json is simplejson, added to the stdlib. But since json was added in 2.6, simplejson has the advantage of working on more Python versions (2.4+).
simplejson is also updated more frequently than Python, so if you need (or want) the latest version, it's best to use simplejson itself, if possible.
A good practice, in my opinion, is to use one or the other as a fallback.
try:
import simplejson as json
except ImportError:
import json
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» pip install simplejson
json is simplejson, added to the stdlib. But since json was added in 2.6, simplejson has the advantage of working on more Python versions (2.4+).
simplejson is also updated more frequently than Python, so if you need (or want) the latest version, it's best to use simplejson itself, if possible.
A good practice, in my opinion, is to use one or the other as a fallback.
try:
import simplejson as json
except ImportError:
import json
I have to disagree with the other answers: the built in json library (in Python 2.7) is not necessarily slower than simplejson. It also doesn't have this annoying unicode bug.
Here is a simple benchmark:
import json
import simplejson
from timeit import repeat
NUMBER = 100000
REPEAT = 10
def compare_json_and_simplejson(data):
"""Compare json and simplejson - dumps and loads"""
compare_json_and_simplejson.data = data
compare_json_and_simplejson.dump = json.dumps(data)
assert json.dumps(data) == simplejson.dumps(data)
result = min(repeat("json.dumps(compare_json_and_simplejson.data)", "from __main__ import json, compare_json_and_simplejson",
repeat = REPEAT, number = NUMBER))
print " json dumps {} seconds".format(result)
result = min(repeat("simplejson.dumps(compare_json_and_simplejson.data)", "from __main__ import simplejson, compare_json_and_simplejson",
repeat = REPEAT, number = NUMBER))
print "simplejson dumps {} seconds".format(result)
assert json.loads(compare_json_and_simplejson.dump) == data
result = min(repeat("json.loads(compare_json_and_simplejson.dump)", "from __main__ import json, compare_json_and_simplejson",
repeat = REPEAT, number = NUMBER))
print " json loads {} seconds".format(result)
result = min(repeat("simplejson.loads(compare_json_and_simplejson.dump)", "from __main__ import simplejson, compare_json_and_simplejson",
repeat = REPEAT, number = NUMBER))
print "simplejson loads {} seconds".format(result)
print "Complex real world data:"
COMPLEX_DATA = {'status': 1, 'timestamp': 1362323499.23, 'site_code': 'testing123', 'remote_address': '212.179.220.18', 'input_text': u'ny monday for less than \u20aa123', 'locale_value': 'UK', 'eva_version': 'v1.0.3286', 'message': 'Successful Parse', 'muuid1': '11e2-8414-a5e9e0fd-95a6-12313913cc26', 'api_reply': {"api_reply": {"Money": {"Currency": "ILS", "Amount": "123", "Restriction": "Less"}, "ProcessedText": "ny monday for less than \\u20aa123", "Locations": [{"Index": 0, "Derived From": "Default", "Home": "Default", "Departure": {"Date": "2013-03-04"}, "Next": 10}, {"Arrival": {"Date": "2013-03-04", "Calculated": True}, "Index": 10, "All Airports Code": "NYC", "Airports": "EWR,JFK,LGA,PHL", "Name": "New York City, New York, United States (GID=5128581)", "Latitude": 40.71427, "Country": "US", "Type": "City", "Geoid": 5128581, "Longitude": -74.00597}]}}}
compare_json_and_simplejson(COMPLEX_DATA)
print "\nSimple data:"
SIMPLE_DATA = [1, 2, 3, "asasd", {'a':'b'}]
compare_json_and_simplejson(SIMPLE_DATA)
And the results on my system (Python 2.7.4, Linux 64-bit):
Complex real world data:
json dumps 1.56666707993 seconds
simplejson dumps 2.25638604164 seconds
json loads 2.71256899834 seconds
simplejson loads 1.29233884811 secondsSimple data:
json dumps 0.370109081268 seconds
simplejson dumps 0.574181079865 seconds
json loads 0.422876119614 seconds
simplejson loads 0.270955085754 seconds
For dumping, json is faster than simplejson.
For loading, simplejson is faster.
Since I am currently building a web service, dumps() is more important—and using a standard library is always preferred.
Also, cjson was not updated in the past 4 years, so I wouldn't touch it.
I would recommend EasyInstall, a package management application for Python.
Once you've installed EasyInstall, you should be able to go to a command window and type:
easy_install simplejson
This may require putting easy_install.exe on your PATH first, I don't remember if the EasyInstall setup does this for you (something like C:\Python25\Scripts).
Really simple way is:
pip install simplejson
I've used this strategy in the past and been pretty happy with it: Encode your custom objects as JSON object literals (like Python dicts) with the following structure:
{ '__ClassName__': { ... } }
That's essentially a one-item dict whose single key is a special string that specifies what kind of object is encoded, and whose value is a dict of the instance's attributes. If that makes sense.
A very simple implementation of an encoder and a decoder (simplified from code I've actually used) is like so:
TYPES = { 'ParentClass': ParentClass,
'ChildClass': ChildClass }
class CustomTypeEncoder(json.JSONEncoder):
"""A custom JSONEncoder class that knows how to encode core custom
objects.
Custom objects are encoded as JSON object literals (ie, dicts) with
one key, '__TypeName__' where 'TypeName' is the actual name of the
type to which the object belongs. That single key maps to another
object literal which is just the __dict__ of the object encoded."""
def default(self, obj):
if isinstance(obj, TYPES.values()):
key = '__%s__' % obj.__class__.__name__
return { key: obj.__dict__ }
return json.JSONEncoder.default(self, obj)
def CustomTypeDecoder(dct):
if len(dct) == 1:
type_name, value = dct.items()[0]
type_name = type_name.strip('_')
if type_name in TYPES:
return TYPES[type_name].from_dict(value)
return dct
In this implementation assumes that the objects you're encoding will have a from_dict() class method that knows how to take recreate an instance from a dict decoded from JSON.
It's easy to expand the encoder and decoder to support custom types (e.g. datetime objects).
EDIT, to answer your edit: The nice thing about an implementation like this is that it will automatically encode and decode instances of any object found in the TYPES mapping. That means that it will automatically handle a ChildClass like so:
class ChildClass(object):
def __init__(self):
self.foo = 'foo'
self.bar = 1.1
self.parent = ParentClass(1)
That should result in JSON something like the following:
{ '__ChildClass__': {
'bar': 1.1,
'foo': 'foo',
'parent': {
'__ParentClass__': {
'foo': 1}
}
}
}
An instance of a custom class could be represented as JSON formatted string with help of following function:
def json_repr(obj):
"""Represent instance of a class as JSON.
Arguments:
obj -- any object
Return:
String that reprent JSON-encoded object.
"""
def serialize(obj):
"""Recursively walk object's hierarchy."""
if isinstance(obj, (bool, int, long, float, basestring)):
return obj
elif isinstance(obj, dict):
obj = obj.copy()
for key in obj:
obj[key] = serialize(obj[key])
return obj
elif isinstance(obj, list):
return [serialize(item) for item in obj]
elif isinstance(obj, tuple):
return tuple(serialize([item for item in obj]))
elif hasattr(obj, '__dict__'):
return serialize(obj.__dict__)
else:
return repr(obj) # Don't know how to handle, convert to string
return json.dumps(serialize(obj))
This function will produce JSON-formatted string for
an instance of a custom class,
a dictionary that have instances of custom classes as leaves,
- a list of instances of custom classes