MACDStrategyCrossed

# --- Do not remove these libs ---
import talib.abstract as ta
from pandas import DataFrame

import coingro.vendor.qtpylib.indicators as qtpylib
from coingro.strategy.interface import IStrategy

# --------------------------------


class MACDStrategyCrossed(IStrategy):
    """
    buy:
        MACD crosses MACD signal above
        and CCI < -50
    sell:
        MACD crosses MACD signal below
        and CCI > 100
    """

    # 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"]
        dataframe["cci"] = ta.CCI(dataframe)

        return dataframe

    def populate_buy_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[
            (
                qtpylib.crossed_above(dataframe["macd"], dataframe["macdsignal"])
                & (dataframe["cci"] <= -50.0)
            ),
            "buy",
        ] = 1

        return dataframe

    def populate_sell_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[
            (
                qtpylib.crossed_below(dataframe["macd"], dataframe["macdsignal"])
                & (dataframe["cci"] >= 100.0)
            ),
            "sell",
        ] = 1

        return dataframe