# source: https://raw.githubusercontent.com/kanaxe/freqtrade_kanaxe/635577b7c04ea237bacbdb2e65c7ef450c0f2abb/stash/BbandRsiHO.py
# --- Do not remove these libs ---
from freqtrade.strategy.interface import IStrategy
from freqtrade.strategy import IntParameter
from pandas import DataFrame
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib


# --------------------------------


class github_kanaxe_freqtrade_kanaxe__BbandRsiHO__20211115_132756(IStrategy):
    """
    author@: Gert Wohlgemuth
    converted from:
    https://github.com/sthewissen/Mynt/blob/master/src/Mynt.Core/Strategies/BbandRsi.cs
    """

    # Minimal ROI designed for the strategy.
    # adjust based on market conditions. We would recommend to keep it low for quick turn arounds
    # This attribute will be overridden if the config file contains "minimal_roi"
    minimal_roi = {
        "0": 0.1
    }

    # Optimal stoploss designed for the strategy
    stoploss = -0.25

    # Optimal timeframe for the strategy
    timeframe = '1h'

    buy_params = {
        "buy_rsi_limit": 22,
    }

    buy_rsi_limit = IntParameter(0, 30, default=30, space='buy', optimize=True, load=True)
    sell_rsi_limit = IntParameter(70, 100, default=70, space='sell', optimize=True, load=True)

    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)

        # Bollinger bands
        bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
        dataframe['bb_lowerband'] = bollinger['lower']
        dataframe['bb_middleband'] = bollinger['mid']
        dataframe['bb_upperband'] = bollinger['upper']

        return dataframe

    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[
            (
                    (dataframe['rsi'] < self.buy_rsi_limit.value) &
                    (dataframe['close'] < dataframe['bb_lowerband'])

            ),
            'buy'] = 1
        return dataframe

    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[
            (
                    (dataframe['rsi'] > self.sell_rsi_limit.value)

            ),
            'sell'] = 1
        return dataframe