From 002d75bb50a4e6b7c41d4f2e873c34022f270895 Mon Sep 17 00:00:00 2001 From: Derek Sollberger Date: Wed, 14 Aug 2024 10:00:50 -0400 Subject: [PATCH 1/2] cohort 9, chapter 12 - added picture and quote of John Chambers - split long slides into two slides each - added example of polymorphism - added two concept maps - noted Bioconductor with S4 - went down the rabbit hole wondering why that package was called "sloop" --- 12_Base_types.Rmd | 147 ++++++++++++++++-- images/base_types/base_types_Sankey_graph.png | Bin 0 -> 148807 bytes .../john_chambers_about_objects.png | Bin 0 -> 271750 bytes images/base_types/sloop_john_b.png | Bin 0 -> 3295810 bytes images/base_types/standards.png | Bin 0 -> 24305 bytes 5 files changed, 133 insertions(+), 14 deletions(-) create mode 100644 images/base_types/base_types_Sankey_graph.png create mode 100644 images/base_types/john_chambers_about_objects.png create mode 100644 images/base_types/sloop_john_b.png create mode 100644 images/base_types/standards.png diff --git a/12_Base_types.Rmd b/12_Base_types.Rmd index ee3616b..1a05ef9 100644 --- a/12_Base_types.Rmd +++ b/12_Base_types.Rmd @@ -5,15 +5,31 @@ - Understand what OOP means--at the very least for R - Know how to discern an object's nature--base or OO--and type +![John Chambers, creator of S programming language](images/base_types/john_chambers_about_objects.png) + +
+Session Info +```{r} +library("DiagrammeR") +``` + +```{r} +utils::sessionInfo() +``` + +
+ + ## Why OOP is hard in R - Multiple OOP systems exist: S3, R6, S4, and (now/soon) R7. - Multiple preferences: some users prefer one system; others, another. - R's OOP systems are different enough that prior OOP experience may not transfer well. -## What is OOP in general? +[![XKCD 927](images/base_types/standards.png)](https://xkcd.com/927/) + -### Two big ideas +## OOP: Big Ideas 1. **Polymorphism.** Function has a single interface (outside), but contains (inside) several class-specific implementations. ```{r, eval=FALSE} @@ -28,18 +44,33 @@ some_function <- function(x) { } ... } ``` + +
+Example of polymorphism + +```{r polymorphism_example} +# data frame +summary(mtcars[,1:4]) + +# statistical model +lin_fit <- lm(mpg ~ hp, data = mtcars) +summary(lin_fit) +``` + +
+ 2. **Encapsulation.** Function "encapsulates"--that is, encloses in an inviolate capsule--both data and how it acts on data. Think of a REST API: a client interacts with with an API only through a set of discrete endpoints (i.e., things to get or set), but the server does not otherwise give access to its internal workings or state. Like with an API, this creates a separation of concerns: OOP functions take inputs and yield results; users only consume those results. -### A few practical ideas +## OOP: Properties -#### Objects have class +### Objects have class - Class defines: - Method (i.e., what can be done with object) - Fields (i.e., data that defines an instance of the class) - Objects are an instance of a class -#### Class is inherited +### Class is inherited - Class is defined: - By an object's class (e.g., ordered factor) @@ -49,9 +80,7 @@ some_function <- function(x) { - If an object doesn't have a method, use the method of the parent class - The process of finding a method, is called dispatch -## What about OOP in R? - -### Two main paradigms +## OOP in R: Two Paradigms **1. Encapsulated OOP** @@ -68,9 +97,42 @@ some_function <- function(x) { - From the outside, look like regular functions: `generic(object, arg2, arg3)` - From the inside, components are also functions -### Overview of the systems +### Concept Map + +```{r, echo = FALSE, eval = TRUE} +DiagrammeR::mermaid(" +graph LR + +OOP --> encapsulated_OOP +OOP --> functional_OOP -In base R: +functional_OOP --> S3 +functional_OOP --> S4 + +encapsulated_OOP --> R6 +encapsulated_OOP --> RC +") +``` + +
