225 lines
8.2 KiB
Python
225 lines
8.2 KiB
Python
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"""
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app/ai/evening.py
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장 후 데이터 준비 스크립트 (claude_evening 헬퍼)
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Claude Code headless가 이 스크립트를 실행해 당일 매매 결과와
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최근 30일 통계를 수집한 뒤, 직접 분석해 리포트를 작성한다.
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실행:
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python app/ai/evening.py # 요약 출력
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python app/ai/evening.py --print # Claude 분석용 전체 데이터 JSON 출력
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"""
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import json
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import math
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import os
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import sqlite3
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import sys
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from datetime import datetime, timedelta
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from pathlib import Path
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def _load_env():
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env_path = Path(".env")
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if not env_path.exists():
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return
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with open(env_path, encoding="utf-8") as f:
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for line in f:
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line = line.strip()
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if not line or line.startswith("#") or "=" not in line:
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continue
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k, _, v = line.partition("=")
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k = k.strip()
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v = v.strip()
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if " #" in v:
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v = v[: v.index(" #")]
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v = v.strip().strip('"').strip("'")
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if k and v and k not in os.environ:
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os.environ[k] = v
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_load_env()
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import sys
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ROOT = Path(__file__).parent.parent.parent
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if str(ROOT) not in sys.path:
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sys.path.insert(0, str(ROOT))
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DB_PATH = os.getenv("DB_PATH", "data/stockbot.db")
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TODAY = datetime.now().strftime("%Y-%m-%d")
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def _conn():
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return sqlite3.connect(DB_PATH)
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# ── 오늘 매매 내역 ────────────────────────────────────────────────────────────
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def get_today_trades() -> list[dict]:
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if not Path(DB_PATH).exists():
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return []
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with _conn() as c:
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rows = c.execute(
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"SELECT ticker, name, entry_time, exit_time, entry_price, exit_price, "
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"quantity, exit_reason, pnl, fee, ai_boosted "
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"FROM trades WHERE date=? ORDER BY entry_time",
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(TODAY,),
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).fetchall()
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cols = ["ticker", "name", "entry_time", "exit_time", "entry_price",
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"exit_price", "quantity", "exit_reason", "pnl", "fee", "ai_boosted"]
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return [dict(zip(cols, r)) for r in rows]
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# ── 최근 N일 일별 요약 ────────────────────────────────────────────────────────
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def get_daily_summaries(days: int = 30) -> list[dict]:
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if not Path(DB_PATH).exists():
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return []
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since = (datetime.now() - timedelta(days=days)).strftime("%Y-%m-%d")
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with _conn() as c:
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rows = c.execute(
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"SELECT date, total_trades, win_trades, lose_trades, "
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"net_pnl, max_drawdown, trading_stopped "
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"FROM daily_summary WHERE date >= ? ORDER BY date",
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(since,),
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).fetchall()
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cols = ["date", "total_trades", "win_trades", "lose_trades",
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"net_pnl", "max_drawdown", "trading_stopped"]
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return [dict(zip(cols, r)) for r in rows]
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# ── 실전 전환 조건 계산 ──────────────────────────────────────────────────────
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def calc_live_ready(summaries: list[dict]) -> dict:
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"""5가지 실전 전환 조건 계산"""
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trading_days = len(summaries)
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if trading_days == 0:
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return {
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"trading_days": 0, "win_rate": 0, "mdd_pct": 0,
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"sharpe": 0, "l3_count": 0, "all_pass": False,
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"details": []
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}
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total_trades = sum(s["total_trades"] for s in summaries)
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win_trades = sum(s["win_trades"] for s in summaries)
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win_rate = win_trades / total_trades * 100 if total_trades else 0
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# MDD: 누적 손익 기준 최대 낙폭
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cum = 0.0
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peak = 0.0
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mdd = 0.0
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for s in summaries:
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cum += s["net_pnl"] or 0
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if cum > peak:
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peak = cum
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drawdown = (peak - cum) / max(abs(peak), 1) * 100
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if drawdown > mdd:
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mdd = drawdown
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# Sharpe: 일별 손익의 mean/std (연환산)
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daily_pnl = [s["net_pnl"] or 0 for s in summaries]
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if len(daily_pnl) >= 2:
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mean = sum(daily_pnl) / len(daily_pnl)
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variance = sum((x - mean) ** 2 for x in daily_pnl) / len(daily_pnl)
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std = math.sqrt(variance) if variance > 0 else 1
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sharpe = (mean / std) * math.sqrt(252)
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else:
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sharpe = 0.0
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# L3 발동 횟수 (trading_stopped=1인 날)
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l3_count = sum(1 for s in summaries if s.get("trading_stopped"))
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checks = [
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("누적 운영 30거래일", trading_days >= 30, f"{trading_days}일"),
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("승률 > 48%", win_rate > 48, f"{win_rate:.1f}%"),
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("MDD < -10%", mdd < 10, f"-{mdd:.1f}%"),
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("샤프 > 1.0", sharpe > 1.0, f"{sharpe:.2f}"),
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("L3 월 2회 이하", l3_count <= 2, f"{l3_count}회"),
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]
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return {
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"trading_days": trading_days,
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"win_rate": round(win_rate, 1),
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"mdd_pct": round(-mdd, 1),
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"sharpe": round(sharpe, 2),
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"l3_count": l3_count,
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"all_pass": all(c[1] for c in checks),
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"details": [{"name": c[0], "pass": c[1], "value": c[2]} for c in checks],
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}
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# ── 최근 로그 ─────────────────────────────────────────────────────────────────
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def get_today_log_tail(lines: int = 50) -> str:
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log_path = Path("logs/stockbot.log")
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if not log_path.exists():
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return ""
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all_lines = log_path.read_text(encoding="utf-8", errors="replace").splitlines()
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today_lines = [l for l in all_lines if TODAY in l]
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return "\n".join(today_lines[-lines:])
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# ── 최근 30일 리포트 목록 ─────────────────────────────────────────────────────
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def get_recent_reports(days: int = 5) -> list[str]:
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reports_dir = Path("reports/daily")
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if not reports_dir.exists():
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return []
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files = sorted(reports_dir.glob("*.md"), reverse=True)[:days]
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return [f.name for f in files]
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# ── 메인 ─────────────────────────────────────────────────────────────────────
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def main(print_mode: bool = False):
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trades = get_today_trades()
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summaries = get_daily_summaries(30)
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live = calc_live_ready(summaries)
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log_tail = get_today_log_tail(30)
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reports = get_recent_reports(5)
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# 오늘 요약 통계
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closed = [t for t in trades if t["exit_time"]]
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wins = [t for t in closed if (t["pnl"] or 0) > 0]
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losses = [t for t in closed if (t["pnl"] or 0) <= 0]
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net_pnl = sum(t["pnl"] or 0 for t in closed)
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summary = {
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"date": TODAY,
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"today": {
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"total_trades": len(closed),
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"wins": len(wins),
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"losses": len(losses),
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"win_rate": round(len(wins) / len(closed) * 100, 1) if closed else 0,
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"net_pnl": round(net_pnl),
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"trades": trades,
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},
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"last_30_days": {
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"trading_days": live["trading_days"],
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"win_rate": live["win_rate"],
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"mdd_pct": live["mdd_pct"],
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"sharpe": live["sharpe"],
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"l3_count": live["l3_count"],
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"daily_summaries": summaries[-10:], # 최근 10일만 (토큰 절약)
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},
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"live_ready": live,
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"recent_reports": reports,
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"log_tail": log_tail,
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}
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if print_mode:
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print(json.dumps(summary, ensure_ascii=False, indent=2))
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else:
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# 콘솔 요약 출력
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print(f"\n[{TODAY}] 장 후 결산")
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print(f" 매매: {len(closed)}회 / 승 {len(wins)} 패 {len(losses)} "
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f"({summary['today']['win_rate']}%) / {net_pnl:+,.0f}원")
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print(f" 실전 전환: {'✅ ALL PASS' if live['all_pass'] else '❌ 미충족'}")
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for d in live["details"]:
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mark = "✅" if d["pass"] else "❌"
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print(f" {mark} {d['name']}: {d['value']}")
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if __name__ == "__main__":
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main(print_mode="--print" in sys.argv)
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