ColinFay / attempt

Tools for defensive programming in R
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{attempt}

Tools for defensive programming, inspired by {purrr} mappers and based on {rlang}.

{attempt} is designed to handle the cases when something / someone attempts to do something it shouldn’t.

For example:

{attempt} provides several condition handlers, from try catch to simple message printing.

{attempt} only depends on {rlang}, and every function is design to be fast, making it easy to implement in other functions and packages.

Install

From CRAN:

install.packages("attempt")

The dev version:

install.packages("attempt", repo = "https://colinfay.me/ran")

Reference

library(attempt)

attempt

attempt() is a wrapper around base try() that allows you to insert a custom messsage on error.

attempt(log("a"))
# Error: non-numeric argument to mathematical function
attempt(log("a"), msg = "Nop !")
# Error: Nop !

You can make it verbose (i.e. returning the expression):

attempt(log("a"), msg = "Nop !", verbose = TRUE)
# Error in log("a"): Nop !

Of course the result is returned if there is one:

attempt(log(1), msg = "Nop !", verbose = TRUE)
# [1] 0

As with try(), the result can be saved as an error object:

a <- attempt(log("a"), msg = "Nop !", verbose = TRUE)
a
# [1] "Error in log(\"a\"): Nop !\n"
# attr(,"class")
# [1] "try-error"
# attr(,"condition")
# <simpleError in log("a"): Nop !>

You can check if the result is an error with is_try_error()

a <- attempt(log("a"), msg = "Nop !", verbose = FALSE)
#> Error: Nop !
is_try_error(a)
#> [1] TRUE

silent_attempt

silent_attempt() is a wrapper around silently() (see further down for more info) and attempt(). It attempts to run the expr, stays silent if the expression succeeds, and returns error or warnings if any.

silent_attempt(log("a"))
# Error: non-numeric argument to mathematical function
silent_attempt(log(1))

try catch

You can write a try catch with these params:

In .e and .f, the .x refers to the error / warning object.

With mappers

try_catch(expr = log("a"), 
          .e = ~ paste0("There is an error: ", .x), 
          .w = ~ paste0("This is a warning: ", .x))
#[1] "There is an error: Error in log(\"a\"): non-numeric argument to mathematical function\n"

try_catch(log("a"), 
          .e = ~ stop(.x), 
          .w = ~ warning(.x))
# Error in log("a") : non-numeric argument to mathematical function

try_catch(matrix(1:3, nrow= 2), 
          .e = ~ print(.x), 
          .w = ~ print(.x))
#<simpleWarning in matrix(1:3, nrow = 2): data length [3] is not a sub-multiple or multiple of the number of rows [2]>

try_catch(expr = 2 + 2 , 
          .f = ~ print("Using R for addition... ok I'm out!"))
# [1] "Using R for addition... ok I'm out!"
# [1] 4

As usual, the handlers are set only if you call them:

try_catch(matrix(1:3, nrow = 2), .e = ~ print("error"))
#      [,1] [,2]
# [1,]    1    3
# [2,]    2    1
# Warning message:
# In matrix(1:3, nrow = 2) :
# data length [3] is not a sub-multiple or multiple of the number of rows [2]
try_catch(matrix(1:3, nrow = 2), .w = ~ print("warning"))
# [1] "warning"

Traditionnal way

{attempt} is flexible in how you can specify your arguments.

You can, as you do with {base} tryCatch(), use a plain old function:

try_catch(log("a"), 
          .e = function(e){
            print(paste0("There is an error: ", e))
            print("Ok, let's save this")
            time <- Sys.time()
            a <- paste("+ At",time, ", \nError:",e)
            # write(a, "log.txt", append = TRUE) # commented to prevent log.txt creation 
            print(paste("log saved on log.txt at", time))
            print("let's move on now")
          })

# [1] "There is an error: Error in log(\"a\"): non-numeric argument to mathematical function\n"
# [1] "Ok, let's save this"
# [1] "log saved on log.txt at 2018-01-30 16:59:13"
# [1] "let's move on now"

You can even mix both:

try_catch(log("a"), 
          .e = function(e){
            paste0("There is an error: ", e)
          },
          .f = ~ print("I'm not sure you can do that pal !"))
# [1] "I'm not sure you can do that pal !"
# [1] "There is an error: Error in log(\"a\"): non-numeric argument to mathematical function\n"

try_catch(log("a"), 
          .e = ~ paste0("There is an error: ", .x),
          .f = function() print("I'm not sure you can do that pal !"))
# [1] "I'm not sure you can do that pal !"
# [1] "There is an error: Error in log(\"a\"): non-numeric argument to mathematical function\n"

try_catch_df()

try_catch_df() returns a tibble with the call, the error message if any, the warning message if any, and the value of the evaluated expression or “error”. The values will always be contained in a list-column.

