feat(db): fully deprecate and delete legacy Python SQLite databases and tools, consolidating into PostgreSQL
This commit is contained in:
@@ -8,8 +8,8 @@ canonical_runtime:
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migration: src/dotnet/QuantEngine.Infrastructure/Migrations/V5__Add_Normalized_Learning_History.sql
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output: Temp/kis_dotnet_collection_v1.json
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legacy_policy:
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python_collector: migration_only
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sqlite_store: migration_only
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python_collector: forbidden
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sqlite_store: forbidden
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xlsx_runtime_input: forbidden
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gates:
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- dotnet_collector_registered
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@@ -1,464 +0,0 @@
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"""SQLite store for platform-transition data collection outputs.
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This store is intentionally small and backend-agnostic enough to be upgraded to
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PostgreSQL later without changing the row contract. The canonical payload is the
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normalized factor row plus provenance metadata.
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"""
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from __future__ import annotations
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import json
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import sqlite3
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from dataclasses import dataclass
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from pathlib import Path
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from typing import Any, Iterable
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SCHEMA = """
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PRAGMA journal_mode=WAL;
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CREATE TABLE IF NOT EXISTS collection_runs (
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run_id TEXT PRIMARY KEY,
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collector_name TEXT NOT NULL,
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started_at TEXT NOT NULL,
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finished_at TEXT,
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status TEXT NOT NULL,
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input_source TEXT,
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output_json_path TEXT,
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output_db_path TEXT,
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notes TEXT,
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created_at TEXT DEFAULT (datetime('now'))
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);
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CREATE TABLE IF NOT EXISTS collection_snapshots (
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run_id TEXT NOT NULL,
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dataset_name TEXT NOT NULL,
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ticker TEXT NOT NULL,
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name TEXT,
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sector TEXT,
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as_of_date TEXT,
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source_priority TEXT,
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source_status TEXT,
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payload_json TEXT NOT NULL,
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provenance_json TEXT NOT NULL,
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created_at TEXT DEFAULT (datetime('now')),
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PRIMARY KEY (run_id, dataset_name, ticker)
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);
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CREATE TABLE IF NOT EXISTS collection_source_errors (
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run_id TEXT NOT NULL,
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ticker TEXT,
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source_name TEXT NOT NULL,
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error_kind TEXT NOT NULL,
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error_message TEXT NOT NULL,
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payload_json TEXT,
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created_at TEXT DEFAULT (datetime('now'))
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);
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CREATE INDEX IF NOT EXISTS idx_collection_snapshots_ticker_time
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ON collection_snapshots(ticker, created_at DESC);
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CREATE INDEX IF NOT EXISTS idx_collection_source_errors_run
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ON collection_source_errors(run_id, source_name);
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"""
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@dataclass(frozen=True)
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class CollectionRun:
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run_id: str
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collector_name: str
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started_at: str
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status: str
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input_source: str | None = None
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output_json_path: str | None = None
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output_db_path: str | None = None
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notes: str | None = None
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# SQLite와 PostgreSQL 연결을 동적으로 감지하여 연결 인스턴스를 리턴하는 헬퍼
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def _get_connection(db_target: Path | str) -> Any:
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db_str = str(db_target)
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if db_str.startswith("postgresql://") or db_str.startswith("postgres://"):
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try:
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import psycopg2
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from psycopg2.extras import RealDictCursor
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conn = psycopg2.connect(db_str)
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# SQLite의 row_factory = Row 처럼 dict 접근을 가능하게 설정
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return conn
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except ImportError:
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raise ImportError("PostgreSQL DSN이 제공되었으나 psycopg2 패키지가 설치되어 있지 않습니다.")
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else:
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return sqlite3.connect(Path(db_target))
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def init_db(db_target: Path | str) -> None:
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db_str = str(db_target)
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if db_str.startswith("postgresql://") or db_str.startswith("postgres://"):
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# PostgreSQL은 DB 서버 측에서 직접 Schema 생성을 관리하므로, CLI 도구가 생성한 DDL 마이그레이션 스텁을 사용합니다.
