init
This commit is contained in:
dsyoon
@@ -114,7 +114,7 @@ export STOCK_TELEGRAM_CHAT_ID="<CHAT_ID>"
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## 사용 방법
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```bash
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$ python stock_monitor.py
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$ python monitor_coin.py
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```
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스크립트가 백그라운드에서 무한 루프로 동작하며 지정된 시간마다 텔레그램 알림을 전송합니다.
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@@ -1,6 +1,6 @@
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from HTS2 import HTS
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import sqlite3
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from stock_monitor import get_coin_more_data
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from monitor_coin import get_coin_more_data
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from config import *
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hts = HTS()
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407
monitor.py
Normal file
407
monitor.py
Normal file
@@ -0,0 +1,407 @@
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import pandas as pd
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from HTS2 import HTS
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from dateutil.relativedelta import relativedelta
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from datetime import datetime, timedelta
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import sqlite3
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import telegram
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import time
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import requests
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import json
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import asyncio
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from multiprocessing import Pool
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import schedule
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from config import *
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import FinanceDataReader as fdr
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import numpy as np
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import os
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class Monitor:
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"""자산(코인/주식/ETF) 모니터링 및 매수 실행 클래스"""
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cooldown_file = None
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def __init__(self, cooldown_file='coins_buy_time.json') -> None:
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self.hts = HTS()
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if cooldown_file is not None:
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self.cooldown_file = cooldown_file
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self.buy_cooldown = self._load_buy_cooldown()
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# ------------- Persistence -------------
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def _load_buy_cooldown(self) -> dict:
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if os.path.exists(self.cooldown_file):
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try:
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with open(self.cooldown_file, 'r', encoding='utf-8') as f:
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data = json.load(f)
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cooldown: dict[str, datetime] = {}
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for symbol, time_str in data.items():
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cooldown[symbol] = datetime.fromisoformat(time_str)
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return cooldown
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except Exception as e:
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print(f"Error loading cooldown data: {e}")
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return {}
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return {}
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def _save_buy_cooldown(self) -> None:
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try:
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data: dict[str, str] = {}
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for symbol, dt in self.buy_cooldown.items():
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data[symbol] = dt.isoformat()
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with open(self.cooldown_file, 'w', encoding='utf-8') as f:
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json.dump(data, f, ensure_ascii=False, indent=2)
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except Exception as e:
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print(f"Error saving cooldown data: {e}")
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# ------------- Telegram -------------
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def _send_coin_msg(self, text: str) -> None:
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coin_client = telegram.Bot(token=COIN_TELEGRAM_BOT_TOKEN)
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asyncio.run(coin_client.send_message(chat_id=COIN_TELEGRAM_CHAT_ID, text=text))
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def _send_stock_msg(self, text: str) -> None:
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stock_client = telegram.Bot(token=STOCK_TELEGRAM_BOT_TOKEN)
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asyncio.run(stock_client.send_message(chat_id=STOCK_TELEGRAM_CHAT_ID, text=text))
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def send_coin_telegram_message(self, message_list: list[str], header: str) -> None:
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payload = header + "\n"
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for i, message in enumerate(message_list):
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payload += message
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if i + 1 % 20 == 0:
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pool = Pool(12)
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pool.map(self._send_coin_msg, [payload])
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payload = ''
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if len(message_list) % 20 != 0:
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pool = Pool(12)
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pool.map(self._send_coin_msg, [payload])
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def send_stock_telegram_message(self, message_list: list[str], header: str) -> None:
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payload = header + "\n"
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for i, message in enumerate(message_list):
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payload += message
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if i + 1 % 20 == 0:
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pool = Pool(12)
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pool.map(self._send_stock_msg, [payload])
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payload = ''
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if len(message_list) % 20 != 0:
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pool = Pool(12)
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pool.map(self._send_stock_msg, [payload])
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# ------------- Indicators -------------
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def normalize_data(self, data: pd.DataFrame) -> pd.DataFrame:
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columns_to_normalize = ['Open', 'High', 'Low', 'Close', 'Volume']
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normalized_data = data.copy()
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for column in columns_to_normalize:
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min_val = data[column].rolling(window=20).min()
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max_val = data[column].rolling(window=20).max()
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denominator = max_val - min_val
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normalized_data[f'{column}_Norm'] = np.where(
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denominator != 0,
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(data[column] - min_val) / denominator,
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0.5,
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)
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return normalized_data
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def calculate_technical_indicators(self, data: pd.DataFrame) -> pd.DataFrame:
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data = self.normalize_data(data)
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data['MA5'] = data['Close'].rolling(window=5).mean()
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data['MA20'] = data['Close'].rolling(window=20).mean()
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data['MA40'] = data['Close'].rolling(window=40).mean()
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data['MA120'] = data['Close'].rolling(window=120).mean()
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data['MA200'] = data['Close'].rolling(window=200).mean()
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data['MA240'] = data['Close'].rolling(window=240).mean()
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data['MA720'] = data['Close'].rolling(window=720).mean()
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data['MA1440'] = data['Close'].rolling(window=1440).mean()
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data['Deviation5'] = (data['Close'] / data['MA5']) * 100
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data['Deviation20'] = (data['Close'] / data['MA20']) * 100
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data['Deviation40'] = (data['Close'] / data['MA40']) * 100
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data['Deviation120'] = (data['Close'] / data['MA120']) * 100
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data['Deviation200'] = (data['Close'] / data['MA200']) * 100
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data['Deviation240'] = (data['Close'] / data['MA240']) * 100
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data['Deviation720'] = (data['Close'] / data['MA720']) * 100
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data['Deviation1440'] = (data['Close'] / data['MA1440']) * 100
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data['golden_cross'] = (data['MA5'] > data['MA20']) & (data['MA5'].shift(1) <= data['MA20'].shift(1))
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data['MA'] = data['Close'].rolling(window=20).mean()
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data['STD'] = data['Close'].rolling(window=20).std()
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data['Upper'] = data['MA'] + (2 * data['STD'])
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data['Lower'] = data['MA'] - (2 * data['STD'])
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return data
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# ------------- Strategy -------------
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def buy_ticker(self, symbol: str, data: pd.DataFrame) -> bool:
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try:
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current_time = datetime.now()
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if data['buy_signal'].iloc[-1] != 'fall_5p':
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buy_amount = 100000
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if symbol in self.buy_cooldown:
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time_diff = current_time - self.buy_cooldown[symbol]
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if time_diff.total_seconds() < 600:
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print(f"{symbol}: 매수 금지 중 (남은 시간: {600 - time_diff.total_seconds():.0f}초)")
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return False
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else:
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if symbol in self.buy_cooldown:
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time_diff = current_time - self.buy_cooldown[symbol]
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if time_diff.total_seconds() < 1200:
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print(f"{symbol}: 매수 금지 중 (남은 시간: {1200 - time_diff.total_seconds():.0f}초)")
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return False
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buy_amount = 5100
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if data['buy_signal'].iloc[-1] == 'movingaverage':
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buy_amount = 7000
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elif data['buy_signal'].iloc[-1] == 'deviation40':
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buy_amount = 10000
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elif data['buy_signal'].iloc[-1] == 'deviation240':
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buy_amount = 6000
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elif data['buy_signal'].iloc[-1] == 'deviation1440':
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if symbol in ['BONK', 'PEPE', 'TON']:
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buy_amount = 30000
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else:
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buy_amount = 50000
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_ = self.hts.buyCoinMarket(symbol, buy_amount)
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if self.cooldown_file is not None:
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self.buy_cooldown[symbol] = current_time
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self._save_buy_cooldown()
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print(f"{KR_COINS[symbol]} ({symbol}): {data['Close'].iloc[-1]:.4f}: 매수 완료, 20분간 매수 금지 시작")
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try:
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pool = Pool(12)
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pool.map(self._send_coin_msg, [
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"[KRW-COIN]" + "\n" + self.format_message('COIN', symbol, KR_COINS[symbol], data['Close'].iloc[-1], data['buy_signal'].iloc[-1])
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])
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except Exception as e:
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print(f"Error sending Telegram message: {str(e)}")
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except Exception as e:
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print(f"Error buying {symbol}: {str(e)}")
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return False
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return True
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def check_buy_point(self, symbol: str, data: pd.DataFrame, simulation: bool | None = None) -> pd.DataFrame:
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data = data.copy()
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data['buy_signal'] = ''
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data['buy_point'] = 0
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if data['buy_point'].iloc[-1] != 1:
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for i in range(1, len(data)):
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if all(data[f'MA{n}'].iloc[i] < data['MA720'].iloc[i] for n in [5, 20, 40, 120, 200, 240]) and \
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all(data[f'MA{n}'].iloc[i] > data[f'MA{n}'].iloc[i - 1] for n in [5, 20, 40, 120, 200, 240]) and \
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data['MA720'].iloc[i] < data['MA1440'].iloc[i]:
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data.at[data.index[i], 'buy_signal'] = 'movingaverage'
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data.at[data.index[i], 'buy_point'] = 1
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if not simulation and data['buy_point'][-3:].sum() > 0:
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data.at[data.index[-1], 'buy_signal'] = 'movingaverage'
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data.at[data.index[-1], 'buy_point'] = 1
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if data['Deviation40'].iloc[i - 1] < data['Deviation40'].iloc[i] and data['Deviation40'].iloc[i - 1] <= 90:
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data.at[data.index[i], 'buy_signal'] = 'deviation40'
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data.at[data.index[i], 'buy_point'] = 1
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if not simulation and data['buy_point'][-3:].sum() > 0:
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data.at[data.index[-1], 'buy_signal'] = 'deviation40'
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data.at[data.index[-1], 'buy_point'] = 1
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if symbol not in ['BONK']:
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if symbol in ['TRX']:
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if data['Deviation240'].iloc[i - 1] < data['Deviation240'].iloc[i] and data['Deviation240'].iloc[i - 1] <= 98:
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data.at[data.index[i], 'buy_signal'] = 'deviation240'
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data.at[data.index[i], 'buy_point'] = 1
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if not simulation and data['buy_point'][-3:].sum() > 0:
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data.at[data.index[-1], 'buy_signal'] = 'deviation240'
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data.at[data.index[-1], 'buy_point'] = 1
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else:
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if data['Deviation240'].iloc[i - 1] < data['Deviation240'].iloc[i] and data['Deviation240'].iloc[i - 1] <= 90:
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data.at[data.index[i], 'buy_signal'] = 'deviation240'
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data.at[data.index[i], 'buy_point'] = 1
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if not simulation and data['buy_point'][-3:].sum() > 0:
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data.at[data.index[-1], 'buy_signal'] = 'deviation240'
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data.at[data.index[-1], 'buy_point'] = 1
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if symbol in ['TON']:
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if data['Deviation1440'].iloc[i - 1] < data['Deviation1440'].iloc[i] and data['Deviation1440'].iloc[i - 1] <= 89:
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data.at[data.index[i], 'buy_signal'] = 'deviation1440'
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data.at[data.index[i], 'buy_point'] = 1
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if not simulation and data['buy_point'][-3:].sum() > 0:
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data.at[data.index[-1], 'buy_signal'] = 'deviation1440'
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data.at[data.index[-1], 'buy_point'] = 1
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elif symbol in ['XRP']:
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if data['Deviation1440'].iloc[i - 1] < data['Deviation1440'].iloc[i] and data['Deviation1440'].iloc[i - 1] <= 90:
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data.at[data.index[i], 'buy_signal'] = 'deviation1440'
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data.at[data.index[i], 'buy_point'] = 1
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if not simulation and data['buy_point'][-3:].sum() > 0:
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data.at[data.index[-1], 'buy_signal'] = 'deviation1440'
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data.at[data.index[-1], 'buy_point'] = 1
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elif symbol in ['BONK']:
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if data['Deviation1440'].iloc[i - 1] < data['Deviation1440'].iloc[i] and data['Deviation1440'].iloc[i - 1] <= 76:
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data.at[data.index[i], 'buy_signal'] = 'deviation1440'
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data.at[data.index[i], 'buy_point'] = 1
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if not simulation and data['buy_point'][-3:].sum() > 0:
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data.at[data.index[-1], 'buy_signal'] = 'deviation1440'
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data.at[data.index[-1], 'buy_point'] = 1
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else:
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if data['Deviation1440'].iloc[i - 1] < data['Deviation1440'].iloc[i] and data['Deviation1440'].iloc[i - 1] <= 80:
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data.at[data.index[i], 'buy_signal'] = 'deviation1440'
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data.at[data.index[i], 'buy_point'] = 1
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if not simulation and data['buy_point'][-3:].sum() > 0:
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data.at[data.index[-1], 'buy_signal'] = 'deviation1440'
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data.at[data.index[-1], 'buy_point'] = 1
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try:
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prev_low = data['Low'].iloc[i - 1]
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curr_close = data['Close'].iloc[i]
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cond_close_drop = curr_close <= prev_low * 0.95
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if cond_close_drop:
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data.at[data.index[i], 'buy_signal'] = 'fall_5p'
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data.at[data.index[i], 'buy_point'] = 1
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if not simulation and data['buy_point'][-3:].sum() > 0:
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data.at[data.index[-1], 'buy_signal'] = 'fall_5p'
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data.at[data.index[-1], 'buy_point'] = 1
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except Exception:
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pass
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return data
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# ------------- Formatting -------------
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def format_message(self, market_type: str, symbol: str, symbol_name: str, close: float, buy_signal: str) -> str:
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message = f"매수 [{market_type}] {symbol_name} ({symbol}): {buy_signal} "
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message += f"현재가: {'$' if market_type == 'US' else '₩'}{close:.4f}, "
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return message
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def format_ma_message(self, info: dict, market_type: str) -> str:
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prefix = '상승 ' if info.get('alert') else ''
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message = prefix + f"[{market_type}] {info['name']} ({info['symbol']}) "
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message += f"현재가: {'$' if market_type == 'US' else '₩'}{info['price']:.4f} \n"
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return message
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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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||||
(
|
||||
interval,
|
||||
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'),
|
||||
data['datetime'].iloc[-i].strftime('%H%M%S'),
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||||
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 get_kr_stock_data(self, symbol: str, retries: int = 3) -> pd.DataFrame | None:
|
||||
for attempt in range(retries):
|
||||
try:
|
||||
end = datetime.now()
|
||||
start = end - timedelta(days=300)
|
||||
data = fdr.DataReader(symbol, start.strftime('%Y-%m-%d'), end.strftime('%Y-%m-%d'))
|
||||
if not data.empty:
|
||||
data = data.rename(columns={
|
||||
'Open': 'Open',
|
||||
'High': 'High',
|
||||
'Low': 'Low',
|
||||
'Close': 'Close',
|
||||
'Volume': 'Volume',
|
||||
})
|
||||
return data
|
||||
print(f"No data received for {symbol}, attempt {attempt + 1}")
|
||||
time.sleep(2)
|
||||
except Exception as e:
|
||||
print(f"Attempt {attempt + 1} failed for {symbol}: {str(e)}")
|
||||
if attempt < retries - 1:
|
||||
time.sleep(5)
|
||||
continue
|
||||
return None
|
||||
164
monitor_coin.py
Normal file
164
monitor_coin.py
Normal file
@@ -0,0 +1,164 @@
|
||||
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) -> None:
|
||||
print("KRW COINs {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S')))
|
||||
for symbol in KR_COINS:
|
||||
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:
|
||||
continue
|
||||
buy_success = self.buy_ticker(symbol, recent_data)
|
||||
if not buy_success:
|
||||
continue
|
||||
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)
|
||||
|
||||
print("\t-{}".format(','.join(KR_COINS.keys())))
|
||||
return
|
||||
# ------------- Scheduler -------------
|
||||
def run_schedule(self) -> None:
|
||||
|
||||
while True:
|
||||
self.monitor_coins()
|
||||
time.sleep(10)
|
||||
|
||||
if __name__ == "__main__":
|
||||
KR_COINS.keys()
|
||||
|
||||
MonitorCoin().run_schedule()
|
||||
113
monitor_stock.py
Normal file
113
monitor_stock.py
Normal file
@@ -0,0 +1,113 @@
|
||||
import pandas as pd
|
||||
from datetime import datetime, timedelta
|
||||
import time
|
||||
import schedule
|
||||
from config import *
|
||||
import FinanceDataReader as fdr
|
||||
|
||||
from monitor import Monitor
|
||||
|
||||
class MonitorStock (Monitor):
|
||||
"""자산(코인/주식/ETF) 모니터링 및 매수 실행 클래스"""
|
||||
|
||||
def __init__(self) -> None:
|
||||
super().__init__(None)
|
||||
|
||||
|
||||
def get_kr_stock_data(self, symbol: str, retries: int = 3) -> pd.DataFrame | None:
|
||||
for attempt in range(retries):
|
||||
try:
|
||||
end = datetime.now()
|
||||
start = end - timedelta(days=300)
|
||||
data = fdr.DataReader(symbol, start.strftime('%Y-%m-%d'), end.strftime('%Y-%m-%d'))
|
||||
if not data.empty:
|
||||
data = data.rename(columns={
|
||||
'Open': 'Open',
|
||||
'High': 'High',
|
||||
'Low': 'Low',
|
||||
'Close': 'Close',
|
||||
'Volume': 'Volume',
|
||||
})
|
||||
return data
|
||||
print(f"No data received for {symbol}, attempt {attempt + 1}")
|
||||
time.sleep(2)
|
||||
except Exception as e:
|
||||
print(f"Attempt {attempt + 1} failed for {symbol}: {str(e)}")
|
||||
if attempt < retries - 1:
|
||||
time.sleep(5)
|
||||
continue
|
||||
return None
|
||||
|
||||
# ------------- Monitors -------------
|
||||
def monitor_us_stocks(self) -> None:
|
||||
message_list: list[str] = []
|
||||
print("US Stocks {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S')))
|
||||
for symbol in US_STOCKS:
|
||||
data = self.get_kr_stock_data(symbol)
|
||||
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:
|
||||
continue
|
||||
print(f" - {US_STOCKS[symbol]} ({symbol}): {recent_data['Close'].iloc[-1]:.2f}")
|
||||
message_list.append(
|
||||
self.format_message('US', symbol, US_STOCKS[symbol], recent_data['Close'].iloc[-1], recent_data['buy_signal'].iloc[-1])
|
||||
)
|
||||
except Exception as e:
|
||||
print(f"Error processing data for {symbol}: {str(e)}")
|
||||
time.sleep(0.5)
|
||||
if len(message_list) > 0:
|
||||
try:
|
||||
self.send_stock_telegram_message(message_list, header="[US-STOCK]")
|
||||
except Exception as e:
|
||||
print(f"Error sending Telegram message: {str(e)}")
|
||||
|
||||
def monitor_kr_stocks(self) -> None:
|
||||
message_list: list[str] = []
|
||||
print("KR ETFs {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S')))
|
||||
for symbol in KR_ETFS:
|
||||
try:
|
||||
clean_symbol = symbol.replace('.KS', '')
|
||||
data = self.get_kr_stock_data(clean_symbol)
|
||||
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:
|
||||
continue
|
||||
print(f" - {KR_ETFS[symbol]} ({symbol}): {recent_data['Close'].iloc[-1]:.2f}")
|
||||
message_list.append(
|
||||
self.format_message('KR', symbol, KR_ETFS[symbol], recent_data['Close'].iloc[-1], recent_data['buy_signal'].iloc[-1])
|
||||
)
|
||||
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(1)
|
||||
except Exception as e:
|
||||
print(f"Unexpected error processing {symbol}: {str(e)}")
|
||||
continue
|
||||
if len(message_list) > 0:
|
||||
try:
|
||||
self.send_stock_telegram_message(message_list, header="[KR-STOCK]")
|
||||
except Exception as e:
|
||||
print(f"Error sending Telegram message: {str(e)}")
|
||||
|
||||
# ------------- Scheduler -------------
|
||||
def run_schedule(self) -> None:
|
||||
schedule.every().day.at("16:30").do(self.monitor_us_stocks)
|
||||
schedule.every().day.at("23:30").do(self.monitor_us_stocks)
|
||||
schedule.every().day.at("23:30").do(self.monitor_us_stocks)
|
||||
schedule.every().day.at("05:10").do(self.monitor_us_stocks)
|
||||
schedule.every().day.at("18:20").do(self.monitor_kr_stocks)
|
||||
schedule.every().day.at("07:10").do(self.monitor_kr_stocks)
|
||||
print("Scheduler started. Stock Monitoring will run at specified times.")
|
||||
print(f"Loaded cooldown data for {len(self.buy_cooldown)} coins")
|
||||
while True:
|
||||
schedule.run_pending()
|
||||
time.sleep(1)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
MonitorStock().run_schedule()
|
||||
458
simulation.py
Normal file
458
simulation.py
Normal file
@@ -0,0 +1,458 @@
|
||||
from dateutil.relativedelta import relativedelta
|
||||
import pandas as pd
|
||||
import yfinance as yf
|
||||
import matplotlib.pyplot as plt
|
||||
import matplotlib.dates
|
||||
import mplcursors
|
||||
plt.rcParams['font.family'] ='AppleGothic'
|
||||
plt.rcParams['axes.unicode_minus'] =False
|
||||
|
||||
from config import *
|
||||
from monitor import Monitor
|
||||
|
||||
|
||||
class Simulation:
|
||||
def __init__(self) -> None:
|
||||
self.monitor = Monitor()
|
||||
self.INTERVAL_MAP = {
|
||||
60: "60m",
|
||||
240: "4h",
|
||||
}
|
||||
|
||||
def detect_turnaround_signal(self, symbol, data, interval=0, params=None):
|
||||
if len(data) < 7:
|
||||
return None
|
||||
current_data = data.iloc[-1]
|
||||
if current_data.get('buy_point', 0) == 1:
|
||||
return {
|
||||
'alert': True,
|
||||
'details': f"매수신호: {current_data.get('buy_signal', 'unknown')}"
|
||||
}
|
||||
return {'alert': False, 'details': "매수신호 없음"}
|
||||
|
||||
def fetch_price_history(self, symbol: str, interval_minutes: int, days: int = 30) -> pd.DataFrame:
|
||||
if symbol in KR_COINS:
|
||||
bong_count = 3000
|
||||
return self.monitor.get_coin_more_data(symbol, interval_minutes, bong_count=bong_count)
|
||||
if interval_minutes not in self.INTERVAL_MAP:
|
||||
raise ValueError("interval must be 60 or 240")
|
||||
interval_str = self.INTERVAL_MAP[interval_minutes]
|
||||
df = yf.download(
|
||||
tickers=symbol,
|
||||
period=f"{days}d",
|
||||
interval=interval_str,
|
||||
progress=False,
|
||||
)
|
||||
if df.empty:
|
||||
raise RuntimeError("No data fetched. Check symbol or interval support.")
|
||||
return df
|
||||
|
||||
def analyze_bottom_period(self, symbol: str, interval_minutes: int, days: int = 90):
|
||||
data = self.fetch_price_history(symbol, interval_minutes, days)
|
||||
data = self.monitor.calculate_technical_indicators(data)
|
||||
data = self.monitor.check_buy_point(symbol, data, simulation=True)
|
||||
print(f"데이터 기간: {data.index[0]} ~ {data.index[-1]}")
|
||||
print(f"총 데이터 수: {len(data)}")
|
||||
bottom_start = pd.Timestamp('2025-06-22')
|
||||
bottom_end = pd.Timestamp('2025-07-09')
|
||||
bottom_data = data[(data.index >= bottom_start) & (data.index <= bottom_end)]
|
||||
if len(bottom_data) == 0:
|
||||
print("저점 기간 데이터가 없습니다.")
