i have JSON file called myresponse.json.
"status":"CONTENT",
"valid":true,
"success":true,
"failure":false,
"content":{
"id":0,"resources":[{
"id":0,"value":52.51742935180664
},
{
"id":1,"value":13.392845153808594
},
{
"id":5,"value":"2021-02-09T13:15:15Z"
},
{
"id":6,"value":20.754192352294922
}]}}}
"status":"CONTENT",
"valid":true,
"success":true,
"failure":false,
"content":{
"id":0,"resources":[{
"id":0,"value":52.51742935180664
},
{
"id":1,"value":13.392845153808594
},
{
"id":5,"value":"2021-02-09T13:15:15Z"
},
{
"id":6,"value":20.754192352294922
}]}}}
obtained with a curl.
how can i use jq to convert json to csv file where "0,1,5,6" must be the columns and the values of "0,1,5,6" must respectively occupy each row of the csv file, like this:
0,1,5,6
52.51742935180664, 13.392845153808594, "2021-02-09T13:15:15Z", 20.754192352294922
52.51742935180664, 13.392845153808594, "2021-02-09T13:15:15Z", 20.754192352294922
Thanks for your help!
The following assumes the input consists of a stream of valid JSON objects along the lines shown in the question.
If the relevant values of .id are known beforehand, then generating the header row is trivial, and a solution implemented with flexibility in mind is as follows:
def oneline:
.content.resources
| INDEX(.[]; .id) | map_values(.value);
def emit($keys):
[.[ $keys[] ]];
[0,1,5,6] as $keys
| $keys,
(inputs | oneline | emit($keys))
| join(",")
Since this relies on inputs to read the input, jq should be invoked with the -r and -n options (e.g. jq -rn -f program.jq)
Using the first object to determine the relevant .id values
If the relevant values of .id are determined by the first JSON object in the stream, the above defs can be reused with the following:
(input | oneline) as $first
| ($first | keys) as $keys
| $keys,
($first | emit($keys)),
(inputs | oneline | emit($keys))
| join(",")
This solution would be used with jq's -r and -n options.
I receive the following input file:
input.json:
[
{"ID":"aaa_12301248","time_CET":"00:00:00","VALUE":10,"FLAG":"0"},
{"ID":"aaa_12301248","time_CET":"00:15:00","VALUE":18,"FLAG":"0"},
{"ID":"aaa_12301248","time_CET":"00:30:00","VALUE":160,"FLAG":"0"},
{"ID":"bbb_0021122","time_CET":"00:00:00","VALUE":null,"FLAG":"?"},
{"ID":"bbb_0021122","time_CET":"00:15:00","VALUE":null,"FLAG":"?"},
{"ID":"bbb_0021122","time_CET":"00:30:00","VALUE":22,"FLAG":"0"},
{"ID":"ccc_0021122","time_CET":"00:00:00","VALUE":null,"FLAG":"?"},
{"ID":"ccc_0021122","time_CET":"00:15:00","VALUE":null,"FLAG":"?"},
{"ID":"ccc_0021122","time_CET":"00:30:00","VALUE":20,"FLAG":"0"},
{"ID":"ddd_122455","time_CET":"00:00:00","VALUE":null,"FLAG":"?"},
{"ID":"ddd_122455","time_CET":"00:15:00","VALUE":null,"FLAG":"?"},
{"ID":"ddd_122455","time_CET":"00:30:00","VALUE":null,"FLAG":"?"},
]
As you can see there are some valid values (FLAG: 0) and some invalid values (FLAG: "?").
Now I got a file looking like this (one for each ID):
aaa.json:
[
{"ID":"aaa_12301248","time_CET":"00:00:00","VALUE":10,"FLAG":"0"},
{"ID":"aaa_12301248","time_CET":"00:15:00","VALUE":null,"FLAG":"?"},
{"ID":"aaa_12301248","time_CET":"00:55:00","VALUE":45,"FLAG":"0"}
]
As you can see, object one is the same as in input.json but object two is invalid (FLAG: "?"). That's why object two has to be replaced by the correct object from input.json (with VALUE:18).
Objects can be identified by "time_CET" and "ID" element.
Additionally, there will be new objects in input.json, that have not been part of aaa.json etc. These objects should be added to the array, and valid objects from aaa.json should be kept.
