feat(web): 增量自动刷新、结构区修复与默认指标/周期
自动刷新常态只拉 recent 尾部 K，每 1 分钟全量重算缠论；修复结构区缓存导入；默认指标/4h·1h·15m/近30天；同步 ECR-009 screener 相关改动。 Co-authored-by: Cursor <cursoragent@cursor.com>
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jackyu66git
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"""Multi-timeframe combo presets for Crypto Wyckoff Screener.
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Roles (engine rule aliases stay D/W/M):
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high → Cycle (rules as 1M)
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mid → Phase (rules as 1w)
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low → Event (rules as 1d)
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Actual bar TFs come from the combo (e.g. 8h/4h/1h).
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"""
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from __future__ import annotations
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import json
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import re
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import threading
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from copy import deepcopy
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from pathlib import Path
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from typing import Any
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from crypto_wyckoff.io import DATA_DIR, ensure_dirs
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ROLE_LOW = "1d"
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ROLE_MID = "1w"
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ROLE_HIGH = "1M"
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# Minutes for ordering / validation (provider labels)
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_TF_MINUTES: dict[str, int] = {
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"1m": 1, "2m": 2, "3m": 3, "4m": 4, "5m": 5,
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"10m": 10, "15m": 15, "20m": 20, "25m": 25, "30m": 30, "45m": 45,
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"1h": 60, "2h": 120, "3h": 180, "4h": 240, "5h": 300,
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"6h": 360, "7h": 420, "8h": 480, "9h": 540, "10h": 600,
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"11h": 660, "12h": 720, "16h": 960, "20h": 1200,
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"1d": 1440, "2d": 2880, "3d": 4320, "4d": 5760, "5d": 7200, "6d": 8640,
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"1w": 10080, "2w": 20160, "3w": 30240,
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"1M": 43200,
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}
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# TFs we allow in custom combos (provider-backed + local 1M)
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ALLOWED_TFS: tuple[str, ...] = (
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"1h", "2h", "3h", "4h", "6h", "8h", "12h",
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"1d", "2d", "3d", "1w", "1M",
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)
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BUILTIN: list[dict[str, Any]] = [
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{
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"id": "h8_4_1",
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"label": "8h / 4h / 1h",
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"high": "8h",
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"mid": "4h",
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"low": "1h",
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"builtin": True,
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},
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{
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"id": "d_w_m",
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"label": "1d / 1w / 1M",
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"high": "1M",
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"mid": "1w",
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"low": "1d",
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"builtin": True,
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},
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]
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_COMBOS_FILE = DATA_DIR / "combos.json"
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_lock = threading.Lock()
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_cache: list[dict[str, Any]] | None = None
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def tf_minutes(tf: str) -> int | None:
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if tf in _TF_MINUTES:
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return _TF_MINUTES[tf]
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# tolerate provider typo "10" → skip
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m = re.fullmatch(r"(\d+)([mhdwM])", tf)
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if not m:
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return None
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n, u = int(m.group(1)), m.group(2)
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mult = {"m": 1, "h": 60, "d": 1440, "w": 10080, "M": 43200}[u]
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return n * mult
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def combo_id_for(high: str, mid: str, low: str) -> str:
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def _tok(t: str) -> str:
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return t.replace("/", "_")
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return f"{_tok(high)}_{_tok(mid)}_{_tok(low)}"
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def validate_combo(high: str, mid: str, low: str) -> str | None:
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"""Return error message or None if ok."""
