentiment_engine_version") or 0) == SENTIMENT_ENGINE_VERSION and all(
+            key in overview
+            for key in (
+                "sentiment_score",
+                "sentiment_label",
+                "sentiment_phase",
+                "sentiment_direction",
+                "sentiment_components",
+            )
+        )
+
+    @staticmethod
+    def _display_compact_date(compact: str) -> str:
+        return f"{compact[:4]}-{compact[4:6]}-{compact[6:8]}"
+
+    def _carry_dashboard(
+        self, snapshot: dict[str, Any], requested_date: str, reason: str
+    ) -> dict[str, Any]:
+        carried = copy.deepcopy(snapshot)
+        meta = carried.setdefault("meta", {})
+        meta.update(
+            {
+                "requested_date": self._display_compact_date(requested_date),
+                "carried_forward": True,
+                "realtime": False,
+                "market_status": "closed",
+                "notice": reason,
+            }
+        )
+        return carried
+
+    def _realtime_snapshot_due(
+        self,
+        normalized_date: str,
+        snapshot: dict[str, Any],
+    ) -> bool:
+        if not self.configured or normalized_date != date.today().strftime("%Y%m%d"):
+            return False
+        now = datetime.now().astimezone()
+        local_time = now.time().replace(tzinfo=None)
+        realtime_start = datetime.strptime("09:15", "%H:%M").time()
+        morning_end = datetime.strptime("11:35", "%H:%M").time()
+        afternoon_start = datetime.strptime("12:55", "%H:%M").time()
+        realtime_end = datetime.strptime("15:05", "%H:%M").time()
+        in_session = (
+            realtime_start <= local_time < morning_end
+            or afternoon_start <= local_time < realtime_end
+        )
+        if not in_session:
+            return False
+        meta = snapshot.get("meta") or {}
+        snapshot_trade_date = str(meta.get("trade_date") or "").replace("-", "")
+        if snapshot_trade_date and snapshot_trade_date != normalized_date:
+            return False
+        if not meta.get("realtime"):
+            return True
+        try:
+            updated_at = datetime.fromisoformat(str(meta.get("updated_at") or ""))
+            if updated_at.tzinfo is None:
+                updated_at = updated_at.replace(tzinfo=now.tzinfo)
+        except ValueError:
+            return True
+        age_seconds = (now - updated_at.astimezone(now.tzinfo)).total_seconds()
+        return age_seconds >= 8
+
+    def sync_dashboard(self, trade_date: str) -> dict[str, Any]:
+        normalized_date = normalize_date(trade_date)
+        source = "tushare"
+        with self.sync_lock:
+            sync_id = self.database.start_sync(normalized_date, source)
+            try:
+                if not self.configured:
+                    raise TushareError("公共行情尚未配置")
+                dashboard = self._tushare_client().dashboard(normalized_date)
+
+                dashboard["meta"]["source"] = source
+                dashboard["meta"]["requested_date"] = self._display_compact_date(normalized_date)
+                dashboard = self._enrich_dashboard_sentiment(dashboard, normalized_date)
+                record_count = self._record_count(dashboard)
+                actual_date = normalize_date(
+                    str(dashboard.get("meta", {}).get("trade_date") or normalized_date)
+                )
+                self.database.save_snapshot(actual_date, source, dashboard)
+                if actual_date != normalized_date:
+                    dashboard.setdefault("meta", {}).update(
+                        {
+                            "carried_forward": True,
+                            "realtime": False,
+                            "market_status": "closed",
+                        }
+                    )
+                    self.database.save_data_snapshot(
+                        "dashboard_request_v1", normalized_date, source, dashboard
+                    )
+                self.database.finish_sync(
+                    sync_id,
+                    "success",
+                    record_count,
+                    dashboard.get("meta", {}).get("notice", ""),
+                    source,
+                )
+                return self._apply_reason_overrides(self._with_storage(dashboard, cached=False))
+            except TushareError as exc:
+                fallback = self.database.get_latest_real_snapshot(normalized_date)
+                if fallback:
+                    carried = self._carry_dashboard(
+                        fallback, normalized_date, f"最新行情暂不可用，沿用最近收盘快照：{exc}"
+                    )
+                    self.database.finish_sync(
+                        sync_id, "fallback", self._record_count(carried), str(exc), "tushare"
+                    )
+                    return self._apply_reason_overrides(self._with_storage(carried, cached=True))
+                self.database.finish_sync(sync_id, "failed", message=str(exc))
+                raise ValueError("暂无可用的真实行情快照，请等待后台完成首次同步。") from exc
+            except Exception as exc:
+                self.database.finish_sync(sync_id, "failed", message=str(exc))
+                raise
+
+    def realtime_aggregate_health(self, sector: str = "") -> dict[str, Any]:
+        sector = validate_text(sector, "板块名称", 50)
+        return self.realtime_aggregator.health_snapshot(sector)
+
+    def _search_market_directory(self) -> list[dict[str, Any]]:
+        cached = self.database.get_data_snapshot("search_directory", "ths") or {}
+        cached_items = list(cached.get("items") or [])
+        if cached_items and int(cached.get("schema_version") or 0) >= 2:
+            return cached_items
+        if not self.configured:
+            return cached_items
+
+        try:
+            rows = self._tushare_client().query(
+                "ths_index",
+                {},
+                "ts_code,name,count,exchange,list_date,type",
+            )
+        except TushareError:
+            return cached_items
+
+        items = []
+        for row in rows:
+            mapping = THS_SEARCH_TYPES.get(str(row.get("type") or "").upper())
+            code = str(row.get("ts_code") or "").strip().upper()
+            name = str(row.get("name") or "").strip()
+            if not mapping or not code or not name or str(row.get("exchange") or "").upper() != "A":
+                continue
+            entity_type, subtitle = mapping
+            items.append(
+                {
+                    "id": code,
+                    "code": code,
+                    "name": name,
+                    "type": entity_type,
+                    "subtitle": subtitle,
+                    "member_count": int(float(row.get("count") or 0)),
+                }
+            )
+        if items:
+            self.database.save_data_snapshot(
+                "search_directory", "ths", "tushare", {"schema_version": 2, "items": items}
+            )
+        return items
+
+    @staticmethod
+    def _search_match_score(item: dict[str, Any], query: str) -> tuple[int, int, str]:
+        name = str(item.get("name") or "").casefold()
+        code = str(item.get("code") or item.get("id") or "").casefold()
+        needle = query.casefold()
+        if code == needle:
+            rank = 0
+        elif name == needle:
+            rank = 1
+        elif code.startswith(needle):
+            rank = 2
+        elif name.startswith(needle):
+            rank = 3
+        else:
+            rank = 4
+        return rank, len(name), code
+
+    def search_entities(self, query: str, trade_date: str) -> dict[str, Any]:
+        needle = str(query or "").strip()
+        normalized_date = normalize_date(trade_date)
+        groups: dict[str, list[dict[str, Any]]] = {
+            "stocks": [],
+            "sectors": [],
+            "themes": [],
+            "indices": [],
+        }
+        if not needle:
+            return {"query": "", "trade_date": normalized_date, "groups": groups}
+
+        stocks = []
+        for row in self.database.search_stock_master(needle, 12):
+            stocks.append(
+                {
+                    "id": str(row.get("code") or ""),
+                    "code": str(row.get("code") or ""),
+                    "name": str(row.get("name") or "--"),
+                    "type": "stock",
+                    "type_label": SEARCH_TYPE_LABELS["stock"],
+                    "industry": str(row.get("industry") or "其他"),
+                    "market": str(row.get("market") or ""),
+                    "subtitle": " · ".join(
+                        part for part in (str(row.get("industry") or ""), str(row.get("market") or "")) if part
+                    ) or "A股",
+                }
+            )
+        groups["stocks"] = stocks[:8]
+
+        market_items = list(self._search_market_directory()) + [dict(item) for item in SEARCH_INDEXES]
+        matched = [
+            item for item in market_items
+            if needle.casefold() in str(item.get("name") or "").casefold()
+            or needle.casefold() in str(item.get("code") or "").casefold()
+        ]
+        matched.sort(key=lambda item: self._search_match_score(item, needle))
+        group_keys = {"sector": "sectors", "theme": "themes", "index": "indices"}
+        for item in matched:
+            group_key = group_keys.get(str(item.get("type") or ""))
+            if not group_key or len(groups[group_key]) >= 8:
+                continue
+            groups[group_key].append(
+                {
+                    **item,
+                    "type_label": SEARCH_TYPE_LABELS[str(item["type"])],
+                }
+            )
+        return {"query": needle, "trade_date": normalized_date, "groups": groups}
+
+    def get_search_detail(
+        self, entity_type: str, identifier: str, trade_date: str
+    ) -> dict[str, Any]:
+        entity_type = str(entity_type or "").strip().lower()
+        identifier = str(identifier or "").strip().upper()
+        normalized_date = normalize_date(trade_date)
+        if entity_type not in {"sector", "theme", "index"}:
+            raise ValueError("搜索详情类型不支持。")
+        if not re.fullmatch(r"[A-Z0-9.]{3,24}", identifier):
+            raise ValueError("搜索详情标识无效。")
+        if not self.configured:
+            raise ValueError("行情数据源尚未配置。")
+
+        if entity_type == "index":
+            index_basic = next((item for item in SEARCH_INDEXES if item["id"] == identifier), None)
+            if not index_basic:
+                raise ValueError("暂不支持该指数详情。")
+            return self._index_search_detail(index_basic, normalized_date)
+
+        directory = self._search_market_directory()
+        basic = next(
+            (
+                item for item in directory
+                if item.get("id") == identifier and item.get("type") == entity_type
+            ),
+            None,
+        )
+        if not basic:
+            raise ValueError("未找到对应的板块或题材。")
+        return self._ths_search_detail(basic, normalized_date)
+
+    def get_intraday_chart(
+        self, entity_type: str, identifier: str
+    ) -> dict[str, Any]:
+        entity_type = str(entity_type or "").strip().lower()
+        identifier = str(identifier or "").strip().upper()
+        if entity_type == "stock":
+            code = validate_stock_code(identifier)
+            chart = self.chart_data.stock_intraday(code)
+            type_label = SEARCH_TYPE_LABELS["stock"]
+        elif entity_type == "index":
+            basic = next((item for item in SEARCH_INDEXES if item["id"] == identifier), None)
+            if not basic:
+                raise ValueError("暂不支持该指数分时行情。")
+            chart = self.chart_data.index_intraday(identifier)
+            type_label = SEARCH_TYPE_LABELS["index"]
+        elif entity_type in {"sector", "theme"}:
+            basic = next(
+                (
+                    item for item in self._search_market_directory()
+                    if item.get("id") == identifier and item.get("type") == entity_type
+                ),
+                None,
+            )
+            if not basic:
+                raise ValueError("未找到对应的板块或题材。")
+            chart = self.chart_data.board_intraday(identifier, str(basic.get("name") or ""))
+            type_label = SEARCH_TYPE_LABELS[entity_type]
+        else:
+            raise ValueError("分时行情类型不支持。")
+
+        return {
+            "meta": {
+                "trade_date": str(chart.get("trade_date") or ""),
+                "previous_close": float(chart.get("previous_close") or 0),
+            },
+            "entity": {
+                "id": identifier,
+                "code": str(chart.get("code") or identifier),
+                "name": str(chart.get("name") or ""),
+                "type": entity_type,
+                "type_label": type_label,
+            },
+            "points": list(chart.get("points") or []),
+        }
+
+    def _ths_search_detail(
+        self, basic: dict[str, Any], trade_date: str
+    ) -> dict[str, Any]:
+        client = self._tushare_client()
+        resolved_date, _ = client.resolve_trade_context(trade_date)
+        end = datetime.strptime(resolved_date, "%Y%m%d")
+        start_date = (end - timedelta(days=190)).strftime("%Y%m%d")
+        identifier = str(basic["id"])
+        snapshot = client.sector_snapshot(identifier, resolved_date)
+        rows = client.query(
+            "ths_daily",
+            {"ts_code": identifier, "start_date": start_date, "end_date": resolved_date},
+            "ts_code,trade_date,open,high,low,close,pct_change,vol,turnover_rate,total_mv,float_mv",
+        )
+        rows.sort(key=lambda item: str(item.get("trade_date") or ""))
+        series = [
+            {
+                "trade_date": self._display_compact_date(str(row.get("trade_date") or "")),
+                "open": float(row.get("open") or 0),
+                "high": float(row.get("high") or 0),
+                "low": float(row.get("low") or 0),
+                "close": float(row.get("close") or 0),
+                "change": float(row.get("pct_change") or 0),
+                "volume": float(row.get("vol") or 0),
+                "turnover_rate": float(row.get("turnover_rate") or 0),
+            }
+            for row in rows[-90:]
+        ]
+        try:
+            chart_series = self.chart_data.board_daily(identifier, resolved_date, 90)
+            if chart_series:
+                series = chart_series
+        except (AttributeError, ChartDataError):
+            pass
+        latest = series[-1] if series else {}
+        snapshot_is_current = str(snapshot.get("trade_date") or "").replace("-", "") == resolved_date
+        change = float(
+            snapshot.get("change")
+            if snapshot_is_current and snapshot.get("change") is not None
+            else latest.get("change") or 0
+        )
+        if latest.get("realtime"):
+            change = float(latest.get("change") or 0)
+        turnover_rate = float(
+            snapshot.get("turnover_rate")
+            if snapshot_is_current and snapshot.get("turnover_rate") is not None
+            else latest.get("turnover_rate") or 0
+        )
+        metrics = [
+            {"label": "涨跌幅", "value": round(change, 2), "unit": "%", "tone": "change"},
+            {"label": "换手率", "value": round(turnover_rate, 2), "unit": "%"},
+            {"label": "成份数量", "value": int(float(basic.get("member_count") or 0)), "unit": "只"},
+        ]
+        up_count = int(float(snapshot.get("up_count") or 0))
+        down_count = int(float(snapshot.get("down_count") or 0))
+        if up_count or down_count:
+            metrics.extend(
+                [
+                    {"label": "上涨家数", "value": up_count, "unit": "家"},
+                    {"label": "下跌家数", "value": down_count, "unit": "家"},
+                ]
+            )
+        leader = str(snapshot.get("leader") or "").strip()
+        if leader and leader != "--":
+            metrics.extend(
+                [
+                    {"label": "领涨标的", "value": leader, "unit": ""},
+                    {"label": "领涨幅", "value": round(float(snapshot.get("leading_pct") or 0), 2), "unit": "%", "tone": "change"},
+                ]
+            )
+        return {
+            "meta": {
+                "trade_date": self._display_compact_date(resolved_date),
+                "realtime": bool(snapshot.get("realtime")),
+            },
+            "entity": {
+                "id": identifier,
+                "code": identifier,
+                "name": str(snapshot.get("name") or basic.get("name") or "--"),
+                "type": str(basic.get("type") or "sector"),
+                "type_label": SEARCH_TYPE_LABELS[str(basic.get("type") or "sector")],
+                "subtitle": str(basic.get("subtitle") or ""),
+                "value": float(latest.get("close") or 0),
+                "change": change,
+            },
+            "series": series,
+            "metrics": metrics,
+        }
+
+    def _index_search_detail(
+        self, basic: dict[str, Any], trade_date: str
+    ) -> dict[str, Any]:
+        client = self._tushare_client()
+        resolved_date, _ = client.resolve_trade_context(trade_date)
+        payload = (
+            client.realtime_market_indices(resolved_date)
+            if client.should_use_realtime(trade_date, resolved_date)
+            else client.market_indices(resolved_date, 90)
+        )
+        current = next(
+            (item for item in payload.get("indices") or [] if item.get("ts_code") == basic["id"]),
+            None,
+        )
+        if not current:
+            raise ValueError("该指数暂无可用行情。")
+        end = datetime.strptime(resolved_date, "%Y%m%d")
+        rows = client.query(
+            "index_daily",
+            {
+                "ts_code": basic["id"],
+                "start_date": (end - timedelta(days=190)).strftime("%Y%m%d"),
+                "end_date": resolved_date,
+            },
+            "ts_code,trade_date,open,high,low,close,pct_chg,vol,amount",
+        )
+        rows.sort(key=lambda item: str(item.get("trade_date") or ""))
+        series = [
+            {
+                "trade_date": self._display_compact_date(str(row.get("trade_date") or "")),
+                "open": float(row.get("open") or 0),
+                "high": float(row.get("high") or 0),
+                "low": float(row.get("low") or 0),
+                "close": float(row.get("close") or 0),
+                "change": float(row.get("pct_chg") or 0),
+                "volume": float(row.get("vol") or 0),
+            }
+            for row in rows[-90:]
+        ]
+        try:
+            chart_series = self.chart_data.index_daily(str(basic["id"]), resolved_date, 90)
+            if chart_series:
+                series = chart_series
+        except (AttributeError, ChartDataError):
+            pass
+        latest = series[-1] if series else {}
+        latest_close = float(latest.get("close") or current.get("close") or 0)
+        latest_change = float(latest.get("change") or current.get("pct_chg") or 0)
+
+        def series_return(days: int) -> float:
+            if len(series) <= days:
+                return 0.0
+            previous = float(series[-days - 1].get("close") or 0)
+            return (latest_close / previous - 1) * 100 if previous > 0 else 0.0
+        return {
+            "meta": {
+                "trade_date": self._display_compact_date(str(current.get("trade_date") or resolved_date)),
+                "realtime": bool(payload.get("realtime")),
+            },
+            "entity": {
+                **basic,
+                "type_label": SEARCH_TYPE_LABELS["index"],
+                "value": latest_close,
+                "change": latest_change,
+            },
+            "series": series,
+            "metrics": [
+                {"label": "涨跌幅", "value": round(latest_change, 2), "unit": "%", "tone": "change"},
+                {"label": "近5日", "value": round(series_return(5), 2), "unit": "%", "tone": "change"},
+                {"label": "近20日", "value": round(series_return(20), 2), "unit": "%", "tone": "change"},
+                {"label": "成交额", "value": round(float(current.get("amount_billion") or 0), 2), "unit": "亿"},
+            ],
+        }
+
+    def get_stock_detail(
+        self, code: str, trade_date: str, force: bool = False
+    ) -> dict[str, Any]:
+        code = validate_stock_code(code)
+        normalized_date = normalize_date(trade_date)
+        cache_key = f"{code}:{normalized_date}"
+        if not force:
+            cached = self.database.get_data_snapshot("stock_detail", cache_key)
+            if cached and str((cached.get("meta") or {}).get("source") or "") != "demo":
+                if not self._stock_detail_cache_needs_refresh(cached, normalized_date):
+                    cached["meta"] = {**cached.get("meta", {}), "cached": True}
+                    return self._prepare_stock_detail(cached, code, normalized_date)
+
+        name, sector = self._stock_identity(code, normalized_date)
+        source = "tushare"
+        if self.configured:
+            try:
+                payload = self._tushare_client().stock_detail(
+                    tushare_code(code), normalized_date
+                )
+                if not payload.get("prices"):
+                    raise TushareError("No price history returned")
+            except TushareError as exc:
+                payload = self.database.get_latest_data_snapshot(
+                    "stock_detail", f"{code}:", cache_key, exclude_source="demo"
+                )
+                if not payload:
+                    raise ValueError(f"暂无 {code} 的真实行情数据：{exc}") from exc
+                payload = copy.deepcopy(payload)
+                payload["meta"] = {
+                    **payload.get("meta", {}),
+                    "cached": True,
+                    "notice": "最新行情暂不可用，已沿用最近真实收盘数据。",
+                }
+                return self._prepare_stock_detail(payload, code, normalized_date)
+        else:
+            payload = self.database.get_latest_data_snapshot(
+                "stock_detail", f"{code}:", cache_key, exclude_source="demo"
+            )
+            if not payload:
+                raise ValueError(f"暂无 {code} 的真实行情数据，请等待后台完成首次同步。")
+            payload = copy.deepcopy(payload)
+            payload["meta"] = {
+                **payload.get("meta", {}),
+                "cached": True,
+                "notice": "公共行情尚未配置，已沿用最近真实收盘数据。",
+            }
+            return self._prepare_stock_detail(payload, code, normalized_date)
+        payload["meta"]["source"] = source
+        payload["meta"]["cached"] = False
+        self.database.save_data_snapshot("stock_detail", cache_key, source, payload)
+        return self._prepare_stock_detail(payload, code, normalized_date)
+
+    @staticmethod
+    def _stock_detail_bar_date(payload: dict[str, Any]) -> str:
+        prices = list(payload.get("prices") or [])
+        return str((prices[-1] if prices else {}).get("trade_date") or "").replace("-", "")
+
+    def _stock_detail_cache_needs_refresh(
+        self, payload: dict[str, Any], requested_date: str
+    ) -> bool:
+        now = datetime.now().astimezone()
+        return (
+            requested_date == now.strftime("%Y%m%d")
+            and now.time().replace(tzinfo=None) >= dt_time(15, 0)
+            and self._stock_detail_bar_date(payload) < requested_date
+        )
+
+    def _prepare_stock_detail(
+        self, payload: dict[str, Any], code: str, requested_date: str
+    ) -> dict[str, Any]:
+        result = copy.deepcopy(payload)
+        now = datetime.now().astimezone()
+        try:
+            result["prices"] = self.chart_data.stock_daily(code, requested_date, 90)
+            result["meta"] = {**(result.get("meta") or {}), "chart_source": "market_chart"}
+        except (AttributeError, ChartDataError):
+            pass
+        result = self._sanitize_stock_detail_prices(result, now)
+        actual_date = self._stock_detail_bar_date(result)
+        if actual_date:
+            result["meta"] = {
+                **(result.get("meta") or {}),
+                "trade_date": f"{actual_date[:4]}-{actual_date[4:6]}-{actual_date[6:]}",
+            }
+        today = now.strftime("%Y%m%d")
+        should_merge = (
+            requested_date == today
+            and actual_date <= today
+            and now.weekday() < 5
+            and now.time().replace(tzinfo=None) >= dt_time(9, 30)
+        )
+        if should_merge:
+            quote = self._ifind_realtime_stock_quote(code)
+            if quote and self._valid_realtime_stock_quote(quote, today):
+                self._merge_realtime_stock_detail(result, quote, requested_date)
+            elif self.configured and actual_date < today:
+                client = self._tushare_client()
+                try:
+                    resolved_date, _ = client.resolve_trade_context(requested_date)
+                    if resolved_date == today:
+                        quote = client.realtime_stock_quote(tushare_code(code), requested_date)
+                        if self._valid_realtime_stock_quote(quote, today):
+                            self._merge_realtime_stock_detail(result, quote, requested_date)
+                except TushareError:
+                    pass
+        return self._enrich_stock_detail(result)
+
+    @staticmethod
+    def _sanitize_stock_detail_prices(
+        payload: dict[str, Any], market_now: datetime
+    ) -> dict[str, Any]:
+        result = copy.deepcopy(payload)
+        raw_prices = list(result.get("prices") or [])
+        raw_latest_date = str(
+            (raw_prices[-1] if raw_prices else {}).get("trade_date") or ""
+        ).replace("-", "")
+        prices = []
+        for bar in raw_prices:
+            open_price = float(bar.get("open") or 0)
+            high = float(bar.get("high") or 0)
+            low = float(bar.get("low") or 0)
+            close = float(bar.get("close") or 0)
+            if (
+                open_price > 0
+                and high >= max(open_price, close)
+                and 0 < low <= min(open_price, close)
+                and close > 0
+            ):
+                prices.append(bar)
+
+        today = market_now.strftime("%Y%m%d")
+        market_open = (
+            market_now.weekday() < 5
+            and market_now.time().replace(tzinfo=None) >= dt_time(9, 30)
+        )
+        if prices and str(prices[-1].get("trade_date") or "").replace("-", "") == today:
+            current = prices[-1]
+            has_market_activity = (
+                float(current.get("volume") or 0) > 0
+                or float(current.get("amount_billion") or 0) > 0
+            )
+            if not market_open or not has_market_activity:
+                prices.pop()
+
+        if raw_latest_date == today and (
+            not prices
+            or str(prices[-1].get("trade_date") or "").replace("-", "") != today
+        ):
+            result["meta"] = {**(result.get("meta") or {}), "realtime": False}
+
+        result["prices"] = prices
+        if prices:
+            latest = prices[-1]
+            stock = dict(result.get("stock") or {})
+            stock.update(
+                {
+                    "price": float(latest.get("close") or 0),
+                    "change": float(latest.get("change") or 0),
+                    "amount_billion": float(latest.get("amount_billion") or 0),
+                }
+            )
+            result["stock"] = stock
+        return result
+
+    @staticmethod
+    def _valid_realtime_stock_quote(quote: dict[str, Any], trade_date: str) -> bool:
+        price = float(quote.get("price") or 0)
+        open_price = float(quote.get("open") or 0)
+        high = float(quote.get("high") or 0)
+        low = float(quote.get("low") or 0)
+        volume = float(quote.get("volume") or 0)
+        amount = float(quote.get("amount_billion") or 0)
+        quote_date = str(quote.get("quote_time") or "")[:10].replace("-", "")
+        return (
+            price > 0
+            and open_price > 0
+            and high >= max(open_price, price)
+            and 0 < low <= min(open_price, price)
+            and (volume > 0 or amount > 0)
+            and (not quote_date or quote_date == trade_date)
+        )
+
+    def _ifind_realtime_stock_quote(self, code: str) -> dict[str, Any] | None:
+        ifind = getattr(self, "ifind", None)
+        if not ifind or not ifind.configured:
+            return None
+        try:
+            rows = ifind.real_time(
+                tushare_code(code),
+                [
+                    "open", "high", "low", "latest", "preClose",
+                    "volume", "amount", "turnoverRatio",
+                ],
+                cache_ttl=10,
+            )
+        except IfindError:
+            return None
+        row = rows[0] if rows else {}
+        price = float(row.get("latest") or 0)
+        previous_close = float(row.get("preClose") or 0)
+        if price <= 0:
+            return None
+        change = (price / previous_close - 1) * 100 if previous_close > 0 else 0.0
+        stock = self._stock_identity(code, date.today().strftime("%Y%m%d"))
+        return {
+            "name": stock[0],
+            "sector": stock[1],
+            "price": price,
+            "open": float(row.get("open") or price),
+            "high": float(row.get("high") or price),
+            "low": float(row.get("low") or price),
+            "change": round(change, 4),
+            "volume": float(row.get("volume") or 0),
+            "volume_unit": "lots",
+            "amount_billion": float(row.get("amount") or 0) / 100_000_000,
+            "turnover_rate": float(row.get("turnoverRatio") or 0),
+            "quote_time": str(row.get("time") or ""),
+        }
+
+    @staticmethod
+    def _merge_realtime_stock_detail(
+        payload: dict[str, Any], quote: dict[str, Any], trade_date: str
+    ) -> None:
+        display_date = f"{trade_date[:4]}-{trade_date[4:6]}-{trade_date[6:]}"
+        realtime_bar = {
+            "trade_date": display_date,
+            "open": quote["open"],
+            "high": quote["high"],
+            "low": quote["low"],
+            "close": quote["price"],
+            "change": quote["change"],
+            "volume": quote["volume"] if quote.get("volume_unit") == "lots" else quote["volume"] / 100,
+            "amount_billion": quote["amount_billion"],
+            "realtime": True,
+        }
+        prices = list(payload.get("prices") or [])
+        if prices and str(prices[-1].get("trade_date") or "").replace("-", "") == trade_date:
+            prices[-1] = realtime_bar
+        else:
+            prices.append(realtime_bar)
+        payload["prices"] = prices[-90:]
+        stock = dict(payload.get("stock") or {})
+        stock.update(
+            {
+                "name": quote["name"],
+                "industry": quote["sector"],
+                "price": quote["price"],
+                "change": quote["change"],
+                "amount_billion": quote["amount_billion"],
+                "turnover_rate": quote["turnover_rate"],
+            }
+        )
+        payload["stock"] = stock
+        payload["meta"] = {
+            **(payload.get("meta") or {}),
+            "trade_date": display_date,
+            "realtime": True,
+            "updated_at": datetime.now().astimezone().isoformat(timespec="seconds"),
+        }
+
+    def get_stock_preview(
+        self, code: str, trade_date: str, force: bool = False
+    ) -> dict[str, Any]:
+        code = validate_stock_code(code)
+        # Hover previews deliberately follow the latest market day, independent
+        # from the review date selected by the page.
+        detail = self.get_stock_detail(code, date.today().strftime("%Y%m%d"), force)
+        detail_meta = detail.get("meta") or {}
+        resolved_date = str(detail_meta.get("trade_date") or trade_date)
+        intraday_points: list[dict[str, Any]] = []
+        intraday_status = "unavailable"
+        intraday_notice = "分时行情暂不可用。"
+
+        intraday_trade_date = ""
+        intraday_previous_close = 0.0
+        try:
+            intraday = self.chart_data.stock_intraday(code)
+            intraday_points = list(intraday.get("points") or [])
+            intraday_trade_date = str(intraday.get("trade_date") or "")
+            intraday_previous_close = float(intraday.get("previous_close") or 0)
+            if intraday_points:
+                intraday_status = "available"
+                intraday_notice = ""
+            else:
+                intraday_status = "empty"
+                intraday_notice = "最近交易日暂无分时数据。"
+        except ChartDataError:
+            intraday_status = "unavailable"
+            intraday_notice = "分时行情暂不可用，请稍后重试。"
+
+        prices = list(detail.get("prices") or [])[-60:]
+        stock = dict(detail.get("stock") or {"code": code})
+        realtime = bool(detail_meta.get("realtime"))
+        return {
+            "meta": {
+                "trade_date": resolved_date,
+                "source": detail_meta.get("source") or "unavailable",
+                "notice": detail_meta.get("notice") or "",
+                "intraday_status": intraday_status,
+                "intraday_notice": intraday_notice,
+                "intraday_trade_date": intraday_trade_date,
+                "intraday_previous_close": intraday_previous_close,
+                "realtime": realtime,
+                "refresh_interval_seconds": 10 if realtime else 0,
+            },
+            "stock": stock,
+            "prices": prices,
+            "intraday": intraday_points,
+        }
+
+    def backfill(self, start_date: str, end_date: str) -> list[dict[str, Any]]:
+        start = datetime.strptime(normalize_date(start_date), "%Y%m%d").date()
+        end = datetime.strptime(normalize_date(end_date), "%Y%m%d").date()
+        if start > end:
+            raise ValueError("开始日期不能晚于结束日期。")
+        weekdays = []
+        current = start
+        while current <= end:
+            if current.weekday() < 5:
+                weekdays.append(current)
+            current += timedelta(days=1)
+        if len(weekdays) > 15:
+            raise ValueError("单次最多回补 15 个工作日。")
+        results = []
+        for day in weekdays:
+            dashboard = self.sync_dashboard(day.strftime("%Y%m%d"))
+            results.append(
+                {
+                    "requested_date": day.isoformat(),
+                    "trade_date": dashboard["meta"]["trade_date"],
+                    "source": dashboard["meta"]["source"],
+                    "records": self._record_count(dashboard),
+                }
+            )
+        return results
+
+    def _stock_identity(self, code: str, trade_date: str) -> tuple[str, str]:
+        snapshot = self.database.get_snapshot(trade_date) or {}
+        for key in ("limits", "broken", "down_limits"):
+            for row in snapshot.get(key) or []:
+                if str(row.get("code")) == code:
+                    return row.get("name") or "--", row.get("sector") or "其他"
+        for item in self.database.list_watchlist(self.current_user_id):
+            if item["code"] == code:
+                return item["name"], item["sector"] or "其他"
+        return "--", "其他"
+
+    def _enrich_stock_detail(self, payload: dict[str, Any]) -> dict[str, Any]:
+        result = dict(payload)
+        stock = dict(payload.get("stock") or {})
+        code = str(stock.get("code") or "")
+        watched = {
+            item["code"]: item
+            for item in self.database.list_watchlist(self.current_user_id)
+        }
+        stock["watchlist"] = watched.get(code)
+        result["stock"] = stock
+        result["notes"] = self.database.list_notes(self.current_user_id, code=code)
+        return result
+
+    def _with_storage(self, dashboard: dict[str, Any], cached: bool) -> dict[str, Any]:
+        result = dict(dashboard)
+        result["meta"] = {
+            **dashboard.get("meta", {}),
+            "storage": "sqlite",
+            "cached": cached,
+        }
+        return result
+
+    @staticmethod
+    def _record_count(dashboard: dict[str, Any]) -> int:
+        return sum(
+            len(dashboard.get(key) or [])
+            for key in ("limits", "broken", "down_limits", "yesterday_limits")
+        )
+

