pull all elements with specific name from a nested list - r

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 with lists nested in some cells. As this dataset gets bigger, I want to pick elements out of this list more smartly so that when this cache becomes big it doesn't take forever to create the data.frame or tibble with the elements I want.
Example where I am trying to pull everything named "type" below into a vector or flat list that I can pull in as a dataframe variable. I named the folder and message level for convenience. Anyone have model code that can help?
library(tidyverse)
l <- list(folder_1 = list(
`msg_1-1` = list(type = "message",
subtype = "channel_join",
ts = "1585771048.000200",
user = "UFUNNF8MA",
text = "<#UFUNNF8MA> has joined the channel"),
`msg_1-2` = list(type = "message",
subtype = "channel_purpose",
ts = "1585771049.000300",
user = "UNFUNQ8MA",
text = "<#UNFUNQ8MA> set the channel purpose: Talk about xyz")),
folder_2 = list(
`msg_2-1` = list(type = "message",
subtype = "channel_join",
ts = "1585771120.000200",
user = "UQKUNF8MA",
text = "<#UQKUNF8MA> has joined the channel"))
)
# gets a specific element
print(l[[1]][[1]][["type"]])
# tried to get all elements named "type", but am not at the right list level to do so
print(purrr::map(l, "type"))

Answer 1

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 2

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 3

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

Answer 4

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")