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假设我写了一个包“ hello”......

R>library(devtools)
R>install_github("jimhester/covr")
R>create("hello")

...使用单个导出函数：

hello <- function() {
  dt<-as.data.table(list(a=1:10))
  dt[,b:=a+2]
  return(sum(dt[,b]))
}

为了使这个包工作，我还添加

Depends:
    data.table

到DESCRIPTION文件。

现在我想为它写一个单元测试：

R>use_testthat("testcovr")

...在文件中tests/testthat/test-hello.R：

context("hello")

test_that("hello works", {
  expect_equal(hello(), 75)
})

当我运行测试时，它们失败了：

R> test()
Loading hello
Loading required package: testthat
Testing hello
hello: 1

Failed -----------------------------------------------------------------------------------------------------------------------
1. Error: hello works (@test-hello.R#7) --------------------------------------------------------------------------------------
Check that is.data.table(DT) == TRUE. Otherwise, := and `:=`(...) are defined for use in j, once only and in particular ways. See help(":=").
1: expect_equal(hello(), 75) at /home/Adama-docs/Adam/linux/tmp/hello/tests/testthat/test-hello.R:7
2: compare(object, expected, ...)
3: hello()
4: dt[, `:=`(b, a + 2)] at /home/Adama-docs/Adam/linux/tmp/hello/R/hello.R:18
5: `[.data.table`(dt, , `:=`(b, a + 2)) at /home/Adama-docs/Adam/linux/tmp/hello/R/hello.R:18
6: `[.data.frame`(x, i, j)
7: `:=`(b, a + 2)
8: stop("Check that is.data.table(DT) == TRUE. Otherwise, := and `:=`(...) are defined for use in j, once only and in particular ways. See help(\":=\").")

DONE =========================================================================================================================

为什么？？testthat尽管我用谷歌搜索了和之间不兼容的其他情况data.table，但它们与:=操作员无关。他们指责testthat包裹。

这是我的会话信息：

Session info ------------------------------------------------------------------------------------------------------------------
 setting  value                       
 version  R version 3.3.0 (2016-05-03)
 system   x86_64, linux-gnu           
 ui       RStudio (0.99.902)          
 language en_US                       
 collate  en_US.UTF-8                 
 tz       <NA>                        
 date     2016-06-16                  

Packages ----------------------------------------------------------------------------------------------------------------------
 package    * version    date       source                          
 chron        2.3-47     2015-06-24 CRAN (R 3.3.0)                  
 crayon       1.3.1      2015-07-13 CRAN (R 3.3.0)                  
 data.table * 1.9.6      2015-09-19 CRAN (R 3.3.0)                  
 devtools   * 1.11.1     2016-04-21 CRAN (R 3.3.0)                  
 digest       0.6.9      2016-01-08 CRAN (R 3.2.4)                  
 magrittr     1.5        2014-11-22 CRAN (R 3.2.0)                  
 memoise      1.0.0      2016-01-29 CRAN (R 3.3.0)                  
 R6           2.1.2      2016-01-26 CRAN (R 3.3.0)                  
 Rcpp         0.12.5     2016-05-14 CRAN (R 3.3.0)                  
 roxygen2     5.0.1      2015-11-11 CRAN (R 3.3.0)                  
 stringi      1.1.1      2016-05-27 CRAN (R 3.3.0)                  
 stringr      1.0.0      2015-04-30 CRAN (R 3.2.0)                  
 testdt     * 0.1.0      <NA>       local                           
 testthat   * 1.0.2      2016-04-23 CRAN (R 3.3.0)                  
 withr        1.0.1.9000 2016-06-15 Github (jimhester/withr@bd42181)

有什么解决方法吗？放弃data.table对我来说不是一个选择，因为我的库处理非常大的数据集。

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