Until recently, you could speed up your programs by simply running them on newer, faster hardware. Now, instead of making CPU’s faster, hardware makers are adding more CPU cores to your computing devices. To make programs run faster today, employing concurrency techniques to get your programs running on multiple cores simultaneously is paramount. In this course, Getting Started with Python Concurrency, you’ll learn how to make your Python programs more efficient, responsive, and faster using Python’s concurrency packages. First, you’ll explore how to choose the right concurrency package for your task. Next, you’ll discover how to distribute a task to worker processes to speed up execution by running on multiple cores. Finally, you’ll cover how to do node.js style asynchronous programming using the asyncio package. When you’re finished with this course, you’ll have a solid understanding of concurrency concepts and how to apply them in Python in a simple and readable manner to achieve greater performance results.
Author Name: Tim Ojo
Author Description:
Tim Ojo is a software developer with a fondness for building scalable backend applications in Java, C#, Python, and Scala. He actively contributes to the developer community by blogging and speaking about topics, such as search engines, recommender systems, databases like Cassandra and Neo4j, general developer best practices, and data science. He considers himself a lifelong learner, that’s what drove him to create podcastdiscovery.net, a website for finding tech podcasts to listen to via search… more

Table of Contents

• Course Overview
  1min
• Concurrency Concepts
  19mins
• Threading
  46mins
• Multiprocessing
  37mins
• Abstracting Concurrency
  15mins
• Asynchronous Programming
  38mins