Interactive Brokers Algotrading

Knowledge base for building production-grade algorithmic trading systems with Interactive Brokers TWS API and ib_async in Python.

When to Use

• Connecting to TWS or IB Gateway with ib_async
• Implementing real-time market data subscriptions
• Designing order execution logic (bracket orders, order lifecycle)
• Handling pacing violations for historical data requests
• Building reconnection resilience for 24/7 production bots
• Deploying IB trading systems on Windows with IBC + Task Scheduler
• Debugging TWS API error codes (162, 200, 201, 354, 1100-1102)

Quick Start

For 80% of use cases, start with:

1. Connection: IB Gateway (headless, lower resources) + IBC (automated lifecycle)
2. Library: pip install ib_async (asyncio-native successor to ib_insync)
3. Data: reqRealTimeBars for live 5-sec bars with local aggregation
4. Orders: Bracket orders with transmit=False pattern
5. Resilience: disconnectedEvent + exponential backoff reconnection
6. Deployment: IBC + Windows Task Scheduler for auto-restart

Then harden incrementally:

• Missing fills on reconnect -- add reqExecutions() reconciliation
• Pacing violations -- add asyncio.Semaphore throttled request queue
• Overnight crashes -- add IBC auto-restart + heartbeat monitoring
• State drift -- add periodic position/order reconciliation via reqPositions()

Reference Materials

• tws-api-architecture.md -- TWS API 10.44, Gateway vs TWS, Client Portal, ib_async setup, clientId strategy, official docs
• event-driven-data.md -- reqMktData, reqRealTimeBars, reqTickByTickData, keepUpToDate, OHLCV construction, pacing violations, historical data
• order-execution.md -- order types, bracket orders, lifecycle states, execDetails monitoring, race conditions, error codes
• reconnection-resilience.md -- daily reset, IBC automation, reconnect patterns, heartbeat, Windows deployment, community resources

Key Decision Points