app/backend/features/pools/__init__.py

@@ -0,0 +1,6 @@
+"""Limit-up, broken-board, limit-down and prior-limit pool feature."""
+
+from .repository import PoolRepositoryMixin
+from .service import PoolServiceMixin
+
+__all__ = ["PoolRepositoryMixin", "PoolServiceMixin"]

app/backend/features/pools/repository.py

@@ -0,0 +1,27 @@
+from __future__ import annotations
+
+from datetime import datetime
+
+
+class PoolRepositoryMixin:
+    def save_reason_override(self, trade_date: str, code: str, reason: str) -> None:
+        now = datetime.now().astimezone().isoformat(timespec="seconds")
+        with self.connect() as connection:
+            connection.execute(
+                """
+                INSERT INTO reason_overrides (trade_date, code, reason, updated_at)
+                VALUES (?, ?, ?, ?)
+                ON CONFLICT(trade_date, code) DO UPDATE SET
+                    reason = excluded.reason,
+                    updated_at = excluded.updated_at
+                """,
+                (trade_date, code, reason, now),
+            )
+
+    def reason_overrides(self, trade_date: str) -> dict[str, str]:
+        with self.connect() as connection:
+            rows = connection.execute(
+                "SELECT code, reason FROM reason_overrides WHERE trade_date = ?",
+                (trade_date,),
+            ).fetchall()
+        return {row["code"]: row["reason"] for row in rows}

app/backend/features/pools/service.py

@@ -0,0 +1,150 @@
+from __future__ import annotations
+
+import re
+from datetime import datetime, time as dt_time
+from typing import Any
+
+from backend.bootstrap.config import normalize_date, validate_stock_code
+from backend.data.providers.ifind_client import IfindError
+
+
+class PoolServiceMixin:
+    def save_reason(self, trade_date: str, code: str, reason: str) -> None:
+        normalized_date = normalize_date(trade_date)
+        code = validate_stock_code(code)
+        reason = reason.strip()
+        if not reason or len(reason) > 200:
+            raise ValueError("涨停原因应为 1 至 200 个字符。")
+        self.database.save_reason_override(normalized_date, code, reason)
+
+    def _apply_reason_overrides(self, dashboard: dict[str, Any]) -> dict[str, Any]:
+        trade_date = str(dashboard.get("meta", {}).get("trade_date", "")).replace("-", "")
+        enrichment = self.database.get_data_snapshot("ifind_event_enrichment_v1", trade_date)
+        if enrichment:
+            self._merge_ifind_event_enrichment(dashboard, enrichment)
+        else:
+            self._schedule_ifind_event_enrichment(trade_date)
+        overrides = self.database.reason_overrides(trade_date)
+        if not overrides:
+            return dashboard
+        for key in ("limits", "broken", "down_limits"):
+            for row in dashboard.get(key) or []:
+                if row.get("code") in overrides:
+                    row["reason"] = overrides[row["code"]]
+                    row["reason_source"] = "manual"
+        return dashboard
+
+    def _schedule_ifind_event_enrichment(self, trade_date: str) -> None:
+        ifind = getattr(self, "ifind", None)
+        if not ifind or not ifind.configured or not re.fullmatch(r"\d{8}", trade_date):
+            return
+        now = datetime.now().astimezone()
+        if trade_date == now.strftime("%Y%m%d") and now.time().replace(tzinfo=None) < dt_time(15, 0):
+            return
+        self.jobs.submit(
+            "market.ifind-event-enrichment",
+            f"{trade_date}:v1",
+            lambda: self._refresh_ifind_event_enrichment(trade_date),
+            {"trade_date": trade_date, "trigger": "dashboard-enrichment"},
+        )
+
+    def _refresh_ifind_event_enrichment(self, trade_date: str) -> None:
+        if not self._ifind_event_lock.acquire(blocking=False):
+            return
+        try:
+            if self.database.get_data_snapshot("ifind_event_enrichment_v1", trade_date):
+                return
+            ifind = getattr(self, "ifind", None)
+            if not ifind or not ifind.configured:
+                return
+            current = datetime.strptime(trade_date, "%Y%m%d")
+            display_date = f"{current.year}年{current.month}月{current.day}日"
+            requests = {
+                "limits": (
+                    f"{display_date}涨停股票，股票代码、股票简称、涨停原因、"
+                    "首次涨停时间、最终涨停时间、开板次数"
+                ),
+                "broken": (
+                    f"{display_date}曾涨停但收盘未涨停的股票，股票代码、股票简称、"
+                    "涨停原因、首次涨停时间、开板次数"
+                ),
+                "down_limits": (
+                    f"{display_date}跌停股票，股票代码、股票简称、跌停原因"
+                ),
+            }
+            result: dict[str, Any] = {
+                "trade_date": trade_date,
+                "generated_at": datetime.now().astimezone().isoformat(timespec="seconds"),
+                "limits": {}, "broken": {}, "down_limits": {}, "partial": False,
+            }
+            for kind, query in requests.items():
+                try:
+                    rows = ifind.wencai(query, "stock", cache_ttl=900)
+                except IfindError:
+                    result["partial"] = True
+                    continue
+                for raw in rows:
+                    code = self._ifind_row_code(raw)
+                    if not code:
+                        continue
+                    reason_tokens = (
+                        ("跌停原因", "风险线索", "原因")
+                        if kind == "down_limits"
+                        else ("涨停原因类别", "涨停原因", "触板逻辑", "原因")
+                    )
+                    reason = str(self._ifind_field(raw, reason_tokens) or "").strip()
+                    first_time = self._normalize_ifind_event_time(
+                        self._ifind_field(raw, ("首次涨停时间", "首次触板时间", "首次封板时间"))
+                    )
+                    last_time = self._normalize_ifind_event_time(
+                        self._ifind_field(raw, ("最终涨停时间", "最后涨停时间", "最后封板时间"))
+                    )
+                    open_times = self._ifind_field(raw, ("开板次数", "打开涨停次数"))
+                    try:
+                        open_count = max(0, int(float(open_times))) if open_times not in (None, "") else None
+                    except (TypeError, ValueError):
+                        open_count = None
+                    result[kind][code] = {
+                        "reason": reason,
+                        "first_time": first_time,
+                        "last_time": last_time,
+                        "open_times": open_count,
+                    }
+            if any(result[kind] for kind in ("limits", "broken", "down_limits")):
+                self.database.save_data_snapshot(
+                    "ifind_event_enrichment_v1", trade_date, "ifind", result
+                )
+        finally:
+            self._ifind_event_lock.release()
+
+    @staticmethod
+    def _normalize_ifind_event_time(value: Any) -> str:
+        text = str(value or "").strip()
+        match = re.search(r"(?:^|\s)(\d{1,2}:\d{2}(?::\d{2})?)(?:$|\s)", text)
+        if not match:
+            match = re.search(r"(?<!\d)(\d{6})(?!\d)", text)
+            if match:
+                compact = match.group(1)
+                return f"{compact[:2]}:{compact[2:4]}:{compact[4:]}"
+            return ""
+        parts = match.group(1).split(":")
+        return ":".join(part.zfill(2) for part in parts)
+
+    @staticmethod
+    def _merge_ifind_event_enrichment(
+        dashboard: dict[str, Any], enrichment: dict[str, Any]
+    ) -> None:
+        for kind in ("limits", "broken", "down_limits"):
+            records = enrichment.get(kind) or {}
+            for row in dashboard.get(kind) or []:
+                event = records.get(str(row.get("code") or "")) or {}
+                reason = str(event.get("reason") or "").strip()
+                if reason:
+                    row["reason"] = reason
+                    row["reason_source"] = "market_event"
+                if event.get("first_time"):
+                    row["first_time"] = event["first_time"]
+                if event.get("last_time"):
+                    row["last_time"] = event["last_time"]
+                if event.get("open_times") is not None:
+                    row["open_times"] = event["open_times"]

app/backend/features/rotation/__init__.py

@@ -0,0 +1,5 @@
+"""Sector rotation history and constituent detail feature."""
+
+from .service import RotationServiceMixin
+
+__all__ = ["RotationServiceMixin"]

app/backend/features/rotation/service.py

@@ -0,0 +1,165 @@
+from __future__ import annotations
+
+from typing import Any
+
+from backend.bootstrap.config import normalize_date, validate_text
+from backend.data.providers.tushare_client import TushareError
+from backend.features.sentiment.engine import (
+    build_sentiment_history,
+    latest_contiguous_history,
+)
+
+
+class RotationServiceMixin:
+    def rotation_history(self, trade_date: str, limit: int = 9) -> dict[str, Any]:
+        normalized_date = normalize_date(trade_date)
+        # 板块轮动固定展示最近 9 个交易日，按由近到远排列。
+        limit = 9
+        snapshots = self.database.list_snapshot_payloads(normalized_date, 240)
+        by_trade_date: dict[str, dict[str, Any]] = {}
+        for snapshot in snapshots:
+            meta = snapshot.get("meta") or {}
+            actual_date = str(meta.get("trade_date") or snapshot.get("_snapshot_date") or "")
+            compact_date = actual_date.replace("-", "")
+            if len(compact_date) == 8:
+                by_trade_date[compact_date] = snapshot
+
+        sentiment_dates = {
+            str(row.get("trade_date") or "").replace("-", "")
+            for row in latest_contiguous_history(build_sentiment_history(snapshots))
+        }
+        ordered_dates = sorted(
+            date_key for date_key in by_trade_date
+            if not sentiment_dates or date_key in sentiment_dates
+        )[-limit:][::-1]
+        rows = []
+        for date_key in ordered_dates:
+            snapshot = by_trade_date[date_key]
+            sector_context = {
+                str(item.get("name") or ""): item
+                for item in snapshot.get("sectors") or []
+            }
+            sectors = []
+            for item in (snapshot.get("sector_rotation") or [])[:12]:
+                name = str(item.get("name") or "").strip()
+                context = sector_context.get(name, {})
+                sectors.append(
+                    {
+                        "name": name,
+                        "rank": int(item.get("rank") or len(sectors) + 1),
+                        "trend": item.get("trend") or "持平",
+                        "count": int(item.get("count") or 0),
+                        "strength": float(item.get("strength") or context.get("strength") or 0),
+                        "change": float(context.get("change") or 0),
+                        "leader": item.get("leader") or context.get("leader") or "--",
+                    }
+                )
+            rows.append(
+                {
+                    "trade_date": f"{date_key[:4]}-{date_key[4:6]}-{date_key[6:]}",
+                    "sectors": sectors,
+                }
+            )
+        return {
+            "trade_date": rows[0]["trade_date"] if rows else normalized_date,
+            "available_days": len(ordered_dates),
+            "requested_days": limit,
+            "rows": rows,
+        }
+
+    def rotation_sector_members(self, trade_date: str, sector_name: str) -> dict[str, Any]:
+        normalized_date = normalize_date(trade_date)
+        sector_name = validate_text(sector_name, "板块名称", 60, required=True)
+        dashboard = self.get_dashboard(normalized_date)
+        actual_date = normalize_date(
+            str((dashboard.get("meta") or {}).get("trade_date") or normalized_date)
+        )
+        cache_key = f"{actual_date}:{sector_name}"
+        cached = self.database.get_data_snapshot("rotation_sector_members_v1", cache_key)
+        if cached:
+            cached["meta"] = {**(cached.get("meta") or {}), "cached": True}
+            return cached
+        if not self.configured:
+            raise ValueError("板块成分数据暂不可用。")
+
+        representative = next(
+            (
+                item for item in dashboard.get("limits") or []
+                if str(item.get("sector") or "").strip() == sector_name
+            ),
+            None,
+        )
+        if not representative:
+            raise ValueError("未找到该板块的代表股票，暂时无法核验成分股。")
+        raw_code = str(representative.get("ts_code") or representative.get("code") or "")
+        if "." in raw_code:
+            ts_code = raw_code
+        elif raw_code.startswith(("4", "8", "92")):
+            ts_code = f"{raw_code}.BJ"
+        elif raw_code.startswith(("6", "68", "90")):
+            ts_code = f"{raw_code}.SH"
+        else:
+            ts_code = f"{raw_code}.SZ"
+        client = self._tushare_client()
+        try:
+            industry = client.sw_stock_industry(ts_code, actual_date)
+            sector_code = str(industry.get("l2_code") or "")
+            members = client.sw_sector_members(sector_code, actual_date)
+        except TushareError as exc:
+            raise ValueError(f"该板块成分股暂不可用：{exc}") from exc
+
+        daily_rows = self.database.daily_bars_for_date(actual_date)
+        if len(daily_rows) < 1000:
+            try:
+                daily_rows = client.query(
+                    "daily",
+                    {"trade_date": actual_date},
+                    "ts_code,trade_date,open,high,low,close,pct_chg,vol,amount",
+                )
+                if daily_rows:
+                    self.database.upsert_daily_bars(daily_rows)
+            except TushareError:
+                daily_rows = self.database.daily_bars_for_date(actual_date)
+        daily_map = {str(item.get("ts_code") or ""): item for item in daily_rows}
+        rows = []
+        for member in members:
+            member_code = str(member.get("ts_code") or "")
+            quote = daily_map.get(member_code) or {}
+            rows.append(
+                {
+                    "code": member_code.split(".")[0],
+                    "ts_code": member_code,
+                    "name": str(member.get("name") or "--"),
+                    "change": quote.get("pct_chg"),
+                    "open": quote.get("open"),
+                    "close": quote.get("close"),
+                    "amount_billion": (
+                        round(float(quote.get("amount") or 0) / 100000, 2)
+                        if quote else None
+                    ),
+                    "quoted": bool(quote),
+                }
+            )
+        rows.sort(
+            key=lambda item: (
+                bool(item.get("quoted")),
+                float(item.get("change") or -999),
+                float(item.get("amount_billion") or 0),
+            ),
+            reverse=True,
+        )
+        result = {
+            "meta": {
+                "trade_date": self._display_compact_date(actual_date),
+                "sector_name": str(industry.get("l2_name") or sector_name),
+                "sector_code": sector_code,
+                "member_count": len(rows),
+                "quoted_count": sum(bool(item.get("quoted")) for item in rows),
+                "cached": False,
+            },
+            "rows": rows,
+        }
+        self.database.save_data_snapshot(
+            "rotation_sector_members_v1", cache_key, "tushare", result
+        )
+        return result

app/backend/features/sentiment/__init__.py

@@ -0,0 +1,19 @@
+"""Market sentiment cycle and history feature."""
+
+from .engine import (
+    COMPONENT_WEIGHTS,
+    SENTIMENT_ENGINE_VERSION,
+    apply_sentiment_to_dashboard,
+    build_sentiment_history,
+    latest_contiguous_history,
+)
+from .service import SentimentServiceMixin
+
+__all__ = [
+    "COMPONENT_WEIGHTS",
+    "SENTIMENT_ENGINE_VERSION",
+    "SentimentServiceMixin",
+    "apply_sentiment_to_dashboard",
+    "build_sentiment_history",
+    "latest_contiguous_history",
+]

