Foray into purrr for error handling

foray.R

library(purrr)
library(dplyr)

#---- SETUP -----------------------------------------
# A function that takes a reasonable amount of inputs
# and errors a bunch
doA <- function(letter, types, nonvar) {
    if (letter >= "c")
        stop("Error")
    expand.grid(letter, types, nonvar)
}

# Some initial values
letter <- letters[1:3]
types <- LETTERS[1:3]
nonvar <- 1

#---- THE PROBLEM -----------------------------------
# With safe values, we can pass our variables
# as a list using `pmap` and then consolidate with
# `bind_rows`.
list(letter[-3], types[-3], nonvar) %>%
    pmap(doA) %>%
    dplyr::bind_rows()

# With erroring values, we get an error
list(letter, types, nonvar) %>%
    pmap(doA) %>%
    dplyr::bind_rows()

#---- MAKING IT WORK --------------------------------
# Use the `safely` to produce list outputs for the
# function. Each element will contain a result and
# an error.
s_doA <- safely(doA)

# Use our safely version - no error!
list(letter, types, nonvar) %>%
    pmap(s_doA) ->
    int_result1

# We need to process it though. Use `map` with a
# name to extract those bits from each element.
# As the empty results aren't interesting, use
# `discard` to drop them.
int_result1 %>%
    map("result") %>%
    discard( ~ is_null(.x)) %>%
    dplyr::bind_rows() ->
    result

# We can get the error messages where applicable
# for tracking which executions errored. We use
# `map` with a vector this time for a nested selection.
# Then we need to convert the NULL elements to something
# that will stick around in a vector. We use `map_if`
# to convert all NULLs to NAs. The `as_vector` then
# simplifies the results.
int_result1 %>%
    map(c("error", "message")) %>%
    map_if(is_null, function(x)
        NA_character_) %>%
    as_vector() ->
    errors

MoreComplex.R

library(purrr)
library(dplyr)

#---- SETUP -----------------------------------------
generateTypeA_<-function(otherstuff){
    if(rnorm(1)>.75) stop(sample(LETTERS,1))
    data_frame(type="TypeA")
}
generateTypeA<-safely(generateTypeA_)

generateTypeB_<-function(otherstuff){
    if(rnorm(1)>.75) stop(sample(LETTERS,1))
    data_frame(type="TypeB")
}
generateTypeB<-safely(generateTypeB_)

generateTypeC_<-function(otherstuff){
    if(rnorm(1)>.75) stop(sample(LETTERS,1))
    data_frame(type="TypeC")
}
generateTypeC<-safely(generateTypeC_)

generateFragment_<-function(torun, otherstuff){
    torun %>% 
        invoke_map(otherstuff)
}

generateFragment<-safely(generateFragment_)

# Some initial values
torun <-c("generateTypeA", "generateTypeB", "generateTypeC")
otherstuff<-"blah"

list(torun, otherstuff) %>%
    pmap(generateFragment) ->
    int_result1

int_result1 %>% 
    map("result") %>% 
    flatten() %>% 
    map_df("result") ->
    result

int_result1 %>% 
    map("error") %>% 
    flatten -> 
    overallerrors

int_result1 %>% 
    map("result") %>% 
    flatten %>% 
    map_chr(c("error","message"), .null=NA_character_) ->
    functionerrors

L48 can become simply discard(is_null) %>%

Courtesy of @jennybc

• Use the crossing function on L10 to make a tibble output - no pesky strings as factors!
• Use pmap_df instead of map %>% bind_rows in L23
• Use compact for more succinct NULL removal in L48
• Use the sneaky .null paramater in map_chr to do L60-61 in one step! (implemented in purrr 0.2.1)