Can someone suggest how I can beautify JSON in Python or through the command line?
The only online based JSON beautifier which could do it was: http://jsonviewer.stack.hu/.
I need to use it from within Python, however.
This is my dataset:
{ "head": {"vars": [ "address" , "description" ,"listprice" ]} , "results": { "bindings": [
{
"address" : { "type":"string", "value" : " Dyne Road, London NW6"},
"description" :{ "type":"string", "value" : "6 bed semi detached house"},
"listprice" : { "type":"string", "value" : "1,150,000"}
}
,
{
"address" : { "type":"string", "value" : " Tweedy Road, Bromley BR1"},
"description" :{ "type":"string", "value" : "5 bed terraced house"},
"listprice" : { "type":"string", "value" : "550,000"}
}
,
{
"address" : { "type":"string", "value" : " Vera Avenue, London N21"},
"description" :{ "type":"string", "value" : "4 bed detached house"},
"listprice" : { "type":"string", "value" : "
995,000
"}
}
,
{
"address" : { "type":"string", "value" : " Wimbledon Park Side, London SW19"},
"description" :{ "type":"string", "value" : "3 bedroom property for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Westbere Road, West Hampstead, London NW2"},
"description" :{ "type":"string", "value" : "5 bedroom semi detached house for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " The Avenue, Hatch End, Pinner HA5"},
"description" :{ "type":"string", "value" : "5 bedroom detached house for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Princes Park Avenue, London NW11"},
"description" :{ "type":"string", "value" : "4 bedroom detached house for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Canons Drive, Edgware HA8"},
"description" :{ "type":"string", "value" : "4 bedroom detached house for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Westbere Road, West Hampstead NW2"},
"description" :{ "type":"string", "value" : "5 bedroom property for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Haymills Estate, Ealing, London"},
"description" :{ "type":"string", "value" : "5 bedroom property for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Dene Terrace Woodclyffe Drive, Chislehurst, Kent BR7"},
"description" :{ "type":"string", "value" : "5 bedroom terraced house for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Dene Terrace Woodclyffe Drive, Chislehurst, Kent BR7"},
"description" :{ "type":"string", "value" : "5 bedroom semi detached house for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Northwick Close, St John's Wood NW8"},
"description" :{ "type":"string", "value" : "3 bedroom property for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Claremont Gardens, Surbiton KT6"},
"description" :{ "type":"string", "value" : "13 bedroom property for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Dene Terrace Woodclyffe Drive, Chislehurst, Kent BR7"},
"description" :{ "type":"string", "value" : "5 bedroom end terrace house for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Stamford Road, London N1"},
"description" :{ "type":"string", "value" : "4 bedroom terraced house for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Stanhope Avenue, London N3"},
"description" :{ "type":"string", "value" : "6 bedroom property for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Haymills Estate, Ealing, London"},
"description" :{ "type":"string", "value" : "5 bedroom property for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Elms Crescent, London SW4"},
"description" :{ "type":"string", "value" : "5 bedroom property for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Princes Park Avenue, London NW11"},
"description" :{ "type":"string", "value" : "4 bedroom property for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Abbeville Road, London SW4"},
"description" :{ "type":"string", "value" : "4 bedroom property for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Canons Drive, Edgware HA8"},
"description" :{ "type":"string", "value" : "4 bedroom detached house for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Henson Avenue, Willesdon Green NW2"},
"description" :{ "type":"string", "value" : "5 bedroom property for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Woodstock Road, London NW11"},
"description" :{ "type":"string", "value" : "5 bedroom property for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Tamworth Street, London SW6"},
"description" :{ "type":"string", "value" : "5 bedroom property for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Stanhope Avenue, Finchley, London"},
"description" :{ "type":"string", "value" : "5 bedroom semi detached house for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " The Old Burlington, Church Street, London W4"},
"description" :{ "type":"string", "value" : "3 bedroom property for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Ebury Close, Northwood HA6"},
