aiotools
Idiomatic asyncio utilities
Decision gist · record as of 2026-08-14
Yes, if you are building asyncio applications on Python 3.11+ and want structured concurrency patterns and safer cancellation semantics. The low install friction, active maintenance, MIT license, and zero known vulnerabilities make it a solid choice. Not necessary if you are using trio, anyio, or other async frameworks, or if you prefer managing task lifecycle manually.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.11 or later; relies on asyncio internals so compatibility is tied to CPython versions.
- Low install friction with a single lightweight runtime dependency (async-lru).
- Active maintenance with a release within the last month and consistent Python 3.11+ support.
License · maintenance · safety
MIT (permissive) — MIT license permits unrestricted use, modification, and distribution in both open-source and commercial projects with minimal obligations.
last release 2026-07-21 (24 days) · last repo commit 2026-07-21 · 167 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 351,681 downloads/mo, #7,321 on PyPI
Alternatives
Verify before relying
pip install aiotools
import asyncio
import aiotools
async def main():
task = asyncio.create_task(asyncio.sleep(1))
await aiotools.cancel_and_wait(task)
asyncio.run(main())- Whether TaskScope exception handling is suitable for production long-running servers without manual result tracking.
- Performance characteristics when managing hundreds or thousands of concurrent tasks.
- Compatibility with asyncio subclasses or alternative event loop implementations.
What it is and what it does
aiotools is a collection of utilities designed to make asyncio programming more ergonomic and safer. It provides structured cancellation primitives (cancel_and_wait), async context manager decorators (@actxmgr), task lifecycle management (TaskScope), and server daemon patterns with automatic signal handling. The package targets vanilla asyncio and couples tightly with asyncio internals, making it most suitable for projects already committed to the standard library's async ecosystem.
The library addresses common pain points in asyncio code: coordinating cancellation without ambiguity about whether to re-raise CancelledError, writing async context managers without boilerplate classes, managing groups of concurrent tasks that complete even when siblings fail, and launching multi-process server daemons with proper lifecycle and signal handling. It depends only on async-lru and requires Python 3.11+, keeping the dependency footprint minimal.
Use it for
- Implement safe task cancellation in asyncio applications without manual CancelledError handling logic.
- Build async context managers and resource cleanup patterns using the @actxmgr decorator.
- Manage concurrent task groups where all tasks must run to completion unless explicitly cancelled.
- Launch multi-process asyncio server daemons with automatic SIGINT/SIGTERM handling.
- Create repeating async timers that can be cleanly cancelled and awaited to completion.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you are building asyncio applications on Python 3.11+ and want structured concurrency patterns and safer cancellation semantics.
The low install friction, active maintenance, MIT license, and zero known vulnerabilities make it a solid choice. Not necessary if you are using trio, anyio, or other async frameworks, or if you prefer managing task lifecycle manually.
Install
aiotools on PyPI
Before you install
Low install friction with a single lightweight runtime dependency (async-lru). Active maintenance with a release within the last month and consistent Python 3.11+ support.
Requires Python 3.11 or later; relies on asyncio internals so compatibility is tied to CPython versions.
License in practice
MIT license permits unrestricted use, modification, and distribution in both open-source and commercial projects with minimal obligations.
Quickstart
pip install aiotools
import asyncio
import aiotools
async def main():
task = asyncio.create_task(asyncio.sleep(1))
await aiotools.cancel_and_wait(task)
asyncio.run(main())Verify before relying
- Whether TaskScope exception handling is suitable for production long-running servers without manual result tracking.
- Performance characteristics when managing hundreds or thousands of concurrent tasks.
- Compatibility with asyncio subclasses or alternative event loop implementations.
Package facts
| License | MIT permissive |
| Python support | Supports the current Python release >=3.11 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | 1 packageasync-lru |
| Maintenance | Actively maintained 24 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 351,681 / month, #7,321 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 5 - Production/StableFramework :: AsyncIOIntended Audience :: DevelopersProgramming Language :: PythonProgramming Language :: Python :: 3Programming Language :: Python :: 3.11Programming Language :: Python :: 3.12Programming Language :: Python :: 3.13Programming Language :: Python :: 3.14Topic :: Software Development |
Evidence: aiotools-2.2.4-py3-none-any.whl
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See also aiojobs · aiometer · aiorun · aiomonitor · async-timeout · wait-for2 · async-exit-stack · aiologic · taskgroup · aiomcache