Msgspec vs orjson A speedy Struct type for representing structured data. import json import time import orjson import requests import simdjson import ujson import msgspec def query_msgspec (data: bytes)-> list [tuple [int, str]]: # Use Struct types to define the JSON schema. I think pydantic use slowly serelize by default P. Github Actions vs. py msgspec: 45. msgspec also works well with other type-checking tooling like mypy and pyright, providing excellent editor integration. May 19, 2023 · The fashionable orjson and msgspec libraries differ slightly from the standard and ujson libraries in the way they implement the dumps function: it returns bytes directly instead of a str object that requires UTF-8 encoding (which makes This shows that the readable msgspec implementation above is 1. This is faster and more similar to the standard library. Oct 16, 2012 · I would greatly recommend you to read this article - My thoughts on MessagePack, written by msgpack's author, that includes everything you need to know vs. encode (content) msgspec. Large lists of floats are the main exception where orjson sneaks out ahead, but it's only a 5% difference. convert . 0. Compare orjson, msgspec. Struct): name: str size: int class RepoData (msgspec. A good example, as per msgspec documentation. Structured as key-value pairs within a map-like format. OPT_PASSTHROUGH_SUBCLASS. class Package (msgspec. orjson is well engineered (as is the backing serde-json decoder), but any JSON decoder that isn't using naive algorithms is mostly bound by the cost of creating PyObjects. Define your message schemas using standard Python type annotations. Performance wise, for 1GB of input data, orjson allows to decrease processing time by 20-30%. Fluentd uses MessagePack for all internal data representation. 0, we introduced msgspec as our serialization backend, replacing orjson. orjson Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy (by ijl) JSON Python Rust Serialization Datetime pyo3 dataclasses Deserialization Numpy Sep 24, 2024 · 在 基准测试 中，msgspec 在解码和验证 JSON 数据时，速度甚至超过了 orjson 的解码速度。 快速的 Struct 类型. 🎉 Support for a wide variety of Python types. 0, but I think this is excessive for such tasks, besides I like the high speed of orjson. But it's faster and smaller. If you’re only renaming a few fields, you might find configuring the new names as part of the field definition to be the simplest option. json(), FastAPI (actually Starlette) first reads the body (using the . 복잡한 모델링을 하다보면 nested model 을 사용하는 일이 왕왕 있다. 5x faster than Pydantic V2 msgspec decodes ~30x faster than Pydantic V1. loads() (using the standard json library of Python) to return a dict/list object to you inside the endpoint—it doesn't use json. The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives. In version 1. msgspec vs pydantic fastapi vs Tornado msgspec vs orjson fastapi vs AIOHTTP msgspec vs pydantic-core fastapi vs django-ninja. It natively supports a wide range of Python builtin types. Dec 27, 2024 · msgspec is a fast serialization and validation library, In benchmarks msgspec decodes and validates JSON faster than orjson can decode it alone. tools for testing autocannon 127. py-object-factory objectfactory is a python package to easily implement the factory design pattern for object creation, serialization, and polymorphism (by devinaconley) Oct 23, 2022 · Reading request data using orjson. This repository manages specification of MessagePack format. Even with orjson, you're still paying the cost of creating a new PyObject for every node in the JSON blob. dumps(), as you mentioned in the comments section beneath your question, as Aug 16, 2021 · Compare orjson vs Robyn and see what are their differences. MessagePack¶. It features: 🚀 High performance encoders/decoders for common protocols. It's crazy fast because of zero-copy optimization of msgpack-ruby. json . """ def render (self, content: Any) -> bytes: assert msgspec is not None, "msgspec must be installed to use MsgSpecJSONResponse" return msgspec. BSON defines more broad native types than the other two, and may be a better match to your object model, but this makes it more verbose. Oct 2, 2022 · In version 1. The library already has support for an HTTP client that allows bypassing Cloudflare - CurlImpersonateHttpClient. See "Strict" vs "Lax" Mode for more information . For decoding without type hints, we're usually ~ the same as orjson. 科普一个冷门的，但是很强的技术：MessagePack，简称msgpack。msgpack不是软件，是一个标准，可以先把它看成二进制的json，“二进制json”容易让人联想到一个更流行一点的标准：BSON。 orjson & msgspec of course solved that issue. This is mainly useful for adding msgspec support for other protocols. py -s localhost:9092 -t test-c 99999 PYTHONMALLOC=malloc memray run --follow-fork test_msgspec. Compare orjson, msgspec, pydantic. loads is very cpu intensive and my own parsing is not as bad as I thought. Aug 19, 2019 · Message Pack VS JSON 既然msgpack比json又小又快，json真的一无是处吗？虽然在网络传输的应用场景上msgpack可以完胜json，可作为配置文件的场景上又如何呢？我们知道JSON格式对用户是很友好的，可读性非常强，在编辑器中代码折叠，类型高亮都非常方便。 