483 lines
16 KiB
Python
483 lines
16 KiB
Python
import sys, time, random, os
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import json
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# load strategy
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# from strategies.indicator import StrategyIndicator
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from backtesting import Backtest # short-tp error
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# load functions
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# from indicator_util import get_indicators_values
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from signal_helper import *
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# load db
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from db import DB
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from itertools import combinations
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from datetime import datetime
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from dateutil.relativedelta import relativedelta
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# from trade.candle import CandlePatterns
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import warnings
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from time import sleep
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from strategy import StrategyCandlePattern
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from multiprocessing import Process, freeze_support
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import gc
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warnings.filterwarnings(action='ignore')
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_db = DB()
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# set config
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start_time = time.time()
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top_cash = 0
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top_profit = 20
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top_win_rate = 90
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# best_pattern_arr = []
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# [0, 0.23, 0.38, 0.5, 0.61, 0.78, 0.88, 1]
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# pivonachi
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profit_arr = [0] + pivo(25)
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loss_arr = [0] + pivo(25)
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# 시그널 보조 지표
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base_indicators = [
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{'HEI': None},
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{'RSI_DIV': 14},
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{'MFI_DIV': 14},
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{'CCI_DIV': 20},
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{'WILLR_DIV': 28},
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{'RSI': 14},
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{'BBANDS': [20, 2]},
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{'BBANDS': [34, 2]},
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{'CCI': 14},
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{'AROON': 14},
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{'SAR': [0.00252, 0.22]},
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{'AROONOSC': 14},
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{'BOP': 14},
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{'CCI': 20},
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{'MFI': 14},
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{'MOM': 10},
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{'MOM': 14},
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{'ROC': 9},
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{'ROC': 14},
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{'WILLR': 14},
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]
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# 시그널 주도 지표(필터링될 지표)
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signal_indicators = [
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{'STOCH_DIV': [14, 1, 1]},
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{'STOCH_DIV': [14, 3, 3]},
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# {'STOCH_DIV': [20, 12, 12]},
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{'STOCHRSI_DIV': [14, 14, 3]},
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{'CMO_DIV': 14},
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{'CCI_DIV': 14},
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{'ADX_DIV': 14},
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{'BOP_DIV': 0},
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{'OBV_DIV': 0},
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{'MOM_DIV': 10},
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{'ROC_DIV': 14},
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{'ROC_DIV': 9},
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{'STOCH_DIV': [14, 3, 14]},
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{'STOCH_DIV': [14, 3, 5]},
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{'ADOSC_DIV': [3, 10]},
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{'ULTOSC_DIV': [7, 14, 28]},
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{'TRIX': [14, 9]},
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{'STOCH': [20, 12, 12]},
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{'STOCH': [14, 3, 14]},
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{'STOCH': [14, 3, 5]},
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{'DMI': 14},
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{'DI': 21},
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{'APO': [10, 20]},
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{'MACD': [12, 26, 9]},
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{'MACDFIX': 26},
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{'MACDFIX': 9},
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{'MACDFIX': 14},
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{'MACDFIX': 31},
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{'PPO': [12, 26, 9]},
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{'STOCHF': [14, 3]},
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{'STOCHRSI': [14, 14, 3]},
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{'ULTOSC': [7, 14, 28]},
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{'EMA': 30},
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{'EMA': 55},
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{'DEMA': 55},
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{'DEMA': 100},
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{'DEMA': 200},
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{'MA': 21},
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{'MA': 55},
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{'MA': 100},
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{'MAMA': [0.5, 0.05]},
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{'T3': [100, 10]},
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{'TRIMA': 30},
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{'TRIMA': 50},
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{'WMA': 30},
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{'WMA': 20},
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]
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'''
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# for test
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# base_indicators = [{'RSI': 14}, {'BBANDS': [34, 2]}, {'CCI': 20}, {'MFI': 14}, {'MOM': 14}]
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# signal_indicators = [{'STOCH_DIV': [14, 3, 3]}, {'ROC_DIV': 14}, {'STOCH_DIV': [14, 3, 5]}]
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data = _db.get_price_data_from_item_table('crypto/bithumb/KRW-BTC/day', '6_M')
