Fast JSON schema for Python
cattrs
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| Fast JSON schema for Python | cattrs | |
|---|---|---|
| 1 | 4 | |
| 345 | 486 | |
| - | 2.7% | |
| 6.7 | 9.1 | |
| 3 months ago | 14 days ago | |
| Python | Python | |
| BSD 3-clause "New" or "Revised" License | MIT License |
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Fast JSON schema for Python
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I wrote okjson - A fast, simple, and pythonic JSON Schema Validator
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.
cattrs
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Taking JSON input for "posts", "tags" etc. How to escape '\' charecter or detect carefully?
I'm fond of attrs and cattrs myself, attrs make creating data classes a snap, writing all of the stupid code python requires to have a dataclass. Note the new built in dataclass is actually a limited copy of attrs. https://www.attrs.org/en/stable/ and https://github.com/python-attrs/cattrs
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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)
- cattrs – an open source Python library for structuring and unstructuring data
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I use attrs instead of pydantic
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Cattrs has some problems with generics [1] [2]. Dacite and marshmallow-dataclasses don't support generics well either, with some issues around Union types.
They do work well for simple python types but what I'd like to see is guarantee that the serialisation operation is completely reversible and if not raise warning/exception.
What are some alternatives?
marshmallow - A lightweight library for converting complex objects to and from simple Python datatypes.
jsonschema - JSON Schema validation library
pydantic - Data parsing and validation using Python type hints
serpy - ridiculously fast object serialization
datamodel-code-generator - Pydantic model generator for easy conversion of JSON, OpenAPI, JSON Schema, and YAML data sources.
Trafaret - Ultimate transformation library that supports validation, contexts and aiohttp.
python-rapidjson - Python wrapper around rapidjson
ultrajson - Ultra fast JSON decoder and encoder written in C with Python bindings
lupin is a Python JSON object mapper - Python document object mapper (load python object from JSON and vice-versa)