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

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README.rst

Celery Flower

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Flower is a web based tool for monitoring and administrating Celery clusters.

Features

  • Real-time monitoring using Celery Events

    • Task progress and history
    • Ability to show task details (arguments, start time, runtime, and more)
    • Graphs and statistics
  • Remote Control

    • View worker status and statistics
    • Shutdown and restart worker instances
    • Control worker pool size and autoscale settings
    • View and modify the queues a worker instance consumes from
    • View currently running tasks
    • View scheduled tasks (ETA/countdown)
    • View reserved and revoked tasks
    • Apply time and rate limits
    • Configuration viewer
    • Revoke or terminate tasks
  • Broker monitoring

    • View statistics for all Celery queues
    • Queue length graphs
  • HTTP API

  • Basic Auth and Google OpenID authentication

API

Flower API enables to manage the cluster via REST api, call tasks and receive task events in real-time via WebSockets.

For example you can restart worker's pool by:

$ curl -X POST http://localhost:5555/api/worker/pool/restart/myworker

Or call a task by:

$ curl -X POST -d '{"args":[1,2]}' http://localhost:5555/api/task/async-apply/tasks.add

Or terminate executing task by:

$ curl -X POST -d 'terminate=True' http://localhost:5555/api/task/revoke/8a4da87b-e12b-4547-b89a-e92e4d1f8efd

Or receive task completion events in real-time:

var ws = new WebSocket('ws://localhost:5555/api/task/events/task-succeeded/');
ws.onmessage = function (event) {
    console.log(event.data);
}

See detailed API documentation here.

Installation

To install, simply:

$ pip install flower

Usage

Launch the server and open http://localhost:5555:

$ flower --port=5555

Or launch from celery:

$ celery flower --address=127.0.0.1 --port=5555

Broker URL and other configuration options can be passed through the standard Celery options:

$ celery flower --broker=amqp://guest:guest@localhost:5672//

Docker Usage

Clone this repository, build flower from the Dockerfile, start the container and open http://localhost:49555:

$ docker build -t "flower" .
$ docker run -d -p=49555:5555 flower flower --port=5555

For more information about running with Docker see: http://docs.docker.io/en/latest/

Documentation

Documentation is available at Github Wiki and IPython Notebook Viewer

Screenshots

https://raw.github.com/mher/flower/master/docs/screenshots/dashboard.pnghttps://raw.github.com/mher/flower/master/docs/screenshots/pool.pnghttps://raw.github.com/mher/flower/master/docs/screenshots/tasks.pnghttps://raw.github.com/mher/flower/master/docs/screenshots/task.pnghttps://raw.github.com/mher/flower/master/docs/screenshots/monitor.png

More screenshots

Getting help

Please head over to #celery IRC channel on irc.freenode.net or open an issue.

Contributing

If you'd like to contribute, simply fork the repository, commit your changes, run the tests (python -m tests) and send a pull request. Make sure you add yourself to AUTHORS.

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