Async Programming with Python Training

Unlock Python's full concurrency potential with this focused 2-day training. Master asyncio from the ground up, understand event loops and coroutines, and build high-performance async applications for networking, APIs, and data processing.

Training Details

Duration	2 days (16 hours)
Level	Advanced
Delivery	In-person, Live online, Hybrid
Certification	N/A

Who Is This For?

• Python developers building high-concurrency applications
• Backend engineers optimizing API throughput
• DevOps engineers writing async tooling and automation
• Anyone working with I/O-bound Python workloads

Learning Outcomes

After completing this training, participants will be able to:

• Write correct async/await code with asyncio coroutines and tasks
• Understand the event loop lifecycle and execution model
• Use concurrent.futures for thread-based and process-based parallelism
• Implement structured concurrency with TaskGroups and cancellation
• Build async clients for HTTP, databases, and message queues
• Debug and profile async applications for performance bottlenecks

Detailed Agenda

Day 1: asyncio Foundations

Module 1: Concurrency in Python

• Concurrency vs parallelism vs asynchrony
• The GIL and its impact on threading
• When to use async vs threads vs processes
• Hands-on: Compare throughput of sync, threaded, and async approaches

Module 2: Coroutines and the Event Loop

• async def, await, and coroutine lifecycle
• The event loop: how it schedules and executes tasks
• Running coroutines with asyncio.run and loop management
• Hands-on: Build an async web scraper from scratch

Module 3: Tasks and Concurrency Primitives

• Creating and managing tasks with asyncio.create_task
• Gathering results with asyncio.gather and asyncio.wait
• TaskGroups for structured concurrency (Python 3.11+)
• Hands-on: Fetch data from multiple APIs concurrently with error handling

Module 4: Synchronization and Flow Control

• Locks, semaphores, and events for coordination
• Queues for producer-consumer patterns
• Rate limiting and backpressure strategies
• Hands-on: Build a rate-limited concurrent API client

Day 2: Production Async Applications

Module 5: concurrent.futures and Mixed Concurrency

• ThreadPoolExecutor for blocking I/O in async code
• ProcessPoolExecutor for CPU-bound work
• Bridging sync and async with run_in_executor
• Hands-on: Parallelize a CPU-intensive data processing pipeline

Module 6: Async I/O and Networking

• Async HTTP with aiohttp and httpx
• Async database access with asyncpg and SQLAlchemy async
• Async file I/O with aiofiles
• Hands-on: Build an async microservice that reads from a database and calls external APIs

Module 7: Error Handling and Cancellation

• Exception propagation in async contexts
• Task cancellation and CancelledError handling
• Timeouts with asyncio.timeout and asyncio.wait_for
• Graceful shutdown patterns
• Hands-on: Add robust error handling and graceful shutdown to an async server

Module 8: Debugging and Performance

• Async debugging with asyncio debug mode
• Profiling event loop utilization
• Identifying blocking calls and slow coroutines
• Common async pitfalls and anti-patterns
• Hands-on: Profile and optimize an async application with performance issues

Prerequisites

• Strong Python programming experience
• Solid understanding of functions, classes, and exceptions
• Familiarity with generators and iterators
• Basic networking concepts (HTTP, TCP) helpful

Delivery Formats

Format	Description
In-Person	On-site at your company's location, hands-on with direct interaction
Live Online	Interactive virtual sessions with screen sharing and real-time labs
Hybrid	Combination of on-site and remote sessions, flexible scheduling

All formats include hands-on labs, course materials, async pattern reference, and post-training support.