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Learning Concurrency in Python

You're reading from   Learning Concurrency in Python Build highly efficient, robust, and concurrent applications

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Product type Paperback
Published in Aug 2017
Publisher Packt
ISBN-13 9781787285378
Length 360 pages
Edition 1st Edition
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Author (1):
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Elliot Forbes Elliot Forbes
Author Profile Icon Elliot Forbes
Elliot Forbes
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Table of Contents (13) Chapters Close

Preface 1. Speed It Up! FREE CHAPTER 2. Parallelize It 3. Life of a Thread 4. Synchronization between Threads 5. Communication between Threads 6. Debug and Benchmark 7. Executors and Pools 8. Multiprocessing 9. Event-Driven Programming 10. Reactive Programming 11. Using the GPU 12. Choosing a Solution

Future objects


Future objects are instantiated whenever we submit a task to an executor, such as how we submitted tasks to ThreadPoolExecutor in previous examples within this chapter. Future objects are objects that will, eventually, be given a value sometime in the future.

Methods in future objects

The future objects have the following methods with which we can access and modify them. Each of these methods will be covered in a full code sample further on in the chapter.

The result() method

The result() method gives us any returned values from the future object. This result method can be called like this:

futureObj.result(timeout=None)

By specifying the timeout parameter, we, basically, put a time limit on our future object. If the future object fails to complete in the given time frame, then a concurrent.futures. The timeout error is raised. This is quite useful, as it gives us more control in terms of capping the amount of time erroneous threads can execute for, and limiting the damage they...

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