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

class Github_DerSalvador_freqtrade_helm_chart__MACD_EMA__20260115_122204(IStrategy):
    INTERFACE_VERSION = 3
    EMA_LONG_TERM = 200
    # 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 = {'60': 0.01, '30': 0.03, '20': 0.04, '0': 0.05}
    # Optimal stoploss designed for the strategy
    stoploss = -0.25
    # Optimal timeframe for the strategy
    timeframe = '5m'

    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        # MACD 
        macd = ta.MACD(dataframe)
        dataframe['macd'] = macd['macd']
        dataframe['macdsignal'] = macd['macdsignal']
        dataframe['macdhist'] = macd['macdhist']
        # EMA 200 for trend indicator
        dataframe['ema_{}'.format(self.EMA_LONG_TERM)] = ta.EMA(dataframe, timeperiod=self.EMA_LONG_TERM)
        return dataframe

    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[qtpylib.crossed_above(dataframe['macd'], dataframe['macdsignal']) & (dataframe['close'] > dataframe['ema_{}'.format(self.EMA_LONG_TERM)]), 'enter_long'] = 1
        return dataframe

    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[qtpylib.crossed_below(dataframe['macd'], dataframe['macdsignal']) & (dataframe['close'] < dataframe['ema_{}'.format(self.EMA_LONG_TERM)]), 'exit_long'] = 1
        return dataframe