# source: https://raw.githubusercontent.com/Kblack0610/freqtrade_trading_attempt/3fd6526cabcf215c2e380199bd30eb7734eeb520/user_data/strategies/berlinguyinca/MultiRSI.py
# directory_url: https://github.com/Kblack0610/freqtrade_trading_attempt/blob/master/user_data/strategies/berlinguyinca/
# User: Kblack0610
# Repository: freqtrade_trading_attempt
# --------------------# --- Do not remove these libs ---
from freqtrade.strategy import IStrategy
from pandas import DataFrame
# --------------------------------
import talib.abstract as ta
from technical.util import resample_to_interval, resampled_merge


class Github_Kblack0610_freqtrade_trading_attempt__MultiRSI__20261105_062517(IStrategy):
    """

    author@: Gert Wohlgemuth

    based on work from Creslin

    """
    INTERFACE_VERSION: int = 3
    minimal_roi = {
        "0": 0.01
    }

    # Optimal stoploss designed for the strategy
    stoploss = -0.05

    # Optimal timeframe for the strategy
    timeframe = '5m'

    def get_ticker_indicator(self):
        return int(self.timeframe[:-1])

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

        dataframe['sma5'] = ta.SMA(dataframe, timeperiod=5)
        dataframe['sma200'] = ta.SMA(dataframe, timeperiod=200)

        # resample our dataframes
        dataframe_short = resample_to_interval(dataframe, self.get_ticker_indicator() * 2)
        dataframe_long = resample_to_interval(dataframe, self.get_ticker_indicator() * 8)

        # compute our RSI's
        dataframe_short['rsi'] = ta.RSI(dataframe_short, timeperiod=14)
        dataframe_long['rsi'] = ta.RSI(dataframe_long, timeperiod=14)

        # merge dataframe back together
        dataframe = resampled_merge(dataframe, dataframe_short)
        dataframe = resampled_merge(dataframe, dataframe_long)

        dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)

        dataframe = dataframe.ffill()

        return dataframe

    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[
            (
                # must be bearish
                (dataframe['sma5'] >= dataframe['sma200']) &
                (dataframe['rsi'] < (dataframe['resample_{}_rsi'.format(self.get_ticker_indicator() * 8)] - 20))
            ),
            'enter_long'] = 1
        return dataframe

    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[
            (
                (dataframe['rsi'] > dataframe['resample_{}_rsi'.format(self.get_ticker_indicator()*2)]) &
                (dataframe['rsi'] > dataframe['resample_{}_rsi'.format(self.get_ticker_indicator()*8)])
            ),
            'exit_long'] = 1
        return dataframe