Phase C dry-run·문서화·DB 증분 저장 및 운영 env 동기화

- 1분봉 다운로드 제외, MONITOR_PERSIST로 05/06 수집 시 coins.db INSERT
- Phase C paper_fires 로그·07 모의 리포트, hybrid 시뮬 산출물·reference 문서 갱신
- .env Phase C(LIVE=0), bootstrap dotenv override=True

Co-authored-by: Cursor <cursoragent@cursor.com>
This commit is contained in:
dsyoon
2026-06-01 23:32:47 +09:00
parent 3cbfa40aab
commit b9ee241d14
19 changed files with 877 additions and 333 deletions

View File

@@ -0,0 +1,165 @@
#!/usr/bin/env python3
"""
Phase C dry-run 종료 후 모의 수익률(참고) 집계.
- 입력: data/ops/paper_fires.jsonl (06 dry-run 발화 로그)
- 출력: docs/05_ops/phase_c_paper_report.json + 콘솔 요약
주의: 실계좌 수익이 아님. 발화가 N봉 후 가격으로 계산한 forward % 합산(참고).
hybrid 복리 PnL은 simulation_report.html 과 다릅니다.
"""
from __future__ import annotations
import json
import runpy
from datetime import datetime
from pathlib import Path
import numpy as np
import pandas as pd
runpy.run_path(str(Path(__file__).resolve().parent / "_bootstrap.py"))
from config import ( # noqa: E402
MATCH_FORWARD_BARS,
MATCH_PRIMARY_INTERVAL,
SYMBOL,
TRADING_FEE_RATE,
)
from deepcoin.matching.label_outcomes import _forward_ret_vectorized # noqa: E402
from deepcoin.ops.monitor import Monitor # noqa: E402
from deepcoin.paths import PAPER_FIRES_LOG, PAPER_WEEKLY_REPORT_JSON # noqa: E402
_FEE_PCT = TRADING_FEE_RATE * 2 * 100
def load_paper_fires(path: Path) -> pd.DataFrame:
"""paper_fires.jsonl → DataFrame."""
if not path.is_file():
return pd.DataFrame()
rows = []
for line in path.read_text(encoding="utf-8").splitlines():
line = line.strip()
if line:
rows.append(json.loads(line))
if not rows:
return pd.DataFrame()
return pd.DataFrame(rows)
def attach_forward_returns(fires: pd.DataFrame, close_df: pd.DataFrame) -> pd.DataFrame:
"""
would_trade=True 발화에 MATCH_FORWARD_BARS 기준 forward 수익률(%) 부여.
Args:
fires: paper 발화.
close_df: 3분 종가 (datetime index).
Returns:
forward_ret_pct 컬럼 추가.
"""
if fires.empty or close_df.empty:
fires["forward_ret_pct"] = np.nan
return fires
close_df = close_df.sort_index()
if not isinstance(close_df.index, pd.DatetimeIndex):
close_df.index = pd.to_datetime(close_df.index)
close_ts_ns = close_df.index.astype(np.int64).values
close_px = close_df["Close"].astype(float).values
sub = fires[fires["would_trade"] == True].copy() # noqa: E712
if sub.empty:
fires["forward_ret_pct"] = np.nan
return fires
sig = pd.to_datetime(sub["signal_dt"])
fire_ns = sig.astype(np.int64).values
c0 = sub["close"].astype(float).values
side = sub["side"].astype(str).values
ret, valid = _forward_ret_vectorized(
fire_ns, c0, close_ts_ns, close_px, side, MATCH_FORWARD_BARS, _FEE_PCT
)
fires = fires.copy()
fires["forward_ret_pct"] = np.nan
idx = sub.index
fires.loc[idx, "forward_ret_pct"] = np.where(valid, ret, np.nan)
return fires
def summarize(fires: pd.DataFrame) -> dict:
"""집계 dict."""
traded = fires[fires["would_trade"] == True] # noqa: E712
with_ret = traded[traded["forward_ret_pct"].notna()]
out: dict = {
"generated_at": datetime.now().isoformat(timespec="seconds"),
"symbol": SYMBOL,
"forward_bars": MATCH_FORWARD_BARS,
"fee_round_trip_pct": _FEE_PCT,
"total_signals": int(len(fires)),
"would_trade_count": int(len(traded)),
"skipped_count": int(len(fires) - len(traded)),
"labeled_count": int(len(with_ret)),
"note": (
"모의 forward 수익률. 실계좌·hybrid 복리 PnL 아님. "
"매수·매도 leg 미결합 단순 합산."
),
}
if not with_ret.empty:
out["mean_forward_ret_pct"] = round(float(with_ret["forward_ret_pct"].mean()), 4)
out["sum_forward_ret_pct"] = round(float(with_ret["forward_ret_pct"].sum()), 4)
by_side = (
with_ret.groupby("side")["forward_ret_pct"]
.agg(["count", "mean", "sum"])
.round(4)
)
out["by_side"] = {k: v.to_dict() for k, v in by_side.iterrows()}
by_rule = (
traded.groupby("rule_id")
.size()
.to_dict()
if not traded.empty
else {}
)
out["fires_by_rule"] = by_rule
return out
def main() -> None:
"""paper_fires 로드 → forward % → 리포트 저장."""
fires = load_paper_fires(PAPER_FIRES_LOG)
if fires.empty:
print(f"[07] 발화 로그 없음: {PAPER_FIRES_LOG}")
print(" Phase C 기간 06_execute_live.py (LIVE=0) 상시 실행 후 재시도")
return
mon = Monitor(cooldown_file=None)
df = mon.read_candles_from_db(SYMBOL, MATCH_PRIMARY_INTERVAL, max_rows=50000)
if df.empty:
df = mon.get_coin_some_data(SYMBOL, MATCH_PRIMARY_INTERVAL)
if not isinstance(df.index, pd.DatetimeIndex):
df = df.set_index(pd.to_datetime(df["datetime"]))
fires = attach_forward_returns(fires, df)
report = summarize(fires)
PAPER_WEEKLY_REPORT_JSON.parent.mkdir(parents=True, exist_ok=True)
PAPER_WEEKLY_REPORT_JSON.write_text(
json.dumps(report, ensure_ascii=False, indent=2),
encoding="utf-8",
)
print(f"[07] 저장: {PAPER_WEEKLY_REPORT_JSON}")
print(f" 기간 로그: {fires['ts'].min()} ~ {fires['ts'].max()}")
print(f" 발화 {report['total_signals']} · 체결가정(would_trade) {report['would_trade_count']}")
if "sum_forward_ret_pct" in report:
print(
f" 모의 forward 합산: {report['sum_forward_ret_pct']}% "
f"(평균 {report['mean_forward_ret_pct']}%, "
f"{MATCH_FORWARD_BARS}봉 후, 참고용)"
)
else:
print(" forward 라벨 가능 건 없음 (봉 데이터 부족 또는 발화 없음)")
if __name__ == "__main__":
main()