app/backend/features/sentiment/engine.py

@@ -0,0 +1,496 @@
+from __future__ import annotations
+
+from copy import deepcopy
+from statistics import mean, median
+from typing import Any
+
+
+COMPONENT_WEIGHTS = {
+    "breadth": 20,
+    "limit_ecology": 25,
+    "profit_effect": 30,
+    "ladder_structure": 15,
+    "liquidity": 10,
+}
+
+SENTIMENT_ENGINE_VERSION = 2
+
+
+def _number(value: Any, default: float = 0.0) -> float:
+    try:
+        number = float(value)
+        return number if number == number else default
+    except (TypeError, ValueError):
+        return default
+
+
+def _clamp(value: float, lower: float = 0.0, upper: float = 100.0) -> float:
+    return min(upper, max(lower, value))
+
+
+def _linear(value: float, low: float, high: float) -> float:
+    if high <= low:
+        return 50.0
+    return _clamp((value - low) / (high - low) * 100)
+
+
+def _percentile(value: float, history: list[float]) -> float:
+    if not history:
+        return 50.0
+    below = sum(item < value for item in history)
+    equal = sum(item == value for item in history)
+    return _clamp((below + equal * 0.5) / len(history) * 100)
+
+
+def _adaptive_score(value: float, fixed: float, history: list[float]) -> float:
+    if len(history) < 20:
+        return fixed
+    return fixed * 0.25 + _percentile(value, history[-250:]) * 0.75
+
+
+def _trade_date(payload: dict[str, Any]) -> str:
+    meta = payload.get("meta") or {}
+    return str(meta.get("trade_date") or payload.get("_snapshot_date") or "").replace("-", "")
+
+
+def _deduplicate_snapshots(snapshots: list[dict[str, Any]]) -> list[dict[str, Any]]:
+    by_trade_date: dict[str, dict[str, Any]] = {}
+    for payload in snapshots:
+        trade_date = _trade_date(payload)
+        if trade_date:
+            by_trade_date[trade_date] = payload
+    return [by_trade_date[key] for key in sorted(by_trade_date)]
+
+
+def _snapshot_stats(payload: dict[str, Any]) -> dict[str, Any]:
+    overview = payload.get("overview") or {}
+    meta = payload.get("meta") or {}
+    limits = list(payload.get("limits") or [])
+    broken = list(payload.get("broken") or [])
+    down_limits = list(payload.get("down_limits") or [])
+    yesterday = list(payload.get("yesterday_limits") or [])
+
+    limit_up = len(limits) if limits else int(_number(overview.get("limit_up_count")))
+    broken_count = len(broken) if broken else int(_number(overview.get("broken_count")))
+    limit_down = len(down_limits) if down_limits else int(_number(overview.get("limit_down_count")))
+    streaks = [max(1, int(_number(row.get("streak"), 1))) for row in limits]
+    first_board = sum(streak == 1 for streak in streaks)
+    second_board = sum(streak == 2 for streak in streaks)
+    three_plus = sum(streak >= 3 for streak in streaks)
+    max_height = max(streaks, default=0)
+    present_levels = set(streaks)
+    ladder_completeness = (
+        sum(level in present_levels for level in range(1, max_height + 1)) / max_height * 100
+        if max_height else 0.0
+    )
+
+    up_count = int(_number(overview.get("up_count")))
+    down_count = int(_number(overview.get("down_count")))
+    flat_count = int(_number(overview.get("flat_count")))
+    active_count = up_count + down_count
+    breadth_ratio = up_count / max(active_count, 1) * 100
+    seal_rate = _number(overview.get("seal_rate"))
+    if not seal_rate and limit_up + broken_count:
+        seal_rate = limit_up / (limit_up + broken_count) * 100
+
+    previous_limit_count = len(yesterday)
+    previous_positive_count = sum(_number(row.get("current_change")) > 0 for row in yesterday)
+    previous_positive_rate = previous_positive_count / max(previous_limit_count, 1) * 100
+    advanced_count = sum(row.get("outcome") == "晋级" for row in yesterday)
+    advance_rate = advanced_count / max(previous_limit_count, 1) * 100
+    average_previous_change = (
+        mean(_number(row.get("current_change")) for row in yesterday) if yesterday else 0.0
+    )
+    median_previous_change = (
+        median(_number(row.get("current_change")) for row in yesterday) if yesterday else 0.0
+    )
+    severe_loss_count = sum(_number(row.get("current_change")) <= -5 for row in yesterday)
+    severe_loss_rate = severe_loss_count / max(previous_limit_count, 1) * 100
+    previous_down_count = sum(row.get("outcome") == "跌停" for row in yesterday)
+    high_previous = [row for row in yesterday if int(_number(row.get("prior_streak"), 1)) >= 2]
+    high_positive_rate = (
+        sum(_number(row.get("current_change")) > 0 for row in high_previous)
+        / max(len(high_previous), 1)
+        * 100
+    )
+
+    amount_billion = _number(overview.get("amount_billion"))
+    limit_amount_billion = sum(_number(row.get("amount_billion")) for row in limits)
+    return {
+        "trade_date": _trade_date(payload),
+        "previous_trade_date": str(meta.get("previous_trade_date") or "").replace("-", ""),
+        "up_count": up_count,
+        "down_count": down_count,
+        "flat_count": flat_count,
+        "breadth_ratio": round(breadth_ratio, 1),
+        "limit_up_count": limit_up,
+        "first_board_count": first_board,
+        "second_board_count": second_board,
+        "three_plus_count": three_plus,
+        "max_height": max_height,
+        "ladder_completeness": round(ladder_completeness, 1),
+        "broken_count": broken_count,
+        "limit_down_count": limit_down,
+        "seal_rate": round(seal_rate, 1),
+        "previous_limit_count": previous_limit_count,
+        "previous_positive_count": previous_positive_count,
+        "previous_positive_rate": round(previous_positive_rate, 1),
+        "advance_rate": round(advance_rate, 1),
+        "average_previous_change": round(average_previous_change, 2),
+        "median_previous_change": round(median_previous_change, 2),
+        "severe_loss_count": severe_loss_count,
+        "severe_loss_rate": round(severe_loss_rate, 1),
+        "previous_down_count": previous_down_count,
+        "high_positive_rate": round(high_positive_rate, 1),
+        "amount_billion": round(amount_billion, 1),
+        "limit_amount_billion": round(limit_amount_billion, 2),
+    }
+
+
+def _sentiment_label(score: float) -> str:
+    if score >= 80:
+        return "情绪高涨"
+    if score >= 60:
+        return "情绪偏强"
+    if score >= 40:
+        return "情绪中性"
+    if score >= 20:
+        return "情绪偏弱"
+    return "情绪冰点"
+
+
+def _phase_signal(score: float, momentum: float, profit_score: float) -> str:
+    if score < 25:
+        return "修复" if momentum > 3 else "冰点"
+    if score < 45:
+        return "修复" if momentum > 3 else "退潮"
+    if score >= 80:
+        return "高潮" if momentum >= -2 and profit_score >= 60 else "分化"
+    if score >= 65:
+        return "分化" if momentum < -3 or profit_score < 50 else "发酵"
+    if momentum < -5:
+        return "退潮"
+    return "发酵" if momentum >= 0 and profit_score >= 45 else "分化"
+
+
+def _confirmed_phase(
+    previous: dict[str, Any] | None,
+    score: float,
+    day_change: float,
+    systemic_health: float,
+    profit_score: float,
+    ecology_score: float,
+    phase_signal: str,
+    extreme_ice: bool,
+    fermentation_signal_count: int,
+) -> tuple[str, str]:
+    if previous is None:
+        return phase_signal, "首个连续交易日，采用原始阶段信号"
+    previous_phase = str(previous.get("phase") or phase_signal)
+    if extreme_ice:
+        return "冰点", "市场宽度与跌停数量触发极端冰点"
+
+    recovery = day_change >= 6 and score >= 25 and systemic_health >= 24
+    fermentation_confirmed = fermentation_signal_count >= 2
+    climax_ready = (
+        score >= 80
+        and profit_score >= 60
+        and systemic_health >= 60
+        and ecology_score >= 70
+    )
+
+    if previous_phase == "冰点":
+        return ("修复", "冰点后首次有效回升") if recovery else ("冰点", "冰点尚未形成有效修复")
+
+    if previous_phase == "退潮":
+        if score < 25:
+            return "冰点", "退潮继续下探至冰点区间"
+        return ("修复", "退潮后出现有效回升") if recovery else ("退潮", "退潮尚未形成有效修复")
+
+    if previous_phase == "修复":
+        if score < 25:
+            return "冰点", "修复失败并重新跌入冰点区间"
+        if day_change <= -6 and score < 45:
+            return "退潮", "修复失败且温度显著回落"
+        if fermentation_confirmed:
+            return "发酵", "发酵条件连续两个交易日成立"
+        return "修复", "修复延续，等待发酵确认"
+
+    if previous_phase == "发酵":
+        if score < 25:
+            return "冰点", "发酵阶段出现极端情绪坍塌"
+        if score < 45 and (day_change < 0 or systemic_health < 35):
+            return "退潮", "发酵阶段温度与系统健康度同步转弱"
+        if climax_ready:
+            return "高潮", "温度、赚钱效应与涨停生态共同达到高潮条件"
+        if phase_signal in {"分化", "退潮"} or day_change <= -6:
+            return "分化", "发酵阶段出现降温或赚钱效应弱化"
+        return "发酵", "发酵状态延续"
+
+    if previous_phase == "高潮":
+        if score < 25:
+            return "冰点", "高潮后出现极端情绪坍塌"
+        if climax_ready:
+            return "高潮", "高潮条件继续成立"
+        if score < 45 or systemic_health < 30:
+            return "退潮", "高潮后风险快速释放"
+        return "分化", "高潮条件消退，进入分化"
+
+    if previous_phase == "分化":
+        if score < 25:
+            return "冰点", "分化继续恶化至冰点区间"
+        if score < 45 or systemic_health < 30:
+            return "退潮", "分化后温度或系统健康度继续下降"
+        if fermentation_confirmed:
+            return "发酵", "分化转强条件连续两个交易日成立"
+        return "分化", "分化延续，等待方向确认"
+
+    return phase_signal, "采用原始阶段信号"
+
+
+def build_sentiment_history(snapshots: list[dict[str, Any]]) -> list[dict[str, Any]]:
+    payloads = _deduplicate_snapshots(snapshots)
+    raw_rows = [_snapshot_stats(payload) for payload in payloads]
+    results: list[dict[str, Any]] = []
+
+    for index, stats in enumerate(raw_rows):
+        previous = raw_rows[:index]
+        limit_history = [float(row["limit_up_count"]) for row in previous]
+        down_limit_history = [float(row["limit_down_count"]) for row in previous]
+        height_history = [float(row["max_height"]) for row in previous]
+        three_plus_history = [float(row["three_plus_count"]) for row in previous]
+        amount_history = [float(row["amount_billion"]) for row in previous[-20:] if row["amount_billion"]]
+
+        breadth_score = _clamp(float(stats["breadth_ratio"]))
+        limit_strength = _adaptive_score(
+            float(stats["limit_up_count"]),
+            _linear(float(stats["limit_up_count"]), 10, 100),
+            limit_history,
+        )
+        down_relief = 100 - _adaptive_score(
+            float(stats["limit_down_count"]),
+            _linear(float(stats["limit_down_count"]), 0, 50),
+            down_limit_history,
+        )
+        seal_quality = _linear(float(stats["seal_rate"]), 35, 90)
+        systemic_health = breadth_score * 0.60 + down_relief * 0.40
+        systemic_gate = 1.0 if systemic_health >= 35 else 0.35 + systemic_health / 35 * 0.65
+        ecology_base_score = limit_strength * 0.35 + seal_quality * 0.35 + down_relief * 0.30
+        # Systemic risk is applied once to the final temperature. Reapplying it here
+        # would count market breadth and limit-down pressure twice.
+        limit_ecology_score = ecology_base_score
+
+        if stats["previous_limit_count"]:
+            positive_score = float(stats["previous_positive_rate"])
+            average_change_score = _clamp(50 + float(stats["average_previous_change"]) * 6)
+            median_change_score = _clamp(50 + float(stats["median_previous_change"]) * 7)
+            advance_score = _clamp(float(stats["advance_rate"]) * 2.5)
+            severe_loss_safety = _clamp(100 - float(stats["severe_loss_rate"]) * 3)
+            down_safety = _clamp(100 - float(stats["previous_down_count"]) / stats["previous_limit_count"] * 700)
+            tail_safety_score = severe_loss_safety * 0.70 + down_safety * 0.30
+            profit_effect_score = (
+                positive_score * 0.30
+                + median_change_score * 0.25
+                + average_change_score * 0.10
+                + advance_score * 0.20
+                + tail_safety_score * 0.15
+            )
+        else:
+            profit_effect_score = 50.0
+
+        max_height_score = _adaptive_score(
+            float(stats["max_height"]),
+            _linear(float(stats["max_height"]), 1, 7),
+            height_history,
+        )
+        continuation_rate = (
+            (float(stats["second_board_count"]) + float(stats["three_plus_count"]))
+            / max(float(stats["limit_up_count"]), 1)
+            * 100
+        )
+        three_plus_density = float(stats["three_plus_count"]) / max(float(stats["limit_up_count"]), 1) * 100
+        three_plus_score = _adaptive_score(
+            float(stats["three_plus_count"]),
+            _clamp(three_plus_density * 5),
+            three_plus_history,
+        )
+        ladder_structure_score = (
+            max_height_score * 0.30
+            + _clamp(continuation_rate * 3) * 0.25
+            + three_plus_score * 0.25
+            + float(stats["ladder_completeness"]) * 0.20
+        )
+
+        amount_baseline = mean(amount_history) if amount_history else float(stats["amount_billion"] or 1)
+        amount_ratio = float(stats["amount_billion"]) / max(amount_baseline, 1)
+        amount_score = _clamp(50 + (amount_ratio - 1) * 100)
+        limit_amount_share = float(stats["limit_amount_billion"]) / max(float(stats["amount_billion"]), 1) * 100
+        liquidity_score = amount_score * 0.70 + _clamp(limit_amount_share * 20) * 0.30
+
+        component_scores = {
+            "breadth": breadth_score,
+            "limit_ecology": limit_ecology_score,
+            "profit_effect": profit_effect_score,
+            "ladder_structure": ladder_structure_score,
+            "liquidity": liquidity_score,
+        }
+        raw_score = sum(component_scores[key] * weight / 100 for key, weight in COMPONENT_WEIGHTS.items())
+        score = round(
+            raw_score * systemic_gate
+        )
+        extreme_ice = float(stats["breadth_ratio"]) <= 15 and float(stats["limit_down_count"]) >= 100
+        if extreme_ice:
+            score = min(score, 15)
+        elif float(stats["breadth_ratio"]) <= 25 and float(stats["limit_down_count"]) >= 50:
+            score = min(score, 24)
+        previous_scores: list[float] = []
+        expected_date = str(stats.get("previous_trade_date") or "")
+        for prior_result in reversed(results):
+            if not expected_date or str(prior_result.get("trade_date") or "") != expected_date:
+                break
+            previous_scores.append(float(prior_result["score"]))
+            expected_date = str(prior_result.get("previous_trade_date") or "")
+            if len(previous_scores) == 3:
+                break
+        momentum = score - mean(previous_scores) if previous_scores else 0.0
+        direction = "升温" if momentum > 3 else "降温" if momentum < -3 else "持平"
+        normalization = "历史百分位" if len(previous) >= 20 else "固定锚点"
+        previous_result = (
+            results[-1]
+            if results and str(stats.get("previous_trade_date") or "") == str(results[-1].get("trade_date") or "")
+            else None
+        )
+        day_change = score - float(previous_result["score"]) if previous_result else 0.0
+        ema_score = round(
+            score if not previous_result
+            else score * 0.5 + float(previous_result.get("ema_score", previous_result["score"])) * 0.5,
+            1,
+        )
+        phase_signal = _phase_signal(score, momentum, profit_effect_score)
+        fermentation_ready = (
+            phase_signal == "发酵"
+            and score >= 45
+            and profit_effect_score >= 45
+            and systemic_health >= 35
+            and not extreme_ice
+        )
+        previous_fermentation_count = int(previous_result.get("fermentation_signal_count") or 0) if previous_result else 0
+        fermentation_signal_count = previous_fermentation_count + 1 if fermentation_ready else 0
+        phase, transition_reason = _confirmed_phase(
+            previous_result,
+            score,
+            day_change,
+            systemic_health,
+            profit_effect_score,
+            limit_ecology_score,
+            phase_signal,
+            extreme_ice,
+            fermentation_signal_count,
+        )
+        previous_phase = str(previous_result.get("phase") or "") if previous_result else ""
+        if phase not in {"修复", "分化"}:
+            fermentation_signal_count = 0
+        elif phase == "分化" and previous_phase != "分化":
+            fermentation_signal_count = 0
+
+        components = {
+            "breadth": {
+                "label": "市场宽度",
+                "score": round(breadth_score, 1),
+                "weight": COMPONENT_WEIGHTS["breadth"],
+                "summary": f"上涨占比 {stats['breadth_ratio']:.1f}%",
+            },
+            "limit_ecology": {
+                "label": "涨停生态",
+                "score": round(limit_ecology_score, 1),
+                "weight": COMPONENT_WEIGHTS["limit_ecology"],
+                "summary": (
+                    f"涨停 {stats['limit_up_count']} · 跌停 {stats['limit_down_count']} · "
+                    f"封板 {stats['seal_rate']:.1f}%"
+                ),
+            },
+            "profit_effect": {
+                "label": "赚钱效应",
+                "score": round(profit_effect_score, 1),
+                "weight": COMPONENT_WEIGHTS["profit_effect"],
+                "summary": (
+                    f"昨涨停红盘 {stats['previous_positive_rate']:.1f}% · "
+                    f"中位 {stats['median_previous_change']:+.2f}% · "
+                    f"重亏 {stats['severe_loss_rate']:.1f}%"
+                    if stats["previous_limit_count"] else "缺少前一交易日样本"
+                ),
+            },
+            "ladder_structure": {
+                "label": "连板结构",
+                "score": round(ladder_structure_score, 1),
+                "weight": COMPONENT_WEIGHTS["ladder_structure"],
+                "summary": f"最高 {stats['max_height']} 板 · 三板以上 {stats['three_plus_count']} 家",
+            },
+            "liquidity": {
+                "label": "成交活跃度",
+                "score": round(liquidity_score, 1),
+                "weight": COMPONENT_WEIGHTS["liquidity"],
+                "summary": f"成交 {stats['amount_billion']:.1f} 亿 · 均值比 {amount_ratio:.2f}",
+            },
+        }
+        results.append(
+            {
+                **stats,
+                "score": score,
+                "ema_score": ema_score,
+                "label": _sentiment_label(score),
+                "phase": phase,
+                "phase_signal": phase_signal,
+                "transition_reason": transition_reason,
+                "fermentation_signal_count": fermentation_signal_count,
+                "day_change": round(day_change, 1),
+                "direction": direction,
+                "momentum": round(momentum, 1),
+                "normalization": "250日历史百分位" if len(previous) >= 20 else normalization,
+                "history_days": len(previous) + 1,
+                "systemic_health": round(systemic_health, 1),
+                "risk_multiplier": round(systemic_gate, 3),
+                "components": components,
+            }
+        )
+    return results
+
+
+def latest_contiguous_history(series: list[dict[str, Any]]) -> list[dict[str, Any]]:
+    if not series:
+        return []
+    contiguous = [series[-1]]
+    for row in reversed(series[:-1]):
+        expected_previous = str(contiguous[0].get("previous_trade_date") or "")
+        if not expected_previous or expected_previous != str(row.get("trade_date") or ""):
+            break
+        contiguous.insert(0, row)
+    return contiguous
+
+
+def apply_sentiment_to_dashboard(
+    dashboard: dict[str, Any],
+    historical_snapshots: list[dict[str, Any]] | None = None,
+) -> dict[str, Any]:
+    result = deepcopy(dashboard)
+    history = list(historical_snapshots or [])
+    history.append(result)
+    series = build_sentiment_history(history)
+    target_date = _trade_date(result)
+    sentiment = next((row for row in reversed(series) if row["trade_date"] == target_date), None)
+    if not sentiment:
+        return result
+    overview = dict(result.get("overview") or {})
+    overview.update(
+        {
+            "sentiment_score": sentiment["score"],
+            "sentiment_trend_score": sentiment["ema_score"],
+            "sentiment_label": sentiment["label"],
+            "sentiment_phase": sentiment["phase"],
+            "sentiment_direction": sentiment["direction"],
+            "sentiment_components": sentiment["components"],
+            "sentiment_engine_version": SENTIMENT_ENGINE_VERSION,
+        }
+    )
+    result["overview"] = overview
+    return result

app/backend/features/sentiment/service.py

@@ -0,0 +1,39 @@
+from __future__ import annotations
+
+from typing import Any
+
+from backend.bootstrap.config import normalize_date
+from backend.features.sentiment.engine import (
+    COMPONENT_WEIGHTS,
+    apply_sentiment_to_dashboard,
+    build_sentiment_history,
+    latest_contiguous_history,
+)
+
+
+class SentimentServiceMixin:
+    def _enrich_dashboard_sentiment(
+        self,
+        dashboard: dict[str, Any],
+        end_date: str,
+    ) -> dict[str, Any]:
+        history = self.database.list_snapshot_payloads(end_date, 260)
+        return apply_sentiment_to_dashboard(dashboard, history)
+
+    def sentiment_history(self, trade_date: str, limit: int = 20) -> dict[str, Any]:
+        normalized_date = normalize_date(trade_date)
+        limit = max(10, min(120, int(limit)))
+        full_series = build_sentiment_history(
+            self.database.list_snapshot_payloads(normalized_date, 240)
+        )
+        series = latest_contiguous_history(full_series)
+        rows = series[-limit:]
+        return {
+            "trade_date": rows[-1]["trade_date"] if rows else normalized_date,
+            "available_days": len(series),
+            "stored_days": len(full_series),
+            "requested_days": limit,
+            "rows": rows,
+            "weights": COMPONENT_WEIGHTS,
+            "normalization": rows[-1]["normalization"] if rows else "固定锚点",
+        }

app/chart_data_provider.py

@@ -1,497 +1,7 @@
-from __future__ import annotations
+"""Compatibility alias for the canonical market chart clients."""
 
