import pandas as pd
from dateutil.relativedelta import relativedelta
from datetime import datetime
import sqlite3
import time
import requests
import json
from config import *

from monitor import Monitor

class MonitorCoin (Monitor):
    """자산(코인/주식/ETF) 모니터링 및 매수 실행 클래스"""

    def __init__(self, cooldown_file: str = 'coins_buy_time.json') -> None:
        super().__init__(cooldown_file)

    # ------------- Data fetch -------------
    def get_coin_data(self, symbol: str, interval: int = 60, to: str | None = None, retries: int = 3) -> pd.DataFrame | None:
        for attempt in range(retries):
            try:
                if to is None:
                    url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200").format(interval, symbol)
                else:
                    url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200&to={}").format(interval, symbol, to)
                headers = {"accept": "application/json"}
                response = requests.get(url, headers=headers)
                json_data = json.loads(response.text)
                df_temp = pd.DataFrame(json_data)
                df_temp = df_temp.sort_index(ascending=False)
                if 'candle_date_time_kst' not in df_temp:
                    return None
                data = pd.DataFrame()
                data['datetime'] = pd.to_datetime(df_temp['candle_date_time_kst'], format='%Y-%m-%dT%H:%M:%S')
                data['Open'] = df_temp['opening_price']
                data['Close'] = df_temp['trade_price']
                data['High'] = df_temp['high_price']
                data['Low'] = df_temp['low_price']
                data['Volume'] = df_temp['candle_acc_trade_volume']
                data = data.set_index('datetime')
                data = data.astype(float)
                data["datetime"] = data.index
                if not data.empty:
                    return data
                print(f"No data received for {symbol}, attempt {attempt + 1}")
                time.sleep(0.5)
            except Exception as e:
                print(f"Attempt {attempt + 1} failed for {symbol}: {str(e)}")
                if attempt < retries - 1:
                    time.sleep(5)
                continue
        return None

    def get_coin_more_data(self, symbol: str, interval: int, bong_count: int = 3000) -> pd.DataFrame:
        to = datetime.now()
        data: pd.DataFrame | None = None
        while data is None or len(data) < bong_count:
            if data is None:
                data = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
            else:
                previous_count = len(data)
                df = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
                data = pd.concat([data, df], ignore_index=True)
                if previous_count == len(data):
                    break
            time.sleep(0.3)
            to = to - relativedelta(minutes=interval * 200)
        data = data.set_index('datetime')
        data = data.sort_index()
        data = data.drop_duplicates(keep='first')
        data["datetime"] = data.index
        return data

    def get_coin_saved_data(self, symbol: str, interval: int, data: pd.DataFrame) -> pd.DataFrame:
        conn = sqlite3.connect('coins.db')
        cursor = conn.cursor()
        for i in range(1, len(data)):
            cursor.execute(
                "SELECT * from " + symbol + " where CODE = ? and ymdhms = ? and interval = ?",
                (symbol, data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'), interval),
            )
            arr = cursor.fetchone()
            if not arr:
                cursor.execute(
                    "INSERT INTO " + symbol + " (interval, CODE, NAME, ymdhms, ymd, hms, close, open, high, low, volume) VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
                    (
                        interval,
                        symbol,
                        KR_COINS[symbol],
                        data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'),
                        data['datetime'].iloc[-i].strftime('%Y%m%d'),
                        data['datetime'].iloc[-i].strftime('%H%M%S'),
                        data['Close'].iloc[-i],
                        data['Open'].iloc[-i],
                        data['High'].iloc[-i],
                        data['Low'].iloc[-i],
                        data['Volume'].iloc[-i],
                    ),
                )
            else:
                break
        cursor.execute(
            "select * from (SELECT Open,Close,High,Low,Volume,ymdhms as datetime from "
            + symbol
            + " order by ymdhms desc limit 5000) subquery order by datetime"
        )
        result = cursor.fetchall()
        conn.commit()
        cursor.close()
        conn.close()
        df = pd.DataFrame(result)
        df.columns = ['Open', 'Close', 'High', 'Low', 'Volume', 'datetime']
        df = df.set_index('datetime')
        df = df.sort_index()
        df['datetime'] = df.index
        return df

    def get_coin_some_data(self, symbol: str, interval: int) -> pd.DataFrame:
        data = self.get_coin_data(symbol, interval)
        data_1 = self.get_coin_data(symbol, interval=1)
        data_1.at[data_1.index[-1], 'Volume'] = data_1['Volume'].iloc[-1] * 60
        saved_data = self.get_coin_saved_data(symbol, interval, data)
        data = pd.concat([data, saved_data, data_1.iloc[[-1]]], ignore_index=True)
        data['datetime'] = pd.to_datetime(data['datetime'], format='%Y-%m-%d %H:%M:%S')
        data = data.set_index('datetime')
        data = data.sort_index()
        data = data.drop_duplicates(keep='first')
        data["datetime"] = data.index
        return data

    def monitor_coins(self, symbol) -> None:
        print("[{}] {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S'), symbol))

        interval = 60
        data = self.get_coin_some_data(symbol, interval)
        if data is not None and not data.empty:
            try:
                data = self.calculate_technical_indicators(data)
                recent_data = self.check_buy_point(symbol, data)
                if recent_data['buy_point'].iloc[-1] != 1:
                    return
                buy_success = self.buy_ticker(symbol, recent_data)
                if not buy_success:
                    return
            except Exception as e:
                print(f"Error processing data for {symbol}: {str(e)}")
        else:
            print(f"Data for {symbol} is empty or None.")

        time.sleep(0.5)

        return
    # ------------- Scheduler -------------
    def run_schedule(self, ticker) -> None:

        while True:
            self.monitor_coins(symbol)
            time.sleep(1)

if __name__ == "__main__":
    symbol = 'BONK'
    cooldown_file = './resources/coins_buy_'+symbol+'.json'

    MonitorCoin(cooldown_file).run_schedule(symbol)