main.py

# -*- coding: utf-8 -*-
"""
Created on Fri Sep 13 00:15:21 2024

@author: Administrator
chatgpt4o

"""

import pandas as pd
import time
from binance.client import Client
from binance.exceptions import BinanceAPIException
import os
from flask import Flask
import threading

# 從環境變數中讀取 API 密鑰
api_key = os.environ.get('API_KEY')
secret_key = os.environ.get('SECRET_KEY')

# 確保 API_KEY 和 SECRET_KEY 都存在，否則提醒錯誤
if not api_key or not secret_key:
    raise ValueError("API_KEY and SECRET_KEY must be set as environment variables.")

# 創建 Binance 客戶端
client = Client(api_key, secret_key)

# 設置交易對參數
symbol = 'BTCUSDT'  # 交易對，Binance格式無斜槓
timeframe = Client.KLINE_INTERVAL_15MINUTE  # 5分鐘K線
short_window = 7     # 短期均線窗口
long_window = 25     # 長期均線窗口
position = None      # 當前持倉（'long', 'short', 或者 None）

# 創建 Flask 應用
app = Flask(__name__)

def fetch_data(symbol, timeframe):
    # 從 Binance 獲取歷史 K 線數據
    try:
        klines = client.get_klines(symbol=symbol, interval=timeframe, limit=100)
        df = pd.DataFrame(klines, columns=['timestamp', 'open', 'high', 'low', 'close', 'volume', 'close_time',
                                           'quote_asset_volume', 'number_of_trades', 'taker_buy_base_asset_volume',
                                           'taker_buy_quote_asset_volume', 'ignore'])
        df['timestamp'] = pd.to_datetime(df['timestamp'], unit='ms')
        df['close'] = pd.to_numeric(df['close'])
        print('data ready')
        return df
    except BinanceAPIException as e:
        print(f"Error fetching data: {e}")
        return None

def calculate_sma(df, window):
    return df['close'].rolling(window=window).mean()

def check_for_signal(df):
    short_sma = calculate_sma(df, short_window)
    long_sma = calculate_sma(df, long_window)

    if short_sma.iloc[-1] > long_sma.iloc[-1] and short_sma.iloc[-2] <= long_sma.iloc[-2]:
        return 'buy'
    elif short_sma.iloc[-1] < long_sma.iloc[-1] and short_sma.iloc[-2] >= long_sma.iloc[-2]:
        return 'sell'
    # return None
    return print('no signal')

def place_order(symbol, side, amount):
    try:
        if side == 'buy':
            order = client.order_market_buy(symbol=symbol, quantity=amount)
        elif side == 'sell':
            order = client.order_market_sell(symbol=symbol, quantity=amount)
        print(f"Order placed: {side} {amount} {symbol}")
    except BinanceAPIException as e:
        print(f"An error occurred: {e}")

# 定義交易機器人邏輯
def run_trading_bot():
    global position
    while True:
        df = fetch_data(symbol, timeframe)
        if df is not None:
            signal = check_for_signal(df)

            if signal == 'buy' and position != 'long':
                print("Buy signal detected")
                place_order(symbol, 'buy', 0.001)  # 假設購買 0.001 BTC
                position = 'long'
            elif signal == 'sell' and position != 'short':
                print("Sell signal detected")
                place_order(symbol, 'sell', 0.001)  # 假設賣出 0.001 BTC
                position = 'short'

        time.sleep(60)  # 每分鐘檢查一次

# 提供健康檢查端點，Render 會通過這個端點檢查服務狀態
@app.route('/')
def home():
    return "交易機器人正在運行", 200

@app.route('/health')
def health():
    return "健康狀態良好", 200

# 在後台啟動交易機器人
if __name__ == '__main__':
    # 使用 threading 啟動交易機器人，讓 Flask 不阻塞
    bot_thread = threading.Thread(target=run_trading_bot)
    bot_thread.start()

    # 啟動 Flask Web 服務
    app.run(host='0.0.0.0', port=5000)