"""일자별 틱·호가 수집 통계 (백테웹 통계 탭). 실매 벤더별 DB 적재량 + 틱↔호가 공백 비율. - 틱/호가 DB는 벤더마다 SAVE 플래그로 **각각** 적재한다 (2·3차 spill일 때만 아님). - MODE=tick: 체결 1건당 그 벤더 RAM 호가가 ``WS_ORDERBOOK_TICK_MAX_AGE_SEC``(기본 3초) 안일 때만 호가행. 스냅 없으면 그 틱의 호가행은 안 생김. - ``LIVE_FEED_FALLBACK``(기본 3초) 초과 틱은 매매 RAM·호가틱동기 skip (틱 DB는 기본 전부 적재). """ from __future__ import annotations from datetime import datetime from typing import Any, Dict, List, Optional, Set def _ymd8(day: str) -> str: s = (day or "").strip().replace("-", "")[:8] if len(s) == 8 and s.isdigit(): return s return datetime.now().strftime("%Y%m%d") def _like(day8: str) -> str: return f"{day8}%" def _row_nc(r: Any) -> Dict[str, Any]: if r is None: return {"n": 0, "codes": 0} if isinstance(r, dict): return {"n": int(r.get("n") or 0), "codes": int(r.get("c") or r.get("codes") or 0)} return {"n": int(r[0] or 0), "codes": int(r[1] or 0)} def _pct(num: float, den: float) -> Optional[float]: if den is None or float(den) <= 0: return None return round(100.0 * float(num) / float(den), 2) def _age_cut_row( *, channel: str, source: str, total: int, pass_n: int, fail_n: int, unknown_n: int, empty_minutes: int = 0, ) -> Dict[str, Any]: """옵투나/실매 읽기나이(LIVE_FEED_FALLBACK) 합격 요약 1행.""" usable = int(pass_n) + int(unknown_n) # lag 미상=실매와 같이 유지 tot = int(total or 0) return { "channel": channel, "source": source, "total": tot, "pass_n": int(pass_n), "fail_n": int(fail_n), "unknown_n": int(unknown_n), "usable_n": usable, "empty_minutes": int(empty_minutes or 0), "pass_pct": _pct(pass_n, tot), "fail_pct": _pct(fail_n, tot), "usable_pct": _pct(usable, tot), } def _feed_age_cut_stats(db, day8: str, age_sec: float) -> Dict[str, Any]: """recv_ts vs 체결/스냅 시각 지연 → 3초(폴백나이) 합격·탈락·미상. 옵투나 ``merge_ticks_time_axis_fallback`` / 호가 lag 컷과 동일 축. lag 미상(NULL)은 실매와 같이 **버리지 않음** → usable 에 포함. empty_minutes = 그 분 틱이 전부 fail 인 (code,분) 수 (비어 재현되는 분). """ age = max(0.0, float(age_sec or 3.0)) like = _like(day8) rows_out: List[Dict[str, Any]] = [] # ── ws_ticks ── try: tick_sql = ( "SELECT source AS src, " "COUNT(*) AS total, " "SUM(CASE WHEN lag_sec IS NOT NULL AND lag_sec <= %s THEN 1 ELSE 0 END) AS pass_n, " "SUM(CASE WHEN lag_sec IS NOT NULL AND lag_sec > %s THEN 1 ELSE 0 END) AS fail_n, " "SUM(CASE WHEN lag_sec IS NULL THEN 1 ELSE 0 END) AS unknown_n " "FROM (" " SELECT source, " " TIMESTAMPDIFF(SECOND, " " STR_TO_DATE(LEFT(COALESCE(NULLIF(tick_time_raw,''), tick_time), 14), '%%Y%%m%%d%%H%%i%%s'), " " recv_ts" " ) AS lag_sec " " FROM ws_ticks WHERE tick_time LIKE %s" ") t GROUP BY source" ) for r in db.conn.execute(tick_sql, (age, age, like)).fetchall() or []: d = dict(r) if not isinstance(r, dict) else r rows_out.append( _age_cut_row( channel="tick", source=str(d.get("src") or ""), total=int(d.get("total") or 0), pass_n=int(d.get("pass_n") or 0), fail_n=int(d.get("fail_n") or 0), unknown_n=int(d.get("unknown_n") or 0), ) ) except Exception: pass # 전량 컷된 분 (틱 채널) — 옵투나에서 그 분 시세 공백 empty_min = 0 try: empty_sql = ( "SELECT