msgspec
ucall
msgspec | ucall | |
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31 | 13 | |
1,868 | 990 | |
- | 1.6% | |
8.6 | 6.4 | |
about 1 month ago | 17 days ago | |
Python | C | |
BSD 3-clause "New" or "Revised" License | Apache License 2.0 |
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.
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 itโs 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.
ucall
- Show HN: U)Search Images demo in 200 lines of Python
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Faster JSON-RPC on Linux kernel 5.19+ with io_uring and simdjson
Type checking was included, and union support is trivial to add. We have just added a feature request and will release it in a few days.
- FLiP Stack Weekly for 13 March 2023
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Show HN: Up to 100x Faster FastAPI with simdjson and io_uring on Linux 5.19
You are right! For the convenience of Python users, we have to introspect the messages and parse JSON into Python objects. Every member of every dictionary being allocated on heap.
To make it as fast as possible we don't use PyBind, NanoBind, SWIG, or any high-level tooling. Our Python bindings are a pure CPython integration. There is just no way to beat that combo, not that I know.
https://github.com/unum-cloud/ujrpc/blob/main/src/python.c
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Lightweight RPC with `simdjson` and `io_uring` on Linux 5.19 and newer
TLDR: UJRPC reaches 230K TCP/IP round-trips per second on 1 socket. Faster than gRPC and much faster than FastAPI.
- Up to 100x Faster FastAPI with simdjson and io_uring on Linux 5.19+
What are some alternatives?
pydantic - Data validation using Python type hints
frontman - Frontman is an open-source API gateway written in Go that allows you to manage your microservices and expose them as a single API endpoint. It acts as a reverse proxy and handles requests from clients, routing them to the appropriate backend service.
orjson - Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy
japronto - Screaming-fast Python 3.5+ HTTP toolkit integrated with pipelining HTTP server based on uvloop and picohttpparser.
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
simdjson - Parsing gigabytes of JSON per second : used by Facebook/Meta Velox, the Node.js runtime, ClickHouse, WatermelonDB, Apache Doris, Milvus, StarRocks
mashumaro - Fast and well tested serialization library
FrameworkBenchmarks - Source for the TechEmpower Framework Benchmarks project
MessagePack - MessagePack serializer implementation for Java / msgpack.org[Java]
Muonbase - Document Database
marshmallow - A lightweight library for converting complex objects to and from simple Python datatypes.
Apache Arrow - Apache Arrow is a multi-language toolbox for accelerated data interchange and in-memory processing