RapidJSON is an extremely fast C++ JSON serialization library.
We do not support legacy Python versions, you will need to upgrade to Python 3 to use this library.
Latest version documentation is automatically rendered by Read the Docs.
First install python-rapidjson:
$ pip install python-rapidjsonRapidJSON tries to be compatible with the standard library json module so
it should be a drop in replacement. Basic usage looks like this:
>>> import rapidjson
>>> data = {'foo': 100, 'bar': 'baz'}
>>> rapidjson.dumps(data)
'{"bar":"baz","foo":100}'
>>> rapidjson.loads('{"bar":"baz","foo":100}')
{'bar': 'baz', 'foo': 100}If you want to install the development version (maybe to contribute fixes or enhancements) you may clone the repository:
$ git clone --recursive https://github.com/python-rapidjson/python-rapidjson.gitNote
The --recursive option is needed because we use a submodule to
include RapidJSON sources. Alternatively you can do a plain
clone immediately followed by a git submodule update --init.
Alternatively, if you already have (a compatible version of)
RapidJSON includes around, you can compile the module specifying
their location with the option --rj-include-dir, for example:
$ python3 setup.py build --rj-include-dir=/usr/include/rapidjsonpython-rapidjson tries to be as performant as possible while staying
compatible with the json module.
The following tables show a comparison between this module and other libraries with different data sets. Last row (“overall”) is the total time taken by all the benchmarks.
Each number show the factor between the time taken by each contender and
python-rapidjson (in other words, they are normalized against a value of
1.0 for python-rapidjson): the lower the number, the speedier the
contender.
In bold the winner.
| serialize | native [1] | ujson [2] | simplejson [3] | stdlib [4] | yajl [5] |
|---|---|---|---|---|---|
| 100 arrays dict | 0.67 | 1.31 | 6.28 | 2.88 | 1.74 |
| 100 dicts array | 0.79 | 1.19 | 7.16 | 2.92 | 1.69 |
| 256 Trues array | 1.19 | 1.41 | 3.02 | 2.19 | 1.20 |
| 256 ascii array | 1.02 | 0.92 | 1.90 | 1.77 | 2.05 |
| 256 doubles array | 1.06 | 7.55 | 8.30 | 7.65 | 4.39 |
| 256 unicode array | 0.87 | 0.72 | 0.82 | 0.88 | 0.53 |
| complex object | 0.82 | 1.41 | 5.17 | 3.39 | 2.87 |
| composite object | 0.68 | 0.93 | 3.01 | 1.92 | 1.85 |
| overall | 0.67 | 1.30 | 6.27 | 2.88 | 1.74 |
| [1] | rapidjson with number_mode=NM_NATIVE |
| [2] | ujson 1.35 |
| [3] | simplejson 3.11.1 |
| [4] | Python 3.6 standard library |
| [5] | yajl 0.3.5 |
| deserialize | native | ujson | simplejson | stdlib | yajl |
|---|---|---|---|---|---|
| 100 arrays dict | 0.90 | 0.97 | 1.48 | 1.25 | 1.20 |
| 100 dicts array | 0.88 | 0.96 | 1.99 | 1.58 | 1.34 |
| 256 Trues array | 1.22 | 1.31 | 2.08 | 1.93 | 2.08 |
| 256 ascii array | 1.05 | 1.37 | 1.14 | 1.25 | 1.56 |
| 256 doubles array | 0.16 | 0.33 | 0.72 | 0.70 | 0.47 |
| 256 unicode array | 0.89 | 0.79 | 4.12 | 4.50 | 1.90 |
| complex object | 0.72 | 0.88 | 1.36 | 1.28 | 1.24 |
| composite object | 0.83 | 0.85 | 1.94 | 1.43 | 1.26 |
| overall | 0.90 | 0.97 | 1.49 | 1.25 | 1.20 |
To run these tests yourself, clone the repo and run:
$ tox -e py36 -- -m benchmark --compare-other-enginesWithout the option --compare-other-engines it will focus only on
RapidJSON. This is particularly handy coupled with the compare past
runs functionality of pytest-benchmark:
$ tox -e py36 -- -m benchmark --benchmark-autosave
# hack, hack, hack!
$ tox -e py36 -- -m benchmark --benchmark-compare=0001
----------------------- benchmark 'deserialize': 18 tests ------------------------
Name (time in us) Min…
----------------------------------------------------------------------------------
test_loads[rapidjson-256 Trues array] (NOW) 5.2320 (1.0)…
test_loads[rapidjson-256 Trues array] (0001) 5.4180 (1.04)…
…To reproduce the tables above, use the option --benchmark-json so that the
the results are written in the specified filename the run the
benchmark-tables.py script giving that filename as the only argument:
$ tox -e py36 -- -m benchmark --compare-other-engines --benchmark-json=comparison.json
$ python3 benchmark-tables.py comparison.jsonHere are things in the standard json library supports that we have decided
not to support:
separatorsargument. This is mostly used for pretty printing and not supported byRapidJSONso it isn't a high priority. We do supportindentkwarg that would get you nice looking JSON anyways.- Coercing keys when dumping.
jsonwill turnTrueinto'True'if you dump it out but when you load it back in it'll still be a string. We want the dump and load to return the exact same objects so we have decided not to do this coercing.