Get Multithreaded Programming

Python does not support multithreading as the CPython interpreter does not support multi-core execution through multithreading. It will not allow you to use the extra CPU cores.

Before C++ 11, there is no built-in support for multithreaded applications. Instead, it relies entirely upon the operating system to provide this feature. This tutorial assumes that you are working on Linux OS and we are going to write multi-threaded C++ program using POSIX.

Python doesn't support multi-threading because Python on the Cpython interpreter does not support true multi-core execution via multithreading. However, Python does have a threading library. The GIL does not prevent threading.

Multithreading in Python. If your code is IO bound, both multiprocessing and multithreading in Python will work for you. Python multiprocessing is easier to just drop in than threading but has a higher memory overhead.

What is MultiThreading? Multithreading enables us to run multiple threads concurrently. For example in a web browser, we can have one thread which handles the user interface, and in parallel we can have another thread which fetches the data to be displayed. So multithreading improves the responsiveness of a system.

Multiprocessing in Python is a built-in package that allows the system to run multiple processes simultaneously. It will enable the breaking of applications into smaller threads that can run independently.

Python is NOT a single-threaded language. Python processes typically use a single thread because of the GIL. Despite the GIL, libraries that perform computationally heavy tasks like numpy, scipy and pytorch utilise C-based implementations under the hood, allowing the use of multiple cores.

Another example of a multithreaded program that we are all familiar with is a word processor. While you are typing, multiple threads are used to display your document, asynchronously check the spelling and grammar of your document, generate a PDF version of the document.