celeryviz_frontend_core 0.0.5

This is the core UI library for the CeleryViz project

CeleryViz Frontend Core

The core Flutter UI library for the CeleryViz project.

This package contains the rendering engine and UI logic behind CeleryViz. It consumes Celery events in JSON format and visualises task execution flow — showing tasks, their states, dependencies, and logs — in a clean, interactive interface. It is designed to be wrapped around other data-source projects rather than used standalone.

👉 Try the Live Demo

📦 Part of the CeleryViz ecosystem →

Quick Start

Clone and install dependencies:

git clone https://github.com/bhavya-tech/celeryviz_frontend_core.git
cd celeryviz_frontend_core
flutter pub get

Run the recommended example (reads a local .ndjson recording — no backend needed):

cd example/ndjson_example
flutter run

Or run against a live backend via Socket.IO:

cd example/socketio_datasource
flutter run

📖 Full development setup guide →

What it does

• Renders task flow: Visualises Celery tasks, their states, and dependencies from a stream of JSON events
• Real-time updates: Connects to a live backend over Socket.IO and renders tasks as they execute
• Offline replay: Accepts .ndjson recordings so you can replay and inspect past task runs
• Embeddable: Designed as a library — wrap it around any data source (Socket.IO, file, custom)
• Cross-platform: Built with Flutter; runs on web, Linux, macOS, and Windows

Examples

Two ready-to-run examples are included in the example/ folder:

Example	Description
ndjson_example	Reads a saved .ndjson recording of Celery events and renders the visualisation. Best for UI development.
socketio_datasource	Connects to a running CeleryViz backend over Socket.IO for live task monitoring.

Used by

This library powers celeryviz_with_lib, which packages the frontend for the CeleryViz Python library.

Roadmap

• Desktop app: A standalone desktop application for use in development environments or for connecting to remote servers
• Persistent backend: A backend that stores Celery events and serves them to the frontend on demand, enabling both real-time monitoring and historical debugging

Contributing

Contributions are welcome! Please read CONTRIBUTING.md before submitting a PR.

• Frontend issues → open an issue here
• Python library issues → open an issue on celeryviz

License

Apache 2.0

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