Automation

How to Build a Perp Trading Bot (Python Tutorial)

This tutorial outlines a research-oriented Python bot skeleton for market observation and alerts. It is not financial advice and does not recommend live trading automation. This article is educational research only, not financial advice, not a recommendation, and no trading advice.

Automation Amplifies Operational Risk

Bots can misread stale data, exceed rate limits, or submit unintended transactions if guards are weak. Start with read-only observation and paper-style dry runs.

  • Are API keys scoped to read-only where possible?
  • Is there a kill switch if signals or connectivity fail?
  • Have you logged and reviewed every automated action in dry-run mode?

Tutorial Architecture Outline

A typical research bot includes: configuration for venue endpoints, a data fetcher for funding and order-book snapshots, normalization layer, alert dispatcher (webhook or log), risk guard module (position caps, rate limits), and structured logging. Python libraries often used include requests, asyncio, and pandas for research notebooks—confirm compatibility with each venue's current API docs.

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Publication Notes

API shapes and authentication methods change. Verify against current venue developer documentation before any deployment.

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