# source: https://raw.githubusercontent.com/DerSalvador/freqtrade-helm-chart/a669dc11b640b0eb63aa8f8b51e9f181fd7ee43c/chart/deployed_strategies/multi_tf.py
import freqtrade.vendor.qtpylib.indicators as qtpylib
import numpy as np
import talib.abstract as ta
from freqtrade.strategy import IStrategy, informative
from pandas import DataFrame, Series
import talib.abstract as ta
import math
import pandas_ta as pta
# from finta import TA as fta
import logging
from logging import FATAL
logger = logging.getLogger(__name__)
# NOT TO BE USED FOR LIVE!!!!!!

class Github_DerSalvador_freqtrade_helm_chart__multi_tf__20260408_060519(IStrategy):

    def version(self) -> str:
        return 'v1'
    INTERFACE_VERSION = 3
    # ROI table:
    minimal_roi = {'0': 0.2}
    # Stoploss:
    stoploss = -0.1
    # Trailing stop:
    trailing_stop = False
    trailing_stop_positive = 0.001
    trailing_stop_positive_offset = 0.01
    trailing_only_offset_is_reached = True
    # Sell signal
    use_exit_signal = True
    exit_profit_only = False
    exit_profit_offset = 0.01
    ignore_roi_if_entry_signal = False
    timeframe = '5m'
    process_only_new_candles = True
    startup_candle_count = 100
    # This method is not required.
    # def informative_pairs(self): ...
    # Define informative upper timeframe for each pair. Decorators can be stacked on same
    # method. Available in populate_indicators as 'rsi_30m' and 'rsi_1h'.

    @informative('30m')
    @informative('1h')
    def populate_indicators_1h(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)
        return dataframe
    # Define BTC/STAKE informative pair. Available in populate_indicators and other methods as
    # 'btc_rsi_1h'. Current stake currency should be specified as {stake} format variable
    # instead of hard-coding actual stake currency. Available in populate_indicators and other
    # methods as 'btc_usdt_rsi_1h' (when stake currency is USDT).

    @informative('1h', 'BTC/{stake}')
    def populate_indicators_btc_1h(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)
        return dataframe
    # Define BTC/ETH informative pair. You must specify quote currency if it is different from
    # stake currency. Available in populate_indicators and other methods as 'eth_btc_rsi_1h'.

    @informative('1h', 'ETH/BTC')
    def populate_indicators_eth_btc_1h(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)
        return dataframe
    # Define BTC/STAKE informative pair. A custom formatter may be specified for formatting
    # column names. A callable `fmt(**kwargs) -> str` may be specified, to implement custom
    # formatting. Available in populate_indicators and other methods as 'rsi_fast_upper'.
    # Resulting column names: `BTC_rsi_fast_upper_1h`, `BTC_close_1h` ...

    @informative('1h', 'BTC/{stake}', 'BTC_{column}_{timeframe}')
    def populate_indicators_btc_1h_2(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe['rsi_fast_upper'] = ta.RSI(dataframe, timeperiod=4)
        return dataframe
    # Define BTC/STAKE informative pair. A custom formatter may be specified for formatting
    # column names. A callable `fmt(**kwargs) -> str` may be specified, to implement custom
    # formatting. Available in populate_indicators and other methods as 'btc_rsi_super_fast_1h'.

    @informative('1h', 'BTC/{stake}', '{base}_{column}_{timeframe}')
    def populate_indicators_btc_1h_3(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe['rsi_super_fast'] = ta.RSI(dataframe, timeperiod=2)
        return dataframe

    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        # Strategy timeframe indicators for current pair.
        dataframe['rsi'] = ta.RSI(dataframe, timeperiod=14)
        # Informative pairs are available in this method.
        dataframe['rsi_less'] = dataframe['rsi'] < dataframe['rsi_1h']
        return dataframe

    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        stake = self.config['stake_currency'].lower()
        dataframe.loc[(dataframe[f'btc_{stake}_rsi_1h'] < 35) & (dataframe['eth_btc_rsi_1h'] < 50) & (dataframe['BTC_rsi_fast_upper_1h'] < 40) & (dataframe['btc_rsi_super_fast_1h'] < 30) & (dataframe['rsi_30m'] < 40) & (dataframe['rsi_1h'] < 40) & (dataframe['rsi'] < 30) & (dataframe['rsi_less'] == True) & (dataframe['volume'] > 0), ['enter_long', 'enter_tag']] = (1, 'entry_signal_rsi')
        return dataframe

    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[(dataframe['rsi'] > 70) & (dataframe['rsi_less'] == False) & (dataframe['volume'] > 0), ['exit_long', 'exit_tag']] = (1, 'exit_signal_rsi')
        return dataframe