Slim embed tab rendering to cut memory use and restore calculator.

Load only per-tab data for embed fragments, skip exchange capital fetches on tab switches, and harden calculator market imports/timeouts.

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

instance_embed_context_lib.py

@@ -0,0 +1,81 @@
+"""embed 壳/片段：按 tab 裁剪 render_main_page 的数据加载，降内存与 API 压力。"""
+
+from __future__ import annotations
+
+from dataclasses import dataclass
+from typing import Any
+
+EMBED_STRATEGY_PAGES = frozenset({"strategy", "strategy_trend", "strategy_roll", "strategy_records"})
+
+
+@dataclass(frozen=True)
+class EmbedRenderPlan:
+    exchange_capitals: bool
+    records_rows: bool
+    records_summary: bool
+    key_history: bool
+    key_list: bool
+    orders: bool
+    stats_bundle: bool
+    strategy: bool
+    orphan_live: bool
+
+
+def embed_render_plan(page: str, embed_mode: str | None) -> EmbedRenderPlan:
+    if embed_mode not in ("fragment", "shell"):
+        return EmbedRenderPlan(
+            exchange_capitals=True,
+            records_rows=True,
+            records_summary=False,
+            key_history=True,
+            key_list=True,
+            orders=True,
+            stats_bundle=True,
+            strategy=True,
+            orphan_live=True,
+        )
+    is_shell = embed_mode == "shell"
+    is_strategy = page in EMBED_STRATEGY_PAGES
+    return EmbedRenderPlan(
+        exchange_capitals=is_shell,
+        records_rows=page == "records",
+        records_summary=is_shell and page != "records",
+        key_history=page == "key_monitor",
+        key_list=page in ("key_monitor", "trade") or is_strategy,
+        orders=page == "trade" or is_strategy,
+        stats_bundle=page == "stats",
+        strategy=is_strategy,
+        orphan_live=page == "trade" and is_shell,
+    )
+
+
+def trade_records_summary(conn, start_bj: str, end_bj: str, tr_ts: str) -> dict[str, Any]:
+    """顶栏统计用 COUNT，避免 embed 壳拉 1000 行交易记录。"""
+    row = conn.execute(
+        f"""
+        SELECT
+            COUNT(*) AS total,
+            SUM(CASE WHEN result = '错过' THEN 1 ELSE 0 END) AS miss_count,
+            SUM(CASE WHEN result IN ('止盈','保本止盈','移动止盈') THEN 1 ELSE 0 END) AS wins,
+            SUM(CASE WHEN result = '错过' AND COALESCE(miss_reason,'') LIKE '%持仓占用%' THEN 1 ELSE 0 END) AS occupied_miss
+        FROM trade_records
+        WHERE {tr_ts} >= ? AND {tr_ts} <= ?
+        """,
+        (start_bj, end_bj),
+    ).fetchone()
+    total = int(row["total"] or 0) if row else 0
+    miss_count = int(row["miss_count"] or 0) if row else 0
+    wins = int(row["wins"] or 0) if row else 0
+    occupied_miss_total = int(row["occupied_miss"] or 0) if row else 0
+    rate = round(wins / total * 100, 2) if total else 0
+    return {
+        "records": [],
+        "total": total,
+        "miss_count": miss_count,
+        "rate": rate,
+        "occupied_miss_total": occupied_miss_total,
+    }
+
+
+def minimal_stats_bundle(reset_hour: int) -> dict[str, Any]:
+    return {"stats_reset_hour": reset_hour, "segments": []}