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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

Understanding the adapter pattern

The adapter pattern is a structural design pattern that helps us make two incompatible interfaces compatible. What does that really mean? If we have an old component and we want to use it in a new system, or a new component that we want to use in an old system, the two can rarely communicate without requiring code changes. But changing the code is not always possible, either because we don't have access to it or because it is impractical. In such cases, we can write an extra layer that makes all the required modifications for enabling communication between the two interfaces. This layer is called an adapter.

To further understand this design pattern, let's consider some real-life examples.

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Advanced Python Programming
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