feat(web): 增量自动刷新、结构区修复与默认指标/周期

自动刷新常态只拉 recent 尾部 K，每 1 分钟全量重算缠论；修复结构区缓存导入；默认指标/4h·1h·15m/近30天；同步 ECR-009 screener 相关改动。

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

web/api/analyze.py

@@ -2,6 +2,9 @@
 from flask import Blueprint, jsonify, request
 from services.runtime import *  # noqa: F403
 from services import runtime as R
+# import * 不会带出下划线私有名；结构区缓存需显式导入
+from services.runtime.state import _zone_cache
+from services.runtime.timeframes import _zone_cache_ttl
 
 bp = Blueprint("analyze", __name__)
 
@@ -785,3 +788,77 @@ def analyze():
 
 	return jsonify(result)
 
+
+def _serialize_kl_tail(df, limit: int):
+	"""只序列化最近 limit 根，供自动刷新增量合并。"""
+	if df is None or getattr(df, "empty", True):
+		return []
+	tail = df.tail(limit)
+	clean = clean_dataframe_for_json(tail)
+	records = clean.to_dict("records")
+	for row in records:
+		d = row.get("date")
+		if hasattr(d, "isoformat"):
+			try:
+				row["date"] = d.isoformat()
+			except Exception:
+				row["date"] = str(d)
+		# timestamp 统一成 int ms，便于前端按 key 合并
+		ts = row.get("timestamp")
+		if ts is not None:
+			try:
+				row["timestamp"] = int(ts)
+			except (TypeError, ValueError):
+				pass
+		elif hasattr(d, "timestamp"):
+			try:
+				row["timestamp"] = int(d.timestamp() * 1000)
+			except Exception:
+				pass
+	return records
+
+
+@bp.route("/api/klines/recent")
+def klines_recent():
+	"""轻量拉取最近 N 根 K 线（不做缠论/威科夫），供主站自动刷新增量。"""
+	symbol = (request.args.get("symbol") or "").strip()
+	if not symbol:
+		return jsonify({"error": "交易对不能为空"}), 400
+
+	timeframe = request.args.get("timeframe", "5m")
+	try:
+		limit = int(request.args.get("limit", 2))
+	except (TypeError, ValueError):
+		limit = 2
+	limit = max(1, min(limit, 20))
+
+	element_timeframe = request.args.get("element_timeframe") or None
+	sub_sub_timeframe = request.args.get("sub_sub_timeframe") or None
+
+	# 只取尾部：不传 start/end，避免全量窗口回拉
+	df = get_kl_data(symbol, timeframe, limit=limit)
+	if df is None:
+		return jsonify({"error": "获取数据失败"}), 502
+	if len(df) == 0:
+		return jsonify({"error": "没有数据"}), 404
+
+	result = {
+		"partial": True,
+		"symbol": symbol,
+		"timeframe": timeframe,
+		"limit": limit,
+		"kline_data": _serialize_kl_tail(df, limit),
+	}
+
+	if element_timeframe:
+		edf = get_kl_data(symbol, element_timeframe, limit=limit)
+		result["element_timeframe"] = element_timeframe
+		result["element_kline_data"] = _serialize_kl_tail(edf, limit) if edf is not None else []
+
+	if sub_sub_timeframe:
+		sdf = get_kl_data(symbol, sub_sub_timeframe, limit=limit)
+		result["sub_sub_timeframe"] = sub_sub_timeframe
+		result["sub_sub_kline_data"] = _serialize_kl_tail(sdf, limit) if sdf is not None else []
+
+	return jsonify(result)
+