345 lines
9.6 KiB
Python
345 lines
9.6 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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import tracemalloc
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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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from cProfile import Profile
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from pstats import Stats
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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 = 60
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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(60)
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loss_arr = [0] + pivo(60)
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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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# 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 = 7
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if str(item['trade_type']) == 'double':
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min_profit = 14
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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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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]] # 112.3MB
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gc.collect()
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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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# 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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df = None
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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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return 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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return 'reboot!'
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# return os.system("shutdown -t 60 -r -f")
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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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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', 'hour4']: # 4시간, 6시간봉 시뮬레이팅
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return simulrating_by_time(item, t_time)
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return reboot()
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simulrating_by_time(item, item['time_unit'])
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return reboot()
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return reboot()
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if __name__ == '__main__':
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tracemalloc.start()
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freeze_support()
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start_backtest()
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# profiler = Profile()
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# profiler.runcall(start_backtest)
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#
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# stats = Stats(profiler)
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# stats.strip_dirs()
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# stats.sort_stats()
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# stats.print_stats()
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'''
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메모리 절약해주는 라이브러리 사용하기
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from profile import profile
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from time import sleep
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from sklearn import datasets # Just an example of 3rd party function call
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# Method 1
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run_profiling = profile(datasets.load_digits)
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data = run_profiling()
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# Method 2
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@profile
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def my_function():
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# do some stuff
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a_list = []
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for i in range(1,100000):
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a_list.append(i)
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return a_list
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res = my_function()
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'''
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