|
||||
return None, []
|
||||
print(f"\n저점 기간 데이터: {bottom_data.index[0]} ~ {bottom_data.index[-1]}")
|
||||
print(f"저점 기간 데이터 수: {len(bottom_data)}")
|
||||
print("\n=== 저점 기간 기술적 지표 분석 ===")
|
||||
min_price = bottom_data['Low'].min()
|
||||
max_price = bottom_data['High'].max()
|
||||
avg_price = bottom_data['Close'].mean()
|
||||
print(f"최저가: {min_price:.4f}")
|
||||
print(f"최고가: {max_price:.4f}")
|
||||
print(f"평균가: {avg_price:.4f}")
|
||||
print(f"가격 변동폭: {((max_price - min_price) / min_price * 100):.2f}%")
|
||||
bb_lower_min = bottom_data['Lower'].min()
|
||||
bb_upper_max = bottom_data['Upper'].max()
|
||||
print(f"\n볼린저 밴드 분석:")
|
||||
print(f"하단 밴드 최저: {bb_lower_min:.4f}")
|
||||
print(f"상단 밴드 최고: {bb_upper_max:.4f}")
|
||||
volume_avg = bottom_data['Volume'].mean()
|
||||
volume_max = bottom_data['Volume'].max()
|
||||
print(f"\n거래량 분석:")
|
||||
print(f"평균 거래량: {volume_avg:.0f}")
|
||||
print(f"최대 거래량: {volume_max:.0f}")
|
||||
actual_bottom_idx = bottom_data['Low'].idxmin()
|
||||
actual_bottom_price = bottom_data.loc[actual_bottom_idx, 'Low']
|
||||
actual_bottom_date = actual_bottom_idx
|
||||
print(f"\n실제 저점:")
|
||||
print(f"날짜: {actual_bottom_date}")
|
||||
print(f"가격: {actual_bottom_price:.4f}")
|
||||
print(f"볼린저 하단 대비: {((actual_bottom_price - bottom_data.loc[actual_bottom_idx, 'Lower']) / bottom_data.loc[actual_bottom_idx, 'Lower'] * 100):.2f}%")
|
||||
print(f"\n=== 매수 신호 분석 ===")
|
||||
bottom_alerts = bottom_data[bottom_data['buy_point'] == 1]
|
||||
alerts = [(idx, row['Close']) for idx, row in bottom_alerts.iterrows()]
|
||||
print(f"저점 기간 매수 신호 수: {len(alerts)}")
|
||||
if alerts:
|
||||
print("매수 신호 발생 시점:")
|
||||
for date, price in alerts:
|
||||
print(f" {date}: {price:.4f}")
|
||||
return bottom_data, alerts
|
||||
|
||||
def run_simulation(self, symbol: str, interval_minutes: int, days: int = 30):
|
||||
data = self.fetch_price_history(symbol, interval_minutes)
|
||||
data = self.monitor.calculate_technical_indicators(data)
|
||||
data = self.monitor.check_buy_point(symbol, data, simulation=True)
|
||||
print(f"데이터 기간: {data.index[0]} ~ {data.index[-1]}")
|
||||
print(f"총 데이터 수: {len(data)}")
|
||||
alerts = []
|
||||
for i in range(len(data)):
|
||||
if data['buy_point'].iloc[i] == 1:
|
||||
alerts.append((data.index[i], data['Close'].iloc[i]))
|
||||
print(f"\n총 매수 신호 수: {len(alerts)}")
|
||||
ma_signals = len(data[(data['buy_point'] == 1) & (data['buy_signal'] == 'movingaverage')])
|
||||
dev40_signals = len(data[(data['buy_point'] == 1) & (data['buy_signal'] == 'deviation40')])
|
||||
dev240_signals = len(data[(data['buy_point'] == 1) & (data['buy_signal'] == 'deviation240')])
|
||||
dev1440_signals = len(data[(data['buy_point'] == 1) & (data['buy_signal'] == 'deviation1440')])
|
||||
print(f" - MA 신호: {ma_signals}")
|
||||
print(f" - Dev40 신호: {dev40_signals}")
|
||||
print(f" - Dev240 신호: {dev240_signals}")
|
||||
print(f" - Dev1440 신호: {dev1440_signals}")
|
||||
fig, (ax1, ax2) = plt.subplots(2, 1, sharex=True, figsize=(15, 8), height_ratios=[3, 1])
|
||||
fig.suptitle(f"{symbol} - 시뮬레이션 {interval_minutes}분봉", fontsize=14)
|
||||
|
||||
# ----------------- 마우스 휠 확대/축소 -----------------
|
||||
def on_scroll(event):
|
||||
# event.button: 'up' -> zoom in, 'down' -> zoom out
|
||||
if event.inaxes not in [ax1, ax2]:
|
||||
return
|
||||
ax = event.inaxes
|
||||
# x 축만 두 축을 동시에 조정
|
||||
cur_xlim = ax1.get_xlim()
|
||||
xdata = event.xdata
|
||||
if xdata is None:
|
||||
return
|
||||
scale_factor = 0.9 if event.button == 'up' else 1/0.9
|
||||
new_width = (cur_xlim[1] - cur_xlim[0]) * scale_factor
|
||||
relx = (cur_xlim[1] - xdata) / (cur_xlim[1] - cur_xlim[0])
|
||||
new_left = xdata - new_width * (1 - relx)
|
||||
new_right = xdata + new_width * relx
|
||||
# 데이터 영역 벗어나지 않도록 클램프
|
||||
xmin, xmax = matplotlib.dates.date2num(data.index[0]), matplotlib.dates.date2num(data.index[-1])
|
||||
if new_left < xmin:
|
||||
new_left = xmin
|
||||
if new_right > xmax:
|
||||
new_right = xmax
|
||||
ax1.set_xlim([new_left, new_right])
|
||||
ax2.set_xlim([new_left, new_right])
|
||||
# y축은 해당 축만 줌
|
||||
cur_ylim = ax.get_ylim()
|
||||
ydata = event.ydata
|
||||
if ydata is not None:
|
||||
new_height = (cur_ylim[1] - cur_ylim[0]) * scale_factor
|
||||
rely = (cur_ylim[1] - ydata) / (cur_ylim[1] - cur_ylim[0])
|
||||
ax.set_ylim([ydata - new_height * (1 - rely), ydata + new_height * rely])
|
||||
ax.figure.canvas.draw_idle()
|
||||
|
||||
fig.canvas.mpl_connect('scroll_event', on_scroll)
|
||||
|
||||
# 캔들스틱 차트 추가 (matplotlib 기본 기능 사용)
|
||||
import matplotlib.dates as mdates
|
||||
|
||||
# 캔들스틱 데이터 준비
|
||||
ohlc_data = []
|
||||
for i, (idx, row) in enumerate(data.iterrows()):
|
||||
ohlc_data.append([
|
||||
mdates.date2num(idx),
|
||||
row['Open'],
|
||||
row['High'],
|
||||
row['Low'],
|
||||
row['Close']
|
||||
])
|
||||
|
||||
# 캔들스틱 그리기 (matplotlib 기본 기능으로 구현)
|
||||
for ohlc in ohlc_data:
|
||||
date, open_price, high, low, close = ohlc
|
||||
|
||||
# 캔들 색상 결정
|
||||
color = 'red' if close >= open_price else 'blue'
|
||||
|
||||
# 캔들 몸통 그리기
|
||||
body_height = abs(close - open_price)
|
||||
body_bottom = min(open_price, close)
|
||||
rect = plt.Rectangle((date - 0.3, body_bottom), 0.6, body_height,
|
||||
facecolor=color, edgecolor='black', alpha=0.7)
|
||||
ax1.add_patch(rect)
|
||||
|
||||
# 캔들 심지 그리기
|
||||
ax1.plot([date, date], [low, high], color='black', linewidth=1)
|
||||
|
||||
# 메인 차트 (가격, 이동평균선, 볼린저 밴드)
|
||||
line_close = ax1.plot(data.index, data["Close"], label="종가", color="black", linewidth=1.5, alpha=0.8)[0]
|
||||
line_ma5 = ax1.plot(data.index, data["MA5"], label="MA5", color="red", linewidth=1)[0]
|
||||
line_ma20 = ax1.plot(data.index, data["MA20"], label="MA20", color="blue", linewidth=1)[0]
|
||||
line_ma40 = ax1.plot(data.index, data["MA40"], label="MA40", color="green", linewidth=1)[0]
|
||||
line_ma120 = ax1.plot(data.index, data["MA120"], label="MA120", color="purple", linewidth=1)[0]
|
||||
line_ma200 = ax1.plot(data.index, data["MA200"], label="MA200", color="brown", linewidth=1)[0]
|
||||
line_ma240 = ax1.plot(data.index, data["MA240"], label="MA240", color="darkred", linewidth=1)[0]
|
||||
line_ma720 = ax1.plot(data.index, data["MA720"], label="MA720", color="cyan", linewidth=1)[0]
|
||||
line_ma1440 = ax1.plot(data.index, data["MA1440"], label="MA1440", color="magenta", linewidth=1)[0]
|
||||
|
||||
# Bollinger Bands
|
||||
line_upper = ax1.plot(data.index, data["Upper"], label="볼린저 Upper", color="grey", linestyle="--", linewidth=1)[0]
|
||||
line_lower = ax1.plot(data.index, data["Lower"], label="볼린저 Lower", color="grey", linestyle="--", linewidth=1)[0]
|
||||
|
||||
ax1.fill_between(data.index, data["Lower"], data["Upper"], color="grey", alpha=0.1)
|
||||
|
||||
# 매수 포인트를 신호 유형별로 다르게 표시 (수직선 포함)
|
||||
# 이동평균선 기반 매수 포인트
|
||||
ma_buy_points = data[(data['buy_point'] == 1) & (data['buy_signal'] == 'movingaverage')]
|
||||
scatter_ma_buy_points = None
|
||||
if len(ma_buy_points) > 0:
|
||||
scatter_ma_buy_points = ax1.scatter(ma_buy_points.index, ma_buy_points['Close'], color='red', s=150, zorder=10, label='MA 매수 포인트', marker='o')
|
||||
for time in ma_buy_points.index:
|
||||
ax1.axvline(x=time, color='red', linestyle='-', alpha=0.5, linewidth=1)
|
||||
|
||||
# Deviation40 기반 매수 포인트
|
||||
dev40_buy_points = data[(data['buy_point'] == 1) & (data['buy_signal'] == 'deviation40')]
|
||||
scatter_dev40_buy_points = None
|
||||
if len(dev40_buy_points) > 0:
|
||||
scatter_dev40_buy_points = ax1.scatter(dev40_buy_points.index, dev40_buy_points['Close'],
|
||||
facecolors='none', edgecolors='red', linestyle='--',
|
||||
linewidth=2, s=200, zorder=10, label='Dev40 매수 포인트')
|
||||
for time in dev40_buy_points.index:
|
||||
ax1.axvline(x=time, color='red', linestyle='--', alpha=0.5, linewidth=1)
|
||||
|
||||
# Deviation240 기반 매수 포인트
|
||||
dev240_buy_points = data[(data['buy_point'] == 1) & (data['buy_signal'] == 'deviation240')]
|
||||
scatter_dev240_buy_points = None
|
||||
if len(dev240_buy_points) > 0:
|
||||
scatter_dev240_buy_points = ax1.scatter(dev240_buy_points.index, dev240_buy_points['Close'],
|
||||
facecolors='none', edgecolors='blue', linestyle='--',
|
||||
linewidth=2, s=200, zorder=10, label='Dev240 매수 포인트')
|
||||
for time in dev240_buy_points.index:
|
||||
ax1.axvline(x=time, color='blue', linestyle='--', alpha=0.5, linewidth=1)
|
||||
|
||||
# Deviation1440 기반 매수 포인트
|
||||
dev1440_buy_points = data[(data['buy_point'] == 1) & (data['buy_signal'] == 'deviation1440')]
|
||||
scatter_dev1440_buy_points = None
|
||||
if len(dev1440_buy_points) > 0:
|
||||
scatter_dev1440_buy_points = ax1.scatter(dev1440_buy_points.index, dev1440_buy_points['Close'],
|
||||
facecolors='none', edgecolors='purple', linestyle='--',
|
||||
linewidth=2, s=200, zorder=10, label='Dev1440 매수 포인트')
|
||||
for time in dev1440_buy_points.index:
|
||||
ax1.axvline(x=time, color='purple', linestyle='--', alpha=0.5, linewidth=1)
|
||||
|
||||
# 마우스 오버 기능 추가 (이동평균선 매수 포인트)
|
||||
if scatter_ma_buy_points is not None:
|
||||
cursor = mplcursors.cursor(scatter_ma_buy_points, hover=True)
|
||||
cursor.connect("add", lambda sel: sel.annotation.set_text(
|
||||
f'MA 매수신호\n날짜: {matplotlib.dates.num2date(sel.target[0]).replace(tzinfo=None).strftime("%Y-%m-%d %H:%M")}\n가격: {sel.target[1]:.2f}'
|
||||
))
|
||||
cursor.connect("remove", lambda sel: sel.annotation.set_visible(False))
|
||||
|
||||
# 마우스 오버 기능 추가 (Deviation40 매수 포인트)
|
||||
if scatter_dev40_buy_points is not None:
|
||||
cursor_dev40 = mplcursors.cursor(scatter_dev40_buy_points, hover=True)
|
||||
cursor_dev40.connect("add", lambda sel: sel.annotation.set_text(
|
||||
f'Dev40 매수신호\n날짜: {matplotlib.dates.num2date(sel.target[0]).replace(tzinfo=None).strftime("%Y-%m-%d %H:%M")}\n가격: {sel.target[1]:.2f}'
|
||||
))
|
||||
cursor_dev40.connect("remove", lambda sel: sel.annotation.set_visible(False))
|
||||
|
||||
# 마우스 오버 기능 추가 (Deviation240 매수 포인트)
|
||||
if scatter_dev240_buy_points is not None:
|
||||
cursor_dev240 = mplcursors.cursor(scatter_dev240_buy_points, hover=True)
|
||||
cursor_dev240.connect("add", lambda sel: sel.annotation.set_text(
|
||||
f'Dev240 매수신호\n날짜: {matplotlib.dates.num2date(sel.target[0]).replace(tzinfo=None).strftime("%Y-%m-%d %H:%M")}\n가격: {sel.target[1]:.2f}'
|
||||
))
|
||||
cursor_dev240.connect("remove", lambda sel: sel.annotation.set_visible(False))
