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"description": "## MrJSON\n\nMrJSON is a JSON encoder and decoder written in C/C++ with bindings for Python 2.5+ and 3. I needed faster performance for long strings and floats and MrJSON benchmarks at 2-3 times faster than the fastest python parsers for my use cases.\n\nTo install it just run Pip as usual:\n\n```sh\n $ pip install mrjson\n```\n\n## Usage\n\nMay be used as a replacement for json\n\n```python\n >>> import mrjson as json\n >>> json.dumps([{\"key\": \"value\"}, 81, True])\n '[{\"key\":\"value\"},81,true]'\n >>> json.loads(\"\"\"[{\"key\": \"value\"}, 81, true]\"\"\")\n [{'key': 'value'}, 81, True]\n```\n\n## Encoder differences\n\n**ensure_ascii** defaults to true in the base json module, but defaults to false here for space and performance reasons. \n\n**indent**, **separators**, and **sortKeys** are not supported as pretty printing doesn't need the performance. Write an issue if you have a use case.\n\n**allow_nan** is unsupported as NaN and infinity are supported by default.\n\nCustom objects are supported if they implement an __json__() method returning a valid json string.\n\n## Benchmarks\t\t\n\nBenchmark your own files as results can vary significantly:\n\n```\n$ python -m timeit -s \"import mrjson as json;st = open('canada.json').read();\" \"json.loads(st)\"\n100 loops, best of 3: 8.05 msec per loop\n\n$ python -m timeit -s \"import json;st = open('canada.json').read();\" \"json.loads(st)\"\n10 loops, best of 3: 32.7 msec per loop\n```\n\nOr run bench.py to test MrJSON against some other modules. MrJSON does particularly well decoding long strings and floating point numbers thanks to intel's AVX2 instructions and [Milo Yip at Tencent](https://github.com/Tencent/rapidjson) for publishing C++ code implementing Florian Loitsch's float to string algorithms. \n\n#### Loads\n\nOnly 128 byte long strings. \n\n![](\"bench/png/str128-2.png\")
\n\nMostly floating point numbers - canada.json from [The Native JSON Benchmark](https://github.com/miloyip/nativejson-benchmark), the fastest C++ JSON parser comes in at 7.9 milliseconds on this machine for comparison\n\n![](\"bench/png/canada-loads.png\")
\n\nA single tweet from twitter - twit.json\n\n![](\"bench/png/twit-loads.png\")
\n\ncitm_catalog.json from [The Native JSON Benchmark](https://github.com/miloyip/nativejson-benchmark)\n\n![](\"bench/png/citm-catalog-loads.png\")
\n\n#### Dumps\n\nOnly 128 byte long strings. \n\n![](\"bench/png/str128-dumps.png\")
\n\nMostly floating point numbers - canada.json from [The Native JSON Benchmark](https://github.com/miloyip/nativejson-benchmark)\n\n![](\"bench/png/canada-dumps.png\")
\n\nA single tweet from twitter - twit.json\n\n![](\"bench/png/twit-dumps.png\")
\n\ncitm_catalog.json from [The Native JSON Benchmark](https://github.com/miloyip/nativejson-benchmark)\n\n![](\"bench/png/citm-catalog-dumps.png\")
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