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df = pd.DataFrame(data)
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df.set_index(df['date'], inplace=True)
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data_columns_init(df)
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df.index.name = str('crypto/bithumb/KRW-BTC/day').replace('/', '_')
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StrategyCandlePattern.use_indicators = [{'HEI': None}]
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StrategyCandlePattern.up_target = float(0)
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StrategyCandlePattern.down_target = float(0)
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bt = Backtest(df, StrategyCandlePattern, cash=cash, commission=commission)
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bt.run()
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print(bt._results)
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bt.plot()
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sys.exit(1)
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'''
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# multi Treading - item
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def simulrating_by_item(item, data, all_indicators, idx, t_time):
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# from guppy.heapy import RM # for monitoring
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global start_time
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# global _db
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_db = DB()
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cash = 1000
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commission = .005
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print('작업 시작 : %s / 지표 수 : %s / 시간프레임 : %s' % (item['job'], idx, t_time))
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# get top_profit and win rate from item-t_time
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top_info = _db.select_top_date(item['job'])
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min_profit = 22
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if str(item['trade_type']) == 'double':
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min_profit = 30
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if top_info['profit_rate'] is None:
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global top_profit
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global top_win_rate
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else:
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top_profit = float(top_info['profit_rate'])
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top_win_rate = float(top_info['win_rate'])
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# bt = Backtest(data, StrategyCandlePattern, cash=cash, commission=commission)
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for indicators in list(combinations(all_indicators, idx)):
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for profit in profit_arr:
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for loss in loss_arr:
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# if str(item['trade_type']) == 'double' and loss > 0 and profit == 0: # 숏 포지션 목표가만 있을 시 에러
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# continue
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# if str(item['trade_type']) == 'double' and (loss != 0 or profit != 0):
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# continue
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StrategyCandlePattern.use_indicators = list(indicators)
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StrategyCandlePattern.up_target = float(profit)
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StrategyCandlePattern.down_target = float(loss)
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StrategyCandlePattern.trade_type = str(item['trade_type'])
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bt = Backtest(data, StrategyCandlePattern, cash=cash, commission=commission)
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bt.run()
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# 수익 및 거래 수 제한
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if bt._results['# Trades'] >= 5 and bt._results['Return [%]'] > min_profit and \
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(bt._results['Return [%]'] > top_profit or float(bt._results['Win Rate [%]']) >= 100):
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filename = 'chart/' + str(item['job']).replace('/', '_') + '_' + str(t_time) + '_' + str(
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time.time())
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_db.insert_simul_result(
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{
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'item': str(item['job']).replace('/', '_'),
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'time_type': t_time,
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'results': bt._results,
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'stop_profit': profit,
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'stop_loss': loss,
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'use_patterns': json.dumps(StrategyCandlePattern.use_indicators),
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'use_pattern_cnt': len(StrategyCandlePattern.use_indicators),
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'filename': filename,
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'period_cycle': item['period_cycle'],
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'trade_type': item['trade_type'],
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})
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if bt._results['Return [%]'] > top_profit:
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top_profit = bt._results['Return [%]']
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# print('-' * 60)
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# print('트레이딩 종류 :', item['trade_type'])
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# print('시간봉 :', t_time)
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# print('지표 조합 개수 :', idx)
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# print('지표 :', StrategyCandlePattern.use_indicators)
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# print("적용된 스탑프로핏 : %0.2f%%" % profit)
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# print("적용된 스탑로스 : %0.2f%%" % loss)
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# print("총 수익률 : %0.2f%%" % bt._results['Return [%]'])
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# print("최종 금액 : %0.2f" % bt._results['Equity Final [$]'])
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# print("거래 수 :", bt._results['# Trades'])
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# print("파일명 :", filename)
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# print('-' * 60)
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# bt.plot()
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if bt._results['Return [%]'] > 50 and float(
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bt._results['Win Rate [%]']) >= 100: # 최상의 수익인 경우 차트 저장
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bt.plot(filename=filename, open_browser=False)
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del [[filename]]
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if bt._results['Win Rate [%]'] >= top_win_rate:
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top_win_rate = bt._results['Win Rate [%]']
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# best_pattern_arr.append({
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# 't_time': t_time,
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# 'indicators': indicators,
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# 'profit': profit,
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# 'loss': loss,
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# 'return': bt._results['Return [%]'],
