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NeteaseUrl/core/db.py
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snowy-yang bd3a4ac70b fix: 统一 core/auth_system 的数据目录解析,消除脑裂隐患
为什么:`core/db.py` 认 SITE_DATA_DIR、`auth_system/db.py` 写死 Path('data'),
而两处指向的是**同一个** data/site.db。web/main.py 的文档字符串还宣称
「数据目录可由 SITE_DATA_DIR 覆盖」——只有 core 侧做到了。

后果:只要运维真的设置 SITE_DATA_DIR,站点库(用户/账本/卡密)与
core 侧读的设置/公告就会落到两个不同文件,且**不会报错**——
表现为「设置改了不生效」「公告消失」这类极难排查的诡异现象。
全仓 grep 确认该变量当前只出现在 core/db.py 与 web/main.py 两处,
没有任何测试或部署在用,所以是纯隐性隐患。

顺带修一个实测到的坑:`os.environ.get('SITE_DATA_DIR', 'data')` 的默认值
只在变量**缺失**时生效,`SITE_DATA_DIR=`(空串,compose/K8s 里很常见)
会让 Path('') 退化成当前工作目录,数据库静默落到 CWD。改用 `or 'data'`。

验证:四种取值(未设置 / 空串 / 绝对路径 / 相对路径)下
core.DATA_DIR == auth_system.DATA_DIR 且 DB_PATH 相同,全部一致。
2026-09-26 14:15:58 +08:00

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# -*- coding: utf-8 -*-
"""异步 SQLite 访问层(aiosqlite + WAL)。
核心目标:**读写同时进行**。
- WAL 模式:读事务与写事务互不阻塞(读快照隔离),这是 SQLite 层并发的根本;
- 读路径:每次操作独立连接、无锁、可并发(`fetch_all`/`fetch_one`/`fetch_val`);
- 写路径:SQLite 全库同一时刻只允许一个写者,用 `asyncio.Lock` 串行化写事务,
但写者不阻塞读者(WAL);
- `busy_timeout`:多进程/多连接下遇到短暂写锁自旋等待而非立刻 SQLITE_BUSY。
与旧实现的差异:旧 `auth_system` 用 `threading.RLock` 把**全部**读写串行化,
读也被写挡住;本层只串行化写,读放行并发,即「读写同时进行」。
"""
import asyncio
import os
from collections.abc import AsyncGenerator, Iterable, Sequence
from contextlib import asynccontextmanager
from pathlib import Path
from typing import Any
import aiosqlite
# 站点数据目录(可经环境变量覆盖,便于测试隔离)。
# 用 `or 'data'` 而不是 get 的默认值:get 的默认只在变量**缺失**时生效,
# 而 `SITE_DATA_DIR=`(空串)会让 Path('') 退化成当前工作目录,
# 数据库静默落到 CWD 而不是 data/。
# 注意:auth_system.db.DATA_DIR 必须与此处保持同一条表达式(两者指向同一个库)
DATA_DIR = Path(os.environ.get('SITE_DATA_DIR') or 'data')
DB_PATH = DATA_DIR / 'site.db'
# 锁按事件循环隔离:asyncio.Lock 绑定创建它的 loop,跨 loop 复用会抛
# "bound to a different event loop"(应用主 loop + 同步桥 loop + 测试各自
# 的 loop 并存,必须分开持有)。
_LOOP_LOCKS: dict[tuple[int, str], asyncio.Lock] = {}
def _loop_lock(kind: str) -> asyncio.Lock:
key = (id(asyncio.get_running_loop()), kind)
lock = _LOOP_LOCKS.get(key)
if lock is None:
lock = asyncio.Lock()
_LOOP_LOCKS[key] = lock
return lock
def _write_lock() -> asyncio.Lock:
"""写事务串行锁(每事件循环一个)。"""
return _loop_lock('write')
def _wal_lock() -> asyncio.Lock:
"""WAL 切换专用锁(不能用 _write_lock:execute() 已持它再调
connect→_configure 会自锁死)。"""
return _loop_lock('wal')
# 已确认切到 WAL 的库路径(首连设置一次;后续连接不再重复执行 PRAGMA 争排他锁)
_WAL_READY_FOR: str | None = None
async def _configure(conn: aiosqlite.Connection) -> None:
global _WAL_READY_FOR
conn.row_factory = aiosqlite.Row
# busy_timeout 先设:让后续语句遇锁自旋等待,而不是立刻报 database is locked
await conn.execute('PRAGMA busy_timeout=15000')
key = str(DB_PATH)
if _WAL_READY_FOR != key:
# 切换日志模式需要排他锁,且 `_WAL_READY_FOR` 的检查不是原子的——
# 并发连接须在专用锁内串行完成「切换 + 标记」,并二次复查,否则批量并发
# 连接会同时执行 PRAGMA journal_mode=WAL 争锁(实测 database is locked)
async with _wal_lock():
if _WAL_READY_FOR != key:
await conn.execute('PRAGMA journal_mode=WAL')
_WAL_READY_FOR = key
await conn.execute('PRAGMA synchronous=NORMAL') # WAL 下兼顾安全与吞吐
await conn.execute('PRAGMA foreign_keys=ON')
async def connect() -> aiosqlite.Connection:
"""新建一个已配置好的连接(调用方负责 close)。"""
DATA_DIR.mkdir(parents=True, exist_ok=True) # noqa: ASYNC240 - 幂等的微秒级一次目录创建,无需线程池
conn = await aiosqlite.connect(str(DB_PATH), timeout=15)
await _configure(conn)
return conn
# ============ 读路径(并发,无锁) ============
async def fetch_all(sql: str, params: Sequence = ()) -> list[aiosqlite.Row]:
conn = await connect()
try:
cur = await conn.execute(sql, params)
return list(await cur.fetchall())
finally:
await conn.close()
async def fetch_one(sql: str, params: Sequence = ()) -> aiosqlite.Row | None:
conn = await connect()
try:
cur = await conn.execute(sql, params)
return await cur.fetchone()
finally:
await conn.close()
async def fetch_val(sql: str, params: Sequence = (), default: Any = None) -> Any:
row = await fetch_one(sql, params)
return row[0] if row is not None else default
# ============ 写路径(串行,不阻塞读) ============
async def execute(sql: str, params: Sequence = ()) -> int:
"""执行单条写语句,返回 lastrowid(INSERT)或 rowcount(UPDATE/DELETE)。"""
async with _write_lock():
conn = await connect()
try:
cur = await conn.execute(sql, params)
await conn.commit()
return cur.lastrowid if cur.lastrowid else cur.rowcount
finally:
await conn.close()
async def execute_many(sql: str, seq: Iterable[Sequence]) -> int:
"""批量写,返回受影响行数。"""
async with _write_lock():
conn = await connect()
try:
cur = await conn.executemany(sql, seq)
await conn.commit()
return cur.rowcount
finally:
await conn.close()
@asynccontextmanager
async def write_transaction() -> AsyncGenerator[aiosqlite.Connection, None]:
"""写事务上下文:多条写语句原子提交(串行锁内)。
用法:
async with write_transaction() as conn:
await conn.execute(...)
await conn.execute(...)
# 退出即 commit;异常则 rollback
"""
async with _write_lock():
conn = await connect()
try:
yield conn
await conn.commit()
except Exception:
await conn.rollback()
raise
finally:
await conn.close()
@asynccontextmanager
async def read_connection() -> AsyncGenerator[aiosqlite.Connection, None]:
"""只读连接上下文(无锁、可并发);需要在一个连接上做多次读时使用。"""
conn = await connect()
try:
yield conn
finally:
await conn.close()