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DOLPHIN/prod/nautilus_event_trader.py.pre_acb_fix_bak

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#!/usr/bin/env python3
"""
DOLPHIN Nautilus Event-Driven Trader
"""
import sys
import json
import math
import time
import signal
import threading
from concurrent.futures import ThreadPoolExecutor
from datetime import datetime, timezone
from pathlib import Path
from collections import deque
# Stablecoins / pegged assets that must never be traded
_STABLECOIN_SYMBOLS = frozenset({
'USDCUSDT', 'BUSDUSDT', 'FDUSDUSDT', 'USDTUSDT', 'TUSDUSDT',
'DAIUSDT', 'FRAXUSDT', 'USDDUSDT', 'USTCUSDT', 'EURUSDT',
})
sys.path.insert(0, '/mnt/dolphinng5_predict')
sys.path.insert(0, '/mnt/dolphinng5_predict/nautilus_dolphin')
from nautilus_dolphin.nautilus.proxy_boost_engine import create_d_liq_engine
from nautilus_dolphin.nautilus.adaptive_circuit_breaker import AdaptiveCircuitBreaker
from nautilus_dolphin.nautilus.ob_features import OBFeatureEngine
from nautilus_dolphin.nautilus.ob_provider import MockOBProvider
try:
from ch_writer import ch_put, ts_us as _ch_ts_us
except ImportError:
def ch_put(*a, **kw): pass
def _ch_ts_us(): return 0
sys.path.insert(0, '/mnt/dolphinng5_predict/prod')
from dolphin_exit_handler import install_exit_handler
install_exit_handler("nautilus_trader")
HZ_CLUSTER = "dolphin"
HZ_HOST = "127.0.0.1:5701"
EIGEN_DIR = Path('/mnt/dolphinng6_data/eigenvalues')
CAPITAL_DISK_CHECKPOINT = Path("/tmp/dolphin_capital_checkpoint.json")
ENGINE_KWARGS = dict(
initial_capital=25000.0, vel_div_threshold=-0.02, vel_div_extreme=-0.05,
min_leverage=0.5, max_leverage=8.0, # note: create_d_liq_engine overrides to D_LIQ_SOFT_CAP=8.0
leverage_convexity=3.0,
fraction=0.20, fixed_tp_pct=0.0095, stop_pct=1.0, max_hold_bars=250, # gold spec: 250
use_direction_confirm=True, dc_lookback_bars=7, dc_min_magnitude_bps=0.75,
dc_skip_contradicts=True, dc_leverage_boost=1.0, dc_leverage_reduce=0.5,
use_asset_selection=True, min_irp_alignment=0.0, # gold spec: no IRP filter
use_sp_fees=True, use_sp_slippage=True,
sp_maker_entry_rate=0.62, sp_maker_exit_rate=0.50,
use_ob_edge=True, ob_edge_bps=5.0, ob_confirm_rate=0.40,
lookback=100, use_alpha_layers=True, use_dynamic_leverage=True, seed=42,
)
