# 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_94_15(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['sma_fast'] = ta.SMA(dataframe, timeperiod=20)
        dataframe['sma_slow'] = ta.SMA(dataframe, timeperiod=50)
        dataframe['natr'] = ta.NATR(dataframe, timeperiod=14)
        stochrsi = ta.STOCHRSI(dataframe, timeperiod=7, fastk_period=3, fastd_period=3)
        dataframe['fastk'] = stochrsi['fastk']
        dataframe['fastd'] = stochrsi['fastd']
        dataframe['willr'] = ta.WILLR(dataframe, timeperiod=7)
        dataframe['cmo'] = ta.CMO(dataframe, timeperiod=14)
        return dataframe

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

    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[
        (
            (dataframe['fastk'] > 85)
        ) & (
            (dataframe['willr'] > -25)
        ) & (
            (dataframe['cmo'] > 50)
        ),
        'exit_long'] = 1
        return dataframe