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Learn how to use Python’s async functions, threads, and multiprocessing capabilities to juggle tasks and improve the responsiveness of your applications.
Python lets you parallelize workloads using threads, subprocesses, or both. Here's what you need to know about Python's thread and process pools and Python threads after Python 3.13.
As this post has mentioned a few times, it is accompanied by a recently published tutorial on how to use Python asyncio, which we encourage anyone interested in using the technology to read.
Ruby and Python's standard implementations make use of a Global Interpreter Lock. Justin James explains the major advantages and downsides of the GIL mechanism.
Threads can provide concurrency, even if they're not truly parallel. In my last article, I took a short tour through the ways you can add concurrency to your programs. In this article, I focus on one ...
With such performance and multithreading issues, why still consider Python? There is, in fact, a very good reason. Python's saving grace: Shorter, cleaner code Python's saving grace can be found ...
I have worker thread(s) that use the logger. In the main thread, I occasionally need to ask the user to take some action. Which means I need to suppress the logger from actually printing until the ...
IPython Console - this is a powerful interactive Python shell. For example, it makes system commands available directly and it allows you to see plots inline. There are many good features of IPython.
Python's "multiprocessing" module feels like threads, but actually launches processes. Many people, when they start to work with Python, are excited to hear that the language supports threading. And, ...