提交

backend/app/data/market_overview.py

@@ -17,7 +17,6 @@
 from __future__ import annotations
 
 import asyncio
-import math
 import time
 from datetime import date, datetime, timedelta
 
@@ -26,6 +25,7 @@ import pandas as pd
 
 from .. import cache
 from ..config import settings
+from .sync_utils import d8_iso, f_clean
 
 # (tushare代码, 名称, 地区, 腾讯符号) —— 展示顺序即列表顺序
 # 首页聚焦中美（港股/国际指数在 /indexes 国际指数页）；标普500 腾讯符号是 s_usINX（不是 s_usSPX）
@@ -57,22 +57,6 @@ class MarketOverviewError(RuntimeError):
     """所有指数都拉不到（token/网络故障）——接口层转 503。"""
 
 
-def _f(v) -> float | None:
-    """pandas 值 -> float；NaN/None -> None（否则 JSON 里会出现 NaN）。"""
-    if v is None:
-        return None
-    try:
-        f = float(v)
-    except (TypeError, ValueError):
-        return None
-    return None if math.isnan(f) else f
-
-
-def _d(v) -> str | None:
-    """YYYYMMDD -> 'YYYY-MM-DD'（字符串便于 JSON 缓存；pydantic 响应模型自动 coerce）。"""
-    return datetime.strptime(str(v), "%Y%m%d").date().isoformat() if v else None
-
-
 def _get_pro():
     if not settings.tushare_token:
         raise MarketOverviewError("未配置 TUSHARE_TOKEN，无法获取大盘行情（backend/.env）")
@@ -165,10 +149,10 @@ def _quote_from_df(df: pd.DataFrame) -> dict | None:
     tail = df.tail(_SPARK_DAYS)
     last = df.iloc[-1]
     return {
-        "close": _f(last["close"]),
-        "change": _f(last.get("change")),
-        "pct_chg": _f(last.get("pct_chg")),
-        "trade_date": _d(last["trade_date"]),
+        "close": f_clean(last["close"]),
+        "change": f_clean(last.get("change")),
+        "pct_chg": f_clean(last.get("pct_chg")),
+        "trade_date": d8_iso(last["trade_date"]),
         "spark": [round(float(c), 4) for c in tail["close"]],
         "spark_dates": [str(d) for d in tail["trade_date"]],
     }
@@ -193,10 +177,10 @@ def _fetch_stats_sync(pro) -> dict | None:
     if sh_m is None or sz_m is None:
         return None
     # 两边各自取最新，日期不一致时以较旧一天为准凑齐口径（罕见，通常同日）
-    d = min(_d(sh_m["trade_date"]), _d(sz_m["trade_date"]))
+    d = min(d8_iso(sh_m["trade_date"]), d8_iso(sz_m["trade_date"]))
 
     def _sum(col: str) -> float | None:
-        a, b = _f(sh_m.get(col)), _f(sz_m.get(col))
+        a, b = f_clean(sh_m.get(col)), f_clean(sz_m.get(col))
         return None if a is None or b is None else round(a + b, 2)
 
     return {
@@ -204,7 +188,7 @@ def _fetch_stats_sync(pro) -> dict | None:
         "total_mv": _sum("total_mv"),
         "float_mv": _sum("float_mv"),
         "amount": _sum("amount"),
-        "turnover": _f(sh_m.get("tr")),  # 换手率仅沪市有，展示口径注明沪市
+        "turnover": f_clean(sh_m.get("tr")),  # 换手率仅沪市有，展示口径注明沪市
     }
 
 
@@ -222,7 +206,7 @@ def _fetch_amount_history_sync(pro) -> list[dict]:
     if len(common) == 0:
         return []
     total = (sh_m[common] + sz_m[common]).sort_index()
-    return [{"date": _d(d), "amount": round(float(v), 2)} for d, v in total.tail(_AMOUNT_HIST_BARS).items()]
+    return [{"date": d8_iso(d), "amount": round(float(v), 2)} for d, v in total.tail(_AMOUNT_HIST_BARS).items()]
 
 
 # ---- EOD 的 SWR（stale-while-revalidate）：新鲜期内直返；过期先返旧值后台刷新 ----