# RichardKnop/machinery

Machinery is an asynchronous task queue/job queue based on distributed message passing.

Repository: https://github.com/RichardKnop/machinery
Canonical: https://ross.abutalabs.com/products/machinery
Language: Go
License: MPL-2.0
License Family: copyleft
Topics: go, golang, task, task-scheduler, queue, amqp, rabbitmq, redis, memcached, mongodb, aws-sqs
Last push: 2025-11-15T04:07:03+00:00

## Health v2 (maintenance only)
Score: 59/100 (v2, computed 2026-09-03T02:20:16.233290+00:00)
- activity 52, release rhythm 44, longevity 100
- inputs: {"age_days": 4168, "days_push": 291, "days_rel": 376, "gap_med": 2.5, "n_releases_24m": 3}
- flags: none
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 7972, forks 934 (observed 2026-08-28T04:10:10.354905+00:00)

## What it is
Machinery is a Go library for asynchronous task and job queues built on distributed message passing. It supports multiple brokers (RabbitMQ, Redis, SQS, MongoDB, GCP PubSub) and provides workflows like groups, chords, chains, retries, and periodic tasks.

## Use cases
- run background jobs in go
- process tasks asynchronously with rabbitmq
- schedule periodic tasks in golang
- chain and group async workflows
- offload long-running work from http handlers
- distribute work across worker processes

## When to choose
- you need a celery-style task queue in Go
- you want pluggable brokers and result backends
- you need retries, delayed tasks, or workflow composition

## When to avoid
- you need a simple in-process job runner without a broker
- you want a standalone queue service rather than a library
- your stack is not Go

## Facets
- artifact type: library
- maturity: stable
- function: message-queue, scheduling, workflow-automation, concurrency
- domain: microservices, backend, developer-tools
- platform: go, cross-platform
- tags: task-queue, job-queue, background-jobs, amqp, rabbitmq, redis, sqs, worker-pool, celery-like, automation

## Member repositories
- RichardKnop/machinery (main) score 59

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:10:10.354905+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 2026-08-29T17:32:36.068441+00:00, confidence not recorded.
  - readme: https://github.com/RichardKnop/machinery (fetched 2026-08-28T04:10:10.354905+00:00, sha 4739151e5354)
- Data as of 2026-08-30T08:39:29.467469+00:00.