fix(web): 自动刷新保留 K 线视窗；威科夫与图表增量更新

自动刷新改用 tail update 与 scrollToPosition 恢复视窗，避免 setData 后跳到最右；拆分 chart_tv 模块并扩展 analyze/recent API。同步威科夫分析、pipeline 增量构建及相关策略与配置。 Co-authored-by: Cursor <cursoragent@cursor.com>
2026-08-25 22:57:43 +08:00
parent 1e60ab3bfa
commit 8ee11317d3
104 changed files with 21452 additions and 4988 deletions
@@ -2,9 +2,103 @@
 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__)

+_WYCKOFF_EMPTY = {
+	'trading_range': None,
+	'bias': 'unknown',
+	'phases': [],
+	'events': [],
+	'volume_profile': {'bins': [], 'poc': None, 'vah': None, 'val': None, 'bin_count': 0},
+	'volume_confirm': {'avg_volume': 0.0, 'event_checks': {}},
+	'cycles': [],
+	'live': None,
+	'lifecycle': 'UNKNOWN',
+}
+
+
+def _localize_wyckoff_payload(w, client_tz):
+	"""把威科夫时间统一成客户端时区 ISO，便于与主图对齐。"""
+	if not w:
+		return w
+
+	def _loc_tr(tr):
+		if not tr:
+			return
+		tr['start_time'] = format_time_safely(tr.get('start_time'), client_tz) or tr.get('start_time')
+		tr['end_time'] = format_time_safely(tr.get('end_time'), client_tz) or tr.get('end_time')
+
+	def _loc_cycle(c):
+		if not c:
+			return
+		per = c.get('period') or {}
+		per['start_time'] = format_time_safely(per.get('start_time'), client_tz) or per.get('start_time')
+		per['end_time'] = format_time_safely(per.get('end_time'), client_tz) or per.get('end_time')
+		c['period'] = per
+		_loc_tr(c.get('trading_range'))
+		for ph in c.get('phases') or []:
+			ph['start_time'] = format_time_safely(ph.get('start_time'), client_tz) or ph.get('start_time')
+			ph['end_time'] = format_time_safely(ph.get('end_time'), client_tz) or ph.get('end_time')
+		for ev in c.get('events') or []:
+			ev['time'] = format_time_safely(ev.get('time'), client_tz) or ev.get('time')
+
+	_loc_tr(w.get('trading_range'))
+	for ph in w.get('phases') or []:
+		ph['start_time'] = format_time_safely(ph.get('start_time'), client_tz) or ph.get('start_time')
+		ph['end_time'] = format_time_safely(ph.get('end_time'), client_tz) or ph.get('end_time')
+	for ev in w.get('events') or []:
+		ev['time'] = format_time_safely(ev.get('time'), client_tz) or ev.get('time')
+	for c in w.get('cycles') or []:
+		_loc_cycle(c)
+	return w
+
+
+def _compute_wyckoff_from_df(df, tf, vp_bins, client_tz=None, range_start_time=None, prefer_start_time=None):
+	"""直接用该周期已有 DataFrame（与缠论同一份）。
+	搜索窗口 = 整段数据；箱体在窗内评分选取（近优分取更长），
+	次/次次可用 prefer_start_time 对齐主箱起点。
+	"""
+	from chanlun.analysis.wyckoff import analyze_wyckoff
+
+	try:
+		if df is None or len(df) < 30:
+			empty = dict(_WYCKOFF_EMPTY)
+			empty['volume_profile'] = dict(_WYCKOFF_EMPTY['volume_profile'])
+			empty['volume_confirm'] = dict(_WYCKOFF_EMPTY['volume_confirm'])
+			empty['timeframe'] = tf
+			return empty
+		lookback = len(df)
+		min_bars = max(24, min(80, lookback // 12))
+		out = analyze_wyckoff(
+			df,
+			lookback=lookback,
+			vp_bins=vp_bins,
+			min_bars=min_bars,
+			range_start_time=range_start_time,
+			prefer_start_time=prefer_start_time,
+		)
+		out['timeframe'] = tf
+		out['lookback'] = lookback
+		out['min_bars'] = min_bars
+		if client_tz is not None:
+			_localize_wyckoff_payload(out, client_tz)
+		return out
+	except Exception as e:
+		print(f"Wyckoff 分析出错 ({tf}): {e}")
+		import traceback
+		traceback.print_exc()
+		empty = dict(_WYCKOFF_EMPTY)
+		empty['volume_profile'] = dict(_WYCKOFF_EMPTY['volume_profile'])
+		empty['volume_confirm'] = dict(_WYCKOFF_EMPTY['volume_confirm'])
+		empty['timeframe'] = tf
+		empty['error'] = str(e)
+		return empty
+
+
@bp.route('/api/analyze')
 def analyze():
 	"""分析接口"""
@@ -25,6 +119,9 @@ def analyze():
 	# 获取分形元素时间周期与次次周期
 	element_timeframe = request.args.get('element_timeframe')
 	sub_sub_timeframe = request.args.get('sub_sub_timeframe')
+	# 供文末三周期威科夫复用（避免重复拉数）
+	element_df_for_wyckoff = None
+	sub_sub_df_for_wyckoff = None
 	
