import ccxt import pandas as pd import ta from colorama import init, Fore, Style import time import logging import sqlite3 import subprocess import json import requests import numpy as np from datetime import datetime # ตั้งค่า logging logging.basicConfig(filename='trading_bot.log', level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s') # ตั้งค่า colorama สำหรับคอนโซล init(autoreset=True) # ตั้งค่า SQLite สำหรับบันทึกการซื้อขาย conn = sqlite3.connect('trades.db') c = conn.cursor() c.execute('''CREATE TABLE IF NOT EXISTS trades (timestamp TEXT, exchange TEXT, type TEXT, entry_price REAL, exit_price REAL, amount REAL, profit REAL)''') conn.commit() # ตั้งค่า API สำหรับ Binance, LBank, Gate.io exchanges = { 'binance': ccxt.binance({ 'apiKey': 'YOUR_BINANCE_API_KEY', 'secret': 'YOUR_BINANCE_SECRET', 'enableRateLimit': True, }), 'lbank': ccxt.lbank({ 'apiKey': 'YOUR_LBANK_API_KEY', 'secret': 'YOUR_LBANK_SECRET', 'enableRateLimit': True, }), 'gateio': ccxt.gateio({ 'apiKey': 'YOUR_GATEIO_API_KEY', 'secret': 'YOUR_GATEIO_SECRET', 'enableRateLimit': True, }) } # ตั้งค่า Telegram สำหรับการแจ้งเตือน TELEGRAM_BOT_TOKEN = 'YOUR_TELEGRAM_BOT_TOKEN' TELEGRAM_CHAT_ID = 'YOUR_TELEGRAM_CHAT_ID' # การตั้งค่าการเทรด symbol = 'BTC/USDT' timeframe = '4h' investment_percentage = 0.25 # ใช้ 25% ของยอดเงิน sl_percentage = 0.30 # Stop Loss 30% tp_percentage = 0.10 # Take Profit 10% # ฟังก์ชันส่งการแจ้งเตือน Telegram def send_telegram_alert(message): url = f"https://api.telegram.org/bot{TELEGRAM_BOT_TOKEN}/sendMessage" payload = {'chat_id': TELEGRAM_CHAT_ID, 'text': message} try: requests.post(url, json=payload) except Exception as e: logging.error(f"Telegram Alert Error: {str(e)}") print(f"{Fore.RED}Telegram Alert Error: {str(e)}") # ฟังก์ชันเรียก Codex CLI def run_codex_exec(task, reasoning_level='medium'): try: result = subprocess.run([ 'codex', 'exec', '-s', 'restricted-access', '-c', f'model_reasoning_effort={reasoning_level}', task ], capture_output=True, text=True) if result.returncode == 0: return json.loads(result.stdout) else: logging.error(f"Codex Error: {result.stderr}") return None except Exception as e: logging.error(f"Codex Execution Error: {str(e)}") return None # ฟังก์ชันคำนวณ Fibonacci Levels def calculate_fibonacci_levels(high, low): diff = high - low fib_levels = { '0.0%': low, '23.6%': low + diff * 0.236, '38.2%': low + diff * 0.382, '50.0%': low + diff * 0.50, '61.8%': low + diff * 0.618, '78.6%': low + diff * 0.786, '100.0%': high, '127.2%': high + diff * 0.272, '161.8%': high + diff * 0.618 } return fib_levels # ฟังก์ชันดึงข้อมูล OHLCV และคำนวณตัวชี้วัด def get_ohlcv(exchange, symbol, timeframe): ohlcv = exchange.fetch_ohlcv(symbol, timeframe, limit=100) df = pd.DataFrame(ohlcv, columns=['timestamp', 'open', 'high', 'low', 'close', 'volume']) df['timestamp'] = pd.to_datetime(df['timestamp'], unit='ms') # คำนวณ SMA และ RSI df['sma_fast'] = ta.trend.sma_indicator(df['close'], window=10) df['sma_slow'] = ta.trend.sma_indicator(df['close'], window=20) df['rsi'] = ta.momentum.rsi_indicator(df['close'], window=14) return