diff --git a/README.md b/README.md index 2e6985f..4ac5b68 100644 --- a/README.md +++ b/README.md @@ -56,7 +56,11 @@ The first extraction pass is already live: - `smart-executor` → `commands.smart_executor` + `services.smart_executor_service` - `precheck` → `commands.precheck` + `services.precheck_service` -- `precheck` internals now also have dedicated service modules for: +- root modules are compatibility facades only: + - `src/coinhunter/precheck.py` + - `src/coinhunter/smart_executor.py` +- `precheck` internals now live in dedicated service modules: + - `services.precheck_core` - `services.precheck_state` - `services.precheck_snapshot` - `services.precheck_analysis` @@ -65,7 +69,20 @@ This keeps behavior stable while giving the codebase a cleaner landing zone for ## Installation -Editable install: +Dedicated user-local install: + +```bash +./scripts/install_local.sh +``` + +This creates: + +- app environment: `~/.local/share/coinhunter-cli/venv` +- launcher: `~/.local/bin/coinhunter` + +The launcher behaves like a normal installed CLI and simply forwards into the dedicated virtualenv. + +Editable install for development: ```bash pip install -e . diff --git a/scripts/install_local.sh b/scripts/install_local.sh new file mode 100755 index 0000000..84de9dc --- /dev/null +++ b/scripts/install_local.sh @@ -0,0 +1,35 @@ +#!/usr/bin/env bash +set -euo pipefail + +APP_HOME="${COINHUNTER_APP_HOME:-$HOME/.local/share/coinhunter-cli}" +VENV_DIR="$APP_HOME/venv" +BIN_DIR="${COINHUNTER_BIN_DIR:-$HOME/.local/bin}" +LAUNCHER="$BIN_DIR/coinhunter" +PYTHON_BIN="${PYTHON:-}" + +if [[ -z "$PYTHON_BIN" ]]; then + if command -v python3 >/dev/null 2>&1; then + PYTHON_BIN="$(command -v python3)" + elif command -v python >/dev/null 2>&1; then + PYTHON_BIN="$(command -v python)" + else + echo "error: python3/python not found in PATH" >&2 + exit 1 + fi +fi + +mkdir -p "$APP_HOME" "$BIN_DIR" + +"$PYTHON_BIN" -m venv "$VENV_DIR" +"$VENV_DIR/bin/python" -m pip install --upgrade pip setuptools wheel +"$VENV_DIR/bin/python" -m pip install --upgrade "$(pwd)" + +cat >"$LAUNCHER" <= run_requested_at: - clear_run_request_fields(sanitized) - if pending_trigger and (not last_triggered_at or last_deep_analysis_at >= last_triggered_at): - sanitized["pending_trigger"] = False - sanitized["pending_reasons"] = [] - sanitized["last_ack_note"] = ( - f"auto-cleared completed trigger at {utc_iso()} because last_deep_analysis_at >= run_requested_at" - ) - pending_trigger = False - notes.append( - f"自动清理已完成的 run_requested 标记：最近深度分析时间 {last_deep_analysis_at.isoformat()} >= 请求时间 {run_requested_at.isoformat()}" - ) - run_requested_at = None - - if run_requested_at and now - run_requested_at > timedelta(minutes=MAX_RUN_REQUEST_MINUTES): - clear_run_request_fields(sanitized) - notes.append( - f"自动清理超时 run_requested 标记：已等待 {(now - run_requested_at).total_seconds() / 60:.1f} 分钟，超过 {MAX_RUN_REQUEST_MINUTES} 分钟" - ) - run_requested_at = None - - pending_anchor = run_requested_at or last_triggered_at or last_deep_analysis_at - if pending_trigger and pending_anchor and now - pending_anchor > timedelta(minutes=MAX_PENDING_TRIGGER_MINUTES): - sanitized["pending_trigger"] = False - sanitized["pending_reasons"] = [] - sanitized["last_ack_note"] = ( - f"auto-recovered stale pending trigger at {utc_iso()} after waiting " - f"{(now - pending_anchor).total_seconds() / 60:.1f} minutes" - ) - notes.append( - f"自动解除 pending_trigger：触发状态已悬挂 {(now - pending_anchor).total_seconds() / 60:.1f} 分钟，超过 {MAX_PENDING_TRIGGER_MINUTES} 分钟" - ) - - sanitized["_stale_recovery_notes"] = notes - return sanitized - - -def save_state(state: dict): - STATE_DIR.mkdir(parents=True, exist_ok=True) - state_to_save = dict(state) - state_to_save.pop("_stale_recovery_notes", None) - STATE_FILE.write_text(json.dumps(state_to_save, indent=2, ensure_ascii=False), encoding="utf-8") - - -def stable_hash(data) -> str: - payload = json.dumps(data, sort_keys=True, ensure_ascii=False, separators=(",", ":")) - return hashlib.sha1(payload.encode("utf-8")).hexdigest() - - -def get_exchange(): - load_env() - api_key = os.getenv("BINANCE_API_KEY") - secret = os.getenv("BINANCE_API_SECRET") - if not api_key or not secret: - raise RuntimeError("Missing BINANCE_API_KEY or BINANCE_API_SECRET in ~/.hermes/.env") - ex = ccxt.binance({ - "apiKey": api_key, - "secret": secret, - "options": {"defaultType": "spot"}, - "enableRateLimit": True, - }) - ex.load_markets() - return ex - - -def fetch_ohlcv_batch(ex, symbols: set, timeframe: str, limit: int): - results = {} - for sym in sorted(symbols): - try: - ohlcv = ex.fetch_ohlcv(sym, timeframe=timeframe, limit=limit) - if ohlcv and len(ohlcv) >= 2: - results[sym] = ohlcv - except Exception: - pass - return results - - -def compute_ohlcv_metrics(ohlcv_1h, ohlcv_4h, current_price, volume_24h=None): - metrics = {} - if ohlcv_1h and len(ohlcv_1h) >= 2: - closes = [c[4] for c in ohlcv_1h] - volumes = [c[5] for c in ohlcv_1h] - metrics["change_1h_pct"] = round((closes[-1] - closes[-2]) / closes[-2] * 100, 2) if closes[-2] != 0 else None - if len(closes) >= 5: - metrics["change_4h_pct"] = round((closes[-1] - closes[-5]) / closes[-5] * 100, 2) if closes[-5] != 0 else None - recent_vol = sum(volumes[-4:]) / 4 if len(volumes) >= 4 else None - metrics["volume_1h_avg"] = round(recent_vol, 2) if recent_vol else None - highs = [c[2] for c in ohlcv_1h[-4:]] - lows = [c[3] for c in ohlcv_1h[-4:]] - metrics["high_4h"] = round(max(highs), 8) if highs else None - metrics["low_4h"] = round(min(lows), 8) if lows else None - - if ohlcv_4h and len(ohlcv_4h) >= 2: - closes_4h = [c[4] for c in ohlcv_4h] - volumes_4h = [c[5] for c in ohlcv_4h] - metrics["change_4h_pct_from_4h"] = round((closes_4h[-1] - closes_4h[-2]) / closes_4h[-2] * 100, 2) if closes_4h[-2] != 0 else None - recent_vol_4h = sum(volumes_4h[-2:]) / 2 if len(volumes_4h) >= 2 else None - metrics["volume_4h_avg"] = round(recent_vol_4h, 2) if recent_vol_4h else None - highs_4h = [c[2] for c in ohlcv_4h] - lows_4h = [c[3] for c in ohlcv_4h] - metrics["high_24h_calc"] = round(max(highs_4h), 8) if highs_4h else None - metrics["low_24h_calc"] = round(min(lows_4h), 8) if lows_4h else None - if highs_4h and lows_4h: - avg_price = sum(closes_4h) / len(closes_4h) - metrics["volatility_4h_pct"] = round((max(highs_4h) - min(lows_4h)) / avg_price * 100, 2) - - if current_price: - if metrics.get("high_4h"): - metrics["distance_from_4h_high_pct"] = round((metrics["high_4h"] - current_price) / metrics["high_4h"] * 100, 2) - if metrics.get("low_4h"): - metrics["distance_from_4h_low_pct"] = round((current_price - metrics["low_4h"]) / metrics["low_4h"] * 100, 2) - if metrics.get("high_24h_calc"): - metrics["distance_from_24h_high_pct"] = round((metrics["high_24h_calc"] - current_price) / metrics["high_24h_calc"] * 100, 2) - if metrics.get("low_24h_calc"): - metrics["distance_from_24h_low_pct"] = round((current_price - metrics["low_24h_calc"]) / metrics["low_24h_calc"] * 100, 2) - - if volume_24h and volume_24h > 0 and metrics.get("volume_1h_avg"): - daily_avg_1h = volume_24h / 24 - metrics["volume_1h_multiple"] = round(metrics["volume_1h_avg"] / daily_avg_1h, 2) - if volume_24h and volume_24h > 0 and metrics.get("volume_4h_avg"): - daily_avg_4h = volume_24h / 6 - metrics["volume_4h_multiple"] = round(metrics["volume_4h_avg"] / daily_avg_4h, 2) - - return metrics - - -def enrich_candidates_and_positions(global_candidates, candidate_layers, positions_view, tickers, ex): - symbols = set() - for c in global_candidates: - symbols.add(c["symbol"]) - for p in positions_view: - sym = p.get("symbol") - if sym: - sym_ccxt = norm_symbol(sym) - symbols.add(sym_ccxt) - - ohlcv_1h = fetch_ohlcv_batch(ex, symbols, "1h", 24) - ohlcv_4h = fetch_ohlcv_batch(ex, symbols, "4h", 12) - - def _apply(target_list): - for item in target_list: - sym = item.get("symbol") - if not sym: - continue - sym_ccxt = norm_symbol(sym) - v24h = to_float(tickers.get(sym_ccxt, {}).get("quoteVolume")) - metrics = compute_ohlcv_metrics( - ohlcv_1h.get(sym_ccxt), - ohlcv_4h.get(sym_ccxt), - item.get("price") or item.get("last_price"), - volume_24h=v24h, - ) - item["metrics"] = metrics - - _apply(global_candidates) - for band_list in candidate_layers.values(): - _apply(band_list) - _apply(positions_view) - return global_candidates, candidate_layers, positions_view - - -def regime_from_pct(pct: float | None) -> str: - if pct is None: - return "unknown" - if pct >= 2.0: - return "bullish" - if pct <= -2.0: - return "bearish" - return "neutral" - - -def to_float(value, default=0.0): - try: - if value is None: - return default - return float(value) - except Exception: - return default - - -def norm_symbol(symbol: str) -> str: - s = symbol.upper().replace("-", "").replace("_", "") - if "/" in s: - return s - if s.endswith("USDT"): - return s[:-4] + "/USDT" - return s - - -def get_local_now(config: dict): - tz_name = config.get("timezone") or "Asia/Shanghai" - try: - tz = ZoneInfo(tz_name) - except Exception: - tz = ZoneInfo("Asia/Shanghai") - tz_name = "Asia/Shanghai" - return utc_now().astimezone(tz), tz_name - - -def session_label(local_dt: datetime) -> str: - hour = local_dt.hour - if 0 <= hour < 7: - return "overnight" - if 7 <= hour < 12: - return "asia-morning" - if 12 <= hour < 17: - return "asia-afternoon" - if 17 <= hour < 21: - return "europe-open" - return "us-session" - - -def _liquidity_score(volume: float) -> float: - return min(1.0, max(0.0, volume / 50_000_000)) - - -def _breakout_score(price: float, avg_price: float | None) -> float: - if not avg_price or avg_price <= 0: - return 0.0 - return (price - avg_price) / avg_price - - -def top_candidates_from_tickers(tickers: dict): - candidates = [] - for symbol, ticker in tickers.items(): - if not symbol.endswith("/USDT"): - continue - base = symbol.replace("/USDT", "") - if base in