# pragma pylint: disable=missing-docstring, invalid-name, too-few-public-methods
"""
TrendMomentumStrategy — tentative d'amélioration du rendement (vs SampleStrategy).

Idée : n'entrer que sur des tendances confirmées et fortes (filtre EMA50 + ADX),
laisser courir les gains (ROI plus haut + trailing), couper vite les perdants.
Objectif : meilleur rendement ajusté du risque — PAS de promesse de +10 %/semaine.
"""
from __future__ import annotations

import talib.abstract as ta
from pandas import DataFrame

from freqtrade.strategy import IStrategy


class TrendMomentumStrategy(IStrategy):
    INTERFACE_VERSION = 3
    timeframe = "1h"

    # Laisser courir : on vise des gains plus gros, on attend plus longtemps.
    minimal_roi = {"0": 0.12, "240": 0.06, "720": 0.03, "1440": 0}
    stoploss = -0.06  # on coupe vite les perdants
    trailing_stop = True
    trailing_stop_positive = 0.025
    trailing_stop_positive_offset = 0.04
    trailing_only_offset_is_reached = True

    startup_candle_count: int = 60
    process_only_new_candles = True
    use_exit_signal = True

    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe["ema_fast"] = ta.EMA(dataframe, timeperiod=9)
        dataframe["ema_slow"] = ta.EMA(dataframe, timeperiod=21)
        dataframe["ema_trend"] = ta.EMA(dataframe, timeperiod=50)
        dataframe["adx"] = ta.ADX(dataframe, timeperiod=14)
        dataframe["rsi"] = ta.RSI(dataframe, timeperiod=14)
        macd = ta.MACD(dataframe)
        dataframe["macd"] = macd["macd"]
        dataframe["macdsignal"] = macd["macdsignal"]
        return dataframe

    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[
            (
                (dataframe["ema_fast"] > dataframe["ema_slow"])        # tendance courte haussière
                & (dataframe["close"] > dataframe["ema_trend"])        # au-dessus tendance MT
                & (dataframe["adx"] > 25)                              # tendance forte
                & (dataframe["macd"] > dataframe["macdsignal"])        # momentum haussier
                & (dataframe["rsi"] > 50)
                & (dataframe["rsi"] < 75)                              # pas en surachat extrême
                & (dataframe["volume"] > 0)
            ),
            "enter_long",
        ] = 1
        return dataframe

    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        dataframe.loc[
            (
                (dataframe["macd"] < dataframe["macdsignal"])          # momentum se retourne
                & (dataframe["close"] < dataframe["ema_slow"])
                & (dataframe["volume"] > 0)
            ),
            "exit_long",
        ] = 1
        return dataframe