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flower

Celery集群的实时监控和管理工具

Flower是一个为Celery集群开发的开源Web应用,专注于实时监控和管理。该工具可实时展示Celery工作节点和任务状态,支持远程控制操作,如工作节点配置调整和任务管理。此外,Flower还集成了消息代理监控、多种认证方式、Prometheus集成及API接口,为Celery用户提供全面的集群管理解决方案。

Flower

.. image:: https://img.shields.io/pypi/dm/flower.svg :target: https://pypistats.org/packages/flower :alt: PyPI - Downloads .. image:: https://img.shields.io/docker/pulls/mher/flower.svg :target: https://hub.docker.com/r/mher/flower :alt: Docker Pulls .. image:: https://github.com/mher/flower/workflows/Build/badge.svg :target: https://github.com/mher/flower/actions .. image:: https://img.shields.io/pypi/v/flower.svg :target: https://pypi.python.org/pypi/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 <http://www.pip-installer.org/>_ 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 <https://docs.celeryq.dev/en/stable/userguide/application.html>_ ::

$ 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 <https://github.com/mher/flower/blob/master/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_

.. _API Reference: https://flower.readthedocs.io/en/latest/api.html

Documentation

Documentation is available at Read the Docs_

.. _Read the Docs: https://flower.readthedocs.io

License

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

.. _License: https://github.com/mher/flower/blob/master/LICENSE

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