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Hyperliquid Trading Dashboard

A dashboard for real-time whale trades, liquidations, and trending tokens from Hyperliquid using Quicknode's Hypercore gRPC.

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Marco de trabajo/biblioteca de front-end:
Next.js
Idioma:
TypeScript
Herramienta de compilación/servidor de desarrollo:
npm
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Resumen

This sample app streams every trade from Hyperliquid via Quicknode's Hypercore gRPC and filters for whale trades, liquidations, and trending tokens. gRPC bidirectional streaming delivers data with sub-second latency, with no polling required.


Recursos adicionales

For video walkthrough of building the app, check out our video

Arquitectura​

      Quicknode Hypercore gRPC
        (stream every trade)
                  │
                  ▼
        ┌─────────────────┐
        │     Worker      │
        │  Filter + Agg   │
        └────────┬────────┘
                 │
    ┌────────────┼────────────┐
    ▼            ▼            ▼
 Whales    Liquidations   Trending
 (≥$50K)                  (1m buckets)
    │            │            │
    └────────────┼────────────┘
                 ▼
        ┌─────────────────┐
        │    PostgreSQL   │
        └────────┬────────┘
                 │
                 ▼
        ┌─────────────────┐
        │     Next.js     │
        │  [15m/30m/1h]   │
        └────────┬────────┘
                 │
                 ▼
        ┌─────────────────┐
        │    Dashboard    │
        └─────────────────┘

Características​


  • Whale trade detection (≥$50K notional, configurable)
  • Liquidation tracking with full metadata (user, mark price, method)
  • Trending tokens ranked by trade count with buy/sell breakdown
  • Time window filtering (15m, 30m, 1h)
  • Custom coin tracking, any Hyperliquid token
  • Volume sparklines with trend indicators
  • Explorer deep links for trade verification
  • 1-minute aggregation buckets for efficient trending queries

Requisitos previos​


  • Node.js 20+ installed
  • A PostgreSQL instance, you can use a platform like Aiven to spin up a hosted instance. We'll need this for DATABASE_URL.
  • Quicknode account with Hypercore gRPC endpoint. We'll need this for GRPC_ENDPOINT y AUTH_TOKEN.

Primeros pasos​

1. Clone and install​

git clone https://github.com/quiknode-labs/qn-guide-examples.git

cd qn-guide-examples/sample-dapps/hyperliquid-trading-dashboard

npm install

2. Start PostgreSQL​

If you are using a hosted PostgreSQL instance, skip this step.

npm run db:up

3. Configure environment​

export DATABASE_URL="postgresql://postgres:postgres@localhost:5432/hypercore"
export GRPC_ENDPOINT="your-endpoint.hype-mainnet.quiknode.pro:10000"
export AUTH_TOKEN="your_quicknode_token"

Note: Just paste these with values in two terminal windows. You'll need one window for the Next.js app and another for the database worker.

4. Initialize database​

npm run db:push

5. Start the worker​

npm run worker

This starts the worker process that:

  • Connects to Quicknode HyperCore gRPC
  • Streams live trading events
  • Stores raw trades and aggregated data in PostgreSQL
  • Tracks whale activity and liquidations

You should see:

Ping ok: { count: 1 }
Ingester running
WHALE_MIN_USD: 50000

6. Start the dashboard​

npm ejecutar dev

Open http://localhost:3000

Database​

PostgreSQL with Prisma ORM. Two tables:

  • TradeEvent - Individual whale trades and liquidations
  • TradeAggMinute - Per-minute aggregations for trending

Common commands:​

npm run db:up       # Start PostgreSQL container
npm run db:push     # Apply schema
npm run db:studio   # Open Prisma Studio

Puntos de conexión de la API​


  • GET /api/whales?coin=BTC&windowMin=15&thresholdUsd=50000 - Whale trades
  • GET /api/liquidations?windowMin=15 - Liquidations
  • GET /api/trending?windowMin=15 - Trending coins
  • GET /api/sparklines?windowMin=15&coins=BTC,ETH,SOL - Volume sparklines
  • GET /api/health - Health check

Vista previa

Vista previa

Más información​


Aportaciones y comentarios
¡Nos encantaría conocer tu opinión y agradecemos cualquier aportación a esta aplicación de ejemplo!
Para informar de problemas o enviar comentarios, abre una incidencia en GitHub en el qn-guide-ejemplos repositorio.
Para colaborar, sigue estos pasos:
  1. Hacer un fork del repositorio
  2. Crear una rama de características:
    git checkout -b feature/amazing-feature
  3. Guarda los cambios:
    git commit -m "Añadir una función increíble"
  4. Envía tu rama:
    git push origin feature/amazing-feature
  5. Abre una solicitud de incorporación de cambios.
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