Online R to Raku Converter
Click to select or drop your input code file here.
You can also type the input code below.
How to use this tool?
This free online converter lets you convert code from R to Raku in a click of a button. To use this converter, take the following steps -
- Type or paste your R code in the input box.
- Click the convert button.
- The resulting Raku code from the conversion will be displayed in the output box.
Key differences between R and Raku
| Characteristic | R | Raku |
|---|---|---|
| Syntax | Specialized for statistical computing; concise but can be idiosyncratic and inconsistent. | Modern, flexible, and expressive; supports multiple paradigms and allows for custom operators and grammars. |
| Paradigm | Primarily functional and vectorized; supports procedural and some object-oriented programming. | Multi-paradigm: supports procedural, object-oriented, functional, concurrent, and reactive programming. |
| Typing | Dynamically typed; weak typing with implicit type conversions. | Gradually typed; supports both dynamic and static typing with strong type checking. |
| Performance | Interpreted; can be slow for loops and large computations unless optimized with C/C++ extensions. | Interpreted; generally slower than many mainstream languages, but performance is improving. |
| Libraries and frameworks | Extensive ecosystem for statistics, data analysis, and visualization (CRAN, Bioconductor). | Smaller ecosystem; general-purpose libraries available but lacks specialized statistical/data science libraries. |
| Community and support | Large, active community; strong support in academia and industry; abundant resources and forums. | Smaller, growing community; active development but fewer resources and less mainstream adoption. |
| Learning curve | Moderate for statistical users; can be steep for general programming due to unique syntax and quirks. | Steep due to rich feature set and flexibility; easier for those familiar with Perl or modern programming concepts. |
