from freqtrade.strategy import IStrategy, merge_informative_pair
from pandas import DataFrame, Series
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib
from technical.indicators import RMI



def chaikin_mf(df, periods=20):
	close = df['close']
	low = df['low']
	high = df['high']
	volume = df['volume']
	mfv = ((close - low) - (high - close)) / (high - low)
	mfv = mfv.fillna(0.0)
	mfv *= volume
	cmf = mfv.rolling(periods).sum() / volume.rolling(periods).sum()
	return Series(cmf, name='cmf')


class TheRealPullback(IStrategy):

	minimal_roi = {
		"0": 100
	}

	stoploss = -0.035

	timeframe = '5m'

	process_only_new_candles = True
	ignore_roi_if_buy_signal = True
	startup_candle_count = 200

	def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:

		bollinger = qtpylib.bollinger_bands(dataframe['close'], window=20, stds=2)
		dataframe['bb_lowerband'] = bollinger['lower']
		dataframe['bb_middleband'] = bollinger['mid']
		dataframe['bb_upperband'] = bollinger['upper']
		dataframe['bb_width'] = ((dataframe['bb_upperband'] - dataframe['bb_lowerband']) / dataframe['bb_middleband'])
		dataframe['bb_bottom_cross'] = qtpylib.crossed_below(dataframe['close'], dataframe['bb_lowerband']).astype('int')

		dataframe['rsi'] = ta.RSI(dataframe, timeperiod=10)

		dataframe['plus_di'] = ta.PLUS_DI(dataframe)
		dataframe['minus_di'] = ta.MINUS_DI(dataframe)

		dataframe['cci'] = ta.CCI(dataframe, 30)

		dataframe['mfi'] = ta.MFI(dataframe, timeperiod=14)

		dataframe['cmf'] = chaikin_mf(dataframe)

		dataframe['rmi'] = RMI(dataframe, length=8, mom=4)

		stoch = ta.STOCHRSI(dataframe, 15, 20, 2, 2)
		dataframe['srsi_fk'] = stoch['fastk']
		dataframe['srsi_fd'] = stoch['fastd']

		dataframe['fastEMA'] = ta.EMA(dataframe['volume'], timeperiod=12)
		dataframe['slowEMA'] = ta.EMA(dataframe['volume'], timeperiod=26)
		dataframe['pvo'] = ((dataframe['fastEMA'] - dataframe['slowEMA']) / dataframe['slowEMA']) * 100

		dataframe['is_dip'] = (
			(dataframe['rmi'] < 20)
			&
			(dataframe['cci'] <= -150)
			&
			(dataframe['srsi_fk'] < 20)
			# Maybe comment mfi and cmf to make more trades
			&
			(dataframe['mfi'] < 25)
			&
			(dataframe['cmf'] <= -0.1)
		).astype('int')

		dataframe['is_break'] = (
			(dataframe['bb_width'] > 0.025)
			&
			(dataframe['bb_bottom_cross'].rolling(10).sum() > 1)
			&
			(dataframe['close'] < 0.99 * dataframe['bb_lowerband'])
		).astype('int')

		dataframe['buy_signal'] = (
			(dataframe['is_dip'] > 0)
			&
			(dataframe['is_break'] > 0)

		).astype('int')

		return dataframe

	def get_name(self) -> str:
		return "therealpullback_strategy"

	def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:

		dataframe.loc[
			(dataframe['buy_signal'] > 0),
			'buy'] = 1

		return dataframe

	def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:

		dataframe.loc[
			(
				(qtpylib.crossed_below(dataframe['close'], dataframe['bb_middleband']))
				|
				(qtpylib.crossed_below(dataframe['close'], dataframe['bb_upperband']))

			), 'sell'] = 1

		return dataframe