Skip to content

Module 07: Performance Patterns

← Module 06 | Topic Home | Next → Module 08

Status Difficulty Time

Stub module — Full content to be generated. This file defines the scope and prerequisites so the topic roadmap is complete.

Overview

Asyncio handles I/O concurrency elegantly, but production services have additional concerns: what happens when downstream dependencies are slow or unavailable? How do you prevent one slow consumer from overwhelming your service? This module covers the engineering patterns that turn a working async program into a reliable, high-throughput production service: connection pooling, rate limiting, circuit breakers, and backpressure.

Table of Contents

  1. Overview
  2. Prerequisites
  3. Objectives
  4. Theory
  5. Key Concepts
  6. Examples
  7. Common Pitfalls
  8. Cross-Links
  9. Summary

Prerequisites

  • Module 06: Structured Concurrency
  • Module 05: Synchronization Primitives
  • Module 04: Async I/O Patterns (especially aiohttp sessions)

Objectives

By the end of this module, you will be able to:

  1. Implement and configure HTTP connection pools with aiohttp.TCPConnector
  2. Build a token bucket rate limiter using asyncio.Semaphore and timers
  3. Implement a circuit breaker that stops sending requests to a failing service
  4. Apply backpressure to prevent overwhelming downstream services or memory
  5. Use asyncio.Queue(maxsize) for bounded producer-consumer pipelines
  6. Profile async programs to identify event loop blocking and I/O bottlenecks

Theory

Full content to be generated. Topics to cover:

  • Connection pooling: why it matters, aiohttp.TCPConnector options, limits
  • Rate limiting patterns: token bucket, sliding window; asyncio.Semaphore implementation
  • Circuit breaker pattern: closed / open / half-open states; implementation with Tasks
  • Backpressure: asyncio.Queue(maxsize=N) as a flow control mechanism
  • Retry with exponential backoff and jitter
  • Profiling async code: asyncio.set_event_loop_policy(), loop.slow_callback_duration
  • Detecting blocking calls with aiomonitor or custom instrumentation
  • Batching requests: combining multiple small requests into larger ones

Key Concepts

To be filled in when this module is fully generated.

Examples

To be filled in when this module is fully generated.

Common Pitfalls

To be filled in when this module is fully generated.

  • [[async-python/modules/06_structured-concurrency]] — prerequisite
  • [[async-python/modules/10_production-patterns]] — production patterns build on what is covered here
  • [[systems-architecture]] — circuit breakers and rate limiting are distributed systems patterns not specific to asyncio

Summary

To be filled in when this module is fully generated.