Benchmarking json loading across json and ujson (precision floats and normal)

benchmark_load.py

import json
import ujson
from timeit import repeat


def decode_json(data):
    json.loads(data)


def decode_ujson(data, precise=False):
    ujson.loads(data, precise_float=precise)


def raw():
    with open("data/some_data.json") as f:
        return f.read()


LOOPS = 100_000
REPEAT = 3

if __name__ == "__main__":
    setup = "from __main__ import decode_json, decode_ujson, raw"
    print("Best of {0} of {1} loads each\n".format(REPEAT, LOOPS))
    print("std json: %.4fs" % min(repeat("decode_json(raw())", setup=setup, number=10000, repeat=3)))
    print("ujson w/o precision load: %.4fs" % min(repeat("decode_ujson(raw())", setup=setup, number=10000, repeat=3)))
    print("ujson w/  precision load: %.4fs" % min(repeat("decode_ujson(raw(), True)", setup=setup, number=10000, repeat=3)))

output

$ python benchmark_load.py
Best of 3 of 100000 loads each

std json: 6.1493s
ujson w/o precision load: 5.0161s
ujson w/  precision load: 5.0040s

$ python benchmark_load.py
Best of 3 of 100000 loads each

std json: 5.1441s
ujson w/o precision load: 4.9517s
ujson w/  precision load: 5.0072s