orjson 1.0.0

No project description provided

orjson

orjson is a fast JSON library for Python. It benchmarks as the fastest Python library for JSON serialization, about twice as fast or more as the nearest other library, with deserialization performance slightly worse to similar to the fastest library.

It supports Python 3.6 and Python 3.7 (CPython only).

Usage

Install

To install a manylinux wheel from PyPI:

pip install --upgrade orjson

To build a release wheel from source, assuming a Rust nightly toolchain and Python environment:

git checkout https://github.com/ijl/orjson.git && cd orjson
pip install --upgrade pyo3-pack
pyo3-pack build --release --strip --interpreter python3.7

There is no runtime dependency other than a manylinux environment (i.e., deploying this does not require Rust or non-libc type libraries.)

Serialize

def dumps(obj: Union[unicode, bytes, dict, list, tuple, int, float]) -> bytes

dumps() serializes Python objects to JSON.

It has no options and does not support hooks for custom objects.

It raises TypeError on an unsupported type or a number that is too large. The error message describes the invalid object.

import orjson

try:
    val = orjson.dumps(...)
except TypeError:
    raise

Deserialize

def loads(obj: Union[bytes, unicode]) -> Any

loads() deserializes JSON to Python objects.

It raises orjson.JSONDecodeError on invalid input.

import orjson

try:
    val = orjson.loads(...)
except orjson.JSONDecodeError:
    raise

Comparison

There are slight differences in output between libraries. The differences are not an issue for interoperability. Note orjson returns bytes. Its output is slightly smaller as well.

>>> import orjson, ujson, rapidjson, json
>>> data = {'bool': True, '🐈':'哈哈', 'int': 9223372036854775807, 'float': 1.337e+40}
>>> orjson.dumps(data)
b'{"bool":true,"\xf0\x9f\x90\x88":"\xe5\x93\x88\xe5\x93\x88","int":9223372036854775807,"float":1.337e40}'
>>> ujson.dumps(data)
'{"bool":true,"\\ud83d\\udc08":"\\u54c8\\u54c8","int":9223372036854775807,"float":1.337000000000000e+40}'
>>> rapidjson.dumps(data)
'{"bool":true,"\\uD83D\\uDC08":"\\u54C8\\u54C8","int":9223372036854775807,"float":1.337e+40}'
>>> json.dumps(data)
'{"bool": true, "\\ud83d\\udc08": "\\u54c8\\u54c8", "int": 9223372036854775807, "float": 1.337e+40}'

Testing

The library has comprehensive tests. There are unit tests against the roundtrip, jsonchecker, and fixtures files of the nativejson-benchmark. It is tested to not crash against the Big List of Naughty Strings. There are integration tests exercising the library's use in web servers (uwsgi and gunicorn, using multiprocess/forked workers) and when multithreaded. It also uses some tests from the ultrajson library.

Performance

Serialization performance of orjson is better than ultrajson, rapidjson, or json. Deserialization performance is worse to about the same as ultrajson.

canada.json deserialization

Library	Median (milliseconds)	Operations per second	Relative (latency)
orjson	17.58	64.3	1.04
ujson	16.85	66.3	1
rapidjson	37.26	28.4	2.21
json	37.53	27.8	2.23

canada.json serialization

Library	Median (milliseconds)	Operations per second	Relative (latency)
orjson	5.08	195.6	1
ujson	9.39	106.3	1.85
rapidjson	43.96	22.7	8.65
json	47.57	21	9.36

citm_catalog.json deserialization

Library	Median (milliseconds)	Operations per second	Relative (latency)
orjson	6.75	120.6	1.02
ujson	6.63	121.5	1
rapidjson	7.99	106.1	1.2
json	7.99	103.7	1.2

citm_catalog.json serialization

Library	Median (milliseconds)	Operations per second	Relative (latency)
orjson	1.12	891	1
ujson	3.97	251.5	3.55
rapidjson	2.37	420.9	2.12
json	5.34	187.1	4.78

twitter.json deserialization

Library	Median (milliseconds)	Operations per second	Relative (latency)
orjson	3.38	278.9	1.17
ujson	2.88	332.8	1
rapidjson	3.35	252.7	1.16
json	3.3	289.2	1.15

twitter.json serialization

Library	Median (milliseconds)	Operations per second	Relative (latency)
orjson	0.59	1699.5	1
ujson	1.89	529.8	3.22
rapidjson	1.57	637.3	2.68
json	2.17	458.5	3.71

This was measured on Python 3.7.1. The above can be reproduced using the pybench and graph scripts.

License

orjson is dual licensed under the Apache 2.0 and MIT licenses. It contains code from the hyperjson and ultrajson libraries. It is implemented using the serde_json and pyo3 libraries.