|
||||
|
||||
# 마우스 오버 기능 추가 (Deviation1440 매수 포인트)
|
||||
if scatter_dev1440_buy_points is not None:
|
||||
cursor_dev1440 = mplcursors.cursor(scatter_dev1440_buy_points, hover=True)
|
||||
cursor_dev1440.connect("add", lambda sel: sel.annotation.set_text(
|
||||
f'Dev1440 매수신호\n날짜: {matplotlib.dates.num2date(sel.target[0]).replace(tzinfo=None).strftime("%Y-%m-%d %H:%M")}\n가격: {sel.target[1]:.2f}'
|
||||
))
|
||||
cursor_dev1440.connect("remove", lambda sel: sel.annotation.set_visible(False))
|
||||
|
||||
# 모든 봉에 마우스 오버 기능 추가
|
||||
cursor3 = mplcursors.cursor(line_close, hover=True)
|
||||
cursor3.connect("add", lambda sel: sel.annotation.set_text(
|
||||
f'종가\n날짜: {matplotlib.dates.num2date(sel.target[0]).replace(tzinfo=None).strftime("%Y-%m-%d %H:%M")}\n가격: {sel.target[1]:.2f}'
|
||||
))
|
||||
cursor3.connect("remove", lambda sel: sel.annotation.set_visible(False))
|
||||
|
||||
ax1.set_ylabel("가격 (KRW)")
|
||||
ax1.set_title(f"{symbol} 차트 - 캔들스틱 & 이동평균선", fontsize=14)
|
||||
ax1.grid(True, linestyle='--', alpha=0.3)
|
||||
|
||||
# 홈 버튼 추가 (초기화 기능)
|
||||
home_button = ax1.text(0.02, 0.98, '홈', transform=ax1.transAxes,
|
||||
bbox=dict(boxstyle="round,pad=0.3", facecolor='lightblue', alpha=0.8),
|
||||
fontsize=10, ha='left', va='top', picker=True)
|
||||
|
||||
# --- 범례 생성 및 인터랙티브 토글 ---
|
||||
legend = ax1.legend(loc='upper left', bbox_to_anchor=(0.02, 0.85), fontsize=10)
|
||||
|
||||
# 범례 클릭 시 해당 선 토글 기능
|
||||
lined = {}
|
||||
if hasattr(legend, "legend_handles"):
|
||||
legend_handles = legend.legend_handles
|
||||
elif hasattr(legend, "legendHandles"):
|
||||
legend_handles = legend.legendHandles
|
||||
else:
|
||||
legend_handles = legend.get_lines()
|
||||
plot_lines = [line_close, line_ma5, line_ma20, line_ma40, line_ma120,
|
||||
line_ma200, line_ma240, line_ma720, line_ma1440,
|
||||
line_upper, line_lower]
|
||||
if scatter_ma_buy_points is not None:
|
||||
plot_lines.append(scatter_ma_buy_points)
|
||||
if scatter_dev40_buy_points is not None:
|
||||
plot_lines.append(scatter_dev40_buy_points)
|
||||
if scatter_dev240_buy_points is not None:
|
||||
plot_lines.append(scatter_dev240_buy_points)
|
||||
if scatter_dev1440_buy_points is not None:
|
||||
plot_lines.append(scatter_dev1440_buy_points)
|
||||
|
||||
for leg_handle, orig in zip(legend_handles, plot_lines):
|
||||
leg_handle.set_picker(True)
|
||||
lined[leg_handle] = orig
|
||||
|
||||
def on_pick(event):
|
||||
leg_handle = event.artist
|
||||
if leg_handle == home_button:
|
||||
ax1.set_xlim(matplotlib.dates.date2num(data.index[0]), matplotlib.dates.date2num(data.index[-1]))
|
||||
ax1.set_ylim(data['Low'].min() * 0.99, data['High'].max() * 1.01)
|
||||
ax2.set_xlim(ax1.get_xlim())
|
||||
ax2.set_ylim(
|
||||
data[['Deviation5', 'Deviation20', 'Deviation40', 'Deviation120', 'Deviation200', 'Deviation240', 'Deviation720', 'Deviation1440']].min().min() * 0.95,
|
||||
data[['Deviation5', 'Deviation20', 'Deviation40', 'Deviation120', 'Deviation200', 'Deviation240', 'Deviation720', 'Deviation1440']].max().max() * 1.05,
|
||||
)
|
||||
fig.canvas.draw_idle()
|
||||
return
|
||||
orig = lined.get(leg_handle)
|
||||
if orig is None:
|
||||
return
|
||||
vis = not orig.get_visible()
|
||||
orig.set_visible(vis)
|
||||
leg_handle.set_alpha(1.0 if vis else 0.2)
|
||||
fig.canvas.draw_idle()
|
||||
|
||||
fig.canvas.mpl_connect('pick_event', on_pick)
|
||||
|
||||
# Deviation subplot (이격도 보조지표)
|
||||
line_dev5 = ax2.plot(data.index, data['Deviation5'], color='red', label='Dev5', linewidth=1)[0]
|
||||
line_dev20 = ax2.plot(data.index, data['Deviation20'], color='blue', label='Dev20', linewidth=1)[0]
|
||||
line_dev40 = ax2.plot(data.index, data['Deviation40'], color='green', label='Dev40', linewidth=2)[0]
|
||||
line_dev120 = ax2.plot(data.index, data['Deviation120'], color='purple', label='Dev120', linewidth=1)[0]
|
||||
line_dev200 = ax2.plot(data.index, data['Deviation200'], color='brown', label='Dev200', linewidth=1)[0]
|
||||
line_dev240 = ax2.plot(data.index, data['Deviation240'], color='darkred', label='Dev240', linewidth=2)[0]
|
||||
line_dev720 = ax2.plot(data.index, data['Deviation720'], color='cyan', label='Dev720', linewidth=1)[0]
|
||||
line_dev1440 = ax2.plot(data.index, data['Deviation1440'], color='magenta', label='Dev1440', linewidth=1)[0]
|
||||
|
||||
cursor_dev = mplcursors.cursor([line_dev5, line_dev20, line_dev40, line_dev120, line_dev200, line_dev240, line_dev720, line_dev1440], hover=True)
|
||||
cursor_dev.connect("add", lambda sel: sel.annotation.set_text(
|
||||
f"{sel.artist.get_label()}\n날짜: {matplotlib.dates.num2date(sel.target[0]).replace(tzinfo=None).strftime('%Y-%m-%d %H:%M')}\n값: {sel.target[1]:.2f}"
|
||||
))
|
||||
line_h90 = ax2.axhline(90, color='red', linestyle='--', linewidth=2, label='90', alpha=0.7)
|
||||
line_h95 = ax2.axhline(95, color='green', linestyle='--', linewidth=2, label='95', alpha=0.7)
|
||||
line_h100 = ax2.axhline(100, color='black', linestyle='-', linewidth=1, label='100', alpha=0.5)
|
||||
ax2.set_ylabel('이격도 (%)')
|
||||
ax2.set_title('이격도 보조지표', fontsize=12)
|
||||
legend2 = ax2.legend(loc='upper left', fontsize=9)
|
||||
|
||||
if legend2 is not None:
|
||||
if hasattr(legend2, "legend_handles"):
|
||||
legend2_handles = legend2.legend_handles
|
||||
elif hasattr(legend2, "legendHandles"):
|
||||
legend2_handles = legend2.legendHandles
|
||||
else:
|
||||
legend2_handles = legend2.get_lines()
|
||||
plot_lines2 = [line_dev5, line_dev20, line_dev40, line_dev120, line_dev200, line_dev240, line_dev720, line_dev1440, line_h90, line_h95]
|
||||
for leg_handle in legend2_handles:
|
||||
label = leg_handle.get_label()
|
||||
target_line = next((pl for pl in plot_lines2 if pl.get_label() == label), None)
|
||||
if target_line is not None:
|
||||
leg_handle.set_picker(True)
|
||||
lined[leg_handle] = target_line
|
||||
ax2.grid(True, linestyle='--', alpha=0.3)
|
||||
|
||||
plt.tight_layout()
|
||||
|
||||
print("그래프를 표시합니다...")
|
||||
print(f"매수 포인트 수: MA={len(ma_buy_points)}, Dev40={len(dev40_buy_points)}, Dev240={len(dev240_buy_points)}")
|
||||
|
||||
# -------- 확대/축소 및 이동 기능 --------
|
||||
press = {}
|
||||
|
||||
def on_scroll(event):
|
||||
ax = event.inaxes
|
||||
if ax is None:
|
||||
return
|
||||
x_left, x_right = ax.get_xlim()
|
||||
x_range = (x_right - x_left)
|
||||
if event.button == 'up': # zoom in
|
||||
scale = 0.8
|
||||
elif event.button == 'down': # zoom out
|
||||
scale = 1.25
|
||||
else:
|
||||
scale = 1.0
|
||||
new_range = x_range * scale
|
||||
center = event.xdata if event.xdata is not None else (x_left + x_right) / 2
|
||||
ax.set_xlim(center - new_range / 2, center + new_range / 2)
|
||||
for other_ax in fig.axes:
|
||||
if other_ax is not ax:
|
||||
other_ax.set_xlim(ax.get_xlim())
|
||||
fig.canvas.draw_idle()
|
||||
|
||||
def on_press(event):
|
||||
if event.button == 1 and event.inaxes is not None:
|
||||
press['xpress'] = event.xdata
|
||||
press['axes'] = event.inaxes
|
||||
|
||||
def on_motion(event):
|
||||
if 'xpress' not in press or press.get('axes') is None or event.inaxes is None:
|
||||
return
|
||||
dx = press['xpress'] - event.xdata
|
||||
for ax in fig.axes:
|
||||
x_left, x_right = ax.get_xlim()
|
||||
ax.set_xlim(x_left + dx, x_right + dx)
|
||||
fig.canvas.draw_idle()
|
||||
|
||||
def on_release(event):
|
||||
press.clear()
|
||||
|
||||
fig.canvas.mpl_connect('scroll_event', on_scroll)
|
||||
fig.canvas.mpl_connect('button_press_event', on_press)
|
||||
fig.canvas.mpl_connect('motion_notify_event', on_motion)
|
||||
fig.canvas.mpl_connect('button_release_event', on_release)
|
||||
|
||||
plt.show()
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
sim = Simulation()
|
||||
interval = 60
|
||||
days = 90
|
||||
target_coins = ['POL']
|
||||
show_graphs = True
|
||||
for symbol in target_coins:
|
||||
print(f"\n=== {symbol} 저점 기간 분석 시작 ===")
|
||||
try:
|
||||
bottom_data, alerts = sim.analyze_bottom_period(symbol, interval, days)
|
||||
print(f"\n=== {symbol} 전체 기간 시뮬레이션 ===")
|
||||
if show_graphs:
|
||||
sim.run_simulation(symbol, interval, days)
|
||||
else:
|
||||
data = sim.fetch_price_history(symbol, interval, days)
|
||||
data = sim.monitor.calculate_technical_indicators(data)
|
||||
data = sim.monitor.check_buy_point(symbol, data, simulation=True)
|
||||
total_buy_signals = len(data[data['buy_point'] == 1])
|
||||
ma_signals = len(data[(data['buy_point'] == 1) & (data['buy_signal'] == 'movingaverage')])
|
||||
dev40_signals = len(data[(data['buy_point'] == 1) & (data['buy_signal'] == 'deviation40')])
|
||||
dev240_signals = len(data[(data['buy_point'] == 1) & (data['buy_signal'] == 'deviation240')])
|
||||
dev1440_signals = len(data[(data['buy_point'] == 1) & (data['buy_signal'] == 'deviation1440')])
|
||||
print(f"총 매수 신호: {total_buy_signals}")
|
||||
print(f" - MA 신호: {ma_signals}")
|
||||
print(f" - Dev40 신호: {dev40_signals}")
|
||||
print(f" - Dev240 신호: {dev240_signals}")
|
||||
print(f" - Dev1440 신호: {dev1440_signals}")
|
||||
except Exception as e:
|
||||
print(f"Error analyzing {symbol}: {str(e)}")
|
||||
592
stock_monitor.py
592
stock_monitor.py
@@ -1,592 +0,0 @@
|
||||
import pandas as pd
|
||||
from HTS2 import HTS
|
||||
from dateutil.relativedelta import relativedelta
|
||||
from datetime import datetime, timedelta
|
||||
import sqlite3
|
||||
import telegram
|
||||
import time
|
||||
import requests
|
||||
import json
|
||||
import asyncio
|
||||
from multiprocessing import Pool
|
||||
import schedule
|
||||
from config import *
|
||||
import FinanceDataReader as fdr
|
||||
import numpy as np
|
||||
import os
|
||||
|
||||
hts = HTS()
|
||||
|
||||
# 매수 금지 시간을 관리하는 JSON 파일 경로
|
||||
COOLDOWN_FILE = 'coins_buy_time.json'
|
||||
|
||||
def load_buy_cooldown():
|
||||
"""매수 금지 시간을 JSON 파일에서 로드"""
|
||||
if os.path.exists(COOLDOWN_FILE):
|
||||
try:
|
||||
with open(COOLDOWN_FILE, 'r', encoding='utf-8') as f:
|
||||
data = json.load(f)
|
||||
# 문자열을 datetime 객체로 변환
|
||||
cooldown = {}
|
||||
for symbol, time_str in data.items():
|
||||
cooldown[symbol] = datetime.fromisoformat(time_str)
|
||||
return cooldown
|
||||
except Exception as e:
|
||||
print(f"Error loading cooldown data: {e}")
|
||||
return {}
|
||||
return {}
|
||||
|
||||
def save_buy_cooldown(cooldown):
|
||||
"""매수 금지 시간을 JSON 파일에 저장"""
|
||||
