Let's assume this is the source json file:
{
"name": "tom",
"age": 12,
"visits": {
"2017-01-25": 3,
"2016-07-26": 4,
"2016-01-24": 1
}
}
I want to get:
[
"age",
"name",
"visits.2017-01-25",
"visits.2016-07-26",
"visits.2016-01-24"
]
I am able to extract the keys using: jq '. | keys' file.json
, but this skips nested fields. How to include those?
With your input, the invocation:
jq 'leaf_paths | join(".")'
produces:
"name"
"age"
"visits.2017-01-25"
"visits.2016-07-26"
"visits.2016-01-24"
If you want to include "visits", use paths
. If you want the result as a JSON array, enclose the filter with square brackets: [ ... ]
If your input might include arrays, then unless you are using jq 1.6 or later, you will need to convert the integer indices to strings explicitly; also, since leaf_paths
is now deprecated, you might want to use its def. The result:
jq 'paths(scalars) | map(tostring) | join(".")'
To include paths to null, you could use allpaths
defined as follows:
def allpaths:
def conditional_recurse(f): def r: ., (select(.!=null) | f | r); r;
path(conditional_recurse(.[]?)) | select(length > 0);
Example:
{"a": null, "b": false} | allpaths | join(".")
produces:
"a"
"b"
Assuming jq version 1.5 or higher, we can get to all_leaf_paths
by following the strategy used in builtin.jq, that is, by adding these definitions:
def allpaths(f):
. as $in | allpaths | select(. as $p|$in|getpath($p)|f);
def isscalar:
. == null or . == true or . == false or type == "number" or type == "string";
def all_leaf_paths: allpaths(isscalar);
Example:
{"a": null, "b": false, "object":{"x":0} } | all_leaf_paths | join(".")
produces:
"a"
"b"
"object.x"