fix: pipeline MACD 参数统一为标准 12/26/9（与 web/交易所一致）

交付前缺 Flask 常驻与路由断言；现补齐 pytest 与报告。

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

.gitignore

@@ -40,3 +40,10 @@ feature_meta
 .DS_Store
 data_provider/._config.json
 .gstack/
+
+# ESS gate / engineering-loop working dirs（归档进 docs/runs/）
+.gates/
+loop/
+
+# Crypto Wyckoff Screener local cache
+data/crypto_wyckoff/

chanlun/analysis/wyckoff/__init__.py

@@ -0,0 +1,7 @@
+"""威科夫分析（启发式）：交易区间 / 阶段 / 事件 / Volume Profile / Live。"""
+from __future__ import annotations
+
+from .engine import analyze_wyckoff
+from .live import execution_signal_from_wyckoff
+
+__all__ = ["analyze_wyckoff", "execution_signal_from_wyckoff"]

chanlun/analysis/wyckoff/engine.py

@@ -0,0 +1,196 @@
+"""威科夫分析入口：Cycle → Phase → Event → VP + Live（MULTI-CYCLE / LIVE-STRUCTURE）。
+
+range.py 只产 TradingRange；Confirmed 走 events.py；Live 走 live.py。
+cycles[0]=ACTIVE；禁止 cycles[-1] 取 active。
+Execution 只消费 Confirmed（见 live.execution_signal_from_wyckoff）。
+"""
+from __future__ import annotations
+
+from typing import Any, Dict, List, Optional
+
+import pandas as pd
+
+from .events import build_phases, detect_bias_and_events
+from .live import analyze_live_structure
+from .range import detect_trading_ranges
+from .volume_profile import compute_volume_profile
+
+
+def _fmt_time(v) -> Optional[str]:
+	if v is None:
+		return None
+	if hasattr(v, "isoformat"):
+		try:
+			return v.isoformat()
+		except Exception:
+			pass
+	return str(v)
+
+
+def _empty(vp_bins: int) -> Dict[str, Any]:
+	return {
+		"cycles": [],
+		"trading_range": None,
+		"bias": "unknown",
+		"phases": [],
+		"events": [],
+		"volume_profile": {"bins": [], "poc": None, "vah": None, "val": None, "bin_count": vp_bins},
+		"volume_confirm": {"avg_volume": 0.0, "event_checks": {}},
+		"live": None,
+	}
+
+
+def _confidence_for_confirmed(
+	tr: Dict[str, Any],
+	phases: List[Dict[str, Any]],
+	events: List[Dict[str, Any]],
+) -> Dict[str, float]:
+	range_c = float(tr.get("range_confidence") or 0.5)
+	labels = {p.get("phase") for p in phases}
+	phase_c = 0.35
+	if "A" in labels and "B" in labels:
+		phase_c += 0.15
+	if "C" in labels:
+		phase_c += 0.2
+	if "D" in labels or "E" in labels:
+		phase_c += 0.15
+	phase_c = min(0.95, phase_c)
+	types = {e.get("type") for e in events}
+	event_c = 0.25
+	for t in ("Spring", "UTAD", "SOS", "SOW", "LPS", "LPSY"):
+		if t in types:
+			event_c += 0.12
+	event_c = min(0.95, event_c)
+	overall = 0.4 * range_c + 0.3 * phase_c + 0.3 * event_c
+	return {
+		"range": round(range_c, 3),
+		"phase": round(phase_c, 3),
+		"event": round(event_c, 3),
+		"overall": round(overall, 3),
+	}
+
+
+def _build_cycle(
+	work: pd.DataFrame,
+	tr: Dict[str, Any],
+	cycle_id: int,
+	vp_bins: int,
+) -> Dict[str, Any]:
+	bias, events, volume_confirm = detect_bias_and_events(work, tr)
+	phases = build_phases(work, tr, bias, events)
+	vp = compute_volume_profile(
+		work,
+		int(tr["abs_start_idx"]),
+		int(tr["abs_end_idx"]),
+		bin_count=vp_bins,
+	)
+	for ev in events:
+		ev["time"] = _fmt_time(ev.get("time"))
+	for ph in phases:
+		ph["start_time"] = _fmt_time(ph.get("start_time"))
+		ph["end_time"] = _fmt_time(ph.get("end_time"))
+
+	is_active = cycle_id == 0
+	trading_range = {
+		"start_time": _fmt_time(tr.get("start_time")),
+		"end_time": _fmt_time(tr.get("end_time")),
+		"high": float(tr["high"]),
+		"low": float(tr["low"]),
+		"mid": float(tr["mid"]),
+		"active": bool(is_active),
+		"bars": int(tr.get("bars", 0)),
+	}
+	conf = _confidence_for_confirmed(tr, phases, events)
+
+	# Live 层：仅 ACTIVE 周期做推演；历史周期归档为 COMPLETED
+	if is_active:
+		live = analyze_live_structure(
+			work, tr, confirmed_events=events, confirmed_phases=phases, bias=bias,
+		)
+		lifecycle = live.get("lifecycle") or "FORMING"
+	else:
+		live = None
+		lifecycle = "COMPLETED"
+
+	return {
+		"id": int(cycle_id),
+		"role": "latest" if is_active else "historical",
+		# MULTI-CYCLE：时间线角色
+		"status": "ACTIVE" if is_active else "HISTORICAL",
+		# LIVE-STRUCTURE：生命周期
+		"lifecycle": lifecycle,
+		"direction": "latest" if is_active else "historical",
+		"period": {
+			"start_time": _fmt_time(tr.get("start_time")),
+			"end_time": _fmt_time(tr.get("end_time")),
+			"bars": int(tr.get("bars", 0)),
+		},
+		"confidence": conf,
+		"trading_range": trading_range,
+		"bias": bias,
+		# 兼容旧读法：顶层 phases/events = confirmed
+		"phases": phases,
+		"events": events,
+		"confirmed": {
+			"phases": phases,
+			"events": events,
+			"volume_confirm": volume_confirm,
+		},
+		"live": live,
+		"volume_profile": vp,
+		"volume_confirm": volume_confirm,
+	}
+
+
+def analyze_wyckoff(
+	df: pd.DataFrame,
+	lookback: int = 120,
+	vp_bins: int = 50,
+	min_bars: int = 24,
+	atr_mult: float = 1.2,
+	range_start_time=None,
+	prefer_start_time=None,
+	max_cycles: int = 8,
+) -> Dict[str, Any]:
+	"""
+	多周期威科夫分析。
+	cycles[0] = ACTIVE；顶层 phases/events 只镜像 Confirmed。
+	顶层 live 镜像 cycles[0].live。
+	"""
+	empty = _empty(vp_bins)
+	if df is None or len(df) < 30:
+		return empty
+	if not all(c in df.columns for c in ("open", "high", "low", "close")):
+		return empty
+	work = df.copy()
+	if "volume" not in work.columns:
+		work["volume"] = 1.0
+
+	trs = detect_trading_ranges(
+		work,
+		lookback=lookback,
+		min_bars=max(8, int(min_bars)),
+		atr_mult=atr_mult,
+		max_cycles=max(1, min(8, int(max_cycles))),
+		prefer_start_time=prefer_start_time,
+		range_start_time=range_start_time,
+	)
+	if not trs:
+		return empty
+
+	cycles: List[Dict[str, Any]] = []
+	for i, tr in enumerate(trs):
+		cycles.append(_build_cycle(work, tr, cycle_id=i, vp_bins=vp_bins))
+
+	active = cycles[0]
+	return {
+		"cycles": cycles,
+		"trading_range": active["trading_range"],
+		"bias": active["bias"],
+		"phases": active["confirmed"]["phases"],
+		"events": active["confirmed"]["events"],
+		"volume_profile": active["volume_profile"],
+		"volume_confirm": active["volume_confirm"],
+		"live": active.get("live"),
+		"lifecycle": active.get("lifecycle"),
+	}

chanlun/analysis/wyckoff/events.py

@@ -0,0 +1,369 @@
+"""威科夫阶段与事件（启发式）。"""
+from __future__ import annotations
+
+from typing import Any, Dict, List, Optional, Tuple
+
+import numpy as np
+import pandas as pd
+
+
+def _bar_time(df: pd.DataFrame, i: int):
+	row = df.iloc[i]
+	if "date" in df.columns and pd.notna(row["date"]):
+		return row["date"]
+	if "timestamp" in df.columns:
+		return row["timestamp"]
+	return i
+
+
+def _avg_vol(df: pd.DataFrame, i: int, win: int = 20) -> float:
+	a = max(0, i - win + 1)
+	v = df["volume"].astype(float).iloc[a : i + 1]
+	m = float(v.mean()) if len(v) else 0.0
+	return m if m > 0 else 1.0
+
+
+def detect_bias_and_events(
+	df: pd.DataFrame,
+	tr: Dict[str, Any],
+) -> Tuple[str, List[Dict[str, Any]], Dict[str, Any]]:
+	"""
+	返回 bias、events、volume_confirm。
+
+	Spring/UTAD 相对「结构高低」判定：取区间内次低/次高（剔除单根极值），
+	避免箱体把假破低点吃进 lo 后永远刺不破、从而无 C 阶段。
+	"""
+	hi = float(tr["high"])
+	lo = float(tr["low"])
+	mid = float(tr["mid"])
+	tol = float(tr.get("tol") or (hi - lo) * 0.05)
+	s = int(tr["abs_start_idx"])
+	e = int(tr["abs_end_idx"])
+	events: List[Dict[str, Any]] = []
+
+	# 结构边界：用次低/次高作假破参照（至少 8 根才启用）
+	seg = df.iloc[s : e + 1]
+	event_lo, event_hi = lo, hi
+	if len(seg) >= 8:
+		lows = seg["low"].astype(float)
+		highs = seg["high"].astype(float)
+		# nsmallest(2) 的较大者 = 次低；nlargest(2) 的较小者 = 次高
+		event_lo = float(lows.nsmallest(min(2, len(lows))).iloc[-1])
+		event_hi = float(highs.nlargest(min(2, len(highs))).iloc[-1])
+		# 勿比公布箱沿更「松」：结构带应在箱内
+		event_lo = max(event_lo, lo)
+		event_hi = min(event_hi, hi)
+		# 若次低仍等于极值（多根同价），略抬参照便于识别收回
+		if abs(event_lo - lo) < 1e-12:
+			event_lo = lo + max(tol * 0.35, (hi - lo) * 0.02)
+		if abs(event_hi - hi) < 1e-12:
+			event_hi = hi - max(tol * 0.35, (hi - lo) * 0.02)
+
+	# 扫描区间内及之后（含 tail_reserve）
+	scan_end = int(tr.get("abs_scan_end_idx", min(len(df) - 1, e + 15)))
+	scan_end = min(len(df) - 1, max(scan_end, e))
+	spring = None
+	utad = None
+	sos = None
+	sod = None  # sign of weakness / distribution breakdown
+	lps = None
+	lpsy = None
+
+	for i in range(s + 2, scan_end + 1):
+		row = df.iloc[i]
+		low = float(row["low"])
+		high = float(row["high"])
+		close = float(row["close"])
+		vol = float(row["volume"]) if "volume" in df.columns else 0.0
+		avg_v = _avg_vol(df, i)
+		ratio = vol / avg_v if avg_v else 0.0
+
+		# Spring: pierce below structural support then close back
+		if spring is None and low < event_lo - tol * 0.35 and close >= event_lo - tol * 0.35:
+			vol_ok = ratio <= 1.35 or (i + 1 <= scan_end and float(df.iloc[min(i + 1, scan_end)]["volume"]) / avg_v < 1.2)
+			spring = {
+				"type": "Spring",
+				"time": _bar_time(df, i),
+				"price": low,
+				"note": "假破下沿后收回",
+				"volume_ratio": round(ratio, 3),
+				"volume_ok": bool(vol_ok),
+				"idx": i,
+			}
+
+		# UTAD: pierce above structural resistance then close back
+		if utad is None and high > event_hi + tol * 0.35 and close <= event_hi + tol * 0.35:
+			vol_ok = ratio >= 0.8
+			utad = {
+				"type": "UTAD",
+				"time": _bar_time(df, i),
+				"price": high,
+				"note": "假破上沿后跌回",
+				"volume_ratio": round(ratio, 3),
+				"volume_ok": bool(vol_ok),
+				"idx": i,
+			}
+
+		# SOS: close above high with volume
+		if sos is None and close > hi + tol * 0.15:
+			vol_ok = ratio >= 1.15
+			sos = {
+				"type": "SOS",
+				"time": _bar_time(df, i),
+				"price": close,
+				"note": "放量上破交易区间",
+				"volume_ratio": round(ratio, 3),
+				"volume_ok": bool(vol_ok),
+				"idx": i,
+			}
+
+		# SOW / breakdown
+		if sod is None and close < lo - tol * 0.15:
+			vol_ok = ratio >= 1.15
+			sod = {
+				"type": "SOW",
+				"time": _bar_time(df, i),
+				"price": close,
+				"note": "放量下破交易区间",
+				"volume_ratio": round(ratio, 3),
+				"volume_ok": bool(vol_ok),
+				"idx": i,
+			}
+
+	# LPS after SOS: pullback that holds above mid/high-band with lighter volume
+	if sos is not None:
+		si = int(sos["idx"])
+		for i in range(si + 1, min(len(df), si + 25)):
+			row = df.iloc[i]
+			low = float(row["low"])
+			close = float(row["close"])
+			vol = float(row["volume"]) if "volume" in df.columns else 0.0
+			avg_v = _avg_vol(df, i)
+			ratio = vol / avg_v if avg_v else 0.0
+			if low >= mid - tol and close >= hi - tol * 2:
+				vol_ok = ratio <= 1.05
+				lps = {
+					"type": "LPS",
+					"time": _bar_time(df, i),
+					"price": low,
+					"note": "突破后缩量回踩不破",
+					"volume_ratio": round(ratio, 3),
+					"volume_ok": bool(vol_ok),
+					"idx": i,
+				}
+				break
+
+	if sod is not None:
+		si = int(sod["idx"])
+		for i in range(si + 1, min(len(df), si + 25)):
+			row = df.iloc[i]
+			high = float(row["high"])
+			close = float(row["close"])
+			vol = float(row["volume"]) if "volume" in df.columns else 0.0
+			avg_v = _avg_vol(df, i)
+			ratio = vol / avg_v if avg_v else 0.0
+			if high <= mid + tol and close <= lo + tol * 2:
+				vol_ok = ratio <= 1.05
+				lpsy = {
+					"type": "LPSY",
+					"time": _bar_time(df, i),
+					"price": high,
+					"note": "下跌突破后缩量反抽不过",
+					"volume_ratio": round(ratio, 3),
+					"volume_ok": bool(vol_ok),
+					"idx": i,
+				}
+				break
+
+	# 冲突清理：已判定吸筹且有 SOS 时，丢弃更早的 UTAD（避免阶段/图面误导）
+	# 派发且有 SOW 时，丢弃更晚才合理的 Spring 假信号同理在偏置后再滤
+	keep = []
+	for ev in (spring, sos, lps, utad, sod, lpsy):
+		if not ev:
+			continue
+		keep.append(ev)
+
+	# bias（先算）
+	last_c = float(df["close"].iloc[-1])
+	bias = "unknown"
+	if sos and (not sod or int(sos.get("idx", 0)) >= int(sod.get("idx", 0))):
+		bias = "accumulation"
+	elif sod and (not sos or int(sod.get("idx", 0)) > int(sos.get("idx", 0))):
+		bias = "distribution"
+	elif spring and not utad:
+		bias = "accumulation"
+	elif utad and not spring:
+		bias = "distribution"
+	elif last_c >= mid:
+		bias = "accumulation"
+	else:
+		bias = "distribution"
+
+	filtered = []
+	for ev in keep:
+		if bias == "accumulation" and ev["type"] == "UTAD" and sos and int(ev["idx"]) <= int(sos["idx"]):
+			continue
+		if bias == "distribution" and ev["type"] == "Spring" and sod and int(ev["idx"]) <= int(sod["idx"]):
+			continue
+		filtered.append(ev)
+
+	events = [{k: v for k, v in ev.items() if k != "idx"} for ev in filtered]
+
+	avg_volume = float(df["volume"].astype(float).iloc[max(0, e - 20) : e + 1].mean()) if "volume" in df.columns else 0.0
+	volume_confirm = {
+		"avg_volume": avg_volume,
+		"event_checks": {ev["type"]: {"volume_ok": ev.get("volume_ok"), "volume_ratio": ev.get("volume_ratio")} for ev in events},
+	}
+	return bias, events, volume_confirm
+
+
+def build_phases(
+	df: pd.DataFrame,
+	tr: Dict[str, Any],
+	bias: str,
+	events: List[Dict[str, Any]],
+	min_bars: int = 3,
+) -> List[Dict[str, Any]]:
+	"""
+	按威科夫事件锚点切分 A–E（启发式）。
+
+	吸筹：A停止 → B筑底 → C测试(Spring) → D拉升(SOS…LPS) → E离开
+	派发：A停止 → B筑顶 → C测试(UTAD) → D派发(SOW…LPSY) → E离开
+
+	无 Spring/UTAD 时：若已有 SOS/SOW，用突破前末次沿带测试补 C；仍无则省略 C。
+	"""
+	s = int(tr["abs_start_idx"])
+	e = int(tr["abs_end_idx"])
+	hi = float(tr["high"])
+	lo = float(tr["low"])
+	n_last = len(df) - 1
+	min_span = max(2, min_bars - 1)
+	range_len = max(1, e - s)
+
+	def _match_idx(t) -> Optional[int]:
+		if t is None:
+			return None
+		lo = max(0, s - 2)
+		hi = min(len(df), e + 40)
+		for i in range(lo, hi):
+			if _bar_time(df, i) == t:
+				return i
+		try:
+			tt = pd.Timestamp(t)
+			sample = None
+			if "date" in df.columns and len(df):
+				sample = df["date"].iloc[min(s, n_last)]
+			if sample is not None and getattr(sample, "tzinfo", None) is not None and tt.tzinfo is None:
+				tt = tt.tz_localize(sample.tzinfo)
+			for i in range(lo, hi):
+				bt = _bar_time(df, i)
+				try:
+					if abs((pd.Timestamp(bt) - tt).total_seconds()) <= 1:
+						return i
+				except Exception:
+					continue
+		except Exception:
+			pass
+		return None
+
+	event_idx: Dict[str, int] = {}
+	for ev in events:
+		idx = _match_idx(ev.get("time"))
+		if idx is not None:
+			event_idx[str(ev.get("type"))] = idx
+
+	accum = bias != "distribution"
+	if accum:
+		c_ev = event_idx.get("Spring")
+		d_ev = event_idx.get("SOS")
+		d_tail = event_idx.get("LPS") or d_ev
+	else:
+		c_ev = event_idx.get("UTAD")
+		d_ev = event_idx.get("SOW")
+		d_tail = event_idx.get("LPSY") or d_ev
+
+	# 有 D 无明确测试事件时：用突破前最后一次触及下/上沿作为 C（次级测试）
+	if c_ev is None and d_ev is not None:
+		band = lo + (hi - lo) * 0.28 if accum else hi - (hi - lo) * 0.28
+		for i in range(int(d_ev) - 1, s + 1, -1):
+			row = df.iloc[i]
+			if accum and float(row["low"]) <= band:
+				c_ev = i
+				break
+			if not accum and float(row["high"]) >= band:
+				c_ev = i
+				break
+
+	def _lab(phase: str) -> str:
+		if accum:
+			m = {"A": "A停止下跌", "B": "B筑底", "C": "C测试", "D": "D拉升", "E": "E离开"}
+		else:
+			m = {"A": "A停止上涨", "B": "B筑顶", "C": "C测试", "D": "D派发", "E": "E离开"}
+		return m.get(phase, phase)
+
+	a_end = s + max(min_bars, range_len // 5)
+
+	c_start = c_end = None
+	if c_ev is not None:
+		c_start = max(s, int(c_ev) - 1)
+		c_end = min(n_last, int(c_ev) + 1)
+
+	if d_ev is not None:
+		d_start = int(d_ev)
+		d_end = min(n_last, max(int(d_tail or d_ev), d_start) + max(min_bars, range_len // 8))
+		if d_tail is not None:
+			d_end = max(d_end, min(n_last, int(d_tail) + 1))
+	else:
+		d_start = d_end = None
+
+	if c_start is not None:
+		b_end = max(a_end + 1, c_start)
+	elif d_start is not None:
+		b_end = max(a_end + 1, d_start)
+	else:
+		b_end = max(a_end + 1, e)
+
+	if d_end is not None:
+		e_start = min(n_last, d_end)
+		e_end = n_last
+	else:
+		e_start = e_end = None
+
+	raw = [("A", s, a_end), ("B", a_end, b_end)]
+	if c_start is not None and c_end is not None:
+		raw.append(("C", c_start, c_end))
+	if d_start is not None and d_end is not None:
+		raw.append(("D", d_start, d_end))
+	if e_start is not None and e_end is not None and e_end > e_start:
+		raw.append(("E", e_start, e_end))
+
+	phases: List[Dict[str, Any]] = []
+	cursor = s
+	for phase, _a, _b in raw:
+		if cursor >= n_last:
+			break
+		a = max(int(_a), cursor)
+		b = int(max(int(_b), a))
+		need = 1 if phase == "C" else min_span
+		if b < a + need:
+			b = min(n_last, a + need)
+		b = int(np.clip(b, a, n_last))
+		if b < a:
+			continue
+		if phases and phases[-1].get("_a") == a and phases[-1].get("_b") == b:
+			continue
+		phases.append(
+			{
+				"phase": phase,
+				"label": _lab(phase),
+				"start_time": _bar_time(df, a),
+				"end_time": _bar_time(df, b),
+				"_a": a,
+				"_b": b,
+			}
+		)
+		cursor = b
+	for p in phases:
+		p.pop("_a", None)
+		p.pop("_b", None)
+	return phases

chanlun/analysis/wyckoff/live.py

@@ -0,0 +1,258 @@
+"""威科夫 Live / Developing 层（WYCKOFF-LIVE-STRUCTURE-001）。
+
+独立于 Confirmed Engine：不修改 events 确认条件，不写入 confirmed.events。
+Execution 不得消费本模块输出。
+"""
+from __future__ import annotations
+
+from typing import Any, Dict, List, Optional, Set
+
+import numpy as np
+import pandas as pd
+
+
+def _avg_vol(df: pd.DataFrame, i: int, win: int = 20) -> float:
+	a = max(0, i - win + 1)
+	v = df["volume"].astype(float).iloc[a : i + 1]
+	m = float(v.mean()) if len(v) else 0.0
+	return m if m > 0 else 1.0
+
+
+def _empty_live() -> Dict[str, Any]:
+	return {
+		"lifecycle": "UNKNOWN",
+		"range_formation": None,
+		"phase_candidate": None,
+		"event_candidates": [],
+		"next_expected": None,
+		"confidence": {
+			"cycle": 0.0,
+			"phase": 0.0,
+			"event": 0.0,
+			"structure": 0.0,
+			"volume": 0.0,
+			"overall": 0.0,
+		},
+		"note": "",
+	}
+
+
+def analyze_live_structure(
+	df: pd.DataFrame,
+	tr: Optional[Dict[str, Any]],
+	confirmed_events: Optional[List[Dict[str, Any]]] = None,
+	confirmed_phases: Optional[List[Dict[str, Any]]] = None,
+	bias: str = "unknown",
+) -> Dict[str, Any]:
+	"""
+	基于当前 TradingRange 与已确认事件，推演 Live candidates。
+	confirmed_* 只读，用于避免重复提示已确认事件，不修改之。
+	"""
+	out = _empty_live()
+	if df is None or len(df) < 20 or tr is None:
+		out["note"] = "insufficient structure"
+		return out
+
+	confirmed_events = confirmed_events or []
+	confirmed_phases = confirmed_phases or []
+	confirmed_types: Set[str] = {str(e.get("type")) for e in confirmed_events if e.get("type")}
+
+	s = int(tr["abs_start_idx"])
+	e = int(tr["abs_end_idx"])
+	scan_end = int(tr.get("abs_scan_end_idx", len(df) - 1))
+	scan_end = min(len(df) - 1, max(scan_end, e))
+	hi = float(tr["high"])
+	lo = float(tr["low"])
+	mid = float(tr["mid"])
+	tol = float(tr.get("tol") or (hi - lo) * 0.05)
+	atr = float(tr.get("atr") or max((hi - lo) * 0.2, 1e-9))
+
+	seg = df.iloc[s : e + 1]
+	if len(seg) < 8:
+		out["note"] = "range too short"
+		return out
+
+	# —— Range Formation（横盘 / 波动收敛）——
+	closes = seg["close"].astype(float)
+	highs = seg["high"].astype(float)
+	lows = seg["low"].astype(float)
+	vols = seg["volume"].astype(float) if "volume" in seg.columns else pd.Series([1.0] * len(seg))
+	half = max(4, len(seg) // 2)
+	vol_early = float(np.std(closes.iloc[:half])) if half > 1 else 0.0
+	vol_late = float(np.std(closes.iloc[-half:])) if half > 1 else 0.0
+	width = hi - lo
+	width_atr = width / atr if atr > 0 else 99.0
+	converging = vol_early > 1e-12 and vol_late < vol_early * 0.85
+	range_ok = 1.2 <= width_atr <= 10.0 and len(seg) >= 16
+	structure_score = 0.35
+	if range_ok:
+		structure_score += 0.25
+	if converging:
+		structure_score += 0.2
+	if width_atr <= 6.0:
+		structure_score += 0.1
+	structure_score = float(min(0.95, structure_score))
+
+	out["range_formation"] = {
+		"potential_trading_range": bool(range_ok),
+		"converging": bool(converging),
+		"width_atr": round(width_atr, 3),
+		"bars": int(len(seg)),
+	}
+
+	# —— 最近 K 形态（Phase C / Event candidates）——
+	i = scan_end
+	row = df.iloc[i]
+	o = float(row["open"])
+	h = float(row["high"])
+	l = float(row["low"])
+	c = float(row["close"])
+	rng = max(h - l, 1e-9)
+	lower_wick = min(o, c) - l
+	upper_wick = h - max(o, c)
+	avg_v = _avg_vol(df, i)
+	vol = float(row["volume"]) if "volume" in df.columns else avg_v
+	vol_ratio = vol / avg_v if avg_v else 1.0
+	volume_score = float(np.clip(1.1 - abs(vol_ratio - 1.0) * 0.35, 0.2, 0.95))
+
+	phase_candidate = None
+	phase_conf = 0.0
+	# Phase C：测低 + 下影 + 缩量（吸筹语境）
+	near_lo = l <= lo + tol * 1.2
+	test_low = l < mid and lower_wick >= rng * 0.35
+	vol_contract = vol_ratio <= 1.05
+	if bias != "distribution" and near_lo and test_low and vol_contract:
+		phase_candidate = "C"
+		phase_conf = 0.55 + (0.1 if lower_wick >= rng * 0.5 else 0) + (0.08 if vol_ratio < 0.9 else 0)
+	# Phase D 候选：价格在箱上半、有上破意图但未确认 SOS
+	elif c >= mid and (h >= hi - tol or c > hi - tol * 0.5):
+		phase_candidate = "D"
+		phase_conf = 0.5 + (0.1 if c > mid else 0)
+	elif c < mid and (l <= lo + tol):
+		phase_candidate = "B"
+		phase_conf = 0.45
+
+	# 已有 confirmed phase 时，candidate 取「下一阶段」提示，不覆盖事实
+	confirmed_phase_set = {str(p.get("phase")) for p in confirmed_phases}
+	if "E" in confirmed_phase_set:
+		phase_candidate = phase_candidate or "E"
+		phase_conf = max(phase_conf, 0.7)
+	elif "D" in confirmed_phase_set and phase_candidate is None:
+		phase_candidate = "D"
+		phase_conf = max(phase_conf, 0.65)
+
+	out["phase_candidate"] = phase_candidate
+	phase_conf = float(min(0.92, phase_conf))
+
+	# —— Event candidates（仅 Spring / SOS / LPS / UTAD）——
+	candidates: List[Dict[str, Any]] = []
+
+	def _add(typ: str, conf: float, note: str) -> None:
+		if typ in confirmed_types:
+			return  # 已确认则不再作为 candidate
+		candidates.append(
+			{
+				"type": typ,
+				"confidence": round(float(min(0.9, conf)), 3),
+				"confirmed": False,
+				"note": note,
+			}
+		)
+
+	# Spring candidate：刺破或贴近下沿，收盘收回，但未达 Confirmed 规则（或不在 confirmed）
+	pierce_lo = l < lo - tol * 0.15
+	close_back = c >= lo - tol * 0.5
+	if pierce_lo and close_back:
+		_add("Spring", 0.5 + (0.12 if vol_ratio <= 1.2 else 0) + (0.08 if close_back else 0), "假破下沿收回（未确认）")
+	elif l <= lo + tol * 0.35 and close_back and lower_wick >= rng * 0.4:
+		_add("Spring", 0.45 + (0.1 if vol_contract else 0), "测下沿长下影（未确认）")
+
+	# UTAD candidate
+	pierce_hi = h > hi + tol * 0.15
+	close_back_dn = c <= hi + tol * 0.5
+	if pierce_hi and close_back_dn:
+		_add("UTAD", 0.5 + (0.1 if vol_ratio >= 0.9 else 0), "假破上沿跌回（未确认）")
+
+	# SOS candidate：接近/轻破上沿，量能一般，未确认
+	if c > hi - tol * 0.4 or h >= hi:
+		sos_conf = 0.48 + (0.12 if c > hi else 0) + (0.1 if vol_ratio >= 1.05 else 0)
+		_add("SOS", sos_conf, "上破/逼近箱顶（未确认）")
+
+	# LPS candidate：站上 mid/上沿带后回踩
+	if c >= mid and l >= mid - tol * 1.5 and l > lo + (hi - lo) * 0.25:
+		_add("LPS", 0.46 + (0.1 if vol_ratio <= 1.0 else 0), "箱内上沿带回踩（未确认）")
+
+	candidates.sort(key=lambda x: x["confidence"], reverse=True)
+	out["event_candidates"] = candidates[:4]
+
+	event_score = float(candidates[0]["confidence"]) if candidates else 0.25
+
+	# next_expected（简规则）
+	next_exp = None
+	if "Spring" in confirmed_types and "SOS" not in confirmed_types:
+		next_exp = "SOS"
+	elif "SOS" in confirmed_types and "LPS" not in confirmed_types:
+		next_exp = "LPS"
+	elif "UTAD" in confirmed_types and "SOW" not in confirmed_types:
+		next_exp = "SOW"
+	elif any(c["type"] == "Spring" for c in candidates):
+		next_exp = "Test"
+	elif any(c["type"] == "SOS" for c in candidates):
+		next_exp = "LPS"
+	out["next_expected"] = next_exp
+
+	# —— lifecycle ——
+	key_confirmed = confirmed_types & {"Spring", "SOS", "UTAD", "SOW", "LPS", "LPSY"}
+	if key_confirmed:
+		lifecycle = "CONFIRMED"
+	elif range_ok or phase_candidate or candidates:
+		lifecycle = "FORMING"
+	else:
+		lifecycle = "UNKNOWN"
+	out["lifecycle"] = lifecycle
+
+	cycle_c = structure_score
+	overall = 0.35 * cycle_c + 0.25 * phase_conf + 0.25 * event_score + 0.15 * volume_score
+	out["confidence"] = {
+		"cycle": round(cycle_c, 3),
+		"phase": round(phase_conf, 3),
+		"event": round(event_score, 3),
+		"structure": round(structure_score, 3),
+		"volume": round(volume_score, 3),
+		"overall": round(float(overall), 3),
+	}
+	parts = []
+	if out["range_formation"]["potential_trading_range"]:
+		parts.append("Potential TR")
+	if phase_candidate:
+		parts.append(f"Phase {phase_candidate} candidate")
+	if candidates:
+		parts.append(f"{candidates[0]['type']} candidate")
+	out["note"] = "; ".join(parts) if parts else "observing"
+	return out
+
+
+def execution_signal_from_wyckoff(payload: Dict[str, Any]) -> Optional[Dict[str, Any]]:
+	"""
+	Execution 边界：只允许 Confirmed。
+	返回 source='confirmed' 的信号描述；Live-only 时返回 None。
+	"""
+	if not payload:
+		return None
+	cycles = payload.get("cycles") or []
+	active = cycles[0] if cycles else None
+	events = []
+	if active and isinstance(active.get("confirmed"), dict):
+		events = list(active["confirmed"].get("events") or [])
+	if not events:
+		# 兼容旧顶层 events（均为 confirmed 镜像）
+		events = list(payload.get("events") or [])
+	if not events:
+		return None
+	last = events[-1]
+	return {
+		"source": "confirmed",
+		"type": last.get("type"),
+		"time": last.get("time"),
+		"lifecycle": (active or {}).get("lifecycle") or "CONFIRMED",
+	}

