# Source: generated via dynamic_strategy_generator
from freqtrade.strategy import IStrategy
from pandas import DataFrame
import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib

class ACO_70_17(IStrategy):
    timeframe = '1h'
    
    # Standard ROI and Stoploss
    minimal_roi = {"0": 0.1, "60": 0.05, "120": 0.0}
    stoploss = -0.05
    
    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe['adx'] = ta.ADX(dataframe, timeperiod=14)
        dataframe['ad'] = ta.AD(dataframe)
        dataframe['ad_sma'] = ta.SMA(dataframe, timeperiod=10, price='ad')
        dataframe['natr'] = ta.NATR(dataframe, timeperiod=14)
        dataframe['apo'] = ta.APO(dataframe, fastperiod=5, slowperiod=20)
        res = ta.AROON(dataframe, timeperiod=14)
        dataframe['aroondown'] = res.iloc[:, 0]
        dataframe['aroonup'] = res.iloc[:, 1]
        dataframe['wma'] = ta.WMA(dataframe, timeperiod=20)
        bbands = ta.BBANDS(dataframe, timeperiod=14, nbdevup=2.0, nbdevdn=2.0)
        dataframe['upperband'] = bbands['upperband']
        dataframe['middleband'] = bbands['middleband']
        dataframe['lowerband'] = bbands['lowerband']
        dataframe['atr'] = ta.ATR(dataframe, timeperiod=14)
        return dataframe

    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[
        (
            (dataframe['adx'] > 25)
        ) & (
            qtpylib.crossed_above(dataframe['ad'], dataframe['ad_sma'])
        ) & (
            (dataframe['natr'] > 2.0)
        ),
        'enter_long'] = 1
        return dataframe

    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[
        (
            qtpylib.crossed_below(dataframe['apo'], 0)
        ) & (
            qtpylib.crossed_below(dataframe['aroonup'], dataframe['aroondown'])
        ) & (
            qtpylib.crossed_below(dataframe['close'], dataframe['wma'])
        ) & (
            (dataframe['close'] > dataframe['upperband'] * 0.98)
        ),
        'exit_long'] = 1
        return dataframe