How to use this tool?

This free online converter lets you convert code from Fsharp to R in a click of a button. To use this converter, take the following steps -

  1. Type or paste your Fsharp code in the input box.
  2. Click the convert button.
  3. The resulting R code from the conversion will be displayed in the output box.

Examples

The following are examples of code conversion from Fsharp to R using this converter. Note that you may not always get the same code since it is generated by an AI language model which is not 100% deterministic and gets updated from time to time.

Example 1 - Is String Palindrome

Program that checks if a string is a palindrome or not.

Fsharp

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R

Example 2 - Even or Odd

A well commented function to check if a number if odd or even.

Fsharp

right arrow

R

Key differences between Fsharp and R

CharacteristicFsharpR
SyntaxF# has a concise and expressive syntax that is similar to OCaml. It supports functional programming and provides powerful pattern matching capabilities.R has a syntax that is primarily focused on statistical analysis and data manipulation. It is more verbose compared to F# and is not as expressive for general-purpose programming.
ParadigmF# is a multi-paradigm language that supports functional programming, object-oriented programming, and imperative programming.R is primarily a functional programming language that is designed for statistical computing and graphics.
TypingF# is a statically typed language that supports type inference. It has a strong type system that helps catch errors at compile-time.R is a dynamically typed language that does not require explicit type declarations. It allows for flexible and dynamic data manipulation.
PerformanceF# is known for its performance and can be comparable to other statically typed languages like C#. It can leverage the .NET runtime for efficient execution.R is not known for its performance as it is primarily focused on data analysis and not optimized for speed. However, performance-critical tasks can be offloaded to external libraries.
Libraries and frameworksF# has access to the extensive .NET ecosystem, which includes a wide range of libraries and frameworks for various purposes.R has a rich ecosystem of packages and libraries specifically designed for statistical analysis, data manipulation, and visualization.
Community and supportF# has a growing community and is supported by Microsoft. It has active online forums, documentation, and resources.R has a large and active community of statisticians, data scientists, and researchers. It has extensive online resources, forums, and packages.
Learning curveF# has a moderate learning curve, especially for developers familiar with functional programming concepts. It may require some adjustment for developers coming from imperative or object-oriented backgrounds.R has a relatively steep learning curve, especially for developers without prior experience in statistical programming. It requires understanding of statistical concepts and specialized syntax.