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

跟BotFather聊天

輸入/newbot

之後他會問你要取什麼名字,注意名字要用bot結尾,之後如果沒有跟別人撞名

應該就會新建好一個bot同時他會告訴你該bot的apiToken

chatID取得:

這個更簡單了跟IDBot聊天輸入:/start

IDBot就會回覆你一個chatID

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