BTC_VOL_WINDOW = 50
# Gold-calibrated from full 5-year BTC history: 0.00026414 (stricter, ~2.7x tighter).
# 2026-04-07: switched to 56-day gold window value (0.00009868) — the exact threshold
# used in the T=2155 ROI=+189% backtest. More permissive; paper trading to gather data.
VOL_P60_THRESHOLD = 0.00009868
# Algorithm Versioning
# v1_shakedown: v50-v150 (noise bug), loose vol gate
# v2_gold_fix: CORRECTED v50-v750 macro divergence (matches parquet backtest)
ALGO_VERSION = "v2_gold_fix_v50-v750"
# Persistent, version-tagged trade log (survives reboots; sorts by date)
_LOG_DIR = "/mnt/dolphinng5_predict/prod/logs"
import os as _os; _os.makedirs(_LOG_DIR, exist_ok=True)
_LOG_DATE = datetime.now(timezone.utc).strftime("%Y%m%d")
TRADE_LOG = f"{_LOG_DIR}/nautilus_trader_{_LOG_DATE}_{ALGO_VERSION}.log"
running = True
def log(msg):
ts = datetime.now(timezone.utc).isoformat()
line = f"[{ts}] {msg}"
print(line, flush=True)
with open(TRADE_LOG, 'a') as f:
f.write(line + '\n')
class DolphinLiveTrader:
def __init__(self):
self.eng = None
self.hz_client = None
self.features_map = None
self.safety_map = None
self.pnl_map = None
self.state_map = None
self.heartbeat_map = None
self.eng_lock = threading.Lock()
self._dedup_lock = threading.Lock() # guards atomic check-and-set on last_scan_number
self._scan_executor = ThreadPoolExecutor(max_workers=1, thread_name_prefix="scan")
self.last_scan_number = -1
self.last_file_mtime = 0
self.bar_idx = 0
self.current_day = None
self.trades_executed = 0
self.scans_processed = 0
self.btc_prices = deque(maxlen=BTC_VOL_WINDOW + 2)
self.cached_posture = "APEX"
self.posture_cache_time = 0
self.ob_assets = []
self.ob_eng = None
self.acb = None
self.last_w750_vel = None
self._pending_entries: dict = {} # trade_id → entry snapshot (for CH trade_events)
self._exf_log_time = 0.0 # throttle for on_exf_update logging
def _build_engine(self):
log("Building NDAlphaEngine...")
self.eng = create_d_liq_engine(**ENGINE_KWARGS)
log(f" Engine: {type(self.eng).__name__}")
log(f" Leverage: soft={self.eng.base_max_leverage}x abs={self.eng.abs_max_leverage}x")
if EIGEN_DIR.exists():
try:
date_strings = sorted([d.name for d in EIGEN_DIR.iterdir() if d.is_dir()])
self.acb = AdaptiveCircuitBreaker()
self.acb.preload_w750(date_strings)
self.eng.set_acb(self.acb)
log(" ACBv6: loaded")
except Exception as e:
log(f" ACBv6: {e}")
else:
self.acb = AdaptiveCircuitBreaker()
self.eng.set_acb(self.acb)
log(" ACBv6: loaded (no preload dates)")
self.eng.set_esoteric_hazard_multiplier(0.0) # gold spec: init guard, MUST precede set_mc_forewarner
log(f" Hazard: set_esoteric_hazard_multiplier(0.0) — soft={self.eng.base_max_leverage}x")
MC_MODELS_DIR = '/mnt/dolphinng5_predict/nautilus_dolphin/mc_results/models'
MC_BASE_CFG = {
'trial_id': 0, 'vel_div_threshold': -0.020, 'vel_div_extreme': -0.050,
'use_direction_confirm': True, 'dc_lookback_bars': 7,
'dc_min_magnitude_bps': 0.75, 'dc_skip_contradicts': True,
'dc_leverage_boost': 1.00, 'dc_leverage_reduce': 0.50,
'vd_trend_lookback': 10, 'min_leverage': 0.50, 'max_leverage': 8.00, # gold spec
'leverage_convexity': 3.00, 'fraction': 0.20, 'use_alpha_layers': True,
'use_dynamic_leverage': True, 'fixed_tp_pct': 0.0095, 'stop_pct': 1.00,
'max_hold_bars': 250, 'use_sp_fees': True, 'use_sp_slippage': True, # gold spec
'sp_maker_entry_rate': 0.62, 'sp_maker_exit_rate': 0.50,
'use_ob_edge': True, 'ob_edge_bps': 5.00, 'ob_confirm_rate': 0.40,
'ob_imbalance_bias': -0.09, 'ob_depth_scale': 1.00,
'use_asset_selection': True, 'min_irp_alignment': 0.0, 'lookback': 100, # gold spec
'acb_beta_high': 0.80, 'acb_beta_low': 0.20, 'acb_w750_threshold_pct': 60,
}
if Path(MC_MODELS_DIR).exists():
try:
from mc.mc_ml import DolphinForewarner
forewarner = DolphinForewarner(models_dir=MC_MODELS_DIR)
self.eng.set_mc_forewarner(forewarner, MC_BASE_CFG)
log(" MC-Forewarner: wired")
except Exception as e:
log(f" MC-Forewarner: {e}")
def _connect_hz(self):
log("Connecting to Hazelcast...")