-import http.client
+import sys
-import json
-import re
-import time
-import urllib.error
-import urllib.parse
-import urllib.request
-from dataclasses import dataclass
-from datetime import datetime, time as dt_time, timedelta
-from threading import Lock
-from typing import Any, ClassVar
 
-from ifind_client import IfindError, IfindHttpClient
+from backend.features.market import charts as _implementation
 
-
+sys.modules[__name__] = _implementation
-class ChartDataError(RuntimeError):
-    pass
-
-
-TRENDS_URL = "https://push2delay.eastmoney.com/api/qt/stock/trends2/get"
-BOARD_LIST_URL = "https://push2delay.eastmoney.com/api/qt/clist/get"
-BROWSER_USER_AGENT = (
-    "Mozilla/5.0 (Windows NT 10.0; Win64; x64) "
-    "AppleWebKit/537.36 (KHTML, like Gecko) "
-    "Chrome/138.0.0.0 Safari/537.36"
-)
-INDEX_SECIDS = {
-    "000001.SH": "1.000001",
-    "399001.SZ": "0.399001",
-    "399006.SZ": "0.399006",
-}
-
-
-class MarketChartClient:
-    """Prefer iFinD for display charts and retain Eastmoney as a last resort."""
-
-    def __init__(self, ifind: IfindHttpClient, fallback: "EastmoneyChartClient") -> None:
-        self.ifind = ifind
-        self.fallback = fallback
-
-    def stock_intraday(self, code: str) -> dict[str, Any]:
-        normalized = str(code or "").strip()
-        if not re.fullmatch(r"\d{6}", normalized):
-            raise ChartDataError("Invalid stock code")
-        ifind_code = _stock_market_code(normalized)
-        try:
-            return self._ifind_intraday(ifind_code, "stock", normalized)
-        except (IfindError, ChartDataError):
-            return self.fallback.stock_intraday(normalized)
-
-    def stock_daily(self, code: str, end_date: str, limit: int = 90) -> list[dict[str, Any]]:
-        normalized = str(code or "").strip()
-        if not re.fullmatch(r"\d{6}", normalized):
-            raise ChartDataError("Invalid stock code")
-        return self._ifind_daily(_stock_market_code(normalized), end_date, limit)
-
-    def index_daily(self, identifier: str, end_date: str, limit: int = 90) -> list[dict[str, Any]]:
-        normalized = str(identifier or "").strip().upper()
-        if normalized not in INDEX_SECIDS:
-            raise ChartDataError("Unsupported index")
-        return self._ifind_daily(normalized, end_date, limit)
-
-    def board_daily(self, identifier: str, end_date: str, limit: int = 90) -> list[dict[str, Any]]:
-        normalized = str(identifier or "").strip().upper()
-        if not normalized:
-            raise ChartDataError("Invalid board code")
-        return self._ifind_daily(normalized, end_date, limit)
-
-    def index_intraday(self, identifier: str) -> dict[str, Any]:
-        normalized = str(identifier or "").strip().upper()
-        if normalized not in INDEX_SECIDS:
-            raise ChartDataError("Unsupported index")
-        try:
-            return self._ifind_intraday(normalized, "index", normalized)
-        except (IfindError, ChartDataError):
-            return self.fallback.index_intraday(normalized)
-
-    def board_intraday(self, identifier: str, name: str = "") -> dict[str, Any]:
-        normalized = str(identifier or "").strip().upper()
-        try:
-            return self._ifind_intraday(normalized, "board", normalized, name)
-        except (IfindError, ChartDataError):
-            return self.fallback.board_intraday(normalized, name)
-
-    def _ifind_intraday(
-        self,
-        ifind_code: str,
-        entity_type: str,
-        identifier: str,
-        name: str = "",
-    ) -> dict[str, Any]:
-        if not self.ifind.configured:
-            raise ChartDataError("iFinD is not configured")
-        now = datetime.now().astimezone()
-        rows: list[dict[str, Any]] = []
-        for offset in range(0, 8):
-            candidate = now.date() - timedelta(days=offset)
-            if candidate.weekday() >= 5:
-                continue
-            display_date = candidate.isoformat()
-            rows = self.ifind.intraday(
-                ifind_code,
-                f"{display_date} 09:30:00",
-                f"{display_date} 15:00:00",
-                cache_ttl=20 if offset == 0 else 6 * 60 * 60,
-            )
-            if rows:
-                break
-        points = [point for row in rows if (point := _ifind_point(row))]
-        if not points:
-            raise ChartDataError("No iFinD intraday chart data returned")
-        latest_date = points[-1]["date"]
-        points = [point for point in points if point["date"] == latest_date]
-        previous_close = self._previous_close(ifind_code, latest_date, points[0]["open"])
-        return {
-            "entity_type": entity_type,
-            "identifier": identifier,
-            "name": name,
-            "code": identifier,
-            "trade_date": latest_date,
-            "previous_close": previous_close,
-            "points": points,
-            "source": "ifind",
-        }
-
-    def _ifind_daily(
-        self, ifind_code: str, end_date: str, limit: int
-    ) -> list[dict[str, Any]]:
-        if not self.ifind.configured:
-            raise ChartDataError("iFinD is not configured")
-        compact_end = str(end_date or "").replace("-", "")
-        if not re.fullmatch(r"\d{8}", compact_end):
-            raise ChartDataError("Invalid chart end date")
-        end = datetime.strptime(compact_end, "%Y%m%d")
-        start = (end - timedelta(days=max(190, limit * 3))).strftime("%Y%m%d")
-        try:
-            rows = self.ifind.history(
-                ifind_code,
-                ["open", "high", "low", "close", "volume", "amount"],
-                start,
-                compact_end,
-                cache_ttl=300,
-            )
-        except IfindError as exc:
-            raise ChartDataError("No iFinD daily chart data returned") from exc
-        normalized = []
-        for row in rows:
-            stamp = str(row.get("time") or "").strip()
-            trade_date = stamp[:10]
-            close = _number(row.get("close"))
-            if not re.fullmatch(r"\d{4}-\d{2}-\d{2}", trade_date) or close <= 0:
-                continue
-            normalized.append(
-                {
-                    "trade_date": trade_date,
-                    "open": _number(row.get("open")),
-                    "high": _number(row.get("high")),
-                    "low": _number(row.get("low")),
-                    "close": close,
-                    "volume": _number(row.get("volume")),
-                    "amount_billion": _number(row.get("amount")) / 100_000_000,
-                }
-            )
-        normalized.sort(key=lambda row: row["trade_date"])
-        for index, row in enumerate(normalized):
-            previous = normalized[index - 1]["close"] if index > 0 else 0
-            row["change"] = round((row["close"] / previous - 1) * 100, 4) if previous else 0.0
-
-        market_now = datetime.now().astimezone()
-        today = market_now.strftime("%Y%m%d")
-        market_open = (
-            market_now.weekday() < 5
-            and market_now.time().replace(tzinfo=None) >= dt_time(9, 30)
-        )
-        today_display = market_now.date().isoformat()
-        if normalized and normalized[-1]["trade_date"] == today_display:
-            current_bar = normalized[-1]
-            current_bar_is_valid = (
-                current_bar["open"] > 0
-                and current_bar["high"] >= max(current_bar["open"], current_bar["close"])
-                and 0 < current_bar["low"] <= min(current_bar["open"], current_bar["close"])
-                and (current_bar["volume"] > 0 or current_bar["amount_billion"] > 0)
-            )
-            if not market_open or not current_bar_is_valid:
-                normalized.pop()
-        if compact_end == today and market_open:
-            try:
-                quote_rows = self.ifind.real_time(
-                    ifind_code,
-                    ["open", "high", "low", "latest", "preClose", "volume", "amount"],
-                    cache_ttl=10,
-                )
-                quote = quote_rows[0] if quote_rows else {}
-                latest = _number(quote.get("latest"))
-                previous = _number(quote.get("preClose"))
-                open_price = _number(quote.get("open"))
-                high = _number(quote.get("high"))
-                low = _number(quote.get("low"))
-                volume = _number(quote.get("volume"))
-                amount = _number(quote.get("amount"))
-                quote_date = str(quote.get("time") or "")[:10].replace("-", "")
-                quote_is_current = not quote_date or quote_date == today
-                has_market_activity = volume > 0 or amount > 0
-                if (
-                    latest > 0
-                    and open_price > 0
-                    and high >= max(open_price, latest)
-                    and 0 < low <= min(open_price, latest)
-                    and has_market_activity
-                    and quote_is_current
-                ):
-                    realtime = {
-                        "trade_date": end.strftime("%Y-%m-%d"),
-                        "open": open_price,
-                        "high": high,
-                        "low": low,
-                        "close": latest,
-                        "change": round((latest / previous - 1) * 100, 4) if previous else 0.0,
-                        "volume": volume,
-                        "amount_billion": amount / 100_000_000,
-                        "realtime": True,
-                    }
-                    if normalized and normalized[-1]["trade_date"] == realtime["trade_date"]:
-                        normalized[-1] = realtime
-                    else:
-                        normalized.append(realtime)
-            except IfindError:
-                pass
-        if not normalized:
-            raise ChartDataError("No iFinD daily chart data returned")
-        return normalized[-max(20, min(180, int(limit))):]
-
-    def _previous_close(self, code: str, trade_date: str, fallback: float) -> float:
-        today = datetime.now().astimezone().date().isoformat()
-        if trade_date == today:
-            try:
-                quote = self.ifind.real_time(code, ["preClose"], cache_ttl=20)
-                value = _number((quote[0] if quote else {}).get("preClose"))
-                if value > 0:
-                    return value
-            except IfindError:
-                pass
-        end = datetime.strptime(trade_date, "%Y-%m-%d")
-        try:
-            rows = self.ifind.history(
-                code,
-                ["close"],
-                (end - timedelta(days=12)).strftime("%Y%m%d"),
-                end.strftime("%Y%m%d"),
-                cache_ttl=6 * 60 * 60,
-            )
-            closes = [_number(row.get("close")) for row in rows if _number(row.get("close")) > 0]
-            if len(closes) >= 2:
-                return closes[-2]
-        except IfindError:
-            pass
-        return fallback
-
-
-@dataclass
-class EastmoneyChartClient:
-    """Isolated display-only minute chart source.
-
-    The returned data must not be used by market snapshots, scoring, screening,
-    or divination. Its only consumer is a chart-rendering endpoint.
-    """
-
-    timeout: int = 6
-    cache_ttl_seconds: int = 20
-    retry_attempts: int = 2
-    _cache: ClassVar[dict[str, dict[str, Any]]] = {}
-    _cache_lock: ClassVar[Lock] = Lock()
-    _board_catalog: ClassVar[dict[str, dict[str, str]]] = {}
-    _board_catalog_at: ClassVar[float] = 0.0
-    _board_catalog_lock: ClassVar[Lock] = Lock()
-
-    def stock_intraday(self, code: str) -> dict[str, Any]:
-        normalized = str(code or "").strip()
-        if not re.fullmatch(r"\d{6}", normalized):
-            raise ChartDataError("Invalid stock code")
-        market = "1" if normalized.startswith(("5", "6", "9")) else "0"
-        return self._intraday(f"{market}.{normalized}", "stock", normalized)
-
-    def index_intraday(self, identifier: str) -> dict[str, Any]:
-        normalized = str(identifier or "").strip().upper()
-        secid = INDEX_SECIDS.get(normalized)
-        if not secid:
-            raise ChartDataError("Unsupported index")
-        return self._intraday(secid, "index", normalized)
-
-    def board_intraday(self, identifier: str, name: str = "") -> dict[str, Any]:
-        normalized = str(identifier or "").strip().upper()
-        if re.fullmatch(r"BK\d{4}", normalized):
-            board_code = normalized
-        else:
-            board_code = self._resolve_board_code(name or identifier)
-        return self._intraday(f"90.{board_code}", "board", board_code)
-
-    def _intraday(self, secid: str, entity_type: str, identifier: str) -> dict[str, Any]:
-        cache_key = f"{entity_type}:{identifier}"
-        cached = self._get_cached(cache_key)
-        if cached is not None:
-            return cached
-
-        payload = self._request_json(
-            TRENDS_URL,
-            {
-                "secid": secid,
-                "fields1": "f1,f2,f3,f4,f5,f6,f7,f8,f9,f10,f11,f12,f13",
-                "fields2": "f51,f52,f53,f54,f55,f56,f57,f58",
-                "iscr": "0",
-                "ndays": "1",
-            },
-            "https://quote.eastmoney.com/",
-        )
-        data = payload.get("data") or {}
-        points = [point for raw in data.get("trends") or [] if (point := _parse_trend(raw))]
-        if not points:
-            raise ChartDataError("No intraday chart data returned")
-
-        result = {
-            "entity_type": entity_type,
-            "identifier": identifier,
-            "name": str(data.get("name") or ""),
-            "code": str(data.get("code") or identifier),
-            "trade_date": points[-1]["date"],
-            "previous_close": _number(data.get("preClose")),
-            "points": points,
-        }
-        with self._cache_lock:
-            self._cache[cache_key] = {"created_at": time.time(), "payload": result}
-        return result
-
-    def _get_cached(self, cache_key: str) -> dict[str, Any] | None:
-        with self._cache_lock:
-            cached = self._cache.get(cache_key)
-        if not cached:
-            return None
-        if time.time() - float(cached.get("created_at") or 0) > self.cache_ttl_seconds:
-            with self._cache_lock:
-                self._cache.pop(cache_key, None)
-            return None
-        return dict(cached["payload"])
-
-    def _resolve_board_code(self, name: str) -> str:
-        normalized = _normalize_name(name)
-        if not normalized:
-            raise ChartDataError("Board name is required")
-        catalog = self._load_board_catalog()
-        item = catalog.get(normalized)
-        if not item:
-            raise ChartDataError("No matching chart board")
-        return item["code"]
-
-    def _load_board_catalog(self) -> dict[str, dict[str, str]]:
-        now = time.time()
-        with self._board_catalog_lock:
-            if self._board_catalog and now - self._board_catalog_at < 6 * 60 * 60:
-                return dict(self._board_catalog)
-
-        rows: list[dict[str, Any]] = []
-        for board_type in ("1", "2", "3"):
-            for page in range(1, 6):
-                payload = self._request_json(
-                    BOARD_LIST_URL,
-                    {
-                        "pn": str(page),
-                        "pz": "100",
-                        "po": "1",
-                        "np": "1",
-                        "fltt": "2",
-                        "invt": "2",
-                        "fid": "f3",
-                        "fs": f"m:90+t:{board_type}",
-                        "fields": "f12,f14",
-                    },
-                    "https://quote.eastmoney.com/center/boardlist.html",
-                )
-                page_rows = (payload.get("data") or {}).get("diff") or []
-                rows.extend(page_rows)
-                if len(page_rows) < 100:
-                    break
-
-        catalog: dict[str, dict[str, str]] = {}
-        for row in rows:
-            code = str(row.get("f12") or "").strip().upper()
-            board_name = str(row.get("f14") or "").strip()
-            if re.fullmatch(r"BK\d{4}", code) and board_name:
-                catalog.setdefault(_normalize_name(board_name), {"code": code, "name": board_name})
-        if not catalog:
-            raise ChartDataError("Board chart directory is unavailable")
-        with self._board_catalog_lock:
-            type(self)._board_catalog = catalog
-            type(self)._board_catalog_at = now
-        return dict(catalog)
-
-    def _request_json(
-        self, url: str, params: dict[str, str], referer: str
-    ) -> dict[str, Any]:
-        request_url = f"{url}?{urllib.parse.urlencode(params)}"
-        last_error: Exception | None = None
-        for attempt in range(max(1, int(self.retry_attempts))):
-            request = urllib.request.Request(
-                request_url,
-                headers={
-                    "Accept": "application/json,text/plain,*/*",
-                    "Connection": "close",
-                    "Referer": referer,
-                    "User-Agent": BROWSER_USER_AGENT,
-                },
-            )
-            try:
-                with urllib.request.urlopen(request, timeout=self.timeout) as response:
-                    payload = json.loads(response.read().decode("utf-8"))
-                if not isinstance(payload, dict):
-                    raise ChartDataError("Invalid intraday chart response")
-                return payload
-            except (
-                urllib.error.URLError,
-                TimeoutError,
-                ConnectionError,
-                OSError,
-                http.client.HTTPException,
-                json.JSONDecodeError,
-                ChartDataError,
-            ) as exc:
-                last_error = exc
-                if attempt + 1 < self.retry_attempts:
-                    time.sleep(0.12)
-        raise ChartDataError("Intraday chart request failed") from last_error
-
-
-def _parse_trend(raw: Any) -> dict[str, Any] | None:
-    fields = str(raw or "").split(",")
-    if len(fields) < 8 or " " not in fields[0]:
-        return None
-    stamp = fields[0].strip()
-    trade_date, trade_time = stamp.split(" ", 1)
-    close = _number(fields[2])
-    if close <= 0:
-        return None
-    return {
-        "date": trade_date,
-        "time": trade_time[:5],
-        "open": _number(fields[1]),
-        "close": close,
-        "high": _number(fields[3]),
-        "low": _number(fields[4]),
-        "volume": _number(fields[5]),
-        "amount": _number(fields[6]),
-        "average": _number(fields[7]),
-    }
-
-
-def _ifind_point(row: dict[str, Any]) -> dict[str, Any] | None:
-    stamp = str(row.get("time") or "").strip()
-    if " " not in stamp:
-        return None
-    trade_date, trade_time = stamp.split(" ", 1)
-    close = _number(row.get("close"))
-    if close <= 0:
-        return None
-    return {
-        "date": trade_date,
-        "time": trade_time[:5],
-        "open": _number(row.get("open")),
-        "close": close,
-        "high": _number(row.get("high")),
-        "low": _number(row.get("low")),
-        "volume": _number(row.get("volume")),
-        "amount": _number(row.get("amount")),
-        "average": _number(row.get("avgPrice")),
-    }
-
-
-def _stock_market_code(code: str) -> str:
-    if code.startswith(("4", "8", "9")):
-        suffix = "BJ"
-    elif code.startswith("6"):
-        suffix = "SH"
-    else:
-        suffix = "SZ"
-    return f"{code}.{suffix}"
-
-
-def _number(value: Any) -> float:
-    try:
-        return float(value or 0)
-    except (TypeError, ValueError):
-        return 0.0
-
-
-def _normalize_name(value: Any) -> str:
-    normalized = re.sub(r"[\s·・（）()\-_/]", "", str(value or "")).casefold()
-    return re.sub(r"(?:概念|行业|[ⅠⅡⅢ])$", "", normalized)

app/database.py

@@ -8,6 +8,8 @@ from typing import Any
 
 from backend.database import MIGRATIONS, MigrationRunner, SQLiteConnectionFactory
 from backend.features.accounts.repository import AccountRepositoryMixin
+from backend.features.market.repository import MarketRepositoryMixin
+from backend.features.pools.repository import PoolRepositoryMixin
 from backend.features.system.repository import SystemSettingsRepositoryMixin
 
 
@@ -20,7 +22,12 @@ def _optional_float(value: Any) -> float | None:
         return None
 
 
-class ReviewDatabase(AccountRepositoryMixin, SystemSettingsRepositoryMixin):
+class ReviewDatabase(
+    AccountRepositoryMixin,
+    MarketRepositoryMixin,
+    PoolRepositoryMixin,
+    SystemSettingsRepositoryMixin,
+):
     def __init__(self, path: Path) -> None:
         self.path = path
         self.path.parent.mkdir(parents=True, exist_ok=True)
@@ -690,118 +697,6 @@ class ReviewDatabase(AccountRepositoryMixin, SystemSettingsRepositoryMixin):
             ).fetchone()
         return int(row["total"] if row else 0)
 
-    def get_snapshot(self, trade_date: str) -> dict[str, Any] | None:
-        with self.connect() as connection:
-            row = connection.execute(
-                "SELECT payload FROM dashboard_snapshots WHERE trade_date = ?",
-                (trade_date,),
-            ).fetchone()
-        if not row:
-            return None
-        try:
-            return json.loads(row["payload"])
-        except json.JSONDecodeError:
-            return None
-
-    def get_latest_real_snapshot(
-        self, trade_date: str, strictly_before: bool = False
-    ) -> dict[str, Any] | None:
-        operator = "<" if strictly_before else "<="
-        with self.connect() as connection:
-            row = connection.execute(
-                f"""
-                SELECT payload FROM dashboard_snapshots
-                WHERE trade_date {operator} ? AND source != 'demo'
-                ORDER BY trade_date DESC LIMIT 1
-                """,
-                (trade_date,),
-            ).fetchone()
-        if not row:
-            return None
-        try:
-            return json.loads(row["payload"])
-        except json.JSONDecodeError:
-            return None
-
-    def save_snapshot(self, trade_date: str, source: str, payload: dict[str, Any]) -> None:
-        updated_at = datetime.now().astimezone().isoformat(timespec="seconds")
-        record_count = sum(
-            len(payload.get(key) or [])
-            for key in ("limits", "broken", "down_limits", "yesterday_limits")
-        )
-        content = json.dumps(payload, ensure_ascii=False, separators=(",", ":"))
-        with self.connect() as connection:
-            connection.execute(
-                """
-                INSERT INTO dashboard_snapshots
-                    (trade_date, source, payload, record_count, updated_at)
-                VALUES (?, ?, ?, ?, ?)
-                ON CONFLICT(trade_date) DO UPDATE SET
-                    source = excluded.source,
-                    payload = excluded.payload,
-                    record_count = excluded.record_count,
-                    updated_at = excluded.updated_at
-                """,
-                (trade_date, source, content, record_count, updated_at),
-            )
-
-    def get_data_snapshot(self, kind: str, cache_key: str) -> dict[str, Any] | None:
-        with self.connect() as connection:
-            row = connection.execute(
-                "SELECT payload FROM data_snapshots WHERE kind = ? AND cache_key = ?",
-                (kind, cache_key),
-            ).fetchone()
-        if not row:
-            return None
-        try:
-            return json.loads(row["payload"])
-        except json.JSONDecodeError:
-            return None
-
-    def get_latest_data_snapshot(
-        self,
-        kind: str,
-        cache_key_prefix: str,
-        maximum_cache_key: str,
-        exclude_source: str = "",
-    ) -> dict[str, Any] | None:
-        source_clause = " AND source != ?" if exclude_source else ""
-        parameters: list[Any] = [kind, f"{cache_key_prefix}%", maximum_cache_key]
-        if exclude_source:
-            parameters.append(exclude_source)
-        with self.connect() as connection:
-            row = connection.execute(
-                f"""
-                SELECT payload FROM data_snapshots
-                WHERE kind = ? AND cache_key LIKE ? AND cache_key <= ?{source_clause}
-                ORDER BY cache_key DESC LIMIT 1
-                """,
-                parameters,
-            ).fetchone()
-        if not row:
-            return None
-        try:
-            return json.loads(row["payload"])
-        except json.JSONDecodeError:
-            return None
-
-    def save_data_snapshot(
-        self, kind: str, cache_key: str, source: str, payload: dict[str, Any]
-    ) -> None:
-        updated_at = datetime.now().astimezone().isoformat(timespec="seconds")
-        content = json.dumps(payload, ensure_ascii=False, separators=(",", ":"))
-        with self.connect() as connection:
-            connection.execute(
-                """
-                INSERT INTO data_snapshots (kind, cache_key, source, payload, updated_at)
-                VALUES (?, ?, ?, ?, ?)
-                ON CONFLICT(kind, cache_key) DO UPDATE SET
-                    source = excluded.source,
-                    payload = excluded.payload,
-                    updated_at = excluded.updated_at
-                """,
-                (kind, cache_key, source, content, updated_at),
-            )
 
     def list_watchlist(self, user_id: int) -> list[dict[str, Any]]:
         with self.connect() as connection:
@@ -869,7 +764,6 @@ class ReviewDatabase(AccountRepositoryMixin, SystemSettingsRepositoryMixin):
                 (int(user_id), code),
             )
             return cursor.rowcount > 0
-
     def list_notes(
         self,
         user_id: int,
@@ -944,27 +838,6 @@ class ReviewDatabase(AccountRepositoryMixin, SystemSettingsRepositoryMixin):
             )
             return cursor.rowcount > 0
 
-    def save_reason_override(self, trade_date: str, code: str, reason: str) -> None:
-        now = datetime.now().astimezone().isoformat(timespec="seconds")
-        with self.connect() as connection:
-            connection.execute(
-                """
-                INSERT INTO reason_overrides (trade_date, code, reason, updated_at)
-                VALUES (?, ?, ?, ?)
-                ON CONFLICT(trade_date, code) DO UPDATE SET
-                    reason = excluded.reason,
-                    updated_at = excluded.updated_at
-                """,
-                (trade_date, code, reason, now),
-            )
-
-    def reason_overrides(self, trade_date: str) -> dict[str, str]:
-        with self.connect() as connection:
-            rows = connection.execute(
-                "SELECT code, reason FROM reason_overrides WHERE trade_date = ?",
-                (trade_date,),
-            ).fetchall()
-        return {row["code"]: row["reason"] for row in rows}
 
     def list_seat_aliases(self) -> dict[str, str]:
         with self.connect() as connection:
@@ -1042,26 +915,6 @@ class ReviewDatabase(AccountRepositoryMixin, SystemSettingsRepositoryMixin):
             )
         return len(values)
 