COUNT(*) AS n FROM (" " SELECT code, LEFT(tick_time,12) AS mk " " FROM (" " SELECT code, tick_time, " " TIMESTAMPDIFF(SECOND, " " STR_TO_DATE(LEFT(COALESCE(NULLIF(tick_time_raw,''), tick_time), 14), '%%Y%%m%%d%%H%%i%%s'), " " recv_ts" " ) AS lag_sec " " FROM ws_ticks WHERE tick_time LIKE %s" " ) x " " GROUP BY code, LEFT(tick_time,12) " " HAVING SUM(CASE WHEN lag_sec IS NULL OR lag_sec <= %s THEN 1 ELSE 0 END)=0 " " AND COUNT(*)>0" ") z" ) r = db.conn.execute(empty_sql, (like, age)).fetchone() empty_min = int((r["n"] if isinstance(r, dict) else r[0]) or 0) except Exception: empty_min = 0 # ── ls_ws_ticks ── try: d0 = datetime.strptime(day8, "%Y%m%d") d1 = d0.replace(hour=23, minute=59, second=59) ls_sql = ( "SELECT 'ls' AS src, " "COUNT(*) AS total, " "SUM(CASE WHEN lag_sec IS NOT NULL AND lag_sec <= %s THEN 1 ELSE 0 END) AS pass_n, " "SUM(CASE WHEN lag_sec IS NOT NULL AND lag_sec > %s THEN 1 ELSE 0 END) AS fail_n, " "SUM(CASE WHEN lag_sec IS NULL THEN 1 ELSE 0 END) AS unknown_n " "FROM (" " SELECT TIMESTAMPDIFF(SECOND, " " STR_TO_DATE(" " CASE WHEN CHAR_LENGTH(REGEXP_REPLACE(IFNULL(chetime,''), '[^0-9]', ''))>=14 " " THEN LEFT(REGEXP_REPLACE(chetime, '[^0-9]', ''), 14) " " WHEN CHAR_LENGTH(REGEXP_REPLACE(IFNULL(chetime,''), '[^0-9]', ''))>=6 " " THEN CONCAT(DATE_FORMAT(ts,'%%Y%%m%%d'), " " RIGHT(REGEXP_REPLACE(chetime, '[^0-9]', ''), 6)) " " ELSE DATE_FORMAT(ts,'%%Y%%m%%d%%H%%i%%s') END, " " '%%Y%%m%%d%%H%%i%%s'), " " ts) AS lag_sec " " FROM ls_ws_ticks WHERE ts>=%s AND ts<=%s" ") t" ) r = db.conn.execute(ls_sql, (age, age, d0, d1)).fetchone() if r: d = dict(r) if not isinstance(r, dict) else r if int(d.get("total") or 0) > 0: rows_out.append( _age_cut_row( channel="tick", source="ls", total=int(d.get("total") or 0), pass_n=int(d.get("pass_n") or 0), fail_n=int(d.get("fail_n") or 0), unknown_n=int(d.get("unknown_n") or 0), ) ) else: rows_out.append( _age_cut_row( channel="tick", source="ls", total=0, pass_n=0, fail_n=0, unknown_n=0, ) ) except Exception: rows_out.append( _age_cut_row( channel="tick", source="ls", total=0, pass_n=0, fail_n=0, unknown_n=0, ) ) # ── ws_orderbook 스트림 ── try: ob_sql = ( "SELECT source AS src, " "COUNT(*) AS total, " "SUM(CASE WHEN lag_sec IS NOT NULL AND lag_sec <= %s THEN 1 ELSE 0 END) AS pass_n, " "SUM(CASE WHEN lag_sec IS NOT NULL AND lag_sec > %s THEN 1 ELSE 0 END) AS fail_n, " "SUM(CASE WHEN lag_sec IS NULL THEN 1 ELSE 0 END) AS unknown_n " "FROM (" " SELECT source, " " TIMESTAMPDIFF(SECOND, " " STR_TO_DATE(" " CASE WHEN CHAR_LENGTH(snap_time)>=14 THEN LEFT(snap_time,14) " " WHEN CHAR_LENGTH(snap_time)>=6 THEN CONCAT(LEFT(%s,8), RIGHT(snap_time,6)) " " ELSE NULL END, " " '%%Y%%m%%d%%H%%i%%s'), " " recv_ts" " ) AS lag_sec " " FROM ws_orderbook WHERE snap_time LIKE %s AND source<>%s" ") t GROUP BY source" ) for r in db.conn.execute(ob_sql, (age, age, day8, like, "filter_eval")).fetchall() or []: d = dict(r) if not isinstance(r, dict) else r