HL Wallet Analyzer

Real-time whale tracking & automatic copy trading for Hyperliquid DEX

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A self-hosted, real-time wallet tracker and automatic copy trading engine for Hyperliquid DEX. Track any number of whale wallets simultaneously, analyze their strategies with a mathematical rating system, and mirror their trades on virtual or live capital — from a single browser tab.

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Features

Wallet Analytics

• Multi-wallet tracking via persistent WebSocket connections
• Live positions, orders, P&L and ROE updated in real time
• TP/SL trigger orders with badges and trigger prices
• SQLite trade history with pagination, sorting and coin filter
• Cumulative PnL column in history
• "Since tracking" P&L — only trades after the wallet was added
• Coin breakdown: Since Tracking vs All Time tabs
• Activity analysis: hourly and daily trade charts
• Order price analysis: avg distance of limit price from mark at placement
• Multi-wallet dashboard with P&L leaderboard
• CSV export + Win/Loss streaks

Copy Trading Simulation

• Automatic copy engine running on virtual capital — zero real risk
• Proportional sizing: mirrors trader's position as % of their portfolio × your allocation
• Per-wallet allocation sliders (must sum ≤ 100%)
• Universal and per-wallet TP/SL
• Trader rating system (0–100, tiers S/A/B/C/D) with minimum rating filter
• Conflict resolution: opposite signals on same coin → higher-rated trader wins
• Full activity log explaining every action (COPY / SKIP / CLOSE / TP HIT / SL HIT / CONFLICT)
• Live virtual positions table with real-time P&L
• Closed trades history with full stats
• State persisted in localStorage between browser sessions

Hyperliquid Live Trading (hl_trading.py)

• Limit and market orders signed with EIP-712 via eth_account
• Close positions, cancel single or all orders
• TP/SL trigger order placement
• Leverage and isolated margin management
• Full balance, positions, and open orders via the Info API

Extended.exchange Live Trading (extended_trading.py)

• Limit and market orders on a Starknet perpetuals DEX
• Close positions, cancel single or all orders
• Account balance: collateral, equity, available margin
• Positions, open orders, and available markets listing
• Authentication via API Key + Stark signature (SNIP-12)

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Stack

| Layer | Tech | |---|---| | Backend | Python 3.13, Flask, flask-cors | | Async / WS | asyncio + websockets (daemon thread) | | Database | SQLite (WAL mode) | | Frontend | Vanilla JS, SSE (Server-Sent Events), Chart.js 4 | | HL API | REST https://api.hyperliquid.xyz/info, WS wss://api.hyperliquid.xyz/ws | | HL Trading | hyperliquid-python-sdk, eth_account (EIP-712) | | Extended | x10-python-trading, Starknet (SNIP-12) |

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Quick Start

git clone https://github.com/yourname/hl-wallet-analyzer.git
cd hl-wallet-analyzer
pip install -r requirements.txt
python web_app.py --port 5030

Open in browser: http://127.0.0.1:5030

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Usage

Analytics

1. In the Wallets section, click + Add → enter a 0x address
2. The wallet auto-subscribes to WebSocket — live data streams immediately
3. Click Analyze once to load full historical trades from the HL API
4. Switching between wallets uses the in-memory cache (no extra API calls)

Copy Trading Simulation

1. Go to API Trading → Simulation
2. Configure starting balance, allocations per wallet, TP/SL, and minimum rating
3. Click ▶ Start — the engine starts copying trades in real time via SSE

Hyperliquid Live Trading

from hl_trading import HLTrader

trader = HLTrader(private_key="0x...", account_address="0x...")
trader.place_limit_order("BTC", is_buy=True, size=0.001, price=60000)
trader.place_tp_sl("BTC", is_buy=False, size=0.001, tp_price=65000, sl_price=58000)
trader.close_position("BTC")

Extended Live Trading

from extended_trading import ExtendedTrader

trader = ExtendedTrader(vault="0x...", private_key="0x...", public_key="0x...", api_key="...")
trader.place_limit_order("BTC-USD", side="BUY", size="0.001", price="60000")
trader.close_position("BTC-USD")

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Project Structure

hl_wallet_analyzer/
├── web_app.py           # Flask server, DB, WS manager, all API routes
├── hl_analyzer.py       # Read-only CLI helper — DO NOT MODIFY
├── hl_trading.py        # Hyperliquid trading functions
├── extended_trading.py  # Extended.exchange trading functions
├── templates/
│   └── index.html       # Single-page app shell
├── static/
│   ├── app.js           # All frontend logic (~2350 lines)
│   └── style.css        # Styles
└── requirements.txt

