# source: https://raw.githubusercontent.com/DerSalvador/freqtrade-helm-chart/a669dc11b640b0eb63aa8f8b51e9f181fd7ee43c/chart/deployed_strategies/binance-futures-k8s-namespace/adx_opt_strat.py
# --- Do not remove these libs ---
from freqtrade.strategy.interface import IStrategy
from pandas import DataFrame
import talib.abstract as ta
# --------------------------------

class Github_DerSalvador_freqtrade_helm_chart__adx_opt_strat__20260115_122204(IStrategy):
    INTERFACE_VERSION = 3
    '\n    author@: Gert Wohlgemuth\n    converted from:\n        https://github.com/sthewissen/Mynt/blob/master/src/Mynt.Core/Strategies/AdxMomentum.cs\n    '
    # Minimal ROI designed for the strategy.
    # adjust based on market conditions. We would recommend to keep it low for quick turn arounds
    # This attribute will be overridden if the config file contains "minimal_roi"
    minimal_roi = {'0': 0.0692, '7': 0.02682, '10': 0.00771, '32': 0}
    # Optimal stoploss designed for the strategy
    stoploss = -0.32766
    # Trailing stoploss
    trailing_stop = True
    trailing_only_offset_is_reached = True
    trailing_stop_positive = 0.32634
    trailing_stop_positive_offset = 0.34487
    # Optimal ticker interval for the strategy
    timeframe = '1m'

    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe['adx'] = ta.ADX(dataframe, timeperiod=14)
        dataframe['plus_di'] = ta.PLUS_DI(dataframe, timeperiod=25)
        dataframe['minus_di'] = ta.MINUS_DI(dataframe, timeperiod=25)
        dataframe['sar'] = ta.SAR(dataframe)
        dataframe['mom'] = ta.MOM(dataframe, timeperiod=14)
        return dataframe

    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[(dataframe['mom'] < 0) & (dataframe['minus_di'] > 48) & (dataframe['plus_di'] < dataframe['minus_di']), 'entry'] = 1
        return dataframe

    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[(dataframe['mom'] > 0) & (dataframe['minus_di'] > 48) & (dataframe['plus_di'] > dataframe['minus_di']), 'exit'] = 1
        return dataframe