There’s more than one way to thread (or not to thread) a Python program. We point you to several threading resources, a fast new static type checker from Astral, a monkey patch for Pandas that ...

Learn how to use Python's threading module for concurrent programming, and how to create, manage, and synchronize threads in your code. Agree & Join LinkedIn ...

The threading module provides easy-to-use thread-based concurrency in Python. Unlike Python multiprocessing, the threading module is limited by the infamous Global Interpreter Lock (GIL). Critically, ...

In the realm of Python software development, two common approaches for managing concurrent operations are threading and asynchronous (async) programming. Both methods allow you to perform multiple ...

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 ...

The GIL is controversial because it only allows one thread at a time to access the Python interpreter. This means that it’s often not possible for threads to take advantage of multi-core systems.

An icon theme can have 1000s of icons, each of which is represented with a widget, all of which must all be shown in the main thread. Showing 1000s of icons will likely block your main thread for up ...

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. Multithreading and parallel ...

An experimental ‘no-GIL’ build mode in Python 3.13 disables the Global Interpreter Lock to enable true parallel execution in Python. Here’s where to start.