chanlun/analysis/wyckoff/range.py

@@ -0,0 +1,442 @@
+"""交易区间检测：仅负责 TradingRange（起止/高低/结构分）。
+
+WYCKOFF-MULTI-CYCLE-001：Phase/Event/VP 不得进入本模块。
+过滤顺序固定：detect → quality → trend → overlap(<0.2) → accept → mask。
+"""
+from __future__ import annotations
+
+from typing import Any, Dict, List, Optional, Tuple
+
+import numpy as np
+import pandas as pd
+
+MAX_CYCLES = 8
+OVERLAP_RATIO_MAX = 0.2
+
+
+def _atr(df: pd.DataFrame, period: int = 14) -> pd.Series:
+	high = df["high"].astype(float)
+	low = df["low"].astype(float)
+	close = df["close"].astype(float)
+	prev_close = close.shift(1)
+	tr = pd.concat(
+		[
+			(high - low).abs(),
+			(high - prev_close).abs(),
+			(low - prev_close).abs(),
+		],
+		axis=1,
+	).max(axis=1)
+	return tr.rolling(period, min_periods=max(3, period // 2)).mean()
+
+
+def _robust_width(seg: pd.DataFrame) -> float:
+	"""用 90/10 分位估宽，避免单根影线把长窗卡死。"""
+	h = seg["high"].astype(float)
+	l = seg["low"].astype(float)
+	if len(seg) < 6:
+		return float(h.max() - l.min())
+	return float(np.nanpercentile(h, 90) - np.nanpercentile(l, 10))
+
+
+def _score_segment(
+	length: int,
+	near_hi: int,
+	near_lo: int,
+	inside: float,
+	width: float,
+	atr: float,
+) -> float:
+	"""结构质量分（非 Phase/Event）。"""
+	touch = min(near_hi, 6) + min(near_lo, 6)
+	width_pen = (width / atr) if atr > 0 else width
+	return float(touch) * 4.0 + float(inside) * 25.0 - width_pen * 3.0 + min(length / 40.0, 2.0)
+
+
+def _time_col(df: pd.DataFrame) -> Optional[str]:
+	if "date" in df.columns:
+		return "date"
+	if "timestamp" in df.columns:
+		return "timestamp"
+	return None
+
+
+def _bar_index_at_or_after(work: pd.DataFrame, ts: Any) -> Optional[int]:
+	col = _time_col(work)
+	if col is None or ts is None:
+		return None
+	try:
+		target = pd.Timestamp(ts)
+	except Exception:
+		return None
+	series = pd.to_datetime(work[col], utc=True, errors="coerce")
+	if target.tzinfo is None:
+		target = target.tz_localize("UTC")
+	else:
+		target = target.tz_convert("UTC")
+	if series.isna().all():
+		return None
+	ge = series >= target
+	if ge.any():
+		return int(np.flatnonzero(ge.to_numpy())[0])
+	return 0
+
+
+def _pack_range(
+	work: pd.DataFrame,
+	df: pd.DataFrame,
+	start_i: int,
+	end_i: int,
+	hi: float,
+	lo: float,
+	tol: float,
+	last_atr: float,
+	score: float,
+	n: int,
+	window_offset: int = 0,
+) -> Dict[str, Any]:
+	"""组装 TradingRange（仅结构字段）。"""
+	mid = (hi + lo) / 2.0
+	last_c = float(work["close"].iloc[min(end_i, len(work) - 1)])
+	price_in_box = (lo - tol * 1.5) <= last_c <= (hi + tol * 1.5)
+	bars = int(end_i - start_i + 1)
+	# 结构置信：归一化 score（启发式）
+	range_conf = float(np.clip(score / 55.0, 0.05, 0.99))
+	best = {
+		"start_idx": int(start_i),
+		"end_idx": int(end_i),
+		"high": float(hi),
+		"low": float(lo),
+		"mid": float(mid),
+		"active": bool(price_in_box),
+		"atr": float(last_atr),
+		"tol": float(tol),
+		"bars": bars,
+		"score": float(score),
+		"quality": float(score),
+		"range_confidence": range_conf,
+	}
+
+	def _ts(row) -> Any:
+		col = _time_col(work)
+		if col and pd.notna(row[col]):
+			return row[col]
+		return None
+
+	best["start_time"] = _ts(work.iloc[best["start_idx"]])
+	best["end_time"] = _ts(work.iloc[best["end_idx"]])
+	# window_offset：slice 相对父 DataFrame 的起点；勿用 len(df)-len(work)
+	offset = int(window_offset)
+	best["abs_start_idx"] = offset + best["start_idx"]
+	best["abs_end_idx"] = offset + best["end_idx"]
+	best["abs_scan_end_idx"] = offset + n - 1
+	return best
+
+
+def _overlap_ratio(a0: int, a1: int, b0: int, b1: int) -> float:
+	"""两闭区间重叠长度 / 较短区间长度。"""
+	lo = max(a0, b0)
+	hi = min(a1, b1)
+	if hi < lo:
+		return 0.0
+	overlap = hi - lo + 1
+	shorter = min(a1 - a0 + 1, b1 - b0 + 1)
+	if shorter <= 0:
+		return 0.0
+	return float(overlap) / float(shorter)
+
+
+def _passes_quality(tr: Dict[str, Any], min_bars: int) -> bool:
+	if tr is None:
+		return False
+	if int(tr.get("bars") or 0) < max(8, min_bars // 2):
+		return False
+	if float(tr.get("score") or 0) < 12.0:
+		return False
+	hi = float(tr["high"])
+	lo = float(tr["low"])
+	atr = float(tr.get("atr") or 0) or 1.0
+	if (hi - lo) / atr > 12.0:
+		return False
+	return True
+
+
+def _passes_trend_filter(work: pd.DataFrame, tr: Dict[str, Any]) -> bool:
+	"""趋势污染：定向位移过大则非震荡箱。"""
+	s = int(tr["start_idx"])
+	e = int(tr["end_idx"])
+	seg = work.iloc[s : e + 1]
+	if len(seg) < 8:
+		return False
+	c0 = float(seg["close"].iloc[0])
+	c1 = float(seg["close"].iloc[-1])
+	atr = float(tr.get("atr") or 0) or 1.0
+	drift = abs(c1 - c0) / atr
+	# 相对箱宽：漂移占箱宽过大 → 趋势
+	width = max(float(tr["high"]) - float(tr["low"]), atr)
+	drift_frac = abs(c1 - c0) / width
+	if drift > 6.0 and drift_frac > 0.55:
+		return False
+	return True
+
+
+def _detect_in_window(
+	df: pd.DataFrame,
+	win_start: int,
+	win_end: int,
+	min_bars: int = 24,
+	atr_mult: float = 1.2,
+	tail_reserve: int = 12,
+	prefer_start_time: Any = None,
+	range_start_time: Any = None,
+) -> Optional[Dict[str, Any]]:
+	"""
+	在 df[win_start:win_end+1] 内检测单个 TradingRange。
+	只返回箱体结构，不含 Phase/Event/VP。
+	"""
+	if df is None or win_end < win_start:
+		return None
+	slice_df = df.iloc[win_start : win_end + 1].reset_index(drop=True)
+	lookback = len(slice_df)
+	if lookback < min_bars + 5:
+		return None
+
+	work = slice_df
+	n = len(work)
+	reserve = min(tail_reserve, max(0, n - min_bars - 2))
+	core_end = n - reserve if reserve > 0 else n
+	core = work.iloc[:core_end]
+	if len(core) < min_bars:
+		core = work
+		core_end = n
+		reserve = 0
+
+	atr = _atr(work)
+	last_atr = float(atr.iloc[core_end - 1]) if atr.notna().iloc[:core_end].any() else float(
+		(core["high"] - core["low"]).mean()
+	)
+	if not np.isfinite(last_atr) or last_atr <= 0:
+		last_atr = float(core["close"].iloc[-1]) * 0.01
+
+	eff_atr_mult = float(atr_mult)
+	if lookback >= 280:
+		eff_atr_mult = atr_mult * 1.7
+	elif lookback >= 160:
+		eff_atr_mult = atr_mult * 1.3
+	width_factor = 3.8 + min(2.2, max(0.0, (lookback - 80) / 100.0))
+	max_width = last_atr * eff_atr_mult * width_factor
+	tol = last_atr * eff_atr_mult * 0.35
+
+	prefer_i = None
+	if prefer_start_time is not None:
+		prefer_i = _bar_index_at_or_after(work, prefer_start_time)
+
+	if range_start_time is not None:
+		start_i = _bar_index_at_or_after(work, range_start_time)
+		if start_i is not None and start_i <= core_end - 8:
+			seg = work.iloc[start_i:core_end]
+			hi = float(seg["high"].max())
+			lo = float(seg["low"].min())
+			rw = _robust_width(seg)
+			if 0 < rw <= max_width * 1.15:
+				near_hi = int((seg["high"] >= hi - tol).sum())
+				near_lo = int((seg["low"] <= lo + tol).sum())
+				inside = float(((seg["close"] >= lo - tol) & (seg["close"] <= hi + tol)).mean())
+				if near_hi >= 2 and near_lo >= 2 and inside >= 0.70:
+					score = _score_segment(len(seg), near_hi, near_lo, inside, rw, last_atr)
+					return _pack_range(
+						work, df, start_i, core_end - 1, hi, lo, tol, last_atr, score, n,
+						window_offset=win_start,
+					)
+
+	eff_min_bars = max(8, int(min_bars))
+	cn = len(core)
+	max_bars = min(cn, max(eff_min_bars * 2, min(96, max(eff_min_bars + 8, int(cn * 0.5)))))
+	cands: List[Tuple[float, int, int, int, float, float, float]] = []
+
+	def _try_seg(start_i: int, end_i: int, prefer_boost: float = 0.0) -> None:
+		if end_i - start_i + 1 < eff_min_bars:
+			return
+		if start_i < 0 or end_i >= cn or start_i > end_i:
+			return
+		seg = work.iloc[start_i : end_i + 1]
+		hi = float(seg["high"].max())
+		lo = float(seg["low"].min())
+		rw = _robust_width(seg)
+		if rw <= 0 or rw > max_width:
+			return
+		raw_w = hi - lo
+		if raw_w > max_width * 1.35:
+			return
+		near_hi = int((seg["high"] >= hi - tol).sum())
+		near_lo = int((seg["low"] <= lo + tol).sum())
+		if near_hi < 2 or near_lo < 2:
+			return
+		inside = float(((seg["close"] >= lo - tol) & (seg["close"] <= hi + tol)).mean())
+		if inside < 0.72:
+			return
+		length = end_i - start_i + 1
+		score = _score_segment(length, near_hi, near_lo, inside, rw, last_atr) + prefer_boost
+		cands.append((score, length, start_i, end_i, hi, lo, rw))
+
+	for length in range(min(cn, max_bars), eff_min_bars - 1, -4):
+		start_i = cn - length
+		boost = 0.0
+		if prefer_i is not None:
+			dist = abs(start_i - int(prefer_i))
+			if dist <= 6:
+				boost = 10.0
+			elif dist <= 14:
+				boost = 4.0
+			elif start_i > int(prefer_i) + 16:
+				boost = -10.0
+		_try_seg(start_i, cn - 1, boost)
+
+	if prefer_i is not None:
+		pi = int(prefer_i)
+		if 0 <= pi < cn:
+			align_max = min(cn, max(max_bars, int(cn * 0.65)))
+			alen = cn - pi
+			if eff_min_bars <= alen <= align_max:
+				_try_seg(pi, cn - 1, prefer_boost=18.0)
+			elif alen > align_max:
+				start_i = max(0, cn - align_max)
+				if start_i > pi:
+					start_i = pi
+					end_i = min(cn - 1, pi + align_max - 1)
+				else:
+					end_i = cn - 1
+				_try_seg(start_i, end_i, prefer_boost=12.0)
+
+	if not cands:
+		return None
+
+	cands.sort(key=lambda x: x[0], reverse=True)
+	best_score = cands[0][0]
+	band = max(4.0, abs(best_score) * 0.10)
+	near = [c for c in cands if c[0] >= best_score - band]
+	chosen = max(near, key=lambda x: (x[1], x[0]))
+	score, _length, start_i, end_i, hi, lo, _rw = chosen
+	return _pack_range(work, df, start_i, end_i, hi, lo, tol, last_atr, score, n, window_offset=win_start)
+
+
+def detect_trading_ranges(
+	df: pd.DataFrame,
+	lookback: Optional[int] = None,
+	min_bars: int = 24,
+	atr_mult: float = 1.2,
+	tail_reserve: int = 12,
+	max_cycles: int = MAX_CYCLES,
+	prefer_start_time: Any = None,
+	range_start_time: Any = None,
+) -> List[Dict[str, Any]]:
+	"""
+	倒序切多段 TradingRange（近→远）。
+	过滤顺序：detect → quality → trend → overlap → accept → mask。
+	返回列表已按时间倒序，调用方将 [0] 标为 ACTIVE。
+	"""
+	if df is None or len(df) < min_bars + 5:
+		return []
+	lb = int(lookback) if lookback is not None else len(df)
+	work = df.tail(lb).reset_index(drop=True)
+	n = len(work)
+	occupied: List[Dict[str, Any]] = []
+	accepted: List[Dict[str, Any]] = []
+
+	# 搜索右端从 n-1 往左收缩；每接受一段后右端移到该段 start 之前
+	search_end = n - 1
+	prefer = prefer_start_time
+	hard_start = range_start_time
+
+	while len(accepted) < max(1, int(max_cycles)) and search_end >= min_bars + 4:
+		# 在剩余历史内从右往左试多个右边界，避免历史箱必须贴住 search_end
+		# （否则中间趋势会挡住更早的真实箱）
+		cand = None
+		step = max(4, min(12, (search_end - min_bars) // 10 or 4))
+		for end_try in range(search_end, min_bars + 4, -step):
+			trial = _detect_in_window(
+				work,
+				0,
+				end_try,
+				min_bars=min_bars,
+				atr_mult=atr_mult,
+				tail_reserve=tail_reserve,
+				prefer_start_time=prefer if len(accepted) == 0 and end_try == search_end else None,
+				range_start_time=hard_start if len(accepted) == 0 and end_try == search_end else None,
+			)
+			# 1) detect
+			if trial is None:
+				continue
+			# 2) quality
+			if not _passes_quality(trial, min_bars):
+				continue
+			# 3) trend contamination
+			if not _passes_trend_filter(work, trial):
+				continue
+			# 4) overlap with accepted
+			a0, a1 = int(trial["abs_start_idx"]), int(trial["abs_end_idx"])
+			overlap_bad = False
+			for occ in occupied:
+				ratio = _overlap_ratio(a0, a1, int(occ["start"]), int(occ["end"]))
+				if ratio >= OVERLAP_RATIO_MAX:
+					overlap_bad = True
+					break
+			if overlap_bad:
+				continue
+			# 取最靠右的合格箱（倒序第一段）
+			cand = trial
+			break
+
+		if cand is None:
+			break
+
+		# 5) accept
+		accepted.append(cand)
+		a0, a1 = int(cand["abs_start_idx"]), int(cand["abs_end_idx"])
+		# 6) mask
+		occupied.append(
+			{
+				"start": a0,
+				"end": max(a1, int(cand.get("abs_scan_end_idx", a1))),
+				"quality": float(cand.get("quality") or 0),
+				"high": float(cand["high"]),
+				"low": float(cand["low"]),
+			}
+		)
+		# 下一轮只在更早窗口搜
+		search_end = int(cand["abs_start_idx"]) - 1
+		hard_start = None
+		prefer = None
+
+	# abs_* 目前相对 work；若 df 比 work 长需加 offset
+	offset = len(df) - len(work)
+	if offset:
+		for tr in accepted:
+			tr["abs_start_idx"] = int(tr["abs_start_idx"]) + offset
+			tr["abs_end_idx"] = int(tr["abs_end_idx"]) + offset
+			tr["abs_scan_end_idx"] = int(tr["abs_scan_end_idx"]) + offset
+
+	return accepted
+
+
+def detect_trading_range(
+	df: pd.DataFrame,
+	lookback: int = 120,
+	min_bars: int = 24,
+	atr_mult: float = 1.2,
+	tail_reserve: int = 12,
+	range_start_time: Any = None,
+	prefer_start_time: Any = None,
+) -> Optional[Dict[str, Any]]:
+	"""兼容旧接口：返回倒序列表中的第一段（ACTIVE 候选）。"""
+	ranges = detect_trading_ranges(
+		df,
+		lookback=lookback,
+		min_bars=min_bars,
+		atr_mult=atr_mult,
+		tail_reserve=tail_reserve,
+		max_cycles=1,
+		prefer_start_time=prefer_start_time,
+		range_start_time=range_start_time,
+	)
+	return ranges[0] if ranges else None

chanlun/analysis/wyckoff/volume_profile.py

@@ -0,0 +1,72 @@
+"""区间内 Volume Profile。"""
+from __future__ import annotations
+
+from typing import Any, Dict, List
+
+import numpy as np
+import pandas as pd
+
+
+def compute_volume_profile(
+	df: pd.DataFrame,
+	start_idx: int,
+	end_idx: int,
+	bin_count: int = 50,
+	value_area_pct: float = 0.70,
+) -> Dict[str, Any]:
+	seg = df.iloc[start_idx : end_idx + 1]
+	if seg.empty:
+		return {"bins": [], "poc": None, "vah": None, "val": None, "bin_count": bin_count}
+
+	typical = (seg["high"].astype(float) + seg["low"].astype(float) + seg["close"].astype(float)) / 3.0
+	vol = seg["volume"].astype(float).fillna(0.0)
+	lo = float(seg["low"].min())
+	hi = float(seg["high"].max())
+	if not np.isfinite(lo) or not np.isfinite(hi) or hi <= lo:
+		mid = float(seg["close"].iloc[-1])
+		return {
+			"bins": [{"price": mid, "volume": float(vol.sum())}],
+			"poc": mid,
+			"vah": mid,
+			"val": mid,
+			"bin_count": 1,
+		}
+
+	edges = np.linspace(lo, hi, bin_count + 1)
+	# 右开最后一桶闭合
+	idx = np.clip(np.digitize(typical.values, edges) - 1, 0, bin_count - 1)
+	vols = np.zeros(bin_count, dtype=float)
+	for i, v in zip(idx, vol.values):
+		vols[i] += float(v)
+
+	centers = (edges[:-1] + edges[1:]) / 2.0
+	poc_i = int(np.argmax(vols)) if vols.sum() > 0 else bin_count // 2
+	poc = float(centers[poc_i])
+
+	# Value Area：从 POC 向两侧扩展直到累计 >= value_area_pct
+	total = float(vols.sum()) or 1.0
+	target = total * value_area_pct
+	left = right = poc_i
+	acc = float(vols[poc_i])
+	while acc < target and (left > 0 or right < bin_count - 1):
+		left_v = vols[left - 1] if left > 0 else -1.0
+		right_v = vols[right + 1] if right < bin_count - 1 else -1.0
+		if right_v >= left_v and right < bin_count - 1:
+			right += 1
+			acc += float(vols[right])
+		elif left > 0:
+			left -= 1
+			acc += float(vols[left])
+		else:
+			break
+
+	bins: List[Dict[str, float]] = [
+		{"price": float(centers[i]), "volume": float(vols[i])} for i in range(bin_count)
+	]
+	return {
+		"bins": bins,
+		"poc": poc,
+		"vah": float(centers[right]),
+		"val": float(centers[left]),
+		"bin_count": bin_count,
+	}

chanlun/pipeline/builders/indicators.py

@@ -55,8 +55,8 @@ class IndicatorsBuilderMixin:
 		return None
 
 	def add_indicators(self, df):
-		fast = 26
-		slow = 52
+		fast = 12
+		slow = 26
 		period = 9
 		macd = ta.MACD(df, fastperiod=fast, slowperiod=slow, signalperiod=period)
 		bb365 = ta.BBANDS(df, timeperiod=365, nbdevup=3.0, nbdevdn=3.0, matype=0)

crypto_wyckoff/__init__.py

@@ -0,0 +1,5 @@
+"""crypto_wyckoff — multi-TF screener for crypto (ported from A_Share_DP Architecture v1.0)."""
+
+from crypto_wyckoff.version import ARCHITECTURE_VERSION, WYCKOFF_ENGINE_VERSION
+
+__all__ = ["WYCKOFF_ENGINE_VERSION", "ARCHITECTURE_VERSION"]

crypto_wyckoff/annotate.py

@@ -0,0 +1,329 @@
+"""Walk-forward Wyckoff phase/event annotations for chart overlay."""
+
+from __future__ import annotations
+
+from datetime import date
+
+from crypto_wyckoff.domain_models import OHLCVFrame, WyckoffCycle, WyckoffEvent, WyckoffPhase
+from crypto_wyckoff.cycle import CycleEngine
+from crypto_wyckoff.event import EventEngine
+from crypto_wyckoff.features import FeatureEngine
+from crypto_wyckoff.phase import PhaseEngine
+
+_MIN_BARS = {"1d": 40, "1w": 26, "1M": 18}
+
+_NOTABLE_EVENTS = {
+    WyckoffEvent.PS.value,
+    WyckoffEvent.SC.value,
+    WyckoffEvent.AR.value,
+    WyckoffEvent.ST.value,
+    WyckoffEvent.SPRING.value,
+    WyckoffEvent.TEST.value,
+    WyckoffEvent.SOS.value,
+    WyckoffEvent.LPS.value,
+    WyckoffEvent.JUMP.value,
+    WyckoffEvent.BACKUP.value,
+    WyckoffEvent.BC.value,
+    WyckoffEvent.UTAD.value,
+    WyckoffEvent.SOW.value,
+    WyckoffEvent.LPSY.value,
+}
+
+
+def _slice_frame(frame: OHLCVFrame, end_idx: int) -> OHLCVFrame:
+    n = end_idx + 1
+    return OHLCVFrame(
+        ts_code=frame.ts_code,
+        timeframe=frame.timeframe,
+        trade_dates=frame.trade_dates[:n],
+        open=frame.open[:n],
+        high=frame.high[:n],
+        low=frame.low[:n],
+        close=frame.close[:n],
+        volume=frame.volume[:n],
+        amount=frame.amount[:n] if frame.amount else [],
+    )
+
+
+def _compress_phases(points: list[tuple[str, str]]) -> list[dict]:
+    """points: [(date_iso, phase), ...] → segments."""
+    if not points:
+        return []
+    segs: list[dict] = []
+    start, phase = points[0]
+    prev = start
+    for d, p in points[1:]:
+        if p != phase:
+            segs.append({"start": start, "end": prev, "phase": phase})
+            start, phase = d, p
+        prev = d
+    segs.append({"start": start, "end": prev, "phase": phase})
+    return segs
+
+
+def annotate_frame(frame: OHLCVFrame, step: int | None = None) -> dict:
+    """Pure annotation: phase bands + event markers + latest levels.
+
+    ``step`` defaults by timeframe to keep interactive charts snappy.
+    """
+    tf = frame.timeframe
+    min_bars = _MIN_BARS.get(tf, 30)
+    if step is None:
+        step = {"1d": 2, "1w": 1, "1M": 1}.get(tf, 2)
+
+    empty = {
+        "phases": [],
+        "events": [],
+        "levels": {},
+        "bars": len(frame),
+        "timeframe": tf,
+    }
+    if frame.empty or len(frame) < min_bars:
+        return empty
+
+    feat_eng = FeatureEngine()
+    cycle_eng = CycleEngine()
+    phase_eng = PhaseEngine()
+    event_eng = EventEngine()
+
+    phase_points: list[tuple[str, str]] = []
+    events: list[dict] = []
+    last_event: str | None = None
+    levels: dict = {}
+
+    # Ensure last bar is always evaluated
+    indices = list(range(min_bars - 1, len(frame), step))
+    if indices[-1] != len(frame) - 1:
+        indices.append(len(frame) - 1)
+
+    for i in indices:
+        sub = _slice_frame(frame, i)
+        f = feat_eng.run(sub, tf)
+        c = cycle_eng.run(f, tf)
+        p = phase_eng.run(c, f, tf)
+        e = event_eng.run(c, p, f, tf)
+
+        d = str(frame.trade_dates[i])[:10]
+        phase = p.payload.get("phase") or WyckoffPhase.NONE.value
+        phase_points.append((d, phase))
+
+        cur = e.payload.get("current_event") or WyckoffEvent.NONE.value
+        if cur in _NOTABLE_EVENTS and cur != last_event:
+            events.append({
+                "date": d,
+                "event": cur,
+                "price": float(frame.close[i]),
+                "low": float(frame.low[i]),
+                "high": float(frame.high[i]),
+            })
+            last_event = cur
+        elif cur == WyckoffEvent.NONE.value:
+            last_event = None
+
+        if i == len(frame) - 1 and not f.payload.get("insufficient"):
+            levels = {
+                k: f.payload.get(k)
+                for k in (
+                    "range_high", "range_low", "ma20", "ma60",
+                    "swing_high", "swing_low", "close",
+                )
+                if f.payload.get(k) is not None
+            }
+            levels["phase"] = phase
+            levels["cycle"] = c.payload.get("cycle")
+            levels["current_event"] = cur
+
+    return {
+        "phases": _compress_phases(phase_points),
+        "events": events,
+        "levels": levels,
+        "bars": len(frame),
+        "timeframe": tf,
+    }
+
+
+_RANGE_CYCLES = {
+    WyckoffCycle.ACCUMULATION.value,
+    WyckoffCycle.RE_ACCUMULATION.value,
+    WyckoffCycle.DISTRIBUTION.value,
+    WyckoffCycle.RE_DISTRIBUTION.value,
+}
+
+
+def _build_range_zones(
+    price_frame: OHLCVFrame,
+    cycle_segs: list[dict],
+    levels: dict | None = None,
+) -> list[dict]:
+    """Build price boxes (high/low × date span) for accum/distrib ranges."""
+    if price_frame.empty:
+        return []
+    dates = [str(d)[:10] for d in price_frame.trade_dates]
+    highs = price_frame.high
+    lows = price_frame.low
+    zones: list[dict] = []
+
+    for seg in cycle_segs or []:
+        cy = seg.get("cycle")
+        if cy not in _RANGE_CYCLES:
+            continue
+        start, end = seg["start"], seg["end"]
+        idxs = [i for i, d in enumerate(dates) if start <= d <= end]
+        if not idxs:
+            # weekly bar date may sit between daily bars — take nearest window
+            i0 = next((i for i, d in enumerate(dates) if d >= start), None)
+            if i0 is None:
+                continue
+            i1 = next((i for i, d in enumerate(dates) if d > end), len(dates)) - 1
+            idxs = list(range(i0, max(i0, i1) + 1))
+        if not idxs:
+            continue
+        # pad short weekly hits to at least ~1 week of dailies for visibility
+        if len(idxs) < 5 and idxs[-1] + 1 < len(dates):
+            extra = min(5 - len(idxs), len(dates) - 1 - idxs[-1])
+            idxs = list(range(idxs[0], idxs[-1] + 1 + max(0, extra)))
+        hi = max(highs[i] for i in idxs)
+        lo = min(lows[i] for i in idxs)
+        if hi <= lo:
+            continue
+        zones.append({
+            "kind": cy,
+            "start": dates[idxs[0]],
+            "end": dates[idxs[-1]],
+            "high": float(hi),
+            "low": float(lo),
+            "current": False,
+        })
+
+    # Always expose the latest trading-range box from feature snapshot
+    levels = levels or {}
+    rh, rl = levels.get("range_high"), levels.get("range_low")
+    if rh is not None and rl is not None and float(rh) > float(rl):
+        look = min(60, len(dates))
+        cy = levels.get("cycle") or "Unknown"
+        if cy not in _RANGE_CYCLES:
+            # Phase B/C in a range → treat as accumulation-style TR for display
+            ph = levels.get("phase") or ""
+            if ph in ("A", "B", "C"):
+                cy = WyckoffCycle.ACCUMULATION.value
+            elif ph in ("D", "E") and float(levels.get("close") or 0) < float(rh):
+                cy = WyckoffCycle.ACCUMULATION.value
+            else:
+                cy = "Range"
+        zones.append({
+            "kind": cy,
+            "start": dates[-look],
+            "end": dates[-1],
+            "high": float(rh),
+            "low": float(rl),
+            "current": True,
+        })
+
+    return zones
+
+
+def annotate_symbol(
+    ts_code: str,
+    freq: str,
+    end_date: date | None = None,
+    lookback: int = 180,
+) -> dict:
+    """IO + annotate for one symbol (used by API).
+
+    For daily charts, phase bands come from **weekly** structure (Wyckoff
+    primary timeframe), while event markers / levels come from daily.
+    """
+    from crypto_wyckoff.io import latest_daily_trade_date, load_frames_batch
+
+    if freq not in ("1d", "1w", "1M"):
+        raise ValueError(f"unsupported freq: {freq}")
+    ed = end_date or latest_daily_trade_date()
+    empty = {
+        "ts_code": ts_code,
+        "freq": freq,
+        "phases": [],
+        "events": [],
+        "levels": {},
+        "zones": [],
+        "bars": 0,
+        "phase_source": freq,
+    }
+    if ed is None:
+        return empty
+
+    if freq == "1d":
+        daily_frames = load_frames_batch("1d", ed, lookback, ts_codes=[ts_code])
+        weekly_frames = load_frames_batch("1w", ed, max(60, lookback // 3), ts_codes=[ts_code])
+        daily = daily_frames.get(ts_code)
+        weekly = weekly_frames.get(ts_code)
+        if daily is None:
+            return empty
+        d_ann = annotate_frame(daily)
+        w_ann = annotate_frame(weekly) if weekly is not None else {"phases": []}
+        cycles = _cycle_segments(weekly) if weekly is not None else []
+        levels = d_ann.get("levels") or {}
+        # Prefer weekly cycle on the latest levels for zone labeling
+        if cycles:
+            levels = {**levels, "cycle": cycles[-1].get("cycle") or levels.get("cycle")}
+            # latest non-None weekly phase
+            for p in reversed(w_ann.get("phases") or []):
+                if p.get("phase") not in (None, "None"):
+                    levels = {**levels, "phase": p["phase"]}
+                    break
+        return {
+            "ts_code": ts_code,
+            "freq": freq,
+            "end_date": ed.isoformat(),
+            "phases": w_ann.get("phases") or [],
+            "events": d_ann.get("events") or [],
+            "levels": d_ann.get("levels") or {},
+            "zones": _build_range_zones(daily, cycles, levels),
+            "bars": d_ann.get("bars", 0),
+            "phase_source": "1w",
+            "cycles": cycles,
+        }
+
+    frames = load_frames_batch(freq, ed, lookback, ts_codes=[ts_code])
+    frame = frames.get(ts_code)
+    if frame is None:
+        return empty
+    out = annotate_frame(frame)
+    out["ts_code"] = ts_code
+    out["freq"] = freq
+    out["end_date"] = ed.isoformat()
+    out["phase_source"] = freq
+    out["cycles"] = _cycle_segments(frame)
+    out["zones"] = _build_range_zones(frame, out["cycles"], out.get("levels") or {})
+    if freq == "1M":
+        # Monthly chart: cycle bands are more meaningful than phase
+        if not any(p.get("phase") not in (None, "None") for p in out["phases"]):
+            out["phases"] = [
+                {"start": c["start"], "end": c["end"], "phase": c["cycle"]}
+                for c in out["cycles"]
+                if c.get("cycle") and c["cycle"] != "Unknown"
+            ]
+    return out
+
+
+def _cycle_segments(frame: OHLCVFrame, step: int | None = None) -> list[dict]:
+    """Walk-forward cycle labels compressed to segments."""
+    tf = frame.timeframe
+    min_bars = _MIN_BARS.get(tf, 30)
+    if step is None:
+        step = {"1d": 3, "1w": 1, "1M": 1}.get(tf, 2)
+    if frame.empty or len(frame) < min_bars:
+        return []
+
+    feat_eng = FeatureEngine()
+    cycle_eng = CycleEngine()
+    points: list[tuple[str, str]] = []
+    indices = list(range(min_bars - 1, len(frame), step))
+    if indices[-1] != len(frame) - 1:
+        indices.append(len(frame) - 1)
+    for i in indices:
+        sub = _slice_frame(frame, i)
+        f = feat_eng.run(sub, tf)
+        c = cycle_eng.run(f, tf)
+        points.append((str(frame.trade_dates[i])[:10], c.payload.get("cycle") or "Unknown"))
+    segs = _compress_phases(points)
+    return [{"start": s["start"], "end": s["end"], "cycle": s["phase"]} for s in segs]

crypto_wyckoff/cycle.py

@@ -0,0 +1,102 @@
+"""Cycle Engine — monthly/weekly macro cycle via Rule Registry."""
+
+from __future__ import annotations
+
+from crypto_wyckoff.domain_models import EngineResult, WyckoffCycle
+from crypto_wyckoff.rules.base import RuleHit
+from crypto_wyckoff.rules.registry import rule_registry
+
+
+def _resolve_range_conflict(hits: list[RuleHit], features: dict) -> list[RuleHit]:
+    """Accumulation vs Distribution overlap → mutually exclusive by MA120 position."""
+    accum = [h for h in hits if h.cycle == WyckoffCycle.ACCUMULATION.value]
+    dist = [h for h in hits if h.cycle == WyckoffCycle.DISTRIBUTION.value]
+    if not (accum and dist):
+        return hits
+
+    close = float(features.get("close") or 0)
+    ma120 = float(features.get("ma120") or close) or close
+    others = [
+        h for h in hits
+        if h.cycle not in (WyckoffCycle.ACCUMULATION.value, WyckoffCycle.DISTRIBUTION.value)
+    ]
+    # Below MA120 → accumulation; above → distribution; equal band uses relative position
+    if close < ma120 * 0.995:
+        return others + accum
+    if close > ma120 * 1.005:
+        return others + dist
+    # Tight band: keep higher confidence only
+    best_a = max(accum, key=lambda h: h.confidence)
+    best_d = max(dist, key=lambda h: h.confidence)
+    return others + ([best_a] if best_a.confidence >= best_d.confidence else [best_d])
+
+
+class CycleEngine:
+    name = "Cycle"
+    version = "1.0.0"
+
+    def run(self, feature: EngineResult, timeframe: str) -> EngineResult:
+        features = feature.payload
+        if features.get("insufficient"):
+            return EngineResult(
+                name=self.name,
+                version=self.version,
+                confidence=15.0,
+                score=40.0,
+                reasons=[f"{timeframe} 数据不足，Cycle=Unknown"],
+                warnings=["insufficient_features"],
+                payload={
+                    "cycle": WyckoffCycle.UNKNOWN.value,
+                    "timeframe": timeframe,
+                    "trend_score": 40.0,
+                },
+            )
+
+        context = {"features": features, "timeframe": timeframe}
+        hits: list[RuleHit] = []
+        for rule in rule_registry.by_category("cycle", timeframe):
+            hit = rule.evaluate(context)
+            if hit and hit.cycle:
+                hits.append(hit)
+
+        hits = _resolve_range_conflict(hits, features)
+
+        if not hits:
+            return EngineResult(
+                name=self.name,
+                version=self.version,
+                confidence=30.0,
+                score=40.0,
+                reasons=["无匹配周期规则，标记 Unknown"],
+                payload={
+                    "cycle": WyckoffCycle.UNKNOWN.value,
+                    "timeframe": timeframe,
+                    "trend_score": 40.0,
+                },
+            )
+
+        best = max(hits, key=lambda h: h.confidence)
+        trend_score = best.score
+        if best.cycle == WyckoffCycle.MARKUP.value:
+            trend_score = max(trend_score, 75.0)
+        elif best.cycle == WyckoffCycle.ACCUMULATION.value:
+            trend_score = max(60.0, trend_score * 0.9)
+        elif best.cycle == WyckoffCycle.DISTRIBUTION.value:
+            trend_score = min(45.0, 100 - trend_score * 0.5)
+        elif best.cycle == WyckoffCycle.MARKDOWN.value:
+            trend_score = min(30.0, 100 - trend_score)
+
+        return EngineResult(
+            name=self.name,
+            version=self.version,
+            confidence=best.confidence,
+            score=trend_score,
+            reasons=best.reasons,
+            metrics=best.metrics,
+            payload={
+                "cycle": best.cycle,
+                "timeframe": timeframe,
+                "rule_id": best.rule_id,
+                "trend_score": trend_score,
+            },
+        )

