# omnilib/aiomultiprocess

Take a modern Python codebase to the next level of performance.

Repository: https://github.com/omnilib/aiomultiprocess
Canonical: https://ross.abutalabs.com/products/aiomultiprocess
Homepage: https://aiomultiprocess.omnilib.dev
Language: Python
License: MIT
License Family: permissive
Topics: python, python3, multiprocessing, asyncio, async, hacktoberfest
Last push: 2024-08-20T15:43:49+00:00

## Health v2 (maintenance only)
Score: 32/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 0, release rhythm 35, longevity 100
- inputs: {"age_days": 3069, "days_push": 743, "days_rel": null, "gap_med": null, "n_releases_24m": 0}
- flags: no_releases
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 1927, forks 107 (observed 2026-08-28T04:05:55.653275+00:00)

## What it is
A Python library that combines AsyncIO and multiprocessing, running a full event loop in each child process to maximize concurrency. It mimics the standard multiprocessing module API with async-friendly Pool and Worker interfaces.

## Use cases
- run thousands of network requests in parallel
- parallelize async workloads across CPU cores
- bypass the GIL for asyncio applications
- build a concurrent web scraper with aiohttp
- map coroutines over a pool of worker processes

## When to choose
- your workload is I/O-bound and benefits from both async concurrency and multi-core parallelism
- you want a multiprocessing-like API for async code
- you need to gather many network requests quickly

## When to avoid
- your workload is purely CPU-bound with no async I/O
- you need Windows-specific spawn behaviors with complex shared state
- you want a maintained library with frequent updates

## Facets
- artifact type: library
- maturity: maintenance
- function: concurrency
- domain: developer-tools, performance
- platform: python, cross-platform
- tags: asyncio, multiprocessing, parallelism, worker-pool

## Member repositories
- omnilib/aiomultiprocess (main) score 32

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:05:55.653275+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-30T03:09:10.226342+00:00, confidence not recorded.
  - readme: https://github.com/omnilib/aiomultiprocess (fetched 2026-08-28T04:05:55.653275+00:00, sha c57c82e8ad69)
  - registry_pypi: https://pypi.org/pypi/aiomultiprocess/json (fetched 2026-08-29T10:49:08.081371+00:00, sha ce9ecd8dd334)
- Data as of 2026-08-30T08:39:29.467469+00:00.