import sys, time, random, os
import json

# load strategy
# from strategies.indicator import StrategyIndicator
from backtesting import Backtest  # short-tp error
import tracemalloc

# load functions
# from indicator_util import get_indicators_values
from signal_helper import *

# load db
from db import DB

from itertools import combinations
from datetime import datetime
from dateutil.relativedelta import relativedelta
# from trade.candle import CandlePatterns
import warnings
from time import sleep

from strategy import StrategyCandlePattern
from multiprocessing import Process, freeze_support

from cProfile import Profile
from pstats import Stats

import gc

warnings.filterwarnings(action='ignore')


_db = DB()

# set config
start_time = time.time()
top_cash = 0
top_profit = 20
top_win_rate = 60
# best_pattern_arr = []

# [0, 0.23, 0.38, 0.5, 0.61, 0.78, 0.88, 1]
# pivonachi
profit_arr = [0] + pivo(60)
loss_arr = [0] + pivo(60)

# 시그널 보조 지표
base_indicators = [
    {'HEI': None},
    {'RSI_DIV': 14},
    {'MFI_DIV': 14},
    {'CCI_DIV': 20},
    {'WILLR_DIV': 28},
    {'RSI': 14},
    {'BBANDS': [20, 2]},
    {'BBANDS': [34, 2]},
    {'CCI': 14},
    {'AROON': 14},
    {'SAR': [0.00252, 0.22]},
    {'AROONOSC': 14},
    {'BOP': 14},
    {'CCI': 20},
    {'MFI': 14},
    {'MOM': 10},
    {'MOM': 14},
    {'ROC': 9},
    {'ROC': 14},
    {'WILLR': 14},
]
# 시그널 주도 지표(필터링될 지표)
signal_indicators = [
    {'STOCH_DIV': [14, 1, 1]},
    {'STOCH_DIV': [14, 3, 3]},
    # {'STOCH_DIV': [20, 12, 12]},
    {'STOCHRSI_DIV': [14, 14, 3]},
    {'CMO_DIV': 14},
    {'CCI_DIV': 14},
    {'ADX_DIV': 14},
    {'BOP_DIV': 0},
    {'OBV_DIV': 0},
    {'MOM_DIV': 10},
    {'ROC_DIV': 14},
    {'ROC_DIV': 9},
    {'STOCH_DIV': [14, 3, 14]},
    {'STOCH_DIV': [14, 3, 5]},
    {'ADOSC_DIV': [3, 10]},
    {'ULTOSC_DIV': [7, 14, 28]},
    {'TRIX': [14, 9]},
    {'STOCH': [20, 12, 12]},
    {'STOCH': [14, 3, 14]},
    {'STOCH': [14, 3, 5]},
    {'DMI': 14},
    {'DI': 21},
    {'APO': [10, 20]},
    {'MACD': [12, 26, 9]},
    {'MACDFIX': 26},
    {'MACDFIX': 9},
    {'MACDFIX': 14},
    {'MACDFIX': 31},
    {'PPO': [12, 26, 9]},
    {'STOCHF': [14, 3]},
    {'STOCHRSI': [14, 14, 3]},
    {'ULTOSC': [7, 14, 28]},
    {'EMA': 30},
    {'EMA': 55},
    {'DEMA': 55},
    {'DEMA': 100},
    {'DEMA': 200},
    {'MA': 21},
    {'MA': 55},
    {'MA': 100},
    {'MAMA': [0.5, 0.05]},
    {'T3': [100, 10]},
    {'TRIMA': 30},
    {'TRIMA': 50},
    {'WMA': 30},
    {'WMA': 20},
]


# multi Treading - fackage
def simulrating_by_item_fackage(item, data, t_time):
    global start_time
    global base_indicators
    global signal_indicators
    # global _db

    _db = DB()
    cash = 1000
    commission = .005

    top_info = _db.select_top_date(item['job'])
    min_profit = 7
    if str(item['trade_type']) == 'double':
        min_profit = 14

    if top_info['profit_rate'] is None:
        global top_profit
        global top_win_rate
    else:
        top_profit = float(top_info['profit_rate'])
        top_win_rate = float(top_info['win_rate'])


    filtered_signal_indicators = []
    for indicator in signal_indicators:
        for profit in profit_arr:
            for loss in loss_arr:
                # if str(item['trade_type']) == 'double' and loss > 0 and profit == 0:  # 숏 포지션 목표가만 있을 시 에러
                #     continue
                # if str(item['trade_type']) == 'double' and (loss != 0 or profit != 0):
                #     continue

                # for test
                # StrategyCandlePattern.use_indicators = [{"WMA": 30}, {"EMA": 30}, {"STOCHF": [14, 3]}]
                StrategyCandlePattern.use_indicators = [indicator]
                StrategyCandlePattern.up_target = float(profit)
                StrategyCandlePattern.down_target = float(loss)
                StrategyCandlePattern.trade_type = str(item['trade_type'])

                bt = Backtest(data, StrategyCandlePattern, cash=cash, commission=commission)
                bt.run()

                # 수익 및 거래 수 제한
                if float(bt._results['Return [%]']) > min_profit and float(bt._results['# Trades']) >= 5:
                    if indicator not in filtered_signal_indicators:
                        filtered_signal_indicators.append(indicator)