df # ฟังก์ชันตรวจสอบสัญญาณซื้อ/ขาย def check_signal(df, exchange_name): last_row = df.iloc[-1] prev_row = df.iloc[-2] # ใช้ Codex CLI เพื่อวิเคราะห์สัญญาณเพิ่มเติม codex_task = f"Analyze 4H OHLCV data for BTC/USDT on {exchange_name} and confirm if SMA crossover is valid with RSI" codex_result = run_codex_exec(codex_task, reasoning_level='medium') signal = None if (prev_row['sma_fast'] < prev_row['sma_slow'] and last_row['sma_fast'] > last_row['sma_slow'] and last_row['rsi'] < 70): # Long: SMA Fast ตัดขึ้น SMA Slow และ RSI ไม่ Overbought signal = 'BUY' elif (prev_row['sma_fast'] > prev_row['sma_slow'] and last_row['sma_fast'] < last_row['sma_slow'] and last_row['rsi'] > 30): # Short: SMA Fast ตัดลง SMA Slow และ RSI ไม่ Oversold signal = 'SELL' if signal and codex_result and codex_result.get('is_valid', False): return signal return None # ฟังก์ชันแสดงสถานะกระพริบ def blink_status(message, color=Fore.YELLOW): for _ in range(3): print(f"{color}🚨 {message} 🚨{Style.RESET_ALL}") time.sleep(0.5) print("\033[1A\033[K", end="") # ลบข้อความก่อนหน้า time.sleep(0.5) # ฟังก์ชันแสดง Progress Bar def display_progress_bar(): print(f"{Fore.CYAN}Analyzing...{Style.RESET_ALL}", end="") for _ in range(10): print("█", end="", flush=True) time.sleep(0.2) print(f"{Fore.GREEN} Done!{Style.RESET_ALL}") # ฟังก์ชันหลักของบอต def trading_bot(): positions = {} # เก็บสถานะ Position สำหรับแต่ละกระดาน while True: try: # รัน Parallel Tasks สำหรับแต่ละกระดาน for exchange_name, exchange in exchanges.items(): print(f"\n{Fore.CYAN}=== Checking {exchange_name} ===") display_progress_bar() # ดึงข้อมูล OHLCV df = get_ohlcv(exchange, symbol, timeframe) current_price = df['close'].iloc[-1] # ตรวจสอบสัญญาณ signal = check_signal(df, exchange_name) if signal: blink_status(f"Signal Detected: {signal} on {exchange_name}!", Fore.RED) logging.info(f"Signal Detected: {signal} on {exchange_name} at price {current_price}") send_telegram_alert(f"🚨 Signal Detected: {signal} on {exchange_name} at {current_price}") # คำนวณ Fibonacci Levels ด้วย Codex CLI high = df['high'].iloc[-20:].max() low = df['low'].iloc[-20:].min() codex_task = f"Calculate Fibonacci retracement levels for BTC/USDT with high={high} and low={low}" fib_levels = run_codex_exec(codex_task, reasoning_level='low') or calculate_fibonacci_levels(high, low) # ดึงยอดเงินในบัญชี balance = exchange.fetch_balance()['total']['USDT'] investment = balance * investment_percentage amount = investment / current_price if signal == 'BUY' and exchange_name not in positions: # เข้า Long entry_price = current_price sl_price = entry_price * (1 - sl_percentage) tp_price = fib_levels['61.8%'] if fib_levels['61.8%'] > entry_price else entry_price * (1 + tp_percentage) order = exchange.create_market_buy_order(symbol, amount) positions[exchange_name] = { 'type': 'Long', 'entry_price': entry_price, 'sl_price': sl_price, 'tp_price': tp_price, 'amount': amount } logging.info(f"Opened Long Position on {exchange_name}: Entry={entry_price}, SL={sl_price}, TP={tp_price}, Amount={amount}") send_telegram_alert(f"🟢 