What's so special about group_by that my function does not work?

Dear all, I'm having trouble with something which unfortunately I absolutely have 0 idea where to start. I have written a function called purely() which allows to catch any condition. A decorated function with purely() will return a list of two elements $result and $log. If everything goes well, $result holds the result, and if something happens, $result is NA and $log has the error/message/warning.
purely() works for any function I've tried, but not for group_by() nor count()(which I guess uses group_by() under the hood).

My guess is that group_by() is a very special function that does something unusual, which purely() doesn't know how to deal with. What's weird, is that no condition is raised, so $log is empty!

Any idea? Below a reprex.

purely <- function(.f){

  function(..., .log = "Log start..."){

    res <- rlang::try_fetch(
                    eval_tidy(.f(...)),
                    condition = function(cnd) cnd
                  )

    final_result <- list(
      result = NULL,
      log = NULL
    )

    final_result$result <- if(c("condition") %in% class(res)){
                             NA
                           } else {
                             res
                           }

    final_result$log <- if(c("condition") %in% class(res)){
                             res$message
                           } else {
                             NA
                           }

    final_result


  }
}

# on a simple function
purely(log)(10)
#> $result
#> [1] 2.302585
#> 
#> $log
#> [1] NA

# error gets caught
purely(log)("10")
#> $result
#> [1] NA
#> 
#> $log
#> [1] "non-numeric argument to mathematical function"

