Tidyjson: is there an 'exit_object()' equivalent? - json

Question

I'm using package tidyjson to parse a json string and extract the key values into columns. The json in nested, and while I can drill down at a node, I can't figure out a way to go up to the previous level. The code is below:
library(tidyjson)
library(data.table)
library(dplyr)
input <- '{
"name": "Bob",
"age": 30,
"social": {
"married": "yes",
"kids": "no"
},
"work": {
"title": "engineer",
"salary": 5000
}
}'
output <- input %>% as.tbl_json() %>%
spread_values(name = jstring("name"),
age = jnumber("age")) %>%
enter_object("social") %>%
spread_values(married = jstring("married"),
kids = jstring("kids")) %>%
#### I would need an exit_obeject() here
enter_object("work") %>%
spread_values(title = jstring("title"),
salary = jnumber("salary"))

Answer 1

There's a note in the documentation:
"Note that there are often situations where there are multiple arrays
or objects of differing types that exist at the same level of the JSON
hierarchy. In this case, you need to use enter_object() to enter each
of them in separate pipelines to create separate data.frames that can
then be joined relationally."
As such I've been staging my tidyjson commands and putting the outputs together with merge, e.g.:
# first the high-level values
output_table <- input_tbl_json %>%
spread_values(val1 = jstring('val1'),
val2 = jnumber('val2'))
# then enter an object and get something from inside, merging it as a new column
output_table <- merge(output_table,
input_tbl_json %>%
enter_object('thing') %>%
spread_values(val3 = jstring('thing1')),
by = c('document.id'))
output table columns should look like | document.id | val1 | val2 | val3 |
That workflow may fall over with operations like gather_keys() that add rows, but I haven't had call to test it.

Answer 2

I think an overlooked piece of functionality within tidyjson is the ability to use more complex paths in the jnumber, jstring, etc. functions.
You can do something like the following without "entering an object." I find this to be a very satisfying solution, for the most part. Perhaps more satisfying than multiple enter/exits.
input <- '{
"name": "Bob",
"age": 30,
"social": {
"married": "yes",
"kids": "no"
},
"work": {
"title": "engineer",
"salary": 5000
}
}'
output <- input %>% as.tbl_json() %>%
spread_values(
name = jstring('name')
, age=jnumber('age')
, married=jstring('social','married')
, kids = jstring('social','kids')
, title= jstring('work','title')
, salary = jnumber('work','salary')
)