在不附加软件包的情况下评估软件包环境中的功能 [英] Evaluate function within package environment without attaching package

问题描述

• 我想用不附加此程序包的程序包环境评估一组R函数
• 我想避免使用 package::

• I would like to evaluate a set of R function with a package environment without attaching this package
• I would like to avoid using package::

给出样本虚拟数据集:

# Data --------------------------------------------------------------------

tmpCSV <- tempfile(fileext = ".CSV", pattern = "mtcars_data_")
write.csv(x = mtcars[, 1:5], file = tmpCSV, row.names = FALSE)
# Confirm
# readLines(con = tmpCSV)[1]

阅读

library

我可以使用 read_csv 函数在 readr 包中提供.

Reading

library

I could read it with use of read_csv function offered within the readr package.

library(readr)
dta <- read_csv(
    file = tmpCSV,
    col_types = cols(
        mpg = col_double(),
        cyl = col_integer(),
        disp = col_integer(),
        hp = col_integer(),
        drat = col_double()
    )
)

readr::

也可以直接调用readr::函数:

readr::

It would be also possible to call readr:: functions directly:

# detach("package:readr", unload=TRUE)
dta <- readr::read_csv(
    file = tmpCSV,
    col_types = readr::cols(
        mpg = readr::col_double(),
        cyl = readr::col_integer(),
        disp = readr::col_integer(),
        hp = readr::col_integer(),
        drat = readr::col_double()
    )
)

问题

我想使用eval/evalq得到相同的结果(如果可能).所需的语法类似于:

Problem

I would like to arrive at the same results using eval/evalq (if possible). Desired syntax would resemble:

eval(expr = read_csv(
    file = tmpCSV,
    col_types = cols(
        mpg = col_double(),
        cyl = col_integer(),
        disp = col_integer(),
        hp = col_integer(),
        drat = col_double()
    )
),
# Naturally, the "" bit does not make sense
envir = "package::readr")

预期错误:

read_csv(file = tmpCSV, col_types = cols(mpg = col_double(),中的错误:找不到函数"read_csv"

Error in read_csv(file = tmpCSV, col_types = cols(mpg = col_double(), : could not find function "read_csv"

---

注释

任务主要涉及直接通过 :: 和 ::: .概念上等效的方法是使用with函数并引用不带$的数据框列:

---

Notes

The task is mostly concerned with accessing package functions without loading package and without calling functions directly via :: and :::. Conceptual equivalent would be using with function and referring to data frame columns without $:

with(mtcars, t.test(disp ~ am))

更好的例子:

with(mtcars, mpg[cyl == 8  &  disp > 350])

推荐答案

只使用with吗?我不明白您为什么不想使用::.

Just use with? I don't understand why you don't want to use ::.

setwd("E:/temp")

tmpCSV <- tempfile(fileext = ".CSV", pattern = "mtcars_data_")
write.csv(x = mtcars[, 1:5], file = tmpCSV, row.names = FALSE)


dta <- readr::read_csv(
  file = tmpCSV,
  col_types = readr::cols(
    mpg = readr::col_double(),
    cyl = readr::col_integer(),
    disp = readr::col_integer(),
    hp = readr::col_integer(),
    drat = readr::col_double()
  )
)

sessionInfo()
#attached base packages:
#  [1] stats     graphics  grDevices datasets  utils     methods   base     

#loaded via a namespace (and not attached):
#[1] readr_1.1.1      compiler_3.4.4   assertthat_0.2.0 R6_2.2.2         cli_1.0.0       
#[6] hms_0.4.2        tools_3.4.4      pillar_1.2.1     rstudioapi_0.7   tibble_1.4.2    
#[11] crayon_1.3.4     Rcpp_0.12.16     utf8_1.1.3       pkgconfig_2.0.1  rlang_0.2.0     
#[16] fortunes_1.5-4 

dtb <- with(asNamespace("readr"), read_csv(
  file = tmpCSV,
  col_types = cols(
    mpg = col_double(),
    cyl = col_integer(),
    disp = col_integer(),
    hp = col_integer(),
    drat = col_double()
  )))
#same happens here

identical(dta, dtb)
#[1] TRUE

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