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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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Concepts
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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

Threads in Python


Before we jump into more detail about the life of a thread, I feel it's important to know what we are going to be instantiating in real terms. In order to know this, however, we'll need to have a look at Python's Thread class definition which can be found in threading.py.

Within this file, you should see the class definition for the Thread class. This has a constructor function which looks something like this:

# Python Thread class Constructor
def __init__(self, group=None, target=None, name=None,
args=(), kwargs=None, verbose=None):

This preceding constructor takes in five real arguments, which are defined within that class definition as follows:

  • group: This is a special parameter which is reserved for a future extension.
  • target:This is the callable object to be invoked by the run() method. If not passed, this will default to None, and nothing will be started.
  • name:This is the thread name.
  • args:This is the argument tuple for target invocation. It defaults to ().
  • kwargs: This is...
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