# source: https://raw.githubusercontent.com/vatesdesign/freq/d303775dedc74d21c630921b0a409471d1c333d8/BbandRsi.py
# --- Do not remove these libs ---
from freqtrade.strategy import IStrategy
from pandas import DataFrame
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib


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


class github_vatesdesign_freq__BbandRsi__20220825_130621(IStrategy):
    """

    author@: Gert Wohlgemuth

    converted from:

    https://github.com/sthewissen/Mynt/blob/master/src/Mynt.Core/Strategies/github_vatesdesign_freq__BbandRsi__20220825_130621.cs

    """

    INTERFACE_VERSION: int = 3
    # 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"

    # ROI table:
    minimal_roi = {
        "0": 0.291,
        "128": 0.067,
        "821": 0.025,
        "1656": 0
    }

    # Stoploss:
    stoploss = -0.303


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

    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_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[
            (
                    (dataframe['close'].shift(1)<dataframe['bb_lowerband']) &
            		(dataframe['close'] > dataframe['bb_lowerband']) &
            		(dataframe['rsi'] < 50)
            ),
            'enter_long'] = 1
        return dataframe



    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[
            (
                    (dataframe['close']>dataframe['bb_upperband']) |
                    (dataframe['rsi'] > 60)

            ),
            'exit_long'] = 1
        return dataframe