# source: https://raw.githubusercontent.com/freqtrade/freqtrade-strategies/dbd5b0b21cfbf5ee80588d37458ace2467b7f8a4/user_data/strategies/berlinguyinca/ASDTSRockwellTrading.py

# --- Do not remove these libs ---
from freqtrade.strategy import IStrategy
from typing import Dict, List
from functools import reduce
from pandas import DataFrame
# --------------------------------

import talib.abstract as ta
import freqtrade.vendor.qtpylib.indicators as qtpylib


class Github_freqtrade_freqtrade_strategies__ASDTSRockwellTrading__20260505_050627(IStrategy):
    """
    trading strategy based on the concept explained at https://www.youtube.com/watch?v=mmAWVmKN4J0
    author@: Gert Wohlgemuth

    idea:

        uptrend definition:
            MACD above 0 line AND above MACD signal


        downtrend definition:
            MACD below 0 line and below MACD signal

        sell definition:
            MACD below MACD signal

    it's basically a very simple MACD based strategy and we ignore the definition of the entry and exit points in this case, since the trading bot, will take of this already

    """

    INTERFACE_VERSION: int = 3
    # Minimal ROI designed for the strategy.
    # This attribute will be overridden if the config file contains "minimal_roi"
    minimal_roi = {
        "60":  0.01,
        "30":  0.03,
        "20":  0.04,
        "0":  0.05
    }

    # Optimal stoploss designed for the strategy
    # This attribute will be overridden if the config file contains "stoploss"
    stoploss = -0.3

    # Optimal timeframe for the strategy
    timeframe = '5m'

    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:

        macd = ta.MACD(dataframe)
        dataframe['macd'] = macd['macd']
        dataframe['macdsignal'] = macd['macdsignal']
        dataframe['macdhist'] = macd['macdhist']

        return dataframe

    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        """
        Based on TA indicators, populates the buy signal for the given dataframe
        :param dataframe: DataFrame
        :return: DataFrame with buy column
        """
        dataframe.loc[
            (
                (dataframe['macd'] > 0) &
                (dataframe['macd'] > dataframe['macdsignal'])
            ),
            'enter_long'] = 1

        return dataframe

    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        """
        Based on TA indicators, populates the sell signal for the given dataframe
        :param dataframe: DataFrame
        :return: DataFrame with buy column
        """
        dataframe.loc[
            (
                (dataframe['macd'] < dataframe['macdsignal'])
            ),
            'exit_long'] = 1
        return dataframe