try:
|
||||
# datetime 객체를 문자열로 변환
|
||||
data = {}
|
||||
for symbol, dt in cooldown.items():
|
||||
data[symbol] = dt.isoformat()
|
||||
|
||||
with open(COOLDOWN_FILE, 'w', encoding='utf-8') as f:
|
||||
json.dump(data, f, ensure_ascii=False, indent=2)
|
||||
except Exception as e:
|
||||
print(f"Error saving cooldown data: {e}")
|
||||
|
||||
# 매수 금지 시간을 추적하는 전역 딕셔너리
|
||||
buy_cooldown = load_buy_cooldown()
|
||||
|
||||
def send_coin_msg(text):
|
||||
coin_client = telegram.Bot(token=COIN_TELEGRAM_BOT_TOKEN)
|
||||
asyncio.run(coin_client.send_message(chat_id=COIN_TELEGRAM_CHAT_ID, text=text))
|
||||
return
|
||||
|
||||
|
||||
def send_coin_telegram_message(message_list, header):
|
||||
pStr = header + "\n"
|
||||
for i, message in enumerate(message_list):
|
||||
pStr += message
|
||||
|
||||
if i + 1 % 20 == 0:
|
||||
pool = Pool(12)
|
||||
pool.map(send_coin_msg, [pStr])
|
||||
pStr = ''
|
||||
|
||||
if len(message_list) % 20 != 0:
|
||||
pool = Pool(12)
|
||||
pool.map(send_coin_msg, [pStr])
|
||||
|
||||
return
|
||||
|
||||
|
||||
def send_stock_msg(text):
|
||||
stock_client = telegram.Bot(token=STOCK_TELEGRAM_BOT_TOKEN)
|
||||
asyncio.run(stock_client.send_message(chat_id=STOCK_TELEGRAM_CHAT_ID, text=text))
|
||||
return
|
||||
|
||||
|
||||
def send_stock_telegram_message(message_list, header):
|
||||
pStr = header + "\n"
|
||||
for i, message in enumerate(message_list):
|
||||
pStr += message
|
||||
|
||||
if i + 1 % 20 == 0:
|
||||
pool = Pool(12)
|
||||
pool.map(send_stock_msg, [pStr])
|
||||
pStr = ''
|
||||
|
||||
if len(message_list) % 20 != 0:
|
||||
pool = Pool(12)
|
||||
pool.map(send_stock_msg, [pStr])
|
||||
|
||||
return
|
||||
|
||||
|
||||
def normalize_data(data):
|
||||
"""데이터 정규화 함수 - 모든 코인에 동일하게 적용"""
|
||||
# Min-Max 정규화를 위한 컬럼
|
||||
columns_to_normalize = ['Open', 'High', 'Low', 'Close', 'Volume']
|
||||
|
||||
normalized_data = data.copy()
|
||||
|
||||
# 각 컬럼별 정규화 (20일 롤링 윈도우 사용)
|
||||
for column in columns_to_normalize:
|
||||
min_val = data[column].rolling(window=20).min()
|
||||
max_val = data[column].rolling(window=20).max()
|
||||
# 0으로 나누기 방지
|
||||
denominator = max_val - min_val
|
||||
normalized_data[f'{column}_Norm'] = np.where(
|
||||
denominator != 0,
|
||||
(data[column] - min_val) / denominator,
|
||||
0.5 # 기본값 설정
|
||||
)
|
||||
|
||||
return normalized_data
|
||||
|
||||
def calculate_technical_indicators(data):
|
||||
"""기술적 지표 계산 - 모든 코인에 동일하게 적용"""
|
||||
# 데이터 정규화
|
||||
data = normalize_data(data)
|
||||
|
||||
# 이동평균선 계산
|
||||
data['MA5'] = data['Close'].rolling(window=5).mean()
|
||||
data['MA20'] = data['Close'].rolling(window=20).mean()
|
||||
data['MA40'] = data['Close'].rolling(window=40).mean()
|
||||
data['MA120'] = data['Close'].rolling(window=120).mean()
|
||||
data['MA200'] = data['Close'].rolling(window=200).mean()
|
||||
data['MA240'] = data['Close'].rolling(window=240).mean()
|
||||
data['MA720'] = data['Close'].rolling(window=720).mean()
|
||||
data['MA1440'] = data['Close'].rolling(window=1440).mean()
|
||||
|
||||
# --- 이격도(Deviation) 계산 ---
|
||||
data['Deviation5'] = (data['Close'] / data['MA5']) * 100
|
||||
data['Deviation20'] = (data['Close'] / data['MA20']) * 100
|
||||
data['Deviation40'] = (data['Close'] / data['MA40']) * 100
|
||||
data['Deviation120'] = (data['Close'] / data['MA120']) * 100
|
||||
data['Deviation200'] = (data['Close'] / data['MA200']) * 100
|
||||
data['Deviation240'] = (data['Close'] / data['MA240']) * 100
|
||||
data['Deviation720'] = (data['Close'] / data['MA720']) * 100
|
||||
data['Deviation1440'] = (data['Close'] / data['MA1440']) * 100
|
||||
|
||||
# 매수 타이밍을 이동평균선으로 결정
|
||||
# 골든크로스: 단기 이동평균선이 장기 이동평균선을 상향 돌파할 때 매수
|
||||
data['golden_cross'] = (data['MA5'] > data['MA20']) & (data['MA5'].shift(1) <= data['MA20'].shift(1))
|
||||
|
||||
# 볼린저 밴드 계산
|
||||
data['MA'] = data['Close'].rolling(window=20).mean()
|
||||
data['STD'] = data['Close'].rolling(window=20).std()
|
||||
data['Upper'] = data['MA'] + (2 * data['STD'])
|
||||
data['Lower'] = data['MA'] - (2 * data['STD'])
|
||||
|
||||
return data
|
||||
|
||||
|
||||
def buy_ticker(symbol, data):
|
||||
try:
|
||||
current_time = datetime.now()
|
||||
|
||||
if data['buy_signal'].iloc[-1] != 'fall_5p':
|
||||
# 5%이상 급락일 때는 10분마다 매수
|
||||
BUY_AMOUNT = 100000
|
||||
else:
|
||||
# 매수 금지 시간 확인 (20분)
|
||||
if symbol in buy_cooldown:
|
||||
time_diff = current_time - buy_cooldown[symbol]
|
||||
if time_diff.total_seconds() < 1200: # 20분 = 1200초
|
||||
print(f"{symbol}: 매수 금지 중 (남은 시간: {1200 - time_diff.total_seconds():.0f}초)")
|
||||
return False
|
||||
|
||||
BUY_AMOUNT = 5100
|
||||
|
||||
if data['buy_signal'].iloc[-1] == 'movingaverage':
|
||||
BUY_AMOUNT = 7000
|
||||
elif data['buy_signal'].iloc[-1] == 'deviation40':
|
||||
BUY_AMOUNT = 10000
|
||||
elif data['buy_signal'].iloc[-1] == 'deviation240':
|
||||
BUY_AMOUNT = 6000
|
||||
elif data['buy_signal'].iloc[-1] == 'deviation1440':
|
||||
if symbol in ['BONK', 'PEPE', 'TON']:
|
||||
BUY_AMOUNT = 30000
|
||||
else:
|
||||
BUY_AMOUNT = 50000
|
||||
|
||||
_ = hts.buyCoinMarket(symbol, BUY_AMOUNT)
|
||||
|
||||
# 매수 성공 시 금지 시간 설정 및 파일에 저장
|
||||
buy_cooldown[symbol] = current_time
|
||||
save_buy_cooldown(buy_cooldown)
|
||||
print(f"{KR_COINS[symbol]} ({symbol}): {data['Close'].iloc[-1]:.4f}: 매수 완료, 20분간 매수 금지 시작")
|
||||
|
||||
try:
|
||||
pool = Pool(12)
|
||||
pool.map(send_coin_msg, ["[KRW-COIN]" + "\n" + format_message('COIN', symbol, KR_COINS[symbol], data['Close'].iloc[-1], data['buy_signal'].iloc[-1])])
|
||||
except Exception as e:
|
||||
print(f"Error sending Telegram message: {str(e)}")
|
||||
|
||||
except Exception as e:
|
||||
print(f"Error buying {symbol}: {str(e)}")
|
||||
return False
|
||||
|
||||
return True
|
||||
|
||||
def check_buy_point(symbol, data, simulation=None):
|
||||
|
||||
# 매수 포인트 탐지 및 표시
|
||||
# 데이터 복사본 생성하여 SettingWithCopyWarning 방지
|
||||
data = data.copy()
|
||||
# 'buy_point' 열 초기화
|
||||
data['buy_signal'] = ''
|
||||
data['buy_point'] = 0
|
||||
|
||||
# FutureWarning 해결
|
||||
if data['buy_point'].iloc[-1] != 1:
|
||||
# 코드 계속
|
||||
for i in range(1, len(data)):
|
||||
# 이동평균선 기반 매수 조건
|
||||
if all(data[f'MA{n}'].iloc[i] < data['MA720'].iloc[i] for n in [5, 20, 40, 120, 200, 240]) and \
|
||||
all(data[f'MA{n}'].iloc[i] > data[f'MA{n}'].iloc[i - 1] for n in [5, 20, 40, 120, 200, 240]) and \
|
||||
data['MA720'].iloc[i] < data['MA1440'].iloc[i]:
|
||||
data.at[data.index[i], 'buy_signal'] = 'movingaverage'
|
||||
data.at[data.index[i], 'buy_point'] = 1
|
||||
if not simulation:
|
||||
if data['buy_point'][-3:].sum() > 0:
|
||||
data.at[data.index[-1], 'buy_signal'] = 'movingaverage'
|
||||
data.at[data.index[-1], 'buy_point'] = 1
|
||||
|
||||
# Deviation40(이격도 40) 기반 매수 조건: 90 이하에서 상승 전환
|
||||
if data['Deviation40'].iloc[i - 1] < data['Deviation40'].iloc[i] and data['Deviation40'].iloc[i - 1] <= 90:
|
||||
data.at[data.index[i], 'buy_signal'] = 'deviation40'
|
||||
data.at[data.index[i], 'buy_point'] = 1
|
||||
if not simulation:
|
||||
if data['buy_point'][-3:].sum() > 0:
|
||||
data.at[data.index[-1], 'buy_signal'] = 'deviation40'
|
||||
data.at[data.index[-1], 'buy_point'] = 1
|
||||
|
||||
if symbol not in ['BONK']:
|
||||
# BONK는 240 체크하지 않음
|
||||
|
||||
if symbol in ['TRX']:
|
||||
# Deviation240(이격도 240) 기반 매수 조건: 90 이하에서 상승 전환
|
||||
if data['Deviation240'].iloc[i - 1] < data['Deviation240'].iloc[i] and data['Deviation240'].iloc[i - 1] <= 98:
|
||||
data.at[data.index[i], 'buy_signal'] = 'deviation240'
|
||||
data.at[data.index[i], 'buy_point'] = 1
|
||||
if not simulation:
|
||||
if data['buy_point'][-3:].sum() > 0:
|
||||
data.at[data.index[-1], 'buy_signal'] = 'deviation240'
|
||||
data.at[data.index[-1], 'buy_point'] = 1
|
||||
else:
|
||||
# Deviation240(이격도 240) 기반 매수 조건: 90 이하에서 상승 전환
|
||||
if data['Deviation240'].iloc[i - 1] < data['Deviation240'].iloc[i] and data['Deviation240'].iloc[i - 1] <= 90:
|
||||
data.at[data.index[i], 'buy_signal'] = 'deviation240'
|
||||
data.at[data.index[i], 'buy_point'] = 1
|
||||
if not simulation:
|
||||
if data['buy_point'][-3:].sum() > 0:
|
||||
data.at[data.index[-1], 'buy_signal'] = 'deviation240'
|
||||
data.at[data.index[-1], 'buy_point'] = 1
|
||||
|
||||
# Deviation240(이격도 240) 기반 매수 조건: 90 이하에서 상승 전환
|
||||
if symbol in ['TON']:
|
||||
if data['Deviation1440'].iloc[i - 1] < data['Deviation1440'].iloc[i] and data['Deviation1440'].iloc[i - 1] <= 89:
|
||||
data.at[data.index[i], 'buy_signal'] = 'deviation1440'
|
||||
data.at[data.index[i], 'buy_point'] = 1
|
||||
if not simulation:
|
||||
if data['buy_point'][-3:].sum() > 0:
|
||||
data.at[data.index[-1], 'buy_signal'] = 'deviation1440'
|
||||
data.at[data.index[-1], 'buy_point'] = 1
|
||||
elif symbol in ['XRP']:
|
||||
if data['Deviation1440'].iloc[i - 1] < data['Deviation1440'].iloc[i] and data['Deviation1440'].iloc[i - 1] <= 90:
|
||||
data.at[data.index[i], 'buy_signal'] = 'deviation1440'
|
||||
data.at[data.index[i], 'buy_point'] = 1
|
||||
if not simulation:
|
||||
if data['buy_point'][-3:].sum() > 0:
|
||||
data.at[data.index[-1], 'buy_signal'] = 'deviation1440'
|
||||
data.at[data.index[-1], 'buy_point'] = 1
|
||||
elif symbol in ['BONK']:
|
||||
if data['Deviation1440'].iloc[i - 1] < data['Deviation1440'].iloc[i] and data['Deviation1440'].iloc[i - 1] <= 76:
|
||||
data.at[data.index[i], 'buy_signal'] = 'deviation1440'
|
||||
data.at[data.index[i], 'buy_point'] = 1
|
||||
if not simulation:
|
||||
if data['buy_point'][-3:].sum() > 0:
|
||||
data.at[data.index[-1], 'buy_signal'] = 'deviation1440'
|
||||
data.at[data.index[-1], 'buy_point'] = 1
|
||||
else:
|
||||
if data['Deviation1440'].iloc[i - 1] < data['Deviation1440'].iloc[i] and data['Deviation1440'].iloc[i - 1] <= 80:
|
||||
data.at[data.index[i], 'buy_signal'] = 'deviation1440'
|
||||
data.at[data.index[i], 'buy_point'] = 1
|
||||
if not simulation:
|
||||
if data['buy_point'][-3:].sum() > 0:
|
||||
data.at[data.index[-1], 'buy_signal'] = 'deviation1440'
|
||||
data.at[data.index[-1], 'buy_point'] = 1
|
||||
|
||||
# 하락 5% 조건: 현재가 또는 현재 봉의 저가가 지난 봉 고가/현재 봉 고가 대비 5% 이상 하락
|
||||
try:
|
||||
prev_low = data['Low'].iloc[i - 1]
|
||||
curr_close = data['Close'].iloc[i]
|
||||
|
||||
cond_close_drop = curr_close <= prev_low * 0.95
|
||||
|
||||
if cond_close_drop:
|
||||
data.at[data.index[i], 'buy_signal'] = 'fall_5p'
