Online R to Gleam 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 Gleam 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 Gleam code from the conversion will be displayed in the output box.
Key differences between R and Gleam
| Characteristic | R | Gleam |
|---|---|---|
| Syntax | R uses a syntax similar to other statistical languages, with a focus on data manipulation and analysis; it is vectorized and often uses functions like apply, lapply, and data.frame. | Gleam has a syntax inspired by ML-family languages (like OCaml), with strong type annotations, pattern matching, and a focus on functional purity. |
| Paradigm | Primarily procedural and functional, with some object-oriented features (S3, S4, R6). | Purely functional, emphasizing immutability and stateless programming. |
| Typing | Dynamically typed; types are checked at runtime. | Statically and strongly typed; types are checked at compile time. |
| Performance | Interpreted and generally slower, especially for loops and non-vectorized code; optimized for statistical operations. | Compiled to Erlang BEAM bytecode or JavaScript; offers better performance for concurrent and scalable applications. |
| Libraries and frameworks | Extensive libraries for statistics, data analysis, and visualization (CRAN, Bioconductor). | Smaller ecosystem; can use Erlang and Elixir libraries, but fewer native libraries and frameworks. |
| Community and support | Large, mature community with strong academic and industry support. | Small but growing community; less mature, with more limited support resources. |
| Learning curve | Moderate; easier for those with a statistics or data science background. | Steeper, especially for those new to functional programming or static typing. |
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