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Advanced Python Programming

You're reading from   Advanced Python Programming Build high performance, concurrent, and multi-threaded apps with Python using proven design patterns

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Product type Course
Published in Feb 2019
Publisher Packt
ISBN-13 9781838551216
Length 672 pages
Edition 1st Edition
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Authors (3):
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Quan Nguyen Quan Nguyen
Author Profile Icon Quan Nguyen
Quan Nguyen
Sakis Kasampalis Sakis Kasampalis
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Sakis Kasampalis
Dr. Gabriele Lanaro Dr. Gabriele Lanaro
Author Profile Icon Dr. Gabriele Lanaro
Dr. Gabriele Lanaro
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Table of Contents (41) Chapters Close

Title Page
Copyright
About Packt
Contributors
Preface
Benchmarking and Profiling FREE CHAPTER Pure Python Optimizations Fast Array Operations with NumPy and Pandas C Performance with Cython Exploring Compilers Implementing Concurrency Parallel Processing Advanced Introduction to Concurrent and Parallel Programming Amdahl's Law Working with Threads in Python Using the with Statement in Threads Concurrent Web Requests Working with Processes in Python Reduction Operators in Processes Concurrent Image Processing Introduction to Asynchronous Programming Implementing Asynchronous Programming in Python Building Communication Channels with asyncio Deadlocks Starvation Race Conditions The Global Interpreter Lock The Factory Pattern The Builder Pattern Other Creational Patterns The Adapter Pattern The Decorator Pattern The Bridge Pattern The Facade Pattern Other Structural Patterns The Chain of Responsibility Pattern The Command Pattern The Observer Pattern 1. Appendix 2. Other Books You May Enjoy Index

Summary


In this chapter, you learned about asynchronous programming, which is a model of programming that takes advantage of coordinating computing tasks to overlap the waiting and processing times. There are three main components to an asynchronous program: the event loop, the coroutines, and the futures. The event loop is in charge of scheduling and managing coroutines using its task queue. Coroutines are computing tasks that are to be executed asynchronously; each coroutine has to specify inside of its function exactly where it will give the execution flow back to the event loop (that is, the task-switching event). Futures are placeholder objects that contain the results obtained from the coroutines.

The asyncio module, together with the Python keywords async and await, provides an easy-to-use API and an intuitive framework to implement asynchronous programs; additionally, this framework makes the asynchronous code just as readable as synchronous code, which is generally quite rare in...

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