+Mermaid code +```{r, echo = TRUE, eval = FALSE} +DiagrammeR::mermaid(" +graph LR + +OOP --> encapsulated_OOP +OOP --> functional_OOP + +functional_OOP --> S3 +functional_OOP --> S4 + +encapsulated_OOP --> R6 +encapsulated_OOP --> RC +") +``` +
+ +## OOP in base R - **S3** - Paradigm: functional OOP @@ -79,7 +141,7 @@ In base R: - Downsides: no guarantees - **S4** - Paradigm: functional OOP - - Noteworthy: rewrite of S3 + - Noteworthy: rewrite of S3, used by `Bioconductor` - Use case: "more guarantees and greater encapsulation" than S3 - Downsides: higher setup cost than S3 - **RC** @@ -88,7 +150,7 @@ In base R: - Use cases: problems that are hard to tackle with functional OOP (in S3 and S4) - Downsides: harder to reason about (because of modify-in-place logic) -In packages: +## OOP in packages - **R6** - Paradigm: encapsulated OOP @@ -104,7 +166,7 @@ In packages: - Paradigm: hybrid functional and encapsulated (?) - **proto** - Paradigm: prototype OOP - - Noteworthy: OOP style used in ggplot2 + - Noteworthy: OOP style used in `ggplot2` ## How can you tell if an object is base or OOP? @@ -127,6 +189,12 @@ is.object(mtcars) sloop::otype(mtcars) ``` +### sloop + +* **S** **L**anguage **O**bject-**O**riented **P**rogramming + +[![XKCD 927](images/base_types/sloop_john_b.png)](https://en.wikipedia.org/wiki/Sloop_John_B) + ### Class OO objects have a "class" attribute: @@ -135,7 +203,7 @@ OO objects have a "class" attribute: # base object has no class attr(1:10, "class") -# OO object has one or more class +# OO object has one or more classes attr(mtcars, "class") ``` @@ -188,6 +256,57 @@ typeof(quote(a + 1)) typeof(formals(my_fun)) ``` +### Concept Map + +![Base types in R](images/base_types/base_types_Sankey_graph.png) + +
+Sankey graph code + +The graph above was made with [SankeyMATIC](https://sankeymatic.com/) + +``` +// toggle "Show Values" +// set Default Flow Colors from "each flow's Source" + +base\ntypes [8] vectors +base\ntypes [3] functions +base\ntypes [1] environments +base\ntypes [1] S4 OOP +base\ntypes [3] language\ncomponents +base\ntypes [6] C components + +vectors [1] NULL +vectors [1] logical +vectors [1] integer +vectors [1] double +vectors [1] complex +vectors [1] character +vectors [1] list +vectors [1] raw + +functions [1] closure +functions [1] special +functions [1] builtin + +environments [1] environment + +S4 OOP [1] S4 + +language\ncomponents [1] symbol +language\ncomponents [1] language +language\ncomponents [1] pairlist + +C components [1] externalptr +C components [1] weakref +C components [1] bytecode +C components [1] promise +C components [1] ... +C components [1] any +``` + +
+ ## Be careful about the numeric type 1. 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Z{~reG9>dZBmF55d002ovPDHLkV1j~{Q(gc7 literal 0 HcmV?d00001 From 1189014f7b95abfd3231faac8e8843b76cf41dbd Mon Sep 17 00:00:00 2001 From: Jon Harmon Date: Wed, 14 Aug 2024 10:19:56 -0500 Subject: [PATCH 2/2] R7 to S7 --- 12_Base_types.Rmd | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/12_Base_types.Rmd b/12_Base_types.Rmd index 1a05ef9..5a4dcd8 100644 --- a/12_Base_types.Rmd +++ b/12_Base_types.Rmd @@ -22,7 +22,7 @@ utils::sessionInfo() ## Why OOP is hard in R -- Multiple OOP systems exist: S3, R6, S4, and (now/soon) R7. +- Multiple OOP systems exist: S3, R6, S4, and (now/soon) S7. - Multiple preferences: some users prefer one system; others, another. - R's OOP systems are different enough that prior OOP experience may not transfer well.

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