Extending R

出版者:Chapman and Hall/CRC

作者:John M. Chambers

页数:382

出版时间:2016-5-26

价格:USD 69.95

装帧:Paperback

isbn号码:9781498775717

具体描述

Features

Shows how the essential of R can benefit small- to large-scale projects

Includes complete coverage of object-oriented programming in R, allowing users to exploit this powerful computing technique using all the R features

Presents new and extended interfaces to other software, such as C++ and Julia

Provides the interfaces, tools, and example packages on GitHub

Summary

Up-to-Date Guidance from One of the Foremost Members of the R Core Team

Written by John M. Chambers, the leading developer of the original S software, Extending R covers key concepts and techniques in R to support analysis and research projects. It presents the core ideas of R, provides programming guidance for projects of all scales, and introduces new, valuable techniques that extend R.

The book first describes the fundamental characteristics and background of R, giving readers a foundation for the remainder of the text. It next discusses topics relevant to programming with R, including the apparatus that supports extensions. The book then extends R’s data structures through object-oriented programming, which is the key technique for coping with complexity. The book also incorporates a new structure for interfaces applicable to a variety of languages.

A reflection of what R is today, this guide explains how to design and organize extensions to R by correctly using objects, functions, and interfaces. It enables current and future users to add their own contributions and packages to R.

作者简介

John M. Chambers is a consulting professor in the Department of Statistics at Stanford University. He previously worked at Bell Labs for 40 years, where he contributed to major research and management in statistical computing and related fields. He was the first statistician to be named a Bell Labs Fellow.

Chambers is best known for the creation and extension of the S software, the predecessor to today’s very popular R. He has continued to contribute essential new directions to R. In 1999, he was honored with the ACM Software System Award, which noted that "S has forever altered the way people analyze, visualize, and manipulate data."

He is a board member of the R Foundation and the R Consortium; a fellow of the ASA, the IMS, and the AAAS; and an elected member of the ISI. He is the author or co-author of nine books, including the first comprehensive book on computational methods for statistics.

目录信息

Table of Contents
Understanding R
Objects, Functions and Interfaces
Three Principles
Everything is an Object
Everything is a Function Call
Interfaces are Part of R
Functional Programming
Object-Oriented Programming
Evolution
Computational Methods
The First Version of S
Functional, Object-Based S
R Arrives and Evolves
Evolution of Object-Oriented Programming
Functional OOP in S and R
S4 and R
R in Operation
Objects and References
Function Calls
Interfaces
The R Evaluator
Programming with R
Small, Medium and Large
Functions
Functional Programming and R
Assignments and Replacements
Computing on the Language
Interfaces and Primitives
Getting it to Run Faster
Objects
Types and Attributes
Object Management
Reference Objects; Environments
Packages
Understanding Packages
Installing a Package
Loading and Attaching a Package
Sharing your Package
In the Large
Object-Oriented Programming
Classes and Methods in R
OOP Software in R
Functional and Encapsulated OOP
Creating Classes in R
Creating Methods in R
Example: Classes for Models
Functional OOP in R
Functional OOP in Extending R
Defining Classes
Defining Methods and Generic Functions
Classes and Methods in an R Package
Functional Classes in Detail
Generic Functions in Detail
Functional Methods in Detail
S3 Methods and Classes
Encapsulated OOP in R
The Structure of Encapsulated OOP
Using Encapsulated OOP
Defining Reference Classes
Fields in Reference Classes
Methods in Reference Classes
Functional Methods for Reference Classes
Interfaces
Understanding Interfaces
Introduction
Available Interfaces
Subroutines and Evaluators
Server Language Software
Server Language Computations
Server Language Object References
Data Conversion
Interfaces for Performance
The XR Structure for Interfaces
Introduction
The XR Interface Structure
Evaluator Objects and Methods
Application Programming
Specializing to the Server Language
Proxy Objects
Proxy Functions and Classes
Data Conversion
An Interface to Python
R and Python
Python Computations
Python Programming
Python Functions
Python Classes
Data Conversion
An Interface to Julia
R and Julia
Julia Computations
Julia Programming
Julia Functions
Julia Types
Data Conversion
Subroutine Interfaces
R, Subroutines and C++
C++ Interface Programming
C++ Functions
C++ Classes
Data Conversion
Bibliography
Index
· · · · · · (收起)

