Archived
snowy-yang
9f56f68b66
异步基础层（core/）：
- db.py aiosqlite + WAL：读路径无锁并发、写路径 asyncio.Lock 串行，
busy_timeout 自旋——实现「读写同时进行」（旧实现用 RLock 全读串行）
- http_client.py aiohttp 连接池 + 有界重试（5xx 重试 / 4xx 不重试）+
响应体上限 + 流式接口；按事件循环隔离 session（支持迁移期双 loop）
工具链：
- pyproject.toml ruff(E/F/W/I/B/UP/C4/ASYNC/S/RUF) + pyright(basic) + pytest(asyncio auto)
- requirements-fastapi.txt FastAPI/aiohttp/aiosqlite/aiofiles 等目标栈
- requirements-dev.txt 开发依赖（pytest/ruff/pyright）
清理：删除无用脚本 _csscheck.py 与产物标记 _css_ok.txt/_pkg_ok.txt，同步 .gitignore
验证：pytest 10/10（含「写 200 条同时 4 读协程零异常」并发用例）；
ruff All checks passed；pyright 0 errors。
138 lines
4.5 KiB
Python
138 lines
4.5 KiB
Python
# -*- coding: utf-8 -*-
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"""异步 SQLite 访问层（aiosqlite + WAL）。
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核心目标：**读写同时进行**。
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- 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；
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- 读路径：每次操作独立连接、无锁、可并发（`fetch_all`/`fetch_one`/`fetch_val`）；
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- 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，
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但写者不阻塞读者（WAL）；
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- `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。
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与旧实现的差异：旧 `auth_system` 用 `threading.RLock` 把**全部**读写串行化，
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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」。
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"""
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import asyncio
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import os
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from collections.abc import AsyncIterator, Iterable, Sequence
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from contextlib import asynccontextmanager
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from pathlib import Path
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from typing import Any
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import aiosqlite
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# 站点数据目录（可经环境变量覆盖，便于测试隔离）
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DATA_DIR = Path(os.environ.get('SITE_DATA_DIR', 'data'))
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DB_PATH = DATA_DIR / 'site.db'
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# 写事务串行锁（惰性创建，避免跨事件循环绑定）
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_WRITE_LOCK: asyncio.Lock | None = None
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def _write_lock() -> asyncio.Lock:
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global _WRITE_LOCK
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if _WRITE_LOCK is None:
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_WRITE_LOCK = asyncio.Lock()
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return _WRITE_LOCK
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async def _configure(conn: aiosqlite.Connection) -> None:
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conn.row_factory = aiosqlite.Row
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await conn.execute('PRAGMA journal_mode=WAL') # 读写并发的前提
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await conn.execute('PRAGMA busy_timeout=15000') # 遇写锁自旋等待，而非立即报错
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await conn.execute('PRAGMA synchronous=NORMAL') # WAL 下兼顾安全与吞吐
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await conn.execute('PRAGMA foreign_keys=ON')
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async def connect() -> aiosqlite.Connection:
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"""新建一个已配置好的连接（调用方负责 close）。"""
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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
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conn = await aiosqlite.connect(str(DB_PATH), timeout=15)
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await _configure(conn)
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return conn
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# ============ 读路径（并发，无锁） ============
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async def fetch_all(sql: str, params: Sequence = ()) -> list[aiosqlite.Row]:
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conn = await connect()
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try:
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cur = await conn.execute(sql, params)
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return list(await cur.fetchall())
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finally:
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await conn.close()
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async def fetch_one(sql: str, params: Sequence = ()) -> aiosqlite.Row | None:
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conn = await connect()
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try:
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cur = await conn.execute(sql, params)
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return await cur.fetchone()
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finally:
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await conn.close()
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async def fetch_val(sql: str, params: Sequence = (), default: Any = None) -> Any:
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row = await fetch_one(sql, params)
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return row[0] if row is not None else default
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# ============ 写路径（串行，不阻塞读） ============
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async def execute(sql: str, params: Sequence = ()) -> int:
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"""执行单条写语句，返回 lastrowid（INSERT）或 rowcount（UPDATE/DELETE）。"""
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async with _write_lock():
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conn = await connect()
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try:
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cur = await conn.execute(sql, params)
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await conn.commit()
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return cur.lastrowid if cur.lastrowid else cur.rowcount
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finally:
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await conn.close()
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async def execute_many(sql: str, seq: Iterable[Sequence]) -> int:
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"""批量写，返回受影响行数。"""
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async with _write_lock():
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conn = await connect()
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try:
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cur = await conn.executemany(sql, seq)
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await conn.commit()
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return cur.rowcount
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finally:
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await conn.close()
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@asynccontextmanager
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async def write_transaction() -> AsyncIterator[aiosqlite.Connection]:
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"""写事务上下文：多条写语句原子提交（串行锁内）。
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用法：
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async with write_transaction() as conn:
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await conn.execute(...)
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await conn.execute(...)
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# 退出即 commit；异常则 rollback
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"""
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async with _write_lock():
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conn = await connect()
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try:
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yield conn
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await conn.commit()
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except Exception:
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await conn.rollback()
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raise
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finally:
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await conn.close()
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@asynccontextmanager
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async def read_connection() -> AsyncIterator[aiosqlite.Connection]:
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"""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。"""
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conn = await connect()
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try:
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yield conn
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finally:
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await conn.close()
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