                    # if float(bt._results['Return [%]']) > top_profit or float(bt._results['Win Rate [%]']) >= 60:
                    # filename = 'chart/' + str(item['job']).replace('/', '_') + '_' + str(t_time) + '_' + str(
                    #     time.time())
                    # 단일 지표 미사용
                    # _db.insert_simul_result(
                    #     {
                    #         'item': str(item['job']).replace('/', '_'),
                    #         'time_type': t_time,
                    #         'results': bt._results,
                    #         'stop_profit': profit,
                    #         'stop_loss': loss,
                    #         'use_patterns': json.dumps(StrategyCandlePattern.use_indicators),
                    #         'use_pattern_cnt': len(StrategyCandlePattern.use_indicators),
                    #         'filename': filename,
                    #         'period_cycle': item['period_cycle'],
                    #         'trade_type': item['trade_type'],
                    #     })

                    # if bt._results['Return [%]'] > top_profit:
                    #     top_profit = bt._results['Return [%]']
                    # if bt._results['Win Rate [%]'] > top_win_rate:
                    #     top_win_rate = bt._results['Win Rate [%]']
                    # bt.plot(filename=filename, open_browser=False)

                    # best_pattern_arr.append({
                    #     't_time': t_time,
                    #     'indicators': [indicator],
                    #     'profit': profit,
                    #     'loss': loss,
                    #     'return': bt._results['Return [%]'],
                    #     'trades': bt._results['# Trades'],
                    # })

                bt = None
                del [[bt]]  # 112.3MB
        gc.collect()

    e = int(time.time() - start_time)
    print('시그널 지표 필터링 완료 :', '{:02d}:{:02d}:{:02d}'.format(e // 3600, (e % 3600 // 60), e % 60))
    print('지표 총합 :', len(filtered_signal_indicators) + len(base_indicators))
    print('필터 지표 리스트', filtered_signal_indicators)

    if len(filtered_signal_indicators) < 2:
        print(item, t_time, '- 수익 모델 조건을 만족하는 전략이 없습니다.')
        return

    all_indicators = filtered_signal_indicators[::-1] + base_indicators


# multi Treading - time
def simulrating_by_time(item, t_time):
    global _db

    '''
    "day": "24H",
    "hour12": "12H",
    "hour6": "06H",
    "hour": "01H",
    "minute30": "30M",
    "minute10": "10M",
    "minute5": "05M",
    "minute3": "03M",
    '''
    data = _db.get_price_data_from_item_table(item['job'], item['period_cycle'])

    df = pd.DataFrame(data)
    # date = df['date'].copy()

    # 최소 데이터 기준 일자 조건문(2달)
    std_date = datetime.now() - relativedelta(months=2)
    if df['date'][0] > std_date:
        df = None
        del [df]
        return

    df.set_index(df['date'], inplace=True)

    data_columns_init(df)
    df.index.name = str(item['job']).replace('/', '_')

    if t_time != 'hour' and t_time != 'day':
        time_type = {
            'hour': '60min',
            'hour2': '120min',
            'hour4': '240min',
            'hour6': '360min',
            'hour12': '720min',
            # 'week': 'W',
            # 'month': 'M',
        }
        ohlc_dict = {
            'Open': 'first',
            'High': 'max',
            'Low': 'min',
            'Close': 'last',
            'Volume': 'sum'
        }
        # df = df.resample(time_type[t_time], how=ohlc_dict, label='left', base=180)  # UTC (트레이딩뷰)
        df = df.resample(time_type[t_time], how=ohlc_dict, label='left', base=540)  # UTC (트레이딩뷰)
        df = df[:-1]

    return simulrating_by_item_fackage(item, df, t_time)

    df = None
    del [df]

def is_bot_by_exchange_name(item):
    target = item['job'].split('/')

    return _db.is_bot_by_exchange_name(target[1])

# reboot for windows
def reboot():
    return 'reboot!'
    # return os.system("shutdown -t 60 -r -f")

def start_backtest():
    global _db

    print('Started Simulating.', datetime.now())

    for item in _db.get_cron_list():
        # 이미 작동중인 봇이 있을 경우 제외 - 거래소 기준
        if is_bot_by_exchange_name(item):
            continue

        if item['time_unit'] == 'hour':
            for t_time in ['hour6', 'hour4']:  # 4시간, 6시간봉 시뮬레이팅
                return simulrating_by_time(item, t_time)

            return reboot()

        simulrating_by_time(item, item['time_unit'])

        return reboot()

    return reboot()


if __name__ == '__main__':
    tracemalloc.start()
    freeze_support()
    start_backtest()

    # profiler = Profile()
    # profiler.runcall(start_backtest)
    #
    # stats = Stats(profiler)
    # stats.strip_dirs()
    # stats.sort_stats()
    # stats.print_stats()

'''
메모리 절약해주는 라이브러리 사용하기
from profile import profile
from time import sleep
from sklearn import datasets # Just an example of 3rd party function call


# Method 1
run_profiling = profile(datasets.load_digits)
data = run_profiling()

# Method 2
@profile
def my_function():
    # do some stuff
    a_list = []
    for i in range(1,100000):
        a_list.append(i)
    return a_list


res = my_function()
'''