|
||||
data.at[data.index[i], 'buy_point'] = 1
|
||||
if not simulation:
|
||||
if data['buy_point'][-3:].sum() > 0:
|
||||
data.at[data.index[-1], 'buy_signal'] = 'fall_5p'
|
||||
data.at[data.index[-1], 'buy_point'] = 1
|
||||
except Exception:
|
||||
pass
|
||||
|
||||
return data
|
||||
|
||||
def format_message(market_type, symbol, symbol_name, close, buy_signal):
|
||||
message = f"매수 [{market_type}] {symbol_name} ({symbol}): {buy_signal} "
|
||||
message += f"현재가: {'$' if market_type == 'US' else '₩'}{close:.4f}, "
|
||||
return message
|
||||
|
||||
|
||||
def format_ma_message(info, market_type):
|
||||
"""MA 알림 메시지 생성"""
|
||||
prefix = '상승 ' if info.get('alert') else ''
|
||||
message = prefix + f"[{market_type}] {info['name']} ({info['symbol']}) "
|
||||
message += f"현재가: {'$' if market_type == 'US' else '₩'}{info['price']:.4f} \n"
|
||||
return message
|
||||
|
||||
|
||||
def get_coin_data(symbol, interval=60, to=None, retries=3):
|
||||
for attempt in range(retries):
|
||||
try:
|
||||
#url = "https://api.bithumb.com/v1/candles/minutes/{}?market=KRW-{}&count=3000".format(interval, symbol)
|
||||
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)
|
||||
|
||||
|
||||
#url = 'https://api.bithumb.com/v1/candles/minutes/60?market=KRW-ADA&count=200'
|
||||
#url = 'https://api.bithumb.com/v1/candles/minutes/minutes/60?market=KRW-ADA&count=200&to=2025-08-06 10:38:38'
|
||||
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.columns = ['datetime', 'open', 'close', 'high', 'low', 'volume']
|
||||
# data['datetime'] = pd.to_datetime(data_temp['candle_date_time_kst'])
|
||||
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(symbol, interval, bong_count=3000):
|
||||
# 코인 데이터 1500개 봉 가져오기
|
||||
to = datetime.now()
|
||||
data = None
|
||||
while data is None or len(data) < bong_count:
|
||||
if data is None:
|
||||
data = get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
else:
|
||||
p_count = len(data)
|
||||
df = get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
|
||||
data = pd.concat([data, df], ignore_index=True)
|
||||
if p_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
|
||||
# 코인 데이터 1500개 봉 가져오기
|
||||
|
||||
return data
|
||||
|
||||
def get_coin_saved_data(symbol, interval, data):
|
||||
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(symbol, interval):
|
||||
data = get_coin_data(symbol, interval)
|
||||
data_1 = get_coin_data(symbol, interval=1)
|
||||
data_1.at[data_1.index[-1], 'Volume'] = data_1['Volume'].iloc[-1] * 60
|
||||
|
||||
saved_data = get_coin_saved_data(symbol, interval, data)
|
||||
|
||||
data = pd.concat([data, saved_data, data_1.iloc[[-1]]], ignore_index=True)
|
||||
#data = pd.concat([data, saved_data], 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 get_kr_stock_data(symbol, retries=3):
|
||||
for attempt in range(retries):
|
||||
try:
|
||||
end = datetime.now()
|
||||
start = end - timedelta(days=300)
|
||||
|
||||
# FinanceDataReader를 사용하여 한국 주식 데이터 가져오기
|
||||
data = fdr.DataReader(symbol, start.strftime('%Y-%m-%d'), end.strftime('%Y-%m-%d'))
|
||||
|
||||
if not data.empty:
|
||||
# FinanceDataReader의 컬럼명을 yfinance 형식으로 변환
|
||||
data = data.rename(columns={
|
||||
'Open': 'Open',
|
||||
'High': 'High',
|
||||
'Low': 'Low',
|
||||
'Close': 'Close',
|
||||
'Volume': 'Volume'
|
||||
})
|
||||
return data
|
||||
|
||||
print(f"No data received for {symbol}, attempt {attempt + 1}")
|
||||
time.sleep(2)
|
||||
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 monitor_us_stocks():
|
||||
message_list = []
|
||||
print("US Stocks {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S')))
|
||||
|
||||
for symbol in US_STOCKS:
|
||||
data = get_kr_stock_data(symbol)
|
||||
if data is not None and not data.empty:
|
||||
try:
|
||||
data = calculate_technical_indicators(data)
|
||||
recent_data = check_buy_point(symbol, data) # Changed to check_buy_point
|
||||
if recent_data['buy_point'].iloc[-1] != 1:
|
||||
continue
|
||||
print(f" - {US_STOCKS[symbol]} ({symbol}): {recent_data['Close'].iloc[-1]:.2f}")
|
||||
message_list.append(format_message('US', symbol, US_STOCKS[symbol], recent_data['Close'].iloc[-1], recent_data['buy_signal'].iloc[-1]))
|
||||
except Exception as e:
|
||||
print(f"Error processing data for {symbol}: {str(e)}")
|
||||
time.sleep(0.5)
|
||||
|
||||
if len(message_list) > 0:
|
||||
try:
|
||||
send_stock_telegram_message(message_list, header="[US-STOCK]")
|
||||
except Exception as e:
|
||||
print(f"Error sending Telegram message: {str(e)}")
|
||||
|
||||
return
|
||||
|
||||
|
||||
def monitor_kr_stocks():
|
||||
message_list = []
|
||||
print("KR ETFs {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S')))
|
||||
|
||||
for symbol in KR_ETFS:
|
||||
try:
|
||||
# .KS 접미사 제거
|
||||
clean_symbol = symbol.replace('.KS', '')
|
||||
data = get_kr_stock_data(clean_symbol)
|
||||
|
||||
if data is not None and not data.empty:
|
||||
try:
|
||||
data = calculate_technical_indicators(data)
|
||||
recent_data = check_buy_point(symbol, data) # Changed to check_buy_point
|
||||
if recent_data['buy_point'].iloc[-1] != 1:
|
||||
continue
|
||||
print(f" - {KR_ETFS[symbol]} ({symbol}): {recent_data['Close'].iloc[-1]:.2f}")
|
||||
message_list.append(format_message('KR', symbol, KR_ETFS[symbol], recent_data['Close'].iloc[-1], recent_data['buy_signal'].iloc[-1]))
|
||||
|
||||
except Exception as e:
|
||||
print(f"Error processing data for {symbol}: {str(e)}")
|
||||
else:
|
||||
print(f"Data for {symbol} is empty or None.")
|
||||
|
||||
# 각 심볼 처리 후 1초 대기
|
||||
time.sleep(1)
|
||||
|
||||
except Exception as e:
|
||||
print(f"Unexpected error processing {symbol}: {str(e)}")
|
||||
continue
|
||||
|
||||
if len(message_list) > 0:
|
||||
try:
|
||||
send_stock_telegram_message(message_list, header="[KR-STOCK]")
|
||||
except Exception as e:
|
||||
print(f"Error sending Telegram message: {str(e)}")
|
||||
|
||||
return
|
||||
|
||||
|
||||
def monitor_coins():
|
||||
message_list = []
|
||||
print("KRW COINs {}".format(datetime.now().strftime('%Y-%m-%d %H:%M:%S')))
|
||||
|
||||
for symbol in KR_COINS:
|
||||
|
||||
# 1시간
|
||||
interval = 60
|
||||
data = get_coin_some_data(symbol, interval)
|
||||
|
||||
if data is not None and not data.empty:
|
||||
try:
|
||||
data = calculate_technical_indicators(data)
|
||||
recent_data = check_buy_point(symbol, data) # Changed to check_buy_point
|
||||
if recent_data['buy_point'].iloc[-1] != 1:
|
||||
continue
|
||||
|
||||
# buy
|
||||
buy_success = buy_ticker(symbol, recent_data)
|
||||
if not buy_success:
|
||||
continue # 매수 금지 중이면 다음 코인으로 넘어감
|
||||
|
||||
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
|
||||
|
||||
def run_schedule():
|
||||
|
||||
# 코인 모니터링 스케줄 (매시간 4분, 14분, 24분, 34분, 44분, 54분)
|
||||
for minute in [2, 12, 22, 32, 42, 52]:
|
||||
schedule.every().hour.at(f":{minute:02d}").do(monitor_coins)
|
||||
|
||||
# 미국 주식 모니터링 스케줄 (매일 저녁 5시 20분)
|
||||
schedule.every().day.at("16:30").do(monitor_us_stocks)
|
||||
schedule.every().day.at("23:30").do(monitor_us_stocks)
|
||||
schedule.every().day.at("05:10").do(monitor_us_stocks)
|
||||
|
||||
# 한국 ETF 모니터링 스케줄 (매일 오전 8시)
|
||||
schedule.every().day.at("18:20").do(monitor_kr_stocks)
|
||||
schedule.every().day.at("07:10").do(monitor_kr_stocks)
|
||||
|
||||
print("Scheduler started. Monitoring will run at specified times.")
|
||||
print(f"Loaded cooldown data for {len(buy_cooldown)} coins")
|
||||
|
||||
while True:
|
||||
schedule.run_pending()
|
||||
time.sleep(1)
|
||||
|
||||
if __name__ == "__main__":
|
||||
run_schedule()
|
||||
@@ -1,542 +0,0 @@
|
||||
from dateutil.relativedelta import relativedelta
|
||||
import pandas as pd
|
||||
import yfinance as yf
|
||||
import matplotlib.pyplot as plt
|
||||
import matplotlib.dates
|
||||
import mplcursors
|
||||
plt.rcParams['font.family'] ='AppleGothic'
|
||||
plt.rcParams['axes.unicode_minus'] =False
|
||||
|
||||
from config import *
|
||||
from stock_monitor import calculate_technical_indicators, get_coin_more_data, check_buy_point
|
||||
|
||||
def detect_turnaround_signal(symbol, data, interval=0, params=None):
|
||||
"""매수 신호 감지 함수 - stock_simulation.py에서 사용"""
|
||||
if len(data) < 7:
|
||||
return None
|
||||
|
||||
# 현재 매수 조건 확인
|
||||
current_data = data.iloc[-1]
|
||||
|
||||
# 매수 신호가 있는지 확인
|
||||
if current_data.get('buy_point', 0) == 1:
|
||||
return {
|
||||
'alert': True,
|
||||
'details': f"매수신호: {current_data.get('buy_signal', 'unknown')}"
|
||||
}
|
||||
|
||||
return {
|
||||
'alert': False,
|
||||
'details': "매수신호 없음"
|
||||
}
|
||||
|
||||
# 비트/알트코인 KRW 마켓 식별: 문자열 "-KRW" 포함 여부로 간단 구분
|
||||
|
||||
INTERVAL_MAP = {
|
||||
60: "60m", # 1시간 (yfinance)
|
||||
240: "4h", # 4시간 (yfinance)
|
||||
}
|
||||
|
||||
BITHUMB_MAX_COUNT = 3000 # API 최대 3000 캔들
|
||||
|
||||
def fetch_price_history(symbol: str, interval_minutes: int, days: int = 30) -> pd.DataFrame:
|
||||
|
||||
"""최근 `days`일 데이터(캔들)를 가져온다. 코인(-KRW)은 빗썸, 그 외 yfinance."""
|
||||
if symbol in KR_COINS:
|
||||
bong_count = 3000
|
||||
return get_coin_more_data(symbol, interval_minutes, bong_count=bong_count)
|
||||
|
||||
# -------- 주식/ETF/해외코인 (yfinance) --------
|
||||
if interval_minutes not in INTERVAL_MAP:
|
||||
raise ValueError("interval must be 60 or 240")
|
||||
|
||||
interval_str = INTERVAL_MAP[interval_minutes]
|
||||
|
||||
df = yf.download(
|
||||
tickers=symbol,
|
||||
period=f"{days}d",
|
||||
interval=interval_str,
|
||||
progress=False,
|
||||
)
|
||||
|
||||
if df.empty:
|
||||
raise RuntimeError("No data fetched. Check symbol or interval support.")
|
||||
|
||||
return df
|
||||
|
||||
|
||||
def analyze_bottom_period(symbol: str, interval_minutes: int, days: int = 90):
|
||||
"""저점 기간(6월 22일~7월 9일) 분석 - 최적화된 버전"""
|
||||
data = fetch_price_history(symbol, interval_minutes, days)
|
||||
data = calculate_technical_indicators(data)
|
||||
data = check_buy_point(symbol, data, simulation=True) # 한 번만 계산
|
||||
|
||||
print(f"데이터 기간: {data.index[0]} ~ {data.index[-1]}")
|
||||
print(f"총 데이터 수: {len(data)}")
|
||||
|
||||
# 저점 기간 필터링 (6월 22일~7월 9일)
|
||||
bottom_start = pd.Timestamp('2025-06-22')
|
||||
bottom_end = pd.Timestamp('2025-07-09')
|
||||
|
||||
bottom_data = data[(data.index >= bottom_start) & (data.index <= bottom_end)]
|
||||
|
||||
if len(bottom_data) == 0:
|
||||
print("저점 기간 데이터가 없습니다.")
