initial: import DOLPHIN baseline 2026-04-21 from dolphinng5_predict working tree
Includes core prod + GREEN/BLUE subsystems: - prod/ (BLUE harness, configs, scripts, docs) - nautilus_dolphin/ (GREEN Nautilus-native impl + dvae/ preserved) - adaptive_exit/ (AEM engine + models/bucket_assignments.pkl) - Observability/ (EsoF advisor, TUI, dashboards) - external_factors/ (EsoF producer) - mc_forewarning_qlabs_fork/ (MC regime/envelope) Excludes runtime caches, logs, backups, and reproducible artifacts per .gitignore.
This commit is contained in:
hjnormey
233
nautilus_dolphin/run_papertrade.py
Executable file
233
nautilus_dolphin/run_papertrade.py
Executable file
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import asyncio
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import aiohttp
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import time
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import json
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import logging
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import numpy as np
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from collections import defaultdict
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import sys
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from pathlib import Path
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# Add project root to path
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sys.path.insert(0, str(Path(__file__).parent.parent))
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from nautilus_dolphin.nautilus.alpha_orchestrator import NDAlphaEngine
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from nautilus_dolphin.nautilus.adaptive_circuit_breaker import AdaptiveCircuitBreaker
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from nautilus_dolphin.nautilus.ob_features import OBFeatureEngine
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from nautilus_dolphin.nautilus.ob_provider import OBProvider, OBSnapshot
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from external_factors.ob_stream_service import OBStreamService
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logging.basicConfig(level=logging.INFO, format='%(asctime)s [%(levelname)s] %(name)s: %(message)s')
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logger = logging.getLogger("PaperTrade")
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class LiveOBAdapter(OBProvider):
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"""Adapts continuous OBStreamService to the OBProvider interface for the Engine."""
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def __init__(self, stream_service: OBStreamService):
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self.stream = stream_service
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self._last_snaps = {}
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self.assets = stream_service.assets
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def _update_snap(self, asset: str, data: dict):
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if data:
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self._last_snaps[asset] = OBSnapshot(
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timestamp=data['timestamp'],
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asset=asset,
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bid_notional=data['bid_notional'].copy(),
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ask_notional=data['ask_notional'].copy(),
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bid_depth=data['bid_depth'].copy(),
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ask_depth=data['ask_depth'].copy()
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)
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def get_snapshot(self, asset: str, timestamp: float):
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# Always returns the absolute latest snapshot regardless of requested timestamp
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# In a real live environment, the engine asks for "now"
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return self._last_snaps.get(asset)
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def get_assets(self):
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return self.assets
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def get_all_timestamps(self, asset: str):
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return np.array([time.time()], dtype=np.float64)
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async def fetch_historical_klines(session: aiohttp.ClientSession, symbol: str, limit: int = 1500) -> list:
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"""Fetch 1500 recent 5m klines to warm up the engine."""
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url = f"https://fapi.binance.com/fapi/v1/klines?symbol={symbol}&interval=5m&limit={limit}"
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async with session.get(url) as resp:
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data = await resp.json()
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# [openTime, open, high, low, close, volume, closeTime, quoteVolume, count, takerBuyVolume, takerBuyQuoteVolume, ignore]
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return [{"ts": d[0]/1000.0, "c": float(d[4])} for d in data]
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async def run_paper_trade():
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assets = ["BTCUSDT", "ETHUSDT", "BNBUSDT", "SOLUSDT"]
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logger.info(f"Starting Paper Trading Environment for {assets}...")
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# 1. Initialize Engine & Components
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ENGINE_KWARGS = dict(
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initial_capital=25000.0, vel_div_threshold=-0.02, vel_div_extreme=-0.05,
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min_leverage=0.5, max_leverage=5.0, leverage_convexity=3.0,
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fraction=0.20, fixed_tp_pct=0.0099, stop_pct=1.0, max_hold_bars=120,
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use_direction_confirm=True, dc_lookback_bars=7, dc_min_magnitude_bps=0.75,
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dc_skip_contradicts=True, dc_leverage_boost=1.0, dc_leverage_reduce=0.5,
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use_asset_selection=True, min_irp_alignment=0.45,
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use_sp_fees=True, use_sp_slippage=True,
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sp_maker_entry_rate=0.62, sp_maker_exit_rate=0.50,
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use_ob_edge=True, ob_edge_bps=5.0, ob_confirm_rate=0.40,
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lookback=100, use_alpha_layers=True, use_dynamic_leverage=True, seed=42,
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)
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engine = NDAlphaEngine(**ENGINE_KWARGS)
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# 2. Start Live OB Streamer
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stream_service = OBStreamService(assets=assets)
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asyncio.create_task(stream_service.stream())
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logger.info("Connecting OB stream...")
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await asyncio.sleep(5) # Let it authenticate and fetch REST models
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live_ob_adapter = LiveOBAdapter(stream_service)
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ob_feature_engine = OBFeatureEngine(live_ob_adapter)
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engine.set_ob_engine(ob_feature_engine)
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# 3. Fetch Warmup Data (last ~5 days of 5m bars)
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async with aiohttp.ClientSession() as session:
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logger.info("Fetching warmup 5m klines from Binance...")
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history = {a: await fetch_historical_klines(session, a) for a in assets}
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# Align by timestamp
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all_ts = set()
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for a in assets:
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for k in history[a]:
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all_ts.add(k['ts'])
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sorted_ts = sorted(list(all_ts))
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logger.info(f"Warming up engine with {len(sorted_ts)} historical bars...")