In the end, aaa.json should look like this:
[
{"ID":"aaa_12301248","time_CET":"00:00:00","VALUE":10,"FLAG":"0"},
{"ID":"aaa_12301248","time_CET":"00:15:00","VALUE":18,"FLAG":"0"},
{"ID":"aaa_12301248","time_CET":"00:30:00","VALUE":160,"FLAG":"0"},
{"ID":"aaa_12301248","time_CET":"00:55:00","VALUE":45,"FLAG":"0"}
]
So, to summarize:
look for FLAG: "?" in aaa.json
replace this object with matching object from input.json using "ID"
and "time_CET" for mapping.
Keep exisiting valid objects and add objects from input.json that
did not exist in aaa.json before (this means only objects starting
with "aaa" in "ID" field)
repeat this for bbb.json, ccc.json and ddd.json
I am not sure if it's possible to get this done all at once with a command like this, because the output has to go to back to the correct id files (aaa, bbb ccc.json):
jq --argfile aaa aaa.json --argfile bbb bbb.json .... -f prog.jq input.json
The problem is, that the number after the identifier (aaa, bbb, ccc etc.) may change. So to make sure objects are added to the correct file/array, a statement like this would be required:
if (."ID"|contains("aaa")) then ....
Or is it better to run the program several times with different input parameters? I am not sure..
Thank you in advance!!
Here is one approach
#!/bin/bash
# usage: update.sh input.json aaa.json bbb.json....
# updates each of aaa.json bbb.json....
input_json="$1"
shift
for i in "$#"; do
jq -M --argfile input_json "$input_json" '
# functions to restrict input.json to keys of current xxx.json file
def prefix: input_filename | split(".")[0];
def selectprefix: select(.ID | startswith(prefix));
# functions to build and probe a lookup table
def pk: [.ID, .time_CET];
def lookup($t;$k): $t | getpath($k);
def lookup($t): lookup($t;pk);
def organize(s): reduce s as $r ({}; setpath($r|pk; $r));
# functions to identify objects in input.json missing from xxx.json
def pks: paths | select(length==2);
def missing($t1;$t2): [$t1|pks] - [$t2|pks] | .[];
def getmissing($t1;$t2): [ missing($t1;$t2) as $p | lookup($t1;$p)];
# main routine
organize(.[]) as $xxx
| organize($input_json[] | selectprefix) as $inp
| map(if .FLAG != "?" then . else . += lookup($inp) end)
| . + getmissing($inp;$xxx)
' "$i" | sponge "$i"
done
The script uses jq in a loop to read and update each aaa.json... file.
The filter creates temporary objects to facilitate looking up values by [ID,time_CET], updates any values in the aaa.json with a FLAG=="?" and finally adds any values from input.json that are missing in aaa.json.
The temporary lookup table for input.json uses input_filename so that only keys starting with a prefix matching the name of the currently processed file will be included.
Sample Run:
$ ./update.sh input.json aaa.json
aaa.json after run:
[
{
"ID": "aaa_12301248",
"time_CET": "00:00:00",
"VALUE": 10,
"FLAG": "0"
},
{
"ID": "aaa_12301248",
"time_CET": "00:15:00",
"VALUE": 18,
"FLAG": "0"
},
{
"ID": "aaa_12301248",
"time_CET": "00:55:00",
"VALUE": 45,
"FLAG": "0"
},
{
"ID": "aaa_12301248",
"time_CET": "00:30:00",
"VALUE": 160,
"FLAG": "0"
}
]
I have a nested JSON object where each level has the same property key and what distinguishes each level is a property called name. If I want to traverse down to a level which has a particular "path" of name properties, how would I formulate the jq filter?
Here is some sample JSON data that represents a file system's directory structure:
{
"subs": [
{
"name": "aaa",
"subs": [
{
"name": "bbb",
"subs": [
{
"name": "ccc",
"subs": [
{
"name": "ddd",
"payload": "xyz"
}
]
}
]
}
]
}
]
}
What's a jq filter for obtaining the value of the payload in the "path" aaa/bbb/ccc/ddd?
Prior research:
jq - select objects with given key name - helpful but looks for any element in the JSON which contains the specified name whereas I'm looking for an element that's nested under a set of objects who also have specific names.
http://arjanvandergaag.nl/blog/wrestling-json-with-jq.html - helpful in section 4 where it shows how to extract an object having a property name having a particular value. However, the recursion performed is based a specific known set of property names ("values[].links.clone[]"). In my case, my equivalent is just "subs[].subs[].subs[]".
