# source: https://raw.githubusercontent.com/cadilhe/freqtrade_2020_tcc/310d045ec6650d6989f38f2d7149489463babf34/user_data/strategies/berlinguyinca/AdxSmas.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_cadilhe_freqtrade_2020_tcc__AdxSmas__20210602_004229(IStrategy):
    """

    author@: Gert Wohlgemuth

    converted from:

    https://github.com/sthewissen/Mynt/blob/master/src/Mynt.Core/Strategies/github_cadilhe_freqtrade_2020_tcc__AdxSmas__20210602_004229.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 ticker interval for the strategy
    timeframe = '1h'

    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe['adx'] = ta.ADX(dataframe, timeperiod=14)
        dataframe['short'] = ta.SMA(dataframe, timeperiod=3)
        dataframe['long'] = ta.SMA(dataframe, timeperiod=6)

        return dataframe

    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[
            (
                    (dataframe['adx'] > 25) &
                    (qtpylib.crossed_above(dataframe['short'], dataframe['long']))

            ),
            'buy'] = 1
        return dataframe

    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[
            (
                    (dataframe['adx'] < 25) &
                    (qtpylib.crossed_above(dataframe['long'], dataframe['short']))

            ),
            'sell'] = 1
        return dataframe