Bot auto-update: src/main_ml.py
This commit is contained in:
Marc Blatter
parent
32ed8cac6d
commit
bd68b491f2
256
src/main_ml.py
256
src/main_ml.py
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@ -1,63 +1,56 @@
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#!/usr/bin/env python3
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"""
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Trading Bot V0.3 - Strategy Rewrite
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Deployed: 2026-07-09 18:30 UTC
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Changes: Fresh balance cache, local min signal, hard TP/SL
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"""
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import os
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import time
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import logging
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"""Trading Bot v0.4 - Dynamic Position Sizing (% of Portfolio)"""
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import os, json, time, logging
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from datetime import datetime
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from decimal import Decimal, ROUND_DOWN
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from dotenv import load_dotenv
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from binance.client import Client
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from binance.exceptions import BinanceAPIException
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# Setup Logging
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logging.basicConfig(level=logging.INFO, format='%(asctime)s | %(levelname)s | %(message)s')
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logger = logging.getLogger(__name__)
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# Setup
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logging.basicConfig(level=logging.INFO, format='%(levelname)s:%(message)s')
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logger = logging.getLogger()
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# Load API Keys
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API_KEY = os.getenv('BINANCE_API_KEY_LIVE')
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API_SECRET = os.getenv('BINANCE_API_SECRET_LIVE')
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load_dotenv()
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try:
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API_KEY = os.getenv('BINANCE_API_KEY_LIVE')
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API_SECRET = os.getenv('BINANCE_API_SECRET_LIVE')
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except:
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if not API_KEY or not API_SECRET:
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logger.error("Missing API keys")
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exit(1)
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# Constants
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# ===== DYNAMIC POSITION SIZING CONSTANTS =====
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SYMBOLS = ['BTCUSDT', 'ETHUSDT', 'BNBUSDT', 'XRPUSDT', 'SOLUSDT']
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MIN_USDT = 5.00
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MAX_TRADE_USDT = 20.00
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MAX_POSITION_PCT = 0.05 # 5% of portfolio per trade (DYNAMIC!)
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KELLY_FRACTION = 0.25 # Conservative Kelly
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ESTIMATED_WIN_RATE = 0.60 # 60% from bot data
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TAKE_PROFIT_PCT = 0.015 # +1.5%
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STOP_LOSS_PCT = -0.008 # -0.8%
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CYCLE_SEC = 60
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class TradingBotV03:
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"""Trading Bot with Fresh Cache + Local Min Signals + Hard Risk Management"""
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class TradingBotV04:
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"""Trading Bot v0.4 with Dynamic Position Sizing"""
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def __init__(self):
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self.client = Client(API_KEY, API_SECRET)
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self.price_history = {sym: [] for sym in SYMBOLS}
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self.active_trades = {} # {symbol: {'entry_price': float, 'qty': float}}
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self.active_trades = {}
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self.portfolio_value = 0
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self.max_trade_usdt = 0
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# CRITICAL: Recover orphaned trades from Binance balance (bot got restarted!)
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# Recover orphaned trades
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try:
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account = self.client.get_account()
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for b in account['balances']:
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asset = b['asset']
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free = float(b['free'])
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# If we hold a symbol's coin, reconstruct it
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for symbol in SYMBOLS:
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if symbol.replace('USDT', '') == asset and free > 0.0001:
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# Get current price to estimate entry
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try:
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current_price = float(self.get_current_price(symbol))
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self.active_trades[symbol] = {
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'entry_price': current_price, # Reconstructed (not exact, but better than 0)
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'entry_price': current_price,
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'qty': free,
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'entry_time': datetime.now().isoformat()
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}
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@ -66,21 +59,43 @@ class TradingBotV03:
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pass
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except Exception as e:
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logger.warning(f"Trade recovery failed: {e}")
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logger.info("Bot V0.3 initialized | Fresh Cache + Local Min + Hard TP/SL")
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logger.info("Bot V0.4 initialized | Dynamic Position Sizing (% of Portfolio)")
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def get_fresh_balance(self):
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"""KEY FIX: Always fetch FRESH balance from API (no stale cache!)"""
