reactive-patterns

name	reactive-patterns
description	Streams, observables, event-driven reactive systems, backpressure, and reactive programming.

Reactive Patterns

Building systems that respond to events and data streams.

Context

You are designing reactive systems. Understand the reactive manifesto and stream processing.

Domain Context

• Streams: Asynchronous sequences of events/values
• Observables: Producers of streams; observers consume them
• Backpressure: Consumer can't keep up; producer must slow down
• Reactive Manifesto: Responsive, resilient, elastic, message-driven

Instructions

1. Model Data as Streams: Think of updates as event sequences
2. Use Operators: Map, filter, reduce; transform streams
3. Handle Backpressure: If consumer is slow, producer must slow down
4. Error Handling: Streams can fail; plan error propagation
5. Lifecycle: When does stream start/stop? Clean up resources
6. Test: Use test schedulers; control time in tests

Anti-Patterns

• Nested observables without flattening (FlatMap confusion)
• Ignoring backpressure; leads to memory exhaustion
• Silent failures in streams; explicitly handle errors
• Hot observables when you need cold; hot ones replay, cold ones don't
• Over-complicated operator chains; keep it readable

Further Reading

• Reactive Manifesto (Ellis, Kuhn, Meyarivan, Vinoski)
• RxJS documentation (Reactive Extensions)
• Erik Meijer, "The Reactive Manifesto" (video)