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Learning Concurrency in Python

Learning Concurrency in Python

By : Forbes
3.3 (3)
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Learning Concurrency in Python

Learning Concurrency in Python

3.3 (3)
By: Forbes

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)
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ProcessPoolExecutor


ProcessPoolExecutors can be used and created in much the same way as your standard ThreadPoolExecutors. It subclasses the Executor class the same way the ThreadPoolExecutor class does, and thus, features many of the same methods within it.

Creating a ProcessPoolExecutor

The process for creating a ProcessPoolExecutor is almost identical to that of the ThreadPoolExecutor except for the fact that we have to specify that we've imported that class from the concurrent.futures module, and that we also instantiate our executor object like this:

executor = ProcessPoolExecutor(max_workers=3)

Example

The following example features a very simple full example of how you can instantiate your own ProcessPoolExecutor and submit a couple of tasks into this pool. It should be noted that our task function here isn't that computationally expensive, so we may not see the full benefit of using multiple processes, and it could, in fact, be significantly slower than your typical single-threaded process...

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