orjson
msgspec
orjson | msgspec | |
---|---|---|
22 | 32 | |
7,137 | 2,987 | |
2.7% | 3.5% | |
8.0 | 6.9 | |
5 days ago | 3 months ago | |
Python | Python | |
Apache License 2.0 | BSD 3-clause "New" or "Revised" License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
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.
orjson
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Web scraping of a dynamic website using Python with HTTP Client
The library already has support for an HTTP client that allows bypassing Cloudflare - CurlImpersonateHttpClient. Since we have to work with JSON responses we could use parsel_crawler added in version 0.3.0, but I think this is excessive for such tasks, besides I like the high speed of orjson.. Therefore, we'll need to implement our crawler rather than using one of the ready-made ones.
- orjson: Fast, correct Python JSON lib supporting dataclasses, datetimes, NumPy
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JSON extra uses orjson instead of ujson
(https://github.com/ijl/orjson). In this implementation, the same JSON
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This Week In Python
orjson β Fast, correct Python JSON library
- Orjson: Fast, correct Python JSON library
- JSON dans les projets data science : Trucs & Astuces
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JSON in data science projects: tips & tricks
orjson is the fastest JSON library available for python. It natively manages dataclass objects, datetime, numpy and UUID objects.
- Segunda linguagem
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Litestar 2.0
As we began venturing down that road, a few things emerged that would constitute significant changes to some of the core parts of Litestar, but there were two things in particular that started a chain reaction of changes by opening up further possibilities: The new DTOs and our switch from orjson to msgspec.
- orjson: Fast, correct Python JSON lib (supports dataclasses, datetimes, numpy)
msgspec
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Don't let dicts spoil your code
gjson [1] and a few other go packages offer a way to parse arbitrary JSON without requiring structs to hold them.
re: Python. I like PyRight/PyLance for Python typing, it seems to "just work" afaict. I also like msgspec for dataclass like behavior [2].
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1: https://github.com/tidwall/gjson
2: https://jcristharif.com/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 itβs 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
What are some alternatives?
ujson
pydantic - Data validation using Python type hints
ormsgpack - Msgpack serialization/deserialization library for Python, written in Rust using PyO3. Reboot of orjson. msgpack.org[Python]
pydantic-core - Core validation logic for pydantic written in rust
pysimdjson - Python bindings for the simdjson project.
MessagePack - MessagePack serializer implementation for Java / msgpack.org[Java]