error using dtplyr in function, object not found?

[sonoshah]

I think I must be missing something obvious here, but I'm not sure what to make of this error. I have a simple function that accepts one argument which is used to filter a df object and pull out the values from a particular column. I had originally written this just using vanilla dplyr, but wanted to see if I could make it more efficient with dtplyr.

The underlying dtplyr code works fine outside the function, but whenever I try to call the function, I get an object not found error. I feel like I must be missing something simple here, any help would be greatly appreciated.

library(reprex)
library(data.table)
library(dtplyr)
library(tidyverse)

data("mtcars")
mtcars <- mtcars %>% rownames_to_column("car_name") 

mtcars_lazy <- lazy_dt(mtcars)

special_cars <- mtcars %>%
  sample_n(10) %>% 
  pull(car_name)

# This works
mtcars_lazy %>% filter(car_name == special_cars[1]) %>% as_tibble() %>% pull(mpg)
#> [1] 30.4

# Wrapping in function...
check_mpg <- function(car){
  print(paste("This is a: ",car))
  
  mtcars_lazy %>%
    filter(car_name == car) %>% as_tibble() %>% pull(mpg)
  
}
# Doesn't work
check_mpg(special_cars[1])
#> [1] "This is a:  Lotus Europa"
#> Error in eval(stub[[3L]], x, enclos): object 'car' not found

Details

sessionInfo()
#> R version 3.6.3 (2020-02-29)
#> Platform: x86_64-pc-linux-gnu (64-bit)
#> Running under: Ubuntu 18.04.4 LTS
#> 
#> Matrix products: default
#> BLAS:   /usr/lib/x86_64-linux-gnu/openblas/libblas.so.3
#> LAPACK: /usr/lib/x86_64-linux-gnu/libopenblasp-r0.2.20.so
#> 
#> locale:
#>  [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
#>  [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
#>  [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
#>  [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
#>  [9] LC_ADDRESS=C               LC_TELEPHONE=C            
#> [11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       
#> 
#> attached base packages:
#> [1] stats     graphics  grDevices utils     datasets  methods   base     
#> 
#> other attached packages:
#>  [1] forcats_0.5.0     stringr_1.4.0     dplyr_1.0.1       purrr_0.3.4      
#>  [5] readr_1.3.1       tidyr_1.1.1       tibble_3.0.3      ggplot2_3.3.2    
#>  [9] tidyverse_1.3.0   dtplyr_1.0.1      data.table_1.13.0 reprex_0.3.0     
#> 
#> loaded via a namespace (and not attached):
#>  [1] Rcpp_1.0.4       cellranger_1.1.0 pillar_1.4.6     compiler_3.6.3  
#>  [5] dbplyr_1.4.4     highr_0.8        tools_3.6.3      digest_0.6.25   
#>  [9] lubridate_1.7.9  jsonlite_1.7.0   evaluate_0.14    lifecycle_0.2.0 
#> [13] gtable_0.3.0     pkgconfig_2.0.3  rlang_0.4.7      cli_2.0.2       
#> [17] DBI_1.1.0        yaml_2.2.1       haven_2.3.1      xfun_0.16       
#> [21] withr_2.2.0      xml2_1.3.2       httr_1.4.2       knitr_1.29      
#> [25] hms_0.5.3        generics_0.0.2   fs_1.5.0         vctrs_0.3.2     
#> [29] grid_3.6.3       tidyselect_1.1.0 glue_1.4.1       R6_2.4.1        
#> [33] fansi_0.4.1      readxl_1.3.1     rmarkdown_2.3    modelr_0.1.8    
#> [37] blob_1.2.1       magrittr_1.5     scales_1.1.1     backports_1.1.8 
#> [41] ellipsis_0.3.1   htmltools_0.5.0  rvest_0.3.6      assertthat_0.2.1
#> [45] colorspace_1.4-1 stringi_1.4.6    munsell_0.5.0    broom_0.7.0     
#> [49] crayon_1.3.4

^{Created on 2020-09-03 by the reprex package (v0.3.0)}

[pnacht]

The problem is that dtplyr is interpretting car as a column name, which doesn't exist.

You therefore need to use bang notation (!!) to make it clear that car is a variable, not a column.

check_mpg <- function(car){
  print(paste("This is a: ",car))
  
  mtcars_lazy %>%
    filter(car_name == !!car) %>% as_tibble() %>% pull(mpg)
  
}
check_mpg(special_cars[1])
#> [1] "This is a:  Lincoln Continental"
#> [1] 10.4

Now, as to why this problem appears in a function but not in the global environment, I don't know. I even tried modifying the non-function version by replacing car_name == special_cars[1] with car_name == car (having previously defined car), but it still works there.

[hadley]

Minimal reprex:

library(dtplyr)
library(dplyr, warn.conflicts = FALSE)

df <- data.frame(x = 1:5, y = 2)
dt <- lazy_dt(df)

x_val <- 1
dt %>% filter(x == x_val) %>% collect()
#> # A tibble: 1 x 2
#>       x     y
#>   <int> <dbl>
#> 1     1     2
rm(x_val)

f <- function(x_val) {
  dt %>% filter(x == x_val) %>% collect()
}
f(2)
#> Error in eval(stub[[3L]], x, enclos): object 'x_val' not found

^{Created on 2021-01-25 by the reprex package (v0.3.0.9001)}

I must be using the wrong environment somewhere.