Learn how to use Python’s async functions, threads, and multiprocessing capabilities to juggle tasks and improve the responsiveness of your applications.

Python knows that I/O can take a long time, and so whenever a Python thread engages in I/O (that is, the screen, disk or network), it gives up control and hands use of the GIL over to a different ...

Learn how to use asynchronous programming in Python 3.13 and higher. Get more done in less time, without waiting. Asynchronous programming, or async, is a feature of many modern languages that ...

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.

Go delivers faster execution and better concurrency for large-scale data tasks.Python offers simplicity and rich libraries ...

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 ...

Multithreaded Python applications don’t perform true parallel computing. Instead, they just create the illusion of parallelism. To achieve this, Python schedules a thread to run for a few CPU cycles, ...

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, ...