How to Build a Production-Ready Polymarket Arbitrage Bot in Python

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A production-grade Polymarket arbitrage bot requires more than checking if two prices sum below $1 — it must account for fees, liquidity, partial fills, and execution risk. The recommended architecture separates market data ingestion, strategy detection, risk management, and execution into distinct layers, preventing the strategy from directly controlling the exchange client. Real-time order book data is consumed via Polymarket's public WebSocket channel using the CLOB V2 trading stack and the official py-clob-client-v2 Python library. Fee-aware opportunity detection compares the combined executable cost of YES and NO legs against the fixed $1 payout, filtering out trades that do not clear a minimum edge threshold. Critical risk controls include position size limits, stale-book timeouts, one-leg fill timeouts, daily loss limits, and emergency shutdown mechanisms to manage two-leg execution exposure.

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