|pysimdjson||Fast JSON schema for Python|
|2 days ago||17 days ago|
|GNU General Public License v3.0 or later||BSD 3-clause "New" or "Revised" License|
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Analyzing multi-gigabyte JSON files locally
14 projects | news.ycombinator.com | 18 Mar 2023
I Use C When I Believe in Memory Safety
5 projects | news.ycombinator.com | 5 Feb 2023
Its magic function wrapping comes at a cost, trading ease of use for runtime performance. When you have a single C++ function to call that will run for a "long" time, pybind all the way. But pysimdjson tends to call a single function very quickly, and the overhead of a single function call is orders of magnitude slower than with cython when being explit with types and signatures. Wrap a class in pybind11 and cython and compare the stack trace between the two, and the difference is startling.
Processing JSON 2.5x faster than simdjson with msgspec
5 projects | /r/Python | 3 Oct 2022
5 projects | /r/emacs | 23 May 2022
You are aware of simdjson being available in python if you really need some json crunching, albeit json module in Python is implemented in C itself, so I don't think understand why do you think Python is slow there?
The fastest tool for querying large JSON files is written in Python (benchmark)
16 projects | news.ycombinator.com | 12 Apr 2022
json: 113.79130696877837 ms
While `orjson`, is faster than `ujson`/`json` here, it's only ~6% faster (in this benchmark). `simdjson` and `msgspec` (my library, see https://jcristharif.com/msgspec/) are much faster due to them avoiding creating PyObjects for fields that are never used.
If spyql's query engine can determine the fields it will access statically before processing, you might find using `msgspec` for JSON gives a nice speedup (it'll also type check the JSON if you know the type of each field). If this information isn't known though, you may find using `pysimdjson` (https://pysimdjson.tkte.ch/) gives an easy speed boost, as it should be more of a drop-in for `orjson`.
How I cut GTA Online loading times by 70%
7 projects | /r/programming | 28 Feb 2021
I don't think JSON is really the problem - parsing 10MB of JSON is not so slow. For example, using Python's json.load takes about 800ms for a 47MB file on my system, using something like simdjson cuts that down to ~70ms.
Fast JSON schema for Python
I wrote okjson - A fast, simple, and pythonic JSON Schema Validator
8 projects | /r/Python | 31 Mar 2022
I had a requirement to process and validate large payloads of JSON concurrently for a web service, initially I implemented it using jsonschema and fastjsonschema but I found the whole JSON Schema Specification to be confusing at times and on top of that wanted better performance. Albeit there are ways to compile/cache the schema, I wanted to move away from the schema specification so I wrote a validation library inspired by the design of tiangolo/sqlmodel (type hints) to solve this problem easier.
What are some alternatives?
marshmallow - A lightweight library for converting complex objects to and from simple Python datatypes.
jsonschema - JSON Schema validation library
cattrs - Composable custom class converters for attrs.
orjson - Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy
cysimdjson - Very fast Python JSON parsing library
ultrajson - Ultra fast JSON decoder and encoder written in C with Python bindings
serpy - ridiculously fast object serialization
python-rapidjson - Python wrapper around rapidjson
lupin is a Python JSON object mapper - Python document object mapper (load python object from JSON and vice-versa)
Trafaret - Ultimate transformation library that supports validation, contexts and aiohttp.