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# 런타임 수집 중 자동 DDL 실행은 락 이슈 예방을 위해 스킵하고 트랜잭션 연결만 보장합니다.
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conn = _get_connection(db_target)
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conn.close()
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return
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db_path = Path(db_target)
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db_path.parent.mkdir(parents=True, exist_ok=True)
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conn = sqlite3.connect(db_path)
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try:
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conn.executescript(SCHEMA)
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conn.commit()
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finally:
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conn.close()
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def upsert_collection_run(db_target: Path | str, run: CollectionRun, finished_at: str | None = None) -> None:
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init_db(db_target)
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conn = _get_connection(db_target)
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db_str = str(db_target)
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is_pg = db_str.startswith("postgresql://") or db_str.startswith("postgres://")
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try:
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# SQLite와 PostgreSQL 쿼리 바인딩 플레이스홀더 분기 (? vs %s)
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param_char = "%s" if is_pg else "?"
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query = f"""
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INSERT INTO collection_runs (
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run_id, collector_name, started_at, finished_at, status,
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input_source, output_json_path, output_db_path, notes
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) VALUES ({', '.join([param_char]*9)})
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ON CONFLICT(run_id) DO UPDATE SET
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collector_name=EXCLUDED.collector_name,
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started_at=EXCLUDED.started_at,
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finished_at=EXCLUDED.finished_at,
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status=EXCLUDED.status,
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input_source=EXCLUDED.input_source,
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output_json_path=EXCLUDED.output_json_path,
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output_db_path=EXCLUDED.output_db_path,
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notes=EXCLUDED.notes
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"""
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# PostgreSQL은 ON CONFLICT 테이블명 제외, EXCLUDED는 대소문자 무관하지만 PostgreSQL의 표준은 대문자 EXCLUDED를 권장
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cursor = conn.cursor()
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cursor.execute(
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query,
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(
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run.run_id,
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run.collector_name,
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run.started_at,
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finished_at,
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run.status,
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run.input_source,
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run.output_json_path,
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run.output_db_path,
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run.notes,
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),
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)
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conn.commit()
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finally:
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conn.close()
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def upsert_collection_snapshot(
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db_target: Path | str,
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*,
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run_id: str,
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dataset_name: str,
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ticker: str,
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name: str | None,
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sector: str | None,
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as_of_date: str | None,
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source_priority: str,
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source_status: str,
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payload: dict[str, Any],
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provenance: dict[str, Any],
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) -> None:
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init_db(db_target)
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conn = _get_connection(db_target)
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db_str = str(db_target)
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is_pg = db_str.startswith("postgresql://") or db_str.startswith("postgres://")
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try:
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param_char = "%s" if is_pg else "?"
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query = f"""
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INSERT INTO collection_snapshots (
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run_id, dataset_name, ticker, name, sector, as_of_date,
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source_priority, source_status, payload_json, provenance_json
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) VALUES ({', '.join([param_char]*10)})
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ON CONFLICT(run_id, dataset_name, ticker) DO UPDATE SET
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name=EXCLUDED.name,
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sector=EXCLUDED.sector,
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as_of_date=EXCLUDED.as_of_date,
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source_priority=EXCLUDED.source_priority,
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source_status=EXCLUDED.source_status,
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payload_json=EXCLUDED.payload_json,
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provenance_json=EXCLUDED.provenance_json
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"""
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cursor = conn.cursor()
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cursor.execute(
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query,
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(
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run_id,
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dataset_name,
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ticker,
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name,
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sector,
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as_of_date,
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source_priority,
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source_status,
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json.dumps(payload, ensure_ascii=False, default=str),
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json.dumps(provenance, ensure_ascii=False, default=str),
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),
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)
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conn.commit()
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finally:
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conn.close()
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def append_collection_error(
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db_target: Path | str,
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*,
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run_id: str,
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source_name: str,
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error_kind: str,
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error_message: str,
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ticker: str | None = None,
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payload: dict[str, Any] | None = None,
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) -> None:
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init_db(db_target)
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conn = _get_connection(db_target)
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db_str = str(db_target)
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is_pg = db_str.startswith("postgresql://") or db_str.startswith("postgres://")
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try:
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param_char = "%s" if is_pg else "?"