Here is the basis for a generic solution:
def descend(name): .subs[] | select(.name == name);
So your particular query could be formulated as follows:
descend( "aaa") | descend( "bbb") | descend( "ccc") | descend( "ddd") | .payload
Or slightly better, still using the above definition of descend:
def path(array):
if (array|length)==0 then .
else descend(array[0]) | path(array[1:])
end;
path( ["aaa", "bbb", "ccc", "ddd"] ) | .payload
TCO
The above recursive definition of path/1 is simple enough but would be unsuitable for very deeply nested data structures, e.g. if the depth is greater than 1000. Here is an alternative definition that takes advantage of jq's tail-call optimization, and that therefore runs very quickly:
def atpath(array):
[array, .]
| until( .[0] == []; .[0] as $a | .[1] | descend($a[0]) | [$a[1:], . ] )
| .[1];
.aaa.bbb.ccc.ddd
If you want to be able to use the .aaa.bbb.ccc.ddd notation, one approach would be to begin by "flattening" the data:
def flat:
{ (.name): (if .subs then (.subs[] | flat) else .payload end) };
Since the top-level element does not have a "name" tag, the query would then be:
.subs[] | flat | .aaa.bbb.ccc.ddd
Here is a more efficient approach, once again using descend defined above:
def payload(p):
def get($array):
if $array == []
then .payload
else descend($array[0]) | get($array[1:]) end;
get( null | path(p) );
payload( .aaa.bbb.ccc.ddd )
The filter in the following jq command recurses down a "path" of objects that have name properties which correspond to the "path" aaa/bbb/ccc/ddd:
jq '.subs[] | select(.name = "aaa") | .subs[] | select(.name = "bbb") | .subs[] | select(.name = "ccc") | .subs[] | .payload'
Here it is live on qplay.org:
https://jqplay.org/s/tblW7UX0Si
In a very large nested json structure I'm trying to find all of the paths that end in a key.
ex:
{
"A": {
"A1": {
"foo": {
"_": "_"
}
},
"A2": {
"_": "_"
}
},
"B": {
"B1": {}
},
"foo": {
"_": "_"
}
}
would print something along the lines of:
["A","A1","foo"], ["foo"]
Unfortunately I don't know at what level of nesting the keys will appear, so I haven't been able to figure it out with a simple select. I've gotten close with jq '[paths] | .[] | select(contains(["foo"]))', but the output contains all the permutations of any tree that contains foo.
output: ["A", "A1", "foo"]["A", "A1", "foo", "_"]["foo"][ "foo", "_"]
Bonus points if I could keep the original data structure format but simply filter out all paths that don't contain the key (in this case the sub trees under "foo" wouldn't need to be hidden).
With your input:
$ jq -c 'paths | select(.[-1] == "foo")'
["A","A1","foo"]
["foo"]
Bonus points:
(1) If your jq has tostream:
$ jq 'fromstream(tostream| select(.[0]|index("foo")))'
Or better yet, since your input is large, you can use the streaming parser (jq -n --stream) with this filter:
fromstream( inputs|select( (.[0]|index("foo"))))
(2) Whether or not your jq has tostream:
. as $in
| reduce (paths(scalars) | select(index("foo"))) as $p
(null; setpath($p; $in|getpath($p)))
In all three cases, the output is:
{
"A": {
"A1": {
"foo": {
"_": "_"
}
}
},
"foo": {
"_": "_"
}
}
I had the same fundamental problem.
With (yaml) input like:
developer:
android:
members:
- alice
- bob
oncall:
- bob
hr:
members:
- charlie
- doug
this:
is:
really:
deep:
nesting:
members:
- example deep nesting
I wanted to find all arbitrarily nested groups and get their members.
Using this:
yq . | # convert yaml to json using python-yq
jq '
. as $input | # Save the input for later
. | paths | # Get the list of paths
select(.[-1] | tostring | test("^(members|oncall|priv)$"; "ix")) | # Only find paths which end with members, oncall, and priv
. as $path | # save each path in the $path variable
( $input | getpath($path) ) as $members | # Get the value of each path from the original input
{
"key": ( $path | join("-") ), # The key is the join of all path keys
"value": $members # The value is the list of members
}
' |
jq -s 'from_entries' | # collect kv pairs into a full object using slurp
yq --sort-keys -y . # Convert back to yaml using python-yq
I get output like this:
developer-android-members:
- alice
- bob
developer-android-oncall:
- bob
hr-members:
- charlie
- doug
this-is-really-deep-nesting-members:
- example deep nesting
Using jq, how can arbitrary JSON encoding an array of shallow objects be converted to CSV?