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"""Always fetch FRESH balance from API"""
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try:
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account = self.client.get_account()
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balances = {}
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portfolio_value = 0
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# Get prices
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prices = {'USDT': 1.0}
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for p in ['BTCUSDT', 'ETHUSDT', 'SOLUSDT', 'BNBUSDT', 'XRPUSDT']:
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try:
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t = self.client.get_ticker(symbol=p)
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prices[p.replace('USDT', '')] = float(t['lastPrice'])
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except:
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pass
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# Calculate balances & portfolio value
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for b in account['balances']:
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balances[b['asset']] = float(b['free'])
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asset, free = b['asset'], float(b['free'])
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balances[asset] = free
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price = prices.get(asset, 1.0)
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portfolio_value += free * price
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usdt_available = balances.get('USDT', 0)
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logger.info(f"Fresh balance: USDT=${usdt_available:.2f}")
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return balances, usdt_available
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# Store for later use
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self.portfolio_value = portfolio_value
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self.max_trade_usdt = portfolio_value * MAX_POSITION_PCT
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logger.info(f"Fresh balance: USDT=${usdt_available:.2f} | Portfolio=${portfolio_value:.2f} | Max Trade=${self.max_trade_usdt:.2f}")
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return balances, usdt_available, portfolio_value
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except BinanceAPIException as e:
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logger.error(f"Balance fetch failed: {e}")
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return {}, 0
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return {}, 0, 0
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def get_current_price(self, symbol):
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"""Get current market price"""
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@ -93,50 +108,37 @@ class TradingBotV03:
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return None
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def calculate_valid_quantity(self, symbol, usdt_amount):
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"""Berechne korrekte Qty mit Decimal precision für LOT_SIZE"""
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"""Calculate correct Qty with Decimal precision"""
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try:
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price = self.get_current_price(symbol)
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if not price:
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return 0
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# Get exchange info for lot size
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info = self.client.get_symbol_info(symbol)
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if not info:
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return 0
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# Hole LOT_SIZE filter
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lot_size_info = None
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for filt in info.get('filters', []):
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if filt['filterType'] == 'LOT_SIZE':
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lot_size_info = filt
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# Find LOT_SIZE filter
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step_size = None
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for f in info.get('filters', []):
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if f['filterType'] == 'LOT_SIZE':
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step_size = float(f['stepSize'])
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break
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if not lot_size_info:
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if not step_size:
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return 0
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step_size = Decimal(lot_size_info.get('stepSize', '0.00001'))
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min_qty = Decimal(lot_size_info.get('minQty', '0'))
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max_qty = Decimal(lot_size_info.get('maxQty', '10000'))
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qty_float = usdt_amount / price
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# Berechne Qty mit Decimal (kein floating-point Fehler!)
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qty_decimal = Decimal(str(usdt_amount)) / Decimal(str(price))
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# Round to step size
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qty_float = int(qty_float / step_size) * step_size
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# Runde auf step_size (immer abrunden, nie aufrunden)
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qty_rounded = (qty_decimal / step_size).quantize(Decimal('1'), rounding=ROUND_DOWN) * step_size
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# Prüfe Min/Max Grenzen
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if qty_rounded < min_qty:
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logger.debug(f"Qty zu klein: {symbol} {qty_rounded} < {min_qty}")
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return 0
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if qty_rounded > max_qty:
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logger.debug(f"Qty zu groß: {symbol} {qty_rounded} > {max_qty}")
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qty_rounded = max_qty
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# Konvertiere zu float mit gerader Präzision
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qty_float = float(qty_rounded)
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# Check minimum notional
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min_notional = 5.0
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notional = qty_float * price
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if notional < MIN_USDT:
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if notional < min_notional:
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logger.debug(f"Order too small: {symbol} ${notional:.2f}")
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return 0
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@ -148,14 +150,13 @@ class TradingBotV03:
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return 0
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def is_local_minimum(self, symbol):
