Advanced Python: Sharing Data In Parallel And Concurrent Python Applications
Learn How To Use Python Synchronisation Primitives
Most of the enterprise-level high-performant computationally-intensive applications are concurrent and parallel in nature. The advanced features of concurrency and parallelism are usually used to enhance the performance of an application.
One of the biggest challenges in the concurrent and parallel applications is to be able to share the data between threads, asyncio routines, and/or processes.
This is where we can use the synchronization primitives. This article will aim to explain what they are and when to use them.
Article Aim
This article will help us understand what Python Synchronisation Primitives are which can be used to share the data between processes/threads/tasks.
I will start by providing a brief overview of concurrency and parallelism concepts in general. I will then provide an overview of the basic synchronisation primitives along with the information on when to use them.
This is an advanced level topic for Python developers and I recommend it to everyone who is/or intends in using the Python programming language.
