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Advanced Python Programming

Advanced Python Programming - Second Edition

By : Quan Nguyen
4.6 (14)
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Advanced Python Programming

Advanced Python Programming

4.6 (14)
By: Quan Nguyen

Overview of this book

Python's powerful capabilities for implementing robust and efficient programs make it one of the most sought-after programming languages. In this book, you'll explore the tools that allow you to improve performance and take your Python programs to the next level. This book starts by examining the built-in as well as external libraries that streamline tasks in the development cycle, such as benchmarking, profiling, and optimizing. You'll then get to grips with using specialized tools such as dedicated libraries and compilers to increase your performance at number-crunching tasks, including training machine learning models. The book covers concurrency, a major solution to making programs more efficient and scalable, and various concurrent programming techniques such as multithreading, multiprocessing, and asynchronous programming. You'll also understand the common problems that cause undesirable behavior in concurrent programs. Finally, you'll work with a wide range of design patterns, including creational, structural, and behavioral patterns that enable you to tackle complex design and architecture challenges, making your programs more robust and maintainable. By the end of the book, you'll be exposed to a wide range of advanced functionalities in Python and be equipped with the practical knowledge needed to apply them to your use cases.
Table of Contents (32 chapters)
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1
Section 1: Python-Native and Specialized Optimization
8
Section 2: Concurrency and Parallelism
18
Section 3: Design Patterns in Python

Chapter 14: Race Conditions

In this chapter, we will discuss the concept of race conditions and their potential causes in the context of concurrency. The definition of a critical section, which is a concept highly relevant to race conditions and concurrent programming, will also be covered. We will use some example code in Python to simulate race conditions and the solutions that are commonly used to address them. Finally, real-life applications that commonly deal with race conditions will also be discussed.

In this chapter, we will cover the following topics:

  • The concept of race conditions
  • Simulating race conditions in Python
  • Locks as a solution to race conditions
  • Race conditions in real life

This chapter, similar to the previous two chapters, offers a closer look at what could go wrong in concurrent programming and exposes us to a wide range of approaches in terms of how to avoid and prevent that. In this chapter, our focus will be on race conditions...

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Advanced Python Programming
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