pysimdjson
json-toolkit
| pysimdjson | json-toolkit | |
|---|---|---|
| 6 | 5 | |
| 629 | 67 | |
| - | - | |
| 5.3 | 4.6 | |
| 3 months ago | about 1 year ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | GNU General Public License v3.0 only |
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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.
Ex: https://github.com/TkTech/pysimdjson/issues/73
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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.
json-toolkit
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Show HN: Comma Separated Values (CSV) to Unicode Separated Values (USV)
CSV is great because excel can import it, but it can't import USV, so at that point, why use USV when you can use JSON?
https://github.com/tyleradams/json-toolkit/
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Analyzing multi-gigabyte JSON files locally
> Also note that this approach generalizes to other text-based formats. If you have 10 gigabyte of CSV, you can use Miller for processing. For binary formats, you could use fq if you can find a workable record separator.
You can also generalize it without learning a new minilanguage by using https://github.com/tyleradams/json-toolkit which converts csv/binary/whatever to/from json
- Fq: Jq for Binary Formats
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Show HN: Angle Grinder – A terminal app to slice, dice, and aggregate your logs
I really like this tool, but I'm not sure what it gets me more than jq (and https://github.com/tyleradams/json-toolkit to convert non-json to json).
What can angle grinder do better than jq?
- Show HN: Transform a CSV into a JSON and vice versa
What are some alternatives?
orjson - Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy
miller - Miller is like awk, sed, cut, join, and sort for name-indexed data such as CSV, TSV, and tabular JSON
cysimdjson - Very fast Python JSON parsing library
ndjson - Streaming line delimited json parser + serializer
ultrajson - Ultra fast JSON decoder and encoder written in C with Python bindings
angle-grinder - Slice and dice logs on the command line
Fast JSON schema for Python - Fast JSON schema validator for Python.
csv2json - Simple tool for converting CSVs to JSON
lupin is a Python JSON object mapper - Python document object mapper (load python object from JSON and vice-versa)
jq - Command-line JSON processor [Moved to: https://github.com/jqlang/jq]
PyValico - Small python wrapper around https://github.com/rustless/valico
nq - Unix command line queue utility