The json module already implements some basic pretty printing with the indent parameter that specifies how many spaces to indent by:
>>> import json
>>>
>>> your_json = ‘[“foo”, {“bar”:[“baz”, null, 1.0, 2]}]’
>>> parsed = json.loads(your_json)
>>> print(json.dumps(parsed, indent=4, sort_keys=True))
[
“foo”,
{
“bar”: [
“baz”,
null,
1.0,
2
]
}
]
To parse a file, use json.load():
with open(‘filename.txt’, ‘r’) as handle:
parsed = json.load(handle)
You can do this on the command line:
python3 -m json.tool some.json
(as already mentioned in the commentaries to the question, thanks to @Kai Petzke for the python3 suggestion).
Actually python is not my favourite tool as far as json processing on the command line is concerned. For simple pretty printing is ok, but if you want to manipulate the json it can become overcomplicated. You’d soon need to write a separate script-file, you could end up with maps whose keys are u”some-key” (python unicode), which makes selecting fields more difficult and doesn’t really go in the direction of pretty-printing.
You can also use jq:
jq . some.json
and you get colors as a bonus (and way easier extendability).
Addendum: There is some confusion in the comments about using jq to process large JSON files on the one hand, and having a very large jq program on the other. For pretty-printing a file consisting of a single large JSON entity, the practical limitation is RAM. For pretty-printing a 2GB file consisting of a single array of real-world data, the “maximum resident set size” required for pretty-printing was 5GB (whether using jq 1.5 or 1.6). Note also that jq can be used from within python after pip install jq.