|
||||
return None, []
|
||||
|
||||
print(f"\n저점 기간 데이터: {bottom_data.index[0]} ~ {bottom_data.index[-1]}")
|
||||
print(f"저점 기간 데이터 수: {len(bottom_data)}")
|
||||
|
||||
# 저점 기간의 기술적 지표 분석
|
||||
print("\n=== 저점 기간 기술적 지표 분석 ===")
|
||||
|
||||
# 1. 가격 분석
|
||||
min_price = bottom_data['Low'].min()
|
||||
max_price = bottom_data['High'].max()
|
||||
avg_price = bottom_data['Close'].mean()
|
||||
|
||||
print(f"최저가: {min_price:.4f}")
|
||||
print(f"최고가: {max_price:.4f}")
|
||||
print(f"평균가: {avg_price:.4f}")
|
||||
print(f"가격 변동폭: {((max_price - min_price) / min_price * 100):.2f}%")
|
||||
|
||||
# 3. 볼린저 밴드 분석
|
||||
bb_lower_min = bottom_data['Lower'].min()
|
||||
bb_upper_max = bottom_data['Upper'].max()
|
||||
|
||||
print(f"\n볼린저 밴드 분석:")
|
||||
print(f"하단 밴드 최저: {bb_lower_min:.4f}")
|
||||
print(f"상단 밴드 최고: {bb_upper_max:.4f}")
|
||||
|
||||
# 4. 거래량 분석
|
||||
volume_avg = bottom_data['Volume'].mean()
|
||||
volume_max = bottom_data['Volume'].max()
|
||||
|
||||
print(f"\n거래량 분석:")
|
||||
print(f"평균 거래량: {volume_avg:.0f}")
|
||||
print(f"최대 거래량: {volume_max:.0f}")
|
||||
|
||||
# 5. 실제 저점 찾기
|
||||
actual_bottom_idx = bottom_data['Low'].idxmin()
|
||||
actual_bottom_price = bottom_data.loc[actual_bottom_idx, 'Low']
|
||||
actual_bottom_date = actual_bottom_idx
|
||||
|
||||
print(f"\n실제 저점:")
|
||||
print(f"날짜: {actual_bottom_date}")
|
||||
print(f"가격: {actual_bottom_price:.4f}")
|
||||
print(f"볼린저 하단 대비: {((actual_bottom_price - bottom_data.loc[actual_bottom_idx, 'Lower']) / bottom_data.loc[actual_bottom_idx, 'Lower'] * 100):.2f}%")
|
||||
|
||||
# 6. 매수 신호 분석 - 최적화된 버전
|
||||
print(f"\n=== 매수 신호 분석 ===")
|
||||
|
||||
# 이미 계산된 매수 포인트에서 저점 기간만 필터링
|
||||
bottom_alerts = bottom_data[bottom_data['buy_point'] == 1]
|
||||
alerts = [(idx, row['Close']) for idx, row in bottom_alerts.iterrows()]
|
||||
|
||||
print(f"저점 기간 매수 신호 수: {len(alerts)}")
|
||||
|
||||
if alerts:
|
||||
print("매수 신호 발생 시점:")
|
||||
for date, price in alerts:
|
||||
print(f" {date}: {price:.4f}")
|
||||
|
||||
return bottom_data, alerts
|
||||
|
||||
def run_simulation(symbol: str, interval_minutes: int, days: int = 30):
|
||||
data = fetch_price_history(symbol, interval_minutes)
|
||||
data = calculate_technical_indicators(data)
|
||||
data = check_buy_point(symbol, data, simulation=True)
|
||||
|
||||
print(f"데이터 기간: {data.index[0]} ~ {data.index[-1]}")
|
||||
print(f"총 데이터 수: {len(data)}")
|
||||
|
||||
# check_buy_point에서 이미 계산된 매수 포인트를 사용
|
||||
alerts = []
|
||||
for i in range(len(data)):
|
||||
if data['buy_point'].iloc[i] == 1:
|
||||
alerts.append((data.index[i], data['Close'].iloc[i]))
|
||||
|
||||
print(f"\n총 매수 신호 수: {len(alerts)}")
|
||||
|
||||
# 매수 신호 유형별 통계 출력
|
||||
ma_signals = len(data[(data['buy_point'] == 1) & (data['buy_signal'] == 'movingaverage')])
|
||||
dev40_signals = len(data[(data['buy_point'] == 1) & (data['buy_signal'] == 'deviation40')])
|
||||
dev240_signals = len(data[(data['buy_point'] == 1) & (data['buy_signal'] == 'deviation240')])
|
||||
dev1440_signals = len(data[(data['buy_point'] == 1) & (data['buy_signal'] == 'deviation1440')])
|
||||
|
||||
print(f" - MA 신호: {ma_signals}")
|
||||
print(f" - Dev40 신호: {dev40_signals}")
|
||||
print(f" - Dev240 신호: {dev240_signals}")
|
||||
print(f" - Dev1440 신호: {dev1440_signals}")
|
||||
|
||||
# 서브플롯 생성 (가격 + Deviation)
|
||||
fig, (ax1, ax2) = plt.subplots(2, 1, sharex=True, figsize=(15, 8), height_ratios=[3, 1])
|
||||
fig.suptitle(f"{symbol} - 시뮬레이션 {interval_minutes}분봉", fontsize=14)
|
||||
|
||||
# ----------------- 마우스 휠 확대/축소 -----------------
|
||||
def on_scroll(event):
|
||||
# event.button: 'up' -> zoom in, 'down' -> zoom out
|
||||
if event.inaxes not in [ax1, ax2]:
|
||||
return
|
||||
ax = event.inaxes
|
||||
# x 축만 두 축을 동시에 조정
|
||||
cur_xlim = ax1.get_xlim()
|
||||
xdata = event.xdata
|
||||
if xdata is None:
|
||||
return
|
||||
scale_factor = 0.9 if event.button == 'up' else 1/0.9
|
||||
new_width = (cur_xlim[1] - cur_xlim[0]) * scale_factor
|
||||
relx = (cur_xlim[1] - xdata) / (cur_xlim[1] - cur_xlim[0])
|
||||
new_left = xdata - new_width * (1 - relx)
|
||||
new_right = xdata + new_width * relx
|
||||
# 데이터 영역 벗어나지 않도록 클램프
|
||||
xmin, xmax = matplotlib.dates.date2num(data.index[0]), matplotlib.dates.date2num(data.index[-1])
|
||||
if new_left < xmin:
|
||||
new_left = xmin
|
||||
if new_right > xmax:
|
||||
new_right = xmax
|
||||
ax1.set_xlim([new_left, new_right])
|
||||
ax2.set_xlim([new_left, new_right])
|
||||
# y축은 해당 축만 줌
|
||||
cur_ylim = ax.get_ylim()
|
||||
ydata = event.ydata
|
||||
if ydata is not None:
|
||||
new_height = (cur_ylim[1] - cur_ylim[0]) * scale_factor
|
||||
rely = (cur_ylim[1] - ydata) / (cur_ylim[1] - cur_ylim[0])
|
||||
ax.set_ylim([ydata - new_height * (1 - rely), ydata + new_height * rely])
|
||||
ax.figure.canvas.draw_idle()
|
||||
|
||||
fig.canvas.mpl_connect('scroll_event', on_scroll)
|
||||
|
||||
# 캔들스틱 차트 추가 (matplotlib 기본 기능 사용)
|
||||
import matplotlib.dates as mdates
|
||||
|
||||
# 캔들스틱 데이터 준비
|
||||
ohlc_data = []
|
||||
for i, (idx, row) in enumerate(data.iterrows()):
|
||||
ohlc_data.append([
|
||||
mdates.date2num(idx),
|
||||
row['Open'],
|
||||
row['High'],
|
||||
row['Low'],
|
||||
row['Close']
|
||||
])
|
||||
|
||||
# 캔들스틱 그리기 (matplotlib 기본 기능으로 구현)
|
||||
for ohlc in ohlc_data:
|
||||
date, open_price, high, low, close = ohlc
|
||||
|
||||
# 캔들 색상 결정
|
||||
color = 'red' if close >= open_price else 'blue'
|
||||
|
||||
# 캔들 몸통 그리기
|
||||
body_height = abs(close - open_price)
|
||||
body_bottom = min(open_price, close)
|
||||
rect = plt.Rectangle((date - 0.3, body_bottom), 0.6, body_height,
|
||||
facecolor=color, edgecolor='black', alpha=0.7)
|
||||
ax1.add_patch(rect)
|
||||
|
||||
# 캔들 심지 그리기
|
||||
ax1.plot([date, date], [low, high], color='black', linewidth=1)
|
||||
|
||||
# 메인 차트 (가격, 이동평균선, 볼린저 밴드)
|
||||
line_close = ax1.plot(data.index, data["Close"], label="종가", color="black", linewidth=1.5, alpha=0.8)[0]
|
||||
line_ma5 = ax1.plot(data.index, data["MA5"], label="MA5", color="red", linewidth=1)[0]
|
||||
line_ma20 = ax1.plot(data.index, data["MA20"], label="MA20", color="blue", linewidth=1)[0]
|
||||
line_ma40 = ax1.plot(data.index, data["MA40"], label="MA40", color="green", linewidth=1)[0]
|
||||
line_ma120 = ax1.plot(data.index, data["MA120"], label="MA120", color="purple", linewidth=1)[0]
|
||||
line_ma200 = ax1.plot(data.index, data["MA200"], label="MA200", color="brown", linewidth=1)[0]
|
||||
line_ma240 = ax1.plot(data.index, data["MA240"], label="MA240", color="darkred", linewidth=1)[0]
|
||||
line_ma720 = ax1.plot(data.index, data["MA720"], label="MA720", color="cyan", linewidth=1)[0]
|
||||
line_ma1440 = ax1.plot(data.index, data["MA1440"], label="MA1440", color="magenta", linewidth=1)[0]
|
||||
|
||||
# Bollinger Bands
|
||||
line_upper = ax1.plot(data.index, data["Upper"], label="볼린저 Upper", color="grey", linestyle="--", linewidth=1)[0]
|
||||
line_lower = ax1.plot(data.index, data["Lower"], label="볼린저 Lower", color="grey", linestyle="--", linewidth=1)[0]
|
||||
|
||||
ax1.fill_between(data.index, data["Lower"], data["Upper"], color="grey", alpha=0.1)
|
||||
|
||||
# 매수 포인트를 신호 유형별로 다르게 표시 (수직선 포함)
|
||||
# 이동평균선 기반 매수 포인트
|
||||
ma_buy_points = data[(data['buy_point'] == 1) & (data['buy_signal'] == 'movingaverage')]
|
||||
scatter_ma_buy_points = None
|
||||
if len(ma_buy_points) > 0:
|
||||
scatter_ma_buy_points = ax1.scatter(ma_buy_points.index, ma_buy_points['Close'], color='red', s=150, zorder=10, label='MA 매수 포인트', marker='o')
|
||||
for time in ma_buy_points.index:
|
||||
ax1.axvline(x=time, color='red', linestyle='-', alpha=0.5, linewidth=1)
|
||||
|
||||
# Deviation40 기반 매수 포인트
|
||||
dev40_buy_points = data[(data['buy_point'] == 1) & (data['buy_signal'] == 'deviation40')]
|
||||
scatter_dev40_buy_points = None
|
||||
if len(dev40_buy_points) > 0:
|
||||
scatter_dev40_buy_points = ax1.scatter(dev40_buy_points.index, dev40_buy_points['Close'],
|
||||
facecolors='none', edgecolors='red', linestyle='--',
|
||||
linewidth=2, s=200, zorder=10, label='Dev40 매수 포인트')
|
||||
for time in dev40_buy_points.index:
|
||||
ax1.axvline(x=time, color='red', linestyle='--', alpha=0.5, linewidth=1)
|
||||
|
||||
# Deviation240 기반 매수 포인트
|
||||
dev240_buy_points = data[(data['buy_point'] == 1) & (data['buy_signal'] == 'deviation240')]
|
||||
scatter_dev240_buy_points = None
|
||||
if len(dev240_buy_points) > 0:
|
||||
scatter_dev240_buy_points = ax1.scatter(dev240_buy_points.index, dev240_buy_points['Close'],
|
||||
facecolors='none', edgecolors='blue', linestyle='--',
|
||||
linewidth=2, s=200, zorder=10, label='Dev240 매수 포인트')
|
||||
for time in dev240_buy_points.index:
|
||||
ax1.axvline(x=time, color='blue', linestyle='--', alpha=0.5, linewidth=1)
|
||||
|
||||
# Deviation1440 기반 매수 포인트
|
||||
dev1440_buy_points = data[(data['buy_point'] == 1) & (data['buy_signal'] == 'deviation1440')]
|
||||
scatter_dev1440_buy_points = None
|
||||
if len(dev1440_buy_points) > 0:
|
||||
scatter_dev1440_buy_points = ax1.scatter(dev1440_buy_points.index, dev1440_buy_points['Close'],
|
||||
facecolors='none', edgecolors='purple', linestyle='--',
|
||||
linewidth=2, s=200, zorder=10, label='Dev1440 매수 포인트')
|
||||
for time in dev1440_buy_points.index:
|
||||
ax1.axvline(x=time, color='purple', linestyle='--', alpha=0.5, linewidth=1)
|
||||
|
||||
|
||||
|
||||
# 마우스 오버 기능 추가 (이동평균선 매수 포인트)
|
||||
if scatter_ma_buy_points is not None:
|
||||
cursor = mplcursors.cursor(scatter_ma_buy_points, hover=True)
|
||||
cursor.connect("add", lambda sel: sel.annotation.set_text(
|
||||
f'MA 매수신호\n날짜: {matplotlib.dates.num2date(sel.target[0]).replace(tzinfo=None).strftime("%Y-%m-%d %H:%M")}\n가격: {sel.target[1]:.2f}'
|
||||
))
|
||||
cursor.connect("remove", lambda sel: sel.annotation.set_visible(False))
|
||||
|
||||
# 마우스 오버 기능 추가 (Deviation40 매수 포인트)
|
||||
if scatter_dev40_buy_points is not None:
|
||||
cursor_dev40 = mplcursors.cursor(scatter_dev40_buy_points, hover=True)
|
||||
cursor_dev40.connect("add", lambda sel: sel.annotation.set_text(
|
||||
f'Dev40 매수신호\n날짜: {matplotlib.dates.num2date(sel.target[0]).replace(tzinfo=None).strftime("%Y-%m-%d %H:%M")}\n가격: {sel.target[1]:.2f}'
|
||||
))
|
||||
cursor_dev40.connect("remove", lambda sel: sel.annotation.set_visible(False))
|
||||
|
||||
# 마우스 오버 기능 추가 (Deviation240 매수 포인트)
|
