C++ software interoperability for Windows programmers: connecting to C#, R, and Python clients / Adam Gladstone.
Gladstone, Adam.
2022
QA76.73.C153
Available Online

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Title C++ software interoperability for Windows programmers: connecting to C#, R, and Python clients / Adam Gladstone.
Author Gladstone, Adam.
ISBN 9781484279663 (electronic bk.)
1484279662 (electronic bk.)
1484279654
9781484279656
DOI https://doi.org/10.1007/978-1-4842-7966-3
Publication Details New York : Apress, 2022.
Language English
Description 1 online resource
Item Number 10.1007/978-1-4842-7966-3 doi
Call Number QA76.73.C153
Dewey Decimal Classification 005.13/3
Summary Get up-to-speed quickly and connect modern code written in C#, R, and Python to an existing codebase written in C++. This book for practitioners is about software interoperability in a Windows environment from C++ to languages such as C#, R, and Python. Using a series of example projects, the book demonstrates how to connect a simple C++ codebase packaged as a static or dynamic library to modern clients written in C#, R, and Python. The book shows you how to develop the in-between components that allow disparate languages to communicate. This book addresses a fundamental question in software design: given an existing C++ codebase, how does one go about connecting that codebase to clients written in C#, R, and Python? How is the C++ functionality exposed to these clients? One answer may be to rewrite the existing codebase in the target language. This is rarely, if ever, feasible and this book's goal is to save you the pain and the high cost of throwing out valuable existing code by showing you how to make that older code function alongside and with the more modern languages that are commonly in use today. The knowledge you will gain from reading this book will help you broaden your architectural choices and take advantage of the growing amount of talent around newer languages. What You Will Learn Build components that connect C++ to other languages Translate between the C++ type system and the type systems of C#, R, and Python Write a managed assembly targeting the .NET framework Create C++ packages for use in R/Studio Develop Python modules based on high-performance C++ code Overcome the difficulties and pitfalls involved in cross-language development.
Bibliography, etc. Note Includes bibliographical references and index.
Access Note Access limited to authorized users.
Source of Description Online resource; title from PDF title page (SpringerLink, viewed February 9, 2022).
Available in Other Form Print version: 9781484279656
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Record Appears in Online Resources > Ebooks
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Intro
Table of Contents
About the Author
About the Technical Reviewer
Acknowledgments
Introduction
Part I: Foundations
Chapter 1: Preliminaries
Introduction
Prerequisites
How to Use This Book
The Software Interoperability Project
The Projects
Terminology
How the Projects Fit Together
Summary
Chapter 2: C++ Components and C++ Clients
Introduction
A Tour of the Source Code
Descriptive Statistics
Linear Regression
The Data Manager
Statistical Tests
Functions, Classes, and Type Conversion
C++ Components
StatsLib

Prerequisites
Project Settings and Configuration
Building and Testing the Project
StatsLibTest
Building, Running, and Checking the Results
StatsDll
Project Settings and Configuration
Building and Testing the Project
C++ Clients
Introduction
StatsConsole
StatsViewer
Summary
Additional Resources
Exercises
Part II: C++/CLI and .NET
Chapter 3: Building a C++/CLI Wrapper
Introduction
Prerequisites
C++/CLI support
StatsCLR
Project Settings
Code Organization
The Statistics Class
Parameters and Return Values
Descriptive Statistics

Linear Regression
Type Conversion
Exception Handling
Testing the Code
StatsCLR.UnitTests
Managed Wrapper Classes
Introduction
The DataManager
The TTest Class
Summary
Additional Resources
Exercises
Chapter 4: C# Clients: Consuming the Managed Wrapper
Introduction
StatsClient
Project Settings
Installing Accord.NET
Code Organization
Statistical Functions
Data Analysis
Data Modelling
Hypothesis Testing
Using Reflection
Module Information
Dynamic Invocation
PowerShell
StatsExcel
Installing Excel-DNA
Project Settings

Exposing Functions to Excel
Type Conversion
Build and Run
Exception Handling
Debugging
Summary
Additional Resources
Exercises
Part III: R and Rcpp
Chapter 5: Building an R Package
Introduction
Prerequisites
Rtools
Installing CodeBlocks
CodeBlocks
Toolchain Setup
Project Setup
R/RStudio Packages
Background
Building a Package with Rcpp
Installing Rcpp
The Project Files
Editing the Makefile
Boilerplate Code
Building StatsR
Summary
Additional Resources
Exercises
Chapter 6: Exposing Functions Using Rcpp
Introduction

The Conversion Layer
Code Organization
Descriptive Statistics
The Code
Exception Handling
Exercising the Functionality
Linear Regression
The Code
Exercising the Functionality
Using a DataFrame
Statistical Tests
Functions vs. Classes
Rcpp Modules
Testing
Measuring Performance
Debugging
Distribution Explorer
Summary
Additional Resources
Exercises
Part IV: Python
Chapter 7: Building a Python Extension Module
Introduction
Prerequisites
Using Visual Studio Community Edition 2019
StatsPythonRaw
Project Settings

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