Jul 3, 2023 · Orjson give very good perfomance for example in FASTAPI 2 codes This with orjson. Making Python classes serializable to/from JSON Apr 4, 2019 · In my benchmarks, msgspec with a schema is generally ~2x faster than orjson, which is the next fastest JSON parser I've found. Due to a more efficient in memory representation, JSON decoding AND schema validation with msgspec than just JSON decoding alone. toml . Allow any of msgspec's supported types as inputs to msgspec. dprint. MessagePack is an efficient binary serialization format. orjson Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy (by ijl) JSON Python Rust Serialization Datetime pyo3 dataclasses Deserialization Numpy 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. body() method of the Request object), and then calls json. Encoding¶ 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. At this time it still looks like msgspec is measurably faster though. msgspec supports multiple serialization protocols, accessed through separate submodules: msgspec. (by dprint) 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. For efficiency we only define # the fields we actually need. dumps to msgspec. Passthrough input unchanged when coercing to typing. Mar 4, 2025 · When benchmarking individual types for the core parsing routines, msgspec's float parser is known to be a bit slower (~15% slower) than orjson's, while the other core type parsing routines are approximately equivalent (we're slightly faster at ints for some reason). > I should mention that spyql leverages orjson, which has a considerable impact on performance. The benchmark not only provides valuable insights for developers but also adds a dash of excitement to the world of Python library comparisons. Python JSON benchmarking and "correctness". orjson Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy (by ijl) JSON Python Rust Serialization Datetime pyo3 dataclasses Deserialization Numpy Compare dprint vs orjson and see what are their differences. Contribute to TkTech/json_benchmark development by creating an account on GitHub. Nov 23, 2023 · Logfmt vs JSON. Jenkins Open Source All Customer Stories Autodesk Builds Better Software Faster with CloudBees Salesforce Migrates DevOps to the Cloud with CloudBees CI American Express Global Business Travel DevOps Test Data Platform Doubles Release Velocity 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. Support encoding subclasses of UUID . May 12, 2022 · Or, you can use msgspec a new library that offers schemas, fast parsing, and some neat tricks to reduce memory usage, all in a single library. json to msgspec. And since msgspec supports both protocols with a consistent interface, switching from msgspec. load多了一点，但收益巨大：同样的硬件条件，使用msgspec. Schemas are useful for reasons other than decoding/encoding performance too: In version 1. orjson is a fast, correct JSON library for Python. This shows that msgspec is able to decode JSON faster when a schema is provided. Each supports a consistent interface, making it simple to switch between protocols as needed. yaml . json. msgspec is friendly. A starting point: built-in json and orjson. We have used some of these posts to build our list of alternatives and similar projects. . 45. 94157397840172 ms orjson: 105. 3. Compare orjson vs dacite and see what are their differences. Making Python classes serializable to/from JSON vs. Any type in msgspec. For some schemas orjson is faster, for some schemas msgspec is faster. The main question this relies on is - are there aggregrates suppported other than list[] and Struct and presumably dict[str, ]?If so, someone might accidentally specify an unsafe type, but that's still technically opting in so it isn't automatic RCE unless your code is wrong. recommended msgpack use cases, pros/cons and other useful pointers related to msgpack and JSON. msgspec is flexible. dataclass instances are now serialized by default and cannot be customized in a default function unless option=orjson. To do this you can use the name argument in msgspec. 1:81 -d 10 -c 30 -w 3 Apr 26, 2019 · Even with the need for additional Unicode decoding, orjson is fastest (for this particular benchmark!). Now MessagePack is an essential component of Fluentd to achieve high performance and flexibility at the same time. The last one was on 2023-12-10. 79130696877837 ms A few comments: All of these are fairly quick, library choice likely doesn't matter at all for simple scripts on small-medium data msgspec supports two places for configuring a field’s name used for encoding/decoding: On the field definition. Apr 15, 2022 · $ python bench_repodata_query. Subclasses of str, int, dict, and list are now serialized. msgpack should be fairly painless. Let’s start by looking at two other libraries: the built-in json module in Python, and the speedy orjson library. 34720402210951 ms ujson: 121. msgspec and Pydantic are two extremely powerful libraries and both serve also different purposes but there are a lot of people that prefer msgspec to Pydantic for its performance. >>> from typing import Optional, Set >>> import msgspec >>> class User(msgspec. It's hard to imagine a situation where JSON serialization is an issue if you're correctly using either of those two The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives. pjqk oujr wzbjhe nwdm jgrtcip uqvshc efrzwa zhvzbdd hcjffz hagqpo nlfumb cvkd sfaa vxhiov anidl