# source: https://raw.githubusercontent.com/harshit4311/freqtrade-algo-trading/25b550eb1ccda3be98a4d155148c4227d044cd8d/user_data/strategies/NewStrategy.py
''' new strat '''

# from freqtrade.strategy import IStrategy
# from pandas import DataFrame
# import numpy as np
# class Github_harshit4311_freqtrade_algo_trading__Github_harshit4311_freqtrade_algo_trading__NewStrategy__20250528_190019__20250528_190019(IStrategy):
#     timeframe = '1h'
#     stoploss = -1
#     minimal_roi = {"0": 0.05}

#     def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
#         dataframe['high_20'] = dataframe['high'].rolling(window=20).max()
#         dataframe['low_20'] = dataframe['low'].rolling(window=20).min()
#         dataframe['low_3'] = dataframe['low'].rolling(window=3).min()
#         return dataframe.dropna().copy()

#     def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
#         dataframe['buy'] = (dataframe['close'] > dataframe['high_20']).astype('bool')
#         return dataframe

#     def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
#         dataframe['exit_long'] = False
#         dataframe['exit_short'] = False
#         return dataframe

#     def custom_stoploss(self, pair: str, trade, current_time, current_rate, current_profit, **kwargs) -> float:
#         dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)
#         idx = dataframe.index.searchsorted(trade.open_date_utc)

#         if idx >= len(dataframe) or idx < 0:
#             return 1.0  # Trigger exit if index is invalid

#         trailing_min = dataframe['low_3'].iloc[idx:].min()
#         if current_rate <= trailing_min:
#             stoploss_rel = (trailing_min - trade.open_rate) / trade.open_rate
#             return max(0.01, abs(stoploss_rel))  # Ensure within valid bounds
#         return 1.0

from freqtrade.strategy import IStrategy
from pandas import DataFrame
import numpy as np
from freqtrade.strategy import IStrategy
from pandas import DataFrame


class Github_harshit4311_freqtrade_algo_trading__Github_harshit4311_freqtrade_algo_trading__NewStrategy__20250528_190019__20250528_190019(IStrategy):
    """
    20-bar breakout strategy with 3-bar trailing stoploss.
    Only one trade is allowed at a time (handled by Freqtrade via max_open_trades = 1).
    """

    # === Configuration ===
    timeframe = '30m'  # Use '1h' for testing, '30m' for actual outputs
    stoploss = -1  # Disable default stoploss; custom stoploss is used
    minimal_roi = {"0": 0.5}  # Placeholder ROI

    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        # Calculate breakout and trailing indicators
        dataframe['high_20'] = dataframe['high'].rolling(window=20).max()
        dataframe['low_20'] = dataframe['low'].rolling(window=20).min()
        dataframe['low_3'] = dataframe['low'].rolling(window=3).min()
        dataframe.dropna(inplace=True)
        return dataframe

    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        # Entry condition: Close breaks out above *previous* 20-bar high
        dataframe['buy'] = (
            dataframe['close'] > dataframe['high_20'].shift(1)
        ).astype('bool')
        return dataframe

    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        # Exit logic is handled via custom stoploss
        dataframe['exit_long'] = False
        dataframe['exit_short'] = False
        return dataframe

    def custom_stoploss(self, pair: str, trade, current_time, current_rate, current_profit, **kwargs) -> float:
        # Use the 3-bar low since the trade was opened as a trailing stop
        dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)

        # Find index where trade was opened
        idx = dataframe.index.searchsorted(trade.open_date_utc)

        if idx >= len(dataframe) or idx < 0:
            return 1.0  # Exit immediately if data is invalid

        # Get trailing minimum 3-bar low after trade entry
        trailing_min = dataframe['low_3'].iloc[idx:].min()

        # If current price drops below that trailing min, exit the trade
        if current_rate <= trailing_min:
            stoploss_rel = (trailing_min - trade.open_rate) / trade.open_rate
            return max(0.01, abs(stoploss_rel))  # Return positive stop between 0 and 1

        return 1.0  # Otherwise, keep trade open