Projects Real-time data · Markets
Hyperliquid Heatmaps
A real-time map of where the leveraged positions on a decentralised exchange would be liquidated.
- Role
- Creator · data, backend, frontend and deployment
- Year
- 2026
- Tools
- Python · FastAPI · WebSockets · SQLite · React · Vite · Docker · AWS EC2
- Status
- Prototype · live demo
How to use it
It reproduces the original terminal and downloads live candles from Hyperliquid’s public API (BTC, ETH, SOL or HYPE, 15-minute or 1-hour). In each candle it spreads trading across typical leverage levels, from 5x to 100x, to estimate where the liquidations would sit; when the price crosses a level, that level disappears because those positions would already have closed. Filter by minimum leverage and read the liquidation book on the right: longs at risk below, shorts above.
It is an estimated model built on public data, not anyone’s real positions, and it is not investment advice.
In leveraged markets, every position has a price at which it closes by itself. If you know where those prices cluster, you know where the market may speed up. I built the map that shows it, in real time.
- 40
- Markets watched, chosen every day by volume
- 24/7
- Live listening to every trade on the exchange
- 3
- Views: heatmap, liquidation book and smart money
- AWS
- Deployed with Docker and its own domain
The idea
In perpetual futures almost everyone trades with leverage. A long position at 10x is liquidated automatically if the price falls 10%, and that forced sale pushes the price a little lower, which can liquidate the next one. That is why the levels where liquidations cluster act like magnets: when the price gets close, the move can speed up on its own.
On traditional exchanges that data is private. Hyperliquid is a decentralised exchange and its data is public: anyone can look up the positions of any wallet, including its liquidation price. The challenge is knowing which wallets to watch and turning millions of data points into something you understand at a glance.
How it works
- Choose the markets. Every day, the system asks the API for the universe of assets and their volume and keeps the 40 most traded, with no fixed lists.
- Discover wallets. A process connected by WebSocket listens to every trade on the exchange in real time. Each trade reveals the two wallets behind it, so the system discovers active wallets by itself.
- Read their positions. Another process goes through those wallets and stores, for each coin, the size, the side (long or short) and the liquidation price.
- Group by price. The backend (FastAPI) adds up the money that would be liquidated in each price band and serves it to the frontend (React), which paints it as heat bands behind the candles.
What it offered
- Liquidation heatmap over the price chart, with the volume at risk at each level.
- Liquidation book: how much long and short money is at stake above and below the current price.
- Smart-money tracking: the most profitable wallets and the positions they hold.
- Live market metrics: open interest, funding and volume.
All packaged with Docker and deployed on AWS with its own domain.
What I take away
How to turn a continuous stream of public data into a visual tool: choosing what to listen to, how to store it and how to show it so that someone understands it in five seconds.