WLD 전용 BB MTF 전략 및 HTML 시뮬 최적화

- strategy.py, candle_features.py, rule_discovery.py로 다봉 BB·캔들 규칙 탐색
- simulation_1h.py: discover 명령, 기본 BB vs 탐색 규칙 자동 선택, Plotly Y축 줌
- mtf_bb.py, downloader/monitor 정리, 다코인 파일 제거

Co-authored-by: Cursor <cursoragent@cursor.com>
This commit is contained in:
2026-05-27 19:14:44 +09:00
parent 1c12a6c94a
commit 7d53090034
42 changed files with 2941 additions and 1650 deletions

View File

@@ -1,34 +1,40 @@
import pandas as pd
from HTS2 import HTS
from dateutil.relativedelta import relativedelta
from datetime import datetime, timedelta
from datetime import datetime
import sqlite3
import telegram
import time
try:
import telegram
except ImportError:
telegram = None # type: ignore
import requests
import json
import asyncio
from multiprocessing import Pool
import FinanceDataReader as fdr
import numpy as np
import os
from config import *
from HTS2 import HTS
import strategy
class Monitor(HTS):
"""자산(코인/주식/ETF) 모니터링 및 매 실행 클래스"""
"""WLD 코인 모니터링 및 매 실행."""
last_signal = None
cooldown_file = None
def __init__(self, cooldown_file='coins_buy_time.json') -> None:
self.hts = HTS()
HTS.__init__(self)
# 최근 매수 신호 저장용(파일은 [신규] 포맷으로 저장)
self.last_signal: dict[str, str] = {}
if cooldown_file is not None:
self.cooldown_file = cooldown_file
self.buy_cooldown = self._load_buy_cooldown()
else:
self.cooldown_file = None
self.buy_cooldown = {}
# ------------- Persistence -------------
def _load_buy_cooldown(self) -> dict:
@@ -106,13 +112,12 @@ class Monitor(HTS):
# ------------- Telegram -------------
def _send_coin_msg(self, text: str) -> None:
if telegram is None:
print(f"[telegram skip] {text}")
return
coin_client = telegram.Bot(token=COIN_TELEGRAM_BOT_TOKEN)
asyncio.run(coin_client.send_message(chat_id=COIN_TELEGRAM_CHAT_ID, text=text))
def _send_stock_msg(self, text: str) -> None:
stock_client = telegram.Bot(token=STOCK_TELEGRAM_BOT_TOKEN)
asyncio.run(stock_client.send_message(chat_id=STOCK_TELEGRAM_CHAT_ID, text=text))
def sendMsg(self, msg):
try:
pool = Pool(12)
@@ -133,18 +138,6 @@ class Monitor(HTS):
pool = Pool(12)
pool.map(self._send_coin_msg, [payload])
def send_stock_telegram_message(self, message_list: list[str], header: str) -> None:
payload = header + "\n"
for i, message in enumerate(message_list):
payload += message + "\n"
if i + 1 % 20 == 0:
pool = Pool(12)
pool.map(self._send_stock_msg, [payload])
payload = ''
if len(message_list) % 20 != 0:
pool = Pool(12)
pool.map(self._send_stock_msg, [payload])
# ------------- Indicators -------------
def normalize_data(self, data: pd.DataFrame) -> pd.DataFrame:
columns_to_normalize = ['Open', 'High', 'Low', 'Close', 'Volume']
@@ -224,236 +217,169 @@ class Monitor(HTS):
return data
# ------------- Strategy -------------
def buy_sell_ticker_1h(self, symbol: str, data: pd.DataFrame, balances=None, is_inverse: bool = False) -> bool:
# ------------- Strategy (strategy.py에 구현) -------------
def annotate_signals(self, symbol: str, data: pd.DataFrame, simulation: bool | None = None) -> pd.DataFrame:
"""strategy.annotate_signals에 위임."""
return strategy.annotate_signals(
symbol, data, simulation=simulation, config=strategy.ACTIVE_CONFIG
)
def _is_in_cooldown(self, symbol: str, side: str) -> bool:
"""매수/매도 쿨다운 여부."""
