Add period selector and crypto-style trend plan preview table.

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

strategy/strategy_db.py

@@ -61,7 +61,8 @@ CREATE TABLE IF NOT EXISTS trend_pullback_plans (
     avg_entry_price REAL,
     lots_open INTEGER DEFAULT 0,
     opened_at TEXT,
-    message TEXT
+    message TEXT,
+    period TEXT DEFAULT '15m'
 )
 """
 
@@ -138,6 +139,10 @@ def init_strategy_tables(conn) -> None:
         CTP_SIM_POSITIONS_SQL,
     ):
         conn.execute(sql)
+    try:
+        conn.execute("ALTER TABLE trend_pullback_plans ADD COLUMN period TEXT DEFAULT '15m'")
+    except Exception:
+        pass
     if not conn.execute("SELECT id FROM ctp_sim_account WHERE id=1").fetchone():
         conn.execute("INSERT INTO ctp_sim_account (id, balance, available) VALUES (1, 100000, 100000)")
     conn.commit()

strategy/strategy_trend_lib.py

@@ -111,3 +111,123 @@ def trend_dca_level_reached(direction: str, mark_price: float, level: float) ->
     d = (direction or "long").strip().lower()
     pf, lv = float(mark_price), float(level)
     return pf <= lv if d == "long" else pf >= lv
+
+
+def trend_strategy_periods() -> list[dict[str, str]]:
+    """策略页可选 K 线周期。"""
+    from kline_chart import MARKET_PERIODS
+
+    skip = frozenset({"timeshare", "w"})
+    return [p for p in MARKET_PERIODS if p["key"] not in skip]
+
+
+def trend_period_label(key: str) -> str:
+    k = (key or "").strip()
+    for p in trend_strategy_periods():
+        if p["key"] == k:
+            return p["label"]
+    return k or "15分"
+
+
+def normalize_trend_period(key: str) -> str:
+    valid = {p["key"] for p in trend_strategy_periods()}
+    k = (key or "15m").strip()
+    return k if k in valid else "15m"
+
+
+def _avg_after_entries(entries: list[tuple[float, int]]) -> float:
+    total = sum(q for _, q in entries)
+    if total <= 0:
+        return 0.0
+    return sum(p * q for p, q in entries) / total
+
+
+def enrich_trend_plan_preview(
+    plan: dict,
+    *,
+    symbol: str,
+    symbol_name: str = "",
+    period: str = "15m",
+) -> dict[str, Any]:
+    """补全预览：周期、风险金额、分档表格（对齐币圈预览样式）。"""
+    out = dict(plan)
+    d = (out.get("direction") or "long").strip().lower()
+    sl = float(out["stop_loss"])
+    tp = float(out["take_profit"])
+    mult = float(out.get("mult") or 1)
+    entry0 = float(out["live_price_ref"])
+    first_lots = int(out["first_lots"])
+    leg_amounts = [int(x) for x in (out.get("leg_amounts") or [])]
+    grid = [float(x) for x in (out.get("grid") or [])]
+    capital = float(out.get("capital_snapshot") or 0)
+    risk_pct = float(out.get("risk_percent") or 0)
+    budget = capital * risk_pct / 100.0
+    remainder = int(out.get("remainder_lots") or sum(leg_amounts))
+
+    out["symbol"] = symbol
+    out["symbol_name"] = symbol_name or symbol
+    out["period"] = normalize_trend_period(period)
+    out["period_label"] = trend_period_label(out["period"])
+    out["stop_loss_budget"] = round(budget, 2)
+    out["direction_label"] = "做多" if d == "long" else "做空"
+
+    entries: list[tuple[float, int]] = [(entry0, first_lots)]
+    rows: list[dict[str, Any]] = []
+
+    def leg_metrics() -> tuple[float, float, float, Optional[float]]:
+        total = sum(q for _, q in entries)
+        avg = _avg_after_entries(entries)
+        if d == "long":
+            profit = (tp - avg) * total * mult
+            loss = (avg - sl) * total * mult
+        else:
+            profit = (avg - tp) * total * mult
+            loss = (sl - avg) * total * mult
+        rr = profit / loss if loss > 0 else None
+        return (
+            round(avg, 4),
+            round(profit, 2),
+            round(loss, 2),
+            round(rr, 2) if rr is not None else None,
+        )
+
+    avg, profit, loss, rr = leg_metrics()
+    rows.append({
+        "level": "首仓",
+        "price": round(entry0, 4),
+        "lots": first_lots,
+        "avg_after": avg,
+        "profit_at_tp": profit,
+        "loss_at_sl": loss,
+        "rr_ratio": rr,
+    })
+    out["first_rr_ratio"] = rr
+
+    for i, lots in enumerate(leg_amounts):
+        price = grid[i] if i < len(grid) else sl
+        entries.append((float(price), int(lots)))
+        avg, profit, loss, rr = leg_metrics()
+        rows.append({
+            "level": f"补仓{i + 1}",
+            "price": round(float(price), 4),
+            "lots": int(lots),
+            "avg_after": avg,
+            "profit_at_tp": profit,
+            "loss_at_sl": loss,
+            "rr_ratio": rr,
+        })
+
+    out["preview_rows"] = rows
+    out["summary_line"] = (
+        f"{out['symbol_name']} {out['symbol']} {out['direction_label']} {out['period_label']}"
+        f" | 权益 {capital:.2f} 元"
+        f" | 参考价 {entry0}"
+        f" | 计划保证金 ≈ {out.get('plan_margin')} 元"
+        f" | 总手 {out.get('target_lots')}（首仓 {first_lots} + 补仓 {remainder}）"
+    )
+    out["detail_line"] = (
+        f"止损价 {sl} | 止损金额 {out['stop_loss_budget']} 元（权益 × 风险 {risk_pct}%）"
+        f" | 补仓边界 {float(out['add_upper'])} | 止盈价 {tp}"
+        f" | 首仓盈亏比 {out['first_rr_ratio'] if out['first_rr_ratio'] is not None else '—'}"
+    )
+    return out