Workers Python Packages

rq

Simple job queues for Python

flower

Real-time monitor and web admin for Celery distributed task queue

python-pq

Job queue for Python backed by Postgres. Process-per-task fork isolation, transactional enqueueing, periodic tasks, priority queues. No broker required.

meesee

Task queue, Long lived workers for work based parallelization, with processes and Redis as back-end. For distributed computing.

sosw

Serverless Orchestrator of Serverless Workers for AWS - Worker

litestar-queues

Task queues, workers, schedules, and backend integrations for Litestar

haki-ya-kazi-mcp

MCP server for Kenya labour rights — minimum wages, dismissal, maternity/paternity, trade unions, ELRC. 5 tools.

astraapi

FastAPI-compatible Python web framework with a compiled C++20 core. Built-in multi-process workers, zero-copy I/O, native dependency injection, and WebSocket support. No Starlette. No ASGI server required. Python 3.14+.

blitzq

A high-performance, framework-agnostic asyncio task queue backed by Redis.

atasker

Python library for modern thread / multiprocessing pooling and task processing via asyncio

celery-connectors

Want to handle 100,000 messages in 90 seconds? Celery and Kombu are that awesome - Multiple publisher-subscriber demos for processing json or pickled messages from Redis, RabbitMQ or AWS SQS. Includes Kombu message processors using native Producer and Consumer classes as well as ConsumerProducerMixin workers for relay publish-hook or caching

rqmonitor

Flask based more dynamic and actionable frontend dashboard for monitoring Redis Queue 👩🏿‍💻 http://python-rq.org

ippy

:rocket: Ping IP addresses and domains in parallel to find the accessible and inaccessible ones.

booltest

BoolTest - polynomial randomness tester

neotasker

Lightweight workers and task management library for Python

django-inngest

Scheduled & background tasks will never be the same once you use Inngest. That's why I made this integration. I'm a fan.

worker-dispatcher

A lightweight Python concurrency framework to orchestrate multi-threaded and multi-processed tasks with a unified API.

machineid-io

Official Python SDK for MachineID - simple device registration and validation for AI agents.

taskq-py

Async-native, Postgres-backed background job library for Python 3.12+

pool-workers

Pool_Workers is a small python package for managing pools, workers, and queues with ease.

pgrelay

PostgreSQL-backed transactional outbox and background jobs for Python — no extra broker needed

flower-with-timeline

Real-time monitor and web admin for Celery distributed task queue

flower-patch

Real-time monitor and web admin for Celery distributed task queue

futurepool

FuturePool is a package that introduce known concept of multiprocessing Pool to the async/await world. It allows for easy translation from multiprocessing to async/await, while keeping the core principle - specified number of workers. FuturePool allows for more flexible usage by providing starimap/starimap_unordered.