# source: https://raw.githubusercontent.com/DerSalvador/freqtrade-helm-chart/a669dc11b640b0eb63aa8f8b51e9f181fd7ee43c/chart/deployed_strategies/binance-michael-k8s-namespace/MultiRSI.py
# --- Do not remove these libs ---
from freqtrade.strategy.interface import IStrategy
from pandas import DataFrame
# --------------------------------
import talib.abstract as ta
from technical.util import resample_to_interval, resampled_merge

class Github_DerSalvador_freqtrade_helm_chart__MultiRSI__20260115_122204(IStrategy):
    INTERFACE_VERSION = 3
    '\n\n    author@: Gert Wohlgemuth\n\n    based on work from Creslin\n\n    '
    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.fillna(method='ffill', inplace=True)
        return dataframe

    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        # must be bearish
        dataframe.loc[(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