R软件包-从导入的软件包转移环境 | 从导入的软件包转移环境

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问题描述

假设一个R包( myPackage )导入了R包 RCircos 通过description文件和NAMESPACE文件.

Assume an R package (myPackage) that imports the R package RCircos via the DESCRIPTION file and the NAMESPACE file.

$ cat DESCRIPTION
Package: myPackage
Imports: RCircos (>= 1.2.0)
...

$ cat NAMESPACE
import(RCircos)
...

RCircos 的优点之一是它定义了一个自定义环境(称为 RCircos.Env )，并从其各种功能读取/写入该环境的变量.例如，函数 RCircos.Initialize.Plot.Parameters 读写在这种环境下.

One of the perks of RCircos is that it defines a custom environment (called RCircos.Env) and reads/writes variables to this environment from various of its functions. For example, function RCircos.Initialize.Plot.Parameters reads and writes to this environment.

...
RCircosEnvironment <- NULL;
RCircosEnvironment <- get("RCircos.Env", envir = globalenv());
RCircosEnvironment[["RCircos.PlotPar"]] <- plot.param;

(其他R软件包也已经认识到这种特殊行为;例如，参见此包).

(This peculiar behavior has also been recognized by other R packages; see, for example, lines 247-249 of this package).

不幸的是，当我仅通过 RCircos 导入 RCircos 时，似乎无法在 myPackage 中立即识别出环境 RCircos.Env .Description文件和NAMESPACE文件.

Unfortunately, it seems that the environment RCircos.Env is not recognized out of the box in myPackage when I simply import RCircos via the DESCRIPTION file and the NAMESPACE file.

那该怎么办?

似乎有两个选项可以使环境 RCircos.Env 可以访问 RCircos.Initialize.Plot.Parameters 之类的函数.但是，这两个选项都会导致CRAN检查( R CMD检查myPackage --as-cran )在提交之前对 myPackage 进行强制评估期间发出警告或注释.到CRAN，从而阻止其被CRAN接受.

There seem to be two options of making the environment RCircos.Env accessible to functions like RCircos.Initialize.Plot.Parameters. However, both of these options cause the CRAN check (R CMD check myPackage --as-cran) to issue WARNINGs or NOTEs during the mandatory evaluation of myPackage prior to the submission to CRAN, thus preventing its acceptance on CRAN.

选项1 :我在函数要求对象之前添加了以下行:

Option 1: I include the following line directly prior to the function demanding the object:

# my code here #
assign("RCircos.Env", RCircos::RCircos.Env, .GlobalEnv)
RCircos.Set.Core.Components(...)
# my code here #

但是，CRAN检查用NOTE突出显示了这一行，从而阻止在CRAN上接受 myPackage .

However, the CRAN check highlights this line with a NOTE, thus preventing the acceptance of myPackage on CRAN.

* checking R code for possible problems ... NOTE
Found the following assignments to the global environment:
File ‘PACViR/R/visualizeWithRCircos.R’:
  assign("RCircos.Env", RCircos::RCircos.Env, .GlobalEnv)

选项2 :在功能需要对象之前，我先加载整个 RCircos 库:

Option 2: I load the entire RCircos library prior to the function demanding the object:

# my code here #
library(RCircos)
RCircos.Set.Core.Components(...)
# my code here #

但是，CRAN检查会在警告中突出显示此选项，再次阻止在CRAN上接受 myPackage .

However, the CRAN check highlights this option with a WARNING, again preventing the acceptance of myPackage on CRAN.

* checking dependencies in R code ... WARNING
'library' or 'require' call not declared from: ‘RCircos’
'library' or 'require' call to ‘RCircos’ in package code.
  Please use :: or requireNamespace() instead.
  See section 'Suggested packages' in the 'Writing R Extensions' manual.

当然，必须有一种简单且与CRAN兼容的方法，使环境 RCircos.Env 可以通过 RCircos.Set.Core.Components 之类的功能进行访问.em> myPackage ！有人可以这样命名和解释吗?

Surely, there must be an easy and CRAN-compatible way of making the environment RCircos.Env accessible to functions such as RCircos.Set.Core.Components within myPackage! Can someone name and explain such a way?

推荐答案

显然，正常的重新导出不适用于环境，而不适用于功能.但这确实可行:

Apparently the normal re-export does not work with environments as it does with functions. But this does work:

RCircos.Env <- RCircos::RCircos.Env

#' test
#'
#' @param ... data
#'
#' @export
test_fun <- function(...) {
  RCircos::RCircos.Set.Core.Components(...)
}

使用 DESCRIPTION :

Package: test
Type: Package
Title: test
Description: This is a description.
Version: 0.1.0
Authors@R: person("Wouter", "van der Bijl",
                  email = "[email protected]",
                  role = c("aut", "cre"))
Maintainer: Wouter van der Bijl <[email protected]>
License: GPL-3
Encoding: UTF-8
LazyData: true
Imports: RCircos
RoxygenNote: 6.1.1

还有这个 NAMESPACE :

# Generated by roxygen2: do not edit by hand

export(test_fun)

测试:

library(test)
data(UCSC.HG19.Human.CytoBandIdeogram, package = 'RCircos')
test_fun(UCSC.HG19.Human.CytoBandIdeogram)

基本上，当 RCircos 运行 get("RCircos.Env"，envir = globalenv())时，它将遍历搜索路径，直到找到而是从您的软件包中选择> RCircos.Env .

Basically, when RCircos runs get("RCircos.Env", envir = globalenv()), it will traverse up the search path until it finds the RCircos.Env from your package instead.

运行R CMD Check时，我得到0个错误，0个警告，0个注释.

When running R CMD Check I get 0 errors, 0 warnings, 0 notes.

请注意， RCircos 使用的这种策略以及通过使用 get(..，envir = globalenv())进行查找的环境实际上是非正统的，通常这不是一个好主意.R函数通常不应有副作用，例如编辑看不见的环境.设置默认值等通常使用 options()完成.整个程序包可能不是您想要模仿的，但至少现在您可以将其用作依赖项.

Note that this strategy that RCircos uses, with an environment that gets looked up by using get(.., envir = globalenv()) is really unorthodox and generally not a good idea. R functions should generally not have side-effects, such as editing unseen environments. Setting default values etc. is typically done using options(). The whole package is probably not something you'd want to emulate, but at least now you can use it as a dependency.

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