# source: https://raw.githubusercontent.com/DerSalvador/freqtrade-helm-chart/a669dc11b640b0eb63aa8f8b51e9f181fd7ee43c/chart/deployed_strategies/Heracles.py
# Github_DerSalvador_freqtrade_helm_chart__Heracles__20260115_122204 Strategy: Strongest Son of GodStra
# ( With just 1 Genome! its a bacteria :D )
# Author: @Mablue (Masoud Azizi)
# github: https://github.com/mablue/
# IMPORTANT:Add to your pairlists inside config.json (Under StaticPairList):
#   {
#       "method": "AgeFilter",
#       "min_days_listed": 100
#   },
# IMPORTANT: INSTALL TA BEFOUR RUN(pip install ta)
# ######################################################################
# Optimal config settings:
# "max_open_trades": 100,
# "stake_amount": "unlimited",
# --- Do not remove these libs ---
import logging
from numpy.lib import math
from freqtrade.strategy.interface import IStrategy
from pandas import DataFrame
# --------------------------------
# Add your lib to import here
# import talib.abstract as ta
import pandas as pd
import ta
from ta.utils import dropna
import freqtrade.vendor.qtpylib.indicators as qtpylib
from functools import reduce
import numpy as np

class Github_DerSalvador_freqtrade_helm_chart__Heracles__20260115_122204(IStrategy):
    INTERFACE_VERSION = 3
    # 65/600:   2275 trades. 1438/7/830 W/D/L.
    # Avg profit   3.10%. Median profit   3.06%.
    # Total profit  113171 USDT ( 7062 Σ%).
    # Avg duration 345 min. Objective: -23.0
    # Buy hyperspace params:
    entry_params = {'entry-cross-0': 'volatility_kcw', 'entry-indicator-0': 'volatility_dcp', 'entry-oper-0': '<'}
    # Sell hyperspace params:
    exit_params = {'exit-cross-0': 'trend_macd_signal', 'exit-indicator-0': 'trend_ema_fast', 'exit-oper-0': '='}
    # ROI table:
    minimal_roi = {'0': 0.32836, '1629': 0.17896, '6302': 0.05372, '10744': 0}
    # Stoploss:
    stoploss = -0.04655
    # Trailing stop:
    trailing_stop = True
    trailing_stop_positive = 0.02444
    trailing_stop_positive_offset = 0.04406
    trailing_only_offset_is_reached = True
    # Buy hypers
    timeframe = '5m'

    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        # Add all ta features
        dataframe = dropna(dataframe)
        dataframe['volatility_kcw'] = ta.volatility.keltner_channel_wband(dataframe['high'], dataframe['low'], dataframe['close'], window=20, window_atr=10, fillna=False, original_version=True)
        dataframe['volatility_dcp'] = ta.volatility.donchian_channel_pband(dataframe['high'], dataframe['low'], dataframe['close'], window=10, offset=0, fillna=False)
        dataframe['trend_macd_signal'] = ta.trend.macd_signal(dataframe['close'], window_slow=26, window_fast=12, window_sign=9, fillna=False)
        dataframe['trend_ema_fast'] = ta.trend.EMAIndicator(close=dataframe['close'], window=12, fillna=False).ema_indicator()
        return dataframe

    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        IND = self.entry_params['entry-indicator-0']
        CRS = self.entry_params['entry-cross-0']
        DFIND = dataframe[IND]
        DFCRS = dataframe[CRS]
        dataframe.loc[DFIND < DFCRS, 'enter_long'] = 1
        return dataframe

    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        IND = self.exit_params['exit-indicator-0']
        CRS = self.exit_params['exit-cross-0']
        DFIND = dataframe[IND]
        DFCRS = dataframe[CRS]
        dataframe.loc[qtpylib.crossed_below(DFIND, DFCRS), 'exit_long'] = 1
        return dataframe