-    def search_stock_master(self, query: str, limit: int = 12) -> list[dict[str, Any]]:
-        text = str(query or "").strip()
-        if not text:
-            return []
-        escaped = text.replace("\\", "\\\\").replace("%", "\\%").replace("_", "\\_")
-        with self.connect() as connection:
-            rows = connection.execute(
-                """
-                SELECT ts_code, code, name, industry, market, list_date
-                FROM stock_master
-                WHERE code = ? OR name = ? OR name LIKE ? ESCAPE '\\'
-                ORDER BY
-                    CASE WHEN code = ? THEN 0 WHEN name = ? THEN 1 ELSE 2 END,
-                    list_date DESC,
-                    code
-                LIMIT ?
-                """,
-                (text, text, f"%{escaped}%", text, text, max(1, min(30, int(limit)))),
-            ).fetchall()
-        return [dict(row) for row in rows]
 
     def list_stock_master(self) -> list[dict[str, Any]]:
         with self.connect() as connection:
@@ -1666,24 +1519,6 @@ class ReviewDatabase(AccountRepositoryMixin, SystemSettingsRepositoryMixin):
             for row in series[-limit:]
         ]
 
-    def list_snapshot_payloads(self, end_date: str, limit: int = 260) -> list[dict[str, Any]]:
-        with self.connect() as connection:
-            rows = connection.execute(
-                """
-                SELECT trade_date, payload FROM dashboard_snapshots
-                WHERE trade_date <= ? ORDER BY trade_date DESC LIMIT ?
-                """,
-                (end_date, limit),
-            ).fetchall()
-        result: list[dict[str, Any]] = []
-        for row in reversed(rows):
-            try:
-                payload = json.loads(row["payload"])
-            except json.JSONDecodeError:
-                continue
-            payload["_snapshot_date"] = row["trade_date"]
-            result.append(payload)
-        return result
 
     def save_screener_strategy(
         self, user_id: int | None, name: str, description: str, regimes: list[str], formula: dict[str, Any],
@@ -2529,64 +2364,3 @@ class ReviewDatabase(AccountRepositoryMixin, SystemSettingsRepositoryMixin):
                 (int(reading_id), int(user_id)),
             )
             return cursor.rowcount > 0
-
-    def start_sync(self, trade_date: str, source: str) -> int:
-        started_at = datetime.now().astimezone().isoformat(timespec="seconds")
-        with self.connect() as connection:
-            cursor = connection.execute(
-                """
-                INSERT INTO sync_runs (trade_date, source, status, started_at)
-                VALUES (?, ?, 'running', ?)
-                """,
-                (trade_date, source, started_at),
-            )
-            return int(cursor.lastrowid)
-
-    def finish_sync(
-        self,
-        sync_id: int,
-        status: str,
-        record_count: int = 0,
-        message: str = "",
-        source: str | None = None,
-    ) -> None:
-        finished_at = datetime.now().astimezone().isoformat(timespec="seconds")
-        with self.connect() as connection:
-            connection.execute(
-                """
-                UPDATE sync_runs
-                SET status = ?, finished_at = ?, record_count = ?, message = ?,
-                    source = COALESCE(?, source)
-                WHERE id = ?
-                """,
-                (status, finished_at, record_count, message[:1000], source, sync_id),
-            )
-
-    def status(self) -> dict[str, Any]:
-        with self.connect() as connection:
-            last_sync = connection.execute(
-                """
-                SELECT id, trade_date, source, status, started_at, finished_at,
-                       record_count, message
-                FROM sync_runs ORDER BY id DESC LIMIT 1
-                """
-            ).fetchone()
-            snapshot_stats = connection.execute(
-                """
-                SELECT COUNT(*) AS dates, COALESCE(SUM(record_count), 0) AS records,
-                       MAX(updated_at) AS updated_at
-                FROM dashboard_snapshots
-                """
-            ).fetchone()
-            watchlist_count = connection.execute("SELECT COUNT(*) FROM watchlist").fetchone()[0]
-            note_count = connection.execute("SELECT COUNT(*) FROM review_notes").fetchone()[0]
-
-        return {
-            "database": str(self.path.name),
-            "snapshot_dates": int(snapshot_stats["dates"]),
-            "snapshot_records": int(snapshot_stats["records"]),
-            "updated_at": snapshot_stats["updated_at"],
-            "last_sync": dict(last_sync) if last_sync else None,
-            "watchlist_count": int(watchlist_count),
-            "note_count": int(note_count),
-        }

app/demo_data.py

@@ -5,7 +5,7 @@ import math
 from datetime import datetime, timedelta
 from typing import Any
 
-from sentiment_engine import apply_sentiment_to_dashboard
+from backend.features.sentiment.engine import apply_sentiment_to_dashboard
 
 
 DEMO_LIMITS = [

app/ifind_client.py

@@ -1,385 +1,7 @@
-from __future__ import annotations
+"""Compatibility alias for the canonical iFinD provider implementation."""
 
-import copy
+import sys
-import json
-import threading
-import time
-import urllib.error
-import urllib.request
-from datetime import datetime, timedelta
-from typing import Any
 
+from backend.data.providers import ifind_client as _implementation
 
-class IfindError(RuntimeError):
+sys.modules[__name__] = _implementation
-    pass
-
-
-class IfindHttpClient:
-    BASE_URL = "https://quantapi.51ifind.com/api/v1"
-    AUTH_ENDPOINT = "get_access_token"
-    AUTH_ERROR_CODES = {-1302, -1303, -1304, -4302, -4303}
-
-    def __init__(
-        self,
-        refresh_token: str = "",
-        access_token: str = "",
-        timeout: int = 15,
-    ) -> None:
-        self.timeout = max(3, int(timeout))
-        self._refresh_token = str(refresh_token or "").strip()
-        self._access_token = str(access_token or "").strip()
-        self._access_expires_at: datetime | None = None
-        self._token_lock = threading.Lock()
-        self._cache_lock = threading.Lock()
-        self._cache: dict[str, dict[str, Any]] = {}
-
-    @property
-    def configured(self) -> bool:
-        return bool(self._refresh_token or self._access_token)
-
-    def set_credentials(self, refresh_token: str, access_token: str = "") -> None:
-        refresh_token = str(refresh_token or "").strip()
-        access_token = str(access_token or "").strip()
-        with self._token_lock:
-            refresh_changed = refresh_token != self._refresh_token
-            self._refresh_token = refresh_token
-            if access_token or refresh_changed:
-                self._access_token = access_token
-                self._access_expires_at = None
-        if refresh_changed:
-            with self._cache_lock:
-                self._cache.clear()
-
-    def status(self) -> dict[str, Any]:
-        return {
-            "configured": self.configured,
-            "access_ready": bool(self._access_token),
-            "access_expires_at": (
-                self._access_expires_at.isoformat(timespec="seconds")
-                if self._access_expires_at
-                else ""
-            ),
-        }
-
-    def test_connection(self) -> dict[str, Any]:
-        payload = self.real_time(
-            "000001.SH",
-            ["open", "high", "low", "latest", "preClose"],
-            cache_ttl=0,
-        )
-        return {
-            "ok": bool(payload),
-            "sample_time": str(payload[0].get("time") or "") if payload else "",
-        }
-
-    def real_time(
-        self,
-        codes: str | list[str],
-        indicators: list[str],
-        cache_ttl: int = 10,
-    ) -> list[dict[str, Any]]:
-        code_text = self._codes(codes)
-        payload = self._request(
-            "real_time_quotation",
-            {"codes": code_text, "indicators": ",".join(indicators)},
-            cache_key=f"rq:{code_text}:{','.join(indicators)}",
-            cache_ttl=cache_ttl,
-        )
-        return self._table_rows(payload)
-
-    def history(
-        self,
-        codes: str | list[str],
-        indicators: list[str],
-        start_date: str,
-        end_date: str,
-        cache_ttl: int = 300,
-    ) -> list[dict[str, Any]]:
-        code_text = self._codes(codes)
-        payload = self._request(
-            "cmd_history_quotation",
-            {
-                "codes": code_text,
-                "indicators": ",".join(indicators),
-                "startdate": self._display_date(start_date),
-                "enddate": self._display_date(end_date),
-                "functionpara": {"CPS": "forward1", "Fill": "Omit"},
-            },
-            cache_key=f"hq:{code_text}:{start_date}:{end_date}:{','.join(indicators)}",
-            cache_ttl=cache_ttl,
-        )
-        return self._table_rows(payload)
-
-    def intraday(
-        self,
-        code: str,
-        start_time: str,
-        end_time: str,
-        cache_ttl: int = 20,
-    ) -> list[dict[str, Any]]:
-        indicators = ["open", "high", "low", "close", "volume", "amount", "avgPrice"]
-        payload = self._request(
-            "high_frequency",
-            {
-                "codes": self._codes(code),
-                "indicators": ",".join(indicators),
-                "starttime": start_time,
-                "endtime": end_time,
-                "functionpara": {
-                    "CPS": "forward1",
-                    "Fill": "Previous",
-                    "Timeformat": "LocalTime",
-                    "Interval": "1",
-                    "Limitstart": "09:30:00",
-                    "Limitend": "15:00:00",
-                },
-            },
-            cache_key=f"hf:{code}:{start_time}:{end_time}",
-            cache_ttl=cache_ttl,
-        )
-        return self._table_rows(payload)
-
-    def snapshots(
-        self,
-        codes: str | list[str],
-        indicators: list[str],
-        start_time: str,
-        end_time: str,
-        cache_ttl: int = 8,
-    ) -> list[dict[str, Any]]:
-        code_text = self._codes(codes)
-        payload = self._request(
-            "snap_shot",
-            {
-                "codes": code_text,
-                "indicators": ",".join(indicators),
-                "starttime": start_time,
-                "endtime": end_time,
-            },
-            cache_key=f"ss:{code_text}:{start_time}:{end_time}:{','.join(indicators)}",
-            cache_ttl=cache_ttl,
-        )
-        return self._table_rows(payload)
-
-    def wencai(self, query: str, search_type: str = "stock", cache_ttl: int = 300) -> list[dict[str, Any]]:
-        normalized = " ".join(str(query or "").split())
-        if not normalized:
-            raise IfindError("问财查询不能为空。")
-        payload = self._request(
-            "smart_stock_picking",
-            {"searchstring": normalized, "searchtype": search_type},
-            cache_key=f"wc:{search_type}:{normalized}",
-            cache_ttl=cache_ttl,
-        )
-        return self._table_rows(payload)
-
-    def report_query(
-        self,
-        codes: str | list[str],
-        begin_date: str,
-        end_date: str,
-        cache_ttl: int = 300,
-    ) -> list[dict[str, Any]]:
-        code_text = self._codes(codes)
-        payload = self._request(
-            "report_query",
-            {
-                "codes": code_text,
-                "beginrDate": self._display_date(begin_date),
-                "endrDate": self._display_date(end_date),
-                "outputpara": (
-                    "reportDate:Y,thscode:Y,secName:Y,ctime:Y,"
-                    "reportTitle:Y,pdfURL:Y,seq:Y"
-                ),
-            },
-            cache_key=f"report:{code_text}:{begin_date}:{end_date}",
-            cache_ttl=cache_ttl,
-        )
-        return self._table_rows(payload)
-
-    def _request(
-        self,
-        endpoint: str,
-        body: dict[str, Any],
-        cache_key: str = "",
-        cache_ttl: int = 0,
-    ) -> dict[str, Any]:
-        if not self.configured:
-            raise IfindError("iFinD 尚未配置。")
-        if cache_key and cache_ttl > 0:
-            cached = self._cached(cache_key, cache_ttl)
-            if cached is not None:
-                return cached
-
-        payload = self._post(endpoint, body, self._ensure_access_token())
-        if self._is_auth_error(payload) and self._refresh_token:
-            self._invalidate_access_token()
-            payload = self._post(endpoint, body, self._ensure_access_token(force=True))
-        self._validate_payload(payload)
-        if cache_key and cache_ttl > 0:
-            with self._cache_lock:
-                self._cache[cache_key] = {
-                    "created_at": time.time(),
-                    "payload": copy.deepcopy(payload),
-                }
-        return payload
-
-    def _ensure_access_token(self, force: bool = False) -> str:
-        with self._token_lock:
-            now = datetime.now().astimezone().replace(tzinfo=None)
-            token_valid = bool(self._access_token) and (
-                self._access_expires_at is None
-                or self._access_expires_at > now + timedelta(minutes=2)
-            )
-            if token_valid and not force:
-                return self._access_token
-            if not self._refresh_token:
-                if self._access_token:
-                    return self._access_token
-                raise IfindError("iFinD Refresh Token 尚未配置。")
-            payload = self._post(self.AUTH_ENDPOINT, {}, "", self._refresh_token)
-            self._validate_payload(payload)
-            data = payload.get("data") or {}
-            token = str(data.get("access_token") or "").strip()
-            if not token:
-                raise IfindError("iFinD 未返回 Access Token。")
-            expires_at = self._parse_datetime(data.get("expired_time"))
-            self._access_token = token
-            self._access_expires_at = expires_at
-            return token
-
-    def _post(
-        self,
-        endpoint: str,
-        body: dict[str, Any],
-        access_token: str,
-        refresh_token: str = "",
-    ) -> dict[str, Any]:
-        headers = {
-            "Accept": "application/json",
-            "Content-Type": "application/json",
-            "User-Agent": "XiaobaiReviewWeb/1.0",
-            "ifindlang": "cn",
-        }
-        if access_token:
-            headers["access_token"] = access_token
-        if refresh_token:
-            headers["refresh_token"] = refresh_token
-        request = urllib.request.Request(
-            f"{self.BASE_URL}/{endpoint}",
-            data=json.dumps(body, ensure_ascii=False, separators=(",", ":")).encode("utf-8"),
-            headers=headers,
-            method="POST",
-        )
-        try:
-            with urllib.request.urlopen(request, timeout=self.timeout) as response:
-                payload = json.loads(response.read().decode("utf-8"))
-        except urllib.error.HTTPError as exc:
-            detail = ""
-            try:
-                detail_payload = json.loads(exc.read().decode("utf-8", errors="replace"))
-                detail = str(detail_payload.get("errmsg") or detail_payload.get("message") or "")
-            except (json.JSONDecodeError, OSError):
-                pass
-            raise IfindError(f"iFinD HTTP {exc.code}{f'：{detail[:160]}' if detail else ''}") from exc
-        except (urllib.error.URLError, TimeoutError, OSError, json.JSONDecodeError) as exc:
-            raise IfindError("iFinD 数据请求失败。") from exc
-        if not isinstance(payload, dict):
-            raise IfindError("iFinD 返回格式不正确。")
-        return payload
-
-    def _cached(self, key: str, ttl: int) -> dict[str, Any] | None:
-        with self._cache_lock:
-            cached = self._cache.get(key)
-            if not cached:
-                return None
-            if time.time() - float(cached.get("created_at") or 0) > ttl:
-                self._cache.pop(key, None)
-                return None
-            return copy.deepcopy(cached["payload"])
-
-    def _invalidate_access_token(self) -> None:
-        with self._token_lock:
-            self._access_token = ""
-            self._access_expires_at = None
-
-    @classmethod
-    def _validate_payload(cls, payload: dict[str, Any]) -> None:
-        try:
-            error_code = int(payload.get("errorcode") or 0)
-        except (TypeError, ValueError):
-            error_code = -1
-        if error_code != 0:
-            message = str(payload.get("errmsg") or "未知错误")
-            raise IfindError(f"iFinD 返回错误：{message[:200]}")
-
-    @classmethod
-    def _is_auth_error(cls, payload: dict[str, Any]) -> bool:
-        try:
-            error_code = int(payload.get("errorcode") or 0)
-        except (TypeError, ValueError):
-            error_code = 0
-        message = str(payload.get("errmsg") or "").casefold()
-        return error_code in cls.AUTH_ERROR_CODES or "token" in message or "鉴权" in message
-
-    @staticmethod
-    def _table_rows(payload: dict[str, Any]) -> list[dict[str, Any]]:
-        tables = payload.get("tables") or []
-        if isinstance(tables, dict):
-            tables = [tables]
-        rows: list[dict[str, Any]] = []
-        for block in tables if isinstance(tables, list) else []:
-            if not isinstance(block, dict):
-                continue
-            table = block.get("table") or {}
-            if not isinstance(table, dict):
-                continue
-            times = block.get("time") or []
-            codes = block.get("thscode") or block.get("thscodes") or []
-            if isinstance(codes, str):
-                codes = [codes]
-            lengths = [len(value) for value in table.values() if isinstance(value, list)]
-            row_count = max(lengths or [len(times) if isinstance(times, list) else 0, 1 if table else 0])
-            for index in range(row_count):
-                row: dict[str, Any] = {}
-                if isinstance(times, list) and index < len(times):
-                    row["time"] = times[index]
-                if codes:
-                    row["thscode"] = codes[index] if index < len(codes) else codes[0]
-                for field, values in table.items():
-                    if isinstance(values, list):
-                        row[field] = values[index] if index < len(values) else None
-                    elif index == 0:
-                        row[field] = values
-                rows.append(row)
-        return rows
-
-    @staticmethod
-    def _codes(codes: str | list[str]) -> str:
-        if isinstance(codes, list):
-            values = [str(code or "").strip().upper() for code in codes]
-        else:
-            values = [part.strip().upper() for part in str(codes or "").split(",")]
-        values = [value for value in values if value]
-        if not values:
-            raise IfindError("iFinD 证券代码不能为空。")
-        if len(values) > 100:
-            raise IfindError("iFinD 单次证券代码过多。")
-        return ",".join(values)
-
-    @staticmethod
-    def _display_date(value: str) -> str:
-        compact = str(value or "").replace("-", "")
-        if len(compact) != 8 or not compact.isdigit():
-            raise IfindError("iFinD 日期格式不正确。")
-        return f"{compact[:4]}-{compact[4:6]}-{compact[6:]}"
-
-    @staticmethod
-    def _parse_datetime(value: Any) -> datetime | None:
-        text = str(value or "").strip()
-        if not text:
-            return None
-        try:
-            return datetime.fromisoformat(text)
-        except ValueError:
-            return None

app/realtime_aggregator.py

@@ -1,426 +1,7 @@
-from __future__ import annotations
+"""Compatibility alias for the canonical display-only realtime observer."""
 
-import copy
+import sys
-import http.client
-import json
-import time
-import urllib.error
-import urllib.parse
-import urllib.request
-from concurrent.futures import ThreadPoolExecutor
-from dataclasses import dataclass
-from datetime import datetime
-from threading import Lock
-from typing import Any, ClassVar
 
