内置json模块被包含在Python 2.6中。任何支持Python < 2.6版本的项目都需要有一个备份。在很多情况下，这种退路很简单。

我不同意其他答案:内置json库(在Python 2.7中)并不一定比simplejson慢。它也没有这个恼人的统一码错误。

下面是一个简单的基准:

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)

在我的系统(Python 2.7.4, Linux 64位)上的结果:

复杂的现实数据: Json转储1.56666707993秒 Simplejson转储2.25638604164秒 Json加载2.71256899834秒 Simplejson加载1.29233884811秒 简单的数据: Json转储0.370109081268秒 Simplejson转储0.574181079865秒 Json加载0.422876119614秒 Simplejson加载0.270955085754秒

对于转储，json比simplejson更快。 对于加载，simplejson更快。

因为我目前正在构建一个web服务，所以dumps()更重要——使用标准库总是首选。

此外，在过去的4年里，csson没有更新过，所以我不会碰它。

我一直在测试json, simplejson和cjson。

json是最快的 Simplejson几乎等同于cjson Json比simplejson慢10倍

http://pastie.org/1507411:

$ python test_serialization_speed.py 
--------------------
   Encoding Tests
--------------------
Encoding: 100000 x {'m': 'asdsasdqwqw', 't': 3}
[      json] 1.12385 seconds for 100000 runs. avg: 0.011239ms
[simplejson] 0.44356 seconds for 100000 runs. avg: 0.004436ms
[     cjson] 0.09593 seconds for 100000 runs. avg: 0.000959ms

Encoding: 10000 x {'m': [['0', 1, '2', 3, '4', 5, '6', 7, '8', 9, '10', 11, '12', 13, '14', 15, '16', 17, '18', 19], ['0', 1, '2', 3, '4', 5, '6', 7, '8', 9, '10', 11, '12', 13, '14', 15, '16', 17, '18', 19], ['0', 1, '2', 3, '4', 5, '6', 7, '8', 9, '10', 11, '12', 13, '14', 15, '16', 17, '18', 19], ['0', 1, '2', 3, '4', 5, '6', 7, '8', 9, '10', 11, '12', 13, '14', 15, '16', 17, '18', 19], ['0', 1, '2', 3, '4', 5, '6', 7, '8', 9, '10', 11, '12', 13, '14', 15, '16', 17, '18', 19], ['0', 1, '2', 3, '4', 5, '6', 7, '8', 9, '10', 11, '12', 13, '14', 15, '16', 17, '18', 19], ['0', 1, '2', 3, '4', 5, '6', 7, '8', 9, '10', 11, '12', 13, '14', 15, '16', 17, '18', 19], ['0', 1, '2', 3, '4', 5, '6', 7, '8', 9, '10', 11, '12', 13, '14', 15, '16', 17, '18', 19], ['0', 1, '2', 3, '4', 5, '6', 7, '8', 9, '10', 11, '12', 13, '14', 15, '16', 17, '18', 19], ['0', 1, '2', 3, '4', 5, '6', 7, '8', 9, '10', 11, '12', 13, '14', 15, '16', 17, '18', 19], ['0', 1, '2', 3, '4', 5, '6', 7, '8', 9, '10', 11, '12', 13, '14', 15, '16', 17, '18', 19], ['0', 1, '2', 3, '4', 5, '6', 7, '8', 9, '10', 11, '12', 13, '14', 15, '16', 17, '18', 19], ['0', 1, '2', 3, '4', 5, '6', 7, '8', 9, '10', 11, '12', 13, '14', 15, '16', 17, '18', 19], ['0', 1, '2', 3, '4', 5, '6', 7, '8', 9, '10', 11, '12', 13, '14', 15, '16', 17, '18', 19], ['0', 1, '2', 3, '4', 5, '6', 7, '8', 9, '10', 11, '12', 13, '14', 15, '16', 17, '18', 19], ['0', 1, '2', 3, '4', 5, '6', 7, '8', 9, '10', 11, '12', 13, '14', 15, '16', 17, '18', 19], ['0', 1, '2', 3, '4', 5, '6', 7, '8', 9, '10', 11, '12', 13, '14', 15, '16', 17, '18', 19], ['0', 1, '2', 3, '4', 5, '6', 7, '8', 9, '10', 11, '12', 13, '14', 15, '16', 17, '18', 19], ['0', 1, '2', 3, '4', 5, '6', 7, '8', 9, '10', 11, '12', 13, '14', 15, '16', 17, '18', 19], ['0', 1, '2', 3, '4', 5, '6', 7, '8', 9, '10', 11, '12', 13, '14', 15, '16', 17, '18', 19]], 't': 3}
[      json] 7.76628 seconds for 10000 runs. avg: 0.776628ms
[simplejson] 0.51179 seconds for 10000 runs. avg: 0.051179ms
[     cjson] 0.44362 seconds for 10000 runs. avg: 0.044362ms

