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.

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 ...

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.

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 ...

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, ...