# source: https://raw.githubusercontent.com/RudoRonuma/freqtrade/4c0a67a5c05922c6735558e344d5888e93184fcf/user_data/strategies/empty_strategy.py
# --- Do not remove these libs ---
# from functools import reduce

import numpy  # noqa

# --------------------------------
# import talib.abstract as ta
from pandas import DataFrame

# import freqtrade.vendor.qtpylib.indicators as qtpylib
from freqtrade.strategy import IStrategy


class Github_RudoRonuma_freqtrade__empty_strategy__20241205_172947(IStrategy):
    """
    An empty strategy.
    """

    INTERFACE_VERSION = 3

    # Minimal ROI designed for the strategy.
    # This attribute will be overridden if the config file contains "minimal_roi"
    minimal_roi = {"1440": 0.01, "80": 0.02, "40": 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 = -0.10

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

    # trailing stoploss
    trailing_stop = False
    trailing_stop_positive = 0.01
    trailing_stop_positive_offset = 0.02

    # run "populate_indicators" only for new candle
    process_only_new_candles = True

    # Experimental settings (configuration will overide these if set)
    use_exit_signal = True
    exit_profit_only = True
    ignore_roi_if_entry_signal = False

    # Optional order type mapping
    order_types = {
        "entry": "limit",
        "exit": "limit",
        "stoploss": "market",
        "stoploss_on_exchange": False,
    }

    # Buy hyperspace params:
    buy_params = {
        "buy_fastd": 1,
        "buy_fishRsiNorma": 5,
        "buy_rsi": 26,
        "buy_volumeAVG": 150,
    }

    # Sell hyperspace params:
    sell_params = {
        "sell_fishRsiNorma": 30,
        "sell_minusDI": 4,
        "sell_rsi": 74,
        "sell_trigger": "rsi-macd-minusdi",
    }

    def informative_pairs(self):
        """
        Define additional, informative pair/interval combinations to be cached from the exchange.
        These pair/interval combinations are non-tradeable, unless they are part
        of the whitelist as well.
        For more information, please consult the documentation
        :return: List of tuples in the format (pair, interval)
            Sample: return [("ETH/USDT", "5m"),
                            ("BTC/USDT", "15m"),
                            ]
        """
        return []

    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        """
        Adds several different TA indicators to the given DataFrame

        Performance Note: For the best performance be frugal on the number of indicators
        you are using. Let uncomment only the indicator you are using in your strategies
        or your hyperopt configuration, otherwise you will waste your memory and CPU usage.
        """

        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
        """
        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
        """
        return dataframe