Colas de tareas asíncronas para Python
Brokers de mensajes distribuidos y librerías de procesamiento de trabajos para gestionar tareas en segundo plano en aplicaciones Python.
Colas de tareas asíncronas para Python
Encuentra los mejores repositorios con IA.Buscaremos los repositorios que mejor coincidan usando IA.
- rq/rq
rq/rq
10,653Ver en GitHubrq is a distributed task queue and background worker system for Python that uses a Redis backend to decouple task submission from execution. It functions as a reliable message queue and task scheduler, allowing Python functions or asyncio coroutines to be processed asynchronously across multiple worker processes. The project distinguishes itself through reliable queuing mechanisms that prevent job loss during worker crashes using atomic operations. It provides specialized orchestration capabilities, including the prevention of duplicate jobs, job execution prioritization, and the ability to m
rq is a well-established Python task queue and background job processor that uses Redis as its broker, supports asyncio coroutines, and provides scheduled tasks, automatic retries, result persistence, and monitoring—making it a comprehensive fit for this search.
PythonCron SchedulingJob Monitoring ToolsAutomatic Retry Mechanisms - coleifer/huey
coleifer/huey
5,933Ver en GitHub.. image:: https://media.charlesleifer.com/blog/photos/huey3-logo.png
Huey is a task queue for Python that supports Redis and SQLite backends with scheduling and retries, but its consumers use threads or greenlets rather than native asyncio, so it does not fully match the request for async/await-first libraries.
PythonTask Retry Policies - celery/celery
celery/celery
28,596Ver en GitHubCelery is an asynchronous job processor and distributed task queue designed to offload time-consuming operations to background worker nodes. By utilizing a message-passing architecture, it decouples task producers from consumers, allowing applications to maintain responsiveness while scaling workloads across multiple isolated environments. The system functions as a distributed workload orchestrator that manages the lifecycle of deferred operations through persistent queues. It distinguishes itself by providing a pluggable transport abstraction, which allows the core task logic to remain indep
Celery is a mature distributed task queue for Python, but its worker model is not asyncio-native—it relies on its own event loop or third-party integration—so while it squarely covers the task queue category, you may need additional setup for native async/await support.
PythonDistributed Task QueuesTask QueuesDistributed Task Processors