rows_out.append( _age_cut_row( channel="orderbook", source=str(d.get("src") or ""), total=int(d.get("total") or 0), pass_n=int(d.get("pass_n") or 0), fail_n=int(d.get("fail_n") or 0), unknown_n=int(d.get("unknown_n") or 0), ) ) except Exception: pass # LS 호가 try: ls_ob_sql = ( "SELECT 'ls_uh1' AS src, " "COUNT(*) AS total, " "SUM(CASE WHEN lag_sec IS NOT NULL AND lag_sec <= %s THEN 1 ELSE 0 END) AS pass_n, " "SUM(CASE WHEN lag_sec IS NOT NULL AND lag_sec > %s THEN 1 ELSE 0 END) AS fail_n, " "SUM(CASE WHEN lag_sec IS NULL THEN 1 ELSE 0 END) AS unknown_n " "FROM (" " SELECT TIMESTAMPDIFF(SECOND, " " STR_TO_DATE(LEFT(snap_time,14), '%%Y%%m%%d%%H%%i%%s'), " " recv_ts) AS lag_sec " " FROM ls_ws_orderbook WHERE snap_time LIKE %s" ") t" ) r = db.conn.execute(ls_ob_sql, (age, age, like)).fetchone() if r: d = dict(r) if not isinstance(r, dict) else r rows_out.append( _age_cut_row( channel="orderbook", source="ls_uh1", total=int(d.get("total") or 0), pass_n=int(d.get("pass_n") or 0), fail_n=int(d.get("fail_n") or 0), unknown_n=int(d.get("unknown_n") or 0), ) ) except Exception: rows_out.append( _age_cut_row( channel="orderbook", source="ls_uh1", total=0, pass_n=0, fail_n=0, unknown_n=0, ) ) # 틱 합계 행 tick_rows = [x for x in rows_out if x.get("channel") == "tick"] if tick_rows: rows_out.append( _age_cut_row( channel="tick", source="Σ(틱)", total=sum(x["total"] for x in tick_rows), pass_n=sum(x["pass_n"] for x in tick_rows), fail_n=sum(x["fail_n"] for x in tick_rows), unknown_n=sum(x["unknown_n"] for x in tick_rows), empty_minutes=empty_min, ) ) return { "age_sec": age, "empty_minutes_all_fail": empty_min, "rows": rows_out, "note": ( f"나이={age:g}s (LIVE_FEED_FALLBACK). " "합격=lag≤나이 · 탈락=lag>나이 · 미상=lag계산불가(유지=usable). " f"전량탈락분={empty_min} (그 분 옵투나 시세 공백 후보)." ), } def _safe_group(db, sql: str, params: tuple) -> List[Dict[str, Any]]: try: rows = db.conn.execute(sql, params).fetchall() or [] except Exception: return [] out: List[Dict[str, Any]] = [] for r in rows: if isinstance(r, dict): out.append( { "key": str(r.get("k") or r.get("source") or r.get("strategy") or ""), "n": int(r.get("n") or 0), "codes": int(r.get("c") or 0), } ) else: out.append({"key": str(r[0] or ""), "n": int(r[1] or 0), "codes": int(r[2] or 0)}) return out def _safe_nc(db, sql: str, params: tuple) -> Dict[str, Any]: try: r = db.conn.execute(sql, params).fetchone() except Exception: return {"n": 0, "codes": 0} return _row_nc(r) def _distinct_codes(db, sql: str, params: tuple) -> Set[str]: try: rows = db.conn.execute(sql, params).fetchall() or [] except Exception: return set() out: Set[str] = set() for r in rows: if isinstance(r, dict): c = str(r.get("code") or "").strip() else: c = str(r[0] or "").strip() if c: out.add(c) return out def _env_flags(db) -> Dict[str, Any]: """운영설정 스냅샷 (표시용). get_env_* 실패해도 탭은 동작.""" out: Dict[str, Any] = {} try: from kis_trader.utils.env import get_env_bool, get_env_float, get_env_from_db except Exception: return out for k, dflt in ( ("LIVE_TICK_PROVIDER", "kis"), ("LIVE_OB_PROVIDER", "kis"), ("LS_WS_ORDERBOOK_SAVE_MODE", "tick"), ("WS_ORDERBOOK_SAVE_MODE", "tick"), ): try: out[k] = str(get_env_from_db(k, dflt) or dflt) except Exception: out[k] = dflt for k, dflt in ( ("LS_WS_ORDERBOOK_SAVE", True), ("WS_ORDERBOOK_SAVE_KIS", True), ("WS_ORDERBOOK_SAVE_KIWOOM", True), ("WS_TICK_SAVE_KIS", True), ("WS_TICK_SAVE_KIWOOM", True), ("LS_WS_TICK_SAVE", False), ("LS_WS_CANDLE_SAVE", True), ("LS_WS_TICK_MIRROR_WS_TICKS", False), ): try: out[k] = bool(get_env_bool(k, dflt)) except Exception: out[k] = dflt for k, dflt in ( ("LIVE_FEED_FALLBACK_MAX_AGE_SEC", 3.0), ("WS_ORDERBOOK_TICK_MAX_AGE_SEC", 3.0), ): try: out[k] = float(get_env_float(k, dflt) or dflt) except Exception: out[k] = float(dflt) return out def _vendor_coverage( *, vendor: str, tick: Dict[str, Any], ob: Dict[str, Any], tick_codes: Optional[Set[str]], ob_codes: Optional[Set[str]], max_age_sec: float, ) -> Dict[str, Any]: """같은 벤더 틱 vs 호가 공백·동기율. tick_codes/ob_codes 가 None 이면(빠른 조회) 종목교집합 지표는 null. """ tick_n = int(tick.get("n") or 0) tick_c = int(tick.get("codes") or (len(tick_codes) if tick_codes is not None else 0) or 0) ob_n = int(ob.get("n") or 0) ob_c = int(ob.get("codes") or (len(ob_codes) if ob_codes is not None else 0) or 0) if tick_codes is None or ob_codes is None: tick_no_ob_n: Optional[int] = None ob_no_tick_n: Optional[int] = None tick_no_ob_pct: Optional[float] = None else: tick_no_ob_n = len(tick_codes - ob_codes) ob_no_tick_n = len(ob_codes - tick_codes) tick_no_ob_pct = _pct(tick_no_ob_n, tick_c) # 호가틱동기 미적재 대리지표: 틱행 대비 호가행이 없는 비율 # (MODE=tick 에서 snap None / skip_ram / 큐드롭 포함) missing_ob_rows = max(0, tick_n - ob_n) return { "vendor": vendor, "tick_n": tick_n, "tick_codes": tick_c, "ob_n": ob_n, "ob_codes": ob_c, "tick_codes_no_ob": tick_no_ob_n, "tick_codes_no_ob_pct": tick_no_ob_pct, "ob_codes_no_tick": ob_no_tick_n, "ob_per_tick_row_pct": _pct(ob_n, tick_n), "missing_ob_row_pct": _pct(missing_ob_rows, tick_n), "avg_tick_per_code": round(tick_n / tick_c, 1) if tick_c else 0.0, "avg_ob_per_code": round(ob_n / ob_c, 1) if ob_c else 0.0, "orderbook_tick_max_age_sec": float(max_age_sec), "sample_tick_no_ob_codes": ( sorted(tick_codes - ob_codes)[:30] if tick_codes is not None and ob_codes is not None else [] ), } def _ob_per_tick_ratio(ob_n: int, tick_n: int) -> Optional[float]: """호가행/틱행 (소수). 틱 0이면 None.""" if tick_n is None or int(tick_n) <= 0: return None return round(float(ob_n) / float(tick_n), 3) def _pack_vendor(label: str, tick_n: int, tick_c: int, ob_n: int, ob_c: int) -> Dict[str, Any]: tn = int(tick_n or 0) on = int(ob_n or 0) ratio = _ob_per_tick_ratio(on, tn) return { "vendor": label, "tick_n": tn, "tick_codes": int(tick_c or 0), "ob_n": on, "ob_codes": int(ob_c or 0), "ob_per_tick": ratio, "ob_per_tick_pct": _pct(on, tn), } def build_feed_collect_stats( db, day: Optional[str] = None, *, heavy: bool = False, ) -> Dict[str, Any]: """한 거래일(KST YYYYMMDD) 수집 요약 + 증권사 대비. 