+from backend.data import realtime as _implementation
 
-class RealtimeAggregateError(RuntimeError):
+sys.modules[__name__] = _implementation
-    pass
-
-
-EASTMONEY_INDEX_URL = "https://push2.eastmoney.com/api/qt/ulist.np/get"
-EASTMONEY_SECTOR_URL = "https://push2.eastmoney.com/api/qt/clist/get"
-TENCENT_INDEX_URL = "https://qt.gtimg.cn/q=sh000001,sz399001,sz399006"
-THS_LIMIT_URL = "https://data.10jqka.com.cn/dataapi/limit_up/limit_up_pool"
-XGB_POOL_URL = "https://flash-api.xuangubao.cn/api/pool/detail"
-BROWSER_USER_AGENT = (
-    "Mozilla/5.0 (Windows NT 10.0; Win64; x64) "
-    "AppleWebKit/537.36 (KHTML, like Gecko) "
-    "Chrome/138.0.0.0 Safari/537.36"
-)
-
-
-@dataclass
-class WebRealtimeAggregator:
-    timeout: int = 8
-    retry_attempts: int = 3
-    retry_delay_seconds: float = 0.2
-    response_cache_ttl_seconds: int = 90
-    _sector_cache: ClassVar[dict[str, Any]] = {}
-    _sector_cache_lock: ClassVar[Lock] = Lock()
-    _response_cache: ClassVar[dict[str, dict[str, Any]]] = {}
-    _response_cache_lock: ClassVar[Lock] = Lock()
-
-    def health_snapshot(self, sector: str = "") -> dict[str, Any]:
-        started = time.perf_counter()
-        sources: dict[str, dict[str, Any]] = {}
-        indices: list[dict[str, Any]] = []
-        sector_payload: dict[str, Any] | None = None
-
-        indices, sources["eastmoney_indices"] = self._capture(self.eastmoney_indices)
-        if sector.strip():
-            sector_payload, sources["eastmoney_sector"] = self._capture(
-                lambda: self.eastmoney_sector(sector)
-            )
-        ths_observation, sources["ths_limit_pool"] = self._capture(self.ths_limit_pool)
-        xgb_observation, sources["xgb_limit_pool"] = self._capture(self.xgb_limit_pool)
-
-        index_times = [int(item.get("quote_time_epoch") or 0) for item in indices or []]
-        now = datetime.now().astimezone()
-        max_skew = 120 if now.hour >= 15 else 15
-        index_consistent = bool(index_times) and max(index_times) - min(index_times) <= max_skew
-        ready = (
-            bool(indices)
-            and len(indices) == 3
-            and index_consistent
-            and (not sector.strip() or bool(sector_payload))
-        )
-        return {
-            "ready": ready,
-            "isolated": True,
-            "generated_at": datetime.now().astimezone().isoformat(timespec="seconds"),
-            "elapsed_ms": round((time.perf_counter() - started) * 1000),
-            "indices": indices or [],
-            "index_consistent": index_consistent,
-            "sector": sector_payload,
-            "sources": sources,
-            "observations": {
-                "ths_limit_pool": ths_observation,
-                "xgb_limit_pool": xgb_observation,
-            },
-            "policy": {
-                "integration": "heaven_realtime_fallback",
-                "max_index_time_skew_seconds": max_skew,
-                "notice": "聚合源仅作为盘中观势的实时指数与板块外显，主行情快照仍由Tushare维护。",
-            },
-        }
-
-    def eastmoney_indices(self) -> list[dict[str, Any]]:
-        try:
-            payload = self._get_json(
-                EASTMONEY_INDEX_URL,
-                {
-                    "secids": "1.000001,0.399001,0.399006",
-                    "fltt": "2",
-                    "invt": "2",
-                    "fields": "f12,f14,f2,f3,f4,f15,f16,f17,f18,f6,f124",
-                },
-                referer="https://quote.eastmoney.com/",
-            )
-        except RealtimeAggregateError:
-            return self.tencent_indices()
-        cache_meta = payload.get("_aggregate_cache") or {}
-        rows = list((payload.get("data") or {}).get("diff") or [])
-        result = []
-        for row in rows:
-            code = str(row.get("f12") or "")
-            if code not in {"000001", "399001", "399006"}:
-                continue
-            epoch = int(_number(row.get("f124")))
-            result.append(
-                {
-                    "code": code,
-                    "name": row.get("f14") or code,
-                    "price": _number(row.get("f2")),
-                    "change": _number(row.get("f3")),
-                    "change_amount": _number(row.get("f4")),
-                    "open": _number(row.get("f17")),
-                    "high": _number(row.get("f15")),
-                    "low": _number(row.get("f16")),
-                    "previous_close": _number(row.get("f18")),
-                    "amount_billion": round(_number(row.get("f6")) / 100000000, 2),
-                    "quote_time_epoch": epoch,
-                    "quote_time": (
-                        datetime.fromtimestamp(epoch).astimezone().isoformat(timespec="seconds")
-                        if epoch else ""
-                    ),
-                    "source": (
-                        "eastmoney_push2_cache" if cache_meta else "eastmoney_push2"
-                    ),
-                    "cache_age_seconds": cache_meta.get("age_seconds", 0),
-                }
-            )
-        if len(result) != 3:
-            raise RealtimeAggregateError(f"Eastmoney returned {len(result)}/3 indices")
-        return result
-
-    def tencent_indices(self) -> list[dict[str, Any]]:
-        raw, cache_age = self._get_text(
-            TENCENT_INDEX_URL,
-            referer="https://gu.qq.com/",
-            encoding="gb18030",
-        )
-        result = []
-        for line in raw.splitlines():
-            if '="' not in line:
-                continue
-            fields = line.split('="', 1)[1].rsplit('";', 1)[0].split("~")
-            if len(fields) < 38:
-                continue
-            code = fields[2]
-            if code not in {"000001", "399001", "399006"}:
-                continue
-            try:
-                quote_time = datetime.strptime(fields[30], "%Y%m%d%H%M%S").astimezone()
-            except ValueError as exc:
-                raise RealtimeAggregateError(
-                    f"Tencent returned invalid quote time for {code}"
-                ) from exc
-            result.append(
-                {
-                    "code": code,
-                    "name": fields[1] or code,
-                    "price": _number(fields[3]),
-                    "change": _number(fields[32]),
-                    "change_amount": _number(fields[31]),
-                    "open": _number(fields[5]),
-                    "high": _number(fields[33]),
-                    "low": _number(fields[34]),
-                    "previous_close": _number(fields[4]),
-                    "amount_billion": round(_number(fields[37]) / 10000, 2),
-                    "quote_time_epoch": int(quote_time.timestamp()),
-                    "quote_time": quote_time.isoformat(timespec="seconds"),
-                    "source": "tencent_qt_cache" if cache_age else "tencent_qt",
-                    "cache_age_seconds": cache_age,
-                }
-            )
-        if len(result) != 3:
-            raise RealtimeAggregateError(f"Tencent returned {len(result)}/3 indices")
-        return result
-
-    def eastmoney_sector(self, query: str) -> dict[str, Any]:
-        target = _normalize_sector(query)
-        candidates = self._eastmoney_sector_catalog()
-        matched = _match_sector(candidates, target)
-        if not matched:
-            raise RealtimeAggregateError(f"Eastmoney sector not found: {query}")
-        epoch = int(_number(matched.get("f124")))
-        return {
-            "code": matched.get("f12") or "",
-            "name": matched.get("f14") or query,
-            "price": _number(matched.get("f2")),
-            "change": _number(matched.get("f3")),
-            "change_amount": _number(matched.get("f4")),
-            "turnover_rate": _number(matched.get("f8")),
-            "up_count": int(_number(matched.get("f104"))),
-            "down_count": int(_number(matched.get("f105"))),
-            "leader": matched.get("f128") or "--",
-            "leader_code": matched.get("f140") or "",
-            "leading_pct": _number(matched.get("f136")),
-            "quote_time_epoch": epoch,
-            "quote_time": (
-                datetime.fromtimestamp(epoch).astimezone().isoformat(timespec="seconds")
-                if epoch else ""
-            ),
-            "source": "eastmoney_push2",
-            "match_query": query,
-        }
-
-    def _eastmoney_sector_catalog(self) -> list[dict[str, Any]]:
-        now = time.time()
-        with self._sector_cache_lock:
-            cached = self._sector_cache.get("eastmoney")
-        if cached and now - float(cached.get("created_at") or 0) < 600:
-            return list(cached.get("rows") or [])
-
-        def load_page(page: int) -> list[dict[str, Any]]:
-            payload = self._get_json(
-                EASTMONEY_SECTOR_URL,
-                {
-                    "pn": str(page),
-                    "pz": "100",
-                    "po": "1",
-                    "np": "1",
-                    "fltt": "2",
-                    "invt": "2",
-                    "fid": "f3",
-                    "fs": "m:90+t:2",
-                    "fields": "f12,f14,f2,f3,f4,f8,f104,f105,f128,f136,f140,f124",
-                },
-                referer="https://quote.eastmoney.com/center/boardlist.html",
-            )
-            return list((payload.get("data") or {}).get("diff") or [])
-
-        with ThreadPoolExecutor(max_workers=5) as executor:
-            pages = list(executor.map(load_page, range(1, 6)))
-        rows = [row for page in pages for row in page]
-        if not rows:
-            raise RealtimeAggregateError("Eastmoney sector catalog is empty")
-        with self._sector_cache_lock:
-            self._sector_cache["eastmoney"] = {"created_at": now, "rows": rows}
-        return rows
-
-    def ths_limit_pool(self) -> dict[str, Any]:
-        payload = self._get_json(
-            THS_LIMIT_URL,
-            {"page": "1", "limit": "3", "field": "199112"},
-            referer="https://data.10jqka.com.cn/limit_up/",
-        )
-        data = payload.get("data") or payload
-        return {
-            "available": True,
-            "keys": sorted(str(key) for key in data.keys()) if isinstance(data, dict) else [],
-            "source": "ths_web_dataapi",
-        }
-
-    def xgb_limit_pool(self) -> dict[str, Any]:
-        payload = self._get_json(
-            XGB_POOL_URL,
-            {"pool_name": "limit_up"},
-            referer="https://xuangubao.cn/",
-        )
-        data = payload.get("data") or {}
-        rows = data if isinstance(data, list) else data.get("pool") or data.get("list") or []
-        return {
-            "available": True,
-            "count": len(rows) if isinstance(rows, list) else 0,
-            "source": "xuangubao_web_api",
-        }
-
-    def _capture(self, operation):
-        started = time.perf_counter()
-        try:
-            value = operation()
-            return value, {
-                "ok": True,
-                "elapsed_ms": round((time.perf_counter() - started) * 1000),
-                "error": "",
-            }
-        except Exception as exc:
-            return None, {
-                "ok": False,
-                "elapsed_ms": round((time.perf_counter() - started) * 1000),
-                "error": str(exc)[:500],
-            }
-
-    def _get_json(
-        self,
-        url: str,
-        params: dict[str, str],
-        referer: str,
-    ) -> dict[str, Any]:
-        request_url = f"{url}?{urllib.parse.urlencode(params)}"
-        last_error: Exception | None = None
-        attempts = max(1, int(self.retry_attempts))
-        for attempt in range(attempts):
-            request = urllib.request.Request(
-                request_url,
-                headers={
-                    "Accept": "application/json,text/plain,*/*",
-                    "Connection": "close",
-                    "Referer": referer,
-                    "User-Agent": BROWSER_USER_AGENT,
-                },
-            )
-            try:
-                with urllib.request.urlopen(request, timeout=self.timeout) as response:
-                    content_type = response.headers.get("Content-Type", "")
-                    raw = response.read().decode("utf-8", errors="replace")
-                if "json" not in content_type.lower() and not raw.lstrip().startswith(("{", "[")):
-                    raise RealtimeAggregateError(
-                        f"non-JSON response: {raw[:120].strip()}"
-                    )
-                payload = json.loads(raw)
-                if not isinstance(payload, dict):
-                    raise RealtimeAggregateError("unexpected response shape")
-                if payload.get("rc") not in (None, 0):
-                    raise RealtimeAggregateError(f"provider rc={payload.get('rc')}")
-                with self._response_cache_lock:
-                    self._response_cache[request_url] = {
-                        "created_at": time.time(),
-                        "payload": copy.deepcopy(payload),
-                    }
-                return payload
-            except (
-                urllib.error.URLError,
-                TimeoutError,
-                ConnectionError,
-                OSError,
-                http.client.HTTPException,
-                json.JSONDecodeError,
-                RealtimeAggregateError,
-            ) as exc:
-                last_error = exc
-                if attempt + 1 < attempts and self.retry_delay_seconds > 0:
-                    time.sleep(self.retry_delay_seconds * (attempt + 1))
-
-        now = time.time()
-        with self._response_cache_lock:
-            cached = self._response_cache.get(request_url)
-        cache_age = now - float((cached or {}).get("created_at") or 0)
-        if cached and cache_age <= self.response_cache_ttl_seconds:
-            payload = copy.deepcopy(cached.get("payload") or {})
-            payload["_aggregate_cache"] = {"age_seconds": round(cache_age, 1)}
-            return payload
-        raise RealtimeAggregateError(f"request failed after {attempts} attempts: {last_error}") from last_error
-
-    def _get_text(
-        self,
-        request_url: str,
-        referer: str,
-        encoding: str = "utf-8",
-    ) -> tuple[str, float]:
-        cache_key = f"text:{request_url}"
-        last_error: Exception | None = None
-        attempts = max(1, int(self.retry_attempts))
-        for attempt in range(attempts):
-            request = urllib.request.Request(
-                request_url,
-                headers={
-                    "Accept": "text/plain,*/*",
-                    "Connection": "close",
-                    "Referer": referer,
-                    "User-Agent": BROWSER_USER_AGENT,
-                },
-            )
-            try:
-                with urllib.request.urlopen(request, timeout=self.timeout) as response:
-                    raw = response.read().decode(encoding, errors="replace")
-                if not raw.strip():
-                    raise RealtimeAggregateError("empty text response")
-                with self._response_cache_lock:
-                    self._response_cache[cache_key] = {
-                        "created_at": time.time(),
-                        "payload": raw,
-                    }
-                return raw, 0
-            except (
-                urllib.error.URLError,
-                TimeoutError,
-                ConnectionError,
-                OSError,
-                http.client.HTTPException,
-                RealtimeAggregateError,
-            ) as exc:
-                last_error = exc
-                if attempt + 1 < attempts and self.retry_delay_seconds > 0:
-                    time.sleep(self.retry_delay_seconds * (attempt + 1))
-
-        now = time.time()
-        with self._response_cache_lock:
-            cached = self._response_cache.get(cache_key)
-        cache_age = now - float((cached or {}).get("created_at") or 0)
-        if cached and cache_age <= self.response_cache_ttl_seconds:
-            return str(cached.get("payload") or ""), round(cache_age, 1)
-        raise RealtimeAggregateError(
-            f"text request failed after {attempts} attempts: {last_error}"
-        ) from last_error
-
-
-def _normalize_sector(value: Any) -> str:
-    text = str(value or "").strip().replace(" ", "")
-    for suffix in ("板块", "概念", "行业", "Ⅱ", "Ⅲ", "(A股)", "（A股）"):
-        text = text.replace(suffix, "")
-    aliases = {"元器件": "元件", "电子元器件": "元件"}
-    return aliases.get(text, text)
-
-
-def _match_sector(rows: list[dict[str, Any]], target: str) -> dict[str, Any] | None:
-    exact = [row for row in rows if _normalize_sector(row.get("f14")) == target]
-    if exact:
-        return min(exact, key=lambda row: len(str(row.get("f14") or "")))
-    fuzzy = [
-        row for row in rows
-        if target and (
-            target in _normalize_sector(row.get("f14"))
-            or _normalize_sector(row.get("f14")) in target
-        )
-    ]
-    return min(fuzzy, key=lambda row: len(_normalize_sector(row.get("f14")))) if fuzzy else None
-
-
-def _number(value: Any, default: float = 0.0) -> float:
-    try:
-        return float(value)
-    except (TypeError, ValueError):
-        return default

app/screener.py

@@ -10,7 +10,7 @@ from typing import Any
 
 from advanced_strategies import ADVANCED_CURATED_STRATEGIES
 from database import ReviewDatabase
-from sentiment_engine import build_sentiment_history, latest_contiguous_history
+from backend.features.sentiment.engine import build_sentiment_history, latest_contiguous_history
 from tushare_client import TushareClient, TushareError
 
 

app/sentiment_engine.py

@@ -1,496 +1,7 @@
-from __future__ import annotations
+"""Compatibility alias for the canonical sentiment engine implementation."""
 
-from copy import deepcopy
+import sys
-from statistics import mean, median
-from typing import Any
 
+from backend.features.sentiment import engine as _implementation
 
-COMPONENT_WEIGHTS = {
+sys.modules[__name__] = _implementation
-    "breadth": 20,
-    "limit_ecology": 25,
-    "profit_effect": 30,
-    "ladder_structure": 15,
-    "liquidity": 10,
-}
-
-SENTIMENT_ENGINE_VERSION = 2
-
-
-def _number(value: Any, default: float = 0.0) -> float:
-    try:
-        number = float(value)
-        return number if number == number else default
-    except (TypeError, ValueError):
-        return default
-
-
-def _clamp(value: float, lower: float = 0.0, upper: float = 100.0) -> float:
-    return min(upper, max(lower, value))
-
-
-def _linear(value: float, low: float, high: float) -> float:
-    if high <= low:
-        return 50.0
-    return _clamp((value - low) / (high - low) * 100)
-
-
-def _percentile(value: float, history: list[float]) -> float:
-    if not history:
-        return 50.0
-    below = sum(item < value for item in history)
-    equal = sum(item == value for item in history)
-    return _clamp((below + equal * 0.5) / len(history) * 100)
-
-
-def _adaptive_score(value: float, fixed: float, history: list[float]) -> float:
-    if len(history) < 20:
-        return fixed
-    return fixed * 0.25 + _percentile(value, history[-250:]) * 0.75
-
-
-def _trade_date(payload: dict[str, Any]) -> str:
-    meta = payload.get("meta") or {}
-    return str(meta.get("trade_date") or payload.get("_snapshot_date") or "").replace("-", "")
-
-
-def _deduplicate_snapshots(snapshots: list[dict[str, Any]]) -> list[dict[str, Any]]:
-    by_trade_date: dict[str, dict[str, Any]] = {}
-    for payload in snapshots:
-        trade_date = _trade_date(payload)
-        if trade_date:
-            by_trade_date[trade_date] = payload
-    return [by_trade_date[key] for key in sorted(by_trade_date)]
-
-
-def _snapshot_stats(payload: dict[str, Any]) -> dict[str, Any]:
-    overview = payload.get("overview") or {}
-    meta = payload.get("meta") or {}
-    limits = list(payload.get("limits") or [])
-    broken = list(payload.get("broken") or [])
-    down_limits = list(payload.get("down_limits") or [])
-    yesterday = list(payload.get("yesterday_limits") or [])
-
-    limit_up = len(limits) if limits else int(_number(overview.get("limit_up_count")))
-    broken_count = len(broken) if broken else int(_number(overview.get("broken_count")))
-    limit_down = len(down_limits) if down_limits else int(_number(overview.get("limit_down_count")))
-    streaks = [max(1, int(_number(row.get("streak"), 1))) for row in limits]
-    first_board = sum(streak == 1 for streak in streaks)
-    second_board = sum(streak == 2 for streak in streaks)
-    three_plus = sum(streak >= 3 for streak in streaks)
-    max_height = max(streaks, default=0)
-    present_levels = set(streaks)
-    ladder_completeness = (
-        sum(level in present_levels for level in range(1, max_height + 1)) / max_height * 100
-        if max_height else 0.0
-    )
-
-    up_count = int(_number(overview.get("up_count")))
-    down_count = int(_number(overview.get("down_count")))
-    flat_count = int(_number(overview.get("flat_count")))
-    active_count = up_count + down_count
-    breadth_ratio = up_count / max(active_count, 1) * 100
-    seal_rate = _number(overview.get("seal_rate"))
-    if not seal_rate and limit_up + broken_count:
-        seal_rate = limit_up / (limit_up + broken_count) * 100
-
-    previous_limit_count = len(yesterday)
-    previous_positive_count = sum(_number(row.get("current_change")) > 0 for row in yesterday)
-    previous_positive_rate = previous_positive_count / max(previous_limit_count, 1) * 100
-    advanced_count = sum(row.get("outcome") == "晋级" for row in yesterday)
-    advance_rate = advanced_count / max(previous_limit_count, 1) * 100
-    average_previous_change = (
-        mean(_number(row.get("current_change")) for row in yesterday) if yesterday else 0.0
-    )
-    median_previous_change = (
-        median(_number(row.get("current_change")) for row in yesterday) if yesterday else 0.0
-    )
-    severe_loss_count = sum(_number(row.get("current_change")) <= -5 for row in yesterday)
-    severe_loss_rate = severe_loss_count / max(previous_limit_count, 1) * 100
-    previous_down_count = sum(row.get("outcome") == "跌停" for row in yesterday)
-    high_previous = [row for row in yesterday if int(_number(row.get("prior_streak"), 1)) >= 2]
-    high_positive_rate = (
-        sum(_number(row.get("current_change")) > 0 for row in high_previous)
-        / max(len(high_previous), 1)
-        * 100
-    )
-
-    amount_billion = _number(overview.get("amount_billion"))
-    limit_amount_billion = sum(_number(row.get("amount_billion")) for row in limits)
-    return {
-        "trade_date": _trade_date(payload),
-        "previous_trade_date": str(meta.get("previous_trade_date") or "").replace("-", ""),
-        "up_count": up_count,
-        "down_count": down_count,
-        "flat_count": flat_count,
-        "breadth_ratio": round(breadth_ratio, 1),
-        "limit_up_count": limit_up,
-        "first_board_count": first_board,
-        "second_board_count": second_board,
-        "three_plus_count": three_plus,
-        "max_height": max_height,
-        "ladder_completeness": round(ladder_completeness, 1),
-        "broken_count": broken_count,
-        "limit_down_count": limit_down,
-        "seal_rate": round(seal_rate, 1),
-        "previous_limit_count": previous_limit_count,
-        "previous_positive_count": previous_positive_count,
-        "previous_positive_rate": round(previous_positive_rate, 1),
-        "advance_rate": round(advance_rate, 1),
-        "average_previous_change": round(average_previous_change, 2),
-        "median_previous_change": round(median_previous_change, 2),
-        "severe_loss_count": severe_loss_count,
-        "severe_loss_rate": round(severe_loss_rate, 1),
-        "previous_down_count": previous_down_count,
-        "high_positive_rate": round(high_positive_rate, 1),
-        "amount_billion": round(amount_billion, 1),
-        "limit_amount_billion": round(limit_amount_billion, 2),
-    }
-
-
-def _sentiment_label(score: float) -> str:
-    if score >= 80:
-        return "情绪高涨"
-    if score >= 60:
-        return "情绪偏强"
-    if score >= 40:
-        return "情绪中性"
-    if score >= 20:
-        return "情绪偏弱"
-    return "情绪冰点"
-
-
-def _phase_signal(score: float, momentum: float, profit_score: float) -> str:
-    if score < 25:
-        return "修复" if momentum > 3 else "冰点"
-    if score < 45:
-        return "修复" if momentum > 3 else "退潮"
-    if score >= 80:
-        return "高潮" if momentum >= -2 and profit_score >= 60 else "分化"
-    if score >= 65:
-        return "分化" if momentum < -3 or profit_score < 50 else "发酵"
-    if momentum < -5:
-        return "退潮"
-    return "发酵" if momentum >= 0 and profit_score >= 45 else "分化"
-
-
-def _confirmed_phase(
-    previous: dict[str, Any] | None,
-    score: float,
-    day_change: float,
-    systemic_health: float,
-    profit_score: float,
-    ecology_score: float,
-    phase_signal: str,
-    extreme_ice: bool,
-    fermentation_signal_count: int,
-) -> tuple[str, str]:
-    if previous is None:
-        return phase_signal, "首个连续交易日，采用原始阶段信号"
-    previous_phase = str(previous.get("phase") or phase_signal)
-    if extreme_ice:
-        return "冰点", "市场宽度与跌停数量触发极端冰点"
-
-    recovery = day_change >= 6 and score >= 25 and systemic_health >= 24
-    fermentation_confirmed = fermentation_signal_count >= 2
-    climax_ready = (
-        score >= 80
-        and profit_score >= 60
-        and systemic_health >= 60
-        and ecology_score >= 70
-    )
-
-    if previous_phase == "冰点":
-        return ("修复", "冰点后首次有效回升") if recovery else ("冰点", "冰点尚未形成有效修复")
-
-    if previous_phase == "退潮":
-        if score < 25:
-            return "冰点", "退潮继续下探至冰点区间"
-        return ("修复", "退潮后出现有效回升") if recovery else ("退潮", "退潮尚未形成有效修复")
-
-    if previous_phase == "修复":
-        if score < 25:
-            return "冰点", "修复失败并重新跌入冰点区间"
-        if day_change <= -6 and score < 45:
-            return "退潮", "修复失败且温度显著回落"
-        if fermentation_confirmed:
-            return "发酵", "发酵条件连续两个交易日成立"
-        return "修复", "修复延续，等待发酵确认"
-
-    if previous_phase == "发酵":
-        if score < 25:
-            return "冰点", "发酵阶段出现极端情绪坍塌"
-        if score < 45 and (day_change < 0 or systemic_health < 35):
-            return "退潮", "发酵阶段温度与系统健康度同步转弱"
-        if climax_ready:
-            return "高潮", "温度、赚钱效应与涨停生态共同达到高潮条件"
-        if phase_signal in {"分化", "退潮"} or day_change <= -6:
-            return "分化", "发酵阶段出现降温或赚钱效应弱化"
-        return "发酵", "发酵状态延续"
-
-    if previous_phase == "高潮":
-        if score < 25:
-            return "冰点", "高潮后出现极端情绪坍塌"
-        if climax_ready:
-            return "高潮", "高潮条件继续成立"
-        if score < 45 or systemic_health < 30:
-            return "退潮", "高潮后风险快速释放"
-        return "分化", "高潮条件消退，进入分化"
-
-    if previous_phase == "分化":
-        if score < 25:
-            return "冰点", "分化继续恶化至冰点区间"
-        if score < 45 or systemic_health < 30:
-            return "退潮", "分化后温度或系统健康度继续下降"
-        if fermentation_confirmed:
-            return "发酵", "分化转强条件连续两个交易日成立"
-        return "分化", "分化延续，等待方向确认"
-
-    return phase_signal, "采用原始阶段信号"
-
-
-def build_sentiment_history(snapshots: list[dict[str, Any]]) -> list[dict[str, Any]]:
-    payloads = _deduplicate_snapshots(snapshots)
-    raw_rows = [_snapshot_stats(payload) for payload in payloads]
-    results: list[dict[str, Any]] = []
-
-    for index, stats in enumerate(raw_rows):
-        previous = raw_rows[:index]
-        limit_history = [float(row["limit_up_count"]) for row in previous]
-        down_limit_history = [float(row["limit_down_count"]) for row in previous]
-        height_history = [float(row["max_height"]) for row in previous]
-        three_plus_history = [float(row["three_plus_count"]) for row in previous]
-        amount_history = [float(row["amount_billion"]) for row in previous[-20:] if row["amount_billion"]]
-
-        breadth_score = _clamp(float(stats["breadth_ratio"]))
-        limit_strength = _adaptive_score(
-            float(stats["limit_up_count"]),
-            _linear(float(stats["limit_up_count"]), 10, 100),
-            limit_history,
-        )
-        down_relief = 100 - _adaptive_score(
-            float(stats["limit_down_count"]),
-            _linear(float(stats["limit_down_count"]), 0, 50),
-            down_limit_history,
-        )
-        seal_quality = _linear(float(stats["seal_rate"]), 35, 90)
-        systemic_health = breadth_score * 0.60 + down_relief * 0.40
-        systemic_gate = 1.0 if systemic_health >= 35 else 0.35 + systemic_health / 35 * 0.65
-        ecology_base_score = limit_strength * 0.35 + seal_quality * 0.35 + down_relief * 0.30
-        # Systemic risk is applied once to the final temperature. Reapplying it here
-        # would count market breadth and limit-down pressure twice.
-        limit_ecology_score = ecology_base_score
-
-        if stats["previous_limit_count"]:
-            positive_score = float(stats["previous_positive_rate"])
-            average_change_score = _clamp(50 + float(stats["average_previous_change"]) * 6)
-            median_change_score = _clamp(50 + float(stats["median_previous_change"]) * 7)
-            advance_score = _clamp(float(stats["advance_rate"]) * 2.5)
-            severe_loss_safety = _clamp(100 - float(stats["severe_loss_rate"]) * 3)
-            down_safety = _clamp(100 - float(stats["previous_down_count"]) / stats["previous_limit_count"] * 700)
-            tail_safety_score = severe_loss_safety * 0.70 + down_safety * 0.30
-            profit_effect_score = (
-                positive_score * 0.30
-                + median_change_score * 0.25
-                + average_change_score * 0.10
-                + advance_score * 0.20
-                + tail_safety_score * 0.15
-            )
-        else:
-            profit_effect_score = 50.0
-
-        max_height_score = _adaptive_score(
-            float(stats["max_height"]),
-            _linear(float(stats["max_height"]), 1, 7),
-            height_history,
-        )
-        continuation_rate = (
-            (float(stats["second_board_count"]) + float(stats["three_plus_count"]))
-            / max(float(stats["limit_up_count"]), 1)
-            * 100
-        )
-        three_plus_density = float(stats["three_plus_count"]) / max(float(stats["limit_up_count"]), 1) * 100
-        three_plus_score = _adaptive_score(
-            float(stats["three_plus_count"]),
-            _clamp(three_plus_density * 5),
-            three_plus_history,
-        )
-        ladder_structure_score = (
-            max_height_score * 0.30
-            + _clamp(continuation_rate * 3) * 0.25
-            + three_plus_score * 0.25
-            + float(stats["ladder_completeness"]) * 0.20
-        )
-
-        amount_baseline = mean(amount_history) if amount_history else float(stats["amount_billion"] or 1)
-        amount_ratio = float(stats["amount_billion"]) / max(amount_baseline, 1)
-        amount_score = _clamp(50 + (amount_ratio - 1) * 100)
-        limit_amount_share = float(stats["limit_amount_billion"]) / max(float(stats["amount_billion"]), 1) * 100
-        liquidity_score = amount_score * 0.70 + _clamp(limit_amount_share * 20) * 0.30
-
-        component_scores = {
-            "breadth": breadth_score,
-            "limit_ecology": limit_ecology_score,
-            "profit_effect": profit_effect_score,
-            "ladder_structure": ladder_structure_score,
-            "liquidity": liquidity_score,
-        }
-        raw_score = sum(component_scores[key] * weight / 100 for key, weight in COMPONENT_WEIGHTS.items())
-        score = round(
-            raw_score * systemic_gate
-        )
-        extreme_ice = float(stats["breadth_ratio"]) <= 15 and float(stats["limit_down_count"]) >= 100
-        if extreme_ice:
-            score = min(score, 15)
-        elif float(stats["breadth_ratio"]) <= 25 and float(stats["limit_down_count"]) >= 50:
-            score = min(score, 24)
-        previous_scores: list[float] = []
-        expected_date = str(stats.get("previous_trade_date") or "")
-        for prior_result in reversed(results):
-            if not expected_date or str(prior_result.get("trade_date") or "") != expected_date:
-                break
-            previous_scores.append(float(prior_result["score"]))
-            expected_date = str(prior_result.get("previous_trade_date") or "")
-            if len(previous_scores) == 3:
-                break
-        momentum = score - mean(previous_scores) if previous_scores else 0.0
-        direction = "升温" if momentum > 3 else "降温" if momentum < -3 else "持平"
-        normalization = "历史百分位" if len(previous) >= 20 else "固定锚点"
-        previous_result = (
-            results[-1]
-            if results and str(stats.get("previous_trade_date") or "") == str(results[-1].get("trade_date") or "")
-            else None
-        )
-        day_change = score - float(previous_result["score"]) if previous_result else 0.0
-        ema_score = round(
-            score if not previous_result
-            else score * 0.5 + float(previous_result.get("ema_score", previous_result["score"])) * 0.5,
-            1,
-        )
-        phase_signal = _phase_signal(score, momentum, profit_effect_score)
-        fermentation_ready = (
-            phase_signal == "发酵"
-            and score >= 45
-            and profit_effect_score >= 45
-            and systemic_health >= 35
-            and not extreme_ice
-        )
-        previous_fermentation_count = int(previous_result.get("fermentation_signal_count") or 0) if previous_result else 0
-        fermentation_signal_count = previous_fermentation_count + 1 if fermentation_ready else 0
-        phase, transition_reason = _confirmed_phase(
-            previous_result,
-            score,
-            day_change,
-            systemic_health,
-            profit_effect_score,
-            limit_ecology_score,
-            phase_signal,
-            extreme_ice,
-            fermentation_signal_count,
-        )
-        previous_phase = str(previous_result.get("phase") or "") if previous_result else ""
-        if phase not in {"修复", "分化"}:
-            fermentation_signal_count = 0
-        elif phase == "分化" and previous_phase != "分化":
-            fermentation_signal_count = 0
-
-        components = {
-            "breadth": {
-                "label": "市场宽度",
-                "score": round(breadth_score, 1),
-                "weight": COMPONENT_WEIGHTS["breadth"],
-                "summary": f"上涨占比 {stats['breadth_ratio']:.1f}%",
-            },
-            "limit_ecology": {
-                "label": "涨停生态",
-                "score": round(limit_ecology_score, 1),
-                "weight": COMPONENT_WEIGHTS["limit_ecology"],
-                "summary": (
-                    f"涨停 {stats['limit_up_count']} · 跌停 {stats['limit_down_count']} · "
-                    f"封板 {stats['seal_rate']:.1f}%"
-                ),
-            },
-            "profit_effect": {
-                "label": "赚钱效应",
-                "score": round(profit_effect_score, 1),
-                "weight": COMPONENT_WEIGHTS["profit_effect"],
-                "summary": (
-                    f"昨涨停红盘 {stats['previous_positive_rate']:.1f}% · "
-                    f"中位 {stats['median_previous_change']:+.2f}% · "
-                    f"重亏 {stats['severe_loss_rate']:.1f}%"
-                    if stats["previous_limit_count"] else "缺少前一交易日样本"
-                ),
-            },
-            "ladder_structure": {
-                "label": "连板结构",
-                "score": round(ladder_structure_score, 1),
-                "weight": COMPONENT_WEIGHTS["ladder_structure"],
-                "summary": f"最高 {stats['max_height']} 板 · 三板以上 {stats['three_plus_count']} 家",
-            },
-            "liquidity": {
-                "label": "成交活跃度",
-                "score": round(liquidity_score, 1),
-                "weight": COMPONENT_WEIGHTS["liquidity"],
-                "summary": f"成交 {stats['amount_billion']:.1f} 亿 · 均值比 {amount_ratio:.2f}",
-            },
-        }
-        results.append(
-            {
-                **stats,
-                "score": score,
-                "ema_score": ema_score,
-                "label": _sentiment_label(score),
-                "phase": phase,
-                "phase_signal": phase_signal,
-                "transition_reason": transition_reason,
-                "fermentation_signal_count": fermentation_signal_count,
-                "day_change": round(day_change, 1),
-                "direction": direction,
-                "momentum": round(momentum, 1),
-                "normalization": "250日历史百分位" if len(previous) >= 20 else normalization,
-                "history_days": len(previous) + 1,
-                "systemic_health": round(systemic_health, 1),
-                "risk_multiplier": round(systemic_gate, 3),
-                "components": components,
-            }
-        )
-    return results
-
-
-def latest_contiguous_history(series: list[dict[str, Any]]) -> list[dict[str, Any]]:
-    if not series:
-        return []
-    contiguous = [series[-1]]
-    for row in reversed(series[:-1]):
-        expected_previous = str(contiguous[0].get("previous_trade_date") or "")
-        if not expected_previous or expected_previous != str(row.get("trade_date") or ""):
-            break
-        contiguous.insert(0, row)
-    return contiguous
-
-
-def apply_sentiment_to_dashboard(
-    dashboard: dict[str, Any],
-    historical_snapshots: list[dict[str, Any]] | None = None,
-) -> dict[str, Any]:
-    result = deepcopy(dashboard)
-    history = list(historical_snapshots or [])
-    history.append(result)
-    series = build_sentiment_history(history)
-    target_date = _trade_date(result)
-    sentiment = next((row for row in reversed(series) if row["trade_date"] == target_date), None)
-    if not sentiment:
-        return result
-    overview = dict(result.get("overview") or {})
-    overview.update(
-        {
-            "sentiment_score": sentiment["score"],
-            "sentiment_trend_score": sentiment["ema_score"],
-            "sentiment_label": sentiment["label"],
-            "sentiment_phase": sentiment["phase"],
-            "sentiment_direction": sentiment["direction"],
-            "sentiment_components": sentiment["components"],
-            "sentiment_engine_version": SENTIMENT_ENGINE_VERSION,
-        }
-    )
-    result["overview"] = overview
-    return result