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# 'trades': bt._results['# Trades'],
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# })
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bt = None
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del [[bt]]
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gc.collect()
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e = int(time.time() - start_time)
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print('(완료) 조합 지표 개수 :', idx, t_time, '{:02d}:{:02d}:{:02d}'.format(e // 3600, (e % 3600 // 60), e % 60))
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print(datetime.now())
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del [[cash, commission, top_info, _db]]
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# del [[item, data, all_indicators, idx, t_time]]
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gc.collect()
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# multi Treading - fackage
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def simulrating_by_item_fackage(item, data, t_time):
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global start_time
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global base_indicators
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global signal_indicators
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global _db
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# _db = DB()
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cash = 1000
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commission = .005
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top_info = _db.select_top_date(item['job'])
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min_profit = 17
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if str(item['trade_type']) == 'double':
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min_profit = 17
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if top_info['profit_rate'] is None:
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global top_profit
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global top_win_rate
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else:
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top_profit = float(top_info['profit_rate'])
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top_win_rate = float(top_info['win_rate'])
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# bt = Backtest(data, StrategyCandlePattern, cash=cash, commission=commission)
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filtered_signal_indicators = []
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for indicator in signal_indicators:
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for profit in profit_arr:
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for loss in loss_arr:
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# if str(item['trade_type']) == 'double' and loss > 0 and profit == 0: # 숏 포지션 목표가만 있을 시 에러
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# continue
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# if str(item['trade_type']) == 'double' and (loss != 0 or profit != 0):
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# continue
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# for test
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# StrategyCandlePattern.use_indicators = [{"WMA": 30}, {"EMA": 30}, {"STOCHF": [14, 3]}]
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StrategyCandlePattern.use_indicators = [indicator]
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StrategyCandlePattern.up_target = float(profit)
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StrategyCandlePattern.down_target = float(loss)
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StrategyCandlePattern.trade_type = str(item['trade_type'])
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bt = Backtest(data, StrategyCandlePattern, cash=cash, commission=commission)
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bt.run()
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# 수익 및 거래 수 제한
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if float(bt._results['Return [%]']) > min_profit and float(bt._results['# Trades']) >= 5:
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if indicator not in filtered_signal_indicators:
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filtered_signal_indicators.append(indicator)
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# if float(bt._results['Return [%]']) > top_profit or float(bt._results['Win Rate [%]']) >= 60:
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# filename = 'chart/' + str(item['job']).replace('/', '_') + '_' + str(t_time) + '_' + str(
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# time.time())
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# 단일 지표 미사용
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# _db.insert_simul_result(
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# {
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# 'item': str(item['job']).replace('/', '_'),
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# 'time_type': t_time,
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# 'results': bt._results,
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# 'stop_profit': profit,
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# 'stop_loss': loss,
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# 'use_patterns': json.dumps(StrategyCandlePattern.use_indicators),
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# 'use_pattern_cnt': len(StrategyCandlePattern.use_indicators),
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# 'filename': filename,
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# 'period_cycle': item['period_cycle'],
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# 'trade_type': item['trade_type'],
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# })
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# if bt._results['Return [%]'] > top_profit:
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# top_profit = bt._results['Return [%]']
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# if bt._results['Win Rate [%]'] > top_win_rate:
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# top_win_rate = bt._results['Win Rate [%]']
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# bt.plot(filename=filename, open_browser=False)
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# best_pattern_arr.append({
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# 't_time': t_time,
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# 'indicators': [indicator],
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# 'profit': profit,
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# 'loss': loss,
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# 'return': bt._results['Return [%]'],
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# 'trades': bt._results['# Trades'],
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# })
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bt = None
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del [[bt]]
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# 총 32개 이하로 유지
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filtered_signal_indicators = filtered_signal_indicators[:12]
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e = int(time.time() - start_time)
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print('시그널 지표 필터링 완료 :', '{:02d}:{:02d}:{:02d}'.format(e // 3600, (e % 3600 // 60), e % 60))
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print('지표 총합 :', len(filtered_signal_indicators) + len(base_indicators))
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print('필터 지표 리스트', filtered_signal_indicators)
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if len(filtered_signal_indicators) < 2:
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print(item, t_time, '- 수익 모델 조건을 만족하는 전략이 없습니다.')
