do.call() 和 tidy 评估

Question

试图do.call()在整洁评估的背景下工作：

library(rlang)
library(dplyr)

data <- tibble(item_name = c("apple", "bmw", "bmw"))

mutate(data, category = case_when(item_name == "apple" ~ "fruit",
                                  item_name == "bmw" ~ "car"))

# # A tibble: 3 x 2
#   item_name category
#   <chr>     <chr>   
# 1 apple     fruit   
# 2 bmw       car     
# 3 bmw       car 

有什么不同：

category_fn <- function(df, ...){
  # browser()
  cat1 <- quos(...)
  mutate(df, category = case_when(!!! cat1))
}

category_fn(df = data, item_name == "apple" ~ "fruit",
                       item_name == "bmw" ~ "car")

# # A tibble: 3 x 2
#   item_name category
#   <chr>     <chr>   
# 1 apple     fruit   
# 2 bmw       car     
# 3 bmw       car 

和：

cat <- list(item_name == "apple" ~ "fruit", item_name == "bmw" ~ "car")

do.call(category_fn, c(list(df = data), cat), quote = FALSE)
# Or:
do.call(category_fn, c(list(df = data), cat), quote = TRUE)
# Or:
rlang::invoke(category_fn, c(list(df = data), cat))

都给出了相同的错误：

# Error in mutate_impl(.data, dots) : 
#   Evaluation error: object 'item_name' not found.

我使用 进入函数browser()，检查参数，在expr(mutate(df, category = case_when(!!! cat1)))那里运行（如http://rpubs.com/lionel-/programming-draft 中建议的通用调试策略），在两种情况下输出相同：mutate(df, category = case_when(~(item_name == "apple" ~ "fruit"), ~(item_name == "bmw" ~ "car")))。

我也试图调整enviror.env参数无济于事。

我的理解是它可能与不同的quosure环境有关，但environment(cat1[[1]])也是相同的（<environment: R_GlobalEnv>）。

注意：
这是我试图回答的带有 dplyr::case_when的Tidy 评估编程的后续。

> sessioninfo::session_info()
? Session info ????????????????????????????????????????????????????????
 setting  value                       
 version  R version 3.4.3 (2017-11-30)
 os       Linux Mint 18               
 system   x86_64, linux-gnu           
 [...]                 

? Packages ????????????????????????????????????????????????????????????
 package     * version    date       source                             
 [...]                
 dplyr       * 0.7.4      2017-09-28 CRAN (R 3.4.3)                     
 [...]                    
 rlang       * 0.1.6      2017-12-21 CRAN (R 3.4.3)                     
 [...]

Answer 1

我们可以创建 'cat' 作为 aquosure然后进行评估 !!!

cat <-  quos(item_name == "apple" ~ "fruit", item_name == "bmw" ~ "car")
category_fn(data, !!!(cat))
# A tibble: 3 x 2
#  item_name category
#  <chr>     <chr>   
#1 apple     fruit   
#2 bmw       car     
#3 bmw       car