if self.cooldown_file is None:
return False
last_dt = self.buy_cooldown.get(symbol, {}).get(side, {}).get("datetime")
if not last_dt:
return False
limit = BUY_COOLDOWN_SEC if side == "buy" else SELL_COOLDOWN_SEC
elapsed = (datetime.now() - last_dt).total_seconds()
if elapsed < limit:
print(f"{symbol}: {side} 쿨다운 중 (남은 시간: {limit - elapsed:.0f}초)")
return True
return False
def _record_trade(self, symbol: str, side: str, signal: str) -> None:
"""매매 기록 저장."""
if self.cooldown_file is None:
return
current_time = datetime.now()
self.last_signal[symbol] = signal
self.buy_cooldown.setdefault(symbol, {})[side] = {
"datetime": current_time,
"signal": signal,
}
self._save_buy_cooldown()
def execute_trade_signal(
self,
symbol: str,
trade: strategy.TradeSignal,
balances: dict | None = None,
) -> bool:
"""TradeSignal 1건에 대해 현물 매수 또는 매도를 실행합니다."""
try:
# 신호 생성 및 최신 포인트 확인
data = self.annotate_signals(symbol, data)
if data['point'].iloc[-1] != 1:
return False
coin_name = KR_COINS.get(symbol, symbol)
signal_name = trade.signal
close = trade.close
if is_inverse:
# BUY_MINUTE_LIMIT 이내라면 매수하지 않음
current_time = datetime.now()
last_buy_dt = self.buy_cooldown.get(symbol, {}).get('sell', {}).get('datetime')
if last_buy_dt:
time_diff = current_time - last_buy_dt
if time_diff.total_seconds() < BUY_MINUTE_LIMIT:
print(f"{symbol}: 매수 금지 중 (남은 시간: {BUY_MINUTE_LIMIT - time_diff.total_seconds():.0f}초)")
return False
# 인버스 데이터: 매수 신호를 매도로 처리 (fall_6p, deviation40 만 허용)
# 허용된 인버스 매도 신호만 처리
last_signal = str(data['signal'].iloc[-1]) if 'signal' in data.columns else ''
if last_signal not in ['fall_6p', 'deviation40']:
if trade.action == "sell":
if self._is_in_cooldown(symbol, "sell"):
return False
available_balance = 0
try:
if balances and symbol in balances:
available_balance = float(balances[symbol].get('balance', 0))
except Exception:
available_balance = 0
if available_balance <= 0:
available = 0.0
if balances and symbol in balances:
available = float(balances[symbol].get("balance", 0))
if available <= 0:
print(f"{symbol}: 매도 신호({signal_name}) — 보유 없음, 스킵")
return False
sell_amount = available_balance * 0.7
_ = self.hts.sellCoinMarket(symbol, 0, sell_amount)
if self.cooldown_file is not None:
try:
self.last_signal[symbol] = str(data['signal'].iloc[-1])
except Exception:
self.last_signal[symbol] = ''
self.buy_cooldown.setdefault(symbol, {})['sell'] = {'datetime': current_time, 'signal': str(data['signal'].iloc[-1])}
self._save_buy_cooldown()
print(f"{KR_COINS[symbol]} ({symbol}) [{data['signal'].iloc[-1]} 매도], 현재가: {data['Close'].iloc[-1]:.4f}")
self.sendMsg("[KRW-COIN]\n" + f"• 매도 [COIN] {KR_COINS[symbol]} ({symbol}): {data['signal'].iloc[-1]} ({''}{data['Close'].iloc[-1]:.4f})")
sell_amount = available * strategy.get_sell_ratio(symbol, signal_name)
if sell_amount <= 0:
return False
self.sellCoinMarket(symbol, 0, sell_amount)
self._record_trade(symbol, "sell", signal_name)
print(f"{coin_name} ({symbol}) [매도 {signal_name}] ₩{close:.4f}, 수량 {sell_amount:.6f}")
self.sendMsg(
f"[KRW-COIN]\n• 매도 {coin_name} ({symbol}): {signal_name}{close:.4f}"
)
return True
else:
check_5_week_lowest = False
# BUY_MINUTE_LIMIT 이내라면 매수하지 않음
current_time = datetime.now()
last_buy_dt = self.buy_cooldown.get(symbol, {}).get('buy', {}).get('datetime')
if last_buy_dt:
time_diff = current_time - last_buy_dt
if time_diff.total_seconds() < BUY_MINUTE_LIMIT:
print(f"{symbol}: 매수 금지 중 (남은 시간: {BUY_MINUTE_LIMIT - time_diff.total_seconds():.0f}초)")
return False
try:
# 5주봉이 20주봉이나 40주봉보다 아래에 있는지 체크
# Convert hourly data to week-based rolling periods (5, 20, 40 weeks)
hours_in_week = 24 * 7 # 168 hours
period_5w = 5 * hours_in_week # 840 hours
period_20w = 20 * hours_in_week # 3,360 hours
period_40w = 40 * hours_in_week # 6,720 hours
if len(data) >= period_40w:
wma5 = data['Close'].rolling(window=period_5w).mean().iloc[-1]
wma20 = data['Close'].rolling(window=period_20w).mean().iloc[-1]
wma40 = data['Close'].rolling(window=period_40w).mean().iloc[-1]
# 5-week MA is the lowest among 5, 20, 40 week MAs
if (wma5 < wma20) and (wma5 < wma40):
check_5_week_lowest = True
except Exception:
# Ignore errors in MA calculation so as not to block trading logic
pass
# 체크: fall_6p
buy_amount = 5100
current_time = datetime.now()
if data['signal'].iloc[-1] == 'fall_6p':
if data['Close'].iloc[-1] > 100:
buy_amount = 300000
else:
buy_amount = 150000
elif data['signal'].iloc[-1] == 'movingaverage':
buy_amount = 10000
elif data['signal'].iloc[-1] == 'deviation40':
buy_amount = 30000
elif data['signal'].iloc[-1] == 'deviation240':
buy_amount = 7000
elif data['signal'].iloc[-1] == 'deviation1440':
if symbol in ['BONK', 'PEPE', 'TON']:
buy_amount = 50000
else:
buy_amount = 70000
if data['signal'].iloc[-1] in ['movingaverage', 'deviation40', 'deviation240', 'deviation1440']:
if check_5_week_lowest:
buy_amount *= 2
# 매수를 진행함
buy_amount = self.hts.buyCoinMarket(symbol, buy_amount)
# 최근 매수 신호를 함께 기록하여 [신규] 포맷으로 저장
if self.cooldown_file is not None:
try:
self.last_signal[symbol] = str(data['signal'].iloc[-1])
except Exception:
self.last_signal[symbol] = ''
self.buy_cooldown.setdefault(symbol, {})['buy'] = {'datetime': current_time, 'signal': str(data['signal'].iloc[-1])}
# 매수를 저장함
self._save_buy_cooldown()
print(f"{KR_COINS[symbol]} ({symbol}) [{data['signal'].iloc[-1]}], 현재가: {data['Close'].iloc[-1]:.4f}, {int(BUY_MINUTE_LIMIT/60)}분간 매수 금지 시작")
self.sendMsg("{}".format(self.format_message(symbol, KR_COINS[symbol], data['Close'].iloc[-1], data['signal'].iloc[-1], buy_amount)))
if self._is_in_cooldown(symbol, "buy"):
return False
buy_amount = strategy.get_buy_amount(
symbol, signal_name, close, trend=trade.trend
)
if strategy.should_double_buy(symbol, signal_name, pd.DataFrame()):
buy_amount *= 2
executed = self.buyCoinMarket(symbol, buy_amount)
self._record_trade(symbol, "buy", signal_name)
print(
f"{coin_name} ({symbol}) [매수 {signal_name}] ₩{close:.4f} "
f"({buy_amount} KRW, 추세={trade.trend})"
)
self.sendMsg(
self.format_message(
symbol, coin_name, close, signal_name, executed or buy_amount
)
)
return True
except Exception as e:
print(f"Error buying {symbol}: {str(e)}")
print(f"Error trading {symbol}: {str(e)}")
return False
return True
def annotate_signals(self, symbol: str, data: pd.DataFrame, simulation: bool | None = None) -> pd.DataFrame:
data = data.copy()
data['signal'] = ''
data['point'] = 0
if data['point'].iloc[-1] != 1:
for i in range(1, len(data)):
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], 'signal'] = 'movingaverage'
data.at[data.index[i], 'point'] = 1
if not simulation and data['point'][-3:].sum() > 0:
data.at[data.index[-1], 'signal'] = 'movingaverage'
data.at[data.index[-1], 'point'] = 1
def process_wld_mtf(self, symbol: str, balances: dict | None = None) -> None:
"""
WLD MTF: 모든 봉 BB 상태 비교 후 정책에 따라 매수/매도.
