0xArchive Examples
August 6, 2026 ยท View on GitHub
Notebook projects that turn 0xArchive market data into working analysis.
0xArchive is granular market data infrastructure for Hyperliquid and Lighter.xyz. Hyperliquid includes core perps, HIP-3 builder perps, HIP-4 outcome markets, and Hyperliquid Spot; Lighter.xyz is the second top-level venue API. Use these examples when you want to verify before wiring an SDK, building an API loop, or exporting Parquet from the Data Catalog.
Start Here
- Create an account at 0xArchive signup.
- Copy an API key from the dashboard.
- Choose the notebook that matches the dataset you want to inspect.
- Run the notebook once before adapting it into a pipeline.
cp .env.example .env
# Add OXARCHIVE_API_KEY=0xa_your_api_key to .env
Projects
| Project | Dataset | Venue scope | Tier | First output |
|---|---|---|---|---|
| Liquidation Heatmap | Liquidation events and price context | Hyperliquid | Free key for supported BTC workflows | Heatmap and scatter views of BTC liquidation clusters |
| Funding Rate Scanner | Funding rates and spread calculations | Hyperliquid and Lighter.xyz | Free key for supported BTC workflows | Cross-venue funding chart, spread bands, and carry view |
| HIP-3 Asset Dashboard | Funding, open interest, trades, candles | Hyperliquid HIP-3 | Free key for HIP-3 workflows | Dashboard for builder-perp price, flow, and derivatives context |
Liquidation Heatmap
cd liquidation-heatmap
pip install -r requirements.txt
cp .env.example .env
jupyter notebook liquidation_heatmap.ipynb
Outputs:
- Price-vs-time liquidation heatmap
- Long/short liquidation scatter plot
- Time-of-day and day-of-week views
- Size distribution and P99 cascade detection
Funding Rate Scanner
cd funding-rate-scanner
pip install -r requirements.txt
cp .env.example .env
jupyter notebook funding_rate_scanner.ipynb
Outputs:
- Hyperliquid vs Lighter funding comparison
- Funding spread with two-standard-deviation bands
- Annualized carry view
- Opportunity window and distribution summaries
HIP-3 Asset Dashboard
cd hip3-asset-dashboard
pip install -r requirements.txt
cp .env.example .env
jupyter notebook hip3_asset_dashboard.ipynb
Outputs:
- Hyperliquid HIP-3 funding, open interest, and trade-flow views
- Funding distribution and annualized APR view
- Volume, fill-count, and trade-size summaries
- Price, volume, and open-interest overlays
Choose Your Next Path
| If you want... | Go here |
|---|---|
| A recurring API loop | SDK docs |
| A shell or agent workflow | CLI docs |
| Claude Code, ChatGPT Codex, or other coding-agent context | AI Clients |
| File-based historical pulls | Data Catalog |
| Route, schema, and auth details | Quick Start, OpenAPI, llms.txt |
Links
Requirements
- Python 3.10+
- Jupyter Notebook
- An 0xArchive API key
No notebook should require secrets in source control. Keep API keys in local .env files only.