Maat
koda-validate
Maat | koda-validate | |
---|---|---|
5 | 10 | |
30 | 108 | |
- | - | |
2.6 | 5.2 | |
8 months ago | 26 days ago | |
Python | Python | |
MIT License | MIT License |
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Maat
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[Guide] A Tour Through the Python Framework Galaxy: Discovering the Stars
Try msgspec | Maat | turbo for fast serialization and validation
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Pydantic V2 leverages Rust's Superpowers [video]
Personally, I think it's great to have many projects solving the same problem and pushing each other further. Although the differences between the faster validations are small, the older ones were quite slow. This will save unnecessary CPU cycles, making it eco-friendly. And now the bar will be even higher with a Rust version, which is really great.
[0]Maat is 2.5 times faster than Pydantic on their own benchmark, as stated in their readme.
[0]https://github.com/Attumm/Maat
- Pydantic
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Parse, Don't Validate (2019)
https://github.com/Attumm/Maat/blob/main/tests/test_validati...
Since validation is written as dictionaries its possible to store the validations in caching db such as Redis.
And since its simple its easy to extend for anyone use case.
Benchmarks of pydantic has Maat around twice as Pydantic.
koda-validate
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Pydantic V2 leverages Rust's Superpowers [video]
As someone who built a pure python validation library[0] that's much faster than pydantic (~1.5x - 12x depending on the benchmark), I have to say that this whole focus on Rust seems premature. There's clearly a lot of room for pydantic to optimize its Python implementation.
Beyond that, rust seems like a great fit for tooling (i.e. ruff), but as a library used at runtime, it seems a little odd to make a validation library (which can expect to receive any kind of data valid python data) to also be constrained by a separate set of data types which are valid in rust.
[0]: https://github.com/keithasaurus/koda-validate
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beartype: It has documentation now. It only took two years, my last hair follicle, precious sanity points (SPs), and working with Sphinx. Don't be like @leycec. Go hard on documentation early.
For the sake of comparison I built a validate_signature function as part of koda-validate, which has a lot of overlap with beartype. I haven't really compared it to beartype, so I'd be interested to see people's thoughts on how the two approaches compare.
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Pydantic vs Protobuf vs Namedtuples vs Dataclasses
FYI I wrote koda-validate, which is significantly faster than pydantic, has a similar API, and is pure python.
- Koda Validate: Alternative to Pydantic that is faster, more flexible, and async-compatible.
- I built a composable validation library. It plays nice with type hints and asyncio. Would love some feedback!
- Koda Validate: Flexible, Explicit, Async-compatible Validation in Python
- Show HN: Koda Validate 2.0 – Async Validation in Python
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This Week In Python
koda-validate – Typesafe Validation
- Show HN: Koda Validate – Typesafe, combinable validation for Python
What are some alternatives?
wiktextract - Wiktionary dump file parser and multilingual data extractor
pydantic-core - Core validation logic for pydantic written in rust
io-ts - Runtime type system for IO decoding/encoding
katara - Synthesize CRDTs from classic data types with verified lifting!
baize - Powerful and exquisite WSGI/ASGI framework/toolkit.
flake8-comments - Report redundant comments in python code
pydantic - Data validation using Python type hints
serialite - Serialization and deserialization library for Python
traitlets - A lightweight Traits like module
typedload - Python library to load dynamically typed data into statically typed data structures
hupper - in-process file monitor / reloader for reloading your code automatically during development
django-pgtransaction - A context manager/decorator which extends Django's atomic function with the ability to set isolation level and retries for a given transaction.