用不到150行python代碼打造專屬你自己的自動化binance自動下單交易程式

步驟1：安裝必要的庫

pip install python-binance

步驟2：設置API密鑰

步驟3：創建Python腳本

步驟4：定義place_order函數

步驟五:定義send_to_telegram函數

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步驟六:定義get_signal函數

import numpy as np
import finlab_crypto
from finlab_crypto import Strategy
pairs = ['BTCUSDT'] #交易對
freq = '15m' # 資料頻率
n1n2 = {}
for i in pairs:
    n1n2[i] = []
def Optimization(pair,freq):
    # 歷史價格數據
    ohlcv = finlab_crypto.crawler.get_nbars_binance(pair,freq,10000,client)
    #定義策略
    @Strategy(sma1=20, sma2=60)
    def sma_strategy(ohlcv):
    # 定義均線策略進出場條件
        close = ohlcv.close
        sma1 = close.rolling(sma_strategy.sma1).mean()
        sma2 = close.rolling(sma_strategy.sma2).mean()
        entries = (sma1 > sma2) & (sma1.shift() < sma2.shift())
        exits = (sma1 < sma2) & (sma1.shift() > sma2.shift())
        figures = {'overlaps': {'sma1': sma1,'sma1': sma2}}
    return entries, exits, figures
    # 策略超參數
    variables = {
    'sma1': np.arange(5, 100, 5),
    'sma2': np.arange(5, 200, 5),
    }
    #回測及優化
    portfolio = sma_strategy.backtest(ohlcv, variables=variables, freq=freq ,plot=True)
    temp = portfolio.total_profit()[portfolio.total_profit()==portfolio.total_profit().max()].to_frame().reset_index()
    n1n2[pair] = [temp['sma1'].values[0],temp['sma2'].values[0]]
for pair in pairs:
    portfolio = Optimization(pair,freq)

#定義策略
@Strategy(sma1=20, sma2=60)
def sma_strategy(ohlcv):
# 定義均線策略進出場條件
    close = ohlcv.close
    sma1 = close.rolling(sma_strategy.sma1).mean()
    sma2 = close.rolling(sma_strategy.sma2).mean()
    entries = (sma1 > sma2) & (sma1.shift() < sma2.shift())
    exits = (sma1 < sma2) & (sma1.shift() > sma2.shift())
    figures = {'overlaps': {'sma1': sma1,'sma1': sma2}}
return entries, exits, figures

portfolio = sma_strategy.backtest(ohlcv, variables=variables, freq=freq ,plot=True)
temp = portfolio.total_profit()[portfolio.total_profit()==portfolio.total_profit().max()].to_frame().reset_index()
n1n2[pair] = [temp['sma1'].values[0],temp['sma2'].values[0]]

def get_signal(
    pair='BTCUSDT',
    freq='15m',
    n_bar = 10000,
    client = client,
    n1 = 65,
    n2 = 95,
    ):
    # get data
    ohlcv = finlab_crypto.crawler.get_nbars_binance(pair,freq,n_bar,client)
    # get signal table
    table = pd.DataFrame()
    table['close'] = ohlcv.close
    table['n1'] = ohlcv.close.rolling(n1).mean()
    table['n2'] = ohlcv.close.rolling(n2).mean()
    table['buy'] = ((table['n1'] > table['n2']) & (table['n1'].shift() < table['n2'].shift())).astype(int)
    table['sell'] = ((table['n1'] < table['n2']) & (table['n1'].shift() > table['n2'].shift())).astype(int)
    table = table.replace(0,np.nan).tail(1)
    if table[['buy','sell']].sum().sum() == 0:
        signal = 'PASS'
    if table[['buy']].values[0][0] == 1:
        signal = 'BUY'
    if table[['sell']].values[0][0] == 1:
        signal = 'SELL'
    return signal,n1,n2