docs: add DOCKER_GUIDE.md and fix .env parsing; chore: update docker and script configurations
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BTC Bot
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scripts/test_ma44_performance.py
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187
scripts/test_ma44_performance.py
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#!/usr/bin/env python3
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"""
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Performance Test Script for MA44 Strategy
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Tests backtesting performance on Synology DS218+ with 6GB RAM
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Usage:
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python test_ma44_performance.py [--days DAYS] [--interval INTERVAL]
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Example:
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python test_ma44_performance.py --days 7 --interval 1m
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"""
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import asyncio
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import argparse
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import time
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import sys
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import os
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from datetime import datetime, timedelta, timezone
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# Add src to path
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sys.path.insert(0, os.path.join(os.path.dirname(__file__), '..', 'src'))
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from data_collector.database import DatabaseManager
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from data_collector.indicator_engine import IndicatorEngine, IndicatorConfig
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from data_collector.brain import Brain
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from data_collector.backtester import Backtester
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async def run_performance_test(days: int = 7, interval: str = "1m"):
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"""Run MA44 backtest and measure performance"""
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print("=" * 70)
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print(f"PERFORMANCE TEST: MA44 Strategy")
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print(f"Timeframe: {interval}")
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print(f"Period: Last {days} days")
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print(f"Hardware: Synology DS218+ (6GB RAM)")
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print("=" * 70)
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print()
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# Database connection (adjust these if needed)
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db = DatabaseManager(
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host=os.getenv('DB_HOST', 'localhost'),
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port=int(os.getenv('DB_PORT', 5432)),
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database=os.getenv('DB_NAME', 'btc_data'),
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user=os.getenv('DB_USER', 'btc_bot'),
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password=os.getenv('DB_PASSWORD', '')
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)
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try:
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await db.connect()
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print("✓ Database connected")
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# Calculate date range
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end_date = datetime.now(timezone.utc)
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start_date = end_date - timedelta(days=days)
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print(f"✓ Date range: {start_date.date()} to {end_date.date()}")
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print(f"✓ Symbol: BTC")
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print(f"✓ Strategy: MA44 (44-period SMA)")
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print()
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# Check data availability
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async with db.acquire() as conn:
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count = await conn.fetchval("""
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SELECT COUNT(*) FROM candles
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WHERE symbol = 'BTC'
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AND interval = $1
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AND time >= $2
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AND time <= $3
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""", interval, start_date, end_date)
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print(f"📊 Data points: {count:,} {interval} candles")
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if count == 0:
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print("❌ ERROR: No data found for this period!")
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print(f" Run: python -m data_collector.backfill --days {days} --intervals {interval}")
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return
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print(f" (Expected: ~{count * int(interval.replace('m','').replace('h','').replace('d',''))} minutes of data)")
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print()
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# Setup indicator configuration
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indicator_configs = [
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IndicatorConfig("ma44", "sma", 44, [interval])
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]
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engine = IndicatorEngine(db, indicator_configs)
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brain = Brain(db, engine)
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backtester = Backtester(db, engine, brain)
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print("⚙️ Running backtest...")
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print("-" * 70)
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# Measure execution time
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start_time = time.time()
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await backtester.run("BTC", [interval], start_date, end_date)
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end_time = time.time()
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execution_time = end_time - start_time
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print("-" * 70)
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print()
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# Fetch results from database
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async with db.acquire() as conn:
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latest_backtest = await conn.fetchrow("""
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SELECT id, strategy, start_time, end_time, intervals, results, created_at
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FROM backtest_runs
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WHERE strategy LIKE '%ma44%'
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ORDER BY created_at DESC
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LIMIT 1
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""")
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if latest_backtest and latest_backtest['results']:
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import json
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results = json.loads(latest_backtest['results'])
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print("📈 RESULTS:")
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print("=" * 70)
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print(f" Total Trades: {results.get('total_trades', 'N/A')}")
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print(f" Win Rate: {results.get('win_rate', 0):.1f}%")
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print(f" Win Count: {results.get('win_count', 0)}")
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print(f" Loss Count: {results.get('loss_count', 0)}")
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print(f" Total P&L: ${results.get('total_pnl', 0):.2f}")
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print(f" P&L Percent: {results.get('total_pnl_pct', 0):.2f}%")
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print(f" Initial Balance: ${results.get('initial_balance', 1000):.2f}")
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print(f" Final Balance: ${results.get('final_balance', 1000):.2f}")
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print(f" Max Drawdown: {results.get('max_drawdown', 0):.2f}%")
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print()
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print("⏱️ PERFORMANCE:")
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print(f" Execution Time: {execution_time:.2f} seconds")
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print(f" Candles/Second: {count / execution_time:.0f}")
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print(f" Backtest ID: {latest_backtest['id']}")
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print()
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# Performance assessment
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if execution_time < 30:
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print("✅ PERFORMANCE: Excellent (< 30s)")
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elif execution_time < 60:
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print("✅ PERFORMANCE: Good (< 60s)")
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elif execution_time < 300:
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print("⚠️ PERFORMANCE: Acceptable (1-5 min)")
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else:
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print("❌ PERFORMANCE: Slow (> 5 min) - Consider shorter periods or higher TFs")
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print()
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print("💡 RECOMMENDATIONS:")
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if execution_time > 60:
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print(" • For faster results, use higher timeframes (15m, 1h, 4h)")
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print(" • Or reduce date range (< 7 days)")
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else:
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print(" • Hardware is sufficient for this workload")
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print(" • Can handle larger date ranges or multiple timeframes")
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else:
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print("❌ ERROR: No results found in database!")
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print(" The backtest may have failed. Check server logs.")
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except Exception as e:
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print(f"\n❌ ERROR: {e}")
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import traceback
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traceback.print_exc()
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finally:
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await db.disconnect()
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print()
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print("=" * 70)
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print("Test completed")
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print("=" * 70)
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def main():
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parser = argparse.ArgumentParser(description='Test MA44 backtest performance')
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parser.add_argument('--days', type=int, default=7,
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help='Number of days to backtest (default: 7)')
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parser.add_argument('--interval', type=str, default='1m',
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help='Candle interval (default: 1m)')
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args = parser.parse_args()
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# Run the async test
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asyncio.run(run_performance_test(args.days, args.interval))
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if __name__ == "__main__":
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main()
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