# these, and many others work
purely(dplyr::select)(mtcars, am, starts_with("c"))
#> $result
#>                     am cyl carb
#> Mazda RX4            1   6    4
#> Mazda RX4 Wag        1   6    4
#> Datsun 710           1   4    1
#> Hornet 4 Drive       0   6    1
#> Hornet Sportabout    0   8    2
#> Valiant              0   6    1
#> Duster 360           0   8    4
#> Merc 240D            0   4    2
#> Merc 230             0   4    2
#> Merc 280             0   6    4
#> Merc 280C            0   6    4
#> Merc 450SE           0   8    3
#> Merc 450SL           0   8    3
#> Merc 450SLC          0   8    3
#> Cadillac Fleetwood   0   8    4
#> Lincoln Continental  0   8    4
#> Chrysler Imperial    0   8    4
#> Fiat 128             1   4    1
#> Honda Civic          1   4    2
#> Toyota Corolla       1   4    1
#> Toyota Corona        0   4    1
#> Dodge Challenger     0   8    2
#> AMC Javelin          0   8    2
#> Camaro Z28           0   8    4
#> Pontiac Firebird     0   8    2
#> Fiat X1-9            1   4    1
#> Porsche 914-2        1   4    2
#> Lotus Europa         1   4    2
#> Ford Pantera L       1   8    4
#> Ferrari Dino         1   6    6
#> Maserati Bora        1   8    8
#> Volvo 142E           1   4    2
#> 
#> $log
#> [1] NA
purely(dplyr::mutate)(mtcars, am2 = 2*am)
#> $result
#>                      mpg cyl  disp  hp drat    wt  qsec vs am gear carb am2
#> Mazda RX4           21.0   6 160.0 110 3.90 2.620 16.46  0  1    4    4   2
#> Mazda RX4 Wag       21.0   6 160.0 110 3.90 2.875 17.02  0  1    4    4   2
#> Datsun 710          22.8   4 108.0  93 3.85 2.320 18.61  1  1    4    1   2
#> Hornet 4 Drive      21.4   6 258.0 110 3.08 3.215 19.44  1  0    3    1   0
#> Hornet Sportabout   18.7   8 360.0 175 3.15 3.440 17.02  0  0    3    2   0
#> Valiant             18.1   6 225.0 105 2.76 3.460 20.22  1  0    3    1   0
#> Duster 360          14.3   8 360.0 245 3.21 3.570 15.84  0  0    3    4   0
#> Merc 240D           24.4   4 146.7  62 3.69 3.190 20.00  1  0    4    2   0
#> Merc 230            22.8   4 140.8  95 3.92 3.150 22.90  1  0    4    2   0
#> Merc 280            19.2   6 167.6 123 3.92 3.440 18.30  1  0    4    4   0
#> Merc 280C           17.8   6 167.6 123 3.92 3.440 18.90  1  0    4    4   0
#> Merc 450SE          16.4   8 275.8 180 3.07 4.070 17.40  0  0    3    3   0
#> Merc 450SL          17.3   8 275.8 180 3.07 3.730 17.60  0  0    3    3   0
#> Merc 450SLC         15.2   8 275.8 180 3.07 3.780 18.00  0  0    3    3   0
#> Cadillac Fleetwood  10.4   8 472.0 205 2.93 5.250 17.98  0  0    3    4   0
#> Lincoln Continental 10.4   8 460.0 215 3.00 5.424 17.82  0  0    3    4   0
#> Chrysler Imperial   14.7   8 440.0 230 3.23 5.345 17.42  0  0    3    4   0
#> Fiat 128            32.4   4  78.7  66 4.08 2.200 19.47  1  1    4    1   2
#> Honda Civic         30.4   4  75.7  52 4.93 1.615 18.52  1  1    4    2   2
#> Toyota Corolla      33.9   4  71.1  65 4.22 1.835 19.90  1  1    4    1   2
#> Toyota Corona       21.5   4 120.1  97 3.70 2.465 20.01  1  0    3    1   0
#> Dodge Challenger    15.5   8 318.0 150 2.76 3.520 16.87  0  0    3    2   0
#> AMC Javelin         15.2   8 304.0 150 3.15 3.435 17.30  0  0    3    2   0
#> Camaro Z28          13.3   8 350.0 245 3.73 3.840 15.41  0  0    3    4   0
#> Pontiac Firebird    19.2   8 400.0 175 3.08 3.845 17.05  0  0    3    2   0
#> Fiat X1-9           27.3   4  79.0  66 4.08 1.935 18.90  1  1    4    1   2
#> Porsche 914-2       26.0   4 120.3  91 4.43 2.140 16.70  0  1    5    2   2
#> Lotus Europa        30.4   4  95.1 113 3.77 1.513 16.90  1  1    5    2   2
#> Ford Pantera L      15.8   8 351.0 264 4.22 3.170 14.50  0  1    5    4   2
#> Ferrari Dino        19.7   6 145.0 175 3.62 2.770 15.50  0  1    5    6   2
#> Maserati Bora       15.0   8 301.0 335 3.54 3.570 14.60  0  1    5    8   2
#> Volvo 142E          21.4   4 121.0 109 4.11 2.780 18.60  1  1    4    2   2
#> 
#> $log
#> [1] NA

# these don't
purely(dplyr::group_by)(mtcars, cyl)
#> $result
#> [1] NA
#> 
#> $log
#> [1] ""
purely(dplyr::count)(mtcars, cyl)
#> $result
#> [1] NA
#> 
#> $log
#> [1] ""

Created on 2022-03-12 by the reprex package (v2.0.1)

Ok, I've found something; seems like group_by raises a condition "dplyr_regroup". So I need to change my if else statement to be more strict.

Folks, never underestimate the power of writing your problems down, and then taking a little break: here is the solution; purely() needs to only catch "error", "message" and "warning" instead of the to permissive "condition":

purely <- function(.f){

  function(..., .log = "Log start..."){

    res <- rlang::try_fetch(
                    eval_tidy(.f(...)),
                    error = function(err) err,
                    warning = function(warn) warn,
                    message = function(message) message,
                  )

    final_result <- list(
      result = NULL,
      log = NULL
    )

    final_result$result <- if(any(c("error", "warning", "message") %in% class(res))){
                             NA
                           } else {
                             res
                           }

    final_result$log <- if(any(c("error", "warning", "message") %in% class(res))){
                             res$message
                           } else {
                             NA
                           }

    final_result


  }
}


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