import hazelcast
self.hz_client = hazelcast.HazelcastClient(cluster_name=HZ_CLUSTER, cluster_members=[HZ_HOST])
self.features_map = self.hz_client.get_map("DOLPHIN_FEATURES")
self.safety_map = self.hz_client.get_map("DOLPHIN_SAFETY")
self.pnl_map = self.hz_client.get_map("DOLPHIN_PNL_BLUE")
self.state_map = self.hz_client.get_map("DOLPHIN_STATE_BLUE")
self.heartbeat_map = self.hz_client.get_map("DOLPHIN_HEARTBEAT")
# Immediate heartbeat — prevents Cat1=0 during startup gap
try:
self.heartbeat_map.blocking().put('nautilus_flow_heartbeat', json.dumps({
'ts': time.time(),
'iso': datetime.now(timezone.utc).isoformat(),
'phase': 'starting',
'flow': 'nautilus_event_trader',
}))
except Exception:
pass
log(" Hz connected")
def _read_posture(self):
now = time.time()
if now - self.posture_cache_time < 10:
return self.cached_posture
try:
posture_raw = self.safety_map.blocking().get("latest") or self.safety_map.blocking().get("posture")
if posture_raw:
if isinstance(posture_raw, str):
try:
parsed = json.loads(posture_raw)
self.cached_posture = parsed.get("posture", posture_raw)
except (json.JSONDecodeError, AttributeError):
self.cached_posture = posture_raw
else:
self.cached_posture = posture_raw.get("posture", "APEX")
self.posture_cache_time = now
except:
pass
return self.cached_posture
def _rollover_day(self):
today = datetime.now(timezone.utc).strftime('%Y-%m-%d')
if today == self.current_day:
return
posture = self._read_posture()
with self.eng_lock:
if today != self.current_day: # double-checked: only one thread calls begin_day
if getattr(self, 'acb', None):
try:
exf_raw = self.features_map.blocking().get('exf_latest') if self.features_map else None
es_raw = self.features_map.blocking().get('latest_eigen_scan') if self.features_map else None
exf_snapshot = json.loads(exf_raw) if isinstance(exf_raw, str) else (exf_raw or {})
eigen_scan = json.loads(es_raw) if isinstance(es_raw, str) else (es_raw or {})
w750_vel = eigen_scan.get('w750_velocity', 0.0)
if exf_snapshot:
self.acb.get_dynamic_boost_from_hz(
date_str=today,
exf_snapshot=exf_snapshot,
w750_velocity=float(w750_vel) if w750_vel else None
)
log(f"ACB: Pre-warmed cache for {today} from HZ")
except Exception as e:
log(f"ACB Rollover Error: {e}")
self.eng.begin_day(today, posture=posture)
self.bar_idx = 0
self.current_day = today
log(f"begin_day({today}) called with posture={posture}")
def _compute_vol_ok(self, scan):
assets = scan.get('assets', [])
prices = scan.get('asset_prices', [])
if not assets or not prices:
return True
prices_dict = dict(zip(assets, prices))
btc_price = prices_dict.get('BTCUSDT')
if btc_price is None:
return True
self.btc_prices.append(float(btc_price))
if len(self.btc_prices) < BTC_VOL_WINDOW:
return True
import numpy as np
arr = np.array(self.btc_prices)
dvol = float(np.std(np.diff(arr) / arr[:-1]))
return dvol > VOL_P60_THRESHOLD
@staticmethod
def _normalize_ng7(scan: dict) -> dict:
"""
Promote NG7-format scan to NG5-compatible flat dict.