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Trader Rating System

| Component | Weight | Formula | |---|---|---| | Win Rate | 35 pts | wins / total × 35 | | Profit Factor | 35 pts | min(gross_profit / (gross_loss + fees), 4) / 4 × 35 | | Experience | 20 pts | min(trade_count, 300) / 300 × 20 | | Consistency | 10 pts | (1 - max_loss_streak × 2 / max(trade_count, 1)) × 10 |

Tiers: S 80–100 · A 65–79 · B 50–64 · C 35–49 · D 0–34

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Notes

• Don't spam the Analyze button — Hyperliquid rate-limits at 429. Wallet switching uses cache
• Simulation runs client-side: it only works while the browser tab is open
• This is a Flask dev server — not for production deployment
• hl_trading.py and extended_trading.py require extra packages:

  pip install hyperliquid-python-sdk eth_account x10-python-trading
  

• For Extended, obtain Stark keys from Extended.exchange → Settings → API Management

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License

MIT

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💡 Tips: Finding & Analyzing Whale Wallets

Why Copy Trading Works on Hyperliquid

Hyperliquid is a fully on-chain perpetuals DEX — every trade, position, and fill is publicly visible in real time. Unlike CEXes where order flow is opaque, on Hyperliquid you can:

• See the exact entry and exit price of any wallet
• Watch position sizes and leverage in real time
• Observe TP/SL placement strategies
• Track funding payments and their timing
• Identify whether a trader scales in (DCA) or enters all at once

This makes it one of the few venues where copying a skilled trader is technically feasible with high fidelity.

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How to Find Interesting Whale Wallets

1. Hyperliquid Leaderboard

• Go to app.hyperliquid.xyz/leaderboard
• Filter by 30-day PnL or All-time PnL
• Focus on wallets with consistent returns, high trade count, no single "lucky" spike
• Copy the wallet address and paste it into this tool

2. On-chain Explorer

• Use hypurrscan.io to browse recent large fills
• Large-size fills from unknown wallets are worth investigating
• Look for wallets that trade multiple assets — it shows systematic thinking, not gambling

3. Social Signals

• Twitter/X: search for Hyperliquid PnL screenshots — traders often reveal their address
• Telegram alpha groups frequently post HL wallet addresses of known whales
• Cross-reference with the leaderboard to verify performance is real

4. Vault Tracking

• Hyperliquid Vaults are public managed strategies — their deployer address is trackable
• A vault with consistent inflows + high APY usually has a skilled manager behind it

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How to Analyze a Wallet with This Tool

Once you have an address:

1. Add the wallet → click + Add in the Wallets panel. WebSocket subscribes instantly.
2. Analyze → loads full fill history. Look at:
   • Win Rate and Profit Factor in the rating badge
   • Coin Breakdown → which coins the trader focuses on
   • Activity chart → what hours and days they trade (timezone clues)
   • Order Price Analysis → how far from mark they place limits (market-making vs directional)
3. Trade History → sort by Net PnL ↓ to find their best trades. What coin, what leverage, how long was it held?
4. Streak data → a long recent win streak may be a hot streak, not a permanent edge. Check streak vs total trade count ratio.
5. Since Tracking PnL → the most honest number: P&L since YOU started watching, not cherry-picked history.

Red flags to avoid:

• High all-time PnL but only 1–2 big trades (lucky, not skilled)
• Trades only during a specific bull run period
• High leverage (>20×) on every trade — eventually blows up
• Very few trades (<20) — not enough sample size

Green flags to copy:

• 100+ trades, consistent win rate >55%, profit factor >1.5
• Trades multiple coins, not just one
• Uses moderate leverage (5–15×)
• Regular activity across different market conditions

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Simulation-First Workflow (Recommended)

Before copying anyone with real money:

1. Add 3–5 wallet candidates to the tracker
2. Go to Simulation, set a virtual balance (e.g. $10,000), allocate across wallets
3. Run for at least 2 weeks — one trade is not a sample
4. Compare: who actually performed during the period YOU were watching?
5. Only promote a wallet to live trading after it proves itself in simulation

This protects you from past-performance bias — the leaderboard shows historical results, simulation shows real-time edge.