# source: https://raw.githubusercontent.com/tradingstrategy-ai/gmx-ccxt-freqtrade/cdcba720b80c0fdcdfe7ab4a90ad61121f9ee9d3/user_data/strategies/ADXMomentum.py
# --- Do not remove these libs ---
from freqtrade.strategy import IStrategy
from pandas import DataFrame
import talib.abstract as ta

class Github_tradingstrategy_ai_gmx_ccxt_freqtrade__ADXMomentum__20251210_191501(IStrategy):
    """
    Trend-following momentum strategy that enters long positions during strong upward trends and exits when momentum reverses.
    
    Entry: ADX > 25 (strong trend), MOM > 0 (positive momentum), PLUS_DI > 25 and PLUS_DI > MINUS_DI (upward directional strength).
    Exit: ADX > 25, MOM < 0 (negative momentum), MINUS_DI > 25 and PLUS_DI < MINUS_DI (downward directional strength).
    """

    INTERFACE_VERSION: int = 3
    
    # 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": 0.05
    }

    # Optimal stoploss designed for the strategy
    stoploss = -0.25

    # Optimal timeframe for the strategy
    timeframe = '1h'

    # Number of candles the strategy requires before producing valid signals
    startup_candle_count: int = 20
    exit_profit_only = False

    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['adx'] > 25) &
                    (dataframe['mom'] > 0) &
                    (dataframe['plus_di'] > 25) &
                    (dataframe['plus_di'] > dataframe['minus_di'])

            ),
            'enter_long'] = 1
        return dataframe

    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[
            (
                    (dataframe['adx'] > 25) &
                    (dataframe['mom'] < 0) &
                    (dataframe['minus_di'] > 25) &
                    (dataframe['plus_di'] < dataframe['minus_di'])

            ),
            'exit_long'] = 1
        return dataframe