celeryviz_frontend_core 0.0.5

This is the core UI library for the CeleryViz project

example/README.md

celeryviz_frontend_core Examples

This directory contains example Flutter apps demonstrating how to integrate celeryviz_frontend_core into your own project.

Quick Start

Each example is a standalone Flutter app. To run any of them:

cd example/<example_name>
flutter pub get
flutter run

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Examples

1. ndjson_example

What it does: Reads Celery events from a local .ndjson file and renders the task visualization, no running backend is needed.

Best for: Offline development, testing with recorded event data, or exploring the visualization without setting up a server.

How to run:

cd example/ndjson_example
flutter pub get
flutter run

If you need to run custom ndjson file, place your .ndjson file (Celery events in JSON format, one event per line) in the app's assets folder and update the path in the app config.

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2. socketio_datasource

What it does: Connects to a live backend server via Socket.IO and renders the Celery task visualization in real-time as events stream in.

Best for: Monitoring a live Celery deployment, or testing with the celeryviz Python backend.

How to run:

cd example/socketio_datasource
flutter pub get
flutter run

Make sure your backend server is running and emitting Celery events in JSON format. Update the server URL in the app config before running if its not on localhost or standard port 9095.

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Minimal Integration Example

To use celeryviz_frontend_core in your own Flutter app:

pubspec.yaml

dependencies:
  celeryviz_frontend_core: ^0.0.4

main.dart

import 'package:flutter/material.dart';
import 'package:celeryviz_frontend_core/celeryviz_frontend_core.dart';

void main() {
  runApp(const MyApp());
}

class MyApp extends StatelessWidget {
  const MyApp({super.key});

  @override
  Widget build(BuildContext context) {
    return MaterialApp(
      home: CeleryVizApp(
        dataSource: YourDataSource(), // plug in your own data source
      ),
    );
  }
}

See the individual example apps above for complete implementations using an ndjson file or a Socket.IO connection.

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Related

• celeryviz : Python backend that emits Celery events consumed by this library.
• celeryviz_with_lib : Packaged frontend built on top of this library.
• Live Demo