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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
Languages
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

Improving our crawler


Now that we've had an in-depth look at both ThreadPoolExecutors and ProcessPoolExecutors, it's time to actually put these newly learned concepts into practice. In Chapter 5, Communication between Threads, we started developing a multithreaded web crawler that was able to crawl every available link on a given website.

Note

The full source code for this Python web crawler can be found at this link: https://github.com/elliotforbes/python-crawler.

It didn't, however, output the results in the most readable format, and the code could be improved using ThreadPoolExecutors. So, let's have a look at implementing both more readable code and more readable results.

The plan

Before we get started, we need to define a general plan as to how we are going to improve our crawler.

New improvements

A few examples of the improvements we might wish to make are as follows:

  • We want to refactor our code to use ThreadPoolExecutors
  • We want to output the results of a crawl in a more readable format such...
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