# 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_17_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['rsi'] = ta.RSI(dataframe, timeperiod=14)
        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['obv'] = ta.OBV(dataframe)
        dataframe['obv_sma'] = ta.SMA(dataframe, timeperiod=10, price='obv')
        dataframe['willr'] = ta.WILLR(dataframe, timeperiod=7)
        dataframe['ad'] = ta.AD(dataframe)
        dataframe['ad_sma'] = ta.SMA(dataframe, timeperiod=20, price='ad')
        dataframe['atr'] = ta.ATR(dataframe, timeperiod=14)
        return dataframe

    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[
        (
            (dataframe['rsi'] < 30)
        ) & (
            (dataframe['close'] < dataframe['lowerband'] * 1.02)
        ) & (
            qtpylib.crossed_above(dataframe['obv'], dataframe['obv_sma'])
        ),
        'enter_long'] = 1
        return dataframe

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