155 lines
5.4 KiB
Python
155 lines
5.4 KiB
Python
"""SqliteDiagnosisSignalStore：baseline 逐题诊断信号的 SQLite 持久化适配器。
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实现 core/evolution/protocols.py::DiagnosisSignalStore 端口。信号行以
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(question_id, baseline_run_id, diag_fingerprint) 为主键，INSERT OR REPLACE
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保证逐题幂等 upsert；bool 字段以 0/1 存储，可空字段以 NULL 存储。表建在
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harness.db，供离线诊断编排写入、视频级切分选择器读取。
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"""
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from __future__ import annotations
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import sqlite3
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from pathlib import Path
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from core.evolution.types import DiagnosisSignalRow
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# 表列顺序即 DiagnosisSignalRow 字段顺序（question_id..session_id），
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# upsert 写入与 load 还原共用，避免手写列名两处漂移。
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_COLUMNS: tuple[str, ...] = (
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"question_id",
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"video_id",
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"baseline_run_id",
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"diag_fingerprint",
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"task_type",
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"error_type",
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"cause_category",
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"tier",
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"evolution_target",
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"degraded",
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"infra",
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"session_id",
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)
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class SqliteDiagnosisSignalStore:
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"""逐题诊断信号的 SQLite 存储实现。
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构造时按需建表（CREATE TABLE IF NOT EXISTS），主键
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(question_id, baseline_run_id, diag_fingerprint) 保证同键覆盖。
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每次写操作单事务 commit，保证原子落盘与断点续跑。
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参数:
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db_path: SQLite 数据库文件路径（通常为 harness.db）。
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"""
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def __init__(self, db_path: str) -> None:
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Path(db_path).parent.mkdir(parents=True, exist_ok=True)
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self._conn = sqlite3.connect(db_path)
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self._conn.row_factory = sqlite3.Row
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self._init_table()
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def _init_table(self) -> None:
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"""创建 baseline_diagnosis 表（若不存在）。"""
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self._conn.execute(
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"""
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CREATE TABLE IF NOT EXISTS baseline_diagnosis (
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question_id TEXT NOT NULL,
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video_id TEXT NOT NULL,
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baseline_run_id TEXT NOT NULL,
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diag_fingerprint TEXT NOT NULL,
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task_type TEXT NOT NULL,
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error_type TEXT,
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cause_category TEXT,
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tier TEXT NOT NULL,
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evolution_target TEXT,
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degraded INTEGER NOT NULL,
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infra INTEGER NOT NULL,
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session_id TEXT,
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PRIMARY KEY (question_id, baseline_run_id, diag_fingerprint)
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)
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"""
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)
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self._conn.commit()
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def upsert(self, row: DiagnosisSignalRow) -> None:
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"""写入或覆盖单题诊断信号（按主键幂等，单事务）。
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参数:
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row: 待持久化的诊断信号行。bool 字段转 0/1，None 存 NULL。
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关键实现:
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用 INSERT OR REPLACE 按主键覆盖，避免重复行；commit 保证原子。
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"""
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placeholders = ", ".join("?" for _ in _COLUMNS)
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col_names = ", ".join(_COLUMNS)
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values = (
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row.question_id,
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row.video_id,
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row.baseline_run_id,
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row.diag_fingerprint,
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row.task_type,
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row.error_type,
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row.cause_category,
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row.tier,
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row.evolution_target,
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int(row.degraded),
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int(row.infra),
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row.session_id,
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)
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self._conn.execute(
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f"INSERT OR REPLACE INTO baseline_diagnosis ({col_names}) VALUES ({placeholders})",
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values,
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)
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self._conn.commit()
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def done_question_ids(self, baseline_run_id: str, diag_fingerprint: str) -> set[str]:
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"""查询指定 run 与诊断指纹下已完成的 question_id 集合。
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参数:
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baseline_run_id: baseline run 标识。
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diag_fingerprint: 诊断口径指纹。
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返回:
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已落盘信号的 question_id 集合；无匹配时为空集，供断点续跑跳过。
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"""
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cursor = self._conn.execute(
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"SELECT DISTINCT question_id FROM baseline_diagnosis"
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" WHERE baseline_run_id = ? AND diag_fingerprint = ?",
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(baseline_run_id, diag_fingerprint),
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)
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return {r["question_id"] for r in cursor.fetchall()}
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def load(self, baseline_run_id: str, diag_fingerprint: str) -> list[DiagnosisSignalRow]:
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"""加载指定 run 与诊断指纹下的全部诊断信号行。
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参数:
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baseline_run_id: baseline run 标识。
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diag_fingerprint: 诊断口径指纹。
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返回:
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还原后的 DiagnosisSignalRow 列表（0/1→bool，NULL→None）。
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"""
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col_names = ", ".join(_COLUMNS)
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cursor = self._conn.execute(
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f"SELECT {col_names} FROM baseline_diagnosis"
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" WHERE baseline_run_id = ? AND diag_fingerprint = ?",
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(baseline_run_id, diag_fingerprint),
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)
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return [
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DiagnosisSignalRow(
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question_id=r["question_id"],
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video_id=r["video_id"],
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baseline_run_id=r["baseline_run_id"],
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diag_fingerprint=r["diag_fingerprint"],
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task_type=r["task_type"],
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error_type=r["error_type"],
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cause_category=r["cause_category"],
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tier=r["tier"],
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evolution_target=r["evolution_target"],
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degraded=bool(r["degraded"]),
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infra=bool(r["infra"]),
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session_id=r["session_id"],
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)
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for r in cursor.fetchall()
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]
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