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Mastering Concurrency in Python

You're reading from   Mastering Concurrency in Python Create faster programs using concurrency, asynchronous, multithreading, and parallel programming

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Product type Paperback
Published in Nov 2018
Publisher Packt
ISBN-13 9781789343052
Length 446 pages
Edition 1st Edition
Languages
Concepts
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Author (1):
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Quan Nguyen Quan Nguyen
Author Profile Icon Quan Nguyen
Quan Nguyen
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Toc

Table of Contents (22) Chapters Close

Preface 1. Advanced Introduction to Concurrent and Parallel Programming FREE CHAPTER 2. Amdahl's Law 3. Working with Threads in Python 4. Using the with Statement in Threads 5. Concurrent Web Requests 6. Working with Processes in Python 7. Reduction Operators in Processes 8. Concurrent Image Processing 9. Introduction to Asynchronous Programming 10. Implementing Asynchronous Programming in Python 11. Building Communication Channels with asyncio 12. Deadlocks 13. Starvation 14. Race Conditions 15. The Global Interpreter Lock 16. Designing Lock-Based and Mutex-Free Concurrent Data Structures 17. Memory Models and Operations on Atomic Types 18. Building a Server from Scratch 19. Testing, Debugging, and Scheduling Concurrent Applications 20. Assessments 21. Other Books You May Enjoy

An example in Python

While we will go into more depth regarding how asynchronous programming can be implemented in Python and the main tools we will be using, including the asyncio module, let's consider how asynchronous programming can improve the execution time of our Python programs.

Let's take a look at the Chapter09/example1.py file:

# Chapter09/example1.py

from math import sqrt

def is_prime(x):
print('Processing %i...' % x)

if x < 2:
print('%i is not a prime number.' % x)

elif x == 2:
print('%i is a prime number.' % x)

elif x % 2 == 0:
print('%i is not a prime number.' % x)

else:
limit = int(sqrt(x)) + 1
for i in range(3, limit, 2):
if x % i == 0:
print('%i is not a prime number.' % x)
return

print('%i is a prime...
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