if data['Deviation40'].iloc[i - 1] < data['Deviation40'].iloc[i] and data['Deviation40'].iloc[i - 1] <= 90:
data.at[data.index[i], 'signal'] = 'deviation40'
data.at[data.index[i], 'point'] = 1
if not simulation and data['point'][-3:].sum() > 0:
data.at[data.index[-1], 'signal'] = 'deviation40'
data.at[data.index[-1], 'point'] = 1
mtf_bb_policy.json 이 있으면 해당 정책, 없으면 ACTIVE_MTF_POLICY 사용.
"""
from mtf_bb import load_frames_from_db, load_policy, print_latest_states
if symbol not in ['BONK']:
if symbol in ['TRX']:
if data['Deviation240'].iloc[i - 1] < data['Deviation240'].iloc[i] and data['Deviation240'].iloc[i - 1] <= 98:
data.at[data.index[i], 'signal'] = 'deviation240'
data.at[data.index[i], 'point'] = 1
if not simulation and data['point'][-3:].sum() > 0:
data.at[data.index[-1], 'signal'] = 'deviation240'
data.at[data.index[-1], 'point'] = 1
else:
if data['Deviation240'].iloc[i - 1] < data['Deviation240'].iloc[i] and data['Deviation240'].iloc[i - 1] <= 90:
data.at[data.index[i], 'signal'] = 'deviation240'
data.at[data.index[i], 'point'] = 1
if not simulation and data['point'][-3:].sum() > 0:
data.at[data.index[-1], 'signal'] = 'deviation240'
data.at[data.index[-1], 'point'] = 1
try:
frames = load_frames_from_db(self, symbol)
if not frames:
print(f"Data for {symbol}: 로드된 봉 없음.")
return
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], 'signal'] = 'deviation1440'
data.at[data.index[i], 'point'] = 1
if not simulation and data['point'][-3:].sum() > 0:
data.at[data.index[-1], 'signal'] = 'deviation1440'
data.at[data.index[-1], '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], 'signal'] = 'deviation1440'
data.at[data.index[i], 'point'] = 1
if not simulation and data['point'][-3:].sum() > 0:
data.at[data.index[-1], 'signal'] = 'deviation1440'
data.at[data.index[-1], '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], 'signal'] = 'deviation1440'
data.at[data.index[i], 'point'] = 1
if not simulation and data['point'][-3:].sum() > 0:
data.at[data.index[-1], 'signal'] = 'deviation1440'
data.at[data.index[-1], '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], 'signal'] = 'deviation1440'
data.at[data.index[i], 'point'] = 1
if not simulation and data['point'][-3:].sum() > 0:
data.at[data.index[-1], 'signal'] = 'deviation1440'
data.at[data.index[-1], 'point'] = 1
df_1d = frames.get(TREND_INTERVAL_1D)
df_1h = frames.get(TREND_INTERVAL_1H)
if df_1d is None or df_1d.empty:
df_1d = frames.get(ENTRY_INTERVAL)
if df_1h is None or df_1h.empty:
df_1h = frames.get(ENTRY_INTERVAL)
# Deviation720 상향 돌파 매수 (92, 93)
try:
prev_d720 = data['Deviation720'].iloc[i - 1]
curr_d720 = data['Deviation720'].iloc[i]
# 92 상향 돌파
if prev_d720 < 92 and curr_d720 >= 92:
data.at[data.index[i], 'signal'] = 'Deviation720'
data.at[data.index[i], 'point'] = 1
if not simulation and data['point'][-3:].sum() > 0:
data.at[data.index[-1], 'signal'] = 'Deviation720'
data.at[data.index[-1], 'point'] = 1
# 93 상향 돌파
if prev_d720 < 93 and curr_d720 >= 93:
data.at[data.index[i], 'signal'] = 'Deviation720'
data.at[data.index[i], 'point'] = 1
if not simulation and data['point'][-3:].sum() > 0:
data.at[data.index[-1], 'signal'] = 'Deviation720'
data.at[data.index[-1], 'point'] = 1
except Exception:
pass
policy = load_policy() or strategy.ACTIVE_MTF_POLICY
cfg = strategy.ACTIVE_CONFIG
print_latest_states(frames, cfg)
print(
f"MTF 정책: {policy.name} | "
f"매수={policy.buy_interval}분 | 매도={policy.sell_interval}분 | "
f"확인={list(policy.buy_confirm_intervals)}"
)
try:
prev_low = data['Low'].iloc[i - 1]
curr_close = data['Close'].iloc[i]
curr_low = data['Low'].iloc[i]
cond_close_drop = curr_close <= prev_low * 0.94