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ph = defaultdict(list)
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b_idx = 0
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all_vols = []
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engine.regime_direction = -1
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engine.regime_size_mult = 1.0
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# Quick warmup loop
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for ts in sorted_ts:
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prices = {}
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for a in assets:
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# Find closest price
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match = next((k['c'] for k in reversed(history[a]) if k['ts'] <= ts), None)
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if match:
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prices[a] = match
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ph[a].append(match)
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if len(ph[a]) > 500: ph[a] = ph[a][-500:]
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# Calculate vel_div (using BTCUSDT as proxy)
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btc_hist = ph["BTCUSDT"]
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vd = 0.0
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vrok = False
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if len(btc_hist) >= 50:
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seg = btc_hist[-50:]
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vd = float(np.std(np.diff(seg)/np.array(seg[:-1])))
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all_vols.append(vd)
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if len(all_vols) > 100:
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vol_p60 = float(np.percentile(all_vols, 60))
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if vd > vol_p60: vrok = True
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# Manually pump the live adapter so OB feature engine registers "something"
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# We don't have historical OB for warmup, so we'll just inject Neutral zeros or live if connected
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for a in assets:
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snap = await stream_service.get_depth_buckets(a)
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if snap: live_ob_adapter._update_snap(a, snap)
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engine.process_bar(bar_idx=b_idx, vel_div=vd, prices=prices, vol_regime_ok=vrok, price_histories=ph)
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b_idx += 1
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# Evaluate warmup metrics
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def print_metrics(prefix="[WARMUP METRICS]"):
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tr = engine.trade_history
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w = [t for t in tr if t.pnl_absolute > 0]
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l = [t for t in tr if t.pnl_absolute <= 0]
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gw = sum(t.pnl_absolute for t in w) if w else 0
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gl = abs(sum(t.pnl_absolute for t in l)) if l else 0
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roi = (engine.capital - 25000) / 25000 * 100
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pf_val = gw / gl if gl > 0 else 999
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wr = len(w) / len(tr) * 100 if tr else 0.0
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logger.info(f"{prefix} Capital: ${engine.capital:,.2f} | ROI: {roi:+.2f}% | PF: {pf_val:.3f} | WR: {wr:.1f}% | Trades: {len(tr)}")
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print_metrics()
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logger.info("=====================================================================")
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logger.info(">>> WARMUP COMPLETE. ENTERING LIVE PAPER TRADING MODE. <<<")
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logger.info("=====================================================================")
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# 4. Live Tick Loop (Every 60s to simulate fast intra-bar ticks or 5m bars)
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# We tick every 20 seconds, updating the price and OB, and letting SmartPlacer evaluate
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last_5m = sorted_ts[-1] if sorted_ts else time.time()
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while True:
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try:
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await asyncio.sleep(20) # 20 second tick
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current_ts = time.time()
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# Fetch latest prices from Live Stream instead of REST
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prices = {}
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for a in assets:
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snap = await stream_service.get_depth_buckets(a)
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if snap:
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live_ob_adapter._update_snap(a, snap)
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# Use mid price
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prices[a] = (snap['best_bid'] + snap['best_ask']) / 2.0
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if not prices:
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logger.warning("No live prices available yet...")
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continue
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# If 5 minutes elapsed, it's a new bar, update histories
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is_new_bar = (current_ts - last_5m) >= 300
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if is_new_bar:
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last_5m = current_ts
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b_idx += 1
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for a in assets:
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if a in prices:
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ph[a].append(prices[a])
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if len(ph[a]) > 500: ph[a] = ph[a][-500:]
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# Update vd
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btc_hist = ph["BTCUSDT"]
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if len(btc_hist) >= 50:
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seg = btc_hist[-50:]
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vd = float(np.std(np.diff(seg)/np.array(seg[:-1])))
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all_vols.append(vd)
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else:
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# Intra-bar read, VD remains same
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btc_hist = ph.get("BTCUSDT", [])
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if len(btc_hist) >= 50:
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seg = btc_hist[-50:]
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vd = float(np.std(np.diff(seg)/np.array(seg[:-1])))
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else:
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vd = 0.0
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vrok = len(all_vols) > 100 and vd > float(np.percentile(all_vols, 60))
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# Process tick
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engine.process_bar(bar_idx=b_idx, vel_div=vd, prices=prices, vol_regime_ok=vrok, price_histories=ph)
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# Show live OB features safely
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btc_ob = ob_feature_engine.get_signal("BTCUSDT", b_idx)
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macro = ob_feature_engine.get_macro()
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imb_str = f"Imb: {btc_ob.imbalance:+.3f}" if btc_ob else "Imb: N/A"
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reg_map = {0: "CALM", -1: "NEUTRAL", 1: "STRESS"}
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reg_str = reg_map.get(macro.regime_signal, "UKWN")
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print_metrics(prefix=f"[LIVE {time.strftime('%H:%M:%S')}] {imb_str} | Macro: {reg_str} |")
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except Exception as e:
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logger.error(f"Live Loop Exception: {e}", exc_info=True)
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await asyncio.sleep(5)
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if __name__ == "__main__":
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try:
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asyncio.run(run_paper_trade())
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except KeyboardInterrupt:
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logger.info("Paper trading stopped.")
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