165 lines
6.9 KiB
Python
165 lines
6.9 KiB
Python
import pandas as pd
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from dateutil.relativedelta import relativedelta
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from datetime import datetime
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import sqlite3
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import time
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import requests
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import json
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from config import *
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from monitor import Monitor
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class MonitorCoin (Monitor):
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"""자산(코인/주식/ETF) 모니터링 및 매수 실행 클래스"""
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def __init__(self, cooldown_file: str = 'coins_buy_time.json') -> None:
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super().__init__(cooldown_file)
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# ------------- Data fetch -------------
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def get_coin_data(self, symbol: str, interval: int = 60, to: str | None = None, retries: int = 3) -> pd.DataFrame | None:
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for attempt in range(retries):
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try:
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if to is None:
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url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200").format(interval, symbol)
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else:
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url = ("https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=200&to={}").format(interval, symbol, to)
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headers = {"accept": "application/json"}
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response = requests.get(url, headers=headers)
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json_data = json.loads(response.text)
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df_temp = pd.DataFrame(json_data)
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df_temp = df_temp.sort_index(ascending=False)
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if 'candle_date_time_kst' not in df_temp:
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return None
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data = pd.DataFrame()
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data['datetime'] = pd.to_datetime(df_temp['candle_date_time_kst'], format='%Y-%m-%dT%H:%M:%S')
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data['Open'] = df_temp['opening_price']
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data['Close'] = df_temp['trade_price']
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data['High'] = df_temp['high_price']
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data['Low'] = df_temp['low_price']
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data['Volume'] = df_temp['candle_acc_trade_volume']
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data = data.set_index('datetime')
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data = data.astype(float)
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data["datetime"] = data.index
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if not data.empty:
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return data
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print(f"No data received for {symbol}, attempt {attempt + 1}")
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time.sleep(0.5)
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except Exception as e:
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print(f"Attempt {attempt + 1} failed for {symbol}: {str(e)}")
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if attempt < retries - 1:
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time.sleep(5)
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continue
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return None
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def get_coin_more_data(self, symbol: str, interval: int, bong_count: int = 3000) -> pd.DataFrame:
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to = datetime.now()
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data: pd.DataFrame | None = None
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while data is None or len(data) < bong_count:
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if data is None:
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data = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
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else:
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previous_count = len(data)
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df = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
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data = pd.concat([data, df], ignore_index=True)
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if previous_count == len(data):
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break
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time.sleep(0.3)
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to = to - relativedelta(minutes=interval * 200)
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data = data.set_index('datetime')
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data = data.sort_index()
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data = data.drop_duplicates(keep='first')
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data["datetime"] = data.index
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return data
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def get_coin_saved_data(self, symbol: str, interval: int, data: pd.DataFrame) -> pd.DataFrame:
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conn = sqlite3.connect('coins.db')
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cursor = conn.cursor()
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for i in range(1, len(data)):
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cursor.execute(
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"SELECT * from " + symbol + " where CODE = ? and ymdhms = ? and interval = ?",
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(symbol, data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'), interval),
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)
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arr = cursor.fetchone()
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if not arr:
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cursor.execute(
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"INSERT INTO " + symbol + " (interval, CODE, NAME, ymdhms, ymd, hms, close, open, high, low, volume) VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
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(
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interval,
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symbol,
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KR_COINS[symbol],
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data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S'),
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data['datetime'].iloc[-i].strftime('%Y%m%d'),
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data['datetime'].iloc[-i].strftime('%H%M%S'),
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data['Close'].iloc[-i],
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data['Open'].iloc[-i],
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data['High'].iloc[-i],
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data['Low'].iloc[-i],
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data['Volume'].iloc[-i],
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),
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)
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else:
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break
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cursor.execute(
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"select * from (SELECT Open,Close,High,Low,Volume,ymdhms as datetime from "
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+ symbol
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+ " order by ymdhms desc limit 5000) subquery order by datetime"
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)
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result = cursor.fetchall()
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conn.commit()
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cursor.close()
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conn.close()
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df = pd.DataFrame(result)
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df.columns = ['Open', 'Close', 'High', 'Low', 'Volume', 'datetime']
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df = df.set_index('datetime')
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df = df.sort_index()
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df['datetime'] = df.index
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return df
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def get_coin_some_data(self, symbol: str, interval: int) -> pd.DataFrame:
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data = self.get_coin_data(symbol, interval)
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data_1 = self.get_coin_data(symbol, interval=1)
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data_1.at[data_1.index[-1], 'Volume'] = data_1['Volume'].iloc[-1] * 60
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saved_data = self.get_coin_saved_data(symbol, interval, data)
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data = pd.concat([data, saved_data, data_1.iloc[[-1]]], ignore_index=True)
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data['datetime'] = pd.to_datetime(data['datetime'], format='%Y-%m-%d %H:%M:%S')
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data = data.set_index('datetime')
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data = data.sort_index()
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data = data.drop_duplicates(keep='first')
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data["datetime"] = data.index
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return data
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def monitor_coins(self, symbol) -> None:
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print("[{}] KRW COINs: {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S'), ','.join(KR_COINS.keys())))
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interval = 60
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data = self.get_coin_some_data(symbol, interval)
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if data is not None and not data.empty:
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try:
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data = self.calculate_technical_indicators(data)
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recent_data = self.check_buy_point(symbol, data)
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if recent_data['buy_point'].iloc[-1] != 1:
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return
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buy_success = self.buy_ticker(symbol, recent_data)
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if not buy_success:
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return
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except Exception as e:
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print(f"Error processing data for {symbol}: {str(e)}")
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else:
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print(f"Data for {symbol} is empty or None.")
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time.sleep(0.5)
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return
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# ------------- Scheduler -------------
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def run_schedule(self, ticker) -> None:
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while True:
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self.monitor_coins(symbol)
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time.sleep(1)
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if __name__ == "__main__":
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symbol = 'TON'
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cooldown_file = './resources/coins_buy_'+symbol+'.json'
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MonitorCoin(cooldown_file).run_schedule(symbol)
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