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"""Signal Logic: Buy when price is at local minimum (not random %)"""
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"""Signal Logic: Buy when price is at local minimum"""
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if len(self.price_history[symbol]) < 5:
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return False
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recent_prices = self.price_history[symbol][-5:]
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current_price = recent_prices[-1]
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# Local min condition: current is lower than all recent prices
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is_min = all(current_price < p for p in recent_prices[:-1])
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if is_min:
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@ -188,58 +189,51 @@ class TradingBotV03:
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logger.info(f"BUY: {qty} {symbol} @ ${entry_price:.2f} (${qty*entry_price:.2f})")
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logger.info(f" TP target: +${qty*entry_price*TAKE_PROFIT_PCT:.2f} ({TAKE_PROFIT_PCT*100:.1f}%)")
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logger.info(f" SL target: -${qty*entry_price*abs(STOP_LOSS_PCT):.2f} ({STOP_LOSS_PCT*100:.1f}%)")
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logger.info(f" [DYNAMIC] Portfolio: ${self.portfolio_value:.2f} | Max Position: ${self.max_trade_usdt:.2f}")
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return order
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except BinanceAPIException as e:
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logger.error(f"Buy order failed: {e}")
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logger.error(f"Order failed: {e}")
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return None
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def check_and_close_positions(self):
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"""HARD RISK MANAGEMENT: Close positions that hit TP or SL"""
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for symbol in list(self.active_trades.keys()):
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trade = self.active_trades[symbol]
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current_price = self.get_current_price(symbol)
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"""Check TP/SL for all active trades"""
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for symbol, trade in list(self.active_trades.items()):
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try:
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current_price = self.get_current_price(symbol)
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if not current_price:
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continue
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if not current_price:
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continue
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entry_price = trade['entry_price']
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qty = trade['qty']
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pnl_pct = ((current_price - entry_price) / entry_price) * 100
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entry_price = trade['entry_price']
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qty = trade['qty']
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pnl_pct = (current_price - entry_price) / entry_price
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pnl_usdt = qty * (current_price - entry_price)
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# Check TP
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if pnl_pct >= TAKE_PROFIT_PCT * 100:
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logger.info(f"SELL (TP): {qty} {symbol} @ ${current_price:.2f} | +{pnl_pct:.2f}%")
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try:
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self.client.order_market_sell(symbol=symbol, quantity=qty)
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del self.active_trades[symbol]
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except:
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pass
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# Check Take Profit (close winners immediately!)
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if pnl_pct >= TAKE_PROFIT_PCT:
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logger.info(f"TAKE PROFIT: {symbol} +{pnl_pct*100:.2f}% (${pnl_usdt:.2f})")
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try:
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# Validiere Qty vor Verkauf (rund ab für LOT_SIZE)
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qty_sell = float(Decimal(str(qty)).quantize(Decimal('0.00000001'), rounding=ROUND_DOWN))
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self.client.order_market_sell(symbol=symbol, quantity=qty_sell)
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del self.active_trades[symbol]
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except Exception as e:
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logger.error(f"Sell failed: {e}")
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continue
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# Check SL
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elif pnl_pct <= STOP_LOSS_PCT * 100:
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logger.info(f"SELL (SL): {qty} {symbol} @ ${current_price:.2f} | {pnl_pct:.2f}%")
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try:
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self.client.order_market_sell(symbol=symbol, quantity=qty)
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del self.active_trades[symbol]
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except:
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pass
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except:
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pass
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# Check Stop Loss (cut losers fast!)
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if pnl_pct <= STOP_LOSS_PCT:
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logger.warning(f"STOP LOSS: {symbol} {pnl_pct*100:.2f}% (${pnl_usdt:.2f})")
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try:
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# Validiere Qty vor Verkauf (rund ab für LOT_SIZE)
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qty_sell = float(Decimal(str(qty)).quantize(Decimal('0.00000001'), rounding=ROUND_DOWN))
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self.client.order_market_sell(symbol=symbol, quantity=qty_sell)
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del self.active_trades[symbol]
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except Exception as e:
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logger.error(f"Sell failed: {e}")
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continue
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def cycle(self):
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"""Main trading cycle (runs every 60 seconds)"""
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def run_cycle(self):
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"""Main trading cycle"""
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logger.info("=" * 70)
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logger.info(f"CYCLE START @ {datetime.now().strftime('%H:%M:%S CET')}")
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# STEP 1: Fresh balance (KEY FIX for cache bug!)
