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  5. C++ vs RStudio

C++ vs RStudio

OverviewDecisionsComparisonAlternatives

Overview

C++
C++
Stacks18.2K
Followers9.4K
Votes866
RStudio
RStudio
Stacks415
Followers455
Votes10
GitHub Stars4.9K
Forks1.1K

C++ vs RStudio: What are the differences?

Key Differences between C++ and RStudio

C++ and RStudio are two popular programming languages that serve different purposes and have distinct features. Here are the key differences between these two languages:

  1. Syntax and Purpose: C++ is a general-purpose programming language primarily used for systems programming, game development, and other performance-driven applications, while RStudio is an integrated development environment (IDE) specifically designed for statistical computing and graphics in the R programming language.

  2. Object-Oriented vs. Functional Programming: C++ supports object-oriented programming (OOP) paradigms, allowing for the creation of classes, objects, and inheritance, which makes it suitable for large-scale software development. On the other hand, RStudio and the R language focus more on functional programming concepts, emphasizing the use of functions and data manipulation.

  3. Performance: C++ is known for its high performance and efficiency, as it directly compiles to machine code. This makes it a preferred choice for applications requiring speed and low-level memory access. In contrast, RStudio runs R code, which is interpreted rather than compiled, leading to slower execution times for computationally intensive tasks.

  4. Community and Packages: C++ has a vast and active community with a wide range of libraries and frameworks available for various applications, including graphics, networking, and machine learning. RStudio, being an IDE for the R language, benefits from the extensive collection of R packages that provide specialized functionality for statistical analysis, data visualization, and data science.

  5. Data Handling and Analysis: RStudio excels in data handling and analysis capabilities, offering a rich set of built-in functions and libraries for statistical modeling, data manipulation, and visualization. It provides an interactive environment to explore and analyze data using techniques such as data frames, statistical modeling, and various specialized data structures. C++, being a general-purpose language, requires additional libraries and frameworks to achieve similar functionality.

  6. Learning Curve and Complexity: C++ is considered a complex language with a steep learning curve, especially for beginners. It requires knowledge of low-level concepts, memory management, and syntax intricacies. RStudio, with its focus on statistical programming, has a relatively gentler learning curve due to its high-level abstractions and intuitive syntax, making it accessible to data scientists and statisticians.

In summary, C++ and RStudio differ in terms of purpose, programming paradigms, performance, community support, data handling capabilities, and learning complexity. These differences make them suitable for distinct applications and cater to different user needs.

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Advice on C++, RStudio

albert
albert

May 5, 2020

Needs advice

I am currently learning Back-End design, and I am confused with the term Back-End API. My question is do I need to have a webserver? That is the Browser send a http request to the Webserver, based on the URL, the Webserver will execute the WEB API and route the request to it and send back the response received from the WEB API to the browser. If so, what are the differences from the WebServer to execute a CGI in the traditional architecture?

If this is not the case, is the WEB API a standalone server/application that can process the HTTP request and send back the response to the browser? Thank you very much for clarifying...

63.8k views63.8k
Comments
Russtopia
Russtopia

Sr. Doodad Imagineer at Russtopia Labs

Dec 8, 2019

Decided

As a personal research project I wanted to add post-quantum crypto KEM (key encapsulation) algorithms and new symmetric crypto session algorithms to openssh. I found the openssh code and its channel/context management extremely complex.

Concurrently, I was learning Go. It occurred to me that Go's excellent standard library, including crypto libraries, plus its much safer memory model and string/buffer handling would be better suited to a secure remote shell solution. So I started from scratch, writing a clean-room Go-based solution, without regard for ssh compatibility. Interactive and token-based login, secure copy and tunnels.

Of course, it needs a proper security audit for side channel attacks, protocol vulnerabilities and so on -- but I was impressed by how much simpler a client-server application with crypto and complex terminal handling was in Go.

<pre> $ sloc openssh-portable Languages Files Code Comment Blank Total CodeLns Total 502 112982 14327 15705 143014 100.0% C 389 105938 13349 14416 133703 93.5% Shell 92 6118 937 1129 8184 5.7% Make 16 468 37 131 636 0.4% AWK 1 363 0 7 370 0.3% C++ 3 79 4 18 101 0.1% Conf 1 16 0 4 20 0.0% $ sloc xs Languages Files Code Comment Blank Total CodeLns Total 34 3658 1231 655 5544 100.0% Go 19 3230 1199 507 4936 89.0% Markdown 2 181 0 76 257 4.6% Make 7 148 4 50 202 3.6% YAML 1 39 0 5 44 0.8% Text 1 30 0 7 37 0.7% Modula 1 16 0 2 18 0.3% Shell 3 14 28 8 50 0.9% </pre>

https://gogs.blitter.com/RLabs/xs

233k views233k
Comments

Detailed Comparison

C++
C++
RStudio
RStudio

C++ compiles directly to a machine's native code, allowing it to be one of the fastest languages in the world, if optimized.

