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
173
prod/clean_arch/paper_trade.py
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173
prod/clean_arch/paper_trade.py
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#!/usr/bin/env python3
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"""
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DOLPHIN Paper Trading Session
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==============================
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Brief paper trading run using clean architecture.
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"""
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import sys
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sys.path.insert(0, '/mnt/dolphinng5_predict/prod/clean_arch')
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sys.path.insert(0, '/mnt/dolphinng5_predict')
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import asyncio
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import logging
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from datetime import datetime
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from typing import Optional
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logging.basicConfig(
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level=logging.INFO,
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format='%(asctime)s [%(levelname)s] %(message)s'
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)
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logger = logging.getLogger("PaperTrade")
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from adapters.hazelcast_feed import HazelcastDataFeed, MarketSnapshot
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class SimplePaperTrader:
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"""Simple paper trader for demonstration."""
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def __init__(self, capital: float = 10000.0):
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self.capital = capital
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self.position = 0.0 # BTC quantity
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self.entry_price = 0.0
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self.trades = []
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self.start_time = datetime.utcnow()
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def on_snapshot(self, snapshot: MarketSnapshot):
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"""Process market snapshot and decide to trade."""
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# Use velocity divergence as signal (non-zero in current data)
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signal = snapshot.velocity_divergence or 0.0
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# Simple mean-reversion strategy on velocity divergence
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BUY_THRESHOLD = -0.01 # Buy when velocity divergence is very negative
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SELL_THRESHOLD = 0.01 # Sell when velocity divergence is very positive
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if signal > BUY_THRESHOLD and self.position == 0:
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# Buy signal
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size = 0.001 # 0.001 BTC
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self.position = size
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self.entry_price = snapshot.price
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self.trades.append({
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'time': datetime.utcnow(),
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'side': 'BUY',
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'size': size,
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'price': snapshot.price,
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'signal': signal
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})
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logger.info(f"🟢 BUY {size} BTC @ ${snapshot.price:,.2f} (signal: {signal:.4f})")
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elif signal < SELL_THRESHOLD and self.position > 0:
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# Sell signal
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pnl = self.position * (snapshot.price - self.entry_price)
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self.trades.append({
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'time': datetime.utcnow(),
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'side': 'SELL',
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'size': self.position,
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'price': snapshot.price,
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'signal': signal,
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'pnl': pnl
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})
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logger.info(f"🔴 SELL {self.position} BTC @ ${snapshot.price:,.2f} (signal: {signal:.4f}, PnL: ${pnl:+.2f})")
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self.position = 0.0
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self.entry_price = 0.0
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def get_status(self) -> dict:
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"""Get current trading status."""
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current_price = self.trades[-1]['price'] if self.trades else 0
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unrealized = self.position * (current_price - self.entry_price) if self.position > 0 else 0
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realized = sum(t.get('pnl', 0) for t in self.trades)
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return {
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'trades': len(self.trades),
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'position': self.position,
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'unrealized_pnl': unrealized,
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'realized_pnl': realized,
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'total_pnl': unrealized + realized
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}
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async def paper_trade(duration_seconds: int = 60):
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"""Run paper trading for specified duration."""
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logger.info("=" * 60)
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logger.info("🐬 DOLPHIN PAPER TRADING SESSION")
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logger.info("=" * 60)
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logger.info(f"Duration: {duration_seconds}s")
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logger.info("")
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# Setup
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feed = HazelcastDataFeed({
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'hazelcast': {'cluster': 'dolphin', 'host': 'localhost:5701'}
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})
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trader = SimplePaperTrader(capital=10000.0)
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# Connect
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logger.info("Connecting to Hazelcast...")
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if not await feed.connect():
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logger.error("Failed to connect!")
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return
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logger.info("✓ Connected. Starting trading loop...")
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logger.info("")
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# Trading loop
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start_time = datetime.utcnow()
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iteration = 0
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try:
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while (datetime.utcnow() - start_time).total_seconds() < duration_seconds:
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iteration += 1
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# Get latest snapshot
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snapshot = await feed.get_latest_snapshot("BTCUSDT")
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if snapshot:
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trader.on_snapshot(snapshot)
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# Log status every 5 iterations
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if iteration % 5 == 0:
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status = trader.get_status()
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pos_str = f"Position: {status['position']:.4f} BTC" if status['position'] > 0 else "Position: FLAT"
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pnl_str = f"PnL: ${status['total_pnl']:+.2f}"
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logger.info(f"[{iteration}] {pos_str} | {pnl_str} | Price: ${snapshot.price:,.2f}")
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# Wait before next iteration (sub-5 second for faster updates)
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await asyncio.sleep(1.0)
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except KeyboardInterrupt:
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logger.info("\n⚠️ Interrupted by user")
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# Cleanup
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await feed.disconnect()
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# Final report
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logger.info("")
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logger.info("=" * 60)
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logger.info("📊 FINAL REPORT")
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logger.info("=" * 60)
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status = trader.get_status()
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logger.info(f"Total Trades: {status['trades']}")
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logger.info(f"Final Position: {status['position']:.6f} BTC")
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logger.info(f"Realized PnL: ${status['realized_pnl']:+.2f}")
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logger.info(f"Unrealized PnL: ${status['unrealized_pnl']:+.2f}")
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logger.info(f"Total PnL: ${status['total_pnl']:+.2f}")
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if trader.trades:
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logger.info("")
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logger.info("Trade History:")
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for t in trader.trades:
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pnl_str = f" (${t.get('pnl', 0):+.2f})" if 'pnl' in t else ""
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logger.info(f" {t['side']:4} {t['size']:.4f} @ ${t['price']:,.2f}{pnl_str}")
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logger.info("=" * 60)
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logger.info("✅ Paper trading session complete")
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if __name__ == "__main__":
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import argparse
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parser = argparse.ArgumentParser()
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parser.add_argument('--duration', type=int, default=30, help='Trading duration in seconds')
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args = parser.parse_args()
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asyncio.run(paper_trade(args.duration))
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