BoxLang vs. Component Pascal vs. Python vs. R Comparison Chart

Component Pascal is a general-purpose language in the tradition of Pascal, Modula-2, and Oberon. Its most important features are block structure, modularity, separate compilation, static typing with strong type checking (also across module boundaries), type extension with methods, dynamic loading of modules, and garbage collection. Type extension makes Component Pascal an object-oriented language. An object is a variable of an abstract data type consisting of private data (its state) and procedures that operate on this data. Abstract data types are declared as extensible records. Component Pascal covers most terms of object-oriented languages by the established vocabulary of imperative languages in order to minimize the number of notions for similar concepts. Complete type safety and the requirement of a dynamic object model make Component Pascal a component-oriented language.

R is a language and environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues. R can be considered as a different implementation of S. There are some important differences, but much code written for S runs unaltered under R. R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, …) and graphical techniques, and is highly extensible. The S language is often the vehicle of choice for research in statistical methodology, and R provides an Open Source route to participation in that activity. One of R’s strengths is the ease with which well-designed publication-quality plots can be produced, including mathematical symbols and formulae where needed.