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query = f"""
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INSERT INTO collection_source_errors (
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run_id, ticker, source_name, error_kind, error_message, payload_json
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) VALUES ({', '.join([param_char]*6)})
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"""
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cursor = conn.cursor()
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cursor.execute(
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query,
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(
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run_id,
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ticker,
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source_name,
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error_kind,
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error_message,
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json.dumps(payload or {}, ensure_ascii=False, default=str),
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),
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)
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conn.commit()
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finally:
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conn.close()
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def fetch_latest_snapshots(db_target: Path | str, ticker: str, dataset_name: str | None = None) -> list[dict[str, Any]]:
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db_str = str(db_target)
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is_pg = db_str.startswith("postgresql://") or db_str.startswith("postgres://")
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if not is_pg and not Path(db_target).exists():
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return []
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conn = _get_connection(db_target)
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if not is_pg:
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conn.row_factory = sqlite3.Row
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try:
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param_char = "%s" if is_pg else "?"
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cursor = conn.cursor()
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if dataset_name:
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cursor.execute(
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f"""
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SELECT * FROM collection_snapshots
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WHERE ticker = {param_char} AND dataset_name = {param_char}
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ORDER BY created_at DESC
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""",
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(ticker, dataset_name),
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)
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else:
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cursor.execute(
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f"""
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SELECT * FROM collection_snapshots
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WHERE ticker = {param_char}
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ORDER BY created_at DESC
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""",
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(ticker,),
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)
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rows = cursor.fetchall()
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return [dict(row) for row in rows]
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finally:
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conn.close()
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def iter_recent_snapshots(db_target: Path | str, limit: int = 50) -> Iterable[dict[str, Any]]:
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db_str = str(db_target)
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is_pg = db_str.startswith("postgresql://") or db_str.startswith("postgres://")
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if not is_pg and not Path(db_target).exists():
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return []
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conn = _get_connection(db_target)
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if not is_pg:
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conn.row_factory = sqlite3.Row
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try:
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param_char = "%s" if is_pg else "?"
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cursor = conn.cursor()
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cursor.execute(
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f"SELECT * FROM collection_snapshots ORDER BY created_at DESC LIMIT {param_char}",
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(limit,),
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)
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rows = cursor.fetchall()
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return [dict(row) for row in rows]
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finally:
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conn.close()
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def load_collection_runs(db_target: Path | str, limit: int = 20) -> list[dict[str, Any]]:
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db_str = str(db_target)
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is_pg = db_str.startswith("postgresql://") or db_str.startswith("postgres://")
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if not is_pg and not Path(db_target).exists():
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return []
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conn = _get_connection(db_target)
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if not is_pg:
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conn.row_factory = sqlite3.Row
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try:
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param_char = "%s" if is_pg else "?"
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cursor = conn.cursor()
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cursor.execute(
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f"""
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SELECT run_id, collector_name, started_at, finished_at, status,
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input_source, output_json_path, output_db_path, notes, created_at
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FROM collection_runs
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ORDER BY started_at DESC, created_at DESC
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LIMIT {param_char}
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""",
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(int(limit),),
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)
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rows = cursor.fetchall()
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return [dict(row) for row in rows]
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finally:
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conn.close()
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def load_collection_errors(db_target: Path | str, limit: int = 20) -> list[dict[str, Any]]:
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db_str = str(db_target)
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is_pg = db_str.startswith("postgresql://") or db_str.startswith("postgres://")
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if not is_pg and not Path(db_target).exists():
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return []
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conn = _get_connection(db_target)
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if not is_pg:
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conn.row_factory = sqlite3.Row
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try:
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param_char = "%s" if is_pg else "?"
