在不附加包的情况下评估包环境中的功能

Evaluate function within package environment without attaching package

背景

例子

数据

给定样本虚拟数据集:

# 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 function offered within the readr 包阅读它。

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:

# 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(如果可能)得到相同的结果。所需的语法类似于:

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:

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


备注

该任务主要关注访问包函数无需加载包和无需直接通过[=调用函数25=]:::。概念上的等价物是使用 with 函数并引用没有 $:

的数据框列
with(mtcars, t.test(disp ~ am))

更好的例子:

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

就用with?我不明白你为什么不想使用 ::.

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