# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
# flake8: noqa: F401
# isort: skip_file
# --- Do not remove these imports ---
from dingtalk import DingTalkBot
import numpy as np
import pandas as pd
from datetime import datetime, timedelta, timezone
from pandas import DataFrame
from typing import Optional, Union
from freqtrade.strategy import (
    IStrategy,
    Trade,
    Order,
    PairLocks,
    informative,  # @informative decorator
    # Hyperopt Parameters
    BooleanParameter,
    CategoricalParameter,
    DecimalParameter,
    IntParameter,
    RealParameter,
    # timeframe helpers
    timeframe_to_minutes,
    timeframe_to_next_date,
    timeframe_to_prev_date,
    # Strategy helper functions
    merge_informative_pair,
    stoploss_from_absolute,
    stoploss_from_open,
)
import logging  
  
logger = logging.getLogger(__name__) 
# --------------------------------
# Add your lib to import here
import talib.abstract as ta
from technical import qtpylib


webhook = "https://oapi.dingtalk.com/robot/send?access_token=21de667159edadd33172c6ec414a2addf9c6359189350ffd36819d2a20e8a0f4"  # 填写你的webhook
secret = "SEC43a0fa0b29717f98637a119b92a0bd5f7b2b6da671bdd2bd1279ed8323454d5e"  # 填写你的加签token（如果有），否则留空

# CTA 群机器人
# webhook = "https://oapi.dingtalk.com/robot/send?access_token=87c7abfcdd69b699c32da4e4f5981cd2ca6b0445474fc6ffb36f2ed0f6262fbb"
# secret = "SECf3d6b43f2f8a87ab91feffd052e71ec314fbf57a1842e483fe07af3c0a0e5aa6"
dingtalk = DingTalkBot(webhook, secret)


class CCIMultiTimeframeSpotStrategy(IStrategy):
    # 策略参数
    INTERFACE_VERSION = 3

    minimal_roi = {"0": 100}
    stoploss = -1
    use_custom_stoploss = False
    trailing_stop = False
    timeframe = '4h'

    use_exit_signal = True
    exit_profit_only = False
    ignore_roi_if_entry_signal = False

    def order_filled(self, pair: str, trade: Trade, order: Order, current_time: datetime, **kwargs) -> None:  
        # 交易对  
        trading_pair = pair  
        
        # 时间  
        fill_time = order.order_filled_date or current_time  
        
        # 价格  
        fill_price = order.average or order.price  
        
        # 买入还是卖出  
        side = order.ft_order_side  # 'buy' 或 'sell'  
        
        # 仓位(当前持仓数量)  
        position = trade.amount  
        
        # 或者使用日志  
        logger.info(  
            f"订单成交 - 交易对: {trading_pair}, "  
            f"时间: {fill_time}, "  
            f"价格: {fill_price}, "  
            f"方向: {side}, "  
            f"仓位: {position}"  
        )  
        # if self.config["runmode"].value in ("live", "dry_run"):
        logger.info(f"11111111{self.config['runmode']}")
        # dingtalk.send_text(
        #     content=f"订单成交 - 交易对: {trading_pair}, 时间: {fill_time}, 价格: {fill_price}, 方向: {side}, 仓位: {position}")
        
        return None

    def TD(self, dataframe:DataFrame):
        close = dataframe['close'].to_list()
        td = [0,0,0,0]
        up = 0
        down = 0
        for i in range(4, len(close)):
            if close[i] > close[i-4]:
                up += 1
                down = 0
                td.append(up)
            else:
                down -= 1
                up = 0
                td.append(down)
        return td

    @informative('1d')  
    def populate_indicators_1d(self, dataframe: DataFrame, metadata: dict) -> DataFrame:  
        dataframe['cci'] = ta.CCI(dataframe, timeperiod=26)  
        dataframe["adx"] = ta.ADX(dataframe)
        macd = ta.MACD(dataframe, fastperiod=12, slowperiod=26, signalperiod=9,)
        dataframe["macd"] = macd["macd"]
        dataframe["macdsignal"] = macd["macdsignal"]
        dataframe["macdhist"] = macd["macdhist"]
        logger.info(dataframe.tail())
        return dataframe
    
    @informative('1w')  
    def populate_indicators_1w(self, dataframe: DataFrame, metadata: dict) -> DataFrame:  
        dataframe['cci'] = ta.CCI(dataframe, timeperiod=26)  
        logger.info(dataframe.tail())
        return dataframe
    def populate_indicators(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        # 计算4h CCI
        dataframe['cci_4h'] = ta.CCI(dataframe, timeperiod=26)
        dataframe['sma12_4h'] = ta.SMA(dataframe, timeperiod=12)
        dataframe['sma26_4h'] = ta.SMA(dataframe, timeperiod=26)
        dataframe["adx_4h"] = ta.ADX(dataframe)
        
        macd = ta.MACD(dataframe, fastperiod=12, slowperiod=26, signalperiod=9,)
        dataframe["macd_4h"] = macd["macd"]
        dataframe["macdsignal_4h"] = macd["macdsignal"]
        dataframe["macdhist_4h"] = macd["macdhist"]

        dataframe['cci_hist_4h'] = ta.CCI(dataframe['macdhist_1d'], dataframe['macdhist_1d'], dataframe['macdhist_1d'], timeperiod=26)

        # dataframe['adx_hist_4h'] = ta.ADX(dataframe['macdhist_4h'])
        dataframe['TD'] = self.TD(dataframe)
        dataframe["atr"] = ta.ATR(dataframe, timeperiod=14)  
        
        logger.info(dataframe.tail())
        return dataframe

    def populate_entry_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        # 入场：1d与4h CCI < -100，且4h CCI上升（当前 > 前一根）
        dataframe.loc[
            (
                (dataframe['cci_4h'] < -100) &
                (dataframe['cci_1d'] < -100) &
                (dataframe['cci_4h'] > dataframe['cci_4h'].shift(1)) &
                # (dataframe['macdhist_1d'] < dataframe['macdhist_1d'].shift(1)) &
                (dataframe['volume'] > 0)
            ),
            'enter_long',
        ] = 1

        return dataframe

    def populate_exit_trend(self, dataframe: DataFrame, metadata: dict) -> DataFrame:
        # 离场：1d与4h CCI > 100，且4h CCI下降（当前 < 前一根）
        dataframe.loc[
            (
                (dataframe['cci_4h'] > 100) &
                (dataframe['cci_1d'] > 100) &
                (dataframe['cci_4h'] < dataframe['cci_4h'].shift(1)) &
                # (dataframe['macdhist_1d'] > dataframe['macdhist_1d'].shift(1)) &
                (dataframe['volume'] > 0)
            ),
            'exit_long',
        ] = 1

        return dataframe

    def custom_stoploss(self, pair: str, trade: Trade, current_time: datetime,  
                    current_rate: float, current_profit: float, after_fill: bool,  
                    **kwargs) -> float | None:  
        dataframe, _ = self.dp.get_analyzed_dataframe(pair, self.timeframe)  
        candle = dataframe.iloc[-1].squeeze()  
        side = 1 if trade.is_short else -1  
        return stoploss_from_absolute(current_rate + (side * candle["atr"] * 3),   
                                    current_rate=current_rate,   
                                    is_short=trade.is_short,  
                                    leverage=trade.leverage)