"description" :{ "type":"string", "value" : "4 bedroom detached house for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Middleton Road, London NW11"},
"description" :{ "type":"string", "value" : "4 bedroom property for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Henson Avenue, Willesden Green NW2"},
"description" :{ "type":"string", "value" : "5 bedroom property for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Huron Road, London SW17"},
"description" :{ "type":"string", "value" : "6 bedroom property for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Corringway, Ealing W5"},
"description" :{ "type":"string", "value" : "5 bedroom detached house for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Woodlands Avenue, New Malden KT3"},
"description" :{ "type":"string", "value" : "5 bedroom detached house for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Gunnersbury Park Area, Ealing, London"},
"description" :{ "type":"string", "value" : "6 bedroom property for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Blenheim Gardens, London, Brent NW2"},
"description" :{ "type":"string", "value" : "6 bedroom property for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Creighton Road, London NW6"},
"description" :{ "type":"string", "value" : "4 bedroom terraced house for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Plaistow Lane, Bromley BR1"},
"description" :{ "type":"string", "value" : "7 bedroom detached house for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Greenfield Gardens, London NW2"},
"description" :{ "type":"string", "value" : "4 bedroom property for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Hendon Avenue, London N3"},
"description" :{ "type":"string", "value" : "3 bedroom detached house for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Peckham Park Road, London SE15"},
"description" :{ "type":"string", "value" : "6 bedroom semi detached house for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Woodclyffe Drive, Chislehurst BR7"},
"description" :{ "type":"string", "value" : "5 bedroom house for sale"},
"listprice" : { "type":"string", "value" : "
From 1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Highwood Hill, Mill Hill, London"},
"description" :{ "type":"string", "value" : "5 bedroom detached house for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Stanhope Avenue, London N3"},
"description" :{ "type":"string", "value" : "5 bedroom semi detached house for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Kersley Mews, London SW11"},
"description" :{ "type":"string", "value" : "3 bedroom mews for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Ebury Close, Northwood HA6"},
"description" :{ "type":"string", "value" : "4 bedroom detached house for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Ellesmere Road, Chiswick W4"},
"description" :{ "type":"string", "value" : "6 bedroom detached house for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " The Avenue, Hatch End, Pinner, Middlesex"},
"description" :{ "type":"string", "value" : "5 bedroom detached house for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Wandsworth, London SW18"},
"description" :{ "type":"string", "value" : "6 bedroom semi detached house for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Carlton Road, New Malden KT3"},
"description" :{ "type":"string", "value" : "4 bedroom detached house for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " St Mary's Mews, Ealing W5"},
"description" :{ "type":"string", "value" : "3 bedroom property for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Ritherdon Road, Balham, London SW17"},
"description" :{ "type":"string", "value" : "5 bedroom semi detached house for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Goldsmith Avenue, London W3"},
"description" :{ "type":"string", "value" : "5 bedroom property for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
,
{
"address" : { "type":"string", "value" : " Plaistow Lane, Bromley, Kent BR1"},
"description" :{ "type":"string", "value" : "7 bedroom detached house for sale"},
"listprice" : { "type":"string", "value" : "
1,250,000
"}
}
] } }
This question is related to
python
json
command-line
The answer is
alias jsonp='pbpaste | python -m json.tool'
This will pretty print JSON that's on the clipboard in OSX. Just Copy it then call the alias from a Bash prompt.
First install pygments
then
echo '<some json>' | python -m json.tool | pygmentize -l json
I didn't like the output of json.dumps(...) -> For my taste way too much newlines. And I didn't want to use a command line tool or install something. I finally found Pythons pprint (= pretty print). Unfortunately it doesn't generate proper JSON but I think it is useful to have a user friendly glympse at the stored data.