cond_low_drop = curr_low <= prev_low * 0.94
if cond_close_drop or cond_low_drop:
data.at[data.index[i], 'signal'] = 'fall_6p'
data.at[data.index[i], 'point'] = 1
if not simulation and data['point'][-3:].sum() > 0:
data.at[data.index[-1], 'signal'] = 'fall_6p'
data.at[data.index[-1], 'point'] = 1
except Exception:
pass
return data
trend = strategy.get_trend(df_1d, df_1h)
print(f"{symbol} 추세: {trend}")
entry = frames.get(ENTRY_INTERVAL)
trade = strategy.evaluate(
symbol,
entry if entry is not None else frames[policy.buy_interval],
df_1h,
df_1d,
config=cfg,
frames=frames,
policy=policy,
)
if trade is None:
return
self.execute_trade_signal(symbol, trade, balances=balances)
except Exception as e:
print(f"Error processing {symbol}: {str(e)}")
def process_symbol(
self,
symbol: str,
interval: int | None = None,
balances: dict | None = None,
use_inverse: bool = False,
) -> None:
"""하위 호환: MTF 전략으로 위임 (use_inverse 무시)."""
self.process_wld_mtf(symbol, balances=balances)
def load_balances_dict(self) -> dict:
"""getBalances() 결과를 currency 키 dict로 변환."""
tmps = self.getBalances()
balances = {}
for tmp in tmps:
balances[tmp["currency"]] = {
"balance": float(tmp["balance"]),
"avg_buy_price": float(tmp["avg_buy_price"]),
}
return balances
# ------------- Formatting -------------
def format_message(self, symbol: str, symbol_name: str, close: float, signal: str, buy_amount: float) -> str:
message = f"[매수] {symbol_name} ({symbol}): "
def format_message(
self, symbol: str, symbol_name: str, close: float, signal: str, buy_amount: float
) -> str:
message = f"[매수] {symbol_name} ({symbol}) [{signal}]: "
if int(close) >= 100:
message += f"{close}"
@@ -472,12 +398,6 @@ class Monitor(HTS):
message += f"[{signal}]"
return message
def format_ma_message(self, info: dict, market_type: str) -> str:
prefix = '상승 ' if info.get('alert') else ''
message = prefix + f"[{market_type}] {info['name']} ({info['symbol']}) "
message += f"{'$' if market_type == 'US' else ''}({info['price']:.4f}) \n"
return message
# ------------- 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):
@@ -520,96 +440,146 @@ class Monitor(HTS):
continue
return None
def get_coin_more_data(self, symbol: str, interval: int, bong_count: int = 3000) -> pd.DataFrame:
def get_coin_more_data(
self,
symbol: str,
interval: int,
bong_count: int = 3000,
verbose: bool = False,
) -> pd.DataFrame:
"""
빗썸 API를 반복 호출해 bong_count개까지 과거 봉을 수집합니다.
Args:
verbose: True면 수집 진행 상황을 출력합니다.
"""
to = datetime.now()
data: pd.DataFrame | None = None
step = 0
while data is None or len(data) < bong_count:
step += 1
if data is None:
data = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
chunk = self.get_coin_data(symbol, interval, to.strftime("%Y-%m-%d %H:%M:%S"))
data = chunk
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):
if df is not None and not df.empty:
data = pd.concat([data, df], ignore_index=True)
if df is None or df.empty or previous_count == len(data):
if verbose:
print(f" API 추가 데이터 없음 (수집 {len(data)}봉)")
break
if verbose and (step == 1 or step % 5 == 0 or len(data) >= bong_count):
label = "일봉" if interval >= 1440 else f"{interval}"
print(f" [{label}] 요청 {step}회 — 누적 {len(data)}/{bong_count}")
time.sleep(0.3)
to = to - relativedelta(minutes=interval * 200)
data = data.set_index('datetime')
if data is None or data.empty:
return pd.DataFrame()
data = data.set_index("datetime")
data = data.sort_index()
data = data.drop_duplicates(keep='first')
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')
def get_coin_saved_data(
self, symbol: str, interval: int, data: pd.DataFrame, db_path: str = "coins.db"
) -> pd.DataFrame:
"""
coins.db에서 저장된 봉을 읽고, API로 받은 최신 봉을 DB에 반영합니다.
