What is faster - Loading a pickled dictionary object or Loading a JSON file - to a dictionary? [closed]

The speed actually depends on the data, it's content and size.

But, anyway, let's take an example json data and see what is faster (Ubuntu 12.04, python 2.7.3) :

• pickle
• cPickle
• json
• simplejson
• ujson
• yajl

Giving this json structure dumped into test.json and test.pickle files:

{    "glossary": {        "title": "example glossary",        "GlossDiv": {            "title": "S",            "GlossList": {                "GlossEntry": {                    "ID": "SGML",                    "SortAs": "SGML",                    "GlossTerm": "Standard Generalized Markup Language",                    "Acronym": "SGML",                    "Abbrev": "ISO 8879:1986",                    "GlossDef": {                        "para": "A meta-markup language, used to create markup languages such as DocBook.",                        "GlossSeeAlso": ["GML", "XML"]                    },                    "GlossSee": "markup"                }            }        }    }}

Testing script:

import timeitimport pickleimport cPickleimport jsonimport simplejsonimport ujsonimport yajldef load_pickle(f):    return pickle.load(f)def load_cpickle(f):    return cPickle.load(f)def load_json(f):    return json.load(f)def load_simplejson(f):    return simplejson.load(f)def load_ujson(f):    return ujson.load(f)def load_yajl(f):    return yajl.load(f)print "pickle:"print timeit.Timer('load_pickle(open("test.pickle"))', 'from __main__ import load_pickle').timeit()print "cpickle:"print timeit.Timer('load_cpickle(open("test.pickle"))', 'from __main__ import load_cpickle').timeit()print "json:"print timeit.Timer('load_json(open("test.json"))', 'from __main__ import load_json').timeit()print "simplejson:"print timeit.Timer('load_simplejson(open("test.json"))', 'from __main__ import load_simplejson').timeit()print "ujson:"print timeit.Timer('load_ujson(open("test.json"))', 'from __main__ import load_ujson').timeit()print "yajl:"print timeit.Timer('load_yajl(open("test.json"))', 'from __main__ import load_yajl').timeit()

Output:

pickle:107.936687946cpickle:28.4231381416json:31.6450419426simplejson:20.5853149891ujson:16.9352178574yajl:18.9763481617

As you can see, unpickling via pickle is not that fast at all - cPickle is definetely the way to go if you choose pickling/unpickling option. ujson looks promising among these json parsers on this particular data.

Also, json and simplejson libraries load much faster on pypy (see Python JSON Performance).

See also:

• Python JSON decoding performance
• Pickle or json?
• Pickle vs JSON — Which is Faster?

It's important to note that the results may differ on your particular system, on other type and size of data.