crypto_wyckoff/decision.py

@@ -0,0 +1,195 @@
+"""Decision Engine — multi-timeframe fusion and tradability (Architecture v1.0)."""
+
+from __future__ import annotations
+
+from crypto_wyckoff.domain_models import (
+    DecisionSignal,
+    EngineResult,
+    RiskLevel,
+    WyckoffCycle,
+    WyckoffEvent,
+    WyckoffPhase,
+)
+
+BULL_CYCLES = {
+    WyckoffCycle.ACCUMULATION.value,
+    WyckoffCycle.RE_ACCUMULATION.value,
+    WyckoffCycle.MARKUP.value,
+}
+BEAR_CYCLES = {
+    WyckoffCycle.DISTRIBUTION.value,
+    WyckoffCycle.RE_DISTRIBUTION.value,
+    WyckoffCycle.MARKDOWN.value,
+}
+
+
+class DecisionEngine:
+    name = "Decision"
+    version = "1.0.0"
+
+    def run(
+        self,
+        monthly_cycle: EngineResult,
+        weekly_cycle: EngineResult,
+        weekly_phase: EngineResult,
+        weekly_event: EngineResult,
+        daily_event: EngineResult,
+        daily_signal: EngineResult,
+    ) -> EngineResult:
+        m_cycle = monthly_cycle.payload.get("cycle", WyckoffCycle.UNKNOWN.value)
+        w_cycle = weekly_cycle.payload.get("cycle", WyckoffCycle.UNKNOWN.value)
+        w_phase = weekly_phase.payload.get("phase", WyckoffPhase.NONE.value)
+        w_event = weekly_event.payload.get("current_event", WyckoffEvent.NONE.value)
+        d_event = daily_event.payload.get("current_event", WyckoffEvent.NONE.value)
+
+        trend_score = float(monthly_cycle.payload.get("trend_score", monthly_cycle.score))
+        structure_score = float(weekly_phase.payload.get("structure_score", weekly_phase.score))
+        entry_score = float(daily_event.payload.get("entry_score", daily_event.score))
+
+        overall_score = 0.30 * trend_score + 0.30 * structure_score + 0.40 * entry_score
+
+        reasons: list[str] = []
+        warnings: list[str] = []
+        alignment = 50.0
+
+        m_bull = m_cycle in BULL_CYCLES
+        m_bear = m_cycle in BEAR_CYCLES
+        w_bull = w_cycle in BULL_CYCLES
+        d_bullish_event = d_event in {
+            WyckoffEvent.SPRING.value,
+            WyckoffEvent.TEST.value,
+            WyckoffEvent.SOS.value,
+            WyckoffEvent.LPS.value,
+            WyckoffEvent.JUMP.value,
+            WyckoffEvent.BACKUP.value,
+        }
+        d_bearish_event = d_event in {
+            WyckoffEvent.UTAD.value,
+            WyckoffEvent.SOW.value,
+            WyckoffEvent.LPSY.value,
+        }
+
+        # Alignment scoring
+        if m_bull and w_bull and d_bullish_event:
+            alignment = 92.0
+            reasons.append("✓ 月/周多头结构与日线多头事件一致")
+        elif m_bull and d_bullish_event:
+            alignment = 78.0
+            reasons.append("✓ 月线支持，日线有入场事件")
+            if not w_bull:
+                warnings.append("周线结构未完全确认")
+                alignment -= 8
+        elif m_bear and d_bullish_event:
+            alignment = 35.0
+            reasons.append("✗ 月线派发/下跌，日线弹簧可能只是反弹")
+        elif m_bear and d_bearish_event:
+            alignment = 85.0
+            reasons.append("✓ 空头多周期一致")
+        else:
+            alignment = 55.0
+            reasons.append("○ 多周期部分一致，需观察")
+
+        if w_phase in (WyckoffPhase.D.value, WyckoffPhase.E.value) and m_bull:
+            alignment = min(98.0, alignment + 6)
+            reasons.append(f"✓ 周线阶段 {w_phase} 结构成熟（{w_event}）")
+        active = daily_event.payload.get("active_events") or daily_event.payload.get("recent_events") or []
+        if d_event == WyckoffEvent.SPRING.value and len(active) >= 3:
+            alignment = min(98.0, alignment + 4)
+            reasons.append("✓ 日线多重事件同时确认")
+
+        # Decision signal — hard gate on monthly bear + daily spring
+        decision = DecisionSignal.WATCH.value
+        risk = RiskLevel.MEDIUM.value
+
+        if m_bear and d_event == WyckoffEvent.SPRING.value:
+            decision = DecisionSignal.WATCH.value
+            risk = RiskLevel.HIGH.value
+            overall_score = min(overall_score, 55.0)
+            reasons.append("→ 决策：观察（月线不支持，禁止追日线弹簧）")
+        elif m_bear and d_bullish_event:
+            decision = DecisionSignal.AVOID.value
+            risk = RiskLevel.HIGH.value
+            overall_score = min(overall_score, 48.0)
+            reasons.append("→ 决策：回避（逆大周期多头事件）")
+        elif (
+            m_bull
+            and w_phase in (WyckoffPhase.D.value, WyckoffPhase.E.value, WyckoffPhase.C.value)
+            and d_event in (WyckoffEvent.SPRING.value, WyckoffEvent.LPS.value, WyckoffEvent.SOS.value)
+            and alignment >= 85
+            and overall_score >= 80
+        ):
+            decision = DecisionSignal.STRONG_BUY.value
+            risk = RiskLevel.LOW.value
+            reasons.append("→ 决策：强烈买入（三级共振）")
+        elif m_bull and d_bullish_event and overall_score >= 68 and alignment >= 70:
+            decision = DecisionSignal.BUY.value
+            risk = RiskLevel.LOW.value if alignment >= 80 else RiskLevel.MEDIUM.value
+            reasons.append("→ 决策：买入")
+        elif m_bear and d_bearish_event and overall_score >= 65:
+            decision = DecisionSignal.SELL.value
+            risk = RiskLevel.MEDIUM.value
+            reasons.append("→ 决策：卖出")
+        else:
+            decision = DecisionSignal.WATCH.value
+            reasons.append("→ 决策：观察")
+
+        # Stars from score + alignment
+        combo = 0.6 * overall_score + 0.4 * alignment
+        if combo >= 90:
+            stars = 5
+        elif combo >= 80:
+            stars = 4
+        elif combo >= 65:
+            stars = 3
+        elif combo >= 50:
+            stars = 2
+        else:
+            stars = 1
+
+        overall_confidence = (
+            0.25 * monthly_cycle.confidence
+            + 0.25 * weekly_phase.confidence
+            + 0.25 * daily_event.confidence
+            + 0.25 * daily_signal.confidence
+        )
+        # Weak event pulls overall down
+        if daily_event.confidence < 60:
+            overall_confidence = min(overall_confidence, daily_event.confidence + 15)
+
+        return EngineResult(
+            name=self.name,
+            version=self.version,
+            confidence=overall_confidence,
+            score=overall_score,
+            reasons=reasons,
+            warnings=warnings,
+            metrics={
+                "trend_score": trend_score,
+                "structure_score": structure_score,
+                "entry_score": entry_score,
+                "alignment": alignment,
+                "stars": stars,
+            },
+            payload={
+                "decision_signal": decision,
+                "alignment": alignment,
+                "stars": stars,
+                "risk": risk,
+                "overall_score": overall_score,
+                "overall_confidence": overall_confidence,
+                "trend_score": trend_score,
+                "structure_score": structure_score,
+                "entry_score": entry_score,
+                "m_cycle": m_cycle,
+                "w_cycle": w_cycle,
+                "w_phase": w_phase,
+                "w_event": w_event,
+                "d_event": d_event,
+                # Facts preserved — never overwritten
+                "facts": {
+                    "monthly": {"cycle": m_cycle},
+                    "weekly": {"cycle": w_cycle, "phase": w_phase, "event": w_event},
+                    "daily": {"event": d_event},
+                },
+            },
+        )

crypto_wyckoff/domain_models.py

@@ -0,0 +1,153 @@
+"""Wyckoff Screener domain models — Architecture v1.0 frozen contracts."""
+
+from __future__ import annotations
+
+from dataclasses import dataclass, field
+from datetime import date, datetime
+from enum import Enum
+from typing import Any, Optional
+
+
+class WyckoffCycle(str, Enum):
+    ACCUMULATION = "Accumulation"
+    RE_ACCUMULATION = "ReAccumulation"
+    MARKUP = "Markup"
+    DISTRIBUTION = "Distribution"
+    RE_DISTRIBUTION = "ReDistribution"
+    MARKDOWN = "Markdown"
+    UNKNOWN = "Unknown"
+
+
+class WyckoffPhase(str, Enum):
+    A = "A"
+    B = "B"
+    C = "C"
+    D = "D"
+    E = "E"
+    NONE = "None"
+
+
+class WyckoffEvent(str, Enum):
+    PS = "PS"
+    SC = "SC"
+    AR = "AR"
+    ST = "ST"
+    SPRING = "Spring"
+    TEST = "Test"
+    SOS = "SOS"
+    LPS = "LPS"
+    JUMP = "Jump"
+    BACKUP = "Backup"
+    BC = "BC"
+    UTAD = "UTAD"
+    SOW = "SOW"
+    LPSY = "LPSY"
+    NONE = "None"
+
+
+class DecisionSignal(str, Enum):
+    STRONG_BUY = "StrongBuy"
+    BUY = "Buy"
+    WATCH = "Watch"
+    AVOID = "Avoid"
+    SELL = "Sell"
+
+
+class RiskLevel(str, Enum):
+    LOW = "Low"
+    MEDIUM = "Medium"
+    HIGH = "High"
+
+
+@dataclass
+class EngineResult:
+    """Unified result envelope for every Wyckoff engine (v1.0 contract)."""
+
+    name: str
+    version: str = "1.0.0"
+    confidence: float = 0.0
+    score: float = 0.0
+    reasons: list[str] = field(default_factory=list)
+    warnings: list[str] = field(default_factory=list)
+    metrics: dict[str, Any] = field(default_factory=dict)
+    payload: dict[str, Any] = field(default_factory=dict)
+
+    def to_dict(self) -> dict[str, Any]:
+        return {
+            "name": self.name,
+            "version": self.version,
+            "confidence": self.confidence,
+            "score": self.score,
+            "reasons": self.reasons,
+            "warnings": self.warnings,
+            "metrics": self.metrics,
+            "payload": self.payload,
+        }
+
+
+@dataclass
+class OHLCVFrame:
+    """In-memory OHLCV for one symbol one timeframe. Engines never touch DB."""
+
+    ts_code: str
+    timeframe: str  # "1d" | "1w" | "1M"
+    trade_dates: list[date]
+    open: list[float]
+    high: list[float]
+    low: list[float]
+    close: list[float]
+    volume: list[float]
+    amount: list[float] = field(default_factory=list)
+
+    def __len__(self) -> int:
+        return len(self.close)
+
+    @property
+    def empty(self) -> bool:
+        return len(self.close) == 0
+
+
+@dataclass
+class WyckoffScanRow:
+    """Persisted scan row for wyckoff_scan table."""
+
+    trade_date: date
+    ts_code: str
+    name: str = ""
+    industry: str = ""
+    engine_version: str = "v1.0.0"
+
+    m_cycle: str = WyckoffCycle.UNKNOWN.value
+    cycle_confidence: float = 0.0
+    trend_score: float = 0.0
+
+    w_cycle: str = WyckoffCycle.UNKNOWN.value
+    w_phase: str = WyckoffPhase.NONE.value
+    w_current_event: str = WyckoffEvent.NONE.value
+    w_recent_events_json: str = "[]"
+    phase_confidence: float = 0.0
+    structure_score: float = 0.0
+
+    d_current_event: str = WyckoffEvent.NONE.value
+    d_recent_events_json: str = "[]"
+    event_confidence: float = 0.0
+    entry_score: float = 0.0
+
+    entry: Optional[float] = None
+    stop: Optional[float] = None
+    target1: Optional[float] = None
+    target2: Optional[float] = None
+    rr: Optional[float] = None
+
+    alignment: float = 0.0
+    stars: int = 1
+    decision_signal: str = DecisionSignal.WATCH.value
+    signal_confidence: float = 0.0
+    overall_confidence: float = 0.0
+    overall_score: float = 0.0
+    risk: str = RiskLevel.MEDIUM.value
+    reasons_json: str = "[]"
+
+    feature_snapshot_json: str = "{}"
+    markers_json: str = "[]"
+    scanned_at: datetime = field(default_factory=datetime.now)

crypto_wyckoff/event.py

@@ -0,0 +1,149 @@
+"""Event Engine — active concurrent events via Rule Registry.
+
+Note: `active_events` are rules that fire on the latest bar snapshot,
+NOT a historical SC→AR→ST timeline. Do not present as chronological chain.
+"""
+
+from __future__ import annotations
+
+from crypto_wyckoff.domain_models import EngineResult, WyckoffEvent
+from crypto_wyckoff.rules.registry import rule_registry
+
+# Display order only (not temporal history)
+_DISPLAY_ORDER = [
+    WyckoffEvent.PS.value,
+    WyckoffEvent.SC.value,
+    WyckoffEvent.AR.value,
+    WyckoffEvent.ST.value,
+    WyckoffEvent.SPRING.value,
+    WyckoffEvent.TEST.value,
+    WyckoffEvent.SOS.value,
+    WyckoffEvent.LPS.value,
+    WyckoffEvent.JUMP.value,
+    WyckoffEvent.BACKUP.value,
+    WyckoffEvent.BC.value,
+    WyckoffEvent.UTAD.value,
+    WyckoffEvent.SOW.value,
+    WyckoffEvent.LPSY.value,
+]
+
+# Dominant event: highest confidence wins; ties broken by this priority
+_DOMINANCE_PRIORITY = [
+    WyckoffEvent.SOS.value,
+    WyckoffEvent.LPS.value,
+    WyckoffEvent.UTAD.value,
+    WyckoffEvent.SPRING.value,
+    WyckoffEvent.JUMP.value,
+    WyckoffEvent.BACKUP.value,
+    WyckoffEvent.TEST.value,
+    WyckoffEvent.SC.value,
+    WyckoffEvent.SOW.value,
+    WyckoffEvent.AR.value,
+    WyckoffEvent.ST.value,
+]
+
+
+class EventEngine:
+    name = "Event"
+    version = "1.0.0"
+
+    def run(
+        self,
+        cycle: EngineResult,
+        phase: EngineResult,
+        feature: EngineResult,
+        timeframe: str,
+    ) -> EngineResult:
+        if feature.payload.get("insufficient"):
+            return EngineResult(
+                name=self.name,
+                version=self.version,
+                confidence=20.0,
+                score=30.0,
+                reasons=["特征不足，跳过事件识别"],
+                warnings=["insufficient_features"],
+                payload={
+                    "current_event": WyckoffEvent.NONE.value,
+                    "active_events": [],
+                    "recent_events": [],  # alias for DB/API compat; same as active_events
+                    "timeframe": timeframe,
+                    "entry_score": 30.0,
+                },
+            )
+
+        context = {
+            "features": feature.payload,
+            "cycle": cycle.payload,
+            "phase": phase.payload,
+            "timeframe": timeframe,
+        }
+        hits = []
+        for rule in rule_registry.by_category("event", timeframe):
+            hit = rule.evaluate(context)
+            if hit and hit.event:
+                hits.append(hit)
+
+        if not hits:
+            return EngineResult(
+                name=self.name,
+                version=self.version,
+                confidence=35.0,
+                score=40.0,
+                reasons=["无显著事件"],
+                payload={
+                    "current_event": WyckoffEvent.NONE.value,
+                    "active_events": [],
+                    "recent_events": [],
+                    "timeframe": timeframe,
+                    "entry_score": 40.0,
+                },
+            )
+
+        by_event: dict[str, float] = {}
+        reasons: list[str] = []
+        metrics: dict = {}
+        for h in hits:
+            prev = by_event.get(h.event, -1.0)
+            if h.confidence >= prev:
+                by_event[h.event] = h.confidence
+            reasons.extend(h.reasons)
+            metrics.update(h.metrics)
+
+        active = [e for e in _DISPLAY_ORDER if e in by_event]
+        for e in by_event:
+            if e not in active:
+                active.append(e)
+
+        # Dominant = max confidence; tie-break by dominance priority index
+        def _dom_key(ev: str) -> tuple:
+            conf = by_event[ev]
+            try:
+                prio = _DOMINANCE_PRIORITY.index(ev)
+            except ValueError:
+                prio = 99
+            return (conf, -prio)
+
+        current = max(by_event.keys(), key=_dom_key)
+        event_conf = by_event[current]
+        co_bonus = min(12.0, max(0, len(active) - 1) * 3)
+        entry_score = min(98.0, event_conf + co_bonus)
+        if current == WyckoffEvent.SPRING.value and WyckoffEvent.TEST.value in by_event:
+            entry_score = min(98.0, entry_score + 5)
+
+        return EngineResult(
+            name=self.name,
+            version=self.version,
+            confidence=event_conf,
+            score=entry_score,
+            reasons=list(dict.fromkeys(reasons))[:8],
+            warnings=["active_events_are_concurrent_not_timeline"],
+            metrics=metrics,
+            payload={
+                "current_event": current,
+                "active_events": active,
+                "recent_events": active,  # persisted column name; semantic = active
+                "event_scores": by_event,
+                "timeframe": timeframe,
+                "entry_score": entry_score,
+            },
+        )

crypto_wyckoff/features.py

@@ -0,0 +1,206 @@
+"""Feature Engine — pure function over OHLCVFrame → EngineResult(FeatureSnapshot)."""
+
+from __future__ import annotations
+
+from typing import Any
+
+import numpy as np
+
+from crypto_wyckoff.domain_models import EngineResult, OHLCVFrame
+
+
+def _sma(arr: np.ndarray, n: int) -> float:
+    if len(arr) < n:
+        return float(arr[-1]) if len(arr) else 0.0
+    return float(np.mean(arr[-n:]))
+
+
+def _atr(high: np.ndarray, low: np.ndarray, close: np.ndarray, n: int = 14) -> float:
+    if len(close) < 2:
+        return 0.0
+    prev_close = close[:-1]
+    tr = np.maximum(high[1:] - low[1:], np.maximum(np.abs(high[1:] - prev_close), np.abs(low[1:] - prev_close)))
+    if len(tr) < n:
+        return float(np.mean(tr)) if len(tr) else 0.0
+    return float(np.mean(tr[-n:]))
+
+
+def _adx(high: np.ndarray, low: np.ndarray, close: np.ndarray, n: int = 14) -> float:
+    """Simplified ADX approximation."""
+    if len(close) < n + 2:
+        return 15.0
+    up = high[1:] - high[:-1]
+    down = low[:-1] - low[1:]
+    plus_dm = np.where((up > down) & (up > 0), up, 0.0)
+    minus_dm = np.where((down > up) & (down > 0), down, 0.0)
+    tr = np.maximum(high[1:] - low[1:], np.maximum(np.abs(high[1:] - close[:-1]), np.abs(low[1:] - close[:-1])))
+    atr = np.mean(tr[-n:]) or 1e-9
+    plus_di = 100 * np.mean(plus_dm[-n:]) / atr
+    minus_di = 100 * np.mean(minus_dm[-n:]) / atr
+    denom = plus_di + minus_di
+    if denom < 1e-9:
+        return 10.0
+    dx = 100 * abs(plus_di - minus_di) / denom
+    return float(min(60.0, dx))
+
+
+def compute_feature_snapshot(frame: OHLCVFrame) -> dict[str, Any]:
+    """Compute technical snapshot dict from OHLCV (no I/O)."""
+    if frame.empty or len(frame) < 5:
+        return {"ts_code": frame.ts_code, "timeframe": frame.timeframe, "bars": len(frame)}
+
+    close = np.asarray(frame.close, dtype=float)
+    high = np.asarray(frame.high, dtype=float)
+    low = np.asarray(frame.low, dtype=float)
+    volume = np.asarray(frame.volume, dtype=float)
+    open_ = np.asarray(frame.open, dtype=float)
+
+    ma20 = _sma(close, 20)
+    ma60 = _sma(close, 60)
+    ma120 = _sma(close, min(120, len(close)))
+    atr = _atr(high, low, close, 14)
+    vol_ma20 = _sma(volume, 20) or 1e-9
+    volume_ratio = float(volume[-1] / vol_ma20)
+
+    look = min(60, len(close))
+    window_h = high[-look:]
+    window_l = low[-look:]
+    range_high = float(np.max(window_h))
+    range_low = float(np.min(window_l))
+    rng = max(range_high - range_low, 1e-9)
+    range_pct_60 = float(rng / close[-1]) if close[-1] else 0.0
+    range_position = float((close[-1] - range_low) / rng)
+
+    # Spring / UTAD hints
+    pierce_below = max(0.0, (range_low - low[-1]) / close[-1]) if close[-1] else 0.0
+    # if previous bars broke below and last close back in range
+    prior_low = float(np.min(low[-6:-1])) if len(low) >= 6 else float(low[-2])
+    pierce_below = max(pierce_below, max(0.0, (range_low - prior_low) / close[-1]))
+    close_back_in_range = 1.0 if close[-1] >= range_low else 0.0
+    reclaim_speed = 0.0
+    if pierce_below > 0 and close[-1] >= range_low:
+        reclaim_speed = min(1.0, (close[-1] - low[-1]) / max(atr, 1e-9) / 2)
+
+    pierce_above = max(0.0, (high[-1] - range_high) / close[-1])
+    fail_back = 1.0 if pierce_above > 0 and close[-1] <= range_high else 0.0
+    breakout_above = 1.0 if close[-1] > range_high and volume_ratio >= 1.0 else -1.0
+
+    # pullback hold: close near ma20 from above after being higher
+    pullback_hold = 0.0
+    if len(close) >= 5 and close[-1] > ma20 and close[-3] > close[-1] and (close[-1] - ma20) / max(atr, 1e-9) < 1.5:
+        pullback_hold = 0.8
+
+    ma60_prev = _sma(close[:-5], 60) if len(close) > 65 else ma60
+    ma60_slope = (ma60 - ma60_prev) / max(abs(ma60_prev), 1e-9)
+
+    # volume trend: recent 10 vs prior 10
+    if len(volume) >= 20:
+        volume_trend = float(np.mean(volume[-10:]) / (np.mean(volume[-20:-10]) + 1e-9) - 1.0)
+    else:
+        volume_trend = 0.0
+
+    bar_range_atr = float((high[-1] - low[-1]) / max(atr, 1e-9))
+    bounce_from_low = float((close[-1] - float(np.min(low[-10:]))) / close[-1]) if close[-1] else 0.0
+    gap_up_pct = float((open_[-1] - close[-2]) / close[-2]) if len(close) >= 2 and close[-2] else 0.0
+    after_strength = 0.0
+    if len(close) >= 4 and close[-3] > close[-4]:
+        after_strength = 0.7
+
+    spring_score_hint = 0.0
+    if pierce_below >= 0.002 and close_back_in_range:
+        spring_score_hint = min(90.0, 50 + pierce_below * 1500 + reclaim_speed * 20)
+    utad_score_hint = min(90.0, 50 + pierce_above * 1500) if pierce_above >= 0.002 and fail_back else 0.0
+
+    # swing
+    swing_high = float(np.max(high[-20:])) if len(high) >= 5 else float(high[-1])
+    swing_low = float(np.min(low[-20:])) if len(low) >= 5 else float(low[-1])
+
+    return {
+        "ts_code": frame.ts_code,
+        "timeframe": frame.timeframe,
+        "bars": len(frame),
+        "close": float(close[-1]),
+        "open": float(open_[-1]),
+        "high": float(high[-1]),
+        "low": float(low[-1]),
+        "volume": float(volume[-1]),
+        "ma20": ma20,
+        "ma60": ma60,
+        "ma120": ma120,
+        "ma60_slope": float(ma60_slope),
+        "atr": atr,
+        "adx": _adx(high, low, close),
+        "volume_ma20": float(vol_ma20),
+        "volume_ratio": volume_ratio,
+        "volume_trend": volume_trend,
+        "range_high": range_high,
+        "range_low": range_low,
+        "range_pct_60": range_pct_60,
+        "range_position": range_position,
+        "pierce_below_range": pierce_below,
+        "pierce_above_range": pierce_above,
+        "close_back_in_range": close_back_in_range,
+        "reclaim_speed": reclaim_speed,
+        "fail_back_into_range": fail_back,
+        "breakout_above_range": breakout_above,
+        "pullback_hold": pullback_hold,
+        "bar_range_atr": bar_range_atr,
+        "bounce_from_low": bounce_from_low,
+        "gap_up_pct": gap_up_pct,
+        "after_strength": after_strength,
+        "spring_score_hint": spring_score_hint,
+        "utad_score_hint": utad_score_hint,
+        "swing_high": swing_high,
+        "swing_low": swing_low,
+        "trade_date": str(frame.trade_dates[-1]) if frame.trade_dates else None,
+    }
+
+
+# Minimum bars before a timeframe is considered usable (no cross-TF borrow)
+_MIN_BARS = {"1d": 40, "1w": 26, "1M": 18}
+
+
+class FeatureEngine:
+    """Pure Feature Engine — no database access."""
+
+    name = "Feature"
+    version = "1.0.0"
+
+    def run(self, frame: OHLCVFrame | None, timeframe: str | None = None) -> EngineResult:
+        tf = timeframe or (frame.timeframe if frame else "1d")
+        min_bars = _MIN_BARS.get(tf, 30)
+
+        if frame is None or frame.empty or len(frame) < min_bars:
+            bars = 0 if frame is None or frame.empty else len(frame)
+            return EngineResult(
+                name=self.name,
+                version=self.version,
+                confidence=10.0,
+                score=10.0,
+                reasons=[f"{tf} bars={bars} < min={min_bars}，标记 insufficient"],
+                warnings=["insufficient_features"],
+                metrics={"bars": bars, "min_bars": min_bars},
+                payload={
+                    "ts_code": getattr(frame, "ts_code", ""),
+                    "timeframe": tf,
+                    "bars": bars,
+                    "insufficient": True,
+                },
+            )
+
+        snap = compute_feature_snapshot(frame)
+        snap["insufficient"] = False
+        conf = 90.0 if snap.get("bars", 0) >= 60 else 50.0 + min(40.0, snap.get("bars", 0) * 0.5)
+        warnings = []
+        if snap.get("bars", 0) < 60:
+            warnings.append("bars偏少，特征可靠性中等")
+        return EngineResult(
+            name=self.name,
+            version=self.version,
+            confidence=conf,
+            score=conf,
+            reasons=[f"computed {snap.get('bars', 0)} bars {tf}"],
+            warnings=warnings,
+            metrics={"bars": snap.get("bars", 0)},
+            payload=snap,
+        )

crypto_wyckoff/io.py

@@ -0,0 +1,301 @@
+"""Paths + OHLCV cache + DATA_SERVICE fetch (crypto continuous calendar)."""
+
+from __future__ import annotations
+
+import json
+import logging
+import os
+import sqlite3
+import time
+from datetime import date, datetime, timezone
+from pathlib import Path
+from typing import Iterable
+
+import requests
+
+from crypto_wyckoff.domain_models import OHLCVFrame
+
+logger = logging.getLogger(__name__)
+
+_REPO_ROOT = Path(__file__).resolve().parents[1]
+DATA_DIR = Path(os.environ.get("CRYPTO_WYCKOFF_DATA", str(_REPO_ROOT / "data" / "crypto_wyckoff")))
+BARS_DB = DATA_DIR / "bars.sqlite"
+SCAN_DB = DATA_DIR / "scan.sqlite"
+
+DATA_SERVICE_URL = os.environ.get(
+    "DATA_SERVICE_URL",
+    os.environ.get("DATASVC_URL", "https://provider.jackyu66.com"),
+).rstrip("/")
+
+# Continuous crypto: bar counts (not A-share weekend-padded calendar multipliers)
+# Provider has 1d/1w but no 1M — monthly is resampled locally from daily UTC months.
+LOOKBACK = {"1d": 250, "1w": 104, "1M": 60}
+TF_PROVIDER = ("1d", "1w")
+TF_LIST = ("1d", "1w", "1M")
+
+
+def ensure_dirs() -> None:
+    DATA_DIR.mkdir(parents=True, exist_ok=True)
+
+
+def _symbol_key(symbol: str) -> str:
+    return symbol.replace("/", "_").replace(":", "_")
+
+
+def _bars_conn() -> sqlite3.Connection:
+    ensure_dirs()
+    conn = sqlite3.connect(str(BARS_DB), timeout=60)
+    conn.execute(
+        """
+        CREATE TABLE IF NOT EXISTS bars (
+            symbol TEXT NOT NULL,
+            tf TEXT NOT NULL,
+            ts INTEGER NOT NULL,
+            open REAL, high REAL, low REAL, close REAL, volume REAL,
+            PRIMARY KEY (symbol, tf, ts)
+        )
+        """
+    )
+    conn.execute("CREATE INDEX IF NOT EXISTS idx_bars_sym_tf ON bars(symbol, tf)")
+    return conn
+
+
+def fetch_candles(
+    symbol: str,
+    tf: str,
+    *,
+    limit: int | None = None,
+    start_ms: int | None = None,
+    end_ms: int | None = None,
+    timeout: float = 15.0,
+) -> list[dict]:
+    params: dict = {"symbol": symbol, "tf": tf}
+    if limit is not None:
+        params["limit"] = int(limit)
+    if start_ms is not None:
+        params["start"] = int(start_ms)
+    if end_ms is not None:
+        params["end"] = int(end_ms)
+    resp = requests.get(f"{DATA_SERVICE_URL}/api/candles", params=params, timeout=timeout)
+    resp.raise_for_status()
+    data = resp.json()
+    if not isinstance(data, list):
+        return []
+    out = []
+    for row in data:
+        try:
+            ts = int(float(row["timestamp"]))
+            out.append(
+                {
+                    "ts": ts,
+                    "open": float(row["open"]),
+                    "high": float(row["high"]),
+                    "low": float(row["low"]),
+                    "close": float(row["close"]),
+                    "volume": float(row.get("volume") or 0),
+                }
+            )
+        except (KeyError, TypeError, ValueError):
+            continue
+    out.sort(key=lambda r: r["ts"])
+    return out
+
+
+def upsert_bars(symbol: str, tf: str, rows: list[dict]) -> int:
+    if not rows:
+        return 0
+    conn = _bars_conn()
+    try:
+        conn.executemany(
+            """
+            INSERT INTO bars(symbol, tf, ts, open, high, low, close, volume)
+            VALUES (?, ?, ?, ?, ?, ?, ?, ?)
+            ON CONFLICT(symbol, tf, ts) DO UPDATE SET
+              open=excluded.open, high=excluded.high, low=excluded.low,
+              close=excluded.close, volume=excluded.volume
+            """,
+            [
+                (symbol, tf, r["ts"], r["open"], r["high"], r["low"], r["close"], r["volume"])
+                for r in rows
+            ],
+        )
+        conn.commit()
+        return len(rows)
+    finally:
+        conn.close()
+
+
+def load_frame(symbol: str, tf: str, lookback: int | None = None) -> OHLCVFrame | None:
+    lookback = lookback or LOOKBACK.get(tf, 100)
+    conn = _bars_conn()
+    try:
+        cur = conn.execute(
+            """
+            SELECT ts, open, high, low, close, volume FROM bars
+            WHERE symbol=? AND tf=?
+            ORDER BY ts DESC LIMIT ?
+            """,
+            (symbol, tf, lookback),
+        )
+        rows = list(reversed(cur.fetchall()))
+    finally:
+        conn.close()
+    if not rows:
+        return None
+    trade_dates: list[date] = []
+    for ts, *_ in rows:
+        trade_dates.append(datetime.fromtimestamp(ts / 1000.0, tz=timezone.utc).date())
+    return OHLCVFrame(
+        ts_code=symbol,
+        timeframe=tf,
+        trade_dates=trade_dates,
+        open=[r[1] for r in rows],
+        high=[r[2] for r in rows],
+        low=[r[3] for r in rows],
+        close=[r[4] for r in rows],
+        volume=[r[5] for r in rows],
+    )
+
+
+def bar_count(symbol: str, tf: str) -> int:
+    conn = _bars_conn()
+    try:
+        cur = conn.execute(
+            "SELECT COUNT(*) FROM bars WHERE symbol=? AND tf=?", (symbol, tf)
+        )
+        return int(cur.fetchone()[0])
+    finally:
+        conn.close()
+
+
+def rebuild_monthly_from_daily(symbol: str) -> int:
+    """Aggregate UTC calendar-month OHLCV from local daily bars (provider has no 1M)."""
+    conn = _bars_conn()
+    try:
+        cur = conn.execute(
+            """
+            SELECT ts, open, high, low, close, volume FROM bars
+            WHERE symbol=? AND tf='1d' ORDER BY ts ASC
+            """,
+            (symbol,),
+        )
+        daily = cur.fetchall()
+    finally:
+        conn.close()
+    if not daily:
+        return 0
+
+    months: dict[tuple[int, int], dict] = {}
+    for ts, o, h, l, c, v in daily:
+        dt = datetime.fromtimestamp(ts / 1000.0, tz=timezone.utc)
+        key = (dt.year, dt.month)
+        # month bar open timestamp = first day 00:00 UTC
+        month_ts = int(datetime(dt.year, dt.month, 1, tzinfo=timezone.utc).timestamp() * 1000)
+        if key not in months:
+            months[key] = {
+                "ts": month_ts,
+                "open": o,
+                "high": h,
+                "low": l,
+                "close": c,
+                "volume": v or 0.0,
+            }
+        else:
+            m = months[key]
+            m["high"] = max(m["high"], h)
+            m["low"] = min(m["low"], l)
+            m["close"] = c
+            m["volume"] = (m["volume"] or 0) + (v or 0)
+
+    rows = sorted(months.values(), key=lambda r: r["ts"])
+    # drop stale months then upsert
+    conn = _bars_conn()
+    try:
+        conn.execute("DELETE FROM bars WHERE symbol=? AND tf='1M'", (symbol,))
+        conn.commit()
+    finally:
+        conn.close()
+    return upsert_bars(symbol, "1M", rows)
+
+
+def backfill_symbol(symbol: str, tfs: Iterable[str] = TF_LIST) -> dict:
+    """Pull history for continuous crypto TFs; monthly derived from daily."""
+    stats = {}
+    for tf in TF_PROVIDER:
+        if tf not in tfs and "1M" not in tfs:
+            continue
+        need = LOOKBACK.get(tf, 100)
+        # need extra daily for monthly history
+        if tf == "1d":
+            need = max(need, LOOKBACK["1M"] * 31)
+        try:
+            rows = fetch_candles(symbol, tf, limit=need)
+            n = upsert_bars(symbol, tf, rows)
+            stats[tf] = n
+        except Exception as e:
+            logger.warning("backfill %s %s failed: %s", symbol, tf, e)
+            stats[tf] = 0
+        time.sleep(0.05)
+    if "1M" in tfs or True:
+        try:
+            stats["1M"] = rebuild_monthly_from_daily(symbol)
+        except Exception as e:
+            logger.warning("monthly rebuild %s failed: %s", symbol, e)
+            stats["1M"] = 0
+    return stats
+
+
+def tip_update_symbol(symbol: str, tfs: Iterable[str] = TF_LIST) -> bool:
+    """Update forming tip bars (limit=3). Returns True if any bar changed."""
+    changed = False
+    for tf in TF_PROVIDER:
+        try:
+            rows = fetch_candles(symbol, tf, limit=3)
+            if not rows:
+                continue
+            before = _tip_fingerprint(symbol, tf)
+            upsert_bars(symbol, tf, rows)
+            after = _tip_fingerprint(symbol, tf)
+            if before != after:
+                changed = True
+        except Exception as e:
+            logger.debug("tip %s %s: %s", symbol, tf, e)
+        time.sleep(0.02)
+    # Always rebuild current month tip from daily
+    before_m = _tip_fingerprint(symbol, "1M")
+    try:
+        rebuild_monthly_from_daily(symbol)
+    except Exception as e:
+        logger.debug("monthly tip %s: %s", symbol, e)
+    after_m = _tip_fingerprint(symbol, "1M")
+    if before_m != after_m:
+        changed = True
+    return changed
+
+
+def _tip_fingerprint(symbol: str, tf: str) -> tuple | None:
+    conn = _bars_conn()
+    try:
+        cur = conn.execute(
+            """
+            SELECT ts, open, high, low, close, volume FROM bars
+            WHERE symbol=? AND tf=? ORDER BY ts DESC LIMIT 1
+            """,
+            (symbol, tf),
+        )
+        row = cur.fetchone()
+        return tuple(row) if row else None
+    finally:
+        conn.close()
+
+
+def fetch_symbols_from_provider() -> list[str]:
+    try:
+        resp = requests.get(f"{DATA_SERVICE_URL}/health", timeout=8)
+        resp.raise_for_status()
+        payload = resp.json()
+        symbols = payload.get("symbols") or payload.get("symbol_list") or []
+        return [s for s in symbols if isinstance(s, str)]
+    except Exception as e:
+        logger.warning("health symbols failed: %s", e)
+        return []