NG7 embeds eigenvalue windows and prices inside result{} — the engine
expects flat top-level fields. Mapping derived from continuous_convert.py:
vel_div = w50_velocity w750_velocity (fast minus slow eigenvalue velocity)
w50_velocity = multi_window_results["50"].tracking_data.lambda_max_velocity
w750_velocity = multi_window_results["750"].tracking_data.lambda_max_velocity
assets = sorted(current_prices.keys()), BTCUSDT always last
"""
result = scan.get('result') or {}
mw = result.get('multi_window_results') or {}
def _vel(win):
v = (mw.get(str(win)) or {}).get('tracking_data', {}).get('lambda_max_velocity')
try:
f = float(v)
return f if math.isfinite(f) else 0.0
except (TypeError, ValueError):
return 0.0
v50 = _vel(50)
v150 = _vel(150)
v750 = _vel(750)
cp = (result.get('pricing_data') or {}).get('current_prices') or {}
assets = [a for a in cp if a != 'BTCUSDT']
if 'BTCUSDT' in cp:
assets.append('BTCUSDT') # BTC always last — matches NG5/Arrow convention
prices = [float(cp[a]) for a in assets]
instability = float((result.get('regime_prediction') or {})
.get('instability_score') or 0.0)
return {
**scan,
'vel_div': v50 - v750,
'w50_velocity': v50,
'w750_velocity': v750,
'assets': assets,
'asset_prices': prices,
'instability_50': instability,
}
def on_scan(self, event):
"""Reactor-thread entry point — dispatches immediately to worker thread."""
if not event.value:
return
listener_time = time.time()
self._scan_executor.submit(self._process_scan, event, listener_time)
def _process_scan(self, event, listener_time):
try:
if not event.value:
return
scan = json.loads(event.value) if isinstance(event.value, str) else event.value
# Normalise NG7 format → NG5-compatible flat dict before any field access
if scan.get('version') == 'NG7':
scan = self._normalize_ng7(scan)
scan_number = int(scan.get('scan_number') or 0)
# Dedup: scan_number is authoritative (monotonically increasing).
# file_mtime / timestamp are unreliable across NG7 restart probes.
with self._dedup_lock:
if scan_number > 0 and scan_number <= self.last_scan_number:
return
self.last_scan_number = scan_number
self.scans_processed += 1
self._rollover_day()
assets = scan.get('assets') or []
if assets and not self.ob_assets:
self._wire_obf(assets)
prices = scan.get('asset_prices') or []
if assets and prices and len(assets) != len(prices):
log(f"WARN scan #{scan_number}: assets/prices mismatch "
f"({len(assets)}≠{len(prices)}) — dropped")
return
prices_dict = dict(zip(assets, prices)) if assets and prices else {}
# Remove stablecoins — they should never be selected as a trade asset
for sym in _STABLECOIN_SYMBOLS:
prices_dict.pop(sym, None)
vol_ok = self._compute_vol_ok(scan)
vel_div = float(scan.get('vel_div') or 0.0)
if not math.isfinite(vel_div):
log(f"WARN scan #{scan_number}: non-finite vel_div={vel_div} — clamped to 0.0")
vel_div = 0.0
v50_vel = float(scan.get('w50_velocity') or 0.0)
v750_vel = float(scan.get('w750_velocity') or 0.0)
if not math.isfinite(v50_vel): v50_vel = 0.0
if not math.isfinite(v750_vel): v750_vel = 0.0
self.last_w750_vel = v750_vel
# Feed live OB data into OBF engine for this bar (AGENT_SPEC_OBF_LIVE_SWITCHOVER)
if self.ob_eng is not None and self.ob_assets:
self.ob_eng.step_live(self.ob_assets, self.bar_idx)
