# pragma pylint: disable=missing-docstring, invalid-name, pointless-string-statement
# flake8: noqa: F401
# isort: skip_file
# --- Do not remove these imports ---
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


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

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

    use_exit_signal = True
    exit_profit_only = False
    ignore_roi_if_entry_signal = False

    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)
        
        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