BLACKLIST: - continue - if not re.fullmatch(r"[A-Z0-9]{2,20}", base): - continue - price = to_float(ticker.get("last")) - change_pct = to_float(ticker.get("percentage")) - volume = to_float(ticker.get("quoteVolume")) - high = to_float(ticker.get("high")) - low = to_float(ticker.get("low")) - avg_price = to_float(ticker.get("average"), None) - if price <= 0: - continue - if MAX_PRICE_CAP is not None and price > MAX_PRICE_CAP: - continue - if volume < 500_000: - continue - if change_pct < MIN_CHANGE_PCT: - continue - momentum = change_pct / 10.0 - liquidity = _liquidity_score(volume) - breakout = _breakout_score(price, avg_price) - score = round(momentum * 0.5 + liquidity * 0.3 + breakout * 0.2, 4) - band = "major" if price >= 10 else "mid" if price >= 1 else "meme" - distance_from_high = (high - price) / max(high, 1e-9) if high else None - candidates.append({ - "symbol": symbol, - "base": base, - "price": round(price, 8), - "change_24h_pct": round(change_pct, 2), - "volume_24h": round(volume, 2), - "breakout_pct": round(breakout * 100, 2), - "high_24h": round(high, 8) if high else None, - "low_24h": round(low, 8) if low else None, - "distance_from_high_pct": round(distance_from_high * 100, 2) if distance_from_high is not None else None, - "score": score, - "band": band, - }) - candidates.sort(key=lambda x: x["score"], reverse=True) - global_top = candidates[:TOP_CANDIDATES] - layers = {"major": [], "mid": [], "meme": []} - for c in candidates: - layers[c["band"]].append(c) - for k in layers: - layers[k] = layers[k][:5] - return global_top, layers - - -def build_snapshot(): - config = load_config() - local_dt, tz_name = get_local_now(config) - ex = get_exchange() - positions = load_positions() - tickers = ex.fetch_tickers() - balances = ex.fetch_balance()["free"] - free_usdt = to_float(balances.get("USDT")) - - positions_view = [] - total_position_value = 0.0 - largest_position_value = 0.0 - actionable_positions = 0 - for pos in positions: - symbol = pos.get("symbol") or "" - sym_ccxt = norm_symbol(symbol) - ticker = tickers.get(sym_ccxt, {}) - last = to_float(ticker.get("last"), None) - qty = to_float(pos.get("quantity")) - avg_cost = to_float(pos.get("avg_cost"), None) - value = round(qty * last, 4) if last is not None else None - pnl_pct = round((last - avg_cost) / avg_cost, 4) if last is not None and avg_cost else None - high = to_float(ticker.get("high")) - low = to_float(ticker.get("low")) - distance_from_high = (high - last) / max(high, 1e-9) if high and last else None - if value is not None: - total_position_value += value - largest_position_value = max(largest_position_value, value) - if value >= MIN_REAL_POSITION_VALUE_USDT: - actionable_positions += 1 - positions_view.append({ - "symbol": symbol, - "base_asset": pos.get("base_asset"), - "quantity": qty, - "avg_cost": avg_cost, - "last_price": last, - "market_value_usdt": value, - "pnl_pct": pnl_pct, - "high_24h": round(high, 8) if high else None, - "low_24h": round(low, 8) if low else None, - "distance_from_high_pct": round(distance_from_high * 100, 2) if distance_from_high is not None else None, - }) - - btc_pct = to_float((tickers.get("BTC/USDT") or {}).get("percentage"), None) - eth_pct = to_float((tickers.get("ETH/USDT") or {}).get("percentage"), None) - global_candidates, candidate_layers = top_candidates_from_tickers(tickers) - global_candidates, candidate_layers, positions_view = enrich_candidates_and_positions( - global_candidates, candidate_layers, positions_view, tickers, ex - ) - leader_score = global_candidates[0]["score"] if global_candidates else 0.0 - portfolio_value = round(free_usdt + total_position_value, 4) - volatility_score = round(max(abs(to_float(btc_pct, 0)), abs(to_float(eth_pct, 0))), 2) - - position_structure = [ - { - "symbol": p.get("symbol"), - "base_asset": p.get("base_asset"), - "quantity": round(to_float(p.get("quantity"), 0), 10), - "avg_cost": to_float(p.get("avg_cost"), None), - } - for p in positions_view - ] - - snapshot = { - "generated_at": utc_iso(), - "timezone": tz_name, - "local_time": local_dt.isoformat(), - "session": session_label(local_dt), - "free_usdt": round(free_usdt, 4), - "portfolio_value_usdt": portfolio_value, - "largest_position_value_usdt": round(largest_position_value, 4), - "actionable_positions": actionable_positions, - "positions": positions_view, - "positions_hash": stable_hash(position_structure), - "top_candidates": global_candidates, - "top_candidates_layers": candidate_layers, - "candidates_hash": stable_hash({"global": global_candidates, "layers": candidate_layers}), - "market_regime": { - "btc_24h_pct": round(btc_pct, 2) if btc_pct is not None else None, - "btc_regime": regime_from_pct(btc_pct), - "eth_24h_pct": round(eth_pct, 2) if eth_pct is not None else None, - "eth_regime": regime_from_pct(eth_pct), - "volatility_score": volatility_score, - "leader_score": round(leader_score, 4), - }, - } - snapshot["snapshot_hash"] = stable_hash({ - "portfolio_value_usdt": snapshot["portfolio_value_usdt"], - "positions_hash": snapshot["positions_hash"], - "candidates_hash": snapshot["candidates_hash"], - "market_regime": snapshot["market_regime"], - "session": snapshot["session"], - }) - return snapshot - - -def build_adaptive_profile(snapshot: dict): - portfolio_value = snapshot.get("portfolio_value_usdt", 0) - free_usdt = snapshot.get("free_usdt", 0) - session = snapshot.get("session") - market = snapshot.get("market_regime", {}) - volatility_score = to_float(market.get("volatility_score"), 0) - leader_score = to_float(market.get("leader_score"), 0) - actionable_positions = int(snapshot.get("actionable_positions") or 0) - largest_position_value = to_float(snapshot.get("largest_position_value_usdt"), 0) - - capital_band = "micro" if portfolio_value < 25 else "small" if portfolio_value < 100 else "normal" - session_mode = "quiet" if session in {"overnight", "asia-morning"} else "active" - volatility_mode = "high" if volatility_score >= 2.5 or leader_score >= 120 else "normal" - dust_mode = free_usdt < MIN_ACTIONABLE_USDT and largest_position_value < MIN_REAL_POSITION_VALUE_USDT - - price_trigger = BASE_PRICE_MOVE_TRIGGER_PCT - pnl_trigger = BASE_PNL_TRIGGER_PCT - portfolio_trigger = BASE_PORTFOLIO_MOVE_TRIGGER_PCT - candidate_ratio = BASE_CANDIDATE_SCORE_TRIGGER_RATIO - force_minutes = BASE_FORCE_ANALYSIS_AFTER_MINUTES - cooldown_minutes = BASE_COOLDOWN_MINUTES - soft_score_threshold = 2.0 - - if capital_band == "micro": - price_trigger += 0.02 - pnl_trigger += 0.03 - portfolio_trigger += 0.04 - candidate_ratio += 0.25 - force_minutes += 180 - cooldown_minutes += 30 - soft_score_threshold += 1.0 - elif capital_band == "small": - price_trigger += 0.01 - pnl_trigger += 0.01 - portfolio_trigger += 0.01 - candidate_ratio += 0.1 - force_minutes += 60 - cooldown_minutes += 10 - soft_score_threshold += 0.5 - - if session_mode == "quiet": - price_trigger += 0.01 - pnl_trigger += 0.01 - portfolio_trigger += 0.01 - candidate_ratio += 0.05 - soft_score_threshold += 0.5 - else: - force_minutes = max(120, force_minutes - 30) - - if volatility_mode == "high": - price_trigger = max(0.02, price_trigger - 0.01) - pnl_trigger = max(0.025, pnl_trigger - 0.005) - portfolio_trigger = max(0.025, portfolio_trigger - 0.005) - candidate_ratio = max(1.1, candidate_ratio - 0.1) - cooldown_minutes = max(20, cooldown_minutes - 10) - soft_score_threshold = max(1.0, soft_score_threshold - 0.5) - - if dust_mode: - candidate_ratio += 0.3 - force_minutes += 180 - cooldown_minutes += 30 - soft_score_threshold += 1.5 - - return { - "capital_band": capital_band, - "session_mode": session_mode, - "volatility_mode": volatility_mode, - "dust_mode": dust_mode, - "price_move_trigger_pct": round(price_trigger, 4), - "pnl_trigger_pct": round(pnl_trigger, 4), - "portfolio_move_trigger_pct": round(portfolio_trigger, 4), - "candidate_score_trigger_ratio": round(candidate_ratio, 4), - "force_analysis_after_minutes": int(force_minutes), - "cooldown_minutes": int(cooldown_minutes), - "soft_score_threshold": round(soft_score_threshold, 2), - "new_entries_allowed": free_usdt >= MIN_ACTIONABLE_USDT and not dust_mode, - "switching_allowed": actionable_positions > 0 or portfolio_value >= 25, - } - - -def _candidate_weight(snapshot: dict, profile: dict) -> float: - if not profile.get("new_entries_allowed"): - return 0.5 - if profile.get("volatility_mode") == "high": - return 1.5 - if snapshot.get("session") in {"europe-open", "us-session"}: - return 1.25 - return 1.0 - - -def analyze_trigger(snapshot: dict, state: dict): - reasons = [] - details = list(state.get("_stale_recovery_notes", [])) - hard_reasons = [] - soft_reasons = [] - soft_score = 0.0 - - profile = build_adaptive_profile(snapshot) - market = snapshot.get("market_regime", {}) - now = utc_now() - - last_positions_hash = state.get("last_positions_hash") - last_portfolio_value = state.get("last_portfolio_value_usdt") - last_market_regime = state.get("last_market_regime", {}) - last_positions_map = state.get("last_positions_map", {}) - last_top_candidate = state.get("last_top_candidate") - pending_trigger = bool(state.get("pending_trigger")) - run_requested_at = parse_ts(state.get("run_requested_at")) - last_deep_analysis_at = parse_ts(state.get("last_deep_analysis_at")) - last_triggered_at = parse_ts(state.get("last_triggered_at")) - last_trigger_snapshot_hash = state.get("last_trigger_snapshot_hash") - last_hard_reasons_at = state.get("last_hard_reasons_at", {}) - - price_trigger = profile["price_move_trigger_pct"] - pnl_trigger = profile["pnl_trigger_pct"] - portfolio_trigger = profile["portfolio_move_trigger_pct"] - candidate_ratio_trigger = profile["candidate_score_trigger_ratio"] - force_minutes = profile["force_analysis_after_minutes"] - cooldown_minutes = profile["cooldown_minutes"] - soft_score_threshold = profile["soft_score_threshold"] - - if pending_trigger: - reasons.append("pending-trigger-unacked") - hard_reasons.append("pending-trigger-unacked") - details.append("上次已触发深度分析但尚未确认完成") - if run_requested_at: - details.append(f"外部门控已在 {run_requested_at.isoformat()} 请求运行分析任务") - - if not last_deep_analysis_at: - reasons.append("first-analysis") - hard_reasons.append("first-analysis") - details.append("尚未记录过深度分析") - elif now - last_deep_analysis_at >= timedelta(minutes=force_minutes): - reasons.append("stale-analysis") - hard_reasons.append("stale-analysis") - details.append(f"距离上次深度分析已超过 {force_minutes} 分钟") - - if last_positions_hash and snapshot["positions_hash"] != last_positions_hash: - reasons.append("positions-changed") - hard_reasons.append("positions-changed") - details.append("持仓结构发生变化") - - if last_portfolio_value not in (None, 0): - portfolio_delta = abs(snapshot["portfolio_value_usdt"] - last_portfolio_value) / max(last_portfolio_value, 1e-9) - if portfolio_delta >= portfolio_trigger: - if portfolio_delta >= 1.0: - reasons.append("portfolio-extreme-move") - hard_reasons.append("portfolio-extreme-move") - details.append(f"组合净值剧烈变化 {portfolio_delta:.1%}，超过 100%，视为硬触发") - else: - reasons.append("portfolio-move") - soft_reasons.append("portfolio-move") - soft_score += 1.0 - details.append(f"组合净值变化 {portfolio_delta:.1%}，阈值 {portfolio_trigger:.1%}") - - for pos in snapshot["positions"]: - symbol = pos["symbol"] - prev = last_positions_map.get(symbol, {}) - cur_price = pos.get("last_price") - prev_price = prev.get("last_price") - cur_pnl = pos.get("pnl_pct") - prev_pnl = prev.get("pnl_pct") - market_value = to_float(pos.get("market_value_usdt"), 0) - actionable_position = market_value >= MIN_REAL_POSITION_VALUE_USDT - - if cur_price and prev_price: - price_move = abs(cur_price - prev_price) / max(prev_price, 1e-9) - if price_move >= price_trigger: - reasons.append(f"price-move:{symbol}") - soft_reasons.append(f"price-move:{symbol}") - soft_score += 1.0 if actionable_position else 0.4 - details.append(f"{symbol} 价格变化 {price_move:.1%}，阈值 {price_trigger:.1%}") - if cur_pnl is not None and prev_pnl is not None: - pnl_move = abs(cur_pnl - prev_pnl) - if pnl_move >= pnl_trigger: - reasons.append(f"pnl-move:{symbol}") - soft_reasons.append(f"pnl-move:{symbol}") - soft_score += 1.0 if actionable_position else 0.4 - details.append(f"{symbol} 盈亏变化 {pnl_move:.1%}，阈值 {pnl_trigger:.1%}") - if cur_pnl is not None: - stop_band = -0.06 if actionable_position else -0.12 - take_band = 0.14 if actionable_position else 0.25 - if cur_pnl <= stop_band or cur_pnl >= take_band: - reasons.append(f"risk-band:{symbol}") - hard_reasons.append(f"risk-band:{symbol}") - details.append(f"{symbol} 接近执行阈值，当前盈亏 {cur_pnl:.1%}") - if cur_pnl <= HARD_STOP_PCT: - reasons.append(f"hard-stop:{symbol}") - hard_reasons.append(f"hard-stop:{symbol}") - details.append(f"{symbol} 盈亏超过 {HARD_STOP_PCT:.1%}，触发紧急硬触发") - - current_market = snapshot.get("market_regime", {}) - if last_market_regime: - if current_market.get("btc_regime") != last_market_regime.get("btc_regime"): - reasons.append("btc-regime-change") - hard_reasons.append("btc-regime-change") - details.append(f"BTC 由 {last_market_regime.get('btc_regime')} 切换为 {current_market.get('btc_regime')}") - if current_market.get("eth_regime") != last_market_regime.get("eth_regime"): - reasons.append("eth-regime-change") - hard_reasons.append("eth-regime-change") - details.append(f"ETH 由 {last_market_regime.get('eth_regime')} 切换为 {current_market.get('eth_regime')}") - - # Candidate hard moon trigger - for cand in snapshot.get("top_candidates", []): - if cand.get("change_24h_pct", 0) >= HARD_MOON_PCT * 100: - reasons.append(f"hard-moon:{cand['symbol']}") - hard_reasons.append(f"hard-moon:{cand['symbol']}") - details.append(f"候选币 {cand['symbol']} 24h 涨幅 {cand['change_24h_pct']:.1f}%，触发强势硬触发") - - current_leader = snapshot.get("top_candidates", [{}])[0] if snapshot.get("top_candidates") else None - candidate_weight = _candidate_weight(snapshot, profile) - - # Layer leader changes - last_layers = state.get("last_candidates_layers", {}) - current_layers = snapshot.get("top_candidates_layers", {}) - for band in ("major", "mid", "meme"): - cur_band = current_layers.get(band, []) - prev_band = last_layers.get(band, []) - cur_leader = cur_band[0] if cur_band else None - prev_leader = prev_band[0] if prev_band else None - if cur_leader and prev_leader and cur_leader["symbol"] != prev_leader["symbol"]: - score_ratio = cur_leader.get("score", 0) / max(prev_leader.get("score", 0.0001), 0.0001) - if score_ratio >= candidate_ratio_trigger: - reasons.append(f"new-leader-{band}:{cur_leader['symbol']}") - soft_reasons.append(f"new-leader-{band}:{cur_leader['symbol']}") - soft_score += candidate_weight * 0.7 - details.append( - f"{band} 层新榜首 {cur_leader['symbol']} 替代 {prev_leader['symbol']}，score 比例 {score_ratio:.2f}" - ) - - current_leader = snapshot.get("top_candidates", [{}])[0] if snapshot.get("top_candidates") else None - if last_top_candidate and current_leader: - if current_leader.get("symbol") != last_top_candidate.get("symbol"): - score_ratio = current_leader.get("score", 0) / max(last_top_candidate.get("score", 0.0001), 0.0001) - if score_ratio >= candidate_ratio_trigger: - reasons.append("new-leader") - soft_reasons.append("new-leader") - soft_score += candidate_weight - details.append( - f"新候选币 {current_leader.get('symbol')} 领先上次榜首，score 比例 {score_ratio:.2f}，阈值 {candidate_ratio_trigger:.2f}" - ) - elif current_leader and not last_top_candidate: - reasons.append("candidate-leader-init") - soft_reasons.append("candidate-leader-init") - soft_score += candidate_weight - details.append(f"首次记录候选榜首 {current_leader.get('symbol')}") - - # --- adaptive cooldown based on signal change magnitude --- - def _signal_delta() -> float: - delta = 0.0 - if last_trigger_snapshot_hash and snapshot.get("snapshot_hash") != last_trigger_snapshot_hash: - delta += 0.5 - if snapshot["positions_hash"] != last_positions_hash: - delta += 1.5 - for pos in snapshot["positions"]: - symbol = pos["symbol"] - prev = last_positions_map.get(symbol, {}) - cur_price = pos.get("last_price") - prev_price = prev.get("last_price") - cur_pnl = pos.get("pnl_pct") - prev_pnl = prev.get("pnl_pct") - if cur_price and prev_price: - if abs(cur_price - prev_price) / max(prev_price, 1e-9) >= 0.02: - delta += 0.5 - if cur_pnl is not None and prev_pnl is not None: - if abs(cur_pnl - prev_pnl) >= 0.03: - delta += 0.5 - current_leader = snapshot.get("top_candidates", [{}])[0] if snapshot.get("top_candidates") else None - last_leader = state.get("last_top_candidate") - if current_leader and last_leader and current_leader.get("symbol") != last_leader.get("symbol"): - delta += 1.0 - current_layers = snapshot.get("top_candidates_layers", {}) - last_layers = state.get("last_candidates_layers", {}) - for band in ("major", "mid", "meme"): - cur_band = current_layers.get(band, []) - prev_band = last_layers.get(band, []) - cur_l = cur_band[0] if cur_band else None - prev_l = prev_band[0] if prev_band else None - if cur_l and prev_l and cur_l.get("symbol") != prev_l.get("symbol"): - delta += 0.5 - if last_market_regime: - if current_market.get("btc_regime") != last_market_regime.get("btc_regime"): - delta += 1.5 - if current_market.get("eth_regime") != last_market_regime.get("eth_regime"): - delta += 1.5 - if last_portfolio_value not in (None, 0): - portfolio_delta = abs(snapshot["portfolio_value_usdt"] - last_portfolio_value) / max(last_portfolio_value, 1e-9) - if portfolio_delta >= 0.05: - delta += 1.0 - # fresh hard reason type not seen in last trigger - last_trigger_hard_types = {r.split(":")[0] for r in (state.get("last_trigger_hard_reasons") or [])} - current_hard_types = {r.split(":")[0] for r in hard_reasons} - if current_hard_types - last_trigger_hard_types: - delta += 2.0 - return delta - - signal_delta = _signal_delta() - effective_cooldown = cooldown_minutes - if signal_delta < 1.0: - effective_cooldown = max(cooldown_minutes, 90) - elif signal_delta >= 2.5: - effective_cooldown = max(0, cooldown_minutes - 15) - - cooldown_active = bool(last_triggered_at and now - last_triggered_at < timedelta(minutes=effective_cooldown)) - - # Dedup hard reasons within window to avoid repeated model wakeups for the same event - dedup_window = timedelta(minutes=HARD_REASON_DEDUP_MINUTES) - for hr in list(hard_reasons): - last_at = parse_ts(last_hard_reasons_at.get(hr)) - if last_at and now - last_at < dedup_window: - hard_reasons.remove(hr) - details.append(f"{hr} 近期已触发，{HARD_REASON_DEDUP_MINUTES}分钟内去重") - - hard_trigger = bool(hard_reasons) - if profile.get("dust_mode") and not hard_trigger and soft_score < soft_score_threshold + 1.0: - details.append("微型资金/粉尘仓位模式：抬高软触发门槛，避免无意义分析") - - if profile.get("dust_mode") and not profile.get("new_entries_allowed") and any(r in {"new-leader", "candidate-leader-init"} for r in soft_reasons): - details.append("当前可用资金低于可执行阈值，新候选币仅做观察，不单独触发深度分析") - soft_score = max(0.0, soft_score - 0.75) - - should_analyze = hard_trigger or soft_score >= soft_score_threshold - - if cooldown_active and not hard_trigger and should_analyze: - should_analyze = False - details.append(f"处于 {cooldown_minutes} 分钟冷却窗口，软触发先记录不升级") - - if cooldown_active and not hard_trigger and reasons and soft_score < soft_score_threshold: - details.append(f"处于 {cooldown_minutes} 分钟冷却窗口，且软信号强度不足 ({soft_score:.2f} < {soft_score_threshold:.2f})") - - status = "deep_analysis_required" if should_analyze else "stable" - - compact_lines = [ - f"状态: {status}", - f"组合净值: ${snapshot['portfolio_value_usdt']:.4f} | 可用USDT: ${snapshot['free_usdt']:.4f}", - f"本地时段: {snapshot['session']} | 时区: {snapshot['timezone']}", - f"BTC/ETH: {market.get('btc_regime')} ({market.get('btc_24h_pct')}%), {market.get('eth_regime')} ({market.get('eth_24h_pct')}%) | 波动分数 {market.get('volatility_score')}", - f"门控画像: capital={profile['capital_band']}, session={profile['session_mode']}, volatility={profile['volatility_mode']}, dust={profile['dust_mode']}", - f"阈值: price={price_trigger:.1%}, pnl={pnl_trigger:.1%}, portfolio={portfolio_trigger:.1%}, candidate={candidate_ratio_trigger:.2f}, cooldown={effective_cooldown}m({cooldown_minutes}m基础), force={force_minutes}m", - f"软信号分: {soft_score:.2f} / {soft_score_threshold:.2f}", - f"信号变化度: {signal_delta:.1f}", - ] - if snapshot["positions"]: - compact_lines.append("持仓:") - for pos in snapshot["positions"][:4]: - pnl = pos.get("pnl_pct") - pnl_text = f"{pnl:+.1%}" if pnl is not None else "n/a" - compact_lines.append( - f"- {pos['symbol']}: qty={pos['quantity']}, px={pos.get('last_price')}, pnl={pnl_text}, value=${pos.get('market_value_usdt')}" - ) - else: - compact_lines.append("持仓: 当前无现货仓位") - if snapshot["top_candidates"]: - compact_lines.append("候选榜:") - for cand in snapshot["top_candidates"]: - compact_lines.append( - f"- {cand['symbol']}: score={cand['score']}, 24h={cand['change_24h_pct']}%, vol=${cand['volume_24h']}" - ) - layers = snapshot.get("top_candidates_layers", {}) - for band, band_cands in layers.items(): - if band_cands: - compact_lines.append(f"{band} 层:") - for cand in band_cands: - compact_lines.append( - f"- {cand['symbol']}: score={cand['score']}, 24h={cand['change_24h_pct']}%, vol=${cand['volume_24h']}" - ) - if details: - compact_lines.append("触发说明:") - for item in details: - compact_lines.append(f"- {item}") - - return { - "generated_at": snapshot["generated_at"], - "status": status, - "should_analyze": should_analyze, - "pending_trigger": pending_trigger, - "run_requested": bool(run_requested_at), - "run_requested_at": run_requested_at.isoformat() if run_requested_at else None, - "cooldown_active": cooldown_active, - "effective_cooldown_minutes": effective_cooldown, - "signal_delta": round(signal_delta, 2), - "reasons": reasons, - "hard_reasons": hard_reasons, - "soft_reasons": soft_reasons, - "soft_score": round(soft_score, 3), - "adaptive_profile": profile, - "portfolio_value_usdt": snapshot["portfolio_value_usdt"], - "free_usdt": snapshot["free_usdt"], - "market_regime": snapshot["market_regime"], - "session": snapshot["session"], - "positions": snapshot["positions"], - "top_candidates": snapshot["top_candidates"], - "top_candidates_layers": layers, - "snapshot_hash": snapshot["snapshot_hash"], - "compact_summary": "\n".join(compact_lines), - "details": details, - } - - -def update_state_after_observation(state: dict, snapshot: dict, analysis: dict): - new_state = dict(state) - new_state.update({ - "last_observed_at": snapshot["generated_at"], - "last_snapshot_hash": snapshot["snapshot_hash"], - "last_positions_hash": snapshot["positions_hash"], - "last_candidates_hash": snapshot["candidates_hash"], - "last_portfolio_value_usdt": snapshot["portfolio_value_usdt"], - "last_market_regime": snapshot["market_regime"], - "last_positions_map": {p["symbol"]: {"last_price": p.get("last_price"), "pnl_pct": p.get("pnl_pct")} for p in snapshot["positions"]}, - "last_top_candidate": snapshot["top_candidates"][0] if snapshot["top_candidates"] else None, - "last_candidates_layers": snapshot.get("top_candidates_layers", {}), - "last_adaptive_profile": analysis.get("adaptive_profile", {}), - }) - if analysis["should_analyze"]: - new_state["pending_trigger"] = True - new_state["pending_reasons"] = analysis["details"] - new_state["last_triggered_at"] = snapshot["generated_at"] - new_state["last_trigger_snapshot_hash"] = snapshot["snapshot_hash"] - new_state["last_trigger_hard_reasons"] = analysis.get("hard_reasons", []) - new_state["last_trigger_signal_delta"] = analysis.get("signal_delta", 0.0) - - # Update hard-reason dedup timestamps and prune old entries - last_hard_reasons_at = dict(state.get("last_hard_reasons_at", {})) - for hr in analysis.get("hard_reasons", []): - last_hard_reasons_at[hr] = snapshot["generated_at"] - cutoff = utc_now() - timedelta(hours=24) - pruned = { - k: v for k, v in last_hard_reasons_at.items() - if parse_ts(v) and parse_ts(v) > cutoff - } - new_state["last_hard_reasons_at"] = pruned - return new_state - - -def mark_run_requested(note: str = ""): - from .services.precheck_state import mark_run_requested as service_mark_run_requested - - return service_mark_run_requested(note) - - -def ack_analysis(note: str = ""): - from .services.precheck_state import ack_analysis as service_ack_analysis - - return service_ack_analysis(note) +from importlib import import_module + +from .services.precheck_service import run as _run_service + +_CORE_EXPORTS = { + "PATHS", + "BASE_DIR", + "STATE_DIR", + "STATE_FILE", + "POSITIONS_FILE", + "CONFIG_FILE", + "ENV_FILE", + "BASE_PRICE_MOVE_TRIGGER_PCT", + "BASE_PNL_TRIGGER_PCT", + "BASE_PORTFOLIO_MOVE_TRIGGER_PCT", + "BASE_CANDIDATE_SCORE_TRIGGER_RATIO", + "BASE_FORCE_ANALYSIS_AFTER_MINUTES", + "BASE_COOLDOWN_MINUTES", + "TOP_CANDIDATES", + "MIN_ACTIONABLE_USDT", + "MIN_REAL_POSITION_VALUE_USDT", + "BLACKLIST", + "HARD_STOP_PCT", + "HARD_MOON_PCT", + "MIN_CHANGE_PCT", + "MAX_PRICE_CAP", + "HARD_REASON_DEDUP_MINUTES", + "MAX_PENDING_TRIGGER_MINUTES", + "MAX_RUN_REQUEST_MINUTES", + "utc_now", + "utc_iso", + "parse_ts", + "load_json", + "load_env", + "load_positions", + "load_state", + "load_config", + "clear_run_request_fields", + "sanitize_state_for_stale_triggers", + "save_state", + "stable_hash", + "get_exchange", + "fetch_ohlcv_batch", + "compute_ohlcv_metrics", + "enrich_candidates_and_positions", + "regime_from_pct", + "to_float", + "norm_symbol", + "get_local_now", + "session_label", + "top_candidates_from_tickers", + "build_snapshot", + "build_adaptive_profile", + "analyze_trigger", + "update_state_after_observation", +} +_STATE_EXPORTS = {"mark_run_requested", "ack_analysis"} + +__all__ = sorted(_CORE_EXPORTS | _STATE_EXPORTS | {"main"}) + + +def __getattr__(name: str): + if name in _CORE_EXPORTS: + return getattr(import_module(".services.precheck_core", __package__), name) + if name in _STATE_EXPORTS: + return getattr(import_module(".services.precheck_state", __package__), name) + raise AttributeError(f"module {__name__!r} has no attribute {name!r}") + + +def __dir__(): + return sorted(set(globals()) | set(__all__)) def main(): - from .services.precheck_service import run - - return run(sys.argv[1:]) + return _run_service(sys.argv[1:]) if __name__ == "__main__": - main() + raise SystemExit(main()) diff --git a/src/coinhunter/services/precheck_analysis.py b/src/coinhunter/services/precheck_analysis.py index 57e3254..7f83b5d 100644 --- a/src/coinhunter/services/precheck_analysis.py +++ b/src/coinhunter/services/precheck_analysis.py @@ -2,16 +2,16 @@ from __future__ import annotations -from .. import precheck as precheck_module +from . import precheck_core def analyze_trigger(snapshot: dict, state: dict) -> dict: - return precheck_module.analyze_trigger(snapshot, state) + return precheck_core.analyze_trigger(snapshot, state) def build_failure_payload(exc: Exception) -> dict: return { - "generated_at": precheck_module.utc_iso(), + "generated_at": precheck_core.utc_iso(), "status": "deep_analysis_required", "should_analyze": True, "pending_trigger": True, diff --git a/src/coinhunter/services/precheck_core.py b/src/coinhunter/services/precheck_core.py new file mode 100644 index 0000000..8f2b440 --- /dev/null +++ b/src/coinhunter/services/precheck_core.py @@ -0,0 +1,900 @@ +"""Service-owned precheck core logic. + +This module holds the reusable implementation. Root-level ``coinhunter.precheck`` +is intentionally kept as a compatibility facade for older imports and direct +module execution. +""" + +from __future__ import annotations + +import hashlib +import json +import os +import re +from datetime import datetime, timedelta, timezone +from pathlib import Path +from zoneinfo import ZoneInfo + +import ccxt + +from ..runtime import get_runtime_paths, load_env_file + +PATHS = get_runtime_paths() +BASE_DIR = PATHS.root +STATE_DIR = PATHS.state_dir +STATE_FILE = PATHS.precheck_state_file +POSITIONS_FILE = PATHS.positions_file +CONFIG_FILE = PATHS.config_file +ENV_FILE = PATHS.env_file + +BASE_PRICE_MOVE_TRIGGER_PCT = 0.025 +BASE_PNL_TRIGGER_PCT = 0.03 +BASE_PORTFOLIO_MOVE_TRIGGER_PCT = 0.03 +BASE_CANDIDATE_SCORE_TRIGGER_RATIO = 1.15 +BASE_FORCE_ANALYSIS_AFTER_MINUTES = 180 +BASE_COOLDOWN_MINUTES = 45 +TOP_CANDIDATES = 10 +MIN_ACTIONABLE_USDT = 12.0 +MIN_REAL_POSITION_VALUE_USDT = 8.0 +BLACKLIST = {"USDC", "BUSD", "TUSD", "FDUSD", "USTC", "PAXG"} +HARD_STOP_PCT = -0.08 +HARD_MOON_PCT = 0.25 +MIN_CHANGE_PCT = 1.0 +MAX_PRICE_CAP = None +HARD_REASON_DEDUP_MINUTES = 15 +MAX_PENDING_TRIGGER_MINUTES = 30 +MAX_RUN_REQUEST_MINUTES = 20 + + +def utc_now(): + return datetime.now(timezone.utc) + + +def utc_iso(): + return utc_now().isoformat() + + +def parse_ts(value: str | None): + if not value: + return None + try: + ts = datetime.fromisoformat(value) + if ts.tzinfo is None: + ts = ts.replace(tzinfo=timezone.utc) + return ts + except Exception: + return None + + +def load_json(path: Path, default): + if not path.exists(): + return default + try: + return json.loads(path.read_text(encoding="utf-8")) + except Exception: + return default + + +def load_env(): + load_env_file(PATHS) + + +def load_positions(): + return load_json(POSITIONS_FILE, {}).get("positions", []) + + +def load_state(): + return load_json(STATE_FILE, {}) + + +def load_config(): + return load_json(CONFIG_FILE, {}) + + +def clear_run_request_fields(state: dict): + state.pop("run_requested_at", None) + state.pop("run_request_note", None) + + +def sanitize_state_for_stale_triggers(state: dict): + sanitized = dict(state) + notes = [] + now = utc_now() + run_requested_at = parse_ts(sanitized.get("run_requested_at")) + last_deep_analysis_at = parse_ts(sanitized.get("last_deep_analysis_at")) + last_triggered_at = parse_ts(sanitized.get("last_triggered_at")) + pending_trigger = bool(sanitized.get("pending_trigger")) + + if run_requested_at and last_deep_analysis_at and last_deep_analysis_at >= run_requested_at: + clear_run_request_fields(sanitized) + if pending_trigger and (not last_triggered_at or last_deep_analysis_at >= last_triggered_at): + sanitized["pending_trigger"] = False + sanitized["pending_reasons"] = [] + sanitized["last_ack_note"] = ( + f"auto-cleared completed trigger at {utc_iso()} because last_deep_analysis_at >= run_requested_at" + ) + pending_trigger = False + notes.append( + f"自动清理已完成的 run_requested 标记：最近深度分析时间 {last_deep_analysis_at.isoformat()} >= 请求时间 {run_requested_at.isoformat()}" + ) + run_requested_at = None + + if run_requested_at and now - run_requested_at > timedelta(minutes=MAX_RUN_REQUEST_MINUTES): + clear_run_request_fields(sanitized) + notes.append( + f"自动清理超时 run_requested 标记：已等待 {(now - run_requested_at).total_seconds() / 60:.1f} 分钟，超过 {MAX_RUN_REQUEST_MINUTES} 分钟" + ) + run_requested_at = None + + pending_anchor = run_requested_at or last_triggered_at or last_deep_analysis_at + if pending_trigger and pending_anchor and now - pending_anchor > timedelta(minutes=MAX_PENDING_TRIGGER_MINUTES): + sanitized["pending_trigger"] = False + sanitized["pending_reasons"] = [] + sanitized["last_ack_note"] = ( + f"auto-recovered stale pending trigger at {utc_iso()} after waiting " + f"{(now - pending_anchor).total_seconds() / 60:.1f} minutes" + ) + notes.append( + f"自动解除 pending_trigger：触发状态已悬挂 {(now - pending_anchor).total_seconds() / 60:.1f} 分钟，超过 {MAX_PENDING_TRIGGER_MINUTES} 分钟" + ) + + sanitized["_stale_recovery_notes"] = notes + return sanitized + + +def save_state(state: dict): + STATE_DIR.mkdir(parents=True, exist_ok=True) + state_to_save = dict(state) + state_to_save.pop("_stale_recovery_notes", None) + STATE_FILE.write_text(json.dumps(state_to_save, indent=2, ensure_ascii=False), encoding="utf-8") + + +def stable_hash(data) -> str: + payload = json.dumps(data, sort_keys=True, ensure_ascii=False, separators=(",", ":")) + return hashlib.sha1(payload.encode("utf-8")).hexdigest() + + +def get_exchange(): + load_env() + api_key = os.getenv("BINANCE_API_KEY") + secret = os.getenv("BINANCE_API_SECRET") + if not api_key or not secret: + raise RuntimeError("Missing BINANCE_API_KEY or BINANCE_API_SECRET in ~/.hermes/.env") + ex = ccxt.binance({ + "apiKey": api_key, + "secret": secret, + "options": {"defaultType": "spot"}, + "enableRateLimit": True, + }) + ex.load_markets() + return ex + + +def fetch_ohlcv_batch(ex, symbols: set, timeframe: str, limit: int): + results = {} + for sym in sorted(symbols): + try: + ohlcv = ex.fetch_ohlcv(sym, timeframe=timeframe, limit=limit) + if ohlcv and len(ohlcv) >= 2: + results[sym] = ohlcv + except Exception: + pass + return results + + +def compute_ohlcv_metrics(ohlcv_1h, ohlcv_4h, current_price, volume_24h=None): + metrics = {} + if ohlcv_1h and len(ohlcv_1h) >= 2: + closes = [c[4] for c in ohlcv_1h] + volumes = [c[5] for c in ohlcv_1h] + metrics["change_1h_pct"] = round((closes[-1] - closes[-2]) / closes[-2] * 100, 2) if closes[-2] != 0 else None + if len(closes) >= 5: + metrics["change_4h_pct"] = round((closes[-1] - closes[-5]) / closes[-5] * 100, 2) if closes[-5] != 0 else None + recent_vol = sum(volumes[-4:]) / 4 if len(volumes) >= 4 else None + metrics["volume_1h_avg"] = round(recent_vol, 2) if recent_vol else None + highs = [c[2] for c in ohlcv_1h[-4:]] + lows = [c[3] for c in ohlcv_1h[-4:]] + metrics["high_4h"] = round(max(highs), 8) if highs else None + metrics["low_4h"] = round(min(lows), 8) if lows else None + + if ohlcv_4h and len(ohlcv_4h) >= 2: + closes_4h = [c[4] for c in ohlcv_4h] + volumes_4h = [c[5] for c in ohlcv_4h] + metrics["change_4h_pct_from_4h"] = round((closes_4h[-1] - closes_4h[-2]) / closes_4h[-2] * 100, 2) if closes_4h[-2] != 0 else None + recent_vol_4h = sum(volumes_4h[-2:]) / 2 if len(volumes_4h) >= 2 else None + metrics["volume_4h_avg"] = round(recent_vol_4h, 2) if recent_vol_4h else None + highs_4h = [c[2] for c in ohlcv_4h] + lows_4h = [c[3] for c in ohlcv_4h] + metrics["high_24h_calc"] = round(max(highs_4h), 8) if highs_4h else None + metrics["low_24h_calc"] = round(min(lows_4h), 8) if lows_4h else None + if highs_4h and lows_4h: + avg_price = sum(closes_4h) / len(closes_4h) + metrics["volatility_4h_pct"] = round((max(highs_4h) - min(lows_4h)) / avg_price * 100, 2) + + if current_price: + if metrics.get("high_4h"): + metrics["distance_from_4h_high_pct"] = round((metrics["high_4h"] - current_price) / metrics["high_4h"] * 100, 2) + if metrics.get("low_4h"): + metrics["distance_from_4h_low_pct"] = round((current_price - metrics["low_4h"]) / metrics["low_4h"] * 100, 2) + if metrics.get("high_24h_calc"): + metrics["distance_from_24h_high_pct"] = round((metrics["high_24h_calc"] - current_price) / metrics["high_24h_calc"] * 100, 2) + if metrics.get("low_24h_calc"): + metrics["distance_from_24h_low_pct"] = round((current_price - metrics["low_24h_calc"]) / metrics["low_24h_calc"] * 100, 2) + + if volume_24h and volume_24h > 0 and metrics.get("volume_1h_avg"): + daily_avg_1h = volume_24h / 24 + metrics["volume_1h_multiple"] = round(metrics["volume_1h_avg"] / daily_avg_1h, 2) + if volume_24h and volume_24h > 0 and metrics.get("volume_4h_avg"): + daily_avg_4h = volume_24h / 6 + metrics["volume_4h_multiple"] = round(metrics["volume_4h_avg"] / daily_avg_4h, 2) + + return metrics + + +def enrich_candidates_and_positions(global_candidates, candidate_layers, positions_view, tickers, ex): + symbols = set() + for c in global_candidates: + symbols.add(c["symbol"]) + for p in positions_view: + sym = p.get("symbol") + if sym: + sym_ccxt = norm_symbol(sym) + symbols.add(sym_ccxt) + + ohlcv_1h = fetch_ohlcv_batch(ex, symbols, "1h", 24) + ohlcv_4h = fetch_ohlcv_batch(ex, symbols, "4h", 12) + + def _apply(target_list): + for item in target_list: + sym = item.get("symbol") + if not sym: + continue + sym_ccxt = norm_symbol(sym) + v24h = to_float(tickers.get(sym_ccxt, {}).get("quoteVolume")) + metrics = compute_ohlcv_metrics( + ohlcv_1h.get(sym_ccxt), + ohlcv_4h.get(sym_ccxt), + item.get("price") or item.get("last_price"), + volume_24h=v24h, + ) + item["metrics"] = metrics + + _apply(global_candidates) + for band_list in candidate_layers.values(): + _apply(band_list) + _apply(positions_view) + return global_candidates, candidate_layers, positions_view + + +def regime_from_pct(pct: float | None) -> str: + if pct is None: + return "unknown" + if pct >= 2.0: + return "bullish" + if pct <= -2.0: + return "bearish" + return "neutral" + + +def to_float(value, default=0.0): + try: + if value is None: + return default + return float(value) + except Exception: + return default + + +def norm_symbol(symbol: str) -> str: + s = symbol.upper().replace("-", "").replace("_", "") + if "/" in s: + return s + if s.endswith("USDT"): + return s[:-4] + "/USDT" + return s + + +def get_local_now(config: dict): + tz_name = config.get("timezone") or "Asia/Shanghai" + try: + tz = ZoneInfo(tz_name) + except Exception: + tz = ZoneInfo("Asia/Shanghai") + tz_name = "Asia/Shanghai" + return utc_now().astimezone(tz), tz_name + + +def session_label(local_dt: datetime) -> str: + hour = local_dt.hour + if 0 <= hour < 7: + return "overnight" + if 7 <= hour < 12: + return "asia-morning" + if 12 <= hour < 17: + return "asia-afternoon" + if 17 <= hour < 21: + return "europe-open" + return "us-session" + + +def _liquidity_score(volume: float) -> float: + return min(1.0, max(0.0, volume / 50_000_000)) + + +def _breakout_score(price: float, avg_price: float | None) -> float: + if not avg_price or avg_price <= 0: + return 0.0 + return (price - avg_price) / avg_price + + +def top_candidates_from_tickers(tickers: dict): + candidates = [] + for symbol, ticker in tickers.items(): + if not symbol.endswith("/USDT"): + continue + base = symbol.replace("/USDT", "") + if base in BLACKLIST: + continue + if not re.fullmatch(r"[A-Z0-9]{2,20}", base): + continue + price = to_float(ticker.get("last")) + change_pct = to_float(ticker.get("percentage")) + volume = to_float(ticker.get("quoteVolume")) + high = to_float(ticker.get("high")) + low = to_float(ticker.get("low")) + avg_price = to_float(ticker.get("average"), None) + if price <= 0: + continue + if MAX_PRICE_CAP is not None and price > MAX_PRICE_CAP: + continue + if volume < 500_000: + continue + if change_pct < MIN_CHANGE_PCT: + continue + momentum = change_pct / 10.0 + liquidity = _liquidity_score(volume) + breakout = _breakout_score(price, avg_price) + score = round(momentum * 0.5 + liquidity * 0.3 + breakout * 0.2, 4) + band = "major" if price >= 10 else "mid" if price >= 1 else "meme" + distance_from_high = (high - price) / max(high, 1e-9) if high else None + candidates.append({ + "symbol": symbol, + "base": base, + "price": round(price, 8), + "change_24h_pct": round(change_pct, 2), + "volume_24h": round(volume, 2), + "breakout_pct": round(breakout * 100, 2), + "high_24h": round(high, 8) if high else None, + "low_24h": round(low, 8) if low else None, + "distance_from_high_pct": round(distance_from_high * 100, 2) if distance_from_high is not None else None, + "score": score, + "band": band, + }) + candidates.sort(key=lambda x: x["score"], reverse=True) + global_top = candidates[:TOP_CANDIDATES] + layers = {"major": [], "mid": [], "meme": []} + for c in candidates: + layers[c["band"]].append(c) + for k in layers: + layers[k] = layers[k][:5] + return global_top, layers + + +def build_snapshot(): + config = load_config() + local_dt, tz_name = get_local_now(config) + ex = get_exchange() + positions = load_positions() + tickers = ex.fetch_tickers() + balances = ex.fetch_balance()["free"] + free_usdt = to_float(balances.get("USDT")) + + positions_view = [] + total_position_value = 0.0 + largest_position_value = 0.0 + actionable_positions = 0 + for pos in positions: + symbol = pos.get("symbol") or "" + sym_ccxt = norm_symbol(symbol) + ticker = tickers.get(sym_ccxt, {}) + last = to_float(ticker.get("last"), None) + qty = to_float(pos.get("quantity")) + avg_cost = to_float(pos.get("avg_cost"), None) + value = round(qty * last, 4) if last is not None else None + pnl_pct = round((last - avg_cost) / avg_cost, 4) if last is not None and avg_cost else None + high = to_float(ticker.get("high")) + low = to_float(ticker.get("low")) + distance_from_high = (high - last) / max(high, 1e-9) if high and last else None + if value is not None: + total_position_value += value + largest_position_value = max(largest_position_value, value) + if value >= MIN_REAL_POSITION_VALUE_USDT: + actionable_positions += 1 + positions_view.append({ + "symbol": symbol, + "base_asset": pos.get("base_asset"), + "quantity": qty, + "avg_cost": avg_cost, + "last_price": last, + "market_value_usdt": value, + "pnl_pct": pnl_pct, + "high_24h": round(high, 8) if high else None, + "low_24h": round(low, 8) if low else None, + "distance_from_high_pct": round(distance_from_high * 100, 2) if distance_from_high is not None else None, + }) + + btc_pct = to_float((tickers.get("BTC/USDT") or {}).get("percentage"), None) + eth_pct = to_float((tickers.get("ETH/USDT") or {}).get("percentage"), None) + global_candidates, candidate_layers = top_candidates_from_tickers(tickers) + global_candidates, candidate_layers, positions_view = enrich_candidates_and_positions( + global_candidates, candidate_layers, positions_view, tickers, ex + ) + leader_score = global_candidates[0]["score"] if global_candidates else 0.0 + portfolio_value = round(free_usdt + total_position_value, 4) + volatility_score = round(max(abs(to_float(btc_pct, 0)), abs(to_float(eth_pct, 0))), 2) + + position_structure = [ + { + "symbol": p.get("symbol"), + "base_asset": p.get("base_asset"), + "quantity": round(to_float(p.get("quantity"), 0), 10), + "avg_cost": to_float(p.get("avg_cost"), None), + } + for p in positions_view + ] + + snapshot = { + "generated_at": utc_iso(), + "timezone": tz_name, + "local_time": local_dt.isoformat(), + "session": session_label(local_dt), + "free_usdt": round(free_usdt, 4), + "portfolio_value_usdt": portfolio_value, + "largest_position_value_usdt": round(largest_position_value, 4), + "actionable_positions": actionable_positions, + "positions": positions_view, + "positions_hash": stable_hash(position_structure), + "top_candidates": global_candidates, + "top_candidates_layers": candidate_layers, + "candidates_hash": stable_hash({"global": global_candidates, "layers": candidate_layers}), + "market_regime": { + "btc_24h_pct": round(btc_pct, 2) if btc_pct is not None else None, + "btc_regime": regime_from_pct(btc_pct), + "eth_24h_pct": round(eth_pct, 2) if eth_pct is not None else None, + "eth_regime": regime_from_pct(eth_pct), + "volatility_score": volatility_score, + "leader_score": round(leader_score, 4), + }, + } + snapshot["snapshot_hash"] = stable_hash({ + "portfolio_value_usdt": snapshot["portfolio_value_usdt"], + "positions_hash": snapshot["positions_hash"], + "candidates_hash": snapshot["candidates_hash"], + "market_regime": snapshot["market_regime"], + "session": snapshot["session"], + }) + return snapshot + + +def build_adaptive_profile(snapshot: dict): + portfolio_value = snapshot.get("portfolio_value_usdt", 0) + free_usdt = snapshot.get("free_usdt", 0) + session = snapshot.get("session") + market = snapshot.get("market_regime", {}) + volatility_score = to_float(market.get("volatility_score"), 0) + leader_score = to_float(market.get("leader_score"), 0) + actionable_positions = int(snapshot.get("actionable_positions") or 0) + largest_position_value = to_float(snapshot.get("largest_position_value_usdt"), 0) + + capital_band = "micro" if portfolio_value < 25 else "small" if portfolio_value < 100 else "normal" + session_mode = "quiet" if session in {"overnight", "asia-morning"} else "active" + volatility_mode = "high" if volatility_score >= 2.5 or leader_score >= 120 else "normal" + dust_mode = free_usdt < MIN_ACTIONABLE_USDT and largest_position_value < MIN_REAL_POSITION_VALUE_USDT + + price_trigger = BASE_PRICE_MOVE_TRIGGER_PCT + pnl_trigger = BASE_PNL_TRIGGER_PCT + portfolio_trigger = BASE_PORTFOLIO_MOVE_TRIGGER_PCT + candidate_ratio = BASE_CANDIDATE_SCORE_TRIGGER_RATIO + force_minutes = BASE_FORCE_ANALYSIS_AFTER_MINUTES + cooldown_minutes = BASE_COOLDOWN_MINUTES + soft_score_threshold = 2.0 + + if capital_band == "micro": + price_trigger += 0.02 + pnl_trigger += 0.03 + portfolio_trigger += 0.04 + candidate_ratio += 0.25 + force_minutes += 180 + cooldown_minutes += 30 + soft_score_threshold += 1.0 + elif capital_band == "small": + price_trigger += 0.01 + pnl_trigger += 0.01 + portfolio_trigger += 0.01 + candidate_ratio += 0.1 + force_minutes += 60 + cooldown_minutes += 10 + soft_score_threshold += 0.5 + + if session_mode == "quiet": + price_trigger += 0.01 + pnl_trigger += 0.01 + portfolio_trigger += 0.01 + candidate_ratio += 0.05 + soft_score_threshold += 0.5 + else: + force_minutes = max(120, force_minutes - 30) + + if volatility_mode == "high": + price_trigger = max(0.02, price_trigger - 0.01) + pnl_trigger = max(0.025, pnl_trigger - 0.005) + portfolio_trigger = max(0.025, portfolio_trigger - 0.005) + candidate_ratio = max(1.1, candidate_ratio - 0.1) + cooldown_minutes = max(20, cooldown_minutes - 10) + soft_score_threshold = max(1.0, soft_score_threshold - 0.5) + + if dust_mode: + candidate_ratio += 0.3 + force_minutes += 180 + cooldown_minutes += 30 + soft_score_threshold += 1.5 + + return { + "capital_band": capital_band, + "session_mode": session_mode, + "volatility_mode": volatility_mode, + "dust_mode": dust_mode, + "price_move_trigger_pct": round(price_trigger, 4), + "pnl_trigger_pct": round(pnl_trigger, 4), + "portfolio_move_trigger_pct": round(portfolio_trigger, 4), + "candidate_score_trigger_ratio": round(candidate_ratio, 4), + "force_analysis_after_minutes": int(force_minutes), + "cooldown_minutes": int(cooldown_minutes), + "soft_score_threshold": round(soft_score_threshold, 2), + "new_entries_allowed": free_usdt >= MIN_ACTIONABLE_USDT and not dust_mode, + "switching_allowed": actionable_positions > 0 or portfolio_value >= 25, + } + + +def _candidate_weight(snapshot: dict, profile: dict) -> float: + if not profile.get("new_entries_allowed"): + return 0.5 + if profile.get("volatility_mode") == "high": + return 1.5 + if snapshot.get("session") in {"europe-open", "us-session"}: + return 1.25 + return 1.0 + + +def analyze_trigger(snapshot: dict, state: dict): + reasons = [] + details = list(state.get("_stale_recovery_notes", [])) + hard_reasons = [] + soft_reasons = [] + soft_score = 0.0 + + profile = build_adaptive_profile(snapshot) + market = snapshot.get("market_regime", {}) + now = utc_now() + + last_positions_hash = state.get("last_positions_hash") + last_portfolio_value = state.get("last_portfolio_value_usdt") + last_market_regime = state.get("last_market_regime", {}) + last_positions_map = state.get("last_positions_map", {}) + last_top_candidate = state.get("last_top_candidate") + pending_trigger = bool(state.get("pending_trigger")) + run_requested_at = parse_ts(state.get("run_requested_at")) + last_deep_analysis_at = parse_ts(state.get("last_deep_analysis_at")) + last_triggered_at = parse_ts(state.get("last_triggered_at")) + last_trigger_snapshot_hash = state.get("last_trigger_snapshot_hash") + last_hard_reasons_at = state.get("last_hard_reasons_at", {}) + + price_trigger = profile["price_move_trigger_pct"] + pnl_trigger = profile["pnl_trigger_pct"] + portfolio_trigger = profile["portfolio_move_trigger_pct"] + candidate_ratio_trigger = profile["candidate_score_trigger_ratio"] + force_minutes = profile["force_analysis_after_minutes"] + cooldown_minutes = profile["cooldown_minutes"] + soft_score_threshold = profile["soft_score_threshold"] + + if pending_trigger: + reasons.append("pending-trigger-unacked") + hard_reasons.append("pending-trigger-unacked") + details.append("上次已触发深度分析但尚未确认完成") + if run_requested_at: + details.append(f"外部门控已在 {run_requested_at.isoformat()} 请求运行分析任务") + + if not last_deep_analysis_at: + reasons.append("first-analysis") + hard_reasons.append("first-analysis") + details.append("尚未记录过深度分析") + elif now - last_deep_analysis_at >= timedelta(minutes=force_minutes): + reasons.append("stale-analysis") + hard_reasons.append("stale-analysis") + details.append(f"距离上次深度分析已超过 {force_minutes} 分钟") + + if last_positions_hash and snapshot["positions_hash"] != last_positions_hash: + reasons.append("positions-changed") + hard_reasons.append("positions-changed") + details.append("持仓结构发生变化") + + if last_portfolio_value not in (None, 0): + portfolio_delta = abs(snapshot["portfolio_value_usdt"] - last_portfolio_value) / max(last_portfolio_value, 1e-9) + if portfolio_delta >= portfolio_trigger: + if portfolio_delta >= 1.0: + reasons.append("portfolio-extreme-move") + hard_reasons.append("portfolio-extreme-move") + details.append(f"组合净值剧烈变化 {portfolio_delta:.1%}，超过 100%，视为硬触发") + else: + reasons.append("portfolio-move") + soft_reasons.append("portfolio-move") + soft_score += 1.0 + details.append(f"组合净值变化 {portfolio_delta:.1%}，阈值 {portfolio_trigger:.1%}") + + for pos in snapshot["positions"]: + symbol = pos["symbol"] + prev = last_positions_map.get(symbol, {}) + cur_price = pos.get("last_price") + prev_price = prev.get("last_price") + cur_pnl = pos.get("pnl_pct") + prev_pnl = prev.get("pnl_pct") + market_value = to_float(pos.get("market_value_usdt"), 0) + actionable_position = market_value >= MIN_REAL_POSITION_VALUE_USDT + + if cur_price and prev_price: + price_move = abs(cur_price - prev_price) / max(prev_price, 1e-9) + if price_move >= price_trigger: + reasons.append(f"price-move:{symbol}") + soft_reasons.append(f"price-move:{symbol}") + soft_score += 1.0 if actionable_position else 0.4 + details.append(f"{symbol} 价格变化 {price_move:.1%}，阈值 {price_trigger:.1%}") + if cur_pnl is not None and prev_pnl is not None: + pnl_move = abs(cur_pnl - prev_pnl) + if pnl_move >= pnl_trigger: + reasons.append(f"pnl-move:{symbol}") + soft_reasons.append(f"pnl-move:{symbol}") + soft_score += 1.0 if actionable_position else 0.4 + details.append(f"{symbol} 盈亏变化 {pnl_move:.1%}，阈值 {pnl_trigger:.1%}") + if cur_pnl is not None: + stop_band = -0.06 if actionable_position else -0.12 + take_band = 0.14 if actionable_position else 0.25 + if cur_pnl <= stop_band or cur_pnl >= take_band: + reasons.append(f"risk-band:{symbol}") + hard_reasons.append(f"risk-band:{symbol}") + details.append(f"{symbol} 接近执行阈值，当前盈亏 {cur_pnl:.1%}") + if cur_pnl <= HARD_STOP_PCT: + reasons.append(f"hard-stop:{symbol}") + hard_reasons.append(f"hard-stop:{symbol}") + details.append(f"{symbol} 盈亏超过 {HARD_STOP_PCT:.1%}，触发紧急硬触发") + + current_market = snapshot.get("market_regime", {}) + if last_market_regime: + if current_market.get("btc_regime") != last_market_regime.get("btc_regime"): + reasons.append("btc-regime-change") + hard_reasons.append("btc-regime-change") + details.append(f"BTC 由 {last_market_regime.get('btc_regime')} 切换为 {current_market.get('btc_regime')}") + if current_market.get("eth_regime") != last_market_regime.get("eth_regime"): + reasons.append("eth-regime-change") + hard_reasons.append("eth-regime-change") + details.append(f"ETH 由 {last_market_regime.get('eth_regime')} 切换为 {current_market.get('eth_regime')}") + + for cand in snapshot.get("top_candidates", []): + if cand.get("change_24h_pct", 0) >= HARD_MOON_PCT * 100: + reasons.append(f"hard-moon:{cand['symbol']}") + hard_reasons.append(f"hard-moon:{cand['symbol']}") + details.append(f"候选币 {cand['symbol']} 24h 涨幅 {cand['change_24h_pct']:.1f}%，触发强势硬触发") + + candidate_weight = _candidate_weight(snapshot, profile) + + last_layers = state.get("last_candidates_layers", {}) + current_layers = snapshot.get("top_candidates_layers", {}) + for band in ("major", "mid", "meme"): + cur_band = current_layers.get(band, []) + prev_band = last_layers.get(band, []) + cur_leader = cur_band[0] if cur_band else None + prev_leader = prev_band[0] if prev_band else None + if cur_leader and prev_leader and cur_leader["symbol"] != prev_leader["symbol"]: + score_ratio = cur_leader.get("score", 0) / max(prev_leader.get("score", 0.0001), 0.0001) + if score_ratio >= candidate_ratio_trigger: + reasons.append(f"new-leader-{band}:{cur_leader['symbol']}") + soft_reasons.append(f"new-leader-{band}:{cur_leader['symbol']}") + soft_score += candidate_weight * 0.7 + details.append( + f"{band} 层新榜首 {cur_leader['symbol']} 替代 {prev_leader['symbol']}，score 比例 {score_ratio:.2f}" + ) + + current_leader = snapshot.get("top_candidates", [{}])[0] if snapshot.get("top_candidates") else None + if last_top_candidate and current_leader: + if current_leader.get("symbol") != last_top_candidate.get("symbol"): + score_ratio = current_leader.get("score", 0) / max(last_top_candidate.get("score", 0.0001), 0.0001) + if score_ratio >= candidate_ratio_trigger: + reasons.append("new-leader") + soft_reasons.append("new-leader") + soft_score += candidate_weight + details.append( + f"新候选币 {current_leader.get('symbol')} 领先上次榜首，score 比例 {score_ratio:.2f}，阈值 {candidate_ratio_trigger:.2f}" + ) + elif current_leader and not last_top_candidate: + reasons.append("candidate-leader-init") + soft_reasons.append("candidate-leader-init") + soft_score += candidate_weight + details.append(f"首次记录候选榜首 {current_leader.get('symbol')}") + + def _signal_delta() -> float: + delta = 0.0 + if last_trigger_snapshot_hash and snapshot.get("snapshot_hash") != last_trigger_snapshot_hash: + delta += 0.5 + if snapshot["positions_hash"] != last_positions_hash: + delta += 1.5 + for pos in snapshot["positions"]: + symbol = pos["symbol"] + prev = last_positions_map.get(symbol, {}) + cur_price = pos.get("last_price") + prev_price = prev.get("last_price") + cur_pnl = pos.get("pnl_pct") + prev_pnl = prev.get("pnl_pct") + if cur_price and prev_price and abs(cur_price - prev_price) / max(prev_price, 1e-9) >= 0.02: + delta += 0.5 + if cur_pnl is not None and prev_pnl is not None and abs(cur_pnl - prev_pnl) >= 0.03: + delta += 0.5 + last_leader = state.get("last_top_candidate") + if current_leader and last_leader and current_leader.get("symbol") != last_leader.get("symbol"): + delta += 1.0 + for band in ("major", "mid", "meme"): + cur_band = current_layers.get(band, []) + prev_band = last_layers.get(band, []) + cur_l = cur_band[0] if cur_band else None + prev_l = prev_band[0] if prev_band else None + if cur_l and prev_l and cur_l.get("symbol") != prev_l.get("symbol"): + delta += 0.5 + if last_market_regime: + if current_market.get("btc_regime") != last_market_regime.get("btc_regime"): + delta += 1.5 + if current_market.get("eth_regime") != last_market_regime.get("eth_regime"): + delta += 1.5 + if last_portfolio_value not in (None, 0): + portfolio_delta = abs(snapshot["portfolio_value_usdt"] - last_portfolio_value) / max(last_portfolio_value, 1e-9) + if portfolio_delta >= 0.05: + delta += 1.0 + last_trigger_hard_types = {r.split(":")[0] for r in (state.get("last_trigger_hard_reasons") or [])} + current_hard_types = {r.split(":")[0] for r in hard_reasons} + if current_hard_types - last_trigger_hard_types: + delta += 2.0 + return delta + + signal_delta = _signal_delta() + effective_cooldown = cooldown_minutes + if signal_delta < 1.0: + effective_cooldown = max(cooldown_minutes, 90) + elif signal_delta >= 2.5: + effective_cooldown = max(0, cooldown_minutes - 15) + + cooldown_active = bool(last_triggered_at and now - last_triggered_at < timedelta(minutes=effective_cooldown)) + + dedup_window = timedelta(minutes=HARD_REASON_DEDUP_MINUTES) + for hr in list(hard_reasons): + last_at = parse_ts(last_hard_reasons_at.get(hr)) + if last_at and now - last_at < dedup_window: + hard_reasons.remove(hr) + details.append(f"{hr} 近期已触发，{HARD_REASON_DEDUP_MINUTES}分钟内去重") + + hard_trigger = bool(hard_reasons) + if profile.get("dust_mode") and not hard_trigger and soft_score < soft_score_threshold + 1.0: + details.append("微型资金/粉尘仓位模式：抬高软触发门槛，避免无意义分析") + + if profile.get("dust_mode") and not profile.get("new_entries_allowed") and any( + r in {"new-leader", "candidate-leader-init"} for r in soft_reasons + ): + details.append("当前可用资金低于可执行阈值，新候选币仅做观察，不单独触发深度分析") + soft_score = max(0.0, soft_score - 0.75) + + should_analyze = hard_trigger or soft_score >= soft_score_threshold + + if cooldown_active and not hard_trigger and should_analyze: + should_analyze = False + details.append(f"处于 {cooldown_minutes} 分钟冷却窗口，软触发先记录不升级") + + if cooldown_active and not hard_trigger and reasons and soft_score < soft_score_threshold: + details.append(f"处于 {cooldown_minutes} 分钟冷却窗口，且软信号强度不足 ({soft_score:.2f} < {soft_score_threshold:.2f})") + + status = "deep_analysis_required" if should_analyze else "stable" + + compact_lines = [ + f"状态: {status}", + f"组合净值: ${snapshot['portfolio_value_usdt']:.4f} | 可用USDT: ${snapshot['free_usdt']:.4f}", + f"本地时段: {snapshot['session']} | 时区: {snapshot['timezone']}", + f"BTC/ETH: {market.get('btc_regime')} ({market.get('btc_24h_pct')}%), {market.get('eth_regime')} ({market.get('eth_24h_pct')}%) | 波动分数 {market.get('volatility_score')}", + f"门控画像: capital={profile['capital_band']}, session={profile['session_mode']}, volatility={profile['volatility_mode']}, dust={profile['dust_mode']}", + f"阈值: price={price_trigger:.1%}, pnl={pnl_trigger:.1%}, portfolio={portfolio_trigger:.1%}, candidate={candidate_ratio_trigger:.2f}, cooldown={effective_cooldown}m({cooldown_minutes}m基础), force={force_minutes}m", + f"软信号分: {soft_score:.2f} / {soft_score_threshold:.2f}", + f"信号变化度: {signal_delta:.1f}", + ] + if snapshot["positions"]: + compact_lines.append("持仓:") + for pos in snapshot["positions"][:4]: + pnl = pos.get("pnl_pct") + pnl_text = f"{pnl:+.1%}" if pnl is not None else "n/a" + compact_lines.append( + f"- {pos['symbol']}: qty={pos['quantity']}, px={pos.get('last_price')}, pnl={pnl_text}, value=${pos.get('market_value_usdt')}" + ) + else: + compact_lines.append("持仓: 当前无现货仓位") + if snapshot["top_candidates"]: + compact_lines.append("候选榜:") + for cand in snapshot["top_candidates"]: + compact_lines.append( + f"- {cand['symbol']}: score={cand['score']}, 24h={cand['change_24h_pct']}%, vol=${cand['volume_24h']}" + ) + layers = snapshot.get("top_candidates_layers", {}) + for band, band_cands in layers.items(): + if band_cands: + compact_lines.append(f"{band} 层:") + for cand in band_cands: + compact_lines.append( + f"- {cand['symbol']}: score={cand['score']}, 24h={cand['change_24h_pct']}%, vol=${cand['volume_24h']}" + ) + if details: + compact_lines.append("触发说明:") + for item in details: + compact_lines.append(f"- {item}") + + return { + "generated_at": snapshot["generated_at"], + "status": status, + "should_analyze": should_analyze, + "pending_trigger": pending_trigger, + "run_requested": bool(run_requested_at), + "run_requested_at": run_requested_at.isoformat() if run_requested_at else None, + "cooldown_active": cooldown_active, + "effective_cooldown_minutes": effective_cooldown, + "signal_delta": round(signal_delta, 2), + "reasons": reasons, + "hard_reasons": hard_reasons, + "soft_reasons": soft_reasons, + "soft_score": round(soft_score, 3), + "adaptive_profile": profile, + "portfolio_value_usdt": snapshot["portfolio_value_usdt"], + "free_usdt": snapshot["free_usdt"], + "market_regime": snapshot["market_regime"], + "session": snapshot["session"], + "positions": snapshot["positions"], + "top_candidates": snapshot["top_candidates"], + "top_candidates_layers": layers, + "snapshot_hash": snapshot["snapshot_hash"], + "compact_summary": "\n".join(compact_lines), + "details": details, + } + + +def