res_log <- try_catch_df(log("a"))
res_log
#>       call                                         error warning value
#> 1 log("a") non-numeric argument to mathematical function      NA error
res_log$value
#> [[1]]
#> [1] "error"

res_matrix <- try_catch_df(matrix(1:3, nrow = 2))
res_matrix
#>                    call error
#> 1 matrix(1:3, nrow = 2)    NA
#>                                                                       warning
#> 1 data length [3] is not a sub-multiple or multiple of the number of rows [2]
#>        value
#> 1 1, 2, 3, 1
res_matrix$value
#> [[1]]
#>      [,1] [,2]
#> [1,]    1    3
#> [2,]    2    1

res_success <- try_catch_df(log(1))
res_success
#>     call error warning value
#> 1 log(1)    NA      NA     0
res_success$value
#> [[1]]
#> [1] 0

map_try_catch()

map_try_catch() and map_try_catch_df() allow you to map on a list of arguments l, to be evaluated by the function in fun.

map_try_catch(l = list(1, 3, "a"), fun = log, .e = ~ .x)
#> [[1]]
#> [1] 0
#> 
#> [[2]]
#> [1] 1.098612
#> 
#> [[3]]
#> <simpleError in .Primitive("log")("a"): non-numeric argument to mathematical function>

map_try_catch_df(list(1,3,"a"), log)
#>                     call                                         error
#> 1   .Primitive("log")(1)                                          <NA>
#> 2   .Primitive("log")(3)                                          <NA>
#> 3 .Primitive("log")("a") non-numeric argument to mathematical function
#>   warning    value
#> 1      NA        0
#> 2      NA 1.098612
#> 3      NA    error

Adverbs

Adverbs take a function and return a modified function.

silently()

silently() transforms a function so that when you call this new function, it returns nothing unless there is an error or a warning (contrary to attempt that returns the result). In a sense, the new function stay silent unless error or warning.

silent_log <- silently(log)
silent_log(1)
silent_log("a")
#> Error in .f(...) : non-numeric argument to mathematical function
# Error in .f(...) : non-numeric argument to mathematical function

With silently(), the result is never returned.

silent_matrix <- silently(matrix)
silent_matrix(1:3, 2)
#Warning message:
#In .f(...) :
#  data length [3] is not a sub-multiple or multiple of the number of rows [2]

surely()

surely() transforms a function so that when you call this new function, it calls attempt() - i.e. in the code below, calling sure_log(1) is the same as calling attempt(log(1)). In a sense, you’re sure this new function will always work.

sure_log <- surely(log)
sure_log(1)
# [1] 0
sure_log("a")
# Error: non-numeric argument to mathematical function

with_message() and with_warning()

These two functions take a function, and add a warning or a message to it.

as_num_msg <- with_message(as.numeric, msg = "We're performing a numeric conversion")
as_num_warn <- with_warning(as.numeric, msg = "We're performing a numeric conversion")
as_num_msg("1")
#> We're performing a numeric conversion
#> [1] 1
as_num_warn("1")
#> Warning in as_num_warn("1"): We're performing a numeric conversion
#> [1] 1

without_message(), without_warning(), and discretly()

These three functions do the opposite, as they remove warnings and messages:

matrix(1:3, ncol = 2)
no_warning_matrix <- without_warning(matrix)
no_warning_matrix(1:3, ncol = 2)

if_ conditions

if_none(), if_any() and if_all() test the elements of the list.

if_all(1:10, ~ .x < 11, ~ return(letters[1:10]))
#>  [1] "a" "b" "c" "d" "e" "f" "g" "h" "i" "j"

if_any(1:10, is.numeric, ~ "Yay!")
#> [1] "Yay!"

if_none(1:10, is.character, ~ rnorm(10))
#>  [1] -0.62041260  1.18903502  0.34425236  0.40211829 -0.89651209
#>  [6]  0.08673175 -0.65066136  0.47734033 -1.34301785 -0.20193553

The defaut for all .p is isTRUE(). So you can:

a <- c(FALSE, TRUE, TRUE, TRUE)

if_any(a, .f = ~ "nop!")
#> [1] "nop!"

if_then() performs a simple “if this then do that”:

if_then(1, is.numeric, ~ "nop!")
#> [1] "nop!"

if_not() runs .f if .p(.x) is not TRUE :

if_not(.x = 1, .p = is.character, ~ ".x is not a character")
#> [1] ".x is not a character"

And if_else() is a wrapper around base::ifelse().

