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[ENAR 2021 Workshop] Targeted Learning in the tlverse: Causal Inference Meets Machine Learning

7 A Primer on the R6 Class System

A central goal of the Targeted Learning statistical paradigm is to estimate scientifically relevant parameters in realistic (usually nonparametric) models.

The tlverse is designed using basic OOP principles and the R6 OOP framework. While we’ve tried to make it easy to use the tlverse packages without worrying much about OOP, it is helpful to have some intuition about how the tlverse is structured. Here, we briefly outline some key concepts from OOP. Readers familiar with OOP basics are invited to skip this section.

7.1 Classes, Fields, and Methods

The key concept of OOP is that of an object, a collection of data and functions that corresponds to some conceptual unit. Objects have two main types of elements:

  1. fields, which can be thought of as nouns, are information about an object, and
  2. methods, which can be thought of as verbs, are actions an object can perform.

Objects are members of classes, which define what those specific fields and methods are. Classes can inherit elements from other classes (sometimes called base classes) – accordingly, classes that are similar, but not exactly the same, can share some parts of their definitions.

Many different implementations of OOP exist, with variations in how these concepts are implemented and used. R has several different implementations, including S3, S4, reference classes, and R6. The tlverse uses the R6 implementation. In R6, methods and fields of a class object are accessed using the $ operator. For a more thorough introduction to R6, see https://adv-r.hadley.nz/r6.html, from Hadley Wickham’s Advanced R (Wickham 2014).

7.2 Object Oriented Programming: Python and R

OO concepts (classes with inherentence) were baked into Python from the first published version (version 0.9 in 1991). In contrast, R gets its OO “approach” from its predecessor, S, first released in 1976. For the first 15 years, S had no support for classes, then, suddenly, S got two OO frameworks bolted on in rapid succession: informal classes with S3 in 1991, and formal classes with S4 in 1998. This process continues, with new OO frameworks being periodically released, to try to improve the lackluster OO support in R, with reference classes (R5, 2010) and R6 (2014). Of these, R6 behaves most like Python classes (and also most like OOP focused languages like C++ and Java), including having method definitions be part of class definitions, and allowing objects to be modified by reference.