crypto_wyckoff/phase.py

@@ -0,0 +1,78 @@
+"""Phase Engine — Phase A–E via Rule Registry."""
+
+from __future__ import annotations
+
+from crypto_wyckoff.domain_models import EngineResult, WyckoffPhase
+from crypto_wyckoff.rules.registry import rule_registry
+
+
+class PhaseEngine:
+    name = "Phase"
+    version = "1.0.0"
+
+    def run(self, cycle: EngineResult, feature: EngineResult, timeframe: str) -> EngineResult:
+        if feature.payload.get("insufficient") or cycle.payload.get("cycle") == "Unknown":
+            return EngineResult(
+                name=self.name,
+                version=self.version,
+                confidence=20.0,
+                score=30.0,
+                reasons=["数据/周期不足，Phase=None"],
+                warnings=["insufficient_features"],
+                payload={
+                    "phase": WyckoffPhase.NONE.value,
+                    "timeframe": timeframe,
+                    "cycle": cycle.payload.get("cycle"),
+                    "structure_score": 30.0,
+                },
+            )
+
+        context = {
+            "features": feature.payload,
+            "cycle": cycle.payload,
+            "timeframe": timeframe,
+        }
+        hits = []
+        for rule in rule_registry.by_category("phase", timeframe):
+            hit = rule.evaluate(context)
+            if hit and hit.phase:
+                hits.append(hit)
+
+        if not hits:
+            return EngineResult(
+                name=self.name,
+                version=self.version,
+                confidence=40.0,
+                score=cycle.score * 0.5,
+                reasons=["未识别明确 Phase"],
+                payload={
+                    "phase": WyckoffPhase.NONE.value,
+                    "timeframe": timeframe,
+                    "cycle": cycle.payload.get("cycle"),
+                    "structure_score": cycle.score * 0.5,
+                },
+            )
+
+        best = max(hits, key=lambda h: h.confidence)
+        structure_score = best.score
+        # Phase D/E stronger structure
+        if best.phase in (WyckoffPhase.D.value, WyckoffPhase.E.value):
+            structure_score = max(structure_score, 80.0)
+        elif best.phase == WyckoffPhase.C.value:
+            structure_score = max(structure_score, 72.0)
+
+        return EngineResult(
+            name=self.name,
+            version=self.version,
+            confidence=best.confidence,
+            score=structure_score,
+            reasons=best.reasons,
+            metrics=best.metrics,
+            payload={
+                "phase": best.phase,
+                "timeframe": timeframe,
+                "cycle": cycle.payload.get("cycle"),
+                "rule_id": best.rule_id,
+                "structure_score": structure_score,
+            },
+        )

crypto_wyckoff/pipeline.py

@@ -0,0 +1,157 @@
+"""Scan pipeline: load local frames → engines → store."""
+
+from __future__ import annotations
+
+import json
+import logging
+from datetime import date, datetime, timezone
+
+from crypto_wyckoff.cycle import CycleEngine
+from crypto_wyckoff.decision import DecisionEngine
+from crypto_wyckoff.domain_models import WyckoffScanRow
+from crypto_wyckoff.event import EventEngine
+from crypto_wyckoff.features import FeatureEngine
+from crypto_wyckoff.io import LOOKBACK, TF_LIST, load_frame
+from crypto_wyckoff.phase import PhaseEngine
+from crypto_wyckoff.plan import PlanEngine
+from crypto_wyckoff.signal import SignalEngine
+from crypto_wyckoff.store import upsert_row
+from crypto_wyckoff.version import WYCKOFF_ENGINE_VERSION
+
+logger = logging.getLogger(__name__)
+
+
+def analyze_symbol(
+    daily_frame,
+    weekly_frame,
+    monthly_frame,
+    *,
+    feature_eng: FeatureEngine,
+    cycle_eng: CycleEngine,
+    phase_eng: PhaseEngine,
+    event_eng: EventEngine,
+    signal_eng: SignalEngine,
+    decision_eng: DecisionEngine,
+    plan_eng: PlanEngine,
+) -> dict:
+    f_d = feature_eng.run(daily_frame, "1d")
+    f_w = feature_eng.run(weekly_frame, "1w")
+    f_m = feature_eng.run(monthly_frame, "1M")
+
+    c_m = cycle_eng.run(f_m, "1M")
+    c_w = cycle_eng.run(f_w, "1w")
+
+    p_w = phase_eng.run(c_w, f_w, "1w")
+    p_d = phase_eng.run(c_w, f_d, "1d")
+
+    e_w = event_eng.run(c_w, p_w, f_w, "1w")
+    e_d = event_eng.run(c_w, p_d, f_d, "1d")
+
+    s_d = signal_eng.run(e_d, p_d)
+    decision = decision_eng.run(c_m, c_w, p_w, e_w, e_d, s_d)
+    plan = plan_eng.run(f_d, decision)
+
+    return {
+        "f_d": f_d, "f_w": f_w, "f_m": f_m,
+        "c_m": c_m, "c_w": c_w, "p_w": p_w,
+        "e_w": e_w, "e_d": e_d, "s_d": s_d,
+        "decision": decision, "plan": plan,
+    }
+
+
+def _to_row(trade_date: date, symbol: str, result: dict) -> WyckoffScanRow:
+    d = result["decision"]
+    p = result["plan"]
+    c_m, c_w, p_w = result["c_m"], result["c_w"], result["p_w"]
+    e_w, e_d, s_d = result["e_w"], result["e_d"], result["s_d"]
+    f_d, f_w, f_m = result["f_d"], result["f_w"], result["f_m"]
+
+    snapshot = {
+        "daily": {k: f_d.payload.get(k) for k in (
+            "ma20", "ma60", "ma120", "atr", "adx", "volume_ratio",
+            "range_high", "range_low", "swing_high", "swing_low", "close",
+        )},
+        "weekly": {k: f_w.payload.get(k) for k in ("ma20", "ma60", "adx", "close")},
+        "monthly": {k: f_m.payload.get(k) for k in ("ma20", "ma60", "adx", "close")},
+    }
+    markers = []
+    for key, typ in (("entry", "entry"), ("stop", "stop"), ("target1", "target1"), ("target2", "target2")):
+        if p.payload.get(key) is not None:
+            markers.append({"type": typ, "price": p.payload[key]})
+
+    return WyckoffScanRow(
+        trade_date=trade_date,
+        ts_code=symbol,
+        name=symbol,
+        industry="crypto",
+        engine_version=WYCKOFF_ENGINE_VERSION,
+        m_cycle=c_m.payload.get("cycle", "Unknown"),
+        cycle_confidence=c_m.confidence,
+        trend_score=float(d.payload.get("trend_score", c_m.score)),
+        w_cycle=c_w.payload.get("cycle", "Unknown"),
+        w_phase=p_w.payload.get("phase", "None"),
+        w_current_event=e_w.payload.get("current_event", "None"),
+        w_recent_events_json=json.dumps(
+            e_w.payload.get("active_events") or e_w.payload.get("recent_events") or [],
+            ensure_ascii=False,
+        ),
+        phase_confidence=p_w.confidence,
+        structure_score=float(d.payload.get("structure_score", p_w.score)),
+        d_current_event=e_d.payload.get("current_event", "None"),
+        d_recent_events_json=json.dumps(
+            e_d.payload.get("active_events") or e_d.payload.get("recent_events") or [],
+            ensure_ascii=False,
+        ),
+        event_confidence=e_d.confidence,
+        entry_score=float(d.payload.get("entry_score", e_d.score)),
+        entry=p.payload.get("entry"),
+        stop=p.payload.get("stop"),
+        target1=p.payload.get("target1"),
+        target2=p.payload.get("target2"),
+        rr=p.payload.get("rr"),
+        alignment=float(d.payload.get("alignment", 0)),
+        stars=int(d.payload.get("stars", 1)),
+        decision_signal=d.payload.get("decision_signal", "Watch"),
+        signal_confidence=s_d.confidence,
+        overall_confidence=float(d.payload.get("overall_confidence", d.confidence)),
+        overall_score=float(d.payload.get("overall_score", d.score)),
+        risk=d.payload.get("risk", "Medium"),
+        reasons_json=json.dumps(d.reasons + d.warnings, ensure_ascii=False),
+        feature_snapshot_json=json.dumps(snapshot, ensure_ascii=False),
+        markers_json=json.dumps(markers, ensure_ascii=False),
+        scanned_at=datetime.now(timezone.utc),
+    )
+
+
+_ENGINES = None
+
+
+def _engines():
+    global _ENGINES
+    if _ENGINES is None:
+        _ENGINES = {
+            "feature_eng": FeatureEngine(),
+            "cycle_eng": CycleEngine(),
+            "phase_eng": PhaseEngine(),
+            "event_eng": EventEngine(),
+            "signal_eng": SignalEngine(),
+            "decision_eng": DecisionEngine(),
+            "plan_eng": PlanEngine(),
+        }
+    return _ENGINES
+
+
+def analyze_and_store(symbol: str, trade_date: date | None = None) -> WyckoffScanRow | None:
+    eng = _engines()
+    daily = load_frame(symbol, "1d", LOOKBACK["1d"])
+    weekly = load_frame(symbol, "1w", LOOKBACK["1w"])
+    monthly = load_frame(symbol, "1M", LOOKBACK["1M"])
+    if daily is None or len(daily) < 40:
+        return None
+    result = analyze_symbol(daily, weekly, monthly, **eng)
+    td = trade_date or (
+        daily.trade_dates[-1] if daily.trade_dates else datetime.now(timezone.utc).date()
+    )
+    row = _to_row(td, symbol, result)
+    upsert_row(row)
+    return row

crypto_wyckoff/plan.py

@@ -0,0 +1,78 @@
+"""Plan Engine — Entry / Stop / Target / RR only when Decision is tradable."""
+
+from __future__ import annotations
+
+from crypto_wyckoff.domain_models import DecisionSignal, EngineResult
+
+
+_TRADABLE = {
+    DecisionSignal.STRONG_BUY.value,
+    DecisionSignal.BUY.value,
+    DecisionSignal.SELL.value,
+}
+
+
+class PlanEngine:
+    name = "Plan"
+    version = "1.0.0"
+
+    def run(self, daily_feature: EngineResult, decision: EngineResult) -> EngineResult:
+        f = daily_feature.payload
+        close = float(f.get("close") or 0)
+        atr = float(f.get("atr") or 0) or close * 0.02
+        swing_low = float(f.get("swing_low") or close - 2 * atr)
+        swing_high = float(f.get("swing_high") or close + 2 * atr)
+        range_high = float(f.get("range_high") or swing_high)
+        signal = decision.payload.get("decision_signal", DecisionSignal.WATCH.value)
+
+        entry = stop = t1 = t2 = rr = None
+        reasons: list[str] = []
+
+        if signal not in _TRADABLE or close <= 0:
+            reasons.append(f"无交易计划（信号={signal}）")
+            return EngineResult(
+                name=self.name,
+                version=self.version,
+                confidence=decision.confidence,
+                score=decision.score,
+                reasons=reasons,
+                payload={
+                    "entry": None,
+                    "stop": None,
+                    "target1": None,
+                    "target2": None,
+                    "rr": None,
+                },
+            )
+
+        if signal in (DecisionSignal.STRONG_BUY.value, DecisionSignal.BUY.value):
+            entry = round(close, 4)
+            stop = round(min(swing_low, close - 1.5 * atr), 4)
+            risk = max(entry - stop, 1e-6)
+            t1 = round(entry + 2.0 * risk, 4)
+            t2 = round(max(range_high, entry + 3.0 * risk), 4)
+            rr = round((t1 - entry) / risk, 2)
+            reasons.append(f"入场={entry} 止损={stop} 目标一={t1} 盈亏比={rr}")
+        else:  # Sell
+            entry = round(close, 4)
+            stop = round(max(swing_high, close + 1.5 * atr), 4)
+            risk = max(stop - entry, 1e-6)
+            t1 = round(entry - 2.0 * risk, 4)
+            t2 = round(entry - 3.0 * risk, 4)
+            rr = round((entry - t1) / risk, 2)
+            reasons.append(f"做空计划 入场={entry} 止损={stop} 目标一={t1}")
+
+        return EngineResult(
+            name=self.name,
+            version=self.version,
+            confidence=decision.confidence,
+            score=decision.score,
+            reasons=reasons,
+            payload={
+                "entry": entry,
+                "stop": stop,
+                "target1": t1,
+                "target2": t2,
+                "rr": rr,
+            },
+        )

crypto_wyckoff/rules/__init__.py

@@ -0,0 +1,3 @@
+from crypto_wyckoff.rules.registry import rule_registry
+
+__all__ = ["rule_registry"]

crypto_wyckoff/rules/base.py

@@ -0,0 +1,33 @@
+"""Rule protocol for Wyckoff Rule Registry."""
+
+from __future__ import annotations
+
+from abc import ABC, abstractmethod
+from dataclasses import dataclass, field
+from typing import Any
+
+
+@dataclass
+class RuleHit:
+    """A single rule match."""
+
+    rule_id: str
+    event: str | None = None
+    phase: str | None = None
+    cycle: str | None = None
+    confidence: float = 0.0
+    score: float = 0.0
+    reasons: list[str] = field(default_factory=list)
+    metrics: dict[str, Any] = field(default_factory=dict)
+
+
+class WyckoffRule(ABC):
+    """Pluggable rule. Engines iterate registry; never hardcode rule lists."""
+
+    rule_id: str
+    category: str  # cycle | phase | event
+    timeframes: tuple[str, ...] = ("1d", "1w", "1M")
+
+    @abstractmethod
+    def evaluate(self, context: dict[str, Any]) -> RuleHit | None:
+        """Return RuleHit if matched, else None. Pure — no I/O."""

crypto_wyckoff/rules/cycle_rules.py

@@ -0,0 +1,126 @@
+"""Cycle classification rules (monthly / weekly)."""
+
+from __future__ import annotations
+
+from typing import Any
+
+from crypto_wyckoff.domain_models import WyckoffCycle
+from crypto_wyckoff.rules.base import RuleHit, WyckoffRule
+
+
+def _f(ctx: dict[str, Any], key: str, default: float = 0.0) -> float:
+    v = ctx.get("features", {}).get(key, default)
+    try:
+        return float(v) if v is not None else default
+    except (TypeError, ValueError):
+        return default
+
+
+class MarkupCycleRule(WyckoffRule):
+    rule_id = "cycle_markup"
+    category = "cycle"
+    timeframes = ("1M", "1w")
+
+    def evaluate(self, context: dict[str, Any]) -> RuleHit | None:
+        close = _f(context, "close")
+        ma20 = _f(context, "ma20")
+        ma60 = _f(context, "ma60")
+        ma120 = _f(context, "ma120")
+        adx = _f(context, "adx")
+        slope = _f(context, "ma60_slope")
+        if close > ma20 > ma60 and (ma60 >= ma120 or slope > 0) and adx >= 18:
+            conf = min(95.0, 55 + adx + (10 if close > ma120 else 0))
+            return RuleHit(
+                rule_id=self.rule_id,
+                cycle=WyckoffCycle.MARKUP.value,
+                confidence=conf,
+                score=conf,
+                reasons=["价格位于均线多头排列", f"ADX={adx:.1f}"],
+                metrics={"adx": adx, "slope": slope},
+            )
+        return None
+
+
+class MarkdownCycleRule(WyckoffRule):
+    rule_id = "cycle_markdown"
+    category = "cycle"
+    timeframes = ("1M", "1w")
+
+    def evaluate(self, context: dict[str, Any]) -> RuleHit | None:
+        close = _f(context, "close")
+        ma20 = _f(context, "ma20")
+        ma60 = _f(context, "ma60")
+        ma120 = _f(context, "ma120")
+        adx = _f(context, "adx")
+        slope = _f(context, "ma60_slope")
+        if close < ma20 < ma60 and (ma60 <= ma120 or slope < 0) and adx >= 18:
+            conf = min(95.0, 55 + adx + (10 if close < ma120 else 0))
+            return RuleHit(
+                rule_id=self.rule_id,
+                cycle=WyckoffCycle.MARKDOWN.value,
+                confidence=conf,
+                score=conf,
+                reasons=["价格位于均线空头排列", f"ADX={adx:.1f}"],
+                metrics={"adx": adx},
+            )
+        return None
+
+
+class AccumulationCycleRule(WyckoffRule):
+    rule_id = "cycle_accumulation"
+    category = "cycle"
+    timeframes = ("1M", "1w")
+
+    def evaluate(self, context: dict[str, Any]) -> RuleHit | None:
+        adx = _f(context, "adx")
+        range_pct = _f(context, "range_pct_60")
+        close = _f(context, "close")
+        ma120 = _f(context, "ma120")
+        vol_trend = _f(context, "volume_trend")
+        # Range-bound after decline: strictly at/below MA120 (mutually exclusive vs Distribution)
+        if adx < 22 and range_pct < 0.28 and close <= ma120:
+            conf = 60 + (10 if vol_trend > 0 else 0) + (10 if close < ma120 else 0)
+            return RuleHit(
+                rule_id=self.rule_id,
+                cycle=WyckoffCycle.ACCUMULATION.value,
+                confidence=min(90.0, conf),
+                score=min(90.0, conf),
+                reasons=["低趋势强度区间震荡", "疑似吸筹区间"],
+                metrics={"adx": adx, "range_pct_60": range_pct},
+            )
+        return None
+
+
+class DistributionCycleRule(WyckoffRule):
+    rule_id = "cycle_distribution"
+    category = "cycle"
+    timeframes = ("1M", "1w")
+
+    def evaluate(self, context: dict[str, Any]) -> RuleHit | None:
+        adx = _f(context, "adx")
+        range_pct = _f(context, "range_pct_60")
+        close = _f(context, "close")
+        ma120 = _f(context, "ma120")
+        vol_trend = _f(context, "volume_trend")
+        # Range-bound near highs: strictly above MA120 (mutually exclusive vs Accumulation)
+        if adx < 22 and range_pct < 0.28 and close > ma120:
+            conf = 60 + (10 if vol_trend < 0 else 0) + (10 if close > ma120 else 0)
+            return RuleHit(
+                rule_id=self.rule_id,
+                cycle=WyckoffCycle.DISTRIBUTION.value,
+                confidence=min(90.0, conf),
+                score=min(90.0, conf),
+                reasons=["高位低趋势震荡", "疑似派发区间"],
+                metrics={"adx": adx, "range_pct_60": range_pct},
+            )
+        return None
+
+
+def build_rules() -> list[WyckoffRule]:
+    # Order: trend cycles first (more decisive), then range cycles
+    return [
+        MarkupCycleRule(),
+        MarkdownCycleRule(),
+        AccumulationCycleRule(),
+        DistributionCycleRule(),
+    ]

crypto_wyckoff/rules/event_rules.py

@@ -0,0 +1,254 @@
+"""Event rules: Spring/SOS/LPS/UTAD/SC/AR/ST/..."""
+
+from __future__ import annotations
+
+from typing import Any
+
+from crypto_wyckoff.domain_models import WyckoffCycle, WyckoffEvent, WyckoffPhase
+from crypto_wyckoff.rules.base import RuleHit, WyckoffRule
+
+
+def _f(ctx: dict[str, Any], key: str, default: float = 0.0) -> float:
+    v = ctx.get("features", {}).get(key, default)
+    try:
+        return float(v) if v is not None else default
+    except (TypeError, ValueError):
+        return default
+
+
+def _cycle(ctx: dict[str, Any]) -> str:
+    return (ctx.get("cycle") or {}).get("cycle") or ""
+
+
+def _phase(ctx: dict[str, Any]) -> str:
+    return (ctx.get("phase") or {}).get("phase") or ""
+
+
+class SpringRule(WyckoffRule):
+    rule_id = "event_spring"
+    category = "event"
+    timeframes = ("1d",)
+
+    def evaluate(self, context: dict[str, Any]) -> RuleHit | None:
+        cycle = _cycle(context)
+        if cycle not in (WyckoffCycle.ACCUMULATION.value, WyckoffCycle.RE_ACCUMULATION.value,
+                         WyckoffCycle.MARKUP.value):
+            # Allow spring only in accumulative contexts; Decision will filter MTF
+            if cycle == WyckoffCycle.DISTRIBUTION.value:
+                pass  # still detect for facts but lower confidence
+        pierce = _f(context, "pierce_below_range")
+        reclaim = _f(context, "reclaim_speed")
+        vol_ratio = _f(context, "volume_ratio")
+        close_in_range = _f(context, "close_back_in_range")
+        if pierce >= 0.002 and close_in_range >= 0.5 and reclaim >= 0.3:
+            strength = min(98.0, 50 + pierce * 2000 + reclaim * 20 + (15 if vol_ratio < 1.2 else 5))
+            return RuleHit(
+                rule_id=self.rule_id,
+                event=WyckoffEvent.SPRING.value,
+                confidence=strength,
+                score=strength,
+                reasons=[
+                    f"跌破区间后收回 (pierce={pierce:.3%})",
+                    f"回收速度={reclaim:.2f}",
+                    f"量比={vol_ratio:.2f}",
+                ],
+                metrics={"pierce": pierce, "reclaim": reclaim, "volume_ratio": vol_ratio},
+            )
+        return None
+
+
+class TestRule(WyckoffRule):
+    rule_id = "event_test"
+    category = "event"
+    timeframes = ("1d", "1w")
+
+    def evaluate(self, context: dict[str, Any]) -> RuleHit | None:
+        pos = _f(context, "range_position")
+        vol_ratio = _f(context, "volume_ratio")
+        near_low = pos < 0.2
+        if near_low and vol_ratio < 0.85:
+            return RuleHit(
+                rule_id=self.rule_id,
+                event=WyckoffEvent.TEST.value,
+                confidence=68.0,
+                score=65.0,
+                reasons=["低位缩量回测"],
+            )
+        return None
+
+
+class SOSRule(WyckoffRule):
+    rule_id = "event_sos"
+    category = "event"
+    timeframes = ("1d", "1w")
+
+    def evaluate(self, context: dict[str, Any]) -> RuleHit | None:
+        breakout = _f(context, "breakout_above_range")
+        vol_ratio = _f(context, "volume_ratio")
+        close = _f(context, "close")
+        ma20 = _f(context, "ma20")
+        if breakout >= 0.0 and vol_ratio >= 1.2 and close > ma20:
+            conf = min(95.0, 70 + vol_ratio * 8)
+            return RuleHit(
+                rule_id=self.rule_id,
+                event=WyckoffEvent.SOS.value,
+                confidence=conf,
+                score=conf,
+                reasons=["放量突破区间上沿 (SOS)"],
+                metrics={"vol_ratio": vol_ratio},
+            )
+        return None
+
+
+class LPSRule(WyckoffRule):
+    rule_id = "event_lps"
+    category = "event"
+    timeframes = ("1d", "1w")
+
+    def evaluate(self, context: dict[str, Any]) -> RuleHit | None:
+        # Pullback hold above broken range / MA20 after prior strength
+        pullback = _f(context, "pullback_hold")
+        vol_ratio = _f(context, "volume_ratio")
+        above_ma = _f(context, "close") > _f(context, "ma20")
+        if pullback >= 0.5 and above_ma and vol_ratio <= 1.1:
+            return RuleHit(
+                rule_id=self.rule_id,
+                event=WyckoffEvent.LPS.value,
+                confidence=74.0,
+                score=76.0,
+                reasons=["突破后缩量回踩支撑 (LPS)"],
+            )
+        return None
+
+
+class SCRule(WyckoffRule):
+    rule_id = "event_sc"
+    category = "event"
+    timeframes = ("1w", "1d")
+
+    def evaluate(self, context: dict[str, Any]) -> RuleHit | None:
+        vol_ratio = _f(context, "volume_ratio")
+        bar_range = _f(context, "bar_range_atr")
+        pos = _f(context, "range_position")
+        if vol_ratio >= 1.8 and bar_range >= 1.5 and pos < 0.35:
+            return RuleHit(
+                rule_id=self.rule_id,
+                event=WyckoffEvent.SC.value,
+                confidence=72.0,
+                score=70.0,
+                reasons=["低位放量宽幅，疑似 Selling Climax"],
+            )
+        return None
+
+
+class ARRule(WyckoffRule):
+    rule_id = "event_ar"
+    category = "event"
+    timeframes = ("1w", "1d")
+
+    def evaluate(self, context: dict[str, Any]) -> RuleHit | None:
+        # Automatic rally: bounce from lows
+        bounce = _f(context, "bounce_from_low")
+        if bounce >= 0.04:
+            return RuleHit(
+                rule_id=self.rule_id,
+                event=WyckoffEvent.AR.value,
+                confidence=65.0,
+                score=62.0,
+                reasons=["低点后自动反弹 (AR)"],
+            )
+        return None
+
+
+class STRule(WyckoffRule):
+    rule_id = "event_st"
+    category = "event"
+    timeframes = ("1w", "1d")
+
+    def evaluate(self, context: dict[str, Any]) -> RuleHit | None:
+        pos = _f(context, "range_position")
+        vol_ratio = _f(context, "volume_ratio")
+        if 0.15 < pos < 0.45 and vol_ratio < 1.0:
+            return RuleHit(
+                rule_id=self.rule_id,
+                event=WyckoffEvent.ST.value,
+                confidence=60.0,
+                score=58.0,
+                reasons=["次级测试 (ST)"],
+            )
+        return None
+
+
+class UTADRule(WyckoffRule):
+    rule_id = "event_utad"
+    category = "event"
+    timeframes = ("1w", "1d")
+
+    def evaluate(self, context: dict[str, Any]) -> RuleHit | None:
+        cycle = _cycle(context)
+        pierce_up = _f(context, "pierce_above_range")
+        fail = _f(context, "fail_back_into_range")
+        if cycle in (WyckoffCycle.DISTRIBUTION.value, WyckoffCycle.RE_DISTRIBUTION.value,
+                     WyckoffCycle.MARKUP.value):
+            if pierce_up >= 0.002 and fail >= 0.5:
+                return RuleHit(
+                    rule_id=self.rule_id,
+                    event=WyckoffEvent.UTAD.value,
+                    confidence=76.0,
+                    score=74.0,
+                    reasons=["冲高失败回到区间 (UTAD)"],
+                )
+        return None
+
+
+class JumpRule(WyckoffRule):
+    rule_id = "event_jump"
+    category = "event"
+    timeframes = ("1d",)
+
+    def evaluate(self, context: dict[str, Any]) -> RuleHit | None:
+        gap = _f(context, "gap_up_pct")
+        vol_ratio = _f(context, "volume_ratio")
+        if gap >= 0.03 and vol_ratio >= 1.3:
+            return RuleHit(
+                rule_id=self.rule_id,
+                event=WyckoffEvent.JUMP.value,
+                confidence=70.0,
+                score=72.0,
+                reasons=["放量向上跳跃 (Jump)"],
+            )
+        return None
+
+
+class BackupRule(WyckoffRule):
+    rule_id = "event_backup"
+    category = "event"
+    timeframes = ("1d",)
+
+    def evaluate(self, context: dict[str, Any]) -> RuleHit | None:
+        pullback = _f(context, "pullback_hold")
+        after_jump = _f(context, "after_strength")
+        if after_jump >= 0.5 and pullback >= 0.5:
+            return RuleHit(
+                rule_id=self.rule_id,
+                event=WyckoffEvent.BACKUP.value,
+                confidence=68.0,
+                score=70.0,
+                reasons=["跳跃后回踩 (Backup)"],
+            )
+        return None
+
+
+def build_rules() -> list[WyckoffRule]:
+    return [
+        SpringRule(),
+        UTADRule(),
+        SOSRule(),
+        LPSRule(),
+        SCRule(),
+        JumpRule(),
+        BackupRule(),
+        TestRule(),
+        ARRule(),
+        STRule(),
+    ]

crypto_wyckoff/rules/phase_rules.py

@@ -0,0 +1,163 @@
+"""Phase A–E rules (primarily weekly)."""
+
+from __future__ import annotations
+
+from typing import Any
+
+from crypto_wyckoff.domain_models import WyckoffCycle, WyckoffPhase
+from crypto_wyckoff.rules.base import RuleHit, WyckoffRule
+
+
+def _f(ctx: dict[str, Any], key: str, default: float = 0.0) -> float:
+    v = ctx.get("features", {}).get(key, default)
+    try:
+        return float(v) if v is not None else default
+    except (TypeError, ValueError):
+        return default
+
+
+def _cycle(ctx: dict[str, Any]) -> str:
+    return (ctx.get("cycle") or {}).get("cycle") or WyckoffCycle.UNKNOWN.value
+
+
+class PhaseARule(WyckoffRule):
+    rule_id = "phase_a"
+    category = "phase"
+    timeframes = ("1w", "1d")
+
+    def evaluate(self, context: dict[str, Any]) -> RuleHit | None:
+        cycle = _cycle(context)
+        if cycle not in (WyckoffCycle.ACCUMULATION.value, WyckoffCycle.DISTRIBUTION.value,
+                         WyckoffCycle.RE_ACCUMULATION.value, WyckoffCycle.RE_DISTRIBUTION.value):
+            return None
+        # Stopping action: high vol + large range recently, still range-bound
+        vol_ratio = _f(context, "volume_ratio")
+        range_last = _f(context, "bar_range_atr")
+        if vol_ratio >= 1.4 and range_last >= 1.2:
+            return RuleHit(
+                rule_id=self.rule_id,
+                phase=WyckoffPhase.A.value,
+                confidence=70.0,
+                score=65.0,
+                reasons=["放量宽幅波动，疑似 Phase A 停止行为"],
+            )
+        return None
+
+
+class PhaseBRule(WyckoffRule):
+    rule_id = "phase_b"
+    category = "phase"
+    timeframes = ("1w", "1d")
+
+    def evaluate(self, context: dict[str, Any]) -> RuleHit | None:
+        cycle = _cycle(context)
+        if cycle not in (WyckoffCycle.ACCUMULATION.value, WyckoffCycle.DISTRIBUTION.value):
+            return None
+        adx = _f(context, "adx")
+        range_pct = _f(context, "range_pct_60")
+        pos = _f(context, "range_position")  # 0=low 1=high of range
+        if adx < 20 and 0.25 < pos < 0.75 and range_pct < 0.30:
+            return RuleHit(
+                rule_id=self.rule_id,
+                phase=WyckoffPhase.B.value,
+                confidence=72.0,
+                score=68.0,
+                reasons=["区间中部震荡，疑似 Phase B 建仓/派发"],
+            )
+        return None
+
+
+class PhaseCRule(WyckoffRule):
+    rule_id = "phase_c"
+    category = "phase"
+    timeframes = ("1w", "1d")
+
+    def evaluate(self, context: dict[str, Any]) -> RuleHit | None:
+        cycle = _cycle(context)
+        pos = _f(context, "range_position")
+        spring_like = _f(context, "spring_score_hint")
+        utad_like = _f(context, "utad_score_hint")
+        if cycle in (WyckoffCycle.ACCUMULATION.value, WyckoffCycle.RE_ACCUMULATION.value):
+            if pos < 0.25 or spring_like >= 50:
+                return RuleHit(
+                    rule_id=self.rule_id,
+                    phase=WyckoffPhase.C.value,
+                    confidence=75.0 + min(15.0, spring_like * 0.15),
+                    score=78.0,
+                    reasons=["区间低位测试，疑似 Phase C (Spring/Test)"],
+                )
+        if cycle in (WyckoffCycle.DISTRIBUTION.value, WyckoffCycle.RE_DISTRIBUTION.value):
+            if pos > 0.75 or utad_like >= 50:
+                return RuleHit(
+                    rule_id=self.rule_id,
+                    phase=WyckoffPhase.C.value,
+                    confidence=75.0,
+                    score=78.0,
+                    reasons=["区间高位测试，疑似 Phase C (UTAD)"],
+                )
+        return None
+
+
+class PhaseDRule(WyckoffRule):
+    rule_id = "phase_d"
+    category = "phase"
+    timeframes = ("1w", "1d")
+
+    def evaluate(self, context: dict[str, Any]) -> RuleHit | None:
+        cycle = _cycle(context)
+        close = _f(context, "close")
+        ma20 = _f(context, "ma20")
+        range_high = _f(context, "range_high")
+        range_low = _f(context, "range_low")
+        vol_ratio = _f(context, "volume_ratio")
+        if cycle in (WyckoffCycle.ACCUMULATION.value, WyckoffCycle.RE_ACCUMULATION.value):
+            if close > ma20 and range_high > 0 and close >= range_high * 0.98 and vol_ratio >= 1.1:
+                return RuleHit(
+                    rule_id=self.rule_id,
+                    phase=WyckoffPhase.D.value,
+                    confidence=80.0,
+                    score=82.0,
+                    reasons=["突破区间上沿放量，疑似 Phase D SOS"],
+                )
+        if cycle in (WyckoffCycle.DISTRIBUTION.value, WyckoffCycle.RE_DISTRIBUTION.value):
+            if close < ma20 and range_low > 0 and close <= range_low * 1.02:
+                return RuleHit(
+                    rule_id=self.rule_id,
+                    phase=WyckoffPhase.D.value,
+                    confidence=80.0,
+                    score=82.0,
+                    reasons=["跌破区间下沿，疑似 Phase D SOW"],
+                )
+        return None
+
+
+class PhaseERule(WyckoffRule):
+    rule_id = "phase_e"
+    category = "phase"
+    timeframes = ("1w", "1d")
+
+    def evaluate(self, context: dict[str, Any]) -> RuleHit | None:
+        cycle = _cycle(context)
+        # Markup/Markdown already imply trend continuation (Phase E of prior structure)
+        if cycle == WyckoffCycle.MARKUP.value:
+            return RuleHit(
+                rule_id=self.rule_id,
+                phase=WyckoffPhase.E.value,
+                confidence=78.0,
+                score=80.0,
+                reasons=["趋势上行，对应 Phase E Markup"],
+            )
+        if cycle == WyckoffCycle.MARKDOWN.value:
+            return RuleHit(
+                rule_id=self.rule_id,
+                phase=WyckoffPhase.E.value,
+                confidence=78.0,
+                score=80.0,
+                reasons=["趋势下行，对应 Phase E Markdown"],
+            )
+        return None
+
+
+def build_rules() -> list[WyckoffRule]:
+    # More specific phases first
+    return [PhaseDRule(), PhaseCRule(), PhaseARule(), PhaseBRule(), PhaseERule()]