Opened Long Position on {exchange_name}: Entry={entry_price}, SL={sl_price}, TP={tp_price}") print(f"{Fore.GREEN}🟢 Opened Long Position: Entry={entry_price}, SL={sl_price}, TP={tp_price}") elif signal == 'SELL' and exchange_name not in positions: # เข้า Short entry_price = current_price sl_price = entry_price * (1 + sl_percentage) tp_price = fib_levels['38.2%'] if fib_levels['38.2%'] < entry_price else entry_price * (1 - tp_percentage) order = exchange.create_market_sell_order(symbol, amount) positions[exchange_name] = { 'type': 'Short', 'entry_price': entry_price, 'sl_price': sl_price, 'tp_price': tp_price, 'amount': amount } logging.info(f"Opened Short Position on {exchange_name}: Entry={entry_price}, SL={sl_price}, TP={tp_price}, Amount={amount}") send_telegram_alert(f"🔴 Opened Short Position on {exchange_name}: Entry={entry_price}, SL={sl_price}, TP={tp_price}") print(f"{Fore.RED}🔴 Opened Short Position: Entry={entry_price}, SL={sl_price}, TP={tp_price}") # ตรวจสอบ Position ที่เปิดอยู่ if exchange_name in positions: pos = positions[exchange_name] print(f"{Fore.MAGENTA}Position Status: {pos['type']} | Entry: {pos['entry_price']} | Current: {current_price} | SL: {pos['sl_price']} | TP: {pos['tp_price']}") # ตรวจสอบ SL/TP if pos['type'] == 'Long' and (current_price <= pos['sl_price'] or current_price >= pos['tp_price']): exchange.create_market_sell_order(symbol, pos['amount']) profit = (current_price - pos['entry_price']) * pos['amount'] c.execute("INSERT INTO trades VALUES (?, ?, ?, ?, ?, ?, ?)", (datetime.now().strftime('%Y-%m-%d %H:%M:%S'), exchange_name, 'Long', pos['entry_price'], current_price, pos['amount'], profit)) conn.commit() logging.info(f"Closed Long Position on {exchange_name}: Price={current_price}, Profit={profit}") send_telegram_alert(f"🟡 Closed Long Position on {exchange_name}: Price={current_price}, Profit={profit}") print(f"{Fore.YELLOW}🟡 Closed Long Position: Price={current_price}, Profit={profit}") del positions[exchange_name] elif pos['type'] == 'Short' and (current_price >= pos['sl_price'] or current_price <= pos['tp_price']): exchange.create_market_buy_order(symbol, pos['amount']) profit = (pos['entry_price'] - current_price) * pos['amount'] c.execute("INSERT INTO trades VALUES (?, ?, ?, ?, ?, ?, ?)", (datetime.now().strftime('%Y-%m-%d %H:%M:%S'), exchange_name, 'Short', pos['entry_price'], current_price, pos['amount'], profit)) conn.commit() logging.info(f"Closed Short Position on {exchange_name}: Price={current_price}, Profit={profit}") send_telegram_alert(f"🟡 Closed Short Position on {exchange_name}: Price={current_price}, Profit={profit}") print(f"{Fore.YELLOW}🟡 Closed Short Position: Price={current_price}, Profit={profit}") del positions[exchange_name] # รอ 5 นาทีก่อนตรวจสอบครั้งต่อไป time.sleep(300) except Exception as e: logging.error(f"Error: {str(e)}") print(f"{Fore.RED}Error: {str(e)}") time.sleep(60) finally: conn.commit() # รันบอต if __name__ == "__main__": print(f"{Fore.CYAN}=== Starting Trading Bot ===") trading_bot() conn.close()