Fast JSON schema for Python VS ultrajson

Compare Fast JSON schema for Python vs ultrajson and see what are their differences.

Fast JSON schema for Python

Fast JSON schema validator for Python. (by horejsek)


Ultra fast JSON decoder and encoder written in C with Python bindings (by ultrajson)
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Fast JSON schema for Python ultrajson
1 2
345 3,737
- 0.6%
6.7 9.0
3 months ago 7 days ago
Python C
BSD 3-clause "New" or "Revised" License GNU General Public License v3.0 or later
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Fast JSON schema for Python

Posts with mentions or reviews of Fast JSON schema for Python. We have used some of these posts to build our list of alternatives and similar projects. The last one was on 2022-03-31.
  • I wrote okjson - A fast, simple, and pythonic JSON Schema Validator
    8 projects | | 31 Mar 2022
    I had a requirement to process and validate large payloads of JSON concurrently for a web service, initially I implemented it using jsonschema and fastjsonschema but I found the whole JSON Schema Specification to be confusing at times and on top of that wanted better performance. Albeit there are ways to compile/cache the schema, I wanted to move away from the schema specification so I wrote a validation library inspired by the design of tiangolo/sqlmodel (type hints) to solve this problem easier.


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 Fast JSON schema for Python and ultrajson you can also consider the following projects:

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

jsonschema - JSON Schema validation library

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

cattrs - Complex custom class converters for attrs.

serpy - ridiculously fast object serialization

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

python-rapidjson - Python wrapper around rapidjson

pysimdjson - Python bindings for the simdjson project.

PyLD - JSON-LD processor written in Python

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