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

Chapter 7: Implementing Concurrency

So far, we have explored how to measure and improve the performance of programs by reducing the number of operations performed by the central processing unit (CPU) through clever algorithms and more efficient machine code. In this chapter, we will shift our focus to programs where most of the time is spent waiting for resources that are much slower than the CPU, such as persistent storage and network resources.

Asynchronous programming is a programming paradigm that helps to deal with slow and unpredictable resources (such as users) and is widely used to build responsive services and user interfaces (UIs). In this chapter, we will show you how to program asynchronously in Python using techniques such as coroutines and reactive programming. As we will see, the successful application of these techniques will allow us to speed up our programs without the use of specialized data structures or algorithms.

In this chapter, we will cover the following...