Question

Object oriented programming in one way or another is very much possible in R. However, unlike for example Python, there are many ways to achieve object orientation:

• The R.oo package
• S3 and S4 classes
• Reference classes
• the proto package

My question is:

What major differences distinguish these ways of OO programming in R?

Ideally the answers here will serve as a reference for R programmers trying to decide which OO programming methods best suits their needs.

As such, I am asking for detail, presented in an objective manner, based on experience, and backed with facts and reference. Bonus points for clarifying how these methods map to standard OO practices.

Answer 1

S3 classes

• Not really objects, more of a naming convention
• Based around the . syntax: E.g. for print, print calls print.lm print.anova, etc. And if not found,print.default

S4 classes

• Can dispatch on multiple arguments
• More complicated to implement than S3

Reference classes

• Primarily useful to avoid making copies of large objects (pass by reference)
• Description of reasons to use RefClasses

proto

• ggplot2 was originally written in proto, but will eventually be rewritten using S3.
• Neat concept (prototypes, not classes), but seems tricky in practice
• Next version of ggplot2 seems to be moving away from it
• Description of the concept and implementation

R6 classes

• By-reference
• Does not depend on S4 classes
• “Creating an R6 class is similar to the reference class, except that there’s no need to separate the fields and methods, and you can’t specify the types of the fields.”