Novaquant-labs

Novaquant-labs / hyperliquid-trading-bot

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github.comNovaquant-labshyperliquid-trading-bot algo-trading automated-trading crypto-bot cryptocurrency decentralized-finance
66
757
85% credibility
Found May 26, 2026 at 68 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
Python
AI Summary

This is an automated trading bot that runs a grid strategy on Hyperliquid, a decentralized exchange. Think of it like a smart assistant that places multiple buy and sell orders at different price levels around your target price. When the market moves up, your sell orders fill and you lock in profit. When it moves down, your buy orders fill and you average in. The bot automatically rebalances when prices move too far outside your range and includes safety features like maximum loss limits to protect your capital. It comes with learning examples showing how to interact with the exchange, and lets you practice on testnet with fake money before risking real funds.

How It Works

1
💡 You discover grid trading

You've heard about automated trading strategies that can profit from market swings by placing orders at different price levels.

2
📦 You download the bot

You grab the project from the internet and install it on your computer in just a few minutes.

3
🔐 You connect your wallet

You safely connect your trading wallet so the bot can place orders on your behalf.

4
⚙️ You choose your settings

You pick how many orders to place, how wide the price range should be, and how much of your money to risk.

5
How do you want to start?
🧪
Practice mode

Start on testnet with play money to learn the ropes without any risk

🚀
Live mode

Switch to real money when you feel confident about how the bot works

6
🤖 Your bot comes to life

The bot starts placing orders automatically, watching the market and adjusting as prices move.

🎉 Your trading runs hands-free

The bot handles your grid strategy 24/7, locking in profits when prices bounce between your levels.

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Star Growth

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AI-Generated Review

What is hyperliquid-trading-bot?

This is a grid trading bot for Hyperliquid, a decentralized perpetuals exchange. It automates the process of placing layered buy and sell orders around a target price, rebalancing when the market moves. The bot ships with built-in risk controls like drawdown limits, stop-loss, and take-profit triggers.

Built in Python with a TypeScript implementation included, the project combines a configurable YAML-based strategy system with WebSocket connectivity for real-time market monitoring. Beyond the main trading engine, it includes extensive learning examples covering the Hyperliquid API—from basic market data fetching to advanced copy-trading implementations with TWAP order mirroring.

Why is it gaining traction?

The educational depth sets this apart. Most trading bot repositories give you a black box. This one teaches you the API as you use it. The learning_examples directory walks through WebSocket connections, funding rate analysis, spot-perp arbitrage, and order management patterns—all with working code.

Dual language support (Python and TypeScript) means developers can prototype in Python and deploy in TypeScript without learning a new ecosystem. The YAML configuration system lets traders experiment with strategies without touching code, which lowers the barrier for non-developers.

The copy trading examples are particularly relevant given Hyperliquid's growing social trading ecosystem.

Who should use this?

Developers building on Hyperliquid who want to understand the API through practical examples rather than documentation. Traders comfortable with configuration files who want a grid strategy runner without writing trading logic from scratch. Teams evaluating Hyperliquid as a trading infrastructure provider will find the learning examples valuable for onboarding.

Not recommended for production trading without significant testing—66 stars and limited test coverage indicate an early-stage project.

Verdict

The credibility score of 0.8500000238418579% reflects solid architecture and active maintenance, but the low star count signals the community is still forming. If you're learning the Hyperliquid API, this is one of the best starting points available. For production trading, treat it as a foundation to build on rather than a turnkey solution.

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