pysimdjson
PyLD
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| pysimdjson | PyLD | |
|---|---|---|
| 6 | 28 | |
| 629 | 577 | |
| - | 1.2% | |
| 5.3 | 5.2 | |
| 2 months ago | about 2 months ago | |
| Python | Python | |
| GNU General Public License v3.0 or later | BSD 1-Clause License |
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.
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.
PyLD
- I Wrote an Activitypub Server in OCaml: Lessons Learnt, Weekends Lost
- JSON for Linking Data
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I'm currently in the interview process for a Jr. Full Stack Developer position, and I was given this take-home test that has me on the verge of pulling my hair out.
3) Things I would need to refresh: JSON-LD (This is actually really useful): https://json-ld.org/
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The need for a more semantic web
Some documentation for you OP: - RDFa. - JSON-LD doesn't have to be in HTML. It's just a specification built on JSON to represent RDF data. Also, from experience, Turtle) is more popular - If you want to dig into what defining semantic vocabularies (ontologies) entails, read on RDF, RDFS, and OWL2.
- Making SEO better for blog posts with Structured Data
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Beginners Guide to Yoast SEO 2023
Schema markup can be added to a web page using the JSON-LD format, which is a structured data format that is supported by Yoast SEO.
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Getting Started with ActivityPub
It's a big long, so the response is at the bottom in Appendix A. The format is JSON for Linking Data, or JSON-LD.
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schema-org-java: Java library for working with Schema.org data in JSON-LD format
So it can be tedious to create all the entities needed for your project and then serialize / deserialize the data in JSON-LD format.
What are some alternatives?
orjson - Fast, correct Python JSON library supporting dataclasses, datetimes, and numpy
RDFLib plugin providing JSON-LD parsing and serialization - JSON-LD parser and serializer plugins for RDFLib
cysimdjson - Very fast Python JSON parsing library
ultrajson - Ultra fast JSON decoder and encoder written in C with Python bindings
marshmallow - A lightweight library for converting complex objects to and from simple Python datatypes.
Fast JSON schema for Python - Fast JSON schema validator for Python.
rdflib - RDFLib is a Python library for working with RDF, a simple yet powerful language for representing information.
lupin is a Python JSON object mapper - Python document object mapper (load python object from JSON and vice-versa)
serpy - ridiculously fast object serialization
PyValico - Small python wrapper around https://github.com/rustless/valico
jsons - 🐍 A Python lib for (de)serializing Python objects to/from JSON