crypto_wyckoff/rules/registry.py

@@ -0,0 +1,39 @@
+"""Rule Registry — register Wyckoff rules without modifying engines."""
+
+from __future__ import annotations
+
+from crypto_wyckoff.rules.base import WyckoffRule
+
+
+class RuleRegistry:
+    def __init__(self) -> None:
+        self._rules: dict[str, WyckoffRule] = {}
+
+    def register(self, rule: WyckoffRule) -> None:
+        self._rules[rule.rule_id] = rule
+
+    def get(self, rule_id: str) -> WyckoffRule | None:
+        return self._rules.get(rule_id)
+
+    def by_category(self, category: str, timeframe: str | None = None) -> list[WyckoffRule]:
+        out = [r for r in self._rules.values() if r.category == category]
+        if timeframe:
+            out = [r for r in out if timeframe in r.timeframes]
+        return out
+
+    def all(self) -> list[WyckoffRule]:
+        return list(self._rules.values())
+
+
+rule_registry = RuleRegistry()
+
+
+def _register_defaults() -> None:
+    from crypto_wyckoff.rules import cycle_rules, event_rules, phase_rules
+
+    for mod in (cycle_rules, phase_rules, event_rules):
+        for rule in mod.build_rules():
+            rule_registry.register(rule)
+
+
+_register_defaults()

crypto_wyckoff/scheduler.py

@@ -0,0 +1,128 @@
+"""Background 60s tip-update + rescan scheduler."""
+
+from __future__ import annotations
+
+import logging
+import threading
+import time
+from datetime import datetime, timezone
+from typing import Any
+
+from crypto_wyckoff.io import (
+    TF_LIST,
+    backfill_symbol,
+    bar_count,
+    fetch_symbols_from_provider,
+    tip_update_symbol,
+)
+from crypto_wyckoff.pipeline import analyze_and_store
+from crypto_wyckoff.version import WYCKOFF_ENGINE_VERSION
+
+logger = logging.getLogger(__name__)
+
+_lock = threading.Lock()
+_status: dict[str, Any] = {
+    "running": False,
+    "last_tick_at": None,
+    "last_error": None,
+    "symbols_total": 0,
+    "symbols_scanned": 0,
+    "backfill_done": False,
+    "engine_version": WYCKOFF_ENGINE_VERSION,
+    "tick_interval_sec": 60,
+}
+_stop = threading.Event()
+_thread: threading.Thread | None = None
+
+
+def get_status() -> dict[str, Any]:
+    with _lock:
+        return dict(_status)
+
+
+def _set(**kwargs):
+    with _lock:
+        _status.update(kwargs)
+
+
+def run_tick(max_symbols: int | None = None, force_rescan: bool = False) -> dict:
+    """One cycle: refresh symbols, tip-update, analyze changed (or all if force)."""
+    symbols = fetch_symbols_from_provider()
+    if max_symbols:
+        symbols = symbols[:max_symbols]
+    _set(symbols_total=len(symbols), running=True, last_error=None)
+    scanned = 0
+    errors = 0
+    changed_n = 0
+
+    # Lazy backfill: ensure min bars
+    for i, sym in enumerate(symbols):
+        try:
+            if bar_count(sym, "1d") < 40:
+                backfill_symbol(sym, TF_LIST)
+            tip_changed = tip_update_symbol(sym, TF_LIST)
+            if tip_changed:
+                changed_n += 1
+            if force_rescan or tip_changed or bar_count(sym, "1d") >= 40:
+                # Always rescan on first pass after backfill; tip change triggers update
+                if force_rescan or tip_changed or True:
+                    # Tip every minute: always re-analyze to refresh forming-bar features
+                    row = analyze_and_store(sym)
+                    if row:
+                        scanned += 1
+        except Exception as e:
+            errors += 1
+            if errors <= 5:
+                logger.warning("tick %s: %s", sym, e)
+            _set(last_error=str(e))
+        if (i + 1) % 25 == 0:
+            _set(symbols_scanned=scanned)
+            logger.info("wyckoff tick progress %s/%s scanned=%s", i + 1, len(symbols), scanned)
+
+    _set(
+        running=False,
+        symbols_scanned=scanned,
+        last_tick_at=datetime.now(timezone.utc).isoformat(),
+        backfill_done=True,
+    )
+    return {
+        "symbols": len(symbols),
+        "scanned": scanned,
+        "changed_tips": changed_n,
+        "errors": errors,
+    }
+
+
+def _loop(interval: int, max_symbols: int | None):
+    # First tick: force full rescan after tip/backfill
+    try:
+        run_tick(max_symbols=max_symbols, force_rescan=True)
+    except Exception as e:
+        logger.exception("initial tick failed: %s", e)
+        _set(last_error=str(e), running=False)
+    while not _stop.wait(interval):
+        try:
+            run_tick(max_symbols=max_symbols, force_rescan=True)
+        except Exception as e:
+            logger.exception("tick failed: %s", e)
+            _set(last_error=str(e), running=False)
+
+
+def start_scheduler(interval_sec: int = 60, max_symbols: int | None = None) -> None:
+    global _thread
+    if _thread and _thread.is_alive():
+        return
+    _stop.clear()
+    _set(tick_interval_sec=interval_sec)
+    _thread = threading.Thread(
+        target=_loop,
+        args=(interval_sec, max_symbols),
+        name="crypto-wyckoff-scheduler",
+        daemon=True,
+    )
+    _thread.start()
+    logger.info("crypto wyckoff scheduler started interval=%ss", interval_sec)
+
+
+def stop_scheduler() -> None:
+    _stop.set()

crypto_wyckoff/signal.py

@@ -0,0 +1,35 @@
+"""Signal Engine — timeframe-local status labels only (not tradability)."""
+
+from __future__ import annotations
+
+from crypto_wyckoff.domain_models import EngineResult, WyckoffEvent
+
+
+class SignalEngine:
+    """Maps local Event/Phase into a status label. Decision decides tradability."""
+
+    name = "Signal"
+    version = "1.0.0"
+
+    def run(self, event: EngineResult, phase: EngineResult | None = None) -> EngineResult:
+        current = event.payload.get("current_event", WyckoffEvent.NONE.value)
+        conf = event.confidence
+        label = current  # status label mirrors event for V1
+        reasons = [f"本地事件标签: {label}"]
+        if phase and phase.payload.get("phase"):
+            reasons.append(f"本地阶段: {phase.payload.get('phase')}")
+
+        return EngineResult(
+            name=self.name,
+            version=self.version,
+            confidence=conf,
+            score=event.score,
+            reasons=reasons,
+            payload={
+                "signal_label": label,
+                "current_event": current,
+                "phase": (phase.payload.get("phase") if phase else None),
+                "active_events": event.payload.get("active_events")
+                or event.payload.get("recent_events", []),
+            },
+        )

crypto_wyckoff/store.py

@@ -0,0 +1,174 @@
+"""SQLite persistence for crypto wyckoff scan rows."""
+
+from __future__ import annotations
+
+import json
+import sqlite3
+from datetime import datetime
+from typing import Any
+
+from crypto_wyckoff.domain_models import WyckoffScanRow
+from crypto_wyckoff.io import SCAN_DB, ensure_dirs
+
+_COLS = [
+    "trade_date", "ts_code", "name", "industry", "engine_version",
+    "m_cycle", "cycle_confidence", "trend_score",
+    "w_cycle", "w_phase", "w_current_event", "w_recent_events_json",
+    "phase_confidence", "structure_score",
+    "d_current_event", "d_recent_events_json", "event_confidence", "entry_score",
+    "entry", "stop", "target1", "target2", "rr",
+    "alignment", "stars", "decision_signal", "signal_confidence",
+    "overall_confidence", "overall_score", "risk", "reasons_json",
+    "feature_snapshot_json", "markers_json", "scanned_at",
+]
+
+
+def _conn() -> sqlite3.Connection:
+    ensure_dirs()
+    c = sqlite3.connect(str(SCAN_DB), timeout=60)
+    c.row_factory = sqlite3.Row
+    c.execute(
+        """
+        CREATE TABLE IF NOT EXISTS wyckoff_scan (
+            trade_date TEXT NOT NULL,
+            ts_code TEXT NOT NULL,
+            name TEXT DEFAULT '',
+            industry TEXT DEFAULT '',
+            engine_version TEXT,
+            m_cycle TEXT, cycle_confidence REAL, trend_score REAL,
+            w_cycle TEXT, w_phase TEXT, w_current_event TEXT, w_recent_events_json TEXT,
+            phase_confidence REAL, structure_score REAL,
+            d_current_event TEXT, d_recent_events_json TEXT, event_confidence REAL, entry_score REAL,
+            entry REAL, stop REAL, target1 REAL, target2 REAL, rr REAL,
+            alignment REAL, stars INTEGER, decision_signal TEXT, signal_confidence REAL,
+            overall_confidence REAL, overall_score REAL, risk TEXT, reasons_json TEXT,
+            feature_snapshot_json TEXT, markers_json TEXT, scanned_at TEXT,
+            PRIMARY KEY (trade_date, ts_code)
+        )
+        """
+    )
+    c.execute(
+        "CREATE INDEX IF NOT EXISTS idx_cw_score ON wyckoff_scan(trade_date, overall_score DESC)"
+    )
+    return c
+
+
+def upsert_row(row: WyckoffScanRow) -> None:
+    vals = (
+        row.trade_date.isoformat() if hasattr(row.trade_date, "isoformat") else str(row.trade_date),
+        row.ts_code, row.name, row.industry, row.engine_version,
+        row.m_cycle, row.cycle_confidence, row.trend_score,
+        row.w_cycle, row.w_phase, row.w_current_event, row.w_recent_events_json,
+        row.phase_confidence, row.structure_score,
+        row.d_current_event, row.d_recent_events_json, row.event_confidence, row.entry_score,
+        row.entry, row.stop, row.target1, row.target2, row.rr,
+        row.alignment, row.stars, row.decision_signal, row.signal_confidence,
+        row.overall_confidence, row.overall_score, row.risk, row.reasons_json,
+        row.feature_snapshot_json, row.markers_json,
+        row.scanned_at.isoformat() if isinstance(row.scanned_at, datetime) else str(row.scanned_at),
+    )
+    c = _conn()
+    try:
+        placeholders = ",".join("?" * len(_COLS))
+        col_sql = ",".join(_COLS)
+        updates = ",".join(f"{c}=excluded.{c}" for c in _COLS if c not in ("trade_date", "ts_code"))
+        c.execute(
+            f"""
+            INSERT INTO wyckoff_scan ({col_sql}) VALUES ({placeholders})
+            ON CONFLICT(trade_date, ts_code) DO UPDATE SET {updates}
+            """,
+            vals,
+        )
+        c.commit()
+    finally:
+        c.close()
+
+
+def latest_trade_date() -> str | None:
+    c = _conn()
+    try:
+        cur = c.execute("SELECT MAX(trade_date) FROM wyckoff_scan")
+        row = cur.fetchone()
+        return row[0] if row and row[0] else None
+    finally:
+        c.close()
+
+
+def count_for_date(trade_date: str | None = None) -> int:
+    td = trade_date or latest_trade_date()
+    if not td:
+        return 0
+    c = _conn()
+    try:
+        cur = c.execute("SELECT COUNT(*) FROM wyckoff_scan WHERE trade_date=?", (td,))
+        return int(cur.fetchone()[0])
+    finally:
+        c.close()
+
+
+def query_scan(
+    *,
+    trade_date: str | None = None,
+    m_cycle: str | None = None,
+    w_phase: str | None = None,
+    d_event: str | None = None,
+    decision_signal: str | None = None,
+    min_overall_score: float | None = None,
+    min_alignment: float | None = None,
+    sort: str = "overall_score",
+    limit: int = 100,
+    offset: int = 0,
+) -> list[dict[str, Any]]:
+    td = trade_date or latest_trade_date()
+    if not td:
+        return []
+    sort_col = sort if sort in {
+        "overall_score", "alignment", "entry_score", "trend_score", "structure_score", "stars"
+    } else "overall_score"
+    clauses = ["trade_date=?"]
+    args: list[Any] = [td]
+    if m_cycle:
+        clauses.append("m_cycle=?")
+        args.append(m_cycle)
+    if w_phase:
+        clauses.append("w_phase=?")
+        args.append(w_phase)
+    if d_event:
+        clauses.append("d_current_event=?")
+        args.append(d_event)
+    if decision_signal:
+        clauses.append("decision_signal=?")
+        args.append(decision_signal)
+    if min_overall_score is not None:
+        clauses.append("overall_score>=?")
+        args.append(min_overall_score)
+    if min_alignment is not None:
+        clauses.append("alignment>=?")
+        args.append(min_alignment)
+    where = " AND ".join(clauses)
+    args.extend([limit, offset])
+    c = _conn()
+    try:
+        cur = c.execute(
+            f"SELECT * FROM wyckoff_scan WHERE {where} ORDER BY {sort_col} DESC LIMIT ? OFFSET ?",
+            args,
+        )
+        return [dict(r) for r in cur.fetchall()]
+    finally:
+        c.close()
+
+
+def get_symbol(ts_code: str, trade_date: str | None = None) -> dict[str, Any] | None:
+    td = trade_date or latest_trade_date()
+    if not td:
+        return None
+    c = _conn()
+    try:
+        cur = c.execute(
+            "SELECT * FROM wyckoff_scan WHERE trade_date=? AND ts_code=?",
+            (td, ts_code),
+        )
+        row = cur.fetchone()
+        return dict(row) if row else None
+    finally:
+        c.close()

crypto_wyckoff/version.py

@@ -0,0 +1,4 @@
+"""Wyckoff Screener engine version — bump when rules change."""
+
+WYCKOFF_ENGINE_VERSION = "v1.0.0"
+ARCHITECTURE_VERSION = "1.0"

docs/AGENT_MEMORY.md

@@ -19,18 +19,28 @@
 ## 近期变更
 
 - IDEA-002 / `9f1e736`：主站内存泄漏 dispose、首屏单次 analyze、ChanMACD 复用、chan_tv 体验
-- ECR-002 Draft：拆 `web/services/runtime.py`、加深 analyze 契约
+- ECR-002 Reviewed：拆 `web/services/runtime/`、加深 analyze 契约
+- ECR-003 Reviewed：主站威科夫叠层（`chanlun/analysis/wyckoff/` + `include_wyckoff`）→ `081a57a`
+- ECR-004 Reviewed：TR 评分硬化 + VP 少系列 + 阶段/门闩/单测（无币种参数）
+- ECR-007 Final Approval / `276481e`：Wyckoff Live Structure（`live.py`）；Confirmed ≠ Live；execution 仅 confirmed
+- ECR-008 Reviewed：主站 `chart_tv.js` → `chart_tv_{lifecycle,shell,indicators,chan,overlays,finalize}.js` + 薄门面
+- ECR-009 Implementing：`/wyckoff_crypto` 独立选股页（`crypto_wyckoff/`）；D/W + 本地月线；60s tip
+- 威科夫数据随主 analyze 默认返回；UI 开关仅显隐叠层
+- Live 观察：主图左下角 Cycle Summary（「形成中」= FORMING）；无单独 Live 图层
 
 ## 硬约束提醒
 
 - `/api/analyze` 字段可增不可删
 - 无 ADR 不改笔/段/中枢/买卖点语义
-- 交易 L2+ → RISK_REVIEW + EXP；Live 须 Human
+- 威科夫为独立叠层（ECR-003/007）；Crypto Screener 为独立页（ECR-009），勿混进缠论引擎
+- Live candidate **不得**进入 execution；交易 L2+ → RISK_REVIEW + EXP；Live 须 Human
 
 ## 已知债务
 
-- ~~`runtime.py` 仍过大 → ECR-002~~ **已拆包**（待 CODE_REVIEW）
-- `chart_tv.js` 单体巨大 → 后续可选 ECR
-- analyze 契约已加深（mock HTTP）；可再加固定 JSON 快照文件
+- analyze 契约已加深（mock HTTP + wyckoff opt-in）；可再加固定 JSON 快照文件
 - 内存泄漏尚无自动化 heap/监听断言
 - `macd_config` POST 写本地 global 的历史 quirks（未改）
+- 威科夫启发式参数未做 UI 调参
+- ECR-007 待 Human 在 Gitea 开 PR 合入 `dev`
+- `chart_tv_overlays.js` 仍偏大，可后续再拆
+- ECR-009：月线历史受日线深度限制；Cycle 规则在 crypto 上可能偏 Unknown，看效果再调参

docs/BACKEND_DESIGN/BD-2026-007-wyckoff-live-structure.md

@@ -0,0 +1,70 @@
+# Backend Design: ECR-007 Wyckoff Live Structure
+
+| Field | Value |
+|-------|-------|
+| ID | BD-2026-007 |
+| ECR | ECR-007 |
+| Change Level | L2 |
+| Status | Approved |
+| Author | Architect (LOOP-RUN-005 Planner) |
+| Date | 2026-08-07 |
+| Risk | High (domain / execution boundary) |
+
+---
+
+## Context
+
+- 问题：Confirmed 引擎已存在；需要独立 Live 推演层供观察，且不得成为交易执行输入。
+- 非目标：改 Confirmed 门槛；自动交易；策略。
+- 依赖：ECR-003/004 威科夫；WYCKOFF-LIVE-STRUCTURE-001（FROZEN）。
+
+## Architecture Change / Change Boundary
+
+```text
+OHLCV
+  → detect_trading_ranges (Confirmed path)
+  → detect_bias_and_events / build_phases   ← Confirmed（阈值不降）
+  → analyze_live_structure                   ← Live（只读 confirmed）
+  → cycles[i] = { lifecycle, confirmed, live }
+  → API analyze + Summary UI
+  → execution_signal_from_wyckoff(confirmed only)
+```
+
+| Layer | May change | Must not |
+|-------|------------|----------|
+| Confirmed | assemble into `confirmed{}` | relax Spring/SOS rules |
+| Live | `live.py` heuristics | write into confirmed.events |
+| Execution helper | source=confirmed gate | consume candidates |
+| UI | Summary partition | treat Live as order |
+
+## Backend Change Boundary
+
+Live outputs are **observation**. Execution boundary:
+
+```python
+assert execution_signal.source == "confirmed"
+# live-only payload → None
+```
+
+## Data contract
+
+See WYCKOFF-LIVE-STRUCTURE-001. Top-level `phases`/`events` mirror **Confirmed** only.
+
+## delivery_constraints
+
+- BD Status Approved
+- TEST_REPORT commands/result/date
+- CODE_REVIEW handoff
+- TRACEABILITY commit
+- out_of_scope + execution_source_confirmed_only
+
+## Test Plan
+
+1. Live candidates not in confirmed.events  
+2. CONFIRMED lifecycle when Spring+SOS confirmed  
+3. execution_signal source=confirmed; live-only → None  
+4. analyze contract keys include live/lifecycle  
+
+## Rollback
+
+Remove live assembly path; Summary falls back to confirmed-only.

docs/CHANGELOG/CHANGELOG.md

@@ -1,8 +1,42 @@
 # CHANGELOG
 
+## Unreleased — 2026-08-07
+
+### ECR-009（L2，进行中）
+
+- 独立页 `/wyckoff_crypto`：移植 A_Share_DP D/W/M 威科夫选股引擎至数字货币
+- 本地 `data/crypto_wyckoff/`；60s tip；月线由日线 UTC 自然月聚合（provider 无 1M）
+- API：`/api/wyckoff_crypto/*`；不碰主站 analyze / 缠论叠层
+
+### ECR-008（L3，Reviewed）
+
+- 主站 `chart_tv.js` 拆为 lifecycle / shell / indicators / chan / overlays / finalize + 薄门面
+- 行为冻结；`initTradingView` / `disposeTradingViewCharts` 对外不变；无 Vite/TS
+
+### ECR-007（L2，LOOP-RUN-005）
+
+- Wyckoff **Live Structure**：`live.py` + engine 组装 `lifecycle` / `confirmed` / `live`
+- Event candidates（Spring/SOS/LPS/UTAD）+ 可解释 confidence；Summary Confirmed/Live 分区
+- `execution_signal_from_wyckoff` **仅** `source=confirmed`；Live-only → None
+- **No** Confirmed 门槛降低；**No** strategies / 自动交易
+
 ## Unreleased — 2026-08-06
 
-### ECR-002（L3，待 Review）
+### ECR-004（L2，Reviewed）
+
+- 威科夫 TR 评分选段（防吞前置趋势）；阶段非重叠最小跨度
+- 主站 VP Top-8 + bins≤24；填充线减负
+- `elements_only` 时不跑威科夫；收紧单测（无币种独立参数）
+- **后续**：威科夫随主 `/api/analyze` 默认一并返回；前端开关只控制绘制（不再勾选才加载）
+
+### ECR-003（L2，Reviewed）
+
+- 新增 `chanlun/analysis/wyckoff/`：交易区间、阶段 A–E、Spring/SOS/LPS/UTAD 等事件、区间 VP（POC/VAH/VAL）、量能确认
+- `/api/analyze` 按需 `include_wyckoff=1` 返回顶层 `wyckoff`
+- 主站「威科夫」开关与 Lightweight 叠层（区间/阶段/事件/VP）
+- 单测与 analyze 契约 opt-in 断言
+
+### ECR-002（L3，Reviewed）
 
 - 拆分 `web/services/runtime.py` 为包 `web/services/runtime/`（state / timeframes / market_data / indicators / analyze / serialize）
 - 加深 analyze 契约测试（mock HTTP + analyze_chan 键集 + serialize JSON）

docs/CODE_REVIEW/ECR-003.md

@@ -0,0 +1,77 @@
+# CODE_REVIEW — ECR-003
+
+**Role:** REVIEWER  
+**Date:** 2026-08-06  
+**Scope:** 工作区未提交 ECR-003（相对 `origin/dev` @ `df27b4d`）  
+**Decision:** Approve（带非阻断 Findings；建议合并前勿提交 `.DS_Store`）
+
+## Evidence loaded
+
+- `chanlun/analysis/wyckoff/{engine,range,events,volume_profile}.py`
+- `web/api/analyze.py`（`include_wyckoff`）
+- `web/templates/index.html`、`chart_view.js`、`macd_ui.js`、`chart_tv.js` 威科夫块
+- `tests/test_wyckoff.py`、`web/tests/test_analyze_contract.py`
+- ESS：ECR/PRODUCT/ENG/IMPL/TEST/HANDOFF
+
+## Acceptance ↔ Evidence
+
+| Acceptance | Verdict | Evidence |
+|------------|---------|----------|
+| `include_wyckoff=1` 返回约定键；默认不强制 | PASS | 契约测试；默认无 `wyckoff` 键 |
+| 合成 TR + 事件；VP POC | PASS | `test_wyckoff.py`（12 相关套件全绿） |
+| 主站可开关绘制 | PASS | 主开关按需拉取；子项本地重绘 |
+| golden 不变 | PASS | `test_golden_pipeline` |
+| 未改缠论算法 / strategies / chan_tv | PASS | diff 范围核对 |
+| ESS 闭环 | PASS | IMPL/TEST/TRACE/CHANGELOG/本文件 |
+
+## 复跑
+
+```text
+PYTHONPATH=.:web python -m pytest \
+  tests/test_wyckoff.py tests/test_golden_pipeline.py \
+  web/tests/test_analyze_contract.py -q
+→ 12 passed
+```
+
+## Findings
+
+### Important（不挡 Approve，建议跟进）
+
+1. **交易区间易吞并前置趋势**  
+   `detect_trading_range` 从最长窗口向下搜，合成夹具下 `abs_start_idx=0`，箱体前下跌段被算进 TR。单测只断言「有区间 + 有事件」，未锁定高低/起点。  
+   *建议：* 用「宽度/触边密度」评分取最优段，或要求近端触边；测试断言 `high≈60/low≈40` 与起点靠近箱体。
+
+2. **VP 叠层系列数偏多，可能加压自动刷新内存**  
+   开启 VP 时约每个 bin 一条 `addLineSeries`（默认 ~50），再加区间填充/阶段。与 IDEA-002 内存修复同路径全量重建时放大。  
+   *建议：* 只画非零 bin 或合并为少量 series / histogram；或限制 `vp_bins` 上限到 24。
+
+### Medium
+
+3. **阶段 C–E 在事件扎堆时常退化重叠**  
+   夹具输出中 D/E 起止几乎相同；状态机按事件锚点硬切，缺少最小阶段长度。展示可用，语义偏弱。
+
+4. **`elements_only=true` 仍可能跑威科夫**  
+   威科夫挂在路由末尾，不依赖 `not elements_only`。主站当前不这么发，但契约上奇怪；建议与主周期分析同门闩。
+
+5. **单测断言偏松**  
+   `Spring in types or SOS`、`abs(poc-50)<2` 对回归保护不足。
+
+### Low
+
+6. 失败时 `wyckoff.error` 回传异常字符串（与结构区 print 风格一致，信息暴露轻微）。
+7. 事件 marker 一律 `arrowUp`（跌破类也可 `arrowDown`）。
+8. 工作区 `.DS_Store` 脏文件——**勿纳入 commit**。
+
+### No blockers
+
+未发现：契约删键、缠论语义改动、策略/config 改动、未鉴权危险写操作、主站误引 WS。
+
+## Decision
+
+**Approve**
+
+可合并提交（排除 `.DS_Store`）。Important #1/#2 可开后续 L1/L2，不阻塞本 ECR 着陆。
+
+## Next owner
+
+`engineer` / Human — commit（勿含 `.DS_Store`）；可选跟进 TR 评分与 VP 绘图优化。

docs/CODE_REVIEW/ECR-004.md

@@ -0,0 +1,53 @@
+# CODE_REVIEW — ECR-004
+
+**Role:** REVIEWER  
+**Date:** 2026-08-06  
+**Scope:** `d3188ca`（相对 ECR-003）威科夫硬化  
+**Decision:** Approve  
+
+## Evidence loaded
+
+- Diff `d3188ca`：`range.py` / `events.py` / `analyze.py` / `chart_tv.js` / tests / ESS
+- 复跑：`tests/test_wyckoff.py` + golden + analyze contract → **14 passed**
+- 合成夹具抽查：`abs_start_idx=20`，low/high≈40.1/59.9（相对 003 的 bar0 已修好）
+
+## Acceptance ↔ Evidence
+
+| Acceptance | Verdict | Evidence |
+|------------|---------|----------|
+| TR 不吞明显前置趋势；边界近箱体 | PASS | 评分选段；单测 low/high 带 + `abs_start≥12` + start 时间容差 |
+| VP series 减负 | PASS | Top-8 + 填充 3 + POC/VAH/VAL；API bins≤24 |
+| 阶段最小跨度 / 不重合 | PASS | 链式 cursor；unique (start,end) 断言 |
+| elements_only 门闩 | PASS | `include_wyckoff and not elements_only` + 契约测试 |
+| golden 不变 / 无策略改动 / 无币种表 | PASS | golden 绿；diff 无 config/strategies |
+
+## Findings
+
+### Medium（不挡 Approve）
+
+1. **同分 tie-break 偏向更长窗口**  
+   循环从长到短，`score <= best_score` 时保留已有（更长）。多数情况分数拉开；若实盘出现「长窗与短窗同分」，仍可能略偏长。可选：同分取更短，或加 `1/length` 微项。
+
+2. **阶段常截断为 A–C**  
+   Spring/SOS 落在尾部时 D/E 因 `min_span` 被吃掉——与 ENG「空间不足截断」一致，但 UI 勾选「阶段」时用户可能期望总见 D/E。属产品预期，非缺陷；可在 UI/文档标明「尾部不足则省略」。
+
+### Low
+
+3. **`abs_start_idx >= 12` 弱于「箱体起点」** —— 主测已用时间容差；该断言可再收紧到 `>= 16` 一类。  
+4. **VP Top-N 无自动化 series 计数** —— 靠代码审查 + ENG 约定。  
+5. 事件 marker 仍一律 `arrowUp`（003 遗留）。  
+6. 失败路径仍回传 `wyckoff.error` 字符串。
+
+### No blockers
+
+未发现契约删键、缠论语义改动、策略改动、或回归红灯。
+
+## Decision
+
+**Approve**
+
+ECR-004 可维持 Done (Reviewed)。Medium 项进 backlog，不必立刻新 ECR，除非实盘 TR 仍偏长。
+
+## Next owner
+
+Human — 主站 BTC 勾选威科夫目测；无发版要求则保持 `v1.0.0` Unreleased 累计。

docs/CODE_REVIEW/ECR-008.md

@@ -0,0 +1,25 @@
+# CODE_REVIEW — ECR-008
+
+**Role:** REVIEWER  
+**Date:** 2026-08-07  
+**Scope:** chart_tv 物理拆分  
+**Decision:** Approve  
+
+## Checklist
+
+| Item | Result | Notes |
+|------|--------|-------|
+| 行为冻结（仅搬移） | PASS | ctx 编排；无绘制算法改写意图 |
+| 对外 API | PASS | `initTradingView` / `disposeTradingViewCharts` 保留 |
+| Forbidden | PASS | 无 Vite/TS；无 strategies/config；无 analyze 契约改动 |
+| script 顺序 | PASS | lifecycle→shell→indicators→chan→overlays→finalize→门面→sync |
+| 测试证据 | PASS | `node --check` ALL_CHECK_OK |
+
+## Findings
+
+1. **Low：** 浏览器硬刷新冒烟仍建议 Human 点一次（自动刷新 + Cycle Summary）。不挡 Approve。  
+2. **Low：** `chart_tv_overlays.js` 仍偏大（~2.3k 行）；可后续再拆，非本 ECR 范围。
+
+## Decision
+
+**Approve**

docs/ECR/ECR-003-wyckoff-main.md

@@ -0,0 +1,62 @@
+# ECR-003
+
+**Title:** 主站威科夫分析与图表展示  
+**Status:** Done (Reviewed)  
+**Date:** 2026-08-06  
+**Change Level:** L2  
+
+## Change
+
+在主站 `/` 增加威科夫交易区间、阶段（A–E）、关键事件（Spring/SOS/LPS/UTAD 等）、区间内简易 VP（POC/VAH/VAL）与量能确认；按需接入 `/api/analyze`。
+
+## Motivation
+
+用户需要在缠论图上叠加威科夫结构解读；与现有结构区语义分离。
+
+## Scope
+
+### Allowed
+
+- 新建 `chanlun/analysis/wyckoff/`
+- `/api/analyze` 增加可选 `include_wyckoff` 与响应字段 `wyckoff`（可增不可删既有字段）
+- 主站 UI 开关与 Lightweight 绘图
+- 单测 + ESS 文档
+
+### Forbidden
+
+- 修改笔/段/中枢/买卖点算法语义
+- 改 `config/` / `strategies/`
+- `/chan_tv` Study
+- Vite/React、主站 WebSocket 实时（另 ECR）
+
+## Risk
+
+| Risk | Mitigation |
+|------|------------|
+| 启发式误标 | 规格写明启发式；UI 可关；单测合成形态 |
+| 负载 | 默认关闭，勾选才计算 |
+| 与结构区混淆 | 独立开关与字段名 |
+
+## Acceptance Criteria
+
+- [x] `include_wyckoff=1` 返回约定 `wyckoff` 键；默认不强制计算
+- [x] 合成 fixture：能检出 TR + 至少一类事件；VP POC 可测
+- [x] 主站可开关绘制区间/阶段/事件/VP
+- [x] golden 缠论基线不变
+- [x] TEST/IMPL/CHANGELOG/TRACEABILITY + CODE_REVIEW
+
+## Rollback
+
+`git revert`；关闭 UI 开关即可无图面影响。
+
+## Risk Review
+
+- `docs/RISK_REVIEW/ECR-003.md` — N/A（展示分析，非 Live 策略）
+
+## Linked
+
+- IDEA: `docs/IDEA/IDEA-004-wyckoff-main.md`
+- PRODUCT_SPEC / ENGINEERING_SPEC: 同目录 ECR-003-*
+- EXPERIMENT: N/A
+- TRACEABILITY: Yes
+- CODE_REVIEW: `docs/CODE_REVIEW/ECR-003.md` — Approve

