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

What is faster:

(A) 'Unpickling' (Loading) a pickled dictionary object, using pickle.load()

(B) Loading a JSON file to a dictionary using simplejson.load()

Assuming: The pickled object file exists already in case A, and that the JSON file exists already in case B.

Solution

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) :

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 timeit

import pickle
import cPickle

import json
import simplejson
import ujson
import yajl


def 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:
107.936687946

cpickle:
28.4231381416

json:
31.6450419426

simplejson:
20.5853149891

ujson:
16.9352178574

yajl:
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).