# 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_5_1(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['atr'] = ta.ATR(dataframe, timeperiod=14)
        dataframe['natr'] = ta.NATR(dataframe, timeperiod=14)
        dataframe['rsi'] = ta.RSI(dataframe, timeperiod=21)
        dataframe['willr'] = ta.WILLR(dataframe, timeperiod=7)
        dataframe['roc'] = ta.ROC(dataframe, timeperiod=20)
        dataframe['sar'] = ta.SAR(dataframe, acceleration=0.03, maximum=0.3)
        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['natr'] > 2.0)
        ),
        'enter_long'] = 1
        return dataframe

    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[
        (
            (dataframe['rsi'] > 65)
        ) & (
            (dataframe['willr'] > -25)
        ) & (
            qtpylib.crossed_below(dataframe['roc'], 0)
        ) & (
            qtpylib.crossed_below(dataframe['close'], dataframe['sar'])
        ) & (
            (dataframe['close'] > dataframe['upperband'] * 1.0)
        ),
        'exit_long'] = 1
        return dataframe