pull all elements with specific name from a nested list

Question

I have some archived Slack data that I am trying to get some of key message properties. I\'d done this by stupidly flattening the entire list, getting a data.frame or tibble

Answer 1

Depending on the desired output, I would probably use a simple recursive function here.

get_elements <- function(x, element) {
  if(is.list(x))
  {
    if(element %in% names(x)) x[[element]]
    else lapply(x, get_elements, element = element)
  }
}

This allows:

get_elements(l, "type")
#> $folder_1
#> $folder_1$`msg_1-1`
#> [1] "message"
#> 
#> $folder_1$`msg_1-2`
#> [1] "message"
#> 
#> 
#> $folder_2
#> $folder_2$`msg_2-1`
#> [1] "message"

Or if you want to get all "users":

get_elements(l, "user")
#> $folder_1
#> $folder_1$`msg_1-1`
#> [1] "UFUNNF8MA"
#> 
#> $folder_1$`msg_1-2`
#> [1] "UNFUNQ8MA"
#> 
#> 
#> $folder_2
#> $folder_2$`msg_2-1`
#> [1] "UQKUNF8MA"

You could obviously unlist the result if you prefer it flattened into a vector.

unlist(get_elements(l, "type"))
#> folder_1.msg_1-1 folder_1.msg_1-2 folder_2.msg_2-1 
#>        "message"        "message"        "message" 

Answer 2

As OP mentioned, this can solve the issue:

#Code
unlist(l)[grepl('.type',names(unlist(l)),fixed=T)]

Output:

folder_1.msg_1-1.type folder_1.msg_1-2.type folder_2.msg_2-1.type 
            "message"             "message"             "message" 

Another options are (Many thanks and credit to @Abdessabour Mtk)

#Code1
purrr::map(l, ~ purrr::map(.x, "type"))

Answer 3

Related to those provided by @Duck & @Abdessabour Mtk yesterday, purrr has a function map_depth() that will let you get a named attribute if you know its name and how deep it is in the hierarchy. REALLY useful when crawling this big nested lists, and is a simpler solution to the nested map() calls above.

purrr::map_depth(l, 2, "type")

Answer 4

Another option is to use rrapply() in the rrapply-package:

library(rrapply)

## return unlisted vector
rrapply(l, condition = function(x, .xname) .xname == "type", how = "unlist")
#> folder_1.msg_1-1.type folder_1.msg_1-2.type folder_2.msg_2-1.type 
#>             "message"             "message"             "message"

## return melted data.frame
rrapply(l, condition = function(x, .xname) .xname == "type", how = "melt")
#>         L1      L2   L3   value
#> 1 folder_1 msg_1-1 type message
#> 2 folder_1 msg_1-2 type message
#> 3 folder_2 msg_2-1 type message