# source: https://raw.githubusercontent.com/DerSalvador/freqtrade-helm-chart/a669dc11b640b0eb63aa8f8b51e9f181fd7ee43c/chart/deployed_strategies/binance-futures-k8s-namespace/MACDCCI.py
# --- Do not remove these libs ---
from freqtrade.strategy.interface 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
import numpy  # noqa
__author__ = 'Kevin Ossenbrück'
__copyright__ = 'Free For Use'
__credits__ = ['Bloom Trading, Mohsen Hassan']
__license__ = 'MIT'
__version__ = '1.0'
__maintainer__ = 'Kevin Ossenbrück'
__email__ = 'kevin.ossenbrueck@pm.de'
__status__ = 'Live'
class_name = 'Github_DerSalvador_freqtrade_helm_chart__MACDCCI__20260115_122204'

class Github_DerSalvador_freqtrade_helm_chart__MACDCCI__20260115_122204(IStrategy):
    INTERFACE_VERSION = 3
    # Disable ROI
    # Could be replaced with new ROI from hyperopt.
    minimal_roi = {'0': 100}
    stoploss = -0.3
    ### Do extra hyperopt for trailing seperat. Use "--spaces default" and then "--spaces trailing".
    ### See here for more information: https://www.freqtrade.io/en/latest/hyperopt
    trailing_stop = False
    trailing_stop_positive = 0.08
    trailing_stop_positive_offset = 0.1
    trailing_only_offset_is_reached = False
    timeframe = '30m'

    def informative_pairs(self):
        return []

    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        macd = ta.MACD(dataframe, fastperiod=12, slowperiod=26, signalperiod=9)
        dataframe['macd'] = macd['macd']
        dataframe['macdsignal'] = macd['macdsignal']
        dataframe['macdhist'] = macd['macdhist']
        ### Add timeperiod from hyperopt (replace xx with value):
        ### "xx" must be replaced even before the first hyperopt is run,
        ### else "xx" would be a syntax error because it must be a Integer value.
        dataframe['cci-entry'] = ta.CCI(dataframe, timeperiod=35)
        dataframe['cci-exit'] = ta.CCI(dataframe, timeperiod=62)
        return dataframe

    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:  # Replace with value from hyperopt.
        dataframe.loc[(dataframe['macd'] > dataframe['macdsignal']) & (dataframe['cci-entry'] <= -100.0), 'enter_long'] = 1
        return dataframe

    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:  # Replace with value from hyperopt.
        dataframe.loc[(dataframe['macd'] < dataframe['macdsignal']) & (dataframe['cci-exit'] >= 200.0), 'exit_long'] = 1
        return dataframe