# source: https://raw.githubusercontent.com/kurtpart/nasosv5/98203e639a699f62f0258a6bebd446c1aef29506/ft_userdata/user_data/strategies/AwesomeMacd.py
# --- Do not remove these libs ---
from freqtrade.strategy.interface import IStrategy
from pandas import DataFrame
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib


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


class github_kurtpart_nasosv5__AwesomeMacd__20220111_201104(IStrategy):
    """

    author@: Gert Wohlgemuth

    converted from:

    https://github.com/sthewissen/Mynt/blob/master/src/Mynt.Core/Strategies/github_kurtpart_nasosv5__AwesomeMacd__20220111_201104.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 = -0.12
    trailing_stop = True
    trailing_stop_positive = 0.0033
    trailing_stop_positive_offset = 0.03
    trailing_only_offset_is_reached = True

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

    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe['adx'] = ta.ADX(dataframe, timeperiod=14)
        dataframe['ao'] = qtpylib.awesome_oscillator(dataframe)

        macd = ta.MACD(dataframe)
        dataframe['macd'] = macd['macd']
        dataframe['macdsignal'] = macd['macdsignal']
        dataframe['macdhist'] = macd['macdhist']

        return dataframe

    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[
            (
                    (dataframe['macd'] > 0) &
                    (dataframe['ao'] > 0) &
                    (dataframe['ao'].shift() < 0)

            ),
            'buy'] = 1
        return dataframe

    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[
            (
                    (dataframe['macd'] < 0) &
                    (dataframe['ao'] < 0) &
                    (dataframe['ao'].shift() > 0)

            ),
            'sell'] = 1
        return dataframe