How to run piped code line by line in R (dplyr)?-CodePudding

Is there any add-in that allows to run piped code line by line in R?

For example, I would press keys at each line and it would print the output in the console.

# AS AN EXAMPLE
library(dplyr)
mtcars %>% 
  mutate(cyl2 = 2 * cyl) %>% 
  filter(cyl2 > 15)

CodePudding user response：

A simple way to debug would be to define the following function, which prints out intermediate steps in the pipe while otherwise continuing the calculation:

`%>>%` <- function(a, b) {
  a <- match.call()$a
  b <- match.call()$b
  print(eval(a))
  eval(substitute(a %>% b))
}

For example, if I wanted to debug the following pipe at the second pipe operator:

mtcars <- mtcars[1:5,]

res <- mtcars %>% 
  mutate(cyl2 = 2 * cyl) %>% 
  filter(cyl2 > 15)

I could replace the %>% with %>>% to find out what the state of the calculation was at that step:

res <- mtcars %>% 
   mutate(cyl2 = 2 * cyl) %>>% 
   filter(cyl2 > 15)
#>                    mpg cyl disp  hp drat    wt  qsec vs am gear carb cyl2
#> Mazda RX4         21.0   6  160 110 3.90 2.620 16.46  0  1    4    4   12
#> Mazda RX4 Wag     21.0   6  160 110 3.90 2.875 17.02  0  1    4    4   12
#> Datsun 710        22.8   4  108  93 3.85 2.320 18.61  1  1    4    1    8
#> Hornet 4 Drive    21.4   6  258 110 3.08 3.215 19.44  1  0    3    1   12
#> Hornet Sportabout 18.7   8  360 175 3.15 3.440 17.02  0  0    3    2   16

But the correct final calculation is still stored in res

res
#>                    mpg cyl disp  hp drat   wt  qsec vs am gear carb cyl2
#> Hornet Sportabout 18.7   8  360 175 3.15 3.44 17.02  0  0    3    2   16

I'm not sure how useful this would be in practice. Typically if debugging a pipe I would comment out the pipe operator at the end of the line then run the code to see where I'm at, then delete the # and move to the next line. I guess there may be cases where that's inconvenient, but I don't recall seeing any.

CodePudding user response：

I usually just highlight the relevant lines in my script and execute manually (ctrl enter in Rstudio).

You mentioned going to each line and pressing keys to inspect output up to that point, so what I often do if debugging a long pipe is add .[] (or sometimes head() depending on the object type and what I want to see from it) at the end to just return whatever happened before and then comment out lines I want to remove (which can easily be done with ctrl shift c in Rstudio - those are your keypresses). Then I un-comment lines one-by-one as I debug. Finally remove the last line and final %>% once you're satisified.

E.g. I might run these in succession.

library(dplyr)

mtcars %>% 
  slice_head(n = 5) %>% 
  # mutate(cyl2 = 2 * cyl) %>%
  # filter(cyl2 > 15) %>%
  .[]
#>                    mpg cyl disp  hp drat    wt  qsec vs am gear carb
#> Mazda RX4         21.0   6  160 110 3.90 2.620 16.46  0  1    4    4
#> Mazda RX4 Wag     21.0   6  160 110 3.90 2.875 17.02  0  1    4    4
#> Datsun 710        22.8   4  108  93 3.85 2.320 18.61  1  1    4    1
#> Hornet 4 Drive    21.4   6  258 110 3.08 3.215 19.44  1  0    3    1
#> Hornet Sportabout 18.7   8  360 175 3.15 3.440 17.02  0  0    3    2
  
mtcars %>% 
  slice_head(n = 5) %>% 
  mutate(cyl2 = 2 * cyl) %>%
  # filter(cyl2 > 15) %>%
  .[]
#>                    mpg cyl disp  hp drat    wt  qsec vs am gear carb cyl2
#> Mazda RX4         21.0   6  160 110 3.90 2.620 16.46  0  1    4    4   12
#> Mazda RX4 Wag     21.0   6  160 110 3.90 2.875 17.02  0  1    4    4   12
#> Datsun 710        22.8   4  108  93 3.85 2.320 18.61  1  1    4    1    8
#> Hornet 4 Drive    21.4   6  258 110 3.08 3.215 19.44  1  0    3    1   12
#> Hornet Sportabout 18.7   8  360 175 3.15 3.440 17.02  0  0    3    2   16

mtcars %>% 
  slice_head(n = 5) %>% 
  mutate(cyl2 = 2 * cyl) %>%
  filter(cyl2 > 15) %>%
  .[]
#>                    mpg cyl disp  hp drat   wt  qsec vs am gear carb cyl2
#> Hornet Sportabout 18.7   8  360 175 3.15 3.44 17.02  0  0    3    2   16

^{Created on 2022-11-21 with reprex v2.0.2}