Output of json.dumps(json_dict, indent=4)
{
"hyperspace": {
"constraints": [],
"design": [
[
"windFarm.windparkSize.k",
"continuous",
[
0,
0,
5
]
],
[
"hydroPlant.primaryControlMax",
"continuous",
[
100,
300
]
]
],
"kpis": [
"frequency.y",
"city.load.p[2]"
]
},
"lhc_size": 10,
"number_of_runs": 10
}
Usage of pprint:
import pprint
json_dict = {"hyperspace": {"constraints": [], "design": [["windFarm.windparkSize.k", "continuous", [0, 0, 5]], ["hydroPlant.primaryControlMax", "continuous", [100, 300]]], "kpis": ["frequency.y", "city.load.p[2]"]}, "lhc_size": 10, "number_of_runs": 10}
formatted_json_str = pprint.pformat(json_dict)
print(formatted_json_str)
pprint.pprint(json_dict)
Result of pprint.pformat(...) or pprint.pprint(...):
{'hyperspace': {'constraints': [],
'design': [['windFarm.windparkSize.k', 'continuous', [0, 0, 5]],
['hydroPlant.primaryControlMax',
'continuous',
[100, 300]]],
'kpis': ['frequency.y', 'city.load.p[2]']},
'lhc_size': 10,
'number_of_runs': 10}
A minimal in-python solution that colors json data supplied via the command line:
import sys
import json
from pygments import highlight, lexers, formatters
formatted_json = json.dumps(json.loads(sys.argv[1]), indent=4)
colorful_json = highlight(unicode(formatted_json, 'UTF-8'), lexers.JsonLexer(), formatters.TerminalFormatter())
print(colorful_json)
Inspired by pjson mentioned above. This code needs pygments to be installed.
Output example:
Use the indent argument of the dumps function in the json module.
From the docs:
>>> import json
>>> print json.dumps({'4': 5, '6': 7}, sort_keys=True, indent=4)
{
"4": 5,
"6": 7
}
From the command-line:
echo '{"one":1,"two":2}' | python -mjson.tool
which outputs:
{
"one": 1,
"two": 2
}
Programmtically, the Python manual describes pretty-printing JSON:
>>> import json
>>> print json.dumps({'4': 5, '6': 7}, sort_keys=True, indent=4)
{
"4": 5,
"6": 7
}
Try underscore-cli:
cat myfile.json | underscore print --color
It's a pretty nifty tool that can elegantly do a lot of manipulation of structured data, execute js snippets, fill templates, etc. It's ridiculously well documented, polished, and ready for serious use. And I wrote it. :)
With jsonlint (like xmllint):
aptitude install python-demjson
jsonlint -f foo.json
It looks like jsbeautifier open sourced their tools and packaged them as Python and JS libs, and as CLI tools. It doesn't look like they call out to a web service, but I didn't check too closely. See the github repo with install instructions.
From their docs for Python CLI and library usage:
To beautify using python:
$ pip install jsbeautifier
$ js-beautify file.js
Beautified output goes to stdout.
To use jsbeautifier as a library is simple:
import jsbeautifier
res = jsbeautifier.beautify('your javascript string')
res = jsbeautifier.beautify_file('some_file.js')
...or, to specify some options:
opts = jsbeautifier.default_options()
opts.indent_size = 2
res = jsbeautifier.beautify('some javascript', opts)
If you want to pass a string instead of a filename, and you are using bash, then you can use process substitution like so:
$ js-beautify <(echo '{"some": "json"}')
Your data is poorly formed. The value fields in particular have numerous spaces and new lines. Automated formatters won't work on this, as they will not modify the actual data. As you generate the data for output, filter it as needed to avoid the spaces.
Use the python tool library
Command line: python -mjson.tool
The cli command I've used with python for this is:
cat myfile.json | python -mjson.tool
You should be able to find more info here:
You could pipe the output to jq. If you python script contains something like
print json.dumps(data)
then you can fire:
python foo.py | jq '.'
Source: Stackoverflow.com