# source: https://raw.githubusercontent.com/bayazknn/trade-automation/b8cc7dbe7c476510b9819e3534c9cd415e9f5ab1/strategies/ACO_30_9.py
# 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 Github_bayazknn_trade_automation__ACO_30_9__20260120_010647(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['sar'] = ta.SAR(dataframe, acceleration=0.01, maximum=0.1)
        dataframe['natr'] = ta.NATR(dataframe, timeperiod=14)
        dataframe['ultosc'] = ta.ULTOSC(dataframe, timeperiod1=7, timeperiod2=14, timeperiod3=28)
        dataframe['adosc'] = ta.ADOSC(dataframe, fastperiod=3, slowperiod=10)
        return dataframe

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

    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[
        (
            (dataframe['ultosc'] > 70)
        ) & (
            qtpylib.crossed_below(dataframe['adosc'], 0)
        ),
        'exit_long'] = 1
        return dataframe