# source: https://raw.githubusercontent.com/Danson77/Freqtrade_AIO_UI/f0bf29851d0577f244c17c0aa7d593ba3a7f3551/user_data/backtest_reports/Registerd_with_100USDT/BinHV45_987/BinHV45_987.py
# directory_url: https://github.com/Danson77/Freqtrade_AIO_UI/blob/main/user_data/backtest_reports/Registerd_with_100USDT/BinHV45_987/
# User: Danson77
# Repository: Freqtrade_AIO_UI
# --------------------
from freqtrade.strategy.interface import IStrategy
from typing import Dict, List
from functools import reduce
from pandas import DataFrame
from freqtrade.strategy import DecimalParameter

import numpy as np


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


def bollinger_bands(stock_price, window_size, num_of_std):
    rolling_mean = stock_price.rolling(window=window_size).mean()
    rolling_std = stock_price.rolling(window=window_size).std()
    lower_band = rolling_mean - (rolling_std * num_of_std)

    return rolling_mean, lower_band


class Github_Danson77_Freqtrade_AIO_UI__BinHV45_987__20260520_191933(IStrategy):
    minimal_roi = {
        "0": 0.0125
    }

    stoploss = -0.05
    timeframe = '5m'

    df_close_bbdelta = DecimalParameter(0.005, 0.06, default=0.008, space='buy', optimize=True, load=True)
    df_close_closedelta = DecimalParameter(0.01, 0.03, default=0.0175, space='buy', optimize=True, load=True)
    df_tail_bbdelta = DecimalParameter(0.15, 0.45, default=0.25, space='buy', optimize=True, load=True)

    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        mid, lower = bollinger_bands(dataframe['close'], window_size=40, num_of_std=2)
        dataframe['mid'] = np.nan_to_num(mid)
        dataframe['lower'] = np.nan_to_num(lower)
        dataframe['bbdelta'] = (dataframe['mid'] - dataframe['lower']).abs()
        dataframe['pricedelta'] = (dataframe['open'] - dataframe['close']).abs()
        dataframe['closedelta'] = (dataframe['close'] - dataframe['close'].shift()).abs()
        dataframe['tail'] = (dataframe['close'] - dataframe['low']).abs()
        return dataframe

    def populate_buy_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[
            (
                dataframe['lower'].shift().gt(0) &
                dataframe['bbdelta'].gt(dataframe['close'] * self.df_close_bbdelta.value) &
                dataframe['closedelta'].gt(dataframe['close'] * self.df_close_closedelta.value) &
                dataframe['tail'].lt(dataframe['bbdelta'] * self.df_tail_bbdelta.value) &
                dataframe['close'].lt(dataframe['lower'].shift()) &
                dataframe['close'].le(dataframe['close'].shift())
            ),
            'buy'] = 1
        return dataframe

    def populate_sell_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        """
        no sell signal
        """
        dataframe.loc[:, 'sell'] = 0
        return dataframe