||||
if scatter_dev240_buy_points is not None:
|
||||
cursor_dev240 = mplcursors.cursor(scatter_dev240_buy_points, hover=True)
|
||||
cursor_dev240.connect("add", lambda sel: sel.annotation.set_text(
|
||||
f'Dev240 매수신호\n날짜: {matplotlib.dates.num2date(sel.target[0]).replace(tzinfo=None).strftime("%Y-%m-%d %H:%M")}\n가격: {sel.target[1]:.2f}'
|
||||
))
|
||||
cursor_dev240.connect("remove", lambda sel: sel.annotation.set_visible(False))
|
||||
|
||||
# 마우스 오버 기능 추가 (Deviation1440 매수 포인트)
|
||||
if scatter_dev1440_buy_points is not None:
|
||||
cursor_dev1440 = mplcursors.cursor(scatter_dev1440_buy_points, hover=True)
|
||||
cursor_dev1440.connect("add", lambda sel: sel.annotation.set_text(
|
||||
f'Dev1440 매수신호\n날짜: {matplotlib.dates.num2date(sel.target[0]).replace(tzinfo=None).strftime("%Y-%m-%d %H:%M")}\n가격: {sel.target[1]:.2f}'
|
||||
))
|
||||
cursor_dev1440.connect("remove", lambda sel: sel.annotation.set_visible(False))
|
||||
|
||||
|
||||
|
||||
# 모든 봉에 마우스 오버 기능 추가
|
||||
cursor3 = mplcursors.cursor(line_close, hover=True)
|
||||
cursor3.connect("add", lambda sel: sel.annotation.set_text(
|
||||
f'종가\n날짜: {matplotlib.dates.num2date(sel.target[0]).replace(tzinfo=None).strftime("%Y-%m-%d %H:%M")}\n가격: {sel.target[1]:.2f}'
|
||||
))
|
||||
cursor3.connect("remove", lambda sel: sel.annotation.set_visible(False))
|
||||
|
||||
ax1.set_ylabel("가격 (KRW)")
|
||||
ax1.set_title(f"{symbol} 차트 - 캔들스틱 & 이동평균선", fontsize=14)
|
||||
ax1.grid(True, linestyle='--', alpha=0.3)
|
||||
|
||||
# 홈 버튼 추가 (초기화 기능)
|
||||
home_button = ax1.text(0.02, 0.98, '홈', transform=ax1.transAxes,
|
||||
bbox=dict(boxstyle="round,pad=0.3", facecolor='lightblue', alpha=0.8),
|
||||
fontsize=10, ha='left', va='top', picker=True)
|
||||
|
||||
# --- 범례 생성 및 인터랙티브 토글 ---
|
||||
legend = ax1.legend(loc='upper left', bbox_to_anchor=(0.02, 0.85), fontsize=10)
|
||||
|
||||
# 범례 클릭 시 해당 선 토글 기능
|
||||
lined = {}
|
||||
# legend 핸들과 실제 plot 선을 매핑 (생성 순서가 동일하다고 가정)
|
||||
# Matplotlib 버전에 따라 legend 객체의 핸들 보유 프로퍼티가 다를 수 있음
|
||||
if hasattr(legend, "legend_handles"):
|
||||
legend_handles = legend.legend_handles
|
||||
elif hasattr(legend, "legendHandles"):
|
||||
legend_handles = legend.legendHandles
|
||||
else:
|
||||
# 마지막 방어(일반적으로 선만 리턴)
|
||||
legend_handles = legend.get_lines()
|
||||
plot_lines = [line_close, line_ma5, line_ma20, line_ma40, line_ma120,
|
||||
line_ma200, line_ma240, line_ma720, line_ma1440,
|
||||
line_upper, line_lower]
|
||||
|
||||
# None이 아닌 scatter plot만 추가
|
||||
if scatter_ma_buy_points is not None:
|
||||
plot_lines.append(scatter_ma_buy_points)
|
||||
if scatter_dev40_buy_points is not None:
|
||||
plot_lines.append(scatter_dev40_buy_points)
|
||||
if scatter_dev240_buy_points is not None:
|
||||
plot_lines.append(scatter_dev240_buy_points)
|
||||
if scatter_dev1440_buy_points is not None:
|
||||
plot_lines.append(scatter_dev1440_buy_points)
|
||||
|
||||
# zip 길이가 짧은 쪽에 맞춰 매핑
|
||||
for leg_handle, orig in zip(legend_handles, plot_lines):
|
||||
leg_handle.set_picker(True) # 클릭 이벤트 활성화
|
||||
lined[leg_handle] = orig
|
||||
|
||||
def on_pick(event):
|
||||
leg_handle = event.artist
|
||||
|
||||
# 홈 버튼 클릭 처리
|
||||
if leg_handle == home_button:
|
||||
# 그래프 초기화
|
||||
ax1.set_xlim(matplotlib.dates.date2num(data.index[0]), matplotlib.dates.date2num(data.index[-1]))
|
||||
ax1.set_ylim(data['Low'].min() * 0.99, data['High'].max() * 1.01)
|
||||
ax2.set_xlim(ax1.get_xlim())
|
||||
ax2.set_ylim(data[['Deviation5', 'Deviation20', 'Deviation40', 'Deviation120', 'Deviation200', 'Deviation240', 'Deviation720', 'Deviation1440']].min().min() * 0.95,
|
||||
data[['Deviation5', 'Deviation20', 'Deviation40', 'Deviation120', 'Deviation200', 'Deviation240', 'Deviation720', 'Deviation1440']].max().max() * 1.05)
|
||||
fig.canvas.draw_idle()
|
||||
return
|
||||
|
||||
# 기존 범례 클릭 처리
|
||||
orig = lined.get(leg_handle)
|
||||
if orig is None:
|
||||
return
|
||||
vis = not orig.get_visible()
|
||||
orig.set_visible(vis)
|
||||
# 범례 아이콘 투명도 조정
|
||||
leg_handle.set_alpha(1.0 if vis else 0.2)
|
||||
fig.canvas.draw_idle()
|
||||
|
||||
fig.canvas.mpl_connect('pick_event', on_pick)
|
||||
|
||||
# Deviation subplot (이격도 보조지표)
|
||||
line_dev5 = ax2.plot(data.index, data['Deviation5'], color='red', label='Dev5', linewidth=1)[0]
|
||||
line_dev20 = ax2.plot(data.index, data['Deviation20'], color='blue', label='Dev20', linewidth=1)[0]
|
||||
line_dev40 = ax2.plot(data.index, data['Deviation40'], color='green', label='Dev40', linewidth=2)[0]
|
||||
line_dev120 = ax2.plot(data.index, data['Deviation120'], color='purple', label='Dev120', linewidth=1)[0]
|
||||
line_dev200 = ax2.plot(data.index, data['Deviation200'], color='brown', label='Dev200', linewidth=1)[0]
|
||||
line_dev240 = ax2.plot(data.index, data['Deviation240'], color='darkred', label='Dev240', linewidth=2)[0]
|
||||
line_dev720 = ax2.plot(data.index, data['Deviation720'], color='cyan', label='Dev720', linewidth=1)[0]
|
||||
line_dev1440 = ax2.plot(data.index, data['Deviation1440'], color='magenta', label='Dev1440', linewidth=1)[0]
|
||||
|
||||
cursor_dev = mplcursors.cursor([line_dev5, line_dev20, line_dev40, line_dev120, line_dev200, line_dev240, line_dev720, line_dev1440], hover=True)
|
||||
cursor_dev.connect("add", lambda sel: sel.annotation.set_text(
|
||||
f"{sel.artist.get_label()}\n날짜: {matplotlib.dates.num2date(sel.target[0]).replace(tzinfo=None).strftime('%Y-%m-%d %H:%M')}\n값: {sel.target[1]:.2f}"
|
||||
))
|
||||
# 이격도 기준선 추가
|
||||
line_h90 = ax2.axhline(90, color='red', linestyle='--', linewidth=2, label='90', alpha=0.7)
|
||||
line_h95 = ax2.axhline(95, color='green', linestyle='--', linewidth=2, label='95', alpha=0.7)
|
||||
line_h100 = ax2.axhline(100, color='black', linestyle='-', linewidth=1, label='100', alpha=0.5)
|
||||
ax2.set_ylabel('이격도 (%)')
|
||||
ax2.set_title('이격도 보조지표', fontsize=12)
|
||||
legend2 = ax2.legend(loc='upper left', fontsize=9)
|
||||
|
||||
# Deviation subplot 범례 클릭 토글 기능
|
||||
if legend2 is not None:
|
||||
if hasattr(legend2, "legend_handles"):
|
||||
legend2_handles = legend2.legend_handles
|
||||
elif hasattr(legend2, "legendHandles"):
|
||||
legend2_handles = legend2.legendHandles
|
||||
else:
|
||||
legend2_handles = legend2.get_lines()
|
||||
plot_lines2 = [line_dev5, line_dev20, line_dev40, line_dev120, line_dev200, line_dev240, line_dev720, line_dev1440, line_h90, line_h95]
|
||||
# 레이블 기준으로 안정적 매핑
|
||||
for leg_handle in legend2_handles:
|
||||
label = leg_handle.get_label()
|
||||
target_line = next((pl for pl in plot_lines2 if pl.get_label() == label), None)
|
||||
if target_line is not None:
|
||||
leg_handle.set_picker(True)
|
||||
lined[leg_handle] = target_line
|
||||
ax2.grid(True, linestyle='--', alpha=0.3)
|
||||
|
||||
plt.tight_layout()
|
||||
|
||||
print("그래프를 표시합니다...")
|
||||
print(f"매수 포인트 수: MA={len(ma_buy_points)}, Dev40={len(dev40_buy_points)}, Dev240={len(dev240_buy_points)}")
|
||||
|
||||
# -------- 확대/축소 및 이동 기능 --------
|
||||
press = {}
|
||||
|
||||
def on_scroll(event):
|
||||
ax = event.inaxes
|
||||
if ax is None:
|
||||
return
|
||||
x_left, x_right = ax.get_xlim()
|
||||
x_range = (x_right - x_left)
|
||||
if event.button == 'up': # zoom in
|
||||
scale = 0.8
|
||||
elif event.button == 'down': # zoom out
|
||||
scale = 1.25
|
||||
else:
|
||||
scale = 1.0
|
||||
new_range = x_range * scale
|
||||
center = event.xdata if event.xdata is not None else (x_left + x_right) / 2
|
||||
ax.set_xlim(center - new_range / 2, center + new_range / 2)
|
||||
# 다른 축들도 동일 적용 (shared x)
|
||||
for other_ax in fig.axes:
|
||||
if other_ax is not ax:
|
||||
other_ax.set_xlim(ax.get_xlim())
|
||||
fig.canvas.draw_idle()
|
||||
|
||||
def on_press(event):
|
||||
if event.button == 1 and event.inaxes is not None:
|
||||
press['xpress'] = event.xdata
|
||||
press['axes'] = event.inaxes
|
||||
|
||||
def on_motion(event):
|
||||
if 'xpress' not in press or press.get('axes') is None or event.inaxes is None:
|
||||
return
|
||||
dx = press['xpress'] - event.xdata
|
||||
for ax in fig.axes:
|
||||
x_left, x_right = ax.get_xlim()
|
||||
ax.set_xlim(x_left + dx, x_right + dx)
|
||||
fig.canvas.draw_idle()
|
||||
|
||||
def on_release(event):
|
||||
press.clear()
|
||||
|
||||
fig.canvas.mpl_connect('scroll_event', on_scroll)
|
||||
fig.canvas.mpl_connect('button_press_event', on_press)
|
||||
fig.canvas.mpl_connect('motion_notify_event', on_motion)
|
||||
fig.canvas.mpl_connect('button_release_event', on_release)
|
||||
|
||||
plt.show()
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
interval = 60
|
||||
days = 90 # 분석 기간을 90일로 늘림 (6월~8월 데이터 포함)
|
||||
#target_coins = ['ADA','APE','ARB','BONK','HBAR','LINK','ONDO','PEPE','POL','SEI','SHIB','STORJ','SUI','TON','TRX','WLD','XLM','XRP']
|
||||
target_coins = ['POL']
|
||||
|
||||
# 그래프 표시 여부 설정 (성능 향상을 위해 기본값은 False)
|
||||
show_graphs = True # True로 설정하면 각 코인마다 그래프 표시
|
||||
|
||||
for symbol in target_coins:
|
||||
print(f"\n=== {symbol} 저점 기간 분석 시작 ===")
|
||||
try:
|
||||
# 저점 기간 분석
|
||||
bottom_data, alerts = analyze_bottom_period(symbol, interval, days)
|
||||
|
||||
# 전체 기간 시뮬레이션 (그래프 표시 옵션 추가)
|
||||
print(f"\n=== {symbol} 전체 기간 시뮬레이션 ===")
|
||||
if show_graphs:
|
||||
run_simulation(symbol, interval, days)
|
||||
else:
|
||||
# 그래프 없이 빠른 분석만 수행
|
||||
data = fetch_price_history(symbol, interval, days)
|
||||
data = calculate_technical_indicators(data)
|
||||
data = check_buy_point(symbol, data, simulation=True)
|
||||
|
||||
# 매수 신호 통계만 출력
|
||||
total_buy_signals = len(data[data['buy_point'] == 1])
|
||||
ma_signals = len(data[(data['buy_point'] == 1) & (data['buy_signal'] == 'movingaverage')])
|
||||
dev40_signals = len(data[(data['buy_point'] == 1) & (data['buy_signal'] == 'deviation40')])
|
||||
dev240_signals = len(data[(data['buy_point'] == 1) & (data['buy_signal'] == 'deviation240')])
|
||||
dev1440_signals = len(data[(data['buy_point'] == 1) & (data['buy_signal'] == 'deviation1440')])
|
||||
|
||||
print(f"총 매수 신호: {total_buy_signals}")
|
||||
print(f" - MA 신호: {ma_signals}")
|
||||
print(f" - Dev40 신호: {dev40_signals}")
|
||||
print(f" - Dev240 신호: {dev240_signals}")
|
||||
print(f" - Dev1440 신호: {dev1440_signals}")
|
||||
|
||||
except Exception as e:
|
||||
print(f"Error analyzing {symbol}: {str(e)}")
|
||||
Reference in New Issue
Block a user