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Python 3 Object-Oriented Programming - Second Edition

You're reading from   Python 3 Object-Oriented Programming - Second Edition Building robust and maintainable software with object oriented design patterns in Python

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Product type Paperback
Published in Aug 2015
Publisher Packt
ISBN-13 9781784398781
Length 460 pages
Edition 1st Edition
Languages
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Author (1):
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Dusty Phillips Dusty Phillips
Author Profile Icon Dusty Phillips
Dusty Phillips
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Table of Contents (15) Chapters Close

Preface 1. Object-oriented Design FREE CHAPTER 2. Objects in Python 3. When Objects Are Alike 4. Expecting the Unexpected 5. When to Use Object-oriented Programming 6. Python Data Structures 7. Python Object-oriented Shortcuts 8. Strings and Serialization 9. The Iterator Pattern 10. Python Design Patterns I 11. Python Design Patterns II 12. Testing Object-oriented Programs 13. Concurrency Index

Futures

Let's start looking at a more asynchronous way of doing concurrency. Futures wrap either multiprocessing or threading depending on what kind of concurrency we need (tending towards I/O versus tending towards CPU). They don't completely solve the problem of accidentally altering shared state, but they allow us to structure our code such that it is easier to track down when we do so. Futures provide distinct boundaries between the different threads or processes. Similar to the multiprocessing pool, they are useful for "call and answer" type interactions in which processing can happen in another thread and then at some point in the future (they are aptly named, after all), you can ask it for the result. It's really just a wrapper around multiprocessing pools and thread pools, but it provides a cleaner API and encourages nicer code.

A future is an object that basically wraps a function call. That function call is run in the background in a thread or process....

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