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A JSON parser benchmark. See README.rst for instructions.
*.cbor
*.log
*.xml
*.yaml
*.json
*.msgpack
*.html
*.marshal
*.pickle
.tox
.idea
.cache
*.pyc

A JSON parsing benchmark

Test code for http://blog.ionelmc.ro/2015/11/22/memory-use-and-speed-of-json-parsers/

Usage

To run:

tox

To run with different dataset (example: canada.json):

tox -- canada.json

For a VERY big data set download (you need tons of RAM for that): https://github.com/zemirco/sf-city-lots-json/raw/master/citylots.json

Other datasets you can try: https://github.com/miloyip/nativejson-benchmark/tree/master/data

If you only want to compare few implementations then run:

BM_IMPL='json simplejson msgpack' tox

On Windows (note that memory measurements are disabled there):

set BM_IMPL=json simplejson msgpack
tox

To bind to a different CPU (default is 0):

BM_CPU='1' tox

CPU binding helps a bit during speed tests, as code is single-threaded.

Measure memory differently: you can use ru_maxrss instead of valgrind (similar to what GNU /bin/time does with %M):

BM_MEM=maxrss tox

Implementations

Implementations that are tested by default:

  • cbor
  • cjson
  • cPickle
  • ijson
  • json
  • jsonlib
  • jsonlib2
  • jsonstreamer
  • msgpack
  • pickle
  • rapidjson
  • simplejson
  • ujson
  • yajl

Extra implementations not included in the defafult BM_IMPL:

  • marshal
  • pyjsmn
  • ruamel.yaml
  • yaml
  • lxml

To test everything plus lxml:

BM_IMPL_ADD='lxml' tox

To test just cbor and msgpack:

BM_IMPL='cbor msgpack' tox

Dependencies

pip install tox

Ubuntu

You might need to run:

apt-get install build-essential git-core python-dev python3.5-dev valgrind libyajl2 libyajl-dev

Python 3.5 is available from the Deadsnakes PPA:

apt-add-repository ppa:fkrull/deadsnakes
def pytest_benchmark_generate_json(config, benchmarks, include_data):
from pytest_benchmark.plugin import pytest_benchmark_generate_json
return pytest_benchmark_generate_json(config=config, benchmarks=benchmarks, include_data=False)
import json
import sys
import dicttoxml
import marshal
import msgpack
import yaml
import cbor
from util import is_format_needed
try:
import cPickle as pickle
except ImportError:
import pickle
if __name__ == '__main__':
if len(sys.argv) > 1:
with open(sys.argv[1]) as fh:
data = json.load(fh)
else:
data = {
"foo": [{
"bar": [
'A"\\ :,;\n1' * 20000000,
],
"b": [
1, 0.333, True,
],
"c": None,
}]
}
if is_format_needed('json'):
with open('data.json', 'w') as fh:
print('Creating data.json ...')
json.dump(data, fh)
if is_format_needed('yaml'):
with open('data.yaml', 'w') as fh:
print('Creating data.yaml ...')
yaml.dump(data, fh)
if is_format_needed('msgpack'):
with open('data.msgpack', 'wb') as fh:
print('Creating data.msgpack ...')
msgpack.dump(data, fh, use_bin_type=True)
if is_format_needed('pickle'):
with open('data.pickle', 'wb') as fh:
print('Creating data.pickle ...')
pickle.dump(data, fh, protocol=pickle.HIGHEST_PROTOCOL)
if is_format_needed('marshal'):
with open('data.marshal', 'wb') as fh:
print('Creating data.marshal ...')
marshal.dump(data, fh)
if is_format_needed('xml'):
with open('data.xml', 'wb') as fh:
print('Creating data.xml ...')
fh.write(dicttoxml.dicttoxml(data))
if is_format_needed('cbor'):
with open('data.cbor', 'wb') as fh:
print('Creating data.cbor ...')
cbor.dump(data, fh)
#!/usr/bin/env python
from __future__ import division
import argparse
import os
import sys
from util import IMPLEMENTATIONS
from util import get_loader
from util import open_data
backend = os.getenv("BM_MEM", "valgrind").lower()
def run(impl):
with open_data(impl) as fh:
data = fh.read()
loader = get_loader(impl)
loader(data)
parser = argparse.ArgumentParser()
parser.add_argument('--save')
parser.add_argument('impl', nargs="?")
if __name__ == '__main__':
args = parser.parse_args()
if args.impl:
run(args.impl)
else:
import operator
import subprocess
results = {}
for impl in IMPLEMENTATIONS:
try:
__import__(impl)
except ImportError:
continue
print('Testing memory use for %r ...' % impl)
if backend == 'valgrind':
massif_log = './massif-%s.log' % impl
subprocess.check_call([
# 'strace',
# '-o',
# './strace-%s.log' % impl,
'valgrind',
'--tool=massif',
'--massif-out-file=%s' % massif_log,
'--pages-as-heap=yes',
'--heap=yes',
'--threshold=0',
'--max-snapshots=1000',
'--peak-inaccuracy=0',
sys.executable,
__file__,
impl
])
memory = 0
with open(massif_log) as fh:
for line in fh:
if line.startswith('mem_heap_B='):
memory = max(memory, int(line.split('=')[-1]))
results[impl] = memory
elif backend == 'maxrss':
pid = os.fork()
if pid:
_, exit_code, usage = os.wait4(pid, 0)
if exit_code:
raise RuntimeError("Failed to run loader. Exit code: %s. Used: %s Mb" % (
exit_code, usage.ru_maxrss / 1024
))
results[impl] = usage.ru_maxrss * 1024
else:
try:
run(impl)
except Exception:
import traceback
traceback.print_exc()
os._exit(5)
finally:
os._exit(0)
else:
raise RuntimeError("Unknown BM_MEM backend %r" % backend)
print('MEMORY USAGE:')
for impl, memory in sorted(results.items(), key=operator.itemgetter(1)):
print('{:>20}: {:>7,.1f} Mb'.format(impl, memory / 1024 / 1024))
if args.save:
import json
dirname = os.path.dirname(args.save)
if not os.path.exists(dirname):
os.makedirs(dirname)
with open(args.save, 'w') as fh:
json.dump(results, fh)
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