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Understanding Python's Garbage Collection: Mechanics of Reference counting in Python

Understanding Python's Garbage Collection: Mechanics of Reference counting in Python

资源信息 | Information

英语| 2018年3月20日| ASIN:B07BMDD7MP | 156页| AZW3 | 0.97 MB

自20世纪90年代构思以来,Python语言已经走过了漫长的道路。今天,Python是一流的企业语言,可以构建从Raspberry Pi应用程序到复杂配置服务器和大型应用程序的任何东西。

Python的兴起源于技术和新架构方法的集合,例如机器学习(ML)和人工智能(AI)的进步,以及微服务和容器。这些技术的集合产生了Python 3,允许企业在整个开发生命周期中使用它,而不仅仅是研究。

最值得注意的是快速增长是其多用途性质。与其他专注于一个利基领域的语言不同,Python几乎可用于任何领域系统操作,科学建模,Web开发和ML。在大规模软件开发方面,没有像Python这样多功能的语言。

但是,关于Python的一个经常被误解但非常重要的特性是垃圾收集(GC)。垃圾收集在Python程序的行为中扮演着不可或缺的角色,但大多数开发人员经常把它放在一边。

除了理解Python GC的工作原理外,Python开发人员还必须了解他们在编程中可以采取的操作(如调优GC)如何影响他们正在开发的应用程序的整体可伸缩性,可靠性和运行时性能。

但是,Python GC是如何工作的?

更具体地说,“如何在Python中开发高度可扩展,可靠且速度更快的应用程序?”

本书深入研究了最新的Python垃圾收集器,为您提供了如何在Python中处理垃圾收集,现代商业系统中使用的不同算法以及如何最大限度地提高Python应用程序性能的全景图。该书分为7章,内容如下:

•第1章探讨了Python的基础知识,包括如何在主要平台上安装并开始使用;

•第2章深入探讨了探索不同语言的垃圾收集机制;

•第3章介绍Python及其垃圾收集算法;

•第4章比较Python和其他语言中的垃圾收集;

•第5章探讨了分析Python应用程序的过程;

•第6章概述了如何优化大规模Python应用程序;和

•第7章提供了有关Python和垃圾收集的未来见解。

最后,本书回顾了Python的垃圾收集系统,以帮助您理解平衡吞吐量,响应性,空间和不同规模级别的可用内存需求所涉及的权衡。欢迎。


English | March 20, 2018 | ASIN: B07BMDD7MP | 156 pages | AZW3 | 0.97 MB

Python language has come a long way ever since it was conceived in the 1990s. Today, Python is a first-class enterprise language that can build anything from Raspberry Pi apps to complex configuration servers and large scale applications.

The rise of Python has come about as a result of a conglomeration of technologies and new architectural approaches such as advancements in Machine Learning (ML) and Artificial Intelligence (AI), and microservices and containers. The conglomeration of these technologies has given rise to Python 3 that allows businesses to use it throughout the entire development lifecycle and not just research.

Most notable for the fast growth is its multi-purpose nature. Unlike other languages that focus on one niche area, Python can be used in virtually any domain—system operations, scientific modeling, web development and ML. When it comes to large scale software development, there is no language as versatile as Python.

But one feature which has often been misunderstood—and yet very important—about Python is Garbage Collection (GC). Garbage Collection plays an integral role in the behavior of Python programs, yet most developers often brush it aside.

Besides understanding how Python GC works, Python developers must also understand how the actions they can take in programming such as tuning GC can affect the overall scalability, reliability and run-time performance of apps they are developing.

But, how does Python GC work?

And more specifically, “How can you develop highly scalable, reliable and faster applications in Python?”

This book delves deeper into the latest Python Garbage Collector to provide you with a big picture view of how garbage collection is handled in Python, different algorithms used in modern commercial systems and how you can maximize the performance of Python applications. The book has been organized into 7 chapters as follows:

•Chapter 1 explores the basics of Python including how to install on major platforms and get you started;

•Chapter 2 delves deeper to explore garbage collection mechanisms in different languages;

•Chapter 3 introduces Python and its garbage collection algorithms;

•Chapter 4 compares garbage collection in Python and other languages;

•Chapter 5 explores the process of profiling Python applications;

•Chapter 6 provides an overview of how you can optimize large scale Python applications; and

•Chapter 7 provides future insights about Python and garbage collection.

Ultimately, the book reviews the Python’s garbage collection system to help you understand the trade-offs involved in balancing requirements for throughput, responsiveness, space, and the available memory across different scale levels. Welcome.

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