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

Summary

In this chapter, we have seen how to use two other creational design patterns: the prototype and the singleton.

A prototype is used to create exact copies of objects. As seen in the implementation example we discussed, using a prototype in Python is natural and based on built-in features, so it is not something even mentioned. The singleton pattern can be implemented by making the singleton class use a metaclass, its type, having previously defined said metaclass. As required, the metaclass's __call__() method holds the code that ensures that only one instance of the class can be created.

Overall, these two design patterns help us implement the use cases that other creational patterns do not support; in effect, we have grown our design pattern toolbox to cover more use cases.

The next chapter is about the adapter pattern, a structural design pattern that can be used to make two incompatible software interfaces compatible.