Logging and Debugging Your Live Trading Bot

When your crypto trading bot makes an unexpected trade at 3 AM, you need logs good enough to reconstruct exactly what happened. Poor logging is one of the leading causes of unresolved bugs in automated crypto trading systems.

Structured Logging

Use structured logging (JSON format) instead of plain text. Every log entry should include: timestamp, log level, component name, and relevant context fields like symbol, order ID, and price. This makes log analysis with tools like Elasticsearch or even grep dramatically easier.

import structlog\nlog = structlog.get_logger()\nlog.info("order_placed", symbol="BTCUSD", side="buy", qty=0.01, price=95000)

Log Levels

Use levels correctly. DEBUG for tick-by-tick data. INFO for order lifecycle events. WARNING for anomalies that don't require immediate action. ERROR for recoverable failures. CRITICAL for events requiring immediate human intervention in your algo trading system.

Post-Mortem Analysis

After any unexpected behavior, replay your logs in chronological order to reconstruct the bot's state. The best crypto algo trading course projects include a dedicated replay tool for exactly this purpose.