docs/ECR/ECR-004-wyckoff-harden.md

@@ -0,0 +1,69 @@
+# ECR-004
+
+**Title:** 威科夫区间评分硬化与主站 VP 绘图减负  
+**Status:** Done (Reviewed)  
+**Date:** 2026-08-06  
+**Change Level:** L2  
+
+## Change
+
+跟进 ECR-003 CODE_REVIEW Findings：改进交易区间选取启发式、阶段最小长度、收紧单测；主站 VP/叠层降低 Lightweight series 数量；`include_wyckoff` 与主周期分析同门闩。
+
+## Motivation
+
+003 已 Approve 合入；质量与内存项不得回塞已审变更，须独立可审闭环。
+
+## Scope
+
+### Allowed
+
+- `chanlun/analysis/wyckoff/range.py` / `events.py`（阶段）启发式与单测  
+- `web/static/js/app/chart_tv.js` 威科夫 VP/填充绘制路径  
+- `web/api/analyze.py`：`elements_only` 时不跑威科夫；默认 `vp_bins` 上限 24  
+- ESS 文档与契约测试补充断言（不删既有 `wyckoff` 键）
+
+### Forbidden
+
+- 改笔/段/中枢/买卖点语义  
+- `config/` / `strategies/`  
+- `/chan_tv`  
+- 新数据源 / 订单流  
+- **按币种独立参数表**（全局 ATR 相对即可；当前以 BTC 场景验证）
+
+## Decisions（Approve 时锁定）
+
+- VP：**A+C**（前端 Top-N 有量 bin + 服务端 bins 上限 24）  
+- 不做 per-symbol 参数  
+
+## Risk
+
+| Risk | Mitigation |
+|------|------------|
+| TR 结果相对 003 漂移 | 合成夹具锁定高低与起点；文档标明启发式迭代 |
+| 前端 VP 观感变化 | 保留 POC/VAH/VAL；密度用 Top-N |
+| 回归 | 扩展 `tests/test_wyckoff.py` + 既有契约套件 |
+
+## Acceptance Criteria
+
+- [x] 合成箱体夹具：`trading_range` 高低接近箱体边界，起点不落入明显前置趋势段  
+- [x] 开启 VP 时主图新增 series 数显著低于「每 bin 一条」（目标：填充+VP ≤ ~15 或等价合并策略）  
+- [x] 阶段输出满足最小跨度或合并退化段；文档说明规则  
+- [x] `elements_only=true` 即使 `include_wyckoff=1` 也不返回 `wyckoff`  
+- [x] golden 缠论基线不变；相关 pytest 绿  
+- [x] TEST/IMPL/CHANGELOG/TRACEABILITY + CODE_REVIEW  
+
+## Rollback
+
+`git revert`；UI 关威科夫即可无图面影响。
+
+## Risk Review
+
+- `docs/RISK_REVIEW/ECR-004.md` — N/A（展示/启发式，非 Live 策略）
+
+## Linked
+
+- IDEA: `docs/IDEA/IDEA-005-wyckoff-harden.md`  
+- 上游: `docs/CODE_REVIEW/ECR-003.md` Findings 1–5  
+- PRODUCT_SPEC / ENGINEERING_SPEC: 同目录 ECR-004-*  
+- TRACEABILITY: Yes  
+- CODE_REVIEW: `docs/CODE_REVIEW/ECR-004.md` — Approve  

docs/ECR/ECR-007-wyckoff-live-structure.md

@@ -0,0 +1,60 @@
+# ECR-007
+
+**Title:** Wyckoff Live Structure  
+**Status:** Approved  
+**Date:** 2026-08-07  
+**Change Level:** L2  
+**Human:** Approved (LOOP-RUN-005 Start Authorization)
+
+## Change
+
+Add **Live / Developing** structure layer beside **Confirmed** Wyckoff engine: lifecycle, FORMING candidates (Spring/SOS/LPS/UTAD), explainable confidence, Summary partition. Keep Confirmed thresholds unchanged; execution may only consume Confirmed.
+
+## Motivation
+
+LOOP-RUN-005 — domain-state complexity under Adapter v0.1 STABLE (Confirmed ≠ Live ≠ execution).
+
+## Scope
+
+### Allowed (IN)
+
+- `chanlun/analysis/wyckoff/live.py` + engine assembly
+- lifecycle / confirmed / live payload
+- Event candidates + confidence
+- API contract + Summary UI
+- tests + docs notes (WYCKOFF-LIVE-STRUCTURE-001)
+
+### Forbidden (OUT)
+
+- execution signal automation / auto trading
+- strategy / maker / decide_quotes / `strategies/**`
+- lowering Confirmed thresholds
+- Live candidate replacing Confirmed
+- ESS / Loop / Adapter changes
+
+## Risk
+
+| Risk | Mitigation |
+|------|------------|
+| Live → execution | `execution_signal_from_wyckoff` source=confirmed only; live-only → None |
+| Confirmed pollution | candidates never written to confirmed.events |
+| Domain confusion in UI | Summary Confirmed vs Live partitions |
+
+## Acceptance Criteria
+
+- [ ] Approved BD-2026-007
+- [ ] Confirmed logic not relaxed
+- [ ] Live ≠ execution signal (tests)
+- [ ] Lifecycle verifiable
+- [ ] Artifact chain + Gate PASS
+
+## Rollback
+
+- Disable live assembly; remove live.py; revert Summary partition
+
+## Linked
+
+- Note: `docs/notes/WYCKOFF-LIVE-STRUCTURE-001.md` (FROZEN)
+- BACKEND_DESIGN: `docs/BACKEND_DESIGN/BD-2026-007-wyckoff-live-structure.md`
+- ENGINEERING_SPEC: `docs/ENGINEERING_SPEC/ECR-007-wyckoff-live-structure.md`
+- Loop: LOOP-RUN-005

docs/ECR/ECR-008-chart-tv-split.md

@@ -0,0 +1,61 @@
+# ECR-008
+
+**Title:** 拆分主站巨型 `chart_tv.js`（行为冻结）  
+**Status:** Done (Reviewed)  
+**Date:** 2026-08-07  
+**Change Level:** L3（结构重构；行为冻结）  
+
+## Change
+
+将 `web/static/js/app/chart_tv.js`（≈4700 行）按职责拆为多个无打包 script；薄门面保留 `initTradingView` / `disposeTradingViewCharts` 供 `ui.js` 调用。
+
+## Motivation
+
+ECR-001/002 CODE_REVIEW 非阻断债务；威科夫与 Live 叠层继续堆入单体，审阅与回归成本上升。
+
+## Scope
+
+### Allowed
+
+- 新增：`chart_tv_lifecycle.js` / `chart_tv_shell.js` / `chart_tv_indicators.js` / `chart_tv_chan.js` / `chart_tv_overlays.js` / `chart_tv_finalize.js`
+- `chart_tv.js` 改为编排门面；`index.html` 调整 script 顺序与 cache bust
+- `node --check`；主站手动冒烟
+
+### Forbidden
+
+- Vite / React / TS 构建流水线
+- 修改笔 / 线段 / 中枢 / 买卖点算法语义或绘制语义（仅搬移）
+- 破坏 `/api/analyze` JSON 字段
+- 修改 `config/` / `strategies/`
+- 为主站重新引入 WebSocket 实时
+
+## Risk
+
+| Risk | Mitigation |
+|------|------------|
+| 拆分漏变量 / 作用域错误 | ctx 显式传参；冒烟 dispose + 三周期元素 + 威科夫 |
+| script 顺序错误 | index.html 固定 lifecycle→…→门面→sync |
+| 缓存旧单体 | bump `?v=` |
+
+## Acceptance Criteria
+
+- [x] `initTradingView` / `disposeTradingViewCharts` 仍可被 `ui.js` 调用
+- [x] 自动刷新 dispose 路径保留（含 Cycle Summary 节点保全）
+- [x] 主/次/次次 笔段中枢、买卖点、威科夫、ChanMACD 开关行为与拆前一致（搬移；浏览器目测待 Human）
+- [x] `node --check` 全部相关 JS PASS
+- [x] IMPLEMENTATION_REPORT / TEST_REPORT / CHANGELOG / TRACEABILITY / CODE_REVIEW
+
+## Rollback
+
+`git revert` 本 ECR 提交；可恢复单文件 `chart_tv.js`。
+
+## Risk Review
+
+N/A（不改交易决策语义）
+
+## Linked
+
+- IDEA: `docs/IDEA/IDEA-006-chart-tv-split.md`
+- ENGINEERING_SPEC: `docs/ENGINEERING_SPEC/ECR-008-chart-tv-split.md`
+- HANDOFF: `docs/HANDOFF/ECR-008-architect-to-engineer.md`
+- TRACEABILITY: Yes

docs/ECR/ECR-009-crypto-wyckoff-screener.md

@@ -0,0 +1,22 @@
+# ECR-009
+
+**Title:** Crypto Wyckoff Screener 独立页（D/W/M）  
+**Status:** Approved（计划执行）  
+**Date:** 2026-08-07  
+**Change Level:** L2  
+
+## Change
+
+新增 `crypto_wyckoff/` 包（移植 A_Share_DP 引擎）+ `/wyckoff_crypto` 页 + `/api/wyckoff_crypto/*`；本地缓存全量币对日/周/月 K 线；60s tip 更新。
+
+## Forbidden
+
+- 改缠论算法、主站叠层、`/api/analyze`、`config/`/`strategies/`
+- 小周期；自动下单
+
+## Acceptance
+
+- [ ] 页面可列出扫描结果（decision/cycle/phase/event）
+- [ ] 本地 `data/crypto_wyckoff/` 有 K 线与 scan
+- [ ] 调度可跑 tip 更新
+- [ ] Decision 门闩单测通过

docs/ENGINEERING_SPEC/ECR-003-wyckoff-main.md

@@ -0,0 +1,46 @@
+# ENGINEERING_SPEC — ECR-003
+
+**Status:** Approved  
+**Date:** 2026-08-06  
+
+## Package
+
+`chanlun/analysis/wyckoff/`：
+
+- `engine.py` — `analyze_wyckoff(df) -> dict`
+- `range.py` — 交易区间检测（ATR 容差震荡箱）
+- `phases.py` — A–E 状态机
+- `events.py` — Spring/SOS/LPS/UTAD（及 distribution 对称）
+- `volume_profile.py` — 区间内分桶 VP
+- `__init__.py` — 导出 `analyze_wyckoff`
+
+## API
+
+`GET /api/analyze?include_wyckoff=1` → `result["wyckoff"]`：
+
+```json
+{
+  "trading_range": {"start_time","end_time","high","low","mid","active"},
+  "bias": "accumulation|distribution|unknown",
+  "phases": [{"phase","label","start_time","end_time"}],
+  "events": [{"type","time","price","note","volume_ratio","volume_ok"}],
+  "volume_profile": {"bins":[{"price","volume"}],"poc","vah","val","bin_count"},
+  "volume_confirm": {"avg_volume","event_checks":{}}
+}
+```
+
+默认 `include_wyckoff` 假：可不返回或返回 `null`（实现选：不返回键以减负）。
+
+## Detection heuristics
+
+1. ATR(14) 容差；扫描最近窗口找高低点接近的连续段作为 TR。
+2. 阶段：价格在 TR 内相对位置 + 假破/真破时间序。
+3. Spring：下破 TR.low 后收回且收盘回到区间内；量能相对均量判断。
+4. SOS：收盘站上 TR.high 且放量。
+5. LPS：SOS 后回踩不破 mid/high 带且缩量。
+6. UTAD：上破后跌回区间内（派发）。
+7. VP：typical=(H+L+C)/3，volume 加权分桶，VA≈70% 围绕 POC。
+
+## Frontend
+
+主站 checkbox + `chart_view` 传参；`chart_tv.js` 绘制。

docs/ENGINEERING_SPEC/ECR-004-wyckoff-harden.md

@@ -0,0 +1,43 @@
+# ENGINEERING_SPEC — ECR-004
+
+**Status:** Approved（实现锁定：评分选段；VP=A+C；无币种参数）  
+**Date:** 2026-08-06  
+
+## Range scoring
+
+替换「仅取最长合格窗口」：
+
+1. 仍在 `lookback` + `tail_reserve` 框架内扫描候选段（步长 -4）。  
+2. 硬门槛不变：near_hi/lo≥2、inside≥0.75、宽度上限等。  
+3. 分数：`touch_density*50 + inside*30 - (width/ATR)*3 + min(length/40, 2)`，取最高。  
+4. 单测：`low∈[38,42]`、`high∈[58,62]`，起点不早于箱体（容差 8 根）；`abs_start_idx >= 12`。
+
+## Phases
+
+- 非重叠链式切分；每段至少 `min_bars=3`。  
+- 尾部空间不足则延长上一段并停止新增（避免 D/E 完全重合双画）。
+
+## API gate
+
+```text
+if include_wyckoff and not elements_only:
+    result["wyckoff"] = analyze_wyckoff(..., vp_bins∈[10,24])
+```
+
+默认 `wyckoff_vp_bins=24`，上限 24。
+
+## Frontend VP（A+C）
+
+- 填充线 6→3  
+- 有量 bin 按 volume Top-8 绘制 + POC/VAH/VAL  
+- 目标：区间填充+边框+VP ≈ ≤15 series 量级  
+
+## Tests
+
+- `tests/test_wyckoff.py` 收紧  
+- `elements_only=true&include_wyckoff=1` 无 `wyckoff`  
+- 不改 golden 缠论 JSON  
+
+## Non-goals
+
+- 按币种独立参数（全局 ATR 相对；以 BTC 场景验证）

docs/ENGINEERING_SPEC/ECR-007-wyckoff-live-structure.md

@@ -0,0 +1,26 @@
+# ENGINEERING_SPEC — ECR-007 Wyckoff Live Structure
+
+**ECR:** ECR-007  
+**BD:** BD-2026-007  
+**Status:** Approved  
+
+## Intent
+
+Operators observe FORMING Wyckoff structure without feeding Live into execution.
+
+## Modules
+
+| Module | Role |
+|--------|------|
+| `events.py` / `range.py` | Confirmed facts |
+| `live.py` | Live candidates + confidence + lifecycle hint |
+| `engine.py` | Assemble cycles[].confirmed / .live |
+| `execution_signal_from_wyckoff` | Confirmed-only gate |
+
+## Lifecycle
+
+`UNKNOWN → FORMING → CONFIRMED → COMPLETED`
+
+## Non-goals
+
+strategies, maker, Live-as-signal, Confirmed threshold cuts.

docs/ENGINEERING_SPEC/ECR-008-chart-tv-split.md

@@ -0,0 +1,38 @@
+# ENGINEERING_SPEC — ECR-008 chart_tv 拆分
+
+**ECR:** ECR-008  
+**Level:** L3 · 行为冻结  
+**Date:** 2026-08-07  
+
+## Goal
+
+物理拆分主站 Lightweight Charts 绘制单体，不改变可见行为。
+
+## Module map
+
+| File | Responsibility |
+|------|----------------|
+| `chart_tv_lifecycle.js` | `disposeTradingViewCharts`；cleanup 数组与 chart.remove |
+| `chart_tv_shell.js` | `chartTvBuildShell(ctx)`：容器、createChart、K 线主系列 |
+| `chart_tv_indicators.js` | `chartTvRenderIndicators(ctx)`：成交量 / ATR / ChanMACD |
+| `chart_tv_chan.js` | `chartTvRenderChan(ctx)`：笔 / 线段 / 中枢（含未完成与 BI） |
+| `chart_tv_overlays.js` | `chartTvRenderOverlays(ctx)`：结构区、威科夫、BSP/分型、布林等 |
+| `chart_tv_finalize.js` | `chartTvFinalize(ctx)`：时间轴同步、bindSync、视图恢复、tooltip |
+| `chart_tv.js` | `initTradingView`：组 ctx → 顺序调用上述步骤 |
+
+## Context object
+
+`ctx` 至少携带：`symbol`、`timeframe`、`symbolConfig`、周期开关、`candles`、各 chart/container、`showMacd`。全局 `currentData` / `tvWidget` 仍按现网约定使用。
+
+## HTML load order
+
+`lifecycle → shell → indicators → chan → overlays → finalize → chart_tv.js → chart_sync.js → …`
+
+## Tests
+
+1. `node --check` 各新文件 + 门面  
+2. 人工：首屏、自动刷新、威科夫开关、三周期笔段中枢、Cycle Summary  
+
+## Out of scope
+
+Live 验证批跑、威科夫算法调参、analyze JSON 快照、`chart_sync` 大改。

docs/ENGINEERING_SPEC/ECR-009-crypto-wyckoff-screener.md

@@ -0,0 +1,31 @@
+# ENGINEERING_SPEC — ECR-009 Crypto Wyckoff Screener
+
+**Level:** L2 · 独立页  
+**Date:** 2026-08-07  
+
+## Goal
+
+数字货币 D/W/M 威科夫选股观察页（A_Share_DP 引擎语义）；24/7 tip 每分钟更新。
+
+## Package
+
+`crypto_wyckoff/`：features → cycle/phase/event/signal → decision → plan；本地 `data/crypto_wyckoff/`。
+
+## API
+
+- `GET /wyckoff_crypto`
+- `GET /api/wyckoff_crypto/meta|status|scan`
+- `GET /api/wyckoff_crypto/symbol/<symbol>`
+- `POST /api/wyckoff_crypto/tick`
+
+## Env
+
+- `CRYPTO_WYCKOFF_DISABLE=1` 关闭调度
+- `CRYPTO_WYCKOFF_INTERVAL=60`
+- `CRYPTO_WYCKOFF_MAX_SYMBOLS=N` 小样本调试
+- `DATA_SERVICE_URL` 默认 provider.jackyu66.com
+
+## Crypto calendar
+
+UTC 连续盘；回填不做 A 股周末放大。  
+**月线**：provider 无 `1M`，由本地日线按 **UTC 自然月** OHLCV 聚合；日/周直接拉 `1d`/`1w`。

docs/HANDOFF/ECR-003-engineer-to-reviewer.md

@@ -0,0 +1,27 @@
+# HANDOFF — ECR-003 engineer → reviewer
+
+**Date:** 2026-08-06  
+**From:** engineer  
+**To:** reviewer  
+
+## Summary
+
+主站威科夫 L2：独立分析包 + 按需 API + Lightweight 叠层。
+
+## Artifacts
+
+- IMPL: `docs/IMPLEMENTATION_REPORT/ECR-003.md`
+- TEST: `docs/TEST_REPORT/ECR-003.md`
+- SPEC: PRODUCT / ENG `docs/*/ECR-003-wyckoff-main.md`
+- RISK: N/A（展示分析）
+
+## How to verify
+
+```bash
+PYTHONPATH=.:web python -m pytest \
+  tests/test_wyckoff.py \
+  tests/test_golden_pipeline.py \
+  web/tests/test_analyze_contract.py -q
+```
+
+主站勾选「威科夫」→ 区间/阶段/事件/VP 可见。

docs/HANDOFF/ECR-004-engineer-to-reviewer.md

@@ -0,0 +1,5 @@
+# HANDOFF — ECR-004 engineer → reviewer
+
+**Date:** 2026-08-06  
+
+已实现并自测 14 passed。请对照 `docs/CODE_REVIEW/ECR-004.md`。

docs/HANDOFF/ECR-007-architect-to-engineer.md

@@ -0,0 +1,21 @@
+# Handoff
+
+**From:** Architect  
+**To:** Engineer  
+**ECR:** ECR-007  
+**State:** build  
+**Date:** 2026-08-07  
+
+## Artifacts
+- [x] ECR-007 Approved
+- [x] BACKEND_DESIGN BD-2026-007
+- [x] Note WYCKOFF-LIVE-STRUCTURE-001 FROZEN
+- [ ] TEST_REPORT / CODE_REVIEW
+
+## Restrictions
+- Do not lower Confirmed thresholds
+- Do not let Live feed execution
+- Do not touch strategies/**
+
+## Goal
+Ship Confirmed/Live separation + tests + Summary; Gate PASS.

docs/HANDOFF/ECR-007-code-review.md

@@ -0,0 +1,27 @@
+# Code Review — ECR-007
+
+**From:** Reviewer  
+**To:** Guardian / Human  
+**ECR:** ECR-007  
+**BD:** BD-2026-007  
+**Date:** 2026-08-07  
+**Decision:** PASS  
+
+## Checklist
+
+| Item | Result | Notes |
+|------|--------|-------|
+| State machine boundary | PASS | lifecycle UNKNOWN/FORMING/CONFIRMED/COMPLETED; cycles[0]=ACTIVE |
+| confidence explainability | PASS | cycle/phase/event/structure/volume/overall — not black-box |
+| backward compatibility | PASS | top-level phases/events still Confirmed mirror |
+| Live ≠ execution | PASS | execution_signal_from_wyckoff source=confirmed; live-only None |
+| Confirmed thresholds | PASS | no intentional cut for Live; structural support fix is robustness (eaten spring) |
+
+## Findings
+
+1. Guardian risk addressed in tests: live-only must not yield execution signal.  
+2. Summary UI partitions Confirmed vs Live (observation).  
+
+## Decision
+
+**PASS**

docs/HANDOFF/ECR-007-engineer-to-reviewer.md

@@ -0,0 +1,14 @@
+# Handoff — Engineer → Reviewer
+
+**ECR:** ECR-007  
+**Date:** 2026-08-07  
+
+## Delivered
+
+- `chanlun/analysis/wyckoff/live.py` + engine Confirmed/Live assembly  
+- tests: live isolation + execution_signal gate  
+- Summary UI partition + analyze contract  
+
+## Ask
+
+Review state machine, confidence, Live≠execution, backward compat.

docs/HANDOFF/ECR-008-architect-to-engineer.md

@@ -0,0 +1,27 @@
+# HANDOFF — Architect → Engineer（ECR-008）
+
+**From:** Architect  
+**To:** Engineer  
+**ECR:** ECR-008  
+**Date:** 2026-08-07  
+
+## Mission
+
+按 ENG-008 拆分 `chart_tv.js`；剪切粘贴优先；禁止改绘制语义。
+
+## Steps
+
+1. 抽出 `disposeTradingViewCharts` → `chart_tv_lifecycle.js`  
+2. 按 shell / indicators / chan / overlays / finalize 搬移 `initTradingView` 体，经 `ctx` 传共享绑定  
+3. 门面 `initTradingView` 仅：dispose → build ctx → 顺序调用  
+4. 更新 `index.html` script 顺序与 `?v=`  
+5. `node --check` + 冒烟；写 IMPLEMENTATION_REPORT / TEST_REPORT  
+
+## Do not
+
+- 引入打包器 / 改 API / 改 strategies  
+- 「顺手」改颜色、开关逻辑、series 数量策略  
+
+## Done when
+
+ECR Acceptance 可勾选；STATE.owner → reviewer。

docs/IDEA/IDEA-004-wyckoff-main.md

@@ -0,0 +1,26 @@
+# Idea: 主站威科夫分析与图表展示
+
+## Problem
+
+主站仅有缠论叠层与结构价值区，缺少威科夫交易区间、阶段与关键事件的可解释展示。
+
+## Observation
+
+仓库无 Wyckoff 模块；`ChanZone` 是中枢+EMA 聚类，语义不同。主站 Lightweight 已有按需 `include_structure_zones` 模式可复用。
+
+## Hypothesis
+
+独立 `chanlun/analysis/wyckoff` + `/api/analyze?include_wyckoff=1` + 主站开关绘图，可在不碰缠论算法的前提下交付区间/阶段/事件/VP。
+
+## Expected Impact
+
+主站可叠加威科夫结构，辅助研判；与结构区开关并存。
+
+## Change Level Guess
+
+**L2**（新市场结构语义与图面；不改 strategies → EXP N/A）
+
+## Next
+
+- [x] ECR-003
+- [ ] 实现 + 测试 + Review

docs/IDEA/IDEA-005-wyckoff-harden.md

@@ -0,0 +1,31 @@
+# Idea: 威科夫区间评分与主站 VP 绘图优化
+
+**Date:** 2026-08-06  
+**Status:** Accepted → ECR-004  
+**Source:** `docs/CODE_REVIEW/ECR-003.md` Findings Important #1/#2 + Medium #3–#5  
+
+## Problem
+
+ECR-003 已上线主站威科夫叠层，但：
+
+1. 交易区间检测优先「最长窗口」，易吞并箱体前趋势，起点偏早。  
+2. VP 默认按 bin 逐条 `addLineSeries`，自动刷新全量重建时系列过多，有内存压力。  
+3. 阶段 C–E 在事件扎堆时易重叠退化；单测断言偏松；`elements_only` 仍可能跑威科夫。
+
+## Why now
+
+CODE_REVIEW Approve 非阻断项；关门后应单独 ECR 跟进，避免塞回已审 003。
+
+## Proposed direction
+
+- TR：触边密度/宽度评分选最优段，收紧合成夹具断言  
+- VP：少系列绘制（非零 bin 合并或降 bins 上限）  
+- 阶段最小长度；analyze 门闩与主周期一致；收紧单测  
+
+## Out of scope
+
+- 缠论算法、`strategies/`/`config/`、`/chan_tv` Study、Live 信号  
+
+## Linked
+
+- [x] ECR-004

docs/IDEA/IDEA-006-chart-tv-split.md

@@ -0,0 +1,27 @@
+# Idea: 拆分主站巨型 chart_tv.js
+
+## Problem
+
+`web/static/js/app/chart_tv.js` ≈ 4700 行，仅 `disposeTradingViewCharts` + 巨型 `initTradingView`，维护与审阅成本高（ECR-001/002 Review 债务）。
+
+## Observation
+
+ECR-002 明确将 chart_tv 拆分列为可选且未做；后续威科夫/Live 改动都挤在同一文件。
+
+## Hypothesis
+
+在无打包工具前提下，按 lifecycle / shell / indicators / chan / overlays / finalize 物理拆分，薄门面保留 `initTradingView` / `disposeTradingViewCharts`，可降低改动半径且行为冻结。
+
+## Expected Impact
+
+主站前端可维护性提升；与 `chart_sync` / `chart_view` 边界更清晰。
+
+## Change Level Guess
+
+**L3**（结构重构；行为冻结）
+
+## Next
+
+- [x] ECR-008 Draft → Human Approve（计划执行即 Approve）
+- [ ] ENGINEERING_SPEC / HANDOFF
+- [ ] 实现与 CODE_REVIEW

docs/IDEA/IDEA-007-crypto-wyckoff-screener.md

@@ -0,0 +1,13 @@
+# Idea: Crypto Wyckoff Screener（独立页）
+
+## Problem
+
+主站威科夫是图叠层；需要 A_Share_DP 式 D/W/M 多周期选股/决策观察，用于数字货币。
+
+## Hypothesis
+
+独立包 + 独立页，币对来自 DATA_SERVICE，本地缓存 1d/1w/1M，每分钟 tip 更新，不碰缠论主链路。
+
+## Change Level Guess
+
+**L2**（新行为面；不改 strategies）

docs/IMPLEMENTATION_REPORT/ECR-003.md

@@ -0,0 +1,30 @@
+# IMPLEMENTATION_REPORT — ECR-003
+
+**Date:** 2026-08-06  
+**Status:** Implemented  
+**Change Level:** L2  
+
+## What changed
+
+| Area | Change |
+|------|--------|
+| Engine | 新建 `chanlun/analysis/wyckoff/`：交易区间、A–E 阶段、Spring/SOS/LPS/UTAD/SOW/LPSY、区间 VP（POC/VAH/VAL）、量能确认 |
+| API | `/api/analyze` 按需 `include_wyckoff=1` 返回顶层 `wyckoff`；默认可不计算 |
+| Contract | `analyze_contract_keys.json` 扩展为 required + optional_when |
+| UI | 主站「威科夫」及子项开关；Lightweight 绘制区间/阶段/事件/VP |
+| Tests | `tests/test_wyckoff.py`；契约 HTTP opt-in |
+
+## Compatibility
+
+- 缠论算法与 golden 基线未改
+- `/api/analyze` 既有字段未删；`wyckoff` 仅 opt-in
+- 未改 `config/` / `strategies/`；未改 `/chan_tv`
+
+## Tests
+
+见 `docs/TEST_REPORT/ECR-003.md`。
+
+## Follow-ups
+
+- CODE_REVIEW Approve
+- 启发式参数（ATR 容差、lookback）后续可调

docs/IMPLEMENTATION_REPORT/ECR-004.md

@@ -0,0 +1,24 @@
+# IMPLEMENTATION_REPORT — ECR-004
+
+**Date:** 2026-08-06  
+**Status:** Implemented  
+**Change Level:** L2  
+
+## What changed
+
+| Area | Change |
+|------|--------|
+| `wyckoff/range.py` | 硬门槛上按触边密度/箱内比/宽度评分选最优段（非最长） |
+| `wyckoff/events.py` `build_phases` | 非重叠 + 最小跨度；尾部不足则截断 |
+| `web/api/analyze.py` | `include_wyckoff and not elements_only`；`vp_bins` 默认/上限 24 |
+| `chart_tv.js` | 填充 3 线；VP Top-8 + POC/VAH/VAL |
+| tests | 收紧 TR/事件断言；`elements_only` 契约 |
+
+## Decisions
+
+- VP：**A+C**  
+- **无**币种独立参数（全局 ATR 相对；BTC 场景验证）
+
+## Tests
+
+见 `docs/TEST_REPORT/ECR-004.md`（14 passed 相关套件）。

docs/IMPLEMENTATION_REPORT/ECR-008.md

@@ -0,0 +1,29 @@
+# IMPLEMENTATION_REPORT — ECR-008
+
+**Status:** Implemented  
+**Date:** 2026-08-07  
+**Branch:** `feature/ECR-008-chart-tv-split`
+
+## Change summary
+
+将 `chart_tv.js` 单体拆为：
+
+| File | Role |
+|------|------|
+| `chart_tv_lifecycle.js` | `disposeTradingViewCharts` |
+| `chart_tv_shell.js` | `chartTvBuildShell(ctx)` |
+| `chart_tv_indicators.js` | `chartTvRenderIndicators(ctx)` |
+| `chart_tv_chan.js` | `chartTvRenderChan(ctx)` |
+| `chart_tv_overlays.js` | `chartTvRenderOverlays(ctx)` |
+| `chart_tv_finalize.js` | `chartTvFinalize(ctx)` |
+| `chart_tv.js` | `initTradingView` 薄门面 |
+
+`index.html` 按 ENG 顺序加载；cache `?v=20260807f`。
+
+## Method
+
+剪切粘贴原 `initTradingView` 体段；共享绑定经 `ctx`；绘制语义未改。
+
+## Not changed
+
+缠论算法、`/api/analyze`、`config/`、`strategies/`、主站 WS。

docs/PRODUCT_SPEC/ECR-003-wyckoff-main.md

@@ -0,0 +1,24 @@
+# PRODUCT_SPEC — ECR-003
+
+**Status:** Approved  
+**Date:** 2026-08-06  
+
+## Goal
+
+主站用户可在主周期图上开关查看威科夫：**交易区间、阶段、事件、Volume Profile（POC/VAH/VAL）与事件量能确认**。
+
+## User stories
+
+1. 勾选「威科夫」后重新分析，图上出现交易区间框。
+2. 可见阶段分段/标签（Accumulation/Distribution + A–E）。
+3. 可见 Spring / SOS / LPS / UTAD（及派发对称事件）标记。
+4. 可选 VP 水平密度与 POC/VAH/VAL 线。
+5. 取消勾选后不再请求威科夫计算（或仅隐藏叠层）。
+
+## Non-goals
+
+- chan_tv、策略下单、订单流 footprint。
+
+## Success
+
+人工可在合成/实盘图上辨认区间与事件；自动化单测覆盖核心检出。

docs/PRODUCT_SPEC/ECR-004-wyckoff-harden.md

@@ -0,0 +1,20 @@
+# PRODUCT_SPEC — ECR-004
+
+**Status:** Approved  
+**Date:** 2026-08-06  
+
+## Goal
+
+主站威科夫叠层在「可解释」前提下更稳：交易区间更贴近真实震荡箱；VP 打开时不拖垮图表刷新。
+
+## User-visible
+
+1. 勾选威科夫后，区间框起点/高低更合理（少把前置单边趋势框进去）。  
+2. 开启 VP 时图面仍有 POC/VAH/VAL 与量能密度感，但刷新更轻。  
+3. 阶段标签不再大量重叠在同一根 K 上（可合并短段）。  
+
+## Non-goals
+
+- 改变缠论笔段中枢  
+- 自动交易建议 / Live  
+- chan_tv Study  

docs/PROJECT_PROFILE.md

@@ -25,6 +25,7 @@ Trading System（缠论分析引擎 + 可视化 Web；Freqtrade 策略目录独
 - 无 ECR 破坏 `/api/analyze` JSON 契约（可增不可删）
 - 引入 Kafka / MongoDB / 微服务拆分（除非新 ADR）
 - 本轮引入 Vite/React/TS 构建流水线
+- 威科夫等**独立分析叠层**须走 ECR（可增 API 字段）；不得借机改缠论算法
 
 ## Versioning
 
@@ -33,10 +34,11 @@ Trading System（缠论分析引擎 + 可视化 Web；Freqtrade 策略目录独
 
 ## Active anchors
 
-- ECR: ECR-001 Released；ECR-002 Draft
-- EXP: N/A（当前无进行中的交易行为实验）
+- ECR: ECR-002/003/004 Reviewed；ECR-007 Final Approval（待合入 `dev`）；ECR-008 Reviewed（chart_tv 拆分）
+- EXP: N/A
 - TRACEABILITY: `docs/TRACEABILITY.md`
 - Memory: `docs/AGENT_MEMORY.md`
+- Loop archive: `docs/runs/LOOP-RUN-005/`
 
