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

Introducing the GIL

The GIL is quite popular in the Python concurrent programming community. Designed as a lock that will only allow one thread to access and control the Python interpreter at any given time, the GIL in Python is often known as the infamous GIL that prevents multithreaded programs from reaching their fully optimized speed.

In this section, we will discuss the concept behind the GIL, as well as its purpose: why it was designed and implemented and how it affects multithreaded programming in Python.

Analyzing memory management in Python

Before we jump into the specifics of the GIL and its effects, let's consider the problems that Python core developers encountered during the early days of Python that gave rise to a need for the GIL. Specifically, there is a significant difference between Python programming and programming in other popular languages, in terms of managing objects in the memory space.

For example, in the programming language C++, a variable...