pysimdjson VS ultrajson

Compare pysimdjson vs ultrajson and see what are their differences.


Ultra fast JSON decoder and encoder written in C with Python bindings (by ultrajson)
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pysimdjson ultrajson
3 2
545 3,779
- 1.1%
5.1 9.0
2 months ago 14 days ago
Python C
MIT License GNU General Public License v3.0 or later
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Posts with mentions or reviews of pysimdjson. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-05-23.
  • [package-find] lsp-bridge
    5 projects | | 23 May 2022
    You are aware of simdjson being available in python if you really need some json crunching, albeit json module in Python is implemented in C itself, so I don't think understand why do you think Python is slow there?
  • The fastest tool for querying large JSON files is written in Python (benchmark)
    16 projects | | 12 Apr 2022
    json: 113.79130696877837 ms

    While `orjson`, is faster than `ujson`/`json` here, it's only ~6% faster (in this benchmark). `simdjson` and `msgspec` (my library, see are much faster due to them avoiding creating PyObjects for fields that are never used.

    If spyql's query engine can determine the fields it will access statically before processing, you might find using `msgspec` for JSON gives a nice speedup (it'll also type check the JSON if you know the type of each field). If this information isn't known though, you may find using `pysimdjson` ( gives an easy speed boost, as it should be more of a drop-in for `orjson`.

  • How I cut GTA Online loading times by 70%
    7 projects | | 28 Feb 2021
    I don't think JSON is really the problem - parsing 10MB of JSON is not so slow. For example, using Python's json.load takes about 800ms for a 47MB file on my system, using something like simdjson cuts that down to ~70ms.


Posts with mentions or reviews of ultrajson. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-05-25.
  • Benchmarking Python JSON serializers - json vs ujson vs orjson
    2 projects | | 25 May 2022
    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
  • The fastest tool for querying large JSON files is written in Python (benchmark)
    16 projects | | 12 Apr 2022
    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 "..."`)?


What are some alternatives?

When comparing pysimdjson and ultrajson you can also consider the following projects:

marshmallow - A lightweight library for converting complex objects to and from simple Python datatypes.

greenpass-covid19-qrcode-decoder - An easy tool for decoding Green Pass Covid-19 QrCode

orjson - Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy

python-rapidjson - Python wrapper around rapidjson

PyLD - JSON-LD processor written in Python

Fast JSON schema for Python - Fast JSON schema validator for Python.

hjson-py - Hjson for Python

serpy - ridiculously fast object serialization

RDFLib plugin providing JSON-LD parsing and serialization - JSON-LD parser and serializer plugins for RDFLib

lupin is a Python JSON object mapper - Python document object mapper (load python object from JSON and vice-versa)

Trafaret - Ultimate transformation library that supports validation, contexts and aiohttp.