Python
Advanced
Python Concurrency: Asyncio & Multiprocessing
Write high-throughput Python applications using event loops, thread pools, and process pools.
Course Overview
Understand GIL constraints, master `asyncio` task management, prevent race conditions, and leverage multi-core CPU scaling for parallel workloads.
What You Will Learn
Deconstruct the Python Event Loop, tasks, coroutines, and future objects
Bypass Global Interpreter Lock (GIL) limitations using `multiprocessing` and process pools
Manage thread pools safely with locking primitives, queues, and semaphores
Handle cancelled tasks, timeouts, and exception propagation in async gathering
Profile CPU-bound vs. I/O-bound bottlenecks to select optimal concurrency models
Tools & Technologies Used
Python 3.11
Asyncio
Concurrent.Futures
cProfile
HTTPX
Structured Curriculum
2 Modules · 4 Lessons · 210 Minutes Total
Module 1
Module 1: Asyncio Event Loop & Non-Blocking I/O
2 lessons
Module 1: Asyncio Event Loop & Non-Blocking I/O
Master async coroutines, task scheduling, and non-blocking I/O.
-
Event Loop Internals & Task Execution
Understand how the event loop multiplexes socket I/O without OS threads.
-
Gathering Tasks, Semaphores & Timeouts
Execute 100+ concurrent API requests safely using `asyncio.Semaphore`.
Module 2
Module 2: Multiprocessing, Threading & GIL Bypass
2 lessons
Module 2: Multiprocessing, Threading & GIL Bypass
Utilize multi-core CPUs for heavy computations and manage shared state.
-
ProcessPoolExecutor vs. ThreadPoolExecutor
Delegate CPU-bound math to worker processes and I/O tasks to thread pools.
-
Concurrency Debugging & Race Condition Prevention
Spot deadlocks, race conditions, and unhandled async exception warnings.
Practical Project & Capstone Outcome
🚀 Capstone Project
High-Throughput Concurrent Web Scraper & Parser Engine
Build an async web scraping service that fetches thousands of pages via `asyncio` and processes HTML parsing across multi-core process pools.
Prerequisites
- Python intermediate proficiency (functions, classes, exception handling)
Intended Audience
- Backend Developers building high-concurrency web services and scrapers
- Systems Engineers optimizing CPU-heavy Python data tools
Instructor Information
G
Gwen Tennyson
Course Author & Industry Expert
Gwen Tennyson is a Senior Python Core Systems Engineer who has architected high-concurrency infrastructure for streaming applications.
Frequently Asked Questions
Does Python 3.13 free-threaded (no-GIL) build affect this material?
The course covers both standard GIL mechanics and how future free-threading models interact with process pools.