109 lines
3.7 KiB
Python
109 lines
3.7 KiB
Python
from binance.spot import Spot
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import talib
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import numpy as np
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import pandas as pd
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import time,setting
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import telegram_sender
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api_key = "HCpeel8g6fsTK2630b7BvGBcS09Z3qfXkLVcAY2JkpaiMm1J6DWRvoQZBQlElDJg"
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api_secret= "TySs6onlHOTrGzV8fMdDxLKTWWYnQ4rCHVAmjrcHby17acKflmo7xVTWVsbqtxe7"
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client = Spot(api_key, api_secret)
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## 获取所有现货交易对
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def get_symbols():
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data = client.exchange_info()["symbols"]
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# 创建DataFrame
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columns = ['symbol', 'status', 'baseAsset', 'quoteAsset']
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df = pd.DataFrame(data, columns=columns)
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# 过滤出在架交易对
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df_in_trade = df[df['status'] == 'TRADING']
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df_in_USDT = df_in_trade[df_in_trade['quoteAsset'] == 'USDT']
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return df_in_USDT['symbol']
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## 根据交易对和周期获取数据集
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def get_dataFrame(symbol,interval):
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# 获取 k 线数据
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data = client.klines(symbol, interval,limit=500)
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# 将数据转换为DataFrame
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columns = ['timestamp', 'open', 'high', 'low', 'close', 'volume',
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'close_time', 'quote_asset_volume', 'number_of_trades',
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'taker_buy_base_asset_volume', 'taker_buy_quote_asset_volume', 'ignore']
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df = pd.DataFrame(data, columns=columns)
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# 转化成 float
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df['open'] = df['open'].astype('float64')
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df['high'] = df['high'].astype('float64')
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df['low'] = df['low'].astype('float64')
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df['close'] = df['close'].astype('float64')
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df['volume'] = df['volume'].astype('float64')
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# 将时间戳转换为日期时间格式
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df['timestamp'] = pd.to_datetime(df['timestamp'], unit='ms')
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df['close_time'] = pd.to_datetime(df['close_time'], unit='ms')
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return df
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# crossover 函数：检测上穿信号
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def crossover(series1, series2):
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return (series1 > series2) & (series1.shift(1) <= series2.shift(1))
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# crossunder 函数：检测下穿信号
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def crossunder(series1, series2):
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return (series1 < series2) & (series1.shift(1) >= series2.shift(1))
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## 检查信号
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def check_signal(symbol, interval,df):
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## 计算 ema
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df['ema13'] = talib.EMA(df['close'], timeperiod=13)
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df['ema144'] = talib.EMA(df['close'], timeperiod=144)
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df['ema169'] = talib.EMA(df['close'], timeperiod=169)
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df['ema576'] = talib.EMA(df['close'], timeperiod=576)
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df['ema676'] = talib.EMA(df['close'], timeperiod=676)
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maxline = np.maximum(df['ema144'], df['ema169'])
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minline = np.minimum(df['ema144'], df['ema169'])
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shortArragement = df['ema13'] < minline
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longArrangement = df['ema13'] > maxline
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confuse = (df['ema13'] >= minline) & (df['ema13'] <= maxline)
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crossRatio = 0.2
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shortA = crossunder(df['ema13'], minline)
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shortB = shortArragement & crossunder(df['close'], minline) & (((minline - df['close']) / df.apply(lambda x: abs(x['open'] - x['close']), axis=1)) > crossRatio)
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df['shortResut'] = (shortA | shortB) & (confuse == False)
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longA = crossover(df['ema13'], maxline)
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longB = longArrangement & crossover(df['close'], maxline) & (((df['close'] - maxline) / df.apply(lambda x: abs(x['open'] - x['close']), axis=1)) > crossRatio)
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df['longResut'] = (longA | longB) & (confuse == False)
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latest = df.iloc[-1]
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direction = ""
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if latest['shortResut']==True:
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direction = '空'
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if latest['longResut']==True:
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direction = '多'
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message = f"⭐️信号提醒⭐️\r\n\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']}"
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print(f"{symbol} - {interval} is checked!")
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if direction != "":
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telegram_sender.send_message(setting.chat_id, message)
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def run(interval):
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print('Vegas策略运行....')
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symbols= get_symbols()
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for s in symbols:
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df = get_dataFrame(s, interval)
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check_signal(s,interval, df)
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time.sleep(1)
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