# Live posture sync — update engine posture + regime_dd_halt together
posture_now = self._read_posture()
with self.eng_lock:
prev_posture = getattr(self.eng, '_day_posture', 'APEX')
if posture_now != prev_posture:
self.eng._day_posture = posture_now
if posture_now in ('TURTLE', 'HIBERNATE'):
self.eng.regime_dd_halt = True
log(f"POSTURE_SYNC: {posture_now} — halt set")
else:
self.eng.regime_dd_halt = False
log(f"POSTURE_SYNC: {posture_now} — halt lifted")
step_start = time.time()
with self.eng_lock:
result = self.eng.step_bar(
bar_idx=self.bar_idx, vel_div=vel_div, prices=prices_dict,
vol_regime_ok=vol_ok, v50_vel=v50_vel, v750_vel=v750_vel
)
self.bar_idx += 1
scan_to_fill_ms = (time.time() - listener_time) * 1000
step_bar_ms = (time.time() - step_start) * 1000
log(f"LATENCY scan #{scan_number}: scan→fill={scan_to_fill_ms:.1f}ms step_bar={step_bar_ms:.1f}ms vel_div={vel_div:.5f}")
ch_put("eigen_scans", {
"ts": _ch_ts_us(),
"scan_number": scan_number,
"scan_uuid": str(scan.get("scan_uuid") or ""),
"vel_div": vel_div,
"w50_velocity": v50_vel,
"w750_velocity": v750_vel,
"instability_50": float(scan.get("instability_50") or 0.0),
"scan_to_fill_ms": scan_to_fill_ms,
"step_bar_ms": step_bar_ms,
})
if result.get('entry'):
self.trades_executed += 1
e = result['entry']
log(f"ENTRY: {e} [{ALGO_VERSION}]")
# Cache entry fields for CH trade_events on exit
tid = e.get('trade_id')
if tid:
self._pending_entries[tid] = {
'asset': e.get('asset', ''),
'side': 'SHORT' if e.get('direction', -1) == -1 else 'LONG',
'entry_price': float(e.get('entry_price', 0) or 0),
'quantity': round(float(e.get('notional', 0) or 0) / float(e.get('entry_price', 1) or 1), 6),
'leverage': float(e.get('leverage', 0) or 0),
'vel_div_entry': float(e.get('vel_div', 0) or 0),
'boost_at_entry': float(getattr(getattr(self, 'eng', None), 'acb_boost', 1.0) or 1.0),
'beta_at_entry': float(getattr(getattr(self, 'eng', None), 'acb_beta', 1.0) or 1.0),
'posture': posture_now,
'entry_ts': _ch_ts_us(),
'entry_date': (self.current_day or ''),
}
if result.get('exit'):
x = result['exit']
log(f"EXIT: {x} [{ALGO_VERSION}]")
tid = x.get('trade_id')
pending = self._pending_entries.pop(tid, {}) if tid else {}
if pending:
# exact bar price the engine exited against — prices_dict is still in scope
exit_price = float(prices_dict.get(pending['asset'], 0) or 0)
ch_put("trade_events", {
"ts": _ch_ts_us(),
"date": pending['entry_date'],
"strategy": "blue",
"asset": pending['asset'],
"side": pending['side'],
"entry_price": pending['entry_price'],
"exit_price": exit_price,
"quantity": pending['quantity'],
"pnl": float(x.get('net_pnl', 0) or 0),
"pnl_pct": float(x.get('pnl_pct', 0) or 0),
"exit_reason": str(x.get('reason', 'UNKNOWN')),
"vel_div_entry": pending['vel_div_entry'],
"boost_at_entry": pending['boost_at_entry'],
"beta_at_entry": pending['beta_at_entry'],
"posture": pending['posture'],
"leverage": pending['leverage'],
"bars_held": int(x.get('bars_held', 0) or 0),
"regime_signal": 0,
})
self._push_state(scan_number, vel_div, vol_ok, self._read_posture())
except Exception as e:
log(f"ERROR in _process_scan: {e}")
def on_exf_update(self, event):
if not event.value: return
