from binance.spot import Spot
import talib
import numpy as np
import pandas as pd
import time,setting
import telegram_sender
import utils


api_key = "HCpeel8g6fsTK2630b7BvGBcS09Z3qfXkLVcAY2JkpaiMm1J6DWRvoQZBQlElDJg"
api_secret= "TySs6onlHOTrGzV8fMdDxLKTWWYnQ4rCHVAmjrcHby17acKflmo7xVTWVsbqtxe7"

client = Spot(api_key, api_secret)

## 获取所有现货交易对
def get_symbols():
    data = client.exchange_info()["symbols"]

    # 创建DataFrame
    columns = ['symbol', 'status', 'baseAsset', 'quoteAsset']
    df = pd.DataFrame(data, columns=columns)

    # 过滤出在架交易对
    df_in_trade = df[df['status'] == 'TRADING']
    df_in_USDT = df_in_trade[df_in_trade['quoteAsset'] == 'USDT']

    return df_in_USDT['symbol']

## 根据交易对和周期获取数据集
def get_dataFrame(symbol,interval):
    # 获取 k 线数据
    data = client.klines(symbol, interval,limit=500)

    # 将数据转换为DataFrame
    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 = pd.DataFrame(data, columns=columns)

    # 转化成 float
    df['open'] = df['open'].astype('float64')
    df['high'] = df['high'].astype('float64')
    df['low'] = df['low'].astype('float64')
    df['close'] = df['close'].astype('float64')
    df['volume'] = df['volume'].astype('float64')

    # 将时间戳转换为日期时间格式
    df['timestamp'] = pd.to_datetime(df['timestamp'], unit='ms')
    df['close_time'] = pd.to_datetime(df['close_time'], unit='ms')

    return df

# crossover 函数：检测上穿信号
def crossover(series1, series2):
    return (series1 > series2) & (series1.shift(1) <= series2.shift(1))

# crossunder 函数：检测下穿信号
def crossunder(series1, series2):
    return (series1 < series2) & (series1.shift(1) >= series2.shift(1))

## 检查信号
def check_signal(symbol, interval,df):
    ## 计算 ema
    df['ema13'] = talib.EMA(df['close'], timeperiod=13)
    df['ema144'] = talib.EMA(df['close'], timeperiod=144)
    df['ema169'] = talib.EMA(df['close'], timeperiod=169)
    df['ema576'] = talib.EMA(df['close'], timeperiod=576)
    df['ema676'] = talib.EMA(df['close'], timeperiod=676)

    maxline = np.maximum(df['ema144'], df['ema169'])
    minline = np.minimum(df['ema144'], df['ema169'])

    shortArragement = df['ema13'] < minline
    longArrangement = df['ema13'] > maxline
    confuse = (df['ema13'] >= minline) & (df['ema13'] <= maxline)
    crossRatio = 0.2

    shortA = crossunder(df['ema13'], minline)
    shortB = shortArragement & crossunder(df['close'], minline) & (((minline - df['close']) / df.apply(lambda x: abs(x['open'] - x['close']), axis=1)) > crossRatio)
    df['shortResut'] = (shortA | shortB) & (confuse == False)

    longA = crossover(df['ema13'], maxline)
    longB = longArrangement & crossover(df['close'], maxline) & (((df['close'] - maxline) / df.apply(lambda x: abs(x['open'] - x['close']), axis=1)) > crossRatio)
    df['longResut'] = (longA | longB) & (confuse == False)

    latest = df.iloc[-1]

    direction = ""
    if latest['shortResut']==True:
        direction = '空'
    if latest['longResut']==True:
        direction = '多'
    
    message = f"⭐️信号提醒⭐️\r\n\r\n策略:【Vegas趋势跟踪V1.0】\r\n品种: {symbol}\r\n周期: {interval}\r\n信号: 【{direction}】\r\n当前价格:{latest['open']}\r\n\r\n{latest['timestamp']}"
    print(f"{symbol} - {interval} is checked!")
    if direction != "":
        telegram_sender.send_message(setting.chat_id, message)
    
def run(interval):
    print('Vegas策略运行....')
    symbols = utils.get_top_binance_usdt_pairs(20)
    for s in symbols:
        df = get_dataFrame(s, interval)
        check_signal(s,interval, df)
        
        time.sleep(1)