Maat
msgspec
Maat | msgspec | |
---|---|---|
5 | 31 | |
30 | 1,877 | |
- | - | |
2.6 | 8.6 | |
8 months ago | about 1 month ago | |
Python | Python | |
MIT License | BSD 3-clause "New" or "Revised" 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.
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.
msgspec
- Htmx, Rust and Shuttle: A New Rapid Prototyping Stack
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Litestar 2.0
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
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FastAPI 0.100.0:Release Notes
> 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
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Pydantic 2.0
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".
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Need help developing a high performance Redis ORM for Python
https://github.com/jcrist/msgspec so I am using this instead of Pydantic.
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Blog post: Writing Python like it’s Rust
Another thing: why pyserde rather than stuff like msgspec? https://github.com/jcrist/msgspec
- Show HN: Msgspec, a fast serialization/validation library for Python
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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 rewritten in Rust is 5-50x faster than Pydantic V1
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
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Starlite updates March '22 | 2.0 is coming
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.
What are some alternatives?
wiktextract - Wiktionary dump file parser and multilingual data extractor
pydantic - Data validation using Python type hints
io-ts - Runtime type system for IO decoding/encoding
orjson - Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy
baize - Powerful and exquisite WSGI/ASGI framework/toolkit.
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
mashumaro - Fast and well tested serialization library
traitlets - A lightweight Traits like module
MessagePack - MessagePack serializer implementation for Java / msgpack.org[Java]
hupper - in-process file monitor / reloader for reloading your code automatically during development
marshmallow - A lightweight library for converting complex objects to and from simple Python datatypes.