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cursor = conn.cursor()
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cursor.execute(
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f"""
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SELECT run_id, ticker, source_name, error_kind, error_message, payload_json, created_at
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FROM collection_source_errors
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ORDER BY created_at DESC
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LIMIT {param_char}
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""",
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(int(limit),),
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)
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rows = cursor.fetchall()
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return [dict(row) for row in rows]
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finally:
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conn.close()
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def load_collection_dashboard_state(
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db_target: Path | str | None = None,
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output_json_path: Path | str | None = None,
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*,
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limit: int = 8,
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) -> dict[str, Any]:
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db_str = str(db_target or "")
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is_pg = db_str.startswith("postgresql://") or db_str.startswith("postgres://")
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db = Path(db_target) if db_target and not is_pg else Path()
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report = Path(output_json_path) if output_json_path else Path()
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state: dict[str, Any] = {
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"db_path": db_str,
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"output_json_path": str(report) if output_json_path else "",
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"runs": [],
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"recent_snapshots": [],
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"recent_errors": [],
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"counts": {
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"collection_runs": 0,
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"collection_snapshots": 0,
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"collection_source_errors": 0,
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},
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"latest_run": {},
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"latest_report": {},
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}
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if report.exists():
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try:
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state["latest_report"] = json.loads(report.read_text(encoding="utf-8"))
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except Exception:
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state["latest_report"] = {}
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if not is_pg and (not db_target or not db.exists()):
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return state
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conn = _get_connection(db_target)
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if not is_pg:
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conn.row_factory = sqlite3.Row
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try:
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cursor = conn.cursor()
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state["counts"] = {
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"collection_runs": cursor.execute("SELECT COUNT(*) FROM collection_runs").fetchone()[0] if not is_pg else cursor.execute("SELECT COUNT(*) FROM collection_runs") or 0,
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"collection_snapshots": cursor.execute("SELECT COUNT(*) FROM collection_snapshots").fetchone()[0] if not is_pg else cursor.execute("SELECT COUNT(*) FROM collection_snapshots") or 0,
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"collection_source_errors": cursor.execute("SELECT COUNT(*) FROM collection_source_errors").fetchone()[0] if not is_pg else cursor.execute("SELECT COUNT(*) FROM collection_source_errors") or 0,
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}
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# PostgreSQL인 경우 단순 fetchone() 보완
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if is_pg:
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# PostgreSQL count 처리
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cursor.execute("SELECT COUNT(*) FROM collection_runs")
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state["counts"]["collection_runs"] = cursor.fetchone()[0]
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cursor.execute("SELECT COUNT(*) FROM collection_snapshots")
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state["counts"]["collection_snapshots"] = cursor.fetchone()[0]
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cursor.execute("SELECT COUNT(*) FROM collection_source_errors")
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state["counts"]["collection_source_errors"] = cursor.fetchone()[0]
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cursor.execute(
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||||
"""
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SELECT run_id, collector_name, started_at, finished_at, status,
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input_source, output_json_path, output_db_path, notes, created_at
|
||||
FROM collection_runs
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||||
ORDER BY started_at DESC, created_at DESC
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LIMIT 1
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||||
"""
|
||||
)
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run_row = cursor.fetchone()
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state["latest_run"] = dict(run_row) if run_row is not None else {}
|
||||
|
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param_char = "%s" if is_pg else "?"
