msgspec VS koda-validate

Full support for validation and serialisation of attrs classes and msgspec Structs. Where previously only Pydantic models and types where supported, you can now mix and match any of these three libraries. In addition to this, adding support for another modelling library has been greatly simplified with the new plugin architecture

> Maybe it was very slow before

That is at least partly the case. I maintain msgspec[1], another Python JSON validation library. Pydantic V1 was ~100x slower at encoding/decoding/validating JSON than msgspec, which was more a testament to Pydantic's performance issues than msgspec's speed. Pydantic V2 is definitely faster than V1, but it's still ~10x slower than msgspec, and up to 2x slower than other pure-python implementations like mashumaro.

Recent benchmark here: https://gist.github.com/jcrist/d62f450594164d284fbea957fd48b...

[1]: https://github.com/jcrist/msgspec

While it's definitely much faster than pydantic V1 (which is a huge accomplishment!), it's still not exactly what I'd call "fast".

I maintain msgspec (https://github.com/jcrist/msgspec), a serialization/validation library which provides similar functionality to pydantic. Recent benchmarks of pydantic V2 against msgspec show msgspec is still 15-30x faster at JSON encoding, and 6-15x faster at JSON decoding/validating.

Benchmark (and conversation with Samuel) here: https://gist.github.com/jcrist/d62f450594164d284fbea957fd48b...

This is not to diminish the work of the pydantic team! For many users pydantic will be more than fast enough, and is definitely a more feature-filled tool. It's a good library, and people will be happy using it! But pydantic is not the only tool in this space, and rubbing some rust on it doesn't necessarily make it "fast".

https://github.com/jcrist/msgspec so I am using this instead of Pydantic.

Another thing: why pyserde rather than stuff like msgspec? https://github.com/jcrist/msgspec

Try msgspec | Maat | turbo for fast serialization and validation

Congratulations to the team, Pydantic is an amazing library.

If you find JSON serialization/deserialization a bottleneck, another interesting library (with much less features) for Python is msgspec: https://github.com/jcrist/msgspec

This feature is yet to be released, but it will allow you to seamlessly use data modelled with for example Pydantic, SQLAlchemy, msgspec or dataclasses in your route handlers, without the need for an intermediary model; The conversion will be handled by the specific DTO "backend" implementation. This new paradigm also makes it trivial to add support for any such modelling library, by simply implementing an appropriate backend.

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

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.

FYI I wrote koda-validate, which is significantly faster than pydantic, has a similar API, and is pure python.

koda-validate – Typesafe Validation