flower

What it is and what it does

Flower is a web application that connects to a Celery message broker and provides a real-time dashboard for monitoring and controlling distributed task clusters. It displays worker status, task progress, queue statistics, and scheduled tasks, and exposes both a web UI and a REST API for cluster management.

The package depends on Celery for task queue integration, Tornado for the web server, Prometheus-client for metrics export, humanize for readable output formatting, and pytz for timezone handling. It runs on port 5555 by default and supports multiple authentication methods including HTTP Basic Auth and OAuth providers. The tool is designed for developers and operators who need visibility into asynchronous task execution across multiple workers.

Use it for:

• Monitor task execution progress and history across a distributed Celery cluster in real time.
• Diagnose worker failures or performance issues by viewing worker statistics and currently running tasks.
• Programmatically manage worker pools, restart workers, or revoke/terminate stuck tasks via the REST API.
• Export Celery metrics to Prometheus for integration with existing monitoring and alerting systems.
• Control task rate limits, autoscaling, and queue assignments for individual workers from a central dashboard.

Worth the install?

AI-flagged interpretation of the facts on this page — verify before relying

Flower is a web-based monitoring and management dashboard for Celery task clusters, providing real-time visibility into worker status, task execution, and remote control capabilities.

Yes. Flower is actively maintained, has no known vulnerabilities, and is the de facto standard web UI for Celery cluster management. Install it if you run Celery in production or development and need visibility into task execution. The low install friction and permissive license make it a straightforward addition to any Celery setup.

Install

flower on PyPI

pip install flower

uv add flower

poetry add flower

Installing flower

Before you install

Low friction installation as a pure Python wheel. Actively maintained with recent commits and a mature codebase (first released in 2012). Depends on five runtime packages including celery, tornado, and prometheus-client, all well-established libraries.

License in practice

BSD permissive license allows use in commercial and proprietary projects with minimal restrictions. Suitable for most deployment scenarios without licensing concerns.

Quickstart

pip install flower

celery -A tasks.app flower

# Then access the web UI at http://localhost:5555

Requires a running Celery broker (e.g., RabbitMQ, Redis) and a Celery application to monitor.

Verify before relying

• Whether the REST API supports all task management operations described in the excerpt or if some are web-UI-only.
• Performance characteristics when monitoring very large numbers of workers or tasks.
• Whether OAuth providers (Google, Github, Gitlab, Okta) require additional configuration beyond basic auth.

Package facts

Evidence: flower-2.0.1-py2.py3-none-any.whl

Tags

More Distributed Computing packages