|
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cursor.execute(
|
||||
f"""
|
||||
SELECT run_id, collector_name, started_at, finished_at, status,
|
||||
input_source, output_json_path, output_db_path, notes, created_at
|
||||
FROM collection_runs
|
||||
ORDER BY started_at DESC, created_at DESC
|
||||
LIMIT {param_char}
|
||||
""",
|
||||
(int(limit),),
|
||||
)
|
||||
state["runs"] = [dict(row) for row in cursor.fetchall()]
|
||||
|
||||
cursor.execute(
|
||||
f"""
|
||||
SELECT run_id, dataset_name, ticker, name, sector, as_of_date,
|
||||
source_priority, source_status, created_at
|
||||
FROM collection_snapshots
|
||||
ORDER BY created_at DESC
|
||||
LIMIT {param_char}
|
||||
""",
|
||||
(int(limit),),
|
||||
)
|
||||
state["recent_snapshots"] = [dict(row) for row in cursor.fetchall()]
|
||||
|
||||
cursor.execute(
|
||||
f"""
|
||||
SELECT run_id, ticker, source_name, error_kind, error_message, created_at
|
||||
FROM collection_source_errors
|
||||
ORDER BY created_at DESC
|
||||
LIMIT {param_char}
|
||||
""",
|
||||
(int(limit),),
|
||||
)
|
||||
state["recent_errors"] = [dict(row) for row in cursor.fetchall()]
|
||||
finally:
|
||||
conn.close()
|
||||
return state
|
||||
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Load Diff
@@ -1,142 +0,0 @@
|
||||
#!/usr/bin/env python3
|
||||
"""
|
||||
데이터베이스 초기화 도구 (2개 DB)
|
||||
1. kis_data_collection.db - KIS API 데이터 수집
|
||||
2. snapshot_admin.db - 성능/포지션 관리
|
||||
"""
|
||||
|
||||
import sqlite3
|
||||
from pathlib import Path
|
||||
from datetime import datetime
|
||||
|
||||
DB1_PATH = "src/quant_engine/kis_data_collection.db"
|
||||
DB2_PATH = "src/quant_engine/snapshot_admin.db"
|
||||
|
||||
def create_kis_db():
|
||||
"""kis_data_collection.db: KIS API 데이터 스키마"""
|
||||
conn = sqlite3.connect(DB1_PATH)
|
||||
cursor = conn.cursor()
|
||||
|
||||
cursor.execute("""
|
||||
CREATE TABLE IF NOT EXISTS data_feed (
|
||||
id INTEGER PRIMARY KEY AUTOINCREMENT,
|
||||
ticker TEXT NOT NULL,
|
||||
name TEXT,
|
||||
close_price REAL,
|
||||
entry_price REAL,
|
||||
quantity INTEGER,
|
||||
stop_price REAL,
|
||||
target_price REAL,
|
||||
entry_stage TEXT,
|
||||
account TEXT,
|
||||
entry_date TEXT,
|
||||
updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
|
||||
velocity_1d REAL,
|
||||
velocity_5d REAL,
|
||||
ma20 REAL,
|
||||
atr20 REAL,
|
||||
rsi_14 REAL,
|
||||
volume INTEGER,
|
||||
avg_trade_value_5d REAL,
|
||||
sector TEXT,
|
||||
beta REAL,
|
||||
UNIQUE(ticker, entry_date)
|
||||
)
|
||||
""")
|
||||
|
||||
cursor.execute("CREATE INDEX IF NOT EXISTS idx_data_feed_ticker ON data_feed(ticker)")
|
||||
cursor.execute("CREATE INDEX IF NOT EXISTS idx_data_feed_entry_date ON data_feed(entry_date)")
|
||||
|
||||
conn.commit()
|
||||
conn.close()
|
||||
print(f"[OK] kis_data_collection.db: data_feed 테이블 생성")
|
||||
|
||||
def create_snapshot_admin_db():
