hankin
423baff73b
- Docker bridge 网络隔离（8000 端口封死） - Gunicorn 4 Worker 多进程 - Alembic 数据库迁移基线 - 日志轮转 20m×3 - JWT 密钥 + DB 密码 + CORS 收紧 - 3-2-1 备份链路（NAS + R740-B 冷备） - 连接池 pool_pre_ping + pool_recycle=3600
40 lines
1.4 KiB
Python
40 lines
1.4 KiB
Python
from contextlib import asynccontextmanager as asynccontextmanager
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from typing import AsyncGenerator, ContextManager, TypeVar
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import anyio.to_thread
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from anyio import CapacityLimiter
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from starlette.concurrency import iterate_in_threadpool as iterate_in_threadpool # noqa
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from starlette.concurrency import run_in_threadpool as run_in_threadpool # noqa
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from starlette.concurrency import ( # noqa
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run_until_first_complete as run_until_first_complete,
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)
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_T = TypeVar("_T")
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@asynccontextmanager
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async def contextmanager_in_threadpool(
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cm: ContextManager[_T],
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) -> AsyncGenerator[_T, None]:
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# blocking __exit__ from running waiting on a free thread
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# can create race conditions/deadlocks if the context manager itself
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# has its own internal pool (e.g. a database connection pool)
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# to avoid this we let __exit__ run without a capacity limit
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# since we're creating a new limiter for each call, any non-zero limit
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# works (1 is arbitrary)
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exit_limiter = CapacityLimiter(1)
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try:
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yield await run_in_threadpool(cm.__enter__)
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except Exception as e:
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ok = bool(
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await anyio.to_thread.run_sync(
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cm.__exit__, type(e), e, e.__traceback__, limiter=exit_limiter
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)
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)
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if not ok:
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raise e
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else:
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await anyio.to_thread.run_sync(
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cm.__exit__, None, None, None, limiter=exit_limiter
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)
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