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return
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all_indicators = filtered_signal_indicators[::-1] + base_indicators
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joined = []
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for idx in range(2, 5):
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_p = Process(target=simulrating_by_item, args=(item, data, all_indicators, idx, t_time,))
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_p.start()
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joined.append(_p)
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del [[item, data, all_indicators, idx, t_time, cash, commission, top_info]]
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gc.collect()
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# 프로세스 조인
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for _p in joined:
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_p.join()
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# multi Treading - time
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def simulrating_by_time(item, t_time):
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global _db
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'''
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"day": "24H",
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"hour12": "12H",
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"hour6": "06H",
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"hour": "01H",
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"minute30": "30M",
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"minute10": "10M",
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"minute5": "05M",
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"minute3": "03M",
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'''
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data = _db.get_price_data_from_item_table(item['job'], item['period_cycle'])
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df = pd.DataFrame(data)
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# date = df['date'].copy()
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# 최소 데이터 기준 일자 조건문(2달)
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std_date = datetime.now() - relativedelta(months=2)
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if df['date'][0] > std_date:
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del [[df]]
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return
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df.set_index(df['date'], inplace=True)
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data_columns_init(df)
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df.index.name = str(item['job']).replace('/', '_')
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if t_time != 'hour' and t_time != 'day':
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time_type = {
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'hour': '60min',
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'hour2': '120min',
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'hour4': '240min',
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'hour6': '360min',
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'hour12': '720min',
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# 'week': 'W',
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# 'month': 'M',
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}
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ohlc_dict = {
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'Open': 'first',
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'High': 'max',
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'Low': 'min',
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'Close': 'last',
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'Volume': 'sum'
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}
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# df = df.resample(time_type[t_time], how=ohlc_dict, label='left', base=180) # UTC (트레이딩뷰)
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df = df.resample(time_type[t_time], how=ohlc_dict, label='left', base=540) # UTC (트레이딩뷰)
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df = df[:-1]
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simulrating_by_item_fackage(item, df, t_time)
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df = None
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del [[df]]
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def is_bot_by_exchange_name(item):
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target = item['job'].split('/')
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return _db.is_bot_by_exchange_name(target[1])
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# reboot for windows
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def reboot():
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print('재부팅 예약 되었습니다.', datetime.now())
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return os.system("shutdown -t 60 -r -f")
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def record_item_per_time():
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# 테이블 생성해서 쓰고 지우기
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print('record_item_per_time')
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print(os.path.expanduser())
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def start_backtest():
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global _db
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print('Started Simulating.', datetime.now())
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zzz = True
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for item in _db.get_cron_list():
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# 이미 작동중인 봇이 있을 경우 제외 - 거래소 기준
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if is_bot_by_exchange_name(item):
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continue
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if item['time_unit'] == 'hour':
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for t_time in ['hour6']: # 6시간봉만 시뮬레이팅
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# for t_time in ['hour6', 'hour4']: # 4시간, 6시간봉 시뮬레이팅
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if _db.is_simulated_item_per_hour(item['job'], t_time):
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continue
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simulrating_by_time(item, t_time)
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# 타임프레임 시뮬레이터 상태 임시 저장
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_db.insert_item_from_simul_item_per_hour(item['job'], t_time)
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return reboot()
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# 타임프레임 시뮬레이터 상태 삭제
|
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_db.remove_item_from_simul_item_per_hour(item['job'])
|
|
_db.update_simul_init_value(item['job'])
|
|
|
|
return reboot()
|
|
|
|
simulrating_by_time(item, item['time_unit'])
|
|
_db.update_simul_init_value(item['job'])
|
|
|
|
return reboot()
|
|
|
|
if zzz:
|
|
print('There is no list of items to run.', datetime.now())
|
|
time.sleep(43400)
|
|
|
|
return reboot()
|
|
|
|
|
|
if __name__ == '__main__':
|
|
freeze_support()
|
|
start_backtest()
|