# source: https://raw.githubusercontent.com/DerSalvador/freqtrade-helm-chart/a669dc11b640b0eb63aa8f8b51e9f181fd7ee43c/chart/deployed_strategies/BbRoi.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__BbRoi__20260115_122204(IStrategy):
    INTERFACE_VERSION = 3
    minimal_roi = {'0': 0.17552, '53': 0.11466, '226': 0.06134, '400': 0}
    # Stoploss:
    stoploss = -0.23701
    # Trailing stop:
    trailing_stop = True
    trailing_stop_positive = 0.01007
    trailing_stop_positive_offset = 0.01821
    trailing_only_offset_is_reached = True
    timeframe = '15m'
    # Experimental settings (configuration will overide these if set)
    use_exit_signal = True
    ignore_roi_if_entry_signal = False
    order_types = {'entry': 'market', 'exit': 'market', 'stoploss': 'limit', 'stoploss_on_exchange': True}

    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)
        # EMA
        dataframe['ema9'] = ta.EMA(dataframe, timeperiod=9)
        dataframe['ema20'] = ta.EMA(dataframe, timeperiod=20)
        dataframe['ema200'] = ta.EMA(dataframe, timeperiod=200)
        # Bollinger bands
        bollinger = qtpylib.bollinger_bands(qtpylib.typical_price(dataframe), window=20, stds=2)
        dataframe['bb_lowerband'] = bollinger['lower']
        dataframe['bb_middleband'] = bollinger['mid']
        dataframe['bb_upperband'] = bollinger['upper']
        return dataframe

    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[(dataframe['close'] > dataframe['bb_middleband']) & (dataframe['close'] < dataframe['bb_upperband']) & (dataframe['close'] > dataframe['ema9']) & (dataframe['close'] > dataframe['ema200']) & (dataframe['ema20'] > dataframe['ema200']), 'enter_long'] = 1
        return dataframe

    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:  # red bar
        dataframe.loc[(dataframe['rsi'] > 75) | (dataframe['close'] < dataframe['bb_middleband'] * 0.97) & (dataframe['open'] > dataframe['close']), 'exit_long'] = 1
        return dataframe