feat: 档案统计独立卡片、共用交易日历与四所统计页日历

内照明心统计表移至顶部卡片，右侧为日历/图表/交易记录；日历样式适配浅深主题，四所统计分析页同步展示按月盈亏日历。

Co-authored-by: Cursor <cursoragent@cursor.com>

trade_stats_calendar_lib.py

@@ -0,0 +1,73 @@
+"""按交易日聚合实例 trade_records 盈亏，供统计分析页日历 API 使用。"""
+from __future__ import annotations
+
+from datetime import datetime, timedelta
+from typing import Any, Callable
+
+
+def build_trade_stats_calendar(
+    pnls: list[tuple],
+    year: int,
+    month: int,
+    segment_key: str,
+    row_matches_fn: Callable[[Any, str], bool],
+    *,
+    reset_hour: int = 8,
+) -> dict[str, Any]:
+    """pnls: _load_completed_trade_pnls 返回值 (pnl, close_dt, trading_day, row)。"""
+    y = int(year)
+    m = int(month)
+    if m < 1 or m > 12:
+        raise ValueError("month 无效")
+    first = f"{y:04d}-{m:02d}-01"
+    if m == 12:
+        next_first = datetime(y + 1, 1, 1)
+    else:
+        next_first = datetime(y, m + 1, 1)
+    last = (next_first - timedelta(days=1)).strftime("%Y-%m-%d")
+    seg = (segment_key or "all").strip() or "all"
+    days: dict[str, dict[str, Any]] = {}
+    for pnl, _close_dt, td, row in pnls:
+        if not td or td < first or td > last:
+            continue
+        if not row_matches_fn(row, seg):
+            continue
+        bucket = days.setdefault(
+            td,
+            {
+                "trading_day": td,
+                "open_count": 0,
+                "pnl_total": 0.0,
+                "turnover_total": 0.0,
+                "commission_total": 0.0,
+                "has_sick": False,
+                "sick_count": 0,
+            },
+        )
+        bucket["open_count"] += 1
+        bucket["pnl_total"] += float(pnl or 0)
+        try:
+            bucket["turnover_total"] += float(row["exchange_turnover_usdt"] or 0)
+        except (TypeError, ValueError, KeyError):
+            pass
+        try:
+            bucket["commission_total"] += float(row["exchange_commission_usdt"] or 0)
+        except (TypeError, ValueError, KeyError):
+            pass
+    for d in days.values():
+        d["pnl_total"] = round(float(d["pnl_total"]), 4)
+        d["turnover_total"] = round(float(d["turnover_total"]), 4)
+        d["commission_total"] = round(float(d["commission_total"]), 4)
+    month_pnl = sum(float(d["pnl_total"]) for d in days.values())
+    month_count = sum(int(d["open_count"]) for d in days.values())
+    return {
+        "year": y,
+        "month": m,
+        "date_from": first,
+        "date_to": last,
+        "segment": seg,
+        "reset_hour": int(reset_hour),
+        "days": days,
+        "month_pnl_total": round(month_pnl, 4),
+        "month_open_count": month_count,
+    }