aiomultiprocess
AsyncIO version of the standard multiprocessing module
Decision gist · record as of 2026-08-14
Yes, if you need true parallelism for async workloads and can tolerate dormant maintenance. The package is stable (no known vulnerabilities, clean install, permissive license), but the 843-day gap since last release means you should verify compatibility with your Python version and async libraries before committing. Best suited for production use when the performance gain justifies the added process overhead.AI-flagged interpretation of the facts on this page — verify before relying
Before you install
- Requires Python 3.8 or newer.
- Installs cleanly with no runtime dependencies.
- Maintenance is dormant—last release was 843 days ago—but the repository remains active with recent commits and no archived status, suggesting the package is stable rather than abandoned.
License · maintenance · safety
permissive license (permissive) — Licensed under MIT (permissive), so you can use, modify, and distribute the package freely in commercial or private projects without restriction.
last release 2024-04-23 (843 days) · last repo commit 2024-08-20 · 1,925 stars
0 known vulnerabilities (OSV.dev, 2026-08-14) · 4,799,965 downloads/mo, #2,226 on PyPI
Alternatives
Verify before relying
pip install aiomultiprocess
import asyncio
from aiomultiprocess import Pool
async def task(item):
return item * 2
async def main():
async with Pool() as pool:
async for result in pool.map(task, [1, 2, 3]):
print(result)
asyncio.run(main())- Whether the package works with modern Python versions (3.11+) given the dormant maintenance status.
- Performance gains in real-world scenarios compared to pure asyncio or multiprocessing alone.
- Compatibility with async libraries beyond aiohttp (e.g., httpx, asyncpg).
What it is and what it does
aiomultiprocess bridges AsyncIO and multiprocessing by spawning child processes, each running its own AsyncIO event loop. This lets you execute multiple async coroutines in parallel across CPU cores, avoiding the Global Interpreter Lock that limits pure AsyncIO to a single thread. The API mirrors Python's standard multiprocessing module, so it feels familiar: you create a Pool, map async functions over data, and iterate results as they complete.
The package is designed for workloads that benefit from both concurrency (many I/O operations) and parallelism (multiple CPU cores). Each worker process can handle multiple coroutines simultaneously, making it useful for tasks like gathering thousands of network requests or running CPU-intensive async operations. It requires Python 3.8+ and has no external runtime dependencies.
Use it for
- Fetching thousands of URLs concurrently across multiple processes to maximize throughput.
- Running CPU-bound async tasks (e.g., data processing) in parallel without GIL contention.
- Scaling async database queries across worker processes for high-concurrency workloads.
- Combining async I/O (aiohttp, asyncpg) with multiprocessing for hybrid I/O and CPU parallelism.
- Building async task queues that distribute work across multiple event loops.
Worth the install?
AI-flagged interpretation of the facts on this page. Verify before relying on it.
Yes, if you need true parallelism for async workloads and can tolerate dormant maintenance.
The package is stable (no known vulnerabilities, clean install, permissive license), but the 843-day gap since last release means you should verify compatibility with your Python version and async libraries before committing. Best suited for production use when the performance gain justifies the added process overhead.
Install
aiomultiprocess on PyPI
Before you install
Installs cleanly with no runtime dependencies. Maintenance is dormant—last release was 843 days ago—but the repository remains active with recent commits and no archived status, suggesting the package is stable rather than abandoned.
Requires Python 3.8 or newer.
License in practice
Licensed under MIT (permissive), so you can use, modify, and distribute the package freely in commercial or private projects without restriction.
Quickstart
pip install aiomultiprocess
import asyncio
from aiomultiprocess import Pool
async def task(item):
return item * 2
async def main():
async with Pool() as pool:
async for result in pool.map(task, [1, 2, 3]):
print(result)
asyncio.run(main())Verify before relying
- Whether the package works with modern Python versions (3.11+) given the dormant maintenance status.
- Performance gains in real-world scenarios compared to pure asyncio or multiprocessing alone.
- Compatibility with async libraries beyond aiohttp (e.g., httpx, asyncpg).
Package facts
| License | permissive license permissive |
| Python support | Supports the current Python release >=3.8 |
| Install friction | Low. Pure-Python wheel |
| Runtime dependencies | None |
| Maintenance | Dormant 843 days since the last release |
| Last repo commit | |
| First released | |
| Downloads | 4,799,965 / month, #2,226 on PyPI 30-day window, as of 2026-08-14 |
| Known vulnerabilities | None known OSV.dev, checked 2026-08-14 |
| Classifiers | Development Status :: 4 - BetaFramework :: AsyncIOIntended Audience :: DevelopersLicense :: OSI Approved :: MIT LicenseTopic :: Software Development :: Libraries |
Evidence: aiomultiprocess-0.9.1-py3-none-any.whl
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See also aioprocessing · mpire · multitasking · asyncio-pool · multiprocess · aioitertools · gilknocker · billiard · loky · caio