The live example
ClearTrace: the neutral DEX execution-intelligence dashboard and API the book's methodology chapters draw on: cross-frontend attribution, sandwich detection, and execution-quality measurement across Ethereum, Base, Arbitrum, and Optimism.
Work along with the book
- Dune Analytics: make a free account; every query in the book runs on the free tier.
- Dune documentation: the query editor, DuneSQL reference, and table schemas.
- Spellbook: the open-source models behind
dex.tradesand the curated tables (Chapter 5). - Dune Data API: programmatic query execution, for Chapter 10's architecture.
The queries
Every runnable query from the book, live on Dune. Fork them, change the chain, break them, learn:
- eth-dex-health: the assembled dashboard from the end of Chapter 3: volume chart, smell-test table, and the what-this-measures text widget.
eth-dex-trades-preview: your first look at live trades (Chapter 3, query 1).eth-dex-daily-volume-7d: daily volume by venue, with the stacked bar chart (Chapter 3, query 2).eth-dex-trades-per-taker-7d: the trades-per-taker smell test (Chapter 3, query 3).quickstart-ch6-calldata-tail-probe: rank the most common call-data tails to surface integrator tags (Chapter 6).quickstart-ch7-sandwich-detector: the teaching sandwich detector, built on in-block ordering (Chapter 7).quickstart-ch7-wash-flow-symmetry: the flow-symmetry screen for wash-trading candidates (Chapter 7).quickstart-ch8-vwap-slippage: the address-pinned VWAP baseline and effective-slippage scoring (Chapter 8).
Going deeper
- A block explorer (e.g., Etherscan): verify any single transaction against the raw chain.
- The Graph: the subgraph/indexer layer from Chapter 2.
- Flashbots: the deepest public material on MEV, ordering, and private orderflow (Chapter 7).
Errata & updates
On-chain tooling moves fast. Corrections and post-publish changes to queries or table names are logged here, newest first.
- None yet. First edition, July 2026. Every query was verified against live Dune data at publication.
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The author
Andrew Maury is the founder of Rantum, a data science and ML studio that turns messy, adversarial data into models, APIs, and products that ship. More at andrewmaury.com.