# source: https://raw.githubusercontent.com/tellyoung/money_game/8b12b7fa13559ab44a6a09104292ad75f0cdaeb0/Trading/user_data/strategies/TrendFollowingStrategy_base.py
from functools import reduce
from pandas import DataFrame
from freqtrade.strategy import IStrategy

import talib.abstract as ta

from freqtrade.strategy.interface import IStrategy

class Github_tellyoung_money_game__TrendFollowingStrategy_base__20250519_005942(IStrategy):

    INTERFACE_VERSION: int = 3
    # ROI table:
    minimal_roi = {"0": 0.15, "30": 0.1, "60": 0.05}
    # minimal_roi = {"0": 1}

    # Stoploss:
    # stoploss = -0.265
    """
        todo: yuty
    """
    stoploss = -0.05

    # Trailing stop:
    trailing_stop = True
    trailing_stop_positive = 0.05
    trailing_stop_positive_offset = 0.1
    trailing_only_offset_is_reached = False

    timeframe = "5m"

    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        # Calculate OBV
        dataframe['obv'] = ta.OBV(dataframe['close'], dataframe['volume'])
        
        # Add your trend following indicators here
        # dataframe['trend'] = dataframe['close'].ewm(span=20, adjust=False).mean()
        """
            todo: yuty
        """
        dataframe['trend'] = dataframe['close'].ewm(span=15, adjust=False).mean()

        return dataframe
    
    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        if dataframe['close'] > dataframe['trend'] and \
            dataframe['close'].shift(1) <= dataframe['trend'].shift(1) and \
            dataframe['obv'] > dataframe['obv'].shift(1):
            print("=====================================")

        # Add your trend following buy signals here
        dataframe.loc[
            (dataframe['close'] > dataframe['trend']) & 
            (dataframe['close'].shift(1) <= dataframe['trend'].shift(1)) &
            (dataframe['obv'] > dataframe['obv'].shift(1)), 
            'enter_long'] = 1
        
        # Add your trend following sell signals here
        dataframe.loc[
            (dataframe['close'] < dataframe['trend']) & 
            (dataframe['close'].shift(1) >= dataframe['trend'].shift(1)) &
            (dataframe['obv'] < dataframe['obv'].shift(1)), 
            'enter_short'] = 1
        
        return dataframe

    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        # Add your trend following exit signals for long positions here
        dataframe.loc[
            (dataframe['close'] < dataframe['trend']) & 
            (dataframe['close'].shift(1) >= dataframe['trend'].shift(1)) &
            (dataframe['obv'] > dataframe['obv'].shift(1)), 
            'exit_long'] = 1
        
        # Add your trend following exit signals for short positions here
        dataframe.loc[
            (dataframe['close'] > dataframe['trend']) & 
            (dataframe['close'].shift(1) <= dataframe['trend'].shift(1)) &
            (dataframe['obv'] < dataframe['obv'].shift(1)), 
            'exit_short'] = 1
        
        return dataframe