기본(heavy=False): GROUP BY COUNT 만 — 탭 체감용. heavy=True: DISTINCT 종목교집합 + 폴백나이(STR_TO_DATE 전수) — 느림, 버튼으로만. 최근 N일 일괄 GROUP BY 는 제거(틱·호가 테이블 폭주). """ day8 = _ymd8(day or "") like = _like(day8) notes: List[str] = [] heavy = bool(heavy) ticks_by_src = _safe_group( db, "SELECT source AS k, COUNT(*) AS n, COUNT(DISTINCT code) AS c " "FROM ws_ticks WHERE tick_time LIKE %s GROUP BY source ORDER BY n DESC", (like,), ) ob_by_src = _safe_group( db, "SELECT source AS k, COUNT(*) AS n, COUNT(DISTINCT code) AS c " "FROM ws_orderbook WHERE snap_time LIKE %s GROUP BY source ORDER BY n DESC", (like,), ) fe_by_strat = _safe_group( db, "SELECT COALESCE(strategy,'') AS k, COUNT(*) AS n, COUNT(DISTINCT code) AS c " "FROM ws_orderbook WHERE source=%s AND snap_time LIKE %s " "GROUP BY strategy ORDER BY n DESC", ("filter_eval", like), ) fe_reject = {"n": 0, "codes": 0} fe_pass = {"n": 0, "codes": 0} if heavy: fe_reject = _safe_nc( db, "SELECT COUNT(*) AS n, COUNT(DISTINCT code) AS c FROM ws_orderbook " "WHERE source=%s AND snap_time LIKE %s AND reject_code IS NOT NULL AND reject_code<>''", ("filter_eval", like), ) fe_pass = _safe_nc( db, "SELECT COUNT(*) AS n, COUNT(DISTINCT code) AS c FROM ws_orderbook " "WHERE source=%s AND snap_time LIKE %s AND (reject_code IS NULL OR reject_code='')", ("filter_eval", like), ) ls_ob = _safe_nc( db, "SELECT COUNT(*) AS n, COUNT(DISTINCT code) AS c FROM ls_ws_orderbook WHERE snap_time LIKE %s", (like,), ) try: d0 = datetime.strptime(day8, "%Y%m%d") d1 = d0.replace(hour=23, minute=59, second=59) ls_ticks = _safe_nc( db, "SELECT COUNT(*) AS n, COUNT(DISTINCT code) AS c FROM ls_ws_ticks " "WHERE ts >= %s AND ts <= %s", (d0, d1), ) except Exception: ls_ticks = {"n": 0, "codes": 0} ls_candles = {"n": 0, "codes": 0} try: ls_candles = _safe_nc( db, "SELECT COUNT(*) AS n, COUNT(DISTINCT code) AS c FROM ls_ws_candles " "WHERE candle_time LIKE %s", (like,), ) except Exception: pass kis_dedicated = _safe_nc( db, "SELECT COUNT(*) AS n, COUNT(DISTINCT code) AS c FROM kis_ws_orderbook WHERE snap_time LIKE %s", (like,), ) def _pick(rows: List[Dict[str, Any]], *keys: str) -> Dict[str, Any]: want = {k.lower() for k in keys} n, c = 0, 0 for r in rows: if str(r.get("key") or "").lower() in want: n += int(r.get("n") or 0) c = max(c, int(r.get("codes") or 0)) return {"n": n, "codes": c} tick_kis = _pick(ticks_by_src, "kis") tick_kw = _pick(ticks_by_src, "kiwoom") tick_ls = _pick(ticks_by_src, "ls") ob_kis = _pick(ob_by_src, "kis_h0stasp0", "kis") ob_kw = _pick(ob_by_src, "kiwoom_0d", "kiwoom") ob_fe = _pick(ob_by_src, "filter_eval") env = _env_flags(db) max_age = float(env.get("WS_ORDERBOOK_TICK_MAX_AGE_SEC") or 3.0) fb_age = float(env.get("LIVE_FEED_FALLBACK_MAX_AGE_SEC") or 3.0) kis_tick_codes: Optional[Set[str]] = None kis_ob_codes: Optional[Set[str]] = None kw_tick_codes: Optional[Set[str]] = None kw_ob_codes: Optional[Set[str]] = None ls_tick_codes: Optional[Set[str]] = None ls_ob_codes: Optional[Set[str]] = None if heavy: kis_tick_codes = _distinct_codes( db, "SELECT DISTINCT code FROM ws_ticks WHERE tick_time LIKE %s AND source=%s", (like, "kis"), ) kis_ob_codes = _distinct_codes( db, "SELECT DISTINCT code FROM ws_orderbook WHERE snap_time LIKE %s AND source=%s", (like, "kis_h0stasp0"), ) kw_tick_codes = _distinct_codes( db, "SELECT DISTINCT code FROM ws_ticks WHERE tick_time LIKE %s AND source=%s", (like, "kiwoom"), ) kw_ob_codes = _distinct_codes( db, "SELECT DISTINCT code FROM ws_orderbook WHERE snap_time LIKE %s AND source=%s", (like, "kiwoom_0d"), ) try: d0 = datetime.strptime(day8, "%Y%m%d") d1 = d0.replace(hour=23, minute=59, second=59) ls_tick_codes = _distinct_codes( db, "SELECT DISTINCT code FROM ls_ws_ticks WHERE ts >= %s AND ts <= %s", (d0, d1), ) except Exception: ls_tick_codes = set() ls_ob_codes = _distinct_codes( db, "SELECT DISTINCT code FROM ls_ws_orderbook WHERE snap_time LIKE %s", (like,), ) coverage = [ _vendor_coverage( vendor="kis", tick=tick_kis, ob=ob_kis, tick_codes=kis_tick_codes, ob_codes=kis_ob_codes, max_age_sec=max_age, ), _vendor_coverage( vendor="kiwoom", tick=tick_kw, ob=ob_kw, tick_codes=kw_tick_codes, ob_codes=kw_ob_codes, max_age_sec=max_age, ), _vendor_coverage( vendor="ls", tick=ls_ticks, ob=ls_ob, tick_codes=ls_tick_codes, ob_codes=ls_ob_codes, max_age_sec=max_age, ), ] vendor_matrix = { "day8": day8, "day": f"{day8[:4]}-{day8[4:6]}-{day8[6:8]}", "vendors": [ _pack_vendor( "kis", int(tick_kis.get("n") or 0), int(tick_kis.get("codes") or 0), int(ob_kis.get("n") or 0), int(ob_kis.get("codes") or 0), ), _pack_vendor( "kiwoom", int(tick_kw.get("n") or 0), int(tick_kw.get("codes") or 0), int(ob_kw.get("n") or 0), int(ob_kw.get("codes") or 0), ), _pack_vendor( "ls", int(ls_ticks.get("n") or 0), int(ls_ticks.get("codes") or 0), int(ls_ob.get("n") or 0), int(ls_ob.get("codes") or 0), ), ], "filter_eval_n": int(ob_fe.get("n") or 0), "filter_eval_codes": int(ob_fe.get("codes") or 0), "kis_tick": int(tick_kis.get("n") or 0), "kis_ob": int(ob_kis.get("n") or 0), "kis_ob_tick": _ob_per_tick_ratio(int(ob_kis.get("n") or 0), int(tick_kis.get("n") or 0)), "kw_tick": int(tick_kw.get("n") or 0), "kw_ob": int(ob_kw.get("n") or 0), "kw_ob_tick": _ob_per_tick_ratio(int(ob_kw.get("n") or 0), int(tick_kw.get("n") or 0)), "ls_tick": int(ls_ticks.get("n") or 0), "ls_ob": int(ls_ob.get("n") or 0), "ls_ob_tick": _ob_per_tick_ratio(int(ls_ob.get("n") or 0), int(ls_ticks.get("n") or 0)), } if heavy and kis_tick_codes is not None and kw_tick_codes is not None: both_tick = len(kis_tick_codes & kw_tick_codes) overlap = { "both_tick_codes": both_tick, "kis_only_tick_codes": len(kis_tick_codes - kw_tick_codes), "kiwoom_only_tick_codes": len(kw_tick_codes - kis_tick_codes), "both_ob_codes": len((kis_ob_codes or set()) & (kw_ob_codes or set())), "kis_only_ob_codes": len((kis_ob_codes or set()) - (kw_ob_codes or set())), "kiwoom_only_ob_codes": len((kw_ob_codes or set()) - (kis_ob_codes or