app/tests/test_data_gateway.py

@@ -48,7 +48,11 @@ class DataGatewayTests(unittest.TestCase):
         from pathlib import Path
 
         source = (
-            Path(__file__).resolve().parents[1] / "backend" / "application.py"
+            Path(__file__).resolve().parents[1]
+            / "backend"
+            / "features"
+            / "market"
+            / "service.py"
         ).read_text(encoding="utf-8")
         self.assertEqual(source.count("TushareClient(self.token)"), 1)
         self.assertIn("return gateway.tushare()", source)

app/tests/test_preservation_slice_ladder_rotation.py

@@ -0,0 +1,92 @@
+from __future__ import annotations
+
+import ast
+import hashlib
+import unittest
+from pathlib import Path
+
+
+APP_ROOT = Path(__file__).resolve().parents[1]
+ORIGINAL_ROOT = APP_ROOT.parent
+
+ROTATION_METHODS = {
+    "rotation_history",
+    "rotation_sector_members",
+}
+LADDER_ROTATION_BUILDERS = {
+    "_build_ladders",
+    "_build_sector_rotation",
+}
+
+
+def class_methods(path: Path, class_name: str) -> dict[str, str]:
+    tree = ast.parse(path.read_text(encoding="utf-8"), filename=str(path))
+    owner = next(
+        node
+        for node in tree.body
+        if isinstance(node, ast.ClassDef) and node.name == class_name
+    )
+    return {
+        node.name: ast.dump(node, include_attributes=False)
+        for node in owner.body
+        if isinstance(node, (ast.FunctionDef, ast.AsyncFunctionDef))
+    }
+
+
+def top_level_functions(path: Path) -> dict[str, str]:
+    tree = ast.parse(path.read_text(encoding="utf-8"), filename=str(path))
+    return {
+        node.name: ast.dump(node, include_attributes=False)
+        for node in tree.body
+        if isinstance(node, (ast.FunctionDef, ast.AsyncFunctionDef))
+        and node.name in LADDER_ROTATION_BUILDERS
+    }
+
+
+def sha256(path: Path) -> str:
+    return hashlib.sha256(path.read_bytes()).hexdigest()
+
+
+class LadderRotationSliceSourceEquivalenceTests(unittest.TestCase):
+    def test_rotation_service_methods_are_exact_original_ast(self) -> None:
+        original = class_methods(ORIGINAL_ROOT / "server.py", "DashboardService")
+        migrated = class_methods(
+            APP_ROOT / "backend" / "features" / "rotation" / "service.py",
+            "RotationServiceMixin",
+        )
+        self.assertEqual(set(migrated), ROTATION_METHODS)
+        for name in sorted(ROTATION_METHODS):
+            self.assertEqual(migrated[name], original[name], name)
+
+    def test_dashboard_service_no_longer_duplicates_rotation_methods(self) -> None:
+        remaining = class_methods(
+            APP_ROOT / "backend" / "application.py", "DashboardService"
+        )
+        self.assertTrue(ROTATION_METHODS.isdisjoint(remaining))
+
+    def test_ladder_and_rotation_builders_are_exact_original_ast(self) -> None:
+        self.assertEqual(
+            top_level_functions(ORIGINAL_ROOT / "tushare_client.py"),
+            top_level_functions(
+                APP_ROOT / "backend" / "data" / "providers" / "tushare_client.py"
+            ),
+        )
+
+    def test_api_and_frontend_assets_are_unchanged(self) -> None:
+        for relative in (
+            "config/api.config.json",
+            "static/index.html",
+            "static/app.js",
+            "static/styles.css",
+            "static/pages/ladder/page.js",
+            "static/pages/rotation/page.js",
+        ):
+            self.assertEqual(
+                sha256(APP_ROOT / relative),
+                sha256(ORIGINAL_ROOT / relative),
+                relative,
+            )
+
+
+if __name__ == "__main__":
+    unittest.main()

app/tests/test_preservation_slice_market.py

@@ -0,0 +1,162 @@
+from __future__ import annotations
+
+import ast
+import hashlib
+import unittest
+from pathlib import Path
+
+import chart_data_provider
+import ifind_client
+import realtime_aggregator
+import tushare_client
+from backend.data import realtime
+from backend.data.providers import ifind_client as canonical_ifind
+from backend.data.providers import tushare_client as canonical_tushare
+from backend.features.market import charts
+
+
+APP_ROOT = Path(__file__).resolve().parents[1]
+ORIGINAL_ROOT = APP_ROOT.parent
+
+MARKET_METHODS = {
+    "_tushare_client",
+    "get_dashboard",
+    "_dashboard_sentiment_ready",
+    "_display_compact_date",
+    "_carry_dashboard",
+    "_realtime_snapshot_due",
+    "sync_dashboard",
+    "realtime_aggregate_health",
+    "_search_market_directory",
+    "_search_match_score",
+    "search_entities",
+    "get_search_detail",
+    "get_intraday_chart",
+    "_ths_search_detail",
+    "_index_search_detail",
+    "get_stock_detail",
+    "_stock_detail_bar_date",
+    "_stock_detail_cache_needs_refresh",
+    "_prepare_stock_detail",
+    "_sanitize_stock_detail_prices",
+    "_valid_realtime_stock_quote",
+    "_ifind_realtime_stock_quote",
+    "_merge_realtime_stock_detail",
+    "get_stock_preview",
+    "backfill",
+    "_stock_identity",
+    "_enrich_stock_detail",
+    "_with_storage",
+    "_record_count",
+}
+
+MARKET_REPOSITORY_METHODS = {
+    "get_snapshot",
+    "get_latest_real_snapshot",
+    "save_snapshot",
+    "get_data_snapshot",
+    "get_latest_data_snapshot",
+    "save_data_snapshot",
+    "search_stock_master",
+    "list_snapshot_payloads",
+    "start_sync",
+    "finish_sync",
+    "status",
+}
+
+
+def class_methods(path: Path, class_name: str) -> dict[str, str]:
+    tree = ast.parse(path.read_text(encoding="utf-8"), filename=str(path))
+    owner = next(
+        node
+        for node in tree.body
+        if isinstance(node, ast.ClassDef) and node.name == class_name
+    )
+    return {
+        node.name: ast.dump(node, include_attributes=False)
+        for node in owner.body
+        if isinstance(node, (ast.FunctionDef, ast.AsyncFunctionDef))
+    }
+
+
+def sha256(path: Path) -> str:
+    return hashlib.sha256(path.read_bytes()).hexdigest()
+
+
+def top_level_definitions(path: Path) -> dict[str, str]:
+    tree = ast.parse(path.read_text(encoding="utf-8"), filename=str(path))
+    return {
+        node.name: ast.dump(node, include_attributes=False)
+        for node in tree.body
+        if isinstance(node, (ast.ClassDef, ast.FunctionDef, ast.AsyncFunctionDef))
+    }
+
+
+class MarketSliceSourceEquivalenceTests(unittest.TestCase):
+    def test_market_service_methods_are_exact_original_ast(self) -> None:
+        original = class_methods(ORIGINAL_ROOT / "server.py", "DashboardService")
+        migrated = class_methods(
+            APP_ROOT / "backend" / "features" / "market" / "service.py",
+            "MarketServiceMixin",
+        )
+        self.assertEqual(set(migrated), MARKET_METHODS)
+        for name in sorted(MARKET_METHODS):
+            self.assertEqual(migrated[name], original[name], name)
+
+    def test_market_repository_methods_are_exact_original_ast(self) -> None:
+        original = class_methods(ORIGINAL_ROOT / "database.py", "ReviewDatabase")
+        migrated = class_methods(
+            APP_ROOT / "backend" / "features" / "market" / "repository.py",
+            "MarketRepositoryMixin",
+        )
+        self.assertEqual(set(migrated), MARKET_REPOSITORY_METHODS)
+        for name in sorted(MARKET_REPOSITORY_METHODS):
+            self.assertEqual(migrated[name], original[name], name)
+
+    def test_original_classes_no_longer_duplicate_moved_methods(self) -> None:
+        remaining_service = class_methods(APP_ROOT / "backend" / "application.py", "DashboardService")
+        remaining_database = class_methods(APP_ROOT / "database.py", "ReviewDatabase")
+        self.assertTrue(MARKET_METHODS.isdisjoint(remaining_service))
+        self.assertTrue(MARKET_REPOSITORY_METHODS.isdisjoint(remaining_database))
+
+    def test_provider_compatibility_modules_are_canonical_aliases(self) -> None:
+        self.assertIs(tushare_client.TushareClient, canonical_tushare.TushareClient)
+        self.assertIs(ifind_client.IfindHttpClient, canonical_ifind.IfindHttpClient)
+        self.assertIs(realtime_aggregator.WebRealtimeAggregator, realtime.WebRealtimeAggregator)
+        self.assertIs(chart_data_provider.MarketChartClient, charts.MarketChartClient)
+
+    def test_provider_logic_is_the_original_implementation(self) -> None:
+        exact_moves = (
+            ("ifind_client.py", "backend/data/providers/ifind_client.py"),
+            ("realtime_aggregator.py", "backend/data/realtime.py"),
+        )
+        for original, migrated in exact_moves:
+            self.assertEqual(sha256(ORIGINAL_ROOT / original), sha256(APP_ROOT / migrated))
+        self.assertEqual(
+            top_level_definitions(ORIGINAL_ROOT / "tushare_client.py"),
+            top_level_definitions(APP_ROOT / "backend/data/providers/tushare_client.py"),
+        )
+        self.assertEqual(
+            top_level_definitions(ORIGINAL_ROOT / "chart_data_provider.py"),
+            top_level_definitions(APP_ROOT / "backend/features/market/charts.py"),
+        )
+
+    def test_unchanged_frontend_assets_match_the_original(self) -> None:
+        for relative in (
+            "index.html",
+            "app.js",
+            "styles.css",
+            "renovation.css",
+            "redesign-v2.css",
+            "theme.css",
+            "wentian-v2.css",
+        ):
+            self.assertEqual(
+                sha256(APP_ROOT / "static" / relative),
+                sha256(ORIGINAL_ROOT / "static" / relative),
+                relative,
+            )
+
+
+if __name__ == "__main__":
+    unittest.main()

app/tests/test_preservation_slice_sentiment_pools.py

@@ -0,0 +1,114 @@
+from __future__ import annotations
+
+import ast
+import hashlib
+import unittest
+from pathlib import Path
+
+import sentiment_engine
+from backend.features.sentiment import engine as canonical_engine
+
+
+APP_ROOT = Path(__file__).resolve().parents[1]
+ORIGINAL_ROOT = APP_ROOT.parent
+
+SENTIMENT_METHODS = {
+    "_enrich_dashboard_sentiment",
+    "sentiment_history",
+}
+POOL_METHODS = {
+    "save_reason",
+    "_apply_reason_overrides",
+    "_schedule_ifind_event_enrichment",
+    "_refresh_ifind_event_enrichment",
+    "_normalize_ifind_event_time",
+    "_merge_ifind_event_enrichment",
+}
+POOL_REPOSITORY_METHODS = {
+    "save_reason_override",
+    "reason_overrides",
+}
+
+
+def class_methods(path: Path, class_name: str) -> dict[str, str]:
+    tree = ast.parse(path.read_text(encoding="utf-8"), filename=str(path))
+    owner = next(
+        node
+        for node in tree.body
+        if isinstance(node, ast.ClassDef) and node.name == class_name
+    )
+    return {
+        node.name: ast.dump(node, include_attributes=False)
+        for node in owner.body
+        if isinstance(node, (ast.FunctionDef, ast.AsyncFunctionDef))
+    }
+
+
+def sha256(path: Path) -> str:
+    return hashlib.sha256(path.read_bytes()).hexdigest()
+
+
+class SentimentPoolSliceSourceEquivalenceTests(unittest.TestCase):
+    def test_sentiment_service_methods_are_exact_original_ast(self) -> None:
+        original = class_methods(ORIGINAL_ROOT / "server.py", "DashboardService")
+        migrated = class_methods(
+            APP_ROOT / "backend" / "features" / "sentiment" / "service.py",
+            "SentimentServiceMixin",
+        )
+        self.assertEqual(set(migrated), SENTIMENT_METHODS)
+        for name in sorted(SENTIMENT_METHODS):
+            self.assertEqual(migrated[name], original[name], name)
+
+    def test_pool_service_methods_are_exact_original_ast(self) -> None:
+        original = class_methods(ORIGINAL_ROOT / "server.py", "DashboardService")
+        migrated = class_methods(
+            APP_ROOT / "backend" / "features" / "pools" / "service.py",
+            "PoolServiceMixin",
+        )
+        self.assertEqual(set(migrated), POOL_METHODS)
+        for name in sorted(POOL_METHODS):
+            self.assertEqual(migrated[name], original[name], name)
+
+    def test_pool_repository_methods_are_exact_original_ast(self) -> None:
+        original = class_methods(ORIGINAL_ROOT / "database.py", "ReviewDatabase")
+        migrated = class_methods(
+            APP_ROOT / "backend" / "features" / "pools" / "repository.py",
+            "PoolRepositoryMixin",
+        )
+        self.assertEqual(set(migrated), POOL_REPOSITORY_METHODS)
+        for name in sorted(POOL_REPOSITORY_METHODS):
+            self.assertEqual(migrated[name], original[name], name)
+
+    def test_original_classes_no_longer_duplicate_moved_methods(self) -> None:
+        remaining_service = class_methods(
+            APP_ROOT / "backend" / "application.py", "DashboardService"
+        )
+        remaining_database = class_methods(APP_ROOT / "database.py", "ReviewDatabase")
+        self.assertTrue((SENTIMENT_METHODS | POOL_METHODS).isdisjoint(remaining_service))
+        self.assertTrue(POOL_REPOSITORY_METHODS.isdisjoint(remaining_database))
+
+    def test_sentiment_engine_is_exact_original_with_legacy_alias(self) -> None:
+        self.assertEqual(
+            sha256(ORIGINAL_ROOT / "sentiment_engine.py"),
+            sha256(APP_ROOT / "backend" / "features" / "sentiment" / "engine.py"),
+        )
+        self.assertIs(sentiment_engine, canonical_engine)
+
+    def test_api_and_frontend_assets_are_unchanged(self) -> None:
+        for relative in (
+            "config/api.config.json",
+            "static/index.html",
+            "static/app.js",
+            "static/styles.css",
+            "static/pages/sentiment/page.js",
+            "static/pages/pools/page.js",
+        ):
+            self.assertEqual(
+                sha256(APP_ROOT / relative),
+                sha256(ORIGINAL_ROOT / relative),
+                relative,
+            )
+
+
+if __name__ == "__main__":
+    unittest.main()

app/tests/test_stock_detail_realtime.py

@@ -90,8 +90,8 @@ class StockDetailRealtimeTests(unittest.TestCase):
             "moneyflow": {},
         }
 
-        with patch("backend.application.datetime", FixedMarketDatetime), patch(
+        with patch("backend.features.market.service.datetime", FixedMarketDatetime), patch(
-            "backend.application.TushareClient", RealtimeClientStub
+            "backend.features.market.service.TushareClient", RealtimeClientStub
         ):
             result = self.service._prepare_stock_detail(cached, "002141", today)
 
@@ -112,8 +112,8 @@ class StockDetailRealtimeTests(unittest.TestCase):
             "stock": {"code": "002141", "price": 10, "change": 1.2},
             "prices": [{"trade_date": historical, "close": 10, "change": 1.2}],
         }
-        with patch("backend.application.datetime", FixedMarketDatetime), patch(
+        with patch("backend.features.market.service.datetime", FixedMarketDatetime), patch(
-            "backend.application.TushareClient", RealtimeClientStub
+            "backend.features.market.service.TushareClient", RealtimeClientStub
         ):
             result = self.service._prepare_stock_detail(payload, "002141", historical)
 
