def build_args(self, cmds):
args = collections.defaultdict(dict)
strats = filter(Strat.is_valid, cmds.keys())
for strat in strats:
params = cmds[strat]
strat = Strat.get_strat(strat)
args["strategy"][strat] = params
masks = filter(Mask.is_valid, cmds.keys())
for mask in masks:
args["masks"][mask] = cmds[mask]
return args
def sign(self, symbol: str, timeframe: str):
"""
"""
df = self.exchange.GetSymbolKlines(symbol=symbol, interval=timeframe)
#df = self.exchange.technicalA(df)
df['3_ema'] = TA.EMA(df, 3)
df['25_sma'] = TA.SMA(df, 25)
#df['10_ema'] = TA.EMA(df, 10)
#df['55_ema'] = TA.EMA(df, 55)
#df2= TA.MACD(df = df, period_fast = 30, period_slow = 20, signal = 30)
df2 = TA.MACD(df, period_fast=30, period_slow=20, signal=30)
df2["HIST"] = df2["MACD"] - df2["SIGNAL"]
df["MACD"] = df2["MACD"]
df["SIGNAL"] = df2["SIGNAL"]
df["HIST"] = df2["HIST"]
df['HIST_ESMA'] = df['3_ema'] - df['25_sma']
#ADX
df["ADX"] = TA.ADX(df)
df["ADX"] = df["ADX"].fillna(0)
df["HIST_ESMA"] = df["HIST_ESMA"].fillna(0)
self.slopCalculator(df)
df.to_csv('./export.csv', sep='\t')
print(df)
exit()
df["sign"] = ""
entrypoint = 'off'
for i in range(0, len(df['close']) - 1):
#strategy_result = Strategies.marginTrade(df = df, step = i)
strategy_result = Strategies.tlStrategy(df=df, step=i)
if strategy_result['signal'] == 'BUY' and entrypoint == 'off':
#print('buy: ',i)
self.buy_signals.append([df['time'][i], df['low'][i]])
df.loc[i, 'sign'] = 'buy'
entrypoint = 'on'
elif strategy_result['signal'] == 'SELL' and entrypoint == 'on':
#print('sell: ',i)
df.loc[i, 'sign'] = 'sell'
self.sell_signals.append([df['time'][i], df['low'][i]])
entrypoint = 'off'
#print(self.sell_signals)
self.chart.plotData(df, symbol, timeframe, self.param,
self.buy_signals, self.sell_signals)
def buildStrategy(self, strats): strat = strats.keys()[0] params = strats[strat] return Strat.build(strat, params)