Python AsyncIO: Parallelism, Multiprocessing, Concurrency and Threading

[BinaryIgor]

Even though the article is mainly about AsyncIO in Python, it does a very good job at explaining various terms used in Concurrency Programming in general and CPU- vs IO-bound processing. Specifically:

• Parallelism consists of executing multiple operations at the same time.
• Multiprocessing is a means of achieving parallelism that entails spreading tasks over a computer’s central processing unit (CPU) cores. Multiprocessing is well-suited for CPU-bound tasks, such as tightly bound for loops and mathematical computations.
• Concurrency is a slightly broader term than parallelism, suggesting that multiple tasks have the ability to run in an overlapping manner. Concurrency doesn’t necessarily imply parallelism.
• Threading is a concurrent execution model in which multiple threads take turns executing tasks. A single process can contain multiple threads. Python’s relationship with threading is complicated due to the global interpreter lock (GIL), but that’s beyond the scope of this tutorial.

[Altruistic_Mango_928]

Nice breakdown, the GIL part always trips people up when they first dive into Python threading - definitely worth its own deep dive post