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for tf in (high, mid, low):
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if tf not in ALLOWED_TFS:
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return f"不支持的周期: {tf}"
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if len({high, mid, low}) < 3:
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return "高/中/低周期必须互不相同"
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hm, mm, lm = tf_minutes(high), tf_minutes(mid), tf_minutes(low)
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if hm is None or mm is None or lm is None:
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return "无法解析周期长度"
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if not (hm > mm > lm):
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return "须满足 高 > 中 > 低（例如 8h > 4h > 1h）"
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return None
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def _normalize(row: dict[str, Any]) -> dict[str, Any] | None:
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high, mid, low = row.get("high"), row.get("mid"), row.get("low")
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if not high or not mid or not low:
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return None
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err = validate_combo(str(high), str(mid), str(low))
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if err:
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return None
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cid = str(row.get("id") or combo_id_for(high, mid, low))
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label = str(row.get("label") or f"{high} / {mid} / {low}")
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return {
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"id": cid,
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"label": label,
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"high": str(high),
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"mid": str(mid),
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"low": str(low),
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"builtin": bool(row.get("builtin", False)),
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}
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def _load_raw() -> list[dict[str, Any]]:
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ensure_dirs()
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if not _COMBOS_FILE.exists():
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return deepcopy(BUILTIN)
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try:
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data = json.loads(_COMBOS_FILE.read_text(encoding="utf-8"))
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items = data.get("combos") if isinstance(data, dict) else data
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if not isinstance(items, list):
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return deepcopy(BUILTIN)
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except (OSError, json.JSONDecodeError):
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return deepcopy(BUILTIN)
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out: list[dict[str, Any]] = []
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seen: set[str] = set()
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for b in BUILTIN:
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out.append(deepcopy(b))
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seen.add(b["id"])
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for row in items:
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if not isinstance(row, dict):
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continue
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norm = _normalize(row)
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if not norm or norm["id"] in seen:
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continue
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if norm["id"] in {b["id"] for b in BUILTIN}:
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continue
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norm["builtin"] = False
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out.append(norm)
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seen.add(norm["id"])
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return out
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def _save(combos: list[dict[str, Any]]) -> None:
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ensure_dirs()
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custom = [c for c in combos if not c.get("builtin")]
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payload = {"combos": custom}
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tmp = _COMBOS_FILE.with_suffix(".tmp")
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tmp.write_text(json.dumps(payload, ensure_ascii=False, indent=2), encoding="utf-8")
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tmp.replace(_COMBOS_FILE)
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def list_combos() -> list[dict[str, Any]]:
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global _cache
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with _lock:
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if _cache is None:
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_cache = _load_raw()
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return deepcopy(_cache)
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def get_combo(combo_id: str | None) -> dict[str, Any]:
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combos = list_combos()
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if combo_id:
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for c in combos:
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if c["id"] == combo_id:
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return deepcopy(c)
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return deepcopy(combos[0])
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def add_combo(high: str, mid: str, low: str, label: str | None = None) -> dict[str, Any]:
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err = validate_combo(high, mid, low)
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if err:
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raise ValueError(err)
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cid = combo_id_for(high, mid, low)
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row = {
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"id": cid,
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"label": label or f"{high} / {mid} / {low}",
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"high": high,
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"mid": mid,
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"low": low,
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"builtin": False,
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}
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with _lock:
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combos = _load_raw()
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for c in combos:
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if c["id"] == cid or (c["high"], c["mid"], c["low"]) == (high, mid, low):
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_cache = combos
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return deepcopy(c)
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combos.append(row)
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_save(combos)
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_cache = combos
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return deepcopy(row)
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def delete_combo(combo_id: str) -> bool:
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with _lock:
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combos = _load_raw()
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kept: list[dict[str, Any]] = []
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removed = False
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for c in combos:
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if c["id"] == combo_id:
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if c.get("builtin"):
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raise ValueError("内置组合不可删除")
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removed = True
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continue
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kept.append(c)
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if removed:
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_save(kept)
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_cache = kept
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return removed
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def all_tfs_for_combos(combos: list[dict[str, Any]] | None = None) -> list[str]:
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"""Unique TFs needed by active combos (stable order)."""
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rows = combos if combos is not None else list_combos()
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seen: list[str] = []
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for c in rows:
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for k in ("low", "mid", "high"):
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tf = c[k]
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if tf not in seen:
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seen.append(tf)
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return seen
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def lookback_for(tf: str) -> int:
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defaults = {
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"1h": 500,
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"2h": 400,
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"3h": 350,
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"4h": 300,
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"6h": 280,
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"8h": 250,
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"12h": 220,
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"1d": 250,
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"2d": 200,
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"3d": 180,
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"1w": 104,
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"1M": 60,
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}
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return defaults.get(tf, 200)
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