Learning Path ⋅ Skills: Python, Concurrency, Async IO, Global Interpreter Lock, Thread Safety, Parallel Processing, Performance Optimization, Multithreading, Code Efficiency
Unlock Python’s full potential with our concurrency and async programming path. Explore concurrency techniques, the Global Interpreter Lock, async IO, thread safety, and parallel processing to boost your program’s performance.
Learning Path ⋅ 7 Resources
#1
Course
Speed Up Python With ConcurrencyLearn what concurrency means in Python and why you might want to use it. You'll see a simple, non-concurrent approach and then look into why you'd want threading, asyncio, or multiprocessing.
#2
Course
Understanding Python's Global Interpreter Lock (GIL)Python's Global Interpreter Lock or GIL, in simple words, is a mutex (or a lock) that allows only one thread to hold the control of the Python interpreter at any one time. In this video course you'll learn how the GIL affects the performance of your Python programs.
#3
Course
Threading in PythonIn this intermediate-level course, you'll learn how to use threading in your Python programs. You'll see how to create threads, how to coordinate and synchronize them, and how to handle common problems that arise in threading.
#4
Course
Thread Safety in Python: Locks and Other TechniquesLearn about the issues that can occur when your code is run in a multithreaded environment. Then you'll explore the various synchronization primitives available in Python's threading module, such as locks, which help you make your code safe.
#5
Tutorial
Getting Started With Async Features in PythonThis step-by-step tutorial gives you the tools you need to start making asynchronous programming techniques a part of your repertoire. You'll learn how to use Python async features to take advantage of IO processes and free up your CPU.
#6
Course
Hands-On Python 3 Concurrency With the asyncio ModuleLearn how to speed up your Python 3 programs using concurrency and the asyncio module in the standard library. See step-by-step how to leverage concurrency and parallelism in your own programs, all the way to building a complete HTTP downloader example app using asyncio and aiohttp.
#7
Tutorial
Bypassing the GIL for Parallel Processing in PythonIn this tutorial, you'll take a deep dive into parallel processing in Python. You'll learn about a few traditional and several novel ways of sidestepping the global interpreter lock (GIL) to achieve genuine shared-memory parallelism of your CPU-bound tasks.
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