用户评价

这本书的阅读体验非常独特，它不像市面上很多技术书籍那样，一上来就抛出大量的代码示例让你模仿。相反，它更像是一位经验丰富的老教授，坐在你对面，娓娓道来他对于R生态系统长期观察和思考的结果。我发现自己花了大量时间在思考作者提出的那些“如果……会怎样”的假设性问题上。例如，书中有一部分探讨了R的解析器如何处理复杂的符号替换，这部分内容极其晦涩，充满了前瞻性的理论推导，但完全没有提供一个可以直接复制粘贴运行的解决方案。它似乎在引导读者跳出“如何使用”的舒适区，转而思考“为什么是这样”的底层逻辑。读完关于垃圾回收机制的那一章后，我清晰地意识到，过去我写的一些优化代码，其实是治标不治本。这本书提供的知识，更像是一种对工具箱进行“定制化改造”的蓝图，而非直接递给你一把已经磨好的瑞士军刀。它的价值在于重塑你的思维框架，而非简单的技能传授。

拿到这本期待已久的《Extending R》时，我的心跳不自觉地加速了。这本书的封面设计简洁而富有力量感，那种深邃的蓝色调仿佛预示着即将踏入一个广阔而未知的领域。我首先被其厚重的质感所吸引，这并非那种轻飘飘的纸质书，而是充满了沉甸甸的知识分量。迫不及待地翻开扉页，目录结构清晰地勾勒出一条从基础概念到高级应用的进阶路径。我特别关注了其中关于“面向对象编程在R中的实践”这一章节的描述，它似乎没有直接探讨如何扩展R的核心功能，反而更倾向于用一种哲学的高度来审视R语言的设计哲学。这让我感到有些意外，因为我原本期望看到更多关于C++或Fortran接口的实用技巧。书中对数据结构深入到内存层面的剖析，虽然理论性极强，但对于理解R内部机制的“黑箱”操作提供了绝佳的视角。它并非一本速成手册，更像是一份严谨的学术研讨录，要求读者具备扎实的计算机科学背景才能完全领会其精髓。

在读完最后几章关于包结构化管理和版本兼容性策略的讨论后，我深切体会到作者的良苦用心。他没有直接提供一个快速生成高级包的模板，而是深入剖析了历史上一些著名R包在演化过程中遇到的棘手问题，并基于此提炼出了一套高阶的工程实践规范。这种“以史为鉴”的叙述手法非常高明，它让原本枯燥的规范变得生动起来。书中的案例研究部分，涉及的都是一些非常小众但技术复杂度极高的领域，比如高维空间数据索引的定制化实现，这显然超出了普通数据分析师的日常工作范畴。这本书给我的最大感受是，它提供了一个“内行人看门道”的视角。它没有教我如何成为一名R程序员，而是告诉我，一个真正能“扩展”R的人，需要具备何种深度的系统认知和工程素养。它更像是为未来的R语言架构师准备的参考书，而非为今天的R用户准备的工具手册。

坦白说，这本书的阅读门槛着实不低，它似乎是为那些已经将R用得出神入化，开始感到现有工具箱无法满足特定高性能计算需求的人准备的。书中对并行计算框架的论述，采用了非常抽象的数学建模方式来阐释，而非简单介绍`parallel`包的使用方法。我花了整整一个下午才搞懂作者是如何将分布式内存模型映射到R的环境变量中的。其中关于如何构建自定义S3/S4类的新颖方法论，远超出了我之前所学的任何面向对象教程。它没有告诉我如何定义一个新类，而是从构建一个“自洽的、可扩展的”对象系统应该具备哪些核心要素入手。这种宏观的、自顶向下的讲解方式，虽然在初读时令人费解，但一旦顿悟，那种豁然开朗的感觉是无与伦比的。它迫使我必须去查阅大量相关的操作系统和编译原理资料，这感觉更像是在进行一场跨学科的知识迁移，而非单纯的R语言学习。

这本书的排版和图示设计，透露出一种对细节的偏执追求。每一张用来解释数据流动的流程图，都经过了精心的设计，线条的粗细、颜色的深浅都似乎经过了严密的计算，旨在最大限度地减少读者的认知负荷。然而，正是这种高度的抽象化，使得某些核心概念的实际应用显得扑朔迷离。书中用了一个篇幅来讨论如何设计一个能够自动适应不同硬件架构的计算后端，整个讨论过程充满了对性能瓶颈的哲学思辨，而非具体的代码优化实例。我期望看到更多关于如何利用现代CPU特性（如SIMD指令集）来加速R代码的秘籍，但这本书似乎认为，理解底层原理比掌握特定技巧更为重要。这使得本书更像是一本理论指导手册，而非实战操作指南。对于那些急需解决手头性能问题的用户来说，这本书提供的可能是“治本之策”，但过程可能会略显漫长和曲折。