There are plenty of Q&As on this site that cover specific data models which hard-code the fields, but answers to this question should work given any JSON, with the only restriction that it's an array of objects with scalar properties (no deep/complex/sub-objects, as flattening these is another question). The result should contain a header row giving the field names. Preference will be given to answers that preserve the field order of the first object, but it's not a requirement. Results may enclose all cells with double-quotes, or only enclose those that require quoting (e.g. 'a,b').
Examples
Input:
[
{"code": "NSW", "name": "New South Wales", "level":"state", "country": "AU"},
{"code": "AB", "name": "Alberta", "level":"province", "country": "CA"},
{"code": "ABD", "name": "Aberdeenshire", "level":"council area", "country": "GB"},
{"code": "AK", "name": "Alaska", "level":"state", "country": "US"}
]
Possible output:
code,name,level,country
NSW,New South Wales,state,AU
AB,Alberta,province,CA
ABD,Aberdeenshire,council area,GB
AK,Alaska,state,US
Possible output:
"code","name","level","country"
"NSW","New South Wales","state","AU"
"AB","Alberta","province","CA"
"ABD","Aberdeenshire","council area","GB"
"AK","Alaska","state","US"
Input:
[
{"name": "bang", "value": "!", "level": 0},
{"name": "letters", "value": "a,b,c", "level": 0},
{"name": "letters", "value": "x,y,z", "level": 1},
{"name": "bang", "value": "\"!\"", "level": 1}
]
Possible output:
name,value,level
bang,!,0
letters,"a,b,c",0
letters,"x,y,z",1
bang,"""!""",0
Possible output:
"name","value","level"
"bang","!","0"
"letters","a,b,c","0"
"letters","x,y,z","1"
"bang","""!""","1"
First, obtain an array containing all the different object property names in your object array input. Those will be the columns of your CSV:
(map(keys) | add | unique) as $cols
Then, for each object in the object array input, map the column names you obtained to the corresponding properties in the object. Those will be the rows of your CSV.
map(. as $row | $cols | map($row[.])) as $rows
Finally, put the column names before the rows, as a header for the CSV, and pass the resulting row stream to the #csv filter.
$cols, $rows[] | #csv
All together now. Remember to use the -r flag to get the result as a raw string:
jq -r '(map(keys) | add | unique) as $cols | map(. as $row | $cols | map($row[.])) as $rows | $cols, $rows[] | #csv'
The Skinny
jq -r '(.[0] | keys_unsorted) as $keys | $keys, map([.[ $keys[] ]])[] | #csv'
or:
jq -r '(.[0] | keys_unsorted) as $keys | ([$keys] + map([.[ $keys[] ]])) [] | #csv'
The Details
Aside
Describing the details is tricky because jq is stream-oriented, meaning it operates on a sequence of JSON data, rather than a single value. The input JSON stream gets converted to some internal type which is passed through the filters, then encoded in an output stream at program's end. The internal type isn't modeled by JSON, and doesn't exist as a named type. It's most easily demonstrated by examining the output of a bare index (.[]) or the comma operator (examining it directly could be done with a debugger, but that would be in terms of jq's internal data types, rather than the conceptual data types behind JSON).
$ jq -c '.[]' <<<'["a", "b"]'
"a"
"b"
$ jq -cn '"a", "b"'
"a"
"b"
Note that the output isn't an array (which would be ["a", "b"]). Compact output (the -c option) shows that each array element (or argument to the , filter) becomes a separate object in the output (each is on a separate line).
A stream is like a JSON-seq, but uses newlines rather than RS as an output separator when encoded. Consequently, this internal type is referred to by the generic term "sequence" in this answer, with "stream" being reserved for the encoded input and output.
Constructing the Filter
The first object's keys can be extracted with:
.[0] | keys_unsorted
Keys will generally be kept in their original order, but preserving the exact order isn't guaranteed. Consequently, they will need to be used to index the objects to get the values in the same order. This will also prevent values being in the wrong columns if some objects have a different key order.
To both output the keys as the first row and make them available for indexing, they're stored in a variable. The next stage of the pipeline then references this variable and uses the comma operator to prepend the header to the output stream.
(.[0] | keys_unsorted) as $keys | $keys, ...
The expression after the comma is a little involved. The index operator on an object can take a sequence of strings (e.g. "name", "value"), returning a sequence of property values for those strings. $keys is an array, not a sequence, so [] is applied to convert it to a sequence,
$keys[]
which can then be passed to .[]
.[ $keys[] ]
This, too, produces a sequence, so the array constructor is used to convert it to an array.
