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https://github.com/mher/flower

Real-time monitor and web admin for Celery distributed task queue
https://github.com/mher/flower

administration asynchronous celery monitoring python rabbitmq redis task-queue workers

Last synced: about 2 months ago
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Real-time monitor and web admin for Celery distributed task queue

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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 `_ 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`_



.. _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