snapshot = json.loads(event.value) if isinstance(event.value, str) else event.value
if not self.current_day or not self.acb: return
try:
w750_vel = getattr(self, 'last_w750_vel', None)
acb_info = self.acb.get_dynamic_boost_from_hz(
date_str=self.current_day,
exf_snapshot=snapshot,
w750_velocity=float(w750_vel) if w750_vel else None
)
with self.eng_lock:
if hasattr(self.eng, 'update_acb_boost'):
self.eng.update_acb_boost(
boost=acb_info['boost'],
beta=acb_info['beta']
)
now = time.time()
if now - self._exf_log_time >= 300:
self._exf_log_time = now
log(f"ACB subday: boost={acb_info['boost']:.4f} beta={acb_info['beta']:.4f} "
f"signals={acb_info['signals']:.1f} src={acb_info.get('source','?')}")
# ACB_EXIT disabled: update_acb_boost() called to keep boost/beta current
# (ACBv6 intact), but SUBDAY_ACB_NORMALIZATION exits are suppressed.
except ValueError as e:
log(f"ACB Stale Data Fallback: {e}")
except Exception as e:
log(f"on_exf_update Error: {e}")
def _wire_obf(self, assets):
if not assets or self.ob_assets:
return
self.ob_assets = assets
from nautilus_dolphin.nautilus.hz_ob_provider import HZOBProvider
live_ob = HZOBProvider(
hz_cluster=HZ_CLUSTER,
hz_host=HZ_HOST,
assets=assets,
)
self.ob_eng = OBFeatureEngine(live_ob)
# No preload_date() call — live mode uses step_live() per scan
self.eng.set_ob_engine(self.ob_eng)
log(f" OBF wired: HZOBProvider, {len(assets)} assets (LIVE mode)")
def _save_capital(self):
"""Persist capital to HZ (primary) and disk (fallback) so restarts survive HZ loss."""
capital = getattr(self.eng, 'capital', None)
if capital is None or not math.isfinite(capital) or capital < 1.0:
return
payload = json.dumps({'capital': capital, 'ts': time.time()})
# Primary: Hazelcast
try:
self.state_map.blocking().put('capital_checkpoint', payload)
except Exception as e:
log(f" capital HZ save failed: {e}")
# Secondary: local disk (survives HZ restart)
try:
CAPITAL_DISK_CHECKPOINT.write_text(payload)
except Exception as e:
log(f" capital disk save failed: {e}")
def _restore_capital(self):
"""On startup, restore capital from HZ or disk checkpoint."""
def _try_load(raw, source):
if not raw:
return False
try:
data = json.loads(raw)
saved = float(data.get('capital', 0))
age_h = (time.time() - data.get('ts', 0)) / 3600
if saved >= 1.0 and math.isfinite(saved) and age_h < 72:
self.eng.capital = saved
log(f" Capital restored from {source}: ${saved:,.2f} (age {age_h:.1f}h)")
return True
except Exception:
pass
return False
# Primary: Hazelcast
try:
raw = self.state_map.blocking().get('capital_checkpoint')
if _try_load(raw, 'HZ'):
return
except Exception as e:
log(f" capital HZ restore failed: {e}")
# Secondary: disk fallback
try:
if CAPITAL_DISK_CHECKPOINT.exists():
raw = CAPITAL_DISK_CHECKPOINT.read_text()
if _try_load(raw, 'disk'):
return
except Exception as e:
log(f" capital disk restore failed: {e}")
log(" Capital: no valid checkpoint — starting at initial_capital")
def _push_state(self, scan_number, vel_div, vol_ok, posture):
try:
with self.eng_lock:
capital = getattr(self.eng, 'capital', 25000.0)
# Engine uses a single NDPosition object, not a list
pos = getattr(self.eng, 'position', None)
if pos is not None:
open_notional = float(getattr(pos, 'notional', 0) or 0)
open_positions_list = [{