An integrated development environment for R, with a console, syntax-highlighting editor that supports direct code execution. Publish and distribute data products across your organization. One button deployment of Shiny applications, R Markdown reports, Jupyter Notebooks, and more. Collections of R functions, data, and compiled code in a well-defined format. You can expand the types of analyses you do by adding packages.

-
Enhanced Security and Authentication; Administrative Tools; Metrics and Monitoring; Advanced Resource Management; Session Load Balancing; Team Productivity Enhancements; Priority Email Support.
Statistics
GitHub Stars
-
GitHub Stars
4.9K
GitHub Forks
-
GitHub Forks
1.1K
Stacks
18.2K
Stacks
415
Followers
9.4K
Followers
455
Votes
866
Votes
10
Pros & Cons
Pros
  • 206
    Performance
  • 108
    Control over memory allocation
  • 99
    Cross-platform
  • 98
    Fast
  • 85
    Object oriented
Cons
  • 8
    Slow compilation
  • 8
    Unsafe
  • 6
    Fragile ABI
  • 6
    Over-complicated
  • 5
    No standard/mainstream dependency management
Pros
  • 3
    Visual editor for R Markdown documents
  • 2
    In-line code execution using blocks
  • 1
    In-line graphing support
  • 1
    Supports Rcpp, python and SQL
  • 1
    Can be themed
Integrations
No integrations available
Jenkins
Jenkins
Docker
Docker
Windows
Windows

What are some alternatives to C++, RStudio?

JavaScript

JavaScript

JavaScript is most known as the scripting language for Web pages, but used in many non-browser environments as well such as node.js or Apache CouchDB. It is a prototype-based, multi-paradigm scripting language that is dynamic,and supports object-oriented, imperative, and functional programming styles.

Python

Python

Python is a general purpose programming language created by Guido Van Rossum. Python is most praised for its elegant syntax and readable code, if you are just beginning your programming career python suits you best.

PHP

PHP

Fast, flexible and pragmatic, PHP powers everything from your blog to the most popular websites in the world.

Sublime Text

Sublime Text

Sublime Text is available for OS X, Windows and Linux. One license is all you need to use Sublime Text on every computer you own, no matter what operating system it uses. Sublime Text uses a custom UI toolkit, optimized for speed and beauty, while taking advantage of native functionality on each platform.

Ruby

Ruby

Ruby is a language of careful balance. Its creator, Yukihiro “Matz” Matsumoto, blended parts of his favorite languages (Perl, Smalltalk, Eiffel, Ada, and Lisp) to form a new language that balanced functional programming with imperative programming.

Java

Java

Java is a programming language and computing platform first released by Sun Microsystems in 1995. There are lots of applications and websites that will not work unless you have Java installed, and more are created every day. Java is fast, secure, and reliable. From laptops to datacenters, game consoles to scientific supercomputers, cell phones to the Internet, Java is everywhere!

Golang

Golang

Go is expressive, concise, clean, and efficient. Its concurrency mechanisms make it easy to write programs that get the most out of multicore and networked machines, while its novel type system enables flexible and modular program construction. Go compiles quickly to machine code yet has the convenience of garbage collection and the power of run-time reflection. It's a fast, statically typed, compiled language that feels like a dynamically typed, interpreted language.

Atom

Atom

At GitHub, we're building the text editor we've always wanted. A tool you can customize to do anything, but also use productively on the first day without ever touching a config file. Atom is modern, approachable, and hackable to the core. We can't wait to see what you build with it.

Vim

Vim

Vim is an advanced text editor that seeks to provide the power of the de-facto Unix editor 'Vi', with a more complete feature set. Vim is a highly configurable text editor built to enable efficient text editing. It is an improved version of the vi editor distributed with most UNIX systems. Vim is distributed free as charityware.

Visual Studio Code

Visual Studio Code

Build and debug modern web and cloud applications. Code is free and available on your favorite platform - Linux, Mac OSX, and Windows.

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