from __future__ import annotations

from pandas import DataFrame
import talib.abstract as ta

from freqtrade.strategy import DecimalParameter, IStrategy


class TrendAlphaV1(IStrategy):
    INTERFACE_VERSION = 3

    timeframe = "5m"
    can_short = False
    process_only_new_candles = True
    startup_candle_count = 240

    minimal_roi = {"0": 0.04, "60": 0.02, "180": 0.0}
    stoploss = -0.08
    trailing_stop = True
    trailing_stop_positive = 0.015
    trailing_stop_positive_offset = 0.035
    trailing_only_offset_is_reached = True

    buy_rsi_min = DecimalParameter(45.0, 62.0, default=52.0, decimals=1, space="buy")
    sell_rsi_max = DecimalParameter(35.0, 55.0, default=46.0, decimals=1, space="sell")

    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe["ema_50"] = ta.EMA(dataframe, timeperiod=50)
        dataframe["ema_200"] = ta.EMA(dataframe, timeperiod=200)
        dataframe["rsi"] = ta.RSI(dataframe, timeperiod=14)
        dataframe["adx"] = ta.ADX(dataframe, timeperiod=14)
        dataframe["atr"] = ta.ATR(dataframe, timeperiod=14)
        dataframe["volume_mean_30"] = dataframe["volume"].rolling(30).mean()
        return dataframe

    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[
            (
                (dataframe["ema_50"] > dataframe["ema_200"])
                & (dataframe["close"] > dataframe["ema_50"])
                & (dataframe["adx"] > 20)
                & (dataframe["rsi"] > self.buy_rsi_min.value)
                & (dataframe["volume"] > dataframe["volume_mean_30"])
            ),
            "enter_long",
        ] = 1
        return dataframe

    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[
            (
                (dataframe["close"] < dataframe["ema_50"])
                | (dataframe["rsi"] < self.sell_rsi_max.value)
            ),
            "exit_long",
        ] = 1
        return dataframe