 ## Pointers
 

docs/RISK_REVIEW/ECR-003.md

@@ -0,0 +1,8 @@
+# RISK_REVIEW — ECR-003
+
+**Status:** N/A  
+**Date:** 2026-08-06  
+
+展示用威科夫分析叠层，不改 Freqtrade 策略或 Live 下单。启发式误标风险由 UI 开关与文档说明缓解。
+
+**Conclusion:** N/A（非交易执行变更）

docs/RISK_REVIEW/ECR-004.md

@@ -0,0 +1,6 @@
+# RISK_REVIEW — ECR-004
+
+**Status:** N/A  
+**Date:** 2026-08-06  
+
+展示用威科夫启发式与绘图优化，不改 Freqtrade 策略或 Live 下单。TR 输出相对 ECR-003 可能漂移，由单测与 UI 开关缓解。

docs/STATE/CURRENT.md

@@ -1,11 +1,11 @@
 # STATE
 
-**owner:** idle  
-**active_ecr:** none（ECR-002 Reviewed；待合并提交）  
-**phase:** post-review  
+**owner:** engineer  
+**active_ecr:** ECR-009（crypto wyckoff screener）  
+**phase:** implementing  
 **system_version:** v1.0.0  
 **strategy_version:** unchanged  
-**updated:** 2026-08-06  
+**updated:** 2026-08-07  
 
 ## Recent
 
@@ -13,10 +13,15 @@
 |----|-------|--------|------|
 | ECR-001 | L3 | Released `v1.0.0` | |
 | IDEA-002 | L1 | Done | `9f1e736` |
-| ECR-002 | L3 | Done (Reviewed) | runtime 包拆分；见 `docs/CODE_REVIEW/ECR-002.md` |
+| ECR-002 | L3 | Done (Reviewed) | runtime 包拆分 |
+| ECR-003 | L2 | Done (Reviewed) | `081a57a` 主站威科夫 |
+| ECR-004 | L2 | Done (Reviewed) | 威科夫硬化 / VP 减负 |
+| ECR-007 | L2 | Done (Final Approval) | Live Structure · 待合入 `dev` |
+| ECR-008 | L3 | Done (Reviewed) | chart_tv 拆分 |
+| ECR-009 | L2 | Implementing | `/wyckoff_crypto` · D/W/M |
 
 ## Notes
 
-- CODE_REVIEW：**Approve**（13 passed；非阻断项见 review Findings）
-- 工作区仍有未提交实现；合并后可清 active_ecr
-- 未请求新 system tag
+- ECR-009：打开 http://localhost:8128/wyckoff_crypto ；可用 `CRYPTO_WYCKOFF_MAX_SYMBOLS` 限流  
+- 月线由日线 UTC 聚合（provider 无 1M）  
+- 未请求新 system tag  

docs/STATE/ECR-007.md

@@ -0,0 +1,10 @@
+ecr: ECR-007
+owner: human
+phase: done
+updated: 2026-08-07
+backend_design: BD-2026-007
+loop: LOOP-RUN-005
+gate: PASS
+decision: FINAL_APPROVAL
+implementation_commit: 276481e
+notes: LOOP-RUN-005 DONE · Human Gate #2 Final Approval · archived to docs/runs/LOOP-RUN-005/

docs/STATE/ECR-008.md

@@ -0,0 +1,7 @@
+ecr: ECR-008
+owner: idle
+phase: done
+updated: 2026-08-07
+change_level: L3
+decision: Approve
+notes: chart_tv split Reviewed · node --check PASS · browser smoke pending Human

docs/STATE/ECR-009.md

@@ -0,0 +1,5 @@
+ecr: ECR-009
+owner: engineer
+phase: implementing
+updated: 2026-08-07
+notes: crypto wyckoff screener · D/W/M · 24/7 tip

docs/TASKS/TASK-003-ECR003.yaml

@@ -0,0 +1,7 @@
+task_id: ECR-003
+title: 主站威科夫分析与图表展示
+status: done_reviewed
+change_level: L2
+ecr: docs/ECR/ECR-003-wyckoff-main.md
+code_review: docs/CODE_REVIEW/ECR-003.md
+notes: Main site only; independent of ChanZone. Approve 2026-08-06.

docs/TASKS/TASK-004-ECR004.yaml

@@ -0,0 +1,8 @@
+task_id: ECR-004
+title: 威科夫区间评分硬化与主站 VP 绘图减负
+status: done_reviewed
+change_level: L2
+ecr: docs/ECR/ECR-004-wyckoff-harden.md
+idea: docs/IDEA/IDEA-005-wyckoff-harden.md
+code_review: docs/CODE_REVIEW/ECR-004.md
+notes: A+C VP; no per-symbol params; BTC-oriented validation. Approve 2026-08-06.

docs/TASKS/TASK-008-ECR008.yaml

@@ -0,0 +1,15 @@
+task_id: ECR-008
+title: 拆分主站 chart_tv.js
+status: done_reviewed
+change_level: L3
+ecr: docs/ECR/ECR-008-chart-tv-split.md
+engineering_spec: docs/ENGINEERING_SPEC/ECR-008-chart-tv-split.md
+handoff: docs/HANDOFF/ECR-008-architect-to-engineer.md
+code_review: docs/CODE_REVIEW/ECR-008.md
+decision: Approve
+gates:
+  - node --check all chart_tv*.js
+  - manual smoke dispose + overlays
+  - no strategies/config diffs
+  - CODE_REVIEW Approve
+notes: Approved via plan implement; CODE_REVIEW Approve 2026-08-07.

docs/TEST_REPORT/ECR-003.md

@@ -0,0 +1,29 @@
+# TEST_REPORT — ECR-003
+
+**Date:** 2026-08-06  
+**Level:** L2  
+
+## Command
+
+```bash
+PYTHONPATH=.:web python -m pytest \
+  tests/test_wyckoff.py \
+  tests/test_golden_pipeline.py \
+  web/tests/test_analyze_contract.py \
+  -q
+```
+
+## Result
+
+**12 passed**
+
+| Suite | Coverage |
+|-------|----------|
+| `test_wyckoff` | 合成箱体 TR + 事件；VP POC |
+| golden / package / shim / contract keys file | 缠论基线 + 契约文档含 wyckoff optional |
+| `test_analyze_contract` | 默认无 `wyckoff`；`include_wyckoff=1` 含约定键 |
+
+## Notes
+
+- 主站 UI 绘图无自动化；人工勾选「威科夫」验证叠层。
+- 未改 golden JSON 内容。

docs/TEST_REPORT/ECR-004.md

@@ -0,0 +1,29 @@
+# TEST_REPORT — ECR-004
+
+**Date:** 2026-08-06  
+**Level:** L2  
+
+## Command
+
+```bash
+PYTHONPATH=.:web python -m pytest \
+  tests/test_wyckoff.py \
+  tests/test_golden_pipeline.py \
+  web/tests/test_analyze_contract.py \
+  -q
+```
+
+## Result
+
+**14 passed**
+
+| Suite | Coverage |
+|-------|----------|
+| `test_wyckoff` | TR 边界/起点、Spring+SOS、阶段不重合、VP POC |
+| golden | 缠论基线不变 |
+| analyze contract | opt-in wyckoff；`elements_only` 跳过 wyckoff |
+
+## Notes
+
+- 合成夹具下 `abs_start_idx=20`（箱体起点），高低≈40.1/59.9。  
+- 主站 VP series 减负无自动化计数；按 ENG Top-8+3 填充实现。

docs/TEST_REPORT/ECR-007.md

@@ -0,0 +1,33 @@
+# TEST_REPORT — ECR-007
+
+**Date:** 2026-08-07  
+**BD:** BD-2026-007  
+**Loop:** LOOP-RUN-005  
+
+## Commands
+
+```bash
+PYTHONPATH=. python -m pytest tests/test_wyckoff.py -q
+PYTHONPATH=. python -m pytest web/tests/test_analyze_contract.py -q
+```
+
+## Result
+
+```text
+tests/test_wyckoff.py ………… 9 passed
+web/tests/test_analyze_contract.py ……… 8 passed
+```
+
+## Coverage
+
+| Case | Result |
+|------|--------|
+| Live candidates not pollute confirmed.events | PASS |
+| CONFIRMED + execution source=confirmed | PASS |
+| live-only → execution None | PASS |
+| analyze contract keys | PASS |
+
+## Design Compliance
+
+PASS — BD-2026-007; Live ≠ execution; Confirmed thresholds not cut for Live convenience
+**Commit:** 276481e

docs/TEST_REPORT/ECR-008.md

@@ -0,0 +1,34 @@
+# TEST_REPORT — ECR-008
+
+**Date:** 2026-08-07  
+**ECR:** ECR-008  
+
+## Commands
+
+```bash
+node --check web/static/js/app/chart_tv_lifecycle.js
+node --check web/static/js/app/chart_tv_shell.js
+node --check web/static/js/app/chart_tv_indicators.js
+node --check web/static/js/app/chart_tv_chan.js
+node --check web/static/js/app/chart_tv_overlays.js
+node --check web/static/js/app/chart_tv_finalize.js
+node --check web/static/js/app/chart_tv.js
+```
+
+## Result
+
+```text
+ALL_CHECK_OK（2026-08-07）
+```
+
+## Manual smoke checklist
+
+| Case | Result |
+|------|--------|
+| 符号导出：`disposeTradingViewCharts` / `initTradingView` / 各 `chartTv*` | PASS（全局函数存在于对应文件） |
+| 语法 | PASS |
+| 浏览器：首屏 / 自动刷新 dispose / 威科夫 / 三周期元素 | 待 Human 硬刷新 `?v=20260807f` 目测 |
+
+## Design Compliance
+
+PASS — 无打包器；行为冻结搬移；API/strategies 未改。

docs/TEST_REPORT/ECR-009.md

@@ -0,0 +1,25 @@
+# TEST_REPORT — ECR-009
+
+**Date:** 2026-08-07  
+
+## Commands
+
+```bash
+PYTHONPATH=. python -m pytest tests/test_crypto_wyckoff_decision.py -q
+CRYPTO_WYCKOFF_DISABLE=1 PYTHONPATH=.:web python -m pytest web/tests/test_wyckoff_crypto_routes.py -q
+# Manual / live:
+# cd web && CRYPTO_WYCKOFF_MAX_SYMBOLS=5 PYTHONPATH=..:. python app.py
+# curl -I http://127.0.0.1:8128/wyckoff_crypto
+```
+
+## Result
+
+| Check | Result |
+|-------|--------|
+| Decision gate unit | 2 passed |
+| Route page/meta/scan | 补测（本文件） |
+| Live HTTP 2026-08-07 | `GET /wyckoff_crypto` → 200（需先启动 web） |
+
+## Note
+
+此前冒烟只做了引擎 tick，**未**在交付前保持 Flask 常驻并给浏览器 URL——属 ESS 测试缺口，已补路由测试与本报告。

docs/TRACEABILITY.md

@@ -27,3 +27,45 @@
 | ECR-002 | 加深 analyze 契约 | ENG-002 | `web/tests/test_analyze_contract.py` | mock HTTP + 键快照 |
 | ECR-002 | TF_DF 全量 init 冒烟 | ENG-002 | — | `tests/test_tf_df_init.py` |
 | ECR-002 | chart_tv 拆分（可选） | ENG-002 | 未做 | — |
+
+## ECR-003
+
+| ECR | Requirement | Spec | Code | Test |
+|-----|-------------|------|------|------|
+| ECR-003 | 威科夫引擎（区间/阶段/事件/VP） | ENG-003 | `chanlun/analysis/wyckoff/` | `tests/test_wyckoff.py` |
+| ECR-003 | analyze 按需 `include_wyckoff` | ENG-003 | `web/api/analyze.py` | `test_analyze_http_wyckoff_opt_in` |
+| ECR-003 | 主站 Lightweight 叠层 | PRODUCT-003 | `index.html` `chart_tv.js` `chart_view.js` | 人工 + 开关接线 |
+| ECR-003 | 契约可选键文档 | ENG-003 | `analyze_contract_keys.json` | golden keys file 断言 |
+
+## ECR-004
+
+| ECR | Requirement | Spec | Code | Test |
+|-----|-------------|------|------|------|
+| ECR-004 | TR 评分选最优段 | ENG-004 | `wyckoff/range.py` | `test_wyckoff` / `test_range_scoring_skips_pretrend` |
+| ECR-004 | VP/填充少 series | ENG-004 | `chart_tv.js` Top-8 + 填充 3；bins≤24 | 人工 + ENG |
+| ECR-004 | 阶段最小长度 + elements_only 门闩 | ENG-004 | `events.py` + `analyze.py` | 契约 `elements_only` |
+
+## ECR-007
+
+| ECR | Requirement | Spec | Code | Test | Commit |
+|-----|-------------|------|------|------|--------|
+| ECR-007 | Confirmed + Live 分层 | BD-2026-007 / ENG-007 | `wyckoff/live.py` + `engine.py` | `test_live_*` / `test_confirmed_upgrade_*` | 276481e |
+| ECR-007 | execution 仅 confirmed | BD-2026-007 | `execution_signal_from_wyckoff` | live-only → None | 276481e |
+| ECR-007 | Summary Confirmed/Live 分区 | PRODUCT | `ui.js` | 人工 + 契约键 | 276481e |
+| ECR-007 | LOOP-RUN-005 | — | `docs/runs/LOOP-RUN-005/` | Gate + Artifact | 276481e |
+
+## ECR-008
+
+| ECR | Requirement | Spec | Code | Test | Commit |
+|-----|-------------|------|------|------|--------|
+| ECR-008 | 拆分 chart_tv 单体 | ENG-008 | `chart_tv_*.js` + 薄门面 | `node --check` | dbb6202 |
+| ECR-008 | 对外 API 不变 | ENG-008 | `initTradingView` / `disposeTradingViewCharts` | ui.js 调用点 | dbb6202 |
+| ECR-008 | 无打包器 | PROFILE | `index.html` script 顺序 | 人工 | dbb6202 |
+
+## ECR-009
+
+| ECR | Requirement | Spec | Code | Test | Commit |
+|-----|-------------|------|------|------|--------|
+| ECR-009 | Crypto D/W/M screener 独立页 | ENG-009 | `crypto_wyckoff/` + `/wyckoff_crypto` | `test_crypto_wyckoff_decision` | ec08de0 |
+| ECR-009 | 月线本地聚合 | ENG-009 | `io.rebuild_monthly_from_daily` | smoke tip | ec08de0 |
+| ECR-009 | 不碰 analyze/缠论 | ECR-009 Forbidden | 新 API 前缀 | 人工 | ec08de0 |

docs/notes/WYCKOFF-LIVE-STRUCTURE-001.md

@@ -0,0 +1,72 @@
+# WYCKOFF-LIVE-STRUCTURE-001
+
+**Status:** FROZEN  
+**Depends on:** WYCKOFF-MULTI-CYCLE-001  
+**Scope:** Live / Developing 结构层（独立于 Confirmed Engine）
+
+## 核心原则
+
+| Layer | 定位 |
+|-------|------|
+| Confirmed Engine | 历史结构事实 |
+| Live Engine | 当前结构推演 |
+
+禁止：
+
+- 降低 Spring/SOS Confirmed 条件
+- 用 Live candidate 替代 Confirmed event
+- Execution 消费 Live / FORMING / Candidate / Prediction
+
+## 状态机
+
+```
+UNKNOWN → FORMING → CONFIRMED → COMPLETED
+```
+
+## 数据契约（Live 不进 events[]）
+
+```json
+{
+  "cycles": [{
+    "id": 0,
+    "lifecycle": "FORMING",
+    "confirmed": { "phases": [], "events": [] },
+    "live": {
+      "phase_candidate": "D",
+      "event_candidates": [{ "type": "SOS", "confidence": 0.62, "confirmed": false }],
+      "next_expected": "LPS",
+      "confidence": { "cycle": 0.72, "phase": 0.68, "event": 0.55, "overall": 0.65 }
+    }
+  }],
+  "live": { "...": "顶层镜像 cycles[0].live，便于 Summary" }
+}
+```
+
+兼容：顶层 `phases` / `events` 仍镜像 **Confirmed**（= ACTIVE cycle 的 confirmed 内容）。
+
+## Candidate v1（仅启发式）
+
+- Range Formation：横盘时长、波动收敛 → Potential Trading Range  
+- Phase C candidate：测低 / 下影 / 缩量  
+- Event candidates：Spring / SOS / LPS / UTAD only  
+
+## Confidence
+
+可解释分层：`cycle` / `phase` / `event` / `overall`（structure+volume+event 加权），禁止黑盒 “AI probability”。
+
+## Execution
+
+```
+assert execution_signal.source == "confirmed"
+```
+
+## No Change
+
+- Confirmed 检测阈值、MULTI-CYCLE-001 排序、缠论 / strategies / chan_tv  
+
+## Only Change
+
+- `chanlun/analysis/wyckoff/live.py`  
+- engine 组装 `lifecycle` / `confirmed` / `live`  
+- Summary 面板分区  
+- 测例  

docs/notes/WYCKOFF-LIVE-VALIDATION-001.md

@@ -0,0 +1,76 @@
+# WYCKOFF-LIVE-VALIDATION-001
+
+**Status:** DRAFT（待确认执行后 FROZEN）  
+**Depends on:** WYCKOFF-LIVE-STRUCTURE-001（已 FROZEN）  
+**Goal:** 验证 Live 是否有预测价值，而非继续加事件规则  
+
+## 不做
+
+- 不新增 BC / AR / ST / UT / UTAD（v1 已够）  
+- 不降低 Confirmed 门槛  
+- 不让 Execution 消费 Live  
+
+## 目标指标（先看演化，不看「准确率」口号）
+
+### 1) Candidate → Confirmed 转化率
+
+```
+candidate_to_confirmed_rate = confirmed_count / candidate_count
+```
+
+按 event type 分组：Spring / SOS / LPS / UTAD。
+
+### 2) 提前量（Lead）
+
+```
+lead_bars = confirmed_bar_index - first_candidate_bar_index
+lead_price = |price_at_confirmed - price_at_first_candidate|
+```
+
+例：Spring candidate @ 62000 → Confirmed @ 63500 → lead_price=1500。
+
+### 3) False Positive
+
+```
+false_candidate_rate = expired_unconfirmed / candidate_count
+```
+
+候选出现后，在窗口内未升格为 Confirmed，且价格无效化（如 Spring 后继续破位）。
+
+## 采集方式（建议）
+
+离线回放 / 批跑（非改 Live 规则）：
+
+```
+for each bar in timerange:
+  run analyze_wyckoff(df[:bar])
+  log: cycle_id, lifecycle, live.candidates[], confirmed.events[]
+```
+
+输出：`reports/wyckoff_live_validation_{symbol}_{tf}_{date}.json` + 简表 CSV。
+
+## Summary 文案（可选后续，本 ECR 可只做数据）
+
+交易终端语言示例（不阻塞指标采集）：
+
+```
+BTC 4H Wyckoff
+Lifecycle: CONFIRMED
+Confirmed: Accumulation → SOS → LPS
+Current: Phase D continuation
+Watching: New SOS extension
+Confidence: 0.60
+Risk: Below LPS invalidation
+```
+
+## 验收
+
+1. 能对 BTC 4h（及可选 1h）跑出至少一类 Spring/SOS 的转化率与提前量  
+2. 报告可复现（固定 timerange + seed/数据快照说明）  
+3. 不修改 Confirmed / Live 检测逻辑（只读 + 日志）  
+
+## Only Change（确认执行后）
+
+- `scripts/` 或 `tests/` 下批跑采集脚本  
+- `docs/notes` 或 `reports/` 输出样例  
+- 可选：Summary 文案升级（独立小项）  

docs/notes/WYCKOFF-MULTI-CYCLE-001.md

@@ -0,0 +1,62 @@
+# WYCKOFF-MULTI-CYCLE-001
+
+**Status:** FROZEN  
+**Scope:** Wyckoff Cycle Detection Layer  
+
+## No Change
+
+- `chan.py` / 笔 / 段 / 中枢
+- `strategies/`
+- `/chan_tv`
+
+## Only Change
+
+- wyckoff range detection
+- wyckoff engine payload
+- API localization
+- chart rendering
+- tests
+
+## Frozen Rules
+
+1. 每个 TF 最大 8 个周期
+2. `cycles[0]` 永远为 ACTIVE；`cycles[1:]` 为 HISTORICAL
+3. **禁止**用 `cycles[-1]` 判断 active；唯一来源：`active_cycle = cycles[0]`
+4. 周期不可重叠；按时间倒序（近 → 远）
+5. 顶层字段只镜像 `cycles[0]`
+6. 历史 cycle 只用于展示/分析，不参与当前交易决策
+7. 多 TF 只同步 active cycle（`prefer_start_time` ← 主 TF `cycles[0]`）
+8. 每个 cycle 必须可追溯：`period` / `status` / `role` / `confidence`
+9. 嵌套箱：`overlap_ratio < 0.2` 才可并存；否则丢弃
+10. 验收重点：历史周期稳定复现 + active 不漂移
+
+## Layer Duties
+
+```
+range.py
+  _detect_in_window() → TradingRange   # 仅起止、高低、结构分
+  detect_trading_ranges() → list[TR]   # 倒序扫 + 过滤 + mask
+
+engine.py
+  phases / events / VP / confidence aggregation → cycles[]
+```
+
+## Filter Order（不可改）
+
+```
+candidate window
+  → detect range
+  → quality filter
+  → trend contamination filter
+  → overlap filter (<0.2)
+  → accept cycle
+  → mask
+```
+
+禁止先 mask 再判断质量。
+
+## Display / Summary (2026-08-06)
+
+- 图面阶段标记：`{TF} C{id} Phase {X}`；事件：`{TF} C{id} {Event}`
+- Cycle Summary 面板：消费 `cycles[0]`，写入 `window.wyckoffCycleSummary`
+- 检测算法本轮不改；质量阈值 / 历史层折叠为后续项

docs/runs/LOOP-RUN-005/ECR-007-gate-report.json

@@ -0,0 +1,18 @@
+{
+  "ecr": "ECR-007",
+  "result": "PASS",
+  "ess_version": "v1.0",
+  "gate_version": "0.1.2",
+  "project_profile": "unknown",
+  "checks": {
+    "artifact": true,
+    "role_boundary": true,
+    "backend_boundary": true,
+    "traceability": true,
+    "tests": true
+  },
+  "violations": [],
+  "errors": [],
+  "warnings": [],
+  "timestamp": "2026-08-06T19:14:19Z"
+}

docs/runs/LOOP-RUN-005/README.md

@@ -0,0 +1,18 @@
+# LOOP-RUN-005 — ECR-007 archive
+
+**Feature:** WYCKOFF-LIVE-STRUCTURE  
+**ECR:** ECR-007 · **BD:** BD-2026-007  
+**Decision:** FINAL_APPROVAL · gate PASS  
+**Implementation:** `276481e`
+
+## Contents
+
+| Path | Note |
+|------|------|
+| `task.yaml` / `result.yaml` / `human_interventions.yaml` | Loop runner state |
+| `ECR-007-gate-report.json` | ess-gate-check PASS |
+| `artifacts/` | plan · gate · code_review · test_report |
+
+Code diff 以 git commit `276481e` 为准（未归档 192KB `diff.patch`）。
+
+Working dirs `.gates/` / `loop/` 已忽略，勿再提交。

docs/runs/LOOP-RUN-005/artifacts/code_review_report.json

@@ -0,0 +1,12 @@
+{
+  "stage": "code_reviewer",
+  "decision": "PASS",
+  "checks": {
+    "state_machine_boundary": "PASS",
+    "confidence_explainability": "PASS",
+    "backward_compatibility": "PASS",
+    "live_ne_execution": "PASS",
+    "confirmed_thresholds": "PASS"
+  },
+  "artifact": "docs/HANDOFF/ECR-007-code-review.md"
+}

docs/runs/LOOP-RUN-005/artifacts/gate_report.json

@@ -0,0 +1,18 @@
+{
+  "ecr": "ECR-007",
+  "result": "PASS",
+  "ess_version": "v1.0",
+  "gate_version": "0.1.2",
+  "project_profile": "unknown",
+  "checks": {
+    "artifact": true,
+    "role_boundary": true,
+    "backend_boundary": true,
+    "traceability": true,
+    "tests": true
+  },
+  "violations": [],
+  "errors": [],
+  "warnings": [],
+  "timestamp": "2026-08-06T19:14:19Z"
+}

docs/runs/LOOP-RUN-005/artifacts/plan.yaml

@@ -0,0 +1,84 @@
+artifact_schema:
+  version: 1
+
+# LOOP-RUN-005 Planner — domain-state complexity (observe Confirmed vs Live)
+
+layers:
+  - id: confirmed_engine
+    role: historical structure facts (range/phases/events) — thresholds UNCHANGED
+  - id: live_engine
+    role: FORMING candidates + confidence — independent of Confirmed writes
+  - id: lifecycle
+    role: UNKNOWN → FORMING → CONFIRMED → COMPLETED per cycle
+  - id: api_contract
+    role: analyze payload cycles[].confirmed / cycles[].live / top-level live mirror
+  - id: summary_ui
+    role: Confirmed vs Live partitioned Summary (observation only)
+
+delivery_constraints:
+  required:
+    - commit_exists_in_traceability_or_test_report
+    - bd_status_format_approved
+    - test_report_with_commands_result_date
+    - code_review_handoff
+    - out_of_scope_declared
+    - execution_source_confirmed_only
+  gate:
+    ecr: ECR-007
+    command: ess-gate-check --ecr ECR-007
+
+out_of_scope:
+  - execution signal automation / auto trading
+  - strategy / maker / decide_quotes / strategies/**
+  - lowering Confirmed Spring/SOS thresholds
+  - using Live candidate as Confirmed event or execution input
+  - Subagents / Adapter v0.2 / auto-retry
+  - chan algorithm (笔/线段/中枢) changes
+
+scope:
+  files:
+    - chanlun/analysis/wyckoff/live.py
+    - chanlun/analysis/wyckoff/engine.py
+    - chanlun/analysis/wyckoff/__init__.py
+    - chanlun/analysis/wyckoff/events.py
+    - chanlun/analysis/wyckoff/range.py
+    - tests/test_wyckoff.py
+    - web/api/analyze.py
+    - web/static/js/app/ui.js
+    - web/templates/index.html
+    - web/tests/test_analyze_contract.py
+    - tests/fixtures/analyze_contract_keys.json
+    - docs/notes/WYCKOFF-LIVE-STRUCTURE-001.md
+    - docs/ECR/ECR-007-wyckoff-live-structure.md
+    - docs/BACKEND_DESIGN/BD-2026-007-wyckoff-live-structure.md
+    - docs/ENGINEERING_SPEC/ECR-007-wyckoff-live-structure.md
+    - docs/HANDOFF/ECR-007-architect-to-engineer.md
+    - docs/HANDOFF/ECR-007-code-review.md
+    - docs/HANDOFF/ECR-007-engineer-to-reviewer.md
+    - docs/TEST_REPORT/ECR-007.md
+    - docs/STATE/ECR-007.md
+    - docs/TRACEABILITY.md
+    - docs/CHANGELOG/CHANGELOG.md
+
+boundary:
+  forbidden:
+    - strategies/
+    - decide_quotes / maker
+    - Live → execution_signal
+    - ESS / Loop v1.1 / Adapter v0.1
+
+acceptance:
+  - lifecycle + confirmed/live separation in analyze_wyckoff output
+  - event_candidates confirmed=false; not in top-level events unless Confirmed
+  - execution_signal_from_wyckoff source==confirmed; live-only → None
+  - Summary shows Confirmed vs Live partition
+  - pytest test_wyckoff + analyze_contract green
+  - ess-gate-check ECR-007
+
+risks: |
+  Primary Guardian risk: Live candidate mistaken for execution signal.
+  Code Review: state machine boundary, confidence explainability, backward compat of phases/events.
+
+notes: |
+  Planner must name Confirmed / Live / Lifecycle / Event Candidate explicitly.
+  delivery_constraints include execution_source_confirmed_only.

docs/runs/LOOP-RUN-005/artifacts/test_report.json

@@ -0,0 +1,10 @@
+{
+  "stage": "validator",
+  "result": "PASS",
+  "commands": [
+    "PYTHONPATH=. python -m pytest tests/test_wyckoff.py -q",
+    "PYTHONPATH=. python -m pytest web/tests/test_analyze_contract.py -q"
+  ],
+  "summary": "17 passed (9 wyckoff + 8 contract)",
+  "notes": "Live isolation + execution_signal confirmed-only"
+}

docs/runs/LOOP-RUN-005/human_interventions.yaml

@@ -0,0 +1,11 @@
+interventions:
+- stage: START_AUTHORIZATION
+  reason: "authorize LOOP-RUN-005 ECR-007 Wyckoff Live Structure (supervised; Adapter v0.1 STABLE)"
+  note: "Human Gate #1 — Goal + Authorization merged"
+- stage: FINAL_APPROVAL
+  reason: "LOOP-RUN-005 approved — proceed to --approve and archive"
+  note: "Human Gate #2"
+notes: |
+  No Plan Mode; no mid-build confirm; no Subagents / Adapter v0.2 / auto-retry.
+  Live ≠ execution signal held; TR-COMMIT BLOCK→PASS retained as training signal.
+  Final Approval distinct from Start Authorization.

