uvg266
ultrajson
| uvg266 | ultrajson | |
|---|---|---|
| 2 | 3 | |
| 199 | 4,251 | |
| 5.5% | 0.5% | |
| 7.8 | 6.9 | |
| 4 months ago | 16 days ago | |
| C | C | |
| BSD 3-clause "New" or "Revised" License | GNU General Public License v3.0 or later |
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uvg266
ultrajson
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Processing JSON 2.5x faster than simdjson with msgspec
ujson
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Benchmarking Python JSON serializers - json vs ujson vs orjson
For most cases, you would want to go with python’s standard json library which removes dependencies on other libraries. On other hand you could try out ujsonwhich is simple replacement for python’s json library. If you want more speed and also want dataclass, datetime, numpy, and UUID instances and you are ready to deal with more complex code, then you can try your hands on orjson
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The fastest tool for querying large JSON files is written in Python (benchmark)
I asked about this on the Github issue regarding these benchmarks as well.
I'm curious as to why libraries like ultrajson[0] and orjson[1] weren't explored. They aren't command line tools, but neither is pandas right? Is it perhaps because the code required to implement the challenges is large enough that they are considered too inconvenient to use through the same way pandas was used (ie, `python -c "..."`)?
[0] https://github.com/ultrajson/ultrajson
What are some alternatives?
vvenc - VVenC, the Fraunhofer Versatile Video Encoder
marshmallow - A lightweight library for converting complex objects to and from simple Python datatypes.
libspng - Simple, modern libpng alternative
greenpass-covid19-qrcode-decoder - An easy tool for decoding Green Pass Covid-19 QrCode
vvdec - VVdeC, the Fraunhofer Versatile Video Decoder
python-rapidjson - Python wrapper around rapidjson
FFmpeg - VVC Decoder for ffmpeg
Fast JSON schema for Python - Fast JSON schema validator for Python.
PyLD - JSON-LD processor written in Python
pysimdjson - Python bindings for the simdjson project.
hjson-py - Hjson for Python
serpy - ridiculously fast object serialization