r - 使用 .onLoad() 将对象加载到 R 包中的全局环境中

Question

我正在开发一个 R 包，我需要在其中随时间管理各种对象的状态。从概念上讲，当包加载 (.onLoad) 时，它会检查缓存中的状态对象，如果它不存在，则会创建一个新实例，保存到缓存中，并在全局环境中分配。使用 devtools::build() 构建站点后，我无法使用 .onLoad() 在全局环境中看到对象。所以，我有三个问题:

.onLoad() 函数是否适合此功能？如果是这样，当前使状态变量在全局环境中可见的最佳实践是什么？

是否开发了用于跨“R session ”管理状态的解决方案(包)？

有没有比我采用的方法更好的解决问题的概念方法？

尝试过的解决方案......到目前为止

我搜索了 SE，阅读(并重新阅读)Hadley 关于 R Packages 和 Advanced R 的书籍，沉思了 Winston Chang 在 R6 上的小插曲(链接在帖子底部)，我将我的实验提炼为三种失败的方法。首先，这是一个简单的“GameClass”，它使用三个变量来实例化一个游戏，玩家 1、玩家 2 和(游戏的)状态。

 #' GameClass
 #' \code{GameClass} Class that...#'
 #' @export
 GameClass <- R6::R6Class(
   "GameClass",
   public = list(
     player1 = character(0),
     player2 = character(0),
     state  = character(0),
     initialize = function(player1, player2) {
       self$player1 <- player1
       self$player2 <- player2
       self$state <- "1st Match"
     }
   )
 )

方法一

  Assign the variable to the global environment using the <<- operator


  .onLoad <- function(libname, pkgname) {

    gameFile <- "./gameFile.Rdata"
    if (file.exists(gameFile)) {
      game <<- load(gameFile)
    } else {
     game  <<- GameClass$new("Eric", "Cassie")
     save(game, file = gameFile)
    } 
  }

方法二:

创建新环境并返回

  .onLoad <- function(libname, pkgname) {
    gameFile <- "./gameFile.Rdata"
    e <- new.env()

    if (file.exists(gameFile)) {
      e$game <- load(gameFile)
    } else {
      e$game <- GameClass$new("Eric", "Cassie")
      save(e$game, file = gameFile)
    }  
    e
  }

方法三:

  .onLoad <- function(libname, pkgname) {
    gameFile <- "./gameFile.Rdata"

    if (file.exists(gameFile)) {
      game <- load(gameFile)
    } else {
      game <- GameClass$new("Eric", "Cassie")
      save(game, file = gameFile)
    }
    assign("game", game, envir = .GlobalEnv)
  }

session 信息

 R version 3.4.1 (2017-06-30)
 Platform: x86_64-w64-mingw32/x64 (64-bit)
 Running under: Windows >= 8 x64 (build 9200)

 Matrix products: default

 locale:
 [1] LC_COLLATE=English_United States.1252  LC_CTYPE=English_United 
 States.1252    LC_MONETARY=English_United States.1252
 [4] LC_NUMERIC=C                           LC_TIME=English_United 
 States.1252    

 attached base packages:
 [1] stats     graphics  grDevices utils     datasets  methods   base     

 other attached packages:
 [1] R6Lab_0.1.0

 loaded via a namespace (and not attached):
 [1] compiler_3.4.1 R6_2.2.2       tools_3.4.1    yaml_2.1.14   

我是 OOP 的新手，R6 的新手，这是我的第一个 R 包，我已经使用 R 大约一年了。显然，我可以从这里的一些见解中受益。

提前致谢。

## References ##
[Hadley's Advanced R][1]
[Hadley's R Packages][2]
[Introduction to R6 Classes][3]
[How to define hidden global variables inside R Packages][4]
[Global variables in packages in r][5]
[Global variables in r][6]
[Global variable in a package which approach is more recommended][7]

  [1]: http://adv-r.had.co.nz/
  [2]: http://r-pkgs.had.co.nz/
  [3]: https://cran.r-project.org/web/packages/R6/vignettes/Introduction.html
  [4]: https://stackoverflow.com/questions/34254716/how-to-define-hidden-global-variables-inside-r-packages
  [5]: https://stackoverflow.com/questions/12598242/global-variables-in-packages-in-r
  [6]: https://stackoverflow.com/questions/1236620/global-variables-in-r
  [7]: https://stackoverflow.com/questions/28246952/global-variable-in-a-package-which-approach-is-more-recommended

Answer 1

应该有一个词来在明显的解决方案中寻找复杂的答案。再明显不过了。

R code workflow

The first practical advantage to using a package is that it’s easy to re-load your code. You can either run devtools::load_all(), or in RStudio press Ctrl/Cmd + Shift + L, which also saves all open files, saving you a keystroke. This keyboard shortcut leads to a fluid development workflow:

1. Edit an R file.
2. Press Ctrl/Cmd + Shift + L.
3. Explore the code in the console.
4. Rinse and repeat.

Congratulations! You’ve learned your first package development workflow. Even if you learn nothing else from this book, you’ll have gained a useful workflow for editing and reloading R code

加载_all()。哇!就这么简单。 Load all 运行 .onload() 函数并将对象渲染到全局环境中。谁知道？
引用:R Code Workflow, R Packages, Hadley