# 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_12_3(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['aroonosc'] = ta.AROONOSC(dataframe, timeperiod=10)
        dataframe['sma_fast'] = ta.SMA(dataframe, timeperiod=9)
        dataframe['sma_slow'] = ta.SMA(dataframe, timeperiod=21)
        dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)
        dataframe['plus_di'] = ta.PLUS_DI(dataframe, timeperiod=14)
        dataframe['minus_di'] = ta.MINUS_DI(dataframe, timeperiod=14)
        dataframe['ema_fast'] = ta.EMA(dataframe, timeperiod=20)
        dataframe['ema_slow'] = ta.EMA(dataframe, timeperiod=50)
        bbands = ta.BBANDS(dataframe, timeperiod=20, nbdevup=1.5, nbdevdn=1.5)
        dataframe['upperband'] = bbands['upperband']
        dataframe['middleband'] = bbands['middleband']
        dataframe['lowerband'] = bbands['lowerband']
        return dataframe

    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[
        (
            (dataframe['adx'] > 30)
        ) & (
            qtpylib.crossed_above(dataframe['aroonosc'], 0)
        ) & (
            qtpylib.crossed_above(dataframe['sma_fast'], dataframe['sma_slow'])
        ),
        'enter_long'] = 1
        return dataframe

    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[
        (
            (dataframe['rsi'] > 70)
        ) & (
            qtpylib.crossed_below(dataframe['plus_di'], dataframe['minus_di'])
        ) & (
            qtpylib.crossed_below(dataframe['ema_fast'], dataframe['ema_slow'])
        ) & (
            (dataframe['close'] > dataframe['upperband'] * 1.0)
        ),
        'exit_long'] = 1
        return dataframe