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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
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Dr. Gabriele Lanaro
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Table of Contents (41) Chapters Close

Title Page
Copyright
About Packt
Contributors
Preface
Benchmarking and Profiling Pure Python Optimizations FREE CHAPTER 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

The concept of a thread


In the field of computer science, a thread of execution is the smallest unit of programming commands (code) that a scheduler (usually as part of an operating system) can process and manage. Depending on the operating system, the implementation of threads and processes (which we will cover in future chapters) varies, but a thread is typically an element (a component) of a process.

Threads versus processes

More than one thread can be implemented within the same process, most often executing concurrently and accessing/sharing the same resources, such as memory; separate processes do not do this. Threads in the same process share the latter's instructions (its code) and context (the values that its variables reference at any given moment).

The key difference between the two concepts is that a thread is typically a component of a process. Therefore, one process can include multiple threads, which can be executing simultaneously. Threads also usually allow for shared resources...

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