compare-go-json
pysimdjson
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compare-go-json | pysimdjson | |
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5 | 6 | |
18 | 628 | |
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0.0 | 5.3 | |
almost 2 years ago | about 2 months ago | |
Go | Python | |
- | GNU General Public License v3.0 or later |
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compare-go-json
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The fastest tool for querying large JSON files is written in Python (benchmark)
For me OjG (https://github.com/ohler55/ojg) has been great. I regularly use it on files that can not be loaded into memory. The best JSON file format for multiple record is one JSON document per record all in the same file. OjG doesn't care if they are on different lines. It is fast (https://github.com/ohler55/compare-go-json) and uses a fairly complete JSONPath implementation for searches. Similar to jq but using JSONPath instead of a proprietary query language.
I am biased though as I wrote OjG to handle what other tools were not able to do.
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OjG now has a tokenizer that is almost 10 times faster than json.Decode
jsoniter is json-iterator/go. It is the 3rd column at https://github.com/ohler55/compare-go-json
The title says it all. The new tokenizer here https://github.com/ohler55/ojg and the benchmarks and comparison to other JSON packages is here https://github.com/ohler55/compare-go-json.
You'll find some examples in second link that does the benchmark. https://github.com/ohler55/compare-go-json.
pysimdjson
- Analyzing multi-gigabyte JSON files locally
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I Use C When I Believe in Memory Safety
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.
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Processing JSON 2.5x faster than simdjson with msgspec
simdjson
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[package-find] lsp-bridge
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?
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The fastest tool for querying large JSON files is written in Python (benchmark)
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`.
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How I cut GTA Online loading times by 70%
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.
What are some alternatives?
orjson - Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy
cysimdjson - Very fast Python JSON parsing library
jsoniter - A high-performance 100% compatible drop-in replacement of "encoding/json"
ultrajson - Ultra fast JSON decoder and encoder written in C with Python bindings
Fast JSON schema for Python - Fast JSON schema validator for Python.
lupin is a Python JSON object mapper - Python document object mapper (load python object from JSON and vice-versa)
PyValico - Small python wrapper around https://github.com/rustless/valico
marshmallow - A lightweight library for converting complex objects to and from simple Python datatypes.
serpy - ridiculously fast object serialization
hjson-py - Hjson for Python
cattrs - Composable custom class converters for attrs.