If you want these function to return a value, you need to wrap these values into a mapper / a function. E.g, to return a vector, you’ll need to write if_then(1, is.numeric, ~ "Yay").

a <- if_else(1, is.numeric, ~ "Yay", ~ "Nay")
a
#> [1] "Yay"

warnings and messages

The stop_if(), warn_if() and message_if() are easy to use functions that send an error, a warning or a message if a condition is met. Each function has its counterpart with _not that returns a message if the condition is not met.

stop_if_not() is quite the same as assert_that() from the {assertthat} package, except that it can takes mappers. It is not the same as base stopifnot(), as it doesn’t take a list of expression.

These functions are also flexible as you can pass base predicates (is.numeric, is.character…), a custom predicate built with mappers, or even your own predicate function.

You can either choose a custom message or just let the built-in messages be printed:

x <- 12
# Stop if .x is numeric
stop_if(.x = x, 
        .p = is.numeric)
#> Error: Test `is.numeric` on `x` returned an error.

y <- "20"
# stop if .x is not numeric
stop_if_not(.x = y, 
            .p = is.numeric, 
            msg = "y should be numeric")
#> Error: y should be numeric
a  <- "this is not numeric"
# Warn if .x is charcter
warn_if(.x = a, 
        .p = is.character)
#> Warning: Test `is.character` on `a` returned a warning.

b  <- 20
# Warn if .x is not equal to 10
warn_if_not(.x = b, 
        .p = ~ .x == 10 , 
        msg = "b should be 10")
#> Warning: b should be 10

c <- "a"
# Message if c is a character
message_if(.x = c, 
           .p = is.character, 
           msg = "You entered a character element")
#> You entered a character element

# Build more complex predicates
d <- 100
message_if(.x = d, 
           .p = ~ sqrt(.x) < 42, 
           msg = "The square root of your element must be more than 42")
#> The square root of your element must be more than 42

# Or, if you're kind of old school, you can still pass classic functions

e <- 30
message_if(.x = e, 
           .p = function(vec){
             return(sqrt(vec) < 42)
           }, 
           msg = "The square root of your element must be more than 42")
#> The square root of your element must be more than 42

If you need to call a function that takes no argument at .p (like curl::has_internet()), use this function as .x.

stop_if(.x = curl::has_internet(), msg = "You shouldn't have internet to do that")
#> Error: You shouldn't have internet to do that

warn_if(.x = curl::has_internet(), 
            msg = "You shouldn't have internet to do that")
#> Warning: You shouldn't have internet to do that

message_if(.x = curl::has_internet(), 
            msg = "Huray, you have internet \\o/")
#> Huray, you have internet \o/

If you don’t specify a .p, the default test is isTRUE().

a <- is.na(airquality$Ozone)
message_if_any(a, msg = "NA found")
#> NA found

In function

That can come really handy inside a function:

my_fun <- function(x){
  stop_if_not(.x = curl::has_internet(), 
              msg = "You should have internet to do that")
  warn_if_not(x, 
          is.character, 
          msg =  "x is not a character vector. The output may not be what you're expecting.")
  paste(x, "is the value.")
}

my_fun(head(iris))
#> Warning: x is not a character vector. The output may not be what you're
#> expecting.
#> [1] "c(5.1, 4.9, 4.7, 4.6, 5, 5.4) is the value."  
#> [2] "c(3.5, 3, 3.2, 3.1, 3.6, 3.9) is the value."  
#> [3] "c(1.4, 1.4, 1.3, 1.5, 1.4, 1.7) is the value."
#> [4] "c(0.2, 0.2, 0.2, 0.2, 0.2, 0.4) is the value."
#> [5] "c(1, 1, 1, 1, 1, 1) is the value."

none, all, any

stop_if(), warn_if() and message_if() all have complementary tests with _all, _any and _none, which combine the if_* and the warn_*, stop_* and message_* seen before. They take a list as first argument, and a predicate. They test if any, all or none of the elements validate the predicate.

stop_if_any(iris, is.factor, msg = "Factors here. This might be due to stringsAsFactors.")
#> Error: Factors here. This might be due to stringsAsFactors.

warn_if_none(1:10, ~ .x < 0, msg = "You need to have at least one number under zero.")
#> Warning: You need to have at least one number under zero.

message_if_all(1:100, is.numeric, msg = "That makes a lot of numbers.")
#> That makes a lot of numbers.

on_error()

on_error() behaves as on.exit() except it happens only when there is an error in the function.

y <- function(x){
  on_error(~ print("ouch"))
  log(x)
}
y(12)
[1] 2.484907
y("a")
Error in log(x) : non-numeric argument to mathematical function
[1] "ouch"

Misc

Acknowledgments

Thanks to Romain for the name suggestion.

Contact

Questions and feedbacks welcome!

You want to contribute ? Open a PR :) If you encounter a bug or want to suggest an enhancement, please open an issue.

Please note that this project is released with a Contributor Code of Conduct. By participating in this project you agree to abide by its terms.