mashumaro
ultrajson
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mashumaro | ultrajson | |
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3 | 3 | |
729 | 4,248 | |
- | 0.8% | |
9.4 | 7.0 | |
5 days ago | 25 days ago | |
Python | C | |
Apache License 2.0 | GNU General Public License v3.0 or later |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
mashumaro
- DotDict: A simple Python library to make chained attributes possible
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apischema v0.17 - I've developed the fastest typed JSON (de)serialization library, and you can also build your GraphQL schema with it
This month, I've released version 0.17, and it's now blazing fast; there is in fact no more comparison with Pydantic, which more than 5x slower (up to 30x in serialization). It's also faster than alternatives like mashumaro or cattrs. (See the quick benchmark result in documentation, and the code)
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I use attrs instead of pydantic
Having run into these issues with Pydantic, we've been using Mashumaro[1], which, while not having all the bells and whistles of Pydantic, has served us pretty well.
1: https://github.com/Fatal1ty/mashumaro
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?
msgspec - A fast serialization and validation library, with builtin support for JSON, MessagePack, YAML, and TOML
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
Fast JSON schema for Python - Fast JSON schema validator for Python.
cattrs - Composable custom class converters for attrs.
python-rapidjson - Python wrapper around rapidjson
PyLD - JSON-LD processor written in Python
serpy - ridiculously fast object serialization
pysimdjson - Python bindings for the simdjson project.