cfbacdacbc
- core/strategy.py: full rewrite to Volume Lead strategy - 10m candle direct detection (no 40m resampling) - F&G 3-tier vol threshold: <=40->6x, 41-50->5x, >50->blocked - Undying signal: price drop does not cancel signal (sig_p fixed) - Vol refresh: stronger vol_r updates signal price and timer - Watch alert: 4x-6x approaching threshold notifies via Telegram - WATCH_VOL_THRESH=4.0, WATCH_COOLDOWN_MIN=30, WATCH_VOL_JUMP=0.5 - daemon/runner.py: remove FNG_MIN_ENTRY block and Bear regime block - Only FNG_MAX_ENTRY(>50) blocks scan (greed/extreme greed) - Fast-poll loop cleaned of regime check - core/notify.py: add notify_watch() for near-signal Telegram alerts - Shows vol_r, distance to threshold, price, quiet pct - tests/: add 1y data collection and simulation scripts - collect_1y_data.py, refresh_cache.py - sim_10m_vol.py, sim_current.py, sim_regime_1y.py - sim_regime_sweep.py, sim_vol_override.py Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
82 lines
2.5 KiB
Python
82 lines
2.5 KiB
Python
"""10분봉 캐시 갱신 스크립트 — 최신 45일 데이터를 Upbit API로 재수집."""
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import os, sys, pickle, time
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from pathlib import Path
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from datetime import datetime, timedelta
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import pyupbit
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from dotenv import load_dotenv
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load_dotenv(dotenv_path=Path(__file__).parent.parent / ".env")
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sys.path.insert(0, str(Path(__file__).parent.parent))
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CACHE_FILE = Path(__file__).parent.parent / "data" / "sim10m_cache.pkl"
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TOP30_FILE = Path(__file__).parent.parent / "data" / "top30_tickers.pkl"
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SIM_DAYS = 45
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TOP_N = 20
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def fetch_10m(ticker: str, days: int) -> "pd.DataFrame | None":
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import pandas as pd
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target_start = datetime.now() - timedelta(days=days)
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all_dfs, to, prev_oldest = [], None, None
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while True:
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kwargs = dict(ticker=ticker, interval="minute10", count=200)
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if to:
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kwargs["to"] = to.strftime("%Y-%m-%d %H:%M:%S")
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try:
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df = pyupbit.get_ohlcv(**kwargs)
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except Exception:
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time.sleep(0.5)
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break
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if df is None or df.empty:
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break
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all_dfs.append(df)
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oldest = df.index[0]
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if prev_oldest is not None and oldest >= prev_oldest:
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break
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prev_oldest = oldest
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if oldest <= target_start:
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break
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to = oldest
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time.sleep(0.12)
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if not all_dfs:
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return None
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combined = pd.concat(all_dfs).sort_index()
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combined = combined[~combined.index.duplicated(keep="last")]
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return combined[combined.index >= target_start]
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def main():
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# 현재 Top20 종목 가져오기
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from core.market import get_top_tickers
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print("Top20 종목 조회...")
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tickers = get_top_tickers()[:TOP_N]
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print(f" {tickers}\n")
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data = {"10m": {}}
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for i, ticker in enumerate(tickers, 1):
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print(f"\r {i:>2}/{len(tickers)} {ticker} ", end="", flush=True)
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df = fetch_10m(ticker, SIM_DAYS)
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if df is not None and len(df) > 100:
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data["10m"][ticker] = df
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time.sleep(0.15)
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print(f"\n\n종목: {len(data['10m'])}개")
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if data["10m"]:
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sample = next(iter(data["10m"].values()))
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print(f"기간: {sample.index[0].strftime('%Y-%m-%d')} ~ {sample.index[-1].strftime('%Y-%m-%d')}")
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print(f"레코드: {len(sample)}개")
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# 저장
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pickle.dump(data, open(CACHE_FILE, "wb"))
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print(f"\n캐시 저장: {CACHE_FILE}")
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# top30 갱신
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pickle.dump(tickers, open(TOP30_FILE, "wb"))
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print(f"종목 저장: {TOP30_FILE}")
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if __name__ == "__main__":
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main()
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