[.[ $keys[] ]]
This expression is to be applied to a single object. map() is used to apply it to all objects in the outer array:
map([.[ $keys[] ]])
Lastly for this stage, this is converted to a sequence so each item becomes a separate row in the output.
map([.[ $keys[] ]])[]
Why bundle the sequence into an array within the map only to unbundle it outside? map produces an array; .[ $keys[] ] produces a sequence. Applying map to the sequence from .[ $keys[] ] would produce an array of sequences of values, but since sequences aren't a JSON type, so you instead get a flattened array containing all the values.
["NSW","AU","state","New South Wales","AB","CA","province","Alberta","ABD","GB","council area","Aberdeenshire","AK","US","state","Alaska"]
The values from each object need to be kept separate, so that they become separate rows in the final output.
Finally, the sequence is passed through #csv formatter.
Alternate
The items can be separated late, rather than early. Instead of using the comma operator to get a sequence (passing a sequence as the right operand), the header sequence ($keys) can be wrapped in an array, and + used to append the array of values. This still needs to be converted to a sequence before being passed to #csv.
The following filter is slightly different in that it will ensure every value is converted to a string. (jq 1.5+)
# For an array of many objects
jq -f filter.jq [file]
# For many objects (not within array)
jq -s -f filter.jq [file]
Filter: filter.jq
def tocsv:
(map(keys)
|add
|unique
|sort
) as $cols
|map(. as $row
|$cols
|map($row[.]|tostring)
) as $rows
|$cols,$rows[]
| #csv;
tocsv
$cat test.json
[
{"code": "NSW", "name": "New South Wales", "level":"state", "country": "AU"},
{"code": "AB", "name": "Alberta", "level":"province", "country": "CA"},
{"code": "ABD", "name": "Aberdeenshire", "level":"council area", "country": "GB"},
{"code": "AK", "name": "Alaska", "level":"state", "country": "US"}
]
$ jq -r '["Code", "Name", "Level", "Country"], (.[] | [.code, .name, .level, .country]) | #tsv ' test.json
Code Name Level Country
NSW New South Wales state AU
AB Alberta province CA
ABD Aberdeenshire council area GB
AK Alaska state US
$ jq -r '["Code", "Name", "Level", "Country"], (.[] | [.code, .name, .level, .country]) | #csv ' test.json
"Code","Name","Level","Country"
"NSW","New South Wales","state","AU"
"AB","Alberta","province","CA"
"ABD","Aberdeenshire","council area","GB"
"AK","Alaska","state","US"
I created a function that outputs an array of objects or arrays to csv with headers. The columns would be in the order of the headers.
def to_csv($headers):
def _object_to_csv:
($headers | #csv),
(.[] | [.[$headers[]]] | #csv);
def _array_to_csv:
($headers | #csv),
(.[][:$headers|length] | #csv);
if .[0]|type == "object"
then _object_to_csv
else _array_to_csv
end;
So you could use it like so:
to_csv([ "code", "name", "level", "country" ])
This variant of Santiago's program is also safe but ensures that the key names in
the first object are used as the first column headers, in the same order as they
appear in that object:
def tocsv:
if length == 0 then empty
else
(.[0] | keys_unsorted) as $firstkeys
| (map(keys) | add | unique) as $allkeys
| ($firstkeys + ($allkeys - $firstkeys)) as $cols
| ($cols, (.[] as $row | $cols | map($row[.])))
| #csv
end ;
tocsv
If you're open to using other Unix tools, csvkit has an in2csv tool:
in2csv example.json
Using your sample data:
> in2csv example.json
code,name,level,country
NSW,New South Wales,state,AU
AB,Alberta,province,CA
ABD,Aberdeenshire,council area,GB
AK,Alaska,state,US
I like the pipe approach for piping directly from jq:
cat example.json | in2csv -f json -
A simple way is to just use string concatenation. If your input is a proper array:
# filename.txt
[
{"field1":"value1", "field2":"value2"},
{"field1":"value1", "field2":"value2"},
{"field1":"value1", "field2":"value2"}
]
then index with .[]:
cat filename.txt | jq -r '.[] | .field1 + ", " + .field2'
or if it's just line by line objects:
# filename.txt
{"field1":"value1", "field2":"value2"}
{"field1":"value1", "field2":"value2"}
{"field1":"value1", "field2":"value2"}
just do this:
cat filename.txt | jq -r '.field1 + ", " + .field2'