# source: https://raw.githubusercontent.com/aak-dev/data/98de3e7b03de2aac1979fd483b94a882afc1e1de/user_data/strategies/slow_fast_ma_cross.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


class github_aak_dev_data__slow_fast_ma_cross__20210602_010401(IStrategy):

    # Minimal ROI designed for the strategy.
    # This attribute will be overridden if the config file contains "minimal_roi"
    minimal_roi = {
        "0": 0.5
    }

    # Optimal stoploss designed for the strategy
    # This attribute will be overridden if the config file contains "stoploss"
    stoploss = -0.2

    # Optimal ticker interval for the strategy
    timeframe = '1h'

    plot_config = {
        'main_plot': {
            # Configuration for main plot indicators.
            # Specifies `ema10` to be red, and `ema50` to be a shade of gray
            'maShort': {'color': 'red'},
            'maMedium': {'color': 'black'},
            # By omitting color, a random color is selected.
            'sar': {},
        }
   }

    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        macd = ta.MACD(dataframe)

        dataframe['maShort'] = ta.MA(dataframe, timeperiod=50)
        dataframe['maMedium'] = ta.MA(dataframe, timeperiod=200)

        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['maShort'], dataframe['maMedium'])
            ),
            '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_above(dataframe['maMedium'], dataframe['maShort'])
            ),
            'sell'] = 1
        return dataframe