1d69c217e2
- feed_fallback.bar_is_garbage: 봉끝 기준 → 각 틱의 recv_ts wall-clock 기준으로 정정 실매 RAM 3초컷과 동일 논리 → 유동성 낮은 종목 부당 스킵 해소 - candle_garbage_fallback_enabled: 기본 True 복원 (wall-clock 정정 후 안전) - param_search_optuna·run_tail_backtest_cli: CANDLE_GARBAGE_FALLBACK·BACKTEST_USE_RUST 강제 os.environ 세팅 제거 → DB env·CLI 플래그로만 관리 (UI 존중) - WS_TICK_DB_SAVE_LAG_CUT_ENABLED 신설 (bool, 기본 false, 3벤더 공통) OFF=키움/KIS/LS 모든 틱 lag 무관 전부 저장 (벤더 통계·재현·백테 정합) ON=lag > LIVE_FEED_FALLBACK_MAX_AGE_SEC 이면 미저장 (미래 A안) - KIWOOM_TICK_LIVE_MAX_LAG_SEC 완전 폐기 → 위 스위치로 통일 - kiwoom_ws: _skip_persist 로직 새 스위치로 교체 - kis_ws·ls_ws: _skip_persist_kis/_ls 신규 (벤더별 상이했던 정책 통일) - docs/정합성.md §9 신설 (문제·결정·시나리오·향후 A안 전환법) - docs/rust_engine_parity_port_plan.md (신규 설계) 실매 스모크: logs/test_live_execution_validation_20260906_191845.log → 최종: 통과 · 👑 완결 브라우저 검증: http://192.168.0.149:5050/#liveconfig → 새 스위치 노출, JS 오류 없음 영향: 실매(DB 저장 정책 통일, RAM 컷 변경 없음) + 백테/Optuna(실매 정합) Co-authored-by: Cursor <cursoragent@cursor.com>
116 lines
3.6 KiB
Python
116 lines
3.6 KiB
Python
#!/usr/bin/env python3
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"""025980 lag~28s vs 어제 아침 max~5s — 스키마 확인 후 1회 조회."""
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from __future__ import annotations
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import sys
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from pathlib import Path
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ROOT = Path(__file__).resolve().parents[1]
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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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from database import TradeDB
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from kis_trader.utils.env import get_env_from_db
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LAG = """
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TIMESTAMPDIFF(
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SECOND,
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STR_TO_DATE(
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CASE
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WHEN CHAR_LENGTH(tick_time) >= 14 THEN LEFT(tick_time, 14)
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WHEN CHAR_LENGTH(tick_time) = 6 THEN CONCAT(DATE_FORMAT(recv_ts, '%%Y%%m%%d'), tick_time)
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ELSE NULL
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END,
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'%%Y%%m%%d%%H%%i%%s'
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),
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recv_ts
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)
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"""
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db = TradeDB()
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cols = [r["Field"] for r in db.conn.execute("SHOW COLUMNS FROM ws_ticks").fetchall()]
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print("ws_ticks cols:", cols)
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print("DB_CUT_ON", get_env_from_db("WS_TICK_DB_SAVE_LAG_CUT_ENABLED")) # 2026-09-06 통일 (구 KIWOOM_TICK_LIVE_MAX_LAG_SEC)
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print("TIME_MAX", get_env_from_db("KIWOOM_TICK_TIME_MAX_LAG_SEC"))
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print("FLUSH", get_env_from_db("WS_TICK_DB_FLUSH_SEC"))
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print("BATCH", get_env_from_db("WS_TICK_DB_BATCH_SIZE"))
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sel = [
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c
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for c in (
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"id",
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"code",
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"tick_time",
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"tick_time_raw",
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"recv_ts",
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"price",
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"volume",
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"source",
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)
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if c in cols
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]
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sel_sql = ", ".join(sel)
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print("\n== 오늘 kiwoom lag>5 ==")
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rows = db.conn.execute(
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f"SELECT {sel_sql}, {LAG} AS lag_sec FROM ws_ticks "
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"WHERE source=%s AND recv_ts >= %s AND recv_ts < %s AND "
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f"{LAG} > 5 ORDER BY lag_sec DESC LIMIT 20",
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("kiwoom", "2026-08-19 09:00:00", "2026-08-19 09:15:00"),
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).fetchall()
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for r in rows:
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print(dict(r))
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print("\n== 025980 09:04:50~09:06:00 (id순) ==")
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rows = db.conn.execute(
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f"SELECT {sel_sql}, {LAG} AS lag_sec FROM ws_ticks "
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"WHERE source=%s AND code=%s AND recv_ts >= %s AND recv_ts <= %s "
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"ORDER BY id",
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("kiwoom", "025980", "2026-08-19 09:04:50", "2026-08-19 09:06:00"),
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).fetchall()
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print("n", len(rows))
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for r in rows:
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print(dict(r))
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# 같은 recv 초에 몰린 종목 수 (WS 스레드 스톨 흔적)
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print("\n== 오늘 09:05:30~09:05:40 recv 초별 건수/종목 ==")
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rows = db.conn.execute(
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"SELECT recv_ts, COUNT(*) n, COUNT(DISTINCT code) codes "
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"FROM ws_ticks WHERE source=%s AND recv_ts >= %s AND recv_ts <= %s "
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"GROUP BY recv_ts ORDER BY recv_ts",
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("kiwoom", "2026-08-19 09:05:30", "2026-08-19 09:05:40"),
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).fetchall()
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for r in rows:
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print(dict(r))
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print("\n== 오늘 09:00~09:10 lag 분포 ==")
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rows = db.conn.execute(
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f"SELECT {LAG} AS lag_sec, COUNT(*) n FROM ws_ticks "
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"WHERE source=%s AND recv_ts >= %s AND recv_ts < %s "
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f"GROUP BY {LAG} ORDER BY lag_sec DESC LIMIT 15",
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("kiwoom", "2026-08-19 09:00:00", "2026-08-19 09:10:00"),
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).fetchall()
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for r in rows:
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print(dict(r))
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print("\n== 어제 09:00~09:15 lag 분포 top ==")
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rows = db.conn.execute(
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f"SELECT {LAG} AS lag_sec, COUNT(*) n FROM ws_ticks "
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"WHERE source=%s AND recv_ts >= %s AND recv_ts < %s "
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f"GROUP BY {LAG} ORDER BY lag_sec DESC LIMIT 15",
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("kiwoom", "2026-08-18 09:00:00", "2026-08-18 09:15:00"),
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).fetchall()
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for r in rows:
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print(dict(r))
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print("\n== 어제 10:51~12:00 (잔존) lag 분포 top ==")
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rows = db.conn.execute(
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f"SELECT {LAG} AS lag_sec, COUNT(*) n FROM ws_ticks "
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"WHERE source=%s AND recv_ts >= %s AND recv_ts < %s "
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f"GROUP BY {LAG} ORDER BY lag_sec DESC LIMIT 10",
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("kiwoom", "2026-08-18 10:51:00", "2026-08-18 12:00:00"),
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).fetchall()
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for r in rows:
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print(dict(r))
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