'asset': pos.asset,
'side': 'SHORT' if pos.direction == -1 else 'LONG',
'entry_price': pos.entry_price,
'quantity': round(open_notional / pos.entry_price, 6) if pos.entry_price else 0,
'notional': open_notional,
'leverage': float(getattr(pos, 'leverage', 0) or 0),
'unrealized_pnl': round(pos.pnl_pct * open_notional, 2),
}]
else:
open_notional = 0.0
open_positions_list = []
cur_leverage = (open_notional / capital) if capital and capital > 0 and math.isfinite(capital) else 0.0
snapshot = {
'capital': capital if math.isfinite(capital) else None,
'open_positions': open_positions_list,
'algo_version': ALGO_VERSION,
'last_scan_number': scan_number, 'last_vel_div': vel_div,
'vol_ok': vol_ok, 'posture': posture,
'scans_processed': self.scans_processed,
'trades_executed': self.trades_executed,
'bar_idx': self.bar_idx,
'timestamp': datetime.now(timezone.utc).isoformat(),
# Leverage envelope — for TUI slider
'leverage_soft_cap': getattr(self.eng, 'base_max_leverage', 8.0),
'leverage_abs_cap': getattr(self.eng, 'abs_max_leverage', 9.0),
'open_notional': round(open_notional, 2),
'current_leverage': round(cur_leverage, 4),
}
future = self.state_map.put('engine_snapshot', json.dumps(snapshot))
future.add_done_callback(lambda f: None)
# Heartbeat — MHS checks age < 30s; we run every scan (~11s)
if self.heartbeat_map is not None:
hb = json.dumps({
'ts': time.time(),
'iso': datetime.now(timezone.utc).isoformat(),
'run_date': self.current_day,
'phase': 'trading',
'flow': 'nautilus_event_trader',
})
self.heartbeat_map.put('nautilus_flow_heartbeat', hb)
# Persist capital so next restart resumes from here
if capital is not None and math.isfinite(capital) and capital >= 1.0:
self._save_capital()
except Exception as e:
log(f" Failed to push state: {e}")
def run(self):
global running
log("=" * 70)
log("🐬 DOLPHIN Nautilus Event-Driven Trader Starting")
log("=" * 70)
self._build_engine()
self._connect_hz()
self._restore_capital()
self._rollover_day()
def listener(event):
self.on_scan(event)
self.features_map.add_entry_listener(
key='latest_eigen_scan', include_value=True,
updated_func=listener, added_func=listener
)
def exf_listener(event):
self.on_exf_update(event)
self.features_map.add_entry_listener(
key='exf_latest', include_value=True,
updated_func=exf_listener, added_func=exf_listener
)
log("✅ Hz listener registered")
log(f"🏷️ ALGO_VERSION: {ALGO_VERSION}")
log("⏳ Waiting for scans...")
try:
while running:
time.sleep(1)
except KeyboardInterrupt:
log("Interrupted")
finally:
self.shutdown()
def shutdown(self):
log("Shutting down...")
self._scan_executor.shutdown(wait=False)
if self.eng and self.current_day:
try:
with self.eng_lock:
summary = self.eng.end_day()
log(f"end_day: {summary}")
except Exception as e:
log(f"end_day failed: {e}")
if self.hz_client:
try:
self.hz_client.shutdown()
log("Hz disconnected")
except:
pass
log(f"🛑 Stopped. Scans: {self.scans_processed}, Trades: {self.trades_executed}")
def signal_handler(signum, frame):
global running
log(f"Signal {signum} received")
running = False
def main():
signal.signal(signal.SIGTERM, signal_handler)
signal.signal(signal.SIGINT, signal_handler)
trader = DolphinLiveTrader()
trader.run()
if __name__ == '__main__':
main()