|
||||
"""snapshot_admin.db: 성능/포지션 스키마"""
|
||||
conn = sqlite3.connect(DB2_PATH)
|
||||
cursor = conn.cursor()
|
||||
|
||||
cursor.execute("""
|
||||
CREATE TABLE IF NOT EXISTS performance (
|
||||
id INTEGER PRIMARY KEY AUTOINCREMENT,
|
||||
ticker TEXT NOT NULL,
|
||||
name TEXT,
|
||||
entry_date TEXT NOT NULL,
|
||||
entry_price REAL NOT NULL,
|
||||
quantity INTEGER,
|
||||
stop_price REAL,
|
||||
target_price REAL,
|
||||
exit_date TEXT,
|
||||
current_price REAL,
|
||||
pnl_pct REAL,
|
||||
status TEXT,
|
||||
t20_milestone TEXT,
|
||||
entry_stage TEXT,
|
||||
account TEXT,
|
||||
recorded_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP,
|
||||
UNIQUE(ticker, entry_date)
|
||||
)
|
||||
""")
|
||||
|
||||
cursor.execute("""
|
||||
CREATE TABLE IF NOT EXISTS positions (
|
||||
id INTEGER PRIMARY KEY AUTOINCREMENT,
|
||||
ticker TEXT NOT NULL UNIQUE,
|
||||
name TEXT,
|
||||
quantity INTEGER,
|
||||
entry_price REAL,
|
||||
current_price REAL,
|
||||
average_cost REAL,
|
||||
sector TEXT,
|
||||
weight_pct REAL,
|
||||
updated_at TIMESTAMP DEFAULT CURRENT_TIMESTAMP
|
||||
)
|
||||
""")
|
||||
|
||||
cursor.execute("CREATE INDEX IF NOT EXISTS idx_performance_ticker ON performance(ticker)")
|
||||
cursor.execute("CREATE INDEX IF NOT EXISTS idx_performance_entry_date ON performance(entry_date)")
|
||||
cursor.execute("CREATE INDEX IF NOT EXISTS idx_positions_ticker ON positions(ticker)")
|
||||
|
||||
conn.commit()
|
||||
conn.close()
|
||||
print(f"[OK] snapshot_admin.db: performance, positions 테이블 생성")
|
||||
|
||||
def verify():
|
||||
"""검증"""
|
||||
print("\n" + "="*80)
|
||||
print("데이터베이스 구조 확인")
|
||||
print("="*80)
|
||||
|
||||
for db_path, db_name in [(DB1_PATH, "kis_data_collection.db"), (DB2_PATH, "snapshot_admin.db")]:
|
||||
conn = sqlite3.connect(db_path)
|
||||
cursor = conn.cursor()
|
||||
|
||||
cursor.execute("SELECT name FROM sqlite_master WHERE type='table'")
|
||||
tables = [row[0] for row in cursor.fetchall()]
|
||||
|
||||
file_size = Path(db_path).stat().st_size / 1024
|
||||
print(f"\n[{db_name}]")
|
||||
print(f" 크기: {file_size:.2f} KB")
|
||||
print(f" 테이블: {', '.join(tables)}")
|
||||
|
||||
for table in tables:
|
||||
if table != 'sqlite_sequence':
|
||||
cursor.execute(f"SELECT COUNT(*) FROM {table}")
|
||||
row_count = cursor.fetchone()[0]
|
||||
cursor.execute(f"PRAGMA table_info({table})")
|
||||
col_count = len(cursor.fetchall())
|
||||
print(f" - {table}: {col_count}개 컬럼, {row_count}개 행")
|
||||
|
||||
conn.close()
|
||||
|
||||
if __name__ == "__main__":
|
||||
print("2개 데이터베이스 초기화 중...\n")
|
||||
|
||||
create_kis_db()
|
||||
create_snapshot_admin_db()
|
||||
|
||||
verify()
|
||||
|
||||
print("\n[완료] 2개 DB 초기화 완료!")
|
||||
print(f" 1. kis_data_collection.db (KIS API)")
|
||||
print(f" 2. snapshot_admin.db (성능/포지션)")
|
||||
Reference in New Issue
Block a user