update_state_after_observation(state: dict, snapshot: dict, analysis: dict): + new_state = dict(state) + new_state.update({ + "last_observed_at": snapshot["generated_at"], + "last_snapshot_hash": snapshot["snapshot_hash"], + "last_positions_hash": snapshot["positions_hash"], + "last_candidates_hash": snapshot["candidates_hash"], + "last_portfolio_value_usdt": snapshot["portfolio_value_usdt"], + "last_market_regime": snapshot["market_regime"], + "last_positions_map": { + p["symbol"]: {"last_price": p.get("last_price"), "pnl_pct": p.get("pnl_pct")} + for p in snapshot["positions"] + }, + "last_top_candidate": snapshot["top_candidates"][0] if snapshot["top_candidates"] else None, + "last_candidates_layers": snapshot.get("top_candidates_layers", {}), + "last_adaptive_profile": analysis.get("adaptive_profile", {}), + }) + if analysis["should_analyze"]: + new_state["pending_trigger"] = True + new_state["pending_reasons"] = analysis["details"] + new_state["last_triggered_at"] = snapshot["generated_at"] + new_state["last_trigger_snapshot_hash"] = snapshot["snapshot_hash"] + new_state["last_trigger_hard_reasons"] = analysis.get("hard_reasons", []) + new_state["last_trigger_signal_delta"] = analysis.get("signal_delta", 0.0) + + last_hard_reasons_at = dict(state.get("last_hard_reasons_at", {})) + for hr in analysis.get("hard_reasons", []): + last_hard_reasons_at[hr] = snapshot["generated_at"] + cutoff = utc_now() - timedelta(hours=24) + pruned = {k: v for k, v in last_hard_reasons_at.items() if parse_ts(v) and parse_ts(v) > cutoff} + new_state["last_hard_reasons_at"] = pruned + return new_state diff --git a/src/coinhunter/services/precheck_snapshot.py b/src/coinhunter/services/precheck_snapshot.py index 81ac936..649ffaf 100644 --- a/src/coinhunter/services/precheck_snapshot.py +++ b/src/coinhunter/services/precheck_snapshot.py @@ -2,8 +2,8 @@ from __future__ import annotations -from .. import precheck as precheck_module +from . import precheck_core def build_snapshot() -> dict: - return precheck_module.build_snapshot() + return precheck_core.build_snapshot() diff --git a/src/coinhunter/services/precheck_state.py b/src/coinhunter/services/precheck_state.py index d05639b..c6665fd 100644 --- a/src/coinhunter/services/precheck_state.py +++ b/src/coinhunter/services/precheck_state.py @@ -4,28 +4,28 @@ from __future__ import annotations import json -from .. import precheck as precheck_module +from . import precheck_core def load_state() -> dict: - return precheck_module.load_state() + return precheck_core.load_state() def save_state(state: dict) -> None: - precheck_module.save_state(state) + precheck_core.save_state(state) def sanitize_state_for_stale_triggers(state: dict) -> dict: - return precheck_module.sanitize_state_for_stale_triggers(state) + return precheck_core.sanitize_state_for_stale_triggers(state) def update_state_after_observation(state: dict, snapshot: dict, analysis: dict) -> dict: - return precheck_module.update_state_after_observation(state, snapshot, analysis) + return precheck_core.update_state_after_observation(state, snapshot, analysis) def mark_run_requested(note: str = "") -> dict: state = load_state() - state["run_requested_at"] = precheck_module.utc_iso() + state["run_requested_at"] = precheck_core.utc_iso() state["run_request_note"] = note save_state(state) payload = {"ok": True, "run_requested_at": state["run_requested_at"], "note": note} @@ -35,7 +35,7 @@ def mark_run_requested(note: str = "") -> dict: def ack_analysis(note: str = "") -> dict: state = load_state() - state["last_deep_analysis_at"] = precheck_module.utc_iso() + state["last_deep_analysis_at"] = precheck_core.utc_iso() state["pending_trigger"] = False state["pending_reasons"] = [] state["last_ack_note"] = note diff --git a/src/coinhunter/smart_executor.py b/src/coinhunter/smart_executor.py old mode 100755 new mode 100644 index 8269aef..3154971 --- a/src/coinhunter/smart_executor.py +++ b/src/coinhunter/smart_executor.py @@ -1,28 +1,99 @@ #!/usr/bin/env python3 -"""Coin Hunter robust smart executor — compatibility facade.""" +"""Backward-compatible facade for smart executor workflows. + +The executable implementation lives in ``coinhunter.services.smart_executor_service``. +This module stays importable for older callers without importing the whole trading +stack up front. +""" + +from __future__ import annotations import sys +from importlib import import_module -from .runtime import get_runtime_paths, load_env_file -from .services.trade_common import CST, is_dry_run, USDT_BUFFER_PCT, MIN_REMAINING_DUST_USDT, log, bj_now_iso, set_dry_run -from .services.file_utils import locked_file, atomic_write_json, load_json_locked, save_json_locked -from .services.smart_executor_parser import build_parser, normalize_legacy_argv, parse_cli_args, cli_action_args -from .services.execution_state import default_decision_id, record_execution_state, get_execution_state, load_executions, save_executions -from .services.portfolio_service import load_positions, save_positions, upsert_position, reconcile_positions_with_exchange -from .services.exchange_service import get_exchange, norm_symbol, storage_symbol, fetch_balances, build_market_snapshot, market_and_ticker, floor_to_step, prepare_buy_quantity, prepare_sell_quantity -from .services.trade_execution import build_decision_context, market_sell, market_buy, action_sell_all, action_buy, action_rebalance, command_status, command_balances from .services.smart_executor_service import run as _run_service -PATHS = get_runtime_paths() -ENV_FILE = PATHS.env_file +_EXPORT_MAP = { + "PATHS": (".runtime", "get_runtime_paths"), + "ENV_FILE": (".runtime", "get_runtime_paths"), + "load_env_file": (".runtime", "load_env_file"), + "CST": (".services.trade_common", "CST"), + "USDT_BUFFER_PCT": (".services.trade_common", "USDT_BUFFER_PCT"), + "MIN_REMAINING_DUST_USDT": (".services.trade_common", "MIN_REMAINING_DUST_USDT"), + "is_dry_run": (".services.trade_common", "is_dry_run"), + "log": (".services.trade_common", "log"), + "bj_now_iso": (".services.trade_common", "bj_now_iso"), + "set_dry_run": (".services.trade_common", "set_dry_run"), + "locked_file": (".services.file_utils", "locked_file"), + "atomic_write_json": (".services.file_utils", "atomic_write_json"), + "load_json_locked": (".services.file_utils", "load_json_locked"), + "save_json_locked": (".services.file_utils", "save_json_locked"), + "build_parser": (".services.smart_executor_parser", "build_parser"), + "normalize_legacy_argv": (".services.smart_executor_parser", "normalize_legacy_argv"), + "parse_cli_args": (".services.smart_executor_parser", "parse_cli_args"), + "cli_action_args": (".services.smart_executor_parser", "cli_action_args"), + "default_decision_id": (".services.execution_state", "default_decision_id"), + "record_execution_state": (".services.execution_state", "record_execution_state"), + "get_execution_state": (".services.execution_state", "get_execution_state"), + "load_executions": (".services.execution_state", "load_executions"), + "save_executions": (".services.execution_state", "save_executions"), + "load_positions": (".services.portfolio_service", "load_positions"), + "save_positions": (".services.portfolio_service", "save_positions"), + "upsert_position": (".services.portfolio_service", "upsert_position"), + "reconcile_positions_with_exchange": (".services.portfolio_service", "reconcile_positions_with_exchange"), + "get_exchange": (".services.exchange_service", "get_exchange"), + "norm_symbol": (".services.exchange_service", "norm_symbol"), + "storage_symbol": (".services.exchange_service", "storage_symbol"), + "fetch_balances": (".services.exchange_service", "fetch_balances"), + "build_market_snapshot": (".services.exchange_service", "build_market_snapshot"), + "market_and_ticker": (".services.exchange_service", "market_and_ticker"), + "floor_to_step": (".services.exchange_service", "floor_to_step"), + "prepare_buy_quantity": (".services.exchange_service", "prepare_buy_quantity"), + "prepare_sell_quantity": (".services.exchange_service", "prepare_sell_quantity"), + "build_decision_context": (".services.trade_execution", "build_decision_context"), + "market_sell": (".services.trade_execution", "market_sell"), + "market_buy": (".services.trade_execution", "market_buy"), + "action_sell_all": (".services.trade_execution", "action_sell_all"), + "action_buy": (".services.trade_execution", "action_buy"), + "action_rebalance": (".services.trade_execution", "action_rebalance"), + "command_status": (".services.trade_execution", "command_status"), + "command_balances": (".services.trade_execution", "command_balances"), +} + +__all__ = sorted(set(_EXPORT_MAP) | {"ENV_FILE", "PATHS", "load_env", "main"}) + + +def __getattr__(name: str): + if name == "PATHS": + runtime = import_module(".runtime", __package__) + return runtime.get_runtime_paths() + if name == "ENV_FILE": + runtime = import_module(".runtime", __package__) + return runtime.get_runtime_paths().env_file + if name == "load_env": + return load_env + if name not in _EXPORT_MAP: + raise AttributeError(f"module {__name__!r} has no attribute {name!r}") + module_name, attr_name = _EXPORT_MAP[name] + module = import_module(module_name, __package__) + if name == "PATHS": + return getattr(module, attr_name)() + if name == "ENV_FILE": + return getattr(module, attr_name)().env_file + return getattr(module, attr_name) + + +def __dir__(): + return sorted(set(globals()) | set(__all__)) def load_env(): - load_env_file(PATHS) + runtime = import_module(".runtime", __package__) + runtime.load_env_file(runtime.get_runtime_paths()) def main(argv=None): - return _run_service(argv) + return _run_service(sys.argv[1:] if argv is None else argv) if __name__ == "__main__":