So now that we've taken a look at the life cycle of a thread, it's important to know how these threads actually work within your machines. Understanding things like the multithreading model and how Python threads map to system threads is important if you are to make the right decisions when designing your high-performance software.
Learning Concurrency in Python
By :
Learning Concurrency in Python
By:
Overview of this book
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.
Table of Contents (13 chapters)
Preface
Free Chapter
Speed It Up!
Parallelize It
Life of a Thread
Synchronization between Threads
Communication between Threads
Debug and Benchmark
Executors and Pools
Multiprocessing
Event-Driven Programming
Reactive Programming
Using the GPU
Choosing a Solution
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