downloader.py로 미리 적재해 두면 장기 MA 계산에 유리합니다.
"""
conn = sqlite3.connect(db_path)
cursor = conn.cursor()
table_name = f"{symbol}_{interval}"
cursor.execute(
f"CREATE TABLE IF NOT EXISTS {table_name} "
"(CODE text, NAME text, ymdhms datetime, ymd text, hms text, "
"Close REAL, Open REAL, High REAL, Low REAL, Volume REAL)"
)
cursor.execute(
f"CREATE INDEX IF NOT EXISTS {table_name}_idx ON {table_name}(CODE, ymdhms)"
)
for i in range(1, len(data)):
cursor.execute("SELECT * from {}_{} where CODE = ? and ymdhms = ?".format(symbol, str(interval)), (symbol, data['datetime'].iloc[-i].strftime('%Y-%m-%d %H:%M:%S')),)
arr = cursor.fetchone()
if not arr:
ymdhms = data["datetime"].iloc[-i].strftime("%Y-%m-%d %H:%M:%S")
cursor.execute(
f"SELECT 1 FROM {table_name} WHERE CODE = ? AND ymdhms = ?",
(symbol, ymdhms),
)
if not cursor.fetchone():
cursor.execute(
"INSERT INTO {}_{} (CODE, NAME, ymdhms, ymd, hms, close, open, high, low, volume) VALUES(?, ?, ?, ?, ?, ?, ?, ?, ?, ?)".format(symbol, interval),
f"INSERT INTO {table_name} "
"(CODE, NAME, ymdhms, ymd, hms, Close, Open, High, Low, Volume) "
"VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?)",
(
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],
ymdhms,
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 {}_{} order by ymdhms desc limit 7000) subquery order by datetime".format(symbol, str(interval)))
cursor.execute(
f"SELECT Open, Close, High, Low, Volume, ymdhms AS datetime "
f"FROM (SELECT Open, Close, High, Low, Volume, ymdhms "
f"FROM {table_name} ORDER BY ymdhms DESC LIMIT 7000) "
f"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')
if not result:
return pd.DataFrame(
columns=["Open", "Close", "High", "Low", "Volume", "datetime"]
)
df = pd.DataFrame(
result, columns=["Open", "Close", "High", "Low", "Volume", "datetime"]
)
df = df.set_index("datetime")
df = df.sort_index()
df['datetime'] = df.index
df["datetime"] = df.index
return df
def get_coin_some_data(self, symbol: str, interval: int) -> pd.DataFrame:
"""
WLD 시세: API 최신 봉 + coins.db 과거 봉 + 1분봉 최신 1개를 합칩니다.
DB가 비어 있으면 API·1분봉만 사용합니다. 과거 적재는 downloader.py 실행.
"""
data = self.get_coin_data(symbol, interval)
if data is None or data.empty:
return pd.DataFrame()
data_1 = self.get_coin_data(symbol, interval=1)
data_1.at[data_1.index[-1], 'Volume'] = data_1['Volume'].iloc[-1] * 60
if data_1 is not None and not data_1.empty:
data_1 = data_1.copy()
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
parts = [data]
if saved_data is not None and not saved_data.empty:
parts.append(saved_data)
if data_1 is not None and not data_1.empty:
parts.append(data_1.iloc[[-1]])
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
merged = pd.concat(parts, ignore_index=True)
merged["datetime"] = pd.to_datetime(merged["datetime"], format="%Y-%m-%d %H:%M:%S")
merged = merged.set_index("datetime")
merged = merged.sort_index()
merged = merged.drop_duplicates(keep="first")
merged["datetime"] = merged.index
return merged