import requests
import pandas as pd
import time
from datetime import datetime, timedelta
import hmac
import hashlib
import base64
import urllib.parse
import json

def send_dingtalk_message(webhook, secret, message):
    timestamp = str(round(time.time() * 1000))
    secret_enc = secret.encode('utf-8')
    string_to_sign = '{}\n{}'.format(timestamp, secret)
    string_to_sign_enc = string_to_sign.encode('utf-8')
    hmac_code = hmac.new(secret_enc, string_to_sign_enc, digestmod=hashlib.sha256).digest()
    sign = urllib.parse.quote_plus(base64.b64encode(hmac_code))
    webhook = '{}&timestamp={}&sign={}'.format(webhook, timestamp, sign)
    headers = {'Content-Type': 'application/json'}
    data = {"msgtype": "text", "text": {"content": message}}
    response = requests.post(url=webhook, headers=headers, data=json.dumps(data))
    print(response.text)

def get_klines(symbol, interval, limit=500):
    url = "https://fapi.binance.com/fapi/v1/klines"
    params = {'symbol': symbol, 'interval': interval, 'limit': limit}
    response = requests.get(url, params=params)
    return response.json()


def calculate_macd(df, short_window=6, long_window=7, signal_window=4):
    df['EMA_short'] = df['Close'].ewm(span=short_window, adjust=False).mean()
    df['EMA_long'] = df['Close'].ewm(span=long_window, adjust=False).mean()
    df['MACD'] = df['EMA_short'] - df['EMA_long']
    df['Signal'] = df['MACD'].ewm(span=signal_window, adjust=False).mean()
    df['DIF'] = df['MACD'] - df['Signal']
    return df


def find_macd_crosses(df):
    crosses = []
    previous_dif = df.iloc[0]['DIF']
    for i, row in df.iterrows():
        current_dif = row['DIF']
        if previous_dif <= 0 and current_dif > 0:
            crosses.append((row['Time'], '金叉上涨', current_dif))
        elif previous_dif >= 0 and current_dif < 0:
            crosses.append((row['Time'], '死叉下跌', current_dif))
        previous_dif = current_dif
    return crosses


def convert_utc_to_local(utc_dt, offset=8):
    return utc_dt + timedelta(hours=offset)


last_cross_time = 0  # 初始化，记录上次交叉点的时间戳

def print_crosses(crosses, webhook, secret):
    global last_cross_time
    for cross in crosses:
        cross_time = cross[0] / 1000  # 获取交叉点的时间戳（秒）
        if cross_time > last_cross_time:  # 仅处理新的交叉点
            local_time = convert_utc_to_local(datetime.utcfromtimestamp(cross_time))
            time_str = local_time.strftime('%Y-%m-%d %H:%M:%S')
            message = f"穿越Time (UTC+8): {time_str}, Type: {cross[1]}, DIF: {cross[2]:.6f} 产生金叉后，等待DIF>0 在买，产生死叉后，等待DIF<0再卖。更稳妥"
            print(message)
            send_dingtalk_message(webhook, secret, message)  # 发送钉钉消息
            last_cross_time = cross_time  # 更新记录的时间戳
        else:
            print(f"No new crosses found at {datetime.now().strftime('%Y-%m-%d %H:%M:%S')} (UTC+8).")

def main():
    symbol = 'BTCUSDT'
    interval = '15m'
    webhook_url = "https://oapi.dingtalk.com/robot/send?access_token=8a6ddcf98d3b47c63333580bfe9d0bad55b17272eea05cc9c0af7f7be4de070d"
    secret = "你的秘钥"
    print("开始循环查询...")
    while True:
        klines = get_klines(symbol, interval, limit=100)
        df = pd.DataFrame(klines,
                          columns=['Time', '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['Close'] = pd.to_numeric(df['Close'])

        df = calculate_macd(df)
        crosses = find_macd_crosses(df)
        if crosses:
            print_crosses(crosses, webhook_url, secret)  # 将webhook和secret传递给print_crosses函数
        else:
            print(f"No crosses found at {datetime.now().strftime('%Y-%m-%d %H:%M:%S')} (UTC+8).")

        time.sleep(2)  # 每分钟查询一次


if __name__ == "__main__":
    main()