Learning Concurrency in Python: Build highly efficient, robust, and concurrent applications

Description

Key Features • Build highly efficient, robust, and concurrent applications • Work through practical examples that will help you address the challenges of writing concurrent code • Improve the overall speed of execution in multiprocessor and multicore systems and keep them highly available Book Description Python is a very high level, general purpose language that is utilized heavily in fields such as data science and research, as well as being one of the top choices for general purpose programming for programmers around the world. It features a wide number of powerful, high and low-level libraries and frameworks that complement its delightful syntax and enable Python programmers to create. This book introduces some of the most popular libraries and frameworks and goes in-depth into how you can leverage these libraries for your own high-concurrent, highly-performant Python programs. We'll cover the fundamental concepts of concurrency needed to be able to write your own concurrent and parallel software systems in Python. The book will guide you down the path to mastering Python concurrency, giving you all the necessary hardware and theoretical knowledge. We'll cover concepts such as debugging and exception handling as well as some of the most popular libraries and frameworks that allow you to create event-driven and reactive systems. By the end of the book, you'll have learned the techniques to write incredibly efficient concurrent systems that follow best practices. What you will learn • Explore the concept of threading and multiprocessing in Python • Understand concurrency with threads • Manage exceptions in child threads • Handle the hardest part in a concurrent system — shared resources • Build concurrent systems with Communicating Sequential Processes (CSP) • Maintain all concurrent systems and master them • Apply reactive programming to build concurrent systems • Use GPU to solve specific problems 1. Speed It Up! 2. How About Parallel It? 3. Life of Thread 4. Synchronization Between Threads 5. Communication Between Threads 6. Debug and Benchmark Threads 7. Executors and Pools 8. Multiprocessing 9. Event-driven Programming 10. Reactive Programming 11. Using GPU 12. Choosing a Solution