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balances, usdt_free = self.get_fresh_balance()
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# STEP 1: Fresh balance & calculate dynamic position size
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balances, usdt_free, portfolio_val = self.get_fresh_balance()
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if usdt_free < MIN_USDT:
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logger.warning(f"Insufficient capital: ${usdt_free:.2f} < ${MIN_USDT}")
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@ -254,7 +248,6 @@ class TradingBotV03:
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price = self.get_current_price(symbol)
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if price:
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self.price_history[symbol].append(price)
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# Keep only last 20 prices
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if len(self.price_history[symbol]) > 20:
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self.price_history[symbol].pop(0)
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@ -267,53 +260,46 @@ class TradingBotV03:
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# STEP 5: Place trade if signal exists and we have capital
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if best_signal and usdt_free >= MIN_USDT:
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# Use max 50% of available capital, but capped at MAX_TRADE_USDT
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trade_amount = min(MAX_TRADE_USDT, usdt_free * 0.5)
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trade_amount = min(self.max_trade_usdt, usdt_free * 0.5)
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self.place_buy_order(best_signal, trade_amount)
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logger.info(f"CYCLE END | Active trades: {len(self.active_trades)} | Free USDT: ${usdt_free:.2f}")
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logger.info(f"CYCLE END | Active trades: {len(self.active_trades)} | Free USDT: ${usdt_free:.2f} | Portfolio: ${portfolio_val:.2f}")
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# Save active trades for dashboard (atomic write with temp file)
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# Save active trades for dashboard
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import json, os
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try:
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temp_file = '/home/marc/bot-deploy/active_trades.json.tmp'
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with open(temp_file, 'w') as f:
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json.dump({'active_trades': self.active_trades, 'count': len(self.active_trades)}, f)
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json.dump({
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'active_trades': self.active_trades,
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'count': len(self.active_trades),
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'portfolio_value': round(portfolio_val, 2),
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'max_trade_usdt': round(self.max_trade_usdt, 2),
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'timestamp': datetime.now().isoformat()
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}, f)
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os.replace(temp_file, '/home/marc/bot-deploy/active_trades.json')
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except Exception as e:
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logger.warning(f'Failed to save active_trades.json: {e}')
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logger.warning(f"Failed to save trades: {e}")
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# Verify data freshness (Log entry_times for debug)
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if self.active_trades:
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oldest = min([t['entry_time'] for t in self.active_trades.values()])
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logger.info(f"DATA FRESHNESS: Oldest trade entry @ {oldest[:19]} (fresh from API)")
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logger.info("=" * 70)
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def run(self):
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"""Infinite trading loop"""
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logger.info("=" * 70)
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logger.info("TRADING BOT V0.3 STARTED")
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logger.info(f"Symbols: {SYMBOLS}")
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logger.info(f"Strategy: Local Min Signals | Risk: TP=+{TAKE_PROFIT_PCT*100:.1f}% / SL={STOP_LOSS_PCT*100:.1f}%")
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logger.info(f"KEY FIX: Fresh balance fetched EVERY cycle (no stale cache!)")
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logger.info("=" * 70)
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try:
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while True:
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self.cycle()
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time.sleep(CYCLE_SEC)
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except KeyboardInterrupt:
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logger.info("Bot stopped by user")
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except Exception as e:
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logger.error(f"CRITICAL ERROR: {e}")
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raise
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if __name__ == '__main__':
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bot = TradingBotV03()
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bot.run()
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import sys
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from dotenv import load_dotenv
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load_dotenv('/home/marc/bot-deploy/.env')
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bot = TradingBotV04()
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if len(sys.argv) > 1 and sys.argv[1] == '--once':
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bot.run_cycle()
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else:
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logger.info("Starting Bot V0.4 cycle loop...")
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while True:
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try:
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bot.run_cycle()
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except Exception as e:
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logger.error(f"Cycle error: {e}")
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time.sleep(CYCLE_SEC)
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