# source: https://raw.githubusercontent.com/remiotore/freqtrade/44beaeb6a420cd8e9f2e4ea93e11d6cfa192ee03/strategies/SMAOffsetOptV1.py

from freqtrade.strategy.interface import IStrategy
from typing import Dict, List
from functools import reduce
from pandas import DataFrame


import talib.abstract as ta
import numpy as np
import freqtrade.vendor.qtpylib.indicators as qtpylib
import datetime
from technical.util import resample_to_interval, resampled_merge
from datetime import datetime, timedelta
from freqtrade.persistence import Trade
from freqtrade.strategy import stoploss_from_open, merge_informative_pair, DecimalParameter, IntParameter, CategoricalParameter


ma_types = {
	'SMA': ta.SMA,
	'EMA': ta.EMA,
}

class Github_remiotore_freqtrade__SMAOffsetOptV1__20260111_210550(IStrategy):
	INTERFACE_VERSION = 2







	buy_params = {
		"base_nb_candles_buy": 34,
		"buy_trigger": 'SMA',
		"low_offset": 0.9,
	}







	sell_params = {
		"base_nb_candles_sell": 30,
		"high_offset": 1.012,
		"sell_trigger": 'EMA',
	}

	stoploss = -0.5

	minimal_roi = {
		"0": 0.10,
		"60": 0.07,
		"90": 0.056,
		"220": 0
	}
	base_nb_candles_buy = IntParameter(5, 80, default=buy_params['base_nb_candles_buy'], space='buy', optimize=False, load=True)
	base_nb_candles_sell = IntParameter(5, 80, default=sell_params['base_nb_candles_sell'], space='sell', optimize=False, load=True)
	low_offset = DecimalParameter(0.8, 0.99, default=buy_params['low_offset'], space='buy', optimize=False, load=True)
	high_offset = DecimalParameter(0.8, 1.1, default=sell_params['high_offset'], space='sell', optimize=False, load=True)
	buy_trigger = CategoricalParameter(ma_types.keys(), default=buy_params['buy_trigger'], space='buy', optimize=False, load=True)
	sell_trigger = CategoricalParameter(ma_types.keys(), default=sell_params['sell_trigger'], space='sell', optimize=False, load=True)

	trailing_stop = True
	trailing_stop_positive = 0.02
	trailing_stop_positive_offset = 0.051
	trailing_only_offset_is_reached = True

	timeframe = '5m'

	use_sell_signal = True
	sell_profit_only = False

	process_only_new_candles = True
	startup_candle_count = 50

	plot_config = {
		'main_plot': {
			'ma_offset_buy': {'color': 'orange'},
			'ma_offset_sell': {'color': 'orange'},
		},
	}

	use_custom_stoploss = False

	def custom_stoploss(self, pair: str, trade: 'Trade', current_time: datetime,
						current_rate: float, current_profit: float, **kwargs) -> float:
		return 1

	def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
		if not self.config['runmode'].value == 'hyperopt':
			dataframe['ma_offset_buy'] = ma_types[self.buy_trigger.value](dataframe, int(self.base_nb_candles_buy.value)) * self.low_offset.value
			dataframe['ma_offset_sell'] = ma_types[self.sell_trigger.value](dataframe, int(self.base_nb_candles_sell.value)) * self.high_offset.value
		return dataframe

	def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
		if self.config['runmode'].value == 'hyperopt':
			dataframe['ma_offset_buy'] = ma_types[self.buy_trigger.value](dataframe, int(self.base_nb_candles_buy.value)) * self.low_offset.value

		dataframe.loc[
			(




				(qtpylib.crossed_above(dataframe['close'], dataframe['ma_offset_buy'])) &
				(dataframe['volume'] > 0)
			),
			'buy'] = 1
		return dataframe

	def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
		if self.config['runmode'].value == 'hyperopt':
			dataframe['ma_offset_sell'] = ma_types[self.sell_trigger.value](dataframe, int(self.base_nb_candles_sell.value)) * self.high_offset.value

		dataframe.loc[
			(

					(qtpylib.crossed_below(dataframe['close'], dataframe['ma_offset_sell'])) &
					(dataframe['volume'] > 0)
			),
			'sell'] = 1
		return dataframe