Book Image

Advanced Python Programming - Second Edition

By : Quan Nguyen
Book Image

Advanced Python Programming - Second Edition

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)
1
Section 1: Python-Native and Specialized Optimization
8
Section 2: Concurrency and Parallelism
18
Section 3: Design Patterns in Python

The concept of deadlocks

In concurrent programming, a deadlock refers to a specific situation in which no progress can be made, and the program becomes locked in its current state. In most cases, this phenomenon is caused by a lack of, or mishandled, coordination between different lock objects (for thread synchronization purposes). In this section, we will discuss a thought experiment, commonly known as the dining philosophers problem, to illustrate the concept of a deadlock and its causes; from there, you will learn how to simulate the problem in a Python concurrent program.

The dining philosophers problem

The dining philosophers problem was first introduced by Edgar Dijkstra, a leading pioneer in concurrent programming, in 1965. This problem was first demonstrated using different technical terms (resource contention in computer systems) and was later rephrased by Tony Hoare, a British computer scientist and the inventor of the quicksort sorting algorithm. The problem statement...