koda-validate
serialite
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koda-validate | serialite | |
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10 | 1 | |
108 | 7 | |
- | - | |
5.2 | 5.1 | |
21 days ago | about 1 month ago | |
Python | Python | |
MIT License | MIT License |
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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.
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
serialite
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Pydantic V2 leverages Rust's Superpowers [video]
Pydantic is so cool and I am really excited to migrate to v2. My biggest pain point in Pydantic is that it has no abstract base class for a serializer/deserializer. There is just BaseModel. This means that there is no "Pydantic interface" to implement. If I need to serialize/deserialize something other than an object with attributes, I basically can't do it in Pydantic, or at least I couldn't figure out how to do it.
In contrast, when I designed Serialite [1], I designed it to have a Serializer base class with two abstract methods: to_data and from_data. Then I added a @serializable decorator that can be applied to any dataclass, which injects concrete implementations of to_data and from_data. The decorator is what I usually use, but I sometimes implement the base class directly when it gets too complicated.
Making Serialite work with FastAPI was almost impossible because there is no interface to implement, duck type or otherwise. In the end, Serialite monkey patches some key FastAPI functions to make them understand Serialite Serializers and that seems to work.
[1] https://github.com/drhagen/serialite
What are some alternatives?
pydantic-core - Core validation logic for pydantic written in rust
Maat - Validation and transformation library powered by deductive ascending parser. Made to be extended for any kind of project.
katara - Synthesize CRDTs from classic data types with verified lifting!
flake8-comments - Report redundant comments in python code
typedload - Python library to load dynamically typed data into statically typed data structures
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.
msgspec - A fast serialization and validation library, with builtin support for JSON, MessagePack, YAML, and TOML
puff - ☁ Puff ☁ - The deep stack framework.
Twitter_Banner_Autoupdater - Twitter banner autoupdater using Tweepy Python module and the Twitter API
cinder - Cinder is Meta's internal performance-oriented production version of CPython.
generalimport - Handle all your optional dependencies with a single call!