Python Async Programming 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.