@@ -151,8 +151,8 @@ class StockDetailRealtimeTests(unittest.TestCase):
                 },
             ],
         }
-        with patch("backend.application.datetime", FixedPreopenDatetime), patch(
+        with patch("backend.features.market.service.datetime", FixedPreopenDatetime), patch(
-            "backend.application.TushareClient", RealtimeClientStub
+            "backend.features.market.service.TushareClient", RealtimeClientStub
         ):
             result = self.service._prepare_stock_detail(payload, "002141", today)
 

app/tools/move_class_methods.py

@@ -0,0 +1,76 @@
+from __future__ import annotations
+
+import argparse
+import ast
+from pathlib import Path
+
+
+MARKER = "    # PRESERVATION_METHODS\n"
+
+
+def method_span(node: ast.FunctionDef | ast.AsyncFunctionDef) -> tuple[int, int]:
+    start = min((decorator.lineno for decorator in node.decorator_list), default=node.lineno)
+    if node.end_lineno is None:
+        raise ValueError(f"Missing end position for {node.name}")
+    return start - 1, node.end_lineno
+
+
+def move_methods(
+    source_path: Path,
+    class_name: str,
+    target_path: Path,
+    method_names: list[str],
+) -> None:
+    source = source_path.read_text(encoding="utf-8")
+    tree = ast.parse(source, filename=str(source_path))
+    owner = next(
+        (
+            node
+            for node in tree.body
+            if isinstance(node, ast.ClassDef) and node.name == class_name
+        ),
+        None,
+    )
+    if owner is None:
+        raise ValueError(f"Class not found: {class_name}")
+
+    methods = {
+        node.name: node
+        for node in owner.body
+        if isinstance(node, (ast.FunctionDef, ast.AsyncFunctionDef))
+    }
+    missing = [name for name in method_names if name not in methods]
+    if missing:
+        raise ValueError(f"Methods not found in {class_name}: {', '.join(missing)}")
+
+    lines = source.splitlines(keepends=True)
+    ordered = sorted((methods[name] for name in method_names), key=lambda node: node.lineno)
+    blocks = ["".join(lines[start:end]).rstrip() for start, end in map(method_span, ordered)]
+
+    for start, end in sorted(map(method_span, ordered), reverse=True):
+        del lines[start:end]
+        while start < len(lines) - 1 and lines[start] == "\n" and lines[start + 1] == "\n":
+            del lines[start]
+
+    target = target_path.read_text(encoding="utf-8")
+    if target.count(MARKER) != 1:
+        raise ValueError(f"Target must contain exactly one method marker: {target_path}")
+    target = target.replace(MARKER, "\n\n".join(blocks) + "\n")
+
+    source_path.write_text("".join(lines), encoding="utf-8")
+    target_path.write_text(target, encoding="utf-8")
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser(description="Mechanically move class methods between modules")
+    parser.add_argument("--source", type=Path, required=True)
+    parser.add_argument("--class-name", required=True)
+    parser.add_argument("--target", type=Path, required=True)
+    parser.add_argument("methods", nargs="+")
+    args = parser.parse_args()
+    move_methods(args.source, args.class_name, args.target, args.methods)
+
+
+if __name__ == "__main__":
+    main()
+

docs/migration/evidence/slice-02/README.md

@@ -0,0 +1,61 @@
+# 切片 02：公共行情、搜索、详情、图表与数据网关
+
+> 基线：`4002f09`（切片 01）  
+> 回档标签：`xiaobai-preservation-slice-02-20260731`  
+> 结论：源码、API、数据库、真实页面和浏览器回归通过；最终视觉仍等待全站人工验收
+
+## 1. 原实现归位
+
+本切片从原版副本机械移动公共行情纵向链路，没有从 `next/` 取用代码，也没有修改计算逻辑。
+
+| 原位置 | 新的唯一实现位置 | 原位置兼容 |
+|---|---|---|
+| `app/backend/application.py` 的 30 个总览、搜索、详情、图表方法 | `app/backend/features/market/service.py` | `DashboardService` 继承 `MarketServiceMixin` |
+| `app/database.py` 的 11 个行情快照、搜索目录、同步记录方法 | `app/backend/features/market/repository.py` | `ReviewDatabase` 继承 `MarketRepositoryMixin` |
+| `app/tushare_client.py` | `app/backend/data/providers/tushare_client.py` | 根模块为同一模块对象的兼容别名 |
+| `app/ifind_client.py` | `app/backend/data/providers/ifind_client.py` | 根模块为同一模块对象的兼容别名 |
+| `app/realtime_aggregator.py` | `app/backend/data/realtime.py` | 根模块为同一模块对象的兼容别名 |
+| `app/chart_data_provider.py` | `app/backend/features/market/charts.py` | 根模块为同一模块对象的兼容别名 |
+
+`app/tools/move_class_methods.py` 使用 Python AST 确定方法及装饰器的源码边界，只移动原文本片段。
+该工具会在缺失方法、目标标记不唯一或源码无法解析时停止，供后续切片继续复用。
+
+## 2. 等价证据
+
+- `test_preservation_slice_market.py` 对 30 个业务方法和 11 个 Repository 方法逐项执行无位置信息
+  AST 比较，全部与根目录原版 `server.py`、`database.py` 完全相同。
+- Tushare、iFinD 和实时观察器文件与原版 SHA-256 完全相同；图表模块全部类和函数 AST 与原版相同，
+  仅内部导入改为新规范位置。
+- 四个根级兼容模块与新模块共享同一类对象，旧导入和旧 monkeypatch 路径继续有效。
+- `config/api.config.json`、API路径、鉴权角色、错误结构和数据库 schema 未修改。
+- `app/static/` 未修改；七个核心 HTML/JS/CSS 文件哈希继续与原版相同。
+- `app-light-1280x720.png` 为真实 `8785` 服务完成载入后的日间模式截图，SHA-256 为
+  `a7ee1b682f68c418d792727dbc4534d7494dae4f4811cdbba208bd86dcf25d10`。
+
+## 3. 真实运行检查
+
+- 迁移副本：`http://127.0.0.1:8785/`，管理员登录成功。
+- 总览：返回 2026-07-30 Tushare 已缓存行情，涨停 56 只。
+- 搜索：搜索“中国平安”返回 `601318`，点击后打开完整个股详情、日 K、资金流、事件逻辑和复盘笔记。
+- 页面：1280px 视口无横向溢出，数据加载状态正常，浏览器控制台 0 个错误。
+- 分时：迁移版与原版在当前本机网络环境均返回同一个 `Intraday chart request failed`，因此记录为
+  既存外部接口状态，不是本切片差异；没有擅自增加降级或改变来源策略。
+
+## 4. 自动验证
+
+| 验证 | 结果 |
+|---|---:|
+| `python -m unittest discover -s tests -q` | 241 项通过 |
+| `python -m unittest tests.test_preservation_slice_market -q` | 6 项通过 |
+| 行情、图表、实时与数据库专项集合 | 61 项通过 |
+| `npx playwright test --reporter=dot` | 45 项通过 |
+| `python -m compileall -q ...` | 通过 |
+| `git diff --check` | 通过 |
+
+## 5. 保留边界
+
+- 情绪计算仍在 `application.py`，切片 03 再归位；行情服务只通过继承调用，没有复制。
+- 竞价、题材、人气、龙虎榜和问天对公共行情客户端的调用仍可通过兼容别名工作，待各自切片迁移。
+- 根级四个数据模块、`DashboardService` 和 `ReviewDatabase` 的兼容面在所有消费者完成迁移前保留。
+- 没有删除待定代码、没有改动根目录正式数据库、没有切换 Docker/NAS。
+

docs/migration/evidence/slice-03/README.md

@@ -0,0 +1,66 @@
+# 切片 03：情绪周期、五类股池与涨停表现
+
+> 基线：`a426432`（切片 02）
+> 回档标签：`xiaobai-preservation-slice-03-20260731`
+> 结论：源码、API、数据库、真实页面和浏览器回归通过；最终视觉仍等待全站人工验收
+
+## 1. 原实现归位
+
+本切片只移动原版副本中的真实实现，没有从 `next/` 取用代码，也没有改写情绪公式、股池数据、
+原因补全、表格、样式或交互。
+
+| 原位置 | 新的唯一实现位置 | 原位置兼容 |
+|---|---|---|
+| `app/backend/application.py` 的 2 个情绪服务方法 | `app/backend/features/sentiment/service.py` | `DashboardService` 继承 `SentimentServiceMixin` |
+| `app/backend/application.py` 的 6 个股池原因及事件补全方法 | `app/backend/features/pools/service.py` | `DashboardService` 继承 `PoolServiceMixin` |
+| `app/database.py` 的 2 个原因覆盖方法 | `app/backend/features/pools/repository.py` | `ReviewDatabase` 继承 `PoolRepositoryMixin` |
+| `app/sentiment_engine.py` | `app/backend/features/sentiment/engine.py` | 根模块为同一模块对象的兼容别名 |
+
+五类股池、涨停梯队和涨停表现仍由切片 02 已归位的原 Tushare 总览实现生成，本切片没有建立第二套
+计算或数据来源。
+
+## 2. 等价证据
+
+- `test_preservation_slice_sentiment_pools.py` 对 8 个业务方法和 2 个 Repository 方法逐项执行无位置
+  信息 AST 比较，全部与根目录原版 `server.py`、`database.py` 完全相同。
+- 新的情绪引擎文件与原版 `sentiment_engine.py` SHA-256 完全相同；根级兼容模块与新模块是同一模块对象。
+- 已归位的应用、行情服务、Tushare Provider、演示数据和选股模块直接导入新的唯一实现；Tushare
+  Provider 仅调整该导入，其全部类和函数 AST 继续与原版一致。
+- 原版 `8784` 与迁移版 `8785` 在相同账号、日期和数据库副本上请求 `/api/dashboard` 与
+  `/api/sentiment/history`，JSON 状态、字段、值和顺序完全相同。
+- 2026-07-30 的同请求结果均为：涨停 56、炸板 23、跌停 83、昨日涨停 81、情绪历史 20 日。
+- 原版和迁移版数据库均为 62 个 schema 对象，schema 哈希均为
+  `17918327f8b919496e6630458293f9f777c7c24662625bb3fc0b64ff0a8fbeef`。
+- `config/api.config.json`、API 路径、鉴权和 `app/static/` 未修改。
+- `app-light-1920x1080.png` 是真实迁移服务载入完成后的情绪周期页面，SHA-256 为
+  `e387417abbe0667e00875a8d4061b5546748ecf2452a692d06d078d516330dab`。
+
+## 3. 真实运行检查
+
+- 迁移副本：`http://127.0.0.1:8785/`，管理员会话与缓存行情载入正常。
+- 情绪周期：20 个连续交易日、当前阶段、评分构成和交易日明细均完整显示。
+- 股池：涨停池 56 行、炸板池 23 行、跌停池 83 行、昨日涨停 81 行。
+- 涨停表现：四档晋级率、市场宽度和今日结论均显示原版结果。
+- 1920×1080 下六个页面横向溢出均为 0；日间、夜间背景与面板状态正常；浏览器控制台无迁移错误。
+
+## 4. 自动验证
+
+| 验证 | 结果 |
+|---|---:|
+| `python -m unittest discover -s tests -q` | 248 项通过 |
+| `python -m unittest tests.test_preservation_slice_sentiment_pools -q` | 6 项通过 |
+| 情绪、总览、缓存、iFinD 与前端契约专项集合 | 48 项通过 |
+| `npx.cmd playwright test --reporter=dot` | 45 项通过 |
+| `python -m compileall -q ...` | 通过 |
+| `git diff --check` | 通过 |
+
+Windows 下由 Playwright 自行创建临时静态服务器时，45 项完成后子进程无法回收；改为预先启动同一个
+`8876` 静态服务器并让 Playwright 复用后，测试以零退出码正常结束，结果为 `45 passed (2.1m)`。
+
+## 5. 保留边界
+
+- 板块轮动仍调用情绪历史公共函数，待切片 04 与市场天梯一并归位。
+- 竞价、题材、人气和龙虎榜对股池数据的消费保持原调用路径，待切片 05 迁移。
+- 根级情绪引擎兼容模块、`DashboardService` 与 `ReviewDatabase` 兼容面继续保留；数据库内尚未迁移的
+  选股统计方法仍走兼容别名，待切片 06 随完整方法一并归位。
+- 没有删除待定代码、没有改动根目录正式数据库、没有切换 Docker/NAS。

docs/migration/evidence/slice-04/README.md

@@ -0,0 +1,58 @@
+# 切片 04：市场天梯与板块轮动
+
+> 基线：`b3555d2`（切片 03）
+> 回档标签：`xiaobai-preservation-slice-04-20260731`
+> 结论：源码、API、真实页面和浏览器回归通过；最终视觉仍等待全站人工验收
+
+## 1. 原实现归位
+
+本切片从原版副本机械移动板块轮动服务，没有从 `next/` 取用代码，也没有修改天梯、轮动的计算、
+排序、展开、配色、页面结构或交互。
+
+| 原位置 | 新的唯一实现位置 | 原位置兼容 |
+|---|---|---|
+| `app/backend/application.py` 的 2 个轮动方法 | `app/backend/features/rotation/service.py` | `DashboardService` 继承 `RotationServiceMixin` |
+| Tushare Provider 的天梯与轮动构造函数 | 保持 `app/backend/data/providers/tushare_client.py` | 切片 02 已归位的公共数据实现 |
+
+市场天梯没有独立后端 API 或第二套计算，直接展示 `/api/dashboard` 中原 Tushare 实现生成的
+`ladders`；因此没有为目录形式建立空的天梯服务。
+
+## 2. 等价证据
+
+- `test_preservation_slice_ladder_rotation.py` 对 2 个轮动服务方法逐项执行无位置信息 AST 比较，
+  全部与根目录原版 `server.py` 完全相同。
+- `_build_ladders` 与 `_build_sector_rotation` 两个原数据构造函数的 AST 与根目录原版完全相同。
+- 原版 `8784` 与迁移版 `8785` 在相同账号、日期和数据库副本上返回的天梯数据及 9 日轮动历史
+  JSON 逐字段完全相同。
+- 成分股接口在当前外部网络状态下两版均返回 HTTP 400、`bad_request` 和相同的
+  `该板块成分股暂不可用：Tushare request failed:`，没有改变错误或增加静默降级。
+- `config/api.config.json`、API 路径、鉴权、数据库 schema 和 `app/static/` 未修改。
+
+## 3. 真实运行检查
+
+- 市场天梯：8 个层级（含断层）、18 个首屏股票单元格、3 个结构分析模块正常；1920×1080 下
+  页面宽度无溢出，首板展开入口保留。
+- 板块轮动：9 个交易日、每日 Top 12 共 108 个板块单元格、由远到近/由近到远两个排序入口正常；
+  1920×1080 下页面宽度无溢出并保持全页滚动。
+- 日间模式页面控制台没有错误或警告。
+- `app-light-ladder-1920x1080.png` SHA-256：
+  `9e57d18d92e745fd92131f7bf08f21faaaa745476dd942cdaa2a703b9a7a303a`。
+- `app-light-rotation-1920x1080.png` SHA-256：
+  `03c092bb40bd0eb672136dff853abffc87e9790840107c2f22e6cf31d5f83c09`。
+
+## 4. 自动验证
+
+| 验证 | 结果 |
+|---|---:|
+| `python -m unittest discover -s tests -q` | 252 项通过 |
+| `python -m unittest tests.test_preservation_slice_ladder_rotation -q` | 4 项通过 |
+| 切片 02 至 04 与总览缓存专项集合 | 24 项通过 |
+| `npx.cmd playwright test --reporter=dot` | 45 项通过 |
+| `git diff --check` | 通过 |
+
+## 5. 保留边界
+
+- 成分股接口依赖的日行情与因子持久化方法仍由原 `ReviewDatabase` 提供，因其同时服务智能选股，
+  待切片 06 随完整共享职责归位。
+- 天梯和轮动前端资产保持原位，切片 10 再按页面职责归档；当前没有复制或改写。
+- 没有删除待定代码、没有改动根目录正式数据库、没有切换 Docker/NAS。

docs/migration/保真迁移状态.json

@@ -1,6 +1,6 @@
 {
   "schema_version": 1,
-  "updated_at": "2026-07-31T00:37:00+08:00",
+  "updated_at": "2026-07-31T01:57:00+08:00",
   "status": "active",
   "migration_mode": "behavior_preserving_source_migration",
   "source_of_truth": "current_original_webapp_runtime_and_source",
@@ -9,10 +9,10 @@
   "failed_roots": [
     "next"
   ],
-  "current_slice": "slice-02-market-search-charts-data",
+  "current_slice": "slice-05-auction-themes-popularity-dragon-tiger",
-  "last_completed_slice": "slice-01-startup-http-accounts-system",
+  "last_completed_slice": "slice-04-ladder-rotation",
-  "last_checkpoint": "xiaobai-preservation-slice-01-20260731",
+  "last_checkpoint": "xiaobai-preservation-slice-04-20260731",
-  "next_action": "capture_slice-02_market_search_chart_data_contracts_then_move_original_implementations",
+  "next_action": "capture_slice-05_auction_theme_popularity_dragon_tiger_contracts_then_move_original_implementations",
   "authoritative_documents": [
     "AGENTS.md",
     "docs/migration/原版保真迁移总纲.md",

docs/migration/保真迁移账本.md

@@ -1,6 +1,6 @@
 # 小白复盘保真迁移账本
 
-> 当前状态：正式迁移，切片01“启动、HTTP、账号、会员与系统管理”已完成
+> 当前状态：正式迁移，切片04“市场天梯与板块轮动”已完成
 
 本账本是上下文恢复和人工审计的连续记录。任何迁移提交必须在同一提交中更新本文件及
 `保真迁移状态.json`。
@@ -21,6 +21,9 @@
 | 2026-07-30 | `xiaobai-preservation-migration-charter-20260730` | 建立保真迁移总纲、状态和恢复协议 | 尚未开始新迁移 |
 | 2026-07-30 | `41329943c4878fc09ed82ec376eb93ab151e4092` | 完成只读资产清查并由用户批准`app/`结构 | 开始切片00 |
 | 2026-07-31 | `xiaobai-preservation-slice-01-20260731` | 启动、HTTP、账号、会员与系统管理原实现归位 | 自动差分通过，进入切片02 |
+| 2026-07-31 | `xiaobai-preservation-slice-02-20260731` | 公共行情、搜索、详情、图表与数据适配原实现归位 | 自动与浏览器差分通过，进入切片03 |
+| 2026-07-31 | `xiaobai-preservation-slice-03-20260731` | 情绪周期、五类股池与涨停表现原实现归位 | 自动、API与浏览器差分通过，进入切片04 |
+| 2026-07-31 | `xiaobai-preservation-slice-04-20260731` | 市场天梯与板块轮动原实现归位 | 自动、API与浏览器差分通过，进入切片05 |
 
 ## 资产处置登记
 
@@ -35,6 +38,11 @@
 | `commonReviewColumns`等5个前端函数 | 疑似无引用符号 | 未发现静态调用 | 待定 | 待删隔离账本 | 仍需动态注册与浏览器覆盖 | 保留 |
 | `wencai_saved_queries`及其方法 | 历史兼容数据 | 当前无前端入口 | 待定 | 数据库兼容区 | 不允许在迁移期破坏旧库 | 保留 |
 | 现有7层CSS | 视觉运行资产 | 全部页面和主题 | 原样保留后逐页归档 | `app/frontend/` | 必须通过截图与计算样式差分 | 保留 |
+| `sentiment_engine.py` | 情绪周期计算 | 总览、轮动、选股 | 移动并保留兼容别名 | `app/backend/features/sentiment/engine.py` | 文件哈希与原版一致；248项Python与45项Playwright通过 | 已移动 |
+| `DashboardService`情绪及股池原因方法 | 业务服务 | 情绪页、五类股池、涨停表现 | 按职责机械移动 | `app/backend/features/sentiment/`、`app/backend/features/pools/` | 8个方法AST与原版一致；真实API完全一致 | 已移动 |
+| `ReviewDatabase`原因覆盖方法 | 持久化 | 股池原因人工覆盖 | 按职责机械移动 | `app/backend/features/pools/repository.py` | 2个方法AST与原版一致；数据库schema哈希一致 | 已移动 |
+| `DashboardService`板块轮动方法 | 业务服务 | 板块轮动页 | 按职责机械移动 | `app/backend/features/rotation/service.py` | 2个方法AST、真实API与原版一致 | 已移动 |
+| Tushare天梯与轮动构造函数 | 公共数据计算 | 市场天梯、板块轮动 | 原位置保持唯一实现 | `app/backend/data/providers/tushare_client.py` | 2个构造函数AST与原版一致 | 已归位 |
 
 处置只允许：`原样保留`、`移动`、`合并重复`、`待定`、`确认废弃`。
 
@@ -61,6 +69,37 @@
 - 回档：标签`xiaobai-preservation-slice-01-20260731`。
 - 完整证据：`docs/migration/evidence/slice-01/README.md`。
 
+已完成切片：`slice-02-market-search-charts-data`。
+
+- 原版基线：提交`4002f09`，即切片01回档点。
+- 迁移范围：30个公共行情服务方法、11个行情持久化方法及Tushare/iFinD/图表/实时观察实现。
+- 兼容边界：四个根级数据模块保留模块别名；未迁移功能继续使用旧导入且指向同一实现。
+- 等价证明：41个方法AST逐项一致，三个数据文件哈希一致，图表定义AST一致，静态资产哈希一致。
+- 验收：241项Python测试、6项切片源码等价测试、45项Playwright测试及真实服务搜索/详情流程通过。
+- 既存状态：原版和迁移版的实时分时在当前环境均返回相同外部请求失败，不作为迁移回归处理。
+- 回档：标签`xiaobai-preservation-slice-02-20260731`。
+- 完整证据：`docs/migration/evidence/slice-02/README.md`。
+
+已完成切片：`slice-03-sentiment-pools-performance`。
+
+- 原版基线：提交`a426432`，即切片02回档点。
+- 迁移范围：情绪计算引擎、2个情绪服务方法、6个股池原因与iFinD事件补全方法、2个原因覆盖持久化方法。
+- 兼容边界：根级`sentiment_engine.py`保留同一模块对象别名；股池生成仍使用切片02的原Tushare总览实现。
+- API与数据库：原版`8784`和迁移版`8785`的总览、情绪历史JSON完全一致；两库schema均为62项且哈希一致。
+- 验收：248项Python测试、6项切片源码等价测试、45项Playwright测试及六个真实页面流程通过。
+- 回档：标签`xiaobai-preservation-slice-03-20260731`。
+- 完整证据：`docs/migration/evidence/slice-03/README.md`。
+
+已完成切片：`slice-04-ladder-rotation`。
+
+- 原版基线：提交`b3555d2`，即切片03回档点。
+- 迁移范围：2个板块轮动服务方法；市场天梯继续使用切片02已归位的原Tushare数据构造实现。
+- 兼容边界：`DashboardService`通过`RotationServiceMixin`保持所有原调用；天梯不制造空服务或第二套计算。
+- API与错误：天梯与9日轮动历史JSON完全一致；成分股两版均返回同一Tushare外部失败语义。
+- 验收：252项Python测试、4项切片源码等价测试、45项Playwright测试及两个真实页面流程通过。
+- 回档：标签`xiaobai-preservation-slice-04-20260731`。
+- 完整证据：`docs/migration/evidence/slice-04/README.md`。
+
 ## 决策记录
 
 | 日期 | 决策 | 原因 |