"""
SOL15mStrategy - 基于15m时间框架的SOL/USDT期货策略

核心逻辑：
    - 15m EMA26/EMA52 交叉做多做空
    - RSI过滤：做多要求RSI<65，做空要求RSI>35（避免超买超卖区入场）
    - 使用 trailing_stop 让利润奔跑
    - 宽止损（2%），给交易足够呼吸空间

使用命令：
    freqtrade backtesting -c ./user_data/Chan/config/Local_Test.json --strategy SOL15mStrategy --strategy-path ./user_data/Chan/strategies --timerange=20250301-
"""

from datetime import datetime
from typing import Optional

import talib.abstract as ta
from pandas import DataFrame

from freqtrade.persistence import Trade
from freqtrade.strategy import IStrategy


class SOL15mStrategy(IStrategy):
    INTERFACE_VERSION: int = 3

    # === 基础配置 ===
    timeframe = "15m"
    can_short = True
    startup_candle_count: int = 200

    # 止损 2%
    stoploss = -0.02
    use_custom_stoploss = False

    # trailing stop: 利润达到1.5%后开始追踪，回撤0.5%止盈
    trailing_stop = True
    trailing_stop_positive = 0.005
    trailing_stop_positive_offset = 0.015
    trailing_only_offset_is_reached = True

    # ROI: 阶梯式止盈
    minimal_roi = {
        "0": 0.04,      # 4%直接止盈
        "60": 0.025,     # 60分钟后 2.5%
        "180": 0.015,    # 3小时后 1.5%
        "480": 0.005,    # 8小时后 0.5%
        "720": 0,        # 12小时后保本退出
    }

    order_types = {
        "entry": "market",
        "exit": "market",
        "stoploss": "market",
        "stoploss_on_exchange": False,
    }

    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        # EMA
        dataframe["ema26"] = ta.EMA(dataframe, timeperiod=26)
        dataframe["ema52"] = ta.EMA(dataframe, timeperiod=52)
        dataframe["ema100"] = ta.EMA(dataframe, timeperiod=100)

        # RSI
        dataframe["rsi"] = ta.RSI(dataframe, timeperiod=14)

        # MACD
        macd = ta.MACD(dataframe, fastperiod=12, slowperiod=26, signalperiod=9)
        dataframe["macd"] = macd["macd"]
        dataframe["macdsignal"] = macd["macdsignal"]

        # EMA26上穿EMA52
        dataframe["ema26_cross_up_52"] = (
            (dataframe["ema26"] > dataframe["ema52"])
            & (dataframe["ema26"].shift(1) <= dataframe["ema52"].shift(1))
        )

        # EMA26下穿EMA52
        dataframe["ema26_cross_dn_52"] = (
            (dataframe["ema26"] < dataframe["ema52"])
            & (dataframe["ema26"].shift(1) >= dataframe["ema52"].shift(1))
        )

        # MACD死叉
        dataframe["macd_cross_dn"] = (
            (dataframe["macd"] < dataframe["macdsignal"])
            & (dataframe["macd"].shift(1) >= dataframe["macdsignal"].shift(1))
        )

        return dataframe

    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        # 做多: EMA26上穿EMA52 + RSI < 65 (不在超买区)
        dataframe.loc[
            (dataframe["ema26_cross_up_52"])
            & (dataframe["rsi"] < 65),
            ["enter_long", "enter_tag"],
        ] = (1, "ema26x52_long")

        # 做空: EMA26下穿EMA52 + RSI > 35 (不在超卖区)
        dataframe.loc[
            (dataframe["ema26_cross_dn_52"])
            & (dataframe["rsi"] > 35),
            ["enter_short", "enter_tag"],
        ] = (1, "ema26x52_short")

        return dataframe

    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        # 不使用信号退出，完全由 trailing_stop + ROI + stoploss 控制
        return dataframe

    def leverage(
        self,
        pair: str,
        current_time: datetime,
        current_rate: float,
        proposed_leverage: float,
        max_leverage: float,
        entry_tag: Optional[str],
        side: str,
        **kwargs,
    ) -> float:
        return 1.0