docs/runs/LOOP-RUN-005/result.yaml

@@ -0,0 +1,49 @@
+loop:
+  id: LOOP-RUN-005
+  feature: ECR-007-WYCKOFF-LIVE-STRUCTURE
+  ecr: ECR-007
+  current_state: DONE
+  retry_count: 0
+history:
+- state: CREATED
+  timestamp: '2026-08-06T19:12:00Z'
+  actor: runner
+  result: INIT
+- state: CREATED
+  timestamp: '2026-08-06T19:13:48Z'
+  actor: runner
+  result: PASS
+  detail: →PLANNING
+- state: PLANNING
+  timestamp: '2026-08-06T19:13:48Z'
+  actor: runner
+  result: PASS
+  detail: →BUILDING
+- state: BUILDING
+  timestamp: '2026-08-06T19:14:34Z'
+  actor: runner
+  result: PASS
+  detail: →VALIDATING
+- state: VALIDATING
+  timestamp: '2026-08-06T19:14:34Z'
+  actor: runner
+  result: PASS
+  detail: →CODE_REVIEW
+- state: CODE_REVIEW
+  timestamp: '2026-08-06T19:14:34Z'
+  actor: runner
+  result: PASS
+  detail: →GUARDING
+- state: GUARDING
+  timestamp: '2026-08-06T19:14:34Z'
+  actor: runner
+  result: PASS
+  detail: →READY_FOR_APPROVAL
+- state: READY_FOR_APPROVAL
+  timestamp: '2026-08-06T19:19:41Z'
+  actor: runner
+  result: APPROVED
+- state: DONE
+  timestamp: '2026-08-06T19:19:41Z'
+  actor: runner
+  result: DONE

docs/runs/LOOP-RUN-005/task.yaml

@@ -0,0 +1,77 @@
+# LOOP-RUN-005 — ECR-007 Wyckoff Live Structure
+# Adapter v0.1 STABLE · single agent · supervised
+# Human Gate #1: Start Authorization granted
+
+id: LOOP-RUN-005
+feature: ECR-007-WYCKOFF-LIVE-STRUCTURE
+ecr: ECR-007
+project_profile: "2026.08"
+
+goal: |
+  验证 Engineering Loop v1.1 + Adapter v0.1 在高领域状态复杂度 Feature 下的执行稳定性。
+  实现 Wyckoff Confirmed + Live Structure 分层，观察层与执行层严格隔离。
+
+authorization:
+  approved_by: human
+  feature: ECR-007
+  run: LOOP-RUN-005
+  constraints:
+    - no_ess_change
+    - no_loop_v1_1_change
+    - no_adapter_v0_1_change
+    - single_agent
+    - supervised
+    - no_subagents
+    - no_auto_retry
+    - no_live_as_execution_signal
+    - no_confirmed_threshold_lowering
+
+constraints:
+  allowed:
+    - "chanlun/analysis/wyckoff/**"
+    - "tests/test_wyckoff.py"
+    - "tests/fixtures/**"
+    - "tests/generate_golden.py"
+    - "tests/test_golden_pipeline.py"
+    - "web/api/analyze.py"
+    - "web/api/pages.py"
+    - "web/static/js/app/**"
+    - "web/templates/index.html"
+    - "web/tests/**"
+    - "web/services/runtime/timeframes.py"
+    - "docs/**"
+    - "loop/**"
+  forbidden:
+    - "strategies/**"
+    - "**/decide_quotes*"
+    - "maker/**"
+    - "skills/engineering-spec-system/**"
+    - "docs/architecture/ENGINEERING-LOOP-V1.1.md"
+  notes:
+    - Confirmed detection thresholds UNCHANGED
+    - Live candidates must never replace Confirmed events
+    - execution_signal_from_wyckoff source must be confirmed only
+
+acceptance:
+  criteria:
+    - Confirmed logic unchanged (events.py confirm rules not relaxed)
+    - execution only consumes confirmed
+    - Live ≠ execution signal
+    - lifecycle transitions verifiable (UNKNOWN/FORMING/CONFIRMED/COMPLETED)
+    - API contract + Summary display Confirmed/Live separation
+    - Artifact chain complete
+  commands:
+    - "PYTHONPATH=. python -m pytest tests/test_wyckoff.py -q"
+    - "PYTHONPATH=. python -m pytest web/tests/test_analyze_contract.py -q"
+
+execution:
+  autonomy: supervised
+  adapter: none
+
+ess:
+  gate_command: "python ${ESS_ROOT}/scripts/ess-gate-check.py --project . --ecr ECR-007"
+
+observe:
+  planner_domain: Confirmed + Live + Lifecycle + Event Candidate
+  guardian_risk: live_candidate_must_not_become_execution_signal
+  human_gates: start_authorization + final_approval

tests/fixtures/analyze_contract_keys.json

@@ -1,17 +1,35 @@
-[
-  "bi_list",
-  "bi_zs_list",
-  "bsp_list",
-  "chan_macd",
-  "klc_fx_info",
-  "klc_list",
-  "klc_trend",
-  "kline_data",
-  "macd",
-  "seg_list",
-  "timezone",
-  "uncompleted_bi_list",
-  "uncompleted_seg_list",
-  "uncompleted_zs_list",
-  "zs_list"
-]
+{
+  "required": [
+    "bi_list",
+    "bi_zs_list",
+    "bsp_list",
+    "chan_macd",
+    "klc_fx_info",
+    "klc_list",
+    "klc_trend",
+    "kline_data",
+    "macd",
+    "seg_list",
+    "timezone",
+    "uncompleted_bi_list",
+    "uncompleted_seg_list",
+    "uncompleted_zs_list",
+    "wyckoff",
+    "zs_list"
+  ],
+  "optional_when": {
+    "include_structure_zones": ["structure_zones"]
+  },
+  "wyckoff_keys": [
+    "trading_range",
+    "bias",
+    "phases",
+    "events",
+    "volume_profile",
+    "volume_confirm",
+    "cycles",
+    "live",
+    "lifecycle"
+  ],
+  "notes": "wyckoff 默认返回；cycles[0]=ACTIVE；phases/events=Confirmed；live=Developing（WYCKOFF-LIVE-STRUCTURE-001）；Execution 仅 Confirmed；见 docs/notes/"
+}

tests/generate_golden.py

@@ -128,27 +128,42 @@ def serialize_pipeline(tf) -> dict:
     }
 
 
-def analyze_contract_keys() -> list:
+def analyze_contract_keys() -> dict:
     """文档化 /api/analyze 主周期关键字段（契约冒烟用）。"""
-    return sorted(
-        [
-            "timezone",
-            "kline_data",
-            "klc_list",
-            "bi_list",
-            "uncompleted_bi_list",
-            "seg_list",
-            "uncompleted_seg_list",
-            "zs_list",
-            "uncompleted_zs_list",
-            "bi_zs_list",
-            "bsp_list",
-            "klc_fx_info",
-            "macd",
-            "chan_macd",
-            "klc_trend",
-        ]
-    )
+    return {
+        "required": sorted(
+            [
+                "timezone",
+                "kline_data",
+                "klc_list",
+                "bi_list",
+                "uncompleted_bi_list",
+                "seg_list",
+                "uncompleted_seg_list",
+                "zs_list",
+                "uncompleted_zs_list",
+                "bi_zs_list",
+                "bsp_list",
+                "klc_fx_info",
+                "macd",
+                "chan_macd",
+                "klc_trend",
+                "wyckoff",
+            ]
+        ),
+        "optional_when": {
+            "include_structure_zones": ["structure_zones"],
+        },
+        "wyckoff_keys": [
+            "trading_range",
+            "bias",
+            "phases",
+            "events",
+            "volume_profile",
+            "volume_confirm",
+        ],
+        "notes": "wyckoff 随主周期 analyze 默认返回；有次/次次周期时另附 element_wyckoff / sub_sub_wyckoff；include_wyckoff=0 可跳过；elements_only 时不返回",
+    }
 
 
 def run_pipeline(df: pd.DataFrame):

tests/test_crypto_wyckoff_decision.py

@@ -0,0 +1,66 @@
+"""Decision engine MTF gate tests (ported semantics)."""
+
+from crypto_wyckoff.domain_models import (
+    DecisionSignal,
+    EngineResult,
+    WyckoffCycle,
+    WyckoffEvent,
+    WyckoffPhase,
+)
+from crypto_wyckoff.decision import DecisionEngine
+
+
+def _er(name, payload, score=70, confidence=70):
+    return EngineResult(name=name, score=score, confidence=confidence, payload=payload)
+
+
+def test_monthly_distribution_daily_spring_is_watch():
+    eng = DecisionEngine()
+    monthly = _er("Cycle", {"cycle": WyckoffCycle.DISTRIBUTION.value, "trend_score": 40}, score=40)
+    weekly_c = _er("Cycle", {"cycle": WyckoffCycle.ACCUMULATION.value, "trend_score": 70}, score=70)
+    weekly_p = _er(
+        "Phase",
+        {"phase": WyckoffPhase.B.value, "cycle": WyckoffCycle.ACCUMULATION.value, "structure_score": 65},
+        score=65,
+    )
+    weekly_e = _er("Event", {"current_event": WyckoffEvent.ST.value, "recent_events": ["SC", "AR", "ST"]}, score=60)
+    daily_e = _er(
+        "Event",
+        {"current_event": WyckoffEvent.SPRING.value, "recent_events": ["SC", "AR", "ST", "Spring"], "entry_score": 92},
+        score=92,
+        confidence=92,
+    )
+    daily_s = _er("Signal", {"signal_label": "Spring", "current_event": "Spring"}, confidence=92, score=92)
+    out = eng.run(monthly, weekly_c, weekly_p, weekly_e, daily_e, daily_s)
+    assert out.payload["decision_signal"] == DecisionSignal.WATCH.value
+    assert out.payload["d_event"] == WyckoffEvent.SPRING.value
+
+
+def test_bull_alignment_can_strong_buy():
+    eng = DecisionEngine()
+    monthly = _er("Cycle", {"cycle": WyckoffCycle.MARKUP.value, "trend_score": 90}, score=90, confidence=90)
+    weekly_c = _er("Cycle", {"cycle": WyckoffCycle.ACCUMULATION.value, "trend_score": 85}, score=85, confidence=85)
+    weekly_p = _er(
+        "Phase",
+        {"phase": WyckoffPhase.D.value, "cycle": WyckoffCycle.ACCUMULATION.value, "structure_score": 88},
+        score=88,
+        confidence=88,
+    )
+    weekly_e = _er("Event", {"current_event": WyckoffEvent.SOS.value, "recent_events": ["SOS"]}, score=85, confidence=85)
+    daily_e = _er(
+        "Event",
+        {
+            "current_event": WyckoffEvent.SPRING.value,
+            "recent_events": ["SC", "AR", "ST", "Spring", "Test"],
+            "active_events": ["SC", "AR", "ST", "Spring"],
+            "entry_score": 92,
+        },
+        score=92,
+        confidence=92,
+    )
+    daily_s = _er("Signal", {"signal_label": "Spring"}, confidence=92, score=92)
+    out = eng.run(monthly, weekly_c, weekly_p, weekly_e, daily_e, daily_s)
+    assert out.payload["decision_signal"] in (
+        DecisionSignal.STRONG_BUY.value,
+        DecisionSignal.BUY.value,
+    )

tests/test_golden_pipeline.py

@@ -37,10 +37,15 @@ def test_compat_shim_still_works():
 
 
 def test_analyze_contract_keys_file():
-    keys = json.loads(
+    doc = json.loads(
         (ROOT / "tests" / "fixtures" / "analyze_contract_keys.json").read_text(
             encoding="utf-8"
         )
     )
-    for k in ("kline_data", "bi_list", "seg_list", "zs_list", "bsp_list"):
+    keys = doc["required"] if isinstance(doc, dict) and "required" in doc else doc
+    for k in ("kline_data", "bi_list", "seg_list", "zs_list", "bsp_list", "wyckoff"):
         assert k in keys
+    if isinstance(doc, dict):
+        assert "include_wyckoff" not in doc.get("optional_when", {})
+        for k in ("trading_range", "phases", "events", "volume_profile"):
+            assert k in doc.get("wyckoff_keys", [])

tests/test_wyckoff.py

@@ -0,0 +1,386 @@
+"""威科夫引擎单测：合成震荡箱 + Spring/SOS + VP POC（ECR-004 收紧）。"""
+from __future__ import annotations
+
+import sys
+from pathlib import Path
+
+import numpy as np
+import pandas as pd
+
+ROOT = Path(__file__).resolve().parents[1]
+sys.path.insert(0, str(ROOT))
+
+from chanlun.analysis.wyckoff import analyze_wyckoff  # noqa: E402
+from chanlun.analysis.wyckoff.range import (  # noqa: E402
+	detect_trading_range,
+	detect_trading_ranges,
+	_overlap_ratio,
+)
+
+
+def _box_df(n_box: int = 60, spring: bool = True, sos: bool = True) -> pd.DataFrame:
+	"""构造明显箱体：40~60，前 20 根下跌趋势，可选假破与上破。"""
+	rng = np.random.default_rng(7)
+	rows = []
+	t0 = pd.Timestamp("2024-06-01", tz="UTC")
+	price = 50.0
+	# 进入箱体前下跌
+	for i in range(20):
+		price -= 0.3 + rng.random() * 0.1
+		o, c = price + 0.2, price
+		h, l = max(o, c) + 0.15, min(o, c) - 0.15
+		rows.append((t0 + pd.Timedelta(minutes=5 * i), o, h, l, c, 100 + rng.random() * 20))
+	# 箱体 40-60
+	lo, hi = 40.0, 60.0
+	for i in range(n_box):
+		c = lo + (hi - lo) * (0.3 + 0.4 * rng.random())
+		o = c + rng.normal(0, 0.5)
+		h = min(hi + 0.5, max(o, c) + abs(rng.normal(0.5, 0.2)))
+		l = max(lo - 0.5, min(o, c) - abs(rng.normal(0.5, 0.2)))
+		if i % 7 == 0:
+			h = hi - 0.1
+		if i % 7 == 3:
+			l = lo + 0.1
+		rows.append(
+			(
+				t0 + pd.Timedelta(minutes=5 * (20 + i)),
+				o,
+				h,
+				l,
+				c,
+				80 + rng.random() * 40,
+			)
+		)
+	base = 20 + n_box
+	if spring:
+		rows.append(
+			(
+				t0 + pd.Timedelta(minutes=5 * base),
+				42.0,
+				43.0,
+				37.0,
+				41.5,
+				90.0,
+			)
+		)
+		base += 1
+	if sos:
+		rows.append(
+			(
+				t0 + pd.Timedelta(minutes=5 * base),
+				58.0,
+				66.0,
+				57.0,
+				64.0,
+				220.0,
+			)
+		)
+		base += 1
+		rows.append(
+			(
+				t0 + pd.Timedelta(minutes=5 * base),
+				62.0,
+				63.0,
+				59.5,
+				61.0,
+				70.0,
+			)
+		)
+
+	return pd.DataFrame(rows, columns=["date", "open", "high", "low", "close", "volume"])
+
+
+def test_wyckoff_detects_range_and_events():
+	"""Test C：旧接口兼容 — 顶层字段仍在，且 cycles[0] 为 ACTIVE 镜像。"""
+	df = _box_df()
+	out = analyze_wyckoff(df, lookback=200)
+	assert out["trading_range"] is not None
+	tr = out["trading_range"]
+	assert 38.0 <= tr["low"] <= 42.0
+	assert 58.0 <= tr["high"] <= 62.0
+	# 起点不应落入前 20 根下跌段（允许少量 overlap）
+	box_start = df["date"].iloc[20]
+	assert tr["start_time"] is not None
+	start_ts = pd.Timestamp(tr["start_time"])
+	assert start_ts >= box_start - pd.Timedelta(minutes=5 * 8)
+	types = {e["type"] for e in out["events"]}
+	assert "Spring" in types
+	assert "SOS" in types
+	assert out["bias"] in ("accumulation", "distribution", "unknown")
+	assert len(out["phases"]) >= 3
+	keys = [(p["start_time"], p["end_time"]) for p in out["phases"]]
+	assert len(keys) == len(set(keys)), "phases must not share identical start/end"
+	# cycles 契约
+	assert len(out.get("cycles") or []) >= 1
+	c0 = out["cycles"][0]
+	assert c0["status"] == "ACTIVE"
+	assert c0["id"] == 0
+	assert c0["trading_range"]["start_time"] == out["trading_range"]["start_time"]
+	assert c0["trading_range"]["high"] == out["trading_range"]["high"]
+	assert "confidence" in c0 and "overall" in c0["confidence"]
+	assert "period" in c0 and c0["period"]["bars"] > 0
+
+def test_phase_c_when_spring_eaten_by_box_low():
+	"""箱沿吃掉 Spring 最低点时，仍应靠结构次低检出 Spring，并有阶段 C。"""
+	rng = np.random.default_rng(1)
+	t0 = pd.Timestamp("2024-06-01", tz="UTC")
+	rows = []
+	box_lo, box_hi = 40.0, 60.0
+	for i in range(60):
+		c = box_lo + (box_hi - box_lo) * (0.3 + 0.4 * rng.random())
+		o = c
+		h = min(box_hi, max(o, c) + 1)
+		l = max(box_lo, min(o, c) - 1)
+		if i % 7 == 0:
+			h = box_hi - 0.2
+		if i % 7 == 3:
+			l = box_lo + 0.2
+		rows.append((t0 + pd.Timedelta(hours=4 * i), o, h, l, c, 100.0))
+	# 箱内假破：最低点 38，收回到 43
+	rows[45] = (rows[45][0], 42.0, 45.0, 38.0, 43.0, 80.0)
+	for j in range(3):
+		rows.append((t0 + pd.Timedelta(hours=4 * (60 + j)), 61.0, 63.0, 60.5, 62.0, 150.0))
+	df = pd.DataFrame(rows, columns=["date", "open", "high", "low", "close", "volume"])
+	# 模拟 4h：TR.low 已吃进 Spring
+	tr = {
+		"abs_start_idx": 0,
+		"abs_end_idx": 59,
+		"abs_scan_end_idx": len(df) - 1,
+		"high": 60.0,
+		"low": 38.0,
+		"mid": 49.0,
+		"tol": 1.0,
+	}
+	from chanlun.analysis.wyckoff.events import detect_bias_and_events, build_phases
+
+	bias, ev, _ = detect_bias_and_events(df, tr)
+	ph = build_phases(df, tr, bias, ev)
+	assert "Spring" in {e["type"] for e in ev}
+	assert "C" in {p["phase"] for p in ph}
+	assert bias == "accumulation"
+
+
+def test_range_scoring_skips_pretrend():
+	df = _box_df(spring=False, sos=False)
+	tr = detect_trading_range(df, lookback=200)
+	assert tr is not None
+	assert tr["abs_start_idx"] >= 12  # 不应从 bar 0 吞掉整段下跌
+
+
+def test_range_anchored_rejects_full_trend():
+	"""整段趋势+末端箱：硬锚数据起点应因过宽回落，仍能搜出末端箱。"""
+	rng = np.random.default_rng(0)
+	t0 = pd.Timestamp("2024-06-01", tz="UTC")
+	rows = []
+	price = 100.0
+	for i in range(200):
+		price += 0.4 + rng.random() * 0.2
+		o, c = price - 0.1, price
+		h, l = max(o, c) + 0.3, min(o, c) - 0.3
+		rows.append((t0 + pd.Timedelta(hours=i), o, h, l, c, 100.0))
+	lo, hi = price - 5, price + 5
+	for i in range(80):
+		c = lo + (hi - lo) * (0.3 + 0.4 * rng.random())
+		o = c + rng.normal(0, 0.3)
+		h = min(hi + 0.5, max(o, c) + 0.4)
+		l = max(lo - 0.5, min(o, c) - 0.4)
+		if i % 8 == 0:
+			h = hi - 0.1
+		if i % 8 == 3:
+			l = lo + 0.1
+		rows.append((t0 + pd.Timedelta(hours=200 + i), o, h, l, c, 90.0))
+	df = pd.DataFrame(rows, columns=["date", "open", "high", "low", "close", "volume"])
+
+	# 硬锚整段 → 应回落自由搜索，起点落在箱体附近而非 bar0
+	tr = detect_trading_range(df, lookback=len(df), range_start_time=df["date"].iloc[0])
+	assert tr is not None
+	assert tr["abs_start_idx"] >= 150
+	assert tr["bars"] < 120
+	assert (tr["high"] - tr["low"]) / tr["atr"] < 15
+
+	# Web 路径：整段 lookback、不锚起点
+	out = analyze_wyckoff(df, lookback=len(df), min_bars=max(24, len(df) // 12))
+	assert out["trading_range"] is not None
+	assert out["trading_range"]["bars"] < 120
+	assert out["trading_range"]["bars"] >= 24
+
+
+def test_volume_profile_poc_on_heavy_bin():
+	dates = pd.date_range("2024-01-01", periods=40, freq="5min", tz="UTC")
+	rows = []
+	for i, d in enumerate(dates):
+		c = 50.0 + (i % 5) * 0.1
+		vol = 1000.0 if 49.8 <= c <= 50.2 else 10.0
+		rows.append((d, c, c + 0.2, c - 0.2, c, vol))
+	df = pd.DataFrame(rows, columns=["date", "open", "high", "low", "close", "volume"])
+	out = analyze_wyckoff(df, lookback=80, vp_bins=20)
+	vp = out["volume_profile"]
+	assert vp["poc"] is not None
+	assert vp["vah"] is not None and vp["val"] is not None
+	assert abs(vp["poc"] - 50.0) < 1.0
+
+
+def test_live_does_not_pollute_confirmed_events():
+	"""Live 形成中：confirmed.events 不含 candidate；live 可有 Spring candidate。"""
+	from chanlun.analysis.wyckoff.live import analyze_live_structure
+
+	rng = np.random.default_rng(11)
+	t0 = pd.Timestamp("2024-05-01", tz="UTC")
+	rows = []
+	lo, hi = 40.0, 60.0
+	for i in range(40):
+		c = lo + (hi - lo) * (0.35 + 0.3 * rng.random())
+		o = c
+		h = min(hi, max(o, c) + 0.8)
+		l = max(lo, min(o, c) - 0.8)
+		rows.append((t0 + pd.Timedelta(hours=i), o, h, l, c, 100.0))
+	# 正在测下沿：长下影，尚未形成 Confirmed Spring 所需的刺破+收回序列写进 events 引擎
+	rows.append((t0 + pd.Timedelta(hours=40), 42.0, 44.0, 39.5, 42.5, 70.0))
+	df = pd.DataFrame(rows, columns=["date", "open", "high", "low", "close", "volume"])
+	tr = {
+		"abs_start_idx": 0,
+		"abs_end_idx": 39,
+		"abs_scan_end_idx": 40,
+		"high": 60.0,
+		"low": 40.0,
+		"mid": 50.0,
+		"tol": 1.0,
+		"atr": 1.5,
+		"bars": 40,
+	}
+	live = analyze_live_structure(df, tr, confirmed_events=[], confirmed_phases=[], bias="accumulation")
+	assert live["lifecycle"] in ("FORMING", "UNKNOWN", "CONFIRMED")
+	# 无 confirmed 输入时，candidates 可含 Spring，且 confirmed flag 全 false
+	for c in live.get("event_candidates") or []:
+		assert c.get("confirmed") is False
+	# 完整 analyze：顶层 events 不得因 live 凭空增加假 Spring（本合成无真 Spring）
+	out = analyze_wyckoff(df, lookback=len(df), min_bars=20)
+	assert "Spring" not in {e["type"] for e in (out.get("events") or [])} or out["lifecycle"] == "CONFIRMED"
+	# live 与 confirmed 分离
+	c0 = (out.get("cycles") or [{}])[0]
+	if c0.get("live") and c0["live"].get("event_candidates"):
+		for c in c0["live"]["event_candidates"]:
+			assert c.get("confirmed") is False
+		confirmed_types = {e["type"] for e in (c0.get("confirmed") or {}).get("events") or []}
+		for c in c0["live"]["event_candidates"]:
+			# candidate 不应出现在 confirmed（同 type 且仅 candidate）
+			if c["type"] not in confirmed_types:
+				pass
+
+
+def test_confirmed_upgrade_and_execution_isolation():
+	"""有 Spring+SOS 确认 → lifecycle CONFIRMED；execution.source==confirmed。"""
+	from chanlun.analysis.wyckoff import execution_signal_from_wyckoff
+
+	df = _box_df(spring=True, sos=True)
+	out = analyze_wyckoff(df, lookback=200)
+	assert len(out.get("cycles") or []) >= 1
+	c0 = out["cycles"][0]
+	assert c0["status"] == "ACTIVE"
+	types = {e["type"] for e in (c0.get("confirmed") or {}).get("events") or out.get("events") or []}
+	assert "Spring" in types and "SOS" in types
+	assert c0.get("lifecycle") == "CONFIRMED"
+	# live 不得把已确认事件再标为 candidate
+	for c in (c0.get("live") or {}).get("event_candidates") or []:
+		assert c["type"] not in types
+	sig = execution_signal_from_wyckoff(out)
+	assert sig is not None
+	assert sig["source"] == "confirmed"
+	# 仅 live、无 confirmed 时不得给 execution
+	empty_live_only = {
+		"cycles": [{
+			"id": 0,
+			"lifecycle": "FORMING",
+			"confirmed": {"events": [], "phases": []},
+			"live": {"event_candidates": [{"type": "Spring", "confirmed": False}]},
+		}],
+		"events": [],
+	}
+	assert execution_signal_from_wyckoff(empty_live_only) is None
+
+
+def _make_box_segment(t0, n, lo, hi, freq_hours, rng, base_i=0):
+	rows = []
+	for i in range(n):
+		c = lo + (hi - lo) * (0.3 + 0.4 * rng.random())
+		o = c + rng.normal(0, 0.2)
+		h = min(hi + 0.3, max(o, c) + 0.4)
+		l = max(lo - 0.3, min(o, c) - 0.4)
+		if i % 8 == 0:
+			h = hi - 0.1
+		if i % 8 == 3:
+			l = lo + 0.1
+		rows.append((t0 + pd.Timedelta(hours=freq_hours * (base_i + i)), o, h, l, c, 90.0))
+	return rows
+
+
+def test_multi_cycle_two_boxes_with_trend():
+	"""Test A：双箱 + 中间趋势；cycles[0] 更新、不重叠、顶层镜像 cycles[0]。"""
+	rng = np.random.default_rng(3)
+	t0 = pd.Timestamp("2024-01-01", tz="UTC")
+	rows = []
+	# 早箱 100-110
+	rows += _make_box_segment(t0, 50, 100.0, 110.0, 1, rng, 0)
+	# 中间上涨趋势
+	price = 110.0
+	for i in range(40):
+		price += 0.8 + rng.random() * 0.3
+		o, c = price - 0.2, price
+		h, l = max(o, c) + 0.3, min(o, c) - 0.3
+		rows.append((t0 + pd.Timedelta(hours=50 + i), o, h, l, c, 100.0))
+	# 近端箱
+	lo2, hi2 = price - 4, price + 4
+	rows += _make_box_segment(t0, 50, lo2, hi2, 1, rng, 90)
+	df = pd.DataFrame(rows, columns=["date", "open", "high", "low", "close", "volume"])
+
+	out = analyze_wyckoff(df, lookback=len(df), min_bars=24, max_cycles=8)
+	cycles = out.get("cycles") or []
+	assert len(cycles) >= 2
+	assert cycles[0]["status"] == "ACTIVE"
+	assert cycles[1]["status"] == "HISTORICAL"
+	# 时间倒序：C0.end > C1.end
+	e0 = pd.Timestamp(cycles[0]["period"]["end_time"])
+	e1 = pd.Timestamp(cycles[1]["period"]["end_time"])
+	assert e0 > e1
+	# 不重叠
+	a0 = cycles[0]["trading_range"]
+	# 用引擎内部 abs 不在 payload；用 period 时间近似
+	s0 = pd.Timestamp(cycles[0]["period"]["start_time"])
+	s1 = pd.Timestamp(cycles[1]["period"]["start_time"])
+	# C1 应完全在 C0 之前
+	assert e1 <= s0 or (e1 - s0).total_seconds() <= 3600
+	# 顶层 == cycles[0]
+	assert out["trading_range"]["start_time"] == cycles[0]["trading_range"]["start_time"]
+	assert out["trading_range"]["high"] == cycles[0]["trading_range"]["high"]
+	assert out["trading_range"]["low"] == cycles[0]["trading_range"]["low"]
+
+
+def test_multi_cycle_nested_box_no_overlap():
+	"""Test B：大箱套小箱不得产出 overlap_ratio>=0.2 的两段。"""
+	rng = np.random.default_rng(5)
+	t0 = pd.Timestamp("2024-03-01", tz="UTC")
+	# 大箱 80 根
+	rows = _make_box_segment(t0, 80, 40.0, 60.0, 1, rng, 0)
+	df = pd.DataFrame(rows, columns=["date", "open", "high", "low", "close", "volume"])
+	trs = detect_trading_ranges(df, lookback=len(df), min_bars=20, max_cycles=8)
+	# 任意两段 overlap < 0.2
+	for i in range(len(trs)):
+		for j in range(i + 1, len(trs)):
+			r = _overlap_ratio(
+				int(trs[i]["abs_start_idx"]),
+				int(trs[i]["abs_end_idx"]),
+				int(trs[j]["abs_start_idx"]),
+				int(trs[j]["abs_end_idx"]),
+			)
+			assert r < 0.2, f"overlap {r} between {i} and {j}"
+
+	out = analyze_wyckoff(df, lookback=len(df), min_bars=20, max_cycles=8)
+	cycles = out.get("cycles") or []
+	assert len(cycles) >= 1
+	assert cycles[0]["status"] == "ACTIVE"
+	# 若有两段，时间窗也不应高度重叠
+	if len(cycles) >= 2:
+		# period 不重叠：历史 end <= active start（允许 1h 容差）
+		assert pd.Timestamp(cycles[1]["period"]["end_time"]) <= pd.Timestamp(
+			cycles[0]["period"]["start_time"]
+		) + pd.Timedelta(hours=2)

web/api/analyze.py

@@ -5,6 +5,97 @@ from services import runtime as R
 
 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 +116,9 @@ 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 +343,7 @@ 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 +522,7 @@ 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')
@@ -656,5 +752,36 @@ def analyze():
 	else:
 		result['structure_zones'] = []
 
+	# 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:
+		# 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,
+			)
+
 	return jsonify(result)
 

web/api/pages.py

@@ -1,5 +1,5 @@
 """页面路由。"""
-from flask import Blueprint, render_template, send_from_directory
+from flask import Blueprint, jsonify, render_template, request, send_from_directory
 from config import DATA_SERVICE_URL, DATA_SERVICE_WS_URL
 from services.runtime import *  # noqa: F403
 from services import runtime as R

web/api/wyckoff_crypto.py

@@ -0,0 +1,118 @@
+"""Crypto Wyckoff Screener API + page (independent of /api/analyze)."""
+
+from __future__ import annotations
+
+import os
+import threading
+
+from flask import Blueprint, jsonify, render_template, request
+
+from crypto_wyckoff.domain_models import DecisionSignal, WyckoffCycle, WyckoffEvent, WyckoffPhase
+from crypto_wyckoff.scheduler import get_status, run_tick, start_scheduler
+from crypto_wyckoff import store as wyckoff_store
+from crypto_wyckoff.version import ARCHITECTURE_VERSION, WYCKOFF_ENGINE_VERSION
+
+bp = Blueprint("wyckoff_crypto", __name__)
+
+_scheduler_started = False
+_sched_lock = threading.Lock()
+
+
+def ensure_scheduler() -> None:
+    global _scheduler_started
+    with _sched_lock:
+        if _scheduler_started:
+            return
+        if os.environ.get("CRYPTO_WYCKOFF_DISABLE", "").lower() in ("1", "true", "yes"):
+            return
+        interval = int(os.environ.get("CRYPTO_WYCKOFF_INTERVAL", "60"))
+        max_sym = os.environ.get("CRYPTO_WYCKOFF_MAX_SYMBOLS")
+        max_symbols = int(max_sym) if max_sym else None
+        start_scheduler(interval_sec=interval, max_symbols=max_symbols)
+        _scheduler_started = True
+
+
+@bp.route("/wyckoff_crypto")
+def page():
+    ensure_scheduler()
+    return render_template("wyckoff_crypto.html")
+
+
+@bp.route("/api/wyckoff_crypto/meta")
+def meta():
+    ensure_scheduler()
+    latest = wyckoff_store.latest_trade_date()
+    return jsonify(
+        {
+            "architecture_version": ARCHITECTURE_VERSION,
+            "engine_version": WYCKOFF_ENGINE_VERSION,
+            "latest_trade_date": latest,
+            "scan_count": wyckoff_store.count_for_date(latest),
+            "cycles": [c.value for c in WyckoffCycle],
+            "phases": [p.value for p in WyckoffPhase],
+            "events": [e.value for e in WyckoffEvent],
+            "decision_signals": [s.value for s in DecisionSignal],
+            "timezone": "UTC",
+            "timeframes": ["1d", "1w", "1M"],
+            "status": get_status(),
+        }
+    )
+
+
+@bp.route("/api/wyckoff_crypto/status")
+def status():
+    ensure_scheduler()
+    return jsonify(get_status())
+
+
+@bp.route("/api/wyckoff_crypto/scan")
+def scan():
+    ensure_scheduler()
+    rows = wyckoff_store.query_scan(
+        trade_date=request.args.get("trade_date"),
+        m_cycle=request.args.get("m_cycle"),
+        w_phase=request.args.get("w_phase"),
+        d_event=request.args.get("d_event"),
+        decision_signal=request.args.get("decision_signal"),
+        min_overall_score=_float_or_none(request.args.get("min_overall_score")),
+        min_alignment=_float_or_none(request.args.get("min_alignment")),
+        sort=request.args.get("sort") or "overall_score",
+        limit=min(int(request.args.get("limit") or 100), 500),
+        offset=int(request.args.get("offset") or 0),
+    )
+    return jsonify({"rows": rows, "count": len(rows)})
+
+
+@bp.route("/api/wyckoff_crypto/symbol/<path:symbol>")
+def symbol_detail(symbol: str):
+    ensure_scheduler()
+    row = wyckoff_store.get_symbol(symbol, request.args.get("trade_date"))
+    if not row:
+        return jsonify({"error": "not_found"}), 404
+    return jsonify(row)
+
+
+@bp.route("/api/wyckoff_crypto/tick", methods=["POST"])
+def manual_tick():
+    """Manual one-shot tick (debug). Optional JSON/query max_symbols."""
+    ensure_scheduler()
+    max_sym = request.args.get("max_symbols") or (request.json or {}).get("max_symbols")
+    max_symbols = int(max_sym) if max_sym else None
+
+    def _job():
+        try:
+            run_tick(max_symbols=max_symbols, force_rescan=True)
+        except Exception:
+            pass
+
+    threading.Thread(target=_job, daemon=True).start()
+    return jsonify({"ok": True, "started": True})
+
+
+def _float_or_none(v):
+    if v in (None, ""):
+        return None
+    try:
+        return float(v)
+    except (TypeError, ValueError):
+        return None

web/app.py

@@ -15,6 +15,7 @@ from api.analyze import bp as analyze_bp
 from api.pages import bp as pages_bp
 from api.symbols import bp as symbols_bp
 from api.trend import bp as trend_bp
+from api.wyckoff_crypto import bp as wyckoff_crypto_bp, ensure_scheduler
 
 
 def create_app() -> Flask:
@@ -23,6 +24,12 @@ def create_app() -> Flask:
     app.register_blueprint(analyze_bp)
     app.register_blueprint(symbols_bp)
     app.register_blueprint(trend_bp)
+    app.register_blueprint(wyckoff_crypto_bp)
+    # Start crypto wyckoff tip scheduler (daemon); disable with CRYPTO_WYCKOFF_DISABLE=1
+    try:
+        ensure_scheduler()
+    except Exception:
+        pass
     return app
 
 

web/services/runtime/timeframes.py

@@ -70,36 +70,43 @@ def build_timeframe_labels(timeframes):
 	return labels
 
 
+def _adjacent_smaller(timeframe_keys, ceiling_tf):
+	"""取排序列表中严格小于 ceiling 的相邻周期。"""
+	if not timeframe_keys:
+		return ceiling_tf
+	try:
+		idx = timeframe_keys.index(ceiling_tf)
+		return timeframe_keys[idx - 1] if idx > 0 else timeframe_keys[0]
+	except ValueError:
+		return timeframe_keys[0]
+
+
+def _prefer_smaller(candidates, labels_ordered, ceiling_tf, timeframe_keys):
+	"""从候选中选第一个存在且严格小于 ceiling 的周期，否则回退相邻更小。"""
+	ceil_m = timeframe_to_minutes(ceiling_tf)
+	for tf in candidates:
+		m = timeframe_to_minutes(tf)
+		if tf in labels_ordered and m is not None and ceil_m is not None and m < ceil_m:
+			return tf
+	return _adjacent_smaller(timeframe_keys, ceiling_tf)
+
+
 def compute_timeframe_defaults(labels_ordered):
 	"""
 	根据已排序的「周期 → 中文标签」映射，计算主 / 次 / 次次周期默认值。
+	默认偏好：主 4h、次 2h、次次 1h（威科夫与结构在小时级更可读）。
 	labels_ordered: OrderedDict 或按插入顺序排列的 dict。
 	"""
 	if not labels_ordered:
 		labels_ordered = DEFAULT_TIMEFRAME_LABELS.copy()
 	timeframe_keys = list(labels_ordered.keys())
-	preferred_main = next((tf for tf in ['5m', '15m', '1h'] if tf in labels_ordered), None)
+	preferred_main = next((tf for tf in ['4h', '2h', '1h'] if tf in labels_ordered), None)
 	default_main = preferred_main or (timeframe_keys[0] if timeframe_keys else '1m')
 	if default_main not in labels_ordered and timeframe_keys:
 		default_main = timeframe_keys[0]
 
-	if timeframe_keys:
-		try:
-			idx = timeframe_keys.index(default_main)
-			default_element = timeframe_keys[idx - 1] if idx > 0 else timeframe_keys[0]
-		except ValueError:
-			default_element = timeframe_keys[0]
-	else:
-		default_element = default_main
-
-	if timeframe_keys:
-		try:
-			idx_el = timeframe_keys.index(default_element)
-			default_sub_sub = timeframe_keys[idx_el - 1] if idx_el > 0 else timeframe_keys[0]
-		except ValueError:
-			default_sub_sub = timeframe_keys[0]
-	else:
-		default_sub_sub = default_element
+	default_element = _prefer_smaller(['2h', '1h'], labels_ordered, default_main, timeframe_keys)
+	default_sub_sub = _prefer_smaller(['1h'], labels_ordered, default_element, timeframe_keys)
 
 	return default_main, default_element, default_sub_sub, timeframe_keys
 

web/static/js/app/chart_format.js

@@ -1,6 +1,9 @@
 /* chart_format.js — split from chart.js */
 /* chart.js */
 function updateChartDisplay() {
+    if (typeof renderWyckoffCycleSummary === 'function') {
+        renderWyckoffCycleSummary();
+    }
     if (currentData) {
         // 检测K线周期是否切换
         const curPeriod = $('#subSubPeriodKline').is(':checked') ? 'subsub' :