 	# 获取是否只需要分形元素数据的参数
 	elements_only_param = request.args.get('elements_only')
@@ -249,6 +346,7 @@ def analyze():
 		if element_df is not None and len(element_df) > 0:
 			# 添加小周期技术指标（包括布林带）
 			element_df = add_indicators(element_df)
+			element_df_for_wyckoff = element_df
 			
 			# 对小周期数据进行缠论分析
 			element_analysis = analyze_chan(element_df, symbol, element_timeframe)
@@ -427,6 +525,7 @@ def analyze():
 				sub_sub_df = get_kl_data(symbol, sub_sub_timeframe, start_time=start_time, end_time=end_time)
 				if sub_sub_df is not None and len(sub_sub_df) > 0:
 					sub_sub_df = add_indicators(sub_sub_df)
+					sub_sub_df_for_wyckoff = sub_sub_df
 					sub_sub_analysis = analyze_chan(sub_sub_df, symbol, sub_sub_timeframe)
 					result['sub_sub_timeframe'] = sub_sub_timeframe
 					result['sub_sub_kline_data'] = clean_dataframe_for_json(sub_sub_df).to_dict('records')
@@ -656,33 +755,110 @@ def analyze():
 	else:
 		result['structure_zones'] = []

-	# 威科夫分析 —— 按需：include_wyckoff=1，且须有主周期分析（非 elements_only）
-	include_wyckoff_param = request.args.get('include_wyckoff', '')
-	include_wyckoff = str(include_wyckoff_param).lower() in ('1', 'true', 'yes')
+	# 威科夫：主 / 次 / 次次各算一份（非 elements_only）；前端开关只控制绘制
+	# include_wyckoff=0 可显式跳过；缺省与其它真值均计算
+	include_wyckoff_param = request.args.get('include_wyckoff', '1')
+	include_wyckoff = str(include_wyckoff_param).lower() not in ('0', 'false', 'no')
 	if include_wyckoff and not elements_only:
-		try:
-			from chanlun.analysis.wyckoff import analyze_wyckoff
-			wyckoff_lookback = int(request.args.get('wyckoff_lookback', 120))
-			# ECR-004：默认/上限 24 bins（A+C）
-			wyckoff_bins = int(request.args.get('wyckoff_vp_bins', 24))
-			result['wyckoff'] = analyze_wyckoff(
-				df,
-				lookback=max(40, min(wyckoff_lookback, 500)),
-				vp_bins=max(10, min(wyckoff_bins, 24)),
+		# 主周期先算；次/次次只同步 active=cycles[0] 的 start（WYCKOFF-MULTI-CYCLE-001）
+		wyckoff_bins = max(10, min(int(request.args.get('wyckoff_vp_bins', 24)), 24))
+		result['wyckoff'] = _compute_wyckoff_from_df(df, timeframe, wyckoff_bins, client_tz=None)
+		main_w = result.get('wyckoff') or {}
+		cycles = main_w.get('cycles') or []
+		# active 唯一来源 cycles[0]；禁止 cycles[-1]
+		active = cycles[0] if cycles else None
+		prefer_start = None
+		if active:
+			prefer_start = ((active.get('trading_range') or {}).get('start_time')
+				or (active.get('period') or {}).get('start_time'))
+		elif main_w.get('trading_range'):
+			prefer_start = main_w['trading_range'].get('start_time')
+		if client_tz is not None:
+			_localize_wyckoff_payload(result['wyckoff'], client_tz)
+		if element_timeframe:
+			result['element_wyckoff'] = _compute_wyckoff_from_df(
+				element_df_for_wyckoff, element_timeframe, wyckoff_bins, client_tz,
+				prefer_start_time=prefer_start,
+			)
+		if sub_sub_timeframe:
+			result['sub_sub_wyckoff'] = _compute_wyckoff_from_df(
+				sub_sub_df_for_wyckoff, sub_sub_timeframe, wyckoff_bins, client_tz,
+				prefer_start_time=prefer_start,
 			)
-		except Exception as e:
-			print(f"Wyckoff 分析出错: {e}")
-			import traceback
-			traceback.print_exc()
-			result['wyckoff'] = {
-				'trading_range': None,
-				'bias': 'unknown',
-				'phases': [],
-				'events': [],
-				'volume_profile': {'bins': [], 'poc': None, 'vah': None, 'val': None, 'bin_count': 0},
-				'volume_confirm': {'avg_volume': 0.0, 'event_checks': {}},
-				'error': str(e),
-			}
+
+	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)