--------------------
   Decoding Tests
--------------------
Decoding: 100000 x {"m": "asdsasdqwqw", "t": 3}
[      json] 3.32861 seconds for 100000 runs. avg: 0.033286ms
[simplejson] 0.37164 seconds for 100000 runs. avg: 0.003716ms
[     cjson] 0.03893 seconds for 100000 runs. avg: 0.000389ms

Decoding: 10000 x {"m": [["0", 1, "2", 3, "4", 5, "6", 7, "8", 9, "10", 11, "12", 13, "14", 15, "16", 17, "18", 19], ["0", 1, "2", 3, "4", 5, "6", 7, "8", 9, "10", 11, "12", 13, "14", 15, "16", 17, "18", 19], ["0", 1, "2", 3, "4", 5, "6", 7, "8", 9, "10", 11, "12", 13, "14", 15, "16", 17, "18", 19], ["0", 1, "2", 3, "4", 5, "6", 7, "8", 9, "10", 11, "12", 13, "14", 15, "16", 17, "18", 19], ["0", 1, "2", 3, "4", 5, "6", 7, "8", 9, "10", 11, "12", 13, "14", 15, "16", 17, "18", 19], ["0", 1, "2", 3, "4", 5, "6", 7, "8", 9, "10", 11, "12", 13, "14", 15, "16", 17, "18", 19], ["0", 1, "2", 3, "4", 5, "6", 7, "8", 9, "10", 11, "12", 13, "14", 15, "16", 17, "18", 19], ["0", 1, "2", 3, "4", 5, "6", 7, "8", 9, "10", 11, "12", 13, "14", 15, "16", 17, "18", 19], ["0", 1, "2", 3, "4", 5, "6", 7, "8", 9, "10", 11, "12", 13, "14", 15, "16", 17, "18", 19], ["0", 1, "2", 3, "4", 5, "6", 7, "8", 9, "10", 11, "12", 13, "14", 15, "16", 17, "18", 19], ["0", 1, "2", 3, "4", 5, "6", 7, "8", 9, "10", 11, "12", 13, "14", 15, "16", 17, "18", 19], ["0", 1, "2", 3, "4", 5, "6", 7, "8", 9, "10", 11, "12", 13, "14", 15, "16", 17, "18", 19], ["0", 1, "2", 3, "4", 5, "6", 7, "8", 9, "10", 11, "12", 13, "14", 15, "16", 17, "18", 19], ["0", 1, "2", 3, "4", 5, "6", 7, "8", 9, "10", 11, "12", 13, "14", 15, "16", 17, "18", 19], ["0", 1, "2", 3, "4", 5, "6", 7, "8", 9, "10", 11, "12", 13, "14", 15, "16", 17, "18", 19], ["0", 1, "2", 3, "4", 5, "6", 7, "8", 9, "10", 11, "12", 13, "14", 15, "16", 17, "18", 19], ["0", 1, "2", 3, "4", 5, "6", 7, "8", 9, "10", 11, "12", 13, "14", 15, "16", 17, "18", 19], ["0", 1, "2", 3, "4", 5, "6", 7, "8", 9, "10", 11, "12", 13, "14", 15, "16", 17, "18", 19], ["0", 1, "2", 3, "4", 5, "6", 7, "8", 9, "10", 11, "12", 13, "14", 15, "16", 17, "18", 19], ["0", 1, "2", 3, "4", 5, "6", 7, "8", 9, "10", 11, "12", 13, "14", 15, "16", 17, "18", 19]], "t": 3}
[      json] 37.26270 seconds for 10000 runs. avg: 3.726270ms
[simplejson] 0.56643 seconds for 10000 runs. avg: 0.056643ms
[     cjson] 0.33007 seconds for 10000 runs. avg: 0.033007ms

simplejson模块比json快1.5倍(在我的计算机上，使用simplejson 2.1.1和Python 2.7 x86)。

如果您愿意，可以尝试基准测试:http://abral.altervista.org/jsonpickle-bench.zip 在我的电脑上，simplejson比cPickle快。我也想知道你的基准!

可能，正如Coady所说，simplejson和json之间的区别在于simplejson包含_speedps .c。 那么，为什么python开发者不使用simplejson呢?

项目使用simplejson的另一个原因是内置json最初不包括它的C加速，所以性能差异是显而易见的。

一些值在simplejson和json之间的序列化方式不同。

值得注意的是，collections.namedtuple的实例被json序列化为数组，而被simplejson序列化为对象。您可以通过将namedtuple_as_object=False传递给simplejson来覆盖此行为。转储，但默认情况下行为不匹配。

>>> import collections, simplejson, json
>>> TupleClass = collections.namedtuple("TupleClass", ("a", "b"))
>>> value = TupleClass(1, 2)
>>> json.dumps(value)
'[1, 2]'
>>> simplejson.dumps(value)
'{"a": 1, "b": 2}'
>>> simplejson.dumps(value, namedtuple_as_object=False)
'[1, 2]'