set())), } else: overlap = { "both_tick_codes": None, "kis_only_tick_codes": None, "kiwoom_only_tick_codes": None, "both_ob_codes": None, "kis_only_ob_codes": None, "kiwoom_only_ob_codes": None, "deferred": True, } notes.append( "틱·호가 DB는 벤더별 SAVE로 각각 적재 (2·3차 spill일 때만 쌓이는 구조 아님). " f"읽기 폴백나이={fb_age:g}s · 호가틱동기 max_age={max_age:g}s." ) if not heavy: notes.append( "빠른 조회(기본): 나이컷·호가0종목 교집합은 「상세 집계」로. " "인덱스(market,code,time)는 종목단위 조회용이라 당일 전수 COUNT/STR_TO_DATE는 여전히 무겁다." ) for cov in coverage: if int(cov.get("tick_codes") or 0) <= 0 and int(cov.get("ob_n") or 0) <= 0: continue no_ob = cov.get("tick_codes_no_ob") miss = cov.get("missing_ob_row_pct") if no_ob is None: if int(cov.get("tick_n") or 0) > 0 and miss is not None and float(miss) >= 5.0: notes.append( f"[{cov['vendor']}] 틱행 대비 호가행 공백≈{miss}% " f"(호가행/틱행={cov.get('ob_per_tick_row_pct')}%). " "호가0종목 수는 상세 집계에서 확인." ) continue no_ob_i = int(no_ob or 0) if int(cov.get("tick_n") or 0) > 0 and ( no_ob_i > 0 or (miss is not None and float(miss) >= 5.0) ): notes.append( f"[{cov['vendor']}] 틱종목 중 호가0종목 {no_ob_i}/{cov['tick_codes']}" f"({cov.get('tick_codes_no_ob_pct')}%) · " f"틱행 대비 호가행 공백≈{miss}% " f"(호가행/틱행={cov.get('ob_per_tick_row_pct')}%). " "원인후보: MODE=tick에서 해당벤더 호가RAM이 max_age 밖·미수신, " "또는 체결 lag>폴백나이로 호가틱동기 skip(틱DB는 기본 유지)." ) if cov.get("vendor") == "ls" and int(cov.get("ob_n") or 0) == 0 and int(cov.get("tick_n") or 0) == 0: notes.append("[ls] 당일 틱·호가 DB 0 — hold외·Bye·SAVE OFF·구독 실패 점검.") if int(ls_ob.get("n") or 0) == 0 and env.get("LS_WS_ORDERBOOK_SAVE"): mode = str(env.get("LS_WS_ORDERBOOK_SAVE_MODE") or "tick").lower() if mode in ("tick", "on_tick", "tick_sync", "sync"): notes.append( "LS 호가 SAVE=ON·MODE=tick 인데 당일 0건 → UH1만으로 DB 안 씀. " "체결 콜백 필요. Bye/구독 빈약이면 0." ) else: notes.append("LS 호가 SAVE=ON 인데 당일 0건 → Bye·구독·interval 스로틀 점검.") if not env.get("LS_WS_TICK_SAVE"): notes.append("LS_WS_TICK_SAVE=false (ls_ws_ticks 미적재). ON이면 구독전체 적재.") else: notes.append("LS_WS_TICK_SAVE=true → 구독 종목 US3를 ls_ws_ticks 에 적재 (영구만이 아님).") if heavy: age_cut = _feed_age_cut_stats(db, day8, fb_age) else: age_cut = { "age_sec": fb_age, "empty_minutes_all_fail": None, "rows": [], "deferred": True, "note": ( f"나이={fb_age:g}s · 기본 조회에서는 생략(전수 STR_TO_DATE 스캔). " "「상세 집계」로 로드." ), } return { "day": f"{day8[:4]}-{day8[4:6]}-{day8[6:8]}", "day8": day8, "heavy": heavy, "env": env, "notes": notes, "vendor_matrix": vendor_matrix, "recent_days": [], "recent_days_n": 0, "age_cut": age_cut, "summary": { "ticks": { "kis": tick_kis, "kiwoom": tick_kw, "ls_mirror": tick_ls, "ls_table": ls_ticks, }, "orderbook": { "kis_h0stasp0": ob_kis, "kiwoom_0d": ob_kw, "filter_eval": ob_fe, "ls_ws_orderbook": ls_ob, "kis_ws_orderbook": kis_dedicated, }, "ls_candles": ls_candles, "filter_eval_pass": fe_pass, "filter_eval_reject": fe_reject, }, "coverage": coverage, "overlap": overlap, "ticks_by_source": ticks_by_src, "orderbook_by_source": ob_by_src, "filter_eval_by_strategy": fe_by_strat, }