View File

@@ -8,4 +8,5 @@ if str(ROOT) not in sys.path:
# .env → config 일관 로드
from deepcoin.env_loader import load_project_env # noqa: E402
load_project_env()
# 프로젝트 .env가 OS에 남은 LIVE_* 등보다 우선 (실거래 설정 일치)
load_project_env(override=True)

17
scripts/run_phase_c.sh Executable file
View File

@@ -0,0 +1,17 @@
#!/bin/bash
# Phase C dry-run (~금요일 저녁). 프로젝트 루트에서 실행.
set -e
cd "$(dirname "$0")/.."
PY="${PY:-/Users/dsyoon/opt/anaconda3/envs/coin/bin/python}"
echo "=== Phase C: LIVE_TRADING_ENABLED=0 확인 ==="
$PY -c "import runpy; from pathlib import Path; runpy.run_path('scripts/_bootstrap.py'); import config; assert not config.LIVE_TRADING_ENABLED, 'LIVE must be 0'"
echo "=== 01 봉 갱신 (1일 1회 권장) ==="
$PY scripts/01_download.py
echo "=== verify ==="
$PY scripts/06_verify_live_dryrun.py
echo "=== 06 dry-run 상시 (Ctrl+C 종료) ==="
exec $PY scripts/06_execute_live.py