Skip to main content

A Celery Beat Scheduler using Redis for persistent storage

Project description

PyPI Actions Status ReadTheDocs Code style: black

RedBeat is a Celery Beat Scheduler that stores the scheduled tasks and runtime metadata in Redis.

Why RedBeat?

  1. Dynamic live task creation and modification, without lengthy downtime

  2. Externally manage tasks from any language with Redis bindings

  3. Shared data store; Beat isn’t tied to a single drive or machine

  4. Fast startup even with a large task count

  5. Prevent accidentally running multiple Beat servers

For more background on the genesis of RedBeat see this blog post

Getting Started

Install with pip:

pip install celery-redbeat

Configure RedBeat settings in your Celery configuration file:

redbeat_redis_url = "redis://localhost:6379/1"

Then specify the scheduler when running Celery Beat:

celery beat -S redbeat.RedBeatScheduler

RedBeat uses a distributed lock to prevent multiple instances running. To disable this feature, set:

redbeat_lock_key = None

More details available on Read the Docs

Development

RedBeat is available on GitHub

Once you have the source you can run the tests with the following commands:

pip install -r requirements.dev.txt
py.test tests

You can also quickly fire up a sample Beat instance with:

celery beat --config exampleconf

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

celery-redbeat-2.0.0.tar.gz (15.3 kB view details)

Uploaded Source

File details

Details for the file celery-redbeat-2.0.0.tar.gz.

File metadata

  • Download URL: celery-redbeat-2.0.0.tar.gz
  • Upload date:
  • Size: 15.3 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/1.13.0 pkginfo/1.5.0.1 requests/2.21.0 setuptools/44.1.1 requests-toolbelt/0.9.1 tqdm/4.31.1 CPython/2.7.16

File hashes

Hashes for celery-redbeat-2.0.0.tar.gz
Algorithm Hash digest
SHA256 cb8d6941be5df2666dd3188c3029c74e0fa33d50de6eaf7da88e0a5b591a190c
MD5 c72178712619403d974a049467788e97
BLAKE2b-256 e020987307ee16027465806f21c51654fc32dcbdce9bfbaefb0af4973147acdb

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page