To help you get started, we've collected the most common ways that flower is being used within popular public projects.

benoitc / flower / test / test_scheduler.py View on Github

def f():
            rlist.append('f')
            return 1/0

        def g():
            rlist.append('bg')
            core.schedule()
            rlist.append('ag')

        def h():
            rlist.append('bh')
            core.schedule()
            rlist.append('ah')

        tg = core.tasklet(g)()
        tf = core.tasklet(f)()
        th = core.tasklet(h)()

        try:
            core.run()
        except ZeroDivisionError:
            rlist.append('E')
        core.schedule()
        core.schedule()

        assert rlist == "bg f E bh ag ah".split()

View more ways to use flower

Flower

Flower is an open-source web application for monitoring and managing Celery clusters. It provides real-time information about the status of Celery workers and tasks.

Features

• Real-time monitoring using Celery Events

  • View task progress and history
  • View task details (arguments, start time, runtime, and more)

• 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
  • Revoke or terminate tasks

• Broker monitoring

  • View statistics for all Celery queues

• HTTP Basic Auth, Google, Github, Gitlab and Okta OAuth

• Prometheus integration

• API

Installation

Installing flower with pip is simple :

$ pip install flower

The development version can be installed from Github :

$ pip install https://github.com/mher/flower/zipball/master#egg=flower

Usage

To run Flower, you need to provide the broker URL :

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

Or use the configuration of celery application :

$ celery -A tasks.app flower

By default, flower runs on port 5555, which can be modified with the port option :

$ celery -A tasks.app flower --port=5001

You can also run Flower using the docker image :

$ docker run -v examples:/data -p 5555:5555 mher/flower celery --app=tasks.app flower

In this example, Flower is using the tasks.app defined in the examples/tasks.py file

API

Flower API enables to manage the cluster via HTTP REST API.

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

For more info checkout API Reference

Documentation

Documentation is available at Read the Docs

License

Flower is licensed under BSD 3-Clause License. See the License file for the full license text.